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 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.