Caching Strategies — Simple

Problem statement (interviewer prompt)

Walk through the four canonical cache patterns (cache-aside, read-through, write-through, write-back) for a read-heavy product. Explain when to use each, how to size the cache, and how to handle stampedes, hot keys, and invalidation across multiple servers.

flowchart LR
  C([Client])
  A[App]
  K[(Cache)]
  D[(DB)]
  C --> A
  A -->|1 read| K
  K -. miss .-> A
  A -->|2 load| D
  D --> A
  A -->|3 fill| K
  A --> C

    classDef client fill:#dbeafe,stroke:#1e40af,stroke-width:1px,color:#0f172a;
    classDef edge fill:#cffafe,stroke:#0e7490,stroke-width:1px,color:#0f172a;
    classDef service fill:#fef3c7,stroke:#92400e,stroke-width:1px,color:#0f172a;
    classDef datastore fill:#fee2e2,stroke:#991b1b,stroke-width:1px,color:#0f172a;
    classDef cache fill:#fed7aa,stroke:#9a3412,stroke-width:1px,color:#0f172a;
    classDef queue fill:#ede9fe,stroke:#5b21b6,stroke-width:1px,color:#0f172a;
    classDef compute fill:#d1fae5,stroke:#065f46,stroke-width:1px,color:#0f172a;
    classDef storage fill:#e5e7eb,stroke:#374151,stroke-width:1px,color:#0f172a;
    classDef external fill:#fce7f3,stroke:#9d174d,stroke-width:1px,color:#0f172a;
    classDef obs fill:#f3e8ff,stroke:#6b21a8,stroke-width:1px,color:#0f172a;
    class C client;
    class A service;
    class K,D datastore;

The four main patterns are cache-aside, read-through, write-through, and write-back.