(upbeat music) >> Announcer: From New York, it's theCUBE. Covering ESCAPE/19. >> Everyone, welcome to theCUBE coverage here in New York City for the ESCAPE Conference 19. This is the inaugural event for multicloud, I think it's the first industry event for, really talking about multicloud and the impact to enterprises and public cloud. My next guest is Steve Mullaney, President and CEO of Aviatrix, storied career in tech, been there done that, seen many waves of innovation. Nicira, Palo Alto Networks, and now Aviatrix. You retired for a while, welcome back! >> I did, yeah, five years, yeah, yeah, yeah. >> Welcome to theCUBE. >> Thank you, thanks for having me. >> It's nice to have you on because I think you have a good perspective on the multicloud because you've been in the industry since the 80s. We've both been broke in at the same time. And we've seen the waves. >> Oh, yeah. >> This wave is bigger than, I think, most of the other waves combined because it brings together so many things, infrastructure, software, cloud scale, and a new modern application environment. And then you complicate everything by throwing IoT out there, edges being pushed to their boundaries, securities equations changed, all this is going on right now, all at the same time. >> No, and that's why I was basically retired for five years, and I was at Nicira, we got bought by VMware, I stayed there for a couple years, and I just said, "Okay, that's it!" I've had a good career and I'm done. And about a year ago, the world changed. And it felt like on a Tuesday morning, I noticed enterprises really, we'd been talking about cloud for 12 years. And five years ago they said, "We're coming in, we're going to do it," but they didn't really mean it. But about a year ago, all in the same day, every enterprise said, "No, now we actually mean it." And I don't know why, I don't know if it was just people retired or just five years of talking about it, they all decided, we're comin' in, and enterprises all moved together. And this wave, as you said, is bigger than, I was around in 1992, in the early 90s, in the movement from mainframe to client server. This is 10 times bigger than that. And more importantly, it's going to happen 10,000 times faster. Because (fingers tapping). What's that? I just deployed 62 data centers around the world. Because if I can leverage the greatest infrastructure built, basic infrastructure of the hyperscalers, AWS, Azure, Google, Alibaba, Oracle, you name it. It's unbelievable the velocity at which you can now start deploying. >> Steve, I think you're onto something big here, and this is why I'm here at this event and why I'm excited, that a lot of the industry thought leaders and practitioners and leaders are doing this event. Small events, inaugural, but I think it has a lot of links. Because there's a lot of tell signs that I like to look at, one is cloud. I've been covering Amazon eight years now, with theCUBE, I've known AWS since it started, and I've done many startups in its launch using AWS. But I've had many conversations with Andy Jassy, one on ones, privately, I got an exclusive coming up for re:Invent with him. I've gotten to know him. It started out, "Everyone's moving to the cloud. "Every data center's not going to exist." And then, you know-- >> Oh, maybe not, yeah, yeah. >> Maybe not, we'll do an output. So I challenged him last year, I said, "Andy, come on, dude, like you were saying like a year ago that." >> Steve: Yeah, it's all AWS or nothing. >> And he said, "John, look I'm not, "I just listen to the customers." And I interviewed him when he did the VMware deal. And he's very customer focused. And when they make these moves with outpost, and I think it's going to be a hybrid message this year at re:Invent, you know it's real. >> Steve: Oh, yeah. >> I think this validates your point, so I got to ask you, what specifically do you see the formula being for multicloud, because certainly everyone's recognized that there's a huge benefit for AWS. But from a scale standpoint, so why not use that? What's going on on the Enterprise on-premise that's making this new thing work? >> I think it all starts with architecture, like anything else. I think right now, enterprises have said, "Okay, we've burned a boat, right? "Now, we're not going to get rid of our data centers, "but in terms of our strategic investment, "we are moving into the cloud. "We are going to leverage "the infrastructure of the hyperscalers. "And whether that is just one hyperscaler, or multiple." And I have not met an enterprise who thinks there only going to be one, right, every single one of them. Now, I don't think they're moving workloads across, I don't think that. I think they see that, I'm going to use Google for AI, I'm going to use AWS because it started there. I'm going to use Azure, for Office 365, and other different things, and everything in infrastructure is always multi. It's never homogeneous, right, it's always that. So I think is going to happen, and I think what people are begging for right now, is, I want to build an architecture that gives me the optionality to be able to deliver a common set of services whether I'm on AWS or multiple clouds. And I want them to be my services and I don't want to have understand the low level abstractions and constructs of each of those clouds, because their all different. One's metric, one's U.S., one's some other weird thing. And I don't have the time, the people, or the resources to be able to do that. Give me a common set of services, that are my services, that I can deploy and abstract away the details of those public clouds. >> Yeah, it's an interesting point there, in fact, I called BS on multicloud last year when it started to kind of rear it's head, I'm like, "Come on, multicloud is bullshit." And I said that on theCUBE. And here's what I meant. Multicloud as an operating model is directionally correct, but the architecture hasn't shown where there's true multicloud. Now, the fact of the matter is, people have Amazon, people have Office and Office 365, that's technically two clouds, >> They're siloed, yeah. >> If they give us Google, that's three clouds. >> I use two or three clouds. >> So, if he have three clouds, I guess they have multiple clouds. But you bring up an interesting point, and going back as a student of the history of tech industry, multi-vendor has been a big deal. >> It is a big deal. >> And like you said, there will be a multi-vendor world, that will happen. The question is how. How do you guys see it happening? >> Well I think what's-- >> Your company is attacking this Aviatrix. >> What's interesting is, so now you think about from a customer perspective which, I do the same thing, same thing with AWS. It's always outside in. Okay, I'm thinking as a enterprise IT person. I'm making the move. Do you believe that your basic infrastructure will lever the hyperscalers, or will you build an on-prem? Everyone says, "I believe that's the way I'm going to go." Great, how do I do that? So, I'm a IT architect, who do I go to to help me? Do I go to CISCO? No. The most shocking thing for me, of the six months I've been at Aviatrix, is that word's never used. It's like it was DEC or IBM in the conversation, when you were talking about client-server, no, why would you? CISCO, Juniper, Arista, any of the networking people, not even in the conversation. VMware, not really in the conversation. So, I don't have any incumbent vendor that I can go to that I used to go to. >> Why aren't they in the conversation? 'Cause of the commodity, they've been extracted away? >> I think it's just because it's the innovation of dilemma. Right, once you're selling a lot of stuff into on-prem, to then go and say, I mean you look at Palo Alto Networks, they're trying to make that transition. Acquiring a bunch of companies, VMware acquiring a bunch of companies. Why are they doing that? Because they know, I got to get off on-prem, everything's going in the cloud. >> So it's a legacy. >> It's a legacy thing, and I think what happens is, there is only one reason, and one reason only, an enterprise customer is not using Aviatrix. 'Cause they never heard of us. That's why, that's the only reason. Once they hear about what they're doing, my God. >> Well, give the plug, talk about the company, what do you guys do-- >> So we deliver, I mean it sounds like I made it up for this conference, but actually this conference was perfect for this. It's networking and security services for the multicloud enterprise. And we're building an architecture, that people can deploy, that will give them this common architecture across all the different clouds. So whether you're just using one cloud or multiple, it doesn't matter, it's the same set of security and networking services. And we do that by embracing and extending the basic constructs that AWS, Google, Azure, and Oracle, and all the other clouds will give you, and to deliver that real enterprise class. Because the other thing we've found is, everyone thinks that the cloud gives you everything and anything you will ever need from networking and security. Let's say AWS, they're going to do everything I need. What the enterprises are figuring out, is once they start going in, what they realize is, it's created for the low-level common basic constructs. And the enterprise starts at, well, I need these BGP feature because guess what, the data center is not going away. And I need more than a hundred route limitations, and I need, all of a sudden there's fifty different limitations AWS will give me. Well, they didn't talk about that! Well, of course they're not going to talk about that. They are just going to go check, check, check, we solve all your problems. As enterprises now move in, with mission critical applications, they're realizing, I need the same level of networking and security services that I had on-prem. I can't get that with the native constructs. So where do I go? That's what we do, so we fill in, we embrace what we can of those constructs, we fill in holes where there are fill in holes. And then we give you the mechanism to be able to orchestrate that across the global network. >> So you operationalize the hyperscale clouds for enterprise, >> Yes. >> that's basically what you do. >> Steve: Exactly, for the enterprise. >> Yeah, exactly. >> On the level that they need. >> So you get the benefits of the cloud, but all those nuances under the cover details like networking and other features you abstract that away and provide an operating model for enterprise compliments. >> And the beautiful thing about it is the velocity, at which we can, we're over the top, effectively over the top. We're integrated into the Cloud Suite, understand what cloud native, we understand all the constructs of accounts, and all the things we need to do. But what we expose to the customer, to the enterprise, is a set of over-the-top services that just work. >> Okay Steve, so I got to ask you, since we are at The Multi-Cloud Conference. What is multicloud, I mean how do you define it, you laid out a pretty compelling architecture of what needs are, levers in the cloud, and on-prem is what Aviatrix does. But what is the definition, how should people understand what is multicloud? >> I think for us, for networking and security in that base, so we're basic infrastructure. We get out there first, right? So, if you're going to build a city, you don't start putting people there first the first thing, if you do it right, is you get sewers, you get electricity, gas, roads, all that. Networking and security, infrastructure, is basic infrastructure goes out first. And you want to create an architecture that's going to live with you for twenty years. You don't want to have to rip up the roads and put the sewers in later. And that architecture needs to be multicloud because, even though you think maybe, most of our customers are 90% AWS right now. But every single one of them say, "But I'm moving to Azure, I'm moving to Google, "I've got retail customers that won't allow me "to put my infrastructure on AWS." Or, "I have machine learning, AI type apps on Google." They all say that same thing. But what they all then say to us, is, "You're going to be the mechanism "upon which I'm going to be able to deploy "this common set of services." So they don't need to know that. >> All right, give an example of a customer you guys have, name a name, we had a customer on stage here-- >> Steve: So, Jefferies. >> John: They did this for a use case. >> Yeah so, Jefferies. Financial Services Institution, lots of requirements, Mark Leon Soon is going to be on stage with me tomorrow. We started working with them about nine months ago. Exactly the same thing, they said, "Okay, you know what? "We need to start moving to the cloud, "we've got to start leveraging the cloud. "But, it's too complicated, right? "Even AWS, says 'Go Build.' "I don't want to go build, I want to consume services. "But they don't have all the service that I needed, "they're too low a level. "They're very high function, high enterprise requirements." So they start using us to orchestrate things, to provide transit networking, to provide egress filtering out to the Internet, we have high performance encryption, AWS will only offer it one gig. We can offer it to 10, 20, 30, 40 gig. So they start deploying, they start realizing all the things we do. Then they go and say, "I want to bring my Palo Alto Networks firewall "into the cloud." When you start looking at that, 'cause then guess what? All my policies, I want the same level that I have on-prem when I'm in the cloud. If I go try to bring in my VM series into AWS the construct that AWS give you, they cause you limitations in performance, in visibility, It's integration hassles, there's performance, sustainability, visibility issues, they force you to use SNAT. And there's all these issues, and they go, "Oh my God, this is a pain in the ass." We solved all that for them. We basically cloudify the VM series for them, so all those limitations go away. So that's just another use case that they use. Now they start looking, and they say, "Okay, now I'm going to start extending into other clouds and I want to use you as the common frame point, the common pane of glass. >> Well Steve, good luck in your venture, you're back in the saddle again. >> Steve: Yeah. >> Another ride here, you feel good about it? >> This is going to be the best, the biggest that I've been, and I was at Palo Alto Networks and VMware Nicira. And this one's going to be bigger than both of those. >> What's your vision for where this is going to be for you, where do you see the company in a few years, what are some of the outcomes you expect to happen? >> Our opportunity, and I look at it as, someone's going to take this opportunity, and the reason I came back is, why not us, someone's going to take it. And the opportunity, honestly, is to become, effectively, what Cisco was in the early 90's. To define the architecture, the networking and the security infrastructure architecture for enterprise customers. They are begging for that right now, that's our opportunity. >> Cloud Interoperability. >> Interoperability, yeah. And so there's so many things that we need to go and do. When you look at also the thing that people are going to say, the operations. So many people think, I want it the same as it was on-prem. I think with the cloud, and across multicloud you can do it right with us, and actually better. Because the visibility that you get is more, than what you get on-prem. >> Well, and the thing that's interesting that's different about this new world that we're talking about is that there is going to be constant improvements in new things which means that the functionality game is going to increase, which means the agility is even more important because the apps are going to have more things to do. >> Yeah. I mean in the end, why do you want to go to cloud? I want to go to cloud 'cause I want it to be self-service and I want agility. I want my developers, I want everybody to be able to do things quicker because all of the sudden they say, "Let's go roll this out", and you want to be able to do it. >> Well, good luck on the new venture, Aviatrix, check 'em out, hot multicloud startup, growing, how many people do you have, put the plug in, >> 100. >> what are you guys looking for, are you hiring, give me a quick plug. >> We just hired a new VP at World Wide Sales, James Winebrenner, who was Viptela CEO, VP Sales in Cisco, hiring a tremendous amount of sales guys right now, we're closing on a $40 million Series C round next week, and we're hiring a lot of people. >> Good luck, we'll be following you Steve, thanks for coming on and sharing your insights. Again, multicloud, this is a shift that's happening, multicloud is just another word for multi-vendor, in a new modern era, this is what it has been in the technology industry, but a whole new world. This is theCUBE coverage here in New York City, ESCAPE/19, I'm John Furrier, thanks for watching. (upbeat music)

(upbeat music) >> Announcer: From New York, it's theCUBE. Covering ESCAPE/19. >> Everyone, welcome to theCUBE coverage here in New York City for the ESCAPE Conference 19. This is the inaugural event for multicloud, I think it's the first industry event for, really talking about multicloud and the impact to enterprises and public cloud. My next guest is Steve Mullaney, President and CEO of Aviatrix, storied career in tech, been there done that, seen many waves of innovation. Nicira, Palo Alto Networks, and now Aviatrix. You retired for a while, welcome back! >> I did, yeah, five years, yeah, yeah, yeah. >> Welcome to theCUBE. >> Thank you, thanks for having me. >> It's nice to have you on because I think you have a good perspective on the multicloud because you've been in the industry since the 80s. We've both been broke in at the same time. And we've seen the waves. >> Oh, yeah. >> This wave is bigger than, I think, most of the other waves combined because it brings together so many things, infrastructure, software, cloud scale, and a new modern application environment. And then you complicate everything by throwing IoT out there, edges being pushed to their boundaries, securities equations changed, all this is going on right now, all at the same time. >> No, and that's why I was basically retired for five years, and I was at Nicira, we got bought by VMware, I stayed there for a couple years, and I just said, "Okay, that's it!" I've had a good career and I'm done. And about a year ago, the world changed. And it felt like on a Tuesday morning, I noticed enterprises really, we'd been talking about cloud for 12 years. And five years ago they said, "We're coming in, we're going to do it," but they didn't really mean it. But about a year ago, all in the same day, every enterprise said, "No, now we actually mean it." And I don't know why, I don't know if it was just people retired or just five years of talking about it, they all decided, we're comin' in, and enterprises all moved together. And this wave, as you said, is bigger than, I was around in 1992, in the early 90s, in the movement from mainframe to client server. This is 10 times bigger than that. And more importantly, it's going to happen 10,000 times faster. Because (fingers tapping). What's that? I just deployed 62 data centers around the world. Because if I can leverage the greatest infrastructure built, basic infrastructure of the hyperscalers, AWS, Azure, Google, Alibaba, Oracle, you name it. It's unbelievable the velocity at which you can now start deploying. >> Steve, I think you're onto something big here, and this is why I'm here at this event and why I'm excited, that a lot of the industry thought leaders and practitioners and leaders are doing this event. Small events, inaugural, but I think it has a lot of links. Because there's a lot of tell signs that I like to look at, one is cloud. I've been covering Amazon eight years now, with theCUBE, I've known AWS since it started, and I've done many startups in its launch using AWS. But I've had many conversations with Andy Jassy, one on ones, privately, I got an exclusive coming up for re:Invent with him. I've gotten to know him. It started out, "Everyone's moving to the cloud. "Every data center's not going to exist." And then, you know-- >> Oh, maybe not, yeah, yeah. >> Maybe not, we'll do an output. So I challenged him last year, I said, "Andy, come on, dude, like you were saying like a year ago that." >> Steve: Yeah, it's all AWS or nothing. >> And he said, "John, look I'm not, "I just listen to the customers." And I interviewed him when he did the VMware deal. And he's very customer focused. And when they make these moves with outpost, and I think it's going to be a hybrid message this year at re:Invent, you know it's real. >> Steve: Oh, yeah. >> I think this validates your point, so I got to ask you, what specifically do you see the formula being for multicloud, because certainly everyone's recognized that there's a huge benefit for AWS. But from a scale standpoint, so why not use that? What's going on on the Enterprise on-premise that's making this new thing work? >> I think it all starts with architecture, like anything else. I think right now, enterprises have said, "Okay, we've burned a boat, right? "Now, we're not going to get rid of our data centers, "but in terms of our strategic investment, "we are moving into the cloud. "We are going to leverage "the infrastructure of the hyperscalers. "And whether that is just one hyperscaler, or multiple." And I have not met an enterprise who thinks there only going to be one, right, every single one of them. Now, I don't think they're moving workloads across, I don't think that. I think they see that, I'm going to use Google for AI, I'm going to use AWS because it started there. I'm going to use Azure, for Office 365, and other different things, and everything in infrastructure is always multi. It's never homogeneous, right, it's always that. So I think is going to happen, and I think what people are begging for right now, is, I want to build an architecture that gives me the optionality to be able to deliver a common set of services whether I'm on AWS or multiple clouds. And I want them to be my services and I don't want to have understand the low level abstractions and constructs of each of those clouds, because their all different. One's metric, one's U.S., one's some other weird thing. And I don't have the time, the people, or the resources to be able to do that. Give me a common set of services, that are my services, that I can deploy and abstract away the details of those public clouds. >> Yeah, it's an interesting point there, in fact, I called BS on multicloud last year when it started to kind of rear it's head, I'm like, "Come on, multicloud is bullshit." And I said that on theCUBE. And here's what I meant. Multicloud as an operating model is directionally correct, but the architecture hasn't shown where there's true multicloud. Now, the fact of the matter is, people have Amazon, people have Office and Office 365, that's technically two clouds, >> They're siloed, yeah. >> If they give us Google, that's three clouds. >> I use two or three clouds. >> So, if he have three clouds, I guess they have multiple clouds. But you bring up an interesting point, and going back as a student of the history of tech industry, multi-vendor has been a big deal. >> It is a big deal. >> And like you said, there will be a multi-vendor world, that will happen. The question is how. How do you guys see it happening? >> Well I think what's-- >> Your company is attacking this Aviatrix. >> What's interesting is, so now you think about from a customer perspective which, I do the same thing, same thing with AWS. It's always outside in. Okay, I'm thinking as a enterprise IT person. I'm making the move. Do you believe that your basic infrastructure will lever the hyperscalers, or will you build an on-prem? Everyone says, "I believe that's the way I'm going to go." Great, how do I do that? So, I'm a IT architect, who do I go to to help me? Do I go to CISCO? No. The most shocking thing for me, of the six months I've been at Aviatrix, is that word's never used. It's like it was DEC or IBM in the conversation, when you were talking about client-server, no, why would you? CISCO, Juniper, Arista, any of the networking people, not even in the conversation. VMware, not really in the conversation. So, I don't have any incumbent vendor that I can go to that I used to go to. >> Why aren't they in the conversation? 'Cause of the commodity, they've been extracted away? >> I think it's just because it's the innovation of dilemma. Right, once you're selling a lot of stuff into on-prem, to then go and say, I mean you look at Palo Alto Networks, they're trying to make that transition. Acquiring a bunch of companies, VMware acquiring a bunch of companies. Why are they doing that? Because they know, I got to get off on-prem, everything's going in the cloud. >> So it's a legacy. >> It's a legacy thing, and I think what happens is, there is only one reason, and one reason only, an enterprise customer is not using Aviatrix. 'Cause they never heard of us. That's why, that's the only reason. Once they hear about what they're doing, my God. >> Well, give the plug, talk about the company, what do you guys do-- >> So we deliver, I mean it sounds like I made it up for this conference, but actually this conference was perfect for this. It's networking and security services for the multicloud enterprise. And we're building an architecture, that people can deploy, that will give them this common architecture across all the different clouds. So whether you're just using one cloud or multiple, it doesn't matter, it's the same set of security and networking services. And we do that by embracing and extending the basic constructs that AWS, Google, Azure, and Oracle, and all the other clouds will give you, and to deliver that real enterprise class. Because the other thing we've found is, everyone thinks that the cloud gives you everything and anything you will ever need from networking and security. Let's say AWS, they're going to do everything I need. What the enterprises are figuring out, is once they stop going in, what they realize is, it's created for the low-level common basic constructs. And the enterprise starts at, well, I need these BGP feature because guess what, the data center is not going away. And I need more than a hundred route limitations, and I need, all of a sudden there's fifty different limitations AWS will give me. Well, they didn't talk about that! Well, of course they're not going to talk about that. They are just going to go check, check, check, we solve all your problems. As enterprises now move in, with mission critical applications, they're realizing, I need the same level of networking and security services that I had on-prem. I can't get that with the native constructs. So where do I go? That's what we do, so we fill in, we embrace what we can of those constructs, we fill in holes where there are fill in holes. And then we give you the mechanism to be able to orchestrate that across the global network. >> So you operationalize the hyperscale clouds for enterprise, >> Yes. >> that's basically what you do. >> Steve: Exactly, for the enterprise. >> Yeah, exactly. >> On the level that they need. >> So you get the benefits of the cloud, but all those nuances under the cover details like networking and other features you abstract that away and provide an operating model for enterprise compliments. >> And the beautiful thing about it is the velocity, at which we can, we're over the top, effectively over the top. We're integrated into the Cloud Suite, understand what cloud native, we understand all the constructs of accounts, and all the things we need to do. But what we expose to the customer, to the enterprise, is a set of over-the-top services that just work. >> Okay Steve, so I got to ask you, since we are at The Multi-Cloud Conference. What is multicloud, I mean how do you define it, you laid out a pretty compelling architecture of what needs are, levers in the cloud, and on-prem is what Aviatrix does. But what is the definition, how should people understand what is multicloud? >> I think for us, for networking and security in that base, so we're basic infrastructure. We get out there first, right? So, if you're going to build a city, you don't start putting people there first the first thing, if you do it right, is you get sewers, you get electricity, gas, roads, all that. Networking and security, infrastructure, is basic infrastructure goes out first. And you want to create an architecture that's going to live with you for twenty years. You don't want to have to rip up the roads and put the sewers in later. And that architecture needs to be multicloud because, even though you think maybe, most of our customers are 90% AWS right now. But every single one of them say, "But I'm moving to Azure, I'm moving to Google, "I've got retail customers that won't allow me "to put my infrastructure on AWS." Or, "I have machine learning, AI type apps on Google." They all say that same thing. But what they all then say to us, is, "You're going to be the mechanism "upon which I'm going to be able to deploy "this common set of services." So they don't need to know that. >> All right, give an example of a customer you guys have, name a name, we had a customer on stage here-- >> Steve: So, Jefferies. >> John: They did this for a use case. >> Yeah so, Jefferies. Financial Services Institution, lots of requirements, Mark Leon Soon is going to be on stage with me tomorrow. We started working with them about nine months ago. Exactly the same thing, they said, "Okay, you know what? "We need to start moving to the cloud, "we've got to start leveraging the cloud. "But, it's too complicated, right? "Even AWS, says 'Go Build.' "I don't want to go build, I want to consume services. "But they don't have all the service that I needed, "they're too low a level. "They're very high function, high enterprise requirements." So they start using us to orchestrate things, to provide transit networking, to provide egress filtering out to the Internet, we have high performance encryption, AWS will only offer it one gig. We can offer it to 10, 20, 30, 40 gig. So they start deploying, they start realizing all the things we do. Then they go and say, "I want to bring my Palo Alto Networks firewall "into the cloud." When you start looking at that, 'cause then guess what? All my policies, I want the same level that I have on-prem when I'm in the cloud. If I go try to bring in my VM series into AWS the construct that AWS give you, they cause you limitations in performance, in visibility, It's integration hassles, there's performance, sustainability, visibility issues, they force you to use SNAT. And there's all these issues, and they go, "Oh my God, this is a pain in the ass." We solved all that for them. We basically cloudify the VM series for them, so all those limitations go away. So that's just another use case that they use. Now they start looking, and they say, "Okay, now I'm going to start extending into other clouds and I want to use you as the common frame point, the common pane of glass. >> Well Steve, good luck in your venture, you're back in the saddle again. >> Steve: Yeah. >> Another ride here, you feel good about it? >> This is going to be the best, the biggest that I've been, and I was at Palo Alto Networks and VMware Nicira. And this one's going to be bigger than both of those. >> What's your vision for where this is going to be for you, where do you see the company in a few years, what are some of the outcomes you expect to happen? >> Our opportunity, and I look at it as, someone's going to take this opportunity, and the reason I came back is, why not us, someone's going to take it. And the opportunity, honestly, is to become, effectively, what Cisco was in the early 90's. To define the architecture, the networking and the security infrastructure architecture for enterprise customers. They are begging for that right now, that's our opportunity. >> Cloud Interoperability. >> Interoperability, yeah. And so there's so many things that we need to go and do. When you look at also the thing that people are going to say, the operations. So many people think, I want it the same as it was on-prem. I think with the cloud, and across multicloud you can do it right with us, and actually better. Because the visibility that you get is more, than what you get on-prem. >> Well, and the thing that's interesting that's different about this new world that we're talking about is that there is going to be constant improvements in new things which means that the functionality game is going to increase, which means the agility is even more important because the apps are going to have more things to do. >> Yeah. I mean in the end, why do you want to go to cloud? I want to go to cloud 'cause I want it to be self-service and I want agility. I want my developers, I want everybody to be able to do things quicker because all of the sudden they say, "Let's go roll this out", and you want to be able to do it. >> Well, good luck on the new venture, Aviatrix, check 'em out, hot multicloud startup, growing, how many people do you have, put the plug in, >> 100. >> what are you guys looking for, are you hiring, give me a quick plug. >> We just hired a new VP at World Wide Sales, James Winebrenner, who was Viptela CEO, VP Sales in Cisco, hiring a tremendous amount of sales guys right now, we're closing on a $40 million Series C round next week, and we're hiring a lot of people. >> Good luck, we'll be following you Steve, thanks for coming on and sharing your insights. Again, multicloud, this is a shift that's happening, multicloud is just another word for multi-vendor, in a new modern era, this is what it has been in the technology industry, but a whole new world. This is theCUBE coverage here in New York City, ESCAPE/19, I'm John Furrier, thanks for watching. (upbeat music)

>> Live from Washington DC, it's theCUBE covering Inforum DC 2018 brought to you by Inforum. >> Well we are back here at Inforum 2018 in Washington DC John Walls with Dave Vellante. We are in the nation's capital and joined right now by Massimo Capoccia who is SVP of Info OS and Rick Rider, product director at for common at Infor. Gentlemen, thanks for joining us, >> Thank you >> Good to see you both. >> Thank you for having us >> Thank you >> Let's start first off good job by the way >> Welcome to keynote.. thanks stage this morning we had some time to shine out there. Your thoughts about the show in general so far? We've been a couple of days in now, how is it going for you? >> Yeah, very very well the customers have received the Infor OS and the technology innovation and what we do with the AI very very well. You know lots of people in the hub, lots of sessions, so lots of interest on the technology innovation for Infor OS and for Infor as well. >> Sure, Rick for you? >> Yeah, its been great, it's been interesting. What we are finding out is getting a lot of this out in front of customers and partners is bringing up some interesting opportunities for us moving forward. So it is not everyday we get the opportunity to get in front of these many people within our network, so it's been great. >> So we'll be hearing from folks Let's talk about AI, especially for those who maybe don't know, haven't embraced it yet. What are the Hesitation, reservations, I mean what are you hearing from them as far as what's going to trigger them to make a decision? >> Yeah, to be honest I think they have been hesitant in the past just because it hasn't really been clear. We have talked about AI in the technology community, it's been hard to define. Some people might in fact define incorrectly, because we are making assumptions about what technology can and can't do. I think what we are uncovering. I feel we've got a pretty unique approach to what we are doing here with Infor OS and common connected to it. We are working directly with customers to identify use cases on how we can apply AI. Rather than just starting at the top and saying, "hey we should be doing all these great things and let's see how we can make it work for our customers." It's kind of we are flipping the script and starting backwards and saying, "hey what are the issues? What are the opportunities the customers have? How can we build the technology using AI to make it meaningful?" So we have business impact they want. And by doing that, I think it's a lot more understandable, it's a lot more relatable, it's a lot more trust able from our customers. >> We from in theCUBE here, watch and observe the ascendancy of the hype and so called big data. And which is sort of moderated now. But in data is plentiful, insights aren't. and so we feel we have come to the conclusion that the innovation recipe, if you will, for the next decade or so, is data, applying machine intelligence, that data and having a cloud to be able to scale it. Having cloud economics to be able to track innovation. You guys seem to have all three >> Yeah >> Of those pieces But AI without the data is just.. I don't know what it is? >> Right? Excited. >> Data without the ability to extract (laughs)...you know insights... What good is it? >> Right >> Yeah. Yeah. >> Then you got to have cloud to scale it. Your thoughts on from a platform perspective with that means? >> Yeah, Absolutely. So I was seeing the interview that you were doing with Charles, says we build this platform from the beginning. And one of the big element is that we have you know, made it possible to synchronize you know real time all this data that the applications will generates, into a single place called the data lake. So when you have the data and data lake then you can do many many things and not only analytics and reporting, which is the classical use case, but now it allows you to do AI. And the difference is we don't have one domain of the data. So some of the vendors have only CRM data or ACM data or financial data. With Infor we have all different domains of data. So we can go from ACM from financials, to asset management, to IoT readings for IoT devices, to ERP and CRM also. So when you combine when you can cross and combine the relationship with this data, then your AI is much more smart and intelligent. When you have only the AI focused on a domain, is less intelligent. So that's actually the power that we do. And our Coleman will take advantage of that, you know that you know rich data lake. >> Okay and we talked a lot to someone earlier about the stack. and that the bottom layer, is the OS >> Yes >> So everybody is familiar with what the operating system does in computer science. How is your OS similar and different? What's the function that it does if we can double-click on that? >> Yeah, so we.. It's in for operating service and we call it a service. Because it's not actually in the database and operating system level, right? So we believe... We are more in the application technology. We are the layer that takes you know the bare technology and makes it usable for a business, for an enterprise. And we build applications on top of it. So what we believe at Infor, when you have an architecture with this composite of a suite of applications. Or even the new Microsoft architecture that developers built. You still have to deliver a uniform user experience, a uniform business process, uniform security and data management and even AI. So if you look at services like Facebook or Netflix, they have maybe the entire Microsoft architecture thousands of that, but the experience is one.alright? Thus what we want to bring it to the enterprise. Infor OS big.. that unify the experience both from the end user and business process, to the enterprises. And we do it for all the cloud suites. Infor OS is all the cloud suites not just one but all of them the same services. >> So, I love the Netflix example, because if you think about digital... digital transformation, digital business. My experience with Netflix is just with Netflix I don't have a... There's no marketing department, sales department service department. I do have a problem, I go to Netflix on my app(laughs) I interact with... >> Absolutely >> So that's... I considered that what's called a product. So Rick, how does this capability get translated into product? >> Yeah. You know one thing that you brought up a lot earlier is, with all this interconnectivity and how we have to package things. So we've got all these different services that OS offer. So we've got the data lake, we've got the API gateway. We've got the integration platform, and... All those pieces is what bring this together to where, we can actually deliver something to our customers. In my case, it's an AI model or it's RPA, because of all these things are packaged together. So they don't actually see what's happening, because it's already packaged for them. >> Okay, so... what I was saying the Charles, you probably you might have seen it, is when we first discovered Infor was like, "What do you guys do?" It wasn't clear exactly what you guys were doing. But he said, and I believe him, was always our vision to have a platform. Now that... the... it's not opaque anymore, the platform is pretty clear. Now you've added the Birst Analytics, you've added Coleman AI on top of that. So you know Andy Jassy AWS always talks about the flywheel effect. So I suspect that you're entering this flywheel phase. What is that phase? What does it kind of mean for you guys, for customers, in terms of innovation? >> Yeah, is a very good question. Actually I worked for years with... We started with this platform, this journey with Charles and we start really with... okay, what's the first first issue. You know, we want to solve the integration promise. We want to give an integration platform. Then we build that. Then we start to say, okay, we want to unify the experience. We build a unified portal with a single sign on. Then we say, okay, we want to unify the data, we build a data lake. So we continue to build out the platform. We are now at the level we have a platform and its unique platform because you can say it fits in one Magic Quadrant. Because yeah, it does the iPass in the past. So with all these magic quadrants. But it doesn't fit in one, it's in all of them, right? So and in... The analyst looks at that and say, Okay, we have a platform doesn't fit in one, if it's in all of them, right? >> The Magic Quadrant is now becoming outdated, because... >> Exactly. >> Because its as you said... I don't need 15 stove pipes... >> Exactly. >> With the stove pipe thinking. >> Exactly. So.. >> With all due respect to my friends at Gartner (laughs) >> But the Fly wheel is... Yeah, the platform is going to become more and more important, relevant. The customers that... you know are in the cloud, are not in the cloud, they will use the platform to get to the cloud. It's going to be a new enabler for those customers are still on premises, to go to the cloud. We the Infor OS is enabler for hybrid process. So some some application can be in the on premises or in the cloud. With the OS they can take the journey and get to the cloud and their own place. >> So architecturally, you don't care. >> We don't care what the application side, >> Okay. But you've certainly done a lot of work to optimize AWS, you know, we're AWS customer, we know it's, it's not trivial, you have to, you know work it. It's simple, developers love it, but to really take advantage of it, integrate it with your processes will take some work. But architectural, you don't care. But it's not. That's not a that's not an offering statement, is it? I mean, today, can I run that multi cloud, run their software anywhere? >> Well >> Doing that? >> Well, today, we have a mix off, we use open source library, but we do utilize AWS, the data lake is built on S3. On AI, we use Laks, or Sagemaker for the training on the models. So we do a lot of AWS, Because it gives you our computing power and any out of the box solution for certain certain pieces. What we do we build interfaces to our application, so that our customers doesn't need to take care of all the plumbing, it's all interconnected and done. So that's, that's one of the power of Infor OS. It brings that application technology layer, between the business application and you know, the basic, you know, technologies >> And the customer doesn't want to think about the plumbing these days, right? >> Right. >> To most customers, infrastructure is irrelevant, you know, again, apologies to my hardware, friends, but they don't care about hardware, right? I mean, >> Yeah. >> It's interesting, Charles said in the keynote yesterday, when we were an onPrem software company, we didn't manage servers for our customers. Customers didn't care really about the server, and any more than they care about the plumbing today, right? >> Right. Yeah. And if I want to relate that to the AI space, all the training, all the science, all the highly computational things that we have to do, customers don't really want to know what that means or how to use that. So what we're actually doing is in conjunction with some of the AI services we're working with, with AWS is we've built a modeling platform to where they're operating in one location. They've got no concept of where this is hosted, what's going on behind the scenes, and then we connect it, we expose an API, and they can do any sort of RPI that they want to. >> So...I mean you are talking about when you talk about your customers, and they don't care about, you know, what's behind the curtain, they just wanted it to handle, maybe something up front, but yet, you have to understand what they can do. Right? You have to understand their potential. So how do you do that, when you're dealing with different companies, different sizes, different priorities, different challenges, they're different technology stages. How do you all address them individually and help them get to that better place? >> Yeah, I think, you know, it's never a one size fits, all right. So we try to give them what we've called citizen developer tool sets in the past. And I've even started to try to say, citizen data science tool set. So how can we make it more consumable by all types of users? So yes, we can provide templates, we can create these things that might work somewhat out of the box. But each one of these customers their data is, is just slightly different than need to make tweaks. So we really want to be able to, you know, provide all that flexibility. And it gets back to we start with our use cases. And then we build from there. So we get all that feedback, and make sure we're making we're hitting those key points. >> So I want to pick up on something you said about citizens, citizen data scientists. I've used that term before in front of data scientists some of them don't like it, right. That denigrates what they do. And it's true, a data scientist is a math whiz, maybe a stats, was there a data hacker they can code, Okay. And that's not every business person, right? Clearly. However, when you think about things like our RPA, I mean, you really want to enable business users. You don't want to repeat the same problem that we had for years with things like decision support, where you had two people in the company that knew how to build a Cube. And you had to have line up with an ask, please can you build my cube, I have a deadline while everybody else does too. Just there wasn't effective. So things like our RPA and low code, citizen data scientists spread that technology throughout. Now, part of that is having a platform that is I vision a studio, whereas a user, I can actually create some kind of process and code that in software, you know, code it. It is something that's repetitive that I don't have to do every day. I do it every day, I do it the same way. Somebody gave the example might have been Soma, I know somebody else, expense report approval? >> Yeah, yeah. Yeah. >> I've never not approved and expense report. I don't crack them open. Look, I don't know, maybe every now and then somebody does. Somebody does, by the way. (laughs) >> (shouts) So don't get any idea here. >> I always press the approval button, right? Why can't a robot do that and look for anomalies and say, Oh, a $300 scotch? That's... >> Yeah Yeah. Absolutely... So is that a capability that you're working on, that you have today. That what I'm envisioning a studio and then I imagine this got some orchestrator... >> Yeah. So yeah, so if you look at throughout all Infor OS, is completely Model Driven. So either you, you build a new integration, or a workflow, or a, an AI model, or a even, we have a platform as a service Mongols, where you build with low code applications. So you can take it to end to end where you you train models in AI, us suppose as an API. You can build your own app on top of it with low code and then, you know, give it to your business users. Very, very simple and in the cloud. You know, in the browser and you can do every customer can do it. So that's very important for us. We work from the beginning with this model to give you know, the tools to everybody, not only an elite of people that can do and then you know, there is the rest of the people that cannot do it. Every new computer science engineer that comes out gets you know, AI out of the box. When I did computer science, Yeah, I got some AI, you know, but it was not really like today. So every everybody can program AI now. And we want to give this tools to every developer and not just went to an elite. >> Yeah. And the workflow prediction model that you've been talking about. If you want to come join us down there, we've actually got a model that we're working on for that exact use case. >> Oh, cool. >> Yeah. So yeah. Giving the ability for those business users, as you say to... it's almost like lowering the barrier to entry to a lot of this AI technology. It's not devaluing or anything, data science, because we've got those advanced tool sets, to where if you want to do something in our studio, bring it over into the Coleman AI platform. You certainly can, we're not devaluing that. But you know, what, if we want to start and take little bites off and you want to give this in the hands of the business users, we've got a great solution for that. >> So this is all the cool stuff. This is stuff that business users care about? I mean, do they... My question is, do people care about what's under the covers? I mean, are they asking you or what's the database? And how does this work? How does that work? Or they just really want to focus on that functionality that they're getting in the business impact? >> Yeah, with the advent of the cloud, you know, people, just those questions like we sh... you know, operating system database, which technology you use? it just went away, right? So people just want to know, the functionality and the value. You know, maybe there are companies that I have more, you know, an IT architects and they want to know, more, you know, that's what they want to go down into the details, then you go into the architecture of the OS, of the application, we integrate with AWS. So we do that as well. We, you know, we talk to customers about it. But most of them, they just want to know, okay, "how can I use this platform to make my business better," right. So it runs the cloud suit, but I now I can connect to other cloud services, I can connect to the other application, I can build my own app and bring it in. So they want that business value immediately. And that's why we built this Infor OS, so that they can run the cloud suite and add business value. >> You guys at last year's analyst meeting, gave a little glimpse of some of the architecture and it was very useful, actually, analysts love that kind of stuff. I didn't get the invite this year, maybe something the some smarmy questions I ask. (laughs) But I found that actually quite impressive in terms of the tech behind it and the RND that you guys are doing there. But ultimately, it comes down to what products you can build and what business impact that has, right? >> Yeah, absolutely. I think where we're heading with this, we really don't have many limitations for what we're seeing right now. We're built in a way to where we can apply to every single industry, every single cloud suite. We have the unique, you know, possibility to where we can go through all these different industries and create these sort of value. So we've got a very unique future ahead of us. >> So. Yeah, So how much better or can you give us an idea of a road map a little bit about what you think Coleman can go? >> Yeah so, we're starting to play in the image recognition space a little bit. Maybe looking at how we can utilize things like drone technology and do inspection reports, those sort of things. It's maybe and at least my opinion, I think others kind of express the same, it's maybe the least developed area and we want to make sure we have something that works for customers the way that they're going to see value immediately. But also we're starting look at edge AI. So how can.... not necessarily just an IoT, but how can we how can we build something in the cloud? How can we create a model, then deploy that for our onprem customers who aren't quite ready, so that they can get that AI experience as well, and that predictive insight. >> It's dvallante@Siliconangle.com Is that right? Your email for the invitation >> David.valante... >> (laughs) to make sure... so what will exchange information later. >> We'll invite you (laughs) >> I'm sure this is not your territory. (laughs) >> Its on me. >> Thanks for joining us. >> Thank you. >> Its been a pleasure. Thank you for the time we appreciate that. Back with more here from Washington DC right after this. You're watching theCUBE.

