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Alauda AI
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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 PageInference Service
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#Introduction

The Inference Service is a core feature of the Alauda AI platform, dedicated to efficiently deploying LLM models as online inference services, supporting various invocation methods such as HTTP API and gRPC. Through the Inference Service, users can rapidly build LLM applications and provide stable, high-performance LLM capabilities externally.

WARNING

Running the built-in runtime in the container requires root privileges. Please ensure it is used in a trusted environment and follow your security policies.