Building Event-Driven Data Pipelines With Airflow 3 at Astrafy with Andrea Bombino

Real-time data expectations are reshaping how modern data teams think about orchestration and dependencies. As event-driven architectures become more common, teams need to rethink how pipelines react to data changes, rather than schedules.In this episode, Andrea Bombino, Co-Founder and Head of Analytics Engineering at Astrafy, joins us to discuss how event-driven scheduling in Airflow is evolving and how Astrafy applies it to deliver faster, more responsive data pipelines.Key Takeaways:00:00 Introduction.02:02 Astrafy’s role in guiding clients across the modern data stack.03:15 Strong DAG dependencies create challenges for time-based scheduling.04:48 Event-driven pipelines respond to increasing real-time data demands.05:30 Airflow 3 introduces native support for event-driven orchestration.06:27 Sensor-based workflows reveal scalability and efficiency limitations.11:32 Event-driven assets improve efficiency and pipeline elegance.14:45 Governance and cross-instance coordination emerge as ongoing challenges.Resources Mentioned:Andrea Bombinohttps://www.linkedin.com/in/andrea-bombino/Astrafy | LinkedInhttps://www.linkedin.com/company/astrafy/Astrafy | Websitehttps://www.astrafy.ioApache Airflowhttps://airflow.apache.org/Google Cloudhttps://cloud.google.com/Google Pub/Subhttps://cloud.google.com/pubsubGoogle BigQueryhttps://cloud.google.com/bigqueryThanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.#AI #Automation #Airflow