The Kubernetes backend executes steps inside standalone Pods. A temporary PVC is created for the lifetime of the pipeline to transfer files between steps.
## Images from private registries
In order to pull private container images defined in your pipeline YAML you must provide [registry credentials in Kubernetes Secret](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/).
As the Secret is Agent-wide, it has to be placed in namespace defined by `WOODPECKER_BACKEND_K8S_NAMESPACE`.
Besides, you need to provide the Secret name to Agent via `WOODPECKER_BACKEND_K8S_PULL_SECRET_NAMES`.
## Job specific configuration
### Resources
The Kubernetes backend also allows for specifying requests and limits on a per-step basic, most commonly for CPU and memory.
We recommend to add a `resources` definition to all steps to ensure efficient scheduling.
Here is an example definition with an arbitrary `resources` definition below the `backend_options` section:
```yaml
steps:
- name: 'My kubernetes step'
image: alpine
commands:
- echo "Hello world"
backend_options:
kubernetes:
resources:
requests:
memory: 200Mi
cpu: 100m
limits:
memory: 400Mi
cpu: 1000m
```
You can use [Limit Ranges](https://kubernetes.io/docs/concepts/policy/limit-range/) if you want to set the limits by per-namespace basis.
### Runtime class
`runtimeClassName` specifies the name of the RuntimeClass which will be used to run this Pod. If no `runtimeClassName` is specified, the default RuntimeHandler will be used.
See the [Kubernetes documentation](https://kubernetes.io/docs/concepts/containers/runtime-class/) for more information on specifying runtime classes.
### Service account
`serviceAccountName` specifies the name of the ServiceAccount which the Pod will mount. This service account must be created externally.
See the [Kubernetes documentation](https://kubernetes.io/docs/concepts/security/service-accounts/) for more information on using service accounts.
### Node selector
`nodeSelector` specifies the labels which are used to select the node on which the job will be executed.
Labels defined here will be appended to a list which already contains `"kubernetes.io/arch"`.
By default `"kubernetes.io/arch"` is inferred from the agents' platform. One can override it by setting that label in the `nodeSelector` section of the `backend_options`.
Without a manual overwrite, builds will be randomly assigned to the runners and inherit their respective architectures.
To overwrite this, one needs to set the label in the `nodeSelector` section of the `backend_options`.
A practical example for this is when running a matrix-build and delegating specific elements of the matrix to run on a specific architecture.
In this case, one must define an arbitrary key in the matrix section of the respective matrix element:
```yaml
matrix:
include:
- NAME: runner1
ARCH: arm64
```
And then overwrite the `nodeSelector` in the `backend_options` section of the step(s) using the name of the respective env var:
You can use [WOODPECKER_BACKEND_K8S_POD_NODE_SELECTOR](#woodpecker_backend_k8s_pod_node_selector) if you want to set the node selector per Agent
or [PodNodeSelector](https://kubernetes.io/docs/reference/access-authn-authz/admission-controllers/#podnodeselector) admission controller if you want to set the node selector by per-namespace basis.
When you use `nodeSelector` and the node pool is configured with Taints, you need to specify the Tolerations. Tolerations allow the scheduler to schedule Pods with matching taints.
See the [Kubernetes documentation](https://kubernetes.io/docs/concepts/scheduling-eviction/taint-and-toleration/) for more information on using tolerations.
Example pipeline configuration:
```yaml
steps:
- name: build
image: golang
commands:
- go get
- go build
- go test
backend_options:
kubernetes:
serviceAccountName: 'my-service-account'
resources:
requests:
memory: 128Mi
cpu: 1000m
limits:
memory: 256Mi
nodeSelector:
beta.kubernetes.io/instance-type: p3.8xlarge
tolerations:
- key: 'key1'
operator: 'Equal'
value: 'value1'
effect: 'NoSchedule'
tolerationSeconds: 3600
```
### Volumes
To mount volumes a PersistentVolume (PV) and PersistentVolumeClaim (PVC) are needed on the cluster which can be referenced in steps via the `volumes` option.
