docker-nvidia-glx-desktop

MATE Desktop container designed for Kubernetes supporting OpenGL GLX and Vulkan for NVIDIA GPUs with WebRTC and HTML5, providing an open source remote cloud graphics or game streaming platform. Spawns its own fully isolated X Server instead of using the host X server, therefore not requiring /tmp/.X11-unix host sockets or host configuration.

Use docker-nvidia-egl-desktop for a MATE Desktop container which directly accesses NVIDIA GPUs without using an X11 Server and supports automatically falling back to software acceleration in the absence of GPUs (but without Vulkan support unlike this container).

Usage

Container startup could take some time at first launch as it automatically installs NVIDIA drivers compatible with the host.

Wine, Winetricks, and PlayOnLinux are bundled by default. Comment out the section where it is installed within Dockerfile if the user wants to remove them from the container.

There are two web interfaces that can be chosen in this container, the first being the default selkies-gstreamer WebRTC HTML5 interface, and the second being the fallback noVNC WebSocket HTML5 interface. The noVNC interface can be enabled by setting NOVNC_ENABLE to true. While the noVNC interface does not support audio forwarding, it can be useful for troubleshooting the selkies-gstreamer WebRTC interface or using this container with low bandwidth environments. When using the noVNC interface, all environment variables related to the selkies-gstreamer WebRTC interface are ignored, with the exception of BASIC_AUTH_PASSWORD. As with the selkies-gstreamer WebRTC interface, the noVNC interface password will be set to BASIC_AUTH_PASSWORD, and use PASSWD by default if not set. The noVNC interface also additionally accepts the NOVNC_VIEWPASS environment variable, where a view only password with only the ability to observe the desktop passively can also be provisioned.

The container requires host NVIDIA GPU driver versions of at least 450.80.02, with the corresponding container toolkit runtime to be also configured on the host for allocating GPUs. All Maxwell or later generation GPUs in the consumer, professional, or datacenter lineups will not have significant issues running this container, although the selkies-gstreamer high performance NVENC backend may not be available (see the next paragraph). Kepler GPUs are untested and likely does not support the NVENC backend, but can be mostly functional using the software acceleration fallback.

The high performance NVENC backend for the selkies-gstreamer WebRTC interface is only supported in GPUs listed as supporting H.264 (AVCHD) under the NVENC - Encoding section of NVIDIA's Video Encode and Decode GPU Support Matrix. If your GPU is not listed as supporting H.264 (AVCHD), add the environment variable WEBRTC_ENCODER with the value x264enc in your container configuration for falling back to software acceleration, which also has a very good performance depending on your CPU.

The username is user in both the container user account and the web authentication prompt. The environment variable PASSWD is the password of the container user account, and BASIC_AUTH_PASSWORD is the password for the HTML5 interface authentication prompt. If ENABLE_BASIC_AUTH is set to true for selkies-gstreamer (not required for noVNC) but BASIC_AUTH_PASSWORD is unspecified, the HTML5 interface password will default to PASSWD.

NOTES: Only one web browser can be connected at a time with the selkies-gstreamer WebRTC interface. If the signaling connection works, but the WebRTC connection fails, read the Using a TURN Server section.

Running with Docker

1. Run the container with Docker (or other similar container CLIs like Podman):

docker run --gpus 1 -it -e TZ=UTC -e SIZEW=1920 -e SIZEH=1080 -e REFRESH=60 -e DPI=96 -e CDEPTH=24 -e VIDEO_PORT=DFP -e PASSWD=mypasswd -e WEBRTC_ENCODER=nvh264enc -e BASIC_AUTH_PASSWORD=mypasswd -p 8080:8080 ghcr.io/ehfd/nvidia-glx-desktop:latest

NOTES: The container tags available are latest and 20.04 for Ubuntu 20.04 and 18.04 for Ubuntu 18.04. Replace all instances of mypasswd with your desired password. BASIC_AUTH_PASSWORD will default to PASSWD if unspecified. The container must not be run in privileged mode. Use the option --tmpfs /dev/shm:rw for a slight performance improvement.

Change WEBRTC_ENCODER to x264enc when using the selkies-gstreamer interface if your GPU doesn't support H.264 (AVCHD) under the NVENC - Encoding section in NVIDIA's Video Encode and Decode GPU Support Matrix.

2. Connect to the web server with a browser on port 8080. You may also separately configure a reverse proxy to this port for external connectivity.

