AI infrastructure strategy is expanding beyond compute and storage specifications as artificial intelligence reshapes who manages enterprise applications and data. Infrastructure teams are increasingly being asked to support virtual machines, Kubernetes, graphics processing units and AI workloads together.
That expansion is reshaping responsibilities traditionally divided among infrastructure, data science and DevOps teams. Platform decisions increasingly require a shared view of how workloads will be built, operated and scaled, according to Cody Hosterman (pictured), senior director of product management at Everpure Inc.
“The conversations I’ve been having in our meeting room and at our booth and in the hallways have not once been about VMs. It’s actually been talking about the datasets and the applications that are consuming them with people who are traditionally infrastructure administrators,” he said. “So the conversation has fully changed.”
Hosterman spoke with theCUBE Research’s Christophe Bertrand and co-host Alison Kosik at VMware Explore, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed hybrid infrastructure, Everpure’s partnership with Broadcom Inc. and the importance of connecting AI investments to business objectives. (* Disclosure below.)
AI infrastructure strategy starts with business outcomes
Everpure is aligning its data platform with VMware Cloud Foundation 9.1 to support virtual machines, Kubernetes and AI workloads. Customers are also using public clouds to test configurations before right-sizing infrastructure in their data centers, reflecting the broader need for data-ready AI infrastructure, according to Hosterman.
“We’re definitely seeing customers leveraging the resources in [Amazon Web Services Inc.] or [Microsoft Azure] to kind of figure some things out. But the motion that we’ve been seeing is, ‘All right, now we’ve got a good idea. We know how we’re going to build these out and how we’re going to consume them,’” Hosterman said. “We can right-size this with best-of-breed infrastructure in the data center.”
Rapid market change can tempt companies to acquire servers and graphics processing units before defining their intended use. The costliest error is treating AI enablement as the objective, Hosterman explained.
“The outcome shouldn’t be, ‘We should be ready to serve the world’s largest AI infrastructure,’” he said. “It should be, ‘No, this is where we want to get our business to. A tool to get us there is AI,’ and then working backwards from that plan.”
Here’s the complete video interview, part of theCUBE’s coverage of VMware Explore:
(* Disclosure: TheCUBE is a paid media partner for the VMware Explore event. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)
