feat(data-export): add scalar queryRange serializer

exportScalarData takes the queryRange response object (formatForWeb webTables payload) + the builder query and serializes via createTableColumnsFromQuery — the exact preparer QueryTable renders from — so exports inherit the on-screen merge, naming and column order 1:1.

docs/api/openapi.yml

@@ -1495,7 +1495,6 @@ components:
       - cassandradb
       - redis
       - cloudsql_postgres
-      - memorystore_redis
       type: string
     CloudintegrationtypesServiceMetadata:
       properties:
@@ -4260,6 +4259,34 @@ components:
           type: number
         clusterName:
           type: string
+        counts:
+          properties:
+            daemonSets:
+              format: int64
+              type: integer
+            deployments:
+              format: int64
+              type: integer
+            jobs:
+              format: int64
+              type: integer
+            namespaces:
+              format: int64
+              type: integer
+            nodes:
+              format: int64
+              type: integer
+            statefulSets:
+              format: int64
+              type: integer
+          required:
+          - nodes
+          - namespaces
+          - deployments
+          - daemonSets
+          - jobs
+          - statefulSets
+          type: object
         meta:
           additionalProperties:
             type: string
@@ -4280,6 +4307,7 @@ components:
       - nodeCountsByReadiness
       - podCountsByPhase
       - podCountsByStatus
+      - counts
       - meta
       type: object
     InframonitoringtypesClusters:
@@ -4801,6 +4829,26 @@ components:
       type: object
     InframonitoringtypesNamespaceRecord:
       properties:
+        counts:
+          properties:
+            daemonSets:
+              format: int64
+              type: integer
+            deployments:
+              format: int64
+              type: integer
+            jobs:
+              format: int64
+              type: integer
+            statefulSets:
+              format: int64
+              type: integer
+          required:
+          - deployments
+          - daemonSets
+          - jobs
+          - statefulSets
+          type: object
         meta:
           additionalProperties:
             type: string
@@ -4824,6 +4872,7 @@ components:
       - namespaceMemory
       - podCountsByPhase
       - podCountsByStatus
+      - counts
       - meta
       type: object
     InframonitoringtypesNamespaces:

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

@@ -2814,7 +2814,6 @@ export enum CloudintegrationtypesServiceIDDTO {
 	cassandradb = 'cassandradb',
 	redis = 'redis',
 	cloudsql_postgres = 'cloudsql_postgres',
-	memorystore_redis = 'memorystore_redis',
 }
 export type CloudintegrationtypesCloudIntegrationServiceDTOAnyOf = {
 	/**
@@ -5670,6 +5669,39 @@ export interface InframonitoringtypesChecksDTO {
 	type: InframonitoringtypesCheckTypeDTO;
 }
 
+export type InframonitoringtypesClusterRecordDTOCounts = {
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	daemonSets: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	deployments: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	jobs: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	namespaces: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	nodes: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	statefulSets: number;
+};
+
 export type InframonitoringtypesClusterRecordDTOMetaAnyOf = {
 	[key: string]: string;
 };
@@ -5814,6 +5846,10 @@ export interface InframonitoringtypesClusterRecordDTO {
 	 * @type string
 	 */
 	clusterName: string;
+	/**
+	 * @type object
+	 */
+	counts: InframonitoringtypesClusterRecordDTOCounts;
 	/**
 	 * @type object,null
 	 */
@@ -6369,6 +6405,29 @@ export interface InframonitoringtypesJobsDTO {
 	warning?: Querybuildertypesv5QueryWarnDataDTO;
 }
 
+export type InframonitoringtypesNamespaceRecordDTOCounts = {
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	daemonSets: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	deployments: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	jobs: number;
+	/**
+	 * @type integer
+	 * @format int64
+	 */
+	statefulSets: number;
+};
+
 export type InframonitoringtypesNamespaceRecordDTOMetaAnyOf = {
 	[key: string]: string;
 };
@@ -6380,6 +6439,10 @@ export type InframonitoringtypesNamespaceRecordDTOMeta =
 	InframonitoringtypesNamespaceRecordDTOMetaAnyOf | null;
 
 export interface InframonitoringtypesNamespaceRecordDTO {
+	/**
+	 * @type object
+	 */
+	counts: InframonitoringtypesNamespaceRecordDTOCounts;
 	/**
 	 * @type object,null
 	 */

frontend/src/container/LogsExplorerViews/LogsExplorerViews.styles.scss

@@ -191,14 +191,6 @@
 				min-height: 0;
 				overflow-y: visible;
 
-				.time-series-view-container-header {
-					display: flex;
-					justify-content: flex-start;
-					align-items: center;
-					padding: 12px;
-					flex-shrink: 0;
-				}
-
 				.time-series-view {
 					flex-shrink: 0;
 					height: 65vh;

frontend/src/container/LogsExplorerViews/index.tsx

@@ -32,7 +32,6 @@ import {
 	getListQuery,
 	getQueryByPanelType,
 } from 'container/LogsExplorerViews/explorerUtils';
-import { BuilderUnitsFilter } from 'container/QueryBuilder/filters/BuilderUnitsFilter';
 import TimeSeriesView from 'container/TimeSeriesView/TimeSeriesView';
 import { useCopyLogLink } from 'hooks/logs/useCopyLogLink';
 import { useGetExplorerQueryRange } from 'hooks/queryBuilder/useGetExplorerQueryRange';
@@ -461,18 +460,17 @@ function LogsExplorerViewsContainer({
 					)}
 					{selectedPanelType === PANEL_TYPES.TIME_SERIES && !showLiveLogs && (
 						<div className="time-series-view-container">
-							<div className="time-series-view-container-header">
-								<BuilderUnitsFilter onChange={onUnitChange} yAxisUnit={yAxisUnit} />
-							</div>
 							<TimeSeriesView
 								isLoading={isLoading || isFetching}
 								data={data}
 								isError={isError}
 								error={error as APIError}
 								yAxisUnit={yAxisUnit}
+								onYAxisUnitChange={onUnitChange}
 								isFilterApplied={!isEmpty(listQuery?.filters?.items)}
 								dataSource={DataSource.LOGS}
 								setWarning={setWarning}
+								allowExport
 							/>
 						</div>
 					)}

frontend/src/container/MetricsExplorer/Explorer/TimeSeries.tsx

@@ -311,6 +311,7 @@ function TimeSeries({
 									dataSource={DataSource.METRICS}
 									error={queries[index].error as APIError}
 									setWarning={setWarning}
+									allowExport
 								/>
 							</div>
 						);

frontend/src/container/TimeSeriesView/TimeSeriesView.styles.scss

@@ -3,6 +3,14 @@
 	min-height: 350px;
 	padding: 0px 12px;
 
+	&__header {
+		display: flex;
+		justify-content: space-between;
+		align-items: center;
+		padding: 12px 0;
+		flex-shrink: 0;
+	}
+
 	.ant-card-body {
 		height: 50vh;
 		min-height: 350px;

frontend/src/container/TimeSeriesView/TimeSeriesView.tsx

@@ -16,6 +16,7 @@ import Uplot from 'components/Uplot';
 import { QueryParams } from 'constants/query';
 import { PANEL_TYPES } from 'constants/queryBuilder';
 import EmptyLogsSearch from 'container/EmptyLogsSearch/EmptyLogsSearch';
+import { BuilderUnitsFilter } from 'container/QueryBuilder/filters/BuilderUnitsFilter';
 import { getLocalStorageGraphVisibilityState } from 'container/GridCardLayout/GridCard/utils';
 import { LogsLoading } from 'container/LogsLoading/LogsLoading';
 import EmptyMetricsSearch from 'container/MetricsExplorer/Explorer/EmptyMetricsSearch';
@@ -41,11 +42,14 @@ import { SuccessResponse, Warning } from 'types/api';
 import { LegendPosition } from 'types/api/dashboard/getAll';
 import APIError from 'types/api/error';
 import { MetricRangePayloadProps } from 'types/api/metrics/getQueryRange';
+import { QueryRangeResponseV5 } from 'types/api/v5/queryRange';
 import { DataSource } from 'types/common/queryBuilder';
 import { GlobalReducer } from 'types/reducer/globalTime';
 import uPlot from 'uplot';
 import { getTimeRange } from 'utils/getTimeRange';
 
+import TimeseriesExportMenu from './TimeseriesExportMenu';
+
 import './TimeSeriesView.styles.scss';
 
 function TimeSeriesView({
@@ -59,6 +63,8 @@ function TimeSeriesView({
 	setWarning,
 	panelType = PANEL_TYPES.TIME_SERIES,
 	stackBarChart = false,
+	allowExport = false,
+	onYAxisUnitChange,
 }: TimeSeriesViewProps): JSX.Element {
 	const graphRef = useRef<HTMLDivElement>(null);
 
@@ -244,10 +250,33 @@ function TimeSeriesView({
 		[baseChartOptions, stackedBands],
 	);
 
+	const showExport = allowExport && !!data?.rawV5Response;
+	const showHeader = showExport || !!onYAxisUnitChange;
+
 	return (
 		<div className="time-series-view">
 			{isError && error && <ErrorInPlace error={error as APIError} />}
 
