As artificial intelligence induces the same infrastructure sprawl previously seen with cloud technologies, AI resource management has emerged as a crucial challenge for enterprises.

Organizations are now inundated with vast sets of static and in-motion data resources, raising the question: what solutions can effectively manage AI resources and infrastructure contained within OpenShift, while supporting companies on their transformation journeys? By integrating with OpenShift, Run:ai provides a robust solution, enabling seamless management of AI resources and infrastructure.

Run:ai’s Sam Heywood discusses the integration with OpenShift AI for operational seamlessness.

“With Red Hat in particular, really strong opportunities to partner because the Run:ai solution we run on top of Kubernetes and OpenShift Kubernetes is widely adopted within the enterprise,” said Sam Heywood (pictured), vice president of product marketing at Run:ai Labs USA Inc. “So we leverage that. And then if you think about the development and the MLOps and all those types of things, OpenShift AI, we just announced a new collaboration with Red Hat on that.”

Heywood spoke with theCUBE Research principal analyst Rob Strechay at Red Hat Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the transformative potential of AI when supported by robust, integrated infrastructure solutions such as Run:ai’s offering. (* Disclosure below.)

Enhancing AI resource management through Run:ai and OpenShift Integration

Known for its expertise in AI infrastructure and graphical processing unit orchestration, Run:ai has deepened its partnership with Red Hat, particularly by integrating with OpenShift AI. The synergy between Run:ai’s GPU orchestration and OpenShift as a Kubernetes orchestration platform aims to provide seamless and efficient enterprise AI solutions, leveraging both companies’ strengths, according to Heywood.

“When you start talking about AI within the enterprise, at the end of the day, the products and the technology need to deliver the promised capabilities,” he said. “But what I’m seeing is enterprises also looking for deep expertise. Sure, you could go buy Run:ai — sure, you could go OpenShift, but bringing the two teams together and providing the opportunity for joint solutioning around the customer problem is a big value add.”

The partnership also addresses the sustainability concerns of AI resource management and infrastructure. By utilizing fractional GPUs, Run:ai enables more efficient use of resources, reducing over-provisioning and ensuring that data scientists and researchers have the necessary tools without unnecessary excess. This approach drives cost savings and accelerates critical AI initiatives, ensuring that infrastructure use aligns with business priorities, Heywood added.

“What we’re there to do is ensure that [companies] have proper support for the critical initiatives and that they’re confident that the way that infrastructure is being used maps back to their highest priorities,” he concluded.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Red Hat Summit: 

(* Disclosure: TheCUBE is a paid media partner for Red Hat Summit. Neither Red Hat Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE