>> Announcer: Live from Las Vegas, it's theCUBE covering Magento Imagine 2019, brought to you by Adobe. >> Welcome to the theCUBE, I'm Lisa Martin at The Wynn, in Las Vegas for Magento Imagine 2019. This is a three day event. You can hear a lot of exciting folks networking behind me, talking tech, talking e-commerce innovation and we're pleased to welcome fresh off the keynote stage a couple of guests from HP. We've got Gillian Campbell, the Head of Omni-channel Strategy and Operations. Gillian, thank you for joining us. >> Thank you for asking us. >> Our pleasure and Herriot Stobo, Director of Omni-channel Innovation and Solutions, also from HP. Welcome. >> Thank you very much. >> So Gillian fresh off the keynote stage, enjoyed your presentation this morning. >> Gillian: Thank you. >> Everybody I think in the world knows HP. Those of us consumers going, you know what actually, that reminds me, I need a new printer. >> We can help you. >> Thank you, excellent. Whether I'm shopping online or in a store. So you gave this really interesting keynote this morning talking about what HP is doing, starting at Apache. You really transform this shopping experience. Talk to us a little bit about HP, as I think you've mentioned it as a $50 billion start up and from a digital experience perspective, what you needed to enable. >> Yeah, so as I said, HP have been around for 80 years and in 2015, we became our own entity, HP Inc., and really started looking at how do we enable digital to be pervasive through everything that we do. Our internal processes are reached to customers and identified a great opportunity to really take leading edge and our digital commerce capabilities and we already had some early proof points and APG so we launched a global initiative and we're now on that journey to enable that best in class experience through the digital platforms. >> So Herriot talk to us about, you're based in Singapore. >> Yes. >> What were some of the market dynamics that really made it obvious that this is where we want to start building out this omni-channel strategy starting in Apache? Is it, you know whether, Gillian you mentioned it before. We started retail spaces, some being expensive. Is it more mobile experience and expectations on consumer's part? >> I think we've got a mix of different starting points across Asia. We've got some mega cities like Hong Kong and Singapore rising, Tokyo. And then we've got you know emerging markets across South-East Asia. We don't necessarily have any single market place that controls the entire market as we might see in other regions and so we've had a lot of runway to go and experiment and try new things. We also have an ecosystem of branded retail in Asia. Not in all markets, predominantly in India but also in some markets in South-East Asia that allow us to really blend the experience across both offline and online and to give customers choice at the end of the day. Let them decide how they want to shop and interact with our brand. So we have been running Magento 1 since we first launched our online store businesses in Indonesia and Thailand about six years ago and then we moved into China, replatformed, lexi-platform onto Magento 1 and then that was really the foundation of what we decided to go and build upon to become a global program. so we already had some proof points under our belt with Magento so. >> And what were some of those early wins that really started to make this really obvious that this omni-channel experience, the ability to give customers choice? Whether they want to start the process online, finish it in store, vice verse, or at least have the opportunity to have a choice? What were some of those early wins and business outcomes that you started to see? >> I think even just from because we're all, customers are people. Whether you're a corporate customer, a small business, or a consumer, we're all people and we all know that we shop that way. So essentially the storyline on that back to HP was we have to enable experiences that we would want to experience as well and it was quite a shift for a tech company who were really all about the products to be thinking about, well, how do we really enable that end to end experience? And as Herriot said, the runway was open. We already had some proof points. I was new in the job so I was like all listening to, you know, what the team were telling me. We have a great opportunity here and took that formered as a new concept for the company. We got funding approval and you know the rest is the history and the journey that we're on. So I think it was just taking a different perspective and a different approach and working with a team who already had the, built some of that credibility and others proof points with the earlier deployments and I think we kind of took a risk at the time when we started the engagement with Magento. They weren't in that leadership quadrant and we took a risk to say, let's partner with an energizing company and do something a little bit different and we're still here working towards it so I think that for me was the breakthrough, was just having the tenacity to say, we're gonna drive this path forward. It may not be how we would have done things in the past, but we're a different company now. and we had much more thinner air cover to be able to do that. >> Little bit more agility and flexibility. >> Yeah, absolutely. So you guys, you talked about, Gillian about all the buyers. We are the consumers and we have this expectation, growing expectation that I want to be able to get any and transact anything that I want to buy, whether I'm a procuring person for a company and I'm traveling but I need to approve expenses or I'm a salesperson maybe sitting next to a medium-small business customer. I need to have the option at least to have this store front. What are the things that you guys launched in Apache, leverage be the power of Magento Commerce was click to collect. So tell me a little bit about from maybe an e-commerce cultural perspective, what is it that makes people want to have the ability to start online and actually complete the transaction in a physical location? >> Essentially I was in the Advisory Board yesterday and one of the other customers of Magento said, "Until we can invent a way to touch and feel online, "there's always gonna be a need to have, "outlets where you can go touch and feel." and I think with the click and collect, some of our products are, you know, high-end PCs and gaming devices and printers that is hard to get a good appreciation of what it looks and feels like online. So if you're gonna be spending you know, a significant money you may want to go in and be able to see the colors, feel the finish. You know some of our newer products with the leather portfolios is not something you can truly appreciate without touching it. So I think we have to enable again those customers who do want to experience, feel the weight, you know feel the finish, see the color scheme 'cause its usually important, again not for all customers. Some customers are quite happy to spend thousands of dollars on an online purchase without seeing it and then making sure they have a good facility to be able to, well if they wanted to, to return if they got the normal the product. >> As we look though at like we talked about, this consumerization of everything where we have this expectation and the numbers, I think you even mentioned it maybe in your keynote, Gillian, the numbers of, or somebody did this morning, like upwards of half of all transactions are starting on mobile so we got to start there. What are some of the things that you guys have seen in region in terms of mobile conversions? >> So there's still a massive gap between desktop and mobile conversions, first of all. I mean we're not anywhere near parity between the two. But obviously we're seeing a huge volume of traffic coming in as well and it's shifting that way, so you would expect it to drop as result. I think with Magento what we've seen over the, you know, past few deployments that we've been running and that were over 8% improven. But the desktop conversions are far higher. I mean in terms of improvement and actual conversion so we've still got a long way to go. There and that's a naturative process, that's a journey that probably never ends in terms of ongoing optimization and experimentation. So yeah a lot happening there. I think just on the click and collect topic as well that you were asking about people wanting to start their journey online and then come into bricks and mortar. We're seeing a huge uptake on it just by experimenting, by piloting. Over 26% of our consumer notebooks in India that we've put onto this program were being collected in store and this is in environments which are inherently chaotic on the streets. You don't want to go out there but actually I'm passing that way anyway so it's just easier for me to pick it up on the way home and probably quicker 'cause I can collect in two hours. So it's just giving people customer choice, no additional incentive and it seems to take. So now we're expanding out regionally. >> So you said there's, this morning, Gillian, in your keynote eight markets covered, mostly Apache, but also in Latin America. >> We just started in Latin America, again, the development process is not just as simple as we're switching on. So we've been doing a lot of work for this past six months with Latin America. The team there, they're super excited to get launched. There's some differences there, we've talked about the regional variation around fulfillment models that we have to adapt towards but the intent is to get Latin America deployed, leveraging some of the layer lengths from what we've done in Asia specific and then starting to move around into more the near region and then ultimately back into the US and Canada. >> So as you look forward and of course you've mentioned we're on this journey right, what are some of the key learnings that you're going to apply? You mentioned this morning, something that was very intriguing and that was, respect the integrity of the Magento platform. Talk about that in context of some of the other learnings that you'd recommend for colleagues and similar or other industries to be able to achieve what you have on a global scale. >> I think from the outset, there was this kind of like baggage of deployments of capabilities not just in commerce but deployment of capabilities across HP that we had not respected the integrity of the platform. We had adjusted the code and developed on the code to make it HP specific and with the new HP Inc. company one of the guided principles was no, when we buy the leverage software applications respect it for what it is and adjust business processes and adjust integration rather than adjust the core so that we can get the advantage of the longer term opportunity without creating such like. So it was really just a foundational, you know, let's not go in here with a mindset that we know better than the core. The core is there for a reason and then build around that and ensure the integration and I think you know with Herriot's leadership, we've been able to you know, just keep that firm is why we can be successful and be successful longer term as well. So that all the, and one of the things we talked about yesterday also is the excellent capabilities that are coming with Adobe and the integration that we talked about the recommendation of Adobe Sensei and integrate that with Magento Core. If you don't keep to the respect the integrity, those upgrades and capabilities become really hard to take benefit of so we're really excited about, you know, again, sticking with the core and enabling and growing with the core with Magento and Adobe. >> I would just build on it, I mean I think its never gonna be easy running a global commerce platform. Single instance, multiple countries, you know, 27 markets to get started with. Who knows where we're gonna end. Its always gonna be a challenge so we have to keep it as simple as possible. These upgrades are fast and furious and that's great and we all gets lots of benefit but if we start going down our own path, we've lost it. We've lost the benefit. >> And that's one of the things too that Jason Wolfsteen said this morning was that the word Magento was gonna be enabling businesses to achieve without getting in their way and it kind of sounds Herriot, like you're saying the same thing. That we've gotta be able to respect the technologies that we're building so we don't get in our own way and we keep it simple as we wanna expand globally. Ultimately at the end of the day, you're creating these personalized experiences with consumers and that personalization is so important because it's more and more not only are we transacting or wanting to on mobile but we want our brands like HP to know us. We want you to know our brand value, you know our average order value so that we can become part of the experience but also ideally get rewarded for being loyal. >> Yeah. >> Yeah, I mean, I mean just coming to mobile again but you know, 2.3 delivers the native PWA capabilities which we're super excited to get started with. You know we've got so many used cases for this straight away, right out the box but you know we've got to do it gradually, do it the right way. I think we're also aware that we're not gonna be able to run with PWA in all markets straight away 'cause not all markets are ready for it quite frankly. User behavior- >> Is that a cultural thing? >> It's purely cultural. Maybe technical and just technical ecosystems as well. Places like China in particular, where, you know, customers use app stores but they use app stores from every single phone manufacturer right there. That's where the customer is. We can't just move away from that so we need to keep some of those legacy approaches for a little while and then yeah test in other regions and then take the learnings when we're ready to adopt it. >> Exciting so here we are at, this is the first Magento Imagine since the Adobe acquisition. Gillian, let's wrap things up with you. What are your, you mentioned you were part of the Customer Advisory Board yesterday, just some of your perspectives on this years' event now that Magento is powering the Adobe commerce cloud. >> I actually attended the Adobe Summit a few weeks ago here also in Vegas and started to see the thread of commerce coming into that conference and then seeing the Adobe, the experience, coming into Magento and I just think it's a perfect combination of opportunities especially for a company like HP where we were linked in to connect, you know, marketing and sales and support across the customer journey and the capabilities with Adobe and some of the marketing stack, and then the commerce stack, and there was support bringing that together is a super exciting opportunity for us. You know the partnership that we have with both Adobe and Magento again as one as I really, they were just starting what the next journey was gonna look like. >> We feel that about so many things, we're just starting, but Gillian, Herriot, it's been a pleasure to have you on theCUBE for Magento Imagine 2019. Thank you both for your time. >> Thank you, thank you. >> Our pleasure. I'm Lisa Martin and you're watching theCUBE live from The Wynn Las Vegas at Magento Imagine 2019. Thanks for watching. (light music)

>> Announcer: Live from Las Vegas, it's The Cube, covering HPE Discover, 2017 brought to you by Hewlett Packard Enterprise. >> Okay, welcome back everyone. We're here live in Las Vegas for our exclusive three day coverage from The Cube Silicon Angle media's flagship program. We go out to events, talk to the smartest people we can find CEOs, entrepreneurs, R&D lab managers and of course we're here at HPE Discover 2017 our next two guests, Andrew Wheeler, the Fellow, VP, Deputy Director, Hewlett Packard Labs and Kirk Bresniker, Fellow and VP, Chief Architect of HP Labs, was on yesterday. Welcome back, welcome to The Cube. Hewlett Packard Labs well known you guys doing great research, Meg Whitman really staying with a focused message and one of the comments she mentioned at our press analyst meeting yesterday was focusing on the lab. So I want ask you where is that range in the labs? In terms of what you guys, when does something go outside the lines if you will? >> Andrew: Yeah good question. So, if you think about Hewlett Packard Labs and really our charter role within the company we're really kind of tasked for looking at things that will disrupt our current business or looking for kind of those new opportunities. So for us we have something we call an innovation horizon and you know it's like any other portfolio that you have where you've got maybe things that are more kind of near term, maybe you know one to three years out, things that are easily kind of transferred or the timing is right. And then we have kind of another bucket that says well maybe it's more of a three to five year kind of in that advanced development category where it needs a little more incubation but you know it needs a little more time. And then you know we reserve probably you know a smaller pocket that's for more kind of pure research. Things that are further out, higher risk. It's a bigger bet but you know we do want to have kind of a complete portfolio of those, and you know over time throughout our history you know we've got really success stories in all of those. So it's always finding kind of that right blend. But you know there's clearly a focus around the advanced development piece now that we've had a lot of things come from that research point and really one of the... >> John: You're looking for breakthroughs. I mean that's what you're... Some-- >> Andrew: Clearly. >> Internal improvement, simplify IT all that good stuff, you guys still have your eyes on some breakthroughs. >> That's right. Breakthroughs, how do we differentiate what we're doing so but yeah clearly, clearly looking for those breakthrough opportunities. >> John: And one of the things that's come up really big in this show is the security and chip thing was pretty hot, very hot, and actually wiki bonds public, true public cloud report that they put out sizing up on prem the cloud mark. >> Dave: True private cloud. >> True private cloud I'm sorry. And that's not including hybrids of $265 billion tam but the notable thing that I want to get your thoughts on is the point they pushed was over 10 years $150 billion is going to shift out of IT on premise into other differentiated services. >> Andrew: Out of labor. >> Out of labor. So this, and I asked them what that means, as he said that means it's going to shift to vendor R&D meaning the suppliers have to do more work. So that the customers don't have to do the R&D. Which we see a lot in cloud where there's a lot of R&D going on. That's your job. So you guys are HP Labs, what's happening in that R&D area that's going to off load that labor so they can move to some other high yield tasks. >> Sure. Take first. >> John: Go ahead take a stab at it. >> When we've been looking at some of the concepts we had in the memory driven computing research and advanced development programs the machine program, you know one of the things that was the kick off for me back in 2003 we looked at what we had in the unix market, we had advanced virtualization technologies, we had great management of resources technologies, we had memory fabric technologies. But they're all kind of proprietary. But Silicon is thinking and back then we were saying how does risk unix compete with industry standards service? This new methodology, new wave, exciting changing cost structures. And for us it was that it was a chance to explore those ideas and understand how they would affect our maintaining the kind of rich set of customer experiences, mission criticality, security, all of these elements. And it's kind of funny that we're sort of just coming back to the future again and we're saying okay we have this move we want to see these things happen on the cloud and we're seeing those same technologies, the composable infrastructure we have in synergy and looking forward to see the research we've done on the machine advanced development program and how will that intersect hardware composability, converged infrastructure so that you can actually have that shift, those technologies coming in taking on more of that burden to allow you freedom of choice, so you can make sure that you end up with that right mix. The right part on a full public cloud, the right mix on a full private cloud, the right mixing on that intelligent edge. But still having the ability to have all of those great software development methodologies that agile methodology, the only thing the kids know how to do out of school is open source and agile now. So you want to make sure that you can embrace that and make sure regardless of where the right spot is for a particular application in your entire enterprise portfolio that you have this common set of experiences and tools. And some of the research and development we're doing will enable us to drive that into that existing, conventional, enterprise market as well as this intelligent edge. Making a continuum, a continuum from the core to the intelligent edge. And something that modern computer science graduates will find completely comfortable. >> One attracting them is going to be the key, I think the edge is kind of intoxicating if you think about all the possibilities that are out there in terms of what you know just from a business model disruption and also technology. I mean wearables are edge, brain implants in the future will be edge, you know the singularities here as Ray Kersewile would say... >> Yeah. >> I mean but, this is the truth. This is what's happened. This is real right now. >> Oh absolutely. You know we think of all that data and right now we're just scratching the surface. I remember it was 1994 the first time I fired up a web server inside of my development team. So I could begin thinning out design information on prototype products inside of HP, and it was a novelty. People would say "What is that thing "you just sent me an email, W W whatever?" And suddenly we went from, like almost overnight, from a novelty to a business necessity, to then it transformed the way that we created the applications for the... >> John: A lot of people don't know this but since you brought it up this historical trivia, HP Labs, Hewlett Packard Labs had scientists who actually invented the web with Tim Berners-Lee, I think HTML founder was an HP Labs scientist. Pretty notable trivia. A lot of people don't know that so congratulations. >> And so I look at just what you're saying there and we see this new edge thing is it's going to be similarly transformative. Now today it's a little gimmicky perhaps it's sort of scratching the surface. It's taking security and it can be problematic at times but that will transform, because there is so much possibility for economic transformation. Right now almost all that data on the edge is thrown away. If you, the first person who understands okay I'm going to get 1% more of that data and turn it into real time intelligence, real time action... That will unmake industries and it will remake new industries. >> John: Andrew this the applied research vision, you got to apply R&D to the problem... >> Andrew: Correct. >> That's what he's getting at but you got to also think differently. You got to bring in talent. The young guns. How are you guys bringing in the young guns? What's the, what's the honeypot? >> Well I think you know for us it's, the sell for us, obviously is just the tradition of Hewlett Packard to begin with right? You know we have recognition on that level even it's not just Hewlett Packard Labs as well it's you know just R&D in general right? Kind of it you know the DNA being an engineering company so... But it's you know I think it is creating kind of these opportunities and whether it's internship programs you know just the various things that we're doing whether it's enterprise related, high performance computing... I think this edge opportunity is a really interesting one as a bridge because if you think about all the things that we hear about in enterprise in terms of "Oh you know I need this deep analytics "capability," or you know even a lot of the in memories things that we're talking about, real time response, driving information, right? All of that needs to happen at the edge as well for various opportunities so it's got a lot of the young graduates excited. We host you know hundreds of interns every year and it's real exciting to see kind of the ideas they come in with and you know they're all excited to work in this space. >> Dave: So Kirk you have your machine button, three, of course you got the logo. And then the machine... >> I got the labs logo, I got the machine logo. >> So when I first entered you talked about in the early 1980s. When I first got in the business I remembered Gene Emdall. "The best IO is no IO." (laughter) >> Yeah that's right. >> We're here again with this sort of memory semantics, centric computing. So in terms of the three that Andrew laid out the three types of sort of projects you guys pursue... Where does the machine fit? IS it sort of in all three? Or maybe you could talk about that a little bit. >> Kirk: I think it is, so we see those technologies that over the last three years we have brought so much new and it was, the critical thing about this is I think it's also sort of the prototyping of the overall approach our leaning in approach here... >> Andrew: That's right. >> It wasn't just researchers. Right? Those 500 people who made that 160 terabyte monster machine possible weren't just from labs. It was engineering teams from across Hewlett Packard Enterprise. It was our supply chain team. It was our services team telling us how these things fit together for real. Now we've had incredible technology experiences, incredible technologist experiences, and what we're seeing is that we have intercepts on conventional platforms where there's the photonics, the persistent memories. Those will make our existing DCIG and SDCG products better almost immediately. But then we also have now these whole cloth applications and as we take all of our learnings, drive them into open source software, drive them into the genesys consortium and we'll see you know probably 18, 24 months from now some of those first optimized silicon designs pop out of that ecosystem then we'll be right there to assemble those again, into conventional systems as well as more expansive, exo-scale computing, intelligent edge with large persistent memories and application specific processing as that next generation of gateways, I think we can see these intercept points at every category Andrew talked about. >> Andrew: And another good point there that kind of magnifies the model we were talking about, if we were sitting here five years ago, we would talking about things like photonics and non-volatile memory as being those big R projects. Those higher risk, longer term things, that right? As those mature, we make more progress innovation happens, right? It gets pulled into that shorter time frame that becomes advanced development. >> Dave: And Meg has talked about that... >> Yeah. >> Wanting to get more productivity out of the labs. And she's also pointed out you guys have spent more on R&D in the last several years. But even as we talked about the other day you want to see a little more D and keep the R going. So my question is, when you get to that point, of being able to support DCIG... Where do you, is it a hand off? Are you guys intimately involved? When you're making decisions about okay so member stir for example, okay this is great, that's still in the R phase then you bring it in. But now you got to commercialize this and you got 3D nan coming out and okay let's use that, that fits into our framework. So how much do you guys get involved in that handoff? You know the commercialization of this stuff? >> We get very involved. So it's at the point where when we think have something that hey we think you know maybe this could get into a product or let's see if there's good intercept here. We work jointly at that point. It's lab engineers, it's the product managers out of the group, engineers out of the business group, they essentially work collectively then on getting it to that next step. So it's kind of just one big R&D effort at that point. >> Dave: And so specifically as it relates to the machine, where do you see in the next in the near term, let's call near term next three years, or five years even, what do you see that looking like? Is it this combination of memory width capacitors or flash extensions? What does that look like in terms of commercial terms that we can expect? >> Kirk: So I really think the palette is pretty broad here. That I can see these going into existing rack and tower products to allow them to have memory that's composable down to the individual module level. To be able to take that facility to have just the right resources applied at just the right time with that API that we have in one view. Extend down to composing the hardware itself. I think we look at those edge line systems and want to have just the right kind of analytic capability, large persistent memories at that edge so we can handle those zeta bytes and zeta bytes of data in full fidelity analyzed at the edge sending back that intelligence to the core but also taking action at the edge in a timeframe that matters. I also see it coming out and being the basis of our exoscale high performance computing. You know when you want to have a exoscale system that has all of the combined capacity of the top 500 systems today but 1/20th of their power that is going to take rather novel technologies and everything we've been working on is exactly what's feeding that research and soon to be advanced development and then soon to be production in supply chain. >> Dave: Great. >> John: So the question I have is obviously we saw some really awesome Gen 10 stuff here at this show you guys are seeing that obviously you're on stage talking about a lot of the cool R&D, but really the reality is that's multiple years in the works some of this root of trust silicon technology that's pretty, getting the show buzzed up everyone's psyched about it. Dreamworks Animation's talking about how inorganic opportunities is helping their business and they got the security with the root of trust NIST certified and compliant. Pretty impressive. What's next? What else are you working on because this is where the R&D is on your shoulders for that next level of innovation. Where, what do you guys see that? Because security is a huge deal. That's that great example of how you guys innovated. Cause that'll stop the vector of a tax in the service area of IOT if you can get the servers to lock down and you have firmware that's secure, makes a lot of sense. That's probably the tip of the iceberg. What else is happening with security? >> Kirk: So when we think about security and our efforts on advanced development research around the machine what you're seeing here with the proliance is making the machines more secure. The inherent platform more secure. But the other thing I would point to you is the application we're running on the prototype. Large scale graph inference. And this is security because you have a platform like the machine. Able to digest hundreds and hundreds of tera bytes worth of log data to look for that fingerprint, that subtle clue that you have a system that has been compromised. And these are not blatant let's just blast everything out to some dot dot x x x sub domain, this is an advanced persistent thread by a very capable adversary who is very subtle in their reach out from a system that has been compromised to that command and control server. The signs are there if you can look at the data holistically. If you can look at that DNS log, graph of billions of entries everyday, constantly changing, if you can look at that as a graph in totality in a timeframe that matters then that's an empowering thing for a cyber defense team and I think that's one of the interesting things that we're adding to this discussion. Not only protect, detect and recover, but giving offensive weapons to our cyber defense team so they can hunt, they can hunt for those events for system threats. >> John: One of the things, Andrew I'll get your thoughts and reaction to this because Ill make an observation and you guys can comment and tell me I'm all wet, fell off the deep end or what not. Last year HP had great marketing around the machine. I love that Star Trek ad. It was beautiful and it was just... A machine is very, a great marketing technique. I mean use the machine... So a lot of people set expectations on the machine You saw articles being written maybe these people didn't understand it. Little bit pulled back, almost dampered down a little bit in terms of the marketing of the machine, other than the bin. Is that because you don't yet know what it's going to look like? Or there's so many broader possibilities where you're trying to set expectations? Cause the machine certainly has a lot of range and it's almost as if I could read your minds you don't want to post the position too early on what it could do. And that's my observation. Why the pullback? I mean certainly as a marketer I'd be all over that. >> Andrew: Yeah, I think part of it has been intentional just on how the ecosystem, we need the ecosystem developed kind of around this at the same time. Meaning, there are a lot of kind of moving parts to it whether