The Astronomer Blog: Data Orchestration Insights & Guides

October 11, 2023

Databricks vs. Airflow From a Management Perspective, Part 2

Databricks vs Airflow from a production management perspective. Explore the differences in setup, monitoring, integrations, scalability & customization.

October 10, 2023

ML for Customer Analytics with Airflow, Snowpark, and Weaviate

An example project showing how to use Apache Airflow® to orchestrate a machine learning pipeline with the Snowpark provider and Snowpark ML.

October 6, 2023

Migrate Python Jobs to Airflow in 4 Simple Steps

Learn how easy it is to migrate Python scripts to Airflow DAGs, streamline orchestration, and leverage Airflow features to boost job efficiency.

September 29, 2023

3 Key Takeaways from Airflow Summit 2023

Last week, the first-ever in-person Airflow Summit occurred in Toronto, Canada. Over 500 attendees from 20+ countries came together for all things Airflow, orchestration, and open source.

September 22, 2023

Ask Astro: An open source LLM Application with Apache Airflow®, Part 2

Build an LLM-powered chatbot with Airflow! Learn how to leverage domain-specific knowledge to create intelligent applications like "Ask Astro." Astro LLM meets Apache Airflow.

September 21, 2023

Day-2 Operations for LLM Applications with Apache Airflow®

Explore how Apache Airflow® solves day-2 operations challenges for LLM applications. Learn about scalable, reliable, and auditable workflows with Airflow.

September 8, 2023

Advanced Airflow CDC Implementation

Dive deeper into Airflow CDC implementation. Explore advanced use cases, best practices, and handle schema evolution & log-based sync effectively.

August 30, 2023

Comparing Data Orchestration: Databricks Workflows vs. Apache Airflow®, Part 1

Choosing the right data orchestration tool for your needs can be tough. This blog post compares Databricks Workflows and Apache Airflow, two popular options.

August 24, 2023

Debugging Airflow Made Easy: 3 Key Steps to Debug your DAGs

Learn how to debug Airflow DAGs in 3 key steps. Eliminate common issues, set up a local development environment, and implement testing for seamless Airflow workflows.

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