>> live from Las Vegas. It's the queue covering Del Technologies. World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners. >> Welcome back to Del Technologies, World twenty nineteen here in Las Vegas. I'm Stew Minutemen with my co host, Dave Volonte, talking multi cloud talking about Del Technologies and all the pieces of the environment. And we're gonna drill in some to some of the storage environment. Happy to welcome back to the program. Ah, Sudhir Vossen, Who's the senior vice president and CEO of the storage division of Delhi? Emcee, Sit here. Thanks so much for joining us. >> Thanks. Thanks for having me, Stew. >> All right, So, as I said, day one lot of the vision Digital transformation multi cloud with such an Adele up on stage. Got a little bit about today. Got back into the products, everything, you know, such a broad portfolio, everything from the latter tattooed, you know, business devices through Of course, many updates on the storage world Been digging in with the number your team gives little flavor as Teo, You know what you've been working on? You know, I know. As a CEO, you can't have a favorite family but in the family. But some of the things you and the team were really proud of to unveil >> Absolutely thanks. It's been a big day as well, and I would say a big year for us. So we, uh, we've shown incredible growth in our business in the last four quarters, taking share every four for every one of those four quarters. Just a phenomenal year. A lot of that has to do with just the strength of the portfolio. Have been investing a lot in innovation in the portfolio. So, uh, I think the biggest one today that I'm really proud of is the unity launch. Think it's, uh, it's a long time coming. We've been working on it for quite a while. The the amount of performance that is going to deliver while also delivering incredible storage efficiency data reduction. That's a huge, a huge boost. But what way haven't spent a whole lot of time talking about from a technology point of view as a Ziggy. What's cool about unity? X TV that you may not have heard a lot about is that it actually is using machine >> learning inside. So last year we lost the power Max that had machine learning inside for making all these real time decisions were taking that across the family and unity >> x t uses. Was she learning in order to actually do deliver that data reduction that we just talked about? The five to one data reduction. And what's why that school is Because, you know, we've had products that do data reduction with brute force where they use a lot of memory. You can't do that in a mid range part because that kicks you out of the cost profile. So we use machine learning, tio take advantage of a little amount of memory, but they still not compromise on the data reduction. >> Yeah, actually, I had to cover they should day talking about power, Max. We made a big deal about what was happening internally as well as what does that mean for the customers and the decisions that they don't have to make you know, in our industry, we've talked about intelligence and, you know, automation in storage for decades. So yeah, and then the mid range. What does that mean? What? What will be different from customers for as they roll out thie X t product line. So >> I think it's simplicity. It's just he's a fuse. We talk about zero touch in this case, this this fewer knobs and dials. You actually don't have to do a lot of tuning at all out of the box. It'LL will serve the majority of the use cases and the requirements. You still have the option if you want to go in. If you're sort of the black, no type and you want to do, uh, customize it to your own needs. You could do that. But that sort of this journey we're on is way. Call this the autonomous or self driving story, so a lot of people are talking about it. We're actually doing it across the portfolio, and it's actually coupled with two parts are coupled with another part. There's intelligence in Unity, Eckstine and Power Max. But there's also intelligence and cloud I. Q, which is our global Blake brain in the Cloud way, saw that on stage today as well, where it's doing long term analytics deeper, learning across longer time rises to help you manage the system without really much effort. >> So couple follow ups, if I may, on the on the data reduction front. Sounds like that's a new innovation. You guys develop come from scratch. Yeah. Um, you bringing it across the portfolio, or is it sort of obviously unity extra? Today it is. The technology apply to other potentially >> absolutely does. And in fact, that's Ah, that's something we're doing across the board from last year to this year. You you've seen with become one storage team, and there's a lot of technology views going on now inside the inside the portfolio. Things that we're doing in unstructured, for example, are we're looking at applying it into other parts of the portfolio. Data reduction is obviously one of the key ones. It's it's the first example that people think off, so we're definitely looking at that. But I'LL also say is from a technology point of view, we're changing the way software is built. We're not building it as monolithic within micro code anymore. It's containerized assets that we can embed in different products >> and then, in terms of the autonomous storage piece, you know, go roll back five, ten years ago, cheering, you know you had and you had a lot of knobs to turn and and that was always featured as an advantage because people wanted to play with it. What you're talking about today is a Zen environment that's much more complex and talk about Maur. What autonomous storages is it? Hands off on great >> questions. So we have this, this internal Carter almost of most. Joke, we call it. You know, we're talking my self driving cars. Surely we can build a self driving storage >> system. Why now, Right? It's it's It's kind of a shame that we're not doing that, but I would say it's four steps just like you have four levels of autonomy and self driving cars. If you follow that level five, I think, is the is the ultimate polio zero fully autonomous way. We'LL never get there, but similarly in storage, I break it up into four parts. One is it's got to be application aware you're not dealing with lungs and file systems and raid groups anymore you're dealing with. This is my application. That's how the human or the user interacts with it. That's easy. Relatively easy. Second element >> really took fifty years. Okay, good >> second, second element is is sort of self awareness are actually actually before. That is policy based. So if you're driving a car, you're not telling the car which which route you want to take. You want to say, I want to take the fastest route or I want to take the scenic route. That's it. And the car needs to figure out what that is. So that's policy based. I want to optimize for Leighton. See performance level. Third element is self awareness, which is story. System needs to know where it's operating in its comfort zone is that close to the edge is going to drive off the cliff. Is it gonna exit the lane to use the car analogies, right? He's You know how far away it is from the car ahead. That's also that's the stuff that we're now releasing with Bara Max and what we're doing. Immunity. That's where we using learning to figure out how close to the operating edge system itself. It's once you have that, then you