Apache Airflow has become one of the most widely used open-source platforms for orchestrating and managing complex data workflows. With its rich features, including DAGs (Directed Acyclic Graphs), task dependencies, and scheduling capabilities, Airflow enables users to automate and scale their data engineering and data science processes. However, as workflows grow in complexity and size, the need for effective monitoring tools becomes crucial to ensure that everything runs smoothly. This is where Airflow Monitor comes into play, providing real-time monitoring, alerting, and troubleshooting features that are essential for managing large-scale Airflow deployments.