This repository is no longer maintained. See Jellyfish Videoroom instead.

Because of a lot of projects repeating Membrane Videoroom's logic, we extracted it into general purpose media server called Jellyfish. Therefore, we no longer maintain this repository and instead we focus on Jellyfish Videoroom which is a clone of Membrane Videoroom but relies on Jellyfish. Jellyfish, of course, still uses awesome Membrane RTC Engine under the hood! If you want to see a little less advanced but still maintained videoconferencing system directly based on Membrane RTC Engine see here.

Membrane Videoroom

Membrane Videoroom is an open-source, basic video conferencing platform using WebRTC. Based on membrane_rtc_engine, it may be a good starting point for building your own real-time communication solution using Elixir and Membrane.

Try it live!

You can test the Videoroom at https://videoroom.membrane.stream

Using the application

The recommended browser for using the application is Google Chrome. To join a room, enter the room name and your name, then click the Join room! button below. If the browser will ask you for a camera or microphone permission, click Allow (otherwise, other people will not be able to see or hear you). After entering a room, you can turn on/off your camera or microphone, or start sharing your screen, by clicking icons at the bottom of the screen. You can also leave the room by clicking the red button or just closing the card in your browser.

Running locally

Installation of the dependencies

To run the Phoenix application manually, you will need to have additional dependencies installed listed in .tool-versions file:

• node.js
• elixir
• erlang

The application has been tested with versions mentioned in .tool-versions file. You can use asdf tool to download and manage required dependencies.

Furthermore, you will need some other dependencies. Depending on an operating system, you might also need to set up some environment variables. Below you can find a list of commands to be executed on a given OS.

macOS with Intel processor

brew install srtp clang-format ffmpeg pkg-config
export LDFLAGS="-L/usr/local/opt/openssl@1.1/lib"
export CFLAGS="-I/usr/local/opt/openssl@1.1/include/"
export CPPFLAGS="-I/usr/local/opt/openssl@1.1/include/"
export PKG_CONFIG_PATH="/usr/local/opt/openssl@1.1/lib/pkgconfig"

macOS with M1 processor

brew install srtp clang-format ffmpeg
export C_INCLUDE_PATH=/opt/homebrew/Cellar/libnice/0.1.18/include:/opt/homebrew/Cellar/opus/1.3.1/include:/opt/homebrew/Cellar/openssl@1.1/1.1.1l_1/include
export LIBRARY_PATH=/opt/homebrew/Cellar/opus/1.3.1/lib
export PKG_CONFIG_PATH=/opt/homebrew/Cellar/openssl@1.1/1.1.1l_1/lib/pkgconfig/

Ubuntu

sudo apt-get install libsrtp2-dev libavcodec-dev libavformat-dev libavutil-dev

Launching of the application

First, install all project dependencies:

mix deps.get
npm ci --prefix=assets

To run, type:

EXTERNAL_IP=<IPv4> mix phx.server

EXTERNAL_IP should be set to the local IP address of the computer this is running on. It is required unless you only connect via localhost.

Then go to http://localhost:4000/.

Running with docker

Videoroom provides a Dockerfile that you can use to run videoroom application yourself without any additional setup and system dependencies installation. All you need is to have Docker Engine installed. You can get it, for example, along with Docker Desktop installation - here you can find the instructions on how to install Docker Desktop on macOS and Ubuntu.

Launching of the application

First, you need to build the image from the source:

docker build -t membrane_videoroom .

Later, you need to obtain the EXTERNAL_IP address. This is the IPv4 address at which your computer is accessible in the network. To make the server available from your local network, you can set it to a private address, like 192.168.*.*. The address can be found with the use of the ifconfig command:

$ ifconfig
...
en0: flags=8863<UP,BROADCAST,SMART,RUNNING,SIMPLEX,MULTICAST> mtu 1500
 options=400<CHANNEL_IO>
 ether 88:66:5a:49:ac:e0
 inet6 fe80::426:8833:1408:cd1a%en0 prefixlen 64 secured scopeid 0x6
 inet 192.168.1.196 netmask 0xffffff00 broadcast 192.168.1.255
 nd6 options=201<PERFORMNUD,DAD>
 media: autoselect
 status: active

(The address we are seeking is the address following the inet field - in that particular case, 192.168.1.196)

Then you can start the container.

