>> Narrator: Live from San Diego, California. It's theCUBE. covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. >> Welcome back to San Diego, everybody. You're watching Cisco Live 2019. This is theCUBE, the leader in live tech coverage. This is day three of our wall-to-wall coverage. We go out to the events, we extract the signal from the noise. My name is Dave Vellante. Stu Miniman is here. Our third host, Lisa Martin is also in the house. Dave Malik is here. He's a fellow and Chief Architect at Cisco. David, good to see you. >> Oh, glad to be here. >> Thanks for coming on. First of all, congratulations on being a fellow. What does that mean, a Cisco Fellow? What do you got to go through to achieve that status? >> It's pretty arduous task. It's one of the most highest technical designations in Cisco, but we work across multiple architectures in technologies, as well as our partners, as well, to drive corporate-wide strategy. >> So you've been talking to customers here, you've been presenting. I think you said you gave three presentations here? Multi-cloud, blockchain, and some stuff on machine intelligence, ML. >> Yes. >> Let's hit those. Kind of summarize the overall themes, and then we'll maybe get into each, and then we got a zillion questions for you. >> Sure, excellent. So multi-cloud, I think one of the customers, we're clearly hearing from them is around, how do we get a universal policy model and connectivity model, and how do you orchestrate workloads seamlessly? And those are some of the challenges that we trying to address at this conference. On blockchain, a lot of buzz out there. We're not talking about Bitcoin or cryptocurrency, it's really about leveraging blockchain from a networking perspective, or an identity and encryption, and providing a uniform ledger that everything is pervasive across infrastructure. And then ML, I think it's the heart of every conversation. How do we take pervasive analytics and bring it into the network so we can drive actionable insights into automation? >> So let's start with the third one. When you talk about ML, was your talk on machine learning? Did it spill into artificial intelligence? What's the difference to you from a technology perspective? >> Machine learning is really getting a lot of the data and looking at repetitive patterns in a very common fashion, and doing a massive correlation across multiple domains. So you may have some things happening in the branch, the data set, or a WAN in cloud, but the whole idea is how do you put them together to drive insight? And through artificial intelligence and algorithms, we can try to take those insights and automate them and push them back into the infrastructure or to the application layer. So now you're driving intelligence for not just consumers or devices, but also humans as well to drive insight. >> All right. So Dave, I wonder if you'd help connect with us what you were talking about there, and we'll get to the multicloud piece because I was at an Amazon show last week from Amazon, talking about how when they look at all the technologies that they use to get packages, their fulfillment centers, everything that they do as a business, ML and AI, they said, is underneath that, and AWS is what's driving that technology from that standpoint. Now, multicloud, AWS is a partner of yours. >> Yes. >> Can you give us how you work in multicloud and does ML and IA, is that a Cisco specific? Are you working with some of the standards out there to connect all those pieces? Help us look at some of the big picture of those items. >> So we believe we're agnostic, whether you connect to Amazon, Azure, Google, et cetera, we believe in a uniform policy model and connectivity model, which is very, very arduous today. So you shouldn't have to have a specific policy model, connectivity model, security model for that matter, for each provider. So we're normalizing that plane completely, which is awesome. Then, at a workload level, regardless of whether your workload is spun up or spun down, it should have the same security posture and visibility. We have certain customers that are running as single applications across multiple clouds, so your data is going to be obviously on-prem, you may be running analytics in TenserFlow, compute in EC2, and connecting to O365, that's one app. And where we're seeing the models go is are you leveraging technology such as this? Do you offer service mesh? How do we tie a lot of these micro-services together and then be able to layer workload orchestration on top? So regardless of where your workload sits, and one key point that we keep hearing from our customers is their ungovernance. How we provide cloud-based governance regardless of where their workload is, and that's something we're doing in a very large fashion with customers that have a multicloud strategy. >> So Stu, I think there's still some confusion around multicloud generally, and maybe Cisco's strategy. I wonder if we could maybe clear it up a little bit. >> Dave, it's that big elephant in the room, and I always feel like everybody describes multicloud from a different angle. >> So let's dig into this a little bit, and let's hear from Cisco's perspective. So you got, to my count, five companies really going after this space. You got Cisco, VMware, IBM Red Hat, Microsoft, and Google with Anthos. Probably all those guys are partners of yours. >> Yes. >> Okay, but you guys want to provide the bromide or the single pane of glass, okay. I'm hearing open and agnostic. That's a differentiator. Security, you're in a good position to make an argument that you're in a good position to make things secure. You got the network and so forth. High-performance network, and cost-effective. Everybody's going to make that argument relative to having multiple stovepipes, but that's part of your story as well. So the question. Why Cisco? What's the key differentiator and what gives you confidence that you can really help win in this marketplace? >> So our core competencies are our networking and security. Whether it's cloud-based security or on-prem security, it's uniform. From a security perspective, we have a universal architecture. Whether it's the endpoint, the edge, the cloud, they're all sharing information and intelligence. That's really important. Instead of having bespoke products, these products and solutions need to communicate with each other, so if someone's sick in one area, we're informing the other one. So threat intelligence and network intelligence is huge. Then more importantly, after working with Google, Microsoft, and Amazon, we have on-prem solutions as well, so as customers are going on their multicloud journey, and eventually the workload will transition, you have the same management experience and security experience. So Anthos was a recent announcement, AWS as well, where you can run on-prem Kubernetes, and you can take the same workload and move it to AWS or GCP, but the management model and the control pane model, they are extremely similar and you don't have to learn anything new from a training perspective. >> Okay, but I used the term agnostic, oh, no. You did agnostic, I said open. But you don't care if it's Anthos or VMware, or