1. Securing ML API Access with GCP IAP


    To secure ML API access on Google Cloud Platform (GCP) using Identity-Aware Proxy (IAP), you need to set up IAP to control access to the ML API. IAP works by verifying a user's identity and ensuring they have the right permission to access your API.

    Here is a high-level overview and the subsequent Pulumi program in Python to demonstrate how to:

    • Create an OAuth2 client ID to use with IAP.
    • Set up an IAP brand, which represents an application that can be protected by IAP.
    • Create an IAP client which you'll use to authenticate programmatic requests.
    • Apply IAM policies to the IAP-secured resource, providing fine-grained access control.

    Before running this Pulumi program, make sure you have authenticated with the GCP provider.

    The resources we're going to use from the Pulumi GCP SDK include:

    • gcp.iap.Brand: This resource represents a brand within Identity-Aware Proxy, which allows you to configure the appearance of the login page and manage OAuth client information that's needed to secure your application.
    • gcp.iap.Client: Represents a client application that needs to authenticate against the brand when accessing an IAP-secured resource.
    • gcp.iap.WebIamBinding, gcp.iap.WebIamMember or gcp.iap.WebIamPolicy: These resources manage IAM roles and permissions for IAP-secured web applications or APIs.

    Let's go step by step to secure an example ML API service.

    import pulumi import pulumi_gcp as gcp # The project ID is typically provided by the `gcp.config.project` when # configuring the GCP provider, but can also be specified explicitly if needed. project_id = 'your-gcp-project-id' # Replace 'your-email@example.com' with the email that will manage OAuth2 client support_email = 'your-email@example.com' # Create an IAP brand for the project. # The brand is what users see on the login page that IAP directs them to # when accessing your application. iap_brand = gcp.iap.Brand("iapBrand", support_email=support_email, project=project_id, application_title="My ML API" ) # Create an OAuth2 client to use with IAP for programmatic access. # This client will be used to authenticate requests to your ML API. iap_client = gcp.iap.Client("iapClient", brand=iap_brand.name, display_name="ML API Client" ) # Output the client ID and secret, which are needed to authenticate against the IAP-secured resource. # IMPORTANT: These values should be treated as sensitive and managed securely. pulumi.export('iap_client_id', iap_client.client_id) pulumi.export('iap_client_secret', iap_client.secret) # Assuming you have an ML API set up and secured by IAP, # you can use WebIamBinding, WebIamMember, or WebIamPolicy to # manage access at a granular level. For example, to allow a specific user # access to the ML API, you'd set up a WebIamMember as follows: # Specify the email of the user or service account for which you want to allow access. member_email = "user:example-user@example.com" # Bind the IAP-secured-web-app-user role to the specified member. # This allows the user to access the IAP-secured resource. iap_web_iam_member = gcp.iap.WebIamMember("iapWebIamMember", project=project_id, role="roles/iap.httpsResourceAccessor", member=member_email ) # Outputs the email of the IAM member with access to the IAP-secured resource. pulumi.export('iam_member_email', iap_web_iam_member.member)

    To run this Pulumi program, save it as main.py, and ensure you've installed both Pulumi CLI and Pulumi GCP SDK. Then, run pulumi up to provision the resources defined in the program.

    In the exports at the end of the program, iap_client_id and iap_client_secret are the credentials you'll use to authenticate API requests to your ML API protected by IAP. The iam_member_email export shows the user who has been granted access to the IAP-secured API. Make sure to handle iap_client_secret with care and treat it as you would any password or secret key.

    This is a basic setup for securing access to an ML API. Depending on the actual application or service being secured, there might be additional steps such as adding domain verification for the brand. Always be sure to review the permissions to ensure they adhere to the principle of least privilege.