(Upbeat music) (Coughs) >> Hi, I'm Peter Burris with another Wikibooks action item quick take. Jim Kobielus, IBM's up to some good with new tooling for managing data. What's going on? >> Yes Peter, it's not brand new tooling but its important because it actually is a foreshadowing of what's going to be universal. I think it's a capability for programming the uni grade as we've been discussing. Essentially this week at the IBM Signature event Sam Whitestone of IBM discussed with Dave Valente a product they have called Queryplex which is on the market for money even more. Essentially it's a data virtualization environment for distributor query processing in a mesh fabric. And what's important about Queryplex to understand, in a uni grade context, is it enables link binding distributed computation to find the lowest latency path between... Across very fairly complex edge clouds. So to speed up queries no matter where the data may reside and so forth in a fairly real time dynamic fashion. So I think the important things to know about Queryplex are A- that it prioritizes connections with lowest latency based on ongoing computations that are performed and is able to distribute this computation to find the lowest path across the network to prevent the query... The computation controller from being a bottle neck. I think that's a fundamental, architectural capability we're going to see more of with the advent or the growth of the uni grade as a broad concept for building up a distributor cloud computing environment. >> And very importantly there are still a lot of applications that run the businesses on top of IBM machines. Jim Kabielus thanks very much talking about IBM Queryplex and some of the next steps coming. This is Peter Burris with another Wikibooks action item quick take. (upbeat music)

(upbeat music) >> Hi, I'm Peter Burris with another Wikibon Action Item Quick Take. Neil Raden. What's going on with Tableau? >> Well, you know, Tableau software has been a huge success story over the years. Ten years or more. But in the last couple of years they've really exploded. What they did is they allowed in users to take data, analytical data, build some models and generate all sorts of beautiful visualizations from it. Problem was, the people who use Tableau had no tools to work with to prep the data, and that was causing the problem. They work with partners and so forth. But that's all changing. Last year they announced Project Maestro, which is their own data prep product. It's built on a in-memory collinder-oriented data base called Hyper that they bought, and my information, coming from developers who are using the data is that Maestro is going to be a huge success for them. >> Excellent. >> And one other thing, I think it points out that a pure play visualization vendor can't survive. They have to expand horizontally. And it will remain to be seen what Tableau will do after this. This is clearly not its last act. >> Great. Neil Raden talking about Tableau and Project Maestro and expectations for it. This is Peter Burris. Thanks again for watching another Wikibon Action Item Quick Take. (upbeat music)

>>Okay, welcome back everyone. This is the Cube's coverage here in Las Vegas. Back at events re Mars, Amazon re Mars. I'm your host, John fur with the cube. Mars stands for machine learning, automation, robotics, and space. It's great event brings together a lot of the industrial space machine learning and all the new changes in scaling up from going on the moon to, you know, doing great machine learning. And we've got two great guests here with kinda called lunar outpost, Justin Sears, CEO, Lauren, man. He's the co-founder and chief strategy officer lunar outpost. They're right next to us, watching their booth. Love the name, gentlemen. Welcome to the cube. >>Yeah. Thanks for having us, John. >>All right. So lunar outpost, I get the clues here. Tell us what you guys do. Start with that. >>Absolutely. So lunar outpost, we're a company based outta Colorado that has two missions headed to the moon over the course of the next 24 months. We're currently operating on Mars, which forest will tell you a little bit more about here in a second. And we're really pushing out towards expanding the infrastructure on the lunar surface. And then we're gonna utilize that to provide sustainable access to other planetary bodies. >>All right, far as teeing it up for you. Go, how cool is this? We don't, we wanna use every minute. What's the lunar surface look like? What's the infrastructure roads. You gonna pave it down. You what's going on. Well, >>Where we're going. No one has ever been. So, um, our first mission is going to Shackleton connecting Ridge on the south pole, the moon, and that's ripe to add infrastructure such as landing pads and other things. But our first Rover will be primarily driving across the surface, uh, exploring, uh, what the material looks like, prospecting for resources and testing new technologies. >>And you have a lot of technology involved. You're getting data in, you're just doing surveillance. What's the tech involved there. >>Yeah. So the primary technology that we're demonstrating is a 4g network for NOK. Um, we're providing them mobility services, which is basically like the old Verizon commercial. Can you hear me now? Uh, where the Rover drives farther and farther away from the Lander to test their signal strength, and then we're gonna have some other payloads ride sharing along with us for the ride >>Reminds me the old days of wifi. We used to call it war drive and you go around and try to find someone's wifi hotspot <laugh> inside the thing, but no, this is kind of cool. It brings up the whole thing. Now on lunar outpost, how big is the company? What's how what's to some of the stats heres some of the stats. >>Absolutely. So lunar outpost, 58 people, uh, growing quite quickly on track to double. So any of you watching, you want a job, please apply <laugh>. But with lunar outpost, uh, very similar to how launch companies provide people access to different parts of space. Lunar outpost provides people access to different spots on planetary bodies, whether it's the moon, Mars or beyond. So that's really where we're starting. >>So it's kinda like a managed service for all kinds of space utilities. If you kind of think about it, you're gonna provide services. Yeah, >>Absolutely. Yeah. It, it's definitely starting there and, and we're pushing towards building that infrastructure and that long term vision of utilizing space resources. But I can talk about that a little bit more here in a sec. >>Let's get into that. Let's talk about Mars first. You guys said what's going on with >>Mars. Absolutely. >>Yeah. So right now, uh, lunar outpost is part of the science team for, uh, Moxi, which is an instrument on the perseverance Rover. Yeah. Moxi is the first demonstration of space resource utilization on another planet. And what space resource utilization is basically taking resources on another planet, turning them into something useful. What Moxi does is it takes the CO2 from the atmosphere of Mars and atmosphere of Mars is mostly CO2 and it uses a process called solid oxide electrolysis to basically strip oxygen off of that CO2 to produce oh two and carbon monoxide. >>So it's what you need to self sustain on the surface. >>Exactly. It's not just sustaining, um, the astronauts, but also for producing oxygen for propellant. So it'll actually produce, um, it's a, it's a technology that'll produce a propellant for return rockets, um, to come back for Mars. So >>This is the real wildcard and all this, this, this exploration is how fast can the discoveries invent the new science to provide the life and the habitat on the surface. And that seems to be the real focus in the, in the conversations I heard on the keynote as well, get the infrastructure up so you can kinda land and, and we'll pull back and forth. Um, where are we on progress? You guys have the peg from one zero to 10, 10 being we're going, my grandmother's going, everyone's going to zero. Nothing's moving. >>We're making pretty rapid >>Progress. A three six, >>You know, I'll, I'll put it on an eight, John an >>Eight, I'll put it on >>Eight. This is why the mission force was just talking about that's launching within the next 12 months. This is no longer 10 years out. This is no longer 20 years away, 12 months. And then we have mission two shortly after, and that's just the beginning. We have over a dozen Landers that are headed to line surface this decade alone and heavy lift Landers and launchers, uh, start going to the moon and coming back by 2025. >>So, and you guys are from Colorado. You mentioned before you came on camera, right with the swap offices. So you got some space in Colorado, then the rovers to move around. You get, you get weird looks when people drive by and see the space gear. >>Oh yeah, definitely. So we have, um, you know, we have our facility in golden and our Nevada Colorado, and we'll take the vehicles out for strolls and you'll see construction workers, building stuff, and looking over and saying, what's >>Good place to work too. So you're, you're hiring great. You're doubling on the business model side. I can see a lot of demand. It's cheaper to launch stuff now in space. Is there becoming any rules of engagement relative to space? I don't wanna say verified, but like, you know, yet somehow get to the point where, I mean, I could launch a satellite, I could launch something for a couple hundred grand that might interfere with something legitimate. Do you see that on the radar because you guys are having ease of use so smaller, faster, cheaper to get out there. Now you gotta refine the infrastructure, get the services going. Is there threats from just random launches? >>It's a, it's a really interesting question. I mean, current state of the art people who have put rovers on other planetary bodies, you're talking like $3 billion, uh, for the March perseverance Rover. So historically there hasn't been that threat, but when you start talking about lowering the cost and the access to some of these different locations, I do think we'll get to the point where there might be folks that interfere with large scale operations. And that's something that's not very well defined in international law and something you won't really probably get any of the major space powers to agree to. So it's gonna be up to commercial companies to operate responsibly so we can make that space sustainable. And if there is a bad actor, I think it they'll weed themselves out over time. >>Yeah. It's gonna be of self govern, I think in the short term. Good point. Yeah. What about the technology? Where are we in the technology? What are some of the big, uh, challenges that we're overcoming now and what's that next 20 M stare in terms of the next milestone? Yeah, a tech perspective. >>Yeah. So the big technology technological hurdle that has been identified by many is the ability to survive the LUN night. Um, it gets exceptionally cold, uh, when the sun on the moon and that happens every 14 days for another, for, you know, for 14 days. So these long, cold lunar nights, uh, can destroy circuit boards and batteries and different components. So lunar outpost has invested in developing thermal technologies to overcome this, um, both in our offices, in the United States, but we also have opened a new office in, uh, Luxembourg in Europe. That's focusing specifically on thermal technologies to survive the lunar night, not just for rovers, but all sorts of space assets. >>Yeah. Huge. That's a hardware, you know, five, nine kind of like meantime between failure conversation, right. >><laugh> and it's, it gets fun, right? Because you talk five nines and it's such like, uh, you know, ingrained part of the aerospace community. But what we're pitching is we can send a dozen rovers for the cost of one of these historical rovers. So even if 25% of 'em fail, you still have eight rovers for the cost of one of the old rovers. And that's just the, economy's a scale. >>I saw James Hamilton here walking around. He's one of the legendary Amazonians who built out the data center. You might come by the cube. That's just like what they did with servers. Hey, if one breaks throw it away. Yeah. Why buy the big mainframe? Yeah. That's the new model. All right. So now about, uh, space space, that's a not space space, but like room to move around when you start getting some of these habitats going, um, how does space factor into the size of the location? Um, cuz you got the, to live there, solve some of the thermal problems. How do I live on space? I gotta have, you know, how many people gonna be there? What's your forecast? You think from a mission standpoint where there'll be dozens of people or is it still gonna be small teams? >>Yeah. >>Uh, what's that look like? >>I mean you >>Can guess it's okay. >>I mean, my vision's thousands of people. Yep. Uh, living and working in space because it's gonna be, especially the moon I think is a destination that's gonna grow, uh, for tourism. There's an insane drive from people to go visit a new destination. And the moon is one of the most unique experiences you could imagine. Yep. Um, in the near term for Artis, we're gonna start by supporting the Artis astronauts, which are gonna be small crews of astronauts. Um, you know, two to six in the near term. >>And to answer your question, uh, you know, in a different way, the habitat that we're actually gonna build, it's gonna take dozens of these robotic systems to build and maintain over time. And when we're actually talking, timelines, force talks, thousands of people living and working in space, I think that's gonna happen within the next 10 to 15 years. The first few folks are gonna be on the moon by 2025. And we're pushing towards having dozens of people living and working in space and by 2030. >>Yeah. I think it's an awesome goal. And I think it's doable question I'll have for you is the role of software in all this. I had a conversation with, uh, space nerd and we were talking and, and I said open sources everywhere now in the software. Yeah. How do you repair in space? Does you know, you don't want to have a firmware be down. So send down backhoe back to the United States. The us, wait a minute, it's the planet. I gotta go back to earth. Yeah. To get apart. So how does break fix work in space? How, how do you guys see that problem? >>So this one's actually quite fun. I mean, currently we don't have astronauts that can pick up a or change a tire. Uh, so you have to make robots that are really reliable, right. That can continuously operate for years at a time. But when you're talking about long-term repairs, there's some really cool ideas and concepts about standardization of some of these parts, you know, just like Lu knots on your car, right? Yeah. If everyone has the same Lu knots on their wheel, great. Now I can go change it out. I can switch off different parts that are available on the line surface. So I think we're moving towards, uh, that in the long >>Term you guys got a great company. Love the mission. Final question for both of you is I noticed that there's a huge community development around Mars, living on Mars, living on the moon. I mean, there's not a chat group that clubhouse app used, used to be around just kind of dying. But now it's when the Twitter spaces Reddit, you name it, there's a fanatical fan base that loves to talk about an engineer and kind of a collective intelligence, not, may not be official engineering, but they just love to talk about it. So there's a huge fan base for space. How does someone get involved if they really want to dive in and then how do you nurture that audience? How does that, is it developing? What's your take on this whole movement? It's it's beyond just being interested. It's it's become, I won't say cult-like but it's been, there's very, a lot of people in young people interested in space. >>Yeah. >>Yeah. There's, there's a whole, lots of places to get involved. There's, you know, societies, right? Like the Mar society there's technical committees, um, there's, you know, even potentially learning about these, you know, taking a space, resources master program and getting into the field and, and joining the company. So, um, we really, uh, thrive on that energy from the community and it really helps press us forward. And we hope to, uh, have a way to take everyone with us on the mission. And so stay tuned, follow our website. We'll be announcing some of that stuff soon. >>Awesome. And just one last, uh, quick pitch for you, John, I'll leave you with one thought. There are two things that space has an infinite amount of the first is power and the second is resources. And if we can find a way to access either of those, we can fundamentally change the way humanity operates. Yeah. So when you're talking about living on Mars long term, we're gonna need to access the resource from Mars. And then long term, once we get the transportation infrastructure in place, we can start bringing those resources back here to earth. So of course there are gonna be those people that sign up for that first mission out to Mars with SpaceX. But, uh, we'd love for folks to join on with us at lunar outpost and be a part of that kind of next leap accessing those resources. >>I love the mission, as always said, once in the cube, everything in star Trek will be invented someday. <laugh>, we're almost there except for the, the, uh, the transporter room. We don't have that done yet, but almost soon be there. All right. Well, thanks for coming. I, I really appreciate Justin for us for sharing. Great story. Final minute. Give a plug for the company. What are you guys looking for? You said hiring. Yep. Anything else you'd like to share? Put a plug in for lunar outpost. >>Absolutely. So we're hiring across the board, aerospace engineering, robotics engineering, sales marketing. Doesn't really matter. Uh, we're doubling as a company currently around 58 people, as we said, and we're looking for the top people that want to make an impact in aerospace. This is truly a unique moment. First time we've ever had continuous reliable operations. First time NASA is pushing really hard on the public private partnerships for commercial companies like ours to go out and create this sustainable presence on the moon. So whether you wanna work with us, our partner with us, we'd be excited to talk to you and, uh, yeah. Please contact us at info. Lunar outpost.com. >>We'll certainly follow up. Thanks for coming. I love the mission we're behind you and everyone else is too. You can see the energy it's gonna happen. It's the cube coverage from re Mars new actions happening in space on the ground, in the, on the moon you name it's happening right here in Vegas. I'm John furrier. Thanks for watching.

>>thank you. I'm very happy to be here. It's no surprise that Kevin, 19, has changed every business, but how it's changed Business is very strong, Matic Lee, according to the company. Fortunately, we are seeing some interesting themes and some interesting opportunities that really spend across companies. So today's session we're going to talk to three different companies that have had three different experiences and look at what some of the opportunities, challenges and consistencies across these companies are. And I'm thrilled to be here today with three amazing presenters that have very different stories about how they embraced >>the >>challenges that covered 19 created and turned it into opportunity to get started. I'd like to introduce Dr Albert Chan. He is the vice president and chief of digital patient experience at Sutter Health. Following Dr Chan, we have Sean Flaherty, who is the head of technical services, the Kraft Heinz Company, and rounding out our Panelists. Today we have Jennifer Brent, the director, business operations and strategic planning for global real estate at H P E. Thank you everybody, for sharing your time and attention with us today. Let's jump right in now. As I said, we are seeing a great deal of change and opportunity. So I'm gonna ask you to the Panelists to talk a little bit about what the organization is and some of the challenges that they have experienced over the course of 2020. Dr. Shen, let's start with you. Could you please introduce us to Sutter Health and the challenges you faced over the course of 2020? >>Thank you, Mayor Bell. It's great to join everyone. Uh, center Health is a integrated delivery network in Northern California. We serve over 100 diverse communities with 14,000 clinicians and 53,000 employees. Um, and it's a great opportunity to serve our community. Thank you. >>Perfect. Uh, Dr Chen, that was great intro. Sean, could you pick up and tell us a little bit about what's going on at Kraft Heinz and what you've experienced? >>Uh huh. I'm Sean flirty, and I'm currently the head of technical services. I previously was the head of manufacturing for Oscar Mar. I've been with Kraft Heinz for over 30 plus years, working across the supply chain both internationally and domestically. Kraft Heinz is 150 years old. We make some of the most beloved products consumed by all of our employees. And we have made some major big brands. We have craft. We have pines. We have Oscar Mayer planters, bagel bites or write a classical Who laid Philadelphia? Jeff Maxwell house. That's just to name a few little my current role. I'm in charge of technical services, I said, which includes engineering, maintenance, capital spend transformational manufacturing, maintenance and all the productivity pipeline that goes with >>certainly a very wide purview for a big product line. Uh, Gen Brent H P E. Tell us a little bit about what you were doing. >>Thank you, Maribel. Appreciate it. So hopefully everyone is familiar with Hewlett Packard. Enterprise are our main mission is really to advance the way that people live and work through technology. Um, and one of the ways that I'm supporting the company, I work for the global real estate organization. Um, global real estate is is obviously a sort of a key area of focus for everyone. Um, thes days, you know, given the cove in 19 impacts that you're speaking to, Maribel. Um, HP has over 200 sites globally. We operate in over 50 countries. Um, with an employee base of over 65,000. So what we're really focused on right now in real estate is how do we sort of take what's happening right now with Cove in 19. How do we advance? You know, the way that our employees or team members live and work? How do we sort of capitalize on this particular situation and think about what the future of work looks like And how we start to design for and deliver that now? Um, so that's really what what me and the team are focused on. >>Great. So I'm gonna pick up with Dr Chan because, you know, it is covered. 19. And there's been a lot going on in the health care industry. Clearly, um, you know, in your case, could you talk a little bit about what happened when cove it hit? What kind of plans did you have to develop? Because it really wasn't businesses usual. >>Thank you, Maribel. Yes, and indeed you're right. It's a business. Not usual. But frankly, it's something in healthcare. We've always had the face. Whether regards the fires or other disasters, thistle is a unique time for us to being involved in the most intimate parts of people's lives, and this is no different. Um, let me let me harking back to a story. Actually, I think, which illustrate the point. Eso I was in clinic in late February and saw two patients who drove straight from the airport to my clinic. They had respiratory symptoms. Their daughter was concerned about their health and I got advanced warning. I've been reading about this thing called Cove in, and so I had to wear a mask gown, face shield, you name it. And I realized then and there that we had a unique challenge that was confronting us here instead of health. Which is how do we protect the patients and our inclinations as well. So, um, during the week of my birthday, actually, we, um, marshals up a group of people over 200 folks, many of whom I've never met to this day actually came together and designed a telehealth strategy to rapidly respond to covet. We took we typically, we one of things we were doing is telemedicine. And prior to covet, we had 20 video visits per day on average, and after co vid 19, we saw up to 7000 video visits per day. So the rapper was tremendous and it was over. We were essentially given this challenge over a four week period instead of a two year roadmap, which is what our initial intent waas. We trained over 4700 questions to deliver care virtually to meet the challenge, >>that it's simply amazing and shows the power of both the will of individuals and technology coming together to make amazing things happen. And I imagine, Sean, um, in your case, you probably had, well, different something similar in the sense that it's food manufacturing. It's not something that can easily be done remotely. Can you tell us a little bit about what you been experiencing during coded 19? >>Yes, eso. As you said, manufacturing is not something that's not very easily remote. And so we had to quickly address the pandemic and make sure that our operation could stay intact and make our employees feel safe and healthy and make sure that that happens. I mean, across our manufacturing facilities we have put in, um, we require face mask. We require health check assessments. We require a temperature check before anybody enters our facilities. We put digital signage across the facility to encourage social distancing. We've taken our break rooms and redid those so that there's, uh, social distance inside with plexiglass. We staggered are break hours or lunch hours so that people don't congratulate inside there. And then we also have mailed newsletters to ever employees home in both English and Spanish to promote yourself social distancing and wearing face masks outside of work so that they could protect their communities and their families. We've limited visits to a plant to one person per week, and that person can only go to a plant once a week we've done came meeting. We've done team meetings inside of our plants to promote social distancing. We've done lots of activities inside of a manufacturing, please sure that our people are safe and then they go home the same when they came and we don't have any transmission of the virus inside of our facility. >>I think this is so critical because you want people to be able to go to work, to feel safe. And, you know, our food supply chain depends on that. So really excited with the work that you've been doing and very happy that you were able to do it. Jen, I know that HP has manufacturing, but I would like to talk about something slightly different with you because I think you have a mixture of employees. So you're in real estate. How are you thinking differently about what to do with the employees? And you know, some people are calling this a hybrid work concept. What has been your experience with coded 19 and a global workforce? >>Absolutely, Maribel. Thank you. So you're absolutely right. We've got a blend in terms of our workforce. We have your sort of knowledge based workers, Aziz. Well, as you know, manufacturing based workers and also essential support. I t support workers. Um, and those latter two categories have continued to use their offices as part of the essential workforce throughout Cove in 19. And so we've implemented very similar sort of safety measures. Social distancing, you know, PP use Onda like, but as we're thinking about what the future of work looks like and really wanting thio leverage all spaces and and sort of re conceptualize or reimagined, as many people are saying, the future of office, um, we're thinking a bit more broadly. And so as a company, we are in the midst of a of a strategy transformation to become the edge of cloud platform as a service company that is the leader in the industry. Uh, similarly, we wanted to think about our strategy in terms of our workplace in a similar way. And so we're framing it as the edge toe office experience, where by the edge, we mean anything, really, that is outside of the office. So that might be your home office. That might be a customer site. That might be, you know, working on the train on your way to the office for a cafe s. So we're really trying to think of the workplaces everywhere. And how do we really design for that? How do we design for a flow, Um, of a workforce that's really moving and working in a space that at that particular time or moment or day best suits their their work. So we're really tackling this in terms of four key areas. Right now we're looking at what is that experience at the edge? What do we need to make people feel comfortable for people to feel safe and connected How are we then? Adapting our office is how are we pivoting those so that they are they really sort of foster used by a much more fluid workforce on, but they're really fostering collaboration and social and connection. Um, then we're looking at the digital experience being that sort of bridge between spaces on dat sort of equalizer, where everyone has a really similar kind of experience, has the ability to engage on. But it's that piece, really that is so core to our culture and ensuring that we continue tohave that really strong cultural element that is core core to HP. And I'm sure, um, to set our health into Kraft Heinz as well on dfo finally really the mindset because I think any time you move into something like hybrid and you have some people that aren't in your physical proximity, how you engage with them is incredibly important on DSO. I think what's what's most exciting? Really, for us is a technology company is the sort of the key, the key part or or piece that technology plays in that where you know, in the in the past, workplace technology and some of these other pieces collaboration technology may have been seen as more of a nice tohave, whereas now it's really an imperative. Um uh, in our view, for, you know, to really support the future workplace. >>I know when we were just talking with Sean, it sounded like there was quite a bit of communications and collaborations that had to happen with the employee based to make sure that they were up to speed on all the changes that were happening in terms of what their work environment, where was going to be on how it will change going forward. Um, now, on Albert side, this also makes me think that, you know, we talked about this tremendous amount of visits that you started doing with telehealth. Can you talk a little bit about the changes of how that might have changed, what the worker environment was like because I went from seeing a lot of patients in person to doing a lot of telehealth Any other changes that you had to associate with this coded 19 shift? >>Well, thank you very well. I think the biggest change is really our belief in what we could get done. So in other words, there's a there's There's always a fundamental belief of what you can achieve, and we've pushed the limits and we keep pushing it. And and really, it's been quite gratifying, actually, to see our our employees, our staff are clinicians. We had to step up to this challenge and feel empowered to do so. So we're we're seeing new models of care we're seeing, for example, patients. I, for example, I diagnosed a hernia. Believe it or not, be a video, which is I leave the graphical images side for a second. Uh, it was an incredible, credible feet and and I thought I never thought my career that I would be able to do this. But certainly you can, um, and this thing you can attitudes really changed our culture. So, as I mentioned earlier, we really marching up about 200 staff members to come together, many of whom we've never worked together. Frankly, to pull this challenge off, we change our training methodology. We, for example, instead of doing in class classroom training, we essentially held five sessions per day for four weeks straight so that we could accommodate the doctor's schedules and get people ready for telemedicine for example, one of the things we needed to do was get equipment out to our doctors. So we provisioned centrally and in a social distance. Safe manner. Um, several 1004. 4000 plus ipads, for example. So we could deploy them. So consider them centrally, deploy them locally to all our clinicians so they could connect to their patients. And the impact was felt almost immediately. We had stories from physicians who said, Hey, um, I had a family, for example, who was really concerned about their baby, and I diagnosed a neurologic disorder via video, for example, Um, in fact, one of our doctors was quoted as saying, You know, this is this is life has changed so much from Kobe 19, where we're seeing this differentiation between B C before coronavirus and a C after coronavirus and care will never be the same again. So it's an incredible transformation. >>I'm excited for the transformation that we've had because I think it'll bring care Teoh a lot more people more seamlessly, which I think is fabulous now. Yeah, Sean, we talked a little bit about what's going on in your manufacturing environment in terms of adding things like social distancing and other protocols. Were there any other manufacturing changes that happened as a result of that or any other challenges that this new environment created? >>Yes. So assed people started to eat more at home. We had to change our whole manufacturing network as, uh, retool because we service restaurants on the go and those two segments started to drop off. People started buying more of their trusted brands that they are used to. And so we had the retool across our manufacturing network in order to make more products that people wanted. That was in high demand. We increased our capacity across many of our segments. We focused on sanitation to production processes, were still ensuring the highest quality of products concert on lean flow and made flow management inside the facilities. We have put challenge all of our operational assumptions and make sure that we get the most out put that we can during this time. I mean, some of the I think there's four key things that we've learned during this. It's our our speed, agility, our death ability, and I read repeatability, and those four things have come to better ways of what better ways of working increase efficiency, greater flexibility and better focus on what the customer really wants. >>It's actually tremendous to think that you can change a manufacturing line like that that you could be that that responsive to shifts in demand. And I think that that that whole concept we've talked about business agility. If you look at it in health care, if you look at it, um, in a mixed blended environment, like what's going on at HP or if you look at it and manufacturing, we've always discussed it, but we we didn't necessarily have that huge imperative and push to get it done as fast as we've done this time. So it's It's wonderful to see that with the right vision and the right technology, you can actually policing together quite quickly and continue to evolve and adapt them as you see different changes in the marketplace. Jenna I wanted to circle back for a minute because you were talking a little bit about this edged office initiative, and how do you think that changes the employee experience? >>Yeah, it's a good question. I mean, I think it changes it in many ways. In many ways, we're gonna We're gonna hold on. Thio, you know, are are sort of primary core beliefs and behaviors Onda way that we operate a love, you know, the example of sort of the the art of the possible. I mean, one of our sort of call core called cultural beliefs are is is the power of yes, we can, um and I think that this what's been so fascinating and heartening about, you know, this context and the previous two examples is people are just surprised at what they've been able to do about, you know, whether that is, you know, entirely changing in manufacturing line. Whether that is, you know, taking an entire patient diagnosis kind of service entirely digital. I think that people are really becoming exposed far more than they have been in the past, to the truly to the power of technology and what we can dio Onda from an employee engagement perspective. You know, HP, as much as we've had a a pretty flexible way of working where, you know, in the past we've had people working from home. Certainly the core of our culture has always been site based. And I think what's been what you know, what we've sort of been shown through the past sort of 67 months is how much connection you could really establish virtually. You know, it may never be ah, wholesale replacement for what you're able to do in person. Um, but the kind of community feelings that were able thio develop, I think the personal connections and we're letting people into our lives a bit more than we would have. Um, otherwise, but we're really seeing a lot of adaptation. Ah, lot of, you know, efficiency gains from certain people. I think a lot of folks had preconceived ideas about not being productive at home. And I think that, you know, barring some of the sort of unique circumstances of cove it I think that's really been flipped on its head s. So I think, you know, from an engagement perspective, productivity, efficiency. Um, I think, you know, very similar to the prior two examples. What we're seeing is, you know, rethinking the way that we all work and being more sort of fluid. Relying more on technology is actually showing us that we can do things differently. Um, and in a way that actually allows people toe work a lot more flexibly in ways that that suit their own personal style without necessarily, you know, seeing any kind of negative impact on on output but actually in the reverse, you know, really seeing an accelerated positive impact. >>Wonderful. So to close out, I like each of you to tell me, what's the number one thing you've learned in the last nine months of this experience? And how do you think you can use that learning going forward? Perhaps we could start this time with Sean. Yes. So I think >>the one thing that we've learned and we started the journey was really created a culture of we versus by and the and the other thing that I think has really been important during this is management style of leadership style. I think I have had to change my leadership style from one of a servant leader because we're not in the plants now to be able to mentor coach people ends on I wonder what I'm going to call attentional leadership tension leadership. To me visibility. You still got to be seen. You still gotta be able to do things. So you got to use teams you got these virtual facetime Got to do something to make people feel engaged. You have to build trust. And remember, this has gone on for nine months. It's gonna go continue to go on a lot of the people you've never really met person yet. You have to have clarity. I think before we set goals at 123 years. Now it's 30 60 90 days because the environment keeps changing around us so fast. Diversity. You have to be very intentional about being reversed and who you slept on. Your team exclusivity. People still want to see you still want to hear you and they still want to be seen. And they still wanna hurt courage. It's x courage to speak up. It takes courage to create clarity. It takes courage to create a diverse team. It takes courage to create to lead in these chaotic times. So that's really the kind of the biggest takeaways that I've had a broken. >>Thank you, Jennifer. You wanna add anything to that? >>I love everything that Sean just said, Um, and in so many ways, it mirrors all of our key themes that we're thinking about in terms of um, you know, the goodness that we want to take from the past few months, um, and and really apply to our go forward strategy or even emphasize e guess the one the one that I would add, I think it it's probably like encompasses so much of that is really just having a bold, you know, the sort of power and believing in bold moves. So I think what's been so exciting is that we had this really quite bold idea moving Teoh. You know, the future is a hybrid, um, from a workplace strategy perspective and really seeing that embraced, um, and being pretty early on in terms of a company that was developing that strategy. And now seeing that you know, ah, lot of are are sort of competitors or peers or coming out with very similar vision statements, um, I think that that's really been a key learning. And that's been something that's, you know, that's cultural to HP. But really, the power of that kind of vision is, you know, having a sort of bold idea and going for >>it. Awesome. How about you, Albert? How >>do I beat these two? This is amazing. Um I think for me it's really an affirmation. So if I think about health care, we have this unique responsibility and opportunity privilege, if you will, to being involved in the most intimate times of patients. Lives and I have been so hardened by the commitment of our teams of our clinicians to be approachable, reachable even in this face, the pandemic and all these things we're all concerned about each and every day that we're committed to our patients. And, uh, and evidence of that. For example, Alcide, our net promoter score for video are Net net promoter score videos 82 which is on par for our in person clinical care and that that, to me reaffirms the power of relationships to connect to people and to care for people when they need us to care for them to empower them and whether it be the pace of change which we've adapted so quickly, or, um or just our ability to can do, you know we'll do, Um, it's really an affirmation that we were committed to helping people in their daily lives, and it's just an affirmation of the power of people in relationships. So, um, it's been really hardening time for all of us. >>Thank you all for such compelling and inspiring stories. I'm sure the audience will take away many tips and tricks on how to turn challenges into opportunities and strategic advantage moving forward, and now I'm going to turn it back to the Cube for the rest of the show.

