Nutanix Enterprise AI: Scalable AI Solution for multicloud workloads

As the urge to support artificial intelligence and machine learning workloads at an enterprise scale skyrockets, having an AI-ready platform is vital.

Nutanix has addressed this need with its Enterprise AI solution, which simplifies the deployment of large language models by leveraging its hyperconverged infrastructure. This scalable solution meets the demanding needs of AI/ML workloads and provides the flexibility to operate in private, public and hybrid cloud environments, according to Luke Congdon (pictured), senior director of product management at Nutanix Inc.

Nutanix’s Luke Congdon talks to theCUBE about how Nutanix Enterprise AI is redefining businesses in the AI age.

“We just released what we’re calling Nutanix Enterprise AI, and it’s our new product line to say we are an AI company,” Congdon said. “We are offering generative AI on-premises now with inference endpoints, with security, with cost control, with simplicity, which is what we’ve always been trying to do.”

Congdon spoke with theCUBE Research’s Savannah Peterson and Rob Strechay at KubeCon + CloudNativeCon NA, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the key role that Nutanix Enterprise AI plays in simplifying infrastructure management. (* Disclosure below.)

How partnerships fit into the Nutanix Enterprise AI picture

To drive AI-driven innovations, partnerships play a vital role, as critical issues, such as comprehensive data management and analytics capabilities, must be effectively addressed. As a result, Nutanix teams up with various players, such as Hugging Face Inc. and Nvidia Corp, to make solutions such as Nutanix Enterprise AI a reality, according to Congdon. 

“Partnerships, I think, are the way to do it,” he said. “Even on the NAI announcement, we partnered with Hugging Face for access to their hub because they’ve got all the models in the world. What I love about it is that these are kind of turbocharged engines and, for the most part, they’re free. They’re Apache II or Meta-licensed. We’ve also partnered with Nvidia, and we’ve been doing that for years both on the GPU side for virtual desktop, as well for their AI for Enterprise suite and their NIMs products.”

To streamline IT operations by supporting Kubernetes deployments and multicloud environments, Nutanix made a strategic acquisition of D2iQ Inc. This move was meant to simplify containerized application development, making it easier to manage complex and distributed workloads across different infrastructures, Congdon pointed out. 

“We’d like to make sure that you’re going to get production-level Kubernetes with security, with load balancing, with ingress, with everything else that you need, because Kubernetes is really great, but it’s one key important orchestrator piece,” he said. “You need so much more. What’s really unique about them coming to Nutanix is they got what has traditionally really been hard for Kubernetes … stateful storage across objects, files, volumes, anything that you need.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of KubeCon + CloudNativeCon NA: 

(* Disclosure: Nutanix Inc. sponsored this segment of theCUBE. Neither Nutanix nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE