k8s-device-plugin
helm
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k8s-device-plugin | helm | |
---|---|---|
11 | 206 | |
2,393 | 26,013 | |
6.3% | 1.1% | |
9.5 | 9.0 | |
6 days ago | 7 days ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
k8s-device-plugin
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Unlocking AI and ML Metal Performance with QBO Kubernetes Engine (QKE) Post
https://github.com/NVIDIA/k8s-device-plugin/issues/332#issue...
- 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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Nvidia GPU Plugin: Am I really limited to one pod per GPU?
Not talking about MIG. NVIDIA device plugin. https://github.com/NVIDIA/k8s-device-plugin
- Nvidia Kubernetes plugin install option that does not require Helm?
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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
helm
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Kubernetes CI/CD Pipelines
Applying Kubernetes manifests individually is problematic because files can get overlooked. Packaging your applications as Helm charts lets you version your manifests and easily repeat deployments into different environments. Helm tracks the state of each deployment as a "release" in your cluster.
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deploying a minio service to kubernetes
helm
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How to take down production with a single Helm command
Explanation here: https://github.com/helm/helm/issues/12681#issuecomment-19593...
Looks like it's a bug in Helm, but actually isn't Helm's fault, the issue was introduced by Fedora Linux.
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Building a VoIP Network with Routr on DigitalOcean Kubernetes: Part I
Helm (Get from here https://helm.sh/)
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The 2024 Web Hosting Report
It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.
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Deploying a Web Service on a Cloud VPS Using Kubernetes MicroK8s: A Comprehensive Guide
Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!
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Deploy Kubernetes in Minutes: Effortless Infrastructure Creation and Application Deployment with Cluster.dev and Helm Charts
Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.
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Kubernets Helm Chart
We can search for charts https://helm.sh/ . Charts can be pulled(downloaded) and optionally unpacked(untar).
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Introduction to Helm: Comparison to its less-scary cousin APT
Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.
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🎀 Five tools to make your K8s experience more enjoyable 🎀
Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.
What are some alternatives?
kubevirt-gpu-device-plugin - NVIDIA k8s device plugin for Kubevirt
crossplane - The Cloud Native Control Plane
harvester - Open source hyperconverged infrastructure (HCI) software
kubespray - Deploy a Production Ready Kubernetes Cluster
aws-eks-share-gpu - How to share the same GPU between pods on AWS EKS
Packer - Packer is a tool for creating identical machine images for multiple platforms from a single source configuration.
aws-virtual-gpu-device-plugin - AWS virtual gpu device plugin provides capability to use smaller virtual gpus for your machine learning inference workloads
krew - 📦 Find and install kubectl plugins
terraform-provider-kubernetes - Terraform Kubernetes provider
skaffold - Easy and Repeatable Kubernetes Development
containers-roadmap - This is the public roadmap for AWS container services (ECS, ECR, Fargate, and EKS).
dapr-demo - Distributed application runtime demo with ASP.NET Core, Apache Kafka and Redis on Kubernetes cluster.