OpenShift, you don't care. >> Don't care. >> And, architecturally, how is it that you can successfully not care? >> Because the underlying, fundamental principles is you can load any workload you want with this, bare metal, virtualized, or Kubernetes-based containers, they all need the same. For example, everyone needs bread and water. It's not different. So why should you be able to discriminate against a workload or OpenShare if they're using Pivotal Cloud Foundry, for example? The same model, all applications still need security, visibility, networking, and management, but they should not be different across all clouds, and that's traditionally what you're seeing from the other vendors in the market. They're very unique to their stovepipe, and we want to break down those stovepipes across the board, regardless of what app and what workload you have. >> Dave, talk a little bit about the automation that Cisco's delivering to help enable this because there's skill set challenges, just the scale of these environments are more than humans alone can take care of, so how does that automation, I know you're heavily involved in the CX beast of Cisco. How does that all tie together? >> So we're working on a lot of automation projects with our large enterprises and SPs, I mean, you see Rakuten being fairly prominent in the show, but more importantly, we understand not everyone's building a greenfield environment, not everything is purely public cloud. We have to deal with brownfield, we have to deal with third-party ecosystem partners, so you can't have a vertically tight single-vendor solution. So again, to your point, it's completely open. Then we have frameworks, meaning you have orchestrators that can talk down to the device through programmatic interfaces. That's why we see DevNet surrounding us, but then more importantly, we're looking at services that have workflows that could span on-prem, off-prem, third-party, it doesn't really matter. And we stitch a lot of those workloads southbound, but more importantly, northbound to security at ITSM Systems. So those frameworks are coming into life, whether you're a telecom cloud provider or you're a large enterprise. And they slowly fall into those workflows as they become more multi-domain. You saw David Goeckeler the other day, talking about SD-WAN, ECI, and campus wired and wireless. These domains are coming together and that's where we're driving a lot of the automation work. >> So automation is a linchpin to what business outcome? Ultimately, what are customers trying to achieve through automation? >> There's a couple of things. Mean time to value. So if you're a service provider, to your internal customers or external, time to value and speed and agility are key. The other ones are mean time to repair and mean time to detect. If I can shorten the time to detect and shorten time to react, then I can take proactive and preemptive action in situations that may happen. So time to value is really, really important. Cost is a play, obviously, 'cause when you have more and more machines doing your work, your OPEX will come down, but it's really not purely a cost play. Agility and speed are really driving automation to that scale as we're working with folks like Rakuten and others. >> What do you see, Dave, as the big challenges of achieving automation when customers, first of all, I was talking like, 10, 15 years ago people, they were afraid of automation. Some still are. But they I think understand as part of a digital transformation, they got to automate. So what are the challenges that they're having and how are you helping them solve them? >> So typically, what people have thought about automation has been more network-centric, but as we just discussed multicloud, automation is extending all the way to the public cloud, at the workload or at the functional level, if you're running in Lambda, for example. And then more importantly, traditionally, customers have been leveraging Python scripts and things of that nature, but the days of scripters are there, but they cannot scale. You need a model-driven framework, you need model-driven telemetry to get insight. So I think the learning curve of customers moving to a model-driven mindset is extremely important, and it's not just about the network alone, it's also about the application. So that's why we're driving a lot of our frameworks and education and training. And talent's a big gap that we're helping with with our training programs. >> Okay, so you're talking about insights. There's a lot of data. The saying goes, "data is plentiful, insights aren't." So how do you get from data to insights? Is that where the machine intelligence comes in? Maybe you can explain that. >> There's a combination. Machines can process much faster than humans can, but more importantly, somebody has to drive the 30 or 40 years of experience that Cisco has from our tech, our architects and CX, and our customers and the community that we're developing through DevNet. So taking trusted expertise from humans, from all that knowledge base, combining that with machine learning so we get the best of both worlds. 'Cause you need that experience. And that is driving insight so we can filter the signal from the noise, and then more importantly, how do you take that signal and then, in an automated fashion, push that down to an intent-based architecture across the board. >> Dave, can you take us inside a little bit of your touchpoints into customers? In the old days, it was a CCIE, his job, his title, it was equipment that he would touch, and today, talking about this multicloud and the automation, it's very dispersed as to who owns it, most of what I am managing is not something that's under their purview, so the touchpoints you have into the company and the relationship you have changed a lot in the last three, five years or so. >> Absolutely, 'cause the buying center's also changing, because folks are getting more and more centric around the line of business and want the outcome we want to drive for their clients. So the cloud architecture teams that are being built, they're more horizontal now. You'll have a security person, an application, networking, operations, for example, and what we're actually pioneering, a lot of the enterprises and SPs, is building the site reliability engineering teams, or SRE, which Google has obviously pioneered, and we're bringing those concepts and teams through a CX framework, through telecos, and some of their high-end enterprises initially, and you'll see more around that over the coming months. Our SRE jobs, if you go on LinkedIn, you'll probably see hundreds of them out there now. >> One of the other things we've been watching is Cisco has a very broad portfolio. This whole CX piece has to make sure that, from a customer's standpoint, no matter where the portfolio, whether core, edge, IOT, all these various devices, I should have a simplified experience today, which isn't necessarily, my words, Cisco's legacy. How do you make sure, is software a unifying factor inside the company? Give us a little bit about those dynamics inside. >> Absolutely, so we take a life cycle approach. It's not one and done. From the time there's