[GitHub Actions](https://github.com/features/actions) is a very useful tool for automating development. GitHub Actions jobs are run in the cloud by default, but you may want to run your jobs in your environment. [Self-hosted runner](https://github.com/actions/runner) can be used for such use cases, but requires the provisioning and configuration of a virtual machine instance. Instead if you already have a Kubernetes cluster, it makes more sense to run the self-hosted runner on top of it.
**actions-runner-controller** makes that possible. Just create a *Runner* resource on your Kubernetes, and it will run and operate the self-hosted runner for the specified repository. Combined with Kubernetes RBAC, you can also build simple Self-hosted runners as a Service.
actions-runner-controller uses [cert-manager](https://cert-manager.io/docs/installation/kubernetes/) for certificate management of Admission Webhook. Make sure you have already installed cert-manager before you install. The installation instructions for cert-manager can be found below.
- [Installing cert-manager on Kubernetes](https://cert-manager.io/docs/installation/kubernetes/)
Install the custom resource and actions-runner-controller with `kubectl` or `helm`. This will create actions-runner-system namespace in your Kubernetes and deploy the required resources.
The solution supports both GitHub Enterprise Cloud and Server editions as well as regular GitHub. Both PAT (personal access token) and GitHub App authentication works for installations that will be deploying either repository level and / or organization level runners. If you need to deploy enterprise level runners then you are restricted to PAT based authentication as GitHub doesn't support GitHub App based authentication for enterprise runners currently.
If you are deploying this solution into a GitHub Enterprise Server environment then you will need version >= [3.0.0](https://docs.github.com/en/enterprise-server@3.0/admin/release-notes#3.0.0).
When deploying the solution for a GitHub Enterprise Server environment you need to provide an additional environment variable as part of the controller deployment:
__**Note: The repository maintainers do not have an enterprise environment (cloud or server). Support for the enterprise specific feature set is community driven and on a best effort basis. PRs from the community are welcomed to add features and maintain support.**__
Functionality wise, there isn't much of a difference between the 2 authentication methods. The primarily benefit of authenticating via a GitHub App is an [increased API quota](https://docs.github.com/en/developers/apps/rate-limits-for-github-apps).
If you are deploying the solution for a GitHub Enterprise Server environment you are able to [configure your rate limiting settings](https://docs.github.com/en/enterprise-server@3.0/admin/configuration/configuring-rate-limits) making the main benefit irrelevant. If you're deploying the solution for a GitHub Enterprise Cloud or regular GitHub environment and you run into rate limiting issues, consider deploying the solution using the GitHub App authentication method instead.
You can create a GitHub App for either your user account or any organization, below are the app permissions required for each supported type of runner:
_Note: Links are provided further down to create an app for your logged in user account or an organisation with the permissions for all runner types set in each link's query string_
_Note: All API routes mapped to their permissions can be found [here](https://docs.github.com/en/rest/reference/permissions-required-for-github-apps) if you wish to review_
---
**Setup Steps**
If you want to create a GitHub App for your account, open the following link to the creation page, enter any unique name in the "GitHub App name" field, and hit the "Create GitHub App" button at the bottom of the page.
- [Create GitHub Apps on your account](https://github.com/settings/apps/new?url=http://github.com/actions-runner-controller/actions-runner-controller&webhook_active=false&public=false&administration=write&actions=read)
If you want to create a GitHub App for your organization, replace the `:org` part of the following URL with your organization name before opening it. Then enter any unique name in the "GitHub App name" field, and hit the "Create GitHub App" button at the bottom of the page to create a GitHub App.
- [Create GitHub Apps on your organization](https://github.com/organizations/:org/settings/apps/new?url=http://github.com/actions-runner-controller/actions-runner-controller&webhook_active=false&public=false&administration=write&organization_self_hosted_runners=write&actions=read)
When the installation is complete, you will be taken to a URL in one of the following formats, the last number of the URL will be used as the Installation ID later (For example, if the URL ends in `settings/installations/12345`, then the Installation ID is `12345`).
Finally, register the App ID (`APP_ID`), Installation ID (`INSTALLATION_ID`), and downloaded private key file (`PRIVATE_KEY_FILE_PATH`) to Kubernetes as Secret.
