chore: remove flamegraph v2 since we've moved to v4 now

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

docs/api/openapi.yml

@@ -1360,6 +1360,8 @@ components:
       - sqs
       - storageaccountsblob
       - cdnprofile
+      - containerapp
+      - aks
       type: string
     CloudintegrationtypesServiceMetadata:
       properties:
@@ -6722,11 +6724,6 @@ components:
       type: object
     SpantypesGettableWaterfallTrace:
       properties:
-        aggregations:
-          items:
-            $ref: '#/components/schemas/SpantypesSpanAggregationResult'
-          nullable: true
-          type: array
         endTimestampMillis:
           minimum: 0
           type: integer
@@ -6814,14 +6811,6 @@ components:
       type: object
     SpantypesPostableWaterfall:
       properties:
-        aggregations:
-          items:
-            $ref: '#/components/schemas/SpantypesSpanAggregation'
-          nullable: true
-          type: array
-        limit:
-          minimum: 0
-          type: integer
         selectedSpanId:
           type: string
         uncollapsedSpans:
@@ -20677,76 +20666,6 @@ paths:
       summary: Get flamegraph view for a trace
       tags:
       - tracedetail
-  /api/v3/traces/{traceID}/waterfall:
-    post:
-      deprecated: false
-      description: Returns the waterfall view of spans for a given trace ID with tree
-        structure, metadata, and windowed pagination
-      operationId: GetWaterfall
-      parameters:
-      - in: path
-        name: traceID
-        required: true
-        schema:
-          type: string
-      requestBody:
-        content:
-          application/json:
-            schema:
-              $ref: '#/components/schemas/SpantypesPostableWaterfall'
-      responses:
-        "200":
-          content:
-            application/json:
-              schema:
-                properties:
-                  data:
-                    $ref: '#/components/schemas/SpantypesGettableWaterfallTrace'
-                  status:
-                    type: string
-                required:
-                - status
-                - data
-                type: object
-          description: OK
-        "400":
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/RenderErrorResponse'
-          description: Bad Request
-        "401":
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/RenderErrorResponse'
-          description: Unauthorized
-        "403":
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/RenderErrorResponse'
-          description: Forbidden
-        "404":
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/RenderErrorResponse'
-          description: Not Found
-        "500":
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/RenderErrorResponse'
-          description: Internal Server Error
-      security:
-      - api_key:
-        - VIEWER
-      - tokenizer:
-        - VIEWER
-      summary: Get waterfall view for a trace
-      tags:
-      - tracedetail
   /api/v4/traces/{traceID}/waterfall:
     post:
       deprecated: false

frontend/src/api/generated/services/sigNoz.schemas.ts

@@ -2651,6 +2651,8 @@ export enum CloudintegrationtypesServiceIDDTO {
 	sqs = 'sqs',
 	storageaccountsblob = 'storageaccountsblob',
 	cdnprofile = 'cdnprofile',
+	containerapp = 'containerapp',
+	aks = 'aks',
 }
 export type CloudintegrationtypesCloudIntegrationServiceDTOAnyOf = {
 	/**
@@ -8091,10 +8093,6 @@ export interface SpantypesWaterfallSpanDTO {
 }
 
 export interface SpantypesGettableWaterfallTraceDTO {
-	/**
-	 * @type array,null
-	 */
-	aggregations?: SpantypesSpanAggregationResultDTO[] | null;
 	/**
 	 * @type integer
 	 * @minimum 0
@@ -8214,15 +8212,6 @@ export interface SpantypesPostableTraceAggregationsDTO {
 }
 
 export interface SpantypesPostableWaterfallDTO {
-	/**
-	 * @type array,null
-	 */
-	aggregations?: SpantypesSpanAggregationDTO[] | null;
-	/**
-	 * @type integer
-	 * @minimum 0
-	 */
-	limit?: number;
 	/**
 	 * @type string
 	 */
@@ -10517,17 +10506,6 @@ export type GetFlamegraph200 = {
 	status: string;
 };
 
-export type GetWaterfallPathParameters = {
-	traceID: string;
-};
-export type GetWaterfall200 = {
-	data: SpantypesGettableWaterfallTraceDTO;
-	/**
-	 * @type string
-	 */
-	status: string;
-};
-
 export type GetWaterfallV4PathParameters = {
 	traceID: string;
 };

frontend/src/api/generated/services/tracedetail/index.ts

@@ -16,8 +16,6 @@ import type {
 	GetFlamegraphPathParameters,
 	GetTraceAggregations200,
 	GetTraceAggregationsPathParameters,
-	GetWaterfall200,
-	GetWaterfallPathParameters,
 	GetWaterfallV4200,
 	GetWaterfallV4PathParameters,
 	RenderErrorResponseDTO,
@@ -228,105 +226,6 @@ export const useGetFlamegraph = <
 > => {
 	return useMutation(getGetFlamegraphMutationOptions(options));
 };
-/**
- * Returns the waterfall view of spans for a given trace ID with tree structure, metadata, and windowed pagination
- * @summary Get waterfall view for a trace
- */
-export const getWaterfall = (
-	{ traceID }: GetWaterfallPathParameters,
-	spantypesPostableWaterfallDTO?: BodyType<SpantypesPostableWaterfallDTO>,
-	signal?: AbortSignal,
-) => {
-	return GeneratedAPIInstance<GetWaterfall200>({
-		url: `/api/v3/traces/${traceID}/waterfall`,
-		method: 'POST',
-		headers: { 'Content-Type': 'application/json' },
-		data: spantypesPostableWaterfallDTO,
-		signal,
-	});
-};
-
-export const getGetWaterfallMutationOptions = <
-	TError = ErrorType<RenderErrorResponseDTO>,
-	TContext = unknown,
->(options?: {
-	mutation?: UseMutationOptions<
-		Awaited<ReturnType<typeof getWaterfall>>,
-		TError,
-		{
-			pathParams: GetWaterfallPathParameters;
-			data?: BodyType<SpantypesPostableWaterfallDTO>;
-		},
-		TContext
-	>;
-}): UseMutationOptions<
-	Awaited<ReturnType<typeof getWaterfall>>,
-	TError,
-	{
-		pathParams: GetWaterfallPathParameters;
-		data?: BodyType<SpantypesPostableWaterfallDTO>;
-	},
-	TContext
-> => {
-	const mutationKey = ['getWaterfall'];
-	const { mutation: mutationOptions } = options
-		? options.mutation &&
-			'mutationKey' in options.mutation &&
-			options.mutation.mutationKey
-			? options
-			: { ...options, mutation: { ...options.mutation, mutationKey } }
-		: { mutation: { mutationKey } };
-
-	const mutationFn: MutationFunction<
-		Awaited<ReturnType<typeof getWaterfall>>,
-		{
-			pathParams: GetWaterfallPathParameters;
-			data?: BodyType<SpantypesPostableWaterfallDTO>;
-		}
-	> = (props) => {
-		const { pathParams, data } = props ?? {};
-
-		return getWaterfall(pathParams, data);
-	};
-
-	return { mutationFn, ...mutationOptions };
-};
-
-export type GetWaterfallMutationResult = NonNullable<
-	Awaited<ReturnType<typeof getWaterfall>>
->;
-export type GetWaterfallMutationBody =
-	| BodyType<SpantypesPostableWaterfallDTO>
-	| undefined;
-export type GetWaterfallMutationError = ErrorType<RenderErrorResponseDTO>;
-
-/**
- * @summary Get waterfall view for a trace
- */
-export const useGetWaterfall = <
-	TError = ErrorType<RenderErrorResponseDTO>,
-	TContext = unknown,
->(options?: {
-	mutation?: UseMutationOptions<
-		Awaited<ReturnType<typeof getWaterfall>>,
-		TError,
-		{
-			pathParams: GetWaterfallPathParameters;
-			data?: BodyType<SpantypesPostableWaterfallDTO>;
-		},
-		TContext
-	>;
-}): UseMutationResult<
-	Awaited<ReturnType<typeof getWaterfall>>,
-	TError,
-	{
-		pathParams: GetWaterfallPathParameters;
-		data?: BodyType<SpantypesPostableWaterfallDTO>;
-	},
-	TContext
-> => {
-	return useMutation(getGetWaterfallMutationOptions(options));
-};
 /**
  * Returns the waterfall view of spans including all spans if total spans are under a limit, a max count otherwise. Aggregations are dropped compared to v3
  * @summary Get waterfall view for a trace

frontend/src/api/trace/getTraceV4.tsx

@@ -27,7 +27,6 @@ const getTraceV4 = async (
 		{
 			selectedSpanId: props.selectedSpanId,
 			uncollapsedSpans,
-			limit: 10000,
 		},
 	);
 

frontend/src/container/QueryBuilder/filters/QueryBuilderSearch/style.ts

@@ -22,11 +22,12 @@ export const StyledCheckOutlined = styled(Check)`
 	float: right;
 `;
 
-export const TagContainer = styled(Badge)`
+export const TagContainer = styled(Badge).attrs({
+	color: 'secondary',
+	variant: 'outline',
+})`
 	&&& {
 		display: flex;
-		border-radius: 3px;
-		padding: 0.1rem 0.2rem;
 		font-weight: 300;
 		font-size: 0.6rem;
 	}
@@ -38,4 +39,5 @@ export const TagLabel = styled.span`
 
 export const TagValue = styled.span`
 	text-transform: capitalize;
+	font-weight: 400;
 `;

pkg/apiserver/signozapiserver/tracedetail.go

@@ -10,25 +10,6 @@ import (
 )
 
 func (provider *provider) addTraceDetailRoutes(router *mux.Router) error {
-	if err := router.Handle("/api/v3/traces/{traceID}/waterfall", handler.New(
-		provider.authzMiddleware.ViewAccess(provider.traceDetailHandler.GetWaterfall),
-		handler.OpenAPIDef{
-			ID:                  "GetWaterfall",
-			Tags:                []string{"tracedetail"},
-			Summary:             "Get waterfall view for a trace",
-			Description:         "Returns the waterfall view of spans for a given trace ID with tree structure, metadata, and windowed pagination",
-			Request:             new(spantypes.PostableWaterfall),
-			RequestContentType:  "application/json",
-			Response:            new(spantypes.GettableWaterfallTrace),
-			ResponseContentType: "application/json",
-			SuccessStatusCode:   http.StatusOK,
-			ErrorStatusCodes:    []int{http.StatusBadRequest, http.StatusNotFound},
-			SecuritySchemes:     newSecuritySchemes(types.RoleViewer),
-		},
-	)).Methods(http.MethodPost).GetError(); err != nil {
-		return err
-	}
-
 	if err := router.Handle("/api/v4/traces/{traceID}/waterfall", handler.New(
 		provider.authzMiddleware.ViewAccess(provider.traceDetailHandler.GetWaterfallV4),
 		handler.OpenAPIDef{

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/azure/aks/icon.svg

@@ -0,0 +1 @@
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pkg/modules/cloudintegration/implcloudintegration/fs/definitions/azure/aks/integration.json

@@ -0,0 +1,293 @@
+{
+  "id": "aks",
+  "title": "Azure Kubernetes Service (AKS)",
+  "icon": "file://icon.svg",
+  "overview": "file://overview.md",
+  "supportedSignals": {
+    "metrics": true,
+    "logs": true
+  },
+  "dataCollected": {
+    "metrics": [
+      {
+        "name": "azure_kube_pod_status_ready_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_pod_status_ready_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_pod_status_phase_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_pod_status_phase_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_node_status_condition_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_node_status_condition_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_cpu_usage_millicores_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_cpu_usage_millicores_maximum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_cpu_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_cpu_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_disk_usage_bytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_disk_usage_bytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_disk_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_disk_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_rss_bytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_rss_bytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_rss_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_rss_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_working_set_bytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_working_set_bytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_working_set_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_memory_working_set_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_network_in_bytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_network_in_bytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_network_out_bytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_node_network_out_bytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_apiserver_current_inflight_requests_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_apiserver_current_inflight_requests_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_apiserver_cpu_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_apiserver_cpu_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_apiserver_memory_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_apiserver_memory_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_etcd_cpu_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_etcd_cpu_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_etcd_database_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_etcd_database_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_etcd_memory_usage_percentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_etcd_memory_usage_percentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_node_status_allocatable_cpu_cores_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_node_status_allocatable_cpu_cores_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_node_status_allocatable_memory_bytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_kube_node_status_allocatable_memory_bytes_total",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      }
+    ],
+    "logs": [
+      {
+        "name": "Resource ID",
+        "path": "resources.azure.resource.id",
+        "type": "string"
+      }
+    ]
+  },
+  "telemetryCollectionStrategy": {
+    "azure": {
+      "resourceProvider": "Microsoft.ContainerService",
+      "resourceType": "managedClusters",
+      "metrics": {},
+      "logs": {
+        "categoryGroups": ["allLogs"]
+      }
+    }
+  },
+  "assets": {
+    "dashboards": [
+      {
+        "id": "overview",
+        "title": "Azure Kubernetes Service (AKS) Overview",
+        "description": "Overview of Azure Kubernetes Service (AKS) metrics",
+        "definition": "file://assets/dashboards/overview.json"
+      }
+    ]
+  }
+}

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/azure/aks/overview.md

@@ -0,0 +1,5 @@
+### Monitor Azure Kubernetes Service (AKS) with SigNoz
+
+Collect key AKS metrics and view them with an out of the box dashboard.
+
+Note: This integration is only for AKS with resource type `Microsoft.ContainerService/managedClusters`.

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/azure/containerapp/icon.svg

@@ -0,0 +1 @@
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pkg/modules/cloudintegration/implcloudintegration/fs/definitions/azure/containerapp/integration.json

@@ -0,0 +1,263 @@
+{
+  "id": "containerapp",
+  "title": "Container App",
+  "icon": "file://icon.svg",
+  "overview": "file://overview.md",
+  "supportedSignals": {
+    "metrics": true,
+    "logs": true
+  },
+  "dataCollected": {
+    "metrics": [
+      {
+        "name": "azure_rxbytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_rxbytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_rxbytes_minimum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_rxbytes_total",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_txbytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_txbytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_txbytes_minimum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_txbytes_total",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_restartcount_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_restartcount_maximum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_restartcount_minimum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_restartcount_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_replicas_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_replicas_maximum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_replicas_minimum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_replicas_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_cpupercentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_cpupercentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_cpupercentage_minimum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_cpupercentage_total",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_memorypercentage_average",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_memorypercentage_maximum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_memorypercentage_minimum",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_memorypercentage_total",
+        "unit": "Percent",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_usagenanocores_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_usagenanocores_maximum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_usagenanocores_minimum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_usagenanocores_total",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_workingsetbytes_average",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_workingsetbytes_maximum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_workingsetbytes_minimum",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_workingsetbytes_total",
+        "unit": "Bytes",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_coresquotaused_maximum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_coresquotaused_minimum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_totalcoresquotaused_average",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_totalcoresquotaused_maximum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      },
+      {
+        "name": "azure_totalcoresquotaused_minimum",
+        "unit": "Count",
+        "type": "Gauge",
+        "description": ""
+      }
+    ],
+    "logs": [
+      {
+        "name": "Resource ID",
+        "path": "resources.azure.resource.id",
+        "type": "string"
+      }
+    ]
+  },
+  "telemetryCollectionStrategy": {
+    "azure": {
+      "resourceProvider": "Microsoft.App",
+      "resourceType": "containerApps",
+      "metrics": {},
+      "logs": {
+        "categoryGroups": ["ContainerAppConsoleLogs", "ContainerAppSystemLogs"]
+      }
+    }
+  },
+  "assets": {
+    "dashboards": [
+      {
+        "id": "overview",
+        "title": "Container App Overview",
+        "description": "Overview of Container App metrics",
+        "definition": "file://assets/dashboards/overview.json"
+      }
+    ]
+  }
+}

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/azure/containerapp/overview.md

@@ -0,0 +1,7 @@
+### Monitor Container Apps with SigNoz
+
+Collect key Container App metrics and view them with an out of the box dashboard.
+
+To collect logs, you need to make sure that you have chosen "Azure Monitor" as the logging option for Container's App Environment.
+
+Note: This integration ingests logs for only "ContainerAppConsoleLogs" and "ContainerAppSystemLogs" diagnostic settings categories.

pkg/modules/metricsexplorer/implmetricsexplorer/module.go

@@ -219,19 +219,7 @@ func (m *module) GetStats(ctx context.Context, orgID valuer.UUID, req *metricsex
 		return nil, err
 	}
 
-	filterWhereClause, err := m.buildFilterClause(ctx, req.Filter, req.Start, req.End)
-	if err != nil {
-		return nil, err
-	}
-
-	// Single query to get stats with samples, timeseries counts in required sorting order
-	metricStats, total, err := m.fetchMetricsStatsWithSamples(
-		ctx,
-		req,
-		filterWhereClause,
-		false,
-		req.OrderBy,
-	)
+	metricStats, total, err := m.fetchMetricsStatsWithSamples(ctx, req, false)
 	if err != nil {
 		return nil, err
 	}
@@ -268,21 +256,16 @@ func (m *module) GetTreemap(ctx context.Context, orgID valuer.UUID, req *metrics
 		return nil, err
 	}
 
-	filterWhereClause, err := m.buildFilterClause(ctx, req.Filter, req.Start, req.End)
-	if err != nil {
-		return nil, err
-	}
-
 	resp := &metricsexplorertypes.TreemapResponse{}
 	switch req.Mode {
 	case metricsexplorertypes.TreemapModeSamples:
-		entries, err := m.computeSamplesTreemap(ctx, req, filterWhereClause)
+		entries, err := m.computeSamplesTreemap(ctx, req)
 		if err != nil {
 			return nil, err
 		}
 		resp.Samples = entries
 	default: // TreemapModeTimeSeries
-		entries, err := m.computeTimeseriesTreemap(ctx, req, filterWhereClause)
+		entries, err := m.computeTimeseriesTreemap(ctx, req)
 		if err != nil {
 			return nil, err
 		}
@@ -974,15 +957,23 @@ func (m *module) buildFilterClause(ctx context.Context, filter *qbtypes.Filter,
 func (m *module) fetchMetricsStatsWithSamples(
 	ctx context.Context,
 	req *metricsexplorertypes.StatsRequest,
-	filterWhereClause *sqlbuilder.WhereClause,
 	normalized bool,
-	orderBy *qbtypes.OrderBy,
 ) ([]metricsexplorertypes.Stat, uint64, error) {
 	ctx = m.withMetricsExplorerContext(ctx, "fetchMetricsStatsWithSamples")
 
+	hasFilter := req.Filter != nil && strings.TrimSpace(req.Filter.Expression) != ""
+	var filterWhereClause *sqlbuilder.WhereClause
+	if hasFilter {
+		var err error
+		filterWhereClause, err = m.buildFilterClause(ctx, req.Filter, req.Start, req.End)
+		if err != nil {
+			return nil, 0, err
+		}
+	}
+
 	start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
-	samplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
-	countExp := telemetrymetrics.CountExpressionForSamplesTable(samplesTable)
+	distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
+	countExp := telemetrymetrics.CountExpressionForSamplesTable(distributedSamplesTable)
 
 	// Timeseries counts per metric
 	tsSB := sqlbuilder.NewSelectBuilder()
@@ -1005,7 +996,7 @@ func (m *module) fetchMetricsStatsWithSamples(
 		"metric_name",
 		fmt.Sprintf("%s AS samples", countExp),
 	)
-	samplesSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, samplesTable))
+	samplesSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedSamplesTable))
 	samplesSB.Where(samplesSB.Between("unix_milli", req.Start, req.End))
 	samplesSB.Where("NOT startsWith(metric_name, 'signoz')")
 
@@ -1013,6 +1004,8 @@ func (m *module) fetchMetricsStatsWithSamples(
 		sqlbuilder.CTEQuery("__time_series_counts").As(tsSB),
 	}
 
+	// Narrow samples scan. With filter: fingerprint IN (per-fingerprint label preds can't fold to metric_name).
+	// No filter (fast path): metric_name IN — aligns with samples table's leading sort key, orders of magnitude cheaper.
 	if filterWhereClause != nil {
 		fingerprintSB := sqlbuilder.NewSelectBuilder()
 		fingerprintSB.Select("fingerprint")
@@ -1025,6 +1018,15 @@ func (m *module) fetchMetricsStatsWithSamples(
 
 		ctes = append(ctes, sqlbuilder.CTEQuery("__filtered_fingerprints").As(fingerprintSB))
 		samplesSB.Where("fingerprint IN (SELECT fingerprint FROM __filtered_fingerprints)")
+	} else {
+		metricNamesSB := sqlbuilder.NewSelectBuilder()
+		metricNamesSB.Select("DISTINCT metric_name")
+		metricNamesSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, localTsTable))
+		metricNamesSB.Where(metricNamesSB.Between("unix_milli", start, end))
+		metricNamesSB.Where("NOT startsWith(metric_name, 'signoz')")
+		metricNamesSB.Where(metricNamesSB.E("__normalized", normalized))
+
+		samplesSB.Where(fmt.Sprintf("metric_name IN (%s)", samplesSB.Var(metricNamesSB)))
 	}
 	samplesSB.GroupBy("metric_name")
 
@@ -1041,7 +1043,7 @@ func (m *module) fetchMetricsStatsWithSamples(
 	finalSB.JoinWithOption(sqlbuilder.FullOuterJoin, "__sample_counts s", "ts.metric_name = s.metric_name")
 	finalSB.Where("(COALESCE(ts.timeseries, 0) > 0 OR COALESCE(s.samples, 0) > 0)")
 
-	orderByColumn, orderDirection, err := getStatsOrderByColumn(orderBy)
+	orderByColumn, orderDirection, err := getStatsOrderByColumn(req.OrderBy)
 	if err != nil {
 		return nil, 0, err
 	}
@@ -1085,9 +1087,19 @@ func (m *module) fetchMetricsStatsWithSamples(
 	return metricStats, total, nil
 }
 
-func (m *module) computeTimeseriesTreemap(ctx context.Context, req *metricsexplorertypes.TreemapRequest, filterWhereClause *sqlbuilder.WhereClause) ([]metricsexplorertypes.TreemapEntry, error) {
+func (m *module) computeTimeseriesTreemap(ctx context.Context, req *metricsexplorertypes.TreemapRequest) ([]metricsexplorertypes.TreemapEntry, error) {
 	ctx = m.withMetricsExplorerContext(ctx, "computeTimeseriesTreemap")
 
+	hasFilter := req.Filter != nil && strings.TrimSpace(req.Filter.Expression) != ""
+	var filterWhereClause *sqlbuilder.WhereClause
+	if hasFilter {
+		var err error
+		filterWhereClause, err = m.buildFilterClause(ctx, req.Filter, req.Start, req.End)
+		if err != nil {
+			return nil, err
+		}
+	}
+
 	start, end, distributedTsTable, _ := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
 
 	totalTSBuilder := sqlbuilder.NewSelectBuilder()
@@ -1151,12 +1163,22 @@ func (m *module) computeTimeseriesTreemap(ctx context.Context, req *metricsexplo
 	return entries, nil
 }
 
-func (m *module) computeSamplesTreemap(ctx context.Context, req *metricsexplorertypes.TreemapRequest, filterWhereClause *sqlbuilder.WhereClause) ([]metricsexplorertypes.TreemapEntry, error) {
+func (m *module) computeSamplesTreemap(ctx context.Context, req *metricsexplorertypes.TreemapRequest) ([]metricsexplorertypes.TreemapEntry, error) {
 	ctx = m.withMetricsExplorerContext(ctx, "computeSamplesTreemap")
 
+	hasFilter := req.Filter != nil && strings.TrimSpace(req.Filter.Expression) != ""
+	var filterWhereClause *sqlbuilder.WhereClause
+	if hasFilter {
+		var err error
+		filterWhereClause, err = m.buildFilterClause(ctx, req.Filter, req.Start, req.End)
+		if err != nil {
+			return nil, err
+		}
+	}
+
 	start, end, distributedTsTable, localTsTable := telemetrymetrics.WhichTSTableToUse(uint64(req.Start), uint64(req.End), nil)
-	samplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
-	countExp := telemetrymetrics.CountExpressionForSamplesTable(samplesTable)
+	distributedSamplesTable, _ := telemetrymetrics.WhichSamplesTableToUse(uint64(req.Start), uint64(req.End), metrictypes.UnspecifiedType, metrictypes.TimeAggregationUnspecified, nil)
+	countExp := telemetrymetrics.CountExpressionForSamplesTable(distributedSamplesTable)
 
 	candidateLimit := req.Limit + 50
 
@@ -1179,7 +1201,7 @@ func (m *module) computeSamplesTreemap(ctx context.Context, req *metricsexplorer
 
 	totalSamplesSB := sqlbuilder.NewSelectBuilder()
 	totalSamplesSB.Select(fmt.Sprintf("%s AS total_samples", countExp))
-	totalSamplesSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, samplesTable))
+	totalSamplesSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedSamplesTable))
 	totalSamplesSB.Where(totalSamplesSB.Between("unix_milli", req.Start, req.End))
 
 	sampleCountsSB := sqlbuilder.NewSelectBuilder()
@@ -1187,7 +1209,7 @@ func (m *module) computeSamplesTreemap(ctx context.Context, req *metricsexplorer
 		"metric_name",
 		fmt.Sprintf("%s AS samples", countExp),
 	)
-	sampleCountsSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, samplesTable))
+	sampleCountsSB.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedSamplesTable))
 	sampleCountsSB.Where(sampleCountsSB.Between("unix_milli", req.Start, req.End))
 	sampleCountsSB.Where("metric_name GLOBAL IN (SELECT metric_name FROM __metric_candidates)")
 

