Launching Ray Clusters on GCP¶
This guide details the steps needed to start a Ray cluster in GCP.
To start a GCP Ray cluster, you will use the Ray cluster launcher with the Google API client.
Install Ray cluster launcher¶
The Ray cluster launcher is part of the
ray CLI. Use the CLI to start, stop and attach to a running ray cluster using commands such as
ray down and
ray attach. You can use pip to install the ray CLI with cluster launcher support. Follow the Ray installation documentation for more detailed instructions.
# install ray pip install -U ray[default]
Install and Configure Google API Client¶
If you have never created a Google APIs Console project, read google Cloud’s Managing Projects page and create a project in the Google API Console.
Next, install the Google API Client using
pip install -U google-api-python-client.
# Install the Google API Client. pip install google-api-python-client
Start Ray with the Ray cluster launcher¶
Once the Google API client is configured to manage resources on your GCP account, you should be ready to launch your cluster. The provided cluster config file will create a small cluster with an on-demand n1-standard-2 head node and is configured to autoscale to up to two n1-standard-2 preemptible workers. Note that you’ll need to fill in your GCP project_id in those templates.
Test that it works by running the following commands from your local machine:
# Download the example-full.yaml wget https://github.com/ray-project/ray/blob/master/python/ray/autoscaler/gcp/example-full.yaml # Edit the example-full.yaml to update project_id. # vi example-full.yaml # Create or update the cluster. When the command finishes, it will print # out the command that can be used to SSH into the cluster head node. ray up example-full.yaml # Get a remote screen on the head node. ray attach example-full.yaml # Try running a Ray program. python -c 'import ray; ray.init()' exit # Tear down the cluster. ray down example-full.yaml
Congrats, you have started a Ray cluster on GCP!