TTFB & backend profiling
Profiling with the tools that show the truth — Blackfire, xhprof, slow query logs — to find where time actually goes.
Magento Performance
Emyrix makes Magento 2 stores fast where it counts — server response time, cache, search, and Core Web Vitals — so pages load quickly and checkout holds up under real traffic. We fix the infrastructure and code ceiling, not just the Lighthouse score.
Magento & Adobe Commerce engineering from Massachusetts, serving e-commerce businesses across the United States.
Overview
Most Magento performance projects start in the wrong place: someone runs Lighthouse, sees red, and spends weeks minifying CSS while the server still takes over a second to return the first byte of HTML. We start with the layer that sets the ceiling for every page — TTFB, full-page cache, Redis, OpenSearch, PHP, and the database — then move to page-type and frontend work once the foundation is solid.
The goal is not a one-time score bump. It is a store that stays fast as the catalog grows and traffic spikes, measured against real business metrics rather than a synthetic lab run.
Services
Profiling with the tools that show the truth — Blackfire, xhprof, slow query logs — to find where time actually goes.
Correct FPC and Varnish configuration, cache warming, and hole-punching so hits are fast and misses are rare.
Redis for cache and sessions, configured and separated properly instead of the defaults that stall under load.
Search and catalog indexing tuned so category and layered-navigation pages stay quick with large catalogs.
Query optimization, index management, and flat-catalog decisions based on your data, not folklore.
LCP, CLS, and INP work on category, product, and checkout pages — measured in the field, not just the lab.
Why Emyrix
We profile before we touch anything, so effort goes where the time is actually being spent.
Priority on the templates that carry revenue — category, product, and checkout — not just the homepage.
Fixes hold at peak-season traffic, not only on an empty staging box.
FAQ
Usually the backend, not the frontend: slow TTFB from missing or misconfigured full-page cache, an under-tuned Redis or database, or heavy custom code. We profile to find the real cause before recommending work.
Yes. We work on LCP, CLS, and INP across category, product, and checkout pages, and measure against field data (real users), not just a lab score.
Speed is one factor among many, but slow category and checkout pages measurably cost sales. We prioritize the templates that carry revenue so the work pays for itself.
Both. We tune existing Luma stores and, where it is the better long-term move, migrate to Hyvä for a lighter frontend.
Related
Let's work together
Share the platform, the problem, and the goal — we'll come back with the best next step.