Merge branch 'main' into nv/6175

feat(onboarding): add Docker support for apm data sources, Convex and simplify PHP flow (#10261 )
* feat(onboarding): add Docker support for apm data sources, Convex and simplify PHP flow - Add Convex logo asset for integration branding - Add Docker deployment options for Java frameworks (Spring Boot, Tomcat, JBoss, Quarkus) - Update JBoss configuration to include WildFly support and associated keywords - Restructure PHP onboarding flow to prioritize environment selection over framework - Update Java keywords to include JDBC and remove deprecated metrics tag * chore: remove 'angular' from related keywords in the onboarding configuration
2026-02-10 19:52:06 +00:00 · 2026-02-10 18:31:57 +05:30 · 2026-02-10 18:23:24 +05:30 · 2026-02-10 18:06:20 +05:30 · 2026-02-10 12:35:31 +00:00 · 2026-02-10 17:44:20 +05:30
15 changed files with 1285 additions and 319 deletions
--- a/frontend/public/Logos/convex-logo.svg
+++ b/frontend/public/Logos/convex-logo.svg
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="184" height="188" fill="none" viewBox="0 0 184 188"><path fill="#f3b01c" d="M108.092 130.021c18.166-2.018 35.293-11.698 44.723-27.854-4.466 39.961-48.162 65.218-83.83 49.711-3.286-1.425-6.115-3.796-8.056-6.844-8.016-12.586-10.65-28.601-6.865-43.135 10.817 18.668 32.81 30.111 54.028 28.122"/><path fill="#8d2676" d="M53.401 90.174c-7.364 17.017-7.682 36.94 1.345 53.336-31.77-23.902-31.423-75.052-.388-98.715 2.87-2.187 6.282-3.485 9.86-3.683 14.713-.776 29.662 4.91 40.146 15.507-21.3.212-42.046 13.857-50.963 33.555"/><path fill="#ee342f" d="M114.637 61.855C103.89 46.87 87.069 36.668 68.639 36.358c35.625-16.17 79.446 10.047 84.217 48.807.444 3.598-.139 7.267-1.734 10.512-6.656 13.518-18.998 24.002-33.42 27.882 10.567-19.599 9.263-43.544-3.065-61.704"/></svg>
--- a/frontend/src/container/OnboardingV2Container/onboarding-configs/onboarding-config-with-links.json
+++ b/frontend/src/container/OnboardingV2Container/onboarding-configs/onboarding-config-with-links.json
@@ -323,7 +323,6 @@
 			"java instrumentation",
 			"java k8s",
 			"java logs",
-			"java metrics",
 			"java microservices",
 			"java monitoring",
 			"java observability",
@@ -332,10 +331,12 @@
 			"java vm",
 			"java windows",
 			"jboss",
+			"wildfly",
 			"jdk 11",
 			"jdk 17",
 			"jdk 21",
 			"jdk 8",
+			"jdbc",
 			"opentelemetry java",
 			"quarkus",
 			"spring boot",
@@ -372,6 +373,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-springboot/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-springboot/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -403,6 +410,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-tomcat/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-tomcat/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -414,7 +427,7 @@
 				},
 				{
 					"key": "jboss",
-					"label": "JBoss",
+					"label": "JBoss/WildFly",
 					"imgUrl": "/Logos/jboss.svg",
 					"link": "/docs/instrumentation/opentelemetry-jboss/",
 					"question": {
@@ -434,6 +447,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-jboss/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-jboss/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -465,6 +484,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-quarkus/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-quarkus/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -495,6 +520,18 @@
 								"label": "Kubernetes",
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-java/"
+							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-java/"
+							},
+							{
+								"key": "windows",
+								"label": "Windows",
+								"imgUrl": "/Logos/windows.svg",
+								"link": "/docs/instrumentation/opentelemetry-java/"
 							}
 						]
 					}
@@ -530,7 +567,6 @@
 			"python in containers",
 			"python instrumentation",
 			"python k8s",
-			"python metrics",
 			"python microservices",
 			"python observability",
 			"python on kubernetes",
@@ -583,7 +619,6 @@
 		],
 		"module": "apm",
 		"relatedSearchKeywords": [
-			"angular",
 			"apm",
 			"apm/traces",
 			"application performance monitoring",
@@ -595,7 +630,6 @@
 			"next.js",
 			"nodejs",
 			"nuxtjs",
-			"reactjs",
 			"traces",
 			"tracing",
 			"ts",
@@ -610,8 +644,8 @@
 			"entityID": "framework",
 			"options": [
 				{
-					"key": "nodejs",
-					"label": "NodeJs",
+					"key": "nodejs-nestjs",
+					"label": "NodeJs/NestJS",
 					"imgUrl": "/Logos/nodejs.svg",
