Introducing Apache Airflow 2.9
- Kenten Danas Manager, Developer Relations
The Airflow 2.9 release brings significant enhancements to user-favorite features like data-aware scheduling, dynamic task mapping, and object storage.
The Airflow 2.9 release brings significant enhancements to user-favorite features like data-aware scheduling, dynamic task mapping, and object storage.
An introduction to testing strategies, best practices, and implementation techniques.
Our beta cohort of 10 is now joined by 23 hand-selected individuals who, we believe, truly embody what it means to champion the Apache Airflow Project.
Boost your career and learn to run a data pipeline by getting Apache Airflow certified with the Astronomer Certification for Apache Airflow Fundamentals.
We give you a tour of the new features in the KubernetesExecutor 2.0. Spoiler alert – it's faster, more flexible, and easier to understand.
Learn how to orchestrate Talend jobs with Airflow so you can use both tools without rewriting your pipelines.
Today, we're excited to release our discovery and distribution hub for Apache Airflow integrations.
Learn how the TaskFlow API in Airflow 2.0 enables a better DAG authoring experience.
Secrets are sensitive information that are used as part of your DAG. Here are some best practices for managing them in Apache Airflow 2.0.
Implementing production-grade change data capture in near real-time on Google CloudSQL with Apache Airflow.
Now that we have these DAGs running locally and built from our dbt `manifest.json` file, the natural next step is to evaluate how these should look in a production context.
Implementing an ideal development experience at the intersection of two popular open-source tools, written in collaboration with our friends at Updater.
Try Astro free for 14 days and power your next big data project.