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* update-cloud-docs Signed-off-by: Richard Liaw <rliaw@berkeley.edu> * Update doc/source/cluster/config.rst Co-authored-by: Ian Rodney <ian.rodney@gmail.com> * fix Signed-off-by: Richard Liaw <rliaw@berkeley.edu> * fix Signed-off-by: Richard Liaw <rliaw@berkeley.edu> Co-authored-by: Ian Rodney <ian.rodney@gmail.com>
66 lines
2.4 KiB
ReStructuredText
66 lines
2.4 KiB
ReStructuredText
.. _ref-automatic-cluster:
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Launching Cloud Clusters with Ray
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=================================
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Ray comes with a built-in cluster launcher that makes deploying a Ray cluster simple.
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The cluster launcher will provision resources from a node provider (like :ref:`AWS EC2 <ref-cloud-setup>` or :ref:`Kubernetes <ray-launch-k8s>`) to instantiate the specified cluster, and start a Ray cluster on the provisioned resources.
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You can configure the Ray Cluster Launcher to use with :ref:`a cloud provider <cluster-cloud>`, an existing :ref:`Kubernetes cluster <ray-launch-k8s>`, or a private cluster of machines.
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.. tabs::
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.. group-tab:: AWS
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.. code-block:: shell
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# First, run `pip install boto3` and `aws configure`
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#
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# Create or update the cluster. When the command finishes, it will print
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# out the command that can be used to SSH into the cluster head node.
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$ ray up ray/python/ray/autoscaler/aws/example-full.yaml
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See :ref:`the AWS section <ref-cloud-setup>` for full instructions.
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.. group-tab:: GCP
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.. code-block:: shell
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# First, ``pip install google-api-python-client``
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# set up your GCP credentials, and
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# create a new GCP project.
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#
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# Create or update the cluster. When the command finishes, it will print
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# out the command that can be used to SSH into the cluster head node.
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$ ray up ray/python/ray/autoscaler/gcp/example-full.yaml
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See :ref:`the GCP section <ref-cloud-setup>` for full instructions.
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.. group-tab:: Azure
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.. code-block:: shell
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# First, install the Azure CLI
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# ``pip install azure-cli azure-core``) then
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# login using (``az login``).
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#
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# Create or update the cluster. When the command finishes, it will print
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# out the command that can be used to SSH into the cluster head node.
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$ ray up ray/python/ray/autoscaler/azure/example-full.yaml
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See :ref:`the Azure section <ref-cloud-setup>` for full instructions.
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Once the Ray cluster is running, you can manually SSH into it or use provided commands like ``ray attach``, ``ray rsync-up``, and ``ray exec`` to access it and run Ray programs.
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.. toctree::
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/cluster/cloud.rst
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/cluster/config.rst
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/cluster/commands.rst
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Questions or Issues?
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--------------------
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.. include:: /_help.rst
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