Merge branch 'main' into feat/infra_disk_usage

frontend/src/api/infraMonitoring/getHostLists.ts

@@ -39,6 +39,7 @@ export interface HostData {
 	waitTimeSeries: TimeSeries;
 	load15: number;
 	load15TimeSeries: TimeSeries;
+	filesystem: number;
 }
 
 export interface HostListResponse {

frontend/src/components/HostMetricsDetail/HostMetricsDetail.styles.scss

@@ -48,7 +48,7 @@
 			.labels-row,
 			.values-row {
 				display: grid;
-				grid-template-columns: 1fr 1.5fr 1.5fr 1.5fr;
+				grid-template-columns: 1fr 1.5fr 1.5fr 1.5fr 1.5fr;
 				gap: 30px;
 				align-items: center;
 			}

frontend/src/components/HostMetricsDetail/HostMetricsDetails.tsx

@@ -426,6 +426,12 @@ function HostMetricsDetails({
 								>
 									MEMORY USAGE
 								</Typography.Text>
+								<Typography.Text
+									type="secondary"
+									className="host-details-metadata-label"
+								>
+									DISK USAGE
+								</Typography.Text>
 							</div>
 
 							<div className="values-row">
@@ -478,6 +484,23 @@ function HostMetricsDetails({
 										className="progress-bar"
 									/>
 								</div>
+								<div className="progress-container">
+									<Progress
+										percent={Number((host.filesystem * 100).toFixed(1))}
+										size="small"
+										strokeColor={((): string => {
+											const filesystemPercent = Number((host.filesystem * 100).toFixed(1));
+											if (filesystemPercent >= 90) {
+												return Color.BG_CHERRY_500;
+											}
+											if (filesystemPercent >= 60) {
+												return Color.BG_AMBER_500;
+											}
+											return Color.BG_FOREST_500;
+										})()}
+										className="progress-bar"
+									/>
+								</div>
 							</div>
 						</div>
 					</div>

frontend/src/container/InfraMonitoringHosts/utils.tsx

@@ -27,6 +27,7 @@ export interface HostRowData {
 	hostName: string;
 	cpu: React.ReactNode;
 	memory: React.ReactNode;
+	filesystem: React.ReactNode;
 	wait: string;
 	load15: number;
 	active: React.ReactNode;
@@ -108,6 +109,14 @@ export const getHostsListColumns = (): ColumnType<HostRowData>[] => [
 		sorter: true,
 		align: 'right',
 	},
+	{
+		title: <div className="column-header-right">Disk Usage</div>,
+		dataIndex: 'filesystem',
+		key: 'filesystem',
+		width: 100,
+		sorter: true,
+		align: 'right',
+	},
 	{
 		title: <div className="column-header-right">IOWait</div>,
 		dataIndex: 'wait',
@@ -178,6 +187,26 @@ export const formatDataForTable = (data: HostData[]): HostRowData[] =>
 				/>
 			</div>
 		),
+		filesystem: (
+			<div className="progress-container">
+				<Progress
+					percent={Number((host.filesystem * 100).toFixed(1))}
+					strokeLinecap="butt"
+					size="small"
+					strokeColor={((): string => {
+						const filesystemPercent = Number((host.filesystem * 100).toFixed(1));
+						if (filesystemPercent >= 90) {
+							return Color.BG_CHERRY_500;
+						}
+						if (filesystemPercent >= 60) {
+							return Color.BG_AMBER_500;
+						}
+						return Color.BG_FOREST_500;
+					})()}
+					className="progress-bar"
+				/>
+			</div>
+		),
 		wait: `${Number((host.wait * 100).toFixed(1))}%`,
 		load15: host.load15,
 	}));

frontend/src/container/LogDetailedView/InfraMetrics/constants.ts

@@ -1623,6 +1623,9 @@ export const getHostQueryPayload = (
 	const diskPendingKey = dotMetricsEnabled
 		? 'system.disk.pending_operations'
 		: 'system_disk_pending_operations';
+	const fsUsageKey = dotMetricsEnabled
+		? 'system.filesystem.usage'
+		: 'system_filesystem_usage';
 
 	return [
 		{
@@ -2483,6 +2486,143 @@ 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: [],
+							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: [],
+							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,
+		},
 		{
 			selectedTime: 'GLOBAL_TIME',
 			graphType: PANEL_TYPES.TIME_SERIES,
@@ -2631,6 +2771,6 @@ export const hostWidgetInfo = [
 	{ title: 'Network connections', yAxisUnit: 'short' },
 	{ title: 'System disk io (bytes transferred)', yAxisUnit: 'bytes' },
 	{ title: 'System disk operations/s', yAxisUnit: 'short' },
+	{ title: 'Disk Usage (%) by mountpoint', yAxisUnit: 'percentunit' },
 	{ title: 'Queue size', yAxisUnit: 'short' },
-	{ title: 'Disk operations time', yAxisUnit: 's' },
 ];

pkg/querier/querier.go

@@ -278,7 +278,7 @@ func (q *querier) QueryRange(ctx context.Context, orgID valuer.UUID, req *qbtype
 	var metricTemporality map[string]metrictypes.Temporality
 	if len(metricNames) > 0 {
 		var err error
-		metricTemporality, err = q.metadataStore.FetchTemporalityMulti(ctx, metricNames...)
+		metricTemporality, err = q.metadataStore.FetchTemporalityMulti(ctx, req.Start, req.End, metricNames...)
 		if err != nil {
 			q.logger.WarnContext(ctx, "failed to fetch metric temporality", "error", err, "metrics", metricNames)
 			// Continue without temporality - statement builder will handle unspecified

