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 PageUninstall
Next PageInfrastructure Management

#Uninstall

This document guides you through the complete uninstallation of Alauda AI and its related components from your cluster. The uninstallation process is divided into two main parts: first, uninstalling the optional Alauda AI Model Serving and its instances, and then, uninstalling the core Alauda AI instance and Operator.

If you don't need the Serverless capability or want to use only the essential core features to save resources, you can choose to perform only the first step to remove the Alauda AI Model Serving components.

Note: Before proceeding with the uninstallation, ensure you have backed up all important data and models. The uninstallation process will permanently delete all resources and configurations associated with Alauda AI.

#TOC

#Uninstalling Alauda AI Model Serving Components

This section guides you on how to uninstall the components that provide Serverless capabilities.

#Deleting the Alauda AI Model Serving Instance

WARNING

Before deleting the Alauda AI Model Serving Instance, you must check the Serverless parameter configuration.

For versions 1.4 and later: Ensure the BuiltIn Knative Serving field is set to Unmanaged.

For version 1.3: Ensure the Knative Serving Mode field is set to Unmanaged.

#Procedure

From the Administrator view:

  1. Click Marketplace / OperatorHub.
  2. At the top of the console, from the Cluster dropdown list, select the cluster you want to uninstall from.
  3. Find and select Alauda AI Model Serving.
  4. On the Alauda AI Model Serving page, click the All Instances tab.
  5. Find the instance (commonly named default-knative-serving, or your custom instance name).
  6. Click the ... menu on the right side of the instance, then select Delete.
  7. In the confirmation window, confirm the deletion, then click Delete.

#Verification

Verify that the instance has been deleted with the following command:

kubectl get knativeservings.components.aml.dev -n knative-serving

If the instance was successfully deleted, the command will return "No resources found in knative-serving namespace."

#Uninstalling the Alauda AI Model Serving Operator

#Procedure

From the Administrator view:

  1. Click Marketplace / OperatorHub.
  2. At the top of the console, from the Cluster dropdown list, select the cluster you want to uninstall from.
  3. Find and select Alauda AI Model Serving.
  4. On the Alauda AI Model Serving page, click Uninstall.
  5. In the confirmation window, check the installation location of the Alauda AI Model Serving Operator (default is kserveless-operator).
  6. Click the Uninstall button.

#Verification

Confirm that the Alauda AI Model Serving tile's status has changed from Installed to Not Installed or has disappeared from the list.

#Uninstalling Core Alauda AI Components

After completing the first section, you can proceed to uninstall the core Alauda AI components.

#Deleting the Alauda AI Instance

#Procedure

From the Administrator view:

  1. Click Marketplace / OperatorHub.
  2. At the top of the console, from the Cluster dropdown list, select the cluster you want to uninstall from.
  3. Find and select Alauda AI.
  4. On the Alauda AI page, click the All Instances tab.
  5. Find the instance named default.
  6. Click the ... menu on the right side of the instance, then select Delete.
  7. In the confirmation window, confirm the deletion, then click Delete.

#Verification

Verify that the instance has been deleted with the following command:

kubectl get amlcluster default

If the instance was successfully deleted, the command will return No resources found or a similar message.

#Uninstalling the Alauda AI Operator

#Procedure

From the Administrator view:

  1. Click Marketplace / OperatorHub.
  2. At the top of the console, from the Cluster dropdown list, select the cluster you want to uninstall from.
  3. Find and select Alauda AI.
  4. On the Alauda AI page, click Uninstall.
  5. In the confirmation window, check the installation location of the Alauda AI Operator (default is aml-operator).
  6. Click the Uninstall button.

#Verification

Confirm that the Alauda AI tile's status has changed from Installed to Not Installed or has disappeared from the list.

#Cleaning Up Remaining Resources

CRDs are not removed automatically when an operator is uninstalled. You can manually clean up these remaining resources, and be aware that:

WARNING

Deleting a CRD will permanently delete all associated data.

The amlnamespaces.manage.aml.dev CRD, which is responsible for managing namespaces, is not included in the deletion commands below. To ensure a complete deletion of resources, you must manually remove the finalizer field after the CRD deletion operation.

It's generally recommended to keep this CRD unless you are certain you no longer need its management capabilities.

# Delete all control plane CRDs
kubectl delete crd amls.components.aml.dev
kubectl delete crd kserves.components.aml.dev
kubectl delete crd amlclusters.amlclusters.aml.dev
kubectl delete crd knativeservings.components.aml.dev