>> Live from Orlando, Florida, it's theCUBE, covering .conf18. Brought to you by Splunk. >> Welcome back to Splunk .conf18, #splunkconf18. You're here watching theCUBE, the leader in live-tech coverage. My name is Dave Vellante, and I'm with my cohost, Stu Miniman, and we're going to take a cruise with the data. Curt Persaud is here. He's the director of IT for Guest Technology at Carnival Cruise Lines. So, he's the ship. And Ariel Molina is here. He's the Senior Director of web development and enterprise architecture at Carnival Cruise Line. He's the shore. Gents, welcome to theCUBE. Good to see you. >> Happy to be here. Very, very. >> Thanks for having us guys. >> Dave, I sea what you did there. (laughs) >> Yeah, Stu, it's pretty good, huh. Well, this is kind of, you know, Splunk is known for a little tongue in cheek. >> Alright, let's keep this interview on course. >> (laughs) Alright, you got it. So Arnold Donald, your CEO, was on stage today with Doug Merritt, a very inspirational individual. You guys have an amazing company. You see those ads and just go "wow." Just makes you want to go. But Ariel, let's start with you, your role, what you guys are doing here. Just kick it off for us. >> So, no, it's fantastic, great to be here. Great energy in the conference today. The keynote was fantastic. It was great to see our CEO up there and really represent our company, really talk about, sort of, where we're heading and how Splunk helps us along that journey when it comes to data. Things are changing, they're moving faster every day, right? We're pressured into delivering more value, delivering innovation at a faster pace, and Splunk is a key enabler of that, for us. >> And Curt, at any one point in time, you guys said you have like 250,000 guests on the seas around the world. Wow! And everybody wants to be connected these days. So that's kind of your purview, right? >> Yeah, absolutely. Five, 10 years ago, what sold cruises was the ability to be disconnected. Right now, people want to be connected more than ever. So what we try to do, beyond just the connectivity, and giving them better bandwidth, and stuff like that, was to try to develop products onboard that helps them be connected, be social, but not miss out on the product that we're actually selling, which is the ship, the people, the crew, and the actual entertainment and the staff onboard. So we're trying to make people social, but not anti-social with some of the technologies that we're bringing onboard, as well. >> Doug Merritt said today, "we're all data emitters." And I think the number was you guys will service 13 million guests in any given year? So a huge, huge number of data emitters. And of course, Ariel, you obviously are analyzing a lot of data, as well. So, how has the use of data changed over the years at Carnival? Maybe you could kind of take us through that. >> Well, ultimately I think it's about personalizing the experience. So, how do we use the data to better understand what folks are looking for in that guest journey? We call the guest journey everything from planning a voyage, purchasing a voyage, purchasing all the auxiliary items that are up for sale, and then ultimately making it into the ship. So, what we're doing these days, is looking at mining this data, and looking for opportunities. On the dot-com side of things, obviously it's about resiliency and personalization. How do we deliver innovation through multiple releases, and then do so in a resilient way? And a lot of those innovations, typically, are around personalization. And we see that move the needle. We're incentivized to have more folks book online. That's ultimately good for the bottom line. So, data's a big part of that. Personalization, resiliency. >> Yeah, it's one of those interesting things we look at. Most people probably think of cruise ships as you're vacation or transportation, everything like that. You're a technology company now. You're tied in, you've got multiple mobile apps, before and during. Maybe bring us a little bit inside what that's like. >> Over the past three years, we've seen a great transformation in terms of the technologies that we're bringing on board. You name it, whether it's very high end tools, like Splunk and other APM tools that we use, to cutting-edge technology like AI, chatbots, facial recognition. We're using the full breadth of all these innovations, in terms of technology, to try to enhance guest experience. And to Ariel's point, the focus is really on trying to be very personal, trying to personalize this information, trying to personalize the guest experience, and using all those data points that we're capturing to really target what a custom experience looks for you. It's really interesting, because one of the things that we try to do in that personalization is try to manage those micro-moments. We're trying to get you what you want, we're trying to get you the feedback that you need in that micro-moment, so that you can do your transaction and move on to enjoying your cruise. >> There's something that you mentioned. You want a balance. You want people to take advantage of what's there. You used to think of a vacation like this, you'd disconnect yourself. Help understand that balance. >> You'd be surprised. We were just recently on a cruise, my family and I, and we don't cruise as often as you would imagine. >> Because you work for the company. >> Even though, when you do, it feels good to be a customer, right? There's so much activity going on on a ship on a given day. It's very hard to understand where to be at a certain point in time, and some people find that overwhelming. What things like the app does is really allow you to curate your day. To say hey, you like music? Let's focus on events that are music-oriented and that's going to be in Location XYZ on the ship. And they're going to be sequenced. So, that's personalizing the experience. But it's also ensuring that folks are really taking advantage of the full product. >> From our perspective, the technology should be in the background. It's more complementary. The real product is really the ship, the crew members, the activities, the entertainment on board. That's the product we really want people to really connect to. The stuff that we do is auxiliary in terms of, let me help you maximize those experiences on board. And that's what we're really trying to do. If we can get that done and accomplished, than we have done our jobs. >> So the app is the digital conduit to the physical experience >> Exactly. >> If you have a good app, it makes all the difference in the world. If you're at Disney, and you're trying to figure out what's next, what do the lines look like? You get a lot of people on a ship, and you want to prioritize. You all call that curating your experience. It's all about the app, as they say. What's the state of the app? The 1.0 probably needed a little work. Where are you know in the evolution? >> We're in a 2.0 release version of it. The original version, we started with what we called the meat and potatoes. The very basic stuff, that hey, where can I get food? What is the entertainment lineup for the day? We started off with some innovation in terms of being able to generate, we did a chat, kind of like, communication, so people could chat with their families onboard without having to purchase a plan or have any bandwidth needs. And then, as we evolved that, then we started to go into things that are more transactional. So, you're able to purchase your photos digitally through the app. We leveraged facial recognition software, so that if a photographer on a ship takes a picture of you, it recognizes that as you and puts your photo in your photo stream and your photo album. So, very, very convenient. We do things like sell shore excursions in terms of transactional stuff. You can sit at the pool and say "oh, tomorrow's a port day, "I'm going to be in the Bahamas. "Let me see what shore excursion I want to do. And you can do it directly from the app without even moving. So now, as we evolve that now, as Ariel said, now we're trying to leverage all that data now, to go beyond the transactions, and make things even more personalized. So, I know that you favor the casino, maybe you're a spa person, you want a facial. We'll target you and say hey, on your previous cruise you did this. Let's target you because we might have something special waiting for you onboard. >> And then carry that across the journey, right. So now they leave our ships. And how do we get them to come back to our ships? How do you create that conversation that's ongoing, notifications about what's going on on our ships. People follow their favorite cruise director. People follow a lot of the unique experiences there. How do you bring that to the online, to the dot-com experience? So that when they're thinking about that next cruise, they can remember what that last cruise was about, and they can know what's happening on each one of our ships in real-time. It's a journey. And technology definitely is a huge enabler for us and the experience. >> So what's the data architecture look like on there? We always talk on theCUBE about the innovation sandwich of the future. It used to be Moore's Law, doubling every two years. Okay, great. Now, it's data, plus machine intelligence, and you scale with the cloud. What's your data architecture look like? >> Well, I think it's early days. I think it's, I mean, they're all over the place, right? I think there's silos within the enterprise that are really maximizing data. I think that that trend continues to happen. But I think there's got to be, and the enterprise architecture world is sort of about wrangling that, and figuring out how data from different dispersed touch points affect that. So, it's early days. I do think that you're starting to see that machine learning algorithms do play a part. I'm seeing it personally, more in the operations side of the world. So all these systems, at the end of the day, they need to be resilient and they need to have high service levels. So, what I'm seeing now is tools, and at Splunk, you saw that today, being able to be really predictive about where the anomalies are. Traditionally, you were having to log errors and then interpret errors, and then that would be the way you action some of these things. The predictive nature of some of these tools are such that you're being proactive. So when you talk about data there's so many different places you can go. If you think about our technology stack, and that guest experience point of view, it's all about really maintaining that SLA's, resolving issues as quickly as possible. And there's a ton of data in that space, right? I mean, it's everywhere, there's a ton of signals. >> Well you guys know, we tend not to throw stuff away in technology. You sort of have to figure out how to integrate. >> A signal via the customer is probably one of those, as well. So at the end of the day, what more information are we collecting about our guest to ultimately personalize that experience? It's centered around that. >> And that's challenging, I mean, look at the airlines. And your app, which you love the airline apps. I mean, you're not, like, tethered to them. But the phone experience, and even the laptop experience, are a little bit different. Because of the data, it's very, very challenging. Have you figured that out? Or are you sort of figuring that out? >> That's API's, right? It's that experienced API layer. Being able to activate that data which is sitting in distinct silos and then do so across those experience apps, the experience channels, which is dot-com, the app, the chatbot, there's so many interfaces out there. But, yeah, it's a solid, mature API strategy that's going to get us there. >> And I think one of the things that our challenge is, as technology partners, is the ability to build those platforms so that the next wave of conversions, as you mentioned, there's some disjointed experience across the desktop view versus the mobile view, is to try to bring those conversions together. And in order to that, like Ariel said, maybe making some API extraction layers figuring out how to mine the data better, figuring out how to leverage insights from different tools or machines and sensors, we have a ton of sensors on these ships as well. And bringing all those things together to be able to put us in a position that when we do finally get a seamless conversion, we're ready for it from a technology and a platform perspective. >> It's obvious why data is important for your business. You actually did a press release with Splunk. Maybe explain a little about how Splunk Cloud fits into this discussion that we've been having? >> Well, Cloud really removes the barriers of experimentation. How do you right-size a problem you don't understand very well? I think Cloud really helps with that. We're looking forward to being able to be flexible. Flexibility in architecture, flexibility in infrastructure. So that's absolutely the use-case I think security's got a number of use-cases. You see it every day in the news. So yeah, more opportunities, I would say, it scales that flexibility that's taken us the cloud route. >> When you think Splunk, you think security. You got guys in the Knock. That's not where you guys are. You're kind of closer to the business. And so you're seeing Splunk, as I said before, permeate into other parts of the organization. You kind of expected somebody else to do that. I don't know, the Hadoop guys. And it's interesting, Splunk never used to talk about big data. Now that the big data era is, sort of, behind us, Splunk talks a lot about big data. It's kind of an interesting flip. >> I would say it's democratizing the data. That's the stuff I liked, that I heard today. How do you get these tools away from the IT operators that are writing these complex queries to get insights? And how do you elevate that up to the analysts, and the product managers? And how do they get access to those interfaces? You know, drag-and-drop, whatever you want to call it. But I think that where I see this happening more so than, machine learning, that's great and predictive. But just empowering others to really leverage that data. I would say Splunk is leading there and it's good to see some of that stuff today. >> Absolutely. It's putting the power where it really needs to be, where it's the end users, the guys making decisions, it's the product owners, the product managers, that are making those slight tweaks to that interface, or to that design, or to that experience, that makes a difference. And that's what we're trying to do, and leverage with tools like Splunk, as well. >> Even the simple visualization, right, the stuff that's out of the box is really important for the business user, right? >> The out of the box part's another thing that I saw today, which is more, sort of, curating for particular use-case, and saying hey, we're going to build that end-to-end and really turn it on and activate it a little sooner. So that infrastructure product we saw today, I think that's a big step forward. Where you're a platform, but at some point you're going to have to start being a little more vertical in the way that you bring to market, the way that they did with security. >> And Doug talked about, you know, Doug Merritt, that is, talked about data is messy, and the messiest landscape is the data. And then he talked about being able to organize that data in the moment. So, I think about, okay, just put it in the, we like to call data ocean, right, and just capture it. But then having the tools to be able to actually look at it in whatever schema you want, when you want it, is a challenge that people have. My question is, did he describe it accurately? I think yes. But then, can you actually do that with this messy data? >> I think it's a great concept. I'm interested to see how that plays out going forward. But I think in our world, we have several use-cases where that makes sense. We have a very captive audience for seven to 10 days. So we really have a very limited amount of time to make a really good impression. So, it's not only about attracting first-time cruisers; it's trying to get a repeat cruiser. So that limited time frame that we have to leave a really lasting impression is very limited. So things like recovery, in terms of getting metrics or data real-time, and being able to act on it immediately. Say you had a bad experience at the sushi bar. If we're able to grab that information, whatever data points that allow us to understand what happened, and then do a quick recovery, we may have a guest for a repeat cruise. Those are the things that we're trying to do. And, if what Doug is saying is something that they've kind of solved, or are able to try to solve in a good way, that is very powerful for us as well, and we definitely see leverage in that. >> Last question, Ariel, you're saying off-camera it's kind of early days. What's the future hold? I mean, that's going to blow our minds. Blow our minds! >> Oh, it's the predictive thing, right? It's bringing you your favorite drink before you're ready to have it, or something. I don't know. The cruise line business, the travel and hospitality space is a very fun space to work in. We get to really see our guests enjoy the product. And us, as technologists, we get to see how technology moves the needle. Continued innovation, right? If you're in the development side of the world, challenging yourself to deploy more often, to deliver more value more often. And if you're on the data side, how to get aggregated, compile all this this data, for ultimately what we're looking for, which is to enhance the guest experience. >> I mean, that real-time notion that you were talking about Curt, you can see that coming together and completely transforming the guest experience. So guys, thanks so much for coming on theCUBE. It was great to have you. Congratulations on all your success and good luck. Alright keep it right there everybody, we'll be back at Splunk .conf18. You're watching theCUBE. Dave Vellante with Stu Miniman. we'll be right back! (upbeat music)

>> Narrator: Live from Las Vegas. It's theCUBE, covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. >> Welcome back everyone. We are here live in Las Vegas for SiliconANGLE Cube's exclusive coverage of HPE Discover 2017. I'm John Furrier with my co-host Dave Vellante. Our next guest is Justin Hotard, Vice President and General Manager of the Service Provider and OEM Solutions for HPE, Hewlett Packard Enterprise and Curt Belusar, Senior Director of Service Provider Engineering. We got the trends, we got the market leader, the go-to market leader, as well as the engineering. Guys, welcome to the CUBE. >> Thanks, great to be here. >> Thank you. >> So, obviously the service providers is an interesting marketplace. We've been covering it for a long time and we know how hot NFV is and all the great stuff going on with the network moving up the stack, applications over the cloud. You name it, it's a crazy world. But you look at the trends around smart cities, autonomous vehicles, and movie and media entertainment, smart home, Apple announcing a home pod. Internet of things. This is a right market for service providers, so my first question is, with 5G over the top, these kinds of trends, to power these transformative use cases. Is it really putting even more pressure on the service providers? So, what's the deal? Where are they at? What are you guys doing with the business? Give us a quick taste of the landscape and some of the forcing functions that are helping your business. >> Yeah absolutely, and I think you hit on a lot of the trends driving the growth in service providers. What we see is a very dynamic market where everybody is trying to figure out their business model and build their services and respond to all these changes. What we see is a lot of customers, our customers as service providers, need a lot of flexibility. They need to be able to respond to these changes. They also need to be able to scale. Globalization is a huge trend because I launched something in the U.S. and Uber or Lyft is a good example. I launch in the U.S. Everybody expects to have that service everywhere else in the world. >> And guess what, they say "Whoa, hold on." >> Exactly, exactly. Then you've got issues with data sovereignty, and security, and privacy, and you have to factor all of those things in. These businesses, our service provider customers, don't have time to wait. So, they really see us as a core partner to them, to enable speed and delivery. Curt, you probably can add a few points cause you've seen this market evolve over the last, almost decade. >> I think what we're seeing is a transition to where there's more data out at the edge, and so you're growing both edge data centers and you're growing central data centers at the same time. The percentage of operating expense that these customers are spending on their IT gear is just a very large percent, and so they are all trying to optimize their spend in that space. That means that they're looking at ways to optimize the gear. They're looking at ways to optimize how they deliver the gear out to the data centers. They're looking at reducing servicibility costs and trying to attack it across the board. >> Let's talk consolidation for a bit because early on everybody said "It's just going "consolidate to a few providers," and the exact opposite has happened. >> Yep. >> It's logical. Services have always been decentralized and local and that's exactly what you're describing. How do you look at the market? How do you segment