[Doc][KubeRay] Improve KubeRay docs based on CUJ (part 2) (#45304)

doc/source/cluster/key-concepts.rst

@@ -76,7 +76,7 @@ The worker that runs the Python script is known as the *driver* of the job.
 There are two ways to run a Ray job on a Ray cluster:
 
 1. (Recommended) Submit the job using the :ref:`Ray Jobs API <jobs-overview>`.
-2. Run the driver script directly on any node of the Ray cluster, for interactive development.
+2. Run the driver script directly on the Ray cluster, for interactive development.
 
 For details on these workflows, refer to the :ref:`Ray Jobs API guide <jobs-overview>`.
 

doc/source/cluster/kubernetes/examples/mobilenet-rayservice.md

@@ -7,7 +7,7 @@
 ## Step 1: Create a Kubernetes cluster with Kind
 
 ```sh
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 ```
 
 ## Step 2: Install KubeRay operator

doc/source/cluster/kubernetes/getting-started/raycluster-quick-start.md

@@ -6,7 +6,7 @@ This guide shows you how to manage and interact with Ray clusters on Kubernetes.
 
 ## Preparation
 
-* Install [kubectl](https://kubernetes.io/docs/tasks/tools/#kubectl) (>= 1.23), [Helm](https://helm.sh/docs/intro/install/) (>= v3.4), and [Kind](https://kind.sigs.k8s.io/docs/user/quick-start/#installation).
+* Install [kubectl](https://kubernetes.io/docs/tasks/tools/#kubectl) (>= 1.23), [Helm](https://helm.sh/docs/intro/install/) (>= v3.4), [Kind](https://kind.sigs.k8s.io/docs/user/quick-start/#installation), and [Docker](https://docs.docker.com/engine/install/).
 * Make sure your Kubernetes cluster has at least 4 CPU and 4 GB RAM.
 
 ## Step 1: Create a Kubernetes cluster
@@ -143,7 +143,7 @@ See the job you submitted in Step 4 in the **Recent jobs** pane as shown below.
 ## Step 6: Cleanup
 
 ```sh
-# [Step 5.1]: Delete the RayCluster CR
+# [Step 6.1]: Delete the RayCluster CR
 # Uninstall the RayCluster Helm chart
 helm uninstall raycluster
 # release "raycluster" uninstalled
@@ -155,7 +155,7 @@ kubectl get pods
 # NAME                                READY   STATUS    RESTARTS   AGE
 # kuberay-operator-7fbdbf8c89-pt8bk   1/1     Running   0          XXm
 
-# [Step 5.2]: Delete the KubeRay operator
+# [Step 6.2]: Delete the KubeRay operator
 # Uninstall the KubeRay operator Helm chart
 helm uninstall kuberay-operator
 # release "kuberay-operator" uninstalled
@@ -164,6 +164,6 @@ helm uninstall kuberay-operator
 kubectl get pods
 # No resources found in default namespace.
 
-# [Step 5.3]: Delete the Kubernetes cluster
+# [Step 6.3]: Delete the Kubernetes cluster
 kind delete cluster
 ```

doc/source/cluster/kubernetes/getting-started/rayjob-quick-start.md

@@ -64,7 +64,7 @@ To understand the following content better, you should understand the difference
 ## Step 1: Create a Kubernetes cluster with Kind
 
 ```sh
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 ```
 
 ## Step 2: Install the KubeRay operator

doc/source/cluster/kubernetes/getting-started/rayservice-quick-start.md

@@ -29,7 +29,7 @@ A RayService manages these components:
 ## Step 1: Create a Kubernetes cluster with Kind
 
 ```sh
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 ```
 
 ## Step 2: Install the KubeRay operator
@@ -40,11 +40,7 @@ Please note that the YAML file in this example uses `serveConfigV2` to specify a
 ## Step 3: Install a RayService
 
 ```sh
-# Step 3.1: Download `ray-service.sample.yaml`
-curl -LO https://raw.githubusercontent.com/ray-project/kuberay/release-1.1.1/ray-operator/config/samples/ray-service.sample.yaml
-
-# Step 3.2: Create a RayService
-kubectl apply -f ray-service.sample.yaml
+kubectl apply -f https://raw.githubusercontent.com/ray-project/kuberay/v1.1.1/ray-operator/config/samples/ray-service.sample.yaml
 ```
 
 ## Step 4: Verify the Kubernetes cluster status 
@@ -114,7 +110,7 @@ curl -X POST -H 'Content-Type: application/json' rayservice-sample-serve-svc:800
 
 ```sh
 # Delete the RayService.
-kubectl delete -f ray-service.sample.yaml
+kubectl delete -f https://raw.githubusercontent.com/ray-project/kuberay/v1.1.1/ray-operator/config/samples/ray-service.sample.yaml
 