Log-in to a GitHub account that has `admin` privileges for the repository, and [create a personal access token](https://github.com/settings/tokens/new) with the appropriate scopes listed below:
_Note: When you deploy enterprise runners they will get access to organisations, however, access to the repositories themselves is **NOT** allowed by default. Each GitHub organisation must allow enterprise runner groups to be used in repositories as an initial one time configuration step, this only needs to be done once after which it is permanent for that runner group._
[GitHub self-hosted runners can be deployed at various levels in a management hierarchy](https://docs.github.com/en/actions/hosting-your-own-runners/about-self-hosted-runners#about-self-hosted-runners):
To launch a single self-hosted runner, you need to create a manifest file includes `Runner` resource as follows. This example launches a self-hosted runner with name *example-runner* for the *actions-runner-controller/actions-runner-controller* repository.
<imgwidth="756"alt="Actions tab in your repository settings"src="https://user-images.githubusercontent.com/230145/73618667-8cbf9700-466c-11ea-80b6-c67e6d3f70e7.png">
Now you can use your self-hosted runner. See the [official documentation](https://help.github.com/en/actions/automating-your-workflow-with-github-actions/using-self-hosted-runners-in-a-workflow) on how to run a job with it.
To add the runner to an organization, you only need to replace the `repository` field with `organization`, so the runner will register itself to the organization.
To add the runner to an enterprise, you only need to replace the `repository` field with `enterprise`, so the runner will register itself to the enterprise.
```yaml
# runner.yaml
apiVersion: actions.summerwind.dev/v1alpha1
kind: Runner
metadata:
name: example-enterprise-runner
spec:
enterprise: your-enterprise-name
```
Now you can see the runner on the enterprise level (if you have enterprise access permissions).
You can either delete the runner deployment, or update it to have `replicas: 0`, so that there will be 0 runner pods in the cluster. This, in combination with e.g. `cluster-autoscaler`, enables you to save your infrastructure cost when there's no need to run Actions jobs.
The implication of setting `replicas: 0` instead of deleting the runner deployment is that you can let GitHub Actions queue jobs until there will be one or more runners. See [#465](https://github.com/actions-runner-controller/actions-runner-controller/pull/465) for more information.
__**IMPORTANT : Due to limitations / a bug with GitHub's [routing engine](https://docs.github.com/en/actions/hosting-your-own-runners/using-self-hosted-runners-in-a-workflow#routing-precedence-for-self-hosted-runners) autoscaling does NOT work correctly with RunnerDeployments that target the enterprise level. Scaling activity works as expected however jobs fail to get assigned to the scaled out replicas. This was explored in issue [#470](https://github.com/actions-runner-controller/actions-runner-controller/issues/470). Once GitHub resolves the issue with their backend service we expect the solution to be able to support autoscaled enterprise runnerdeploments without any additional changes.**__
A `RunnerDeployment` (excluding enterprise runners) can scale the number of runners between `minReplicas` and `maxReplicas` fields based the chosen scaling metric as defined in the `metrics` attribute
In the below example, `actions-runner` will poll GitHub for all pending workflows with the poll period defined by the sync period configuration. It will then scale to e.g. 3 if there're 3 pending jobs at sync time.
With this scaling metric we are required to define a list of repositories within our metric.
The scale out performance is controlled via the manager containers startup `--sync-period` argument. The default value is set to 10 minutes to prevent default deployments rate limiting themselves from the GitHub API.
1. Repositories must be named within the scaling metric, maintaining a list of repositories may not be viable in larger environments or self-serve environments.
2. May not scale quick enough for some users needs. This metric is pull based and so the queue depth is polled as configured by the sync period, as a result scaling performance is bound by this sync period meaning there is a lag to scaling activity.
3. Relatively large amounts of API requests required to maintain this metric, you may run in API rate limiting issues depending on the size of your environment and how aggressive your sync period configuration is
4. The GitHub API doesn't provide a way to filter workflow jobs to just those targeting self-hosted runners. If your environment's workflows target both self-hosted and GitHub hosted runners then the queue depth this metric scales against isn't a true 1:1 mapping of queue depth to required runner count. As a result of this, this metric may scale too aggressively for your actual self-hosted runner count needs.
By default, it doesn't scale down until the grace period of 10 minutes passes after a scale up. The grace period can be configured however by adding the setting `scaleDownDelaySecondsAfterScaleOut` in the `HorizontalRunnerAutoscaler``spec`:
The `HorizontalRunnerAutoscaler` will poll GitHub based on the configuration sync period for the number of busy runners which live in the RunnerDeployment's namespace and scale based on the settings
1. Supports named repositories server side the same as the `TotalNumberOfQueuedAndInProgressWorkflowRuns` metric [#313](https://github.com/actions-runner-controller/actions-runner-controller/pull/313)
2. Supports GitHub organization wide scaling without maintaining an explicit list of repositories, this is especially useful for those that are working at a larger scale. [#223](https://github.com/actions-runner-controller/actions-runner-controller/pull/223)
4. Supports scaling desired runner count on both a percentage increase / decrease basis as well as on a fixed increase / decrease count basis [#223](https://github.com/actions-runner-controller/actions-runner-controller/pull/223) [#315](https://github.com/actions-runner-controller/actions-runner-controller/pull/315)
1. May not scale quick enough for some users needs. This metric is pull based and so the number of busy runners are polled as configured by the sync period, as a result scaling performance is bound by this sync period meaning there is a lag to scaling activity.
