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.

Creating data pipelines and applications for the cloud comes with challenges like a complicated developer experience, dealing with managed cloud dependencies, and enduring long build times. These issues often disrupt your development and testing cycles. LocalStack's cloud emulation allows you to construct, deploy, and test data pipelines on your local machine. It facilitates integration testing of cloud solutions both locally and in CI pipelines. This approach saves time and money, enhances developer velocity, and supports high-quality, agile, test-driven development. In this talk, Harsh delves into developing and testing cloud-based data pipelines on your local machine. The session will provide a firsthand look at the new Snowflake emulator and demonstrate how you can use LocalStack to create Snowflake warehouses, databases, schemas, and tables, and integrate frameworks like Snowpark.

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.

Running AI/ML workloads in the cloud can be expensive, opaque, and difficult to iterate on. LocalStack changes this by enabling engineers to develop and test AI-powered cloud applications entirely locally, emulating services like SageMaker, Bedrock, Redshift, and Snowflake. In this presentation, Waldemar Hummer, CTO of LocalStack, demonstrates how to prototype and validate AI & ML data pipelines safely and cost-effectively using LocalStack’s cloud emulators. You’ll see how to emulate complex AI workflows, test integrations, and use “vibe coding” techniques confidently in a fully sandboxed local environment.