Add documentation for ArgoCD

doc/source/cluster/kubernetes/examples/argocd.md

@@ -0,0 +1,157 @@
+(deploying-on-argocd-example)=
+
+# Deploying via ArgoCD
+
+Below is an example template on how to deploy using ArgoCD with
+3 different worker groups:
+
+```yaml
+apiVersion: argoproj.io/v1alpha1
+kind: Application
+metadata:
+  name: ray-operator-crds
+  namespace: argocd
+spec:
+  project: default
+  destination:
+    server: https://kubernetes.default.svc
+    namespace: ray-cluster
+  source:
+    repoURL: https://github.com/ray-project/kuberay
+    targetRevision: v1.4.0  # update this as necessary
+    path: helm-chart/kuberay-operator/crds
+  syncPolicy:
+    automated:
+      prune: true
+      selfHeal: true
+    syncOptions:
+      - CreateNamespace=true
+      - Replace=true
+
+---
+
+apiVersion: argoproj.io/v1alpha1
+kind: Application
+metadata:
+  name: ray-operator
+  namespace: argocd
+spec:
+  project: default
+  source:
+    repoURL: https://github.com/ray-project/kuberay
+    targetRevision: v1.4.0  # update this as necessary
+    path: helm-chart/kuberay-operator
+    helm:
+      skipCrds: true   # note this step is required
+  destination:
+    server: https://kubernetes.default.svc
+    namespace: ray-cluster
+  syncPolicy:
+    automated:
+      prune: true
+      selfHeal: true
+    syncOptions:
+      - CreateNamespace=true
+
+---
+
+apiVersion: argoproj.io/v1alpha1
+kind: Application
+metadata:
+  name: raycluster
+  namespace: argocd
+spec:
+  project: default
+  destination:
+    server: https://kubernetes.default.svc
+    namespace: ray-cluster
+  ignoreDifferences:
+    - group: ray.io
+      kind: RayCluster
+      name: raycluster-kuberay
+      namespace: ray-cluster
+      jsonPointers:
+        - /spec/workerGroupSpecs/0/replicas
+        - /spec/workerGroupSpecs/1/replicas
+        - /spec/workerGroupSpecs/2/replicas
+  source:
+    repoURL: https://ray-project.github.io/kuberay-helm/
+    chart: ray-cluster
+    targetRevision: "1.4.1"
+    helm:
+      releaseName: raycluster
+      valuesObject:
+        image:
+          repository: docker.io/rayproject/ray
+          tag: latest
+          pullPolicy: IfNotPresent
+        head:
+          rayStartParams:
+            num-cpus: "0"
+          enableInTreeAutoscaling: true
+          autoscalerOptions:
+            version: v2
+            upscalingMode: Default
+            idleTimeoutSeconds: 600 # 10 minutes
+            env:
+            - name: AUTOSCALER_MAX_CONCURRENT_LAUNCHES
+              value: "100"
+        worker:
+          groupName: standard-worker
+          replicas: 1
+          minReplicas: 1
+          maxReplicas: 200
+          rayStartParams:
+            resources: '"{\"standard-worker\": 1}"'
+        additionalWorkerGroups:
+          additional-worker-group1:
+            image:
+              repository: docker.io/rayproject/ray
+              tag: latest
+              pullPolicy: IfNotPresent
+            disabled: false
+            replicas: 0
+            minReplicas: 0
+            maxReplicas: 30
+            rayStartParams:
+              resources: '"{\"additional-worker-group1\": 1}"'
+          additional-worker-group2:
+            image:
+              repository: docker.io/rayproject/ray
+              tag: latest
+              pullPolicy: IfNotPresent
+            disabled: false
+            replicas: 1
+            minReplicas: 1
+            maxReplicas: 200
+            rayStartParams:
+              resources: '"{\"additional-worker-group2\": 1}"'
+  syncPolicy:
+    automated:
+      prune: true
+      selfHeal: true
+    syncOptions:
+      - CreateNamespace=true
+
+```
+
+## Auto Scaling
+
+With regard to the Ray autoscaler, note this section in the ArgoCD application:
+
+```yaml
+  ignoreDifferences:
+    - group: ray.io
+      kind: RayCluster
+      name: raycluster-kuberay
+      namespace: ray-cluster
+      jsonPointers:
+        - /spec/workerGroupSpecs/0/replicas
+        - /spec/workerGroupSpecs/1/replicas
+        - /spec/workerGroupSpecs/2/replicas
+```
+
+It has been observed that without this `ignoreDifferences` section, ArgoCD
+and the Ray Autoscaler may conflict, resulting in unexpected behaviour when
+it comes to requesting workers dynamically (e.g. `ray.autoscaler.sdk.request_resources`).
+More specifically, when requesting N workers, the Autoscaler would not spin up N workers.