kubernetes/argo-cd/applications/production-hm/ray-cluster/argo-cd-manifests/hm-ray-cluster-application.yaml
---
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
sources:
- 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
---
image:
repository: docker.io/rayproject/ray
tag: 2.32.0
head:
serviceAccountName: hm-ray-cluster-service-account
containerEnv:
- name: RAY_GRAFANA_IFRAME_HOST
value: https://hm-grafana.internal.hongbomiao.com
- name: RAY_GRAFANA_HOST
value: http://hm-prometheus-grafana.production-hm-prometheus.svc:80
- name: RAY_PROMETHEUS_HOST
value: http://hm-prometheus-kube-pr-prometheus.production-hm-prometheus.svc:9090
ports: []
resources:
requests:
cpu: 1000m
memory: 2Gi
limits:
cpu: 2000m
memory: 4Gi
worker:
replicas: 10
minReplicas: 2
maxReplicas: 100
serviceAccountName: hm-ray-cluster-service-account
containerEnv:
# https://github.com/ray-project/kuberay/issues/2239
- name: RANDOM_ENV
value: "1"
ports: []
resources:
requests:
cpu: 1000m
memory: 1Gi
limits:
cpu: 2000m
memory: 8Gi
- repoURL: git@github.com:hongbo-miao/hongbomiao.com.git
targetRevision: HEAD
path: kubernetes/argo-cd/applications/production-hm/ray-cluster/kubernetes-manifests
destination:
namespace: production-hm-ray-cluster
server: https://kubernetes.default.svc
syncPolicy:
syncOptions:
- ServerSideApply=true
automated:
prune: true