Webinars

Operational Data Maturity: What Separates AI Leaders from AI Experimenters

Learn how operational data maturity separates AI leaders from experimenters, with lessons from GEODIS.

Production-Ready ELT Pipelines with Airflow 3 and Snowflake

In this webinar, we'll walk through everything you need to build reliable, production-ready ELT pipelines using Airflow and Snowflake — how Astronomer's own data team runs their pipelines in production.

Best practices for Dag authoring in Airflow

Dag authoring doesn’t have to be slow and manual. Airflow 3 features, Blueprint, and Airflow Skills agents offer more efficient ways to author, review, and improve Dags, for data engineers and the analysts they support. In this webinar, we’ll walk through the modern way to author Dags end-to-end.

Local data engineering in the agentic era

Hallucinations, outdated syntax, and code that does not follow best practices are the result of missing context and AI tools that don't understand your codebase. In this hands-on webinar, we will walk you through a modern local Airflow development setup built for the agentic era.

Best Practices for Running Apache Airflow® in Production

Airflow is built to scale, with data teams at OpenAI and GitHub running thousands to millions of tasks every day. But as deployments multiply, so does the operational burden: managing disjointed deployments across different systems, manually provisioning workers, and debugging failures across dependencies. In this webinar, we'll share the operational best practices that keep Airflow running reliably as your deployments grow.

Bonnes pratiques pour utiliser Airflow à grande échelle

Des leaders mondiaux comme Uber et LinkedIn s'appuient sur Apache Airflow® pour orchestrer des centaines de milliers de tâches quotidiennement. Cependant, pour faire passer à l'échelle plusieurs déploiements de manière efficace, il est crucial d'optimiser la gestion des ressources, de fluidifier le cycle de développement et de garantir une observabilité robuste. L'enjeu : éliminer les goulots d'étranglement techniques et booster la productivité de vos développeurs.

AI Context Engineering with Apache Airflow®

This webinar breaks down how to build a self-improving AI agent for customer support with Airflow: from ingesting and transforming data from multiple sources into AI-ready context, to tracing human and agentic decisions and structuring them into a context graph.

Airflow 2 End-of-life: Plan your upgrade to Airflow 3

Apache Airflow® 3.0 was the biggest release in Airflow’s history with features including Dag versioning, remote execution, and more. With the recent releases of version 3.2 and open-source Airflow 2 reaching end-of-life on April 22, 2026, it's never been more urgent to upgrade. In this webinar, we’ll cover everything you need to plan a smooth upgrade from Airflow 2 to 3, without breaking your workflows or stretching your team thin.

Introducing Apache Airflow® 3.2

Airflow 3.2 brings advances in asset/data-awareness functionality, expansion of key integrations, and improvements to core Airflow. This webinar provides a comprehensive look at the new release and shows you practical ways you can leverage these updates in your own environments.

Hands-on Workshop: Building ETL/ELT pipelines with Apache Airflow® 3

In this hands-on workshop, you will learn essential ETL/ELT patterns using Airflow's most powerful features, all in your browser, no setup required. Work through a realistic scenario processing interplanetary travel data for AstroTrips, a fictional space tourism company.

How to run Airflow-as-a-Service in regulated environments

In this webinar, we’ll show how platform teams at enterprises like Northern Trust and Autodesk run Airflow-as-a-service in their own environments – delivering a standardized, secure orchestration service at scale, without the operational burden.

Stopping bad data before it breaks your Airflow pipelines

In this webinar, we’ll cover everything you need to know about both approaches to data quality, including when to choose Dag-level checks, platform-level checks, or both and more.

Best practices for writing ETL/ELT pipelines

Airflow is specifically designed for moving and transforming data in ETL/ELT pipelines, and new features in Airflow 3 like assets, backfills, and event-driven scheduling make orchestrating ETL/ELT pipelines easier than ever.

Best practices for writing ETL/ELT pipelines (AEDT)

Learn ETL vs ELT best practices with Apache Airflow 3. Join our webinar on Feb 19, 2026 at 11am AEDT for scalable, dynamic ETL/ELT pipelines.

Stop Reacting, Start Preventing: Observability at the Orchestration Layer

In this webinar, Ashley Kuhlwilm, Senior Product Marketing Manager, will share how to enable proactive monitoring by moving observability upstream.