>>Hello. My name is Isaac twang and I am on the faculty at MIT in electrical engineering and computer science and in physics. And it is a pleasure for me to be presenting at today's NTT research symposium of 2020 to share a little bit with you about programmable quantum simulators theory and practice the simulation of physical systems as described by their Hamiltonian. It's a fundamental problem which Richard Fineman identified early on as one of the most promising applications of a hypothetical quantum computer. The real world around us, especially at the molecular level is described by Hamiltonians, which captured the interaction of electrons and nuclei. What we desire to understand from Hamiltonian simulation is properties of complex molecules, such as this iron molded to them. Cofactor an important catalyst. We desire there are ground States, reaction rates, reaction dynamics, and other chemical properties, among many things for a molecule of N Adams, a classical simulation must scale exponentially within, but for a quantum simulation, there is a potential for this simulation to scale polynomials instead. >>And this would be a significant advantage if realizable. So where are we today in realizing such a quantum advantage today? I would like to share with you a story about two things in this quest first, a theoretical optimal quantum simulation, awkward them, which achieves the best possible runtime for generic Hamiltonian. Second, let me share with you experimental results from a quantum simulation implemented using available quantum computing hardware today with a hardware efficient model that goes beyond what is utilized by today's algorithms. I will begin with the theoretically optimal quantum simulation uncle rhythm in principle. The goal of quantum simulation is to take a time independent Hamiltonian age and solve Schrodinger's equation has given here. This problem is as hard as the hardest quantum computation. It is known as being BQ P complete a simplification, which is physically reasonable and important in practice is to assume that the Hamiltonian is a sum over terms which are local. >>For example, due to allow to structure these local terms, typically do not commute, but their locality means that each term is reasonably small, therefore, as was first shown by Seth Lloyd in 1996, one way to compute the time evolution that is the exponentiation of H with time is to use the lead product formula, which involves a successive approximation by repetitive small time steps. The cost of this charterization procedure is a number of elementary steps, which scales quadratically with the time desired and inverse with the error desired for the simulation output here then is the number of local terms in the Hamiltonian. And T is the desired simulation time where Epsilon is the desired simulation error. Today. We know that for special systems and higher or expansions of this formula, a better result can be obtained such as scaling as N squared, but as synthetically linear in time, this however is for a special case, the latest Hamiltonians and it would be desirable to scale generally with time T for a order T time simulation. >>So how could such an optimal quantum simulation be constructed? An important ingredient is to transform the quantum simulation into a quantum walk. This was done over 12 years ago, Andrew trials showing that for sparse Hamiltonians with around de non-zero entries per row, such as shown in this graphic here, one can do a quantum walk very much like a classical walk, but in a superposition of right and left shown here in this quantum circuit, where the H stands for a hazard market in this particular circuit, the head Mar turns the zero into a superposition of zero and one, which then activate the left. And the right walk in superposition to graph of the walk is defined by the Hamiltonian age. And in doing so Childs and collaborators were able to show the walk, produces a unitary transform, which goes as E to the minus arc co-sign of H times time. >>So this comes close, but it still has this transcendental function of age, instead of just simply age. This can be fixed with some effort, which results in an algorithm, which scales approximately as towel log one over Epsilon with how is proportional to the sparsity of the Hamiltonian and the simulation time. But again, the scaling here is a multiplicative product rather than an additive one, an interesting insight into the dynamics of a cubit. The simplest component of a quantum computer provides a way to improve upon this single cubits evolve as rotations in a sphere. For example, here is shown a rotation operator, which rotates around the axis fi in the X, Y plane by angle theta. If one, the result of this rotation as a projection along the Z axis, the result is a co-sign squared function. That is well-known as a Ravi oscillation. On the other hand, if a cubit is rotated around multiple angles in the X Y plane, say around the fee equals zero fee equals 1.5 and fee equals zero access again, then the resulting response function looks like a flat top. >>And in fact, generalizing this to five or more pulses gives not just flattered hops, but in fact, arbitrary functions such as the Chevy chef polynomial shown here, which gets transplants like bullying or, and majority functions remarkably. If one does rotations by angle theta about D different angles in the X Y plane, the result is a response function, which is a polynomial of order T in co-sign furthermore, as captured by this theorem, given a nearly arbitrary degree polynomial there exists angles fi such that one can achieve the desired polynomial. This is the result that derives from the Remez exchange algorithm used in classical discreet time signal processing. So how does this relate to quantum simulation? Well recall that a quantum walk essentially embeds a Hamiltonian insight, the unitary transform of a quantum circuit, this embedding generalize might be called and it involves the use of a cubit acting as a projector to control the application of H if we generalize the quantum walk to include a rotation about access fee in the X Y plane, it turns out that one obtains a polynomial transform of H itself. >>And this it's the same as the polynomial in the quantum signal processing theorem. This is a remarkable result known as the quantum synchrony value transformed theorem from contrast Julian and Nathan weep published last year. This provides a quantum simulation auger them using quantum signal processing. For example, can start with the quantum walk result and then apply quantum signal processing to undo the arc co-sign transformation and therefore obtain the ideal expected Hamiltonian evolution E to the minus I H T the resulting algorithm costs a number of elementary steps, which scales as just the sum of the evolution time and the log of one over the error desired this saturates, the known lower bound, and thus is the optimal quantum simulation algorithm. This table from a recent review article summarizes a comparison of the query complexities of the known major quantum simulation algorithms showing that the cubitus station and quantum sequel processing algorithm is indeed optimal. >>Of course, this optimality is a theoretical result. What does one do in practice? Let me now share with you the story of a hardware efficient realization of a quantum simulation on actual hardware. The promise of quantum computation traditionally rests on a circuit model, such as the one we just used with quantum circuits, acting on cubits in contrast, consider a real physical problem from quantum chemistry, finding the structure of a molecule. The starting point is the point Oppenheimer separation of the electronic and vibrational States. For example, to connect it, nuclei, share a vibrational mode, the potential energy of this nonlinear spring, maybe model as a harmonic oscillator since the spring's energy is determined by the electronic structure. When the molecule becomes electronically excited, this vibrational mode changes one obtains, a different frequency and different equilibrium positions for the nuclei. This corresponds to a change in the spring, constant as well as a displacement of the nuclear positions. >>And we may write down a full Hamiltonian for this system. The interesting quantum chemistry question is known as the Frank Condon problem. What is the probability of transition between the original ground state and a given vibrational state in the excited state spectrum of the molecule, the Frank content factor, which gives this transition probability is foundational to quantum chemistry and a very hard and generic question to answer, which may be amiable to solution on a quantum computer in particular and natural quantum computer to use might be one which already has harmonic oscillators rather than one, which has just cubits. This has provided any Sonic quantum processors, such as the superconducting cubits system shown here. This processor has both cubits as embodied by the Joseph's injunctions shown here, and a harmonic oscillator as embodied by the resonant mode of the transmission cavity. Given here more over the output of this planar superconducting circuit can be connected to three dimensional cavities instead of using cubit Gates. >>One may perform direct transformations on the bull's Arctic state using for example, beam splitters, phase shifters, displacement, and squeezing operators, and the harmonic oscillator, and may be initialized and manipulated directly. The availability of the cubit allows photon number resolve counting for simulating a tri atomic two mode, Frank Condon factor problem. This superconducting cubits system with 3d cavities was to resonators cavity a and cavity B represent the breathing and wiggling modes of a Triumeq molecule. As depicted here. The coupling of these moles was mediated by a superconducting cubit and read out was accomplished by two additional superconducting cubits, coupled to each one of the cavities due to the superconducting resonators used each one of the cavities had a, a long coherence time while resonator States could be prepared and measured using these strong coupling of cubits to the cavity. And Posana quantum operations could be realized by modulating the coupling cubit in between the two cavities, the cavities are holes drilled into pure aluminum, kept superconducting by millikelvin scale. >>Temperatures microfiber, KT chips with superconducting cubits are inserted into ports to couple via a antenna to the microwave cavities. Each of the cavities has a quality factor so high that the coherence times can reach milliseconds. A coupling cubit chip is inserted into the port in between the cavities and the readout and preparation cubit chips are inserted into ports on the sides. For sake of brevity, I will skip the experimental details and present just the results shown here is the fibrotic spectrum obtained for a water molecule using the Pulsonix superconducting processor. This is a typical Frank content spectrum giving the intensity of lions versus frequency in wave number where the solid line depicts the theoretically expected result and the purple and red dots show two sets of experimental data. One taken quickly and another taken with exhaustive statistics. In both cases, the experimental results have good agreement with the theoretical expectations. >>The programmability of this system is demonstrated by showing how it can easily calculate the Frank Condon spectrum for a wide variety of molecules. Here's another one, the ozone and ion. Again, we see that the experimental data shown in points agrees well with the theoretical expectation shown as a solid line. Let me emphasize that this quantum simulation result was obtained not by using a quantum computer with cubits, but rather one with resonators, one resonator representing each one of the modes of vibration in this trial, atomic molecule. This approach represents a far more efficient utilization of hardware resources compared with the standard cubit model because of the natural match of the resonators with the physical system being simulated in comparison, if cubit Gates had been utilized to perform the same simulation on the order of a thousand cubit Gates would have been required compared with the order of 10 operations, which were performed for this post Sonic realization. >>As in topically, the Cupid motto would have required significantly more operations because of the need to retire each one of the harmonic oscillators into some max Hilbert space size compared with the optimal quantum simulation auger rhythms shown in the first half of this talk, we see that there is a significant gap between available quantum computing hardware can perform and what optimal quantum simulations demand in terms of the number of Gates required for a simulation. Nevertheless, many of the techniques that are used for optimal quantum simulation algorithms may become useful, especially if they are adapted to available hardware, moving for the future, holds some interesting challenges for this field. Real physical systems are not cubits, rather they are composed from bolt-ons and from yawns and from yawns need global anti-Semitism nation. This is a huge challenge for electronic structure calculation in molecules, real physical systems also have symmetries, but current quantum simulation algorithms are largely governed by a theorem, which says that the number of times steps required is proportional to the simulation time. Desired. Finally, real physical systems are not purely quantum or purely classical, but rather have many messy quantum classical boundaries. In fact, perhaps the most important systems to simulate are really open quantum systems. And these dynamics are described by a mixture of quantum and classical evolution and the desired results are often thermal and statistical properties. >>I hope this presentation of the theory and practice of quantum simulation has been interesting and worthwhile. Thank you.