it, and what's you're thinking in terms of the explosion or contraction of this market, in terms of number of players? >> A lot of what we see in the press or what's discussed is, we talk a lot about the infrastructure of service providers, and the largest service providers. The reality is that the market is fragmenting because more and more businesses are moving to an as-a-service model. There's business as a service, software as a service, and each of these customers has a unique business model. How they make money, where they extract value, how they respond to their customers. We really see that trend, and I don't think it's going to change. That's not to say that the largest players in the market won't continue to grow in scale. As we've seen, they've been doing that pretty consistently, but we're still going to see those different services and different values because it is local, it's customized. You think about autonomous driving. There's going to be, you brought that up earlier, right? There's the people that are going to provide autonomous vehicles for consumers. There's going to be people that provide it as a service. There's going to be people that provide services into those vehicles. >> Data services? >> Data services. Content services. We think all of those models will continue, and the economics of one-size-fits-all just don't work. When you look at our product strategy, our solution strategy, including point next and how we go to market. It's recognizing that. We have customers in Europe, for example, that buy what we might consider more traditional data infrastructure gear. A lot of the core products we have in market today. We have customers that want customized, we talk about white-box a lot, but customized solutions, the latest technology. Integrated, optimized for their workload, for their scale, and we run the gamut. A lot of that is because one size just doesn't fit all in this environment. Let alone what Curt was talking about with where they're deploying their technology. >> Yeah, I see the same trends. I think that both the large, public cloud providers are going to continue to grow, and then you're going to see the next tier down is also going to continue to grow. It's everything as-a-service is starting to explode. >> How are the requirements, are they dramatically different? I mean the large guys, they've got massive scale and gimme the stuff and get out of my way sort of attitude. But the second and third tier, there's a lot of customization required. Where do you see HPE being able to add value in that space? >> We're going to see customization at both ends. It's just going to be more customization with the top-tier customers. It's interesting, what you've seen is a lot of the IT skill-sets and people have migrated from some of the top-tier providers down to the second tier and so you see them wanting to employ a lot of the same techniques to go save cost and optimize their environment. When we say customize, there's a very good reason why they customize. They will customize to the extent that it allows them to go lower their total cost of ownership. >> Well that's a great point. Dave mentioned in an earlier segment that all companies are becoming technology companies. Jim Jackson was talking about the digital technology issues, so you have a power law going on. You're going to have it at the head and the long tail of the service providers. Some enterprises, you say enterprise market. You can almost say, okay there's a line. You guys are now the service providers, and the rest are traditional enterprises. In a way, they're SMBs from that old classical definition. The point is, the definition's changing. >> Yeah. >> How does that impact your business and your product offering? >> It's really interesting. I think your point is every company is a service provider, and so we also see this even within our Enterprise customers. They have workloads that are running on Enterprise. They run mission critical workloads, and then they run service provider platforms, and they're looking for that flexibility. They don't want to be bucketized. In order to compete, in order to have a service that might deliver content into their products or provide conductivity into their products for intelligence or AI, they need to have the same cost advantages, the same technology advantages, the same forward planning. Because a big thing we see in the service provider's space, is they buy ahead on technology because they're trying to run the life cycle of what they might need and get that return on investment. We see those same behaviors across our Enterprise customers that are buying as service providers. So there is a bit of a blending of the business. >> Is there a pattern that you can talk to in the marketplace? This is interesting cause if you believe that, which I do, and I think you guys would agree, that everyone's becoming a service provider. But service providers have had a legacy business that had completely different dimensions than say, a classic enterprise. A lot of online. A lot of hyper-scaler's upfront. Now you have data tsunami coming, so are there patterns that this is a little service provider like, that now the enterprises have to deal with. Can you share insight into some of the things that you guys are doing to solve that, and I mean I know the flexibility thing is a key message. Composability, I get that. What are the core customer problems that now look like service provider problems? >> Well, there are a lot of Enterprise customers that are going and starting to stand up environments that look like service provider environments. There's different reasons why they do that. They could need an internal cloud for some reason. They could actually be standing up a service now that they're offering out to the public. The answer is they are all looking for some of the same things in their cloud-like environment. They want consistency in the way that they want to go and deploy and talk to the servers. They want to have lowest cost, total cost of ownership, and that's both on a capital expense side, in terms of what they pay to go buy the actual equipment, but also on the operating expense side. The more that they can make their cloud or their grid look uniform, it becomes easier to service, it becomes easier to maintain. You're starting to see them on a smaller scale perhaps, but employ a lot of the same techniques that are used in the large clouds. >> The business model question too comes up. In the old days, the ones who were online, highly big procurers of gear, servers and storage. Financial services, healthcare, I mean, these are highly online, transactional businesses, and service providers also fell in that bucket, but now as everyone sassifies. Hello! Your revenue model is tied to those services. >> Yep, and it's interesting too because we put a lot of emphasis, I mean by virtue of being a technology company, we've put a lot of emphasis on the tech and making sure we've got the right systems and configurations we're delivering to the customer. The other thing is, it turns out that there's some laws around physics. So power matters, real estate matters, footprint matters. >> Distance? >> Distance. All those things for latency and proximity, and we talked about some of the other elements. But those are actually huge operating costs, huge value points for our customers. So, helping them make sure that they're balancing all those choice points. Because if we get the operating expense right on the tech, but then they can't handle the power, they can't handle the footprint, they've got a different issue. >> Scale's a huge issue. >> They can't scale, exactly. That actually puts a limit on their growth, so there's all these different things that we balance and where we bring value, and it's not just the technology, but that total solution. >> The service provider space has always been a harbinger for what's going to happen in the Enterprise. If you looked 10 years back it was virtualization, and then DevOps and containers, and all that stuff that's hitting the Enterprise now was being done years ago. What are the tech trends that are driving the service provider space now? What are you seeing there that might show us a glimpse as to what's coming in the future? Where are they focused? >> I think that we're seeing continuation and furthering of some of the technologies that we've seen the public clouds rolling out starting to happen with the Enterprise, but when I think from a technology trend standpoint, things that folks are looking at today. We're seeing alternate processors become available this year. ARM 64, we're getting into the second generation of that. We're seeing trends coming like NVMe drives, the ability to pull data off of a drive much quicker. If you're a financial services industry company that wants to transact data real quick, that's helping out there. We're seeing NVDIMM technology that's coming into play, and that's shifting everything. Storage and memory is starting to come together, and so the way that they move around and cache data is something that's going to change. Applications are going to have to change. >> John: Architectures are changing, big time. >> Absolutely. >> What are the drivers behind that? Because you brought up data and memory, and then also, we just had talking to the server, options, lead, and this is a big deal. Memory used to be a constraint that you have to program around. Swapping out, back in the old days, but now it's almost limitless, with the persistent SSDs, speed, and that gives app developers huge flexibility, so this should change the game on the service providers. >> It's all about the data. There is just more and more and more data being stored for different reasons, and the data sets that people want to operate on are just getting larger and larger. And to the extent that we can pull those in and operate on them in a faster way in memory, it helps. >> You guys have a very dynamic market, so I've got to ask the question, what is the biggest way that you guys are riding on the go-to market? And from a technology standpoint because if you believe this conversation we're having, what is happening is, a service provider, of a service provider, of a service provider, is going on because someone may be a specialist in say big data analytics service provider for cars. Or I am a healthcare service provider that's out of scale, so scale becomes now the new differentiation. >> Yep. >> That's the locked-in aspect, but I mean it's not really locked in, it's just they have scale. You can almost envision this channel of service providers. How would that play out, I mean, that would be certainly game-changing. How do you guys rationalize that trend? What is the wave that you're riding? >> I think it all goes back to our customers, and we're doing a few different things. So one is deep-direct engagement with these customers, especially the ones on the cutting edge. To have a early dialogue with them, make sure we're delivering the right solutions. The other thing is actually bringing value, so we do some things through it. We have a program called Partner Ready Service Provider. We bring in, actually from our service provider customers, and this is a global program. We actually then deliver those services cause we have certain customers that might, again back to that mix in a CIO's environment, they might look like an enterprise, they might look like a hyper-scale service provider customer, they may also look like they're a consumer of service providers. >> All three? >> Exactly. Actually being able to do all of that is really important, and we think when we wrap all of that with our service delivery, our global footprint, our supply chain, the ability to deliver products anywhere in the world. Those are all things that give us a solution advantage for our customers. >> Curt, talk about open, the cloud line server portfolio, fast grow in the cloud age is here, open infrastructure. I was just talking to some of the guys in the labs. You've seen some of the stuff at the network layer becoming open-source projects. You almost take the network stack and say, "Oh wow, there's like six open-source projects "that make up HP, Arista, Juniper, and Cisco." Core technologies, yet you have to build your own proprietary stuff around that to differentiate. How does open fit into all of this because at the end of the day, it's going to be an open-source driven software world with the cloud? >> I think there's open-source software pieces, and I think we will get to the point where we have more open standards around hardware too. You've seen OCP, you've seen Open19 launch a couple weeks ago and you're starting to see standards around the hardware as well. I think the open's critical. I think that it is the way of the future. In this space, I think that we, again back to the comment about what the large grids or large service provider customers need. They need uniformity in their data center to a certain extent. It makes it easier to manage and easier to operate. If you just start with that principle, that implies that we're going to have open standards. They're going to want open standards around the rack, they're going to want open standards around the gear, open standards around some of the options that go in the gear. There's going to be open standards from a software standpoint, and it's going to be the companies that go and sell that gear responsibility to make those bullet proof, to make them to the point where they're secure, to make them on the hardware side to the point where you can distribute it worldwide and service it. Open is here to stay. >> We've been predicting on the theCube, I know Dave's got a question, but I want to get this point out. We've been predicting, it hasn't yet come true, and most of our predictions come true, so we're kind of waiting for the signals. Since open compute, we're seeing a maker culture going on, where we believe there's going to be a hardware renaissance, and when I say open hardware, there's really a driver on that. Thoughts on that? Because, this certainly would change the game. You see people trying to do their own servers, but yet they can't get a fab plan opened up, they can't do this. Interesting trend. If software's eating the world, then data's going to eat software, which we believe. Then you might see a really big shift to soft, I mean the hardware. We had Microsoft's Ballmer say at the conference last week, we should have got in the hardware business earlier. I mean, what is that all about? So again, this points to a renaissance. Do you agree? >> Totally. I think you hit it dead on. We see the same thing, and it's a business model shift. It's a different business model than where we're been, but the opportunity to deliver value in open, around platforms, around making sure there's inter-operability, quality, security, exposing performance. Those are all things that are enabled through hardware, and they make a difference, and Curt talked earlier about some of these technology trends. They're very hardware centric because that's actually what delivers the difference in software and data. >> And systems too, and having systems experience is now the new IP. Not necessarily having the fastest board. >> Yeah. >> Yeah, that's right. Having that ability to integrate it and deliver an experience and performance. Those are things that make the difference. >> Curt, your thoughts. >> Like I said, I think that we are going to see more and more open standards around it, and I think it's going to help people scale. It's about putting the systems together, in a open-scalable way. It's also about getting more work done out of the systems. It's kind of a, if you think about through Capex and Opex, there's going to be a work per watt per dollar done. How can I get that best done in the most standard way? And standards are going to have to be there, to enable all these pieces to go together and come together with a uniform look in the data center, which is what anybody who's deploying the cloud needs. >> So Justin, put a bow on this segment. Summarize from your perspective Hewlett Packard Enterprise's cloud service provider strategy. Where can you add the most value? Where's the sweet spot, and where you going to make the money? >> I think what we add the most value in is being able to be a comprehensive provider for all of our customer's solutions, and that's not just the product. It's being able to deliver the specific product or that specific workload or application. Being able to provide that global footprint and supply chain, the services on top of it. So that a customer, when a customer makes a decision that they need help, they've got one partner to go to, and I think ultimately that's where we'll make the value. >> Justin Hotard, who's the VP GM Service Provider, of OEM Solutions, and Curt Belusar, Senior Director of Service Provider Engineering. Guys, thanks for this insight. Great conversation. We love it, we love hardware. We all love software too. All that machine learning out there, there's going to be more and more power available. This is theCUBE, bringing you all the action here at HPE Discover, doing our job delivering a bunch of great services around data and video. Of course, bringing you live stream here. I'm John Furrier with Dave Vellante. We'll be right back after this short break. (techno music)

(upbeat music) >> Hello, this is Dave Valente with theCUBE, and one of the most gratifying aspects of my role as a host of "theCUBE TV" is I get to cover a wide range of topics. And quite often, we're able to bring to our program a level of expertise that allows us to more deeply explore and unpack some of the topics that we cover throughout the year. And one of our favorite topics, of course, is data. Now, in 2021, after being in isolation for the better part of two years, a group of industry analysts met up at AWS re:Invent and started a collaboration to look at the trends in data and predict what some likely outcomes will be for the coming year. And it resulted in a very popular session that we had last year focused on the future of data management. And I'm very excited and pleased to tell you that the 2023 edition of that predictions episode is back, and with me are five outstanding market analyst, Sanjeev Mohan of SanjMo, Tony Baer of dbInsight, Carl Olofson from IDC, Dave Menninger from Ventana Research, and Doug Henschen, VP and Principal Analyst at Constellation Research. Now, what is it that we're calling you, guys? A data pack like the rat pack? No, no, no, no, that's not it. It's the data crowd, the data crowd, and the crowd includes some of the best minds in the data analyst community. They'll discuss how data management is evolving and what listeners should prepare for in 2023. Guys, welcome back. Great to see you. >> Good to be here. >> Thank you. >> Thanks, Dave. (Tony and Dave faintly speaks) >> All right, before we get into 2023 predictions, we thought it'd be good to do a look back at how we did in 2022 and give a transparent assessment of those predictions. So, let's get right into it. We're going to bring these up here, the predictions from 2022, they're color-coded red, yellow, and green to signify the degree of accuracy. And I'm pleased to report there's no red. Well, maybe some of you will want to debate that grading system. But as always, we want to be open, so you can decide for yourselves. So, we're going to ask each analyst to review their 2022 prediction and explain their rating and what evidence they have that led them to their conclusion. So, Sanjeev, please kick it off. Your prediction was data governance becomes key. I know that's going to knock you guys over, but elaborate, because you had more detail when you double click on that. >> Yeah, absolutely. Thank you so much, Dave, for having us on the show today. And we self-graded ourselves. I could have very easily made my prediction from last year green, but I mentioned why I left it as yellow. I totally fully believe that data governance was in a renaissance in 2022. And why do I say that? You have to look no further than AWS launching its own data catalog called DataZone. Before that, mid-year, we saw Unity Catalog from Databricks went GA. So, overall, I saw there was tremendous movement. When you see these big players launching a new data catalog, you know that they want to be in this space. And this space is highly critical to everything that I feel we will talk about in today's call. Also, if you look at established players, I spoke at Collibra's conference, data.world, work closely with Alation, Informatica, a bunch of other companies, they all added tremendous new capabilities. So, it did become key. The reason I left it as yellow is because I had made a prediction that Collibra would go IPO, and it did not. And I don't think anyone is going IPO right now. The market is really, really down, the funding in VC IPO market. But other than that, data governance had a banner year in 2022. >> Yeah. Well, thank you for that. And of course, you saw data clean rooms being announced at AWS re:Invent, so more evidence. And I like how the fact that you included in your predictions some things that were binary, so you dinged yourself there. So, good job. Okay, Tony Baer, you're up next. Data mesh hits reality check. As you see here, you've given yourself a bright green thumbs up. (Tony laughing) Okay. Let's hear why you feel that was the case. What do you mean by reality check? >> Okay. Thanks, Dave, for having us back again. This is something I just wrote and just tried to get away from, and this just a topic just