| 10:30-10:55 |
Becoming an Apache Airflow Committer from 0by Zhe-You Liu |
| 11:00-11:25 |
Automating Threat Intelligence with Airflow, XDR, and LLMs using the MITRE ATT&CK Frameworkby Karan Alang |
| 11:30-11:55 |
Custom Operators in Action: A Guide to Extending Airflow's Capabilitiesby Shalabh Agarwal |
| 12:00-12:25 |
Enhancing Airflow REST API: From Basic Integration to Enterprise Scaleby Vishal Vijayvargiya |
| 12:30-12:55 |
Transforming Data Engineering: Achieving Efficiency and Ease with an Intuitive Orchestration Solutionby Rakesh Kumar Tai & Mili Tripathi |
| 14:00-14:25 |
Task failures troubleshooting based on Airflow & Kubernetes signalsby Khadija Al Ahyane |
| 14:30-14:55 |
Navigating Secure and Cost-Efficient Flink Batch on Kubernetes with Airflowby Purshotam Shah & Prakash Nandha Mukunthan |
| 15:00-15:25 |
AWS Lambda Executor: The Speed of Local Execution with the Advantages of Remoteby Niko Oliveira |
| 15:45-16:10 |
From Repetition to Refactor: Smarter DAG Design in Airflow 3by Steven Woods |
| 16:15-16:40 |
Lessons from Airflow gone wrong: How to set yourself up to scale successfullyby Annie Friedman & Caitlin Petro |
| 16:45-17:10 |
Scaling ML Infrastructure: Lessons from Building Distributed Systemsby Ashok Prakash |