>>from the Cube Studios >>in Palo Alto and >>Boston connecting with thought leaders all around the world. This is a cube conversation. >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're doing a special presentation today really talking about AI and making ai really with two companies that are right in the heart of the Dell EMC as well as Intel. So we're excited to have a couple Cube alumni back on the program. Haven't seen him in a little while. First off from Intel. Lisa Spelman. She is the corporate VP and GM for the Xeon Group in Jersey on and Memory Group. Great to see you, Lisa. >>Good to see you again, too. >>And we've got Ravi Pinter. Conte. He is the SBP server product management, also from Dell Technologies. Ravi, great to see you as well. >>Good to see you on beast. Of course, >>yes. So let's jump into it. So, yesterday, Robbie, you guys announced a bunch of new kind of ai based solutions where if you can take us through that >>Absolutely so one of the things we did Jeff was we said it's not good enough for us to have a point product. But we talked about hope, the tour of products, more importantly, everything from our workstation side to the server to these storage elements and things that we're doing with VM Ware, for example. Beyond that, we're also obviously pleased with everything we're doing on bringing the right set off validated configurations and reference architectures and ready solutions so that the customer really doesn't have to go ahead and do the due diligence. Are figuring out how the various integration points are coming for us in making a solution possible. Obviously, all this is based on the great partnership we have with Intel on using not just their, you know, super cues, but FPG's as well. >>That's great. So, Lisa, I wonder, you know, I think a lot of people you know, obviously everybody knows Intel for your CPU is, but I don't think they recognize kind of all the other stuff that can wrap around the core CPU to add value around a particular solution. Set or problems. That's what If you could tell us a little bit more about Z on family and what you guys are doing in the data center with this kind of new interesting thing called AI and machine learning. >>Yeah. Um, so thanks, Jeff and Ravi. It's, um, amazing. The way to see that artificial intelligence applications are just growing in their pervasiveness. And you see it taking it out across all sorts of industries. And it's actually being built into just about every application that is coming down the pipe. And so if you think about meeting toe, have your hardware foundation able to support that. That's where we're seeing a lot of the customer interest come in. And not just a first Xeon, but, like Robbie said on the whole portfolio and how the system and solution configuration come together. So we're approaching it from a total view of being able to move all that data, store all of that data and cross us all of that data and providing options along that entire pipeline that move, um, and within that on Z on. Specifically, we've really set that as our cornerstone foundation for AI. If it's the most deployed solution and data center CPU around the world and every single application is going to have artificial intelligence in it, it makes sense that you would have artificial intelligence acceleration built into the actual hardware so that customers get a better experience right out of the box, regardless of which industry they're in or which specialized function they might be focusing on. >>It's really it's really wild, right? Cause in process, right, you always move through your next point of failure. So, you know, having all these kind of accelerants and the ways that you can carve off parts of the workload part of the intelligence that you can optimize betters is so important as you said Lisa and also Rocket and the solution side. Nobody wants General Ai just for ai sake. It's a nice word. Interesting science experiment. But it's really in the applied. A world is. We're starting to see the value in the application of this stuff, and I wonder you have a customer. You want to highlight Absalon, tell us a little bit about their journey and what you guys did with them. >>Great, sure. I mean, if you didn't start looking at Epsilon there in the market in the marketing business, and one of the crucial things for them is to ensure that they're able to provide the right data. Based on that analysis, there run on? What is it that the customer is looking for? And they can't wait for a period of time, but they need to be doing that in the near real time basis, and that's what excellent does. And what really blew my mind was the fact that they actually service are send out close to 100 billion messages. Again, it's 100 billion messages a year. And so you can imagine the amount of data that they're analyzing, which is in petabytes of data, and they need to do real time. And that's all possible because of the kind of analytics we have driven into the power It silver's, you know, using the latest of the Intel Intel Xeon processor couple with some of the technologies from the BGS side, which again I love them to go back in and analyze this data and service to the customers very rapidly. >>You know, it's funny. I think Mark Tech is kind of an under appreciated ah world of ai and, you know, in machine to machine execution, right, That's the amount of transactions go through when you load a webpage on your site that actually ideas who you are you know, puts puts a marketplace together, sells time on that or a spot on that ad and then lets people in is a really sophisticated, as you said in massive amounts of data going through the interesting stuff. If it's done right, it's magic. And if it's done, not right, then people get pissed off. You gotta have. You gotta have use our tools. >>You got it. I mean, this is where I talked about, you know, it can be garbage in garbage out if you don't really act on the right data. Right. So that is where I think it becomes important. But also, if you don't do it in a timely fashion, but you don't service up the right content at the right time. You miss the opportunity to go ahead and grab attention, >>right? Right. Lisa kind of back to you. Um, you know, there's all kinds of open source stuff that's happening also in the in the AI and machine learning world. So we hear things about tense or flow and and all these different libraries. How are you guys, you know, kind of embracing that world as you look at ai and kind of the development. We've been at it for a while. You guys are involved in everything from autonomous vehicles to the Mar Tech. Is we discussed? How are you making sure that these things were using all the available resources to optimize the solutions? >>Yeah, I think you and Robbie we're just hitting on some of those examples of how many ways people have figured out how to apply AI now. So maybe at first it was really driven by just image recognition and image tagging. But now you see so much work being driven in recommendation engines and an object detection for much more industrial use cases, not just consumer enjoyment and also those things you mentioned and hit on where the personalization is a really fine line you walk between. How do you make an experience feel good? Personalized versus creepy personalized is a real challenge and opportunity across so many industries. And so open source like you mentioned, is a great place for that foundation because it gives people the tools to build upon. And I think our strategy is really a stack strategy that starts first with delivering the best hardware for artificial intelligence and again the other is the foundation for that. But we also have, you know, Milat type processing for out of the Edge. And then we have all the way through to very custom specific accelerators into the data center, then on top about the optimized software, which is going into each of those frameworks and doing the work so that the framework recognizes the specific acceleration we built into the CPU. Whether that steel boost or recognizes the capabilities that sit in that accelerator silicon, and then once we've done that software layer and this is where we have the opportunity for a lot of partnership is the ecosystem and the solutions work that Robbie started off by talking about. So Ai isn't, um, it's not easy for everyone. It has a lot of value, but it takes work to extract that value. And so partnerships within the ecosystem to make sure that I see these are taking those optimization is building them in and fundamentally can deliver to customers. Reliable solution is the last leg of that of that strategy, but it really is one of the most important because without it you get a lot of really good benchmark results but not a lot of good, happy customer, >>right? I'm just curious, Lee says, because you kind of sit in the catbird seat. You guys at the core, you know, kind of under all the layers running data centers run these workloads. How >>do you see >>kind of the evolution of machine learning and ai from kind of the early days, where with science projects and and really smart people on mahogany row versus now people are talking about trying to get it to, like a citizen developer, but really a citizen data science and, you know, in exposing in the power of AI to business leaders or business executioners. Analysts, if you will, so they can apply it to their day to day world in their day to day life. How do you see that kind of evolving? Because you not only in it early, but you get to see some of the stuff coming down the road in design, find wins and reference architectures. How should people think about this evolution? >>It really is one of those things where if you step back from the fundamentals of AI, they've actually been around for 50 or more years. It's just that the changes in the amount of computing capability that's available, the network capacity that's available and the fundamental efficiency that I t and infrastructure managers and get out of their cloud architectures as allowed for this pervasiveness to evolve. And I think that's been the big tipping point that pushed people over this fear. Of course, I went through the same thing that cloud did where you had maybe every business leader or CEO saying Hey, get me a cloud and I'll figure out what for later give me some AI will get a week and make it work, But we're through those initial use pieces and starting to see a business value derived from from those deployments. And I think some of the most exciting areas are in the medical services field and just the amount, especially if you think of the environment we're in right now. The amount of efficiency and in some cases, reduction in human contact that you could require for diagnostics and just customer tracking and ability, ability to follow their entire patient History is really powerful and represents the next wave and care and how we scale our limited resource of doctors nurses technician. And the point we're making of what's coming next is where you start to see even more mass personalization and recommendations in that way that feel very not spooky to people but actually comforting. And they take value from them because it allows them to immediately act. Robbie reference to the speed at which you have to utilize the data. When people get immediately act more efficiently. They're generally happier with the service. So we see so much opportunity and we're continuing to address across, you know, again that hardware, software and solution stack so we can stay a step ahead of our customers, >>Right? That's great, Ravi. I want to give you the final word because you guys have to put the solutions together, it actually delivering to the customer. So not only, you know the hardware and the software, but any other kind of ecosystem components that you have to bring together. So I wonder if you can talk about that approach and how you know it's it's really the solution. At the end of the day, not specs, not speeds and feeds. That's not really what people care about. It's really a good solution. >>Yeah, three like Jeff, because end of the day I mean, it's like this. Most of us probably use the A team to retry money, but we really don't know what really sits behind 80 and my point being that you really care at that particular point in time to be able to put a radio do machine and get your dollar bills out, for example. Likewise, when you start looking at what the customer really needs to know, what Lisa hit upon is actually right. I mean what they're looking for. And you said this on the whole solution side house. To our our mantra to this is very simple. We want to make sure that we use the right basic building blocks, ensuring that we bring the right solutions using three things the right products which essentially means that we need to use the right partners to get the right processes in GPU Xen. But then >>we get >>to the next level by ensuring that we can actually do things we can either provide no ready solutions are validated reference architectures being that you have the sausage making process that you now don't need to have the customer go through, right? In a way. We have done the cooking and we provide a recipe book and you just go through the ingredient process of peering does and then off your off right to go get your solution done. And finally, the final stages there might be helped that customers still need in terms of services. That's something else Dell technology provides. And the whole idea is that customers want to go out and have them help deploying the solutions. We can also do that we're services. So that's probably the way we approach our data. The way we approach, you know, providing the building blocks are using the right technologies from our partners, then making sure that we have the right solutions that our customers can look at. And finally, they need deployment. Help weaken due their services. >>Well, Robbie, Lisa, thanks for taking a few minutes. That was a great tee up, Rob, because I think we're gonna go to a customer a couple of customer interviews enjoying that nice meal that you prepared with that combination of hardware, software, services and support. So thank you for your time and a great to catch up. All right, let's go and run the tape. Hi, Jeff. I wanted to talk about two examples of collaboration that we have with the partners that have yielded Ah, really examples of ah put through HPC and AI activities. So the first example that I wanted to cover is within your AHMAD team up in Canada with that team. We collaborated with Intel on a tuning of algorithm and code in order to accelerate the mapping of the human brain. So we have a cluster down here in Texas called Zenith based on Z on and obtain memory on. And we were able to that customer with the three of us are friends and Intel the norm, our team on the Dell HPC on data innovation, injuring team to go and accelerate the mapping of the human brain. So imagine patients playing video games or doing all sorts of activities that help understand how the brain sends the signal in order to trigger a response of the nervous system. And it's not only good, good way to map the human brain, but think about what you can get with that type of information in order to help cure Alzheimer's or dementia down the road. So this is really something I'm passionate about. Is using technology to help all of us on all of those that are suffering from those really tough diseases? Yeah, yeah, way >>boil. I'm a project manager for the project, and the idea is actually to scan six participants really intensively in both the memory scanner and the G scanner and see if we can use human brain data to get closer to something called Generalized Intelligence. What we have in the AI world, the systems that are mathematically computational, built often they do one task really, really well, but they struggle with other tasks. Really good example. This is video games. Artificial neural nets can often outperform humans and video games, but they don't really play in a natural way. Artificial neural net. Playing Mario Brothers The way that it beats the system is by actually kind of gliding its way through as quickly as possible. And it doesn't like collect pennies. For example, if you play Mary Brothers as a child, you know that collecting those coins is part of your game. And so the idea is to get artificial neural nets to behave more like humans. So like we have Transfer of knowledge is just something that humans do really, really well and very naturally. It doesn't take 50,000 examples for a child to know the difference between a dog and a hot dog when you eat when you play with. But an artificial neural net can often take massive computational power and many examples before it understands >>that video games are awesome, because when you do video game, you're doing a vision task instant. You're also doing a >>lot of planning and strategy thinking, but >>you're also taking decisions you several times a second, and we record that we try to see. Can we from brain activity predict >>what people were doing? We can break almost 90% accuracy with this type of architecture. >>Yeah, yeah, >>Use I was the lead posts. Talk on this collaboration with Dell and Intel. She's trying to work on a model called Graph Convolution Neural nets. >>We have being involved like two computing systems to compare it, like how the performance >>was voting for The lab relies on both servers that we have internally here, so I have a GPU server, but what we really rely on is compute Canada and Compute Canada is just not powerful enough to be able to run the models that he was trying to run so it would take her days. Weeks it would crash, would have to wait in line. Dell was visiting, and I was invited into the meeting very kindly, and they >>told us that they started working with a new >>type of hardware to train our neural nets. >>Dell's using traditional CPU use, pairing it with a new >>type off memory developed by Intel. Which thing? They also >>their new CPU architectures and really optimized to do deep learning. So all of that sounds great because we had this problem. We run out of memory, >>the innovation lab having access to experts to help answer questions immediately. That's not something to gate. >>We were able to train the attic snatch within 20 minutes. But before we do the same thing, all the GPU we need to wait almost three hours to each one simple way we >>were able to train the short original neural net. Dell has been really great cause anytime we need more memory, we send an email, Dell says. Yeah, sure, no problem. We'll extended how much memory do you need? It's been really simple from our end, and I think it's really great to be at the edge of science and technology. We're not just doing the same old. We're pushing the boundaries. Like often. We don't know where we're going to be in six months. In the big data world computing power makes a big difference. >>Yeah, yeah, yeah, yeah. The second example I'd like to cover is the one that will call the data accelerator. That's a publisher that we have with the University of Cambridge, England. There we partnered with Intel on Cambridge, and we built up at the time the number one Io 500 storage solution on. And it's pretty amazing because it was built on standard building blocks, power edge servers until Xeon processors some envy me drives from our partners and Intel. And what we did is we. Both of this system with a very, very smart and elaborate suffering code that gives an ultra fast performance for our customers, are looking for a front and fast scratch to their HPC storage solutions. We're also very mindful that this innovation is great for others to leverage, so the suffering Could will soon be available on Get Hub on. And, as I said, this was number one on the Iot 500 was initially released >>within Cambridge with always out of focus on opening up our technologies to UK industry, where we can encourage UK companies to take advantage of advanced research computing technologies way have many customers in the fields of automotive gas life sciences find our systems really help them accelerate their product development process. Manage Poor Khalidiya. I'm the director of research computing at Cambridge University. Yeah, we are a research computing cloud provider, but the emphasis is on the consulting on the processes around how to exploit that technology rather than the better results. Our value is in how we help businesses use advanced computing resources rather than the provision. Those results we see increasingly more and more data being produced across a wide range of verticals, life sciences, astronomy, manufacturing. So the data accelerators that was created as a component within our data center compute environment. Data processing is becoming more and more central element within research computing. We're getting very large data sets, traditional spinning disk file systems can't keep up and we find applications being slowed down due to a lack of data, So the data accelerator was born to take advantage of new solid state storage devices. I tried to work out how we can have a a staging mechanism for keeping your data on spinning disk when it's not required pre staging it on fast envy any stories? Devices so that can feed the applications at the rate quiet for maximum performance. So we have the highest AI capability available anywhere in the UK, where we match II compute performance Very high stories performance Because for AI, high performance storage is a key element to get the performance up. Currently, the data accelerated is the fastest HPC storage system in the world way are able to obtain 500 gigabytes a second read write with AI ops up in the 20 million range. We provide advanced computing technologies allow some of the brightest minds in the world really pushed scientific and medical research. We enable some of the greatest academics in the world to make tomorrow's discoveries. Yeah, yeah, yeah. >>Alright, Welcome back, Jeff Frick here and we're excited for this next segment. We're joined by Jeremy Raider. He is the GM digital transformation and scale solutions for Intel Corporation. Jeremy, great to see you. Hey, thanks for having me. I love I love the flowers in the backyard. I thought maybe you ran over to the Japanese, the Japanese garden or the Rose Garden, Right To very beautiful places to visit in Portland. >>Yeah. You know, you only get him for a couple. Ah, couple weeks here, so we get the timing just right. >>Excellent. All right, so let's jump into it. Really? And in this conversation really is all about making Ai Riel. Um, and you guys are working with Dell and you're working with not only Dell, right? There's the hardware and software, but a lot of these smaller a solution provider. So what is some of the key attributes that that needs to make ai riel for your customers out there? >>Yeah, so, you know, it's a it's a complex space. So when you can bring the best of the intel portfolio, which is which is expanding a lot, you know, it's not just the few anymore you're getting into Memory technologies, network technologies and kind of a little less known as how many resources we have focused on the software side of things optimizing frameworks and optimizing, and in these key ingredients and libraries that you can stitch into that portfolio to really get more performance in value, out of your machine learning and deep learning space. And so you know what we've really done here with Dell? It has started to bring a bunch of that portfolio together with Dell's capabilities, and then bring in that ai's V partner, that software vendor where we can really take and stitch and bring the most value out of that broad portfolio, ultimately using using the complexity of what it takes to deploy an AI capability. So a lot going on. They're bringing kind of the three legged stool of the software vendor hardware vendor dental into the mix, and you get a really strong outcome, >>right? So before we get to the solutions piece, let's stick a little bit into the Intel world. And I don't know if a lot of people are aware that obviously you guys make CPUs and you've been making great CPIs forever. But there's a whole lot more stuff that you've added, you know, kind of around the core CPU. If you will in terms of of actual libraries and ways to really optimize the seond processors to operate in an AI world. I wonder if you can kind of take us a little bit below the surface on how that works. What are some of the examples of things you can do to get more from your Gambira Intel processors for ai specific applications of workloads? >>Yeah, well, you know, there's a ton of software optimization that goes into this. You know that having the great CPU is definitely step one. But ultimately you want to get down into the libraries like tensor flow. We have data analytics, acceleration libraries. You know, that really allows you to get kind of again under the covers a little bit and look at it. How do we have to get the most out of the kinds of capabilities that are ultimately used in machine learning in deep learning capabilities, and then bring that forward and trying and enable that with our software vendors so that they can take advantage of those acceleration components and ultimately, you know, move from, you know, less training time or could be a the cost factor. But those are the kind of capabilities we want to expose to software vendors do these kinds of partnerships. >>Okay. Ah, and that's terrific. And I do think that's a big part of the story that a lot of people are probably not as aware of that. There are a lot of these optimization opportunities that you guys have been leveraging for a while. So shifting gears a little bit, right? AI and machine learning is all about the data. And in doing a little research for this, I found actually you on stage talking about some company that had, like, 350 of road off, 315 petabytes of data, 140,000 sources of those data. And I think probably not great quote of six months access time to get that's right and actually work with it. And the company you're referencing was intel. So you guys know a lot about debt data, managing data, everything from your manufacturing, and obviously supporting a global organization for I t and run and ah, a lot of complexity and secrets and good stuff. So you know what have you guys leveraged as intel in the way you work with data and getting a good data pipeline. That's enabling you to kind of put that into these other solutions that you're providing to the customers, >>right? Well, it is, You know, it's absolutely a journey, and it doesn't happen overnight, and that's what we've you know. We've seen it at Intel on We see it with many of our customers that are on the same journey that we've been on. And so you know, this idea of building that pipeline it really starts with what kind of problems that you're trying to solve. What are the big issues that are holding you back that company where you see that competitive advantage that you're trying to get to? And then ultimately, how do you build the structure to enable the right kind of pipeline of that data? Because that's that's what machine learning and deep learning is that data journey. So really a lot of focus around you know how we can understand those business challenges bring forward those kinds of capabilities along the way through to where we structure our entire company around those assets and then ultimately some of the partnerships that we're gonna be talking about these companies that are out there to help us really squeeze the most out of that data as quickly as possible because otherwise it goes stale real fast, sits on the shelf and you're not getting that value out of right. So, yeah, we've been on the journey. It's Ah, it's a long journey, but ultimately we could take a lot of those those kind of learnings and we can apply them to our silicon technology. The software optimization is that we're doing and ultimately, how we talk to our enterprise customers about how they can solve overcome some of the same challenges that we did. >>Well, let's talk about some of those challenges specifically because, you know, I think part of the the challenge is that kind of knocked big data, if you will in Hadoop, if you will kind of off the rails. Little bit was there's a whole lot that goes into it. Besides just doing the analysis, there's a lot of data practice data collection, data organization, a whole bunch of things that have to happen before. You can actually start to do the sexy stuff of AI. So you know, what are some of those challenges. How are you helping people get over kind of these baby steps before they can really get into the deep end of the pool? >>Yeah, well, you know, one is you have to have the resource is so you know, do you even have the resource is if you can acquire those Resource is can you keep them interested in the kind of work that you're doing? So that's a big challenge on and actually will talk about how that fits into some of the partnerships that we've been establishing in the ecosystem. It's also you get stuck in this poc do loop, right? You finally get those resource is and they start to get access to that data that we talked about. It start to play out some scenarios, a theorize a little bit. Maybe they show you some really interesting value, but it never seems to make its way into a full production mode. And I think that is a challenge that has faced so many enterprises that are stuck in that loop. And so that's where we look at who's out there in the ecosystem that can help more readily move through that whole process of the evaluation that proved the r a y, the POC and ultimately move that thing that capability into production mode as quickly as possible that you know that to me is one of those fundamental aspects of if you're stuck in the POC. Nothing's happening from this. This is not helping your company. We want to move things more quickly, >>right? Right. And let's just talk about some of these companies that you guys are working with that you've got some reference architectures is data robot a Grid dynamics H 20 just down the road in Antigua. So a lot of the companies we've worked with with Cube and I think you know another part that's interesting. It again we can learn from kind of old days of big data is kind of generalized. Ai versus solution specific. Ai and I think you know where there's a real opportunity is not AI for a sake, but really it's got to be applied to a specific solution, a specific problem so that you have, you know, better chatbots, better customer service experience, you know, better something. So when you were working with these folks and trying to design solutions or some of the opportunities that you saw to work with some of these folks to now have an applied a application slash solution versus just kind of AI for ai's sake. >>Yeah. I mean, that could be anything from fraud, detection and financial services, or even taking a step back and looking more horizontally like back to that data challenge. If if you're stuck at the AI built a fantastic Data lake, but I haven't been able to pull anything back out of it, who are some of the companies that are out there that can help overcome some of those big data challenges and ultimately get you to where you know, you don't have a data scientist spending 60% of their time on data acquisition pre processing? That's not where we want them, right? We want them on building out that next theory. We want them on looking at the next business challenge. We want them on selecting the right models, but ultimately they have to do that as quickly as possible so that they can move that that capability forward into the next phase. So, really, it's about that that connection of looking at those those problems or challenges in the whole pipeline. And these companies like data robot in H 20 quasi. Oh, they're all addressing specific challenges in the end to end. That's why they've kind of bubbled up as ones that we want to continue to collaborate with, because it can help enterprises overcome those issues more fast. You know more readily. >>Great. Well, Jeremy, thanks for taking a few minutes and giving us the Intel side of the story. Um, it's a great company has been around forever. I worked there many, many moons ago. That's Ah, that's a story for another time, but really appreciate it and I'll interview you will go there. Alright, so super. Thanks a lot. So he's Jeremy. I'm Jeff Frick. So now it's time to go ahead and jump into the crowd chat. It's crowdchat dot net slash make ai real. Um, we'll see you in the chat. And thanks for watching

>> Narrator: From theCUBE studios in Palo Alto and Boston connecting with thought leaders all around the world, this is a CUBE conversation. >> Hello everyone, welcome to this CUBE conversation here in the Palo Alto studios for theCUBE. I'm John Furrier, the host. We're here during this time where everyone's sheltering in place during the COVID-19 crisis. We're getting the interviews out and getting the stories that matter for you. It's theCUBE's mission just to share and extract the data from, signal from the noise, and share that with you. Of course the conversation here is about how the data analytics are being used. We have a great friend and CUBE alum, Bruno Kurtic, VP, founding VP of Product and Strategy for Sumo Logic, a leader in analytics. We've been following you guys, kind of going back I think many, many years, around big data, now with AI and machine learning. You guys are an industry leader. Bruno, thanks for spending the time to come on theCUBE, I know you're sheltering in place. Thanks for coming on. >> You're welcome, pleasure. >> Obviously with the crisis, the work at home has really highlighted the at-scale problem, right? We've been having many conversations on theCUBE of cybersecurity at scale, because now the endpoint protection business has been exploding, literally, a lot of pressure of malware. A convenient crime time for those hackers. You're starting to see cloud failure. Google had 18 hours of downtime. Azure's got some downtime. I think Amazon's the only one that haven't had any downtime. But everything is being at scale now, because the new work environment is actually putting pressure on the industry, not only just the financial pressure of people losing their jobs or the hiring freezes, but now the focus is staying in business and getting through this. But the pressure points of scale are starting to show. And working at home is one of them. Analytics has become a big part of it. Can you share your perspective of how people using analytics to get through this, because now the scale of the problem-solving is there with analytics. It's in charts on the virus, exponential curves, people want to know the impact of their business in all this. What's your view on this situation? >> Yeah. The world has changed so quickly. Analytics has always been important. But there are really two aspects of analytics that are important right now. A lot of our enterprises today, obviously, as you said, are switching to this sort of remote workforce. Everybody who was local is now remote, so, people are working from home. That is putting stress on the systems that support that working from home. It's putting stress on infrastructure, things like VPNs and networks and things like that because they're carrying more bits and bytes. It's putting stress on productivity tools, things like cloud provider tools, things like Office 365, and Google Drive, and Salesforce, and other things that are now being leveraged more and more as people are remote. Enterprises are leveraging analytics to optimize and to ensure that they can facilitate course of business, understand where their issues are, understand where their failures are, internal and external, route traffic appropriately to make sure that they can actually do the business they need. But that's only half of the problem. In fact, I think the other half of the problem is maybe even bigger. We as humans are no longer able to go out. We're not supposed to, and able to go shopping and doing things as we normally do, so all of these enterprises are not only working remotely, leveraging productivity tools and quote-unquote "digital technologies" to do work. They're also serving more customers through their digital properties. And so their sites, their apps, their retail stores online, and all of the digital aspects of enterprises today are under more load because consumers and customers are leveraging those channels more. People are getting groceries delivered at home, pharmaceuticals delivered at home. Everything is going through online systems rather than us going to Walgreens and other places to pick things up. Both of those aspects of scale and security are important. Analytics is important in both figuring out how do you serve your customers effectively, and how do you secure those sites. Because now that there's more load, there's more people, and it's a bigger honeypot. And then also, how do you actually do your own business to support that in a digital world? >> Bruno, that's a great point. I just want to reiterate that the role of data in all this is really fundamental and clear, the value that you can get out of the data. Now, you and I, we've had many conversations with you guys over the years. For all of us insiders, we all know this already. Data analytics, everyone's instrumenting their business. But now when you see real-life examples of death and destruction, I mean, I was reporting yesterday that leaked emails from the CDC in the United States showed that in January, they saw that people didn't have fevers with COVID-19. The system was lagging. There was no real-time notifications. This is our world. We've been living in this for this past decade, in the big data world. This is highlighting a global problem, that with notifications, with the right use of data, is a real game-changer. You couldn't get any more clear. I have to ask you, with all this kind of revelations, and I don't mean to be all gloom-and-doom, but that's the reality, highlights the fact that instrumenting and having the data analytics is a must-have. Can you share your reaction to that? >> Yeah, absolutely. You're right. Like you said, we are insiders here, and we've been espousing this world of what we internally in Sumo call the continuous intelligence, which essentially means to us and to our customers, that you collect and process all signals that are available to you as a business, as a government, as a whatever entity that is dealing with critical things. You need to process all of that data as quickly as you can. You need to mine it for insights. You need to, in an agile fashion, just like software development, you need to consume those insights, build them into your processes to improve, to react, to respond quickly, and then deliver better outcomes. The sooner you understand what the data is telling you, the sooner you can actually respond to whatever that data is telling you, and actually avoid bad outcomes, improve good outcomes, and overall, react to whatever is forcing you to react. >> I was just talking with Dave Vellante last week about this, my co-host, and also Jeff Frick, my general manager, who interviewed you in the past on theCUBE, about the transition and transformation that's happening. I want to just get your reaction to what we're seeing, and I wanted to get your thoughts on it. There's transitions and there's transformations. Yeah, we've been kind of in this data transition around analytics. You pointed out, as insiders, we've been pointing this out for years. But I think now there's more of a transformative component to this. I think it's becoming clear to everyone the role of data, and you've laid out some good things there. Now I want to ask you, on this transformation. Do you agree with it, and if you do, how does that change the roles? Because if I'm going to react to this as a business, whether small, medium, and large business, large enterprise or government, I now realize that the old world's over. I need to get to the new way. That means new roles, new responsibilities, new outcomes, new ways to measure. Can you share your thoughts on that? Do you agree with the transformation, and two, what are some of those new role changes? How should a business manager or technologist make that transformation? >> Yeah. If it was ever more clear, getting a switch, or a transformation as you say, from the old way we did business and we did technology to the new way, is only being highlighted by this crisis. If you are an enterprise, and you are trying to do everything yourself, running your own IT stacks and all of that, it is clear today that it is much more difficult to do that than if you were leveraging next generation technologies: clouds, SaaS, PaaS, and other things, because it is hard to get people even to work. I think if we have ever been in a place where this sort of transformation is a must, not a slow choice or an evolution, it is now. Because enterprises who have done that, who have done that already, are now at an advantage. I think this is a critical moment in time for us all as we all wake up to this new reality. It is not to say that enterprises are going to be switched over after this specific crisis, but what's going to happen, I believe, is that, I think the philosophies are going to change, enterprises are going to think of this as the new normal. They're going to think about, "Hey, if I don't have the data "about my business, about my customers, "about my infrastructure, about my systems, "I won't be able to respond to the next one." Because right now there's a lot of plugging the holes in the dam with fingers and toes, but we are going to need to be ready for this, because if you think about what this particular pandemic means, this isn't going to end in April or May. Because without a treatment, or without a vaccination, it's going to continue to resurface. Unless we eradicate the entire population of the virus, any new incident is going to start up like a small flare-up, and that is going to continue to bring us back into the situation. Over this time, we're going to have to continue to respond to this crisis as we are, and we need to plan for the future ones like this. That might not be a pandemic type of crisis. It could be a change in the business. It could be other types of world events, whatever it might be. But I think this is the time when enterprises are going to start adopting these types of procedures and technologies to be able to respond. >> It's interesting, Bruno, you bring up some good points. I think about all the conversations that I've had over the years with pros around "disaster recovery" and continuous operations. This is a different vector of what that means, because when you highlighted earlier, IT, it's not like a hurricane or a power outage. This is a different kind of disruption. We talked about scale. What are some of the things that you're seeing right now that businesses are being faced with, that you guys are seeing in the analytics, or use cases that have emerged from this new normal that is facing today's business with this crisis. What's changed? What is this new challenge? When you think about the business continuity and how continuous operations need to be sustained because, again, it's a different vector. It's not a blackout, it's not a hurricane. It's a different kind of disruption. It's one where the business needs to stay on more than ever. >> Yep. Correct. True. What's really interesting, and there are some relatively straightforward use cases that we're seeing. People are dealing with their authentication, VPN network issues, because everybody is low on bandwidth. Everybody is, all of these systems are at their breaking point because they're carrying more than they ever did. These are use cases that existed all along. The problem with the use cases that existed all along is that they've been slowly picking up and growing. This is the discontinuity right now. What's happened right now, all of a sudden you've got double, triple, quadruple the load, and you need to both scale up your infrastructure, scale up your monitoring, be much more vigilant about that monitoring, speed up your recovery because more is at stake, and all of those things. That's the generic use case that existed all along, but have not been in this disruptive type of operating environment. Second is, enterprises are now learning very quickly what they need to do in terms of scaling and monitoring their production, customer-facing infrastructure, what used to be in the data center, the three-tier world, adding a few notes to an application, to your website over time, worked. Right now everybody is realizing that this whole bent on building our microservices, building for scale, rearchitecting and all that stuff, so that you can respond to an instantaneous burst of traffic on your site. You want to capture that traffic, because it means revenue. If you don't capture it, you miss out on it, and then customers go elsewhere, and never come back, and all that stuff. A lot of the work loads are to ensure that the systems, the mission-critical systems, are up and running. It's all about monitoring real-time telemetry, accelerating root cause analysis across systems that are cloud systems, and so on. >> It's a great point. You actually were leading into my next question I wanted to ask you. You know, the old saying goes, "Preparation meets opportunity. Those are the lucky ones." Luck is never really there. You're prepared, and opportunity. Can you talk about those people that have been prepared, that are doing it right now, or who are actually getting through this? What does preparation look like? What's that opportunity? Who's not prepared? Who's hurting the most? Who's suffering, and what could they do differently? Are you seeing any patterns out there, that people, they did their work, they're cloud native, they're scaled out, or they have auto-scaling. What are some of the things where people were prepared, and could you describe that, and on the other side where people weren't prepared, and they're hurting. Can you describe those two environments? >> Sure. Yeah. You think about the spectrum of companies that are going through digital transformation. There are companies who are on the left side. I don't know whether I'm mirroring or not. Basically, on the left side are people who are just making that transformation and moving to serving customers digitally, and on the right side are the ones that are basically all in, already there, and have been building modern architectures to support that type of transformation. The ones that are already all the way on the right, companies like us, right? We've been in this business forever. We serve customers who are early adopters of digital, so we've had to deal with things like November 6th, primary elections, and all of our media and entertainment customers who were spiking. Or we have to deal with companies that do sporting events like World Cup or Super Bowl and things like that. We knew that our business was going to always demand of us to be able to respond to both scheduled and unscheduled disruptions, and we needed to build systems that can scale to that without many human interactions. And there are many of our customers, and companies who are in that position today, who are actually able to do business and are now thriving, because they are the ones capturing market share at this point in time. The people who are struggling are people who have not yet made it to that full transformation, people who, essentially, assume business as normal, who are maybe beginning that transformation, but don't have the know-how, or the architecture, or the technology yet to support it. Their customers are coming to them through their new digital channels, but those digital channels struggle. You'll see this, more often than not you're going to find these still running in a traditional data center than in the cloud. Sometimes they're running in the cloud where they've done just a regular lift-and-shift instead of rearchitecting and things like that. There's really a spectrum, and it's really funny and amazing how much it maps to the journey in digital transformation, and how this specific thing is essentially, what's happening right now, it looks like the business environment demands everybody to be fully digital, but not everybody is. Effectively, the ones that are not are struggling more than the ones that are. >> Yeah. Certainly, we're seeing with theCUBE, with the digital events happening on our side, all events are canceled, so they've got to move online. You can't just take a physical, old way of doing something, where there's content value, and moving it to digital. It's a whole different ball game. There's different roles, there's different responsibilities. It's a completely different set of things. That's putting pressure on all these teams, and that's just one use case. You're seeing it in IT, you're seeing it happen in marketing and sales, how people are doing business. This is going to be very, very key for these companies. The data will be, ultimately, the key. You guys are doing a great job. I do want to get to the news, and I want to get the plug in for Sumo Logic. I want to say congratulations to you guys. A press release went out today from Sumo Logic. You guys are offering free cloud-based data analytics to support work from home and online classroom environments. That's great news. Can you just share and give a plug for that, PSA? >> Sure! We basically have a lot of customers who, just like us, are now starting to work from home. As soon as this began, we got inbound demands saying, "Oh, could you get, do you have an application for this, "do you have some analytics for that, "things that support our work from home." We thought hey, why don't we just make this as a package, and actually build out-of-the-box solutions that can support people who have common working from home technologies that they used to use for 10% of their workforce, and now work for 100% of their workforce. Let's package those, let's push those out. Let's support educational institutions who are now struggling. I have two kids in here who are learning. Everything is online, right? We had to get another computer for them and all this stuff. They're younger, they're in fourth grade. They are doing this, I can see personally how the schools are struggling, how they're trying to learn this whole new model. They need to have their systems be reliable and resilient, and this is not just elementaries, but middle school, high schools, colleges have all expanded their on-premise teaching. So we said, "Okay. Let's do something to help the community "with what we do best." Which is, we can help them make sure that the things that they do, that they need to do for this remote workforce, remote learning, whatever it might be, is efficient, working, and secure. We packaged several bundles of these solutions and offered those for free for a while, so that both our customers, and non-customers, and educational institutions have something they can go and reach for when they are struggling to keep their systems up and running. >> Yeah, it's also a mindset change, too. They want comfort. They want to have a partner. I think that's great that you guys are doing for the community. Can you just give some color commentary on how this all went down? Did you guys have a huddle in your room, said, "Hey, this is a part of our business. "We could really package this up "and really push it out and help people." Is that how it all came together? Can you share some inside commentary on how this all went down and what happened? >> Yeah. Basically, we had a discussion, literally, I think, the first or the second day when we all were sent home. We got on our online meeting and sat down, and essentially learned about this inbound demand from our customers, and what they were looking to do. We were like, "Okay, why don't we, "why don't we just offer this? "Why don't we package it?" It was a cross-functional team that just sat there. It was a no-brainer. Nobody was agonizing over doing this for free or anything like that. We were just sitting there thinking, "What can we do? "Right now is the time for us to all "pull each other up and help each other. "It'll all sort itself out afterwards." >> You know, during the bubonic plague, Shakespeare wrote Macbeth during that time. You guys are being creative during this time, as the coronavirus, so props to you guys at Sumo Logic. Congratulations, and thanks for taking the time. Can you give some parting thoughts on it, for the folks who are working at home? Just some motivational inspiration from you guys? What's going to come next for you guys? >> Sure. And thank you for having me on this video. I would say that we have been making slow transition towards remote workforce as it is. In a lot of places around the world, it's not that easy to make it to an office. Traffic is getting worse, big centers are getting populated, real estate is getting more expensive, all of this stuff. I think, actually, this is an opportunity for enterprises, for companies, and for people to figure out how this is done. We can actually practice now. We're forced to practice. It might actually have positive impact on all industries. We are going to probably figure out how to travel less, probably figure out how to actually do this more effectively, the cost of doing business is going to go down, ability to actually find new jobs might broaden, because you might be able to actually find jobs at companies who never thought they could do this remotely, and now are willing to hire remote workforces and people. I think this is going to be all good for us in the end. Right now it feels painful, and everybody's scared, and all that stuff, but I think long term, both the transformation into digitally serving our customers and the transformation towards remote workforce is going to be good for business. >> Yeah. It takes a community, and we really appreciate the effort you guys make, making that free for people, the classrooms. Remember, Isaac Newton discovered gravity and calculus while sheltering in place. A lot of interesting, new things are going to happen. I appreciate it. >> Bruno: Absolutely. >> Bruno, thank you for taking the time and sharing your insights from your place, sheltering. I made a visit into the studio to get this interview and a variety of other interviews we're doing digitally here. Thanks for sharing. Appreciate your time. >> Thank you. Appreciate you as well. >> I'm John Furrier with theCUBE here. CUBE conversation with Bruno from Sumo Logic sharing his perspective on the COVID-19. The impact, the disruption and path to the future out of this, and the new normal that is going to change our lives. Thanks for watching.

