1. Identity Federation for Multi-Cloud AI Services on OCI


    Identity Federation allows you to set up a single identity that can be recognized across multiple platforms or cloud services. For your goal of setting up Identity Federation for Multi-Cloud AI Services on Oracle Cloud Infrastructure (OCI), you would typically configure federated single sign-on using identity providers from different clouds along with setting up resources for your AI services.

    In the context of infrastructure as code with Pulumi and using OCI, you would work with resources such as oci.Identity.DomainsIdentityProvider to set up the federated identity providers, and possibly oci.AiVision.Project if you're using OCI AI Vision services.

    Below is a Pulumi Python program that illustrates how to set up a federated identity provider in OCI and an AI Vision project resource. Both these OCI services can work in tandem with other cloud providers toward a multi-cloud federation for AI services.

    The DomainsIdentityProvider resource configures federation with an external identity provider. For simplification, I'm showing a pseudo-implementation as in a real scenario, you'd need to provide details like metadata URL, SAML specifications, or other depending on your identity provider type.

    The AiVision.Project resource sets up an AI project in OCI, where you can organize and manage your AI workloads.

    import pulumi import pulumi_oci as oci # Configure federated single sign-on using an Identity Provider on OCI. # In a real-world scenario, you would provide actual values from your identity provider # and the specific protocol and parameters it requires (e.g. SAML, OAuth). federated_identity_provider = oci.Identity.DomainsIdentityProvider("my-domains-identity-provider", type="SAML2", metadata="<METADATA_FROM_IDENTITY_PROVIDER>", # Replace with actual metadata from your SAML IDP enabled=True, description="Example federated identity provider for Multi-Cloud AI services", nameIdFormat="urn:oasis:names:tc:SAML:1.1:nameid-format:emailAddress", # Example nameID format, adjust as needed logoutEnabled=True, display_name="MultiCloudAI-IDP" ) # Here we create an AI Vision project under OCI. # This is where you can manage your AI workloads within OCI. ai_vision_project = oci.AiVision.Project("my-ai-vision-project", display_name="MultiCloudAI-Vision", description="AI Vision project for federated multi-cloud services", compartment_id="YOUR_COMPARTMENT_ID" # Replace with compartment ID where you want to create the project ) # We output specific details about the created resources. # For the Identity Provider, one might be interested in the provider ID, # which could be used in automated configuration scripts or other integrations. pulumi.export("identity_provider_id", federated_identity_provider.id) # For the AI Vision Project, we're exporting the project ID # which could be referenced in applications using the AI services. pulumi.export("ai_vision_project_id", ai_vision_project.id)

    Explanation of Resources:

    1. DomainsIdentityProvider: Represents the identity provider in OCI that we are federating with. This is set using parameters like the type (just an example given for SAML2), metadata from the identity provider, and other settings like nameIdFormat and logoutEnabled which are specific to the federation protocol used.

    2. AiVision.Project: This resource creates a project for organizing AI workloads in OCI. A project in AI services is typically a way to group resources and manage access. The compartment_id is a unique identifier that specifies where in OCI you're organizing your resources.

    3. Exports: These lines make sure that the IDs of the created resources are made available outside of the Pulumi program, which can be useful for auditing, compliance, or integration with other systems.

    Please note that in real-world usage, additional parameters and setup may be required depending on the specifics of the identity provider and AI services you want to use. The metadata for the identity provider, for example, would be unique to your setup. The AI services might also require specialized configurations based on the AI models and resources you plan to utilize.

    Remember to replace:

    • "<METADATA_FROM_IDENTITY_PROVIDER>" with the actual metadata XML or URL from your third-party Identity Provider.
    • "YOUR_COMPARTMENT_ID" with the actual compartment ID in your OCI account which is going to host the AI Vision project.

    Before running the code, ensure you have the Pulumi CLI installed and configured with appropriate OCI credentials. You should also have installed the Pulumi OCI provider package for Python in your environment.