pkg/query-service/app/inframetrics/common.go

@@ -10,6 +10,7 @@ import (
 )
 
 var dotMetricMap = map[string]string{
+	"system_filesystem_usage":               "system.filesystem.usage",
 	"system_cpu_time":                       "system.cpu.time",
 	"system_memory_usage":                   "system.memory.usage",
 	"system_cpu_load_average_15m":           "system.cpu.load_average.15m",

pkg/query-service/app/inframetrics/hosts.go

@@ -53,10 +53,11 @@ var (
 	}
 
 	queryNamesForTopHosts = map[string][]string{
-		"cpu":    {"A", "B", "F1"},
-		"memory": {"C", "D", "F2"},
-		"wait":   {"E", "F", "F3"},
-		"load15": {"G"},
+		"cpu":        {"A", "B", "F1"},
+		"memory":     {"C", "D", "F2"},
+		"wait":       {"E", "F", "F3"},
+		"load15":     {"G"},
+		"filesystem": {"H", "I", "F4"},
 	}
 
 	// TODO(srikanthccv): remove hardcoded metric name and support keys from any system metric
@@ -67,10 +68,11 @@ var (
 		GetDotMetrics("os_type"),
 	}
 	metricNamesForHosts = map[string]string{
-		"cpu":    GetDotMetrics("system_cpu_time"),
-		"memory": GetDotMetrics("system_memory_usage"),
-		"load15": GetDotMetrics("system_cpu_load_average_15m"),
-		"wait":   GetDotMetrics("system_cpu_time"),
+		"cpu":        GetDotMetrics("system_cpu_time"),
+		"memory":     GetDotMetrics("system_memory_usage"),
+		"load15":     GetDotMetrics("system_cpu_load_average_15m"),
+		"wait":       GetDotMetrics("system_cpu_time"),
+		"filesystem": GetDotMetrics("system_filesystem_usage"),
 	}
 )
 
@@ -494,10 +496,11 @@ func (h *HostsRepo) GetHostList(ctx context.Context, orgID valuer.UUID, req mode
 	for _, result := range formattedResponse {
 		for _, row := range result.Table.Rows {
 			record := model.HostListRecord{
-				CPU:    -1,
-				Memory: -1,
-				Wait:   -1,
-				Load15: -1,
+				CPU:        -1,
+				Memory:     -1,
+				Wait:       -1,
+				Load15:     -1,
+				Filesystem: -1,
 			}
 
 			if hostName, ok := row.Data[hostNameAttrKey].(string); ok {
@@ -516,6 +519,9 @@ func (h *HostsRepo) GetHostList(ctx context.Context, orgID valuer.UUID, req mode
 			if load15, ok := row.Data["G"].(float64); ok {
 				record.Load15 = load15
 			}
+			if filesystem, ok := row.Data["F4"].(float64); ok {
+				record.Filesystem = filesystem
+			}
 			record.Meta = map[string]string{}
 			if _, ok := hostAttrs[record.HostName]; ok {
 				record.Meta = hostAttrs[record.HostName]

