Fault tolerant distributed training on Amazon EKS using NVRx

Large-scale distributed training jobs run for hours or days across dozens of nodes. At that scale and duration, interruptions are statistically inevitable: network partitions, memory errors, software exceptions, or infrastructure events will eventually disrupt at least one worker. A single GPU fault triggers a cascade: NVIDIA Collective Communication Library (NCCL) timeouts propagate to healthy workers, pods crash and restart out of sync, and your cluster burns expensive GPU hours while making zero training progres