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SebastianLuser/claude-code-arcane32026年10月27日 更新
免费在 GitHub 公开
performance
Rate limiting and caching strategy for backend services.
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SebastianLuser/claude-code-arcane星标 3(GitHub 3 + cccskills 0)
集成工具Redis
实测评分 未实测
查看安装方法包含的文件（4）
- SKILL.md1.6 KB
- references/anti-patterns.md631 B
- references/cache-strategy.md1.6 KB
- references/rate-limit-config.md1.9 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
performance — Rate Limiting & Caching Strategy
Stack: Fastify + Prisma + PostgreSQL + Redis + Zod + TypeScript.
RATE LIMITING
Default algorithm: Sliding Window Counter. Three tiers required: CDN/WAF, API Gateway, App Middleware (Redis). Use rate-limiter-flexible with Redis.
→ Read references/rate-limit-config.md for algorithm comparison, implementation tiers, recommended limits per endpoint, key dimensions, response headers, and failure modes
CACHING
Rule Zero: Before caching, profile. Caching hides problems a database index would solve. Default pattern: cache-aside. Default invalidation: short TTL.
→ Read references/cache-strategy.md for cache layer decision table, TTL strategy, patterns, stampede prevention, HTTP headers, and Redis key conventions
ANTI-PATTERNS
→ Read references/anti-patterns.md for rate limiting (7 items) and caching (11 items) anti-patterns
Checklist
- Algorithm matches use case; all three tiers covered
- Keys include user dimension; RateLimit-* headers + Retry-After on 429
- Fail-open default, fail-closed for sensitive endpoints
- Cache justified by profiling; TTL has explicit rationale
- Invalidation strategy documented; stampede protection on hot paths
- App works when Redis is down; hit/miss/eviction metrics exported
- Redis key naming follows
domain:entity:id:variantconvention
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