pkg/query-service/app/inframetrics/hosts_query.go

@@ -269,42 +269,130 @@ var HostsTableListQuery = v3.QueryRangeParamsV3{
 					Items:    []v3.FilterItem{},
 				},
 			},
-			"G": {
-				QueryName:  "G",
-				DataSource: v3.DataSourceMetrics,
-				AggregateAttribute: v3.AttributeKey{
-					Key:      metricNamesForHosts["load15"],
-					DataType: v3.AttributeKeyDataTypeFloat64,
-				},
-				Temporality: v3.Unspecified,
-				Filters: &v3.FilterSet{
-					Operator: "AND",
-					Items: []v3.FilterItem{
-						{
-							Key: v3.AttributeKey{
-								Key:      hostNameAttrKey,
-								DataType: v3.AttributeKeyDataTypeString,
-								Type:     v3.AttributeKeyTypeResource,
-							},
-							Operator: v3.FilterOperatorNotContains,
-							Value:    agentNameToIgnore,
-						},
-					},
-				},
-				GroupBy: []v3.AttributeKey{
-					{
-						Key:      hostNameAttrKey,
-						DataType: v3.AttributeKeyDataTypeString,
-						Type:     v3.AttributeKeyTypeResource,
-					},
-				},
-				Expression:       "G",
-				ReduceTo:         v3.ReduceToOperatorAvg,
-				TimeAggregation:  v3.TimeAggregationAvg,
-				SpaceAggregation: v3.SpaceAggregationSum,
-				Disabled:         false,
-				Legend:           "CPU Load Average (15m)",
+		"G": {
+			QueryName:  "G",
+			DataSource: v3.DataSourceMetrics,
+			AggregateAttribute: v3.AttributeKey{
+				Key:      metricNamesForHosts["load15"],
+				DataType: v3.AttributeKeyDataTypeFloat64,
 			},
+			Temporality: v3.Unspecified,
+			Filters: &v3.FilterSet{
+				Operator: "AND",
+				Items: []v3.FilterItem{
+					{
+						Key: v3.AttributeKey{
+							Key:      hostNameAttrKey,
+							DataType: v3.AttributeKeyDataTypeString,
+							Type:     v3.AttributeKeyTypeResource,
+						},
+						Operator: v3.FilterOperatorNotContains,
+						Value:    agentNameToIgnore,
+					},
+				},
+			},
+			GroupBy: []v3.AttributeKey{
+				{
+					Key:      hostNameAttrKey,
+					DataType: v3.AttributeKeyDataTypeString,
+					Type:     v3.AttributeKeyTypeResource,
+				},
+			},
+			Expression:       "G",
+			ReduceTo:         v3.ReduceToOperatorAvg,
+			TimeAggregation:  v3.TimeAggregationAvg,
+			SpaceAggregation: v3.SpaceAggregationSum,
+			Disabled:         false,
+			Legend:           "CPU Load Average (15m)",
+		},
+		"H": {
+			QueryName:  "H",
+			DataSource: v3.DataSourceMetrics,
+			AggregateAttribute: v3.AttributeKey{
+				Key:      metricNamesForHosts["filesystem"],
+				DataType: v3.AttributeKeyDataTypeFloat64,
+			},
+			Temporality: v3.Cumulative,
+			Filters: &v3.FilterSet{
+				Operator: "AND",
+				Items: []v3.FilterItem{
+					{
+						Key: v3.AttributeKey{
+							Key:      "state",
+							DataType: v3.AttributeKeyDataTypeString,
+							Type:     v3.AttributeKeyTypeTag,
+						},
+						Operator: v3.FilterOperatorEqual,
+						Value:    "used",
+					},
+					{
+						Key: v3.AttributeKey{
+							Key:      hostNameAttrKey,
+							DataType: v3.AttributeKeyDataTypeString,
+							Type:     v3.AttributeKeyTypeResource,
+						},
+						Operator: v3.FilterOperatorNotContains,
+						Value:    agentNameToIgnore,
+					},
+				},
+			},
+			GroupBy: []v3.AttributeKey{
+				{
+					Key:      hostNameAttrKey,
+					DataType: v3.AttributeKeyDataTypeString,
+					Type:     v3.AttributeKeyTypeResource,
+				},
+			},
+			Expression:       "H",
+			ReduceTo:         v3.ReduceToOperatorAvg,
+			TimeAggregation:  v3.TimeAggregationAvg,
+			SpaceAggregation: v3.SpaceAggregationSum,
+			Disabled:         true,
+		},
+		"I": {
+			QueryName:  "I",
+			DataSource: v3.DataSourceMetrics,
+			AggregateAttribute: v3.AttributeKey{
+				Key:      metricNamesForHosts["filesystem"],
+				DataType: v3.AttributeKeyDataTypeFloat64,
+			},
+			Temporality: v3.Cumulative,
+			Filters: &v3.FilterSet{
+				Operator: "AND",
+				Items: []v3.FilterItem{
+					{
+						Key: v3.AttributeKey{
+							Key:      hostNameAttrKey,
+							DataType: v3.AttributeKeyDataTypeString,
+							Type:     v3.AttributeKeyTypeResource,
+						},
+						Operator: v3.FilterOperatorNotContains,
+						Value:    agentNameToIgnore,
+					},
+				},
+			},
+			GroupBy: []v3.AttributeKey{
+				{
+					Key:      hostNameAttrKey,
+					DataType: v3.AttributeKeyDataTypeString,
+					Type:     v3.AttributeKeyTypeResource,
+				},
+			},
+			Expression:       "I",
+			ReduceTo:         v3.ReduceToOperatorAvg,
+			TimeAggregation:  v3.TimeAggregationAvg,
+			SpaceAggregation: v3.SpaceAggregationSum,
+			Disabled:         true,
+		},
+		"F4": {
+			QueryName:  "F4",
+			Expression: "H/I",
+			Legend:     "Disk Usage (%)",
+			Filters: &v3.FilterSet{
+				Operator: "AND",
+				Items:    []v3.FilterItem{},
+			},
+		},
 		},
 		PanelType: v3.PanelTypeTable,
 		QueryType: v3.QueryTypeBuilder,

pkg/query-service/model/infra.go

@@ -26,14 +26,15 @@ type HostListRequest struct {
 }
 
 type HostListRecord struct {
-	HostName string            `json:"hostName"`
-	Active   bool              `json:"active"`
-	OS       string            `json:"os"`
-	CPU      float64           `json:"cpu"`
-	Memory   float64           `json:"memory"`
-	Wait     float64           `json:"wait"`
-	Load15   float64           `json:"load15"`
-	Meta     map[string]string `json:"meta"`
+	HostName   string            `json:"hostName"`
+	Active     bool              `json:"active"`
+	OS         string            `json:"os"`
+	CPU        float64           `json:"cpu"`
+	Memory     float64           `json:"memory"`
+	Wait       float64           `json:"wait"`
+	Load15     float64           `json:"load15"`
+	Filesystem float64           `json:"filesystem"`
+	Meta       map[string]string `json:"meta"`
 }
 
 type HostListResponse struct {
@@ -64,6 +65,10 @@ func (r *HostListResponse) SortBy(orderBy *v3.OrderBy) {
 		sort.Slice(r.Records, func(i, j int) bool {
 			return r.Records[i].Wait > r.Records[j].Wait
 		})
+	case "filesystem":
+		sort.Slice(r.Records, func(i, j int) bool {
+			return r.Records[i].Filesystem > r.Records[j].Filesystem
+		})
 	}
 	// the default is descending
 	if orderBy.Order == v3.DirectionAsc {

pkg/telemetrymetadata/metadata.go

@@ -1597,12 +1597,12 @@ func (t *telemetryMetaStore) GetAllValues(ctx context.Context, fieldValueSelecto
 	return values, complete, nil
 }
 
-func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, metricName string) (metrictypes.Temporality, error) {
+func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
 	if metricName == "" {
 		return metrictypes.Unknown, errors.Newf(errors.TypeInternal, errors.CodeInternal, "metric name cannot be empty")
 	}
 
-	temporalityMap, err := t.FetchTemporalityMulti(ctx, metricName)
+	temporalityMap, err := t.FetchTemporalityMulti(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricName)
 	if err != nil {
 		return metrictypes.Unknown, err
 	}
@@ -1615,13 +1615,13 @@ func (t *telemetryMetaStore) FetchTemporality(ctx context.Context, metricName st
 	return temporality, nil
 }
 
-func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, error) {
+func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
 	if len(metricNames) == 0 {
 		return make(map[string]metrictypes.Temporality), nil
 	}
 
 	result := make(map[string]metrictypes.Temporality)
-	metricsTemporality, err := t.fetchMetricsTemporality(ctx, metricNames...)
+	metricsTemporality, err := t.fetchMetricsTemporality(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)
 	if err != nil {
 		return nil, err
 	}
@@ -1630,8 +1630,12 @@ func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, metricNa
 
 	// For metrics not found in the database, set to Unknown
 	for _, metricName := range metricNames {
-		if temporality, exists := metricsTemporality[metricName]; exists {
-			result[metricName] = temporality
+		if temporality, exists := metricsTemporality[metricName]; exists && len(temporality) > 0 {
+			if len(temporality) > 1 {
+				result[metricName] = metrictypes.Multiple
+			} else {
+				result[metricName] = temporality[0]
+			}
 			continue
 		}
 		if temporality, exists := meterMetricsTemporality[metricName]; exists {
@@ -1644,8 +1648,10 @@ func (t *telemetryMetaStore) FetchTemporalityMulti(ctx context.Context, metricNa
 	return result, nil
 }
 
-func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, error) {
-	result := make(map[string]metrictypes.Temporality)
+func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string][]metrictypes.Temporality, error) {
+	result := make(map[string][]metrictypes.Temporality)
+
+	adjustedStartTs, adjustedEndTs, tsTableName, _ := telemetrymetrics.WhichTSTableToUse(queryTimeRangeStartTs, queryTimeRangeEndTs, nil)
 
 	// Build query to fetch temporality for all metrics
 	// We use attr_string_value where attr_name = '__temporality__'
@@ -1653,14 +1659,18 @@ func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, metric
 	// and metric_name column contains temporality value, so we use the correct mapping
 	sb := sqlbuilder.Select(
 		"metric_name",
-		"argMax(temporality, last_reported_unix_milli) as temporality",
-	).From(t.metricsDBName + "." + t.metricsFieldsTblName)
+		"temporality",
+	).
+		From(t.metricsDBName + "." + tsTableName)
 
 	// Filter by metric names (in the temporality column due to data mix-up)
-	sb.Where(sb.In("metric_name", metricNames))
+	sb.Where(
+		sb.In("metric_name", metricNames),
+		sb.GTE("unix_milli", adjustedStartTs),
+		sb.LT("unix_milli", adjustedEndTs),
+	)
 
-	// Group by metric name to get one temporality per metric
-	sb.GroupBy("metric_name")
+	sb.GroupBy("metric_name", "temporality")
 
 	query, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse)
 
@@ -1692,8 +1702,12 @@ func (t *telemetryMetaStore) fetchMetricsTemporality(ctx context.Context, metric
 			// Unknown or empty temporality
 			temporality = metrictypes.Unknown
 		}
-
-		result[metricName] = temporality
+		if temporality != metrictypes.Unknown {
+			result[metricName] = append(result[metricName], temporality)
+		}
+	}
+	if err := rows.Err(); err != nil {
+		return nil, errors.Wrapf(err, errors.TypeInternal, errors.CodeInternal, "error iterating over metrics temporality rows")
 	}
 
 	return result, nil

pkg/telemetrymetrics/statement_builder.go

@@ -21,6 +21,10 @@ const (
 	RateWithoutNegative     = `If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, per_series_value / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window), (per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))`
 	IncreaseWithoutNegative = `If((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) < 0, per_series_value, ((per_series_value - lagInFrame(per_series_value, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window)) * (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))`
 
+	RateWithoutNegativeMultiTemporality     = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, IF((%s - lagInFrame(%s, 1, 0) OVER rate_window) < 0, %s / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window), (%s - lagInFrame(%s, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))) AS per_series_value`
+	IncreaseWithoutNegativeMultiTemporality = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, IF((%s - lagInFrame(%s, 1, 0) OVER rate_window) < 0, %s, ((%s - lagInFrame(%s, 1, 0) OVER rate_window) / (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window)) * (ts - lagInFrame(ts, 1, toDateTime(fromUnixTimestamp64Milli(%d))) OVER rate_window))) AS per_series_value`
+	OthersMultiTemporality                  = `IF(LOWER(temporality) LIKE LOWER('delta'), %s, %s) AS per_series_value`
+
 	RateWithInterpolation = `
 		CASE 
 			WHEN row_number() OVER rate_window = 1 THEN 
@@ -377,7 +381,7 @@ func (b *MetricQueryStatementBuilder) buildTimeSeriesCTE(
 		sb.LTE("unix_milli", end),
 	)
 
