chore: add enable prefix

* fix(dashboard): clickhouse table panel collapses value columns onto query name

A table/scalar panel backed by a ClickHouse SQL query rendered every
aggregation column with the header "A" (the query name) and the same value in
each, while only the group columns (e.g. service.name) showed correctly.

Root cause: the scalar-response column-naming utils derive a value column's
display name and row-data key from request-side aggregation metadata, which
only exists for builder_query envelopes. A clickhouse_sql query has none, so
getColName/getColId fell through to the query name for every value column.
Sharing one id ("A") collapsed all value columns onto a single row key, so the
last column written (total_requests) overwrote the rest.

The backend already returns correct data: readAsScalar names each ClickHouse
SELECT column with its real SQL alias and a unique aggregationIndex. This is a
frontend-only consumption fix.

Fix: when a column belongs to a clickhouse_sql query (determined from the
request's query type, not a name heuristic), name and key it by the response
column's real SQL alias. Builder queries are unchanged; formulas/promql keep
the legend || queryName fallback. Applied to both the V1 converter
(convertV5Response.ts, the live table-panel path) and the V2 path
(prepareScalarTables.ts).

* chore: minor type fix

docs/api/openapi.yml

@@ -647,8 +647,12 @@ components:
           type: string
         name:
           type: string
+        transactionGroups:
+          $ref: '#/components/schemas/AuthtypesTransactionGroups'
       required:
       - name
+      - description
+      - transactionGroups
       type: object
     AuthtypesPostableRotateToken:
       properties:
@@ -703,6 +707,34 @@ components:
         useRoleAttribute:
           type: boolean
       type: object
+    AuthtypesRoleWithTransactionGroups:
+      properties:
+        createdAt:
+          format: date-time
+          type: string
+        description:
+          type: string
+        id:
+          type: string
+        name:
+          type: string
+        orgId:
+          type: string
+        transactionGroups:
+          $ref: '#/components/schemas/AuthtypesTransactionGroups'
+        type:
+          type: string
+        updatedAt:
+          format: date-time
+          type: string
+      required:
+      - id
+      - name
+      - description
+      - type
+      - orgId
+      - transactionGroups
+      type: object
     AuthtypesSamlConfig:
       properties:
         attributeMapping:
@@ -736,11 +768,35 @@ components:
       - relation
       - object
       type: object
+    AuthtypesTransactionGroup:
+      properties:
+        objectGroup:
+          $ref: '#/components/schemas/CoretypesObjectGroup'
+        relation:
+          $ref: '#/components/schemas/AuthtypesRelation'
+      required:
+      - relation
+      - objectGroup
+      type: object
+    AuthtypesTransactionGroups:
+      items:
+        $ref: '#/components/schemas/AuthtypesTransactionGroup'
+      type: array
     AuthtypesUpdatableAuthDomain:
       properties:
         config:
           $ref: '#/components/schemas/AuthtypesAuthDomainConfig'
       type: object
+    AuthtypesUpdatableRole:
+      properties:
+        description:
+          type: string
+        transactionGroups:
+          $ref: '#/components/schemas/AuthtypesTransactionGroups'
+      required:
+      - description
+      - transactionGroups
+      type: object
     AuthtypesUserRole:
       properties:
         createdAt:
@@ -3938,6 +3994,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesClusterRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -3948,6 +4006,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesDaemonSetRecord:
@@ -4004,6 +4063,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesDaemonSetRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4014,6 +4075,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesDeploymentRecord:
@@ -4070,6 +4132,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesDeploymentRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4080,6 +4144,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesHostFilter:
@@ -4145,6 +4210,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesHostRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4155,6 +4222,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesJobRecord:
@@ -4217,6 +4285,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesJobRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4227,6 +4297,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesNamespaceRecord:
@@ -4261,6 +4332,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesNamespaceRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4271,6 +4344,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesNodeCondition:
@@ -4335,6 +4409,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesNodeRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4345,6 +4421,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesPodCountsByPhase:
@@ -4430,6 +4507,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesPodRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4440,6 +4519,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesPostableClusters:
@@ -4702,6 +4782,16 @@ components:
       - end
       - limit
       type: object
+    InframonitoringtypesRequiredMetricsCheck:
+      properties:
+        missingMetrics:
+          items:
+            type: string
+          nullable: true
+          type: array
+      required:
+      - missingMetrics
+      type: object
     InframonitoringtypesResponseType:
       enum:
       - list
@@ -4761,6 +4851,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesStatefulSetRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4771,6 +4863,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesVolumeRecord:
@@ -4818,6 +4911,8 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesVolumeRecord'
           type: array
+        requiredMetricsCheck:
+          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4828,6 +4923,7 @@ components:
       - type
       - records
       - total
+      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     LlmpricingruletypesGettablePricingRules:
@@ -10213,6 +10309,15 @@ paths:
         name: limit
         schema:
           type: integer
+      - in: query
+        name: q
+        schema:
+          type: string
+      - in: query
+        name: isOverride
+        schema:
+          nullable: true
+          type: boolean
       responses:
         "200":
           content:
@@ -11018,7 +11123,7 @@ paths:
               schema:
                 properties:
                   data:
-                    $ref: '#/components/schemas/AuthtypesRole'
+                    $ref: '#/components/schemas/AuthtypesRoleWithTransactionGroups'
                   status:
                     type: string
                 required:
@@ -11053,7 +11158,7 @@ paths:
       tags:
       - role
     patch:
-      deprecated: false
+      deprecated: true
       description: This endpoint patches a role
       operationId: PatchRole
       parameters:
@@ -11114,6 +11219,68 @@ paths:
       summary: Patch role
       tags:
       - role
+    put:
+      deprecated: false
+      description: This endpoint updates a role
+      operationId: UpdateRole
+      parameters:
+      - in: path
+        name: id
+        required: true
+        schema:
+          type: string
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/AuthtypesUpdatableRole'
+      responses:
+        "204":
+          description: No Content
+        "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
+        "451":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Unavailable For Legal Reasons
+        "500":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Internal Server Error
+        "501":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Not Implemented
+      security:
+      - api_key:
+        - role:update
+      - tokenizer:
+        - role:update
+      summary: Update role
+      tags:
+      - role
   /api/v1/roles/{id}/relations/{relation}/objects:
     get:
       deprecated: false
@@ -11193,7 +11360,7 @@ paths:
       tags:
       - role
     patch:
-      deprecated: false
+      deprecated: true
       description: Patches the objects connected to the specified role via a given
         relation type
       operationId: PatchObjects
@@ -14655,10 +14822,10 @@ paths:
         for custom groupBy keys; in both modes every row aggregates nodes and pods
         in the group. Supports filtering via a filter expression, custom groupBy,
         ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination
-        via offset/limit. Also reports whether the requested time range falls before
-        the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable,
-        clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data
-        is available for that field.'
+        via offset/limit. Also reports missing required metrics and whether the requested
+        time range falls before the data retention boundary. Numeric metric fields
+        (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable)
+        return -1 as a sentinel when no data is available for that field.'
       operationId: ListClusters
       requestBody:
         content:
@@ -14731,11 +14898,11 @@ paths:
         row aggregates pods owned by daemonsets in the group. Supports filtering via
         a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit
         / memory / memory_request / memory_limit / desired_nodes / current_nodes,
-        and pagination via offset/limit. Also reports whether the requested time range
-        falls before the data retention boundary. Numeric metric fields (daemonSetCPU,
-        daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest,
-        daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel
-        when no data is available for that field.'
+        and pagination via offset/limit. Also reports missing required metrics and
+        whether the requested time range falls before the data retention boundary.
+        Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit,
+        daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes,
+        currentNodes) return -1 as a sentinel when no data is available for that field.'
       operationId: ListDaemonSets
       requestBody:
         content:
@@ -14806,11 +14973,11 @@ paths:
         group. Supports filtering via a filter expression, custom groupBy, ordering
         by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit
         / desired_pods / available_pods, and pagination via offset/limit. Also reports
-        whether the requested time range falls before the data retention boundary.
-        Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit,
-        deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods,
-        availablePods) return -1 as a sentinel when no data is available for that
-        field.'
+        missing required metrics and whether the requested time range falls before
+        the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest,
+        deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit,
+        desiredPods, availablePods) return -1 as a sentinel when no data is available
+        for that field.'
       operationId: ListDeployments
       requestBody:
         content:
@@ -14875,9 +15042,10 @@ paths:
         custom groupBy to aggregate hosts by any attribute, ordering by any of the
         five metrics, and pagination via offset/limit. The response type is ''list''
         for the default host.name grouping or ''grouped_list'' for custom groupBy
-        keys. Also reports whether the requested time range falls before the data
-        retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage)
-        return -1 as a sentinel when no data is available for that field.'
+        keys. Also reports missing required metrics and whether the requested time
+        range falls before the data retention boundary. Numeric metric fields (cpu,
+        memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available
+        for that field.'
       operationId: ListHosts
       requestBody:
         content:
@@ -14951,11 +15119,11 @@ paths:
         jobs in the group. Supports filtering via a filter expression, custom groupBy,
         ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit
         / desired_successful_pods / active_pods / failed_pods / successful_pods, and
-        pagination via offset/limit. Also reports whether the requested time range
-        falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest,
-        jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods,
-        activePods, failedPods, successfulPods) return -1 as a sentinel when no data
-        is available for that field.'
+        pagination via offset/limit. Also reports missing required metrics and whether
+        the requested time range falls before the data retention boundary. Numeric
+        metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest,
+        jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods)
+        return -1 as a sentinel when no data is available for that field.'
       operationId: ListJobs
       requestBody:
         content:
@@ -15020,10 +15188,10 @@ paths:
         type is ''list'' for the default k8s.namespace.name grouping or ''grouped_list''
         for custom groupBy keys; in both modes every row aggregates pods in the group.
         Supports filtering via a filter expression, custom groupBy, ordering by cpu
-        / memory, and pagination via offset/limit. Also reports whether the requested
-        time range falls before the data retention boundary. Numeric metric fields
-        (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available
-        for that field.'
+        / memory, and pagination via offset/limit. Also reports missing required metrics
+        and whether the requested time range falls before the data retention boundary.
+        Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel
+        when no data is available for that field.'
       operationId: ListNamespaces
       requestBody:
         content:
@@ -15091,10 +15259,10 @@ paths:
         for custom groupBy keys (each row aggregates nodes in the group; condition
         stays no_data). Supports filtering via a filter expression, custom groupBy,
         ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination
-        via offset/limit. Also reports whether the requested time range falls before
-        the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable,
-        nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is
-        available for that field.'
+        via offset/limit. Also reports missing required metrics and whether the requested
+        time range falls before the data retention boundary. Numeric metric fields
+        (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1
+        as a sentinel when no data is available for that field.'
       operationId: ListNodes
       requestBody:
         content:
@@ -15163,10 +15331,11 @@ paths:
         is one pod with its current phase) or ''grouped_list'' for custom groupBy
         keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase:
         { pending, running, succeeded, failed, unknown } derived from each pod''s
-        latest phase in the window). Also reports whether the requested time range
-        falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest,
-        podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1
-        as a sentinel when no data is available for that field.'
+        latest phase in the window). Also reports missing required metrics and whether
+        the requested time range falls before the data retention boundary. Numeric
+        metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest,
+        podMemoryLimit, podAge) return -1 as a sentinel when no data is available
+        for that field.'
       operationId: ListPods
       requestBody:
         content:
@@ -15233,10 +15402,11 @@ paths:
         usage, inodes, inodes_free, inodes_used), and pagination via offset/limit.
         The response type is ''list'' for the default k8s.persistentvolumeclaim.name
         grouping or ''grouped_list'' for custom groupBy keys; in both modes every
-        row aggregates volumes in the group. Also reports whether the requested time
-        range falls before the data retention boundary. Numeric metric fields (volumeAvailable,
-        volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed)
-        return -1 as a sentinel when no data is available for that field.'
+        row aggregates volumes in the group. Also reports missing required metrics
+        and whether the requested time range falls before the data retention boundary.
+        Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes,
+        volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is
+        available for that field.'
       operationId: ListVolumes
       requestBody:
         content:
@@ -15307,10 +15477,11 @@ paths:
         statefulsets in the group. Supports filtering via a filter expression, custom
         groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request
         / memory_limit / desired_pods / current_pods, and pagination via offset/limit.
-        Also reports whether the requested time range falls before the data retention
-        boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit,
-        statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods,
-        currentPods) return -1 as a sentinel when no data is available for that field.'
+        Also reports missing required metrics and whether the requested time range
+        falls before the data retention boundary. Numeric metric fields (statefulSetCPU,
+        statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest,
+        statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel
+        when no data is available for that field.'
       operationId: ListStatefulSets
       requestBody:
         content:

ee/authz/openfgaauthz/provider.go

@@ -179,13 +179,36 @@ func (provider *provider) CreateManagedUserRoleTransactions(ctx context.Context,
 	return provider.Write(ctx, tuples, nil)
 }
 
-func (provider *provider) Create(ctx context.Context, orgID valuer.UUID, role *authtypes.Role) error {
+func (provider *provider) Create(ctx context.Context, orgID valuer.UUID, role *authtypes.RoleWithTransactionGroups) error {
 	_, err := provider.licensing.GetActive(ctx, orgID)
 	if err != nil {
 		return errors.New(errors.TypeLicenseUnavailable, errors.CodeLicenseUnavailable, "a valid license is not available").WithAdditional("this feature requires a valid license").WithAdditional(err.Error())
 	}
 
-	return provider.store.Create(ctx, role)
+	existingRole, err := provider.GetByOrgIDAndName(ctx, orgID, role.Name)
+	if err != nil && !errors.Asc(err, authtypes.ErrCodeRoleNotFound) {
+		return err
+	}
+
+	if existingRole != nil {
+		return errors.Newf(errors.TypeAlreadyExists, authtypes.ErrCodeRoleAlreadyExists, "role with name: %s already exists", existingRole.Name)
+	}
+
+	tuples, err := authtypes.NewTuplesFromTransactionGroups(role.Name, orgID, role.TransactionGroups)
+	if err != nil {
+		return err
+	}
+
+	err = provider.Write(ctx, tuples, nil)
+	if err != nil {
+		return err
+	}
+
+	if err := provider.store.Create(ctx, role.Role); err != nil {
+		return err
+	}
+
+	return nil
 }
 
 func (provider *provider) GetOrCreate(ctx context.Context, orgID valuer.UUID, role *authtypes.Role) (*authtypes.Role, error) {
@@ -213,6 +236,26 @@ func (provider *provider) GetOrCreate(ctx context.Context, orgID valuer.UUID, ro
 	return role, nil
 }
 
+func (provider *provider) GetWithTransactionGroups(ctx context.Context, orgID valuer.UUID, id valuer.UUID) (*authtypes.RoleWithTransactionGroups, error) {
+	_, err := provider.licensing.GetActive(ctx, orgID)
+	if err != nil {
+		return nil, errors.New(errors.TypeLicenseUnavailable, errors.CodeLicenseUnavailable, "a valid license is not available").WithAdditional("this feature requires a valid license").WithAdditional(err.Error())
+	}
+
+	role, err := provider.store.Get(ctx, orgID, id)
+	if err != nil {
+		return nil, err
+	}
+
+	tuples, err := provider.readAllTuplesForRole(ctx, role.Name, orgID)
+	if err != nil {
+		return nil, err
+	}
+
+	transactionGroups := authtypes.MustNewTransactionGroupsFromTuples(tuples)
+	return authtypes.MakeRoleWithTransactionGroups(role, transactionGroups), nil
+}
+
 func (provider *provider) GetObjects(ctx context.Context, orgID valuer.UUID, id valuer.UUID, relation authtypes.Relation) ([]*coretypes.Object, error) {
 	_, err := provider.licensing.GetActive(ctx, orgID)
 	if err != nil {
@@ -247,6 +290,36 @@ func (provider *provider) GetObjects(ctx context.Context, orgID valuer.UUID, id
 	return objects, nil
 }
 
+func (provider *provider) Update(ctx context.Context, orgID valuer.UUID, updatedRole *authtypes.RoleWithTransactionGroups) error {
+	_, err := provider.licensing.GetActive(ctx, orgID)
+	if err != nil {
+		return errors.New(errors.TypeLicenseUnavailable, errors.CodeLicenseUnavailable, "a valid license is not available").WithAdditional("this feature requires a valid license").WithAdditional(err.Error())
+	}
+
+	existingRole, err := provider.GetWithTransactionGroups(ctx, orgID, updatedRole.ID)
+	if err != nil {
+		return err
+	}
+
+	additions, deletions := existingRole.TransactionGroups.Diff(updatedRole.TransactionGroups)
+	additionTuples, err := authtypes.NewTuplesFromTransactionGroups(existingRole.Name, orgID, additions)
+	if err != nil {
+		return err
+	}
+
+	deletionTuples, err := authtypes.NewTuplesFromTransactionGroups(existingRole.Name, orgID, deletions)
+	if err != nil {
+		return err
+	}
+
+	err = provider.Write(ctx, additionTuples, deletionTuples)
+	if err != nil {
+		return err
+	}
+
+	return provider.store.Update(ctx, orgID, updatedRole.Role)
+}
+
 func (provider *provider) Patch(ctx context.Context, orgID valuer.UUID, role *authtypes.Role) error {
 	_, err := provider.licensing.GetActive(ctx, orgID)
 	if err != nil {
@@ -286,7 +359,7 @@ func (provider *provider) Delete(ctx context.Context, orgID valuer.UUID, id valu
 		return errors.New(errors.TypeLicenseUnavailable, errors.CodeLicenseUnavailable, "a valid license is not available").WithAdditional("this feature requires a valid license").WithAdditional(err.Error())
 	}
 
-	role, err := provider.store.Get(ctx, orgID, id)
+	role, err := provider.GetWithTransactionGroups(ctx, orgID, id)
 	if err != nil {
 		return err
 	}
@@ -302,7 +375,12 @@ func (provider *provider) Delete(ctx context.Context, orgID valuer.UUID, id valu
 		}
 	}
 
-	if err := provider.deleteTuples(ctx, role.Name, orgID); err != nil {
+	tuples, err := authtypes.NewTuplesFromTransactionGroups(role.Name, orgID, role.TransactionGroups)
+	if err != nil {
+		return err
+	}
+
+	if err := provider.Write(ctx, nil, tuples); err != nil {
 		return errors.WithAdditionalf(err, "failed to delete tuples for the role: %s", role.Name)
 	}
 
@@ -361,7 +439,7 @@ func (provider *provider) getManagedRoleTransactionTuples(orgID valuer.UUID) []*
 	return tuples
 }
 
-func (provider *provider) deleteTuples(ctx context.Context, roleName string, orgID valuer.UUID) error {
+func (provider *provider) readAllTuplesForRole(ctx context.Context, roleName string, orgID valuer.UUID) ([]*openfgav1.TupleKey, error) {
 	subject := authtypes.MustNewSubject(coretypes.NewResourceRole(), roleName, orgID, &coretypes.VerbAssignee)
 
 	tuples := make([]*openfgav1.TupleKey, 0)
@@ -371,26 +449,10 @@ func (provider *provider) deleteTuples(ctx context.Context, roleName string, org
 			Object: objectType.StringValue() + ":",
 		})
 		if err != nil {
-			return err
+			return nil, err
 		}
 		tuples = append(tuples, typeTuples...)
 	}
 
-	if len(tuples) == 0 {
-		return nil
-	}
-
-	for idx := 0; idx < len(tuples); idx += provider.config.OpenFGA.MaxTuplesPerWrite {
-		end := idx + provider.config.OpenFGA.MaxTuplesPerWrite
-		if end > len(tuples) {
-			end = len(tuples)
-		}
-
-		err := provider.Write(ctx, nil, tuples[idx:end])
-		if err != nil {
-			return err
-		}
-	}
-
-	return nil
+	return tuples, nil
 }

ee/query-service/app/api/featureFlags.go

@@ -98,6 +98,15 @@ func (ah *APIHandler) getFeatureFlags(w http.ResponseWriter, r *http.Request) {
 		Route:      "",
 	})
 
