>> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the CloudNative Computing Foundation, and Ecosystem Partners. >> Hi and welcome back to theCUBE's coverage of KubeCon, CloudNativeCon 2020 in Europe, of course the virtual edition. I'm Stu Miniman and happy to welcome back to the program one of the keynote speakers, he's also a board member of the CNCF, Vijoy Pandey who is the vice president and chief technology officer for Cloud at Cisco. Vijoy, nice to see you and thanks so much for joining us. >> Thank you Stu, and nice to see you again. It's a strange setting to be in but as long as we are both health, everything is good. >> Yeah, it's still a, we still get to be together a little bit even though while we're apart, we love the engagement and interaction that we normally get through the community but we just have to do it a little bit differently this year. So we're going to get to your keynote. We've had you on the program to talk about "Network, Please Evolve", been watching that journey. But why don't we start it first, you know, you've had a little bit of change in roles and responsibility. I know there's been some restructuring at Cisco since the last time we got together. So give us the update on your role. >> Yeah, so that, yeah let's start there. So I've taken on a new responsibility. It's VP of Engineering and Research for a new group that's been formed at Cisco. It's called Emerging Tech and Incubation. Liz Centoni leads that and she reports into Chuck. The role, the charter for this team, this new team, is to incubate the next bets for Cisco. And, if you can imagine, it's natural for Cisco to start with bets which are closer to its core business, but the charter for this group is to mover further and further out from Cisco's core business and takes this core into newer markets, into newer products, and newer businesses. I am running the engineering and research for that group. And, again, the whole deal behind this is to be a little bit nimble, to be a little startupy in nature, where you bring ideas, you incubate them, you iterate pretty fast and you throw out 80% of those and concentrate on the 20% that make sense to take forward as a venture. >> Interesting. So it reminds me a little bit, but different, I remember John Chambers a number of years back talking about various adjacencies, trying to grow those next, you know, multi-billion dollar businesses inside Cisco. In some ways, Vijoy, it reminds me a little bit of your previous company, very well known for, you know, driving innovation, giving engineering 20% of their time to work on things. Give us a little bit of insight. What's kind of an example of a bet that you might be looking at in the space? Bring us inside a little bit. >> Well that's actually a good question and I think a little bit of that comparison is, are those conversations that taking place within Cisco as well as to how far out from Cisco's core business do we want to get when we're incubating these bets. And, yes, my previous employer, I mean Google X actually goes pretty far out when it comes to incubations. The core business being primarily around ads, now Google Cloud as well, but you have things like Verily and Calico and others which are pretty far out from where Google started. And the way we are looking at these things within Cisco is, it's a new muscle for Cisco so we want to prove ourselves first. So the first few bets that we are betting upon are pretty close to Cisco's core but still not fitting into Cisco's BU when it comes to go-to-market alignment or business alignment. So while the first bets that we are taking into account is around API being the queen when it comes to the future of infrastructure, so to speak. So it's not just making our infrastructure consumable as infrastructure's code, but also talking about developer relevance, talking about how developers are actually influencing infrastructure deployments. So if you think about the problem statement in that sense, then networking needs to evolve. And I talked a lot about this in the past couple of keynotes where Cisco's core business has been around connecting and securing physical endpoints, physical I/O endpoints, whatever they happen to be, of whatever type they happen to be. And one of the bets that we are, actually two of the bets that we are going after is around connecting and securing API endpoints wherever they happen to be of whatever type they happen to be. And so API networking, or app networking, is one big bet that we're going after. Our other big bet is around API security and that has a bunch of other connotations to it where we think about security moving from runtime security where traditionally Cisco has played in that space, especially on the infrastructure side, but moving into API security which is only under the developer pipeline and higher up in the stack. So those are two big bets that we're going after and as you can see, they're pretty close to Cisco's core business but also very differentiated from where Cisco is today. And once when you prove some of these bets out, you can walk further and further away or a few degrees away from Cisco's core as it exists today. >> All right, well Vijoy, I mentioned you're also on the board for the CNCF, maybe let's talk a little bit about open source. How does that play into what you're looking at for emerging technologies and these bets, you know, so many companies, that's an integral piece, and we've watched, you know really, the maturation of Cisco's journey, participating in these open source environments. So help us tie in where Cisco is when it comes to open source. >> So, yeah, so I think we've been pretty deeply involved in open source in our past. We've been deeply involved in Linux foundational networking. We've actually chartered FD.io as a project there and we still are. We've been involved in OpenStack. We are big supporters of OpenStack. We have a couple of products that are on the OpenStack offering. And as you all know, we've been involved in CNCF right from the get go as a foundational member. We brought NSM as a project. It's sandbox