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 strategyHow to start experimenting with controlled failure locally, before it happens in the wildReal-world examples of chaos experiments that catch bugs you'd never find in traditional testingTools and techniques to get started without blowing up your infrastructureThrough 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.

Why wait for the cloud to test your app? In this episode, we’ll write and run an integration test to validate our LocalStack app. You’ll learn how to upload a file, trigger the Lambda-SQS-DynamoDB flow, and assert the results all locally.

Testing AWS CI/CD pipelines in the cloud can be slow, error-prone, and hard to debug, especially when you're wrestling with IAM permissions or waiting on long feedback cycles. This session walks through how you can now emulate complete DevOps workflows locally using LocalStack.We cover recent additions to LocalStack that support new service providers such as: CodeBuild: Run build processes across different runtimes directly on your machine CodeDeploy: Emulate deployment steps without touching the real infrastructure CodePipeline: Create and test CI pipelines, transitions, and triggers locallyThrough a live demo, we’ll walk through a working example of a CI/CD pipeline — building a Rust project, deploying it, and running the pipeline stages — all without leaving your laptop.This session is useful for developers building or debugging AWS-native CI/CD workflows and looking for faster, more controlled ways to test them.

dbt (Data Build Tool) helps data engineers manage data transformations using modular SQL and brings version control, testing, and documentation to their transformation logic. However, running dbt against production data warehouses like Snowflake can be slow, expensive, and risky.This session introduces a new way to develop and test dbt workflows locally using the Snowflake emulator in LocalStack. You'll learn how to: Set up a local dbt environment Configure dbt to connect to the Snowflake emulator Run and validate dbt models locally without using a real Snowflake account Iterate quickly on transformations before pushing them to productionThrough a hands-on factory app example, we’ll walk through how to use the Snowflake emulator to run dbt models on your laptop, helping you test logic, catch issues early, and reduce cloud costs.