Set up a GCP Project

Follow these steps to set up your GCP project:

1. Select or create a project on the GCP Console.

2. Make sure that you have the owner role for the project. The deployment process creates various service accounts with appropriate roles in order to enable seamless integration with GCP services. This process requires that you have the owner role for the project in order to deploy Kubeflow.

3. Make sure that billing is enabled for your project. See the guide to modifying a project’s billing settings.

4. Go to the following pages on the GCP Console and ensure that the specified APIs are enabled:

   • Compute Engine API
   • Kubernetes Engine API
   • Identity and Access Management (IAM) API
   • Deployment Manager API
   • Cloud Resource Manager API
   • Cloud Filestore API
   • AI Platform Training & Prediction API
   • Cloud Build API (It’s required if you plan to use Fairing in your Kubeflow cluster)

5. If you are using the GCP Free Tier or the 12-month trial period with $300 credit, note that you can’t run the default GCP installation of Kubeflow, because the free tier does not offer enough resources. You need to upgrade to a paid account.

   For more information, see the following issues:

   • kubeflow/website #1065 reports the problem.
   • kubeflow/kubeflow #3936 requests a Kubeflow configuration to work with a free trial project.

6. Read the GCP guide to resource quotas to understand the quotas on resource usage that Compute Engine enforces, and to learn how to check your quota and how to request an increase in quota.

You do not need a running GKE cluster. The deployment process creates a cluster for you.

Next steps

• Set up an OAuth credential if you want to use Cloud Identity-Aware Proxy (Cloud IAP). Cloud IAP is recommended for production deployments or deployments with access to sensitive data. You can skip this step if you want to test Kubeflow in a non-production environment.

• Choose one of the following ways to deploy Kubeflow:

  • Using the UI. This option provides a simple way to deploy Kubeflow.
  • Using the CLI. This option provides more control over the deployment process.

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