currently. We're hoping to move it forward. But even beyond that, I mean we are big users of open source. You know a lot of us has offerings that we have from Cisco and you would not know this if you're not inside of Cisco, but Webex, for example, is a big, big user of linger D right from the get go from version 1.0. But we don't talk about it, which is sad. I think for example, we use Kubernetes pretty deeply in our DNAC platform on the enterprise site. We use Kubernetes very deeply in our security platforms. So we are pretty deep users internally in all our SAS products. But we want to press the accelerator and accelerate this whole journey towards open source quite a bit moving forward as part of ET&I, Emerging Tech and Incubation as well. So you will see more of us in open source forums, not just the NCF but very recently we joined the Linux Foundation for Public Health as a premier foundational member. Dan Kohn, our old friend, is actually chartering that initiative and we actually are big believers in handling data in ethical and privacy preserving ways. So that's actually something that enticed us to join Linux Foundation for Public Health and we will be working very closely with Dan and the foundational companies there to, not just bring open source, but also evangelize and use what comes out of that forum. >> All right. Well, Vijoy, I think it's time for us to dig into your keynote. We've spoken with you in previous KubeCons about the "Network, Please Evolve" theme that you've been driving on, and big focus you talked about was SD-WAN. Of course anybody that been watching the industry has watched the real ascension of SD-WAN. We've called it one of those just critical foundational pieces of companies enabling Multicloud, so help us, you know, help explain to our audience a little bit, you know, what do you mean when you talk about things like CloudNative, SD-WAN, and how that helps people really enable their applications in the modern environment? >> Yeah, so, well we we've been talking about SD-WAN for a while. I mean, it's one of the transformational technologies of our time where prior to SD-WAN existing, you had to stitch all of these MPLS labels and actual data connectivity across to your enterprise or branch and SD-WAN came in and changed the game there. But I think SD-WAN as it exists today is application-alaware. And that's one of the big things that I talk about in my keynote. Also, we've talked about how NSM, the other side of the spectrum, is how NSM, or network service mesh, has actually helped us simplify operational complexities, simplify the ticketing and process hell that any developer needs to go through just to get a multicloud, multicluster app up and running. So the keynote actually talked about bringing those two things together where we've talked about using NSM in the past, in chapter one and chapter two, ah chapter two, no this is chapter three and at some point I would like to stop the chapters. I don't want this to be like, like an encyclopedia of networking (mumbling) But we are at chapter three and we are talking about how you can take the same consumption models that I talked about in chapter two which is just adding a simple annotation in your CRD and extending that notion of multicloud, multicluster wires within the components of our application but extending it all the way down to the user in an enterprise. And as you saw an example, Gavin Russom is trying to give a keynote holographically and he's suffering from SD-WAN being application alaware. And using this construct of a simple annotation, we can actually make SD-WAN CloudNative. We can make it application-aware, and we can guarantee the SLOs that Gavin is looking for in terms of 3D video, in terms of file access or audio just to make sure that he's successful and Ross doesn't come in and take his place. >> Well I expect Gavin will do something to mess things up on his own even if the technology works flawly. You know, Vijoy the modernization journey that customers are on is a neverending story. I understand the chapters need to end on the current volume that you're working on. But, you know, we'd love to get your view point. You talk about things like service mesh. It's definitely been a hot topic of conversation for the last couple of years. What are you hearing from your customers? What are some of the the kind of real challenges but opportunities that they see in today's CloudNative space? >> In general, service meshes are here to stay. In fact, they're here to proliferate to some degree and we are seeing a lot of that happening where not only are we seeing different service meshes coming into the picture through various open source mechanisms. You've got Istio there, you've got linger D, you've got various proprietary notions around control planes like App Mesh from Amazon. There's Console which is an open source project But not part of (mumbles) today. So there's a whole bunch of service meshes in terms of control planes coming in on volumes becoming a de facto side car data plane, whatever you would like to call it, de facto standard there which is good for the community I would say. But this proliferation of control planes is actually a problem. And I see customers actually deploying a multitude of service meshes in their environment. And that's here to stay. In fact, we are seeing a whole bunch of things that we would use different tools for. Like API Gate was in the past. And those functions are actually rolling into service meshes. And so I think service meshes are here to stay. I think the diversity of some service meshes is here to stay. And so some work has to be done in bringing these things together and that's something that we are trying to focus in on all as well because that's something that our customers are asking for. >> Yeah, actually you connected for me something I wanted to get your viewpoint on. Dial back you know 10, 15 years ago and everybody would say, "Ah, you know, I really want to have single pane of glass "to be able to manage everything." Cisco's partnering with all of the major cloud providers. I saw, you