Red Hat OpenShift Data Science Self-Managed Life Cycle

Overview

This document applies to the current release of Red Hat OpenShift Data Science Self-Managed.

Red Hat provides a published product life cycle for Red Hat OpenShift Data Science Self-Managed in order for customers and partners to effectively plan, deploy, and support their applications running on the platform. Red Hat publishes this life cycle in order to provide as much transparency as possible and may make exceptions from these policies as conflicts may arise.

The life cycle of Red Hat OpenShift Data Science Self-Managed follows a modern release-driven, phased life cycle approach, where at least four versions are available and will be supported at any one time. Red Hat aims to release these at a 3 weeks cadence, providing customers opportunity to plan updates.

Red Hat OpenShift Data Science Self-Managed is available as an add-on 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 Data Science Self-Managed is currently supported with the following OpenShift versions:

  • 4.10
  • 4.11
  • 4.12
For a more detailed overview of all the supported configuration, please refer to this article.

Life-cycle Dates

Red Hat Data Science Self-Managed Life Cycle Dates

Upgrade Policy

The Red Hat OpenShift Data Science Add-on, and installed components, will be automatically updated to the latest version, unless the manual update path is opted for. For a detailed walk through on how to configure the update strategy please refer to the RHODS Documentation. The upgrade process will support upgrading between consecutive minor releases. Customers are advised to deploy the latest available point release at their earliest convenience.

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