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- Apache Airflow
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 services
- What is Airflow®? — Airflow 3. 0. 2 Documentation - Apache Airflow
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 connecting with virtually any technology
- Quick Start — Airflow 3. 0. 2 Documentation
Note Successful installation requires a Python 3 environment Starting with Airflow 2 7 0, Airflow supports Python 3 9, 3 10, 3 11, and 3 12 Officially supported installation methods include pip and uv Both tools provide a streamlined workflow for installing Airflow and managing dependencies
- Documentation - Apache Airflow
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
- Tutorials — Airflow 3. 0. 2 Documentation
Tutorials ¶ Once you have Airflow up and running with the Quick Start, these tutorials are a great way to get a sense for how Airflow works
- Installation of Airflow® — Airflow 3. 0. 2 Documentation
You are responsible for setting up the database, creating and managing database schema with airflow db commands, automated startup and recovery, maintenance, cleanup and upgrades of Airflow and the Airflow Providers
- Core Concepts — Airflow 3. 0. 2 Documentation
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
- Use Cases - Apache Airflow
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 of use cases
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