>> Announcer: Live from San Francisco, it's theCUBE covering RSA Conference 2020, San Francisco. Brought to you by SiliconANGLE Media. >> Welcome back everybody, Jeff Frick with theCUBE. We're at RSA 2020. It's day four, it's Thursday. This is a crazy long conference, 40,000 people. Even with the challenges presented by coronavirus, and there's a lot of weird stuff going on, the team pulled it together, they went forward. And even though there was drops out here and there, I think all in all, most people will tell you, it's been a pretty successful conference. And we're excited to be joined by really one of the top level sponsors here, that's still here and still doing good things. It's Vittorio Viare... Viarengo, sorry, the new interim CMO of McAfee. >> Yeah. >> Vittorio, I just call you Vittorio all the time. I never look past your first name. Great to see you. >> Likewise. It's always a pleasure to be here with an institution of Silicon Valley-- >> Oh thank you, thank you. So interim CMO, I always think of like interim football coaches that they get pulled in halfway through the season, so the good news is you kind of got the job and all the responsibilities. The bad news is, you still have that interim thing, but you don't care, you just go to work, right? >> Now whenever you have an interim job, you have to just do the job and then that's the best way to operate. >> Yeah, so again, I couldn't help but go back and look at that conversation that we had at Xerox Parc, which is interesting. That's pretty foundational, everything that happens in Silicon Valley, and so many discoveries up there. And you touched on some really key themes in the way you manage your teams, but I think they're really much more valuable, and worth bringing back up again. And the context was using scrum as a way to manage people, but more importantly, what you said is it forced you as a leader to set first priorities and have great communication; and to continually do that on this two week pace, to keep everybody moving down the road. I think that is so powerful and so lacking unfortunately, in a lot of organizations today. >> Yeah, look, I think that when you hire smart people, if you just make sure that they understand what their priorities are, and then remove the obstacle and get out of the way, magical things happen. And I give you example that is very close to your heart. When I took over a great team at Skyhigh, that got bought by McAfee, they had content marketing down to a science, but they were lacking videos. So I brought that in. I said, "Guys, people watch videos, "people engage with videos, "we need to start telling the story through videos." And I started pushing, pushing, pushing, and then I pulled back, and these guys took it to a whole new level. And then they're doing videos, they're very creative, they are crisp. And I'm like, "Yeah, my job is done." >> It is really wild how video has become such an important way for education. I mean it used to be... I remember the first time I ever saw an engineer use Google to answer a question on writing code. I had never seen that before. I'm not a coder. Wow, I thought it was just for finding my local store or whatever. And now to see what really... I think YouTube has pushed people to expect that the answer to any question should be in a video. >> So, yesterday literally, somebody from a company I don't even know stopped me and said, "I watch you to videos on container. "Thank you very much." I was like, "What, you?" And the genesis of that was the sales people ask me, "Hey, we're selling container security and all that," but I don't even understand what containers are. Okay, sure. So I shot a video and I'm the CMO, I was the vice president. I think you have to put your face on your content. It doesn't matter how senior you are, you're not in a corner office, you're down there with the team. So I got into the studio, based on my background at VMware, I knew virtual machine, and I said, "Okay, how do you explain this "to somebody who's not technical?" And next thing you know, it makes its way out there, not just to our sales force, but to the market at large. That's fantastic. >> Right, and let me ask you to follow up on that because it seems like the world is very divergent as to those who kind of want their face, and more their personality to be part of their business culture and their business messaging, and those that don't. And you know, as part of our process, we always are looking at people's LinkedIn, and looking at people's Twitter. I get when people don't have Twitter, but it really surprises me when professionals, senior professionals within the industry aren't on LinkedIn. And is just like, wow! That is such a different kind of world. >> LinkedIn right now is... and I'm stealing this from Gary on the Chuck, as a big believer in this. LinkedIn right now is like Facebook 10 years ago. You get amazing organic distribution, and it's a crime not to use it. And the other thing is if you don't use it, how are you going to inspire your team to do the right thing? Modern marketing is all about organic distribution with a great content. If you're not doing it yourself... I grew up in a bakery. I used to look at my mom, we have a big bakery. We had eight people working, and I said, "Ma, why are you workin' so hard? "Your first day, last hour?" And she said, "Look, you cannot ask your people, "to work harder than you do." That was an amazing lesson. So it's not just about working hard, and harder than your team, it's about are you walking the walk? Are you doing the content? Are you doing the modern marketing things that work today, if you expect your people to also do it? >> Yeah, it's just funny 'cause, when we talk to them, I'm like, "If you don't even have a LinkedIn account, "we shouldn't even be talking to you "because you just won't get what we do. "You won't see the value, you won't understand it "and if you're not engaging at least "a little bit in the world then..." And then you look at people say like Michael Dell, I'll pick on or Pat Gelsinger who use social media, and put their personalities out there. And I think it's, people want to know who these people are, they want to do business with people that they they like, right? >> Absolutely. You know what's the worst to me? I can tell when an executive as somebody else manages their account, I can tell from a mile away. That's the other thing. You have to be genuine. You have to be who you are on your social and all your communication because people resonate with that, right? >> Right. All right, so what are you doing now? You got your new title, you've got some new power, you've got a great brand, leading brand in the industry, been around for a while, what are some of your new priorities? What's some of the energy that you're bringing in and where you want to to go with this thing? >> Well, my biggest priority right now is to get the brand and our marketing to catch up with what the products and the customers are already which is, Cloud, Cloud, Cloud. So when we spun off from Intel two years ago, we had this amazing heritage in the endpoint security. And then we bought Skyhigh, and Skyhigh was transformational for us because it became the foundation for us to move to become a cloud-first organization. And is in the process of becoming a cloud-first organization, and creating a business that is growing really fast. We also brought along the endpoint, which now is all delivered from the Cloud, to the cloud-first open unified approach, which is exciting. >> And we see Edge is just an extension of endpoints, I would assume. It just changes the game. >> Yeah, so if you think about today modern work gets done with the backend in the Cloud, and accessing those backends from the device, right? >> Right. >> And so, our strategy is to secure data where modern work gets done, and it's in the device, in the Cloud, and on the edge. Because data moves in and out of the Cloud, and that's kind of the edge of the Cloud. That's what we launched this week at RSA we launched Unified Cloud Edge, which is our kind of a, Gartner call's it SaaS-y, so that we are kind of the security. We believe we have the most complete and unified security part of the SaaS-y world. >> Okay, I just laugh at Gartner and the trough of disillusion men and Jeff and I always go back to a Mars law. Mar does not get enough credit for a Mars law. We've got a lot of laws, but Mars law, we tend to overestimate in the short term, the impact of these technologies, and they completely underestimate really the long tail of this technology improvements, and we see it here. So let's shift gears a little bit. When you have your customers coming in here, and they walk into RSA for the first time, how do you tell people to navigate this crazy show and the 5,000 vendors and the more kind of solutions and spin vocabulary, then is probably save for anyone to consume over three days? >> Look, security is tough because you look around and say, "You have six, 700 vendors here." It's hard to stand out from the crowd. So what I tell our customers is use this as a way to meet with your strategic vendors in the booth upstairs. That's where you conduct business and all that. And I walk around to see from the ground up, send your more junior team out there to see what's happening because some of these smaller companies that are out here will be the big transformational companies or the future like Skyhigh was three four years ago, and now we're part of McAfee, and leading the charge there. >> Yeah, just how do you find the diamond in the rough, right? >> Yeah. >> 'Cause there's just so much. But it's still the little guys that are often on the leading edge and the bleeding edge, of the innovation so you want to know what's going on so that you're kind of walking into the back corners of the floor as well. >> That's why I am lifelong learner, so I go around to see what people do from a marketing perspective because, the last thing I want to do, I want to become obsolete. (Jeff laughs) And the way you don't become obsolete is to see what the new kids on the block do and steal their ideas, steal their tactics take them to the next level. >> Right, so I want to ask you a sensitive question about the conference itself and the coronavirus thing and we all saw what happened in Mobile World Congress. I guess it just got announced today that Facebook pulled F8, their developer conference. We're in the conference business. You go to a lot of conferences. Did you have some thought process? There were some big sponsors that pulled out of this thing. How did you guys kind of approach the situation? >> It's a tough one. >> It's a really tough one. >> It's a very tough one 'cause last thing you want to do is to put your employees and your customers at risk. But the way we looked at it was there were zero cases of coronavirus in San Francisco. And we saw what the rest of the industry was doing, and we made the call to come here, give good advice to our employees, wash their hands, and usual and this too will pass. >> Yeah, yeah. Well Vittorio, it's always great to catch up with you. >> Likewise. >> I just loved the energy, and congratulations. I know you'll do good things, and I wouldn't be at all surprised if that interim title fades away like we see with most great coaches. >> Good. >> So thanks for stopping by. >> My pleasure. >> All right, he's Vittorio, I'm Jeff. You're watching theCUBE, we're at RSA 2020 in San Francisco. Thanks for watching, we'll see you next time. (upbeat music)

(upbeat music) >> From New York, it's the Cube covering escape nineteen. (upbeat music) >> Hello, welcome back to the cube coverage here in New York city for the first inaugural multi-cloud conference called escape 2019, I'm John Furrier host of the Cube, we're here with Natalie Gholmieh who's the data manager of data and integration services at the university of California, San Diego campus, office, >> sprawling data center, >> Yes (laughing) >> tons of IT, a lot of challenges. Welcome. >> Yeah, thank you for having me. >> So, thanks for taking the time out, you're a practitioner, you're here. Why are you at this conference, what are you hoping to gain from here? What interests you here at the multi-cloud escape conference. >> This conference is very much within the spirit of what we're trying to do. Uh- we- our CIO has directives which is, to avoid locking and to do multi-vendor orchestration um, an, uh, to go with containers first and open source wherever possible. So- and, I, this conference pretty much speaks to all of that. >> So, this is a really interesting data point because it seems the common thread is data and cloud is an integration thing so people are trying to find that integration point so they can have multiple vendors, multiple clouds. It seems like the multi-vendor were all back in the old days where you had multiple vendors, had a regimeous environment, data seems to be the lynch pin in all this. That's what you do- >> Right. >> How do you think about this because it used to be the big database ran the world, now you have lots of databases. You have applications, >> Right. >> they're everywhere now. >> Yeah, data is born in multiple systems but the data is also an asset right now, to all of the organizations including the university so, um, what we want to try to accomplish is to, uh, get all of this data possibly in one place or in multiple places and to be able to, to do analytics on top of this and this is what the value added processing over the data. >> What's exciting to you these days in the university? You guys try to change the business, what, what- it could be technology. What are the cool things that you like that you're working with right now or that you envision emerging? >> Yeah, so my team is currently building a platform to do an integrat- um, all of the data integration and we are planning to offer, this platform as a service to Developers to streamline and standardize, application development as well as integration development within the central IT of university. So this is pretty much the most exciting thing that we're doing is putting together this platform that is quite complex It is a journey that we're taking Together with the people who are already operating existing systems, and so we are putting this new thing that we're operating in parallel and we will be migrating to that new platform over time. >> I'm sure containers are involved >> Troupernetties >> Yes >> To be part of it >> Mhm, Mhm, yeah so the platform has two parts There is the application, publishing with Gooddoctrine troupernetties And we have also the streaming side of it Where to build the data pipeline with open source tools like ApacheNinefive and Apache kafka. So um yes So this is going to be wiring the data pipelines from source to target and moving the data in real time In order to- >> And you see that as a nice way to keep uh an option to move from cloud to cloud >> Potentially since the platforms role is to decouple the infrastructure from devolepment that way you could spin a portion of the platform on any cloud pretty much and run your workload. Anywhere you want. >> So classic Dev ops, Separate infrustracture as code provide a codified layer >> Yeah, Yeah >> So let me ask you a question, How did you get into all this data business? I mean what attracted you to the data field? What's your story? Tell us your story. >> Ah, so the data, you know, I personally started I mean I was I had more of a networking background and then I became a sys Admin and then I got into the business of logging and log aggregation for machine data And then I was you know using that Data to create Dashboards of system health and you know data correlation and this is what exposed me, personally, first to the data world. And then I saw the value in, in doing all of this With data and the value is even more impactful to the business, when you're working with actual business data. And then Right so I'm very excited about that. >> So you were swimming in the first data lake before data lakes were data lakes. >> Yeah, right, for machine data >> And once you're in there you see value Data exhaust comes in as we used to say back in the day. During the Hedupe days. Data exhaust. So now that you're doing the business value is the conversations the same, or are they different conversations? Or is it still the same kind of data conversation? What's, or is the, job the same? Because you still have machine data applications are throwing off data. >> Right >> You have infrastructure data being thrown off You have new abstrac-New software layers >> Yes >> Is it the same or is it different? Describe the current situation. >> Eh, you know, maybe the concepts are the same Uh, but I think the, the logging machine data has more value to IT to give incites on how to improve your, uh SLA's and your you know within the scope of IT. But the business data really will impact the business, the whole entire University for us. So, One of the things we're doing on the business side with the business data is to provide some analytics on students um, the student data in order to um, increase their chances for success so getting all of that data. Doing some reports and pattern analytics. And then yeah, and then coaching students. >> Not a bad place to live in San Diego. >> Oh It's excellent >> Isn't it, the weather's always perfect >> Oh yeah. >> The marine layers not as bad L.A. you know, or is it? >> Yeah we do have a good. University- >> The marine layer. >> University is right on the coast. So yeah, sometimes its gloomy the whole entire day. = [John] Yeah, I love it there I wish I could have gone to school at the university of San Diego >> It is great, It's a great place to be >> Love to go see my friends at Lajolla Del mar. >> Yeah >> Beautiful areas, >> Yup >> Great country. Well thank you for coming on, and sharing your insights into multi-cloudism and that thinking. It seems you're very foundational right now. In this whole thinking there's no master plan yet. People are really having good conversations around how to set it all up. >> Yup >> The architecture, >> Right >> The role, >> Yup >> You see the same thing? >> Yes architecture is actually a very essential piece of it because you need to plan before you go if you go without planning I think your bill is going be Up the roof, so it yeah >> So you'll sink in the quicksand of the data lake And get sucked into the data swamp >> Yeah, Right, yeah so, architecture is a big piece of it Design, and then build and then continuous improvement That's a huge thing at UC of San Diego >> You know what I get excited about, Is I get excited about real time, how real time, time series data is becoming a big part of the application development and understanding the context between good data and bad data, is always a hard problem a hard tech problem6. >> Yeah that is true, yeah their are a lot of processes that, uh should be set around the data to make sure that data is clean, and it's, a good data set and all that >> If data's an asset then does it have a value? Does it have a balance sheet? Should we value the data? Is some data more valuable then others? That's a good question, huh >> That is a good question, but I don't know the answer to that. >> No one knows it's like we always ask the question I think that's going to, I think that's a future state where at some point data can be recognized but right now it's hard to tell what's valuable or not. >> I think the value is in the return services And the value added services, that you As an organization, can bring to your customer base. This is where the value is and if you want to put a dollar amount on that, eheh, I don't know It's not my job >> And of course multiden here, Multi-clouds All have it and of course thank you so much for coming on Special time conversation. Keep conversation here theCube coverage. Of the first inaugural multi-cloud conference call to escape nineteen. Where the industry best are coming together practitioners, entrepenures, founders, executives and thought leaders, talking about what multi-cloud really can be and foundationally what it needs to be in place and this is what happens here at these conferences Tons of hallway conversations Natalie thank you for spending the time. Cube coverage. I'm John Furrier, thanks for watching. (simple upbeat music)

[Announcer] - From New York, it's theCUBE! Covering ESCAPE/19. >> Hello, welcome back to theCUBE coverage here in New York City for the first inaugural Multi-Cloud Conference called ESCAPE/2019. I'm John Furrier, host of theCUBE. We're here with Natalie Gholmieh who is the Manager of Data and Integration Services at the University of California San Diego campus/office- sprawling data center, tons of IT, a lot of challenges, welcome. >> Yeah, thank you for having me. >> So, thanks for taking the time out. You're a practitioner, you're here. Why are you at this conference? What are you hoping to gain from here? What interests you here at the Multi-Cloud Escape Conference? >> So, this conference is very much within the spirit of what we're trying to do. Our CIO has directives which is to avoid lock-in, to do multi-vendor orchestration, to go with containers first, and open-source wherever possible. So, this conference pretty much speaks to all of that. >> So, this is a really interesting data point, because it seems the common thread is data. >> Mhmm. >> The cloud is an integration of things, so people are trying to find that integration point so they can have multiple vendors, multiple clouds. It seems like the multi-vendor world back in the old days, where you had multiple vendors, heterogeneous environment, data seems to be the linchpin in all this. >> Right, yes. >> That's what you do. >> Right. >> How do you think about this? Because it used to be that the big database ran the world, now you have lots of databases, you have applications. >> Right, yeah. >> Databases are everywhere now. >> Data is born in multiple systems, but the data is also an asset right now to all of the organizations, including the university. So, what we want to try to accomplish is to get all of this data possibly in one place, or in multiple places, and be able to do analytics on top of this, and this is what the value-added processing over the data. >> What's exciting to you these days in the University? You guys try to change the business, could be technology? What are the cool things that you like, that you're working with right now, or that you envision emerging? >> Yeah. So, my team is currently building a platform to do all of the data integration and we are planning to offer this platform as a service to developers to streamline and standardize application development, as well as integration development, within the central IT at the University. So this is pretty much the most exciting thing that we're doing, is putting together this platform that is quite complex, it is a journey that we're taking together with the people who already operate the existing systems. So we're putting up this new thing that we're operating in parallel and then we will be migrating to that new platform. >> I'm sure containers are involved, >> Yes. >> Kubernetes is a key part of it. >> Yes, mhmm. So, the platform has two parts. There is the application publishing with Docker and Kubernetes, and we also have the streaming side of it, to build the data pipeline with open-source tools like Apache NiFi and Apache Kafka. So this is going to be wiring the data pipelines from source to target and moving the data in real time in order to- >> And you see that as a nice way to keep an option to move from cloud to cloud? >> Potentially, since the platform's role is to decouple the infrastructure from development. That way, you could spin a portion of the platform on any cloud, pretty much, and run your workload anywhere you want. >> So classic DevOps. >> Yeah. >> Separate infrastructure as code, provide a codified layer. >> Yeah. >> So, let me ask you a question. How did you get into all this data business? I mean, what attracted you to the data field? What's your story? Tell us your story. >> So, the data, you know, I personally started, I mean, I had more of a networking background. Then I became Sys Admin, then I got into the business of logging and log aggregation for machine data, and then I was, you know, using that data to create dashboards of system health and, you know, data correlation, and this is what exposed me, personally, first to the data world, and then I saw the value in doing all of this with data, and the value is even more impactful to the business when you're working with actual business data. So I'm very excited about that. >> So you were swimming in the first data lake before data lakes were data lakes. >> Yes, yeah, right, for machine data. >> Once you're in there, you see value, the data exhaust comes in, as we used to say back in the day, data exhaust! >> Yeah. >> So, now that you're dealing with the business value, is the conversation the same? Or are they different conversations? Or is it still the same, kind of, data conversation? Or is the job the same? Because you still have machine data, applications are throwing off data, you have infrastructure data being thrown off, you have new software layers. >> Yes, yeah. >> Is it the same, or is it different? Describe your current situation. >> You know, maybe the concepts are the same, but I think the logging machine data has more value to IT to give insights on how to improve your SLAs, within the scope of IT, but the business data really will impact the business, the whole entire university for us. So, one of the things that we're doing on the business side with the business data is to provide some analytics on the student data in order to increase their chances for success. So, getting all of that data, doing some reports and pattern analytics, and then coaching the students. >> Not a bad place to live, in San Diego, is it? >> Oh, it's excellent. >> Weather's always perfect? >> Oh, yeah. >> Marine layer's not as bad as L.A., but, you know. >> Yeah. >> Or is it? >> No, we do have- The university is right on the coast, so yeah. Sometimes it's gloomy the whole entire day. >> I love it there. I wish I could've gone to school at the University of San Diego. >> It is great. It's a great place to be. >> Love to go down, see my friends in La Jolla, Del Mar, beautiful areas. Great country. >> Yeah. >> Well, thank you for coming on and sharing your insights into multi-cloud and some of the thinking. It seems to be very foundational right now in its whole thinking. >> Mhmm. >> There's no master plan yet. People are really having good conversations around how to set it all up. >> Yeah. >> The architecture. >> Right. >> The role. >> Yeah, yeah. >> Do you see the same thing? >> Yes, architecture is actually a very essential piece of it because you need to plan before you go. If you go without planning, I think your bill is going to be off the roof. >> Huge bill. >> Yeah. >> And you'll sink in the quicksand and the data lake and you can be sucked into the data swamp. >> Yeah. Right. Yeah. So, architecture is a big piece of it, design, then build, and then continuous improvement, that's a huge thing at UC San Diego. >> You know what I get excited about? I get excited about real time, and how real time, time series data is becoming a big part of the application development, and understanding the context between good data and bad data. >> Mhmm. >> It's always a hard problem. It's a hard tech problem. >> Yeah, that is true, yeah. There are a lot of processes that should be set around the data to make sure the data's clean and it's a good data set and all of that. >> If data's an asset, then has it got a value? Is it on the balance sheet? Shouldn't we value the data? Some data's more valuable than others? It's a good question, huh? >> It is a good question, but I don't know the answer to that. >> No one knows. We always ask the question. I think that's a future state where at some point, data can be recognized, but right now it's hard to tell what's valuable or not. >> I think the value is in the returned services and the value-added services that you, as an organization, can bring to your customer base. This is where the value is, and if you want to put a dollar amount on that, I don't know, it's not my job. >> Thank you so much for coming on, special time of conversation. >> Thank you. >> CUBE Conversation here, the CUBE Coverage of the first inaugural Multi-Cloud Conference called ESCAPE/19, where the industry best are coming together. Practitioners, entrepreneurs, founders, executives, and finally, just talking about what multi-cloud really can be, foundationally what needs to be in place. And this is what happens here at these conferences, tons of hallway conversations. Natalie, thank you for spending the time with us. CUBE Coverage, I'm John Furrier. Thanks for watching.