+			{showHeader && (
+				<div className="time-series-view__header">
+					<div>
+						{onYAxisUnitChange && (
+							<BuilderUnitsFilter onChange={onYAxisUnitChange} yAxisUnit={yAxisUnit} />
+						)}
+					</div>
+					{showExport && data?.rawV5Response && (
+						<TimeseriesExportMenu
+							dataSource={dataSource}
+							yAxisUnit={yAxisUnit}
+							queryResponse={data.rawV5Response}
+							query={currentQuery}
+							legendMap={data.legendMap}
+							fileName={`${dataSource}-timeseries`}
+						/>
+					)}
+				</div>
+			)}
+
 			<div
 				className="graph-container"
 				style={{ height: '100%', width: '100%' }}
@@ -295,7 +324,11 @@ function TimeSeriesView({
 }
 
 interface TimeSeriesViewProps {
-	data?: SuccessResponse<MetricRangePayloadProps> & { warning?: Warning };
+	data?: SuccessResponse<MetricRangePayloadProps> & {
+		warning?: Warning;
+		rawV5Response?: QueryRangeResponseV5;
+		legendMap?: Record<string, string>;
+	};
 	yAxisUnit?: string;
 	isLoading: boolean;
 	isError: boolean;
@@ -305,6 +338,11 @@ interface TimeSeriesViewProps {
 	setWarning?: Dispatch<SetStateAction<Warning | undefined>>;
 	panelType?: PANEL_TYPES;
 	stackBarChart?: boolean;
+	// Opt-in: render the client-side export menu (Logs explorer for now).
+	allowExport?: boolean;
+	// Opt-in: render the y-axis unit selector in the header (views without their
+	// own selector, e.g. Logs). Metrics keeps its separate YAxisUnitSelector.
+	onYAxisUnitChange?: (value: string) => void;
 }
 
 TimeSeriesView.defaultProps = {

frontend/src/container/TimeSeriesView/TimeseriesExportMenu.styles.scss

@@ -0,0 +1,33 @@
+.timeseries-export-popover {
+	width: 240px;
+	padding: 0 12px 12px 12px;
+
+	.title {
+		display: flex;
+		color: var(--l1-foreground);
+		font-family: Inter;
+		font-size: var(--periscope-font-size-small);
+		font-style: normal;
+		font-weight: 500;
+		line-height: 18px;
+		letter-spacing: 0.88px;
+		text-transform: uppercase;
+		margin-bottom: 8px;
+	}
+
+	.export-format {
+		padding: 12px 4px;
+		display: flex;
+		flex-direction: column;
+
+		// radio option labels — radix popover content inherits the root font
+		// size; pin to the app's 13px base the antd popover used to impose
+		label {
+			font-size: var(--periscope-font-size-base);
+		}
+	}
+
+	.export-button {
+		width: 100%;
+	}
+}

frontend/src/container/TimeSeriesView/TimeseriesExportMenu.tsx

@@ -0,0 +1,91 @@
+import { Download } from '@signozhq/icons';
+import { Button } from '@signozhq/ui/button';
+import { Popover, PopoverContent, PopoverTrigger } from '@signozhq/ui/popover';
+import { RadioGroup, RadioGroupItem } from '@signozhq/ui/radio-group';
+import { TooltipSimple } from '@signozhq/ui/tooltip';
+import { Typography } from '@signozhq/ui/typography';
+import { useClientExport } from 'hooks/useExportData/useClientExport';
+import { ExportFormat } from 'lib/exportData/types';
+import { useCallback, useState } from 'react';
+import { Query } from 'types/api/queryBuilder/queryBuilderData';
+import { QueryRangeResponseV5 } from 'types/api/v5/queryRange';
+import { DataSource } from 'types/common/queryBuilder';
+
+import './TimeseriesExportMenu.styles.scss';
+
+interface TimeseriesExportMenuProps {
+	dataSource: DataSource;
+	queryResponse: QueryRangeResponseV5;
+	query?: Query;
+	yAxisUnit?: string;
+	legendMap?: Record<string, string>;
+	fileName?: string;
+}
+
+// Download menu for in-memory timeseries data (client-side serialization).
+// The raw/list backend export keeps its own menu in DownloadOptionsMenu.
+export default function TimeseriesExportMenu({
+	dataSource,
+	queryResponse,
+	query,
+	yAxisUnit,
+	legendMap,
+	fileName,
+}: TimeseriesExportMenuProps): JSX.Element {
+	const [exportFormat, setExportFormat] = useState<string>(ExportFormat.Csv);
+	const [isPopoverOpen, setIsPopoverOpen] = useState<boolean>(false);
+
+	const { isExporting, handleExport: handleClientExport } = useClientExport({
+		response: queryResponse,
+		query,
+		yAxisUnit,
+		legendMap,
+		fileName,
+	});
+
+	const handleExport = useCallback((): void => {
+		setIsPopoverOpen(false);
+		handleClientExport({ format: exportFormat as ExportFormat });
+	}, [exportFormat, handleClientExport]);
+
+	return (
+		<Popover open={isPopoverOpen} onOpenChange={setIsPopoverOpen}>
+			<TooltipSimple title="Download">
+				<PopoverTrigger asChild>
+					<Button
+						variant="ghost"
+						color="secondary"
+						size="icon"
+						aria-label="Download"
+						data-testid={`timeseries-export-${dataSource}`}
+						disabled={isExporting}
+						loading={isExporting}
+					>
+						<Download size={14} />
+					</Button>
+				</PopoverTrigger>
+			</TooltipSimple>
+			<PopoverContent align="end" className="timeseries-export-popover">
+				<div className="export-format">
+					<Typography.Text className="title">FORMAT</Typography.Text>
+					<RadioGroup value={exportFormat} onChange={setExportFormat}>
+						<RadioGroupItem value={ExportFormat.Csv}>csv</RadioGroupItem>
+						<RadioGroupItem value={ExportFormat.Jsonl}>jsonl</RadioGroupItem>
+					</RadioGroup>
+				</div>
+
+				<Button
+					variant="solid"
+					color="primary"
+					className="export-button"
+					onClick={handleExport}
+					disabled={isExporting}
+					loading={isExporting}
+					prefix={<Download size={16} />}
+				>
+					Export
+				</Button>
+			</PopoverContent>
+		</Popover>
+	);
+}

frontend/src/container/TimeSeriesView/__tests__/TimeSeriesView.test.tsx

@@ -0,0 +1,138 @@
+import { render } from '@testing-library/react';
+import { MemoryRouter } from 'react-router-dom';
+// eslint-disable-next-line no-restricted-imports
+import { Provider } from 'react-redux';
+import configureStore from 'redux-mock-store';
+import store from 'store';
+import { DataSource } from 'types/common/queryBuilder';
+
+import TimeSeriesView from '../TimeSeriesView';
+
+jest.mock('components/Uplot', () => ({
+	__esModule: true,
+	default: (): JSX.Element => <div data-testid="uplot-chart" />,
+}));
+
+jest.mock('../TimeseriesExportMenu', () => ({
+	__esModule: true,
+	default: (): JSX.Element => <div data-testid="timeseries-export-menu" />,
+}));
+
+jest.mock('container/QueryBuilder/filters/BuilderUnitsFilter', () => ({
+	BuilderUnitsFilter: (): JSX.Element => (
+		<div data-testid="builder-units-filter" />
+	),
+}));
+
+jest.mock('hooks/queryBuilder/useQueryBuilder', () => ({
+	useQueryBuilder: (): unknown => ({ currentQuery: null }),
+}));
+
+jest.mock('lib/uPlotLib/getUplotChartOptions', () => ({
+	getUPlotChartOptions: (): unknown => ({}),
+}));
+
+jest.mock('lib/uPlotLib/utils/getUplotChartData', () => ({
+	getUPlotChartData: (): number[][] => [
+		[1, 2],
+		[3, 4],
+	],
+}));
+
+jest.mock(
+	'container/DashboardContainer/visualization/charts/utils/stackSeriesUtils',
+	() => ({ stackSeries: (): unknown => ({ data: [], bands: [] }) }),
+);
+
+jest.mock('container/GridCardLayout/GridCard/utils', () => ({
+	getLocalStorageGraphVisibilityState: (): unknown => ({
+		graphVisibilityStates: [],
+	}),
+}));
+
+jest.mock('providers/Timezone', () => ({
+	useTimezone: (): unknown => ({ timezone: { value: 'UTC' } }),
+}));
+
+jest.mock('hooks/useDimensions', () => ({
+	useResizeObserver: (): unknown => ({ width: 800, height: 400 }),
+}));
+
+jest.mock('api/common/logEvent', () => ({
+	__esModule: true,
+	default: jest.fn(),
+}));
+
+const mockStore = configureStore([])({ ...store.getState() });
+
+const rawV5Response = {
+	type: 'time_series',
+	data: { results: [] },
+	meta: {},
+};
+
+function makeData(withRawV5: boolean): any {
+	return {
+		statusCode: 200,
+		error: null,
+		message: '',
+		payload: { data: { result: [], resultType: '' } },
+		...(withRawV5 ? { rawV5Response, legendMap: {} } : {}),
+	};
+}
+
+function renderView(props: {
+	allowExport?: boolean;
+	withRawV5?: boolean;
+	onYAxisUnitChange?: (value: string) => void;
+}): ReturnType<typeof render> {
+	const { allowExport, withRawV5 = true, onYAxisUnitChange } = props;
+	return render(
+		<Provider store={mockStore}>
+			<MemoryRouter>
+				<TimeSeriesView
+					isLoading={false}
+					isError={false}
+					isFilterApplied
+					dataSource={DataSource.LOGS}
+					data={makeData(withRawV5)}
+					allowExport={allowExport}
+					onYAxisUnitChange={onYAxisUnitChange}
+				/>
+			</MemoryRouter>
+		</Provider>,
+	);
+}
+
+describe('TimeSeriesView header gating', () => {
+	it('renders the export menu when allowExport is set and raw V5 data is present', () => {
+		const { queryByTestId } = renderView({ allowExport: true });
+		expect(queryByTestId('timeseries-export-menu')).toBeInTheDocument();
+	});
+
+	it('renders no export menu without allowExport', () => {
+		const { queryByTestId } = renderView({});
+		expect(queryByTestId('timeseries-export-menu')).not.toBeInTheDocument();
+	});
+
+	it('renders no export menu when the raw V5 response is missing', () => {
+		const { queryByTestId } = renderView({ allowExport: true, withRawV5: false });
+		expect(queryByTestId('timeseries-export-menu')).not.toBeInTheDocument();
+	});
+
+	it('renders the unit selector only when onYAxisUnitChange is passed', () => {
+		const withUnit = renderView({ onYAxisUnitChange: jest.fn() });
+		expect(withUnit.queryByTestId('builder-units-filter')).toBeInTheDocument();
+		withUnit.unmount();
+
+		const withoutUnit = renderView({ allowExport: true });
+		expect(
+			withoutUnit.queryByTestId('builder-units-filter'),
+		).not.toBeInTheDocument();
+	});
+
+	it('renders no header row when neither export nor unit selector is enabled', () => {
+		const { container } = renderView({ withRawV5: false });
+		expect(container.querySelector('.time-series-view__header')).toBeNull();
+	});
+});

