ray/doc/source/cluster/getting-started.rst
Chen Shen ddca52d2ca
[cluster doc] Promote new doc and deprecate the old (#27759)
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
2022-08-10 17:41:56 -07:00

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2.6 KiB
ReStructuredText

.. include:: /_includes/clusters/announcement.rst
.. include:: /_includes/clusters/we_are_hiring.rst
.. _cluster-index-under-construction:
Ray Clusters Overview
=====================
What is a Ray cluster?
----------------------
One of Ray's strengths is the ability to leverage multiple machines for
distributed execution. Ray is great for multiprocessing on a single machine.
However, the real power of Ray is the ability to seamlessly scale to a cluster
of machines.
A Ray cluster is a set of one or more nodes that are running Ray and share the same :ref:`head node<cluster-head-node-under-construction>`.
Ray clusters can either be a fixed-size number of nodes or :ref:`can autoscale<cluster-autoscaler-under-construction>` (i.e., automatically provision or deprovision the number of nodes in a cluster) according to the demand of the Ray workload.
How can I use Ray clusters?
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Ray clusters are officially supported on the following technology stacks:
* The :ref:`Ray cluster launcher on AWS and GCP<ref-cluster-quick-start-vms-under-construction>`. Community-supported Azure and Aliyun integrations also exist.
* :ref:`KubeRay, the official way to run Ray on Kubernetes<kuberay-index>`.
Advanced users may want to :ref:`deploy Ray clusters on-premise <on-prem>`
or onto infrastructure platforms not listed here by :ref:`providing a custom node provider <ref-cluster-setup-under-construction>`.
Where to go from here?
----------------------
.. panels::
:container: text-center
:column: col-lg-6 px-3 py-2
:card:
**I want to learn key Ray cluster concepts**
^^^
Understand the key concepts and main ways of interacting with a Ray cluster.
+++
.. link-button:: cluster-key-concepts-under-construction
:type: ref
:text: Learn Key Concepts
:classes: btn-outline-info btn-block
---
**I want to run Ray on a cloud provider**
^^^
Take a sample application designed to run on a laptop and scale it up in the
cloud. Access to an AWS or GCP account is required.
+++
.. link-button:: ref-cluster-quick-start-vms-under-construction
:type: ref
:text: Getting Started with Ray Clusters on VMs
:classes: btn-outline-info btn-block
---
**I want to run Ray on Kubernetes**
^^^
Deploy a Ray application to a Kubernetes cluster. You can run the tutorial on a
remote Kubernetes cluster or on your laptop via KinD.
+++
.. link-button:: kuberay-quickstart
:type: ref
:text: Getting Started with Ray on Kubernetes
:classes: btn-outline-info btn-block
.. include:: /_includes/clusters/announcement_bottom.rst