know, not that long before this event, Google had their Google Cloud show talking about the partnership that you have with Cisco with Google. They have Anthos. You look at Azure has Arc. You know, VMware has Tanzu. Everybody's talking about, really, kind of this multicluster management type of solution out there. And just want to get your viewpoint on this Vijoy is to, you know, how are we doing on the management plane and what do you think we need to do as a industry as a whole to make things better for customers? >> Yeah, but I think this is where I think we need to be careful as an industry, as a community and make things simpler for our customers because, like I said, the proliferation of all of these control planes begs the question, do we need to build something else to bring all of these things together. And I think the SMI apropos from Microsoft is bang on on that front where you're trying to unify at least the consumption model around how you consume these service meshes. But it's not just a question of service meshes. As you saw in the SD-WAN and also going back in the Google discussion that you just, or Google conference that we just offered It's also how SD-WANs are going to interoperate with the services that exist within these cloud silos to some degree. And how does that happen? And there was a teaser there that you saw earlier in the keynote where we are taking those constructs that we talked about in the Google conference and bringing it all the way to a CloudNative environment in the keynote. But I think the bigger problem here is how do we manage this complexity of disparate stacks, whether it's service meshes, whether it's development stacks, or whether it's SD-WAN deployments, how do we manage that complexity? And, single pane of glass is over loaded as a term because it brings in these notions of big, monolithic panes of glass. And I think that's not the way we should be solving it. We should be solving it towards using API simplicity and API interoperability. I think that's where we as a community need to go. >> Absolutely. Well, Vijoy, as you said, you know, the API economy should be able to help on these, you know, multi, the service architecture should allow things to be more flexible and give me the visibility I need without trying to have to build something that's completely monolithic. Vijoy, thanks so much for joining. Looking forward to hearing more about the big bets coming out of Cisco and congratulations on the new role. >> Thank you Stu. It was a pleasure to be here. >> All right, and stay tuned for much more coverage of theCUBE at KubeCon, CloudNativeCon. I'm Stu Miniman and thanks for watching. (light digital music)

(upbeat music) >> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation, and the ecosystem partners. >> Hi, and welcome back to theCUBE's coverage of KubeCon + CloudNativeCon 2020 in Europe, of course, the virtual edition. I'm Stu Miniman, and happy to welcome you back to the program. One of the keynote speakers is also a board member of the CNCF, Vijoy Pandey, who is the Vice President and Chief Technology Officer for Cloud at Cisco. Vijoy, nice to see you, thanks so much for joining us. >> Hi there, Stu, so nice to see you again. It's a strange setting to be in, but as long as we are both healthy, everything's good. >> Yeah, we still get to be together a little bit even though while we're apart. We love the the engagement and interaction that we normally get to the community, but we just have to do it a little bit differently this year. So we're going to get to your keynote. We've had you on the program to talk about "Networking, Please Evolve". I've been watching that journey. But why don't we start at first, you've had a little bit of change in roles and responsibility. I know there's been some restructuring at Cisco since the last time we got together. So give us the update on your role. >> Yeah, so let's start there. So I've taken on a new responsibility. It's VP of Engineering and Research for a new group that's been formed at Cisco. It's called Emerging Tech and Incubation. Liz Centoni leads that and she reports on to Chuck. The charter for the team, this new team, is to incubate the next bets for Cisco. And if you can imagine, it's natural for Cisco to start with bets which are closer to its core business. But the charter for this group is to move further and further out from Cisco's core business and take Cisco into newer markets, into newer products, and newer businesses. I'm running the engineering and resource for that group. And again, the whole deal behind this is to be a little bit nimble, to be a little bit, to startupy in nature, where you bring ideas, you incubate them, you iterate pretty fast, and you throw out 80% of those, and concentrate on the 20% that makes sense to take forward as a venture. >> Interesting. So it reminds me a little bit but different, I remember John Chambers, a number of years back, talking about various adjacencies trying to grow those next multi-billion dollar businesses inside Cisco. In some ways, Vijoy, it reminds me a little bit of your previous company, very well known for driving innovation, giving engineers 20% of their time to work on things, maybe give us a little bit insight, what's kind of an example of a bet that you might be looking at in this space, bring us in tight a little bit. >> Well, that's actually a good question. And I think a little bit of that comparison is all those conversations are taking place within Cisco as well as to how far out from Cisco's core business do we want to get when we're incubating these bets? And yes, my previous employer, I mean, Google X actually goes pretty far out when it comes to incubations, the core business being primarily around ads, now Google Cloud as well. But you have things like Verily and Calico, and others, which are pretty far out from where Google started. And the way we're looking at the these things within Cisco is, it's a new muscle for Cisco, so we want to prove ourselves first. So the first few bets that we are betting upon are pretty close to Cisco's core but still not fitting