stable/dask/values.yaml - master - githubmirror/charts

stable/dask/values.yaml
115 строк3 KB
Harald Haas
[stable/dask] Dask ingress (#16787)
30 сен 2019, 17:09
30 сен 2019, 17:091c90df1
---
# nameOverride: dask
# fullnameOverride: dask

scheduler:
  name: scheduler
  image:
    repository: "daskdev/dask"
    tag: 1.1.5
    pullPolicy: IfNotPresent
    # See https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
    pullSecrets:
    #  - name: regcred
  replicas: 1
  # serviceType: "ClusterIP"
  # serviceType: "NodePort"
  serviceType: "LoadBalancer"
  servicePort: 8786
  resources: {}
  #  limits:
  #    cpu: 1.8
  #    memory: 6G
  #  requests:
  #    cpu: 1.8
  #    memory: 6G
  tolerations: []
  nodeSelector: {}
  affinity: {}

webUI:
  name: webui
  servicePort: 80
  ingress:
    enabled: false
    tls: false
    # secretName: dask-scheduler-tls
    hostname: dask-ui.example.com
    annotations:
     # kubernetes.io/ingress.class: "nginx"
     # secretName: my-tls-cert
     # kubernetes.io/tls-acme: "true"

worker:
  name: worker
  image:
    repository: "daskdev/dask"
    tag: 1.1.5
    pullPolicy: IfNotPresent
    # dask_worker: "dask-cuda-worker"
    dask_worker: "dask-worker"
    pullSecrets:
    #  - name: regcred
  replicas: 3
  aptPackages: >-
  default_resources:  # overwritten by resource limits if they exist
    cpu: 1
    memory: "4GiB"
  env:
  #  - name: EXTRA_CONDA_PACKAGES
  #    value: numba xarray -c conda-forge
  #  - name: EXTRA_PIP_PACKAGES
  #    value: s3fs dask-ml --upgrade
  resources: {}
  #  limits:
  #    cpu: 1
  #    memory: 3G
  #    nvidia.com/gpu: 1
  #  requests:
  #    cpu: 1
  #    memory: 3G
  #    nvidia.com/gpu: 1
  tolerations: []
  nodeSelector: {}
  affinity: {}

jupyter:
  name: jupyter
  enabled: true
  image:
    repository: "daskdev/dask-notebook"
    tag: 1.1.5
    pullPolicy: IfNotPresent
    pullSecrets:
    #  - name: regcred
  replicas: 1
  # serviceType: "ClusterIP"
  # serviceType: "NodePort"
  serviceType: "LoadBalancer"
  servicePort: 80
  # This hash corresponds to the password 'dask'
  password: 'sha1:aae8550c0a44:9507d45e087d5ee481a5ce9f4f16f37a0867318c'
  env:
  #  - name: EXTRA_CONDA_PACKAGES
  #    value: "numba xarray -c conda-forge"
  #  - name: EXTRA_PIP_PACKAGES
  #    value: "s3fs dask-ml --upgrade"
  resources: {}
  #  limits:
  #    cpu: 2
  #    memory: 6G
  #  requests:
  #    cpu: 2
  #    memory: 6G
  tolerations: []
  nodeSelector: {}
  affinity: {}
  ingress:
    enabled: false
    tls: false
    # secretName: dask-jupyter-tls
    hostname: dask-jupyter.example.com
    annotations:
      # kubernetes.io/ingress.class: "nginx"
      # secretName: my-tls-cert
      # kubernetes.io/tls-acme: "true"