The article provides a comprehensive guide on effectively debugging Apache Airflow Directed Acyclic Graphs (DAGs) by emphasizing three key strategies: setting up a robust local development environment, eliminating common issues, and implementing effective DAG testing. It highlights the importance of a local development setup using tools like the Astro CLI, which allows developers to quickly identify and fix bugs such as syntax errors or dependency conflicts before deployment. The text also underscores the significance of addressing frequent issues, such as DAGs not appearing in the UI or not running as scheduled, by using tools like the Airflow CLI for diagnosing import errors. Additionally, it stresses the necessity of rigorous DAG testing both locally and during deployment with methods like dag.test() in Airflow 2.5+, which facilitates faster iterations and debugging. The article concludes by encouraging developers to leverage community resources, such as Airflow Slack channels and GitHub, for additional support and suggests considering managed Airflow services like Astro for a more streamlined experience.