Explicit port exposure (macOS compatible)

docker run -p 50000-50050:50000-50050/udp -p 4000:4000/tcp -e INTEGRATED_TURN_PORT_RANGE=50000-50050 -e EXTERNAL_IP=<IPv4 address> -e VIRTUAL_HOST=localhost membrane_videoroom

Using host network (Linux only)

docker run --network=host -e EXTERNAL_IP=<IPv4 address> -e VIRTUAL_HOST=localhost membrane_videoroom

NOTE On macOS you need to explicitly publish ports since the --network=host option doesn't work there. Make sure that the ports you are publishing with the option -p of the docker run command are corresponding to the ports specified within the INTEGRATED_TURN_PORT_RANGE variable. Please also keep in mind that the port range cannot be too wide as it might cause problems with the docker container starting.

Finally, go to http://localhost:4000/.

More advanced configuration

Environment variables

Below you can find a list of runtime environment variables, used to configure the application:

• VIRTUAL_HOST - host passed to the endpoint config, defaults to localhost on non-production environments (where MIX_ENV != prod)

• USE_TLS - true or false, if set to true then https will be used and certificate paths will be required

• KEY_FILE_PATH - path to certificate key file, used when USE_TLS is set to true

• CERT_FILE_PATH - path to certificate file, used when USE_TLS is set to true

• EXTERNAL_IP - the IP address, on which TURN servers will listen. By default set to 127.0.0.1, so if you don't explicitly set it, the videoroom won't be accessible from outside of localhost.

• INTEGRATED_TURN_PORT_RANGE - port range, where UDP TURN will try to open ports. By default set to 50000-59999. The bigger the range is, the more users server will be able to handle. Useful when not using the --network=host option to limit the UDP ports used only to ones published from a Docker container.

• INTEGRATED_TCP_TURN_PORT - port number of TCP TURN

• INTEGRATED_TLS_TURN_PORT - port number of TLS TURN, used when INTEGRATED_TURN_PKEY and INTEGRATED_TURN_CERT are provided

• INTEGRATED_TURN_CERT - SSL certificate for TLS TURN

• INTEGRATED_TURN_PKEY - SSL private key for TLS TURN

• STORE_METRICS - true or false, if set to true, then Membrane.RTC.Engine metrics will be stored in the database. By default set to false

• METRICS_SCRAPE_INTERVAL - number of seconds between Membrane.RTC.Engine metrics reports scrapes

• DATABASE - the name of the database used to store Membrane.RTC.Engine metrics reports

• DB_USERNAME - the name of the database user

• DB_PASSWORD - password for the database user

• DB_HOSTNAME - hostname of the database server

• DB_PORT - port of the database server

.env file

Default environment variables are available in .env file. If you are using the Docker setup, you might want to make the container use the variables defined in .env - you can do so by providing the --env-file .env flag to docker run command. With the variables defined in the .env file, you won't need to use -e switch of the docker run command:

docker run <rest of the options...> -env-file .env membrane_videoroom

You can surely add other environment variables definitions to the .env file

IMPORTANT If you intend to use TLS with the docker setup, remember that setting paths in the .env file is not enough. Those paths will be used inside the docker container therefore besides setting env variables you will need to mount those paths to the docker container on your own. You can do it by adding -v flag with proper paths to docker command, which will mount the desired volumes in the container's file system:

docker run <rest of the options...> -e INTEGRATED_TURN_CERT=/usr/local/key.cert -e INTEGRATED_TURN_PKEY=/usr/local/key.priv -v <path to the certificate on the host filesystem>:/usr/local/key.cert -v <path to the private key on the host filesystem>:/usr/local/key.priv membrane_videoroom

OpenTelemetry

The videoroom provides observability metrics. By default, OpenTelemetry is turned off. You can turn it on by going to config/runtime.exs and changing otel_state to one of three possible values:

• :local - OpenTelemetry traces will be printed on stdout
• :zipkin - OpenTelemetry traces are sent to Zipkin. You can change the url traces that are sent to in config/runtime.exs. To set up zipkin you can run this command docker run -d -p 9411:9411 openzipkin/zipkin.
• :honeycomb - OpenTelemetry traces are sent to Honeycomb. You have to specify "x-honeycomb-team", which is API KEY for this service.

