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Apache Airflow is a tool for orchestrating complex workflows and data processing pipelines. The Kedro-Airflow plugin can be used for:

• Rapid pipeline creation in the prototyping phase. You can write Python functions in Kedro without worrying about schedulers, daemons, services or having to recreate the Airflow DAG file.
• Automatic dependency resolution in Kedro. This allows you to bypass Airflow's need to specify the order of your tasks.
• Distributing Kedro tasks across many workers. You can also enable monitoring and scheduling of the tasks' runtimes.

kedro-airflow is a Python plugin. To install it:

pip install kedro-airflow

You can use kedro-airflow to deploy a Kedro pipeline as an Airflow DAG by following these steps:

At the root directory of the Kedro project, run:

kedro airflow create

This command will generate an Airflow DAG file located in the airflow_dags/ directory in your project. You can pass a --pipeline flag to generate the DAG file for a specific Kedro pipeline and an --env flag to generate the DAG file for a specific Kedro environment.

For more information about the DAGs folder, please visit Airflow documentation.

After generating and deploying the DAG file, you will then need to package and install the Kedro pipeline into the Airflow executor's environment. Please visit the guide to deploy Kedro as a Python package for more details.