datadog-pgo is a tool for integrating continuous profile-guided optimization (PGO) into your Go build process. It fetches representative CPU profiles from Datadog and merges them into a default.pgo file that is used by the Go toolchain to optimize your application.

• This tool is currently in public beta. Please open a GitHub issue if you have any feedback or questions.
• Always use the latest version of datadog-pgo in CI as shown below. Old versions may become deprecated and stop working on short notice.
• We're considering to integrate this tool into datadog-ci. Please let us know if you're interested in this.

1. Create a dedicated API key and unscoped Application key for PGO as described in the documentation.
2. Set DD_API_KEY, DD_APP_KEY and DD_SITE via the environment secret mechanism of your CI provider.
3. Run datadog-pgo before your build step. E.g. for a service foo that runs in prod and has its main package in ./cmd/foo, you should add this step:

go run github.com/DataDog/datadog-pgo@latest 'service:foo env:prod' ./cmd/foo/default.pgo

That's it. The go toolchain will automatically pick up any default.pgo file in the main package, so there is no need to modify your go build step.

usage: datadog-pgo [OPTIONS]... QUERY... DEST

datadog-pgo fetches CPU profiles from Datadog using the given QUERY arguments
and merges the results into a single DEST file suitable for profile-guided
optimization.

In order to use this, you need to set the following environment variables.

	DD_API_KEY: A Datadog API key
	DD_APP_KEY: A Datadog Application key
	DD_SITE: A Datadog site to use (defaults to datadoghq.com)

After this, typical usage will look like this:

	datadog-pgo 'service:my-service env:prod' ./cmd/my-service/default.pgo

The go toolchain will automatically pick up any default.pgo file found in the
main package (go1.21+), so you can build your service as usual, for example:

	go build ./cmd/my-service

Unless the -fail flag is set, datadog-pgo will always return with a zero exit
code in order to let your build succeed, even if a PGO download error occured.

OPTIONS
  -fail
    	return with a non-zero exit code on failure
  -from duration
    	how far back to search for profiles (default 72h0m0s)
  -json
    	print logs in json format
  -profiles int
    	the number of profiles to fetch per query (default 5)
  -timeout duration
    	timeout for fetching PGO profile (default 1m0s)
  -v	verbose output

By default datadog-pgo selects the top 5 profiles by CPU utilization within the last 72 hours. You can change this behavior using the -profiles and -from flags.

This oppinionated approach is based on our internal testing where it has yielded better results than taking a sample of average profiles.

Please open a GitHub issue if you have feedback on this.

The official PGO documentation recommends using profiles from your production environment. Profiles from other environments may not be representative of the production workload and will likely yield suboptimal results.

dd-trace-go tags the profiles of PGO-enabled applications with a pgo:true tag. You can search for profiles with this tag in the profile explorer.

The impact of PGO can be tricky to measure. When in doubt, try to measure CPU time per request by building a dashboard widget that divides the CPU usage of your application by the number of requests it serves. We hope to provide a better solution for this in the future.

datadog-pgo will always return with a zero exit code in order to let your build succeed, even if pgo downloading failed. If you want to fail the build on error, use the -fail flag.

1. Copy the the debug-query output from the last log line of datadog-pgo.
2. Go to the profile explorer in the Datadog UI and paste the query.
3. Increase the time range to 1 week to make sure you see all profiles.

Please note that the profile retention is 7 days. If you're interested in the use case of retaining pgo profiles for longer, please let us know by opening an github issue on this repo.

Just open a GitHub issue on this repository. We're happy to hear from you!