Data Orchestration in Azure: Patterns for Scale and Reliability

In this webinar, we’ll share why leading enterprises are standardizing on Apache Airflow, then walk through your options for running an Airflow-based orchestration strategy in Azure.

The State of Apache Airflow® 2026

Join us to hear directly from leaders in the community and discover how to get the most out of Airflow in the year ahead.

Apache Airflow® 3 Certification Crash Course

Join Airflow expert Marc Lamberti, creator of Data with Marc, for a fast-track, expert-led introduction to Apache Airflow 3 fundamentals designed to help you confidently prepare for the official Airflow 3 certification exam.

Best practices for debugging your Airflow Dags

Join this webinar to learn a systematic approach for fixing pipeline failures and how to future proof your Dags to make them more reliable and easier to debug.

From Apache Airflow® 2 to 3: How to plan your upgrade

In this webinar, you’ll learn how to successfully upgrade to Airflow 3 to start using the recently released features, including Dag versioning, event-driven scheduling, and remote execution.

Implementing CI/CD workflows for your Airflow pipelines

Learn how to leverage CI/CD to develop faster, more securely, and more reliably by automating key parts of your pipeline development lifecycle.

How to automate Airflow operations with Astro

Join us for a 30-minute live demo to learn how Astro, the fully-managed DataOps platform built on Apache Airflow®, eliminates time-consuming operations work.

Production-Ready ELT Pipelines with Airflow 3 and Snowflake

Discover how Airflow 3 streamlines data operations in Snowflake. This session covers building an end-to-end ETL pipeline featuring Snowflake Stages, automated validation, and human-in-the-loop integration.

Build vs Buy? How to choose your Airflow strategy

We’ll break down what it really takes to run Airflow, including installation, infrastructure setup, and ongoing maintenance, and share how a fully-managed service can help simplify those challenges.

Best practices for running Airflow at scale

This session explores how to optimize configurations, automate infrastructure, and improve workflow development so you can run Airflow efficiently at scale.

Modernizing Your Data Stack: Replacing Legacy Schedulers with Apache Airflow

Legacy schedulers can slow delivery and limit flexibility as teams move to the cloud or prepare for AI initiatives. This session outlines a practical blueprint for modern orchestration with Airflow that ensures reliable, scalable data pipelines.

What's new in Apache Airflow® 3.1

In this webinar, we’ll highlight the most important Apache Airflow 3.1 updates you won’t want to miss.

Best practices for writing ETL/ELT pipelines

Be among the first to see Airflow 3 in action and get your questions answered directly by the Astronomer team.

The best way to orchestrate your dbt workflows with Airflow

In this webinar, we’ll cover everything you need to know about using dbt and Airflow together.

How to write better DAGs in Airflow

Whether you’re writing traditional ELT/ETL pipelines or complex ML workflows, you’ll learn how to make Airflow work best for even your most critical data products.

How to increase the reliability of your Airflow pipelines

In this webinar, Maggie Stark, Staff Data Engineer at Astronomer, will share how Astronomer’s data engineering team reduced DAG failure rates by 81%.

Best practices for debugging and testing Airflow pipelines

Learn how to easily and effectively debug your DAGs and implement testing so issues don’t make it to production.

Best Practices for Running Airflow at Scale

Whether engineering resilient pipelines or managing scalable Airflow infrastructure, this session will equip you with actionable insights for successful Airflow operations.

Airflow 3 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

Why Data Observability Needs an Orchestration-First Approach

In this session, we explore how the next generation of observability is shifting into the orchestration layer to help teams detect and resolve issues faster, reduce blind spots, and increase trust in their data.

Best practices for Upgrading to Airflow 3

In this webinar, we’ll cover everything you need to know to plan your upgrade path from Airflow 2 to 3, so you can start taking advantage of the new features as soon as possible.

From Zero to Production: Orchestrating LLM workflows with the Airflow AI SDK

We’ll introduce the open-source AI SDK for Apache Airflow, built to simplify the creation of production-ready LLM workflows.

New in Airflow 3: Data Assets and Event-Driven Scheduling Deep Dive

Learn how Airflow 3 is expanding on assets, the foundational datasets feature, by introducing asset watchers, the most powerful option for event-driven scheduling in Airflow to date

Optimizing your Airflow Developer Experience: Exploring DAG Versioning and Backfills

Explore how Airflow 3 features like DAG versioning and backfills can improve productivity, simplify troubleshooting, and help you manage pipeline history more efficiently.

