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David Comroe, The Wharton School of the University of Pennsylvania | Dell Technologies World 2018


 

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Dell Technologies World 2018. Brought to you by Dell EMC, and it's ecosystem partners. >> And welcome back to Las Vegas, as thCUBE continues our coverage here of Dell Technologies World 2018. So glad to have you along here for our Day Three coverage. Along with Stu Miniman, I'm John Walls. It's now a pleasure to welcome David Comroe with us. David is the Senior Director of Client Technology Services at the Wharton School of Business, at the University of Pennsylvania. David, thanks for being with us. >> No problem. Glad to be here. >> Thank for sharing your time with us. First off let's just talk about, about the scope of your work. Again, you take care of all the obviously IT needs for the largest business school faculty in the world. Right? No pressure on you there. But talk about day to day, those responsibilities. >> As you mentioned my title is Senior Director for Client Technology Services. I'm essentially responsible for providing the support and services to four very distinct user groups that we happen to have at a university. That's of course our wonderful faculty, our staff that make everything happen, our incredible students, and of course our alumni group, which is about 100,000 people strong at this point. Just Wharton alums that are again, very important. Give back to the school. Provide mentorship and job opportunities for our graduates. Again very distinct needs for each of those four groups. We provide a high quality, and all the buzzwords. You know, secure, safe, efficient, highly available services to these groups. That's kind of what I do all day. >> One of the cool things, I love acronyms. Not that this industry doesn't have a few, as you know Stu. But WHOOPPEE. I absolutely love making whoopie. But not what you might think. But walk us through that and what it stands for, and what you did in it. It really was groundbreaking. >> You're putting me on the spot with this one. So WHOOPPEE is the Wharton, let's see if I can get this, Online Ordinal Peer Performance Evaluation Engine. One of our incredible faculty, Pete Fader, came up with this idea. It's no secret that grading is kind of bad. Faculty grading students. There's all kinds of challenges. >> It's tedious. >> Well it's tedious. There's inherit biases when you're, the larger the class. And when you have to grade 80 papers, or 100 papers or 200 papers. It's really hard to keep consistency across when your grading paper one through paper 100 through paper 200. Plus when you start divvying up the work between TA's and different faculty teaching the same class. Again fraught with bias. A number of people, again Pet Fader's idea, to come up with basically an algorithm that helps the grading process. And basically what happens is, is students are grading themselves. What we'll do is we'll give them five papers or five projects to grade. And they don't actually grade. All they have to do is rank it. You know, this is the best one. This is number one. This is the worst one. This is number five. And then there's this magic behind the scenes that that runs in our local infrastructure, in our cloud infrastructure. That basically runs an algorithm. And that algorithm is the secret sauce that some of our statistical geniuses at the Wharton school, of which we have many, came up with. And it has all kinds of cool features. You can say, well this batch of five papers might be harder. I might have the five best papers in the class. That's not fair. They still have to rank one the worst. You know, five. You can't say these two are the best. And this one's third. You actually, the students have to read the paper, and just rank it. I like this one the best. I like second, third, fourth, fifth. The algorithm takes into account difficulty of batches of papers. You could literally have the five best or the five worst papers in the class. And that's still going to provide meaningful data to the algorithm. So when you have 50, 100, 500 batches of five. They all start to figure it out. And the algorithm will actually figure out what the best paper is in the class. And what the maybe again at the Wharton. But not so great, greatest paper in the class. >> But not the worst. Just not so great. Again cause our students are brilliant. It basically goes on the fact that if you do a quality paper. If the algorithm says you're the best. Your weight means more than someone who might not have done such a good job on the paper. And you're considered a better grader. And it's weighted towards the better graders. There's all kinds of really cool stuff in there that we think is going to change... Get rid of some of that bias that I spoke about before. And help provide. And the data we've seen is, frankly the students like doing it. They don't like the additional work involved with it. We're seeing some empirical evidence, and some in person interviews. That they're learning more. They're reading five other student's papers. They're getting five other perspectives. They're saying, hey I didn't think about that. Or even, hey they're all wrong here. My paper was much better than theirs. But again that doesn't necessarily matter when we start running the ranks. And we're getting much better, much better grading, which is hard to quantify, but the folks that are on the academic team that are doing that, have some really great data. With the data. Yup, mm-hm. >> David, one of the themes we keep hearing in this show is about transformation. Is change happening? You're talking about IT, how it's working with the business more and more. Bring us inside university life in general and specifically. You work with one of the ancient eight. How does cutting edge technology fit in with - >> That's really interesting. I do have a couple thoughts on that. My boss has a picture in his office, of a Penn classroom from I think it's like 1908 or 1910. And there's literally a bunch of students sitting around. There's a faculty member standing up. And there's a candle-powered projector, which I didn't know is a thing but it's in the picture, projecting an image onto the wall. From over 100 years ago. What's different about our classrooms today? Everything's the same, except the projector's now in LED. Or a L3D projector. We still got people sitting around the room, standing up. I think what we're seeing now in probably the previous ten years from now and to the next ten years is education's probably going to change more in those 20 years than it has in 2,000 years since Socrates was standing around with a stone tablet or whatever they were doing. Things like globalization, online courses, the MOOC space, where Wharton is huge in the MOOC space. Wharton online programs. Where students can take, not even students, anybody! If you're in China or Africa or South America. You can take an introduction to Wharton, introduction to marketing class from a Wharton professor for free. I mean we're a business school. We sell some of that content as well. But you can get verified certificates. We're seeing a lot of stuff change. The students today expect more. We can get into, we won't though, we can get into the whole millennial issue and short attention span and all that kind of stuff. Students today expect their faculty to be technology savvy. They expect content to be online. They expect to use devices. The expect to use... We got tablets, and laptops and phones. They want to be able to consume this content on multiple devices. We're seeing significant transformations in education. Which is, hasn't necessarily changed much in 2,000 years. Or even 200 years, right? So there's that. Speaking specifically about Wharton, one of the things I really thought is interesting, is I've been there 13 years now. When I first started working there, I'm going to make some generalizations here, a lot of our student wanted to go work in iBanking. They wanted to go work for the big banks. They wanted to go work for Goldman Sachs and things like that. In the last five, seven, ten years ago. They wanted to create their own company. Start up their own company. Be entrepreneurial. Have their app. Have their their big idea. Start the next whatever dot com. And be successful that way. Now in the last two or three, four years. We're seeing a lot of our students analytics. We're putting analytics with everything. Companies, businesses, organizations, no matter what you are, we have huge amounts of data available. How can we make meaningful decisions based on that data? Our dean. I guess I can't call him our new dean. He's been there three or four years at this point. Really wants to position Wharton as the analytics school. Every company in the world is trying to hire these kinds of people. There just frankly aren't enough of them out there. The thing we're trying to teach our students is, or one of the many things, is how to analyze data. How to make meaningful decisions based on that data. And of course when you have more data, you need more storage. You need more infrastructure. You need more processing. All the stuff that you know, Dell and Nutanix are providing us, with their hyper convergence infrastructure. Their cloud offerings. Whether private cloud, public cloud, hybrid cloud. All that kind of stuff is... Positioning us as the analytics school requires a significant amount of technology on the backend. And again working with our trusted partners like Dell and Nutanix we can provide that seamlessly in the backend. They don't necessarily know, is it in our data center? Is it in the cloud? And they don't care. They shouldn't care. But as they're collecting huge amounts of data, running these reports, and creating it, and going back to creating these algorithms that do incredible things. And these secret sauces. We need the infrastructure to run that kind of stuff. That's I think one of the greatest things that Wharton Computing provides the Wharton School of Business, and their business, which is creating and disseminating knowledge. >> David, I think you've encapsulated something that I've been hearing from lot's of users over the last year or so. The vendors sometimes, it's private, it's hybrid, it's public. From the user standpoint it's like, no well we have a cloud strategy that we're working on. Can you bring us inside a little bit? How did you get to where you are today? How do you choose who you're partnering with? What leads to some of those decisions? >> I love the word partner. I hate the word vendor. One of the great things about working at Wharton is, is we get to have these awesome partners. I want someone... When we're going to make an IT spend, we want someone who cares about our business. We don't want somebody who just, will come in, give you a dog and pony show, write us a check. And when you want more stuff call us. We want folks that are going to provide the support. You know, pre-sales during installation. Post-sales when they're coming out with new features. We want them to be invested in what we do. I can truly say that Nutanix is a fantastic partner of ours. Dell-Nutanix are great partners. Dell is a great partner of Wharton and Penn as well. That's what we really look for, is someone who is willing to invest their time, their smart people. Tell us about the new features and functionality that are coming out. Call on us and say, hey how are thing going? It's not just the little things. But those little things really mean a lot to us as we're picking an IT partner. Because when you're working for the best business school in the world. Having the best students, the brightest faculty, the best, hardest working staff. We want to provide them a very, very high quality IT support. We need high quality partners. And not just vendors who care about the transaction. That's really the bottom line for us. When we're choosing our partners. >> When you were talking about analytics, and Wharton being the school of data analytics. What are your measuring sticks? In terms of what are you looking at? You're talking about four very separate groups of constituencies. What are you doing to evaluate your performance? And what's critical? >> I think it all comes down to, what do our business units think about us? We're a service organization. Almost all IT shops are. If the business units aren't successful, they don't need an IT department. If we're not providing them high quality IT services, we're not going to get the best faculty. We're not going to get the brightest students. We're not going to get the alumni engagement. They want to be wowed by their IT support. That's a big part of my job, is providing that quality of support. Helping train. Technology breaks, right? How do you deal with the problem? Nobody runs at rock solid 100% infrastructure. Murphy's Law always comes into play. Problems always happen. How do you deal with the cracks in the armor as they come off? I think that's what our business units want. I think we're fortunate that we're computing. Our team, our staff, our CIO. My colleagues, my peers, my team. Our team, right? They're very well thought of, hopefully, by our clients. And that's how we're measured is by their success. We want to help them, empower them to do their job at the highest level. We are playing in pretty rare air, when it comes to the faculty, staff, students and alumni, that we attract to Penn and Wharton. We want to keep doing that. One of the things I love best, and I tell our wonderful faculty when we meet with them, is don't tell me we did a great job. Here's what I want you to tell me. I want you to say, three years ago I was at, I'm not going to name drop schools, but I was at this school and I asked them to do this thing, that you said, sure, no problem to. And they couldn't do it, wouldn't do it, didn't have the ability, the infrastructure in place to do that. But you guys with a smile on your face just made it happen. Stuff like WHOOPPEE. Stuff like the analytics stuff. All the, tying it back to why we're here today, is our partners and our technology partners that help us provide scalable, flexible solutions. That's how we're measured. >> Higher learning. >> Higher learning, absolutely. >> David, thanks for being with us. >> No problem, it was great. >> David Comroe from the Wharton School of Business, University of Pennsylvania. Back with more live coverage here from Dell Technologies World 2018. Right after this break. You're watching theCUBE.

Published Date : May 2 2018

SUMMARY :

Brought to you by Dell EMC, David is the Senior Director of Client Technology Services Glad to be here. for the largest business school faculty in the world. and all the buzzwords. One of the cool things, You're putting me on the spot with this one. You actually, the students have to read the paper, And the data we've seen is, David, one of the themes we keep hearing in this show We need the infrastructure to run that kind of stuff. over the last year or so. One of the great things about working at Wharton is, and Wharton being the school of data analytics. One of the things I love best, David Comroe from the Wharton School of Business,

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Neil and John Chambers Correct Title


 

>>I'm really glad to have you with us today, john, I know you stepped out of vacation so thanks very much for joining us. >>No, it's great to be joining you from Hawaii and I love the partnership with H. P. E. And the way you're reinventing an industry, >>well, you've always excelled john at catching market transitions and there are so many transitions and paradigm shifts happening in the market and text specifically right now as you see, companies rush to accelerate their transformation. What do you see as the keys to success? >>Well, I, I think you're seeing actually an acceleration following the covid challenges that always faced and I wasn't sure that would happen. It's, it's probably at three times the paces before. There was a discussion point about how quickly the companies need to go digital. Uh, that's no longer discussion point. Almost all companies are moving with tremendous speed on digital and its ability as the cloud moves to the edge with compute and security uh, at the edge and how you deliver these services to where the majority of applications uh reside are going to determine. I think the future of the next generation company leadership and it's the area that Neil we're working together on in many, many ways. So I think it's about innovation. It's about the cloud moving to the edge and an architectural play with silicon to speed up that innovation. >>Yes, we certainly see the our customers of all sizes trying to accelerate what's next and get that digital transformation moving even faster as a result of the environment the world living in. And we're finding that workload focus is really key customers and all kinds of different scales are having to adapt and support the remote workforces with beady eye. And as you say, john they're having to deal with the deployment of workloads at the edge, with so much data getting generated at the edge and being acted upon on the edge. The analytics and the infrastructure to manage that as these processes get digitized and automated is so important for so many workflows. We really believe that the choice of infrastructure partner that underpins those transformations really matters. A partner that can help create the financial capacity that can help optimize your environments and enable our customers to focus on supporting their business are all super key to success. And you mentioned that in the last year there's been a lot of rapid course correction for all of us, a demand for velocity and the ability to deployed resources. That scale is more and more needed, maybe more than ever. What are you hearing customers looking for as they are rolling out their digital transformation efforts? >>Well, I think they're being realistic that they're going to have to move a lot faster than before and they're also realistic on core versus context. Their their their core capability is not the technology themselves, it's how to deploy it and there were looking for partners that can help bring them there together, but there can also innovate. And very often the leaders who might have been a leader in a prior generation may not be on this next move. Hence the opportunity for HP and startups like Monsanto to work together as the cloud moves to the edge and perhaps really balanced or even challenge some of the big, big incumbents in this category as well as partners uniquely with our joint customers on how do we achieve their business goals? Tell me a little bit more about how you move from this being a technology position in for a J e to literally helping your customers achieve their outcomes they want and and how are you changing hb in that way? >>Well, I think when you consider these transformations the infrastructure that you choose to underpin, it is incredibly critical. Our customers need a software defined management plane that enables them to automate so much of their infrastructure. They need to be able to take faster action where the data is and to do all of this in a cloud like experience where they can deliver their infrastructure as code anywhere from exa scale through the enterprise data center to the edge. And really critically, they have to be able to do this securely, which becomes an ever increasing challenge and doing it at the right economics relative to the alternatives. And part of the right economics, of course includes adopting the best practices from web scale architectures and bringing them to the heart of the enterprise. And in our partnership with Pensando, we're working to enable these new ideas of Web scale architecture and fleet management for the enterprise at scale. >>You know, what is fun is HP has an unusual talent from the very beginning Silicon Valley of working together with others and creating a win win innovation approach. If you watch what your team has been able to do. And I want to say this for everybody listening, you work with startups better than any other company I've seen in terms of how you do win win together and pennsylvania is just the example of that. Uh this startup, which by the way, is the ninth time I have done with this team, a new generation of products and we're designing that together with H. P. E. In terms of as the cloud moves to the edge, how do we get the leverage out of that and produce results for your customers on this? Uh, to give the audience appeal for it. You're talking with Manzano alone in terms of the efficiency versus an amazon amazon web services of an order of magnitude. I'm not talking 100% grader, I'm talking 10 X grader and things went through, Put number of connections, you do the jitter capability, etcetera. And it talks how to companies uniquely who believe in innovation and trust with each other and have very similar cultures can work uniquely together on it. How do you bring that to life with an H. B? How do you get your company to really say that's harvest the advantages of your ecosystem in your advantages of startups? >>Well, you say more and more companies are faced with these challenges of hitting the right economics for the infrastructure. And we see many enterprises of various sizes trying to come to terms with infrastructures that look a lot more like a service provider that require that software defined management plane and the automation to deploy at scale. And with the world we're doing with Pensando, the benefits that we bring in terms of the observe ability and the telemetry and the encryption and the distributed network functions. But also a security architecture that enables that efficiency on the individual nodes is just so key to building a competitive architecture moving forwards for an on prem private cloud or internal service provider operation. And we're really excited about the work we've done to bring that technology across our portfolio and bring that to our customers so that they can achieve those kind of economics and capabilities and go focus on their own transformations rather than building and running the infrastructure themselves. Artisanal e and having to deal with integrating all of that great technology themselves >>makes tremendous sense. You know, Neil you and I work on a board together etcetera. I've watched your summarization skills and I always like to ask a question after you do a quick summary like this, what are the three or four takeaways we would like for the audience to get out of our conversation? >>Well, that's a great question. Thanks john we believe that customers need a trusted partner to work through these digital transformations that are facing them and confront the challenge of the time that the covid crisis has taken away. As you set out front, every organizations having to transform and transform more quickly and more digitally. I'm working with a trusted partner with the expertise that only comes from decades of experience is a key enabler for that, a partner with the ability to create the financial capacity to transform the workload expertise to get more from the infrastructure and optimize the environment so that you can focus on your own business, a partner that can deliver the systems and the security and the automation that makes it easily deployable and manageable anywhere you need them at any scale, whether the edge, the enterprise data center or all the way up to exa scale in high performance computing and can do that all as a service as we can at H P E through H PE Green Lake enabling our customers most critical workloads. It's critical that all of that is underpinned by an A I powered, digitally enabled service experience so that our customers can get on with their transformation and running their business instead of dealing with their infrastructure. And really only H PE can provide this combination of capabilities and we're excited and committed to helping our customers accelerate what's next for their businesses >>Neil. It's fun. I love being your partner and your wingman or values and cultures are so similar. Thanks for letting me be a part of this discussion today. >>Thanks for being with us, john, it was great avenue here. >>Oh, his friends were like.

Published Date : Apr 23 2021

SUMMARY :

No, it's great to be joining you from Hawaii and I love the partnership with H. P. E. and paradigm shifts happening in the market and text specifically right now as you see, and its ability as the cloud moves to the edge with compute and security The analytics and the infrastructure to manage that as these processes get digitized Well, I think they're being realistic that they're going to have to move a lot faster than before and they're also increasing challenge and doing it at the right economics relative to the alternatives. H. P. E. In terms of as the cloud moves to the edge, how do we get the leverage out of that and produce that software defined management plane and the automation to deploy at scale. You know, Neil you and I work on a board together etcetera. and the security and the automation that makes it easily deployable and manageable anywhere you Thanks for letting me be a part of this discussion today.

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Aarthi Raju & Rima Olinger, AWS | AWS re:Invent 2020 Partner Network Day


 

(bright music) >> Announcer: From around the globe, it's theCUBE, with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Global Partner Network. >> Okay, welcome back everyone to theCUBE Virtual Experience here for re:Invent coverage 2020 virtual. Normally we're in person doing interviews face to face, but we're remote this year because of the pandemic. We're here for the APN partner experience, kickoff coverage with two great guests, Rima Olinger, of global lead for VMware cloud on AWS. And Aarthi Raju, Senior Manager Solutions Architecture for Amazon Web Services. Thanks for coming on, appreciate it. >> Good to be with you John, thank you. >> So I got, want to get it out there this partner network experience, it's really about the ecosystem. And VMware has been one of the biggest success stories. They've been around for a long time, and not one of the earliest ecosystem partners, but a big success. 2016, when that announcement happened, a lot of people were like, whoa, we VMware is giving into Amazon. And Amazon was like, no, that's not how it works. So turns out everyone was been proven wrong, it's been hugely successful beneficial to both. What's the momentum, share an update this year on the AWS VMware momentum. >> So John, as you know, we're into our third anniversary, and the relationship cannot be any stronger. We see customers are leaning into the service very heavily. We see great adoption across multiple industries. As some data points for you, if we look at October of this year to October prior year, we're seeing the number of active nodes, or the number of consuming host and active VMS, nearly doubled year over year. we also continue to see greater partner interest in the solution, we have over 300 ISVs that have validated the services on VMC. And we see over 600 plus partners that continue to take the competencies and build practices around it. So the momentum is very strong, for years still today. >> One of the comments I made when the naysayers were like kind of pooh-poohing the deal, I was like, no, no, the cloud growth is going to be a factor at that time, then, the trendy thing was software's eating the world, was a big trend there. If you look at the growth of cloud scale, and software innovation, and the operating side of it, 'cause VMware runs IT, they let operators running IT. There's no conflict because Amazon's growing and now the operator roles growing and changing. So you have two dynamics going on. I think this is a really nuanced point for the VMware, AWS relationship around, how they both fit together. Because it's a win win better together scenario, and it is on AWS, which is a distinction. Can you guys share your reaction to kind of that dynamic of operating software at scale, and how this translates for customers? >> Absolutely, we see a lot of benefits that this service is bringing to the customers. Because what it's doing is providing them with this consistent infrastructure and operations across hybrid cloud environments. And in this way, they have the choice of where to place their applications on-prem or in the cloud, specifically. And this is one of the reasons why AWS is a VMware's preferred cloud provider for all vSphere workloads. We see the customers gravitate towards it and be receptive to it specifically because they say I accelerate my path towards migrating and modernizing my application. It provides me with consistent as I mentioned, operations and infrastructure. And it also helps them with factoring, and helps us scale their business and very fast, very seamless fashion. Aarthi what is your perspective, maybe additional things. >> Yeah. >> Yeah, from a technical innovation perspective, the momentum, John has been very strong, especially, listening to what customers have been asking us the past couple of years. 2020 has been a big year for us in terms of launching some giant innovations. A couple of things to call out is, we launched the VMware Transit Connect. This was announced during VMworld this year and customers have been telling us, hey, we are migrating workloads from on premises to the cloud, we need a simplified way of connecting all these resources on-prem resources, resources on VMware cloud on AWS, and their AWS native resources as well. So, the VMware Transit Connect, uses the AWS transit gateway that we launched at re:Invent two years back to provide that simplified connectivity model for our customers. The next big thing this year was, we introduced a new instance type i3en.metal, So customers have been telling us they want denser nodes for especially storage heavy workload. So we launched this i3en, that comes with approximately, like 45 terabytes of storage per node. So that's a lot of storage for individual nodes. So customers have been taking advantage of these dense nodes as well. There was other areas that we kind of focused on from a lower entry point for our customers. When we initially started the service, John, you know that we had, the minimum entry point as four nodes, we've scaled that down to three, and now we've come to two nodes, giving the same production SLA for customers. The other big launch this year was the acquisition of Datrium by VMware and how we introduce the VMware cloud disaster recovery. Datrium uses the eight native AWS services like S3 and EC2, providing customers this low cost TR options. We're talking about the APN here and for partners, we launched the VMware cloud Director Service, which delivers multi-tenancy to our managed service providers, so that they can cater to small, to medium sized enterprises. >> What are some of the other use cases that are the key in these migrations, because this becomes a big benefit we're hearing, certainly, during the partner day, here at re:Invent, is, migration, cloud SaaSification, getting to a SaaS, but not losing the business model. Either was on premises or born in the cloud, this done new operating models, the key thing, what are some of the key use cases for partners? >> The most widely adopted use case that John, which you rightfully touched on, is really the cloud migration. We see around 41% of customers use the service just for cloud migrations. Now, this could be an application migration, like SAP, SQL server or Oracle Applications, or it could be a complete data center evacuation. And we see that with some customers who have a cloud mandate, or they have refresh cycles that are coming up, or maybe they're in a colo, and they're not happy with their SLA. I could use the example of William Hill, is one of the customers largest betting and gaming companies that are in the UK. And what's the use case was, a combination of a data center extension as well as a capacity expansion specifically. And what William Hill was able to do is, move 800 on-premise servers, and they decommission them in the first 12 months. And they also migrated 3000 VM. So that is cloud migrations is a big use case. The second big use case, as I mentioned earlier, is the data center extension that includes also VDI, the combination of both is around 42% of the use cases, with around 26%, I would say for data center extension and 16% for VDI. Why, customers want to expand their footprint, they want to go to a new region, and they want to meet on demand, cyclical capacity needs, or sometimes temporary needs for some events or some seasonal spikes. So we see that as a second big use case. A third one equally important, tend to be disaster recovery. Now, this is either to augment an existing DR. Replace a DR that is already in place, or start a new DR, and that constitutes around 17% of the use cases that we see. Because customers want to reduce their DR, avert some cost by moving to the cloud. And one example that comes to mind is Pennsylvania Lumbers Men's Mutual Insurance, it was a DR use Case. They worked with an external storage partner of ours faction in order to put that in place. So overall a great use cases across the board. And I know a big one is application modernization, Aarthi, I know you work with your teams on that, if there's any feedback from you on that. >> Yeah, the next generation applications or application modernization comes a lot. We talk to like AWS customers who are migrating from on-premises to the cloud using VMware cloud on AWS. And three or four years back as we were building the service and architecting, one thing was very evident, like we wanted to make sure that as we were building the service, we wanted to ensure that customers can take advantage of the native AWS services. We've got 175 plus services and new services launching at re:Invent, So we wanted to make sure that there is this, seamless mechanism and seamless path for customers to modernize using native AWS services. So what we've done as part of like onboarding for customers and as customers built on VMware cloud on AWS, is provide them both the network path and data path. So they can as your into the same availability zone or region, they're like, hey, I can use S3 for backups. I can use EFS, for file shares, etcetera. So we're seeing a wide range of next generation application use cases that customers are building on. >> Why would I get at the reasons why customers are continuing to adopt VMware cloud on AWS? Can you guys share an update, I'll show you the obvious reasons, the beginning was nice strategy for VMware, it's proven to be clear. But where's the innovation coming from? What's the key drivers for the adoption of VMware cloud on AWS? >> So one of the key patterns that we are seeing is, customers who used to be risk averse, customers will be invested a lot in VMware. And at the point, they did not want to move their workloads or applications to the cloud because of the risk involved, or sometimes they didn't want to refactor, or they were worried about the investment in tools, resources, they tend to gravitate towards this solution. The fact that you could provide your customers with this consistent infrastructure and operations across on premise, as well as on the cloud environment. The fact that you do not need to do an application refactoring. You could optimize your workload placement, based on your business needs, you could move your workloads bidirectionally, you could either leave it on-prem, or move it to the cloud, and vice versa. We've also noticed that there is a lower TCO associated with the use of the service. We know from a study that VMware commissioned Forrester in 2019, for that study, that 59%, there is a recurring savings in terms of infrastructure, and operational savings that is related to that. Customers tell us that, this consistency in infrastructure is translating it, into zero refactoring. This consistency in operations, is leading them to use their existing skill sets. And with the ability to relocate the workload skill into the environment that best suits them, that is providing customers with maximum flexibility. So I would say it is delivering on the promise of accelerating the migration and the modernization of our customers applications so that they can continue to respond to their business needs and continue to be competitive in the marketplace. >> Aarthi I want you to weigh in and get reaction to that. Because again, I've talked publicly and also privately with Ragu, for instance, at VMware, when this was all going down. It's a joint integration, so there's a lot of things going on under the hood that are important, what are the most important things that people should pay attention to around this partnership? Could you share your opinion? >> Yeah, sure, John. So one of the most common questions that we get from customers is, hey, this is giant integration, we can take use of make use of native AWS services, but what are some of the use cases that we should be targeting, right? As we talk to customers, some of the common use cases to think about is, it also depends on the audience. Remember, admin scoring example, who might not be familiar with the AWS side of services, they can start with something simple like backing up. So S3, which is our simple storage service, we see that use case way more often with our VMware cloud on AWS customers. This also ties with that Datrium integration that I talked about with the VCD or the VMware cloud disaster recovery, providing that low cost TR option. We are also starting to see customers offload database management, for example, with Amazon RDS, and taking advantage of the manage database service. As we talk to more customers, some of the use cases that comes up are like, hey, how do I build this data lake architecture? I've migrated to the cloud, I want to make use of the data that I have in the cloud now, how do I build my data lake architecture or perform analytics or build this operation resiliency across both these environments, their VMware cloud on AWS, as well as their native AWS environments? So we've got that seamless connectivity that they can take advantage of with VMware Transit Connect, we've got the cross account ENI model that we built, that they can take advantage of. And he talks about this one, and talks about the security is always job zero for us. And we're also seeing customers that take advantage of the AWS services like the web application firewall or shield, and integrating it with the VMware cloud on AWS environment. And that provides a seamless access right? You now have all these security services that AWS provides, that allows you to build a secure environment on VMware cloud on AWS. So providing customers the choice has always been a priority, right? We're talking about like infrastructure level services. As we move up the stack, and as customers are going through this modernization journey, like VMware provides containerization option using VMware Tanzu, that came out at VMworld. And then they also have the native options, we provide a EKS, which is our Kubernetes as a managed service. And then we also have other services that enables customers to take that jump into that modernization journey. One customer we've been working very recently with is PennyMac. They migrated their VDI infrastructure into VMware cloud on AWS. And that's allowed them to scale their environment for the remote workers. But what they are doing as part of their modernization journey, is now we're helping them build this completely serverless architecture, using Lambda on the AWS cloud. >> Yeah, that's really where they see that, the value is high level services, the old expression prima, they use the hockey from Wayne Gretzky skate to where the puck is going to be, or, get to where the ball will be in the field. This is kind of what's happening, and I'm kind of smiling, when Aarthi was talking because, I've been saying it's been, going to, IT operations, and IT serviceman's is going to change radically so years ago. But you're really talking about here is the operating side of IT coming together with cloud. VMware, I think is a leading indicator of, you still got to operate IT, you still got to operate stuff. Software needs to be operated apps need to be operated. So this new operating model is being shown here with cloud, this is the theme with and without IT. With automation, this is the big trend from re:Invent this year. Obviously AI machine learning, you still got to operate the stuff. It's IT, depends on, we got lammed in automation doesn't go away, the game is still the same, isn't it what's happening here? >> Absolutely, so what we're saying is, once there's that you're absolutely right about the fact that they needed to, worry about the operations, once they migrate their workloads, they're taking their data, they're saying, how do I make sure that I put in place operational excellence, and this is where, AWS comes in, and we provide them with the tools needed to do that. And then step number two, say, what can I do with this data? How do I translate it into a business benefit? And this is where the AI ML tools come in place, and so forth. And then the third step, which is all right, what can I do to modernize these applications further. So you're spot on, John, in saying that this is like a transformation, it is no longer a discussion about, migration anymore, it is more of a discussion about modernizing what you have in place. And this is, again, where this brilliancy between the collaboration, between VMware and AWS, is bringing to the table, sets of tools and framework for customers, whether it's security framework or networking framework, to make the pieces fit together. So I'm very excited about this partnership. And we continue to innovate, as you heard in prior discussions with our executives on behalf of our customers, we spoke about the RDS Amazon, relational database service on vSphere. We spoke about how to post on VMware cloud on AWS, to bring the cloud to the customers data center for specific needs that they have in spite. And we're not stopping here. We are continuing not to make more joint engineering and more announcements, hopefully in the future to come. >> That's great insight. And a lot of people who were commenting, three, four years ago, when this is all going down, they're on the wrong side of history, that the data is undeniable, refutable, it's a success. Aarthi give us the final word, modern applications, modern infrastructure, what does that mean, these days? What's the bottom line when you talk to people out there? When you're at a party or friends or on zoom, or a Jime, in conference? What do you tell people when they say, what's a modern application infrastructure look like? >> Yes, the word modern application, the good or bad thing is it's going to, what I said yesterday could be different from what I'm saying today. But in general, I think modern application is where we enable our customers to focus more on their business priorities using our services, versus worrying about the infrastructure or worrying about like, hey, should I be worrying about capacity? Should I be worrying about my operational needs or monitoring? I think we want to abstract all that. We want to take that heavy lifting off of customers and help them focus on their business. >> Horizontally scalable and leveraging software in the application, can't go wrong with that formula in the cloud. Thanks for coming on, and thanks for the awesome conversation. Thanks for coming on. >> Thank you John. >> Thank you >> Okay, it's theCUBE Virtual for re:Invent Experience 2020, this is virtual, not in person this year. I'm John Furrier, your host from the theCUBE, thanks for watching. (bright music)

Published Date : Dec 3 2020

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Guy Bartram, VMware and Doug Lieberman, Dell Technologies | Dell Technologies World 2020


 

>> Narrator: From around the globe, it's theCUBE with digital coverage of Dell Technologies World Digital Experience brought to you by Dell Technologies. >> Hi welcome back everybody, Jeff Frick here with theCUBE coming to you from our Palo Alto studios, with our ongoing coverage of the Dell Technology World 2020, the digital experience, we can't be together this year, but we can still get together this way. And we're excited for our very next segment, really talking about one of the big leverage points that the Dell VMware relationship can result in, so we're excited. Joining us our next guest is Guy Bartram, he is the Director of Product Marketing for Cloud Director, for VMware. Guy great to see you, where are you coming in from? >> Thanks for having me on Jeff. >> Where are you coming in from today? (Guy chuckles) >> So this yeah, this London for me, this is from London. >> Excellent, great to see you. >> In the UK. >> And also joining us, Doug Lieberman, he is the Global Solutions Director for Dell Technology, Doug, great to see you, where are you coming in from today? >> Well, thanks for having me, I'm calling in from just outside of Philadelphia, Pennsylvania in the United States. >> Excellent, love Philly's lived there for a couple of years and man, there's some terrific food in that part of the world, I tell yah. So let's get into--- >> You say--- >> Are you Pat's or Geno's. >> Actually I'll eat either one but I think I prefer Pat. >> Okay buddy, I used to get one of each and eat half and half and piss people off that were the purest, but that's a difference--- >> That's the right way to do it. (Jeff and Guy laughs) >> Right, so let's get into it, you know, before we turned on the cameras, you guys were talking about this exciting announcement that you've been working on for a really long time. So before we get kind of into the depths and the importance, why don't we just go ahead and tell us, what is the big announcement that we're sharing today? Go to you Guy. >> And so VMware and Dell really have worked together and we both have partner programs that are focused on service providers, Cloud Service providers, and systems integrators and strategic outsourcers. And what we've done is work together to build a solution that is really targeted towards them in the cloud arena, so taking our cloud capabilities and solutions and optimizing it for cloud providers and doing that through what we call, leveraging our Dell Technologies Cloud Platform and putting VMware Cloud Director on top of that. >> So that's pretty amazing, and really, to you Guy, what does that enable Cloud Service providers to do that they couldn't do so well before? >> It brings a whole lot of benefits to a Cloud Service provider, I mean, for cloud providers, historically they've had to have infrastructure services that've been, you know, quite heavy for them to build, taken a long time to get the market, and really had a high burn and operational costs and this solution VMware Cloud Director on Dell Technologies Cloud Platform is going to bring them the multitenancy aspects of cloud director and all of the speed and efficiencies in application and infrastructure delivery to enable them to address the common need now around hybrid cloud management and hybrid cloud operations. >> And you talked about before, I'm sorry, go ahead, Doug. >> No, I was saying, you know, I think that the big key piece is that, there're special requirements that cloud providers really need from their infrastructure, from their cloud, that makes it special to their business model, and what this aims to do, is to provide those capabilities in a easily consumable and rapid implementation format so that they can get to revenue faster and they can get to higher level services faster. >> It's funny, you talked about getting to revenue faster, back in the day I worked at Intel and Craig Barrett was famous for TTM. TTM, everyone used to think it was time to market bringing a new product to market, and he said, no, no, no, it's time to money, right, how fast can you get operational, so that you can basically get this thing to start generating revenue, I always think of that when you look at seven 37 sitting at a gate, you know, how do you get it operational? So Doug, what were some of those special challenges that they have in their market and how are you helping them solve them? >> So it's a great question, Jeff, as we work with service providers all over the world, they've given us a consistent message, that the days of the value in their service being, how they build the underlying cloud and how they do that orchestration automation are really behind us, right, they're expecting today, an end to end capability delivered as sort of an appliance for that underlying infrastructure for the cloud components, so that they can focus on the higher level services and the things that provide more value and more margin for them, and so, you know, the as a service offerings that run on top of the underlying cloud. And so what this joint solution does is really provide a validated design so that they can redirect their engineering resources from figuring out how to make that base cloud work in a service provider format, with multitenancy, chargeback, showback, portals, et cetera, and get that up and running faster and not have to worry about how to automate all that themselves, so they can focus their engineering efforts on those higher level services that provide greater value to their bottom line, to be honest, >> Great, that's great, and Guy, I want to go back to you, you know, the Cloud Service providers probably don't get as much of publicity as you know, we hear all the time about the big public Cloud Providers, you know, the big three or four or however you want to count them and we hear a lot about data centers and staff migrating between those two, we don't hear a lot of conversation in kind of the hybrid or the multicloud discussion about the role of the smaller Cloud Service providers. So I wonder if you can share a little bit about how they play in the market, you know why this is a really important segment for everyone's, you know, kind of architecture and ability to deliver applications. >> That's great common, I mean, one of the things we tend to call on our partners internally is the fall of mega cloud, that you know you really haven't heard of, there's 4,000 partners in our partner program and all of them are providing very valuable cloud services. They provide cloud services they've in all areas of cloud, so this could be into Azure, Google, AWS or in their own data centers, and many of them have come from infrastructure rich environments or what we call asset heavy environments and delivering services in these environments. The recent kind of drive to cloud adoption and digital transformation has meant that there's been a growing demand for Cloud Service providers to deliver valuable managed services and professional services to help customer do that digital transformation and really help the customer identify, where their customer's workloads, would be best apt and running. And, you know, cloud providers specialize in delivering these services like Doug was saying, they're looking at that higher value and they brought a lot of skills and capability in those areas. >> That's great, 'cause it's really good to keep in mind they pay a really important role in this whole thing. And Doug I want to go back to you in terms of working together with VMware in the solution space, right, so it's one thing to talk about a relationship between two companies, it's one thing to see Michael Dell and Pat Gelsinger on stage together, it's a whole nother deal to get together and put in the investment in these joint solutions. So I wonder if you could share a little bit more color on not only today's announcement, but what this really means for you guys going forward and more importantly, your customers, and ultimately your customer's customers. >> Absolutely, so Dell and VMware are both committed to really driving the success of our Cloud Provider partners all over the world, and to do that, we recognize that there's an additional level of capabilities that we need to bring together and jointly do that. And so we agreed to work together to go build a series of capabilities that are really targeted at going beyond just the basic HCI market and the basic cloud market and extending that for capabilities that are targeted specifically and built specifically for our service providers. And so this solution that we're announcing today is the first step on a journey, but we both committed to and made investments in, continuing that and adding more and more capabilities as we move forward and really addressing that very specific market. And working with our Cloud Service provider partners to figure out what is the next step, what do they need from us, at the end of the day, we're looking to jointly help them be more successful and accelerate their time to market and their go to market capabilities. >> Right, that's great, and Guy back to you, you actually had some numbers, some IDC numbers that you can share in terms of some of the real measurable benefits of this. >> That's right Jeff, yeah, we have, IDC did a recent analysis for us with about 12 partners interviewed across the globe, and some of the results that came back were pretty astounding actually, this pay-for is available on our VCE product page on vmware.com. But just as kind of summarize, you know, we talk about getting to revenue faster, they found that on average service providers were able to onboard customers, i.e migrate them, into their cloud environment around 72% faster, 57% faster delivery of new services and we all know that, you know, portfolio and construction of services takes a long time, but you get business units to buy in to give it support services, so 57% faster delivery of services is incredible. And then, you know, obviously getting to revenue 32% more revenue from VCD services than without VCD and 51% overall more growth with VCD from things like more efficient operations, which are also marked at like 31%. So, you know, significant advantages to having Cloud Director bringing those economies of scale, bringing that capability to migrate from a customer premise into service providers cloud, and then obviously be able to utilize multiple larger clouds across multiple regions. >> That's great, and Doug, I wonder if you could share, are there some specific applications that are driving this more than others, is there any particular kind of subset of the solutions that you can highlight where you're getting the most demand and where you see kind of the both short term opportunity as well as mid and longterm opportunity? >> A great question, I think it really evolves around a couple of different aspects. So one is from a pure security standpoint and things like data sovereignty, we're seeing an increased demand for the service providers that are our partners, as in the ecosystem of cloud, there will always be a role for the hyperscaler clouds as well as the role of these independent Cloud Service providers that are at the next tier down, both for the data sovereignty issues, things like GDPR, but as well as kind of that personal feel, that personal touch and specialty in applications, some of the specific