+	aiObservability := ah.Signoz.Flagger.BooleanOrEmpty(ctx, flagger.FeatureEnableAIObservability, evalCtx)
+	featureSet = append(featureSet, &licensetypes.Feature{
+		Name:       valuer.NewString(flagger.FeatureEnableAIObservability.String()),
+		Active:     aiObservability,
+		Usage:      0,
+		UsageLimit: -1,
+		Route:      "",
+	})
+
 	if constants.IsDotMetricsEnabled {
 		for idx, feature := range featureSet {
 			if feature.Name == licensetypes.DotMetricsEnabled {

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

@@ -39,7 +39,7 @@ import { GeneratedAPIInstance } from '../../../generatedAPIInstance';
 import type { ErrorType, BodyType } from '../../../generatedAPIInstance';
 
 /**
- * Returns a paginated list of Kubernetes clusters with key aggregated metrics derived by summing per-node values within the group: CPU usage, CPU allocatable, memory working set, memory allocatable. Each row also reports per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready value) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each cluster includes metadata attributes (k8s.cluster.name). The response type is 'list' for the default k8s.cluster.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates nodes and pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes clusters with key aggregated metrics derived by summing per-node values within the group: CPU usage, CPU allocatable, memory working set, memory allocatable. Each row also reports per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready value) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each cluster includes metadata attributes (k8s.cluster.name). The response type is 'list' for the default k8s.cluster.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates nodes and pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
  * @summary List Clusters for Infra Monitoring
  */
 export const listClusters = (
@@ -122,7 +122,7 @@ export const useListClusters = <
 	return useMutation(getListClustersMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes DaemonSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the daemonset, plus average CPU/memory request and limit utilization (daemonSetCPURequest, daemonSetCPULimit, daemonSetMemoryRequest, daemonSetMemoryLimit). Each row also reports the latest known node-level counters from kube-state-metrics: desiredNodes (k8s.daemonset.desired_scheduled_nodes, the number of nodes the daemonset wants to run on) and currentNodes (k8s.daemonset.current_scheduled_nodes, the number of nodes the daemonset currently runs on) — note these are node counts, not pod counts. It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each daemonset includes metadata attributes (k8s.daemonset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.daemonset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by daemonsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_nodes / current_nodes, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes DaemonSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the daemonset, plus average CPU/memory request and limit utilization (daemonSetCPURequest, daemonSetCPULimit, daemonSetMemoryRequest, daemonSetMemoryLimit). Each row also reports the latest known node-level counters from kube-state-metrics: desiredNodes (k8s.daemonset.desired_scheduled_nodes, the number of nodes the daemonset wants to run on) and currentNodes (k8s.daemonset.current_scheduled_nodes, the number of nodes the daemonset currently runs on) — note these are node counts, not pod counts. It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each daemonset includes metadata attributes (k8s.daemonset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.daemonset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by daemonsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_nodes / current_nodes, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel when no data is available for that field.
  * @summary List DaemonSets for Infra Monitoring
  */
 export const listDaemonSets = (
@@ -205,7 +205,7 @@ export const useListDaemonSets = <
 	return useMutation(getListDaemonSetsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes Deployments with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the deployment, plus average CPU/memory request and limit utilization (deploymentCPURequest, deploymentCPULimit, deploymentMemoryRequest, deploymentMemoryLimit). Each row also reports the latest known desiredPods (k8s.deployment.desired) and availablePods (k8s.deployment.available) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each deployment includes metadata attributes (k8s.deployment.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.deployment.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by deployments in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / available_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods, availablePods) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes Deployments with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the deployment, plus average CPU/memory request and limit utilization (deploymentCPURequest, deploymentCPULimit, deploymentMemoryRequest, deploymentMemoryLimit). Each row also reports the latest known desiredPods (k8s.deployment.desired) and availablePods (k8s.deployment.available) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each deployment includes metadata attributes (k8s.deployment.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.deployment.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by deployments in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / available_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods, availablePods) return -1 as a sentinel when no data is available for that field.
  * @summary List Deployments for Infra Monitoring
  */
 export const listDeployments = (
@@ -288,7 +288,7 @@ export const useListDeployments = <
 	return useMutation(getListDeploymentsMutationOptions(options));
 };
 /**
- * Returns a paginated list of hosts with key infrastructure metrics: CPU usage (%), memory usage (%), I/O wait (%), disk usage (%), and 15-minute load average. Each host includes its current status (active/inactive based on metrics reported in the last 10 minutes) and metadata attributes (e.g., os.type). Supports filtering via a filter expression, filtering by host status, custom groupBy to aggregate hosts by any attribute, ordering by any of the five metrics, and pagination via offset/limit. The response type is 'list' for the default host.name grouping or 'grouped_list' for custom groupBy keys. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of hosts with key infrastructure metrics: CPU usage (%), memory usage (%), I/O wait (%), disk usage (%), and 15-minute load average. Each host includes its current status (active/inactive based on metrics reported in the last 10 minutes) and metadata attributes (e.g., os.type). Supports filtering via a filter expression, filtering by host status, custom groupBy to aggregate hosts by any attribute, ordering by any of the five metrics, and pagination via offset/limit. The response type is 'list' for the default host.name grouping or 'grouped_list' for custom groupBy keys. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available for that field.
  * @summary List Hosts for Infra Monitoring
  */
 export const listHosts = (
@@ -371,7 +371,7 @@ export const useListHosts = <
 	return useMutation(getListHostsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes Jobs with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the job, plus average CPU/memory request and limit utilization (jobCPURequest, jobCPULimit, jobMemoryRequest, jobMemoryLimit). Each row also reports the latest known job-level counters from kube-state-metrics: desiredSuccessfulPods (k8s.job.desired_successful_pods, the target completion count), activePods (k8s.job.active_pods), failedPods (k8s.job.failed_pods, cumulative across the lifetime of the job), and successfulPods (k8s.job.successful_pods, cumulative). It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value); note podCountsByPhase.failed (current pod-phase) is distinct from failedPods (cumulative job kube-state-metric). Each job includes metadata attributes (k8s.job.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.job.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by jobs in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_successful_pods / active_pods / failed_pods / successful_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes Jobs with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the job, plus average CPU/memory request and limit utilization (jobCPURequest, jobCPULimit, jobMemoryRequest, jobMemoryLimit). Each row also reports the latest known job-level counters from kube-state-metrics: desiredSuccessfulPods (k8s.job.desired_successful_pods, the target completion count), activePods (k8s.job.active_pods), failedPods (k8s.job.failed_pods, cumulative across the lifetime of the job), and successfulPods (k8s.job.successful_pods, cumulative). It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value); note podCountsByPhase.failed (current pod-phase) is distinct from failedPods (cumulative job kube-state-metric). Each job includes metadata attributes (k8s.job.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.job.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by jobs in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_successful_pods / active_pods / failed_pods / successful_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods) return -1 as a sentinel when no data is available for that field.
  * @summary List Jobs for Infra Monitoring
  */
 export const listJobs = (
@@ -454,7 +454,7 @@ export const useListJobs = <
 	return useMutation(getListJobsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes namespaces with key aggregated pod metrics: CPU usage and memory working set (summed across pods in the group), plus per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value in the window). Each namespace includes metadata attributes (k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.namespace.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / memory, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes namespaces with key aggregated pod metrics: CPU usage and memory working set (summed across pods in the group), plus per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value in the window). Each namespace includes metadata attributes (k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.namespace.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / memory, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available for that field.
  * @summary List Namespaces for Infra Monitoring
  */
 export const listNamespaces = (
@@ -537,7 +537,7 @@ export const useListNamespaces = <
 	return useMutation(getListNamespacesMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes nodes with key metrics: CPU usage, CPU allocatable, memory working set, memory allocatable, per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready in the window) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } for pods scheduled on the listed nodes). Each node includes metadata attributes (k8s.node.uid, k8s.cluster.name). The response type is 'list' for the default k8s.node.name grouping (each row is one node with its current condition string: ready / not_ready / no_data) or 'grouped_list' for custom groupBy keys (each row aggregates nodes in the group; condition stays no_data). Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes nodes with key metrics: CPU usage, CPU allocatable, memory working set, memory allocatable, per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready in the window) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } for pods scheduled on the listed nodes). Each node includes metadata attributes (k8s.node.uid, k8s.cluster.name). The response type is 'list' for the default k8s.node.name grouping (each row is one node with its current condition string: ready / not_ready / no_data) or 'grouped_list' for custom groupBy keys (each row aggregates nodes in the group; condition stays no_data). Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
  * @summary List Nodes for Infra Monitoring
  */
 export const listNodes = (
@@ -620,7 +620,7 @@ export const useListNodes = <
 	return useMutation(getListNodesMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes pods with key metrics: CPU usage, CPU request/limit utilization, memory working set, memory request/limit utilization, current pod phase (pending/running/succeeded/failed/unknown/no_data), and pod age (ms since start time). Each pod includes metadata attributes (namespace, node, workload owner such as deployment/statefulset/daemonset/job/cronjob, cluster). Supports filtering via a filter expression, custom groupBy to aggregate pods by any attribute, ordering by any of the six metrics (cpu, cpu_request, cpu_limit, memory, memory_request, memory_limit), and pagination via offset/limit. The response type is 'list' for the default k8s.pod.uid grouping (each row is one pod with its current phase) or 'grouped_list' for custom groupBy keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase: { pending, running, succeeded, failed, unknown } derived from each pod's latest phase in the window). Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes pods with key metrics: CPU usage, CPU request/limit utilization, memory working set, memory request/limit utilization, current pod phase (pending/running/succeeded/failed/unknown/no_data), and pod age (ms since start time). Each pod includes metadata attributes (namespace, node, workload owner such as deployment/statefulset/daemonset/job/cronjob, cluster). Supports filtering via a filter expression, custom groupBy to aggregate pods by any attribute, ordering by any of the six metrics (cpu, cpu_request, cpu_limit, memory, memory_request, memory_limit), and pagination via offset/limit. The response type is 'list' for the default k8s.pod.uid grouping (each row is one pod with its current phase) or 'grouped_list' for custom groupBy keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase: { pending, running, succeeded, failed, unknown } derived from each pod's latest phase in the window). Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1 as a sentinel when no data is available for that field.
  * @summary List Pods for Infra Monitoring
  */
 export const listPods = (
@@ -703,7 +703,7 @@ export const useListPods = <
 	return useMutation(getListPodsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes persistent volume claims (PVCs) with key volume metrics: available bytes, capacity bytes, usage (capacity - available), inodes, free inodes, and used inodes. Each row also includes metadata attributes (k8s.persistentvolumeclaim.name, k8s.pod.uid, k8s.pod.name, k8s.namespace.name, k8s.node.name, k8s.statefulset.name, k8s.cluster.name). Supports filtering via a filter expression, custom groupBy to aggregate volumes by any attribute, ordering by any of the six metrics (available, capacity, usage, inodes, inodes_free, inodes_used), and pagination via offset/limit. The response type is 'list' for the default k8s.persistentvolumeclaim.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates volumes in the group. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes persistent volume claims (PVCs) with key volume metrics: available bytes, capacity bytes, usage (capacity - available), inodes, free inodes, and used inodes. Each row also includes metadata attributes (k8s.persistentvolumeclaim.name, k8s.pod.uid, k8s.pod.name, k8s.namespace.name, k8s.node.name, k8s.statefulset.name, k8s.cluster.name). Supports filtering via a filter expression, custom groupBy to aggregate volumes by any attribute, ordering by any of the six metrics (available, capacity, usage, inodes, inodes_free, inodes_used), and pagination via offset/limit. The response type is 'list' for the default k8s.persistentvolumeclaim.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates volumes in the group. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is available for that field.
  * @summary List Volumes for Infra Monitoring
  */
 export const listVolumes = (
@@ -786,7 +786,7 @@ export const useListVolumes = <
 	return useMutation(getListVolumesMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes StatefulSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the statefulset, plus average CPU/memory request and limit utilization (statefulSetCPURequest, statefulSetCPULimit, statefulSetMemoryRequest, statefulSetMemoryLimit). Each row also reports the latest known desiredPods (k8s.statefulset.desired_pods) and currentPods (k8s.statefulset.current_pods) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each statefulset includes metadata attributes (k8s.statefulset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.statefulset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by statefulsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / current_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes StatefulSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the statefulset, plus average CPU/memory request and limit utilization (statefulSetCPURequest, statefulSetCPULimit, statefulSetMemoryRequest, statefulSetMemoryLimit). Each row also reports the latest known desiredPods (k8s.statefulset.desired_pods) and currentPods (k8s.statefulset.current_pods) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each statefulset includes metadata attributes (k8s.statefulset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.statefulset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by statefulsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / current_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel when no data is available for that field.
  * @summary List StatefulSets for Infra Monitoring
  */
 export const listStatefulSets = (

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

@@ -20,6 +20,7 @@ import type {
 import type {
 	AuthtypesPatchableRoleDTO,
 	AuthtypesPostableRoleDTO,
+	AuthtypesUpdatableRoleDTO,
 	CoretypesPatchableObjectsDTO,
 	CreateRole201,
 	DeleteRolePathParameters,
@@ -31,6 +32,7 @@ import type {
 	PatchObjectsPathParameters,
 	PatchRolePathParameters,
 	RenderErrorResponseDTO,
+	UpdateRolePathParameters,
 } from '../sigNoz.schemas';
 
 import { GeneratedAPIInstance } from '../../../generatedAPIInstance';
@@ -365,6 +367,7 @@ export const invalidateGetRole = async (
 
 /**
  * This endpoint patches a role
+ * @deprecated
  * @summary Patch role
  */
 export const patchRole = (
@@ -436,6 +439,7 @@ export type PatchRoleMutationBody =
 export type PatchRoleMutationError = ErrorType<RenderErrorResponseDTO>;
 
 /**
+ * @deprecated
  * @summary Patch role
  */
 export const usePatchRole = <
@@ -462,6 +466,105 @@ export const usePatchRole = <
 > => {
 	return useMutation(getPatchRoleMutationOptions(options));
 };
+/**
+ * This endpoint updates a role
+ * @summary Update role
+ */
+export const updateRole = (
+	{ id }: UpdateRolePathParameters,
+	authtypesUpdatableRoleDTO?: BodyType<AuthtypesUpdatableRoleDTO>,
+	signal?: AbortSignal,
+) => {
+	return GeneratedAPIInstance<void>({
+		url: `/api/v1/roles/${id}`,
+		method: 'PUT',
+		headers: { 'Content-Type': 'application/json' },
+		data: authtypesUpdatableRoleDTO,
+		signal,
+	});
+};
+
+export const getUpdateRoleMutationOptions = <
+	TError = ErrorType<RenderErrorResponseDTO>,
+	TContext = unknown,
+>(options?: {
+	mutation?: UseMutationOptions<
+		Awaited<ReturnType<typeof updateRole>>,
+		TError,
+		{
+			pathParams: UpdateRolePathParameters;
+			data?: BodyType<AuthtypesUpdatableRoleDTO>;
+		},
+		TContext
+	>;
+}): UseMutationOptions<
+	Awaited<ReturnType<typeof updateRole>>,
+	TError,
+	{
+		pathParams: UpdateRolePathParameters;
+		data?: BodyType<AuthtypesUpdatableRoleDTO>;
+	},
+	TContext
+> => {
+	const mutationKey = ['updateRole'];
+	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 updateRole>>,
+		{
+			pathParams: UpdateRolePathParameters;
+			data?: BodyType<AuthtypesUpdatableRoleDTO>;
+		}
+	> = (props) => {
+		const { pathParams, data } = props ?? {};
+
+		return updateRole(pathParams, data);
+	};
+
+	return { mutationFn, ...mutationOptions };
+};
+
+export type UpdateRoleMutationResult = NonNullable<
+	Awaited<ReturnType<typeof updateRole>>
+>;
+export type UpdateRoleMutationBody =
+	| BodyType<AuthtypesUpdatableRoleDTO>
+	| undefined;
+export type UpdateRoleMutationError = ErrorType<RenderErrorResponseDTO>;
+
+/**
+ * @summary Update role
+ */
+export const useUpdateRole = <
+	TError = ErrorType<RenderErrorResponseDTO>,
+	TContext = unknown,
+>(options?: {
+	mutation?: UseMutationOptions<
+		Awaited<ReturnType<typeof updateRole>>,
+		TError,
+		{
+			pathParams: UpdateRolePathParameters;
+			data?: BodyType<AuthtypesUpdatableRoleDTO>;
+		},
+		TContext
+	>;
+}): UseMutationResult<
+	Awaited<ReturnType<typeof updateRole>>,
+	TError,
+	{
+		pathParams: UpdateRolePathParameters;
+		data?: BodyType<AuthtypesUpdatableRoleDTO>;
+	},
+	TContext
+> => {
+	return useMutation(getUpdateRoleMutationOptions(options));
+};
 /**
  * Gets all objects connected to the specified role via a given relation type
  * @summary Get objects for a role by relation
@@ -565,6 +668,7 @@ export const invalidateGetObjects = async (
 
 /**
  * Patches the objects connected to the specified role via a given relation type
+ * @deprecated
  * @summary Patch objects for a role by relation
  */
 export const patchObjects = (
@@ -636,6 +740,7 @@ export type PatchObjectsMutationBody =
 export type PatchObjectsMutationError = ErrorType<RenderErrorResponseDTO>;
 
 /**
+ * @deprecated
  * @summary Patch objects for a role by relation
  */
 export const usePatchObjects = <

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

@@ -2224,15 +2224,31 @@ export interface AuthtypesPostableEmailPasswordSessionDTO {
 	password?: string;
 }
 
+export interface CoretypesObjectGroupDTO {
+	resource: CoretypesResourceRefDTO;
+	/**
+	 * @type array
+	 */
+	selectors: string[];
+}
+
+export interface AuthtypesTransactionGroupDTO {
+	objectGroup: CoretypesObjectGroupDTO;
+	relation: AuthtypesRelationDTO;
+}
+
+export type AuthtypesTransactionGroupsDTO = AuthtypesTransactionGroupDTO[];
+
 export interface AuthtypesPostableRoleDTO {
 	/**
 	 * @type string
 	 */
-	description?: string;
+	description: string;
 	/**
 	 * @type string
 	 */
 	name: string;
+	transactionGroups: AuthtypesTransactionGroupsDTO;
 }
 
 export interface AuthtypesPostableRotateTokenDTO {
@@ -2275,6 +2291,40 @@ export interface AuthtypesRoleDTO {
 	updatedAt?: string;
 }
 
+export interface AuthtypesRoleWithTransactionGroupsDTO {
+	/**
+	 * @type string
+	 * @format date-time
+	 */
+	createdAt?: string;
+	/**
+	 * @type string
+	 */
+	description: string;
+	/**
+	 * @type string
+	 */
+	id: string;
+	/**
+	 * @type string
+	 */
+	name: string;
+	/**
+	 * @type string
+	 */
+	orgId: string;
+	transactionGroups: AuthtypesTransactionGroupsDTO;
+	/**
+	 * @type string
+	 */
+	type: string;
+	/**
+	 * @type string
+	 * @format date-time
+	 */
+	updatedAt?: string;
+}
+
 export interface AuthtypesSessionContextDTO {
 	/**
 	 * @type boolean
@@ -2295,6 +2345,14 @@ export interface AuthtypesUpdatableAuthDomainDTO {
 	config?: AuthtypesAuthDomainConfigDTO;
 }
 
+export interface AuthtypesUpdatableRoleDTO {
+	/**
+	 * @type string
+	 */
+	description: string;
+	transactionGroups: AuthtypesTransactionGroupsDTO;
+}
+
 export interface AuthtypesUserRoleDTO {
 	/**
 	 * @type string
@@ -3065,14 +3123,6 @@ export interface CommonJSONRefDTO {
 	$ref?: string;
 }
 
-export interface CoretypesObjectGroupDTO {
-	resource: CoretypesResourceRefDTO;
-	/**
-	 * @type array
-	 */
-	selectors: string[];
-}
-
 export interface CoretypesPatchableObjectsDTO {
 	/**
 	 * @type array,null
@@ -5423,6 +5473,13 @@ export interface InframonitoringtypesClusterRecordDTO {
 	podCountsByPhase: InframonitoringtypesPodCountsByPhaseDTO;
 }
 
