caching-strategies

Caching Strategies

Caching is the most commonly misapplied performance technique. The failure mode is not "cache too little" — it is "cache without an invalidation strategy and then discover the problem in production six months later when users complain about stale data that you cannot explain."

When to Use

✅ Use for:

• Choosing which caching pattern fits a use case (cache-aside, write-through, write-behind)
• Designing TTL values for different data freshness requirements
• Implementing Redis caching patterns: sorted sets, pub/sub invalidation, Lua scripts
• Configuring Cache-Control headers, ETags, and CDN behavior
• Preventing cache stampedes via locking, probabilistic early expiry, or background refresh
• Cache warming strategies for cold-start scenarios
• Multi-tier cache design (in-memory L1, Redis L2, CDN L3)

❌ NOT for:

• Database-internal query plan caching (handled by the database)
• Python functools.lru_cache / JavaScript memoize utilities (pure function memoization)
• CPU branch prediction or hardware cache tuning
• Session storage (use dedicated session skill)

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Which Caching Pattern?

flowchart TD
    Q1{Who writes to cache?} --> WA[Application writes]
    Q1 --> WC[Cache writes automatically]
    WA --> Q2{When does the cache get populated?}
    Q2 -->|On read miss| CA[Cache-Aside\n'Lazy loading']
    Q2 -->|On every write| WT[Write-Through\n'Eager write']
    WC --> Q3{Sync or async write-back?}
    Q3 -->|Sync — write completes when cache updates| WT
    Q3 -->|Async — write returns fast, flush later| WB[Write-Behind\n'Write-back']
    CA --> N1{Is stale data OK\nfor a short period?}
    N1 -->|Yes| CA_USE[Use cache-aside\nwith TTL expiry]
    N1 -->|No| INVAL[Add explicit invalidation\nor use write-through]
    WT --> NOTE2[Good for read-heavy data\nthat changes infrequently]
    WB --> NOTE3[Good for write-heavy workloads\nRisk: data loss on crash]

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Multi-Tier Cache Architecture

flowchart LR
    USER[User Request] --> CDN{CDN / Edge Cache\nL3 — 100ms+ saved}
    CDN -->|Cache hit| RESP[Response]
    CDN -->|Cache miss| LB[Load Balancer]
    LB --> APP[App Server]
    APP --> L1{In-Process Cache\nL1 — ~0ms}
    L1 -->|Hit| APP
    L1 -->|Miss| REDIS{Redis\nL2 — 1-5ms}
    REDIS -->|Hit| APP
    REDIS -->|Miss| DB[(Database\n10-100ms)]
    DB --> REDIS
    REDIS --> APP
    APP --> L1
    APP --> CDN
    APP --> RESP