Services

Next.js Performance and Stability Debugging

The first engagement can be a focused diagnostic of a slow, stale, or unreliable Next.js route. We agree the affected journey and the conditions to reproduce before I trace it through rendering, data loading, scripts, caching, or deployment behaviour.

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

You receive reproduction steps, baseline measurements where available, and prioritised findings with supporting evidence. I separate confirmed causes from hypotheses and record any issue I could not reproduce. The handover explains the recommended fix or next investigation and the checks your team can repeat. Implementation or a wider review can then be agreed from those findings.

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

  • Start with the affected URLs, the steps that trigger the problem, when it began, and any relevant release or configuration changes. Repository access, deployment logs, browser errors, and field data where available help narrow the cause.
  • I focus on the agreed routes and user journeys, compare production behaviour with a reproducible local or preview environment where possible, and trace the relevant rendering, data, script, image, font, or cache path. I keep lab measurements separate from real‑user data.
  • 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