1. AI Model Rollback with S3 Bucket Versioning


    To handle AI model rollback, we can use AWS S3 Bucket Versioning. Versioning in S3 buckets is a means of keeping multiple variants of an object in the same bucket. You can use this feature to preserve, retrieve, and restore every version of every object stored in your S3 bucket. This way, if you deploy a new AI model and find issues with it, you can easily roll back to a previous version of the model.

    Here's how to do it with Pulumi and AWS:

    1. Create an AWS S3 bucket with versioning enabled.
    2. Store your AI model files in the bucket.
    3. If needed, roll back to a previous version by copying the desired version to the current version.

    Let's translate this into code:

    import pulumi import pulumi_aws as aws # Create an AWS S3 bucket with versioning enabled ai_models_bucket = aws.s3.Bucket("aiModelsBucket", versioning=aws.s3.BucketVersioningArgs( enabled=True, # This turns on versioning for the bucket ) ) # Output the bucket name and versioning status pulumi.export("bucket_name", ai_models_bucket.id) pulumi.export("versioning_status", ai_models_bucket.versioning.apply(lambda v: v.enabled))

    In the above program:

    • We import the Pulumi SDK and the aws provider module.
    • We create an S3 bucket named aiModelsBucket with versioning enabled by setting enabled=True within the aws.s3.BucketVersioningArgs object.
    • Finally, we use pulumi.export to output the name of the bucket and the status of the versioning.

    Handling Rollback:

    To rollback a model, you would list the versions of the model file in the S3 bucket, identify the required version, and then set that version as the current version. This can be done using the AWS CLI or AWS SDK. Pulumi doesn't natively handle object-level operations such as rolling back to a previous version of a file, as it focuses on infrastructure as code. However, you can use it to set up the infrastructure needed to facilitate such operations.