1. Data warehousing with AWS Lake Formation


    Sure, below you can find a simplified Pulumi program for setting up a data warehouse with AWS Lake Formation. The program does the following:

    1. Registers an S3 bucket with AWS Lake Formation.
    2. Sets up certain administrators and permission defaults for creating databases and tables in the warehouse.
    3. Grants necessary Lake Formation permissions to an IAM principal.

    Please replace all placeholder values ("your-value-here") with real values relevant to your use case.

    import pulumi from pulumi_aws import s3, iam, lakeformation # Create an AWS S3 Bucket. bucket = s3.Bucket("my-bucket") # Creating IAM role assume_role_policy = '{"Version":"2012-10-17","Statement":[{"Sid":"","Effect":"Allow","Principal":{"Service":"lakeformation.amazonaws.com"},"Action":"sts:AssumeRole"}]}' iam_role = iam.Role("iam-role", assume_role_policy=assume_role_policy) # Register AWS S3 bucket with Lake Formation. lf_resource = lakeformation.Resource("lf-resource", arn=bucket.arn, role_arn=iam_role.arn) # Set up the AWS Lake Formation Data Lake settings. lake_settings = lakeformation.DataLakeSettings("lake-settings", admins=["your-admin-arn-here"], # Set of ARNs of AWS Lake Formation principals (IAM users or roles). create_database_default_permissions=[{ "permissions": ["ALL"], "principal": "your-principal-arn-here", }], create_table_default_permissions=[{ "permissions": ["ALL"], "principal": "your-principal-arn-here", }]) # Grant permissions to a principal. lf_permissions = lakeformation.Permissions("lf-permissions", permissions=["ALL"], principal="your-principal-arn-here", table={ "database_name": "your-database-here", "name": "your-table-here", }) # Export names of the created resources pulumi.export("bucket_name", bucket.bucket_name) pulumi.export("lake_settings_id", lake_settings.id) pulumi.export("lf_resource_role_arn", lf_resource.role_arn) pulumi.export("lf_permissions_id", lf_permissions.id)

    Useful links:

    Please note that the above program is a basic example and might not cover all your needs for a full-fledged data warehousing solution. Don't hesitate to further customize it according to your requirements.