 					"link": "/docs/instrumentation/opentelemetry-javascript/",
 					"question": {
@@ -631,6 +665,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-javascript/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-javascript/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -640,99 +680,6 @@
 						]
 					}
 				},
-				{
-					"key": "express",
-					"label": "Express",
-					"imgUrl": "/Logos/express.svg",
-					"link": "/docs/instrumentation/opentelemetry-express/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/opentelemetry-express/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/opentelemetry-express/"
-							},
-							{
-								"key": "windows",
-								"label": "Windows",
-								"imgUrl": "/Logos/windows.svg",
-								"link": "/docs/instrumentation/opentelemetry-express/"
-							}
-						]
-					}
-				},
-				{
-					"key": "nestjs",
-					"label": "NestJS",
-					"imgUrl": "/Logos/nestjs.svg",
-					"link": "/docs/instrumentation/opentelemetry-nestjs/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/opentelemetry-nestjs/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/opentelemetry-nestjs/"
-							},
-							{
-								"key": "windows",
-								"label": "Windows",
-								"imgUrl": "/Logos/windows.svg",
-								"link": "/docs/instrumentation/opentelemetry-nestjs/"
-							}
-						]
-					}
-				},
-				{
-					"key": "angular",
-					"label": "Angular",
-					"imgUrl": "/Logos/angular.svg",
-					"link": "/docs/instrumentation/opentelemetry-angular/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/opentelemetry-angular/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/opentelemetry-angular/"
-							},
-							{
-								"key": "windows",
-								"label": "Windows",
-								"imgUrl": "/Logos/windows.svg",
-								"link": "/docs/instrumentation/opentelemetry-angular/"
-							}
-						]
-					}
-				},
 				{
 					"key": "nextjs",
 					"label": "NextJS",
@@ -755,6 +702,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-nextjs/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-nextjs/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -764,37 +717,6 @@
 						]
 					}
 				},
-				{
-					"key": "reactjs",
-					"label": "ReactJS",
-					"imgUrl": "/Logos/reactjs.svg",
-					"link": "/docs/instrumentation/opentelemetry-reactjs/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/opentelemetry-reactjs/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/opentelemetry-reactjs/"
-							},
-							{
-								"key": "windows",
-								"label": "Windows",
-								"imgUrl": "/Logos/windows.svg",
-								"link": "/docs/instrumentation/opentelemetry-reactjs/"
-							}
-						]
-					}
-				},
 				{
 					"key": "nuxtjs",
 					"label": "NuxtJS",
@@ -817,6 +739,12 @@
 								"imgUrl": "/Logos/kubernetes.svg",
 								"link": "/docs/instrumentation/opentelemetry-nuxtjs/"
 							},
+							{
+								"key": "docker",
+								"label": "Docker",
+								"imgUrl": "/Logos/docker.svg",
+								"link": "/docs/instrumentation/opentelemetry-nuxtjs/"
+							},
 							{
 								"key": "windows",
 								"label": "Windows",
@@ -830,32 +758,7 @@
 					"key": "react-native",
 					"label": "React Native",
 					"imgUrl": "/Logos/reactjs.svg",
-					"link": "/docs/instrumentation/opentelemetry-react-native/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/opentelemetry-react-native/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/opentelemetry-react-native/"
-							},
-							{
-								"key": "windows",
-								"label": "Windows",
-								"imgUrl": "/Logos/windows.svg",
-								"link": "/docs/instrumentation/opentelemetry-react-native/"
-							}
-						]
-					}
+					"link": "/docs/instrumentation/opentelemetry-react-native/"
 				}
 			]
 		}
@@ -889,7 +792,6 @@
 			"golang",
 			"golang apm",
 			"golang instrumentation",
-			"golang metrics",
 			"golang observability",
 			"golang performance monitoring",
 			"golang tracing",
@@ -980,69 +882,39 @@
 			"php-fpm monitoring",
 			"slim php",
 			"traces",
-			"tracing"
+			"tracing",
+			"wordpress"
 		],
 		"id": "php",
+		"link": "/docs/instrumentation/opentelemetry-php/",
 		"question": {
-			"desc": "Which PHP framework do you use?",
+			"desc": "What is your Environment?",
 			"type": "select",
-			"entityID": "framework",
+			"entityID": "environment",
 			"options": [
 				{
-					"key": "laravel",
-					"label": "Laravel",
-					"imgUrl": "/Logos/laravel.svg",
