>> Live from San Francisco. It's the Cube covering artists. A conference twenty nineteen Brought to You by Four Scout >> Welcome back, everybody, Geoffrey. Here with the cue, we're in North America and the newly refinished Mosconi Center Downtown San Francisco in the force Cow boo. Happy to be here first time and we have our next guest. She's Charlotte Wiley, chief of staff from Symantec. Great to meet you. >> Nice to meet you, teacher. Thanks for having >> absolutely so impressions of the show. This is a crazy show. Forty dollars, people. Aren't many shows like this >> it issue just a little overwhelming. It's my second year here, and it's no less overwhelming. Second year here. It's, uh it's just prolific. Everything that say the session, the keynotes all day, all the networking, the basis. Amazing. >> So I'm curious how your perception has changed. I >> was looking at your background, Your hearing a financial institution before your own kind of the purchaser side of the house. >> Now you're over on >> this side of the house. How's that kind of change your perception when you walk this crazy floor, I imagine before you're like, Yeah, how am I going to digest all this? >> Well, no one wants to be my friend anymore, which is interesting. So, um, you know, working on the vendor side of the defense is the dark side. It's It's a very different experience. When I came here a couple years go to bank. Everyone wants to talk to you. Or is this time? Is this a healthy, competitive nature going on between all the vendors, which is great. You want to see that? Yeah. It sze got the same enthusiasm. Same vase on the floor, which is wonderful. >> So semantics. Been a leader in the space for a very, very long time. One of the original, you know, kind of original security companies back in the day when we're just trying to protect that. You know, I guess our Web browser right from from some malicious activity. Wow. The world has changed. And one of the big new components now is his internet of things. In this tie of it with ot operations technology. You know something you've spent some time on a wonderful get your take on how that's increasing the threat surface, you know, increasing the complexity. And yet there's still a lot of value there if you can bring those systems together. >> Yeah, absolutely. So I think that Kate thing is this. You know, this simplicity here is, uh What? What you don't know, You can see. And what you can't see you can't monitor on DH. That's the key thing to remember when you think about t n OT so with Coyote specifically, if you, uh you've definitely got a nice routine, you network somewhere everyone has. But if you can't see that thing, it is incredibly vulnerable Throat vector for any organization. So really, it's it's a point of egress for any doubt of ex filtration. And if you've got someone compromised in the network already on your way, see it as being a very opportune ingress point to getting a lateral move. Right. So they are incredibly, inherently vulnerable. Right? These things are they're usually hard coded, authenticated. They are. They have massive under. Police often remain unpatched. When you cannot see, you don't know, Right? So some of the dirty side of the fence, right? The same problem exists. They typically were not built to connect to the Internet. Right. So this is something very new that we're trying to tackle right. And one of the key things I think about is that it's probably a little bit few tile to make these OT and I and I. A device is inherently secure. You think about in twenty twenty. We're going to see like twenty five billion devices proliferating our globe, which is incredible. So how do we how do we make it more school? Let's back off from becoming inherently secure. Let's up on the visibility. If you visualize you, Khun Segment, and you can enforce. And then you can take control of what has access to your network, right? A >> lot of interesting conversations about this today, obviously or in the force cow boo. But I think one of the people earlier said they had fifty percent more devices on the network than they anticipated. And it turns out his remote offices and people are plugging things in. Another little factoid is that maybe that hit no s on that device is actually windows in tea. Is it a tea? A little box. And nobody even knew because you knew that's an embedded in team. But then on the other side, we had a lease on, and she was talking about great example on security cameras and just that a lot of these newer devices that you can connect have a plethora of services packaged in on the assumption that you might use them. So rather than have not too many, they put them all in. But you don't necessarily need to turn all those things on. So again, you're just opening up this huge kind of exposure. >> Huge explosion. That's it. I think it's a really good conversation to have with your stakeholders about talking about the target breach. So when people start to understand that that really originated from a hate tax system, right compromise haystack system. So when you're talking about T initialization, that's a really good years case to say. Look, this is a huge bridge that was compromised from because we didn't They didn't have visibility over the anxiety. >> It's funny if you each Max keep coming up, over and over and over there. Obviously the biggest threat that way have I'm jacket to see if I could see like a movie with me. Nasty HBC think come until that munching up the company. But it's funny. Different topic. Shifting gears completely, really, about kind of diversity, diversity of opinion, diversity of perspective, diversity of thought and how that's a really important and effective tool use in trying to accomplish missions. In this really crazy, complex task, you can't abs single point of view, single point of reference, kind of a single pain that you think about. I know that's something that you've been in a lot of time on, >> so my role it's semantic because Chief of staff, I own the diversity agenda for the global security office. And it's bean aerial laser focus on me for the past twelve months, which is our industry has a systemic problem around attracting and retaining talent from diverse backgrounds. Right? We're gonna tackle it head on on We don't really successfully in semantics. Oh, wait. Give this fabulous mandate through to our leadership who got on board with laser focus around, making sure that we get a diverse slate of candidates when we bring in new people and that that translated incredibly well. So we saw a rise of interview to conversion. Foreign ft for females in six months off forty percent >> fourteen or forty four zero for zero. >> So just by making it part of the interviewing experience. Having a diverse slate of candidates, making sure that we're really giving a foreign opportunities coming right really has changed playing Plainfield. >> And then the other thing, of course, is the retention, which is a big problem for attention that we're, you know, women dropping out and not coming back. >> That's and this every organization has to step up to make sure that they're waiting, but their making a workforce that is flexible, that accommodates so some of that. Some of the mental load that women have, whether it's through a child, care whether it's to do with older parents. But also when we talk about diversity, it's nothing. You know just about the gender piece, right? We're going to accommodate for other people as well underrepresented minorities. Early Korea, Different people have different socio economic backgrounds, maybe haven't come from a typical university training course, right, Something that we've focused on heavily. We've been working with a large enough profits to bring in early career guys who have not had a university background who may have had a really rough time coming out of school, getting them in, training them up through internships, bringing them up to speed over six months and converting them into FDA, which I feel is really a way tio to build a diverse workforce and get people an opportunity that didn't have it >> now was someone spearheading that before you came on border was there Was there an effort that really kind of put a dedicated resource on it when you when you took it over? >> So I took over about a year ago and I double down on the effort. We were working with Europe before that. Had a fantastic colleague was doing a lot of work with Europe on. We're just seeing fabulous results with converted nearly thirty three percent of our internships into FT. >> Thirty three and you're not in those thirty three or not coming from, you know, kind of a classic. They're not coming pig population. >> Absolutely these air IGA passionate, enthusiastic young people who have a tenacity to just pick things up because they're so grateful to be there right there, so happy to be given the opportunity. And it's some It's an untapped resource that I think a lot of people who are looking to have solved aside the security talent shortages should be looking into great that we get programs in place for a Girl Scout middle school. But let's think about alternative ways of getting new talent in. And I think that they're not for profit right way after >> such a big problem. And like you say, it's a big problem, you know, from from little girls. And, you know, all the way up to mid mid career women that air dropping out and not coming back before you even get into the boardroom. We work with a ton of organization like Athena Alliance with towards that the boardroom level all the way down to Grace Hopper. You know, this working more kind of college graduate level girls intact? I mean, there's a lot of luckily, a lot of people are trying to focus on the problem, but unfortunately, the numbers or not turning in the correct direction, they're actually turning in the wrong direction. Yeah, >> so really, that's it for me. It's about laser focus. You really got it. If you make your party your agenda making party returned right? Don't give it. The nursery had not. Don't say that you will do the things actually commit to it and get it done right. I'm not a huge fan of talk. It's Qatargas work on. So, yeah, I think there's a lot of opportunity. The people they don't step up to the great doing enough >> to to your earlier first line, right? If you're not measuring it, you know, and tracking against it, how do you know if you're being silly and what it's under served? You have to give it a little juice, right? You can't just have to expect the status quo to suddenly change, right? >> Absolutely metrics. Incredibly employed. And start with you metrics. Dashboard record where your tracking, in terms of your representation of females, underrepresented minorities. Your bets. You're early Korea. Really? What you want to see is a huge influx or the interviewing stage into the into the FT conversion. You want to see an influx in your leadership. You want more women in your leadership team because that's the way to drive a better female pipeline, right? Same goes on because I'm are minority. Same guys. Early career. >> Yeah, so important that they look up and see somebody that looks like one hundred percent C. C an opportunity to be that person, something alright. Charlotte. Well, thanks for, uh, for taking a few minutes of your day. And great Teo learned about all your What you working on? That's >> great. Thanks. Having >> alright? She Charlotte? I'm Jeff. You're watching the Cube? Where are, say twenty nineteen in the force Cow booth. Thanks for watching. >> We'LL see you next time.

>> Announcer: "theCUBE" presents KubeCon and CloudNativeCon Europe 2022 brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain and KubeCon and CloudNativeCon Europe 2022. I'm Keith Townsend, my co-host, Paul Gillin, Senior Editor Enterprise Architecture for SiliconANGLE. We're going to talk, or continue to talk to amazing people. The coverage has been amazing, but also the city of Valencia is beautiful. I have to eat a little crow, I landed and I saw the convention center, Paul, have you got out and explored the city at all? >> Absolutely, my first reaction to Valencia when we were out in this industrial section was, "This looks like Cincinnati." >> Yes. >> But then I got on the bus second day here, 10 minutes to downtown, another world, it's almost a middle ages flavor down there with these little winding streets and just absolutely gorgeous city. >> Beautiful city. I compared it to Charlotte, no disrespect to Charlotte, but this is an amazing city. Naina Singh, Principal Product Manager at Red Hat, and Roland Huss, also Principal Product Manager at Red Hat. We're going to talk a little serverless. I'm going to get this right off the bat. People get kind of feisty when we call things like Knative serverless. What's the difference between something like a Lambda and Knative? >> Okay, so I'll start. Lambda is, like a function as a server, right? Which is one of the definitions of serverless. Serverless is a deployment platform now. When we introduced serverless to containers through Knative, that's when the serverless got revolutionized, it democratized serverless. Lambda was proprietary-based, you write small snippets of code, run for a short duration of time on demand, and done. And then Knative which brought serverless to containers, where all those benefits of easy, practical, event-driven, running on demand, going up and down, all those came to containers. So that's where Knative comes into picture. >> Yeah, I would also say that Knative is based on containers from the very beginning, and so, it really allows you to run arbitrary workloads in your container, whereas with Lambda you have only a limited set of language that you can use and you have a runtime contract there which is much easier with Knative to run your applications, for example, if it's coming in a language that is not supported by Lambda. And of course the most important benefit of Knative is it's run on top of Kubernetes, which allows you- >> Yes. >> To run your serverless platform on any other Kubernetes installation, so I think this is one of the biggest thing. >> I think we saw about three years ago there was a burst of interest around serverless computing and really some very compelling cost arguments for using it, and then it seemed to die down, we haven't heard a lot about serverless, and maybe I'm just not listening to the right people, but what is it going to take for serverless to kind of break out and achieve its potential? >> Yeah, I would say that really the big advantage of course of Knative in that case is that you can scale down to zero. I think this is one of the big things that will really bring more people onto board because you really save a lot of money with that if your applications are not running when they're not used. Yeah, I think also that, because you don't have this vendor log in part thing, when people realize that you can run really on every Kubernete platform, then I think that the journey of serverless will continue. >> And I will add that the event-driven applications, there hasn't been enough buzz around them yet. There is, but serverless is going to bring a new lease on life on them, right? The other thing is the ease of use for developers. With Knative, we are introducing a new programming model, the functions, where you don't even have to create containers, it would do create containers for you. >> So you create the servers, but not the containers? >> Right now, you create the containers and then you deploy them in a serverless fashion using Knative. But the container creation was on the developers, and functions is going to be the third component of Knative that we are developing upstream, and Red Hat donated that project, is going to be where code to cloud capability. So you bring your code and everything else will be taken care of, so. >> So, I'd call a function or, it's funny, we're kind of circular with this. What used to be, I'd write a function and put it into a container, this server will provide that function not just call that function as if I'm developing kind of a low code no code, not no code, but a low code effort. So if there's a repetitive thing that the community wants to do, you'll provide that as a predefined function or as a server. >> Yeah, exactly. So functions really helps the developer to bring their code into the container, so it's really kind of a new (indistinct) on top of Knative- >> on top op. >> And of course, it's also a more opinionated approach. It's really more closer coming to Lambda now because it also comes with a programming model, which means that you have certain signature that you have to implement and other stuff. But you can also create your own templates, because at the end what matters is that you have a container at the end that you can run on Knative. >> What kind of applications is serverless really the ideal platform? >> Yeah, of course the ideal application is a HTTP-based web application that has no state and that has a very non-uniform traffic shape, which means that, for example, if you have a business where you only have spikes at certain times, like maybe for Super Bowl or Christmas, when selling some merchandise like that, then you can scale up from zero very quickly at a arbitrary high depending on the load. And this is, I think, the big benefit over, for example, Kubernetes Horizontal Pod Autoscaling where it's more like indirect measures of value scaling based on CPR memory, but here, it directly relates one to one to the traffic that is coming in to concurrent request. Yeah, so this helps a lot for non-uniform traffic shapes that I think this has become one of the ideal use case. >> Yeah. But I think that is one of the most used or defined one, but I do believe that you can write almost all applications. There are some, of course, that would not be the right load, but as long as you are handling state through external mechanism. Let's say, for example you're using database to save the state, or you're using physical volume amount to save the state, it increases the density of your cluster because when they're running, the containers would pop up, when your application is not running, the container would go down, and the resources can be used to run any other application that you want to us, right? >> So, when I'm thinking about Lambda, I kind of get the event-driven nature of Lambda. I have a S3 bucket, and if a S3 event is driven, then my functions as the server will start, and that's kind of the listening servers. How does that work with Knative or a Kubernetes-based thing? 'Cause I don't have an event-driven thing that I can think of that kicks off, like, how can I do that in Kubernetes? >> So I'll start. So it is exactly the same thing. In Knative world, it's the container that's going to come up and your servers in the container, that will do the processing of that same event that you are talking. So let's say the notification came from S3 server when the object got dropped, that would trigger an application. And in world of Kubernetes, Knative, it's the container that's going to come up with the servers in it, do the processing, either find another servers or whatever it needs to do. >> So Knative is listening for the event, and when the event happens, then Knative executes the container. >> Exactly. >> Basically. >> So the concept of Knative source which is kind of adapted to the external world, for example, for the S3 bucket. And as soon as there is an event coming in, Knative will wake up that server, will transmit this event as a cloud event, which is another standard from the CNCF, and then when the server is done, then the server spins down again to zero so that the server is only running when there are events, which is very cost effective and which people really actually like to have this kind of way of dynamic scaling up from zero to one and even higher like that. >> Lambda has been sort of synonymous with serverless in the early going here, is Knative a competitor to Lambda, is it complimentary? Would you use the two together? >> Yeah, I would say that Lambda is a offering from AWS, so it's a cloud server there. Knative itself is a platform, so you can run it in the cloud, and there are other cloud offerings like from IBM, but you can also run it on-premise for example, that's the alternative. So you can also have hybrid set scenarios where you really can put one part into the cloud, the other part on-prem, and I think there's a big difference in that you have a much more flexibility and you can avoid this kind of Windows login compared to AWS Lambda. >> Because Knative provides specifications and performance tests, so you can move from one server to another. If you are on IBM offering that's using Knative, and if you go to a Google offering- >> A google offering. >> That's on Knative, or a Red Hat offering on Knative, it should be seamless because they're both conforming to the same specifications of Knative. Whereas if you are in Lambda, there are custom deployments, so you are only going to be able to run those workloads only on AWS. >> So KnativeCon, co-located event as part of KubeCon, I'm curious as to the level of effort in the user interaction for deploying Knative. 'Cause when I think about Lambda or cloud-run or one of the other functions as a servers, there is no backend that I have to worry about. And I think this is where some of the debate becomes over serverless versus some other definition. What's the level of lifting that needs to be done to deploy Knative in my Kubernetes environment? >> So if you like... >> Is this something that comes as based part of the OpenShift install or do I have to like, you know, I have to... >> Go ahead, you answer first. >> Okay, so actually for OpenShift, it's a code layer product. So you have this catalog of operator that you can choose from, and OpenShift Serverless is one part of that. So it's really kind of a one click install where you have also get a default configuration, you can flexibly configure it as you like. Yeah, we think that's a good user experience and of course you can go to these cloud offerings like Google Cloud one or IBM Code Engine, they just have everything set up for you. And the idea of other different alternatives, you have (indistinct) charts, you can install Knative in different ways, you also have options for the backend systems. For example, we mentioned that when an event comes in, then there's a broker in the middle of something which dispatches all the events to the servers, and there you can have a different backend system like Kafka or AMQ. So you can have very production grade messaging system which really is responsible for delivering your events to your servers. >> Now, Knative has recently, I'm sorry, did I interrupt you? >> No, I was just going to say that Knative, when we talk about, we generally just talk about the serverless deployment model, right? And the Eventing gets eclipsed in. That Eventing which provides this infrastructure for producing and consuming event is inherent part of Knative, right? So you install Knative, you install Eventing, and then you are ready to connect all your disparate systems through Events. With CloudEvents, that's the specification we use for consistent and portable events. >> So Knative recently admitted to the, or accepted by the Cloud Native Computing Foundation, incubating there. Congratulations, it's a big step. >> Thank you. >> Thanks. >> How does that change the outlook for Knative adoption? >> So we get a lot of support now from the CNCF which is really great, so we could be part of this conference, for example which was not so easy before that. And we see really a lot of interest and we also heard before the move that many contributors were not, started into looking into Knative because of this kind of non being part of a mutual foundation, so they were kind of afraid that the project would go away anytime like that. And we see the adoption really increases, but slowly at the moment. So we are still ramping up there and we really hope for more contributors. Yeah, that's where we are. >> CNCF is almost synonymous with open source and trust. So, being in CNCF and then having this first KnativeCon event as part of KubeCon, we are hoping, and it's a recent addition to CNCF as well, right? So we are hoping that this events and these interviews, this will catapult more interest into serverless. So I'm really, really hopeful and I only see positive from here on out for Knative. >> Well, I can sense the excitement. KnativeCon sold out, congratulations on that. >> Thank you. >> I can talk about serverless all day, it's a topic that I really love, it's a fascinating way to build applications and manage applications, but we have a lot more coverage to do today on "theCUBE" from Spain. From Valencia, Spain, I'm Keith Townsend along with Paul Gillin, and you're watching "theCUBE," the leader in high-tech coverage. (gentle upbeat music)

>>Hey, welcome back everyone to the cubes coverage of eaters reinvent 2021. So our third day wall-to-wall coverage. I'm my coach, Dave Alonzo. He we're getting all the action two sets in person. It's also a virtual hybrid events with a lot of great content online, bringing you all the fresh voices, all the knowledge, all the news and all the action and got great guests here today. As your renderer, managing director of AWS is Europe, middle east, and Africa also known as EMIA. Welcome to the cube. Welcome, >>Welcome. Thanks for coming on. Lovely to be here. >>So Europe is really hot. Middle east Africa. Great growth. The VC culture in Europe specifically has been booming this year. A lot of great action. We've done many cube gigs out there talking to folks, uh, entrepreneurship, cloud, native growth, and then for us it's global. It's awesome. So first question got to ask you is, is you're new to AWS? What brought you here? >>Yeah, no, John, thank you so much. I've been here about three and a half months now, actually. Um, so what brought me here? Um, I have been in and around the tech world since I was a baby. Um, my father was an entrepreneur. I sold fax machines and microfilm equipment in my early days. And then my career has spanned technology in some form or the other. I was at EMC when we bought VMware. Uh, I was a Colt when we did a FinTech startup joined Schneider in my background, which is industrial tech. So I guess I'm a bit of a tech nerd, although I'm not an engineer, that's for sure. The other thing is I've spent a huge part of my career advising clients. And so while I was at McKinsey on business transformation and cloud keeps coming up, especially post pandemic, huge, huge, huge enabler, right of transformation. So when I got the call from AWS, I thought here's my opportunity to finally take what companies are wrestling with, bring together a pioneer in cloud with our enterprise and start-up and SMB clients connect those dots between business and technology and make things happen. So it real magic. So that's what brought me here. And I guess the only other thing to say is I'd heard a lot of other culture, customer mash, obsession, and leadership principles. >>That's why I'm here. It's been a great success. I got to ask you too, now that your new ostium McKinsey, even seeing the front lines, all the transformation, the pandemic has really forced everybody globally to move faster. Uh, things like connect were popular in EMEA. How, how is that going out? There's at the same kind of global pressure on the digital transformation with cloud? What are you seeing out there? >>I've been traveling since I joined, uh, around 10 of the countries already. So Ben planes, trains, automobiles, and what you definitely see is massive acceleration. And I think it's around reinvention of the business. So people are adopting cloud because it's obviously there's cost reasons. There's MNA reasons. There's really increasingly more about innovating. How do I innovate my business? How do I reinvent my business? So you see that constantly. Um, and whether you're a enterprise company or you're a startup, they're all adopting cloud in different, different ways. Um, I mean, I want to tell a core to stack because it's really interesting. And Adam mentioned this in his keynote five to 15% only of workloads have moved to the cloud. So there's a tremendous runway ahead of us. Um, and the three big things on people's minds helped me become a tech company. So it doesn't matter who you are, you're retail, whether you're life sciences or healthcare. You've probably heard about the Roche, uh, work that we're doing with Roche around accelerating R and D with data, or if you're a shoes Addie desk, how do you accelerate again, your personalized experiences? So it doesn't matter who you have helped me become a tech company, give me skills, digital skills, and then help me become a more sustainable company. Those are the three big things I'm thinking of. >>So a couple of things to unpack there. So think about it. Transformation. We still have a long way to go to your point, whatever 10, 15%, depending on which numbers you look at. We've been talking a lot in the cube about the next decade around business transformation, deeper business integration, and the four smarts to digital. And the woke us up to that, accelerated that as you say, so as you travel around to customers in AMEA, what are you hearing with regard to that? I mean, many customers maybe didn't have time to plan. Now they can sit back and take what they've learned. What are you hearing? >>Yeah. And it's, it's a little bit different in different places, right? So, I mean, if you start, if you look at, uh, you know, our businesses, for example, in France, if you look at our businesses in Iberia or Italy, a lot of them are now starting they're on the, at least on the enterprise front, they are now starting to adopt cloud. So they stepping back and thinking about their overall strategy, right? And then the way that they're doing it is actually they're using data as the first trigger point. And I think that makes it easier to migrate because if you, if you look at large enterprises and if you think of the big processes that they've got and all the mainframes and everything that they need to do, if you S if you look at it as one big block, it's too difficult. But when you think about data, you can actually start to aggregate all of your data into one area and then start to analyze and unpack that. >>So I think what I'm seeing for sure is in those countries, data is the first trigger. If you go out to Israel, well that you've got all, it's really start up nation as you know, right. And then we've got more of the digital natives and they want to, you know, absorb all of the innovation that we're throwing at them. And you've heard a lot here at reinvent on some of the things, whether it's digital twins or robotics, or frankly, even using 5g private network, we've just announcement. They are adopting innovation and really taking that in. So it really does differ, but I think the one big message I would leave you with is bringing industry solutions to business is critical. So rather than just talking it and technology, we've got to be able to bring some of what we've done. So for example, the Goldman Sachs financial cloud, bring that to the rest of financial services companies and the media, or if you take the work we're doing on industrials and IOT. So it's really about connecting what industry use cases with. >>What's interesting about the Goldman Dave and I were commenting. I think we coined the term, the story we wrote on Thursday last week, and then PIP was Sunday superclouds because you look at the rise of snowflake and Databricks and Goldman Sachs. You're going to start to see people building on AWS and building these super clouds because they are taking unique platform features of AWS and then sacrificing it for their needs, and then offering that as a service. So there's kind of a whole nother tier developing in the natural evolution of clouds. So the partners are on fire right now because the creativity, the market opportunities are there to be captured. So you're seeing this opportunity recognition, opportunity, capture vibe going on. And it's interesting. I'd love to get your thoughts on how you see that, because certainly the VCs are here in force. I did when I saw all the top Silicon valley VCs here, um, and some European VCs are all here. They're all seeing this. >>So pick up on two things you mentioned that I think absolutely spot on. We're absolutely seeing with our partners, this integration on our platform is so important. So we talk about the power of three, which is you bring a JSI partner, you bring an ISV partner, you bring AWS, you create that power of three and you take it to our customers. And it doesn't matter which industry we are. Our partner ecosystem is so rich. The Adam mentioned, we have a hundred thousand partners around the world, and then you integrate that with marketplace. Um, and the AWS marketplace just opens the world. We have about 325,000 active customers on marketplace. So sassiphy cation integration with our platform, bringing in the GSI and the NSIs. I think that's the real power to, to, to coming back to your point on transformation on the second one, the unicorns, you know, it's interesting. >>So UK France, um, Israel, Mia, I spent a lot of time, uh, recently in Dubai and you can see it happening there. Uh, Africa, Nigeria, South Africa, I mean all across those countries, you're saying huge amount of VC funding going in towards developers, towards startups to at scale-ups more and more of a, um, our startup clients, by the way, uh, are actually going IPO. You know, initially it used to be a lot of M and a and strategic acquisitions, but they have actually bigger aspirations and they're going IPO and we've seen them through from when they were seed or pre-seed all the way to now that they are unicorns. Right? So that there's just a tremendous amount happening in EMEA. Um, and we're fueling that, you know, you know, I mean, born in the cloud is easy, right? In terms of what AWS brings to the table. >>Well, I've been sacred for years. I always talked to Andy Jassy about this. Cause he's a big sports nut. When you bring like these stadiums to certain cities that rejuvenates and Amazon regions are bringing local rejuvenation around the digital economies. And what you see with the startup culture is the ecosystems around it. And Silicon valley thrives because you have all the service providers, you have all the fear of failure goes away. There's support systems. You start to see now with AWS as ecosystem, that same ecosystem support the robustness of it. So, you know, it's classic, rising tide floats all boats kind of vibe. So, I mean, we don't really