docker-documentation/images/docker-jellyfin.md

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linuxserver/jellyfin

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Jellyfin is a Free Software Media System that puts you in control of managing and streaming your media. It is an alternative to the proprietary Emby and Plex, to provide media from a dedicated server to end-user devices via multiple apps. Jellyfin is descended from Emby's 3.5.2 release and ported to the .NET Core framework to enable full cross-platform support. There are no strings attached, no premium licenses or features, and no hidden agendas: just a team who want to build something better and work together to achieve it.

Supported Architectures

Our images support multiple architectures such as x86-64, arm64 and armhf. We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.

Simply pulling linuxserver/jellyfin should retrieve the correct image for your arch, but you can also pull specific arch images via tags.

The architectures supported by this image are:

Architecture Tag
x86-64 amd64-latest
arm64 arm64v8-latest
armhf arm32v7-latest

Usage

Here are some example snippets to help you get started creating a container from this image.

docker

docker create \
  --name=jellyfin \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=Europe/London \
  -e UMASK_SET=<022> `#optional` \
  -p 8096:8096 \
  -p 8920:8920 `#optional` \
  -v </path/to/library>:/config \
  -v <path/to/tvseries>:/data/tvshows \
  -v </path/to/movies>:/data/movies \
  -v </path for transcoding>:/transcode `#optional` \
  --device /dev/dri:/dev/dri `#optional` \
  --restart unless-stopped \
  linuxserver/jellyfin

docker-compose

Compatible with docker-compose v2 schemas.

---
version: "2"
services:
  jellyfin:
    image: linuxserver/jellyfin
    container_name: jellyfin
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=Europe/London
      - UMASK_SET=<022> #optional
    volumes:
      - </path/to/library>:/config
      - <path/to/tvseries>:/data/tvshows
      - </path/to/movies>:/data/movies
    volumes:
      - </path for transcoding>:/transcode #optional
    ports:
      - 8096:8096
    ports:
      - 8920:8920 #optional
    devices:
      - /dev/dri:/dev/dri #optional
    restart: unless-stopped

Parameters

Docker images are configured using parameters passed at runtime (such as those above). These parameters are separated by a colon and indicate <external>:<internal> respectively. For example, -p 8080:80 would expose port 80 from inside the container to be accessible from the host's IP on port 8080 outside the container.

Ports (-p)

Parameter Function
8096 Http webUI.
8920 Https webUI (you need to setup your own certificate).

Environment Variables (-e)

Env Function
PUID=1000 for UserID - see below for explanation
PGID=1000 for GroupID - see below for explanation
TZ=Europe/London Specify a timezone to use EG Europe/London
UMASK_SET=<022> for umask setting of Emby, default if left unset is 022.

Volume Mappings (-v)

Volume Function
/config Jellyfin data storage location. This can grow very large, 50gb+ is likely for a large collection.
/data/tvshows Media goes here. Add as many as needed e.g. /data/movies, /data/tv, etc.
/data/movies Media goes here. Add as many as needed e.g. /data/movies, /data/tv, etc.
/transcode Path for transcoding folder, optional.

Device Mappings (--device)

Parameter Function
/dev/dri Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi).

User / Group Identifiers

When using volumes (-v flags), permissions issues can arise between the host OS and the container, we avoid this issue by allowing you to specify the user PUID and group PGID.

Ensure any volume directories on the host are owned by the same user you specify and any permissions issues will vanish like magic.

In this instance PUID=1000 and PGID=1000, to find yours use id user as below:

  $ id username
    uid=1000(dockeruser) gid=1000(dockergroup) groups=1000(dockergroup)

Application Setup

Webui can be found at http://<your-ip>:8096

More information can be found in their official documentation here .

Hardware acceleration users for Intel Quicksync will need to mount their /dev/dri video device inside of the container by passing the following command when running or creating the container:

--device=/dev/dri:/dev/dri

We will automatically ensure the abc user inside of the container has the proper permissions to access this device.

Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:

https://github.com/NVIDIA/nvidia-docker

We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime --runtime=nvidia and add an environment variable -e NVIDIA_VISIBLE_DEVICES=all (can also be set to a specific gpu's UUID, this can be discovered by running nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv ). NVIDIA automatically mounts the GPU and drivers from your host into the jellyfin docker container.

Support Info

  • Shell access whilst the container is running:
    • docker exec -it jellyfin /bin/bash
  • To monitor the logs of the container in realtime:
    • docker logs -f jellyfin
  • Container version number
    • docker inspect -f '{{ index .Config.Labels "build_version" }}' jellyfin
  • Image version number
    • docker inspect -f '{{ index .Config.Labels "build_version" }}' linuxserver/jellyfin

Versions

  • 31.07.19: - Add AMD drivers for vaapi support on x86.
  • 13.06.19: - Add Intel drivers for vaapi support on x86.
  • 07.06.19: - Initial release.