-	if query.Aggregations[0].Temporality != metrictypes.Unknown {
+	if query.Aggregations[0].Temporality != metrictypes.Multiple && query.Aggregations[0].Temporality != metrictypes.Unknown {
 		sb.Where(sb.ILike("temporality", query.Aggregations[0].Temporality.StringValue()))
 	}
 
@@ -407,8 +411,10 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggregationCTE(
 ) (string, []any, error) {
 	if query.Aggregations[0].Temporality == metrictypes.Delta {
 		return b.buildTemporalAggDelta(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
+	} else if query.Aggregations[0].Temporality != metrictypes.Multiple {
+		return b.buildTemporalAggCumulativeOrUnspecified(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
 	}
-	return b.buildTemporalAggCumulativeOrUnspecified(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
+	return b.buildTemporalAggForMultipleTemporalities(ctx, start, end, query, timeSeriesCTE, timeSeriesCTEArgs)
 }
 
 func (b *MetricQueryStatementBuilder) buildTemporalAggDelta(
@@ -528,6 +534,58 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 	}
 }
 
+// because RateInterpolation is not enabled anywhere due to some gaps in the logic wrt cache handling, it hasn't been considered for the multi temporality
+func (b *MetricQueryStatementBuilder) buildTemporalAggForMultipleTemporalities(
+	_ context.Context,
+	start, end uint64,
+	query qbtypes.QueryBuilderQuery[qbtypes.MetricAggregation],
+	timeSeriesCTE string,
+	timeSeriesCTEArgs []any,
+) (string, []any, error) {
+	stepSec := int64(query.StepInterval.Seconds())
+	sb := sqlbuilder.NewSelectBuilder()
+
+	sb.SelectMore(fmt.Sprintf(
+		"toStartOfInterval(toDateTime(intDiv(unix_milli, 1000)), toIntervalSecond(%d)) AS ts",
+		stepSec,
+	))
+	for _, g := range query.GroupBy {
+		sb.SelectMore(fmt.Sprintf("`%s`", g.TelemetryFieldKey.Name))
+	}
+
+	aggForDeltaTemporality := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Delta, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	aggForCumulativeTemporality := AggregationColumnForSamplesTable(start, end, query.Aggregations[0].Type, metrictypes.Cumulative, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	if query.Aggregations[0].TimeAggregation == metrictypes.TimeAggregationRate {
+		aggForDeltaTemporality = fmt.Sprintf("%s/%d", aggForDeltaTemporality, stepSec)
+	}
+
+	switch query.Aggregations[0].TimeAggregation {
+	case metrictypes.TimeAggregationRate:
+		rateExpr := fmt.Sprintf(RateWithoutNegativeMultiTemporality, aggForDeltaTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, start, aggForCumulativeTemporality, aggForCumulativeTemporality, start)
+		sb.SelectMore(rateExpr)
+	case metrictypes.TimeAggregationIncrease:
+		increaseExpr := fmt.Sprintf(IncreaseWithoutNegativeMultiTemporality, aggForDeltaTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, aggForCumulativeTemporality, start, start)
+		sb.SelectMore(increaseExpr)
+	default:
+		expr := fmt.Sprintf(OthersMultiTemporality, aggForDeltaTemporality, aggForCumulativeTemporality)
+		sb.SelectMore(expr)
+	}
+
+	tbl := WhichSamplesTableToUse(start, end, query.Aggregations[0].Type, query.Aggregations[0].TimeAggregation, query.Aggregations[0].TableHints)
+	sb.From(fmt.Sprintf("%s.%s AS points", DBName, tbl))
+	sb.JoinWithOption(sqlbuilder.InnerJoin, timeSeriesCTE, "points.fingerprint = filtered_time_series.fingerprint")
+	sb.Where(
+		sb.In("metric_name", query.Aggregations[0].MetricName),
+		sb.GTE("unix_milli", start),
+		sb.LT("unix_milli", end),
+	)
+	sb.GroupBy("fingerprint", "ts", "temporality")
+	sb.GroupBy(querybuilder.GroupByKeys(query.GroupBy)...)
+	queryWithoutWindow, args := sb.BuildWithFlavor(sqlbuilder.ClickHouse, timeSeriesCTEArgs...)
+	queryWithWindowAndOrder := queryWithoutWindow + " WINDOW rate_window AS (PARTITION BY fingerprint ORDER BY fingerprint ASC, ts ASC) ORDER BY ts"
+	return fmt.Sprintf("__temporal_aggregation_cte AS (%s)", queryWithWindowAndOrder), args, nil
+}
+
 func (b *MetricQueryStatementBuilder) buildSpatialAggregationCTE(
 	_ context.Context,
 	_ uint64,

pkg/types/metrictypes/metrictypes.go

@@ -19,6 +19,7 @@ var (
 	Cumulative  = Temporality{valuer.NewString("cumulative")}
 	Unspecified = Temporality{valuer.NewString("unspecified")}
 	Unknown     = Temporality{valuer.NewString("")}
+	Multiple    = Temporality{valuer.NewString("__multiple__")}
 )
 
 func (t Temporality) Value() (driver.Value, error) {

pkg/types/telemetrytypes/store.go

@@ -27,10 +27,10 @@ type MetadataStore interface {
 	GetAllValues(ctx context.Context, fieldValueSelector *FieldValueSelector) (*TelemetryFieldValues, bool, error)
 
