Case Study
L1 Market Data Engine
Real-time market data ingestion and distribution platform for low-latency trading applications.
Overview
A real-time market data engine that consumes exchange feeds, computes trading metrics, and exposes normalized market information through WebSocket interfaces.
Architecture
Exchange WebSocket feeds are ingested and normalized into a common schema. Market metrics such as spread, mid-price, VWAP, and trade velocity are computed in real time and distributed through a FastAPI WebSocket layer.
Tech Stack
System Design
The system separates ingestion, processing, analytics, and distribution into independent stages. A rolling in-memory buffer stores recent market events for metric computation and visualization.
Challenges
- 01Synchronizing trade and quote streams arriving independently
- 02Maintaining low-latency calculations without blocking ingestion
- 03Designing a reusable schema for future multi-exchange support
Implementation
Implemented concurrent WebSocket consumers for trades and quotes, rolling VWAP calculations, spread tracking, mid-price computation, and real-time broadcasting to connected clients.
Results
Successfully processed live market streams while maintaining responsive downstream updates suitable for trading dashboards and future strategy development.
Lessons Learned
- —Market data quality is more important than raw throughput
- —Streaming systems require careful separation of ingestion and processing
- —Observability becomes critical as data rates increase