1. CodeArtifact as a Repository for AI Deployment Packages


    AWS CodeArtifact is a fully managed artifact repository service that makes it easy for organizations to securely store, publish, and share software packages used in their software development process. When setting up CodeArtifact for AI deployment packages, we'll define a domain which serves as a logical grouping of repositories. Then, we'll create a repository within that domain to store the actual AI packages.

    Step 1: Create a CodeArtifact Domain

    A domain is used to aggregate and manage multiple repositories. You will need to specify a domainName, and you can optionally define tags or an encryptionKey if you want to encrypt your domain with a customer-managed AWS KMS key.

    Step 2: Create a CodeArtifact Repository within the Domain

    Once a domain is established, you can create a repository in that domain to store your AI deployment packages. You should name your repository (repositoryName) to reflect the type of packages it will hold, for example, ai-models.

    Let's set up a Pulumi program in Python to accomplish this. The Pulumi AWS provider offers resources corresponding to AWS CodeArtifact entities.

    Python Pulumi Code for Setting Up CodeArtifact

    import pulumi import pulumi_aws as aws # Step 1: Create a CodeArtifact Domain for your AI packages ai_domain = aws.codeartifact.Domain("aiDomain", domain_name="ai-deployment-domain", # Optionally, add tags or KMS encryption key tags={ "purpose": "AI Deployment Packages", }) # Step 2: Create a CodeArtifact Repository within the Domain ai_repository = aws.codeartifact.Repository("aiRepository", repository_name="ai-models", domain=ai_domain.domain_name, # Optionally, specify upstreams, description, domain owner description="Repository for AI deployment packages" ) # Export the domain and repository ARNs pulumi.export("domain_arn", ai_domain.arn) pulumi.export("repository_arn", ai_repository.arn)

    In the code above, we've created a CodeArtifact domain with pulumi_aws.codeartifact.Domain and specified its name with domain_name. Next, we created a repository with pulumi_aws.codeartifact.Repository. The repository is associated with the domain we created and is named ai-models.

    The tags parameter is used to add metadata to resources, which can help with organization and cost allocation. The description property describes the purpose of the repository.

    Exported values are ARNs (Amazon Resource Names) of the domain and repository, which can be used to reference these resources in other parts of your AWS infrastructure or Pulumi programs.

    This program, once applied with Pulumi, will set up AWS CodeArtifact service for AI deployment packages, automating the infrastructure setup required for managing your software artifacts.