NestJS Microservices: Build a Distributed Job Engine (Udemy.com)

Master the art of building scalable, distributed microservices with NestJS by developing a fully functional job engine from the ground up. This course is designed to teach you NestJS microservices the right way, covering everything from architecture and design to deployment and scaling in production.

You’ll start by setting up a monorepo with Nx, allowing you to manage multiple services within a single codebase efficiently. Using gRPC as the transport layer, you'll enable high-performance, low-latency communication between services. The course dives into Apache Pulsar, a powerful distributed messaging system, that allows us to add multiple consumers to a shared queue & achieve scale. You'll also expose a GraphQL API, providing a flexible and efficient way to interact with your microservices.

Security is a core focus, and you'll implement JWT-based authentication with secure, HTTP-only cookies. Throughout the course, everything is built using object-oriented design principles, ensuring a clean, modular, and reusable codebase that follows DRY (Don’t Repeat Yourself) principles. This makes your codebase more maintainable as it scales.

You'll also optimize your Docker setup, using Nx libraries with separate package.json files for better dependency management. Horizontal scaling techniques will ensure your services can handle increasing workloads efficiently. As your job engine matures, you'll implement job state tracking, allowing you to monitor job progress.

For database management, you’ll use Prisma ORM and Drizzle ORM with PostgreSQL, ensuring type safety, migrations, and optimized queries. Finally, you’ll deploy everything to Kubernetes, taking your microservices to production with AWS, a custom domain, and SSL encryption.

By the end of this course, you'll have a fully operational distributed job engine with robust state tracking and the expertise to design, develop, and deploy scalable NestJS microservices in real-world production environments.