Performance Monitoring

Performance should be monitored continuously — not only during launch week.

01 — Purpose

Monitor beyond launch week

Performance should be monitored continuously — real-user performance matters more than synthetic scores alone.

A fast staging build on a developer laptop proves little. Users on mid-range phones, congested networks, and cold caches experience something else entirely. Continuous monitoring keeps that gap visible.

See Core Web Vitals and frontend observability for the wider operational picture.

02 — Principles

Real users over lab scores

Performance monitoring should reveal real user experience quality.

  • Core Web Vitals tracking in production — LCP, CLS, INP at scale
  • real-device testing — not only emulators on fast hardware
  • mobile monitoring — most traffic is mobile; measure it as such
  • regression alerts — catch degradation before users complain

03 — Practice

Good performance monitoring

Combine field data, lab debugging, and release discipline.

  • instrument key templates with RUM — homepage, product, checkout, search
  • segment by device class, connection, geography, and cache state
  • use Lighthouse and WebPageTest to diagnose — not as the only scoreboard
  • set budgets and fail CI when LCP, CLS, or INP regress — see Core Web Vitals
  • correlate metric changes with deploys and third-party script updates

04 — Avoid

Monitoring theatre

A green Lighthouse score does not guarantee happy users.

  • relying only on Lighthouse — lab conditions hide field reality
  • ignoring real-user metrics — p75 INP on mobile tells a different story
  • measuring only fast devices — developer hardware skews results
  • no alerts — dashboards that nobody acts on
  • optimising one page while regressions ship elsewhere unnoticed

05 — Close

Measure what users feel

Continuous monitoring turns performance from a launch checklist into an operational habit.

Pick three templates that matter most. Track CWV weekly, alert on regressions, and review after every release. When field data dips, use lab tools to find the cause — then verify the fix in production.

See Core Web Vitals, frontend observability, and the performance review checklist.