Authoring Mwaa Workflow

作者 aws0d6167ad2e6d無授權條款2.8K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

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).

僅公開檔案列表。將技能安裝到工作區後即可檢視檔案內容。

路徑大小類型
references/authoring-provisioned-dag.md13.9 KBtext/markdown
references/authoring-serverless-workflow.md7.4 KBtext/markdown
references/dag-patterns.md7.9 KBtext/markdown
references/deploying-mwaa.md10 KBtext/markdown
references/serverless-code-packaging.md3.8 KBtext/markdown
references/yaml-schema.md4.7 KBtext/markdown
SKILL.md11 KBtext/markdown

來源與署名

來源:aws/agent-toolkit-for-aws位於plugins/aws-data-analytics/skills/authoring-mwaa-workflow提交0d6167a

授權條款: 無授權條款

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架