Cache Invalidation Patterns: Best Practices and Anti-Patterns

Cache invalidation is a deceptively difficult problem. When caches are large, distributed, and used across multiple layers (browser, CDN, edge, origin), ensuring data freshness without excessive origin load or stale responses requires deliberate patterns and operational discipline.

"There are two hard things in computer science: cache invalidation and naming things." — A classic adage that is never wrong in practice.

Why Invalidation is Hard

Distributed caches can have varying propagation delays, rate limits on purge APIs, and different semantics (e.g., eventual vs. immediate invalidation). Furthermore, content often varies across headers or user contexts, making blanket invalidation risky.

Pattern 1: Cache Busting via Asset Versioning

For static assets like CSS and JS, the simplest approach is to include a content hash in filenames. Whenever content changes, the filename changes, and caches treat it as a new resource—no purge required.

app.ab12cd34.js
styles.9efg5678.css

This is straightforward, robust, and often the preferred approach for front-end assets.

Pattern 2: Time-Based Expiry (TTL)

Set conservative TTLs where appropriate. Use short TTLs for frequently changing resources and longer TTLs for static assets. Combine TTLs with validation (ETags) if you want to reduce bandwidth on validation requests.

Pattern 3: Purge APIs and Programmatic Invalidation

Many CDNs offer purge APIs to invalidate objects by URL or tag. Use this for dynamic content that must be updated on demand. However, consider rate limits and the eventual-propagation model—test your vendor's behavior under load.

Pattern 4: Tag-Based Invalidation

Tag-based invalidation lets you attach logical tags to cached objects (e.g., 'product-123') and purge by tag. This is more efficient than purging by URL when many URLs depend on the same underlying entity.

Pattern 5: Soft Purge / Revalidation

Instead of immediately removing an object from the cache, mark it as stale and allow serving while revalidation occurs in the background. This avoids cache stampedes and sudden latency spikes but requires careful implementation of background refresh mechanisms.

Pattern 6: Conditional Requests / Validation

Use ETags and Last-Modified headers so caches can validate resources with the origin. This preserves bandwidth and reduces full response traffic while ensuring changes are detected.

Anti-Patterns

• Purge Everything: Purging the entire CDN or cache removes all benefits of caching and creates a thundering herd on the origin.
• Cache Personalization Without Segregation: Caching responses that vary by user without including varying headers or creating separate caches leads to data leaks and incorrect responses.
• Blindly Long TTLs: Using long TTLs on frequently changing data causes stale data to be served until manual purge occurs.
• No Observability: Not measuring hit ratios, purge propagation times, or origin request spikes. Without metrics, you can't make informed adjustments.

Operational Checklist for Safe Invalidation

1. Define data classes and TTL expectations per class.
2. Use versioned asset URLs for static files.
3. Prefer tag-based purges over sweeping wildcard purges.
4. Implement monitoring: origin request rate, cache hit ratio, purge latencies.
5. Test purge and rollback procedures in staging before production use.
6. Use rate limiting and backoff for purge APIs to avoid quota issues.

Example Invalidation Flow for a CMS

1. Author updates an article.
2. The application writes the new content and updates metadata.
3. A background job tags affected cache objects (the article page, related feed endpoints) with 'article-456'.
4. The system triggers a tag-based purge on the CDN and revalidates origin caches.
5. Soft purge serves stale content while origin regenerates updated content if configured.

Conclusion

Cache invalidation requires strategy and tooling. Use versioning for static assets, tag-based purges for content connected to entities, and conservative TTLs combined with validation. Avoid broad purges and poor personalization practices. When planned and instrumented properly, cache invalidation becomes manageable rather than a recurring source of incidents.