Release v0.6.0 doc validation (ray-project#1271)

Release v0.6.0 doc validation
lowang-bh · Jul 26, 2023 · 907be43 · 907be43
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diff --git a/.github/workflows/actions/configuration/action.yaml b/.github/workflows/actions/configuration/action.yaml
@@ -63,7 +63,7 @@ runs:
     env:
       GITHUB_ACTIONS: true
       RAY_IMAGE: rayproject/ray:${{ inputs.ray_version }}
-      OPERATOR_IMAGE: kuberay/operator:v0.5.0 # The operator image in the latest KubeRay release.
+      OPERATOR_IMAGE: kuberay/operator:v0.6.0 # The operator image in the latest KubeRay release.
     run: |
       python tests/test_sample_raycluster_yamls.py
     shell: bash
@@ -83,7 +83,7 @@ runs:
     env:
       GITHUB_ACTIONS: true
       RAY_IMAGE: rayproject/ray:${{ inputs.ray_version }}
-      OPERATOR_IMAGE: kuberay/operator:v0.5.0 # The operator image in the latest KubeRay release.
+      OPERATOR_IMAGE: kuberay/operator:v0.6.0 # The operator image in the latest KubeRay release.
     run: |
       python tests/test_sample_rayjob_yamls.py
     shell: bash
diff --git a/.github/workflows/image-release.yaml b/.github/workflows/image-release.yaml
@@ -7,7 +7,7 @@ on:
         description: 'Commit reference (branch or SHA) from which to build the images.'
         required: true
       tag:
-        description: 'Desired release version tag (e.g. v0.5.0-rc.0).'
+        description: 'Desired release version tag (e.g. v0.6.0-rc.0).'
         required: true
 
 jobs:

diff --git a/README.md b/README.md
@@ -45,12 +45,12 @@ We also recommend checking out the official Ray guides for deploying on Kubernet
 ## Quick Start
 
 * Try this [end-to-end example](helm-chart/ray-cluster/README.md)!
-* Please choose the version you would like to install. The examples below use the latest stable version `v0.5.0`.
+* Please choose the version you would like to install. The examples below use the latest stable version `v0.6.0`.
 
 | Version  |  Stable |  Suggested Kubernetes Version |
 |----------|:-------:|------------------------------:|
 |  master  |    N    | v1.19 - v1.25 |
-|  v0.5.0  |    Y    | v1.19 - v1.25 |
+|  v0.6.0  |    Y    | v1.19 - v1.25 |
 
 ### Use YAML
 
@@ -59,19 +59,19 @@ Once you have connected to a Kubernetes cluster, run the following commands to d
 
 ```sh
 # case 1: kubectl >= v1.22.0
-export KUBERAY_VERSION=v0.5.0
+export KUBERAY_VERSION=v0.6.0
 kubectl create -k "github.com/ray-project/kuberay/ray-operator/config/default?ref=${KUBERAY_VERSION}&timeout=90s"
 
 # case 2: kubectl < v1.22.0
-# Clone KubeRay repository and checkout to the desired branch e.g. `release-0.5`.
+# Clone KubeRay repository and checkout to the desired branch e.g. `release-0.6`.
 kubectl create -k ray-operator/config/default
 ```
 
 To deploy both the KubeRay Operator and the optional KubeRay API Server run the following commands.
 
 ```sh
 # case 1: kubectl >= v1.22.0
-export KUBERAY_VERSION=v0.5.0
+export KUBERAY_VERSION=v0.6.0
 kubectl create -k "github.com/ray-project/kuberay/manifests/cluster-scope-resources?ref=${KUBERAY_VERSION}&timeout=90s"
 kubectl apply -k "github.com/ray-project/kuberay/manifests/base?ref=${KUBERAY_VERSION}&timeout=90s"
 
@@ -92,8 +92,8 @@ Please read [kuberay-operator](helm-chart/kuberay-operator/README.md) to deploy
 ```sh
 helm repo add kuberay https://ray-project.github.io/kuberay-helm/
 
-# Install both CRDs and KubeRay operator v0.5.0.
-helm install kuberay-operator kuberay/kuberay-operator --version 0.5.0
+# Install both CRDs and KubeRay operator v0.6.0.
+helm install kuberay-operator kuberay/kuberay-operator --version 0.6.0
 
 # Check the KubeRay operator Pod in `default` namespace
 kubectl get pods

diff --git a/apiserver/README.md b/apiserver/README.md
@@ -34,8 +34,8 @@ helm version
   ```sh
   helm repo add kuberay https://ray-project.github.io/kuberay-helm/
 
-  # Install KubeRay APIServer v0.5.0.
-  helm install kuberay-apiserver kuberay/kuberay-apiserver --version 0.5.0
+  # Install KubeRay APIServer v0.6.0.
+  helm install kuberay-apiserver kuberay/kuberay-apiserver --version 0.6.0
 
   # Check the KubeRay APIServer Pod in `default` namespace
   kubectl get pods
@@ -59,8 +59,8 @@ To list the `my-release` deployment:
 