>> Live from Las Vegas. It's the queue covering Adobe Summit twenty nineteen brought to you >> by Adobe. >> Well, Brian, welcome to the Cube Lives Conversations here. Recovering Adobe summat twenty nineteen in Las Vegas. I'm tougher with Jeff Frick co hosting for the next two days wall to wall coverage around Adobe Summit, a company that is transformed from some making software to being a full blown cloud and data provider. Changing the user experience That's our Kino revue. Jeff, this morning was the keynote. The CEO Sean Tom knew no. Ryan took over in two thousand seven. Bruce Chizen Cube alumni, right. What a transformation. They actually did it. They kind of kept down low. But over those years absolutely changed the face of Adobe. We're seeing it now with a slew of acquisitions. Now seventeen thousand people attending this conference. This is kind of interesting story, your thoughts >> a lot of interesting stuff going on here, John and I think fundamentally they they took the risk right. They change your business from a by a news buying new license every year for eight hundred bucks. Nine hundred bucks, whatever used to be for Creative Cloud to go to an online model. And I think what was interesting about what Johnson, who said, is when you are when you're collecting money monthly, you have to deliver value monthly. And it completely changed the way that they paste their company the way they deliver products the way their product development works. And they moved to as we talked about all the time, instead of a sample of data that's old and making decisions. Now you can make decisions based on real time data in the way people are actually using the product. And so they've driven that transformation. And then now, by putting your whole sweet and with these gargantuan acquisitions of Mar Keto, now they're helping their customers really make that transition to a really time dynamic, digitally driven, data driven enterprise to drive this customer experience. >> It's interesting. Adobes, transformations, realist, legit It happened. It's happening. It's interesting, Jeff, you and I both live in Palo Alto, and I was looking through my Lincoln and my Facebook. There's literally dozens of friends and your colleagues over the years that I've interfaced with that all work at Adobe but feed all the acquisitions. They've built quite a huge company, and they brought a different set of experiences, and this is the to be the big story. That hasn't been told yet. Adobe again. This our first time covering Adobe Summit and excited to be here and continue to cover this. But here's what's going on That's really important. They transformed and are continuing Transformer. They did it in a way that was clever, smart and very predictive in their mind. They took a slow, slow approach to getting it right, and we heard the CEO talk about this. They had an old software model that was too slow. They want to attract the next generation of users, and they wanted to reimagine their product and the ecosystem changed their business model and change their engagement with customers. Very targeted in its approach, very specific to their business model. And their goals were innovate faster, moved to the cloud moved to a subscription based business model. But that's not it. Here the story is, the data equation was some kind of nuances in the keynote, like we didn't get the data right. Initially, we got cloud right, but data is super important, and then they got it right, and that's the big story. Here is the data driven and this is the playbook. I mean, you can almost substitute Adobe for your company. If someone's looking to do Tracy, pick your spots, execute, don't just talk about >> it, right? Right? Yeah. They call it the DDO in the data driven operating model, and he pulled up the dash board with some fake data talked about The management team runs off of this data, and when you know it's everything from marketing spend and direct campaigns and where people are sampling, there was a large conversation, too, about the buyer journey. But to me, the most important part is the buying act is not the end of the story, right. You want to continue to engage with that customer wherever and however, and whenever they want you. There was an interesting stat that came out during the keynote, where you know the more platforms your customer engages with you, the much higher the likelihood that they're goingto that they're going to renew, that they're going to retain so to me. I think you know, we talk a lot about community and engagement and this experience concept where the product is a piece of the puzzle, but it's not. It's not the most important piece that might be the piece Well, what she experiences built around, but it's It's just a simple piece. I think the guy from Best Buy was phenomenal. The story, the transformation, that company. But they want to be your trusted. A provider of all these services of two hundred dollars a year. They'LL come take care of everything in your home so you know they don't just want to ship a box. Say, say goodbye. They want to stay. >> Well, let's talk. Let's talk about that use case. I think the best bike Kino Best Buy was on the Kino with CEO. But I think that what I what? I was teasing out of that interview and you just brought it up. I want to expand on that They actually had massive competition from Amazon. So you think, Oh my God, they're going to be out of business? No, they match the price. They took price off the table so they don't lose their customers who want to buy it on Amazon. You can still come in the story of experience, right? They shifted the game to their advantage where they said, we're not going to be a product sales company. We're going to sell whatever the client want customers want and match Amazons pricing and then provide that level of personalization. That then brought up the keys CEOs personalization piece, which I'd like to get your thoughts on because you made a stat around their emails, right, he said, Quote personalization at scale, Right? That's what they're >> that's that they're doing right? And he talked about, you know, they used to do an e mail blast and it was an email blast. Now they have forty million versions of that e mail that go out forty million version. So it is this kind of personalization at scale. And you know, the three sixty view of the customer has been thrown around. We could go in the archives. We've been talking about that forever. But it seems that now you know the technology is finally getting to where, where needs to be. The cloud based architectures allow people to engage in this Army Channel way that they could never do it before. And you're seeing As you said, the most important thing is a data architecture that can pull from disparate sources they talked about in the Kenya. The show does they actually built their customer profile as the person was engaging with the website as they gave more information so that they can customize all this stuff for that person. Of course, then they always mentioned, But don't be creepy about it. I >> don't have too >> far so really delivering this mask mask, personalization at scale. >> I think one of the lessons that's coming out a lot of our interviews in the Cube is Get the cloud equation right first, then the data one. And I think Adobe validates that here in my mind when it continue investigating, report that dynamic the hard news. Jeff The show was Adobe Cloud experiences generally available, and I thought that was pretty interesting. They have a multiple clouds because a member they bought Magenta and Marquette on a variety of other acquisitions. So they have a full on advertising cloud analytics, cloud marketing cloud and a commerce cloud. And underneath those key cloud elements, they have Adobe, sensi and Adobe Experience platform, and we have a couple of night coming on to talk about that, and that's making up. They're kind of the new new platform. Cloud platforms experience Cloud. They're calling it, but the CEO at Incheon quote. I want to get your reaction to that. This, he said, quote people by experiences, not products. That's why they're calling it the experience cloud. I hear you in the office all the time talking about this, Jeff. So it's about to experience the product anymore, >> right? It is the passion that you can build around a community in that experience. My favorite examples from the old days is Harley Davidson. How many people would give you know they're left pinkie toe, have their customers tattoo their brand on their body? Right in The Harley Davidson brand is a very special, a special connotation, and the people that associate with that really feel like a part of a community. The other piece of it is the ecosystem. They talk about ecosystem of developers and open source. If you can get other people building their business on the back of your platform again, it's just deepens the hook of engagements that opens up your innovation cycle. And I think it's such a winning formula, John, that we see over and over again. Nobody can do by themselves. Nobody's got all the smartest people in the room, so get unengaged community. Get unengaged, developer ecosystem, more talk of developers and really open it up and let the creativity of your whole community drive the engagement and the experience. >> We will be following the personalization of scale Cube alumni former keep alumni who is not at the show. I wanted to get opinion. Satya Krishna Swami. He's head of persuasion. Adobe had pinned them on linked him. We'LL get him on the Cuban studio so keep on, we're going to follow that story. I think that's huge. This notion of personalization of scale is key, and that brings us to the next big news. The next big news was from our friend former CEO of Marquette. Oh, Steve Lucas. Keep alumni. They launched a account based experience initiative with Adobe, Microsoft and Lincoln, and I find that very interesting. And I'd start with Ron Miller TechCrunch on Twitter about this. Lincoln's involved, but they're keeping in Lincoln again. The problem of data is you have these silos, but you have to figure out how to make it work. So I'm really curious to see how that works, so that brings up that. But I think Steve Lucas it was it was very aggressive on stage, but he brought up a point that I want to get your thoughts on, He said. Were B to B company, but we're doing B to seeing metrics the numbers that they were doing at Marquette. Oh, we're in the B to see rain. So is this notion of B to B B to see kind of blurring? I mean, everyone is a B to C company these days. If everything's direct to consumer, which essentially what cloud is, it's a B to see. >> Yeah, well, it's interesting records. We've talked about the consumer ization of again. Check the tapes for years and years and years, and the expectations of our engagement with applications is driven by how we interact with Amazon. How we interact with Facebook, how we interact with these big platforms. And so you're seeing it more and more. The thing that we talked about in studio the other day with Guy is that now, too, you have all these connected devices, so no longer is distribution. This this buffer between the manufacturing, the ultimate consumer, their products. Now they're all connected. Now they phone home. Now the Tesla's says, Hey, people are breaking in the back window. Let's reconfigure the software tohave a security system that we didn't have yesterday that wasn't on our road map. But people want, and now we have it today. So I think Steve's perception is right on. The other thing is that you know, there's so much information out there. So how do you add value when that person finally visits you in their journey? And let's face it, most of the time, a predominant portion of their engagement is going to be Elektronik, right? They're going to fill out a form. They're going to explore things. How are you collecting that data? How are you magic? How are you moving them along? Not only to the purchase but again, is that it was like to say, is never the orders, the reorder in this ongoing engagement. >> And that's their journey. They want to have this whole life cycle of customer experience. But the thing that that got that caught me off guard by McKeen against first time I went satin Aquino for an adobe on event was with me. All these parts coming together with the platform. This is a cloud show. Let's plain and simple. This is Cloud Technologies, the data show we've gone to all the cloud shows Amazon, Google, Microsoft, you name it CNC Athletics Foundation. This is a show about the application of being creative in a variety of use cases. But the underpinnings of the conversations are all cloud >> right, And they had, you know, to show their their commitments of data and the data message right? They had another cube alumni on Jewell of police have rounded to dupe some it all the time, and she talked about the data architecture and again, some really interesting facts goes right to cloud, she said. You know, most people, if you don't have cloud's been too much time baby sitting your architecture, baby sitting your infrastructure Get out of the way Let the cloud babe sit your infrastructure and talk. And she talked about a modern big data pipe, and she's been involved with Duke. She's been involved with Spark has been involved in all this progression, and she said, You know, every engagement creates more data. So how are you collecting that data? How are you analyzing that data and how are you doing it in real time with new real time so you could actually act on it. So it's It's very much kind of pulling together many of the scenes that we've uncovered >> in the last two parts of a Kino wass. You had a CEO discussion between Cynthia Stoddard and >> Atticus Atticus, other kind. Both of them >> run into it again. Both big Amazon customs, by the way, who have been very successful with the cloud. Then you had and you're talking engineering, that's all. They're my takeaway from the CEO. One chef I want to get your thoughts on because it can be long in the tooth, sometimes the CEO conversation. But they highlighted that cloud journey is is there for Adobe Inn into it? But the data is has to be integrated, totally felt like data. Variables come out the commonality of date, and she mentioned three or four other things. And then they made a point and said, quote data architectures are valuable for the experience and the workload. This is critical with hearing us over and over again. The date is not about which cloud you're using. It's about what the workload, right, right? The workloads are determining cloud selection, so if you need one cloud. That's good. You need to write. It's all depending on the workload, not some predetermined risk management. Multi cloud procurement decision. This is a big shift. This is going to change the game in the landscape because that changes how people buy and that is going to be radical. And I think they're they're adobes right on the right wave. Here they're focusing on the user experience, customer experience, building the platform for the needs of the experience. I think it's very clever. I think it's a brilliant architecture. >> Yeah, she said that the data archive data strategy lagged. Right? The reporting lag. They're trying to do this ddo m >> um, >> they didn't have commonality of data. They didn't have really a date. Architecture's so again. You can't build the house unless you put in the rebar. You build the foundation, you get some cement. But once you get that, that enabled you to build something big and something beautiful, and you've got to pay attention. But really, we talk about data driven. We talk about real time data, they're executing it and really forcing themselves by moving into the subscription business model. >> Alright, Final question I want to get one more thought from you before I weigh in on my my answer to my question, which is What do you mean your opinion? What was the most important story that came out of the keynote one or two >> or well or again? You know, John, I was in the TV business for years and years before getting into tech, and I know the best buy story on what came before them and what came before them and what came before them. So what really impressed me was the digital transformation story that the CEO shared first, to basically try to get even with their number one competitors with which was Amazon in terms of pricing and delivery. And then really rethink who they are Is a company around using technology to improve people's lives. They happen to play in laundry. They play in kitchen, they play in home entertainment. They play in computers and education, so they have a broad footprint and to really refocus. And as he said, To be successful, you need to align your corporate strategy and mission with people's strategy and mission. Sounds like they've been very successful in that and they continue to change the company. >> I agree. And I would just kind of level it up and say the top story, in my opinion, wass the fact that Adobe is winning their innovating. If you look at who's on stage like best buy into it, the people around them are actually executing with Cloud with Dae that at a whole another level that they've gone the next level. I think the big story here is Adobe has transferred, has transformed and continues to do transformation. And they just had a whole nother level. And I think the story is Oracle will be eating their dust because I think they're going to tow. You know, I think sales force should be watching Adobe. This is a big move. I think Oracle is gonna be twisting in the wind from adobes success. >> Well, like he said, you know, they tie the whole thing together from the creativity, which is what creative cloud is to the delivery to them, the monetization in the measuring. So now they you know, they put those pieces together, so it's a pretty complete suite. So now you can tie back. How has my conversion based on What type of creative How is my conversion based on what type of campaigns? And again the forty million email number just blows me away. It's not the same game anymore. You have to do this and you can't do by yourself. You gotta have automation. You got have good analytics and you got a date infrastructure that will support your ability to do that. >> So just a little report card in adobe old suffer model that's over. They have the new model, and it's growing revenues supporting it. They are attracting new generation of users. You look at the demographics here, Jeff. This is not, you know, a bunch of forty something pluses here. This is a young generation new creative model and the products on the customer testimonials standing on this stage represent, in my opinion, a modern architecture, a modern practice, modern cloud kind of capabilities. So, you know, Adobe Certainly looking good from this keynote. I'm impressed, you know. Okay, >> good. Line up all the >> days of live cube coverage here in Las Vegas for Doby summit. I'm John for Jeff. Rick, Thanks for watching. We'll be back with a short break