frontend/src/container/TimeSeriesView/__tests__/TimeseriesExportMenu.test.tsx

@@ -0,0 +1,84 @@
+import { fireEvent, render, screen } from 'tests/test-utils';
+import { QueryRangeResponseV5 } from 'types/api/v5/queryRange';
+import { DataSource } from 'types/common/queryBuilder';
+
+import TimeseriesExportMenu from '../TimeseriesExportMenu';
+
+const mockHandleExport = jest.fn();
+let mockIsExporting = false;
+
+jest.mock('hooks/useExportData/useClientExport', () => ({
+	useClientExport: (): unknown => ({
+		isExporting: mockIsExporting,
+		handleExport: mockHandleExport,
+	}),
+}));
+
+const response = {
+	type: 'time_series',
+	data: { results: [] },
+	meta: {},
+} as unknown as QueryRangeResponseV5;
+
+const TEST_ID = `timeseries-export-${DataSource.LOGS}`;
+
+function renderMenu(): void {
+	render(
+		<TimeseriesExportMenu
+			dataSource={DataSource.LOGS}
+			queryResponse={response}
+			fileName="logs-timeseries"
+		/>,
+	);
+}
+
+describe('TimeseriesExportMenu', () => {
+	beforeEach(() => {
+		mockHandleExport.mockReset();
+		mockIsExporting = false;
+	});
+
+	it('renders the download trigger button', () => {
+		renderMenu();
+		expect(screen.getByTestId(TEST_ID)).toBeInTheDocument();
+	});
+
+	it('shows only format options — no shape, row-count, or column controls', () => {
+		renderMenu();
+		fireEvent.click(screen.getByTestId(TEST_ID));
+
+		expect(screen.getByText('FORMAT')).toBeInTheDocument();
+		expect(screen.getByRole('radio', { name: 'csv' })).toBeInTheDocument();
+		expect(screen.getByRole('radio', { name: 'jsonl' })).toBeInTheDocument();
+
+		expect(screen.queryByText('Number of Rows')).not.toBeInTheDocument();
+		expect(screen.queryByText('Columns')).not.toBeInTheDocument();
+		expect(screen.queryByRole('radio', { name: 'long' })).not.toBeInTheDocument();
+		expect(screen.queryByRole('radio', { name: 'wide' })).not.toBeInTheDocument();
+	});
+
+	it('exports as csv by default', () => {
+		renderMenu();
+		fireEvent.click(screen.getByTestId(TEST_ID));
+		fireEvent.click(screen.getByText('Export'));
+
+		expect(mockHandleExport).toHaveBeenCalledTimes(1);
+		expect(mockHandleExport).toHaveBeenCalledWith({ format: 'csv' });
+	});
+
+	it('exports as jsonl when selected', () => {
+		renderMenu();
+		fireEvent.click(screen.getByTestId(TEST_ID));
+		fireEvent.click(screen.getByRole('radio', { name: 'jsonl' }));
+		fireEvent.click(screen.getByText('Export'));
+
+		expect(mockHandleExport).toHaveBeenCalledWith({ format: 'jsonl' });
+	});
+
+	it('disables the trigger while an export is in progress', () => {
+		mockIsExporting = true;
+		renderMenu();
+
+		expect(screen.getByTestId(TEST_ID)).toBeDisabled();
+	});
+});

frontend/src/container/TimeSeriesView/utils.ts

@@ -1,10 +1,41 @@
 import { SuccessResponse } from 'types/api/index';
 import { MetricRangePayloadProps } from 'types/api/metrics/getQueryRange';
+import { QueryRangeResponseV5, TimeSeriesData } from 'types/api/v5/queryRange';
 import { QueryData } from 'types/api/widgets/getQuery';
 
+type ConvertibleData = SuccessResponse<MetricRangePayloadProps> & {
+	rawV5Response?: QueryRangeResponseV5;
+};
+
+// Applies the same ns→ms conversion to the raw V5 tree, so client-side export
+// serializes the values the chart displays (not the original nanoseconds).
+function convertRawV5ValuesToMs(
+	response: QueryRangeResponseV5,
+): QueryRangeResponseV5 {
+	if (response.type !== 'time_series') {
+		return response;
+	}
+
+	const results = (response.data.results as TimeSeriesData[]).map((result) => ({
+		...result,
+		aggregations: (result.aggregations ?? []).map((bucket) => ({
+			...bucket,
+			series: (bucket.series ?? []).map((series) => ({
+				...series,
+				values: (series.values ?? []).map((value) => ({
+					...value,
+					value: value.value / 1000000,
+				})),
+			})),
+		})),
+	}));
+
+	return { ...response, data: { ...response.data, results } };
+}
+
 export const convertDataValueToMs = (
-	data?: SuccessResponse<MetricRangePayloadProps>,
-): SuccessResponse<MetricRangePayloadProps> | undefined => {
+	data?: ConvertibleData,
+): ConvertibleData | undefined => {
 	const convertedData = data;
 
 	const convertedResult: QueryData[] = data?.payload?.data?.result
@@ -22,5 +53,11 @@ export const convertDataValueToMs = (
 		convertedData.payload.data.result = convertedResult;
 	}
 
+	if (convertedData?.rawV5Response) {
+		convertedData.rawV5Response = convertRawV5ValuesToMs(
+			convertedData.rawV5Response,
+		);
+	}
+
 	return convertedData;
 };

frontend/src/lib/dashboard/getQueryResults.ts

@@ -22,7 +22,11 @@ import { SuccessResponseV2, Warning } from 'types/api';
 import { IDashboardVariable } from 'types/api/dashboard/getAll';
 import { MetricQueryRangeSuccessResponse } from 'types/api/metrics/getQueryRange';
 import { IBuilderQuery, Query } from 'types/api/queryBuilder/queryBuilderData';
-import { ExecStats, MetricRangePayloadV5 } from 'types/api/v5/queryRange';
+import {
+	ExecStats,
+	MetricRangePayloadV5,
+	QueryRangeResponseV5,
+} from 'types/api/v5/queryRange';
 import { QueryData } from 'types/api/widgets/getQuery';
 import { EQueryType } from 'types/common/dashboard';
 import { DataSource } from 'types/common/queryBuilder';
@@ -192,6 +196,8 @@ export async function GetMetricQueryRange(
 		| SuccessResponseV2<MetricRangePayloadV5>;
 	let warning: Warning | undefined;
 	let meta: ExecStats | undefined;
+	// Raw V5 response, kept before it's converted to legacy — powers client-side export.
+	let rawV5Response: QueryRangeResponseV5 | undefined;
 
 	const panelType = props.originalGraphType || props.graphType;
 
@@ -268,6 +274,8 @@ export async function GetMetricQueryRange(
 				endTime: props.end * 1000,
 			});
 
+			rawV5Response = publicResponse.data.data;
+
 			// Convert V5 response to legacy format for components
 			response = convertV5ResponseToLegacy(
 				{
@@ -288,6 +296,8 @@ export async function GetMetricQueryRange(
 				headers,
 			);
 
+			rawV5Response = v5Response.data.data;
+
 			// Convert V5 response to legacy format for components
 			response = convertV5ResponseToLegacy(
 				{
@@ -366,6 +376,8 @@ export async function GetMetricQueryRange(
 		...response,
 		warning,
 		meta,
+		rawV5Response,
+		legendMap,
 	};
 }
 

frontend/src/lib/exportData/__tests__/exportScalarData.test.ts

@@ -0,0 +1,94 @@
+import { SuccessResponse } from 'types/api';
+import { MetricRangePayloadProps } from 'types/api/metrics/getQueryRange';
+import { Query } from 'types/api/queryBuilder/queryBuilderData';
+
+import { exportScalarData } from '../exportScalarData';
+
+const query = {
+	queryType: 'builder',
+	builder: {
+		queryData: [
+			{
+				queryName: 'A',
+				dataSource: 'logs',
+				aggregations: [{ expression: 'count()' }],
+				groupBy: [
+					{ key: 'service.name', dataType: 'string', type: 'tag', id: 'svc' },
+				],
+				legend: '',
+			},
+		],
+		queryFormulas: [],
+	},
+} as unknown as Query;
+
+function makeResponse(
+	tables: {
+		queryName: string;
+		columns: { name: string; id?: string; isValueColumn: boolean }[];
+		rows: Record<string, string | number>[];
+	}[],
+): SuccessResponse<MetricRangePayloadProps> {
+	return {
+		statusCode: 200,
+		error: null,
+		message: '',
+		payload: {
+			data: {
+				resultType: 'scalar',
+				result: tables.map((table) => ({
+					queryName: table.queryName,
+					legend: '',
+					series: null,
+					list: null,
+					table: {
+						columns: table.columns.map((col) => ({
+							...col,
+							queryName: table.queryName,
+						})),
+						rows: table.rows.map((row) => ({ data: row })),
+					},
+				})),
+			},
+		},
+	} as unknown as SuccessResponse<MetricRangePayloadProps>;
+}
+
+describe('exportScalarData', () => {
+	it('serializes the table exactly as QueryTable prepares it', () => {
+		const data = makeResponse([
+			{
+				queryName: 'A',
+				columns: [
+					{ name: 'service.name', id: 'service.name', isValueColumn: false },
+					{ name: 'count()', id: 'A', isValueColumn: true },
+				],
+				rows: [
+					{ 'service.name': 'frontend', A: 120 },
+					{ 'service.name': 'cart', A: 80 },
+				],
+			},
+		]);
+
+		const table = exportScalarData({ data, query });
+
+		// group + aggregation columns, raw values, on-screen order — inherited
+		// 1:1 from createTableColumnsFromQuery (the renderer's own preparer)
+		expect(table).toStrictEqual({
+			headers: ['service.name', 'count()'],
+			rows: [
+				['frontend', 120],
+				['cart', 80],
+			],
+		});
+	});
+
+	it('returns an empty table for an empty response', () => {
+		const table = exportScalarData({
+			data: makeResponse([]),
+			query,
+		});
+
+		expect(table.rows).toStrictEqual([]);
+	});
+});

