Unlocking ease of use for deployment across LocalStack and AWS

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—and without access to create or modify resource configurations.* Simplifying the deployment experience by eliminating complexity and security requirements to run environments on AWS.* Tracking all activity to identify performance issues for LocalStack deployments and wasted cloud costs for AWS deployments proactively.

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Saving & Sharing Your LocalStack State with CloudPods

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/

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Running dbt workflows locally with LocalStack

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.

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Running an EC2 instance locally using LocalStack

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