2. We are scaling up and down based on indicative information rather than a count of the actual number of queued jobs and so the desired runner count is likely to under provision new runners or overprovision them relative to actual job queue depth, this may or may not be a problem for you.
scaleUpThreshold: '0.75' # The percentage of busy runners at which the number of desired runners are re-evaluated to scale up
scaleDownThreshold: '0.3' # The percentage of busy runners at which the number of desired runners are re-evaluated to scale down
ScaleUpAdjustment: '2' # The scale up runner count added to desired count
ScaleDownAdjustment: '1' # The scale down runner count subtracted from the desired count
```
Like the previous metric, the scale down factor respects the anti-flapping configuration is applied to the `HorizontalRunnerAutoscaler` as mentioned previously:
__**IMPORTANT : Due to missing webhook events, webhook based scaling is not available for enterprise level RunnerDeployments. This was explored in issue [#470](https://github.com/actions-runner-controller/actions-runner-controller/issues/470).**__
The above command will result in exposing the node port 33080 for Webhook events. Usually, you need to create an
external loadbalancer targeted to the node port, and register the hostname or the IP address of the external loadbalancer
to the GitHub Webhook.
Once you were able to confirm that the Webhook server is ready and running from GitHub - this is usually verified by the
GitHub sending PING events to the Webhook server - create or update your `HorizontalRunnerAutoscaler` resources
by learning the following configuration examples.
- [Example 1: Scale up on each `check_run` event](#example-1-scale-up-on-each-check_run-event)
- [Example 2: Scale on each `pull_request` event against `develop` or `main` branches](#example-2-scale-on-each-pull_request-event-against-develop-or-main-branches)
##### Example 1: Scale up on each `check_run` event
> Note: This should work almost like https://github.com/philips-labs/terraform-aws-github-runner
To scale up replicas of the runners for `example/myrepo` by 1 for 5 minutes on each `check_run`, you write manifests like the below:
See ["activity types"](https://docs.github.com/en/actions/reference/events-that-trigger-workflows#pull_request) for the list of valid values for `scaleUpTriggers[].githubEvent.pullRequest.types`.
This is due to that `PercentageRunnersBusy`, by its definition, needs one or more GitHub runners that can become `busy`, which cannot happen at all when you have 0 active runners.
If and only if HorizontalRunnerAutoscaler is configured to have a secondary metric of `TotalNumberOfQueuedAndInProgressWorkflowRuns` and the controller sees the primary metric of `PercentageRunnersBusy` returned 0 desired replicas, it uses the secondary metric for calculating the desired replicas once again.
A correctly configured `TotalNumberOfQueuedAndInProgressWorkflowRuns` can return non-zero desired replicas even when there are no runners other than [registration-only runners](#note-on-scaling-tofrom-0), hence the `PercentageRunnersBusy` + `TotalNumberOfQueuedAndInProgressWorkflowRuns` configuration makes scaling from zero possible.
Similarly, Webhook-based autoscaling works regardless of there are active runners, hence `PercentageRunnersBusy` + Webhook-based autoscaling configuration makes scaling from zero, too.
usually, this feature is used for following scenarios:
- You want to pay for your infrastructure cost running runners only in business hours
- You want to prepare for scheduled spikes in workloads
For the first scenario, you might consider configuration like the below:
```
apiVersion: actions.summerwind.dev/v1alpha1
kind: HorizontalRunnerAutoscaler
metadata:
name: example-runner-deployment-autoscaler
spec:
scaleTargetRef:
name: example-runner-deployment
scheduledOverrides:
# Override minReplicas to 0 only between 0am sat to 0am mon
- startTime: "2021-05-01T00:00:00+09:00"
endTime: "2021-05-03T00:00:00+09:00"
recurrenceRule:
frequency: Weekly
untilTime: "2022-05-01T00:00:00+09:00"
minReplicas: 0
minReplicas: 1
```
For the second scenario, you might consider something like the below:
```
apiVersion: actions.summerwind.dev/v1alpha1
kind: HorizontalRunnerAutoscaler
metadata:
name: example-runner-deployment-autoscaler
spec:
scaleTargetRef:
name: example-runner-deployment
scheduledOverrides:
# Override minReplicas to 100 only between 2021-06-01T00:00:00+09:00 and 2021-06-03T00:00:00+09:00
- startTime: "2021-06-01T00:00:00+09:00"
endTime: "2021-06-03T00:00:00+09:00"
minReplicas: 100
minReplicas: 1
```
The most basic usage of this feature is actually the second scenario mentioned above.
A scheduled override without `recurrenceRule` is considered a one-off override, that is active between `startTime` and `endTime`. In the second scenario, it overrides `minReplicas` to `100` only between `2021-06-01T00:00:00+09:00` and `2021-06-03T00:00:00+09:00`.
A scheduled override with `recurrenceRule` is considered a recurring override. A recurring override is initially active between `startTime` and `endTime`, and then it repeatedly get activated after a certain period of time denoted by `frequency`.
By default, a scheduled override repeats forever. If you want it to repeat until a specific point in time, define `untilTime`. The controller create the last recurrence of the override until the recurrence's `startTime` is equal or earlier than `untilTime`.
Do note that you have enough slack for `untilTime`, so that a delayed or offline `actions-runner-controller` is much less likely to miss the last recurrence. For example, you might want to set `untilTime` to `M` minutes after the last recurrence's `startTime`, so that `actions-runner-controller` being offline up to `M` minutes doesn't miss the last recurrence.
**Combining Multiple Scheduled Overrides**:
In case you have a more complex scenarios, try writing two or more entries under `scheduledOverrides`.
The earlier entry is prioritized higher than later entries. So you usually define one-time overrides in the top of your list, then yearly, monthly, weekly, and lastly daily overrides.
When using default runner, runner pod starts up 2 containers: runner and DinD (Docker-in-Docker). This might create issues if there's `LimitRange` set to namespace.
#All level/role/type/user values will vary based on your SELinux policies.
#See https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux_atomic_host/7/html/container_security_guide/docker_selinux_security_policy for information about SELinux with containers
# true = No docker sidecar container is deployed in the runner pod but docker can be used within the runner container instead. The image summerwind/actions-runner-dind is used by default.
# You can mount some of the shared volumes to the runner container using volumeMounts.
# NOTE: Do not try to mount the volume onto the runner workdir itself as it will not work. You could mount it however on a sub directory in the runner workdir
# Please see https://github.com/actions-runner-controller/actions-runner-controller/issues/630#issuecomment-862087323 for more information.
To run a workflow job on a self-hosted runner, you can use the following syntax in your workflow:
```yaml
jobs:
release:
runs-on: self-hosted
```
When you have multiple kinds of self-hosted runners, you can distinguish between them using labels. In order to do so, you can specify one or more labels in your `Runner` or `RunnerDeployment` spec.
Once this spec is applied, you can observe the labels for your runner from the repository or organization in the GitHub settings page for the repository or organization. You can now select a specific runner from your workflow by using the label in `runs-on`:
Note that if you specify `self-hosted` in your workflow, then this will run your job on _any_ self-hosted runner, regardless of the labels that they have.
Runner groups can be used to limit which repositories are able to use the GitHub Runner at an organization level. Runner groups have to be [created in GitHub first](https://docs.github.com/en/actions/hosting-your-own-runners/managing-access-to-self-hosted-runners-using-groups) before they can be referenced.
As similar as for regular pods and deployments, you firstly need an existing service account with the IAM role associated.
Create one using e.g. `eksctl`. You can refer to [the EKS documentation](https://docs.aws.amazon.com/eks/latest/userguide/iam-roles-for-service-accounts.html) for more details.
Once you set up the service account, all you need is to add `serviceAccountName` and `fsGroup` to any pods that uses the IAM-role enabled service account.
Istio 1.7.0 or greater has `holdApplicationUntilProxyStarts` added in https://github.com/istio/istio/pull/24737, which enables you to delay the `runner` container startup until the injected `istio-proxy` container finish starting. Try using it if you need to use Istio. Otherwise the runner is unlikely to work, because it fails to call any GitHub API to register itself due to `istio-proxy` being not up and running yet.
Note that there's no official Istio integration in actions-runner-controller. It should work, but it isn't covered by our acceptance test(contribution is welcomed). In addition to that, none of the actions-runner-controller maintainers use Istio daily. If you need more information, or have any issues using it, refer to the following links:
> This is a documentation about a unreleased version of actions-runner-controller.
