>>It's the queue covering the virtual vertical Big Data Conference 2020. Brought to you by vertical. >>Hello, everybody. Welcome to the new Normal. You're watching the Cube, and it's remote coverage of the vertical big data event on digital or gone Virtual. My name is Dave Volante, and I'm here with Colin Mahoney, who's a senior vice president at Micro Focus and the GM of Vertical Colin. Well, strange times, but the show goes on. Great to see you again. >>Good to see you too, Dave. Yeah, strange times indeed. Obviously, Safety first of everyone that we made >>a >>decision to go Virtual. I think it was absolutely the right all made it in advance of how things have transpired, but we're making the best of it and appreciate your time here, going virtual with us. >>Well, Joe and we're super excited to be here. As you know, the Cube has been at every single BDC since its inception. It's a great event. You just you just presented the key note to your to your audience, You know, it was remote. You didn't have that that live vibe. And you have a lot of fans in the vertical community But could you feel the love? >>Yeah, you know, it's >>it's hard to >>feel the love virtually, but I'll tell you what. The silver lining in all this is the reach that we have for this event now is much broader than it would have been a Z you know, you know, we brought this event back. It's been a few years since we've done it. We're super excited to do it, obviously, you know, in Boston, where it was supposed to be on location, but there wouldn't have been as many people that could participate. So the silver lining in all of this is that I think there's there's a lot of love out there we're getting, too. I have a lot of participants who otherwise would not have been able to participate in this. Both live as well. It's a lot of these assets that we're gonna have available. So, um, you know, it's out there. We've got an amazing customers and of practitioners with vertical. We've got so many have been with us for a long time. We've of course, have a lot of new customers as well that we're welcoming, so it's exciting. >>Well, it's been a while. Since you've had the BDC event, a lot of transpired. You're now part of micro focus, but I know you and I know the vertical team you guys have have not stopped. You've kept the innovation going. We've been following the announcements, but but bridge the gap between the last time. You know, we had coverage of this event and where we are today. A lot has changed. >>Oh, yeah, a lot. A lot has changed. I mean, you know, it's it's the software industry, right? So nothing stays the same. We constantly have Teoh keep going. Probably the only thing that stays the same is the name Vertical. Um and, uh, you know, you're not spending 10 which is just a phenomenal released for us. So, you know, overall, the the organization continues to grow. The dedication and commitment to this great form of vertical continues every single release we do as you know, and this hasn't changed. It's always about performance and scale and adding a whole bunch of new capabilities on that front. But it's also about are our main road map and direction that we're going towards. And I think one of the things have been great about it is that we've stayed true that from day one we haven't tried to deviate too much and get into things that are barred to outside your box. But we've really done, I think, a great job of extending vertical into places where people need a lot of help. And with vertical 10 we know we're going to talk more about that. But we've done a lot of that. It's super exciting for our customers, and all of this, of course, is driven by our customers. But back to the big data conference. You know, everybody has been saying this for years. It was one of the best conferences we've been to just so really it's. It's developers giving tech talks, its customers giving talks. And we have more customers that wanted to give talks than we had slots to fill this year at the event, which is another benefit, a little bit of going virtually accommodate a little bit more about obviously still a tight schedule. But it really was an opportunity for our community to come together and talk about not just America, but how to deal with data, you know, we know the volumes are slowing down. We know the complexity isn't slowing down. The things that people want to do with AI and machine learning are moving forward in a rapid pace as well. There's a lot talk about and share, and that's really huge part of what we try to do with it. >>Well, let's get into some of that. Um, your customers are making bets. Micro focus is actually making a bet on one vertical. I wanna get your perspective on one of the waves that you're riding and where are you placing your bets? >>Yeah, No, it's great. So, you know, I think that one of the waves that we've been writing for a long time, obviously Vertical started out as a sequel platform for analytics as a sequel, database engine, relational engine. But we always knew that was just sort of takes that we wanted to do. People were going to trust us to put enormous amounts of data in our platform and what we owe everyone else's lots of analytics to take advantage of that data in the lots of tools and capabilities to shape that data to get into the right format. The operational reporting but also in this day and age for machine learning and from some pretty advanced regressions and other techniques of things. So a huge part of vertical 10 is just doubling down on that commitment to what we call in database machine learning and ai. Um, And to do that, you know, we know that we're not going to come up with the world's best algorithms. Nor is that our focus to do. Our advantage is we have this massively parallel platform to ingest store, manage and analyze the data. So we made some announcements about incorporating PM ML models into the product. We continue to deepen our python integration. Building off of a new open source project we started with uber has been a great customer and partner on This is one of our great talks here at the event. So you know, we're continuing to do that, and it turns out that when it comes to anything analytics machine learning, certainly so much of what you have to do is actually prepare the big shape the data get the data in the right format, apply the model, fit the model test a model operationalized model and is a great platform to do that. So that's a huge bet that were, um, continuing to ride on, taking advantage of and then some of the other things that we've just been seeing. You continue. I'll take object. Storage is an example on, I think Hadoop and what would you point through ultimately was a huge part of this, but there's just a massive disruption going on in the world around object storage. You know, we've made several bets on S three early we created America Yang mode, which separates computing