pkg/modules/metricsexplorer/implmetricsexplorer/module_test.go

@@ -0,0 +1,270 @@
+package implmetricsexplorer_test
+
+import (
+	"context"
+	"regexp"
+	"testing"
+
+	"github.com/DATA-DOG/go-sqlmock"
+	cmock "github.com/SigNoz/clickhouse-go-mock"
+	"github.com/SigNoz/signoz/pkg/cache"
+	"github.com/SigNoz/signoz/pkg/cache/cachetest"
+	"github.com/SigNoz/signoz/pkg/errors"
+	"github.com/SigNoz/signoz/pkg/instrumentation/instrumentationtest"
+	"github.com/SigNoz/signoz/pkg/modules/metricsexplorer"
+	"github.com/SigNoz/signoz/pkg/modules/metricsexplorer/implmetricsexplorer"
+	"github.com/SigNoz/signoz/pkg/telemetrystore"
+	"github.com/SigNoz/signoz/pkg/telemetrystore/telemetrystoretest"
+	"github.com/SigNoz/signoz/pkg/types/metricsexplorertypes"
+	qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
+	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
+	"github.com/SigNoz/signoz/pkg/types/telemetrytypes/telemetrytypestest"
+	"github.com/SigNoz/signoz/pkg/valuer"
+	"github.com/stretchr/testify/assert"
+)
+
+const (
+	// fixed, deterministic time window (range < 6h so the table selectors resolve
+	// to stable table names that the expected SQL strings can hard-code).
+	testStartMillis                int64 = 1700000000000
+	testEndMillis                  int64 = 1700003600000 // +1h
+	statsNoFilterSQL                     = "WITH __time_series_counts AS (SELECT metric_name, uniq(fingerprint) AS timeseries FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? GROUP BY metric_name), __sample_counts AS (SELECT metric_name, count(*) AS samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND metric_name IN (SELECT DISTINCT metric_name FROM signoz_metrics.time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ?) GROUP BY metric_name) SELECT COALESCE(ts.metric_name, s.metric_name) AS metric_name, COALESCE(ts.timeseries, 0) AS timeseries, COALESCE(s.samples, 0) AS samples, COUNT(*) OVER() AS total FROM __time_series_counts ts FULL OUTER JOIN __sample_counts s ON ts.metric_name = s.metric_name WHERE (COALESCE(ts.timeseries, 0) > 0 OR COALESCE(s.samples, 0) > 0) ORDER BY samples DESC, metric_name ASC LIMIT ? OFFSET ?"
+	statsOrderTimeseriesSQL              = "WITH __time_series_counts AS (SELECT metric_name, uniq(fingerprint) AS timeseries FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? GROUP BY metric_name), __sample_counts AS (SELECT metric_name, count(*) AS samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND metric_name IN (SELECT DISTINCT metric_name FROM signoz_metrics.time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ?) GROUP BY metric_name) SELECT COALESCE(ts.metric_name, s.metric_name) AS metric_name, COALESCE(ts.timeseries, 0) AS timeseries, COALESCE(s.samples, 0) AS samples, COUNT(*) OVER() AS total FROM __time_series_counts ts FULL OUTER JOIN __sample_counts s ON ts.metric_name = s.metric_name WHERE (COALESCE(ts.timeseries, 0) > 0 OR COALESCE(s.samples, 0) > 0) ORDER BY timeseries ASC, metric_name ASC LIMIT ? OFFSET ?"
+	statsWithFilterSQL                   = "WITH __time_series_counts AS (SELECT metric_name, uniq(fingerprint) AS timeseries FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? AND JSONExtractString(labels, 'host.name') = ? GROUP BY metric_name), __filtered_fingerprints AS (SELECT fingerprint FROM signoz_metrics.time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? AND JSONExtractString(labels, 'host.name') = ? GROUP BY fingerprint), __sample_counts AS (SELECT metric_name, count(*) AS samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND fingerprint IN (SELECT fingerprint FROM __filtered_fingerprints) GROUP BY metric_name) SELECT COALESCE(ts.metric_name, s.metric_name) AS metric_name, COALESCE(ts.timeseries, 0) AS timeseries, COALESCE(s.samples, 0) AS samples, COUNT(*) OVER() AS total FROM __time_series_counts ts FULL OUTER JOIN __sample_counts s ON ts.metric_name = s.metric_name WHERE (COALESCE(ts.timeseries, 0) > 0 OR COALESCE(s.samples, 0) > 0) ORDER BY samples DESC, metric_name ASC LIMIT ? OFFSET ?"
+	treemapTimeseriesNoFilterSQL         = "WITH __total_time_series AS (SELECT uniq(fingerprint) AS total_time_series FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND __normalized = ?), __metric_totals AS (SELECT metric_name, uniq(fingerprint) AS total_value FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? GROUP BY metric_name) SELECT mt.metric_name, mt.total_value, CASE WHEN tts.total_time_series = 0 THEN 0 ELSE (mt.total_value * 100.0 / tts.total_time_series) END AS percentage FROM __metric_totals mt JOIN __total_time_series tts ON 1=1 ORDER BY percentage DESC LIMIT ?"
+	treemapTimeseriesWithFilterSQL       = "WITH __total_time_series AS (SELECT uniq(fingerprint) AS total_time_series FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND __normalized = ?), __metric_totals AS (SELECT metric_name, uniq(fingerprint) AS total_value FROM signoz_metrics.distributed_time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? AND JSONExtractString(labels, 'host.name') = ? GROUP BY metric_name) SELECT mt.metric_name, mt.total_value, CASE WHEN tts.total_time_series = 0 THEN 0 ELSE (mt.total_value * 100.0 / tts.total_time_series) END AS percentage FROM __metric_totals mt JOIN __total_time_series tts ON 1=1 ORDER BY percentage DESC LIMIT ?"
+	treemapSamplesNoFilterSQL            = "WITH __metric_candidates AS (SELECT metric_name FROM signoz_metrics.distributed_time_series_v4 WHERE NOT startsWith(metric_name, 'signoz') AND __normalized = ? AND unix_milli BETWEEN ? AND ? GROUP BY metric_name ORDER BY uniq(fingerprint) DESC LIMIT ?), __sample_counts AS (SELECT metric_name, count(*) AS samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ? AND metric_name GLOBAL IN (SELECT metric_name FROM __metric_candidates) GROUP BY metric_name), __total_samples AS (SELECT count(*) AS total_samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ?) SELECT mc.metric_name, COALESCE(sc.samples, 0) AS samples, CASE WHEN ts.total_samples = 0 THEN 0 ELSE (COALESCE(sc.samples, 0) * 100.0 / ts.total_samples) END AS percentage FROM __metric_candidates mc LEFT JOIN __sample_counts sc ON mc.metric_name = sc.metric_name JOIN __total_samples ts ON 1=1 ORDER BY percentage DESC LIMIT ?"
+	treemapSamplesWithFilterSQL          = "WITH __metric_candidates AS (SELECT metric_name FROM signoz_metrics.distributed_time_series_v4 WHERE NOT startsWith(metric_name, 'signoz') AND __normalized = ? AND unix_milli BETWEEN ? AND ? AND JSONExtractString(labels, 'host.name') = ? GROUP BY metric_name ORDER BY uniq(fingerprint) DESC LIMIT ?), __filtered_fingerprints AS (SELECT fingerprint FROM signoz_metrics.time_series_v4 WHERE unix_milli BETWEEN ? AND ? AND NOT startsWith(metric_name, 'signoz') AND __normalized = ? AND JSONExtractString(labels, 'host.name') = ? AND metric_name GLOBAL IN (SELECT metric_name FROM __metric_candidates) GROUP BY fingerprint), __sample_counts AS (SELECT metric_name, count(*) AS samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ? AND metric_name GLOBAL IN (SELECT metric_name FROM __metric_candidates) AND fingerprint IN (SELECT fingerprint FROM __filtered_fingerprints) GROUP BY metric_name), __total_samples AS (SELECT count(*) AS total_samples FROM signoz_metrics.distributed_samples_v4 WHERE unix_milli BETWEEN ? AND ?) SELECT mc.metric_name, COALESCE(sc.samples, 0) AS samples, CASE WHEN ts.total_samples = 0 THEN 0 ELSE (COALESCE(sc.samples, 0) * 100.0 / ts.total_samples) END AS percentage FROM __metric_candidates mc LEFT JOIN __sample_counts sc ON mc.metric_name = sc.metric_name JOIN __total_samples ts ON 1=1 ORDER BY percentage DESC LIMIT ?"
+)
+
+var testOrgID = valuer.GenerateUUID()
+
+type statsOpt func(*metricsexplorertypes.StatsRequest)
+
+type treemapOpt func(*metricsexplorertypes.TreemapRequest)
+
+// newTestModule builds the metricsexplorer module backed by a mocked clickhouse
+// connection, a mock metadata store, and an in-memory cache.
+func newTestModule(t *testing.T, matcher sqlmock.QueryMatcher) (metricsexplorer.Module, cmock.ClickConnMockCommon, *telemetrytypestest.MockMetadataStore) {
+	t.Helper()
+
+	ts := telemetrystoretest.New(telemetrystore.Config{}, matcher)
+	md := telemetrytypestest.NewMockMetadataStore()
+	c, err := cachetest.New(cache.Config{Provider: "memory", Memory: cache.Memory{NumCounters: 1000, MaxCost: 1 << 20}})
+	if err != nil {
+		t.Fatalf("cachetest.New: %v", err)
+	}
+
+	settings := instrumentationtest.New().ToProviderSettings()
+	mod := implmetricsexplorer.NewModule(ts, md, c, nil /*ruleStore*/, nil /*dashboardModule*/, settings, metricsexplorer.Config{})
+
+	return mod, ts.Mock(), md
+}
+
+func statsRequest(opts ...statsOpt) *metricsexplorertypes.StatsRequest {
+	req := &metricsexplorertypes.StatsRequest{
+		Start: testStartMillis,
+		End:   testEndMillis,
+		Limit: 10,
+	}
+	for _, o := range opts {
+		o(req)
+	}
+	return req
+}
+
+func withStatsFilter(expr string) statsOpt {
+	return func(req *metricsexplorertypes.StatsRequest) {
+		req.Filter = &qbtypes.Filter{Expression: expr}
+	}
+}
+
+func withStatsLimit(limit int) statsOpt {
+	return func(req *metricsexplorertypes.StatsRequest) {
+		req.Limit = limit
+	}
+}
+
+func withStatsOrderBy(name string, dir qbtypes.OrderDirection) statsOpt {
+	return func(req *metricsexplorertypes.StatsRequest) {
+		req.OrderBy = &qbtypes.OrderBy{
+			Key:       qbtypes.OrderByKey{TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: name}},
+			Direction: dir,
+		}
+	}
+}
+
+func treemapRequest(mode metricsexplorertypes.TreemapMode, opts ...treemapOpt) *metricsexplorertypes.TreemapRequest {
+	req := &metricsexplorertypes.TreemapRequest{
+		Start: testStartMillis,
+		End:   testEndMillis,
+		Limit: 10,
+		Mode:  mode,
+	}
+	for _, o := range opts {
+		o(req)
+	}
+	return req
+}
+
+func withTreemapFilter(expr string) treemapOpt {
+	return func(req *metricsexplorertypes.TreemapRequest) {
+		req.Filter = &qbtypes.Filter{Expression: expr}
+	}
+}
+
+// seedFilterKey registers a string attribute field so buildFilterClause can
+// resolve it when parsing a filter expression that references it.
+func seedFilterKey(md *telemetrytypestest.MockMetadataStore, name string) {
+	md.KeysMap[name] = []*telemetrytypes.TelemetryFieldKey{
+		{
+			Name:          name,
+			Signal:        telemetrytypes.SignalMetrics,
+			FieldContext:  telemetrytypes.FieldContextAttribute,
+			FieldDataType: telemetrytypes.FieldDataTypeString,
+		},
+	}
+}
+
+// anyArgs returns n nil wildcards. cmock treats a nil expected arg as a match
+// for any actual value, so this asserts only the bound-arg count, not values
+// (the SQL text itself is what we verify). The count must match the query.
+func anyArgs(n int) []any {
+	return make([]any, n)
+}
+
+func treemapEntryRows() *cmock.Rows {
+	return cmock.NewRows(
+		[]cmock.ColumnType{
+			{Name: "metric_name", Type: "String"},
+			{Name: "total_value", Type: "UInt64"},
+			{Name: "percentage", Type: "Float64"},
+		},
+		[][]any{
+			{"metric_a", uint64(50), 50.0},
+			{"metric_b", uint64(30), 30.0},
+		},
+	)
+}
+
+func TestGetStats(t *testing.T) {
+	tests := []struct {
+		name      string
+		opts      []statsOpt
+		seedKey   string
+		queryErr  error
+		expectSQL string
+		argCount  int
+		noQuery   bool // SQL never reaches clickhouse (validation/build error)
+		wantCode  errors.Code
+	}{
+		{name: "NoFilter_FastPathSQL", expectSQL: statsNoFilterSQL, argCount: 10},
+		{name: "WhitespaceFilter_FastPathSQL", opts: []statsOpt{withStatsFilter("   ")}, expectSQL: statsNoFilterSQL, argCount: 10},
+		{name: "WithFilter_FingerprintSQL", opts: []statsOpt{withStatsFilter("host.name = 'foo'")}, seedKey: "host.name", expectSQL: statsWithFilterSQL, argCount: 12},
+		{name: "OrderByTimeseriesAsc", opts: []statsOpt{withStatsOrderBy("timeseries", qbtypes.OrderDirectionAsc)}, expectSQL: statsOrderTimeseriesSQL, argCount: 10},
+		{name: "OrderByInvalid", opts: []statsOpt{withStatsOrderBy("nonsense", qbtypes.OrderDirectionAsc)}, noQuery: true, wantCode: errors.CodeInvalidInput},
+		{name: "QueryError", queryErr: assert.AnError, expectSQL: statsNoFilterSQL, argCount: 10, wantCode: errors.CodeInternal},
+		{name: "InvalidRequest_Limit", opts: []statsOpt{withStatsLimit(0)}, noQuery: true, wantCode: errors.CodeInvalidInput},
+	}
+
+	for _, tc := range tests {
+		t.Run(tc.name, func(t *testing.T) {
+			mod, mock, md := newTestModule(t, sqlmock.QueryMatcherRegexp)
+			if tc.seedKey != "" {
+				seedFilterKey(md, tc.seedKey)
+			}
+
+			if !tc.noQuery {
+				eq := mock.ExpectQuery(regexp.QuoteMeta(tc.expectSQL)).WithArgs(anyArgs(tc.argCount)...)
+				if tc.queryErr != nil {
+					eq.WillReturnError(tc.queryErr)
+				} else {
+					eq.WillReturnRows(cmock.NewRows(nil, nil))
+				}
+			}
+
+			_, err := mod.GetStats(context.Background(), testOrgID, statsRequest(tc.opts...))
+			if tc.wantCode.String() != "" {
+				assert.Error(t, err)
+				assert.Truef(t, errors.Asc(err, tc.wantCode), "want code %s, got %v", tc.wantCode, err)
+				return
+			}
+			assert.NoError(t, err)
+			assert.NoError(t, mock.ExpectationsWereMet())
+		})
+	}
+}
+
+func TestGetTreemap(t *testing.T) {
+	wantEntries := []metricsexplorertypes.TreemapEntry{
+		{MetricName: "metric_a", TotalValue: 50, Percentage: 50.0},
+		{MetricName: "metric_b", TotalValue: 30, Percentage: 30.0},
+	}
+
+	tests := []struct {
+		name        string
+		mode        metricsexplorertypes.TreemapMode
+		opts        []treemapOpt
+		seedKey     string
+		queryErr    error
+		expectSQL   string
+		argCount    int
+		rows        *cmock.Rows
+		wantSamples []metricsexplorertypes.TreemapEntry
+		wantTS      []metricsexplorertypes.TreemapEntry
+		noQuery     bool
+		wantCode    errors.Code
+		wantErr     bool
+	}{
+		{name: "TimeSeries_NoFilter_SQL", mode: metricsexplorertypes.TreemapModeTimeSeries, expectSQL: treemapTimeseriesNoFilterSQL, argCount: 7},
+		{name: "TimeSeries_WithFilter_SQL", mode: metricsexplorertypes.TreemapModeTimeSeries, opts: []treemapOpt{withTreemapFilter("host.name = 'foo'")}, seedKey: "host.name", expectSQL: treemapTimeseriesWithFilterSQL, argCount: 8},
+		{name: "TimeSeries_ScansEntries", mode: metricsexplorertypes.TreemapModeTimeSeries, expectSQL: treemapTimeseriesNoFilterSQL, argCount: 7, rows: treemapEntryRows(), wantTS: wantEntries},
+		{name: "Samples_NoFilter_SQL", mode: metricsexplorertypes.TreemapModeSamples, expectSQL: treemapSamplesNoFilterSQL, argCount: 9},
+		{name: "Samples_WithFilter_SQL", mode: metricsexplorertypes.TreemapModeSamples, opts: []treemapOpt{withTreemapFilter("host.name = 'foo'")}, seedKey: "host.name", expectSQL: treemapSamplesWithFilterSQL, argCount: 14},
+		{name: "Samples_ScansEntries", mode: metricsexplorertypes.TreemapModeSamples, expectSQL: treemapSamplesNoFilterSQL, argCount: 9, rows: treemapEntryRows(), wantSamples: wantEntries},
+		{name: "FilterBuildError", mode: metricsexplorertypes.TreemapModeTimeSeries, opts: []treemapOpt{withTreemapFilter("host.name =")}, noQuery: true, wantErr: true},
+		{name: "QueryError", mode: metricsexplorertypes.TreemapModeTimeSeries, queryErr: assert.AnError, expectSQL: treemapTimeseriesNoFilterSQL, argCount: 7, wantCode: errors.CodeInternal},
+		{name: "InvalidMode", mode: metricsexplorertypes.TreemapMode{}, noQuery: true, wantCode: errors.CodeInvalidInput},
+	}
+
+	for _, tc := range tests {
+		t.Run(tc.name, func(t *testing.T) {
+			mod, mock, md := newTestModule(t, sqlmock.QueryMatcherRegexp)
+			if tc.seedKey != "" {
+				seedFilterKey(md, tc.seedKey)
+			}
+
+			if !tc.noQuery {
+				eq := mock.ExpectQuery(regexp.QuoteMeta(tc.expectSQL)).WithArgs(anyArgs(tc.argCount)...)
+				switch {
+				case tc.queryErr != nil:
+					eq.WillReturnError(tc.queryErr)
+				case tc.rows != nil:
+					eq.WillReturnRows(tc.rows)
+				default:
+					eq.WillReturnRows(cmock.NewRows(nil, nil))
+				}
+			}
+
+			resp, err := mod.GetTreemap(context.Background(), testOrgID, treemapRequest(tc.mode, tc.opts...))
+			switch {
+			case tc.wantCode.String() != "":
+				assert.Error(t, err)
+				assert.Truef(t, errors.Asc(err, tc.wantCode), "want code %s, got %v", tc.wantCode, err)
+				return
+			case tc.wantErr:
+				assert.Error(t, err)
+				return
+			}
+
+			assert.NoError(t, err)
+			assert.NoError(t, mock.ExpectationsWereMet())
+			if tc.wantTS != nil {
+				assert.Equal(t, tc.wantTS, resp.TimeSeries)
+			}
+			if tc.wantSamples != nil {
+				assert.Equal(t, tc.wantSamples, resp.Samples)
+			}
+		})
+	}
+}

pkg/modules/tracedetail/config.go

@@ -59,19 +59,19 @@ func (c Config) Validate() error {
 		return errors.NewInvalidInputf(errors.CodeInvalidInput, "traces.waterfall.max_limit_to_select_all_spans must be positive")
 	}
 	if c.Flamegraph.MaxSelectedLevels <= 0 {
-		return errors.NewInvalidInputf(errors.CodeInvalidInput, "tracedetail.flamegraph.level_limit must be positive, got %d", c.Flamegraph.MaxSelectedLevels)
+		return errors.NewInvalidInputf(errors.CodeInvalidInput, "traces.flamegraph.max_selected_levels must be positive, got %d", c.Flamegraph.MaxSelectedLevels)
 	}
 	if c.Flamegraph.MaxSpansPerLevel <= 0 {
-		return errors.NewInvalidInputf(errors.CodeInvalidInput, "tracedetail.flamegraph.spans_per_level must be positive, got %d", c.Flamegraph.MaxSpansPerLevel)
+		return errors.NewInvalidInputf(errors.CodeInvalidInput, "traces.flamegraph.max_spans_per_level must be positive, got %d", c.Flamegraph.MaxSpansPerLevel)
 	}
 	if c.Flamegraph.SamplingTopLatencySpansCount < 0 {
-		return errors.NewInvalidInputf(errors.CodeInvalidInput, "tracedetail.flamegraph.top_latency_count cannot be negative, got %d", c.Flamegraph.SamplingTopLatencySpansCount)
+		return errors.NewInvalidInputf(errors.CodeInvalidInput, "traces.flamegraph.sampling_top_latency_count cannot be negative, got %d", c.Flamegraph.SamplingTopLatencySpansCount)
 	}
 	if c.Flamegraph.SamplingBucketCount <= 0 {
-		return errors.NewInvalidInputf(errors.CodeInvalidInput, "tracedetail.flamegraph.bucket_count must be positive, got %d", c.Flamegraph.SamplingBucketCount)
+		return errors.NewInvalidInputf(errors.CodeInvalidInput, "traces.flamegraph.sampling_bucket_count must be positive, got %d", c.Flamegraph.SamplingBucketCount)
 	}
 	if c.Flamegraph.SelectAllSpansLimit == 0 {
-		return errors.NewInvalidInputf(errors.CodeInvalidInput, "tracedetail.flamegraph.max_limit_to_select_all_spans must be positive")
+		return errors.NewInvalidInputf(errors.CodeInvalidInput, "traces.flamegraph.select_all_spans_limit must be positive")
 	}
 	return nil
 }

pkg/modules/tracedetail/impltracedetail/handler.go

@@ -18,27 +18,6 @@ func NewHandler(module tracedetail.Module) tracedetail.Handler {
 	return &handler{module: module}
 }
 
-func (h *handler) GetWaterfall(rw http.ResponseWriter, r *http.Request) {
-	req := new(spantypes.PostableWaterfall)
-	if err := binding.JSON.BindBody(r.Body, req); err != nil {
-		render.Error(rw, err)
-		return
-	}
-
-	if err := req.Validate(); err != nil {
-		render.Error(rw, err)
-		return
-	}
-
-	result, err := h.module.GetWaterfall(r.Context(), mux.Vars(r)["traceID"], req)
-	if err != nil {
-		render.Error(rw, err)
-		return
-	}
-
-	render.Success(rw, http.StatusOK, result)
-}
-
 func (h *handler) GetWaterfallV4(rw http.ResponseWriter, r *http.Request) {
 	req := new(spantypes.PostableWaterfall)
 	if err := binding.JSON.BindBody(r.Body, req); err != nil {
@@ -51,7 +30,7 @@ func (h *handler) GetWaterfallV4(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	result, err := h.module.GetWaterfallV4(r.Context(), mux.Vars(r)["traceID"], req.SelectedSpanID, req.UncollapsedSpans, req.Limit)
+	result, err := h.module.GetWaterfallV4(r.Context(), mux.Vars(r)["traceID"], req.SelectedSpanID, req.UncollapsedSpans)
 	if err != nil {
 		render.Error(rw, err)
 		return

pkg/modules/tracedetail/impltracedetail/module.go

@@ -34,66 +34,21 @@ func NewModule(traceStore spantypes.TraceStore, providerSettings factory.Provide
 	}
 
 	m.metrics.waterfallSpanLimit.Record(context.Background(), int64(cfg.Waterfall.MaxLimitToSelectAllSpans), metric.WithAttributes(attrResponseType.String(attrResponseTypeWindowed)))
+	m.metrics.flamegraphSpanLimit.Record(context.Background(), int64(cfg.Flamegraph.SelectAllSpansLimit), metric.WithAttributes(attrResponseType.String(attrResponseTypeSampled)))
 
 	return m
 }
 
-func (m *module) GetWaterfall(ctx context.Context, traceID string, req *spantypes.PostableWaterfall) (*spantypes.GettableWaterfallTrace, error) {
-	waterfallTrace, err := m.getTraceData(ctx, traceID)
-	if err != nil {
-		return nil, err
-	}
-
-	selectedSpans, uncollapsedSpans, selectedAllSpans := waterfallTrace.GetWaterfallSpans(
-		req.UncollapsedSpans,
-		req.SelectedSpanID,
-		min(req.Limit, m.config.Waterfall.MaxLimitToSelectAllSpans),
-		m.config.Waterfall.SpanPageSize,
-		m.config.Waterfall.MaxDepthToAutoExpand,
-	)
-
-	aggregationResults := make([]spantypes.SpanAggregationResult, 0, len(req.Aggregations))
-	for _, a := range req.Aggregations {
-		aggregationResults = append(aggregationResults, waterfallTrace.GetSpanAggregation(a.Aggregation, a.Field))
-	}
-
-	return spantypes.NewGettableWaterfallTrace(waterfallTrace, selectedSpans, uncollapsedSpans, selectedAllSpans, aggregationResults), nil
-}
-
-// getTraceData fetches all spans for a trace and builds the WaterfallTrace.
-func (m *module) getTraceData(ctx context.Context, traceID string) (*spantypes.WaterfallTrace, error) {
-	summary, err := m.store.GetTraceSummary(ctx, traceID)
-	if err != nil {
-		return nil, err
-	}
-
-	spanItems, err := m.store.GetTraceSpans(ctx, traceID, summary)
-	if err != nil {
-		return nil, err
-	}
-
-	if len(spanItems) == 0 {
-		return nil, spantypes.ErrTraceNotFound
-	}
-
-	nodes := make([]*spantypes.WaterfallSpan, len(spanItems))
-	for i := range spanItems {
-		nodes[i] = spanItems[i].ToWaterfallSpan(traceID)
-	}
-	return spantypes.NewWaterfallTraceFromSpans(nodes), nil
-}
-
 // GetWaterfallV4 is the OOM-safe V4 waterfall.
 // For large traces (NumSpans > effectiveLimit) it uses a two-step fetch:
 // minimal fields for all spans to build the tree, then full fields for the
 // visible window only. Aggregations are not returned.
-func (m *module) GetWaterfallV4(ctx context.Context, traceID string, selectedSpanID string, uncollapsedSpans []string, selectAllLimit uint) (*spantypes.GettableWaterfallTrace, error) {
+func (m *module) GetWaterfallV4(ctx context.Context, traceID string, selectedSpanID string, uncollapsedSpans []string) (*spantypes.GettableWaterfallTrace, error) {
 	summary, err := m.store.GetTraceSummary(ctx, traceID)
 	if err != nil {
 		return nil, err
 	}
-	effectiveLimit := min(selectAllLimit, m.config.Waterfall.MaxLimitToSelectAllSpans)
-	if summary.NumSpans > uint64(effectiveLimit) {
+	if summary.NumSpans > uint64(m.config.Waterfall.MaxLimitToSelectAllSpans) {
 		attrs := metric.WithAttributes(attrResponseType.String(attrResponseTypeWindowed))
 		m.metrics.waterfallRequestCount.Add(ctx, 1, attrs)
 		m.metrics.waterfallSpanCount.Add(ctx, int64(summary.NumSpans), attrs)
@@ -119,7 +74,7 @@ func (m *module) getFullWaterfall(ctx context.Context, traceID string, summary *
 	waterfallTrace := spantypes.NewWaterfallTraceFromSpans(nodes)
 	selectedSpans := waterfallTrace.GetAllSpans()
 
-	return spantypes.NewGettableWaterfallTrace(waterfallTrace, selectedSpans, nil, true, nil), nil
+	return spantypes.NewGettableWaterfallTrace(waterfallTrace, selectedSpans, nil, true), nil
 }
 
 func (m *module) GetTraceAggregations(ctx context.Context, traceID string, req *spantypes.PostableTraceAggregations) (*spantypes.GettableTraceAggregations, error) {
@@ -173,6 +128,7 @@ func (m *module) GetFlamegraph(ctx context.Context, traceID string, selectedSpan
 	if summary.NumSpans <= uint64(m.config.Flamegraph.SelectAllSpansLimit) {
 		return m.getFullFlamegraph(ctx, traceID, summary, selectFields)
 	}
+	m.metrics.flamegraphRequestCount.Add(ctx, 1, metric.WithAttributes(attrResponseType.String(attrResponseTypeSampled)))
 	return m.getWindowedFlamegraph(ctx, traceID, selectedSpanID, summary, selectFields)
 }
 
@@ -213,7 +169,7 @@ func (m *module) getWindowedWaterfall(ctx context.Context, traceID, selectedSpan
 	spantypes.EnrichSelectedSpans(selectedSpans, fullSpans)
 
 	return spantypes.NewGettableWaterfallTrace(
-		waterfallTrace, selectedSpans, uncollapsedSpans, false, nil,
+		waterfallTrace, selectedSpans, uncollapsedSpans, false,
 	), nil
 }
 

pkg/modules/tracedetail/impltracedetail/telemetry.go

@@ -9,12 +9,16 @@ import (
 const (
 	attrResponseType         = attribute.Key("response_type")
 	attrResponseTypeWindowed = "windowed"
+	attrResponseTypeSampled  = "sampled"
 )
 
 type moduleMetrics struct {
 	waterfallSpanLimit    metric.Int64Gauge
 	waterfallRequestCount metric.Int64Counter
 	waterfallSpanCount    metric.Int64Counter
+
+	flamegraphSpanLimit    metric.Int64Gauge
+	flamegraphRequestCount metric.Int64Counter
 }
 
 func newModuleMetrics(meter metric.Meter) (*moduleMetrics, error) {
@@ -47,9 +51,30 @@ func newModuleMetrics(meter metric.Meter) (*moduleMetrics, error) {
 		errs = errors.Join(errs, err)
 	}
 
+	flamegraphSpanLimit, err := meter.Int64Gauge(
+		"signoz.traces.flamegraph.span.limit",
+		metric.WithDescription("The span count limit above which sampled flamegraph is returned instead of the full flamegraph."),
+		metric.WithUnit("{span}"),
+	)
+	if err != nil {
+		errs = errors.Join(errs, err)
+	}
+
+	flamegraphRequestCount, err := meter.Int64Counter(
+		"signoz.traces.flamegraph.request.count",
+		metric.WithDescription("Total number of flamegraph requests, by response_type."),
+		metric.WithUnit("{request}"),
+	)
+	if err != nil {
+		errs = errors.Join(errs, err)
+	}
+
 	return &moduleMetrics{
 		waterfallSpanLimit:    spanLimit,
 		waterfallRequestCount: requestCount,
 		waterfallSpanCount:    spanCount,
+
+		flamegraphSpanLimit:    flamegraphSpanLimit,
+		flamegraphRequestCount: flamegraphRequestCount,
 	}, errs
 }

pkg/modules/tracedetail/impltracedetail/waterfall_test.go

@@ -260,7 +260,7 @@ func TestGetSelectedSpans_MultipleRoots(t *testing.T) {
 	trace := getWaterfallTrace([]*spantypes.WaterfallSpan{root1, root2}, spanMap)
 	spans, _ := trace.GetSelectedSpans([]string{"root1", "root2"}, "root1", 500, 5)
 
-	traceRespnose := spantypes.NewGettableWaterfallTrace(trace, spans, nil, false, nil)
+	traceRespnose := spantypes.NewGettableWaterfallTrace(trace, spans, nil, false)
 
 	assert.Equal(t, []string{"root1", "child1", "root2", "child2"}, spanIDs(spans), "root1 subtree must precede root2 subtree")
 	assert.Equal(t, "svc-a", traceRespnose.RootServiceName, "metadata comes from first root")
@@ -567,7 +567,7 @@ func TestGetAllSpans(t *testing.T) {
 	)
 	trace := getWaterfallTrace([]*spantypes.WaterfallSpan{root}, nil)
 	spans := trace.GetAllSpans()
-	traceResponse := spantypes.NewGettableWaterfallTrace(trace, spans, nil, true, nil)
+	traceResponse := spantypes.NewGettableWaterfallTrace(trace, spans, nil, true)
 	assert.ElementsMatch(t, spanIDs(spans), []string{"root", "childA", "grandchildA", "leafA", "childB", "grandchildB", "leafB"})
 	assert.Equal(t, "svc", traceResponse.RootServiceName)
 	assert.Equal(t, "root-op", traceResponse.RootServiceEntryPoint)

pkg/modules/tracedetail/tracedetail.go

@@ -10,7 +10,6 @@ import (
 
 // Handler exposes HTTP handlers for trace detail APIs.
 type Handler interface {
-	GetWaterfall(http.ResponseWriter, *http.Request)
 	GetWaterfallV4(http.ResponseWriter, *http.Request)
 	GetTraceAggregations(http.ResponseWriter, *http.Request)
 	GetFlamegraph(http.ResponseWriter, *http.Request)
@@ -18,8 +17,7 @@ type Handler interface {
 
 // Module defines the business logic for trace detail operations.
 type Module interface {
-	GetWaterfall(ctx context.Context, traceID string, req *spantypes.PostableWaterfall) (*spantypes.GettableWaterfallTrace, error)
-	GetWaterfallV4(ctx context.Context, traceID string, selectedSpanID string, uncollapsedSpans []string, selectAllLimit uint) (*spantypes.GettableWaterfallTrace, error)
+	GetWaterfallV4(ctx context.Context, traceID string, selectedSpanID string, uncollapsedSpans []string) (*spantypes.GettableWaterfallTrace, error)
 	GetTraceAggregations(ctx context.Context, traceID string, req *spantypes.PostableTraceAggregations) (*spantypes.GettableTraceAggregations, error)
 	GetFlamegraph(ctx context.Context, traceID string, selectedSpanID string, selectFields []telemetrytypes.TelemetryFieldKey) (*spantypes.GettableFlamegraphTrace, error)
 }

pkg/query-service/app/clickhouseReader/reader.go

@@ -18,7 +18,6 @@ import (
 	"github.com/uptrace/bun"
 
