Automated Airflow DAG Run Monitoring Workflow

This n8n workflow automates the process of triggering and monitoring an Airflow DAG run via API calls, making it ideal for orchestrating scheduled data workflows. It begins with an external trigger, such as a webhook, to initiate a DAG run using the Airflow API. The workflow then periodically checks the status of the DAG run, waiting until it reaches a terminal state (success, failed, or queued). If the DAG run remains queued or takes too long, it raises appropriate errors, ensuring reliable operation. The workflow can be customized with wait times and retries, making it suitable for data pipelines or ETL processes that require close monitoring.