won't go away. I did speak with a number of folks, early adopters and non-adopters during the year. And I did find that basically that it pretty much validated what I was expecting, which was that there was a lot more, this has now become a front burner issue. And if I had any doubt in my mind, the evidence I would point to is what was originally intended to be a throwaway post on LinkedIn, which I just quickly scribbled down the night before leaving for re:Invent. I was packing at the time, and for some reason, I was doing Google search on data mesh. And I happened to have tripped across this ridiculous article, I will not say where, because it doesn't deserve any publicity, about the eight (Dave laughing) best data mesh software companies of 2022. (Tony laughing) One of my predictions was that you'd see data mesh washing. And I just quickly just hopped on that maybe three sentences and wrote it at about a couple minutes saying this is hogwash, essentially. (laughs) And that just reun... And then, I left for re:Invent. And the next night, when I got into my Vegas hotel room, I clicked on my computer. I saw a 15,000 hits on that post, which was the most hits of any single post I put all year. And the responses were wildly pro and con. So, it pretty much validates my expectation in that data mesh really did hit a lot more scrutiny over this past year. >> Yeah, thank you for that. I remember that article. I remember rolling my eyes when I saw it, and then I recently, (Tony laughing) I talked to Walmart and they actually invoked Martin Fowler and they said that they're working through their data mesh. So, it takes a really lot of thought, and it really, as we've talked about, is really as much an organizational construct. You're not buying data mesh >> Bingo. >> to your point. Okay. Thank you, Tony. Carl Olofson, here we go. You've graded yourself a yellow in the prediction of graph databases. Take off. Please elaborate. >> Yeah, sure. So, I realized in looking at the prediction that it seemed to imply that graph databases could be a major factor in the data world in 2022, which obviously didn't become the case. It was an error on my part in that I should have said it in the right context. It's really a three to five-year time period that graph databases will really become significant, because they still need accepted methodologies that can be applied in a business context as well as proper tools in order for people to be able to use them seriously. But I stand by the idea that it is taking off, because for one thing, Neo4j, which is the leading independent graph database provider, had a very good year. And also, we're seeing interesting developments in terms of things like AWS with Neptune and with Oracle providing graph support in Oracle database this past year. Those things are, as I said, growing gradually. There are other companies like TigerGraph and so forth, that deserve watching as well. But as far as becoming mainstream, it's going to be a few years before we get all the elements together to make that happen. Like any new technology, you have to create an environment in which ordinary people without a whole ton of technical training can actually apply the technology to solve business problems. >> Yeah, thank you for that. These specialized databases, graph databases, time series databases, you see them embedded into mainstream data platforms, but there's a place for these specialized databases, I would suspect we're going to see new types of databases emerge with all this cloud sprawl that we have and maybe to the edge. >> Well, part of it is that it's not as specialized as you might think it. You can apply graphs to great many workloads and use cases. It's just that people have yet to fully explore and discover what those are. >> Yeah. >> And so, it's going to be a process. (laughs) >> All right, Dave Menninger, streaming data permeates the landscape. You gave yourself a yellow. Why? >> Well, I couldn't think of a appropriate combination of yellow and green. Maybe I should have used chartreuse, (Dave laughing) but I was probably a little hard on myself making it yellow. This is another type of specialized data processing like Carl was talking about graph databases is a stream processing, and nearly every data platform offers streaming capabilities now. Often, it's based on Kafka. If you look at Confluent, their revenues have grown at more than 50%, continue to grow at more than 50% a year. They're expected to do more than half a billion dollars in revenue this year. But the thing that hasn't happened yet, and to be honest, they didn't necessarily expect it to happen in one year, is that streaming hasn't become the default way in which we deal with data. It's still a sidecar to data at rest. And I do expect that we'll continue to see streaming become more and more mainstream. I do expect perhaps in the five-year timeframe that we will first deal with data as streaming and then at rest, but the worlds are starting to merge. And we even see some vendors bringing products to market, such as K2View, Hazelcast, and RisingWave Labs. So, in addition to all those core data platform vendors adding these capabilities, there are new vendors approaching this market as well. >> I like the tough grading system, and it's not trivial. And when you talk to practitioners doing this stuff, there's still some complications in the data pipeline. And so, but I think, you're right, it probably was a yellow plus. Doug Henschen, data lakehouses will emerge as dominant. When you talk to people about lakehouses, practitioners, they all use that term. They certainly use the term data lake, but now, they're using lakehouse more and more. What's your thoughts on here? Why the green? What's your evidence there? >> Well, I think, I was accurate. I spoke about it specifically as something that vendors would be pursuing. And we saw yet more lakehouse advocacy in 2022. Google introduced its BigLake service alongside BigQuery. Salesforce introduced Genie, which is really a lakehouse architecture. And it was a safe prediction to say vendors are going to be pursuing this in that AWS, Cloudera, Databricks, Microsoft, Oracle, SAP, Salesforce now, IBM, all advocate this idea of a single platform for all of your data. Now, the trend was also supported in 2023, in that we saw a big embrace of Apache Iceberg in 2022. That's a structured table format. It's used with these lakehouse platforms. It's open, so it ensures portability and it also ensures performance. And that's a structured table that helps with the warehouse side performance. But among those announcements, Snowflake, Google, Cloud Era, SAP, Salesforce, IBM, all embraced Iceberg. But keep in mind, again, I'm talking about this as something that vendors are pursuing as their approach. So, they're advocating end users. It's very cutting edge. I'd say the top, leading edge, 5% of of companies have really embraced the lakehouse. I think, we're now seeing the fast followers, the next 20 to 25% of firms embracing this idea and embracing a lakehouse architecture. I recall Christian Kleinerman at the big Snowflake event last summer, making the announcement about Iceberg, and he asked for a show of hands for any of you in the audience at the keynote, have you heard of Iceberg? And just a smattering of hands went up. So, the vendors are ahead of the curve. They're pushing this trend, and we're now seeing a little bit more mainstream uptake. >> Good. Doug, I was there. It was you, me, and I think, two other hands were up. That was just humorous. (Doug laughing) All right, well, so I liked the fact that we had some yellow and some green. When you think about these things, there's the prediction itself. Did it come true or not? There are the sub predictions that you guys make, and of course, the degree of difficulty. So, thank you for that open assessment. All right, let's get into the 2023 predictions. Let's bring up the predictions. Sanjeev, you're going first. You've got a prediction around unified metadata. What's the prediction, please? >> So, my prediction is that metadata space is currently a mess. It needs to get unified. There are too many use cases of metadata, which are being addressed by disparate systems. For example, data quality has become really big in the last couple of years, data observability, the whole catalog space is actually, people don't like to use the word data catalog anymore, because data catalog sounds like it's a catalog, a museum, if you may, of metadata that you go and admire. So, what I'm saying is that in 2023, we will see that metadata will become the driving force behind things like data ops, things like orchestration of tasks using metadata, not rules. Not saying that if this fails, then do this, if this succeeds, go do that. But it's like getting to the metadata level, and then making a decision as to what to orchestrate, what to automate, how to do data quality check, data observability. So, this space is starting to gel, and I see there'll be more maturation in the metadata space. Even security privacy, some of these topics, which are handled separately. And I'm just talking about data security and data privacy. I'm not talking about infrastructure security. These also need to merge into a unified metadata management piece with some knowledge graph, semantic layer on top, so you can do analytics on it. So, it's no longer something that sits on the side, it's limited in its scope. It is actually the very engine, the very glue that is going to connect data producers and consumers. >> Great. Thank you for that. Doug. Doug Henschen, any thoughts on what Sanjeev just said? Do you agree? Do you disagree? >> Well, I agree with many aspects of what he says. I think, there's a huge opportunity for consolidation and streamlining of these as aspects of governance. Last year, Sanjeev, you said something like, we'll see more people using catalogs than BI. And I have to disagree. I don't think this is a category that's headed for mainstream adoption. It's a behind the scenes activity for the wonky few, or better yet, companies want machine learning and automation to take care of these messy details. We've seen these waves of management technologies, some of the latest data observability, customer data platform, but they failed to sweep away all the earlier investments in data quality and master data management. So, yes, I hope the latest tech offers, glimmers that there's going to be a better, cleaner way of addressing these things. But to my mind, the business leaders, including the CIO, only want to spend as much time and effort and money and resources on these sorts of things to avoid getting breached, ending up in headlines, getting fired or going to jail. So, vendors bring on the ML and AI smarts and the automation of these sorts of activities. >> So, if I may say something, the reason why we have this dichotomy between data catalog and the BI vendors is because data catalogs are very soon, not going to be standalone products, in my opinion. They're going to get embedded. So, when you use a BI tool, you'll actually use the catalog to find out what is it that you want to do, whether you are looking for data or you're looking for an existing dashboard. So, the catalog becomes embedded into the BI tool. >> Hey, Dave Menninger, sometimes you have some data in your back pocket. Do you have any stats (chuckles) on this topic? >> No, I'm glad you asked, because I'm going to... Now, data catalogs are something that's interesting. Sanjeev made a statement that data catalogs are falling out of favor. I don't care what you call them. They're valuable to organizations. Our research shows that organizations that have adequate data catalog technologies are three times more likely to express satisfaction with their analytics for just the reasons that Sanjeev was talking about. You can find what you want, you know you're getting the right information, you know whether or not it's trusted. So, those are good things. So, we expect to see the capabilities, whether it's embedded or separate. We expect to see those capabilities continue to permeate the market. >> And a lot of those catalogs are driven now by machine learning and things. So, they're learning from those patterns of usage by people when people use the data. (airy laughs) >> All right. Okay. Thank you, guys. All right. Let's move on to the next one. Tony Bear, let's bring up the predictions. You got something in here about the modern data stack. We need to rethink it. Is the modern data stack getting long at the tooth? Is it not so modern anymore? >> I think, in a way, it's got almost too modern. It's gotten too, I don't know if it's being long in the tooth, but it is getting long. The modern data stack, it's traditionally been defined as basically you have the data platform, which would be the operational database and the data warehouse. And in between, you have all the tools that are necessary to essentially get that data from the operational realm or the streaming realm for that matter into basically the data warehouse, or as we might be seeing more and more, the data lakehouse. And I think, what's important here is that, or I think, we have seen a lot of progress, and this would be in the cloud, is with the SaaS services. And especially you see that in the modern data stack, which is like all these players, not just the MongoDBs or the Oracles or the Amazons have their database platforms. You see they have the Informatica's, and all the other players there in Fivetrans have their own SaaS services. And within those SaaS services, you get a certain degree of simplicity, which is it takes all the housekeeping off the shoulders of the customers. That's a good thing. The problem is that what we're getting to unfortunately is what I would call lots of islands of simplicity, which means that it leads it (Dave laughing) to the customer to have to integrate or put all that stuff together. It's a complex tool chain. And so, what we really need to think about here, we have too many pieces. And going back to the discussion of catalogs, it's like we have so many catalogs out there, which one do we use? 'Cause chances are of most organizations do not rely on a single catalog at this point. What I'm calling on all the data providers or all the SaaS service providers, is to literally get it together and essentially make this modern data stack less of a stack, make it more of a blending of an end-to-end solution. And that can come in a number of different ways. Part of it is that we're data platform providers have been adding services that are adjacent. And there's some very good examples of this. We've seen progress over the past year or so. For instance, MongoDB integrating search. It's a very common, I guess, sort of tool that basically, that the applications that are developed on MongoDB use, so MongoDB then built it into the database rather than requiring an extra elastic search or open search stack. Amazon just... AWS just did the zero-ETL, which is a first step towards simplifying the process from going from Aurora to Redshift. You've seen same thing with Google, BigQuery integrating basically streaming pipelines. And you're seeing also a lot of movement in database machine learning. So, there's some good moves in this direction. I expect to see more than this year. Part of it's from basically the SaaS platform is adding some functionality. But I also see more importantly, because you're never going to get... This is like asking your data team and your developers, herding cats to standardizing the same tool. In most organizations, that is not going to happen. So, take a look at the most popular combinations of tools and start to come up with some pre-built integrations and pre-built orchestrations, and offer some promotional pricing, maybe not quite two for, but in other words, get two products for the price of two services or for the price of one and a half. I see a lot of potential for this. And it's to me, if the class was to simplify things, this is the next logical step and I expect to see more of this here. >> Yeah, and you see in Oracle, MySQL heat wave, yet another example of eliminating that ETL. Carl Olofson, today, if you think about the data stack and the application stack, they're largely separate. Do you have any thoughts on how that's going to play out? Does that play into this prediction? What do you think? >> Well, I think, that the... I really like Tony's phrase, islands of simplification. It really says (Tony chuckles) what's going on here, which is that all these different vendors you ask about, about how these stacks work. All these different vendors have their own stack vision. And you can... One application group is going to use one, and another application group is going to use another. And some people will say, let's go to, like you go to a Informatica conference and they say, we should be the center of your universe, but you can't connect everything in your universe to Informatica, so you need to use other things. So, the challenge is how do we make those things work together? As Tony has said, and I totally agree, we're never going to get to the point where people standardize on one organizing system. So, the alternative is to have metadata that can be shared amongst those systems and protocols that allow those systems to coordinate their operations. This is standard stuff. It's not easy. But the motive for the vendors is that they can become more active critical players in the enterprise. And of course, the motive for the customer is that things will run better and more completely. So, I've been looking at this in terms of two kinds of metadata. One is the meaning metadata, which says what data can be put together. The other is the operational metadata, which says basically where did it come from? Who created it? What's its current state? What's the security level? Et cetera, et cetera, et cetera. The good news is the operational stuff can actually be done automatically, whereas the meaning stuff requires some human intervention. And as we've already heard from, was it Doug, I think, people are disinclined to put a lot of definition into meaning metadata. So, that may be the harder one, but coordination is key. This problem has been with us forever, but with the addition of new data sources, with streaming data with data in different formats, the whole thing has, it's been like what a customer of mine used to say, "I understand your product can make my system run faster, but right now I just feel I'm putting my problems on roller skates. (chuckles) I don't need that to accelerate what's already not working." >> Excellent. Okay, Carl, let's stay with you. I remember in the early days of the big data movement, Hadoop movement, NoSQL was the big thing. And I remember Amr Awadallah said to us in theCUBE that SQL is the killer app for big data. So, your prediction here, if we bring that up is SQL is back. Please elaborate. >> Yeah. So, of course, some people would say, well, it never left. Actually, that's probably closer to true, but in the perception of the marketplace, there's been all this noise about alternative ways of storing, retrieving data, whether it's in key value stores or document databases and so forth. We're getting a lot of messaging that for a while had persuaded people that, oh, we're not going to do analytics in SQL anymore. We're going to use Spark for everything, except that only a handful of people know how to use Spark. Oh, well, that's a problem. Well, how about, and for ordinary conventional business analytics, Spark is like an over-engineered solution to the problem. SQL works just great. What's happened in the past couple years, and what's going to continue to happen is that SQL is insinuating itself into everything we're seeing. We're seeing all the major data lake providers offering SQL support, whether it's Databricks or... And of course, Snowflake is loving this, because that is what they do, and their success is certainly points to the success of SQL, even MongoDB. And we were all, I think, at the MongoDB conference where on one day, we hear SQL is dead. They're not teaching SQL in schools anymore, and this kind of thing. And then, a couple days later at the same conference, they announced we're adding a new analytic capability-based on SQL. But didn't you just say SQL is dead? So, the reality is that SQL is better understood than most other methods of certainly of retrieving and finding data in a data collection, no matter whether it happens to be relational or non-relational. And even in systems that are very non-relational, such as graph and document databases, their query languages are being built or extended to resemble SQL, because SQL is something people understand. >> Now, you remember when we were in high school and you had had to take the... Your debating in the class and you were forced to take one side and defend it. So, I was was at a Vertica conference one time up on stage with Curt Monash, and I had to take the NoSQL, the world is changing paradigm shift. And so just to be controversial, I said to him, Curt Monash, I said, who really needs acid compliance anyway? Tony Baer. And so, (chuckles) of course, his head exploded, but what are your thoughts (guests laughing) on all this? >> Well, my first thought is congratulations, Dave, for surviving being up on stage with Curt Monash. >> Amen. (group laughing) >> I definitely would concur with Carl. We actually are definitely seeing a SQL renaissance and if there's any proof of the pudding here, I see lakehouse is being icing on the cake. As Doug had predicted last year, now, (clears throat) for the record, I think, Doug was about a year ahead of time in his predictions that this year is really the year that I see (clears throat) the lakehouse ecosystems really firming up. You saw the first shots last year. But anyway, on this, data lakes will not go away. I've actually, I'm on the home stretch of doing a market, a landscape on the lakehouse. And lakehouse will not replace data lakes in terms of that. There is the need for those, data scientists who do know Python, who knows Spark, to go in there and basically do their thing without all the restrictions or the constraints of a pre-built, pre-designed table structure. I get that. Same thing for developing models. But on the other hand, there is huge need. Basically, (clears throat) maybe MongoDB was saying that we're not teaching SQL anymore. Well, maybe we have an oversupply of SQL developers. Well, I'm being facetious there, but there is a huge skills based in SQL. Analytics have been built on SQL. They came with lakehouse and why this really helps to fuel a SQL revival is that the core need in the data lake, what brought on the lakehouse was not so much SQL, it was a need for acid. And what was the best way to do it? It was through a relational table structure. So, the whole idea of acid in the lakehouse was not to turn it into a transaction database, but to make the data trusted, secure, and more granularly governed, where you could govern down to column and row level, which you really could not do in a data lake or a file system. So, while lakehouse can be queried in a manner, you can go in there with Python or whatever, it's built on a relational table structure. And so, for that end, for those types of data lakes, it becomes the end state. You cannot bypass that table structure as I learned the hard way during my research. So, the bottom line I'd say here is that lakehouse is proof that we're starting to see the revenge of the SQL nerds. (Dave chuckles) >> Excellent. Okay, let's bring up back up the predictions. Dave Menninger, this one's really thought-provoking and interesting. We're hearing things like data as code, new data applications, machines actually generating plans with no human involvement. And your prediction is the definition of data is expanding. What do you mean by that? >> So, I think, for too long, we've thought about data as the, I would say facts that we collect the readings off of devices and things like that, but data on its own is really insufficient. Organizations need to manipulate that data and examine derivatives of the data to really understand what's happening in their organization, why has it happened, and to project what might happen in the future. And my comment is that these data derivatives need to be supported and managed just like the data needs to be managed. We can't treat this as entirely separate. Think about all the governance discussions we've had. Think about the metadata discussions we've had. If you separate these things, now you've got more moving parts. We're talking about simplicity and simplifying the stack. So, if these things are treated separately, it creates much more complexity. I also think it creates a little bit of a myopic view on the part of the IT organizations that are acquiring these technologies. They need to think more broadly. So, for instance, metrics. Metric stores are becoming much more common part of the tooling that's part of a data platform. Similarly, feature stores are gaining traction. So, those are designed to promote the reuse and consistency across the AI and ML initiatives. The elements that are used in developing an AI or ML model. And let me go back to metrics and just clarify what I mean by that. So, any type of formula involving the data points. I'm distinguishing metrics from features that are used in AI and ML models. And the data platforms themselves are increasingly managing the models as an element of data. So, just like figuring out how to calculate a metric. Well, if you're going to have the features associated with an AI and ML model, you probably need to be managing the model that's associated with those features. The other element where I see expansion is around external data. Organizations for decades have been focused on the data that they generate within their own organization. We see more and more of these platforms acquiring and publishing data to external third-party sources, whether they're within some sort of a partner ecosystem or whether it's a commercial distribution of that information. And our research shows that when organizations use external data, they derive even more benefits from the various analyses that they're conducting. And the last great frontier in my opinion on this expanding world of data is the world of driver-based planning. Very few of the major data platform providers provide these capabilities today. These are the types of things you would do in a spreadsheet. And we all know the issues associated with spreadsheets. They're hard to govern, they're error-prone. And so, if we can take that type of analysis, collecting the occupancy of a rental property, the projected rise in rental rates, the fluctuations perhaps in occupancy, the interest rates associated with financing that property, we can project forward. And that's a very common thing to do. What the income might look like from that property income, the expenses, we can plan and purchase things appropriately. So, I think, we need this broader purview and I'm beginning to see some of those things happen. And the evidence today I would say, is more focused around the metric stores and the feature stores starting to see vendors offer those capabilities. And we're starting to see the ML ops elements of managing the AI and ML models find their way closer to the data platforms as well. >> Very interesting. When I hear metrics, I think of KPIs, I think of data apps, orchestrate people and places and things to optimize around a set of KPIs. It sounds like a metadata challenge more... Somebody once predicted they'll have more metadata than data. Carl, what are your thoughts on this prediction? >> Yeah, I think that what Dave is describing as data derivatives is in a way, another word for what I was calling operational metadata, which not about the data itself, but how it's used, where it came from, what the rules are governing it, and that kind of thing. If you have a rich enough set of those things, then not only can you do a model of how well your vacation property rental may do in terms of income, but also how well your application that's measuring that is doing for you. In other words, how many times have I used it, how much data have I used and what is the relationship between the data that I've used and the benefits that I've derived from using it? Well, we don't have ways of doing that. What's interesting to me is that folks in the content world are way ahead of us here, because they have always tracked their content using these kinds of attributes. Where did it come from? When was it created, when was it modified? Who modified it? And so on and so forth. We need to do more of that with the structure data that we have, so that we can track what it's used. And also, it tells us how well we're doing with it. Is it really benefiting us? Are we being efficient? Are there improvements in processes that we need to consider? Because maybe data gets created and then it isn't used or it gets used, but it gets altered in some way that actually misleads people. (laughs) So, we need the mechanisms to be able to do that. So, I would say that that's... And I'd say that it's true that we need that stuff. I think, that starting to expand is probably the right way to put it. It's going to be expanding for some time. I think, we're still a distance from having all that stuff really working together. >> Maybe we should say it's gestating. (Dave and Carl laughing) >> Sorry, if I may- >> Sanjeev, yeah, I was going to say this... Sanjeev, please comment. This sounds to me like it supports Zhamak Dehghani's principles, but please. >> Absolutely. So, whether we call it data mesh or not, I'm not getting into that conversation, (Dave chuckles) but data (audio breaking) (Tony laughing) everything that I'm hearing what Dave is saying, Carl, this is the year when data products will start to take off. I'm not saying they'll become mainstream. They may take a couple of years to become so, but this is data products, all this thing about vacation rentals and how is it doing, that data is coming from different sources. I'm packaging it into our data product. And to Carl's point, there's a whole operational metadata associated with it. The idea is for organizations to see things like developer productivity, how many releases am I doing of this? What data products are most popular? I'm actually in right now in the process of formulating this concept that just like we had data catalogs, we are very soon going to be requiring data products catalog. So, I can discover these data products. I'm not just creating data products left, right, and center. I need to know, do they already exist? What is the usage? If no one is using a data product, maybe I want to retire and save cost. But this is a data product. Now, there's a associated thing that is also getting debated quite a bit called data contracts. And a data contract to me is literally just formalization of all these aspects of a product. How do you use it? What is the SLA on it, what is the quality that I am prescribing? So, data product, in my opinion, shifts the conversation to the consumers or to the business people. Up to this point when, Dave, you're talking about data and all of data discovery curation is a very data producer-centric. So, I think, we'll see a shift more into the consumer space. >> Yeah. Dave, can I just jump in there just very quickly there, which is that what Sanjeev has been saying there, this is really central to what Zhamak has been talking about. It's basically about making, one, data products are about the lifecycle management of data. Metadata is just elemental to that. And essentially, one of the things that she calls for is making data products discoverable. That's exactly what Sanjeev was talking about. >> By the way, did everyone just no notice how Sanjeev just snuck in another prediction there? So, we've got- >> Yeah. (group laughing) >> But you- >> Can we also say that he snuck in, I think, the term that we'll remember today, which is metadata museums. >> Yeah, but- >> Yeah. >> And also comment to, Tony, to your last year's prediction, you're really talking about it's not something that you're going to buy from a vendor. >> No. >> It's very specific >> Mm-hmm. >> to an organization, their own data product. So, touche on that one. Okay, last prediction. Let's bring them up. Doug Henschen, BI analytics is headed to embedding. What does that mean? >> Well, we all know that conventional BI dashboarding reporting is really commoditized from a vendor perspective. It never enjoyed truly mainstream adoption. Always that 25% of employees are really using these things. I'm seeing rising interest in embedding concise analytics at the point of decision or better still, using analytics as triggers for automation and workflows, and not even necessitating human interaction with visualizations, for example, if we have confidence in the analytics. So, leading companies are pushing for next generation applications, part of this low-code, no-code movement we've seen. And they want to build that decision support right into the app. So, the analytic is right there. Leading enterprise apps vendors, Salesforce, SAP, Microsoft, Oracle, they're all building smart apps with the analytics predictions, even recommendations built into these applications. And I think, the progressive BI analytics vendors are supporting this idea of driving insight to action, not necessarily necessitating humans interacting with it if there's confidence. So, we want prediction, we want embedding, we want automation. This low-code, no-code development movement is very important to bringing the analytics to where people are doing their work. We got to move beyond the, what I call swivel chair integration, between where people do their work and going off to separate reports and dashboards, and having to interpret and analyze before you can go back and do take action. >> And Dave Menninger, today, if you want, analytics or you want to absorb what's happening in the business, you typically got to go ask an expert, and then wait. So, what are your thoughts on Doug's prediction? >> I'm in total agreement with Doug. I'm going to say that collectively... So, how did we get here? I'm going to say collectively as an industry, we made a mistake. We made BI and analytics separate from the operational systems. Now, okay, it wasn't really a mistake. We were limited by the technology available at the time. Decades ago, we had to separate these two systems, so that the analytics didn't impact the operations. You don't want the operations preventing you from being able to do a transaction. But we've gone beyond that now. We can bring these two systems and worlds together and organizations recognize that need to change. As Doug said, the majority of the workforce and the majority of organizations doesn't have access to analytics. That's wrong. (chuckles) We've got to change that. And one of the ways that's going to change is with embedded analytics. 2/3 of organizations recognize that embedded analytics are important and it even ranks higher in importance than AI and ML in those organizations. So, it's interesting. This is a really important topic to the organizations that are consuming these technologies. The good news is it works. Organizations that have embraced embedded analytics are more comfortable with self-service than those that have not, as opposed to turning somebody loose, in the wild with the data. They're given a guided path to the data. And the research shows that 65% of organizations that have adopted embedded analytics are comfortable with self-service compared with just 40% of organizations that are turning people loose in an ad hoc way with the data. So, totally behind Doug's predictions. >> Can I just break in with something here, a comment on what Dave said about what Doug said, which (laughs) is that I totally agree with what you said about embedded analytics. And at IDC, we made a prediction in our future intelligence, future of intelligence service three years ago that this was going to happen. And the thing that we're waiting for is for developers to build... You have to write the applications to work that way. It just doesn't happen automagically. Developers have to write applications that reference analytic data and apply it while they're running. And that could involve simple things like complex queries against the live data, which is through something that I've been calling analytic transaction processing. Or it could be through something more sophisticated that involves AI operations as Doug has been suggesting, where the result is enacted pretty much automatically unless the scores are too low and you need to have a human being look at it. So, I think that that is definitely something we've been watching for. I'm not sure how soon it will come, because it seems to take a long time for people to change their thinking. But I think, as Dave was saying, once they do and they apply these principles in their application development, the rewards are great. >> Yeah, this is very much, I would say, very consistent with what we were talking about, I was talking about before, about basically rethinking the modern data stack and going into more of an end-to-end solution solution. I think, that what we're talking about clearly here is operational analytics. There'll still be a need for your data scientists to go offline just in their data lakes to do all that very exploratory and that deep modeling. But clearly, it just makes sense to bring operational analytics into where people work into their workspace and further flatten that modern data stack. >> But with all this metadata and all this intelligence, we're talking about injecting AI into applications, it does seem like we're entering a new era of not only data, but new era of apps. Today, most applications are about filling forms out or codifying processes and require a human input. And it seems like there's enough data now and enough intelligence in the system that the system can actually pull data from, whether it's the transaction system, e-commerce, the supply chain, ERP, and actually do something with that data without human involvement, present it to humans. Do you guys see this as a new frontier? >> I think, that's certainly- >> Very much so, but it's going to take a while, as Carl said. You have to design it, you have to get the prediction into the system, you have to get the analytics at the point of decision has to be relevant to that decision point. >> And I also recall basically a lot of the ERP vendors back like 10 years ago, we're promising that. And the fact that we're still looking at the promises shows just how difficult, how much of a challenge it is to get to what Doug's saying. >> One element that could be applied in this case is (indistinct) architecture. If applications are developed that are event-driven rather than following the script or sequence that some programmer or designer had preconceived, then you'll have much more flexible applications. You can inject decisions at various points using this technology much more easily. It's a completely different way of writing applications. And it actually involves a lot more data, which is why we should all like it. (laughs) But in the end (Tony laughing) it's more stable, it's easier to manage, easier to maintain, and it's actually more efficient, which is the result of an MIT study from about 10 years ago, and still, we are not seeing this come to fruition in most business applications. >> And do you think it's going to require a new type of data platform database? Today, data's all far-flung. We see that's all over the clouds and at the edge. Today, you cache- >> We need a super cloud. >> You cache that data, you're throwing into memory. I mentioned, MySQL heat wave. There are other examples where it's a brute force approach, but maybe we need new ways of laying data out on disk and new database architectures, and just when we thought we had it all figured out. >> Well, without referring to disk, which to my mind, is almost like talking about cave painting. I think, that (Dave laughing) all the things that have been mentioned by all of us today are elements of what I'm talking about. In other words, the whole improvement of the data mesh, the improvement of metadata across the board and improvement of the ability to track data and judge its freshness the way we judge the freshness of a melon or something like that, to determine whether we can still use it. Is it still good? That kind of thing. Bringing together data from multiple sources dynamically and real-time requires all the things we've been talking about. All the predictions that we've talked about today add up to elements that can make this happen. >> Well, guys, it's always tremendous to get these wonderful minds together and get your insights, and I love how it shapes the outcome here of the predictions, and let's see how we did. We're going to leave it there. I want to thank Sanjeev, Tony, Carl, David, and Doug. Really appreciate the collaboration and thought that you guys put into these sessions. Really, thank you. >> Thank you. >> Thanks, Dave. >> Thank you for having us. >> Thanks. >> Thank you. >> All right, this is Dave Valente for theCUBE, signing off for now. Follow these guys on social media. Look for coverage on siliconangle.com, theCUBE.net. Thank you for watching. (upbeat music)

