What package should I use?

shopping

Mafalda SFU modular design allows you to use the packages that better fit for your use case, and easily upgrade to other ones when you need it. To help you to decide were to start, we’ve defined here some use cases:

I’m writting a new server

If you are writting a new server from scratch, the best option is to start with Mafalda package. This one will allow you not only to abstract from creating and managing yourself the usage of multiple Mediasoup Workers, but also to load balance the creation of Mediasoup Routers on them, or pipe and join the Router instances between them to by-pass Mediasoup per-Worker limits.

Mafalda
Mediasoup

I’m using only non-interconnected Router instances that I need them to scale

If you already have an app server using Mediasoup Routers and until now you didn’t need to interconnect them to by-pass Mediasoup per-Worker limits, it would pay-off the efforts of migrate your Mediasoup code to use Mafalda instead. Mafalda API and design is based on Mediasoup one, so migration should be easy to do, and you would enjoy all the advantages of scalability and abstracted management that Mafalda provides, without almost needing to change your application logic nor worrying about managing them yourself.

In addition to that, by using Mafalda will prepare your code to later upgrade to use Mafalda-horizontal and scale your app to multiple servers too.

I have mixed app logic and media, that want to split to improve architecture

If your app server code directly access Mediasoup API, and need to move it out to another machine to improve your systems architecture, or to use a server with more resources to increase media performance, the easiest solution is to use Remote Mediasoup package. After creating and configuring a Remote Mediasoup client, it will expose an object with the same API that Mediasoup provides, so your you’ll be able to control a Mediasoup instance running in another server without needing to modify the logic of your app code at all.

Mediasoup server
Mediasoup
Remote Mediasoup server
Remote Mediasoup client

Alternatively, you can also use Mediasoup-horizontal, that will already prepare your application to scale to multiple servers without changes, or use the same Remote Mediasoup client instance to connect instead to a Mediasoup-cluster CLI server.

I’m using Mafalda, and want to move out media server to improve performance

If you are already using Mafalda in a monolithic server, you can split your code by moving out the media logic to another server as you would do with any other Mediasoup based server by using Remote Mediasoup and improvevyour performance by having a dedicated media server, or make use of Remote Mafalda package for additional beneficts, like manage abstract remote Mafalda Router instances. Similar to Remote Mediasoup, you’ll be able to control a Mafalda instance running in another server, and prepare your code to upgrade later to use Mafalda-horizontal and allow each one of your sessions to grow and span over multiple CPUs and servers.

App server
Remote Mediasoup client
Mafalda
Remote Mediasoup server
App server
Mafalda media server
Remote Mafalda client
Remote Mediasoup client
Remote Mafalda server
Remote Mediasoup server

My app uses Mediasoup, and I need to scale it to a large number of servers

If you need your Mediasoup-based app to being able to manage multiple media servers, your solutions are to use Mediasoup-horizontal if you want your app process to control them directly, or use Mediasoup-cluster CLI if you want to move the management of the multiple media servers from your actual app server. Both of them will allows you to control multiple Mediasoup instances as a single one (only difference is where’s the management is efectively being done), and to have both remote Workers and Routers all over them in a transparent way, as if running a single machine with lots of CPU cores.

App server
Mediasoup Horizontal
Remote Mediasoup client 1
Remote Mediasoup client 2
Remote Mediasoup server 1
Remote Mediasoup server 2
Mediasoup cluster
Mediasoup-horizontal
Remote Mediasoup server
Remote Mediasoup client 1
Remote Mediasoup client 2
Remote Mediasoup client

I need to host huge sessions that will span several CPUs in multiple servers

If your sessions can be potentially big and exceed the capability that can offer a single server, Mafalda-horizontal will help here. It will automatically create, manage and interconnect the Router instances on the different servers while providing the same API of Mafalda, so you’ll only need to worry about using it in your app code as if you only would need a single Router local instance.

App server
Mafalda media server 2
Mafalda media server 1
Mafalda Horizontal
Remote Mafalda client 1
Remote Mafalda client 2
Remote Mediasoup client 1
Remote Mediasoup client 2
Remote Mafalda server 2
Remote Mediasoup server 2
Remote Mafalda server 1
Remote Mediasoup server 1

Currently in development

I host humongous big sessions, and need to access them from multiple places

If your sessions can be really big or can’t be predicted when that usage spikes could happen or can be a lot of difference in sessions load from ones to other, if the number of servers you need to manage is huge or you can’t easily control when or how to add them, if you need that stream distribution auto regulates itself finding the shortest path, or if you need to access the servers network from multiple entry points (for example, from multiple regions), then now we’re talking.

Mafalda-swarm will provide a federated and decentralized P2P architecture build on top of the Mafalda network, self-managing its resources and allowing access to it from any of their nodes by providing a search mechanism of the streams.

Estimated August 2023

I need to monitor the stats, loads and connections of all my Mafalda servers

Not directly related to solve scalability problem, but scalability-derived ones, Mafalda-monitor allows to control and monitor from a single place the activity of all your Remote Mafalda servers and their network clients. With it, you can have a real-time graphical view of the number of their Workers and Routers, their CPU loads, their Transports, how are they inter-connected…

Estimated December 2023