Introducing Apache Airflow® 3.0
Be among the first to see Airflow 3.0 in action and get your questions answered directly by the Astronomer team.
Astronomer Webinars
Join us for upcoming online events!
Optimizing your Airflow Developer Experience: Exploring DAG Versioning and Backfills
Explore how new features in Airflow 3.0, including DAG versioning and backfills, can improve your productivity and help you manage your pipelines more efficiently. Whether you are an experienced Airflow user or just getting started, you’ll learn how to quickly troubleshoot and manage your pipeline history.
New in Airflow 3.0: Data Assets and Event-Driven Scheduling Deep Dive
Learn how Airflow 3.0 is expanding on assets, the foundational datasets feature, by introducing asset watchers, the most powerful option for event-driven scheduling in Airflow to date
Airflow 3.0 Security Enhancements: Remote Execution and Task Isolation Deep Dive
In this session, we’ll break down these architectural changes and show you how to use these new features to run your tasks anywhere
Watch Recorded Webinars On-Demand
Data-Aware Scheduling with the Astro Python SDK
Live with Astronomer dives into implementing data-aware scheduling with the Astro Python SDK. The new Airflow Datasets feature allows you to schedule DAGs based on updates to your data and easily view cross-DAG relationships. This feature is part of the Astro Python SDK, so it requires almost no effort from the DAG author to implement. We'll show you everything you need to do (and don't need to do) to take advantage of Datasets.
Running Airflow Tasks in Isolated Environments
Airflow DAG authors have multiple options for running tasks in isolated environments. In this webinar, we'll cover everything you need to know.
How to Migrate from Oozie to Airflow: A Guided Walkthrough
In this webinar, we’ll cover everything you need to know about migrating from Oozie to Airflow.
The New DAG Schedule Parameter
We’ll provide a quick refresher of scheduling concepts and discuss how scheduling DAGs is easier and more powerful in newer versions of Airflow.
Batch Inference with Airflow and SageMaker
We’ll walk through using the new SageMaker Async Operators, as well as the new SageMaker OpenLineage integration, for end-to-end ML OPs for batch inference use cases.
Dynamic Task Mapping on Multiple Parameters
On October 25, Live with Astronomer will dive into updates to the dynamic task mapping feature released in Airflow 2.4. We’ll show a couple of new methods for mapping over multiple parameters, and discuss how to choose the best mapping method for your use case.
Dynamic Tasks in Airflow
With the releases of Airflow 2.3 and 2.4, users can write DAGs that dynamically generate parallel tasks at runtime. In this webinar, we’ll cover everything you need to know to implement dynamic tasks in your DAGs.
Data Driven Scheduling
In this session, Live with Astronomer explores the new datasets feature introduced in Airflow 2.4. We’ll show how DAGs that access the same data now have explicit, visible relationships, and how DAGs can be scheduled based on updates to these datasets.
What’s New in Airflow 2.4
In this webinar, we’ll cover all the great 2.4 updates that make Airflow even more powerful and observable.
