About runner scale sets
Runner scale sets is a group of homogeneous runners that can be assigned jobs from GitHub Actions. The number of active runners owned by a runner scale set can be controlled by auto-scaling runner solutions such as 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 Managing access to self-hosted runners using groups.
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 Using Actions Runner Controller runners in a workflow.
Deploying a runner scale set
To deploy a runner scale set, you must have ARC up and running. For more information, see Quickstart for Actions Runner Controller.
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
- As a security best practice, create your runner pods in a different namespace than the namespace containing your operator pods.
- As a security best practice, create Kubernetes secrets and pass the secret references. Passing your secrets in plain text via the CLI can pose a security risk.
- We recommend running production workloads in isolation. GitHub 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.
-
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 ofruns-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 theactions-runner-controller
repository.Bash 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 "${INSTALLATION_NAME}" \ --namespace "${NAMESPACE}" \ --create-namespace \ --set githubConfigUrl="${GITHUB_CONFIG_URL}" \ --set githubConfigSecret.github_token="${GITHUB_PAT}" \ oci://ghcr.io/actions/actions-runner-controller-charts/gha-runner-scale-set
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 "${INSTALLATION_NAME}" \ --namespace "${NAMESPACE}" \ --create-namespace \ --set githubConfigUrl="${GITHUB_CONFIG_URL}" \ --set githubConfigSecret.github_token="${GITHUB_PAT}" \ oci://ghcr.io/actions/actions-runner-controller-charts/gha-runner-scale-set
For additional Helm configuration options, see
values.yaml
in the ARC repository.
-
-
To check your installation, run the following command in your terminal.
Bash helm list -A
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
-
To check the manager pod, run the following command in your terminal.
Bash kubectl get pods -n arc-systems
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 Troubleshooting Actions Runner Controller errors 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.
Note
You can only deploy runner scale sets at the enterprise level when using personal access token (classic) authentication.
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
.
githubConfigUrl: "http(s)://<HOSTNAME>/<'enterprises/your_enterprise'/'org'/'org/repo'>"
For additional Helm configuration options, see values.yaml
in the ARC repository.
Using a GitHub App for authentication
If you are not using enterprise-level runners, you can use GitHub Apps to authenticate with the GitHub API. For more information, see Authenticating to the GitHub API.
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 GitHub App, create a Kubernetes secret and pass the reference to that secret in your copy of the values.yaml
file.
Note
Create the secret in the same namespace where the gha-runner-scale-set
chart is installed. In this example, the namespace is arc-runners
to match the quickstart documentation. For more information, see "Quickstart for Actions Runner Controller."
kubectl create secret generic pre-defined-secret \
--namespace=arc-runners \
--from-literal=github_app_id=123456 \
--from-literal=github_app_installation_id=654321 \
--from-literal=github_app_private_key='-----BEGIN RSA PRIVATE KEY-----********'
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 personal access token (classic)
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-----
For additional Helm configuration options, see values.yaml
in the ARC repository.
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 Managing access to self-hosted runners using groups.
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"
For additional Helm configuration options, see values.yaml
in the ARC repository.
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.
Note
Create the secret in the same namespace where the gha-runner-scale-set
chart is installed. In this example, the namespace is arc-runners
to match the quickstart documentation. For more information, see "Quickstart for Actions Runner Controller."
kubectl create secret generic proxy-auth \ --namespace=arc-runners \ --from-literal=username=proxyUsername \ --from-literal=password=proxyPassword \
kubectl create secret generic proxy-auth \
--namespace=arc-runners \
--from-literal=username=proxyUsername \
--from-literal=password=proxyPassword \
For additional Helm configuration options, see values.yaml
in the ARC repository.
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, 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
, 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 incertificateFrom
. - 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 to1
(as of version2.303.0
, 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.
For additional Helm configuration options, see values.yaml
in the ARC repository.
Using a private container registry
Warning
This Actions Runner Controller customization option may be outside the scope of what GitHub Support can assist with and may cause unexpected behavior when configured incorrectly.
For more information about what GitHub Support can assist with, see About support for Actions Runner Controller.
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>
For additional Helm configuration options, see values.yaml
in the ARC repository.
Updating the pod specification for the runner pod
Warning
This Actions Runner Controller customization option may be outside the scope of what GitHub Support can assist with and may cause unexpected behavior when configured incorrectly.