[Music] [Music] [Music] [Laughter] [Laughter] [Laughter] [Laughter] [Music] [Music] [Music] [Music] you you [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] wake up feeling blessed peace you warned that Russia ain't afraid to show it I'll expose it if I dressed up riding in that Chester roasted nigga catch you slippin on myself rocks on I messed up like yes sir [Music] [Music] [Music] [Music] our program [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] you are not welcome to Red Hat summit 2018 2018 [Music] [Music] [Music] [Laughter] [Music] Wow that is truly the coolest introduction I've ever had thank you Wow I don't think I feel cool enough to follow an interaction like that Wow well welcome to the Red Hat summit this is our 14th annual event and I have to say looking out over this audience Wow it's great to see so many people here joining us this is by far our largest summit to date not only did we blow through the numbers we've had in the past we blew through our own expectations this year so I know we have a pretty packed house and I know people are still coming in so it's great to see so many people here it's great to see so many familiar faces when I had a chance to walk around earlier it's great to see so many new people here joining us for the first time I think the record attendance is an indication that more and more enterprises around the world are seeing the power of open source to help them with their challenges that they're facing due to the digital transformation that all of enterprises around the world are going through the theme for the summit this year is ideas worth exploring and we intentionally chose that because as much as we are all going through this digital disruption and the challenges associated with it one thing I think is becoming clear no one person and certainly no one company has the answers to these challenges right this isn't a problem where you can go buy a solution this is a set of capabilities that we all need to build it's a set of cultural changes that we all need to go through and that's going to require the best ideas coming from so many different places so we're not here saying we have the answers we're trying to convene the conversation right we want to serve as a catalyst bringing great minds together to share ideas so we all walk out of here at the end of the week a little wiser than when we first came here we do have an amazing agenda for you we have over 7,000 attendees we may be pushing 8,000 by the time we got through this morning we have 36 keynote speakers and we have a hundred and twenty-five breakout sessions and have to throw in one plug scheduling 325 breakout sessions is actually pretty difficult and so we used the Red Hat business optimizer which is an AI constraint solver that's new in the Red Hat decision manager to help us plan the summit because we have individuals who have a clustered set of interests and we want to make sure that when we schedule two breakout sessions we do it in a way that we don't have overlapping sessions that are really important to the same individual so we tried to use this tool and what we understand about people's interest in history of what they wanted to do to try to make sure that we spaced out different times for things of similar interests for similar people as well as for people who stood in the back of breakouts before and I know I've done that too we've also used it to try to optimize room size so hopefully we will do our best to make sure that we've appropriately sized the spaces for those as well so it's really a phenomenal tool and I know it's helped us a lot this year in addition to the 325 breakouts we have a lot of our customers on stage during the main sessions and so you'll see demos you'll hear from partners you'll hear stories from so many of our customers not on our point of view of how to use these technologies but their point of views of how they actually are using these technologies to solve their problems and you'll hear over and over again from those keynotes that it's not just about the technology it's about how people are changing how people are working to innovate to solve those problems and while we're on the subject of people I'd like to take a moment to recognize the Red Hat certified professional of the year this is known award we do every year I love this award because it truly recognizes an individual for outstanding innovation for outstanding ideas for truly standing out in how they're able to help their organization with Red Hat technologies Red Hat certifications help system administrators application developers IT architects to further their careers and help their organizations by being able to advance their skills and knowledge of Red Hat products and this year's winner really truly is a great example about how their curiosity is helped push the limits of what's possible with technology let's hear a little more about this year's winner when I was studying at the University I had computer science as one of my subjects and that's what created the passion from the very beginning they were quite a few institutions around my University who were offering Red Hat Enterprise Linux as a course and a certification paths through to become an administrator Red Hat Learning subscription has offered me a lot more than any other trainings that have done so far that gave me exposure to so many products under red hair technologies that I wasn't even aware of I started to think about the better ways of how these learnings can be put into the real life use cases and we started off with a discussion with my manager saying I have to try this product and I really want to see how it really fits in our environment and that product was Red Hat virtualization we went from deploying rave and then OpenStack and then the open shift environment we wanted to overcome some of the things that we saw as challenges to the speed and rapidity of release and code etc so it made perfect sense and we were able to do it in a really short space of time so you know we truly did use it as an Innovation Lab I think idea is everything ideas can change the way you see things an Innovation Lab was such an idea that popped into my mind one fine day and it has transformed the way we think as a team and it's given that playpen to pretty much everyone to go and test their things investigate evaluate do whatever they like in a non-critical non production environment I recruited Neha almost 10 years ago now I could see there was a spark a potential with it and you know she had a real Drive a real passion and you know here we are nearly ten years later I'm Neha Sandow I am a Red Hat certified engineer all right well everyone please walk into the states to the stage Neha [Music] [Applause] congratulations thank you [Applause] I think that - well welcome to the red has some of this is your first summit yes it is thanks so much well fantastic sure well it's great to have you here I hope you have a chance to engage and share some of your ideas and enjoy the week thank you thank you congratulations [Applause] neha mentioned that she first got interest in open source at university and it made me think red hats recently started our Red Hat Academy program that looks to programmatically infuse Red Hat technologies in universities around the world it's exploded in a way we had no idea it's grown just incredibly rapidly which i think shows the interest that there really is an open source and working in an open way at university so it's really a phenomenal program I'm also excited to announce that we're launching our newest open source story this year at Summit it's called the science of collective discovery and it looks at what happens when communities use open hardware to monitor the environment around them and really how they can make impactful change based on that technologies the rural premier that will be at 5:15 on Wednesday at McMaster Oni West and so please join us for a drink and we'll also have a number of the experts featured in that and you can have a conversation with them as well so with that let's officially start the show please welcome red hat president of products and technology Paul Cormier [Music] Wow morning you know I say it every year I'm gonna say it again I know I repeat myself it's just amazing we are so proud here to be here today too while you all week on how far we've come with opens with open source and with the products that we that we provide at Red Hat so so welcome and I hope the pride shows through so you know I told you Seven Summits ago on this stage that the future would be open and here we are just seven years later this is the 14th summit but just seven years later after that and much has happened and I think you'll see today and this week that that prediction that the world would be open was a pretty safe predict prediction but I want to take you just back a little bit to see how we started here and it's not just how Red Hat started here this is an open source in Linux based computing is now in an industry norm and I think that's what you'll you'll see in here this week you know we talked back then seven years ago when we put on our prediction about the UNIX error and how Hardware innovation with x86 was it was really the first step in a new era of open innovation you know companies like Sun Deck IBM and HP they really changed the world the computing industry with their UNIX models it was that was really the rise of computing but I think what we we really saw then was that single company innovation could only scale so far could really get so far with that these companies were very very innovative but they coupled hardware innovation with software innovation and as one company they could only solve so many problems and even which comp which even complicated things more they could only hire so many people in each of their companies Intel came on the scene back then as the new independent hardware player and you know that was really the beginning of the drive for horizontal computing power and computing this opened up a brand new vehicle for hardware innovation a new hardware ecosystem was built around this around this common hardware base shortly after that Stallman and leanness they had a vision of his of an open model that was created and they created Linux but it was built around Intel this was really the beginning of having a software based platform that could also drive innovation this kind of was the beginning of the changing of the world here that system-level innovation now having a hardware platform that was ubiquitous and a software platform that was open and ubiquitous it really changed this system level innovation and that continues to thrive today it was only possible because it was open this could not have happened in a closed environment it allowed the best ideas from anywhere from all over to come in in win only because it was the best idea that's what drove the rate of innovation at the pace you're seeing today and it which has never been seen before we at Red Hat we saw the need to bring this innovation to solve real-world problems in the enterprise and I think that's going to be the theme of the show today you're going to see us with our customers and partners talking about and showing you some of those real-world problems that we are sought solving with this open innovation we created rel back then for this for the enterprise it started it's it it wasn't successful because it's scaled it was secure and it was enterprise ready it once again changed the industry but this time through open innovation this gave the hardware ecosystem a software platform this open software platform gave the hardware ecosystem a software platform to build around it Unleashed them the hardware side to compete and thrive it enabled innovation from the OEMs new players building cheaper faster servers even new architectures from armed to power sprung up with this change we have seen an incredible amount of hardware innovation over the last 15 years that same innovation happened on the software side we saw powerful implementations of bare metal Linux distributions out in the market in fact at one point there were 300 there are over 300 distributions out in the market on the foundation of Linux powerful open-source equivalents were even developed in every area of Technology databases middleware messaging containers anything you could imagine innovation just exploded around the Linux platform in innovation it's at the core also drove virtualization both Linux and virtualization led to another area of innovation which you're hearing a lot about now public cloud innovation this innovation started to proceed at a rate that we had never seen before we had never experienced this in the past in this unprecedented speed of innovation and software was now possible because you didn't need a chip foundry in order to innovate you just needed great ideas in the open platform that was out there customers seeing this innovation in the public cloud sparked it sparked their desire to build their own linux based cloud platforms and customers are now are now bringing that cloud efficiency on-premise in their own data centers public clouds demonstrated so much efficiency the data centers and architects wanted to take advantage of it off premise on premise I'm sorry within their own we don't within their own controlled environments this really allowed companies to make the most of existing investments from data centers to hardware they also gained many new advantages from data sovereignty to new flexible agile approaches I want to bring Burr and his team up here to take a look at what building out an on-premise cloud can look like today Bure take it away I am super excited to be with all of you here at Red Hat summit I know we have some amazing things to show you throughout the week but before we dive into this demonstration I want you to take just a few seconds just a quick moment to think about that really important event your life that moment you turned on your first computer maybe it was a trs-80 listen Claire and Atari I even had an 83 b2 at one point but in my specific case I was sitting in a classroom in Hawaii and I could see all the way from Diamond Head to Pearl Harbor so just keep that in mind and I turn on an IBM PC with dual floppies I don't remember issuing my first commands writing my first level of code and I was totally hooked it was like a magical moment and I've been hooked on computers for the last 30 years so I want you to hold that image in your mind for just a moment just a second while we show you the computers we have here on stage let me turn this over to Jay fair and Dini here's our worldwide DevOps manager and he was going to show us his hardware what do you got Jay thank you BER good morning everyone and welcome to Red Hat summit we have so many cool things to show you this week I am so happy to be here and you know my favorite thing about red hat summit is our allowed to kind of share all of our stories much like bird just did we also love to you know talk about the hardware and the technology that we brought with us in fact it's become a bit of a competition so this year we said you know let's win this thing and we actually I think we might have won we brought a cloud with us so right now this is a private cloud for throughout the course of the week we're going to turn this into a very very interesting open hybrid cloud right before your eyes so everything you see here will be real and happening right on this thing right behind me here so thanks for our four incredible partners IBM Dell HP and super micro we've built a very vendor heterogeneous cloud here extra special thanks to IBM because they loaned us a power nine machine so now we actually have multiple architectures in this cloud so as you know one of the greatest benefits to running Red Hat technology is that we run on just about everything and you know I can't stress enough how powerful that is how cost-effective that is and it just makes my life easier to be honest so if you're interested the people that built this actual rack right here gonna be hanging out in the customer success zone this whole week it's on the second floor the lobby there and they'd be glad to show you exactly how they built this thing so let me show you what we actually have in this rack so contained in this rack we have 1056 physical chorus right here we have five and a half terabytes of RAM and just in case we threw 50 terabytes of storage in this thing so burr that's about two million times more powerful than that first machine you boot it up thanks to a PC we're actually capable of putting all the power needs and cooling right in this rack so there's your data center right there you know it occurred to me last night that I can actually pull the power cord on this thing and kick it up a notch we could have the world's first mobile portable hybrid cloud so I'm gonna go ahead and unplug no no no no no seriously it's not unplug the thing we got it working now well Berg gets a little nervous but next year we're rolling this thing around okay okay so to recap multiple vendors check multiple architectures check multiple public clouds plug right into this thing check and everything everywhere is running the same software from Red Hat so that is a giant check so burn Angus why don't we get the demos rolling awesome so we have totally we have some amazing hardware amazing computers on this stage but now we need to light it up and we have Angus Thomas who represents our OpenStack engineering team and he's going to show us what we can do with this awesome hardware Angus thank you Beth so this was an impressive rack of hardware to Joe has bought a pocket stage what I want to talk about today is putting it to work with OpenStack platform director we're going to turn it from a lot of potential into a flexible scalable private cloud we've been using director for a while now to take care of managing hardware and orchestrating the deployment of OpenStack what's new is that we're bringing the same capabilities for on-premise manager the deployment of OpenShift director deploying OpenShift in this way is the best of both worlds it's bare-metal performance but with an underlying infrastructure as a service that can take care of deploying in new instances and scaling out and a lot of the things that we expect from a cloud provider director is running on a virtual machine on Red Hat virtualization at the top of the rack and it's going to bring everything else under control what you can see on the screen right now is the director UI and as you see some of the hardware in the rack is already being managed at the top level we have information about the number of cores in the amount of RAM and the disks that each machine have if we dig in a bit there's information about MAC addresses and IPs and the management interface the BIOS kernel version dig a little deeper and there is information about the hard disks all of this is important because we want to be able to make sure that we put in workloads exactly where we want them Jay could you please power on the two new machines at the top of the rack sure all right thank you so when those two machines come up on the network director is going to see them see that they're new and not already under management and is it immediately going to go into the hardware inspection that populates this database and gets them ready for use so we also have profiles as you can see here profiles are the way that we match the hardware in a machine to the kind of workload that it's suited to this is how we make sure that machines that have all the discs run Seth and machines that have all the RAM when our application workouts for example there's two ways these can be set when you're dealing with a rack like this you could go in an individually tag each machine but director scales up to data centers so we have a rules matching engine which will automatically take the hardware profile of a new machine and make sure it gets tagged in exactly the right way so we can automatically discover new machines on the network and we can automatically match them to a profile that's how we streamline and scale up operations now I want to talk about deploying the software we have a set of validations we've learned over time about the Miss configurations in the underlying infrastructure which can cause the deployment of a multi node distributed application like OpenStack or OpenShift to fail if you have the wrong VLAN tags on a switch port or DHCP isn't running where it should be for example you can get into a situation which is really hard to debug a lot of our validations actually run before the deployment they look at what you're intending to deploy and they check in the environment is the way that it should be and they'll preempts problems and obviously preemption is a lot better than debugging something new that you probably have not seen before is director managing multiple deployments of different things side by side before we came out on stage we also deployed OpenStack on this rack just to keep me honest let me jump over to OpenStack very quickly a lot of our opens that customers will be familiar with this UI and the bare metal deployment of OpenStack on our rack is actually running a set of virtual machines which is running Gluster you're going to see that put to work later on during the summit Jay's gone to an awful lot effort to get this Hardware up on the stage so we're going to use it as many different ways as we can okay let's deploy OpenShift if I switch over to the deployed a deployment plan view there's a few steps first thing you need to do is make sure we have the hardware I already talked about how director manages hardware it's smart enough to make sure that it's not going to attempt to deploy into machines they're already in use it's only going to deploy on machines that have the right profile but I think with the rack that we have here we've got enough next thing is the deployment configuration this is where you get to customize exactly what's going to be deployed to make sure that it really matches your environment if they're external IPs for additional services you can set them here whatever it takes to make sure that the deployment is going to work for you as you can see on the screen we have a set of options around enable TLS for encryption network traffic if I dig a little deeper there are options around enabling ipv6 and network isolation so that different classes of traffic there are over different physical NICs okay then then we have roles now roles this is essentially about the software that's going to be put on each machine director comes with a set of roles for a lot of the software that RedHat supports and you can just use those or you can modify them a little bit if you need to add a monitoring agent or whatever it might be or you can create your own custom roles director has quite a rich syntax for custom role definition and custom Network topologies whatever it is you need in order to make it work in your environment so the rawls that we have right now are going to give us a working instance of openshift if I go ahead and click through the validations are all looking green so right now I can click the button start to the deploy and you will see things lighting up on the rack directors going to use IPMI to reboot the machines provisioned and with a trail image was the containers on them and start up the application stack okay so one last thing once the deployment is done you're going to want to keep director around director has a lot of capabilities around what we call de to operational management bringing in new Hardware scaling out deployments dealing with updates and critically doing upgrades as well so having said all of that it is time for me to switch over to an instance of openshift deployed by a director running on bare metal on our rack and I need to hand this over to our developer team so they can show what they can do it thank you that is so awesome Angus so what you've seen now is going from bare metal to the ultimate private cloud with OpenStack director make an open shift ready for our developers to build their next generation applications thank you so much guys that was totally awesome I love what you guys showed there now I have the honor now I have the honor of introducing a very special guest one of our earliest OpenShift customers who understands the necessity of the private cloud inside their organization and more importantly they're fundamentally redefining their industry please extend a warm welcome to deep mar Foster from Amadeus well good morning everyone a big thank you for having armadillos here and myself so as it was just set I'm at Mario's well first of all we are a large IT provider in the travel industry so serving essentially Airlines hotel chains this distributors like Expedia and others we indeed we started very early what was OpenShift like a bit more than three years ago and we jumped on it when when Retta teamed with Google to bring in kubernetes into this so let me quickly share a few figures about our Mario's to give you like a sense of what we are doing and the scale of our operations so some of our key KPIs one of our key metrics is what what we call passenger borders so that's the number of customers that physically board a plane over the year so through our systems it's roughly 1.6 billion people checking in taking the aircrafts on under the Amarillo systems close to 600 million travel agency bookings virtually all airlines are on the system and one figure I want to stress out a little bit is this one trillion availability requests per day that's when I read this figure my mind boggles a little bit so this means in continuous throughput more than 10 million hits per second so of course these are not traditional database transactions it's it's it's highly cached in memory and these applications are running over like more than 100,000 course so it's it's it's really big stuff so today I want to give some concrete feedback what we are doing so I have chosen two applications products of our Mario's that are currently running on production in different in different hosting environments as the theme here is of this talk hybrid cloud and so I want to give some some concrete feedback of how we architect the applications and of course it stays relatively high level so here I have taken one of our applications that is used in the hospitality environment so it's we have built this for a very large US hotel chain and it's currently in in full swing brought into production so like 30 percent of the globe or 5,000 plus hotels are on this platform not so here you can see that we use as the path of course on openshift on that's that's the most central piece of our hybrid cloud strategy on the database side we use Oracle and Couchbase Couchbase is used for the heavy duty fast access more key value store but also to replicate data across two data centers in this case it's running over to US based data centers east and west coast topology that are fit so run by Mario's that are fit with VMware on for the virtualization OpenStack on top of it and then open shift to host and welcome the applications on the right hand side you you see the kind of tools if you want to call them tools that we use these are the principal ones of course the real picture is much more complex but in essence we use terraform to map to the api's of the underlying infrastructure so they are obviously there are differences when you run on OpenStack or the Google compute engine or AWS Azure so some some tweaking is needed we use right at ansible a lot we also use puppet so you can see these are really the big the big pieces of of this sense installation and if we look to the to the topology again very high high level so these two locations basically map the data centers of our customers so they are in close proximity because the response time and the SLA is of this application is are very tight so that's an example of an application that is architectures mostly was high ability and high availability in minds not necessarily full global worldwide scaling but of course it could be scaled but here the idea is that we can swing from one data center to the unit to the other in matters of of minutes both take traffic data is fully synchronized across those data centers and while the switch back and forth is very fast the second example I have taken is what we call the shopping box this is when people go to kayak or Expedia and they're getting inspired where they want to travel to this is really the piece that shoots most of transit of the transactions into our Mario's so we architect here more for high scalability of course availability is also a key but here scaling and geographical spread is very important so in short it runs partially on-premise in our Amarillo Stata Center again on OpenStack and we we deploy it mostly in the first step on the Google compute engine and currently as we speak on Amazon on AWS and we work also together with Retta to qualify the whole show on Microsoft Azure here in this application it's it's the same building blocks there is a large swimming aspect to it so we bring Kafka into this working with records and another partner to bring Kafka on their open shift because at the end we want to use open shift to administrate the whole show so over time also databases and the topology here when you look to the physical deployment topology while it's very classical we use the the regions and the availability zone concept so this application is spread over three principal continental regions and so it's again it's a high-level view with different availability zones and in each of those availability zones we take a hit of several 10,000 transactions so that was it really in very short just to give you a glimpse on how we implement hybrid clouds I think that's the way forward it gives us a lot of freedom and it allows us to to discuss in a much more educated way with our customers that sometimes have already deals in place with one cloud provider or another so for us it's a lot of value to set two to leave them the choice basically what up that was a very quick overview of what we are doing we were together with records are based on open shift essentially here and more and more OpenStack coming into the picture hope you found this interesting thanks a lot and have a nice summer [Applause] thank you so much deeper great great solution we've worked with deep Marv and his team for a long for a long time great solution so I want to take us back a little bit I want to circle back I sort of ended talking a little bit about the public cloud so let's circle back there you know even so even though some applications need to run in various footprints on premise there's still great gains to be had that for running certain applications in the public cloud a public cloud will be as impactful to to the industry as as UNIX era was of computing was but by itself it'll have some of the same limitations and challenges that that model had today there's tremendous cloud innovation happening in the public cloud it's being driven by a handful of massive companies and much like the innovation that sundeck HP and others drove in a you in the UNIX era of community of computing many customers want to take advantage of the best innovation no matter where it comes from buddy but as they even eventually saw in the UNIX era they can't afford the best innovation at the cost of a siloed operating environment with the open community we are building a hybrid application platform that can give you access to the best innovation no matter which vendor or which cloud that it comes from letting public cloud providers innovate and services beyond what customers or anyone can one provider can do on their own such as large scale learning machine learning or artificial intelligence built on the data that's unique probably to that to that one cloud but consumed in a common way for the end customer across all applications in any environment on any footprint in in their overall IT infrastructure this is exactly what rel brought brought to our customers in the UNIX era of computing that consistency across any of those footprints obviously enterprises will have applications for all different uses some will live on premise some in the cloud hybrid cloud is the only practical way forward I think you've been hearing that from us for a long time it is the only practical way forward and it'll be as impactful as anything we've ever seen before I want to bring Byrne his team back to see a hybrid cloud deployment in action burr [Music] all right earlier you saw what we did with taking bare metal and lighting it up with OpenStack director and making it openshift ready for developers to build their next generation applications now we want to show you when those next turn and generation applications and what we've done is we take an open shift and spread it out and installed it across Asia and Amazon a true hybrid cloud so with me on stage today as Ted who's gonna walk us through an application and Brent Midwood who's our DevOps engineer who's gonna be making sure he's monitoring on the backside that we do make sure we do a good job so at this point Ted what have you got for us Thank You BER and good morning everybody this morning we are running on the stage in our private cloud an application that's providing its providing fraud detection detect serves for financial transactions and our customer base is rather large and we occasionally take extended bursts of traffic of heavy traffic load so in order to keep our latency down and keep our customers happy we've deployed extra service capacity in the public cloud so we have capacity with Microsoft Azure in Texas and with Amazon Web Services in Ohio so we use open chip container platform on all three locations because openshift makes it easy for us to deploy our containerized services wherever we want to put them but the question still remains how do we establish seamless communication across our entire enterprise and more importantly how do we balance the workload across these three locations in such a way that we efficiently use our resources and that we give our customers the best possible experience so this is where Red Hat amq interconnect comes in as you can see we've deployed a MQ interconnect alongside our fraud detection applications in all three locations and if I switch to the MQ console we'll see the topology of the app of the network that we've created here so the router inside the on stage here has made connections outbound to the public routers and AWS and Azure these connections are secured using mutual TLS authentication and encrypt and once these connections are established amq figures out the best way auda matically to route traffic to where it needs to get to so what we have right now is a distributed reliable broker list message bus that expands our entire enterprise now if you want to learn more about this make sure that you catch the a MQ breakout tomorrow at 11:45 with Jack Britton and David Ingham let's have a look at the message flow and we'll dive in and isolate the fraud detection API that we're interested in and what we see is that all the traffic is being handled in the private cloud that's what we expect because our latencies are low and they're acceptable but now if we take a little bit of a burst of increased traffic we're gonna see that an EQ is going to push a little a bi traffic out onto the out to the public cloud so as you're picking up some of the load now to keep the Layton sees down now when that subsides as your finishes up what it's doing and goes back offline now if we take a much bigger load increase you'll see two things first of all asher is going to take a bigger proportion than it did before and Amazon Web Services is going to get thrown into the fray as well now AWS is actually doing less work than I expected it to do I expected a little bit of bigger a slice there but this is a interesting illustration of what's going on for load balancing mq load balancing is sending requests to the services that have the lowest backlog and in order to keep the Layton sees as steady as possible so AWS is probably running slowly for some reason and that's causing a and Q to push less traffic its way now the other thing you're going to notice if you look carefully this graph fluctuate slightly and those fluctuations are caused by all the variances in the network we have the cloud on stage and we have clouds in in the various places across the country there's a lot of equipment locked layers of virtualization and networking in between and we're reacting in real-time to the reality on the digital street so BER what's the story with a to be less I noticed there's a problem right here right now we seem to have a little bit performance issue so guys I noticed that as well and a little bit ago I actually got an alert from red ahead of insights letting us know that there might be some potential optimizations we could make to our environment so let's take a look at insights so here's the Red Hat insights interface you can see our three OpenShift deployments so we have the set up here on stage in San Francisco we have our Azure deployment in Texas and we also have our AWS deployment in Ohio and insights is highlighting that that deployment in Ohio may have some issues that need some attention so Red Hat insights collects anonymized data from manage systems across our customer environment and that gives us visibility into things like vulnerabilities compliance configuration assessment and of course Red Hat subscription consumption all of this is presented in a SAS offering so it's really really easy to use it requires minimal infrastructure upfront and it provides an immediate return on investment what insights is showing us here is that we have some potential issues on the configuration side that may need some attention from this view I actually get a look at all the systems in our inventory including instances and containers and you can see here on the left that insights is highlighting one of those instances as needing some potential attention it might be a candidate for optimization this might be related to the issues that you were seeing just a minute ago insights uses machine learning and AI techniques to analyze all collected data so we combine collected data from not only the system's configuration but also with other systems from across the Red Hat customer base this allows us to compare ourselves to how we're doing across the entire set of industries including our own vertical in this case the financial services industry and we can compare ourselves to other customers we also get access to tailored recommendations that let us know what we can do to optimize our systems so in this particular case we're actually detecting an issue here where we are an outlier so our configuration has been compared to other configurations across the customer base and in this particular instance in this security group were misconfigured and so insights actually gives us the steps that we need to use to remediate the situation and the really neat thing here is that we actually get access to a custom ansible playbook so if we want to automate that type of a remediation we can use this inside of Red Hat ansible tower Red Hat satellite Red Hat cloud forms it's really really powerful the other thing here is that we can actually apply these recommendations right from within the Red Hat insights interface so with just a few clicks I can select all the recommendations that insights is making and using that built-in ansible automation I can apply those recommendations really really quickly across a variety of systems this type of intelligent automation is really cool it's really fast and powerful so really quickly here we're going to see the impact of those changes and so we can tell that we're doing a little better than we were a few minutes ago when compared across the customer base as well as within the financial industry and if we go back and look at the map we should see that our AWS employment in Ohio is in a much better state than it was just a few minutes ago so I'm wondering Ted if this had any effect and might be helping with some of the issues that you were seeing let's take a look looks like went green now let's see what it looks like over here yeah doesn't look like the configuration is taking effect quite yet maybe there's some delay awesome fantastic the man yeah so now we're load balancing across the three clouds very much fantastic well I have two minute Ted I truly love how we can route requests and dynamically load transactions across these three clouds a truly hybrid cloud native application you guys saw here on on stage for the first time and it's a fully portable application if you build your applications with openshift you can mover from cloud to cloud to cloud on stage private all the way out to the public said it's totally awesome we also have the application being fully managed by Red Hat insights I love having that intelligence watching over us and ensuring that we're doing everything correctly that is fundamentally awesome thank you so much for that well we actually have more to show you but you're going to wait a few minutes longer right now we'd like to welcome Paul back to the stage and we have a very special early Red Hat customer an Innovation Award winner from 2010 who's been going boldly forward with their open hybrid cloud strategy please give a warm welcome to Monty Finkelstein from Citigroup [Music] [Music] hi Marty hey Paul nice to see you thank you very much for coming so thank you for having me Oh our pleasure if you if you wanted to we sort of wanted to pick your brain a little bit about your experiences and sort of leading leading the charge in computing here so we're all talking about hybrid cloud how has the hybrid cloud strategy influenced where you are today in your computing environment so you know when we see the variable the various types of workload that we had an hour on from cloud we see the peaks we see the valleys we see the demand on the environment that we have we really determined that we have to have a much more elastic more scalable capability so we can burst and stretch our environments to multiple cloud providers these capabilities have now been proven at City and of course we consider what the data risk is as well as any regulatory requirement so how do you how do you tackle the complexity of multiple cloud environments so every cloud provider has its own unique set of capabilities they have they're own api's distributions value-added services we wanted to make sure that we could arbitrate between the different cloud providers maintain all source code and orchestration capabilities on Prem to drive those capabilities from within our platforms this requires controlling the entitlements in a cohesive fashion across our on Prem and Wolfram both for security services automation telemetry as one seamless unit can you talk a bit about how you decide when you to use your own on-premise infrastructure versus cloud resources sure so there are multiple dimensions that we take into account right so the first dimension we talk about the risk so low risk - high risk and and really that's about the data classification of the environment we're talking about so whether it's public or internal which would be considered low - ooh confidential PII restricted sensitive and so on and above which is really what would be considered a high-risk the second dimension would be would focus on demand volatility and responsiveness sensitivity so this would range from low response sensitivity and low variability of the type of workload that we have to the high response sensitivity and high variability of the workload the first combination that we focused on is the low risk and high variability and high sensitivity for response type workload of course any of the workloads we ensure that we're regulatory compliant as well as we achieve customer benefits with within this environment so how can we give developers greater control of their their infrastructure environments and still help operations maintain that consistency in compliance so the main driver is really to use the public cloud is scale speed and increased developer efficiencies as well as reducing cost as well as risk this would mean providing develop workspaces and multiple environments for our developers to quickly create products for our customers all this is done of course in a DevOps model while maintaining the source and artifacts registry on-prem this would allow our developers to test and select various middleware products another product but also ensure all the compliance activities in a centrally controlled repository so we really really appreciate you coming by and sharing that with us today Monte thank you so much for coming to the red echo thanks a lot thanks again tamati I mean you know there's these real world insight into how our products and technologies are really running the businesses today that's that's just the most exciting part so thank thanks thanks again mati no even it with as much progress as you've seen demonstrated here and you're going to continue to see all week long we're far from done so I want to just take us a little bit into the path forward and where we we go today we've talked about this a lot innovation today is driven by open source development I don't think there's any question about that certainly not in this room and even across the industry as a whole that's a long way that we've come from when we started our first summit 14 years ago with over a million open source projects out there this unit this innovation aggregates into various community platforms and it finally culminates in commercial open source based open source developed products these products run many of the mission-critical applications in business today you've heard just a couple of those today here on stage but it's everywhere it's running the world today but to make customers successful with that interact innovation to run their real-world business applications these open source products have to be able to leverage increase increasingly complex infrastructure footprints we must also ensure a common base for the developer and ultimately the application no matter which footprint they choose as you heard mati say the developers want choice here no matter which no matter which footprint they are ultimately going to run their those applications on they want that flexibility from the data center to possibly any public cloud out there in regardless of whether that application was built yesterday or has been running the business for the last 10 years and was built on 10-year old technology this is the flexibility that developers require today but what does different infrastructure we may require different pieces of the technical stack in that deployment one example of this that Effects of many things as KVM which provides the foundation for many of those use cases that require virtualization KVM offers a level of consistency from a technical perspective but rel extends that consistency to add a level of commercial and ecosystem consistency for the application across all those footprints this is very important in the enterprise but while rel and KVM formed the foundation other technologies are needed to really satisfy the functions on these different footprints traditional virtualization has requirements that are satisfied by projects like overt and products like Rev traditional traditional private cloud implementations has requirements that are satisfied on projects like OpenStack and products like Red Hat OpenStack platform and as applications begin to become more container based we are seeing many requirements driven driven natively into containers the same Linux in different forms provides this common base across these four footprints this level of compatible compatibility is critical to operators who must best utilize the infinite must better utilize secure and deploy the infrastructure that they have and they're responsible for developers on the other hand they care most about having a platform that can creates that consistency for their applications they care about their services and the services that they need to consume within those applications and they don't want limitations on where they run they want service but they want it anywhere not necessarily just from Amazon they want integration between applications no matter where they run they still want to run their Java EE now named Jakarta EE apps and bring those applications forward into containers and micro services they need able to orchestrate these frameworks and many more across all these different footprints in a consistent secure fashion this creates natural tension between development and operations frankly customers amplify this tension with organizational boundaries that are holdover from the UNIX era of computing it's really the job of our platforms to seamlessly remove these boundaries and it's the it's the goal of RedHat to seamlessly get you from the old world to the new world we're gonna show you a really cool demo demonstration now we're gonna show you how you can automate this transition first we're gonna take a Windows virtual machine from a traditional VMware deployment we're gonna convert it into a KVM based virtual machine running in a container all under the kubernetes umbrella this makes virtual machines more access more accessible to the developer this will accelerate the transformation of those virtual machines into cloud native container based form well we will work this prot we will worked as capability over the product line in the coming releases so we can strike the balance of enabling our developers to move in this direction we want to be able to do this while enabling mission-critical operations to still do their job so let's bring Byrne his team back up to show you this in action for one more thanks all right what Red Hat we recognized that large organizations large enterprises have a substantial investment and legacy virtualization technology and this is holding you back you have thousands of virtual machines that need to be modernized so what you're about to see next okay it's something very special with me here on stage we have James Lebowski he's gonna be walking us through he's represents our operations folks and he's gonna be walking us through a mass migration but also is Itamar Hine who's our lead developer of a very special application and he's gonna be modernizing container izing and optimizing our application all right so let's get started James thanks burr yeah so as you can see I have a typical VMware environment here I'm in the vSphere client I've got a number of virtual machines a handful of them that make up my one of my applications for my development environment in this case and what I want to do is migrate those over to a KVM based right at virtualization environment so what I'm gonna do is I'm gonna go to cloud forms our cloud management platform that's our first step and you know cloud forms actually already has discovered both my rev environment and my vSphere environment and understands the compute network and storage there so you'll notice one of the capabilities we built is this new capability called migrations and underneath here I could begin to there's two steps and the first thing I need to do is start to create my infrastructure mappings what this will allow me to do is map my compute networking storage between vSphere and Rev so cloud forms understands how those relate let's go ahead and create an infrastructure mapping I'll call that summit infrastructure mapping and then I'm gonna begin to map my two environments first the compute so the clusters here next the data stores so those virtual machines happen to live on datastore - in vSphere and I'll target them a datastore data to inside of my revenue Arman and finally my networks those live on network 100 so I'll map those from vSphere to rover so once my infrastructure is map the next step I need to do is actually begin to create a plan to migrate those virtual machines so I'll continue to the plan wizard here I'll select the infrastructure mapping I just created and I'll select migrate my development environment from those virtual machines to Rev and then I need to import a CSV file the CSV file is going to contain a list of all the virtual machines that I want to migrate that were there and that's it once I hit create what's going to happen cloud forms is going to begin in an automated fashion shutting down those virtual machines begin converting them taking care of all the minutia that you'd have to do manually it's gonna do that all automatically for me so I don't have to worry about all those manual interactions and no longer do I have to go manually shut them down but it's going to take care of that all for me you can see the migrations kicked off here this is the I've got the my VMs are migrating here and if I go back to the screen here you can see that we're gonna start seeing those shutdown okay awesome but as people want to know more information about this how would they dive deeper into this technology later this week yeah it's a great question so we have a workload portability session in the hybrid cloud on Wednesday if you want to see a presentation that deep dives into this topic and how some of the methodologies to migrate and then on Thursday we actually have a hands-on lab it's the IT optimization VM migration lab that you can check out and as you can see those are shutting down here yeah we see a powering off right now that's fantastic absolutely so if I go back now that's gonna take a while you got to convert all the disks and move them over but we'll notice is previously I had already run one migration of a single application that was a Windows virtual machine running and if I browse over to Red Hat virtualization I can see on the dashboard here I could browse to virtual machines I have migrated that Windows virtual machine and if I open up a tab I can now browse to my Windows virtual machine which is running our wingtip toy store application our sample application here and now my VM has been moved over from Rev to Vita from VMware to Rev and is available for Itamar all right great available to our developers all right Itamar what are you gonna do for us here well James it's great that you can save cost by moving from VMware to reddit virtualization but I want to containerize our application and with container native virtualization I can run my virtual machine on OpenShift like any other container using Huebert a kubernetes operator to run and manage virtual machines let's look at the open ship service catalog you can see we have a new virtualization section here we can import KVM or VMware virtual machines or if there are already loaded we can create new instances of them for the developer to work with just need to give named CPU memory we can do other virtualization parameters and create our virtual machines now let's see how this looks like in the openshift console the cool thing about KVM is virtual machines are just Linux processes so they can act and behave like other open shipped applications we build in more than a decade of virtualization experience with KVM reddit virtualization and OpenStack and can now benefit from kubernetes and open shift to manage and orchestrate our virtual machines since we know this virtual machine this container is actually a virtual machine we can do virtual machine stuff with it like shutdown reboot or open a remote desktop session to it but we can also see this is just a container like any other container in openshift and even though the web application is running inside a Windows virtual machine the developer can still use open shift mechanisms like services and routes let's browse our web application using the OpenShift service it's the same wingtip toys application but this time the virtual machine is running on open shift but we're not done we want to containerize our application since it's a Windows virtual machine we can open a remote desktop session to it we see we have here Visual Studio and an asp.net application let's start container izing by moving the Microsoft sequel server database from running inside the Windows virtual machine to running on Red Hat Enterprise Linux as an open shipped container we'll go back to the open shipped Service Catalog this time we'll go to the database section and just as easily we'll create a sequel server container just need to accept the EULA provide password and choose the Edition we want and create a database and again we can see the sequel server is just another container running on OpenShift now let's take let's find the connection details for our database to keep this simple we'll take the IP address of our database service go back to the web application to visual studio update the IP address in the connection string publish our application and go back to browse it through OpenShift fortunately for us the user experience team heard we're modernizing our application so they pitched in and pushed new icons to use with our containerized database to also modernize the look and feel it's still the same wingtip toys application it's running in a virtual machine on openshift but it's now using a containerized database to recap we saw that we can run virtual machines natively on openshift like any other container based application modernize and mesh them together we containerize the database but we can use the same approach to containerize any part of our application so some items here to deserve repeating one thing you saw is Red Hat Enterprise Linux burning sequel server in a container on open shift and you also saw Windows VM where the dotnet native application also running inside of open ships so tell us what's special about that that seems pretty crazy what you did there exactly burr if we take a look under the hood we can use the kubernetes commands to see the list of our containers in this case the sequel server and the virtual machine containers but since Q Bert is a kubernetes operator we can actually use kubernetes commands like cube Cpl to list our virtual machines and manage our virtual machines like any other entity in kubernetes I love that so there's your crew meta gem oh we can see the kind says virtual machine that is totally awesome now people here are gonna be very excited about what they just saw we're gonna get more information and when will this be coming well you know what can they do to dive in this will be available as part of reddit Cloud suite in tech preview later this year but we are looking for early adopters now so give us a call also come check our deep dive session introducing container native virtualization Thursday 2:00 p.m. awesome that is so incredible so we went from the old to the new from the close to the open the Red Hat way you're gonna be seeing more from our demonstration team that's coming Thursday at 8 a.m. do not be late if you like what you saw this today you're gonna see a lot more of that going forward so we got some really special things in store for you so at this point thank you so much in tomorrow thank you so much you guys are awesome yeah now we have one more special guest a very early adopter of Red Hat Enterprise Linux we've had over a 12-year partnership and relationship with this organization they've been a steadfast Linux and middleware customer for many many years now please extend a warm welcome to Raj China from the Royal Bank of Canada thank you thank you it's great to be here RBC is a large global full-service is back we have the largest bank in Canada top 10 global operate in 30 countries and run five key business segments personal commercial banking investor in Treasury services capital markets wealth management and insurance but honestly unless you're in the banking segment those five business segments that I just mentioned may not mean a lot to you but what you might appreciate is the fact that we've been around in business for over 150 years we started our digital transformation journey about four years ago and we are focused on new and innovative technologies that will help deliver the capabilities and lifestyle our clients are looking for we have a very simple vision and we often refer to it as the digitally enabled bank of the future but as you can appreciate transforming a hundred fifty year old Bank is not easy it certainly does not happen overnight to that end we had a clear unwavering vision a very strong innovation agenda and most importantly a focus towards a flawless execution today in banking business strategy and IT strategy are one in the same they are not two separate things we believe that in order to be the number one bank we have to have the number one tactic there is no question that most of today's innovations happens in the open source community RBC relies on RedHat as a key partner to help us consume these open source innovations in a manner that it meets our enterprise needs RBC was an early adopter of Linux we operate one of the largest footprints of rel in Canada same with tables we had tremendous success in driving cost out of infrastructure by partnering with rahat while at the same time delivering a world-class hosting service to your business over our 12 year partnership Red Hat has proven that they have mastered the art of working closely with the upstream open source community understanding the needs of an enterprise like us in delivering these open source innovations in a manner that we can consume and build upon we are working with red hat to help increase our agility and better leverage public and private cloud offerings we adopted virtualization ansible and containers and are excited about continuing our partnership with Red Hat in this journey throughout this journey we simply cannot replace everything we've had from the past we have to bring forward these investments of the past and improve upon them with new and emerging technologies it is about utilizing emerging technologies but at the same time focusing on the business outcome the business outcome for us is serving our clients and delivering the information that they are looking for whenever they need it and in whatever form factor they're looking for but technology improvements alone are simply not sufficient to do a digital transformation creating the right culture of change and adopting new methodologies is key we introduced agile and DevOps which has boosted the number of adult projects at RBC and increase the frequency at which we do new releases to our mobile app as a matter of fact these methodologies have enabled us to deliver apps over 20x faster than before the other point about around culture that I wanted to mention was we wanted to build an engineering culture an engineering culture is one which rewards curiosity trying new things investing in new technologies and being a leader not necessarily a follower Red Hat has been a critical partner in our journey to date as we adopt elements of open source culture in engineering culture what you seen today about red hearts focus on new technology innovations while never losing sight of helping you bring forward the investments you've already made in the past is something that makes Red Hat unique we are excited to see red arts investment in leadership in open source technologies to help bring the potential of these amazing things together thank you that's great the thing you know seeing going from the old world to the new with automation so you know the things you've seen demonstrated today they're they're they're more sophisticated than any one company could ever have done on their own certainly not by using a proprietary development model because of this it's really easy to see why open source has become the center of gravity for enterprise computing today with all the progress open-source has made we're constantly looking for new ways of accelerating that into our products so we can take that into the enterprise with customers like these that you've met what you've met today now we recently made in addition to the Red Hat family we brought in core OS to the Red Hat family and you know adding core OS has really been our latest move to accelerate that innovation into our products this will help the adoption of open shift container platform even deeper into the enterprise and as we did with the Linux core platform in 2002 this is just exactly what we did with with Linux back then today we're announcing some exciting new technology directions first we'll integrate the benefits of automated operations so for example you'll see dramatic improvements in the automated intelligence about the state of your clusters in OpenShift with the core OS additions also as part of open shift will include a new variant of rel called Red Hat core OS maintaining the consistency of rel farhat for the operation side of the house while allowing for a consumption of over-the-air updates from the kernel to kubernetes later today you'll hear how we are extending automated operations beyond customers and even out to partners all of this starting with the next release of open shift in July now all of this of course will continue in an upstream open source innovation model that includes continuing container linux for the community users today while also evolving the commercial products to bring that innovation out to the enterprise this this combination is really defining the platform of the future everything we've done for the last 16 years since we first brought rel to the commercial market because get has been to get us just to this point hybrid cloud computing is now being deployed multiple times in enterprises every single day all powered by the open source model and powered by the open source model we will continue to redefine the software industry forever no in 2002 with all of you we made Linux the choice for enterprise computing this changed the innovation model forever and I started the session today talking about our prediction of seven years ago on the future being open we've all seen so much happen in those in those seven years we at Red Hat have celebrated our 25th anniversary including 16 years of rel and the enterprise it's now 2018 open hybrid cloud is not only a reality but it is the driving model in enterprise computing today and this hybrid cloud world would not even be possible without Linux as a platform in the open source development model a build around it and while we have think we may have accomplished a lot in that time and we may think we have changed the world a lot we have but I'm telling you the best is yet to come now that Linux and open source software is firmly driving that innovation in the enterprise what we've accomplished today and up till now has just set the stage for us together to change the world once again and just as we did with rel more than 15 years ago with our partners we will make hybrid cloud the default in the enterprise and I will take that bet every single day have a great show and have fun watching the future of computing unfold right in front of your eyes see you later [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] anytime [Music]

