Performance & reliability engineering
Core Web Vitals, p99 latency, cache hit rates — green and steady.
Performance & reliability engineering is core web vitals, p99 latency, cache hit rates — green and steady.
Why this work matters
Performance regressions sneak in PR by PR. By month six the page is 4× slower than launch and nobody noticed because nobody was watching. We watch, and we keep budgets.
The work, in detail.
- Core Web Vitals tuning (LCP/INP/CLS)
- Database query optimization
- Cache layering (HTTP, edge, app, DB)
- Edge offload for static + dynamic
- Capacity planning + load testing
- Quarterly perf budgets
- →Perf budget + CI gates
- →Quarterly performance audit
- →Optimized critical paths
- →Capacity & load test reports
We turn dashboards green and keep them green. Real performance engineering, not 'add a CDN'.
The approach.
Perf budgets in CI
Every PR runs Lighthouse + Web Vitals checks against a budget. Regressions fail CI before they merge.
Profile, don't guess
Real flamegraphs, real query plans, real cache hit ratios. Optimization decisions are data-driven; we don't 'add a Redis' on a hunch.
Capacity, ahead of need
Load tests against forecast traffic, not yesterday's traffic. We catch the bottleneck on the next-tier scale, not in the middle of a launch.
Performance & reliability engineering — common questions
What does performance engineering cover here?
Core Web Vitals tuning (LCP, INP, CLS), database query optimization, cache layering across HTTP, edge, application, and database, edge offload for static and dynamic content, and capacity planning with load testing. It's real performance engineering across the stack, not just adding a CDN.
How do you keep performance from regressing after you fix it?
We put performance budgets in CI. Every PR runs Lighthouse and Web Vitals checks against a budget, and regressions fail CI before they merge. We also run a quarterly performance audit and set quarterly perf budgets so the dashboards stay green instead of drifting 4x slower by month six.
How do you decide what to optimize?
We profile, we don't guess. Optimization decisions come from real flamegraphs, query plans, and cache hit ratios — not a hunch that you need a Redis. That keeps effort on the changes that actually move p99 latency and cache hit rates.
Will you be ready for a traffic spike or launch?
We do capacity planning ahead of need by load testing against forecast traffic rather than yesterday's. The aim is to catch the bottleneck at the next tier of scale, not in the middle of a launch. You get capacity and load-test reports as part of the engagement.
What do we receive as deliverables?
A perf budget with CI gates, a quarterly performance audit, optimized critical paths, and capacity and load-test reports. The CI gates and quarterly cadence are what keep the work durable rather than a one-time cleanup.
Is this a one-time audit or an ongoing function?
It's ongoing. Regressions sneak in PR by PR, so the value is in continuous budgets, profiling, and capacity work rather than a single audit that's stale within a quarter. We watch the dashboards and hold the budgets so you don't have to.
More from Software Management
The cost of waiting
is your competitor.
Every 90 days you delay is 90 days of authority compounding for someone else. Get the audit. See the math. Then decide.