Introducing Apache Airflow® 3.0

Be among the first to see Airflow 3 in action and get your questions answered directly by the Astronomer team.

Best Practices for Building Secure Data Pipelines with Apache Airflow®

Hosted with DZone, this session covers practical security measures for protecting credentials, maintaining compliance, and ensuring reliable production ready data pipelines.

Migrating Airflow off ADF? Evaluating Astro vs. Fabric

Join us to learn why top data teams are choosing Astro on Azure instead of Microsoft Fabric for their mission-critical Airflow workloads.

Modernizing Data Workflows: Moving from legacy schedulers to Airflow

Learn how Airflow helps you deliver workflows faster, reduce downtime, and scale operations. See how Astronomer's Orbiter tool simplifies migration from legacy systems to modern orchestration.

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.

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.

Introducing Astro Observe: Pipeline-level Observability

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).

Implementing CI/CD workflows for your Airflow pipelines

In this session, you’ll learn everything you need to know about using CI/CD to manage your Airflow DAGs.

Astro 101 Webinar: An Introduction to fully-managed Airflow

In this session, we’ll introduce how you can enhance your data workflows by running Airflow with Astro.

Best practices for running Airflow at scale

In this webinar, we’ll cover best practices for running Airflow at scale so you can provide your teams with a robust, reliable Airflow service.

Data Engineering Digest and Astronomer | The Ultimate Guide to DAG Writing

In this webinar hosted with Data Engineering Digest, Tamara Fingerlin, Developer Advocate at Astronomer, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust.

Airflow best practices: debugging and testing

In this webinar, you'll learn how to easily and effectively debug your DAGs when an error inevitably occurs, and implement testing so issues don’t make it to production.

How to Orchestrate Databricks Jobs Using Airflow

In this webinar, you’ll learn how to use Airflow to orchestrate your Databricks Jobs by using the Airflow Databricks Provider.

Introduction to Observability for Data Pipelines

In this webinar, we’ll give an overview of data observability for Airflow, including topics like tracking data lineage, monitoring data quality, and insights into the performance of your data operations.

DAG Writing Best Practices

Whether you’re writing traditional ELT/ETL pipelines or complex ML workflows, you’ll learn how to make Airflow work best for your use case.

Best practices for writing ETL and ELT pipelines

In this webinar, we’ll cover DAG writing best practices applicable to ETL and ELT pipelines, including things like how to approach building ETL and ELT pipelines from scratch.

How to orchestrate your dbt workflows with Airflow

In this webinar, we’ll discuss Cosmos and Astro features in depth, including native support for installing and running dbt in a virtual environment to avoid dependency conflicts with Airflow.

Implementing reliable ETL & ELT pipelines with Airflow and Snowflake

In this webinar, we’ll cover everything you need to know to orchestrate ETL operations in Snowflake with Airflow.

How to build reliable data products with Astro

We’ll cover how we think about data products at Astronomer and highlight best practices learned from the most critical data product applications we’ve seen.

What's new in Airflow 2.10

The release of Airflow 2.10 brings greater flexibility and expansion of some of the most widely used features. In this webinar, we’ll cover all the significant 2.10 updates that you won’t want to miss.

Modern Infrastructure for World Class AI Applications

In this webinar, Astronomer and Weaviate cover how they are providing modern infrastructure for world class AI applications, and how to best build production-quality applications with the latest advances in ML and AI.

Q2 2024 Astro Release: Seamlessly Integrate dbt with Astro

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.

Best Practices for Effectively Running dbt in Airflow

This webinar covers a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code.

Learn from the experts: how to write data pipelines with Airflow

This webinar is designed for those new to Airflow, providing a thorough introduction to its core concepts and practical applications.

How Grindr uses Airflow to monitor and optimize Snowflake usage

In this webinar, Matt Shancer, Staff Data Engineer at Grindr, will discuss how they implemented their Snowflake monitoring solution using Astronomer.

Optimize your developer workflows with CI/CD

Join us to deepen your understanding of CI/CD and learn best practices for more efficient data pipeline management.

Driving Next-Gen AI Applications with AWS and Astronomer

In this webinar, resident AI/ML experts from AWS and Astronomer explore top strategies to harness the potential of AI and natural language processing to drive innovation.

