Bull & NestJS = Achieving Scale in Node.js
When it comes to building scalable applications in Node.js, developers often face challenges in handling a large number of concurrent tasks or jobs. This is where Bull and NestJS come in, offering a powerful combination to achieve scale and efficiency in Node.js applications.
Understanding Bull
Bull is a popular, feature-rich, and fast job queue for Node.js, built on top of Redis. It allows developers to easily create and manage queues for processing jobs in a distributed and efficient manner. With Bull, you can handle a high volume of jobs without impacting the performance of your application, making it an ideal choice for building scalable Node.js applications.
Introducing NestJS
NestJS is a progressive Node.js framework that provides a solid architectural design and development experience for building efficient and scalable server-side applications. It is heavily inspired by Angular and is built with TypeScript, making it easy to write maintainable and scalable code. NestJS’s modular and extensible architecture allows developers to seamlessly integrate Bull for handling asynchronous tasks and achieving scale in their applications.
The Power of Bull & NestJS
By combining Bull with NestJS, developers can leverage the power of job queues and the robust architecture of NestJS to achieve scale in their Node.js applications. Bull seamlessly integrates with NestJS, allowing you to easily define and process queues within your NestJS application. Whether you need to process time-consuming tasks, handle high volumes of concurrent requests, or achieve fault tolerance and load balancing, Bull and NestJS provide a comprehensive solution for building scalable and efficient applications.
Conclusion
Bull and NestJS offer a powerful combination for achieving scale in Node.js applications. Whether you are building a real-time chat application, a background job processing system, or a complex microservices architecture, Bull and NestJS provide the tools and capabilities to handle large volumes of tasks efficiently and reliably. By leveraging the features and functionalities of these two tools, developers can build robust and scalable Node.js applications that can handle the demands of modern, high-performance environments.
you are using bull and the video title says bullmq. This is not good.
This is not BullMQ
Can we use kafka or rabbitmq instead of bullmq? Is that the right way
Very nice content, but I would like to ask you. How to return data from the queue to one front end via websocket?
Great content again.
Quick question though, with your first example "transcode an audio file", why choose to go for a job with BullMQ (the queueing system with Redis) instead of an event with EventEmitter (appart from showcasing it of course)?
Both would achieve the same result right ? Not blocking the thread and decoupling the producer/emitter from the consumer/listener ?
My question is thus : are those 2 patterns just different ways to implement a distributed system ? Why go for one or the other then ? What are the main differences ?
I don't like the nest.js. over engineered and complicated.
Thank you for making this.
Just one thing to mention, nestjs/bull !== nestjs/bullmq!
bullmq should be used instead of bull
For a newbie in Nest I didnt get quite a number but somehow this ia looking so cool and helpful.|
Cant wait to flow in Nest and deployments with K8s like you did on this project.
Thanks mate 🙂
Brilliant teaching quality and the amount of knowledge you have on the topics you teach is phenomenal.
Hi Michael, could you explain what difference between bull and rabiitmq? I’m an newer for backend, Thanks!
Great guide. Like and subscribed.
…need to set TTL on those bull:transcode..
waiting for full course from fundamental to advance
Amazing tutorial, new skill added to NestJS. I've done same but using PM2 instead of Kubernetes/Docker, for sake of simplicity.
So instead of using Docker and K8s orchestration what if we're using a LB with multiple ec2 instances (like in AWS) would the entire setup still pick only 1 of the consumer to process the message and not multiple consumers (from other servers) fighting to process that message?
I mean is this the nature of distributed queuing system that allows this to happen or something else?
Great tutorial. Thank you…But how do you set up the kubernetes cluster you're using ? Can you help me with that ?
Can you amazon clone or any big projects using node microservice architecture and mongodb as a db.
great content keep rocking🚀