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FinTechDhanYatri
High-Frequency Algo Trading & Alert System
Key Growth Metric
50k+ Concurrent Users
Industry
Financial Technology
Client
DhanYatri
01. The Challenge
DhanYatri faced a critical bottleneck: their legacy monolithic system couldn't handle the massive data spikes during market opening hours. Traders were receiving price alerts with a 2-3 second delay, which is catastrophic in high-frequency trading. They needed a system that could process millions of market ticks per second and push mobile notifications instantly.
02. Our Solution
We architected a completely new, event-driven trading engine. By shifting from a monolith to a distributed microservices model using Node.js and Go, we isolated the data ingestion, signal computation, and notification layers. We used Kafka for real-time stream processing and implemented a custom WebSocket layer for instant client communication. The infrastructure was deployed on a multi-region Kubernetes cluster with automated scaling.
03. The Results
The transition was transformative. Alert latency dropped from 3000ms to under 50ms. The platform now seamlessly handles over 50,000 concurrent users during market peak hours without a single minute of downtime in the last 12 months. This digital transformation directly led to a 400% increase in trading volume on the platform.
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