In the high-stakes world of algorithmic trading, infrastructure costs and execution latency are the primary enemies of alpha. But what if you could run a production-grade, event-driven trading engine for less than the cost of a cup of coffee per year?
This session explores the architectural blueprint of LambdaForge, an open-source trading platform built entirely on a serverless stack. We will break down how to orchestrate Python microservices, AWS Lambda, and EventBridge to handle real-time market data and execute high-stakes trades with sub-second latency, all while maintaining an operational cost of ~$0.15/month.