have our narrative get down on this, but we're seeing this ecosystem kind of play going on. Yeah. >>And actually it's a real virtuous circle, or we call flywheel right within AWS because a startup wants to connect to an enterprise. An enterprise wants to connect to a startup, right? A lot of our ISV partners, by the way, were startups. Now they've graduated and they're like very large. So what we are, I see our role. And by the way, this is one of the other reasons I came here is I see our role to be able to be real facilitators of these ecosystems. Right. And, you know, we've got something that we kicked off in EMEA, which I'm really proud of called our EMEA startup loft accelerator. And we launched that a web summit. And the idea is to bring startups into our space virtually and physically and help them build and help them make those connections. So I think really, I really do think, and I enterprise clients are asking us all the time, right? Who do I need to involve if I'm thinking IOT, who do I need to involve if I want to do something with data. And that's what we do. Super connectors, >>John, you mentioned the, the Goldman deal. And I think it was Adam in his keynote was talking about our customers are asking us to teach them how to essentially build a Supercloud. I mean, our words. But so with your McKinsey background, I would imagine there's real opportunities there, especially as you, I hear you talk about IMIA going around to see customers. There must be a lot of, sort of non-digital businesses that are now transforming to digital. A lot of capital needs there, but maybe you could talk about sort of how you see that playing out over the next several years in your role and AWS's role in affecting that transfer. >>Yeah, no, absolutely. I mean, you're right actually. And I, you know, maybe I will, from my past experience pick up on something, you know, I was in the world of industry, uh, with Schneider as an example. And, you know, we did business through the channel. Um, and a lot of our channel was not digitized. You know, you had point of sale, electrical distributors, wholesalers, et cetera. I think all of those businesses during the pandemic realized that they had to go digital and online. Right. And so they started from having one fax machine in a store. Real literally I'm not kidding nothing else to actually having to go online and be able to do click and collect and various other things. And we were able with AWS, you can spin up in minutes, right. That sort of service, right. I love the fact that you have a credit card you can get onto our cloud. >>Right. That's the whole thing. And it's about instances. John Adam talked about instances, which I think is great. How do businesses transform? And again, I think it's about unpacking the problem, right? So what we do a lot is we sit down with our customers and we actually map a migration journey with them, right? We look across their core infrastructure. We look at their SAP systems. For example, we look at what's happening in the various businesses, their e-commerce systems, that customer life cycle value management systems. I think you've got to go business by business by business use case by use case, by use case, and then help our technology enable that use case to actually digitize. And whether it's front office or back office. I think the advantages are pretty clear. It's more, I think the difficulty is not technology anymore. The difficulty is mindset, leadership, commitment, the operating model, the organizational model and skills. And so what we have to do is AWS is bringing not only our technology, but our culture of innovation and our digital innovation teams to help our clients on that journey >>Technology. Well, we really appreciate you taking the time coming on the cube. We have a couple more minutes. I do want to get into what's your agenda. Now that you're got you're in charge, got the landscape and the 20 mile stare in front of you. Cloud's booming. You got some personal passion projects. Tell us what your plans are. >>So, um, three or four things, right? Three or four, really big takeaways for me is one. I, I came here to help make sure our customers could leverage the power of the cloud. So I will not feel like my job's been done if I haven't been able to do that. So, you know, that five to 15% we talked about, we've got to go 50, 60, 70%. That that's, that's the goal, right? And why not a hundred percent at some point, right? So I think over the next few years, that's the acceleration we need to help bring in AMEA Americas already started to get there as you know, much more, and we need to drive that into me. And then eventually our APJ colleagues are going to do the same. So that's one thing. The other is we talked about partners. I really want to accelerate and expand our partner ecosystem. >>Um, we have actually a huge growth by the way, in the number of partners signing up the number of certifications they're taking, I really, really want to double down on our partners and actually do what they ask us for, which is join. Co-sell joined marketing globalization. So that's two, I think the third big thing is when you mentioned industry industry industry, we've got to bring real use cases and solutions to our customers and not only talk technology got to connect those two dots. And we have lots of examples to bring by the way. Um, and then for hire and develop the best, you know, we've got a new LP as you know, to strive to be at its best employer. I want to do that in a Mia. I want to make sure we can actually do that. We attract, we retain and we grow and we develop that. >>And the diversity has been a huge theme of this event. It's front and center in virtually every company. >>I am. I'm usually passionate about diversity. I'm proud actually that when I was back at Schneider, I launched something called the power women network. We're a network of a hundred senior women and we meet every month. I've also got a podcast out there. So if anyone's listening, it's called power. Women's speak. It is, I've done 16 over the pandemic with CEOs of women podcast, our women speak >>Or women speak oh, >>And Spotify and >>Everything else. >>And, um, you know, what I love about what we're doing is AWS on diversity and you heard Adam onstage, uh, talk to this. We've got our restock program where we really help under employed and unemployed to get a 12 week intensive course and get trained up on thought skills. And the other thing is, get it helping young girls, 12 to 15, get into stem. So lots of different things on the whole, but we need to do a lot more of course, on diversity. And I look forward to helping our clients through that as well. >>Well, we had, we had the training VP on yesterday. It's all free trainings free. >>We've got such a digital skills issue that I love that we've said 29 million people around the world, free cloud training. >>Literally the th the, the gap there between earnings with cloud certification, you can be making six figures like with cloud training. So, I mean, it's really easy. It's free. It's like, it's such a great thing. >>Have you seen the YouTube video on Charlotte Wilkins? Donald's fast food. She changed her mind. She wanted to take Korea. She now has a tech career as a result of being part of restock. Awesome. >>Oh, really appreciate. You got a lot of energy and love, love the podcast. I'm subscribing. I'm going to listen. We love doing the podcast as well. So thanks for coming on the >>Queue. Thank you so much for having me >>Good luck on anemia and your plans. Thank you. Okay. Cube. You're watching the cube, the leader in global tech coverage. We go to the events and extract the signal from the noise. I'm John furrier with Dave, a lot to here at re-invent physical event in person hybrid event as well. Thanks for watching.

>>Yeah, >>yeah. Hello and welcome to this track to creating engaging analytics experiences for all. I'm Hannah Sinden Thought spots Omiya director of marketing on. I'm delighted to have you here today. A boy Have we got to show for you now? I might be a little bit biased as the host of this track, but in my humble opinion, you've come to a great place to start because this track is all about everything. Thought spot. We'll be talking about embedded search in a I thought spot one spot I. Q. We've got great speakers from both thoughts about andare customers as well as some cool product demos. But it's not all product talk. We'll be looking at how to leverage the tech to give your users a great experience. So first up is our thoughts about one deep dive. This session will be showing you how we've built on our already superb search experience to make it even easier for users across your company to get insight. We've got some great speakers who are going to be telling you about the cool stuff they've been working on to make it really fantastic and easy for non technical people to get the answers they need. So I'm really delighted to introduce Bob Baxley s VP of design and experience That thought spot on Vishal Kyocera Thought spots director of product management. So without further ado, I'll hand it over to Bob. Thanks, >>Hannah. It's great to be here with everybody today and really excited to be able to present to you thought spot one. We've been working on this for months and months and are super excited to share it before we get to the demo with Shawl, though, I just want to set things up a little bit to help people understand how we think about design here. A thought spot. The first thing is that we really try to think in terms of thought. Spot is a consumer grade product, terms what we wanted. Consumer grade you x for an analytics. And that means that for reference points rather than looking at other enterprise software companies, we tend to look at well known consumer brands like Google, YouTube and WhatsApp. We firmly believe that people are people, and it doesn't matter if they're using software for their own usage or thought are they're using software at work We wanted to have a great experience. The second piece that we were considering with thoughts about one is really what we call the desegregation of bundles. So instead of having all of your insights wraps strictly into dashboards, we want to allow users to get directly to individual answers. This is similar to what we saw in music. Were instead of you having to buy the entire album, of course, you could just buy individual songs. You see this in iTunes, Spotify and others course. Another key idea was really getting rid of gate keepers and curators and kind of changing people from owning the information, helping enable users to gather together the most important and interesting insights So you can follow curator rather than feeling like you're limited in the types of information you can get. And finally, we wanted to make search the primary way, for people are thinking about thought spot. As you'll see, we've extended search from beyond simply searching for your data toe, also searching to be able to find pin boards and answers that have been created by other people. So with that, I'll turn it over to my good friend Rachel Thio introduce more of thought, spot one and to show you a demo of the product. >>Thank you, Bob. It's a pleasure to be here to Hello, everyone. My name is Michelle and Andy, product management for Search. And I'm really, really excited to be here talking about thoughts about one our Consumer analytics experience in the Cloud. Now, for my part of the talk, we're gonna first to a high level overview of thoughts about one. Then we're going to dive into a demo, and then we're gonna close with just a few thoughts about what's coming next. So, without any today, let's get started now at thought spot. Our mission is to empower every user regardless of their expertise, to easily engage with data on make better data driven decisions. We want every user, the nurse, the neighborhood barista, the teacher, the sales person, everyone to be able to do their jobs better by using data now with thoughts about one. We've made it even more intuitive for all these business users to easily connect with the insights that are most relevant for them, and we've made it even easier for analysts to do their jobs more effectively and more efficiently. So what does thoughts about one have? There's a lot off cool new features, but they all fall into three main categories. The first main category is enhanced search capabilities. The second is a brand new homepage that's built entirely for you, and the third is powerful tools for the analysts that make them completely self service and boost their productivity. So let's see how these work Thought Spot is the pioneer for search driven analytics. We invented search so that business users can ask questions of data and create new insights. But over the years we realized that there was one key piece off functionality that was missing from our search, and that was the ability to discover insights and content that had already been created. So to clarify, our search did allow users to create new content, but we until now did not have the ability to search existing content. Now, why does that matter? Let's take an example. I am a product manager and I am always in thought spot, asking questions to better understand how are users are using the product so we can improve it now. Like me, A lot of my colleagues are doing the same thing. Ah, lot of questions that I asked have already been answered either completely are almost completely by many of my colleagues, but until now there's been no easy way for me to benefit from their work. And so I end up recreating insights that already exists, leading to redundant work that is not good for the productivity off the organization. In addition, even though our search technology is really intuitive, it does require a little bit of familiarity with the underlying data. You do need to know what metric you care about and what grouping you care about so that you can articulate your questions and create new insights. Now, if I consider in New employees product manager who joins Hotspot today and wants to ask questions, then the first time they use thought spot, they may not have that data familiarity. So we went back to the drawing board and asked ourselves, Well, how can we augment our search so that we get rid off or reduced the redundant work that I described? And in addition, empower users, even new users with very little expertise, maybe with no data familiarity, to succeed in getting answers to their questions the first time they used Hot Spot, and we're really proud and excited to announce search answers. Search answers allows users to search across existing content to get answers to their questions, and its a great compliment to search data, which allows them to search the underlying data directly to create new content. Now, with search answers were shipping in number of cool features like Answer Explainer, Personalized search Results, Answer Explorer, etcetera that make it really intuitive and powerful. And we'll see how all of these work in action in the demo. Our brand new homepage makes it easier than ever for all these business users to connect with the insights that are most relevant to them. These insights could be insights that these users already know about and want to track regularly. For example, as you can see, the monitor section at the top center of the screen thes air, the KP eyes that I may care most about, and I may want to look at them every day, and I can see them every day right here on my home page. By the way, there's a monitoring these metrics in the bankrupt these insights that I want to connect with could also be insights that I want to know more about the search experience that I just spoke about ISS seamlessly integrated into the home page. So right here from the home page, I can fire my searchers and ask whatever questions I want. Finally, and most interestingly, the homepage also allows me to connect with insights that I should know about, even if I didn't explicitly ask for them. So what's an example? If you look at the panel on the right, I can discover insights that are trending in my organization. If I look at the panel on the left, I can discover insights based on my social graph based on the people that I'm following. Now you might wonder, How do we create this personalized home page? Well, our brand new, personalized on boarding experience makes it a piece of cake as a new business user. The very first time I log into thought spot, I pay three people I want to follow and three metrics that I want to follow, and I picked these from a pool of suggestions that Ai has generated. And just like that, the new home page gets created. And let's not forget about analysts. We have a personalized on boarding experience specifically for analysts that's optimized for their needs. Now, speaking of analysts, I do want to talk about the tools that I spoke off earlier that made the analysts completely self service and greatly boost their productivity's. We want analysts to go from zero to search in less than 30 minutes, and with our with our new augmented data modeling features and thoughts about one, they can do just that. They get a guided experience where they can connect, model and visualize their data. With just a few clicks, our AI engine takes care off a number of tasks, including figuring out joints and, you know, cleaning up column names. In fact, our AI engine also helps them create a number of answers to get started quickly so that these analysts can spend their time and energy on what matters most answering the most complicated and challenging and impactful questions for the business. So I spoke about a number of different capabilities off thoughts about one, but let's not forget that they are all packaged in a delightful user experience designed by Bob and his team, and it powers really, really intuitive and powerful user flows, from personalized on boarding to searching to discover insights that already exist on that are ranked based on personalized algorithms to making refinements to these insights with a assistance to searching, to create brand new insights from scratch. And finally sharing all the insights that you find interesting with your colleagues so that it drives conversations, decisions and, most importantly, actions so that your business can improve. With that said, let's drive right into the demo for this demo. We're going to use sales data set for a company that runs a chain off retail stores selling apparel. Our user is a business user. Her name is Charlotte. She's a merchandiser, She's new to this company, and she is going to be leading the genes broader category. She's really excited about job. She wants to use data to make better decisions, so she comes to thought spot, and this is what she sees. There are three main sections on the home page that she comes to. The central section allows you to browse through items that she has access to and filter them in various ways. Based for example, on author or on tags or based on what she has favorited. The second section is this panel on the right hand side, which allows her to discover insights that are trending within her company. This is based on what other people within her company are viewing and also personalized to her. Finally, there's this search box that seamlessly integrated into the home page. Now Charlotte is really curious to learn how the business is doing. She wants to learn more about sales for the business, so she goes to the search box and searches for sales, and you can see that she's taken to a page with search results. Charlotte start scanning the search results, and she sees the first result is very relevant. It shows her what the quarterly results were for the last year, but the result that really catches her attention is regional sales. She'd love to better understand how sales are broken down by regions. Now she's interested in the search result, but she doesn't yet want to commit to clicking on it and going to that result. She wants to learn more about this result before she does that, and she could do that very easily simply by clicking anywhere on the search result card. Doing that reveals our answer. Explain our technology and you can see this information panel on the right side. It shows more details about the search results that she selected, and it also gives her an easy to understand explanation off the data that it contains. You can see that it tells her that the metrics sales it's grouped by region and splitter on last year. She can also click on this preview button to see a preview off the chart that she would see if she went to that result. It shows her that region is going to be on the X axis and sales on the Y axis. All of this seems interesting to her, and she wants to learn more. So she clicks on this result, and she's brought to this chart now. This contains the most up to date data, and she can interact with this data. Now, as she's looking at this data, she learns that Midwest is the region with the highest sales, and it has a little over $23 million in sales, and South is the region with the lowest sales, and it has about $4.24 million in sales. Now, as Charlotte is looking at this chart, she's reminded off a conversation she had with Suresh, another new hire at the company who she met at orientation just that morning. Suresh is responsible for leading a few different product categories for the Western region off the business, and she thinks that he would find this chart really useful Now she can share this chart with Suresh really easily from right here by clicking the share button. As Charlotte continues to look at this chart and understand the data, she thinks, uh, that would be great for her to understand. How do these sales numbers across regions look for just the genes product category, since that's the product category that she is going to be leading? And she can easily narrow this data to just the genes category by using her answer Explorer technology. This panel on the right hand side allows her to make the necessary refinements. Now she can do that simply by typing in the search box, or she can pick from one off the AI generated suggestions that are personalized for her now. In this case, the AI has already suggested genes as a prototype for her. So with just a single click, she can narrow the data to show sales data for just jeans broken down by region. And she can see that Midwest is still the region with the highest sales for jeans, with $1.35 million in sales. Now let's spend a minute thinking about what we just saw. This is the first time that Charlotte is using Thought spot. She does not know anything about the data sources. She doesn't know anything about measures or attributes. She doesn't know the names of the columns. And yet she could get to insights that are relevant for her really easily using a search interface that's very much like Google. And as she started interacting with search results, she started building a slightly better understanding off the underlying data. When she found an insight that she thought would be useful to a colleague offers, it was really seamless for her to share it with that colleague from where she Waas. Also, even though she's searching over content that has already been created by her colleagues in search answers. She was in no way restricted to exactly that data as we just saw. She could refine the data in an insight that she found by narrowing it. And there's other things you can do so she could interact with the data for the inside that she finds using search answers. Let's take a slightly more complex question that Charlotte may have. Let's assume she wanted to learn about sales broken down by, um, by category so that she can compare her vertical, which is jeans toe other verticals within the company. Again, she can see that the very first result that she gets is very relevant. It shows her search Sorry, sales by category for last year. But what really catches her attention about this result is the name of the author. She's thrilled to note that John, who is the author of this result, was also an instructor for one off for orientation sessions and clearly someone who has a lot of insight into the sales data at this company. Now she would love to see mawr results by John, and to do that, all she has to do is to click on his name now all of the search results are only those that have been authored by John. In fact, this whole panel at the top of the results allow her to filter her search results or sort them in different ways. By clicking on these authors filter, she can discover other authors who are reputed for the topic that she's searching for. She can also filter by tags, and she can sort these results in different ways. This whole experience off doing a search and then filtering search results easily is similar to how we use e commerce search engines in the consumer world. For example, Amazon, where you may search for a product and then filter by price range or filter by brand. For example, Let's also spend a minute talking about how do we determine relevance for these results and how they're ranked. Um, when considering relevance for these results, we consider three main categories of things. We want to first make sure that the result is in fact relevant to the question that the user is asking, and for that we look at various fields within the result. We look at the title, the author, the description, but also the technical query underpinning that result. We also want to make sure that the results are trustworthy, because we want users to be able to make business decisions based on the results that they find. And for that we look at a number of signals as well. For example, how popular that result is is one of those signals. And finally, we want to make sure the results are relevant to the users themselves. So we look at signals to personalize the result for that user. So those are all the different categories of signals that we used to determine overall ranking for a search result. You may be wondering what happens if if Charlotte asks a question for which nobody has created any answer, so no answers exist. Let's say she wants to know what the total sales of genes for last year and no one's created that well. It's really easy for her to switch from searching for answers, which is searching for content that has already been created to searching the data directly so she can create a new insight from scratch. Let's see how that works. She could just click here, and now she's in the search data in her face and for the question that I just talked about. She can just type genes sales last year. And just like that, she could get an answer to her question. The total sales for jeans last year were almost $4.6 million. As you can see, the two modes off search searching for answers and searching, the data are complementary, and it's really easy to switch from one to the other. Now we understand that some business users may not be motivated to create their own insights from scratch. Or sometimes some of these business users may have questions that are too complicated, and so they may struggle to create their own inside from scratch. Now what happens usually in these circumstances is that these users will open a ticket, which would go to the analyst team. The analyst team is usually overrun with these tickets and have trouble prioritizing them. And so we started thinking, How can we make that entire feedback loop really efficient so that analysts can have a massive impact with as little work as possible? Let me show you what we came up with. Search answers comes with this system generated dashboard that analysts can see to see analytics on the queries that business users are asking in search answers so it contains high level K P. I is like, You know how many searches there are and how many users there are. It also contains one of the most popular queries that users are asking. But most importantly, it contains information about what are popular queries where users are failing. So the number on the top right tells you that about 10% off queries in this case ended with no results. So the user clearly failed because there were no results on the table. Right below it shows you here are the top search queries for original results exist. So, for example, the highlighted row there says jean sales with the number three, which tells the analysts that last week there were three searches for the query jean sales and the resulted in no results on search answers. Now, when an analyst sees a report like this, they can use it to prioritize what kind of content they could be creating or optimizing. Now, in addition to giving them inside into queries which led to no results or zero results. This dashboard also contains reports on creatives that lead to poor results because the user did get some results but didn't click on anything, meaning that they didn't get the answer that they were looking for. Taking all these insights, analysts can better prioritize and either create or optimize their content to have maximum impact for their business users with the least amount of for. So that was the demo. As you can see with search answers, we've created a very consumer search interface that any business user can use to get the answers to their questions by leveraging data or answers that have already been created in the system by other users in their organization. In addition, we're creating tools that allow analysts toe create or optimized content that can have the highest impact for these business users. All right, so that was the demo or thoughts about one and hope you guys liked it. We're really excited about it. Now Let me just spend a minute talking about what's coming next. As I've mentioned before, we want to connect every business user with the insights that are most relevant for them, and for that we will continue to invest in Advanced AI and personalization, and some of the ways you will see it is improved relevance in ranking in recommendations in how we understand your questions across the product within search within the home page everywhere. The second team that will continue to invest in is powerful analyst tools. We talked about tools and, I assure you, tools that make the analysts more self service. We are committed to improving the analyst experience so that they can make the most off their time. An example of a tool that we're really excited about is one that allows them to bridge the vocabulary difference that this even business user asks questions. A user asked a question like revenue, but the column name for the metric in the data set its sales. Now analysts can get insights into what are the words that users air using in their questions that aren't matching anything in the data set and easily create synonyms so that that vocabulary difference gets breached. But that's just one example of how we're thinking about empowering the analysts so that with minimal work, they can amplify their impact and help their business users succeed. So there's a lot coming, and we're really excited about how we're planning to evolve thoughts about one. With all that said, Um, there's just, well, one more thing that my friend Bob wants to talk to you guys about. So back to you, Bob. >>Thanks, Michelle. It's such a great demo and so fun to see all the new work that's going on with thought. Spot one. All the happenings for the new features coming out that will be under the hood. But of course, on the design side, we're going to continue to evolve the front end as well, and this is what we're hoping to move towards. So here you'll see a new log in screen and then the new homepage. So compared to the material that you saw just a few minutes ago, you'll notice this look is much lighter. A little bit nicer use of color up in the top bar with search the features over here to allow you to switch between searching against answers at versus creating new answers, the settings and user profile controls down here and then on the search results page itself also lighter look and feel again. Mork color up in the search bar up the top. A little bit nicer treatments here. We'll continue to evolve the look and feel the product in coming months and quarters and look forward to continue to constantly improving thoughts about one Hannah back to you. >>Thanks, Bob, and thank you both for showing us the next generation of thought spot. I'd love to go a bit deeper on some of the points you touched on there. I've got a couple of questions here. Bob, how do you think about designing for consumer experience versus designing for enterprise solutions? >>Yes, I mentioned Hannah. We don't >>really try to distinguish so much between enterprise users and consumer users. It's really kind of two different context of use. But we still always think that users want some product and feature and experience that's easy to use and makes sense to them. So instead of trying to think about those is two completely different design processes I think about it may be the way Frank Lloyd Wright would approached architecture. >>Er I >>mean, in his career, he fluidly moved between residential architecture like falling water and the Robie House. But he also designed marquis buildings like the Johnson wax building. In each case, he simply looked at the requirements, thought about what was necessary for those users and designed accordingly. And that's really what we do. A thought spot. We spend time talking to customers. We spend time talking to users, and we spent a lot of time thinking through the problem and trying to solve it holistically. And it's simply a possible >>thanks, Bob. That's a beautiful analogy on one last question for you. Bischel. How frequently will you be adding features to this new experience, >>But I'm glad you asked that, Hannah, because this is something that we are really really excited about with thoughts about one being in the cloud. We want to go really, really fast. So we expect to eventually get to releasing new innovations every day. We expect that in the near future, we'll get to, you know, every month and every week, and we hope to get to everyday eventually fingers crossed on housing. That can happen. Great. Thanks, >>Michelle. And thank you, Bob. I'm so glad you could all join us this morning to hear more about thoughts about one. Stay close and get ready for the next session. which will be beginning in a few minutes. In it will be introduced to thoughts for >>everywhere are >>embedded analytics product on. We'll be hearing directly from our customers at Hayes about how they're using embedded analytics to help healthcare providers across billing compliance on revenue integrity functions. To make more informed decisions on make effective actions to avoid risk and maximize revenue. See you there.