a concept where you want to build out a blueprint, but there's no transformation journey, we have to make sure we walk the client through preparation, planning, design, architecture optimization, but then making sure they actually adopt, and get the true value. So we're working with our customers to make sure that they go around the entire life cycle, from end to end, from cradle to grave, and be able to constantly optimize. You're hearing the word continuous pretty much everywhere. It's kind of the fundamental of CICD, so we believe in a continuous life cycle approach that we're walking the customers end to end to make sure from the point of purchase to the point of decommissioning, making sure they're getting the most value out of the solutions they're getting from Cisco. >> All right Dave, we'll give you the last word on Cisco Live 2019. Thoughts? Takeaways? >> I think there's just amazing energy here, and there's a lot more to come. Come down to the CX booth and we'll have to show you some more gadgets and solutions where we're taking our forward customers. >> Great. David, thank you very much for coming to The Cube. >> Pleasure, thank you. >> All right, 28,000 people and The Cube bringing it to you live. This is Dave Vellante with Stu Miniman. Lisa Martin is also in the house. We'll be right back from Cisco Live San Diego 2019, Day 3. You're watching The Cube.

(upbeat music) >> Hello everyone, welcome to a special CUBE Conversation here at the SiliconANGLE Media, CUBE and Wikibon studio in Palo Alto. I'm John Furrier, co-founder of SiliconANGLE Media, Inc. I'm here with Peter Burris, head of research, for a special Amazon Web Services re:Invent preview. We just had a great session with Peter's weekly Action Item roundtable meeting with analysts surrounding the trend. So that'll be up on YouTube, check that out. Really in-depth conversation around what to expect at Amazon Web Service's re:Invent coming up in about a week and a half, and great content in there. But I want to go here, Peter, have a conversation with you back and forth, 'cause we've been having a debate, ping-ponging back and forth around what we think might happen. We certainly have some visibility in some of the news that might be happening at re:Invent. But you guys have been doing a great job with the research. I want to get your thoughts and I want to just have a conversation around Amazon Web Services. Continuing to kick ass, they've had a run on their own for many, many years now. But they got competition. The visibility in Wall Street is clear. They know the profitability. The numbers are all taking shape. Microsoft stock's up from 26 to wherever it is now. It's clear the cloud is the game. That's what's going on, and you have, again, the top three: Amazon, Azure, Google. And then, you can argue four through seven, including Alibaba and others, big game going on. This is causing a lot of opportunities, but disruption to business models, technology architectures, and ultimately how customers are going to deploy their IT and/or their digital business. Your thoughts? >> I think one of the most interesting things about this, John, is that in the first 10 years of the cloud, it was implied that it was a cost play. Don't do IT anymore, it's blah, blah, blah, blah, blah, do the cloud, do AWS. And I think that because the competition is so real now, and a lot of businesses are starting to realize what actually could be done if you're able to use your data in new and different ways, and dramatically accelerate and transform your businesses, that all this has become a value play. And the minute that it becomes a value play, in other words, new types of work, new types of capabilities, then for Amazon, for AWS, it becomes an ecosystem play. So I think one of the things that's most interesting about this re:Invent, is it's, from my opinion, it's going to be the first one where it's truly a strong ecosystem story. It's about how Amazon is providing services that the rest of the world's going to be able to consume and create new types of value through the Amazon ecosystem. >> Great point, I want to bring up a topic that we've been talking on theCUBE in some of my other CUBE Conversations, as it relates to the ecosystem is, in all these major ways, and we've seen many, you've covered many ways as an analyst over the years, there's always been a gestation period between a disruptive enabler, you could talk about TCP/IP, you could talk about HTTP, there's always a period of gestation. Sometimes it's accelerated now more than ever, but you start to see the impact of that disruptive enabler. Certainly cloud, and what Amazon has done, has been a disruptive enabler. Value's been created, more value's being created, more and more everyday we're seeing it. You're starting to see new things pop up from this gestation period, problems that become opportunities. And competitors that are now partners, partners that are now competitors. So a full changeover is happening in the landscape because of it. So the question for you is, what are you seeing, given your experience in seeing other ways before, what is starting to be clear in terms of visibility that are becoming known points of obvious straight and narrow trends that are happening with this cloud enabling? >> Well, let's talk about perhaps one of the biggest differences between traditional IT and cloud-oriented IT. And to kind of tell that story, I'll do something that a lot of people don't think about when they think about innovation. But if you really think about innovation, you got to break it down into two distinct acts. There's the act of inventing, which is an engineering act. It's, how do I take knowledge of physics, or knowledge of sociology, or knowledge of something, and invent something new that reflects my understanding of the problem and creating a solution? And then there's an innovation act, which is always a social act. It's getting people to change the way they do things. Businesses to change the way they do things. That's a social act. And one of the interesting things about the transition, this transition, this cloud-based transition, is we're moving into a world where the social acts are much more synonymous with the actual engineering act. And by that I mean, when something is positioned as a service, that the customer gets and just acts on it because they're now renting a service, that is truly an innovation process. You are adopting it as a service and embedding it more quickly. What we're seeing now in many respects, going back to your core point, is everything being done as a service, it means that the binding of the inventing and the innovating is much more strong, and much more immediate. And AWS re:Invent's been a forum where we see this. It's not just inventing or putting forward a new product that may get out to market in six months or nine months. It is, here is a service, people are consuming it, we're embedding it in our other AWS stuff. We're putting this AI into how folks are going to manage AWS, and the invention innovation process collapses very quickly. >> That's a good point. I would just give you some validation on that by seeing other trend points that talk about that social