+export interface InframonitoringtypesRequiredMetricsCheckDTO {
+	/**
+	 * @type array,null
+	 */
+	missingMetrics: string[] | null;
+}
+
 export enum InframonitoringtypesResponseTypeDTO {
 	list = 'list',
 	grouped_list = 'grouped_list',
@@ -5458,6 +5515,7 @@ export interface InframonitoringtypesClustersDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesClusterRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5535,6 +5593,7 @@ export interface InframonitoringtypesDaemonSetsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesDaemonSetRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5612,6 +5671,7 @@ export interface InframonitoringtypesDeploymentsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesDeploymentRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5697,6 +5757,7 @@ export interface InframonitoringtypesHostsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesHostRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5782,6 +5843,7 @@ export interface InframonitoringtypesJobsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesJobRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5831,6 +5893,7 @@ export interface InframonitoringtypesNamespacesDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesNamespaceRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5897,6 +5960,7 @@ export interface InframonitoringtypesNodesDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesNodeRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5980,6 +6044,7 @@ export interface InframonitoringtypesPodsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesPodRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -6327,6 +6392,7 @@ export interface InframonitoringtypesStatefulSetsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesStatefulSetRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -6395,6 +6461,7 @@ export interface InframonitoringtypesVolumesDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesVolumeRecordDTO[];
+	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -9433,6 +9500,16 @@ export type ListLLMPricingRulesParams = {
 	 * @description undefined
 	 */
 	limit?: number;
+	/**
+	 * @type string
+	 * @description undefined
+	 */
+	q?: string;
+	/**
+	 * @type boolean,null
+	 * @description undefined
+	 */
+	isOverride?: boolean | null;
 };
 
 export type ListLLMPricingRules200 = {
@@ -9542,7 +9619,7 @@ export type GetRolePathParameters = {
 	id: string;
 };
 export type GetRole200 = {
-	data: AuthtypesRoleDTO;
+	data: AuthtypesRoleWithTransactionGroupsDTO;
 	/**
 	 * @type string
 	 */
@@ -9552,6 +9629,9 @@ export type GetRole200 = {
 export type PatchRolePathParameters = {
 	id: string;
 };
+export type UpdateRolePathParameters = {
+	id: string;
+};
 export type GetObjectsPathParameters = {
 	id: string;
 	relation: string;

frontend/src/api/v5/queryRange/convertV5Response.test.ts

@@ -274,4 +274,110 @@ describe('convertV5ResponseToLegacy', () => {
 			},
 		});
 	});
+
+	it('clickhouse_sql scalar keeps each value column distinct (regression: all-"A" collapse)', () => {
+		const scalar: ScalarData = {
+			columns: [
+				{
+					name: 'service.name',
+					queryName: 'A',
+					aggregationIndex: 0,
+					columnType: 'group',
+				} as unknown as ScalarData['columns'][number],
+				{
+					name: 'current_availability',
+					queryName: 'A',
+					aggregationIndex: 0,
+					columnType: 'aggregation',
+				} as unknown as ScalarData['columns'][number],
+				{
+					name: 'error_budget_remaining',
+					queryName: 'A',
+					aggregationIndex: 1,
+					columnType: 'aggregation',
+				} as unknown as ScalarData['columns'][number],
+				{
+					name: 'budget_status',
+					queryName: 'A',
+					aggregationIndex: 2,
+					columnType: 'group',
+				} as unknown as ScalarData['columns'][number],
+				{
+					name: 'total_requests',
+					queryName: 'A',
+					aggregationIndex: 4,
+					columnType: 'aggregation',
+				} as unknown as ScalarData['columns'][number],
+			],
+			data: [['kuja-api_gateway-service', 99.985, 0.985, 'Healthy ✅', 2181216]],
+		};
+
+		const v5Data: QueryRangeResponseV5 = {
+			type: 'scalar',
+			data: { results: [scalar] },
+			meta: { rowsScanned: 0, bytesScanned: 0, durationMs: 0, stepIntervals: {} },
+		};
+
+		// A clickhouse_sql envelope contributes no aggregation metadata.
+		const params = makeBaseParams('scalar', [
+			{
+				type: 'clickhouse_sql',
+				spec: {
+					name: 'A',
+					query: 'SELECT ...',
+					disabled: false,
+				},
+			} as unknown as QueryRangeRequestV5['compositeQuery']['queries'][number],
+		]);
+
+		const input: SuccessResponse<MetricRangePayloadV5, QueryRangeRequestV5> =
+			makeBaseSuccess({ data: v5Data }, params);
+		// formatForWeb=true is the table-panel path.
+		const result = convertV5ResponseToLegacy(input, { A: '' }, true);
+
+		const [tableEntry] = result.payload.data.result;
+		// Headers keep their real names instead of collapsing to "A".
+		expect(tableEntry.table?.columns).toStrictEqual([
+			{
+				name: 'service.name',
+				queryName: 'A',
+				isValueColumn: false,
+				id: 'service.name',
+			},
+			{
+				name: 'current_availability',
+				queryName: 'A',
+				isValueColumn: true,
+				id: 'current_availability',
+			},
+			{
+				name: 'error_budget_remaining',
+				queryName: 'A',
+				isValueColumn: true,
+				id: 'error_budget_remaining',
+			},
+			{
+				name: 'budget_status',
+				queryName: 'A',
+				isValueColumn: false,
+				id: 'budget_status',
+			},
+			{
+				name: 'total_requests',
+				queryName: 'A',
+				isValueColumn: true,
+				id: 'total_requests',
+			},
+		]);
+		// Ids are unique, so value columns don't overwrite each other in the row.
+		expect(tableEntry.table?.rows?.[0]).toStrictEqual({
+			data: {
+				'service.name': 'kuja-api_gateway-service',
+				current_availability: 99.985,
+				error_budget_remaining: 0.985,
+				budget_status: 'Healthy ✅',
+				total_requests: 2181216,
+			},
+		});
+	});
 });

frontend/src/api/v5/queryRange/convertV5Response.ts

@@ -15,6 +15,7 @@ function getColName(
 	col: ScalarData['columns'][number],
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
+	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
@@ -39,16 +40,32 @@ function getColName(
 		return alias || expression || col.queryName;
 	}
 
+	// clickhouse_sql value columns carry their real SQL alias in col.name — use
+	// it so each value column keeps its own header instead of collapsing onto
+	// the query name. Formulas/promql use placeholder names, so they fall back
+	// to legend || queryName.
+	if (clickhouseQueryNames.has(col.queryName)) {
+		return col.name;
+	}
 	return legend || col.queryName;
 }
 
 function getColId(
 	col: ScalarData['columns'][number],
 	aggregationPerQuery: Record<string, any>,
+	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
 	}
+
+	// clickhouse_sql value columns are keyed by their real SQL alias so multiple
+	// value columns stay unique instead of all collapsing onto the query name
+	// (which would overwrite every cell in the row with the last column's value).
+	if (clickhouseQueryNames.has(col.queryName)) {
+		return col.name;
+	}
+
 	const aggregation =
 		aggregationPerQuery?.[col.queryName]?.[col.aggregationIndex];
 	const expression = aggregation?.expression || '';
@@ -141,6 +158,7 @@ function convertScalarDataArrayToTable(
 	scalarDataArray: ScalarData[],
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
+	clickhouseQueryNames: Set<string>,
 ): QueryDataV3[] {
 	// If no scalar data, return empty structure
 
@@ -166,10 +184,10 @@ function convertScalarDataArrayToTable(
 
 		// Collect columns for this specific query
 		const columns = scalarData?.columns?.map((col) => ({
-			name: getColName(col, legendMap, aggregationPerQuery),
+			name: getColName(col, legendMap, aggregationPerQuery, clickhouseQueryNames),
 			queryName: col.queryName,
 			isValueColumn: col.columnType === 'aggregation',
-			id: getColId(col, aggregationPerQuery),
+			id: getColId(col, aggregationPerQuery, clickhouseQueryNames),
 		}));
 
 		// Process rows for this specific query
@@ -177,8 +195,13 @@ function convertScalarDataArrayToTable(
 			const rowData: Record<string, any> = {};
 
 			scalarData?.columns?.forEach((col, colIndex) => {
-				const columnName = getColName(col, legendMap, aggregationPerQuery);
-				const columnId = getColId(col, aggregationPerQuery);
+				const columnName = getColName(
+					col,
+					legendMap,
+					aggregationPerQuery,
+					clickhouseQueryNames,
+				);
+				const columnId = getColId(col, aggregationPerQuery, clickhouseQueryNames);
 				rowData[columnId || columnName] = dataRow[colIndex];
 			});
 
@@ -202,6 +225,7 @@ function convertScalarWithFormatForWeb(
 	scalarDataArray: ScalarData[],
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
+	clickhouseQueryNames: Set<string>,
 ): QueryDataV3[] {
 	if (!scalarDataArray || scalarDataArray.length === 0) {
 		return [];
@@ -210,13 +234,18 @@ function convertScalarWithFormatForWeb(
 	return scalarDataArray.map((scalarData) => {
 		const columns =
 			scalarData.columns?.map((col) => {
-				const colName = getColName(col, legendMap, aggregationPerQuery);
+				const colName = getColName(
+					col,
+					legendMap,
+					aggregationPerQuery,
+					clickhouseQueryNames,
+				);
 
 				return {
 					name: colName,
 					queryName: col.queryName,
 					isValueColumn: col.columnType === 'aggregation',
-					id: getColId(col, aggregationPerQuery),
+					id: getColId(col, aggregationPerQuery, clickhouseQueryNames),
 				};
 			}) || [];
 
@@ -289,6 +318,7 @@ function convertV5DataByType(
 	v5Data: any,
 	legendMap: Record<string, string>,
 	aggregationPerQuery: Record<string, any>,
+	clickhouseQueryNames: Set<string>,
 ): MetricRangePayloadV3['data'] {
 	switch (v5Data?.type) {
 		case 'time_series': {
@@ -307,6 +337,7 @@ function convertV5DataByType(
 				scalarData,
 				legendMap,
 				aggregationPerQuery,
+				clickhouseQueryNames,
 			);
 			return {
 				resultType: 'scalar',
@@ -373,6 +404,15 @@ export function convertV5ResponseToLegacy(
 				{} as Record<string, any>,
 			) || {};
 
+	// clickhouse_sql queries have no aggregation metadata; their value columns
+	// are named/keyed by the real SQL alias the response carries (see getColId).
+	const clickhouseQueryNames = new Set<string>(
+		(params?.compositeQuery?.queries ?? [])
+			.filter((query) => query.type === 'clickhouse_sql')
+			.map((query) => (query.spec as { name?: string })?.name)
+			.filter((name): name is string => !!name),
+	);
+
 	// If formatForWeb is true, return as-is (like existing logic)
 	if (formatForWeb && v5Data?.type === 'scalar') {
 		const scalarData = v5Data.data.results as ScalarData[];
@@ -380,6 +420,7 @@ export function convertV5ResponseToLegacy(
 			scalarData,
 			legendMap,
 			aggregationPerQuery,
+			clickhouseQueryNames,
 		);
 
 		return {
@@ -402,6 +443,7 @@ export function convertV5ResponseToLegacy(
 		v5Data,
 		legendMap,
 		aggregationPerQuery,
+		clickhouseQueryNames,
 	);
 
 	// Create legacy-compatible response structure

frontend/src/constants/features.ts

@@ -12,4 +12,5 @@ export enum FeatureKeys {
 	USE_JSON_BODY = 'use_json_body',
 	USE_FINE_GRAINED_AUTHZ = 'use_fine_grained_authz',
 	USE_DASHBOARD_V2 = 'use_dashboard_v2',
+	EMABLE_AI_OBSERVABILITY = 'enable_ai_observability',
 }

frontend/src/container/RolesSettings/RolesComponents/CreateRoleModal.tsx

@@ -116,7 +116,8 @@ function CreateRoleModal({
 			} else {
 				const data: AuthtypesPostableRoleDTO = {
 					name: values.name,
-					...(values.description ? { description: values.description } : {}),
+					description: values.description || '',
+					transactionGroups: [],
 				};
 				createRole({ data });
 			}

frontend/src/pages/DashboardPageV2/DashboardContainer/queryV5/__tests__/prepareScalarTables.test.ts

@@ -5,6 +5,7 @@ import type {
 
 import {
 	extractAggregationsPerQuery,
+	extractClickhouseQueryNames,
 	prepareScalarTables,
 } from '../prepareScalarTables';
 
@@ -56,6 +57,24 @@ describe('extractAggregationsPerQuery', () => {
 	});
 });
 
+describe('extractClickhouseQueryNames', () => {
+	it('collects names of clickhouse_sql queries, ignoring other envelope types', () => {
+		const request = requestWith([
+			{ type: 'clickhouse_sql', spec: { name: 'A', query: 'SELECT 1' } },
+			{
+				type: 'builder_query',
+				spec: { name: 'B', aggregations: [{ expression: 'count()' }] },
+			},
+			{ type: 'promql', spec: { name: 'P', query: 'up' } },
+		]);
+		expect(extractClickhouseQueryNames(request)).toStrictEqual(new Set(['A']));
+	});
+
+	it('returns an empty set for an undefined payload', () => {
+		expect(extractClickhouseQueryNames(undefined)).toStrictEqual(new Set());
+	});
+});
+
 describe('prepareScalarTables', () => {
 	it('builds keyed rows with group + aggregation columns (V1 getColName/getColId parity)', () => {
 		const [table] = prepareScalarTables({
@@ -194,18 +213,115 @@ describe('prepareScalarTables', () => {
 		expect(tables.map((t) => t.queryName)).toStrictEqual(['A', 'B']);
 	});
 
-	it('queries without aggregation metadata fall back to legend || queryName', () => {
+	it('clickhouse_sql single value column uses the SQL alias over the legend', () => {
 		const [table] = prepareScalarTables({
 			results: [
+				scalarResult(
+					[
+						{
+							name: 'current_availability',
+							queryName: 'A',
+							columnType: 'aggregation',
+						},
+					],
+					[],
+				),
+			],
+			legendMap: { A: 'Legend' },
+			requestPayload: requestWith([
+				{ type: 'clickhouse_sql', spec: { name: 'A', query: 'SELECT ...' } },
+			]),
+		});
+		// The query is clickhouse_sql, so the response column's real SQL alias is
+		// used for both header and key (a single legend can't be the column name).
+		expect(table.columns[0].name).toBe('current_availability');
+		expect(table.columns[0].id).toBe('current_availability');
+	});
+
+	it('non-clickhouse query without aggregation metadata falls back to legend || queryName', () => {
+		const [table] = prepareScalarTables({
+			results: [
+				// Formulas/promql carry placeholder names and are not clickhouse_sql,
+				// so they must not adopt the response column name.
 				scalarResult(
 					[{ name: '__result_0', queryName: 'A', columnType: 'aggregation' }],
 					[],
 				),
 			],
 			legendMap: { A: 'Legend' },
-			requestPayload: requestWith([]),
+			requestPayload: requestWith([
+				{ type: 'promql', spec: { name: 'A', query: 'up' } },
+			]),
 		});
 		expect(table.columns[0].name).toBe('Legend');
 		expect(table.columns[0].id).toBe('A');
 	});
+
+	it('clickhouse_sql query keeps each value column distinct (regression: all-"A" collapse)', () => {
+		const [table] = prepareScalarTables({
+			results: [
+				scalarResult(
+					[
+						{ name: 'service.name', queryName: 'A', columnType: 'group' },
+						{
+							name: 'current_availability',
+							queryName: 'A',
+							columnType: 'aggregation',
+							aggregationIndex: 0,
+						},
+						{
+							name: 'error_budget_remaining',
+							queryName: 'A',
+							columnType: 'aggregation',
+							aggregationIndex: 1,
+						},
+						{ name: 'budget_status', queryName: 'A', columnType: 'group' },
+						{
+							name: 'total_requests',
+							queryName: 'A',
+							columnType: 'aggregation',
+							aggregationIndex: 4,
+						},
+					],
+					[['kuja-api_gateway-service', 99.985, 0.985, 'Healthy ✅', 2181216]],
+				),
+			],
+			legendMap: { A: '' },
+			// A clickhouse_sql envelope contributes no aggregation metadata.
+			requestPayload: requestWith([
+				{
+					type: 'clickhouse_sql',
+					spec: { name: 'A', query: 'SELECT ...' },
+				},
+			]),
+		});
+
+		// Headers keep their real names instead of collapsing to "A".
+		expect(table.columns.map((col) => col.name)).toStrictEqual([
+			'service.name',
+			'current_availability',
+			'error_budget_remaining',
+			'budget_status',
+			'total_requests',
+		]);
+		// Ids are unique, so value columns don't overwrite each other in the row.
+		expect(table.columns.map((col) => col.id)).toStrictEqual([
+			'service.name',
+			'current_availability',
+			'error_budget_remaining',
+			'budget_status',
+			'total_requests',
+		]);
+		expect(table.rows).toStrictEqual([
+			{
+				data: {
+					'service.name': 'kuja-api_gateway-service',
+					current_availability: 99.985,
+					error_budget_remaining: 0.985,
+					budget_status: 'Healthy ✅',
+					total_requests: 2181216,
+				},
+			},
+		]);
+	});
 });

frontend/src/pages/DashboardPageV2/DashboardContainer/queryV5/prepareScalarTables.ts

@@ -1,5 +1,6 @@
 import type {
 	Querybuildertypesv5ColumnDescriptorDTO,
+	Querybuildertypesv5QueryEnvelopeClickHouseSQLDTO,
 	Querybuildertypesv5QueryRangeRequestDTO,
 	Querybuildertypesv5ScalarDataDTO,
 } from 'api/generated/services/sigNoz.schemas';
@@ -44,16 +45,43 @@ export function extractAggregationsPerQuery(
 	return perQuery;
 }
 
+/**
+ * Names of the request's clickhouse_sql queries. These have no aggregation
+ * metadata, but their value columns carry the user's real SQL alias in the
+ * response `col.name` — so columns of these queries are named/keyed by that
+ * alias rather than collapsing onto the query name. Builder/formula/promql use
+ * placeholder names (`__result`/`__result_N`) and are excluded here.
+ */
+export function extractClickhouseQueryNames(
+	requestPayload: Querybuildertypesv5QueryRangeRequestDTO | undefined,
+): Set<string> {
+	const names = new Set<string>();
+	(requestPayload?.compositeQuery?.queries ?? []).forEach((envelope) => {
+		if (envelope.type !== Querybuildertypesv5QueryTypeDTO.clickhouse_sql) {
+			return;
+		}
+		const spec = (envelope as Querybuildertypesv5QueryEnvelopeClickHouseSQLDTO)
+			.spec;
+		if (spec?.name) {
+			names.add(spec.name);
+		}
+	});
+	return names;
+}
+
 /**
  * Column display name. Group columns keep their field name; aggregation
  * columns resolve alias > legend > expression > queryName — with the legend
  * skipped when the query has multiple aggregations, because one legend can't
- * label several value columns. (Port of V1 `getColName`.)
+ * label several value columns. clickhouse_sql columns have no aggregation
+ * metadata, so their value columns are named by the real SQL alias the
+ * response carries in `col.name`. (Port of V1 `getColName`.)
  */
 function getColName(
 	col: Querybuildertypesv5ColumnDescriptorDTO,
 	legendMap: Record<string, string>,
 	aggregationsPerQuery: AggregationsPerQuery,
+	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
@@ -74,6 +102,13 @@ function getColName(
 		return alias || expression || queryName;
 	}
 
+	// clickhouse_sql value columns carry their real SQL alias in col.name — use
+	// it so each value column keeps its own header instead of collapsing onto
+	// the query name. Formulas/promql use placeholder names, so they fall back
+	// to legend || queryName.
+	if (clickhouseQueryNames.has(queryName)) {
+		return col.name;
+	}
 	return legend || queryName;
 }
 