>>long from Las Vegas. It's the Q covering a ws re invent 2019. Brought to you by Amazon Web service is and in along with its ecosystem partners. >>Welcome back to the Cube. We are in Las Vegas, Lisa Martin with John Wall's. I'm very excited that we're kind of color coordinated >>way. Didn't compare notes to begin with, but certainly the pink thing. It's worth it if >>you like. You complete me. >>Oh, thank you. Really, Joe, I don't hear that very often. My wife says that >>you tell that we're at the end of day one of the coverage of A W s three in bed. Good day, though. Yes, it has been very excited. We have a couple of guests joining us for our final segment on this. Please welcome. We have Bill Gerard CTO of Digital Transformation and Scale solutions at Intel Bill, welcome to our show. >>Thank you very much. Happy to be here >>And one of our friends. That's no stranger to the Cube. One of our former host, Bobby Allyn, the CEO of Cloud Generate. Bobby. >>Thank you. Thank you for having us. >>Guys, here we are. This there has not been a lull in the background noise all day. Not reinvent day one. But Bobby want to start with you. Talk to her audience about cloud genera. Who are you guys? What do you do? And what's different about what you're delivering? >>One of the first things is different about Claude Generous where we're located. So we're in Charlotte, which I call Silicon South. So we're kind of representing the East Coast, and we're a company that focuses, focuses on helping with workload, placement and transformation. So where you don't know whether something should go on from off grim. If you put it in Amazon, which service's should have consumed licensing models? Pricing models way help you make data driven decisions, right? So you're not just going based on opinion, you're going based on fact. >>And that's challenging because, you know, in the as, as John Ferrier would say, No Cloud Wanda Otto, which was compute network storage, it was the easy I shouldn't say easy, but the lift and shit applications that enterprises do are these workloads should go to the cloud. Now we have you know what's left over, and that's challenging for organization. Some of the legacy once can't move. How do you help from a Consul Tatum's down point that customers evaluate workloads? What data are they running? What the value that data has and if they are able to move some of those more challenging applications. >>So part of the framework for us, Lisa, is we want to make sure we understand what people are willing and able to change right, because sometimes it's not just about lower costs. Sometimes it's about agility, flexibility, deploying a different region. So what we often start with his wit is better look like you would assist us with life for your organization. And so then, based on that, we analyze the applications with an objective, data driven framework and then make sure the apse land where they're supposed to go. We're not selling any skewer product. We're selling advice to give you inside about what you should do, >>Bobby, I think. And maybe Bill to you could chime in here on this. If you give people a choice, What does this look like? What you know, What do you want? I don't want to do anything right. I want to stay put, right? But that obviously that's not an option, But you I'm sure you do get pushed back quite a bit from these almost the legacy mindset. And we've talked a lot about this whole transformation versus transition. Some people don't want to go, period. So how do you cajole them? Persuade them bring them along on this journey? Because it's gonna be a long trip. Yeah, I think you gotta pack a lunch. >>It's a good point. I think what we've seen, most of them have data experience that this is a tried and elements didn't get the results that they expected. This is where you know, the partnership that we have with call General. Really? You know that data driven, intelligent, based planning is super important, right? We want to really fundamentally health organizations move the right workloads, make sure they get the right results and not have to redo it. Right? And so part of that, you know, move when you're either past scars or not used to what you're doing. Give him the data and the information to be able to do that intelligently and make that as fast as they can. And you know, at the right, you know, experience in performance from a capability perspective. >>So so many businesses these days, if they're not legacy if they're not looking in the rear view mirror, what is the side mirror site? Objects are closer than they appear, even for Amazon. Right? For all of these companies, there are smaller organizations that might be born in a cloud compared to the legacy two words. And if they're not looking at, we have to transform from the top down digitally, truly transform. Their business may not be here in a year or two, so the choice and I think they need to pack a lunch and a hip flask for this because it's quite the journey. But I'm curious with the opportunity that cloud provides. When you have these consultation conversations, what are This? Could be so transformative not just to a business, but to a do an entire industry. Bill talked to us from your perspective about some of the things that you've seen and how this next generation of cloud with a I machine learning, for example, can can really transfer like what's the next industry that you think is prime to be really flipped upside down? >>Well, the good news is I think most of the industries in the segment that we talked to have realized they need to some level of transformation. So doing the business as usual really isn't an option to really grow and drive in the future. But I do think the next evolution really does center on what's happening in a I and analytics. Whether it's, you know, moving manufacturing from video based defect detection, supply chain integrity. You know what's happening from a retail was really the first in that evolution, but we see it in health care in Federal Data Center modernization, and it's really moving at a faster pace and adopting those cloud technologies wherever they needed, both in their data center in the public, cloud out of the edge. And we'll start to see a real shift from really consolidation in tow. Large hyper converts, data centers to distributed computing where everything again. And that's where we're excited about the work we're doing with the Amazon, the work we're doing with Eyes V partners to be at the capability where they need it, but I think it will be really the next. Evolution of service is everywhere. >>Never talk us through an example or use case of a customer that you're working with, a cloud genera with intel and and a W S. What does that trifecta look like for, say, a retailer or financial service is organization >>so that that looks like this? ELISA. When we when we talk about workload placement, we think that most companies look at that as a single question. It's at least a five fold question. Right there is the venue. There's the service. There's the configuration, the licensing model and the pricing model. You need to look at all five of those things. So even if you decided on a DBS is your strategic partner, we're not done yet. So we have a very large financialservices customer that I can't name publicly. But we've collaborated with them to analyze tens of thousands of workloads, some that go best off from some that go best on for him. And they need guidance and coaching on things like, Are you paying for redhead twice your pay for licensing on him? Are you also paying for that in the cloud? There are things that maybe should be running an RT s database as a service. Here's your opportunity to cut down on labor and shift some of the relationships tohave, toe re index and databases is not glamorous or differential to value for your business. Let's take advantage of what a TBS does well and make this better for your company. One of the things that I want to kind of introduce to piggyback on your question. We lean on people process technology as kind of the three, the three legged horse in the Enterprise. I want to change that people process product or people process problem. We're falling in love with the tech and getting lazy. Technology should be almost ubiquitous or under the covers to make a product better or to solve a problem for the customer. >>Well, maybe on that, I mean automation concern to come in and make a big play here because we're taking all these new tasks if you could automate them that you free your people, your developers to do their thing right. So you raise an interesting point on that about being lazy and relying on things. But yet you do want off put our offload some of these nasty not to free up that creativity and free up the people to do what they're supposed to be doing. It's a delicate balance, though, isn't it? It is. It is. This >>is where I think the data driven, you know, informed decisions important. We did a lot of research with Cloud Jenner and our customers, and there's really four key technical characteristics when evaluating workload. The 1st 1 of course, is the size of the data. Where is the created words They use Words that consumed the 2nd 1? Is the performance right? Either performance not only to other systems around it or the end user, but the performance of the infrastructure. What do you need out of the capability? The level of integration with other systems? And then, of course, security. We hear that time and again, right? Regulatory needs. What are we having from top secret data to company sensitive data? Really Getting that type of information to drive those workload placement decision becomes at the forefront of that on getting, you know, using cloud gender to help understand the number of interfaces in and out the sides of the data. The performance utilization of the system's really helps customers understand how to move the right workload. What's involved and then how to put that in the right eight of us instance, and use the right ideas capabilities, >>and you and you both have hit on something here because the complexity of this decision, because it's multi dimensional, you talked about the five points a little bit ago. Now you talked about four other factors. Sue, this is not a static environment, No, and to me that as you're making a decision, that point is what's very difficult for, I would assume for the people that you're interfacing with on the company level. Yes, because it's a moving target for them, right? They just it's it's dynamic and changing your data flows exponentially. Increasing capabilities are changing. How do you keep them from just breaking down? >>I don't want to jump in on that, because again, I'm going to repeat this again. That my thesis is often technology is the easy part. We need to have conversations about what we want to do. And so I had a conversation earlier today. Think of Amazon like a chef. They could make anything I want, but I need to decide what I want to eat. If I'm a vegan and he wants steak. That's not Amazons fault. If they can't cook something, that's a mismatch of a bad conversation. We need to communicate. So what I'm finding is a lot of executives are worried about this. There were Then you're going to give me the right the wrong answer to the right question. The reality is you may have the wrong question. First of all right, the question is usually further upstream, so the worry that you're gonna give me the wrong answer to the right question. But often you need to worry that you're getting your starting with the wrong question. You're gonna get the right answer asked the right question first. And then you got a chance to get to the final destination. But >>and then he in this multi cloud world that many organizations live in, mostly not My strategy could be by Emma A could be bi developer preference for different solutions. A lot of Serios air telling us we've inherited a lot of this multi cloud and technical debt. Exactly. So does not just compound the problem because to your point, I mean you think of one way we hear so many different stats about the number of clouds that on average enterprises using is like 5 to 9. That whole world. That's a reality for organizations. So in terms of how the business can be transformed by what you guys are doing together, it seems like there's a tremendous opportunity there. But to your point, Bobby, where do you start? How do you help them understand what? That right first question is at the executive level so that those four technical points that Bill talked about Tek thee you know, the executive staff is all on board with Yes, this is the question we're asking then will understand it. The technology is right. Sold >>it. It's got to start with, Really? What? The company's business imperatives, right? It can't start with an I t objective. It's it's Are we moving into new markets? Do we need thio deploy capabilities faster? Are we doing a digital customer experience? Transformation? Are we deploying new factories, new products into new regions, and so really the first areas? What's the core company strategy, imperatives of the business objectives? And >>then how >>does I t really help them achieve that? In some cases, it may be we have to shift and reduce our data center footprints way have to move capabilities to where we have a new region. Deployments, right? We've got to get him over to Europe. We don't have capabilities in Europe. We're going to Asia. I've got a mobile sales force now where I need to get that customer, meet the customer where they're doing, you know, in the retail store, and >>that >>really then leads quite simply, too. What are the capabilities that we have in house that we're using? >>How are >>they being utilized? And he's using them, and then how do we get them to where they need to be? Some cases accost, imperative. Some cases and agility, Time to market and another's and we're seeing this more often is really what are the new sets of technologies? A. I service is training in forgetting that we're not experience to do and set up, and we don't want to spend the time to go train our infrastructure teams on the technology. So we'll put our data scientists in there figuring out the right set of workloads, the right set of technology, that we can then transform and move our applications to utilize it really starts, I think with the business conversation, or what's the key inflection point that they're experiencing? >>And have you seen that change in the last few years that now it's where you know, cloud not cloud. What goes on Cloud was an I t conversation to your point, Bill. And then the CEO got involved in a little bit later. But now we're we're seeing and hearing the CEO has got to be involved from a business imperative perspective. >>Share some data, right? Uh, so, you know, a couple of years ago, everybody was pursuing cloud largely for cost. Agility started to become primary, and that's still very important. A lot of the internal enterprise data modernizations were essentially stalled a bit because they were trying to figure how much do we move to the the public cloud, right. We want to take advantage of those modern service is at that time, we did a lot of research with our partners. He was roughly 56% of enterprise workload for in their own data center. You know, the rest of them Republic Cloud. And then we saw really the work, the intelligent workload discussion that says we've had some false starts. Organizations now really consistently realize they need both, you know, their own infrastructure and public cloud, and we've actually seen on increase of infrastructure modernization. While they're moving more and more stuff to the cloud, they're actually growing there on centre. It's now roughly 59% on Prem today for that same business, and that's largely because they're using more. Cloud service is that they're also even using Maur on premise, and they're realizing it's a balance and not stalling one or starving one and then committing to the other the committing to both and really just growing the business where it needs to go. >>Strategic reasons. All right? >>Yes, well, there should be four strategic reasons. There aren't always back to your question about which question asked. One of the questions I often ask is, What do you think the benefits will be if you go to cloud? And part of what happens is is not a cloud capability? Problem is an expectation problem. You're not gonna put your GOP system in the cloud and dropped 30% costs in a month, and so that's where we need to have a conversation on, You know, let's iterating on what this is actually gonna look like. Let's evolve the organization. Let's change our thinking. And then the other part of this and this were clouded or an intel come in. Let's model with simulation looks like. So we're gonna take those legacy work clothes unless model containers. Let's model Micro Service is so before you have to invest in transformation to may not make sense. Let's see what the outcome's look like through simulation through a through M l and understand. Where does it make sense to apply? The resource is, you know, to double click on that solution that will help the business. >>I was gonna finish my last question, Bobby, with you saying, Why, Cloud General? But I think you just answered that. So last question for you, though, from from an expectation perspective, give me one of your favorite examples of customer whatever kind of industry there and that you've come in and helped them really level, set their expectations and kick that door wide open. >>That's tough, many >>to choose from. >>Yeah, let me let me try to tackle that one quickly. Store's computer databases. Those are all things that people look at I think what people are struggling with the most in terms of kind of expectations is what they're willing and able to change. So this is kind of what I leave on. Bill and I talked about this earlier today. A product is good, a plan is better. A partnership is best. Because with the enterprises of saying is, we're overwhelmed. Either fix it for me or get in there with me and do it right. Be in this together. So what we've learned is it's not about were close applications. It's all kind of the same. We need help. We're overwhelmed. I want a partner in telling Claude Juncker the get in this thing with me. Help me figure this out because I told you this cloud is at best a teenager. They just learned how to drive is very capable, but it needs some guard rails. >>I love that. Thanks you guys So much for explaining with Johnny what you guys are doing together and how you're really flipping the model for what customers need to be evaluated and what they need to be asking. We appreciate your time. >>Thank you for having us >>our pleasure. Thank you. for John Wall's I'm Lisa Martin. You've been watching the Cube at Reinvent 19 from Vegas. Wants to go tomorrow.