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Welcome back everyone. We are wrapping up three at days of wall to wall coverage of Microsoft ignite. It is a game day atmosphere on the show floor at the orange County civic center. Thank you so much to Cohesity for hosting the cube for this fantastic three days. I'm your host, Rebecca Knight along with my co host Stu Miniman. Still this is awesome. We talk about the buzz on the floor and the energy on the show and definitely guy here Cohesity always bright and activity >>in the booth and it's been a lot of fun hanging out here for the week with you Rebecca and our hosts and all, all of the guests. Yes, absolutely. So this is day three. We are starting our series of interviews, but I want to hear because you are so in this community you have a lot of connections, a lot of buddies, a lot of colleagues, former colleagues, current colleagues. What has impressed you about the show and what is missing? Let's start with the positives and it's interesting because this is only my second year coming. One of those, you know, my background networking, I've interacted with Microsoft for most of my career. I would not say I am deep in the community, but I know enough of the MVPs, have friends here and really have learned a lot in these two years. So first of all, the breadth of this show is just so impressive. >>One of the things that you and I've been talking about the last two years, years, what is the show? It started out as a windows admin show. Lot of discussion about office migration to windows 10 was the big thing last year. We haven't heard as much about this this year. Yesterday was a big developer day. Of course Azure sits at the center of everything. Lots of big announcements here. Felt like a kind of on par with what we hear at AWS. It shows with just so many announcements across the board. But really when you talk about the applications of business productivity, people come to this show. When I talk to people in the booth, I'm looking for solutions and how do I put those together? It's not some of the tech shows where you just, you're constantly down in the speeds and feeds and what they're doing and some of the competitive dynamics. >>I have a problem, my business needs something in, this is what I'm looking to solve. And Microsoft has a broad and diverse ecosystem and the word we kept coming back to the word of the week I think is of course trust. >> Absolutely. I couldn't agree more with what you've just said. That is what we hear. And the other thing about Microsoft is that at a time when big tech is really under a lot of fire, there's a lot of suspicion policymakers, regulators are bearing down on a lot of the tech CEOs. Microsoft really stands above. And when you think about antitrust, there's major presidential candidates talking about breaking up big Chuck, big tech. Microsoft is really riding above that fray. There's sort of a feeling of deja VU for Microsoft, I'm sure. But that they're really been there, done that. They're not. Yeah, I mean it was Satya Nadella to, you know, really put a pointed attack. >>He did not say it, but we all know it's Google. You know the company that was do no evil at the start. Now everybody's concerned because Google's model is primarily selling ads and while Google will say what they're doing in the enterprise, they just acquired Fitbit and said, you're not going to get ads on your Fitbit. We're not going to leverage that way, but there's not that trust built up. And then the number one competitor out there is AWS. And if you talk about the ecosystem, the concern that every AWS show is, Oh my gosh, what announcements are Amazon going to make and are they going to steal my lunch money if you were or put me out of business for the years worth of work on doing. Microsoft doesn't feel that way. They, you know, if you talk about the ecosystem I was talking, they made announcements that do compete against number the products, RPA, or was announced as part of the power platform out there. >>There's a number of RPA companies here. I talked to them there. Microsoft's a strong partner. We've been doing breakouts, we're talking with them. Yes, they are just like SAP getting into this market, but it's a Microsoft shop and it's not, you know, it is new. It's not the best of breed. They're on it. They are not concerned that they can still live in this environment. And I'd say both AWS and Azure very much about choice and ecosystem and building them out. >> So you're talking about the marketplace here. So in terms of the marketplace, what is Microsoft doing to drive business and is it effective? Well actually I'm glad you, so specifically we talk about the marketplace. So there's the ecosystem and then there's actually the marketplace. So AWS has what we really consider, it's the enterprise app store. If I want to go buy software, you know there's Salesforce and all of their connectors and everyone that uses Salesforce knows that. >>But AWS really has driven a robust ecosystem just like on amazon.com most of the products that are sold are from third parties. The AWS marketplace is mostly how I can procure and buy software. And they drive a lot of it. So a lot of the AWS adoption is through the marketplace and the ecosystem makes lots of dollars. Reminds me, we used to talk about VMware for years is for every dollar of VMware you bought you would buy, you know, 10 $20 worth of third party ecosystem. But we were talking about things like storage and like for AWS it's on procuring software and underneath on leveraging the AWS services. While Microsoft Azure has a marketplace, it is not as mature. They don't really push as many people through it. So while I've talked to a number of the partners that are, yes we're part of the marketplace, but people buy lots of different ways as opposed to AWS is trying to get everybody from a customer and an ecosystem through it. >>And part of that is to simplify the environment, how I purchase it. But it's that balance of trust and you know, ease of use out there. So when I look forward, what do I like to see from Azure is how will they mature there. I was actually something John furrier had had us digging into here and the marketplace at Azure definitely is, I would say years behind where AWS is, is there, but you know, Azure great growth, doing really well, a strong trusted ecosystem. Just some areas for improvement that I would look for going forward. >>But maybe that's part of their, their approach and their strategy is we'll work with you, we, we collaborate, we can do this together. Whereas AWS there is that, that feeling sometimes when you're at reinvent, as you said, roll out the beer, CURT's early please. My business is over. So, so, so comparing the two show, the three, the various cloud shows, and this is not just a cloud show, of course we're going to get into that more. But when you think about re-invent and you think about VM world, how does the, the feel and the energy here differ? >>Yeah. So the thing that always strikes me when I go to an AWS show, and I have been to many of them from the regional shows through the big one and reinvent, which is more than twice the size of this 26,000 person show. The customers there are always trying new things. They are open and looking for the environment that they can do new things. Here what we're talking about here feels like it's like a tweener. We had a lot of conversations about building bridges to where customers are while AWS is starting to talk hybrid more and meet you in your data center and doing outpost Microsoft, they have their windows install base, they have their own three 65 pieces. So there's a broad spectrum of from the latest and greatest autonomous systems. You want to talk about it. Microsoft has that through, you know, I'm a, you know, 20 year CIS admin and I, you know, I'm going to hold on to, you know, my servers, you know, as long as I can, they're there for you. >>So Microsoft does bam, that gamut and VMware is more, once again making that transition as we go to the cloud. So Microsoft right in the middle of that transition, we talked a bunch about digital transformation with the customers on here. So it really, it has all a lot for a lot of different people. You know is one of the things I've heard is they really ramped up some of the developer activity at this show. They just bought get hub, get hub, has their own show, get hub universe next week, which will stay very focused on that environment. But Microsoft also has a conference build and there's been some rumblings that maybe build an ignite get wrapped together. We saw that with IBM. IBM had lots of different shows and they put all the wood behind think and made that a massive show. There's pros and cons of that, seeing lots of companies that have taken a big show and put it into a 40 show around the globe. >>Now someone like Amazon has reinvented, but then they have of second tier and third tier regional shows to push that out. So lots of different ways to, to get to customers. Um, and it is interesting, you know, we spent a lot of time talking about Azure Ark. I'll be at the cube con cloud-native clown show in just two weeks and San Diego and expect that to be talked. And really it is in preview mode. So when I look at it at the end of the day is, you know, you've got red hat open shift, you have Google, you have what AWS is doing with outpost and welcome to the party. Microsoft, they have got a strong hybrid solution already because they played at both ends. But really as your arc is unifying and pulling those together so that it's not just my data center and Azure, but even AWS, they're saying, we'll see how this all plays out. >>Microsoft definitely has a strong data focus and a strong application focus. And so it be interesting to see where that adoption happens. I've been saying for a couple of weeks. Really Kubernetes just get baked in everywhere and you know, customers aren't going to have to think about it in a most Microsoft definitely strong partner focus. Just to reinforce something I've said a couple times this week, they still have a partnership with red hat. They still have a partnership with VMware. The Azure arc is not the only way to get the Kubernetes story in play into your Microsoft environment. And Microsoft's done well with that. We all know from the early days of Microsoft living on tops of lots of hardware. Now Microsoft software will live a lot of places. Yes, their cloud is large growing one of the top two choices out there. But they truly embrace that it will be multi-cloud and be able to live in lots of environments. >>So I want to talk about something that's more in my wheel, hasn't met his productivity. So we have heard a little bit about teams. I mean there was a lot of announcements. It's not exactly where we focused a lot here on the cube this week, but there were some really interesting announcements about the ways in which Microsoft is thinking about human productivity, both at individual productivity and team collaboration, the way teams interact and communicate. There are a lot of interesting new uh, characteristics and elements to what they're doing in terms of Cortana re read me my emails. Uh, I'm going to send this email but I'm actually gonna wait, it's good. It's going to be a scheduled send. It's going to send when the, when the, the person I'm sending it to is, is actually at his or her desk. Um, and so those are just some interesting things to me that really speak volumes about how Microsoft views the future of work and views the, the future of our, of our lives. And, and, and understanding how much technology has encroached in our lives because they're saying, read me my emails while I take my dog for a walk while I am actually doing, while I'm on a run first thing in the morning. I, you know, make me more productive but also give me my time back. And so I think those are some really, really interesting ways in which Microsoft, as I said, understands the technology has taken over and they're trying to give you a bit of your time back. >>It's interesting cause you know when I look back, Microsoft has a bit of a checkered history when it comes to some of those environments. We all know the office suite teams is now part of O three 65 and I hear very strong. The people that use it really do like it. But those of us look back and we said, Oh I used to like using Skype and then Microsoft got ahold of it and Oh my gosh, what a horrendous mess. Skype was for a long time when it taught to a collaborative environment. Google really jumped Microsoft with the G suite and many smaller companies were like, Oh, it's relatively easy to use and I can collaborate there. Well teams really has gone through and understand that and we talk about a collaborative environment, you know, Microsoft teams, best of breeds. I attended an enterprise connect earlier this year and I couldn't hear enough about how much that was going on. >>And you know, strong ecosystem of companies that Microsoft worked with. So it's very strong, but it's kind of, if you're a Microsoft shop, you're doing it. But they did lose many companies too free or less expensive or lighter weight options out there. And then everything from Slack ate into it. But you know, Microsoft has a good product. Absolutely. It just, some of it is the perception and some of it is the pricing. You know, they do a good job of making sure that when you get get to college, you, you want to use some of these environments. Oh yeah, the pricing is graded free. But then when you get in the real world, hopefully you'll like it. So Microsoft does a little bit about now something we focused a lot on but did hear really good things about it. And it does get lost a little bit in some of the general discussion about all the other pieces, you know, autonomous systems, AI and the leaders. This stuff of Azure take a little bit of precedent over the, some of the things that are a little bit more on just as you said, business productivity or even on the consumer side of the house for Microsoft. >>So we are, we're, we're wrapping up here but I want to hear just final thoughts, final predictions for 2020 and you've really gotten, you've, we've, we've covered a lot of ground here, this wording, but I'm interested to hear what you think is on tap for Microsoft in 2020 I'll bring >>back to something we kicked off with the jet ideal coming in here really has that that whole process of winning that bid was a fortune function from Microsoft to rapidly mature some of their environment. You talk about security and trust, you know the government is not going to give that environment if it to Microsoft, if they could not trust them. Back when AWS won a CIA deal, it was like, Oh wait, if the security is good enough for the CIA, it's probably good enough for me to consider it. So the government agencies, which historically is not who you think about when you talk about innovation in driving change today. Public sector is really interesting. Even when we were talking to some of the people about, Hey, how can we haven't heard as much about Azure stack over the years? Well, it's been a lot of service providers and government agencies that have been deploying this and therefore we'll do it. So Microsoft still has a lot of work to do contracts. They still have to get some more security clearances. They need to make sure their performance and reliability is up to snuff on because they just can't have outages. If I, if this becomes a greater and greater piece of my overall how I run my business, I can't say, oops, wait, you know the Internet's down. This is now 2019 going into 2020 and in 2020 we'll all have perfect. >>Oh, of course. Oh yes indeed. Sue, I'm looking forward to another great day of coverage with you, and thank you again to Cohesity for hosting us in this really cool booth. Uh, so please stay tuned for more of the cubes live coverage of Microsoft ignite coming up in just a little bit.

[Music] [Applause] I'll Buena Burris and welcome to another cube conversation from our fantastic studios in beautiful palo alto california today we're going to be talking about what infrastructure can do to accelerate AI and specifically we're gonna use a relationship a burgeoning relationship between PDN and nvidia to describe what we can do to accelerate AI workloads by using higher performance smarter and more focused of infrastructure for computing now to have this conversation we've got two great guests here we've got Kurt ku kind who is the senior director of marketing at ddn and also Darren Johnson is a global director of technical marketing for enterprise and NVIDIA Kurt Gerron welcome to the cube thanks for thank you very much so let's get going on this because this is a very very important topic and I think it all starts with this notion of that there is a relationship that you guys have put forward Kurt once you describe it sure well so what we're announcing today is ddn's a3i architecture powered by Nvidia so it is a full rack level solution a reference architecture that's been fully integrated and fully tested to deliver an AI infrastructure very simply very completely so if we think about how this is gonna or why this is important AI workloads clearly have a special stress on underlying technology Darin talk to us a little bit about the nature of these workloads and why in particular things like GPUs and other technologies are so important to make them go fast absolutely and as you probably know AI is all about the data whether you're doing medical imaging whether you're doing natural language processing whatever it is it's all driven by the data the more data that you have the better results that you get but to drive that data into the GPUs you need great IO and that's why we're here today to talk about ddn and the partnership of how to bring that I owe to the GPUs on our dgx platforms so if we think about what you described a lot of small files off and randomly just riveted with nonetheless very high-profile jobs that just can't stop midstream and start over absolutely and if you think about the history of high-performance computing which is very similar to a I really I owe is just that lots of files you have to get it they're low latency high throughput and that's why ddn's probably nearly twenty years of experience working in that exact same domain is perfect because you get the parallel file system which gives you that throughput gives you that low latency just helps drive the GPU so we you'd mention HPC from 20 years of experience now it used to be that HPC you'd have scientists with a bunch of graduate students setting up some of these big honkin machines but now we're moving into the commercial domain you don't have graduate students running around you don't have very low cost high quality people you're you know a lot of administrators who nonetheless good people but a lot to learn so how does this relationship actually start making or bringing AI within reach of the commercial world exactly where this reference architecture comes in right so a customer doesn't need to start from scratch they have a design now that allows them to quickly implement AI it's something that's really easily deployable we've fully integrated this solution ddn has made changes to our parallel file system appliance to integrate directly within the DG x1 environment makes that even easier to deploy from there and extract the maximum performance out of this without having to run around and tune a bunch of knobs change a bunch of settings it's really gonna work out of the box and the you know nvidia has done more than just the DG x1 it's more than hardware you've done a lot of optimization of different of AI toolkits if Sarah I'm talking what about that Darin yeah so I mean talking about the example I use researchers in the past with HPC what we have today are data scientists data scientists understand pie tours they understand tensorflow they understand the frameworks they don't want to understand the underlying filesystem networking RDMA InfiniBand any of that they just want to be able to come in run their tensorflow get the data get the results and just turn that keep turning that whether it's a single GPU or 90 Jex's or as many dejection as you want so this solution helps bring that to customers much easier so those data scientists don't have to be system administrators so a reference architecture that makes things easier but that's more than just for some of these commercial things it's also the overall ecosystem new application providers application developers how is this going to impact the aggregate ecosystem it's growing up around the need to do AI related outcomes well I think one point that Darrin was getting to you there and one of the big effects is also as these ecosystems reach a point where they're going to need to scale right there's somewhere where ddn has tons of experience right so many customers are starting off with smaller data sets they still need the performance a parallel file system in that case is going to deliver that performance but then also as they grow right going from one GPU to 90 G X's is going to be an incredible amount of both performance scalability that they're going to need from their i/o as well as probably capacity scalability and that's another thing that we've made easy with a3i is being able to scale that environment seamlessly within a single namespace so that people don't have to deal with a lot of again tuning and turning of knobs to make this stuff work really well and drive those outcomes that they need as they're successful right so in the end it is the application that's most important to both of us right it's it's not the infrastructure it's making the discoveries faster it's processing information out in the field faster it's doing analysis of the MRI faster it's you know helping the doctors helping the anybody who's using this to really make faster decisions better decisions exactly and just to add to that I mean in automotive industry you have datasets that are from 50 to 500 petabytes and you need access to all that data all the time because you're constantly training and Retraining to create better models to create better autonomous vehicles and you need you need the performance to do that ddn helps bring that to bear and with this reference architecture simplifies it so you get the value add of nvidia gpus plus its ecosystem of software plus DD on its match made in heaven Darren Johnson Nvidia Curt Koo Kien ddn thanks very much for being on the cube thank you very much and I'm Peter burrs and once again I'd like to thank you for watching this cube conversation until next time [Music]

