Astronomer Webinars

Join us for upcoming online events!

What’s New in the Astro Platform Release, Q2 2024

Hosted By

  • Kenten Danas
  • Ian Moritz
  • Conor Beverland

The latest release of Astro, Astronomer’s fully managed Airflow platform, includes new features that let you unify workloads, improve pipeline resilience, and automate infrastructure provisioning and management.

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Watch Recorded Webinars On-Demand

How to Save Money using Airflow’s asynchronous Azure operators

Many Azure users leverage Airflow for best-in-class orchestration of their Azure services. Recent updates to the Azure provider have brought greater functionality and new Airflow features to Azure operators. In this “Live with Astronomer” session, we’ll dive into the newly developed asynchronous Azure operators that offer cost savings and greater scalability. We’ll show how with only small updates to your DAGs, you can take advantage of asynchronous functionality when orchestrating services like Azure Data Factory and Azure Databricks.

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Using the new Fivetran provider

With more than 30,000 downloads per month, the Fivetran provider for Airflow is incredibly popular. Using Fivetran and Airflow together gives users the benefits of first-class orchestration, pipelines as code, and automated ELT processes.

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Organizing Your Airflow Project Code with the Astro CLI

One of the benefits of Airflow is having pipelines as Python code, which lets you treat your data pipelines like any other piece of software. In this “Live with Astronomer” session, we’ll dive into how to use the open-source Astro CLI to effectively manage your Airflow project code so you can share code with your team, test DAGs before you deploy them, keep your code organized for easy reviews, and more.

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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.

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