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It’s easy to get your pipelines up and running with Apache Airflow®. This quickstart offers three learning paths. Choose between these popular use cases:
  • Learning Airflow: an introduction to Airflow’s lean and dynamic pipelines-as-Python-code
  • ETL: an introduction to modern, enhanced ETL development with Airflow
  • Generative AI: an introduction to generative AI model development with Airflow
Launch your journey with Airflow by signing up for a trial! You’ll be able to deploy your projects to Astro at the end of this tutorial.
Other ways to learnFor more help getting started, also check out our step-by-step Get Started with Airflow tutorial.

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Time to complete

This quickstart takes approximately 30 minutes to complete.

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Assumed knowledge

To get the most out of this quickstart, you should have an understanding of:

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Prerequisites

  • The Astro CLI version 1.25.0 or higher.
  • An integrated development environment (IDE) for Python development, such as VS Code, Sublime Text, or PyCharm.
  • (Optional) A local installation of Python 3 to improve your Python developer experience.

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Step 1: Clone the Astronomer Quickstart repository

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Step 2: Start up Airflow and explore the UI

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Step 3: Explore the project

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Step 4: Get your hands dirty!

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Next steps: run Airflow on Astro

The easiest way to run Airflow in production is with Astro. To get started, create an Astro trial. During your trial signup, you will have the option of choosing the same template project you worked with in this quickstart.