piece. You hear about social engineering in cyber security, that that's now a big part of how hackers are getting in, through social engineering. Open-source software is a social engineering act, 'cause it's got a community dynamic. Blockchains, huge social engineering around how these companies are forming. So I would 100% agree, that's a great, great point. The other thing I'd ask you to elaborate on is something that is a trend that's obvious, 'cause everyone talks about the old way, new way. Legacy is being disrupted. New players like Amazon are disrupting the people like Oracle. And Oracle thinks they're winning, Amazon thinks they're winning. The scoreboards aren't the same, but here's the question. Technology used to be built to solve technology problems. You build a box, you ship it, and it works. Software, craft it, ship it. It does work or it doesn't work. Now software and technology we can use to solve non-technology problems. This brings it to a whole nother level when you take your social comment, an invention. This is now a new dynamic that tend to be, I don't want to say minimized in the old days, but the old ways was, load some boxes, rack it up, and you got a PC on your desk. We could work effectively on a network. Now it's completely going non-technology problems, healthcare, verticals. >> Here's the way we look at it, John. >> John: What's your thoughts on that? >> Our simple bromide is that we are in the midst of the transition in computing. And by that I mean, for the first 50 years we talked about known process, unknown technology. By that I mean, for example, have you ever seen a GAAP accounting convention wandering out in the wild? No, it doesn't exist, it's manmade, it's artifice. There's nothing wrong with it. We all agree what an accounting thing is, but it's all highly stylized and extremely well-defined. It's a known process. And the first 50 years were about taking those known processes in accounting, and in HR, and a lot of other domains, and then saying, okay, what's the right technology to automate as much of this as possible? And we did a phenomenal job of it. It started with mainframes, then client/server. And was it this server, or that server? Unix or something else? TCP/IP or some other network? But that was the first 50 years of computing. Now we've got a lot of those things out. In fact, cloud kind of summarizes and puts forward a common set of experiences, still a lot of technology questions are going to be important. I don't want to suggest that that's not important. But increasingly it's, okay, what are the processes that we're going to try to automate? So we're now in a world where the technology's much more known, but the processes are incredibly unknown. So we went from a known-- >> So what is that impact to the cloud players, like Amazon? Because what I'm trying to figure out is, what will be the posture on the keynotes? Is it going to be a speeds and feeds show? Or is it going to be much more holistic, business impact, or societal impact? >> The obvious one is that Amazon increasingly has to be able to render these common building blocks for infrastructure up through to developers, and a new way of thinking about how do you solve problems. And so a lot more of what we're likely to see this year is Amazon continuing to move up the stack and say, here's how you're going to look at a problem, here's how you're going to solve the problem, here's the tooling, and here's the ecosystem that we're going to bring along with us. So it's much more problem-solving at the value level, going back to what we talked about earlier, problem solving that creates new types of business value, as opposed to problem solving to reduce the costs of existing infrastructure. >> Now we have a VIP chat on crowdchat.net/awsreinvent. If you want to participate, we're going to open it. We're going to keep it open for a long time, weigh in on that. We just had a great research meeting that you do weekly called Action Item, which is a format that's designed to flush out the latest and greatest research that's tied to current events or trends. And then unpack the action item for buyers and customers, large businesses in the industry. What's the summary for the meeting we just had here? A lot of stuff being talked about, Unigrid, we're talking about under the hood with data, a lot of good stuff. What's the bottom line? How do you up-level it for the CIO or CXO that's watching or listening, doesn't have time to get in the weeds? >> Well, I think the three fundamental conclusions that we reached this year is that we expect AWS to spend a lot of time talking about AI, both as a generalized way of moving up the stack, as we talked about. Here's the services the developers are going to work with. Here's the tool kits that they're going to utilize, et cetera, to solve more general problems. But also AI being embedded more deeply within AWS and how it runs as a service, and how it integrates and works with other clouds. So AI machine learning for IT operations management through AWS. So AI's going to be a major feature. The second one we think that we're going to hear a lot about is, Amazon's been putting forward this notion that they were going to facilitate migration of Legacy applications into AWS. That's been a slog, but we expect to see a more focused effort by going after specific big software houses, that have large installed bases of on-premise stuff, and see if they can't, with the software house, bring more of that infrastructure, or more of those installations, into AWS. Now, I don't want to call VMware an application house, but not unlike what they did with VMware about a year and a half ago. The last one is that we don't think that Amazon is going to put forward a general purpose IoT Edge solution this year. We think that they're going to reveal further what their approach to those problems are, which is, bigger networks, more PoPs. >> More scale. >> More scale, a lot of additional services for building applications that operate within that framework, but not that kind of, here's what the hybrid cloud by Amazon is going to look like. >> Let's talk about competition in China. Obviously, they kind of go hand in hand. Obviously, Andy Jassy and the Amazon Web Services team are seeing for the first time, massive competition. Obviously Microsoft stocks, I might have mentioned earlier. So you're starting to see the competition wheels cranking. Oracle's certainly been all over Amazon, we know that. Microsoft's just upping their game, trying to catch up, and their numbers are looking good. You got SAP playing the multicloud game. You got Google differentiating on things like TenserFlow and other AI and developer tools. This is interesting. This is the first time Amazon's really had some competition, I won't say nipping at its heels, but putting pressure. It's not the one game in town. People are talking multicloud, kind of talking about lock-in. And then you got the China situation. You got Alibaba, technically the number four cloud by some standards. Some will argue that position. The point is, it's massive. >> Yeah, I think it's by any reasonable standard. They are a big cloud player. >> So let's go through that. China, let's start with China. Amazon just announced, and the news was broken by the Wall Street Journal, who actually got it wrong and didn't correct their story for almost 24 hours. Really kind of screwed up the market, everyone thought that they were selling AWS to China. It was a unique deal. Rob Hof and the team reported and corrected, >> Peter: At SiliconANGLE. >> At siliconangle.com, we got it right, and that is is that it was a $300 million data center deal, not intellectual property, but this is the China playbook. >> They sold their physical assets. They didn't sell their IP. They didn't sell the services or the ability to provide the services. >> Based upon my reporting, and this is again still, the facts on the ground are loose, 'cause China, it's hard to get the data. But from what I can gather, they were already doing business in China. Apple went through this, even though they're hardware, they still have software. Everyone has that standoff, but ultimately getting into China requires a government-owned partner, or a Chinese company. Government-owned is quasi, you could argue that. And then they expand from there. Apple now has, I think, six stores or more in Shanghai and all over China. So this is a growth opportunity for Amazon if they play it right. Thoughts on that? I mean, obviously we cover a lot of the Chinese companies here. >> Well, I don't want to present myself as an expert on this, John. I've been watching, the Silicon Valley ANGLE reporting has been my primary information source. But I think that it's interesting. We talk about hard assets and soft assets. Hard assets are buildings, machines, and in the IT world, it's the hardware, it's the building, et cetera. And when China talks about ownership, they talk about ownership of those assets. And it sounds to me anyway, like AWS has done a very interesting thing, where they said, okay, fine, you want 51% of the hard assets? Have 51% of the hard, have 100% of the hard assets. But we are going to decide what those assets look like, and we are going to continue to own and operate the software that runs on those assets. So it sounds like, through that, they're going to provide a service into China, whatever the underlying hardware assets are running on. Interesting play. >> Well, we get the story right, and the story is, they're going into China, and they had to cut a deal. (laughs) That's the story. >> But for the hard assets. >> For the hard assets, they didn't get intellectual property. I think it's a good deal for Amazon. We'll see, we're going to watch that closely. I'm going to ask Andy Jassy that specific question. Now on the competition. The FUD is off the charts, fear, uncertainty and doubt. You see that in competitive markets, the competition throwing FUD. Sometimes it's really blatantly obvious FUD, sometimes it's just how they report numbers. I've been, not critical, but pointing out that Azure includes Office 365. Well when you start getting down that road, do you bundle in the sales floor as a cloud player? So all these things start to-- >> Peter: Yeah. >> Of course, so what is true cloud? Are people parsing the categories too narrowly, in your opinion? What's the opinion from the research team on, on what is cloud? >> Well, what is cloud? We like to talk about the cloud experience where the data demand's free or business. So the cloud experience is basically, it's self-provisioning, it's a service, it is continuous, and it allows you a range of different options about what assets you do or do not want to own, according to the physical realities, the legal realities, and intellectual property realities of the data that runs your business. So that's kind of what we mean by cloud. So let's talk about a couple of these. First-- >> Hold on, before you get to those, Andy Jassy said a couple years ago, he believes all enterprises will move to the cloud. (laughs) I mean, he was kind of, of course, he's buying 100% Amazon, and Amazon's defined as cloud. But he's kind of referring to that the enterprise on-premise current business model, and the associated technology, will move to cloud. Now, I'm not sure he would agree that the true private cloud is the same as Amazon. But if he cuts a deal with VMware like he did, is that AWS? So will his prediction come true? Ultimately, everyone's saying that will never be full cloud. >> I think this is one of those things where we got to be a little bit careful about trying to read too much into what he said. But here's what we think. Our advice to customers is don't think about moving your enterprise to the cloud, think about moving the cloud to your enterprise. And I think that's the whole basis for the hybrid cloud conversation that we're having. And the reason why we say the cloud experience where your data demands, is that there are physical realities that every enterprise is going to have to deal with, latency, bandwidth. There are legal realities that every enterprise is going to have to deal with. GDPR, what it means to handle privacy and handle data. And then there's finally intellectual property realities that every enterprise is going to have to deal with. Amazon not wanting to sell its IP to a Chinese partner, to comply with Chinese laws. Every business faces these issues. And they're not going to go away. And that's what's going to shape every businesses configuration of how they're using the cloud. >> And by the way, when I did ask him that question, it might have been three years ago. I can't actually remember, I'm losing my mind here. But at that time, cloud was not yet endorsed as the viable way. So he might have been referring to, again, I'm going to ask him this when I see him in my one on one. He might have been referring to old enterprise ways. So I mean-- >> Let's be honest. Amazon has done such an incredible job of making this a real thing. And our opinion is that they're going to continue to grow as fast as the cloud industry, however we define it. What we tend to define, we think that SaaS is going to be a big player, and it's going to be the biggest part of the player. We think Infrastructure as a Service is going to continue to be critically important. We think that the competition for developers is going to heat up in a big way. AI, machine learning, deep learning, all of those things are going to be part of that competition. In our view of things, we're going to see SaaS be much bigger in a few years. We're going to see this notion of true private cloud, which is a cloud experience on-premise with your assets, because you need to control your data in different ways, is going to be bigger than IaaS, but it's all going to be cloud. >> I mean, in all poise, my opinion and what I'm looking for this year, Peter, just to kind of wrap up the segment is, I think, and if you look at Amazon's new ad campaign, the builders, that's a topic that we talked about last year. >> Peter: Developers. >> Developers. We are living in a world where DevOps is now going mainstream. And there are still cultural issues around, what does that actually mean for a business? The personnel, how they operate, and some of the things you guys point out in your true private cloud report, illuminates those