
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.

With the growing Serverless workloads, managing and maintaining them is best recommended with Infrastructure as Code (IaC). While this holds the complete infrastructure and its configurations, we could have events from one service destined to another via configuration. When building these configurations, we could also reduce the application code making it more maintainable and scalable.In this session, Jones walked us through a fully end-to-end solution built with Amazon EventBridge and AWS Step Functions with SDK integrations which have helped him to improvise the application with just IaC and very minimal application code.

Tired of rebuilding your stack from scratch every time you run tests or restart your dev environment? In this episode, we dive into Cloud Pods, LocalStack’s powerful state management feature.You’ll learn how to:- Snapshot your entire LocalStack environment (services, resources, data)- Restore that exact state across machines, teams, or CI runs- Speed up test cycles and workflows- Use Cloud Pods to make testing in CI/CD faster and more reliableCloud Pods let you freeze your infrastructure in time. Perfect for repeatable tests, isolated dev environments, or onboarding new teammates.🔗 Read the companion blog post: https://blog.localstack.cloud/save-and-share-localstack-state-with-cloudpods/

dbt (Data Build Tool) helps data engineers manage data transformations using modular SQL and brings version control, testing, and documentation to their transformation logic. However, running dbt against production data warehouses like Snowflake can be slow, expensive, and risky.This session introduces a new way to develop and test dbt workflows locally using the Snowflake emulator in LocalStack. You'll learn how to: Set up a local dbt environment Configure dbt to connect to the Snowflake emulator Run and validate dbt models locally without using a real Snowflake account Iterate quickly on transformations before pushing them to productionThrough a hands-on factory app example, we’ll walk through how to use the Snowflake emulator to run dbt models on your laptop, helping you test logic, catch issues early, and reduce cloud costs.