1. CI/CD Pipelines for AI Development using OCI Artifacts


    Creating a CI/CD pipeline for AI development using OCI (Oracle Cloud Infrastructure) Artifacts involves several steps. The pipeline typically consists of stages for development, building, testing, and deployment. In the context of AI development, the pipeline may also include steps specific to machine learning such as training models, evaluating their performance, and versioning them.

    OCI Artifacts is a service within Oracle Cloud that allows you to share and manage development artifacts. This service can be used for storing various types of artifacts, from container images to general-purpose development artifacts.

    In a Pulumi program, we create resources that represent different aspects of the infrastructure we want to provision. The program below demonstrates how to create a container repository in OCI, where you could push container images of your AI applications. These images can then be used in later stages of the pipeline for deployment.

    import pulumi import pulumi_oci as oci # Replace these values with your own configuration compartment_id = "ocid1.compartment.oc1..exampleuniqueID" display_name = "ai-container-repo" is_immutable = True # To prevent changes to images once pushed, set to "True" # Creating an OCI Container Repository # This repository will hold container images for the AI applications. # For more information: https://www.pulumi.com/registry/packages/oci/api-docs/artifacts/containerrepository/ container_repo = oci.artifacts.ContainerRepository("aiContainerRepo", compartment_id=compartment_id, is_immutable=is_immutable, display_name=display_name ) pulumi.export("container_repo_id", container_repo.id) pulumi.export("container_repo_name", container_repo.display_name)

    In this program, the oci.artifacts.ContainerRepository resource creates a new OCI Container Repository. We set a display name for the repository and specify if it should be immutable. An immutable repository ensures that once a container image is pushed, it cannot be overwritten, thus preserving the integrity of the images used in your CI/CD pipelines.

    After running this Pulumi program with the pulumi up command, the outputs will include the ID and name of the OCI Container Repository created, which can then be used in your CI/CD pipeline to push or pull container images.

    Next, you could set up a mechanism to automatically build container images whenever there's a change in your AI application's source code (e.g., using GitHub Actions or OCI DevOps service), tag those images appropriately, and push them to the OCI Container Repository you've created above. This fits into the larger CI/CD process but would require additional steps and configurations outside of this infrastructure definition.

    Remember, this is just one component of a full CI/CD pipeline. A complete solution would involve additional resources such as build servers, artifact storage for model binaries, and compute resources for testing and deployment, which are defined and managed similarly but were not covered in this example.