A GPU cluster can have a healthy training fabric and still miss its checkpoint window. The useful buying question is not “How fast is this storage appliance?” It is “Can this complete training state reach recoverable storage before the deadline, while the other jobs keep running?” This guide provides a reusable sizing worksheet, a worked 256-GPU example, a bottleneck matrix and a deployment acceptance checklist.
Scope: Everything in the worked design is hypothetical. Bandwidth values are planning assumptions, not benchmark results or vendor performance promises. Calculations use decimal GB/TB and single-direction network rates. No GPU, storage or failure-injection tests were executed for this article; the sizing arithmetic was executed locally.
