Merge branch 'main' into issue-5535

chore: add to ci
2026-07-06 22:50:38 +01:00 · 2026-07-06 20:55:56 +05:30 · 2026-07-06 11:51:09 +05:30 · 2026-07-06 11:50:46 +05:30 · 2026-07-06 11:19:45 +05:30
28 changed files with 1605 additions and 772 deletions
--- a/.github/workflows/integrationci.yaml
+++ b/.github/workflows/integrationci.yaml
@@ -56,6 +56,8 @@ jobs:
          - querier_json_body
          - querier_skip_resource_fingerprint
          - ttl
+          - clickhousecluster
+          - metricreduction
        sqlstore-provider:
          - postgres
          - sqlite
--- a/frontend/src/assets/Logos/cassandra.svg
+++ b/frontend/src/assets/Logos/cassandra.svg
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" fill="#1287b1" viewBox="0 0 24 24"><title>Apache Cassandra</title><path d="M10.374 10.53a3 3 0 0 1-.428-.222l.555.143c0 .02-.01.036-.01.055l-.117.025zm-.283 1.506-.315.253.852-1.079-1.078.391c.002.017.009.033.009.05a.57.57 0 0 1-.184.42q.154.327.375.616a3.2 3.2 0 0 1 .34-.651zm.717-2.347-.652-.82a.43.43 0 0 1-.506.162c-.054.073-.083.162-.13.24l1.258.463zm-1.666.444c-.07.314-.087.637-.05.956a.57.57 0 0 1 .451.475l.946-.606c-.067-.022-.126-.06-.191-.088l-1.119-.08.64-.14a3.2 3.2 0 0 1-.668-.554zM20.1 11.648c-.164.202.833 1.022.833 1.022s-1.654-1.022-2.234-.72c-.278.144.574.811 1.175 1.242-.428-.274-.982-.571-1.175-.408-.328.277 1.565 2.549 1.565 2.549s-2.145-2.322-2.36-2.209c-.214.114.593 1.224.593 1.224s-1.06-1.16-1.35-.959c-.29.202 1.514 3.218 1.514 3.218s-1.956-3.091-2.763-2.574c1.268 2.782.795 3.18.795 3.18s-.162-2.839-1.742-2.764c-.795.038.379 2.12.379 2.12s-1.08-1.902-1.8-1.864c1.326 2.51.854 3.53.854 3.53s.219-2.143-1.58-3.336c.682.606-.427 3.336-.427 3.336s.976-4.023-.719-3.256c-.268.121-.019 2.007-.019 2.007s-.34-2.158-.851-2.045c-.298.066-1.893 2.99-1.893 2.99s1.306-3.16.908-3.027c-.29.096-.833 1.4-.833 1.4s.265-1.287 0-1.363c-.264-.075-1.74 1.363-1.74 1.363s1.097-1.287.908-1.552c-.287-.402-.623-.42-1.022-.265-.581.226-1.363 1.287-1.363 1.287s.78-1.074.643-1.476c-.219-.647-2.46 1.249-2.46 1.249s1.325-1.25 1.022-1.514c-.303-.265-1.947-.183-2.46-.185-1.515-.004-2.039-.36-2.498-.724 1.987.997 3.803-.151 6.094.494l.21.06c-1.3-.558-2.144-1.378-2.226-2.354-.036-.416.074-.827.297-1.222.619-.4 1.29-.773 2.06-1.095a4 4 0 0 0-.064.698c0 2.44 2.203 4.417 4.92 4.417s4.92-1.977 4.92-4.417c0-.45-.083-.881-.223-1.29 1.431.404 2.45.968 3.132 1.335.022.092.045.184.053.279.024.274-.018.547-.11.814.095-.147.198-.288.28-.445.367-.997 1.855.227 1.855.227s-1.085-.454-1.06-.24c.026.215 1.628.96 1.628.96s-1.45-.455-1.362-.114c.088.34 1.817 1.703 1.817 1.703s-1.956-1.489-2.12-1.287zm-7.268 2.65.042-.008-.06.01zM9.256 9.753c.12.13.26.234.396.343l.927-.029-1.064-.788c-.093.154-.195.303-.26.474Zm10.62 3.44c.3.215.54.373.54.373s-.24-.181-.54-.374zM7.507 8.617c-.14.229-.214.492-.215.76a3.99 3.99 0 0 0 2.358 3.64q0-.008.003-.014a3.2 3.2 0 0 1-.58-.788c-.648.099-.926-.794-.336-1.08a3.2 3.2 0 0 1 .138-1.388 3.16 3.16 0 0 1-.52-1.36q-.444.105-.848.23m1.488.82q.163-.36.402-.661a.435.435 0 0 1 .568-.557c.077-.059.166-.099.248-.15a16 16 0 0 0-1.727.284c.114.388.272.76.509 1.084m2.285 3.928c1.4 0 2.633-.723 3.344-1.816a3.4 3.4 0 0 0-1.265-.539l-.297-.023.916.9-1.197-.467.704 1.078-1.074-.832-.012.006.347 1.278-.596-1.134-.098 1.33-.401-1.326-.472 1.261.114-1.359-.015-.008-.814 1.154.286-1.067c-.34.322-.605.713-.781 1.146q.143.153.303.29.484.126 1.008.128m10.145-4.434c.971-.567 1.716-1.955 1.716-1.955s-1.893 1.955-3.205 1.665c1.186-.934 1.766-2.549 1.766-2.549s-1.506 2.325-2.448 2.423c1.086-.959 1.54-2.322 1.54-2.322s-1.237 1.817-2.196 1.944c1.287-1.161 1.338-1.893 1.338-1.893s-1.781 2.302-2.499 1.943c.858-.934 1.439-2.12 1.439-2.12s-1.489 2.019-1.893 1.69c-.277-.05.454-.958.454-.958s-.908.807-1.16.606c.454-.278 1.236-1.64 1.236-1.64S16 7.505 15.621 7.304l.731-1.483s-.73 1.483-1.715 1.23c.454-.58.63-1.112.63-1.112s-.756 1.213-1.69.885c-.22-.077.273-.635.273-.635s-.626.61-1.055.534c-.43-.076.025-.858.025-.858s-.757 1.186-.908 1.136.075-.833.075-.833-.555.908-.858.858 0-.934 0-.934-.328.984-.58.909c-.252-.076-.303-.656-.303-.656s-.068.788-.429.858c-2.725.53-5.728 1.69-9.489 5.45C3.887 10.738 5.3 7.91 11.962 7.659c5.044-.191 7.399 2.137 8.177 2.17C22.51 9.93 24 7.633 24 7.633s-1.489 1.716-2.574 1.3zm-7.74.872-.608.464v.001l.054.003a3.4 3.4 0 0 0 .554-.468m1.583-.426c0-.536-.237-.929-.594-1.217a3.2 3.2 0 0 1-.165.825.393.393 0 0 1-.328.681c-.154.233-.34.445-.549.63l.661.034-.995.237c-.025.018-.045.041-.07.058a3.2 3.2 0 0 1 1.536.691c.32-.574.504-1.235.504-1.94zM10.99 7.996a3.5 3.5 0 0 0-.785.46.43.43 0 0 1-.013.357l.885.643.023-.016-.36-1.262.627 1.12c.018-.006.04-.006.058-.011l-.02-1.251.398 1.163.477-1.15.016 1.268.012.007.713-1.005-.363 1.218.009.01 1.04-.69-.759 1.05.002.005.95-.34.041-.045a.395.395 0 0 1 .394-.632 3.4 3.4 0 0 0 .27-.784 14 14 0 0 0-2.798-.168c-.286.011-.55.033-.817.053"/></svg>
--- a/frontend/src/assets/Logos/fluxcd.svg
+++ b/frontend/src/assets/Logos/fluxcd.svg
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" viewBox="48 -2.25 262.5 364"><defs><style>.cls-1{fill:#326ce5}.cls-3{fill:none}</style></defs><path d="M59.724 97.778a10.183 10.183 0 0 1 0-17.073l114.07-74.16a10.18 10.18 0 0 1 11.1 0l114.07 74.16a10.183 10.183 0 0 1 0 17.073l-114.07 74.16a10.18 10.18 0 0 1-11.1 0z" class="cls-1"/><path fill="#c1d2f7" d="M197.356 110.866h7.912a6.003 6.003 0 0 0 5.2-9.005l-25.924-44.902a6.004 6.004 0 0 0-10.399 0l-25.924 44.902a6.003 6.003 0 0 0 5.2 9.005h7.912a6.003 6.003 0 0 1 6.004 6.003v51.257l5.31 3.452a12.29 12.29 0 0 0 13.395 0l5.31-3.452v-51.257a6.003 6.003 0 0 1 6.004-6.003"/><path d="M173.793 353.271a10.1 10.1 0 0 0 3.457 1.402 119 119 0 0 0-6.623-3.46zm-6.456-161.195-11.316 7.356a111 111 0 0 0 11.316 6.6zm24.015 23.716c9.739 3.115 19.813 5.648 30.11 8.186 10.92 2.692 21.973 5.427 32.818 9.009l-35.416-23.025a216 216 0 0 1-27.512-9.41zm0 62.191v.586c0 2.57-2.688 4.652-6.003 4.652H173.34c-3.315 0-6.003-2.083-6.003-4.652v-6.605c-24.906-6.402-49.873-14.485-70.86-33.82l-14.529 9.445c22.468 22.05 50.28 28.933 79.715 36.189 27.178 6.698 55.18 13.651 78.685 33.442l14.68-9.544c-18.532-16.504-40.41-23.687-63.676-29.693M93.315 300.95l38.908 25.295c20.064 5.113 40.2 11.248 58.31 23.36l14.901-9.687c-19.752-13.672-42.55-19.313-66.419-25.197-15.287-3.767-30.835-7.616-45.7-13.771m74.022-82.254a124.3 124.3 0 0 1-21.534-12.62l-14.805 9.625a124.5 124.5 0 0 0 36.339 18.708zm51.41 16.294c-9.106-2.245-18.304-4.524-27.395-7.299v13.682q5.051 1.286 10.177 2.538c29.934 7.379 60.888 15.01 85.708 39.829.61.61 1.162 1.24 1.752 1.857l9.974-6.484a10.1 10.1 0 0 0 3.475-3.8 101 101 0 0 0-3.289-3.486c-22.585-22.585-50.669-29.508-80.402-36.837m-19.933 19.933q-3.722-.918-7.462-1.855v13.21c25.817 6.561 51.803 14.688 73.455 35.04l14.521-9.44-.11-.118c-22.586-22.585-50.67-29.509-80.404-36.837m-31.477-8.587c-16.28-5.278-32.118-12.397-46.344-24.131l-14.682 9.545c17.87 15.557 38.784 22.673 61.026 28.5z" class="cls-3"/><path d="M73.24 254.96c-.348-.348-.658-.71-1-1.06l-12.514 8.136a10 10 0 0 0-1.644 1.397c1.053 1.157 2.115 2.31 3.245 3.44 22.585 22.585 50.67 29.509 80.403 36.837 25.343 6.247 51.401 12.717 73.865 29.603l14.806-9.626c-20.865-16.42-45.53-22.509-71.453-28.898-29.934-7.379-60.888-15.01-85.708-39.83" class="cls-3"/><path d="m218.864 209.962-27.512-17.886v8.476a216 216 0 0 0 27.512 9.41m-27.512 5.83v11.9c9.091 2.774 18.289 5.053 27.395 7.298 29.733 7.329 57.817 14.252 80.402 36.837a101 101 0 0 1 3.29 3.486 10.193 10.193 0 0 0-3.476-13.277l-44.683-29.05c-10.845-3.58-21.898-6.316-32.818-9.008-10.297-2.538-20.371-5.071-30.11-8.186m-24.015-9.76a111 111 0 0 1-11.316-6.6l-10.218 6.644a124.3 124.3 0 0 0 21.534 12.62zm34.192 37.88q-5.125-1.264-10.177-2.539v11.695q3.737.938 7.462 1.855c29.733 7.328 57.818 14.252 80.403 36.837.039.039.073.079.111.118l9.66-6.28c-.589-.618-1.142-1.248-1.751-1.858-24.82-24.82-55.774-32.45-85.708-39.829m-34.192-9.503a124.5 124.5 0 0 1-36.34-18.708l-10.004 6.504c14.226 11.734 30.064 18.853 46.344 24.13zm0 25.842c-22.242-5.828-43.156-12.944-61.026-28.5l-9.834 6.392c20.987 19.336 45.954 27.42 70.86 33.821zm24.015 17.732c23.266 6.006 45.144 13.19 63.675 29.693l9.78-6.358c-21.652-20.352-47.638-28.479-73.455-35.04zM81.948 247.59l-9.707 6.311c.341.35.652.712 1 1.06 24.82 24.82 55.773 32.45 85.707 39.829 25.922 6.39 50.588 12.478 71.452 28.898l9.948-6.467c-23.505-19.791-51.507-26.744-78.685-33.442-29.436-7.256-57.247-14.138-79.715-36.189m-20.621 19.284c-1.13-1.13-2.192-2.283-3.245-3.44a10.154 10.154 0 0 0 1.644 15.68l33.589 21.837c14.865 6.155 30.413 10.004 45.7 13.771 23.869 5.884 46.667 11.525 66.419 25.197l10.16-6.605c-22.463-16.886-48.521-23.356-73.864-29.603-29.733-7.328-57.818-14.252-80.403-36.837m109.3 84.34a119 119 0 0 1 6.623 3.46 10.16 10.16 0 0 0 7.645-1.402l5.639-3.666c-18.11-12.112-38.247-18.247-58.311-23.36z" class="cls-1"/></svg>
--- a/frontend/src/assets/Logos/planetscale.svg
+++ b/frontend/src/assets/Logos/planetscale.svg
@@ -1 +0,0 @@
-<svg xmlns="http://www.w3.org/2000/svg" fill="currentColor" viewBox="0 0 24 24"><title>PlanetScale</title><path d="M0 12C0 5.373 5.373 0 12 0c4.873 0 9.067 2.904 10.947 7.077l-15.87 15.87a12 12 0 0 1-1.935-1.099L14.99 12H12l-8.485 8.485A11.96 11.96 0 0 1 0 12m12.004 12L24 12.004C23.998 18.628 18.628 23.998 12.004 24"/></svg>
--- a/frontend/src/container/AIAssistant/ConversationView/ConversationView.tsx
+++ b/frontend/src/container/AIAssistant/ConversationView/ConversationView.tsx
@@ -177,13 +177,7 @@ export default function ConversationView({
 				conversationId={conversationId}
 				messages={messages}
 				isStreaming={isStreamingHere}
-				onSendSuggestedPrompt={(text): void => {
-					handleSend(
-						text,
-						undefined,
-						autoContexts.length > 0 ? autoContexts : undefined,
-					);
-				}}
+				onSendSuggestedPrompt={(text): void => handleSend(text)}
 			/>
 			{showDisclaimer && (
 				<div className={disclaimerClass} role="note" aria-live="polite">
--- a/frontend/src/container/AIAssistant/ConversationView/tests/ConversationView.test.tsx
+++ b/frontend/src/container/AIAssistant/ConversationView/tests/ConversationView.test.tsx
@@ -1,142 +0,0 @@
-import { MemoryRouter } from 'react-router-dom';
-// eslint-disable-next-line no-restricted-imports
-import { fireEvent, render } from '@testing-library/react';
-import { MessageContext } from 'api/ai-assistant/chat';
-import { useAIAssistantStore } from 'container/AIAssistant/store/useAIAssistantStore';
-import { VariantContext } from 'container/AIAssistant/VariantContext';
-
-const CHIP_ID = 'recent-errors';
-const CHIP_TEXT = 'Show me recent errors';
-
-// Auto-derived page context that a normal (typed) send would attach. The chip
-// send must forward the exact same array.
-const mockAutoContexts: MessageContext[] = [
-	{
-		source: 'auto',
-		type: 'dashboard',
-		resourceId: 'dashboard-123',
-		resourceName: 'Checkout dashboard',
-	},
-];
-
-jest.mock('api/common/logEvent', () => ({
-	__esModule: true,
-	default: jest.fn(),
-}));
-
-jest.mock('container/AIAssistant/getAutoContexts', () => ({
-	getAutoContexts: jest.fn(() => mockAutoContexts),
-}));
-
-jest.mock('container/AIAssistant/hooks/useAIAssistantAnalyticsContext', () => ({
-	normalizePage: (page: string): string => page,
-	useAIAssistantAnalyticsContext: (): unknown => ({ threadId: 'thread-1' }),
-}));
-
-// ChatInput is heavy and irrelevant here — the chip path lives entirely in the
-// empty state. Provide a lightweight stub plus the `autoContextKey` named export
-// ConversationView imports for its dismissed-context filter.
-jest.mock('container/AIAssistant/components/ChatInput', () => ({
-	__esModule: true,
-	default: (): JSX.Element => <div data-testid="chat-input" />,
-	autoContextKey: (): string => '',
-}));
-
-jest.mock('container/AIAssistant/components/ConversationSkeleton', () => ({
-	__esModule: true,
-	default: (): JSX.Element => <div data-testid="skeleton" />,
-}));
-
-// VirtualizedMessages renders the real empty-state chips; stub only its
-// never-rendered-in-empty-state children and the virtual list.
-jest.mock('components/Noz/Noz', () => ({
-	__esModule: true,
-	default: (): JSX.Element => <div data-testid="noz" />,
-}));
-
-jest.mock('container/AIAssistant/components/MessageBubble', () => ({
-	__esModule: true,
-	default: (): null => null,
-}));
-
-jest.mock('container/AIAssistant/components/StreamingMessage', () => ({
-	__esModule: true,
-	default: (): null => null,
-}));
-
-jest.mock('react-virtuoso', () => ({
-	__esModule: true,
-	Virtuoso: (): null => null,
-}));
-
-jest.mock(
-	'container/AIAssistant/components/VirtualizedMessages/useEmptyStateChips',
-	() => ({
-		useEmptyStateChips: (): { chips: { id: string; text: string }[] } => ({
-			chips: [{ id: CHIP_ID, text: CHIP_TEXT }],
-		}),
-	}),
-);
-
-// eslint-disable-next-line import/first
-import ConversationView from '../ConversationView';
-
-const CONVERSATION_ID = 'conv-1';
-
-function renderView(variant: 'panel' | 'page' | 'modal'): {
-	getByTestId: (id: string) => HTMLElement;
-} {
-	return render(
-		<MemoryRouter initialEntries={['/dashboard/dashboard-123']}>
-			<VariantContext.Provider value={variant}>
-				<ConversationView conversationId={CONVERSATION_ID} />
-			</VariantContext.Provider>
-		</MemoryRouter>,
-	);
-}
-
-describe('ConversationView — empty-state chip context', () => {
-	let sendMessage: jest.Mock;
-
-	beforeEach(() => {
-		jest.clearAllMocks();
-		sendMessage = jest.fn();
-		useAIAssistantStore.setState({
-			conversations: {
-				[CONVERSATION_ID]: {
-					id: CONVERSATION_ID,
-					messages: [],
-					createdAt: 1,
-					updatedAt: 1,
-				},
-			},
-			streams: {},
-			activeConversationId: CONVERSATION_ID,
-			isLoadingThread: false,
-			sendMessage,
-		} as unknown as Partial<ReturnType<typeof useAIAssistantStore.getState>>);
-	});
-
-	it('forwards the page auto-contexts when a chip is clicked (embedded variant)', () => {
-		const { getByTestId } = renderView('panel');
-
-		fireEvent.click(getByTestId(`empty-state-chip-${CHIP_ID}`));
-
-		// The chip send must carry the same auto-contexts a typed message would.
-		expect(sendMessage).toHaveBeenCalledTimes(1);
-		expect(sendMessage).toHaveBeenCalledWith(
-			CHIP_TEXT,
-			undefined,
-			mockAutoContexts,
-		);
-	});
-
-	it('sends undefined contexts on the standalone page (no page context to attach)', () => {
-		const { getByTestId } = renderView('page');
-
-		fireEvent.click(getByTestId(`empty-state-chip-${CHIP_ID}`));
-
-		expect(sendMessage).toHaveBeenCalledTimes(1);
-		expect(sendMessage).toHaveBeenCalledWith(CHIP_TEXT, undefined, undefined);
-	});
-});
--- a/frontend/src/container/LogDetailedView/InfraMetrics/constants.ts
+++ b/frontend/src/container/LogDetailedView/InfraMetrics/constants.ts
@@ -1625,9 +1625,6 @@ export const getHostQueryPayload = (
 	const diskPendingKey = dotMetricsEnabled
 		? 'system.disk.pending_operations'
 		: 'system_disk_pending_operations';
-	const fsUsageKey = dotMetricsEnabled
-		? 'system.filesystem.usage'
-		: 'system_filesystem_usage';