FAQ

Below you can find a list of Frequently Asked Questions (FAQ). In case of any errors occurring during the setup, we encourage you to get familiar with that list. If you haven't found an answer to your question, we invite you to ask it on the Membrane's Discord server.

Videoroom capabilities

What is the maximum number of users in a Membrane videoroom conference?

That is limited mostly by the hardware you are using, and the usage scenario. Let's consider a server with 64 GiB RAM, access to a 10 Gbit network, and 32 vCPUs. Below you can find a table comparing a cost of such a server from three different cloud providers.

name	RAM	CPU	Storage	Network	Cost, on-demand
Amazon EC c5ad.8xlarge	64.0 GiB	32 vCPUs	1200 GB (2 * 600 GB NVMe SSD)	10 Gbps	$1.376 hourly
Microsoft Azure Standard_D32plds_v5	64.0 GiB	32 vCPUs	1200 GiB	---------	$1.552 hourly
Google Cloud VM c2d-highcpu-32	64.0 GiB	32 vCPUs	----------	32 Gbps	$1.321 hourly

With such hardware:

• when it comes to hosting a conference where we have e.g. two presenters that are sending audio and video and multiple passive participants, who are only watching the stream, we can handle at least ~10 rooms, 17 participants each (2 speakers, 15 passive participants).
• in the case of a casual room where everyone can send their media, with low-quality video, one big room for 21 participants (each of them was sending audio and video) was using about 21% of the CPU resources of the given machine.

Does Membrane videoroom support broadcasting (only one peer streaming and many peers who are only watching)?

Membrane videoroom is an application meant to mimic the behaviour of a videoconferencing room (e.g. Google Meet or Jitsi Meet). It has mechanisms to reduce resource consumption when only part of the video conference participants are actively participating (streaming the multimedia), and the rest are only watching the stream. At the same time, for broadcasting multimedia to thousands of viewers, other mechanisms need to be used, and it can be achieved with the use of the Membrane Framework. We invite you to take a look at other Membrane demos, especially:

• WebRTC to HLS demo
• RTMP to HLS demo which are demo applications meant to broadcast the media sent by the streamer to many viewers.

Configuration

Can you use the external TURN server instead of the integrated one?

It's not possible at the moment. Since the SFU needs to be publicly available, we don't see a purpose in having a separate publicly available TURN server. The architecture proposed by us: client --- NETWORK ---> SFU with TURN reduces the number of 'hops' in the network by one. In contrast, the architecture with the separate TURN server would like that: client --- NETWORK -- TURN --- NETWORK ---> SFU. If you can think of a use case for a separate TURN server, feel free to start a discussion on our discord server.

Known issues

(Mix) Could not compile dependency :fast_tls,

As the error suggests, there was a problem with the :fast_tls dependency compilation. It's usually caused by the fact, that the compiler cannot find OpenSSL dependencies in your system. In the setup instruction above we have set the compiler flags pointing to the appropriate directories containing OpenSSL dependencies on a given OS. However, if you have your OpenSSL installed in some custom location, you will need to change the compiler flags (i.e. [LDFLAGS, CFLAGS, CPPFLAGS] or [C_INCLUDE_PATH, LIBRARY_PATH], depending on your compiler and OS) and the PKG_CONFIG_PATH environment variable. For more instructions on how to install the :fast_tls dependency, please visit the Fast TLS repository.

Why, after joining the room, I don't see a video stream from the others?

That might be due to the misconfiguration of the EXTERNAL_IP environment variable. Make sure, that the variable is set in the environment where you are running the server, as well as that it is the IPv4 address pointing to the server, visible to all the peers. Please also keep in mind that you need to publish docker UDP ports used for sending and receiving media (the ones set with INTEGRATED_TURN_PORT_RANGE environment variable) and the TCP port set with INTEGRATED_TCP_TURN_PORT environment variable. Alternatively, you can use the host network if you are running on Linux.

Copyright and License

Copyright 2020, Software Mansion

Licensed under the Apache License, Version 2.0