 # Uninstall the KubeRay operator.
 helm uninstall kuberay-operator

doc/source/cluster/kubernetes/k8s-ecosystem/ingress.md

@@ -185,12 +185,12 @@ kubectl wait --namespace ingress-nginx \
 # Step 3: Install KubeRay operator and CRD
 helm repo add kuberay https://ray-project.github.io/kuberay-helm/
 helm repo update
-helm install kuberay-operator kuberay/kuberay-operator --version 1.0.0
+helm install kuberay-operator kuberay/kuberay-operator --version 1.1.1
 
 # Step 4: Install RayCluster and create an ingress separately.
 # More information about change of setting was documented in https://github.com/ray-project/kuberay/pull/699 
 # and `ray-operator/config/samples/ray-cluster.separate-ingress.yaml`
-curl -LO https://raw.githubusercontent.com/ray-project/kuberay/v1.0.0/ray-operator/config/samples/ray-cluster.separate-ingress.yaml
+curl -LO https://raw.githubusercontent.com/ray-project/kuberay/v1.1.1/ray-operator/config/samples/ray-cluster.separate-ingress.yaml
 kubectl apply -f ray-operator/config/samples/ray-cluster.separate-ingress.yaml
 
 # Step 5: Check the ingress created in Step 4.

doc/source/cluster/kubernetes/k8s-ecosystem/kubeflow.md

@@ -23,7 +23,7 @@ The [Kubeflow](https://www.kubeflow.org/) project is dedicated to making deploym
 ## Step 1: Create a Kubernetes cluster with Kind.
 ```sh
 # Kubeflow is sensitive to Kubernetes version and Kustomize version.
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 kustomize version --short
 # 3.2.0
 ```

doc/source/cluster/kubernetes/user-guides/configuring-autoscaling.md

@@ -55,7 +55,7 @@ Then, the KubeRay operator deletes the Pods in the `workersToDelete` field.
 ### Step 1: Create a Kubernetes cluster with Kind
 
 ```bash
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 ```
 
 ### Step 2: Install the KubeRay operator
@@ -65,8 +65,7 @@ Follow [this document](kuberay-operator-deploy) to install the latest stable Kub
 ### Step 3: Create a RayCluster custom resource with autoscaling enabled
 
 ```bash
-curl -LO https://raw.githubusercontent.com/ray-project/kuberay/release-1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml
-kubectl apply -f ray-cluster.autoscaler.yaml
+kubectl apply -f https://raw.githubusercontent.com/ray-project/kuberay/v1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml
 ```
 
 ### Step 4: Verify the Kubernetes cluster status
@@ -89,7 +88,7 @@ kubectl get configmaps
 ```
 
 The RayCluster has one head Pod and zero worker Pods. The head Pod has two containers: a Ray head container and a Ray Autoscaler sidecar container.
-Additionally, the [ray-cluster.autoscaler.yaml](https://github.com/ray-project/kuberay/blob/release-1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml) includes a ConfigMap named `ray-example` that houses two Python scripts: `detached_actor.py` and `terminate_detached_actor`.py.
+Additionally, the [ray-cluster.autoscaler.yaml](https://github.com/ray-project/kuberay/blob/v1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml) includes a ConfigMap named `ray-example` that houses two Python scripts: `detached_actor.py` and `terminate_detached_actor`.py.
 
 * `detached_actor.py` is a Python script that creates a detached actor which requires 1 CPU.
   ```py
@@ -249,7 +248,7 @@ kubectl logs $HEAD_POD -c autoscaler | tail -n 20
 
 ```bash
 # Delete RayCluster and ConfigMap
-kubectl delete -f ray-cluster.autoscaler.yaml
+kubectl delete -f https://raw.githubusercontent.com/ray-project/kuberay/v1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml
 
 # Uninstall the KubeRay operator
 helm uninstall kuberay-operator
@@ -258,7 +257,7 @@ helm uninstall kuberay-operator
 (kuberay-autoscaling-config)=
 ## KubeRay Autoscaling Configurations
 
-The [ray-cluster.autoscaler.yaml](https://github.com/ray-project/kuberay/blob/release-1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml) used in the quickstart example contains detailed comments about the configuration options.
+The [ray-cluster.autoscaler.yaml](https://github.com/ray-project/kuberay/blob/v1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml) used in the quickstart example contains detailed comments about the configuration options.
 ***It's recommended to read this section in conjunction with the YAML file.***
 