 	return [
 		{
@@ -2660,155 +2657,6 @@ export const getHostQueryPayload = (
 			start,
 			end,
 		},
-		{
-			selectedTime: 'GLOBAL_TIME',
-			graphType: PANEL_TYPES.TIME_SERIES,
-			query: {
-				builder: {
-					queryData: [
-						{
-							aggregateAttribute: {
-								dataType: DataTypes.Float64,
-								id: 'system_filesystem_usage--float64--Gauge--true',
-
-								key: fsUsageKey,
-								type: 'Gauge',
-							},
-							aggregateOperator: 'avg',
-							dataSource: DataSource.METRICS,
-							disabled: true,
-							expression: 'A',
-							filters: {
-								items: [
-									{
-										id: 'fs_f1',
-										key: {
-											dataType: DataTypes.String,
-											id: 'host_name--string--tag--false',
-
-											key: hostNameKey,
-											type: 'tag',
-										},
-										op: '=',
-										value: hostName,
-									},
-									{
-										id: 'fs_f2',
-										key: {
-											dataType: DataTypes.String,
-											id: 'state--string--tag--false',
-
-											key: 'state',
-											type: 'tag',
-										},
-										op: '=',
-										value: 'used',
-									},
-								],
-								op: 'AND',
-							},
-							functions: [],
-							groupBy: [
-								{
-									dataType: DataTypes.String,
-									id: 'mountpoint--string--tag--false',
-
-									key: 'mountpoint',
-									type: 'tag',
-								},
-							],
-							having: [
-								{
-									columnName: `SUM(${fsUsageKey})`,
-									op: '>',
-									value: 0,
-								},
-							],
-							legend: '{{mountpoint}}',
-							limit: null,
-							orderBy: [],
-							queryName: 'A',
-							reduceTo: ReduceOperators.AVG,
-							spaceAggregation: 'sum',
-							stepInterval: 60,
-							timeAggregation: 'avg',
-						},
-						{
-							aggregateAttribute: {
-								dataType: DataTypes.Float64,
-								id: 'system_filesystem_usage--float64--Gauge--true',
-
-								key: fsUsageKey,
-								type: 'Gauge',
-							},
-							aggregateOperator: 'avg',
-							dataSource: DataSource.METRICS,
-							disabled: true,
-							expression: 'B',
-							filters: {
-								items: [
-									{
-										id: 'fs_f3',
-										key: {
-											dataType: DataTypes.String,
-											id: 'host_name--string--tag--false',
-
-											key: hostNameKey,
-											type: 'tag',
-										},
-										op: '=',
-										value: hostName,
-									},
-								],
-								op: 'AND',
-							},
-							functions: [],
-							groupBy: [
-								{
-									dataType: DataTypes.String,
-									id: 'mountpoint--string--tag--false',
-
-									key: 'mountpoint',
-									type: 'tag',
-								},
-							],
-							having: [
-								{
-									columnName: `SUM(${fsUsageKey})`,
-									op: '>',
-									value: 0,
-								},
-							],
-							legend: '{{mountpoint}}',
-							limit: null,
-							orderBy: [],
-							queryName: 'B',
-							reduceTo: ReduceOperators.AVG,
-							spaceAggregation: 'sum',
-							stepInterval: 60,
-							timeAggregation: 'avg',
-						},
-					],
-					queryFormulas: [
-						{
-							disabled: false,
-							expression: 'A/B',
-							legend: '{{mountpoint}}',
-							queryName: 'F1',
-						},
-					],
-					queryTraceOperator: [],
-				},
-				clickhouse_sql: [{ disabled: false, legend: '', name: 'A', query: '' }],
-				id: 'a1b2c3d4-e5f6-7890-abcd-ef1234567890',
-				promql: [{ disabled: false, legend: '', name: 'A', query: '' }],
-				queryType: EQueryType.QUERY_BUILDER,
-			},
-			variables: {},
-			formatForWeb: false,
-			start,
-			end,
-		},
 	];
 };

@@ -2884,5 +2732,4 @@ export const hostWidgetInfo = [
 	{ title: 'System disk operations/s', yAxisUnit: 'short' },
 	{ title: 'Queue size', yAxisUnit: 'short' },
 	{ title: 'System disk operation time/s', yAxisUnit: 's' },
-	{ title: 'Disk Usage (%) by mountpoint', yAxisUnit: 'percentunit' },
 ];
--- a/frontend/src/container/OnboardingV2Container/onboarding-configs/onboarding-config-with-links.ts
+++ b/frontend/src/container/OnboardingV2Container/onboarding-configs/onboarding-config-with-links.ts
@@ -20,7 +20,6 @@ import azureOpenaiUrl from '@/assets/Logos/azure-openai.svg';
 import azureSqlDatabaseMetricsUrl from '@/assets/Logos/azure-sql-database-metrics.svg';
 import azureVmUrl from '@/assets/Logos/azure-vm.svg';
 import basetenUrl from '@/assets/Logos/baseten.svg';
-import cassandraUrl from '@/assets/Logos/cassandra.svg';
 import celeryUrl from '@/assets/Logos/celery.svg';
 import certManagerUrl from '@/assets/Logos/cert-manager.svg';
 import claudeCodeUrl from '@/assets/Logos/claude-code.svg';
@@ -52,7 +51,6 @@ import externalApiMonitoringUrl from '@/assets/Logos/external-api-monitoring.svg
 import fluentbitUrl from '@/assets/Logos/fluentbit.svg';
 import fluentdUrl from '@/assets/Logos/fluentd.svg';
 import flutterMonitoringUrl from '@/assets/Logos/flutter-monitoring.svg';
-import fluxcdUrl from '@/assets/Logos/fluxcd.svg';
 import flyIoUrl from '@/assets/Logos/fly-io.svg';
 import fromLogFileUrl from '@/assets/Logos/from-log-file.svg';
 import gcpAppEngineUrl from '@/assets/Logos/gcp-app-engine.svg';
@@ -96,7 +94,6 @@ import langtraceUrl from '@/assets/Logos/langtrace.svg';
 import litellmUrl from '@/assets/Logos/litellm.svg';
 import livekitUrl from '@/assets/Logos/livekit.svg';
 import llamaindexUrl from '@/assets/Logos/llamaindex.svg';
-import llmMonitoringUrl from '@/assets/Logos/llm-monitoring.svg';
 import logrusUrl from '@/assets/Logos/logrus.svg';
 import logsUrl from '@/assets/Logos/logs.svg';
 import logstashUrl from '@/assets/Logos/logstash.svg';
@@ -123,7 +120,6 @@ import opentelemetryUrl from '@/assets/Logos/opentelemetry.svg';
 import phpUrl from '@/assets/Logos/php.svg';
 import pinoUrl from '@/assets/Logos/pino.svg';
 import pipecatUrl from '@/assets/Logos/pipecat.svg';
-import planetscaleUrl from '@/assets/Logos/planetscale.svg';
 import postgresqlUrl from '@/assets/Logos/postgresql.svg';
 import prometheusUrl from '@/assets/Logos/prometheus.svg';
 import pydanticAiUrl from '@/assets/Logos/pydantic-ai.svg';
@@ -1530,28 +1526,6 @@ const onboardingConfigWithLinks = [
 		id: 'nginx-tracing',
 		link: '/docs/instrumentation/opentelemetry-nginx/',
 	},
-	{
-		dataSource: 'nginx-ingress-controller',
-		label: 'NGINX Ingress Controller',
-		imgUrl: nginxUrl,
-		tags: ['infrastructure monitoring'],
-		module: 'metrics',
-		relatedSearchKeywords: [
-			'ingress',
-			'ingress controller',
-			'kubernetes ingress',
-			'monitoring',
-			'nginx ingress',
-			'nginx ingress controller',
-			'nginx ingress metrics',
-			'nginx ingress monitoring',
-			'nginx ingress observability',
-			'observability',
-			'opentelemetry nginx ingress',
-		],
-		id: 'nginx-ingress-controller',
-		link: '/docs/metrics-management/nginx-ingress-controller/',
-	},
 	{
 		dataSource: 'opentelemetry-cloudflare',
 		label: 'Cloudflare Tracing',
@@ -1612,119 +1586,6 @@ const onboardingConfigWithLinks = [
 		id: 'opentelemetry-cloudflare-logs',
 		link: '/docs/logs-management/send-logs/cloudflare-logs/',
 	},
-	{
-		dataSource: 'cloudflare-workers',
-		label: 'Cloudflare Workers',
-		imgUrl: cloudflareUrl,
-		tags: ['apm/traces'],
-		module: 'apm',
-		relatedSearchKeywords: [
-			'cloudflare',
-			'cloudflare workers',
-			'cloudflare workers monitoring',
-			'cloudflare workers observability',
-			'cloudflare workers otlp',
-			'edge computing monitoring',
-			'monitor cloudflare workers',
-			'monitoring',
-			'observability',
-			'opentelemetry cloudflare workers',
-			'otlp',
-			'serverless monitoring',
-		],
-		id: 'cloudflare-workers',
-		link: '/docs/integrations/outposts/cloudflare-workers/',
-	},
-	{
-		dataSource: 'opentelemetry-cassandra',
-		label: 'Cassandra',
-		imgUrl: cassandraUrl,
-		tags: ['database'],
-		module: 'apm',
-		relatedSearchKeywords: [
-			'apache cassandra',
-			'cassandra',
-			'cassandra database',
-			'cassandra logs',
-			'cassandra metrics',
-			'cassandra monitoring',
-			'cassandra observability',
-			'database',
-			'monitoring',
-			'nosql',
-			'observability',
-			'opentelemetry cassandra',
-		],
-		id: 'opentelemetry-cassandra',
-		link: '/docs/integrations/opentelemetry-cassandra/',
-	},
-	{
-		dataSource: 'fluxcd',
-		label: 'FluxCD',
-		imgUrl: fluxcdUrl,
-		tags: ['infrastructure monitoring'],
-		module: 'metrics',
-		relatedSearchKeywords: [
-			'continuous delivery',
-			'flux',
-			'fluxcd',
-			'fluxcd dashboard',
-			'fluxcd metrics',
-			'fluxcd monitoring',
-			'fluxcd observability',
-			'gitops',
-			'kubernetes',
-			'monitoring',
-			'observability',
-			'opentelemetry fluxcd',
-		],
-		id: 'fluxcd',
-		link: '/docs/metrics-management/fluxcd-metrics/',
-	},
-	{
-		dataSource: 'planetscale',
-		label: 'PlanetScale',
-		imgUrl: planetscaleUrl,
-		tags: ['database'],
-		module: 'apm',
-		relatedSearchKeywords: [
-			'database',
-			'monitoring',
-			'mysql',
-			'observability',
-			'opentelemetry planetscale',
-			'planetscale',
-			'planetscale database',
-			'planetscale metrics',
-			'planetscale monitoring',
-			'planetscale observability',
-			'serverless database',
-		],
-		id: 'planetscale',
-		link: '/docs/metrics-management/opentelemetry-planetscale/',
-	},
-	{
-		dataSource: 'hermes-agent',
-		label: 'Hermes Agent',
-		imgUrl: llmMonitoringUrl,
-		tags: ['LLM Monitoring'],
-		module: 'apm',
-		relatedSearchKeywords: [
-			'ai agent monitoring',
-			'hermes',
-			'hermes agent',
-			'hermes agent monitoring',
-			'hermes agent observability',
-			'hermes monitoring',
-			'llm monitoring',
-			'monitoring',
-			'nous research',
-			'observability',
-			'opentelemetry hermes',
-		],
-		id: 'hermes-agent',
-		link: '/docs/hermes-monitoring/',
-	},
 	{
 		dataSource: 'convex-logs',
 		label: 'Convex Logs',
--- a/frontend/src/pages/AIAssistantPage/AIAssistantPage.tsx
+++ b/frontend/src/pages/AIAssistantPage/AIAssistantPage.tsx
@@ -26,8 +26,8 @@ export default function AIAssistantPage(): JSX.Element {

 	// Skip the mount-time Opened fire when the user expanded an already-open
 	// drawer/modal — that surface already emitted Opened with the right source.
-	// Router state (vs a module flag) survives page remounts and aborted
-	// navigations.
+	// Router state (vs a module flag) survives StrictMode double-mount and
+	// aborted navigations.
 	const fromInApp = location.state?.fromInApp === true;
 	useEffect(() => {
 		if (fromInApp) {
@@ -52,34 +52,18 @@ export default function AIAssistantPage(): JSX.Element {
 		(s) => s.startNewConversation,
 	);

-	// Keep refs so the effect can read the latest store state without re-firing
-	// when it mutates the store mid-effect (it only depends on the URL param).
+	// Keep a ref so the effect can read latest conversations without re-firing
+	// when startNewConversation mutates the store mid-effect.
 	const conversationsRef = useRef(conversations);
 	conversationsRef.current = conversations;
-	const activeConversationIdRef = useRef(activeConversationId);
-	activeConversationIdRef.current = activeConversationId;

 	useEffect(() => {
-		// URL points at a known conversation → just activate it.
-		if (conversationId && conversationsRef.current[conversationId]) {
+		if (conversationsRef.current[conversationId]) {
 			setActiveConversation(conversationId);
-			return;
+		} else {
+			const newId = startNewConversation();
+			history.replace(ROUTES.AI_ASSISTANT.replace(':conversationId', newId));
 		}
-
-		// The URL has no usable conversation id (bare `/ai-assistant`, or a stale
-		// param). Prefer resuming the active conversation — including the
-		// rehydrating placeholder for the persisted thread — over minting a new
-		// one. This is what stops a throwaway blank chat from flashing as a
-		// second thread during load, and stops a duplicate when the page
-		// remounts during startup route churn (the active id is already set, so
-		// we resume instead of create). Starting fresh is the last resort, only
-		// when there is genuinely nothing to resume.
-		const activeId = activeConversationIdRef.current;
-		const resumeId =
-			activeId && conversationsRef.current[activeId]
-				? activeId
-				: startNewConversation();
-		history.replace(ROUTES.AI_ASSISTANT.replace(':conversationId', resumeId));
 		// Only re-run when the URL param changes, not when conversations mutates.
 		// eslint-disable-next-line react-hooks/exhaustive-deps
 	}, [conversationId]);
--- a/frontend/src/pages/AIAssistantPage/tests/AIAssistantPage.test.tsx
+++ b/frontend/src/pages/AIAssistantPage/tests/AIAssistantPage.test.tsx
@@ -1,181 +0,0 @@
-import { MemoryRouter, Route } from 'react-router-dom';
-// eslint-disable-next-line no-restricted-imports
-import { render } from '@testing-library/react';
-import ROUTES from 'constants/routes';
-import { useAIAssistantStore } from 'container/AIAssistant/store/useAIAssistantStore';
-
-jest.mock('api/common/logEvent', () => ({
-	__esModule: true,
-	default: jest.fn(),
-}));
-
-jest.mock('container/AIAssistant/ConversationView', () => ({
-	__esModule: true,
-	default: (): JSX.Element => <div data-testid="conversation-view" />,
-}));
-
-jest.mock('container/AIAssistant/components/ConversationsList', () => ({
-	__esModule: true,
-	default: (): JSX.Element => <div data-testid="conversations-list" />,
-}));
-
-jest.mock('components/Noz/Noz', () => ({
-	__esModule: true,
-	default: (): JSX.Element => <div data-testid="noz" />,
-}));
-
-jest.mock('container/AIAssistant/hooks/useAIAssistantAnalyticsContext', () => ({
-	normalizePage: (page: string): string => page,
-	useAIAssistantAnalyticsContext: (): unknown => ({ mode: 'page' }),
-}));
-
-// eslint-disable-next-line import/first
-import AIAssistantPage from '../AIAssistantPage';
-
-function renderAt(entry: string): { unmount: () => void } {
-	return render(
-		<MemoryRouter initialEntries={[entry]}>
-			<Route
-				exact
-				path={[ROUTES.AI_ASSISTANT_BASE, ROUTES.AI_ASSISTANT]}
-				component={AIAssistantPage}
-			/>
-		</MemoryRouter>,
-	);
-}
-
-function renderAtBase(): { unmount: () => void } {
-	return renderAt(ROUTES.AI_ASSISTANT_BASE);
-}
-
-function conversationCount(): number {
-	return Object.keys(useAIAssistantStore.getState().conversations).length;
-}
-
-function conversationIds(): string[] {
-	return Object.keys(useAIAssistantStore.getState().conversations);
-}
-
-function activeId(): string | null {
-	return useAIAssistantStore.getState().activeConversationId;
-}
-
-describe('AIAssistantPage', () => {
-	beforeEach(() => {
-		useAIAssistantStore.setState({
-			conversations: {},
-			streams: {},
-			activeConversationId: null,
-		});
-	});
-
-	it('opens exactly one conversation when navigating to /ai-assistant', () => {
-		const { unmount } = renderAtBase();
-
-		expect(conversationCount()).toBe(1);
-
-		unmount();
-	});
-
-	it('does not stack a second conversation when the page remounts at the bare URL (route churn)', () => {
-		// First mount at `/ai-assistant` creates one blank conversation and
-		// redirects to `/ai-assistant/:id`.
-		const { unmount } = renderAtBase();
-		expect(conversationCount()).toBe(1);
-		const firstId = conversationIds()[0];
-
-		// Startup route-list churn unmounts and remounts the page while the URL
-		// is momentarily back at the bare `/ai-assistant`. This previously
-		// created a second blank conversation — now it reuses the first.
-		unmount();
-		const { unmount: unmount2 } = renderAtBase();
-
-		expect(conversationCount()).toBe(1);
-		// The surviving conversation is the original one, resumed — not a fresh mint.
-		expect(conversationIds()).toStrictEqual([firstId]);
-		expect(activeId()).toBe(firstId);
-
-		unmount2();
-	});
-
-	it('activates the conversation named in the URL without creating a new one', () => {
-		useAIAssistantStore.setState({
-			conversations: {
-				existing: {
-					id: 'existing',
-					messages: [],
-					createdAt: 1,
-					updatedAt: 1,
-				},
-			},
-			streams: {},
-			activeConversationId: null,
-		});
-
-		const { unmount } = renderAt(
-			ROUTES.AI_ASSISTANT.replace(':conversationId', 'existing'),
-		);
-
-		expect(conversationCount()).toBe(1);
-		expect(activeId()).toBe('existing');
-
-		unmount();
-	});
-
-	it('resumes the active conversation on /ai-assistant/new instead of minting a new one', () => {
-		// The sidenav only routes to `/ai-assistant/new` as a fallback, but if an
-		// active conversation exists the page must resume it rather than spawn a
-		// throwaway blank thread for the unknown "new" param.
-		useAIAssistantStore.setState({
-			conversations: {
-				active: {
-					id: 'active',
-					messages: [],
-					createdAt: 1,
-					updatedAt: 1,
-				},
-			},
-			streams: {},
-			activeConversationId: 'active',
-		});
-
-		const { unmount } = renderAt(
-			ROUTES.AI_ASSISTANT.replace(':conversationId', 'new'),
-		);
-
-		expect(conversationCount()).toBe(1);
-		expect(conversationIds()).toStrictEqual(['active']);
-		expect(activeId()).toBe('active');
-
-		unmount();
-	});
-
-	it('resumes the persisted (hydrating) conversation during load instead of creating a second', () => {
-		// Simulates `onRehydrateStorage` priming the persisted active
-		// conversation as a hydrating placeholder before `fetchThreads` resolves.
-		useAIAssistantStore.setState({
-			conversations: {
-				persisted: {
-					id: 'persisted',
-					messages: [],
-					createdAt: 1,
-					updatedAt: 1,
-					isHydrating: true,
-				},
-			},
-			streams: {},
-			activeConversationId: 'persisted',
-		});
-
-		const { unmount } = renderAtBase();
-
-		// Opening the bare URL must resume the persisted conversation, not mint a
-		// throwaway blank alongside it (which flashed as a 2nd thread during load).
-		expect(conversationCount()).toBe(1);
-		expect(
-			Object.keys(useAIAssistantStore.getState().conversations),
-		).toStrictEqual(['persisted']);
-
-		unmount();
-	});
-});
--- a/pkg/modules/llmpricingrule/impllmpricingrule/module.go
+++ b/pkg/modules/llmpricingrule/impllmpricingrule/module.go
@@ -29,7 +29,7 @@ type module struct {
 }

 func NewModule(store llmpricingruletypes.Store, flagger flagger.Flagger, querier querier.Querier) llmpricingrule.Module {
-	return &module{store: store, flagger: flagger, querier: querier}
+	return &module{store: store, flagger: flagger}
 }