 	"github.com/SigNoz/signoz/pkg/prometheus"
-	"github.com/SigNoz/signoz/pkg/query-service/utils/timestamp"
 	"github.com/SigNoz/signoz/pkg/sqlstore"
 	"github.com/SigNoz/signoz/pkg/telemetrystore"
 	"github.com/SigNoz/signoz/pkg/types"
@@ -47,7 +46,6 @@ import (
 	"github.com/SigNoz/signoz/pkg/query-service/app/resource"
 	"github.com/SigNoz/signoz/pkg/query-service/app/services"
 	"github.com/SigNoz/signoz/pkg/query-service/app/traces/smart"
-	"github.com/SigNoz/signoz/pkg/query-service/app/traces/tracedetail"
 	"github.com/SigNoz/signoz/pkg/query-service/common"
 	"github.com/SigNoz/signoz/pkg/query-service/constants"
 
@@ -898,390 +896,6 @@ func (r *ClickHouseReader) GetSpansForTrace(ctx context.Context, traceID string,
 	return searchScanResponses, nil
 }
 
-func (r *ClickHouseReader) GetWaterfallSpansForTraceWithMetadataCache(ctx context.Context, orgID valuer.UUID, traceID string) (*model.GetWaterfallSpansForTraceWithMetadataCache, error) {
-	cachedTraceData := new(model.GetWaterfallSpansForTraceWithMetadataCache)
-	err := r.cacheForTraceDetail.Get(ctx, orgID, strings.Join([]string{"getWaterfallSpansForTraceWithMetadata", traceID}, "-"), cachedTraceData)
-	if err != nil {
-		r.logger.Debug("error in retrieving getWaterfallSpansForTraceWithMetadata cache", errorsV2.Attr(err), "traceID", traceID)
-		return nil, err
-	}
-
-	if time.Since(time.UnixMilli(int64(cachedTraceData.EndTime))) < r.fluxIntervalForTraceDetail {
-		r.logger.Info("the trace end time falls under the flux interval, skipping getWaterfallSpansForTraceWithMetadata cache", "traceID", traceID)
-		return nil, errors.Errorf("the trace end time falls under the flux interval, skipping getWaterfallSpansForTraceWithMetadata cache, traceID: %s", traceID)
-	}
-
-	r.logger.Info("cache is successfully hit, applying cache for getWaterfallSpansForTraceWithMetadata", "traceID", traceID)
-	return cachedTraceData, nil
-}
-
-func (r *ClickHouseReader) GetWaterfallSpansForTraceWithMetadata(ctx context.Context, orgID valuer.UUID, traceID string, req *model.GetWaterfallSpansForTraceWithMetadataParams) (*model.GetWaterfallSpansForTraceWithMetadataResponse, error) {
-	response := new(model.GetWaterfallSpansForTraceWithMetadataResponse)
-	var startTime, endTime, durationNano, totalErrorSpans, totalSpans uint64
-	var spanIdToSpanNodeMap = map[string]*model.Span{}
-	var traceRoots []*model.Span
-	var serviceNameToTotalDurationMap = map[string]uint64{}
-	var serviceNameIntervalMap = map[string][]tracedetail.Interval{}
-	var hasMissingSpans bool
-
-	cachedTraceData, err := r.GetWaterfallSpansForTraceWithMetadataCache(ctx, orgID, traceID)
-	if err == nil {
-		startTime = cachedTraceData.StartTime
-		endTime = cachedTraceData.EndTime
-		durationNano = cachedTraceData.DurationNano
-		spanIdToSpanNodeMap = cachedTraceData.SpanIdToSpanNodeMap
-		serviceNameToTotalDurationMap = cachedTraceData.ServiceNameToTotalDurationMap
-		traceRoots = cachedTraceData.TraceRoots
-		totalSpans = cachedTraceData.TotalSpans
-		totalErrorSpans = cachedTraceData.TotalErrorSpans
-		hasMissingSpans = cachedTraceData.HasMissingSpans
-	}
-
-	if err != nil {
-		r.logger.Info("cache miss for getWaterfallSpansForTraceWithMetadata", "traceID", traceID)
-
-		searchScanResponses, err := r.GetSpansForTrace(ctx, traceID, fmt.Sprintf("SELECT DISTINCT ON (span_id) timestamp, duration_nano, span_id, trace_id, has_error, kind, resource_string_service$$name, name, links as references, attributes_string, attributes_number, attributes_bool, resources_string, events, status_message, status_code_string, kind_string FROM %s.%s WHERE trace_id=$1 and ts_bucket_start>=$2 and ts_bucket_start<=$3 ORDER BY timestamp ASC, name ASC", r.TraceDB, r.traceTableName))
-		if err != nil {
-			return nil, err
-		}
-		if len(searchScanResponses) == 0 {
-			return response, nil
-		}
-		totalSpans = uint64(len(searchScanResponses))
-		for _, item := range searchScanResponses {
-			ref := []model.OtelSpanRef{}
-			err := json.Unmarshal([]byte(item.References), &ref)
-			if err != nil {
-				r.logger.Error("getWaterfallSpansForTraceWithMetadata: error unmarshalling references", errorsV2.Attr(err), "traceID", traceID)
-				return nil, errorsV2.Newf(errorsV2.TypeInvalidInput, errorsV2.CodeInvalidInput, "getWaterfallSpansForTraceWithMetadata: error unmarshalling references %s", err.Error())
-			}
-
-			// merge attributes_number and attributes_bool to attributes_string
-			for k, v := range item.Attributes_bool {
-				item.Attributes_string[k] = fmt.Sprintf("%v", v)
-			}
-			for k, v := range item.Attributes_number {
-				item.Attributes_string[k] = strconv.FormatFloat(v, 'f', -1, 64)
-			}
-			for k, v := range item.Resources_string {
-				item.Attributes_string[k] = v
-			}
-
-			events := make([]model.Event, 0)
-			for _, event := range item.Events {
-				var eventMap model.Event
-				err = json.Unmarshal([]byte(event), &eventMap)
-				if err != nil {
-					r.logger.Error("Error unmarshalling events", errorsV2.Attr(err))
-					return nil, errorsV2.Newf(errorsV2.TypeInternal, errorsV2.CodeInternal, "getWaterfallSpansForTraceWithMetadata: error in unmarshalling events %s", err.Error())
-				}
-				events = append(events, eventMap)
-			}
-
-			startTimeUnixNano := uint64(item.TimeUnixNano.UnixNano())
-
-			jsonItem := model.Span{
-				SpanID:           item.SpanID,
-				TraceID:          item.TraceID,
-				ServiceName:      item.ServiceName,
-				Name:             item.Name,
-				Kind:             int32(item.Kind),
-				DurationNano:     item.DurationNano,
-				HasError:         item.HasError,
-				StatusMessage:    item.StatusMessage,
-				StatusCodeString: item.StatusCodeString,
-				SpanKind:         item.SpanKind,
-				References:       ref,
-				Events:           events,
-				TagMap:           item.Attributes_string,
-				Children:         make([]*model.Span, 0),
-				TimeUnixNano:     startTimeUnixNano, // Store nanoseconds temporarily
-			}
-
-			// metadata calculation
-			if startTime == 0 || startTimeUnixNano < startTime {
-				startTime = startTimeUnixNano
-			}
-			if endTime == 0 || (startTimeUnixNano+jsonItem.DurationNano) > endTime {
-				endTime = (startTimeUnixNano + jsonItem.DurationNano)
-			}
-			if durationNano == 0 || jsonItem.DurationNano > durationNano {
-				durationNano = jsonItem.DurationNano
-			}
-
-			if jsonItem.HasError {
-				totalErrorSpans = totalErrorSpans + 1
-			}
-
-			// collect the intervals for service for execution time calculation
-			serviceNameIntervalMap[jsonItem.ServiceName] =
-				append(serviceNameIntervalMap[jsonItem.ServiceName], tracedetail.Interval{StartTime: jsonItem.TimeUnixNano, Duration: jsonItem.DurationNano, Service: jsonItem.ServiceName})
-
-			// append to the span node map
-			spanIdToSpanNodeMap[jsonItem.SpanID] = &jsonItem
-		}
-
-		// traverse through the map and append each node to the children array of the parent node
-		// and add the missing spans
-		for _, spanNode := range spanIdToSpanNodeMap {
-			hasParentSpanNode := false
-			for _, reference := range spanNode.References {
-				if reference.RefType == "CHILD_OF" && reference.SpanId != "" {
-					hasParentSpanNode = true
-
-					if parentNode, exists := spanIdToSpanNodeMap[reference.SpanId]; exists {
-						parentNode.Children = append(parentNode.Children, spanNode)
-					} else {
-						// insert the missing span
-						missingSpan := model.Span{
-							SpanID:           reference.SpanId,
-							TraceID:          spanNode.TraceID,
-							ServiceName:      "",
-							Name:             "Missing Span",
-							TimeUnixNano:     spanNode.TimeUnixNano,
-							Kind:             0,
-							DurationNano:     spanNode.DurationNano,
-							HasError:         false,
-							StatusMessage:    "",
-							StatusCodeString: "",
-							SpanKind:         "",
-							Events:           make([]model.Event, 0),
-							Children:         make([]*model.Span, 0),
-						}
-						missingSpan.Children = append(missingSpan.Children, spanNode)
-						spanIdToSpanNodeMap[missingSpan.SpanID] = &missingSpan
-						traceRoots = append(traceRoots, &missingSpan)
-						hasMissingSpans = true
-					}
-				}
-			}
-			if !hasParentSpanNode && !tracedetail.ContainsWaterfallSpan(traceRoots, spanNode) {
-				traceRoots = append(traceRoots, spanNode)
-			}
-		}
-
-		// sort the trace roots to add missing spans at the right order
-		sort.Slice(traceRoots, func(i, j int) bool {
-			if traceRoots[i].TimeUnixNano == traceRoots[j].TimeUnixNano {
-				return traceRoots[i].Name < traceRoots[j].Name
-			}
-			return traceRoots[i].TimeUnixNano < traceRoots[j].TimeUnixNano
-		})
-
-		serviceNameToTotalDurationMap = tracedetail.CalculateServiceTime(serviceNameIntervalMap)
-
-		// TODO: set the span data (model.GetWaterfallSpansForTraceWithMetadataCache) in cache here
-		// removed existing cache usage since it was not getting used due to this bug https://github.com/SigNoz/engineering-pod/issues/4648
-		// and was causing out of memory issues https://github.com/SigNoz/engineering-pod/issues/4638
-	}
-
-	processingPostCache := time.Now()
-	// When req.Limit is 0 (not set by the client),  selectAllSpans is set to false
-	// preserving the old paged behaviour for backward compatibility
-	limit := min(req.Limit, tracedetail.MaxLimitToSelectAllSpans)
-	selectAllSpans := totalSpans <= uint64(limit)
-
-	var (
-		selectedSpans                          []*model.Span
-		uncollapsedSpans                       []string
-		rootServiceName, rootServiceEntryPoint string
-	)
-	if selectAllSpans {
-		selectedSpans, rootServiceName, rootServiceEntryPoint = tracedetail.GetAllSpans(traceRoots)
-	} else {
-		selectedSpans, uncollapsedSpans, rootServiceName, rootServiceEntryPoint = tracedetail.GetSelectedSpans(req.UncollapsedSpans, req.SelectedSpanID, traceRoots, spanIdToSpanNodeMap, req.IsSelectedSpanIDUnCollapsed)
-	}
-	r.logger.Info("getWaterfallSpansForTraceWithMetadata: processing post cache", "duration", time.Since(processingPostCache), "traceID", traceID)
-
-	// convert start timestamp to millis because right now frontend is expecting it in millis
-	for _, span := range selectedSpans {
-		span.TimeUnixNano = span.TimeUnixNano / 1000000
-	}
-
-	for serviceName, totalDuration := range serviceNameToTotalDurationMap {
-		serviceNameToTotalDurationMap[serviceName] = totalDuration / 1000000
-	}
-
-	response.Spans = selectedSpans
-	response.UncollapsedSpans = uncollapsedSpans // ignoring if all spans are returning
-	response.StartTimestampMillis = startTime / 1000000
-	response.EndTimestampMillis = endTime / 1000000
-	response.TotalSpansCount = totalSpans
-	response.TotalErrorSpansCount = totalErrorSpans
-	response.RootServiceName = rootServiceName
-	response.RootServiceEntryPoint = rootServiceEntryPoint
-	response.ServiceNameToTotalDurationMap = serviceNameToTotalDurationMap
-	response.HasMissingSpans = hasMissingSpans
-	response.HasMore = !selectAllSpans
-	return response, nil
-}
-
-func (r *ClickHouseReader) GetFlamegraphSpansForTraceCache(ctx context.Context, orgID valuer.UUID, traceID string) (*model.GetFlamegraphSpansForTraceCache, error) {
-	cachedTraceData := new(model.GetFlamegraphSpansForTraceCache)
-	err := r.cacheForTraceDetail.Get(ctx, orgID, strings.Join([]string{"getFlamegraphSpansForTrace", traceID}, "-"), cachedTraceData)
-	if err != nil {
-		r.logger.Debug("error in retrieving getFlamegraphSpansForTrace cache", errorsV2.Attr(err), "traceID", traceID)
-		return nil, err
-	}
-
-	if time.Since(time.UnixMilli(int64(cachedTraceData.EndTime))) < r.fluxIntervalForTraceDetail {
-		r.logger.Info("the trace end time falls under the flux interval, skipping getFlamegraphSpansForTrace cache", "traceID", traceID)
-		return nil, errors.Errorf("the trace end time falls under the flux interval, skipping getFlamegraphSpansForTrace cache, traceID: %s", traceID)
-	}
-
-	r.logger.Info("cache is successfully hit, applying cache for getFlamegraphSpansForTrace", "traceID", traceID)
-	return cachedTraceData, nil
-}
-
-func (r *ClickHouseReader) GetFlamegraphSpansForTrace(ctx context.Context, orgID valuer.UUID, traceID string, req *model.GetFlamegraphSpansForTraceParams) (*model.GetFlamegraphSpansForTraceResponse, error) {
-	trace := new(model.GetFlamegraphSpansForTraceResponse)
-	var startTime, endTime, durationNano uint64
-	var spanIdToSpanNodeMap = map[string]*model.FlamegraphSpan{}
-	// map[traceID][level]span
-	var selectedSpans = [][]*model.FlamegraphSpan{}
-	var traceRoots []*model.FlamegraphSpan
-
-	// get the trace tree from cache!
-	cachedTraceData, err := r.GetFlamegraphSpansForTraceCache(ctx, orgID, traceID)
-
-	if err == nil {
-		startTime = cachedTraceData.StartTime
-		endTime = cachedTraceData.EndTime
-		durationNano = cachedTraceData.DurationNano
-		selectedSpans = cachedTraceData.SelectedSpans
-		traceRoots = cachedTraceData.TraceRoots
-	}
-
-	if err != nil {
-		r.logger.Info("cache miss for getFlamegraphSpansForTrace", "traceID", traceID)
-
-		selectCols := "timestamp, duration_nano, span_id, trace_id, has_error, links as references, resource_string_service$$name, name, events"
-		if len(req.SelectFields) > 0 {
-			selectCols += ", attributes_string, attributes_number, attributes_bool, resources_string"
-		}
-		flamegraphQuery := fmt.Sprintf("SELECT %s FROM %s.%s WHERE trace_id=$1 and ts_bucket_start>=$2 and ts_bucket_start<=$3 ORDER BY timestamp ASC, name ASC", selectCols, r.TraceDB, r.traceTableName)
-
-		searchScanResponses, err := r.GetSpansForTrace(ctx, traceID, flamegraphQuery)
-		if err != nil {
-			return nil, err
-		}
-		if len(searchScanResponses) == 0 {
-			return trace, nil
-		}
-
-		for _, item := range searchScanResponses {
-			ref := []model.OtelSpanRef{}
-			err := json.Unmarshal([]byte(item.References), &ref)
-			if err != nil {
-				r.logger.Error("Error unmarshalling references", errorsV2.Attr(err))
-				return nil, errorsV2.Newf(errorsV2.TypeInternal, errorsV2.CodeInternal, "getFlamegraphSpansForTrace: error in unmarshalling references %s", err.Error())
-			}
-
-			events := make([]model.Event, 0)
-			for _, event := range item.Events {
-				var eventMap model.Event
-				err = json.Unmarshal([]byte(event), &eventMap)
-				if err != nil {
-					r.logger.Error("Error unmarshalling events", errorsV2.Attr(err))
-					return nil, errorsV2.Newf(errorsV2.TypeInternal, errorsV2.CodeInternal, "getFlamegraphSpansForTrace: error in unmarshalling events %s", err.Error())
-				}
-				events = append(events, eventMap)
-			}
-
-			jsonItem := model.FlamegraphSpan{
-				SpanID:       item.SpanID,
-				TraceID:      item.TraceID,
-				ServiceName:  item.ServiceName,
-				Name:         item.Name,
-				DurationNano: item.DurationNano,
-				HasError:     item.HasError,
-				References:   ref,
-				Events:       events,
-				Children:     make([]*model.FlamegraphSpan, 0),
-			}
-
-			if len(req.SelectFields) > 0 {
-				jsonItem.SetRequestedFields(item, req.SelectFields)
-			}
-
-			// metadata calculation
-			startTimeUnixNano := uint64(item.TimeUnixNano.UnixNano())
-			if startTime == 0 || startTimeUnixNano < startTime {
-				startTime = startTimeUnixNano
-			}
-			if endTime == 0 || (startTimeUnixNano+jsonItem.DurationNano) > endTime {
-				endTime = (startTimeUnixNano + jsonItem.DurationNano)
-			}
-			if durationNano == 0 || jsonItem.DurationNano > durationNano {
-				durationNano = jsonItem.DurationNano
-			}
-
-			jsonItem.TimeUnixNano = uint64(item.TimeUnixNano.UnixNano() / 1000000)
-			spanIdToSpanNodeMap[jsonItem.SpanID] = &jsonItem
-		}
-
-		// traverse through the map and append each node to the children array of the parent node
-		// and add missing spans
-		for _, spanNode := range spanIdToSpanNodeMap {
-			hasParentSpanNode := false
-			for _, reference := range spanNode.References {
-				if reference.RefType == "CHILD_OF" && reference.SpanId != "" {
-					hasParentSpanNode = true
-					if parentNode, exists := spanIdToSpanNodeMap[reference.SpanId]; exists {
-						parentNode.Children = append(parentNode.Children, spanNode)
-					} else {
-						// insert the missing spans
-						missingSpan := model.FlamegraphSpan{
-							SpanID:       reference.SpanId,
-							TraceID:      spanNode.TraceID,
-							ServiceName:  "",
-							Name:         "Missing Span",
-							TimeUnixNano: spanNode.TimeUnixNano,
-							DurationNano: spanNode.DurationNano,
-							HasError:     false,
-							Events:       make([]model.Event, 0),
-							Children:     make([]*model.FlamegraphSpan, 0),
-						}
-						missingSpan.Children = append(missingSpan.Children, spanNode)
-						spanIdToSpanNodeMap[missingSpan.SpanID] = &missingSpan
-						traceRoots = append(traceRoots, &missingSpan)
-					}
-				}
-			}
-			if !hasParentSpanNode && !tracedetail.ContainsFlamegraphSpan(traceRoots, spanNode) {
-				traceRoots = append(traceRoots, spanNode)
-			}
-		}
-
-		selectedSpans = tracedetail.GetAllSpansForFlamegraph(traceRoots, spanIdToSpanNodeMap)
-
-		// TODO: set the trace data (model.GetFlamegraphSpansForTraceCache) in cache here
-		// removed existing cache usage since it was not getting used due to this bug https://github.com/SigNoz/engineering-pod/issues/4648
-		// and was causing out of memory issues https://github.com/SigNoz/engineering-pod/issues/4638
-	}
-
-	processingPostCache := time.Now()
-	selectedSpansForRequest := selectedSpans
-	clientLimit := min(req.Limit, tracedetail.MaxLimitWithoutSampling)
-	totalSpanCount := tracedetail.GetTotalSpanCount(selectedSpans)
-	if totalSpanCount > uint64(clientLimit) {
-		// using trace start and end time if boundary ts are set to zero (or not set)
-		boundaryStart := max(timestamp.MilliToNano(req.BoundaryStartTS), startTime)
-		boundaryEnd := timestamp.MilliToNano(req.BoundaryEndTS)
-		if boundaryEnd == 0 {
-			boundaryEnd = endTime
-		}
-
-		selectedSpansForRequest = tracedetail.GetSelectedSpansForFlamegraphForRequest(req.SelectedSpanID, selectedSpans, boundaryStart, boundaryEnd)
-	}
-	r.logger.Debug("getFlamegraphSpansForTrace: processing post cache", "duration", time.Since(processingPostCache), "traceID", traceID, "totalSpans", totalSpanCount, "limit", clientLimit)
-
-	trace.Spans = selectedSpansForRequest
-	trace.StartTimestampMillis = startTime / 1000000
-	trace.EndTimestampMillis = endTime / 1000000
-	trace.HasMore = totalSpanCount > uint64(clientLimit)
-	return trace, nil
-}
 
 func (r *ClickHouseReader) GetDependencyGraph(ctx context.Context, queryParams *model.GetServicesParams) (*[]model.ServiceMapDependencyResponseItem, error) {
 

pkg/query-service/app/http_handler.go

@@ -534,8 +534,8 @@ func (aH *APIHandler) RegisterRoutes(router *mux.Router, am *middleware.AuthZ) {
 
 	router.HandleFunc("/api/v2/traces/fields", am.ViewAccess(aH.traceFields)).Methods(http.MethodGet)
 	router.HandleFunc("/api/v2/traces/fields", am.EditAccess(aH.updateTraceField)).Methods(http.MethodPost)
-	router.HandleFunc("/api/v2/traces/flamegraph/{traceId}", am.ViewAccess(aH.GetFlamegraphSpansForTrace)).Methods(http.MethodPost)
-	router.HandleFunc("/api/v2/traces/waterfall/{traceId}", am.ViewAccess(aH.GetWaterfallSpansForTraceWithMetadata)).Methods(http.MethodPost)
+
+
 
 	router.HandleFunc("/api/v1/version", am.OpenAccess(aH.getVersion)).Methods(http.MethodGet)
 	router.HandleFunc("/api/v1/features", am.ViewAccess(aH.getFeatureFlags)).Methods(http.MethodGet)
@@ -1446,73 +1446,6 @@ func (aH *APIHandler) SearchTraces(w http.ResponseWriter, r *http.Request) {
 
 }
 
-func (aH *APIHandler) GetWaterfallSpansForTraceWithMetadata(w http.ResponseWriter, r *http.Request) {
-	claims, err := authtypes.ClaimsFromContext(r.Context())
-	if err != nil {
-		render.Error(w, err)
-		return
-	}
-	orgID, err := valuer.NewUUID(claims.OrgID)
-	if err != nil {
-		render.Error(w, err)
-		return
-	}
-	traceID := mux.Vars(r)["traceId"]
-	if traceID == "" {
-		render.Error(w, errors.NewInvalidInputf(errors.CodeInvalidInput, "traceID is required"))
-		return
-	}
-
-	req := new(model.GetWaterfallSpansForTraceWithMetadataParams)
-	err = json.NewDecoder(r.Body).Decode(&req)
-	if err != nil {
-		RespondError(w, model.BadRequest(err), nil)
-		return
-	}
-
-	result, apiErr := aH.reader.GetWaterfallSpansForTraceWithMetadata(r.Context(), orgID, traceID, req)
-	if apiErr != nil {
-		render.Error(w, apiErr)
-		return
-	}
-
-	aH.WriteJSON(w, r, result)
-}
-
-func (aH *APIHandler) GetFlamegraphSpansForTrace(w http.ResponseWriter, r *http.Request) {
-	claims, err := authtypes.ClaimsFromContext(r.Context())
-	if err != nil {
-		render.Error(w, err)
-		return
-	}
-	orgID, err := valuer.NewUUID(claims.OrgID)
-	if err != nil {
-		render.Error(w, err)
-		return
-	}
-
-	traceID := mux.Vars(r)["traceId"]
-	if traceID == "" {
-		render.Error(w, errors.NewInvalidInputf(errors.CodeInvalidInput, "traceID is required"))
-		return
-	}
-
-	req := new(model.GetFlamegraphSpansForTraceParams)
-	err = json.NewDecoder(r.Body).Decode(&req)
-	if err != nil {
-		RespondError(w, model.BadRequest(err), nil)
-		return
-	}
-
-	result, apiErr := aH.reader.GetFlamegraphSpansForTrace(r.Context(), orgID, traceID, req)
-	if apiErr != nil {
-		render.Error(w, apiErr)
-		return
-	}
-
-	aH.WriteJSON(w, r, result)
-}
-
 func (aH *APIHandler) listErrors(w http.ResponseWriter, r *http.Request) {
 
 	query, err := parseListErrorsRequest(r)

pkg/query-service/app/traces/tracedetail/flamegraph.go

@@ -1,199 +0,0 @@
-package tracedetail
-
-import (
-	"sort"
-
-	"github.com/SigNoz/signoz/pkg/query-service/model"
-)
-
-var (
-	flamegraphSpanLevelLimit      float64 = 50
-	flamegraphSpanLimitPerLevel   int     = 100
-	flamegraphSamplingBucketCount int     = 50
-	flamegraphTopLatencySpanCount int     = 5
-
-	MaxLimitWithoutSampling uint = 120_000
-)
-
-func ContainsFlamegraphSpan(slice []*model.FlamegraphSpan, item *model.FlamegraphSpan) bool {
-	for _, v := range slice {
-		if v.SpanID == item.SpanID {
-			return true
-		}
-	}
-	return false
-}
-
-func BfsTraversalForTrace(span *model.FlamegraphSpan, level int64) map[int64][]*model.FlamegraphSpan {
-	bfs := map[int64][]*model.FlamegraphSpan{}
-	bfs[level] = []*model.FlamegraphSpan{span}
-
-	for _, child := range span.Children {
-		childBfsMap := BfsTraversalForTrace(child, level+1)
-		for _level, nodes := range childBfsMap {
-			bfs[_level] = append(bfs[_level], nodes...)
-		}
-	}
-	span.Level = level
-	span.Children = make([]*model.FlamegraphSpan, 0)
-
-	return bfs
-}
-
-func FindIndexForSelectedSpan(spans [][]*model.FlamegraphSpan, selectedSpanId string) int {
-	var selectedSpanLevel int = 0
-
-	for index, _spans := range spans {
-		for _, span := range _spans {
-			if span.SpanID == selectedSpanId {
-				selectedSpanLevel = index
-				break
-			}
-		}
-	}
-
-	return selectedSpanLevel
-}
-
-// GetAllSpansForFlamegraph groups all spans as per their level
-func GetAllSpansForFlamegraph(traceRoots []*model.FlamegraphSpan, spanIdToSpanNodeMap map[string]*model.FlamegraphSpan) [][]*model.FlamegraphSpan {
-
-	var traceIdLevelledFlamegraph = map[string]map[int64][]*model.FlamegraphSpan{}
-	selectedSpans := [][]*model.FlamegraphSpan{}
-
-	// sort the trace roots to add missing spans at the right order
-	sort.Slice(traceRoots, func(i, j int) bool {
-		if traceRoots[i].TimeUnixNano == traceRoots[j].TimeUnixNano {
-			return traceRoots[i].Name < traceRoots[j].Name
-		}
-		return traceRoots[i].TimeUnixNano < traceRoots[j].TimeUnixNano
-	})
-
-	for _, rootSpanID := range traceRoots {
-		if rootNode, exists := spanIdToSpanNodeMap[rootSpanID.SpanID]; exists {
-			bfsMapForTrace := BfsTraversalForTrace(rootNode, 0)
-			traceIdLevelledFlamegraph[rootSpanID.SpanID] = bfsMapForTrace
-		}
-	}
-
-	for _, trace := range traceRoots {
-		keys := make([]int64, 0, len(traceIdLevelledFlamegraph[trace.SpanID]))
-		for key := range traceIdLevelledFlamegraph[trace.SpanID] {
-			keys = append(keys, key)
-		}
-
-		sort.Slice(keys, func(i, j int) bool {
-			return keys[i] < keys[j]
-		})
-
-		for _, level := range keys {
-			if ok, exists := traceIdLevelledFlamegraph[trace.SpanID][level]; exists {
-				selectedSpans = append(selectedSpans, ok)
-			}
-		}
-	}
-
-	return selectedSpans
-}
-
-func getLatencyAndTimestampBucketedSpans(spans []*model.FlamegraphSpan, selectedSpanID string, isSelectedSpanIDPresent bool, startTime uint64, endTime uint64) []*model.FlamegraphSpan {
-	var sampledSpans []*model.FlamegraphSpan
-	// sort the spans by latency for latency filtering
-	sort.Slice(spans, func(i, j int) bool {
-		return spans[i].DurationNano > spans[j].DurationNano
-	})
-
-	// pick the top 5 latency spans
-	for idx := range flamegraphTopLatencySpanCount {
-		sampledSpans = append(sampledSpans, spans[idx])
-	}
-
-	// always add the selectedSpan
-	if isSelectedSpanIDPresent {
-		idx := -1
-		for _idx, span := range spans {
-			if span.SpanID == selectedSpanID {
-				idx = _idx
-			}
-		}
-		if idx != -1 {
-			sampledSpans = append(sampledSpans, spans[idx])
-		}
-	}
-
-	bucketSize := (endTime - startTime) / uint64(flamegraphSamplingBucketCount)
-	if bucketSize == 0 {
-		bucketSize = 1
-	}
-
-	bucketedSpans := make([][]*model.FlamegraphSpan, flamegraphSamplingBucketCount)
-
-	for _, span := range spans {
-		if span.TimeUnixNano >= startTime && span.TimeUnixNano <= endTime {
-			bucketIndex := int((span.TimeUnixNano - startTime) / bucketSize)
-			if bucketIndex >= 0 && bucketIndex < flamegraphSamplingBucketCount {
-				bucketedSpans[bucketIndex] = append(bucketedSpans[bucketIndex], span)
-			}
-		}
-	}
-
-	for i := range bucketedSpans {
-		if len(bucketedSpans[i]) > 2 {
-			// Keep only the first 2 spans
-			bucketedSpans[i] = bucketedSpans[i][:2]
-		}
-	}
-
-	// Flatten the bucketed spans into a single slice
-	for _, bucket := range bucketedSpans {
-		sampledSpans = append(sampledSpans, bucket...)
-	}
-
-	return sampledSpans
-}
-
-func GetSelectedSpansForFlamegraphForRequest(selectedSpanID string, selectedSpans [][]*model.FlamegraphSpan, startTime uint64, endTime uint64) [][]*model.FlamegraphSpan {
-	var selectedSpansForRequest = make([][]*model.FlamegraphSpan, 0)
-	var selectedIndex = 0
-
-	if selectedSpanID != "" {
-		selectedIndex = FindIndexForSelectedSpan(selectedSpans, selectedSpanID)
-	}
-
-	lowerLimit := selectedIndex - int(flamegraphSpanLevelLimit*0.4)
-	upperLimit := selectedIndex + int(flamegraphSpanLevelLimit*0.6)
-
-	if lowerLimit < 0 {
-		upperLimit = upperLimit - lowerLimit
-		lowerLimit = 0
-	}
-
-	if upperLimit > len(selectedSpans) {
-		lowerLimit = lowerLimit - (upperLimit - len(selectedSpans))
-		upperLimit = len(selectedSpans)
-	}
-
-	if lowerLimit < 0 {
-		lowerLimit = 0
-	}
-
-	for i := lowerLimit; i < upperLimit; i++ {
-		if len(selectedSpans[i]) > flamegraphSpanLimitPerLevel {
-			_spans := getLatencyAndTimestampBucketedSpans(selectedSpans[i], selectedSpanID, i == selectedIndex, startTime, endTime)
-			selectedSpansForRequest = append(selectedSpansForRequest, _spans)
-		} else {
-			selectedSpansForRequest = append(selectedSpansForRequest, selectedSpans[i])
-		}
-	}
-
-	return selectedSpansForRequest
-}
-
-func GetTotalSpanCount(spans [][]*model.FlamegraphSpan) uint64 {
-	levelCount := len(spans)
-	spanCount := uint64(0)
-	for i := range levelCount {
-		spanCount += uint64(len(spans[i]))
-	}
-	return spanCount
-}