>> Announcer: Live form the Computer History Museum in Mountain View, California, it's theCUBE. Covering DevNet Create 2018. Brought to you by Cisco. >> Hi, my name is Lauren Cooney and welcome back to theCUBE. Today we're actually at down in Mountain View at DevNet Connect where we're talking to folks about Cloud, DevOps, things along those lines and really what developers are looking for in today's environment. Today I'm here with Curt. And we're going to talk a little bit about what Kurt is doing and why he's here and what's going on in your world? >> Thanks Lauren. I'm excited to be here. This is, being at a DevNet Create, where IOT is sort of a major backdrop is a change of pace for us and something that we're very excited about to get involved in. >> Great, so what, you're here for IOT, what're you really looking at within IOT? What is interesting to you? >> Well, so I work with Sonatype and our, sort of, passion and what we bring to the world of IT in general, is software supply change. We saw a gap in virtually unlimited supply of open source components that are being used to develop modern solutions and we've been helping our enterprise customers solve this problem for a while and it now occurs to us that it's just going to explode and get much bigger with IOT. >> Lauren: And all the types of devices. >> And it's all the same problems and it's the same sorts of things that we need to think about as a traditional IT, if you will. Traditional applications. >> Great. So what's an example of a customer that you would help with regards to your solution and with IOT? >> So, it would be generally a large enterprise that's looking to put some governance around what's flowing into their organization in terms of these free components: libraries, utilities, that are being packaged together and delivered. In the world of IOT, what's interesting is we also need to be very careful about what we put in there for possible exploits. And we need to be thinking about how are we going to keep them patched and updated, right? >> Lauren: Mhm. >> We have a saying at Sonatype that software ages like milk and not like wine. So it's generally just a matter of time before components start to show their age and suffer from known exploit patterns. And so we're going to need to get in front of that problem and make sure we're thinking about it as we start to develop, you know, the millions and billions of devices that are going to start to proliferate throughout our lives. >> Exactly and so how do you decide, kind of, what open source you support or what devices you support inside of that supply chain? >> Yeah, so we're focused on it. So we're looking at just the open source, right? So, it's not the proprietary stuff. It's not the commercial stuff. So we're watching like the 60 million github repositories and we're watching a million events a day trigger. And we're just looking through the forums and through the commit logs and a variety of others, you know, like a thousand plus other sources. And correlating all that data into something that's very specific and actionable, so that our customers can ultimately make an informed decision about what they're using, right? So half of the battle of managing risk is simply being aware -- >> Oh definitely. >> of what you got. The goal is not necessarily to be perfectly clean but to have really good awareness of where your weaknesses are so that you can sort of prepare or brace yourself against it or put up other mitigating controls. >> Great and so do you guys provide a dashboard, for example for a compliance team inside of a company? >> What we provide is a fully automated solution that embeds throughout your software delivery life cycle. It's designed for the modern world. It's designed to be very precise so you can automate against it and that's where traditional tools fall down. They were, sort of, built for a waterfall era, where people could take days to go through an approval process. We feel it needs to be done in a matter of minutes, so it fits in a modern pipeline. So yeah we provide that intelligence feed and then we're tied into your build and delivery process and then it does surface. It can break the pipeline and surfaces as a dashboard report where you can drill into the details and then figure out what you got to do to move forward. >> Great, and that tracks licenses and things along those lines as well? >> Yeah, licenses is sort of the original concern of open source. >> Mhm, it is. >> It's been overshadowed by more recent security concerns but licensing is a very important part too if you want to protect your IP, you need to be careful about what you're putting in these devices. >> Oh by far. Now, I was looking at your LinkedIn a little bit earlier and you have a lot of experience with DevOps and actually driving DevOps environments, tooling, things along those lines. Tell us about that. >> Yeah, so I started getting involved in DevOps sort of, when it was very first a word, if you will. I literally rebranded my team, the DevOps team and it was meant to provoke conversations. It was fairly effective at that. But I did develop a high trust team. I actually was able to implement the cultural part of that within my team. I couldn't change the whole Fortune 100 insurance company but we could demonstrate the art of the possible. It was an awesome ride. I was also inviting security to the table long before DevSecOps came on the scene, because I intuitively understand it was holistic and we needed to get everybody involved. So yeah, I'd like to think I was a little bit ahead of the curve there and had an opportunity to do some great work with some great people that continues to serve me well to this day as we as a industry mature into it. >> Yeah, I think it's really interesting. I remember going into a large customer and we were talking about, kind of, a solution for this customer. And at one end of the table was the infrastructure developers. The other end of the table was the app developers and in the middle sat the tooling guys. Right, and so it was always interesting to see how they kind of flock to their different sides and when they started working together, how, you know, a couple people would sit together and they morphed a bit. And I think that's really interesting in terms of the culture element. >> Yeah, I mean that's essentially what my team was. We were that tooling team. But we acted as the team that was bridging those relationships and bringing those teams together. The middle ware team in particular, along with our development team. Ops was a little bit further down the line. But also getting security and audit involved. Stuff like that. So yeah, it was an interesting role. And it's just neat to see that we're maturing as an industry and this is starting to become very real and the tooling now exists to make this stuff very doable, unlike five years ago. You know, there just wasn't quite the tooling there. Conceptually we knew what we wanted to do, but until the tooling shows up, it's hard to really automate it and do it the way you want. >> So, what kind of tooling is exciting you right now? What are you seeing out there, just, you know? >> So what excites me is, in addition to our own product, which is in a family of products that I would say is automated inspection. Right, and so gone are the days of late life cycle, you know, heavy lift, manual inspections and here today, now we have an ability to inspect continuously, early in the process, you know, in that CI pipeline where things are happening ten times a day. We can get that feedback to those delivery teams when it's most timely. And then so you combine that with containerization, at least in the regular application space, which gives us a converge supply change. So now my OS, my midware, everything is flowing through that pipeline, as opposed to when I was doing it. I was taking the application and ultimately deploying it to a statically provision environment. No two of which of those environments ever look quite the same. Now with containers, that problem, sort of, goes away and we have all this inspection tooling that helps us build quality in and not try to inspect it in later. >> Exactly and just, one of the things I'm looking at when I look at supply chain, the question comes to mind around Blockchain. And are you looking at Blockchain as something you might integrate into your solutions at some point in time? >> I'm personally not looking at it yet but it's hard to imagine that I won't be looking at it soon, because I can't read three articles, and one of them not be about Blockchain these days. It seems to hold a lot of promise in terms of providence and you know, basically, chain of custody type things, which are also important to this whole supply chain issue. So yeah I think it has a future. I think I've got a few things on my plate I need to get off first and then I'll have to start looking at Blockchain. >> That's great. Now, is there anything that was really wowing you from the show? I mean we've got, there's Meraki here, they're giving away something like 1.2 million dollars of equipment. You know, were you surprised to see anything or really, you know, outside of just IOT, what're you really seeing pop? >> Yeah, like I said, this is a bit of a new venue for me. I've been attending DevOps days and DevOps enterprise summit and local meetups and I've been really narrowly focused in that space in this last year. So now I'm getting more into the cloud and this is my first IOT based event. It's great to see Cisco in their second year, having such a successful event. It's really grown a lot. It's in a terrific venue. But in terms of wowing me, I think it's just access for me personally to the folks in the IOT communities, so that I can start to wrap my head around it and share our story with them, which I think is a raised some eyebrows and got some interest to think about supply chain issues in that context. >> Well I think it's absolutely necessary that you actually enable the software across the enterprise. I know that my experience in many enterprise organizations would've been a lot easier if I had had your software and the ability to do that. >> Curtis: Yeah. >> You know, I think that's great. So, you know, one of my other questions is are you partnering with DevNet? Is there a relationship there or is this just educational for you? >> No we definitely, we have a relationship with Cisco and we like to support events like this. It helps us get out. It helps us build these types of relationships. Yeah, I mean, I think this is a emerging relationship between Cisco and Sonatype and obviously IOT has such a big future. There's a lot of potential there for both parties I think. >> That's awesome. Well thank you so much for being here. Thank you so much for sharing everything that you did. And we will be right back from Cisco DevNet.

(upbeat music) >> Live from Las Vegas, it's theCUBE. Covering Fortinet Accelerate 18. Brought to you by Fortinet. >> Welcome back to theCUBEs continuing coverage of Fortinet Accelerate 2018. I'm Lisa Martin here in Las Vegas with my co-host Peter Burris and we're excited to welcome a Cuba alumni back to theCUBE, please welcome Eric Kohl, the VP of Advanced Solutions from Ingram Micro. Welcome back! >> Thank you, thanks for having me back. Excited to be here. >> Yes, we're very excited. So tell us, what's new? We talked to you last year at this event, what's new and Ingram? Tell us about your role there and the things that are all exciting Ingram Micro. >> Yeah, brand-new for me. I'm in my 20th year at Ingram Micro. I lead our security practice for Ingram Micro U.S. and I have responsibility for sales, vendor management, strategy and execution on behalf of our manufacturer partners. It's a ever evolving space. It's such a great space to be in, I love watching the news every day. You know there's going to be some big logo but just as much fun as I have watching those, that's some of these small breaches that you don't hear about and it's just fascinating. So much more exciting than virtualization. (laughs) >> Some might argue with that. So tell us about the partnership that you guys have with Fortinet. How has that evolved over your time there? >> Yeah so been at Ingram for 10 and I've been working with Fortinet for, I'm sorry I've been at Ingram for 20 and been with Fortinet for over 10, back to when we signed the contract together. Just a very great partnership. They're our security partner of the year, last year. Good friends, excited to see John Bove back leading channels back to Fortinet and you know, we both invest in each other's success and so I think that's pretty unique. Huge investment for them here, having an event like this. Not every company does it but to bring everybody together where you can have security conversations get on the same page, it's extremely valuable, huge investment, and we're proud to be a sponsor. >> I'd love to chat about a little bit of the evolution that you've seen at Fortinet in the last 10 years as we look at, you mentioned breaches. I mean, there were some very notable things that happened in 2017. How have you seen the evolution from them on a security transformation standpoint as it relates to your customers and digital transformation. >> Yeah, so I mean it's something that we see every day from you know, as you know we sell to and through partners but you know, one thing obviously is their breath of solutions has expanded. But you know, also things that partners are asking us today is how is this technology being consumed? And in the face of digital transformation, that's a huge value point because ultimately we want to help our partners to architect, recommend the right technology to solve that business problem and then how do you want to consume it? How does your want to your client want to consume that? So I think that's one of the biggest kind of trends that we're seeing right now. >> So as you think about where you've come from to where you are and we'll talk a little bit about where you think might go, what were the stories you told about security 10 years ago? And how are they different from the stories you're telling about security today? >> I would say it's changed from my perspective because at Ingram, we have never ever been a services company like we are today. And so what I mean by that is, we wrap our services, partner services around the Fortinet solution to make it stronger. 10 years ago I would say we are living more in the traditional distribution role of hey, how do we get a box from here to there? Certainly channel enablement, we've been doing that for a long time but our offering of services to help drive demand is incredibly strong. You know, we work with Fortinet for example, on their threat assessment program and we have an engineer that can go and help. Our partners understand to do that, it's a huge partner ecosystem and so we've got to help them with all those channel enablement efforts. >> What are some of the biggest security challenges that you're hearing, say in the last year or so through the channel, that your partnership with Fortinet can help address? >> You know, it's all around complexity and that as you have likely heard that the shortage of folks that can get out and do some of these services have limitations. There's incredibly high demand for services, you know we're serving a channel ecosystem of roughly 12,000 companies that are buying security technology from us, all with varying degrees of capability and so we've really got to help them understand, hey, how can we help you deploy these services, etc. >> So as you imagine then the steps associated with helping the customer, the roles and relationships between Fortinet, Ingram, and your partners also must be evolving. So how is, as a person responsible for ensuring that that stays bound together in a coherent way for customers, how are you seeing that changing? >> Well you know, look it's a three-legged stool. (laughs) It's us, it's Fortinet and that's our partner community and we're reliant on each other to go and be successful in the market. Look, we couldn't be as great as we are working with our Fortinet channel ecosystem if we didn't have the support of Fortinet, the investments they make, the team that they have wrapped around our business, the team we've put in place wrapped around their business so that's kind of what I'm seeing there. >> They shared a lot of momentum not only in the keynotes this morning but also a number of the guests that we've had on the show today in terms of what Fortinet achieved last year. 1.8 billion in billing, nearly 18 thousand new customers acquired, a lot of momentum, a lot of numbers, I love that theme of the event today. So if we look at some of the things that were shared by Kenzie this morning for example, like I mentioned that the customer numbers and even talking about what they're doing to protect 90% of customers in the global S&P 100 and showed some some big brands there. Tell us a little bit about the partnership and how you're leveraging the momentum of what Fortinet is able to do in terms of capturing customers. How does that momentum translate and really kind of maybe fuel Ingram and what you're able to do? >> Well look, I mean there's incredible demand in security today. There was a slide that they showed this morning and I think it was the perfect storm. I like to call the security space a beautiful disaster. It's a mess, it's complicated, it's scary, the threat attacks are you know new and different and they're never going to stop but it again comes back to hey, how do we work together to kind of harness this? How do we go and there's a great partner community here, lots of our friends are here but they can't all be here. So we want to be able to help take that message out to our channel partners that were not here. Things like that. >> What are some of, oh sorry, go ahead Peter. >> I was going to say so Ingram, Ingram itself has changed. You said you've now, are now introducing security or you're introducing more services. So how is that.. How is security leading that charge to move from a more of a product and a distributor to now services? Is security one of the reasons why Ingram is going in that direction? >> It's one of them. I joked on virtualization but there's a lot of services that we can wrap around and I think, obviously there's a high demand of services and we will lead with Fortinet services and solutions where we can. We want our partners to lead with theirs but really we've hired people to go out do assessments. We have a partner ecosystem where, hey I can't get down to New Mexico to do an install. We have a partner network where they can tap into that and make sure that everything is installed correctly, all the features are turned on. You think about all these breaches that happen in the news, it's not that they didn't have the technology, they missed an alert or they didn't have it all deployed. We want to be able to help our partners solve for that. >> Along the partnership front, what are some of the things that excite you about the Fabric-Ready Partner Program and the announcements they've made today? >> Yeah, love it. Look Fortinet has built comprehensive end-to-end solutions within their Fortinet, I'm sorry, for their Fabric ecosystem but they've also recognized that they can't do it all alone and so they've introduced a lot of partners into that. And so what's exciting for me, leading our security category is, hey how do we bring new partners into our ecosystem too? Because it is a differentiator for Ingram to be able to provide multi-vendor solutions. To have somebody you can go to to say, how does SentinelOne work with for Fortinet Fabric? Those types of things, those conversations are happening all the time. >> Another thing that was announced today was what they're doing with with AI. Tell us a little bit about that and how are you seeing what they're going to be able to do with AI as an advantage for your partners and customers. >> Again the artificial intelligence, machine learning, it all goes back to making the technology easier to use. I still think, you think intelligence and I think back to the human factor. Some of these big breaches, look the threat actors are going to get in but how you recover from a breach, I think if we could inject some artificial intelligence into some of these companies that haven't figured out how to successfully pivot. You know paying your hacker a hundred thousand dollars to keep quiet is not the answer but I think that some of these machine learning things are going to make it easier. It's going to be easier to manage the alerts that are happening every day. So anything that helps eliminate, as they said today, the enemy of security is complexity. Things that help to discover these threats and remediate against them, all good stuff for our partners. >> On the enablement side, when we were talking with the channel chief, John Bove, earlier today and talking about sort of this long history of partner focused culture at Fortinet. Tell us about that in terms of the enablement that you're able to glean from them and then pass on to your channels in terms of selling strategies, marketing to, marketing through. What are some of the things that-- >> Look, we have an amazing team. John Bove, Curt Stratton, the folks that really spent so much time working with Ingram and then we've built an amazing team. I think we have 12 people from our company here at this event to make sure we're making the most out of it but you know. If you heard, we're at The Cosmo. They have Secret Pizza, have you been there? Have you heard about it? >> Lisa: No, Secret Pizza? >> Yeah, it's amazing, it's pretty good, okay. (laughs) >> You didn't bring any, I noticed that but continue. >> I didn't but it's secret not-so-secret pizza but we have some secret not so secret weapons. Jenna Tombolesi an NSE 7. She's one of the highest certified engineers on the planet and she works for Ingram Micro helping to technically enable some of our partners. We've got a guy by the name of Will The Thrill Sharland and The Thrill is out talking to partners every single day, helping them to be more profitable, trusted security advisors helping them through anything you can imagine from a channel enablement perspective. And then just huge teams of people that we go to serve this big