 func (module *module) List(ctx context.Context, orgID valuer.UUID, offset, limit int, search string, isOverride *bool) ([]*llmpricingruletypes.LLMPricingRule, int, error) {
--- a/pkg/telemetrymetrics/reduced_test.go
+++ b/pkg/telemetrymetrics/reduced_test.go
@@ -39,48 +39,48 @@ func TestReducedStatementBuilder(t *testing.T) {
 			name:  "gauge_sum_latest",
 			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationLatest, metrictypes.SpaceAggregationSum),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, anyLast(last) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, argMax(value, unix_milli) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, anyLast(last) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, argMax(value, unix_milli) AS per_series_value FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`sum_last`, points.computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), false, "test.metric", uint64(1746999900000), uint64(1747172760000)},
 			},
 		},
 		{
 			name:  "gauge_avg_avg",
 			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationAvg, metrictypes.SpaceAggregationAvg),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`sum_last`, points.computed_at) AS value, argMax(`count_series`, points.computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), false, "test.metric", uint64(1746999900000), uint64(1747172760000)},
 			},
 		},
 		{
 			name:  "gauge_min_min",
 			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationMin, metrictypes.SpaceAggregationMin),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(min) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(value) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`min`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(min) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, min(value) AS per_series_value FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`min`, points.computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, min(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), false, "test.metric", uint64(1746999900000), uint64(1747172760000)},
 			},
 		},
 		{
 			name:  "gauge_max_max",
 			query: reducedQuery("test.metric", metrictypes.GaugeType, metrictypes.Unspecified, metrictypes.TimeAggregationMax, metrictypes.SpaceAggregationMax),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(value) AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`max`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(value) AS per_series_value FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`max`, points.computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_last_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, max(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), false, "test.metric", uint64(1746999900000), uint64(1747172760000)},
 			},
 		},
 		{
 			name:  "counter_sum_rate",
 			query: reducedQuery("test.metric.sum", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationRate, metrictypes.SpaceAggregationSum),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) / 300 AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric.sum", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric.sum", uint64(1746999600000), uint64(1747172760000), 0, "test.metric.sum", uint64(1746999600000), uint64(1747172760000), "test.metric.sum", uint64(1746999600000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) / 300 AS per_series_value FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`sum`, points.computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric.sum", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric.sum", uint64(1746999600000), uint64(1747172760000), 0, "test.metric.sum", uint64(1746999600000), uint64(1747172760000), false, "test.metric.sum", uint64(1746999600000), uint64(1747172760000)},
 			},
 		},
 		{
 			name:  "counter_avg_increase",
 			query: reducedQuery("test.metric", metrictypes.SumType, metrictypes.Cumulative, metrictypes.TimeAggregationIncrease, metrictypes.SpaceAggregationAvg),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0, "test.metric", uint64(1746999600000), uint64(1747172760000), "test.metric", uint64(1746999600000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value, per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`sum`, points.computed_at) AS value, argMax(`count_series`, points.computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric", uint64(1746999600000), uint64(1747172760000), 0, "test.metric", uint64(1746999600000), uint64(1747172760000), false, "test.metric", uint64(1746999600000), uint64(1747172760000)},
 			},
 		},
 		{
@@ -103,16 +103,16 @@ func TestReducedStatementBuilder(t *testing.T) {
 			name:  "histogram_p99",
 			query: reducedQuery("test.metric.bucket", metrictypes.HistogramType, metrictypes.Cumulative, metrictypes.TimeAggregationUnspecified, metrictypes.SpaceAggregationPercentile99),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, `le`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, sum(value) / 300 AS per_series_value FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum`, computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts, `le`), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric.bucket", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric.bucket", uint64(1746999900000), uint64(1747172760000), 0, "test.metric.bucket", uint64(1746999900000), uint64(1747172760000), "test.metric.bucket", uint64(1746999900000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT ts, `le`, multiIf(row_number() OVER rate_window = 1, nan, (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1) OVER rate_window) / (ts - lagInFrame(ts, 1) OVER rate_window)) AS per_series_value FROM (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, max(max) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts, `le` ORDER BY fingerprint, ts) WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint, ts)), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, `le`, sum(value) / 300 AS per_series_value FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, `le`, argMax(`sum`, points.computed_at) AS value FROM signoz_metrics.distributed_samples_v4_reduced_sum_60s AS points INNER JOIN (SELECT fingerprint, JSONExtractString(labels, 'le') AS `le` FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint, `le`) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli, `le`) GROUP BY fingerprint, ts, `le`), __spatial_aggregation_cte AS (SELECT ts, `le`, sum(per_series_value) AS value FROM __temporal_aggregation_cte GROUP BY ts, `le`) SELECT ts, histogramQuantile(arrayMap(x -> toFloat64(x), groupArray(le)), groupArray(value), 0.990) AS value FROM __spatial_aggregation_cte GROUP BY ts ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric.bucket", uint64(1746921600000), uint64(1747172760000), "cumulative", false, "test.metric.bucket", uint64(1746999900000), uint64(1747172760000), 0, "test.metric.bucket", uint64(1746999900000), uint64(1747172760000), false, "test.metric.bucket", uint64(1746999900000), uint64(1747172760000)},
 			},
 		},
 		{
 			name:  "summary_avg",
 			query: reducedQuery("test.metric", metrictypes.SummaryType, metrictypes.Unspecified, metrictypes.TimeAggregationAvg, metrictypes.SpaceAggregationAvg),
 			expected: qbtypes.Statement{
-				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT reduced_fingerprint AS fingerprint, unix_milli, argMax(`sum_last`, computed_at) AS value, argMax(`count_series`, computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY reduced_fingerprint, unix_milli) AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
-				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), "test.metric", uint64(1746999900000), uint64(1747172760000), false},
+				Query: "SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, sum(sum) / sum(count) AS per_series_value FROM signoz_metrics.distributed_samples_v4_agg_5m AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_1day WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND LOWER(temporality) LIKE LOWER(?) AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, ts ORDER BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, avg(per_series_value) AS value FROM __temporal_aggregation_cte WHERE isNaN(per_series_value) = ? GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) UNION ALL SELECT * FROM (WITH __temporal_aggregation_cte AS (SELECT fingerprint, toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(300)) AS ts, avg(value) AS per_series_value, avg(weight) AS per_series_weight FROM (SELECT points.reduced_fingerprint AS fingerprint, points.unix_milli AS unix_milli, argMax(`sum_last`, points.computed_at) AS value, argMax(`count_series`, points.computed_at) AS weight FROM signoz_metrics.distributed_samples_v4_reduced_last_60s AS points INNER JOIN (SELECT fingerprint FROM signoz_metrics.time_series_v4_reduced WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli <= ? AND __normalized = ? GROUP BY fingerprint) AS filtered_time_series ON points.reduced_fingerprint = filtered_time_series.fingerprint WHERE metric_name IN (?) AND unix_milli >= ? AND unix_milli < ? GROUP BY fingerprint, unix_milli) GROUP BY fingerprint, ts), __spatial_aggregation_cte AS (SELECT ts, sum(per_series_value) / sum(per_series_weight) AS value FROM __temporal_aggregation_cte GROUP BY ts) SELECT * FROM __spatial_aggregation_cte ORDER BY ts) ORDER BY ts",
+				Args:  []any{"test.metric", uint64(1746921600000), uint64(1747172760000), "unspecified", false, "test.metric", uint64(1746999900000), uint64(1747172760000), 0, "test.metric", uint64(1746999900000), uint64(1747172760000), false, "test.metric", uint64(1746999900000), uint64(1747172760000)},
 			},
 		},
 	}
--- a/pkg/telemetrymetrics/statement_builder.go
+++ b/pkg/telemetrymetrics/statement_builder.go
@@ -338,19 +338,24 @@ func (b *MetricQueryStatementBuilder) buildReducedTemporalAggregationCTE(

 	// dedup recomputed buckets: latest computed_at wins per (series, 60s bucket)
 	dedup := sqlbuilder.NewSelectBuilder()
-	dedup.Select("reduced_fingerprint AS fingerprint", "unix_milli")
-	dedup.SelectMore(fmt.Sprintf("argMax(%s, computed_at) AS value", value))
-	if weight != "" {
-		dedup.SelectMore(fmt.Sprintf("argMax(%s, computed_at) AS weight", weight))
+	dedup.Select("points.reduced_fingerprint AS fingerprint", "points.unix_milli AS unix_milli")
+	for _, g := range query.GroupBy {
+		dedup.SelectMore(fmt.Sprintf("`%s`", g.Name))
 	}
-	dedup.From(fmt.Sprintf("%s.%s", DBName, WhichReducedSamplesTableToUse(agg.Type)))
+	dedup.SelectMore(fmt.Sprintf("argMax(%s, points.computed_at) AS value", value))
+	if weight != "" {
+		dedup.SelectMore(fmt.Sprintf("argMax(%s, points.computed_at) AS weight", weight))
+	}
+	dedup.From(fmt.Sprintf("%s.%s AS points", DBName, WhichReducedSamplesTableToUse(agg.Type)))
+	dedup.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.reduced_fingerprint = filtered_time_series.fingerprint")
 	dedup.Where(
 		dedup.In("metric_name", agg.MetricName),
 		dedup.GTE("unix_milli", start),
 		dedup.LT("unix_milli", end),
 	)
-	dedup.GroupBy("reduced_fingerprint", "unix_milli")
-	dedupQuery, dedupArgs := dedup.BuildWithFlavor(sqlbuilder.ClickHouse)
+	dedup.GroupBy("fingerprint", "unix_milli")
+	dedup.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+	dedupQuery, dedupArgs := dedup.BuildWithFlavor(sqlbuilder.ClickHouse, timeSeriesCTEArgs...)

 	sb := sqlbuilder.NewSelectBuilder()
 	sb.Select("fingerprint")
@@ -364,13 +369,11 @@ func (b *MetricQueryStatementBuilder) buildReducedTemporalAggregationCTE(
 		// denominator is reduced with avg
 		sb.SelectMore("avg(weight) AS per_series_weight")
 	}
-	sb.From(fmt.Sprintf("(%s) AS points", dedupQuery))
-	sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
+	sb.From(fmt.Sprintf("(%s)", dedupQuery))
 	sb.GroupBy("fingerprint", "ts")
 	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)

-	initArgs := append(append([]any{}, dedupArgs...), timeSeriesCTEArgs...)
-	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, initArgs...)
+	q, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, dedupArgs...)
 	return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", q), args, true
 }

--- a/tests/fixtures/clickhouse.py
+++ b/tests/fixtures/clickhouse.py
@@ -2,6 +2,7 @@ import os
 from collections.abc import Callable, Generator
 from datetime import datetime
 from typing import Any
+from uuid import uuid4

 import clickhouse_connect
 import clickhouse_connect.driver
@@ -10,37 +11,93 @@ import docker
 import docker.errors
 import pytest
 from testcontainers.clickhouse import ClickHouseContainer
-from testcontainers.core.container import Network
+from testcontainers.core.container import DockerContainer, Network

 from fixtures import reuse, types
 from fixtures.logger import setup_logger

 logger = setup_logger(__name__)

+CLICKHOUSE_USERNAME = "signoz"
+CLICKHOUSE_PASSWORD = "password"

-@pytest.fixture(name="clickhouse", scope="package")
-def clickhouse(
-    tmpfs: Generator[types.LegacyPath, Any],
-    network: Network,
-    zookeeper: types.TestContainerDocker,
-    request: pytest.FixtureRequest,
-    pytestconfig: pytest.Config,
-) -> types.TestContainerClickhouse:
-    """
-    Package-scoped fixture for Clickhouse TestContainer.
+CUSTOM_FUNCTION_CONFIG = """
+<functions>
+    <function>
+        <type>executable</type>
+        <name>histogramQuantile</name>
+        <return_type>Float64</return_type>
+        <argument>
+            <type>Array(Float64)</type>
+            <name>buckets</name>
+        </argument>
+        <argument>
+            <type>Array(Float64)</type>
+            <name>counts</name>
+        </argument>
+        <argument>
+            <type>Float64</type>
+            <name>quantile</name>
+        </argument>
+        <format>CSV</format>
+        <command>./histogramQuantile</command>
+    </function>
+</functions>
+"""
+
+# Distributed inserts to a remote shard are async by default. We force
+# sycn at the profile level for deterministic tests.
+CLUSTER_USERS_CONFIG = """
+<clickhouse>
+    <profiles>
+        <default>
+            <insert_distributed_sync>1</insert_distributed_sync>
+        </default>
+    </profiles>
+</clickhouse>
+"""
+
+
+def render_remote_servers(shard_hosts: list[tuple[str, int]], secret: str | None = None) -> str:
+    """Render the <remote_servers> block for a cluster named `cluster` with one
+    single-replica shard per (host, port).
    """
+    shards = "".join(
+        f"""
+                <shard>
+                    <replica>
+                        <host>{host}</host>
+                        <port>{port}</port>
+                    </replica>
+                </shard>"""
+        for host, port in shard_hosts
+    )

-    def create() -> types.TestContainerClickhouse:
-        version = request.config.getoption("--clickhouse-version")
+    # Multi-node clusters need `secret` because distributed queries otherwise
+    # authenticate as the `default` user, which the docker entrypoint restricts
+    # to localhost when a custom user is configured.
+    secret_block = (
+        f"""
+                    <secret>{secret}</secret>"""
+        if secret
+        else ""
+    )

-        container = ClickHouseContainer(
-            image=f"clickhouse/clickhouse-server:{version}",
-            port=9000,
-            username="signoz",
-            password="password",
-        )
+    return f"""
+            <remote_servers>
+                <cluster>{secret_block}{shards}
+                </cluster>
+            </remote_servers>"""

-        cluster_config = f"""
+
+def render_node_config(
+    zookeeper_address: str,
+    zookeeper_port: int,
+    shard: str,
+    remote_servers: str,
+    distributed_ddl_path: str = "/clickhouse/task_queue/ddl",
+) -> str:
+    return f"""
        <clickhouse>
            <logger>
                <level>information</level>
@@ -55,33 +112,23 @@ def clickhouse(
            </logger>

            <macros>
-                <shard>01</shard>
+                <shard>{shard}</shard>
                <replica>01</replica>
            </macros>

            <zookeeper>
                <node>
-                    <host>{zookeeper.container_configs["2181"].address}</host>
-                    <port>{zookeeper.container_configs["2181"].port}</port>
+                    <host>{zookeeper_address}</host>
+                    <port>{zookeeper_port}</port>
                </node>
            </zookeeper>
-
-            <remote_servers>
-                <cluster>
-                    <shard>
-                        <replica>
-                            <host>127.0.0.1</host>
-                            <port>9000</port>
-                        </replica>
-                    </shard>
-                </cluster>
-            </remote_servers>
+{remote_servers}

            <user_defined_executable_functions_config>*function.xml</user_defined_executable_functions_config>
            <user_scripts_path>/var/lib/clickhouse/user_scripts/</user_scripts_path>

            <distributed_ddl>
-                <path>/clickhouse/task_queue/ddl</path>
+                <path>{distributed_ddl_path}</path>
                <profile>default</profile>
            </distributed_ddl>

@@ -122,38 +169,66 @@ def clickhouse(
        </clickhouse>
        """

-        custom_function_config = """
-        <functions>
-            <function>
-                <type>executable</type>
-                <name>histogramQuantile</name>
-                <return_type>Float64</return_type>
-                <argument>
-                    <type>Array(Float64)</type>
-                    <name>buckets</name>
-                </argument>
-                <argument>
-                    <type>Array(Float64)</type>
-                    <name>counts</name>
-                </argument>
-                <argument>
-                    <type>Float64</type>
-                    <name>quantile</name>
-                </argument>
-                <format>CSV</format>
-                <command>./histogramQuantile</command>
-            </function>
-        </functions>
-        """

-        tmp_dir = tmpfs("clickhouse")
+def install_histogram_quantile(container: ClickHouseContainer) -> None:
+    wrapped = container.get_wrapped_container()
+    exit_code, output = wrapped.exec_run(
+        [
+            "bash",
+            "-c",
+            (
+                'version="v0.0.1" && '
+                'node_os=$(uname -s | tr "[:upper:]" "[:lower:]") && '
+                "node_arch=$(uname -m | sed s/aarch64/arm64/ | sed s/x86_64/amd64/) && "
+                "cd /tmp && "
+                'wget -O histogram-quantile.tar.gz "https://github.com/SigNoz/signoz/releases/download/histogram-quantile%2F${version}/histogram-quantile_${node_os}_${node_arch}.tar.gz" && '
+                "tar -xzf histogram-quantile.tar.gz && "
+                "mkdir -p /var/lib/clickhouse/user_scripts && "
+                "mv histogram-quantile /var/lib/clickhouse/user_scripts/histogramQuantile && "
+                "chmod +x /var/lib/clickhouse/user_scripts/histogramQuantile"
+            ),
+        ],
+    )
+    if exit_code != 0:
+        raise RuntimeError(f"Failed to install histogramQuantile binary: {output.decode()}")
+
+
+def create_clickhouse(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    keeper: types.TestContainerDocker,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+    cache_key: str = "clickhouse",
+    version: str | None = None,
+) -> types.TestContainerClickhouse:
+    coordinator = next(iter(keeper.container_configs.values()))
+
+    def create() -> types.TestContainerClickhouse:
+        clickhouse_version = version or request.config.getoption("--clickhouse-version")
+
+        container = ClickHouseContainer(
+            image=f"clickhouse/clickhouse-server:{clickhouse_version}",
+            port=9000,
+            username=CLICKHOUSE_USERNAME,
+            password=CLICKHOUSE_PASSWORD,
+        )
+
+        cluster_config = render_node_config(
+            zookeeper_address=coordinator.address,
+            zookeeper_port=coordinator.port,
+            shard="01",
+            remote_servers=render_remote_servers([("127.0.0.1", 9000)]),
+        )
+
+        tmp_dir = tmpfs(cache_key)
        cluster_config_file_path = os.path.join(tmp_dir, "cluster.xml")
        with open(cluster_config_file_path, "w", encoding="utf-8") as f:
            f.write(cluster_config)

        custom_function_file_path = os.path.join(tmp_dir, "custom-function.xml")
        with open(custom_function_file_path, "w", encoding="utf-8") as f:
-            f.write(custom_function_config)
+            f.write(CUSTOM_FUNCTION_CONFIG)

        container.with_volume_mapping(cluster_config_file_path, "/etc/clickhouse-server/config.d/cluster.xml")
        container.with_volume_mapping(
@@ -163,27 +238,7 @@ def clickhouse(
        container.with_network(network)
        container.start()

