values.yaml

# Default values for ray-cluster.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.

# The KubeRay community welcomes PRs to expose additional configuration
# in this Helm chart.

image:
  repository: rayproject/ray
  tag: 2.0.0
  pullPolicy: IfNotPresent

nameOverride: "kuberay"
fullnameOverride: ""

imagePullSecrets: []
  # - name: an-existing-secret

head:
  # If enableInTreeAutoscaling is true, the autoscaler sidecar will be added to the Ray head pod.
  # Ray autoscaler integration is supported only for Ray versions >= 1.11.0
  # Ray autoscaler integration is Beta with KubeRay >= 0.3.0 and Ray >= 2.0.0.
  enableInTreeAutoscaling: true
  # autoscalerOptions is an OPTIONAL field specifying configuration overrides for the Ray autoscaler.
  # The example configuration shown below below represents the DEFAULT values.
  autoscalerOptions:
    upscalingMode: Default
    idleTimeoutSeconds: 60
    securityContext: {}
    env: []
    envFrom: []
    # resources specifies optional resource request and limit overrides for the autoscaler container.
    # For large Ray clusters, we recommend monitoring container resource usage to determine if overriding the defaults is required.
    resources:
      limits:
        cpu: "500m"
        memory: "512Mi"
      requests:
        cpu: "500m"
        memory: "512Mi"
  labels: {}
  rayStartParams:
    dashboard-host: '0.0.0.0'
    block: 'true'
  # containerEnv specifies environment variables for the Ray container,
  # Follows standard K8s container env schema.
  containerEnv: []
  # - name: EXAMPLE_ENV
  #   value: "1"
  envFrom: []
    # - secretRef:
    #     name: my-env-secret
  # ports optionally allows specifying ports for the Ray container.
  # ports: []
  # resource requests and limits for the Ray head container.
  # Modify as needed for your application.
  # Note that the resources in this example are much too small for production;
  # we don't recommend allocating less than 8G memory for a Ray pod in production.
  # Ray pods should be sized to take up entire K8s nodes when possible.
  # Always set CPU and memory limits for Ray pods.
  # It is usually best to set requests equal to limits.
  # See https://docs.ray.io/en/latest/cluster/kubernetes/user-guides/config.html#resources
  # for further guidance.
  resources:
    limits:
      cpu: "1"
      # To avoid out-of-memory issues, never allocate less than 2G memory for the Ray head.
      memory: "2G"
    requests:
      cpu: "1"
      memory: "2G"
  annotations: {}
  nodeSelector: {}
  tolerations: []
  affinity: {}
  # Ray container security context.
  securityContext: {}
  volumes:
    - name: log-volume
      emptyDir: {}
  # Ray writes logs to /tmp/ray/session_latests/logs
  volumeMounts:
    - mountPath: /tmp/ray
      name: log-volume
  # sidecarContainers specifies additional containers to attach to the Ray pod.
  # Follows standard K8s container spec.
  sidecarContainers: []
  # See docs/guidance/pod-command.md for more details about how to specify
  # container command for head Pod.
  command: []
  args: []


worker:
  # If you want to disable the default workergroup
  # uncomment the line below
  # disabled: true
  groupName: workergroup
  replicas: 0
  labels: {}
  rayStartParams:
    block: 'true'
  initContainerImage: 'busybox:1.28'  # Enable users to specify the image for init container. Users can pull the busybox image from their private repositories.
  # Security context for the init container.
  initContainerSecurityContext: {}
  # containerEnv specifies environment variables for the Ray container,
  # Follows standard K8s container env schema.
  containerEnv: []
  # - name: EXAMPLE_ENV
  #   value: "1"
  envFrom: []
    # - secretRef:
    #     name: my-env-secret
  # ports optionally allows specifying ports for the Ray container.
  # ports: []
  # resource requests and limits for the Ray head container.
  # Modify as needed for your application.
  # Note that the resources in this example are much too small for production;
  # we don't recommend allocating less than 8G memory for a Ray pod in production.
  # Ray pods should be sized to take up entire K8s nodes when possible.
  # Always set CPU and memory limits for Ray pods.
  # It is usually best to set requests equal to limits.
  # See https://docs.ray.io/en/latest/cluster/kubernetes/user-guides/config.html#resources
  # for further guidance.
  resources:
    limits:
      cpu: "1"
      memory: "1G"
    requests:
      cpu: "1"
      memory: "1G"
  annotations: {}
  nodeSelector: {}
  tolerations: []
  affinity: {}
  # Ray container security context.
  securityContext: {}
  volumes:
    - name: log-volume
      emptyDir: {}
  # Ray writes logs to /tmp/ray/session_latests/logs
  volumeMounts:
    - mountPath: /tmp/ray
      name: log-volume
  # sidecarContainers specifies additional containers to attach to the Ray pod.
  # Follows standard K8s container spec.
  sidecarContainers: []
  # See docs/guidance/pod-command.md for more details about how to specify
  # container command for worker Pod.
  command: []
  args: []

# The map's key is used as the groupName.
# For example, key:small-group in the map below
# will be used as the groupName
additionalWorkerGroups:
  smallGroup:
    # Disabled by default
    disabled: true
    replicas: 0
    minReplicas: 0
    maxReplicas: 3
    labels: {}
    rayStartParams:
      block: 'true'
    initContainerImage: 'busybox:1.28'  # Enable users to specify the image for init container. Users can pull the busybox image from their private repositories.
    # Security context for the init container.
    initContainerSecurityContext: {}
  # containerEnv specifies environment variables for the Ray container,
  # Follows standard K8s container env schema.
    containerEnv: []
      # - name: EXAMPLE_ENV
      #   value: "1"
    envFrom: []
        # - secretRef:
        #     name: my-env-secret
    # ports optionally allows specifying ports for the Ray container.
    # ports: []
  # resource requests and limits for the Ray head container.
  # Modify as needed for your application.
  # Note that the resources in this example are much too small for production;
  # we don't recommend allocating less than 8G memory for a Ray pod in production.
  # Ray pods should be sized to take up entire K8s nodes when possible.
  # Always set CPU and memory limits for Ray pods.
  # It is usually best to set requests equal to limits.
  # See https://docs.ray.io/en/latest/cluster/kubernetes/user-guides/config.html#resources
  # for further guidance.
    resources:
      limits:
        cpu: 1
        memory: "1G"
      requests:
        cpu: 1
        memory: "1G"
    annotations: {}
    nodeSelector: {}
    tolerations: []
    affinity: {}
    # Ray container security context.
    securityContext: {}
    volumes:
      - name: log-volume
        emptyDir: {}
  # Ray writes logs to /tmp/ray/session_latests/logs
    volumeMounts:
      - mountPath: /tmp/ray
        name: log-volume
    sidecarContainers: []
    # See docs/guidance/pod-command.md for more details about how to specify
    # container command for worker Pod.
    command: []
    args: []

# Configuration for Head's Kubernetes Service
service:
  # This is optional, and the default is ClusterIP.
  type: ClusterIP