Cache TTL Optimizer

TTL (Time To Live) is the number of seconds a cached value is considered valid before the cache evicts or revalidates it. Too short a TTL means the cache is effectively bypassed and every request hits the database, killing performance. Too long a TTL means stale data is served to users — a product showing an old price, or a session that should have expired. Choosing the right TTL is a trade-off between freshness and performance.

Strict consistency means every read sees the latest write — typically required for financial balances, inventory counts, or anything users directly transact on. Moderate consistency tolerates a short window of staleness (seconds to minutes) — acceptable for dashboards, profiles, or recommendation data. Eventual consistency allows minutes to hours of lag — fine for static content, marketing pages, or cached aggregation reports.

Under high traffic, a short TTL causes a stampede: when many requests hit the cache at the same moment the entry expires, they all miss simultaneously and pound the database. We recommend slightly longer TTLs under high traffic combined with stale-while-revalidate or jitter patterns to spread revalidation. Under low traffic, a shorter TTL is safe since simultaneous misses are unlikely.

Cache jitter (or TTL jitter) adds a small random delta to each item's expiry time. Instead of all cached user profiles expiring at exactly 5 minutes, they expire between 4.5 and 5.5 minutes. This prevents cache stampedes under high traffic. The config snippets include jitter where appropriate.

The recommendations focus on application-level caches (Redis, Memcached). For CDN caching you also need to consider the Cache-Control: s-maxage header and surrogate key invalidation. Generally CDN TTLs for dynamic content should be shorter or zero (with stale-while-revalidate for edge-side), while static assets can use very long TTLs with content-hash fingerprinting.

stale-while-revalidate is a pattern where the cache immediately serves the expired (stale) value and simultaneously kicks off a background refresh. The user sees a fast response, and the next request already has a fresh value. Redis does not support this natively, but it is trivial to implement: if the TTL has expired, return the old value and asynchronously update. The config snippet includes a commented implementation hint.