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title shortTitle intro versions type topics defaultPlatform
Deploying runner scale sets with Actions Runner Controller
Deploying runner scale sets
Learn how to deploy runner scale sets with {% data variables.product.prodname_actions_runner_controller %}, and use advanced configuration options to tailor {% data variables.product.prodname_actions_runner_controller %} to your needs.
fpt ghec ghes
*
*
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overview
Actions Runner Controller
linux

Legal notice

About runner scale sets

Runner scale sets is a group of homogeneous runners that can be assigned jobs from {% data variables.product.prodname_actions %}. The number of active runners owned by a runner scale set can be controlled by auto-scaling runner solutions such as {% data variables.product.prodname_actions_runner_controller %} (ARC).

You can use runner groups to manage runner scale sets. Similar to self-hosted runners, you can add runner scale sets to existing runner groups. However, runner scale sets can belong to only one runner group at a time and can only have one label assigned to them. For more information on runner groups, see AUTOTITLE.

To assign jobs to a runner scale set, you must configure your workflow to reference the runner scale set's name. For more information, see AUTOTITLE.

Deploying a runner scale set

To deploy a runner scale set, you must have ARC up and running. For more information, see AUTOTITLE.

You can deploy runner scale sets with ARC's Helm charts or by deploying the necessary manifests. Using ARC's Helm charts is the preferred method, especially if you do not have prior experience using ARC.

Note

  • {% data reusables.actions.actions-runner-controller-security-practices-namespace %}
  • {% data reusables.actions.actions-runner-controller-security-practices-secret %}
  • We recommend running production workloads in isolation. {% data variables.product.prodname_actions %} workflows are designed to run arbitrary code, and using a shared Kubernetes cluster for production workloads could pose a security risk.
  • Ensure you have implemented a way to collect and retain logs from the controller, listeners, and ephemeral runners.

  1. To configure your runner scale set, run the following command in your terminal, using values from your ARC configuration.

    When you run the command, keep the following in mind.

    • Update the INSTALLATION_NAME value carefully. You will use the installation name as the value of runs-on in your workflows.

    • Update the NAMESPACE value to the location you want the runner pods to be created.

    • Set the GITHUB_CONFIG_URL value to the URL of your repository, organization, or enterprise. This is the entity that the runners will belong to.

    • This example command installs the latest version of the Helm chart. To install a specific version, you can pass the --version argument with the version of the chart you want to install. You can find the list of releases in the actions-runner-controller repository. {% ifversion not ghes %}

      INSTALLATION_NAME="arc-runner-set"
NAMESPACE="arc-runners"
GITHUB_CONFIG_URL="https://github.com./<your_enterprise/org/repo>"
GITHUB_PAT="<PAT>"
helm install "{% raw %}${INSTALLATION_NAME}{% endraw %}" \
    --namespace "{% raw %}${NAMESPACE}{% endraw %}" \
    --create-namespace \
    --set githubConfigUrl="{% raw %}${GITHUB_CONFIG_URL}{% endraw %}" \
    --set githubConfigSecret.github_token="{% raw %}${GITHUB_PAT}{% endraw %}" \
    oci://ghcr.io/actions/actions-runner-controller-charts/gha-runner-scale-set

      {% endif %} {% ifversion ghes %}

      INSTALLATION_NAME="arc-runner-set"
NAMESPACE="arc-runners"
GITHUB_CONFIG_URL="http(s)://<HOSTNAME>/<'enterprises/your_enterprise'/'org'/'org/repo'>"
GITHUB_PAT="<PAT>"
helm install "{% raw %}${INSTALLATION_NAME}{% endraw %}" \
    --namespace "{% raw %}${NAMESPACE}{% endraw %}" \
    --create-namespace \
    --set githubConfigUrl="{% raw %}${GITHUB_CONFIG_URL}{% endraw %}" \
    --set githubConfigSecret.github_token="{% raw %}${GITHUB_PAT}{% endraw %}" \
    oci://ghcr.io/actions/actions-runner-controller-charts/gha-runner-scale-set

      {% endif %}

      {% data reusables.actions.actions-runner-controller-helm-chart-options %}

  2. To check your installation, run the following command in your terminal.

    helm list -A

    You should see an output similar to the following.

    NAME            NAMESPACE       REVISION        UPDATED                                 STATUS          CHART                                       APP VERSION
arc             arc-systems     1               2023-04-12 11:45:59.152090536 +0000 UTC deployed        gha-runner-scale-set-controller-0.4.0       0.4.0
arc-runner-set  arc-systems     1               2023-04-12 11:46:13.451041354 +0000 UTC deployed        gha-runner-scale-set-0.4.0                  0.4.0

  3. To check the manager pod, run the following command in your terminal.

    kubectl get pods -n arc-systems

    If the installation was successful, the pods will show the Running status.

