Services

Next.js Performance and Stability Debugging

This is not the broad Core Web Vitals service and it is not a general performance wish list. It is for live stacks where a route, release, script, cache rule, build step, hydration boundary, or production‑only behaviour is making the site slower or less trustworthy.

Debug live Next.js estates where slow routes, stale data, hydration faults, scripts, cache behaviour, or deployment history are now affecting real users and release confidence.

Short Answer

The Next.js site is already live, so the priority is isolating the constraint without turning production into a rewrite. A bad metric may be a symptom of rendering, data loading, caching, scripts, deployment history, hydration, or production configuration. I reproduce the issue on the affected route, trace the first failing boundary, and decide whether the fix is performance triage, stability repair, deployment debugging, or a wider platform review.

Why It Matters

For product and delivery leaders, the priority is stopping more changes from compounding the regression. I isolate live‑stack constraints that are affecting conversion, platform stability, and release confidence.

Common Situations

  • Live routes are slow, stale, unstable, or inconsistent after a release, redesign, third‑party change, or deployment event.
  • Hydration mismatches or server/client rendering boundaries are breaking confidence in production behaviour.
  • Slow pages are tied to scripting overhead, image or font weight, data fetching, cache behaviour, or build and deployment history.

Choose the problem that most closely matches the current live‑stack behaviour.

What I Look at First

  • I start with one affected route, live reproduction, deployment history, field data, production logs where available, and whether the issue is speed, stability, freshness, hydration, or runtime failure.
  • Then I tie the symptom back to rendering cost, server/client boundaries, image delivery, font loading, third‑party scripts, caching, data loading, and production‑only differences.
  • That same production‑first method shaped e‑commerce troubleshooting work for Selfridges and John Lewis: finding the first real bottleneck quickly rather than collecting broad optimisation suggestions.

What Usually Changes

  • Live regressions are tied to routes, templates, runtime behaviour, scripts, images, data loading, or cache paths.
  • The first real bottleneck is separated from score noise and secondary symptoms.
  • Fixes are prioritised by user journey, commercial exposure, and release complexity.
  • The team has a verification path for field data, lab checks, and production behaviour.
  • Release confidence improves because the cause and the fix route are both clear.

How This Usually Works

  1. Technical Diagnostic

    A focused review to establish what is happening, where the risk sits, and what should happen next, ending with a prioritised plan the team can take into delivery.

  2. Recovery Sprint

    A short, concentrated engagement to isolate a defined problem, stabilise the immediate situation, and move the first fixes into delivery.

  3. Embedded Delivery Support

    Senior hands‑on support inside an existing team when architecture, implementation, review, and delivery decisions need to stay connected.

This May Not Be the Right Fit If

  • You only need a score‑chasing exercise, a one‑off Lighthouse export, or cosmetic advice without implementation authority. If a measurable regression needs engineering diagnosis, Next.js Core Web Vitals Regression Fix is the better starting point.
  • The business is not ready to prioritise routes, templates, scripts, and release changes by real user and commercial impact. If the immediate pressure is script weight or tag behaviour, Third‑Party Script Performance Optimisation may be the more focused route.

Need to improve web performance?

Tell me which pages or journeys matter most and what the data is showing. I'll read it and suggest where to start.

Related Case Studies and Project Work

  1. Screenshot of the Selfridges website; part of John Kavanagh's selected project work.

    A New User Experience and Features for Selfridges

    At Selfridges, e‑commerce front‑end work had to keep perceived speed, release quality, and commercial flows stable under pressure.

    View case study
  2. Screenshot of the John Lewis website; part of John Kavanagh's selected project work.

    The Optimisation and Rebrand of johnlewis.com

    At John Lewis in 2018, my work included front‑end performance improvements and third‑party script optimisation across high‑traffic retail pages.

    View case study
  3. Screenshot of the Nando’s website; part of John Kavanagh's selected project work.

    A Complete Migration and Replatform for Nando’s

    On Nando’s restaurant pages, speed, structured data, and local discovery were handled as one customer path rather than separate score‑chasing exercises.

    View case study