intel-device-plugins-for-kubernetes VS clusterplex

Install the Intel Device Plugin Operator: More information on this can be found at https://github.com/intel/intel-device-plugins-for-kubernetes/blob/main/cmd/operator/README.md. I highly recommend installing this operator via the Helm chart available here: https://github.com/intel/helm-charts/tree/main/charts/device-plugin-operator.

In my K8S cluster, I have 2 Intel NUC 8i5 and I use a plugin to use their integrated GPUs in containers : https://github.com/intel/intel-device-plugins-for-kubernetes

GPU Plugin for Kubernetes: https://github.com/intel/intel-device-plugins-for-kubernetes/blob/main/cmd/gpu_plugin/README.md

Same thing for the GPU plugin — https://github.com/intel/intel-device-plugins-for-kubernetes

Clusterplex

I'm also very interested in distributing transcoding jobs via https://github.com/pabloromeo/clusterplex. Have you tried that yet?

Here is a link to one of the Cluster projects: https://github.com/pabloromeo/clusterplex

I use a forked version of this: https://github.com/pabloromeo/clusterplex which has been working awesome.

This is not true. You could setup Plex in a cluster and based on which content is requested let it handle by a certain transcoding worker. You have Clusterplex or you have UnicornTranscoder. Both are actively maintained repositories. This does however require some knowledge of Linux/Kubernetes so if OP (/u/slacktopuss) doesn't know how Ubuntu and Kubernetes works, it's going to take a long time before you're up and running.

And if UnicornTranscoder isn't it, you can always look intoClusterPlex's implementation. Basically the same as how UnicornTranscoder works (Node.JS as balancer and some remote FFMPEG installs).

To see full working examples of this we can take a look at the builds of two pet projects of mine: Docker-Dogecoin and ClusterPlex.