Google Cloud Run

To find out if this integration is available in your organization, see your Datadog Integrations page or ask your organization administrator.

To initiate an exception request to enable this integration for your organization, email support@ddog-gov.com.

Présentation

Cloud Run est une plateforme de calcul gérée qui vous permet d’exécuter des conteneurs sans état accessibles via des requêtes HTTP.

Activez cette intégration et instrumentez votre conteneur pour visualiser dans Datadog toutes vos métriques et traces ainsi que tous vos logs Cloud Run.

Pour plus d’informations sur Cloud Run for Anthos, consultez la documentation Google Cloud Run for Anthos.

Configuration

Collecte de métriques

Installation

Configurez lʼintégration Google Cloud Platform pour commencer à recueillir des métriques prêtes à l’emploi. Pour configurer des métriques personnalisées, consultez la documentation sur le sans serveur.

APM

Intégration

Google Cloud Run expose également des logs d’audit. Les logs Google Cloud Run sont recueillis avec Google Cloud Logging et envoyés à une tâche Dataflow par le biais d’un sujet Cloud Pub/Sub. Si vous ne l’avez pas encore fait, configurez la journalisation avec le modèle Dataflow Datadog.

Une fois cette opération effectuée, exportez vos logs Google Cloud Run depuis Google Cloud Logging vers la rubrique Pub/Sub :

  1. Accédez à la page Google Cloud Logging et filtrez les logs Google Cloud Run.

  2. Cliquez sur Create Sink et nommez le récepteur.

  3. Choisissez « Cloud Pub/Sub » comme destination et sélectionnez le sujet Pub/Sub créé à cette fin. Remarque : le sujet Pub/Sub peut se situer dans un autre projet.

    Exporter les logs Google Cloud Pub/Sub vers le Pub Sub
  4. Cliquez sur Create et attendez que le message de confirmation s’affiche.

Journalisation directe

Pour plus d’informations sur la journalisation directe des applications vers Datadog depuis vos services Cloud Run, consultez la documentation sur lʼinformatique sans serveur.

Tracing

Pour plus d’informations sur les instructions d’installation spécialisée de lʼAgent pour Google Cloud Run entièrement géré, consultez la documentation sur lʼinformatique sans serveur.