@@ -85,15 +120,23 @@ function getColName(
 function getColId(
 	col: Querybuildertypesv5ColumnDescriptorDTO,
 	aggregationsPerQuery: AggregationsPerQuery,
+	clickhouseQueryNames: Set<string>,
 ): string {
 	if (col.columnType === 'group') {
 		return col.name;
 	}
 
 	const queryName = col.queryName ?? '';
+
+	// clickhouse_sql value columns are keyed by their real SQL alias so multiple
+	// value columns stay unique instead of all collapsing onto the query name
+	// (which would overwrite every cell in the row with the last column's value).
+	if (clickhouseQueryNames.has(queryName)) {
+		return col.name;
+	}
+
 	const aggregations = aggregationsPerQuery[queryName];
 	const expression = aggregations?.[col.aggregationIndex ?? 0]?.expression || '';
-
 	if ((aggregations?.length || 0) > 1 && expression) {
 		return `${queryName}.${expression}`;
 	}
@@ -119,6 +162,7 @@ export function prepareScalarTables({
 	requestPayload,
 }: PrepareScalarTablesArgs): PanelTable[] {
 	const aggregationsPerQuery = extractAggregationsPerQuery(requestPayload);
+	const clickhouseQueryNames = extractClickhouseQueryNames(requestPayload);
 
 	return results.map((scalarData) => {
 		if (!scalarData) {
@@ -132,10 +176,10 @@ export function prepareScalarTables({
 		const queryName = scalarData.columns?.[0]?.queryName ?? '';
 
 		const columns: PanelTableColumn[] = (scalarData.columns ?? []).map((col) => ({
-			name: getColName(col, legendMap, aggregationsPerQuery),
+			name: getColName(col, legendMap, aggregationsPerQuery, clickhouseQueryNames),
 			queryName: col.queryName ?? '',
 			isValueColumn: col.columnType === 'aggregation',
-			id: getColId(col, aggregationsPerQuery),
+			id: getColId(col, aggregationsPerQuery, clickhouseQueryNames),
 		}));
 
 		const rows = (scalarData.data ?? []).map((dataRow) => {

pkg/apiserver/signozapiserver/inframonitoring.go

@@ -16,7 +16,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListHosts",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Hosts for Infra Monitoring",
-			Description:         "Returns a paginated list of hosts with key infrastructure metrics: CPU usage (%), memory usage (%), I/O wait (%), disk usage (%), and 15-minute load average. Each host includes its current status (active/inactive based on metrics reported in the last 10 minutes) and metadata attributes (e.g., os.type). Supports filtering via a filter expression, filtering by host status, custom groupBy to aggregate hosts by any attribute, ordering by any of the five metrics, and pagination via offset/limit. The response type is 'list' for the default host.name grouping or 'grouped_list' for custom groupBy keys. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of hosts with key infrastructure metrics: CPU usage (%), memory usage (%), I/O wait (%), disk usage (%), and 15-minute load average. Each host includes its current status (active/inactive based on metrics reported in the last 10 minutes) and metadata attributes (e.g., os.type). Supports filtering via a filter expression, filtering by host status, custom groupBy to aggregate hosts by any attribute, ordering by any of the five metrics, and pagination via offset/limit. The response type is 'list' for the default host.name grouping or 'grouped_list' for custom groupBy keys. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableHosts),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Hosts),
@@ -35,7 +35,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListPods",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Pods for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes pods with key metrics: CPU usage, CPU request/limit utilization, memory working set, memory request/limit utilization, current pod phase (pending/running/succeeded/failed/unknown/no_data), and pod age (ms since start time). Each pod includes metadata attributes (namespace, node, workload owner such as deployment/statefulset/daemonset/job/cronjob, cluster). Supports filtering via a filter expression, custom groupBy to aggregate pods by any attribute, ordering by any of the six metrics (cpu, cpu_request, cpu_limit, memory, memory_request, memory_limit), and pagination via offset/limit. The response type is 'list' for the default k8s.pod.uid grouping (each row is one pod with its current phase) or 'grouped_list' for custom groupBy keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase: { pending, running, succeeded, failed, unknown } derived from each pod's latest phase in the window). Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes pods with key metrics: CPU usage, CPU request/limit utilization, memory working set, memory request/limit utilization, current pod phase (pending/running/succeeded/failed/unknown/no_data), and pod age (ms since start time). Each pod includes metadata attributes (namespace, node, workload owner such as deployment/statefulset/daemonset/job/cronjob, cluster). Supports filtering via a filter expression, custom groupBy to aggregate pods by any attribute, ordering by any of the six metrics (cpu, cpu_request, cpu_limit, memory, memory_request, memory_limit), and pagination via offset/limit. The response type is 'list' for the default k8s.pod.uid grouping (each row is one pod with its current phase) or 'grouped_list' for custom groupBy keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase: { pending, running, succeeded, failed, unknown } derived from each pod's latest phase in the window). Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostablePods),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Pods),
@@ -54,7 +54,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListNodes",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Nodes for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes nodes with key metrics: CPU usage, CPU allocatable, memory working set, memory allocatable, per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready in the window) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } for pods scheduled on the listed nodes). Each node includes metadata attributes (k8s.node.uid, k8s.cluster.name). The response type is 'list' for the default k8s.node.name grouping (each row is one node with its current condition string: ready / not_ready / no_data) or 'grouped_list' for custom groupBy keys (each row aggregates nodes in the group; condition stays no_data). Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes nodes with key metrics: CPU usage, CPU allocatable, memory working set, memory allocatable, per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready in the window) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } for pods scheduled on the listed nodes). Each node includes metadata attributes (k8s.node.uid, k8s.cluster.name). The response type is 'list' for the default k8s.node.name grouping (each row is one node with its current condition string: ready / not_ready / no_data) or 'grouped_list' for custom groupBy keys (each row aggregates nodes in the group; condition stays no_data). Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableNodes),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Nodes),
@@ -73,7 +73,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListNamespaces",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Namespaces for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes namespaces with key aggregated pod metrics: CPU usage and memory working set (summed across pods in the group), plus per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value in the window). Each namespace includes metadata attributes (k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.namespace.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / memory, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes namespaces with key aggregated pod metrics: CPU usage and memory working set (summed across pods in the group), plus per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value in the window). Each namespace includes metadata attributes (k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.namespace.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / memory, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableNamespaces),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Namespaces),
@@ -92,7 +92,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListClusters",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Clusters for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes clusters with key aggregated metrics derived by summing per-node values within the group: CPU usage, CPU allocatable, memory working set, memory allocatable. Each row also reports per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready value) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each cluster includes metadata attributes (k8s.cluster.name). The response type is 'list' for the default k8s.cluster.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates nodes and pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes clusters with key aggregated metrics derived by summing per-node values within the group: CPU usage, CPU allocatable, memory working set, memory allocatable. Each row also reports per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready value) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each cluster includes metadata attributes (k8s.cluster.name). The response type is 'list' for the default k8s.cluster.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates nodes and pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableClusters),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Clusters),
@@ -111,7 +111,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListVolumes",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Volumes for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes persistent volume claims (PVCs) with key volume metrics: available bytes, capacity bytes, usage (capacity - available), inodes, free inodes, and used inodes. Each row also includes metadata attributes (k8s.persistentvolumeclaim.name, k8s.pod.uid, k8s.pod.name, k8s.namespace.name, k8s.node.name, k8s.statefulset.name, k8s.cluster.name). Supports filtering via a filter expression, custom groupBy to aggregate volumes by any attribute, ordering by any of the six metrics (available, capacity, usage, inodes, inodes_free, inodes_used), and pagination via offset/limit. The response type is 'list' for the default k8s.persistentvolumeclaim.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates volumes in the group. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes persistent volume claims (PVCs) with key volume metrics: available bytes, capacity bytes, usage (capacity - available), inodes, free inodes, and used inodes. Each row also includes metadata attributes (k8s.persistentvolumeclaim.name, k8s.pod.uid, k8s.pod.name, k8s.namespace.name, k8s.node.name, k8s.statefulset.name, k8s.cluster.name). Supports filtering via a filter expression, custom groupBy to aggregate volumes by any attribute, ordering by any of the six metrics (available, capacity, usage, inodes, inodes_free, inodes_used), and pagination via offset/limit. The response type is 'list' for the default k8s.persistentvolumeclaim.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates volumes in the group. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableVolumes),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Volumes),
@@ -130,7 +130,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListDeployments",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Deployments for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes Deployments with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the deployment, plus average CPU/memory request and limit utilization (deploymentCPURequest, deploymentCPULimit, deploymentMemoryRequest, deploymentMemoryLimit). Each row also reports the latest known desiredPods (k8s.deployment.desired) and availablePods (k8s.deployment.available) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each deployment includes metadata attributes (k8s.deployment.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.deployment.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by deployments in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / available_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods, availablePods) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes Deployments with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the deployment, plus average CPU/memory request and limit utilization (deploymentCPURequest, deploymentCPULimit, deploymentMemoryRequest, deploymentMemoryLimit). Each row also reports the latest known desiredPods (k8s.deployment.desired) and availablePods (k8s.deployment.available) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each deployment includes metadata attributes (k8s.deployment.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.deployment.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by deployments in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / available_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods, availablePods) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableDeployments),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Deployments),
@@ -149,7 +149,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListStatefulSets",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List StatefulSets for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes StatefulSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the statefulset, plus average CPU/memory request and limit utilization (statefulSetCPURequest, statefulSetCPULimit, statefulSetMemoryRequest, statefulSetMemoryLimit). Each row also reports the latest known desiredPods (k8s.statefulset.desired_pods) and currentPods (k8s.statefulset.current_pods) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each statefulset includes metadata attributes (k8s.statefulset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.statefulset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by statefulsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / current_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes StatefulSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the statefulset, plus average CPU/memory request and limit utilization (statefulSetCPURequest, statefulSetCPULimit, statefulSetMemoryRequest, statefulSetMemoryLimit). Each row also reports the latest known desiredPods (k8s.statefulset.desired_pods) and currentPods (k8s.statefulset.current_pods) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each statefulset includes metadata attributes (k8s.statefulset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.statefulset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by statefulsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / current_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableStatefulSets),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.StatefulSets),
@@ -168,7 +168,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListJobs",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List Jobs for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes Jobs with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the job, plus average CPU/memory request and limit utilization (jobCPURequest, jobCPULimit, jobMemoryRequest, jobMemoryLimit). Each row also reports the latest known job-level counters from kube-state-metrics: desiredSuccessfulPods (k8s.job.desired_successful_pods, the target completion count), activePods (k8s.job.active_pods), failedPods (k8s.job.failed_pods, cumulative across the lifetime of the job), and successfulPods (k8s.job.successful_pods, cumulative). It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value); note podCountsByPhase.failed (current pod-phase) is distinct from failedPods (cumulative job kube-state-metric). Each job includes metadata attributes (k8s.job.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.job.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by jobs in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_successful_pods / active_pods / failed_pods / successful_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes Jobs with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the job, plus average CPU/memory request and limit utilization (jobCPURequest, jobCPULimit, jobMemoryRequest, jobMemoryLimit). Each row also reports the latest known job-level counters from kube-state-metrics: desiredSuccessfulPods (k8s.job.desired_successful_pods, the target completion count), activePods (k8s.job.active_pods), failedPods (k8s.job.failed_pods, cumulative across the lifetime of the job), and successfulPods (k8s.job.successful_pods, cumulative). It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value); note podCountsByPhase.failed (current pod-phase) is distinct from failedPods (cumulative job kube-state-metric). Each job includes metadata attributes (k8s.job.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.job.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by jobs in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_successful_pods / active_pods / failed_pods / successful_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableJobs),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.Jobs),
@@ -187,7 +187,7 @@ func (provider *provider) addInfraMonitoringRoutes(router *mux.Router) error {
 			ID:                  "ListDaemonSets",
 			Tags:                []string{"inframonitoring"},
 			Summary:             "List DaemonSets for Infra Monitoring",
-			Description:         "Returns a paginated list of Kubernetes DaemonSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the daemonset, plus average CPU/memory request and limit utilization (daemonSetCPURequest, daemonSetCPULimit, daemonSetMemoryRequest, daemonSetMemoryLimit). Each row also reports the latest known node-level counters from kube-state-metrics: desiredNodes (k8s.daemonset.desired_scheduled_nodes, the number of nodes the daemonset wants to run on) and currentNodes (k8s.daemonset.current_scheduled_nodes, the number of nodes the daemonset currently runs on) — note these are node counts, not pod counts. It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each daemonset includes metadata attributes (k8s.daemonset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.daemonset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by daemonsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_nodes / current_nodes, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel when no data is available for that field.",
+			Description:         "Returns a paginated list of Kubernetes DaemonSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the daemonset, plus average CPU/memory request and limit utilization (daemonSetCPURequest, daemonSetCPULimit, daemonSetMemoryRequest, daemonSetMemoryLimit). Each row also reports the latest known node-level counters from kube-state-metrics: desiredNodes (k8s.daemonset.desired_scheduled_nodes, the number of nodes the daemonset wants to run on) and currentNodes (k8s.daemonset.current_scheduled_nodes, the number of nodes the daemonset currently runs on) — note these are node counts, not pod counts. It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each daemonset includes metadata attributes (k8s.daemonset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.daemonset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by daemonsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_nodes / current_nodes, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel when no data is available for that field.",
 			Request:             new(inframonitoringtypes.PostableDaemonSets),
 			RequestContentType:  "application/json",
 			Response:            new(inframonitoringtypes.DaemonSets),

pkg/apiserver/signozapiserver/role.go

@@ -73,7 +73,7 @@ func (provider *provider) addRoleRoutes(router *mux.Router) error {
 			Description:         "This endpoint gets a role",
 			Request:             nil,
 			RequestContentType:  "",
-			Response:            new(authtypes.Role),
+			Response:            new(authtypes.RoleWithTransactionGroups),
 			ResponseContentType: "application/json",
 			SuccessStatusCode:   http.StatusOK,
 			ErrorStatusCodes:    []int{},
@@ -91,6 +91,60 @@ func (provider *provider) addRoleRoutes(router *mux.Router) error {
 		return err
 	}
 
+	if err := router.Handle("/api/v1/roles/{id}", handler.New(
+		provider.authzMiddleware.CheckResources(provider.authzHandler.Update, authtypes.SigNozAdminRoleName),
+		handler.OpenAPIDef{
+			ID:                  "UpdateRole",
+			Tags:                []string{"role"},
+			Summary:             "Update role",
+			Description:         "This endpoint updates a role",
+			Request:             new(authtypes.UpdatableRole),
+			RequestContentType:  "",
+			Response:            nil,
+			ResponseContentType: "application/json",
+			SuccessStatusCode:   http.StatusNoContent,
+			ErrorStatusCodes:    []int{http.StatusNotFound, http.StatusNotImplemented, http.StatusUnavailableForLegalReasons},
+			Deprecated:          false,
+			SecuritySchemes:     newScopedSecuritySchemes([]string{coretypes.ResourceRole.Scope(coretypes.VerbUpdate)}),
+		},
+		handler.WithResourceDefs(handler.BasicResourceDef{
+			Resource: coretypes.ResourceRole,
+			Verb:     coretypes.VerbUpdate,
+			Category: coretypes.ActionCategoryAccessControl,
+			ID:       coretypes.PathParam("id"),
+			Selector: provider.roleSelector,
+		}),
+	)).Methods(http.MethodPut).GetError(); err != nil {
+		return err
+	}
+
+	if err := router.Handle("/api/v1/roles/{id}", handler.New(
+		provider.authzMiddleware.CheckResources(provider.authzHandler.Delete, authtypes.SigNozAdminRoleName),
+		handler.OpenAPIDef{
+			ID:                  "DeleteRole",
+			Tags:                []string{"role"},
+			Summary:             "Delete role",
+			Description:         "This endpoint deletes a role",
+			Request:             nil,
+			RequestContentType:  "",
+			Response:            nil,
+			ResponseContentType: "application/json",
+			SuccessStatusCode:   http.StatusNoContent,
+			ErrorStatusCodes:    []int{http.StatusNotFound, http.StatusNotImplemented, http.StatusUnavailableForLegalReasons},
+			Deprecated:          false,
+			SecuritySchemes:     newScopedSecuritySchemes([]string{coretypes.ResourceRole.Scope(coretypes.VerbDelete)}),
+		},
+		handler.WithResourceDefs(handler.BasicResourceDef{
+			Resource: coretypes.ResourceRole,
+			Verb:     coretypes.VerbDelete,
+			Category: coretypes.ActionCategoryAccessControl,
+			ID:       coretypes.PathParam("id"),
+			Selector: provider.roleSelector,
+		}),
+	)).Methods(http.MethodDelete).GetError(); err != nil {
+		return err
+	}
+
 	if err := router.Handle("/api/v1/roles/{id}/relations/{relation}/objects", handler.New(
 		provider.authzMiddleware.CheckResources(provider.authzHandler.GetObjects, authtypes.SigNozAdminRoleName),
 		handler.OpenAPIDef{
@@ -131,7 +185,7 @@ func (provider *provider) addRoleRoutes(router *mux.Router) error {
 			ResponseContentType: "application/json",
 			SuccessStatusCode:   http.StatusNoContent,
 			ErrorStatusCodes:    []int{http.StatusNotFound, http.StatusNotImplemented, http.StatusUnavailableForLegalReasons},
-			Deprecated:          false,
+			Deprecated:          true,
 			SecuritySchemes:     newScopedSecuritySchemes([]string{coretypes.ResourceRole.Scope(coretypes.VerbUpdate)}),
 		},
 		handler.WithResourceDefs(handler.BasicResourceDef{
@@ -158,7 +212,7 @@ func (provider *provider) addRoleRoutes(router *mux.Router) error {
 			ResponseContentType: "application/json",
 			SuccessStatusCode:   http.StatusNoContent,
 			ErrorStatusCodes:    []int{http.StatusNotFound, http.StatusBadRequest, http.StatusNotImplemented, http.StatusUnavailableForLegalReasons},
-			Deprecated:          false,
+			Deprecated:          true,
 			SecuritySchemes:     newScopedSecuritySchemes([]string{coretypes.ResourceRole.Scope(coretypes.VerbUpdate)}),
 		},
 		handler.WithResourceDefs(handler.BasicResourceDef{
@@ -172,32 +226,5 @@ func (provider *provider) addRoleRoutes(router *mux.Router) error {
 		return err
 	}
 
-	if err := router.Handle("/api/v1/roles/{id}", handler.New(
-		provider.authzMiddleware.CheckResources(provider.authzHandler.Delete, authtypes.SigNozAdminRoleName),
-		handler.OpenAPIDef{
-			ID:                  "DeleteRole",
-			Tags:                []string{"role"},
-			Summary:             "Delete role",
-			Description:         "This endpoint deletes a role",
-			Request:             nil,
-			RequestContentType:  "",
-			Response:            nil,
-			ResponseContentType: "application/json",
-			SuccessStatusCode:   http.StatusNoContent,
-			ErrorStatusCodes:    []int{http.StatusNotFound, http.StatusNotImplemented, http.StatusUnavailableForLegalReasons},
-			Deprecated:          false,
-			SecuritySchemes:     newScopedSecuritySchemes([]string{coretypes.ResourceRole.Scope(coretypes.VerbDelete)}),
-		},
-		handler.WithResourceDefs(handler.BasicResourceDef{
-			Resource: coretypes.ResourceRole,
-			Verb:     coretypes.VerbDelete,
-			Category: coretypes.ActionCategoryAccessControl,
-			ID:       coretypes.PathParam("id"),
-			Selector: provider.roleSelector,
-		}),
-	)).Methods(http.MethodDelete).GetError(); err != nil {
-		return err
-	}
-
 	return nil
 }

pkg/authz/authz.go

@@ -33,8 +33,8 @@ type AuthZ interface {
 	// Lists the selectors for objects assigned to subject (s) with relation (r) on resource (s)
 	ListObjects(context.Context, string, authtypes.Relation, coretypes.Type) ([]*coretypes.Object, error)
 
-	// Creates the role.
-	Create(context.Context, valuer.UUID, *authtypes.Role) error
+	// Creates the role with its transaction groups.
+	Create(context.Context, valuer.UUID, *authtypes.RoleWithTransactionGroups) error
 
 	// Gets the role if it exists or creates one.
 	GetOrCreate(context.Context, valuer.UUID, *authtypes.Role) (*authtypes.Role, error)
@@ -48,12 +48,18 @@ type AuthZ interface {
 	// Patches the objects in authorization server associated with the given role and relation
 	PatchObjects(context.Context, valuer.UUID, string, authtypes.Relation, []*coretypes.Object, []*coretypes.Object) error
 
+	// Updates the role's metadata and reconciles its transaction groups.
+	Update(context.Context, valuer.UUID, *authtypes.RoleWithTransactionGroups) error
+
 	// Deletes the role and tuples in authorization server.
 	Delete(context.Context, valuer.UUID, valuer.UUID) error
 
 	// Gets the role
 	Get(context.Context, valuer.UUID, valuer.UUID) (*authtypes.Role, error)
 
