Magento 2 performance
Measure where the wait begins
We connect frontend measurements with Magento profiling, logs, caching and infrastructure to identify the actual bottleneck.
Evidence-led optimisation
A fast homepage does not prove Magento performance
Magento performance varies by page, customer state, cache and load. We measure representative journeys and separate browser work, application time, database activity, external services and infrastructure. Optimisation is prioritised only after that evidence exists.
Core Web Vitals help describe user experience but do not explain why an uncached category, checkout step or cron process is slow. Both perspectives belong in the same investigation.
01
Different causes of poor performance
The same slow page can originate in code, data, cache or an external dependency.
TTFB spikes on certain pages
Uncached requests, plugins or database queries keep PHP busy too long.
The frontend feels heavy
JavaScript, fonts, images or layout shifts delay rendering and interaction.
Caching is unpredictable
Varnish, full-page cache, Redis or invalidation do not produce stable behaviour.
Traffic peaks cause failures
Bots, imports, indexers, queues or external APIs compete for capacity.
02
Performance across every layer
We select measurements that reflect real customer and operational journeys, recording environment, cache state and test conditions.
Frontend measurement
Core Web Vitals, waterfalls, rendering and resources per representative template.
Application profiling
Investigate slow code paths, plugins, observers, blocks and external calls.
Data and caching
Analyse queries, indexers, Redis, full-page cache and invalidation.
Priority plan
Order opportunities transparently by impact, complexity and risk.
03
From complaint to measurable improvement
No disconnected optimisation tips without a baseline.
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01
Measurement plan
Select representative pages, journeys, cache states and load.
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02
Baseline
Record browser and server measurements with versions and conditions.
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03
Validate bottleneck
Confirm hypotheses through profiling, logs or controlled tests.
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04
Improve and remeasure
Measure changes separately so their effect remains attributable.
04A
Suitable when
- Performance differs by journey
- Your team cannot identify the bottleneck
- Caching or infrastructure is complex
- You need an evidence-based priority list
04B
Not responsible to promise
- A universal score of 100
- A fixed speed increase without baseline
- Conversion growth from engineering alone
- Unbounded production load tests
Technical questions answered
No. We combine user-facing metrics with server, application, database and cache analysis.
Hyvä can significantly simplify the frontend, but results still depend on implementation, content, extensions, backend and infrastructure.
Yes. Unwanted crawling can generate uncached requests and search activity. We first establish which traffic creates actual load.
That is agreed in advance. An audit can stand alone or be followed by phased implementation and remeasurement.
Technical intake
Personally reviewed