    NAME                                                   READY   STATUS    RESTARTS   AGE
arc-gha-runner-scale-set-controller-594cdc976f-m7cjs   1/1     Running   0          64s
arc-runner-set-754b578d-listener                       1/1     Running   0          12s

If your installation was not successful, see AUTOTITLE for troubleshooting information.

Using advanced configuration options

ARC offers several advanced configuration options.

Configuring the runner scale set name

Note

Runner scale set names are unique within the runner group they belong to. If you want to deploy multiple runner scale sets with the same name, they must belong to different runner groups.

To configure the runner scale set name, you can define an INSTALLATION_NAME or set the value of runnerScaleSetName in your copy of the values.yaml file.

## The name of the runner scale set to create, which defaults to the Helm release name
runnerScaleSetName: "my-runners"

Make sure to pass the values.yaml file in your helm install command. See the Helm Install documentation for more details.

Choosing runner destinations

Runner scale sets can be deployed at the repository, organization, or enterprise levels.

{% ifversion ghec or ghes %}

Note

You can only deploy runner scale sets at the enterprise level when using {% data variables.product.pat_v1 %} authentication.

{% endif %}

To deploy runner scale sets to a specific level, set the value of githubConfigUrl in your copy of the values.yaml to the URL of your repository, organization, or enterprise.

The following example shows how to configure ARC to add runners to octo-org/octo-repo.

{% ifversion not ghes %}

githubConfigUrl: "https://github.com./octo-ent/octo-org/octo-repo"

{% endif %} {% ifversion ghes %}

githubConfigUrl: "http(s)://<HOSTNAME>/<'enterprises/your_enterprise'/'org'/'org/repo'>"

{% endif %}

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Using a {% data variables.product.prodname_github_app %} for authentication

If you are not using enterprise-level runners, you can use {% data variables.product.prodname_github_apps %} to authenticate with the {% data variables.product.company_short %} API. For more information, see AUTOTITLE.

Note

Given the security risk associated with exposing your private key in plain text in a file on disk, we recommend creating a Kubernetes secret and passing the reference instead.

You can either create a Kubernetes secret, or specify values in your values.yaml file.

Option 1: Create a Kubernetes secret (recommended)

Once you have created your {% data variables.product.prodname_github_app %}, create a Kubernetes secret and pass the reference to that secret in your copy of the values.yaml file.

{% data reusables.actions.arc-runners-namespace %}

kubectl create secret generic pre-defined-secret \
  --namespace=arc-runners \
  --from-literal=github_app_id=123456 \
  --from-literal=github_app_installation_id=654321 \
  --from-file=github_app_private_key=private-key.pem

In your copy of the values.yaml pass the secret name as a reference.

githubConfigSecret: pre-defined-secret

Option 2: Specify values in your values.yaml file

Alternatively, you can specify the values of app_id, installation_id and private_key in your copy of the values.yaml file.

## githubConfigSecret is the Kubernetes secret to use when authenticating with GitHub API.
## You can choose to use a GitHub App or a {% data variables.product.pat_v1 %}
githubConfigSecret:
  ## GitHub Apps Configuration
  ## IDs must be strings, use quotes
  github_app_id: "123456"
  github_app_installation_id: "654321"
  github_app_private_key: |
    -----BEGIN RSA PRIVATE KEY-----
    ...
    HkVN9...
    ...
    -----END RSA PRIVATE KEY-----

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Managing access with runner groups

You can use runner groups to control which organizations or repositories have access to your runner scale sets. For more information on runner groups, see AUTOTITLE.

To add a runner scale set to a runner group, you must already have a runner group created. Then set the runnerGroup property in your copy of the values.yaml file. The following example adds a runner scale set to the Octo-Group runner group.

runnerGroup: "Octo-Group"

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Configuring an outbound proxy

To force HTTP traffic for the controller and runners to go through your outbound proxy, set the following properties in your Helm chart.

proxy:
  http:
    url: http://proxy.com:1234
    credentialSecretRef: proxy-auth # a Kubernetes secret with `username` and `password` keys
  https:
    url: http://proxy.com:1234
    credentialSecretRef: proxy-auth # a Kubernetes secret with `username` and `password` keys
  noProxy:
    - example.com
    - example.org

ARC supports using anonymous or authenticated proxies. If you use authenticated proxies, you will need to set the credentialSecretRef value to reference a Kubernetes secret. You can create a secret with your proxy credentials with the following command.

