Project Icon

clusterplex

提升Plex分布式转码效率

ClusterPlex扩展了Plex的功能,引入分布式转码系统。它包含修改的Plex Media Server、转码协调器和Workers。通过共享存储和本地中继,ClusterPlex实现了高效的分布式转码。该项目兼容Kubernetes和Docker Swarm,增强了Plex的性能和扩展性,改善了媒体流服务质量。

ClusterPlex

GitHub license GitHub release ci

What is it?

ClusterPlex is basically an extended version of Plex, which supports distributed Workers across a cluster to handle transcoding requests. It has been tested on Kubernetes and Docker Swarm.

Kubernetes

Docker Swarm

Components

It's made up of 3 parts:

  • Plex Media Server

    There are two alternatives here:
    1. RECOMMENDED: Running the Official LinuxServer Plex image (ghcr.io/linuxserver/plex:latest) and applying the ClusterPlex dockermod (ghcr.io/pabloromeo/clusterplex_dockermod:latest)
    2. Running the ClusterPlex PMS docker image (ghcr.io/pabloromeo/clusterplex_pms:latest)
  • Transcoding Orchestrator

    Running a container using ghcr.io/pabloromeo/clusterplex_orchestrator:latest
  • Transcoding Workers

    Just as with PMS, two alternatives:
    1. RECOMMENDED: Official image (ghcr.io/linuxserver/plex:latest) with the Worker dockermod (ghcr.io/pabloromeo/clusterplex_worker_dockermod:latest)
    2. Custom Docker image: ghcr.io/pabloromeo/clusterplex_worker:latest

How does it work?

Overview

  • In the customized PMS server, Plex’s own transcoder is renamed and a shim is put in its place which calls a small Node.js app that communicates with the Orchestrator container over websockets. Also, a Local Relay is installed (an NGINX forward-proxy) which forwards calls coming from Workers to PMS as if they were made locally.

  • The Orchestrator (Node.js application which receives all transcoding requests from PMS) forwards it to one of the active Workers available over websockets.

  • Workers receive requests from the Orchestrator and kick off the transcoding and report progress back to the Local Relay running on PMS. Workers can come online or go offline and the Orchestrator manages their registrations and availability. These Workers can run as replicated services managed by the cluster.

Requirements

You will need to have a mechanism for sharing content between PMS and your Workers that supports ReadWriteMany (RWX).

This can be NFS, SMB, Ceph, GlusterFS or Longhorn, to name a few.

The content that needs to be shared are the Media Libraries, and the transcoding location, and paths MUST be the same on all workers and the main PMS.

Shared Storage

Media Libraries

In order for Workers to function properly, all Media content should be shared using identical paths between PMS and the Workers. This would be using network shared storage supporting ReadWriteMany (RWX), such as NFS, SMB, Ceph, GlusterFS, Longhorn, etc.

Transcoding location

The same applies to the /transcode directory, in both PMS and the Workers. You CAN use a different directory name other than /transcode, however, it MUST match between PMS and all Workers, as well as be configured within Plex as the transcoding path:

transcode-path

Non-shared Persistent Storage

Plex Application Data

IMPORTANT: PMS's Application Data mount (/config) does NOT need to be shared with the Workers, so you can use your preferred method for persistent storage. Just beware that Plex doesn't play very well with network storage for this, especially regarding symlinks and file locks (used by their sqlite db).

The recommendation is to use Ceph, Longhorn or GlusterFS.

Codecs

Workers require a path to store downloaded codecs for the particular architecture of the Worker. Codecs are downloaded when the worker container starts up.

The path within the container is /codecs, which you can mount to a volume in order to have them persisted across container recreations. Subdirectories for each plex version and architecture are created within it.

Network settings in PMS

Latest versions of ClusterPlex don't require any special network configuration, due to the new Local Relay functionality which forwards calls from Workers to Plex, which is enabled by default.

However, if you have disabled Local Relay by setting LOCAL_RELAY_ENABLED to "0", then in Plex's Network Configuration, you must add the IPs or the range that will be used by Workers to the "List of IP addresses and networks that are allowed without auth".

For example: network-ips

Installation

See the docs section for details on each component's configuration parameters and example configurations both on Kubernetes and Docker Swarm.

项目侧边栏1项目侧边栏2
推荐项目
Project Cover

豆包MarsCode

豆包 MarsCode 是一款革命性的编程助手,通过AI技术提供代码补全、单测生成、代码解释和智能问答等功能,支持100+编程语言,与主流编辑器无缝集成,显著提升开发效率和代码质量。

Project Cover

AI写歌

Suno AI是一个革命性的AI音乐创作平台,能在短短30秒内帮助用户创作出一首完整的歌曲。无论是寻找创作灵感还是需要快速制作音乐,Suno AI都是音乐爱好者和专业人士的理想选择。

Project Cover

白日梦AI

白日梦AI提供专注于AI视频生成的多样化功能,包括文生视频、动态画面和形象生成等,帮助用户快速上手,创造专业级内容。

Project Cover

有言AI

有言平台提供一站式AIGC视频创作解决方案,通过智能技术简化视频制作流程。无论是企业宣传还是个人分享,有言都能帮助用户快速、轻松地制作出专业级别的视频内容。

Project Cover

Kimi

Kimi AI助手提供多语言对话支持,能够阅读和理解用户上传的文件内容,解析网页信息,并结合搜索结果为用户提供详尽的答案。无论是日常咨询还是专业问题,Kimi都能以友好、专业的方式提供帮助。

Project Cover

讯飞绘镜

讯飞绘镜是一个支持从创意到完整视频创作的智能平台,用户可以快速生成视频素材并创作独特的音乐视频和故事。平台提供多样化的主题和精选作品,帮助用户探索创意灵感。

Project Cover

讯飞文书

讯飞文书依托讯飞星火大模型,为文书写作者提供从素材筹备到稿件撰写及审稿的全程支持。通过录音智记和以稿写稿等功能,满足事务性工作的高频需求,帮助撰稿人节省精力,提高效率,优化工作与生活。

Project Cover

阿里绘蛙

绘蛙是阿里巴巴集团推出的革命性AI电商营销平台。利用尖端人工智能技术,为商家提供一键生成商品图和营销文案的服务,显著提升内容创作效率和营销效果。适用于淘宝、天猫等电商平台,让商品第一时间被种草。

Project Cover

AIWritePaper论文写作

AIWritePaper论文写作是一站式AI论文写作辅助工具,简化了选题、文献检索至论文撰写的整个过程。通过简单设定,平台可快速生成高质量论文大纲和全文,配合图表、参考文献等一应俱全,同时提供开题报告和答辩PPT等增值服务,保障数据安全,有效提升写作效率和论文质量。

投诉举报邮箱: service@vectorlightyear.com
@2024 懂AI·鲁ICP备2024100362号-6·鲁公网安备37021002001498号