-					"link": "/docs/instrumentation/laravel/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/laravel/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/laravel/"
-							}
-						]
-					}
+					"key": "vm",
+					"label": "VM",
+					"imgUrl": "/Logos/vm.svg",
+					"link": "/docs/instrumentation/opentelemetry-php/"
 				},
 				{
-					"key": "Others",
-					"label": "Others",
-					"imgUrl": "/Logos/php-others.svg",
-					"link": "/docs/instrumentation/opentelemetry-php/",
-					"question": {
-						"desc": "What is your Environment?",
-						"type": "select",
-						"entityID": "environment",
-						"options": [
-							{
-								"key": "vm",
-								"label": "VM",
-								"imgUrl": "/Logos/vm.svg",
-								"link": "/docs/instrumentation/opentelemetry-php/"
-							},
-							{
-								"key": "k8s",
-								"label": "Kubernetes",
-								"imgUrl": "/Logos/kubernetes.svg",
-								"link": "/docs/instrumentation/opentelemetry-php/"
-							},
-							{
-								"key": "windows",
-								"label": "Windows",
-								"imgUrl": "/Logos/windows.svg",
-								"link": "/docs/instrumentation/opentelemetry-php/"
-							}
-						]
-					}
+					"key": "k8s",
+					"label": "Kubernetes",
+					"imgUrl": "/Logos/kubernetes.svg",
+					"link": "/docs/instrumentation/opentelemetry-php/"
+				},
+				{
+					"key": "docker",
+					"label": "Docker",
+					"imgUrl": "/Logos/docker.svg",
+					"link": "/docs/instrumentation/opentelemetry-php/"
+				},
+				{
+					"key": "windows",
+					"label": "Windows",
+					"imgUrl": "/Logos/windows.svg",
+					"link": "/docs/instrumentation/opentelemetry-php/"
 				}
 			]
 		}
@@ -1117,6 +989,12 @@
 					"imgUrl": "/Logos/kubernetes.svg",
 					"link": "/docs/instrumentation/opentelemetry-dotnet/"
 				},
+				{
+					"key": "docker",
+					"label": "Docker",
+					"imgUrl": "/Logos/docker.svg",
+					"link": "/docs/instrumentation/opentelemetry-dotnet/"
+				},
 				{
 					"key": "windows",
 					"label": "Windows",
@@ -1128,7 +1006,7 @@
 	},
 	{
 		"dataSource": "ruby-on-rails",
-		"label": "Ruby on Rails",
+		"label": "Ruby",
 		"imgUrl": "/Logos/ruby-on-rails.svg",
 		"tags": [
 			"apm/traces"
@@ -1168,9 +1046,12 @@
 			"ruby tracing",
 			"ruby-on-rails",
 			"traces",
-			"tracing"
+			"tracing",
+			"sinatra",
+			"sidekiq",
+			"resque"
 		],
-		"id": "ruby-on-rails",
+		"id": "ruby",
 		"link": "/docs/instrumentation/opentelemetry-ruby-on-rails/",
 		"question": {
 			"desc": "What is your Environment?",
@@ -1189,6 +1070,12 @@
 					"imgUrl": "/Logos/kubernetes.svg",
 					"link": "/docs/instrumentation/opentelemetry-ruby-on-rails/"
 				},
+				{
+					"key": "docker",
+					"label": "Docker",
+					"imgUrl": "/Logos/docker.svg",
+					"link": "/docs/instrumentation/opentelemetry-ruby-on-rails/"
+				},
 				{
 					"key": "windows",
 					"label": "Windows",
@@ -1468,41 +1355,6 @@
 		"id": "nginx-tracing",
 		"link": "/docs/instrumentation/opentelemetry-nginx/"
 	},
-	{
-		"dataSource": "opentelemetry-wordpress",
-		"label": "WordPress",
-		"imgUrl": "/Logos/wordpress.svg",
-		"tags": [
-			"apm/traces"
-		],
-		"module": "apm",
-		"relatedSearchKeywords": [
-			"apm",
-			"apm/traces",
-			"application performance monitoring",
-			"monitor wordpress site",
-			"opentelemetry",
-			"opentelemetry wordpress",
-			"opentelemetry-wordpress",
-			"otel",
-			"otel wordpress",
-			"traces",
-			"tracing",
-			"wordpress",
-			"wordpress apm",
-			"wordpress instrumentation",
-			"wordpress metrics",
-			"wordpress monitoring",
-			"wordpress observability",
-			"wordpress performance",
-			"wordpress php monitoring",
-			"wordpress plugin monitoring",
-			"wordpress to signoz",
-			"wordpress tracing"
-		],
-		"id": "opentelemetry-wordpress",
-		"link": "/docs/instrumentation/opentelemetry-wordpress/"
-	},
 	{
 		"dataSource": "opentelemetry-cloudflare",
 		"label": "Cloudflare Tracing",
@@ -1567,6 +1419,25 @@
 		"id": "opentelemetry-cloudflare-logs",
 		"link": "/docs/logs-management/send-logs/cloudflare-logs/"
 	},
+	{
+		"dataSource": "convex-logs",
+		"label": "Convex Logs",
+		"imgUrl": "/Logos/convex-logo.svg",
+		"tags": [
+			"logs"
+		],
+		"module": "logs",
+		"relatedSearchKeywords": [
+			"convex",
+			"convex log streaming",
+			"convex logs",
+			"convex webhook",
+			"logging",
+			"logs"
+		],
+		"id": "convex-logs",
+		"link": "/docs/logs-management/send-logs/convex-log-streams-signoz/"
+	},
 	{
 		"dataSource": "kubernetes-pod-logs",
 		"label": "Kubernetes Pod Logs",
@@ -4568,6 +4439,7 @@
 		],
 		"module": "metrics",
 		"relatedSearchKeywords": [
+			"browser metrics",
 			"core web vitals metrics",
 			"frontend metrics",
 			"frontend monitoring",
@@ -4587,7 +4459,7 @@
 			"svelte",
 			"sveltekit",
 			"nextjs",
-"next.js"
+			"next.js"
 		],
 		"link": "/docs/frontend-monitoring/web-vitals-with-metrics/"
 	},
@@ -4622,7 +4494,7 @@
 			"svelte",
 			"sveltekit",
 			"nextjs",
-"next.js"
+			"next.js"
 		],
 		"link": "/docs/frontend-monitoring/web-vitals-with-traces/"
 	},
@@ -4664,7 +4536,7 @@
 			"svelte",
 			"sveltekit",
 			"nextjs",
-"next.js"
+			"next.js"
 		],
 		"link": "/docs/frontend-monitoring/document-load/"
 	},
@@ -5316,23 +5188,6 @@
 		],
 		"link": "/docs/metrics-management/mysql-metrics/"
 	},
-	{
-		"dataSource": "jvm",
-		"label": "JVM",
-		"imgUrl": "/Logos/java.svg",
-		"tags": [
-			"metrics"
-		],
-		"module": "metrics",
-		"relatedSearchKeywords": [
-			"java virtual machine",
-			"jvm",
-			"jvm metrics",
-			"jvm monitoring",
-			"runtime"
-		],
-		"link": "/docs/tutorial/jvm-metrics/"
-	},
 	{
 		"dataSource": "jmx",
 		"label": "JMX",
@@ -5348,7 +5203,7 @@
 			"jmx monitoring",
 			"runtime"
 		],
-		"link": "/docs/tutorial/jmx-metrics/"
+		"link": "/docs/metrics-management/send-metrics/applications/opentelemetry-java/jmx-metrics/"
 	},
 	{
 		"dataSource": "prometheus-metrics",
@@ -5574,16 +5429,17 @@
 			"svelte",
 			"sveltekit",
 			"nextjs",
-"next.js"
+			"next.js"
 		],
 		"link": "/docs/frontend-monitoring/sending-logs-with-opentelemetry/"
 	},
 	{
 		"dataSource": "frontend-traces",
-		"label": "Frontend Traces",
+		"label": "Frontend Tracing",
 		"imgUrl": "/Logos/traces.svg",
 		"tags": [
-			"Frontend Monitoring"
+			"Frontend Monitoring",
+			"apm/traces"
 		],
 		"module": "apm",
 		"relatedSearchKeywords": [
@@ -5605,7 +5461,7 @@
 			"svelte",
 			"sveltekit",
 			"nextjs",
-"next.js"
+			"next.js"
 		],
 		"link": "/docs/frontend-monitoring/sending-traces-with-opentelemetry/"
 	},
@@ -5636,7 +5492,7 @@
 			"svelte",
 			"sveltekit",
 			"nextjs",
-"next.js"
+			"next.js"
 		],
 		"link": "/docs/frontend-monitoring/sending-metrics-with-opentelemetry/"
 	},
@@ -5683,7 +5539,6 @@
 		"label": "Golang Metrics",
 		"imgUrl": "/Logos/go.svg",
 		"tags": [
-			"apm/traces",
 			"metrics"
 		],
 		"module": "metrics",
@@ -5737,12 +5592,64 @@
 			]
 		}
 	},
+	{
+		"dataSource": "java-metrics",
+		"label": "Java Metrics",
+		"imgUrl": "/Logos/java.svg",
+		"tags": [
+			"metrics"
+		],
+		"module": "metrics",
+		"relatedSearchKeywords": [
+			"java",
+			"java metrics",
+			"java monitoring",
+			"java observability",
+			"jvm metrics",
+			"metrics",
+			"opentelemetry java",
+			"otel java",
+			"runtime metrics"
+		],
+		"id": "java-metrics",
+		"link": "/docs/metrics-management/send-metrics/applications/opentelemetry-java/",
+		"question": {
+			"desc": "What is your Environment?",
+			"type": "select",
+			"entityID": "environment",
+			"options": [
+				{
+					"key": "vm",
+					"label": "VM",
+					"imgUrl": "/Logos/vm.svg",
+					"link": "/docs/metrics-management/send-metrics/applications/opentelemetry-java/"
+				},
+				{
+					"key": "k8s",
+					"label": "Kubernetes",
+					"imgUrl": "/Logos/kubernetes.svg",
+					"link": "/docs/metrics-management/send-metrics/applications/opentelemetry-java/"
+				},
+				{
+					"key": "windows",
+					"label": "Windows",
+					"imgUrl": "/Logos/windows.svg",
+					"link": "/docs/metrics-management/send-metrics/applications/opentelemetry-java/"
+				},
+				{
+					"key": "docker",
+					"label": "Docker",
+					"imgUrl": "/Logos/docker.svg",
+					"link": "/docs/metrics-management/send-metrics/applications/opentelemetry-java/"
+				}
+			]
+		}
+	},
 	{
 		"dataSource": "python-metrics",
 		"label": "Python Metrics",
 		"imgUrl": "/Logos/python.svg",
 		"tags": [
-			"apm/traces",
 			"metrics"
 		],
 		"module": "metrics",
@@ -5796,7 +5703,6 @@
 		"label": ".NET Metrics",
 		"imgUrl": "/Logos/dotnet.svg",
 		"tags": [
-			"apm/traces",
 			"metrics"
 		],
 		"module": "metrics",
@@ -5853,7 +5759,6 @@
 		"label": "Node.js Metrics",
 		"imgUrl": "/Logos/nodejs.svg",
 		"tags": [
-			"apm/traces",
 			"metrics"
 		],
 		"module": "metrics",
--- a/pkg/querier/querier.go
+++ b/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
--- a/pkg/query-service/app/clickhouseReader/reader.go
+++ b/pkg/query-service/app/clickhouseReader/reader.go
@@ -830,7 +830,7 @@ func (r *ClickHouseReader) GetUsage(ctx context.Context, queryParams *model.GetU

