概要

Cloud Run は、HTTP リクエストを使って呼び出し可能なステートレスコンテナを実行できるマネージド型のコンピューティングプラットフォームです。

このインテグレーションを有効にしてコンテナをインスツルメンテーションすると、Cloud Run のメトリクス、トレース、ログのすべてを Datadog に表示できます。

Cloud Run for Anthos の詳細については、Google Cloud Run for Anthos ドキュメントを参照してください。

セットアップ

メトリクスの収集

インストール

Google Cloud Platform インテグレーションをセットアップして、すぐに使えるメトリクスの収集を開始します。カスタムメトリクスを設定するには、Serverless ドキュメントを参照してください。

収集データ

インテグレーション

Google Cloud Run は監査ログも公開します。 Google Cloud Run のログは Google Cloud Logging で収集され、Cloud Pub/Sub トピックを通じて Dataflow ジョブに送信されます。まだの場合は、Datadog Dataflow テンプレートでロギングをセットアップしてください

これが完了したら、Google Cloud Run のログを Google Cloud Logging から Pub/Sub トピックへエクスポートします。

  1. Google Cloud Logging のページに移動し、Google Cloud Run のログを絞り込みます。

  2. シンクを作成し、シンクに適宜名前を付けます。

  3. 宛先として “Cloud Pub/Sub” を選択し、その目的で作成された Pub/Sub トピックを選択します。: Pub/Sub トピックは別のプロジェクトに配置できます。

    Google Cloud Pub/Sub ログを Pub Sub へエクスポート
  4. 作成をクリックし、確認メッセージが表示されるまで待ちます。

直接ロギング

Cloud Run サービスから Datadog へのアプリケーションの直接ロギングについては、Serverless ドキュメントを参照してください。

トレーシング

フルマネージド Google Cloud Run に特化した Agent の設定手順については、Serverless ドキュメントを参照してください。

収集データ

メトリクス

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.
gcp.run.container.gpu.memory_utilizations.samplecount
(gauge)
The sample count for container GPU memory utilization distribution across all container instances.
gcp.run.container.gpu.memory_utilizations.sumsqdev
(gauge)
The sum of squared deviation for container GPU memory utilization distribution across all container instances.
gcp.run.container.gpu.utilizations.avg
(gauge)
The average container GPU utilization distribution across all container instances.
gcp.run.container.gpu.utilizations.samplecount
(gauge)
The sample count for container GPU utilization distribution across all container instances.
gcp.run.container.gpu.utilizations.sumsqdev
(gauge)
The sum of squared deviation for container GPU utilization distribution across all container instances.
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

イベント

Google Cloud Functions インテグレーションには、イベントは含まれません。

サービスチェック

Google Cloud Functions インテグレーションには、サービスのチェック機能は含まれません。

トラブルシューティング

ご不明な点は、Datadog のサポートチームまでお問合せください。

その他の参考資料