Google Cloud Run

Información general

Cloud Run es una plataforma de computación administrada que permite ejecutar contenedores sin estado invocables mediante solicitudes HTTP.

Habilita esta integración e instrumenta tu contenedor para ver todas tus métricas, trazas (traces) y logs de Cloud Run en Datadog.

Para más información sobre Cloud Run para Anthos, consulta la documentación de Google Cloud Run para Anthos.

Configuración

Recopilación de métricas

Instalación

Configura la integración de Google Cloud Platform para empezar a recopilar métricas de forma predefinida. Para configurar métricas personalizadas consulta la documentación serverless .

APM

integración

Google Cloud Run también expone logs de auditoría. Los logs de Google Cloud Run se recopilan con Google Cloud Logging y se envían a un trabajo de Dataflow a través de un tema Cloud Pub/Sub. Si todavía no lo has hecho, configura el registro con la plantilla Datadog Dataflow.

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

  1. Ve a la página de Google Cloud Logging y filtra los logs de Google Cloud Run.

  2. Haz clic en Crear receptor y asigna el nombre correspondiente al receptor.

  3. Elige “Cloud Pub/Sub” como destino y selecciona el tema Pub/Sub creado para tal fin. Nota: El tema Pub/Sub puede estar ubicado en un proyecto diferente.

    Exportar logs de Google Cloud Pub/Sub Logs a Pub Sub
  4. Haz clic en Crear y espera a que aparezca el mensaje de confirmación.

Registro directo

Para más información sobre el registro directo de aplicaciones en Datadog desde tus servicios de Cloud Run, consulta la documentación serverless .

Rastreo

Para obtener más información sobre las instrucciones de configuración especializadas del Agent para Google Cloud Run totalmente administrado, consulta la documentación serverless.