{% data reusables.actions.arc-runners-namespace %}

  kubectl create secret generic proxy-auth \
    --namespace=arc-runners \
    --from-literal=username=proxyUsername \
    --from-literal=password=proxyPassword \

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Setting the maximum and minimum number of runners

The maxRunners and minRunners properties provide you with a range of options to customize your ARC setup.

Note

ARC does not support scheduled maximum and minimum configurations. You can use a cronjob or any other scheduling solution to update the configuration on a schedule.

Example: Unbounded number of runners

If you comment out both the maxRunners and minRunners properties, ARC will scale up to the number of jobs assigned to the runner scale set and will scale down to 0 if there aren't any active jobs.

## maxRunners is the max number of runners the auto scaling runner set will scale up to.
# maxRunners: 0

## minRunners is the min number of idle runners. The target number of runners created will be
## calculated as a sum of minRunners and the number of jobs assigned to the scale set.
# minRunners: 0

Example: Minimum number of runners

You can set the minRunners property to any number and ARC will make sure there is always the specified number of runners active and available to take jobs assigned to the runner scale set at all times.

## maxRunners is the max number of runners the auto scaling runner set will scale up to.
# maxRunners: 0

## minRunners is the min number of idle runners. The target number of runners created will be
## calculated as a sum of minRunners and the number of jobs assigned to the scale set.
minRunners: 20

Example: Set maximum and minimum number of runners

In this configuration, {% data variables.product.prodname_actions_runner_controller %} will scale up to a maximum of 30 runners and will scale down to 20 runners when the jobs are complete.

Note

The value of minRunners can never exceed that of maxRunners, unless maxRunners is commented out.

## maxRunners is the max number of runners the auto scaling runner set will scale up to.
maxRunners: 30

## minRunners is the min number of idle runners. The target number of runners created will be
## calculated as a sum of minRunners and the number of jobs assigned to the scale set.
minRunners: 20

Example: Jobs queue draining

In certain scenarios you might want to drain the jobs queue to troubleshoot a problem or to perform maintenance on your cluster. If you set both properties to 0, {% data variables.product.prodname_actions_runner_controller %} will not create new runner pods when new jobs are available and assigned.

## maxRunners is the max number of runners the auto scaling runner set will scale up to.
maxRunners: 0

## minRunners is the min number of idle runners. The target number of runners created will be
## calculated as a sum of minRunners and the number of jobs assigned to the scale set.
minRunners: 0

Custom TLS certificates

Note

If you are using a custom runner image that is not based on the Debian distribution, the following instructions will not work.

Some environments require TLS certificates that are signed by a custom certificate authority (CA). Since the custom certificate authority certificates are not bundled with the controller or runner containers, you must inject them into their respective trust stores.

githubServerTLS:
  certificateFrom:
    configMapKeyRef:
      name: config-map-name
      key: ca.crt
  runnerMountPath: /usr/local/share/ca-certificates/

When you do this, ensure you are using the Privacy Enhanced Mail (PEM) format and that the extension of your certificate is .crt. Anything else will be ignored.

The controller executes the following actions.

  • Creates a github-server-tls-cert volume containing the certificate specified in certificateFrom.
  • Mounts that volume on path runnerMountPath/<certificate name>.
  • Sets the NODE_EXTRA_CA_CERTS environment variable to that same path.
  • Sets the RUNNER_UPDATE_CA_CERTS environment variable to 1 (as of version 2.303.0, this will instruct the runner to reload certificates on the host).

ARC observes values set in the runner pod template and does not overwrite them.

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Using a private container registry

{% data reusables.actions.actions-runner-controller-unsupported-customization %}

To use a private container registry, you can copy the controller image and runner image to your private container registry. Then configure the links to those images and set the imagePullPolicy and imagePullSecrets values.

Configuring the controller image

You can update your copy of the values.yaml file and set the image properties as follows.

image:
  repository: "custom-registry.io/gha-runner-scale-set-controller"
  pullPolicy: IfNotPresent
  # Overrides the image tag whose default is the chart appVersion.
  tag: "0.4.0"

imagePullSecrets:
  - name: <registry-secret-name>

The listener container inherits the imagePullPolicy defined for the controller.