into Cisco's BU when it comes to, go to market alignment or business alignment. So one of the first bets that we're taking into account is around API being the queen when it comes to the future of infrastructure, so to speak. So it's not just making our infrastructure consumable as infrastructure as code but also talking about developer relevance, talking about how developers are actually influencing infrastructure deployments. So if you think about the problem statement in that sense, then networking needs to evolve. And I've talked a lot about this in the past couple of keynotes, where Cisco's core business has been around connecting and securing physical endpoints, physical I/O endpoints, wherever they happen to be, of whatever type they happen to be. And one of the bets that we are, actually two of the bets, that we're going after is around connecting and securing API endpoints, wherever they happen to be, of whatever type they happen to be. And so API networking or app networking is one big bet that we're going after. Another big bet is around API security. And that has a bunch of other connotations to it, where we think about security moving from runtime security, where traditionally Cisco has played in that space, especially on the infrastructure side, but moving into API security, which is earlier in the development pipeline, and higher up in the stack. So those are two big bets that we're going after. And as you can see, they're pretty close to Cisco's core business, but also are very differentiated from where Cisco is today. And once you prove some of these bets out, you can walk further and further away, or a few degrees away from Cisco's core. >> All right, Vijoy, why don't you give us the update about how Cisco is leveraging and participating in open source? >> So I think we've been pretty, deeply involved in open source in our past. We've been deeply involved in Linux Foundation Networking. We've actually chartered FD.io as a project there and we still are. We've been involved in OpenStack, we have been supporters of OpenStack. We have a couple of products that are around the OpenStack offering. And as you all know, we've been involved in CNCF, right from the get-go, as a foundation member. We brought NSM as a project. I had Sandbox currently, but we're hoping to move it forward. But even beyond that, I mean, we are big users of open source, a lot of those has offerings that we have from Cisco, and you will not know this if you're not inside of Cisco. But Webex, for example, is a big, big user of Linkerd, right from the get-go, from version 1.0, but we don't talk about it, which is sad. I think, for example, we use Kubernetes pretty deeply in our DNAC platform on the enterprise side. We use Kubernetes very deeply in our security platforms. So we're pretty good, pretty deep users internally in our SaaS products. But we want to press the accelerator and accelerate this whole journey towards open source, quite a bit moving forward as part of ET&I, Emerging Tech and Incubation, as well. So you will see more of us in open source forums, not just CNCF, but very recently, we joined the Linux Foundation for Public Health as a premier foundational member. Dan Kohn, our old friend, is actually chartering that initiative, and we actually are big believers in handling data in ethical and privacy-preserving ways. So that's actually something that enticed us to join Linux Foundation for Public Health, and we will be working very closely with Dan and foundational companies that do not just bring open source but also evangelize and use what comes out of that forum. >> All right, well, Vijoy, I think it's time for us to dig into your keynote. We've we've spoken with you in previous KubeCons about the "Network, Please Evolve" theme that you've been driving on. And big focus you talked about was SD-WAN. Of course, anybody that's been watching the industry has watched the real ascension of SD-WAN. We've called it one of those just critical foundational pieces of companies enabling multi-cloud. So help explain to our audience a little bit, what do you mean when you talk about things like Cloud Native SD-WAN and how that helps people really enable their applications in the modern environment? >> Yes, well, I mean, we've been talking about SD-WAN for a while. I mean, it's one of the transformational technologies of our time where prior to SD-WAN existing, you had to stitch all of these MPLS labels and actually get your connectivity across to your enterprise or branch. And SD-WAN came in and changed the game there, but I think SD-WAN, as it exists today, is application-unaware. And that's one of the big things that I talk about in my keynote. Also, we've talked about how NSM, the other side of the spectrum, is how NSM or Network Service Mesh has actually helped us simplify operational complexities, simplify the ticketing and process health that any developer needs to go through just to get a multi-cloud, multi-cluster app up and running. So the keynote actually talked about bringing those two things together, where we've talked about using NSM in the past in chapter one and chapter two. And I know this is chapter three, and at some point, I would like to stop the chapters. I don't want this like an encyclopedia of "Networking, Please Evolve". But we are at chapter three, and we are talking about how you can take the same consumption models that I talked about in chapter two, which is just adding a simple annotation in your CRD, and extending that notion of multi-cloud, multi-cluster wires within the components of our application, but extending it all the way down to the user in an enterprise. And as we saw an example, Gavin Belson is trying to give a keynote holographically and he's suffering from SD-WAN being application-unaware. And using this construct of a simple annotation, we can actually make SD-WAN cloud native, we can make it application-aware, and we can guarantee the SLOs, that Gavin is looking for, in terms of 3D video, in terms of file access for audio, just to make sure that he's successful and Ross doesn't come in and take his place. >> Well, I expect Gavin will do something to mess things up on his own even if the technology works flawlessly. Vijoy, the modernization journey that customers are on is a never-ending story. I understand the chapters need to end on the current volume that you're working on, but we'd love to get your viewpoint. You talk about things like service mesh, it's definitely been a hot topic of conversation for the last couple of years. What are you hearing from your customers? What are some of the kind of real challenges but opportunities that they see in today's cloud native space? >> In general, service meshes are here to stay. In fact, they're here to proliferate to some degree, and we are seeing a lot of that happening, where not only are we seeing different service meshes coming into the picture through various open source mechanisms. You've got Istio there, you've Linkerd, you've got various proprietary notions around control planes like App Mesh, from Amazon, there's Consul, which is an open source project, but not part of CNCF today. So there's a whole bunch of service meshes in terms of control planes coming in. Envoy is becoming a de facto sidecar data plane, whatever you would like to call it, de facto standard there, which is good for the community, I would say. But this proliferation of control planes is actually a problem. And I see customers actually deploying a multitude of service meshes in their environment, and that's here to stay. In fact, we are seeing a whole bunch of things that we would use different tools for, like API gateways in the past, and those functions actually rolling into service meshes. And so I think service meshes are here to stay. I think the diversity of service meshes is here to stay. And so some work has to be done in bringing these things together. And that's something that we are trying to focus in on as well. Because that's something that our customers are asking for. >> Yeah, actually, you connected for me something I wanted to get your viewpoint on, go dial back, 10, 15 years ago, and everybody would say, "Oh, I really want to have a single pane of glass "to be able to manage everything." Cisco's partnering with all of the major cloud providers. I saw, not that long before this event, Google had their Google Cloud Show, talking about the partnership that you have with, Cisco with Google. They have Anthos, you look at Azure has Arc, VMware has Tanzu. Everybody's talking about really the kind of this multi-cluster management type of solution out there, and just want to get your viewpoint on this Vijoy as to how are we doing on the management plane, and what do you think we need to do as an industry as a whole to make things better for customers? >> Yeah, I think this is where I think we need to be careful as an industry, as a community and make things simpler for our customers. Because, like I said, the proliferation of all of these control planes begs the question, do we need to build something else to bring all these things together? I think the SMI proposal from Microsoft is bang on on that front, where you're trying to unify at least the consumption model around how you consume these service meshes. But it's not just a question of service meshes as you saw in the SD-WAN announcement back in the Google discussion that we just, Google conference that you just referred. It's also how SD-WANs are going to interoperate with the services that exist within these cloud silos to some degree. And how does that happen? And there was a teaser there that you saw earlier in the keynote where we are taking those constructs that we talked about in the Google conference and bringing it all the way to a cloud native environment in the keynote. But I think the bigger problem here is how do we manage this complexity of this pallet stacks? Whether it's service meshes, whether it's development stacks, or whether it's SD-WAN deployments, how do we manage that complexity? And single pane of glass is overloaded as a term, because it brings in these notions of big monolithic panes of glass. And I think that's not the way we should be solving it. We should be solving it towards using API simplicity and API interoperability. And I think that's where we as a community need to go. >> Absolutely. Well, Vijoy, as you said, the API economy should be able to help on these, the service architecture should allow things to be more flexible and give me the visibility I need without trying to have to build something that's completely monolithic. Vijoy, thanks so much for joining. Looking forward to hearing more about the big bets coming out of Cisco, and congratulations on the new role. >> Thank you, Stu. It was a pleasure to be here. >> All right, and stay tuned for lots more coverage of theCUBE at KubeCon + CloudNativeCon. I'm Stu Miniman. Thanks for watching. (upbeat music)

>> Narrator: Live from Midtown Manhattan it's theCUBE! Covering Big Data, New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsor. >> Okay, welcome back everyone. Live here in New York this is theCUBE's coverage of Big Data NYC, our event. We've been doing it for five years, it's our event in conjunction with Strata Data, which is the O'Reilly Media that we run, it's a separate event. But we've been covering the Big Data for eight years since 2010, Hadoop World. This is theCUBE. Of course theCUBE is never going to change, they might call it Strata AI next year, whatever trend that they might see. But we're going to keep it theCUBE. This is in New York City, our eighth year of coverage. Guys, welcome to theCUBE. Our next two guests is Andrew Burt, Chief Privacy Officer and Andrew Gillman, Chief Customer Officer and CMO. It's a start-up so you got all these fancy titles, but you're on the A-team from Immuta. Hot start-up. Welcome to theCUBE. Great to see you again. >> Thanks for having us, appreciate it. >> Okay, so you guys are the start-up feature here this week on theCUBE, our little segment here. I think you guys are the hottest start-up that is out there and that people aren't really talking a lot about. So you guys are brand new, you guys have got a really good reputation. Getting a lot of props inside the community. Especially in the people who know data, data science, and know some of the intelligence organizations. But respectful people like Dan Hutchin says you guys are rockstars and doing great. So why all the buzz inside the community? Now you guys are just starting to go to the market? What's the update on the company? >> So great story. Founded in 2014, (mumbles) Investment, it was announced earlier this year. And the team, group of serial entrepreneurs sold their last company CSC, ran the public sector business for them for a while. Really special group of engineers and technologists and data scientists. Headquartered out of D.C. Customer success organization out of Columbus, Ohio, and we're servicing Fortune 100 companies. >> John: So Immuta, I-M-M-U-T-A. >> Immuta.com we just launched the new website earlier this week in preparation for the show. And the easiest way-- >> Immuta, immutable, I mean-- >> Immutable, I'm sure there's a backstory. >> Immutable, yeah. We do not ever touch the raw data. So we're all about managing risk and managing the integrity of the data. And so risk and integrity and security are baked into everything we do. We want our customers to know that their data will be immutable, and that in using us they'll never pose an additional risk to that underlying data. >> I think of blockchain when I think of immutability, like I'm so into blockchaining these dayS as you guys know, I've been totally into it. >> There's no blockchain in their technology. >> I know, but let's get down to why the motivation to enter the market. There's a lot of noisy stuff out there. Why do we need another unified platform? >> The big opportunity that we saw was, organizations had spent basically the past decade refining and upgrading their application infrastructure. But in doing so under the guise of digital transformation. We've really built that organization's people processes to support monolithic applications. Now those applications are moving to the cloud, they're being rearchitected in a microsurfaces architecture. So we have all this data now, how do we manage it for the new application, which we see is really algorithm-centric? The Amazons of the world have proven, how do you compete against anyone? How do you disrupt any industry? That's operationalize your data in a new way. >> Oh, they were developer-centric right? They were very focused on the developer. You guys are saying you're algorithm-centric, meaning the software within the software kind of thing. >> It's really about, we see the future enterprise to compete. You have to build thousands of algorithms. And each one of those algorithms is going to do something very specific, very precise, but faster than any human can do. And so how do you enable an application, excuse me, an algorithm-centric infrastructure to support that? And today, as we go and meet with our customers and other groups, the people, the processes, the data is everywhere. The governance folks who have to control how the data is used, the laws are dynamic. The tooling is complex. So this whole world looks very much like pre-DevOps IT, or pre-cloud IT. It takes on average between four to six months to get a data scientist up and running on a project. >> Let's get into the company. I wanted to just get that gist out, put some context. I see the problem you solve: a lot of algorithms out there, more and more open sources coming up to the scene. With the Linux Foundation, having their new event Rebrand the Open Source summit, shows exponential growth in open source. So no doubt about it, software's going to be new guys coming on, new gals. Tons of software. What is the company positioning? What do you guys do? How many employees? Let's go down by the numbers and then talk about the problem that you solve. >> Okay, cool. So, company. We'll be about 40 people by Q1. Heavy engineering, go to market. We're operating and working with, as I mentioned, Fortune 100 clients. Highly regulated industries. Financial services, healthcare, government, insurance, et cetera. So where you have lots of data that you need to operationalize, that's very sensitive to use. What else? Company positioning. So we are positioned as data management for data science. So the opportunity that we saw, again, managing data for applications is very different than managing data for algorithm development, data sciences. >> John: So you're selling to the CDO, Chief Data Officer? Are you selling to the analytics? >> In a lot of our customers, like in financial services, we're going right into the line of business. We're working with managing directors who are building next generation analytics infrastructure that need to unify and connect the data in a new way that's dynamic. It's not just the data that they have within their organization, they're looking to bring data in from outside. They want to also work collaboratively with governance professionals and lawyers who in financial services, they are, you know, we always jest in the company that different organizations have these cool new tools, like data scientists have all their new tools. And the data owners have flash disks and they have all this. But the governance people still have Microsoft Word. And maybe the newer tools are like Wikis. So now we can get it off of Word and make it shareable. But what we allow them to do is, and what Andrew Burt has really driven, is the ability for you to take internal logic, internal policies, external regulations, and put them into code that becomes dynamically enforceable as you're querying the data, as you're using it, to train algorithms, and to drive, mathematical decision-making in the enterprise. >> Let's jump into some of the privacy. You're the Chief Privacy Officer, which is codeword for you're doing all the governance stuff. And there's a lot of stuff business-wise that's going on around GDPR which is actually relevant. There's a lot of dollars on table for that too, so it's probably good for business. But there's a lot of policy stuff going on. What's going on with you