+	// Gets the role with transaction groups
+	GetWithTransactionGroups(context.Context, valuer.UUID, valuer.UUID) (*authtypes.RoleWithTransactionGroups, error)
+
 	// Gets the role by org_id and name
 	GetByOrgIDAndName(context.Context, valuer.UUID, string) (*authtypes.Role, error)
 
@@ -101,6 +107,8 @@ type Handler interface {
 
 	PatchObjects(http.ResponseWriter, *http.Request)
 
+	Update(http.ResponseWriter, *http.Request)
+
 	Check(http.ResponseWriter, *http.Request)
 
 	Delete(http.ResponseWriter, *http.Request)

pkg/authz/openfgaauthz/provider.go

@@ -83,6 +83,10 @@ func (provider *provider) Get(ctx context.Context, orgID valuer.UUID, id valuer.
 	return provider.store.Get(ctx, orgID, id)
 }
 
+func (provider *provider) GetWithTransactionGroups(ctx context.Context, orgID valuer.UUID, id valuer.UUID) (*authtypes.RoleWithTransactionGroups, error) {
+	return nil, errors.Newf(errors.TypeUnsupported, authtypes.ErrCodeRoleUnsupported, "not implemented")
+}
+
 func (provider *provider) GetByOrgIDAndName(ctx context.Context, orgID valuer.UUID, name string) (*authtypes.Role, error) {
 	return provider.store.GetByOrgIDAndName(ctx, orgID, name)
 }
@@ -168,7 +172,7 @@ func (provider *provider) CreateManagedUserRoleTransactions(ctx context.Context,
 	return provider.Grant(ctx, orgID, []string{authtypes.SigNozAdminRoleName}, authtypes.MustNewSubject(coretypes.NewResourceUser(), userID.String(), orgID, nil))
 }
 
-func (setter *provider) Create(_ context.Context, _ valuer.UUID, _ *authtypes.Role) error {
+func (setter *provider) Create(_ context.Context, _ valuer.UUID, _ *authtypes.RoleWithTransactionGroups) error {
 	return errors.Newf(errors.TypeUnsupported, authtypes.ErrCodeRoleUnsupported, "not implemented")
 }
 
@@ -180,6 +184,10 @@ func (provider *provider) GetObjects(ctx context.Context, orgID valuer.UUID, id
 	return nil, errors.Newf(errors.TypeUnsupported, authtypes.ErrCodeRoleUnsupported, "not implemented")
 }
 
+func (provider *provider) Update(_ context.Context, _ valuer.UUID, _ *authtypes.RoleWithTransactionGroups) error {
+	return errors.Newf(errors.TypeUnsupported, authtypes.ErrCodeRoleUnsupported, "not implemented")
+}
+
 func (provider *provider) Patch(_ context.Context, _ valuer.UUID, _ *authtypes.Role) error {
 	return errors.Newf(errors.TypeUnsupported, authtypes.ErrCodeRoleUnsupported, "not implemented")
 }

pkg/authz/openfgaserver/server.go

@@ -212,6 +212,30 @@ func (server *Server) CheckWithTupleCreationWithoutClaims(ctx context.Context, o
 }
 
 func (server *Server) Write(ctx context.Context, additions []*openfgav1.TupleKey, deletions []*openfgav1.TupleKey) error {
+	maxTuplesPerWrite := server.config.OpenFGA.MaxTuplesPerWrite
+
+	if len(additions)+len(deletions) <= maxTuplesPerWrite {
+		return server.write(ctx, additions, deletions)
+	}
+
+	for idx := 0; idx < len(additions); idx += maxTuplesPerWrite {
+		end := min(idx+maxTuplesPerWrite, len(additions))
+		if err := server.write(ctx, additions[idx:end], nil); err != nil {
+			return err
+		}
+	}
+
+	for idx := 0; idx < len(deletions); idx += maxTuplesPerWrite {
+		end := min(idx+maxTuplesPerWrite, len(deletions))
+		if err := server.write(ctx, nil, deletions[idx:end]); err != nil {
+			return err
+		}
+	}
+
+	return nil
+}
+
+func (server *Server) write(ctx context.Context, additions []*openfgav1.TupleKey, deletions []*openfgav1.TupleKey) error {
 	if len(additions) == 0 && len(deletions) == 0 {
 		return nil
 	}

pkg/authz/signozauthzapi/handler.go

@@ -36,14 +36,14 @@ func (handler *handler) Create(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	role := authtypes.NewRole(req.Name, req.Description, authtypes.RoleTypeCustom, valuer.MustNewUUID(claims.OrgID))
-	err = handler.authz.Create(ctx, valuer.MustNewUUID(claims.OrgID), role)
+	roleWithTransactionGroups := authtypes.NewRoleWithTransactionGroups(req.Name, req.Description, authtypes.RoleTypeCustom, valuer.MustNewUUID(claims.OrgID), req.TransactionGroups)
+	err = handler.authz.Create(ctx, valuer.MustNewUUID(claims.OrgID), roleWithTransactionGroups)
 	if err != nil {
 		render.Error(rw, err)
 		return
 	}
 
-	render.Success(rw, http.StatusCreated, types.Identifiable{ID: role.ID})
+	render.Success(rw, http.StatusCreated, types.Identifiable{ID: roleWithTransactionGroups.ID})
 }
 
 func (handler *handler) Get(rw http.ResponseWriter, r *http.Request) {
@@ -65,13 +65,13 @@ func (handler *handler) Get(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	role, err := handler.authz.Get(ctx, valuer.MustNewUUID(claims.OrgID), roleID)
+	roleWithTransactionGroups, err := handler.authz.GetWithTransactionGroups(ctx, valuer.MustNewUUID(claims.OrgID), roleID)
 	if err != nil {
 		render.Error(rw, err)
 		return
 	}
 
-	render.Success(rw, http.StatusOK, role)
+	render.Success(rw, http.StatusOK, roleWithTransactionGroups)
 }
 
 func (handler *handler) GetObjects(rw http.ResponseWriter, r *http.Request) {
@@ -224,6 +224,48 @@ func (handler *handler) PatchObjects(rw http.ResponseWriter, r *http.Request) {
 	render.Success(rw, http.StatusNoContent, nil)
 }
 
+func (handler *handler) Update(rw http.ResponseWriter, r *http.Request) {
+	ctx := r.Context()
+	claims, err := authtypes.ClaimsFromContext(ctx)
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
+	id, err := valuer.NewUUID(mux.Vars(r)["id"])
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
+	req := new(authtypes.UpdatableRole)
+	if err := binding.JSON.BindBody(r.Body, req); err != nil {
+		render.Error(rw, err)
+		return
+	}
+
+	role, err := handler.authz.Get(ctx, valuer.MustNewUUID(claims.OrgID), id)
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
+	roleWithTransactionGroups := authtypes.MakeRoleWithTransactionGroups(role, nil)
+	err = roleWithTransactionGroups.Update(req.Description, req.TransactionGroups)
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
+	err = handler.authz.Update(ctx, valuer.MustNewUUID(claims.OrgID), roleWithTransactionGroups)
+	if err != nil {
+		render.Error(rw, err)
+		return
+	}
+
+	render.Success(rw, http.StatusNoContent, nil)
+}
+
 func (handler *handler) Delete(rw http.ResponseWriter, r *http.Request) {
 	ctx := r.Context()
 	claims, err := authtypes.ClaimsFromContext(ctx)

pkg/flagger/registry.go

@@ -3,15 +3,16 @@ package flagger
 import "github.com/SigNoz/signoz/pkg/types/featuretypes"
 
 var (
-	FeatureUseSpanMetrics      = featuretypes.MustNewName("use_span_metrics")
-	FeatureKafkaSpanEval       = featuretypes.MustNewName("kafka_span_eval")
-	FeatureHideRootUser        = featuretypes.MustNewName("hide_root_user")
-	FeatureGetMetersFromZeus   = featuretypes.MustNewName("get_meters_from_zeus")
-	FeaturePutMetersInZeus     = featuretypes.MustNewName("put_meters_in_zeus")
-	FeatureUseMeterReporter    = featuretypes.MustNewName("use_meter_reporter")
-	FeatureUseJSONBody         = featuretypes.MustNewName("use_json_body")
-	FeatureUseFineGrainedAuthz = featuretypes.MustNewName("use_fine_grained_authz")
-	FeatureUseDashboardV2      = featuretypes.MustNewName("use_dashboard_v2")
+	FeatureUseSpanMetrics        = featuretypes.MustNewName("use_span_metrics")
+	FeatureKafkaSpanEval         = featuretypes.MustNewName("kafka_span_eval")
+	FeatureHideRootUser          = featuretypes.MustNewName("hide_root_user")
+	FeatureGetMetersFromZeus     = featuretypes.MustNewName("get_meters_from_zeus")
+	FeaturePutMetersInZeus       = featuretypes.MustNewName("put_meters_in_zeus")
+	FeatureUseMeterReporter      = featuretypes.MustNewName("use_meter_reporter")
+	FeatureUseJSONBody           = featuretypes.MustNewName("use_json_body")
+	FeatureUseFineGrainedAuthz   = featuretypes.MustNewName("use_fine_grained_authz")
+	FeatureUseDashboardV2        = featuretypes.MustNewName("use_dashboard_v2")
+	FeatureEnableAIObservability = featuretypes.MustNewName("enable_ai_observability")
 )
 
 func MustNewRegistry() featuretypes.Registry {
@@ -88,6 +89,14 @@ func MustNewRegistry() featuretypes.Registry {
 			DefaultVariant: featuretypes.MustNewName("disabled"),
 			Variants:       featuretypes.NewBooleanVariants(),
 		},
+		&featuretypes.Feature{
+			Name:           FeatureEnableAIObservability,
+			Kind:           featuretypes.KindBoolean,
+			Stage:          featuretypes.StageExperimental,
+			Description:    "Controls whether ai observability is enabled",
+			DefaultVariant: featuretypes.MustNewName("disabled"),
+			Variants:       featuretypes.NewBooleanVariants(),
+		},
 	)
 	if err != nil {
 		panic(err)

pkg/modules/inframonitoring/implinframonitoring/helpers.go

@@ -413,27 +413,64 @@ func (m *module) buildFilterClause(ctx context.Context, filter *qbtypes.Filter,
 // NOTE: this method is not specific to infra monitoring — it queries attributes_metadata generically.
 // Consider moving to telemetryMetaStore when a second use case emerges.
 //
-// getEarliestMetricTime returns the earliest first_reported_unix_milli across the
-// given metric names. It is used solely for the end-time-before-retention check.
-// When none of the metrics have ever been reported, it returns 0.
-func (m *module) getEarliestMetricTime(ctx context.Context, metricNames []string) (uint64, error) {
+// getMetricsExistenceAndEarliestTime checks which of the given metric names have been
+// reported. It returns a list of missing metrics (those not found or with zero count)
+// and the earliest first-reported timestamp across all present metrics.
+// When all metrics are missing, minFirstReportedUnixMilli is 0.
+// TODO(nikhilmantri0902, srikanthccv): This method was designed this way because querier errors if any of the metrics
+// in the querier list was never sent, the QueryRange call throws not found error. Modify this method, if QueryRange
+// behaviour changes towards this.
+func (m *module) getMetricsExistenceAndEarliestTime(ctx context.Context, metricNames []string) ([]string, uint64, error) {
 	if len(metricNames) == 0 {
-		return 0, nil
+		return nil, 0, nil
 	}
 
 	sb := sqlbuilder.NewSelectBuilder()
-	sb.Select("min(first_reported_unix_milli) AS min_first_reported")
+	sb.Select("metric_name", "count(*) AS cnt", "min(first_reported_unix_milli) AS min_first_reported")
 	sb.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, telemetrymetrics.AttributesMetadataTableName))
 	sb.Where(sb.In("metric_name", sqlbuilder.List(metricNames)))
+	sb.GroupBy("metric_name")
 
 	query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
 
-	var minFirstReported uint64
-	if err := m.telemetryStore.ClickhouseDB().QueryRow(ctx, query, args...).Scan(&minFirstReported); err != nil {
-		return 0, err
+	rows, err := m.telemetryStore.ClickhouseDB().Query(ctx, query, args...)
+	if err != nil {
+		return nil, 0, err
+	}
+	defer rows.Close()
+
+	type metricInfo struct {
+		count            uint64
+		minFirstReported uint64
+	}
+	found := make(map[string]metricInfo, len(metricNames))
+
+	for rows.Next() {
+		var name string
+		var cnt, minFR uint64
+		if err := rows.Scan(&name, &cnt, &minFR); err != nil {
+			return nil, 0, err
+		}
+		found[name] = metricInfo{count: cnt, minFirstReported: minFR}
+	}
+	if err := rows.Err(); err != nil {
+		return nil, 0, err
 	}
 
-	return minFirstReported, nil
+	var missingMetrics []string
+	var globalMinFirstReported uint64
+	for _, name := range metricNames {
+		info, ok := found[name]
+		if !ok || info.count == 0 {
+			missingMetrics = append(missingMetrics, name)
+			continue
+		}
+		if globalMinFirstReported == 0 || info.minFirstReported < globalMinFirstReported {
+			globalMinFirstReported = info.minFirstReported
+		}
+	}
+
+	return missingMetrics, globalMinFirstReported, nil
 }
 
 // getMetadata fetches the latest values of additionalCols for each unique combination of groupBy keys,

pkg/modules/inframonitoring/implinframonitoring/module.go

@@ -78,18 +78,26 @@ func (m *module) ListHosts(ctx context.Context, orgID valuer.UUID, req *inframon
 		resp.Type = inframonitoringtypes.ResponseTypeGroupedList
 	}
 
-	// If req.End is before the earliest reported time for these metrics, return early
-	// with endTimeBeforeRetention=true.
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, hostsTableMetricNamesList)
+	// 1. Check which required metrics exist and get earliest retention time.
+	// If any required metric is missing, return early with the list of missing metrics.
+	// 2. If metrics exist but req.End is before the earliest reported time, return early with endTimeBeforeRetention=true.
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, hostsTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.HostRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.HostRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	// TOD(nikhilmantri0902): replace this separate ClickHouse query with a sub-query inside the main query builder query
 	// once QB supports sub-queries.
@@ -183,16 +191,23 @@ func (m *module) ListPods(ctx context.Context, orgID valuer.UUID, req *inframoni
 		resp.Type = inframonitoringtypes.ResponseTypeGroupedList
 	}
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, podsTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, podsTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.PodRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.PodRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getPodsTableMetadata(ctx, req)
 	if err != nil {
@@ -261,16 +276,23 @@ func (m *module) ListNodes(ctx context.Context, orgID valuer.UUID, req *inframon
 		resp.Type = inframonitoringtypes.ResponseTypeGroupedList
 	}
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, nodesTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, nodesTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.NodeRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.NodeRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getNodesTableMetadata(ctx, req)
 	if err != nil {
@@ -344,16 +366,23 @@ func (m *module) ListNamespaces(ctx context.Context, orgID valuer.UUID, req *inf
 		resp.Type = inframonitoringtypes.ResponseTypeGroupedList
 	}
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, namespacesTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, namespacesTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.NamespaceRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.NamespaceRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getNamespacesTableMetadata(ctx, req)
 	if err != nil {
@@ -421,16 +450,23 @@ func (m *module) ListClusters(ctx context.Context, orgID valuer.UUID, req *infra
 		resp.Type = inframonitoringtypes.ResponseTypeGroupedList
 	}
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, clustersTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, clustersTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.ClusterRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.ClusterRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getClustersTableMetadata(ctx, req)
 	if err != nil {
@@ -511,16 +547,23 @@ func (m *module) ListVolumes(ctx context.Context, orgID valuer.UUID, req *infram
 	}
 	req.Filter.Expression = mergeFilterExpressions(volumesBaseFilterExpr, req.Filter.Expression)
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, volumesTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, volumesTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.VolumeRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.VolumeRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getVolumesTableMetadata(ctx, req)
 	if err != nil {
@@ -589,16 +632,23 @@ func (m *module) ListDeployments(ctx context.Context, orgID valuer.UUID, req *in
 	}
 	req.Filter.Expression = mergeFilterExpressions(deploymentsBaseFilterExpr, req.Filter.Expression)
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, deploymentsTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, deploymentsTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.DeploymentRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.DeploymentRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getDeploymentsTableMetadata(ctx, req)
 	if err != nil {
@@ -672,16 +722,23 @@ func (m *module) ListStatefulSets(ctx context.Context, orgID valuer.UUID, req *i
 	}
 	req.Filter.Expression = mergeFilterExpressions(statefulSetsBaseFilterExpr, req.Filter.Expression)
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, statefulSetsTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, statefulSetsTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.StatefulSetRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.StatefulSetRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getStatefulSetsTableMetadata(ctx, req)
 	if err != nil {
@@ -757,16 +814,23 @@ func (m *module) ListJobs(ctx context.Context, orgID valuer.UUID, req *inframoni
 	}
 	req.Filter.Expression = mergeFilterExpressions(jobsBaseFilterExpr, req.Filter.Expression)
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, jobsTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, jobsTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.JobRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.JobRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getJobsTableMetadata(ctx, req)
 	if err != nil {
@@ -842,16 +906,23 @@ func (m *module) ListDaemonSets(ctx context.Context, orgID valuer.UUID, req *inf
 	}
 	req.Filter.Expression = mergeFilterExpressions(daemonSetsBaseFilterExpr, req.Filter.Expression)
 
-	minFirstReportedUnixMilli, err := m.getEarliestMetricTime(ctx, daemonSetsTableMetricNamesList)
+	missingMetrics, minFirstReportedUnixMilli, err := m.getMetricsExistenceAndEarliestTime(ctx, daemonSetsTableMetricNamesList)
 	if err != nil {
 		return nil, err
 	}
+	if len(missingMetrics) > 0 {
+		resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: missingMetrics}
+		resp.Records = []inframonitoringtypes.DaemonSetRecord{}
+		resp.Total = 0
+		return resp, nil
+	}
 	if req.End < int64(minFirstReportedUnixMilli) {
 		resp.EndTimeBeforeRetention = true
 		resp.Records = []inframonitoringtypes.DaemonSetRecord{}
 		resp.Total = 0
 		return resp, nil
 	}
+	resp.RequiredMetricsCheck = inframonitoringtypes.RequiredMetricsCheck{MissingMetrics: []string{}}
 
 	metadataMap, err := m.getDaemonSetsTableMetadata(ctx, req)
 	if err != nil {

pkg/modules/llmpricingrule/impllmpricingrule/handler.go

@@ -54,7 +54,7 @@ func (h *handler) List(rw http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	rules, total, err := h.module.List(ctx, orgID, q.Offset, q.Limit)
+	rules, total, err := h.module.List(ctx, orgID, q.Offset, q.Limit, q.Search, q.IsOverride)
 	if err != nil {
 		render.Error(rw, err)
 		return

pkg/modules/llmpricingrule/impllmpricingrule/module.go

@@ -21,8 +21,8 @@ func NewModule(store llmpricingruletypes.Store) llmpricingrule.Module {
 	return &module{store: store}
 }
 
-func (module *module) List(ctx context.Context, orgID valuer.UUID, offset, limit int) ([]*llmpricingruletypes.LLMPricingRule, int, error) {
-	return module.store.List(ctx, orgID, offset, limit)
+func (module *module) List(ctx context.Context, orgID valuer.UUID, offset, limit int, search string, isOverride *bool) ([]*llmpricingruletypes.LLMPricingRule, int, error) {
+	return module.store.List(ctx, orgID, offset, limit, search, isOverride)
 }
 
 func (module *module) Get(ctx context.Context, orgID valuer.UUID, id valuer.UUID) (*llmpricingruletypes.LLMPricingRule, error) {
@@ -108,7 +108,7 @@ func (module *module) RecommendAgentConfig(orgID valuer.UUID, currentConfYaml []
 }
 
 func (module *module) getEnabledRules(ctx context.Context, orgID valuer.UUID) ([]*llmpricingruletypes.LLMPricingRule, error) {
-	rules, _, err := module.List(ctx, orgID, 0, 10000)
+	rules, _, err := module.List(ctx, orgID, 0, 10000, "", nil)
 	if err != nil {
 		return nil, err
 	}

pkg/modules/llmpricingrule/impllmpricingrule/store.go

@@ -17,14 +17,25 @@ func NewStore(sqlstore sqlstore.SQLStore) llmpricingruletypes.Store {
 	return &store{sqlstore: sqlstore}
 }
 
