Home/Services/Performance Optimisation
Service · Modernise & operate

Faster pages, faster queries, a smaller cloud bill.

We measure where your application actually spends its time and money, fix the things that matter most, and leave behind the budgets and monitoring that stop it drifting back.

Performance OptimisationWhat we do
01Database and queries
02Application and APIs
03Front end and Core Web Vitals
04Infrastructure and cost
How it runs
  1. Instrument and baseline
  2. Fix in order
  3. Lock it in
  4. Report
Why it exists

A before-and-after you can show the board.

Slow software costs money twice: once in the customers and staff who wait, and again in the cloud bill that grows because the easy fix for slowness is a bigger server. Most performance problems are not mysterious — a query without an index, a page loading four megabytes of script, a job that runs every minute when once an hour would do — but nobody has measured, so everyone guesses.

We do not guess. We instrument the system, find where time and money actually go, and fix the handful of causes that account for most of it. Then we leave performance budgets in the build, so a pull request that makes a page slower fails before it ships, and dashboards that show the numbers to the people who own them.

The deliverable is a before-and-after you can show the board: response times, error rates and monthly cost, measured the same way on both sides.

What we fix

Four places performance is lost.

Every engagement starts with measurement; the order below is the order the fixes usually pay back.

01

Database and queries

Missing indexes, N+1 queries, locks held too long, tables that needed partitioning a year ago. Many of the wins live here, and they are found with traces, not opinions.

02

Application and APIs

Serial calls that could be parallel, caches that are missing or wrong, payloads far larger than the screen needs, background jobs on the request path. Profiled under real load, fixed with tests.

03

Front end and Core Web Vitals

Script weight, render-blocking resources, images without sizes, layout shift. Measured with real-user data, not a lab score, and fixed route by route against a budget enforced in CI.

04

Infrastructure and cost

Right-sized instances, autoscaling that actually scales down, storage tiers, idle environments, egress. A cost model per workload so the bill is explained, then reduced. See DevOps & Cloud.

In practice

How the work runs, day to day.

01

Measure first, fix the top causes, lock it in.

The work starts with instrumentation: traces across the request path, database statistics, real-user metrics on the front end and a cost breakdown per workload. The result is a ranked list of causes with the share of time or cost each one carries. We fix from the top, re-measure after each change, and stop when the curve flattens.

  • Distributed tracing and database statistics before any change
  • Each fix measured on its own, so the report shows what actually helped
  • Performance budgets per route and per query, enforced in the pipeline
  1. 01Instrument
  2. 02Rank
  3. 03Fix
  4. 04Re-measure
  5. 05Budget

Top causes first, each one proven before the next

Rollout

How the work runs.

01

Instrument and baseline

Tracing, database statistics, real-user metrics and the cost breakdown. The baseline report lists the top causes with their share.

02

Fix in order

The top causes fixed and re-measured one at a time, released through your normal pipeline with tests.

03

Lock it in

Performance budgets added to CI, dashboards and alerts handed to the owners, the cost model documented.

04

Report

The before-and-after on the same measures: response times, error rates, Core Web Vitals and monthly cost.

Deliverables

What you keep.

  • A baseline report with ranked causes and their share of time or cost
  • The fixes, merged with tests through your own pipeline
  • Performance budgets enforced in CI per route and per query
  • Dashboards and alerts for latency, errors and cost
  • A before-and-after report on identical measures
Usually runs with
OpenTelemetryPostgreSQLRedisk6Lighthouse / CrUXGrafanaKubernetesCloud cost tooling
Fit

When this is the right call.

Right fit

Choose this when users complain about speed, the cloud bill has grown faster than the business, or a launch is coming and nobody knows whether the system will hold.

Look elsewhere

Look elsewhere if the architecture itself is the limit — a monolith that cannot scale a single hot path — in which case the honest answer is modernisation, and we will say so after the baseline.

FAQ

Frequently asked questions

We do not promise a number before measuring. The baseline report states what the top causes are and what fixing them should return — then each fix is measured.
Usually not. Most of the gain comes from queries, caching, payloads and configuration. Where the architecture is the limit, the report says so and the engagement stops there if you prefer.
Often both improve together: idle capacity, oversized instances and chatty services cost money and time. The cost model separates what is waste from what is load.
Yes — Core Web Vitals measured with real-user data, fixed route by route, with budgets in CI so regressions fail the build.
Your team, with dashboards, budgets and a documented cost model. If you want coverage, maintenance and support continues from here.

Which page or report is too slow?

Tell us where users wait. An engineer reads it and replies in writing with what the measurement would cover.

✓ No pitch deck✓ Reply from an AI-native engineer✓ Written follow-up