k8s-device-plugin
terraform-provider-kubernetes
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k8s-device-plugin | terraform-provider-kubernetes | |
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11 | 6 | |
2,304 | 1,533 | |
4.6% | 1.2% | |
9.5 | 9.0 | |
5 days ago | 3 days ago | |
Go | Go | |
Apache License 2.0 | Mozilla Public License 2.0 |
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k8s-device-plugin
- Nos – Open-Source to Maximize GPU Utilization in Kubernetes
- Show HN: Nos – Open-Source to Maximize GPU Utilization in Kubernetes
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Time-Slicing GPUs with Karpenter
K8s-device-plugin
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Understanding Kubernetes Limits and Requests
This framework allows the use of external devices (e.g., NVIDIA GPUs, AMD GPUS, SR-IOV NICs) without modifying core Kubernetes components.
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What is the difference between nvidia device plugin and GPU operator?
GPU Operator Device plugin
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Share a GPU between pods on AWS EKS
If you ever tried to use GPU-based instances with AWS ECS, or on EKS using the default Nvidia plugin, you would know that it's not possible to make a task/pod shared the same GPU on an instance. If you want to add more replicas to your service (for redundancy or load balancing), you would need one GPU for each replica.
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Looking for a sanity check on a project I'm working on at home, hoping you fine people can help - Raspberry Pi Kubernetes Cluster
Some notes on Plex/Emby/Kodi and transcoding. If you want true transcoding with GPU acceleration, you have to have Nvidia GPU or be a k8s device plugin genius. The whole idea of mounting elastic devices in k8s is fairly new and rather complex. In the mean time transcoding is best done on a beefy device with a proper CPU (eg i7) or specifically Nvidia GPU because there are numerous pre-made plugins. I just run Plex and Emby on an old ATX gaming machine without GPU acceleration and it works totally fine. They were barely usable for just me when running on the RPis, wouldn't recommend it unless you can figure out how to mount the correct devices in the pod using a custom raspberry pi device plugin . . . lol good luck! - Arm labs device manager: https://community.arm.com/developer/research/b/articles/posts/a-smarter-device-manager-for-kubernetes-on-the-edge - Deis labs Akri device manager: https://github.com/deislabs/akri - Nvidia GPU plugin: https://github.com/NVIDIA/k8s-device-plugin
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NVIDIA GPU passthrough with k3s?
Thanks for jumping in to help! So maybe I’m missing something - isn’t this only for Kubevirt? My setup is just a regular Ubuntu 20.04 VM with the GPU passed through. K3s from Rancher Labs (https://k3s.io/) is then running inside that VM. I’m using the NVIDIA Device Plugin Daemonset as well: https://github.com/NVIDIA/k8s-device-plugin
terraform-provider-kubernetes
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Share a GPU between pods on AWS EKS
After the resources be provisioned, you might want to run terraform apply -refresh-only to refresh your local state as the creation of some resource change the state of others within AWS. Also, state differences on metadata.resource_version of k8s resources almost always show up after an apply. This seems to be related to this issue.
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What are your experiences in using the Kubernetes and Helm Providers?
We want to do that, but this issue has been a huge blocker for us. You might not hit it unless you’re using AKS, though.
What are some alternatives?
kubevirt-gpu-device-plugin - NVIDIA k8s device plugin for Kubevirt
harvester - Open source hyperconverged infrastructure (HCI) software
aws-eks-share-gpu - How to share the same GPU between pods on AWS EKS
azure-service-operator - Azure Service Operator allows you to create Azure resources using kubectl
terrajet - Generate Crossplane Providers from any Terraform Provider
aws-virtual-gpu-device-plugin - AWS virtual gpu device plugin provides capability to use smaller virtual gpus for your machine learning inference workloads
containers-roadmap - This is the public roadmap for AWS container services (ECS, ECR, Fargate, and EKS).
asdf-awscli
asdf-tflint - An asdf plugin for installing terraform-linters/tflint.
asdf-hashicorp - HashiCorp plugin for the asdf version manager
csi-driver-smb - This driver allows Kubernetes to access SMB Server on both Linux and Windows nodes.