>> Live from Washington, D.C., it's theCUBE! Covering Inforum D.C. 2018. Brought to you by Infor. >> Well, welcome back to Washington, D.C., We are alive here at the Convention Center at Inforum 18, along with Dave Vellante, I'm John Walls. It's a pleasure now, welcome to theCUBE, Leigh Martin, who is the Senior Director of the Dynamic Science Labs at Infor, and good afternoon to you Leigh! >> Good afternoon, thank you for having me. >> Thanks for comin' on. >> Thank you for being here. Alright, well tell us about the Labs first off, obviously, data science is a big push at Infor. What do you do there, and then why is data science such a big deal? >> So Dynamic Science Labs is based in Cambridge, Massachusetts, we have about 20 scientists with backgrounds in math and science areas, so typically PhDs in Statistics and Operations Research, and those types of areas. And, we've really been working over the last several years to build solutions for Infor customers that are Math and Science based. So, we work directly with customers, typically through proof of concept, so we'll work directly with customers, we'll bring in their data, and we will build a solution around it. We like to see them implement it, and make sure we understand that they're getting the value back that we expect them to have. Once we prove out that piece of it, then we look for ways to deliver it to the larger group of Infor customers, typically through one of the Cloud Suites, perhaps functionality, that's built into a Cloud Suite, or something like that. >> Well, give me an example, I mean it's so, as you think-- you're saying that you're using data that's math and science based, but, for application development or solution development if you will. How? >> So, I'll give you an example, so we have a solution called Inventory Intelligence for Healthcare, it's moving towards a more generalized name of Inventory Intelligence, because we're going to move it out of the healthcare space and into other industries, but this is a product that we built over the last couple of years. We worked with a couple of customers, we brought in their loss and data, so their loss in customers, we bring the data into an area where we can work on it, we have a scientist in our team, actually, she's one of the Senior Directors in the team, Dawn Rose, who led the effort to design and build this, design and build the algorithm underlying the product; and what it essentially does is, it allows hospitals to find the right level of inventory. Most hospitals are overstocked, so this gives them an opportunity to bring down their inventory levels, to a manageable place without increasing stockouts, so obviously, it's very important in healthcare, that you're not having a lot of stockouts. And so, we spent a lot of time working with these customers, really understanding what the data was like that they were giving to us, and then Dawn and her team built the algorithm that essentially says, here's what you've done historically, right? So it's based on historic data, at the item level, at the location level. What've you done historically, and how can we project out the levels you should have going forward, so that they're at the right level where you're saving money, but again, you're not increasing stockouts, so. So, it's a lot of time and effort to bring those pieces together and build that algorithm, and then test it out with the customers, try it out a couple of times, you make some tweaks based on their business process and exactly how it works. And then, like I said, we've now built that out into originally a stand-alone application, and in about a month, we're going to go live in Cloud Suite Financials, so it's going to be a piece of functionality inside of Cloud Suite Financials. >> So, John, if I may, >> Please. >> I'm going to digress for a moment here because the first data scientist that I ever interviewed was the famous Hilary Mason, who's of course now at Cloudera, but, and she told me at the time that the data scientist is a part mathematician, part scientist, part statistician, part data hacker, part developer, and part artist. >> Right. (laughs) >> So, you know it's an amazing field that Hal Varian, who is the Google Economist said, "It's going to be the hottest field, in the next 10 years." And this is sort of proven true, but Leigh, my question is, so you guys are practitioners of data science, and then you bring that into your product, and what we hear from a lot of data scientists, other than that sort of, you know, panoply of skill sets, is, they spend more time wrangling data, and the tooling isn't there for collaboration. How are you guys dealing with that? How has that changed inside of Infor? >> It is true. And we actually really focus on first making sure we understand the data and the context of the data, so it's really important if you want to solve a particular business problem that a customer has, to make sure you understand exactly what is the definition of each and every piece of data that's in all of those fields that they sent over to you, before you try to put 'em inside an algorithm and make them do something for you. So it is very true that we spend a lot of time cleaning and understanding data before we ever dive into the problem solving aspect of it. And to your point, there is a whole list of other things that we do after we get through that phase, but it's still something we spend a lot of time on today, and that has been the case for, a long time now. We, wherever we can, we apply new tools and new techniques, but actually just the simple act of going in there and saying, "What am I looking at, how does it relate?" Let me ask the customer to clarify this to make sure I understand exactly what it means. That part doesn't go away, because we're really focused on solving the customer solution and then making sure that we can apply that to other customers, so really knowing what the data is that we're working with is key. So I don't think that part has actually changed too much, there are certainly tools that you can look at. People talk a lot about visualization, so you can start thinking, "Okay, how can I use some visualization to help me understand the data better?" But, just that, that whole act of understanding data is key and core to what we do, because, we want to build the solution that really answers the answers the business problem. >> The other thing that we hear a lot from data scientists is that, they help you figure out what questions you actually have to ask. So, it sort of starts with the data, they analyze the data, maybe you visualize the data, as you just pointed out, and all these questions pop out. So what is the process that you guys use? You have the data, you've got the data scientist, you're looking at the data, you're probably asking all these questions. You get, of course, get questions from your customers as well. You're building models maybe to address those questions, training the models to get better and better and better, and then you infuse that into your software. So, maybe, is that the process? Is it a little more complicated than that? Maybe you could fill in the gaps. >> Yeah, so, I, my personal opinion, and I think many of my colleagues would agree with me on this is, starting with the business problem, for us, is really the key. There are ways to go about looking at the data and then pulling out the questions from the data, but generally, that is a long and involved process. Because, it takes a lot of time to really get that deep into the data. So when we work, we really start with, what's the business problem that the customer's trying to solve? And then, what's the data that needs to be available for us to be able to solve that? And then, build the algorithm around that. So for us, it's really starting with the business problem. >> Okay, so what are some of the big problems? We heard this morning, that there's a problem in that, there's more job openings than there are candidates, and productivity, business productivity is not being impacted. So there are two big chewy problems that data scientists could maybe attack, and you guys seem to be passionate about those, so. How does data science help solve those problems? >> So, I think that, at Infor, I'll start off by saying at Infor there's actually, I talked about the folks that are in our office in Cambridge, but there's quite a bit of data science going on outside of our team, and we are the data science team, but there are lots of places inside of Infor where this is happening. Either in products that contains some sort of algorithmic approach, the HCM team for sure, the talent science team which works on HCM, that's a team that's led by Jill Strange, and we work with them on certain projects in certain areas. They are very focused on solving some of those people-related problems. For us, we work a little bit more on the, some of the other areas we work on is sort of the manufacturing and distribution areas, we work with the healthcare side of things, >> So supply chain, healthcare? >> Exactly. So some of the other areas, because they are, like I said, there are some strong teams out there that do data science, it's just, it's also incorporated with other things, like the talent science team. So, there's lots of examples of it out there. In terms of how we go about building it, so we, like I was saying, we work on answering the business, the business question upfront, understanding the data, and then, really sitting with the customer and building that out, and, so the problems that come to us are often through customers who have particular things that they want to answer. So, a lot of it is driven by customer questions, and particular problems that they're facing. Some of it is driven by us. We have some ideas about things that we think, would be really useful to customers. Either way, it ends up being a customer collaboration with us, with the product team, that eventually we'll want to roll it out too, to make sure that we're answering the problem in the way that the product team really feels it can be rolled out to customers, and better used, and more easily used by them. >> I presume it's a non-linear process, it's not like, that somebody comes to you with a problem, and it's okay, we're going to go look at that. Okay now, we got an answer, I mean it's-- Are you more embedded into the development process than that? Can you just explain that? >> So, we do have, we have a development team in Prague that does work with us, and it's depending on whether we think we're going to actually build a more-- a product with aspects to it like a UI, versus just a back end solution. Depends on how we've decided we want to proceed with it. so, for example, I was talking about Inventory Intelligence for Healthcare, we also have Pricing Science for Distribution, both of those were built initially with UIs on them, and customers could buy those separately. Now that we're in the Cloud Suites, that those are both being incorporated into the Cloud Suite. So, we have, going back to where I was talking about our team in Prague, we sometimes build product, sort of a fully encased product, working with them, and sometimes we work very closely with the development teams from the various Cloud Suites. And the product management team is always there to help us, to figure out sort of the long term plan and how the different pieces fit together. >> You know, kind of big picture, you've got AI right, and then machine learning, pumping all kinds of data your way. So, in a historical time frame, this is all pretty new, this confluence right? And in terms of development, but, where do you see it like 10 years from now, 20 years from now? What potential is there, we've talked about human potential, unlocking human potential, we'll unlock it with that kind of technology, what are we looking at, do you think? >> You know, I think that's such a fascinating area, and area of discussion, and sort of thinking, forward thinking. I do believe in sort of this idea of augmented intelligence, and I think Charles was talking a little bit about, about that this morning, although not in those particular terms; but this idea that computers and machines and technology will actually help us do better, and be better, and being more productive. So this idea of doing sort of the rote everyday tasks, that we no longer have to spend time doing, that'll free us up to think about the bigger problems, and hopefully, and my best self wants to say we'll work on famine, and poverty, and all those problems in the world that, really need our brains to focus on, and work. And the other interesting part of it is, if you think about, sort of the concept of singularity, and are computers ever going to actually be able to think for themselves? That's sort of another interesting piece when you talk about what's going to happen down the line. Maybe it won't happen in 10 years, maybe it will never happen, but there's definitely a lot of people out there, who are well known in sort of tech and science who talk about that, and talk about the fears related to that. That's a whole other piece, but it's fascinating to think about 10 years, 20 years from now, where we are going to be on that spectrum? >> How do you guys think about bias in AI and data science, because, humans express bias, tribalism, that's inherent in human nature. If machines are sort of mimicking humans, how do you deal with that and adjudicate? >> Yeah, and it's definitely a concern, it's another, there's a lot of writings out there and articles out there right now about bias in machine learning and in AI, and it's definitely a concern. I actually read, so, just being aware of it, I think is the first step, right? Because, as scientists and developers develop these algorithms, going into it consciously knowing that this is something they have to protect against, I think is the first step, for sure. And then, I was just reading an article just recently about another company (laughs) who is building sort of a, a bias tracker, so, a way to actually monitor your algorithm and identify places where there is perhaps bias coming in. So, I do think we'll see, we'll start to see more of those things, it gets very complicated, because when you start talking about deep learning and networks and AI, it's very difficult to actually understand what's going on under the covers, right? It's really hard to get in and say this is the reason why, your AI told you this, that's very hard to do. So, it's not going to be an easy process but, I think that we're going to start to see that kind of technology come. >> Well, we heard this morning about some sort of systems that could help, my interpretation, automate, speed up, and minimize the hassle of performance reviews. >> Yes. (laughs) >> And that's the classic example of, an assertive woman is called abrasive or aggressive, an assertive man is called a great leader, so it's just a classic example of bias. I mentioned Hilary Mason, rock star data scientist happens to be a woman, you happen to be a woman. Your thoughts as a woman in tech, and maybe, can AI help resolve some of those biases? >> Yeah. Well, first of all I want to say, I'm very pleased to work in an organization where we have some very strong leaders, who happen to be women, so I mentioned Dawn Rose, who designed our IIH solution, I mentioned Jill Strange, who runs the talent science organization. Half of my team is women, so, particularly inside of sort of the science area inside of Infor, I've been very pleased with the way we've built out some of that skill set. And, I'm also an active member of WIN, so the Women's Infor Network is something I'm very involved with, so, I meet a lot of people across our organization, a lot of women across our organization who have, are just really strong technology supporters, really intelligent, sort of go-getter type of people, and it's great to see that inside of Infor. I think there's a lot of work to be done, for sure. And you can always find stories, from other, whether it's coming out of Silicon Valley, or other places where you hear some, really sort of arcane sounding things that are still happening in the industry, and so, some of those things it's, it's disappointing, certainly to hear that. But I think, Van Jones said something this morning about how, and I liked the way he said it, and I'm not going to be able say it exactly, but he said something along the lines of, "The ground is there, the formation is starting, to get us moving in the right direction." and I think, I'm hopeful for the future, that we're heading in that way, and I think, you know, again, he sort of said something like, "Once the ground swell starts going in that direction, people will really jump in, and will see the benefits of being more diverse." Whether it's across, having more women, or having more people of color, however things expand, and that's just going to make us all better, and more efficient, and more productive, and I think that's a great thing. >> Well, and I think there's a spectrum, right? And on one side of the spectrum, there's intolerable and unacceptable behavior, which is just, should be zero tolerance in my opinion, and the passion of ours in theCUBE. The other side of that spectrum is inclusion, and it's a challenge that we have as a small company, and I remember having a conversation, earlier this year with an individual. And we talk about quotas, and I don't think that's the answer. Her comment was, "No, that's not the answer, you have to endeavor to reach deeper beyond your existing network." Which is hard sometimes for us, 'cause you're so busy, you're running around, it's like okay it's the convenient thing to do. But you got to peel the onion on that network, and actually take the extra time and make it a priority. I mean, your thoughts on that? >> No, I think that's a good point, I mean, if I think about who my circle is, right? And the people that I know and I interact with. If I only reach out to the smallest group of people, I'm not getting really out beyond my initial circle. So I think that's a very good point, and I think that that's-- we have to find ways to be more interactive, and pull from different areas. And I think it's interesting, so coming back to data science for a minute, if you sort of think about the evolution of where we got to, how we got to today where, now we're really pulling people from science areas, and math areas, and technology areas, and data scientists are coming from lots of places, right? And you don't always have to have a PhD, right? You don't necessary have to come up through that system to be a good data scientist, and I think, to see more of that, and really people going beyond, beyond just sort of the traditional circles and the traditional paths to really find people that you wouldn't normally identify, to bring into that, that path, is going to help us, just in general, be more diverse in our approach. >> Well it certainly it seems like it's embedded in the company culture. I think the great reason for you to be so optimistic going forward, not only about your job, but about the way companies going into that doing your job. >> What would you advise, young people generally, who want to crack into the data science field, but specifically, women, who have clearly, are underrepresented in technology? >> Yeah, so, I think the, I think we're starting to see more and more women enter the field, again it's one of those, people know it, and so there's less of a-- because people are aware of it, there's more tendency to be more inclusive. But I definitely think, just go for it, right? I mean if it's something you're interested in, and you want to try it out, go to a coding camp, and take a science class, and there's so many online resources now, I mean there's, the massive online courses that you can take. So, even if you're hesitant about it, there are ways you can kind of be at home, and try it out, and see if that's the right thing for you. >> Just dip your toe in the water. >> Yes, exactly, exactly! Try it out and see, and then just decide if that's the right thing for you, but I think there's a lot of different ways to sort of check it out. Again, you can take a course, you can actually get a degree, there's a wide range of things that you can do to kind of experiment with it, and then find out if that's right for you. >> And if you're not happy with the hiring opportunities out there, just start a company, that's my advice. >> That's right. (laughing together) >> Agreed, I definitely agree! >> We thank you-- we appreciate the time, and great advice, too. >> Thank you so much. >> Leigh Martin joining us here at Inforum 18, we are live in Washington, D.C., you're watching the exclusive coverage, right here, on theCUBE. (bubbly music)