story. And so for us that separation is not just about being able to take care of your take advantage of cloud economics as we do, or the economics of object storage. It's also about being able to truly isolate workloads and start to set the sort of platform to be able to do very autonomous things in the databases in the database could actually start self analysing without impacting many operational workloads, and so that continues with our partnership with pure storage. On premise, we just announced that we're supporting beyond Google Cloud now. In addition to Amazon, we supported on we've got a CFS now being supported by are you on mode. So we continue to ride on that mega trend as well. Just the clouds in general. Whether it's a public cloud, it's a private cloud on premise. Giving our customers the flexibility and choice to run wherever it makes sense for them is something that we are very committed to. From a flexibility standpoint. There's a lot of lock in products out there. There's a lot of cloud only products now more than ever. We're hearing our customers that they want that flexibility to be able to run anywhere. They want the ease of use and simplicity of native cloud experiences, which we're giving them as well. >>I want to stay in that architectural component for a minute. Talk about separating compute from storage is not just about economics. I mean apart Is that you, you know, green, really scale compute separate from storage as opposed to in chunks. It's more efficient, but you're saying there's other advantages to operational and workload. Specificity. Um, what is unique about vertical In this regard, however, many others separate compute from storage? What's different about vertical? >>Yeah, I think you know, there's a lot of differences about how we do it. It's one thing if you're a cloud native company, you do it and you have a shared catalog. That's key value store that all of your customers are using and are on the same one. Frankly, it's probably more of a security concern than anything. But it's another thing. When you give that capability to each customer on their own, they're fully protected. They're not sharing it with any other customers. And that's something that we hear a lot of insights from our customers. They want to be able to separate compute and storage. But they want to be able to do this in their own environment so that they know that in their data catalog there's no one else is. You share in that catalog, there's no single point of failure. So, um, that's one huge advantage that we have. And frankly, I think it just comes from being a company that's operating on premise and, uh, up in the cloud. I think another huge advantages for us is we don't know what object storage platform is gonna win, nor do we necessarily have. We designed the young vote so that it's an sdk. We started with us three, but it could be anything. It's DFS. That's three. Who knows what what object storage formats were going to be there and then finally, beyond just the object storage. We're really one of the only database companies that actually allows our customers to natively operate on data in very different formats, like parquet and or if you're familiar with those in the Hadoop community. So we not only embrace this kind of object storage disruption, but we really embrace the different data formats. And what that means is our customers that have data pipelines that you know, fully automated, putting this information in different places. They don't have to completely reload everything to take advantage of the Arctic analytics. We can go where the data is connected into it, and we offer them a lot of different ways to take advantage of those analytics. So there are a couple of unique differences with verdict, and again, I think are really advance. You know, in many ways, by not being a cloud native platform is that we're very good at operating in different environments with different formats that changing formats over time. And I don't think a lot of the other companies out there that I think many, particularly many of the SAS companies were scrambling. They even have challenges moving from saying Amazon environment to a Microsoft azure environment with their office because they've got so much unique Band Aid. Excuse me in the background. Just holding the system up that is native to any of those. >>Good. I'm gonna summarize. I'm hearing from you your Ferrari of databases that we've always known. Your your object store agnostic? Um, it's any. It's the cloud experience that you can bring on Prem to virtually any cloud. All the popular clouds hybrid. You know, aws, azure, now Google or on Prem and in a variety of different data formats. And that is, I think, you know, you need the combination of those I think is unique in the marketplace. Um, before we get into the news, I want to ask you about data silos and data silos. You mentioned H DFs where you and I met back in the early days of big data. You know, in some respects, you know, Hadoop help break down the silos with distributing the date and leave it in place, and in other respects, they created Data Lakes, which became silos. And so we have. Yet all these other sales people are trying to get to, Ah, digital transformation meeting, putting data at their core virtually obviously, and leave it in place. What's your thoughts on that in terms of data being a silo buster Buster, How does verdict of way there? >>Yeah, so And you're absolutely right, I think if even if you look at his due for all the new data that gets into the do. In many ways, it's created yet another large island of data that many organizations are struggling with because it's separate from their core traditional data warehouse. It's separate from some of the operational systems that they have, and so there might be a lot of data in there, but they're still struggling with How do I break it out of that large silo and or combine it again? I think some some of the things that verdict it doesn't part of the announcement just attend his migration tools to make it really easy. If you do want to move it from one platform to another inter vertical, but you don't have to move it, you can actually take advantage of a lot of the data where it resides with vertical, especially in the Hadoop brown with our external table storage with our building or compartment natively. So we're very pragmatic about how our customers go about this. Very few customers, Many of them tried it with Hadoop and realize that didn't work. But very few customers want a wholesale. Just say we're going to throw everything out. We're gonna get rid of our data warehouse. We're gonna hit the pause button and we're going to go from there. Just it's not possible to do that. So we've spent a lot of time investing in the product, really work with them to go where the data is and then seamlessly migrate. And when it makes sense to migrate, you