Use Profile-Guided Optimization (PGO) for Go apps

In 2023, Go 1.21 introduced Profile-Guided Optimization (PGO), which allows you to provide a profile of your application to the Go compiler at runtime, which the Go compiler uses to make smarter decisions about how to optimize your code in the next build.

Teams from Google and Uber have been working together since 2021 to build PGO. Together, we've experimented with various optimizations to increase compute efficiency and reduce costs. Today, Uber is rolling out PGO across its fleet, reducing CPU utilization across many of its services. Learn how to use PGO in your Go applications, including on Google Cloud, here.

What is PGO?

When you build a Go binary, the Go compiler performs optimizations to try to produce the best performing binary possible. However, this is not always a trivial task; there is often a trade-off between overly aggressive optimizations resulting in slower performance or longer build times. Without knowing how your code will be used at runtime, the compiler uses static heuristics to guess which paths through your code are called most frequently and optimizes them accordingly.

But what if you could tell the compiler exactly how your code will be used at runtime? With PGO, you can. By collecting a profile of your application in production and using this profile in the next build, the compiler can make more informed decisions, like optimizing your most frequently used functions more aggressively or more accurately selecting common cases within a function.

Using PGO in Go applications

Using PGO is easy: just collect a profile of your application at runtime and provide that profile to the compiler the next time you build it. Here's how to do it:

1. Import and enable profiling: In your main package, import the net/http/pprof package, which automatically adds a /debug/pprof/profile endpoint to your server for getting CPU profiles.

2. Collect a profile: Build your project as you normally would and run your application in a representative environment, such as production, staging, or realistic test conditions. While your application is running and experiencing normal load, download the profile from the server endpoint you created in the last step. For example, if your application is running locally:

Sources 1/ https://Google.com/ 2/ https://cloud.google.com/blog/products/application-development/using-profile-guided-optimization-for-your-go-apps The mention sources can contact us to remove/changing this article

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