 func (r *ClickHouseReader) GetSpansForTrace(ctx context.Context, traceID string, traceDetailsQuery string) ([]model.SpanItemV2, *model.ApiError) {
 	var traceSummary model.TraceSummary
-	summaryQuery := fmt.Sprintf("SELECT * from %s.%s FINAL WHERE trace_id=$1", r.TraceDB, r.traceSummaryTable)
+	summaryQuery := fmt.Sprintf("SELECT trace_id, min(start) AS start, max(end) AS end, sum(num_spans) AS num_spans FROM %s.%s WHERE trace_id=$1 GROUP BY trace_id", r.TraceDB, r.traceSummaryTable)
 	err := r.db.QueryRow(ctx, summaryQuery, traceID).Scan(&traceSummary.TraceID, &traceSummary.Start, &traceSummary.End, &traceSummary.NumSpans)
 	if err != nil {
 		if err == sql.ErrNoRows {
@@ -6458,7 +6458,7 @@ func (r *ClickHouseReader) SearchTraces(ctx context.Context, params *model.Searc
 	}

 	var traceSummary model.TraceSummary
-	summaryQuery := fmt.Sprintf("SELECT * from %s.%s FINAL WHERE trace_id=$1", r.TraceDB, r.traceSummaryTable)
+	summaryQuery := fmt.Sprintf("SELECT trace_id, min(start) AS start, max(end) AS end, sum(num_spans) AS num_spans FROM %s.%s WHERE trace_id=$1 GROUP BY trace_id", r.TraceDB, r.traceSummaryTable)
 	err := r.db.QueryRow(ctx, summaryQuery, params.TraceID).Scan(&traceSummary.TraceID, &traceSummary.Start, &traceSummary.End, &traceSummary.NumSpans)
 	if err != nil {
 		if err == sql.ErrNoRows {
--- a/pkg/telemetrymetadata/metadata.go
+++ b/pkg/telemetrymetadata/metadata.go
@@ -10,6 +10,7 @@ import (
 	"github.com/SigNoz/signoz/pkg/factory"
 	"github.com/SigNoz/signoz/pkg/querybuilder"
 	"github.com/SigNoz/signoz/pkg/telemetrylogs"
+	"github.com/SigNoz/signoz/pkg/telemetrymeter"
 	"github.com/SigNoz/signoz/pkg/telemetrymetrics"
 	"github.com/SigNoz/signoz/pkg/telemetrystore"
 	"github.com/SigNoz/signoz/pkg/telemetrytraces"
@@ -1597,12 +1598,12 @@ 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
 	}
@@ -1615,27 +1616,35 @@ 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
 	}
 	// TODO: return error after table migration are run
-	meterMetricsTemporality, _ := t.fetchMeterSourceMetricsTemporality(ctx, metricNames...)
+	meterMetricsTemporality, _ := t.fetchMeterSourceMetricsTemporality(ctx, queryTimeRangeStartTs, queryTimeRangeEndTs, metricNames...)