it's around the open source community and kind of getting their head wrapped around what is this new architecture look like. We've got things like you know the Jin Zee Consortium where we're pouring a lot of our understanding and knowledge into that. And so we need a lot of partners, we know we're in a day and an age where look there's no single one company that's going to do every piece and part themselves. So part of it is kind of enough to get out there, to get the buzz, get the excitement to get other people then on board and now we have been heads down especially this last six months of... >> John: Jamming hard on it. >> Getting it all together. You know you think about what we showed first essentially first booted the thing in November and now you know we've got it running at this scale, that's really been the focus. But we needed a lot of that early engagement, interaction to get a lot of the other, members of the ecosystem kind of on board and starting to contribute. And really that's where we're at today. >> John: It's almost you want it let it take its own course organically because you mentioned just on the cyber surveillance opportunity around the crunching, you kind of don't know yet what the killer app is right? >> And that's the great thing of where we're at today now that we have kind of the prototype running at scale like this, it is allowing us to move beyond, look we've had the simulators to work with, we've had kind of emulation vehicles now you've got the real thing to run actual workloads on. You know we had the announcement around DZ and E as kind of an early early example, but it really now will allow us to do some refinement that allows us to get to those product concepts. >> Dave: I want to just ask the closing question. So I've had this screen here, it's like the theater, and I've been seeing these great things coming up and one was "Moore's Law is dead." >> Oh that was my session this morning. >> Another one was block chain. And unfortunately I couldn't hear it but I could see the tease. So when you guys come to work in the morning what's kind of the driving set of assumptions for you? Is it just the technology is limitless and we're going to go figure it out or are there things that sort of frame your raison d'etre? That drive your activities and thinking? And what are the fundamental assumptions that you guys use to drive your actions? >> Kirk: So what's been driving me for the last couple years is this exponential growth of information that we create as a species. That seems to have no upper bounding function that tamps it down. At the same time, the timeframe we want to get from information, from raw information to insight that we can take action on seems to be shrinking from days, weeks, minutes... Now it's down to micro seconds. If I want to have an intelligent power grid, intelligent 3G communication, I have to have micro seconds. So if you look at those two things and at the same time we just have to be the lucky few who are sitting in these seats right when Moore's Law is slowing down and will eventually flatten out. And so all the skills that we've had over the last 28 years of my career you look at those technologies and you say "Those aren't the ones that are going "to take us forward." This is an opportunity for us to really look and examine every piece of this, because if was something we could of just can't we just dot dot dot do one thing? We would do it, right? We can't just do one thing. We have to be more holistic if we're going to create the next 20, 30, 40 years of innovation. And that's really what I'm looking at. How do we get back exponential scaling on supply to meet this unending exponential demand? >> Dave: So technically I would imagine, that's a very hard thing to balance because the former says that we're going to have more data than we've ever seen. The latter says we've got to act on it fast which is a great trend for memory but the economics are going to be such a challenge to meet, to balance that. >> Kirk: We have to be able to afford the energy, and we have to be able to afford the material cost, and we have to be able to afford the business processes that do all these things. So yeah, you need breakthroughs. And that's really what we've been doing. And I think that's why we're so fortunate at Hewlett Packard Enterprise to have the labs team but also that world class engineering and that world class supply chain and a services team that can get us introduced to every interesting customer around the world who has those challenging problems and can give us that partnership and that insight to get those kind of breakthroughs. >> Dave: And I wonder if there will be a tipping point, if the tipping point will be, and I'm sure you've thought about this, a change in the application development model that drives so much value and so much productivity that it offsets some of the potential cost issues of changing the development paradigm. >> And I think you're seeing hints of that. Now we saw this when we went from systems of record, OLTP systems, to systems of engagement, mobile systems, and suddenly new ways to develop it. I think now the interesting thing is we move over to systems of action and we're moving from programmatic to training. And this is this interesting thing if you have those data bytes of data you can't have a pair of human eyeballs in front of that, you have to have a machine learning algorithm. That's the only thing that's voracious enough to consume this data in a timely enough fashion to get us answers, but you can't program it. We saw those old approaches in old school A.I., old school autonomous vehicle programs, they go about 10 feet, boom, and they'd flip over, right? Now you know they're on our streets and they are functioning. They're a little bit raw right now but that improvement cycle is fantastic because they're training, they're not programming. >> Great opportunity to your point about Moore's Law but also all this new functionality that has yet been defined, is right on the doorstep. Andrew, Kirk thank you so much for sharing. >> Andrew: Thank you >> Great insight, love Hewlett Packard Labs love the R&D conversation. Gets us a chance to go play in the wild and dream about the future you guys are out creating it congratulations and thanks for spending the time on The Cube, appreciate it. >> Thanks. >> The Cube coverage will continue here live at Las Vegas for HPE Discover 2017, Hewlett Packard Enterprises annual event. We'll be right back with more, stay with us. (bright music)

>> Announcer: Live from San Francisco, it's theCube, covering Spark Summit 2017, brought to you by Databricks. >> Welcome back to theCube at Spark Summit 2017. I don't know about you, George, I'm having a great time learning from all of our attendees. >> We've been absorbing now for almost two days. >> Yeah, well, and we're about to absorb a little bit more here, too, because the next guest, I looking forward to, I saw his name on the schedule, all right, that's the guy who talks about herding cats, it's John Cavanaugh, Master Architect from HP. John, welcome to the show. >> Great, thanks for being here. >> Well, I did see, I don't know if it's about cats in the Internet, but either cats or self-driving cars, one of the two in analogies. But talk to us about your session. Why did you call it Herding Cats, and is that related to maybe the organization at HP? >> Yeah, there's a lot of organizational dynamics as part of our migration at Spark. HP is a very distributed organization, and it has had a lot of distributed autonomy, so, you know, trying to get centralized activity is often a little challenging. You guys have often heard, you know, I am from the government, I'm here to help. That's often the kind of shields-up response you will get from folks, so we got a lot of dynamics in terms of trying to bring these distributed organizations on board to a new common platform, and a allay many of the fears that they had with making any kind of a change. >> So, are you centered at a specific division? >> So, yes, I'm the print platforms and future technology group. You know, there's two large business segments with HP. There's our personal systems group that produces everything from phones to business PCs to high-end gaming. But I'm in the printing group, and while many people are very familiar with your standard desktop printer, you know, the printers we sell really vary from a very small product we call Sprocket, it fits in your hand, battery-operated, to literally a web press that's bigger than your house and prints at hundreds of feet per minute. So, it's a very wide product line, and it has a lot of data collection. >> David: Do you have 3D printing as well? >> We do have 3D printing as well. That's an emergent area for us. I'm not super familiar with that. I'm mostly on the 2D side, but that's a very exciting space as well. >> So tell me about what kind of projects that you're working on that do require that kind of cross-team or cross-departmental cooperation. >> So, you know, in my talk, I talked about the Wild West Era of Big Data, and that was prior to 2015, and we had a lot of groups that were standing up all kinds of different big data infrastructures. And part of this stems from the fact that we were part of HP at the time, and we could buy servers and racks of servers at cost. Storage was cheap, all these things, so they sprouted up everywhere. And, around 2015, everybody started realizing, oh my God, this is completely fragmented. How do we pull things back together? And that's when a lot of groups started trying to develop platformish types of activities, and that's where we knew we needed to go, but there was even some disagreement from different groups, how do we move forward. So, there's been a lot of good work within HP in terms of creating a virtual community, and Spark really kind of caught on pretty quickly. Many people were really tired of kind of Hadoop. There were a lot of very opinionated models in Hadoop, where Spark opens up a lot more into the data science community. So, that went really well, and we made a big push into AWS for much of our cloud activities, and we really ended up then pretty quickly with Databricks as an enterprise partner for us. >> And so, George, you've done a lot of research. I'm sure you talked to enterprise companies along the way. Is this a common issue with big enterprises? >> Well, for most big data projects they've started, the ones we hear a lot about is there's a mandate from the CIO, we need a big data strategy, and so some of those, in the past, stand up five or 10-node Hadoop cluster and run some sort of pilot and say, this is our strategy. But is sounds like you herded a lot of cats... >> We had dozens of those small Hadoop clusters all around the company. (laughter) >> So, how did you go about converting that energy, that excess energy towards something more harmonized around Databricks? >> Well, a lot of people started recognizing we had a problem, and this really wasn't going to scale, and we really needed to come up with a broader way to share things across the organization. So, the timing was really right, and a lot of people were beginning to understand that. And, you know, we said for us, probably about five different kind of key decisions we ended up making. And part of the whole strategy was to empower the businesses. As I have mentioned, we are a very distributed organization, so, you can't really dictate the businesses. The businesses really need the owners' success. And one of the decisions that was made, it might be kind of controversial for many CIOs, is that we've made a big push on cloud-hosted and business-owned, not IT-owned. And one of the real big reasons for that is we were no longer viewing data and big data as kind of a business-intelligence activity or a standardized reporting activity. We really knew that, to be successful moving forward, is needed to be built into our products and services, and those products and services are managed by the businesses. So, it can't be something that would be tossed off to an IT organization. >> So that the IT organization, then, evolved into being more of an innovative entity versus a reactive or supportive entity for all those different distributing groups. >> Well, in our regard, we've ended up with AWS as part of our activity, and, really, much of our big data activities are driven by the businesses. The connections we have with IT are more related to CRM and product data master sheets and selling in channels and all that information. >> But if you take a bunch of business-led projects and then try and centralize some aspect of them, wouldn't IT typically become the sort of shared infrastructure architecture advisor for that, and then the businesses now have a harmonized platform on which they can build shared data sets? >> Actually, in our case, that's what we did. We had a lot of our businesses that already had significant services hosted in AWS. And those were very much part of the high-data generators. So, it became a very natural evolution to continue with some of our AWS relationships and continue on to Databricks. So, as an organization today, we have three kind of main buckets for our Databricks, but, you know, any business, they can get their accounts. We try and encourage everything to get into a data link, and that's three, and Parquet formats, one of the decisions that was adapted. And then, from there, people can begin to move. You know, you can get notebooks, you can share notebooks, you can look at those things. You know, the beauty of Databricks and AWS is instant on. If I want to play around with something with a half a dozen nodes, it's great. If I need a thousand for a workload, boom, I've got it! I know, kind of others, then, with this cost and the value returned, there's really no need for permissions or coordination with other entities, and that's kind of what we wanted the businesses to have that autonomy to drive their business success. >> But, does there not to be some central value added in the way of, say, data curation through a catalog or something like that? >> Yes, so, this is not necessarily a model where all the businesses are doing all kinds of crazy things. One of the things that we shepherded by one of our CTOs and the other functions, we ended up creating a virtual community within HP. This kind of started off with a lot of "tribal elders" or "tribal leaders." With this virtual community, today we get together every two weeks, and we have presentations and discussions on all things from data science into machine learning, and that's where a lot of this activity around how do we get better at sharing. And this is fostered, kind of splinters off for additional activity. So we have one on data telemetry within our organization. We're trying to standardize more data formats and schemas for those so we can have more broader sharing. So, these things have been occurring more organically as part of a developer enablement kind of moving up rather than more of kind of dictates moving down. >> That's interesting. Potentially, really important, when you say, you're trying to standardize some of the telemetry, what are you instrumenting. Is it just all the infrastructure or is it some of the products that HP makes? >> It's definitely the products and the software. You know, like I said, we manage a huge spectrum of print products, and my apologies if I'm focusing on it, but that is what I know the best. You know, we've actually been doing telemetry and analysis since the late 90s. You know, we wanted to understand use of supplies and usage so we could do our own forecasting, and that's really, really grown over the years. You know, now, we have parts of our services organization management services, where they're offering big data analytics as part of the package, and we provide information about predictive failure of parts. And that's going to be really valuable for some of our business partners that allows them. We have all kinds fancy algorithms that we work on. The customers have specific routes that they go for servicing, and we may be able to tell them, hey, in a certain time period, we think these devices in your field so you can coordinate your route to hit those on an efficient route rather than having to make a single truck roll for one repair, and do that before a customer experiences a problem. So, it's been kind of a great example of different ways that big data can impact the business. >> You know, I think Ali mentioned in the keynote this morning about the example of a customer getting a notification that their ink's going to run out, and the chance that you get to touch that customer and get them to respond and buy, you could make millions of dollar difference, right? Let's talk about some of the business outcomes and the impact that some of your workers have done, and what it means, really, to the business. >> Right now, we're trying to migrate a lot of legacy stuff, and you know, that's kind of boring. (laughs) It's just a lot of work, but there are things that need to happen. But there's really the power of the big data platform has been really great with Databricks. I know, John Landry, one of our CTOs, he's in the personal systems group. He had a great example on some problems they had with batteries and laptops, and, you know, they have a whole bunch of analytics. They've been monitoring batteries, and they found a collection of batteries that experienced very early failure rates. I happen to be able to narrow it down to specific lots from a specific supplier, and they were able to reach out to customers to get those batteries replaced before they died. >> So, a mini-recall instead of a massive PR failure. (laughs) >> You know, it was really focused on, you know, customers didn't even know they were going to have a problem with these batteries, that they were going to die early. You know, you got to them ahead of time, told them we knew this was going to be a problem and try to help them. I mean, what a great experience for a customer. (laughs) That's just great. >> So, once you had this telemetry, and it sounds like a bunch of shared repositories, not one intergalactic one. What were some of the other use cases like, you know, like the battery predictive failure type scenarios. >> So, you know, we have some very large gaps, or not gaps, with different categories. We have clearly consumer products. You know, you sell millions and millions of those, and we have little bit of telemetry with those. I think we want to understand failures and ink levels and some of these other things. But, on our commercial web presses, these very large devices, these are very sensitive. These things are down, they have a big problem. So, these things are generating all kinds of data. All right, we have systems on a premise with customers that are alerting them to potential failures, and there's more and more activity going on there to understand predictive failure and predictive kind of tolerance slippages. I'm not super familiar with that business, but I know some guys that they've started introducing more sensors into products, specifically so they can get more data, to understand things. You know, slight variations in tensioning and paper, you know, these things that are running hundreds of feet per minute can have a large impact. So, I think that's really where we see more and more of the value coming from is being able to return that value back to the customer, not just help us make better decisions, but to get that back to the customer. You know, we're talking about expanding more customer-facing analytics in these cases, or we'll expose to customers some of the raw data, and they can build their own dashboards. Some of these industries have traditionally been very analog, so this move to digital web process and this mountain of data is a little new for them, but HP can bring a lot to the table in terms of our experience in computing and big data to help them with their businesses. >> All right, great stuff. And we just got a minute to go before we're done. I have two questions for you, the first is an easy yes/no question. >> John: Okay. >> Is Purdue going to repeat as Big 10 champ in basketball? >> Oh, you know, I don't know. (laughs) I hope so! >> We both went to Purdue. >> I'm more focused on the Warriors winning. (laughter) >> All right, go Warriors! And, the real question is, what surprised you the most? This is your first Spark Summit. What surprised you the most about the event? >> So, you know, you see a lot of Internet-born companies, and it's amazing how many people have just gone fully native with Spark all over the place, and it's a beautiful thing to see. You know, in larger enterprises, that transition doesn't happen like that. I'm kind of jealous. (laughter) We have a lot more things slug through, but the excitement here and all the things that people are working on, you know, you can only see so many tracks. I'm going to have to spend two days when I get back, just watching the videos on all of the tracks I couldn't attend. >> All right, Internet-born companies versus the big enterprise. Good luck herding those cats, and thank you for sharing your story with us today and talking a little bit about the culture there at HP. >> John: Thank you very much. >> And thank you all for watching this segment of theCube. Stay with us, we're still covering Spark Summit 2017. This is Day Two, and we're not done yet. We'll see you in a few minutes. (theCube jingle)

>> Announcer: Live from Las Vegas, it's the CUBE! Covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. >> Hey, welcome back, everyone. We are live here in Las Vegas for SiliconANGLE Media's CUBE exclusive coverage of HPE Discover 2017. I'm John Furrier, my co-host, Dave Vellante. Our next guest is Kirk Bresniker, fellow and VP chief architect of Hewlett Packard Labs, and Natalia Vassilieva, senior research manager, Hewlett Packard Labs. Did I get that right? >> Yes! >> John: Okay, welcome to theCUBE, good to see you. >> Thank you. >> Thanks for coming on, really appreciate you guys coming on. One of the things I'm most excited about here at HPE Discover is, always like to geek out on the Hewlett Packard Labs booth, which is right behind us. If you go to the wide shot, you can see the awesome display. But there's some two things in there that I love. The Machine is in there, which I love the new branding, by the way, love that pyramid coming out of the, the phoenix rising out of the ashes. And also Memristor, really game-changing. This is underlying technology, but what's powering the business trends out there that you guys are kind of doing the R&D on is AI, and machine learning, and software's changing. What's your thoughts as you look at the labs, you look out on the landscape, and you do the R&D, what's the vision? >> One of the things what is so fascinating about the transitional period we're in. We look at the kind of technologies that we've had 'til date, and certainly spent a whole part of my career on, and yet all these technologies that we've had so far, they're all kind of getting about as good as they're going to get. You know, the Moore's Law semiconductor process steps, general-purpose operating systems, general-purpose microprocessors, they've had fantastic productivity growth, but they all have a natural life cycle, and they're all maturing. And part of The Machine research program has been, what do we think is coming next? And really, what's informing us as what we have to set as the goals are the kinds of applications that we expect. And those are data-intensive applications, not just petabytes, exabytes, but zettabytes. Tens of zettabytes, hundreds of zettabytes of data out there in all those sensors out there in the world. And when you want to analyze that data, you can't just push it back to the individual human, you need to employ machine learning algorithms to go through that data to call out and find those needles in those increasingly enormous haystacks, so that you can get that key correlation. And when you don't have to reduce and redact and summarize data, when you can operate on the data at that intelligent edge, you're going to find those correlations, and that machine learning algorithm is going to be that unbiased and unblinking eye that's going to find that key relationship that'll really have a transformational effect. >> I think that's interesting. I'd like to ask you just one follow-up question on that, because I think, you know, it reminds me back when I was in my youth, around packets, and you'd get the buffer, and the speeds, and feeds. At some point there was a wire speed capability. Hey, packets are moving, and you can do all this analysis at wire speed. What you're getting at is, data processing at the speed of, as fast as the data's coming in and out. Is that, if I get that right, is that kind of where you're going with this? Because if you have more data coming, potentially an infinite amount of data coming in, the data speed is going to be so high-velocity, how do you know what a needle looks like? >> I think that's a key, and that's why the research Natalia's been doing is so fundamental, is that we need to be able to process that incredible amount of information and be able to afford to do it. And the way that you will not be able to have it scale is if you have to take that data, compress it, reduce it, select it down because of some pre-determined decision you've made, transmit it to a centralized location, do the analysis there, then send back the action commands. Now, we need that cycle of intelligence measurement, analysis and action to be microseconds. And that means it needs to happen at the intelligent edge. I think that's where the understanding of how machine learning algorithms, that you don't program, you train, so that they can work off of this enormous amount of data, they voraciously consume the data, and produce insights. That's where machine learning will be the key. >> Natalia, tell us about your research on this area. Curious. Your thoughts. >> We started to look at existing machine learning algorithms, and whether their limiting factors today in the infrastructure which don't allow to progress the machine learning algorithms fast enough. So, one of the recent advances in AI is appearance, or revival, of those artificial neural networks. Deep learning. That's a very large hype around those types of algorithms. Every speech assistant which you get, Siri in your phone, Cortana, or whatever, Alexa by Amazon, all of them use deep learning to train speech recognition systems. If you go to Facebook and suddenly it starts you to propose to mark the faces of your friends, that the face detection, face recognition, also that was deep learning. So that's a revival of the old artificial neural networks. Today we are capable to train byte-light enough models for those types of tasks, but we want to move forward. We want to be able to process larger volumes of data, to find more complicated patterns, and to do that, we need more compute power. Again, today, the only way how you can add more compute power to that, you scale out. So there is no compute device on Earth today which is capable to do all the computation. You need to have many of them interconnect together, and they all crunch numbers for the same problem. But at some point, the communication between those nodes becomes a bottleneck. So you need to let know laboring node what you achieved, and you can't scale out anymore. Adding yet another node to the cluster won't lead up to the reduction of the training time. With The Machine, when we have added the memory during computing architecture, when all data seeds in the same shared pool of memory, and when all computing nodes have an ability to talk to that memory. We don't have that limitation anymore. So for us, we are looking forward to deploy those algorithms on that type of architecture. We envision significant speedups in the training. And it will allow us to retrain the model on the new data, which is coming. To do not do training offline anymore. >> So how does this all work? When HP split into two companies, Hewlett Packard Labs went to HPE and HP Labs went to HP Ink. So what went where, and then, first question. Then second question is, how do you decide what to work on? >> I think in terms of how we organize ourselves, obviously, things that were around printing and personal systems went to HP Ink. Things that were around analytics, enterprise, hardware and research, went to Hewlett Packard Labs. The one thing that we both found equally interesting was security, 'cause obviously, personal systems, enterprise systems, we all need systems that are increasingly secure because of the advanced, persistent threats that are constantly assaulting everything from our personal systems up through enterprise and public infrastructure. So that's how we've organized ourselves. Now in terms of what we get to work on, you know, we're in an interesting position. I came to Labs three years ago. I used to be the chief technologist for the server global business unit. I was in the world of big D, tiny R. Natalia and the research team at Labs, they were out there looking out five, 10, 15, or 20 years. Huge R, and then we would meet together occasionally. I think one of the things that's happened with our machine advanced development and research program is, I came to Labs not to become a researcher, but to facilitate that communication to bring in the engineering, the supply chain team, that technical and production prowess, our experience from our services teams, who know how things actually get deployed in the real world. And I get to set them at the bench with Natalia, with the researchers, and I get to make everyone unhappy. Hopefully in equal amounts. That the development teams realize we're going to make some progress. We will end up with fantastic progress and products, both conventional systems as well as new systems, but it will be a while. We need to get through, that's why we had to build our prototype. To say, "No, we need a construction proof of these ideas." The same time, with Natalia and the research teams, they were always looking for that next horizon, that next question. Maybe we pulled them a little bit closer, got a little answers out of them rather than the next question. So I think that's part of what we've been doing at the Labs is understanding, how do we organize ourselves? How do we work with the Hewlett Packard Enterprise Pathfinder program, to find those little startups who need that extra piece of something that we can offer as that partnering community? It's really a novel approach for us to understand how do we fill that gap, how do we still have great conventional products, how do we enable breakthrough new category products, and have it in a timeframe that matters? >> So, much tighter connection between the R and the D. And then, okay, so when Natalia wants to initiate a project, or somebody wants Natalia to initiate a project around AI, how does that work? Do you say, "Okay, submit an idea," and then it goes through some kind of peer review? And then, how does it get funded? Take us through that. >> I think I'll give my perspective, I would love to hear what you have from your side. For me, it's always been organic. The ideas that we had on The Machine, for me, my little thread, one of thousands that's been brought in to get us to this point, started about 2003, where we were getting ready for, we're midway through Blade Systems C-class. A category-defining product. A absolute home run in defining what a Blade system was going to be. And we're partway through that, and you realize you got a success on your hands. You think, "Wow, nothing gets better than this!" Then it starts to worry, what if nothing gets better than this? And you start thinking about that next set of things. Now, I had some insights of my own, but when you're a technologist and you have an insight, that's a great feeling for a little while, and then it's a little bit of a lonely feeling. No one else understands this but me, and is it always going to be that way? And then you have to find that business opportunity. So that's where talking with our field teams, talking with our customers, coming to events like Discover, where you see business opportunities, and you realize, my ingenuity and this business opportunity are a match. Now, the third piece of that is someone who can say, a business leader, who can say, "You know what?" "Your ingenuity and that opportunity can meet "in a finite time with finite resources." "Let's do it." And really, that's what Meg and leadership team did with us on The Machine. >> Kirk, I want to shift gears and talk about the Memristor, because I think that's a showcase that everyone's talking about. Actually, The Machine has been talked about for many years now, but Memristor changes the game. It kind of goes back to old-school analog, right? We're talking about, you know, login, end-login kind of performance, that we've never seen before. So it's a completely different take on memory, and this kind of brings up your vision and the team's vision of memory-driven computing. Which, some are saying can scale machine learning. 