-func (store *store) List(ctx context.Context, orgID valuer.UUID, offset, limit int) ([]*llmpricingruletypes.LLMPricingRule, int, error) {
+func (store *store) List(ctx context.Context, orgID valuer.UUID, offset, limit int, search string, isOverride *bool) ([]*llmpricingruletypes.LLMPricingRule, int, error) {
 	rules := make([]*llmpricingruletypes.LLMPricingRule, 0)
 
-	count, err := store.sqlstore.
+	query := store.sqlstore.
 		BunDBCtx(ctx).
 		NewSelect().
 		Model(&rules).
-		Where("org_id = ?", orgID).
+		Where("org_id = ?", orgID)
+
+	if search != "" {
+		like := "%" + search + "%"
+		query = query.Where("(LOWER(model) LIKE LOWER(?) OR LOWER(provider) LIKE LOWER(?))", like, like)
+	}
+
+	if isOverride != nil {
+		query = query.Where("is_override = ?", *isOverride)
+	}
+
+	count, err := query.
 		Order("created_at DESC").
 		Offset(offset).
 		Limit(limit).

pkg/modules/llmpricingrule/llmpricingrule.go

@@ -13,7 +13,7 @@ type Module interface {
 	// Since this module interacts with OpAMP, it must implement the AgentFeature interface.
 	agentConf.AgentFeature
 
-	List(ctx context.Context, orgID valuer.UUID, offset, limit int) ([]*llmpricingruletypes.LLMPricingRule, int, error)
+	List(ctx context.Context, orgID valuer.UUID, offset, limit int, search string, isOverride *bool) ([]*llmpricingruletypes.LLMPricingRule, int, error)
 	Get(ctx context.Context, orgID valuer.UUID, id valuer.UUID) (*llmpricingruletypes.LLMPricingRule, error)
 	CreateOrUpdate(ctx context.Context, orgID valuer.UUID, userEmail string, rules []*llmpricingruletypes.UpdatableLLMPricingRule) (err error)
 	Delete(ctx context.Context, orgID, id valuer.UUID) error

pkg/query-service/app/http_handler.go

@@ -1678,6 +1678,15 @@ func (aH *APIHandler) getFeatureFlags(w http.ResponseWriter, r *http.Request) {
 		Route:      "",
 	})
 
+	aiObservability := aH.Signoz.Flagger.BooleanOrEmpty(r.Context(), flagger.FeatureEnableAIObservability, evalCtx)
+	featureSet = append(featureSet, &licensetypes.Feature{
+		Name:       valuer.NewString(flagger.FeatureEnableAIObservability.String()),
+		Active:     aiObservability,
+		Usage:      0,
+		UsageLimit: -1,
+		Route:      "",
+	})
+
 	if constants.IsDotMetricsEnabled {
 		for idx, feature := range featureSet {
 			if feature.Name == licensetypes.DotMetricsEnabled {

pkg/types/authtypes/role.go

@@ -20,6 +20,7 @@ var (
 	ErrCodeRoleEmptyPatch                   = errors.MustNewCode("role_empty_patch")
 	ErrCodeInvalidTypeRelation              = errors.MustNewCode("role_invalid_type_relation")
 	ErrCodeRoleNotFound                     = errors.MustNewCode("role_not_found")
+	ErrCodeRoleAlreadyExists                = errors.MustNewCode("role_already_exists")
 	ErrCodeRoleFailedTransactionsFromString = errors.MustNewCode("role_failed_transactions_from_string")
 	ErrCodeRoleUnsupported                  = errors.MustNewCode("role_unsupported")
 	ErrCodeRoleHasUserAssignees             = errors.MustNewCode("role_has_user_assignees")
@@ -72,9 +73,20 @@ type Role struct {
 	OrgID       valuer.UUID   `bun:"org_id,type:string" json:"orgId" required:"true"`
 }
 
+type RoleWithTransactionGroups struct {
+	*Role
+	TransactionGroups TransactionGroups `json:"transactionGroups" required:"true" nullable:"false"`
+}
+
 type PostableRole struct {
-	Name        string `json:"name" required:"true"`
-	Description string `json:"description"`
+	Name              string            `json:"name" required:"true"`
+	Description       string            `json:"description" required:"true"`
+	TransactionGroups TransactionGroups `json:"transactionGroups" required:"true" nullable:"false"`
+}
+
+type UpdatableRole struct {
+	Description       string            `json:"description" required:"true"`
+	TransactionGroups TransactionGroups `json:"transactionGroups" required:"true" nullable:"false"`
 }
 
 type PatchableRole struct {
@@ -97,6 +109,22 @@ func NewRole(name, description string, roleType valuer.String, orgID valuer.UUID
 	}
 }
 
+func NewRoleWithTransactionGroups(name, description string, roleType valuer.String, orgID valuer.UUID, transactionGroups TransactionGroups) *RoleWithTransactionGroups {
+	role := NewRole(name, description, roleType, orgID)
+
+	return &RoleWithTransactionGroups{
+		Role:              role,
+		TransactionGroups: transactionGroups,
+	}
+}
+
+func MakeRoleWithTransactionGroups(role *Role, transactionGroups TransactionGroups) *RoleWithTransactionGroups {
+	return &RoleWithTransactionGroups{
+		Role:              role,
+		TransactionGroups: transactionGroups,
+	}
+}
+
 func NewManagedRoles(orgID valuer.UUID) []*Role {
 	return []*Role{
 		NewRole(SigNozAdminRoleName, SigNozAdminRoleDescription, RoleTypeManaged, orgID),
@@ -118,6 +146,18 @@ func (role *Role) PatchMetadata(description string) error {
 	return nil
 }
 
+func (role *RoleWithTransactionGroups) Update(description string, transactionGroups TransactionGroups) error {
+	err := role.ErrIfManaged()
+	if err != nil {
+		return err
+	}
+
+	role.Description = description
+	role.TransactionGroups = transactionGroups
+	role.UpdatedAt = time.Now()
+	return nil
+}
+
 func (role *Role) ErrIfManaged() error {
 	if role.Type == RoleTypeManaged {
 		return errors.Newf(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "cannot edit/delete managed role: %s", role.Name)
@@ -127,31 +167,58 @@ func (role *Role) ErrIfManaged() error {
 }
 
 func (role *PostableRole) UnmarshalJSON(data []byte) error {
-	type shadowPostableRole struct {
-		Name        string `json:"name"`
-		Description string `json:"description"`
-	}
+	type Alias PostableRole
+	var temp Alias
 
-	var shadowRole shadowPostableRole
-	if err := json.Unmarshal(data, &shadowRole); err != nil {
+	if err := json.Unmarshal(data, &temp); err != nil {
 		return err
 	}
 
-	if shadowRole.Name == "" {
+	if temp.Name == "" {
 		return errors.New(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "name is missing from the request")
 	}
 
-	if match := roleNameRegex.MatchString(shadowRole.Name); !match {
+	if match := roleNameRegex.MatchString(temp.Name); !match {
 		return errors.New(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "name must contain only lowercase letters (a-z) and hyphens (-), and be at most 50 characters long.")
 	}
 
-	if strings.HasPrefix(shadowRole.Name, managedRolePrefix) {
+	if strings.HasPrefix(temp.Name, managedRolePrefix) {
 		return errors.Newf(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "role name cannot start with %q as it is reserved for SigNoz managed roles.", managedRolePrefix)
 	}
 
-	role.Name = shadowRole.Name
-	role.Description = shadowRole.Description
+	if temp.TransactionGroups == nil {
+		return errors.New(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "transactionGroups is required").WithAdditional("send an empty array to create a role with no transaction groups")
+	}
 
+	role.Name = temp.Name
+	role.Description = temp.Description
+	role.TransactionGroups = temp.TransactionGroups
+	return nil
+}
+
+func (role *UpdatableRole) UnmarshalJSON(data []byte) error {
+	shadow := struct {
+		Description       *string           `json:"description"`
+		TransactionGroups TransactionGroups `json:"transactionGroups"`
+	}{}
+
+	if err := json.Unmarshal(data, &shadow); err != nil {
+		return err
+	}
+
+	// A pointer distinguishes an omitted/null description from an explicit empty string: the field
+	// must be sent (update reconciles to exactly what is given), but an empty string is allowed so a
+	// caller can deliberately clear the description.
+	if shadow.Description == nil {
+		return errors.New(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "description is required").WithAdditional("send an empty string to clear the description")
+	}
+
+	if shadow.TransactionGroups == nil {
+		return errors.New(errors.TypeInvalidInput, ErrCodeRoleInvalidInput, "transactionGroups is required").WithAdditional("send an empty array to clear the role's transaction groups")
+	}
+
+	role.Description = *shadow.Description
+	role.TransactionGroups = shadow.TransactionGroups
 	return nil
 }
 

pkg/types/authtypes/transaction.go

@@ -13,6 +13,13 @@ type Transaction struct {
 	Object   coretypes.Object `json:"object" required:"true"`
 }
 
+type TransactionGroup struct {
+	Relation    Relation              `json:"relation" required:"true"`
+	ObjectGroup coretypes.ObjectGroup `json:"objectGroup" required:"true"`
+}
+
+type TransactionGroups []*TransactionGroup
+
 type GettableTransaction struct {
 	Relation   Relation         `json:"relation" required:"true"`
 	Object     coretypes.Object `json:"object" required:"true"`
@@ -32,6 +39,18 @@ func NewTransaction(relation Relation, object coretypes.Object) (*Transaction, e
 	return &Transaction{ID: valuer.GenerateUUID(), Relation: relation, Object: object}, nil
 }
 
+func NewTransactionGroup(relation Relation, objectGroup coretypes.ObjectGroup) (*TransactionGroup, error) {
+	if err := coretypes.ErrIfVerbNotValidForResource(relation.Verb, objectGroup.Resource); err != nil {
+		return nil, err
+	}
+
+	if _, err := coretypes.NewObjectsFromObjectGroup(objectGroup); err != nil {
+		return nil, err
+	}
+
+	return &TransactionGroup{Relation: relation, ObjectGroup: objectGroup}, nil
+}
+
 func NewGettableTransaction(results []*TransactionWithAuthorization) []*GettableTransaction {
 	gettableTransactions := make([]*GettableTransaction, len(results))
 	for i, result := range results {
@@ -45,6 +64,10 @@ func NewGettableTransaction(results []*TransactionWithAuthorization) []*Gettable
 	return gettableTransactions
 }
 
+func (groups TransactionGroups) Diff(desired TransactionGroups) (additions, deletions TransactionGroups) {
+	return desired.subtract(groups), groups.subtract(desired)
+}
+
 func (transaction *Transaction) UnmarshalJSON(data []byte) error {
 	var shadow = struct {
 		Relation Relation
@@ -65,6 +88,71 @@ func (transaction *Transaction) UnmarshalJSON(data []byte) error {
 	return nil
 }
 
+func (transactionGroup *TransactionGroup) UnmarshalJSON(data []byte) error {
+	var shadow = struct {
+		Relation    Relation
+		ObjectGroup coretypes.ObjectGroup
+	}{}
+
+	err := json.Unmarshal(data, &shadow)
+	if err != nil {
+		return err
+	}
+
+	group, err := NewTransactionGroup(shadow.Relation, shadow.ObjectGroup)
+	if err != nil {
+		return err
+	}
+
+	*transactionGroup = *group
+	return nil
+}
+
 func (transaction *Transaction) TransactionKey() string {
 	return transaction.Relation.StringValue() + ":" + transaction.Object.Resource.Type.StringValue() + ":" + transaction.Object.Resource.Kind.String()
 }
+
+func (groups TransactionGroups) subtract(other TransactionGroups) TransactionGroups {
+	otherSelectors := other.selectorSet()
+
+	order := make([]string, 0)
+	grouped := make(map[string]*TransactionGroup)
+	for _, group := range groups {
+		for _, selector := range group.ObjectGroup.Selectors {
+			if _, ok := otherSelectors[group.selectorKey(selector)]; ok {
+				continue
+			}
+
+			groupKey := group.Relation.StringValue() + "|" + group.ObjectGroup.Resource.String()
+			out, ok := grouped[groupKey]
+			if !ok {
+				out = &TransactionGroup{Relation: group.Relation, ObjectGroup: coretypes.ObjectGroup{Resource: group.ObjectGroup.Resource, Selectors: make([]coretypes.Selector, 0)}}
+				grouped[groupKey] = out
+				order = append(order, groupKey)
+			}
+			out.ObjectGroup.Selectors = append(out.ObjectGroup.Selectors, selector)
+		}
+	}
+
+	result := make(TransactionGroups, 0, len(order))
+	for _, key := range order {
+		result = append(result, grouped[key])
+	}
+
+	return result
+}
+
+func (groups TransactionGroups) selectorSet() map[string]struct{} {
+	set := make(map[string]struct{})
+	for _, group := range groups {
+		for _, selector := range group.ObjectGroup.Selectors {
+			set[group.selectorKey(selector)] = struct{}{}
+		}
+	}
+
+	return set
+}
+
+func (group *TransactionGroup) selectorKey(selector coretypes.Selector) string {
+	return group.Relation.StringValue() + "|" + group.ObjectGroup.Resource.String() + "|" + selector.String()
+}

pkg/types/authtypes/tuple.go

@@ -47,14 +47,58 @@ func NewTuplesFromTransactions(transactions []*Transaction, subject string, orgI
 	return tuples, nil
 }
 
-// NewTuplesFromTransactionsWithCorrelations converts transactions to tuples for BatchCheck,
-// and for each transaction whose selector is not already a wildcard, generates an additional
-// tuple with the wildcard selector. This ensures that permissions granted via wildcard
-// selectors (e.g., dashboard:*) are checked alongside exact selectors (e.g., dashboard:abc-123).
-//
-// Returns:
-//   - tuples: all tuples to check (exact + correlated), keyed by transaction ID or generated correlation ID
-//   - correlations: maps transaction ID to a slice of correlation IDs for the additional tuples
+func NewTuplesFromTransactionGroups(name string, orgID valuer.UUID, transactionGroups []*TransactionGroup) ([]*openfgav1.TupleKey, error) {
+	tuples := make([]*openfgav1.TupleKey, 0)
+	subject := MustNewSubject(coretypes.NewResourceRole(), name, orgID, &coretypes.VerbAssignee)
+
+	for _, transactionGroup := range transactionGroups {
+		if err := coretypes.ErrIfVerbNotValidForResource(transactionGroup.Relation.Verb, transactionGroup.ObjectGroup.Resource); err != nil {
+			return nil, err
+		}
+
+		resource, err := coretypes.NewResourceFromTypeAndKind(transactionGroup.ObjectGroup.Resource.Type, transactionGroup.ObjectGroup.Resource.Kind)
+		if err != nil {
+			return nil, err
+		}
+
+		objectGroupTuples := NewTuples(resource, subject, transactionGroup.Relation, transactionGroup.ObjectGroup.Selectors, orgID)
+		tuples = append(tuples, objectGroupTuples...)
+	}
+
+	return tuples, nil
+}
+
+func MustNewTransactionGroupsFromTuples(tuples []*openfgav1.TupleKey) []*TransactionGroup {
+	objectsByRelation := make(map[string][]*coretypes.Object)
+
+	for _, tuple := range tuples {
+		verb, err := coretypes.NewVerb(tuple.GetRelation())
+		if err != nil {
+			panic(err)
+		}
+
+		object := coretypes.MustNewObjectFromString(tuple.GetObject())
+		objectsByRelation[verb.StringValue()] = append(objectsByRelation[verb.StringValue()], object)
+	}
+
+	transactionGroups := make([]*TransactionGroup, 0)
+	for _, verb := range coretypes.Verbs {
+		objects := objectsByRelation[verb.StringValue()]
+		if len(objects) == 0 {
+			continue
+		}
+
+		for _, objectGroup := range coretypes.NewObjectGroupsFromObjects(objects) {
+			transactionGroups = append(transactionGroups, &TransactionGroup{
+				Relation:    Relation{Verb: verb},
+				ObjectGroup: *objectGroup,
+			})
+		}
+	}
+
+	return transactionGroups
+}
+
 func NewTuplesFromTransactionsWithCorrelations(transactions []*Transaction, subject string, orgID valuer.UUID) (tuples map[string]*openfgav1.TupleKey, correlations map[string][]string, err error) {
 	tuples = make(map[string]*openfgav1.TupleKey)
 	correlations = make(map[string][]string)
@@ -83,10 +127,6 @@ func NewTuplesFromTransactionsWithCorrelations(transactions []*Transaction, subj
 	return tuples, correlations, nil
 }
 
-// NewTuplesFromTransactionsWithManagedRoles converts transactions to tuples for BatchCheck.
-// Direct role-assignment transactions (TypeRole + VerbAssignee) produce one tuple keyed by txn ID.
-// Other transactions are expanded via managedRolesByTransaction into role-assignee checks, keyed by "txnID:roleName".
-// Transactions with no managed role mapping are marked as pre-resolved (false) in the returned map.
 func NewTuplesFromTransactionsWithManagedRoles(
 	transactions []*Transaction,
 	subject string,
@@ -131,10 +171,6 @@ func NewTuplesFromTransactionsWithManagedRoles(
 	return tuples, preResolved, roleCorrelations, nil
 }
 
-// NewTransactionWithAuthorizationFromBatchResults merges batch check results into an ordered
-// slice of TransactionWithAuthorization matching the input transactions order.
-// preResolved contains txn IDs whose authorization was determined without BatchCheck.
-// roleCorrelations maps txn IDs to correlation IDs used for managed role checks.
 func NewTransactionWithAuthorizationFromBatchResults(
 	transactions []*Transaction,
 	batchResults map[string]*TupleKeyAuthorization,

pkg/types/coretypes/object.go

@@ -9,6 +9,7 @@ import (
 
 var (
 	ErrCodeInvalidPatchObject = errors.MustNewCode("authz_invalid_patch_objects")
+	ErrCodeInvalidObject      = errors.MustNewCode("authz_invalid_object")
 )
 
 type Object struct {

pkg/types/inframonitoringtypes/clusters.go

@@ -12,6 +12,7 @@ type Clusters struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []ClusterRecord        `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/daemonsets.go

@@ -12,6 +12,7 @@ type DaemonSets struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []DaemonSetRecord      `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/deployments.go

@@ -12,6 +12,7 @@ type Deployments struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []DeploymentRecord     `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/hosts.go

@@ -12,6 +12,7 @@ type Hosts struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []HostRecord           `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }
@@ -29,6 +30,10 @@ type HostRecord struct {
 	Meta              map[string]string `json:"meta" required:"true"`
 }
 
+type RequiredMetricsCheck struct {
+	MissingMetrics []string `json:"missingMetrics" required:"true"`
+}
+
 type PostableHosts struct {
 	Start   int64                `json:"start" required:"true"`
 	End     int64                `json:"end" required:"true"`

pkg/types/inframonitoringtypes/jobs.go

@@ -12,6 +12,7 @@ type Jobs struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []JobRecord            `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/namespaces.go

@@ -12,6 +12,7 @@ type Namespaces struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []NamespaceRecord      `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/nodes.go

@@ -12,6 +12,7 @@ type Nodes struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []NodeRecord           `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/pods.go

@@ -12,6 +12,7 @@ type Pods struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []PodRecord            `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/statefulsets.go

@@ -12,6 +12,7 @@ type StatefulSets struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []StatefulSetRecord    `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/inframonitoringtypes/volumes.go