mentioned the performance of America. Um, and you talked about it is the variety. It definitely is. And one other thing that we're really proud of this is that it actually is not a gas guzzler. Easy either One of the things that we're seeing, a lot of the other cloud databases pound for pound you get on the 10th the hardware vertical running up there. You get over 10 x performance. We're seeing that a lot, so it's Ah, it's not just about the performance, but it's about the efficiency as well. And I think that efficiency is really important when it comes to silos. Because there's there's just only so much horsepower out there. And it's easier for companies to play tricks and lots of servers environment when they start up for so many organizations and cloud and frankly, looking at the bills they're getting from these cloud workloads that are running. They really conscious of that. >>Yeah. The big, big energy companies love the gas guzzlers. A lot of a lot of cloud. Cute. But let's get into the news. Uh, 10 dot io you shared with your the audience in your keynote. One of the one of the highlights of data. What do we need to know? >>Yeah, so, you know, again doubling down on these mega trends, I'll start with Machine Learning and ai. We've done a lot of work to integrate so that you can take native PM ml models, bring them into vertical, run them massively parallel and help shape you know your data and prepare it. Do all the work that we know is required true machine learning. And for all the hype that there is around it, this is really you know, people want to do a lot of unsupervised machine learning, whether it's for healthcare fraud, detection, financial services. So we've doubled down on that. We now also support things like Tensorflow and, you know, as I mentioned, we're not going to come up with the best algorithms. Our job is really to ensure that those algorithms that people coming up with could be incorporated, that we can run them against massive data sets super efficiently. So that's that's number one number two on object storage. We continue to support Mawr object storage platforms for ya mode in the cloud we're expanding to Google G CPI, Google's cloud beyond just Amazon on premise or in the cloud. Now we're also supporting HD fs with beyond. Of course, we continue to have a great relationship with our partners, your storage on premise. Well, what we continue to invest in the eon mode, especially. I'm not gonna go through all the different things here, but it's not just sort of Hey, you support this and then you move on. There's so many different things that we learn about AP I calls and how to save our customers money and tricks on performance and things on the third areas. We definitely continue to build on that flexibility of deployment, which is related to young vote with. Some are described, but it's also about simplicity. It's also about some of the migration tools that we've announced to make it easy to go from one platform to another. We have a great road map on these abuse on security, on performance and scale. I mean, for us. Those are the things that we're working on every single release. We probably don't talk about them as much as we need to, but obviously they're critically important. And so we constantly look at every component in this product, you know, Version 10 is. It is a huge release for any product, especially an analytic database platform. And so there's We're just constantly revisiting you know, some of the code base and figuring out how we can do it in new and better ways. And that's a big part of 10 as well. >>I'm glad you brought up the machine Intelligence, the machine Learning and AI piece because we would agree that it is really one of the things we've noticed is that you know the new innovation cocktail. It's not being driven by Moore's law anymore. It's really a combination of you. You've collected all this data over the last 10 years through Hadoop and other data stores, object stores, etcetera. And now you're applying machine intelligence to that. And then you've got the cloud for scale. And of course, we talked about you bringing the cloud experience, whether it's on Prem or hybrid etcetera. The reason why I think this is important I wanted to get your take on this is because you do see a lot of emerging analytic databases. Cloud Native. Yes, they do suck up, you know, a lot of compute. Yeah, but they also had a lot of value. And I really wanted to understand how you guys play in that new trend, that sort of cloud database, high performance, bringing in machine learning and AI and ML tools and then driving, you know, turning data into insights and from what I'm hearing is you played directly in that and your differentiation is a lot of the things that we talk about including the ability to do that on from and in the cloud and across clouds. >>Yeah, I mean, I think that's a great point. We were a great cloud database. We run very well upon three major clouds, and you could argue some of the other plants as well in other parts of the world. Um, if you talk to our customers and we have hundreds of customers who are running vertical in the cloud, the experience is very good. I think it would always be better. We've invested a lot in taking advantage of the native cloud ecosystem, so that provisioning and managing vertical is seamless when you're in that environment will continue to do that. But vertical excuse me as a cloud platform is phenomenal. And, um, you know, there's a There's a lot of confusion out there, you know? I think there's a lot of marketing dollars spent that won't name many of the companies here. You know who they are, You know, the cloud Native Data Warehouse and it's true, you know their their software as a service. But if you talk to a lot of our customers, they're getting very good and very similar. experiences with Bernie comic. We stopped short of saying where software is a service because ultimately our customers have that control of flexibility there. They're putting verdict on whichever cloud they want to run it on, managing it. Stay tuned on that. I think you'll you'll hear from or more from us about, you know, that going going even further. But, um, you know, we do really well in the cloud, and I think he on so much of yang. And, you know, this has really been a sort of 2.5 years and never for us. But so much of eon is was designed around. The cloud was designed around Cloud Data Lakes s three, separation of compute and storage on. And if you look at the work that we're doing around container ization and a lot of these other elements, it just takes that to the next level. And, um, there's a lot of great work, so I think we're gonna get continue to get better at cloud. But I would argue that we're already and have been for some time very good at being a cloud analytic data platform. >>Well, since you open the door I got to ask you. So it's e. I hear you