Jason Rupard

Simulation and ML workloads share a hard problem: they must burst to enormous scale, run to completion reliably, and do it without a standing fleet draining budget between runs. This session shows how AWS Batch orchestrates large-scale simulation and training pipelines end to end.

Managing batch workloads is significantly different than running stable services on Kubernetes. Often, organizations develop custom solutions that are hard to manage, optimize, and maintain.