OpenShift and OpenShift AI

Red Hat OpenShift AI is a fully Red Hat managed cloud service that is available as an add-on to:

  • Red Hat OpenShift Dedicated

  • Red Hat OpenShift Service on Amazon Web Services (ROSA Classic)

  • Red Hat OpenShift on Azure (ARO)

Both an OpenShift and OpenShift AI add-on subscriptions are required.

OpenShift AI Add-on Requirements

Installing OpenShift AI as a managed cloud service add-on involves the following high-level tasks:

  • Confirm that your OpenShift cluster meets all requirements.

  • Configure an identity provider for your OpenShift cluster.

  • Add administrative users for your OpenShift cluster.

  • Subscribe to the Red Hat OpenShift AI Add-on.

For OpenShift Dedicated with a CCS for AWS or GCP, get a subscription through Red Hat.

Customer Cloud Subscriptions (CCS) on AWS such as OpenShift Dedicated utilizes a Customer Cloud Subscription (CCS) model that allows Red Hat to deploy and manage clusters into a customer’s existing Amazon Web Service (AWS) account.

An OpenShift Dedicated or ROSA cluster configuration that meets the following requirements: At least 2 worker nodes with at least 8 CPUs and 32 GiB RAM available for OpenShift AI to use when you install the Add-on. If this requirement is not met, the installation process fails to start and an error is displayed.

When you create a new cluster, select m6a.2xlarge for the computer node instance type to satisfy the requirements.

OpenShift AI Operator

The Red Hat OpenShift AI Operator is a meta-operator that deploys and maintains all components and sub-operators that are part of OpenShift AI.

When you install the Red Hat OpenShift AI operator add-on into an compatible OpenShift Container Platform (OCP) Cluster , the following new projects (namepsace) are created:

  • The redhat-ods-operator project contains the Red Hat OpenShift AI Operator.

  • The redhat-ods-applications project installs the dashboard and other required components of OpenShift AI.

  • The redhat-ods-monitoring project contains services for monitoring and billing.

  • The rhods-notebooks project is where notebook environments are deployed by default.

Once installed and an OpenShift AI Data Science Cluster (DSC) is created, AI/ML Engineers, Data Scientist, Data Engineers, and IT & Operations can begin to use OpenShift AI as the central platform for AI application and model development.

AI Engineers and data scientists must create additional projects for the applications that will use your machine learning models. These are created using OpenShift AI dashboard or OpenShift CLI to create a new data science project, which creates a new project within OpenShift.

Access to object storage

Components of OpenShift AI require or can use S3-compatible object storage such as AWS S3, MinIO, Ceph, or IBM Cloud Storage. An object store is a data storage mechanism that enables users to access their data either as an object or as a file. The S3 API is the recognized standard for HTTP-based access to object storage services.

You can also purchase Red Hat OpenShift AI as self-managed software. To purchase a new subscription, contact your Red Hat account manager. If you do not yet have an account manager, complete the form at https://www.redhat.com/en/contact to request one.