-        # Download and install the histogramQuantile binary
-        wrapped = container.get_wrapped_container()
-        exit_code, output = wrapped.exec_run(
-            [
-                "bash",
-                "-c",
-                (
-                    'version="v0.0.1" && '
-                    'node_os=$(uname -s | tr "[:upper:]" "[:lower:]") && '
-                    "node_arch=$(uname -m | sed s/aarch64/arm64/ | sed s/x86_64/amd64/) && "
-                    "cd /tmp && "
-                    'wget -O histogram-quantile.tar.gz "https://github.com/SigNoz/signoz/releases/download/histogram-quantile%2F${version}/histogram-quantile_${node_os}_${node_arch}.tar.gz" && '
-                    "tar -xzf histogram-quantile.tar.gz && "
-                    "mkdir -p /var/lib/clickhouse/user_scripts && "
-                    "mv histogram-quantile /var/lib/clickhouse/user_scripts/histogramQuantile && "
-                    "chmod +x /var/lib/clickhouse/user_scripts/histogramQuantile"
-                ),
-            ],
-        )
-        if exit_code != 0:
-            raise RuntimeError(f"Failed to install histogramQuantile binary: {output.decode()}")
+        install_histogram_quantile(container)

        connection = clickhouse_connect.get_client(
            user=container.username,
@@ -253,7 +308,7 @@ def clickhouse(
    return reuse.wrap(
        request,
        pytestconfig,
-        "clickhouse",
+        cache_key,
        empty=lambda: types.TestContainerSQL(
            container=types.TestContainerDocker(id="", host_configs={}, container_configs={}),
            conn=None,
@@ -265,6 +320,334 @@ def clickhouse(
    )


+@pytest.fixture(name="clickhouse", scope="package")
+def clickhouse(
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    zookeeper: types.TestContainerDocker,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerClickhouse:
+    """
+    Package-scoped fixture for Clickhouse TestContainer.
+    """
+    return create_clickhouse(
+        tmpfs=tmpfs,
+        network=network,
+        keeper=zookeeper,
+        request=request,
+        pytestconfig=pytestconfig,
+    )
+
+
+def local_series_counts(
+    node_conns: list[clickhouse_connect.driver.client.Client],
+    table: str,
+    metric_name: str,
+) -> list[int]:
+    """Distinct series per node via the LOCAL (non-distributed) table."""
+    return [
+        int(
+            conn.query(
+                f"SELECT count(DISTINCT fingerprint) FROM signoz_metrics.{table} WHERE metric_name = %(metric_name)s",
+                parameters={"metric_name": metric_name},
+            ).result_rows[0][0]
+        )
+        for conn in node_conns
+    ]
+
+
+def assert_spans_shards(
+    node_conns: list[clickhouse_connect.driver.client.Client],
+    table: str,
+    metric_name: str,
+    total: int,
+) -> None:
+    """Guard for distributed tests: a green run on a cluster proves nothing
+    unless the seeded series actually landed on more than one shard."""
+    counts = local_series_counts(node_conns, table, metric_name)
+    assert sum(counts) == total, f"expected {total} series in {table} across shards, got {counts}"
+    assert min(counts) > 0, f"seeded series in {table} all landed on one shard: {counts}"
+
+
+@pytest.fixture(name="clickhouse_node_conns", scope="function")
+def clickhouse_node_conns(
+    clickhouse: types.TestContainerClickhouse,
+) -> Generator[list[clickhouse_connect.driver.client.Client], Any]:
+    """Per-node clients (index 0 = the initiator) for asserting shard-local
+    state via the local, non-distributed tables. Empty for single-node
+    fixtures, which don't populate `nodes`."""
+    conns = [
+        clickhouse_connect.get_client(
+            user=clickhouse.env["SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_USERNAME"],
+            password=clickhouse.env["SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_PASSWORD"],
+            host=node.host_configs["8123"].address,
+            port=node.host_configs["8123"].port,
+        )
+        for node in clickhouse.nodes
+    ]
+    yield conns
+    for conn in conns:
+        conn.close()
+
+
+KEEPER_CONFIG = """
+<clickhouse>
+    <listen_host>0.0.0.0</listen_host>
+    <keeper_server>
+        <tcp_port>9181</tcp_port>
+        <server_id>1</server_id>
+        <log_storage_path>/var/lib/clickhouse-keeper/coordination/log</log_storage_path>
+        <snapshot_storage_path>/var/lib/clickhouse-keeper/coordination/snapshots</snapshot_storage_path>
+        <coordination_settings>
+            <operation_timeout_ms>10000</operation_timeout_ms>
+            <session_timeout_ms>30000</session_timeout_ms>
+            <raft_logs_level>warning</raft_logs_level>
+        </coordination_settings>
+        <raft_configuration>
+            <server>
+                <id>1</id>
+                <hostname>localhost</hostname>
+                <port>9234</port>
+            </server>
+        </raft_configuration>
+    </keeper_server>
+</clickhouse>
+"""
+
+
+def create_clickhouse_keeper(
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+    cache_key: str = "clickhousekeeper",
+    version: str | None = None,
+) -> types.TestContainerDocker:
+
+    def create() -> types.TestContainerDocker:
+        keeper_version = version or request.config.getoption("--clickhouse-version")
+
+        tmp_dir = tmpfs(cache_key)
+        keeper_config_file_path = os.path.join(tmp_dir, "keeper_config.xml")
+        with open(keeper_config_file_path, "w", encoding="utf-8") as f:
+            f.write(KEEPER_CONFIG)
+
+        container = DockerContainer(image=f"clickhouse/clickhouse-keeper:{keeper_version}")
+        container.with_volume_mapping(keeper_config_file_path, "/etc/clickhouse-keeper/keeper_config.xml")
+        container.with_exposed_ports(9181)
+        container.with_network(network=network)
+
+        container.start()
+        return types.TestContainerDocker(
+            id=container.get_wrapped_container().id,
+            host_configs={
+                "9181": types.TestContainerUrlConfig(
+                    scheme="tcp",
+                    address=container.get_container_host_ip(),
+                    port=container.get_exposed_port(9181),
+                )
+            },
+            container_configs={
+                "9181": types.TestContainerUrlConfig(
+                    scheme="tcp",
+                    address=container.get_wrapped_container().name,
+                    port=9181,
+                )
+            },
+        )
+
+    def delete(container: types.TestContainerDocker):
+        client = docker.from_env()
+        try:
+            client.containers.get(container_id=container.id).stop()
+            client.containers.get(container_id=container.id).remove(v=True)
+        except docker.errors.NotFound:
+            logger.info(
+                "Skipping removal of ClickHouse Keeper, Keeper(%s) not found. Maybe it was manually removed?",
+                {"id": container.id},
+            )
+
+    def restore(cache: dict) -> types.TestContainerDocker:
+        return types.TestContainerDocker.from_cache(cache)
+
+    return reuse.wrap(
+        request,
+        pytestconfig,
+        cache_key,
+        lambda: types.TestContainerDocker(id="", host_configs={}, container_configs={}),
+        create,
+        delete,
+        restore,
+    )
+
+
+def create_clickhouse_cluster(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    keeper: types.TestContainerDocker,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+    cache_key: str = "clickhouse_cluster",
+    shards: int = 2,
+    version: str | None = None,
+) -> types.TestContainerClickhouse:
+    """
+    To some extent, taken inspiration from how ClickHouse's own integration
+    harness composes real clusters: deterministic hostnames
+    (network aliases), per-node shard macros, and a shared cluster definition
+    named `cluster`.
+
+    `conn`/`env` point at node 1 i.e the initiator every query-service query and
+    migration goes through. Per-node containers are exposed via `nodes` so
+    tests can assert shard-local state. `keeper` is any coordination service
+    (ZooKeeper or ClickHouse Keeper).
+    """
+    coordinator = next(iter(keeper.container_configs.values()))
+
+    def create() -> types.TestContainerClickhouse:
+        clickhouse_version = version or request.config.getoption("--clickhouse-version")
+
+        # Unique aliases per creation: docker allows duplicate network aliases
+        # (DNS round-robin), so a stale cluster must never share names with a
+        # fresh one.
+        suffix = uuid4().hex[:6]
+        aliases = [f"signoz-ch-{suffix}-{i:02d}" for i in range(1, shards + 1)]
+        remote_servers = render_remote_servers([(alias, 9000) for alias in aliases], secret=cache_key)
+        # Own DDL queue path: the keeper instance may be shared with other
+        # environments under --reuse; its DDL queue stays separate.
+        distributed_ddl_path = f"/clickhouse/{cache_key}-{suffix}/task_queue/ddl"
+
+        nodes: list[types.TestContainerDocker] = []
+        started: list[ClickHouseContainer] = []
+        try:
+            for i, alias in enumerate(aliases, start=1):
+                node_config = render_node_config(
+                    zookeeper_address=coordinator.address,
+                    zookeeper_port=coordinator.port,
+                    shard=f"{i:02d}",
+                    remote_servers=remote_servers,
+                    distributed_ddl_path=distributed_ddl_path,
+                )
+
+                tmp_dir = tmpfs(f"clickhouse-{suffix}-{i:02d}")
+                cluster_config_file_path = os.path.join(tmp_dir, "cluster.xml")
+                with open(cluster_config_file_path, "w", encoding="utf-8") as f:
+                    f.write(node_config)
+                custom_function_file_path = os.path.join(tmp_dir, "custom-function.xml")
+                with open(custom_function_file_path, "w", encoding="utf-8") as f:
+                    f.write(CUSTOM_FUNCTION_CONFIG)
+                users_config_file_path = os.path.join(tmp_dir, "users.xml")
+                with open(users_config_file_path, "w", encoding="utf-8") as f:
+                    f.write(CLUSTER_USERS_CONFIG)
+
+                container = ClickHouseContainer(
+                    image=f"clickhouse/clickhouse-server:{clickhouse_version}",
+                    port=9000,
+                    username=CLICKHOUSE_USERNAME,
+                    password=CLICKHOUSE_PASSWORD,
+                )
+                container.with_volume_mapping(cluster_config_file_path, "/etc/clickhouse-server/config.d/cluster.xml")
+                container.with_volume_mapping(custom_function_file_path, "/etc/clickhouse-server/custom-function.xml")
+                container.with_volume_mapping(users_config_file_path, "/etc/clickhouse-server/users.d/integration-cluster.xml")
+                container.with_network(network)
+                container.with_network_aliases(alias)
+                container.start()
+                started.append(container)
+
+                install_histogram_quantile(container)
+
+                nodes.append(
+                    types.TestContainerDocker(
+                        id=container.get_wrapped_container().id,
+                        host_configs={
+                            "9000": types.TestContainerUrlConfig(
+                                "tcp",
+                                container.get_container_host_ip(),
+                                container.get_exposed_port(9000),
+                            ),
+                            "8123": types.TestContainerUrlConfig(
+                                "tcp",
+                                container.get_container_host_ip(),
+                                container.get_exposed_port(8123),
+                            ),
+                        },
+                        container_configs={
+                            "9000": types.TestContainerUrlConfig("tcp", alias, 9000),
+                            "8123": types.TestContainerUrlConfig("tcp", alias, 8123),
+                        },
+                    )
+                )
+        except Exception:
+            for container in started:
+                container.stop()
+            raise
+
+        connection = clickhouse_connect.get_client(
+            user=CLICKHOUSE_USERNAME,
+            password=CLICKHOUSE_PASSWORD,
+            host=nodes[0].host_configs["8123"].address,
+            port=nodes[0].host_configs["8123"].port,
+        )
+
+        return types.TestContainerClickhouse(
+            container=nodes[0],
+            conn=connection,
+            env={
+                "SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_DSN": f"tcp://{CLICKHOUSE_USERNAME}:{CLICKHOUSE_PASSWORD}@{aliases[0]}:{9000}",
+                "SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_USERNAME": CLICKHOUSE_USERNAME,
+                "SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_PASSWORD": CLICKHOUSE_PASSWORD,
+                "SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_CLUSTER": "cluster",
+            },
+            nodes=nodes,
+        )
+
+    def delete(resource: types.TestContainerClickhouse) -> None:
+        client = docker.from_env()
+        for node in resource.nodes or [resource.container]:
+            try:
+                client.containers.get(container_id=node.id).stop()
+                client.containers.get(container_id=node.id).remove(v=True)
+            except docker.errors.NotFound:
+                logger.info(
+                    "Skipping removal of Clickhouse cluster node, node(%s) not found. Maybe it was manually removed?",
+                    {"id": node.id},
+                )
+
+    def restore(cache: dict) -> types.TestContainerClickhouse:
+        nodes = [types.TestContainerDocker.from_cache(node) for node in cache["nodes"]]
+        env = cache["env"]
+        host_config = nodes[0].host_configs["8123"]
+
+        conn = clickhouse_connect.get_client(
+            user=env["SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_USERNAME"],
+            password=env["SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_PASSWORD"],
+            host=host_config.address,
+            port=host_config.port,
+        )
+
+        return types.TestContainerClickhouse(
+            container=nodes[0],
+            conn=conn,
+            env=env,
+            nodes=nodes,
+        )
+
+    return reuse.wrap(
+        request,
+        pytestconfig,
+        cache_key,
+        empty=lambda: types.TestContainerClickhouse(
+            container=types.TestContainerDocker(id="", host_configs={}, container_configs={}),
+            conn=None,
+            env={},
+        ),
+        create=create,
+        delete=delete,
+        restore=restore,
+    )
+
+
@pytest.fixture(name="check_query_log")
 def check_query_log(
    signoz: types.SigNoz,
--- a/tests/fixtures/http.py
+++ b/tests/fixtures/http.py
@@ -18,19 +18,22 @@ from fixtures.logger import setup_logger
 logger = setup_logger(__name__)


-@pytest.fixture(name="zeus", scope="package")
-def zeus(
+ZEUS_NETWORK_ALIAS = "signoz-zeus-it"
+
+
+def create_zeus(
    network: Network,
    request: pytest.FixtureRequest,
    pytestconfig: pytest.Config,
+    cache_key: str = "zeus",
+    alias: str | None = None,
 ) -> types.TestContainerDocker:
-    """
-    Package-scoped fixture for running zeus
-    """

    def create() -> types.TestContainerDocker:
        container = WireMockContainer(image="wiremock/wiremock:2.35.1-1", secure=False)
        container.with_network(network)
+        if alias:
+            container.with_network_aliases(alias)
        container.start()

        return types.TestContainerDocker(
@@ -42,7 +45,7 @@ def zeus(
                    container.get_exposed_port(8080),
                )
            },
-            container_configs={"8080": types.TestContainerUrlConfig("http", container.get_wrapped_container().name, 8080)},
+            container_configs={"8080": types.TestContainerUrlConfig("http", alias or container.get_wrapped_container().name, 8080)},
        )

    def delete(container: types.TestContainerDocker):
@@ -62,7 +65,7 @@ def zeus(
    return reuse.wrap(
        request,
        pytestconfig,
-        "zeus",
+        cache_key,
        lambda: types.TestContainerDocker(id="", host_configs={}, container_configs={}),
        create,
        delete,
@@ -70,6 +73,18 @@ def zeus(
    )


+@pytest.fixture(name="zeus", scope="package")
+def zeus(
+    network: Network,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerDocker:
+    """
+    Package-scoped fixture for running zeus
+    """
+    return create_zeus(network=network, request=request, pytestconfig=pytestconfig)
+
+
@pytest.fixture(name="gateway", scope="package")
 def gateway(
    network: Network,
--- a/tests/fixtures/metricreduction.py
+++ b/tests/fixtures/metricreduction.py
@@ -0,0 +1,51 @@
+import datetime
+from collections.abc import Sequence
+
+from fixtures.metrics import MetricsBufferSample, MetricsBufferTimeSeries
+
+
+def build_ruled_gauge_buffer(
+    metric_name: str,
+    base_epoch: int,
+    services: Sequence[str],
+    pods_per_service: int,
+    minutes: int,
+    value: float = 1.0,
+) -> tuple[list[MetricsBufferTimeSeries], list[MetricsBufferSample]]:
+    """Collector-shaped buffer rows for a gauge under a reduction rule that
+    keeps `service`: per raw series a raw series row (is_reduced=false, full
+    labels, reduced_fingerprint -> group) plus the group's reduced series row
+    (is_reduced=true, kept labels), and one raw sample per series per minute
+    carrying both fingerprints. Returns (time_series, samples) for
+    insert_buffer_metrics."""
+    reduced_series = {
+        service: MetricsBufferTimeSeries(
+            metric_name=metric_name,
+            labels={"service": service},
+            timestamp=datetime.datetime.fromtimestamp(base_epoch, tz=datetime.UTC),
+            is_reduced=True,
+        )
+        for service in services
+    }
+    raw_series = [
+        MetricsBufferTimeSeries(
+            metric_name=metric_name,
+            labels={"service": service, "pod": f"pod-{service}-{i}"},
+            timestamp=datetime.datetime.fromtimestamp(base_epoch, tz=datetime.UTC),
+            reduced_fingerprint=reduced_series[service].fingerprint,
+        )
+        for service in services
+        for i in range(pods_per_service)
+    ]
+    samples = [
+        MetricsBufferSample(
+            metric_name=metric_name,
+            fingerprint=ts.fingerprint,
+            timestamp=datetime.datetime.fromtimestamp(base_epoch + minute * 60, tz=datetime.UTC),
+            value=value,
+            reduced_fingerprint=ts.reduced_fingerprint,
+        )
+        for ts in raw_series
+        for minute in range(minutes)
+    ]
+    return raw_series + list(reduced_series.values()), samples
--- a/tests/fixtures/metrics.py
+++ b/tests/fixtures/metrics.py
@@ -11,6 +11,14 @@ import pytest
 from fixtures import types
 from fixtures.time import parse_timestamp

+_REDUCED_METRICS_TABLES_TO_TRUNCATE = [
+    "time_series_v4_reduced",
+    "samples_v4_reduced_last_60s",
+    "samples_v4_reduced_sum_60s",
+    "time_series_v4_buffer",
+    "samples_v4_buffer",
+]
+

 class MetricsTimeSeries(ABC):
    """Represents a row in the time_series_v4 table."""
@@ -414,6 +422,267 @@ class Metrics(ABC):
        return metrics


+class MetricsReducedTimeSeries(ABC):
+    """Represents a row in the time_series_v4_reduced table i.e what
+    the time_series_v4_reduced_mv materializes for a metric under a
+    reduction rule. One row per kept-label group. `fingerprint` holds the
+    reduced fingerprint and `labels` contains only the kept labels.
+
+    The fingerprint recipe (md5, like MetricsTimeSeries) does not match the
+    collector's real hash; it only needs to be consistent with the
+    reduced_fingerprint used in the reduced samples rows.
+    """
+
+    def __init__(  # pylint: disable=too-many-arguments
+        self,
+        metric_name: str,
+        kept_labels: dict[str, str],
+        timestamp: datetime.datetime,
+        temporality: str = "Unspecified",
+        description: str = "",
+        unit: str = "",
+        type_: str = "Gauge",
+        is_monotonic: bool = False,
+        env: str = "default",
+    ) -> None:
+        kept_labels = dict(kept_labels)
+        kept_labels["__name__"] = metric_name
+        self.env = env
+        # mirror time_series_v4_reduced_mv: monotonic cumulative counters are
+        # reduced as deltas
+        if temporality == "Cumulative" and is_monotonic:
+            temporality = "Delta"
+        self.temporality = temporality
+        self.metric_name = metric_name
+        self.description = description
+        self.unit = unit
+        self.type = type_
+        self.is_monotonic = is_monotonic
+        self.labels = json.dumps(kept_labels, separators=(",", ":"))
+        self.attrs = kept_labels
+        self.unix_milli = np.int64(int(timestamp.timestamp() * 1e3))
+        self.normalized = False
+
+        fingerprint_str = metric_name + self.labels
+        self.fingerprint = np.uint64(int(hashlib.md5(fingerprint_str.encode()).hexdigest()[:16], 16))
+
+    def to_row(self) -> list:
+        return [
+            self.env,
+            self.temporality,
+            self.metric_name,
+            self.description,
+            self.unit,
+            self.type,
+            self.is_monotonic,
+            self.fingerprint,
+            self.unix_milli,
+            self.labels,
+            self.attrs,
+            {},
+            {},
+            self.normalized,
+        ]
+
+
+class MetricsReducedSampleLast60s(ABC):
+    """Represents a row in the samples_v4_reduced_last_60s table. One 60s
+    bucket per reduced group, as the samples_v4_reduced_last_60s_mv refresh
+    would emit it (gauges and non-monotonic cumulative sums)."""
+
+    def __init__(  # pylint: disable=too-many-arguments
+        self,
+        metric_name: str,
+        reduced_fingerprint: np.uint64,
+        timestamp: datetime.datetime,
+        sum_last: float,
+        min_value: float,
+        max_value: float,
+        sum_values: float,
+        count_series: int,
+        count_samples: int,
+        temporality: str = "Unspecified",
+        env: str = "default",
+        computed_at: datetime.datetime | None = None,
+    ) -> None:
+        self.env = env
+        self.temporality = temporality
+        self.metric_name = metric_name
+        self.reduced_fingerprint = reduced_fingerprint
+        # buckets are 60s-aligned: intDiv(unix_milli, 60000) * 60000
+        self.unix_milli = np.int64((int(timestamp.timestamp() * 1e3) // 60000) * 60000)
+        self.sum_last = np.float64(sum_last)
+        self.min = np.float64(min_value)
+        self.max = np.float64(max_value)
+        self.sum_values = np.float64(sum_values)
+        self.count_series = np.uint64(count_series)
+        self.count_samples = np.uint64(count_samples)
+        # the refresh stamps now(); default to shortly after the bucket closes
+        if computed_at is None:
+            computed_at = datetime.datetime.fromtimestamp(int(self.unix_milli) / 1e3, tz=datetime.UTC) + datetime.timedelta(seconds=180)
+        self.computed_at = computed_at
+
+    def to_row(self) -> list:
+        return [
+            self.env,
+            self.temporality,
+            self.metric_name,
+            self.reduced_fingerprint,
+            self.unix_milli,
+            self.sum_last,
+            self.min,
+            self.max,
+            self.sum_values,
+            self.count_series,
+            self.count_samples,
+            self.computed_at,
+        ]
+
+
+class MetricsReducedSampleSum60s(ABC):
+    """Represents a row in the samples_v4_reduced_sum_60s table. One 60s
+    bucket per reduced group for delta counters and histograms."""
+
+    def __init__(  # pylint: disable=too-many-arguments
+        self,
+        metric_name: str,
+        reduced_fingerprint: np.uint64,
+        timestamp: datetime.datetime,
+        sum_value: float,
+        count_series: int,
+        count_samples: int,
+        temporality: str = "Delta",
+        env: str = "default",
+        computed_at: datetime.datetime | None = None,
+    ) -> None:
+        self.env = env
+        self.temporality = temporality
+        self.metric_name = metric_name
+        self.reduced_fingerprint = reduced_fingerprint
+        self.unix_milli = np.int64((int(timestamp.timestamp() * 1e3) // 60000) * 60000)
+        self.sum = np.float64(sum_value)
+        self.count_series = np.uint64(count_series)
+        self.count_samples = np.uint64(count_samples)
+        if computed_at is None:
+            computed_at = datetime.datetime.fromtimestamp(int(self.unix_milli) / 1e3, tz=datetime.UTC) + datetime.timedelta(seconds=180)
+        self.computed_at = computed_at
+
+    def to_row(self) -> list:
+        return [
+            self.env,
+            self.temporality,
+            self.metric_name,
+            self.reduced_fingerprint,
+            self.unix_milli,
+            self.sum,
+            self.count_series,
+            self.count_samples,
+            self.computed_at,
+        ]
+
+
+class MetricsBufferTimeSeries(ABC):
+    """Represents a row in the time_series_v4_buffer table. This is the collector's
+    universal landing target under cardinality control. For a ruled metric the
+    collector writes two rows per series: the raw one (is_reduced=false, full
+    labels, reduced_fingerprint pointing at its group) and the group's reduced
+    one (is_reduced=true, kept labels, fingerprint = reduced fingerprint)."""
+
+    def __init__(  # pylint: disable=too-many-arguments
+        self,
+        metric_name: str,
+        labels: dict[str, str],
+        timestamp: datetime.datetime,
+        reduced_fingerprint: np.uint64 | int = 0,
+        is_reduced: bool = False,
+        temporality: str = "Unspecified",
+        description: str = "",
+        unit: str = "",
+        type_: str = "Gauge",
+        is_monotonic: bool = False,
+        env: str = "default",
+    ) -> None:
+        labels = dict(labels)
+        labels["__name__"] = metric_name
+        self.env = env
+        self.temporality = temporality
+        self.metric_name = metric_name
+        self.description = description
+        self.unit = unit
+        self.type = type_
+        self.is_monotonic = is_monotonic
+        self.reduced_fingerprint = np.uint64(reduced_fingerprint)
+        self.is_reduced = is_reduced
+        self.labels = json.dumps(labels, separators=(",", ":"))
+        self.attrs = labels
+        self.unix_milli = np.int64(int(timestamp.timestamp() * 1e3))
+        self.normalized = False
+
+        fingerprint_str = metric_name + self.labels
+        self.fingerprint = np.uint64(int(hashlib.md5(fingerprint_str.encode()).hexdigest()[:16], 16))
+
+    def to_row(self) -> list:
+        return [
+            self.env,
+            self.temporality,
+            self.metric_name,
+            self.description,
+            self.unit,
+            self.type,
+            self.is_monotonic,
+            self.fingerprint,
+            self.reduced_fingerprint,
+            self.is_reduced,
+            self.unix_milli,
+            self.labels,
+            self.attrs,
+            {},
+            {},
+            self.normalized,
+        ]
+
+
+class MetricsBufferSample(ABC):
+    """Represents a row in the samples_v4_buffer table. Ruled samples carry
+    the raw fingerprint plus the group's reduced_fingerprint; unruled samples
+    have reduced_fingerprint = 0."""
+
+    def __init__(  # pylint: disable=too-many-arguments
+        self,
+        metric_name: str,
+        fingerprint: np.uint64,
+        timestamp: datetime.datetime,
+        value: float,
+        reduced_fingerprint: np.uint64 | int = 0,
+        is_monotonic: bool = False,
+        temporality: str = "Unspecified",
+        env: str = "default",
+        flags: int = 0,
+    ) -> None:
+        self.env = env
+        self.temporality = temporality
+        self.metric_name = metric_name
+        self.fingerprint = fingerprint
+        self.reduced_fingerprint = np.uint64(reduced_fingerprint)
+        self.is_monotonic = is_monotonic
+        self.unix_milli = np.int64(int(timestamp.timestamp() * 1e3))
+        self.value = np.float64(value)
+        self.flags = np.uint32(flags)
+
+    def to_row(self) -> list:
+        return [
+            self.env,
+            self.temporality,
+            self.metric_name,
+            self.fingerprint,
+            self.reduced_fingerprint,
+            self.is_monotonic,
+            self.unix_milli,
+            self.value,
+            self.flags,
+        ]
+
+
 def insert_metrics_to_clickhouse(conn, metrics: list[Metrics]) -> None:
    """
    Insert metrics into ClickHouse tables.
@@ -576,6 +845,163 @@ def insert_metrics(
    )