market together. >> Are you seeing any vertical specificities? When Ken was sharing some slides this morning, they were talking about, they showed some verticals from a kind of market share perspective but I'm curious some of the verticals that kind of come to mind where security is concerned that maybe are a little bit more elevated than some of the others in terms of risk or health care education and financial services. Maybe Fed, SLED, are you seeing any verticals in particular, maybe those that are really going to be kind of having to be leading-edge, where security transformation is concerned? >> They have to be. Think about health care and when they're big ransomware attack hit last year. There's guys on CNN saying, they had to postpone my surgery because ransomware head. I mean that's life-and-death stuff there but I don't think there's any vertical that's immune to what's going on today. So I think you know regardless of your vertical, you have to be prepared, you have to choose the right technology, and choose the right partner to help you implement it. >> If you imagine where Ingram's going to go with this relationship, what kinds of things are you looking to be able to do as a consequence of great strong partnership with Fortinet. >> Look, the way that companies want to consume technology is changing in the space of digital transformation. Once we work with Fortinet and the partner to recommend the right technology and I mentioned this, like how do you want to consume it? Is it public cloud, is it AWS, or Azure? We have an answer for that today is that hey, it's on premise but I need some creative financing to help close this deal to solve a budget constraint. We have an answer for that. There's several variations of that but however that technology wants to be consumed, we have an answer together. So I think that's a testament to the strength of our relationship. >> And I think one of the words that I saw in, at least one of the press releases, was adaptability. Adaptability of some of the technologies and even John Madison was kind of talking about how customers can go, I've got 20-plus security products, how do I start this Fabric? And that word adaptability kind of jumped out at me as how do you enable adaptability when your customers, through the channel, have so many technologies in place and how does Fortinet help that adaptation? >> I would say they're placing bets like we are on top partners that are going to lead with that technology. They've got to go be the experts in that field and really start driving that. Events like this help get everybody on the same page, understand the new offerings. I mentioned Jenna, she was locked in a room all day yesterday all excited about all these things. She's been running around all day but look we've just got to help the channel understand what the new technologies are, what are the new offerings, and hey, how do we go solve that customer problem together. >> So are there any particular new approaches or tactics or techniques that you're using to get the channels to understand better? >> I don't think that there's anything necessarily new. We're all driving towards the same common goal. Having a security conversation today is easier than ever before so you know, I think we're we're going to continue doing what we've been doing. It's been very successful for us but that's, you know. >> What are some of the things, kind of wrapping up here, that you're looking forward to throughout the rest of 2018? We're kind of still in the first quarter calendar, some big announcements from your partner here today. What are some of the things that excite you at Ingram about the year of 2018? >> Look, it's a market that's that's really ripe right now and I think that when you talk about their new technologies, when you talk about the machine learning, there's a lot of these things happening out there. It's just look, we've got a huge market. The potential is unlimited and I think one area where we're really going to drill down this year is down market, down SMB in mid market because they need enterprise grade technology and Fortinet delivers that and has a history of delivering that. So I think we're going to double click down there together this year and John and his team have been great around putting some programs together for us to go and tackle that together. >> Excellent, well we thank you so much Eric for stopping by theCUBE again. >> Yes and I'll bring pizza next time. >> Please do. >> All right. >> Yes and maybe some beverages so we don't have dry throats. >> Of course, yes. >> So we wish you and Ingram the best of luck in this next year and we look forward to talking to you next year, if not sooner. >> Sounds good. Great, thank you. >> We want to thank you for watching theCUBE's continuing coverage of Fortinet Accelerate 2018. For Peter Burris, I'm Lisa Martin, after the short break we'll be right back. (upbeat music)

>> Announcer: Live from New York City. It's theCUBE. Covering Lenovo Transform 2017. Brought to you by Lenovo. >> Welcome back to theCUBE's coverage of Lenovo Transform. I'm your host Rebecca Knight, along with my co-host Stu Miniman. We are joined by Kamran Amini. He is the General Manager, Server and Storage Business Unit, here at Lenovo. Thanks so much. >> Thank you for having me. >> Welcome back to theCUBE, I should say. (Kamran laughs) >> Thank you. >> So today we've heard a lot about the largest product portfolio data storage product portfolio launch in Lenovo history. >> Kamran: Umhmm. Can you put this in perspective for us, though, in terms of the customer and why is this meaningful for the customer? >> Absolutely, so one of the key things with the entire Think System Portfolio, we started three years ago. A clean sheet and really listening to our clients, listening to our channel partner. What are their challenges with IT? Outside of wanting performance and everything else? How can we simplify their experience, from the buying experience, to life cycle management of the products, simplify part purchases. So a couple of things we did was common building blocks. So, the majority of the Think System Server Portfolio have common power supplies that go across. One of the things customer asked us was you have too many power supplies, right? I'm buying a part, I have to decide which server you have, and what form factor goes in. Now, we have one common across the board. Same thing with management software, we provide one look, and one feel experience for our clients. The whole philosophy of our Think System was start clean, deliver what customers are really valuing around IT and be able to help accelerate and future-proof the technology for them. As they're evolving their workloads and applications, as they're moving to Flash technologies, how do we provide that flexibility? And that's really the foundation of the Think System. >> Yeah, so, Kamran, there was discussion in the keynote this morning, it's about harnessing the intelligence revolution and AI. Can you connect the dots for us as to how that fits into servers, and specifically this launch the new Skylake Chipset? >> Absolutely, so, of course with the new scalable xenon processor, you're getting tremendous increase in performance. And I think when you look at AI and machine learning, there's the aspect that requires acceleration applications, and there's still computing happening on the CPU aspect of the AI machine learning. And you're seeing more the analytics and big data coming into this play. So that's really where we're leveraging the foundational excellence we have with our analytic platforms, and also looking at big data. And bring in with the accelerator's platforms to drive that end to end view around artificial intelligence. And that's where the Think System Portfolio is really shining. It's bringing that end to end view from a client perspective for all their purpose to drive the AI platform environments. >> One of the things we keep hearing about is Lenovo being number one in customer satisfaction, number one in reliability. Can you talk about how you make that happen? How do you ensure that you are as reliable as you come to be known to be? >> Yeah, so one of the things with Lenovo is we listen. If you're not listening to your clients and understand where they're going, what their challenges are, it's hard to be able to adapt. And one of the things you'll see from a reliability perspective, we believe even as you think about the future of software defined, that foundational server is going to be, it has to be reliable. You're getting away from the legacy thinking of redundancy of infrastructure to running everything on a server base. So now that server has to truly deliver five nines. So, we design stuff. A lot of people think x86 is a commodity space. My background is engineering, and I think you can do different styles of engineering. And our engineer team is a great team that thinks about how do we take the Intel processor technology, build a platform around it to be able to have the highest reliability? And, of course, with the highest reliability, it also leads to customers basically having gooder customer engagement, customer satisfaction. So they sort of go hand in hand, right? And that's where we try to continue drive innovation. As you heard from Curt in the main tent, our purpose is not to let go of that, but figure out how we can continuously drive improvement in our reliability. Ideally, I like to have six nines if I can in the server one day. But that's the foundation from an engineering aspect, and innovation that's leading into the actual platforms and offerings for our clients. >> Kamran, can you bring us inside what your customers are asking for? You talked about massive amounts of data, there's so many choices out there, I hear. You look in the AI space, it's like, oh, there's the public cloud with their GPUs and TPUs, versus moving to more distributed architectures internally. What kind of feedback are you getting from your customers, and what are they excited about that they can do this year that they couldn't do next? >> So I think a lot of >> Stu: Last. >> customers will love to have purpose-driven platforms. And I think, if you look at the market today, there's plenty of servers out there by a variety of different vendors. The challenge for customers is some customers are very price performance sensitive. And you know, sometimes they get siloed into I have to buy the expensive thing, even though my application might not require Flash, might not require GPUs. So if you look at the Think System Portfolio, we really focused on the segments of clients. All the way from SMB to large enterprises. And how are they actually using it? What's their purchasing philosophy? And build the platforms that accommodate that segment, plus the capabilities inside those platforms. So you'll see, for example, our mainstream two socket server where it has full capability with GPU, NVMe capabilities, future Intel technology built-in, versus we have our value line really focused around customers that are looking for really SMB environment. Give me that price performance that fits my budget friendly environment. And then you also see places like dense optimized platforms, really driving innovation around our HPC but also being leveraged around hyper-converg platforms and general purpose consolidations. And finally, we do believe that the big data analytics platforms are going to be mainstream one day. They're sitting in your backend of your center running your mission critical but they're becoming more and more relevant today. As you see AI happening. More and more stuff is going to go on those backend system to drive the analytics. And that's where we believe we're positioned very well in the portfolio we're delivering across the 14 servers. >> So what will it take for big data to really become an important part of they way companies do business. There is a deluge of data right now. And we're still trying to figure out how to, what to do with it, how to slice it and dice it. And how to, how to make improvements based on it. What will it take do you think? >> I think you're seeing a lot of ISP that we're doing traditionally. Traditional analytics are bring big data into the analytics. So that's their first movement, that the ISPs are merging those two environments together. The next thing is for people like Lenovo be able to deliver the infrastructure platform that actually can leverage that environment. Big data requires a lot of storage. And you'll see in our next gen analytics system, we almost quadruple the amount of storage you have in that platform because we know more and more is going to go from a storage perspective, and analytic and memory database environment. So it's really looking how the ISPs are looking in this challenge and building the right platform that actually leverage those those ISP solutions. >> Kamran, I loved how you were talking about some of the applications because when I talk to customers, it's that spectrum of application they have that they're struggling. Everything from building new microservices-based architecture to I've got my ERP solution, sitting back there. How do you help customers with that portfolio to modernize their infrastructure, optimize what they're doing and stay agile. >> Well, part of that is actually our service organization. It's really sitting and listening to understanding where the customer wants to go. Sometimes I think a lot of companies approach customers by saying here's what I have and try and force feed that offering into the customer environment. We actually are leveraging our professional service and consulting services to get a better idea. What does the customer want to do today but moving into tomorrow. And what platform or solutions will actually benefit the client from server storage or networking or even our engineers solutions that we have at Lenovo. >> When you're thinking about, when you're hearing the customer feedback, and trying to anticipate what the customer needs tomorrow, is there any area that worries you in particular that the customer may be have have a blind spot for? It could be about data storage or it could be about internet of things or cloud computing. What keeps you up at night? >> I think a lot of it is, to be personal, is around cloud. I think cloud initially provides a value prop around, for public cloud economics. But I think what we're seeing is a lot of customers have that philosophy of clouds but I think as they start looking into the actual deployment and how you manage that environment, the economics evolves. So what keeps me awake is, making sure that clients understand our story. Understand what Lenovo can bring into the table both for what their traditional IT needs, but also their next gen IT. Plus have establish for them a private cloud environment and tie into hybrid environment as well. We want to make sure our clients understand and drive the best value. One of things I always tell my clients is, look, if I could sell you one less server, but you're getting more benefit, I'm here to consult you in that way. I want to make sure the result that you see is what we want to achieve. And that's what we're focused on. And to me, that's what keeps me up is making sure our clients understand the journey as they want to go to cloud and what's the right path for them. >> Kamran, it's been about three years since Lenovo acquired the x86 business. Give us, as you look back, what surprised you in those three years. The keynote this morning, Y Y said, we wouldn't be able to think 18 months ago where we are today. So, what's changed the most, what surprised you the most about the journey with x86? >> So I did come from system X as part of the acquisition. And to be very frank, I think one of things that was stated in the keynote today was, the agility that Lenovo acts on. It's okay to make a mistake. As long as you quickly react and fix the mistake. And I think what I've noticed in the three years I've been here Lenovo now is, one, the culture is very flat. Everyone is empowered to make a decision. There's no hierarchical decision making. Of course, there's always the president. There's always the CEO. But people are empowered to make decisions that's beneficial for our clients. And we're seeing a huge focus around customer experience. It's not just a organizationally, it's not just a individual KPIs. It's really looking from end to end of our business. How can we transform our customer experience? To drive a better experience for our customers. And I think that's, with Lenovo being that agile of a company. I had great service years at, 17 years at IBM, very successful. But because of the size of the company and the different structures of the company, a lot of clients didn't feel we could adjust their needs immediately. And I think with Lenovo you're seeing a lot more faster agility. From our supply chain to how customers get quotes. From a product perspective and support. Those are all the things that I see slightly different, and we've been transforming as we've been going. Enhancing those capabilities. And we've learned through our mistakes through the last three years. It hasn't been any mistakes that we haven't came out with. But we constantly learn and try enhance as we go forward. And I'm very excited going into this year. Especially with these announcements that we're going to be driving a lot more enhancements and how our customers see Lenovo as a data center provider. >> A lot have been made about the fact that this is, Thinkpad and x86 25th year anniversary. Which seems amazing, really. >> Mmhmm. >> Now that these products are in their sort of adulthood so to speak, what do you think we should expect in terms performance and in terms of approach. Just because they are now, they've fully worked out the kinks of the youth and their adolescence. >> Yeah so if you look at, for example, in the server business, and the server portfolio Think System, from just gen to gen, literally, this is three years ago, two three years ago. You're going to see customers be able to run 150% more VDI, users. And that drives a better economics, dollar per user. So just from a gen to gen you're seeing tremendous platform improvements. And that's where I think, we're going to see customers. Customer, I think are going to see driving more and faster applications. I think we're going to see huge adoption of Flash within the server technology. And therefore, I think you're going to see where software define and server generation we're delivering come together very nicely. Where we believe that, my personal belief, you're going to see a lot more customers moving away from a traditional storage array to now software defined or all Flash software define environments. Where they're leveraging a commodity server base with huge amount of performance capabilities and software on top to deliver the business value. >> Kamran, where do you think we're going to be, next year but then also 10 years down the road. As you talk about the pace of business, change is incredible aren't they now. Can you predict a little bit into the future? (Kamran laughs) >> About what we're going to, I know it's a tough one. >> Kamran: I wish I could predict. I think you're going to see a lot of different applications coming together. I think you're going to see AI being a key factor to drive and generate a lot of information with machine learning. And being able to take that information and figure out how you drive business agility. I think you're going to see retail driving AI aggressively. I think you're already seeing automotive industry driving machine learning and everything else into their cars. So for us, it's very exciting as an IT provider. Were we see an evolution happening and eventually another revolution happening in IT, I think in the next 10, 15 years. You're going to see I think more dense platforms because you're going to drive more density with the nut form factor. I think you're going to see a lot more powerful systems. And I think you're going to see software becoming more relevant. And I think that the legacy status goal is going to eventually be gone I think. I think legacy, 10 years from now, legacy is going to be considered software defined I believe. >> Great. Bold predictions. (Rebecca laughs) >> Predictions. (Kamran laughs) >> Well, Kamran Amini, thank you so much for joining us. It's always a pleasure having you on the show. >> Kamran: Thank you for having me. >> I'm Rebecca Knight for Stu Miniman. We will have more from theCUBE at Lenovo Transform just after this. (upbeat music)