frontend/src/lib/exportData/__tests__/exportTableData.test.ts

@@ -0,0 +1,58 @@
+import { exportTableData } from '../exportTableData';
+
+const columns = [
+	{ name: 'service.name', key: 'service.name' },
+	{ name: 'count()', key: 'A', isValueColumn: true },
+	{ name: 'avg(duration)', key: 'B', isValueColumn: true },
+];
+
+describe('exportTableData', () => {
+	it('serializes raw values in display column order', () => {
+		const table = exportTableData({
+			columns,
+			dataSource: [
+				{ 'service.name': 'frontend', A: 120, B: 45.5 },
+				{ 'service.name': 'cart', A: 80, B: 12 },
+			],
+		});
+
+		expect(table).toStrictEqual({
+			headers: ['service.name', 'count()', 'avg(duration)'],
+			rows: [
+				['frontend', 120, 45.5],
+				['cart', 80, 12],
+			],
+		});
+	});
+
+	it('appends column units to value columns only, skipping display-only ids', () => {
+		const table = exportTableData({
+			columns,
+			dataSource: [{ 'service.name': 'frontend', A: 120, B: 45.5 }],
+			columnUnits: { A: 'short', B: 'ms', 'service.name': 'ms' },
+		});
+
+		// group column never gets a unit; 'short' is display-only and skipped
+		expect(table.headers).toStrictEqual([
+			'service.name',
+			'count()',
+			'avg(duration) (ms)',
+		]);
+	});
+
+	it('marks missing cells as blank gaps', () => {
+		const table = exportTableData({
+			columns,
+			dataSource: [{ 'service.name': 'frontend', A: 120 }],
+		});
+
+		expect(table.rows).toStrictEqual([['frontend', 120, '']]);
+	});
+
+	it('returns a headers-only table for empty data', () => {
+		expect(exportTableData({ columns, dataSource: [] })).toStrictEqual({
+			headers: ['service.name', 'count()', 'avg(duration)'],
+			rows: [],
+		});
+	});
+});

frontend/src/lib/exportData/__tests__/exportTimeseriesData.test.ts

@@ -81,6 +81,18 @@ describe('exportTimeseriesData', () => {
 		]);
 	});
 
+	it('omits display-only format ids (short/none) from headers', () => {
+		const data = [
+			makeQuery('A', [{ series: [makeSeries({ service: 'a' }, [[1000, 1]])] }]),
+		];
+
+		const short = exportTimeseriesData({ data, yAxisUnit: 'short' });
+		expect(short.headers[short.headers.length - 1]).toBe('value');
+
+		const none = exportTimeseriesData({ data, yAxisUnit: 'none' });
+		expect(none.headers[none.headers.length - 1]).toBe('value');
+	});
+
 	it('multi-query: query is its own column; label keys are unioned', () => {
 		const data = [
 			makeQuery('A', [{ series: [makeSeries({ service: 'x' }, [[1000, 1]])] }]),

frontend/src/lib/exportData/exportScalarData.ts

@@ -0,0 +1,48 @@
+import { createTableColumnsFromQuery } from 'lib/query/createTableColumnsFromQuery';
+import { SuccessResponse } from 'types/api';
+import { MetricRangePayloadProps } from 'types/api/metrics/getQueryRange';
+import { Query } from 'types/api/queryBuilder/queryBuilderData';
+import { QueryDataV3 } from 'types/api/widgets/getQuery';
+
+import { exportTableData } from './exportTableData';
+import { SerializedTable } from './types';
+
+interface ExportScalarDataArgs {
+	// The queryRange response object the table mount already holds (the
+	// formatForWeb payload carrying webTables).
+	data?: SuccessResponse<MetricRangePayloadProps>;
+	query: Query;
+}
+
+/**
+ * Serializes a scalar/table queryRange response into a table — via
+ * createTableColumnsFromQuery, the exact preparer QueryTable renders from, so
+ * the export inherits the on-screen merge, naming and column order 1:1.
+ */
+export function exportScalarData({
+	data,
+	query,
+}: ExportScalarDataArgs): SerializedTable {
+	const queryTableData = (data?.payload?.data?.newResult?.data?.result ||
+		data?.payload?.data?.result ||
+		[]) as QueryDataV3[];
+
+	const { columns, dataSource } = createTableColumnsFromQuery({
+		query,
+		queryTableData,
+	});
+
+	return exportTableData({
+		// antd widens title/dataIndex; createTableColumnsFromQuery always sets strings
+		columns: columns.map((column) => {
+			const rawIndex = 'dataIndex' in column ? column.dataIndex : undefined;
+			const key =
+				typeof rawIndex === 'string' || typeof rawIndex === 'number'
+					? String(rawIndex)
+					: '';
+			const name = typeof column.title === 'string' ? column.title : key;
+			return { name, key: key || name };
+		}),
+		dataSource: dataSource as unknown as Record<string, unknown>[],
+	});
+}

frontend/src/lib/exportData/exportTableData.ts

@@ -0,0 +1,46 @@
+import { SerializedTable } from './types';
+import { withUnit } from './withUnit';
+
+/** Generic table-model column — any prepared table (QueryTable, dashboard
+ * tables, plain antd tables) adapts to this in a line or two. */
+export interface ExportTableColumn {
+	/** Display name, used as the export header (column order = array order). */
+	name: string;
+	/** Key into each dataSource record. */
+	key: string;
+	isValueColumn?: boolean;
+}
+
+interface ExportTableDataArgs {
+	columns: ExportTableColumn[];
+	dataSource: Record<string, unknown>[];
+	/** Per-column display unit, keyed by column key (dashboards; absent in explorer). */
+	columnUnits?: Record<string, string>;
+}
+
+/**
+ * Serializes a prepared table model into a format-agnostic table — raw values
+ * in display column order (lossless; no cell formatting applied).
+ */
+export function exportTableData({
+	columns,
+	dataSource,
+	columnUnits,
+}: ExportTableDataArgs): SerializedTable {
+	const headers = columns.map((column) =>
+		column.isValueColumn
+			? withUnit(column.name, columnUnits?.[column.key])
+			: column.name,
+	);
+
+	const rows = dataSource.map((record) =>
+		columns.map((column) => {
+			const value = record[column.key];
+			return value === undefined || value === null
+				? ''
+				: (value as string | number);
+		}),
+	);
+
+	return { headers, rows };
+}

frontend/src/lib/exportData/exportTimeseriesData.ts

@@ -5,6 +5,7 @@ import { TimeSeries, TimeSeriesData } from 'types/api/v5/queryRange';
 import { QueryData } from 'types/api/widgets/getQuery';
 
 import { SerializedTable } from './types';
+import { withUnit } from './withUnit';
 
 interface ExportTimeseriesDataArgs {
 	data: TimeSeriesData[];
@@ -98,11 +99,6 @@ function flatten(
 	return flat;
 }
 
-// Appends the y-axis unit to the value header: `value` → `value (ms)`.
-function withUnit(header: string, yAxisUnit?: string): string {
-	return yAxisUnit ? `${header} (${yAxisUnit})` : header;
-}
-
 function toIso(timestamp: number): string {
 	return new Date(timestamp).toISOString();
 }

frontend/src/lib/exportData/withUnit.ts

@@ -0,0 +1,11 @@
+// Display-format ids, not physical units — meaningful on a chart axis
+// (compact-number formatting) but misleading in an export header.
+const DISPLAY_ONLY_UNITS = new Set(['short', 'none']);
+
+/** Appends a unit to a header: `value` → `value (ms)`. Skips display-only ids. */
+export function withUnit(header: string, unit?: string): string {
+	if (!unit || DISPLAY_ONLY_UNITS.has(unit)) {
+		return header;
+	}
+	return `${header} (${unit})`;
+}

frontend/src/pages/TracesExplorer/TimeSeriesView/index.tsx

@@ -10,7 +10,6 @@ import { useSelector } from 'react-redux';
 import { ENTITY_VERSION_V5 } from 'constants/app';
 import { initialQueriesMap, PANEL_TYPES } from 'constants/queryBuilder';
 import { REACT_QUERY_KEY } from 'constants/reactQueryKeys';
-import { BuilderUnitsFilter } from 'container/QueryBuilder/filters';
 import TimeSeriesView from 'container/TimeSeriesView/TimeSeriesView';
 import { convertDataValueToMs } from 'container/TimeSeriesView/utils';
 import { useGetQueryRange } from 'hooks/queryBuilder/useGetQueryRange';
@@ -116,9 +115,6 @@ function TimeSeriesViewContainer({
 
 	return (
 		<div className="trace-explorer-time-series-view-container">
-			<div className="trace-explorer-time-series-view-container-header">
-				<BuilderUnitsFilter onChange={onUnitChange} yAxisUnit={yAxisUnit} />
-			</div>
 			<TimeSeriesView
 				isFilterApplied={isFilterApplied}
 				isError={isError}
@@ -126,8 +122,10 @@ function TimeSeriesViewContainer({
 				isLoading={isLoading || isFetching}
 				data={responseData}
 				yAxisUnit={yAxisUnit}
+				onYAxisUnitChange={onUnitChange}
 				dataSource={dataSource}
 				setWarning={setWarning}
+				allowExport
 			/>
 		</div>
 	);

frontend/src/types/api/metrics/getQueryRange.ts

@@ -8,7 +8,11 @@ import {
 	IClickHouseQuery,
 	IPromQLQuery,
 } from '../queryBuilder/queryBuilderData';
-import { ExecStats, QueryRangeRequestV5 } from '../v5/queryRange';
+import {
+	ExecStats,
+	QueryRangeRequestV5,
+	QueryRangeResponseV5,
+} from '../v5/queryRange';
 import { QueryData, QueryDataV3 } from '../widgets/getQuery';
 
 export type QueryRangePayload = {
@@ -48,6 +52,9 @@ export interface MetricQueryRangeSuccessResponse extends SuccessResponse<
 > {
 	warning?: Warning;
 	meta?: ExecStats;
+	// Raw V5 response (pre-legacy-conversion) + per-query legend map, for client-side export.
+	rawV5Response?: QueryRangeResponseV5;
+	legendMap?: Record<string, string>;
 }
 
 export interface MetricRangePayloadV3 {

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/gcp/memorystore_redis/icon.svg