>>from Las Vegas. It's the Q covering. Next work. 2019 America's Do You buy Juniper Networks? Come back already. Jeffrey here with the Cube were in Las Vegas at Caesar's at the Juniper. Next work event. About 1000 people kind of going over a lot of new cool things. 400 gigs. Who knew that was coming out of new information for me? But that's not what we're here today. We're here for the fourth installment of around the Cube unpacking. I were happy to have all the winners of the three previous rounds here at the same place. We don't have to do it over the phone s so we're happy to have him. Let's jump into it. So winner of Round one was Bob Friday. He is the VP and CTO at Missed the Juniper Company. Bob, Great to see you. Good to be back. Absolutely. All the way from Seattle. Sharna Parky. She's a VP applied scientist at Tech CEO could see Sharna and, uh, from Google. We know a lot of a I happen to Google. Rajan's chef. He is the V p ay ay >>product management on Google. Welcome. Thank you, Christy. Here >>All right, so let's jump into it. So just warm everybody up and we'll start with you. Bob, What are some When you're talking to someone at a cocktail party Friday night talking to your mom And they say, What is a I What >>do you >>give him? A Zen examples of where a eyes of packing our lives today? >>Well, I think we all know the examples of the south driving car, you know? Aye, aye. Starting to help our health care industry being diagnosed cancer for me. Personally, I had kind of a weird experience last week at a retail technology event where basically had these new digital mirrors doing facial recognition. Right? And basically, you start to have little mirrors were gonna be a skeevy start guessing. Hey, you have a beard, you have some glasses, and they start calling >>me old. So this is kind >>of very personal. I have a something for >>you, Camille, but eh? I go walking >>down a mall with a bunch of mirrors, calling me old. >>That's a little Illinois. Did it bring you out like a cane or a walker? You know, you start getting some advertising's >>that were like Okay, you guys, this is a little bit over the top. >>Alright, Charlotte, what about you? What's your favorite example? Share with people? >>Yeah, E think one of my favorite examples of a I is, um, kind of accessible in on your phone where the photos you take on an iPhone. The photos you put in Google photos, they're automatically detecting the faces and their labeling them for you. They're like, Here's selfies. Here's your family. Here's your Children. And you know, that's the most successful one of the ones that I think people don't really think about a lot or things like getting loan applications right. We actually have a I deciding whether or not we get loans. And that one is is probably the most interesting one to be right now. >>Roger. So I think the father's example is probably my favorite as well. And what's interesting to me is that really a I is actually not about the Yeah, it's about the user experience that you can create as a result of a I. What's cool about Google photos is that and my entire family uses Google photos and they don't even know actually that the underlying in some of the most powerful a I in the world. But what they know is they confined every picture of our kids on the beach whenever they whenever they want to. Or, you know, we had a great example where we were with our kids. Every time they like something in the store, we take a picture of it, Um, and we can look up toy and actually find everything that they've taken picture. >>It's interesting because I think most people don't even know the power that they have. Because if you search for beach in your Google photos or you search for, uh, I was looking for an old bug picture from my high school there it came right up until you kind of explore. You know, it's pretty tricky, Raja, you know, I think a lot of conversation about A They always focus the general purpose general purpose, general purpose machines and robots and computers. But people don't really talk about the applied A that's happening all around. Why do you think that? >>So it's a good question. There's there's a lot more talk about kind of general purpose, but the reality of where this has an impact right now is, though, are those specific use cases. And so, for example, things like personalizing customer interaction or, ah, spotting trends that did that you wouldn't have spotted for turning unstructured data like documents into structure data. That's where a eyes actually having an impact right now. And I think it really boils down to getting to the right use cases where a I right? >>Sharon, I want ask you. You know, there's a lot of conversation. Always has A I replace people or is it an augmentation for people? And we had Gary Kasparov on a couple years ago, and he talked about, you know, it was the combination if he plus the computer made the best chess player, but that quickly went away. Now the computer is actually better than Garry Kasparov. Plus the computer. How should people think about a I as an augmentation tool versus a replacement tool? And is it just gonna be specific to the application? And how do you kind of think about those? >>Yeah, I would say >>that any application where you're making life and death decisions where you're making financial decisions that disadvantage people anything where you know you've got u A. V s and you're deciding whether or not to actually dropped the bomb like you need a human in the loop. If you're trying to change the words that you are using to get a different group of people to apply for jobs, you need a human in the loop because it turns out that for the example of beach, you type sheep into your phone and you might get just a field, a green field and a I doesn't know that, uh, you know, if it's always seen sheep in a field that when the sheep aren't there, that that isn't a sheep like it doesn't have that kind of recognition to it. So anything were we making decisions about parole or financial? Anything like that needs to have human in the loop because those types of decisions are changing fundamentally the way we live. >>Great. So shift gears. The team are Jeff Saunders. Okay, team, your mind may have been the liquid on my bell, so I'll be more active on the bell. Sorry about that. Everyone's even. We're starting a zero again, so I want to shift gears and talk about data sets. Um Bob, you're up on stage. Demo ing some some of your technology, the Miss Technology and really, you know, it's interesting combination of data sets A I and its current form needs a lot of data again. Kind of the classic Chihuahua on blue buried and photos. You got to run a lot of them through. How do you think about data sets? In terms of having the right data in a complete data set to drive an algorithm >>E. I think we all know data sets with one The tipping points for a I to become more real right along with cloud computing storage. But data is really one of the key points of making a I really write my example on stage was wine, right? Great wine starts a great grape street. Aye, aye. Starts a great data for us personally. L s t M is an example in our networking space where we have data for the last three months from our customers and rule using the last 30 days really trained these l s t m algorithms to really get that tsunami detection the point where we don't have false positives. >>How much of the training is done. Once you once you've gone through the data a couple times in a just versus when you first started, you're not really sure how it's gonna shake out in the algorithm. >>Yeah. So in our case right now, right, training happens every night. So every night, we're basically retraining those models, basically, to be able to predict if there's gonna be an anomaly or network, you know? And this is really an example. Where you looking all these other cat image thinks this is where these neural networks there really were one of the transformational things that really moved a I into the reality calling. And it's starting to impact all our different energy. Whether it's text imaging in the networking world is an example where even a I and deep learnings ruling starting to impact our networking customers. >>Sure, I want to go to you. What do you do if you don't have a big data set? You don't have a lot of pictures of chihuahuas and blackberries, and I want to apply some machine intelligence to the problem. >>I mean, so you need to have the right data set. You know, Big is a relative term on, and it depends on what you're using it for, right? So you can have a massive amount of data that represents solar flares, and then you're trying to detect some anomaly, right? If you train and I what normal is based upon a massive amount of data and you don't have enough examples of that anomaly you're trying to detect, then it's never going to say there's an anomaly there, so you actually need to over sample. You have to create a population of data that allows you to detect images you can't say, Um oh, >>I'm going to reflect in my data set the percentage of black women >>in Seattle, which is something below 6% and say it's fair. It's not right. You have to be able thio over sample things that you need, and in some ways you can get this through surveys. You can get it through, um, actually going to different sources. But you have to boot, strap it in some way, and then you have to refresh it, because if you leave that data set static like Bob mentioned like you, people are changing the way they do attacks and networks all the time, and so you may have been able to find the one yesterday. But today it's a completely different ball game >>project to you, which comes first, the chicken or the egg. You start with the data, and I say this is a ripe opportunity to apply some. Aye, aye. Or do you have some May I objectives that you want to achieve? And I got to go out and find the >>data. So I actually think what starts where it starts is the business problem you're trying to solve. And then from there, you need to have the right data. What's interesting about this is that you can actually have starting points. And so, for example, there's techniques around transfer, learning where you're able to take an an algorithm that's already been trained on a bunch of data and training a little bit further with with your data on DSO, we've seen that such that people that may have, for example, only 100 images of something, but they could use a model that's trained on millions of images and only use those 100 thio create something that's actually quite accurate. >>So that's a great segue. Wait, give me a ring on now. And it's a great Segway into talking about applying on one algorithm that was built around one data set and then applying it to a different data set. Is that appropriate? Is that correct? Is air you risking all kinds of interesting problems by taking that and applying it here, especially in light of when people are gonna go to outweigh the marketplace, is because I've got a date. A scientist. I couldn't go get one in the marketplace and apply to my data. How should people be careful not to make >>a bad decision based on that? So I think it really depends. And it depends on the type of machine learning that you're doing and what type of data you're talking about. So, for example, with images, they're they're they're well known techniques to be able to do this, but with other things, there aren't really and so it really depends. But then the other inter, the other really important thing is that no matter what at the end, you need to test and generate based on your based on your data sets and on based on sample data to see if it's accurate or not, and then that's gonna guide everything. Ultimately, >>Sharon has got to go to you. You brought up something in the preliminary rounds and about open A I and kind of this. We can't have this black box where stuff goes into the algorithm. That stuff comes out and we're not sure what the result was. Sounds really important. Is that Is that even plausible? Is it feasible? This is crazy statistics, Crazy math. You talked about the business objective that someone's trying to achieve. I go to the data scientist. Here's my data. You're telling this is the output. How kind of where's the line between the Lehman and the business person and the hard core data science to bring together the knowledge of Here's what's making the algorithm say this. >>Yeah, there's a lot of names for this, whether it's explainable. Aye, aye. Or interpret a belay. I are opening the black box. Things like that. Um, the algorithms that you use determine whether or not they're inspect herbal. Um, and the deeper your neural network gets, the harder it is to inspect, actually. Right. So, to your point, every time you take an aye aye and you use it in a different scenario than what it was built for. For example, um, there is a police precinct in New York that had a facial recognition software, and, uh, victim said, Oh, it looked like this actor. This person looked like Bill Cosby or something like that, and you were never supposed to take an image of an actor and put it in there to find people that look like them. But that's how people were using it. So the Russians point yes, like it. You can transfer learning to other a eyes, but it's actually the humans that are using it in ways that are unintended that we have to be more careful about, right? Um, even if you're a, I is explainable, and somebody tries to use it in a way that it was never intended to be used. The risk is much higher >>now. I think maybe I had, You know, if you look at Marvis kind of what we're building for the networking community Ah, good examples. When Marvis tries to do estimate your throughput right, your Internet throughput. That's what we usually call decision tree algorithm. And that's a very interpretive algorithm. and we predict low throughput. We know how we got to that answer, right? We know what features God, is there? No. But when we're doing something like a NAMI detection, that's a neural network. That black box it tells us yes, there's a problem. There's some anomaly, but that doesn't know what caused the anomaly. But that's a case where we actually used neural networks, actually find the anomie, and then we're using something else to find the root cause, eh? So it really depends on the use case and where the night you're going to use an interpreter of model or a neural network which is more of a black box model. T tell her you've got a cat or you've got a problem >>somewhere. So, Bob, that's really interested. So can you not unpacking? Neural network is just the nature of the way that the communication and the data flows and the inferences are made that you can't go in and unpack it, that you have to have the >>separate kind of process too. Get to the root cause. >>Yeah, assigned is always hard to say. Never. But inherently s neural networks are very complicated. Saito set of weights, right? It's basically usually a supervised training model, and we're feeding a bunch of data and trying to train it to detect a certain features, sir, an output. But that is where they're powerful, right? And that's why they basically doing such good, Because they are mimicking the brain, right? That neural network is a very complex thing. Can't like your brain, right? We really don't understand how your brain works right now when you have a problem, it's really trialling there. We try to figure out >>right going right. So I want to stay with you, bought for a minute. So what about when you change what you're optimizing? Four? So you just said you're optimizing for throughput of the network. You're looking for problems. Now, let's just say it's, uh, into the end of the quarter. Some other reason we're not. You're changing your changing what you're optimizing for, Can you? You have to write separate algorithm. Can you have dynamic movement inside that algorithm? How do you approach a problem? Because you're not always optimizing for the same things, depending on the market conditions. >>Yeah, I mean, I think a good example, you know, again, with Marvis is really with what we call reinforcement. Learning right in reinforcement. Learning is a model we use for, like, radio resource management. And there were really trying to optimize for the user experience in trying to balance the reward, the models trying to reward whether or not we have a good balance between the network and the user. Right, that reward could be changed. So that algorithm is basically reinforcement. You can finally change hell that Algren works by changing the reward you give the algorithm >>great. Um, Rajan back to you. A couple of huge things that have come into into play in the marketplace and get your take one is open source, you know, kind of. What's the impact of open source generally on the availability, desire and more applications and then to cloud and soon to be edge? You know, the current next stop. How do you guys incorporate that opportunity? How does it change what you can do? How does it open up the lens of >>a I Yeah, I think open source is really important because I think one thing that's interesting about a I is that it's a very nascent field and the more that there's open source, the more that people could build on top of each other and be able to utilize what what others others have done. And it's similar to how we've seen open source impact operating systems, the Internet, things like things like that with Cloud. I think one of the big things with cloud is now you have the processing power and the ability to access lots of data to be able to t create these thes networks. And so the capacity for data and the capacity for compute is much higher. Edge is gonna be a very important thing, especially going into next few years. You're seeing Maur things incorporated on the edge and one exciting development is around Federated learning where you can train on the edge and then combine some of those aspects into a cloud side model. And so that I think will actually make EJ even more powerful. >>But it's got to be so dynamic, right? Because the fundamental problem used to always be the move, the computer, the data or the date of the computer. Well, now you've got on these edge devices. You've got Tanya data right sensor data all kinds of machining data. You've got potentially nasty hostile conditions. You're not in a nice, pristine data center where the environmental conditions are in the connective ity issues. So when you think about that problem yet, there's still great information. There you got latent issues. Some I might have to be processed close to home. How do you incorporate that age old thing of the speed of light to still break the break up? The problem to give you a step up? Well, we see a lot >>of customers do is they do a lot of training on the cloud, but then inference on the on the edge. And so that way they're able to create the model that they want. But then they get fast response time by moving the model to the edge. The other thing is that, like you said, lots of data is coming into the edge. So one way to do it is to efficiently move that to the cloud. But the other way to do is filter. And to try to figure out what data you want to send to the clouds that you can create the next days. >>Shawna, back to you let's shift gears into ethics. This pesky, pesky issue that's not not a technological issue at all, but right. We see it often, especially in tech. Just cause you should just cause you can doesn't mean that you should. Um so and this is not a stem issue, right? There's a lot of different things that happened. So how should people be thinking about ethics? How should they incorporate ethics? Um, how should they make sure that they've got kind of a, you know, a standard kind of overlooking kind of what they're doing? The decisions are being made. >>Yeah, One of the more approachable ways that I have found to explain this is with behavioral science methodologies. So ethics is a massive field of study, and not everyone shares the same ethics. However, if you try and bring it closer to behavior change because every product that we're building is seeking to change of behavior. We need to ask questions like, What is the gap between the person's intention and the goal we have for them? Would they choose that goal for themselves or not? If they wouldn't, then you have an ethical problem, right? And this this can be true of the intention, goal gap or the intention action up. We can see when we regulated for cigarettes. What? We can't just make it look cool without telling them what the cigarettes are doing to them, right so we can apply the same principles moving forward. And they're pretty accessible without having to know. Oh, this philosopher and that philosopher in this ethicist said these things, it can be pretty human. The challenge with this is that most people building these algorithms are not. They're not trained in this way of thinking, and especially when you're working at a start up right, you don't have access to massive teams of people to guide you down this journey, so you need to build it in from the beginning, and you need to be open and based upon principles. Um, and it's going to touch every component. It should touch your data, your algorithm, the people that you're using to build the product. If you only have white men building the product, you have a problem you need to pull in other people. Otherwise, there are just blind spots that you are not going to think of in order to still that product for a wider audience, but it seems like >>they were on such a razor sharp edge. Right with Coca Cola wants you to buy Coca Cola and they show ads for Coca Cola, and they appeal to your let's all sing together on the hillside and be one right. But it feels like with a I that that is now you can cheat. Right now you can use behavioral biases that are hardwired into my brain is a biological creature against me. And so where is where is the fine line between just trying to get you to buy Coke? Which somewhat argues Probably Justus Bad is Jule cause you get diabetes and all these other issues, but that's acceptable. But cigarettes are not. And now we're seeing this stuff on Facebook with, you know, they're coming out. So >>we know that this is that and Coke isn't just selling Coke anymore. They're also selling vitamin water so they're they're play isn't to have a single product that you can purchase, but it is to have a suite of products that if you weren't that coke, you can buy it. But if you want that vitamin water you can have that >>shouldn't get vitamin water and a smile that only comes with the coat. Five. You want to jump in? >>I think we're going to see ethics really break into two different discussions, right? I mean, ethics is already, like human behavior that you're already doing right, doing bad behavior, like discriminatory hiring, training, that behavior. And today I is gonna be wrong. It's wrong in the human world is gonna be wrong in the eye world. I think the other component to this ethics discussion is really round privacy and data. It's like that mirror example, right? No. Who gave that mirror the right to basically tell me I'm old and actually do something with that data right now. Is that my data? Or is that the mirrors data that basically recognized me and basically did something with it? Right. You know, that's the Facebook. For example. When I get the email, tell me, look at that picture and someone's take me in the pictures Like, where was that? Where did that come from? Right? >>What? I'm curious about to fall upon that as social norms change. We talked about it a little bit for we turn the cameras on, right? It used to be okay. Toe have no black people drinking out of a fountain or coming in the side door of a restaurant. Not that long ago, right in the 60. So if someone had built an algorithm, then that would have incorporated probably that social norm. But social norms change. So how should we, you know, kind of try to stay ahead of that or at least go back reflectively after the fact and say kind of back to the black box, That's no longer acceptable. We need to tweak this. I >>would have said in that example, that was wrong. 50 years ago. >>Okay, it was wrong. But if you ask somebody in Alabama, you know, at the University of Alabama, Matt Department who have been born Red born, bred in that culture as well, they probably would have not necessarily agreed. But so generally, though, again, assuming things change, how should we make sure to go back and make sure that we're not again carrying four things that are no longer the right thing to do? >>Well, I think I mean, as I said, I think you know what? What we know is wrong, you know is gonna be wrong in the eye world. I think the more subtle thing is when we start relying on these Aye. Aye. To make decisions like no shit in my car, hit the pedestrian or save my life. You know, those are tough decisions to let a machine take off or your balls decision. Right when we start letting the machines Or is it okay for Marvis to give this D I ps preference over other people, right? You know, those type of decisions are kind of the ethical decision, you know, whether right or wrong, the human world, I think the same thing will apply in the eye world. I do think it will start to see more regulation. Just like we see regulation happen in our hiring. No, that regulation is going to be applied into our A I >>right solutions. We're gonna come back to regulation a minute. But, Roger, I want to follow up with you in your earlier session. You you made an interesting comment. You said, you know, 10% is clearly, you know, good. 10% is clearly bad, but it's a soft, squishy middle at 80% that aren't necessarily super clear, good or bad. So how should people, you know, kind of make judgments in this this big gray area in the middle? >>Yeah, and I think that is the toughest part. And so the approach that we've taken is to set us set out a set of AI ai principles on DDE. What we did is actually wrote down seven things that we will that we think I should do and four things that we should not do that we will not do. And we now have to actually look at everything that we're doing against those Aye aye principles. And so part of that is coming up with that governance process because ultimately it boils down to doing this over and over, seeing lots of cases and figuring out what what you should do and so that governments process is something we're doing. But I think it's something that every company is going to need to do. >>Sharon, I want to come back to you, so we'll shift gears to talk a little bit about about law. We've all seen Zuckerberg, unfortunately for him has been, you know, stuck in these congressional hearings over and over and over again. A little bit of a deer in a headlight. You made an interesting comment on your prior show that he's almost like he's asking for regulation. You know, he stumbled into some really big Harry nasty areas that were never necessarily intended when they launched Facebook out of his dorm room many, many moons ago. So what is the role of the law? Because the other thing that we've seen, unfortunately, a lot of those hearings is a lot of our elected officials are way, way, way behind there, still printing their e mails, right? So what is the role of the law? How should we think about it? What shall we What should we invite from fromthe law to help sort some of this stuff out? >>I think as an individual, right, I would like for each company not to make up their own set of principles. I would like to have a shared set of principles that were following the challenge. Right, is that with between governments, that's impossible. China is never gonna come up with same regulations that we will. They have a different privacy standards than we D'oh. Um, but we are seeing locally like the state of Washington has created a future of work task force. And they're coming into the private sector and asking companies like text you and like Google and Microsoft to actually advise them on what should we be regulating? We don't know. We're not the technologists, but they know how to regulate. And they know how to move policies through the government. What will find us if we don't advise regulators on what we should be regulating? They're going to regulate it in some way, just like they regulated the tobacco industry. Just like they regulated. Sort of, um, monopolies that tech is big enough. Now there is enough money in it now that it will be regularly. So we need to start advising them on what we should regulate because just like Mark, he said. While everyone else was doing it, my competitors were doing it. So if you >>don't want me to do it, make us all stop. What >>can I do? A negative bell and that would not for you, but for Mark's responsibly. That's crazy. So So bob old man at the mall. It's actually a little bit more codified right, There's GDP are which came through May of last year and now the newness to California Extra Gatorade, California Consumer Protection Act, which goes into effect January 1. And you know it's interesting is that the hardest part of the implementation of that I think I haven't implemented it is the right to be for gotten because, as we all know, computers, air, really good recording information and cloud. It's recorded everywhere. There's no there there. So when these types of regulations, how does that impact? Aye, aye, because if I've got an algorithm built on a data set in in person, you know, item number 472 decides they want to be forgotten How that too I deal with that. >>Well, I mean, I think with Facebook, I can see that as I think. I suspect Mark knows what's right and wrong. He's just kicking ball down tires like >>I want you guys. >>It's your problem, you know. Please tell me what to do. I see a ice kind of like any other new technology, you know, it could be abused and used in the wrong waste. I think legally we have a constitution that protects our rights. And I think we're going to see the lawyers treat a I just like any other constitutional things and people who are building products using a I just like me build medical products or other products and actually harmful people. You're gonna have to make sure that you're a I product does not harm people. You're a product does not include no promote discriminatory results. So I >>think we're going >>to see our constitutional thing is going applied A I just like we've seen other technologies work. >>And it's gonna create jobs because of that, right? Because >>it will be a whole new set of lawyers >>the holdings of lawyers and testers, even because otherwise of an individual company is saying. But we tested. It >>works. Trust us. Like, how are you gonna get the independent third party verification of that? So we're gonna start to see a whole terrorist proliferation of that type of fields that never had to exist before. >>Yeah, one of my favorite doctor room. A child. Grief from a center. If you don't follow her on Twitter Follower. She's fantastic and a great lady. So I want to stick with you for a minute, Bob, because the next topic is autonomous. And Rahman up on the keynote this morning, talked about missed and and really, this kind of shifting workload of fixing things into an autonomous set up where the system now is, is finding problems, diagnosing problems, fixing problems up to, I think, he said, even generating return authorizations for broken gear, which is amazing. But autonomy opens up all kinds of crazy, scary things. Robert Gates, we interviewed said, You know, the only guns that are that are autonomous in the entire U. S. Military are the ones on the border of North Korea. Every single other one has to run through a person when you think about autonomy and when you can actually grant this this a I the autonomy of the agency toe act. What are some of the things to think about in the word of the things to keep from just doing something bad, really, really fast and efficiently? >>Yeah. I mean, I think that what we discussed, right? I mean, I think Pakal purposes we're far, you know, there is a tipping point. I think eventually we will get to the CP 30 Terminator day where we actually build something is on par with the human. But for the purposes right now, we're really looking at tools that we're going to help businesses, doctors, self driving cars and those tools are gonna be used by our customers to basically allow them to do more productive things with their time. You know, whether it's doctor that's using a tool to actually use a I to predict help bank better predictions. They're still gonna be a human involved, you know, And what Romney talked about this morning and networking is really allowing our I T customers focus more on their business problems where they don't have to spend their time finding bad hard were bad software and making better experiences for the people. They're actually trying to serve >>right, trying to get your take on on autonomy because because it's a different level of trust that we're giving to the machine when we actually let it do things based on its own. But >>there's there's a lot that goes into this decision of whether or not to allow autonomy. There's an example I read. There's a book that just came out. Oh, what's the title? You look like a thing. And I love you. It was a book named by an A I, um if you want to learn a lot about a I, um and you don't know much about it, Get it? It's really funny. Um, so in there there is in China. Ah, factory where the Aye Aye. Is optimizing um, output of cockroaches now they just They want more cockroaches now. Why do they want that? They want to grind them up and put them in a lotion. It's one of their secret ingredients now. It depends on what parameters you allow that I to change, right? If you decide Thio let the way I flood the container, and then the cockroaches get out through the vents and then they get to the kitchen to get food, and then they reproduce the parameters in which you let them be autonomous. Over is the challenge. So when we're working with very narrow Ai ai, when use hell the Aye. Aye. You can change these three things and you can't just change anything. Then it's a lot easier to make that autonomous decision. Um and then the last part of it is that you want to know what is the results of a negative outcome, right? There was the result of a positive outcome. And are those results something that we can take actually? >>Right, Right. Roger, don't give you the last word on the time. Because kind of the next order of step is where that machines actually write their own algorithms, right? They start to write their own code, so they kind of take this next order of thought and agency, if you will. How do you guys think about that? You guys are way out ahead in the space, you have huge data set. You got great technology. Got tensorflow. When will the machines start writing their own A their own out rhythms? Well, and actually >>it's already starting there that, you know, for example, we have we have a product called Google Cloud. Ottawa. Mel Village basically takes in a data set, and then we find the best model to be able to match that data set. And so things like that that that are there already, but it's still very nascent. There's a lot more than that that can happen. And I think ultimately with with how it's used I think part of it is you have to start. Always look at the downside of automation. And what is what is the downside of a bad decision, whether it's the wrong algorithm that you create or a bad decision in that model? And so if the downside is really big, that's where you need to start to apply Human in the loop. And so, for example, in medicine. Hey, I could do amazing things to detect diseases, but you would want a doctor in the loop to be able to actually diagnose. And so you need tohave have that place in many situations to make sure that it's being applied well. >>But is that just today? Or is that tomorrow? Because, you know, with with exponential growth and and as fast as these things are growing, will there be a day where you don't necessarily need maybe need the doctor to communicate the news? Maybe there's some second order impacts in terms of how you deal with the family and, you know, kind of pros and cons of treatment options that are more emotional than necessarily mechanical, because it seems like eventually that the doctor has a role. But it isn't necessarily in accurately diagnosing a problem. >>I think >>I think for some things, absolutely over time the algorithms will get better and better, and you can rely on them and trust them more and more. But again, I think you have to look at the downside consequence that if there's a bad decision, what happens and how is that compared to what happens today? And so that's really where, where that is. So, for example, self driving cars, we will get to the point where cars are driving by themselves. There will be accidents, but the accident rate is gonna be much lower than what's there with humans today, and so that will get there. But it will take time. >>And there was a day when will be illegal for you to drive. You have manslaughter, right? >>I I believe absolutely there will be in and and I don't think it's that far off. Actually, >>wait for the day when I have my car take me up to Northern California with me. Sleepy. I've only lived that long. >>That's right. And work while you're while you're sleeping, right? Well, I want to thank everybody Aton for being on this panel. This has been super fun and these air really big issues. So I want to give you the final word will just give everyone kind of a final say and I just want to throw out their Mars law. People talk about Moore's law all the time. But tomorrow's law, which Gardner stolen made into the hype cycle, you know, is that we tend to overestimate in the short term, which is why you get the hype cycle and we turn. Tend to underestimate, in the long term the impacts of technology. So I just want it is you look forward in the future won't put a year number on it, you know, kind of. How do you see this rolling out? What do you excited about? What are you scared about? What should we be thinking about? We'll start with you, Bob. >>Yeah, you know, for me and, you know, the day of the terminus Heathrow. I don't know if it's 100 years or 1000 years. That day is coming. We will eventually build something that's in part of the human. I think the mission about the book, you know, you look like a thing and I love >>you. >>Type of thing that was written by someone who tried to train a I to basically pick up lines. Right? Cheesy pickup lines. Yeah, I'm not for sure. I'm gonna trust a I to help me in my pickup lines yet. You know I love you. Look at your thing. I love you. I don't know if they work. >>Yeah, but who would? Who would have guessed online dating is is what it is if you had asked, you know, 15 years ago. But I >>think yes, I think overall, yes, we will see the Terminator Cp through It was probably not in our lifetime, but it is in the future somewhere. A. I is definitely gonna be on par with the Internet cell phone, radio. It's gonna be a technology that's gonna be accelerating if you look where technology's been over last. Is this amazing to watch how fast things have changed in our lifetime alone, right? Yeah, we're just on this curve of technology accelerations. This in the >>exponential curves China. >>Yeah, I think the thing I'm most excited about for a I right now is the addition of creativity to a lot of our jobs. So ah, lot of we build an augmented writing product. And what we do is we look at the words that have happened in the world and their outcomes. And we tell you what words have impacted people in the past. Now, with that information, when you augment humans in that way, they get to be more creative. They get to use language that have never been used before. To communicate an idea. You can do this with any field you can do with composition of music. You can if you can have access as an individual, thio the data of a bunch of cultures the way that we evolved can change. So I'm most excited about that. I think I'm most concerned currently about the products that we're building Thio Give a I to people that don't understand how to use it or how to make sure they're making an ethical decision. So it is extremely easy right now to go on the Internet to build a model on a data set. And I'm not a specialist in data, right? And so I have no idea if I'm adding bias in or not, um and so it's It's an interesting time because we're in that middle area. Um, and >>it's getting loud, all right, Roger will throw with you before we have to cut out, or we're not gonna be able to hear anything. So I actually start every presentation out with a picture of the Mosaic browser, because what's interesting is I think that's where >>a eyes today compared to kind of weather when the Internet was around 1994 >>were just starting to see how a I can actually impact the average person. As a result, there's a lot of hype, but what I'm actually finding is that 70% of the company's I talked to the first question is, Why should I be using this? And what benefit does it give me? Why 70% ask you why? Yeah, and and what's interesting with that is that I think people are still trying to figure out what is this stuff good for? But to your point about the long >>run, and we underestimate the longer I think that every company out there and every product will be fundamentally transformed by eye over the course of the next decade, and it's actually gonna have a bigger impact on the Internet itself. And so that's really what we have to look forward to. >>All right again. Thank you everybody for participating. There was a ton of fun. Hope you had fun. And I look at the score sheet here. We've got Bob coming in and the bronze at 15 points. Rajan, it's 17 in our gold medal winner for the silver Bell. Is Sharna at 20 points. Again. Thank you. Uh, thank you so much and look forward to our next conversation. Thank Jeffrey Ake signing out from Caesar's Juniper. Next word unpacking. I Thanks for watching.

