* [Unable to scale to zero with TotalNumberOfQueuedAndInProgressWorkflowRuns](#unable-to-scale-to-zero-with-totalnumberofqueuedandinprogressworkflowruns)
This issue can come up for various reasons like leftovers from previous installations or not being able to access the K8s service's clusterIP associated with the admission webhook server (of ARC).
Post "https://actions-runner-controller-webhook.actions-runner-system.svc:443/mutate-actions-summerwind-dev-v1alpha1-runnerdeployment?timeout=10s": context deadline exceeded
If that didn't work then probably your K8s control-plane is somehow unable to access the K8s service's clusterIP associated with the admission webhook server:
1. You're running apiserver as a binary and you didn't make service cluster IPs available to the host network.
2. You're running the apiserver in the pod but your pod network (i.e. CNI plugin installation and config) is not good so your pods(like kube-apiserver) in the K8s control-plane nodes can't access ARC's admission webhook server pod(s) in probably data-plane nodes.
2. Set up a firewall rule to allow the master node to connect to the default
webhook port. The exact way to do this may vary, but the following script
should point you in the right direction:
```sh
# 1) Retrieve the network tag automatically given to the worker nodes
# NOTE: this only works if you have only one cluster in your GCP project. You will have to manually inspect the result of this command to find the tag for the cluster you want to target
"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"
}
```
**Solution**
Your base64'ed PAT token has a new line at the end, it needs to be created without a `\n` added, either:
Error: UPGRADE FAILED: failed to create resource: Internal error occurred: failed calling webhook "webhook.cert-manager.io": failed to call webhook: Post "https://cert-manager-webhook.cert-manager.svc:443/mutate?timeout=10s": x509: certificate signed by unknown authority
```
Apparently, it's failing while `helm` is creating one of resources defined in the ARC chart and the cause was that cert-manager's webhook is not working correctly, due to the missing or the invalid CA certficate.
You'd try to tail logs from the `cert-manager-cainjector` and see it's failing with an error like:
I0703 03:32:12.339197 1 request.go:645] Throttling request took 1.047437675s, request: GET:https://10.96.0.1:443/apis/storage.k8s.io/v1beta1?timeout=32s
E0703 03:32:13.143790 1 start.go:151] cert-manager/ca-injector "msg"="Error registering certificate based controllers. Retrying after 5 seconds." "error"="no matches for kind \"MutatingWebhookConfiguration\" in version \"admissionregistration.k8s.io/v1beta1\""
Error: error registering secret controller: no matches for kind "MutatingWebhookConfiguration" in version "admissionregistration.k8s.io/v1beta1"
```
**Solution**
Your cluster is based on a new enough Kubernetes of version 1.22 or greater which does not support the legacy `admissionregistration.k8s.io/v1beta1` API anymore, and your `cert-manager` is not up-to-date hence it's still trying to use the leagcy Kubernetes API.
In many cases, it's not an option to downgrade Kubernetes. So, just upgrade `cert-manager` to a more recent version that does have have the support for the specific Kubernetes version you're using.
Troubeshooting runbooks that relate to ARC operational problems
### Stuck runner kind or backing pod
**Problem**
Sometimes either the runner kind (`kubectl get runners`) or it's underlying pod can get stuck in a terminating state for various reasons. You can get the kind unstuck by removing its finaliser using something like this:
**Solution**
Remove the finaliser from the relevent runner kind or pod
ARC isn't involved in jobs actually getting allocated to a runner. ARC is responsible for orchestrating runners and the runner lifecycle. Why some people see large delays in job allocation is not clear however it has been confirmed https://github.com/actions/actions-runner-controller/issues/1387#issuecomment-1122593984 that this is caused from the self-update process somehow.
> Added originally to help users with older istio instances.
> Newer Istio instances can use Istio's `holdApplicationUntilProxyStarts` attribute ([istio/istio#11130](https://github.com/istio/istio/issues/11130)) to avoid having to delay starting up the runner.
You can add a delay to the runner's entrypoint script by setting the `STARTUP_DELAY_IN_SECONDS` environment variable for the runner pod. This will cause the script to sleep X seconds, this works with any runner kind.
Some random outgoing network actions hangs indefinitely. This could be because your cluster does not give Docker the standard MTU of 1500, you can check this out by running `ip link` in a pod that encounters the problem and reading the outgoing interface's MTU value. If it is smaller than 1500, then try the following.
**Solution**
Add a `dockerMTU` key in your runner's spec with the value you read on the outgoing interface. For instance:
HRA doesn't scale the RunnerDeployment to zero, even though you did configure HRA correctly, to have a pull-based scaling metric `TotalNumberOfQueuedAndInProgressWorkflowRuns`, and set `minReplicas: 0`.
You very likely have some dangling workflow jobs stuck in `queued` or `in_progress` as seen in [#1057](https://github.com/actions/actions-runner-controller/issues/1057#issuecomment-1133439061).
If you noticed that it takes several minutes for sidecar dind container to be created or it exits with with error just after being created it might indicate that you are experiencing disk performance issue. You might see message `failed to reserve container name` when scaling up multiple runners at once. When you ssh on kubernetes node that problematic pods were scheduled on you can use tools like `atop`, `htop` or `iotop` to check IO usage and cpu time percentage used on iowait. If you see that disk usage is high (80-100%) and iowaits are taking a significant chunk of you cpu time (normally it should not be higher than 10%) it means that performance is being bottlenecked by slow disk.
The solution is to switch to using faster storage, if you are experiencing this issue you are probably using HDD storage. Switching to SSD storage fixed the problem in my case. Most cloud providers have a list of storage options to use just pick something faster that your current disk, for on prem clusters you will need to invest in some SSDs.
If you are running many containers on your runner you might encounter an issue where docker daemon is unable to start new containers and you see error `no space left on device`.
**Solution**
Add a `dockerVarRunVolumeSizeLimit` key in your runner's spec with a higher size limit (the default is 1M) For instance: