Cross-Cloud AI Services Access Using Federated Identities.

Question

Pulumi · Accepted Answer

To access Cross-Cloud AI services using federated identities, we can utilize the identity and access management (IAM) services provided by cloud providers such as Azure and Google Cloud Platform.

What I'll demonstrate is how to create federated identity credentials in Azure and set up a service account in Google Cloud, which could potentially interact with AI services across these clouds.

In Azure, we'll use a `FederatedIdentityCredential` for an application, which will allow it to authenticate using external identity providers. In Google Cloud, we will establish a service identity that will be used by Google's AI services, which can be associated with the federated identity provided by Azure, enabling cross-cloud authentication and authorization.

Here's a Python program using Pulumi that sets up a federated identity credential in Azure and creates a Google Cloud service account. This is only the infrastructure setup and doesn't include the detailed logic to interconnect these services at an application level, which would involve additional programming and configurations on the application code and service side.

### Pulumi Python Program

```python
import pulumi
import pulumi_azure_native as azure_native
import pulumi_gcp as gcp

# Set up an Azure Federated Identity Credential
azure_federated_identity_credential = azure_native.managedidentity.FederatedIdentityCredential(
    resource_name="myFederatedCredential",
    resource_group_name="myResourceGroup",
    audiences=["api://AzureADTokenExchange"],
    # The issuer of the token.
    issuer="https://sts.windows.net/{tenant-id}/",
    # The subject property of the JWT token.
    subject="user@domain.com",
)

# Set up a Google Cloud Service Account
google_cloud_service_identity = gcp.projects.ServiceIdentity(
    "myGoogleServiceIdentity",
    service="my-google-cloud-service"
)

# pulumi.export is used to output the ID of the resources on completion of `pulumi up`.
# It allows you to access the ID outside of Pulumi, which is helpful for integration and operational tasks.
pulumi.export('azureCredentialId', azure_federated_identity_credential.id)
pulumi.export('googleServiceAccountId', google_cloud_service_identity.email)
```

### Explanation

- **Federated Identity Credential**: The Azure Federated Identity Credential is set up to allow an application to authenticate using an external identity. This permits the Azure services to recognize users and services from different identity providers such as Google or Microsoft.

- **Service Identity**: On the Google Cloud side, a service identity is created for a specific Google Cloud service. This identity can be granted IAM roles and permissions in GCP, and it can also be connected with the Azure federated identity, allowing services to authenticate and authorize across cloud platforms.

- **Resource Export**: Using `pulumi.export`, we ensure that the identifiers of the created resources are available as stack outputs once the Pulumi program is applied. These identifiers can then be used to refer to the resources in subsequent operations, such as AI service API calls or within other infrastructure components.

To operationalize cross-cloud AI service access with these identities, you'll need to include additional configurations, policies, and potentially application-level code to handle token acquisition, exchange, permission granting, and service interactions. This program sets up the necessary IAM groundwork for such cross-cloud capabilities.

Please note that we have not set up any specific AI services in this program. To interact with AI services, you would need to utilize the SDKs or APIs provided by Azure AI and Google AI services and implement the logic to exchange and validate tokens obtained through the federated credentials.