Configuring the runner image

You can update your copy of the values.yaml file and set the template.spec properties as follows.

template:
  spec:
    containers:
      - name: runner
        image: "custom-registry.io/actions-runner:latest"
        imagePullPolicy: Always
        command: ["/home/runner/run.sh"]
    imagePullSecrets:
      - name: <registry-secret-name>

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Updating the pod specification for the runner pod

{% data reusables.actions.actions-runner-controller-unsupported-customization %}

You can fully customize the PodSpec of the runner pod and the controller will apply the configuration you specify. The following is an example pod specification.

template:
  spec:
    containers:
      - name: runner
        image: ghcr.io/actions/actions-runner:latest
        command: ["/home/runner/run.sh"]
        resources:
          limits:
            cpu: 500m
            memory: 512Mi
        securityContext:
          readOnlyRootFilesystem: true
          allowPrivilegeEscalation: false
          capabilities:
            add:
              - NET_ADMIN

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Updating the pod specification for the listener pod

{% data reusables.actions.actions-runner-controller-unsupported-customization %}

You can customize the PodSpec of the listener pod and the controller will apply the configuration you specify. The following is an example pod specification.

Note

It's important to not change the listenerTemplate.spec.containers.name value of the listener container. Otherwise, the configuration you specify will be applied to a new side-car container.

listenerTemplate:
  spec:
    containers:
    # If you change the name of the container, the configuration will not be applied to the listener,
    # and it will be treated as a side-car container.
    - name: listener
      securityContext:
        runAsUser: 1000
      resources:
        limits:
          cpu: "1"
          memory: 1Gi
        requests:
          cpu: "1"
          memory: 1Gi

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Using Docker-in-Docker or Kubernetes mode for containers

{% data reusables.actions.actions-runner-controller-unsupported-customization %}

If you are using container jobs and services or container actions, the containerMode value must be set to dind or kubernetes.

  • For more information on container jobs and services, see AUTOTITLE.
  • For more information on container actions, see AUTOTITLE.

Using Docker-in-Docker mode

Note

The Docker-in-Docker container requires privileged mode. For more information, see Configure a Security Context for a Pod or Container in the Kubernetes documentation.

By default, the dind container uses the docker:dind image, which runs the Docker daemon as root. You can replace this image with docker:dind-rootless as long as you are aware of the known limitations and run the pods with --privileged mode. To learn how to customize the Docker-in-Docker configuration, see Customizing container modes.

Docker-in-Docker mode is a configuration that allows you to run Docker inside a Docker container. In this configuration, for each runner pod created, ARC creates the following containers.

  • An init container
  • A runner container
  • A dind container

To enable Docker-in-Docker mode, set the containerMode.type to dind as follows.

containerMode:
  type: "dind"

The template.spec will be updated to the following default configuration.

template:
  spec:
    initContainers:
      - name: init-dind-externals
        image: ghcr.io/actions/actions-runner:latest
        command:
          ["cp", "-r", "/home/runner/externals/.", "/home/runner/tmpDir/"]
        volumeMounts:
          - name: dind-externals
            mountPath: /home/runner/tmpDir
    containers:
      - name: runner
        image: ghcr.io/actions/actions-runner:latest
        command: ["/home/runner/run.sh"]
        env:
          - name: DOCKER_HOST
            value: unix:///var/run/docker.sock
        volumeMounts:
          - name: work
            mountPath: /home/runner/_work
          - name: dind-sock
            mountPath: /var/run
      - name: dind
        image: docker:dind
        args:
          - dockerd
          - --host=unix:///var/run/docker.sock
          - --group=$(DOCKER_GROUP_GID)
        env:
          - name: DOCKER_GROUP_GID
            value: "123"
        securityContext:
          privileged: true
        volumeMounts:
          - name: work
            mountPath: /home/runner/_work
          - name: dind-sock
            mountPath: /var/run
          - name: dind-externals
            mountPath: /home/runner/externals
    volumes:
      - name: work
        emptyDir: {}
      - name: dind-sock
        emptyDir: {}
      - name: dind-externals
        emptyDir: {}

The values in template.spec are automatically injected and cannot be overridden. If you want to customize this setup, you must unset containerMode.type, then copy this configuration and apply it directly in your copy of the values.yaml file.

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Using Kubernetes mode

In Kubernetes mode, ARC uses runner container hooks to create a new pod in the same namespace to run the service, container job, or action.

Prerequisites

Kubernetes mode relies on persistent volumes to share job details between the runner pod and the container job pod. For more information, see the Persistent Volumes section in the Kubernetes documentation.

To use Kubernetes mode, you must do the following.

  • Create persistent volumes available for the runner pods to claim.
  • Use a solution to automatically provision persistent volumes on demand.

For testing, you can use a solution like OpenEBS.

Configuring Kubernetes mode

To enable Kubernetes mode, set the containerMode.type to kubernetes in your values.yaml file.

containerMode:
  type: "kubernetes"
  kubernetesModeWorkVolumeClaim:
    accessModes: ["ReadWriteOnce"]
    storageClassName: "dynamic-blob-storage"
    resources:
      requests:
        storage: 1Gi

{% data reusables.actions.actions-runner-controller-helm-chart-options %}

Note

When Kubernetes mode is enabled, workflows that are not configured with a container job will fail with an error similar to:

Jobs without a job container are forbidden on this runner, please add a 'container:' to your job or contact your self-hosted runner administrator.