pkg/query-service/app/traces/tracedetail/waterfall.go

@@ -1,287 +0,0 @@
-package tracedetail
-
-import (
-	"maps"
-	"slices"
-	"sort"
-
-	"github.com/SigNoz/signoz/pkg/query-service/model"
-)
-
-var (
-	SPAN_LIMIT_PER_REQUEST_FOR_WATERFALL float64 = 500
-
-	maxDepthForSelectedSpanChildren int  = 5
-	MaxLimitToSelectAllSpans        uint = 10_000
-)
-
-type Interval struct {
-	StartTime uint64
-	Duration  uint64
-	Service   string
-}
-
-func mergeIntervals(intervals []Interval) []Interval {
-	if len(intervals) == 0 {
-		return nil
-	}
-
-	var merged []Interval
-	current := intervals[0]
-
-	for i := 1; i < len(intervals); i++ {
-		next := intervals[i]
-		if current.StartTime+current.Duration >= next.StartTime {
-			endTime := max(current.StartTime+current.Duration, next.StartTime+next.Duration)
-			current.Duration = endTime - current.StartTime
-		} else {
-			merged = append(merged, current)
-			current = next
-		}
-	}
-	// Add the last interval
-	merged = append(merged, current)
-
-	return merged
-}
-
-func ContainsWaterfallSpan(slice []*model.Span, item *model.Span) bool {
-	for _, v := range slice {
-		if v.SpanID == item.SpanID {
-			return true
-		}
-	}
-	return false
-}
-
-func findIndexForSelectedSpanFromPreOrder(spans []*model.Span, selectedSpanId string) int {
-	var selectedSpanIndex = -1
-
-	for index, span := range spans {
-		if span.SpanID == selectedSpanId {
-			selectedSpanIndex = index
-			break
-		}
-	}
-
-	return selectedSpanIndex
-}
-
-func getPathFromRootToSelectedSpanId(node *model.Span, selectedSpanId string) (bool, []string) {
-	spansFromRootToNode := []string{}
-
-	spansFromRootToNode = append(spansFromRootToNode, node.SpanID)
-	if node.SpanID == selectedSpanId {
-		return true, spansFromRootToNode
-	}
-
-	isPresentInSubtreeForTheNode := false
-	for _, child := range node.Children {
-		isPresentInThisSubtree, _spansFromRootToNode := getPathFromRootToSelectedSpanId(child, selectedSpanId)
-		// if the interested node is present in the given subtree then add the span node to uncollapsed node list
-		if isPresentInThisSubtree {
-			isPresentInSubtreeForTheNode = true
-			spansFromRootToNode = append(spansFromRootToNode, _spansFromRootToNode...)
-			break
-		}
-	}
-	return isPresentInSubtreeForTheNode, spansFromRootToNode
-}
-
-// traverseOpts holds the traversal configuration that remains constant
-// throughout the recursion. Per-call state (level, isPartOfPreOrder, etc.)
-// is passed as direct arguments.
-type traverseOpts struct {
-	uncollapsedSpans          map[string]struct{}
-	selectedSpanID            string
-	isSelectedSpanUncollapsed bool
-	selectAll                 bool
-}
-
-func traverseTrace(
-	span *model.Span,
-	opts traverseOpts,
-	level uint64,
-	isPartOfPreOrder bool,
-	hasSibling bool,
-	autoExpandDepth int,
-) ([]*model.Span, []string) {
-
-	preOrderTraversal := []*model.Span{}
-	autoExpandedSpans := []string{}
-
-	// sort the children to maintain the order across requests
-	sort.Slice(span.Children, func(i, j int) bool {
-		if span.Children[i].TimeUnixNano == span.Children[j].TimeUnixNano {
-			return span.Children[i].Name < span.Children[j].Name
-		}
-		return span.Children[i].TimeUnixNano < span.Children[j].TimeUnixNano
-	})
-
-	span.SubTreeNodeCount = 0
-	nodeWithoutChildren := model.Span{
-		SpanID:           span.SpanID,
-		TraceID:          span.TraceID,
-		ServiceName:      span.ServiceName,
-		TimeUnixNano:     span.TimeUnixNano,
-		Name:             span.Name,
-		Kind:             int32(span.Kind),
-		DurationNano:     span.DurationNano,
-		HasError:         span.HasError,
-		StatusMessage:    span.StatusMessage,
-		StatusCodeString: span.StatusCodeString,
-		SpanKind:         span.SpanKind,
-		References:       span.References,
-		Events:           span.Events,
-		TagMap:           span.TagMap,
-		Children:         make([]*model.Span, 0),
-		HasChildren:      len(span.Children) > 0,
-		Level:            level,
-		HasSiblings:      hasSibling,
-		SubTreeNodeCount: 0,
-	}
-
-	if isPartOfPreOrder {
-		preOrderTraversal = append(preOrderTraversal, &nodeWithoutChildren)
-	}
-
-	remainingAutoExpandDepth := 0
-	if span.SpanID == opts.selectedSpanID && opts.isSelectedSpanUncollapsed {
-		remainingAutoExpandDepth = maxDepthForSelectedSpanChildren
-	} else if autoExpandDepth > 0 {
-		remainingAutoExpandDepth = autoExpandDepth - 1
-	}
-
-	_, isAlreadyUncollapsed := opts.uncollapsedSpans[span.SpanID]
-	for index, child := range span.Children {
-		// A child is included in the pre-order output if its parent is uncollapsed
-		// OR if the child falls within MAX_DEPTH_FOR_SELECTED_SPAN_CHILDREN levels
-		// below the selected span.
-		isChildWithinMaxDepth := remainingAutoExpandDepth > 0
-		childIsPartOfPreOrder := opts.selectAll || (isPartOfPreOrder && (isAlreadyUncollapsed || isChildWithinMaxDepth))
-
-		if isPartOfPreOrder && isChildWithinMaxDepth && !isAlreadyUncollapsed {
-			if !slices.Contains(autoExpandedSpans, span.SpanID) {
-				autoExpandedSpans = append(autoExpandedSpans, span.SpanID)
-			}
-		}
-
-		_childTraversal, _autoExpanded := traverseTrace(child, opts, level+1, childIsPartOfPreOrder, index != (len(span.Children)-1), remainingAutoExpandDepth)
-		preOrderTraversal = append(preOrderTraversal, _childTraversal...)
-		autoExpandedSpans = append(autoExpandedSpans, _autoExpanded...)
-		nodeWithoutChildren.SubTreeNodeCount += child.SubTreeNodeCount + 1
-		span.SubTreeNodeCount += child.SubTreeNodeCount + 1
-	}
-
-	nodeWithoutChildren.SubTreeNodeCount += 1
-	return preOrderTraversal, autoExpandedSpans
-
-}
-
-func CalculateServiceTime(serviceIntervals map[string][]Interval) map[string]uint64 {
-	totalTimes := make(map[string]uint64)
-
-	for service, serviceIntervals := range serviceIntervals {
-		sort.Slice(serviceIntervals, func(i, j int) bool {
-			return serviceIntervals[i].StartTime < serviceIntervals[j].StartTime
-		})
-		mergedIntervals := mergeIntervals(serviceIntervals)
-		totalTime := uint64(0)
-		for _, interval := range mergedIntervals {
-			totalTime += interval.Duration
-		}
-		totalTimes[service] = totalTime
-	}
-
-	return totalTimes
-}
-
-func GetSelectedSpans(uncollapsedSpans []string, selectedSpanID string, traceRoots []*model.Span, spanIdToSpanNodeMap map[string]*model.Span, isSelectedSpanIDUnCollapsed bool) ([]*model.Span, []string, string, string) {
-
-	var preOrderTraversal = make([]*model.Span, 0)
-	var rootServiceName, rootServiceEntryPoint string
-
-	// create a map of uncollapsed spans for quick lookup
-	uncollapsedSpanMap := make(map[string]struct{})
-	for _, spanID := range uncollapsedSpans {
-		uncollapsedSpanMap[spanID] = struct{}{}
-	}
-
-	selectedSpanIndex := -1
-	for _, rootSpanID := range traceRoots {
-		if rootNode, exists := spanIdToSpanNodeMap[rootSpanID.SpanID]; exists {
-			present, spansFromRootToNode := getPathFromRootToSelectedSpanId(rootNode, selectedSpanID)
-			if present {
-				for _, spanID := range spansFromRootToNode {
-					if selectedSpanID == spanID && !isSelectedSpanIDUnCollapsed {
-						continue
-					}
-					uncollapsedSpanMap[spanID] = struct{}{}
-				}
-			}
-
-			opts := traverseOpts{
-				uncollapsedSpans:          uncollapsedSpanMap,
-				selectedSpanID:            selectedSpanID,
-				isSelectedSpanUncollapsed: isSelectedSpanIDUnCollapsed,
-			}
-			_preOrderTraversal, _autoExpanded := traverseTrace(rootNode, opts, 0, true, false, 0)
-			// Merge auto-expanded spans into updatedUncollapsedSpans for returning in response
-			for _, spanID := range _autoExpanded {
-				uncollapsedSpanMap[spanID] = struct{}{}
-			}
-			_selectedSpanIndex := findIndexForSelectedSpanFromPreOrder(_preOrderTraversal, selectedSpanID)
-
-			if _selectedSpanIndex != -1 {
-				selectedSpanIndex = _selectedSpanIndex + len(preOrderTraversal)
-			}
-
-			preOrderTraversal = append(preOrderTraversal, _preOrderTraversal...)
-
-			if rootServiceName == "" {
-				rootServiceName = rootNode.ServiceName
-			}
-
-			if rootServiceEntryPoint == "" {
-				rootServiceEntryPoint = rootNode.Name
-			}
-		}
-	}
-
-	// if we couldn't find the selectedSpan in the trace then defaulting the selected index to 0
-	if selectedSpanIndex == -1 && selectedSpanID != "" {
-		selectedSpanIndex = 0
-	}
-
-	// get the 0.4*[span limit] before the interested span index
-	startIndex := selectedSpanIndex - int(SPAN_LIMIT_PER_REQUEST_FOR_WATERFALL*0.4)
-	// get the 0.6*[span limit] after the intrested span index
-	endIndex := selectedSpanIndex + int(SPAN_LIMIT_PER_REQUEST_FOR_WATERFALL*0.6)
-
-	// adjust the sliding window according to the available left and right spaces.
-	if startIndex < 0 {
-		endIndex = endIndex - startIndex
-		startIndex = 0
-	}
-	if endIndex > len(preOrderTraversal) {
-		startIndex = startIndex - (endIndex - len(preOrderTraversal))
-		endIndex = len(preOrderTraversal)
-	}
-	if startIndex < 0 {
-		startIndex = 0
-	}
-
-	return preOrderTraversal[startIndex:endIndex], slices.Collect(maps.Keys(uncollapsedSpanMap)), rootServiceName, rootServiceEntryPoint
-}
-
-func GetAllSpans(traceRoots []*model.Span) (spans []*model.Span, rootServiceName, rootEntryPoint string) {
-	if len(traceRoots) > 0 {
-		rootServiceName = traceRoots[0].ServiceName
-		rootEntryPoint = traceRoots[0].Name
-	}
-	for _, root := range traceRoots {
-		childSpans, _ := traverseTrace(root, traverseOpts{selectAll: true}, 0, true, false, 0)
-		spans = append(spans, childSpans...)
-	}
-	return
-}

pkg/query-service/app/traces/tracedetail/waterfall_test.go

@@ -1,446 +0,0 @@
-// Package tracedetail tests — waterfall
-//
-// # Background
-//
-// The waterfall view renders a trace as a scrollable list of spans in
-// pre-order (parent before children, siblings left-to-right). Because a trace
-// can have thousands of spans, only a window of ~500 is returned per request.
-// The window is centred on the selected span.
-//
-// # Key concepts
-//
-// uncollapsedSpans
-//
-//	The set of span IDs the user has manually expanded in the UI.
-//	Only the direct children of an uncollapsed span are included in the
-//	output; grandchildren stay hidden until their parent is also uncollapsed.
-//	When multiple spans are uncollapsed their children are all visible at once.
-//
-// selectedSpanID
-//
-//	The span currently focused — set when the user clicks a span in the
-//	waterfall or selects one from the flamegraph.  The output window is always
-//	centred on this span.  The path from the trace root down to the selected
-//	span is automatically uncollapsed so ancestors are visible even if they are
-//	not in uncollapsedSpans.
-//
-// isSelectedSpanIDUnCollapsed
-//
-//	Controls whether the selected span's own children are shown:
-//	  true  — user expanded the span (click-to-open in waterfall or flamegraph);
-//	          direct children of the selected span are included.
-//	  false — user selected without expanding;
-//	          the span is visible but its children remain hidden.
-//
-// traceRoots
-//
-//	Root spans of the trace — spans with no parent in the current dataset.
-//	Normally one, but multiple roots are common when upstream services are
-//	not instrumented or their spans were not sampled/exported.
-
-package tracedetail
-
-import (
-	"fmt"
-	"testing"
-
-	"github.com/SigNoz/signoz/pkg/query-service/model"
-	"github.com/stretchr/testify/assert"
-)
-
-// Pre-order traversal is preserved: parent before children, siblings left-to-right.
-func TestGetSelectedSpans_PreOrderTraversal(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("child1", "svc", mkSpan("grandchild", "svc")),
-		mkSpan("child2", "svc"),
-	)
-	spanMap := buildSpanMap(root)
-	spans, _, _, _ := GetSelectedSpans([]string{"root", "child1"}, "root", []*model.Span{root}, spanMap, false)
-
-	assert.Equal(t, []string{"root", "child1", "grandchild", "child2"}, spanIDs(spans))
-}
-
-// Multiple roots: both trees are flattened into a single pre-order list with
-// root1's subtree before root2's. Service/entry-point come from the first root.
-//
-//	root1 svc-a          ← selected
-//	  └─ child1
-//	root2 svc-b
-//	  └─ child2
-//
-// Expected output order: root1 → child1 → root2 → child2
-func TestGetSelectedSpans_MultipleRoots(t *testing.T) {
-	root1 := mkSpan("root1", "svc-a", mkSpan("child1", "svc-a"))
-	root2 := mkSpan("root2", "svc-b", mkSpan("child2", "svc-b"))
-	spanMap := buildSpanMap(root1, root2)
-
-	spans, _, svcName, entryPoint := GetSelectedSpans([]string{"root1", "root2"}, "root1", []*model.Span{root1, root2}, spanMap, false)
-
-	assert.Equal(t, []string{"root1", "child1", "root2", "child2"}, spanIDs(spans), "root1 subtree must precede root2 subtree")
-	assert.Equal(t, "svc-a", svcName, "metadata comes from first root")
-	assert.Equal(t, "root1-op", entryPoint, "metadata comes from first root")
-}
-
-// Multiple spans uncollapsed simultaneously: children of all uncollapsed spans
-// are visible at once.
-//
-//	root
-//	  ├─ childA (uncollapsed) → grandchildA ✓
-//	  └─ childB (uncollapsed) → grandchildB ✓
-func TestGetSelectedSpans_MultipleUncollapsed(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("childA", "svc", mkSpan("grandchildA", "svc")),
-		mkSpan("childB", "svc", mkSpan("grandchildB", "svc")),
-	)
-	spanMap := buildSpanMap(root)
-	spans, _, _, _ := GetSelectedSpans([]string{"root", "childA", "childB"}, "root", []*model.Span{root}, spanMap, false)
-
-	assert.Equal(t, []string{"root", "childA", "grandchildA", "childB", "grandchildB"}, spanIDs(spans))
-}
-
-// Collapsing a span with other uncollapsed spans
-//
-// root
-// ├─ childA  (previously expanded — in uncollapsedSpans)
-// │    ├─ grandchild1 ✓
-// │    │    └─ greatGrandchild ✗  (grandchild1 not in uncollapsedSpans)
-// │    └─ grandchild2 ✓
-// └─ childB                        ← selected (not expanded)
-func TestGetSelectedSpans_ManualUncollapse(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("childA", "svc",
-			mkSpan("grandchild1", "svc", mkSpan("greatGrandchild", "svc")),
-			mkSpan("grandchild2", "svc"),
-		),
-		mkSpan("childB", "svc"),
-	)
-	spanMap := buildSpanMap(root)
-	// childA was expanded in a previous interaction; childB is now selected without expanding
-	spans, _, _, _ := GetSelectedSpans([]string{"childA"}, "childB", []*model.Span{root}, spanMap, false)
-
-	// path to childB auto-uncollpases root → childA and childB appear; childA is in
-	// uncollapsedSpans so its children appear; greatGrandchild stays hidden.
-	assert.Equal(t, []string{"root", "childA", "grandchild1", "grandchild2", "childB"}, spanIDs(spans))
-}
-
-// A collapsed span hides all children.
-func TestGetSelectedSpans_CollapsedSpan(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("child1", "svc"),
-		mkSpan("child2", "svc"),
-	)
-	spanMap := buildSpanMap(root)
-	spans, _, _, _ := GetSelectedSpans([]string{}, "root", []*model.Span{root}, spanMap, false)
-
-	assert.Equal(t, []string{"root"}, spanIDs(spans))
-}
-
-// Selecting a span auto-uncollpases the path from root to that span so it is visible.
-//
-//	root → parent → selected
-func TestGetSelectedSpans_PathToSelectedIsUncollapsed(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("parent", "svc",
-			mkSpan("selected", "svc"),
-		),
-	)
-	spanMap := buildSpanMap(root)
-	// no manually uncollapsed spans — path should still be opened
-	spans, _, _, _ := GetSelectedSpans([]string{}, "selected", []*model.Span{root}, spanMap, false)
-
-	assert.Equal(t, []string{"root", "parent", "selected"}, spanIDs(spans))
-}
-
-// The path-to-selected spans are returned in updatedUncollapsedSpans.
-func TestGetSelectedSpans_PathReturnedInUncollapsed(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("parent", "svc",
-			mkSpan("selected", "svc"),
-		),
-	)
-	spanMap := buildSpanMap(root)
-	spans, uncollapsed, _, _ := GetSelectedSpans([]string{}, "selected", []*model.Span{root}, spanMap, false)
-
-	assert.ElementsMatch(t, []string{"root", "parent"}, uncollapsed)
-	assert.Equal(t, []string{"root", "parent", "selected"}, spanIDs(spans))
-}
-
-// Siblings of ancestors are rendered as collapsed nodes but their subtrees
-// must NOT be expanded.
-//
-//	root
-//	  ├─ unrelated → unrelated-child (✗)
-//	  └─ parent → selected
-func TestGetSelectedSpans_SiblingsNotExpanded(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("unrelated", "svc", mkSpan("unrelated-child", "svc")),
-		mkSpan("parent", "svc",
-			mkSpan("selected", "svc"),
-		),
-	)
-	spanMap := buildSpanMap(root)
-	spans, uncollapsed, _, _ := GetSelectedSpans([]string{}, "selected", []*model.Span{root}, spanMap, false)
-
-	// children of root sort alphabetically: parent < unrelated; unrelated-child stays hidden
-	assert.Equal(t, []string{"root", "parent", "selected", "unrelated"}, spanIDs(spans))
-	// only the path nodes are tracked as uncollapsed — unrelated is not
-	assert.ElementsMatch(t, []string{"root", "parent"}, uncollapsed)
-}
-
-// An unknown selectedSpanID must not panic; returns a window from index 0.
-func TestGetSelectedSpans_UnknownSelectedSpan(t *testing.T) {
-	root := mkSpan("root", "svc", mkSpan("child", "svc"))
-	spanMap := buildSpanMap(root)
-	spans, _, _, _ := GetSelectedSpans([]string{}, "nonexistent", []*model.Span{root}, spanMap, false)
-	assert.Equal(t, []string{"root"}, spanIDs(spans))
-}
-
-// Test to check if Level, HasChildren, HasSiblings, and SubTreeNodeCount are populated correctly.
-//
-//	root          level=0, hasChildren=true,  hasSiblings=false, subTree=4
-//	  child1      level=1, hasChildren=true,  hasSiblings=true,  subTree=2
-//	    grandchild level=2, hasChildren=false, hasSiblings=false, subTree=1
-//	  child2      level=1, hasChildren=false, hasSiblings=false, subTree=1
-func TestGetSelectedSpans_SpanMetadata(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("child1", "svc", mkSpan("grandchild", "svc")),
-		mkSpan("child2", "svc"),
-	)
-	spanMap := buildSpanMap(root)
-	spans, _, _, _ := GetSelectedSpans([]string{"root", "child1"}, "root", []*model.Span{root}, spanMap, false)
-
-	byID := map[string]*model.Span{}
-	for _, s := range spans {
-		byID[s.SpanID] = s
-	}
-
-	assert.Equal(t, uint64(0), byID["root"].Level)
-	assert.Equal(t, uint64(1), byID["child1"].Level)
-	assert.Equal(t, uint64(1), byID["child2"].Level)
-	assert.Equal(t, uint64(2), byID["grandchild"].Level)
-
-	assert.True(t, byID["root"].HasChildren)
-	assert.True(t, byID["child1"].HasChildren)
-	assert.False(t, byID["child2"].HasChildren)
-	assert.False(t, byID["grandchild"].HasChildren)
-
-	assert.False(t, byID["root"].HasSiblings, "root has no siblings")
-	assert.True(t, byID["child1"].HasSiblings, "child1 has sibling child2")
-	assert.False(t, byID["child2"].HasSiblings, "child2 is the last child")
-	assert.False(t, byID["grandchild"].HasSiblings, "grandchild has no siblings")
-
-	assert.Equal(t, uint64(4), byID["root"].SubTreeNodeCount)
-	assert.Equal(t, uint64(2), byID["child1"].SubTreeNodeCount)
-	assert.Equal(t, uint64(1), byID["grandchild"].SubTreeNodeCount)
-	assert.Equal(t, uint64(1), byID["child2"].SubTreeNodeCount)
-}
-
-// If the selected span is already in uncollapsedSpans AND isSelectedSpanIDUnCollapsed=true,
-func TestGetSelectedSpans_DuplicateInUncollapsed(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("selected", "svc", mkSpan("child", "svc")),
-	)
-	spanMap := buildSpanMap(root)
-	_, uncollapsed, _, _ := GetSelectedSpans(
-		[]string{"selected"}, // already present
-		"selected",
-		[]*model.Span{root}, spanMap,
-		true,
-	)
-
-	count := 0
-	for _, id := range uncollapsed {
-		if id == "selected" {
-			count++
-		}
-	}
-	assert.Equal(t, 1, count, "should appear once")
-}
-
-// makeChain builds a linear trace: span0 → span1 → … → span(n-1).
-// All span IDs are "span0", "span1", … so the caller can reference them by index.
-func makeChain(n int) (*model.Span, map[string]*model.Span, []string) {
-	spans := make([]*model.Span, n)
-	for i := n - 1; i >= 0; i-- {
-		if i == n-1 {
-			spans[i] = mkSpan(fmt.Sprintf("span%d", i), "svc")
-		} else {
-			spans[i] = mkSpan(fmt.Sprintf("span%d", i), "svc", spans[i+1])
-		}
-	}
-	uncollapsed := make([]string, n)
-	for i := range spans {
-		uncollapsed[i] = fmt.Sprintf("span%d", i)
-	}
-	return spans[0], buildSpanMap(spans[0]), uncollapsed
-}
-
-// The selected span is centred: 200 spans before it, 300 after (0.4 / 0.6 split).
-func TestGetSelectedSpans_WindowCentredOnSelected(t *testing.T) {
-	root, spanMap, uncollapsed := makeChain(600)
-	spans, _, _, _ := GetSelectedSpans(uncollapsed, "span300", []*model.Span{root}, spanMap, false)
-
-	assert.Equal(t, 500, len(spans), "window should be 500 spans")
-	// window is [100, 600): span300 lands at position 200 (300 - 100)
-	assert.Equal(t, "span100", spans[0].SpanID, "window starts 200 before selected")
-	assert.Equal(t, "span300", spans[200].SpanID, "selected span at position 200 in window")
-	assert.Equal(t, "span599", spans[499].SpanID, "window ends 300 after selected")
-}
-
-// When the selected span is near the start, the window shifts right so no
-// negative index is used — the result is still 500 spans.
-func TestGetSelectedSpans_WindowShiftsAtStart(t *testing.T) {
-	root, spanMap, uncollapsed := makeChain(600)
-	spans, _, _, _ := GetSelectedSpans(uncollapsed, "span10", []*model.Span{root}, spanMap, false)
-
-	assert.Equal(t, 500, len(spans))
-	assert.Equal(t, "span0", spans[0].SpanID, "window clamped to start of trace")
-	assert.Equal(t, "span10", spans[10].SpanID, "selected span still in window")
-}
-
-// Auto-expanded span IDs from ALL branches are returned in
-// updatedUncollapsedSpans. Only internal nodes (spans with children) are
-// tracked — leaf spans are never added.
-//
-//	root (selected)
-//	  ├─ childA (internal ✓)
-//	  │    └─ grandchildA (internal ✓)
-//	  │         └─ leafA (leaf ✗)
-//	  └─ childB (internal ✓)
-//	       └─ grandchildB (internal ✓)
-//	            └─ leafB (leaf ✗)
-func TestGetSelectedSpans_AutoExpandedSpansReturnedInUncollapsed(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("childA", "svc",
-			mkSpan("grandchildA", "svc",
-				mkSpan("leafA", "svc"),
-			),
-		),
-		mkSpan("childB", "svc",
-			mkSpan("grandchildB", "svc",
-				mkSpan("leafB", "svc"),
-			),
-		),
-	)
-	spanMap := buildSpanMap(root)
-	_, uncollapsed, _, _ := GetSelectedSpans([]string{}, "root", []*model.Span{root}, spanMap, true)
-
-	// all internal nodes across both branches must be tracked
-	assert.Contains(t, uncollapsed, "root")
-	assert.Contains(t, uncollapsed, "childA", "internal node depth 1, branch A")
-	assert.Contains(t, uncollapsed, "childB", "internal node depth 1, branch B")
-	assert.Contains(t, uncollapsed, "grandchildA", "internal node depth 2, branch A")
-	assert.Contains(t, uncollapsed, "grandchildB", "internal node depth 2, branch B")
-	// leaves have no children to show — never added to uncollapsedSpans
-	assert.NotContains(t, uncollapsed, "leafA", "leaf spans are never added to uncollapsedSpans")
-	assert.NotContains(t, uncollapsed, "leafB", "leaf spans are never added to uncollapsedSpans")
-}
-
-// ─────────────────────────────────────────────────────────────────────────────
-// maxDepthForSelectedSpanChildren boundary tests
-// ─────────────────────────────────────────────────────────────────────────────
-
-// Depth is measured from the selected span, not the trace root.
-// Ancestors appear via the path-to-root logic, not the depth limit.
-// Each depth level has two children to confirm the limit is enforced on all
-// branches, not just the first.
-//
-//	root
-//	  └─ A                           ancestor ✓ (path-to-root)
-//	       └─ selected
-//	            ├─ d1a               depth 1 ✓
-//	            │    ├─ d2a          depth 2 ✓
-//	            │    │    ├─ d3a     depth 3 ✓
-//	            │    │    │    ├─ d4a   depth 4 ✓
-//	            │    │    │    │    ├─ d5a  depth 5 ✓
-//	            │    │    │    │    │    └─ d6a  depth 6 ✗
-//	            │    │    │    │    └─ d5b  depth 5 ✓
-//	            │    │    │    └─ d4b   depth 4 ✓
-//	            │    │    └─ d3b     depth 3 ✓
-//	            │    └─ d2b          depth 2 ✓
-//	            └─ d1b               depth 1 ✓
-func TestGetSelectedSpans_DepthCountedFromSelectedSpan(t *testing.T) {
-	selected := mkSpan("selected", "svc",
-		mkSpan("d1a", "svc",
-			mkSpan("d2a", "svc",
-				mkSpan("d3a", "svc",
-					mkSpan("d4a", "svc",
-						mkSpan("d5a", "svc",
-							mkSpan("d6a", "svc"), // depth 6 — excluded
-						),
-						mkSpan("d5b", "svc"), // depth 5 — included
-					),
-					mkSpan("d4b", "svc"), // depth 4 — included
-				),
-				mkSpan("d3b", "svc"), // depth 3 — included
-			),
-			mkSpan("d2b", "svc"), // depth 2 — included
-		),
-		mkSpan("d1b", "svc"), // depth 1 — included
-	)
-	root := mkSpan("root", "svc", mkSpan("A", "svc", selected))
-
-	spanMap := buildSpanMap(root)
-	spans, _, _, _ := GetSelectedSpans([]string{}, "selected", []*model.Span{root}, spanMap, true)
-	ids := spanIDs(spans)
-
-	assert.Contains(t, ids, "root", "ancestor shown via path-to-root")
-	assert.Contains(t, ids, "A", "ancestor shown via path-to-root")
-	for _, id := range []string{"d1a", "d1b", "d2a", "d2b", "d3a", "d3b", "d4a", "d4b", "d5a", "d5b"} {
-		assert.Contains(t, ids, id, "depth ≤ 5 — must be included")
-	}
-	assert.NotContains(t, ids, "d6a", "depth 6 > limit — excluded")
-}
-
-func TestGetAllSpans(t *testing.T) {
-	root := mkSpan("root", "svc",
-		mkSpan("childA", "svc",
-			mkSpan("grandchildA", "svc",
-				mkSpan("leafA", "svc2"),
-			),
-		),
-		mkSpan("childB", "svc3",
-			mkSpan("grandchildB", "svc",
-				mkSpan("leafB", "svc2"),
-			),
-		),
-	)
-	spans, rootServiceName, rootEntryPoint := GetAllSpans([]*model.Span{root})
-	assert.ElementsMatch(t, spanIDs(spans), []string{"root", "childA", "grandchildA", "leafA", "childB", "grandchildB", "leafB"})
-	assert.Equal(t, rootServiceName, "svc")
-	assert.Equal(t, rootEntryPoint, "root-op")
-}
-
-func mkSpan(id, service string, children ...*model.Span) *model.Span {
-	return &model.Span{
-		SpanID:      id,
-		ServiceName: service,
-		Name:        id + "-op",
-		Children:    children,
-	}
-}
-
-// spanIDs returns SpanIDs in order.
-func spanIDs(spans []*model.Span) []string {
-	ids := make([]string, len(spans))
-	for i, s := range spans {
-		ids[i] = s.SpanID
-	}
-	return ids
-}
-
-// buildSpanMap indexes every span in a set of trees by SpanID.
-func buildSpanMap(roots ...*model.Span) map[string]*model.Span {
-	m := map[string]*model.Span{}
-	var walk func(*model.Span)
-	walk = func(s *model.Span) {
-		m[s.SpanID] = s
-		for _, c := range s.Children {
-			walk(c)
-		}
-	}
-	for _, r := range roots {
-		walk(r)
-	}
-	return m
-}

