Core

Latency Optimization

Measure p50, p95, and p99 before you touch anything, then find where the time actually goes: tokenization, retrieval, inference, or post-processing. A naive RAG pipeline that takes 1.5 seconds can usually reach sub-100ms perceived latency by caching, parallelizing retrieval, picking a smaller model, and streaming the first token, in that order of payoff.

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RELATED CONCEPTS

KV Cache Inference Serving (vLLM, TGI)Rate Limiting Observability for AI Systems

LESSONS THAT TEACH THIS

Hard DeploymentsMeasure throughput and user latency before choosing a batching policy30 min→The FDE EngagementCost per unit of their work is the number, and it decides the architecture25 min→

PRACTICE THIS IN REAL QUESTIONS

System Design & Production EngineeringWhat do p50, p95, and p99 latency actually mean, and why do production engineers obsess over the tail?→MLOps & ML EngineeringWhat problem does a feature store solve? Explain the online store versus the offline store.→ML Infrastructure & GPUsWhat is occupancy, and how do you balance it against register and shared-memory usage when choosing block size?→ML Infrastructure & GPUsHow do you determine whether a kernel is memory-bound or compute-bound?→System Design & Production EngineeringIt's 9am Monday and p99 latency is 10x normal. Walk me through your first 30 minutes.→System Design & Production EngineeringA customer's Next.js site has a 3-second TTFB. Diagnose it and walk me through fixes, and how you'd prove each one worked.→