Red Hat OpenShift AI Self-Managed Life Cycle

Overview

Red Hat provides a product life cycle for Red Hat OpenShift AI (RHOAI) Self-Managed allowing for customers and partners to effectively plan, deploy, and support their applications running on the platform. Red Hat publishes this life cycle to provide transparency but might make exceptions from these policies if conflicts might arise.

Release Types:

RHOAI release types, and their respective life cycles, generally fall under three main categories:

  • Fast releases: These releases include Full Support for one month, or until the next fast release is available. In some cases, the next release might be later than a month.
  • Stable releases: These releases include Full Support for seven months. Red Hat issues a stable release every three minor releases.
  • Extended Update Support (EUS) releases: These releases include Full Support for seven months followed by Extended Update Support for eleven months. Red Hat issues a EUS release every nine minor releases.

Caution:

Due to a known issue with the stream image delivery process, fast releases are currently available on unintended streaming channels, for example, stable and stable-x.y. For accurate release type, channel, and support lifecycle information, refer to the Life-cycle Dates table below.

In order to understand how to effectively deploy and maintain a specific release type, refer to the Upgrade Strategy section.

During the Full Support phase, qualified Critical and Important Security Advisories (RHSAs) will be released as they become available. Urgent and Selected High Priority Bug Fix Advisories (RHBAs) will be released as they become available; all other available fix and qualified patches may be released via periodic updates. In order to receive security and bug fixes, customers are expected to upgrade their OpenShift AI environment to the most current supported micro (x.y.z) version.

During the Extended Update Support phase Red Hat will maintain component specific support. For supported components in a given release, please refer to the Supported Configurations page.

Red Hat OpenShift AI Self-Managed is available as an Operator to Red Hat OpenShift and maintains a release schedule that is independent from other Red Hat products and services.

The Red Hat OpenShift Life Cycle provides information on supported versions for Red Hat OpenShift. Red Hat OpenShift AI Self-Managed currently supports the following OpenShift versions:

  • 4.17
  • 4.16
  • 4.15
  • 4.14
For information on RHOAI supported configurations, see the Supported Configurations article.

Life-cycle Dates

Red Hat OpenShift AI Self-Managed Life Cycle Dates

Upgrade Policy

The RHOAI operator and installed components, are automatically updated to the latest version, unless the manual upgrade strategy is opted for. For more information about how to install the operator and configure the update strategy, see the RHOAI Documentation. Customers are advised to deploy the latest available minor version at their earliest convenience.

This upgrade policy includes feature releases, as well as bug and security fix releases.

Upgrade Strategy and Paths

Customers are advised to choose their upgrade strategy according to their needs, which might vary in terms of release longevity or number of features available. When defining this strategy, It is important to consider that choosing the automatic approach ensures that customers will receive all the latest security and bug fixes for the currently supported version. Red Hat OpenShift AI uses major (x.), minor (x.y), and micro (x.y.z) release versions and maintains a release schedule that is independent from other Red Hat products and services. Red Hat tests and supports upgrade paths that are allowed according to the OLM rules enforced by the operator. The customer is free to change the streaming channels accordingly.
Note: Red Hat recommends that you plan your upgrades so that you are on a supported channel at all times. You must be on the latest available version in your selected channel to receive support for Red Hat OpenShift AI.

fast

Customers that want access to the latest product features are recommended to choose the fast streaming channel. Be advised that Red Hat supports only one fast release at a given time. These types of deployments are recommended for where having the lasted features is desirable. Red Hat recommends choosing this streaming channel with selecting the automatic update strategy in order to avoid the overhead of upgrading manually monthly. For the fast update channel, Red Hat supports direct, single-step upgrades from the previous minor version only (y-1). Red Hat does not test updates to noncontiguous versions and cannot guarantee compatibility with earlier versions. For example, upgrading directly from OpenShift AI 2.13 (fast) to the latest version of 2.15 (fast) is not supported. Instead, users could upgrade as follows:

  • 2.13 (fast) -> 2.14 (fast)
  • 2.14 (fast) -> 2.15 (fast)

stable and stable-x.y

Customers who prioritize stability over new feature availability are recommended to choose the stable or stable-x.y streaming channels. Selecting the automatic updates strategy with the stable, unnumbered channel, will result in the deployments being upgraded to the latest stable minor version as soon as it is released. This choice will reduce the overhead of updating manually as soon as a new stable release is available and will grant access to the latest stable features. Alternatively, the selection of the numbered stable channels will allow customers to plan and execute the upgrade to the next stable release while keeping their deployment under full support within a four months time window. Be advised that Red Hat supports from two to three stable releases at a given time. These types of deployments are recommended for most stage and production environments. In the stable and stable-x.y update channels, Red Hat supports single-step upgrades from the most recent previous minor stable version to the latest minor stable version and sequential upgrades from stable to the latest fast version. For example, users could upgrade from OpenShift AI 2.10.0 (stable) as follows:

  • 2.10.0 (stable) -> 2.10.1 (stable)
  • 2.10.1 (stable) -> 2.13.0 (stable)
  • 2.13.0 (stable) -> 2.13.1 (stable)
and, switching to the fast channel:
  • 2.13.1 (stable) -> 2.14.0 (fast)
  • 2.14.0 (fast) -> 2.15.0 (fast)

eus-x.y

For customers prioritizing stability, the eus-x.y streaming channels offer up to nine months for planning upgrades to the next Extended Update Support (EUS) release. These channels suit enterprise environments needing extended support beyond a seven-month upgrade cycle. Red Hat supports single-step upgrades between consecutive minor EUS versions and sequential upgrades from EUS to the latest fast version. This dual approach enables seamless transitions, accommodating both stability and access to newer releases.

Red Hat tests and supports upgrade paths that are allowed according to the OLM rules enforced by the operator. The customer is free to change the streaming channels accordingly.

Components Life Cycle

Data science pipelines v1 support removed

Previously, data science pipelines in OpenShift AI were based on KubeFlow Pipelines v1. Starting with OpenShift AI 2.9, data science pipelines are based on KubeFlow Pipelines v2, which uses a different workflow engine. Data science pipelines 2.0 is enabled and deployed by default in OpenShift AI.

Starting with OpenShift AI 2.16, data science pipelines 1.0 resources are no longer supported or managed by OpenShift AI. It is no longer possible to deploy, view, or edit the details of pipelines that are based on data science pipelines 1.0 from either the dashboard or the KFP API server.

OpenShift AI does not automatically migrate existing data science pipelines 1.0 instances to 2.0. If you are upgrading to OpenShift AI 2.16, you must manually migrate your existing data science pipelines 1.0 instances. For more information, see Migrating to data science pipelines 2.0.