Example RayCluster spec with Labels and label_selector API (#4136)

* Add label selector example yaml

Signed-off-by: Ryan O'Leary <[email protected]>

* Refactor yaml

Signed-off-by: Ryan O'Leary <[email protected]>

---------

Signed-off-by: Ryan O'Leary <[email protected]>

Author: ryanaoleary

ray-operator/config/samples/ray-cluster-label-selector.yaml

@@ -0,0 +1,161 @@
+apiVersion: ray.io/v1
+kind: RayCluster
+metadata:
+  name: ray-label-cluster
+spec:
+  enableInTreeAutoscaling: true
+  autoscalerOptions:
+    version: v2
+    upscalingMode: Default
+    idleTimeoutSeconds: 600
+    imagePullPolicy: Always
+    securityContext: {}
+    env: []
+    envFrom: []
+    resources:
+      limits:
+        cpu: "500m"
+        memory: "512Mi"
+      requests:
+        cpu: "500m"
+        memory: "512Mi"
+  headGroupSpec:
+    labels:
+      ray.io/region: us-central2
+    resources:
+      cpu: "0"
+    template:
+      spec:
+        containers:
+        - name: ray-head
+          image: rayproject/ray:nightly
+          ports:
+          - containerPort: 6379
+            name: gcs
+          - containerPort: 8265
+            name: dashboard
+          - containerPort: 10001
+            name: client
+          resources:
+            limits:
+              cpu: "1"
+              memory: "2G"
+            requests:
+              cpu: "1"
+              memory: "2G"
+          volumeMounts:
+          - mountPath: /home/ray/samples
+            name: ray-example-configmap
+        volumes:
+        - name: ray-example-configmap
+          configMap:
+            name: ray-example
+            defaultMode: 0777
+            items:
+            - key: example_task.py
+              path: example_task.py
+            - key: example_actor.py
+              path: example_actor.py
+            - key: example_placement_group.py
+              path: example_placement_group.py
+  workerGroupSpecs:
+  - replicas: 1
+    minReplicas: 1
+    maxReplicas: 10
+    groupName: large-cpu-group
+    labels:
+      cpu-family: intel
+      ray.io/market-type: on-demand
+    rayStartParams: {}
+    template:
+      spec:
+        containers:
+        - name: ray-worker
+          image: rayproject/ray:nightly
+          resources:
+            limits:
+              cpu: "2"
+              memory: "4G"
+            requests:
+              cpu: "2"
+              memory: "4G"
+        nodeSelector:
+          cloud.google.com/machine-family: "N4"
+  - replicas: 0
+    minReplicas: 0
+    maxReplicas: 10
+    groupName: accelerator-group
+    labels:
+      ray.io/market-type: on-demand
+      ray.io/region: us-central2
+    rayStartParams: {}
+    template:
+      spec:
+        containers:
+        - name: ray-worker
+          image: rayproject/ray:nightly-gpu
+          resources:
+            limits:
+              cpu: "1"
+              nvidia.com/gpu: "1"
+              memory: "1G"
+            requests:
+              cpu: "1"
+              nvidia.com/gpu: "1"
+              memory: "1G"
+        nodeSelector:
+          cloud.google.com/gke-spot: "true"
+          cloud.google.com/gke-accelerator: "nvidia-tesla-a100"
+  - replicas: 0
+    minReplicas: 0
+    maxReplicas: 5
+    groupName: spot-group
+    labels:
+      cpu-family: amd
+      ray.io/market-type: spot
+    rayStartParams: {}
+    template:
+      spec:
+        containers:
+        - name: ray-worker
+          image: rayproject/ray:nightly
+          resources:
+            limits:
+              cpu: "1"
+              memory: "1G"
+            requests:
+              cpu: "1"
+              memory: "1G"
+        nodeSelector:
+          cloud.google.com/gke-spot: "true"
+---
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: ray-example
+data:
+  example_task.py: |
+    import ray
+    @ray.remote(num_cpus=1, label_selector={"ray.io/market-type": "on-demand", "cpu-family": "in(intel,amd)"})
+    def test_task():
+      pass
+    ray.init()
+    ray.get(test_task.remote())
+  example_actor.py: |
+    import ray
+    @ray.remote(num_gpus=1, label_selector={"ray.io/accelerator-type": "A100"})
+    class Actor:
+      def ready(self):
+        return True
+    ray.init()
+    my_actor = Actor.remote()
+    ray.get(my_actor.ready.remote())
+  example_placement_group.py: |
+    import ray
+    from ray.util.placement_group import placement_group
+    ray.init()
+    pg = placement_group(
+      [{"CPU": 1}] * 2,
+      bundle_label_selector=[{"ray.io/market-type": "spot", "ray.io/region": "!us-central2"},] * 2, strategy="SPREAD"
+    )
+    ray.get(pg.ready())