Astronomer Webinars

Join us for upcoming online events!

February 20, 2025

Introducing Astro Observe: Pipeline-level Observability

Hosted By

Jason Ma VP, Product
Naveen Sukumar Head of PMM & DevRel

By the end of this webinar, you’ll be ready to take the next step with Astro Observe, now compatible with OSS Airflow, Astro, Amazon Managed Workflows (MWAA), and Google Cloud Composer (GCC).

February 27, 2025

The State of Airflow 2025

Our panel of experts will discuss the state of Airflow in 2025, including trends and results from the recent annual Airflow survey.

March 19, 2025

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

March 28, 2023

How to Orchestrate Machine Learning Workflows with Airflow

In this webinar on machine learning orchestration with Apache Airflow®, we’ll provide an overview of machine learning orchestration, its importance in managing ML workflows, and how it fits in with MLOps.

March 21, 2023

How to Orchestrate Databricks Jobs Using Airflow

In this “Live with Astronomer” session, we’ll dive into Cosmos, an open-source framework developed by Astronomer for dynamically generating Airflow DAGs from other tools.

March 14, 2023

How to Automate and Scale Data Ingestion with Fivetran and Airflow

In this webinar, we’ll dive into the newly updated Fivetran provider and discuss the benefits of using Airflow and Fivetran together for your ELT pipelines. We’ll cover how to implement the available Fivetran operators to orchestrate sync jobs, how to leverage asynchronous functionality for cost savings, and how to use lineage generated from Fivetran tasks to get insight into your data pipelines.

March 7, 2023

How to easily test your Airflow DAGs with the new dag.test() function

In this “Live with Astronomer” session, we’ll dive into the new `dag.test()` function, which allows you to debug DAGs directly in your IDE in a single, serialized Python process. We’ll show how this function lets you quickly iterate and debug errors during your DAG development, and even test argument-specific DAG runs.

February 28, 2023

Astronomer Webinars

Introducing Astro Observe: Pipeline-level Observability

The State of Airflow 2025

Modernizing Data Workflows: Moving from legacy schedulers to Airflow

Watch Recorded Webinars On-Demand

How to Orchestrate Machine Learning Workflows with Airflow

How to Orchestrate Databricks Jobs Using Airflow

How to Automate and Scale Data Ingestion with Fivetran and Airflow

How to easily test your Airflow DAGs with the new dag.test() function

How to Improve Data Quality with Airflow's Great Expectations Operator

How to Save Money using Airflow’s asynchronous Azure operators

Simplified DAG Authoring with New Airflow Features

The Airflow Templates VS Code Extension

Debugging your Airflow DAGs

Build, run, & observe
your data workflows.
All in one place.

Astronomer Webinars

Watch Recorded Webinars On-Demand

Build, run, & observe your data workflows. All in one place.

Build, run, & observe
your data workflows.
All in one place.