Instrument serverless apps with agentic onboarding

Datadog’s serverless agentic onboarding is designed to reduce the manual effort of instrumenting applications running on AWS Lambda, Google Cloud Run, and Azure Container Apps across varied runtimes and deployment tools. Users can initiate setup through an MCP-compatible AI coding assistant connected to the Datadog MCP Server or through the AI Setup CLI, which examines a local project and generates suitable configuration changes. The system supports AWS SAM, AWS CDK, Serverless Framework, Terraform, and datadog-ci for Lambda workloads, as well as sidecar or in-container approaches for Cloud Run and Azure Container Apps, adapting generated files to each project’s existing structure. It also configures relevant environment variables and standard service, environment, and version tags to support consistent observability. Safety measures include scoped setup questions, local staged changes, permission requirements for AI assistants, and user-controlled review, testing, approval, and deployment, while applying Datadog-recommended Agent versions and telemetry settings.

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