from a performance and architectural perspective, but you're also alluding two. I think something else. I don't know what you can share with us. You said stay tuned on that. But I think you're talking about Optionality, maybe different consumption models. That am I getting that right and you share >>your difficult in that right? And actually, I'm glad you wrote something. I think a huge part of Cloud is also has nothing to do with the technology. I think it's how you and seeing the product. Some companies want to rent the product and they want to rent it for a certain period of time. And so we allow our customers to do that. We have incredibly flexible models of how you provision and purchase our product, and I think that helps a lot. You know, I am opening the door Ah, a little bit. But look, we have customers that ask us that we're in offer them or, you know, we can offer them platforms, brawl in. We've had customers come to us and say please take over systems, um, and offer something as a distribution as I said, though I think one thing that we've been really good at is focusing on on what is our core and where we really offer offer value. But I can tell you that, um, we introduced something called the Verdict Advisor Tool this year. One of the things that the Advisor Tool does is it collects information from our customer environments on premise or the cloud, and we run through our own machine learning. We analyze the customer's environment and we make some recommendations automatically. And a lot of our customers have said to us, You know, it's funny. We've tried managed service, tried SAS off, and you guys blow them away in terms of your ability to help us, like automatically managed the verdict, environment and the system. Why don't you guys just take this product and converted into a SAS offering, so I won't go much further than that? But you can imagine that there's a lot of innovation and a lot of thoughts going into how we can do that. But there's no reason that we have to wait and do that today and being able to offer our customers on premise customers that same sort of experience from a managed capability is something that we spend a lot of time thinking about as well. So again, just back to the automation that ease of use, the going above and beyond. Its really excited to have an analytic platform because we can do so much automation off ourselves. And just like we're doing with Perfect Advisor Tool, we're leveraging our own Kool Aid or Champagne Dawn. However you want to say Teoh, in fact, tune up and solve, um, some optimization for our customers automatically, and I think you're going to see that continue. And I think that could work really well in a bunch of different wallets. >>Welcome. Just on a personal note, I've always enjoyed our conversations. I've learned a lot from you over the years. I'm bummed that we can't hang out in Boston, but hopefully soon, uh, this will blow over. I loved last summer when we got together. We had the verdict throwback. We had Stone Breaker, Palmer, Lynch and Mahoney. We did a great series, and that was a lot of fun. So it's really it's a pleasure. And thanks so much. Stay safe out there and, uh, we'll talk to you soon. >>Yeah, you too did stay safe. I really appreciate it up. Unity and, you know, this is what it's all about. It's Ah, it's a lot of fun. I know we're going to see each other in person soon, and it's the people in the community that really make this happen. So looking forward to that, but I really appreciate it. >>Alright. And thank you, everybody for watching. This is the Cube coverage of the verdict. Big data conference gone, virtual going digital. I'm Dave Volante. We'll be right back right after this short break. >>Yeah.

(soft electronic music) >> Announcer: Live from Vancouver, Canada, it's theCUBE. Covering OpenStack Summit North America 2018. Brought to you by Red Hat, the OpenStack Foundation, and it's ecosystem partners. >> Welcome back, I'm Stu Miniman here with my cohost John Troyer and you're watching theCUBE's exclusive coverage of OpenStack Summit 2018 in Vancouver. Happy to welcome you back to the program, off the keynote stage this morning, Mark Shuttleworth, the founder of Canonical. Thank you so much for joining us. >> Stu, thanks for the invitation. >> Alright, so you've been involved in this OpenStack stuff for quite a bit. >> Right, since the beginning. >> I remember three years ago we were down in the other hall talking about the maturity of the platform. I think three years ago, it was like this container thing was kind of new and the basic infrastructure stuff was starting to get, in a nice term, boring. Because that meant we could go about business and be on the buzz of there's this cool new thing and we're going to kill Amazon, kill VMware, whatever else things that people thought that had a misconceived notion. So bring us forward to where we are 2018, what you're hearing from customers as you look at OpenStack and this community. >> Well, I think you pretty much called it. OpenStack very much now is about solving a real business problem, which is the automation of the data center and the cost parody of private data centers with public data centers. So I think we're at a time now where people understand the public cloud is a really good thing. It's great that you have these giant companies dueling it out to deliver better quality infrastructure at a better price. But then at the same time, having your own private infrastructure that runs cost-effectively is important. And OpenStack really is the only approach to that that exists today. And it's important to us that the conversation is increasingly about what we think really matters, which is the economics of owning it, the economics of running it, and how people can essentially keep that in line with what they get from the public cloud providers. >> Yeah, one of the barometers I use for vendors these days is in this multi-cloud world, where do you sit? Do you play with the HyperScalers? Are you a public cloud denier? Or, like most people you're, most people are somewhere in-between. In your keynote this morning, you were talking a bit about all of the HyperScalers that use your products as well as-- >> Ubuntu is at the heart of all of the major public cloud operations at multiple levels. So we see them as great drivers of innovation, great drivers of exposure of Ubuntu into the enterprise. We're still, by far, the number one platform used in public cloud by enterprises. It's hard to argue that public cloud is testing Dev now. It really, really isn't and so most of that is still Ubuntu. And now we're seeing that pendulum swing, all of those best practices, that consumption of Ubuntu, that understanding of what a leaner, meaner Enterprise Linux looks like. Bringing that back to the data center is exciting. For us, it's an opportunity to help enterprises rethink the data center to