1. OCI Artifacts for Versioning AI Model Containers


    Creating OCI artifacts for versioning AI model containers is an integral aspect of managing and deploying machine learning models in the cloud. In the Oracle Cloud Infrastructure (OCI), you can use the oci.Artifacts.ContainerRepository resource to create a container repository, and the oci.Artifacts.ContainerConfiguration resource to configure the repository settings, such as whether a repository is created on the first push of a container image.

    The oci.Artifacts.ContainerRepository resource allows you to create a repository for your Docker container images, which is essential for housing the various versions of your AI models packaged as containers. By setting the isImmutable flag to True, you can ensure that once a container image is pushed with a specific tag, it can't be overwritten, thus achieving a form of version control.

    The oci.Artifacts.ContainerConfiguration resource offers additional options to configure the default repository settings on your tenancy level.

    Let me provide you with a Pulumi program written in Python to accomplish this:

    import pulumi import pulumi_oci as oci # Replace the following variables with your relevant OCI compartment information. compartment_id = 'ocid1.compartment.oc1..your_compartment_ocid' # Create a container repository to store AI model containers. ai_model_repository = oci.artifacts.ContainerRepository('aiModelRepository', compartment_id=compartment_id, display_name='AIModelRepository', is_public=False, is_immutable=True, # Ensures images are not overwritten once pushed. readme=oci.artifacts.ContainerRepositoryReadmeArgs( content='c29tZSBzYW1wbGUgYmFzZTY0ZW5jb2RlZA==', # Base64-encoded README content. format='TEXT_MARKDOWN', ) ) # Configure the container repository settings for your tenancy. container_configuration = oci.artifacts.ContainerConfiguration('containerConfiguration', compartment_id=compartment_id, is_repository_created_on_first_push=True ) # Export the repository URL to access it later. Replace 'region' and 'tenancy_namespace' accordingly. repository_url = pulumi.Output.concat("https://", compartment_id, ".ocir.io/v2/", 'tenancy_namespace', "/", ai_model_repository.display_name) pulumi.export('repository_url', repository_url) # To view the exported repository URL after deployment, run `pulumi stack output repository_url`.


    1. Import Dependencies: We import the required Pulumi packages for OCI resources.
    2. Specify Compartment ID: Replace 'ocid1.compartment.oc1..your_compartment_ocid' with the specific compartment OCID where you want to create the artifact.
    3. Create a Container Repository: We instantiate an oci.Artifacts.ContainerRepository resource, which sets up a repository for our AI models.
      • display_name gives a human-readable name for the repository.
      • is_public is set to False, meaning the repository will be private.
      • is_immutable is set to True, ensuring that tags cannot be overwritten.
      • The readme property provides a base64-encoded string that represents the readme content; here, it's TEXT_MARKDOWN.
    4. Configure the Container Repository: We create a oci.Artifacts.ContainerConfiguration resource to set up default repository settings.
      • is_repository_created_on_first_push allows a repository to automatically be created the first time a Docker image is pushed if the repository doesn't already exist.
    5. Export Repository URL: We combine strings to form the URL of the repository and export it so you can easily access the output after deployment.
    6. Running the Program: Upon deploying this Pulumi program with pulumi up, it will create the OCI artifacts and output the repository URL. You can view the URL by running pulumi stack output repository_url.

    Remember to replace placeholder strings such as 'region', 'tenancy_namespace', and the compartment OCID with your actual OCI tenancy information. The compartment OCID should be available in your OCI console under the "Identity & Security" section.