Optimizing ML/AI Workflows with Essential Airflow Features

In this webinar, you’ll learn best practices for using the latest Airflow features, including those recently released in Airflow 2.9, for generative AI and general machine learning use cases.

What’s new in Airflow 2.9

In this webinar, we’ll cover all the significant 2.9 updates that you won’t want to miss. We’ll spend extra time on updates that expand the functionality of some of Airflow’s most widely used features.

What’s New in the Astro Platform Release, Q1 2024

The latest release of Astro, Astronomer’s fully managed Airflow platform, contains exciting new features that let you deploy faster, and give you greater operational efficiency, and increased visibility, security, and growth potential.

How to orchestrate Azure Data Factory jobs with Airflow

In this webinar, we’ll cover everything you need to know about using Airflow and ADF together.

2024 Apache Airflow®: Trends and Insights

Join us for an in-depth analysis of the 2023 Apache Airflow® survey, where our panel of experts explore insights into how Airflow is used across industries for data orchestration and workflow management.

Best practices for managing Airflow across teams

In this webinar, we’ll cover best practices for running Airflow at scale in production so you can provide your teams with a robust, reliable Airflow service.

DAG writing for data engineers and data scientists

In this webinar, we’ll cover DAG writing best practices applicable to data engineers and data scientists.

How to manage connections in Airflow

In this webinar, we will cover everything you need to know about managing connections in Airflow.

What’s new in Airflow 2.8

In this webinar, we’ll cover all the significant Apache Airflow® 2.8 updates that make Airflow more flexible and easy to use.

Orchestrate next-generation AI tools: Explore six new Airflow providers

A paradigm shift occurred leading to the formation of the large language model operations (LLMOps) modern data stack with Apache Airflow® right at the center. Join us in this webinar to explore these providers and learn how you can leverage them to take your LLMOps to the next level.

What’s New in the Astro Platform Release, Q4 2023

This webinar will provide a comprehensive overview of the new features in the latest Astro release, complete with live demos. Whether you're already using Astro or considering it for your data orchestration needs, don't miss this opportunity to learn from the experts and have your questions answered.

Airflow at Faire: Democratizing Machine Learning at Scale

In this webinar, we’ll dive into this story with Faire and discuss how Faire leverages Airflow to power ML training and extends it with a framework that powers feature stores.

Deliver Data with Precision: Supercharge your Airflows with Apache Airflow® on Astro - An Azure Native ISV Service

Join us for this live webinar on November 29th to learn how Apache Airflow® on Astro - An Azure Native ISV Service provides an enterprise-grade Apache Airflow platform.

Intro to Airflow: Get Started Writing Pipelines for Any Use Case

Data professionals all over the world use Airflow for MLOps, LLMOps, ELT/ETL, operationalized analytics, and more. In this webinar, we’ll cover everything you need to get started with Airflow,

Run LLMOps in production with Apache Airflow®

Join us in this webinar where we’ll show how to use the Ask Astro LLMOps reference architecture to create your own retrieval augmented LLM application, feeding state of the art models with domain specific knowledge.

The Laurel Algorithm: MLOps, AI, and Airflow for Perfect Timekeeping

In this webinar, you will get a behind-the-scenes look at how Laurel accelerated their AI journey with Airflow to stand at the forefront of ML innovations.

Programmatic workflow management with the Airflow and Astro APIs

In this webinar, we’ll show how to level-up your Airflow usage by leveraging both the Airflow API and Astro API to automate common workflow management tasks. If you find yourself frequently completing the same steps in the Airflow UI and want greater efficiency, this is the webinar for you!

Power your LLMOps with Airflow’s Weaviate Provider

In this webinar, we’ll show how to use the new Weaviate provider to make the most of Airflow’s orchestration power for AI and ML use cases.

Develop ML Pipelines with the Astro Cloud IDE

In this webinar, we’ll show how the Astro Cloud IDE is the easiest way to develop and test your ML pipelines and schedule them with Airflow.

Efficient data quality checks with Airflow 2.7

In this webinar, we’ll cover everything you need to know about setup/teardown tasks and how to use them to support your data quality checks.

Swinging for Success: How Big Data is Redefining the Texas Rangers' Playbook

In this webinar, you will get a behind-the-scenes look at how the Texas Rangers, a team at the forefront of this transformation, are using big data to deliver real-time game analytics and gain a competitive advantage.