pkg/query-service/interfaces/interface.go

@@ -43,9 +43,6 @@ type Reader interface {
 
 	// Search Interfaces
 	SearchTraces(ctx context.Context, params *model.SearchTracesParams) (*[]model.SearchSpansResult, error)
-	GetWaterfallSpansForTraceWithMetadata(ctx context.Context, orgID valuer.UUID, traceID string, req *model.GetWaterfallSpansForTraceWithMetadataParams) (*model.GetWaterfallSpansForTraceWithMetadataResponse, error)
-	GetFlamegraphSpansForTrace(ctx context.Context, orgID valuer.UUID, traceID string, req *model.GetFlamegraphSpansForTraceParams) (*model.GetFlamegraphSpansForTraceResponse, error)
-
 	// Setter Interfaces
 	SetTTL(ctx context.Context, orgID string, ttlParams *retentiontypes.TTLParams) (*retentiontypes.SetTTLResponseItem, *model.ApiError)
 	SetTTLV2(ctx context.Context, orgID string, params *retentiontypes.CustomRetentionTTLParams) (*retentiontypes.CustomRetentionTTLResponse, error)

pkg/query-service/model/cacheable.go

@@ -1,89 +0,0 @@
-package model
-
-import (
-	"encoding/json"
-	"maps"
-
-	"github.com/SigNoz/signoz/pkg/types/cachetypes"
-)
-
-type GetWaterfallSpansForTraceWithMetadataCache struct {
-	StartTime                     uint64            `json:"startTime"`
-	EndTime                       uint64            `json:"endTime"`
-	DurationNano                  uint64            `json:"durationNano"`
-	TotalSpans                    uint64            `json:"totalSpans"`
-	TotalErrorSpans               uint64            `json:"totalErrorSpans"`
-	ServiceNameToTotalDurationMap map[string]uint64 `json:"serviceNameToTotalDurationMap"`
-	SpanIdToSpanNodeMap           map[string]*Span  `json:"spanIdToSpanNodeMap"`
-	TraceRoots                    []*Span           `json:"traceRoots"`
-	HasMissingSpans               bool              `json:"hasMissingSpans"`
-}
-
-func (c *GetWaterfallSpansForTraceWithMetadataCache) Clone() cachetypes.Cacheable {
-	copyOfServiceNameToTotalDurationMap := make(map[string]uint64)
-	maps.Copy(copyOfServiceNameToTotalDurationMap, c.ServiceNameToTotalDurationMap)
-
-	copyOfSpanIdToSpanNodeMap := make(map[string]*Span)
-	maps.Copy(copyOfSpanIdToSpanNodeMap, c.SpanIdToSpanNodeMap)
-
-	copyOfTraceRoots := make([]*Span, len(c.TraceRoots))
-	copy(copyOfTraceRoots, c.TraceRoots)
-	return &GetWaterfallSpansForTraceWithMetadataCache{
-		StartTime:                     c.StartTime,
-		EndTime:                       c.EndTime,
-		DurationNano:                  c.DurationNano,
-		TotalSpans:                    c.TotalSpans,
-		TotalErrorSpans:               c.TotalErrorSpans,
-		ServiceNameToTotalDurationMap: copyOfServiceNameToTotalDurationMap,
-		SpanIdToSpanNodeMap:           copyOfSpanIdToSpanNodeMap,
-		TraceRoots:                    copyOfTraceRoots,
-		HasMissingSpans:               c.HasMissingSpans,
-	}
-}
-
-func (c *GetWaterfallSpansForTraceWithMetadataCache) Cost() int64 {
-	const perSpanBytes = 256
-	return int64(c.TotalSpans) * perSpanBytes
-}
-
-func (c *GetWaterfallSpansForTraceWithMetadataCache) MarshalBinary() (data []byte, err error) {
-	return json.Marshal(c)
-}
-func (c *GetWaterfallSpansForTraceWithMetadataCache) UnmarshalBinary(data []byte) error {
-	return json.Unmarshal(data, c)
-}
-
-type GetFlamegraphSpansForTraceCache struct {
-	StartTime     uint64              `json:"startTime"`
-	EndTime       uint64              `json:"endTime"`
-	DurationNano  uint64              `json:"durationNano"`
-	SelectedSpans [][]*FlamegraphSpan `json:"selectedSpans"`
-	TraceRoots    []*FlamegraphSpan   `json:"traceRoots"`
-}
-
-func (c *GetFlamegraphSpansForTraceCache) Clone() cachetypes.Cacheable {
-	return &GetFlamegraphSpansForTraceCache{
-		StartTime:     c.StartTime,
-		EndTime:       c.EndTime,
-		DurationNano:  c.DurationNano,
-		SelectedSpans: c.SelectedSpans,
-		TraceRoots:    c.TraceRoots,
-	}
-}
-
-func (c *GetFlamegraphSpansForTraceCache) Cost() int64 {
-	const perSpanBytes = 128
-	var spans int64
-	for _, row := range c.SelectedSpans {
-		spans += int64(len(row))
-	}
-	spans += int64(len(c.TraceRoots))
-	return spans * perSpanBytes
-}
-
-func (c *GetFlamegraphSpansForTraceCache) MarshalBinary() (data []byte, err error) {
-	return json.Marshal(c)
-}
-func (c *GetFlamegraphSpansForTraceCache) UnmarshalBinary(data []byte) error {
-	return json.Unmarshal(data, c)
-}

pkg/query-service/model/queryParams.go

@@ -2,8 +2,6 @@ package model
 
 import (
 	"time"
-
-	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
 )
 
 type InstantQueryMetricsParams struct {
@@ -331,21 +329,6 @@ type SearchTracesParams struct {
 	MaxSpansInTrace  int    `json:"maxSpansInTrace"`
 }
 
-type GetWaterfallSpansForTraceWithMetadataParams struct {
-	SelectedSpanID              string   `json:"selectedSpanId"`
-	IsSelectedSpanIDUnCollapsed bool     `json:"isSelectedSpanIDUnCollapsed"`
-	UncollapsedSpans            []string `json:"uncollapsedSpans"`
-	Limit                       uint     `json:"limit"`
-}
-
-type GetFlamegraphSpansForTraceParams struct {
-	SelectedSpanID  string                             `json:"selectedSpanId"`
-	Limit           uint                               `json:"limit"`
-	BoundaryStartTS uint64                             `json:"boundaryStartTsMilli"`
-	BoundaryEndTS   uint64                             `json:"boundarEndTsMilli"`
-	SelectFields    []telemetrytypes.TelemetryFieldKey `json:"selectFields"`
-}
-
 type SpanFilterParams struct {
 	TraceID            []string `json:"traceID"`
 	Status             []string `json:"status"`

pkg/query-service/model/response.go

@@ -7,7 +7,6 @@ import (
 	"strconv"
 	"time"
 
-	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
 	"github.com/pkg/errors"
 	"github.com/prometheus/prometheus/promql/parser"
 	"github.com/prometheus/prometheus/util/stats"
@@ -293,69 +292,6 @@ type Span struct {
 	Level            uint64 `json:"level"`
 }
 
-type FlamegraphSpan struct {
-	TimeUnixNano uint64            `json:"timestamp"`
-	DurationNano uint64            `json:"durationNano"`
-	SpanID       string            `json:"spanId"`
-	TraceID      string            `json:"traceId"`
-	HasError     bool              `json:"hasError"`
-	ServiceName  string            `json:"serviceName"`
-	Name         string            `json:"name"`
-	Level        int64             `json:"level"`
-	Events       []Event           `json:"event"`
-	References   []OtelSpanRef     `json:"references,omitempty"`
-	Children     []*FlamegraphSpan `json:"children"`
-	Attributes   map[string]any    `json:"attributes,omitempty"`
-	Resource     map[string]string `json:"resource,omitempty"`
-}
-
-// SetRequestedFields extracts the requested attribute/resource fields from item into s.
-// This can eventually support missing fieldContext by checking both
-func (s *FlamegraphSpan) SetRequestedFields(item SpanItemV2, fields []telemetrytypes.TelemetryFieldKey) {
-	for _, field := range fields {
-		switch field.FieldContext {
-		case telemetrytypes.FieldContextResource:
-			if v, ok := item.Resources_string[field.Name]; ok && v != "" {
-				if s.Resource == nil {
-					s.Resource = make(map[string]string)
-				}
-				s.Resource[field.Name] = v
-			}
-		case telemetrytypes.FieldContextAttribute:
-			if v := item.AttributeValue(field.Name); v != nil {
-				if s.Attributes == nil {
-					s.Attributes = make(map[string]any)
-				}
-				s.Attributes[field.Name] = v
-			}
-		}
-	}
-}
-
-type GetWaterfallSpansForTraceWithMetadataResponse struct {
-	StartTimestampMillis          uint64            `json:"startTimestampMillis"`
-	EndTimestampMillis            uint64            `json:"endTimestampMillis"`
-	DurationNano                  uint64            `json:"durationNano"`
-	RootServiceName               string            `json:"rootServiceName"`
-	RootServiceEntryPoint         string            `json:"rootServiceEntryPoint"`
-	TotalSpansCount               uint64            `json:"totalSpansCount"`
-	TotalErrorSpansCount          uint64            `json:"totalErrorSpansCount"`
-	ServiceNameToTotalDurationMap map[string]uint64 `json:"serviceNameToTotalDurationMap"`
-	Spans                         []*Span           `json:"spans"`
-	HasMissingSpans               bool              `json:"hasMissingSpans"`
-	// this is needed for frontend and query service sync
-	UncollapsedSpans []string `json:"uncollapsedSpans"`
-	HasMore          bool     `json:"hasMore"`
-}
-
-type GetFlamegraphSpansForTraceResponse struct {
-	StartTimestampMillis uint64              `json:"startTimestampMillis"`
-	EndTimestampMillis   uint64              `json:"endTimestampMillis"`
-	DurationNano         uint64              `json:"durationNano"`
-	Spans                [][]*FlamegraphSpan `json:"spans"`
-	HasMore              bool                `json:"hasMore"`
-}
-
 type OtelSpanRef struct {
 	TraceId string `json:"traceId,omitempty"`
 	SpanId  string `json:"spanId,omitempty"`

pkg/types/cloudintegrationtypes/serviceid.go

@@ -27,6 +27,8 @@ var (
 	// Azure services.
 	AzureServiceStorageAccountsBlob = ServiceID{valuer.NewString("storageaccountsblob")}
 	AzureServiceCDNProfile          = ServiceID{valuer.NewString("cdnprofile")}
+	AzureServiceContainerApp        = ServiceID{valuer.NewString("containerapp")}
+	AzureServiceAKS                 = ServiceID{valuer.NewString("aks")}
 )
 
 func (ServiceID) Enum() []any {
@@ -46,6 +48,8 @@ func (ServiceID) Enum() []any {
 		AWSServiceSQS,
 		AzureServiceStorageAccountsBlob,
 		AzureServiceCDNProfile,
+		AzureServiceContainerApp,
+		AzureServiceAKS,
 	}
 }
 
@@ -69,6 +73,8 @@ var SupportedServices = map[CloudProviderType][]ServiceID{
 	CloudProviderTypeAzure: {
 		AzureServiceStorageAccountsBlob,
 		AzureServiceCDNProfile,
+		AzureServiceContainerApp,
+		AzureServiceAKS,
 	},
 }
 

pkg/types/spantypes/aggregation_test.go

@@ -1,251 +0,0 @@
-package spantypes
-
-import (
-	"testing"
-
-	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
-	"github.com/stretchr/testify/assert"
-)
-
-// mkASpan builds a WaterfallSpan with timing and field data for analytics tests.
-func mkASpan(id string, resource map[string]string, attributes map[string]any, startNs, durationNs uint64) *WaterfallSpan {
-	return &WaterfallSpan{
-		SpanID:       id,
-		Resource:     resource,
-		Attributes:   attributes,
-		TimeUnix:     startNs,
-		DurationNano: durationNs,
-		Children:     make([]*WaterfallSpan, 0),
-	}
-}
-
-func buildTraceFromSpans(spans ...*WaterfallSpan) *WaterfallTrace {
-	spanMap := make(map[string]*WaterfallSpan, len(spans))
-	var startTime, endTime uint64
-	initialized := false
-	for _, s := range spans {
-		spanMap[s.SpanID] = s
-		if !initialized || s.TimeUnix < startTime {
-			startTime = s.TimeUnix
-			initialized = true
-		}
-		if end := s.TimeUnix + s.DurationNano; end > endTime {
-			endTime = end
-		}
-	}
-	return NewWaterfallTrace(startTime, endTime, uint64(len(spanMap)), 0, spanMap, nil, false)
-}
-
-var (
-	fieldServiceName = telemetrytypes.TelemetryFieldKey{
-		Name:         "service.name",
-		FieldContext: telemetrytypes.FieldContextResource,
-	}
-	fieldHTTPMethod = telemetrytypes.TelemetryFieldKey{
-		Name:         "http.method",
-		FieldContext: telemetrytypes.FieldContextAttribute,
-	}
-	fieldCached = telemetrytypes.TelemetryFieldKey{
-		Name:         "db.cached",
-		FieldContext: telemetrytypes.FieldContextAttribute,
-	}
-)
-
-func TestGetSpanAggregation_SpanCount(t *testing.T) {
-	tests := []struct {
-		name  string
-		trace *WaterfallTrace
-		field telemetrytypes.TelemetryFieldKey
-		want  map[string]uint64
-	}{
-		{
-			name: "counts by resource field",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "frontend"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{"service.name": "frontend"}, nil, 10, 5),
-				mkASpan("s3", map[string]string{"service.name": "backend"}, nil, 20, 8),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"frontend": 2, "backend": 1},
-		},
-		{
-			name: "counts by string attribute field",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", nil, map[string]any{"http.method": "GET"}, 0, 10),
-				mkASpan("s2", nil, map[string]any{"http.method": "POST"}, 10, 5),
-				mkASpan("s3", nil, map[string]any{"http.method": "GET"}, 20, 8),
-			),
-			field: fieldHTTPMethod,
-			want:  map[string]uint64{"GET": 2, "POST": 1},
-		},
-		{
-			name: "counts by boolean attribute field",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", nil, map[string]any{"db.cached": true}, 0, 10),
-				mkASpan("s2", nil, map[string]any{"db.cached": false}, 10, 5),
-				mkASpan("s3", nil, map[string]any{"db.cached": true}, 20, 8),
-			),
-			field: fieldCached,
-			want:  map[string]uint64{"true": 2, "false": 1},
-		},
-		{
-			name: "spans missing the field are excluded",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "frontend"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{}, nil, 10, 5), // no service.name
-				mkASpan("s3", map[string]string{"service.name": "backend"}, nil, 20, 8),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"frontend": 1, "backend": 1},
-		},
-		{
-			// empty string is a valid field value — counted under the "" key, unlike a missing field
-			name: "span with empty service.name is counted under empty string key",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "frontend"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{"service.name": ""}, nil, 10, 5),
-				mkASpan("s3", map[string]string{"service.name": "backend"}, nil, 20, 8),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"frontend": 1, "backend": 1, "": 1},
-		},
-	}
-
-	for _, tc := range tests {
-		t.Run(tc.name, func(t *testing.T) {
-			result := tc.trace.GetSpanAggregation(SpanAggregationSpanCount, tc.field)
-			assert.Equal(t, tc.field, result.Field)
-			assert.Equal(t, SpanAggregationSpanCount, result.Aggregation)
-			assert.Equal(t, tc.want, result.Value)
-		})
-	}
-}
-
-func TestGetSpanAggregation_Duration(t *testing.T) {
-	tests := []struct {
-		name  string
-		trace *WaterfallTrace
-		field telemetrytypes.TelemetryFieldKey
-		want  map[string]uint64
-	}{
-		{
-			name: "non-overlapping spans — merged equals sum",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "frontend"}, nil, 0, 100),
-				mkASpan("s2", map[string]string{"service.name": "frontend"}, nil, 100, 50),
-				mkASpan("s3", map[string]string{"service.name": "backend"}, nil, 0, 80),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"frontend": 150, "backend": 80},
-		},
-		{
-			name: "non-overlapping attribute groups — merged equals sum",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", nil, map[string]any{"http.method": "GET"}, 0, 30),
-				mkASpan("s2", nil, map[string]any{"http.method": "GET"}, 50, 20),
-				mkASpan("s3", nil, map[string]any{"http.method": "POST"}, 0, 70),
-			),
-			field: fieldHTTPMethod,
-			want:  map[string]uint64{"GET": 50, "POST": 70},
-		},
-		{
-			name: "overlapping spans — non-overlapping interval merge",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "svc"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{"service.name": "svc"}, nil, 5, 10),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"svc": 15}, // [0,10] ∪ [5,15] = [0,15]
-		},
-	}
-
-	for _, tc := range tests {
-		t.Run(tc.name, func(t *testing.T) {
-			result := tc.trace.GetSpanAggregation(SpanAggregationDuration, tc.field)
-			assert.Equal(t, tc.field, result.Field)
-			assert.Equal(t, SpanAggregationDuration, result.Aggregation)
-			assert.Equal(t, tc.want, result.Value)
-		})
-	}
-}
-
-func TestGetSpanAggregation_ExecutionTimePercentage(t *testing.T) {
-	tests := []struct {
-		name  string
-		trace *WaterfallTrace
-		field telemetrytypes.TelemetryFieldKey
-		want  map[string]uint64
-	}{
-		{
-			// trace [0,30]: svc occupies [0,10]+[20,30]=20 → 20*100/30 = 66%
-			name: "non-overlapping spans",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "svc"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{"service.name": "svc"}, nil, 20, 10),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"svc": 66},
-		},
-		{
-			// trace [0,15]: svc [0,15]=15 → 100%
-			name: "partially overlapping spans",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "svc"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{"service.name": "svc"}, nil, 5, 10),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"svc": 100},
-		},
-		{
-			// trace [0,20]: outer absorbs inner → 100%
-			name: "fully contained span",
-			trace: buildTraceFromSpans(
-				mkASpan("outer", map[string]string{"service.name": "svc"}, nil, 0, 20),
-				mkASpan("inner", map[string]string{"service.name": "svc"}, nil, 5, 5),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"svc": 100},
-		},
-		{
-			// trace [0,30]: svc [0,15]+[20,30]=25 → 25*100/30 = 83%
-			name: "three spans with two merges",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "svc"}, nil, 0, 10),
-				mkASpan("s2", map[string]string{"service.name": "svc"}, nil, 5, 10),
-				mkASpan("s3", map[string]string{"service.name": "svc"}, nil, 20, 10),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"svc": 83},
-		},
-		{
-			// trace [0,28]: frontend [0,15]=15 → 53%, backend [0,5]+[20,28]=13 → 46%
-			name: "independent groups are computed separately",
-			trace: buildTraceFromSpans(
-				mkASpan("a1", map[string]string{"service.name": "frontend"}, nil, 0, 10),
-				mkASpan("a2", map[string]string{"service.name": "frontend"}, nil, 5, 10),
-				mkASpan("b1", map[string]string{"service.name": "backend"}, nil, 0, 5),
-				mkASpan("b2", map[string]string{"service.name": "backend"}, nil, 20, 8),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"frontend": 53, "backend": 46},
-		},
-		{
-			// trace [100,150]: svc [100,150]=50 → 100%
-			name: "single span",
-			trace: buildTraceFromSpans(
-				mkASpan("s1", map[string]string{"service.name": "svc"}, nil, 100, 50),
-			),
-			field: fieldServiceName,
-			want:  map[string]uint64{"svc": 100},
-		},
-	}
-
-	for _, tc := range tests {
-		t.Run(tc.name, func(t *testing.T) {
-			result := tc.trace.GetSpanAggregation(SpanAggregationExecutionTimePercentage, tc.field)
-			assert.Equal(t, tc.field, result.Field)
-			assert.Equal(t, SpanAggregationExecutionTimePercentage, result.Aggregation)
-			assert.Equal(t, tc.want, result.Value)
-		})
-	}
-}

pkg/types/spantypes/flamegraph_trace.go

@@ -40,13 +40,56 @@ func NewFlamegraphTraceFromStorable(spans []StorableSpan, selectFields []telemet
 	return t
 }
 
+// GetAllLevels return level wise spans using BFS on trace.
 func (t *FlamegraphTrace) GetAllLevels() [][]*FlamegraphSpan {
-	return nil
+	var result [][]*FlamegraphSpan
+	for _, root := range t.roots {
+		currentLevel := []*FlamegraphSpan{root}
+		for depth := int64(0); len(currentLevel) > 0; depth++ {
+			var nextLevel []*FlamegraphSpan
+			for _, node := range currentLevel {
+				node.Level = depth
+				nextLevel = append(nextLevel, node.Children...)
+				node.Children = nil // release tree reference
+			}
+			result = append(result, currentLevel)
+			currentLevel = nextLevel
+		}
+	}
+
+	return result
 }
 
 // GetSelectedLevels returns the window of levels around selectedSpanID with sampling applied to dense levels.
 func (t *FlamegraphTrace) GetSelectedLevels(selectedSpanID string, levelLimit, spansPerLevel, topLatencyCount, bucketCount int) []FlamegraphLevel {
-	return nil
+	allLevels := t.GetAllLevels()
+
+	selectedIndex := getLevelIndex(allLevels, selectedSpanID)
+
+	// 40% window above level with selected span and 60% below that
+	beforeSelectedLevel := int(float64(levelLimit) * 0.4)
+	startLevel := max(0, selectedIndex-beforeSelectedLevel)
+	endLevel := min(len(allLevels), startLevel+levelLimit)
+	startLevel = max(0, endLevel-levelLimit) // utilize the page size if endLevel is clamped
+
+	result := make([]FlamegraphLevel, 0, endLevel-startLevel)
+	for i := startLevel; i < endLevel; i++ {
+		spans := allLevels[i]
+		sampled := spans
+		if len(spans) > spansPerLevel {
+			sampled = t.sampleLevel(spans, selectedSpanID, i == selectedIndex, topLatencyCount, bucketCount)
+		}
+		if len(sampled) == 0 {
+			continue
+		}
+		spanIDs := make([]string, len(sampled))
+		for j, s := range sampled {
+			spanIDs[j] = s.SpanID
+		}
+		result = append(result, FlamegraphLevel{Level: spans[0].Level, SpanIDs: spanIDs})
+	}
+
+	return result
 }
 
 func (t *FlamegraphTrace) EnrichSelectedSpans(selectedSpans []FlamegraphLevel, fullSpans []StorableSpan, selectFields []telemetrytypes.TelemetryFieldKey) [][]*FlamegraphSpan {
@@ -101,6 +144,77 @@ func (t *FlamegraphTrace) buildSpanTree() {
 	})
 }
 
+func (t *FlamegraphTrace) sampleLevel(spans []*FlamegraphSpan, selectedSpanID string, isSelectedLevel bool, topLatencyCount, bucketCount int) []*FlamegraphSpan {
+	sorted := make([]*FlamegraphSpan, len(spans))
+	copy(sorted, spans)
+	sort.Slice(sorted, func(i, j int) bool {
+		return sorted[i].DurationNano > sorted[j].DurationNano
+	})
+
+	sampled := make(map[string]*FlamegraphSpan, topLatencyCount+1)
+
+	topK := min(topLatencyCount, len(sorted))
+	for _, span := range sorted[:topK] {
+		sampled[span.SpanID] = span
+	}
+
+	// include the selected span.
+	if isSelectedLevel {
+		for _, span := range sorted {
+			if span.SpanID == selectedSpanID {
+				sampled[span.SpanID] = span
+				break
+			}
+		}
+	}
+
+	for _, span := range t.bucketSampleSpans(sorted, bucketCount, sampled) {
+		sampled[span.SpanID] = span
+	}
+
+	result := make([]*FlamegraphSpan, 0, len(sampled))
+	for _, span := range sampled {
+		result = append(result, span)
+	}
+	return result
+}
+
+func (t *FlamegraphTrace) bucketSampleSpans(sorted []*FlamegraphSpan, bucketCount int, exclude map[string]*FlamegraphSpan) []*FlamegraphSpan {
+	bucketSize := (t.endTime - t.startTime) / uint64(bucketCount)
+	if bucketSize == 0 {
+		bucketSize = 1
+	}
+	buckets := make([][]*FlamegraphSpan, bucketCount)
+	for _, span := range sorted {
+		if _, ok := exclude[span.SpanID]; ok {
+			continue
+		}
+		if span.Timestamp < t.startTime || span.Timestamp > t.endTime {
+			continue
+		}
+		idx := min(int((span.Timestamp-t.startTime)/bucketSize), bucketCount-1)
+		if len(buckets[idx]) < 2 {
+			buckets[idx] = append(buckets[idx], span)
+		}
+	}
+	var result []*FlamegraphSpan
+	for _, bucket := range buckets {
+		result = append(result, bucket...)
+	}
+	return result
+}
+
+func getLevelIndex(levels [][]*FlamegraphSpan, spanID string) int {
+	for i, lvl := range levels {
+		for _, span := range lvl {
+			if span.SpanID == spanID {
+				return i
+			}
+		}
+	}
+	return 0
+}
+
 func flamegraphSpanIndex(spans []*FlamegraphSpan, spanID string) int {
 	for i, s := range spans {
 		if s.SpanID == spanID {

