Backend Development 52 min read

Comprehensive Guide to Caching: Concepts, Types, Strategies, and Best Practices

This comprehensive guide explains caching fundamentals, motivations, and hardware/software perspectives, details client, network, and server cache types, addresses common problems like breakdown, avalanche, and penetration with solutions, and covers strategies, consistency, expiration policies, distributed architectures, design best practices, and implementation examples.

Tencent Cloud Developer
Tencent Cloud Developer
Tencent Cloud Developer
Comprehensive Guide to Caching: Concepts, Types, Strategies, and Best Practices

This article provides a systematic introduction to caching, covering its definition, motivations, hardware and software perspectives, and its role in improving system performance.

It explains why caching is essential for reducing CPU and I/O pressure, enhancing throughput, and improving user experience, while also warning about the risks of misuse.

The piece outlines who uses caching, including hardware engineers (CPU, GPU caches), software developers, client developers (page, app, browser caches), backend developers (local caches, Redis, Memcached), distributed developers, and OS developers (page cache).

It categorizes caching by location (client, network, server) and details each type, such as client-side page and app caches, HTTP strong and negotiated caches, network proxies (forward and reverse), CDN edge caches, and server-side caches (container, middleware, page static, file storage).

Key cache problems are discussed: cache breakdown, cache avalanche, and cache penetration, with analysis of causes and practical solutions like using mutexes, random TTL, multi‑level caches, Bloom filters, and appropriate eviction policies.

Cache pre‑heating, degradation, and update patterns (Cache‑Aside, Read‑Through, Write‑Through, Write‑Behind) are described, including their workflows and trade‑offs.

Consistency between cache and database is examined, highlighting issues with concurrent reads/writes and presenting the delayed double‑delete strategy to achieve eventual consistency.

Cache expiration strategies, including TTL settings, Russian‑doll caching, soft/hard TTL, and eviction algorithms (FIFO, LRU, LFU, TinyLFU, W‑TinyLFU, ARC, LIRS) are reviewed.

The article also covers distributed caching architectures (replicated vs. centralized), consistency models (AP vs. CP), multi‑level transparent caching, and practical considerations for cache design, component selection, metrics, high availability, monitoring, security, and placement.

Finally, it offers design guidelines, references, and author information.

Code examples:

HTTP/1.1 200 OK
<link rel="dns-prefetch" href="//domain.not-wallbig.club">
distributed systemsperformance optimizationbackend developmentcachingCache Strategies
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