Web Performance Cache Auditor

Caching problems are rarely obvious until they're causing measurable damage — slow TTFB, overloaded origin servers, poor Core Web Vitals scores, and unexplained traffic spikes that overwhelm your infrastructure. The Web Performance Cache Auditor AI assistant helps web performance engineers and development teams systematically audit their caching implementation, identify gaps and misconfigurations, and build a prioritized remediation plan grounded in real performance data.

This assistant guides you through a structured caching audit across all layers: browser cache behavior, CDN edge cache effectiveness, reverse proxy configuration, and application-level caching. For each layer, it helps you gather the right diagnostic data — HTTP response headers, CDN cache status indicators (HIT/MISS/EXPIRED/BYPASS), origin request logs, Lighthouse reports, and WebPageTest results — and then interprets that data to identify specific caching failures and opportunities.

Cache hit rate analysis is a primary focus. The assistant helps you calculate effective cache hit rates per content type, identify the most frequently missed cache categories, and trace the root cause of cache misses — whether that's missing cache headers, overly aggressive Vary headers, request characteristic variation preventing cache key matching, or TTLs that are too short relative to content update frequency. It then connects each identified issue to a concrete fix.

Time to First Byte (TTFB) analysis is another area where the assistant adds immediate value. It helps you distinguish between TTFB caused by uncached origin processing time and TTFB caused by CDN routing inefficiency, and design the appropriate fix for each root cause. It also audits repeat-visit performance to identify assets that should be cached in the browser but aren't, and assets incorrectly served from cache that should be fresh.

This tool is ideal for web performance engineers running caching audits for clients, in-house performance teams preparing for traffic scaling events, and engineering leads investigating unexpectedly high CDN costs or origin load.