@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="24px" height="24px" viewBox="0 0 24 24"><defs><style>.cls-1,.cls-4{fill:#669df6;}.cls-2{fill:#4285f4;}.cls-2,.cls-3,.cls-4{fill-rule:evenodd;}.cls-3{fill:#aecbfa;}</style></defs><title>Icon_24px_MemoryStore_Color</title><g data-name="Product Icons"><g ><rect class="cls-1" x="2" y="3.94" width="3.33" height="2.58"/><rect class="cls-1" x="2" y="8.45" width="3.33" height="2.58"/><rect class="cls-1" x="2" y="12.97" width="3.33" height="2.58"/><rect class="cls-1" x="2" y="17.48" width="3.33" height="2.58"/><rect class="cls-1" x="18.67" y="3.94" width="3.33" height="2.58"/><rect class="cls-1" x="18.67" y="8.45" width="3.33" height="2.58"/><rect class="cls-1" x="18.67" y="12.97" width="3.33" height="2.58"/><rect class="cls-1" x="18.67" y="17.48" width="3.33" height="2.58"/><polygon class="cls-2" points="21.33 6.52 18.67 6.52 18.67 3.94 21.33 6.52"/><polygon class="cls-2" points="21.33 11.03 18.67 11.03 18.67 8.45 21.33 11.03"/><polygon class="cls-2" points="21.33 15.55 18.67 15.55 18.67 12.97 21.33 15.55"/><polygon class="cls-2" points="21.33 20.07 18.67 20.07 18.67 17.48 21.33 20.07"/><path class="cls-3" d="M5.33,22H18.67V2H5.33Zm6-9H8l4.67-7.74V11H16l-4.67,7.74Z"/><polygon class="cls-4" points="11.33 22 11.33 18.77 16 11.03 12.67 11.03 12.67 2 18.67 2 18.67 22 11.33 22"/></g></g></svg>

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/gcp/memorystore_redis/integration.json

@@ -1,94 +0,0 @@
-{
-  "id": "memorystore_redis",
-  "title": "GCP Memorystore Redis",
-  "icon": "file://icon.svg",
-  "overview": "file://overview.md",
-  "supportedSignals": {
-    "metrics": true,
-    "logs": true
-  },
-  "dataCollected": {
-    "metrics": [
-      {
-        "name": "redis.googleapis.com/server/uptime",
-        "unit": "Seconds",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/stats/memory/usage_ratio",
-        "unit": "None",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/stats/memory/system_memory_usage_ratio",
-        "unit": "None",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/stats/cpu_utilization_main_thread",
-        "unit": "Seconds",
-        "type": "Sum",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/clients/connected",
-        "unit": "Count",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/stats/cache_hit_ratio",
-        "unit": "None",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/keyspace/keys",
-        "unit": "Count",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/commands/usec_per_call",
-        "unit": "Microseconds",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/commands/calls",
-        "unit": "Count",
-        "type": "Sum",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/clients/blocked",
-        "unit": "Count",
-        "type": "Gauge",
-        "description": ""
-      },
-      {
-        "name": "redis.googleapis.com/stats/reject_connections_count",
-        "unit": "Count",
-        "type": "Sum",
-        "description": ""
-      }
-    ],
-    "logs": []
-  },
-  "telemetryCollectionStrategy": {
-    "gcp": {}
-  },
-  "assets": {
-    "dashboards": [
-      {
-        "id": "overview",
-        "title": "GCP Memorystore Redis Overview",
-        "description": "Overview of GCP Memorystore Redis metrics",
-        "definition": "file://assets/dashboards/overview.json"
-      }
-    ]
-  }
-}

pkg/modules/cloudintegration/implcloudintegration/fs/definitions/gcp/memorystore_redis/overview.md

@@ -1,3 +0,0 @@
-### Monitor GCP Memorystore Redis with SigNoz
-
-Collect key GCP Memorystore Redis metrics and view them with an out of the box dashboard.

pkg/modules/inframonitoring/implinframonitoring/clusters.go

@@ -21,6 +21,7 @@ func buildClusterRecords(
 	nodeConditionCountsMap map[string]nodeConditionCounts,
 	podPhaseCountsMap map[string]podPhaseCounts,
 	podStatusCounts map[string]podStatusCounts,
+	resourceCounts map[string]map[string]int64,
 ) []inframonitoringtypes.ClusterRecord {
 	metricsMap := parseFullQueryResponse(resp, groupBy)
 
@@ -74,6 +75,15 @@ func buildClusterRecords(
 			record.PodCountsByStatus = podStatusCountsToResponse(podStatusCountsForGroup)
 		}
 
+		if counts, ok := resourceCounts[compositeKey]; ok {
+			record.Counts.Nodes = counts[inframonitoringtypes.NodeNameAttrKey]
+			record.Counts.Namespaces = counts[inframonitoringtypes.NamespaceNameAttrKey]
+			record.Counts.Deployments = counts[inframonitoringtypes.DeploymentNameAttrKey]
+			record.Counts.DaemonSets = counts[inframonitoringtypes.DaemonSetNameAttrKey]
+			record.Counts.Jobs = counts[inframonitoringtypes.JobNameAttrKey]
+			record.Counts.StatefulSets = counts[inframonitoringtypes.StatefulSetNameAttrKey]
+		}
+
 		if attrs, ok := metadataMap[compositeKey]; ok {
 			for k, v := range attrs {
 				record.Meta[k] = v

pkg/modules/inframonitoring/implinframonitoring/clusters_constants.go

@@ -1,6 +1,8 @@
 package implinframonitoring
 
 import (
+	"slices"
+
 	"github.com/SigNoz/signoz/pkg/types/inframonitoringtypes"
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
 	qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
@@ -35,6 +37,26 @@ var clusterAttrKeysForMetadata = []string{
 	"k8s.cluster.name",
 }
 
+// clusterCountAttrKeys are the resource attributes whose distinct values are
+// counted per cluster. Node name is read from the node metric universe, while
+// namespace + workload names come from the pod metric universe — both unioned
+// into clusterCountMetricNamesList.
+var clusterCountAttrKeys = []string{
+	inframonitoringtypes.NodeNameAttrKey,
+	inframonitoringtypes.NamespaceNameAttrKey,
+	inframonitoringtypes.DeploymentNameAttrKey,
+	inframonitoringtypes.DaemonSetNameAttrKey,
+	inframonitoringtypes.JobNameAttrKey,
+	inframonitoringtypes.StatefulSetNameAttrKey,
+}
+
+// clusterMetricNamesListForCounts is the metric universe for per-cluster distinct
+// counts. It unions the pod universe (carries namespace + workload owner labels)
+// with the cluster/node universe (carries k8s.node.name), so a single query can
+// count nodes, namespaces, and workloads per cluster. Overlapping pod
+// phase/status metrics are left in — harmless in a metric_name IN (...) list.
+var clusterMetricNamesListForCounts = slices.Concat(podsTableMetricNamesList, clustersTableMetricNamesList)
+
 var orderByToClustersQueryNames = map[string][]string{
 	inframonitoringtypes.ClustersOrderByCPU:               {"A"},
 	inframonitoringtypes.ClustersOrderByCPUAllocatable:    {"B"},

pkg/modules/inframonitoring/implinframonitoring/helpers.go

@@ -11,6 +11,7 @@ import (
 	"github.com/SigNoz/signoz/pkg/querybuilder"
 	"github.com/SigNoz/signoz/pkg/telemetrymetrics"
 	"github.com/SigNoz/signoz/pkg/types/featuretypes"
+	"github.com/SigNoz/signoz/pkg/types/inframonitoringtypes"
 	"github.com/SigNoz/signoz/pkg/types/metrictypes"
 	qbtypes "github.com/SigNoz/signoz/pkg/types/querybuildertypes/querybuildertypesv5"
 	"github.com/SigNoz/signoz/pkg/types/telemetrytypes"
@@ -762,3 +763,197 @@ func (m *module) getMetadata(
 
