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How do you detect that a model in production got worse, when nothing in your infrastructure metrics changed?

Latency is flat, errors are zero, and the answers are worse. Quality regression is invisible to every metric a platform team normally owns, which is why it needs its own pipeline.

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.

Latency is flat, errors are zero, and the answers are worse. Quality regression is invisible to every metric a platform team normally owns, which is why it needs its own pipeline.

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Next in this trackYour distributed training run died six hours into an epoch on preemptible GPUs. What happens next, and how do you design for it?Next in this trackA team wants to fine-tune a model every time their labelled data grows. Build them the pipeline.Next in this trackHow often should a large training run checkpoint, and what does the answer depend on?

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