@@ -12,6 +12,7 @@ type Volumes struct {
 	Type                   ResponseType           `json:"type" required:"true"`
 	Records                []VolumeRecord         `json:"records" required:"true" nullable:"false"`
 	Total                  int                    `json:"total" required:"true"`
+	RequiredMetricsCheck   RequiredMetricsCheck   `json:"requiredMetricsCheck" required:"true"`
 	EndTimeBeforeRetention bool                   `json:"endTimeBeforeRetention" required:"true"`
 	Warning                *qbtypes.QueryWarnData `json:"warning,omitempty"`
 }

pkg/types/llmpricingruletypes/pricing.go

@@ -125,8 +125,10 @@ type UpdatableLLMPricingRules struct {
 }
 
 type ListPricingRulesQuery struct {
-	Offset int `query:"offset" json:"offset"`
-	Limit  int `query:"limit"  json:"limit"`
+	Offset     int    `query:"offset" json:"offset"`
+	Limit      int    `query:"limit"  json:"limit"`
+	Search     string `query:"q" json:"q"`
+	IsOverride *bool  `query:"isOverride" json:"isOverride"`
 }
 
 type GettablePricingRules struct {

pkg/types/llmpricingruletypes/store.go

@@ -7,7 +7,7 @@ import (
 )
 
 type Store interface {
-	List(ctx context.Context, orgID valuer.UUID, offset, limit int) ([]*LLMPricingRule, int, error)
+	List(ctx context.Context, orgID valuer.UUID, offset, limit int, search string, isOverride *bool) ([]*LLMPricingRule, int, error)
 	Get(ctx context.Context, orgID, id valuer.UUID) (*LLMPricingRule, error)
 	GetBySourceID(ctx context.Context, orgID, sourceID valuer.UUID) (*LLMPricingRule, error)
 	Create(ctx context.Context, rule *LLMPricingRule) error

tests/fixtures/role.py

@@ -26,10 +26,10 @@ def find_role_by_name(signoz: types.SigNoz, token: str, name: str) -> str:
 
 
 def create_custom_role(signoz: types.SigNoz, token: str, name: str) -> str:
-    """Create a custom role and return its ID."""
+    """Create a custom role and return its ID. transactionGroups is required (send [] for none)."""
     resp = requests.post(
         signoz.self.host_configs["8080"].get(ROLES_BASE),
-        json={"name": name},
+        json={"name": name, "transactionGroups": []},
         headers={"Authorization": f"Bearer {token}"},
         timeout=5,
     )

tests/integration/testdata/inframonitoring/clusters_metric_key_pair.jsonl

@@ -1,36 +0,0 @@
-{"metric_name": "k8s.node.cpu.usage", "labels": {"k8s.node.name": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster", "deployment.environment": "prod"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster", "deployment.environment": "prod"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster", "deployment.environment": "prod"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n1", "k8s.node.uid": "acc-c1-n1-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n1-p-uid", "k8s.pod.name": "acc-c1-n1-p", "k8s.namespace.name": "ns-x", "k8s.node.name": "acc-c1-n1", "k8s.cluster.name": "kp-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": "acc-c1-n1-p-uid", "k8s.pod.name": "acc-c1-n1-p", "k8s.namespace.name": "ns-x", "k8s.node.name": "acc-c1-n1", "k8s.cluster.name": "kp-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": "acc-c1-n1-p-uid", "k8s.pod.name": "acc-c1-n1-p", "k8s.namespace.name": "ns-x", "k8s.node.name": "acc-c1-n1", "k8s.cluster.name": "kp-cluster"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.node.cpu.usage", "labels": {"k8s.node.name": "acc-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster", "deployment.environment": "prod"}, "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": "acc-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster", "deployment.environment": "prod"}, "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": "acc-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster", "deployment.environment": "prod"}, "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": "acc-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster"}, "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-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster"}, "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": "acc-c1-n2", "k8s.node.uid": "acc-c1-n2-uid", "k8s.cluster.name": "kp-cluster"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 1000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
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tests/integration/testdata/inframonitoring/daemonsets_metric_key_pair.jsonl

@@ -1,48 +0,0 @@
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-{"metric_name": "k8s.daemonset.desired_scheduled_nodes", "labels": {"k8s.daemonset.name": "kp-ds", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.daemonset.current_scheduled_nodes", "labels": {"k8s.daemonset.name": "kp-ds", "k8s.namespace.name": "ns-acc", "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.daemonset.desired_scheduled_nodes", "labels": {"k8s.daemonset.name": "kp-ds", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
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-{"metric_name": "k8s.daemonset.current_scheduled_nodes", "labels": {"k8s.daemonset.name": "kp-ds", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/deployments_metric_key_pair.jsonl

@@ -1,48 +0,0 @@
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-{"metric_name": "k8s.deployment.desired", "labels": {"k8s.deployment.name": "kp-dep", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.deployment.available", "labels": {"k8s.deployment.name": "kp-dep", "k8s.namespace.name": "ns-acc", "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.deployment.desired", "labels": {"k8s.deployment.name": "kp-dep", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.deployment.available", "labels": {"k8s.deployment.name": "kp-dep", "k8s.namespace.name": "ns-acc", "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.deployment.desired", "labels": {"k8s.deployment.name": "kp-dep", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.deployment.available", "labels": {"k8s.deployment.name": "kp-dep", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/hosts_metric_key_pair.jsonl

@@ -1,36 +0,0 @@
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "user"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 100, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "user"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 200, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "user"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 300, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "system"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 50, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "system"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 100, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "system"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 150, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "idle"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 400, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "idle"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 600, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "idle"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 800, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "wait"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 10, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "wait"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 20, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.cpu.time", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "wait"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 30, "temporality": "Cumulative", "type_": "Sum", "is_monotonic": true}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "used", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 2000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "used", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 2100000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "used", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2200000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "free", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 6000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "free", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 5900000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "free", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 5800000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "buffered", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 500000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "buffered", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 500000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "buffered", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 500000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "cached", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 1500000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "cached", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 1500000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.memory.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "cached", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 1500000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.cpu.load_average.15m", "labels": {"host.name": "kp-h1", "os.type": "linux"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 1.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "system.cpu.load_average.15m", "labels": {"host.name": "kp-h1", "os.type": "linux"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 1.55, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "system.cpu.load_average.15m", "labels": {"host.name": "kp-h1", "os.type": "linux"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 1.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "used", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 50000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "used", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 51000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "used", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 52000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "free", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 50000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "free", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 49000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "free", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 48000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "reserved", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 5000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "reserved", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 5000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}
-{"metric_name": "system.filesystem.usage", "labels": {"host.name": "kp-h1", "os.type": "linux", "state": "reserved", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 5000000000, "temporality": "Unspecified", "type_": "Sum", "is_monotonic": false}

tests/integration/testdata/inframonitoring/jobs_metric_key_pair.jsonl

@@ -1,54 +0,0 @@
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.phase", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.active_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.failed_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.job.successful_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.desired_successful_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.active_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.failed_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.job.successful_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.desired_successful_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.active_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.failed_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.job.successful_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "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.job.desired_successful_pods", "labels": {"k8s.job.name": "kp-job", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/namespaces_metric_key_pair.jsonl

@@ -1,18 +0,0 @@
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-ns", "k8s.cluster.name": "cluster-x", "deployment.environment": "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": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-ns", "k8s.cluster.name": "cluster-x", "deployment.environment": "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": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-ns", "k8s.cluster.name": "cluster-x", "deployment.environment": "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": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-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": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-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": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-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": "acc-p1a-uid", "k8s.pod.name": "acc-p1a", "k8s.namespace.name": "kp-ns", "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": "kp-ns", "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": "kp-ns", "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": "kp-ns", "k8s.cluster.name": "cluster-x", "deployment.environment": "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": "acc-p1b-uid", "k8s.pod.name": "acc-p1b", "k8s.namespace.name": "kp-ns", "k8s.cluster.name": "cluster-x", "deployment.environment": "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": "acc-p1b-uid", "k8s.pod.name": "acc-p1b", "k8s.namespace.name": "kp-ns", "k8s.cluster.name": "cluster-x", "deployment.environment": "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": "acc-p1b-uid", "k8s.pod.name": "acc-p1b", "k8s.namespace.name": "kp-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": "acc-p1b-uid", "k8s.pod.name": "acc-p1b", "k8s.namespace.name": "kp-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": "acc-p1b-uid", "k8s.pod.name": "acc-p1b", "k8s.namespace.name": "kp-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": "acc-p1b-uid", "k8s.pod.name": "acc-p1b", "k8s.namespace.name": "kp-ns", "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": "kp-ns", "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": "kp-ns", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/nodes_metric_key_pair.jsonl

@@ -1,18 +0,0 @@
-{"metric_name": "k8s.node.cpu.usage", "labels": {"k8s.node.name": "kp-n1", "k8s.node.uid": "kp-n1-uid", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "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": "kp-n1", "k8s.node.uid": "kp-n1-uid", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "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": "kp-n1", "k8s.node.uid": "kp-n1-uid", "k8s.cluster.name": "cluster-x", "deployment.environment": "prod"}, "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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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}
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-{"metric_name": "k8s.node.memory.working_set", "labels": {"k8s.node.name": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "kp-n1", "k8s.node.uid": "kp-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": "acc-pod-1a-uid", "k8s.pod.name": "acc-pod-1a", "k8s.namespace.name": "ns-a", "k8s.node.name": "kp-n1", "k8s.cluster.name": "cluster-x", "k8s.node.uid": "kp-n1-uid"}, "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-pod-1a-uid", "k8s.pod.name": "acc-pod-1a", "k8s.namespace.name": "ns-a", "k8s.node.name": "kp-n1", "k8s.cluster.name": "cluster-x", "k8s.node.uid": "kp-n1-uid"}, "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-pod-1a-uid", "k8s.pod.name": "acc-pod-1a", "k8s.namespace.name": "ns-a", "k8s.node.name": "kp-n1", "k8s.cluster.name": "cluster-x", "k8s.node.uid": "kp-n1-uid"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/pods_metric_key_pair.jsonl

@@ -1,21 +0,0 @@
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-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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__", "deployment.environment": "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": "kp-p1-uid", "k8s.pod.name": "kp-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__", "deployment.environment": "prod"}, "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": "kp-p1-uid", "k8s.pod.name": "kp-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": 0.25, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:02:00+00:00", "value": 0.25, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:04:00+00:00", "value": 0.25, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:02:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:04:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": 524288000, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:02:00+00:00", "value": 524288000, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:04:00+00:00", "value": 524288000, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:02:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:04:00+00:00", "value": 0.5, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": 0.25, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:02:00+00:00", "value": 0.25, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:04:00+00:00", "value": 0.25, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:02:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "kp-p1-uid", "k8s.pod.name": "kp-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": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/statefulsets_metric_key_pair.jsonl

@@ -1,48 +0,0 @@
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory.working_set", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "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.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.4, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.phase", "labels": {"k8s.pod.uid": "acc-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "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-1-p1-uid", "k8s.pod.name": "acc-1-p1", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu.usage", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.cpu_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_request_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 0.6, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.pod.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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.memory_limit_utilization", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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.phase", "labels": {"k8s.pod.uid": "acc-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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-1-p2-uid", "k8s.pod.name": "acc-1-p2", "k8s.namespace.name": "ns-acc", "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.statefulset.desired_pods", "labels": {"k8s.statefulset.name": "kp-sts", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.statefulset.current_pods", "labels": {"k8s.statefulset.name": "kp-sts", "k8s.namespace.name": "ns-acc", "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.statefulset.desired_pods", "labels": {"k8s.statefulset.name": "kp-sts", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.statefulset.current_pods", "labels": {"k8s.statefulset.name": "kp-sts", "k8s.namespace.name": "ns-acc", "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.statefulset.desired_pods", "labels": {"k8s.statefulset.name": "kp-sts", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 3, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.statefulset.current_pods", "labels": {"k8s.statefulset.name": "kp-sts", "k8s.namespace.name": "ns-acc", "k8s.cluster.name": "cluster-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 2, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/volumes_formula_operand_missing.jsonl

@@ -1,12 +0,0 @@
-{"metric_name": "k8s.volume.capacity", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 100000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.capacity", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 100000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.capacity", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 100000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 1000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 1000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 1000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.free", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 800000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.free", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 800000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.free", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 800000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.used", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 200000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.used", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 200000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.used", "labels": {"k8s.persistentvolumeclaim.name": "fop-pvc", "k8s.pod.uid": "fop-pvc-uid", "k8s.pod.name": "pod-fop-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 200000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/testdata/inframonitoring/volumes_metric_key_pair.jsonl

@@ -1,15 +0,0 @@
-{"metric_name": "k8s.volume.available", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 30000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.available", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 30000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.available", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 30000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.capacity", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 100000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.capacity", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 100000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.capacity", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x", "deployment.environment": "prod"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 100000000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 1000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 1000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 1000000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.free", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 800000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.free", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 800000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.free", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 800000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.used", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:00:00+00:00", "value": 200000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.used", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:02:00+00:00", "value": 200000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}
-{"metric_name": "k8s.volume.inodes.used", "labels": {"k8s.persistentvolumeclaim.name": "kp-pvc", "k8s.pod.uid": "kp-pvc-uid", "k8s.pod.name": "pod-kp-pvc", "k8s.namespace.name": "ns-acc", "k8s.node.name": "node-x", "k8s.cluster.name": "cluster-x", "k8s.statefulset.name": "ss-x"}, "timestamp": "2025-01-10T10:04:00+00:00", "value": 200000.0, "temporality": "Unspecified", "type_": "Gauge", "is_monotonic": false}

tests/integration/tests/inframonitoring/01_hosts.py

@@ -11,7 +11,7 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/hosts"
 
@@ -56,8 +56,7 @@ def test_hosts_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["hostName"] for r in data["records"]} == set(exp_by_host.keys())
 
@@ -80,108 +79,45 @@ def test_hosts_accuracy(
             assert compare_values(record[field], exp[field], 1e-9), f"{record['hostName']}.{field}: got {record[field]}, expected {exp[field]}"
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: a required host metric was never ingested. Post-#11754 the
-        # querier drops it instead of hard-erroring, so the endpoint returns 200
-        # with the hosts that DO have data; the never-seen metric's column is the
-        # -1 sentinel and a "has never been received" warning is surfaced.
-        pytest.param(
-            {
-                "dataset": "hosts_missing_metrics.jsonl",  # seeds only system.cpu.time
-                "body": {"filter": {"expression": "host.name = 'miss-h1'"}},
-                # singular form is "has", plural (>1 missing) is "have" -> match the common stem
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "system.memory.usage",
-                    "system.cpu.load_average.15m",
-                    "system.filesystem.usage",
-                ],
-                # cpu/wait derive from the present system.cpu.time; the rest come
-                # from never-seen metrics -> -1 sentinel.
-                "data_fields": ["cpu", "wait"],
-                "no_data_fields": ["memory", "load15", "diskUsage"],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (seen on some metrics) but
-        # was never seen together with the host metrics. deployment.environment is
-        # seeded on system.memory.usage + system.filesystem.usage only, so the key
-        # resolves (the page-groups IN-filter parses -> no 400) but the cpu.time /
-        # load_average metrics miss the (metric, key) pair and the statement builder
-        # falls back to raw labels, surfacing "key `...` not found on metric ...".
-        # Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "hosts_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "host.name = 'kp-h1'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_hosts_warnings(
+def test_hosts_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data),
-    not hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """Seed only system.cpu.time; assert other 3 required metrics flagged missing."""
     now = datetime.now(tz=UTC).replace(microsecond=0)
     insert_metrics(
         Metrics.load_from_file(
-            get_testdata_file_path(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/hosts_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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
+    assert response.status_code == HTTPStatus.OK
     data = response.json()["data"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == {
+        "system.memory.usage",
+        "system.cpu.load_average.15m",
+        "system.filesystem.usage",
+    }
+    # Endpoint short-circuits when any required metric is missing:
+    # records is empty and total=0 regardless of which hosts have partial data.
+    # See pkg/modules/inframonitoring/implinframonitoring/module.go:84-89.
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

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

@@ -11,11 +11,26 @@ 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, get_all_warnings
+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__"
 
@@ -101,8 +116,7 @@ def test_pods_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    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())
 
@@ -148,115 +162,42 @@ def test_pods_accuracy(
         assert record["podAge"] == expected_age_ms, f"{pod_name}.podAge: got {record['podAge']}, expected {expected_age_ms}"
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: required metrics were never ingested. Post-#11754 the querier
-        # drops them (no hard error), so the endpoint returns 200 with the pod that
-        # DOES have data; never-seen columns are the -1 sentinel and a
-        # "have never been received" warning is surfaced. Pods has no formulas, so
-        # each missing metric maps straight to one -1 column.
-        pytest.param(
-            {
-                "dataset": "pods_missing_metrics.jsonl",  # seeds only k8s.pod.cpu.usage
-                "body": {"filter": {"expression": "k8s.pod.name = 'miss-p1'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "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",
-                ],
-                # podCPU derives from the present k8s.pod.cpu.usage; the rest from
-                # never-seen metrics -> -1 sentinel.
-                "data_fields": ["podCPU"],
-                "no_data_fields": [
-                    "podCPURequest",
-                    "podCPULimit",
-                    "podMemory",
-                    "podMemoryRequest",
-                    "podMemoryLimit",
-                ],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.pod.cpu.usage only) but was never seen together with the
-        # other pod metrics. The key resolves (the page-groups IN-filter parses ->
-        # no 400), but B-F miss the (metric, key) pair and the statement builder
-        # falls back to raw labels, surfacing "key `...` not found on metric ...".
-        # Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "pods_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.pod.name = 'kp-p1'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_pods_warnings(
+def test_pods_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """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(
-            f"inframonitoring/{case['dataset']}",
+            "inframonitoring/pods_missing_metrics.jsonl",
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

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

@@ -11,10 +11,24 @@ 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, get_all_warnings
+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,
@@ -57,8 +71,7 @@ def test_nodes_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["nodeName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -94,107 +107,38 @@ def test_nodes_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: required metrics were never ingested. Post-#11754 the querier
-        # drops them (no hard error), so the endpoint returns 200 with the node that
-        # DOES have data; never-seen columns are the -1 sentinel + a
-        # "have never been received" warning. Nodes has no formulas, so each missing
-        # metric maps straight to one -1 column.
-        pytest.param(
-            {
-                "dataset": "nodes_missing_metrics.jsonl",  # seeds only k8s.node.cpu.usage
-                "body": {"filter": {"expression": "k8s.node.name = 'miss-n1'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "k8s.node.allocatable_cpu",
-                    "k8s.node.memory.working_set",
-                    "k8s.node.allocatable_memory",
-                ],
-                # nodeCPU derives from the present k8s.node.cpu.usage; the rest from
-                # never-seen metrics -> -1 sentinel.
-                "data_fields": ["nodeCPU"],
-                "no_data_fields": ["nodeCPUAllocatable", "nodeMemory", "nodeMemoryAllocatable"],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.node.cpu.usage only) but was never seen together with the
-        # other node metrics. The key resolves (the page-groups IN-filter parses ->
-        # no 400), but B/C/D miss the (metric, key) pair and the statement builder
-        # falls back to raw labels, surfacing "key `...` not found on metric ...".
-        # Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "nodes_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.node.name = 'kp-n1'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_nodes_warnings(
+def test_nodes_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """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(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/nodes_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.node.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

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

@@ -11,10 +11,18 @@ 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, get_all_warnings
+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,
@@ -63,8 +71,7 @@ def test_namespaces_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["namespaceName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -92,103 +99,38 @@ def test_namespaces_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: a required metric was never ingested. Post-#11754 the querier
-        # drops it (no hard error), so the endpoint returns 200 with the namespace
-        # that DOES have data; the never-seen column is the -1 sentinel + a
-        # "have never been received" warning. Namespaces has no formulas (2 columns:
-        # namespaceCPU=A, namespaceMemory=D). Default groupBy is two keys
-        # [k8s.namespace.name, k8s.cluster.name]; the seed carries both so the
-        # page-groups IN-filter parses.
-        pytest.param(
-            {
-                "dataset": "namespaces_missing_metrics.jsonl",  # seeds only k8s.pod.cpu.usage
-                "body": {"filter": {"expression": "k8s.namespace.name = 'miss-ns'"}},
-                "warn_substrings": ["never been received", "k8s.pod.memory.working_set"],
-                "warn_names": [],
-                "data_fields": ["namespaceCPU"],
-                "no_data_fields": ["namespaceMemory"],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.pod.cpu.usage only) but was never seen together with
-        # k8s.pod.memory.working_set. The key resolves (page-groups IN-filter parses
-        # -> no 400), but the memory metric misses the (metric, key) pair and the
-        # statement builder falls back to raw labels, surfacing
-        # "key `...` not found on metric ...". Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "namespaces_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.namespace.name = 'kp-ns'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_namespaces_warnings(
+def test_namespaces_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """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(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/namespaces_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/inframonitoring/05_clusters.py

@@ -11,10 +11,21 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/clusters"
 
+# Required metrics for the v2 clusters endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/clusters_constants.go:23-30).
+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",
+}
+
 
 def test_clusters_accuracy(
     signoz: types.SigNoz,
@@ -63,8 +74,7 @@ def test_clusters_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["clusterName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -103,106 +113,38 @@ def test_clusters_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: a required metric was never ingested. Post-#11754 the querier
-        # drops it (no hard error), so the endpoint returns 200 with the cluster
-        # that DOES have data; never-seen columns are the -1 sentinel + a
-        # "have never been received" warning. Clusters has no formulas
-        # (clusterCPU=A, clusterCPUAllocatable=B, clusterMemory=C,
-        # clusterMemoryAllocatable=D).
-        pytest.param(
-            {
-                "dataset": "clusters_missing_metrics.jsonl",  # seeds only k8s.node.cpu.usage
-                "body": {"filter": {"expression": "k8s.cluster.name = 'miss-cluster'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "k8s.node.allocatable_cpu",
-                    "k8s.node.memory.working_set",
-                    "k8s.node.allocatable_memory",
-                ],
-                "data_fields": ["clusterCPU"],
-                "no_data_fields": ["clusterCPUAllocatable", "clusterMemory", "clusterMemoryAllocatable"],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.node.cpu.usage only) but was never seen together with the
-        # other node metrics. The key resolves (page-groups IN-filter parses -> no
-        # 400), but B/C/D miss the (metric, key) pair and the statement builder
-        # falls back to raw labels, surfacing "key `...` not found on metric ...".
-        # Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "clusters_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.cluster.name = 'kp-cluster'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_clusters_warnings(
+def test_clusters_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """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(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/clusters_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.node.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/inframonitoring/06_volumes.py

@@ -11,10 +11,20 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/pvcs"
 
+# Required metrics for the v2 volumes endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/volumes_constants.go:20-27).
+REQUIRED_METRICS = {
+    "k8s.volume.available",
+    "k8s.volume.capacity",
+    "k8s.volume.inodes",
+    "k8s.volume.inodes.free",
+    "k8s.volume.inodes.used",
+}
+
 
 def test_volumes_accuracy(
     signoz: types.SigNoz,
@@ -61,8 +71,7 @@ def test_volumes_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["persistentVolumeClaimName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -108,104 +117,38 @@ def test_volumes_accuracy(
             assert compare_values(record[field], exp[field], 1e-6), f"{record['persistentVolumeClaimName']}.{field}: got {record[field]}, expected {exp[field]}"
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: a metric was never ingested. Post-#11754 the querier drops it
-        # (no hard error), so the endpoint returns 200 with whatever flowed; the
-        # never-seen column is the -1 sentinel + a "have never been received"
-        # warning. Here we omit the FORMULA OPERAND k8s.volume.available
-        # (volumeUsage = capacity - available): since A uses TimeAggregationAvg it is
-        # NOT zero-defaultable, so the formula drops the group -> volumeUsage == -1
-        # (it does NOT fall back to capacity). capacity + inodes stay real.
-        pytest.param(
-            {
-                "dataset": "volumes_formula_operand_missing.jsonl",
-                "body": {"filter": {"expression": "k8s.persistentvolumeclaim.name = 'fop-pvc'"}},
-                "warn_substrings": ["never been received", "k8s.volume.available"],
-                "warn_names": [],
-                "data_fields": ["volumeCapacity", "volumeInodes", "volumeInodesFree", "volumeInodesUsed"],
-                "no_data_fields": ["volumeAvailable", "volumeUsage"],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.volume.capacity only) but was never seen together with the
-        # other volume metrics. The key resolves (page-groups IN-filter parses ->
-        # no 400), but the other metrics miss the (metric, key) pair and the
-        # statement builder falls back to raw labels, surfacing
-        # "key `...` not found on metric ...". Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "volumes_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.persistentvolumeclaim.name = 'kp-pvc'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_volumes_warnings(
+def test_volumes_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers a never-seen formula operand (scenario 1: volumeUsage
-    stays -1, not capacity) and a never-seen (metric, key) pair via groupBy
-    (scenario 2)."""
+    """Seed only k8s.volume.available; other 4 required metrics flagged missing."""
     now = datetime.now(tz=UTC).replace(microsecond=0)
     insert_metrics(
         Metrics.load_from_file(
-            get_testdata_file_path(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/volumes_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.volume.available"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/inframonitoring/07_deployments.py

@@ -11,10 +11,24 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/deployments"
 
+# Required metrics for the v2 deployments endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/deployments_constants.go:24-34).
+REQUIRED_METRICS = {
+    "k8s.pod.phase",
+    "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.deployment.desired",
+    "k8s.deployment.available",
+}
+
 
 def test_deployments_accuracy(
     signoz: types.SigNoz,
@@ -61,8 +75,7 @@ def test_deployments_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["deploymentName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -110,113 +123,38 @@ def test_deployments_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: required metrics were never ingested. Post-#11754 the querier
-        # drops them (no hard error), so the endpoint returns 200 with the deployment
-        # that DOES have data; never-seen columns are the -1 sentinel + a
-        # "have never been received" warning. No formulas; pod- and deployment-level
-        # metrics each map to one column.
-        pytest.param(
-            {
-                "dataset": "deployments_missing_metrics.jsonl",  # seeds only k8s.pod.cpu.usage
-                "body": {"filter": {"expression": "k8s.deployment.name = 'miss-dep'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "k8s.pod.memory.working_set",
-                    "k8s.deployment.desired",
-                    "k8s.deployment.available",
-                ],
-                "data_fields": ["deploymentCPU"],
-                "no_data_fields": [
-                    "deploymentCPURequest",
-                    "deploymentCPULimit",
-                    "deploymentMemory",
-                    "deploymentMemoryRequest",
-                    "deploymentMemoryLimit",
-                    "desiredPods",
-                    "availablePods",
-                ],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.pod.cpu.usage only) but was never seen together with the
-        # other metrics. The key resolves (page-groups IN-filter parses -> no 400),
-        # but the other metrics miss the (metric, key) pair and the statement builder
-        # falls back to raw labels, surfacing "key `...` not found on metric ...".
-        # Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "deployments_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.deployment.name = 'kp-dep'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_deployments_warnings(
+def test_deployments_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """Seed only k8s.pod.cpu.usage; assert other 8 required metrics flagged missing."""
     now = datetime.now(tz=UTC).replace(microsecond=0)
     insert_metrics(
         Metrics.load_from_file(
-            get_testdata_file_path(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/deployments_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/inframonitoring/08_statefulsets.py

@@ -11,10 +11,24 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/statefulsets"
 
+# Required metrics for the v2 statefulsets endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/statefulsets_constants.go:24-34).
+REQUIRED_METRICS = {
+    "k8s.pod.phase",
+    "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.statefulset.desired_pods",
+    "k8s.statefulset.current_pods",
+}
+
 
 def test_statefulsets_accuracy(
     signoz: types.SigNoz,
@@ -61,8 +75,7 @@ def test_statefulsets_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["statefulSetName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -110,116 +123,38 @@ def test_statefulsets_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: required metrics were never ingested. Post-#11754 the querier
-        # drops them (no hard error), so the endpoint returns 200 with the
-        # statefulset that DOES have data; never-seen columns are the -1 sentinel +
-        # a "have never been received" warning. No formulas; each missing metric
-        # maps to one -1 column.
-        pytest.param(
-            {
-                "dataset": "statefulsets_missing_metrics.jsonl",  # seeds only k8s.pod.cpu.usage
-                "body": {"filter": {"expression": "k8s.statefulset.name = 'miss-ss'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "k8s.pod.memory.working_set",
-                    "k8s.statefulset.desired_pods",
-                    "k8s.statefulset.current_pods",
-                ],
-                "data_fields": ["statefulSetCPU"],
-                "no_data_fields": [
-                    "statefulSetCPURequest",
-                    "statefulSetCPULimit",
-                    "statefulSetMemory",
-                    "statefulSetMemoryRequest",
-                    "statefulSetMemoryLimit",
-                    "desiredPods",
-                    "currentPods",
-                ],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2 (FAITHFUL (metric,key)-pair): pods are NOT labelled with
-        # k8s.statefulset.name, while the statefulset-level metrics ARE. Grouping by
-        # the default [statefulset.name, namespace.name, cluster.name], the base
-        # filter (k8s.statefulset.name != '') excludes the label-less pod metrics ->
-        # statefulSet* (pod-derived) come back -1, while desiredPods/currentPods
-        # (statefulset metrics) stay real. Reproduces the production response.
-        # The "key ... not found on metric" warning fires deterministically: the
-        # (pod-metric, k8s.statefulset.name) pair is absent from distributed_metadata
-        # (insert_metrics truncates it per function; the suite runs serially), so the
-        # statement builder falls back to raw labels and warns. The -1 partial render
-        # is the robust core.
-        pytest.param(
-            {
-                "dataset": "statefulsets_metric_key_pair.jsonl",
-                "body": {"filter": {"expression": "k8s.statefulset.name = 'kp-sts'"}},
-                "warn_substrings": ["key `k8s.statefulset.name` not found on metric"],
-                "warn_names": [],
-                "data_fields": ["desiredPods", "currentPods"],
-                "no_data_fields": [
-                    "statefulSetCPU",
-                    "statefulSetCPURequest",
-                    "statefulSetCPULimit",
-                    "statefulSetMemory",
-                    "statefulSetMemoryRequest",
-                    "statefulSetMemoryLimit",
-                ],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_statefulsets_warnings(
+def test_statefulsets_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and a faithful never-seen
-    (metric, key) pair (scenario 2: pod columns -1, statefulset counts real)."""
+    """Seed only k8s.pod.cpu.usage; assert other 8 required metrics flagged missing."""
     now = datetime.now(tz=UTC).replace(microsecond=0)
     insert_metrics(
         Metrics.load_from_file(
-            get_testdata_file_path(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/statefulsets_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/inframonitoring/09_jobs.py

@@ -11,10 +11,26 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/jobs"
 
+# Required metrics for the v2 jobs endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/jobs_constants.go:24-36).
+REQUIRED_METRICS = {
+    "k8s.pod.phase",
+    "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.job.active_pods",
+    "k8s.job.failed_pods",
+    "k8s.job.successful_pods",
+    "k8s.job.desired_successful_pods",
+}
+
 
 def test_jobs_accuracy(
     signoz: types.SigNoz,
@@ -62,8 +78,7 @@ def test_jobs_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["jobName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -113,115 +128,38 @@ def test_jobs_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: required metrics were never ingested. Post-#11754 the querier
-        # drops them (no hard error), so the endpoint returns 200 with the job that
-        # DOES have data; never-seen columns are the -1 sentinel + a
-        # "have never been received" warning. No formulas; pod- and job-level
-        # metrics each map to one column.
-        pytest.param(
-            {
-                "dataset": "jobs_missing_metrics.jsonl",  # seeds only k8s.pod.cpu.usage
-                "body": {"filter": {"expression": "k8s.job.name = 'miss-job'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "k8s.pod.memory.working_set",
-                    "k8s.job.desired_successful_pods",
-                    "k8s.job.successful_pods",
-                ],
-                "data_fields": ["jobCPU"],
-                "no_data_fields": [
-                    "jobCPURequest",
-                    "jobCPULimit",
-                    "jobMemory",
-                    "jobMemoryRequest",
-                    "jobMemoryLimit",
-                    "desiredSuccessfulPods",
-                    "activePods",
-                    "failedPods",
-                    "successfulPods",
-                ],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2: groupBy a key that IS in metadata (deployment.environment is
-        # seeded on k8s.pod.cpu.usage only) but was never seen together with the
-        # other metrics. The key resolves (page-groups IN-filter parses -> no 400),
-        # but the other metrics miss the (metric, key) pair and the statement builder
-        # falls back to raw labels, surfacing "key `...` not found on metric ...".
-        # Still 200, no hard error.
-        pytest.param(
-            {
-                "dataset": "jobs_metric_key_pair.jsonl",
-                "body": {
-                    "filter": {"expression": "k8s.job.name = 'kp-job'"},
-                    "groupBy": [
-                        {
-                            "name": "deployment.environment",
-                            "fieldDataType": "string",
-                            "fieldContext": "resource",
-                        }
-                    ],
-                },
-                "warn_substrings": ["key `deployment.environment` not found on metric"],
-                "warn_names": [],
-                "data_fields": [],
-                "no_data_fields": [],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_jobs_warnings(
+def test_jobs_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and never-seen
-    (metric, key) pairs via groupBy (scenario 2)."""
+    """Seed only k8s.pod.cpu.usage; assert other 10 required metrics flagged missing."""
     now = datetime.now(tz=UTC).replace(microsecond=0)
     insert_metrics(
         Metrics.load_from_file(
-            get_testdata_file_path(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/jobs_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/inframonitoring/10_daemonsets.py

@@ -11,10 +11,24 @@ 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, get_all_warnings
+from fixtures.querier import compare_values
 
 ENDPOINT = "/api/v2/infra_monitoring/daemonsets"
 
+# Required metrics for the v2 daemonsets endpoint
+# (pkg/modules/inframonitoring/implinframonitoring/daemonsets_constants.go:24-34).
+REQUIRED_METRICS = {
+    "k8s.pod.phase",
+    "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.daemonset.desired_scheduled_nodes",
+    "k8s.daemonset.current_scheduled_nodes",
+}
+
 
 def test_daemonsets_accuracy(
     signoz: types.SigNoz,
@@ -61,8 +75,7 @@ def test_daemonsets_accuracy(
     # Shape/contract.
     assert data["total"] == len(expected["records"])
     assert len(data["records"]) == len(expected["records"])
-    # Full data present -> no warnings surfaced.
-    assert get_all_warnings(response.json()) == []
+    assert data["requiredMetricsCheck"]["missingMetrics"] == []
     assert data["endTimeBeforeRetention"] is False
     assert {r["daemonSetName"] for r in data["records"]} == set(exp_by_name.keys())
 
@@ -110,116 +123,38 @@ def test_daemonsets_accuracy(
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
 
 
-@pytest.mark.parametrize(
-    "case",
-    [
-        # Scenario 1: required metrics were never ingested. Post-#11754 the querier
-        # drops them (no hard error), so the endpoint returns 200 with the daemonset
-        # that DOES have data; never-seen columns are the -1 sentinel + a
-        # "have never been received" warning. No formulas; pod- and daemonset-level
-        # metrics each map to one column.
-        pytest.param(
-            {
-                "dataset": "daemonsets_missing_metrics.jsonl",  # seeds only k8s.pod.cpu.usage
-                "body": {"filter": {"expression": "k8s.daemonset.name = 'miss-ds'"}},
-                "warn_substrings": ["never been received"],
-                "warn_names": [
-                    "k8s.pod.memory.working_set",
-                    "k8s.daemonset.desired_scheduled_nodes",
-                    "k8s.daemonset.current_scheduled_nodes",
-                ],
-                "data_fields": ["daemonSetCPU"],
-                "no_data_fields": [
-                    "daemonSetCPURequest",
-                    "daemonSetCPULimit",
-                    "daemonSetMemory",
-                    "daemonSetMemoryRequest",
-                    "daemonSetMemoryLimit",
-                    "desiredNodes",
-                    "currentNodes",
-                ],
-            },
-            id="metric_never_seen",
-        ),
-        # Scenario 2 (FAITHFUL (metric,key)-pair): pods are NOT labelled with
-        # k8s.daemonset.name, while the daemonset-level metrics ARE. Grouping by the
-        # default [daemonset.name, namespace.name, cluster.name], the base filter
-        # (k8s.daemonset.name != '') excludes the label-less pod metrics ->
-        # daemonSet* (pod-derived) come back -1, while desiredNodes/currentNodes
-        # (daemonset metrics) stay real. Mirrors the statefulsets faithful case.
-        # The "key ... not found on metric" warning fires deterministically: the
-        # (pod-metric, k8s.daemonset.name) pair is absent from distributed_metadata
-        # (insert_metrics truncates it per function; the suite runs serially), so the
-        # statement builder falls back to raw labels and warns. The -1 partial render
-        # is the robust core.
-        pytest.param(
-            {
-                "dataset": "daemonsets_metric_key_pair.jsonl",
-                "body": {"filter": {"expression": "k8s.daemonset.name = 'kp-ds'"}},
-                "warn_substrings": ["key `k8s.daemonset.name` not found on metric"],
-                "warn_names": [],
-                "data_fields": ["desiredNodes", "currentNodes"],
-                "no_data_fields": [
-                    "daemonSetCPU",
-                    "daemonSetCPURequest",
-                    "daemonSetCPULimit",
-                    "daemonSetMemory",
-                    "daemonSetMemoryRequest",
-                    "daemonSetMemoryLimit",
-                ],
-            },
-            id="metric_key_pair_not_seen",
-        ),
-    ],
-)
-def test_daemonsets_warnings(
+def test_daemonsets_missing_metrics(
     signoz: types.SigNoz,
     create_user_admin: None,  # pylint: disable=unused-argument
     get_token,
     insert_metrics,
-    case: dict,
 ) -> None:
-    """Data-availability gaps surface as non-blocking warnings (200 + data), not
-    hard errors. Covers never-seen metrics (scenario 1) and a faithful never-seen
-    (metric, key) pair (scenario 2: pod columns -1, daemonset counts real)."""
+    """Seed only k8s.pod.cpu.usage; assert other 8 required metrics flagged missing."""
     now = datetime.now(tz=UTC).replace(microsecond=0)
     insert_metrics(
         Metrics.load_from_file(
-            get_testdata_file_path(f"inframonitoring/{case['dataset']}"),
+            get_testdata_file_path("inframonitoring/daemonsets_missing_metrics.jsonl"),
             base_time=now - timedelta(minutes=4),
         )
     )
 
     token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
-    body: dict = {
-        "start": int((now - timedelta(minutes=5)).timestamp() * 1000),
-        "end": int(now.timestamp() * 1000),
-        "limit": 50,
-    }
-    body.update(case["body"])
-
     response = requests.post(
         signoz.self.host_configs["8080"].get(ENDPOINT),
         headers={"authorization": f"Bearer {token}"},
-        json=body,
+        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"]
-    warnings = get_all_warnings(response.json())
 
-    for substr in case["warn_substrings"]:
-        assert any(substr in w["message"] for w in warnings), f"{substr!r} not surfaced: {warnings!r}"
-    for name in case["warn_names"]:
-        assert any(name in w["message"] for w in warnings), f"{name!r} not surfaced: {warnings!r}"
-
-    assert len(data["records"]) >= 1, f"expected at least one record: {data!r}"
-    if case["data_fields"] or case["no_data_fields"]:
-        record = data["records"][0]
-        for field in case["data_fields"]:
-            assert record[field] != -1, f"expected {field} populated, got {record[field]}"
-        for field in case["no_data_fields"]:
-            assert record[field] == -1, f"expected {field} == -1 sentinel, got {record[field]}"
+    assert set(data["requiredMetricsCheck"]["missingMetrics"]) == (REQUIRED_METRICS - {"k8s.pod.cpu.usage"})
+    assert data["records"] == []
+    assert data["total"] == 0
 
 
 @pytest.mark.parametrize(

tests/integration/tests/role/03_fga.py

@@ -63,7 +63,7 @@ def test_create_role_with_signoz_prefix_rejected(
     for name in ("signoz-custom", "signozcustom"):
         resp = requests.post(
             signoz.self.host_configs["8080"].get(ROLES_BASE),
-            json={"name": name},
+            json={"name": name, "transactionGroups": []},
             headers={"Authorization": f"Bearer {admin_token}"},
             timeout=5,
         )
@@ -175,7 +175,7 @@ def test_role_readonly_forbidden_operations(
     # Create role — forbidden.
     resp = requests.post(
         signoz.self.host_configs["8080"].get(ROLES_BASE),
-        json={"name": "role-fga-should-fail"},
+        json={"name": "role-fga-should-fail", "transactionGroups": []},
         headers={"Authorization": f"Bearer {token}"},
         timeout=5,
     )
@@ -238,7 +238,7 @@ def test_role_grant_write_permissions(
     # Create role — now allowed.
     resp = requests.post(
         signoz.self.host_configs["8080"].get(ROLES_BASE),
-        json={"name": "role-fga-write-test"},
+        json={"name": "role-fga-write-test", "transactionGroups": []},
         headers={"Authorization": f"Bearer {custom_token}"},
         timeout=5,
     )