Assuming a PVC named `woodpecker-cache` exists, it can be referenced as follows in a step:
```yaml
steps:
- name: "Restore Cache"
image: meltwater/drone-cache
volumes:
- woodpecker-cache:/woodpecker/src/cache
settings:
mount:
- "woodpecker-cache"
[...]
```
### Security context
Use the following configuration to set the [Security Context](https://kubernetes.io/docs/tasks/configure-pod-container/security-context/) for the Pod/container running a given pipeline step:
```yaml
steps:
- name: test
image: alpine
commands:
- echo Hello world
backend_options:
kubernetes:
securityContext:
runAsUser: 999
runAsGroup: 999
privileged: true
[...]
```
Note that the `backend_options.kubernetes.securityContext` object allows you to set both Pod and container level security context options in one object.
By default, the properties will be set at the Pod level. Properties that are only supported on the container level will be set there instead. So, the
configuration shown above will result in something like the following Pod spec:
```yaml
kind: Pod
spec:
securityContext:
runAsUser: 999
runAsGroup: 999
containers:
- name: wp-01hcd83q7be5ymh89k5accn3k6-0-step-0
image: alpine
securityContext:
privileged: true
[...]
```
You can also restrict a container's syscalls with [seccomp](https://kubernetes.io/docs/tutorials/security/seccomp/) profile
```yaml
backend_options:
kubernetes:
securityContext:
seccompProfile:
type: Localhost
localhostProfile: profiles/audit.json
```
or restrict a container's access to resources by specifying [AppArmor](https://kubernetes.io/docs/tutorials/security/apparmor/) profile
You can specify arbitrary [annotations](https://kubernetes.io/docs/concepts/overview/working-with-objects/annotations/) and [labels](https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/) to be set on the Pod definition for a given workflow step using the following configuration:
```yaml
backend_options:
kubernetes:
annotations:
workflow-group: alpha
io.kubernetes.cri-o.Devices: /dev/fuse
labels:
environment: ci
app.kubernetes.io/name: builder
```
In order to enable this configuration you need to set the appropriate environment variables to `true` on the woodpecker agent:
CRI-O users currently need to configure the workspace for all workflows in order for them to run correctly. Add the following at the beginning of your configuration:
```yaml
workspace:
base: '/woodpecker'
path: '/'
```
See [this issue](https://github.com/woodpecker-ci/woodpecker/issues/2510) for more details.
Like the below env vars used for configuration, this can be set in the environment fonfiguration of the agent. It configures the address of the Kubernetes API server to connect to.
If running the agent within Kubernetes, this will already be set and you don't have to add it manually.
These env vars can be set in the `env:` sections of the agent.
### `WOODPECKER_BACKEND_K8S_NAMESPACE`
> Default: `woodpecker`
The namespace to create worker Pods in.
### `WOODPECKER_BACKEND_K8S_VOLUME_SIZE`
> Default: `10G`
The volume size of the pipeline volume.
### `WOODPECKER_BACKEND_K8S_STORAGE_CLASS`
> Default: empty
The storage class to use for the pipeline volume.
### `WOODPECKER_BACKEND_K8S_STORAGE_RWX`
> Default: `true`
Determines if `RWX` should be used for the pipeline volume's [access mode](https://kubernetes.io/docs/concepts/storage/persistent-volumes/#access-modes). If false, `RWO` is used instead.
### `WOODPECKER_BACKEND_K8S_POD_LABELS`
> Default: empty
Additional labels to apply to worker Pods. Must be a YAML object, e.g. `{"example.com/test-label":"test-value"}`.
Determines if containers must be required to run as non-root users.
### `WOODPECKER_BACKEND_K8S_PULL_SECRET_NAMES`
> Default: empty
Secret names to pull images from private repositories. See, how to [Pull an Image from a Private Registry](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/).
