Case Study · Retail & E-commerce
High-Volume E-commerce Performance Optimisation
Profiling-led performance engineering on a high-traffic commerce store — turning slow pages and peak-trading instability into measured, repeatable performance.
MagentoVarnishRedisElasticsearchNew Relick6AWS
01
The Business Challenge
A high-traffic retailer suffered slow page loads in normal trading and instability during sales events. Previous fixes had been guesswork — bigger servers, cache plugins — with little lasting effect.
The business needed measurable improvement before its next peak trading period.
02
Existing Technology Environment
- High-traffic Magento store with a large catalogue
- Oversized but poorly configured infrastructure
- No performance monitoring or load testing in place
03
Our Approach
- 01Established baseline measurements first: real-user metrics, server-side profiling and load tests that reproduced peak traffic.
- 02Fixed in order of measured impact — database queries, cache configuration, third-party script weight and frontend rendering — rather than by assumption.
- 03Load-tested after each change to prove the gain and catch regressions.
- 04Left behind monitoring dashboards and a capacity plan for future peaks.
04
The Solution Delivered
- A measurably faster storefront with performance budgets enforced in CI.
- Right-sized infrastructure with caching layers configured correctly for the catalogue and traffic profile.
- Continuous performance monitoring and a repeatable load-testing capability.
05
Business Impact
- [ADD METRIC] Improved page speed from X to Y
- [ADD METRIC] Survived peak trading at X× normal traffic without incident
- [ADD METRIC] Reduced infrastructure cost by X%
- Performance is now measured and defended, not rediscovered every peak
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