'Cause now you have data response times in microseconds, as you said, and provisioning containers in microseconds is actually really amazing. So, the question is, what is memory-driven computing? What does that mean? And what are the challenges in deep learning today? >> I'll do the machine learning-- >> I will do deep learning. >> You'll do the machine learning. So, when I think of memory-driven computing, it's the realization that we need a new set of technologies, and it's not just one thing. Can't we just do, dot-dot-dot, we would've done that one thing. This is more taking a holistic approach, looking at all the technologies that we need to pull together. Now, memories are fascinating, and our Memristor is one example of a new class of memory. But they also-- >> John: It's doing it differently, too, it's not like-- >> It's changing the physics. You want to change the economics of information technology? You change the physics you're using. So here, we're changing physics. And whether it's our work on the Memristor with Western Digital and the resistive RAM program, whether it's the phase-change memories, whether it's the spin-torque memories, they're all applying new physics. What they all share, though, is the characteristic that they can continue to scale. They can scale in the layers inside of a die. The die is inside of a package. The package is inside of a module, and then when we add photonics, a transformational information communications technology, now we're scaling from the package, to the enclosure, to the rack, cross the aisle, and then across the data center. All that memory accessible as memory. So that's the first piece. Large, persistent memories. The second piece is the fabric, the way we interconnect them so that we can have great computational, great memory, great communication devices available on industry open standards, that's the Gen-Z Consortium. The last piece is software. New software as well as adapting existing productive programming techniques, and enabling people to be very productive immediately. >> Before Natalia gets into her piece, I just want to ask a question, because this is interesting to me because, sorry to get geeky here, but, this is really cool because you're going analog with signaling. So, going back to the old concepts of signaling theory. You mentioned neural networks. It's almost a hand-in-glove situation with neural networks. Here, you have the next question, which is, connect the dots to machine learning and neural networks. This seems to be an interesting technology game-changer. Is that right? I mean, am I getting this right? What's this mean? >> I'll just add one piece, and then hear Natalia, who's the expert on the machine learning. For me, it's bringing that right ensemble of components together. Memory technologies, communication technologies, and, as you say, novel computational technologies. 'Cause transistors are not going to get smaller for very much longer. We have to think of something more clever to do than just stamp out another copy of a standard architecture. >> Yes, you asked about changes of deep learning. We look at the landscape of deep learning today, and the set of tasks which are solved today by those problems. We see that although there is a variety of tasks solved, most of them are from the same area. So we can analyze images very efficiently, we can analyze video, though it's all visual data, we can also do speech processing. There are few examples in other domains, with other data types, but they're much fewer. It's much less knowledge how to, which models to train for those applications. The thing that one of the challenges for deep learning is to expand the variety of applications which it can be used. And it's known that artificial neural networks are very well applicable to the data where there are many hidden patterns underneath. And there are multi-dimensional data, like data from sensors. But we still need to learn what's the right topology of neural networks to do that. What's the right algorithm to train that. So we need to broaden the scope of applications which can take advantage of deep learning. Another aspect is, which I mentioned before, the computational power of today's devices. If you think about the well-known analogy of artificial neural network in our brain, the size of the model which we train today, the artificial neural networks, they are much, much, much smaller than the analogous thing in our brain. Many orders of magnitude. It was shown that if you increase the size of the model, you can get better accuracy for some tasks. You can process a larger variety of data. But in order to train those large models, you need more data and you need more compute power. Today, we don't have enough compute power. Actually did some computation, though in order to train a model which is comparable in size with our human brain, you will need to train it in a reasonable time. You will need a compute device which is capable to perform 10 to the power of 26 floating-point operations per second. We are far, far-- >> John: Can you repeat that again? >> 10 to the power of 26. We are far, far below that point now. >> All right, so here's the question for you guys. There's all this deep learning source code out there. It's open bar for open source right now. All this goodness is pouring in. Google's donating code, you guys are donating code. It used to be like, you had to build your code from scratch. Borrow here and there, and share in open source. Now it's a tsunami of greatness, so I'm just going to build my own deep learning. How do customers do that? It's too hard. >> You are right on the point to the next challenge of deep learning, which I believe is out there. Because we have so many efforts to speed up the infrastructure, we have so many open source libraries. So now the question is, okay, I have my application at hand. What should I choose? What is the right compute node to the deep learning? Everybody use GPUs, but is it true for all models? How many GPUs do I need? What is the optimal number of nodes in the cluster? And we have a research effort towards to answer those questions as well. >> And a breathalyzer for all the drunk coders out there, open bar. I mean, a lot of young kids are coming in. This is a great opportunity for everyone. And in all seriousness, we need algorithms for the algorithms. >> And I think that's where it's so fascinating. We think of some classes of things, like recognizing written handwriting, recognizing voice, but when we want to apply machine learning and algorithms to the volume of sensor data, so that every manufactured item, and not only every item we manufacture, but every factory that can be fully instrumented with machine learning understanding how it can be optimized. And then, what of the business processes that are feeding that factory? And then, what are the overall economic factors that are feeding that business? And instrumenting and having this learning, this unblinking, unbiased eye examining to find those hidden correlations, those hidden connections, that could yield a very much more efficient system at every level of human enterprise. >> And the data's more diverse now than ever. I'm sorry to interrupt, but in Voice you mentioned you saw Siri, you see Alexa, you see Voice as one dataset. Data diversity's massive, so more needles, more types of needles than ever before. >> In that example that you gave, you need a domain expert. And there's plenty of those, but you also need a big brain to build the model, and train the model, and iterate. And there aren't that many of those. Is the state of machine learning and AI going to get to the point where that problem will solve itself, or do we just need to train more big brains? >> Actually, one of the advantages of deep learning that you don't need that much effort from the domain experts anymore, from the step which was called future engineering, like, what do you do with your data before you throw machine learning algorithm into that? So they're, pretty thing, cool thing about deep learning, artificial neural network, that you can throw almost raw data into that. And there are some examples out there, that the people without any knowledge in medicine won the competition of the drug recognition by applying deep neural networks to that, without knowing all the details about their connection between proteins, like that. Not domain experts, but they still were able to win that competition. Just because algorithm that good. >> Kirk, I want to ask you a final question before we break in the segment because, having spent nine years of my career at HP in the '80s and '90s, it's been well-known that there's been great research at HP. The R&D has been spectacular. Not too much R, I mean, too much D, not enough applied, you mention you're bringing that to market faster, so, the question is, what should customers know about Hewlett Packard Labs today? Your mission, obviously the memory-centric is the key thing. You got The Machine, you got the Memristor, you got a novel way of looking at things. What's the story that you'd like to share? Take a minute, close out the segment and share Hewlett Packard Labs' mission, and what expect to see from you guys in terms of your research, your development, your applications. What are you guys bringing out of the kitchen? What's cooking in the oven? >> I think for us, it is, we've been given an opportunity, an opportunity to take all of those ideas that we have been ruminating on for five, 10, maybe even 15 years. All those things that you thought, this is really something. And we've been given the opportunity to build a practical working example. We just turned on the prototype with more memory, more computation addressable simultaneously than anyone's ever assembled before. And so I think that's a real vote of confidence from our leadership team, that they said, "Now, the ideas you guys have, "this is going to change the way that the world works, "and we want to see you given every opportunity "to make that real, and to make it effective." And I think everything that Hewlett Packard Enterprise has done to focus the company on being that fantastic infrastructure, provider and partner is just enabling us to get this innovation, and making it meaningful. I've been designing printed circuit boards for 28 years, now, and I must admit, it's not as, you know, it is intellectually stimulating on one level, but then when you actually meet someone who's changing the face of Alzheimer's research, or changing the way that we produce energy as a society, and has an opportunity to really create a more sustainable world, then you say, "That's really worth it." That's why I get up, come to Labs every day, work with fantastic researchers like Natalia, work with great customers, great partners, and our whole supply chain, the whole team coming together. It's just spectacular. >> Well, congratulations, thanks for sharing the insight on theCUBE. Natalia, thank you very much for coming on. Great stuff going on, looking forward to keeping the progress and checking in with you guys. Always good to see what's going on in the Lab. That's the headroom, that's the future. That's the bridge to the future. Thanks for coming in theCUBE. Of course, more CUBE coverage here at HP Discover, with the keynotes coming up. Meg Whitman on stage with Antonio Neri. Back with more live coverage after this short break. Stay with us. (energetic techno music)

>> Live from Boston, Massachusetts, this is the CUBE, covering Spark Summit East 2017 brought to you by databricks. Now, here are your hosts Dave Valante and George Gilbert. >> Welcome back to Boston everyone. It's snowing like crazy outside, it's a cold mid-winter day here in Boston but we're here with the CUBE, the world-wide leader in tech coverage. We are live covering Spark Summit. This is wall to wall coverage, this is our second day here. John Landry with us, he's the distinguished technologist for HP's personal systems data science group within Hewlett Packard. John, welcome. >> Thank you very much for having me here. >> So I was saying, I was joking, we do a lot of shows with HPE, it's nice to have HP back on the CUBE, it's been awhile. But I want to start there. The company split up just over a year ago and it's seemingly been successful for both sides but you were describing to us that you've gone through an IT transformation of sorts within HP. Can you describe that? >> In the past, we were basically a data warehousing type of approach with reporting and what have you coming out of data warehouses, using Vertica, but recently, we made an investment into more of a programming platform for analytics and so where transformation to the cloud is about that where we're basically instead of investing into our own data centers because really, with the split, our data centers went with Hewlett Packard Enterprise, is that we're building our software platform in the cloud and that software platform includes analytics and in this case, we're building big data on top of Spark and so that transformation is huge for us, but it's also enabled us to move a lot faster, the velocity of our business and to be able to match up to that better. Like I said, it's mainly around the software development really more than anything else. >> Describe your role in a little bit more detail inside of HP. >> My role is I'm the leader in our big data investments and so I've been leading teams internally and also collaborating across HP with our print group and what we've done is we've managed to put together a strategy around our cloud-based solution to that. One of the things that was important was we had a common platform because when you put a program platform in place, if it's not common, then we can't collaborate. Our investment could be fractured, we could have a lot of side little efforts going on and what have you so my role is to pry the leadership in the direction for that and also one of the reasons I'm here today is to get involved in the Spark community because our investment is in Spark so that's another part of my role is to get involved with the industry and to be able to connect with the experts in the industry so we can leverage off of that because we don't have that expertise internally. >> What are the strategic and tactical objectives of your analytics initiatives? Is it to get better predictive maintenance on your devices? Is it to create new services for customers? Can you describe that? >> It's two-fold, internal and external so internally, we got millions of dollars of opportunity to better our products with cost, also to optimize our business models and the way we can do that is by using the data that comes back from our products, our services, our customers, combining that together and creating models around that that are then automated and can be turned into apps that can be used internally by our organizations. The second part is to take the same approach, same data, but apply that back towards our customers and so with the split, our enterprise services group also went with Hewlett Packard Enterprise and so now, we have a dedicated effort towards creating manage services for the commercial environment. And that's both on the print size and on the personal system side so to basically fuel that, analytics is a big part of the story. So we've had different things that you'll see out there like touch point manager is one of our services we're delivering in personal systems. >> Dave: What is that? >> Touch point manager is aimed at providing management services for SMB and for commercial environments. So for instance, in touch point manager, we can provide predictive type of capabilities for support. A number of different services that companies are looking for when they buy our products. Another thing we're going after too is device as a service. So there's another thing that we've announced recently that basically we're invested into there and so this is obviously if you're delivering devices as a service, you want to do that as optimal as possible. Well, being able to understand the devices, what's happening with them, been able to predictive support on them, been able to optimize the usage of those devices, that's all important. >> Dave: A lot of data. >> The data really helps us out, right? So the data that we can collect back from our devices and to be able to take that and turn that around into applications that are delivering information inside or outside is huge for us, a huge opportunity. >> It's interesting where you talk about internal initiatives and manage services, which sound like they're most external, but on the internal ones, you were talking about taking customer data and internal data and turning those into live models. Can you elaborate on that? >> Sure, I can give you a great example is on our mobile products, they all have batteries. All of our batteries are instrumented as smart batteries and that's an industry standard but HP actually goes a step further on that, it's the information that we put into our batteries. So by monitoring those batteries and the usage in the field is we can tell how optimally they're performing, but also how they're being used and how we can better design batteries going forward. So in addition, we can actually provide information back into our supply chain. For instance, there's a cell supplier for the battery, there's a pack supplier, there's our unit manufacturer for the product, and so a lot of things that we've been able to uncover is that we can go and improve process. And so improving process alone helps to improve the quality of what we deliver and the quality of the experience to our customers. So that's one example of just using the data, turning that around into a model. >> Is there an advantage to having such high volume, such market share in getting not just more data, but sort of more of the bell curve, so you get the edge conditions? >> Absolutely, it's really interesting because when we started out on this, everybody's used to doing reporting which is absolute numbers and how much did you shift and all that kind of stuff. But, we're doing big data, right? So in big data, you just need a good sample population. Turn the data scientist into that and they've got their statistical algorithms against that. They give you the confidence factor based upon the data that you have so it's absolutely a good factor for us because we don't have to see all the platforms out there. Then, the other thing is, when you look at populations, we see variances in different customers so we're looking at, like one of our populations that's very valuable to us is our own, so we take the 60 thousand units that we have internally at HP and that's one of our sample populations. What a better way to get information on your own products? But, you take that and you take it to one of our other customers and their population's going to look slight different. Why? Because they use the products differently. So one of the things is just usage of the products, the environment they're used in, how they use them. Our sample populations are great in that respect. Of course, the other thing is, very important to point out, we only collect data under the rules and regulations that are out there, so we absolutely follow that and we absolutely keep our data secure and we absolutely keep everything and that's important. Sometimes, today they get a little bit spooked sometimes around that, but the case is that our services are provided based on customers signing up for them. >> I'm guessing you don't collect more data than Google. >> No, we're nowhere near Google. >> So, if you're not spooked at Google - >> That's what I tell people. I say if you got a smartphone, you're giving up a lot more data than we're collecting. >> Buy something from Amazon. Spark, where does Spark fit into all of this? >> Spark is great because we needed a programming platform that could scale in our data centers and in our previous approaches, we didn't have a programming platform. We started with a Hadoop, the Hadoop was very complex though. It really gets down to the hardware and you're programming and trying to distribute that load and getting clusters and you pick up Spark and immediately abstraction. The other thing is it allows me to hire people that can actually program on top of it. I don't have to get someone that knows Map Reduce. I can sit there and it's like what do you know? You know R, Scala, you know Python, it doesn't matter. I can run all of that on top of it. So that's huge for us. The other thing is flat out the speed because as you start getting going with this, we get this pull all of a sudden. It's like well I only need the data like once a month, it's like I need it once a week, I need it once a day, I need the output of this by the hour now. So, the scale and the speed of that is huge and then when you put that on the cloud platform, you know, Spark on a cloud platform like Amazon, now I've got access to all the compute instances. I can scale that, I can optimize it because I don't always need all the power. The flexibility of Spark and being able to deliver that is huge for our success. >> So, I've got to ask some columbo questions and George, maybe you can help me sort of frame it. So you mentioned you were using Hadoop. Like a lot of Hadoop practitioners, you found it very complex. Now, Hewlett Packard has resources. Many companies don't but so you mentioned people out doing Python and R and Scale and Map Reduce, are you basically saying okay, we're going to unify portions of our Hadoop complexity with Spark and that's going to simplify our efforts? >> No, what we actually did was we started on the Hadoop side of it. The first thing we did was try to move from a data warehouse to more of a data lake approach or repository and that was internal, right? >> Dave: And that was a cost reduction? >> That was a cost reduction but also, data accessibility. >> Dave: Yeah, okay. >> The other thing we did was ingesting the data. When you're starting to bring data in from millions of devices, we had a problem coming through the firewall type approach and you got to have something in front of that like a Kafka or something in front of it that can handle it. So when we moved to the cloud, we didn't even try to put up our own, we just used Kinesis and that we didn't have to spend any resources to go solve that problem. Well, the next thing was, when we got the data, you need to ingest the data in and our data's coming in, we want to split it out, we needed to clean it and what you, we actually started out running Java and then we ran Java on top of Hadoop, but then we came across Spark and we said that's it. For us to go to the next step of actually really get into Hadoop, we were going to have to get some more skills and to find the skills to actually program in Hadoop was going to be complex. And to train them organically was going to be complex. We got a lot of smart people, but- >> Dave: You got a lot of stuff to do, too. >> That's the thing, we wanted to spend more time getting information out of the data as opposed to the framework of getting it to run and everything. >> Dave: Okay, so there's a lot of questions coming out. You mentioned Kinesis, so you've replaced that? >> Yeah, when we went to the cloud, we used as many Amazon services as we can as opposed to growing something for ourselves so when we get onto Amazon, you know, getting data into an S3 bucket through Kineses was a no-brainer. When we transferred over to the cloud, it took us less than 30 days to point our devices at Kinesis and we had all our data flowing into S3. So that was like wow, let's go do something else. >> So I got to ask you something else. Again, I love when practitioners come on. So, one of the complaints that I hear sometimes from AWS users and I wonder if you see this is the data pipeline is getting more and more complex. I got an API for Kinesis, one for S3, one for DynamoDB, one for Elastic Plus. There must be 15 proprietary APIs that are primitive, and again, it gets complicated and sometimes it's hard to even figure out what's the right cost model to use. Is that increasingly becoming more complex or is it just so much simpler than what you had before and you're in nirvana right now? >> When you mentioned costs, just the cost of moving to the cloud was a major cost reduction for us. >> Reduction? >> So now it's - >> You had that HP corporate tax on you before - >> Yeah, now we're going from data centers and software licenses. >> So that was a big win for you? >> Yeah, huge, and that released us up to go spend dollars on resources to focus on the data science aspect. So when we start looking at it, we continually optimized, don't get me wrong. But, the point is, if we can bring it up real quickly, that's going to save us a lot of money even if you don't have to maintain it. So we want to focus on creating the code inside of Spark that's actually doing the real work as opposed to the infrastructure. So that cost savings was huge. Now, when you look at it over time, we could've over analyzed that and everything else, but what we did was we used a rapid prototyping approach and then from there, we continued to optimize. So what's really good about the cloud is you can predict the cost and with internal data centers and software licenses and everything else, you can't predict the cost because everybody's trying to figure out who's paying for what. But in the case of the cloud, it's all pretty much you get your bill and you understand what you're paying. So anyway - >> And then you can adjust accordingly? >> We continue to optimize so we use the services but if we have for some reason, it's going to deliver us an advantage, we'll go develop it. But right now, our advantage is we got umteen opportunities to create AI type code and applications to basically automate these services, we don't even have enough resources to do it right now. But, the common programming platform's going to help us. >> Can you drill into those umpteen examples? Just some of them because - >> I mentioned the battery one for instance. So take that across the whole system so now you've got your storage devices, you've got your software that's running on there, we've got built into our system security monitoring at the firmware level just basically connecting into that and adding AI around that is huge because now we can see a tax that may be happening upon your fleet and we can create services out of that. Anything that you can automate around that is money in our pocket or money in our customers' pocket so if we can save them money with these new services, they're going to be more willing to come to HP for products. >> It's actually more than just automation because it's the stuff you couldn't do with 1,000 monkeys trying to write Shakespeare. You have data that you could not get before. >> You're right, what we're doing, the automation is helping us uncover things that we would've never seen and you're right, the whole gorilla walking through the room, I could sit there and I could show you tons of examples of where we're missing the boat. Even when we brought up our first data sets, we started looking at them and some of the stuff we looked at, we thought this is just bad data and actually it wasn't, it was bad product. >> People talk about dark data - >> We had no data models, we had no data model to say is it good or bad? And now we have data models and we're continuing to create those data models around, you create the data model and then you can continue to teach it and that's where we create the apps around it. Our primitives are the data models that we're creating from the device data that we have. >> Are there some of these apps where some of the intelligence lives on the device and it can, like in a security attack, it's a big surface area, you want to lock it down right away. >> We do. The good example on the security is we built something into our products called Sure Start. What essentially it is is we have ability to monitor the firmware layer and so there's a local process that's running independent of everything else that's running that's monitoring what's happening at that firmware level. Well, if there's an attack, it's going to immediately prevent the attack or recover from the attack. Well, that's built into the product. >> But it has to have a model of what this anomalous behavior is. >> Well in our case, we're monitoring what the firmware should look like and if we see that the firmware, you know you take check sums from the firmware or the pattern - >> So the firmware does not change? >> Well basically we can take the characteristics of the firmware and monitor it. If we see that changing, then we know something's wrong. Now it can get corrupt through hardware failure maybe because glitches can happen maybe. I mean solar flares can cause problems sometimes. So, the point is we've found that customers had problems sometimes where basically their firmware would get corrupted and they couldn't start their system. So we're like are we getting attacked? Is this a hardware issue? Could it be bad Flash devices? There's always all kinds of things that could cause that. Well now we monitor it and we know what's going on. Now, the other cool thing is we create logs from that so when those events occur, we can collect those logs and we're monitoring those events so now we can have something monitor the logs that are monitoring all the units. So, if you've got millions of units out there, how are you going to do that manually? You can't and that's where the automation comes in. >> So the logs give you the ability up in the cloud or at HP to look at the ecosystem of devices, but there is intelligence down on the - >> There's intelligence to protect the device in an auto recover which is really cool. So in the past, you had to get your repair. Imagine if someone attacked your fleet of notebooks. Say you got 10 thousand of them and basically it brought every single one of them down one day. What would you do? >> Dave: Freak. >> And everything you got to replace. It was just an attack and it could happen so we basically protect against that with our products and at the same time, we can see that may be a current and then from the footprints of it, we can then do analysis on it and determine was that malicious, is this happening because of a hardware issue, is this happening because maybe we tried to update the firmware and something happened there? What caused that to happen? And so that's where collecting the data from the population then helps us do that and then mix that with other things like service events. Are we seeing service events being driven by this? Thermal, we can look at the thermal data. Maybe there's some kind of heat issue that's causing this to happen. So we starting mixing that. >> Did Samsung come calling to buy this? >> Well, actually what's funny is Samsung is actually a supplier of ours, is a battery supplier of ours. So, by monitoring the batteries, what's interesting is we're helping them out because we go back to them. One of the things I'm working on, is we want to create apps that can go back to them and they can see the performance of their product that they're delivering to us. So instead of us having to call a meeting and saying hey guys let's talk about this, we've got some problems here. Imagine how much time that takes. But if they can self-monitor, then they're going to want to keep supplying to us, then they're going to better their product. >> That's huge. What a productivity boost because you're like hey, we got a problem, let's meet and talk about it and then you take an action to go and figure out what it is. Now if you need a meeting, it's like let's look at the data. >> Yeah, you don't have enough people. >> But there's also potentially a shift in pricing power. I would imagine it shifts a little more in your favor if you have all the data that indicates the quality of their product. >> That's an interesting thing. I don't know that we've reached that point. I think that in the future, it would be something that could be included in the contracts. The fact that the world is the way it is today and data is a big part of that to where going forward, absolutely, the fact that you have that data helps you to better have a relationship with your suppliers. >> And your customers, I mean it used to be that the brand used to have all the information. The internet obviously changed all that, but this whole digital transformation and IOT and all those log data, that sort of levels the playing field back to the brand. >> John: It actually changes it. >> You can now add value for the consumer that you couldn't before. >> And that's what HP's trying to do. We're invested to exactly do that is to really improve or increase the value of our brand. We have a strong brand today but - >> What do you guys do with - we got to wrap - but what do you do with databricks? What's the relationship there? >> Databricks, again we decided that we didn't want to be the experts on managing the whole Spark thing. The other part was that we're going to be involved with Spark and help them drive the direction as far as our use cases and what have you. Databricks and Spark go hand in hand. They got the experts there and it's been huge, our relationship, being able to work with these guys. But I recognize the fact that, and going back to software development and everything else, we don't want to spare resources on that. We got too many other things to do and the less that I have to worry about my Spark code running and scaling and the cost of it and being able to put code in production, the better and so, having that layer there is saving us a ton of money and resources and a ton of time. Just imagine time to market, it's just huge. >> Alright, John, sorry we got to wrap. Awesome having you on, thanks for sharing your story. >> It's great to talk to you guys. >> Alright, keep it right there everybody. We'll be back with our next guest. This is the CUBE live from Spark Summit East, we'll be right back.