(upbeat music) >> Live from Orlando, Florida it's theCube, covering Cisco Live 2018. Brought to you by Cisco, NetApp, and theCube's Ecosystem partners. >> Hello everyone and welcome back. It's theCube's exclusive coverage here in Orlando, Florida for Cisco Live 2018. It's day three of three days of live coverage. Go to thecube.net, siliconANGLE.com, to get all of the stories. And of course, I'm here with Stu Miniman, analyst at Wikibon, my co-host for the week. Our next guest is Gary Harrison, Head of Technology Services, Metsi Technologies, welcome to theCube. Thanks for joining us. >> Thank you guys, it's good to be here. >> So, you're in the Cisco Ecosystem, so Stu and I have been talking about this all week. A couple of big trends: open, Cisco's opening up, you've got DevNet success with developers. Cloud is a new architecture, okay. Intent driven architectures are huge. Sounds like outcomes to me, so I hear a lot of these conversations about "what's the outcome?", and then building a technology. So I wanted to get your thoughts on that, from your perspective, what does that mean to you? When you hear that, intent networking, developer community, it sounds a lot like a different Cisco. >> It's a different model. It's changing, I think, the way business processors are today, and getting organizations to understand the process of capturing what they want the infrastructure intent, and their application intent look like. And then understanding how that drives different models for deploying services, as well as the operations behind it. >> You guys do a lot of stuff with customer, I want you to take a minute to explain what you guys do, your company. What are some of the things you guys get involved in? Where are you in the ecosystem? What kinds of projects are you engaging on? >> We're a company, so we're a professional services partner, we're a service only integration partner with Cisco. So it's just through, we don't resell, so we get to focus on purely customer success, and we help enable the channel and the partners directly. And the focus is the Enterprise Cloud Suite. So it's really around helping customers understand how to get the most out of those technologies, how to choose the right element of the cloud suite for the job. >> Gary, so you're in an interesting position, to watch some of the transformations going on in Cisco. We said the old way of measuring Cisco was boxes and ports, and the new way is, you know, software, to open and those things. Since you're not one of the, you know, not in a derogatory way, box sellers, you know, give us your viewpoint as to how Cisco's going through that transformation and how your customers are reacting to that. >> So it's definitely a good shift towards those softer elements of it. And we're seeing the strength of the software and the products that come out, and the capabilities, it's rapidly changing. And you're seeing the increase in the product suite recently, the number of, the move towards analytics and other software to support operational life cycles as well as just the provisioning cycles. I think a challenge for the customers is a lot of complexities introduced. A lot of the new tools out of the box out there. And the difficult question is always how to best use each particular tool to get value for the business. >> Yeah, it's one of the big questions is it used to be, I really understood my network because I built it. I racked it, stacked it, wired it, you know. Configured it in the CLI, today a lot of the pieces of the network you're managing, you don't own. They're in the cloud, they're extending beyond. How do your services and solutions help customers get their arms around this, kind of, multi-cloud world? >> It's always the focus on, I guess, is reducing that complexity. There's a lot you can do with the different software that's out there. And really, to try and step back from just the solo tools, and looking at the cloud stack as a whole, and starting small, starting simple. Identifying those early use cases that will help drive cloud adoption in an organization, and then understanding how the software and the tools benefit them to do that. You know as you say, you can't see inside the software easily. If you're going to bare the infrastructures code, you need a way to make sure that as you build that code and those processors that you keep that visibility into what that softwares meant to be doing for you. >> Gary, on that point, I want to just double down on that concept holistically. We hear that, all week we've heard from interviews, from Cisco executives as customers, that it's the systems view almost, it's not the box view. What does that mean to the customer today, and how far along are your customers in that mindset? Are they there, are they kicking the tires? 'Cause you got to engage on real frontline projects where there's outcomes involved and the plumbing's in place. Okay, so how do you get there without disrupting? Right, that's the question we hear. But so how do I get the holistic view without disrupting the business? What's your thoughts on customer's position on that? >> I think to get the holistic view, it's about the business needs I think embrace that. And understanding, though, it's about delivering applications and services now. And the infrastructures there to support that. And not focus on these infrastructure-centric models. So that's the first journey, is understanding, you know, what are the services that are important to the business, and how those services are involved. And then I think the challenge we see from the customers is actually, you know, intend to your organizational and process challenges. The technology itself is not necessarily all the complexities, it's how that aligns to the organization. And so I think those early wins and those early outcomes are a organization that's aware of those challenges. >> Like almost getting a little stepping stone, you get a little success, you know, don't take a big project. What's your take on road-mapping in that? Because that's challenging. What have you seen for success use cases that customers can take right out of the gate to get this intent thing going? What are some of the low-hanging-fruit opportunities? >> So one thing we focus on, I guess, is changing our engagement model with the customers. It's something we sort, I guess, of pride ourselves on. Is we're a lot more flexible and agile, ourselves, as a, in terms of delivering infrastructure services. So again, we try to communicate to our customers find used cases that deliver value and return on investment early. And focus on delivering that, sort of, one use case. It doesn't matter what it is in the cloud-sect, whether it's through automation of network infrastructure, orchestration of services on top of there. We pick a very clear use case and develop that first, and then once you understand how the technology's stitched together end to end, you can then start to grow that inside the organization. >> Is there any use cases that pop out that you can just point to, anecdotally, that seem to be popular? >> So there's a couple different extremes, so ACI is a massive enabler at the moment. You know, it's really, since SDN's come along it's a catalyst to drive the rest of the cloud change infrastructure. So we have some very specific use cases around automating that infrastructure. Not just what ACI does itself, but to create that automation layer on top of that. So, you know, people are deploying lots of infrastructure, so that's one of the specific use cases we see. >> Gary, I really like what you said about it's changing the engagement model, because it used to be "I'm gonna' roll out a new application, "okay, I need to figure out the plumbing." Now when I look at intent based offerings there, it's really more about I'm building new applications and the network is a critical piece of it, it actually helps me drive some of these new, you know, modern micro architectures there. You've got to, I'm sure, be talking to a little bit of a broader, you know, jobs inside the customer. How does that change your engagement? Who are the roles that you're talking to today? >> Well actually this is what we find, is tools like Cloud Sender, and for me one of it's strengths is it's fine ability to tangibly capture intent in a application blueprint. And I find that's a good way to bring organizations together, because now we have a focal point for your network and infrastructure, your platforms teams, and your application teams to come together. And it provides a common language to talk about it. And that's one of the real strengths we find to start having those conversations with those different teams within the organizations. >> Gary talk about the old way and new way. We always like to kind of break things down in a very simplistic way. And Chuck Robbins, the CEO, on stage said "that's the old way", it looked like an architecture, hey, firewall, I get that. And he's like, some people actually have this today. And he's kind of looking at the modern cloud, obviously the circle with all the different services. So kind of Cisco plug. But from your standpoint, when you talk to customers, what was the older conversations, that you could point to saying "we used to do it this way", this is what we would talk about, these are the meetings we would have, now the shift is towards this. What's the old way, and what's it transforming into, when you actually have those conversations, what is it like? >> So the big difference for the infrastructure projects, where they were projects, they're very traditional waterfall model. You work out what you want to buy, where you want to be, you put a project plan around that and deliver that. But the engagement we have today to say to people, all the importance is in the software. It's the services you're delivering on the software, and the capability to develop in the software. And that's not something out of the box. It's very difficult to say: where do I want to be in six months, or where do I want to be in a year? So again the way we encourage and the way we engage with our customers is to put a roadmap together, but to identify something in a much shorter term that you can deliver. Start delivering something, and then take a more agile approach around it, to come back, review, and re-plan again, and look at what your priorities are. >> What's the role of the solution architect on this, 'cause a lot of the things we're seeing and then we're trying to, kind of, connect the dots here. Holistic roadmaps are interesting, because you've got have to have a foundational architecture. What is the preferred kind of consistent theme you're seeing around architectural decisions? Are there table stakes, are there certain things that are always going to be in flux? How do you view the big picture on the solution architect piece of it? Is there certain things that are must-haves, weight on this? What's your reaction to that? >> I think a solution, I think it's a challenging piece. I think it's probably where you see organizations are probably weaker, is having a cloud-solution architecture function. We still see infrastructure architecture, enterprise architecture, but that solution architecture for the cloud model, I think that's actually more a challenging piece. I don't think there's any obvious answer in what, you know, for the customers we see, there's no common answer. >> That's a really hot area right now. >> Gary, one of the biggest challenges we see in multi-cloud, is no two customers are alike. >> No. >> But through the customers that you're talking to, what are some of the common stumbling blocks or hurdles for really getting, you know, full value out of their solutions that you see from customers today? >> I think it's understanding the end to end life cycle of a service. So we can do a lot with a multi-cloud capabilities, in deploying when an internal infrastructure to external. But the processes have to be the same, with security, compliance, these other aspects that come into it add a lot of complexity. And also it's not just the way the applications and the infrastructure are built, patching life cycles, you know, post-deployment of, you know, virtual images. The way people then update and maintain them and that life cycle around it. And I think it's different in a virtualized world, in a containerized world we see a lot more advancements around it, and multi-cloud is easier. I think it's for people to take their legacy applications and try and move them into a cloud-native scenario, which is a real challenge. >> Gary, pretend that I'm a friend of yours and I come to you and say "hey Gary, you know, "I'm new to this whole intent-based networking thing, what is it?", how would you describe it? What's your definition of, what is intent based networking really mean? >> There's two parts of it: one is to identify somewhere to capture what the definition of your applications and services are, and what that means, and the infrastructure that lies underneath. Say cloud centers one part of it, other organizations may have other models, but it's rather than working two traditional high level design, low level design, and we see your requirements analysis, now capturing that intent in somewhere that's both software consumable and can be software defined. You can use software to push intent in there, and you can consume it through software. And the next major bit of the puzzle is to provide that freedom to the infrastructure layers underneath so they get to decide how they implement that intent. And that's what gives you this multi-cloud freedom, you know, how we're implemented in our public cloud can be different to how we're implemented in the private cloud. The tools, the processes, the infrastructure, the software, can be different, but the outcome that's delivered is the same. >> Yeah it's interesting to show, you mentioned SDN earlier, we see a lot of activity on software defined data center, architectural things, and again, it's challenging because not everything looks the same, but it's super important. But then we hear things like Google Cloud on stage, and we hear Kubernetes, we hear ISTIO, which is a service mesh, so you start to see up the stack, the applications taking, kind of, almost a network services-like mindset. I mean, micro services are basically, have the same feel as networking, but it's more up higher in the stacks. So you've got some really interesting dynamics. You've got the SDN thing going on, and then you've got in the middle of the stack, towards the application, these cool Micro services with cloud native. This is an opportunity for network engineers. I mean, how would you describe to the audience out there the opportunity for a network engineer, or someone who's in the network game, to take advantage of that, this new trend that's coming very fast? >> It's a different model of networking. And again, the good thing about containers is they do provide this very application-centric focus. Networking is now about providing a service for the application sit on there. And Container Frameworks make that very obvious. So I'd say network engineer, it's a good place to understand that model and that ecosystem. And then see how that can be applied to what we've done in virtualization. And as SDN comes along in a more traditional private cloud infrastructure, on top of the data center infrastructure we have today, take some of those models that we learned from things like Container Frameworks and how do we apply them to virtualization. >> That's a great point about the virtualization, it's almost a roadmap to how to understand the impact and interplay between the networks. It really is. Okay final question for you is, you know, Cisco Live this year seems to be different, what's the vibe of the show, what's your, if you had to, for someone who didn't come here that's watching, say "hey, I missed it this year, "heard there's a lot of action, DevNet's got 500,000 developers", what's different about this year for Cisco Live, what's the most important story? Can you share your opinion on what's happening? >> I guess for us, being the definite village, it is about the definite zone. The buzz we're seeing, the people, the types of questions we get asked on the stand now, there's definitely a lot more interest in this development side of it. >> What's some of the questions you're getting? What are the hot topics if you stack ranked them? >> People just want to understand, you know, new trends in software, coding, you know, how can I apply my coding skills to coding the network, or where do I learn about that, and we get asked lots of questions as people pass the stands. >> Gary, thanks so much for coming on theCube, great to see you, thanks for coming on and sharing your commentary here. Appreciate it. >> Thank you very much. >> Alright, this is the live Cube cover day three here at Cisco live, I'm John Furrier, Stu Miniman, we're here breaking all the action down, we'll be back with more. Stay with us for day three coverage. We'll be right back after this short break. (upbeat music)

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

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

