values.yaml

# Default values for gha-runner-scale-set-controller.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.
labels: {}

# leaderElection will be enabled when replicaCount>1,
# So, only one replica will in charge of reconciliation at a given time
# leaderElectionId will be set to {{ define gha-runner-scale-set-controller.fullname }}.
replicaCount: 1

image:
  repository: "ghcr.io/actions/gha-runner-scale-set-controller"
  pullPolicy: IfNotPresent
  # Overrides the image tag whose default is the chart appVersion.
  tag: ""

imagePullSecrets: []
nameOverride: ""
fullnameOverride: ""

env:
## Define environment variables for the controller pod
#  - name: "ENV_VAR_NAME_1"
#    value: "ENV_VAR_VALUE_1"
#  - name: "ENV_VAR_NAME_2"
#    valueFrom:
#      secretKeyRef:
#        key: ENV_VAR_NAME_2
#        name: secret-name
#        optional: true

serviceAccount:
  # Specifies whether a service account should be created for running the controller pod
  create: true
  # Annotations to add to the service account
  annotations: {}
  # The name of the service account to use.
  # If not set and create is true, a name is generated using the fullname template
  # You can not use the default service account for this.
  name: ""

podAnnotations: {}

podLabels: {}

podSecurityContext: {}
# fsGroup: 2000

securityContext: {}
# capabilities:
#   drop:
#   - ALL
# readOnlyRootFilesystem: true
# runAsNonRoot: true
# runAsUser: 1000

resources: {}
## We usually recommend not to specify default resources and to leave this as a conscious
## choice for the user. This also increases chances charts run on environments with little
## resources, such as Minikube. If you do want to specify resources, uncomment the following
## lines, adjust them as necessary, and remove the curly braces after 'resources:'.
# limits:
#   cpu: 100m
#   memory: 128Mi
# requests:
#   cpu: 100m
#   memory: 128Mi

nodeSelector: {}

tolerations: []

affinity: {}

topologySpreadConstraints: []

# Mount volumes in the container.
volumes: []
volumeMounts: []

# Leverage a PriorityClass to ensure your pods survive resource shortages
# ref: https://kubernetes.io/docs/concepts/configuration/pod-priority-preemption/
# PriorityClass: system-cluster-critical
priorityClassName: ""

## If `metrics:` object is not provided, or commented out, the following flags
## will be applied the controller-manager and listener pods with empty values:
## `--metrics-addr`, `--listener-metrics-addr`, `--listener-metrics-endpoint`.
## This will disable metrics.
##
## To enable metrics, uncomment the following lines.
# metrics:
#   controllerManagerAddr: ":8080"
#   listenerAddr: ":8080"
#   listenerEndpoint: "/metrics"

flags:
  ## Log level can be set here with one of the following values: "debug", "info", "warn", "error".
  ## Defaults to "debug".
  logLevel: "debug"
  ## Log format can be set with one of the following values: "text", "json"
  ## Defaults to "text"
  logFormat: "text"

  ## Restricts the controller to only watch resources in the desired namespace.
  ## Defaults to watch all namespaces when unset.
  # watchSingleNamespace: ""

  ## The maximum number of concurrent reconciles which can be run by the EphemeralRunner controller.
  # Increase this value to improve the throughput of the controller.
  # It may also increase the load on the API server and the external service (e.g. GitHub API).
  runnerMaxConcurrentReconciles: 2

  ## Defines how the controller should handle upgrades while having running jobs.
  ##
  ## The strategies available are:
  ## - "immediate": (default) The controller will immediately apply the change causing the
  ##   recreation of the listener and ephemeral runner set. This can lead to an
  ##   overprovisioning of runners, if there are pending / running jobs. This should not
  ##   be a problem at a small scale, but it could lead to a significant increase of
  ##   resources if you have a lot of jobs running concurrently.
  ##
  ## - "eventual": The controller will remove the listener and ephemeral runner set
  ##   immediately, but will not recreate them (to apply changes) until all
  ##   pending / running jobs have completed.
  ##   This can lead to a longer time to apply the change but it will ensure
  ##   that you don't have any overprovisioning of runners.
  updateStrategy: "immediate"

  ## Defines a list of prefixes that should not be propagated to internal resources.
  ## This is useful when you have labels that are used for internal purposes and should not be propagated to internal resources.
  ## See https://github.com/actions/actions-runner-controller/issues/3533 for more information.
  ##
  ## By default, all labels are propagated to internal resources
  ## Labels that match prefix specified in the list are excluded from propagation.
  # excludeLabelPropagationPrefixes:
  #   - "argocd.argoproj.io/instance"

  ## Defines the K8s client rate limiter parameters.
  # k8sClientRateLimiterQPS: 20
  # k8sClientRateLimiterBurst: 30