Performance

HTTP caching (Cache-Control, ETag, fresh/stale, immutable static resources); reverse proxies; application-layer: side vs inline cache, LRU eviction, TTL, local vs external cache, thundering herd, cascading failure; 80% hit rate as scalability threshold

CDN overlay network; BGP limitations; global DNS LB; IXP placement; edge+intermediary caching layers; DDoS shielding

*Foundations of Scalable Systems* — Ian Gorton

HTTP/1.1 vs HTTP/2 vs HTTP/3 (QUIC); multiplexing; HOL blocking; connection management; relationship to REST

Inference metrics (TTFT, TPOT, throughput, goodput, MFU, MBU); prefill (compute-bound) vs decode (memory bandwidth-bound); speculative decoding; KV cache management (PagedAttention, FlashAttention, GQA/MQA); continuous batching; prefill-decode decoupling; prompt caching

Symptom → diagnosis → action playbook; three analytical lenses (Little's Law, utilisation curve, percentile arithmetic); capacity planning workflow; antipatterns (sizing for average, running at high utilisation, unbounded queues); when performance tuning doesn't apply

Little's Law (L=λW), utilisation curves (W=S/(1−ρ)) and hyperbolic response-time growth, tail latency amplification in fan-out designs, percentile arithmetic (averages lie; can't average percentiles; t-digest/HdrHistogram), queues in series, thread pools as queueing systems; practical heuristics for capacity and tuning

definition; replication vs optimization strategies; scale up vs scale out; stateless services requirement; Amdahl's Law; hyperscale; quality attribute trade-offs (performance, availability, security, manageability); architecture evolution pattern

Hash indexes, SSTables/LSM-Trees, B-Trees, OLTP vs OLAP, column-oriented storage, materialized aggregates