Pre-installation Configuration

Enable Fine-Tuning and Training Features

Install Alauda AI Essentials

Install Alauda AI

Upgrade from AI 1.3

Infrastructure Management

Device Management

About Alauda Build of Hami

About Alauda Build of NVIDIA GPU Device Plugin

Namespace Management

Create WorkspaceKind

Create Workbench

Model Deployment & Inference

Inference Service

Inference Service

Extend Inference Runtimes

Configure External Access for Inference Services

Configure Scaling for Inference Services

Configure Accurately Scheduling Inference Services based on the CUDA version

Troubleshooting

Experiencing Inference Service Timeouts with MLServer Runtime

Inference Service Fails to Enter Running State

Model Management

Model Repository

Upload Models Using Notebook

Create Fine-tuning Tasks

Developing Custom Fine-Tuning Templates

Create Training Tasks

Develop Custom Training Templates

Monitoring & Ops

Features Overview

Logging & Tracing

Resource Monitoring

Resource Monitoring

Install Label Studio

Kubernetes APIs

Inference Service APIs

ClusterServingRuntime [serving.kserve.io/v1alpha1]

InferenceService [serving.kserve.io/v1beta1]

Workspace Kind [kubeflow.org/v1beta1]

Workspace [kubeflow.org/v1beta1]

AmlNamespace [manage.aml.dev/v1alpha1]

AmlCluster [amlclusters.aml.dev/v1alpha1]

Resource Monitoring

Introduction

Introduction

Usage Limitations

Guides

Resource Monitoring

Function Overview
Main Features
Accessing Resource Monitoring
Monitoring Metrics

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