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Kubernetes backend
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.
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:
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 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 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 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:
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:
[...]
backend_options:
kubernetes:
nodeSelector:
kubernetes.io/arch: "${ARCH}"
You can use WOODPECKER_BACKEND_K8S_POD_NODE_SELECTOR if you want to set the node selector per Agent or PodNodeSelector admission controller if you want to set the node selector by per-namespace basis.
Tolerations
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 for more information on using tolerations.
Example pipeline configuration:
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:
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 for the Pod/container running a given pipeline step:
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:
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 profile
backend_options:
kubernetes:
securityContext:
seccompProfile:
type: Localhost
localhostProfile: profiles/audit.json
or restrict a container's access to resources by specifying AppArmor profile
backend_options:
kubernetes:
securityContext:
apparmorProfile:
type: Localhost
localhostProfile: k8s-apparmor-example-deny-write
:::note AppArmor syntax follows KEP-24. :::
Annotations and labels
You can specify arbitrary annotations and labels to be set on the Pod definition for a given workflow step using the following configuration:
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:
WOODPECKER_BACKEND_K8S_POD_ANNOTATIONS_ALLOW_FROM_STEP and/or WOODPECKER_BACKEND_K8S_POD_LABELS_ALLOW_FROM_STEP.
Tips and tricks
CRI-O
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:
workspace:
base: '/woodpecker'
path: '/'
See this issue for more details.
KUBERNETES_SERVICE_HOST
environment variable
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.
Configuration
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. 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"}
.
WOODPECKER_BACKEND_K8S_POD_LABELS_ALLOW_FROM_STEP
Default:
false
Determines if additional Pod labels can be defined from a step's backend options.
WOODPECKER_BACKEND_K8S_POD_ANNOTATIONS
Default: empty
Additional annotations to apply to worker Pods. Must be a YAML object, e.g. {"example.com/test-annotation":"test-value"}
.
WOODPECKER_BACKEND_K8S_POD_ANNOTATIONS_ALLOW_FROM_STEP
Default:
false
Determines if Pod annotations can be defined from a step's backend options.
WOODPECKER_BACKEND_K8S_POD_NODE_SELECTOR
Default: empty
Additional node selector to apply to worker pods. Must be a YAML object, e.g. {"topology.kubernetes.io/region":"eu-central-1"}
.
WOODPECKER_BACKEND_K8S_SECCTX_NONROOT
Default:
false
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.