 	// 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 {
-			result[metricName] = temporality
+		if temporality, exists := meterMetricsTemporality[metricName]; exists && len(temporality) > 0 {
+			if len(temporality) > 1 {
+				result[metricName] = metrictypes.Multiple
+			} else {
+				result[metricName] = temporality[0]
+			}
 			continue
 		}
 		result[metricName] = metrictypes.Unknown
@@ -1644,8 +1653,10 @@ 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 +1664,18 @@ 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)

@@ -1692,26 +1707,35 @@ 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
 }

-func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporality(ctx context.Context, metricNames ...string) (map[string]metrictypes.Temporality, error) {
-	result := make(map[string]metrictypes.Temporality)
+func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporality(ctx context.Context, queryTimeRangeStartTs, queryTimeRangeEndTs uint64, metricNames ...string) (map[string][]metrictypes.Temporality, error) {
+	result := make(map[string][]metrictypes.Temporality)

 	sb := sqlbuilder.Select(
 		"metric_name",
-		"argMax(temporality, unix_milli) as temporality",
-	).From(t.meterDBName + "." + t.meterFieldsTblName)
+		"temporality",
+	).
+		From(t.meterDBName + "." + t.meterFieldsTblName)

+	adjustedStartTs := telemetrymeter.AdjustStartTsForSamplesTable(queryTimeRangeStartTs, t.meterFieldsTblName)
 	// 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", queryTimeRangeEndTs),
+	)

