Serverless Data Warehouse ETL Workflow

In this workflow, a Glue ETL job takes a JSON file as an input from S3 and then transforms one of the field name. Together with the transformation, required data catalog is created and data is inserted to Redshift serverless datawarehouse by running Glue Connectors.

Pre-requisite:

• Redshift Serverless namespace is created.
• AWS Glue Job is defined.
• Glue Connector Redshift Serverless is created
• Job for Connector is created

Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the AWS Pricing page for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.

Requirements

• Create an AWS account if you do not already have one and log in. The IAM user that you use must have sufficient permissions to make necessary AWS service calls and manage AWS resources.
• AWS CLI installed and configured
• Git Installed
• AWS Serverless Application Model (AWS SAM) installed

Deployment Instructions

1. Create a new directory, navigate to that directory in a terminal and clone the GitHub repository:

   git clone https://github.com/aws-samples/step-functions-workflows-collection
   

2. Change directory to the pattern directory:

   cd dwh-etl
   

3. From the command line, use AWS SAM to deploy the AWS resources for the workflow as specified in the template.yaml file:

   sam deploy --guided
   

4. During the prompts:

   • Enter a stack name
   • Enter the desired AWS Region
   • Allow SAM CLI to create IAM roles with the required permissions.

   Once you have run sam deploy --guided mode once and saved arguments to a configuration file (samconfig.toml), you can use sam deploy in future to use these defaults.

5. Note the outputs from the SAM deployment process. These contain the resource names and/or ARNs which are used for testing.

How it works

1. Send your prompt and model ID as input.

   {
     "prompt": "YOUR-PROMPT",
     "modelID": "ARN-OF-BEDROCK-MODEL"
   }    
   

2. Step Functions will invoke the selected model on Amazon Bedrock.

Testing

1. Navigate to the AWS Step Functions console and select the bedrock-invokemodel workflow.
2. Select Start Execution and use the following JSON data as input.

    {
      "prompt": "where is the largest city",
      "modelID": "arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-v2"
    }    
   

3. Select Start Execution
4. Observe the task in the Step Functions console.

Cleanup

To delete the resources created by this template, use the following command:

sam delete

---

Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

SPDX-License-Identifier: MIT-0