HPE Discover in Las Vegas was a chance to shine a spotlight on the importance of networking in the global AI landscape. Today’s enterprises know that staying ahead in AI is just as much about infrastructure as it is about the ability to scale it, and HPE’s premier annual event is a reinforcement of that reality.
The Vultr team was excited to see our partnership with HPE featured prominently throughout the event, including in HPE CEO Antonio Neri’s keynote address and in a roundtable with Vultr CEO J.J. Kardwell.
This week, Vultr and HPE announced our collaboration with NVIDIA for large-scale data center deployments designed for enterprise-scale AI inference workloads. The deployments will utilize NVIDIA GB300 NVL72 by HPE and NVIDIA Spectrum-X networking, combining HPE’s AI factory capabilities, NVIDIA accelerated computing, and Vultr’s global composable cloud platform to accelerate innovation while maintaining cost-efficiency.
This collaboration was a focus of Neri’s keynote.
“What Vultr is building at the hyperscale points to a truth that every architect knows: that there is always one core element of your infrastructure that touches everything,” Neri said. “With AI, that core element is the network. The performance of your entire architecture depends on it.”
The address showcased a video in which Kardwell explained why our commitment to HPE is such an integral aspect of our global, enterprise-scale AI infrastructure. (See the full video here.)
Vultr’s open architecture and open stacks are central to how we power some of the world’s most demanding enterprise AI workloads, from model training to inference and production at scale. But teams cannot leverage that backbone effectively if they cannot scale it efficiently. That’s where HPE comes in.
“Success depends on how fast data moves,” Kardwell says in the video. “With HPE networking, Vultr can scale AI infrastructure globally, in real-time, without bottlenecks.”
He expanded on this in a roundtable with theCUBE after Neri’s keynote. Kardwell talked about how the maturation of the AI market has made optimal networking even more important than it already was. As organizations move from pilots to operationalized, production workloads delivering tangible business impact, infrastructure needs to specifically meet enterprise needs.
These include security, trust, compliance, and privacy – but also execution, a faster pathway to operationalization, and increased flexibility to quickly integrate new emerging technologies. That’s especially true for the largest buyers making up more and more of the AI market.
“The impact of networking in these large cluster deployments is so massive,” Kardwell said. “The impact of HPE networking is, frankly, the biggest it's ever been because of the architecture needs of those systems … It’s a partnership. We’re truly committed to their business success.”
AI teams have moved beyond experimentation. They’re focused on real business value, which means they need to trust that their solution can deliver quickly, reliably, without bottlenecks. Vultr and HPE, each with a decades-long history serving large businesses with advanced enterprise-scale technology, are designed for this environment.
And it’s not just about meeting modern AI demands. “It’s open, automated, and built to adapt,” Kardwell said in the video from Neri’s keynote, “not just for tomorrow’s applications — but for the ones we haven’t imagined yet.”
Learn more about how Vultr is getting ahead of the curve with HPE and NVIDIA.