vmworld 2015 brought to you by VMware and its ecosystem sponsors and now your host dave vellante welcome back to San Francisco everybody this is the cue the cube is SiliconANGLE wiki bonds continuous coverage of vmworld 2015 this is our sixth year at vmworld we go out to the events we extract the signal from the noise our friend vish mulchen is here with HP storage fish it's always good to see you you know in your hometown and of in the backyard it's great to be in moscone thanks for coming back on the cube thanks Dave great great to be here as always again so we have seen you know I go back to 2010 and at the time you know 3par was a separate company and then we watched the the acquisition occur I'm really badly needed that acquisition was we were at vmworld when the the bidding war was occurring between Dell and yeah that's right and we predicted HP he's going to win that war and of course that changed change the course of the storage at HP you know permanently yes so it's been an amazing run three pars become the crown jewel of the of the portfolio but the most amazing thing is how you've evolved that platform into play into the all flash world very very competitive product so so we've been sort of documenting that that traction but give us the update let's talk about sort of where you've come from and you know where we are today sure sure Dave so I mean if we look back in june 2013 when we first announced the AFA right and since jun 2013 we've had a fire series of announcements in in december we announce something called adaptive sparing which you know was actually very unique flash innovation treating the flash separately giving customers twenty percent more capacity in jun 2014 we brought two dollars per gig deduplication in december 2014 we brought the constable we call the converge flash array right flasher a flash focus design but hey you can add spinning this to it if you want right and several of our customers are actually doing that because they have a need for that and then in june of 2015 we double down right and we announced the 20000 series we brought the affordability even better to a dollar fifty a gig and that was in June so the other amazing thing is the pace of the cadence of announcements I mean I had to say I mean remember for years you know HP the announcements were very slow to come up maybe have one a year maybe you know maybe a name change but now it's like bang bang bang I presume it to the architecture that allows you to do that but a lot of skeptics when you came out yes with the all-flash right yeah it's going to be a bolt on you said no you know NASA died we'll see but now you're proving it why help the people who sort of don't understand the nuances how was it that you were able to do that and what are the proof points that it's not just a bolt on right so you know I think the it all comes down to the architecture right you have to have an architecture that's modular that extensible and you know as we looked at the three Power Architecture all the attributes that we put in place early on we're very applicable to flash now flash did have some differences and we did account for some of the differences in the architecture but the architecture proved to be able to be extensible and a lot of the tenants around scalable controllers for performance the ASIC to offload the fine-grained virtualized operating system with a very small page allocation size all of those fundamentals were perfectly suited for flash right and and you can almost probably say they were there were too much for spinning disk right why was to say was that just was that luck because a bit but of a lot of what the original designers a three-part did were trying to most of it was trying to offset the deficiencies of spinning disk yeah you know did they just have like amazing vision or was it just I give I give the founders a lot of credit for their foresight and in fact if you look at the founders and I spoke to them they were they had a server background and they started right and they said its own server guess I'm sorry guys say they said to me wish when we did a server benchmark it would take us six months four and a half of those six months was getting the storage right and they said they really don't understand why it had to be so hard right and I think they've brought a very different approach to storage to how sort of the industry was handling storage right it was it was very different it actually turned it on his head and they are actually architected some very interesting capabilities which you know I'm very confident as we go to flash 2 point 0 as we talk about other newer non-volatile memory technologies if nan something other than man comes about you know I'm very confident that the architecture will be able to gehen to isolate the media from the customer Martin fake hope said that's member stare but we'll see we'll see what whatever gentleman sorry you know we'll go about the industry members has a big element there but we'll go what the industry wants to look at of course so let's talk about vmworld 2015 what you guys are doing here you know sure emphasize the announcements that you're making talk about that a little bit sure so in vmworld we had several announcements we made what i'll focus in is on the flash announcements and you know if you look at the approach we've taken with flash we've had three vectors right affordability performance and data services and some companies have done one or two but i think it's rare to see all three vectors being attack of the same time and that's been our approach from the start and all the announcements we talked about and in this announcement that we made this week same approach so let's let's maybe go down those three vectors Dave if you allow me to yeah please okay so so let's start with affordability and we announced a new 8000 series which is a refresh to the 7000 line right a very successful 7000 line of which is 7450 flash arrays one of them now the starting point for the 8200 the old flash 8200 now is down to nineteen thousand four hundred ninety seven dollars two controllers six drives six terabyte usable capacity 19,000 999 we're under 20 grand by a lot we make sure you got that 497 right so that's great we also announced then a lower entry price point to the 20000 series that we announced in earlier in June those were as your call aight controller systems we announced a lower price point 2450 a 4 controller capable system as well again on the theme of bringing affordability right driving the price down okay so you have dollar fifty per gig if you want to buy that way if low entry price point with 19 k if you want to buy that way or if you want a scalable system that you can grow to the extreme you can buy affordable price point that way as well right so in my mind the the adoption the success we've had in the marketplace has been a function of a couple of things affordability is a key one right it's economics that's what drives adoption okay now your performance everything's okay let's flash over he's got the same performance is high performance now it's somewhat true because relative to spinning disk it's gonna be you know better performance but there's it's nuanced so talk about your performance yeah so performance is very important we announced a couple of interesting performance first we talked about some some improvements in bandwidth now let's take a look at sort of why that matters right Dave so if you were doing a million iOS and there were small 4k blocks do the math it's four gigabytes per second now if you're doing large block iOS like if you're doing a sequel database query analytical query those are typically large block ayos right we do a million of those and there Sarah megan size then that bandwidth becomes a choke point to the array so we've announced with with the 8000 series you know twenty four gigs the second of bandwidth which is two and a half times more than so but this is ever saw it started erupting but this is why a lot of the existing arrays that bolted on flash failed what yeah so one of the reasons why they fail is their controllers are not able to handle the IO load and once even if they do can they handle the bandwidth requirements and then you know here's the other thing that matters is the latency right so the other thing we announced at the this week was a forty-four percent improvement in latency soumillon I ops 387 microseconds latency Adam denials that's just low latency so you're setting up this little latency storage versus capacity storage right and you got you playing both but we're obviously talking about the latency piece here okay correct so that's the performance piece and then there's there's there's actually two more there's the availability which answer this well free part is known for high availability and it's the new tier one yeah yeah so and it but there's data services associated with that yeah so the resiliency is a big factor there and you know there's single system resiliency pull out a drive pull out a controller fail a cache board how do you react right in fact the reason why we succeed in the marketplace that our customers tell us is that reliability factor and they go and they have these tests where they pull things in and out right and they watch how the other arrays operate right and you know consistently we've come back really operating well in the area of single system resiliency now there's also a multi-system resiliency which is what do I do with replication what I do with snapshots can I move my snapshots to addy duplicating backup device all right how quickly can I move how much do I move so I think there are all of these elements that you look at resiliency that I think important that's another piece and resiliency that's coming up as well emerging Dave and that's around protecting the access to your data security do you encrypt the data so now if you encrypt the data and you have a snapshot and you move that snapshot to a duplicating device what happens to that snapshot and the key do you have to a multiple key so your keys get compromised so that resiliency topic is a big one lots of different areas to go off go after and whether it's replications snapshots backup devices encryption key managers we have all those elevators well how about so again one of the we always talked about this one of the big advantages of an architecture that's been around for a decade is is you've got the stack it's hardened you know that sets the storage services so that's that's a big differentiator from what you see in a lot of the startups yes and and or the bolt ons which everybody thought you're going to be both on baby architected the whole thing so that's cool what about quality of service what about the ability to sort of address quality of service to pin application performance and to actually change that programmatically yeah so quality of service is a very very big big attribute of ours in fact week the product for full HP three parts called priority optimization and in this week's announcement we announce further enhancements first of all we have latency goals on our queue as product which i think is unique nobody else offers latency goals and this week we announced the latency goals going down to half a millisecond I mean if that array is operating at you know three to four hundred microseconds you want to be able to control your priorities with that granularity right and so qos granularity is exactly what we brought and you know Dave Lee if you remember when we did the last cube we talked to the cloud and they they had taken a gold silver bronze tier hardware-based and then put her on a flash array and put priority optimization to implement in software the gold silver bronze right yeah the cloud is a company music louder company yeah so that's right and that was interesting to see that they did that with with flash right you know yeah exactly yeah what do you think is going to happen there right is a worship we're hearing increasingly it shows like this and others that that you're starting to see more tearing and flash you're hearing it now in in the hadoop world and big data world the example that you just gave a lot of people initially and maybe still think you're going to have flashed here in the latency tier and you're going to have the capacity to air the bit bucket what's yours what you're thinking now on how that shakes shakes out and how practitioners should be thinking about their storage architectures going forward and I think you were gonna see the variety of that I think that's one very possible use case which says hey I have a applications that are critical service optimized service level optimized right that got to be on flash and then I may have either a backing store for time or I might have another set of applications that are not service level optimized more cost optimized may be right so and maybe that changes over time maybe it changes by quarter what is cost optimized today needs a spike and come back so this notion of data mobility I think it's very key right and sort of the fourth data service pillar I want to talk about because we announced for wave Federation which is the ability to take for arrays and operate as a single logical hole and you can federated Atta among those arrays now but if you extend the ideas can you federated to a backup device can you fed rate it to the generic cloud right can you federated to an archived here I think these are the kinds of things that our customers are asked that's right they want a first of all federal rate to another array to work load balance for example Oh asset refresh right but all of the other use cases federated a cloud federated to archived here those are all coming up alright so I suspect we're gonna see more of those as I said can I and let's stay tuned state-owned you know I mean as we as we look to to raise the bar once again these are some of the things what we're thinking about all right so so I know you can't give details but give us high level road map what should we be thinking about watching you know HP generally 3par and all flesh specifically yeah so I think we'll continue to drive a affordability right 3d and 3d Nance available as well now there's other flash technologies and you know we want to isolate our customers from whether it's CML CML see 3d 9 i'm gonna say to them look what's your price point what's your capacity point what's your availability point ok and we'll meet that let us worry about that technology problem out there how we get there so that continues to work us on you know the media faster controllers again to drive up the drive of the performance hosting the connects you know there's a lot of talk around the role of 25 gig Ethernet 32 gig fibre channel the RDMA technologies right I sir are I war rocky so there's all these things here nvm e to the backplane nvme to the host so you know flash j-bot so look at yeah it's shit we're shifting the bottleneck are we are you going to look at the bottlenecks across all areas into n and make sure that you're looking at this holistically right as you drive as you drive forward doesn't get less complicated but at least for the for the for the guys who are building this stuff hopefully for I we who are using it it does but fish motion thanks very much baby greater pleasure always pleasure sir I keep right there everybody will be back with our next guest this is the cube we're live from vmworld 2015 in moscone we'll be right back you

live from Boston Massachusetts extracting the signal from the noise it's the kue covering HP big data conference 2015 brought to you by HP software now your host John furrier and Dave vellante okay welcome back everyone we are here live in boston massachusetts for HP's big data conference this is a special presentation of the cube our flagship program where we go out to the events and extract the season for the noise I'm John furrier with Dave allante here Wikibon down on research our next guest Stephanie McReynolds VP margon elation hot new startup that's been kind of coming out of stealth that's out there big data a lot of great stuff Stephanie welcome to the cube great see you great to be here tell us what the start at first of all because good buzz going on it's kind of stealth buzz but it's really with the fought leaders and really the you know the people in the industry who know what they're talking about like what you guys are doing so so introduce the company tells me you guys are doing and relationship with Vertica and exciting stuff absolutely a lesion is a exciting company we just started to come out of south in March of this year and we came out of self with some great production customers so eBay is a customer they have hundreds of analysts using our systems we also have square as a customer smaller analytics team but the value that you Neelix teams are getting out of this product is really being able to access their data in human context so we do some machine learning to look at how individuals are using data in an organization and take that machine learning and also gather some of the human insights about how that data is being used by experts surface that all in line with in work so what kind of data cuz Stonebreaker was kind of talking yesterday about the 3 v's which we all know but the one that's really coming mainstream in terms of a problem space is variety variety you have the different variety of schema sources and then you have a lot of unstructured exhaust or data flying around can you be specific on what you guys do yeah I mean it's interesting because there's several definitions of data and big data going around right and so I'm you know we connect to a lot of database systems and we also connect to a lot of Hadoop implementations so we deal with both structured data as well as what i consider unstructured data and i think the third part of what we do is bring in context from human created data or cumin information with which robert yesterday was talking about a little bit which is you know what happens in a lot of analytic organizations is that and there's a very manual process of documenting some of the data that's being used in these projects and that's done on wiki pages or spreadsheets that are floating around the organization and that's actually a really black base camp all these collaboration all these collaboration platforms and what you realize when you start to really get into the work of using that information to try to write your queries is that trying to reference a wiki page and then write your sequel and flip back and forth between maybe ten different documents is not very productive for the analyst so what our customers are seeing is that by consolidating all of that data and information in one place where the tables are actually reference side by side with the annotations their analysts can get from twenty to fifty percent savings and productivity and new analysts maybe more importantly new analyst can get up to speed quite a bit quicker and that square the day I was talking to one of the the data scientists and he was was talking about you know his process for finding data in the organization which prior to using elation it would take about 30 minutes going two maybe three or four people to find the data he needed for his analysis and with elation in five seconds he can run a query search for the date he wants gets it back gets all kind of all that expert annotation already around that base data said he's ready to roll he can start I'm testing some of us akashi go platform right they've heard it was it a platform and it and you said you work with a lot of database the databases right so it's tightly integrated with the database in this use case so it's interesting and you know we see databases as a source of information so we don't create copies of the data on our platform we go out and point to the data where it lies and surface that you know that data to to the end user now in the case of verdict on our relationship with Vertica and we've also integrated verdict in our stack to support we call data forensics which is the building for not an analyst who's using the system day to day but for NIT individual to understand where the behaviors around this data and the types of analysis that are being done and so verdicts a great high performance platform for dashboarding and business intelligence a back end of that providing you know quick access to aggregates so one of they will work on a vertica you guys just the engine what specifically again yeah so so we use the the vertica the vertical engine underneath our forensics product and then the that's you know one portion of our platform the rest of our platform is built out on other other technologies so verdict is part of your solution it's part of our solution it's it's one application that we part of one application we deliver so we've been talking all week about this week Colin Mahoney in his talk yesterday and I saw a pretty little history on erp how initially was highly customized and became packaged apps and he sort of pointed to a similar track with analytics although he said it's not going to be the same it's going to be more composable sort of applications I wonder and historically the analytics in the database have been closely aligned I'll say maybe not integrated you see that model continuing do you see it more packaged apps or will thus what Collins calling composable apps what's the relationship between your platforming and the application yeah so our platform is is really more tooling for those individuals that are building or creating those applications so we're helping data scientists and analysts find what algorithms they want to use as a foundation for those applications so a little bit more on the discovery side where folks are doing a lot of experiment and experimentation they may be having to prepare data in different ways in order to figure out what might work for those applications and that's where we fit in as a vendor and what's your license model and so you know we're on a subscription model we have customers that have data teams in the in the hundreds at a place like eBay you know the smaller implementations could be maybe just teams of five analyst 10a analyst fairly small spatial subscription and it's a seat base subscription but we can run in the cloud we can run on premise and we do some interesting things around securing the data where you can and see your columns bommana at the data sets for financial services organizations and our customers that have security concerns and most of those are on premise top implementation 70 talk about the inspiration of the company in about the company he's been three years since then came out of stealth what's the founders like what's the DNA the company what do you guys do differently and what was the inspiration behind this yeah what's really what's really interesting I think about the founding of the company is that and the technical founders come from both Google and Apple so you have an interesting observation that both individuals had made independently hardcore algorithmic guy and then like relevant clean yeah and both those kind of made interesting observations about how Google and Apple two of the most data-driven companies you know on the planet we're struggling and their analytics teams were struggling with being able to share queries and share data sets and there was a lot of replication of work that was happening and so much for the night you know but both of these folks from different angles kind of came together at adulation said look there's there's a lot of machine learning algorithms that could help with this process and there's also a lot of good ways with natural language processing to let people interact with their data in more natural ways the founder from from Apple Aaron key he was on the Siri team so we had a lot of experience designing products for navigability and ease of use and natural language learning and so those two perspectives coming together have created some technology fundamentals in our product and it's an experience to some scar tissue from large-scale implementations of data yeah very large-scale implementations of data and also a really deep awareness of what the human equation brings to the table so machine learning algorithms aren't enough in and of themselves and I think ken rudin had some interesting comments this morning where you know he kind of pushed it one step further and said it's not just about finding insight data science about is about having impact and you can't have impact unless you create human contacts and you have communication and collaboration around the data so we give analyst a query tool by which we surface the machine learning context that we have about the data that's being used in the organization and what queries have been running that data but we surface in a way where the human can get recommendations about how to improve their their sequel and drive towards impact and then share that understanding with other analysts in the organization so you get an innovation community that's started so who you guys targets let's step back on the page go to market now you guys are launched got some funding can you share the amount or is it private confidential or was how much did you raise who are you targeting what's your go-to market what's the value proposition give us the give us this data yeah so its initial value proposition is just really about analyst productivity that's where we're targeted how can you take your teams of analysts and everyone knows it's hard to hire these days so you're not going to be able to grow those teams out overnight how do you make the analyst the data scientist the phd's you have on staff much more productive how do you take that eighty to ninety percent of the time that they make them using stuff sharing data because I stuff you in the sharing data try to get them out of the TD of trying to just find eight in the organization and prepare it and let them really innovate and and use that to drive value back to the to the organization so we're often selling to individual analysts to analytics teams the go to market starts there and the value proposition really extends much further in the organization so you know you find teams and organizations that have been trying to document their data through traditional data governance means or ETL tools for a very long time and a lot of those projects have stalled out and the way that we crawl systems and use machine learning automation and to automate some of that documentation really gives those projects and new life in our enterprise data has always been elusive I mean do you go back decades structured day to all these pre pre built databases it's been hard right so it's you can crack that nut that's going to be a very lucrative in this opportunity I got the Duke clusters now storing everything I mean some clients we talked to here on the key customers of a CHP or IBM big companies they're storing everything just because they don't know they do it again yeah I mean if the past has been hard in part because we in some cases over manage the modeling of the data and I think what's exciting now about storing all your data in Hadoop and storing first and then asking questions later is you're able to take a more discovery oriented hypothesis testing iterative approach and if you think about how true innovation works you know you build insights on top of one another to get to the big breakthrough concepts and so I think we're at an interesting point in the market for a solution like this that can help with that increasing complexity of data environment so you just raise your series a raised nine million you maybe did some seed round before that so pretty early days for you guys you mentioned natural language processing before one of your founders are you using NLP and in your solution in any way or so we have a we have a search interface that allows you to look for that technical data to look for metadata and for data objects and by entering a simple simple natural language search terms so we are using that as part of our interface in solution right and so kind of early customer successes can you talk about any examples or yeah you know there's some great examples and jointly with Vertica square is as a customer and their analytics team is using us on a day-to-day basis not only to find data sets and the organization but to document those those data sets and eBay has hundreds of analysts that are using elation today in a day to day manner and they've seen quite a bit of productivity out of their new analysts that are coming on the system's it used to take analysts about 18 months to really get their feet around them in the ebay environment because of the complexity of all of the different systems at ebay and understanding where to go for that customer table you know that they needed to use and now analysts are up and running about six months and their data governance team has found that elation has really automated and prioritized the process around documentation for them and so it's a great light a great foundation for them there and data curators and data stewards to go in and rich the data and collaborate more with the analysts and the actual data users to get to a point of catalogued catalog data disease so what's the next you guys going to be on the road in New York Post Radek hadoop world big data NYC is coming up a big event in New York I'm Cuba visa we're getting the word out about elation and then what we're doing we have customers that are you know starting to speak about their use cases and the value that they're seeing and will be in New York market share I believe will be speaking on our behalf there to share their stories and then we're also going to a couple other conferences after that you know the fall is an exciting time which one's your big ones there so i will be at strada in New York and a September early October and then mid-october we're going to be at both teradata partners and tableaus conference as well so we connect not only to databases of all set different sorts but also to go with users are the tools yeah awesome well anything else you'd like to add share at the company is awesome we're some great things about you guys been checking around I'll see you found out about you guys and a lot of people like the company I mean a lot of insiders like moving little see you didn't raise too much cash that's raised lettin that's not the million zillion dollar round I think what led you guys take nine million yeah raised a million and I you know I think we're building this company in a traditional value oriented way great word hey stay long bringing in revenue and trying to balance that out with the venture capital investment it's not that we won't take money but we want to build this company in a very durable so the vision is to build a durable company absolutely absolutely and that may be different than some of our competitors out there these days but that's that we've and I have not taken any financing and SiliconANGLE at all so you know we're getting we believe in that and you might pass up some things but you know what have control and you guys have some good partners so congratulations um final word what's this conference like you go to a lot of events what's your take on this on this event yeah I do i do end up going to a lot of events that's part of the marketing role you know i think what's interesting about this conference is that there are a lot of great conversations that are happening and happening not just from a technology perspective but also between business people and deep thinking about how to innovate and verticals customers i think are some of the most loyal customers i've seen in the in the market so it's great in their advanced to they're talking about some pretty big problems but they're solving it's not like little point solutions it's more we architecting some devops i get a dev I'm good I got trashed on Twitter private messages all last night about me calling this a DevOps show it's not really a DevOps cloud show but there's a DevOps vibe here the people who are working on the solutions I think they're just a real of real vibe people are solving real problems and they're talking about them and they're sharing their opinions and I I think that's you know that's similar to what you see in DevOps the guys with dev ops are in the front line the real engineers their engineering so they have to engineer because of that no pretenders here that's for sure are you talking about it's not a big sales conference right it's a lot of customer content their engineering solutions talking to Peter wants a bullshit they want reaiah I mean I got a lot on the table i'm gonna i'm doing some serious work and i want serious conversations and that's refreshing for us but we love love of hits like it's all right Stephanie thinks for so much come on cubes sharing your insight congratulations good luck with the new startup hot startups here in Boston hear the verdict HP software show will be right back more on the cube after this short break you you