pkg/types/spantypes/flamegraph_trace_test.go

@@ -0,0 +1,270 @@
+package spantypes
+
+import (
+	"fmt"
+	"testing"
+	"time"
+
+	"github.com/stretchr/testify/assert"
+)
+
+// mkMinimal builds a MinimalSpan. timestamp and duration are in nanoseconds.
+func mkMinimal(id, parentID string, timestamp, duration uint64) MinimalSpan {
+	return MinimalSpan{
+		SpanID:       id,
+		ParentSpanID: parentID,
+		StartTime:    time.Unix(0, int64(timestamp)),
+		DurationNano: duration,
+	}
+}
+
+// levelIDs extracts span IDs level-by-level from GetAllLevels output.
+func levelIDs(levels [][]*FlamegraphSpan) [][]string {
+	out := make([][]string, len(levels))
+	for i, lvl := range levels {
+		ids := make([]string, len(lvl))
+		for j, s := range lvl {
+			ids[j] = s.SpanID
+		}
+		out[i] = ids
+	}
+	return out
+}
+
+// makeChainFG builds a linear trace of n spans: span0 → span1 → … → span(n-1).
+func makeChainFG(n int) *FlamegraphTrace {
+	spans := make([]MinimalSpan, n)
+	for i := range n {
+		parent := ""
+		if i > 0 {
+			parent = fmt.Sprintf("span%d", i-1)
+		}
+		spans[i] = mkMinimal(fmt.Sprintf("span%d", i), parent, uint64(i*100), 100)
+	}
+	return NewFlamegraphTraceFromMinimal(spans)
+}
+
+// makeBroadTrace builds a trace: root → N children (wide, one level deep).
+func makeBroadTrace(n int) *FlamegraphTrace {
+	spans := make([]MinimalSpan, n+1)
+	spans[0] = mkMinimal("root", "", 0, uint64(n*100))
+	for i := range n {
+		spans[i+1] = mkMinimal(fmt.Sprintf("child%d", i), "root", uint64(i*100), 100)
+	}
+	return NewFlamegraphTraceFromMinimal(spans)
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// buildSpanTree / GetAllLevels
+// ─────────────────────────────────────────────────────────────────────────────
+
+func TestGetAllLevels(t *testing.T) {
+	tests := []struct {
+		name  string
+		spans []MinimalSpan
+		check func(t *testing.T, levels [][]*FlamegraphSpan)
+	}{
+		{
+			// root → child → grandchild: three levels, one span each.
+			name: "linear_chain",
+			spans: []MinimalSpan{
+				mkMinimal("root", "", 100, 300),
+				mkMinimal("child", "root", 150, 200),
+				mkMinimal("grandchild", "child", 200, 100),
+			},
+			check: func(t *testing.T, levels [][]*FlamegraphSpan) {
+				assert.Equal(t, [][]string{{"root"}, {"child"}, {"grandchild"}}, levelIDs(levels))
+			},
+		},
+		{
+			// root → [A, B]: level 0 has root, level 1 has both children.
+			name: "two_siblings",
+			spans: []MinimalSpan{
+				mkMinimal("root", "", 100, 300),
+				mkMinimal("A", "root", 150, 100),
+				mkMinimal("B", "root", 200, 100),
+			},
+			check: func(t *testing.T, levels [][]*FlamegraphSpan) {
+				assert.Equal(t, []string{"root"}, levelIDs(levels)[0])
+				assert.ElementsMatch(t, []string{"A", "B"}, levelIDs(levels)[1])
+			},
+		},
+		{
+			// child references a non-existent parent → synthetic "Missing Span" root at level 0.
+			name: "missing_parent",
+			spans: []MinimalSpan{
+				mkMinimal("child", "ghost", 100, 100),
+			},
+			check: func(t *testing.T, levels [][]*FlamegraphSpan) {
+				assert.Len(t, levels, 2)
+				assert.Equal(t, "ghost", levels[0][0].SpanID)
+				assert.Equal(t, "Missing Span", levels[0][0].Name)
+				assert.Equal(t, "child", levels[1][0].SpanID)
+			},
+		},
+		{
+			// Children must be nil after BFS so the tree does not stay live in memory.
+			name: "children_nilled_after_bfs",
+			spans: []MinimalSpan{
+				mkMinimal("root", "", 100, 200),
+				mkMinimal("child", "root", 150, 100),
+			},
+			check: func(t *testing.T, levels [][]*FlamegraphSpan) {
+				for _, lvl := range levels {
+					for _, s := range lvl {
+						assert.Nil(t, s.Children)
+					}
+				}
+			},
+		},
+	}
+
+	for _, tc := range tests {
+		t.Run(tc.name, func(t *testing.T) {
+			tc.check(t, NewFlamegraphTraceFromMinimal(tc.spans).GetAllLevels())
+		})
+	}
+}
+
+// ─────────────────────────────────────────────────────────────────────────────
+// GetSelectedLevels
+// ─────────────────────────────────────────────────────────────────────────────
+
+func TestGetSelectedLevels(t *testing.T) {
+	tests := []struct {
+		name          string
+		buildTrace    func() *FlamegraphTrace
+		selectedSpan  string
+		levelLimit    int
+		spansPerLevel int
+		topK          int
+		bucketCount   int
+		check         func(t *testing.T, levels []FlamegraphLevel)
+	}{
+		{
+			// Middle: 40% above (20 levels) + 60% below (30 levels) = 50 total.
+			name:          "window_middle",
+			buildTrace:    func() *FlamegraphTrace { return makeChainFG(100) },
+			selectedSpan:  "span50",
+			levelLimit:    50,
+			spansPerLevel: 1000,
+			topK:          5,
+			bucketCount:   50,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				assert.Equal(t, 50, len(levels))
+				assert.Equal(t, "span30", levels[0].SpanIDs[0])
+			},
+		},
+		{
+			// Near start: clamp at 0, redistribute budget downward — still 50 levels.
+			name:          "window_near_start",
+			buildTrace:    func() *FlamegraphTrace { return makeChainFG(100) },
+			selectedSpan:  "span5",
+			levelLimit:    50,
+			spansPerLevel: 1000,
+			topK:          5,
+			bucketCount:   50,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				assert.Equal(t, 50, len(levels))
+				assert.Equal(t, "span0", levels[0].SpanIDs[0])
+			},
+		},
+		{
+			// Near end: clamp at total, redistribute budget upward — still 50 levels.
+			name:          "window_near_end",
+			buildTrace:    func() *FlamegraphTrace { return makeChainFG(100) },
+			selectedSpan:  "span95",
+			levelLimit:    50,
+			spansPerLevel: 1000,
+			topK:          5,
+			bucketCount:   50,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				assert.Equal(t, 50, len(levels))
+				assert.Equal(t, "span50", levels[0].SpanIDs[0])
+			},
+		},
+		{
+			// Unknown span ID falls back to level 0.
+			name:          "unknown_span_defaults_to_level_zero",
+			buildTrace:    func() *FlamegraphTrace { return makeChainFG(10) },
+			selectedSpan:  "nonexistent",
+			levelLimit:    5,
+			spansPerLevel: 1000,
+			topK:          5,
+			bucketCount:   50,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				assert.Equal(t, "span0", levels[0].SpanIDs[0])
+			},
+		},
+		{
+			// Dense levels are sampled down to approximately spansPerLevel.
+			name:          "sampling_respects_cap",
+			buildTrace:    func() *FlamegraphTrace { return makeBroadTrace(200) },
+			selectedSpan:  "root",
+			levelLimit:    10,
+			spansPerLevel: 10,
+			topK:          3,
+			bucketCount:   5,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				for _, lvl := range levels {
+					assert.LessOrEqual(t, len(lvl.SpanIDs), 10+3+5*2)
+				}
+			},
+		},
+		{
+			// Selected span always survives sampling even when not in topK.
+			name:          "selected_span_always_included",
+			buildTrace:    func() *FlamegraphTrace { return makeBroadTrace(200) },
+			selectedSpan:  "child99",
+			levelLimit:    10,
+			spansPerLevel: 5,
+			topK:          3,
+			bucketCount:   5,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				found := false
+				for _, lvl := range levels {
+					for _, id := range lvl.SpanIDs {
+						if id == "child99" {
+							found = true
+						}
+					}
+				}
+				assert.True(t, found, "selected span must survive sampling")
+			},
+		},
+		{
+			// Selected span is also the highest-latency span (lands in topK) — must not appear twice.
+			name: "no_duplicate_span_ids",
+			buildTrace: func() *FlamegraphTrace {
+				spans := make([]MinimalSpan, 201)
+				spans[0] = mkMinimal("root", "", 0, 10000)
+				for i := range 200 {
+					spans[i+1] = mkMinimal(fmt.Sprintf("child%d", i), "root", uint64(i*50), uint64(200-i)*10)
+				}
+				return NewFlamegraphTraceFromMinimal(spans)
+			},
+			selectedSpan:  "child0",
+			levelLimit:    10,
+			spansPerLevel: 5,
+			topK:          3,
+			bucketCount:   10,
+			check: func(t *testing.T, levels []FlamegraphLevel) {
+				for _, lvl := range levels {
+					seen := map[string]bool{}
+					for _, id := range lvl.SpanIDs {
+						assert.False(t, seen[id], "duplicate span ID %q at level %d", id, lvl.Level)
+						seen[id] = true
+					}
+				}
+			},
+		},
+	}
+
+	for _, tc := range tests {
+		t.Run(tc.name, func(t *testing.T) {
+			// fresh trace per subtest: GetAllLevels is destructive (nils Children)
+			levels := tc.buildTrace().GetSelectedLevels(tc.selectedSpan, tc.levelLimit, tc.spansPerLevel, tc.topK, tc.bucketCount)
+			tc.check(t, levels)
+		})
+	}
+}

pkg/types/spantypes/waterfall_span.go

@@ -21,28 +21,13 @@ const (
 // ErrTraceNotFound is returned when a trace ID has no matching spans in ClickHouse.
 var ErrTraceNotFound = errors.NewNotFoundf(errors.CodeNotFound, "trace not found")
 
-// PostableWaterfall is the request body for the v3 waterfall API.
+// PostableWaterfall is the request body for the waterfall API.
 type PostableWaterfall struct {
-	SelectedSpanID   string            `json:"selectedSpanId"`
-	UncollapsedSpans []string          `json:"uncollapsedSpans"`
-	Limit            uint              `json:"limit"`
-	Aggregations     []SpanAggregation `json:"aggregations"`
+	SelectedSpanID   string   `json:"selectedSpanId"`
+	UncollapsedSpans []string `json:"uncollapsedSpans"`
 }
 
 func (p *PostableWaterfall) Validate() error {
-	if len(p.Aggregations) > maxAggregationItems {
-		return ErrTooManyAggregationItems
-	}
-	for _, a := range p.Aggregations {
-		if !a.Aggregation.isValid() {
-			return errors.NewInvalidInputf(errors.CodeInvalidInput, "unknown aggregation type: %q", a.Aggregation)
-		}
-		fc := a.Field.FieldContext
-		if fc != telemetrytypes.FieldContextResource && fc != telemetrytypes.FieldContextAttribute {
-			return errors.NewInvalidInputf(errors.CodeInvalidInput, "aggregation field context must be %q or %q, got %q",
-				telemetrytypes.FieldContextResource, telemetrytypes.FieldContextAttribute, fc)
-		}
-	}
 	return nil
 }
 

pkg/types/spantypes/waterfall_trace.go

@@ -8,7 +8,6 @@ import (
 	"time"
 
 	"github.com/SigNoz/signoz/pkg/types/cachetypes"
-	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
 )
 
 type TraceSummary struct {
@@ -29,19 +28,18 @@ type WaterfallTrace struct {
 	HasMissingSpans     bool                      `json:"hasMissingSpans"`
 }
 
-// GettableWaterfallTrace is the response for the v3 waterfall API.
+// GettableWaterfallTrace is the response for the waterfall API.
 type GettableWaterfallTrace struct {
-	StartTimestampMillis  uint64                  `json:"startTimestampMillis"`
-	EndTimestampMillis    uint64                  `json:"endTimestampMillis"`
-	RootServiceName       string                  `json:"rootServiceName"`
-	RootServiceEntryPoint string                  `json:"rootServiceEntryPoint"`
-	TotalSpansCount       uint64                  `json:"totalSpansCount"`
-	TotalErrorSpansCount  uint64                  `json:"totalErrorSpansCount"`
-	Spans                 []*WaterfallSpan        `json:"spans"`
-	HasMissingSpans       bool                    `json:"hasMissingSpans"`
-	UncollapsedSpans      []string                `json:"uncollapsedSpans"`
-	HasMore               bool                    `json:"hasMore"`
-	Aggregations          []SpanAggregationResult `json:"aggregations"`
+	StartTimestampMillis  uint64           `json:"startTimestampMillis"`
+	EndTimestampMillis    uint64           `json:"endTimestampMillis"`
+	RootServiceName       string           `json:"rootServiceName"`
+	RootServiceEntryPoint string           `json:"rootServiceEntryPoint"`
+	TotalSpansCount       uint64           `json:"totalSpansCount"`
+	TotalErrorSpansCount  uint64           `json:"totalErrorSpansCount"`
+	Spans                 []*WaterfallSpan `json:"spans"`
+	HasMissingSpans       bool             `json:"hasMissingSpans"`
+	UncollapsedSpans      []string         `json:"uncollapsedSpans"`
+	HasMore               bool             `json:"hasMore"`
 }
 
 // NewWaterfallTrace constructs a WaterfallTrace from processed span data.
@@ -122,23 +120,6 @@ func NewWaterfallTraceFromSpans(nodes []*WaterfallSpan) *WaterfallTrace {
 	)
 }
 
-func (wt *WaterfallTrace) GetWaterfallSpans(uncollapsedSpanIDs []string, selectedSpanID string, limit uint, spanPageSize float64, maxDepthToAutoExpand int) ([]*WaterfallSpan, []string, bool) {
-	// Span selection decision: all spans or windowed
-	selectAllSpans := wt.TotalSpans <= uint64(limit)
-
-	var (
-		selectedSpans    []*WaterfallSpan
-		uncollapsedSpans []string
-	)
-
-	if selectAllSpans {
-		selectedSpans = wt.GetAllSpans()
-	} else {
-		selectedSpans, uncollapsedSpans = wt.GetSelectedSpans(uncollapsedSpanIDs, selectedSpanID, spanPageSize, maxDepthToAutoExpand)
-	}
-	return selectedSpans, uncollapsedSpans, selectAllSpans
-}
-
 // GetAllSpans returns all spans with pre order traversal.
 func (wt *WaterfallTrace) GetAllSpans() []*WaterfallSpan {
 	var preOrderedSpans []*WaterfallSpan
@@ -237,7 +218,6 @@ func NewGettableWaterfallTrace(
 	selectedSpans []*WaterfallSpan,
 	uncollapsedSpans []string,
 	selectAllSpans bool,
-	aggregations []SpanAggregationResult,
 ) *GettableWaterfallTrace {
 	var rootServiceName, rootServiceEntryPoint string
 	if len(traceData.TraceRoots) > 0 {
@@ -250,15 +230,6 @@ func NewGettableWaterfallTrace(
 		span.TimeUnix = span.TimeUnix / 1_000_000
 	}
 
-	// duration values are in nanoseconds; convert in-place to milliseconds.
-	for i := range aggregations {
-		if aggregations[i].Aggregation == SpanAggregationDuration {
-			for k, v := range aggregations[i].Value {
-				aggregations[i].Value[k] = v / 1_000_000
-			}
-		}
-	}
-
 	return &GettableWaterfallTrace{
 		Spans:                 selectedSpans,
 		UncollapsedSpans:      uncollapsedSpans,
@@ -270,7 +241,6 @@ func NewGettableWaterfallTrace(
 		RootServiceEntryPoint: rootServiceEntryPoint,
 		HasMissingSpans:       traceData.HasMissingSpans,
 		HasMore:               !selectAllSpans,
-		Aggregations:          aggregations,
 	}
 }
 
@@ -292,78 +262,3 @@ func windowAroundIndex(selectedIndex, total int, spanLimitPerRequest float64) (s
 	start = max(start, 0)
 	return
 }
-
-// mergeSpanIntervals computes non-overlapping execution time for a set of spans.
-func mergeSpanIntervals(spans []*WaterfallSpan) uint64 {
-	if len(spans) == 0 {
-		return 0
-	}
-	sort.Slice(spans, func(i, j int) bool {
-		return spans[i].TimeUnix < spans[j].TimeUnix
-	})
-
-	currentStart := spans[0].TimeUnix
-	currentEnd := currentStart + spans[0].DurationNano
-	total := uint64(0)
-
-	for _, span := range spans[1:] {
-		startNano := span.TimeUnix
-		endNano := startNano + span.DurationNano
-		if currentEnd >= startNano {
-			if endNano > currentEnd {
-				currentEnd = endNano
-			}
-		} else {
-			total += currentEnd - currentStart
-			currentStart = startNano
-			currentEnd = endNano
-		}
-	}
-	return total + (currentEnd - currentStart)
-}
-
-// GetSpanAggregation computes one aggregation result over all spans in the trace.
-// Duration values are returned in nanoseconds; callers convert to milliseconds as needed.
-func (wt *WaterfallTrace) GetSpanAggregation(aggregation SpanAggregationType, field telemetrytypes.TelemetryFieldKey) SpanAggregationResult {
-	result := SpanAggregationResult{
-		Field:       field,
-		Aggregation: aggregation,
-		Value:       make(map[string]uint64),
-	}
-
-	switch aggregation {
-	case SpanAggregationSpanCount:
-		for _, span := range wt.SpanIDToSpanNodeMap {
-			if key, ok := span.FieldValue(field); ok {
-				result.Value[key]++
-			}
-		}
-
-	case SpanAggregationDuration:
-		spansByField := make(map[string][]*WaterfallSpan)
-		for _, span := range wt.SpanIDToSpanNodeMap {
-			if key, ok := span.FieldValue(field); ok {
-				spansByField[key] = append(spansByField[key], span)
-			}
-		}
-		for key, spans := range spansByField {
-			result.Value[key] = mergeSpanIntervals(spans)
-		}
-
-	case SpanAggregationExecutionTimePercentage:
-		traceDuration := wt.EndTime - wt.StartTime
-		spansByField := make(map[string][]*WaterfallSpan)
-		for _, span := range wt.SpanIDToSpanNodeMap {
-			if key, ok := span.FieldValue(field); ok {
-				spansByField[key] = append(spansByField[key], span)
-			}
-		}
-		if traceDuration > 0 {
-			for key, spans := range spansByField {
-				result.Value[key] = mergeSpanIntervals(spans) * 100 / traceDuration
-			}
-		}
-	}
-
-	return result
-}

tests/integration/testdata/inframonitoring/namespaces_filter_dataset.jsonl

@@ -0,0 +1,144 @@
+{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 100000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 100000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 100000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1a-uid", "k8s.pod.name": "web-a-prod-acc-p1a", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1b-uid", "k8s.pod.name": "web-a-prod-acc-p1b", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "web-a-prod-acc-p1b-uid", "k8s.pod.name": "web-a-prod-acc-p1b", "k8s.namespace.name": "web-a-prod", "k8s.cluster.name": "cluster-a", "env": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
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+{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "api-b-dev-acc-p1b-uid", "k8s.pod.name": "api-b-dev-acc-p1b", "k8s.namespace.name": "api-b-dev", "k8s.cluster.name": "cluster-b", "env": "dev"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "api-b-dev-acc-p1b-uid", "k8s.pod.name": "api-b-dev-acc-p1b", "k8s.namespace.name": "api-b-dev", "k8s.cluster.name": "cluster-b", "env": "dev"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/namespaces_groupby.jsonl

@@ -0,0 +1,36 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-1-uid","k8s.pod.name":"pod-gb-ns-1","k8s.namespace.name":"gb-ns-1","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-2-uid","k8s.pod.name":"pod-gb-ns-2","k8s.namespace.name":"gb-ns-2","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-2-uid","k8s.pod.name":"pod-gb-ns-2","k8s.namespace.name":"gb-ns-2","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-2-uid","k8s.pod.name":"pod-gb-ns-2","k8s.namespace.name":"gb-ns-2","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-2-uid","k8s.pod.name":"pod-gb-ns-2","k8s.namespace.name":"gb-ns-2","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-2-uid","k8s.pod.name":"pod-gb-ns-2","k8s.namespace.name":"gb-ns-2","k8s.cluster.name":"gb-cluster-a"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-3-uid","k8s.pod.name":"pod-gb-ns-3","k8s.namespace.name":"gb-ns-3","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-ns-4-uid","k8s.pod.name":"pod-gb-ns-4","k8s.namespace.name":"gb-ns-4","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/namespaces_missing_metrics.jsonl

@@ -0,0 +1,3 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"miss-p-uid","k8s.pod.name":"miss-p","k8s.namespace.name":"miss-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"miss-p-uid","k8s.pod.name":"miss-p","k8s.namespace.name":"miss-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"miss-p-uid","k8s.pod.name":"miss-p","k8s.namespace.name":"miss-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/namespaces_orderby.jsonl

@@ -0,0 +1,45 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":500000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":500000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":500000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-1-uid","k8s.pod.name":"pod-order-ns-1","k8s.namespace.name":"order-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":400000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":400000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":400000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-2-uid","k8s.pod.name":"pod-order-ns-2","k8s.namespace.name":"order-ns-2","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":3.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":3.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":3.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":300000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":300000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":300000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-3-uid","k8s.pod.name":"pod-order-ns-3","k8s.namespace.name":"order-ns-3","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-order-ns-4-uid","k8s.pod.name":"pod-order-ns-4","k8s.namespace.name":"order-ns-4","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pod-order-ns-5-uid","k8s.pod.name":"pod-order-ns-5","k8s.namespace.name":"order-ns-5","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":5.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/namespaces_pagination.jsonl

@@ -0,0 +1,63 @@
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tests/integration/testdata/inframonitoring/namespaces_pod_phases.jsonl

@@ -0,0 +1,63 @@
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+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-fail-2-uid","k8s.pod.name":"pp-fail-2","k8s.namespace.name":"pp-ns","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/namespaces_value_accuracy.jsonl

@@ -0,0 +1,45 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p1a-uid","k8s.pod.name":"acc-p1a","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p1b-uid","k8s.pod.name":"acc-p1b","k8s.namespace.name":"acc-ns-1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2a-uid","k8s.pod.name":"acc-p2a","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2b-uid","k8s.pod.name":"acc-p2b","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.75,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":200000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2c-uid","k8s.pod.name":"acc-p2c","k8s.namespace.name":"acc-ns-2","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/namespaces_value_accuracy_expected.json

@@ -0,0 +1,16 @@
+{
+  "records": [
+    {
+      "namespaceName": "acc-ns-1",
+      "namespaceCPU": 1.0,
+      "namespaceMemory": 200000000.0,
+      "podCountsByPhase": {"pending": 0, "running": 2, "succeeded": 0, "failed": 0, "unknown": 0}
+    },
+    {
+      "namespaceName": "acc-ns-2",
+      "namespaceCPU": 2.25,
+      "namespaceMemory": 600000000.0,
+      "podCountsByPhase": {"pending": 0, "running": 3, "succeeded": 0, "failed": 0, "unknown": 0}
+    }
+  ]
+}

tests/integration/testdata/inframonitoring/nodes_conditions.jsonl

@@ -0,0 +1,33 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"ready-n","k8s.node.uid":"ready-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/nodes_conditions_grouped.jsonl

@@ -0,0 +1,54 @@
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-g-notready-1-uid","k8s.pod.name":"pod-g-notready-1","k8s.namespace.name":"ns-x","k8s.node.name":"g-notready-1","k8s.cluster.name":"cluster-mixed"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-g-notready-1-uid","k8s.pod.name":"pod-g-notready-1","k8s.namespace.name":"ns-x","k8s.node.name":"g-notready-1","k8s.cluster.name":"cluster-mixed"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-g-notready-1-uid","k8s.pod.name":"pod-g-notready-1","k8s.namespace.name":"ns-x","k8s.node.name":"g-notready-1","k8s.cluster.name":"cluster-mixed"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/nodes_conditions_transition.jsonl

@@ -0,0 +1,18 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"trans-n","k8s.node.uid":"trans-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/nodes_filter_dataset.jsonl

@@ -0,0 +1,144 @@
+{"metric_name": "k8s.node.cpu.usage", "labels": {"k8s.node.name": "web-a-us-1", "k8s.node.uid": "f-w-aus-1-uid", "k8s.cluster.name": "cluster-a", "zone": "us"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 1.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
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+{"metric_name": "k8s.node.allocatable_cpu", "labels": {"k8s.node.name": "web-a-eu-1", "k8s.node.uid": "f-w-aeu-1-uid", "k8s.cluster.name": "cluster-a", "zone": "eu"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 4.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
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+{"metric_name": "k8s.node.condition_ready", "labels": {"k8s.node.name": "web-a-eu-1", "k8s.node.uid": "f-w-aeu-1-uid", "k8s.cluster.name": "cluster-a", "zone": "eu"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 1, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
+{"metric_name": "k8s.node.condition_ready", "labels": {"k8s.node.name": "web-a-eu-1", "k8s.node.uid": "f-w-aeu-1-uid", "k8s.cluster.name": "cluster-a", "zone": "eu"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 1, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
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tests/integration/testdata/inframonitoring/nodes_groupby.jsonl

@@ -0,0 +1,72 @@
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+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:00:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:02:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:04:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"gb-b-eu","k8s.node.uid":"gb-beu-uid","k8s.cluster.name":"gb-cluster-b","zone":"eu"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-b-eu-uid","k8s.pod.name":"pod-gb-b-eu","k8s.namespace.name":"ns-x","k8s.node.name":"gb-b-eu","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-b-eu-uid","k8s.pod.name":"pod-gb-b-eu","k8s.namespace.name":"ns-x","k8s.node.name":"gb-b-eu","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pod-gb-b-eu-uid","k8s.pod.name":"pod-gb-b-eu","k8s.namespace.name":"ns-x","k8s.node.name":"gb-b-eu","k8s.cluster.name":"gb-cluster-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/nodes_missing_metrics.jsonl

@@ -0,0 +1,3 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"miss-n1","k8s.node.uid":"miss-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"miss-n1","k8s.node.uid":"miss-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"miss-n1","k8s.node.uid":"miss-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/nodes_no_pods.jsonl

@@ -0,0 +1,18 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"no-pod-n","k8s.node.uid":"no-pod-n-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"carrier-pod-uid","k8s.pod.name":"carrier-pod","k8s.namespace.name":"carrier-ns","k8s.node.name":"carrier-phantom-host","k8s.cluster.name":"carrier-cluster"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"carrier-pod-uid","k8s.pod.name":"carrier-pod","k8s.namespace.name":"carrier-ns","k8s.node.name":"carrier-phantom-host","k8s.cluster.name":"carrier-cluster"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"carrier-pod-uid","k8s.pod.name":"carrier-pod","k8s.namespace.name":"carrier-ns","k8s.node.name":"carrier-phantom-host","k8s.cluster.name":"carrier-cluster"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/nodes_orderby.jsonl

@@ -0,0 +1,78 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":20.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":20.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":20.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":50000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":50000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":50000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"order-n1","k8s.node.uid":"order-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":16.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":16.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":16.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":40000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":40000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":40000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"order-n2","k8s.node.uid":"order-n2-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n3","k8s.node.uid":"order-n3-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":3.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n3","k8s.node.uid":"order-n3-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":3.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"order-n3","k8s.node.uid":"order-n3-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":3.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n3","k8s.node.uid":"order-n3-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":12.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"order-n3","k8s.node.uid":"order-n3-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":12.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/nodes_pagination.jsonl

@@ -0,0 +1,108 @@
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+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"page-n7","k8s.node.uid":"page-n7-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"carrier-pod-uid","k8s.pod.name":"carrier-pod","k8s.namespace.name":"carrier-ns","k8s.node.name":"carrier-phantom-host","k8s.cluster.name":"carrier-cluster"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"carrier-pod-uid","k8s.pod.name":"carrier-pod","k8s.namespace.name":"carrier-ns","k8s.node.name":"carrier-phantom-host","k8s.cluster.name":"carrier-cluster"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"carrier-pod-uid","k8s.pod.name":"carrier-pod","k8s.namespace.name":"carrier-ns","k8s.node.name":"carrier-phantom-host","k8s.cluster.name":"carrier-cluster"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/nodes_pod_phases.jsonl

@@ -0,0 +1,30 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"pp-n1","k8s.node.uid":"pp-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-run-1-uid","k8s.pod.name":"pp-pod-run-1","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-run-2-uid","k8s.pod.name":"pp-pod-run-2","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-run-3-uid","k8s.pod.name":"pp-pod-run-3","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-fail-1-uid","k8s.pod.name":"pp-pod-fail-1","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-fail-1-uid","k8s.pod.name":"pp-pod-fail-1","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-fail-2-uid","k8s.pod.name":"pp-pod-fail-2","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"pp-pod-fail-2-uid","k8s.pod.name":"pp-pod-fail-2","k8s.namespace.name":"ns-x","k8s.node.name":"pp-n1","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/nodes_value_accuracy.jsonl

@@ -0,0 +1,36 @@
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_cpu","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":4.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":2000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":2000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":2000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:02:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.allocatable_memory","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:04:00+00:00","value":8000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"acc-n1","k8s.node.uid":"acc-n1-uid","k8s.cluster.name":"cluster-x"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.node.memory.working_set","labels":{"k8s.node.name":"acc-n2","k8s.node.uid":"acc-n2-uid","k8s.cluster.name":"cluster-y"},"timestamp":"2025-01-10T10:02:00+00:00","value":4000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/nodes_value_accuracy_expected.json

@@ -0,0 +1,24 @@
+{
+  "records": [
+    {
+      "nodeName": "acc-n1",
+      "nodeCPU": 1.0,
+      "nodeCPUAllocatable": 4.0,
+      "nodeMemory": 2000000000.0,
+      "nodeMemoryAllocatable": 8000000000.0,
+      "condition": "ready",
+      "nodeCountsByReadiness": {"ready": 1, "notReady": 0},
+      "podCountsByPhase": {"pending": 0, "running": 1, "succeeded": 0, "failed": 0, "unknown": 0}
+    },
+    {
+      "nodeName": "acc-n2",
+      "nodeCPU": 3.0,
+      "nodeCPUAllocatable": 16.0,
+      "nodeMemory": 4000000000.0,
+      "nodeMemoryAllocatable": 32000000000.0,
+      "condition": "ready",
+      "nodeCountsByReadiness": {"ready": 1, "notReady": 0},
+      "podCountsByPhase": {"pending": 0, "running": 1, "succeeded": 0, "failed": 0, "unknown": 0}
+    }
+  ]
+}

tests/integration/testdata/inframonitoring/pods_filter_dataset.jsonl

@@ -0,0 +1,168 @@
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tests/integration/testdata/inframonitoring/pods_groupby.jsonl

@@ -0,0 +1,84 @@
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+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_limit_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_limit_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_limit_utilization","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"g-p4-uid","k8s.pod.name":"g-p4","k8s.namespace.name":"gns-b","k8s.node.name":"node-b","k8s.deployment.name":"gdep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/pods_missing_metrics.jsonl

@@ -0,0 +1,3 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"miss-p1-uid","k8s.pod.name":"miss-p1","k8s.namespace.name":"ns-a","k8s.node.name":"node-a","k8s.deployment.name":"dep-1","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"2025-01-10T09:00:00+00:00"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"miss-p1-uid","k8s.pod.name":"miss-p1","k8s.namespace.name":"ns-a","k8s.node.name":"node-a","k8s.deployment.name":"dep-1","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"2025-01-10T09:00:00+00:00"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"miss-p1-uid","k8s.pod.name":"miss-p1","k8s.namespace.name":"ns-a","k8s.node.name":"node-a","k8s.deployment.name":"dep-1","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"2025-01-10T09:00:00+00:00"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/pods_orderby.jsonl

@@ -0,0 +1,105 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.9,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.9,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.9,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":1000000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"order-p1-uid","k8s.pod.name":"order-p1","k8s.namespace.name":"ns-order","k8s.node.name":"node-a","k8s.deployment.name":"order-dep","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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tests/integration/testdata/inframonitoring/pods_pagination.jsonl

@@ -0,0 +1,147 @@
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tests/integration/testdata/inframonitoring/pods_phases.jsonl

