logo
Alauda AI
English
Русский
English
Русский
logo
Alauda AI
Navigation

Overview

Introduction
Quick Start
Release Notes

Install

Pre-installation Configuration
Install Alauda AI Essentials
Install Alauda AI

Upgrade

Upgrade from AI 1.3

Uninstall

Uninstall

Infrastructure Management

Device Management

About Alauda Build of Hami
About Alauda Build of NVIDIA GPU Device Plugin

Multi-Tenant

Guides

Namespace Management

Workbench

Overview

Introduction
Install
Upgrade

How To

Create WorkspaceKind
Create Workbench

Model Deployment & Inference

Overview

Introduction
Features

Inference Service

Introduction

Guides

Inference Service

How To

Extend Inference Runtimes
Configure External Access for Inference Services
Configure Scaling for Inference Services

Troubleshooting

Experiencing Inference Service Timeouts with MLServer Runtime
Inference Service Fails to Enter Running State

Model Management

Introduction

Guides

Model Repository

Monitoring & Ops

Overview

Introduction
Features Overview

Logging & Tracing

Introduction

Guides

Logging

Resource Monitoring

Introduction

Guides

Resource Monitoring

API Reference

Introduction

Kubernetes APIs

Inference Service APIs

ClusterServingRuntime [serving.kserve.io/v1alpha1]
InferenceService [serving.kserve.io/v1beta1]

Workbench APIs

Workspace Kind [kubeflow.org/v1beta1]
Workspace [kubeflow.org/v1beta1]

Manage APIs

AmlNamespace [manage.aml.dev/v1alpha1]

Operator APIs

AmlCluster [amlclusters.aml.dev/v1alpha1]
Glossary
Previous PageAbout Alauda Build of Hami
Next PageMulti-Tenant

#About Alauda Build of NVIDIA GPU Device Plugin

The NVIDIA device plugin for Kubernetes is a Daemonset that allows you to automatically:

  • Expose the number of GPUs on each nodes of your cluster
  • Keep track of the health of your GPUs
  • Run GPU enabled containers in your Kubernetes cluster.
Note
Because Alauda Build of NVIDIA GPU Device Plugin releases on a different cadence from Alauda Container Platform, the Alauda Build of NVIDIA GPU Device Plugin documentation is now available as a separate documentation set at .