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new 293b7b12e3 [YUNIKORN-2894] Update KubeRay operator documentation for
YuniKorn integration (#489)
293b7b12e3 is described below
commit 293b7b12e33e35732c50d3486fac3f7d81b881d1
Author: Ryan <[email protected]>
AuthorDate: Thu Oct 24 12:34:46 2024 -0500
[YUNIKORN-2894] Update KubeRay operator documentation for YuniKorn
integration (#489)
Closes: #489
Signed-off-by: Craig Condit <[email protected]>
---
.../user_guide/workloads/kuberay/_ray_operator.mdx | 2 +-
docs/user_guide/workloads/run_ray_cluster.md | 133 +++++++++++++++++++--
2 files changed, 126 insertions(+), 9 deletions(-)
diff --git a/docs/user_guide/workloads/kuberay/_ray_operator.mdx
b/docs/user_guide/workloads/kuberay/_ray_operator.mdx
index 55d81b3ba1..c6664ba9fe 100644
--- a/docs/user_guide/workloads/kuberay/_ray_operator.mdx
+++ b/docs/user_guide/workloads/kuberay/_ray_operator.mdx
@@ -2,7 +2,7 @@
```
helm repo add kuberay https://ray-project.github.io/kuberay-helm/
helm repo update
-helm install kuberay-operator kuberay/kuberay-operator --version 1.1.1
+helm install kuberay-operator kuberay/kuberay-operator --version 1.2.2 --set
batchScheduler.name=yunikorn
```
- The result should be as shown below
diff --git a/docs/user_guide/workloads/run_ray_cluster.md
b/docs/user_guide/workloads/run_ray_cluster.md
index edae78fec1..ef57e4a9ac 100644
--- a/docs/user_guide/workloads/run_ray_cluster.md
+++ b/docs/user_guide/workloads/run_ray_cluster.md
@@ -29,23 +29,138 @@ specific language governing permissions and limitations
under the License.
-->
-:::info[Note]
-This example demonstrates how to set up
[KubeRay](https://docs.ray.io/en/master/cluster/kubernetes/getting-started.html)
and run a
[RayCluster](https://docs.ray.io/en/master/cluster/kubernetes/getting-started/raycluster-quick-start.html)
with the YuniKorn scheduler. It relies on an admission controller to configure
the default applicationId and queue name. If you want more details, please
refer to [Yunikorn supported
labels](https://yunikorn.apache.org/docs/user_guide/labels_and_annotati [...]
+:::note
+This example demonstrates how to set up
[KubeRay](https://docs.ray.io/en/master/cluster/kubernetes/getting-started.html)
and run a
[RayCluster](https://docs.ray.io/en/master/cluster/kubernetes/getting-started/raycluster-quick-start.html)
with the YuniKorn scheduler. Here're the pre-requisites:
+- This tutorial assumes YuniKorn is
[installed](../../get_started/get_started.md) under the namespace `yunikorn`
+- Use kube-ray version >= 1.2.2 to enable support for YuniKorn gang scheduling
:::
-<YunikornConfigMapPatch />
+## Install YuniKorn
+
+A simple script to install YuniKorn under the namespace `yunikorn`, refer to
[Get Started](../../get_started/get_started.md) for more details.
+
+```shell script
+helm repo add yunikorn https://apache.github.io/yunikorn-release
+helm repo update
+helm install yunikorn yunikorn/yunikorn --create-namespace --namespace yunikorn
+```
+
<RayOperator/>
-## Create RayCluster
+## Create RayCluster with YuniKorn
+
+In the example, we set the `ray.io/gang-scheduling-enabled` label to `true` to
enable gang scheduling.
+
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+<Tabs>
+<TabItem value="amd64" label="x86-64 (Intel/Linux)">
+
+```yaml
+cat <<EOF | kubectl apply -f -
+apiVersion: ray.io/v1
+kind: RayCluster
+metadata:
+ name: test-yunikorn-0
+ labels:
+ ray.io/gang-scheduling-enabled: "true"
+ yunikorn.apache.org/app-id: test-yunikorn-0
+ yunikorn.apache.org/queue: root.default
+spec:
+ rayVersion: "2.9.0"
+ headGroupSpec:
+ rayStartParams: {}
+ template:
+ spec:
+ containers:
+ - name: ray-head
+ image: rayproject/ray:2.9.0
+ 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:2.9.0
+ resources:
+ limits:
+ cpu: "1"
+ memory: "1Gi"
+ requests:
+ cpu: "1"
+ memory: "1Gi"
+EOF
```
-helm install raycluster kuberay/ray-cluster --version 1.1.1
+
+</TabItem>
+<TabItem value="aarch64" label="Apple Silicon(arm64)">
+
+```yaml
+cat <<EOF | kubectl apply -f -
+apiVersion: ray.io/v1
+kind: RayCluster
+metadata:
+ name: test-yunikorn-0
+ labels:
+ ray.io/gang-scheduling-enabled: "true"
+ yunikorn.apache.org/app-id: test-yunikorn-0
+ yunikorn.apache.org/queue: root.default
+spec:
+ rayVersion: "2.9.0"
+ headGroupSpec:
+ rayStartParams: {}
+ template:
+ spec:
+ containers:
+ - name: ray-head
+ image: rayproject/ray:2.9.0-aarch64
+ 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:2.9.0-aarch64
+ resources:
+ limits:
+ cpu: "1"
+ memory: "1Gi"
+ requests:
+ cpu: "1"
+ memory: "1Gi"
+EOF
```
+
+</TabItem>
+</Tabs>
+
- RayCluster result
- YuniKorn UI
-
-<RayCRDYunikornConfig />
## Submit a RayJob to RayCluster
```
@@ -57,10 +172,12 @@ kubectl exec -it $HEAD_POD -- python -c "import ray;
ray.init(); print(ray.clust
Services in Kubernetes aren't directly accessible by default. However, you can
use port-forwarding to connect to them locally.
```
-kubectl port-forward service/raycluster-kuberay-head-svc 8265:8265
+kubectl port-forward service/test-yunikorn-0-head-svc 8265:8265
```
After port-forward set up, you can access the Ray dashboard by going to
`http://localhost:8265` in your web browser.
- Ray Dashboard
+Have doubts? Check out the [KubeRay integration with Apache
YuniKorn](https://docs.ray.io/en/master/cluster/kubernetes/k8s-ecosystem/yunikorn.html)
official documents.
+
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