LocalStack enables organizations to automate their application testing and integration process through DevOps practices, such as continuous integration (CI). LocalStack allows organizations to move away from complicated AWS testing and staging environments by enabling a key component of testing and delivering cloud-native applications.To further automate the process, we use Infrastructure-as-Code (IaC) frameworks like Terraform that allow you to create your resources declaratively and apply those resources. Testing your Terraform modules against the real AWS cloud can be time-consuming and costly and can make you run into the risk of dangling resources after an unsuccessful CI run. Using LocalStack to emulate a mock ephemeral AWS infrastructure on CI pipelines allows you to work on the same functionality the real AWS cloud provides while cutting down testing costs and deployment times.In this session, Jim Sheldon, Senior Developer Advocate at Harness, will demonstrate how to use LocalStack to test Terraform modules on Harness CI. Harness CI allows you to create software pipelines that will enable you to check out your code, build the software, run your tests, and validate every code change. We wind up the session with updates about the all-new LocalStack release!

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?