Profiling Go applications

This page describes how to modify your Go application to capture profiling data and have that data sent to your Google Cloud project. For general information about profiling, see Profiling concepts.

Profile types for Go:

  • CPU time
  • Heap
  • Allocated heap
  • Contention (Go mutex)
  • Threads (Go goroutine)

Supported Go language versions:

Supported profiling agent versions:

  • The most recent release of the agent is supported. In general, releases older than one year aren't supported. We recommend that you use the most recently released version of the agent.

Supported operating systems:

  • Linux. Profiling Go applications is supported for Linux kernels whose standard C library is implemented with glibc or with musl. For configuration information specific to Linux Alpine kernels, see Running on Linux Alpine.

Supported environments:

  • Compute Engine
  • Google Kubernetes Engine (GKE)
  • App Engine flexible environment
  • App Engine standard environment (requires Go 1.11 or higher)
  • Outside of Google Cloud (For information on the additional configuration requirements, see Profiling applications running outside of Google Cloud.)

Enabling the Profiler API

Before you use the profiling agent, ensure that the underlying Profiler API is enabled. You can check the status of the API and enable it if necessary by using either the Google Cloud CLI or the Google Cloud console:

gcloud CLI

  1. If you have not already installed the Google Cloud CLI on your workstation, see the Google Cloud CLI documentation.

  2. Run the following command:

    gcloud services enable cloudprofiler.googleapis.com

For more information, see gcloud services.

Google Cloud console

  1. Enable the required API.

    Enable the API

  2. If API enabled is displayed, then the API is already enabled. If not, click the Enable button.

Using Cloud Profiler

In all of the supported environments, you use the Profiler by importing the package in your application and then initializing the Profiler as early as possible in your application.

You can enable Mutex-contention profiling (“Contention” in the interface) by setting the MutexProfiling configuration option to true.

For more information on the Profiler API, including all the configuration options, see the public API docs.

Compute Engine

For Compute Engine, in profiler.Config set Service with a name for the service being profiled and optionally set ServiceVersion with the service version:


// snippets is an example of starting cloud.google.com/go/profiler.
package main

import (
	"cloud.google.com/go/profiler"
)

func main() {
	cfg := profiler.Config{
		Service:        "myservice",
		ServiceVersion: "1.0.0",
		// ProjectID must be set if not running on GCP.
		// ProjectID: "my-project",

		// For OpenCensus users:
		// To see Profiler agent spans in APM backend,
		// set EnableOCTelemetry to true
		// EnableOCTelemetry: true,
	}

	// Profiler initialization, best done as early as possible.
	if err := profiler.Start(cfg); err != nil {
		// TODO: Handle error.
	}
}

If you have dependencies in your source code that are fetched manually, then you might need to add the following to your build script or Dockerfile: 

go get cloud.google.com/go/profiler

GKE

For GKE, in profiler.Config set Service with a name for the service being profiled and optionally set ServiceVersion with the service version:


// snippets is an example of starting cloud.google.com/go/profiler.
package main

import (
	"cloud.google.com/go/profiler"
)

func main() {
	cfg := profiler.Config{
		Service:        "myservice",
		ServiceVersion: "1.0.0",
		// ProjectID must be set if not running on GCP.
		// ProjectID: "my-project",

		// For OpenCensus users:
		// To see Profiler agent spans in APM backend,
		// set EnableOCTelemetry to true
		// EnableOCTelemetry: true,
	}

	// Profiler initialization, best done as early as possible.
	if err := profiler.Start(cfg); err != nil {
		// TODO: Handle error.
	}
}

If you have dependencies in your source code that are fetched manually, then you might need to add the following to your build script or Dockerfile: 

go get cloud.google.com/go/profiler

App Engine

For the App Engine flexible environment and the App Engine standard environment, the code additions are nearly identical to those for Compute Engine and GKE. There is one exception. In both App Engine environments, the Service and ServiceVersion parameters are derived from the environment, so you don't have to specify them.


