Red Hat OpenShift AI Self-Managed 2.16

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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

Provide feedback on Red Hat documentation

Let Red Hat know how we can make our documentation better.

Documentation for OpenShift AI users

Guidance for ML Ops Engineers and Data Scientists on how to work in OpenShift AI

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 an example model in JupyterLab, deploy the model, and refine the model by using automated pipelines

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

Serving models

Serve models in Red Hat OpenShift AI Self-Managed

API tiers

View a list of API tiers and API version examples for OpenShift AI

Documentation for OpenShift AI administrators

Guidance for managing OpenShift AI administration settings

Managing resources

Manage administration tasks from the OpenShift AI dashboard

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 cluster administrators

Guidance on installing and managing OpenShift AI for OpenShift cluster administrators

Supported configurations

Supported software platforms and architecture

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

Managing OpenShift AI

Cluster administrator tasks for managing OpenShift AI

Configuring the model registry component

Configuring the model registry component in Red Hat OpenShift AI Self-Managed

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