[doc] Add Anyscale as an option to get started with Ray (ray-project#…

…50772)

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## Why are these changes needed?

<!-- Please give a short summary of the change and the problem this
solves. -->
Adding Anyscale as an option to get started with Ray. This is the first
round of changes to add the option to 3 pages.

## Related issue number

<!-- For example: "Closes ray-project#1234" -->

## Checks

- [x] I've signed off every commit(by using the -s flag, i.e., `git
commit -s`) in this PR.
- [x] I've run `scripts/format.sh` to lint the changes in this PR.
- [ ] I've included any doc changes needed for
https://docs.ray.io/en/master/.
- [ ] I've added any new APIs to the API Reference. For example, if I
added a
method in Tune, I've added it in `doc/source/tune/api/` under the
           corresponding `.rst` file.
- [ ] I've made sure the tests are passing. Note that there might be a
few flaky tests, see the recent failures at https://flakey-tests.ray.io/
- Testing Strategy
   - [ ] Unit tests
   - [ ] Release tests
   - [ ] This PR is not tested :(

---------

Signed-off-by: Sijie Wang <3463757+sijieamoy@users.noreply.github.com>
Co-authored-by: angelinalg <122562471+angelinalg@users.noreply.github.com>

doc/source/_static/css/custom.css

@@ -401,3 +401,8 @@ table.autosummary tr > td:first-child > p > a > code > span {
 readthedocs-flyout {
   display: none !important;
 }
+
+/* Styling the experimental Anyscale upsell CTA */
+.anyscale-cta {
+  margin-bottom: 16px;
+}

doc/source/cluster/getting-started.rst

@@ -32,6 +32,7 @@ Ray provides native cluster deployment support on the following technology stack
 
 * On :ref:`AWS and GCP <cloud-vm-index>`. Community-supported Azure, Aliyun and vSphere integrations also exist.
 * On :ref:`Kubernetes <kuberay-index>`, via the officially supported KubeRay project.
+* On `Anyscale <https://www.anyscale.com/ray-on-anyscale?utm_source=ray_docs&utm_medium=docs&utm_campaign=ray-doc-upsell&utm_content=ray-cluster-deployment>`_, a fully managed Ray platform by the creators of Ray. You can either bring an existing AWS, GCP, Azure and Kubernetes clusters, or use the Anyscale hosted compute layer.
 
 Advanced users may want to :ref:`deploy Ray manually <on-prem>`
 or onto :ref:`platforms not listed here <ref-cluster-setup>`.

doc/source/cluster/kubernetes/index.md

@@ -41,6 +41,8 @@ See [Getting Started](kuberay-quickstart) to learn the basics of KubeRay and fol
 * [RayJob Quick Start](kuberay-rayjob-quickstart)
 * [RayService Quick Start](kuberay-rayservice-quickstart)
 
+Additionally, [Anyscale](https://www.anyscale.com/ray-on-anyscale?utm_source=ray_docs&utm_medium=docs&utm_campaign=ray-doc-upsell&utm_content=deploy-ray-on-k8s) is the managed Ray platform developed by the creators of Ray. It offers an easy path to deploy Ray clusters on your existing Kubernetes infrastructure, including EKS, GEK, AKS, or self-hosted Kubernetes.
+
 ## Learn More
 
 The Ray docs present all the information you need to start running Ray workloads on Kubernetes.

doc/source/ray-overview/getting-started.md

@@ -135,8 +135,18 @@ with 4 workers, and use it to run the new training function.
 :end-before: __torch_trainer_end__
 :dedent: 4
 ```
+
+To accelerate the training job using GPU, make sure you have GPU configured, then set `use_gpu` to `True`. If you don't have a GPU environment, Anyscale provides a development workspace integrated with an autoscaling GPU cluster for this purpose.
+
+<div class="anyscale-cta">
+    <a href="https://www.anyscale.com/ray-on-anyscale?utm_source=ray_docs&utm_medium=docs&utm_campaign=ray-doc-upsell&utm_content=get-started-train-torch">
+        <img src="../_static/img/try-ray-on-anyscale.svg" alt="Try Ray on Anyscale">
+    </a>
+</div>
+
 ````
 
+
 ````{tab-item} TensorFlow
 
 This example shows how you can use Ray Train to set up [Multi-worker training
@@ -198,6 +208,14 @@ with 4 workers, and use it to run the new training function.
 :dedent: 0
 ```
 
+To accelerate the training job using GPU, make sure you have GPU configured, then set `use_gpu` to `True`. If you don't have a GPU environment, Anyscale provides a development workspace integrated with an autoscaling GPU cluster for this purpose.
+
+<div class="anyscale-cta">
+    <a href="https://www.anyscale.com/ray-on-anyscale?utm_source=ray_docs&utm_medium=docs&utm_campaign=ray-doc-upsell&utm_content=get-started-train-tf">
+        <img src="../_static/img/try-ray-on-anyscale.svg" alt="Try Ray on Anyscale">
+    </a>
+</div>
+
 ```{button-ref}  ../train/train
 :color: primary
 :outline:
@@ -604,6 +622,21 @@ Learn more about launching Ray Clusters on Kubernetes
 
 `````
 
+`````{dropdown} <img src="images/ray_svg_logo.svg" alt="ray" width="50px"> Clusters: Launching a Ray Cluster on Anyscale 
+:animate: fade-in-slide-down
+
+Anyscale is the company behind Ray. The Anyscale platform provides an enterprise-grade Ray deployment on top of your AWS, GCP, Azure, or on-prem Kubernetes clusters.
+
+```{button-link} https://www.anyscale.com/ray-on-anyscale?utm_source=ray_docs&utm_medium=docs&utm_campaign=ray-doc-upsell&utm_content=get-started-launch-ray-cluster
+:color: primary
+:outline:
+:expand:
+
+Try Ray on Anyscale
+```
+
+`````
+
 ## Debugging and Monitoring Quickstart
 
 Use built-in observability tools to monitor and debug Ray applications and clusters.