| 09:15-10:00 |
Airflow as a Platform for Agentic AI Digital Products Within Enterprisesby Peeyush Rai & Vikram Koka |
| 10:30-10:55 |
Orchestrating MLOps and Data Transformation at EDB with Airflowby Karthik Dulam |
| 11:00-11:25 |
Your privacy or our progress: rethinking telemetry in Airflowby Bolke de Bruin |
| 11:30-11:55 |
Orchestrating AI Knowledge Bases with Apache Airflowby Theo Lebrun |
| 12:00-12:25 |
Airflow Uses in an on-prem Research Settingby Lawrence Gerstley |
| 12:30-12:55 |
Common provider abstractions: Key for multi-cloud data handlingby Vikram Koka |
| 14:00-14:25 |
From Cron to Data-Aware: Evolving Airflow Scheduling at Scaleby Yunhao Qing |
| 14:30-14:55 |
Learn from Deutsche Bank: Using Apache Airflow in Regulated Environmentsby Christian Foernges |
| 15:00-15:25 |
Modernizing Automation in Secure, Regulated Environments: Lessons from Deploying Airflowby Oluwafemi Olawoyin |
| 15:45-16:10 |
Fine-Tuning Airflow: Parameters You May Not Know Aboutby Yu Lung Law & Ivan Sayapin |
| 16:15-16:40 |
No More Missed Beats: How Airflow Rescued Our Analytics Pipelineby pei-chi-miko-chen |
| 16:45-17:10 |
Lessons learned for building open source Airflow operators at AWSby Yuhang Huang & Arunav Gupta |
| 17:30-17:35 |
Lightning talk: Supercharging Apache Airflow: Enhancing Core Components with Rustby Shahar Epstein |