>
> It would be great if you could try building the latest controller image following https://github.com/actions-runner-controller/actions-runner-controller#contributing if you are eager to test it early and help
> developers by reporting any bugs :smile:
`actions-runner-controller` supports `RunnerSet` API that let you deploy stateful runners. A stateful runner is designed to be able to store some data persists across GitHub Actions workflow and job runs. You might find it useful, for example, to speed up your docker builds by persisting the docker layer cache.
A basic `RunnerSet` would look like this:
```
apiVersion: actions.summerwind.dev/v1alpha1
kind: RunnerSet
metadata:
name: example
spec:
ephemeral: false
replicas: 2
repository: mumoshu/actions-runner-controller-ci
# Other mandatory fields from StatefulSet
selector:
matchLabels:
app: example
serviceName: example
template:
metadata:
labels:
app: example
```
As it is based on `StatefulSet`, `selector` and `template.medatada.labels` needs to be defined and haev the exact same set of labels. `serviceName` must be set to some non-empty string as it is also required by `StatefulSet`.
Runner-related fields like `ephemeral`, `repository`, `organiåtion`, `enterprise`, and so on should be written directly under `spec`.
Fields like `volumeClaimTemplates` that originates from `StatefulSet` shuold also be written directly under `spec`.
Pod-related fields like security contexts and volumes are written under `spec.template.spec` like `StatefulSet`.
Simillarly, container-related fields like resource requests and limits, container image names and tags, security context, and so on are written under `spec.template.spec.containers`. There are two reserved container `name`, `runner` and `docker`. The former is for the container that runs [actions runner](https://github.com/actions/runner) and the latter is for the container that runs a dockerd.
For a more complex example, see the below:
```
apiVersion: actions.summerwind.dev/v1alpha1
kind: RunnerSet
metadata:
name: example
spec:
# NOTE: RunnerSet supports non-ephemeral runners only today
ephemeral: false
replicas: 2
repository: mumoshu/actions-runner-controller-ci
dockerdWithinRunnerContainer: true
template:
spec:
securityContext:
#All level/role/type/user values will vary based on your SELinux policies.
#See https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux_atomic_host/7/html/container_security_guide/docker_selinux_security_policy for information about SELinux with containers
seLinuxOptions:
level: "s0"
role: "system_r"
type: "super_t"
user: "system_u"
containers:
- name: runner
env: []
resources:
limits:
cpu: "4.0"
memory: "8Gi"
requests:
cpu: "2.0"
memory: "4Gi"
- name: docker
resources:
limits:
cpu: "4.0"
memory: "8Gi"
requests:
cpu: "2.0"
memory: "4Gi"
```
You can also read the design and usage documentation written in the original pull request that introduced `RunnerSet` for more information.
Under the hood, `RunnerSet` relies on Kubernetes's `StatefulSet` and Mutating Webhook. A statefulset is used to create a number of pods that has stable names and dynamically provisioned persistent volumes, so that each statefulset-managed pod gets the same persisntet volume even after restarting. A mutating webhook is used to dynamically inject a runner's "registration token" which is used to call GitHub's "Create Runner" API.
We envision that `RunnerSet` will eventually replaces `RunnerDeployment`, as `RunnerSet` provides a more standard API that is easy to learn and use because it is based on `StatefulSet`, and it has a support for `volumeClaimTemplates` which is crucial to manage dynamically provisioned persistent volumes.
The project supports being deployed on the various cloud Kubernetes platforms (e.g. EKS), it does not however aim to go beyond that. No cloud specific tooling is bundled in the base runner, this is an active decision to keep the overhead of maintaining the solution manageable.
The GitHub hosted runners include a large amount of pre-installed software packages. GitHub maintain a list in README files at <https://github.com/actions/virtual-environments/tree/main/images/linux>
This solution maintains a few runner images with `latest` aligning with GitHub's Ubuntu version. Older images are maintained whilst GitHub also provides them as an option. These images do not contain all of the software installed on the GitHub runners. It contains the following subset of packages from the GitHub runners:
The virtual environments from GitHub contain a lot more software packages (different versions of Java, Node.js, Golang, .NET, etc) which are not provided in the runner image. Most of these have dedicated setup actions which allow the tools to be installed on-demand in a workflow, for example: `actions/setup-java` or `actions/setup-node`
If there is a need to include packages in the runner image for which there is no setup action, then this can be achieved by building a custom container image for the runner. The easiest way is to start with the `summerwind/actions-runner` image and installing the extra dependencies directly in the docker image:
"error": "failed to create registration token: Post \"https://api.github.com/orgs/$YOUR_ORG_HERE/actions/runners/registration-token\": net/http: invalid header field value \"Bearer $YOUR_TOKEN_HERE\\n\" for key Authorization"
