DevOps & Infrastructure
Authoring MWAA Workflow
Authors and deploys MWAA workflow artifacts: Python Airflow DAGs for provisioned environments or YAML workflow files for Serverless. Covers operator selection, timeout design, retry strategy, scheduling, failure notifications, idempotency, and MWAA Serverless schema compliance. Deploys the artifact (S3 DAG upload or Serverless CreateWorkflow/UpdateWorkflow), creates an environment inline when approved, and redeploys fixes, then optionally hands off to testing-mwaa-workflow. Triggers on: create a DAG, write a pipeline, build a workflow, orchestrate tasks, Airflow DAG, data pipeline, schedule a job, deploy a DAG, deploy a workflow, YAML workflow. Not applicable to converting or migrating existing DAGs between provisioned and serverless (conversion is out of scope), running or smoke-testing a deployed workflow (handled by testing-mwaa-workflow) or diagnosing a failed run (handled by debugging-mwaa-workflow).
- Publisher / source
- aws/agent-toolkit-for-aws (found on skills.sh)
- Upstream record
- aws/agent-toolkit-for-aws
- Version
- Version 3
- Published
- Publication review
- Approved for publication
- Content fingerprint
4cfbda2407de1643a2857dc239d50d3ed2ee0075de7092d44f9e4bd1f38b672c