 	// FetchTemporality fetches the temporality for metric
-	FetchTemporality(ctx context.Context, metricName string) (metrictypes.Temporality, error)
+	FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error)
 
 	// FetchTemporalityMulti fetches the temporality for multiple metrics
-	FetchTemporalityMulti(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, error)
+	FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error)
 
 	// ListLogsJSONIndexes lists the JSON indexes for the logs table.
 	ListLogsJSONIndexes(ctx context.Context, filters ...string) (map[string][]schemamigrator.Index, error)

pkg/types/telemetrytypes/telemetrytypestest/metadata_store.go

@@ -265,7 +265,7 @@ func (m *MockMetadataStore) SetAllValues(lookupKey string, values *telemetrytype
 }
 
 // FetchTemporality fetches the temporality for a metric
-func (m *MockMetadataStore) FetchTemporality(ctx context.Context, metricName string) (metrictypes.Temporality, error) {
+func (m *MockMetadataStore) FetchTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricName string) (metrictypes.Temporality, error) {
 	if temporality, exists := m.TemporalityMap[metricName]; exists {
 		return temporality, nil
 	}
@@ -273,7 +273,7 @@ func (m *MockMetadataStore) FetchTemporality(ctx context.Context, metricName str
 }
 
 // FetchTemporalityMulti fetches the temporality for multiple metrics
-func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, error) {
+func (m *MockMetadataStore) FetchTemporalityMulti(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string]metrictypes.Temporality, error) {
 	result := make(map[string]metrictypes.Temporality)
 
 	for _, metricName := range metricNames {

tests/integration/fixtures/querier.py

@@ -52,7 +52,7 @@ def build_builder_query(
     time_aggregation: str,
     space_aggregation: str,
     *,
-    temporality: str = "cumulative",
+    temporality: Optional[str] = None,
     step_interval: int = DEFAULT_STEP_INTERVAL,
     group_by: Optional[List[str]] = None,
     filter_expression: Optional[str] = None,
@@ -65,7 +65,6 @@ def build_builder_query(
         "aggregations": [
             {
                 "metricName": metric_name,
-                "temporality": temporality,
                 "timeAggregation": time_aggregation,
                 "spaceAggregation": space_aggregation,
             }
@@ -73,6 +72,8 @@ def build_builder_query(
         "stepInterval": step_interval,
         "disabled": disabled,
     }
+    if temporality:
+        spec["aggregations"][0]["temporality"] = temporality
 
