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.Providing modular examples that can be deployed to AWS or LocalStack with ease, enabling developers to explore libraries.

In this live session, Brian from LocalStack will demonstrate the WireMock extension for LocalStack, showing how developers can achieve end-to-end local testing by combining AWS service emulation with external API mocking. Brian will walk through real-world use cases, demonstrate the integration in action, and explain how this unified approach simplifies testing complex cloud applications that depend on both AWS services and third-party APIs.

In this live session, WireMock CTO Tom Akehurst will introduce hybrid API simulation (local + cloud) with WireMock Runner. Tom will explain why we built Runner, how developers are using it today, and how it fits into modern dev and test workflows - such as simulating APIs during testing, prototyping, and AI-native development.

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 developmentHow the LocalStack MCP Server turns manual cloud tasks into automated workflowsHow 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.