1. Enabling APIs for AI Platform Pipelines with GCP Service Usage.


    Enabling APIs is a crucial first step when working with Google Cloud Platform (GCP) services, as this allows your applications to interact with Google Cloud resources. In this specific context, you want to enable APIs for AI Platform Pipelines, a service offered by GCP to deploy robust, repeatable machine learning pipelines.

    To enable APIs for AI Platform Pipelines, you'll use the GCP Service Usage API. The Service Usage API gives you access to service enablement and quota management for all Google Cloud services.

    In the following Pulumi program, you'll see how to use Pulumi's GCP provider to programmatically enable the AI Platform Pipelines API on your GCP project.

    The key resource used here is gcp.serviceusage.Service, which is responsible for enabling the specific API on the Google Cloud project. You'll need to specify the service name that corresponds to AI Platform Pipelines, which is aiplatform.googleapis.com, and provide the project ID where this service should be enabled.

    Here's a Pulumi program that does exactly that:

    import pulumi from pulumi_gcp import serviceusage # Replace 'your-gcp-project-id' with your actual GCP project ID. project_id = 'your-gcp-project-id' # Enable AI Platform Pipelines API using the GCP Service Usage API. ai_platform_pipelines_api = serviceusage.Service( "ai-platform-pipelines-api", service="aiplatform.googleapis.com", project=project_id, ) # Export the name of the API that was enabled. pulumi.export('ai_platform_pipelines_api', ai_platform_pipelines_api.service)

    Before running this program, ensure you have authenticated with GCP using the gcloud CLI and set up the Pulumi environment for your GCP project.

    The program begins by importing the necessary modules: pulumi for the overall Pulumi context and pulumi_gcp.serviceusage for interacting with the GCP Service Usage API.

    We then define a serviceusage.Service resource named ai_platform_pipelines_api. The service argument takes the API identifier, and the project argument is your project ID, which informs GCP where to enable the API.

    Finally, we export the name of the service using pulumi.export, making it easy to verify that the correct API has been enabled after the program is applied. When you run this Pulumi program, it will reach out to GCP and enable the AI Platform Pipelines API if it is not already enabled. If it is already enabled, Pulumi will simply recognize this and not make any changes.

    To run this Pulumi program, save it to a file with a .py extension, navigate to the directory containing the file in the command-line interface, and execute the following commands:

    # Initialize a new Pulumi stack if you haven't already done so pulumi stack init dev # Install the necessary GCP plugin for Pulumi pulumi plugin install resource gcp v6.67.0 # Set the GCP project and region as required configuration for your stack pulumi config set gcp:project your-gcp-project-id pulumi config set gcp:region your-gcp-region # For example, `us-central1` # Run the Pulumi program to deploy the infrastructure pulumi up

    When the deployment is complete, you will see the output with the name of the enabled API, confirming that the AI Platform Pipelines API is ready for use in your GCP project.