live from San Francisco celebrating ten years of high-tech coverage it's the cube covering vmworld 2019 brought to you by VMware and its ecosystem partners welcome to day two of the cubes coverage of VMworld 2019 double vowels two sets going on on our other set day Volante and John Fourier they're talking to Michael Dell they're talking to passenger but over here we know where the hot action is talking about even Steve Young you know the Hall of Fame quarterback from the 49ers knows what hyper-converged infrastructure is and they're from well I'm excited to welcome back to the program Chad Dunn who is the vice president of product management and hyper-converged infrastructure for Delly MC Chad great to see you great to be back soon and also I want to also welcome my guest host for this segment who is Bobby Allen coming up to us from Charlotte North Carolina a cube alum now flipping the desk and gonna be asking some questions with me so Chad well my first question is why did you put me up against Michael and Pat well because we knew you could take it you know some people would be like oh that's the other Chad even but Ron you know HCI you know still a big story it's a big piece of what goes into VMware's vfc yeah story there you know VMware's talking about there's 20,000 deployments that they have a v san and i believe you might know who the number one partner is in the number one solution set out of those 20 thousands I think I might and I think that's also the leading product in terms of volume and the leading product in terms of revenue in the hyper-converged market as a blast so I will give you a second you know give us some of the you know you know the the drum beat the chest thumping of how the VX RL product line and and your portfolio is doing the the portfolio is doing great and the integration of V CF on VX rail is just throwing gasoline on to the fire in terms of adoption you know we see hyper-converged now mainstream moving into the data center mission-critical applications are being run on it infrastructure as a service right alongside container as a service so a few things that we announced this week in addition to you know the latest update of VCF on rail we added fibre channel 2 to V X rail a move that people are very is very polarizing move for people to chat why we have people who continue to love their primary storage arrays that are fiber channel connected and very often we're selling to someone who's refreshing servers but they have life left on the the array they want to preserve it they want to migrate data so they demanded fiber channel we gave them fiber right so if I understand this though it's that I've seen certain HD eyes where there's like you know a faucet on the side that I can plug in I scuzzy now you're just saying there's that it's not like you haven't a V X rail that is you know fiber dole baked in through and through so there's a server architect there's still v Santa at the core of VX rail but we give you the option now attaching primary storage either in the context of VCF or or in standalone other big news is we've recently refreshed a product line to the next generation of Xeon processor the cascade Lake version that gives us about a 28 to 30 percent performance increase and Intel opt in cache drives so there are lots of hardware updates along with software updates that that accelerate our LCM or lifecycle management process so Chad thank you for the update but I've got a different question I want to go in a different direction I talk to customers all the time cxos what would you tell the ciock so who's who's scared to invest more in the data center because public cloud seems like the one is in its sales but obviously Dell has a story to tell how do you help them defend their their turf well III I don't think they should get territorial about that every customer that I engaged with has a hybrid cloud strategy and very often it's more than one public cloud there's always a champion challenger relationship right we as CX know you want to keep your vendors honest correct right so you may have multiple public clouds you may have multiple infrastructure providers but VMware and in VCF on the X rail can be that common thread between the two so I can use tools like VMware Cloud Health to determine where it makes sense to run the workload I think very seamlessly move that workload from a VCF on VX rail deployment into a public cloud when it makes sense I can bring it back when it makes sense I can move it to Amazon to Azure to Google to any one of the VMware cloud providers and really hedge my bets right in terms of where it's best to run that workload so we encourage public cloud are you seeing customers actually take advantage of those capabilities yet or is it something they're still kind of waiting to see how that develops in terms of hybrid multi-cloud we see customers taking advantage of it right away so I'll give you an example I have a large retail customer right now and they've got about 900 different workloads that are existing virtual machines so they're looking at how they either refactor those into cloud native and move them into the cloud or whether they rationalize some of those away which is sort of a natural process with the Dell technologies cloud platform which is based on VCF on the X rail they can effectively put off that decision and they can move those workloads into the public cloud as virtual machines and start to enjoy those economics while they decide which ones to refactor while they decide which ones to rationalize away yeah so chata tell tech world we talked a bunch about how I have you know V X rel is the underpinning for the VMware cloud on Dell EMC right here at the show you know we talk a lot about cloud and even you know kubernetes was mentioned just a few times a couple of times in the keynote there was some guy in the audience you know Hootin Hollerin about some of that but you know help us you know draw the line you know where your customers today what are they starting to do and you know where does that put this portfolio extend to in the future great well first of all I'm gonna do a session tomorrow morning at 9:30 and we're gonna be talking about the business aspect of containers of service and kubernetes to customers so a good session to check out if if the viewers can but from our perspective we see customers at different points in that journey toward container as a service or cloud native on their premises or in a hybrid cloud scenario and it's funny one of the slides that I'll do tomorrow says that about 71 percent of customers are spending their budgets on operating their infrastructures and services are traditional VMs when they want to be able to reinvest some of that money and move to cloud native now this is almost the exact same slide and same percentage that we use you know five six eight years ago to talk about keeping the lights on with 70 percent of IT budgets it was 8020 back then so it's the exact same dynamic we're seeing it really be mainstreamed now every dtw or EMC world that I would go to I would always ask how much of your workload is cloud native they would always say 1% how much is it going to be in five years they say we have no idea now they're telling us about what those projects are and and they're rapidly adopting them but the nice thing about the VCF on rail is you can create workload domains that are traditional infrastructure as a service with virtual machines but you can also spin up container as a service workload domain with d KS and NS xt and so as you start to refactor those applications and there's that balance changes you simply increase the number and the size of your cloud native workload domains and you shrink your infrastructure as a service so you're in an ideal spot to be able to run virtual infrastructure workload domains virtual desktop workload domains cloud native workload domains consistent operating model across-the-board consistent hardware layer which is VX rail so you get those economics and as your business demands change you as an IT operator are able to serve those DevOps organizations within your company because if you're not providing them a kubernetes dial-tone they're gonna find it right and you're gonna see shadow IT spring up and they're gonna be in the public cloud before you know what happens so Chad want one of the things that I'm curious about so this is a software conference obviously right we're talking about a lot of the goodness that's hypervisor and above yep what would you say to the person who says doesn't matter what sort of hardware I'm running is that a commodity what is Dells differentiate a value in this software-defined world if I wanted to be a smart aleck I would tell you to look at some of the other hyper-converged competitors who went software only and then go take a look at their market cap but if I wanted to be serious I would say that hardware really does matter and when you look at you know how we need to lifecycle manage that infrastructure and make it seamless and effortless for the customer it means that you need to think about that hardware layer so if I look inside a PowerEdge server for example there are between nine and twelve different programmable parts from BIOS to HBAs to drive firmware backplane power supply you name it all those things have dependencies on the software drivers that you use being able to look at that all in context and be able to update that all at once so users don't have to worry about the bits and bytes of drivers and and firmware compatibility really saves them money saves them time and effort and lets them concentrate on things they're gonna differentiate their business and we see customers making that switch daily now and understanding that they can now redeploy some of that cost and resources toward things that are more differentiated like you know moving to cloud native so Chad what about the folks that have a they've got a Dell footprint they've got some other competitors and that how do you help them where there may be in the midst of changing over right they've got some other manufacturers that provided hardware before some of that story may not be as consistent so what can they do when they may be in the midst of a change over so you really need to look at what that operating expense savings is gonna be so we we certainly want to get as much life out of that existing infrastructure as we can and then provide migration fibre channel and and IP attached storage is an example of that right where people are not necessarily ready to move away from those arrays so say great right continue to leverage those assets but also if it's an existing VC on infrastructure based on bare metal servers the migration from one VC on environment to another is a pretty seamless one right because you preserve that storage policy based management as you make the migration so you know it typically is a pretty easy migration for customers to move on to hyper conversion they think and obviously we'll provide whatever professional services are necessary right if you look it by the way and I'll plug VMware since I'm at at VMworld if you look at VMware HDX if we're doing migration across these environments either to or from a public cloud or from a legacy environment to a next-generation HCI environment that's one of the coolest tools out there for doing that migration and preserving all the policies security and Software Defined Networking policies and micro segmentation from one environment to the other so really impressed with with what VMware has done there yeah definitely a theme we've heard it this show is you know VMware talk to their install base and says oh my gosh you look at all these cloud native things out there and kubernetes is super hard so you know we're gonna build it enable it in there um when I've looked at the you know Dell and VMware family there's been a few different kubernetes options out there help gives a little clarity where that fits into your world and you know where we are today where it's going kind of yeah future yeah there has been a sort of a dichotomy of you know cloud native ins inside VMware and cloud native inside pivotal for example and we've worked with with both of those organizations in fact we've been very successful with what platform and container as a service on the x rail going to market with pivotal but now that PKS is moving into VMware and really all of pivotal is moving into VMware it sort of unifies that strategy and if you look at the acquisitions that VMware is making with hep tio and others and actually embedding kubernetes into ESX I I mean that's a game changer an absolutely game-changer so now we have all of the the software assets to you know build run and manage cloud native were closed all within the VMware portfolio now the great thing about VX rail is we inherit all that work natively and build that natively into our hyper-converged platform so you know we sort of get that for free so you know not only can we now be the the leading hyper-converged infrastructure player for infrastructure as a service of traditional VMs we now can expand that and be the number one player in the new container world and you know as you saw with the the performance discussion that Pat had yesterday they actually see these things running faster in a virtualized ESXi environment than we do on bare metal only single digits but that's pretty impressive right it's very counter intuitive right so we're really happy to be able to take advantage of that and we have still have the pivotal labs team which really gets engaged with these customers to make it more transformational in terms of how they develop and how they deliver applications to their end users and by the way I mean not to preview something that's pretty far down the road we're looking at how we change up how we deliver software updates in VX rail and how we architect the software to make it a continuous integration continuous delivery pipeline because we need to make the infrastructure more intelligent and more agile and products like VX rail ace which we just announced a dtw does exactly that right it gives us the ability to pull back telemetry from VX rail apply machine learning and in an artificial intelligence to it in our own cloud and then push that data back out to our VX rail users to Auto remediating problems so the infrastructure is going to get more agile and it's going to get more intelligent as we go yeah um we've been talking a bit about some of the future stuff before we go but want to bring back to you know one of the core things that we wanted to do in this space it was simplification how do we make it super easy when I talk to most people that do HCI it's like you know where is that it's like I don't know it got installed and I've never touched it since then my understanding you're doing some things even on the management side to make things even easier there's some virtual reality in there too no we like to think everything is real reality yeah we are doing things to to even further simplify our lifecycle management process to make that that infrastructure something that that operators don't need to worry about so we're now doing pre staging of updates future scheduling of updates pause and resume of updates to fit within customers maintenance windows more effectively we'll be doing updates that are delivered via the cloud through the ACE platform coming up in in a release that's that's about to ship so again the idea is to you know simultaneously make the the product more flexible but maintain the simplicity because as I said we've moved into these core data center deployments where people are buying you know six hundred eight hundred thousand units at a time and deploying its scale and they expect flexibility you know all the flexibility you would get with an ESXi server with all the simplification and and day 2 operations that you get from HDI so we're in a constant state of trying to balance those two things and optimize for both use cases and by the way at the same time software-defined networking containers are coming at us at light speed the VMware has acquired more more companies in the last three months and then I can name I can name them all so it's a very fast-moving space yeah I don't think I can keep over the last week all right Bobby final question I guess quick sound bite what should people know about VMware cloud on Dale that they don't know VMware cloud on Dell EMC formerly project to mention right the extension of the MC on the customer premises I think this is incredibly strategic for us and for VMware because it gives you that cloud consumption model on-premises in an operating expense model so just into two initial access with that beta customers are turned up and the feedback has been extremely positive vmware dell technologies cloud platform which is VCF on VX rail really off to the races on that right we've had huge uptake in that we're seeing deals of literally hundreds of nodes at a time data centers at a time are consuming this deploying it we're demoing it here at the show if you go to the nvidia booth all the VDI demos are being run on VCF on VX rail that's sitting over in a hotel across the street it's a very hot hotel room cuz we get a lot of GPUs in those but it's also something that users can actually go see it live and working nice alright and just a quick tip for you if you haven't made it to VM world or even if you came here Chad mentioned he's doing a session this week they do make all of those available to people out there and of course all of our content is always available on the cube net Chad Dunn always great to catch up with you Bobby Allen thanks so much for joining me for this segment and my audience as always thanks for watching the Q

>> Narrator: Live from London, England, it's theCUBE covering AWS summit London 2019, brought to you by Amazon Web Services. >> Welcome back to XL London everybody, My name is Dave Velante and you're watching theCUBE, the leader in live tech coverage. This is our one-day coverage of AWS summit, London. theCUBE will go up to the events we extract the signal of the noise and I have recruited a co-host Theresa Carlson who's a friend and vice president worldwide public sector at AWS and we have a really special segment for you today. Anna Sergeant is here. She's a computing teacher and Charlotte who's a student at Townley. Wait till you see what we have in store for you. Theresa, let's get it started. So first of all, welcome (mumbles). >> Well, and I'm so thrilled to be your co-host, I just wanna tell you that right now. >> That's a first for you, right? >> Yes, it is. >> I finally got one up on for you. >> Yeah, exactly, I get to be on theCUBE (mumbles). >> So here's the deal, so you have this GetIT program. Tell us what that's all about and then we'll get into it. >> Well you know, we talked about over the last few years just in general about skills. Skills development, how critical it is and important for every age and GetIT is really a continuation of what we're trying to do to create job skills around cloud computing at every age, especially in elementary and primary school years. So GetIT today, what you're going to see from both Charlotte and Anna is we did a competition, there was over 160 applicants and it got netted down to ten schools that came here today and then we had two finalists and then we deemed a winner and they're going to get support and help but also, all these schools are gonna get support and help but it's really about the experience of them learning how to utilize cloud computing in a real-world application that actually matters to them which you can also fight to kind of social responsibility which most of these young people really relate to because they want to do something that matters to them. Just tech for tech is not exciting but tech for good is very exciting and I think that's what you're gonna hear about here today. >> We love to talk about tech for good and Anna, you're at the heart of this so how did you get into this, how did you get this all started, tell us your story. >> Well, my head teacher is quite an innovative person and she's been in conversations with Amazon and Future Foundations and they came to the school with the idea last year and invited the school to be part of the pilot program and so the Amazon ambassadors delivered their presentation to the school in September and as a team in the computing department, we got together and said, well we think this is a great opportunity for girls in tech. So we actually rolled it out as an actual scheme of lessons so the whole year eight, so that's 224 year eight students got together. They all were divided into groups of their own choice and we gave them the outline or the brief and said you know, think of an app for good that would fulfill a social need in your community. So think about the community and prepare a pitch and we then set timelines and deadlines and helped them through the research and obviously spoke to Amazon, came to the London offices as well and spent some time with your colleagues in the London office and you know, and then basically helped the girls pitch their final idea. >> So Charlotte, you got this prompt essentially and then you took it from there. Tell us a little bit about yourself and then how this all came about and what you guys did with that prompt. >> And today is your birthday so happy birthday. >> Congratulations. >> Thank you. So basically I'm 13 at the moment but we've been doing this project in year eight as Anna said and basically, we were given the idea to make an app and everyone was really excited initially, but we weren't too sure about what we wanted to make it on and we were lucky enough to have the choice to choose whatever topic we wanted to make it on and kind of decide what cause we wanted to help and the solution to help it with and then we were given loads of help with the Amazon ambassadors and they really were like really kinda generous with all their help. They came to visit us and they watched our presentations and it really gained our confidence because we presented to the class and in front of the teachers and Amazon ambassadors and it's been really lovely because we've been able to gain skills that we didn't have before in computing and it's gained our confidence, it's boosted it and we've just become much like more interested in STEM and computing. >> Charlotte, let me ask you, what was your application about and what inspired you for the application? >> So my app was called Positive Of Me and we based it off of a mental health and kind of having a more positive outlook on life and we decided to do that topic because we thought that it was really important to students to have a stress-free time in school rather than always feeling stressed and under the weather because they have a lot of work or they're under-organized and stuff like that so we believe that it was quite important to help people like that so our features included like a planner, a mood tracker and just other things to kind of keep you organized and happy throughout your school life. >> So fascinated by the adoption of this approach and were you always interested in STEM or was it something that, this catalyzed your interests in your colleagues. >> I was always interested in STEM and in Townley, they like promote it a lot and they're very interested in like, because it's an all-girls school. We promote females and like we try to make sure that girls are interested in all subjects no matter what and it's been quite nice but I believe that it kind of made me more interested in STEM with my classmates because we've had a fun experience. It's not just been doing computing, it's been having a fun experience. We've been designing our own thing that we're passionate about so it's been really lovely in that sense. >> Dave: So, please go ahead. >> Well, I was gonna ask you, how did you bring it together as a group. What were kind of the core components that you worked on to bring the app together and then have the final that you got here today with. >> So we kind of thought of the idea first about mental health, that was kind of our starting point and then we developed it to what features we can include in the app. We made a mind map saying whatever features we wanted, what topics we wanted to cover and then we thought about the target audiences and they really helped us think about this in the boot camp that they hosted. It was really helpful because Amazon ambassadors came to each kind of app and they helped us with what we could include and how to build on that idea. So that helped us include the target audiences, the ages that we wanted to target our app towards and it kind of helped us with that general theme and how many features we wanted to include. >> Because you had time pressures, right, so you have to make some trade-offs. So how did you make those trade-offs? You just talked to the potential recipients of the app or sort of brainstorm? >> We did a lot of surveys to what features people thought were the most important for our app and a lot of groups did that because it kind of, because there were a few different times that we needed to get it done by and every time we obviously had a time limit and so we needed to put the most important features in to our PowerPoints and our presentations and the prototypes and so people, we did surveys and people answered what features they thought were the most important to put in the app and then we implemented those before any other like more unnecessary ones. >> How did you organize your team? How many pizzas did they eat? >> Did you hear about that two pizza team, did Amazon talk to you about, Amazon Web Services, that if you had more people on your team that feeds two pizzas, that's too many 'cause that way you can move faster. >> We mainly decided to team because we got to choose like our friends to work with and obviously, we work better with the people who we're more comfortable around. So that was quite nice that we got to decide who we worked with but then the roles that we were given, we kind of just decided on what each person knew the most about, wanted to do research on and then from there, we kind of just carried on with the topics that we were initially started with. >> You told me something a while ago that really peaked my interest. You said you're an all-girl school and you almost had to reverse engineer your gender because it was all too pink. Can you talk about your thinking around a different kind of diversity. >> So basically we wanted to make the app like accept all the beliefs and stuff so that was our main focus with diversity and we didn't really realize initially that it was mainly quite girly, but then when we presented our initial presentation, obviously we got through the first round where we presented to the class but then we got some feedback from Miss and she really helped us telling us that you know, we want to make it unisex so that it's more approachable for all people and all students rather than just girls schools and then it would have more not purchases but it would have more audience. >> Yeah, better adoption but so, what did that involve? Was it colors, was it language, was it, what made it less girly? >> I mean, it was more colors and the whole theme of the app like the logo. We made it logo that was quite like not young, but quite young and girly a bit and it was mainly the colors though. We did like pink, which is, I mean it's traditionally seen as girly, pink, so we tried to make it, we searched up like unisex colors and it was more green, purple, blue, stuff like that so we implemented that into our app in the second round so that it was more unisex. >> Last time I interviewed you, I had my pink tie and pink shirt on. >> Yes, which I like, I think that was good. I've got my unisex on screen but one of the things that you did do that I really liked is you did the usability which you went out and you asked individuals what features would they like the most. I think that was really important and you can of course always do that with those boys and girls and figure out but that was really smart. So let me ask you another question. One of the things that we do find with girls and something I've been passionate about is they don't get into STEM or technology and they don't stay there. After going through this experience, one, do you think you might be more inclined to stay with technology and then I'd like to just know your opinion on how we can continue to forward this with girls after this experience, what else would you recommend? >> Yes, so as I said earlier, Townley promotes STEM massively. They have STEM days and everything so the girls at our school, we are really interested in it. This project has like really boosted my confidence and like my interest in STEM though because it's, as I said, it's made it more fun. It's not only just doing the computing work, it's made it a fun way to do it and you're working for, you're targeting towards an achievement at