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.

Recreating the unique state of a cloud app environment is notoriously complex, making it difficult to diagnose bugs, collaborate with teammates, or even just pick up where you left off. Join us as we deep dive into LocalStack’s powerful state management and persistence features, exploring how to maintain, snapshot, and seamlessly share your local cloud environments using core features like persistence, Cloud Pods, and state files. Learn how to restore a previous state, share preconfigured environments with colleagues for collaboration or onboarding, or restore preset services and data for functional tests in CI. We'll also showcase LocalStack's new Model Context Protocol (MCP) integration, revealing how AI can manage, inspect, and automate your local cloud state.

An agent will write you a CDK stack, a Terraform module, or a stack of IAM policies in seconds.
Whether any of it works is a separate question, and the usual way to find out is to deploy to a real AWS account and watch what breaks.
In an agentic workflow, that means giving AI access to a public cloud account, racking up costs on the AWS bill, and waiting for provisioning to complete every time you push new code to the environment.

The rise of agentic AI in the software delivery lifecycle creates a dilemma with high-stakes implications.
As agents create new applications at an unprecedented rate, how do you integrate security without slowing down delivery?