
Developers are used to running kubectl apply and waiting on the magic to happen resulting in a running Kubernetes pod. But what actually happens between entering the command and the deployment being ready? What's the reality behind the "magic"? In this talk, Kiah will dissect all the stages of a Kubernetes deployment in a way that is easy to understand. She'll walk through that deployment happening locally on LocalStack to inspect what's really going on at each stage. At the end of this session, attendees will have a deeper understanding of the Kubernetes deployment process that can help debug many common issues and will gain an understanding of how LocalStack enables local testing of Kubernetes.

Multi-account and multi-region compatibility enables users to manage and deploy resources across multiple AWS accounts and geographic regions. This functionality enhances the robustness of the deployments by offering improved fault tolerance, scalability, and regulatory compliance. By segregating resources into separate accounts and distributing them across various regions, users can minimize the impact of potential failures and optimize performance. In this session from LocalStack Community Meetup May '24, Sannya Singhal discussed how you could use LocalStack to emulate multi-account and multi-region environments locally for testing and development purposes, ensuring that applications were resilient and scalable before deployment to the cloud.

LocalStack's cloud emulator lets you run Amazon Elastic Container Service (ECS) clusters and tasks on your local computer. It's sometimes useful to mount code from the host filesystem directly into the ECS container. This helps quickly test changes without needing to rebuild and redeploy the ECS Task's Docker image each time. This video explains how to use code mounting with the ECS bind mounts feature.

We’re partnering with gdotv to simplify development with our Amazon Neptune cloud emulator component. You can now easily query, visualise and model your graph data either interactively or using the Gremlin querying language with G.V() - Gremlin IDE. With G.V(), you can considerably enhance your graph database development experience whilst gaining access to a powerful reporting and visualisation toolset for your production data. With LocalStack’s core cloud emulator, parity is ensured between a local Neptune instance and AWS’s own, meaning Gremlin queries in your development environment will behave identically on Amazon Neptune. In this video we demonstrate how to use G.V() with LocalStack Neptune.