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https://github.com/vale981/ray
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a70ada7341
Implements a landing page for the new KubeRay-based deployment guide. Implements a "Getting started" Jupyter notebook
40 lines
1.5 KiB
Markdown
40 lines
1.5 KiB
Markdown
# Ray on Kubernetes
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(kuberay-index)=
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## Overview
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You can execute your distributed Ray programs on a Kubernetes cluster.
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The [KubeRay Operator](https://ray-project.github.io/kuberay/components/operator/) provides a Kubernetes-native
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interface for managing Ray clusters. Each Ray cluster consist of a head pod and collection of worker pods.
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Optional autoscaling support allows the KubeRay Operator to size your Ray clusters according to the requirements
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of your Ray workload, adding and removing Ray pods as needed.
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## Learn More
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The Ray docs present all the information you need to start running Ray workloads on Kubernetes.
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```{eval-rst}
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.. panels::
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:container: text-center
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:column: col-lg-12 p-2
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:card:
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**Getting started**
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^^^
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Learn how to start a Ray cluster and deploy Ray applications on Kubernetes.
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+++
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.. link-button:: kuberay-quickstart
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:type: ref
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:text: Get Started with Ray on Kubernetes
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:classes: btn-outline-info btn-block
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```
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## The KubeRay project
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Ray's Kubernetes support is developed at the [KubeRay GitHub repository](https://github.com/ray-project/kuberay), under the broader [Ray project](https://github.com/ray-project/).
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- Visit the [KubeRay GitHub repo](https://github.com/ray-project/kuberay) to track progress, report bugs, propose new features, or contribute to
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the project.
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- Check out the [KubeRay docs](https://ray-project.github.io/kuberay/) for further technical information, developer guides,
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and discussion of new and upcoming features.
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