>> Announcer: Live from Las Vegas, it's the Cube! Covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. (light, upbeat music) >> Hey, welcome back everyone. We're here live in Las Vegas at the Mandalay Bay. This is the Cube. Silicon Angle's flagship program, where we go out to the events and extract the noise. I'm John Furrier with my co-host Peter Burris, Head of Research at Silicon Angle, Wikibon.com. And our next guest is Steve Krauss, Group Vice President of Product Management for Oracle Marketing Cloud. Great to see you again, welcome back to the cube. >> Thank you John. >> So a lot of great announcements today. I want to just jump into it. First of all, you've got a great job. You've got the product side. You've been busy this year, so congratulations. Some announcements I want to get your reaction to that we saw today. The Adaptive Intelligence, love that. I love how it speaks to the data in motion, real time needs of applications. >> Peter: 150 milliseconds >> 150 milliseconds boot shot. We got that on the queue, so it's on the record. It's going to be good, it's going to be good. And also the chat bot thing, which big fan of chat bots as an illustration of what's coming. Not so much as chat bots by themselves, but it does speak to the new user interactions, the new interfaces, new ways to notify and inform as part of that experience. This is some heavy tech, so I want, the first question is AI. Everyone seems to be washing thereselves. Oh, we've got A.I. >> Yeah, Yeah. >> Well that's just predictive analytics, that's been done before. >> Steve: M-Hmm. But Augmented Intelligence or Artificial Intelligence and Neural Networks have been around for a while. What are you guys doing specifically on the product side? Because this is super exciting announcements, to make Adaptive Intelligence work, what's the key tech? >> Steve: Yeah, Well there's a couple things. In fact, I think often when people talk about AI, they want to go immediately to the algorithms and think that somehow that is the only secret sauce. And the reality is, you know, like a lot of things in the world of computing, you put bad data into one of these things and you get bad results out. You put good data, you get good results. You put better data, that's when things start getting really interesting. And so one of the neat things about the marketing version of Adaptive Intelligence is called Adaptive Intelligence Offers, is that it has the ability to not just take the data that the marketer has, but it can reach into something called the Oracle Data Cloud and get additional data to drive better signal into the AI algorithms to make them run better. So we're bringing a data advantage to the table, and then probably as you've heard from the AI apps people, there's already a heritage at Oracle for building these real time decisioning systems. And so you've got these algorithms that are real time, that can adapt every click, update themselves, make the models go better. If you've tracked data mining for a long time, data mining contests, honestly the winner in second place is usually a very small margin. We think really that data piece is going to be the thing that's going to be the biggest differentiator. Because there's a lot of smart people with really great adaptive algorithms. So we're bringing both to the table. >> John: Okay, data or algorithms, there's always been the chicken in the egg syndrome. >> Yeah. >> Is it algorithms or the data, data or algorithms? A lot of people are voting in the crowd, that conversation we're involved in, data trumps algorithms. >> Steve: I would vote that way as well. I think there's far greater variance in what you can do with data if you collect it in a smart way. And in the case of Oracle, we've assembled this massive data cloud. It's not something someone else can casually do. The reality is with a lot of the algorithms, Google's open sourcing a lot of tents are slow, and so we'll see. I mean, it's not like we are chumps with the algorithms. We take that stuff very seriously, but the data itself just make everything more better. >> John: But the right tool for the right job is the same premise, you articulate for algorithms. Pick your tool, pick your algorithm, but if you don't have the data, you're SOL anyway. >> Peter: As you've mentioned John, the algorithms have been around a long time. What's new is that we now have so many more data sources, so we have data for the first time. >> John: And massive compute. >> And now we have massive compute that can be set up easily, so we actually do something with it. I want to point out, I want to test ya on this, we had Jack Berkowitz on honorly which is the source the 150 millisecond. Jack noted that Oracle aspires to be able to have the right answer anywhere in the world inside 150 milliseconds. Which is an amazing, amazing vision, and for most people who think of the cloud, they think of data flying all over the place. >> Steve: Yeah. For you guys, Jack said something very interesting, and I want to, as a proof point, Jack said, "Yeah but sometimes you don't have to move the data." >> Steve: Yes. >> And one of the advantages that you guys have, I think, which is what I want to test you on, is that by having a relatively complete, installed set of capabilities, you have that primary person data-first person data, and there is an advantage to not having to move it. Could you just articulate that a little bit? What does that... >> John: Is that true? >> First of all, is that true, and what kind of possibilities does that open up for Oracle and Oracle customers if it is true? >> Steve: Well yeah, I think you are onto something. Oracle obviously has the long heritage of having many enterprises and government's data in Oracle systems already in the first place. And those investments have been made. And so when you start talking about, "Let's add to that, let's add applications like Adaptive Intelligence offers." Well instead of saying we have to do these massive data transfers it may well be the case at this point that that data is resident an Oracle data center in the first place, and of course Oracle owns its own data centers. These are all world wide, so there's a bunch of advantages to the Oracle scale here. And one of them is that we don't have to move the mountain. Right? The mountain is already in the Oracle database, and we can go and put these services next to it that allow an ease of integration. And John, we were talking about this before we started here. It matters to make this stuff work fast when its a year long project to see if maybe its going to fly. That's no longer a reasonable thing, and so agility matters. Having the data where you already need it is great. >> John: Well and also the trend is system of record database and mountains of corpuses of stuff that you can tap into which you are pointing out, but also, I believe that the winner of all this will use a term that's used in the cloud industry: Standing Up Apps. >> Steve: Uh-huh. And I think that one of the things that's very clear to me if you look at the SAS marketplace where it's, and I think Mark Hurd said this, "There is no past, it's a SAS." So, in infrastructure, so and you kind of see in the separation, you have to have stuff done in weeks-apps. And I mean literally, not months, weeks. >> Steve: Yeah. >> And I would argue that minutes become it. So with that as a backdrop, how do you look at microservices? Because now, if look at, out of the move the data, so I might want to compose something and send it somewhere else, and move an app to the edge of the network or have a retail lab or do something in email. So now I can compose an app from data here and then move it so that brings up orchestration, microservices, and some of these cloud native concepts. How do you guys deal with that? >> Steve: Yeah, well let me give you the marketing part of this in terms of the Oracle Marketing Cloud. Because there are so many parts of Oracle, they have their own versions. For us, one of the big things we want is to have this concept called Orchestration that says if I'm a marketer, I should be able to reach my customer wherever he or she welcomes my messaging. These days, it no longer is just email. These are people who getting mobile messaging, they're potentially interacting with things like chat bots, it's become very fragmented. And so what Oracle wants to do is provide these Orchestration systems that allow apps plug in some that we build, but others that third parties build. So that as this complexity increases and there's more ways you can communicate, we can keep up with this in an agile way either ourselves or with others who do this really well. So that's one of the theories. >> John: It's the marketing cloud plus it's broader Oracle suite-cloud suite. >> Steve: Beautiful, yes. It's the Oracle Cloud suite which includes Oracle CX. It also includes something that we call the Oracle Marketing App Cloud, which is this third party ecosystem. Because we're Oracle, we have a lot of customers, we have hundreds of companies that say, "Yeah, I would love my stuff to get in the hands of Oracle's customer base." The way I'm going to do it is I'm going to make a turn key integration. So that when they buy it from me, they can just request turn it on for Oracle, and it will, again as you said, "Don't make it weeks, make it minutes." It's minutes when the integration is already done. >> So software business Larry Ellison, founder of Oracle, still around one of the legends of the industry. Larry, if you're watching, you're still hanging around, taking names and kicking butt. Started off with shrink wrap software, then download on the internet, then you SAS, now you have SAS plus coming on. Which is smarter apps, smarter customer experience. So it begs the question on this next journey for customers, it's going to be really cloud all the way right. >> Steve: Yeah. >> So you're going to have to have this cloud component, you guys have a strategy there. Isn't Oracle moving away from, a smarter CX's data by the way, so Oracle's no longer a software company. You're a data company. >> Steve: M-hmm. >> Data is eating the world. Yeah no, software is eating the world, which Marc Andreessen wrote, now data is eating software. >> Steve: Uh-huh. How do you view that because some people say that software is never going to go away. But data is becoming much more of a front burner issue, vis-a-vis just like software was in software development. >> Steve: Sure, well I think some of this is just semantics as where software leave off and data begin. But a great example is the thing you talked about earlier, Adaptive Intelligence, where part of the power of this, what makes it different from what you can get elsewhere is that it comes with data included that is different data then is available from anyone else. And so, in fact, you know Oracle, when it made the big investment in the data cloud, people I think thought, "What are you doing, you just set up a vending machine for data? Is that what Oracle's going to be about?". And the answer there is no. I mean there is a good data business, but where it gets profound is when that strategic asset, all that data, all of the sudden enables new products like Adaptive Intelligence Offers to be fundamentally different than came before. >> John: It's an enabling technology. >> It can be absolutely, yes. >> John: Data is enabling. It brings to life apps and then offers new apps opportunities. That's what you said. >> Steve: Yes, and marking data very much is the fuel for the marketing engine. So you get richer fuel, you will get richer results. >> John: Alright, so we're getting down the weeds here, so bottom line, let's up level it up for the person that's watching and saying, "Hey, I got the message." >> Steve: Yeah. >> "Data is super important." >> Steve: Yeah. Bottom line, what is happening this week here in Modern CX that's important for the person that has to scratch their head, isn't inside the ropes in the industry? What's going off of their world? What should they be thinking about? How should they be planning their life moving forward in this new modern era of marketing? >> Steve: Yeah, so I think the big things announced this week definitely involves things like a new level of being able to do recommendations of offers and products using the Oracle Data Cloud. It involves conversational user interfaces such as the new chat bot's platform. And in the case of the marketing cloud, we've got a series of products that have come out that allow a greater degree of self service for both marketers as well as their stakeholders like sales people. So how does the sales person get the output of a marketing automation system? Sales people aren't necessarily known for assiduously going and looking for marketing assets. We've got some new things around, for example, content portals. We've got some new things around features that let people be more autonomous in getting their own work done rather than needing to go to some other system somewhere. >> John: Awesome. And the customer we had on this morning from Royal Philips, really was the head of CRM. So customer relationship management is not a new concept obviously, you guys have a big chunk of business there in the software side of it. But customer relationship management, that is marketing cloud now >> Steve: M-Hmm. >> and customer experiences. So you're starting to see that really go to the next level. What's the big take away for the person at home? Watching in their businesses as they go on their journeys. How should they be thinking about the customer relationship? >> Peter: Well, that's a big question. I think for a CRM oriented person who maybe started out in something like database marketing, where you had a list, and you somehow try to learn about people on the list, that world has gotten a lot bigger now. Where it used to be you learned about someone once they became your customer. These days, though various advertising technologies, you can learn about people you don't yet know, but you know of their existence. And you can start creating that relationship, hoping to draw them in maybe with ads to the point where they do self identify. So there's this whole front end to CRM that is showing up in ad tech with things like DMP's-Data Management Platforms, that solve the same problem, but do it in these whole other realms. >> John: And new channels. Adaptive Intelligence, I think, is an awesome position. Love that Adaptive Intelligence Apps, Apps being stood up on a platform. You guys have it. >> Steve: Yes. >> Where's the next level? Take us through, you run the product rode map. You know, share with the folks, what's on the road maps? What should they be expecting more from Oracle, where are you going to be doubling down, where's the work you filling the white spaces, and what should they expect of the next year? >> Steve: Sure. Well, at least in my key note this morning which again focused on marketing, we had four themes. One was intelligence, we already talked about that one quite a bit. Another is mobile, and that's not just mobile like chat bots, but it's actually mobilizing the experience of our customers' customers for the marketing. So example of this, we have a product called the Eloqua which lots of email can be sent. They have a new email designer that inherently builds responsively designed emails. So those are the ones you open up on your phone that look good, you open on the desktop they look good. That's how it all should work. Unfortunately, it's not for a lot of folks today. So just having that be part of the tooling, big deal. So that's the mobile part. We talked a bit about self service, that's theme number three. And the fourth theme is actually a bit of a sleeper, it's about taking another pass through some of the core technologies we already have that people use the most, and being able to find... >> John: Like what? >> Maximizer a test and targeting a personalization tool. Used by a lot of our customers, the fundamental thing you do inside maximizer is you live in a campaign designer. And it allows you to adjust various parts of a webpage for testing, targeting, and personalization. We've got an entirely new way to do that that's based on an analysis of what do people do when they use this and how can we shave off some number of clicks per session? How can we make it less error prone when people are deciding what to do? How can we make more performant? You talked about 150 milliseconds, how about if we just eliminate the save button altogether so that anything you do automatically saves in the background. You don't have to reload anything. That kind of stuff comes from watching people use the product and realizing, wow, they're in there all day long. If we can just make all of those things a little better, over a course of a year, that's huge. >> John: So basically, we're looking at the core jewels and the platform and making it simpler, reducing the steps to do things, just end up being more efficient in some of the proven tools. >> Steve: Exactly, and in the speech this morning, we said, "Hey look, we don't talk about this enough." >> John: That's not a sleeper that's good. >> The tendency is to come out here, and we all want to talk about everything that's new like AI and the people who are our actual customers. They're seeing pearls rain from the sky when all of the sudden something that took them 12 minutes to do at a time now takes eight, and they do that 2000 times a year. >> John: I always say it's a great business model by, you know, making things simpler, reducing the time to do things and steps >> Steve: Yeah >> and making things intuitive and easy to use. Which it sounds like you're doing, but now let's talk about the glamor side of it. Because I think AI and chat bots speaks to the future, what other glam do you see happening out there right now? Obviously, AI is hot right now. >> Steve: Yeah, I think the other glam at this point is a little more speculative at least as it applies to my area with marketing like Augmented Reality, Virtual Reality, and so on. There's also internet of things. Certainly that world is changing. There are more devices of various types that can talk to the network. We've got a customer, you may be familiar with it, a sleep number bed company, the ones that have the bed where you can pick your number. That's actually a connected device, and so there's some interesting things that can be done there with careful discretion about what data you're collecting. But when we started thinking about, incidentally, so many things that in the past used to be a inert objects are generating data. That can feed into various applications whether it's marketing or other areas. >> John: And more data's coming in, it's just not stopping. >> And it's great for Oracle because if Oracle is good at anything it's good at dealing with very large scale data. That's been the business for a long time, and the trend won't change. There will continue to be larger and larger scale data. >> Steve, final point, what's the theme of the show this year besides the messaging that you have? What do you seeing that's happening here that's evolving? What's the top story here? >> Steve: Well, you know we did a customer advisory board meeting here for the marketing cloud, and I think if I were going to ask the customers what their top story is, I think their top story is they themselves want to continue becoming more customer centric. Everybody talks about it. Well of course, we should be that way. But so many companies grew up doing things like focusing on the thing we're selling, they're being offer centric. And so organizationally changing, using the technologies like we have so they can create the kinds of experiences, we call them the connected customer experience that they themselves want to have. It's a bit challenge, and so their permissions are to say transform ourselves to be from the tech down to the organizational incentives, truly customer centric. >> John: Steve Krauss, Group Vice President of Product Management Oracle Marketing Cloud. Great to see you. Thanks for sharing the insight of the real road map and all the exciting stuff happening here and your clean up this morning, congratulations. I'm John Furrier and Peter Burris. More live coverage coming up here at the Mandalay Bay in Las Vegas with the Cube after this short break. (live upbeat music)

(upbeat music) [Narrator] Live from Las Vegas. It's the CUBE, covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Welcome back everyone. We're live in Las Vegas here at the Mandalay Bay for Oracle's Modern Customer Experience conference, their second year. This is the CUBE, Silicon ANGLES flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier. My co-host Peter Burris, head of research at Wikibon.com. Our next guest is Jack Berkowitz who's the Vice President of Products and Data Science at Oracle. Well, great to have you on the CUBE. Thanks for coming on. >> Thanks a lot. >> Appreciate it. Love talking to the product guys, getting down and dirty on the products. So, AI is hot this year. It's everywhere. Everyone's got an AI in their product. What is the AI component in your product? >> Well, what we're working on is building truly adaptive experiences for people. So, we have a whole bunch of different techniques and technologies all of it comes together essentially to create a system that amplifies peoples capabilities. That's really the key thing. Two real important components. First of all, it's all about data. Everybody talks about it. Well, what we've put together is, in terms of consumers, is the largest collection of consumer data in the Oracle data cloud. So we take advantage of all that consumer data. We also have a lot of work going on with collecting business data, both Oracle originated data as well as partner data. We're bringing that all that together and it sets the context for the AI. Now on top of that we have not just the latest trends in terms of machine learning or neural networks or things like that, but we're borrowing concepts from advertising, borrowing concepts from hedge funds so that we can make a real-time system. It's all about real-time. >> You mentioned neural networks. A lot of stuff conceptually in computer science has been around literally for decades. What is, from your definition - obviously cloud creates a lot of data out there now, but what is AI these days? Because everyone now is seeing AI as a mainstream term. Even the word metadata, since Snowden's thing, is now a mainstream term. Who would have thought metadata and AI would be talked about at kitchen tables? >> Yeah. >> What is AI from your perspective? >> Yeah, from my perspective it's really about augmenting folks. It's really about helping people do things. So maybe we'll automate some very manual tasks out, right, that will free up people to have more time to do some other things. I don't think it's about replacing people. People are creative. We want to get people back to being creative and people are great at problem solving so let's get them that information. Let's get them aid so they can get back to it. >> And give them options. >> Give them options, exactly. Exactly. You know, if you can free up somebody from having to manipulate spreadsheets and all this other stuff so they can just get the answer and get on with things, people are happier. >> So Oracle is using first-person data and third-person data to build these capabilities, right? >> Jack: Yeah, exactly. >> How is that going to play out? How is Oracle going to go to a customer and say we will appropriately utilize this third-person data in a way that does not undermine your first-person rights or value proposition? >> That's a great question. So, privacy and respect has been sort of the principle we've been driving at here. So there's the mechanics of it. People can opt in. People can opt out. There's all the mechanics and the regulatory side of it but it's really about how do you use these things so that it doesn't feel creepy. How do you do this in a subtle way so that somebody accepts the fact that that's the case? And it's really about the benefit to the person as to whether or not they're willing to make that trade-off. A great example is Waze. Waze I use all the time to get around San Francisco traffic. You guys probably use it as well. Well, guess what? If you really think about it, Waze knows what time I leave the house in the morning, what time I come home. Uber knows that once a month I leave at 2:00 on a Sunday and come back a week later. So, as long as you think about that, I'm getting a benefit from Waze I'm happy to have that partnership with them in terms of my data and they respect it and so therefore it works. >> And that comes back to some of the broader concepts of modern customer experience. It is that quid pro quo that I'll take a little data from you to improve the service that I'm able to provide as measured by the increasing value customer experience that's provided. >> Yeah, that's right. I used to live in London and in London there's these stores where you can go in and that sales guy has been there for like twenty years and you just develop a relationship. He knows you. He knows your kids, and so sure enough, stationary store or whatever it is and he gives you that personal experience. That's a relationship that I've built. That really all we're trying to do with all of this. We're trying to create a situation where people can have relationships again. >> And he's prompted with history of knowing you, just give you a pleasant surprise or experience that makes you go wow. And that's data driven now. So how do you guys do that? Cause this is something that, you know, Mark Heard brought up in his keynote that every little experience in the world is a data touchpoint. >> Jack: Yeah. >> And digital, whatever you're doing, so how do you guys put that in motion for data because that means data's got to be freely available. >> Data's got to be freely available. One of the big things that we brought to bear with the Suite X is that the data is connected and the experiences are connected so really we're talking about adding that connected intelligence on top of that data. So, it's not just the data. In fact we talked about it last night. It's not just the data even from the CX systems from service, but even the feed of what inventory's going on in real-time. So I can tell somebody if something's broken, hey, tell you what. This store has it. You can go exchange it, in real-time. Instead of having to wait for a courier or things like that. So it is that data being connected and the fact that our third-party data, you know this consumer data, is actually connected as well. So we bring that in on the fly with the appropriate context so it just works. >> So one of the new things here is the adaptive intelligence positioning products. What is that and take a minute to explain the features of how that came to be and how it's different from the competition. >> Okay, great. So the products are very purposeful built apps that plug in and amplify Oracle cloud apps and you can actually put in a third-party capability if you happen to have it. So that's the capability and it's got the decision science and machine learning and the data. >> Peter: So give me an example of a product. >> So a product is adaptive intelligence offers which we were showing here. It gives product recommendations, gives promotions, gives content recommendations on websites but also in your email. If you go into the store you get the same stuff and we can then go and activate advertising campaigns to bring in more people based on those successful pick ups of products or promotions. Its a great example. Very constrained use case addressed? >> Peter: Fed by a lot of different data. >> Fed by a lot of different data. The reason why they're adaptive is because they happen in real-time. So this isn't a batch mode thing. We don't calculate it the day before. We don't calculate it a week before or every three hours. It's actually click by click for you, and for you, reacting and re-scoring and re-balancing. And so we can get a wisdom of the crowds going on and an individual reaction, click by click, interaction by interaction. >> This is an important point I think that's nuanced in the industry. You mentioned batch mode which talks about how things are processed and managed to real-time and the big data space is a huge transition whether you're looking at hadoop or in memory or at all the architectures out there from batch data lakes to data in motion they're calling it. >> Yeah, exactly. >> So now you have this free flowing scalable data layers, if you will, every where, so being adaptive means what? Being ready? Being ... >> Being ready is the fundamental principle to getting to being adaptive. Being adaptive is just like this conversation. Being able to adjust, right? And not giving you the same exact answer seven times in a row because you asked me the same question. >> Or if it's in some talking point database you'd pull up from a FAQ. >> Peter: So it adapts to context. >> It's all about adapting to context. If the concepts change, then the system will adopt that context and adapt it's response. >> That's right. And we were showing last night, even in the interaction, as more context is given, the system can then pick that up and spin and then give you what you need? >> The Omni Channel is a term that's not new but certainly is amplified by this because now you have a world certainly with multiple clouds available to customers but also data is everywhere. Data is everywhere and channels are everywhere. >> Data is everywhere. And being adaptive also means customizing something at a point and time >> Exactly. and you might not know what it is up until seconds or near real-time or actually real-time. >> Real time, right? Real human time. 100 milliseconds. 150 milliseconds, anywhere in the world, is what we're striving for. >> And that means knowing that in some database somewhere you checked into a hotel, The Four Seasons, doing a little check in the hotel and now, oh, you left your house on Uber. Oh, you're the CEO of Oracle. You're in a rental car. I'm going to give you a different experience. >> Jack: Yeah. >> Knowing you're a travel warrior, executive. That's kind of what Mark Heard was trying to get to yesterday. >> Yeah, that's what he's getting to. So it's a bit of a journey, right? This is not a sprint. So there's been all this press and you think, oh my god, if I don't have ... It's a journey. It's a bit of a marathon, but these are the experiences that are happening. >> I want to pick up on 150 milliseconds is quite the design point. I mean human beings are not able to register information faster than about 80 milliseconds. >> Jack: Yeah, yeah. So you're talking about two brain cycles coming back to that. >> Jack: Yeah. >> I mean it's an analogy but it's not a bad one. >> Jack: No. >> 150 milliseconds anywhere in the world. That is a supreme design point. >> And it is what we're shooting for. Obviously there's things about networks and everything that have to be worked through but yeah, that responsiveness, but you're seeing that responsiveness at some of the big consumer sites. You see that type of responsiveness. That's what we want to get to. >> So at the risk of getting too technical here, how does multiple cloud integration or hopping change that equation? Is this one of the reasons it's going to drive customers to a tighter relationship with Oracle because it's going to be easier to provide the 150 millisecond response inside the Oracle fabric? >> Yeah, you nailed it. And I don't want to take too many shots at my competitors, but I'm going to. We don't have to move data. I don't have to move my data from me to AWS to some place else, right, Blue Mix, whatever it happens to be. And because we don't have to move data, we can get that speed. And because it's behind the fabric, as you put it, we can get that speed. We have the ability to scale the data centers. We have the data centers located where we need them. Now your recommendations, if you happen to be here today, they're here. They may transition to Sydney if you're in Australia to be able to give you that speed but that is the notion to have that seamless experience for you, even for travelers. >> That's a gauntlet. You just threw down a gauntlet. >> Jack: I did. Yeah. >> And that's what we're going to go compete against. Because what we're competing is on the experience for people. We're not competing on who's got the better algorithm. We're competing on that experience to people and everything about that. >> So that also brings up the point of third-party data because to have that speed certainly you have advantages in your architecture but humans don't care about Oracle and on which server. They care about what's going on on their phone, on their mobile. >> Jack: That's right. >> Okay, so the user, that requires some integration. So it won't be 100 percent Oracle. There's some third-party. What's the architecture, philosophy, guiding principles around integrating third-party data for you guys. Because it's certainly part of the system. It's part of the product, but I don't think it's ... >> So there's third=party data which could be from data partners or Oracle originated data through our Oracle data cloud or the 1500 licensed data partners there and there's also third-party systems. So for example if somebody had Magento Commerce and they wanted to include that into our capability. On the third party systems, we actually have built this around an API architecture or infrastructure using REST and it's basically a challenge I gave my PMs. I said look, I want you to test against the Oracle cloud system. I want you to test against the Oracle on-prem system and I want you to find the leading third-party system. I don't care if it's sales force or anybody else and I want you to test against that and so as long as people can map to the REST APIs that we have, they can have inter-operation with their systems. >> I mean the architectural philosophy is to decouple and make highly cohesive elements and you guys are a big part of that with Oracle as a component. >> Jack: That's right. >> But I'm still going to need to get stuff from other places and so API is a strategy and microservices are all going to be involved with that. >> Yeah, and actually we deployed a full microservice architecture so behind the scenes on that offers one, 19 microservices interplaying and operating. >> But the reality is this is going to be one of the biggest challenges that answers faces is that how we bridge, or how we gateway, cloud services from a lot of different providers is a non-trivial challenge. >> Jack: That's right. >> I remember back early on in my career when we had all these mini computer companies and each one had their own proprietary network on the shop floor for doing cell controllers or finance or whatever it might be and when customers wanted to bring those things together the mini computer companies said, yeah, put a bridge in place. >> Yeah, exactly. >> And along came TCPIP and Cisco and said forget that. Throw them all out. It wasn't the microprocessor that couldn't stick to those mini computer companies. It was TCPIP. The challenge that we face here is how are we going to do something similar because we're not going to bridge these things. The latency and the speed, and you hit the key point, where is the data, is going to have an enormous impact on this. >> That's right. And again, the investments we have been making with the CX Cloud Suite will allow us to do that. Allow us to take advantage with a whole bunch of data right away and the integration with the ODCs, so we couldn't probably have done this two or three years ago because we weren't ready. We're ready now. And now we can start to build it. We can start to take it now up to the next level. >> And to his point about the road map and TCPIP was interesting. We're all historians here. We're old enough to remember those days, but TCPIP standardized the OSI model which was a fantasy of seven layers of open standards if you remember. >> Jack: Seven layers, yep, whew. >> Peter: See we still talk about it. >> What layer are you on? >> But at the time, the proprietary was IBM and DEC owned the network stacks so that essentially leveled off there so the high-water mark was operating at TCPIP. Is there an equivalent analog to that in this world because IF you can almost take what he said and say take it to the cloud and say look at some point in this whatever stack you want to call it, if it is a stack, there has to be a moment of coalescing around something for everybody. And then a point of differentiation. >> So yeah, and again I'm just going to go back - and that's a great question by the way and it's - I'm like thinking this through as I say it, but I'm going to go right back to what I said. It's about people. So if I coalesce the information around that person, whether that person is a consumer or that person's a sales guy or that person's working on inventory management or better yet disaster relief, which is all those things put together. It's about them and about what they need. So if I get that central object around people, around companies then I have something that I can coalesce and share a semantic on. So the semantic is another old seven layer word. I didn't want to say it today but I can have ... >> Disruptive enabler. >> So then what you're saying is that we need a stack, and I use that word prohibitively, but we need a way of characterizing layer seven application so that we have ... >> Or horizontal >> Either way. But the idea is that we need to get more into how the data gets handled and not just how the message gets handled. >> Jack: That's right. >> OSI's always focused on how the message got handled. Now we're focused on how the data gets handled given that messaging substraight and that is going to be the big challenge for the industry. >> Jack: Yeah. >> Well, certainly Larry Ellis is going to love this conversation, OSI, TCPIP, going old school right here. >> Jack: Like you said, we're all old and yeah, that's what we grew up in. >> Yeah, but this is definitely ... >> Hey, today's computers and today's notions are built on the shoulders of giants. >> Well the enabling that's happening is so disruptive it's going to be a 20 or 30 year innovation window and we're just at the beginning. So the final question I have for you Jack is summarize for the folks watching. What is the exciting things about the AI and the adaptive intelligence announcements and products that you guys are showing here and how does that go forward into the future without revealing any kind of secrets on Oracle like you're a public company. What's the bottom line? What's the exciting thing they should know about? >> I think the exciting thing is that they're going to be able to take advantage of these technologies, these techniques, all this stuff, without having to hire a thousand data scientists in a seven month program or seven year program to take advantage of it. They're going to be able to get up and running very, very quickly. They can experiment with it to be able to make sure that it's doing the right thing. From a CX company, they can get back to doing what they do which is building great product, building great promotions, building a great customer service experience. They don't have to worry about gee, what's our seven year plan for building AI capabilities? That's pretty exciting. It lets them get back to doing what they do which is to compete on their products. >> And I think the messaging of this show is really good because you talk about empowerment, the hero. It's kind of gimmicky but the truth is what cloud has shown in the world is you can offload some of those mundane stuff and really focus on the task at hand, being creative or building solutions, or whatever you're doing. >> Yeah. Mark was talking about it. You have this much money to spend, what's my decision to spend it on. Spend it on competing with your products. >> All right, Jack Berkowitz live here inside the CUBE here at Oracle's Modern Customer Experience, talking about the products, the data science, AI's hot. Great products. Thanks for joining us. Appreciate it. Welcome to the CUBE and good job sharing some great insight and the data here. I'm John Furrier with Peter Burris. We'll be back with more after this short break. (upbeat music)

