Product Documentation for Red Hat OpenShift AI Self-Managed 2.25
Version:
Related Products
-
Red Hat OpenShift AI Cloud Service
Switch to the managed Cloud Service documentation -
Red Hat AI Inference Server
Switch to the AI Inference Server documentation -
Red Hat Enterprise Linux AI
Switch to the Enterprise Linux AI documentation
Welcome
-
Release notes
Features, enhancements, resolved issues, and known issues associated with this release -
Introduction to Red Hat OpenShift AI
OpenShift AI is a platform for data scientists and developers of artificial intelligence and machine learning (AI/ML) applications -
Supported configurations
Supported software platforms and architecture -
Product life cycle
Understand the product life cycle to plan deployments and support applications using the product -
This content is not included.Red Hat AI learning hub
Explore a curated collection of learning resources designed to help you accomplish key tasks with Red Hat AI products and services -
Provide feedback on Red Hat documentation
Let Red Hat know how we can make our documentation better
Documentation for OpenShift cluster administrators
-
Installing and uninstalling OpenShift AI Self-Managed
Install and uninstall OpenShift AI Self-Managed -
Installing and uninstalling OpenShift AI Self-Managed in a disconnected environment
Install and uninstall OpenShift AI Self-Managed in a disconnected environment -
Upgrading OpenShift AI Self-Managed
Upgrade OpenShift AI on OpenShift -
Upgrading OpenShift AI Self-Managed in a disconnected environment
Upgrade Red Hat OpenShift AI on OpenShift in a disconnected environment -
Creating a workbench
Create a workbench and a custom image by using Custom Resource Definitions (CRDs) and the command-line. -
Managing OpenShift AI
Cluster administrator tasks for managing OpenShift AI -
Enabling the model registry component
Enabling the model registry component in Red Hat OpenShift AI Self-Managed -
Managing and monitoring models
Manage and monitor models in Red Hat OpenShift AI Self-Managed -
Working with machine learning features (Technology Preview)
Store, manage, and serve features to machine learning models with Feature Store -
Usage data collection notice
Learn about data collected in relation with your usage of the software
Documentation for OpenShift AI administrators
-
Managing resources
Manage administration tasks from the OpenShift AI dashboard -
Configuring your model-serving platform
Configure your model-serving platform in Red Hat OpenShift AI Self-Managed -
Working with Llama Stack
Working with Llama Stack in Red Hat OpenShift AI Self-Managed -
Working with accelerators
Working with accelerators from Red Hat OpenShift AI Self-Managed -
Managing model registries
Managing model registries in Red Hat OpenShift AI Self-Managed
Documentation for OpenShift AI users
-
Getting started with Red Hat OpenShift AI Self-Managed
Learn how to work in an OpenShift AI environment -
OpenShift AI tutorial - Fraud detection example
Use OpenShift AI to train and deploy an example fraud detection model -
Working with data in an S3-compatible object store
Work with data stored in an S3-compatible object store from your workbench -
Working on data science projects
Organize your work in projects and workbenches, create and collaborate on notebooks, train and deploy models, configure model servers, and implement pipelines -
Working in your data science IDE
Working in your data science IDE from Red Hat OpenShift AI Self-Managed -
Working with data science pipelines
Work with data science pipelines from Red Hat OpenShift AI Self-Managed -
Monitoring data science models
Monitor your OpenShift AI models for fairness -
Working with distributed workloads
Use distributed workloads for faster and more efficient data processing and model training -
Working with connected applications
Connect to applications from Red Hat OpenShift AI Self-Managed -
Working with model registries
Working with model registries in Red Hat OpenShift AI Self-Managed -
Working with the model catalog
Working with the model catalog in Red Hat OpenShift AI Self-Managed -
Deploying models
Deploy models in Red Hat OpenShift AI Self-Managed -
API tiers
View a list of API tiers and API version examples for OpenShift AI