Web Application Caching Strategies

Why You Need a Caching Strategy

Caching is the most powerful performance optimization tool available. A proper caching strategy can reduce server load by 90%, decrease response times by 10-100x, and significantly save on infrastructure costs. But caching without a strategy leads to stale data, bugs, and difficult debugging.

Caching Layers

1. Browser Cache (Client-Side)

The layer closest to the user. Controlled by HTTP headers: Cache-Control, ETag, Expires. Zero latency on cache hit — the resource loads from disk.

Best for: static resources (CSS, JS, images, fonts), rarely changing pages.

2. Service Worker / Application Cache

A programmable cache in the browser. Service Workers intercept network requests and can serve them from cache, even offline. Gives complete control over client-side caching strategy.

Best for: PWAs, offline functionality, API документацию response caching.

3. CDN (Content Delivery Network)

A distributed network of servers caching content closer to users. Reduces latency and offloads the origin server. Controlled by Cache-Control, s-maxage, Surrogate-Control headers.

Best for: static resources, APIs with public data, HTML pages.

4. Reverse Proxy (Varnish, nginx)

A caching proxy in front of the application server. Serves requests from cache without reaching the application. Varnish can handle tens of thousands of requests per second.

Best for: HTML pages, API responses, reducing application server load.

5. Application Server Cache

In-memory cache (Redis, Memcached) within the application. Caches computation results, serialized objects, external API call results.

Best for: complex query results, external API responses, sessions, configuration.

6. Database Cache

Built-in DBMS cache (InnoDB buffer pool, query cache). Caches data and indexes in memory. Managed by DB configuration, requires no code changes.

Best for: frequently read data, repeated queries.

Caching Patterns

Cache-Aside (Lazy Loading)

The application checks the cache. If data is missing (cache miss), it loads from the DB and stores in cache. The most common pattern.

function getUser(int $id): array {
    $key = "user:{$id}";
    $cached = cacheGet($key);
    if ($cached !== null) {
        return $cached; // cache hit
    }
    $user = db_query("SELECT * FROM users WHERE id = ?", [$id]);
    cacheSet($key, $user, 3600); // TTL: 1 hour
    return $user;
}

Pros: simple, data is cached on demand.

Cons: first request is always slow, data may be stale until TTL expires.

Write-Through

On write, data is updated simultaneously in cache and DB. Cache is always current.

Pros: data is always fresh, no cache miss on reads.

Cons: slows down writes, caches all data (even data that's never read).

Write-Behind (Write-Back)

Data is written to cache first, then to DB asynchronously with a delay. Maximum write speed.

Pros: fast writes, reduced DB load.

Cons: risk of data loss on cache failure, implementation complexity.

Read-Through

The cache itself loads data from DB on a miss. The application only talks to the cache.

Pros: simple application code.

Cons: cache must know about the data source.

Cache Invalidation

"There are only two hard things in Computer Science: cache invalidation and naming things." — Phil Karlton.

Time-Based (TTL)

Cache automatically expires after a set time. The simplest approach, but data may be stale until TTL expires.

Event-Based

Cache is invalidated when data changes. More complex but ensures freshness.

function updateUser(int $id, array $data): void {
    db_query("UPDATE users SET ... WHERE id = ?", [...$data, $id]);
    cacheDel("user:{$id}");  // Invalidate cache
}

Versioning

For static resources: filename contains a content hash (app.a1b2c3.css). Content change = new URL = automatic invalidation.

Purge API

CDNs and proxies typically provide APIs for forced cache clearing. Use for urgent updates.

Common Mistakes

• Caching without TTL — data may become stale forever
• TTL too short — cache doesn't have time to provide benefit
• Personal data in shared cache — data leaks between users
• Cache stampede — when a popular cache entry expires, hundreds of requests hit the DB simultaneously. Solution: mutex lock or stale-while-revalidate
• No monitoring — without hit/miss ratio metrics, cache effectiveness is impossible to evaluate

Monitoring Effectiveness

Use the Enterno.io Speed Test to assess caching's impact on load time. Check HTTP response headers to verify Cache-Control settings on your site.

Summary

An effective caching strategy uses multiple layers: browser for static assets, CDN for global delivery, Redis for application data. Choose a pattern (Cache-Aside for most cases) and plan your invalidation. Monitor hit/miss ratios and tune TTLs based on data.