Setup

1. Install the Datadog Node.js tracer.

   1. In your main application, add dd-trace-js.

      Copy

      npm install dd-trace --save

   2. Add the following to your application code to initialize the tracer:

      Copy

      const tracer = require('dd-trace').init({
       logInjection: true,
      });

   3. Set the following environment variable to specify that the dd-trace/init module is required when the Node.js process starts:

      Copy

      ENV NODE_OPTIONS="--require dd-trace/init"

   Note: Cloud Run Jobs run to completion rather than serving requests, so auto instrumentation won’t create a top-level “job” span. For end-to-end visibility, create your own root span. See the Node.js Custom Instrumentation instructions.

   For more information, see Tracing Node.js applications.

2. Install serverless-init.

   Serverless-init automatically creates a span for the duration of a task, even if the tracer is not installed. You can disable this by setting DD_APM_ENABLED=false. However, tracing is recommended because it is required for task-level visibility.
   Cloud Run Jobs requires serverless-init version 1.9.0 or later.
   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 ["/nodejs/bin/node", "/path/to/your/app.js"]
   

   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", "/nodejs/bin/node", "/path/to/your/app.js"]
   

   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", "/nodejs/bin/node", "/path/to/your/app.js"]
   

   As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

   
   

3. Set up logs.

   To enable logging, set the environment variable DD_LOGS_ENABLED=true. This allows serverless-init to read logs from stdout and stderr.

   Datadog also recommends setting the environment variable DD_LOGS_INJECTION=true and DD_SOURCE=nodejs to enable advanced Datadog log parsing.

   If you want multiline logs to be preserved in a single log message, Datadog recommends writing your logs in JSON format. For example, you can use a third-party logging library such as winston:

   Copy

   const tracer = require('dd-trace').init({
     logInjection: true,
   });
   const { createLogger, format, transports } = require('winston');
   
   const logger = createLogger({
     level: 'info',
     exitOnError: false,
     format: format.json(),
     transports: [
       new transports.Console()
     ],
   });
   
   logger.info('Hello world!');

   For more information, see Correlating Node.js Logs and Traces.

4. Configure your application.

   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.

5. 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.

6. Set up a retention filter for Cloud Run Jobs traces. Datadog relies on traces to display executions and tasks in the UI. To ensure traces are retained, create a retention filter with the query @origin:cloudrunjobs and set the span retention rate to 100%.

   

7. Send custom metrics.

   To send custom metrics, view code examples. In serverless, only the distribution metric type is supported.

Environment variables

Distributed tracing with Pub/Sub

To get end-to-end distributed traces between Pub/Sub producers and Cloud Run jobs, 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 proper 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.

1. Create the Eventarc trigger:

   Copy

   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" \
     --event-filters="topic=projects/my-project/topics/orders" \
     --location=us-central1

2. Find the auto-created subscription:

   Copy

   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
   

3. Update the subscription for trace propagation:

   Copy

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

Troubleshooting

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.

Further reading

Más enlaces, artículos y documentación útiles:

Tracing Node.js ApplicationsDOCUMENTATION Correlating Node.js Logs and TracesDOCUMENTATION