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## Introduction
After building and maintaining 15+ automated trading bots in production — processing hundreds of orders per month — I want to share the key architectural decisions that made the difference between a fragile prototype and a reliable production system.
## The Core Challenge
Real-time trading systems have unforgiving requirements:
- **Latency**: Every millisecond matters. A slow system misses opportunities.
- **Reliability**: Downtime = missed trades = financial impact.
- **Concurrency**: You need to handle multiple data streams and order executions simultaneously.
## WebSocket Architecture
The foundation of any real-time trading system is a solid WebSocket connection manager.
```typescript
class ConnectionManager {
private ws: WebSocket | null = null;
private reconnectDelay = 1000;
private maxReconnectDelay = 30000;
connect(url: string) {
this.ws = new WebSocket(url);
this.ws.on('open', () => {
this.reconnectDelay = 1000; // reset on success
this.onConnected();
});
this.ws.on('close', () => this.scheduleReconnect());
this.ws.on('error', (err) => this.handleError(err));
}
private scheduleReconnect() {
setTimeout(() => {
this.reconnectDelay = Math.min(
this.reconnectDelay * 2,
this.maxReconnectDelay
);
this.connect(this.url);
}, this.reconnectDelay);
}
}
```
The exponential backoff is critical — without it, you'll hammer the server with reconnection attempts during an outage.
## Order Execution Pipeline
```typescript
interface OrderJob {
id: string;
symbol: string;
side: 'buy' | 'sell';
quantity: number;
price?: number;
priority: number;
}
class OrderQueue {
private queue: PriorityQueue<OrderJob>;
async process(job: OrderJob): Promise<void> {
const result = await this.execute(job);
await this.persistResult(result);
this.emit('order:filled', result);
}
}
```
## Key Lessons
1. **Always implement circuit breakers** — if the exchange API starts failing, stop sending orders immediately.
2. **Persist every state change** — you need to reconstruct system state after a crash.
3. **Monitor latency percentiles, not averages** — p99 latency is what kills you in production.
4. **Test with real market data** — paper trading with historical data is not enough.
## Conclusion
Building reliable trading systems is fundamentally an exercise in distributed systems design. The trading domain just adds time pressure.
The patterns described here have served our fleet of 15+ bots through volatile market conditions. Start with a solid foundation — connection resilience, state persistence, and monitoring — and the trading logic becomes almost secondary.
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