 	return result, nil
 }
+
+// countAttrIdentityTuples maps a counted attr to the full label tuple that
+// uniquely identifies its entity, so uniqExact counts real entities rather than
+// bare names (namespace-scoped workloads with the same name across namespaces,
+// or cluster-scoped nodes/namespaces across clusters, would otherwise collapse).
+// Attrs absent from this map are counted on their bare name.
+var countAttrIdentityTuples = map[string][]string{
+	inframonitoringtypes.NamespaceNameAttrKey:   {inframonitoringtypes.ClusterNameAttrKey, inframonitoringtypes.NamespaceNameAttrKey},
+	inframonitoringtypes.NodeNameAttrKey:        {inframonitoringtypes.ClusterNameAttrKey, inframonitoringtypes.NodeNameAttrKey},
+	inframonitoringtypes.DeploymentNameAttrKey:  {inframonitoringtypes.ClusterNameAttrKey, inframonitoringtypes.NamespaceNameAttrKey, inframonitoringtypes.DeploymentNameAttrKey},
+	inframonitoringtypes.DaemonSetNameAttrKey:   {inframonitoringtypes.ClusterNameAttrKey, inframonitoringtypes.NamespaceNameAttrKey, inframonitoringtypes.DaemonSetNameAttrKey},
+	inframonitoringtypes.JobNameAttrKey:         {inframonitoringtypes.ClusterNameAttrKey, inframonitoringtypes.NamespaceNameAttrKey, inframonitoringtypes.JobNameAttrKey},
+	inframonitoringtypes.StatefulSetNameAttrKey: {inframonitoringtypes.ClusterNameAttrKey, inframonitoringtypes.NamespaceNameAttrKey, inframonitoringtypes.StatefulSetNameAttrKey},
+}
+
+// getPerGroupDistinctCounts returns, per groupBy combination, the exact distinct
+// count of each attr in attrNames within the time range and metric universe.
+// It mirrors getMetadata: fingerprints come from the samples table, labels are
+// read from the timeseries table (raw only, or raw+reduced union when reduction
+// is enabled), and the user filter is merged with the page-groups IN clauses.
+// The returned map keys group column values by "\x00", mapping to attr -> count.
+func (m *module) getPerGroupDistinctCounts(
+	ctx context.Context,
+	orgID valuer.UUID,
+	start, end int64,
+	filter *qbtypes.Filter,
+	groupBy []qbtypes.GroupByKey,
+	pageGroups []map[string]string,
+	attrNames []string,
+	metricNames []string,
+) (map[string]map[string]int64, error) {
+	if len(pageGroups) == 0 || len(groupBy) == 0 {
+		return map[string]map[string]int64{}, nil
+	}
+	if len(attrNames) == 0 {
+		return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "attrNames must not be empty")
+	}
+	if len(metricNames) == 0 {
+		return nil, errors.NewInvalidInputf(errors.CodeInvalidInput, "metricNames must not be empty")
+	}
+
+	// Merge user filter with page-groups IN clauses.
+	userFilterExpr := ""
+	if filter != nil {
+		userFilterExpr = filter.Expression
+	}
+	pageGroupsFilterExpr := buildPageGroupsFilterExpr(pageGroups)
+	mergedFilterExpr := mergeFilterExpressions(userFilterExpr, pageGroupsFilterExpr)
+
+	reductionEnabled := m.fl.BooleanOrEmpty(ctx, flagger.FeatureEnableMetricsReduction, featuretypes.NewFlaggerEvaluationContext(orgID))
+
+	// Step-floor the window and pick the right tables — same bounds the QB v5
+	// metric querier uses (see alignedMetricWindow / getMetadata).
+	samplesStartMs, flooredEndMs, tsAdjustedStartMs, distributedTimeSeriesTbl, _, _, localSamplesTbl := alignedMetricWindow(start, end)
+
+	fpSB := m.buildSamplesTblFingerprintSubQuery(metricNames, localSamplesTbl, samplesStartMs, flooredEndMs)
+
+	groupByCols := make([]string, len(groupBy))
+	for i, key := range groupBy {
+		groupByCols[i] = key.Name
+	}
+
+	sb := sqlbuilder.NewSelectBuilder()
+
+	// SELECT: one JSONExtractString per groupBy col + one uniqExactIf per attr.
+	selectCols := make([]string, 0, len(groupByCols)+len(attrNames))
+	for _, col := range groupByCols {
+		selectCols = append(selectCols,
+			fmt.Sprintf("JSONExtractString(labels, %s) AS %s", sb.Var(col), quoteIdentifier(col)),
+		)
+	}
+	for _, attr := range attrNames {
+		// Guard on != '' so a series missing the attr isn't counted as one empty value.
+		extract := fmt.Sprintf("JSONExtractString(labels, %s)", sb.Var(attr))
+
+		// Count on the entity's full identity tuple where one is defined, so
+		// same-named entities in different scopes (e.g. workloads sharing a name
+		// across namespaces) aren't collapsed. Falls back to the bare name.
+		valueExpr := extract
+		if tuple, ok := countAttrIdentityTuples[attr]; ok {
+			parts := make([]string, len(tuple))
+			for i, col := range tuple {
+				parts[i] = fmt.Sprintf("JSONExtractString(labels, %s)", sb.Var(col))
+			}
+			valueExpr = fmt.Sprintf("(%s)", strings.Join(parts, ", "))
+		}
+
+		selectCols = append(selectCols,
+			fmt.Sprintf("uniqExactIf(%s, %s != '') AS %s", valueExpr, extract, quoteIdentifier(attr)),
+		)
+	}
+	sb.Select(selectCols...)
+
+	if reductionEnabled {
+		var filterClause *sqlbuilder.WhereClause
+		if mergedFilterExpr != "" {
+			var err error
+			filterClause, err = m.buildFilterClause(ctx, &qbtypes.Filter{Expression: mergedFilterExpr}, start, end)
+			if err != nil {
+				return nil, err
+			}
+		}
+
+		reducedFpSB := m.buildReducedSamplesTblFingerprintSubQuery(metricNames, samplesStartMs, flooredEndMs)
+
+		rawSrc := sqlbuilder.NewSelectBuilder()
+		rawSrc.Select("labels")
+		rawSrc.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedTimeSeriesTbl))
+		rawSrc.Where(
+			rawSrc.In("metric_name", sqlbuilder.List(metricNames)),
+			rawSrc.GE("unix_milli", tsAdjustedStartMs),
+			rawSrc.LE("unix_milli", flooredEndMs),
+			fmt.Sprintf("fingerprint IN (%s)", rawSrc.Var(fpSB)),
+		)
+		if filterClause != nil {
+			rawSrc.AddWhereClause(sqlbuilder.CopyWhereClause(filterClause))
+		}
+
+		reducedSrc := sqlbuilder.NewSelectBuilder()
+		reducedSrc.Select("labels")
+		reducedSrc.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, telemetrymetrics.TimeseriesV4ReducedTableName))
+		reducedSrc.Where(
+			reducedSrc.In("metric_name", sqlbuilder.List(metricNames)),
+			reducedSrc.GE("unix_milli", tsAdjustedStartMs),
+			reducedSrc.LE("unix_milli", flooredEndMs),
+			fmt.Sprintf("fingerprint IN (%s)", reducedSrc.Var(reducedFpSB)),
+		)
+		if filterClause != nil {
+			reducedSrc.AddWhereClause(sqlbuilder.CopyWhereClause(filterClause))
+		}
+
+		sb.From(sb.BuilderAs(sqlbuilder.UnionAll(rawSrc, reducedSrc), "series"))
+	} else {
+		sb.From(fmt.Sprintf("%s.%s", telemetrymetrics.DBName, distributedTimeSeriesTbl))
+		sb.Where(
+			sb.In("metric_name", sqlbuilder.List(metricNames)),
+			sb.GE("unix_milli", tsAdjustedStartMs),
+			sb.LE("unix_milli", flooredEndMs),
+			fmt.Sprintf("fingerprint IN (%s)", sb.Var(fpSB)),
+		)
+		if mergedFilterExpr != "" {
+			filterClause, err := m.buildFilterClause(ctx, &qbtypes.Filter{Expression: mergedFilterExpr}, start, end)
+			if err != nil {
+				return nil, err
+			}
+			if filterClause != nil {
+				sb.AddWhereClause(filterClause)
+			}
+		}
+	}
+
+	groupByAliases := make([]string, 0, len(groupByCols))
+	for _, col := range groupByCols {
+		groupByAliases = append(groupByAliases, quoteIdentifier(col))
+	}
+	sb.GroupBy(groupByAliases...)
+
+	query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
+
+	rows, err := m.telemetryStore.ClickhouseDB().Query(ctx, query, args...)
+	if err != nil {
+		return nil, err
+	}
+	defer rows.Close()
+
+	result := make(map[string]map[string]int64)
+	for rows.Next() {
+		groupVals := make([]string, len(groupByCols))
+		counts := make([]uint64, len(attrNames))
+
+		scanPtrs := make([]any, 0, len(groupByCols)+len(attrNames))
+		for i := range groupVals {
+			scanPtrs = append(scanPtrs, &groupVals[i])
+		}
+		for i := range counts {
+			scanPtrs = append(scanPtrs, &counts[i])
+		}
+
+		if err := rows.Scan(scanPtrs...); err != nil {
+			return nil, err
+		}
+
+		attrCounts := make(map[string]int64, len(attrNames))
+		for i, attr := range attrNames {
+			attrCounts[attr] = int64(counts[i])
+		}
+		result[compositeKeyFromList(groupVals)] = attrCounts
+	}
+	if err := rows.Err(); err != nil {
+		return nil, err
+	}
+
+	return result, nil
+}

pkg/modules/inframonitoring/implinframonitoring/module.go

@@ -632,6 +632,7 @@ func (m *module) ListNamespaces(ctx context.Context, orgID valuer.UUID, req *inf
 		phaseCounts      map[string]podPhaseCounts
 		podStatusCounts  map[string]podStatusCounts
 		podStatusWarning *qbtypes.QueryWarnData
+		resourceCounts   map[string]map[string]int64
 	)
 