 ```sh
 helm ls
-# NAME                    NAMESPACE       REVISION        UPDATED                                 STATUS  CHART                    APP VERSION
-# kuberay-apiserver       default         1               2023-02-07 09:28:15.510869781 -0500 EST deployedkuberay-apiserver-0.5.0
+# NAME                    NAMESPACE       REVISION        UPDATED                                 STATUS   CHART                    APP VERSION
+# kuberay-apiserver       default         1               2023-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx deployed kuberay-apiserver-0.6.0
 ```
 
 ### Uninstall the Chart

diff --git a/clients/python-client/python_client/__init__.py b/clients/python-client/python_client/__init__.py
@@ -1 +1 @@
-__version__ = "0.5.0"
+__version__ = "0.6.0"
diff --git a/clients/python-client/setup.cfg b/clients/python-client/setup.cfg
@@ -1,6 +1,6 @@
 [metadata]
 name = python_client
-version = 0.5.0
+version = 0.6.0
 author = Ali Kanso
 description = A Kuberay python client library to create/delete/update clusters
 long_description = file: README.md

diff --git a/docs/deploy/docker.md b/docs/deploy/docker.md
@@ -3,7 +3,7 @@
 Find the Docker images for various KubeRay components on [Dockerhub](https://hub.docker.com/u/kuberay).
 
 #### Stable versions
-For stable releases, use version tags (e.g. `kuberay/operator:v0.5.0`).
+For stable releases, use version tags (e.g. `kuberay/operator:v0.6.0`).
 
 #### Master commits
 The first seven characters of the git SHA specify images built from specific commits

diff --git a/docs/deploy/installation.md b/docs/deploy/installation.md
@@ -26,10 +26,10 @@ helm install kuberay-operator kuberay/kuberay-operator
 #### Method 2: Kustomize
 ```sh
 # Install CRDs
-kubectl create -k "github.com/ray-project/kuberay/manifests/cluster-scope-resources?ref=v0.5.0&timeout=90s"
+kubectl create -k "github.com/ray-project/kuberay/manifests/cluster-scope-resources?ref=v0.6.0&timeout=90s"
 
 # Install KubeRay operator
-kubectl apply -k "github.com/ray-project/kuberay/manifests/base?ref=v0.5.0"
+kubectl apply -k "github.com/ray-project/kuberay/manifests/base?ref=v0.6.0"
 ```
 
 > Observe that we must use `kubectl create` to install cluster-scoped resources.
@@ -43,8 +43,8 @@ Users can use the following commands to deploy KubeRay operator in a specific na
 export KUBERAY_NAMESPACE=<my-awesome-namespace>
 
 # Install CRDs (Executed by cluster admin)
-kustomize build "github.com/ray-project/kuberay/manifests/overlays/single-namespace-resources?ref=v0.5.0" | envsubst | kubectl create -f -
+kustomize build "github.com/ray-project/kuberay/manifests/overlays/single-namespace-resources?ref=v0.6.0" | envsubst | kubectl create -f -
 
 # Install KubeRay operator (Executed by user)
-kustomize build "github.com/ray-project/kuberay/manifests/overlays/single-namespace?ref=v0.5.0" | envsubst | kubectl apply -f -
+kustomize build "github.com/ray-project/kuberay/manifests/overlays/single-namespace?ref=v0.6.0" | envsubst | kubectl apply -f -
 ```
diff --git a/docs/guidance/ingress.md b/docs/guidance/ingress.md
@@ -37,12 +37,7 @@ popd
 # (2) Set the name of head pod service to `spec...backend.service.name`
 eksctl get cluster ${YOUR_EKS_CLUSTER} # Check subnets on the EKS cluster
 
-# Step 4: Create an ALB ingress. When an ingress with proper annotations creates,
-#        AWS Load Balancer controller will reconcile a ALB (not in AWS EKS cluster).
-# For RayService, you can use ray-operator/config/samples/ray_v1alpha1_rayservice-alb-ingress.yaml
-kubectl apply -f ray-operator/config/samples/alb-ingress.yaml
-
-# Step 5: Check ingress created by Step 4.
+# Step 4: Check ingress created by Step 4.
 kubectl describe ingress ray-cluster-ingress
 
