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.), and 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.

Want to modernize your CI/CD workflows? 🚀 In this session, Jason McCallister introduces Dagger, the open-source programmable CI/CD engine that’s redefining how we build, test, and ship software. You'll learn what makes Dagger different from traditional CI/CD tools, how to write pipelines as code and run them locally, how to compose reusable, testable pipeline components, real-world examples of solving CI headaches with Dagger, and integration tips with Docker, Kubernetes, and beyond. Whether you’re a DevOps pro, platform engineer, or just tired of brittle YAML, this talk will show you how Dagger helps you ship faster and smarter.

For one-off tasks, AWS Lambda really can be incredibly easy. You write a few lines of code, deploy it, and you have a function running in the cloud ready to respond to events, scale automatically, and that only costs you pennies. But as your application grows, so does some necessary complexity. When a few one-off functions become a full serverless backend architecture made up of interconnected services, you’ll need to pay careful attention to best practices to ensure that your application is easy to debug, maintain, and scale. That’s where AWS Powertools for Lambda fits in. It’s a suite of reusable utilities designed to simplify bringing best practices around things like logging, tracing, metrics, idempotency and more to your Lambda functions with minimal effort. This demo session will dive into some of the functionality provided by the AWS Powertools (TypeScript) core libraries, such as encapsulating best practices into reusable libraries for structured logging, metrics collection, idempotency, and more; leveraging Middy middleware to integrate common cross-cutting concerns, such as injecting Lambda context or automatically flushing metric; enabling local testing with LocalStack, allowing you to deploy and debug Lambda functions with structured logs, trace data, and embedded metrics; and providing modular examples that can be deployed to AWS or LocalStack with ease, enabling developers to explore libraries.

LocalStack Applications in Developer Hub provides sample templates to help LocalStack users adopt real-world scenarios to rapidly and conveniently create, configure, and deploy applications locally.
Getting started with Step-up-authentication demo
In this demo, we will setup a step-up authentication workflow for a higher level of security, deployed using Cloud Development Kit on LocalStack