Your fleet is replacing one percent of its GPUs every month. Is that normal, and how would you find out?

Determine what the replacement count measures, compare equivalent device exposure and investigate differences by cohort, location, age, software and policy. Job-interruption statistics cannot supply a hardware replacement baseline.

Updated Sep 2026 · Learn how AI infrastructure works through explanations, worked examples and diagrams, then practise applying it to interview questions.

The full answer is part of Premium. A free account includes more answers in each topic, but does not unlock this one.

20 answers per topic instead of 10, plus saved progress and bookmarks · no cardor unlock all 316 remaining answers · ₹2,000 / $25

The concepts behind this question

Use these concept explanations to review the ideas behind this question.

Foundational

🧮 Open Weights & Serving Engines

Serving Benchmarks That Do Not LieDesign reproducible serving experiments with realistic arrivals, cache state and failure accounting. Interpret latency-qualified throughput and conditional per-rank bounds without turning optimistic kernel estimates into production capacity.

Foundational

🖧 Hardware & Cluster Build-Out

Burn-In and Acceptance TestingAcceptance testing checks that a new cluster meets agreed performance and reliability criteria. Sustained tests and comparisons between nodes help reveal defects before production.

Advanced

🚀 Inference & Serving🔒 Premium

The Serving Optimization WaterfallTune an LLM deployment one change at a time against one fixed workload, in an order that follows the binding constraint. A measured run went from 789 to 6,568 output tokens per second, and the two biggest wins were not the knobs people usually reach for first.

Foundational

🩺 Fleet Reliability & Observability

GPU Failure Modes and XID ErrorsXID messages report GPU errors that need interpretation alongside logs and workload behavior. Use the code, recovery guidance and recurrence pattern to choose the next check.

Explore the full curriculum →

UP NEXT ON YOUR JOURNEY

Closest to this topicDescribe a time you were confidently wrong about a root cause. What did it cost?Closest to this topicHow do GPUs actually fail at fleet scale, how often, and which failures should the platform expect to handle every day?Closest to this topicA CUDA upgrade improves warm runs but slows the first request. Would you ship it?

FEDITOR'S NOTE

Ask for serial-level replacement history and device-days of exposure. A high count can reflect repeat swaps or a changed replacement policy as well as a hardware problem.

DISCUSSION · 0

No comments yet — be the first to share your approach.