Unlocking ease of use for deployment across LocalStack and AWS

When it comes to productivity, developer experience is more than just a buzzword. Creating an intuitive developer experience could help you get more out of LocalStack by democratizing access, cutting out manual tasks, and making environments more easily interchangeable between LocalStack and AWS. On a day-to-day basis, this could mean fewer tickets, less time spent creating environments, and more time on the important work that your environments support. This demo session will show how LocalStack’s new integration with Quali Torque can accelerate deployment on both LocalStack and AWS by using generative AI to create reusable environment templates that can be deployed to LocalStack and AWS interchangeably in just a few clicks, providing a self-service catalog for your teams to find and provision environments quickly and easily without access to create or modify resource configurations, simplifying the deployment experience by eliminating complexity and security requirements to run environments on AWS, and tracking all activity to identify performance issues for LocalStack deployments and wasted cloud costs for AWS deployments proactively.

Related Talks

Getting started with the LocalStack Model Context Protocol (MCP) Server

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.

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Getting started with the LocalStack Dagger module

Looking to bring AWS emulation directly into your CI/CD pipelines? This hands-on session with Harsh Mishra shows you how to integrate LocalStack with Dagger to level up your development workflows. In this session, you'll learn how to run full AWS emulation locally inside Dagger pipelines, spin up LocalStack as a service using Dagger’s composable syntax, use Cloud Pods for persistent state across pipeline runs, and create ephemeral environments for fast, clean, isolated testing. Keep your cloud workflows repeatable, testable, and fast. Whether you’re building serverless apps, managing infrastructure-as-code, or optimizing your DevOps pipelines, this talk will help you bring LocalStack into the heart of your CI/CD setup.

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Getting started with LocalStack's Extension for Docker Desktop

LocalStack's Docker Extension allows developers to manage and run cloud applications locally within Docker Desktop efficiently. With a fully-integrated experience with features such as configuration profiles, container logs, and more, developers can now easily manage their LocalStack instance. In this video, Harsh from LocalStack discusses the LocalStack Docker Extension and how you can capitalize on an intuitive user experience to manage your LocalStack image, configuration profiles, and container logs directly within the Docker Desktop.

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