Datos recopilados

Métricas

gcp.run.container.billable_instance_time
(rate)
Billable time aggregated from all container instances of the revision (ms/s).
Shown as millisecond
gcp.run.container.completed_probe_attempt_count
(count)
Number of completed health check probe attempts and their results.
gcp.run.container.completed_probe_count
(count)
Number of completed health check probes and their results.
gcp.run.container.containers
(gauge)
Number of container instances that exist, broken down by state.
gcp.run.container.cpu.allocation_time
(rate)
Container CPU allocation of the revision in seconds.
Shown as core
gcp.run.container.cpu.usage.avg
(gauge)
The average actual container CPU usage in CPU seconds broken down by the metric field, container name.
Shown as second
gcp.run.container.cpu.usage.samplecount
(gauge)
The sample count for actual container CPU usage in CPU seconds broken down by the metric field, container name.
Shown as second
gcp.run.container.cpu.usage.sumsqdev
(gauge)
The sum of squared deviation for actual container CPU usage in CPU seconds broken down by the metric field, container name.
Shown as second
gcp.run.container.cpu.utilizations.avg
(gauge)
The average distribution of container CPU utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.cpu.utilizations.p95
(gauge)
The 95th percentile distribution of container CPU utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.cpu.utilizations.p99
(gauge)
The 99th percentile distribution of container CPU utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.cpu.utilizations.samplecount
(count)
Sample count of the distribution of service request times in milliseconds.
Shown as fraction
gcp.run.container.gpu.memory_usages.avg
(gauge)
The average container GPU memory usage distribution across all container instances.
Shown as byte
gcp.run.container.gpu.memory_usages.samplecount
(gauge)
The sample count for container GPU memory usage distribution across all container instances.
Shown as byte
gcp.run.container.gpu.memory_usages.sumsqdev
(gauge)
The sum of squared deviation for container GPU memory usage distribution across all container instances.
Shown as byte
gcp.run.container.gpu.memory_utilizations.avg
(gauge)
The average container GPU memory utilization distribution across all container instances.
Shown as percent (multiplied by 100)
gcp.run.container.gpu.memory_utilizations.samplecount
(gauge)
The sample count for container GPU memory utilization distribution across all container instances.
Shown as percent (multiplied by 100)
gcp.run.container.gpu.memory_utilizations.sumsqdev
(gauge)
The sum of squared deviation for container GPU memory utilization distribution across all container instances.
Shown as percent (multiplied by 100)
gcp.run.container.gpu.utilizations.avg
(gauge)
The average container GPU utilization distribution across all container instances.
Shown as percent (multiplied by 100)
gcp.run.container.gpu.utilizations.samplecount
(gauge)
The sample count for container GPU utilization distribution across all container instances.
Shown as percent (multiplied by 100)
gcp.run.container.gpu.utilizations.sumsqdev
(gauge)
The sum of squared deviation for container GPU utilization distribution across all container instances.
Shown as percent (multiplied by 100)
gcp.run.container.instance_count
(gauge)
The number of container instances that exist, broken down by state.
Shown as container
gcp.run.container.max_request_concurrencies.avg
(gauge)
Average of the maximum number of concurrent requests being served by each container instance over a minute.
Shown as request
gcp.run.container.max_request_concurrencies.p95
(gauge)
95th percentile distribution of the maximum number of concurrent requests being served by each container instance over a minute.
Shown as request
gcp.run.container.max_request_concurrencies.p99
(gauge)
99th percentile distribution of the maximum number of concurrent requests being served by each container instance over a minute.
Shown as request
gcp.run.container.max_request_concurrencies.samplecount
(count)
Sample count of the distribution of the maximum number of concurrent requests being served by each container instance over a minute.
Shown as request
gcp.run.container.memory.allocation_time
(rate)
Container memory allocation of the revision in Gigabyte-seconds.
Shown as gibibyte
gcp.run.container.memory.usage.avg
(gauge)
The average actual container memory usage in bytes broken down by the metric field, container name.
Shown as byte
gcp.run.container.memory.usage.samplecount
(gauge)
The sample count for actual container memory usage in bytes broken down by the metric field, container name.
Shown as byte
gcp.run.container.memory.usage.sumsqdev
(gauge)
The sum of squared deviation for actual container memory usage in bytes broken down by the metric field, container name.
Shown as byte
gcp.run.container.memory.utilizations.avg
(gauge)
Average of the container memory utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.memory.utilizations.p95
(gauge)
95th percentile distribution of the container memory utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.memory.utilizations.p99
(gauge)
99th percentile distribution of the container memory utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.memory.utilizations.samplecount
(count)
Sample count of the container memory utilization distribution across all container instances of the revision.
Shown as fraction
gcp.run.container.network.received_bytes_count
(count)
The incoming socket and HTTP response traffic of revision, in bytes.
Shown as byte
gcp.run.container.network.sent_bytes_count
(count)
The outgoing socket and HTTP response traffic of revision, in bytes.
Shown as byte
gcp.run.container.network.throttled_inbound_bytes_count
(count)
Inbound bytes dropped due to network throttling.
Shown as byte
gcp.run.container.network.throttled_inbound_packets_count
(count)
Inbound packets dropped due to network throttling.
Shown as byte
gcp.run.container.network.throttled_outbound_bytes_count
(count)
Outbound bytes dropped due to network throttling.
Shown as byte
gcp.run.container.network.throttled_outbound_packets_count
(count)
Outbound packets dropped due to network throttling.
Shown as byte
gcp.run.container.probe_attempt_latencies.avg
(count)
The average distribution of time spent running a single probe attempt before success or failure in milliseconds.
Shown as millisecond
gcp.run.container.probe_attempt_latencies.samplecount
(count)
The sample count for distribution of time spent running a single probe attempt before success or failure in milliseconds.
Shown as millisecond
gcp.run.container.probe_attempt_latencies.sumsqdev
(count)
The sum of squared deviation for distribution of time spent running a single probe attempt before success or failure in milliseconds.
Shown as millisecond
gcp.run.container.probe_latencies.avg
(count)
The average distribution of time spent running a probe before success or failure in milliseconds.
Shown as millisecond
gcp.run.container.probe_latencies.samplecount
(count)
The sample count for distribution of time spent running a probe before success or failure in milliseconds.
Shown as millisecond
gcp.run.container.probe_latencies.sumsqdev
(count)
The sum of squared deviation for distribution of time spent running a probe before success or failure in milliseconds.
Shown as millisecond
gcp.run.container.startup_latencies.avg
(count)
The average distribution of time spent starting a new container instance in milliseconds.
Shown as millisecond
gcp.run.container.startup_latencies.samplecount
(count)
The sample count for distribution of time spent starting a new container instance in milliseconds.
Shown as millisecond
gcp.run.container.startup_latencies.sumsqdev
(count)
The sum of squared deviation for distribution of time spent starting a new container instance in milliseconds.
Shown as millisecond
gcp.run.infrastructure.cloudsql.connection_latencies.avg
(count)
The average distribution of latency in microseconds for connections originating from Cloud Run to CloudSQL.
Shown as microsecond
gcp.run.infrastructure.cloudsql.connection_latencies.samplecount
(count)
The sample count for distribution of latency in microseconds for connections originating from Cloud Run to CloudSQL.
Shown as microsecond
gcp.run.infrastructure.cloudsql.connection_latencies.sumsqdev
(count)
The sum of squared deviation for distribution of latency in microseconds for connections originating from Cloud Run to CloudSQL.
Shown as microsecond
gcp.run.infrastructure.cloudsql.connection_refused_count
(count)
Total number of connections refused originating from Cloud Run to CloudSQL.
gcp.run.infrastructure.cloudsql.connection_request_count
(count)
Total number of connection requests originating from Cloud Run to CloudSQL.
gcp.run.infrastructure.cloudsql.received_bytes_count
(count)
Number of bytes received by Cloud Run from CloudSQL over the network.
Shown as byte
gcp.run.infrastructure.cloudsql.sent_bytes_count
(count)
Number of bytes sent by Cloud Run to CloudSQL over the network.
Shown as byte
gcp.run.job.completed_execution_count
(count)
Number of completed job executions and their result.
gcp.run.job.completed_task_attempt_count
(count)
Number of completed task attempts and its corresponding exit result.
gcp.run.job.running_executions
(gauge)
Number of running job executions.
gcp.run.job.running_task_attempts
(gauge)
Number of running task attempts.
gcp.run.pending_queue.pending_requests
(gauge)
Number of pending requests.
gcp.run.request_count
(count)
The number of service requests.
Shown as request
gcp.run.request_latencies.avg
(gauge)
Average distribution of service request times in milliseconds.
Shown as millisecond
gcp.run.request_latencies.p95
(gauge)
The 95th percentile distribution of service request times in milliseconds.
Shown as millisecond
gcp.run.request_latencies.p99
(gauge)
The 99th percentile distribution of service request times in milliseconds.
Shown as millisecond
gcp.run.request_latencies.samplecount
(count)
Sample count of the distribution of service request times in milliseconds.
Shown as millisecond
gcp.run.request_latencies.sumsqdev
(gauge)
Sum of squared deviation of the distribution of service request times in milliseconds.
Shown as millisecond

Eventos

La integración de las funciones de Google Cloud no incluye ningún evento.

Checks de servicios

La integración de las funciones de Google Cloud no incluye ningún check de servicios.

Resolución de problemas

¿Necesitas ayuda? Ponte en contacto con el servicio de asistencia de Datadog.

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