guys in this area? >> So I think policy is really catching up to the world of big data. We've known for a very long time that data is incredibly important. It's the lifeblood of an increasingly large number of organizations, and because data is becoming more important, laws are starting to catch up. I think GDPR is really, it's hot to talk about. I think it is just the beginning of a larger trend. >> People are scared. People are nervous. It's like they don't know, this could be a blank check that they're signing away. The enforcement side is pretty outrageous. >> So I mean-- >> Is that right? I mean people are scared, or do you think? >> I think people are terrified because they know that its important, and they're also terrified because data scientists, and folks in IT have never really had to think very seriously about implementing complex laws. I think GDPR is the first example of laws, forcing technology to basically blend software and law. The only way, I mean one of our theses is, the only way to actually solve for GDPR is to invent laws within the software you're using. And so, we're moving away from this meetings and memos type approach to governing data, which is very slow and can take months, and we need it to happen dynamically. >> This is why I wanted to bring you guys in. Not only, Andrew, we knew each other from another venture, but what got my attention for you guys was really this intersection between law and society and tech. And this is just the beginning. You look at the tell-signs there. Peter Burris who runs research for Wikibon coined the term programming the real world. Life basically. You've got wearables, you've got IOT, this is happening. Self-driving cars. Who decides what side of the street people walk on now? Law and code are coming together. That's algorithm. There'll be more of them. Is there an algorithm for the algorithms? Who teaches the data set, who shares the data set? Wait a minute, I don't want to share my data set because I have a law that says I can't. Who decides all this stuff? >> Exactly. We're starting to enter a world where governments really, really care about that stuff. Just in-- >> In Silicon Valley, that's not in their DNA. You're seeing it all over the front pages of the news, they can't even get it right in inclusion and diversity. How can they work with laws? >> Tension is brewing. In the U.S. our regulatory environment is a little more lax, we want to see innovation happen first and then regulate. But the EU is completely different. Their laws in China and Russia and elsewhere around the world. And it's basically becoming impossible to be a global organization and still take that approach where you can afford to be scared of the law. >> John: I don't know how I feel about this because I get all kinds of rushes of intoxication to fear. Look at what's going on with Bitcoin and Blockchain, underbelly is a whole new counterculture going on around in-immutable data. Anonymous cultures, where they're complete anonymous underbellies going on. >> I think the risk-factors going up, when you mentioned IOTs, so its where you are and your devices and your home. Now think about 23 and Me, Verily, Freenome, where you're digitizing your DNA. We've already started to do that with MRIs and other operations that we've had. You think about now, I'm handing over my DNA to an organization because I want find out my lineage. I want to learn about where I came from. How do I make sure that the derived data off of that digital DNA is used properly? Not just for me, as Andrew, but for my progeny. That introduces some really interesting ethical issues. It's an intersection of this new wave of investment, to your point, like in Silicon Valley, of bringing healthcare into data science, into technology and the intersection. And the underpinning of the whole thing is the data. How do we manage the data, and what do we do-- >> And AI really is the future here. Even though machine-learning is the key part of AI, we just put out an article this morning on SiliconANGLE from Gina Smith, our new writer. Google Brain Chief: AI tops humans in computer vision, and healthcare will never be the same. They talk about little things, like in 2011 you can barely do character recognition of pictures, now you can 100%. Now you take that forward, in Heidelberg, Germany, the event this week we were covering the Heidelberg Laureate Forum, or HLF 2017. All the top scientists were there talking about this specific issue of, this is society blending in with tech. >> Absolutely. >> This societal impact, legal impact, kind of blending. Algorithms are the only thing that are going to scale in this area. This is what you guys are trying to do, right? >> Exactly, that's the interesting thing. When you look at training models and algorithms in AI, right, AI is the new cloud. We're in New York, I'm walking down the street, and there's the algorithm you're writing, and everything is Ernestine Young. Billboards on algorithms, I mean who would have thought, right? An AI. >> John: theCUBE is going to be an AI pretty soon. "Hey, we're AI! "Brought to you by, hey, Siri, do theCUBE interview." >> But the interesting part of the whole AI and the algorithm is you have n number of models. We have lots of data scientists and AI experts. Siri goes off. >> Sorry Siri, didn't mean to do that. >> She's trying to join the conversation. >> Didn't mean to insult you, Siri. But you know, it's applied math by a different name. And you have n number of models, assuming 90% of all algorithms are single linear regression. What ultimately drives the outcome is going to be how you prepare and manage the data. And so when we go back to the governance story. Governance in applications is very different than governance in data science because how we actually dynamically change the data is going to drive the outcome of that algorithm directly. If I'm in Immuta, we connect the data, we connect the data science tools. We allow you to control the data in a unique way. I refer to that as data personalization. It's not just, can I subscribe to the data? It's what does the