Trace AWS Lambda durable functions with Datadog

Datadog now provides tracing for AWS Lambda durable functions, which support long-running, multi-step workflows that can pause, resume, retry, and maintain state across multiple Lambda invocations. Its Node.js and Python tracers automatically instrument durable operations including steps, waits, callbacks, parallel tasks, maps, invokes, and child contexts, combining their telemetry into a single trace and flame graph rather than separate invocation-level traces. Cross-invocation context is stored in an additional Datadog checkpoint that preserves the trace ID without modifying user checkpoint data, enabling users to move from the AWS console to the associated Datadog trace. The integration helps investigate errors, retries, and replayed operations through span tags, attached error details, execution-level operation summaries, and filtering by execution ARN or status. No workflow code changes are required for Lambda functions already using the Datadog Lambda Library and Extension, although retention filters are recommended for very long-running executions. Datadog also offers Serverless View dashboards and metrics to monitor durable execution status, duration, utilization, failures, timeouts, and other behavior across workflows.

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