Apache Airflow is a Python-based platform for programmatically authoring, scheduling, and monitoring workflows as directed acyclic graphs (DAGs). Originally developed at Airbnb and open-sourced in 2015, it has become the de facto standard for data pipeline orchestration across batch, streaming, and machine learning workflows. Airflow's core strength lies in its code-as-configuration approach where workflows are defined in Python, enabling version control, testing, and dynamic generation. The platform operates on the principle that tasks are discrete units of work arranged in a DAG, with dependencies explicitly defined to ensure proper execution order—a model that scales from simple ETL pipelines to complex multi-team data platforms orchestrating thousands of workflows.