@@ -0,0 +1,105 @@
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tests/integration/testdata/inframonitoring/pods_phases_grouped.jsonl

@@ -0,0 +1,126 @@
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+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"g-pend-1-uid","k8s.pod.name":"g-pend-1","k8s.namespace.name":"ns-mixed","k8s.node.name":"node-b","k8s.deployment.name":"dep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"g-pend-1-uid","k8s.pod.name":"g-pend-1","k8s.namespace.name":"ns-mixed","k8s.node.name":"node-b","k8s.deployment.name":"dep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"g-pend-1-uid","k8s.pod.name":"g-pend-1","k8s.namespace.name":"ns-mixed","k8s.node.name":"node-b","k8s.deployment.name":"dep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"g-pend-1-uid","k8s.pod.name":"g-pend-1","k8s.namespace.name":"ns-mixed","k8s.node.name":"node-b","k8s.deployment.name":"dep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"g-pend-1-uid","k8s.pod.name":"g-pend-1","k8s.namespace.name":"ns-mixed","k8s.node.name":"node-b","k8s.deployment.name":"dep-y","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/pods_phases_transition.jsonl

@@ -0,0 +1,21 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_request_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.cpu_limit_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory.working_set","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":100000000.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_request_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_limit_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_limit_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.memory_limit_utilization","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":1,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"trans-p-uid","k8s.pod.name":"trans-p","k8s.namespace.name":"ns-x","k8s.node.name":"node-a","k8s.deployment.name":"phase-test","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/pods_value_accuracy.jsonl

@@ -0,0 +1,42 @@
+{"metric_name":"k8s.pod.cpu.usage","labels":{"k8s.pod.uid":"acc-p1-uid","k8s.pod.name":"acc-p1","k8s.namespace.name":"ns-a","k8s.node.name":"node-a","k8s.deployment.name":"dep-1","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
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+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2-uid","k8s.pod.name":"acc-p2","k8s.namespace.name":"ns-b","k8s.node.name":"node-b","k8s.deployment.name":"dep-2","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2-uid","k8s.pod.name":"acc-p2","k8s.namespace.name":"ns-b","k8s.node.name":"node-b","k8s.deployment.name":"dep-2","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-p2-uid","k8s.pod.name":"acc-p2","k8s.namespace.name":"ns-b","k8s.node.name":"node-b","k8s.deployment.name":"dep-2","k8s.cluster.name":"cluster-x","k8s.statefulset.name":"","k8s.daemonset.name":"","k8s.job.name":"","k8s.cronjob.name":"","k8s.pod.start_time":"__START_TIME__"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/pods_value_accuracy_expected.json

@@ -0,0 +1,26 @@
+{
+  "records": [
+    {
+      "podName": "acc-p1",
+      "podCPU": 0.5,
+      "podCPURequest": 0.25,
+      "podCPULimit": 0.5,
+      "podMemory": 524288000.0,
+      "podMemoryRequest": 0.5,
+      "podMemoryLimit": 0.25,
+      "podPhase": "running",
+      "podCountsByPhase": {"pending": 0, "running": 1, "succeeded": 0, "failed": 0, "unknown": 0}
+    },
+    {
+      "podName": "acc-p2",
+      "podCPU": 1.5,
+      "podCPURequest": 0.75,
+      "podCPULimit": 1.0,
+      "podMemory": 1073741824.0,
+      "podMemoryRequest": 0.75,
+      "podMemoryLimit": 0.5,
+      "podPhase": "running",
+      "podCountsByPhase": {"pending": 0, "running": 1, "succeeded": 0, "failed": 0, "unknown": 0}
+    }
+  ]
+}

tests/integration/tests/inframonitoring/02_pods.py

@@ -0,0 +1,760 @@
+"""Integration tests for v2 infra-monitoring pod endpoints."""
+
+import json
+from datetime import UTC, datetime, timedelta
+from http import HTTPStatus
+
+import pytest
+import requests
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.fs import get_testdata_file_path
+from fixtures.metrics import Metrics
+from fixtures.querier import compare_values
+from fixtures.time import parse_timestamp
+
+ENDPOINT = "/api/v2/infra_monitoring/pods"
+
+# Required metrics for the v2 pods endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/pods_constants.go:24-32).
+REQUIRED_METRICS = {
+    "k8s.pod.cpu.usage",
+    "k8s.pod.cpu_request_utilization",
+    "k8s.pod.cpu_limit_utilization",
+    "k8s.pod.memory.working_set",
+    "k8s.pod.memory_request_utilization",
+    "k8s.pod.memory_limit_utilization",
+    "k8s.pod.phase",
+}
+
+# Numeric values emitted by the k8s.pod.phase metric (OTel kubeletstatsreceiver).
+PHASE_NUM = {"pending": 1, "running": 2, "succeeded": 3, "failed": 4, "unknown": 5}
+
+# Placeholder in JSONL labels that gets substituted with a runtime ISO string.
+START_TIME_PLACEHOLDER = "__START_TIME__"
+
+
+def _load_pods_metrics(
+    file_relpath: str,
+    base_time: datetime,
+    start_time: datetime | None = None,
+) -> list[Metrics]:
+    """Load pod metrics JSONL with optional k8s.pod.start_time substitution.
+
+    Mirrors Metrics.load_from_file's base_time rebase logic but adds a hook
+    for the start_time label. Lines carrying ``k8s.pod.start_time =
+    __START_TIME__`` get rewritten to ``start_time.isoformat()`` before
+    construction, ensuring podAge is deterministic across runs.
+    """
+    path = get_testdata_file_path(file_relpath)
+    start_time_iso = start_time.isoformat() if start_time else None
+    rows = []
+    with open(path, encoding="utf-8") as f:
+        for line in f:
+            line = line.strip()
+            if not line:
+                continue
+            data = json.loads(line)
+            labels = data.get("labels", {})
+            if start_time_iso and labels.get("k8s.pod.start_time") == START_TIME_PLACEHOLDER:
+                labels["k8s.pod.start_time"] = start_time_iso
+            rows.append(data)
+    if not rows:
+        return []
+    earliest = min(parse_timestamp(r["timestamp"]) for r in rows)
+    offset = base_time - earliest
+    metrics = []
+    for r in rows:
+        ts = parse_timestamp(r["timestamp"]) + offset
+        r["timestamp"] = ts.isoformat()
+        metrics.append(Metrics.from_dict(r))
+    return metrics
+
+
+def test_pods_accuracy(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Seed 2 pods x 7 metrics; assert response shape/contract + exact per-pod
+    metric values, podAge, and podCountsByPhase against precomputed expected
+    output. Locks in numerical determinism."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    start_time = now - timedelta(minutes=10)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_value_accuracy.jsonl",
+            base_time=now - timedelta(minutes=4),
+            start_time=start_time,
+        )
+    )
+
+    with open(
+        get_testdata_file_path("inframonitoring/pods_value_accuracy_expected.json"),
+        encoding="utf-8",
+    ) as f:
+        expected = json.load(f)
+    exp_by_name = {r["podName"]: r for r in expected["records"]}
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    req_end_ms = int(now.timestamp() * 1000)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": req_end_ms,
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+
+    # Shape/contract.
+    assert data["total"] == len(expected["records"])
+    assert len(data["records"]) == len(expected["records"])
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
+    assert data["endTimeBeforeRetention"] is False
+    assert {r["meta"]["k8s.pod.name"] for r in data["records"]} == set(exp_by_name.keys())
+
+    # podAge = req.End - k8s.pod.start_time (in milliseconds). Verified equal to
+    # the precise expected value computed from the test's known start_time.
+    expected_age_ms = req_end_ms - int(start_time.timestamp() * 1000)
+
+    for record in data["records"]:
+        for field in (
+            "podUID",
+            "podCPU",
+            "podCPURequest",
+            "podCPULimit",
+            "podMemory",
+            "podMemoryRequest",
+            "podMemoryLimit",
+            "podPhase",
+            "podCountsByPhase",
+            "podAge",
+            "meta",
+        ):
+            assert field in record, f"missing {field} in {record!r}"
+
+        # Five phase buckets always present, integer-typed.
+        for bucket in ("pending", "running", "succeeded", "failed", "unknown"):
+            assert bucket in record["podCountsByPhase"], f"missing phase bucket {bucket} in {record['podCountsByPhase']!r}"
+            assert isinstance(record["podCountsByPhase"][bucket], int)
+
+        # Exact values.
+        pod_name = record["meta"]["k8s.pod.name"]
+        exp = exp_by_name[pod_name]
+        for field in (
+            "podCPU",
+            "podCPURequest",
+            "podCPULimit",
+            "podMemory",
+            "podMemoryRequest",
+            "podMemoryLimit",
+        ):
+            assert compare_values(record[field], exp[field], 1e-9), f"{pod_name}.{field}: got {record[field]}, expected {exp[field]}"
+        assert record["podPhase"] == exp["podPhase"]
+        assert record["podCountsByPhase"] == exp["podCountsByPhase"]
+        assert record["podAge"] == expected_age_ms, f"{pod_name}.podAge: got {record['podAge']}, expected {expected_age_ms}"
+
+
+def test_pods_missing_metrics(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Seed only k8s.pod.cpu.usage; assert other 6 required metrics flagged missing.
+
+    The endpoint short-circuits and returns empty records + total=0 when any
+    required metric is missing (module.go:192-197).
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_missing_metrics.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
+
+
+@pytest.mark.parametrize(
+    "expression,expected_pods",
+    [
+        pytest.param(
+            "k8s.namespace.name = 'ns-prod' AND k8s.deployment.name = 'web'",
+            {"web-prod-1", "web-prod-2"},
+            id="and",
+        ),
+        pytest.param(
+            "k8s.pod.name IN ('web-prod-1', 'api-dev-1')",
+            {"web-prod-1", "api-dev-1"},
+            id="in",
+        ),
+        pytest.param(
+            "k8s.deployment.name NOT IN ('api')",
+            {"web-prod-1", "web-prod-2", "web-dev-1", "web-dev-2"},
+            id="not_in",
+        ),
+        pytest.param(
+            "k8s.pod.name CONTAINS 'web'",
+            {"web-prod-1", "web-prod-2", "web-dev-1", "web-dev-2"},
+            id="contains",
+        ),
+        pytest.param(
+            "k8s.namespace.name = 'ns-prod' AND k8s.pod.name IN ('web-prod-1', 'api-prod-1')",
+            {"web-prod-1", "api-prod-1"},
+            id="and_in",
+        ),
+        pytest.param(
+            "k8s.namespace.name = 'ns-prod' AND k8s.pod.name NOT IN ('web-prod-1', 'web-prod-2')",
+            {"api-prod-1", "api-prod-2"},
+            id="and_not_in",
+        ),
+        pytest.param(
+            "k8s.namespace.name = 'ns-dev' AND k8s.pod.name CONTAINS 'web'",
+            {"web-dev-1", "web-dev-2"},
+            id="and_contains",
+        ),
+        pytest.param(
+            "k8s.pod.name IN ('web-prod-1', 'web-dev-1', 'api-dev-1') AND k8s.pod.name CONTAINS 'web'",
+            {"web-prod-1", "web-dev-1"},
+            id="in_contains",
+        ),
+    ],
+)
+def test_pods_filter(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    expression: str,
+    expected_pods: set,
+) -> None:
+    """Filter operators (=, IN, NOT IN, CONTAINS) and their AND-combinations
+    return exactly the matching pods, with undistorted per-pod metric values."""
+    # Every pod in pods_filter_dataset.jsonl carries the same sample pattern
+    # as acc-p1 in pods_value_accuracy.jsonl, so all filtered records must
+    # resolve to these exact values (mirrors pods_value_accuracy_expected.json
+    # acc-p1).
+    expected_values = {
+        "podCPU": 0.5,
+        "podCPURequest": 0.25,
+        "podCPULimit": 0.5,
+        "podMemory": 524288000.0,
+        "podMemoryRequest": 0.5,
+        "podMemoryLimit": 0.25,
+    }
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_filter_dataset.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": expression},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert {r["meta"]["k8s.pod.name"] for r in data["records"]} == expected_pods
+    assert data["total"] == len(expected_pods)
+
+    # Filtering must not distort per-pod aggregation values.
+    for record in data["records"]:
+        for field in expected_values:
+            assert compare_values(record[field], expected_values[field], 1e-9), f"{record['meta']['k8s.pod.name']}.{field}: got {record[field]}, expected {expected_values[field]}"
+
+
+@pytest.mark.parametrize(
+    "expression,err_substr",
+    [
+        pytest.param("k8s.pod.namee = 'web-prod-1'", "k8s.pod.namee", id="bad_attr_name"),
+        pytest.param("k8s.pod.name =", None, id="trailing_op"),
+        pytest.param("(k8s.pod.name = 'web-prod-1'", None, id="unclosed_paren"),
+    ],
+)
+def test_pods_filter_invalid(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    expression: str,
+    err_substr,
+) -> None:
+    """Invalid filter expressions (typo'd attribute key, malformed grammar) return
+    400 invalid_input with structured errors; bad attribute keys are named in them."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_filter_dataset.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": expression},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.BAD_REQUEST, f"expected 400, got {response.status_code}: {response.text}"
+    body = response.json()
+    assert body["status"] == "error"
+    assert body["error"]["code"] == "invalid_input"
+    assert len(body["error"]["errors"]) > 0
+    if err_substr is not None:
+        assert any(err_substr in e["message"] for e in body["error"]["errors"]), f"{err_substr!r} not surfaced: {body['error']['errors']!r}"
+
+
+# Pod names per phase, as seeded in pods_phases.jsonl.
+_PHASE_TO_POD_NAME = {
+    "pending": "pend-p",
+    "running": "run-p",
+    "succeeded": "succ-p",
+    "failed": "fail-p",
+    "unknown": "unk-p",
+}
+
+
+@pytest.mark.parametrize(
+    "phase_name",
+    [
+        pytest.param("pending", id="pending"),
+        pytest.param("running", id="running"),
+        pytest.param("succeeded", id="succeeded"),
+        pytest.param("failed", id="failed"),
+        pytest.param("unknown", id="unknown"),
+    ],
+)
+def test_pods_phase_counts_list_mode(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    phase_name: str,
+) -> None:
+    """List mode (no groupBy): each pod's record carries podPhase derived from its
+    latest k8s.pod.phase sample, AND podCountsByPhase has exactly that bucket=1
+    with all others 0. Verifies the phase-derivation logic at pods.go:82-94.
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_phases.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    pod_name = _PHASE_TO_POD_NAME[phase_name]
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": f"k8s.pod.name = '{pod_name}'"},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+    assert rec["meta"]["k8s.pod.name"] == pod_name
+    assert rec["podPhase"] == phase_name
+    assert rec["podCountsByPhase"][phase_name] == 1
+    for other in {"pending", "running", "succeeded", "failed", "unknown"} - {phase_name}:
+        assert rec["podCountsByPhase"][other] == 0, f"expected {other}=0 when latest phase={phase_name}, got {rec['podCountsByPhase']}"
+
+
+def test_pods_phase_counts_latest_wins(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Pod with k8s.pod.phase transitioning pending->running across the window:
+    podPhase reflects the LATEST sample (running) via argMax, not the earliest.
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_phases_transition.jsonl",
+            base_time=now - timedelta(minutes=8),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=10)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+    assert rec["meta"]["k8s.pod.name"] == "trans-p"
+    assert rec["podPhase"] == "running"
+    assert rec["podCountsByPhase"]["running"] == 1
+    assert rec["podCountsByPhase"]["pending"] == 0
+
+
+def test_pods_phase_counts_grouped_mode(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """groupBy=[k8s.namespace.name] aggregates phase counts across all pods in
+    the group. podPhase becomes "no_data" because no single pod identifies the
+    group, and per-pod fields (podUID, podAge, meta) clear out.
+    Dataset: ns-mixed contains 3 running + 2 failed + 1 pending.
+    See pods.go:80-95 (list-vs-grouped phase handling).
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_phases_grouped.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "groupBy": [
+                {
+                    "name": "k8s.namespace.name",
+                    "fieldDataType": "string",
+                    "fieldContext": "resource",
+                }
+            ],
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+
+    # Grouped-mode invariants: per-pod fields cleared, but meta surfaces the
+    # groupBy key so the client can identify the group.
+    assert rec["podUID"] == ""
+    assert rec["podAge"] == -1
+    assert rec["podPhase"] == "no_data"
+    assert rec["meta"].get("k8s.namespace.name") == "ns-mixed"
+
+    # Aggregated phase counts across the namespace.
+    assert rec["podCountsByPhase"] == {
+        "pending": 1,
+        "running": 3,
+        "succeeded": 0,
+        "failed": 2,
+        "unknown": 0,
+    }
+
+
+@pytest.mark.parametrize(
+    "group_key,expected_groups",
+    [
+        pytest.param("k8s.namespace.name", {"gns-a", "gns-b"}, id="namespace"),
+        pytest.param("k8s.deployment.name", {"gdep-x", "gdep-y"}, id="deployment"),
+    ],
+)
+def test_pods_groupby(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    group_key: str,
+    expected_groups: set,
+) -> None:
+    """groupBy aggregates 2 pods per group into one record. Per-pod identity
+    fields (uid, age, phase) are cleared, but meta must surface the groupBy
+    key so the client can identify each group.
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_groupby.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "groupBy": [
+                {
+                    "name": group_key,
+                    "fieldDataType": "string",
+                    "fieldContext": "resource",
+                }
+            ],
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == len(expected_groups)
+    assert len(data["records"]) == len(expected_groups)
+
+    groups_seen = set()
+    for rec in data["records"]:
+        assert rec["podUID"] == ""
+        assert rec["podPhase"] == "no_data"
+        assert rec["podAge"] == -1
+        # meta surfaces the groupBy key so the client can identify the group.
+        assert group_key in rec["meta"], rec["meta"]
+        groups_seen.add(rec["meta"][group_key])
+        # Each group has 2 running pods.
+        assert rec["podCountsByPhase"]["running"] == 2
+        for other in ("pending", "succeeded", "failed", "unknown"):
+            assert rec["podCountsByPhase"][other] == 0
+    assert groups_seen == expected_groups
+
+
+def test_pods_pagination(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Pagination: per-page len matches min(limit, total-offset), total invariant,
+    pages cover the full set with no overlap. The final offset is beyond total:
+    it returns empty records while total still reflects dataset size."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_pagination.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    K, limit = 7, 3
+    seen_pods: list[str] = []
+    seen_totals: set[int] = set()
+
+    for offset in (0, 3, 6, K + 5):
+        response = requests.post(
+            signoz.self.host_configs["8080"].get(ENDPOINT),
+            headers={"authorization": f"Bearer {token}"},
+            json={
+                "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+                "end": int(now.timestamp() * 1000),
+                "limit": limit,
+                "offset": offset,
+            },
+            timeout=5,
+        )
+        assert response.status_code == HTTPStatus.OK, response.text
+        data = response.json()["data"]
+        seen_totals.add(data["total"])
+        expected_len = max(0, min(limit, K - offset))
+        assert len(data["records"]) == expected_len, f"offset={offset}: expected {expected_len} records, got {len(data['records'])}"
+        seen_pods.extend(r["meta"]["k8s.pod.name"] for r in data["records"])
+
+    assert seen_totals == {K}
+    assert len(seen_pods) == K
+    assert set(seen_pods) == {f"page-p{i}" for i in range(1, K + 1)}
+
+
+# orderBy keys per pods_constants.go:42-48 (snake_case request keys, camelCase
+# response fields). k8s.pod.name sorts via the metadata-name branch
+# (PaginateMetadataByName) and is only allowed when groupBy is empty.
+@pytest.mark.parametrize(
+    "column,record_field",
+    [
+        pytest.param("cpu", "podCPU", id="cpu"),
+        pytest.param("cpu_request", "podCPURequest", id="cpu_request"),
+        pytest.param("cpu_limit", "podCPULimit", id="cpu_limit"),
+        pytest.param("memory", "podMemory", id="memory"),
+        pytest.param("memory_request", "podMemoryRequest", id="memory_request"),
+        pytest.param("memory_limit", "podMemoryLimit", id="memory_limit"),
+        pytest.param("k8s.pod.name", None, id="pod_name"),
+    ],
+)
+@pytest.mark.parametrize("direction", ["asc", "desc"])
+def test_pods_orderby(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    column: str,
+    record_field,
+    direction: str,
+) -> None:
+    """Every orderBy column x direction: total/len stay K (invariant under
+    sort) and records come back sorted by the requested column."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        _load_pods_metrics(
+            "inframonitoring/pods_orderby.jsonl",
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    K = 5
+
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "orderBy": {"key": {"name": column}, "direction": direction},
+            # Guards against pods seeded by other tests in the shared backend.
+            "filter": {"expression": "k8s.pod.name CONTAINS 'order-'"},
+        },
+        timeout=5,
+    )
+    ctx = f"orderBy={column} {direction}"
+    assert response.status_code == HTTPStatus.OK, f"{ctx}: {response.text}"
+    data = response.json()["data"]
+    assert data["total"] == K, f"{ctx}: total={data['total']}"
+    assert len(data["records"]) == K, f"{ctx}: len(records)={len(data['records'])}"
+
+    # record_field None => pod name lives in meta, not a top-level field.
+    values = [r["meta"]["k8s.pod.name"] if record_field is None else r[record_field] for r in data["records"]]
+    expected = sorted(values, reverse=(direction == "desc"))
+    assert values == expected, f"{ctx} not sorted; got {values}"
+
+
+@pytest.mark.parametrize(
+    "payload_override,err_substr",
+    [
+        pytest.param({"start": 0}, "start must be greater than 0", id="start_zero"),
+        pytest.param({"start": -1}, "start must be greater than 0", id="start_negative"),
+        pytest.param({"end": 0}, "end must be greater than 0", id="end_zero"),
+        pytest.param({"end": -1}, "end must be greater than 0", id="end_negative"),
+        pytest.param({"_use_end_eq_start": True}, "must be less than end", id="start_equals_end"),
+        pytest.param({"_use_start_gt_end": True}, "must be less than end", id="start_greater_than_end"),
+        pytest.param({"limit": 0}, "limit must be between", id="limit_zero"),
+        pytest.param({"limit": 5001}, "limit must be between", id="limit_too_large"),
+        pytest.param({"offset": -1}, "offset cannot be negative", id="offset_negative"),
+        pytest.param(
+            {"orderBy": {"key": {"name": "bogus_col"}, "direction": "desc"}},
+            "invalid order by key",
+            id="orderby_invalid_key",
+        ),
+        pytest.param(
+            {"orderBy": {"key": {"name": "phase"}, "direction": "desc"}},
+            "invalid order by key",
+            id="orderby_phase_rejected",
+        ),
+        pytest.param(
+            {"orderBy": {"key": {"name": "cpu"}, "direction": "up"}},
+            "invalid order by direction",
+            id="orderby_invalid_direction",
+        ),
+        pytest.param(
+            {
+                "orderBy": {
+                    "key": {"name": "k8s.pod.name"},
+                    "direction": "desc",
+                },
+                "groupBy": [
+                    {
+                        "name": "k8s.namespace.name",
+                        "fieldDataType": "string",
+                        "fieldContext": "resource",
+                    }
+                ],
+            },
+            "is only allowed when groupBy is empty",
+            id="orderby_podname_with_groupby",
+        ),
+    ],
+)
+def test_pods_validation_errors(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    payload_override: dict,
+    err_substr: str,
+) -> None:
+    """All PostablePods.Validate() rules reject with 400 + descriptive error.
+    See pkg/types/inframonitoringtypes/pods.go:56-107."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    body: dict = {
+        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+        "end": int(now.timestamp() * 1000),
+        "limit": 50,
+    }
+    if payload_override.pop("_use_end_eq_start", False):
+        body["end"] = body["start"]
+    if payload_override.pop("_use_start_gt_end", False):
+        body["start"] = body["end"] + 1
+    body.update(payload_override)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json=body,
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.BAD_REQUEST, response.text
+    error = response.json()["error"]
+    assert error["code"] == "invalid_input"
+    assert err_substr.lower() in error["message"].lower(), f"expected substring {err_substr!r} not found in: {error['message']!r}"

