AWS Glue is a managed ETL (extract, transform, and load) and data integration service for building and running data pipelines. It lets you prepare and transform data for analytics without managing the underlying infrastructure. Glue integrates with common AWS services such as S3, Athena, and Redshift and can scale to large workloads. This makes it a practical option for running automated ETL at scale. If you’re learning ETL orchestration and data workflows on AWS, Glue is a good service to know.
In this Cloud Lab, you’ll create an S3 bucket with input and output folders and enable EventBridge notifications. You’ll create an ETL job that transforms CSV files from an S3 bucket by converting dates, standardizing product names, calculating total amounts, and filtering out cancelled or returned orders. Next, you’ll create an EventBridge rule to trigger your Glue workflow whenever a new file is uploaded and add the ETL job to the workflow. Finally, you’ll monitor the workflow execution and validate the transformed output in the S3 output folder.
By the end of this Cloud Lab, you’ll gain hands-on experience orchestrating AWS Glue workflows, automating ETL jobs, and configuring S3 and EventBridge integrations. You’ll be able to implement event-driven data processing pipelines, monitor job runs, and manage workflow executions efficiently. This knowledge will help you build scalable, automated data pipelines in real-world scenarios.
The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:
