LocalStack Resource Library

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.

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.

What if your software could fix its own bugs—before anyone even notices them? In this session, LogicStar co-founder Boris Paskalev shares how self-healing applications are becoming a reality—fixing bugs automatically, before they reach production or immediately after an issue is detected/reported. LogicStar combines classical computer science, deep tech research from the pioneers of “AI for Code” and Agentic AI to detect, reproduce, and fix real production issues with validated, test-backed pull requests.This session is for engineering leaders, PMs, and AI builders ready to rethink the boundaries of autonomy in software delivery.

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- Integration tips with Docker, Kubernetes, and beyondWhether 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.

Modern software systems operate in complex, dynamic environments where failures are inevitable. Traditional monitoring and manual incident response are no longer sufficient to ensure resilience or customer satisfaction. This talk explores how to design and implement self-healing software systems by combining telemetry data with an AI-driven agentic approach. We’ll start by examining how high-quality telemetry forms the foundation for detecting anomalies and predicting failures. Next, we’ll show how modern GenAI (LLMs) can transform this telemetry into actionable insights for AI agents that interpret data, pinpoint root causes, and apply automated fixes. Through a practical, real-world example, you’ll see how telemetry and AI work together to create adaptive feedback loops that continuously improve system reliability, while freeing engineers from repetitive operational tasks.

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.

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.

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.

Building and debugging cloud-native applications often involves slow CI/CD pipelines, hard-to-reproduce bugs, and the need for costly shared environments. LocalStack offers a better way — letting developers simulate real AWS services entirely on their local machine. In this presentation, Kiah Imani gives a hands-on walkthrough of building and testing AWS workflows locally with LocalStack. From Lambda functions to S3 pre-signed uploads and SNS/SQS pipelines, you'll see how to prototype, debug, and iterate on cloud-native apps without ever deploying to the cloud.