The State of Airflow 2025
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Our panel of experts will discuss the state of Airflow in 2025, including trends and results from the recent annual Airflow survey.
Astronomer Webinars
Join us for upcoming online events!
Datasets and Data-Aware Scheduling in Airflow
In this webinar, we’ll explore how to take full advantage of datasets and data-aware scheduling in Apache Airflow.
Modernizing Data Workflows: Moving from legacy schedulers to Airflow
Join us to discover how Airflow helps you deliver workflows faster, minimize downtime, and scale your operations effortlessly. Plus, you’ll see how Astronomer’s Orbiter tool takes the complexity out of migration and allows you to modernize your data operations with ease.
Watch Recorded Webinars On-Demand
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.
A Deep Dive into the Airflow UI
In this webinar, we’ll take an in-depth tour of the Airflow UI and cover the many features that users may not be aware of.
Data Transformations with the Astro Python SDK
On September 13, Live with Astronomer will dive into implementing data transformations with the Astro Python SDK. The Astro Python SDK is an open source Python package that allows for clean and rapid development on ELT workflows. We’ll show how you can use the transform and dataframe functions to easily transform your data using Python or SQL and seamlessly transition between the two.
Implementing Data Quality Checks in Airflow
Executing SQL queries — one of the most common use cases for data pipelines — is a simple way to implement data quality checks. In this webinar, we’ll cover everything you need to know about using SQL for data quality checks.
The Astro Python SDK Load File Function
Learn about the Astro Python SDK load_file function. See how to get data from filesystems into a data warehouse with only a few lines of code.