the end, to get the app made so everyone's trying really hard to get it done and that kind of gains your knowledge and then you learn all the new technology as you're going along so it's quite interesting. >> What are your thoughts on that Anna. I mean, we're always having this discussion on theCUBE. You look around the show, amazing show first of all, but there's a lot of men here. The line out the men's room is huge and so, because in a male-dominated industry, you look inside your own circles and your circles happen to be other men's so it's a challenge that we want to surface and be aware of. What more would your recommendations be to break those barriers? >> To do the programs like this, to actually go into schools and encourage young people because I think by encouraging all young people you know, you'll get the diversity and also the awareness. We're very subject driven in a way that our education system and actually a lot of the job roles out there we're in school, we're not aware of because we're busy teaching. So it's great to actually come in and we think about app developers and we think about testers and we think about programmers but there's all the other aspects as well which actually, unless industry comes into education and helps us show the students what the breadth of roles are out there you know, it's very easy for students to just go into a sort of like a very sort of set path. So by having programs like this coming into schools and having the industry come and talk to the students and inspire them is you know, a fantastic opportunity hence the reason why we decided to run in the whole year eight, the program >> And I've seen, like you saw today from all the groups but the kind of tech for good that the girls and the boys were able to actually decide on something that was meaningful to them and I've seen that a lot just around the world that when you go and talk to children about tech, you've got to connect the dots and I think you guys did that really well and what you were doing with your particular application but across the board the thing that we saw today which I think inspired them even more 'cause it was the thing that they were passionate about which teaches them along the way. >> Yes, yeah. >> So we love tech and I was introduced at age 12, the C prompt and learn basic. Kids today, you learn tech before you can speak you're you know, punching devices but so what was the tech behind what you were doing. Were you programming, were using cloud technologies. What was behind it? >> We mainly use more simple technology and most of the work was just making PowerPoint presentations and Word documents but obviously there were side things like we made the surveys on Word. We used Photoshop to make prototypes of the screens for the app and we learned a lot of technology at the bootcamp as well. We learned about the different kind of things we could use to make features of the app work and we learnt about obviously, Amazon were like the leaders of the program. >> You Learned about S3 storage, right. You learned about EC2, you learned about all the applications in AWS that you could build it because at the end as you build it, you'll use hopefully all those technologies is what we'll be helping you with. >> You know what I love about this story though is, and Teresa you know this, you can do almost anything with tech. Now sometimes it's too expensive or too complicated but the tech in many ways is the least important. It's more important to understand what the consumer wants, what the customer wants, what that experience is like, what the colors should be, right and then you can make the tech, apply the tech to solve that problem. >> 100%, and put all those tools together but I do hope that you learned what cloud computing was during your, because that was, I always kind of joke because one of the students at the beginning they use it but they don't always know what cloud computing is. So kind of learning the scalability and how, the ease and testing and just moving fast. So I think that's what you guys have done in a big way. From a teacher's point of view, are there other aspects that you think that should be done like either continued or done even better or faster that we're not getting to. >> This is definitely a step in the right direction. We are a bit more traditional because we introduce the students to Python. So they sort of start programming using Python and perhaps we should look more at cloud technology in greater detail in schools but we're kind of a little bit behind in terms of education in the way that we actually, and we need and we need to speed that up. >> And this is one of the big things that we're trying to do on the AWS side, is bring the new technologies into education because that is the highlight of what we see is there's using kind of older outdated technologies and getting them excited to understand how they learn with and utilize new technologies within AWS and a cloud platform because you can move faster, experiment, have quick failures and recoveries and the expenses you know a lot less expensive than you normally did. >> Well I've been around a long time. AWS changed the world and it changed it from a world where technology, especially information technology and enterprises was a world of no. We can't do that because it'll take too long, it's too expensive, no, no, no and what Amazon has done has sort of removed all that friction and turned it into a world yes you know, and builders and it's just amazing what's happening. You're the future and it's really such a pleasure having you both today. >> Thank you. >> Thank you for having us. >> Anna and Charlotte and of course Teresa, thank you guys for being on theCUBE. >> It's an honor, I agree, it's an honor to co-host but to have you guys and hear your passion and excitement for what you're doing. So my advice, keep it up, don't give up, stick with technology and STEM, you will not regret it, it's a great career. >> And have fun, all right, thanks again. >> Thank you. >> Thank you. >> All right and thank you for watching. Keep it right there, we'll be back with our next guest. We're live from the Excel center here at AWS summit London, you're watching theCUBE. (light electronic music)

>> from the Silicon Angle Media Office in Boston, Massachusetts. It's the cue. Here's your host. Still Minutemen. >> Hi, I'm Stew Minutemen. And welcome to a special cute conversation here in our Boston Areas studio where in spring 2019 whole lot of shows where the cubes gonna be on going to lots of events so many different technologies were covering on one of the areas we always love to be able to dig into is what's happening with the users. Many of these shows, we go to our user conferences as well as the community. Really happy to Boca Burger. Believe first time on the program. Steve Methodists famous. Who is the newly elected president of the mug s. So I think most of Ronan should know the V mug organization to the VM where User group. We've done cube events at, you know, the most related events. Absolute talked about the mug we've had, you know, the CEO of the mug on the program. And of course, the VM were Community 2019 will be the 10th year of the Cube at VM World. Still figuring out if we should do a party and stuff like that. We know all the ins and outs of what happened at that show. But you know the V mugs itself? I've attended many. Your Boston V mug is one that I've been, too. But before we get into the mug stuff, Steve could just give us a little bit of your back, because you are. You're practicing your user yourself. >> Yeah, well, first thanks for having me. You know what? I've been watching the cube for years, and it's ah, it's great to be on this side of the of the screen, right? So, yes. So I'm Steve. I think I, you know, show up every day as the associate chief information officer of the University of Massachusetts. Little just for 95 here, and that's my day job. That's my career, right? But what? You know what? I'm excited to be here to talk about what I'm excited in general with the mug is it's a community organization. And so it's a volunteer gig, and that's true of all of our leadership, right? So the from the president of the board of directors to our local leaders around the world, they're all volunteers, and that's I think, what makes it special is We're doing this because we're excited about it. We're passionate about it. >> Yeah, you know the mugs, It's, you know, created by users for user's. You go to them, talk a little bit. It's evolved a lot, you know, It started as just a bunch of independent little events. Is now you know, my Twitter feed. I feel like constantly every day. It's like, Oh, wait, who is at the St Louis? The Wisconsin one? I'll get like ads for like, it's like a weight is the Northeast one. I'm like, Oh, is that here in New England that I don't know about? No, no, no. It's in the UK on things like that. So I get ads and friends around the world and I love seeing the community. So, boy, how do you guys keep it all straight? Man, is that allow both the organic nature as well as some of the coordination and understanding of what's going on. How do you balance that? >> Yeah, that's a great question. And you know, So I was a V mug member for many, many years before I ever got interested in becoming a leader, and you're right it when it started, it was 10 of us would get around with a six pack of beer and a box of pizza, right? And we'd be talking shop and that, you know, that was awesome. And that's what would that was, how it started. But you get to a certain scale when you start talking about having 50,000 now, over 125,000 members around the world. You gotta coordinate that somehow you're right on the money with that. And so that's why you know, we have, you know, a strong, um, coordination effort that is our offices down in Nashville, Tennessee, and their their role is to enable our leaders to give back to their community and take the burden out of running these things. You know, sourcing venues and, you know, working with hotels and stuff. That is effort that not everybody wants to do all the time. And so to do that for them lets them focus on the really cool stuff which is the tech and connecting users. >> Yeah. Can you speak a little bit too? You know what were some of the speeds and feed to the event? How many do you have How much growing, you know, Like I'm signed up. I get the newsletter for activities as well as you know, lots of weapons. I've spoken on some of the webinars too. >> Yeah, well, first thanks for that s o. We have over 30 user cons around the world on three continents. >> In fact, what's the user cough? >> Great questions. So user kind is user conference, you know, consolidated into user Connery. And those are hundreds of end users getting together around the world were on three continents. In fact, I was fortunate enough in March, I went to Australia and I spoke at Sydney and Melbourne on That was awesome, getting to meet users literally, almost a sw far away from Boston. As you can get having the same challenges in the office day today, solving the same business problems with technology. So that was exciting. And so we've got those all over. We also have local meetings which are, you know, smaller in scope and often more focused on content. We've got 235 or Maur local chapters around the world. They're talking about this, and so we're really engaged at multiple levels with this and like you talk about. We have the online events which are global in scope. And we do those, you know, we time so that people in our time zone here in the States could get to them as well as folks in, you know, e m b A and a factory. >> Yeah, and I have to imagine the attendees have to vary. I mean, is it primarily for, you know, Sylvie, um, where admin is the primary title there up to, you know, people that are CEOs or one of the CEOs? >> Yes. So that actually we've seen that change over the past couple years, which is exciting for me being in the role that I'm in is you're right historically was vey Sphere admits, right? And we're all getting together. We're talking about how do we partition our lungs appropriately, right? And now it has switched. We see a lot more architect titles. We Seymour director titles coming in because, you know, I said the other day I was in Charlotte talking and I said, You know, business is being written in code, right? And so there's a lot more emphasis on what it's happening with V m wearing his VM worth portfolio expands. We've got a lot of new type of members coming into the group, which is exciting. >> Yeah, And what about the contents out? How much of it is user generated content versus VM were content and then, you know, I understand sponsorships or part of it vendors. The vendor ecosystem, which vm where has a robust ecosystem? Yes, you know, help make sure that it's financially viable for things to happen and as well as participate in the contest. >> Yes, I feel like I almost planted that question because it's such a good one. So, you know, in 2018 we started putting a strong emphasis on community content because we were, you know, we heard from remembers that awesome VM were content, awesome partner content. But we're starting to miss some of the user to user from the trenches, battle war stories, right? And so we put an emphasis on getting that back in and 2018 we've doubled down in 2019 in a big way, so if you've been to a user kind yet in 2019 but we've limited the number of sponsors sessions that we have, right so that we have more room for community content. We're actually able to get people from around the world to these events. So again, me and a couple folks from the States went toe Australia to share our story and then user story, right? And at the end of the day, we used to have sponsored sessions to sort of close it out. Now we have a community, our right, and Sophie Mug provides food and beverages and a chance to get together a network. And so that is a great community. Our and you know, I was at one recently and I was able to watch Ah, couple folks get to them. We're talking about different problems. They're having this and let me get your card so we can touch base on this later, which at the end of the day, that's what gets me motivated. That's what >> it's about. It's Steve. I won't touch on that for a second. You know what? Get you motivated. You've been doing this for years. You're, you know, putting your time in your president. I know. When I attended your Boston V mark the end of the day, it was a good community member talking about career and got some real good, you know, somebody we both know and it really gets you pumped up in something very, a little bit different from there. So talk a little bit without kind of your goals. For a CZ president of Emma, >> Sure eso I get excited about Vima because it's a community organization, right? And because, you know, I've said this a bunch of times. But for me, what excites me is it's a community of people with similar interests growing together right and reinforcing each other. I know for a fact that I can call ah whole bunch of people around the world and say, Hey, I'm having a problem technically or hey, I'm looking for some career advice or hey, one of my buddies is looking for work. Do you know of any opening somewhere? And that's really powerful, right? Because of the end of the day, I think the mug is about names and people and not logos, right? And so that's what it motivates me is seeing the change and the transformation of people and their career growth that V mug can provide. In fact, I know ah ton of people from Boston. In fact, several of them have. You know, they were administrators at a local organization. Maybe they moved into partners. Maybe they moved into vendors. Maybe they stay where they are, and they kept accelerating their growth. But I've seen tons of career growth and that that gets me excited watching people take the next step to be ableto to build a >> career, I tell you, most conferences, I go to the kind of jobs take boards, especially if you're kind of in the hot, cool new space they're all trying to hire. But especially when you go to a local on the smaller events, it's so much about the networking and the people. When I go to a local user, event it. Hey, what kind of jobs you hiring for who you're looking for and who do I know that's looking for those kind of things and trying to help connect? You know, people in cos cause I mean, you know, we all sometime in our career, you know we'll need help alone those lines that I have, something that's personally that you know, I always love to help >> you. I have a friend who said it. I think best, and I can't take credit for this, right? But it's It can be easy to get dismissed from your day job, right? One errant click could be the career limiting click. It is nigh impossible to be fired from the community, right? And that that, to me, is a powerful differentiator for folks that are plugged into a community versus those that are trying to go it >> alone. Yeah, there are some community guidelines that if you don't follow, you might be checking for sure, but no, if if we're there in good faith and we're doing everything like out, tell me it's speaking. You know, this is such, you know, change. Is this the constant in our world? You know, I've been around in the interview long enough. That's like, you know, I remember what the, um where was this tiny little company that had, you know, once a week, they had a barbecue for everybody in the company because they were, like, 100 of them. And, you know, you know, desktop was what they started working on first. And, you know, we also hear stories about when we first heard about the emotion and the like. But, you know, today you know Veum world is so many different aspects. The community is, you know, in many ways fragmented through so many different pieces. What are some of the hot, interesting things? How does seem a deal with the Oh, hey, I want the Aye Aye or the Dev Ops or the you know where where's the vmc cloud versus all these various flavors? How do you balance all that out? All these different pieces of the community? >> Yeah, it's an interesting question. And to be fair with you, I think that's an area that were still getting better at. And we're still adapting to write. You know, if you look at V mug Five years ago, we were the V's fear, sort of first, last and always right. And now you know, especially is VM. Where's portfolio keeps increasing and they keep moving into new areas. That's new areas for us, too. And so, you know, we've got a big, uh, initiative over the next year to really reach out and and see where we can connect with, you know, the kubernetes environment, right? Cause that the hefty oh acquisition is a really big deal. and I think fundamentally changes or potential community, right? And so you know, we've launched a bunch of special interest groups over the span of the past couple years, and I think that's a big piece of it, which is, if you're really interested in networking and security, here's an area that you can connect in and folks that are like minded. If you're really interested in and user computing, here's what you can connect into. And so I think, you know, as we continue to grow and you know, we're, you know, hundreds of thousands of people now around the world so that you can be a challenge. But I think it's It's also a huge opportunity for us to be ableto keep building that connection with folks and saying, Hey, you know, as you continue to move through your career, it's not always gonna be this. You're right. Change is constant. So hey, what's on the horizon for >> you? When I look at like the field organization for being where boy, I wonder when we're gonna have the sand and NSX user groups just because there's such a strong emphasis on the pieces, the business right now? Yeah, All right, Steve, let's change that for a second. Sure said, You know, you're you got CEO is part of your title, their eyes, what you're doing. Tell me about your life these days and you know the stresses and strains And what what's changing these days and what's exciting? You >> sure? So you know, it's exciting to have moved for my career because I'm an old school admin, right? I mean, that's my background. Uh, so, you know, as I've progressed, you know, I keep getting different things in my portfolio, right? So it started out as I was, you know, I was the admin, and then I was managing the systems engineering team. And then they added desktop support that was out of necessity was like, I'm not really a dustup person, right? So something new you need to learn. But then you start seeing where these synergies are, right? Not to hate, like the words energies. But the reality is that's where we launched our VD. I project at U Mass. Lowell, and that has been transformative for how we deliver education. And it has been a lot of ways. Reduced barriers to students to get access to things they couldn't before. So we had engineering students that would have to go out and finance a 3 $4000 laptop to get the horsepower to do their work. Now, that can use a chromebook, right? They don't have to have that because we do that for them and just they have to have any device t get access via via where horizon. Right, So that happened, and then, you know, then they moved in. Our service is operation, right? So what I'm interested now is how do we deliver applications seamlessly to users to give them the best possible experience without needing to think about it? Because if you and I have been around long enough that it used to be a hassle to figure out okay, I need to get this done. That means they need to get this new applications I have to go to I t there and I have my laptop. Now it's the expectation is just like you and I really want to pull out my phone now and go to the APP store and get it right. So how do we enable that to make it very seamless and remove any friction to people getting their work >> done? Yeah, absolutely. That the enterprise app store is something we've talked about is not just the Amazon marketplace these days. >> In some ways, it is so not all applications rate. Some applications are more specific to platforms. And so that's a challenge, which is, you know, I'm a professor. I really like my iPad. Well, how do I get S P ss on that? Okay, well, let me come up with some solutions. >> Yeah, it's interesting. I'm curious if you have any thoughts just from the education standpoint, how that ties into i t. Personally myself, I think I was in my second job out of school before I realized I was in the i t industry because I studied engineering they didn't teach us about. Oh, well, here's the industry's You're working. I knew tech, and I knew various pieces of it and, you know, was learning networking and all these various pieces there. But, you know, the industry viewpoint as a technology person wasn't something. I spend a lot of time. I was just in a conference this week and they were talking about, you know, some of the machine learning pieces. There was an analyst got up on stage is like here I have a life hack for you, he said. What you need to do is get a summer intern that's been at least a junior in college that studied this stuff, and they can educate you on all these cool new things because those of us have been here a while that there's only tools and they're teaching them at the universities. And therefore that's one of those areas that even if you have years, well, if you need to get that retraining and they can help with that >> no, that's that to me is one of most exciting parts about working in education is that our faculty are constantly pushing us in new directions that we haven't even contemplated yet. So we were buying GPU raise in order to start doing a I. Before I even knew why we were doing and there was like, Hey, I need this and I was like, Are you doing like a quake server? Like they were mining Bitcoins? I don't think so, but it was, you know, that was that was that was an area for us and now we're old. Had it this stuff, right? And so that is a exciting thing to be able to partner with people that are on the bleeding edge of innovation and hear about the work that they're doing and not just in in the tech field, but how technology is enabling Other drew some groundbreaking research in, you know, the life sciences space that the technology is enabling in a way that it wasn't possible before. In fact, I had one faculty member tell me, Geez, maybe six months ago. That said, the laboratory of the past is beakers and Silla scopes, right? The laboratory of the future is how many cores can you get? >> Yeah, all right, So next week is Del Technologies world. So you know the show. The combination of what used to be A M, C World and Del World put together a big show expecting around 15,000 people in Las Vegas to be the 10th year actually of what used to be M. C world. We actually did a bunch of dead worlds together. For me personally, it's like 17 or 18 of the M C world that I've been, too, just because disclaimer former emcee employees. So V mugs there on dhe, Maybe explain. You know, the mugs roll there. What you're looking to accomplish what you get out of a show like that. >> Sure. So V mug is a part of the affiliation of del Technologies user communities. Right? And what I love about user communities is they're not mutually exclusive, right? You absolutely can. Being a converged and Avi mug and a data protection user group. It's all about what fits your needs and what you're doing back in the office. And, you know, we're excited to be there because there's a ton of the move members that are coming to Deltek World, right? And so we're there to support our community and be a resource for them. And that's exciting for us because, you know, Del Del Technologies World is a whole bunch of really cool attack that were that were seeing people run vm were on Ray. We're seeing via more partner with, and so that's exciting for us. >> Yeah, and it's a try. Hadn't realized because, like, I've been to one of the converted user group events before, didn't realize that there was kind of an affiliation between those but makes all the sense in the world. >> Yeah, right. And it's, you know, again, it's an open hand thing, right? Beaten and one being the other. You realize them both. For what? They're what They're great at connecting with people that are doing the same thing. There's a ton of people running VM wear on. Ah, myriad. Like you talked about earlier VM Where's partner? Ecosystem is massive, right? But many, many, many in fact, I would say a huge majority of converged folks are running VM we're >> on it. All right. So, Steve want to give you the final word? What's the call to action? Understand? A lot of people in the community, but always looking from or always, ways for people to get involved. So where do they go? What? What would you recommend? >> Yeah, thanks. So if if you are not plugged into user community now, when you're in the tech field, I would strongly encourage you to do so. Right? V mug, obviously, is the one that's closest to my heart, right? If you're in that space, we'd love to have you as part of our community. And it's really easy. Go to V mug. dot com and sign up and see where the next meet up is and go there, right? If you're not into the VM where space and I know you have lots of folks that air, they're doing different things. Go check out your community, right? But I tell you, the career advantages to being in a user community are immense, and I frankly was able to track my career growth from admin to manager to director to associate CEO, right alongside my community involvement. And so it's something I'm passionate about, and I would encourage everybody to check out. >> Yeah, it's Steve. Thank you so much for joining us. Yeah, I give a personal plug on this. There are a lot of communities out there, the virtual ization community, especially the VM. One specifically is, you know, a little bit special from the rest. You know, I've seen it's not the only one, but is definitely Maur of. It's definitely welcoming. They're always looking for feedback, and it's a good collaborative environment. I've done surveys in the group that you get way better feedback than I do in certain other sectors in just so many people that are looking to get involved. So it's one that you know, I'm not only interviewing, but, you know, I can personally vouch for its steeple. Thank you. Thank you so much. Always a pleasure to see you. >> Thanks for having me. >> Alright. And be sure to check out the cube dot net. Of course, we've got dealt technologies world in the immediate future. Not that long until we get to the end of summer. And vm World 2019 back in San Francisco, the Q will be there. Double set. So for both del world del Technologies world and VM World. So come find us in Las Vegas. If you're Adele or Mosconi West in the lobby is where will be for the emerald 2019 and lots and lots of other shows. So thank you so much for watching. Thank you.

