Separate extraction, validation, transformation, and publication into tasks.
Manage dependencies, schedules, and backfills as a Python DAG.
Which service is most appropriate?
Use Amazon MWAA to run Apache Airflow DAGs with dependencies, schedules, retries, and backfills.
Detailed explanation
MWAA provides a managed Airflow environment for dependencies, scheduling, retries, and backfills.
MWAA provides a managed Airflow environment for dependencies, scheduling, retries, and backfills.
An IAM group is a set of principals and does not represent data-task ordering.
An IAM group is a set of principals and does not represent data-task ordering.
A SORTKEY controls table layout, not workflow dependencies.
A SORTKEY controls table layout, not workflow dependencies.
S3 events can notify a target but do not provide DAG history, backfills, or task dependencies.
S3 events can notify a target but do not provide DAG history, backfills, or task dependencies.
Check official documentation
Compare the following points with the official documentation.
Amazon MWAA、Airflow DAG、スケジュール、バックフィルの公式説明を確認する。
What to confirm
イベント通知やテーブル物理設計と、DAGオーケストレーションを区別できる。
Key points
- MWAA
- Apache Airflow
- DAG
- Backfill
Notes
- Environment: AWS公式DEA-C01試験ガイドと各サービスの公式ドキュメントの確認
- Confirm current AWS service behavior in the official DEA-C01 documentation.
Foundation review
Dependency graph
A DAG gives each task an explicit upstream and downstream relationship.
Operational history
Airflow records task runs, retries, schedules, and backfill outcomes.