To allow jobs without a job container to run, set ACTIONS_RUNNER_REQUIRE_JOB_CONTAINER to false on your runner container. This instructs the runner to disable this check.

template:
  spec:
    containers:
      - name: runner
        image: ghcr.io/actions/actions-runner:latest
        command: ["/home/runner/run.sh"]
        env:
          - name: ACTIONS_RUNNER_REQUIRE_JOB_CONTAINER
            value: "false"

Customizing container modes

When you set the containerMode in the values.yaml file for the gha-runner-scale-set helm chart, you can use either of the following values:

  • dind or
  • kubernetes

Depending on which value you set for the containerMode, a configuration will automatically be injected into the template section of the values.yaml file for the gha-runner-scale-set helm chart.

To customize the spec, comment out or remove containerMode, and append the configuration you want in the template section.

Example: running dind-rootless

Before deciding to run dind-rootless, make sure you are aware of known limitations. {% ifversion not ghes %}

## githubConfigUrl is the GitHub url for where you want to configure runners
## ex: https://github.com./myorg/myrepo or https://github.com./myorg
githubConfigUrl: "https://github.com./actions/actions-runner-controller"

## githubConfigSecret is the k8s secrets to use when auth with GitHub API.
## You can choose to use GitHub App or a PAT token
githubConfigSecret: my-super-safe-secret

## maxRunners is the max number of runners the autoscaling runner set will scale up to.
maxRunners: 5

## minRunners is the min number of idle runners. The target number of runners created will be
## calculated as a sum of minRunners and the number of jobs assigned to the scale set.
minRunners: 0

runnerGroup: "my-custom-runner-group"

## name of the runner scale set to create. Defaults to the helm release name
runnerScaleSetName: "my-awesome-scale-set"

## template is the PodSpec for each runner Pod
## For reference: https://kubernetes.io/docs/reference/kubernetes-api/workload-resources/pod-v1/#PodSpec
template:
  spec:
    initContainers:
    - name: init-dind-externals
      image: ghcr.io/actions/actions-runner:latest
      command: ["cp", "-r", "/home/runner/externals/.", "/home/runner/tmpDir/"]
      volumeMounts:
        - name: dind-externals
          mountPath: /home/runner/tmpDir
    - name: init-dind-rootless
      image: docker:dind-rootless
      command:
        - sh
        - -c
        - |
          set -x
          cp -a /etc/. /dind-etc/
          echo 'runner:x:1001:1001:runner:/home/runner:/bin/ash' >> /dind-etc/passwd
          echo 'runner:x:1001:' >> /dind-etc/group
          echo 'runner:100000:65536' >> /dind-etc/subgid
          echo 'runner:100000:65536' >> /dind-etc/subuid
          chmod 755 /dind-etc;
          chmod u=rwx,g=rx+s,o=rx /dind-home
          chown 1001:1001 /dind-home
      securityContext:
        runAsUser: 0
      volumeMounts:
        - mountPath: /dind-etc
          name: dind-etc
        - mountPath: /dind-home
          name: dind-home
    containers:
    - name: runner
      image: ghcr.io/actions/actions-runner:latest
      command: ["/home/runner/run.sh"]
      env:
        - name: DOCKER_HOST
          value: unix:///run/user/1001/docker.sock
      securityContext:
        privileged: true
        runAsUser: 1001
        runAsGroup: 1001
      volumeMounts:
        - name: work
          mountPath: /home/runner/_work
        - name: dind-sock
          mountPath: /run/user/1001
    - name: dind
      image: docker:dind-rootless
      args:
        - dockerd
        - --host=unix:///run/user/1001/docker.sock
      securityContext:
        privileged: true
        runAsUser: 1001
        runAsGroup: 1001
      volumeMounts:
        - name: work
          mountPath: /home/runner/_work
        - name: dind-sock
          mountPath: /run/user/1001
        - name: dind-externals
          mountPath: /home/runner/externals
        - name: dind-etc
          mountPath: /etc
        - name: dind-home
          mountPath: /home/runner
    volumes:
    - name: work
      emptyDir: {}
    - name: dind-externals
      emptyDir: {}
    - name: dind-sock
      emptyDir: {}
    - name: dind-etc
      emptyDir: {}
    - name: dind-home
      emptyDir: {}

