Making Kubernetes Simpler for Accelerated Workloads - Panel
Kubernetes and the open-source ecosystem for AI frameworks have been great for LLM innovation, empowering developers to build applications that use natural language as the interface to data. Yet, many developers and cluster operators struggle to put these frameworks into production use. In this session, hear from several platform engineers responsible for designing core infrastructure supporting accelerated workloads, services, large language model training and inference pipelines. You can expect to come away with guidance, hear of pitfalls to watch out for and learn how they successfully abstracted the infrastructure complexity to improve their research users’ experience and velocity.
Panelists
- Susan Wu, Outbound Product Manager, Google
- Lucy Sweet, Senior Software Engineer (Infrastructure), Uber
- Mitch McKenzie, Staff Site Reliability Engineer - MLOps, Weave
- Aditya Shanker, Senior Product Manager, Crusoe Cloud
- Rebecca Weekly, VP Platform and Infrastructure Eng, Geico
When
Wednesday November 13, 2024 4:30pm - 5:05pm MST
Where
This talk was given at Kubecon 2024 in Salt Lake City, Utah.
A PDF version of the slides for this talk can be accessed here