| 10:30-10:55 |
Scaling ML Infrastructure: Lessons from Building Distributed Systemsby Ashok Prakash |
| 11:00-11:25 |
How Pinterest Uses Ai to Empower Airflow Users for Troubleshootingby Rachel Sun |
| 11:30-11:55 |
From Oops to Secure Ops: Self-Hosted AI for Airflow Failure Diagnosisby Nathan Hadfield |
| 12:00-12:25 |
5 Simple Strategies To Enhance Your DAGs For Data Processingby William Orgertrice |
| 12:30-12:55 |
Scaling and Unifying Multiple Airflow Instances with Orchestration Frederatorby Chirag Todarka & Alvin Zhang |
| 14:00-14:25 |
A Decade in Data Engineering - Lessons Realities and Where We Go From Hereby Ben Rogojan |
| 14:30-14:55 |
Simplifying Data Management with DAG Factoryby Katarzyna Kalek & Jakub Orlowski |
| 15:00-15:25 |
DAGnostics: Shift-Left Airflow Governance with Policy Enforcement Frameworkby Yifan Wang |
| 15:45-16:10 |
Enabling SQL testing in Airflow workflows using Pydantic typesby Gurmeet Saran & Kushal Thakkar |
| 16:15-16:40 |
Model Context Protocol with Airflowby Abhishek Bhakat & Sudarshan Chaudhari |