>> Announcer: Live from Boston, Massachusetts, it's theCUBE, covering Spark Summit East 2017. Brought to you by Databricks. Now, here are your hosts Dave Vellante and George Gilbert. >> Welcome back to snowy Boston, everybody. This is theCUBE, the leader in live tech coverage. We're here at Spark Summit East, hashtag SparkSummit. Manish Gupta is here, he's the CMO at Redis Labs. Manish, welcome to theCUBE. >> Thank you, good to be here. >> So, you know, 10 years ago you say you're in the database business and everybody would yawn. Now you're the life of the party. >> Yeah, the world has changed. I think the party has lots and lots of players. We are happy to be on the top of that heap. >> It is a crowded space, so how does Redis Labs differentiate? >> Redis Labs is the company behind the massively popular open source Redis, and Redis became popular because of its performance primarily, and then simplicity. Developers could very easily run up an instance of Redis, solve some very hairy problems, and time to market was a big issue for them. Redis Enterprise took that forward and enabled it to be mission critical, ready for the largest workloads, ready for things that the enterprises need in a highly distributed clustered environment. So they have resilience and they benefit from the performance of Redis. >> And your claim to fame, as you say, is that top-gun performance, you guys will talk about some of the benchmarks later. We're talking about use cases like fraud detection, as example. Obviously ad serving would be another one. But add some color to that if you would. >> Redis is whatever you need to make real time real, Redis plays a very important role. It is able to deliver millions of operations per second with sub-millisecond latency, and that's the hallmark. With data structures that comprise Redis, you can solve the problems in a way, and the reason you can get that performance is because the data structures take some very complex issues and simplify the operation. Depending on the use case, you could use one of the data structures, you can mix and match the data structures, so that's the power of a Redis. We're used for ITO, for machine learning, for metering of billing and telecommunications environment, for personalization, for ad serving with companies like Groupon and others, and the list goes on and on. >> Yeah, you've got a big list on your website of all your customers, so you can check that out. Let's get the business model piece out of the way. Everybody's always fascinated. Okay, you got open source, how do you make money? How does Redis make money? >> Yeah, you know, we believe strategically fostering the growth of open source is foundational in our business model, and we invest heavily both R&D and marketing to do that. On top of that, to enable enterprise success and deployment of Redis, we have the mission critical, highly available Redis Enterprise offerings. Our monetization is entirely based on the Redis Enterprise platform, which takes advantage of the data structures and performance of core Redis, but layers on top management and the capabilities that make things like auto-recovery, auto-sorting, management much, much easier for the enterprise. We make that available in four deployment models. The enterprise can select us as Redis cloud, which runs on a public infrastructure on any of the four major platforms. We also allow for the enterprise to select a VPC environment in their own private clouds. They can also get software and self-manage that, or get our software and we can manage it for them. Four deployment options are the modalities in other ways where the enterprise customers help us monetize. >> When you said four major platforms, you meant cloud platforms? >> That's right. AWS, >> So, AWS, Azure >> Azure, Google, and IBM. >> Is IBM software, got there in the fourth, alright. >> That's right, all four. >> Go to the whip IBM. Go ahead, George. >> Along the lines of the business model, and we were sort of starting to talk about this earlier offline, you're just one component in building an application, and there's always this challenge of, well, I can manage my component better than anyone else, but it's got to fit with a bunch of other vendors' components. How do you make that seamless to the customer so that it's not defaulting over to a cloud vendor who has to build all the components themselves to make it work together? >> Certainly, you know, database is an integral part of your stack, of your application stack, but it is a stack, so there are other components. Redis and Redis Labs has a very, very large ecosystem within which we operate. We work closely with others for interfaces, for connectors, for interoperability, and that's a sustained environment that we invest in on a continuous basis. >> How do handle application consistency? A lot of in the no-SQL world, even in the AWS world, you hear about eventual consistency, but in the real-time world, there's a need for more rigorous, what's your philosophy there, how do you approach that? >> I think that's an issue that many no-SQL vendors have not been able to crack. Redis Labs has been at the forefront of that. We are taking an approach, and we are offering what we call tuneable consistency. Depending on the economics and the business model and the use case, the needs of consistency vary. In some cases, you do need immediate consistency. In other cases, you don't ever need consistency. And to give that flexibility to the customer is very important, so we've taken the approach where you can go from loose consistency to what we call strong eventual consistency. That approach is based on a fairly well trusted architecture and approach called CRDT, Conflict-free Replication Data Type. That approach allows us to, regardless of what the cluster magnitude or the distribution looks like geographically, we can deliver strong eventual consistency which meets the needs of majority of the customers. >> What are you seeing in terms of, you know, also in that a discussion about acid properties, and how many workloads really need acid properties. What are seeing now as you get more cloud native workloads and more no-SQL oriented workloads in terms of the requirement for those acid properties? >> First of all, we truly believe and agree that not all environments required acid support. Having said that, to be a truly credible database, you must support acid, and we do. Redis is acid-compli, supports acid, and Redis Labs certainly supports that. >> I remember on a stage once with Curt Monash, I'm sure you know Curt, right? Very famous database person. And he basically had a similar answer. But you would say that increasingly there are workloads that, the growth workloads don't necessarily require that, is that fair statement? >> That's a fair statement I would say. >> Dave: Great, good. >> There's a trade-off, though, when you talked about strong eventual consistency, potentially you have to wait for, presumably, a quorum of the partitions, I'm getting really technical here, but in other words, you've got a copy of the data here-- >> Dave: Good CMO question. (laughing) >> But your value proposition to the customers, we get this stuff done fast, but if you have to wait for a couple other servers to make sure that they've got the update, that can slow things way down. How does that trade-off work? >> I think that's part of the power of our architecture. We have a nothing shared, single proxy architecture where all of the replication, the disaster recovery, and the consistency management of the back end is handled by the proxy, and we ensure that the performance is not degraded when you are working through the consistency challenges, and that's where significant amount of IP is in the development of that proxy. >> I'll take that as a, let's go into it even more offline. >> Manish: Sounds good. >> And I have some other CMO questions, if I may. A lot of young companies like yours, especially in open source world, when they go to get the word out, they rely on their community, their open source community, and that's the core, and that makes a lot of sense, it's their peeps. As you become, grow more into enterprise grade apps and workloads, how do you extend beyond that? What is Redis Labs doing to sort of reach that C-Suite, are you even trying to reach that C-Suite up level to messaging? How do you as a CMO deal with those challenges? >> Maybe I'll begin by talking about our personas that matter to us in the ecosystem. The enterprise level, the architects, the developers, are the primary target, which we try to influence in early part of the decision cycle, it's at the architectural level. The ultimate teams that manage, run, and operate the infrastructure is certainly the DevOps, or the operations teams, and we spend time there. All along for some of the enterprise engagements, CIOs, chief data officers, and CTOs tend to play a very important role in the decisions and the selection process, and so, we do influence and interact with the C-Suite quite heavily. What the power of the open source gives us is that groundswell of love for Redis. Literally you can walk around a developer environment, such as the Spark Summit here, and you'll find people wearing Redis Geek shirts. And we get emails from Kazakhstan and strange, places from all over the world where we don't necessarily have salesforce, and requesting t-shirts, "send us stickers." Because people love Redis, and the word of mouth, that ground level love for the technology enables the decisions to be so much easier and smoother. We're not convincing, it's not a philosophical battle anymore. It's simply about the use case and the solution where Redis Enterprise fits or doesn't fit. >> Okay, so it really is that core developer community that are your advocates, and they're able to internally sell to the C-Suite. A lot of times the C-Suite, not the CTO so much, but certainly the CIO, CDO are like, "Yeah, yeah, they're geekin' out on some new hot thing. "What's the business impact?" Do you get that question a lot, and how do address it? >> I think then you get to some of the very basic tools, ROI calculators and the value proposition. For the C-level, the message is very simple. We are the least risky bet. We are the best long-term proposition, and we are the best cost answer for their implementation. Particularly as the needs are increasingly becoming more real-time in nature, they are not batch processed. Yes, there will always be some of that, but as the workloads are becoming, there is a need for faster processing, there is a need for quick insights, and real-time is not a moniker anymore, right. Real-time truly needs to be delivered today. And so, I think those three propositions for the C-Suite are resonating very well. >> Let's talk about ROI calculators for a second. I love talking about it because it underscores what a company feels as though its core value proposition is. I would think with Redis Labs part of the value proposition is you are enabling new types of workloads and new types of, whether it's sources of revenue or productivity. And these are generally telephone numbers as compared to some of the cost savings head to head to your competition, which of course you want to stress as well because the CFO cares about the cap-backs. What do you emphasize in that, and we don't have to get into the calculator itself, but in the conceptual model, what's the emphasis? Is it on those sort of business value attributes, is it on the sort of cost-savings? How do you translate performance into that business value? A lot of questions there, but if you could summarize, that'd be great. >> Well, I think you can think of it in three dimensions. The very first one is, does the performance support the use case or the solution that is required? That's the very first one. The second piece that fits in it, and that's in our books, that's operations per second and the latency. The second piece is the cost side, and that has two components to it. The first component is, what are the compute requirements? So, what is the infrastructure underneath that has to support it? And the efficiency that Redis and Redis Enterprise has is dramatically superior to the alternatives. And so, the economics show up. To run a million operations per second, we can do that on two nodes as opposed to alternative, which might need 50 nodes or 300 nodes. >> You can utilize your assets on the floor much better than maybe the competition can. >> This is where the data structures come into play quite a bit. That's one part of-- >> Dave: That's one part of the cost. >> Yeah. The other part of the cost is the human cost. >> Dave: People, yeah. >> And because, and this goes back to the open source, because the people available with the talent and the competency and appreciation for Redis, it's easy to procure those people, and your cost of acquisition and deploying goes down quite a bit. So, there's a human cost to it. The third dimension to this whole equation is time to market. And time to market is measured in many ways. Is it lost revenue if it takes you longer to get there? And Redis consistently from multiple analysts' reports gets top ranking for fastest way to get to market because of how simple it is. Beyond performance, simplicity is a second hallmark. >> That's a benefit acceleration, and you can quantify that. >> Absolutely, absolutely. And that's a revenue parameter, right. >> For years, people have been saying this Cambrian explosion of databases is unsustainable, and sort of in response we've gotten a squaring of the Cambrian explosion. The question is, with your sort of very flexible, I don't want to get too geeky, 'cause Dave'll cut me off, but the idea that you can accommodate time series and all these different ways of, all these different types of data, are we approaching a situation where customers can start consolidating their database choices and have fewer vendors, fewer products in their landscape? >> I think not only are we getting there, but we must get there. You've got over 300 databases in the marketplace, and imagine a CIO or an architect trying to have to sort through that to make a decision, it's difficult, and you certainly cannot support it from a trading standpoint or from an investment, cap-backs, and all that standpoint. What we have done with Redis is introduce something called Redis Modules. We released that at the last RedisConf in May in San Francisco. And the Redis Module is a very simple concept but a very powerful concept. It's an API which can be utilized to take an existing development effort, written as CC++, that can be ported onto the Redis data structures. This gives you the flexibility without having to reinvent the wheel every single time to take that investment, port it on top of Redis, and you get the performance, and you can make now Redis becomes a multi-model database. And I'm going to get to your answer of how do you address the multiple needs so you don't need multiple databases. To give you some examples, since the introduction of Redis Modules, we have now over 50 modules that have been published by a variety of places, not just Redis Labs. To indicate how simple and how powerful this model is. We took Lucene and developed the world's fastest full-text search engine as a module. We have very recently introduced Redis machine learning as a module that works with Spark ML and serves as a great serving layer in the machine learning domain. Just two very simple examples, but work that's being done ported over onto Redis data structures and now you have ability to do some very powerful things because of what Redis is. And this is the way future's going to be. I think every database is trying to offer multi-functionality to be multi-model in nature, but instead of doing it one step at a time, this approach gives us the ability to leverage the entire ecosystem. >> Your point being consolidation's inevitable in this business as well. >> Manish: Architectural consolidation. >> Yes, but also you would think, company consolidation, isn't that going to follow? What do you make of the market, and tell me, if you look back on the database market and what Oracle was able to achieve in the face of, maybe not as many players, but you had Sybase and Informix, and certainly DB2's still around, and SQL Server's still around, but Oracle won, and maybe it was SQL standards that. It's great to be lucky and good. Can we learn from that, or is this a whole different world? Are there similarities, and how do you, how do you see that consolidation potentially shaking out, if you agree that there will be consolidation? >> Yeah, there has to be, first and foremost, an architectural approach that solves the OPEX, CAPEX challenge for the enterprise. But beyond that, no industry can sustain the diversity and the fragmentation that exists in database world. I think there will always be new things coming out, of universities particularly. There's great innovation and research happening, and that is required to augment. But at the end of the day, the commercial enterprises cannot be of the fragmented volume that we have today in the database world, so there is going to be some consolidation, and it's not unnatural. I think it's natural, it's expected, time will tell what that looks like. We've seen some of our competitors acquire smaller companies to add graph functionality, to add search functionality. We just don't think that's the level of consolidation that really moves the needle for the industry. It's got to be at a higher level of consolidation. >> I don't want to, don't take this the wrong way, don't hate me for saying it, but is Oracle sort of the enemy, if I can say that. I mean, it's like, no, okay. >> Depends how you define enemy. >> I'm not going to go do many of the workloads that you're talking about on Oracle, despite what Larry tells me at Oracle OpenWorld. And I'm not going to make Oracle my choice for any of the workloads that you guys are working on. I guess in terms, I mean, everybody who's in the database business looks at that and say, "Hey, we can do it cheaper, better, "more productively," but, could you respond to that, and what do you make of Amazon's moves in the database world? Does that concern you? >> We think of Amazon and Oracle as two very different philosophies, if you can use that word. The approach we have taken is really a forward-looking approach and philosophy. We believe that the needs of the market need to be solved in new ways, and new ways should not be encumbered by old approaches. We're not trying to go and replicate what was done in the SQL world or in a relational database world. Our approach is how do you deliver a multi-model database that has the real-time attribute attached to it in a way that requires very limited computer force power and very few resources to manage? You take all of those things as kind of the core philosophy, which is a forward-looking philosophy. We are definitely not trying to replicate what an Oracle used to be. AWS I think is a very different animal. >> Dave: Interesting, though. >> They have defined the cloud, and I think play a very important role. We are a strong partner of theirs, much of our traffic runs on AWS infrastructure, certainly also on other clouds. I think AWS is one to watch in how they evolve. They have database offerings, including Redis offerings. However, we fully recognize, and the industry recognizes that that's not to the same capability as Redis Enterprise. It's open sourced Redis managed by AWS, and that's fine as a cache, but you cannot persist, and you really cannot have a multi-model capability that's a full database in that approach. >> And you're in the marketplace. >> Manish: We are in the marketplace. >> Obviously. >> And actually, we announced earlier, a few weeks ago, that you can buy and get Redis cloud access, which is Redis Enterprise cloud, on AWS through the integrated billing approach on their marketplace. You can have an AWS account and get our service, the true Redis Enterprise service. >> And as a software company, you'd figure, okay, the cloud infrastructures are service, we don't care what infrastructure it runs on. Whatever the customer wants, but you see AWS making these moves up-market, you got to obviously be paying attention to that. >> Manish: Certainly, certainly. >> Go ahead, last question. >> Interesting that you were saying that to solve this problem of proliferation of choice it has to be multi-model with speed and low resource requirement. If I were to interpret that from an old-style database perspective, it would be you're going to get, the multi-model is something you are addressing now, with the extensibility, but the speed means taking out that abstraction layer that was the query optimizer sort of and working almost at the storage layer, or having an option to do that. Would that be a fair way to say? >> No, I don't think that necessarily needs to be the case. For us, speed translates from the simplicity and the power of the data structures. Instead of having to serialize, deserialize before you process data in a Spark context, or instead of having to look for data that is perhaps not put in sorted sets for a use case that you might be doing, running a query on, if the data is already handled through one of the data structures, you now have a much faster query time, you now have the ability to reach the data in the right approach. And again, this is no-SQL, right, so it's a schema lesson write and it sets your scheme as you want it be on read. We marry that with the data structures, and that gives you the ultimate speed. >> We have to leave it there, but Manish, I'll give you the last word. Things we should be paying attention to for Redis Labs this year, events, announcements? >> I think the big thing I would leave the audience with is RedisConf 2017. It's May 31 to June 2 in San Francisco. We are expecting over 1,000 people. The brightest minds around Redis of the database world will be there, and anybody who is considering deploying the next generation database should attend. >> Dave: Where are you doing that? >> It's the Marriott Marquis in San Franciso. >> Great, is that on Howard Street, across from the--? >> It is right across from Moscone. >> Great, awesome location. People know it, easy to get to. Well, congratulations on the success. We'll be lookin' for outputs from that event, and hope to see you again on theCUBE. >> Thank you, enjoyed the conversation. >> Alright, good. Keep it right there, everybody, we'll be back with our next guest. This is theCUBE, we're live from Spark Summit East. Be right back. (upbeat electronic rock music)