A cache entry is a promise about freshness Caching can reduce database load, but it also creates another copy of application state. Before adding a cache k...
A cache entry is a promise about freshness
Caching can reduce database load, but it also creates another copy of application state. Before adding a cache key, define who may read it, which inputs affect the value, how long staleness is acceptable, and which writes invalidate it. A fast wrong answer is worse than a slightly slower correct one for permissions, pricing, or account state.
Consider a project listing. It may vary by category, language, publication status, and tenant. Each dimension that changes the result belongs in the cache key or in a separately scoped cache.
Choose an invalidation method
A short TTL is simple for data where a few minutes of staleness is acceptable. Event based invalidation is more immediate but every write path must remove the affected entries. Versioned keys can simplify broad invalidation by changing a namespace version, at the cost of temporarily retaining old entries until expiration.
Avoid a cache forever strategy without a reliable ownership and purge process. Administrative edits should be reflected in the public site on a documented schedule.
Prevent cross tenant leaks
Use verified tenant and permission scope in cache keys for tenant specific data. Never use one global key for a response containing customer records. A permission change may require invalidating per user or per role data even when the underlying records did not change.
For public content, be careful with preview and draft modes. A preview request must not populate a public cache with unpublished data.
Handle stampedes and failure
An expired popular key can trigger many simultaneous database queries. Use a lock or stale while revalidate approach when the framework and consistency needs permit it. If Redis is unavailable, decide whether the request should fall back to the database or fail; that decision depends on whether the cache holds only derived data or essential session state.
Verify behavior
Test cache hit and miss, an edit that invalidates affected keys, a permission change, tenant switching, and an expired key under concurrent load. Measure database queries and response time before and after. Keep the cache key format documented for operations staff.
Conclusion
Caching is useful when freshness, scope, and invalidation are explicit. Start with a correct query and add cache only where measurement justifies it. See cloud and DevOps solutions for operating the supporting infrastructure.
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