make it fully automated from the ground up. OpenStack is part of that, Kubernetes is part of that and now the cherry on top is really AI where people understand they have to be able to do it on public cloud, on private infrastructure and at the Edge. >> Mark, I wanted to talk about open source. Marketing open source, for a minute. We are obviously here, we're part of an open source community. Open source, defacto, has won the cloud technology stack wars. So there's one way of selling OpenStack where you pound on open a lot. >> I'm always a bit nervous about projects that put open. It sounds like they're sort of trying to gloss over something or wash over something or prove a point. They shouldn't have to. >> There's one about the philosophy of open source, which certainly has to stay there, right. Because that's what drove the innovation but I was kind of impressed about on the stage today, you talked about the benefits. You didn't say, well the venture's open. You said, well, we're facilitating these benefits. Speed to market, cost, et cetera. Can you talk about your approach, Canonical's approach to talking about this open source product in terms of its benefits? >> Sure, look, open source is a license. Under that license, there's room for a huge spectrum of interest and opinions and approaches. And I'd say that I certainly see an enormous amount of value in what I would call the passion-based open source story. Now, OpenStack is not that. It's too big, too complicated, to be one person's deep passion. It really isn't. But there's still a ton of innovation that happens in our world, across the full spectrum of what we see with open source, which is really experts trying to do something beautiful and elegant. And I still think that's really important in open source. You also have a new kind of dimension, which is almost like industrial trench warfare with open source. Which is huge organizations leveraging effectively their ability go get something widespread, widely adopted, quickly and efficiently by essentially publishing it as open source. And often, people get confused between these two ends of the spectrum. There's a bunch in between. What I like about OpenStack is that I think it's over the industrial trench warfare phase. You know, you just don't see a ton of people showing up here to throw parties and prove to everyone how cool they are. They've moved on to other open source projects. The people who are here are people who essentially have the real problem of I want to automate my data center, I want to have, essentially, a cloud that runs cost-effectively in my data center that I can use as part of a multi-cloud strategy. And so now I think we're in to that sort of, a more mature place with OpenStack. We're not either sort of artisan or craftsmen oriented, nor are we a guns blazing brand oriented. It's kind of now just solving the problems. >> Mark, there's still some nay-sayers out in the marketplace. Either they say that this never matured, there's a certain analyst firm that put out a report a couple of months ago that, it kind of denigrated what's happening here. And then there's others that, as you said, off chasing that next big wave of open source. What are you hearing from your customers? You've got a good footprint around the globe. >> So that report is nonsense, for a start. They're always wrong, right. If they're hyping something, they're wrong and if they're dissing something then they're usually wrong too. >> Stu: They have a cycle for that, I believe. (chuckling) >> Exactly. Selling gold at the barroom. Here's how I see it. I think that enterprises have a real problem, which is how do they create private cloud infrastructure. OpenStack had a real problem in that it had too many opinions, too many promises. Essentially a governing structure not a leadership structure. Our position on this has always been focus on the stuff that is really necessary. There was a ton of nonsense in OpenStack and that stuff is all failing. And so what? It was never essential to the mission. The mission is stand up a data center in an automated way, provide it, essentially, as resources, as a service to everybody who you think is authorized to be there, effectively. Segment and operate that efficiently. There's only a small part of OpenStack that was ever really focused on that. That's the stuff that's succeeding, that's the stuff we deliver. That's the stuff, we think very carefully about how to automate it so that, essentially, anybody can consume it at reasonable prices. Now, we have learned that it's better for us to do the operations almost. It's better for us actually to take it to people as a solution, say look, explain your requirements to us then let us architect that cloud with you then let us build that cloud then let us operate that cloud. Until it's all stable and the economics are good, then you can take over. I think what we have seen is that you ask every single different company to build OpenStack, they will make a bunch of mistakes and then they'll say OpenStack is the problem. OpenStack's not the problem. Because we do it again and again and again, because we do it in many different data centers, because we do it with many different industries, we're able to essentially put it on rails. When you consume OpenStack that way it's super cheap. These aren't my numbers, analysts have studied the costs of public infrastructure, the cost of the established, incumbent enterprise, virtualization solutions and so on. And they found that when you consume OpenStack from Canonical it is much, much cheaper than any of your other options in your own private data center. And I think that's a success that OpenStack should be proud of. >> Alright, you've always done a good job at poking at some of the discussions happening in the industry. I wouldn't say I was surprised but you were highlighting AI as something that was showing a lot of promise. People have been a little hot and cold depending on what part of the market you're at. Tell us about AI and I'd love to hear your thoughts in general. Kubernetes, Serverless, and ask you to talk about some of those new trends that are out there. >> Sure, the big problem with data science was always finding the right person to ask the right question. So you could get all the data in the world in a data lake but now you have to hire somebody who instinctively has to ask the right question that you can test out of that data. And that's a really hard problem. What machine learning does is kind of inverts the problem. It says, well, why don't we put all that data through a pattern matching system and then we'll end up with something that reflects the underlying patterns, even if we don't know what they are. Now, we can essentially say if you saw this, what would you expect? And that turns out to be a very powerful way to deal with huge amounts of data that, previously, you had to kind