Website performance testing
that catches regressions
Synthetic monitoring, real-user measurement, and deploy-triggered regression tests — so you always know when performance degrades and why.
Four types of performance testing
Automated performance tests run from multiple global locations on a schedule. Catch regressions before real users do.
Measure performance from actual visitor sessions across all devices, browsers, and connection speeds.
Simulate concurrent users to find your site's performance limits and infrastructure bottlenecks.
Automatically compare every deploy against a performance baseline and block regressions from reaching production.
Why one-off tests aren't enough
A new image carousel, a third-party script, or a misconfigured CDN can double your LCP overnight. Without continuous testing, you find out when Google downgrades your rankings or users complain.
Running a manual test once tells you your score at that moment. It can't tell you what it was last Tuesday, whether it's trending up or down, or whether it changes by region or device.
Controlled tests use a mid-range device on a simulated 4G connection. Your real users include users on low-end Android phones on 3G — and they're the ones most likely to bounce.
Performance testing best practices
Define maximum acceptable values for LCP, CLS, INP, TTFB, and Lighthouse score. Treat budget violations as build failures — block deploys that break the budget.
A CDN that's fast in the US may be slow in Southeast Asia. Run synthetic tests from at least 3–5 locations covering your key user geographies.
Lab data (synthetic tests) catches regressions fast. Field data (RUM) shows what real users experience. Both are needed — Google uses field data (CrUX) for Core Web Vitals rankings.
Third-party scripts (analytics, chat, ads) often cause more performance damage than your own code. Track their contribution to Total Blocking Time and LCP independently.
Throttled desktop Chrome doesn't fully replicate low-end Android performance. Include real device testing in your mobile performance baseline.
FAQ
What is website performance testing?
Website performance testing measures how quickly and reliably a website loads and responds under different conditions. It includes synthetic monitoring (lab-based tests on a schedule), real-user monitoring (measuring actual visitor sessions), load testing (simulating many concurrent users), and regression testing (checking that deploys don't degrade performance).
What's the difference between load testing and stress testing?
Load testing measures your site's performance under expected traffic volumes — how fast it responds with 100, 500, or 1,000 concurrent users. Stress testing pushes beyond normal limits to find your breaking point — at what traffic level does the site degrade or fail? Both are important but serve different purposes.
How often should I run performance tests?
Synthetic monitoring should run continuously (every 5–60 minutes) to catch regressions immediately. Deeper load tests should run on every significant deploy, weekly on production, and after any infrastructure change. One-off speed tests tell you your current state but won't catch regressions.
What's a performance regression?
A performance regression is when a metric that was previously at an acceptable level degrades — for example, LCP rising from 1.8s to 3.2s after a deploy that introduced a large unoptimized image. Without continuous monitoring, regressions go undetected until users complain or rankings drop.
What metrics should performance testing measure?
At minimum: LCP, CLS, INP (Core Web Vitals), TTFB, FCP, Time to Interactive, Total Blocking Time, and Lighthouse score. For ecommerce add conversion rate correlation. For high-traffic sites add p95 and p99 response times to catch tail latency that averages hide.
Catch regressions before your users do
AuditJet runs synthetic tests on a schedule, alerts you the moment a metric regresses, and shows you the revenue impact in dollars — not just milliseconds.
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