Chapter 1. Overview of AI workloads on OpenShift Container Platform

You can use the Leader Worker Set Operator to enable large-scale AI inference workloads to run reliably across nodes with synchronization between leader and worker processes. Without proper coordination, large training runs might fail or stall.

For more information, see "Leader Worker Set Operator overview".

You can use Red Hat build of Kueue to provide structured queues and prioritization so that workloads are handled fairly and efficiently. Without proper prioritization, important jobs might be delayed while less critical jobs occupy resources.

For more information, see Introduction to Red Hat build of Kueue in the Red Hat build of Kueue documentation.