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Caching and Rate Limiting ​

Caching and Rate Limiting Graphics Coverage ​

Primary chapter graphic: Caching Layers Along a Request Flow, Cache Location Map, Redis and Memcached Cache Tradeoffs. Accepted graphics: 3. Reviewed non-signal pages: 0. Open graphics in review: 0. QA status lives in graphics audit and visual review ledger.

Corpus pages: p. 72, p. 90, p. 97, p. 171, p. 302 Coverage: 5 pages; low-confidence extraction ranges: p. 302

This chapter is part of Marius's owned architecture build corpus. The text routes decisions; durable implementation signal is carried by accepted graphics, reviewed non-signal decisions, and the linked QA audit.

Chapter Visuals ​

Accepted graphics carry the canonical design signal for this chapter. Each selected source page is either accepted as a graphic or explicitly marked non-signal in the source-faithful ledger. Review and QA state live in visual inventory, visual review ledger, and graphics audit.

Caching Layers Along a Request Flow ​

Caching Layers Along a Request Flow

Cache Location Map ​

Cache Location Map

Redis and Memcached Cache Tradeoffs ​

Redis and Memcached Cache Tradeoffs

Open Review Queue ​

  • none

Reviewed Non-Signal Pages ​

  • none

Use When ​

  • Repeated reads, renders, or vendor calls are too slow or expensive.

Avoid When ​

  • Freshness and permission requirements are unknown.

Core Model ​

  • Caching is a controlled staleness contract. Rate limiting is controlled fairness and protection.
  • Prefer explicit ownership over accidental coupling. Every boundary should say who owns correctness, cost, data, recovery, and change.
  • Use corpus page pointers for inspection, and keep the chapter notes focused on reusable design decisions.

Implementation Guidance ​

  • Define cache key, TTL, invalidation, stale behavior, identity dimensions, and burst limits.
  • Write the smallest useful design note: purpose, inputs, outputs, state, failure behavior, observability, and rollback.
  • Choose the first implementation that can be tested against the real workflow without hiding a known production risk.

Tradeoffs ​

  • Long TTLs reduce cost but can make users distrust the result.
  • Centralization reduces duplicated work but can become a bottleneck when every team needs exceptions.
  • Specialized infrastructure helps at scale, but it must earn its operational cost.

Failure Modes ​

  • A user-specific response is cached under a shared key.
  • The diagram shows boxes but not ownership, retry behavior, data freshness, or user-visible failure.
  • The system has no proof path for the highest-risk assumption.

Decision Checklist ​

  • Track hit rate, stale serves, evictions, limited requests, and bypass behavior.
  • Name the owner, source of truth, timeout, retry policy, and evidence that the path works.
  • Add one regression check for the failure mode most likely to recur.

Neutral Automation Examples ​

  • A catalog service caches public product metadata while never caching customer-specific prices without a scoped key.
  • A neutral internal automation starts with fixtures, then adds credentials, permissions, and production scheduling only after the boundary is tested.
  • A customer-facing workflow keeps irreversible actions behind explicit approval until metrics show it is safe to automate further.