Correct reuse starts with an explicit boundary: the object, the audience, and the allowed freshness. Explore basic CDN behavior, demand-based warming, and API response reuse without treating them as interchangeable policies.
Before changing a cache, classify the content and write down which request attributes can change the answer. Then test anonymous requests, authorized requests, and fresh versus stale objects separately. Use origin load and the relevant hit-ratio denominator to evaluate the change.
Connect these ideas with the CDN + ML overview. If the question spans several parts of the system, the guide directory offers a sequence through the related decisions.
API caching starts with deciding who may receive a response. Learn how to review HTTP directives, design complete cache keys, separate public and personal content, and test identity boundaries before expanding a caching policy.
Predictive caching moves a possible future miss ahead of the user's request. Learn how to rank eligible objects, set a warming budget, handle stale forecasts, and test whether earlier transfers improve delivery enough to justify their cost.
Machine learning can help a delivery system choose what to cache, where to send traffic, and when to investigate unusual behavior. Start with a narrow decision, a clear baseline, and boundaries that remain dependable when predictions fail.