// appengine is an example of starting cloud.google.com/go/profiler on
// App Engine.
package main

import (
	"cloud.google.com/go/profiler"
)

func main() {
	// Profiler initialization, best done as early as possible.
	if err := profiler.Start(profiler.Config{
		// Service and ServiceVersion can be automatically inferred when running
		// on App Engine.
		// ProjectID must be set if not running on GCP.
		// ProjectID: "my-project",
	}); err != nil {
		// TODO: Handle error.
	}
}

When you run the application locally, set the ProjectID (the ID of your Google Cloud project) and Service parameters in profiler.Config, since they cannot be derived from a local environment. You don't need to set ServiceVersion.

If you are using App Engine standard environment, see Migrating your app to Go 1.11 for detailed information on changes you might need to make to your application. Also, you must use Google Cloud CLI version 226.0.0 or later. To update the Google Cloud CLI, run the following command:

    gcloud components update

To run your application:

  1. Update the dependencies:

    go get cloud.google.com/go/profiler

  2. Deploy the application to your App Engine flexible environment or to your App Engine standard environment:

    gcloud app deploy [DEPLOYMENT]

    where DEPLOYMENT is the path to your configuration file. For example, DEPLOYMENT might be main/app.yaml.

Analyzing data

After Profiler has collected data, you can view and analyze this data using the Profiler interface.

In the Google Cloud console, go to the Profiler page:

Go to Profiler

You can also find this page by using the search bar.

Service name and version arguments

When you load the Profiler agent, you specify a service-name argument and an optional service-version argument to configure it.

The service name lets Profiler collect profiling data for all replicas of that service. The profiler service ensures a collection rate of one profile per minute, on average, for each service name across each combination service versions and zones.

For example, if you have a service with two versions running across replicas in three zones, the profiler will create an average of 6 profiles per minute for that service.

If you use different service names for your replicas, then your service will be profiled more often than necessary, with a correspondingly higher overhead.

When selecting a service name:

  • Choose a name that clearly represents the service in your application architecture. The choice of service name is less important if you only run a single service or application. It is more important if your application runs as a set of micro-services, for example.

  • Make sure to not use any process-specific values, like a process ID, in the service-name string.

  • The service-name string must match this regular expression:

    ^[a-z0-9]([-a-z0-9_.]{0,253}[a-z0-9])?$

A good guideline is to use a static string like imageproc-service as the service name.

The service version is optional. If you specify the service version, Profiler can aggregate profiling information from multiple instances and display it correctly. It can be used to mark different versions of your services as they get deployed. The Profiler UI lets you filter the data by service version; this way, you can compare the performance of older and newer versions of the code.

The value of the service-version argument is a free-form string, but values for this argument typically look like version numbers, for example, 1.0.0 or 2.1.2.

Agent logging

The profiling agent can report debug information in its logs. By default, agent logging is disabled.

To enable agent logging, set the DebugLogging option to true when starting the agent:

profiler.Start(profiler.Config{..., DebugLogging: true});

Troubleshooting

This section lists issues that are specific to profiling Go applications. See Troubleshooting for help with common problems.

Behavior Cause Solution
CPU time profiles aren't collected for applications built with -buildmode=c-archive. Heap, contention, and thread profiles are collected. GitHub issue By default, CPU profiling isn't enabled for Go applications when the -buildmode flag is c-archive or c-shared. Add a call to
signal.Notify(make(
chan os.Signal), syscall.SIGPROF) before calling profiler.Start.
Response to GitHub issue.

Running with Linux Alpine

The Go profiling agent for Linux Alpine is supported only for Google Kubernetes Engine configurations.

Authentication error

If you use Docker images that run with Linux Alpine (such as golang:alpine or just alpine), you might see the following authentication error:

connection error: desc = "transport: authentication handshake failed: x509: failed to load system roots and no roots provided"

Note that to see the error you must have agent logging enabled. By default the agent for Go doesn't output any log messages.

The error indicates that the Docker images with Linux Alpine don't have the root SSL certificates installed by default. Those certificates are necessary for the profiling agent to communicate with the profiler API. To resolve this error, add the following apk command to your Dockerfile:

FROM alpine
...
RUN apk add --no-cache ca-certificates

You then need to rebuild and redeploy your application.

What's next