 	g, gCtx := errgroup.WithContext(ctx)
@@ -651,12 +652,17 @@ func (m *module) ListNamespaces(ctx context.Context, orgID valuer.UUID, req *inf
 		podStatusCounts, podStatusWarning, err = m.getPerGroupPodStatusCountsWithReqMetricChecks(gCtx, req.Start, req.End, req.Filter, req.GroupBy, pageGroups)
 		return err
 	})
+	g.Go(func() error {
+		var err error
+		resourceCounts, err = m.getPerGroupDistinctCounts(gCtx, orgID, req.Start, req.End, req.Filter, req.GroupBy, pageGroups, namespaceCountAttrKeys, namespacesTableMetricNamesList)
+		return err
+	})
 
 	if err := g.Wait(); err != nil {
 		return nil, err
 	}
 
-	resp.Records = buildNamespaceRecords(queryResp, pageGroups, req.GroupBy, metadataMap, phaseCounts, podStatusCounts)
+	resp.Records = buildNamespaceRecords(queryResp, pageGroups, req.GroupBy, metadataMap, phaseCounts, podStatusCounts, resourceCounts)
 	resp.Warning = mergeQueryWarnings(queryResp.Warning, podStatusWarning)
 
 	return resp, nil
@@ -732,6 +738,7 @@ func (m *module) ListClusters(ctx context.Context, orgID valuer.UUID, req *infra
 		podPhaseCountsMap      map[string]podPhaseCounts
 		podStatusCounts        map[string]podStatusCounts
 		podStatusWarning       *qbtypes.QueryWarnData
+		resourceCounts         map[string]map[string]int64
 	)
 
 	g, gCtx := errgroup.WithContext(ctx)
@@ -756,12 +763,17 @@ func (m *module) ListClusters(ctx context.Context, orgID valuer.UUID, req *infra
 		podStatusCounts, podStatusWarning, err = m.getPerGroupPodStatusCountsWithReqMetricChecks(gCtx, req.Start, req.End, req.Filter, req.GroupBy, pageGroups)
 		return err
 	})
+	g.Go(func() error {
+		var err error
+		resourceCounts, err = m.getPerGroupDistinctCounts(gCtx, orgID, req.Start, req.End, req.Filter, req.GroupBy, pageGroups, clusterCountAttrKeys, clusterMetricNamesListForCounts)
+		return err
+	})
 
 	if err := g.Wait(); err != nil {
 		return nil, err
 	}
 
-	resp.Records = buildClusterRecords(queryResp, pageGroups, req.GroupBy, metadataMap, nodeConditionCountsMap, podPhaseCountsMap, podStatusCounts)
+	resp.Records = buildClusterRecords(queryResp, pageGroups, req.GroupBy, metadataMap, nodeConditionCountsMap, podPhaseCountsMap, podStatusCounts, resourceCounts)
 	resp.Warning = mergeQueryWarnings(queryResp.Warning, podStatusWarning)
 
 	return resp, nil

pkg/modules/inframonitoring/implinframonitoring/namespaces.go

@@ -19,6 +19,7 @@ func buildNamespaceRecords(
 	metadataMap map[string]map[string]string,
 	phaseCounts map[string]podPhaseCounts,
 	podStatusCounts map[string]podStatusCounts,
+	resourceCounts map[string]map[string]int64,
 ) []inframonitoringtypes.NamespaceRecord {
 	metricsMap := parseFullQueryResponse(resp, groupBy)
 
@@ -57,6 +58,13 @@ func buildNamespaceRecords(
 			record.PodCountsByStatus = podStatusCountsToResponse(podStatusCountsForGroup)
 		}
 
+		if counts, ok := resourceCounts[compositeKey]; ok {
+			record.Counts.Deployments = counts[inframonitoringtypes.DeploymentNameAttrKey]
+			record.Counts.DaemonSets = counts[inframonitoringtypes.DaemonSetNameAttrKey]
+			record.Counts.Jobs = counts[inframonitoringtypes.JobNameAttrKey]
+			record.Counts.StatefulSets = counts[inframonitoringtypes.StatefulSetNameAttrKey]
+		}
+
 		if attrs, ok := metadataMap[compositeKey]; ok {
 			for k, v := range attrs {
 				record.Meta[k] = v

pkg/modules/inframonitoring/implinframonitoring/namespaces_constants.go

@@ -32,6 +32,16 @@ var namespaceAttrKeysForMetadata = []string{
 	"k8s.cluster.name",
 }
 
+// namespaceCountAttrKeys are the workload resource attributes whose distinct
+// values are counted per namespace. They are read from the pod metric universe,
+// which carries the owner workload names for each pod series.
+var namespaceCountAttrKeys = []string{
+	inframonitoringtypes.DeploymentNameAttrKey,
+	inframonitoringtypes.DaemonSetNameAttrKey,
+	inframonitoringtypes.JobNameAttrKey,
+	inframonitoringtypes.StatefulSetNameAttrKey,
+}
+
 var orderByToNamespacesQueryNames = map[string][]string{
 	inframonitoringtypes.NamespacesOrderByCPU:    {"A"},
 	inframonitoringtypes.NamespacesOrderByMemory: {"D"},

pkg/types/cloudintegrationtypes/serviceid.go

@@ -42,7 +42,6 @@ var (
 
 	// GCP services.
 	GCPServiceCloudSQLPostgres = ServiceID{valuer.NewString("cloudsql_postgres")}
-	GCPServiceMemorystoreRedis = ServiceID{valuer.NewString("memorystore_redis")}
 )
 
 func (ServiceID) Enum() []any {
@@ -75,7 +74,6 @@ func (ServiceID) Enum() []any {
 		AzureServiceCassandraDB,
 		AzureServiceRedis,
 		GCPServiceCloudSQLPostgres,
-		GCPServiceMemorystoreRedis,
 	}
 }
 
@@ -114,7 +112,6 @@ var SupportedServices = map[CloudProviderType][]ServiceID{
 	},
 	CloudProviderTypeGCP: {
 		GCPServiceCloudSQLPostgres,
-		GCPServiceMemorystoreRedis,
 	},
 }
 

pkg/types/inframonitoringtypes/clusters.go

@@ -28,7 +28,15 @@ type ClusterRecord struct {
 	NodeCountsByReadiness    NodeCountsByReadiness `json:"nodeCountsByReadiness" required:"true"`
 	PodCountsByPhase         PodCountsByPhase      `json:"podCountsByPhase" required:"true"`
 	PodCountsByStatus        PodCountsByStatus     `json:"podCountsByStatus" required:"true"`
-	Meta                     map[string]string     `json:"meta" required:"true"`
+	Counts                   struct {
+		Nodes        int64 `json:"nodes" required:"true"`
+		Namespaces   int64 `json:"namespaces" required:"true"`
+		Deployments  int64 `json:"deployments" required:"true"`
+		DaemonSets   int64 `json:"daemonSets" required:"true"`
+		Jobs         int64 `json:"jobs" required:"true"`
+		StatefulSets int64 `json:"statefulSets" required:"true"`
+	} `json:"counts" required:"true"`
+	Meta map[string]string `json:"meta" required:"true"`
 }
 
 // PostableClusters is the request body for the v2 clusters list API.

pkg/types/inframonitoringtypes/namespaces.go

@@ -22,7 +22,13 @@ type NamespaceRecord struct {
 	NamespaceMemory   float64           `json:"namespaceMemory" required:"true"`
 	PodCountsByPhase  PodCountsByPhase  `json:"podCountsByPhase" required:"true"`
 	PodCountsByStatus PodCountsByStatus `json:"podCountsByStatus" required:"true"`
-	Meta              map[string]string `json:"meta" required:"true"`
+	Counts            struct {
+		Deployments  int64 `json:"deployments" required:"true"`
+		DaemonSets   int64 `json:"daemonSets" required:"true"`
+		Jobs         int64 `json:"jobs" required:"true"`
+		StatefulSets int64 `json:"statefulSets" required:"true"`
+	} `json:"counts" required:"true"`
+	Meta map[string]string `json:"meta" required:"true"`
 }
 
 // PostableNamespaces is the request body for the v2 namespaces list API.

