diff --git a/docs/guidance/volcano-integration.md b/docs/guidance/volcano-integration.md
index 3b2420ebcb..10b08480d4 100644
--- a/docs/guidance/volcano-integration.md
+++ b/docs/guidance/volcano-integration.md
@@ -6,76 +6,90 @@ Note that this is a new feature. Feedback and contributions welcome.
 
 ## Setup
 
-### Install Volcano
+### Step 1: Create a Kubernetes cluster with KinD
+```shell
+kind create cluster
+```
 
-Volcano needs to be successfully installed in your Kubernetes cluster before enabling Volcano integration with KubeRay. Refer to the [Quick Start Guide](https://github.com/volcano-sh/volcano#quick-start-guide) for Volcano installation instructions.
+### Step 2: Install Volcano
 
-### Install KubeRay Operator with Batch Scheduling
+Volcano needs to be successfully installed in your Kubernetes cluster before enabling Volcano integration with KubeRay.
+Refer to the [Quick Start Guide](https://github.com/volcano-sh/volcano#quick-start-guide) for Volcano installation instructions.
 
-Deploy the KubeRay Operator with the `--enable-batch-scheduler` flag to enable Volcano batch scheduling support.
+### Step 3: Install KubeRay Operator with Batch Scheduling
 
-When installing via Helm, you can set the following in your `values.yaml` file:
+Deploy the KubeRay Operator with the `--enable-batch-scheduler` flag to enable Volcano batch scheduling support.
 
-```
+When installing KubeRay Operator via Helm, you should either set `batchScheduler.enabled` to `true` in your
+[`values.yaml`](https://github.com/ray-project/kuberay/blob/753dc05dbed5f6fe61db3a43b34a1b350f26324c/helm-chart/kuberay-operator/values.yaml#L48)
+file:
+```shell
+# values.yaml file
 batchScheduler:
     enabled: true
 ```
 
-Or on the command line:
-
-```
-# helm install kuberay-operator --set batchScheduler.enabled=true
+**or** pass `--set batchScheduler.enabled=true` flag when running on the command line:
+```shell
+# Install Helm chart with --enable-batch-scheduler flag set to true 
+helm install kuberay-operator kuberay/kuberay-operator --version ${KUBERAY_VERSION} --set batchScheduler.enabled=true
 ```
 
-## Run Ray Cluster with Volcano scheduler
+Follow the [KubeRay installation documentation](https://github.com/ray-project/kuberay/blob/master/helm-chart/kuberay-operator/README.md) to install the latest stable KubeRay operator.
 
-Add the `ray.io/scheduler-name: volcano` label to your RayCluster CR to submit the cluster pods to Volcano for scheduling.
+### Step 4: Install a RayCluster with Volcano scheduler
 
-Example:
+RayCluster custom resource must include label `ray.io/scheduler-name: volcano` to submit the cluster pods to Volcano for scheduling.
 
-```
-apiVersion: ray.io/v1alpha1
-kind: RayCluster
-metadata:
-  name: test-cluster
-  labels:
-    ray.io/scheduler-name: volcano
-    volcano.sh/queue-name: kuberay-test-queue
-spec:
-  rayVersion: '2.6.3'
-  headGroupSpec:
-    rayStartParams: {}
-    replicas: 1
-    template:
-      spec:
-        containers:
-        - name: ray-head
-          image: rayproject/ray:2.6.3
-          resources:
-            limits:
-              cpu: "1"
-              memory: "2Gi"
-            requests:
-              cpu: "1"
-              memory: "2Gi"
-  workerGroupSpecs: []
+```shell
+# Path: kuberay/ray-operator/config/samples
+# Includes label `ray.io/scheduler-name: volcano` in the metadata.labels
+kubectl apply -f ray-cluster.volcano-scheduler.yaml
+
+# Check RayCluster
+kubectl get pod -l ray.io/cluster=test-cluster-0
+# NAME                                 READY   STATUS    RESTARTS   AGE
+# test-cluster-0-head-jj9bg            1/1     Running   0          36s
 ```
 
-The following labels can also be provided in the RayCluster metadata:
+In addition, the following labels can also be provided in the RayCluster metadata:
 
 - `ray.io/priority-class-name`: the cluster priority class as defined by Kubernetes [here](https://kubernetes.io/docs/concepts/scheduling-eviction/pod-priority-preemption/#priorityclass).
+  - This label will only work after the creation of a `PriorityClass` resource
+  - ```shell
+    labels:
+      ray.io/scheduler-name: volcano
+      ray.io/priority-class-name: <replace with correct PriorityClass resource name>
+    ```
 - `volcano.sh/queue-name`: the Volcano [queue](https://volcano.sh/en/docs/queue/) name the cluster will be submitted to.
+  - This label will only work after the creation of a `Queue` resource
+  - ```shell
+    labels:
+      ray.io/scheduler-name: volcano
+      volcano.sh/queue-name: <replace with correct Queue resource name>
+    ```
 
 If autoscaling is enabled, `minReplicas` will be used for gang scheduling, otherwise the desired `replicas` will be used.
 
-### Example: Gang scheduling
+### Step 5: Use Volcano for batch scheduling
+
+If you need some guidance, check out [examples](https://github.com/volcano-sh/volcano/tree/master/example) available.
+
+## Example
+
+Before going through the example, remove any ray clusters running to ensure successful run through of the example below. 
+```shell
+kubectl delete raycluster --all
+```
+
+### Gang scheduling
 
 In this example, we'll walk through how gang scheduling works with Volcano and KubeRay.
 
 First, let's create a queue with a capacity of 4 CPUs and 6Gi of RAM:
 
-```
-$ kubectl create -f - <<EOF
+```shell
+kubectl create -f - <<EOF
 apiVersion: scheduling.volcano.sh/v1beta1
 kind: Queue
 metadata:
@@ -94,296 +108,215 @@ The **capability** is a hard constraint on the maximum resources the queue will
 
 Next we'll create a RayCluster with a head node (1 CPU + 2Gi of RAM) and two workers (1 CPU + 1Gi of RAM each), for a total of 3 CPU and 4Gi of RAM:
 
-```
-$ kubectl create -f - <<EOF
-apiVersion: ray.io/v1alpha1
-kind: RayCluster
-metadata:
-  name: test-cluster-0
-  labels:
-    ray.io/scheduler-name: volcano
-    volcano.sh/queue-name: kuberay-test-queue
-spec:
-  rayVersion: '2.6.3'
-  headGroupSpec:
-    rayStartParams: {}
-    replicas: 1
-    template:
-      spec:
-        containers:
-        - name: ray-head
-          image: rayproject/ray:2.6.3
-          resources:
-            limits:
-              cpu: "1"
-              memory: "2Gi"
-            requests:
-              cpu: "1"
-              memory: "2Gi"
-  workerGroupSpecs:
-    - groupName: worker
-      rayStartParams: {}
-      replicas: 2
-      minReplicas: 2
-      maxReplicas: 2
-      template:
-        spec:
-          containers:
-          - name: ray-head
-            image: rayproject/ray:2.6.3
-            resources:
-              limits:
-                cpu: "1"
-                memory: "1Gi"
-              requests:
-                cpu: "1"
-                memory: "1Gi"
-EOF
+```shell
+# Path: kuberay/ray-operator/config/samples
+# Includes labels `ray.io/scheduler-name: volcano` and `volcano.sh/queue-name: kuberay-test-queue` in the metadata.labels
+kubectl apply -f ray-cluster.volcano-scheduler-queue.yaml
 ```
 
 Because our queue has a capacity of 4 CPU and 6Gi of RAM, this resource should schedule successfully without any issues. We can verify this by checking the status of our cluster's Volcano PodGroup to see that the phase is `Running` and the last status is `Scheduled`:
 
