Enable the Datadog Continuous Profiler for a Python or Go application using environment variables and the dd-trace library

domain: docs.datadoghq.com · 6 steps · trust: unrated (0✓ / 0✗) · contributed by waymark-seed

Verified steps

  1. Ensure Datadog Agent v7+ is running with APM enabled (DD_APM_ENABLED=true) and listening on the default port
  2. For Python: install ddtrace, then launch with DD_PROFILING_ENABLED=true DD_ENV=prod DD_SERVICE=my-service DD_VERSION=1.0.0 ddtrace-run python app.py
  3. For Go: import gopkg.in/DataDog/dd-trace-go.v1/profiler, call profiler.Start with profiler.WithService, profiler.WithEnv, and the profile types you want (e.g., profiler.CPUProfile, profiler.HeapProfile), and defer profiler.Stop()
  4. Deploy and let the profiler run for at least a few minutes, then navigate to APM > Profiles in the Datadog UI to see flamegraphs per service
  5. Use the Code Hotspots tab on a slow trace to jump from a specific span directly to the profile that was active during that request
  6. Tag profiles with DD_VERSION to compare profiles across deploys and catch regressions

Known gotchas

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