1. Data orchestration using AWS Lake Formation


    Okay! Here is a basic example of how you might use Pulumi and AWS Lake Formation to orchestrate data storage.

    In this program, we will accomplish the following:

    1. Create an S3 bucket with AWS.
    2. Register the bucket as a resource with AWS Lake Formation.
    3. Set up Lake Formation's data access permissions for the bucket.

    For brevity, we will use an IAM role that already exists, but you can also create that using Pulumi.

    import pulumi from pulumi_aws import s3, lakeformation # Create the S3 Bucket bucket = s3.Bucket('bucket') # Register the bucket with LakeFormation resource = lakeformation.Resource('resource', arn=bucket.arn) # Create lakeFormation data lake settings data_lake_settings = lakeformation.DataLakeSettings('data-lake-settings', admins=[{ 'arn': 'arn-of-iam-role', # Replace with ARN of IAM role }] ) # Create permissions for the lake permissions = lakeformation.Permissions('permissions', permissions=['ALL'], principal='arn-of-iam-role', # Replace with ARN of IAM role data_location={ 'arn': bucket.arn, } ) # Export the name of the bucket pulumi.export('bucket_name', bucket.id)

    This program will set up a new S3 bucket and register it with Lake Formation. It will then give the IAM role specified full access to the bucket.

    Here is the relevant documentation for the aws.lakeformation.Resource.

    This is the documentation for aws.lakeformation.DataLakeSettings.

    Here is the documentation for aws.lakeformation.Permissions.

    Please replace 'arn-of-iam-role' with the ARN of the IAM Role that you want to grant permissions for accessing data stored in the S3 bucket.

    This is just a basic setup of AWS Lake Formation, and there's a lot more functionality available through AWS and Pulumi. Check out the above documentation links for more details on how to use Pulumi with AWS Lake Formation.