things. And that is, whoever can automate and create great tooling for the DevOps culture going forward, whatever that's called, new developers, new normal? Whatever it is, that to me is going to be the competitive landscape. >> Let me parse that slightly, or put it slightly differently. I think everybody put forward this concept of DevOps as, hey, business, redefine yourself around DevOps. And it hasn't gone as well as a lot of people thought it would. I think what's really going to happen, I don't think you're disagreeing with me, John, is that we need to bring more developers into cloud building that cloud experience, building more of the application value, building more of the enterprise value, in cloud. Now that's happening, and they are going to start snapping this DevOps concept into place. But I think it really is going to boil down to, how are developers going to fully embrace the cloud? What's it going to look like? It's going to be multicloud. Let's go back to the competition. Microsoft, you're right, but they're a big SaaS player. Companies are building enormous relations, big contracts, with Microsoft. They're going to be there. Google, last year they couldn't get out of their own way. Diane Greene comes in, we see a much more focused effort. There's some real engineering that's going on for Google Cloud Services, or Platform, that wasn't there before. Google is emerging as a big player. We're having a lot of conversations with users, where they're taking Google very seriously. IBM is still out there, still got some things going on. You've already mentioned Alibaba, Tencent, a whole bunch of other players in the globe. This is going to be a market that's going to be very, very contentious, but Amazon's going to get there first share. >> And I think we pointed out years ago, that DevOps will merge to cloud developers. You nailed it, I think you just said it. Okay, Peter Burris, here for the Amazon Web Service preview. Of course theCUBE will be there with two sets. We're going to have over 75 interviews over the course of 3 days. In the hall, look for theCUBE, if you've watched this video and you want to come by. If you got a ticket, it's sold out. But come by if you have a ticket. We'll be there, in Las Vegas, for Amazon Web Services re:Invent. I'm John Furrier, thanks for watching this CUBE Conversation from Palo Alto. (upbeat techno music)

(upbeat music) >> Announcer: Live from the Javits Center in New York City. It's the Cube. Covering Inforum 2017. Brought to by Infor. >> Welcome back to the cube's coverage of Inforum here at the Javits center in New York City. I'm your host Rebecca Knight along with my co-host Dave Vellante, and Jim Kobielus who is the lead analyst for Wikibon in AI. So guys we're wrapping up day one of this conference. What do we think? What did we learn? Jim you've been, we've been here at the desk, interviewing people, and we've certainly learned a lot from them, but you've been out there talking to people, and off the record I should say. >> Yeah. >> So give us. >> I'm going to name names. >> Yes. >> If I may, I want to clarify something. >> Yeah, okay, sorry. >> I said this morning that the implied valuation was like three point seven, three point eight billion. >> Rebecca: Okay. >> Charles Phillips indicated to us off camera actually it was more like 10 and a half billion. >> Yeah, yeah. >> But I still can't make the math work. So I'm working on that. >> Okay. >> I suspect what's happened, was that a pre debt number. Remember they have a lot of debt. >> Yes. >> So I will figure it out, find out, and report back, okay. >> You do. >> So I just wanted to clarify that. >> Run those numbers okay. >> I'll call George. >> Kay, right, but Jim back to you. What do think is the biggest impression you have of the day in terms of where Infor is? >> Yeah, I've had the better part of this day to absorb the Coleman announcement which of course, ya know AI is one my core focus areas at Wikibon, and it really seems to me that, well Infor's direct competitors are the ERP space of all in cloud it's SAP, it's Oracle, it's Microsoft. They all have AI investments strategies going for in their ERP portfolios. So I was going back, and doing my own research today, just to get my head around where does Coleman put Infor in the race, cause it's a very competitive race. I referred to it this morning maybe a little bit extremely as a war of attrition, but what I think is that Coleman represents a milestone in the development of the ERP cloud, ERP market. Where with SAP, Oracle, and Microsoft, they're all going deep on AI and ERP, but none of them has the comprehensive framework or strategy to AI enable their suites for human augmentation, ya know, natural language processing, conversational UI's, Ya know, recommenders in line to the whole experience of ya know inventory management, and so forth. What infor has done with Coleman is laid out a, more than just a framework and a strategy, but they've got a lot of other assets behind the whole AI first strategy, that I think will put in them in good steady terms of innovating within their portfolio going forward. One of which is they've got this substantial infusion of capital from coke industries of course, and coke is very much as we've heard today at this show very much behind where the infor team under Charles is going with AI enabling everything, but also the Burst team is now on board with it, and the acquisition closed last month Brad Peters spoke this morning, and of course he spoke yesterday at the analyst pre-brief, and so David and I have more than 24 hours to absorb, what they're saying about where Burst fits into this. Burst has AI assets all ready. That, ya know Infor is very much committed to converging the best of what Burst has with where Coleman is going throughout their portfolio. What Infor announced this morning is all of that. Plus the fact that they've already got some Colemanize it's a term I'm using, applications in their current portfolio. So it's not just a future statement of direction. It's all that they've already done. Significant development and productization of Coleman, and they've also announced a commitment Infor with in the coming year, to bring, to introduce Coleman features throughout each of the industry vertical suite, cloud suites, like I said, human augmentation, plus automation, plus assistants, that are ya know, chat bots sort of inline. In other words, Infor has a far more ambitious and I think, potentially revolutionary strategy to really make ERP, to take ERP away from the legacy of protecters that have all been based on deterministic business rules, that a thicket, a rickety thicket of business rules that need to be maintained. Bringing it closer to the future of cognitive applications, where the logic will be in predictive, and deterministic, predictive, data driven algorithms that are continually learning, continually adapting, continually optimizing all interactions and transactions that's the statement of direction that I think that Infor is on the path to making it happen in the next couple of years in a way that will probably force SAP, Oracle, Microsoft to step up their game, and bring their cognitive or