Compute
RecognitionAWS Batch
Managed scheduling and compute for bounded batch processing workloads.
Key points
- AWS Batch queues and schedules bounded containerized jobs onto managed compute environments.
- Job definitions, resource requirements, queues, retries, and the chosen compute environment shape execution.
Best-known use cases
- Schedule containerized batch transformations and backfills.
- Provision compute for queued data-processing jobs with varying resource needs.
What candidates often confuse it with
- Batch is designed for queued finite jobs; ECS or EKS is appropriate when the team owns a longer-lived container platform.
Key takeaway
Choose AWS Batch for containerized transformations and backfills that can run as queued jobs.
Relevant exam tasks
- D1.1 — Task 1.1: Perform data ingestion
- 1.1.2 — Read data from batch sources (for example, Amazon S3, AWS Glue, Amazon EMR, AWS DMS, Amazon Redshift, AWS Lambda, Amazon AppFlow).
- D1.2 — Task 1.2: Transform and process data
- 1.2.5 — Implement data transformation services based on requirements (for example, Amazon EMR, AWS Glue, Lambda, Amazon Redshift).