Setting up Google Cloud Compute¶
This page describes the process of setting up Google Cloud and configuring Studio to integrate with it.
Configuring Google Cloud Compute¶
Create and select a new Google Cloud project¶
Go to the Google Cloud console (https://console.cloud.google.com), and either choose a project that you will use to back cloud computing or create a new one. If you have not used the Google console before and there are no projects, there will be a big button “create project” in the dashboard. Otherwise, you can create a new project by selecting the drop-down arrow next to current project name in the top panel, and then clicking the “+” button.
Enable billing for the project¶
Google Cloud computing actually bills you for the compute time you use, so you must have billing enabled. On the bright side, when you sign up with Google Cloud they provide $300 of promotional credit, so really in the beginning you are still using it for free. On the not so bright side, to use machines with gpus you’ll need to show that you are a legitimate customer and add $35 to your billing account. In order to enable billing, go to the left-hand pane in the Google Cloud console, select billing, and follow the instructions to set up your payment method.
Generate service credentials¶
The machines that submit cloud jobs will need to be authorized with service credentials. Go to the left-hand pane in the Google Cloud console and select API Manager -> Credentials. Then click the “Create credentials” button, choose service account key, leave key type as JSON, and in the “Service account” drop-down select “New service account”. Enter a service account name (the name can be virtually anything and won’t matter for the rest of the instructions). The important part is selecting a role. Click the “Select a role” dropdown menu, in “Project” select “Service Account Actor”, and then scroll down to “Compute Engine” and select “Compute Engine Admin (v1)”. Then scroll down to “Pub/Sub”, and add a role “Pub/Sub editor” (this is required to create queues, publish and read messages from them). If you are planning to use Google Cloud storage (directly, without the Firebase layer) for artifact storage, select the Storage Admin role as well. You can also add other roles if you are planning to use these credentials in other applications. When done, click “Create”. Google Cloud console should generate a json credentials file and save it to your computer.
Copy the json file credentials to the machine where Studio will be
run, and create the environment variable
that points to it. That is, run
Note that this variable will be gone when you restart the terminal, so
if you want to reuse it, add it to
~/.bashrc (linux) or
~/.bash_profile (OS X)
Modifying the configuration file¶
In the config file (the one that you use with the
--config flag, or, if you
use the default, in the
studio/default_config.yaml), go to the
section. Change projectId to the project id of the Google project for which
you enabled cloud computing. You can also modify the default instance
parameters (see Cloud computing for studio for
To test if things are set up correctly, go to
studio/examples/general and run
studio run --cloud=gcloud report_system_info.py
studio locally, and watch the new experiment. In a little
while, it should change its status to “finished” and show the system
information (number of cpus, amount of ram / hdd) of a default instance.
See Cloud computing for studio for more instructions on
using an instance with specific hardware parameters.