What’s New in Airflow 2.7

In this webinar, we’ll cover all the great 2.7 updates that make it even easier to implement your pipelines in Airflow.

Hands-on Workshop: automate your data ingestion with Fivetran and Astronomer

In this free, virtual workshop, you’ll get hands-on experience setting up a data ingestion pipeline with Fivetran and Astronomer.

How to deploy your Airflow pipelines with CI/CD

In this webinar, we’ll show how you can use CI/CD with Airflow to manage the deployment and testing of your DAGs. We’ll discuss the benefits of CI/CD for data pipelines, how to select an appropriate deployment strategy, and more.

The Astro CLI: the easiest way to get started with Airflow

Recent releases of the Astro CLI have greatly expanded its functionality, bringing additional features for debugging, testing, and upgrading DAGs. In this webinar, we’ll show you how to get started with the Astro CLI and how to take advantage of these new features.

Introducing Cosmos: The Easy Way to Run dbt Models in Airflow

In this webinar, we’ll show you how Cosmos can be used to dynamically generate Airflow DAGs from your dbt models.

How to expertly organize your DAGs with task groups

In this webinar, we’ll cover everything you need to know to use task groups both in simple and advanced ways.

Astro Cloud IDE: Write data pipelines with no Airflow setup

Build data pipelines effortlessly! Discover Astro Cloud IDE's simple notebook interface, custom operator creation, and direct deployment. Start coding now!

Scheduling in Airflow: A Comprehensive Introduction

In this webinar, we’ll cover everything you need to know to use both simple and advanced scheduling methods

How to use Snowpark with Airflow

In preparation for the upcoming Snowflake Summit, we’re excited to host a webinar on the best ways to use Snowpark with Apache Airflow®.

Streamlining Data Pipelines with Sophi: An Airflow Journey

Sophi.io, a leading AI-powered content optimization platform, faced scale challenges as their data pipeline grew using Apache Airflow®. Learn how Sophi optimized their data pipelines after migrating from Amazon Managed Workflows for Apache Airflow® (MWAA) to Astronomer and dramatically improved their data pipeline scalability and reliability.

Airflow 101: How to get started writing data pipelines with Apache Airflow®

Apache Airflow® is an open source tool for authoring, scheduling, and monitoring your data pipelines In this webinar, we’ll cover everything you need to get started with Apache Airflow®.

How to monitor your pipelines with Airflow and Astro alerts

In this webinar, we’ll show how Airflow’s notifications and Astro’s deployment and pipeline monitoring and alerting ensure you always know what’s going on in your pipelines.

Implementing data quality checks with the Astro SDK

In this webinar, we’ll give an overview of the Astro SDK and how it can be used to create ELT pipelines with integrated data quality checks in Python or SQL. We’ll cover everything you need to get started using this open source tool to ensure errant data never ends up in production.

How Astro makes Airflow upgrades easy and painless

In this webinar, we’ll cover everything you need to know about managing Airflow versions with Astro Runtime.

What’s New in Airflow 2.6

Simplified DAG authoring with the Astro SDK

In this “Live with Astronomer” session, we’ll give an overview of the Astro SDK and show how it makes writing ELT pipelines easy and efficient. We’ll cover everything you need to get started using this open source tool in just a few minutes.

The easiest way to orchestrate your dbt workflows from Airflow

In this webinar, we’ll cover the new, open-source Astronomer Cosmos tool, a framework for dynamically generating Airflow DAGs from your dbt models that massively simplifies the Airflow-dbt integration.

How to use DuckDB with Airflow

In this “Live with Astronomer” session, we’ll dive into the best ways to use DuckDB with Airflow.

How to pass data between your Airflow tasks

In this webinar, we’ll cover the implementation and nuances of different methods for passing data between your Airflow tasks.

How to test and debug your Airflow connections

We’ll dive into the easiest ways to test and debug your Airflow connections. We’ll show how the new `dag.test()` function allows you to test connections without even running Airflow, how new Airflow UI features make testing connections faster, and how to solve common issues that arise when working with connections.

4 Things To Consider When Deciding How to Run Airflow

Teams can run Airflow themselves, go with a managed infrastructure option like MWAA and GCC, or choose Astro. Whether you’ve been running Airflow in production for years or if you’re just thinking about the right Airflow strategy is for your team, we’ll go through all the options available.