live from the sands convention center las vegas nevada extracting a signal from the noise it's the cube covering HP discover 2015 brought to you by HP and now your host dave vellante welcome back to HP discover everybody this is dave vellante check out HP discovered on social for all the social streams the video the content the special access patrick osborne is here from HP cube alum and he's joined by Bill Walker of 20th Century Fox gents welcome to the cube good thank you yeah thanks for having us discovering another discover a little different this year Patrick we got Meg talking about business outcomes and absolutely uber and their yeah all the kinds of some shit models are very different I mean obviously you come out here every year for the past number of years and you know it's all about the technology i'm always wowed by the broad you know portfolio that we have but really at the end of the day I think some of the messaging to the customers is you know we're here to help you solve your problems and parts of that is technology part of its services so this hot sort of new high-level messaging around transformation and helping people achieve these business outcomes I think it's a good fresh start yes so bill your business going through some interesting transformations yes today to talk about the high level the drivers in your business the yet new competitors you got you got huge opportunities to go into this digital transformation you've sort of early on in that so maybe talk about some of the drivers in your business sure absolutely I think for us you know you really hit the nail on the head in the sense that it's really been about the physical to digital transformation that the industry is you know kind of going through and also Fox is and you know on the infrastructure side and the IT side we're trying to support that you know as best we can and you know the name of the game lately has been speed to market right so we partnered very tightly with HP on not only the hardware but the software side in you know building out kind of a brand new digital supply chain environment in Las Vegas actually right here and one of our major data centers where we deliver all of our digital content to all of our providers so EST VOD providers like amazon and itunes as well as you know major broadcasters so you've got a facility out here that is essentially your your cloud yes yes we do that that's our primary place where we deliver everything out of its it's great we're using all HP hardware and software there so we're customers across the board in the sense that we have blades we've got three par we're using store once as well as the HP software stack like cloud system on top of that that part is part of a super nap yes yes so yeah we we're facility we're in super net we love it it's a great facility we moved there like a little over two years ago and it's it's been awesome experience that made it into the any of the movies no it must hey I know well they it's impressive on the outside and the inside right yeah was it the old member the robocop oh yeah they have that storagetek tape library way magnet yeah they were great at four days these impressive data centers look amazing so so talk a little bit more about the you called it the digital supply chain that's a powerful concept what's behind that yeah so you know we we've obviously been in the physical supply chain business for a while on the home entertainment side so thank DVDs you know blu-rays that kind of thing but as we transition from people buying physical media to digital media a lot of the workflows and you know the supply chain aspect of it is still there but now we're talking digital and not physical so one of the things we've done at Fox is we've you know we've created what we call our digital supply chain so you've got you know they not only you know things like content delivery in there but you've got you know watermarking you know all the all the hallmarks of what you would need in a in a digital environment to deliver that customer you know quality product from end to end and protect your IP yeah exactly where T is a big one so we'll talk about more about security data maybe there's a general topic and then let's go to dig deeper every good for sure I mean security is obviously one of our big drivers I mean obviously with everything that's been in the news lately we're no different in the sense that we take it very very seriously you know on the data protection front like I said we're big store wants customers we love the product we're using it heavily in our in our data center to protect our content as well as our data so how much time let's unpack that a little bit what's it what's it look like laughs so you said a bunch of different you know HP products can you can you help us to understand how much you know storage kind of servers what kind of apps paint a picture of your your infrastructure for sure so we've got you know a lot actually several racks of gear 3par like I said we're big three part customers so we have several racks a three part that we're using kind of across the board a lot on the database side you know and heiio scenarios storeonce is kind of that underpinning piece that everything funnels back to that provides you know data deduplication backup archival that kind of thing okay so can we talk more about sort of your objectives of protecting data I mean obviously don't lose it but there's you know time to recover there's data loss how are you approaching that yep so we we've got you know our primary facility at switch as well as a dr facility off-site we're using store once we r you know we've got them in both places we're doing replication both ways to ensure you know if we were to have a vent at one facility or we didn't have data available we can quickly recover from the other you know rtly is it's been a great success for us because we've moved from tape-based you know back up and i really didn't mention that but you know where we came from you know two two and a half years ago you know from our LA and chandler data centers we have very very heavy investment in tape infrastructure and one of the things we into decided when we went to this new you know environment in Las Vegas is we wanted it to be completely tapeless you know to be flexible right in that environment and you know we pick store once we went all disk-based and you know RTO wise is fantastic because you know as opposed to tape if you have an event if you happen to not have the tape on site your RT 0 is dictated you know kind of by when you can get the tape back with the exit yes yes fast as you can get here right with the store once though it's just there we can we can you know bring it back in minutes and in fact we actually had a kind of not funny but but interesting incident happened early on where you know we kind of had an hoops incident where somebody deleted a vm and you know with store once we already had it had it there we were able to recover it in minutes and have it working again which is not something we were able to do in in previous iteration so it's really RTO is your primary supposed to RP oh yeah and Patrick I'm sure you see it all over the board with with customers right i mean yeah absolutely i mean it is the whole environment is based on this digital content that it's the lifeblood of you know what they're doing as a business and what they're delivering you know to your customers so that what we're seeing in the data protection standpoint is that more apps are mission critical right they're moving from business-critical the mission-critical the RTOS and our feos are definitely more aggressive you know month by month quarter-by-quarter people are moving from days two hours to minutes and we want to have more they won't have access to more data that's near line and online for so you can basically restore that right away so we're seeing people architecting solutions for store ones where they'd want a couple weeks maybe a couple months of data stored on that from a vaca perspective now we're talking having conversations about three to five years seven years 10 years right so definitely a paradigm shift in terms of data protection and the clouds change that a lot absolutely how so talk about that I think you know because the cloud there's not really a concept of tape per se I mean I know you know some providers have a delayed you know a kind of recovery type mechanism but I think in general people are assuming you've got the data on disk or you know available somewhere and you're able to recall it right and you know almost any cloud provider I think today is structured that way and has some kind of object storage where you can back up to but it's an online situation right and I think that's kind of become the new the new standard for the expectation of you know it's dumping it into an object store an able to recover from that yeah i like to say backup is one thing recoveries everything so there's a software component that that's the good that and what about tape you using I mean you must be used tape in your business right we do still have tape but I think where it makes sense we're trying to get rid of it you know we obviously there's a lot of physical nature with tape you know for us it's also manpower you have to have you know it's a lot of manpower involved in just managing tape and whatnot so where we can especially strategically in our data centers we're trying to get out out of using tape and using you know just a long-term archiving long-term retention with your digital assets obviously you would take for that we definitely have scenarios at the studio where it's still used for sure yeah but not obviously not for backup no yeah yeah I think you know with my team we're starting to think of the the notion of backup maybe in the traditional sense it's kind of going away because I think what people think of backup they think tape they think these scenarios and I think it's you know it's changing to more of a you know having having various generations on disk so you have the concept of you know okay being able to go back in time but near real-time recovery a time machine for the enterprise yeah yeah we talk when we talk to customers it's usually around the areas of application data protection or a service data protection and then long term preservation of assets as opposed to backup and archive right so there because they have a very different business processes around them and you can apply different technologies to the two of them so in some some technologies are appropriate for one some are appropriate for the others so we're you know we're seeing a lot of customers really focus on day one of how I'm going to protect that data how I'm going to make data protection an automatic part of the infrastructure so I don't have to have separate backup team and separate you know specific processes this whole area of things being sort of automatically protected as part of the infrastructure is it's definitely worth a lot but I think that's a really important point to make data protection has historically been a bolt on right uh we got to protect the data yep and so you're saying that you're finally seeing customers integrate data protection as part of the fundamental solution absolutely the two things so the two things that now I'm seeing it from a fundamental part of the initial solution bill that is data protections built in right so you're seeing the techniques of snapshot and replication being melded with you know backup techniques like policy management indexing and all that kind of stuff right and then the other sort of conversation we're having with people who put infrastructure in place is how am I going to get off this in five years five to seven years right so because the amount the size of the data sets are becoming so big that replicating data data migrations migrating your backup data are there they're difficult the difficult task so people are doing a lot more planning ahead to understand how am I going to protect this data now right from a different set of scenarios and how am I going to start do some hardware lifecycle management from an infrastructure standpoint underneath that data as I go into the future are you a data protector customer what do you use not not currently although we are you know we are looking at it for sure yeah today we're actually net back up yeah yeah okay I mean it's a lot of ways to skin that kappa yeah that's still not in your group is it nope nice meg just make it but they have a saying this for a decade the data protect there should be a part of the storage solution I mean it's anyway we work with them every day fantastic I got a tight relationship yeah yeah I'm still get paid for it do get paid for it that's good okay well that's a start yeah yeah awesome alright let's see what else uh what's going on the show this year with you Oh lots of stuff of the show so obviously you you heard about flash right yeah we've heard a lot of flashes fam yeah it's great mokin fast yeah so there's a in it's funny there's a lot of implications to flash even on data protection right so this is a big area for us obviously is huge in the market the media and the speed in what flash brings to the table allows you to do some different things from Dave protection standpoint as well right so this concept of copy data management you've heard this in terms of now i can take copies of databases copies of data sets serve them up to uat test development environment so you know your speed of development by having access to copies of that you know of that original production data set is being enabled by media like flash no flash you can do lots of random i/o you can with with modern architectures like three par for example it's multi-tenant right you have quality of service on there so now we're in the past you'd have to clone a number of data sets copy them off restore them from backups for the purposes of having a you know a test data set now you can run all that on the same infrastructure so flash is great from a performance standpoint for you know speeding up your transactions feeding of your database your workflow but there's a lot of other things that allows us to do to help the overall speed of development which is kind of cool so the copy data management things interesting I mean yeah so active feos obviously popularizing it Dell fixes another one yeah the problem is they want me to rip out or not use my might reap are snapshots and I love my three parts don't want to put in a whole new infrastructure around it so is there I mean the opportunity you got a catalog in in-store wants maybe I could use that somehow that technology so that's what we're doing right so we're taking these techniques that you've had in traditional backup for years and then things you have on primary storage right snapshots and replication but with the with the advantages of flash now you're able to do a lot more with it and bringing those two techniques together we're doing it with software we're doing it with sort of extensible protocols and SD SDKs on the infrastructure itself so we're not introducing any sort of sand virtualization techniques or you know in line fibre channel you know type of virtualization technology we're allowing you do that as a part of the infrastructure itself so you know we're combining things like three par with Recovery Manager central and store ones to provide those type of experience I think the killer app they're Jews potentially is test dev right i mean if you can take copies that are more current give it to the especially with flash give it to the developers but they're not working on you know n minus three copies absolutely yeah and they're way more productive I know what kind of discussions are you having internal how do you service the developer community are they what kind of pressures are they putting on you bill yeah it's that probably the same things you've heard I mean you know agility speed I know for us you know because we're we're big on the cloud journey right now in terms of delivering you know private cloud services for our customers inside Fox one of the areas where we're actively really striving for is to do you know some deeper integration with some of the dev teams where they've got you know kind of closed loop cycles you know DevOps type cycles that they're developing with you know familiar tooling which you know is in the market that out there the Jenkins etc you know my team we're definitely working on trying to integrate a lot of the automation we're doing around cloud with what they're doing on the test dev site to kind of create a nice you know cohesive whole so you know rather than delivering just a server to them we can deliver an entire in a build environment and tear it down you know build it up and tear down dynamic flames so you mentioned a store once customer talked about RTO being really on the primary metric that you're trying to optimize waiting sir patrick comes out to California you know hits the beach makes a quick sales call writes it off wait what do you want to know from him yeah okay Oh with you that the time so what kind of discussions do you have with with Patrick around where you want to where you want to go what you want out of the product when I roadmap to the club yeah I think one of the things you know we're as I said before you know we're three par and store wants customers and I think we're where we see you know things headed in the future we'd love to see even deeper integration with three par and store once and you know we're actually having a discussion my team before this and one of the things they threw out there like hey why can't we just combine them into one product you know and I know right now they're separate but sure maybe maybe in the near future you know the the notion of having this this external device it's separate from 3par that you're you know moving to you know maybe maybe some of that gets melded together and what does that do for you it minimizes the need to manage another appliance absolutely right so it simplifies your your infrastructure tighter integration yep so better reliability and yeah I mean you know we're like a lot of technology shops in the sense that well we're trying to squeeze you know as much as we can you know with the team that we have in terms of Technology and still deliver a lot of services so you know we're always looking to if we can take two and make it one or you know that kind of scenario for simplification that's what we want to do too and more with less but no so let me ask you a question when you do more with less and you've dropped money to the CFO's bottom line today they carve off the you get a lick off that cone or they say hey they'll nice job here's a little you know we'll take twenty percent of that savings and give it back yeah it's I for us it's just the you know the slap on the back the handshake that we did it what are you seeing without me from our mothers hear from our product portfolio standpoint we're simplifying right we want to have I think we're in a unique position in terms of we want to be the best storage division inside of HP Enterprise right we don't want to be the best storage division standalone right so that affords us a lot of experiences for that we can bring to the customer when you bring in you know the blades and compute and networking and storage I mean what you see up on stage with one view and all of our element managers you know it's it doesn't sound sexy at the end of the day but basically having a same look and feel the same taxonomy that you use for all of our products is like a huge simplification for customers not having to you know learn new you is and why not so we have other competitors who you know they're bringing 7 10 12 you know different architectures for a primary storage the table right we're consolidating that and providing customers that the ability to they can go in a cost optimized software to find you know deployment model you can have appliances that are tuned in high performance same look and feel same CLI same utilities same data services so we want choice but it has to be simple because too much so what do you think about that whole software-defined mean is that the future is it this Patrick sort of implying sort of the the lower-cost sort of software only model what do you guys say yeah well we're big believers in software to find you know like I said we're we're kind of in it on you know on the whole stack in the sense that we know not only a part where we have software with HP we're also doing a lot with the team around Helion OpenStack right now and you know one of the big bets we're making is we think openstax going to be big we you know I know internally when we've talked with you know a lot of the development teams the idea of API defined infrastructure that's more malleable is tremendously exciting so what are you in with OpenStack well so right now we're actually we're kind of in that you know early stage entire ya des you know trying to trying to get a feel for it cuz you know one of the things I always say you know right now with OpenStack is it's kind of a two-way street you know there's the infrastructure part of it that my team has to deliver but the the other side of it is really the developers you know getting their hands around it getting a feel for it you know maybe even doing some platform-as-a-service with Cloud Foundry you know that kind of thing and they're really developing for that platform and getting the most out of it because you know in a lot of cases you know you're coming from a traditional environment where you know you had physical servers you put virtualization on top of it everybody's kind of used to that maybe a single VM kind of scenario but when you move to something like OpenStack you kind of got to rethink how you approach application building just think all right gents we're out of time going to leave it there but Patrick last last word for you why HP why HP I think we've got some exciting times ahead of us this year right so unlocking some velocity and value for for everyone with HP Enterprise kind of like just to echo what I said before about you know we're a portfolio company that brings a lot of technology services to our customers and at the end of the day my bet is that standalone companies that focus on one thing like storage or one thing like network or specifically compute I don't see a path forward for that over time right customers are buying solutions and systems and converged art you know infrastructure how you see this you know hyper converge theme right HP is one of the few companies that can bring all those elements to our customers as part of the equation so that for me that's why I stay here and why we've got such a great technology path forward yeah the 80s and 90s are about disintegration of IT and creating those silos and now we're seeing the reintegration so Patrick a bill thanks very much for coming on the cube absolutely thank you so much to have you guys here all right all right keep it right to everybody will be back with our next guest right after this short break you

>>Live from Las Vegas, Nevada. It's a queue at HP. Discover 2014 brought to you by HP. >>Welcome back, everyone live here in Las Vegas for HP. Discover 2014. This is the cube we're out. We go where the action is. We're on the ground here at HP. Discover getting all the signals, sharing them with you, extracting the signal from the noise. I'm John furrier, founder of SiliconANGLE. I joined Steve Woolwich VP of product marketing at map art technologies. Great to see you welcome to the cube. Thank you. I know you got a plane to catch up, but I really wanted to squeeze you in because you guys are a leader in the big data space. You guys are in the top three, the three big whales map are Hortonworks, Cloudera. Um, you know, part of the original big data industry, which, you know, when we did the cube, when we first started the industry, you had like 30, 34 employees, total combined with three, one company Cloudera, and then Matt are announced and then Hortonworks, you guys have been part of that. Holy Trinity of, of early pioneers. Give us the update you guys are doing very, very well. Uh, we talked to you guys at the dupe summit last week. So Jack Norris for the party, give us the update what's going on with the momentum and the traction. And then I want to talk about some of the things with the product. >>Yeah. So we've seen a tremendous uptick in sales at map. Are we tripled revenue? We announced that publicly about a month ago. So we went up 300% in sales, over Q3, I'm sorry, Q1 of 2013. And I think it's really, you know, the maturity of the market. As people move more towards production, they appreciate the enterprise features. We built into the map, our distribution for Hadoop. So, um, you know, the stats I would share is that 80% of our customers triple the size of their cluster within the first 12 months and 50% of them doubled the size of the cluster because there's the, you know, they had that first production success use case and they find other applications and start rolling out more and more. So it's been great for us. >>You know, I always joke with Jack Norris, who's the VP of marketing over there. And John Frodo is the CEO about Matt bars, humbleness. You don't have the fanfare of all the height, depressed love cloud era. Now see they had done some pretty amazing things. They've had a liquidity event, so essentially kind of an IPO, if you will, that huge ex uh, financing from Intel and they're doing great big Salesforce. Hortonworks has got their open source play. You guys got, you got your heads down as well. So talk about that. How many employees you guys have and what's going on with the product? How many, how many new, what, how many products do you guys actually, >>We have, well, we have one product. So we have the map, our distribution for Hadoop, and it's got all the open source packages directly within it, but where we really innovate is in the course. So that's where we, we spent our time early on was really innovating that data platform to give everything within the Hadoop ecosystem, more reliability, better availability, performance, security scale, >>It's open source contributions to the court. And you guys put stuff on top of that, uh, >>And how it works. Yeah. And even some projects we lead the projects like with Apache Mahal and Apache drill, which is coming into beta shortly other projects, we commit and contribute back. But, um, so we take in the distribution, we're distributing all those projects, but where we really innovate is at that data platform level. So >>HP is a big data leader officer. They bought, uh, autonomy. They have HP Vertica. You guys are here. Hey, what are you doing here? Obviously we covered the cube, uh, the announcement with, uh, with, with HP Vertica, you here for that reason, is there other biz dev other activity going on other integration opportunities? >>Yeah, a few things. So, um, obviously the HP Vertica news was big. We went into general availability that solution the first week of may. So, um, what we have is the HP Vertica database integrated directly on top of our data platform. So it's this hybrid solution where you have full SQL database directly within your Hadoop distribution. Um, so it had a couple sessions on that. We had, uh, a nice panel discussion with our friends from Cloudera and Hortonworks. So really good discussion with HP about just the ecosystem and how it's evolving. The other things we're doing with HP now is, you know, we've got reference architectures on their hardware lines. So, um, you know, people can deploy Mapbox on the hardware of HP, but then also we're talking with the, um, the autonomy group about enterprise search and looking at a similar type of integration where you could have the search integrated directly into your Hadoop distro. And we've got some joint accounts we're piloting that she goes, now, >>You guys are integrating with HP pretty significantly that deals is working well. Absolutely. What's the coolest thing that you've seen with an HP that you can share. How so I asked you in the big data landscape, everyone's Bucher, you know, hunkering down, working on their feature, but outside in the real world, big data, it's not on the top of mind of the CIO, 24 7. It's probably an item that they're dressing. What have you seen and what have you been most impressed with at HP here? >>Yeah. Say, you know, this is my first HP event like this. I think the strategy they have is really good. I think in certain areas like the cloud in particular with the helium, I think they made a lot of early investments there and place some bets. And I think that's going to pay off well for them. And that marries pretty nicely with our strategy as well in terms of, you know, we have on-premise deployments, but we're also an OEM if you will, within Amazon web services. So we have a lot of agility in the cloud if you will. And I think as those products and the partnerships with HP, evolvable, we'll be playing a lot more with them in the cloud as well. >>I see that asks you a question. I want you to share with the folks out there in your own words, what is it about map bar that they may or may not understand or might not know about? Um, a little humble brag out there and share some, share some, uh, insight of, into, into map bar for folks that don't know you guys as a company and for the folks that may have a misperception of what you guys do shit share with them, with what, what map map is all about. >>Yeah. I mean, for me, I was in this space with Aster data and kind of the whole Hadoop and MapReduce area since 2008 and pretty familiar with everybody in the space. I really looked at Matt bars, the best technology hands down, you look at the Forrester wave and they rank us as having the best technology today, as well as product roadmap. I think the misperception is people think, oh, it's proprietary and close. It's actually the opposite of that. We have an unbiased open-source approach where we'll ship in support in our distribution, in the entire Apache spark stack. We're not selective over which projects within Apache spark. We support. Um, I feel like SQL on Hadoop. We support Impala as well as hive and other SQL on to do technologies, including the ability to integrate HP Vertica directly in the system. And it's because of the openness of our platform. I'd say it's actually more open because of the standards we've integrated into the data platform to support a lot of third-party tools directly within it. So there is no locked in the storage formats are all the same. The code that runs on top of the distribution from the projects is exactly the same. So you can build a project in hive or some other system, and you can port it between any of the distributions. So there isn't a, lock-in >>The end of the day, what the customers want is they want ease of integration. They want reliability. That's right. And so what are you guys working on next? What's the big, uh, product marketing roadmap that you can share with us? >>Yeah, I think for us, because of the innovations we did in the data platform allows us to support not only more applications, but more types of operational systems. So integrating things like fraud detection and recommendation engines directly with the analytical systems to really speed up that, um, accuracy and, and, uh, in targeting and detecting risk and things like that. So I think now over time, you know, Hadoop has sort of been this batch analytic type of platform, but the ability to converge operations and analytics in one system is really going to be enabled by technology like Matt BARR. >>How many employees do you guys have now? Uh, >>I'm not sure what our CFO would. Let me say that before. You can say we're over 200 at this point >>As well. And over five, the customers which got the data, you guys do summit graduations, we covered your relationship with HP during our big data SV. That was exciting. Good to see John Schroeder, big, very impressive team. I'm impressed with map. I will always have been. You guys have Stephanie kept your knitting saved. Are you going to do, and again, leading the big data space, um, and again, not proprietary is a very key word and that's really cool. So thanks for coming on. Like you really appreciate Steve. We'll be right back. This is the cube live in Las Vegas, extracting the city from the noise with map bar here at the HP discover 2014. We'll be right back here for the short break.

