Apache Airflow® is an open-source platform for developing, scheduling, and monitoring batch-oriented workflows. Airflow’s extensible Python framework enables you to build workflows …

Apache Airflow® provides many plug-and-play operators that are ready to execute your tasks on Google Cloud Platform, Amazon Web Services, Microsoft Azure and many other third-party …

Airflow is a platform that lets you build and run workflows. A workflow is represented as a DAG (a Directed Acyclic Graph), and contains individual pieces of work called Tasks, arranged with …

Loading dags ¶ Airflow loads dags from Python source files in dag bundles. It will take each file, execute it, and then load any DAG objects from that file. This means you can define multiple …

Apache Airflow® allows you to define almost any workflow in Python code, no matter how complex. Because of its versatility, Airflow is used by companies all over the world for a variety …

Here you can find detailed documentation about each one of the core concepts of Apache Airflow® and how to use them, as well as a high-level architectural overview.

Apache Airflow is an open-source platform for developing, scheduling, and monitoring batch-oriented workflows. Airflow’s extensible Python framework enables you to build workflows …

Welcome to world of Apache Airflow! In this tutorial, we’ll guide you through the essential concepts of Airflow, helping you understand how to write your first DAG.

This guide will help you quickly set up Apache Airflow using uv, a fast and modern tool for managing Python environments and dependencies. uv makes the installation process easy …

Airflow has an official Helm Chart that will help you set up your own Airflow on a cloud/on-prem Kubernetes environment and leverage its scalable nature to support a large group of users.