AI operations are moving out of the slide deck and into the platform itself. Hiring freezes and smaller teams come with increasing workloads. As a result, companies now expect the infrastructure layer to investigate, plan for, and help resolve issues.
Kubernetes platforms are among the first places where change is happening. Red Hat Inc. this week launched OpenShift 5, the first major release of the platform in seven years, with Model Context Protocol servers, guardrails and agent capabilities integrated into the stack. According to Mike Barrett (pictured left), vice president and general manager of hybrid platforms at Red Hat, customer expectations for the platform have changed enough to warrant a new version number.
“We started putting in guardrails. We started putting in agent capabilities, and now you can really have an agent experience with the platform,” Barrett said. “The platform itself can actually do things for you. It can tell what’s going on.”
Barrett and Ju Lim (pictured right), senior manager of product management at Red Hat, spoke with theCUBE’s John Furrier and Rebecca Knight at KubeCon + CloudNativeCon NA during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how OpenShift 5 integrates AI into upgrades, troubleshooting, and daily operations. (*Disclosure below.)
From weeks of planning to one click
On paper, upgrades look like routine, predictable work. In practice, a single cluster can run hundreds of applications, each with its own dependencies, release notes, and Kubernetes version requirements. OpenShift 5 uses AI to sort through all of that and create an upgrade plan, Barrett explained.
“We have customers who sometimes plan this in weeks and months,” Lim said. “Because of what Mike just said, we now have a way to actually create an AI plan with a single click that actually does all the risk analysis and assessment for you.”
Troubleshooting is handled the same way. According to Lim, OpenShift 5 draws on telemetry, logs and Kubernetes resource metadata to investigate problems and suggest solutions. Every action is optional and a human operator remains in control. Fully autonomous troubleshooting and agent updates remain in technology preview, according to Virtualization Review. Red Hat’s own site reliability engineering team provides an early test case.
“We run OpenShift as a managed service and they see between 8x and 10x improvement in time to get to the root cause of issues,” Barrett said.
Security increases urgency. Barrett said a spate of software vulnerabilities and exploits has shortened the time between disclosure and attack from days to hours. Customers want help moving legacy applications faster, and running existing virtual machines in Kubernetes clusters is part of Red Hat’s answer.
“We felt like this really highlighted a change in numbers,” Barrett said. “The way people want to work with the platform is completely different now, and that’s why we needed a large number.”
(*Disclosure: Red Hat Inc. sponsored this segment of theCUBE. Neither Red Hat Inc. nor other sponsors have editorial control over the content of theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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