>> Hey, welcome back everybody. Jeff Rick here with the Cube. We are live in downtown San Jose at the historic Pagoda Lounge, part of Big Data SV, which is part of Strata + Hadoop Conference, which is part of Big Data Week because everything big data is pretty much in San Jose this week. So we're excited to be here. We're here with George Gilbert, our big data analyst from Wikibon, and a great guest, Gaurav Dhillon, Chairman and CEO of SnapLogic. Gaurav, great to see you. >> Pleasure to be here, Jeff. Thank you for having me. George, good to see you. >> You guys have been very busy since we last saw you about a year ago. >> We have. We had a pretty epic year. >> Yeah, give us an update, funding, and customers, and you guys have a little momentum. >> It's a good thing. It's a good thing, you know. A friend and a real mentor to us, Dan Wormenhoven, the Founder and CEO of NetApp for a very long time, longtime CEO of NetApp, he always likes to joke that growth cures all startup problems. And you know what, that's the truth. >> Jeff: Yes. >> So we had a scorching year, you know. 2016 was a year of continuing to strengthen our products, getting a bunch more customers. We got about 300 new customers. >> Jeff: 300 new customers? >> Yes, and as you know, we don't sell to small business. We sell to the enterprise. >> Right, right. >> So, this is the who's who of pharmaceuticals, continued strength in high-tech, continued strength in retail. You know, all the way from Subway Sandwich to folks like AstraZeneca and Amgen and Bristol-Myers Squibb. >> Right. >> So, some phenomenal growth for the company. But, you know, we look at it very simply. We want to double our company every year. We want to do it in a responsible way. In other words, we are growing our business in such a way that we can sail over to cash flow break-even at anytime. So responsibly doubling your business is a wonderful thing. >> So when you look at it, obviously, you guys are executing, you've got good products, people are buying. But what are some of the macro-trends that you're seeing talking to all these customers that are really helping push you guys along? >> Right, right. So what we see is, and it used to be the majority of our business. It's now getting to be 50/50. But still I would say, historically, the primary driver for 2016 of our business was a digital transformation at a boardroom level causing a rethinking of the appscape and people bringing in cloud applications like Workday. So, one of the big drivers of our growth is helping fit Workday into the new fabric in many enterprises: Vassar College, into Capital One, into finance and various other sectors. Where people bring in Workday, they want to make that work with what they have and what they're going to buy in the future, whether it's more applications or new types of data strategies. And that is the primary driver for growth. In the past, it was probably a secondary driver, this new world of data warehousing. We like to think of it as a post-modern era in the use of data and the use of analytics. But this year, it's trending to be probably 50/50 between apps and data. And that is a shift towards people deploying in the same way that they moved from on-premise apps to SAS apps, a move towards looking at data platforms in the cloud for all the benefits of racking and stacking and having the capability rather than being in the air-conditioning, HVAC, and power consumption business. And that has been phenomenal. We've seen great growth with some of the work from Microsoft Azure with the Insights products, AWS's Redshift is a fantastic growth area for us. And these sorts of technologies, we think are going to be of significant impact to the everyday, the work clothing types of analytics. Maybe the more exotic stuff will stay on prem, but a lot of the regular business-like stuff, you know, stuff in suits and ties is moving into the cloud at a rapid pace. >> And we just came off the Google Next show last week. And Google really is helping continue to push kind of ML and AI out front. And so, maybe it's not the blue suit analytics. >> Gaurav: Indeed, yes. >> But it does drive expectations. And you know, the expectations of what we can get, what we should get, what we should be moving towards is rapidly changing. >> Rapidly changing, for example, we saw at The New York Times, which as many of Google's flagship enterprise customers are media-related. >> Jeff: Right. >> No accident, they're so proficient themselves being in the consumer internet space. So as we encountered in places like The New York Times, is there's a shift away from a legacy data warehouse, which people like me and others in the last century, back in my time in Informatica, might have sold them towards a cloud-first strategy of using, in their case, Google products, Bigtable, et cetera. And also, they're doing that because they aspirationally want to get at consumer prices without having to have a campus and the expense of Google's big brain. They want to benefit from some of those things like TensorFlow, et cetera, through the machine learning and other developer capabilities that are now coming along with that in the cloud. And by the way, Microsoft has amazing machine learning capability in its Azure for Microsoft Research as well. >> So Gaurav, it's interesting to hear sort of the two drivers. We know PeopleSoft took off starting with HR first and then would add on financials and stumble a little bit with manufacturing. So, when someone wants to bring in Workday, is it purely an efficiency value prop? And then, how are you helping them tie into the existing fabric of applications? >> Look, I think you have to ask Dave or Aneel or ask them together more about that dynamic. What I know, as a friend of the firm and as somebody we collaborate with, and, you know, this is an interesting statistic, 20 percent of Workday's financial customers are using SnapLogic, 20 percent. Now, it's a nascent business for them and you and I were around in the last century of ERP. We saw the evolution of functional winners. Some made it into suites and some didn't. Siebel never did. PeopleSoft at least made a significant impact on a variety of other things. Yes, there was Bonn and other things that prevented their domination of manufacturing and, of course, the small company in Walldorf did a very good job on it too. But that said, what we find is it's very typical, in a sense, how people using TIBCO and Informatica in the last century are looking at SnapLogic. And it's no accident because we saw Workdays go to market motion, and in a sense, are following, trying to do the same thing Dave and Aneel have done, but we're trying to do the same thing, being a bunch of ex-Informatica guys. So here's what it is. When you look at your legacy installation, and you want to modernize it, what are your choices? You can do a big old upgrade because it's on-premise software. Or you can say, "You know what? "For 20% more, I could just get the new thing." And guess what? A lot of people want to get the new thing. And that's what you're going to see all the time. And that's what's happening with companies like SnapLogic and Workday is, you know, someone. Right here locally, Adobe, it's an icon in technology and certainly in San Jose that logo is very big. A few years ago, they decided to make the jump from legacy middleware, TIBCO, Informatica, WebMethods, and they've replaced everything globally with SnapLogic. So in that same way, instead of trying to upgrade this version and that version and what about what we do in Japan, what do we do in Sweden, why don't you just find a platform as a service that lets you elevate your success and go towards a better product, more of a self-service better UX, millennial-friendly type of product? So that's what's happening out there. >> But even that three-letter company from Walldorf was on-stage last week. You can now get SAP on the Google Cloud Platform which I thought was pretty amazing. And the other piece I just love but there's still a few doubters out there on the SAS platform is now there's a really visual representation. >> Gaurav: There is. >> Of the dominance of that style going up in downtown San Francisco. It's 60 stories high, and it's taken over the landscape. So if there's ever any a doubt of enterprise adaptation of SAS, and if anything, I would wonder if kind of the proliferation of apps now within the SAS environment inside the enterprise starts to become a problem in and of its own self. Because now you have so many different apps that you're working on and working. God help if the internet goes down, right? >> It's true, and you know, and how do you make e pluribus unim, out of many one, right? So it's hilarious. It is almost at proliferation at this point. You know, our CFO tapped me the other day. He said, "Hey, you've got to check this out." "They're using a SAS application which they got "from a law firm to track stock options "inside the company." I'm like, "Wow, that is a job title and a vertical." So only high growth private venture backed companies need this, and typically it's high tech. And you have very capable SAS, even in the small grid squares in the enterprise. >> Jeff: Right, right. >> So, a sign, and I think that's probably another way to think about the work that we do at SnapLogic and others. >> Jeff: Right, right. >> Other people in the marketplace like us. What we do essentially is we give you the ERP of one. Because if you could choose things that make sense for you and they could work together in a very good way to give you very good fabric for your purposes, you've essentially bought a bespoke suit at rack prices. Right? Without that nine times multiplier of the last century of having to have just consultants without end, darkened the sky with consultants to make that happen. You know? So that, yes, SAS proliferation is happening. That is the opportunity, also the problem. For us, it's an opportunity where that glass is half-full we come in with SnapLogic and knit it together for you to give you fabric back. And people love that because the businesses can buy what they want, and the enterprise gets a comprehensive solution. >> Jeff: Right, right. >> Well, at the risk of taking a very short tangent, that comment about darkening the skies, if I recall, was the battle of the Persians threatening the 300 Greeks at the battle of Thermopylae. >> Gaurav: Yes. >> And they said, "We'll darken the skies with our arrows." And so the Greek. >> Gaurav: Come and get 'em. >> No, no. >> The famous line was, he said, "Give us your weapons." And the guy says, "Come and get 'em." (laughs) >> We got to that point, the Greek general says, "Well, we'll fight in the shade." (all laughing) But I wanted to ask you. >> This is the movie 300 as well, right? >> Yes. >> The famous line is, "Give us your weapons." He said, "Come and get 'em." (all laughing) >> But I'm thinking also of the use case where a customer brings in Workday and you help essentially instrument it so it can be a good citizen. So what does that make, or connect it so it can be a good citizen. How much easier does that mean or does that make fitting in other SAS apps or any other app into the fabric, application fabric? >> Right, right. Look, George. As you and I know, we both had some wonderful runs in the last century, and here we are doing version 2.0 in many ways, again, very similar to the Workday management. The enterprise is hip to the fact that there is a Switzerland nature to making things work together. So they want amazing products like Workday. They want amazing products like the SAP Cloud Suite, now with Concur, SuccessFactors in there. Some very cool things happening in the analytics world which you'll see at Sapphire and so on. So some very, very capable products coming from, I mean, Oracle's bought 80 SAS companies or 87 SAS companies. And so, what you're seeing is the enterprise understands that there's going to be red versus blue and a couple other stripes and colors and that they want their businesspeople to buy whatever works for them. But they want to make them work together. All right? So there is a natural sort of geographic or structural nature to this business where there is a need for Switzerland and there is a need for amazing technology, some of which can only come from large companies with big balance sheets and vertical understanding and a legacy of success. But if a customer like an AstraZeneca where you have a CIO like Dave Smoley who transformed Flextronics, is now doing the same thing at AstraZeneca bringing cloud apps, is able to use companies like SnapLogic and then deploy Workday appropriately, SAP appropriately, have his own custom development, some domestic, some overseas, all over the world, then you've got the ability again to get something very custom, and you can do that at a fraction of the cost of overconsulting or darkening the skies in the way that things were done in the last century. >> So, then tell us about maybe the convergence of the new age data warehousing, the data science pipeline, and then this bespoke collection of applications, not bespoke the way Oracle tried it 20 years ago where you had to upgrade every app tied into every other app on prem, but perhaps the integration, more from many to one because they're in the cloud. There's only one version of each. How do you tie those two worlds together? >> You know, it's like that old bromide, "Know when to hold 'em. "Know when to fold them." There is a tendency when programming becomes more approachable, you have more millennials who are able to pick up technology in a way. I mean, it's astounding what my children can do. So what you want to do is as a enterprise, you want to very carefully build those things that you want to build, make sure you don't overbuild. Or, say, if you have a development capability, then every problem looks like a development nail and you have a hammer called development. "Let's hire more Java programmers." That's not the answer. Conversely, you don't want to lose sight of the fact that to really be successful in this millennium, you have to have a core competence around technology. So you want to carefully assemble and build your capability. Now, nobody should ever outsource management. That's a bad idea. (chuckles) But what you want to do is you want to think about those things that you want to buy as a package. Is that a core competence? So, there are excellent products for finance, for human capital management, for travel expense management. Coupa just announced today their for managing your spend. Some of the work at Ariba, now the Ariba Cloud at SAP, are excellent products to help you do certain job titles really well. So you really shouldn't be building those things. But what you should be doing is doing the right element of build and buy. So now, what does that mean for the world of analytics? In my view, people building data platforms or using a lot of open source and a lot of DevOps labor and virtualization engineering and all that stuff may be less valuable over time because where the puck is going is where a lot of people should skate to is there is a nature of developing certain machine language and certain kind of AI capabilities that I think are going to be transformational for almost every industry. It is hard to imagine anything in a more mechanized back office, moving paper, manufacturing, that cannot go through a quantum of improvement through AI. There are obviously moral and certain humanity dystopia issues around that to be dealt with. But what people should be doing is I think building out the AI capabilities because those are very custom to that business. Those have to do with the business's core competence, its milieu of markets and competitors. But there should be, in a sense, stroking a purchase order in the direction of a SAS provider, a cloud data provider like Microsoft Azure or Redshift, and shrinking down their lift-and-shift bill and their data center bill by doing that. >> It's fascinating how long it took enterprises to figure out that. Just like they've been leveraging ADP for God knows how many years, you know, there's a lot of other SAS applications you can use to do your non-differentiated heavy lifting, but they're clearly all in now. So Gaurav, we're running low on time. I just want to say, when we get you here next year, what's top of your plate? What's top of priorities for 2017? Cause obviously you guys are knocking down things left and right. >> Thank you, Jeff. Look, priority for us is growth. We're a growth company. We grow responsibly. We've seen a return to quality on the part of investors, on the part of public and private investors. And you know, you'll see us continue to sort of go at that growth opportunity in a manner consistent with our core values of building product with incredible success. 99% of our customers are new to our products last quarter. >> Jeff: Ninety-nine percent? >> Yes sir. >> That says it all. >> And in the world of enterprise software where there's a lot of snake oil, I'm proud to say that we are building new product with old-fashioned values, and that's what you see from us. >> Well 99% customer retention, you can't beat that. >> Gaurav: Hard to beat! There's no way but down from there, right? (laughing) >> Exactly. Alright Gaurav, well, thanks. >> Pleasure. >> For taking a few minutes out of your busy day. >> Thank you, Jeff. >> And I really appreciate the time. >> Thank you, Jeff, thank you, George. >> Alright, he's George Gilbert. I'm Jeff Rick. You're watching the Cube from the historic Pagoda Lounge in downtown San Jose. Thanks for watching.