of have this magical intuition to kind of get to the bottom of. So I think machine learning is real, it's valuable in almost every industry, and the challenges now are really about standardizing underlying operations so that the people who focus on the business problems can, essentially, use them. So that's really what I wanted to show today is us working with, in that case it was Google, but you can generalize that. To standardize the experience for an institution who wants to hire developers, have them effectively build machine-driven models if they can then put those into production. There's a bunch of stuff I didn't show that's interesting. For example, you really want to take the learnings from machine-learning and you want to put those at the Edge. You want to react to what's happening as close to where it's happening as possible. So there's a bunch of stuff that we're working on with various companies. It's all about taking that AI outcome right to the Edge, to IOT, to Edge Cloud but we don't have time to get in to all of that today. >> Yeah, and Ubuntu is at the Edge, on the mobile platform. >> So we're in a great position that we're on the Cloud. Now you see what we're doing in the data center for enterprises, effectively recrafting the data center has a much leaner, more automated machine. Really driving down the cost of the data center. And yes, we're on the higher-end things. We're never going to be on the LightBulb. We're a full general-purpose operating system. But you can run Ubuntu on a $10 board now and that means that people are taking it everywhere. Amazon, for example, put Ubuntu on the DeepLens so that's a great example of AI at the edge. It's super exciting. >> So the Kubernetes, Serverless-type applications, what are your thinkings around there? >> Serverless is a lovely way to think about the flow of code in a distributed system. It's a really nice way to solve certain problems. What we haven't yet seen is we haven't seen a Serverless framework that you can port. We've seen great Serverless experiences being built inside the various public clouds but there's nothing consistent about them. Everything that you invest in a particular place is very useful there but you can't imagine taking that anywhere else. I think that's fine. >> Stu: Today's primarily Lando. >> And I think the other clouds have done a credible job of getting there quickly. But kudos to Amazon for kind of pioneering that. I do think we'll see generalized Serverless, it just doesn't exist at the moment and as soon as it does we'll be itching to get it into people's hands. >> Okay, yeah? >> Well, I just wanted to pull out something that you had said in case people miss it, you talked about managed OpenStack. And that, I think, managed Kubernetes has been a trend over the last year. Managed OpenStack now. Has been trans-- >> With these complex pieces of infrastructure, you could easily drown in learning it all and if you're only ever going to do one, maybe it makes sense to have somebody else do it for a while. You can always take it over later. So we're unusual in that we will essentially standup something complex like an OpenStack or a Kubernetes, operate it as long as people want and then train them to take over. So we're not exclusively managed and we're not exclusively arms-length. We're happy to start the one way and then hand over. >> I think that's an important development, though, that's been developing as the systems get more complicated. One UNIX admin needs a whole new skill set or broader skill set now that we're orchestrating a whole cloud so that's, I think that's great. And that's interesting. Anything else you're looking forward to, in terms of operation models. I guess we've said, Ubuntu everywhere from the edge to the center and now managed, as well. Anything else we're looking at in terms of operators should be looking at? >> Well, I think it just is going to stay sort of murky for a while simply because each different group inside a large institution has a boundary of their authority and to them, that's the edge. (chuckling) And so the term is heavily overloaded. But I would say, ultimately, there are a couple of underlying problems that have to be solved and if you look at the reference architectures that the various large institutions are putting out, they all show you how they're trying to attack these patterns using Ubuntu. One is physical provisioning. The one thing that's true with every Edge deployment is there are no humans there. So you can't kind of Band-Aid over the idea that when something breaks you need to completely be able to reset it from the ground up. So MAAS, Middle as a Service, shows up in the reference architectures from AT&T and from SoftBank and from Dorich Telecom and a bunch of others because it solves their problem. It's the smallest piece of software you can use to take one server or 10 servers or 100 servers and just reflash them with Windows or CentOS or whatever you need. That's one thing. The other thing that I think is consistently true in all these different H-Cloud permutations or combinations is that overhead's really toxic. If you need three nodes of overhead for a hundred node OpenStack, it's 3%. For a thousand node OpenStack, it's .3%. It's nothing, you won't notice it. If you need three nodes of OpenStack for a nine node Edge Cloud, well then that's 30% of your infrastructure costs. So really thinking through how to get the overhead down is kind of a key for us. And all the projects with telcos in particular that we're working, that's really what we bring is that underlying understanding and some of those really lightweight tools to solve those problems. On top of that, they're all different, right. Kubenetes here, Lixti there, OpenStack on the next one. AI everywhere. But those two problems, I think, are the consistent things we see as a pattern in the Edge. >> Alright, so Mark, last question I have for you. Company update. So last year we talked a little bit about focusing, where the company's going, talked a bit about the business model and you said to me, "Developers should never have to pay for anything." It's the governance people and everything like that. Give us the company update, everything from rumors from hey, maybe you're IPO-ing to what's happening, what can you share? >> Right, so the twin areas of focus, IOT and cloud infrastructure. IOT continues to be an area of R and D for us so we're still essentially underwriting an IOT investment. I'm very excited about that. I think it's the right thing to be doing at the moment. I think IOT is the next wave, effectively, and we're in a special position. We really can get down, both economically and operationally, into that sort of small itch kind of scenario. Cloud, for us, is a growth story. I talked a little bit about taking Ubuntu and Canonical into the finance sector. In one year, we closed deals with 20% of the