Rebuilding a Payment Dashboard for 3× Performance at Scale
Key Brains didn't just rebuild our platform — they gave us a system we can grow into for the next decade. The migration was seamless, and the results were immediate.
-- Rahul Nair, CTO, ClearPay Inc.
The Challenge
ClearPay had grown rapidly from Series A to Series B, but their monolithic PHP application was buckling under 10× user growth. Transaction failures were climbing, API response times had ballooned to 8+ seconds during peak load, and their engineering team spent more time firefighting than shipping new features.
They came to us with a clear mandate: modernize the architecture, eliminate downtime, and create a foundation that could support 100× growth — all without interrupting a single live transaction.
Our Approach
We started with a 3-week discovery sprint — instrumenting the existing system, mapping every data flow, and identifying the 20% of the codebase causing 80% of the performance issues. Rather than a risky big-bang rewrite, we designed a strangler fig migration strategy: incrementally replacing services while the monolith remained live.
The Solution
We extracted the payment processing core into an isolated microservice deployed on Kubernetes with horizontal auto-scaling. A new event-driven architecture via Apache Kafka handled real-time transaction streams. The dashboard UI was rebuilt in React with WebSocket connections for live updates. A shadow deployment strategy let us run old and new systems in parallel for 6 weeks before cutover.
The Results
Within 30 days of cutover, transaction processing times dropped from 8.2s to under 2.7s. The engineering team reduced incident response time by 80% thanks to new observability tooling. ClearPay successfully closed their Series C two months later, citing infrastructure stability as a key investor signal.