AI strategies in portfolios. >> So I want to talk some more about the horse in the track, but I want to still understand what it is. >> Jim: Yes. >> So the competitors are going to say is oh. It's Alexa. Okay, okay it is partially. >> Jim: Yeah sure. It's very reductive that's their job to reduce. >> Yeah you're right, you've lived that world for a while. Actually that was not your job, so. >> If you don't understand technology, you're just some very smart guy who talks a good talk. >> Yeah, okay. >> So, yeah. >> So, okay, so what we heard yesterday in the analyst meeting, and maybe you found this out today, was is conversational UX. >> Yes. >> It's chat wired into the APIs, and that's table stakes. It augments, it automates, an example is early payments versus by cash on hand. Should I take the early payment deal, and take the discount, or, and so it helps decide those decisions, and which can, if you have a lot of volume could be complex, and it advises it uncovers insights. Now what I don't know is how much of the IP is ya know, We'em defense essentially from Amazon, and how much is actual Infor IP, ya know. >> Good question, good question, whether it's all organically developed so far, or whether they've sourced it from partners, is an open issue. >> Question for Duncan Demarro. >> Duncan Demarra, exactly. >> Okay, so who are the horses in the track. I mean obviously there's Google, there's Amazon, there's I guess Facebook, even though they're not competing in the enterprise, there's IMB Watson, and then you mentioned Oracle, and SAP. >> Well, here's the thing. You named at least one of those solution providers, IBM for example, provides obviously a really sophisticated, cognitive AI suite under Watson that is not imbedded however, within an ERP application suite from that vendor. >> No it's purpose built for whatever. >> It's purpose built for stand alone deployment into all manner of applications. What Infor is not doing with Coleman, and they make that very clear, they're not building a stand alone AI platform. >> Which strategy do you like better. >> Do I like? They're both valid strategies. First of all, Infor is very much a sass vendor, going forward in that they don't they haven't given any indications of going into past. I mean that's why they've partnered with Amazon, for example. So it's clear for a sass vendor like Infor going forward to do what they've done which is that they're not going to allow their customers apparently to decouple the Coleman infrastructure from everything else that ya know, Infor makes money on. >> Which for them is the right strategy. >> Yeah, that's the right strategy for them, and I'm not saying it's a bad strategy for anybody who wants to be in Infor's market. >> So what is in Oracle, or in a SAP, or for that matter, a work day do, I mean service now made some AI announcements at their knowledge event. So they're spending money on that. I think that was organic IP, or I don't know maybe they're open swamps AI compenents. >> Sure, sure, A they need to have a cloud data platform that provides the data upon which to build and train the algorithm. Clearly Infor has cast a slot with AWS, ya know, SAP, Microsoft, Orcale, IBM they all have their own cloud platform. So >> And GT Nexus plays into that data corpus or? >> Yeah, cause GT Nexus is very much a commerce network, ya know, and there is EDI for this century, that is a continual free flowing, ever replenishing, pool of data. Upon which to build and train. >> Okay, but I interrupted you. You said number one, you need the cloud platform with data. >> Ya need the conversational UI, you know, the user reductive term chat bots, ya know, digital assistant. You need that technology, and it ya know, it's very much a technology in the works, its' not like. Everybody's building chat bots, doesn't mean that every customer is using them, or that they perform well, but chat bots are at the very heart of a new generation of application development conversational interfaces. Which is why Wikibon, why are are doing a study, on the art of building, and training, and tuning chat bots. Cause they are so fundamental to the UX of every product category in the cloud. >> Rebecca: And only getting more so. >> IOT, right, desk top applications. Everything's going with , moving towards more of a conversational interface, ya know. For starters, so you need a big data cloud platform. You need a chat bot framework, for building and ya know, the engagement, and ya know, the UI and all of that. You need obviously, machine learning, and deep learning capabilities. Ya know, open source. We are looking at a completely open source stack in the middle there for all the data. Ya know, you need obviously things like tenserflow for deep learning. Which is becoming the standard there. Things like Spark, ya know, for machine learning, streaming analytics and so forth. You need all that plumbing to make it happen, but you need in terms of ERP of course, you need business applications, and you need to have a business application stacked to infuse with this capability, and there's only a hardcore of really dominant vendors in that space. >> But the precious commodity seems to be data. >> Yeah. >> Right. >> Precious commodity is data both to build the algorithms, and an ongoing basis to train them. Ya see, the thing is training is just as important as building the algorithms cause training makes all the difference in the world between whether a predictive analytics, ya know ML algorithm actually predicts what it's supposed to predict or doesn't. So without continual retraining of the algorithms, they'll lose their ability to do predictions, and classifications and pattern recognitions. So, ya know, the vendors in the cloud arena who are in a good place are the Googles and the Facebooks, and others who generate this data organically as part of their services. Google's got YouTube, and YouTube is mother load of video and audio and so forth for training all the video analytics, all the speech recognition, everything else that you might want to do, but also very much, ya know, you look at natural language processing, ya know, text data, social media data. I mean everybody is tapping into the social media fire hose to tune all the NLP, ongoing. That's very, very important. So the vendor that can assemble a complete solution portfolio that provides all the data, and also very much this something people often overlook, training the data involves increasingly labeling the data, and labeling needs a hardcore of resources increasingly crowdsource to do that training. That's why companies like Crowd Flower, and Mighty AI, and of course Amazon with mechanical terf are becoming evermore important. They are the go to solution providers in the cloud for training these algorithms to keep them fit for purpose. >> Mmm, alright Rebecca, what are your thoughts as a sort of newbie to Infor. >> I'm a newbie yes, and well to be honest, yes I'm a newbie, and I have only an inch wide, an inch deep understanding of the technology, but one thing that has really resonated with me. >> You fake it really well. >> Well, thank you, I appreciate that, thank you. That I've really taken away from this is the