top 20 banks in the world to build Ubuntu base and open infrastructure. That's a huge shift from the traditional dependence exclusively on VMware Red Hat. Now, suddenly, Ubuntu's in there, Canonical's in there. I think everybody understands that telcos really love Ubuntu and so that continues to grow for us. Commercially, we're expanding both in Emir and here in the Americas. I won't talk more about our corporate plans other than to say I see no reason for us to scramble to cover any other areas. I think cloud infrastructure and IOT is plenty for one company. For me, it's a privilege to combine that kind of business with what happens in the Ubuntu community. I'm still very passionate about the fact that we enable people to consume free software and innovate. And we do that without any friction. We don't have an enterprise version of Ubuntu. We don't need an enterprise version of Ubuntu, the whole thing's enterprise. Even if you're a one-person startup. >> Mark Shuttleworth, always a pleasure to catch up. Thank you so much for joining us. >> Mark: Thank you, Stu. >> For John Troyer, I'm Stu Miniman. Back with lots more coverage here from OpenStack Summit 2018 in Vancouver. Thanks for watching theCUBE. (soft electronic music)

>> Announcer: Live from Las Vegas, it's The Cube, covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. >> Welcome back everyone. Live here in Las Vegas is SiliconANGLE's CUBE, our flight ship program. We go out to the event ... I'm John Furrier, My co-host David Vellante. Been watching 3 days of wall to wall exclusive coverage of Hewlett Packard Enterprise Discover 2017. Our seventh year covering HP Discover, now called HPE Discover. Dave, we've covered them all. Now we're doing some European versions. I missed the last one in London, but you were there. But you and I have covered HP Discover, Now HPE Discover, for now our 7th year. Interesting times as they say. >> Dave: I'll say. >> We live in interesting times. HP's been getting hammered. Certainly the competitions been slamming them, The press has not been kind to them, People think they're irrelevant. Wall Street just slammed them, so Jim Cramer on CNBC, really taking Meg to task, But we always come back and we feel differently when we're actually at the event. When you actually talk to the people in the company. They got a lot of cash on the books. They've got a lot of customers. They got technology. They're doing the vendor R&D that you guys have pointed out in your recent, ground-breaking, true private cloud research market sizing you put out there. Astonishing change. And I think, my gut is, yeah, certainly HP's had some changes in corporate development, but the reality is that they now have set that up and the market is exploding. It's got the cloud market that's coming on premise. The private cloud business is taking off. >> Yeah, you know, John, we have documented this over the last seven years, and it's like the Band-Aid is coming off slowly, and it finally feels like this Discover (ripping noise) is finally almost there, right? Because you remember the split, and then the spin merge, and then the software business, okay. This has been the cleanest Hewlett-Packard Enterprise Discover that we've been to. There wasn't a lot of noise about software, they had a little separate event going on. Not a lot of talk about the spin merge, a lot of talk about Pointnext, I think that's good, I like their branding. >> It's like they cleaned up all the rooms in the house, and the outside's got a new fresh coat of paint. I got to say, last year- noticeably, the branding, which we were kind of originally critical on two and a half, three years ago; the show was beautiful, the branding's amazing this year, again, they're going to that next level, you're starting to see the clean messaging, it's as if the ship has been kind of re-readied. And we said that last year, but to be fair, we did say last year that they got to prove it to you, They got to show the results. And we were talking with Alain, who runs their data center infrastructure group, he agrees; the metrics that all the other analyst firms are using out there are irrelevant, and he believes that new metrics have to be redefined. This to me is the biggest story of this show, is that HP is eyeing a new sea change and I don't think people understand it. That's my personal opinion. >> I think you're right, I mean, the narrative on HP is, oh, they're just a hardware company, hardware's dying, what are they doing, et cetera. Well the reality is, people have been telling me the hardware business is dying since I've been in the business. The good trend for them is, the hardware business is consolidating. Of course, the tough news is, a lot of it's going to the public cloud. But as you've been pointing out all week, there's plenty of growth, on prem, in what we call the true private cloud. >> That's the biggest discussion of the show here, is the impact of the Wikibon research, the true private cloud report that you guys put out, I want to spend some time with you on that and ask you some really pointed questions. What is the true private cloud report that Wikibon put out, and what does it mean, why are people talking about this research so much here? >> So three years ago, the team at Wikibon started to quantify this notion of private cloud, and we looked at it and said, ah, this is cloud-washing. Really this is just virtualization. What we really want to see is, on prem, mimicking,to a substantial degree, the public cloud. Orchestration, certainly, >> Agility, >> Management, agility, pay-as-you-go, those types of things. Okay, so, the genesis of the market move is something that we heard from Alan Nance, our friend, several years ago at the Vertica user conference. He said- he was, at the time, CIO of Philips- he said, "my CEO said 75% of our spend in infrastructure "is non-differentiated, so we're going to eliminate it, "and everything we're going to do is going to be as a service." That was three years ago. So, massive change, and Philips went out to all of its suppliers and said, this is what were doing, if you can't do business with us this way, you're out. And remember, we wrote a bunch of stuff about it, and Alain came back, okay. So they were one of the early folks making that move. Everybody is now doing that. So what's happening is, there's going to be $150 billion that is going to vaporize out of non-differentiated heavy lifting. And it's going to go in two places: it's going to go into the public cloud, and it's going to go to what we call true private cloud, and that true private cloud business is going to grow to be about $250 billion within the next 10 years, okay? So that's a long term market forecast. >> So the addressable market for true private cloud is what, 260, or 250 plus- >> 250, just under $250 billion. Which is growing faster than infrastructure as a service, public cloud, and