 From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. Hi everybody, this is Dave Vellante, and welcome to this CUBE Conversation. I'm here with Dave Fafel, who is the chief architect at WEI. And we're going to chat about intelligence storage and specifically HPE, intelligence storage. Dave, good to see you again. Thanks for coming on. Thanks for having me. All right, so HPE uses this, you know, everybody has these cool marketing terms, intelligence storage, intelligence storage platform. It sounds pretty cool. What's it all about? Well, HPE has done a really good job at developing their storage platform to leverage AI and machine learning and deliver some useful analytics and information to their customers. And here's what they're doing. They are, from a machine learning perspective, taking their entire install base of storage devices, gathering that information, not personal information such as, you know, what the data is that sits on the storage, but more of the performance. We understand it's this type of application, it's this type of data. And here's how it performs across all these different environments. And they're sharing that with their customers to say, if you have this type of data on your storage, here's the optimal performance settings to be able to get the most out of your storage and the best performance. Additionally, they're using AI machine learning, that same idea to give customers heads up on when they might run into trouble, either from a break fix perspective. For instance, you've got some drives that may be failing. You've got a controller that's acting up. You've got a connectivity issue someplace. All the way to, you don't have a performance issue yet, but trends we see with your data types may deliver some part performance under these conditions, be aware of that. So they're giving insight to their customers by leveraging everything that they're learning across their entire install base, which is pretty neat. And they're taking that same capability that they have on storage and applying that to their compute environments as well. So think about, think about this from an HP perspective, they're able to give their customers through their info site application the ability to see and discover performance issues and constraints well before it ever happens to avoid customers from having to find that out the hard way. So there's a really good example of the application of AI. We talk about AI like it's some mysterious thing. It's really machine intelligence and machine learning. And I think it's a practical application because it's relatively narrow. You're talking about predictive analytics around infrastructure and being able to, you know, identify potential hotspots, taking the humans out of the equation to do some of that stuff that is really not value add for the business, freeing up time to do some other things. Is that the right way to think about it? That's exactly the right way to think about it. You're absolutely right. With this type of intelligence, you don't need to have IT administrators digging through logs to try to figure out where performance problems are after they've already occurred. Instead, you're getting this information before it ever occurs and you're able to head it off at the pass. So I liked the Nimble acquisition by HPE. The one thing you like about Nimble, you think Nimble, you think InfoSight. Correct. One of the other things I like about the acquisition is if I understand it correctly, and I think you pointed this out, they drove that technology across its entire portfolio. And you think about three-par HPE made the three-par acquisition, gosh, 10 years ago now, 2010. And that was kind of the gold standard for simplicity, for high-end storage. They had great metadata reports and now, Nimble fast-forward has a sort of modern version of that with AI and predictive analytics. The fact that HPE has taken that and pushed it across the portfolio. And I think even into compute, into servers as well, is it's an impressive use of a technology. Sometimes companies buy tech and it just sits there for years and they don't do anything with it. So your thoughts on that? Yeah, no, I think you're absolutely right. HPE did it right. They leverage this technology to add additional value to their compute platforms such as their Proline Brands and their Synergy Platform. So it's a very smart thing to do and it's a very good use of that technology from the Nimble acquisition. And you can see where HPE is heading with predictive analytics across their entire portfolio. So it's all about that insight to information and be able to head off problems before they occur. Yet at the same time, how do we optimize or automatically optimize our environments based on all of this information which organizations never had access to before. So, WEI, you guys are a trusted partner of your customers. You work with large customers, they look to you. You're not trying to jam a specific solution down their throat. Yeah, you think of a financial advisor as, oh, here's an insurance policy. Well, if they're getting a vague on that insurance policy, you go, oh, wait a minute, you guys have to be agnostic. So my question to you as a sort of a trusted advisor is, what's the sweet spot for HPE storage? Where is its, you know, best thing? That's a trick question, right? No. It really depends on the platform. So, you know, when we talk about Nimble and we talk about InfoSight, you know, there is a market segment that that fits well in. As well as, you know, the same could be said for 3PAR, for example. And now with their new release, the Primera Storage Platform, you know, I think you'll see a lot more adoption. But one of the things that all of those platforms have in common is the ability to connect into data center automation and provisioning strategies. And so, that's where, from our perspective, from WEI's perspective, the value that we're adding around customers is, how do we architect that IT service delivery model that's cloud-like in nature? And what are the platforms that allow us to easily enable those provisioning models? So, irrespective of the vendor name on the bezel, what are you looking for in a storage platform? Well, what we're, again, what we're looking for is the ability to do a couple things. One, to easily integrate into a provisioning model, right? And to automation, right? Are they, you know, are there investments made by the OEM into the API calls that we can now leverage to connect to either public services or to on-prem compute resources and to software-defined networking and other areas that we need to connect to when we're kind of creating those mile-to-mile-three automation, automations that enable those provisioning models. You know, the other thing we're looking for, of course, is availability, reliability, you know, and performance. So, you know, selecting the right storage platform based on the customer need, based on cost are the things that, you know, that go into that. But you're absolutely right. We're designing architectures at WAI based on customer's business needs, right? Based on how well it fits into their environment and how well that they can maintain those, you know, those cloud-like IT service delivery models. And once we've understood what those business requirements are, what the IT requirements are, what their relationships with different services might be and their preferences for different types of automations, then we work with them to introduce the right storage platform. And HP has a nice portfolio of storage platforms that fit into many, many different hybrid cloud and hybrid IT environments. All right, good stuff. Dave, thanks for taking us through sort of your perspectives on HPE, specifically in storage in general. Appreciate it. Thanks. All right, thank you for watching. We'll see you next time. This is Dave Vellante with theCUBE. Thank you.