data look like based on who I am and what those internal and external policies are? Think about this for example, I'm training a model that doesn't mask against race, and doesn't generalize against age. What do you think is going to happen to that model when it goes to start to interact? Either it's delivered as-- >> Well context is critical. And the usability of data, because it's perishable at this point. Data that comes in quick is worth more, but historically the value goes down. But it's worth more when you train the machine. So it's two different issues. >> Exactly. So it's really about longevity of the model. How can we create and train a model that's going to be able to stay in? It's like the new availability, right? That it's going to stay, it's going to be relevant, and it's going to keep us out of jail, and keep us from getting sued as long as possible. >> Well Jeff Dean, I just want to quote one more thing to add context. I want to ask Andrew over here about his view on this. Jeff Dean, the Google Brain Chief behind all of the stuff is saying AI-enabled healthcare. The sector's set to grow at an annual rate of 40% through 2021, when it's expected to hit 6.6 billion spent on AI-enabled healthcare. 6.6 billion. Today it's around 600 million. That's the growth just in AI healthcare impact. Just healthcare. This is going to go from a policy privacy issue, One, healthcare data has been crippled with HIPPA slowing us down. But where is the innovation going to come from? Where's the data going to be in healthcare? And other verticals. This is one vertical. Financial services is crazy too. >> I mean, honestly healthcare is one of the most interesting examples of applied AI, and it's because there's no other realm, at least now, where people are thinking about AI, and the risk is so apparent. If you get a diagnosis and the doctor doesn't understand why it's very apparent. And if they're using a model that has a very low level of transparency, that ends up being really important. I think healthcare is a really fascinating sector to think about. But all of these issues, all of these different types of risks that have been around for a while are starting to become more and more important as AI takes-- >> John: Alright, so I'm going to wrap up here. Give you guys both a chance, and you can't copy each other's answer. So we'll start with you Andrew over here. Explain Immuta in a simple way. Someone who's not in the industry. What do you guys do? And then do a version for someone in the industry. So elevator pitch for someone who's a friend, who's not in the industry, and someone who is. >> So Immuta is a data management platform for data science. And what that actually gives you is, we take the friction out of trying to access data, and trying to control data, and trying to comply with all of the different rules that surround the use of that data. >> John: Great, now do the one for normal people. >> That was the normal pitch. >> Okay! (laughing) I can't wait to hear the one for the insiders. >> And then for the insiders-- >> Just say, "It's magic". >> It's magic. >> We're magic, you know. >> Coming from the infrastructure role, I like to refer to it as a VMWare for data science. We create an abstraction layer than sits between the data and the data science tools, and we'll dynamically enforce policies based on the values of the organization. But also, it drives better outcomes. Because today, the data owners aren't confident that you're going to do with the data what you say you're going to do. So they try to hold it. Like the old server-huggers, the data-huggers. So we allowed them to unlock that and make it universally available. We allow the governance people to get off those memos, that have to be interpreted by IT and enforced, and actually allow them to write code and have it be enforced as the policy mandates. >> And the number one problem you solve is what? >> Accelerate with confidence. We allow the data scientists to go and build models faster by connecting to the data in a way that they're confident that when they deploy their model, that it's going to go into production, and it's going to stay into production for as long as possible. >> And what's the GDPR angle? You've got the legal brain over here, in policy. What's going on with GDPR? How are you guys going to be a solution for that? >> We have the most, I'd say, robust option of policy enforcement on data, I think, available. We make it incredibly easy to comply with GDPR. We actually put together a sample memo that says, "Here's what it looks like to comply with GDPR." It's written from a governance department, sent to the internal data science department. It's about a page and a half long. We actually make that very onerous process-- >> (mumbles) GDPR, you guys know the size of that market? In terms of spend that's going to be coming around the corner? I think it's like the Y2K problem that's actually real. >> Exactly, it feels the same way. And actually Andrew and his team have taken apart the regulation article by article and have actually built-in product features that satisfy that. It's an interesting and unique--- >> John: I think it's really impressive that you guys bring a legal and a policy mind into the product discussion. I think that's something that I think you guys are doing a little bit different than I see anyone out there. You're bringing legal and policy into the software fabric, which is unique, and I think it's going to be the standard in my opinion. Hopefully this is a good trend, hopefully you guys keep in touch. Thanks for coming on theCUBE, thanks for-- >> Thanks for having us. >> For making time to come over. This is theCUBE, breaking out the start-up action sharing the hot start-ups here, that really are a good position in the marketplace, as the generation of the infrastructure changes. It's a whole new ballgame. Global development platform, called the Internet. The new Internet. It's decentralized, we even get into Blockchain, we want to try that a little later, maybe another segment. It's theCUBE in New York City. More after this short break.