Thanks for connecting with us at the Airflow Summit in San Francisco!

We hope you found value in learning about:

Astro® by Astronomer: Our fully-managed Airflow platform that reduces costs, boosts developer productivity, and powers your most critical data pipelines reliably.

The launch of Astro Observe (private preview): Unifying data orchestration and observability into one platform to give you seamless visibility and control over your data pipelines.

dbt on Astro: Simplify your data workflows by managing dbt and Airflow from a single interface, eliminating the complexity of juggling multiple tools.

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Run Airflow with Unmatched Ease, Security, and Reliability

Astro by Astronomer is the premier fully-managed solution for maximizing your Airflow capabilities, delivering 10x the performance while eliminating maintenance burdens.

Enjoy robust integration, automation, and scalability for even the most complex data projects. With unparalleled high availability and durability, Astro ensures your critical workflows remain uninterrupted under any conditions.

Choose Astro to experience the best platform for running Airflow—complete, easy, secure, and resilient. Schedule a consultation with our experts now to see how Astro can optimize your Airflow workflows.

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100%

Astronomer drives 100% of Apache Airflow® releases.

55%

Our team has contributed 55% of Airflow code.

16 of 25

We have 16 of the top 25 committers and 7 PMC members on staff.

30K

There are 30,000 Airflow students in the Academy ecosystem.

Forward-thinking Perspectives from Our Customers

Expert Insights from The Astronomer Team

10 years of Airflow: history, insights, and looking forward

  • Kenten Danas
  • Marc Lamberti
  • Ash Berlin-Taylor

AIP-63: DAG Versioning - Where are we?

  • Jed Cunningham

Airflow 3 - Roadmap Discussion

  • Kaxil Naik

Airflow UI Roadmap

  • Brent Bovenzi

Connecting the Dots in Airflow: From User to Contributor

  • Briana Okyere
  • Ryan Hatter

Converting Legacy Schedulers to Airflow

  • Fritz Davenport

Data-Centric Airflow

  • Tzu Ping Chung

Gen AI using Airflow 3: A vision for Airflow RAGs

  • Vikram Koka
  • Kaxil Naik
  • Ash Berlin-Taylor

Investigating the Many Loops of the Airflow Scheduler

  • Philippe Gagnon

Managing version upgrades without feelings of terror

  • Daniel Standish

Optimizing Airflow Performance: Strategies, Techniques, and Best Practices

  • Pankaj Singh
  • Pankaj Koti

Overcoming performance hurdles in Integrating dbt with Airflow

  • Tatiana Al-Chueyr Martins

Running Airflow tasks anywhere, in any language

  • Ash Berlin-Taylor

Why Do Airflow Tasks Fail? A Principal Component Analysis

  • Julian LaNeve
  • David Xue

Using the power of Apache Airflow® and Ray for Scalable AI deployments

  • Venkata Jagannath

A New DAG Paradigm: Less Airflow more DAGs

  • Marion Azoulai
  • Maggie Stark

Mastering Advanced Dataset Scheduling in Apache Airflow®

  • Ankit Chaurasia

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