doc/source/cluster/kubernetes/examples/text-summarizer-rayservice.md
(kuberay-text-summarizer-rayservice-example)=
Note: The Python files for the Ray Serve application and its client are in the ray-project/serve_config_examples repository.
See aws-eks-gpu-cluster.md or gcp-gke-gpu-cluster.md or ack-gpu-cluster.md to create a Kubernetes cluster with 1 CPU node and 1 GPU node.
Follow this document to install the latest stable KubeRay operator using the Helm repository.
# Create a RayService
kubectl apply -f https://raw.githubusercontent.com/ray-project/kuberay/master/ray-operator/config/samples/ray-service.text-summarizer.yaml
tolerations. Meanwhile, the worker Pods use the following tolerations so the scheduler won't assign the head Pod to the GPU node.
# Please add the following taints to the GPU node.
tolerations:
- key: "ray.io/node-type"
operator: "Equal"
value: "worker"
effect: "NoSchedule"
# Step 4.1: Wait until the RayService is ready to serve requests.
kubectl describe rayservices text-summarizer
# Step 4.2: Get the service name.
kubectl get services
# [Example output]
# text-summarizer-head-svc ClusterIP None <none> 10001/TCP,8265/TCP,6379/TCP,8080/TCP,8000/TCP 31s
# text-summarizer-raycluster-tb9zf-head-svc ClusterIP None <none> 10001/TCP,8265/TCP,6379/TCP,8080/TCP,8000/TCP 108s
# text-summarizer-serve-svc ClusterIP 34.118.226.139 <none> 8000/TCP 31s
# Step 4.3: Forward the port of Serve.
kubectl port-forward svc/text-summarizer-serve-svc 8000
# Step 5.1: Download `text_summarizer_req.py`
curl -LO https://raw.githubusercontent.com/ray-project/serve_config_examples/master/text_summarizer/text_summarizer_req.py
# Step 5.2: Send a request to the Summarizer model.
python text_summarizer_req.py
# Check printed to console
kubectl delete -f https://raw.githubusercontent.com/ray-project/kuberay/master/ray-operator/config/samples/ray-service.text-summarizer.yaml
Follow this document to uninstall the latest stable KubeRay operator using the Helm repository.