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Projected peak traffic multiplier
P99 page load time (was 4.2s)
Projected on-call alert reduction
Delivery timeline
01 — The challenge
Black Friday 2023 was a disaster. Their monolithic PHP storefront collapsed at 09:14 CET. Cart abandonment hit 67%. The CEO watched revenue drop in real time on a dashboard in the office. They spent €180K on emergency cloud scaling that day, most of it on over-provisioned VMs that sat idle by Monday. For 2024, they had two options: hire a 40-person platform team, or fix the architecture. They chose the latter and gave us 14 weeks.
02 — Our approach
We would containerise the storefront and checkout flows, but the real work would not be the containers — it would be understanding traffic patterns. We would spend the first 3 weeks tracing every user journey and expect to find that the majority of database load comes from a handful of N+1 query patterns in the product catalog. Fixing those queries would give more headroom than any infrastructure change. We would add a CDN with edge caching for static assets and product images, build autoscaling that reacts to queue depth (not just CPU), and set up a war room dashboard the business team can actually read — revenue per minute, not CPU percentage. The biggest negotiation would likely be with the merchandising team: they want to push price updates live every 15 minutes, which busts the cache. We would work toward a batch window during peak hours.
03 — Expected outcomes
Projected handling of 10×+ peak traffic with zero downtime across a multi-day campaign window
P99 page load time expected to fall from 4.2 seconds to under 1.2 seconds — sub-second may be blocked by third-party widgets
Cart abandonment projected to drop significantly during peak traffic (the remaining rate depends on UX and merchandising decisions)
On-call alerts during the campaign window expected to fall by over 50% through better autoscaling and caching
Ready to start
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