Google Cloud Run

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.

Formule et utilisation

Collecte de métriques

Liste des infrastructures

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

Presse-papiers Datadog

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 le Pub/Sub :

Accédez à la page Google Cloud Logging et filtrez les logs Google Cloud Run.
Cliquez sur Create Sink et nommez le récepteur.
Choisissez Cloud Pub/Sub comme destination et sélectionnez le Pub/Sub créé à cette fin. Remarque : le Pub/Sub peut se situer dans un autre projet.
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.

Aide

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.

Real User Monitoring

Analyse d’entonnoirs

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.cpu.allocation_time (rate)	Container CPU allocation of the revision in seconds. Shown as core
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.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 Gigabytes-seconds. Shown as gibibyte
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.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