     if group_by:
         spec["groupBy"] = [

tests/integration/src/querier/07_metrics_multi_temporality.py

@@ -0,0 +1,399 @@
+"""
+Look at the multi_temporality_counters_1h.jsonl file for the relevant data
+"""
+
+import os
+from datetime import datetime, timedelta, timezone
+from http import HTTPStatus
+import random
+from typing import Any, Callable, List
+import pytest
+
+from fixtures import types
+from fixtures.auth import USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD
+from fixtures.metrics import Metrics
+from fixtures.querier import (
+    build_builder_query,
+    get_all_series,
+    get_series_values,
+    make_query_request,
+)
+from fixtures.utils import get_testdata_file_path
+
+MULTI_TEMPORALITY_FILE = get_testdata_file_path("multi_temporality_counters_1h.jsonl")
+MULTI_TEMPORALITY_FILE_10h = get_testdata_file_path("multi_temporality_counters_10h.jsonl")
+MULTI_TEMPORALITY_FILE_24h = get_testdata_file_path("multi_temporality_counters_24h.jsonl")
+
+@pytest.mark.parametrize(
+    "time_aggregation, expected_value_at_31st_minute, expected_value_at_32nd_minute, steady_value",
+    [
+        ("rate", 0.0167, 0.133, 0.0833),
+        ("increase", 2, 8, 5),
+    ],
+)
+def test_with_steady_values_and_reset(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_aggregation: str,
+    expected_value_at_31st_minute: float,
+    expected_value_at_32nd_minute: float,
+    steady_value: float
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_{time_aggregation}_stale"
+
+    metrics = Metrics.load_from_file(
+        MULTI_TEMPORALITY_FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_aggregation,
+        "sum",
+        filter_expression='endpoint = "/orders"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) >= 59
+    # the counter reset happened at 31st minute
+    assert (
+        result_values[30]["value"] == expected_value_at_31st_minute
+    )
+    assert (
+        result_values[31]["value"] == expected_value_at_32nd_minute
+    )
+    assert (
+        result_values[39]["value"] == steady_value
+    ) # 39th minute is when cumulative shifts to delta
+    count_of_steady_rate = sum(1 for v in result_values if v["value"] == steady_value)
+    assert (
+        count_of_steady_rate >= 56
+    )  # 59 - (1 reset + 1 high rate + 1 at the beginning)
+    # All rates should be non-negative (stale periods = 0 rate)
+    for v in result_values:
+        assert v["value"] >= 0, f"{time_aggregation} should not be negative: {v['value']}"
+
+@pytest.mark.parametrize(
+    "time_aggregation, stable_health_value, stable_products_value, stable_checkout_value, spike_checkout_value, stable_orders_value, spike_users_value",
+    [
+        ("rate", 0.167, 0.333, 0.0167, 0.833, 0.0833, 0.0167),
+        ("increase", 10, 20, 1, 50, 5, 1),
+    ],
+)
+def test_group_by_endpoint(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_aggregation: str,
+    stable_health_value: float,
+    stable_products_value: float,
+    stable_checkout_value: float,
+    spike_checkout_value: float,
+    stable_orders_value: float,
+    spike_users_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_{time_aggregation}_groupby"
+
+    metrics = Metrics.load_from_file(
+        MULTI_TEMPORALITY_FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_aggregation,
+        "sum",
+        group_by=["endpoint"],
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    all_series = get_all_series(data, "A")
+    # Should have 5 different endpoints
+    assert (
+        len(all_series) == 5
+    ), f"Expected 5 series for 5 endpoints, got {len(all_series)}"
+
+    # endpoint -> values
+    endpoint_values = {}
+    for series in all_series:
+        endpoint = series.get("labels", [{}])[0].get("value", "unknown")
+        values = sorted(series.get("values", []), key=lambda x: x["timestamp"])
+        endpoint_values[endpoint] = values
+
+    expected_endpoints = {"/products", "/health", "/checkout", "/orders", "/users"}
+    assert (
+        set(endpoint_values.keys()) == expected_endpoints
+    ), f"Expected endpoints {expected_endpoints}, got {set(endpoint_values.keys())}"
+
+    # at no point rate should be negative
+    for endpoint, values in endpoint_values.items():
+        for v in values:
+            assert (
+                v["value"] >= 0
+            ), f"Rate for {endpoint} should not be negative: {v['value']}"
+
+    # /health: 60 data points (t01-t60), steady +10/min
+    health_values = endpoint_values["/health"]
+    assert (
+        len(health_values) >= 58
+    ), f"Expected >= 58 values for /health, got {len(health_values)}"
+    count_steady_health = sum(1 for v in health_values if v["value"] == stable_health_value) 
+    assert (
+        count_steady_health >= 57
+    ), f"Expected >= 57 steady rate values ({stable_health_value}) for /health, got {count_steady_health}"
+    # all /health rates should be state except possibly first/last due to boundaries
+    for v in health_values[1:-1]:
+        assert v["value"] == stable_health_value, f"Expected /health rate {stable_health_value}, got {v['value']}"
+
+    # /products: 51 data points with 10-minute gap (t20-t29 missing), steady +20/min
+    products_values = endpoint_values["/products"]
+    assert (
+        len(products_values) >= 49
+    ), f"Expected >= 49 values for /products, got {len(products_values)}"
+    count_steady_products = sum(1 for v in products_values if v["value"] == stable_products_value)
+
+    # most values should be stable, some boundary values differ due to 10-min gap
+    assert (
+        count_steady_products >= 46
+    ), f"Expected >= 46 steady rate values ({stable_products_value}) for /products, got {count_steady_products}"
+
+    # check that non-stable values are due to gap averaging (should be lower)
+    gap_boundary_values = [v["value"] for v in products_values if v["value"] != stable_products_value]
+    for val in gap_boundary_values:
+        assert (
+            0 < val < stable_products_value
+        ), f"Gap boundary values should be between 0 and {stable_products_value}, got {val}"
+
+    # /checkout: 61 data points (t00-t60), +1/min normal, +50/min spike at t40-t44
+    checkout_values = endpoint_values["/checkout"]
+    assert (
+        len(checkout_values) >= 59
+    ), f"Expected >= 59 values for /checkout, got {len(checkout_values)}"
+    count_steady_checkout = sum(1 for v in checkout_values if v["value"] == stable_checkout_value)
+    assert (
+        count_steady_checkout >= 53
+    ), f"Expected >= 53 steady {time_aggregation} values ({stable_checkout_value}) for /checkout, got {count_steady_checkout}"
+    # check that spike values exist (traffic spike +50/min at t40-t44)
+    count_spike_checkout = sum(1 for v in checkout_values if v["value"] == spike_checkout_value)