-	// 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)

@@ -1743,8 +1767,12 @@ func (t *telemetryMetaStore) fetchMeterSourceMetricsTemporality(ctx context.Cont
 			// 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 meter temporality rows")
 	}

 	return result, nil
--- a/pkg/telemetrymeter/tables.go
+++ b/pkg/telemetrymeter/tables.go
@@ -15,6 +15,8 @@ const (
 )

 var (
+	oneHourInMilliseconds  = uint64(time.Hour.Milliseconds() * 1)
+	oneDayInMilliseconds   = uint64(time.Hour.Milliseconds() * 24)
 	oneMonthInMilliseconds = uint64(time.Hour.Milliseconds() * 24 * 30)

 	// when the query requests for almost 1 day, but not exactly 1 day, we need to add an offset to the end time
@@ -57,6 +59,13 @@ func WhichSamplesTableToUse(

 }

+func AdjustStartTsForSamplesTable(start uint64, table string) uint64 {
+	if table == SamplesTableName || table == SamplesLocalTableName {
+		return start - (start % oneHourInMilliseconds)
+	}
+	return start - (start % oneDayInMilliseconds)
+}
+
 func AggregationColumnForSamplesTable(
 	start, end uint64,
 	metricType metrictypes.Type,
--- a/pkg/telemetrymetrics/statement_builder.go
+++ b/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 +534,57 @@ func (b *MetricQueryStatementBuilder) buildTemporalAggCumulativeOrUnspecified(
 	}
 }