it will ultimately, we believe, be larger than that IAAS business. Not as large as SASS, that's going to be the biggest public cloud market, but it's a huge opportunity for companies, and it's a land grab, and it's a dogfight. >> So, I want you to explain this, 'cause I think this is important, and it took me a couple minutes to click on this. You had mentioned that- there's a point in your slide on that deck, the size of the market is huge, it's $250 billion, that's a lot of cash. But the TAM component of labor costs, now, this is the big fear, everyone thinks, "oh, my job is going away, AIs and auto ate my job away", but yet you're saying $150 billion of cash costs are going to shift. >> To where? >> Absolutely. Okay, so a couple of things. What is going to shift? Today, there's so much IT labor spent on provisioning servers, provisioning storage, tuning systems, tuning databases, all this stuff that can be now hyper-automated, as the CEO of Wipro said, so that's happening today, as we speak. So, vendor R&D, i.e., R&D money that goes into appliances, boxes, new systems, new software, is going to replace and automate out those non-differentiated tasks. So if your job is provisioning LUNs, you really want to re-skill. >> So what's that mean for the customer in HP, and why is that important to this show, why are people talking about this report, what's the relevance? >> Because everybody's talking about their digital transformation. And how do you fund a digital transformation, right? You've got to spend all this money to become a digital, data driven company. Well, where do I get that money? >> John: Real cash involved, basically. >> Yeah, there's cash involved, so how do I do that? Well, I have to shift away from things that aren't driving value for my business, and eliminate that, and put the resources in things that are driving value. Application development, new development paradigms, digital transformations, new partnerships, and that's where the money's going. And so again, if you're an IT infrastructure patch management pro, you either have to re-skill, or you're going to be out of a job. >> Did you see Kate Swanborg light up when we talked about the private cloud, 'cause that's exactly what was her point. >> Yeah, well they're seeing it at DreamWorks, because essentially what they're doing, they're changing the game in animation. My prediction is, they're going to be able to pump out many more movies within a year now, and that's going to make them more competitive. I think that's part of the reason why she didn't want to dig too deep into what they're doing, 'cause I think they see it as a competitive advantage. >> Yeah, and she did tease a little bit out by saying that the creative people are so much more productive, she mentioned the dragon. Alright, other impact: Wall Street. We see a lot of analysts kind of taking HP to town. We know the competition, we talked to Michael Dell, he came on The Cube; Meg stopped by but she did not come in, that's notable for the folks out there, Michael certainly sits down with us; Michael says, "hey, I got plenty of cash", when I bring up the debt thing, he thinks bigger is better, HP thinks smaller and nimbler is better- >> This is going to be really interesting- >> Your thoughts on that as we move forward? >> Look, there's two, sort of, bromides, right, with Wall Street. First disappointment is never the last; uh oh, that would be bad news for HP, but Meg said, "we have bottomed in terms of margins, margins will improve." And a big thing's going to happen next month, HP's gets the cash from the spin merges, right, that's going to happen, and that's a big deal because their balance sheet- they're going to have $12 billion in cash on the balance sheet, which will match their debt, and they're going to start to be acquisitive. Dell EMC can't be acquisitive right now. They got to retire that debt and delever. >> We saw SimpliVity and Nimble, front and center, a lot of good success with the software there. >> Yep, so this will be really interesting to see, is this the last disappointment, is this a buying opportunity? >> Yeah, we're going to watch it, and- >> So if I had to bet, if I had to bet I'd say it is a buying opportunity, based on what I'm seeing here. It's much cleaner, leaner, and they've also restructured the sales organization to a great extent, so hopefully the execution's going to be better. >> Well, I'm not that generous, I think I want to see more results, I think- >> I know, but if you see more results, you're going to miss the upturn. (laughs) >> Well the question, to me, is- I do believe that they have an advantage with the true private cloud report you guys put out, I think that validates the shift of spend in IT, which validates the fact that it's growing, not shrinking, and yes, people might not be buying boxes but they're going to be buying IT. >> And the big thing is, well you know, John, the street right now wants growth. That's why Amazon can make no money and still crank, right? But if HPE can eke out any growth and start throwing off cash again, I think the stock is going to do just fine. >> Other notable things; obviously, the outsource business is gone, Pointnext is the solution, we had Ana on from Pointnext, she was the leader; other notable thing is the absence of Chris Hsu with Micro Focus, we had a chance to ... saw him at the Foundation Room at the Mandalay Bay the other night, had a great conversation. Apparently, they're not included in HPE Discover because they're a separate company. They're apparently doing really well. >> Well Micro Focus is killing it, right? I mean, their stock price increased faster than Facebook last year (laughs) so, that's an interesting play. I think it's a new private equity play, John. You know, the private equity play used to be, suck as much cash out and then leave the carcass. I think the new private equity play is, invest, and then take it to market again, and try to get that value from the market, so increase the value. >> I think you're onto something, and this is why I've always been complimentary of HP's corporate governance game, because I think that private equity is all about taking things private, and being nimble, and then going public again, so- >> And Micro Focus, in my opinion, picked up those assets for short money. >> Yeah; well, HP owns a big part of the company, so- >> Yeah, of course, but that's why they did the deal, it's short money, and they wanted the cash, and that's why they had to put the security piece in there. >> Alright- Dave Vellante, I'm John Furrier here breaking it down, ending our three days of exclusive coverage, at HPE 2017. Look for us at Madrid, the show there; I won't be there, Dave will be there; and again, HPE Discover, enjoy the rest of the conference, thanks for watching; this is The Cube out, thanks to the team and everyone here for a great job, see you next time.