Transcript
data centers. Storage has really come into focus and has become the cool thing again, if you will, right? I don't know if it was ever cool, but it's cool now. The tech industry continues to innovate to keep up with the explosion of data. One of the latest developments is a partnership between Nutanix and Pure Storage, which combines virtualization with FlashArray technologies. It's removing complexity. It's removing cost. All those things that I, as an IT leader, really care about. The background of this story begins with the rise of hyper-converged infrastructure. Matt Kimball of More Insights and Strategy, in an interview at the 2025.next conference, talked about the early days of HCI. Nutanix found a huge kind of opening in the market with HCI, and it went after, you know, there was a segment of enterprise IT that really thrived in HCI. There were some limitations when it comes to HCI. When it comes to HCI, you have to scale everything kind of linearly, right? You need more storage, well, you have to add more compute, more network. And so over time, that can add complexity in and add cost in, but still a very kind of simple deployment model. But that ability to scale both elements, compute and storage independently, mattered a lot. If I'm deploying a really large database environment, data warehouse, I'm going to want to add a bunch of storage, but I don't need all that compute, right? With Pure, you have two companies that are, you know, in their own right, the innovators and kind of the scrappy underdogs in a space that have done very well for themselves. And there's a lot of enthusiasm among their customer bases. So I think you're going to see a lot of enthusiasm in the respective customer bases for this joint solution. And it addresses that scale issue that maybe you were limited by somewhat in what was the old days of HCI. When you look at what Pure and Nutanix announced, it's not just, hey, we're going to take the Nutanix hypervisor, AHV, and we're going to connect it to storage arrays, flash arrays from Pure, and we're going to call it a solution. It was, you know, a year's worth of co-engineering to drive optimization. It was decisions like, hey, I'm going to use NVMe over TCP instead of fiber because it gives me better performance, because it doesn't tie me into some standard that's not open, right? Because it's better for my customers and because this is where the cloud is going. So it's decisions like that. It's the ability. It's Pure and taking flash array and exposing it or exploiting it up through Prism. So I can see that environment and manage that environment from a single interface. It's things like this that drive that deeper partnership that deliver real value. And that's why you get that enthusiastic response from customers. When you look at a typical enterprise organization, you know, there are about four or five different primary storage vendors. Some have as many as 13, right? So you will see within an organization Pure and Nutanix and sometimes Nutanix and Pure. This to me is that kind of that tight coupling that delivers a solution. So as you talk about kind of data center modernization, which is a big deal, right? It is the first step in going toward a kind of that agentic AI outcome. When you look at these efforts going on, this work that gets done between a Pure and a Nutanix, again, it's not just kind of like, and it's not just we co-engineered, it's delivering to an outcome. It's delivering to an outcome for IT and it's removing risk. It's removing complexity. It's removing cost. It's one of those things that I, as an IT leader, really care about. Storage has become so critical over the course of the last couple of years as data analytics and as AI started to kind of become more and more part of the conversation within IT. Start to realize the importance of data and of course, data is driven by or is driven by your storage back end, right? So storage has really come into focus and has become the cool thing again, if you will, right? I don't know if it was ever cool, but it's cool now. It became the cool thing again for IT organizations and became a critical part of that AI equation. How fast can I take that data from a platform and feed my processing engines, which is typically a GPU or some accelerator, to kind of get that model trained or to tune that model and then to provide kind of value on the other side of the equation. It's also critical for CloudNative, right? The ability for an organization to leverage a pool of resources very easily, kind of from a software-defined perspective, is absolutely critical and that is all sitting typically on a storage back end. Well, thank you. Thank you. Thank you.
