There may be cases when you need to do CPU-intensive tasks on the backend like big JSON parsing, video encoding, compression, etc. If you have at least 2 cores in your processor's configuration you can run javascript in parallel for these tasks and not block the main thread

Introduction: This blog post is the final installment of a three-part series dedicated to scaling a NestJS chat app to handle millions of users. In the first two episodes, we discussed the scaling process and demonstrated how to deploy it locally using Docker and Minikube. However, in this final episode,

In our previous blog post, we explored how to write a scalable NestJS chat app using a distributed architecture and WebSockets for real-time communication. Building upon that, we will now dive deeper into improving the app's efficiency and deploying it on Kubernetes using minikube. If you're

Hello, in this guide, I will teach you how to scale a NestJS app to millions of users. Prerequisites: * Experience with JavaScript. * Experience with NestJS. * Experience as a backend engineer. Access the GitHub repository for this project here. To scale your app, you will need to scale horizontally by creating