(upbeat music) >> Live from Nassau in the Bahamas, it's theCUBE Covering Polycon '18. Brought to you by Polymath >> Okay, welcome back everyone. This is theCUBE's exclusive live coverage here in the Bahamas for Polycon '18, put on by Polymath and Grit Capital. I'm here with the CEO of both of those companies, who have been gracious enough to let us come in and tap into the bandwidth, tap into the guests, and host us here at theCUBE's two days of exclusive coverage. We have great guests, Trevor Koverko, CEO of Polymath, really changing the game. Security tokens are really kind of driving great, fast, accelerated innovation. And we have Genevieve Roch-Decter who's a CEO of Grit Capital, funding it, being part of it. You guys created a great community. Welcome to theCUBE! >> Great, thanks for having us. >> Thank you. >> So, live coverage, thank you very much. We really appreciate the collaboration with you guys, great guests. But there's something magical going on here. You've got a big even, couple hundred, 400 people. But it feels like the early days of, when I was in my 20s, the computer revolution, PC, and then the internet came. People are doing deals. This is a very intimate conference, you've got whales, billionaires, you've got entrepreneurs, you've got folks from investment banking companies coming into the sector, young guns, all dudes and gals. I mean, This is a melting pot! >> We have professional athletes, too, yeah, no we've really brought together a cluster of different zones, if you will. I come from the world of the Canadian equivalent of Wall Street, Bay Street, and so we've got institutional investors here who don't have wallets don't have coins, and are learning about it from the top Crypto minds in the world, so it's quite magical. I don't think Trevor and I have slept in 60 days. We literally came up with this idea, it's supposed to be a very intimate setting of 20 or 30 people and it's ballooned into 600, mostly because Trevor has so many friends and is partnering up with a lot of them on his projects, so yeah it's been a great time so far. >> And Trevor you, by the way, you're not sleeping 'cause everyone's staying out til two in the morning. It's been a great intimate gathering, people are mingling. But they're players, they're not pretenders here. This is a really interesting group, people who are investing their time, it's mission-driven here. We talk about societal change, but there's money-making going on, too, you're powering that, I mean you've got to be exhausted, how do you feel? >> I call it the eye of the hurricane, this was like if you weren't here this week, in crypto, you're just not relevant, this is where you wanted to be. And it's all about the attendees, the caliber of the people that came just blew me away, very humbled by the quality of people that we had here, it's no surprise, we have a beautiful venue like here in the Bahamas, and at Baha Mar, and amazing people. Good things are going to happen. >> Community is a very important formula for success in this world, we've seen this movie before, in open-source software It started out as a tier-2 citizen, now it runs softwares tier-1 class capabilities, cloud computing has been amazing growth, crypto, same model, you know, it's emerged as the money, the value store, technology-enablement. What are you guys seeing as the pattern, 'cause honestly, people recognize that certainly in the in industry. If you don't you're going to miss the boat on this one. Most people who don't get it will probably miss the boat. But a lot of people are getting in, what is the pattern that's happening, why is this moving so fast? Is it the wealth creation, is it the money-making? Is it the technology enablement, what's you guys' reaction to the why? What's the why, here? >> I think it's a convergence of a lot of mega-trends going on right now, both of the technology and on the regulatory side. If you look at, you know, the exciting sexiness of having this liquid tokens that kind of feel like stocks, but are also utilities in the sense that you can use them to do certain things with, that's a big component of it. But I think another reason is just, there's a lot of strangling going on in the capital markets, where you have a lot less companies going public, you have a lot more barriers to raise capital, in a lot of ways. And this is kind of like, light peeking through the hole. Where you have new ways re-imagined ways to raise capital. So we're seeing just a convergence of a lot of mega-trends, I think. >> And a lot of pros are coming in, and they're either young pros that are learning and growing with this trend, the young guns, I call them, and then you've got pros coming in from other industries, whether it's banking, and other sectors, this is interesting. So the question I have for you, is the security token. This has been a big deal, a lot of companies have seen the ICOs on the utility side, certainly the SEC in the US has been really sending signals pretty radically, like hey, don't pump and dump, I don't want to see any, watch that advisor stuff, and oh by the way, show me the utility, how we test et cetera, et cetera. That the startups who have to build the future are trying to rush a utility token out, now have a safe harbor in the security token, and existing companies can raise money with the security token that are tokenizing a real business, this is a pretty important point. Can you guys share some color commentary on that? Do you agree with it, and then, if you do, share some color around this whole trend. >> Yeah, I mean, right now if you look today, there's two major categories of tokens as you alluded to, you have utilities on the one hand, and securities on the other hand. And the distribution right now is extremely one-sided. Security tokens are dominated by utilities. Utilities like Bitcoin, Ether, Ripple, they make up 99% of the total market cap of alt coins, so, where does that leave us? Well it depends, today it means all the action is in utilities, there's more upside, they're faster, they're simpler, I'm very bullish on utilities. But what's even more exciting to me, is the mega-trend the tsunami of real-world financial assets migrating to the blockchain. And that's what I see as the next sort of part two, second-wave of crypto, is real-world, tangible assets tokenizing and migrating to the blockchain. >> And you know what I think, you know the SEC kind of gets a bad rap in all this, but the rules are there for a certain reason: to protect investors, and I think that this industry is in the beginning it's a nascent, and you know, with Trevor's company Polymath introducing the securities token. Literally, I think you coined the word. It's growing up, it's an industry that has to, you know, it's going to have some red tape, too, right, and I think working with the regulators, and Trevor's company has done that, you know, befriend them, and be open-source about it, and communal. And, you know there's certain aspects about the regulations that are not good, and we don't want communication and the communities that have formed, Telegram's a great example of this, so there's a lot of these chat rooms that I'm in and literally people are sharing information about companies and teaching each other, and learning and that's great. But there is an assymetry of information sharing, that at some point, you know, we have to rein that in. But we don't want to lose the positive aspects. >> You could choke the innovation, if you put too much regulatory on it, the innovation won't grow, so you have to have a balance, I mean, that's what you're saying, right? You got to get through it, but redefine a new era. And the SEC in the US has not been too bad, I think they're just sending a signal, and I think they're not, And they can be hardcore. They could be harder core, I think, than they are. But thank God they're not, you want to let these startups figure out what to do. Alright so I got to talk about liquidity and funding. So, Grit Capital, you guys are involved in investments also, you're enabling partnerships at Polymath. A lot of people you're connecting into your system, we had one on earlier. The funding environment, certainly a lot of investors are here I talked to probably at least a dozen actively investing, different profile make-ups some go hardcore protocol under the hood, some are more business we're going to decentralize apps. Make-up, Persona, trends, can you share? >> Yeah! >> You know that world. Eight months ago, so, I'm from Toronto, I'm from Canada. Eight months ago, there was literally no publicly-traded blockchain company in Canada. And now there's probably, I think, 70, you know, new one every day, name change. But yeah, there's been a lot of equity raised. There's two companies about to go public actually, in Canada Hut 8 Mining, who's our sponsor here at the conference, and Galaxy Digital Michael Novogratz's company, and I think between the two of them, they've raised almost half a billion dollars in capital. Or, like market capitalization when they go public. Probably about 250 million in actual capital. But that's huge, those checks were written not by just by high net worth people, but actual institutions. And those people that are here today, they're good with writing equity checks, ICO checks and that is going to come. And I think the securities token aspect of it will give them a lot of comfort that they can write checks in those kinds of-- >> And how does Grit Capital, talk about Grit Capital. >> Yeah so very simply, we introduce companies to capital holders, investors. So I was a portfolio manager for nine years, and I like to say I was in the no game for nine years, 'cause when you're portfolio managing-- >> Now you're in the yes game! >> Yeah, your goal-tending, you're like trying not to let bad deals in, and that wasn't really conducive to my personality and now I'm in the yes game, I'm you know, I like this company, I'm going to invest in it, but I'm going to introduce them to these other capital holders. And it's a positive experience. >> How much is community involved in what you do? 'cause we're seeing obviously the pattern of kind of paying it forward, which is great culture, but also people are, you know help scratch my back, I'll scratch your back on deal flow, and also on participation, it seems to be a big part of the current rules of engagement, or implied protocol. Is that going on? >> Yeah, you know, look I think this is a very collaborative ecosystem, and It's has to be because by definition, open-source communities are powered by the people that make it up, and it's all about volunteering, about helping, about giving back, and it's one of the reasons I'm so passionate about this space. >> I think you should probably talk about your fund that you just announced that you're launching. And it probably plays into, so Trevor's network is global, it's extensive he has deal-flow coming at him all the time. >> Alright, so what's in the news? >> Yeah what are going to do with that deal flow? You holding news back? >> Yeah, I've got a bit of a brain freeze, I have so many announcements out there, uh, yeah we're doing a lot of exciting initiatives right now, and part of what I'm excited about, and also slightly intimidated by, is that there's just so much opportunity, there's so many key components of this new infrastructure that need to get build, that aren't in existence yet, that is easy to get, you know, carried away. But for me it's about prioritizing and finding out the real kind of high-leverage initiatives that are going to help us achieve our goals. >> And so you're putting a fund together to invest in the ecosystem, or is this for financial investment, is it a crypto fund, or what are you, what's going on? >> One of those initiatives is a securities token focused venture fund, this will be the first one that I know of that exists, and it would be to help our ecosystem get financed, and that's a big component of this marketplace is capital, is investors, is demand. And we just want to channel all of that to the best deals. So Polymath capital-- >> Ecosystem is important to you guys, Polymath your ecosystem is strategic, right? >> Yes. >> How do you see that playing out, what's your vision? What do you hope to unfold in your ecosystem? Obviously, people connect in the variety of things that you can help people with, and vice versa. How do you see your ecosystem rolling out? >> Well, part of it is I want an arms length organization that has its own kind of mandate, its own charter. And the way I look at it is, if you look at Ethereum, which I am very familiar with being from Toronto and knowing those guys kind of since day one. They opted not to do a venture fund, but if they had, it would have been literally the most, >> John: high performance fund ever in history? >> Of all time, yeah, just mathematically-speaking, so we don't want to lose out on an opportunity like that. And in the process of building another potentially profitable entity we want to also seed the ecosystem and help projects that we're excited about. Get the first check. >> Who are you looking for in your ecosystem? Is it developers, 'cause obviously Ethereum, we're Ethereum developed we're a ERC20 token, we love it. It's easy to work with, smart contracts are easy to work with, so it's clearly a developer market on that side, are you guys looking for the same? Is it a different kind of partner, what is some of the partner makeup that you hope to attract, in case they're watching now, why should they work with you, who are they? Describe the persona of your ideal ecosystem partners, or partner. >> For better or worse we have a lot of verticals that we have to build communities within, so those are the business community, we want leaders, we want action-takers we want people that can structure deals, we want legal professionals, that's a big component of the security token landscape, is the regulation is the exemptions, and the offerings, and the memorandums, and all the legal stuff, so we need a legal community. And then finally, most importantly, we need a developer for community, we need the best technical minds just like any other decentralized project, so that's what my full-time job is, when people ask me, is building communities with our broader community. >> Well I can totally give you props, one, because I know you're super busy, and you're drinking from the fire hose at all levels, and certainly the event's been great. I think a breath of fresh air, a sigh of relief from the world when see entrepreneurs, at least from the perspective of the entrepreneurs and the markets is that security tokens, finally someone just made a decision let's just use this security token as a way to get the funding and get set up, and not foreclose the option for, say, a utility token. Why rush and force a utility, needs to be built out. And lot of these utilities have really missed out because they had to run so fast to write code funded by a utility, that has a test. So I think you guys are doing a great service, I want to give you props for that. >> Thank you, yeah I would whole-heartedly agree, I think a lot of these so-called utility coins are actually securities masquerading as utilities, and you know, >> I think that's the game everyone kind of is realizing like, okay great, now you have the platform, so what's the update on the platform, the company? Take a quick minute to explain to the folks about Polymath. >> We are inundated and overwhelmed with demand right now. And we have thousands, tens of thousands of sign-ups on both the investor and issuer side. And kind of my goal right now on a day-to-day basis is to scale our on-boarding process so we can take all these issuers and give them a secure and robust token that they can fundraise on top of. And we are in the process of unveiling our application layer that's going to make that kind of self-serve process exciting and scalable. >> Well congratulations, and Grit Capital, genevieve, thanks for connecting, great to connect with you. Shout out to Bill Tai who made it happen. If it wasn't for Bill Tai and Genevieve, theCUBE would not be here, and of course Polymath supporting us as well. It's been great, so thank you very much! >> Thank you! >> Great event, and we'll keep on following you guys and thanks for coming on, sharing success. Final question: The craziest thing that's happened here this week, one, two, three, things that might have won? Craziest thing that's happened, could be good, bad, or ugly. Did someone fall in the pool? Was someone found on the beach? Share a funny story or two. >> We found a mermaid. >> there was a mermaid, yeah. >> A real, live mermaid, we actually found a mermaid. And we put her in the pool for the cocktail event. >> And we almost put Trevor in the pool as a merman. Just to balance it out. >> Merman, We're a mermaid-neutral company we have mermen as well, oh geez, what else? We had uh, a friend of our decided to get the jacuzzi suite at the top floor and uh, I don't know if you've ever seen the movie Scarface? But there was a lot of uh, opulence going on, which was a little more than I bargained for. And then Genevieve being the celebrity that she is. Umm, what do you think? >> Umm, I mean there's been so much, like, we've had literally 13 side-events within the conference. So drinking from a fire hose is an understatement, I would say, there's still more to do, we're going to Cabana pool party now so maybe, I think there's going to be a bull there, a stampede security bull there? >> Trevor: Oh geez, is there? >> And maybe the SEC, no! (laughs) >> Well, hey congratulations, you guys are doing a great service in the industry and I love how you brought together the inner-circle major players, really the community really admires that so appreciate your help. Okay this is theCUBE, live coverage in the Bahamas. More interviews after this short break, stay with us. (upbeat music)