tests/integration/testdata/inframonitoring/clusters_value_accuracy.jsonl

@@ -13,9 +13,9 @@
 {"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"acc-c1-n1","k8s.node.uid":"acc-c1-n1-uid","k8s.cluster.name":"acc-cluster-1"},"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":"acc-cluster-1"},"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":"acc-cluster-1"},"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":"acc-cluster-1"},"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":"acc-cluster-1"},"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":"acc-cluster-1"},"timestamp":"2025-01-10T10:04:00+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":"acc-cluster-1","k8s.deployment.name":"dep-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"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":"acc-cluster-1","k8s.deployment.name":"dep-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"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":"acc-cluster-1","k8s.deployment.name":"dep-a"},"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":"acc-cluster-1"},"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":"acc-cluster-1"},"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":"acc-cluster-1"},"timestamp":"2025-01-10T10:04:00+00:00","value":0.5,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
@@ -31,9 +31,12 @@
 {"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"acc-c1-n2","k8s.node.uid":"acc-c1-n2-uid","k8s.cluster.name":"acc-cluster-1"},"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-n2","k8s.node.uid":"acc-c1-n2-uid","k8s.cluster.name":"acc-cluster-1"},"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-n2","k8s.node.uid":"acc-c1-n2-uid","k8s.cluster.name":"acc-cluster-1"},"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-n2-p-uid","k8s.pod.name":"acc-c1-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1"},"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-n2-p-uid","k8s.pod.name":"acc-c1-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1"},"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-n2-p-uid","k8s.pod.name":"acc-c1-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c1-n2-p-uid","k8s.pod.name":"acc-c1-n2-p","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1","k8s.statefulset.name":"sts-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c1-n2-p-uid","k8s.pod.name":"acc-c1-n2-p","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1","k8s.statefulset.name":"sts-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c1-n2-p-uid","k8s.pod.name":"acc-c1-n2-p","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1","k8s.statefulset.name":"sts-a"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c1-n2-p2-uid","k8s.pod.name":"acc-c1-n2-p2","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1","k8s.deployment.name":"dep-a"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c1-n2-p2-uid","k8s.pod.name":"acc-c1-n2-p2","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1","k8s.deployment.name":"dep-a"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c1-n2-p2-uid","k8s.pod.name":"acc-c1-n2-p2","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c1-n2","k8s.cluster.name":"acc-cluster-1","k8s.deployment.name":"dep-a"},"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-c2-n1","k8s.node.uid":"acc-c2-n1-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
 {"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-c2-n1","k8s.node.uid":"acc-c2-n1-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
 {"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-c2-n1","k8s.node.uid":"acc-c2-n1-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
@@ -49,9 +52,9 @@
 {"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"acc-c2-n1","k8s.node.uid":"acc-c2-n1-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n1","k8s.node.uid":"acc-c2-n1-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n1","k8s.node.uid":"acc-c2-n1-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n1-p-uid","k8s.pod.name":"acc-c2-n1-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n1","k8s.cluster.name":"acc-cluster-2"},"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-c2-n1-p-uid","k8s.pod.name":"acc-c2-n1-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n1","k8s.cluster.name":"acc-cluster-2"},"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-c2-n1-p-uid","k8s.pod.name":"acc-c2-n1-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n1","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n1-p-uid","k8s.pod.name":"acc-c2-n1-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n1","k8s.cluster.name":"acc-cluster-2","k8s.deployment.name":"dep-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n1-p-uid","k8s.pod.name":"acc-c2-n1-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n1","k8s.cluster.name":"acc-cluster-2","k8s.deployment.name":"dep-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n1-p-uid","k8s.pod.name":"acc-c2-n1-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n1","k8s.cluster.name":"acc-cluster-2","k8s.deployment.name":"dep-b"},"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-c2-n2","k8s.node.uid":"acc-c2-n2-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
 {"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-c2-n2","k8s.node.uid":"acc-c2-n2-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
 {"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-c2-n2","k8s.node.uid":"acc-c2-n2-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
@@ -67,9 +70,9 @@
 {"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"acc-c2-n2","k8s.node.uid":"acc-c2-n2-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n2","k8s.node.uid":"acc-c2-n2-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n2","k8s.node.uid":"acc-c2-n2-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n2-p-uid","k8s.pod.name":"acc-c2-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n2","k8s.cluster.name":"acc-cluster-2"},"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-c2-n2-p-uid","k8s.pod.name":"acc-c2-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n2","k8s.cluster.name":"acc-cluster-2"},"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-c2-n2-p-uid","k8s.pod.name":"acc-c2-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n2","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n2-p-uid","k8s.pod.name":"acc-c2-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n2","k8s.cluster.name":"acc-cluster-2","k8s.daemonset.name":"ds-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n2-p-uid","k8s.pod.name":"acc-c2-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n2","k8s.cluster.name":"acc-cluster-2","k8s.daemonset.name":"ds-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n2-p-uid","k8s.pod.name":"acc-c2-n2-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n2","k8s.cluster.name":"acc-cluster-2","k8s.daemonset.name":"ds-b"},"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-c2-n3","k8s.node.uid":"acc-c2-n3-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:00:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
 {"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-c2-n3","k8s.node.uid":"acc-c2-n3-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:02:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
 {"metric_name":"k8s.node.cpu.usage","labels":{"k8s.node.name":"acc-c2-n3","k8s.node.uid":"acc-c2-n3-uid","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:04:00+00:00","value":1.0,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
@@ -85,6 +88,6 @@
 {"metric_name":"k8s.node.condition_ready","labels":{"k8s.node.name":"acc-c2-n3","k8s.node.uid":"acc-c2-n3-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n3","k8s.node.uid":"acc-c2-n3-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n3","k8s.node.uid":"acc-c2-n3-uid","k8s.cluster.name":"acc-cluster-2"},"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-c2-n3-p-uid","k8s.pod.name":"acc-c2-n3-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n3","k8s.cluster.name":"acc-cluster-2"},"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-c2-n3-p-uid","k8s.pod.name":"acc-c2-n3-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n3","k8s.cluster.name":"acc-cluster-2"},"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-c2-n3-p-uid","k8s.pod.name":"acc-c2-n3-p","k8s.namespace.name":"ns-x","k8s.node.name":"acc-c2-n3","k8s.cluster.name":"acc-cluster-2"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n3-p-uid","k8s.pod.name":"acc-c2-n3-p","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c2-n3","k8s.cluster.name":"acc-cluster-2","k8s.job.name":"job-b"},"timestamp":"2025-01-10T10:00:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n3-p-uid","k8s.pod.name":"acc-c2-n3-p","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c2-n3","k8s.cluster.name":"acc-cluster-2","k8s.job.name":"job-b"},"timestamp":"2025-01-10T10:02:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}
+{"metric_name":"k8s.pod.phase","labels":{"k8s.pod.uid":"acc-c2-n3-p-uid","k8s.pod.name":"acc-c2-n3-p","k8s.namespace.name":"ns-y","k8s.node.name":"acc-c2-n3","k8s.cluster.name":"acc-cluster-2","k8s.job.name":"job-b"},"timestamp":"2025-01-10T10:04:00+00:00","value":2,"temporality":"Unspecified","type_":"Gauge","is_monotonic":false}

tests/integration/testdata/inframonitoring/clusters_value_accuracy_expected.json

@@ -12,10 +12,18 @@
       },
       "podCountsByPhase": {
         "pending": 0,
-        "running": 2,
+        "running": 3,
         "succeeded": 0,
         "failed": 0,
         "unknown": 0
+      },
+      "counts": {
+        "nodes": 2,
+        "namespaces": 2,
+        "deployments": 2,
+        "daemonSets": 0,
+        "jobs": 0,
+        "statefulSets": 1
       }
     },
     {
@@ -34,6 +42,14 @@
         "succeeded": 0,
         "failed": 0,
         "unknown": 0
+      },
+      "counts": {
+        "nodes": 3,
+        "namespaces": 2,
+        "deployments": 1,
+        "daemonSets": 1,
+        "jobs": 1,
+        "statefulSets": 0
       }
     }
   ]

tests/integration/testdata/inframonitoring/namespaces_value_accuracy.jsonl

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

tests/integration/testdata/inframonitoring/namespaces_value_accuracy_expected.json

@@ -4,13 +4,15 @@
       "namespaceName": "acc-ns-1",
       "namespaceCPU": 1.0,
       "namespaceMemory": 200000000.0,
-      "podCountsByPhase": {"pending": 0, "running": 2, "succeeded": 0, "failed": 0, "unknown": 0}
+      "podCountsByPhase": {"pending": 0, "running": 2, "succeeded": 0, "failed": 0, "unknown": 0},
+      "counts": {"deployments": 2, "daemonSets": 0, "jobs": 0, "statefulSets": 0}
     },
     {
       "namespaceName": "acc-ns-2",
       "namespaceCPU": 2.25,
       "namespaceMemory": 600000000.0,
-      "podCountsByPhase": {"pending": 0, "running": 3, "succeeded": 0, "failed": 0, "unknown": 0}
+      "podCountsByPhase": {"pending": 0, "running": 3, "succeeded": 0, "failed": 0, "unknown": 0},
+      "counts": {"deployments": 1, "daemonSets": 1, "jobs": 1, "statefulSets": 0}
     }
   ]
 }

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

@@ -74,6 +74,7 @@ def test_namespaces_accuracy(
             "namespaceCPU",
             "namespaceMemory",
             "podCountsByPhase",
+            "counts",
             "meta",
         ):
             assert field in record, f"missing {field} in {record!r}"
@@ -81,6 +82,9 @@ def test_namespaces_accuracy(
         for bucket in ("pending", "running", "succeeded", "failed", "unknown"):
             assert bucket in record["podCountsByPhase"]
             assert isinstance(record["podCountsByPhase"][bucket], int)
+        for bucket in ("deployments", "daemonSets", "jobs", "statefulSets"):
+            assert bucket in record["counts"]
+            assert isinstance(record["counts"][bucket], int)
 
         assert record["meta"].get("k8s.namespace.name") == record["namespaceName"]
         assert "k8s.cluster.name" in record["meta"]
@@ -90,6 +94,7 @@ def test_namespaces_accuracy(
         for field in ("namespaceCPU", "namespaceMemory"):
             assert compare_values(record[field], exp[field], 1e-6), f"{record['namespaceName']}.{field}: got {record[field]}, expected {exp[field]}"
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
+        assert record["counts"] == exp["counts"]
 
 
 @pytest.mark.parametrize(

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

@@ -78,6 +78,7 @@ def test_clusters_accuracy(
             "clusterMemoryAllocatable",
             "nodeCountsByReadiness",
             "podCountsByPhase",
+            "counts",
             "meta",
         ):
             assert field in record, f"missing {field} in {record!r}"
@@ -88,6 +89,9 @@ def test_clusters_accuracy(
         for bucket in ("pending", "running", "succeeded", "failed", "unknown"):
             assert bucket in record["podCountsByPhase"]
             assert isinstance(record["podCountsByPhase"][bucket], int)
+        for bucket in ("nodes", "namespaces", "deployments", "daemonSets", "jobs", "statefulSets"):
+            assert bucket in record["counts"]
+            assert isinstance(record["counts"][bucket], int)
 
         assert record["meta"].get("k8s.cluster.name") == record["clusterName"]
 
@@ -102,6 +106,7 @@ def test_clusters_accuracy(
             assert compare_values(record[field], exp[field], 1e-6), f"{record['clusterName']}.{field}: got {record[field]}, expected {exp[field]}"
         assert record["nodeCountsByReadiness"] == exp["nodeCountsByReadiness"]
         assert record["podCountsByPhase"] == exp["podCountsByPhase"]
+        assert record["counts"] == exp["counts"]
 
 
 @pytest.mark.parametrize(