Alauda AI
API Reference
Introduction

Pre-installation Configuration

Install Workbench

Install Alauda AI Essentials

Install Alauda AI

Tools Menu Configuration

Upgrade Alauda AI

Migrating to Knative Operator

Infrastructure Management

Hardware Profile

Hardware Profile Management

Create Hardware Profile using CLI

Schedule Workloads to Specific GPU Nodes

Creating CPU-Only and GPU-Accelerated Profiles

Device Management

About Alauda Build of Hami

About Alauda Build of NVIDIA GPU Device Plugin

Namespace Management

Create Workbench

Fine-tuning LLMs using Workbench

Fine-tuning LLMs with Training Hub

Fine-tune and Pretrain LLMs on Ascend NPU Using Workbench

Kubeflow Trainer Quick Start

Run Kubeflow Pipelines from JupyterLab with Elyra

Using Connections

Model Deployment & Inference

Inference Service

Inference Service

Create Inference Service using CLI

Extend Inference Runtimes

Using KServe Modelcar for Model Storage

Enable Expert Parallel for vLLM Inference Services

Configure External Access for Inference Services

Configure Scaling for Inference Services

Scheduling Inference Services based on the CUDA version

Set Up Autoscaling for Inference Services with KEDA

Troubleshooting

Experiencing Inference Service Timeouts with MLServer Runtime

Inference Service Fails to Enter Running State

Model Management

Model Repository

Upload Models Using Notebook

Monitoring & Ops

Features Overview

Logging & Tracing

Resource Monitoring

Resource Monitoring

Add a Monitoring Dashboard

Troubleshooting

Monitor Dashboard Stuck at Loading

Install Label Studio

LLM Compressor with Alauda AI

Alauda Build of KubeRay Operator

CodeFlare SDK Tutorial

Alauda Build of Kueue

Configuring quotas

Monitoring pending workloads

Configuring fair sharing

Gang scheduling

Integrate with Alauda DevOps Pipelines

Integrate with InferenceService

Alauda Build of KServe

Alauda Build of Llama Stack

Install Llama Stack

Alauda Build of LeaderWorkerSet

Install LeaderWorkerSet

Evaluating RAG with Ragas

Alauda Build of TrustyAI

Install TrustyAI

AI Guardrails for LLM safety

NeMo Guardrails

TrustyAI Service (TAS)

Alauda Build of Envoy AI Gateway

Install Envoy AI Gateway

Alauda Build of Feast

Alauda support for Kubeflow

Install Kubeflow Plugins

Upgrade Kubeflow Plugins

how_to

Use Kubeflow Notebooks

Use Kubeflow Tensorboards

Use Kubeflow Volumes

Use Kubeflow Model Registry

Use Kubeflow Pipelines

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]

Architecture, Version and Components

Introduction

Note

For the introduction to the usage methods of ACP APIs, please refer to ACP APIs Guide.

Previous pageAPI Reference Next pageKubernetes APIs