live from Las Vegas Nevada it's the cube at HP discover 2014 brought to you by HP the keynotes this afternoon meg whitman was just on a panel with thomas friedman and intel and satya nadella microsoft and pretty interesting i was it was interesting i'm here with Jeff Rick to note how passionate meg is about politics and government wow I'm she comforted by boat for Bobby Patrick is here we've been drilling down into cloud all day Bobby is the CMO of the HP Cloud Division a lot of new announcements coming on a lot of action and HP Cloud Bobby welcome to the cube yeah thank it's great to be here yeah good to see you so yeah good keynotes good good that was a good refresher you know a lot of these keynotes just products pushing and pushing we had some of that earlier but I thought it was a good eye opening refreshing right kind of discussion so it was very worthwhile but anyway you're relatively new to to HP to run to actually soon how's it going it's great it's exciting i joined it like a great time for the company we were gearing up for the big launch of our new brand HP Helion that that was launched on May seventh so just a little over a month ago and we hit the mark market hard globally it's a complete pull together of all of our products and services around cloud under a single brand customers love it and and it's really reiterated our commitment to OpenStack and you know it's great HP announced the billion dollar commitment to HP Helion over the next two years so it's backed by some some big funding that's a great time to come in so I saw that what is that would help us unpack that billion dollars it was big number right it's popular number right even we aren't buffin right her site Warren Buffett hehe underwrote the whole thing the March Madness right giving away a billion dollars for the perfect bracket right no longer a million does out of the abelian so what is that billion what does it go to what does it comprised yeah I mean it goes 2 r.d where where the most where the most active corporate sponsor behind OpenStack which is the fastest-growing open source project on the planet we are we have more contributors we have more team leads for the different projects and so we're working with the community we're hiring OpenStack experts always looking for the best in the world all around the world and we're then hardening and curating it in making a commercial now with our support and we believe it's the underpinning of the future of what we call hybrid cloud the ability to put some of your information some of your applications with an enterprise some of the public cloud some in different countries that matter for compliance reasons and to be able to move around between those different clouds in a very easy fashion so this money is going to that rd2 skills and to you know truly a global global launch so when you think about the sort of messaging for our HP Cloud what do you want customers to think about in the Helion brand and the HP Cloud yeah the number one thing is commitment to open standards so we are if you heard Martin Fink today talk about HP Labs and they're coming to open source we're all in on open source we believe it's the way to deliver innovation faster we can bring the market tech new technologies faster to customers so we're all into open source we are committed to the projects that matter to the next 20 years of IT and so that could emma has a real though we have to be to prove it with to say you know you can run our software on other hardware we think it'll be we'll have some optimal integrated solutions for you using our entire stack but this is about this is about eliminating vendor lock-in which is one of the biggest challenges at IT departments have faced in the last 20 years and so I think the commitment behind it open is at the core of our messaging so we should mention so Martin fake gave i really liked his presentation i have been safer I don't know for years that HP's got to get back to its roots right which are in fence right and I have not heard until today something that excited me about invention and we saw it today right now invention is not easy all we've talked about a lot that the previous administration cut cut cut by the bone right it takes a long time to turn that's Nisha but but we saw today think was put into that job for very particular reason I said about two things one it's a guy who's going to commercialize inventions answer the marketplace and two there's going to be a heavy systems focus so he basically showed a little leg on the machine which eventually is probably gonna be powering your clouds right he also announced HP is going to put forth a new open source operating system optimized for non-volatile memory not only a blank sheet of paper that they're going to work on with universities but also a Linux derivative stripped-down Linux driven and one for Android that was excited yeah I think what's great also is the cloud business actually falls under market so our our entire business worldwide in our cloud effort our rd on product development is all under martin who runs our CTO of our of our HP labs and when you look at the problems he's addressing with the machine and he's going after it's going after the massive scale challenges of the internet right and the massive scale challenge to the cloud and the day-to-day lose that we're all that we're all facing within the Internet of Things and so you know what's great is by being a part of the labs and being part of Martin's organization you know we're we're injecting that thinking into our cloud we're injecting it into our innovation and and you can see a road map here right you can see this this whole new architecture you talk about architecture that's been in existence since 1950 it was called the von Neumann architecture all the way to now and you know the world with copper at the core you know the world's in need of a new architecture and so it's great to be part of that there's that was a cool talk you talking about electrons photons and ions electrons compute compute autonomy photon photons communicate anions door right and that in essence is the future direction of where HP is going with the machine run a civ massive memory blowing away the volatility hierarchy blowing way ultimately slow spinning disks using memory store right as the platform for future systems I love it yeah he mentioned also but one thing that's close to my heart is the distributed mesh you saw that distributed mesh where we're different different hardware software combinations sit at different points of the you know the net work and they work together you know compute and data and that's really hybrid cloud you know hybrid cloud is putting compute workloads in certain areas and having data stored and distributed for maximum availability and doing that you know with self-service and doing that in a way that you know I see over nations can scale effectively yeah I think that you know as a marketing person you realize that customers want to know that your relevant for their future right and you know as much as I love things like store once it's not the future of computing Ryan comes out HP Labs this potentially is so that's got to have customers really excite this really the first time you've unveiled it right massively in the public scale right maybe you're talking you know that's why that's why i joined the HP i saw that coming out a few months ago and the the new style of IT thinking we're we're saying you know we're radically going to be at the core of helping IT transition from the old style very inward to a customer centric style 21 you know where you're delivering the customer you know consumer experience in the business world and i saw that with HP and it got me excited and i joined on board not upside yeah the other part that Martin mentioned I no idea of the power of HP Labs but the leveraging open source as well which are I probably not a tool in the arsenal not that long ago to really bring the power of a large communities engaged you can attack right specific problems and make that a core piece of the of the process yeah we think about it we've got thousands of the world's best developers right the Millennial developers these guys working all around the clock working on you know our core cloud future called OpenStack contributing to that right including our experts and then we're taking that and then bringing it to market you know into providing that twenty four seven support testing and hardening it you know doing the things need to do to help it enterprise feel comfortable with that decision you could never do that we could never do that and deliver that kind of innovation on our own just couldn't afford it we wouldn't be able to deliver on it you know these are the best minds of the world who are contributing this and we're we're all in nope in fact so you talked about we talked about what the brand is stand for you said open no lock-in can open source innovation occur at a pace with somebody who's got full control of a stack it's much faster actually I mean this is the you watch the innovation of OpenStack it's only what four years old we just at a four-year birthday of OpenStack already that's an entire cloud computing platform you've got databases service projects like trove you've got object storage projects like Swift and block storage like Senator you know all of these things are being worked on by people around the world you could never deliver and so what's happening is the pace of innovation with an open source project like OpenStack is like it's a hockey stick and and so I think yeah I think if we did this ourselves we or anyone else you would never be able to deliver the kind of innovation it's coming to market now we talked about some of the announcements you guys know why don't we actually go back a month right but Helion and then work through today we've got some HPC announcements you got the network you know for Helion right start with Helia so what's great about healing on is is it really brought together a lot of great products and services of the cloud that already existed and it took OpenStack and it was our first foray into the market with an OpenStack distribution and what's important actually is we have technology one called HP cloud system that is actually the most popular cloud platform right now private cloud platform on the planet about almost two thousand users right or two thousand companies third of the Fortune 100 right now using that technology so it is a proven capable platform used by big banks and others we're injecting OpenStack into that so that you can you can over time scale that out with new applications and so the launch really was about pulling all the pieces together pulling our support and services together and saying to a customer you know with confidence here's here's our cloud portfolio and here's how we can take you on a journey it's your pace and accelerate that journey take advantage of that cloud portfolio and that was really the launch month ago today and it discover I mean only a month later we've already done a number of great things but one is we brought out OpenStack the commercial version so we've launched community one you can download it thousands of downloads already the commercial versions coming up now and we announced pricing and what we are all about here this is what it really really important we are about accelerating the adoption of OpenStack throughout the enterprise we're about breaking down the barriers that have that have inhibited the proliferation of this great technology so one of those things today was the price point we announced 1000 for three dollars per year per server all in price point for HP Helion OpenStack and that's critical because this is a scale out a scale-out product you're going to have dozens hundreds maybe even thousands of these all around the world and so the price point is it's disruptive it's the lowest of the planet and and you know we said it's gonna be simple and easy we're not going to do all of this good better best packaging it's it's super easy and that's a big part of today the other part of today as we said you know what we're going to work with partners we're going to deploy this all around the world and that was the helium Network announcement along with ATT and the British Telecom and Intel and that's that's just huge for today now now helium comprises both on-premise in an HP public cloud correct that's right so talk about how that pricing works I mean I like what you're saying simple because cloud pricing is really complicated yeah so we use we wear that we're probably the largest user of OpenStack in production in production today without public cloud so we use it and people can consume services from that buy them on a on a you know on an as you go basis but with OpenStack which you what's really happening is people are able to deploy their own private clouds right they're able to a service provider could deploy and build their own public cloud so when I talk about the price point talking about a customer building their own cloud building their own cloud and a third party data center or in one of HP's 82 data centers and that that price point is is is you know it's easy easy to use you can predict it in your business model and feel comfortable about what it's going to cost you know two three four years out and so help me understand let's unpack that a little bit what am I getting for that fourteen hundred dollars per so you get the entire so this is what's amazing you get the entire cloud operating system called OpenStack right you get all of the projects now that are part of the OpenStack bill you're getting a top you're getting an object story it's it's a you know a la amazon s3 but in a box called Swift right with a swift API and you can build that and do that yourself now you can do that in a way that controls that gives you full control and full flexibility you get databases the service product you get a cute engine with cinder grizzly everything that's right no lad for the computer and so you get all of this in that box all of this and you can go deploy this and you can benefit now from the thousands of developers who are every six weeks putting out new code and innovative so okay so all the new innovations will fall under that umbrella and that's right at any price they choose to use you might say I'm just building a cloud storage environment you might choose to be heavy on Swift that's what you're doing but it is all inclusive and you can use the entire cloud platform or you can build a storage platform or databases a service platform that's a different model clearly what a customer is telling you about that yeah so they well they want they want the control and the flexibility of having their own platform for you know security reasons their own for compliance they want to put their data you know in their own centers but they're also saying I want to use public cloud some too and I like the idea that if OpenStack is here and OpenStack is here right same code bases I can fairly easily take a workload take an application to go from here to here and back and forth that kind of flexibility call interoperability and that's what's coming down the road with OpenStack underneath is something that does not exist today is everybody wants make sure I understand so I'm paid 1400 hours per server for that OpenStack instance on-premise and then when I want to access public cloud services I'm what you would pay an answer you might want to burst you might want to just go do you might have some peak demand he's burst out there you pay for and I would vote for money to make your partner of ours yep excellent now you also had some hpc announcements that's right so there's a number what's great is HP now is people are taking Helion OpenStack and they're putting it in their products are hpc group a high-performance computing group said hey we want to have a self-service mechanism we want to be able to scale out sap architecture people want in that in hpc so they put OpenStack inside their solution and launched it today and so it's you know OpenStack and better than hpc open hybrid simple to consume is what I'm that's right that's right it's ductable and predictable all right good Dave Lisa Marie wrote the book on this so this is great if you don't believe Bobby Lisa came I gave me this right gave me the books it's the OpenStack technology breaking the enterprise barrier you've got it you got it it's one of the best best reads on the planet right now yeah excellent all right so what does it go to the next level what is it I'm just buying computer part of just I'm just getting capacity if you just want capacity you might say you might just build a storage cloud yourself or you might use the our public cloud storage or with our Helia network our partners around the world be deploying OpenStack and you can buy it from them awesome all right we got to leave it there Bobby thanks so much for coming to the cube is a pleasure meantime take it all right keep it right to everybody John furrier is in the house he's back from San Francisco or San Jose good to have him back John keep right there but back with job fair in just a moment

(upbeat music) >> Hello, welcome to the Cube's coverage of International Women's Day 2023. I'm John Furrier, host of the CUBE series of profiles around leaders in the tech industry sharing their stories, advice, best practices, what they're doing in their jobs their vision of the future, and more importantly, passing it on and encouraging more and more networking and telling the stories that matter. Our next guest is a great executive leader talking about how to lead in challenging times. Krista Satterthwaite, who is Senior Vice President and GM of Mainstream Compute. Krista great to see you're Cube alumni. We've had you on before talking about compute power. And by the way, congratulations on your BPT and Black Professional Tech Network 2023 Black Tech Exec of the Year Award. >> Thank you very much. Appreciate it. And thanks for having me. >> I knew I liked you the first time we were doing interviews together. You were so smart and so on top of it. Thanks for coming on. >> No problem. >> All kidding aside, let's get into it. You know, one of the things that's coming out on these interviews is leadership is being showcased and there's a network effect happening in the industry and you're starting to see people look and hear stories that they may or may not have heard before or news stories are coming out. So, one of the things that's interesting is that also in the backdrop of post pandemic, there's been a turn in the industry a little bit, there's a little bit of headwind in certain areas, some tailwinds in cloud and other areas. Compute, your area is doing very well. It could be challenging. And as a leader, has the conversation changed? And where are you at right now in the network of folks you're working with? What's the mood? >> Yeah, so actually I, things are much better. Obviously we had a chip shortage last year. Things are much, much better. But I learned a lot when it came to going through challenging times and leadership. And I think when we talk to customers, a lot of 'em are in challenging situations. Sometimes it's budget, sometimes it's attracting and retaining talent and sometimes it's just demands because, it's really exciting that technology is behind everything. But that means the demands on IT are bigger than ever before. So what I find when it comes to challenging times is that there's really three qualities that are game changers when it comes to leading and challenging times. And the first one is positivity. People have to feel like there's a light at the end of the tunnel to make sure that, their attitudes stay up, that they stay working really really hard and they look to the leader for that. The second one is communication. And I read somewhere that communication is leadership. And we had a great example from our CEO Antonio Neri when the pandemic hit and everything shut down. He had an all employee meeting every week for a month and we have tens of thousands of employees. And then even after that month, we had 'em very regularly. But he wanted to make sure that everybody heard from, him his thoughts had all the updates, knew how their peers were doing, how we were helping customers. And I really learned a lot from that in terms of communicating and communicating more during tough times. And then I would say the third one is making sure that they are informed and they feel empowered. So I would say a leader who is able to do that really, really stands out in a challenging time. >> So how do you get yourself together? Obviously you the chip shortage everyone knows in the industry and for the folks not in the tech industry, it was an economic potential disaster, because you don't get the chips you need. You guys make servers and technology, chips power everything. If you miss a shipment, it could cause a lot of backlash. So Cisco had an earnings impact. It has impact to the business. When do you have that code red moment where it's like, okay, we have to kind of put the pause and go into emergency mode. And how do you handle that? >> Well, you know, it is funny 'cause when it, when we have challenges, I come to learn that people can look at challenges and hard work as a burden or a mission and they behave totally different. If they see it as a burden, then they're doing the bare minimum and they're pointing fingers and they're complaining and they're probably not getting a whole lot done. If they see it as a mission, then all of a sudden they're going above and beyond. They're working really hard, they're really partnering. And if it affects customers for HPE, obviously we, HPE is a very customer centric company, so everyone pays attention and tries to pitch in. But when it comes to a mission, I started thinking, what are the real ingredients for a mission? And I think it's important. I think it's, people feel like they can make an impact. And then I think the third one is that the goal is clear, even if the path isn't, 'cause you may have to pivot a lot if it's a challenge. And so when it came to the chip shortage, it was a mission. We wanted to make sure that we could ship to customers as quickly as possible. And it was a mission. Everybody pulled together. I learned how much our team could pull off and pull together through that challenge. >> And the consequences can be quantified in economics. So it's like the burn the boats example, you got to burn the boats, you're stuck. You got to figure out a solution. How does that change the demands on people? Because this is, okay, there's a mission it they're not, it's not normal. What are some of those new demands that arise during those times and how do you manage that? How do you be a leader? >> Yeah, so it's funny, I was reading this statement from James White who used to be the CEO of Jamba Juice. And he was talking about how he got that job. He said, "I think it was one thing I said that really convinced them that I was the right person." And what he said was something like, "I will get more out of people than nine out of 10 leaders on the planet." He said, "Because I will look at their strengths and their capabilities and I will play to their passions." and their capabilities and I will play their passions. and getting the most out people in difficult times, it is all about how much you can get out of people for their own sake and for the company's sake. >> That's great feedback. And to people watching who are early in their careers, leading is getting the best out of your team, attitude. Some of the things you mentioned. What advice would you give folks that are starting to get into the workforce, that are starting to get into that leadership track or might have a trajectory or even might have an innate ability that they know they have and they want to pursue that dream? >> Yeah so. >> What advice would you give them? >> Yeah, what I would say, I say this all the time that, for the first half of my career I was very job conscious, but I wasn't very career conscious. So I'd get in a role and I'd stay in that role for long periods of time and I'd do a good job, but I wasn't really very career conscious. And what I would say is, everybody says how important risk taking is. Well, risk taking can be a little bit of a scary word, right? Or term. And the way I see it is give it a shot and see what happens. You're interested in something, give it a shot and see what happens. It's kind of a less intimidating way of looking at risk because even though I was job conscious, and not career conscious, one thing I did when people asked me to take something on, hey Krista, would you like to take on more responsibility here? The answer was always yes, yes, yes, yes. So I said yes because I said, hey I'll give it a shot and see what happens. And that helped me tremendously because I felt like I am giving it a try. And the more you do that, the the better it is. >> It's great. >> And actually the the less scary it is because you do that, a few times and it goes well. It's like a muscle that builds. >> It's funny, a woman executive was on the program. I said, the word balance comes up a lot. And she stopped and said, "Let's just talk about balance for a second." And then she went contrarian and said, "It's about not being unbalanced. It's about being, taking a chance and being a little bit off balance to put yourself outside your comfort zone to try new things." And then she also came up and followed and said, "If you do that alone, you increase your risk. But if you do it with people, a team that you trust and you're authentic and you're vulnerable and you're communicating, that is the chemistry." And that was a really good point. What's your reaction? 'Cause you were talking about authentic conversations good communications with Antonio. How does someone get, feel, find that team and do you agree with it? And what was your, how would you react to that? >> Yes, I agree with that. And when it comes to being authentic, that's the magic and when someone isn't, if someone's not really being themselves, it's really funny because you can feel it, you can sense it. There's kind of a wall between you and them. And over time people won't be able to put their finger on it, but they'll feel a distance from you. But when you're authentic and you share who you are, what you find is you find things in common with other people. 'Cause you're sharing more of who you are and it's like, oh, I do that too. Oh, I'm interested in that too. And build the bonds between people and the authenticity. And that's what people crave. They want people to be authentic and people can tell when you're authentic and when you're not. >> Is managing and leading through a crisis a born talent or can you learn it? >> Oh, definitely learned. I think that we're born knowing nothing and I once read people are nurtured into greatness and I think that's true. So yeah, definitely learned. >> What are some examples that can come out of a tough time as folks may look at a crisis and be shy away from it? How do they lean into it? What advice would you give folks? How do you handle it? I mean, everyone's got different personality. Okay, they get to a position but stepping through that door. >> Yeah, well, I do this presentation called, "10 things I Wish I Knew Earlier in my Career." And one of those things is about the growth mindset and the growth mindset. There's a book called "Mindset" by Carol Dweck and the growth mindset is all about learning and not always having to know everything, but really the winning is in the learning. And so if you have a growth mindset it makes you feel better about everything because you can't lose. You're winning because you're learning. So when I've learned that, I started looking at things much differently. And when it comes to going through tough times, what I find is you're exercising muscles that you didn't even know you had, which makes you stronger when the crisis is over, obviously. And I also feel like you become a lot a much more creative when you're in challenging times. You're forced to do things that you hadn't had to do before. And it also bonds the team. It's almost like going through bootcamp together. When you go through a challenge together it bonds you for life. >> I mean, you could have bonding, could be trauma bonding or success bonding. People love to be on the success side because that's positive and that's really the key mindset. You're always winning if you have that attitude. And learnings is also positive. So it's not, it's never a failure unless you make it. >> That's right, exactly. As long as you learn from it. And that's the name of the game. So, learning is the goal. >> So I have to ask you, on your job now, you have a really big responsibility HPE compute and big division. What's the current mindset that you have right now in your career, where you're at? What are some of the things on your mind that you think about? We had other, other seniors leaders say, hey, you know I got the software as my brain and the hardware's my body. I like to keep software and hardware working together. What is your current state of your career and how you looking at it, what's next and what's going on in your mind right now? >> Yeah, so for me, I really want to make sure that for my team we're nurturing the next generation of leadership and that we're helping with career development and career growth. And people feel like they can grow their careers here. Luckily at HPE, we have a lot of people stay at HPE a long time, and even people who leave HPE a lot of times they come back because the culture's fantastic. So I just want to make sure I'm contributing to that culture and I'm bringing up the next generation of leaders. >> What's next for you? What are you looking at from a career personal standpoint? >> You know, it's funny, I, I love what I'm doing right now. I'm actually on a joint venture board with H3C, which is HPE Joint Venture Company. And so I'm really enjoying that and exploring more board service opportunities. >> You have a focus of good growth mindset, challenging through, managing through tough times. How do you stay focused on that North star? How do you keep the reinforcement of the mission? How do you nurture the team to greatness? >> Yeah, so I think it's a lot of clarity, providing a lot of clarity about what's important right now. And it goes back to some of the communication that I mentioned earlier, making sure that everybody knows where the North Star is, so everybody's focused on the same thing, because I feel like with the, I always felt like throughout my career I was set up for success if I had the right information, the right guidance and the right goals. And I try to make sure that I do that with my team. >> What are some of the things that you could share as we wrap up here for the folks watching, as the networks increase, as the stories start to unfold more and more on digital like we're doing here, what do you hope people walk away with? What's working, what needs work, and what is some things that people aren't talking about that should be discussed publicly? >> Do you mean from a career standpoint or? >> For career? For growing into tech and into leadership positions. >> Okay. >> Big migration tech is now a wide field. I mean, when I grew up, broke into the eighties, it was computer science, software engineering, and three degrees in engineering, right? >> I see huge swath of AI coming. So many technical careers. There's a lot more women. >> Yeah. And that's what's so exciting about being in a technical career, technical company, is that everything's always changing. There's always opportunity to learn something new. And frankly, you know, every company is in the business of technology right now, because they want to closer to their customers. Typically, they're using technology to do that. Everyone's digitally transforming. And so what I would say is that there's so much opportunity, keep your mind open, explore what interests you and keep learning because it's changing all the time. >> You know I was talking with Sue, former HP, she's on a lot of boards. The balance at the board level still needs a lot of work and the leaderships are getting better, but the board at the seats at the table needs work. Where do you see that transition for you in the future? Is that something on your mind? Maybe a board seat? You mentioned you're on a board with HPE, but maybe sitting on some other boards? Any, any? >> Yes, actually, actually, we actually have a program here at HPE called the Board Ready Now program that I'm a part of. And so HPE is very supportive of me exploring an independent board seat. And so they have some education and programming around that. And I know Sue well, she's awesome. And so yes, I'm looking into those opportunities right now. >> She advises do one no more than two. The day job. >> Yeah, I would only be doing one current job that I have. >> Well, kris, it was great to chat with you about these topics and leadership and challenging times. Great masterclass, great advice. As SVP and GM of mainstream compute for HPE, what's going on in your job these days? What's the most exciting thing happening? Share some of your work situations. >> Sure, so the most exciting thing happening right now is HPE Gen 11, which we just announced and started shipping, brings tremendous performance benefit, has an intuitive operating experience, a trusted security by design, and it's optimized to run workloads so much faster. So if anybody is interested, they should go check it out on hpe.com. >> And of course the CUBE will be at HPE Discover. We'll see you there. Any final wisdom you'd like to share as we wrap up the last minute here? >> Yeah, so I think the last thing I'll say is that when it comes to setting your sights, I think, expecting it, good things to happen usually happens when you believe you deserve it. So what happens is you believe you deserve it, then you expect it and you get it. And so sometimes that's about making sure you raise your thermostat to expect more. And I always talk about you don't have to raise it all up at once. You could do that incrementally and other people can set your thermostat too when they say, hey, you should be, you should get a level this high or that high, but raise your thermostat because what you expect is what you get. >> Krista, thank you so much for contributing to this program. We're going to do it quarterly. We're going to do getting more stories out there, so we'll have you back and if you know anyone with good stories, send them our way. And congratulations on your BPTN Tech Executive of the Year award for 2023. Congratulations, great prize there and great recognition for your hard work. >> Thank you so much, John, I appreciate it. >> Okay, this is the Cube's coverage of National Woodman's Day. I'm John Furrier, stories from the front lines, management ranks, developers, all there, global coverage of international events with theCUBE. Thanks for watching. (soft music)

