Understanding Airflow#
Airflow represents dependencies as Directed Acyclic Graphs (DAGs). Its robust scheduler tracks execution retries, distributes worker tasks, and surfaces telemetry via a web dashboard.
Everyday Analogy#
An automated airport air-traffic control schedule ensuring airplanes only land after runways clear and baggage handlers arrive at the gate.
Practical Applications#
- Orchestrating nightly multi-stage analytics pipelines across disparate cloud vendors
- Triggering automated model retraining jobs when new training datasets arrive