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[Bug] spec.workerGroupSpecs[0].template.spec.containers[0].env: Invalid value: "null" #2239

@hongbo-miao

Description

@hongbo-miao

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KubeRay Component

Ray Cluster

What happened + What you expected to happen

I try to deploy Ray Cluster by Helm Chart 1.1.1. I expect it succeed, but got error.

Reproduction script

When deploy Ray Cluster (I am using Argo CD)

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: hm-ray-cluster
  namespace: production-hm-argo-cd
  labels:
    app.kubernetes.io/name: hm-ray-cluster
spec:
  project: production-hm
  source:
    repoURL: https://ray-project.github.io/kuberay-helm
    # https://github.com/ray-project/kuberay/releases
    targetRevision: 1.1.1
    chart: ray-cluster
    helm:
      releaseName: hm-ray-cluster
      values: |
        # https://github.com/ray-project/kuberay/blob/master/helm-chart/ray-cluster/values.yaml
        ---
        head:
          resources:
            requests:
              cpu: 1000m
              memory: 2Gi
            limits:
              cpu: 2000m
              memory: 4Gi
        worker:
          resources:
            requests:
              cpu: 1000m
              memory: 1Gi
            limits:
              cpu: 2000m
              memory: 8Gi
  destination:
    namespace: production-hm-ray-cluster
    server: https://kubernetes.default.svc
  syncPolicy:
    syncOptions:
      - ServerSideApply=true
    automated:
      prune: true

I got error

RayCluster.ray.io "hm-ray-cluster-kuberay" is invalid: [spec.headGroupSpec.template.spec.containers[0].env: Invalid value: "null": spec.headGroupSpec.template.spec.containers[0].env in body must be of type array: "null", spec.workerGroupSpecs[0].template.spec.containers[0].env: Invalid value: "null": spec.workerGroupSpecs[0].template.spec.containers[0].env in body must be of type array: "null", spec.workerGroupSpecs[0].template.spec.containers[0].ports: Invalid value: "null": spec.workerGroupSpecs[0].template.spec.containers[0].ports in body must be of type array: "null"]

Anything else

Currently I found the workaround way is adding random containerEnv and ports: [] for both head and worker.
(Note containerEnv has to has value, containerEnv: [] will still throw same error)

head:
  resources:
    requests:
      cpu: 1000m
      memory: 2Gi
    limits:
      cpu: 2000m
      memory: 4Gi
  containerEnv:
    - name: RANDOM_ENV
      value: "1"
  ports: []
worker:
  resources:
    requests:
      cpu: 1000m
      memory: 1Gi
    limits:
      cpu: 2000m
      memory: 8Gi
  containerEnv:
    - name: RANDOM_ENV
      value: "1"
  ports: []

Are you willing to submit a PR?

  • Yes I am willing to submit a PR!

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