(soft music) >> Announcer: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Spain, everybody. We're here at the Fira in MWC23. Is just an amazing day. This place is packed. They said 80,000 people. I think it might even be a few more walk-ins. I'm Dave Vellante, Lisa Martin is here, David Nicholson. But right now we have the Analyst Hot Takes with three friends of theCUBE. Chris Lewis is back again with me in the co-host seat. Zeus Kerravala, analyst extraordinaire. Great to see you, Z. and Sarbjeet SJ Johal. Good to see you again, theCUBE contributor. And that's my new name for him. He says that is his nickname. Guys, thanks for coming back on. We got the all male panel, sorry, but it is what it is. So Z, is this the first time you've been on it at MWC. Take aways from the show, Hot Takes. What are you seeing? Same wine, new bottle? >> In a lot of ways, yeah. I mean, I was talking to somebody this earlier that if you had come from like MWC five years ago to this year, a lot of the themes are the same. Telco transformation, cloud. I mean, 5G is a little new. Sustainability is certainly a newer theme here. But I think it highlights just the difficulty I think the telcos have in making this transformation. And I think, in some ways, I've been unfair to them in some degree 'cause I've picked on them in the past for not moving fast enough. These are, you know, I think these kind of big transformations almost take like a perfect storm of things that come together to happen, right? And so, in the past, we had technologies that maybe might have lowered opex, but they're hard to deploy. They're vertically integrated. We didn't have the software stacks. But it appears today that between the cloudification of, you know, going to cloud native, the software stacks, the APIs, the ecosystems, I think we're actually in a position to see this industry finally move forward. >> Yeah, and Chris, I mean, you have served this industry for a long time. And you know, when you, when you do that, you get briefed as an analyst, you actually realize, wow, there's a lot of really smart people here, and they're actually, they have challenges, they're working through it. So Zeus was saying he's been tough on the industry. You know, what do you think about how the telcos have evolved in the last five years? >> I think they've changed enormously. I think the problem we have is we're always looking for the great change, the big step change, and there is no big step change in a way. What telcos deliver to us as individuals, businesses, society, the connectivity piece, that's changed. We get better and better and more reliable connectivity. We're shunting a load more capacity through. What I think has really changed is their attitude to their suppliers, their attitude to their partners, and their attitude to the ecosystem in which they play. Understanding that connectivity is not the end game. Connectivity is part of the emerging end game where it will include storage, compute, connect, and analytics and everything else. So I think the realization that they are not playing their own game anymore, it's a much more open game. And some things they will continue to do, some things they'll stop doing. We've seen them withdraw from moving into adjacent markets as much as we used to see. So a lot of them in the past went off to try and do movies, media, and a lot went way way into business IT stuff. They've mainly pulled back from that, and they're focusing on, and let's face it, it's not just a 5G show. The fixed environment is unbelievably important. We saw that during the pandemic. Having that fixed broadband connection using wifi, combining with cellular. We love it. But the problem as an industry is that the users often don't even know the connectivity's there. They only know when it doesn't work, right? >> If it's not media and it's not business services, what is it? >> Well, in my view, it will be enabling third parties to deliver the services that will include media, that will include business services. So embedding the connectivity all the way into the application that gets delivered or embedding it so the quality mechanism deliver the gaming much more accurately or, I'm not a gamer, so I can't comment on that. But no, the video quality if you want to have a high quality video will come through better. >> And those cohorts will pay for that value? >> Somebody will pay somewhere along the line. >> Seems fuzzy to me. >> Me too. >> I do think it's use case dependent. Like you look at all the work Verizon did at the Super Bowl this year, that's a perfect case where they could have upsold. >> Explain that. I'm not familiar with it. >> So Verizon provided all the 5G in the Super Bowl. They provided a lot of, they provided private connectivity for the coaches to talk to the sidelines. And that's a mission critical application, right? In the NFL, if one side can't talk, the other side gets shut down. You can't communicate with the quarterback or the coaches. There's a lot of risk at that. So, but you know, there's a case there, though, I think where they could have even made that fan facing. Right? And if you're paying 2000 bucks to go to a game, would you pay 50 bucks more to have a higher tier of bandwidth so you can post things on social? People that go there, they want people to know they were there. >> Every football game you go to, you can't use your cell. >> Analyst: Yeah, I know, right? >> All right, let's talk about developers because we saw the eight APIs come out. I think ISVs are going to be a big part of this. But it's like Dee Arthur said. Hey, eight's better than zero, I guess. Okay, so, but so the innovation is going to come from ISVs and developers, but what are your hot takes from this show and now day two, we're a day and a half in, almost two days in. >> Yeah, yeah. There's a thing that we have talked, I mentioned many times is skills gravity, right? Skills have gravity, and also, to outcompete, you have to also educate. That's another theme actually of my talks is, or my research is that to puts your technology out there to the practitioners, you have to educate them. And that's the only way to democratize your technology. What telcos have been doing is they have been stuck to the proprietary software and proprietary hardware for too long, from Nokia's of the world and other vendors like that. So now with the open sourcing of some of the components and a few others, right? And they're open source space and antenna, you know? Antennas are becoming software now. So with the invent of these things, which is open source, it helps us democratize that to the other sort of skirts of the practitioners, if you will. And that will bring in more applications first into the IOT space, and then maybe into the core sort of California, if you will. >> So what does a telco developer look like? I mean, all the blockchain developers and crypto developers are moving into generative AI, right? So maybe those worlds come together. >> You'd like to think though that the developers would understand everything's network centric today. So you'd like to think they'd understand that how the network responds, you know, you'd take a simple app like Zoom or something. If it notices the bandwidth changes, it should knock down the resolution. If it goes up it, then you can add different features and things and you can make apps a lot smarter that way. >> Well, G2 was saying today that they did a deal with Mercedes, you know this probably better than I do, where they're going to embed WebEx in the car. And if you're driving, it'll shut off the camera. >> Of course. >> I'm like, okay. >> I'll give you a better example though. >> But that's my point. Like, isn't there more that we can do? >> You noticed down on the SKT stand the little helicopter. That's a vertical lift helicopter. So it's an electric vertical lift helicopter. Just think of that for a second. And then think of the connectivity to control that, to securely control that. And then I was recently at an event with Zeus actually where we saw an air traffic control system where there was no people manning the tower. It was managed by someone remotely with all the cameras around them. So managing all of those different elements, we call it IOT, but actually it's way more than what we thought of as IOT. All those components connecting, communicating securely and safely. 'Cause I don't want that helicopter to come down on my head, do you? (men laugh) >> Especially if you're in there. (men laugh) >> Okay, so you mentioned sustainability. Everybody's talking about power. I don't know if you guys have a lot of experience around TCO, but I'm trying to get to, well, is this just because energy costs are so high, and then when the energy becomes cheap again, nobody's going to pay any attention to it? Or is this the real deal? >> So one of the issues around the, if we want to experience all that connectivity locally or that helicopter wants to have that connectivity, we have to ultimately build denser, more reliable networks. So there's a CapEx, we're going to put more base stations in place. We need more fiber in the ground to support them. Therefore, the energy consumption will go up. So we need to be more efficient in the use of energy. Simple as that. >> How much of the operating expense is energy? Like what percent of it? Is it 10%? Is it 20%? Is it, does anybody know? >> It depends who you ask and it depends on the- >> I can't get an answer to that. I mean, in the enterprise- >> Analyst: The data centers? >> Yeah, the data centers. >> We have the numbers. I think 10 to 15%. >> It's 10 to 12%, something like that. Is it much higher? >> I've got feeling it's 30%. >> Okay, so if it's 30%, that's pretty good. >> I do think we have to get better at understanding how to measure too. You know, like I was talking with John Davidson at Sysco about this that every rev of silicon they come out with uses more power, but it's a lot more dense. So at the surface, you go, well, that's using a lot more power. But you can consolidate 10 switches down to two switches. >> Well, Intel was on early and talking about how they can intelligently control the cores. >> But it's based off workload, right? That's the thing. So what are you running over it? You know, and so, I don't think our industry measures that very well. I think we look at things kind of boxed by box versus look at total consumption. >> Well, somebody else in theCUBE was saying they go full throttle. That the networks just say just full throttle everything. And that obviously has to change from the power consumption standpoint. >> Obviously sustainability and sensory or sensors from IOT side, they go hand in hand. Just simple examples like, you know, lights in the restrooms, like in public areas. Somebody goes in there and just only then turns. The same concept is being applied to servers and compute and storage and every aspects and to networks as well. >> Cell tower. >> Yeah. >> Cut 'em off, right? >> Like the serverless telco? (crosstalk) >> Cell towers. >> Well, no, I'm saying, right, but like serverless, you're not paying for the compute when you're not using it, you know? >> It is serverless from the economics point of view. Yes, it's like that, you know? It goes to the lowest level almost like sleep on our laptops, sleep level when you need more power, more compute. >> I mean, some of that stuff's been in networking equipment for a long time, it just never really got turned on. >> I want to ask you about private networks. You wrote a piece, Athenet was acquired by HPE right after Dell announced a relationship with Athenet, which was kind of, that was kind of funny. And so a good move, good judo move by by HP. I asked Dell about it, and they said, look, we're open. They said the right things. We'll see, but I think it's up to HP. >> Well, and the network inside Dell is. >> Yeah, okay, so. Okay, cool. So, but you said something in that article you wrote on Silicon Angle that a lot of people feel like P5G is going to basically replace wireless or cannibalize wireless. You said you didn't agree with that. Explain why? >> Analyst: Wifi. >> Wifi, sorry, I said wireless. >> No, that's, I mean that's ridiculous. Pat Gelsinger said that in his last VMware, which I thought was completely irresponsible. >> That it was going to cannibalize? >> Cannibalize wifi globally is what he said, right? Now he had Verizon on stage with him, so. >> Analyst: Wifi's too inexpensive and flexible. >> Wifi's cheap- >> Analyst: It's going to embed really well. Embedded in that. >> It's reached near ubiquity. It's unlicensed. So a lot of businesses don't want to manage their own spectrum, right? And it's great for this, right? >> Analyst: It does the job. >> For casual connectivity. >> Not today. >> Well, it does for the most part. Right now- >> For the most part. But never at these events. >> If it's engineered correctly, it will. Right? Where you need private 5G is when reliability is an absolute must. So, Chris, you and I visited the Port of Rotterdam, right? So they're putting 5G, private 5G there, but there's metal containers everywhere, right? And that's going to disrupt it. And so there are certain use cases where it makes sense. >> I've been in your basement, and you got some pretty intense equipment in there. You have private 5G in there. >> But for carpeted offices, it does not make sense to bring private. The economics don't make any sense. And you know, it runs hot. >> So where's it going to be used? Give us some examples of where we should be looking for. >> The early ones are obviously in mining, and you say in ports, in airports. It broadens cities because you've got so many moving parts in there, and always think about it, very expensive moving parts. The cranes in the port are normally expensive piece of kits. You're moving that, all that logistics around. So managing that over a distance where the wifi won't work over the distance. And in mining, we're going to see enormous expensive trucks moving around trying to- >> I think a great new use case though, so the Cleveland Browns actually the first NFL team to use it for facial recognition to enter the stadium. So instead of having to even pull your phone out, it says, hey Dave Vellante. You've got four tickets, can we check you all in? And you just walk through. You could apply that to airports. You could do put that in a hotel. You could walk up and check in. >> Analyst: Retail. >> Yeah, retail. And so I think video, realtime video analytics, I think it's a perfect use case for that. >> But you don't need 5G to do that. You could do that through another mechanism, couldn't you? >> You could do wire depending on how mobile you want to do it. Like in a stadium, you're pulling those things in and out all the time. You're moving 'em around and things, so. >> Yeah, but you're coming in at a static point. >> I'll take the contrary view here. >> See, we can't even agree on that. (men laugh) >> Yeah, I love it. Let's go. >> I believe the reliability of connection is very important, right? And the moving parts. What are the moving parts in wifi? We have the NIC card, you know, the wifi card in these suckers, right? In a machine, you know? They're bigger in size, and the radios for 5G are smaller in size. So neutralization is important part of the whole sort of progress to future, right? >> I think 5G costs as well. Yes, cost as well. But cost, we know that it goes down with time, right? We're already talking about 60, and the 5G stuff will be good. >> Actually, sorry, so one of the big boom areas at the moment is 4G LTE because the component price has come down so much, so it is affordable, you can afford to bring it all together. People don't, because we're still on 5G, if 5G standalone everywhere, you're not going to get a consistent service. So those components are unbelievably important. The skillsets of the people doing integration to bring them all together, unbelievably important. And the business case within the business. So I was talking to one of the heads of one of the big retail outlets in the UK, and I said, when are you going to do 5G in the stores? He said, well, why would I tear out all the wifi? I've got perfectly functioning wifi. >> Yeah, that's true. It's already there. But I think the technology which disappears in front of you, that's the best technology. Like you don't worry about it. You don't think it's there. Wifi, we think we think about that like it's there. >> And I do think wifi 5G switching's got to get easier too. Like for most users, you don't know which is better. You don't even know how to test it. And to your point, it does need to be invisible where the user doesn't need to think about it, right? >> Invisible. See, we came back to invisible. We talked about that yesterday. Telecom should be invisible. >> And it should be, you know? You don't want to be thinking about telecom, but at the same time, telecoms want to be more visible. They want to be visible like Netflix, don't they? I still don't see the path. It's fuzzy to me the path of how they're not going to repeat what happened with the over the top providers if they're invisible. >> Well, if you think about what telcos delivers to consumers, to businesses, then extending that connectivity into your home to help you support secure and extend your connection into Zeus's basement, whatever it is. Obviously that's- >> His awesome setup down there. >> And then in the business environment, there's a big change going on from the old NPLS networks, the old rigid structures of networks to SD1 where the control point is moved outside, which can be under control of the telco, could be under the control of a third party integrator. So there's a lot changing. I think we obsess about the relative role of the telco. The demand is phenomenal for connectivity. So address that, fulfill that. And if they do that, then they'll start to build trust in other areas. >> But don't you think they're going to address that and fulfill that? I mean, they're good at it. That's their wheelhouse. >> And it's a 1.6 trillion market, right? So it's not to be sniffed at. That's fixed on mobile together, obviously. But no, it's a big market. And do we keep changing? As long as the service is good, we don't move away from it. >> So back to the APIs, the eight APIs, right? >> I mean- >> Eight APIs is a joke actually almost. I think they released it too early. The release release on the main stage, you know? Like, what? What is this, right? But of course they will grow into hundreds and thousands of APIs. But they have to spend a lot of time and effort in that sort of context. >> I'd actually like to see the GSMA work with like AWS and Microsoft and VMware and software companies and create some standardization across their APIs. >> Yeah. >> I spoke to them yes- >> We're trying to reinvent them. >> Is that not what they're doing? >> No, they said we are not in the business of a defining standards. And they used a different term, not standard. I mean, seriously. I was like, are you kidding me? >> Let's face it, there aren't just eight APIs out there. There's so many of them. The TM forum's been defining when it's open data architecture. You know, the telcos themselves are defining them. The standards we talked about too earlier with Danielle. There's a lot of APIs out there, but the consistency of APIs, so we can bring them together, to bring all the different services together that will support us in our different lives is really important. I think telcos will do it, it's in their interest to do it. >> All right, guys, we got to wrap. Let's go around the horn here, starting with Chris, Zeus, and then Sarbjeet, just bring us home. Number one hot take from Mobile World Congress MWC23 day two. >> My favorite hot take is the willingness of all the participants who have been traditional telco players who looked inwardly at the industry looking outside for help for partnerships, and to build an ecosystem, a more open ecosystem, which will address our requirements. >> Zeus? >> Yeah, I was going to talk about ecosystem. I think for the first time ever, when I've met with the telcos here, I think they're actually, I don't think they know how to get there yet, but they're at least aware of the fact that they need to understand how to build a big ecosystem around them. So if you think back like 50 years ago, IBM and compute was the center of everything in your company, and then the ecosystem surrounded it. I think today with digital transformation being network centric, the telcos actually have the opportunity to be that center of excellence, and then build an ecosystem around them. I think the SIs are actually in a really interesting place to help them do that 'cause they understand everything top to bottom that I, you know, pre pandemic, I'm not sure the telcos were really understand. I think they understand it today, I'm just not sure they know how to get there. . >> Sarbjeet? >> I've seen the lot of RN demos and testing companies and I'm amazed by it. Everything is turning into software, almost everything. The parts which are not turned into software. I mean every, they will soon. But everybody says that we need the hardware to run something, right? But that hardware, in my view, is getting miniaturized, and it's becoming smaller and smaller. The antennas are becoming smaller. The equipment is getting smaller. That means the cost on the physicality of the assets is going down. But the cost on the software side will go up for telcos in future. And telco is a messy business. Not everybody can do it. So only few will survive, I believe. So that's what- >> Software defined telco. So I'm on a mission. I'm looking for the monetization path. And what I haven't seen yet is, you know, you want to follow the money, follow the data, I say. So next two days, I'm going to be looking for that data play, that potential, the way in which this industry is going to break down the data silos I think there's potential goldmine there, but I haven't figured out yet. >> That's a subject for another day. >> Guys, thanks so much for coming on. You guys are extraordinary partners of theCUBE friends, and great analysts and congratulations and thank you for all you do. Really appreciate it. >> Analyst: Thank you. >> Thanks a lot. >> All right, this is a wrap on day two MWC 23. Go to siliconangle.com for all the news. Where Rob Hope and team are just covering all the news. John Furrier is in the Palo Alto studio. We're rocking all that news, taking all that news and putting it on video. Go to theCUBE.net, you'll see everything on demand. Thanks for watching. This is a wrap on day two. We'll see you tomorrow. (soft music)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright upbeat music) >> Good morning everyone. Welcome to theCUBE. We are live at MWC '23 in Barcelona, Spain. I'm Lisa Martin, and I'm going to have a great conversation next with our esteemed CUBE analyst, Dave Nicholson. Dave, great to have you here. Great to be working this event with you. >> Good to be here with you, Lisa. >> So there are, good to be here with you and about 80,000 people. >> Dave: That's right. >> Virtually and and physically. And it's jammed in, and this is the most jammed show I've seen in years. >> Dave: It's crazy. >> So much going on in the telecom industry. What are some of your expectations for what you're going to hear and see at this year's event? >> So, I expect to hear a lot about 5G. Specifically 5G private networks, and the disaggregation of the hardware and software stacks that have driven telecom for decades. So we're at this transition into 5G. From a consumer perspective, we feel like, oh well 5G has been around for years. In terms of where it's actually been deployed, we're just at the beginning stages of that. >> Right, right. Talk about the changing of the stack. You know, the disaggregation. Why now is it too late? And what are the advantages? That it's going to enable telcos to move faster, I imagine? >> Yeah, so it's really analogous to what we see in the general IT industry that we cover so much. The move to cloud, sometimes you're gaining performance. You're always gaining agility and flexibility. A big concern of the legacy telecom providers is going to be maintaining availability, reliability against a backdrop of increasing agility in the direction that they want to go. So that's going to be the conversation. It's going to be the old school folks, who are interested in maintaining primarily availability and performance, excuse me, contrasted with the open source, OpenStack providers, who are going to be saying, hey this is a path to the future. Without that path to the future, things will stagnate. >> Talk about some of those OpenStack providers. I imagine those are some of the folks that we know quite well? >> Sure, sure. Yeah, so someone like Dell, for example. They're perfectly positioned at this sort of crossroads, because Dell has been creating "cloud stacks," that will live sometimes on-premises. And those stacks of infrastructure, based on cots, commercial off-the-shelf components, integrated within an ecosystem can live at the edge, at literally the base of transmitter towers. So when you think about this whole concept of RAN or a radio access network, think of a cellular tower with an antenna and a transmitter. The transmitter might live on that tower, or it might live in pieces at the base of the tower. But there's always at that base of the tower, forget about the acronyms, it's a box of stuff, teleco stuff. All of these things historically have been integrated into single packages. >> Right. >> For good reason. >> Right. >> Think back to a mainframe, where it was utterly, absolutely reliable. We moved, in the general IT space, from the era of the mainframe to the world of client server, through virtualization, containerization. That exact transition is happening in the world of telecom right now. >> Why is it finally happening now? It seems a bit late, given that in our consumer lives, we have this expectation that we could be mobile 24 by seven. >> Right. Well it's because, first of all, we get mad if a call doesn't go through. How often, when you make, when you try to make a cellular call or when you try to send a text, how often does it not work? >> I can count on one hand. >> Right, rarely. >> Right. >> Now, you may be in an area that has spotty coverage. But when you're in an area where you have coverage it just works all of the time. And you expect it to work all of the time. And the miracle of the services that have been delivered to us over the last decade has really kind of blunted the need for next generation stuff. Well, we're at this transition point. And 5G as a technology enables so much more bandwidth. Think of it as, you know, throughput bandwidth latency. It allows the kind of performance characteristics so that things can be delivered that couldn't be delivered in the past. Virtual reality, augmented reality. We're already seeing you know 4K data streams to our phones. So, it's sort of lagged because of our expectations for absolute, rock solid, reliability. >> Yeah. >> The technology is ahead of that area now. And so this question is how do you navigate from utter reliability to awesome openness without sacrificing performance and reliability? >> Well, and also from a stack perspective, from looking at desegregation, and the opportunities there are for the telcos, but also the public cloud providers, are they friends, are they foes? What's the relationship like? >> They're going to be frenemies. >> Lisa: Frenemies? >> Yeah, coopetition is going to be the word of the day again. Yeah because when you think of a cloud, most people automatically think off-premises. >> Lisa: Yes. >> Maybe they even think automatically you know, hyper scale or Azure, GCP, AWS. In this case, it really is a question of cloud as an operating model. Cloud facilitating agility, cloud adopting cloud native architecture from a software perspective, so that you can rapidly deploy net new capabilities into an environment. You can't do that with proprietary closed systems that might use a waterfall development process and take years to develop. You and I have covered the Kubernetes world pretty closely. And what's the big thing that we hear constantly? The hunger, the thirst for human resources, >> Right. >> people who can actually work in this world of containerization. >> Yes, yes. >> Well guess what? In the macroeconomic environment, a lot of folks in the IT space have recently been disrupted. This is a place to look, if you have that skillset. Look at the telecom space, because they need people who are forward thinking in the era of cloud. But this concept of cloud is really, it's going to be, the telcos are both competing and partnering with what we think of as the traditional, hyper scale public cloud providers. >> And what do you think, one of the things that we know at MWC '23 is virtually every industry is represented here. Every vertical is here, whether it's a sports arena, or a retail outlet, or a manufacturer. Every organization, every industry needs to have networks that deliver what they need to do but also enable them to move faster and deliver what the end user wants. What are some of the industries that you think are really ripe for this disruption? And the ability to use private 5G networks, for example? >> Well, so it's interesting, you mentioned private 5G networks. I think a good example of the transition that's underway is this, the move to 4K video. So, you get a high definition television. The first time you see a 720p TV, it's like oh my gosh, amazing. Then we get 1080p, then