Choosing an Instrumentation Method for Containers

Use the Datadog MCP server

Use the Datadog MCP server to set up monitoring for your Cloud Run containers with AI assistance. After you connect, try a prompt like:

Help me monitor my GCP Cloud Run services with Datadog using Terraform.

To instrument your Google Cloud Run containers with Datadog, choose one of two options:

In-Container: Wraps your application container with the Datadog Agent. Choose this option for a simpler setup, lower cost overhead, and direct log piping.
Sidecar: Deploys the Datadog Agent in a separate container alongside your app container. Choose this option if you have multiple containers in a single service, if you prefer strict isolation of the Datadog Agent, or if you have performance-sensitive workloads.

Aspect	In-Container	Sidecar
Deployment	One container (your app, wrapped with the Datadog Agent)	Two containers (your app, Datadog Agent)
Image changes	Increases app image size.	No change to app image.
Cost overhead	Less than sidecar (no extra container).	Extra vCPU/memory. Overallocating the sidecar wastes cost; underallocating leads to premature scaling.
Logging	Direct stdout/stderr access.	Shared volume + log library routing to a log file. Uncaught errors require extra handling, since they are not automatically handled by your logging library.
Failure isolation	In rare cases, Datadog Agent bugs can affect your app.	Datadog Agent faults are isolated.