Autoscaling with self-hosted runners

You can automatically scale your self-hosted runners in response to webhook events.

About autoscaling

You can automatically increase or decrease the number of self-hosted runners in your environment in response to the webhook events you receive with a particular label. For example, you can create automation that adds a new self-hosted runner each time you receive a workflow_job webhook event with the queued activity, which notifies you that a new job is ready for processing. The webhook payload includes label data, so you can identify the type of runner the job is requesting. Once the job has finished, you can then create automation that removes the runner in response to the workflow_job completed activity.

GitHub recommends and partners closely with two open source projects that you can use for autoscaling your runners. One or both solutions may be suitable, based on your needs.

The following repositories have detailed instructions for setting up these autoscalers:

Each solution has certain specifics that may be important to consider:

功能actions-runner-controllerterraform-aws-github-runner
RuntimeKubernetesLinux and Windows VMs
Supported CloudsAzure, Amazon Web Services, Google Cloud Platform, on-premisesAmazon Web Services
Where runners can be scaledEnterprise, organization, and repository levels. By runner label and runner group.Organization and repository levels. By runner label and runner group.
Pull-based autoscaling support

Using ephemeral runners for autoscaling

GitHub recommends implementing autoscaling with ephemeral self-hosted runners; autoscaling with persistent self-hosted runners is not recommended. In certain cases, GitHub cannot guarantee that jobs are not assigned to persistent runners while they are shut down. With ephemeral runners, this can be guaranteed because GitHub only assigns one job to a runner.

This approach allows you to manage your runners as ephemeral systems, since you can use automation to provide a clean environment for each job. This helps limit the exposure of any sensitive resources from previous jobs, and also helps mitigate the risk of a compromised runner receiving new jobs.

To add an ephemeral runner to your environment, include the --ephemeral parameter when registering your runner using config.sh. 例如:

$ ./config.sh --url https://github.com/octo-org --token example-token --ephemeral

The GitHub Actions service will then automatically de-register the runner after it has processed one job. You can then create your own automation that wipes the runner after it has been de-registered.

Note: If a job is labeled for a certain type of runner, but none matching that type are available, the job does not immediately fail at the time of queueing. Instead, the job will remain queued until the 24 hour timeout period expires.

Using webhooks for autoscaling

You can create your own autoscaling environment by using payloads received from the workflow_job webhook. This webhook is available at the repository, organization, and enterprise levels, and the payload for this event contains an action key that corresponds to the stages of a workflow job's life-cycle; for example when jobs are queued, in_progress, and completed. You must then create your own scaling automation in response to these webhook payloads.

Authentication requirements

You can register and delete repository and organization self-hosted runners using the API. To authenticate to the API, your autoscaling implementation can use an access token or a GitHub app.

Your access token will require the following scope:

  • For private repositories, use an access token with the repo scope.
  • For public repositories, use an access token with the public_repo scope.

To authenticate using a GitHub App, it must be assigned the following permissions:

  • For repositories, assign the administration permission.
  • For organizations, assign the organization_self_hosted_runners permission.

You can register and delete enterprise self-hosted runners using the API. To authenticate to the API, your autoscaling implementation can use an access token.

Your access token will require the manage_runners:enterprise scope.

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