difficulties of implementing this stuff, and this what you hear time and time again. Is that the technology is tough, but it's the change management piece that is what trips up these companies because of personalities who are resistant to it, and just the entrenched ways of doing things. It is so hard. >> Yes, change management, yes I agree, there's so many moving parts in these stacks, it's incredible. >> Rebecca: Yeah. >> If you we just focus on the moving parts that represent the business logic that's driving all of this AI, that's a governance mess in it's own right. Because what you're governing, I mean version controls and so forth, are both traditional business rules that drive all of these applications, application code, plus all of these predictive algorithms, model governance, and so forth, and so on. I mean just making sure that all of that is, you're controlling versions of that. You've got stewards, who are managing the quality of all that. Then it moves in lock step with each other so. >> Rebecca: Exactly. >> So when you change the underlying coding of a chat bot, for example, you're also making sure to continue to refresh and train, and verify that the algorithms that were built along with that code are doing their job, so forth. I'm just giving sort of this meta data, and all of that other stuff that needs to be managed in a unified way within, what I call, a business logic governance framework for cloud data driven applications like AI. >> And in companies that are so big, and where people are so disparately located, these are the biggest challenges that companies are facing. >> Yeah, you're going to get your data scientists in lets say China to build the deep learning algorithms, probably to train them, your probably going to get coders in Poland, or in Uruguay or somewhere else to build the code, and over time, there'll be different pockets of development all around the world, collaborating within a unified like dev ops environment for data science. Another focus for us by the way, dev ops for data science, over time these applications like any application, it'll be year after year, after year of change and change. The people who are building and tuning and tweaking This stuff now probably weren't the people five years ago, as this stuff gets older, who built the original. So you're going to need to manage the end to end life cycle, ya know like documentation, and change control, and all that. It's a dev ops challenge ongoing within a broader development initiative to keep this stuff from flying apart from the sheer complexity. >> Rebecca: Yes. >> So, just I don't Jim, if you can help me answer this, this might be more of a foyer sort of issue, but when we heard from the analyst meeting yesterday, Soma, their chief technical guy, who's been on the Cube before in New Orleans, very sharp dude, Two things that stood out. Remember that architecture slide, they showed? They showed a slide of the XI and the architecture, and obviously they're building on AWS cloud. So their greatest strengths are in my view, any way the achilles heel is here, and one is edge. Let's talk about edge. So edge to cloud. >> Jim : Yes. >> Very expensive to move data into the cloud, and that's where ya know, we heard today that all the analysis is going to be done, we know that, but you're really only going to be moving the needles, presumably, into the cloud. The haystacks going to stay at the edge, and the processing going to be done at the edge, it's going to be interesting to see how Amazon plays there. We've seen Amazon make some moves to the edge with snowball, and greenfield and things like that, and but it just seems that analytics are going to happen at the edge, otherwise it's going to be too expensive. The economic model doesn't favor edge to cloud. One sort of caveat. The second was the complexity of the data pipeline. So we saw a lot of AWS in that slide yesterday. I mean I wrote down dynamo DB, kineses, S3 redshift, I'm sure there's some EC2. These are all discreet sort of one trick pony platforms with a proprietary API, and that data pipeline is going to get very, very complex. >> Flywheel platforms I think when you were talking to Charles Phillips. >> But when you talk to Andy Jasse, he says look we want to have access to primitive access to those APIs. Cause we don't know what the markets going to do. So we have to have control. It's all about control, but that said, it's this burgeoning collection of at least 10 to 15 data services. So the end to end, the question I have is Oracle threw down the gauntlet in cloud. They said they'll be able to service any user request in a 150 milliseconds. What is the end to end performance going to be as that data pipeline gets more robust, and more complicated. I don't know the answer to that, but I think it's something to watch. Can you deliver that in under 150 milliseconds, can Oracle even do that, who knows? >> Well, you can if you deliver more of the actual logic, ya know, machine learning and code to the edge, I mean close the user, close to the point of decision, yes. Keep in mind that the term pipeline is ambiguous here. One one hand, it refers, in many people's minds to the late ya know, the end to end path of a packet for example, from source to target application, but in the context of development or dev ops it refers to the end to end life cycle of a given asset, ya know, code or machine learning, modeling and so forth. In context of data science in the pipeline for data science much of the training the whole notion of training, and machine learning models, say for predictive analysis that doesn't happen in real time in line to actual executing, that happens, Ya know, it happens, but it doesn't need it's not inline in a critical path of the performance of the application much of that will stay in the cloud cause that's massively parallel processing, of ya know, of tensorflow, graphs and so forth. Doesn't need to happen in real time. What needs to happen in real time is that the algorithms like tensorflow that are trained will be pushed to the edge, and they'll execute in increasingly nanoscopic platforms like your smartphone and like smart sensors imbedded in your smart car and so forth. So the most of the application logic, probabilistic ya know, machine learning, will execute at the edge. More of the pipeline functions like model building, model training and so forth, data ingest, and data discovery. That will not happen in real time, but it'll happen in the cloud. It need not happen in the edge. >> Kind of geeky topics, but still one that I wanted to just sort of bring up, and riff on a little bit, but let's bring it back up, and back into sort of. >> And this is the thing there's going to be a lot more to talk about. >> Geeking out Rebecca, we apologize. >> You do indeed, it's okay, it's okay. >> Dave indulges me. >> No, you love it too. >> Of course, no I learn every time I try to describe these things, and get smart people like Jim to help unpack it, and so. >> And we'll do more unpacking tomorrow at two day of Inforum 2017. Well, we will all return. Jim Kobielus, Dave Vellante, I'm Rebecca Knight. We will see you back here tomorrow for day two. (upbeat music)