Category: Amazon SageMaker HyperPod

Introduction Large-scale machine learning workloads: training, fine-tuning, and inference run on clusters of hundreds to thousands of GPU instances for days or weeks at a stretch. Keeping operational visibility across a fleet of this size is a constant challenge: hardware health events, node lifecycle transitions, capacity fluctuations, and workload-level issues appear in the event stream around […]