>> Live from New York, it's The Cube, covering The Cube New York City 2018 brought to you by SiliconAngle Media and its Ecosystem partners. >> Okay, welcome back everyone, here live in New York City for Cube NYC, formally Big Data NYC, now called CubeNYC. The topic has moved beyond big data. It's about cloud, it's about data, it's also about potentially blockchain in the future. I'm John Furrier, Dave Vellante. We're happy to have a special guest here, Arun Murthy. He's the cofounder and chief product officer of Hortonworks, been in the Ecosystem from the beginning, at Yahoo, already been on the Cube many times, but great to see you, thanks for coming in, >> My pleasure, >> appreciate it. >> thanks for having me. >> Super smart to have you on here, because a lot of people have been squinting through the noise of the market place. You guys have been now for a few years on this data plan idea, so you guys have actually launched Hadoop with Cloudera, they were first. You came after, Yahoo became second, two big players. Evolved it quickly, you guys saw early on that this is bigger than Hadoop. And now, all the conversations on what you guys have been talking about three years ago. Give us the update, what's the product update? How is the hybrids a big part of that, what's the story? >> We started off being the Hadoop company, and Rob, our CEO who was here on Cube, a couple of hours ago, he calls it sort of the phase one of the company, where it were Hadoop company. Very quickly realized we had to help enterprises manage the entire life cycle data, all the way from the edge to the data center, to the cloud, and between, right. So which is why we did acquisition of YARN, we've been talking about it, which kind of became the basis of our Hot marks Data flow product. And then as we went through the phase of that journey it was quickly obvious to us that enterprises had to manage data and applications in a hybrid manner right which is both on prem And public load and increasingly Edge, which is really very we spend a lot of time these days With IOT and everything from autonomous cars to video monitoring to all these aspects coming in. Which is why we wanted to get to the data plan architecture it allows to get you to a consistent security governance model. There's a lot of, I'll call it a lot of, a lot of fight about Cloud being insecure and so on, I don't think there's anything inherently insecure about the Cloud. The issue that we see is lack of skills and our enterprises know how to manage the data on-prem they know how to do LDAP, groups, and curb rows, and AAD, and what have you, they just don't have the skill sets yet to be able to do it on the public load, which leads to mistakes occasionally. >> Um-hm. >> And Data breaches and so on. So we recognize really early that part of data plan was to get that consistent security in governance models, so you don't have to worry about how you set up IMRL's on Amazon versus LDAP on-prem versus something else on Google. >> It's operating consistency. >> It's operating, exactly. I've talked about this in the past. So getting that Data plan was that journey, and this week at Charlotte work week we announced was we wanted to take that step further we've been able to kind of allow enterprise to manage this hybrid architecture on prem, multiple public loads. >> And the Edge. >> In a connected manner, the issue we saw early on and it's something we've been working on for a long while. Is that we've been able to connect the architectures Hadoop when it started it was more of an on premise architecture right, and I was there in 2005, 2006 when it started, Hadoop's started was bought on the world wide web we had a gigabyte of ethernet and I was up to the rack. From the rack on we had only eight gigs up to the rack so if you have a 2000 or cluster your dealing with eight gigs of connection. >> Bottleneck >> Huge bottleneck, fast forward today, you have at least ten if not one hundred gigabits. Moving to one hundred to a terabyte architecture, for that standpoint, and then what's happening is everything in that world, if you had the opportunity to read things on the assumptions we have in Hadoop. And then the good news is that when Cloud came along Cloud already had decoupled storage and architecture, storage and compute architectures. As we've sort of helped customers navigate the two worlds, with data plan, it's been a journey that's been reasonably successful and I think we have an opportunity to kind of provide identical consistent architectures both on prem and on Cloud. So it's almost like we took Hadoop and adapted it to Cloud. I think we can adapt the Cloud architecture back on prem, too to have consistent architectures. >> So talk about the Cloud native architecture. So you have a post that just got published. Cloud native architecture for big data and the data center. No, Cloud native architecture to big data in the data center. That's hyrid, explain the hybrid model, how do you define that? >> Like I said, for us it's really important to be able to have consistent architectures, consistent security, consistent governance, consistent way to manage data, and consistent way to actually to double up and port applications. So portability for data is important, which is why having security and governance consistently is a key. And then portability for the applications themselves are important, which is why we are so excited to kind of be, kind of first to embrace the whole containerize the ecosystem initiative. We've announced the open hybrid architecture initiative which is about decoupling storage and compute and then leveraging containers for all the big data apps, for the entire ecosystem. And this is where we are really excited to be working with both IBM and Redhat especially Redhat given their sort of investments in Kubernetes and open ship. We see that much like you'll have S3 and EC2, S3 for storage, EC2 for compute, and same thing with ADLS and azure compute. You'll actually have the next gen HDFS and Kubernetives. So is this a massive architectural rewrite, or is it more sort of management around the core. >> Great question. So part of it is evolution of the architecture. We have to get, whether it's Spark or Kafka or any of these open source projects, we need to do some evolution in the architecture, to make them work in the ecosystem, in the containerized world. So we are containerizing every one of the 28 animals 30 animals, in the zoo, right. That's a lot of work, we are kind of you know, sort of do it, we've done it in the past. Along with your point it's not enough to just have the architecture, you need to have a consistent fabric to be able to manage and operate it, which is really where the data plan comes in again. That was really the point of data plane all the time, this is a multi-roadmap, you know when we sit down we are thinking about what we'll do in 22, and 23. But we really have to execute on a multi-roadmap. >> And Data plane was a lynch pin. >> Well it was just like the sharp edge of the sword. Right, it was the tip of the sphere, but really the idea was always that we have to get data plan in to kind of get that hybrid product out there. And then we can sort of get to a inter generational data plan which would work with the next generation of the big data ecosystem itself. >> Do you see Kubernetes and things like Kubernetes, you've got STO a few service meshes up the stack, >> Absolutely are going to play a pretty instrumental role around orchestrating work loads and providing new stateless and stateful application with data, so now data you've got more data being generated there. So this is a new dynamic, it sounds like that's a fit for what you guys are doing. >> Which is something we've seen for awhile now. Like containers are something we've tracked for a long time and really excited to see Docker and RedHat. All the work that they are doing with Redhat containers. Get the security and so on. It's the maturing of that ecosystem. And now, the ability to port, build and port applications. And the really cool part for me is that, we will definitely see Kubenetes and open shift, and prem but even if you look at the Cloud the really nice part is that each of the Cloud providers themselves, provide a Kubenesos. Whether it's GKE on Google or Fargate on Amazon or AKS on Microsoft, we will be able to take identical architectures and leverage them. When we containerize high mark aft or spark we will be able to do this with kubernetes on spark with open shift and there will be open shift on leg which is available in the public cloud but also GKE and Fargate and AKS. >> What's interesting about the Redhat relationship is that I think you guys are smart to do this, is by partnering with Redhat you can, customers can run their workloads, analytical workloads, in the same production environment that Redhat is in. But with kind of differentiation if you will. >> Exactly with data plane. >> Data plane is just a wonderful thing there. So again good move there. Now around the ecosystem. Who else are you partnering with? what else do you see out there? who is in your world that is important? >> You know again our friends at IBM, that we've had a long relationship with them. We are doing a lot of work with IBM to integrate, data plane and also ICPD, which is the IBM Cloud plane for data, which brings along all of the IBM ecosystem. Whether it's DBT or IGC information governance catalogs, all that kind of were back in this world. What we also believe this will give a flip to is the whole continued standardization of security and governance. So you guys remember the old dpi, it caused a bit of a flutter, a few years ago. (anxious laughing) >> We know how that turned out. >> What we did was we kind of said, old DPI was based on the old distributions, now it's DPI's turn to be more about merit and governance. So we are collaborating with IBM on DPI more on merit and governance, because again we see that as being very critical in this sort of multi-Cloud, on prem edge world. >> Well the narrative, was always why do you need it, but it's clear that these three companies have succeeded dramatically, when you look at the financials, there has been statements made about IBM's contribution to seven figure deals to you guys. We had Redhat on and you guys are birds of a feather. [Murhty] Exactly. >> It certainly worked for you three, which presumably means it confers value to your customers. >> Which is really important, right from a customer standpoint, what is something we really focus on is that the benefit of the bargain is that now they understand that some of their key vendor partners that's us and Ibm and Redhat, we have a shared roadmap so now they can be much more sure about the fact that they can go to containers and kubernetes and so on and so on. Because all of the tools that they depend on are and all the partners they depend on are working together. >> So they can place bets. >> So they can place bets, and the important thing is that they can place longer term bets. Not a quarter bet, we hear about customers talking about building the next gen data centers, with kubernetes in mind. >> They have too. >> They have too, right and it's more than just building machines up, because what happens is with this world we talked about things like networking the way you do networking in this world with kubernetes, is different than you do before. So now they have to place longer term bets and they can do this now with the guarantee that the three of us will work together to deliver on the architecture. >> Well Arun, great to have you on the Cube, great to see you, final question for you, as you guys have a good long plan which is very cool. Short term customers are realizing, the set-up phase is over, okay now they're in usage mode. So the data has got to deliver value, so there is a real pressure for ROI, we would give people a little bit of a pass earlier on because set-up everything, set-up the data legs, do all this stuff, get it all operationalized, but now, with the AI and the machine learning front and center that's a signal that people want to start putting this to work. What have you seen customers gravitate to from the product side? Where are they going, is it the streaming is it the Kafka, is it the, what products are they gravitating to? >> Yeah definitely, I look at these in my role, in terms of use cases, right, we are certainly seeing a continued push towards the real-time analytics space. Which is why we place a longer-term bet on HDF and Kafka and so on. What's been really heartening kind of back to your sentiment, is we are seeing a lot of push right now on security garments. That's why we introduced for GDPR, we introduced a bunch of cable readies and data plane, with DSS and James Cornelius wrote about this earlier in the year, we are seeing customers really push us for key aspects like GDPR. This is a reflection for me of the fact of the maturing of the ecosystem, it means that it's no longer something on the side that you play with, it's something that's more, the whole ecosystem is now more a system of record instead of a system of augmentation, so that is really heartening but also brings a sharper focus and more sort of responsibility on our shoulders. >> Awesome, well congratulations, you guys have stock prices at a 52-week high. Congratulations. >> Those things take care of themselves. >> Good products, and stock prices take care of themselves. >> Okay the Cube coverage here in New York City, I'm John Vellante, stay with us for more live coverage all things data happening here in New York City. We will be right back after this short break. 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(upbeat music) >> Announcer: From the SiliconANGLE Media Office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Stu Miniman. >> Hi, and welcome to a special presentation of CUBE Conversation. I'm Stu Miniman and we're here in our Boston-area studio, happy to welcome to the program first-time guest Brian Kelly, who's the Co-founder and CEO of CLoudGenera. Brian, thanks so much for joining me. >> Stu, thank you so much for having us here. >> All right, first of all Brian, we always love. We get you know a co-founder on the program, you got to bring us back to kind of the why. You know, why was CLoudGenera formed? We've had a chance to dig into it but CLoudGenera, there's cloud in the name, there's generation. Tell me about the company, the name, and a little bit about your background. >> Be glad to. So like most great companies, our company was born of the market's necessity. We saw trend happening as many businesses we're shifting the way they manage their IT and the trend took the form of this buzzword cloud. And so you know CLoudGenera as a company absolutely helps businesses figure out their most efficient path towards leveraging cloud technologies. But our value proposition is actually greater than that. Our business exists to help companies determine the best IT services to support the needs of their organization. >> Great. Well luckily cloud's simple. Enterprise IT, we just have a button we press, and everything works awesome. I think the reality is though, nobody ever gets rid of anything. Changing applications is really tough and it's a really complicated and super fast changing market out there. So maybe, drill in just a tiny bit and explain what it is that you do and why that's a little bit different than some of the other things happening in the marketplace. >> Sure. Well the big easy button does exist, when you push it nothing happens. Maybe it makes a funny sound. As the name would suggest, CLoudGenera specializes in the formation of clouds and to the point that you made, this is not simple, this is not easy. Cloud is not a target state. Unlike virtualization, which was a target state, cloud is really an operating model. And also as you highlighted, there's so much variability and complexity associated with cloud. Am i talking about infrastructure? Am i talking about platforms? Am i talking about software as a service? Cloud for us can be any of those things. It can be you managing your infrastructure. Can be somebody else managing your infrastructure, all the way up through your apps. And so what our business aims to do is to demystify all the variability and complexity associated with making cloud decisions. Really it's about helping people figure out where to place their workloads and what we commonly see is that the migration does not generate success unless you've considered how to optimize your workloads in advance of selecting a new execution venue. So as a business our software, our technology, helps customers to determine how do I optimize my workloads, regardless of whether or not I'm going to move them. And ultimately, how do I get the best value for my spend at IT services as I'm contemplating cloud as a model for hosting my apps? >> Yeah, so every vendor I talk to out there, if I'm a cloud platform vendor or if I'm an infrastructure vendor, they all have these tools that say hey, here's how the experience is going to be on our platform. Maybe it compares against a couple of things out there but you're not pushing hardware, you're not pushing platforms. Explain how you fit into kind of the ecosystem and you're not just, when you say cloud it's it's not just public cloud, it's you know, talk a little bit about the spectrum of things that you support. >> Okay, be happy to. So first, what I would say is that when you look at a vendor strategy, their strategy is to drive you to adopt their technologies, their solutions. And so any of the tools that they're bringing to market, any of the services that they're bringing to market, are biased towards the outcome that they're trying to achieve. This was actually when I say CLoudGenera was born of the market's necessity, the market really needed a solution that was agnostic and unbiased to the outcome. Something that would be so bold is to recommend not doing anything if that was the best option available to your business. That's really what makes CLoudGenera special. We are the best place to go in the market to get that unbiased agnostic viewpoint that's tailored to your needs as an organization and guides you to the right vendors and the right solutions. >> Yeah. It's interesting you think about like there's consulting companies that would get involved and send a bunch of people and help you through your journey. We talked about there's been lots of tools out that have poked at this but there's a big elephant in the room and it's a little tough to kind of figure out where to start. So I just want to, talk a little bit about kind of the breadth and depth of what you do. How do you keep up with all of these things? I mean, while we were talking I'm pretty sure Amazon released one or two new features. And the next time Intel comes out with a spin, you've got a billion SKUs that you have to update. So how does this impact you and how do you help keep up with it? >> So Stu, this is really what creates the longevity and value proposition for my business. The market is changing at breakneck speed. To your point, the major providers both in data center as well as in cloud have probably released a half a dozen new services for the market to contemplate just in our conversation. So CLoudGenera addresses this in a couple of different ways. But all of it born in automation and intelligence. And so we have a cloud research function as a part of our platform that is continually ingesting the data around what the market can offer. So this could be services you could consume from public cloud providers like the Microsoft Azure, the Amazon EC2, the Google Compute as an example, but we're not an infrastructure play. We actually move up and down the stack. So if you want to look at platform as a service solution like Cloud Foundry as an example, you're moving towards no SQL, as an example, for managing data. Do I do that is infrastructure? Do I do it as a platform, as a service? Right, what level of service is available in the market? Our automation, our intelligence, gathering that market data is the big value for our customers because through that automation we give them something that have avoids their need to spend a lot of money on consultants or to spend a lot of time internally trying to assess what the market can offer. And then most importantly once you have that data, how do you turn it into insights? How do you take that data and make it actionable for your business based upon your needs and the requirements of your workloads? So that that's a big part of our secret sauce. A big part of our IP. We stay current with the market so that you don't have to. And what's interesting about our business is that we don't just do point in time comparisons. In fact, we sit on historical data and trends, both how you can modernize in your data center and how you can leverage cloud services and that data set is over four years large, I like to say, not four years old. And so in that way we can even predict where the market is headed so if you're if you're leveraging us or doing this manual as opposed to leveraging our automated methods, we've got the recipe of how to make good decisions and really it is staying current on the market. That's the only way that that you can address it. Love to touch on another aspect of the question you asked, which is consultancies. If there's one thing that we're disrupting in the market, it is the ability to do this analysis at scale. Many of our clients tell us that it's cost prohibitive to hire an army of consultants to come in and assess their current capabilities and then attempt to map that to what the market can offer. If you're using a manual method powered by labor, you're likely going to have an answer that reflects the market ninety days ago, 180 days ago. CLoudGenera gives you the power at your fingertips to get those sort of insights immediately. And when I talk about disruption, it's really doing in minutes what normally took months. it's also a fraction of the cost, Both productivity and labor as well as the true costs if you're leveraging consultants to do this sort of analysis. and so in that way we can scale to servinG customers that are as large and as complicated as the Global Five. We can also scale far and wide to serve many customers in the market at the same time. Again, it's because we're using algorithms. We're using data science. We're not trying to solve this problem with labor. >> Yeah, I love that and you talked about, it's not just about the platform, you're looking at what we've said for years. Customers need to look at their data, they need to look at their applications, and that's where you need to start. I'd like you to talk a little bit about your users because you know, talked to so many companies, it's like oh, they've tried either building their own in-house solution or going to a service provider or going to a public cloud and they get one or two apps. Some critical one or some real important or some cool new one and then they're like okay, I've got hundreds or thousands of other apps and trying to figure out how they do that, you got to use some intelligence. You need to use some, you know, it needs to be driven by software. It can't be some big process that I'd have some consultancy or a thing like that. Do you have some customer examples you can bring us through or talk to how that typically works? >> Yeah, absolutely. I'll share a few patterns that we see in the market. One pattern and it doesn't have a bias towards a particular industry vertical or a particular size of customer. But there's an illusion out there in the market that you'll be able to lift and shift your workload from your data center to Amazon's data center, as an example, and then magically that's going to take care of all your problems. Amazon's going to manage your mess for less. Well, the harsh reality that customers are finding is that while Amazon, as an example, might be an excellent provider of IT services for your business, if you're not optimizing your workload to leverage that provider, you're not going to get the benefits that you'd hope. And so one trend we see commonly in the industry and it's a mistake we hope folks make, whether they leverage our service or they solve this problem some other way, is you know please don't try to do the lift and shift. In fact, another big trend we see in the industry of companies that have gone that route is they do what we like to call repatriation. Where they made the full-fledged push into migrating their workloads to a new venue and ultimately to figure out that the lift and shift was not successful for them. And the larger the client, the more pain they've experienced because the more money they're spending on IT and the harder that gets. >> Just to poke at that a tiny bit and I know we don't have a lot of time to dig into it but it's if you lift and shift and that's the step one of doing, I need to break something apart, I want to refactor some pieces, and eventually know I'll get there. But is that okay and are there paths to get there? Or are you saying hey, you want to sort those pieces out first before you get to the cloud? >> There's some use cases where lift and shift absolutely has a benefit, absolutely has a value. If you're dedicating IT capacity and it's dedicated towards something that's used sporadically, well just the usage model alone, you could potentially get a benefit out of a lift and shift. You're getting the benefit of the optimization just by being able to leverage the elasticity of cloud. But beyond some of those low hanging fruit use cases, we actually see this as a detriment to many company's success. I like to use the analogy of a moving company. The last thing you want to do is pack the box, pick up the box, move the box, and then move it three or four times before you actually get to the destination. That's what lift and shift is really doing. You just pick up what you had in your data center, you put it in somebody else's data center, and now you're in a foreign land and you're going to try to break that thing apart and re-engineer it there. That's actually going to be a lot harder in practice than what we've seen as more of a better option, which is optimized where you are. If you're if your target state for the next innovation is to get to containers, figure out how to containerize before you make the migration as an example. If your endgame is to move from a database on infrastructure to a platform as-a-service, well optimized that databases deployment, optimize that workload before you attempt to transition it to the path. So I would say nine times out of ten, you're probably going to want to treat an application workload before you attempt to move it someplace else. Otherwise, you're just going to be lifting and carrying that box several times. >> Yeah, it unfortunately reminds me of anybody that's moved and you know, you move someplace and three to five years later you run across that box and you're like why did I even move this to my environment. I've outgrown it, I don't need it. I could have either gotten rid of it or done something else with it. Last piece of the technology I want to cover for today is we've talked a bunch about the public cloud, you do a lot with service providers and with the in-house data center stuff. Maybe talk a little bit as to what you cover. Public clouds, there's a few really big ones but there's so many service providers. What do you engage with? What do you cover there and in the data center there's just, I can't imagine how many options there are. What's the scope of what you cover? >> So this might be a little controversial for some folks because if you read the the trade rags, cloud is the answer. Whatever cloud may be, moving to cloud is the answer. Our philosophy