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At 512 GPUs something fails every few hours. How does a training run survive that?

Failure stops being an event and becomes a rate. Once mean time between failures drops below the length of a run, the design question is not how to avoid interruption but how cheaply you can absorb one.

Updated Sep 2026 · Grounded in researched DevOps, SRE and platform engineering interview loops, written to a senior-engineer editorial bar, and never padded to hit a word count.

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UP NEXT ON YOUR JOURNEY

Next in this trackYour GPUs sit at 40 percent utilisation during training and the model code is fine. What is starving them?Next in this trackDesign the path a model takes from a training run to production traffic. What gates does it pass?Next in this trackA model scores well offline and performs badly in production. What infrastructure causes would you check first?

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