{% endif %} {% ifversion ghes %}

## githubConfigUrl is the GitHub url for where you want to configure runners
## ex: https://<HOSTNAME>/enterprises/my_enterprise or https://<HOSTNAME>/myorg
githubConfigUrl: "https://<HOSTNAME>/actions/actions-runner-controller"

## githubConfigSecret is the k8s secrets to use when auth with GitHub API.
## You can choose to use GitHub App or a PAT token
githubConfigSecret: my-super-safe-secret

## maxRunners is the max number of runners the autoscaling runner set will scale up to.
maxRunners: 5

## minRunners is the min number of idle runners. The target number of runners created will be
## calculated as a sum of minRunners and the number of jobs assigned to the scale set.
minRunners: 0

runnerGroup: "my-custom-runner-group"

## name of the runner scale set to create. Defaults to the helm release name
runnerScaleSetName: "my-awesome-scale-set"

## template is the PodSpec for each runner Pod
## For reference: https://kubernetes.io/docs/reference/kubernetes-api/workload-resources/pod-v1/#PodSpec
template:
  spec:
    initContainers:
    - name: init-dind-externals
      image: ghcr.io/actions/actions-runner:latest
      command: ["cp", "-r", "/home/runner/externals/.", "/home/runner/tmpDir/"]
      volumeMounts:
        - name: dind-externals
          mountPath: /home/runner/tmpDir
    - name: init-dind-rootless
      image: docker:dind-rootless
      command:
        - sh
        - -c
        - |
          set -x
          cp -a /etc/. /dind-etc/
          echo 'runner:x:1001:1001:runner:/home/runner:/bin/ash' >> /dind-etc/passwd
          echo 'runner:x:1001:' >> /dind-etc/group
          echo 'runner:100000:65536' >> /dind-etc/subgid
          echo 'runner:100000:65536' >> /dind-etc/subuid
          chmod 755 /dind-etc;
          chmod u=rwx,g=rx+s,o=rx /dind-home
          chown 1001:1001 /dind-home
      securityContext:
        runAsUser: 0
      volumeMounts:
        - mountPath: /dind-etc
          name: dind-etc
        - mountPath: /dind-home
          name: dind-home
    containers:
    - name: runner
      image: ghcr.io/actions/actions-runner:latest
      command: ["/home/runner/run.sh"]
      env:
        - name: DOCKER_HOST
          value: unix:///run/user/1001/docker.sock
      securityContext:
        privileged: true
        runAsUser: 1001
        runAsGroup: 1001
      volumeMounts:
        - name: work
          mountPath: /home/runner/_work
        - name: dind-sock
          mountPath: /run/user/1001
    - name: dind
      image: docker:dind-rootless
      args:
        - dockerd
        - --host=unix:///run/user/1001/docker.sock
      securityContext:
        privileged: true
        runAsUser: 1001
        runAsGroup: 1001
      volumeMounts:
        - name: work
          mountPath: /home/runner/_work
        - name: dind-sock
          mountPath: /run/user/1001
        - name: dind-externals
          mountPath: /home/runner/externals
        - name: dind-etc
          mountPath: /etc
        - name: dind-home
          mountPath: /home/runner
    volumes:
    - name: work
      emptyDir: {}
    - name: dind-externals
      emptyDir: {}
    - name: dind-sock
      emptyDir: {}
    - name: dind-etc
      emptyDir: {}
    - name: dind-home
      emptyDir: {}

{% endif %}

Understanding runner-container-hooks

When the runner detects a workflow run that uses a container job, service container, or Docker action, it will call runner-container-hooks to create a new pod. The runner relies on runner-container-hooks to call the Kubernetes APIs and create a new pod in the same namespace as the runner pod. This newly created pod will be used to run the container job, service container, or Docker action. For more information, see the runner-container-hooks repository.

Configuring hook extensions

As of ARC version 0.4.0, runner-container-hooks support hook extensions. You can use these to configure the pod created by runner-container-hooks. For example, you could use a hook extension to set a security context on the pod. Hook extensions allow you to specify a YAML file that is used to update the PodSpec of the pod created by runner-container-hooks.

There are two options to configure hook extensions.

  • Store in your custom runner image. You can store the PodSpec in a YAML file anywhere in your custom runner image. For more information, see AUTOTITLE.
  • Store in a ConfigMap. You can create a config map with the PodSpec and mount that config map in the runner container. For more information, see ConfigMaps in the Kubernetes documentation.

Note

With both options, you must set the ACTIONS_RUNNER_CONTAINER_HOOK_TEMPLATE environment variable in the runner container spec to point to the path of the YAML file mounted in the runner container.

