Python Cloud Run Container コンテナ内でのインスツルメンテーション

ドキュメント > サーバーレス > Google Cloud Run > コンテナのインスツルメンテーション方法の選択 > In-Container Instrumentation > Python Cloud Run Container コンテナ内でのインスツルメンテーション

セットアップ

サンプルアプリケーションは GitHub で入手可能です。

Datadog Python SDK をインストールします。
requirements.txt または pyproject.toml に ddtrace を追加します。最新バージョンは、PyPI から入手できます。
requirements.txt
```
ddtrace==<VERSION>
```
または、Dockerfile に SDK をインストールできます。
Dockerfile
```
RUN pip install ddtrace
```
次に、開始コマンドを ddtrace-run でラップします。
Dockerfile
```
CMD ["ddtrace-run", "python", "app.py"]
```
詳細については、Python アプリケーションのトレースを参照してください。
serverless-init をインストールします。
Datadog publishes new releases of the serverless-init container image to Google’s gcr.io, AWS’s ECR, and on Docker Hub:
hub.docker.com gcr.io public.ecr.aws
datadog/serverless-init gcr.io/datadoghq/serverless-init public.ecr.aws/datadog/serverless-init
Images are tagged based on semantic versioning, with each new version receiving three relevant tags:
- 1, 1-alpine: use these to track the latest minor releases, without breaking changes
- 1.x.x, 1.x.x-alpine: use these to pin to a precise version of the library
- latest, latest-alpine: use these to follow the latest version release, which may include breaking changes
Add the following instructions and arguments to your Dockerfile.
```
COPY --from=datadog/serverless-init:<YOUR_TAG> /datadog-init /app/datadog-init
ENTRYPOINT ["/app/datadog-init"]
CMD ["ddtrace-run", "python", "path/to/your/python/app.py"]
```
Alternative configuration
Datadog expects serverless-init to be the top-level application, with the rest of your app’s command line passed in for serverless-init to execute.
If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.
```
CMD ["/app/datadog-init", "ddtrace-run", "python", "path/to/your/python/app.py"]
```
If you require your entrypoint to be instrumented as well, you can instead swap your entrypoint and CMD arguments.
```
ENTRYPOINT ["/app/datadog-init"]
CMD ["/your_entrypoint.sh", "ddtrace-run", "python", "path/to/your/python/app.py"]
```
As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.
ログを設定します。
ロギングを有効にするには、環境変数 DD_LOGS_ENABLED=true を設定します。これにより、serverless-init が標準出力と標準エラーからログを読み取ることができます。
Datadog では、次の環境変数も推奨しています。
- ENV PYTHONUNBUFFERED=1: Python の出力がバッファリングされずに、コンテナログにすぐ表示されるようにします。
- ENV DD_LOGS_INJECTION=true: サポートされているロガーのログ/トレース相関を有効にします。
- ENV DD_SOURCE=python: 高度な Datadog ログパースを有効にします。
複数行のログを 1 つのログメッセージとして保持する場合は、JSON 形式でログを記述することをお勧めします。たとえば、structlog のようなサードパーティのロギングライブラリを使用できます。
```
import structlog

def tracer_injection(logger, log_method, event_dict):
    event_dict.update(tracer.get_log_correlation_context())
    return event_dict

structlog.configure(
    processors=[
        tracer_injection,
        structlog.processors.EventRenamer("msg"),
        structlog.processors.JSONRenderer()
    ],
    logger_factory=structlog.WriteLoggerFactory(file=sys.stdout),
)

logger = structlog.get_logger()

logger.info("Hello world!")
```
詳細については、Python ログとトレースの相関付けを参照してください。
アプリケーションを構成します。
After the container is built and pushed to your registry, set the required environment variables for the Datadog Agent:
- DD_API_KEY: Your Datadog API key, used to send data to your Datadog account. For privacy and safety, configure this API key as a Google Cloud Secret.
- DD_SITE: Your Datadog site. For example, datadoghq.com.
For more environment variables, see the Environment variables section on this page.
The following command deploys the service and allows any external connection to reach it. In this example, your service listening is set to port 8080. Ensure that this port number matches the exposed port inside of your Dockerfile.
```
gcloud run deploy <APP_NAME>
  --image=gcr.io/<YOUR_PROJECT>/<APP_NAME> \
  --port=8080 \
  --update-env-vars=DD_API_KEY=$DD_API_KEY \
  --update-env-vars=DD_SITE=$DD_SITE \
```

hub.docker.com	gcr.io	public.ecr.aws
datadog/serverless-init	gcr.io/datadoghq/serverless-init	public.ecr.aws/datadog/serverless-init

Add a service label in Google Cloud. In your Cloud Run service’s info panel, add a label with the following key and value:
Key Value
service The name of your service. Matches the value provided as the DD_SERVICE environment variable.
See Configure labels for services in the Cloud Run documentation for instructions.