NOTES: Additional configurations and environment variables for the selkies-gstreamer WebRTC HTML5 interface are listed in lines that start with parser.add_argument within the selkies-gstreamer main script.

Running with Kubernetes

1. Create the Kubernetes Secret with your authentication password:

kubectl create secret generic my-pass --from-literal=my-pass=YOUR_PASSWORD

NOTES: Replace YOUR_PASSWORD with your desired password, and change the name my-pass to your preferred name of the Kubernetes secret with the xgl.yml file changed accordingly as well. It is possible to skip the first step and directly provide the password with value: in xgl.yml, but this exposes the password in plain text.

2. Create the pod after editing the xgl.yml file to your needs:

kubectl create -f xgl.yml

NOTES: The container tags available are latest and 20.04 for Ubuntu 20.04 and 18.04 for Ubuntu 18.04. BASIC_AUTH_PASSWORD will default to PASSWD if unspecified.

Change WEBRTC_ENCODER to x264enc when using the selkies-gstreamer WebRTC interface if your GPU doesn't support H.264 (AVCHD) under the NVENC - Encoding section in NVIDIA's Video Encode and Decode GPU Support Matrix.

3. Connect to the web server spawned at port 8080. You may configure the ingress endpoint or reverse proxy that your Kubernetes cluster provides to this port for external connectivity.

NOTES: Additional configurations and environment variables for the selkies-gstreamer WebRTC HTML5 interface are listed in lines that start with parser.add_argument within the selkies-gstreamer main script.

Using a TURN Server

Note that this section is only required for the selkies-gstreamer WebRTC HTML5 interface. For an easy fix to when the signaling connection works, but the WebRTC connection fails, add the option --network=host to your Docker command, or uncomment hostNetwork: true in your xgl.yml file when using Kubernetes (note that your cluster may have not allowed this, resulting in an error). This exposes your container to the host network, which disables network isolation. If this does not fix the connection issue (normally when the host is behind another firewall) or you do not want to use this fix for security or technical reasons, read the below text.

In most cases when either of your server or client has a permissive firewall, the default Google STUN server configuration will work without additional configuration. However, when connecting from networks that cannot be traversed with STUN, a TURN server is required. Provide the TURN server address, port, and shared secret in order to take advantage of the TURN relay capabilities and improve connection success.

An open source TURN server that can be used is coTURN, and an example container implementation ghcr.io/selkies-project/selkies-gstreamer/coturn:latest is available. For dynamic IP addresses, dynamic-coturn is a container implementation which restarts the TURN server whenever the public IP address gets changed. Pion TURN is another TURN server implementation compatible with all major operating systems, and restund is a TURN server implementation for OpenWRT.

The Numb STUN/TURN Server is a free TURN server instance that may be used for personal purposes upon registration, but may not be optimal for production usage.

With Docker, use the -e option to add the TURN_HOST, TURN_PORT environment variables. You also require to provide either just TURN_SHARED_SECRET for time-limited shared secret TURN authentication, or both TURN_USERNAME and TURN_PASSWORD for legacy long term TURN authentication, depending on your TURN server configuration. Provide just one of these authentication methods, not both.

Configuring With Kubernetes

Your TURN server will use only one out of two ways to authenticate the client, so only provide one type of authentication method. The time-limited shared secret TURN authentication requires to only provide the Base64 encoded TURN_SHARED_SECRET. The legacy long term TURN authentication requires to provide both TURN_USERNAME and TURN_PASSWORD credentials.

Time-Limited Shared Secret Authentication

1. Create a secret containing the TURN shared secret:

kubectl create secret generic turn-shared-secret --from-literal=turn-shared-secret=MY_TURN_SHARED_SECRET

NOTES: Replace MY_TURN_SHARED_SECRET with the shared secret of the TURN server, then changing the name turn-shared-secret to your preferred name of the Kubernetes secret, with the xgl.yml file also being changed accordingly.

2. Uncomment the lines in the xgl.yml file related to TURN server usage, updating the TURN_HOST and TURN_PORT environment variable as needed:

- name: TURN_HOST
  value: "turn.example.com"
- name: TURN_PORT
  value: "3478"
- name: TURN_SHARED_SECRET
  valueFrom:
    secretKeyRef:
      name: turn-shared-secret
      key: turn-shared-secret

NOTES: It is possible to skip the first step and directly provide the shared secret with value:, but this exposes the shared secret in plain text.