Astro Product Roadmap

Join the Astronomer team to learn more about upcoming Astro features and our product roadmap.

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.

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.

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.

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.

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

In this webinar, Airflow Engineering Advocate Benji Lampel will demonstrate the new features of the Great Expectations Operator, which make Great Expectations more Airflow-centric and simpler to use. The latest set of releases under the new repository hosted by Astronomer provides some dramatic changes, including a default Checkpoint feature. The webinar will feature a demo of the new operator and how to use these features.

How to Save Money using Airflow’s asynchronous 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.

Simplified DAG Authoring with New Airflow Features

In this webinar, we’ll cover best practices for implementing important open-source features and frameworks that will simplify the DAG-authoring process.

The Airflow Templates VS Code Extension

In this “Live with Astronomer” session, we’ll walk through one of those contributions – new Airflow Templates VS Code extension, which includes code completion for all Airflow Provider operators.

Debugging your Airflow DAGs

In this webinar, you'll learn how to easily and effectively debug your DAGs when an error inevitably occurs.

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.

What’s New in Airflow 2.5

In this webinar, we’ll cover all the great 2.5 updates that make Airflow even easier to use and implement at scale.

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.

Airflow 101: Essential Tips For Beginners - Dec 2022

What is Airflow? Apache Airflow® is a platform used to programmatically author, schedule, and monitor data pipelines.

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

Running tasks in a separate environment can help you avoid common data pipeline issues, like dependency conflicts or out-of-memory errors, and it can save resources. 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

Migrating between orchestrators can be a difficult process fraught with technical and organizational hurdles. However, the end result of applying Airflow’s orchestration capabilities is worth the effort, and working with the right partner can make this journey much easier. In this webinar, we’ll cover everything you need to know about migrating from Oozie to Airflow.

The New DAG Schedule Parameter

Live with Astronomer will discuss the new consolidated `schedule` parameter introduced in Airflow 2.4. 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.

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

The next Live with Astronomer will dive into the Astro Python SDK load_file function. 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 load_file for the ‘Extract’ step of your pipeline to easily get data from your filesystems into your data warehouse, without any operator-specific knowledge.

The Astro Python SDK

Astronomer is excited to announce the release of the Astro Python SDK version 1.0. The Astro Python SDK is an open source tool powered by Airflow and maintained by Astronomer, that allows for rapid and clean development of ETL workflows using Python.

The SQL Table Check Operator

In this session we’ll dive into the new Common SQL provider package and show how to use the SQLTableCheckOperator. We’ll show how you can easily use this operator to implement data quality checks in your DAGs, ensuring that errant data never makes it to production.

Airflow 101: Essential Tips For Beginners - Aug 2022

What is Airflow? Apache Airflow® is a platform used to programmatically author, schedule, and monitor data pipelines.

The SQL Column Check Operator

In this session we’ll show how you can easily use the SQLColumnCheckOperator operator to implement data quality checks in your DAGs, ensuring that errant data never makes it to production.

Using Airflow with Tensorflow and MLFlow

We’ll delve further into how Airflow can be integrated with Tensorflow and MLFlow specifically to manage ML pipelines in production, using a worked example to demonstrate.

Reusable DAG Patterns with TaskGroups

In this session we’ll show how Astronomer’s data and intelligence team uses TaskGroups to reduce the amount of code the team has to write while adhering to DAG authoring best practices.

Anatomy of an Operator

Operators are the building blocks of Apache Airflow®. In this webinar we’ll look under the hood, covering everything you need to know about operators to tailor them for your use cases.

Using the Snowflake Deferrable Operator

Live with Astronomer will dive into using the Snowflake Deferrable Operator. We’ll show how with a very small update to your DAGs, you can start saving money when orchestrating your Snowflake queries with Airflow.

Writing Functional DAGs with Decorators

In this webinar, we’ll demystify decorators and show you everything you need to know to start using decorators in your DAGs.

The Python Task Decorator

Live with Astronomer will dive into the Python task decorator. We’ll show how to easily turn your Python functions into tasks in your DAG using functional programming, and how using the Python task decorator can limit the boilerplate code needed in your DAGs.

Intro: Getting Started with Airflow

What is Airflow? Apache Airflow® is a platform used to programmatically author, schedule, and monitor data pipelines.

