Google Cloud Run para Anthos

Documentos > Integraciones > Google Cloud Run para Anthos

Información general

Google Cloud Run para Anthos es una plataforma de desarrollo serverless flexible para entornos híbridos y multinube. Cloud Run para Anthos es la oferta Knative gestionada y totalmente soportada de Google. Si utilizas Google Cloud totalmente gestionado, consulta la documentación de Google Cloud Run.

Utiliza la integración de Google Cloud Platform con Datadog para recopilar métricas de Google Cloud Run para Anthos.

Configuración

Recopilación de métricas

Instalación

Si aún no lo has hecho, configura la integración de Google Cloud Platform.

Si ya autenticas tus servicios Cloud Run para Anthos utilizando Workload Identity, entonces no es necesario realizar más pasos.

Si no has habilitado Workload Identity, debes migrar para utilizar Workload Identity y empezar a recopilar métricas de Knative. Esto implica vincular una cuenta de servicio de Kubernetes a una cuenta de servicio de Google y configurar cada servicio del que quieres recopilar métricas para que utilice Workload Identity.

Para obtener instrucciones detalladas de configuración, consulta Google Cloud Workload Identity.

APM

Google Cloud Run para Anthos expone logs de servicios. Los logs de Google Cloud Run pueden recopilarse con Google Cloud Logging y enviarse a una tarea de Dataflow a través de un tema Cloud Pub/Sub. Si aún no lo has hecho, configura la generación de logs con la plantilla Dataflow de Datadog.

Una vez hecho esto, exporta tus logs de Google Cloud Run de Google Cloud Logging al tema Pub/Sub:

Ve a [Cloud Run for Anthos]]7, haz clic en los servicios elegidos y ve a la pestaña Logs.
Haz clic en View in Logs Explorer (Ver en el Explorador de logs) para ir a la Página de generación de logs de Google Cloud.
Haz clic en Create sink (Crear sumidero) y asigna al sumidero el nombre correspondiente.
Elige “Cloud Pub/Sub” como destino y selecciona el tema Pub/Sub creado para tal fin. Nota: El tema Pub/Sub puede encontrarse en un proyecto diferente.
{< img src=“integrations/google_cloud_pubsub/creating_sink2.png” alt=“Exportar logs de Google Cloud Pub/Sub a Pub Sub” >}}
Haz clic en Create (Crear) y espera a que aparezca el mensaje de confirmación.

Rastreo y métricas personalizadas

Utiliza el Controlador de admisión de Datadog para configurar rastreadores APM y clientes DogStatsD automáticamente. Inyecta las variables de entorno DD_AGENT_HOST y DD_ENTITY_ID utilizando uno de los siguientes métodos:

Añade la etiqueta (label) admission.datadoghq.com/enabled: "true" a tu pod.
Configura el Controlador de admisión del Cluster Agent definiendo mutateUnlabelled: true.

Para evitar que los pods reciban variables de entorno, añade la etiqueta admission.datadoghq.com/enabled: "false". Esto funciona incluso si defines mutateUnlabelled: true. Para obtener más información, consulta la documentación del Controlador de admisión de Datadog.

Datos recopilados

Métricas

gcp.knative.eventing.broker.event_count (count)	Number of events received by a broker.
gcp.knative.eventing.trigger.event_count (count)	Number of events received by a trigger.
gcp.knative.eventing.trigger.event_dispatch_latencies.avg (gauge)	Average of time spent dispatching an event to a trigger subscriber. Shown as millisecond
gcp.knative.eventing.trigger.event_dispatch_latencies.p99 (gauge)	99th percentile of time spent dispatching an event to a trigger subscriber. Shown as millisecond
gcp.knative.eventing.trigger.event_dispatch_latencies.p95 (gauge)	95th percentile of time spent dispatching an event to a trigger subscriber. Shown as millisecond
gcp.knative.eventing.trigger.event_processing_latencies.avg (gauge)	Average of time spent processing an event before it is dispatched to a trigger subscriber. Shown as millisecond
gcp.knative.eventing.trigger.event_processing_latencies.p99 (gauge)	99th percentile of time spent processing an event before it is dispatched to a trigger subscriber. Shown as millisecond
gcp.knative.eventing.trigger.event_processing_latencies.p95 (gauge)	95th percentile of time spent processing an event before it is dispatched to a trigger subscriber. Shown as millisecond
gcp.knative.serving.activator.request_count (count)	The number of requests that are routed to the activator. Shown as request
gcp.knative.serving.activator.request_latencies.avg (gauge)	Average of service request times in milliseconds for requests that go through the activator. Shown as millisecond
gcp.knative.serving.activator.request_latencies.p99 (gauge)	99th percentile of service request times in milliseconds for requests that go through the activator. Shown as millisecond
gcp.knative.serving.activator.request_latencies.p95 (gauge)	95th percentile of service request times in milliseconds for requests that go through the activator. Shown as millisecond
gcp.knative.serving.autoscaler.actual_pods (gauge)	Number of pods that are allocated currently.
gcp.knative.serving.autoscaler.desired_pods (gauge)	Number of pods autoscaler wants to allocate.
gcp.knative.serving.autoscaler.panic_mode (gauge)	Set to 1 if autoscaler is in panic mode for the revision, otherwise 0.
gcp.knative.serving.autoscaler.panic_request_concurrency (gauge)	Average requests concurrency observed per pod during the shorter panic autoscaling window. Shown as request
gcp.knative.serving.autoscaler.requested_pods (gauge)	Number of pods autoscaler requested from Kubernetes.
gcp.knative.serving.autoscaler.stable_request_concurrency (gauge)	Average requests concurrency observed per pod during the stable autoscaling window. Shown as request
gcp.knative.serving.autoscaler.target_concurrency_per_pod (gauge)	The desired average requests concurrency per pod during the stable autoscaling window. Shown as request
gcp.knative.serving.revision.request_count (count)	The number of requests reaching the revision. Shown as request
gcp.knative.serving.revision.request_latencies.avg (gauge)	Average of service request times in milliseconds for requests reaching the revision. Shown as millisecond
gcp.knative.serving.revision.request_latencies.p99 (gauge)	99th percentile of service request times in milliseconds for requests reaching the revision. Shown as millisecond
gcp.knative.serving.revision.request_latencies.p95 (gauge)	95th percentile of service request times in milliseconds for requests reaching the revision. Shown as millisecond