Example: Using config map to set securityContext

Create a config map in the same namespace as the runner pods. For example:

apiVersion: v1
kind: ConfigMap
metadata:
  name: hook-extension
  namespace: arc-runners
data:
  content: |
    metadata:
      annotations:
        example: "extension"
    spec:
      containers:
        - name: "$job" # Target the job container
          securityContext:
            runAsUser: 1000
  • The .metadata.labels and metadata.annotations fields will be appended as is, unless their keys are reserved. You cannot override the .metadata.name and metadata.namespace fields.
  • The majority of the PodSpec fields are applied from the specified template, and will override the values passed from your Helm chart values.yaml file.
  • If you specify additional volumes they will be appended to the default volumes specified by the runner.
  • The spec.containers are merged based on the names assigned to them.
    • If the name of the container is $job:
      • The spec.containers.name and spec.containers.image fields are ignored.
      • The spec.containers.env, spec.containers.volumeMounts, and spec.containers.ports fields are appended to the default container spec created by the hook.
      • The rest of the fields are applied as provided.
    • If the name of the container is not $job, the fields will be added to the pod definition as they are.

Enabling metrics

Note

Metrics for ARC are available as of version gha-runner-scale-set-0.5.0.

ARC can emit metrics about your runners, your jobs, and time spent on executing your workflows. Metrics can be used to identify congestion, monitor the health of your ARC deployment, visualize usage trends, optimize resource consumption, among many other use cases. Metrics are emitted by the controller-manager and listener pods in Prometheus format. For more information, see Exposition formats in the Prometheus documentation.

To enable metrics for ARC, configure the metrics property in the values.yaml file of the gha-runner-scale-set-controller chart.

The following is an example configuration.

metrics:
  controllerManagerAddr: ":8080"
  listenerAddr: ":8080"
  listenerEndpoint: "/metrics"

Note

If the metrics: object is not provided or is commented out, the following flags will be applied to the controller-manager and listener pods with empty values: --metrics-addr, --listener-metrics-addr, --listener-metrics-endpoint. This will disable metrics for ARC.

Once these properties are configured, your controller-manager and listener pods emit metrics via the listenerEndpoint bound to the ports that you specify in your values.yaml file. In the above example, the endpoint is /metrics and the port is :8080. You can use this endpoint to scrape metrics from your controller-manager and listener pods.

To turn off metrics, update your values.yaml file by removing or commenting out the metrics: object and its properties.

Available metrics for ARC

The following table shows the metrics emitted by the controller-manager and listener pods.

Note

The metrics that the controller-manager emits pertain to the controller runtime and are not owned by {% data variables.product.company_short %}.

Owner Metric Type Description
controller-manager gha_controller_pending_ephemeral_runners gauge Number of ephemeral runners in a pending state
controller-manager gha_controller_running_ephemeral_runners gauge Number of ephemeral runners in a running state
controller-manager gha_controller_failed_ephemeral_runners gauge Number of ephemeral runners in a failed state
controller-manager gha_controller_running_listeners gauge Number of listeners in a running state
listener gha_assigned_jobs gauge Number of jobs assigned to the runner scale set
listener gha_running_jobs gauge Number of jobs running or queued to run
listener gha_registered_runners gauge Number of runners registered by the runner scale set
listener gha_busy_runners gauge Number of registered runners currently running a job
listener gha_min_runners gauge Minimum number of runners configured for the runner scale set
listener gha_max_runners gauge Maximum number of runners configured for the runner scale set
listener gha_desired_runners gauge Number of runners desired (scale up / down target) by the runner scale set
listener gha_idle_runners gauge Number of registered runners not running a job
listener gha_started_jobs_total counter Total number of jobs started since the listener became ready [1]
listener gha_completed_jobs_total counter Total number of jobs completed since the listener became ready [1]
listener gha_job_startup_duration_seconds histogram Number of seconds spent waiting for workflow job to get started on the runner owned by the runner scale set
listener gha_job_execution_duration_seconds histogram Number of seconds spent executing workflow jobs by the runner scale set

[1]: Listener metrics that have the counter type are reset when the listener pod restarts.

{% ifversion ghes %}

Using ARC with {% data variables.product.prodname_dependabot %} and {% data variables.product.prodname_code_scanning %}

You can use {% data variables.product.prodname_actions_runner_controller %} to create dedicated runners for your {% data variables.product.prodname_ghe_server %} instance that {% data variables.product.prodname_dependabot %} can use to help secure and maintain the dependencies used in repositories on your enterprise. For more information, see AUTOTITLE.

