KITE ENGINE
ARCHITECTURE

Latency

< 50ms

Role

Systems Engineer

Focus

WebSockets & Redis

Stack

MERN + Socket.io

01 // The Architecture

Financial applications cannot rely on standard HTTP request/response cycles. If a user has to refresh the page to see a price change, the platform is already obsolete.

I designed a highly concurrent architecture using Node.js for the main server, Redis for fast in-memory pub/sub message brokering, and WebSockets (Socket.io) to push binary market data directly to the React client.

React Client
UI / Charting
Node.js API
Socket.io Server
Redis
Pub/Sub Broker

02 // Order Execution

When a user places a trade, speed and reliability are paramount. The order is instantly validated on the backend and pushed to the matching engine.

orderService.js
const processOrder = async(orderData) => {// 1. Validate marginconst user = await User.findById(orderData.userId);if(user.margin < orderData.requiredMargin) {throw new Error('Insufficient Funds');}// 2. Publish to Redis Queue for Matching Engineawait redisClient.publish('order_channel', JSON.stringify(orderData));// 3. Acknowledge receipt to client instantlyreturn { status: 'PENDING', orderId: orderData.id };};
Live Order Firehose (Simulated)

03 // The Data Firehose

Rendering thousands of data points on a frontend chart (like TradingView or custom Canvas charts) causes massive DOM bottlenecking if done incorrectly.

To solve this, I completely bypassed React's standard rendering cycle for the charts. Instead, incoming socket data is fed directly into a raw HTML5 `<canvas>` context. This ensures steady 60FPS animations even when the market is highly volatile and receiving hundreds of ticks per second.