tests/integration/tests/inframonitoring/03_nodes.py

@@ -0,0 +1,760 @@
+"""Integration tests for v2 infra-monitoring node endpoints."""
+
+import json
+from datetime import UTC, datetime, timedelta
+from http import HTTPStatus
+
+import pytest
+import requests
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.fs import get_testdata_file_path
+from fixtures.metrics import Metrics
+from fixtures.querier import compare_values
+
+ENDPOINT = "/api/v2/infra_monitoring/nodes"
+
+# Required metrics for the v2 nodes endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/nodes_constants.go:22-29).
+REQUIRED_METRICS = {
+    "k8s.node.cpu.usage",
+    "k8s.node.allocatable_cpu",
+    "k8s.node.memory.working_set",
+    "k8s.node.allocatable_memory",
+    "k8s.node.condition_ready",
+    "k8s.pod.phase",
+}
+
+# Numeric values emitted by k8s.node.condition_ready.
+COND_NUM = {"ready": 1, "not_ready": 0}
+
+
+def test_nodes_accuracy(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Seed 2 nodes x 5 metrics + pods; assert response shape/contract + exact
+    per-node metric values, condition, and both count buckets against
+    precomputed expected output."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_value_accuracy.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    with open(
+        get_testdata_file_path("inframonitoring/nodes_value_accuracy_expected.json"),
+        encoding="utf-8",
+    ) as f:
+        expected = json.load(f)
+    exp_by_name = {r["nodeName"]: r for r in expected["records"]}
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+
+    # Shape/contract.
+    assert data["total"] == len(expected["records"])
+    assert len(data["records"]) == len(expected["records"])
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
+    assert data["endTimeBeforeRetention"] is False
+    assert {r["nodeName"] for r in data["records"]} == set(exp_by_name.keys())
+
+    for record in data["records"]:
+        for field in (
+            "nodeName",
+            "condition",
+            "nodeCountsByReadiness",
+            "podCountsByPhase",
+            "nodeCPU",
+            "nodeCPUAllocatable",
+            "nodeMemory",
+            "nodeMemoryAllocatable",
+            "meta",
+        ):
+            assert field in record, f"missing {field} in {record!r}"
+
+        for bucket in ("ready", "notReady"):
+            assert bucket in record["nodeCountsByReadiness"]
+        for bucket in ("pending", "running", "succeeded", "failed", "unknown"):
+            assert bucket in record["podCountsByPhase"]
+
+        assert record["meta"].get("k8s.node.name") == record["nodeName"]
+        assert "k8s.node.uid" in record["meta"]
+        assert "k8s.cluster.name" in record["meta"]
+
+        # Exact values.
+        exp = exp_by_name[record["nodeName"]]
+        for field in ("nodeCPU", "nodeCPUAllocatable", "nodeMemory", "nodeMemoryAllocatable"):
+            assert compare_values(record[field], exp[field], 1e-6), f"{record['nodeName']}.{field}: got {record[field]}, expected {exp[field]}"
+        assert record["condition"] == exp["condition"]
+        assert record["nodeCountsByReadiness"] == exp["nodeCountsByReadiness"]
+        assert record["podCountsByPhase"] == exp["podCountsByPhase"]
+
+
+def test_nodes_missing_metrics(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Seed only k8s.node.cpu.usage; assert other 5 required metrics flagged missing."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_missing_metrics.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.node.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
+
+
+@pytest.mark.parametrize(
+    "expression,expected_nodes",
+    [
+        pytest.param(
+            "k8s.cluster.name = 'cluster-a' AND zone = 'us'",
+            {"web-a-us-1", "api-a-us-1"},
+            id="and",
+        ),
+        pytest.param(
+            "k8s.node.name IN ('web-a-us-1', 'api-b-eu-1')",
+            {"web-a-us-1", "api-b-eu-1"},
+            id="in",
+        ),
+        pytest.param(
+            "k8s.cluster.name NOT IN ('cluster-a')",
+            {"web-b-us-1", "web-b-eu-1", "api-b-us-1", "api-b-eu-1"},
+            id="not_in",
+        ),
+        pytest.param(
+            "k8s.node.name CONTAINS 'web'",
+            {"web-a-us-1", "web-a-eu-1", "web-b-us-1", "web-b-eu-1"},
+            id="contains",
+        ),
+        pytest.param(
+            "k8s.cluster.name = 'cluster-a' AND k8s.node.name IN ('web-a-us-1', 'api-a-us-1')",
+            {"web-a-us-1", "api-a-us-1"},
+            id="and_in",
+        ),
+        pytest.param(
+            "k8s.cluster.name = 'cluster-a' AND k8s.node.name NOT IN ('web-a-us-1', 'web-a-eu-1')",
+            {"api-a-us-1", "api-a-eu-1"},
+            id="and_not_in",
+        ),
+        pytest.param(
+            "zone = 'us' AND k8s.node.name CONTAINS 'web'",
+            {"web-a-us-1", "web-b-us-1"},
+            id="and_contains",
+        ),
+        pytest.param(
+            "k8s.node.name IN ('web-a-us-1', 'web-b-us-1', 'api-a-us-1') AND k8s.node.name CONTAINS 'web'",
+            {"web-a-us-1", "web-b-us-1"},
+            id="in_contains",
+        ),
+    ],
+)
+def test_nodes_filter(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    expression: str,
+    expected_nodes: set,
+) -> None:
+    """Filter operators (=, IN, NOT IN, CONTAINS) and their AND-combinations
+    return exactly the matching nodes, with undistorted per-node metric values."""
+    # Every node in nodes_filter_dataset.jsonl carries the same sample pattern
+    # as acc-n1 in nodes_value_accuracy.jsonl, so all filtered records must
+    # resolve to these exact values (mirrors nodes_value_accuracy_expected.json
+    # acc-n1).
+    expected_values = {
+        "nodeCPU": 1.0,
+        "nodeCPUAllocatable": 4.0,
+        "nodeMemory": 2000000000.0,
+        "nodeMemoryAllocatable": 8000000000.0,
+    }
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_filter_dataset.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": expression},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert {r["nodeName"] for r in data["records"]} == expected_nodes
+    assert data["total"] == len(expected_nodes)
+
+    # Filtering must not distort per-node aggregation values.
+    for record in data["records"]:
+        for field in expected_values:
+            assert compare_values(record[field], expected_values[field], 1e-6), f"{record['nodeName']}.{field}: got {record[field]}, expected {expected_values[field]}"
+
+
+@pytest.mark.parametrize(
+    "expression,err_substr",
+    [
+        pytest.param("k8s.node.namee = 'web-a-us-1'", "k8s.node.namee", id="bad_attr_name"),
+        pytest.param("k8s.node.name =", None, id="trailing_op"),
+        pytest.param("(k8s.node.name = 'web-a-us-1'", None, id="unclosed_paren"),
+    ],
+)
+def test_nodes_filter_invalid(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    expression: str,
+    err_substr,
+) -> None:
+    """Invalid filter expressions (typo'd attribute key, malformed grammar) return
+    400 invalid_input with structured errors; bad attribute keys are named in them."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_filter_dataset.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": expression},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.BAD_REQUEST, f"expected 400, got {response.status_code}: {response.text}"
+    body = response.json()
+    assert body["status"] == "error"
+    assert body["error"]["code"] == "invalid_input"
+    assert len(body["error"]["errors"]) > 0
+    if err_substr is not None:
+        assert any(err_substr in e["message"] for e in body["error"]["errors"]), f"{err_substr!r} not surfaced: {body['error']['errors']!r}"
+
+
+@pytest.mark.parametrize(
+    "node_name,expected_condition",
+    [
+        pytest.param("ready-n", "ready", id="ready"),
+        pytest.param("notready-n", "not_ready", id="not_ready"),
+    ],
+)
+def test_nodes_condition_list_mode(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    node_name: str,
+    expected_condition: str,
+) -> None:
+    """List mode: each node's record carries condition derived from latest
+    k8s.node.condition_ready sample. Counts match per nodes.go:69-76."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_conditions.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": f"k8s.node.name = '{node_name}'"},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+    assert rec["nodeName"] == node_name
+    assert rec["condition"] == expected_condition
+    if expected_condition == "ready":
+        assert rec["nodeCountsByReadiness"] == {"ready": 1, "notReady": 0}
+    else:
+        assert rec["nodeCountsByReadiness"] == {"ready": 0, "notReady": 1}
+
+
+def test_nodes_condition_latest_wins(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Node with condition_ready transitioning 0->1: latest argMax wins -> ready.
+
+    Note: the dataset also seeds a phantom k8s.pod.phase sample (otherwise the
+    nodes endpoint short-circuits — pod.phase is in nodesTableMetricNamesList).
+    The phantom surfaces as an extra node via the metadata getter (which groups
+    by k8s.node.name across ALL required-metric series, including pod-phase),
+    so the test filters explicitly to the trans-n node.
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_conditions_transition.jsonl"),
+            base_time=now - timedelta(minutes=8),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=10)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": "k8s.node.name = 'trans-n'"},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+    assert rec["nodeName"] == "trans-n"
+    assert rec["condition"] == "ready"
+    assert rec["nodeCountsByReadiness"] == {"ready": 1, "notReady": 0}
+
+
+def test_nodes_condition_grouped_mode(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """groupBy=[k8s.cluster.name] aggregates condition counts across nodes.
+    Per the contract (nodes.go:69-76): condition stays no_data in grouped mode."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_conditions_grouped.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "groupBy": [
+                {
+                    "name": "k8s.cluster.name",
+                    "fieldDataType": "string",
+                    "fieldContext": "resource",
+                }
+            ],
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+
+    # Grouped-mode invariants: per-node fields cleared.
+    assert rec["nodeName"] == ""
+    assert rec["condition"] == "no_data"
+    # Aggregated condition counts across the cluster.
+    assert rec["nodeCountsByReadiness"] == {"ready": 2, "notReady": 1}
+    # Pod-phase counts aggregated: 3 running pods (one per node).
+    assert rec["podCountsByPhase"]["running"] == 3
+    for other in ("pending", "succeeded", "failed", "unknown"):
+        assert rec["podCountsByPhase"][other] == 0
+    # meta surfaces the groupBy key.
+    assert rec["meta"].get("k8s.cluster.name") == "cluster-mixed"
+
+
+@pytest.mark.parametrize(
+    "dataset,node_name,filter_expr,expected_counts",
+    [
+        # Node hosts 3 running + 2 failed pods: phase buckets aggregate correctly.
+        pytest.param(
+            "nodes_pod_phases.jsonl",
+            "pp-n1",
+            None,
+            {"pending": 0, "running": 3, "succeeded": 0, "failed": 2, "unknown": 0},
+            id="mixed_phases",
+        ),
+        # Node with no pods: all-zero buckets, node still appears. Filter on the
+        # node to ignore the carrier phantom (see test_nodes_condition_latest_wins).
+        pytest.param(
+            "nodes_no_pods.jsonl",
+            "no-pod-n",
+            "k8s.node.name = 'no-pod-n'",
+            {"pending": 0, "running": 0, "succeeded": 0, "failed": 0, "unknown": 0},
+            id="no_pods",
+        ),
+    ],
+)
+def test_nodes_pod_phase_counts(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    dataset: str,
+    node_name: str,
+    filter_expr,
+    expected_counts: dict,
+) -> None:
+    """podCountsByPhase per node aggregates the pods scheduled on it (k8s.pod.phase
+    joined via k8s.node.name). A node with no pods reports all-zero buckets and
+    still appears in the result."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path(f"inframonitoring/{dataset}"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    body = {
+        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+        "end": int(now.timestamp() * 1000),
+        "limit": 50,
+    }
+    if filter_expr is not None:
+        body["filter"] = {"expression": filter_expr}
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json=body,
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+    assert rec["nodeName"] == node_name
+    assert rec["podCountsByPhase"] == expected_counts
+
+
+@pytest.mark.parametrize(
+    "group_key,expected",
+    [
+        # groupBy=[k8s.node.name]: one record per node, nodeName populated and
+        # condition derived per node (isNodeNameInGroupBy branch, nodes.go:69-76).
+        pytest.param(
+            "k8s.node.name",
+            {
+                "gb-a-us": {"condition": "ready", "readiness": {"ready": 1, "notReady": 0}, "running": 1},
+                "gb-a-eu": {"condition": "ready", "readiness": {"ready": 1, "notReady": 0}, "running": 1},
+                "gb-b-us": {"condition": "ready", "readiness": {"ready": 1, "notReady": 0}, "running": 1},
+                "gb-b-eu": {"condition": "ready", "readiness": {"ready": 1, "notReady": 0}, "running": 1},
+            },
+            id="node_name",
+        ),
+        # groupBy=[k8s.cluster.name]: aggregated across each cluster's 2 nodes,
+        # nodeName empty and condition stays no_data (custom-groupBy branch).
+        pytest.param(
+            "k8s.cluster.name",
+            {
+                "gb-cluster-a": {"condition": "no_data", "readiness": {"ready": 2, "notReady": 0}, "running": 2},
+                "gb-cluster-b": {"condition": "no_data", "readiness": {"ready": 2, "notReady": 0}, "running": 2},
+            },
+            id="cluster",
+        ),
+    ],
+)
+def test_nodes_groupby(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    group_key: str,
+    expected: dict,
+) -> None:
+    """groupBy returns one record per distinct group with aggregated readiness
+    and pod-phase counts. nodeName is populated and condition is derived only
+    when grouping by k8s.node.name (nodes.go:69-76 list-vs-grouped branch)."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_groupby.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "groupBy": [
+                {
+                    "name": group_key,
+                    "fieldDataType": "string",
+                    "fieldContext": "resource",
+                }
+            ],
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == len(expected)
+
+    group_of = lambda r: r["nodeName"] if group_key == "k8s.node.name" else r["meta"][group_key]  # noqa: E731  # pylint: disable=unnecessary-lambda-assignment
+    by_group = {group_of(r): r for r in data["records"]}
+    assert set(by_group.keys()) == set(expected.keys())
+
+    for group, exp in expected.items():
+        rec = by_group[group]
+        # nodeName populated per node when grouping by k8s.node.name, empty otherwise.
+        assert rec["nodeName"] == (group if group_key == "k8s.node.name" else "")
+        assert rec["condition"] == exp["condition"]
+        assert rec["nodeCountsByReadiness"] == exp["readiness"]
+        assert rec["podCountsByPhase"]["running"] == exp["running"]
+        assert group_key in rec["meta"], rec["meta"]
+
+
+def test_nodes_pagination(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Pagination: per-page len matches min(limit, total-offset), total invariant,
+    pages cover the full set with no overlap. The final offset is beyond total:
+    it returns empty records while total still reflects dataset size."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_pagination.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    K, limit = 7, 3
+    seen_nodes: list[str] = []
+    seen_totals: set[int] = set()
+
+    for offset in (0, 3, 6, K + 5):
+        response = requests.post(
+            signoz.self.host_configs["8080"].get(ENDPOINT),
+            headers={"authorization": f"Bearer {token}"},
+            json={
+                "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+                "end": int(now.timestamp() * 1000),
+                "limit": limit,
+                "offset": offset,
+                # Exclude the dataset's carrier phantom (see test_nodes_condition_latest_wins).
+                "filter": {"expression": "k8s.node.name CONTAINS 'page-'"},
+            },
+            timeout=5,
+        )
+        assert response.status_code == HTTPStatus.OK, response.text
+        data = response.json()["data"]
+        seen_totals.add(data["total"])
+        expected_len = max(0, min(limit, K - offset))
+        assert len(data["records"]) == expected_len, f"offset={offset}: expected {expected_len} records, got {len(data['records'])}"
+        seen_nodes.extend(r["nodeName"] for r in data["records"])
+
+    assert seen_totals == {K}
+    assert len(seen_nodes) == K
+    assert set(seen_nodes) == {f"page-n{i}" for i in range(1, K + 1)}
+
+
+# orderBy keys per nodes_constants.go:33-37 (snake_case request keys,
+# camelCase response fields). k8s.node.name sorts via the metadata-name branch
+# (PaginateMetadataByName) and is only allowed when groupBy is empty.
+@pytest.mark.parametrize(
+    "column,record_field",
+    [
+        pytest.param("cpu", "nodeCPU", id="cpu"),
+        pytest.param("cpu_allocatable", "nodeCPUAllocatable", id="cpu_allocatable"),
+        pytest.param("memory", "nodeMemory", id="memory"),
+        pytest.param("memory_allocatable", "nodeMemoryAllocatable", id="memory_allocatable"),
+        pytest.param("k8s.node.name", "nodeName", id="node_name"),
+    ],
+)
+@pytest.mark.parametrize("direction", ["asc", "desc"])
+def test_nodes_orderby(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    column: str,
+    record_field: str,
+    direction: str,
+) -> None:
+    """Every orderBy column x direction: total/len stay K (invariant under
+    sort) and records come back sorted by the requested column."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/nodes_orderby.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    K = 5
+
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "orderBy": {"key": {"name": column}, "direction": direction},
+            # Guards against nodes seeded by other tests in the shared backend.
+            "filter": {"expression": "k8s.node.name CONTAINS 'order-'"},
+        },
+        timeout=5,
+    )
+    ctx = f"orderBy={column} {direction}"
+    assert response.status_code == HTTPStatus.OK, f"{ctx}: {response.text}"
+    data = response.json()["data"]
+    assert data["total"] == K, f"{ctx}: total={data['total']}"
+    assert len(data["records"]) == K, f"{ctx}: len(records)={len(data['records'])}"
+
+    values = [r[record_field] for r in data["records"]]
+    expected = sorted(values, reverse=(direction == "desc"))
+    assert values == expected, f"{ctx} not sorted; got {values}"
+
+
+@pytest.mark.parametrize(
+    "payload_override,err_substr",
+    [
+        pytest.param({"start": 0}, "start must be greater than 0", id="start_zero"),
+        pytest.param({"start": -1}, "start must be greater than 0", id="start_negative"),
+        pytest.param({"end": 0}, "end must be greater than 0", id="end_zero"),
+        pytest.param({"end": -1}, "end must be greater than 0", id="end_negative"),
+        pytest.param({"_use_end_eq_start": True}, "must be less than end", id="start_equals_end"),
+        pytest.param({"_use_start_gt_end": True}, "must be less than end", id="start_greater_than_end"),
+        pytest.param({"limit": 0}, "limit must be between", id="limit_zero"),
+        pytest.param({"limit": 5001}, "limit must be between", id="limit_too_large"),
+        pytest.param({"offset": -1}, "offset cannot be negative", id="offset_negative"),
+        pytest.param(
+            {"orderBy": {"key": {"name": "bogus_col"}, "direction": "desc"}},
+            "invalid order by key",
+            id="orderby_invalid_key",
+        ),
+        pytest.param(
+            {"orderBy": {"key": {"name": "condition"}, "direction": "desc"}},
+            "invalid order by key",
+            id="orderby_condition_rejected",
+        ),
+        pytest.param(
+            {"orderBy": {"key": {"name": "cpu"}, "direction": "up"}},
+            "invalid order by direction",
+            id="orderby_invalid_direction",
+        ),
+        pytest.param(
+            {
+                "orderBy": {"key": {"name": "k8s.node.name"}, "direction": "desc"},
+                "groupBy": [
+                    {
+                        "name": "k8s.cluster.name",
+                        "fieldDataType": "string",
+                        "fieldContext": "resource",
+                    }
+                ],
+            },
+            "is only allowed when groupBy is empty",
+            id="orderby_nodename_with_groupby",
+        ),
+    ],
+)
+def test_nodes_validation_errors(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    payload_override: dict,
+    err_substr: str,
+) -> None:
+    """All PostableNodes.Validate() rules reject with 400 + descriptive error.
+    See pkg/types/inframonitoringtypes/nodes.go:51-102."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    body: dict = {
+        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+        "end": int(now.timestamp() * 1000),
+        "limit": 50,
+    }
+    if payload_override.pop("_use_end_eq_start", False):
+        body["end"] = body["start"]
+    if payload_override.pop("_use_start_gt_end", False):
+        body["start"] = body["end"] + 1
+    body.update(payload_override)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json=body,
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.BAD_REQUEST, response.text
+    error = response.json()["error"]
+    assert error["code"] == "invalid_input"
+    assert err_substr.lower() in error["message"].lower(), f"expected substring {err_substr!r} not found in: {error['message']!r}"

tests/integration/tests/inframonitoring/04_namespaces.py

@@ -0,0 +1,568 @@
+"""Integration tests for v2 infra-monitoring namespace endpoints."""
+
+import json
+from datetime import UTC, datetime, timedelta
+from http import HTTPStatus
+
+import pytest
+import requests
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.fs import get_testdata_file_path
+from fixtures.metrics import Metrics
+from fixtures.querier import compare_values
+
+ENDPOINT = "/api/v2/infra_monitoring/namespaces"
+
+# Required metrics for the v2 namespaces endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/namespaces_constants.go:22-26).
+REQUIRED_METRICS = {
+    "k8s.pod.cpu.usage",
+    "k8s.pod.memory.working_set",
+    "k8s.pod.phase",
+}
+
+
+def test_namespaces_accuracy(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Seed 2 namespaces x 3 metrics; assert response shape/contract + exact
+    per-namespace metric values and podCountsByPhase.
+
+    Tests v1-parity expectation: SpaceAggregationSum across pods within a
+    namespace (pods_query.go A=cpu, D=memory both use Sum, namespaces.go:225
+    clones PodsTableListQuery; v2 namespaces_constants.go:54,73 use Sum too).
+    Predicted: acc-ns-1 (2 pods @ cpu=0.5,mem=1e8) -> cpu=1.0, mem=2e8;
+    acc-ns-2 (3 pods @ cpu=0.75,mem=2e8) -> cpu=2.25, mem=6e8.
+    """
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_value_accuracy.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    with open(
+        get_testdata_file_path("inframonitoring/namespaces_value_accuracy_expected.json"),
+        encoding="utf-8",
+    ) as f:
+        expected = json.load(f)
+    exp_by_name = {r["namespaceName"]: r for r in expected["records"]}
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+
+    # Shape/contract.
+    assert data["total"] == len(expected["records"])
+    assert len(data["records"]) == len(expected["records"])
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
+    assert data["endTimeBeforeRetention"] is False
+    assert {r["namespaceName"] for r in data["records"]} == set(exp_by_name.keys())
+
+    for record in data["records"]:
+        for field in (
+            "namespaceName",
+            "namespaceCPU",
+            "namespaceMemory",
+            "podCountsByPhase",
+            "meta",
+        ):
+            assert field in record, f"missing {field} in {record!r}"
+
+        for bucket in ("pending", "running", "succeeded", "failed", "unknown"):
+            assert bucket in record["podCountsByPhase"]
+            assert isinstance(record["podCountsByPhase"][bucket], int)
+
+        assert record["meta"].get("k8s.namespace.name") == record["namespaceName"]
+        assert "k8s.cluster.name" in record["meta"]
+
+        # Exact values.
+        exp = exp_by_name[record["namespaceName"]]
+        for field in ("namespaceCPU", "namespaceMemory"):
+            assert compare_values(record[field], exp[field], 1e-6), f"{record['namespaceName']}.{field}: got {record[field]}, expected {exp[field]}"
+        assert record["podCountsByPhase"] == exp["podCountsByPhase"]
+
+
+def test_namespaces_missing_metrics(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Seed only k8s.pod.cpu.usage; assert other 2 required metrics flagged missing."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_missing_metrics.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
+
+
+@pytest.mark.parametrize(
+    "expression,expected",
+    [
+        pytest.param(
+            "k8s.cluster.name = 'cluster-a' AND env = 'prod'",
+            {"web-a-prod", "api-a-prod"},
+            id="and",
+        ),
+        pytest.param(
+            "k8s.namespace.name IN ('web-a-prod', 'api-b-dev')",
+            {"web-a-prod", "api-b-dev"},
+            id="in",
+        ),
+        pytest.param(
+            "k8s.cluster.name NOT IN ('cluster-a')",
+            {"web-b-prod", "web-b-dev", "api-b-prod", "api-b-dev"},
+            id="not_in",
+        ),
+        pytest.param(
+            "k8s.namespace.name CONTAINS 'web'",
+            {"web-a-prod", "web-a-dev", "web-b-prod", "web-b-dev"},
+            id="contains",
+        ),
+        pytest.param(
+            "k8s.cluster.name = 'cluster-a' AND k8s.namespace.name IN ('web-a-prod', 'api-a-prod')",
+            {"web-a-prod", "api-a-prod"},
+            id="and_in",
+        ),
+        pytest.param(
+            "k8s.cluster.name = 'cluster-a' AND k8s.namespace.name NOT IN ('web-a-prod', 'web-a-dev')",
+            {"api-a-prod", "api-a-dev"},
+            id="and_not_in",
+        ),
+        pytest.param(
+            "env = 'prod' AND k8s.namespace.name CONTAINS 'web'",
+            {"web-a-prod", "web-b-prod"},
+            id="and_contains",
+        ),
+        pytest.param(
+            "k8s.namespace.name IN ('web-a-prod', 'web-b-prod', 'api-a-prod') AND k8s.namespace.name CONTAINS 'web'",
+            {"web-a-prod", "web-b-prod"},
+            id="in_contains",
+        ),
+    ],
+)
+def test_namespaces_filter(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    expression: str,
+    expected: set,
+) -> None:
+    """Filter operators (=, IN, NOT IN, CONTAINS) and their AND-combinations
+    return exactly the matching namespaces, with undistorted per-namespace
+    metric values."""
+    # Every namespace in namespaces_filter_dataset.jsonl carries the same
+    # sample pattern as acc-ns-1 in namespaces_value_accuracy.jsonl (2 pods),
+    # so all filtered records must resolve to these exact values (mirrors
+    # namespaces_value_accuracy_expected.json acc-ns-1).
+    expected_values = {
+        "namespaceCPU": 1.0,
+        "namespaceMemory": 200000000.0,
+    }
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_filter_dataset.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": expression},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert {r["namespaceName"] for r in data["records"]} == expected
+    assert data["total"] == len(expected)
+
+    # Filtering must not distort per-namespace aggregation values.
+    for record in data["records"]:
+        for field in expected_values:
+            assert compare_values(record[field], expected_values[field], 1e-6), f"{record['namespaceName']}.{field}: got {record[field]}, expected {expected_values[field]}"
+
+
+@pytest.mark.parametrize(
+    "expression,err_substr",
+    [
+        pytest.param("k8s.namespace.namee = 'web-a-prod'", "k8s.namespace.namee", id="bad_attr_name"),
+        pytest.param("k8s.namespace.name =", None, id="trailing_op"),
+        pytest.param("(k8s.namespace.name = 'web-a-prod'", None, id="unclosed_paren"),
+    ],
+)
+def test_namespaces_filter_invalid(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    expression: str,
+    err_substr,
+) -> None:
+    """Invalid filter expressions (typo'd attribute key, malformed grammar) return
+    400 invalid_input with structured errors; bad attribute keys are named in them."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_filter_dataset.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": expression},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.BAD_REQUEST, f"expected 400, got {response.status_code}: {response.text}"
+    body = response.json()
+    assert body["status"] == "error"
+    assert body["error"]["code"] == "invalid_input"
+    assert len(body["error"]["errors"]) > 0
+    if err_substr is not None:
+        assert any(err_substr in e["message"] for e in body["error"]["errors"]), f"{err_substr!r} not surfaced: {body['error']['errors']!r}"
+
+
+def test_namespaces_pod_phase_aggregation(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Namespace with mixed pod phases: podCountsByPhase aggregates correctly.
+    Dataset: 4 running + 1 pending + 2 failed pods all in pp-ns."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_pod_phases.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "filter": {"expression": "k8s.namespace.name = 'pp-ns'"},
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == 1
+    rec = data["records"][0]
+    assert rec["namespaceName"] == "pp-ns"
+    assert rec["podCountsByPhase"] == {
+        "pending": 1,
+        "running": 4,
+        "succeeded": 0,
+        "failed": 2,
+        "unknown": 0,
+    }
+
+
+@pytest.mark.parametrize(
+    "group_key,expected_running",
+    [
+        # groupBy=[k8s.namespace.name]: one record per namespace, namespaceName
+        # populated (namespaces.go:27-30). Each namespace has 1 running pod.
+        pytest.param(
+            "k8s.namespace.name",
+            {"gb-ns-1": 1, "gb-ns-2": 1, "gb-ns-3": 1, "gb-ns-4": 1},
+            id="namespace_name",
+        ),
+        # groupBy=[k8s.cluster.name]: aggregated across each cluster's 2
+        # namespaces, namespaceName empty. Each cluster has 2 x 1 = 2 running pods.
+        pytest.param(
+            "k8s.cluster.name",
+            {"gb-cluster-a": 2, "gb-cluster-b": 2},
+            id="cluster",
+        ),
+    ],
+)
+def test_namespaces_groupby(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    group_key: str,
+    expected_running: dict,
+) -> None:
+    """groupBy returns one record per distinct group with aggregated pod-phase
+    counts. namespaceName is populated only when grouping by k8s.namespace.name
+    (namespaces.go:27-30 list-vs-grouped branch); meta surfaces the groupBy key."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_groupby.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "groupBy": [
+                {
+                    "name": group_key,
+                    "fieldDataType": "string",
+                    "fieldContext": "resource",
+                }
+            ],
+        },
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    data = response.json()["data"]
+    assert data["total"] == len(expected_running)
+
+    group_of = lambda r: r["namespaceName"] if group_key == "k8s.namespace.name" else r["meta"][group_key]  # noqa: E731  # pylint: disable=unnecessary-lambda-assignment
+    by_group = {group_of(r): r for r in data["records"]}
+    assert set(by_group.keys()) == set(expected_running.keys())
+
+    for group, running in expected_running.items():
+        rec = by_group[group]
+        # namespaceName populated per namespace when grouping by k8s.namespace.name,
+        # empty otherwise.
+        assert rec["namespaceName"] == (group if group_key == "k8s.namespace.name" else "")
+        assert rec["podCountsByPhase"]["running"] == running
+        for other in ("pending", "succeeded", "failed", "unknown"):
+            assert rec["podCountsByPhase"][other] == 0
+        assert group_key in rec["meta"], rec["meta"]
+
+
+def test_namespaces_pagination(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+) -> None:
+    """Pagination: per-page len matches min(limit, total-offset), total invariant,
+    pages cover the full set with no overlap. The final offset is beyond total:
+    it returns empty records while total still reflects dataset size."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_pagination.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    K, limit = 7, 3
+    seen_names: list[str] = []
+    seen_totals: set[int] = set()
+
+    for offset in (0, 3, 6, K + 5):
+        response = requests.post(
+            signoz.self.host_configs["8080"].get(ENDPOINT),
+            headers={"authorization": f"Bearer {token}"},
+            json={
+                "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+                "end": int(now.timestamp() * 1000),
+                "limit": limit,
+                "offset": offset,
+            },
+            timeout=5,
+        )
+        assert response.status_code == HTTPStatus.OK, response.text
+        data = response.json()["data"]
+        seen_totals.add(data["total"])
+        expected_len = max(0, min(limit, K - offset))
+        assert len(data["records"]) == expected_len, f"offset={offset}: expected {expected_len}, got {len(data['records'])}"
+        seen_names.extend(r["namespaceName"] for r in data["records"])
+
+    assert seen_totals == {K}
+    assert len(seen_names) == K
+    assert set(seen_names) == {f"page-ns-{i}" for i in range(1, K + 1)}
+
+
+# orderBy keys per namespaces_constants.go (cpu, memory only).
+# k8s.namespace.name sorts via the metadata-name branch (PaginateMetadataByName)
+# and is only allowed when groupBy is empty.
+@pytest.mark.parametrize(
+    "column,record_field",
+    [
+        pytest.param("cpu", "namespaceCPU", id="cpu"),
+        pytest.param("memory", "namespaceMemory", id="memory"),
+        pytest.param("k8s.namespace.name", "namespaceName", id="namespace_name"),
+    ],
+)
+@pytest.mark.parametrize("direction", ["asc", "desc"])
+def test_namespaces_orderby(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    insert_metrics,
+    column: str,
+    record_field: str,
+    direction: str,
+) -> None:
+    """Every orderBy column x direction: total/len stay K (invariant under
+    sort) and records come back sorted by the requested column."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    insert_metrics(
+        Metrics.load_from_file(
+            get_testdata_file_path("inframonitoring/namespaces_orderby.jsonl"),
+            base_time=now - timedelta(minutes=4),
+        )
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    K = 5
+
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json={
+            "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+            "end": int(now.timestamp() * 1000),
+            "limit": 50,
+            "orderBy": {"key": {"name": column}, "direction": direction},
+            # Guards against namespaces seeded by other tests in the shared backend.
+            "filter": {"expression": "k8s.namespace.name CONTAINS 'order-'"},
+        },
+        timeout=5,
+    )
+    ctx = f"orderBy={column} {direction}"
+    assert response.status_code == HTTPStatus.OK, f"{ctx}: {response.text}"
+    data = response.json()["data"]
+    assert data["total"] == K, f"{ctx}: total={data['total']}"
+    assert len(data["records"]) == K, f"{ctx}: len(records)={len(data['records'])}"
+
+    values = [r[record_field] for r in data["records"]]
+    expected = sorted(values, reverse=(direction == "desc"))
+    assert values == expected, f"{ctx} not sorted; got {values}"
+
+
+@pytest.mark.parametrize(
+    "payload_override,err_substr",
+    [
+        pytest.param({"start": 0}, "start must be greater than 0", id="start_zero"),
+        pytest.param({"start": -1}, "start must be greater than 0", id="start_negative"),
+        pytest.param({"end": 0}, "end must be greater than 0", id="end_zero"),
+        pytest.param({"end": -1}, "end must be greater than 0", id="end_negative"),
+        pytest.param({"_use_end_eq_start": True}, "must be less than end", id="start_equals_end"),
+        pytest.param({"_use_start_gt_end": True}, "must be less than end", id="start_greater_than_end"),
+        pytest.param({"limit": 0}, "limit must be between", id="limit_zero"),
+        pytest.param({"limit": 5001}, "limit must be between", id="limit_too_large"),
+        pytest.param({"offset": -1}, "offset cannot be negative", id="offset_negative"),
+        pytest.param(
+            {"orderBy": {"key": {"name": "bogus_col"}, "direction": "desc"}},
+            "invalid order by key",
+            id="orderby_invalid_key",
+        ),
+        pytest.param(
+            {"orderBy": {"key": {"name": "cpu"}, "direction": "up"}},
+            "invalid order by direction",
+            id="orderby_invalid_direction",
+        ),
+        pytest.param(
+            {
+                "orderBy": {"key": {"name": "k8s.namespace.name"}, "direction": "desc"},
+                "groupBy": [
+                    {
+                        "name": "k8s.cluster.name",
+                        "fieldDataType": "string",
+                        "fieldContext": "resource",
+                    }
+                ],
+            },
+            "is only allowed when groupBy is empty",
+            id="orderby_nsname_with_groupby",
+        ),
+    ],
+)
+def test_namespaces_validation_errors(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token,
+    payload_override: dict,
+    err_substr: str,
+) -> None:
+    """All PostableNamespaces.Validate() rules reject with 400 + descriptive error.
+    See pkg/types/inframonitoringtypes/namespaces.go:40-91."""
+    now = datetime.now(tz=UTC).replace(microsecond=0)
+    body: dict = {
+        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
+        "end": int(now.timestamp() * 1000),
+        "limit": 50,
+    }
+    if payload_override.pop("_use_end_eq_start", False):
+        body["end"] = body["start"]
+    if payload_override.pop("_use_start_gt_end", False):
+        body["start"] = body["end"] + 1
+    body.update(payload_override)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = requests.post(
+        signoz.self.host_configs["8080"].get(ENDPOINT),
+        headers={"authorization": f"Bearer {token}"},
+        json=body,
+        timeout=5,
+    )
+    assert response.status_code == HTTPStatus.BAD_REQUEST, response.text
+    error = response.json()["error"]
+    assert error["code"] == "invalid_input"
+    assert err_substr.lower() in error["message"].lower(), f"expected substring {err_substr!r} not found in: {error['message']!r}"