Dynamic Task Mapping

On May 24, Live with Astronomer will dive into the Dynamic Task Mapping feature introduced in Airflow 2.3. We’ll show how to easily add dynamic tasks to your DAGs, and discuss ways to make the best use of this feature.

Astronomer Providers

This webinar will dive into the Astronomer Providers repository, which includes Airflow Providers containing Deferrable Operators and Sensors created by Astronomer. We’ll go beyond the basics to look at key implementation details and best practices.

What’s New in Airflow 2.3

The Airflow project is rapidly evolving, with frequent releases bringing advancements in DAG authoring, observability, and project stability. We’re super excited for the release of Airflow 2.3, which comes with big changes in the flexibility of DAG creation, improvements to the Airflow UI, and much more.

Using Airflow as a Data Analyst

Airflow is sometimes thought of as primarily a data engineering tool, but its use cases are really much broader. A data analyst’s workflow typically involves ingesting and transforming data to extract insights, then presenting the insights in a manner that allows business stakeholders to easily interpret trends and take appropriate action. Airflow’s ease of use and extensive provider ecosystem make it an ideal tool for orchestrating such analytics workflows.

OpenLineage and Airflow: A Deeper Dive

Data lineage is the complex set of relationships between your jobs and datasets. Using OpenLineage with Apache Airflow®, you can observe and analyze these relationships, allowing you to find and fix issues more quickly. This webinar will provide a deeper dive on OpenLineage, extending beyond the basics into key implementation details and best practices.

Improve Your DAGs with Hidden Airflow Features

Apache Airflow® is flexible and powerful. It has a rich ecosystem and an incredibly active community. But are you sure you haven’t missed anything? A new feature or concept that could put your DAGs at another level? It can be challenging to keep up with the latest Airflow features, and sometimes we miss the most useful ones. For this webinar, I'd like to introduce you to a couple of lesser-known features of Apache Airflow® that can dramatically improve your data pipelines.

Scaling Out Airflow

Airflow is purpose-built for high-scale workloads and high availability on a distributed platform. Since the advent of Airflow 2.0, there are even more tools and features to ensure that Airflow can be scaled to accommodate high-throughput, data-intensive workloads. In this webinar, Alex Kennedy will discuss the process of scaling out Airflow utilizing the Celery and Kubernetes Executor, including the parameters that need to be tuned when adding nodes to Airflow and the thought process behind deciding when it’s a good idea to scale Airflow, horizontally and vertically. Consistent and aggregated logging is key when scaling Airflow, and we will also briefly discuss best practices for logging on a distributed Airflow platform, as well as the pitfalls that many Airflow users experience when designing and building their distributed Airflow platform.

Data Quality Use Cases with Airflow and Great Expectations

At this webinar, Benji Lampel (Enterprise Platform Architect @ Astronomer) and Tal Gluck (Software Engineer @ Superconductive) will present several Airflow DAGs using Great Expectations that cover more advanced DAG patterns and data quality checking cases.

The Airflow API

Did you know that Airflow has a fully stable REST API? In this webinar, we’ll cover how to use the API, and why it’s a great tool in your Airflow toolbox for managing and monitoring your data pipelines.

Introducing Astro: Data Centric DAG Authoring

With Airflow 2.0, we introduced the concept of providers. We’re taking that to the next level with Astro, a new DAG writing experience, brought to you by Astronomer.

Data Lineage with OpenLineage and Airflow

If one out of your hundreds of DAGs fails, how do you know which downstream datasets have become out-of-date? The answer is data lineage. Data lineage is the complex set of relationships between your jobs and datasets. In this webinar, you'll learn how to use OpenLineage to collect lineage metadata from Airflow and assemble a lineage graph - a picture of your pipeline worth way more than a thousand words.

Best Practices for Writing DAGs in Airflow 2

Because Airflow is 100% code, knowing the basics of Python is all it takes to get started writing DAGs. However, writing DAGs that are efficient, secure, and scalable requires some Airflow-specific finesse. In this webinar, you’ll learn the best practices for writing DAGs that will ensure you get the most out of Airflow. We’ll include a reference repo with DAGs you can run yourself with the Astro CLI.

Iterative Data Quality in Airflow DAGs

Data quality is an often overlooked component of data pipelines. Learn why it is a valuable part of data systems and how to get started integrating data quality checks into existing pipelines with a variety of tools.