(energetic electronic music) >> Narrator: Live, from Nassau, in the Bahamas it's theCUBE covering POLYCON18. Brought to you by, Polymath. (attendees chatting indistinctly) >> Crew Member: So, go, we're live. >> Okay, we're live, welcome back! This is day two of our exclusive CUBE coverage of the Bahamas' POLYCON18 It's a security token conference. It's where the world of cryptocurrency, Blockchain, Bitcoin and everything comes together around powering a new value economy. A new kind of decentralized internet. This is the biggest wave that I've seen in my lifetime. It's really bigger than all the other waves, combined. I'm here with Dave Vellante. We have two days of wall-to-wall coverage. And the bottom line is, Dave, we are seeing historic, massive, wealth creation. We're seeing crypto-billionaires here. I mean, people are new money, they're old money and a massive new landscape is emerging. And the tell-sign of this is, institutional money is coming in, real professionals are coming in. It's moving from a culture of Burning Man and cult of the personalities to real industry formation. You see that with companies coming out with real commercial opportunities. You're seeing ecosystems developing, and you're starting to see biz dev. And it's been probably at least a couple decades since I've gone to a conference where this kind of computer-industry movement is happening where the players are doing deals in the hallways. You're hearing people having substantive conversations around how they can work together to create tons of value. This is a dynamic that is absolutely happening. And we're seeing a lot of wealth involved, from people who have made tons of money, billions of dollars in Bitcoin, to kind of, new migration coming into the sector from Wall Street, from other global markets. We're seeing a sea change of democratizing, with an open-source ethos. To me, this is something that we've never seen before. It has all the elements of the modernization, business model modernizations, technology modernizations, real, disruptive, enabling, technology at the heart of it. And some people ask questions like, "How do we make money?" Bottom line is, there is money being made. How and with who, is the real question. So Dave, day one's over. We were out 'til one in the morning last night, working the hallways, having great conversations. I probably talked to at least six whales as they're called, billionaires in the business, and the vibe is the same. We're here to play the long game, we love this market. There's a culture of ethos, of partnership, and openness, and unwritten rules, and tons of activity. Sure there's bad actors! But there's a lot of great players here, and they are starting to crack down on behavior that's not right, because this is a funding dynamic. It's a funding growth companies dynamic. It's a liquidity dynamic. All these things, classic, business model modernization, happening with a massive wave, your take. >> So, let's share with our audience. Well, first of all, this is an investor conference. It's the first conference built around the topic of security tokens. And we can, maybe, explain that in a moment. But, I have, John, I have never seen at an investor conference, which I guess this is, but it's more than that, Blockchain, technology, etc. But, I've never seen such diversity. Like you said, there's new money, there's old money. There's tons of millennials. 100% of the people here are doing deals. >> Yeah. >> And the conversations in the hall, it's all about ICO's, security tokens, utility tokens, protocols, white papers, business models. So, a lot of diversity. Some super smart millennials. Developers that really understand this stuff, and a lot of money. >> And, more women in tech here than I had thought. >> Yeah, I think it's slightly higher proportion. But, you're also seeing, just really interesting, you're seeing VC's who aren't going to sit back and wait and get disintermediated. You're seeing developers who have made a ton of dough, that are now sprinkling the wealth. You're seeing private equity, you're seeing hedge funds. You're seeing, like I say, traditional VC's, new types of VC's. And, very importantly, you're seeing a major diversity in cultural impact, nationalities. And this is a heavily Canadian show, because the organizers of POLYCON, the folks who started Ethereum. But, a lot of diversity in terms of where people are coming from. It's not just U.S. based, you know, MBA's-- >> Silicon Valley. >> Yeah. >> I mean, the game's changing. The other thing I observed is, we're seeing validation of my premise, a couple weeks ago when I was in Washington D.C. with Theresa Carlson, the most powerful woman in D.C. She's also the chief, and head of, Amazon Web Services' global public sector. Is that the global national stage, the nation building, the digital nation transformation, is part of it. Two, the validation that societal change and entrepreneurship, that was used to be involved in non-profits that never went anywhere, you know, these philanthropy projects. Social entrepreneurship, or societal entrepreneurship, as I call it, is absolutely real. And, in this culture, you're seeing people with Bitcoin, and crypto-currencies funding mission based activities. Now, the younger demographics, I think, lean towards that. That's pretty clear in our reporting and our data. That the younger generation wants to work for companies and communities that have an ethos of mission base. But, mission base is not about changing the world, it's about saving the world. And, this is real, you're looking at Blockchain ventures that track water supply. You're looking at Blockchain ventures that track, you know, food supply. You're looking at solving world hunger kind of challenges. And I think the tell here is, Blockchain is used to identify markets and incumbents, or opportunities where there's idle resource. So, whether that's using compute in a P2P way or solving the world hunger problem, anywhere there's an opportunity to be efficient, Blockchain is being used to solve those problems. And, the creative talent is the technology providers. This is a completely new dynamic. One that Silicon Valley pays lip service to. 'Cause they don't actually do societal change. They say they do, but, they build apps and platforms. So, I think this is a nuanced, but an important game changer for the industry, and the global economy and global entrepreneurship, because you can do things now that can be global impact based investing, and technology investing, in one shot. So, you get a double down effect for change. This is not just cloud computing, have more power, faster, better apps, more monetization. Sure, but now you have over the top, impact to users. The community dynamic, and the societal change is very, very real. That's a big driver of this ecosystem in terms of market selection, human capital, technology, leverage, and now financial. So, it is pretty intoxicating here. People are geared up, they're energized, and it's just pretty phenomenal. >> So, many people in our audience are still probably saying, I just don't get it. So, let's go back to 2008 when Satoshi, whoever that person was, writes this, I think it was an eight page white paper. And, remember what 2008 was like, banks were blowing up, too big to fail, the economic system was melting down, and guess who paid for it? The taxpayers. So, some libertarian minded people said, screw that, we're going to change the world. We're going to create a virtual currency and we're going to take back what the government is taking from us. Essentially, okay. So, that started people like, what, I don't really get it. That has formed a whole new, and people often say, it's not about Bitcoin, it's about Blockchain. Blockchain is building out this whole new internet. And we've talked about that all week. But, what you're seeing now is this concept of a value store a virtual value store, and people leveraging that in so many different ways to build out this new internet. And, they're building protocols, they're building apps, they're building new capabilities that we haven't seen before. That brings state to the internet, a state of communications. Now, let's talk about the investor profiles that we see here. I want to start with developers. So, developers built the internet, and most of them didn't really get paid huge money. Here, many of the developers are like multi, multi-millionaires flying in on private jets. Okay, so why? Because they've developed a new token that they, basically, invested in with their sweat and their money, and the price has gone through the roof. Bitcoin, Ethereum, etc., VC's. VC's, you know, they elbowed out, well they're elbowing their way back in. Private equity, hedge funds, big money. And there's two paths there, one is, guys that read white papers, real hard core technical guys who say, I'm going to invest in just this infrastructure token, utility token. Other guys who say, You know what, I've got big money, I don't really understand the technology, but, I'm going to sprinkle my money around and try to get a big hit. You got angels, you got entrepreneurs, you got superstars that have become billionaires, that are mission based. All these, and here's the thing John, and I want you to sort of explain this to the audience. You have these investor ecosystems forming. It's like the PayPal Mafia, and they're basically buying up all the tokens early, elbowing other people out. You know, one investor told us, We're fighting steel with steel. Steel beats steel, you have to form, it's like Survivor Baha Mar, right? And they're forming groups, and they're eyeing each other, attacking opportunities, elbowing each out, and it's really interesting. >> I mean, it's happening, big time. And, this is healthy, I think, in my mind. Emerging ecosystems have this behavior. The early days of Silicon Valley was very much the same. And it became very much war, now in Silicon Valley. See, people don't syndicate deals as much as they used to. Some are and some aren't, but the notion of teamwork has always been part of Silicon Valley. The old saying is, venture capital is a team sport. That is very much what's going on here. Now, they team up because they have to, but, steel on steel implies art of war. You know, we're going to take more allocations down. That's because the new pro persona of the investor, Dave, is the billionaire developer who captured value from the technology that they built, not someone else, not some central organization, they're the players. Developers, and or the actors who were making money in the early days of Bitcoin, cryptocurrency and Blockchain actually are also starting funds themselves. So, that is a new dynamic. We've never seen that before, where you see a wealthy developer become rich and then also start investing at the same time. You have a smarter investor there, but they're doing it in packs and herds. You have a tribe mentality and people are starting to recognize that, okay, this group here loves Burning Man, this group here is more commercial oriented, this group here, like Polychain is much more technical, and BlockTower's much more Goldman Sachs like. So, you're starting to see the formation of categorical roles in the ecosystem. This is very healthy. Now, in the short term there's some jockeying, right? So, you're starting to see people syndicate together. You buy my coin, I'll buy your coin. So, there's a healthy, robust equilibrium going on where the market of insiders is very much the story. The insiders of this industry are the players. They are the ones, not just building the technology, they're funding technology, they're also recruiting, the talent issue, human capital role, mission based. These are all new dynamics. This is going to be a hard nut to crack if you're an incumbent, venture capitalist, or hedge fund, trying to walk into this ecosystem, throw your weight around and compete on a frontal basis, money for money, steel on steel, if you don't play by the rules of engagement that's emerging. Such as, open source communities, unwritten rules, certain kinds of syndications, eliminating bad behavior. This is a dynamic that's real, and you'll either win or lose if you're an investor, win or lose if you're an entrepreneur if you don't recognize that, kind of, big picture. So, you get down and dirty, you got to pull back and say, okay, what's going on, how do I engage? This is where the true money making is going on. >> That's great analysis, John. You mentioned the word dynamics several times. The other underpinning dynamic is, we are going to take control of our own destinies. I've heard things all week like, I might move out of the U.S. Ya know. (laughs) Do you have a bank account overseas? (laughs) >> Estonia's looking good right now. >> Right, because I'm going to move to a place that's more friendly to this kind of concept. And the U.S. is anti-competitive. And this is the ethos of this community, We are going to control our own destiny. And we're going to go live in places and work in places that are friendly. >> This, to me, is perfect capitalism at work. You know, some would criticize Barack Obama or other folks that might have more of a socialistic bent around having government do redistribution of wealth. This is actually an example where I see redistribution of wealth going on in a capitalistic way. Where the enabling technology, Blockchain, and or new business models with cryptocurrency, which is money, basically open sourced money, as Miko Matsumura would say, and that is the dynamic. That is actually creating real value and redistribution of wealth. And the premise of Blockchain and cryptocurrency, although Bill Tighe pointed out, investor, and leader in the area, money's a concept, right? A dollar's a dollar, it has money value because it's a concept. But, if you look at things like what we learned in business school, the value chain of a organization, value chain, Blockchain, cryptocurrency money, is that this redistribution of wealth is going on in context to redefining business, redefining how people work. And again, I said earlier, the human capital component is very much a real dynamic, it's not just machines taking over the world. Some poopoo AI, some poopoo all this technology, but, human capital, a big force in this market. And, it is a big issue, and you got to learn protocols. We're all developers. So, again, zoom out, opportunity is right there. I think I'm long on this sector. I'm long on this game because the actors are going to self organize, Steel on steel turns into handshakes, or, steel on steel in the right areas, eliminating bad actors. FCC makes some regulations, that's only in the U.S. What about the opportunities for digital nations to say, hey, we're going to be the Wall Street of crypto. There are country opportunities right now where whoever builds that system, taking in crypto, converting it to fiat, will win everything. It's like, I'm surprised no one's done that yet. >> Yeah >> This is coming. >> I can't tell you what the price of Bitcoin is in August, but I agree with you, longterm, there's no question in my mind that this is going to be a key contributor to the digital economy. The build out of the next internet. Remember the fundamentals, you got Bitcoin, it's essentially, you know, a virtual Fort Knox. You got Ethereum, which is a horizontal infrastructure that's much more easily programmed by developers. And then you've got a zillion other protocols and tokens. I want to talk about risk factors. Like what could blow this up, what have we heard? Tax exposure, all these people, all these Bitcoin millionaires and billionaires that think, I don't have to pay taxes, well, guess what? (laughs) You do have to pay taxes. And so, one theory is that's why the price has moderated lately, 'cause people are saying, Wow, it's like I exercised the option, but I don't have cash to pay my taxes. 'Cause we saw a pullback recently. Regulation's the other one we heard. Too much regulation could put some brakes on the momentum here, your thoughts. >> Talent, talent. >> Yep, skill sets, and developer talent, right? >> Yeah, well, the top talent, in the protocol area is going to be at a premium. This is a global issue, so, you know, the old days when cloud, old days, when cloud computing came around, full stack developers were all the rage. Now protocol developers are all the rage. So, if you're a full stack developer and a protocol developer, you can have a lot of leverage. So, the danger, in my opinion is the job hopping nature of some of these ICO's. Hey, I made a bunch of dough on this ICO, they paid me in Ether and or Bitcoin whatever, I'm off to the next one and make a couple million bucks there, and move on to the next one. And so the job hopping factor for top talent is an issue. We heard that loud and clear. The tax thing, I'm bullish on Bitcoin, post April 16th. I think, buy Bitcoin right now and look for it to pop in April. Because I think people are going to realize, Oh shit, I should have sold some and had a tax carry over. >> Well, be careful, be careful. They might have to sell more to meet their tax bill. They might be holding on for a little bit, but I don't know. >> File the extension. (laughs) But anyway, I love the opportun-- >> No, you owe your taxes on the date. Extension doesn't remove you from paying the taxes. >> Yeah, but the issue Dave, is, that what's a scam and what's not a scam? So, you know, if you ask Joe Six Pack on the street, throw crypto and Bitcoin, it's a scam. There's a lot of stuff going on. This industry is absolutely, acutely aware of that dynamic. The risk on the wealth creation opportunity. They know it, so they're creating mechanisms to kind of weed that out. You're seeing PR firms having internal, called, in baseball and in sports it's like, clubhouse issues. There's a clubhouse issue going on in this industry. And they're going to take it amongst themselves. And I think that is going to be the tell sign if this ecosystem succeeds or not. >> Do you think there's more scams, or less scams going on there? >> There'll be less scams because, obviously there's too much money to be made right now. >> Right, and in terms of the percentage of the activity that's going on, in my opinion, the smallest percentages is the scams. The challenge is, anyone could be a scam so you have to sort that out, you got to do-- >> Due diligence. >> As always, you got to do homework. >> Alright, well, day two Dave, we're going to drill into. We got a great line up of guests. We'll be talking to investors, entrepreneurs, some whales coming on, we're going to get their opinion on the future of this market. What's the liquidity, how do you get paid? Who's making the money? How is the value that's being created ultimately captured? And, who's going to get that value? It's theCUBE coverage, from the Bahamas, exclusive coverage of the cryptocurrency, tokenization, here at POLYCON18. We'll be right back. (electronic music)

>> Announcer: Live from San Jose, California, it's theCUBE, covering Innovating to Fuel the Next Decade of Big Data, brought to you by Western Digital. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're at Western Digital's headquarters in San Jose, California at the Almaden campus. Lot of innovation's been going on here, especially in storage for decades, and we're excited to be at this special press and analyst event that Western Digital put on today to announce some exciting new products. It's called Innovating to Fuel the Next Decade of Data. I'm super happy to have a long-time industry veteran, he just told me, 35 years, I don't know if I can tell (Mark laughs) that on air or not. He's Mark Grace, he's the Senior Vice President of Devices for Western Digital, Mar, great to have you on. >> Thanks Jeff, glad to be here. >> Absolutely, so you've seen this movie over and over and over, I mean that's one of the cool things about being in the Valley, is this relentless pace of innovation. So how does today's announcement stack up as you kind of look at this versus kind of where we've come from? >> Oh I think this is maybe one of the, as big as it comes, Jeff, to be honest. I think we've plotted a course now that I think was relatively uncertain for the hard drive industry and the data center, and plotted a course that I think we can speak clearly to the market, and clearly to customers about the value proposition for rotating magnetic storage for decades to come. >> Which is pretty interesting, 'cause, you know, rotating drives have been taking a hit over the last couple of years, right, flash has been kind of the sexy new kid on the block, so this is something new, >> Mark: It is. >> And a new S curve I think as John said. >> I agree, we're jumping onto a, we're extending the S curve, let's call it that. I think there's actually plenty of other S curve opportunities for us, but in this case, I think the industry, and I would say our customer base, we have been less than clear with those guys about how we see the future of rotating storage in the cloud and enterprise space, and I think today's announcement clarifies that and gives some confidence about architectural decisions relative to rotating storage going forward for a long time. >> Well I think it's pretty interesting, 'cause compared to the other technology that was highlighted, the other option, the HAMR versus the MAMR, this was a much more elegant, simpler way to add this new S curve into an existing ecosystem. >> You know, elegant's probably a good word for it, and it's always the best solution I would say. HAMR's been a push for many years. I can't remember the first time I heard about HAMR. It's still something we're going to continue to explore and invest in, but it has numerous hurdles compared to the simplicity and elegance, as you say, of MAMR, not the least of which is we're going to operate at normal ambient temperatures versus apply tremendous heat to try and energize the recording and the technologies. So any time you introduce extraordinary heat you face all kinds of ancillary engineering challenges, and this simplifies those challenges down to one critical innovation, which is the oscillator. >> Pretty interesting, 'cause it seems pretty obvious that heat's never a good thing. So it's curious that in the quest for this next S curve that the HAMR path was pursued for as long as it was, it sounds like, because it sounds like that's a pretty tough thing to overcome. >> Yeah, I think it initially presented perhaps the most longevity perhaps in early exploration days. I would say that HAMR has certainly received the most press as far as trying to assert it as the extending recording technology for enterprise HDDs. I would say we've invested for almost as long in MAMR, but we've been extremely quiet about it. This is kind of our nature. When we're ready to talk about something, you can kind of be sure we're ready to go with it, and ready to think about productization. So we're quite confident in what we're doing. >> But I'm curious from your perspective, having been in the business a long time, you know, we who are not directly building these magical machines, just now have come to expect that Moore's Law will contain, has zero to do with semiconductor physics anymore, it's really an attitude and this relentless pace of innovation that now is expected and taken for granted. You're on the other side, and have to face real physics and mechanical limitations of the media and the science and everything else. So is that something that gets you up every day >> Mark: Keeps me awake every night! >> Obviously keeps you awake at night and up every day. You've been doing it for 35 years, so there must be some appeal. >> Yeah. (laughs) >> But you know, it's a unique challenge, 'cause at the same time not only has it got to be better and faster and bigger, it's got to be cheaper, and it has been. So when you look at that, how does that kind of motivate you, the teams here, to deliver on that promise? >> Yeah, I mean in this case, we are a little bit defensive, in the sense of the flash expectations that you mentioned, and I think as we digest our news today, we'll be level setting a little bit more in a more balanced way the expectations for contribution from rotating magnetic storage and solid state storage to what I think is a more accurate picture of its future going forward in the enterprise and hyperscale space. To your point about just relentless innovation, a few of us were talking the other day in advance of this announcement that this MAMR adventure feels like the early days of PMR, perpendicular, the current recording technology. It feels like we understand a certain amount of distance ahead of us, and that's about this four-terabit per inch kind of distance, but it feels like the early days where we could only see so far but the road actually goes much further, and we're going to find more and more ways to extend this technology, and keep that order of magnitude cost advantage going from a hard drive standpoint versus flash. >> I wonder how this period compares to that, just to continue, in terms of on the demand side, 'cause you know, back in the day, the demand and the applications for these magical compute machines weren't near, I would presume, as pervasive as now, or am I missing the boat? 'Cause now clearly there is no shortage of demand for storage and compute. >> Yeah, depending on where you're coming from, you could take two different views of that. The engine that drove the scale of the hard drive industry to date has, a big piece of it in the long history of the hard drive industry has been the PC space. So you see that industry converting to flash and solid state storage more aggressively, and we embrace that, you know we're invested in flash and we have great products in that space, and we see that happening. The opportunity in the hyperscale and cloud space is we're only at the tip of the iceberg, and therefore I think, as we think about this generation, we think about it differently than those opportunities in terms of breadth of applications, PCs, and all that kind of create the foundation for the hard drive, but what we see here is the virtuous cycle of more storage, more economical storage begets more value proposition, more opportunities to integrate more data, more data collection, more storage. And that virtuous cycle seems to me that we're just getting started. So long live data, that's what we say. (both laugh) >> The other piece that I find interesting is before the PCs were the driver of scale relative to an enterprise data center, but with the hyperscale guys and the proliferation of cloud and actually the growth of PCs is slowing down dramatically, that it's kind of flipped the bit. Now the data centers themselves have the scale to drive >> Absolutely. >> the scale innovation that before was before was really limited to either a PC or a phone or some more consumer device. >> Absolutely the case. When you take that cross-section of hard drive applications, that's a hundred percent the case, and in fact, we look at the utilization as a vertically integrated company we look at our media facilities for the disks, we look at our wafer facilities for heads, and those facilities as we look forward are going to be as busy as busier than they've ever been. I mean the amount of data is relative to the density as well as disks and heads and how many you can employ. So we see this in terms of fundamental technology and component construction, manufacturing, busier than it's ever been. We'll make fewer units. I mean there will be fewer units as they become bigger and denser for this application space, but the fundamental consumption of magnetic recording technology and components is all-time records. >> Right. And you haven't even talked about the software-defined piece that's dragging the utilization of that data across multiple applications. >> And it's just one of these that come in to help everybody there too, yeah. >> Jeff: You got another 35 years more years in you? (both laugh) >> I hope so. >> All right. >> But that would be the edge of it, I think. >> All right, we're going to take Mark Grace here, only 35 more years, Lord knows what he'll be working on. Well Mark, thanks for taking a few minutes and answering your prospective >> No that's fine, thanks a lot. >> Absolutely, Mark Grace, I'm Jeff Frick, you're watching theCUBE from Western Digital headquarters in San Jose, California. Thanks for watching. >> Mark: All right.

(calm and uplifting music) (moves into soft and soothing music) >> Announcer: Live from Las Vegas, it's theCUBE. Covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. (chill and calm electronic music) >> Hey, welcome back everyone. We are live here at the Mandalay Bay in Las Vegas for theCUBE's special coverage of Oracle's marketing clouds event called Modern CX for Modern Customer Experience. I'm John Furrier, founder of SiliconANGLE, with Peter Burris, head of research at wikibon.com. This is our wrap up of day one. We've got day two coverage tomorrow. Peter, we saw some great news from Oracle on stage. I'll say modernizing their platform, the positioning, certainly, how they're packaging the offering of a platform with the focus of apps, with the additive concept of adaptive intelligence, which gives the notion of moving from batch to realtime, data in motion, and then a series of other enhancements going on. And the guests we talked to have been phenomenal, but what's coming out of this, at least in my mind, I would love to get your reaction to today, is data. Data is the key, and it's clear that Oracle is differentiating with their data. They have a database. They're now bringing their Cloud Suite concept to marketing and extending that out. Interesting. AI is in there, they got some chatbots, so some sizzle, but the steak is the data. So you got the sizzle and you got the steak. >> Well, we heard, you're absolutely right, John. We heard today a lot, and I think this is a terminology that we're going to hear more frequently, is this notion of first person data versus third person data. Where first person data is the data that's being generated by the business and the business's applications and third person data being data that's generated by kind of the noise that's happening in a lot of other people's first person data. And I think that's going to be one of the biggest challenges in the industry. And Oracle has an inside track on a lot of that first person data because a lot of people are big time Oracle customers for big time operational acts, applications that are today delivering big time revenue into the business. >> In the spirit of marketing speak at these events you hear things, "It's outcomes, digital transmissions. "It's all about the outcomes." Agreed, that's standard, we hear that. But here we're seeing something for the first time. You identified it in one of our interviews with Jack Horowitz, which had 150 milliseconds, it's a speeds and feeds game. So Oracle's premise, you pointed out, I'd like to get deeper on this, because this is about not moving the data around if you don't have to. >> Yeah, yeah. >> This is interesting. >> This is a centerpiece of Wikibon's research right now, is that if you start with a proposition that we increasingly through digital transformation are now talking about how we're going to use data to differentiate business, then we need to think about what does it mean to design business, design business activities, design customer promises around the availability of data or the desire to get more data. And data has a physical element. Moving data around takes time and it generates cost, and we have to be very, very careful about what that means, let alone some of the legal and privacy issues. So we think that there's two things that all businesses are going to have to think about, the relationship between data and time. Number one, Can I serve up the right response, the right business action, faster than my competitors, which is going to matter, and number two is can I refine and improve the quality of my models that I'm using to serve things up faster than my competitors. So it's a cycle time on what the customer needs right now, but it's also a strategic cycle time in how I improve the quality of the models that I'm using to run my business. >> What's also interesting is some things that, again that you're doing on the research side, that I think plays into the conversations and the content and conversations here at Oracle's Modern CX event is the notion of the business value of digital. And I think, and I want to get your reaction to this because this is some insight that I saw this morning through my interviews, is that there are jump in points for companies starting this transformation. Some are more advanced than others, some are at the beginning, some are in kindergarten, some are in college, some are graduated, and so on and so forth. But the key is, you're seeing an Agile mindset. That was a term that was here, we had the Agile Marketer, the author of The Agile Marketer, here on our-- Roland Smart, who wrote the book The Agile Marketer. But Agile can be applied because technology's now everywhere. But with data and now software, you now have the ability to not only instrument, but also get value models from existing and new applications. >> Well let's bring it back to the fundamental point that you made up front, because it's the right one. None of this changes if you don't recognize these new sources of data, typically and increasingly, the customer being a new source, and what we can do with it. So go back to this notion of Agile. Agile works when you are, as we talked about in the interview, when you have three things going on. First off, the business has to be empirical, it has to acknowledge that these new sources of information are useful. You have to be willing to iterate. Which means you have to sometimes recognize you're going to fail, and not kill people who fail as long as they do it quickly. And then you have to be opportunistic. When you find a new way of doing things, you got to go after it as hard as you possibly can. >> And verify it, understand it, and then double down on it. >> Absolutely, absolutely. Yeah, customer-centric and all the other stuff. But if you don't have those three things in place, you are not going to succeed in this new world. You have to be empirical, you have to be iterative, and you have to be opportunistic. Now take that, tie that back to some of the points that you were making. At the end of the day, we heard a lot of practitioners as well as a lot of Oracle executives, I don't want to say, be challenged to talk about the transformation or the transition, but sometimes they use different language. But when we push them, it all boiled down to, for the first time, our business acknowledged the value of data, and specifically customer data, in making better decisions. The roadmap always started with an acknowledgement of the role that data's going to play. >> And the pilots that we heard from Time Warner's CMO, Kristen O'Hara, pointed it out really brilliantly that she did pilots as a way to get started, but she had to show the proof. But not instant gratification, it was, "Okay, we'll give you some running room, "three feet and a cloud of dust, go see what happens. "Here's enough rope to hang yourself or be successful." But getting those proof points, to your point of iteration. You don't need to hit the home run right out of the gate. >> Absolutely not. In fact, typically you're not. But the idea is, you know, people talk about how frequently product launches fail. Products, you know, the old adage is it fails 80% of the time. We heard a couple of people talk about how other research firms have done research that suggests that 83 or 84% of leads are useless to salespeople. We're talking about very, very high failure rates here and just little changes, little improvements in the productivity of those activities, have enormous implications for the revenue that the business is able to generate and the cost that the business has to consume to generate those revenues. >> John: I want to get your reaction to-- Oh, go ahead, sorry. >> No, all I was going to say, it all starts with that fundamental observation that data is an asset that can be utilized differently within business. And that's what we believe is the essence of digital business. >> The other reaction I'd like to get your thoughts on is a word that we've been using on theCUBE that you had brought up here first in the conversation, empathy to users. And then we hear the word empowerment, they're calling about heroes is their theme, but it's really empowerment, right? Enabling people in the organization to leverage the data, identify new insights, be opportunistic as you said, and jump on these new ways of doing things. So that's a key piece. So with empathy for the users, which is the customer experience, and the empowerment for the people to make those things happen, you have the convergence of ad tech and mar-tech, marketing tech. Advertising tech and marketing tech, known as ad tech and mar-tech, coming together. One was very good at understanding collective intelligence for which best ad to serve where. Now the infrastructure's changing. Mar-tech is an ever-evolving and consolidating ecosystem, with winners and losers coming together and changing so the blender of ad tech and mar-tech is now becoming re-platformed for the enterprise. How does a practitioner who's looking at sources like Oracle and others grock this concept? Because they know about ads and that someone buys the ads, but also they have marketing systems in place and sales clouds. >> Well, I think, and again, it's this notion of hero and empowerment and enablement, all of them boil down to are we making our people better? And I think, in many respects, a way of thinking about this is the first thing we have to acknowledge is the data is really valuable. The second thing we have to acknowledge is that when we use data better, we make our people more successful. We make our people more valuable. We talk about the customer experience, well employee experience also matters because at the end of the day, those employees, and how we empower them and how we turn them into heroes, is going to have an enormous impact on the attitude that they take when they speak with customers, their facility at working with customers, the competency that they bring to the table, and the degree to which the customer sees them as a valuable resource. So in many respects, the way it all comes together is, we can look at all these systems, but are these systems, in fact, making the people that are really generating the value within the business more or less successful? And I think that's got to be a second touchstone that we have to keep coming back to. >> Some great interviews here this morning on day one. Got some great ones tomorrow, but two notables. I already mentioned the CMO, Kristen O'Hara, who was at Time Warner, great executive, made great change in how they're changing their business practices, as well as the financial outcome. But the other one was Jack Berkowitz. And we had an old school moment, we felt like a bunch of old dogs and historians, talking about the OSI, Open Systems Interconnect Model, seven layers of openness, of which it only went half way, stopped at TCPIP, but you can argue some other stuff was standardized. But, really, if you look at the historical perspective, it was really fun, because you can also learn, what you can learn about history as it relates to what's happening today. It's not always going to be the same, but you can learn from it. And that moment was this grocking of what happened with TCPIP as a standardization, coalescing moment. And it's not yet known in this industry what that will be. We sense it to be data. It's not clear yet how that's going to manifest itself. Or is it to you? >> Well here's what I'd say, John. I think you're right, kind of the history moment was geez, wasn't it interesting that TCPIP, the OSI stack, and they're related, they're not the same, obviously, but that it defined how a message, standards for moving messages around, now messages are data, but it's a specialized kind of a data. And then what we talked about is when we get to layer seven, it's going to be interesting to see what kind of standards are introduced, in other words, the presentation layer, or the application layer. What kind of standards are going to be introduced so that we can enfranchise multiple sources of cloud services together in new ways. Now Oracle appears to have an advantage here. Why? Because Oracle's one of those companies that can talk about end to end. And what Jack was saying, it goes back again to one of the first things we mentioned in this wrap, is that it's nice to have that end to end capability so you can look at it and say "When do we not have to move the data?" And a very powerful concept that Jack introduced is that Oracle's going to, you know, he threw the gauntlet down, and he said "We are going to help our customers "serve their customers within 150 milliseconds. "On a worldwide basis, "anywhere that customer is in the world, any device, "we're going to help our customers serve their customers "in 150 milliseconds." >> That means pulling data from any database, anywhere, first party, third party, all unified into one. >> But you can do it if and only if you don't have to move the data that much. And that's going to be one of the big challenges. Oracle's starting from an end to end perspective that may not be obviously cloud baked. Other people are starting with the cloud native perspective, but don't have that end to end capability. Who's going to win is going to be really interesting. And that 150 millisecond test is, I think, going to emerge as a crucial test in the industry about who's going to win. >> And we will be watching who will win because we're going to be covering it on SiliconANGLE.com and wikibon.com, which has got great research. Check out wikibon.com, it's subscription only. Join the membership there, it's really valuable data headed up by Peter. And, of course, theCUBE at siliconangle.tv is bringing you all the action. I'm John Furrier with Peter Burris, Day one here at the Mandalay Bay at the Oracle Modern CX, #ModernCX. Tweet us @theCUBE. Glad to chat with you. Stay tuned for tomorrow. Thanks for watching. (chill and calm electronic music) >> Announcer: Robert Herjavec >> Interviewer: People obviously know you from Shark Tank but the Herjavec group has been--