You can also use ARC with {% data variables.product.prodname_codeql %} to identify vulnerabilities and errors in your code. For more information, see AUTOTITLE. If you're already using {% data variables.product.prodname_code_scanning %} and want to configure a runner scale set to use default setup, set INSTALLATION_NAME=code-scanning. For more information about {% data variables.product.prodname_code_scanning %} default setup, see AUTOTITLE.

{% data variables.product.prodname_actions_runner_controller %} does not use multiple labels to route jobs to specific runner scale sets. Instead, to designate a runner scale set for {% data variables.product.prodname_dependabot %} updates or {% data variables.product.prodname_code_scanning %} with {% data variables.product.prodname_codeql %}, use a descriptive installation name in your Helm chart, such as dependabot or code-scanning. You can then set the runs-on value in your workflows to the installation name as the single label, and use the designated runner scale set for {% data variables.product.prodname_dependabot %} updates or {% data variables.product.prodname_code_scanning %} jobs.

If you're using default setup for {% data variables.product.prodname_code_scanning %}, the analysis will automatically look for a runner scale set with the installation name code-scanning {% ifversion code-scanning-default-setup-customize-labels %} but you can specify a custom name in the configuration, so that individual repositories can use different runner scale sets. See AUTOTITLE{% endif %}.

Note

The Dependabot Action is used to run {% data variables.product.prodname_dependabot %} updates via {% data variables.product.prodname_actions %}. This action requires Docker as a dependency. For this reason, you can only use {% data variables.product.prodname_actions_runner_controller %} with {% data variables.product.prodname_dependabot %} when Docker-in-Docker (DinD) mode is enabled. For more information, see AUTOTITLE and AUTOTITLE.

{% endif %}

Upgrading ARC

Because there is no support for upgrading or deleting CRDs with Helm, it is not possible to use Helm to upgrade ARC. For more information, see Custom Resource Definitions in the Helm documentation. To upgrade ARC to a newer version, you must complete the following steps.

  1. Uninstall all installations of gha-runner-scale-set.
  2. Wait for resources cleanup.
  3. Uninstall ARC.
  4. If there is a change in CRDs from the version you currently have installed, to the upgraded version, remove all CRDs associated with actions.github.com. API group.
  5. Reinstall ARC again.

For more information, see Deploying a runner scale set.

If you would like to upgrade ARC but are concerned about downtime, you can deploy ARC in a high availability configuration to ensure runners are always available. For more information, see High availability and automatic failover.

Note

Transitioning from the community supported version of ARC to the GitHub supported version is a substantial architectural change. The GitHub supported version involves a redesign of many components of ARC. It is not a minor software upgrade. For these reasons, we recommend testing the new versions in a staging environment that matches your production environment first. This will ensure stability and reliability of the setup before deploying in production.

Deploying a canary image

You can test features before they are released by using canary releases of the controller-manager container image. Canary images are published with tag format canary-SHORT_SHA. For more information, see gha-runner-scale-set-controller on the {% data variables.product.prodname_container_registry %}.

Note

  • You must use Helm charts on your local file system.
  • You cannot use the released Helm charts.
  1. Update the tag in the gha-runner-scale-set-controller values.yaml file to: canary-SHORT_SHA
  2. Update the field appVersion in the Chart.yaml file for gha-runner-scale-set to: canary-SHORT_SHA
  3. Re-install ARC using the updated Helm chart and values.yaml files.

High availability and automatic failover

ARC can be deployed in a high availability (active-active) configuration. If you have two distinct Kubernetes clusters deployed in separate regions, you can deploy ARC in both clusters and configure runner scale sets to use the same runnerScaleSetName. In order to do this, each runner scale set must be assigned to a distinct runner group. For example, you can have two runner scale sets each named arc-runner-set, as long as one runner scale set belongs to runner-group-A and the other runner scale set belongs to runner-group-B. For information on assigning runner scale sets to runner groups, see AUTOTITLE.

If both runner scale sets are online, jobs assigned to them will be distributed arbitrarily (assignment race). You cannot configure the job assignment algorithm. If one of the clusters goes down, the runner scale set in the other cluster will continue to acquire jobs normally without any intervention or configuration change.

Using ARC across organizations

A single installation of {% data variables.product.prodname_actions_runner_controller %} allows you to configure one or more runner scale sets. These runner scale sets can be registered to a repository, organization, or enterprise. You can also use runner groups to control the permissions boundaries of these runner scale sets.

As a best practice, create a unique namespace for each organization. You could also create a namespace for each runner group or each runner scale set. You can install as many runner scale sets as needed in each namespace. This will provide you the highest levels of isolation and improve your security. You can use {% data variables.product.prodname_github_apps %} for authentication and define granular permissions for each runner scale set.

Legal notice

{% data reusables.actions.actions-runner-controller-legal-notice %}