Authoring Mwaa Workflow
by aws0d6167ad2e6dNo license2.8K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today
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).
- 0d6167ad2e6dCurrentcommit 0d6167aPublished Oct 8, 2026
Source and attribution
Source:aws/agent-toolkit-for-awsinplugins/aws-data-analytics/skills/authoring-mwaa-workflowat commit0d6167a
License: No license
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