Données collectées

Métriques

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)
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)
Actual container cpu usage in cpu seconds broken down by the metric field, container name.
gcp.run.container.cpu.usage.sumsqdev
(gauge)
Actual container cpu usage in cpu seconds broken down by the metric field, container name.
gcp.run.container.cpu.utilizations.avg
(gauge)
Container CPU utilization distribution across all container instances.
Shown as percent
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)
Container CPU utilization distribution across all container instances.
gcp.run.container.gpu.memory_usages.avg
(gauge)
Container GPU memory usage distribution across all container instances.
Shown as byte
gcp.run.container.gpu.memory_usages.samplecount
(gauge)
Container GPU memory usage distribution across all container instances.
gcp.run.container.gpu.memory_usages.sumsqdev
(gauge)
Container GPU memory usage distribution across all container instances.
gcp.run.container.gpu.memory_utilizations.avg
(gauge)
Container GPU memory utilization distribution across all container instances.
Shown as percent
gcp.run.container.gpu.memory_utilizations.samplecount
(gauge)
Container GPU memory utilization distribution across all container instances.
gcp.run.container.gpu.memory_utilizations.sumsqdev
(gauge)
Container GPU memory utilization distribution across all container instances.
gcp.run.container.gpu.utilizations.avg
(gauge)
Container GPU utilization distribution across all container instances.
Shown as percent
gcp.run.container.gpu.utilizations.samplecount
(gauge)
Container GPU utilization distribution across all container instances.
gcp.run.container.gpu.utilizations.sumsqdev
(gauge)
Container GPU utilization distribution across all container instances.
gcp.run.container.instance_count
(gauge)
Number of container instances that exist, broken down by state.
gcp.run.container.max_request_concurrencies.avg
(gauge)
Distribution of the maximum number of concurrent requests being served by each container instance over a minute. Filter by ‘state’ = ‘active’ only get the concurrency of active container instances.
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)
Distribution of the maximum number of concurrent requests being served by each container instance over a minute. Filter by ‘state’ = ‘active’ only get the concurrency of active container instances.
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)
Actual container memory usage in bytes broken down by the metric field, container name.
Shown as byte
gcp.run.container.memory.usage.samplecount
(gauge)
Actual container memory usage in bytes broken down by the metric field, container name.
gcp.run.container.memory.usage.sumsqdev
(gauge)
Actual container memory usage in bytes broken down by the metric field, container name.
gcp.run.container.memory.utilizations.avg
(gauge)
Container memory utilization distribution across all container instances.
Shown as percent
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)
Container memory utilization distribution across all container instances.
gcp.run.container.network.received_bytes_count
(count)
Incoming socket and HTTP request traffic, in bytes.
Shown as byte
gcp.run.container.network.sent_bytes_count
(count)
Outgoing socket and HTTP response traffic, 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.
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.
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)
Distribution of time spent running a single probe attempt before success or failure in milliseconds.
gcp.run.container.probe_attempt_latencies.sumsqdev
(count)
Distribution of time spent running a single probe attempt before success or failure in milliseconds.
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)
Distribution of time spent running a probe before success or failure in milliseconds.
gcp.run.container.probe_latencies.sumsqdev
(count)
Distribution of time spent running a probe before success or failure in milliseconds.
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)
Distribution of time spent starting a new container instance in milliseconds.
gcp.run.container.startup_latencies.sumsqdev
(count)
Distribution of time spent starting a new container instance in milliseconds.
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)
Distribution of latency in microseconds for connections originating from Cloud Run to CloudSQL.
gcp.run.infrastructure.cloudsql.connection_latencies.sumsqdev
(count)
Distribution of latency in microseconds for connections originating from Cloud Run to CloudSQL.
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)
Number of requests reaching the revision. Excludes requests that are not reaching your container instances (for example, unauthorized requests or when maximum number of instances is reached). Captured at the end of the request lifecycle.
gcp.run.request_latencies.avg
(gauge)
Distribution of request latency in milliseconds reaching the revision. Latency is measured from when the request reaches the running container to when it exits. Notably, it does not include container startup latency.
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)
Distribution of request latency in milliseconds reaching the revision. Latency is measured from when the request reaches the running container to when it exits. Notably, it does not include container startup latency.
gcp.run.request_latencies.sumsqdev
(gauge)
Sum of squared deviation of the distribution of service request times in milliseconds.
Shown as millisecond
gcp.run.container.enhanced.cold_start
(count)
Number of times a container initialized with a cold start.
Shown as event
gcp.run.container.enhanced.shutdown
(count)
Number of times a container shut down.
Shown as event
gcp.run.container.enhanced.cpu.limit
(gauge)
The maximum CPU available to a cloud run service or job, including sidecar containers.
Shown as nanocore
gcp.run.container.enhanced.cpu.usage
(gauge)
The total CPU usage for a cloud run service or job, including sidecar containers.
Shown as nanocore
gcp.run.job.enhanced.task.started
(count)
Number of times a task started.
Shown as event
gcp.run.job.enhanced.task.ended
(count)
Number of times a task ended.
Shown as event
gcp.run.job.enhanced.task.duration
(gauge)
Average duration of one task in the execution.
Shown as millisecond
gcp.run.enhanced.cold_start
(count)
Number of times a container or function initialized with a cold start.
gcp.run.enhanced.shutdown
(count)
Number of times a container or function shut down.

Événements

L’intégration Google Cloud Functions n’inclut aucun événement.

Checks de service

L’intégration Google Cloud Functions n’inclut aucun check de service.

Dépannage

Besoin d’aide ? Contactez l’assistance Datadog.

Pour aller plus loin

Further Reading