Real-Time FinTech Dashboard
Engineering a 500k events/sec trading analytics platform with sub-50ms end-to-end latency.
The Problem
A quantitative hedge fund needed a real-time analytics dashboard giving portfolio managers millisecond-level visibility into their positions, P&L, and market exposure across 12 asset classes simultaneously. Their existing solution — a Tableau dashboard refreshing every 5 minutes — was causing traders to make decisions on stale data, resulting in significant slippage costs.
The core engineering challenge was extreme: the platform needed to ingest upwards of 500,000 market events per second from multiple exchange feeds, compute derived metrics (VWAP, Greeks, rolling volatility) in real time, and push updates to active browser sessions within 50ms end-to-end — all while maintaining strict data integrity for regulatory audit trails.
The Architecture
The ingestion layer was built on Apache Kafka with a dedicated cluster of 9 brokers partitioned by asset class, giving us horizontal throughput scaling to 1M+ events/sec with sub-5ms producer-to-consumer latency. A fleet of Python Kafka consumers performed stateless metric computation (VWAP, Greeks) using Pandas + Numba JIT compilation, then wrote enriched events to ClickHouse — a columnar OLAP database capable of ingesting 1M rows/sec per server and returning complex time-series aggregations in under 10ms.
The WebSocket layer was built on a Node.js cluster behind an nginx TCP load balancer. Each WebSocket server maintained subscriptions per dashboard widget, performing delta diffing before broadcasting — only changed values were transmitted, cutting payload sizes by 80%. Connection state was managed via Redis Pub/Sub, ensuring seamless failover if a WebSocket server restarted.
The React frontend used a custom subscription hook wrapping the WebSocket connection, with immutable state updates via Immer. Charts rendered with D3.js on an offscreen canvas, transferred to a visible canvas via OffscreenCanvas API — keeping the main thread free for user interactions even during high-frequency updates.
Technology Stack
The Outcome
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