For more information about what GitHub Support can assist with, see About support for Actions Runner Controller.
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
For additional Helm configuration options, see values.yaml
in the ARC repository.
Updating the pod specification for the listener pod
Warning
This Actions Runner Controller customization option may be outside the scope of what GitHub Support can assist with and may cause unexpected behavior when configured incorrectly.
For more information about what GitHub Support can assist with, see About support for Actions Runner Controller.
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
For additional Helm configuration options, see values.yaml
in the ARC repository.
Using Docker-in-Docker or Kubernetes mode for containers
Warning
This Actions Runner Controller customization option may be outside the scope of what GitHub Support can assist with and may cause unexpected behavior when configured incorrectly.
For more information about what GitHub Support can assist with, see About support for Actions Runner Controller.
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 Running jobs in a container.
- For more information on container actions, see Creating a Docker container action.
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.
For additional Helm configuration options, see values.yaml
in the ARC repository.
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
For additional Helm configuration options, see values.yaml
in the ARC repository.
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
orkubernetes
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.
- See the
dind
configuration. - See the
kubernetes
configuration.
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.
## 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:///var/run/docker.sock
volumeMounts:
- name: work
mountPath: /home/runner/_work
- name: dind-sock
mountPath: /var/run
- name: dind
image: docker:dind-rootless
args:
- dockerd
- --host=unix:///var/run/docker.sock
securityContext:
privileged: true
runAsUser: 1001
runAsGroup: 1001
volumeMounts:
- name: work
mountPath: /home/runner/_work
- name: dind-sock
mountPath: /var/run
- 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: {}
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 About Actions Runner Controller.
- 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
andmetadata.annotations
fields will be appended as is, unless their keys are reserved. You cannot override the.metadata.name
andmetadata.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
andspec.containers.image
fields are ignored. - The
spec.containers.env
,spec.containers.volumeMounts
, andspec.containers.ports
fields are appended to the default container spec created by the hook. - The rest of the fields are applied as provided.
- The
- If the name of the container is not
$job
, the fields will be added to the pod definition as they are.
- If the name of the container is
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 GitHub.
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] |
[1]: Listener metrics that have the counter type are reset when the listener pod restarts.
Using ARC with Dependabot and code scanning
You can use Actions Runner Controller to create dedicated runners for your GitHub Enterprise Server instance that Dependabot can use to help secure and maintain the dependencies used in repositories on your enterprise. For more information, see Managing self-hosted runners for Dependabot updates on your enterprise.
You can also use ARC with CodeQL to identify vulnerabilities and errors in your code. For more information, see About code scanning with CodeQL. If you're already using code scanning and want to configure a runner scale set to use default setup, set INSTALLATION_NAME=code-scanning
. For more information about code scanning default setup, see Configuring default setup for code scanning.
Actions Runner Controller does not use multiple labels to route jobs to specific runner scale sets. Instead, to designate a runner scale set for Dependabot updates or code scanning with 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 Dependabot updates or code scanning jobs.
If you're using default setup for code scanning, the analysis will automatically look for a runner scale set with the installation name code-scanning
.
Note
The Dependabot Action is used to run Dependabot updates via GitHub Actions. This action requires Docker as a dependency. For this reason, you can only use Actions Runner Controller with Dependabot when Docker-in-Docker (DinD) mode is enabled. For more information, see Managing self-hosted runners for Dependabot updates on your enterprise and Deploying runner scale sets with Actions Runner Controller.
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.
- Uninstall all installations of
gha-runner-scale-set
. - Wait for resources cleanup.
- Uninstall ARC.
- 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. - 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 Container registry.
Note
- You must use Helm charts on your local file system.
- You cannot use the released Helm charts.
- Update the
tag
in the gha-runner-scale-set-controllervalues.yaml
file to:canary-SHORT_SHA
- Update the field
appVersion
in theChart.yaml
file forgha-runner-scale-set
to:canary-SHORT_SHA
- 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 Managing access to self-hosted runners using groups.
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 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 GitHub Apps for authentication and define granular permissions for each runner scale set.
Legal notice
Portions have been adapted from https://github.com/actions/actions-runner-controller/ under the Apache-2.0 license:
Copyright 2019 Moto Ishizawa
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.