+def insert_reduced_metrics_to_clickhouse(
+    conn,
+    time_series: list[MetricsReducedTimeSeries],
+    last_samples: list[MetricsReducedSampleLast60s] | None = None,
+    sum_samples: list[MetricsReducedSampleSum60s] | None = None,
+) -> None:
+    """Insert reduced series into distributed_time_series_v4_reduced and 60s
+    buckets into the reduced samples tables. These tables exist only when
+    the schema migrator version includes the metrics cardinality-control
+    migration."""
+    if time_series:
+        conn.insert(
+            database="signoz_metrics",
+            table="distributed_time_series_v4_reduced",
+            column_names=[
+                "env",
+                "temporality",
+                "metric_name",
+                "description",
+                "unit",
+                "type",
+                "is_monotonic",
+                "fingerprint",
+                "unix_milli",
+                "labels",
+                "attrs",
+                "scope_attrs",
+                "resource_attrs",
+                "__normalized",
+            ],
+            data=[ts.to_row() for ts in time_series],
+        )
+
+    if last_samples:
+        conn.insert(
+            database="signoz_metrics",
+            table="distributed_samples_v4_reduced_last_60s",
+            column_names=[
+                "env",
+                "temporality",
+                "metric_name",
+                "reduced_fingerprint",
+                "unix_milli",
+                "sum_last",
+                "min",
+                "max",
+                "sum_values",
+                "count_series",
+                "count_samples",
+                "computed_at",
+            ],
+            data=[sample.to_row() for sample in last_samples],
+        )
+
+    if sum_samples:
+        conn.insert(
+            database="signoz_metrics",
+            table="distributed_samples_v4_reduced_sum_60s",
+            column_names=[
+                "env",
+                "temporality",
+                "metric_name",
+                "reduced_fingerprint",
+                "unix_milli",
+                "sum",
+                "count_series",
+                "count_samples",
+                "computed_at",
+            ],
+            data=[sample.to_row() for sample in sum_samples],
+        )
+
+
+def insert_buffer_metrics_to_clickhouse(
+    conn,
+    time_series: list[MetricsBufferTimeSeries],
+    samples: list[MetricsBufferSample],
+) -> None:
+    if time_series:
+        conn.insert(
+            database="signoz_metrics",
+            table="distributed_time_series_v4_buffer",
+            column_names=[
+                "env",
+                "temporality",
+                "metric_name",
+                "description",
+                "unit",
+                "type",
+                "is_monotonic",
+                "fingerprint",
+                "reduced_fingerprint",
+                "is_reduced",
+                "unix_milli",
+                "labels",
+                "attrs",
+                "scope_attrs",
+                "resource_attrs",
+                "__normalized",
+            ],
+            data=[ts.to_row() for ts in time_series],
+        )
+
+    if samples:
+        conn.insert(
+            database="signoz_metrics",
+            table="distributed_samples_v4_buffer",
+            column_names=[
+                "env",
+                "temporality",
+                "metric_name",
+                "fingerprint",
+                "reduced_fingerprint",
+                "is_monotonic",
+                "unix_milli",
+                "value",
+                "flags",
+            ],
+            data=[sample.to_row() for sample in samples],
+        )
+
+
+@pytest.fixture(name="insert_reduced_metrics", scope="function")
+def insert_reduced_metrics(
+    clickhouse: types.TestContainerClickhouse,
+) -> Generator[Callable[..., None], Any]:
+    def _insert_reduced_metrics(
+        time_series: list[MetricsReducedTimeSeries],
+        last_samples: list[MetricsReducedSampleLast60s] | None = None,
+        sum_samples: list[MetricsReducedSampleSum60s] | None = None,
+    ) -> None:
+        insert_reduced_metrics_to_clickhouse(clickhouse.conn, time_series, last_samples, sum_samples)
+
+    yield _insert_reduced_metrics
+
+    cluster = clickhouse.env["SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_CLUSTER"]
+    for table in _REDUCED_METRICS_TABLES_TO_TRUNCATE:
+        clickhouse.conn.query(f"TRUNCATE TABLE signoz_metrics.{table} ON CLUSTER '{cluster}' SYNC")
+
+
+@pytest.fixture(name="insert_buffer_metrics", scope="function")
+def insert_buffer_metrics(
+    clickhouse: types.TestContainerClickhouse,
+) -> Generator[Callable[..., None], Any]:
+    def _insert_buffer_metrics(
+        time_series: list[MetricsBufferTimeSeries],
+        samples: list[MetricsBufferSample],
+    ) -> None:
+        insert_buffer_metrics_to_clickhouse(clickhouse.conn, time_series, samples)
+
+    yield _insert_buffer_metrics
+
+    cluster = clickhouse.env["SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_CLUSTER"]
+    for table in _REDUCED_METRICS_TABLES_TO_TRUNCATE:
+        clickhouse.conn.query(f"TRUNCATE TABLE signoz_metrics.{table} ON CLUSTER '{cluster}' SYNC")
+
+
@pytest.fixture(name="remove_metrics_ttl_and_storage_settings", scope="function")
 def remove_metrics_ttl_and_storage_settings(signoz: types.SigNoz):
    """
--- a/tests/fixtures/migrator.py
+++ b/tests/fixtures/migrator.py
@@ -8,27 +8,30 @@ from fixtures.logger import setup_logger
 logger = setup_logger(__name__)


-def create_migrator(
+def create_migrator(  # pylint: disable=too-many-arguments,too-many-positional-arguments
    network: Network,
    clickhouse: types.TestContainerClickhouse,
    request: pytest.FixtureRequest,
    pytestconfig: pytest.Config,
    cache_key: str = "migrator",
    env_overrides: dict | None = None,
+    version: str | None = None,
 ) -> types.Operation:
    """
    Factory function for running schema migrations.
-    Accepts optional env_overrides to customize the migrator environment.
+    Accepts optional env_overrides to customize the migrator environment, and
+    an optional version to pin a schema-migrator release different from the
+    --schema-migrator-version option.
    """

    def create() -> None:
-        version = request.config.getoption("--schema-migrator-version")
+        migrator_version = version or request.config.getoption("--schema-migrator-version")
        client = docker.from_env()

        environment = dict(env_overrides) if env_overrides else {}

        container = client.containers.run(
-            image=f"signoz/signoz-schema-migrator:{version}",
+            image=f"signoz/signoz-schema-migrator:{migrator_version}",
            command=f"sync --replication=true --cluster-name=cluster --up= --dsn={clickhouse.env['SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_DSN']}",
            detach=True,
            auto_remove=False,
@@ -47,7 +50,7 @@ def create_migrator(
        container.remove()

        container = client.containers.run(
-            image=f"signoz/signoz-schema-migrator:{version}",
+            image=f"signoz/signoz-schema-migrator:{migrator_version}",
            command=f"async --replication=true --cluster-name=cluster --up= --dsn={clickhouse.env['SIGNOZ_TELEMETRYSTORE_CLICKHOUSE_DSN']}",
            detach=True,
            auto_remove=False,
--- a/tests/fixtures/querier.py
+++ b/tests/fixtures/querier.py
@@ -189,6 +189,35 @@ def make_query_request(
    )


+def aligned_epoch(ago: timedelta, step_seconds: int = DEFAULT_STEP_INTERVAL) -> int:
+    """Epoch seconds for `now - ago`, floored to a step boundary so seeded
+    points land exactly on the query's toStartOfInterval buckets."""
+    return (int((datetime.now(tz=UTC) - ago).timestamp()) // step_seconds) * step_seconds
+
+
+def query_metric_values(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    signoz: types.SigNoz,
+    token: str,
+    metric_name: str,
+    start_epoch: int,
+    end_epoch: int,
+    time_agg: str,
+    space_agg: str,
+    step_interval: int = DEFAULT_STEP_INTERVAL,
+) -> list[dict]:
+    """Run a single metrics builder query over [start_epoch, end_epoch) in
+    epoch seconds and return its series values sorted by timestamp."""
+    response = make_query_request(
+        signoz,
+        token,
+        start_ms=start_epoch * 1000,
+        end_ms=end_epoch * 1000,
+        queries=[build_builder_query("A", metric_name, time_agg, space_agg, step_interval=step_interval)],
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+    return sorted(get_series_values(response.json(), "A"), key=lambda v: v["timestamp"])
+
+
 def build_builder_query(
    name: str,
    metric_name: str,
--- a/tests/fixtures/types.py
+++ b/tests/fixtures/types.py
@@ -1,4 +1,4 @@
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import Literal
 from urllib.parse import urljoin

@@ -84,11 +84,16 @@ class TestContainerClickhouse:
    container: TestContainerDocker
    conn: clickhouse_connect.driver.client.Client
    env: dict[str, str]
+    # Per-node containers when running a multi-node cluster. Empty for the
+    # default single-node setup; nodes[0] is the node `conn`/`env` point at
+    # (the initiator every query goes through).
+    nodes: list[TestContainerDocker] = field(default_factory=list)

    def __cache__(self) -> dict:
        return {
            "container": self.container.__cache__(),
            "env": self.env,
+            "nodes": [node.__cache__() for node in self.nodes],
        }