it's 4K. People get 4K TVs, they bring them home, and there's no content. >> No. >> The first content, was it from your cable provider? No. >> Yeah. >> Was it over the air? ABC, NBC, CBS? No, it was YouTube. YouTube delivered the first reliable 4K content, over the internet. Similarly, everything comes to us now to our mobile devices. So we're not accessing the world around us so much from a desktop or even a laptop. It's mobile. So if you want to communicate with a customer, it's mobile. If you're creating a private 5G network, you now are standing something up that is net new in a greenfield environment. And you can deploy agility and functionality that the large scale telecom providers can't, because of the massive investment they might need. So the irony is, you have a factory that sits on 20 acres and you have folks traveling around, if you create a private 5G network, it might become, it might be more feature rich than what your employees are used to being able to access through their personal mobile devices. >> Wow. >> Yeah, because you're starting net new, you have the luxury of starting greenfield, as opposed to the responsibility and legacy for supporting a massive system that exists already. >> So then, what's in it for the existing incumbent telcos from an advantage opportunity perspective? Because you mentioned frenemies, coopetition. >> Right. >> There's irony there, as you talked about. >> Right, well you could look at it as either opportunity or headache. And it's both. Because they have very, very real SLAs that they need to meet. >> Right. >> Very, very real expectations that have been set in terms of reliability, availability, and performance. So they can't slip off of that. Making that transition is, I think going to be driven by economics, because the idea of having things be open means that there's competition for every part of the stack. There will be a critical role for integration vendors. Folks like Dell, and the ecosystems that they're creating around this will be critical, because often you would prefer to have one back to pat or one throat to choke instead of many. So, you still want to have that centralized entity to go to when something goes wrong. >> Right. >> Or when you want to implement something new. So, for the incumbents, it's a classic example of what you do in the face of disruption. How do you leverage technology? In my role as adjunct faculty at the Wharton CTO Academy, we talk about the CTO mindset. And the idea that your role is to leverage technology, in the service of your organization's mission, whatever that organization and mission is. So from a telecom provider perspective, they need to stay on top of this. >> Yes. >> Or they will be disrupted. >> Right. >> It's fascinating to think of how this disruption's taking place. >> Lisa: They have no choice, if they want to survive. >> No, yeah they have no choice. >> Lisa: In the next few years. >> They have no choice, but they'll come along, kicking and screaming. I'm sure if you had someone sitting here in the industry, they'd say, well, no, no, no, no, no. >> Yeah, of course. >> We love it! It's like, yeah, well but you're going to have to make some painful changes to adopt these things. >> What are some of the opportunities for those folks like Dell that you mentioned, in terms of coming in, being able to disrupt that stack, open things up? Great opportunities for the Dells, and other similar organizations to really start gaining a bigger foothold in the telecom industry, I imagine. >> Well, I look at it through the lens of sort of traditional IT and the transitions that we've been watching for the last couple of decades. It's exactly the same. I mean you, there is a parallel. It is like coming out of the mainframe era to the client server era. So, you know, we went in that transition, it was mainframe operating systems, very, very closed systems to more slightly opened. You know, the worlds of SUN and SGI and HP, and the likes, transitioned to kind of Microsoft based software running with like Dell hardware. >> Yeah. >> And, that stack is now getting deployed into one of the remaining legacy environments which is the telco space. So, the opportunity for Dell is pretty massive because on some fronts they're competing with the move to proper off-premises public cloud. >> Right. >> In this case, they are the future for telecom as opposed to sort of representing legacy, compared to some of the other cloud opportunities that are out there. >> So ultimately, what does a modern telecom network look like? I imagine, cloud native? Distributed? >> Yeah, yeah. So, traditionally, like I said, you've got the tower and the transmitters and the computer hardware that's running it. Those are then networked together. So you can sort of think of it as leaves on a twig, on a branch, on a tree. Eventually it gets into a core network, where there is terrestrial line communication and or communication up to satellites. And that's all been humming along just fine, making the transition from 3G to 4G to 5G. But, the real transition from a cloud perspective is this idea that you're taking these proprietary systems, disaggrevating, disaggrevating them and disaggregating them, carving them up into pieces where now you're introducing virtualization. So there's a VMware play here. Some things are virtualized using that stack. I think more often we're going to be talking about containerized and truly cloud native stacks. So instead of having the proprietary stack, where all the hardware and software is designed together. Now you're going to have Dell servers running some execution layer, orchestration layer, for cloud native, containerized applications and microservices. And that's the way things are going to be developed. >> And who, from a stakeholder perspective is involved here? 'Cause one of the things that I'm hearing is with this disaggregation of the staff, which is a huge change, what you're articulated, that's already happened at enterprise IT, change management is a hard thing to do. If they want to be successful, and well not just survive, they want to thrive. I'm just imagining, who are the stakeholders that are involved in having to push those incumbents to make these decisions, to move faster, to become agile, to compete. >> So, I remember when VMware had the problem that anytime they suggested introducing a hypervisor to to virtualize a physical machine and then run software on top or an operating system on top, and then applications, the big question the customer would have was, well is Microsoft going to support that? What if I can't get support from Microsoft? I dunno if I can do this. Within about a year of those conversations taking place, the question was, can I run this in my production environment? So it was, can I get support in my test environment too? Can I please run this in production? >> Yeah. >> And so, there are folks in the kind of legacy telecom world who are going to be afraid. It's, whatever the dynamic is, there is a no one ever got fired for buying from fill in the blank >> Exactly, yep. >> in the telecom space. >> Yeah, yeah. >> Because they would buy a consolidated, aggregated stack. >> Right. >> And, if something went wrong they could say, boom, blame you. And yeah, that stack doesn't lend itself to the kind of pace of change. >> Right. >> So it doesn't necessarily need the same kind of change management. Or at least it's very, very centralized. >> Okay. Okay. >> We're getting into the brave new world of things where if you let them spin out of control, you can have big problems. And that's where the folks like Dell come in, to make sure that yes, disaggregated, yes best of commercial off-the-shelf stuff, but also the best in terms of performance and reliability and availability. >> Yeah. >> So, that's the execution part, you must execute flawlessly. >> It sounds like from a thematic perspective, the theme of MWC '23 is velocity. But it seems like an underlying theme under that, or maybe an overlying theme is disruption. It's going to be so interesting, we're only on day one. We just started our coverage. Four days of wall to wall coverage on theCUBE. Excited to hear what you're excited about, what you learn over the next few days. We get to host some segments together. >> Yeah. >> But it seems like disruption is the overall theme. And it's going to be so interesting to see how this industry evolves, what the opportunities are, what the coopetition opportunities are. We're going to be learning a lot this week. I'm excited. >> Yeah, and what's fascinating to me about this whole thing is we talk about this, all of this tumultuous, disruptive stuff that's happening. For the average consumer, they're never going to be aware of it. >> Nope. >> Dave: They're just going to see services piled on top of services. >> Which is what we want. >> There are billions of people with mobile devices and the hundreds of billions, I don't know, trillions I guess at some point of connected devices at the edge. >> Lisa: Yes, yes. >> The whole concept of the internet of things. We'll sort of be blissfully unaware of what's happening at the middle. But there's a lot of action there. So we're going to be focusing on that action that's going on. In, you know, in in the middle of it. >> Yeah. >> But there's also some cool consumer stuff out here. >> There is. >> I know I'm going to be checking out the augmented reality and virtual reality stuff. >> Yeah, yeah. Well it's all about that customer experience. We expect things right away, 24/7, wherever we are in the world. And it's enabling that to make that happen. >> Yeah. >> Dave, thank you so much for really sharing what you think you're excited about for the event and some of the trends in telecom. It sounds like it's such an interesting time to be unpacking this. >> It's going to be a great week. >> It is going to be a great week. All right, for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage, covering day one of MWC '23. Stick around. We'll be back with our next guest in just a minute. (bright music resumes) (music fades out)

>> Hello and welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. Got a variety of interviews across the gamut from topics, women in tech, mentoring, pipelining, developers, open source, executives. Stanford's having International Women's Day celebration with the women in data science, which we're streaming that live as well. Variety of programs. In this segment, Meagen Eisenberg, friend of theCUBE, she's the CMO of Laceworks, is an amazing executive, got a great journey story as a CMO but she's also actively advising startups, companies and really pays it forward. I want to say Meagen, thank you for coming on the program and thanks for sharing. >> Yeah, thank you for having me. I'm happy to be here. >> Well, we're going to get into some of the journey celebrations that you've gone through and best practice what you've learned is pay that forward. But I got to say, one of the things that really impresses me about you as an executive is you get stuff done. You're a great CMO but also you're advised a lot of companies, you have a lot of irons in the fires and you're advising companies and sometimes they're really small startups to bigger companies, and you're paying it forward, which I love. That's kind of the spirit of this day. >> Yeah, I mean, I agree with you. When I think about my career, a lot of it was looking to mentors women out in the field. This morning I was at a breakfast by Eileen and we had the CEO of General Motors on, and she was talking about her journey nine years as a CEO. And you know, and she's paying it forward with us. But I think about, you know, when you're advising startups, you know, I've gathered knowledge and pattern recognition and to be able to share that is, you know, I enjoy it. >> Yeah. And the startups are also fun too, but it's not always easy and it can get kind of messy as you know. Some startups don't make it some succeed and it's always like the origination story is kind of rewritten and then that's that messy middle. And then it's like that arrows that don't look like a straight line but everyone thinks it's great and you know, it's not for the faint of heart. And Teresa Carlson, who I've interviewed many times, former Amazon, now she's the president of Flexport, she always says, sometimes startups on certain industries aren't for the faint of heart so you got to have a little bit of metal, right? You got to be tough. And some cases that you don't need that, but startups, it's not always easy. What have you learned? >> Yeah, I mean, certainly in the startup world, grit, creativity. You know, when I was at TripActions travel company, pandemic hits, nobody's traveling. You cut budget, you cut heads, but you focus on the core, right? You focus on what you need to survive. And creativity, I think, wins. And, you know, as a CMO when you're marketing, how do you get through that noise? Even the security space, Lacework, it's a fragmented market. You've got to be differentiated and position yourself and you know, be talking to the right target audience and customers. >> Talk about your journey over the years. What have you learned? What's some observations? Can you share any stories and best practices that someone watching could learn from? I know there's a lot of people coming into the tech space with the generative AI things going on in Cloud computing, scaling to the edge, there's a lot more aperture for technical jobs as well as just new roles and new roles that haven't, you really don't go to college for anymore. You got cybersecurity you're in. What are some of the things that you've done over your career if you can share and some best practices? >> Yeah, I think number one, continual learning. When I look through my career, I was constantly reading, networking. Part of the journey is who you're meeting along the way. As you become more senior, your ability to hire and bring in talent matters a lot. I'm always trying to meet with new people. Yeah, if I look at my Amazon feed of books I've bought, right, it kind of chronicle of my history of things I was learning about. Right now I'm reading a lot about cybersecurity, how the, you know, how how they tell me the world ends is the one I'm reading most recently. But you've got to come up to speed and then know the product, get in there and talk to customers. Certainly on the marketing front, anytime I can talk with the customer and find out how they're using us, why they love us, that, you know, helps me better position and differentiate our company. >> By the way, that book is amazing. I saw Nicole speak on Tuesday night with John Markoff and Palo Alto here. What a great story she told there. I recommend that book to everyone. It goes in and she did eight years of research into that book around zero day marketplaces to all the actors involved in security. And it was very interesting. >> Yeah, I mean, it definitely wakes you up, makes you think about what's going on in the world. Very relevant. >> It's like, yeah, it was happening all the time, wasn't it. All the hacking. But this brings me, this brings up an interesting point though, because you're in a cybersecurity area, which by the way, it's changing very fast. It's becoming a bigger industry. It's not just male dominated, although it is now, it's still male dominated, but it's becoming much more and then just tech. >> Yeah, I mean it's a constantly evolving threat landscape and we're learning, and I think more than ever you need to be able to use the data that companies have and, you know, learn from it. That's one of the ways we position ourselves. We're not just about writing rules that won't help you with those zero day attacks. You've got to be able to understand your particular environment and at any moment if it changes. And that's how we help you detect a threat. >> How is, how are things going with you? Is there any new things you guys got going on? Initiatives or programs for women in tech and increasing the range of diversity inclusion in the industry? Because again, this industry's getting much wider too. It's not just specialized, it's also growing. >> Yes, actually I'm excited. We're launching secured by women, securedbywomen.com and it's very much focused on women in the industry, which some studies are showing it's about 25% of security professionals are women. And we're going to be taking nominations and sponsoring women to go to upcoming security events. And so excited to launch that this month and really celebrate women in security and help them, you know, part of that continual learning that I talked about, making sure they're there learning, having the conversations at the conferences, being able to network. >> I have to ask you, what inspired you to pursue the career in tech? What was the motivation? >> You know, if I think way back, originally I wanted to be on the art side and my dad said, "You can do anything as long as it's in the sciences." And so in undergrad I did computer science and MIS. Graduated with MIS and computer science minor. And when I came out I was a IT engineer at Cisco and you know, that kind of started my journey and decided to go back and get my MBA. And during that process I fell in love with marketing and I thought, okay, I understand the buyer, I can come out and market technology to the IT world and developers. And then from there went to several tech companies. >> I mean my father was an engineer. He had the same kind of thing. You got to be an engineer, it's a steady, stable job. But that time, computer science, I mean we've seen the evolution of computer science now it's the most popular degree at Berkeley we've heard and around the world and the education formats are changing. You're seeing a lot of people's self-training on YouTube. The field has really changed. What are some of the challenges you see for folks trying to get into the industry and how would you advise today if you were talking to your young self, what would you, what would be the narrative? >> Yeah, I mean my drawback then was HTML pages were coming out and I thought it would be fun to design, you know, webpages. So you find something you're passionate about in the space today, whether it's gaming or it's cybersecurity. Go and be excited about it and apply and don't give up, right? Do whatever you can to read and learn. And you're right, there are a ton of online self-help. I always try to hire women and people who are continual learners and are teaching themselves something. And I try to find that in an interview to know that they, because when you come to a business, you're there to solve problems and challenges. And the folks that can do that and be innovative and learn, those are the ones I want on my team. >> It's interesting, you know, technology is now impacting society and we need everyone involved to participate and give requirements. And that kind of leads my next question for you is, like, in your opinion, or let me just step back, let me rephrase. What are some of the things that you see technology being used for, for society right now that will impact people's lives? Because this is not a gender thing. We need everybody involved 'cause society is now digital. Technology's pervasive. The AI trends now we're seeing is clearly unmasking to the mainstream that there's some cool stuff happening. >> Yeah, I mean, I think ChatGPT, think about that. All the different ways we're using it we're writing content and marketing with it. We're, you know, I just read an article yesterday, folks are using it to write children's stories and then selling those stories on Amazon, right? And the amount that they can produce with it. But if you think about it, there's unlimited uses with that technology and you've got all the major players getting involved on it. That one major launch and piece of technology is going to transform us in the next six months to a year. And it's the ability to process so much data and then turn that into just assets that we use and the creativity that's building on top of it. Even TripActions has incorporated ChatGPT into your ability to figure out where you want when you're traveling, what's happening in that city. So it's just, you're going to see that incorporated everywhere. >> I mean we've done an interview before TripAction, your other company you were at. Interesting point you don't have to type in a box to say, I'm traveling, I want a hotel. You can just say, I'm going to Barcelona for Mobile World Congress, I want to have a good time. I want some tapas and a nice dinner out. >> Yes. Yeah. That easy. We're making it easy. >> It's efficiency. >> And actually I was going to say for women specifically, I think the reason why we can do so much today is all the technology and apps that we have. I think about DoorDash, I think about Waze you know, when I was younger you had to print out instructions. Now I get in the car real quick, I need to go to soccer practice, I enter it, I need to pick them up at someone's house. I enter it. It's everything's real time. And so it takes away all the things that I don't add value to and allows me to focus on what I want in business. And so there's a bunch of, you know, apps out there that have allowed me to be so much more efficient and productive that my mother didn't have for sure when I was growing up. >> That is an amazing, I think that actually illustrates, in my opinion, the best example of ChatGPT because the maps and GPS integration were two techs, technologies merged together that replace driving and looking at the map. You know, like how do you do that? Like now it's automatically. This is what's going to happen to creative, to writing, to ideation. I even heard Nicole from her book read said that they're using ChatGPT to write zero day exploits. So you seeing it... >> That's scary stuff. You're right. >> You're seeing it everywhere. Super exciting. Well, I got to ask you before you get into some of the Lacework things that you're involved with, cause I think you're doing great work over there is, what was the most exciting projects you've worked on in your career? You came in Cisco, very technical company, so got the technical chops, CSMIS which stands for Management of Information Science for all the young people out there, that was the state of the art back then. What are some of the exciting things you've done? >> Yeah, I mean, I think about, I think about MongoDB and learning to market to developers. Taking the company public in 2017. Launching Atlas database as a service. Now there's so much more of that, you know, the PLG motion, going to TripActions, you know, surviving a pandemic, still being able to come out of that and all the learnings that went with it. You know, they recently, I guess rebranded, so they're Navan now. And then now back in the security space, you know, 14 years ago I was at ArcSite and we were bought by HP. And so getting back into the security world is exciting and it's transformed a ton as you know, it's way more complicated than it was. And so just understanding the pain of our customers and how we protect them as is fun. And I like, you know, being there from a marketing standpoint. >> Well we really appreciate you coming on and sharing that. I got to ask you, for folks watching they might be interested in some advice that you might have for them and their career in tech. I know a lot of young people love the tech. It's becoming pervasive in our lives, as we mentioned. What advice would you give for folks watching that want to start a career in tech? >> Yeah, so work hard, right? Study, network, your first job, be the best at it because every job after that you get pulled into a network. And every time I move, I'm hiring people from the last job, two jobs before, three jobs before. And I'm looking for people that are working hard, care, you know, are continual learners and you know, add value. What can you do to solve problems at your work and add value? >> What's your secret networking hack or growth hack or tip that you can share? Because you're a great networker by the way. You're amazing and you do add a lot of value. I've seen you in action. >> Well, I try never to eat alone. I've got breakfast, I've got lunch, I've got coffee breaks and dinner. And so when I'm at work, I try and always sit and eat with a team member, new group. If I'm out on the road, I'm, you know, meeting people for lunch, going for dinner, just, you know, don't sit at your desk by yourself and don't sit in the hotel room. Get out and meet with people. >> What do you think about now that we're out of the pandemic or somewhat out of the pandemic so to speak, events are back. >> Yes. >> RSA is coming up. It's a big event. The bigger events are getting bigger and then the other events are kind of smaller being distributed. What's your vision of how events are evolving? >> Yeah, I mean, you've got to be in person. Those are the relationships. Right now more than ever people care about renewals and you are building that rapport. And if you're not meeting with your customers, your competitors are. So what I would say is get out there Lacework, we're going to be at RSA, we're going to be at re:Inforce, we're going to be at all of these events, building relationships, you know, coffee, lunch, and yeah, I think the future of events are here to stay and those that don't embrace in person are going to give up business. They're going to lose market share to us. >> And networking is obviously very key on events as well. >> Yes. >> A good opportunity as always get out to the events. What's the event networking trick or advice do you give folks that are going to get out to the networking world? >> Yeah, schedule ahead of time. Don't go to an event and expect people just to come by for great swag. You should be partnering with your sales team and scheduling ahead of time, getting on people's calendars. Don't go there without having 100 or 200 meetings already booked. >> Got it. All right. Let's talk about you, your career. You're currently at Lacework. It's a very hot company in a hot field, security, very male dominated, you're a leader there. What's it like? What's the strategies? How does a woman get in there and be successful? What are some tricks, observations, any data you can share? What's the best practice? What's the secret sauce from Meagen Eisenberg? >> Yes. Yeah, for Meagen Eisenberg. For Lacework, you know, we're focused on our customers. There's nothing better than getting, being close to them, solving their pain, showcasing them. So if you want to go into security, focus on their, the issues and their problems and make sure they're aware of what you're delivering. I mean, we're focused on cloud security and we go from build time to run time. And that's the draw for me here is we had a lot of, you know, happy, excited customers by what we were doing. And what we're doing is very different from legacy security providers. And it is tapping into the trend of really understanding how much data you have and what's happening in the data to detect the anomalies and the threats that are there. >> You know, one of the conversations that I was just having with a senior leader, she was amazing and I asked her what she thought of the current landscape, the job market, the how to get promoted through the careers, all those things. And the response was interesting. I want to get your reaction. She said interdisciplinary skills are critical. And now more than ever, the having that, having a set of skills, technical and social and emotional are super valuable. Do you agree? What's your reaction to that and what would, how would you reframe that? >> Yeah, I mean, I completely agree. You can't be a leader without balance. You've got to know your craft because you're developing and training your team, but you also need to know the, you know, how to build relationships. You're not going to be successful as a C-level exec if you're not partnering across the functions. As a CMO I need to partner with product, I need to partner with the head of sales, I need to partner with finance. So those relationships matter a ton. I also need to attract the right talent. I want to have solid people on the team. And what I will say in the security, cybersecurity space, there's a talent shortage and you cannot hire enough people to protect your company in that space. And that's kind of our part of it is we reduce the number of alerts that you're getting. So you don't need hundreds of people to detect an issue. You're using technology to show, you know, to highlight the issue and then your team can focus on those alerts that matter. >> Yeah, there's a lot of emerging markets where leveling up and you don't need pedigree. You can just level up skill-wise pretty quickly. Which brings me to the next question for you is how do you keep up with all the tech day-to-day and how should someone watching stay on top of it? Because I mean, you got to be on top of this stuff and you got to ride the wave. It's pretty turbulent, but it's still growing and changing. >> Yeah, it's true. I mean, there's a lot of reading. I'm watching the news. Anytime something comes out, you know, ChatGPT I'm playing with it. I've got a great network and sharing. I'm on, you know, LinkedIn reading articles all the time. I have a team, right? Every time I hire someone, they bring new information and knowledge in and I'm you know, Cal Poly had this learn by doing that was the philosophy at San Luis Obispo. So do it. Try it, don't be afraid of it. I think that's the advice. >> Well, I love some of the points you mentioned community and network. You mentioned networking. That brings up the community question, how could people get involved? What communities are out there? How should they approach communities? 'Cause communities are also networks, but also they're welcoming people in that form networks. So it's a network of networks. So what's your take on how to engage and work with communities? How do you find your tribe? If someone's getting into the business, they want support, they might want technology learnings, what's your approach? >> Yeah, so a few, a few different places. One, I'm part of the operator collective, which is a strong female investment group that's open and works a lot with operators and they're in on the newest technologies 'cause they're investing in it. Chief I think is a great organization as well. You've got a lot of, if you're in marketing, there's a ton of CMO networking events that you can go to. I would say any field, even for us at Lacework, we've got some strong CISO networks and we do dinners around you know, we have one coming up in the Bay area, in Boston, New York, and you can come and meet other CISOs and security leaders. So when I get an invite and you know we all do, I will go to it. I'll carve out the time and meet with others. So I think, you know, part of the community is get out there and, you know, join some of these different groups. >> Meagen, thank you so much for spending the time. Final question for you. How do you see the future of tech evolving and how do you see your role in it? >> Yeah, I mean, marketing's changing wildly. There's so many different channels. You think about all the social media channels that have changed over the last five years. So when I think about the future of tech, I'm looking at apps on my phone. I have three daughters, 13, 11, and 8. I'm telling you, they come to me with new apps and new technology all the time, and I'm paying attention what they're, you know, what they're participating in and what they want to be a part of. And certainly it's going to be a lot more around the data and AI. I think we're only at the beginning of that. So we will continue to, you know, learn from it and wield it and deal with the mass amount of data that's out there. >> Well, you saw TikTok just got banned by the European Commission today around their staff. Interesting times. >> It is. >> Meagen, thank you so much as always. You're a great tech athlete. Been following your career for a while, a long time. You're an amazing leader. Thank you for sharing your story here on theCUBE, celebration of International Women's Day. Every day is IWD and thanks for coming on. >> Thank you for having me. >> Okay. I'm John Furrier here in theCUBE Studios in Palo Alto. Thank you for watching, more to come stay with us. (bright music)