Ever wonder why some teams intentionally break their own systems? Welcome to the world of chaos engineering — a practice that's not just for Netflix-scale infrastructure, but for any team that wants to build resilient, reliable applications.

In this session, we'll demystify chaos engineering and explain why intentionally breaking things is actually the smart move. You'll learn:

• What chaos engineering really is (in plain English, no buzzwords)
• Why waiting for production failures is a terrible strategy
• How to start experimenting with controlled failure locally, before it happens in the wild
• Real-world examples of chaos experiments that catch bugs you'd never find in traditional testing
• Tools and techniques to get started without blowing up your infrastructure

Through practical demos using LocalStack's cloud emulation and chaos engineering tools, we'll simulate failures like network latency, service outages, and resource exhaustion right from your laptop.

If you've ever said "it worked on my machine" only to watch it crash in production, this talk is for you—let's break things intentionally so they don't break unexpectedly.

What if your AI coding assistant could not only write infrastructure code, but also deploy it, test it, and fix issues automatically — all on your local machine? That's exactly what the LocalStack MCP Server makes possible.

In this session, we'll introduce the LocalStack Model Context Protocol (MCP) Server, a new tool that lets AI agents manage your entire local cloud development lifecycle through a conversational interface. You'll learn:

• What MCP is and why it's a game-changer for AI-assisted development
• How the LocalStack MCP Server turns manual cloud tasks into automated workflows
• How to set up and configure the server with your favorite AI editor (Cursor, VS Code, etc.)
• Real-world demos: deploying CDK apps, analyzing logs, running chaos tests, managing state with Cloud Pods, and more.

Through hands-on examples, we'll walk through a complete workflow where an AI agent deploys a serverless application, verifies resources, troubleshoots issues, and tests resilience, all without leaving the conversation.

If you've ever wished your AI assistant could do more than just generate code, this talk will show you what's possible when agents can actually manage your local cloud environment.