 ### 1. Enabling autoscaling
@@ -322,7 +321,7 @@ for container environment variables.
 The Ray Autoscaler reads the `rayStartParams` field or the Ray container's resource limits in the RayCluster custom resource specification to determine the Ray Pod's resource requirements.
 The information regarding the number of CPUs is essential for the Ray Autoscaler to scale the cluster.
 Therefore, without this information, the Ray Autoscaler would report an error and fail to start.
-Take [ray-cluster.autoscaler.yaml](https://github.com/ray-project/kuberay/blob/release-1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml) as an example below:
+Take [ray-cluster.autoscaler.yaml](https://github.com/ray-project/kuberay/blob/v1.1.1/ray-operator/config/samples/ray-cluster.autoscaler.yaml) as an example below:
 
 * If users set `num-cpus` in `rayStartParams`, Ray Autoscaler would work regardless of the resource limits on the container.
 * If users don't set `rayStartParams`, the Ray container must have a specified CPU resource limit.

doc/source/cluster/kubernetes/user-guides/helm-chart-rbac.md

@@ -49,7 +49,7 @@ The operator has cluster-scoped access to create and manage resources, using Clu
 
 ```shell
 # Create a Kubernetes cluster using Kind.
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 
 # Create namespaces.
 kubectl create ns n1
@@ -96,7 +96,7 @@ The operator has Role and RoleBinding in the same namespace.
 
 ```shell
 # Create a Kubernetes cluster using Kind.
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 
 # Create namespaces.
 kubectl create ns n1
@@ -151,7 +151,7 @@ Case 3 creates Role and RoleBinding for multiple namespaces, allowing a single K
 
 ```shell
 # Create a Kubernetes cluster using Kind.
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 
 # Create namespaces.
 kubectl create ns n1

doc/source/cluster/kubernetes/user-guides/kuberay-gcs-ft.md

@@ -34,7 +34,7 @@ See {ref}`Ray Serve end-to-end fault tolerance documentation <serve-e2e-ft-guide
 ### Step 1: Create a Kubernetes cluster with Kind
 
 ```sh
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 ```
 
 ### Step 2: Install the KubeRay operator

doc/source/cluster/kubernetes/user-guides/pod-security.md

@@ -23,7 +23,7 @@ This tutorial requires several files in the repository.
 
 ```bash
 # Path: kuberay/
-kind create cluster --config ray-operator/config/security/kind-config.yaml --image=kindest/node:v1.24.0
+kind create cluster --config ray-operator/config/security/kind-config.yaml --image=kindest/node:v1.26.0
 ```
 
 The `kind-config.yaml` enables audit logging with the audit policy defined in `audit-policy.yaml`. The `audit-policy.yaml`

doc/source/cluster/kubernetes/user-guides/rayservice-high-availability.md

@@ -13,7 +13,7 @@
 ### Step 1: Create a Kubernetes cluster with Kind
 
 ```sh
-kind create cluster --image=kindest/node:v1.23.0
+kind create cluster --image=kindest/node:v1.26.0
 ```
 
 ### Step 2: Install the KubeRay operator

doc/source/cluster/kubernetes/user-guides/rayservice.md

@@ -40,11 +40,7 @@ Note that the YAML file in this example uses `serveConfigV2` to specify a multi-
 ## Step 3: Install a RayService
 
 ```sh
-# Step 3.1: Download `ray-service.sample.yaml`
-curl -LO https://raw.githubusercontent.com/ray-project/kuberay/release-1.1.1/ray-operator/config/samples/ray-service.sample.yaml
-
-# Step 3.2: Create a RayService
-kubectl apply -f ray-service.sample.yaml
+kubectl apply -f https://raw.githubusercontent.com/ray-project/kuberay/v1.1.1/ray-operator/config/samples/ray-service.sample.yaml
 ```
 
 * First, look at the Ray Serve configuration `serveConfigV2` embedded in the RayService YAML. Notice two high-level applications: a fruit stand app and a calculator app. Take note of some details about the fruit stand application:
@@ -183,7 +179,7 @@ curl -X POST -H 'Content-Type: application/json' rayservice-sample-serve-svc:800
 
 You can update the configurations for the applications by modifying `serveConfigV2` in the RayService configuration file. Reapplying the modified configuration with `kubectl apply` reapplies the new configurations to the existing RayCluster instead of creating a new RayCluster.
 
-Update the price of mangos from `3` to `4` for the fruit stand app in [ray-service.sample.yaml](https://github.com/ray-project/kuberay/blob/release-1.1.1/ray-operator/config/samples/ray-service.sample.yaml). This change reconfigures the existing MangoStand deployment, and future requests will use the updated Mango price.
+Update the price of mangos from `3` to `4` for the fruit stand app in [ray-service.sample.yaml](https://github.com/ray-project/kuberay/blob/v1.1.1/ray-operator/config/samples/ray-service.sample.yaml). This change reconfigures the existing MangoStand deployment, and future requests will use the updated Mango price.
 
 ```sh
 # Step 7.1: Update the price of mangos from 3 to 4.