+    assert (
+        count_spike_checkout >= 4
+    ), f"Expected >= 4 spike {time_aggregation} values ({spike_checkout_value}) for /checkout, got {count_spike_checkout}"
+
+    # spike values should be consecutive
+    spike_indices = [
+        i for i, v in enumerate(checkout_values) if v["value"] == spike_checkout_value
+    ]
+    assert len(spike_indices) >= 4, f"Expected >= 4 spike indices, got {spike_indices}"
+    # consecutiveness
+    for i in range(1, len(spike_indices)):
+        assert (
+            spike_indices[i] == spike_indices[i - 1] + 1
+        ), f"Spike indices should be consecutive, got {spike_indices}"
+
+    # /orders: 60 data points (t00-t60) with gap at t30, counter reset at t31 (150->2)
+    # reset at t31 causes: rate/increase at t30 includes gap (lower), t31 has high rate after reset
+    orders_values = endpoint_values["/orders"]
+    assert (
+        len(orders_values) >= 58
+    ), f"Expected >= 58 values for /orders, got {len(orders_values)}"
+    count_steady_orders = sum(1 for v in orders_values if v["value"] == stable_orders_value)
+    assert (
+        count_steady_orders >= 55
+    ), f"Expected >= 55 steady {time_aggregation} values ({stable_orders_value}) for /orders, got {count_steady_orders}"
+    # check for counter reset effects - there should be some non-standard values
+    non_standard_orders = [v["value"] for v in orders_values if v["value"] != stable_orders_value]
+    assert (
+        len(non_standard_orders) >= 2
+    ), f"Expected >= 2 non-standard values due to counter reset, got {non_standard_orders}"
+    # post-reset value should be higher (new counter value / interval)
+    high_rate_orders = [v for v in non_standard_orders if v > stable_orders_value]
+    assert (
+        len(high_rate_orders) >= 1
+    ), f"Expected at least one high {time_aggregation} value after counter reset, got {non_standard_orders}"
+
+    # /users: 56 data points (t05-t60), sparse +1 every 5 minutes
+    users_values = endpoint_values["/users"]
+    assert (
+        len(users_values) >= 54
+    ), f"Expected >= 54 values for /users, got {len(users_values)}"
+    count_zero_users = sum(1 for v in users_values if v["value"] == 0)
+    # most values should be 0 (flat periods between increments)
+    assert (
+        count_zero_users >= 40
+    ), f"Expected >= 40 zero {time_aggregation} values for /users (sparse data), got {count_zero_users}"
+    # non-zero values should be 0.0167 (1/60 increment rate)
+    non_zero_users = [v["value"] for v in users_values if v["value"] != 0]
+    count_increment_rate = sum(1 for v in non_zero_users if v == spike_users_value)
+    assert (
+        count_increment_rate >= 8
+    ), f"Expected >= 8 increment {time_aggregation} values ({spike_users_value}) for /users, got {count_increment_rate}"
+
+@pytest.mark.parametrize(
+    "time_aggregation, expected_value_at_30th_minute, expected_value_at_31st_minute, value_at_switch",
+    [
+        ("rate", 0.183, 0.183, 0.25),
+        ("increase", 11, 12, 15),
+    ],
+)
+def test_for_service_with_switch(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_aggregation: str,
+    expected_value_at_30th_minute: float,
+    expected_value_at_31st_minute: float,
+    value_at_switch: float
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(minutes=65)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_{time_aggregation}_count"
+
+    metrics = Metrics.load_from_file(
+        MULTI_TEMPORALITY_FILE,
+        base_time=now - timedelta(minutes=60),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_aggregation,
+        "sum",
+        filter_expression='service = "api"',
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    assert len(result_values) >= 60
+    assert (
+        result_values[30]["value"] == expected_value_at_30th_minute #0.183
+    ) 
+    assert (
+        result_values[31]["value"] == expected_value_at_31st_minute # 0.183
+    )
+    assert (
+        result_values[38]["value"] == value_at_switch # 0.25
+    ) 
+    assert (
+        result_values[39]["value"] == value_at_switch # 0.25
+    ) # 39th minute is when cumulative shifts to delta
+    # All rates should be non-negative (stale periods = 0 rate)
+    for v in result_values:
+        assert v["value"] >= 0, f"{time_aggregation} should not be negative: {v['value']}"
+
+@pytest.mark.parametrize(
+    "time_aggregation, expected_value",
+    [
+        ("rate", 0.0122),
+        ("increase", 22),
+    ],
+)
+def test_for_week_long_time_range(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_aggregation: str,
+    expected_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(days=7)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_{time_aggregation}_" + hex(random.getrandbits(32))[2:]
+
+    metrics = Metrics.load_from_file(
+        MULTI_TEMPORALITY_FILE_10h,
+        base_time=now - timedelta(minutes=600),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_aggregation,
+        "sum",
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    # the zeroth value may not cover the whole time range
+    for value in result_values[1:]:
+        assert value["value"] == expected_value
+
+@pytest.mark.parametrize(
+    "time_aggregation, expected_value",
+    [
+        ("rate", 0.0122),
+        ("increase", 110),
+    ],
+)
+def test_for_month_long_time_range(
+    signoz: types.SigNoz,
+    create_user_admin: None,  # pylint: disable=unused-argument
+    get_token: Callable[[str, str], str],
+    insert_metrics: Callable[[List[Metrics]], None],
+    time_aggregation: str,
+    expected_value: float,
+) -> None:
+    now = datetime.now(tz=timezone.utc).replace(second=0, microsecond=0)
+    start_ms = int((now - timedelta(days=31)).timestamp() * 1000)
+    end_ms = int(now.timestamp() * 1000)
+    metric_name = f"test_{time_aggregation}_" + hex(random.getrandbits(32))[2:]
+
+    metrics = Metrics.load_from_file(
+        MULTI_TEMPORALITY_FILE_24h,
+        base_time=now - timedelta(minutes=1441),
+        metric_name_override=metric_name,
+    )
+    insert_metrics(metrics)
+
+    token = get_token(USER_ADMIN_EMAIL, USER_ADMIN_PASSWORD)
+    query = build_builder_query(
+        "A",
+        metric_name,
+        time_aggregation,
+        "sum",
+    )
+
+    response = make_query_request(signoz, token, start_ms, end_ms, [query])
+    assert response.status_code == HTTPStatus.OK
+    data = response.json()
+    result_values = sorted(get_series_values(data, "A"), key=lambda x: x["timestamp"])
+    ## the zeroth and last values may not cover the whole 9000 seconds
+    for value in result_values[1:-1]:
+        assert value["value"] == expected_value

tests/integration/testdata/multi_temporality_counters_10h.jsonl

@@ -0,0 +1,84 @@
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