World Congress 2026 North America

The $0.15/month Algo-Trader: Architecting High-Performance Serverless Trading Engines

September 25, 2026 14:50 – 15:20 · 30 min Stage 7

World Congress 2026 North America

September 23–25, 2026 · San José, CA

Attend in person

Get tickets

Watch remotely

Watch live with Pro

Pro

Can’t make it to San José? Watch this session live with Pro. You also get:

  • All full videos, bookmarks, and playlists
  • World Congress livestreams
See pricing

What this session covers

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.

Related talks at this congress

Open session

World Congress 2026 North America

September 25, 2026 · 16:00–16:10

Outdoor Stage

public void saveMoney(AI): The Developer's Guide to Unit Economics

Hrushikesh Pokala

Senior Software Engineer Lead at Equifax

Hrushikesh Pokala
Open session

World Congress 2026 North America

September 25, 2026 · 12:55–13:25

Stage 9

It’s Alive! Taming the MLOps Franken-Stack: Write, Run, and Serve with Michelangelo

Eric Wang, Paul Zimmerman

Eric Wang
Paul Zimmerman
Open session

World Congress 2026 North America

September 23, 2026 · 10:45–12:45

Stage 10

Agents That Own Their Inference: Building Production AI Agents on Dedicated GPUs

Duan Lightfoot

Sr. AI Engineer, Akamai

Duan Lightfoot
Open session

World Congress 2026 North America

September 24, 2026 · 14:10–14:40

Stage 1

Anatomy of an AI Request: Where Latency and Cost Are Really Born

Dan Fu

VP of Kernels at Together AI

Dan Fu
All sessions at this congress