Running dbt workflows locally with LocalStack

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.

Get started with LocalStack in minutes! In this episode, we’ll clone a ready-to-go AWS sample app, spin up LocalStack, and run everything locally without a cloud account. By the end, you’ll have a fully functional event-driven app running on your machine.📖 Want more?Check out the companion blog post for a deeper breakdown of the architecture, project structure, and all the commands you’ll need to run it yourself.🔗 https://blog.localstack.cloud/why-i-run-my-serverless-apps-locally/

This is where it all comes together.CI/CD lets dev teams ship code automatically — but only if your pipeline is built to handle the cloud.In this episode, I show you how local testing + automated deployment = cloud apps that ship faster, safer, and smarter.Stick around to the end, this is the final episode of WTH is the Cloud?!