A performance improvement should make a defined experience better under stated conditions. This collection covers caching experiments, latency distributions, and the telemetry that distinguishes a faster successful response from a fast failure.
Choose a representative workload and a useful comparison. Include quiet periods, bursts, cold starts, and errors. A global average may hide a small group of very slow requests, while a request hit ratio may hide large origin transfers. Keep the population and measurement boundaries visible.
Connect these ideas with the Analytics overview. If the question spans several parts of the system, the guide directory offers a sequence through the related decisions.
Averages can hide the requests that make an application feel unreliable. Learn what p95 and p99 describe, how to measure complete user journeys, and how to compare regional traffic and latency distributions without misleading aggregation.
Useful CDN analytics connects cache behavior, latency, and errors to a clear operational decision. Learn to define trustworthy metrics, interpret request and byte hit ratios, manage sampling and privacy, and test changes with meaningful guardrails.
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.