Key	Value
`service`	The name of your service. Matches the value provided as the `DD_SERVICE` environment variable.

カスタムメトリクスを送信します。
カスタムメトリクスを送信するには、DogStatsD クライアントをインストールし、コード例を参照してください。サーバーレスでは、ディストリビューションメトリクスタイプのみがサポートされます。
プロファイリングを有効にします (プレビュー)。
Continuous Profiler を有効にするには、環境変数 DD_PROFILING_ENABLED=true を設定します。
Datadog の Continuous Profiler は、Google Cloud Run サービス向けにプレビュー版で利用可能です。

Environment variables

Variable	Description
`DD_API_KEY`	Datadog API key - Required
`DD_SITE`	Datadog site - Required
`DD_SERVICE`	Datadog Service name. Required
`DD_LOGS_ENABLED`	When true, send logs (stdout and stderr) to Datadog. Defaults to false.
`DD_LOGS_INJECTION`	When true, enrich all logs with trace data for supported loggers. See Correlate Logs and Traces for more information.
`DD_VERSION`	See Unified Service Tagging.
`DD_ENV`	See Unified Service Tagging.
`DD_SOURCE`	Set the log source to enable a Log Pipeline for advanced parsing. To automatically apply language-specific parsing rules, set to `python`, or use your custom pipeline. Defaults to `cloudrun`.
`DD_TAGS`	Add custom tags to your logs, metrics, and traces. Tags should be comma separated in key/value format (for example: `key1:value1,key2:value2`).

Do not set the following environment variables in your serverless environment. They should only be set in non-serverless environments.

DD_AGENT_HOST
DD_TRACE_AGENT_URL

Pub/Sub を使用した分散型トレーシング

DD_TRACE_INFERRED_PROXY_SERVICES_ENABLED=true を設定します。これにより、プッシュリクエストの推論 gcp.pubsub.receive スパンが作成されます。

Google Cloud Pub/Sub プッシュサブスクリプションのトレースには、ddtrace バージョン 4.8.0 以降が必要です。

To get end-to-end distributed traces between Pub/Sub producers and Cloud Run, configure your push subscriptions with the --push-no-wrapper and --push-no-wrapper-write-metadata flags. This moves message attributes from the JSON body to HTTP headers, allowing Datadog to extract producer trace context and create span links.

For more information, see Producer-aware tracing for Google Cloud Pub/Sub and Cloud Run and Payload unwrapping in the Google Cloud documentation.

Configure push subscriptions for full trace visibility

Create a new push subscription:

gcloud pubsub subscriptions create order-processor-sub \
  --topic=orders \
  --push-endpoint=https://order-processor-xyz.run.app/pubsub \
  --push-no-wrapper \
  --push-no-wrapper-write-metadata

Update an existing push subscription:

gcloud pubsub subscriptions update order-processor-sub \
  --push-no-wrapper \
  --push-no-wrapper-write-metadata

Configure Eventarc Pub/Sub triggers

Eventarc Pub/Sub triggers use push subscriptions as the underlying delivery mechanism. When you create an Eventarc trigger, GCP automatically creates a managed push subscription. However, Eventarc does not expose --push-no-wrapper-write-metadata as a trigger creation parameter, so you must manually update the auto-created subscription.

Create the Eventarc trigger:

gcloud eventarc triggers create order-processor-trigger \
  --destination-run-service=order-processor \
  --destination-run-region=us-central1 \
  --event-filters="type=google.cloud.pubsub.topic.v1.messagePublished" \
  --transport-topic=projects/my-project/topics/orders \
  --location=us-central1

Find the auto-created subscription:

gcloud pubsub subscriptions list \
  --filter="topic:projects/my-project/topics/orders" \
  --format="table(name,pushConfig.pushEndpoint)"

Example output:

NAME                                                          PUSH_ENDPOINT
eventarc-us-central1-order-processor-trigger-abc-sub-def      https://order-processor-xyz.run.app

Update the subscription for trace propagation:

gcloud pubsub subscriptions update \
  eventarc-us-central1-order-processor-trigger-abc-sub-def \
  --push-no-wrapper \
  --push-no-wrapper-write-metadata

トラブルシューティング

This integration depends on your runtime having a full SSL implementation. If you are using a slim image, you may need to add the following command to your Dockerfile to include certificates:

RUN apt-get update && apt-get install -y ca-certificates

To have your Cloud Run services appear in the software catalog, you must set the DD_SERVICE, DD_VERSION, and DD_ENV environment variables.

If you are using request-based billing for a Google Cloud Run application instrumented in-container, very short requests may lead to dropped logs during the post-request CPU throttling. You can control the speed at which logs are sent to Datadog using the DD_LOGS_CONFIG_BATCH_WAIT environment variable. Set DD_LOGS_CONFIG_BATCH_WAIT to a value shorter than your typical request duration to avoid dropped logs. Sidecar instrumentation also prevents this issue, as the sidecar is not affected by request-based CPU throttling.