    def __log__(self) -> str:
--- a/tests/integration/tests/clickhousecluster/01_basic_cluster.py
+++ b/tests/integration/tests/clickhousecluster/01_basic_cluster.py
@@ -0,0 +1,52 @@
+import clickhouse_connect.driver.client
+
+from fixtures import types
+
+TOTAL_ROWS = 64
+
+
+def test_topology(
+    clickhouse: types.TestContainerClickhouse,
+    clickhouse_node_conns: list[clickhouse_connect.driver.client.Client],
+) -> None:
+    aliases = {node.container_configs["9000"].address for node in clickhouse.nodes}
+
+    # Every node sees the same 2-shard cluster definition and identifies
+    # exactly itself as the local replica
+
+    for i, conn in enumerate(clickhouse_node_conns, start=1):
+        rows = conn.query("SELECT shard_num, host_name, is_local FROM system.clusters WHERE cluster = 'cluster' ORDER BY shard_num").result_rows
+        assert [row[0] for row in rows] == [1, 2], f"node {i}: expected 2 shards, got {rows}"
+        assert {row[1] for row in rows} == aliases, f"node {i}: cluster hosts {rows} != node aliases {aliases}"
+        local = [row[0] for row in rows if row[2]]
+        assert local == [i], f"node {i}: expected to be local for shard {i} only, got {local}"
+
+
+def test_replicated_distributed_round_trip(
+    clickhouse: types.TestContainerClickhouse,
+    clickhouse_node_conns: list[clickhouse_connect.driver.client.Client],
+) -> None:
+    # ON CLUSTER DDL reaches both nodes, Replicated engines register with the
+    # keeper via per-node macros, and a sharded Distributed insert scatters rows
+    # across shards while the distributed read returns the union.
+    conn = clickhouse.conn
+    try:
+        conn.query("CREATE DATABASE IF NOT EXISTS it_cluster ON CLUSTER 'cluster'")
+        conn.query("CREATE TABLE it_cluster.events ON CLUSTER 'cluster' (id UInt64, payload String) ENGINE = ReplicatedMergeTree ORDER BY id")
+        conn.query("CREATE TABLE it_cluster.distributed_events ON CLUSTER 'cluster' AS it_cluster.events ENGINE = Distributed('cluster', 'it_cluster', 'events', cityHash64(id))")
+
+        conn.insert(
+            database="it_cluster",
+            table="distributed_events",
+            column_names=["id", "payload"],
+            data=[[i, f"payload-{i:03d}"] for i in range(TOTAL_ROWS)],
+        )
+
+        distributed_count = int(conn.query("SELECT count() FROM it_cluster.distributed_events").result_rows[0][0])
+        assert distributed_count == TOTAL_ROWS
+
+        local_counts = [int(node_conn.query("SELECT count() FROM it_cluster.events").result_rows[0][0]) for node_conn in clickhouse_node_conns]
+        assert sum(local_counts) == TOTAL_ROWS, f"local counts {local_counts} do not add up to {TOTAL_ROWS}"
+        assert min(local_counts) > 0, f"all rows landed on one shard: {local_counts}"
+    finally:
+        conn.query("DROP DATABASE IF EXISTS it_cluster ON CLUSTER 'cluster' SYNC")
--- a/tests/integration/tests/clickhousecluster/init.py
+++ b/tests/integration/tests/clickhousecluster/init.py
--- a/tests/integration/tests/clickhousecluster/conftest.py
+++ b/tests/integration/tests/clickhousecluster/conftest.py
@@ -0,0 +1,47 @@
+from collections.abc import Generator
+from typing import Any
+
+import pytest
+from testcontainers.core.container import Network
+
+from fixtures import types
+from fixtures.clickhouse import create_clickhouse_cluster, create_clickhouse_keeper
+
+CLICKHOUSE_VERSION = "25.12.5"
+
+
+@pytest.fixture(name="keeper", scope="package")
+def keeper_cluster(
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerDocker:
+    return create_clickhouse_keeper(
+        tmpfs=tmpfs,
+        network=network,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="keeper_cluster",
+        version=CLICKHOUSE_VERSION,
+    )
+
+
+@pytest.fixture(name="clickhouse", scope="package")
+def clickhouse_cluster(
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    keeper: types.TestContainerDocker,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerClickhouse:
+    return create_clickhouse_cluster(
+        tmpfs=tmpfs,
+        network=network,
+        keeper=keeper,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="clickhouse_cluster",
+        shards=2,
+        version=CLICKHOUSE_VERSION,
+    )
--- a/tests/integration/tests/metricreduction/01_reduced_gauge.py
+++ b/tests/integration/tests/metricreduction/01_reduced_gauge.py
@@ -0,0 +1,203 @@
+from collections.abc import Callable
+from datetime import UTC, datetime, timedelta
+
+import clickhouse_connect.driver.client
+import pytest
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.clickhouse import assert_spans_shards
+from fixtures.metrics import (
+    Metrics,
+    MetricsReducedSampleLast60s,
+    MetricsReducedTimeSeries,
+)
+from fixtures.querier import aligned_epoch, query_metric_values
+
+
+def test_stitch_across_epoch(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[list[Metrics]], None],
+    insert_reduced_metrics: Callable[..., None],
+    clickhouse_node_conns: list[clickhouse_connect.driver.client.Client],
+) -> None:
+    """Before the rule activates, samples live in the raw tables; after, only
+    the reduced 60s tables have data. One query spanning the boundary must
+    stitch the two branches into a continuous series with no gap and no double
+    counting: 32 raw series at 2.0 collapse into 16 groups whose sum_last is
+    4.0, so the summed value stays 320 per step across the epoch. Enough
+    series to guarantee both shards hold data (guarded below), so the totals
+    also prove the raw and reduced joins execute shard-local."""
+    metric_name = "test_reduction_stitch"
+    base_epoch = aligned_epoch(timedelta(hours=30), step_seconds=300)
+    services = [f"svc-{i:02d}" for i in range(16)]
+
+    # first 30 minutes: raw samples (2 pods per service, one sample per minute)
+    insert_metrics(
+        [
+            Metrics(
+                metric_name=metric_name,
+                labels={"service": service, "pod": f"{service}-pod-{pod}"},
+                timestamp=datetime.fromtimestamp(base_epoch + minute * 60, tz=UTC),
+                value=2.0,
+                type_="Gauge",
+                is_monotonic=False,
+            )
+            for service in services
+            for pod in range(2)
+            for minute in range(30)
+        ]
+    )
+
+    # next 30 minutes: reduced 60s buckets (one group per service)
+    time_series = [
+        MetricsReducedTimeSeries(
+            metric_name=metric_name,
+            kept_labels={"service": service},
+            timestamp=datetime.fromtimestamp(base_epoch + 30 * 60, tz=UTC),
+        )
+        for service in services
+    ]
+    insert_reduced_metrics(
+        time_series,
+        [
+            MetricsReducedSampleLast60s(
+                metric_name=metric_name,
+                reduced_fingerprint=ts.fingerprint,
+                timestamp=datetime.fromtimestamp(base_epoch + (30 + minute) * 60, tz=UTC),
+                sum_last=4.0,
+                min_value=2.0,
+                max_value=2.0,
+                sum_values=4.0,
+                count_series=2,
+                count_samples=2,
+            )
+            for ts in time_series
+            for minute in range(30)
+        ],
+    )
+
+    assert_spans_shards(clickhouse_node_conns, "time_series_v4", metric_name, total=len(services) * 2)
+    assert_spans_shards(clickhouse_node_conns, "time_series_v4_reduced", metric_name, total=len(services))
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    values = query_metric_values(signoz, token, metric_name, base_epoch, base_epoch + 3600, "sum", "sum", step_interval=300)
+
+    assert [v["timestamp"] for v in values] == [(base_epoch + step * 300) * 1000 for step in range(12)]
+    assert [v["value"] for v in values] == [320.0] * 12
+
+
+@pytest.mark.parametrize(
+    "space_agg, expected",
+    [
+        ("sum", 12.0),  # sum_last: 4 + 8
+        ("avg", 3.0),  # sum(sum_last) / sum(count_series): 12 / 4
+        ("min", 1.0),  # min(min)
+        ("max", 6.0),  # max(max)
+    ],
+)
+def test_space_aggregations(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_reduced_metrics: Callable[..., None],
+    space_agg: str,
+    expected: float,
+) -> None:
+    """Space aggregations read the reduced pre-aggregated columns: sum/avg
+    from sum_last with the count_series weight, min/max from the min/max
+    columns."""
+    metric_name = f"test_reduction_space_{space_agg}"
+    base_epoch = aligned_epoch(timedelta(hours=30), step_seconds=300)
+
+    groups = [
+        # (service, sum_last, min, max, count_series)
+        ("a", 4.0, 1.0, 3.0, 2),
+        ("b", 8.0, 2.0, 6.0, 2),
+    ]
+    time_series = {
+        service: MetricsReducedTimeSeries(
+            metric_name=metric_name,
+            kept_labels={"service": service},
+            timestamp=datetime.fromtimestamp(base_epoch, tz=UTC),
+        )
+        for service, _, _, _, _ in groups
+    }
+    insert_reduced_metrics(
+        list(time_series.values()),
+        [
+            MetricsReducedSampleLast60s(
+                metric_name=metric_name,
+                reduced_fingerprint=time_series[service].fingerprint,
+                timestamp=datetime.fromtimestamp(base_epoch + minute * 60, tz=UTC),
+                sum_last=sum_last,
+                min_value=min_value,
+                max_value=max_value,
+                sum_values=sum_last,
+                count_series=count_series,
+                count_samples=count_series,
+            )
+            for service, sum_last, min_value, max_value, count_series in groups
+            for minute in range(20)
+        ],
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    values = query_metric_values(signoz, token, metric_name, base_epoch, base_epoch + 20 * 60, "avg", space_agg, step_interval=300)
+
+    assert [v["timestamp"] for v in values] == [(base_epoch + step * 300) * 1000 for step in range(4)]
+    assert [v["value"] for v in values] == [expected] * 4
+
+
+def test_dedup_latest_computed_at_wins(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_reduced_metrics: Callable[..., None],
+) -> None:
+    """The refreshable MVs re-emit every bucket on each refresh with a newer
+    computed_at (APPEND mode); reads must dedup to the latest version per
+    (series, bucket). Recompute the same buckets with a newer computed_at and
+    a different value: only the newer value may be counted."""
+    metric_name = "test_reduction_dedup"
+    base_epoch = aligned_epoch(timedelta(hours=30), step_seconds=300)
+
+    time_series = [
+        MetricsReducedTimeSeries(
+            metric_name=metric_name,
+            kept_labels={"service": service},
+            timestamp=datetime.fromtimestamp(base_epoch, tz=UTC),
+        )
+        for service in ("a", "b")
+    ]
+
+    def buckets(sum_last: float, computed_at_offset_seconds: int) -> list[MetricsReducedSampleLast60s]:
+        return [
+            MetricsReducedSampleLast60s(
+                metric_name=metric_name,
+                reduced_fingerprint=ts.fingerprint,
+                timestamp=datetime.fromtimestamp(base_epoch + minute * 60, tz=UTC),
+                sum_last=sum_last,
+                min_value=sum_last,
+                max_value=sum_last,
+                sum_values=sum_last,
+                count_series=1,
+                count_samples=1,
+                computed_at=datetime.fromtimestamp(base_epoch + minute * 60 + computed_at_offset_seconds, tz=UTC),
+            )
+            for ts in time_series
+            for minute in range(10)
+        ]
+
+    # first refresh emits 1.0; a later refresh recomputes the same buckets to 5.0
+    insert_reduced_metrics(time_series, buckets(sum_last=1.0, computed_at_offset_seconds=120))
+    insert_reduced_metrics(time_series, buckets(sum_last=5.0, computed_at_offset_seconds=180))
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    values = query_metric_values(signoz, token, metric_name, base_epoch, base_epoch + 10 * 60, "sum", "sum", step_interval=300)
+
+    # 2 groups x 5 buckets x 5.0 per step; 1.0 rows must not contribute
+    assert [v["timestamp"] for v in values] == [(base_epoch + step * 300) * 1000 for step in range(2)]
+    assert [v["value"] for v in values] == [50.0] * 2
--- a/tests/integration/tests/metricreduction/02_reduced_counter.py
+++ b/tests/integration/tests/metricreduction/02_reduced_counter.py
@@ -0,0 +1,70 @@
+from collections.abc import Callable
+from datetime import UTC, datetime, timedelta
+
+import pytest
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.metrics import (
+    MetricsReducedSampleSum60s,
+    MetricsReducedTimeSeries,
+)
+from fixtures.querier import aligned_epoch, query_metric_values
+
+
+@pytest.mark.parametrize(
+    "time_agg, expected",
+    [
+        # 2 groups x 5 buckets x 30.0 per 300s step
+        ("rate", 1.0),  # 300 / 300s
+        ("increase", 300.0),
+    ],
+)
+def test_counter_rate_and_increase(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_reduced_metrics: Callable[..., None],
+    time_agg: str,
+    expected: float,
+) -> None:
+    metric_name = f"test_reduction_counter_{time_agg}"
+    base_epoch = aligned_epoch(timedelta(hours=30), step_seconds=300)
+
+    # monotonic cumulative counter: MetricsReducedTimeSeries mirrors the
+    # collector's temporality rewrite to Delta
+    time_series = [
+        MetricsReducedTimeSeries(
+            metric_name=metric_name,
+            kept_labels={"service": service},
+            timestamp=datetime.fromtimestamp(base_epoch, tz=UTC),
+            temporality="Cumulative",
+            type_="Sum",
+            is_monotonic=True,
+        )
+        for service in ("a", "b")
+    ]
+    assert all(ts.temporality == "Delta" for ts in time_series)
+
+    insert_reduced_metrics(
+        time_series,
+        sum_samples=[
+            MetricsReducedSampleSum60s(
+                metric_name=metric_name,
+                reduced_fingerprint=ts.fingerprint,
+                timestamp=datetime.fromtimestamp(base_epoch + minute * 60, tz=UTC),
+                sum_value=30.0,
+                count_series=2,
+                count_samples=2,
+                temporality="Delta",
+            )
+            for ts in time_series
+            for minute in range(20)
+        ],
+    )
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    values = query_metric_values(signoz, token, metric_name, base_epoch, base_epoch + 20 * 60, time_agg, "sum", step_interval=300)
+
+    assert [v["timestamp"] for v in values] == [(base_epoch + step * 300) * 1000 for step in range(4)]
+    assert [v["value"] for v in values] == [expected] * 4
--- a/tests/integration/tests/metricreduction/03_reduced_buffer_window.py
+++ b/tests/integration/tests/metricreduction/03_reduced_buffer_window.py
@@ -0,0 +1,70 @@
+from collections.abc import Callable
+from datetime import timedelta
+from http import HTTPStatus
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.metricreduction import build_ruled_gauge_buffer
+from fixtures.querier import (
+    aligned_epoch,
+    build_builder_query,
+    get_all_series,
+    index_series_by_label,
+    make_query_request,
+    query_metric_values,
+)
+
+SERVICES = ("a", "b")
+PODS_PER_SERVICE = 2
+MINUTES = 20
+
+
+def test_recent_window_reads_buffer_totals(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_buffer_metrics: Callable[..., None],
+) -> None:
+    metric_name = "test_reduction_buffer_totals"
+    # samples span [now-25m, now-5m); the query window sits inside the last 24h
+    base_epoch = aligned_epoch(timedelta(minutes=25), step_seconds=300)
+    insert_buffer_metrics(*build_ruled_gauge_buffer(metric_name, base_epoch, SERVICES, PODS_PER_SERVICE, MINUTES))
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    values = query_metric_values(signoz, token, metric_name, base_epoch, base_epoch + MINUTES * 60, "sum", "sum", step_interval=300)
+
+    # 4 raw series x 5 samples x 1.0 per step: full raw resolution, and the
+    # is_reduced=true series rows must not join in (their fingerprints match
+    # no samples, and the ts CTE filters them out)
+    assert [v["timestamp"] for v in values] == [(base_epoch + step * 300) * 1000 for step in range(4)]
+    assert [v["value"] for v in values] == [float(len(SERVICES) * PODS_PER_SERVICE * 5)] * 4
+
+
+def test_recent_window_group_by_raw_label(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_buffer_metrics: Callable[..., None],
+) -> None:
+    """Group-by resolves against the raw buffer series rows (full labels), so
+    grouping by the kept label still sees every raw series underneath."""
+    metric_name = "test_reduction_buffer_groupby"
+    base_epoch = aligned_epoch(timedelta(minutes=25), step_seconds=300)
+    insert_buffer_metrics(*build_ruled_gauge_buffer(metric_name, base_epoch, SERVICES, PODS_PER_SERVICE, MINUTES))
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    response = make_query_request(
+        signoz,
+        token,
+        start_ms=base_epoch * 1000,
+        end_ms=(base_epoch + MINUTES * 60) * 1000,
+        queries=[build_builder_query("A", metric_name, "sum", "sum", step_interval=300, group_by=["service"])],
+    )
+    assert response.status_code == HTTPStatus.OK, response.text
+
+    series_by_service = index_series_by_label(get_all_series(response.json(), "A"), "service")
+    assert set(series_by_service.keys()) == set(SERVICES)
+    for service in SERVICES:
+        values = sorted(series_by_service[service]["values"], key=lambda v: v["timestamp"])
+        # 2 pods x 5 samples x 1.0 per step
+        assert [v["value"] for v in values] == [float(PODS_PER_SERVICE * 5)] * 4
--- a/tests/integration/tests/metricreduction/init.py
+++ b/tests/integration/tests/metricreduction/init.py
--- a/tests/integration/tests/metricreduction/conftest.py
+++ b/tests/integration/tests/metricreduction/conftest.py
@@ -0,0 +1,114 @@
+from collections.abc import Generator
+from typing import Any
+
+import pytest
+from testcontainers.core.container import Network
+
+from fixtures import types
+from fixtures.auth import register_admin
+from fixtures.clickhouse import create_clickhouse_cluster, create_clickhouse_keeper
+from fixtures.http import ZEUS_NETWORK_ALIAS, create_zeus
+from fixtures.migrator import create_migrator
+from fixtures.signoz import create_signoz
+
+SCHEMA_MIGRATOR_VERSION = "v0.144.6-rc.2"
+CLICKHOUSE_VERSION = "25.12.5"
+
+
+@pytest.fixture(name="keeper", scope="package")
+def keeper_metricreduction(
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerDocker:
+    return create_clickhouse_keeper(
+        tmpfs=tmpfs,
+        network=network,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="keeper_metricreduction",
+        version=CLICKHOUSE_VERSION,
+    )
+
+
+@pytest.fixture(name="zeus", scope="package")
+def zeus_metricreduction(
+    network: Network,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerDocker:
+    return create_zeus(
+        network=network,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="zeus_metricreduction",
+        alias=ZEUS_NETWORK_ALIAS,
+    )
+
+
+@pytest.fixture(name="clickhouse", scope="package")
+def clickhouse_metricreduction(
+    tmpfs: Generator[types.LegacyPath, Any],
+    network: Network,
+    keeper: types.TestContainerDocker,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.TestContainerClickhouse:
+    return create_clickhouse_cluster(
+        tmpfs=tmpfs,
+        network=network,
+        keeper=keeper,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="clickhouse_metricreduction",
+        shards=2,
+        version=CLICKHOUSE_VERSION,
+    )
+
+
+@pytest.fixture(name="migrator", scope="package")
+def migrator_metricreduction(
+    network: Network,
+    clickhouse: types.TestContainerClickhouse,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.Operation:
+    return create_migrator(
+        network=network,
+        clickhouse=clickhouse,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="migrator_metricreduction",
+        version=SCHEMA_MIGRATOR_VERSION,
+    )
+
+
+@pytest.fixture(name="signoz", scope="package")
+def signoz_metricreduction(  # pylint: disable=too-many-arguments,too-many-positional-arguments
+    network: Network,
+    zeus: types.TestContainerDocker,
+    gateway: types.TestContainerDocker,
+    sqlstore: types.TestContainerSQL,
+    clickhouse: types.TestContainerClickhouse,
+    request: pytest.FixtureRequest,
+    pytestconfig: pytest.Config,
+) -> types.SigNoz:
+    return create_signoz(
+        network=network,
+        zeus=zeus,
+        gateway=gateway,
+        sqlstore=sqlstore,
+        clickhouse=clickhouse,
+        request=request,
+        pytestconfig=pytestconfig,
+        cache_key="signoz_metricreduction",
+        env_overrides={
+            "SIGNOZ_FLAGGER_CONFIG_BOOLEAN_ENABLE__METRICS__REDUCTION": True,
+        },
+    )
+
+
+@pytest.fixture(name="create_user_admin", scope="package")
+def create_user_admin_metricreduction(signoz: types.SigNoz, request: pytest.FixtureRequest, pytestconfig: pytest.Config) -> types.Operation:
+    return register_admin(signoz, request, pytestconfig, cache_key="create_user_admin_metricreduction")
Author	SHA1	Message	Date
Srikanth Chekuri	b180df8e3e	Merge branch 'main' into issue-5535	2026-07-06 20:55:56 +05:30
Srikanth Chekuri	c6bb7569af	Merge branch 'main' into issue-5535	2026-07-06 11:51:09 +05:30
srikanthccv	5d431f9f6f	chore: add to ci	2026-07-06 11:50:46 +05:30
srikanthccv	1f0113645e	chore: add integration tests for metrics under reduction - query part	2026-07-06 11:19:45 +05:30
				`@@ -1 +0,0 @@`
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