A lot of serverless AWS Service supports versioning and alias for deployment. It made the blue / green deployment, canary deployment and rolling back super easy.
- AWS Lambda Versioning and Alias
- AWS StepFunction Versioning and Alias
- AWS SageMaker Model Registry Versioning
However, Airflow DAG does not support this feature yet. This library provides a way to manage Airflow DAG versioning and alias so you can deploy Airflow DAG with confidence.
Please read this tutorial to learn how to use this library.
It also has native AWS MWAA support for DAG deployment automation, with the DAG versioning manage, which is not official supported by Apache Airflow. Please read this example to learn how to use this library with AWS MWAA.
airflow_dag_artifact is released on PyPI, so all you need is to:
$ pip install airflow-dag-artifactTo upgrade to latest version:
$ pip install --upgrade airflow-dag-artifact