-```
-$ kubectl get podgroup ray-test-cluster-0-pg -o yaml
-
-apiVersion: scheduling.volcano.sh/v1beta1
-kind: PodGroup
-metadata:
-  creationTimestamp: "2022-12-01T04:43:30Z"
-  generation: 2
-  name: ray-test-cluster-0-pg
-  namespace: test
-  ownerReferences:
-  - apiVersion: ray.io/v1alpha1
-    blockOwnerDeletion: true
-    controller: true
-    kind: RayCluster
-    name: test-cluster-0
-    uid: 7979b169-f0b0-42b7-8031-daef522d25cf
-  resourceVersion: "4427347"
-  uid: 78902d3d-b490-47eb-ba12-d6f8b721a579
-spec:
-  minMember: 3
-  minResources:
-    cpu: "3"
-    memory: 4Gi
-  queue: kuberay-test-queue
-status:
-  conditions:
-  - lastTransitionTime: "2022-12-01T04:43:31Z"
-    reason: tasks in gang are ready to be scheduled
-    status: "True"
-    transitionID: f89f3062-ebd7-486b-8763-18ccdba1d585
-    type: Scheduled
-  phase: Running
+```shell
+kubectl get podgroup ray-test-cluster-0-pg -o yaml
+
+# apiVersion: scheduling.volcano.sh/v1beta1
+# kind: PodGroup
+# metadata:
+#   creationTimestamp: "2022-12-01T04:43:30Z"
+#   generation: 2
+#   name: ray-test-cluster-0-pg
+#   namespace: test
+#   ownerReferences:
+#   - apiVersion: ray.io/v1alpha1
+#     blockOwnerDeletion: true
+#     controller: true
+#     kind: RayCluster
+#     name: test-cluster-0
+#     uid: 7979b169-f0b0-42b7-8031-daef522d25cf
+#   resourceVersion: "4427347"
+#   uid: 78902d3d-b490-47eb-ba12-d6f8b721a579
+# spec:
+#   minMember: 3
+#   minResources:
+#     cpu: "3"
+#     memory: 4Gi
+#   queue: kuberay-test-queue
+# status:
+#   conditions:
+#   - lastTransitionTime: "2022-12-01T04:43:31Z"
+#     reason: tasks in gang are ready to be scheduled
+#     status: "True"
+#     transitionID: f89f3062-ebd7-486b-8763-18ccdba1d585
+#     type: Scheduled
+#   phase: Running
 ```
 
 And checking the status of our queue to see that we have 1 running job:
 
-```
-$ kubectl get queue kuberay-test-queue -o yaml
-
-apiVersion: scheduling.volcano.sh/v1beta1
-kind: Queue
-metadata:
-  creationTimestamp: "2022-12-01T04:43:21Z"
-  generation: 1
-  name: kuberay-test-queue
-  resourceVersion: "4427348"
-  uid: a6c4f9df-d58c-4da8-8a58-e01c93eca45a
-spec:
-  capability:
-    cpu: 4
-    memory: 6Gi
-  reclaimable: true
-  weight: 1
-status:
-  reservation: {}
-  running: 1
-  state: Open
+```shell
+kubectl get queue kuberay-test-queue -o yaml
+
+# apiVersion: scheduling.volcano.sh/v1beta1
+# kind: Queue
+# metadata:
+#   creationTimestamp: "2022-12-01T04:43:21Z"
+#   generation: 1
+#   name: kuberay-test-queue
+#   resourceVersion: "4427348"
+#   uid: a6c4f9df-d58c-4da8-8a58-e01c93eca45a
+# spec:
+#   capability:
+#     cpu: 4
+#     memory: 6Gi
+#   reclaimable: true
+#   weight: 1
+# status:
+#   reservation: {}
+#   running: 1
+#   state: Open
 ```
 
-Next we'll add an additional RayCluster with the same configuration of head / worker nodes, but a different name:
+Next, we'll add an additional RayCluster with the same configuration of head / worker nodes, but a different name:
 
