Web performance consultant for Magento
Optimize web performance on Magento stores
Magento (Adobe Commerce) is powerful but one of the heaviest CMSs on the market. Misconfigured Full Page Cache, legacy RequireJS and Knockout, deep layout XML, long checkout: I work across the entire stack to deliver green Core Web Vitals and functional fluidity.
They trust me
Magento symptoms calling for an audit
Magento exhibits characteristic bottlenecks on the legacy frontend, Full Page Cache and checkout.
🐌 TTFB exploding on uncached pages (cart, checkout)
Varnish doesn't cache pages with sessions. Without backend optimization (opcache, PHP 8.x JIT, MySQL tuning, Redis sessions), cart and checkout TTFB easily exceeds 2 seconds during peaks.
📦 Native JavaScript bundle above 1.5 MB
RequireJS + Knockout + Magento UI Library forms a massive JS block users download on every visit if browser cache isn't calibrated. Main thread saturates, mobile INP turns red.
🖼️ Product images not prioritized, no next-gen formats
Native Magento doesn't set fetchpriority on the product page LCP image. WebP/AVIF formats are absent or poorly served. Product page LCP systematically drifts above 3 seconds.
🛒 Multi-step checkout with red mobile INP
Magento checkout shows Long Tasks at every step (validations, shipping/tax calculations). Profiling diagnosis identifies the bottlenecks, JS refactor or migration to a one-step checkout resolves them.
🔎 Slow categories with active layered navigation
Misconfigured ElasticSearch, numerous configurable attributes, layered navigation with range filters: 600ms to 2s to serve a category page is common without tuning. ES audit + cache fragments drops that time below 200ms.
🧱 Deep and heavy layout XML to parse
The Magento layout XML system is powerful but parsing-costly. On highly personalized pages (B2B, multi-store), parse time can represent 30% of TTFB. Layout rationalization + proper DI compilation reduces this cost.
Magento optimization methodology
4 steps to transform your performance
1. Complete stack audit
Hosting, Magento version, PHP 8.x + opcache + JIT, Varnish, ElasticSearch, Redis cache + sessions, MySQL tuning. Identify levers with highest impact.
2. Backend optimization
Activate opcache and JIT, configure Varnish FPC (TTL, cache key, ESI), Redis for cache + sessions, MySQL tuning, properly scheduled indexers and cron.
3. Frontend migration or optimization
Evaluate Hyvä migration vs native optimization. Defer non-critical JavaScript, refactor custom JS modules, prioritize LCP image.
4. ElasticSearch + checkout
ES tuning (analyzers, shards), checkout rebuild if red INP, cache fragments on categories. Post-deployment measurement via SpeedCurve or mPulse.
1. Complete stack audit
Hosting, Magento version, PHP 8.x + opcache + JIT, Varnish, ElasticSearch, Redis cache + sessions, MySQL tuning. Identify levers with highest impact.
2. Backend optimization
Activate opcache and JIT, configure Varnish FPC (TTL, cache key, ESI), Redis for cache + sessions, MySQL tuning, properly scheduled indexers and cron.
3. Frontend migration or optimization
Evaluate Hyvä migration vs native optimization. Defer non-critical JavaScript, refactor custom JS modules, prioritize LCP image.
4. ElasticSearch + checkout
ES tuning (analyzers, shards), checkout rebuild if red INP, cache fragments on categories. Post-deployment measurement via SpeedCurve or mPulse.
Mission commitments
Frequently asked questions
Should I migrate to Hyvä?
Does Adobe Commerce Cloud change available optimizations?
Magento Open Source vs Adobe Commerce for performance?
How are your Magento engagements structured?
Get your Magento Core Web Vitals green
Data 2023-2026
What my clients say
Excellent work.
Paul has significantly improved the site's speed and perfectly aligned it with Google's recommendations.
Professional, thorough, and efficient, I highly recommend.
Nicolas - April Moto
Digital & E-commerce Director
We are very satisfied with Paul's work. He is quick, available, and particularly effective. Since his arrival, very good results have been observed, both in terms of performance and responsiveness. A real asset for our team.
Léo - Luxury brand
E-commerce Product Owner
I don't know if we've said it enough.
But if you want to improve your loading speed,
Make Google happy and get your Core Web Vitals in the green,
Contact Paul Delcloy.
Florian Darroman - Les Makers
Co-founder
Magento, the most complete and heaviest e-commerce CMS
Magento 2 (Adobe Commerce) remains one of the most complete e-commerce platforms for mid-market and enterprise stores. Its flexibility has a price: it's also one of the heaviest CMSs by default, with a frontend built on RequireJS + Knockout (2014-era technologies) and a deep layout XML system that makes optimization non-trivial.
The e-commerce web performance optimization angle on Magento is multi-layer: properly configured Varnish Full Page Cache (TTL, cache key, Vary), ElasticSearch tuning for category listings, PHP opcache and JIT, MySQL tuning, and increasingly a migration to Hyvä Themes (a modern frontend replacing RequireJS/Knockout with AlpineJS + Tailwind).
Hyvä, the game-changing frontend lever
The native Magento frontend is obsolete for Core Web Vitals. RequireJS and Knockout load in bulk, the main thread saturates, mobile INP drifts systematically. Hyvä is an alternative theme built on Tailwind + AlpineJS that divides JavaScript weight by 5 to 10 and gains a second or more on mobile LCP.
Hyvä migration is a project in itself, but the webperf ROI is massive. For stores that can't migrate immediately, native frontend optimization remains possible (aggressive deferral, JS module rebuild, useless features removal) with more modest gains.
Checkout and catalog, two critical templates
On a Magento store, two templates concentrate the performance stake: the product page (LCP critical for catalog SEO) and the checkout (INP critical for conversion). The native Magento checkout is complex — multi-step, JS validations, AJAX tax/shipping calculations — and regularly shows red INP on mobile. Profiling diagnosis identifies Long Tasks for refactoring.
The other angle is ElasticSearch indexing on category listings. A category with 2000 SKUs, 30 filters and 5 configurable attributes can take 600ms to build if the index is misconfigured. ES tuning (analyzers, shards, sorting) drops that time below 100ms.
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