Red Hat extends Lightspeed AI to Linux, OpenShift

Red Hat is extending its Lightspeed generative AI technology to work with the company’s Red Hat OpenShift hybrid cloud application platform as well as with Red Hat Enterprise Linux (RHEL).

Announced May 7, Red Hat OpenShift Lightspeed and Red Hat Enterprise Linux Lightspeed will offer intelligent, natural language processing capabilities, intended to make OpenShift and RHEL easier for novices to use and more efficient for experienced professionals, Red Hat said. Red Hat OpenShift Lightspeed is slated for availability in late 2024. Red Hat Enterprise Linux is in the planning stage.

Red Hat OpenShift Lightspeed applies generative AI to deploying and scaling both traditional and cloud-native applications on OpenShift clusters, helping OpenShift novices to more quickly build skills to run the application platform and helping experts to be more efficient. For example, when a cluster is at capacity, Lightspeed will suggest to the user that autoscaling should be enabled and, after assessing that clusters are hosted on a public cloud, suggest a new instance of the appropriate size, Red Hat said. Lightspeed then could offer to enable autoscaling down once capacity requirements decrease.

Red Hat Enterprise Linux Lightspeed will help simplify how organizations deploy and maintain Linux environments. As systems scale and complexity becomes a challenge, Red Hat Enterprise Linux Lightspeed will help RHEL operations teams do more faster, Red Hat said. Lightspeed could flag an administrator that a security advisory has been released with fixes, for example.

In addition to introducing Lightspeed for OpenShift and RHEL, Red Hat announced that Red Hat Ansible Lightspeed has been enhanced with model customization and tuning and a dashboard for viewing telemetry data. Red Hat Ansible Lightspeed was introduced in Red Hat Ansible Automation Platform in May 2023. 

Model customization and tuning via IBM Watsonx Code Assistant enables Ansible Lightspeed users to use their existing Ansible content to train the model. Customers can improve the quality and accuracy of their Ansible content with code recommendations that are tailored to their organizations’ specific needs and automation patterns, Red Hat said.