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frontend/public/Logos/convex-logo.svg
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frontend/public/Logos/convex-logo.svg
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@@ -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>
|
||||
|
After Width: | Height: | Size: 811 B |
@@ -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",
|
||||
|
||||
@@ -247,8 +247,6 @@ func FilterResponse(results []*qbtypes.QueryRangeResponse) []*qbtypes.QueryRange
|
||||
}
|
||||
}
|
||||
resultData.Rows = filteredRows
|
||||
case *qbtypes.ScalarData:
|
||||
resultData.Data = filterScalarDataIPs(resultData.Columns, resultData.Data)
|
||||
}
|
||||
|
||||
filteredData = append(filteredData, result)
|
||||
@@ -274,39 +272,6 @@ func shouldIncludeSeries(series *qbtypes.TimeSeries) bool {
|
||||
return true
|
||||
}
|
||||
|
||||
func filterScalarDataIPs(columns []*qbtypes.ColumnDescriptor, data [][]any) [][]any {
|
||||
// Find column indices for server address fields
|
||||
serverColIndices := make([]int, 0)
|
||||
for i, col := range columns {
|
||||
if col.Name == serverAddressKeyLegacy || col.Name == serverAddressKey {
|
||||
serverColIndices = append(serverColIndices, i)
|
||||
}
|
||||
}
|
||||
|
||||
if len(serverColIndices) == 0 {
|
||||
return data
|
||||
}
|
||||
|
||||
filtered := make([][]any, 0, len(data))
|
||||
for _, row := range data {
|
||||
includeRow := true
|
||||
for _, colIdx := range serverColIndices {
|
||||
if colIdx < len(row) {
|
||||
if strVal, ok := row[colIdx].(string); ok {
|
||||
if net.ParseIP(strVal) != nil {
|
||||
includeRow = false
|
||||
break
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
if includeRow {
|
||||
filtered = append(filtered, row)
|
||||
}
|
||||
}
|
||||
return filtered
|
||||
}
|
||||
|
||||
func shouldIncludeRow(row *qbtypes.RawRow) bool {
|
||||
if row.Data != nil {
|
||||
for _, key := range []string{serverAddressKeyLegacy, serverAddressKey} {
|
||||
|
||||
@@ -116,59 +116,6 @@ func TestFilterResponse(t *testing.T) {
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
name: "should filter out IP addresses from scalar data",
|
||||
input: []*qbtypes.QueryRangeResponse{
|
||||
{
|
||||
Data: qbtypes.QueryData{
|
||||
Results: []any{
|
||||
&qbtypes.ScalarData{
|
||||
QueryName: "endpoints",
|
||||
Columns: []*qbtypes.ColumnDescriptor{
|
||||
{
|
||||
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "net.peer.name"},
|
||||
Type: qbtypes.ColumnTypeGroup,
|
||||
},
|
||||
{
|
||||
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "endpoints"},
|
||||
Type: qbtypes.ColumnTypeAggregation,
|
||||
},
|
||||
},
|
||||
Data: [][]any{
|
||||
{"192.168.1.1", 10},
|
||||
{"example.com", 20},
|
||||
{"10.0.0.1", 5},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
expected: []*qbtypes.QueryRangeResponse{
|
||||
{
|
||||
Data: qbtypes.QueryData{
|
||||
Results: []any{
|
||||
&qbtypes.ScalarData{
|
||||
QueryName: "endpoints",
|
||||
Columns: []*qbtypes.ColumnDescriptor{
|
||||
{
|
||||
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "net.peer.name"},
|
||||
Type: qbtypes.ColumnTypeGroup,
|
||||
},
|
||||
{
|
||||
TelemetryFieldKey: telemetrytypes.TelemetryFieldKey{Name: "endpoints"},
|
||||
Type: qbtypes.ColumnTypeAggregation,
|
||||
},
|
||||
},
|
||||
Data: [][]any{
|
||||
{"example.com", 20},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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 {
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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,
|
||||
|
||||
@@ -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,
|
||||
|
||||
@@ -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) {
|
||||
|
||||
@@ -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)
|
||||
|
||||
@@ -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 {
|
||||
|
||||
@@ -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"] = [
|
||||
|
||||
396
tests/integration/src/querier/07_metrics_multi_temporality.py
Normal file
396
tests/integration/src/querier/07_metrics_multi_temporality.py
Normal file
@@ -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
|
||||
84
tests/integration/testdata/multi_temporality_counters_10h.jsonl
vendored
Normal file
84
tests/integration/testdata/multi_temporality_counters_10h.jsonl
vendored
Normal file
@@ -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":{}}
|
||||
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||||
288
tests/integration/testdata/multi_temporality_counters_1h.jsonl
vendored
Normal file
288
tests/integration/testdata/multi_temporality_counters_1h.jsonl
vendored
Normal file
@@ -0,0 +1,288 @@
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|
||||
196
tests/integration/testdata/multi_temporality_counters_24h.jsonl
vendored
Normal file
196
tests/integration/testdata/multi_temporality_counters_24h.jsonl
vendored
Normal file
@@ -0,0 +1,196 @@
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||||
{"metric_name":"http.request.count","labels":{"__temporality__":"Cumulative","service":"web","endpoint":"/checkout","status_code":"200"},"timestamp":"2025-01-10T23:00:00+00:00","value":47,"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":"web","endpoint":"/checkout","status_code":"200"},"timestamp":"2025-01-10T23:30:00+00:00","value":48,"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":"web","endpoint":"/checkout","status_code":"200"},"timestamp":"2025-01-11T00:00:00+00:00","value":49,"temporality":"Cumulative","type_":"Sum","is_monotonic":true,"flags":0,"description":"","unit":"","env":"default","resource_attrs":{},"scope_attrs":{}}
|
||||
Reference in New Issue
Block a user