as a company is that public cloud is not the only game in town, nor will it be the only game in town in the future. We believe in companies investing in technology to get the best value for their spend. And as a result there's a continuum of options that we see existing far into the future and those include regional data center providers. Frequently we see them being value-added because they can offer a level of service that's not yet been implemented in public cloud. Who's going to manage the stuff that an Azure doesn't manage, as an example. These regional providers, these service providers, many of whom are evolving to do managed services and other people's data centers, not just their own, are going to play a key role in this next wave of technology. And so again, these regional providers, we see them being very important for delivering the service level that customers expect. There's also and this is a very prominent topic right now, there's concerns about data privacy and data sovereignty. While the hyper scalars have done a great job of building a global footprint, they still have gaps. And so if companies are concerned about GDPR in Europe, as an example. If they're concerned about PIPEDA up in Canada, as an example. These regional service providers have the compliance capabilities, they have the protection already in place to not just deliver a high service level but also to deliver a solution that can be lower risk for your business. And so that's really where we see service providers fitting in the market and we see customers having the right mix of public cloud and service provider powered infrastructure. As well as for large companies, they may still have the buying power, and they may still have the level of expertise in house, so like my Fortune 50 clientele but you could even take it down probably to the Fortune 500. Where it's more cost-effective for them to still operate in their data center. Today, because we're a data-driven company and we live in the data and the insights it provides, still the majority of the workloads, either for service level security or if you're a large company, the economics to run IT are still better suited in data center. We don't know that it's always going to be the majority in your data center. We see this evolving as the public cloud providers continue to mature, over the last few years they've matured greatly. But again, we see a continuum of options for customers to consider. We think those options will get smaller but we still think you're going to have a purpose to consider in your data center, in a regional service provider, as well as considering a hyper scalar for your needs. >> All right. Brian, last thing. Need to get speeds and feeds on CLoudGenera. How many employees you have, how many customers you have. Can talk anything about the funding? And tell us about this looking south. >> The Silicon South. Well, let me start there. One of the things we're very proud about is being a company that's headquartered here on the East Coast and specifically in the South. That said, we're already a global company. We have customers around the world. There's well over a thousand subscribers of our cloud assist technology, which is where you can both model future uses of technology as well as load in your existing inventories and analyze your business at scale. What I would share again about the Silicon South is that we're one of these cool companies that is helping the southeast kind of rise up as a technology center. Not one of the normal places that folks think of as innovation hubs but very much in the Carolinas in particular, we have a market that's on the rise with very smart data scientists, very smart developers, and very strong business leaders. And so that's one of the things we are very proud of as a company. There are 22 employees in CLoudGenera today. As I mentioned, we have a global footprint in terms of customers. I gave you a stat just around our cloud assist product. One of the cool things about us is that we serve both the consumer, so that would be the enterprise that's trying to figure out what to do with their technology investments. We also serve their suppliers. We will not bias ourselves so they can't bias the output of our software but what they can do is leverage our software to guide their customers decisions. In fact, our relationship with Amazon, Microsoft, and Google are relationships where they know sometimes our software will recommend an outcome that they can't monetize but they still choose to work with us and they still choose to recommend us and in some cases, leverage us for their clients to make sure their clients are getting the best value for their spent. >> Well, Brian Kelly, Charlotte North Carolina based CLoudGenera. Appreciate you joining. Thanks so much for sharing with us some of the nuance and complexity that you're trying to help enterprises glean through. We'll be back. Check out lots more coverage at theCUBE.net. So many shows where companies are trying to sort through this very complicated space. So be sure to check out theCUBE.net for all the videos. Wikibon.com where we're digging through with our analysis on our team. I'm Stu Miniman, thanks so much for watching theCUBE. (upbeat music)

>>From Las Vegas, it's the cube cuddle EMC world 2016, brought to you by EMC. Now your host, John furrier. Welcome >>Back everyone. We are here, live in Las Vegas for EMC world 2012. I'm John Ferrari, the founder of Silicon angle and host of the cube. And we are extracting the signal from noise. And one of our traditions at EMC world is to do a conversation and panel discussion around women of the world with Stella Lowe, who is VP of global communications for EMC and Susan Carter, Nico, who's the founder and CEO of authentic leadership. Stella. Every year we do this as one of my favorite things. As we wrap up EMC world, soon, it may be Dell world or Dell EMC, whatever that kind of turns into. Yeah, I wish you can't comment. Cause your communications is, is to talk about kind of the human side of what's going on. And the theme for EMC was modernization of enterprise, you know, infrastructure, speed, performance, scalability. And you've taken this theme this year with women of the world to modernizing your career in an era of change. And tell me about what that was this year. >>Yeah, absolutely. John. So yeah, we were in this, um, tech industry is changing all the time, but right now we're in this kind of unprecedented change. Um, you, this, this is gonna be a lot of consolidations is the thinking over the next two years, a lot of people find a lot of companies finding their dance partners. In some ways we've already found our dance partner, which is Dell, but there's gonna be a lot of that going on. And um, and there's definitely a lot of change happening here at EMC. So we wanted to make sure that we were focusing on how to own modernize and direct your career within this sea of tremendous James. >>So Susan, I want to get your take on this because we are living as the theme of the show is, is a transformation happening, which means there are certainly change and there's big bets being made in the business that requires people process and technology transformation. People is a big part of it. And people have to be bold. There's some gambling, there's some bets and with that will come maybe some missteps or some failures and how you can overcome that will define ultimately your success to take maybe little failures, not big failures, but like, but this is part of the evolution of innovation. How does that affect people, specifically women, as they're in this now converge workforce, male, men and women coming together. What's your thoughts on this? >>Well, men and women alike change is hard, right? So as industries converge as merchants and acquisitions happen, you know, the industry itself is in such a massive transformation mode. It's requiring people of all of all levels and in all fields, but particularly in the world of technology to completely redefine their skillsets, their relevance, the way they're going to actually help sort of step into this new era of digital technology. So it's causing, you know, ripple effects of reinvention and change all over the place. You know, we all to change as human beings at a very personal level. What does it mean for me? And so a big part of what we discussed today at the conference was just, how do you sort of lean into that change and how can you begin to look at your own potential and your own skillsets from, with a different lens? >>You know, um, we tend to box ourselves in as far as our potential goes and we say, okay, I've been in this functional area for all of my career. So I guess my opportunities sit squarely in this box. And we talked a lot about the value of sort of reinventing and taking a hard look at our transferable skill sets. So the attributes that we have as, as human beings that could let be leveraged into other roles or expanded roles and the skill sets that have made us so successful in what we're doing today. So how might we bust that open and find new opportunities in this world of change? And it's pretty important that we do it now. I mean, there was a, um, it was announced just a few days ago that in 2015, there were 359 new CEOs announced, uh, in the top two and a half thousand companies around the world. Only 10 were women, John 10, 10 out of 359. It's shocking. So if we're going to change, reverse that trend, we've got to start reversing that rate from that >>Consistent though across all industry, even venture capital, which has really highlighted in Silicon Valley where we live and that's obvious a male dominate, but now there's no women VCs. Now cowboy ventures is a bunch of them that are coming together and Hey, we can play ball each other. >>What does it surprise you that there's less women learning about tech now learning, you know, in tech education now than there was in the eighties? I mean, so, so we've already got to grapple with this and, and, and change the course of this. And, and women have got to start taking responsibility for their own careers and their own direction. >>What are some of the stories that you've heard this week at, at your event, as you guys talk with each other, what are some of the common patterns and stories that you're hearing? >>So we're certainly hearing from the women in the room, but they see that the impending change as exciting as an opportunity, but they're also, there's also some things anxiety around that change. There's definitely fear there and that's what we're seeing. Um, you know, and, and, um, you know, they need, people need to take that fair and use it as a catalyst for positive things. Right, right. I mean, 10 people tend to shut down when they're in environments of fear. And one of the things that we talked a great deal about was how do you sort of turn that around and, um, use that as a catalyst to take stock in not only sort of what your inherent capabilities are, but your vision for your life and the values that you hold dear and say, okay. So if my job serves my life, then what is my end game and what steps in choices can I make, you know, putting myself back in the driver's seat versus letting this this change. That's sort of at the, both of my macro level and the micro level, like sweet meander and, and, and create a, of a victim mentality. We talked a lot about sort of that empowerment and the accountability to sort of take charge of your own desks. >>It's interesting. You mentioned leaned in earlier. So Sheryl Sandberg's in my community in Palo Alto, Facebook friend, you know, where I'm involved a lot with some Facebook stuff. And I put, I've been following her lean in and I want to bring this up is you mentioned the word fearless. Um, you know, I've been called fearless, fearless. That's a guy thing, right. Guys can be fearless. Is it okay for women to be fearless and is lean in a fearless kind of vibes? It's not so much, I don't wanna get semantically tied on views, but this brings up a point that people get stuck on the semantics, but that kind of is a bias thing. Be more fearless and you'll get ahead versus lean in is a guess could be construed as a female version of fearless, the words matter. But at the same day, how does a woman become fearless? It doesn't matter. Yeah. >>So the other speaker that we had on the panel today, we were very lucky also to have Rashma, um, uh Rashma Sudani uh, and she, she, um, has the company, uh, founded the company, girls who code, and she says that women were brought up to be, uh, perfect. Whereas boys were brought up to be brave. So it's okay for a boy to climb a tree and go to the top. But with girls were like, no, no, sit in the chair, look pretty, be nice, you know, but be perfect. Um, and so women are very scared to go into areas that don't know because they're worried about making mistakes. And what we were trying to get over today was imperfection is okay, it's okay to make mistakes. It's okay to, you know, and you've got to get kind of get over that fear to do that. >>And it's the attributes Susan. So a woman and a man, they have different attributes. So maybe fearless my, Oh, he's feeling at the top of the tree, but every attribute in a diverse environment can contribute to a common outcome that makes it better. I mean, that's kind of the theme that I'm seeing. >>It's true. Um, fearlessness in you say words matter, uh, concept is kind of the same. We talked a lot about self con self-confidence and the, the contrast in the sexes, uh, when it comes to self-confidence and then so many women seem to sort of stop short of having that self confidence to step out and you say, be fearless to take risk to just sort of seize that moment and say, you know, what, if it doesn't work out, I can choose again. There's we just seem to stop short of being able to do that, where guys seem to be a little bit more comfortable. And part of it is the way we're raised, you know, women to be perfect. And we tend to be very, very quiet about those failures. And so it kind of sends that message. Like, I really need to set a stay away from those arenas where I just, I might not be a stunning success. >>So there was some discussion around men versus women in the imposter syndrome, which tends to afflict a lot of women, particularly women in business, where we kind of doubt our own worth as, as a leader, as a professional. And there's this fear that, you know, at some point we're going to be found out that we're really not as good as others around us think we are. And that drives a certain kind of behavior in the workplace. So, you know, um, workaholism, perfectionism, procrastination, just so afraid to make a mistake and be found out. So, you know, that seems to be, um, more characteristic of females than males. Um, there are just a lot of, there's a lot of complexity around >>The guys that are faking it, that good will be found out. It may be, maybe there's a thing there, but modernizing your career though. That's the theme? What is the pattern that, what does that mean? I mean, how, how do you talk to that? Because everyone wants, I mean, who doesn't want to be modern, right. And we're in the modern era, we want to be happy. We want to be cool when advance, okay. Advancement means you're climbing the ladder or you're, you're trying something new, which means you will fall and stumble. We all stumble when we learn is that part of the modernization is dealing with the environment and the change and the failure. >>Yeah, it is. In fact, um, the first thing that we talked about was the need to be incredibly strategic in this environment, we're business people. And when facing any business challenge, you tend to do scenario planning, right? And you say, well, if this happens, here's my strategy. Uh, if that happens, here's my strategy. So you say worst case, best case likely case. And, and when you start to develop strategies around how you're going to navigate those things, it gives you additional power and confidence to sort of move forward in your redefinition. So that's sort of that the first step in modernizing your career, we also talked a bit a bit ago about, um, understanding where you might have some self limiting beliefs about where you might play, you know, the, what arena, where you might, you might sit and so starting to sort of broaden your horizons. >>Um, yeah, definitely. I mean, uh, women will look at a job spec, um, and have a completely different perspective from men. So men will look at it and they'll say, well, I can do about 38% of this. So I'm going to go for this job. Um, women will look at it unless they can do 85% of it, or they've done that they have experienced in 85% of it. They won't even go for the job. So we have to start to really broaden our view of the types of jobs we can go for the types of opportunities we can go for and start to think more, well, much more openly. So be >>More aggressive on the job. Applicants was one was >>One. Yeah. Broaden your horizons. Think about this, the transferable skill sets that you have, that you can take into other areas. And, and don't be, don't be fair fearful of things that you haven't done before. >>So I had a public failure startup that was very funded and then the public failure and it's traumatizing. And I dealt with that and you know, this whole failure is rewarded in Silicon Valley. That's BS, in my opinion, people tolerate failure, but they loved the comeback. That's part of learning is coming back. And, but, you know, and so I had to deal with that until I was in my own way as a guy, but there's a post in Silicon Valley going around today, around a woman who failed. And she didn't know whether she should be vulnerable or just be that what'd you call it the imposter syndrome, fake it till you make it. And she was saying, no, I want to be vulnerable. Because what she found is by being vulnerable, people were helping her. So that brings up the concept of vulnerability, male, female, and two in the modern world. We have social networks now. So lean is a great example of some gravity around peer groups. Can you guys talk about that? Does that come up at all on your radar, in terms of the dynamic there around men versus women being vulnerable versus being strong and also the notion of networks and how that could be? >>Well, I think vulnerability is often tied to shame and that fear of shame causes people to hold back in sharing their real stories. You said something very important and that's that people care about what you've learned along the way. They don't necessarily care about what, you know, they care about what you've learned. Most people are comfortable talking about what they've learned when they're on the other side of that. So it's not in the, in the middle of that trail here, when you are just feeling horrible, you're feeling horrible. You're feeling like a failure. You're feeling embarrassed, you're feeling shame. So the ability to kind of step up to that is it's a tall order. Now you talked about social networks in this environment of social media. Authenticity is so important, right? So it's that happy balance. If you're not all that comfortable with being completely naked in that vulnerability, maybe there's a happy medium where you can share some of the challenges and things that you've been facing while not necessarily going all the way down to the, you know, to the bare nub of it. Um, I think we're right. >>So authenticity will track the right alchemy of, of help or it relationship as a way to signal to people. I mean, I guess, and that's just me. I love this concept. I mean, I feel like I should get you guys with my life coach. This is my lifestyle. So this is the next one. So, okay. So that's cool. I love that theme. I love this topic because that really helps you get through to the other side and gain to the other side. You're on the comeback. That's a learning what you've learned and applying what you've learned is a growth mindset. Now there's a lot of women, my age, I'm 50 that I've grown through the ranks and they get up to the top. And you mentioned the numbers, aren't that significant on the seat level of women it's lonely yet. They're being asked to be mentors down to the new generation of ladies coming up or women. And, but they're lonely at the top. How do they deal with that? As you're moving closer to the top, have they talked about that >>Only at the top? And I would like still, I was a senior executive at a big company and found that loneliness to be quite palpable. Right? Um, it's part of the choice you make to be in that arena, stepping up to that position of leadership. It often means that you're distancing yourself. You're being more, you're more concerned with being respected than you are being liked. And you know, there there's a, there's a new game, right? New parameters around your relationships like CEO's, um, who find solace in their peer relationships. I think that same goes for women. You know, you, you need to actively cultivate your formal and informal networks and they may be with, with, uh, peers outside of your company, outside of your functional area. Those relationships though are so important because you can become isolated and insulated. Um, people may not always come to you with the, with the truth. >>And so, you know, making sure that you keep those lines of communication and mutual support open is really pivotal. Now you mentioned mentorship. Um, I think it is incumbent on senior women to reach down and find opportunities to mentor other women and sponsor other women. You know, there's mentorship and sponsorship, and both are crucial in terms of sort of direct feedback and developmental advice on the mentorship side, but then sponsorship literally actively opening doors for other women and, and reaching a hand and helping them come up to because that's often where we find a gap. People think I had to claw my way up. It was a lot of work. So I'm just going to sort of protect myself and hang out and let everybody else kind of go on their own journey. We talked a lot today about the need to sort of reach down and help other women. >>So the takeaway there is develop your formal informal networks. That's a foundational really critical linchpin to the whole success. Um, what about now, as we look at the progression going forward, um, the skill development, you mentioned the job applications, a lot of these jobs that are going to come with the next industrial revolution as Michael Dell was pointing out, don't even exist today. So there might be an opportunity here as we look to the future. Did that come up at all on the radar of your sessions? >>Well, we talked, I think it comes back to really transferable skill sets. You need to take a look at what, what you do and who you are, bring it up a level because I got to tell you if you can manage well in ambiguity, if you can lead and motivate people. I mean, if you, there, there are certain attributes that, that pick the job. Yeah. If you have those, if you have those attributes and those skills, you can learn a discipline, but those inherent leadership skills are going to pay off the big time as this industry continues to redefine. And as you say, jobs that we don't even know exist yet, suddenly come onto the table. >>What surprises you the most in this, in the conversation around modernization, as you talk with folks out there, what's a trend that surprised you that you kind of knew about, but, Oh my God, this is really more acute or more explosive than in a good way, or in bad way. Anything you can share, like the literally like, wow, this is really more pressing than I thought, or this is actually more amazing than I thought. >>Yeah. Um, one of the things the Rushman talked about is women supporting other women. I mean, sometimes we are the worst critics of other women and, uh, you know, female bosses can be harder on female employees and so on. And I think there's got to be that kind of sisterhood, um, uh, around, uh, all of us have been bring women up as, as, um, Susan has said, support other women, uh, make sure that you are their back and they are watching yours. And, uh, it will help with the loneliness factor, but it also helps to, to bring women forward. And I think that's always a surprise to me that women don't want to do that. And they, and they don't want to get involved in that. We should be paying that back and paying it. >>So is there anything that surprised you looking back at, and then the constitution here? >>I think I would echo what Stella said. It's, um, it's important to understand the role you may be playing in the plight that faces you. So, you know, we talk about women sometimes being their own worst enemy and trying to, to again, modernize and redefine what that relationship looks like and what that success looks like and how accountable we each are for, you know, moving forward and pushing the envelope. >>Okay. Final question. If you guys could each answer, this would be great. What advice would you give the people watching here live, and then on demand things that they could do to modernize their career in this change, uh, advice that you can surface and share insight around their opportunity, things that they could do differently or new, or, >>Yeah, I'll let Susan have the last word on this. Cause you'll have some fabulous advice, but you know, one thing I would say is, is, uh, be comfortable in your imperfection. You don't have to be perfect. You'd go for it, widen your spear of opportunities and, uh, you know, Matt Mo uh, Charlotte, your way and, and dream bigger and he dreamed bigger. You might, you know, you'll get somewhere bigger. Very good. Um, I would say first and foremost, one of the best things that you can do is challenge some of the beliefs that you might hold about what your potential next steps or career path might be, um, get clear on what your end game is for your life and what your values are, because that becomes a very important lens through which to view future opportunity, get, get really clear that you can always choose. >>Again. I think this fear of making a mistake and that you talked about fearlessness, um, you know, I think people tend to, to limit their opportunities because they think, wow, if I make this choice and it's mistake, then I'm done, but you can just turn around and make a new choice and begin again. And there are limitless choices that you can make. So a lot of this I find is mindset related. You know, we're heading into a, we are in a highly turbulent time. It's going to continue. We need to be agile in our thinking part of that is getting grounded in who we are and what are our potential could be getting clear on what we want because our jobs serve our life, not the, not the other way around and really sort of getting into the driver's seat versus letting whatever the change is, whether it's up here, the industry consolidation level, or whether it's down in, whether we're in the middle of a merger, or we've just gotten a new boss that we don't particularly click with, we can default to a victim mentality. So part of this is just saying, you know what, I am going to pick this thing up and I am going to manage to the change myself >>And we are living in a world where there's great opportunities, women of the world. Great segment. Thank you so much, Stella. We thank you so much, Susan, really great to have you guys sharing your insight here on the cube. Um, congratulations again, always my favorite conversation. I learned a lot, um, and I love, I feel like I'm learning so much and this is a world of diversity and it's great. And the outcome is diversity is fantastic. And I think that's what everyone's seeing. So congratulations on the great work. This is the queue here at EMC world 2016. I'm John for a, you're watching the cube >>Looking back at the history of it.