-```
-$ kubectl create -f - <<EOF
-apiVersion: ray.io/v1alpha1
-kind: RayCluster
-metadata:
-  name: test-cluster-1
-  labels:
-    ray.io/scheduler-name: volcano
-    volcano.sh/queue-name: kuberay-test-queue
-spec:
-  rayVersion: '2.6.3'
-  headGroupSpec:
-    rayStartParams: {}
-    replicas: 1
-    template:
-      spec:
-        containers:
-        - name: ray-head
-          image: rayproject/ray:2.6.3
-          resources:
-            limits:
-              cpu: "1"
-              memory: "2Gi"
-            requests:
-              cpu: "1"
-              memory: "2Gi"
-  workerGroupSpecs:
-    - groupName: worker
-      rayStartParams: {}
-      replicas: 2
-      minReplicas: 2
-      maxReplicas: 2
-      template:
-        spec:
-          containers:
-          - name: ray-head
-            image: rayproject/ray:2.6.3
-            resources:
-              limits:
-                cpu: "1"
-                memory: "1Gi"
-              requests:
-                cpu: "1"
-                memory: "1Gi"
-EOF
+```shell
+# Path: kuberay/ray-operator/config/samples
+# Includes labels `ray.io/scheduler-name: volcano` and `volcano.sh/queue-name: kuberay-test-queue` in the metadata.labels
+# Replaces the name to test-cluster-1
+sed 's/test-cluster-0/test-cluster-1/' ray-cluster.volcano-scheduler-queue.yaml | kubectl apply -f-
 ```
 
 Now check the status of its PodGroup to see that its phase is `Pending` and the last status is `Unschedulable`:
 
-```
-$ kubectl get podgroup ray-test-cluster-1-pg -o yaml
-
-apiVersion: scheduling.volcano.sh/v1beta1
-kind: PodGroup
-metadata:
-  creationTimestamp: "2022-12-01T04:48:18Z"
-  generation: 2
-  name: ray-test-cluster-1-pg
-  namespace: test
-  ownerReferences:
-  - apiVersion: ray.io/v1alpha1
-    blockOwnerDeletion: true
-    controller: true
-    kind: RayCluster
-    name: test-cluster-1
-    uid: b3cf83dc-ef3a-4bb1-9c42-7d2a39c53358
-  resourceVersion: "4427976"
-  uid: 9087dd08-8f48-4592-a62e-21e9345b0872
-spec:
-  minMember: 3
-  minResources:
-    cpu: "3"
-    memory: 4Gi
-  queue: kuberay-test-queue
-status:
-  conditions:
-  - lastTransitionTime: "2022-12-01T04:48:19Z"
-    message: '3/3 tasks in gang unschedulable: pod group is not ready, 3 Pending,
-      3 minAvailable; Pending: 3 Undetermined'
-    reason: NotEnoughResources
-    status: "True"
-    transitionID: 3956b64f-fc52-4779-831e-d379648eecfc
-    type: Unschedulable
-  phase: Pending
+```shell
+kubectl get podgroup ray-test-cluster-1-pg -o yaml
+
+# apiVersion: scheduling.volcano.sh/v1beta1
+# kind: PodGroup
+# metadata:
+#   creationTimestamp: "2022-12-01T04:48:18Z"
+#   generation: 2
+#   name: ray-test-cluster-1-pg
+#   namespace: test
+#   ownerReferences:
+#   - apiVersion: ray.io/v1alpha1
+#     blockOwnerDeletion: true
+#     controller: true
+#     kind: RayCluster
+#     name: test-cluster-1
+#     uid: b3cf83dc-ef3a-4bb1-9c42-7d2a39c53358
+#   resourceVersion: "4427976"
+#   uid: 9087dd08-8f48-4592-a62e-21e9345b0872
+# spec:
+#   minMember: 3
+#   minResources:
+#     cpu: "3"
+#     memory: 4Gi
+#   queue: kuberay-test-queue
+# status:
+#   conditions:
+#   - lastTransitionTime: "2022-12-01T04:48:19Z"
+#     message: '3/3 tasks in gang unschedulable: pod group is not ready, 3 Pending,
+#       3 minAvailable; Pending: 3 Undetermined'
+#     reason: NotEnoughResources
+#     status: "True"
+#     transitionID: 3956b64f-fc52-4779-831e-d379648eecfc
+#     type: Unschedulable
+#   phase: Pending
 ```
 
 Because our new cluster requires more CPU and RAM than our queue will allow, even though we could fit one of the pods with the remaining 1 CPU and 2Gi of RAM, none of the cluster's pods will be placed until there is enough room for all the pods. Without using Volcano for gang scheduling in this way, one of the pods would ordinarily be placed, leading to the cluster being partially allocated, and some jobs (like [Horovod](https://github.com/horovod/horovod) training) getting stuck waiting for resources to become available.
 
 We can see the effect this has on scheduling the pods for our new RayCluster, which are listed as `Pending`:
 
