Building a Real-Time Market Monitoring Platform

Building a Real-Time Market Monitoring Platform

After spending months building Tredye, a real-time market monitoring platform, I've accumulated valuable insights into the unique challenges of systems that stream live market data. Here's what I learned.

The Challenge of Real-Time

Live market monitoring has requirements that push traditional web architectures to their limits:

• Low latency: Price updates must reach users as they happen
• High throughput: Thousands of events per second per user
• Data consistency: Every tick must land once, in order
• Always-on reliability: Downtime in market hours leaves users blind

Architecture Decisions

Message-Driven Architecture

We chose Apache Kafka as our event backbone. Every price tick and market event flows through Kafka topics. This provides:

1. Durability: Events are persisted and can be replayed
2. Ordering: Critical for maintaining price history
3. Scalability: Easy to add more consumers as load increases

WebSocket Strategy

REST APIs don't cut it for real-time data. We implemented a WebSocket layer with:

• Connection pooling: Efficient resource management
• Heartbeat mechanism: Detect and recover from stale connections
• Reconnection logic: Automatic recovery with exponential backoff
• Message batching: Aggregate updates within animation frames

State Management

The frontend uses a carefully designed state architecture:

// Tick batching for smooth updates
const tickBuffer = new Map<string, PriceTick>();
const BATCH_INTERVAL = 16; // 60fps

setInterval(() => {
  if (tickBuffer.size > 0) {
    updatePrices(Array.from(tickBuffer.values()));
    tickBuffer.clear();
  }
}, BATCH_INTERVAL);

Lessons Learned

1. Measure Everything

Without metrics, you're flying blind. We instrumented:

• WebSocket message latency
• End-to-end tick delay, from the feed to the screen
• UI render performance
• Database query duration

2. Plan for Failure

In a live market feed, failure modes must be well-defined:

• What happens when Kafka is down?
• How do we handle database failover?
• What's the degraded experience for users?

3. Test Under Load

We discovered critical bugs only under production-like load. Invest in load testing infrastructure early.

Conclusion

Building real-time market monitoring is challenging but rewarding. The key is embracing event-driven architecture, investing in observability, and planning for failure from day one.