Intro to Apache Airflow® Orchestration and Data Organization

With Apache Airflow®'s orchestration capabilities, manage your data like never before. Discover how to leverage Airflow in any company.

Scheduling In Airflow

The flexibility and freedom that Airflow offers you is incredible, but to really take advantage of it you need to master some concepts first, one of which has just been released in Airflow 2.2 By the end of the webinar, you will be able to define schedule intervals that you thought were impossible before.

Everything you Need to Know About Airflow 2.2

In this informative webinar we will cover everything you need to know about Airflow 2.2. We'll go through all of the new features large and small, as well as show you how to leverage all of the new features and how you can get cleaner and more efficient DAGs as a result

Testing Airflow to Bullet Proof Your Code

Airflow, by nature, is an orchestration framework, not a data processing framework. At first sight it can be unclear how to test Airflow code. Are you triggering DAGs in the UI to validate your Airflow code? In this webinar we'll demonstrate various examples how to test Airflow code and integrate tests in a CI/CD pipeline, so that you're certain your code works before deploying to production.

Manage Dependencies Between Airflow Deployments, DAGs, and Tasks

More often that not, your Airflow components will have a desired order of execution particularly if you are performing a traditional ETL process—for example, before the Transform step in ETL, Extraction had to have happened in an upstream pipeline. In this webinar we will discuss how to properly setup dependencies and define an order of execution or operation for your pipelines using dependencies.

Create Powerful Data Pipelines by Mastering Sensors

Do you use Sensors in your data pipelines? Do you need to wait for a file before executing the next step? Are you looking to execute your task after a task completes in another DAG? Would you like to wait for an import in your SQL table before executing the next task?

Using Airflow with Azure Data Factory

While Airflow and ADF (Azure Data Factory) have pros and cons, they can be used in tandem for data pipelines across your organization. In this webinar, we’ll cover how using the two together can really get you the best of both worlds!

Monitor Your DAGs with Airflow Notifications

Anytime you’re running business critical pipelines, you need to know when something goes wrong. Airflow has a built in notification system that can be used to throw alerts when your DAGs fail, succeed, or anything in between. In this webinar, we’ll do a deep dive into how you can customize your notifications in Airflow to meet your needs.

Intro to Airflow for ETL With Snowflake

ETL is one of the most common data engineering use cases, and it's one where Airflow really shines. In this webinar, we'll cover everything you need to get started as a new Airflow user, and dive into how to implement ETL pipelines as Airflow DAGs.

Getting Started With the Official Airflow Helm Chart

The official helm chart of Apache Airflow® is out! The days of wondering what Helm Chart to use in production are over. Now, you only have one chart maintained and tested by Airflow PMC members as well as the community. It’s time to get your hands on it and take it for a spin! At the end of the webinar, you will have a fully functional Airflow instance deployed with the Official Helm Chart and running within a Kubernetes cluster locally.

Dynamic DAGs

In this webinar, we'll talk about when you might want to dynamically generate your DAGs, show a couple of methods for doing so, and discuss problems that can arise when implementing dynamic generation at scale.

Using Airflow with Multiple AWS Accounts

In AWS, it's common for organizations to use multiple AWS accounts for various reasons, from Dev, Stage, Prod accounts to accounts being dedicated to LOBs. What do you do when your Data Pipeline needs to span AWS accounts? This webinar will show how you can run a single DAG across multiple AWS accounts in a secure manner.

Intro to Airflow

Learn about the core concepts, components, and benefits of working with Airflow. Watch this Intro to Airflow webinar today!

Airflow 2.0 + Kubernetes

Learn more about using Airflow 2.0 with Kubernetes.

Airflow 2.0 Providers

Learn everything about Airflow 2.0 providers including what defines a provider, how to create your own provider, and customizing provider packages.

TaskFlow API in Airflow 2.0

Watch the webinar recap and learn how Taskflow API can help simplify DAGs that make heavy use of Python tasks and XComs.

Secrets Management in Airflow 2.0 - March 2021

Watch the webinar recording to learn the best practices for managing secrets with various backends in Apache Airflow® 2.0.

DAG Writing Best Practices in Apache Airflow®

Learn the best practices for writing DAGs in Apache Airflow® with a repo of example DAGs that you can run with the Astro CLI.