-```
-$ kubectl get pods
-
-NAME                                            READY   STATUS         RESTARTS   AGE
-test-cluster-0-worker-worker-ddfbz              1/1     Running        0          7m
-test-cluster-0-head-vst5j                       1/1     Running        0          7m
-test-cluster-0-worker-worker-57pc7              1/1     Running        0          6m59s
-test-cluster-1-worker-worker-6tzf7              0/1     Pending        0          2m12s
-test-cluster-1-head-6668q                       0/1     Pending        0          2m12s
-test-cluster-1-worker-worker-n5g8k              0/1     Pending        0          2m12s
+```shell
+kubectl get pods
+
+# NAME                                            READY   STATUS         RESTARTS   AGE
+# test-cluster-0-worker-worker-ddfbz              1/1     Running        0          7m
+# test-cluster-0-head-vst5j                       1/1     Running        0          7m
+# test-cluster-0-worker-worker-57pc7              1/1     Running        0          6m59s
+# test-cluster-1-worker-worker-6tzf7              0/1     Pending        0          2m12s
+# test-cluster-1-head-6668q                       0/1     Pending        0          2m12s
+# test-cluster-1-worker-worker-n5g8k              0/1     Pending        0          2m12s
 ```
 
 If we dig into the pod details, we'll see that this is indeed because Volcano cannot schedule the gang:
 
-```
-$ kubectl describe pod test-cluster-1-head-6668q | tail -n 3
+```shell
+kubectl describe pod test-cluster-1-head-6668q | tail -n 3
 
-  Type     Reason            Age   From     Message
-  ----     ------            ----  ----     -------
-  Warning  FailedScheduling  4m5s  volcano  3/3 tasks in gang unschedulable: pod group is not ready, 3 Pending, 3 minAvailable; Pending: 3 Undetermined
+# Type     Reason            Age   From     Message
+# ----     ------            ----  ----     -------
+# Warning  FailedScheduling  4m5s  volcano  3/3 tasks in gang unschedulable: pod group is not ready, 3 Pending, 3 minAvailable; Pending: 3 Undetermined
 ```
 
 Let's go ahead and delete the first RayCluster to clear up space in the queue:
 
-```
-$ kubectl delete raycluster test-cluster-0
+```shell
+kubectl delete raycluster test-cluster-0
 ```
 
 The PodGroup for the second cluster has moved to the `Running` state, as there are now enough resources available to schedule the entire set of pods:
 
-```
-$ kubectl get podgroup ray-test-cluster-1-pg -o yaml
-
-apiVersion: scheduling.volcano.sh/v1beta1
-kind: PodGroup
-metadata:
-  creationTimestamp: "2022-12-01T04:48:18Z"
-  generation: 9
-  name: ray-test-cluster-1-pg
-  namespace: test
-  ownerReferences:
-  - apiVersion: ray.io/v1alpha1
-    blockOwnerDeletion: true
-    controller: true
-    kind: RayCluster
-    name: test-cluster-1
-    uid: b3cf83dc-ef3a-4bb1-9c42-7d2a39c53358
-  resourceVersion: "4428864"
-  uid: 9087dd08-8f48-4592-a62e-21e9345b0872
-spec:
-  minMember: 3
-  minResources:
-    cpu: "3"
-    memory: 4Gi
-  queue: kuberay-test-queue
-status:
-  conditions:
-  - lastTransitionTime: "2022-12-01T04:54:04Z"
-    message: '3/3 tasks in gang unschedulable: pod group is not ready, 3 Pending,
-      3 minAvailable; Pending: 3 Undetermined'
-    reason: NotEnoughResources
-    status: "True"
-    transitionID: db90bbf0-6845-441b-8992-d0e85f78db77
-    type: Unschedulable
-  - lastTransitionTime: "2022-12-01T04:55:10Z"
-    reason: tasks in gang are ready to be scheduled
-    status: "True"
-    transitionID: 72bbf1b3-d501-4528-a59d-479504f3eaf5
-    type: Scheduled
-  phase: Running
-  running: 2
+```shell
+kubectl get podgroup ray-test-cluster-1-pg -o yaml
+
+# apiVersion: scheduling.volcano.sh/v1beta1
+# kind: PodGroup
+# metadata:
+#   creationTimestamp: "2022-12-01T04:48:18Z"
+#   generation: 9
+#   name: ray-test-cluster-1-pg
+#   namespace: test
+#   ownerReferences:
+#   - apiVersion: ray.io/v1alpha1
+#     blockOwnerDeletion: true
+#     controller: true
+#     kind: RayCluster
+#     name: test-cluster-1
+#     uid: b3cf83dc-ef3a-4bb1-9c42-7d2a39c53358
+#   resourceVersion: "4428864"
+#   uid: 9087dd08-8f48-4592-a62e-21e9345b0872
+# spec:
+#   minMember: 3
+#   minResources:
+#     cpu: "3"
+#     memory: 4Gi
+#   queue: kuberay-test-queue
+# status:
+#   conditions:
+#   - lastTransitionTime: "2022-12-01T04:54:04Z"
+#     message: '3/3 tasks in gang unschedulable: pod group is not ready, 3 Pending,
+#       3 minAvailable; Pending: 3 Undetermined'
+#     reason: NotEnoughResources
+#     status: "True"
+#     transitionID: db90bbf0-6845-441b-8992-d0e85f78db77
+#     type: Unschedulable
+#   - lastTransitionTime: "2022-12-01T04:55:10Z"
+#     reason: tasks in gang are ready to be scheduled
+#     status: "True"
+#     transitionID: 72bbf1b3-d501-4528-a59d-479504f3eaf5
+#     type: Scheduled
+#   phase: Running
+#   running: 3
 ```
 