+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,
--- a/pkg/types/metrictypes/metrictypes.go
+++ b/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) {
--- a/pkg/types/telemetrytypes/store.go
+++ b/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)
--- a/pkg/types/telemetrytypes/telemetrytypestest/metadata_store.go
+++ b/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 {
--- a/tests/integration/fixtures/querier.py
+++ b/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"] = [
--- a/tests/integration/src/querier/07_metrics_multi_temporality.py
+++ b/tests/integration/src/querier/07_metrics_multi_temporality.py
@@ -0,0 +1,396 @@
+"""
+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, steady_value",
+    [
+        ("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,
+    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}_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[39]["value"] == steady_value # 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=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 and last values may not cover the whole 9000 seconds
+    for value in result_values[1:-1]:
+        assert value["value"] == expected_value
--- a/tests/integration/testdata/multi_temporality_counters_10h.jsonl
+++ b/tests/integration/testdata/multi_temporality_counters_10h.jsonl
@@ -0,0 +1,84 @@
+{"metric_name":"http.request.count","labels":{"__temporality__":"Cumulative","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T10:00:00+00:00","value":10,"temporality":"Cumulative","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Cumulative","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T10:30:00+00:00","value":20,"temporality":"Cumulative","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Cumulative","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T11:00:00+00:00","value":30,"temporality":"Cumulative","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Cumulative","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T11:30:00+00:00","value":40,"temporality":"Cumulative","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T12:00:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T12:30:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T13:00:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T13:30:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T14:00:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T14:30:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T15:00:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T15:30:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T16:00:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
+{"metric_name":"http.request.count","labels":{"__temporality__":"Delta","service":"api","endpoint":"/health","status_code":"200"},"timestamp":"2025-01-10T16:30:00+00:00","value":10,"temporality":"Delta","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
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--- a/tests/integration/testdata/multi_temporality_counters_24h.jsonl
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Author	SHA1	Message	Date
Naman Verma	799a4d896e	Merge branch 'main' into nv/6175	2026-02-10 18:31:57 +05:30
Vishal Sharma	a3bd72ad86	feat(onboarding): add Docker support for apm data sources, Convex and simplify PHP flow (#10261 ) Some checks are pending build-staging / prepare (push) Waiting to run Details build-staging / js-build (push) Blocked by required conditions Details build-staging / go-build (push) Blocked by required conditions Details build-staging / staging (push) Blocked by required conditions Details Release Drafter / update_release_draft (push) Waiting to run Details * feat(onboarding): add Docker support for apm data sources, Convex and simplify PHP flow - Add Convex logo asset for integration branding - Add Docker deployment options for Java frameworks (Spring Boot, Tomcat, JBoss, Quarkus) - Update JBoss configuration to include WildFly support and associated keywords - Restructure PHP onboarding flow to prioritize environment selection over framework - Update Java keywords to include JDBC and remove deprecated metrics tag * chore: remove 'angular' from related keywords in the onboarding configuration	2026-02-10 18:23:24 +05:30
Naman Verma	f6402bf4a3	Merge branch 'main' into nv/6175	2026-02-10 18:06:20 +05:30
Nikhil Soni	786070d90b	refactor: switch group by instead of triggering aggregation (#10263 ) Using FINAL in clickhouse query will trigger the aggregation merge of data while using group by will be more efficient. It's recommended id docs as well - https://clickhouse.com/ docs/engines/table-engines/mergetree-family/ aggregatingmergetree#select-and-insert	2026-02-10 12:35:31 +00:00
Naman Verma	bcf52e4311	fix: incorrect method name fix	2026-02-10 17:44:20 +05:30
Naman Verma	5543bf10fc	fix: check for unknown temporality	2026-02-10 13:58:31 +05:30
Naman Verma	f85b2ff7fd	fix: meter query remove distinct and use adjusted start time	2026-02-10 13:56:29 +05:30
Naman Verma	4b7478f601	Merge branch 'main' into nv/6175	2026-02-10 13:17:26 +05:30
Naman Verma	e5df344587	fix: handle rows.Err() for iteration errors	2026-02-10 12:56:49 +05:30
Naman Verma	012ffbe4b5	fix: use distributed table instead of local	2026-02-10 12:53:09 +05:30
Naman Verma	b11f349800	test: remove Any from enumerate	2026-02-10 11:13:16 +05:30
Naman Verma	723af781af	fix: use adjusted timestamps when fetching temporality	2026-02-10 11:12:57 +05:30
Naman Verma	29198814fd	test: test data fix	2026-02-10 11:06:32 +05:30
Naman Verma	0bac18265b	Merge branch 'main' into nv/6175	2026-02-10 11:04:50 +05:30
Naman Verma	459357ab45	test: missing git add . for file name variable	2026-02-09 23:00:41 +05:30
Naman Verma	f59ecd34da	test: add test for month long duration	2026-02-09 22:57:07 +05:30
Naman Verma	58380a3ae2	test: add test for long duration	2026-02-09 22:28:34 +05:30
Naman Verma	bc96c270b2	fix: use local table like time aggregation cte in statement builder does	2026-02-09 20:29:52 +05:30
Naman Verma	053fc5e83d	feat: remove todo	2026-02-09 18:36:22 +05:30
Naman Verma	dc947a2ad3	fix: use time series table to support custom time ranges. fix column issue seen in long time ranges	2026-02-09 18:34:42 +05:30
Naman Verma	b68219b8bc	feat: check for first time of reporting as well to handle custom time ranges	2026-02-09 17:25:07 +05:30
Naman Verma	db688db875	fix: remove hardcoded value from test	2026-02-09 16:59:29 +05:30
Naman Verma	09cf8ddbf4	test: use pytest.mark.parametrize on new tests	2026-02-09 16:57:20 +05:30
Naman Verma	41449b8d61	test: parametrize similar tests to make it follow DRY	2026-02-09 16:39:51 +05:30
Srikanth Chekuri	ed1b5e78bb	Merge branch 'main' into nv/6175	2026-02-09 15:02:28 +05:30
Naman Verma	6d4fcdf323	test: fix groupby test for increase aggregation scenario	2026-02-09 13:55:00 +05:30
Naman Verma	92a9369752	feat: remove todo	2026-02-09 13:13:07 +05:30
Naman Verma	ca170e6e62	test: integration tests	2026-02-09 13:09:17 +05:30
Naman Verma	23f73371da	feat: no NaN for first entry in series	2026-02-09 13:08:20 +05:30
Naman Verma	660e454dbf	chore: remove comment	2026-02-06 11:52:52 +05:30
Naman Verma	224619bb9e	feat: introduce __multiple__ as a temporality	2026-02-06 11:45:42 +05:30
Naman Verma	b820cf9b81	feat: add support for simultaneous delta and cumulative temporality	2026-02-05 17:06:46 +05:30
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