 # [Example]

diff --git a/docs/guidance/kubeflow-integration.md b/docs/guidance/kubeflow-integration.md
@@ -37,7 +37,7 @@ kustomize version --short
 ```sh
 # Create a RayCluster CR, and the KubeRay operator will reconcile a Ray cluster
 # with 1 head Pod and 1 worker Pod.
-helm install raycluster kuberay/ray-cluster --version 0.5.0 --set image.tag=2.2.0-py38-cpu
+helm install raycluster kuberay/ray-cluster --version 0.6.0 --set image.tag=2.2.0-py38-cpu
 
 # Check RayCluster
 kubectl get pod -l ray.io/cluster=raycluster-kuberay

diff --git a/docs/guidance/mobilenet-rayservice.md b/docs/guidance/mobilenet-rayservice.md
@@ -10,8 +10,8 @@ kind create cluster --image=kindest/node:v1.23.0
 
 ## Step 2: Install KubeRay operator
 
-Follow [this document](../../helm-chart/kuberay-operator/README.md) to install the nightly KubeRay operator via 
-Helm. Note that the YAML file in Step 3 uses `serveConfigV2`, which is first supported by KubeRay v0.6.0.
+Follow [this document](../../helm-chart/kuberay-operator/README.md) to install the latest stable KubeRay operator via Helm repository.
+Please note that the YAML file in this example uses `serveConfigV2`, which is supported starting from KubeRay v0.6.0.
 
 ## Step 3: Install a RayService
 

diff --git a/docs/guidance/prometheus-grafana.md b/docs/guidance/prometheus-grafana.md
@@ -35,7 +35,7 @@ kubectl get all -n prometheus-system
 ## Step 4: Install a RayCluster
 
 ```sh
-helm install raycluster kuberay/ray-cluster --version 0.5.0
+helm install raycluster kuberay/ray-cluster --version 0.6.0
 
 # Check ${RAYCLUSTER_HEAD_POD}
 kubectl get pod -l ray.io/node-type=head
@@ -271,6 +271,7 @@ kubectl port-forward --address 0.0.0.0 prometheus-prometheus-kube-prometheus-pro
 - Go to `${YOUR_IP}:9090/targets` (e.g. `127.0.0.1:9090/targets`). You should be able to see:
   - `podMonitor/prometheus-system/ray-workers-monitor/0 (1/1 up)`
   - `serviceMonitor/prometheus-system/ray-head-monitor/0 (1/1 up)`
+
 ![Prometheus Web UI](../images/prometheus_web_ui.png)
 
 - Go to `${YOUR_IP}:9090/graph`. You should be able to query:

diff --git a/docs/guidance/rayjob.md b/docs/guidance/rayjob.md
@@ -5,7 +5,7 @@
 ## Prerequisites
 
 * Ray 1.10 or higher
-* KubeRay v0.3.0+. (v0.5.0+ is recommended)
+* KubeRay v0.3.0+. (v0.6.0+ is recommended)
 
 ## What is a RayJob?
 

diff --git a/docs/guidance/rayservice.md b/docs/guidance/rayservice.md
@@ -33,9 +33,8 @@ kind create cluster --image=kindest/node:v1.23.0
 
 ## Step 2: Install the KubeRay operator
 
-Follow [this document](https://github.com/ray-project/kuberay/blob/master/helm-chart/kuberay-operator/README.md) to install the nightly KubeRay operator via Helm.
-Note that sample RayService in this guide uses `serveConfigV2` to specify a multi-application Serve config.
-This will be first supported in Kuberay 0.6.0, and is currently supported only on the nightly KubeRay operator.
+Follow [this document](../../helm-chart/kuberay-operator/README.md) to install the latest stable KubeRay operator via Helm repository.
+Please note that the YAML file in this example uses `serveConfigV2` to specify a multi-application Serve config, which is supported starting from KubeRay v0.6.0.
 
 ## Step 3: Install a RayService
 

diff --git a/docs/guidance/stable-diffusion-rayservice.md b/docs/guidance/stable-diffusion-rayservice.md
@@ -7,10 +7,10 @@ and [the Ray documentation](https://docs.ray.io/en/latest/serve/tutorials/stable
 
 Follow [aws-eks-gpu-cluster.md](./aws-eks-gpu-cluster.md) or [gcp-gke-gpu-cluster.md](./gcp-gke-gpu-cluster.md) to create a Kubernetes cluster with 1 CPU node and 1 GPU node.
 
-## Step 2: Install the nightly KubeRay operator
+## Step 2: Install KubeRay operator
 
-Follow [this document](../../helm-chart/kuberay-operator/README.md) to install the **nightly** KubeRay operator via 
-Helm. We're installing the nightly release here since this example's YAML file uses `serveConfigV2`, which uses features that will be released in KubeRay v0.6.0.
+Follow [this document](../../helm-chart/kuberay-operator/README.md) to install the latest stable KubeRay operator via Helm repository.
+Please note that the YAML file in this example uses `serveConfigV2`, which is supported starting from KubeRay v0.6.0.
 
 ## Step 3: Install a RayService
 

diff --git a/docs/guidance/tls.md b/docs/guidance/tls.md
@@ -34,7 +34,7 @@ This [YouTube video](https://youtu.be/T4Df5_cojAs) is a good start.
 your CA private key in a Kubernetes Secret in your production environment.
 
 ```sh
-# Install v0.5.0 KubeRay operator
+# Install v0.6.0 KubeRay operator
 # `ray-cluster.tls.yaml` will cover from Step 1 to Step 3 (path: kuberay/)
 kubectl apply -f ray-operator/config/samples/ray-cluster.tls.yaml