 Checking the pods again, we see that the second cluster is now up and running:
 
-```
-$ kubectl get pods
+```shell
+kubectl get pods
 
-NAME                                            READY   STATUS         RESTARTS   AGE
-test-cluster-1-worker-worker-n5g8k              1/1     Running        0          9m4s
-test-cluster-1-head-6668q                       1/1     Running        0          9m4s
-test-cluster-1-worker-worker-6tzf7              1/1     Running        0          9m4s
+# NAME                                            READY   STATUS         RESTARTS   AGE
+# test-cluster-1-worker-worker-n5g8k              1/1     Running        0          9m4s
+# test-cluster-1-head-6668q                       1/1     Running        0          9m4s
+# test-cluster-1-worker-worker-6tzf7              1/1     Running        0          9m4s
 ```
 
-Finally, we'll cleanup the remaining cluster and queue:
+Finally, we'll clean up the remaining cluster and queue:
 
-```
-$ kubectl delete raycluster test-cluster-1
-$ kubectl delete queue kuberay-test-queue
+```shell
+kubectl delete raycluster test-cluster-1
+kubectl delete queue kuberay-test-queue
 ```
 
 ## Questions
diff --git a/ray-operator/config/samples/ray-cluster.volcano-scheduler-queue.yaml b/ray-operator/config/samples/ray-cluster.volcano-scheduler-queue.yaml
new file mode 100644
index 0000000000..902a90b390
--- /dev/null
+++ b/ray-operator/config/samples/ray-cluster.volcano-scheduler-queue.yaml
@@ -0,0 +1,42 @@
+apiVersion: ray.io/v1alpha1
+kind: RayCluster
+metadata:
+  name: test-cluster-0
+  labels:
+    ray.io/scheduler-name: volcano
+    volcano.sh/queue-name: kuberay-test-queue
+spec:
+  rayVersion: '2.6.3'
+  headGroupSpec:
+    rayStartParams: {}
+    replicas: 1
+    template:
+      spec:
+        containers:
+        - name: ray-head
+          image: rayproject/ray:2.6.3
+          resources:
+            limits:
+              cpu: "1"
+              memory: "2Gi"
+            requests:
+              cpu: "1"
+              memory: "2Gi"
+  workerGroupSpecs:
+    - groupName: worker
+      rayStartParams: {}
+      replicas: 2
+      minReplicas: 2
+      maxReplicas: 2
+      template:
+        spec:
+          containers:
+          - name: ray-head
+            image: rayproject/ray:2.6.3
+            resources:
+              limits:
+                cpu: "1"
+                memory: "1Gi"
+              requests:
+                cpu: "1"
+                memory: "1Gi"
\ No newline at end of file
diff --git a/ray-operator/config/samples/ray-cluster.volcano-scheduler.yaml b/ray-operator/config/samples/ray-cluster.volcano-scheduler.yaml
new file mode 100644
index 0000000000..e7b7e9ae03
--- /dev/null
+++ b/ray-operator/config/samples/ray-cluster.volcano-scheduler.yaml
@@ -0,0 +1,24 @@
+apiVersion: ray.io/v1alpha1
+kind: RayCluster
+metadata:
+  name: test-cluster-0
+  labels:
+    ray.io/scheduler-name: volcano
+spec:
+  rayVersion: '2.6.3'
+  headGroupSpec:
+    rayStartParams: {}
+    replicas: 1
+    template:
+      spec:
+        containers:
+        - name: ray-head
+          image: rayproject/ray:2.6.3
+          resources:
+            limits:
+              cpu: "1"
+              memory: "2Gi"
+            requests:
+              cpu: "1"
+              memory: "2Gi"
+  workerGroupSpecs: []
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