Legacy Long Term Authentication

1. Create a secret containing the TURN password:

kubectl create secret generic turn-password --from-literal=turn-password=MY_TURN_PASSWORD

NOTES: Replace MY_TURN_PASSWORD with the password of the TURN server, then changing the name turn-password to your preferred name of the Kubernetes secret, with the xgl.yml file also being changed accordingly.

2. Uncomment the lines in the xgl.yml file related to TURN server usage, updating the TURN_HOST, TURN_PORT, and TURN_USERNAME environment variable as needed:

- name: TURN_HOST
  value: "turn.example.com"
- name: TURN_PORT
  value: "3478"
- name: TURN_USERNAME
  value: "username"
- name: TURN_PASSWORD
  valueFrom:
    secretKeyRef:
      name: turn-password
      key: turn-password

NOTES: It is possible to skip the first step and directly provide the TURN password with value:, but this exposes the TURN password in plain text.

Troubleshooting

The container simulates the GPU being virtually plugged into a physical DVI-D/HDMI/DisplayPort digital video interface in consumer and professional GPUs. The container uses virtualized DVI-D ports for this purpose in Datacenter (Tesla) GPUs. The ports to be used should be connected with an actual monitor only when the user wants the remote desktop screen to be shown on that monitor. If you want to show the remote desktop screen spawned by the container in a physical monitor, connect the monitor and set VIDEO_PORT to the the video interface identifier that is connected to the monitor. Manually specify a video interface identifier that is not connected to a monitor in VIDEO_PORT if you have a physical monitor connected and want to do the opposite. VIDEO_PORT identifiers and their connection states can be obtained by typing xrandr -q when the DISPLAY environment variable is set to the number of the spawned X server display (for example :0).

NOTES: Do not start two or more X servers for a single GPU. Use a separate GPU (or use Xvfb/Xdummy/XVnc without hardware acceleration to use no GPUs) if you need a host X server unaffiliated with containers, and do not make the GPU available to the container runtime.

Since this container simulates the GPU being virtually plugged into a physical monitor while it actually does not, make sure the resolutions specified with the environment variables SIZEW and SIZEH are within the maximum size supported by the GPU. The environment variable VIDEO_PORT can override which video port is used (defaults to DFP, the first interface detected in the driver). Therefore, specifying VIDEO_PORT to an unplugged DisplayPort (for example numbered like DP-0, DP-1, and so on) is recommended for resolutions above 1920 x 1200 at 60 hz, because some driver restrictions are applied when the default is set to an unplugged physical DVI-D or HDMI port. The maximum size that should work in all cases is 1920 x 1200 at 60 hz, mainly for when the default VIDEO_PORT identifier DFP is not set to DisplayPort. The screen sizes over 1920 x 1200 at 60 hz but under the maximum supported display size specified for each port (supported by GPU specifications) will be possible if the port is set to DisplayPort (both physically connected or disconnected), or when a physical monitor or dummy plug to any other type of display ports (including DVI-D and HDMI) has been physically connected. If all GPUs in the cluster have at least one DisplayPort and they are not physically connected to any monitors, simply setting VIDEO_PORT to DP-0 is recommended (but this is not set as default because of legacy GPU compatibility reasons).

Datacenter (Tesla) GPUs seem to only support resolutions of up to around 2560 x 1600 at 60 hz (VIDEO_PORT must be kept to DFP instead of changing to DP-0 or other DisplayPort identifiers). The K40 (Kepler) GPU did not support RandR (required for some graphical applications using SDL and other graphical frameworks). Other Kepler generation Datacenter GPUs (maybe except the GRID K1 and K2 GPUs with vGPU capabilities) are also unlikely to support RandR, thus Datacenter GPU RandR support probably starts from Maxwell. Other tested Datacenter GPUs (V100, T4, A40, A100) support all graphical applications that consumer GPUs support. However, the performances were not better than consumer GPUs that usually cost a fraction of Datacenter GPUs, and the maximum supported resolutions were even lower.

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Please post issues relevant to the selkies-gstreamer WebRTC HTML5 interface to the selkies-gstreamer repository.

This project involved a collaboration effort with Dan Isla of the Selkies Project, incorporating the selkies-gstreamer WebRTC remote desktop streaming application.

This work was supported in part by NSF awards CNS-1730158, ACI-1540112, ACI-1541349, OAC-1826967, the University of California Office of the President, and the University of California San Diego’s California Institute for Telecommunications and Information Technology/Qualcomm Institute. Thanks to CENIC for the 100Gbps networks.