can start optimizing self healing. >> That's a level four, and that self awareness. So you've got you've got decades of data. Were you able to leverage that data? Or is that is that not a cz much you. So you have >> absolutely the case. Okay, that's that's the key differentiator. Actually, thanks for bringing it up because there's a lot of washing going on. Right is everybody says that about you, but the eyes, one thing you can't just deliver develop over way have used all of the decades of dial home data we've been working on with she learning technologies for the last five years. I would say, at least so were those models are being trained with the dial home data and cloud, like you is doing that on a daily basis. Now, >> why now in two thousand nineteen? Severe is that we at the point where this has become reality is a compute power. Is that the amount of data? Just better algorithms. It's Do you >> think you nailed it? Those two things, it's It's first and foremost compute power. But also I think, uh, algorithms they they're they're much more sophisticated now. And they were well understood what algorithms to use for what types of problems. I think there was initial thirty years ago. There was like, uber intelligence. That was a very ambitious goal, I would say, even today, that's not reality. while we're succeeding is we're applying it to very focused problems, just like in the rest of the industry. Were playing through focus problems that we can't solve and then broadening our effort >> had to be clear. This is this is meta data. It's not customer data utilizing obviously across the portfolio. >> No way. We're looking at things like how much CPU it's using. How much memories? Using what? How's the Leighton Sea varying over time, how far it is away, this from its service level. Things like >> you're still just another advantage of being old. Yeah, so you talked >> about that's metadata. But what one of things we talk about is when you talk about digital transformation, it's customers become data driven, right? So wave covered this year, this the tenth year we've been at this show. In the early days it was storage and oh, my gosh, my growth of data and I can't take care of it. Big data was the bit flip of turned that from a challenge to I should be able to turn that into an opportunity city. And the next wave of a I is I should be able to monetize that run my business and the data is one of the most valuable things we have bring us inside. You know how that shift in thinking in data is impacting storage architectures and how you work with customers. >> That's awesome. Great questions. O Data Capital is the big thing around. You've heard that today as well. Wear definitely sort of growing. Going beyond thinking of ourselves as a storage division to a data division. And I'm locking the data capital. I'd say there's several elements wonders building the best storage fore fore data applications, especially I and M L. So I think our unstructured products clearly are leading the charge of this. We've got the machine learning solution with Isil on. It's a perfect fit for that kind of application that's here and now already using a GPU Technologies in conjunction with our scale, our architectures critical. But going beyond we're looking at doesn't make sense for some of these data crunching applications to be closer to the storage layer, you know, thinking meet similar to what hyper converse is done for general computer. Is that a thing that would that would really unlock the data capital? We think that's a lot of potentials. So >> and I'm glad you brought that up because you know, when the storage geeks, you know, talk about envy me, envy me over fabric and storage class memory. Explain how that fits into what you were talking about, and not just the next, you know, major wave of, you know, a tool inside the infrastructure >> train. So I think so. Storage. Envy me. Envy me over fabric was part one off a two part story, as is your You know that that allowed us to get that super Lolita C high speed connection from application to storage with the data. But the data devices themselves were still very flash is great prepared TV, but they're talking single microsecond type of sub microsecond applications that need that kind of leniency. And that's where storage last memory comes in. Right? So we're finally getting to that point where the storage devices are in operating in that ten microsecond range, which will start to really get us to back if we can get those things go located close by unlocks a lot of things. And the beauty of envy me over fabric is that it can give you the sense of being closed by without actually physically being close by. So you could still be disaggregated, and that opens up a whole lot of architectural options >> can fall. Question on storage class memory The skeptics would say. It's just way too expensive and you're not going to get the volume of flash that you get with these. Uh, what do you What do you think? >> That's what they said about Flash dude in there, >> last one in tow. Consumer devices, not you're on this scale. Bring the price down. >> Maybe maybe before iPhones. They said that, but iPhone was the catalyst. Eyes. They're a consumer analog for storage, club consumer >> and long. I think that's fair, but I think there will be volume to drive it down. However, I will say it's a fair point. I think that with actual magic lies and combining superfast, perhaps expensive storage last memory with cheaper flash storage, and so you almost have a hybrid solution again. So the old hybrid becomes you hybrids back in such >> fashion, even with solid state, >> the storage pyramid lives Exactly way. >> Think that's going to be the killer combination? >> All right, so sit here. Can't let you go without. Give us a little bit of a look, for we talked about where we are. Talk about some of the journeys that were there. So it's our tenth year here at the show. Come back for your eleven, you know, How do you foresee the industry maturing and moving forward? >> I think for your eleven, the big things we're going to see is Cloud Two things I would say one is CL Cloud and the other is software to find. I think those are the two that are going to be big news next year. >> We're seeing some sneak previews of that this year with the cloud announcements we made you'LL see a lot more of that next year from from the storage side, both in be part of the Delta Clock Technologies Cloud Platform but also cloud enabling our storage arrays across all the all public clouds. And then the second part is software defined. I think that's really the next way. So, as I said, we are a long journey internally. We've already been on it where were transforming our internal storage assets to be more software centric, and you'LL start to see some of that All right, well, >> sit here. Really appreciate you helping us geek out on, dig into, You know, a lot of the pieces here at Del Technology World twenty nineteen. Thank you. Alright. For David Dante, I'm stew minimum, and this is the end of two days of water wall coverage. We're coming back for one more. And as always, check out the cute dot net for all the videos. Silicon angle dot com For all the articles. Wiki bond dot com For all of the in depth analysis Hit up, Dave myself, John furry in the whole team were available on social media channels and, as always, thank you for watching the cue.