areas we're seeing are things like business process management capabilities, database as a service, VDI as a service, but even more critically things like cyber recovery and backup as a service we're seeing, especially in the current situation that we're in, really an uptick in the cyber attacks and the ransomware, et cetera, and so solutions such as our cyber recovery are critical in those capabilities and those higher level services tied into and integrated with an overall service provider framework are key. And so in the area that we're really seeing uptake are really the business critical mission functions that enterprises are looking to run in a trusted partner's data center, and that's what we're seeing, where we're a lot of traction for this Dell Technologies Cloud Platform, combining VCD and VCF together to give you all those features and enterprise reliability. >> Right, and I didn't ask you Guy kind of the partnership question about having the opportunity to put your capability, you know, on the Dell Cloud Platform, opens up a whole new set of field resources, a whole new set of technical resources, you know, a whole different resources, not that VMware's short on resources by any stretch of the imagination, but it's certainly an additive, you know, kind of one plus one makes three opportunity. >> Yeah, I mean, it's great to be doing this and we've actually already been doing this on a couple of other initiatives, so from my perspective, I, you know, I manage Cloud Director Portfolio and we've already integrated Dell, Data Domain Dell, Avamar backup solutions, Data Protection Suite, into VCD as self service and we've already put in quite a bit of work, working together with Dell on that, as we go forward we're going to be putting more work into supporting VCD on the Dell Technologies Cloud Platform and integrating more services from Dell and from other vendors into the solution as well. So all we want to really provide is the capability for service provider to have the easy to consume hardware model, easy to consume subscription software model, with our program, and then the extensibility of services over and above just the infrastructure layer. So looking at things like object storage, and as Doug said, data protection, migration services, container cluster services, there's a myriad of services that VCD provides today out the box, and then there's the a whole extensibility framework, which we use when we work with partners, like we've done with Dell to deliver things like data protection. >> Yeah, I want to go back to you Doug, in terms of kind of a higher level, this whole transition to as a service, you've been in the business for a long time, you've been in the solutions a long time, but, you know, switching everything to as a service, as often as we can, and as frequently as we can, and as broadly across portfolio is really a terrific response to what the customers now, are looking for. So I'm wondering if you share some color on, you know, this philosophy of trying to get to, as a service, as much as you can, across the broadest solution set as you can. >> Yeah and if you look over the last decade, and decade and a half, there has been this increasing trend to moving to as a service offerings and the public clouds really drove a large part of that, than in tier two service providers around the globe. The key piece especially in the current business model, then going forward is how do you optimize, your CapEx versus OPEX and how do you really leverage the IT infrastructure to the maximum extent possible, based upon current business conditions, and that means the ability to grow and train and the ability to only consume what you need. In the past, when we had traditional data centers, you basically built for the worst case, and so the worst case was you had, an accounting run that happened at the end of the month that required a lot of processing power, then you built to that and that's what you use, and for the rest of the month, it really mostly idle. The cloud model really gives you the ability to A, improve their, or only use what you need and consume when you want to use it, but also adds in really shifting the responsibility for the management and the operations into someone, people who are experts in that area, so that again, you as a business can focus on your mission critical aspects of what you do whether that's developing a drug, building cars, making pizza, whatever it is, really as a service model enables your business to drive their core competency and not have to worry about the IT infrastructure that other people can do more efficiently and with better value than you could do it internally. And all that drive to that as a service model with the additional financial models that really aligned to the business paradigm that really companies are looking for. >> As you're saying that I'm thinking, wow, remember those days when our worst case scenario, was running a big batch load at the end of the month or the end of the quarter, and that would be re-missed, right, we are 2020, we're spread out all over the country and the world on both sides of the Atlantics. If I didn't say something about, you know, kind of the COVID impacts in terms of this accelerate, 'cause we hear it all the time in social media, right, who's driving your digital transformation, is it the CEO, the CIO, of COVID, and we've moved from this kind of light switch moment and then merged to, hey, this is an ongoing thing, and you know, kind of the new normal, is the new normal. And it's really shifted, a lot of people are talking about, you know, kind of shifts in the cloud infrastructure, the direction of the traffic, right, from going now from East to West and it's North to South, 'cause it's going to everybody's home. I wonder, I'll go back to you Guy, in terms of, the response that you've heard from some of your customers, in a response to, you know, kind of A, let's put a stop gap in early March that was interesting, and critical, and done, but now, kind of looking forward as to, you know, kind of a redistribution of workloads and architecture and users and I think Doug talked about security. How are you seeing any kind of ongoing effects and how is this impacting, you know, kind of you go to market and what you guys are bringing to market. >> Yeah, we're definitely seeing a lot of change in the way that service providers are trying to address this now. At the start of COVID, it was really a struggle, I think, for everyone to get the resources that they required to keep customers up from running, a lot of people started re-examining their disaster recovery contingency planning, and realizing that actually, what has happened in the last couple of years is, you know, workloads have exploded, a lot of patient workloads have completely gone through the roof and container workloads have grown drastically, and what's happened is the contingency plans behind all this stuff haven't changed and they just simply can't keep up the dynamic nature of the way we're doing business. Quite simply put technology is outpacing our weight, our ability to deal with that, so, you know, service providers need to provide a platform solution that enables them to be able to orchestrate at scale and enables them to orchestrate securely at scale, and really that means they've got to move away from this is hardware analog and move into virtual resourcing, cloud resource pooling elasticity, and particularly hypothesy. I know VMware we talk a lot about hybrid solutions and multicloud, but it's a reality when you look at where customers are today in their cloud journey, most of them have a footprint in their premise, have a footprint in a cloud provider premise and have multiple footprints in public cloud environments, so they need to have that consistent security model across that, they need to have data contingency and backup solutions, and someone needs to be in that to manage that, and that's where the service providers come in. They need to move away from the kind of infrastructure day to day operations that they were doing before and scale it out to now application protection and application development environments. >> Right, so Doug, I'm going to give you the last word as we wrap up this segment, you know, it's easy for us and pundits and people to write about multicloud and hybrid cloud and all these concepts, you guys actually have to make it work on the ground with real customers and real workloads. So I wonder if you could just kind of, you know, share your perspective, you've been working on this Dell Cloud Platform, you know, kind of how you see this evolving over time, and again, kind of what gets you up in the morning as you look forward as to what this journey is going to be over the next six months, one year, two year, three years down the road. >> Brought a lot of functionality capabilities to the world, right, the ability to consume things as you need them, the ability to really rely on a combined set of clouds and multicloud, and if you look at any enterprise that by any estimate, any company of any size, it's probably got 12, 15 clouds that contain their multicloud between using hyperscalers, tier two service providers, as well as cloud based services like Salesforce.com or Office 365, and you combine all those together and what that provides is a lot of flexibility, a lot of functionality, but also an extreme amount of complexity. And that complexity is really where Dell Technologies Cloud and Dell Technologies Cloud Platform is looking to help and to reduce that complexity, 'cause ultimately a successful enterprise is going to leverage the best from multiple clouds across multiple different implementations in order to provide the end to end IT experience that they need for both their external facing and internal IT operations. And with Dell Technologies Cloud Platform and working with our service providers, what we aim to do is to simplify the implementation of those multiple clouds and how they work together and make it as seamless as possible to shift workloads where they need to be, see your entire virtual enterprise IT environment, no matter where it's running, and to really optimize on your business to understand how you're using cloud, where you're using cloud, and how those clouds work together. And so the integration of all the different features with VMware and Dell bring together that end to end capability to significantly simplify the multicloud experience, and then ultimately our service provider partners, can help you on that journey to provide that management and orchestration across those different clouds and the data transformation, the digital transformation necessary in order to drive success. >> That's great, well, thank you Doug, for putting a nice big bow on it, and congratulations to you both for getting this release out, I know there's a lot of hard work and effort behind it, so it's always kind of good to finally get to expose it to the real world, so thanks for taking a few minutes with us. >> Great, thank you for having us. >> Absolutely. >> Yeah thanks Jeff, thank you. >> All right, he's Guy, he's Doug, I'm Jeff, you're watching theCUBE's continuous coverage of Dell Technologies World 2020, the digital experience. Thanks for watching, we'll see you next time. (soft upbeat music)

Published Date : Oct 22 2020

SUMMARY :

brought to you by Dell Technologies. that the Dell VMware So this yeah, this London for me, in the United States. in that part of the world, I tell yah. one but I think I prefer Pat. (Jeff and Guy laughs) Go to you Guy. and doing that through what we call, and all of the speed and efficiencies And you talked about before, and they can get to higher and how are you helping them solve them? and the things that provide more value and ability to deliver applications. and really help the customer identify, and put in the investment and to do that, we recognize and Guy back to you, and we all know that, you know, and the ransomware, et cetera, Right, and I didn't ask you Guy so from my perspective, I, you know, and as broadly across portfolio and so the worst case was you had, and you know, kind of the new and enables them to to give you the last word and to really optimize on your business and congratulations to you both 2020, the digital experience.

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Caitlin Gordon 10 21 V1


 

>> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. (soft music) >> Hi, Lisa Martin, with theCUBE here, talking with Caitlin Gordon, the VP of Product Marketing, at Dell technologies. Caitlin how are you? It's great to see you. >> I'm doing very well Lisa, thank you so much for having me. >> Nice to see you back on theCUBE. So lots of stuff going on in the news the last few months or so. A lot of stuff with respect to Cyber Recovery, Cyber Security, but talk to us about what's happening in the Purpose-Built Appliance Backup Appliance market. This market is growing. What's happening there, and talk to me about Dell's leadership role. >> Yeah, we've kind of come full circle. I've been in the data protection space for a while and I would say that, you know now we're looking at this as a $4 billion industry and security and protection has bubbled backup to the top of the list from an IT perspective. And one of the simplest, fastest ways to improve data protection is leveraging Backup Appliances. And there's really two segments within that. There's what I'll refer to as the target appliances and the integrated appliances. And we actually have had leadership in this space, since really the beginning. You know 50 cents of every dollar in this market is spent on Dell equipment. Where we see massive growth is really in that integrated appliance market. And those integrated appliances really simplify the deployment of not only the protection storage, but the protection software. So you can modernize your data protection, get much faster recovery, faster backups, as well as really get a smaller footprint, better efficiency, all in one single solution. And that's really where we've seen a lot of growth in the appliance market recently. >> Yeah. So as that, an integrated appliance market is growing twice as fast as targeted, give us a picture. You mentioned a few things, but kind of dig deeper into why customers are opting more and more for the integrated approach. >> Yeah that comes back to kind of a lot of the trends we see in IT overall. It's simplicity. It's ease of, how can you get to a better solution, a better outcome faster. And when it comes to integrated data protection appliances, it really it takes the guesswork out of it. You know, you have software and hardware, that's optimized to work together. You're really quick and easy to deploy, really simple to manage, 'cause it's all fully integrated and you get to a solution where you can get things like 65 one data reduction, get a very small footprint, get really fast improvements to not only backups, but probably even more importantly to recovery, get instant access to that data. And you really are able to with one purchase, transform all of your data protection. Now there's still a lot of great uses for target appliances as well of better flexibility. But, we've seen this overall you've seen this Lisa, every trend in probably IT and life, right? Simplicity. How can you get a faster, better answer? And integrated appliances really lean into that. It's as similar to what we see in the hyperconverged space, kind of in the primary storage and compute side of things. >> Yeah, I think we all want faster, simpler, better in every walk of life. One of the things this year that, in all of that lack of simplification, the complexity that we're living in that we've seen, is the rise of ransomware. It's not only on the rise, it's getting more personal. We've seen, you know, big companies, Garmin was attacked, one of the Cruise Lines was attacked, The New Zealand Stock Exchange, Facebook and Tik Tok were hacked. So we're starting to see so much more vulnerability and the ability of these hackers to expose more vulnerabilities. Have you seen that impacting your customers saying, "Hey, we need help here because now we have so many employees and devices, scattered." >> Yeah, unfortunately we have. You know, we've been talking about Ransomware Protection, Cyber Resiliency, Cyber Recovery with our customers for quite a number of years. And, now it's not a niche conversation just with financial institutions, it's a conversation with all of our customers. 'Cause either they've felt it or they've seen their competitors feel it and they need to protect themselves. So it has really become a conversation but it's not only our specialty sellers, but all of our sellers are having with our customers. And, it's really about not only being able to protect against them, which is an important part, but also recover from them. And that's really what our PowerProtect Cyber Recovery Solution is all about. And the exciting thing for us is that we actually have recently become the first Cyber Recovery Solution endorsed by Sheltered Harbor. Which really gives you an idea of the level of investment that we've made to provide that secure, automated air gap solution to give our customers that peace of mind. Because unfortunately this is becoming table stakes for any data protection out there today. >> Well, and as more and more, we see every company either becoming a data company or needing to become a data company to not just survive these times, but become successful as time goes on. To a point, it's one thing about protecting the data, but the actual need is to recover it should anything happen. Tell us a little bit more about Sheltered Harbor and what you guys were the first there to receive? Tell me a little bit more about that. >> Yeah, absolutely. Okay a little bit more on overall our solution and Sheltered Harbor is actually a consortium of organizations, primarily financial institutions that have really come together to define the standards, of what we need or Cyber Resiliency for Cyber Recovery. And for us with PowerProtect Cyber Recovery, we've worked closely with that organization, to meet those standards. And with that work and with that actual deploying in with one of our customers, we were able to become the first Cyber Recovery Solution endorsed by Sheltered Harbor to meet their standards there. And what's an important about our solution is that it's both that automated air-gapped solution for the data isolation, which is a part of it. But it's also, we have the CyberSense analytics and forensic tools that give you the ability to discover, to diagnose and to remediate against these attacks. So it gives you both sides of protecting that data air-gapping it, but also being able to intelligently discover and remediate against those attacks, if they do indeed happen. >> As VP of Product Marketing, I'm sure you're with customers often these days virtually. When you're having customer conversations, as you were singing out data protection and being able to recover and remediate, should anything like a ransomware attack happen, that's business critical. That's, you know, lifeline kind of stuff we're talking about. Have you seen the conversations within customer organizations shifts or is this now a board level or a C-level conversation in terms of data protection? >> Yeah, it's interesting. It's become a more frequent conversation. The people involved, are different. It's not just the backup administrators that are involved, it's really about the overall compliance strategy, the CSOs that are involved here. And it's becoming a corporate mandate as it really unfortunately needs to be at this point. So it's coming up more frequently, but also the types of people involved in that conversation have really changed the types of things we're having to talk about and build solutions for. So it's really changed that dynamic for us. And it's been great to really be on the front lines of that with our customers. You know, it started with those financial institutions and now it's really commonplace, to talk about this with everyone. >> So let's talk customers. Give us an example or two of some customers that are leveraging this new technology that are really achieving like the big deduplication ratio that you talked about, but also enabling their business to move forward. >> Yeah. One of my favorite ones for a couple of reasons I'll confess is, World Candy. Actually there are a World Corporation, but to me, they're a candy company. They actually make some chocolate out of Pennsylvania one of my favorites, chocolate covered pretzels. And they're a great example, right? 'Cause they're certainly not an IT specialty organization. They're trying to contract manufactured candy and they want to get things done as efficiently as possible. So they were looking a solution to overall modernize, their overall IT and that came with the combination of an Integrated Data Protection Appliance, as well as VXRail. And by implementing that, they were able to reduce their backup times from running overnight all night, to just two hours. They were able to get dedupe ratios of a 12O to one, 99.2% reduction, which is just incredible. And they were able to reduce their physical server footprint by 60%. So you can just imagine with an organization like this, that needs to run things as efficiently, as simply, as quickly as possible, how transformational that is. And, probably one of the other things that we find out of customers like this is, it's really about finding them a partner that can solve all of their problems in one place. And for data protection that's certainly one of the biggest things for PowerProtect is we now have a one-stop shop appliances software for all your data protection needs, large and small. And my favorite thing is actually our quote from this customer which is, he calls it a perfect partnership and that they have a single hand to high five. And we love to get those high fives from our customer and we really like to be that partner for them and to help them solve these challenges really no matter where their data is or what their challenges are. >> I like that a single can for a virtual high five. Speaking of partners, what's the channel play here? >> Yeah, absolutely. I mean, for us, Dell Technology is overall channel partners are absolutely critical and in the data protection space, probably even more so. So channel partners are a huge part of our go-to-market. And one of the reason that channel partners really like to work with us, with Dell technologies on the data protection side, is because of the breadth of that portfolio. And now with our most recent enhancements on the appliance side, you now have a full PowerProtect portfolio. Target appliances, integrated appliances, physical, virtual, as well as modern data protection software with PowerProtect data manager. And for our partners, and for us, it's so important that they can have one vendor to offer all of these solutions because we know that our customer's challenges are complex, they're diverse, their data sets are diverse and they need to be able to partner with someone, leverage us as a vendor, leverage our partners, leveraging us as a vendor to really give our customers that answer. And that could be very different needs. They have traditional applications, they have new modern applications in Kubernetes and the growth of, and the importance of those types of applications. Our partners don't want and our customers don't want to have to deal with multiple vendors. Multiple vendors actually can increase risk, increase costs. They want to keep that simple, efficient. And that's why partnering with us, with Dell Technologies, why our channel partners really find us to be such a critical vendor to work with on the data protection side. >> So you've shared some impressive stats about what the technology is able to deliver. You gave us the great World Candy company example in terms of the things I heard a big workforce productivity there, they've got big deduplication there. They're able to sounds like reduce their on-prem footprint. From an economic value perspective, help us understand what the economic value of the DP series and even maybe feedback from the analyst community. >> Yeah, we've actually got a recent study which I'd encourage you guys to go read and I will just kind of give you the Cliffs Notes version of it. Which shows you the advantages of leveraging Dell Technologies portfolio for data protection. You can have your cost to protect as low as 1 cent per gigabyte per month, which is impressive. And that's that efficiency that you can get with PowerProtect. It's a reduction in the administration costs for data reduction of 22%, a reduction of 84% in your Cloud resources and services. We all know that people have moved to Public Cloud and probably one of the biggest concerns is the cost of that. By implementing the right data protection solutions, leveraging our in-cloud backup and protection, you can actually significantly reduce that because of the way that we've implemented it. And overall, you can't argue with anything that reduces costs by 98%. So you can reduce your storage resource costs by 98% by leveraging the PowerProtect portfolio. And again, it's a recent ESG study, which you can find on our website and read more about that study and the economic elements that lead into that. But you can just see the dramatic impact that can have, not only are you protecting your most valuable asset of data, but you're doing so in a way that saves the company money, and time and resources. And we all know that's never been more critical than ever. >> Those are very impressive, but compelling stats. Last question, talking about the three waves that we know Dell technologies is writing, we've got VMware, Cloud, Cyber Recovery, give us a flavor of the launch and the news and the new capabilities for this one-stop shop with perspective of what's happening in Cyber Recovery today. >> Yeah, so we've got enhancements on all fronts. So we, let me go in order there. So we've got on the Cloud front our PowerProtect data manager, which we've talked about a lot this year. We continued to really enhance that. Some recent enhancements, the ability to deploy that in Azure and AWS Cloud, to be able to do in-Cloud data protection. On the VMware side as we talked about just recently at VMworld, we've got new integrations with Storage Based Policy Management to really simplify and automate protection for the Vadmins as well as protection administrators. The ability to support, real mission critical applications and VMs, that are something we're working on to be able to more intelligently protect those VMs that have become more challenging to protect in traditional methods as well as integration with protect VCF. And then lastly, I think we've covered a bit today is certainly on that Cyber Recovery, Cyber Resiliency solution. First one to be endorsed by Sheltered Harbor in providing that air gap solution, as well as that ability to discover to remediate from those attacks. And you can kind of get a sense of, where we're really focused on. Those are our big three areas in both our appliance as well as our software portfolio really focused on simplifying that for our customers. >> Well Caitlin, we thank you for joining us as per what theCUBE has seen for many years with Dell Technologies. Lots of innovation, continued innovation. We thank you so much for joining us on theCUBE today. >> Thanks so much for having me. It was great to be here, Lisa. >> Excellent. With Caitlin Gordon, I'm Lisa Martin. You're watching theCUBE. (soft music)

Published Date : Oct 21 2020

SUMMARY :

leaders all around the world, It's great to see you. thank you so much for having me. So lots of stuff going on in the news And one of the simplest, fastest ways for the integrated approach. Yeah that comes back to One of the things this year that, of the level of investment that we've made but the actual need is to recover it And for us with and being able to recover and remediate, And it's been great to ratio that you talked about, and that came with the combination the channel play here? and in the data protection space, of the DP series and even maybe feedback and probably one of the biggest concerns and the news and the new capabilities the ability to deploy that We thank you so much for Thanks so much for having me. (soft music)

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Bob Evans, Cloud Wars Media | Citrix Cloud Summit 2020


 

>> Woman: From theCube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is theCube conversation. >> Hey, welcome back everybody. Jeff Frick here with theCube coming to you from our Palo Alto studios to have a Cube conversation with a real leader in the industry he's been publishing for a long, long time. I've been following him in social media. First time I've ever get the met in person and kind of a virtual COVID 20, 20 way. And we're excited to welcome into the studio. Bob Evans. He's a founder and principal analyst, the Cloud Wars Media coming to us. Bob where are you coming to us from today? >> In Pittsburgh today. Jeff. Good to see you. >> Awesome. Pittsburgh Pennsylvania. There's a lot of Fricks in Pittsburgh Pennsylvania cause Henry Clay was there many moons ago so that's a good town. So welcome. >> Thank you, Jeff. Thanks. Great to be here. And I look forward to our conversation. >> Absolutely. So let's, let's jump into it. So I know you attended today, the Citrix Cloud Summit you know, we've covered Citrix energy in the past this year, they decided to go we'll obviously virtual like everybody did but they, you know, they did something a little creative I think as, and they broke it into pieces, which, which I think is the way of the future. There's no reason to necessarily aggregate all of your news, all of your customer stuff, all your customer appreciation, the party the partners, all for three days in Vegas. Cause that's the only time you could get the Science Convention Center. So today was the Cloud Summit all day long. First off, just, you know, your general impressions of the event, >> Jeff, you know, I just thought that the guys had hit a really good note about what's going on in the outside world. You know, sometimes I think it's a little awkward when tech companies come in and the first thing they want to talk about is themselves, which I guess in some ways fine but I think the Citrix guys did a really good job at coming outside in here's what's going on in the outside world. Here's how we as a technology player trying to adapt to that and deliver the maximum value to our customers in this time of unprecedented change. So I thought they really nailed that with cloud and some of the other big topics that they laid out >> Great. And you've been covering cloud for a long time and, and you know, COVID is, we're still in it. There's a lot of really bad things that are happening. There's hundreds of thousands of people that are dying and a lot of businesses are getting crushed especially hospitality, travel you know, anything that relies on an aggregation of people. Conversely though we're, we're fortunate to be in the IT industry and in the information industry. And for a lot of industries, it's actually been kind of an accelerant. And one of the main accelerants is this, you know kind of digital transformation and new way to work. And some of these things that were initiatives in play but on March 15th, approximately it was go, right? It was Light switch no more planning, no more talking, it's here now. Ready, set, go. And it's in, you know, Citrix is in a pretty good position in terms of the products that they offer, the services that they offer, the customer base that they have to take advantage of that opportunity and, and you know, go to this, we've all seen the social media memes right? Who's driving your digital transformation the CEO, the CIO, or COVID. And we all know what the answer to the question is. They're pretty well positioned and it seems like, you know, they're doing a good job kind of doubling down on the opportunity. >> Jeff. Yeah. And I'd sure echo your, your initial point there about the nightmare that everybody's experienced over the last six or seven months. There's, there's no way around that yet. It has forced in these categories like, you know, that we've all heard hundreds of thousand time digital transformation to the point where the term almost becomes a cliche but in fact right? You know, it has become something that's really you know, one of the driving forces, touching everybody in the planet, right? There's, and I think digital transformation. Isn't so much about the technology, of course but it's because, you know, there's a couple billion people around the world who want to live digitally enhanced digitally driven lifestyles. And the pandemic only accelerated that as you said. So it triggered things you know, in our personal lives and our new set of requirements and expectations sort of rippled up to the B2C companies and from them back up to the B2B companies So every company on earth, every industry has had to do this. And like you said, if they were, deluding themselves maybe telling themselves these different companies that yeah, we're going fast, we're aggressive. Well, when this thing hit earlier this year as you said, they just had to really slam their foot down. I think that David Henshall from Citrix said that they had some companies that had, they were compressing three years into five months or he said in some cases even weeks. So it's really been extraordinary. And cloud has been the vehicle for these companies to get over into their digital future. >> Right. And let's talk about that for a minute because you know, Moore's law is my favorite law that nobody knows which was, you know, we tend to underestimate, excuse me we tend to overestimate the impact of technology in the short term of specific technology and underestimate the longterm impact. You know, Gardener kind of uses a similar thing with the hype cycle. And then you know, the thing goes at the end, you know, had COVID hit five years ago, 10 years ago, 15 years ago you know, the ease in which the information workers were able to basically just not show up and turn on their computer at home and have access to most of their tools and most of the security and most of their applications that wasn't even possible. So it's a really interesting, you know, just validation on the enabler that we are actually able to not go to work on Tuesday the 16th or whatever the day was. And for the most part, you know, get most of our work done. >> Yeah. Yeah. Jeff, you know, I've thought about it a lot over the last several months. Remember the big consultant companies used to try to do these measures of technology and they'd always come out and say, well, we've done all these studies. And despite the billions of dollars of investment we can't show that IT has actually boosted productivity or, you know, delivered an ROI that customers should be happy with. I was always puzzled by some of the things that went into those. But I would say that today over these last six or seven months to your point, we have seen extraordinary validation of these investments in technology broadly. But specifically I think some of these things that are happening with the cloud, you know, as you've said how fast some companies have been able to do this and then not remarkable thing, Jeff right. About human nature. And we hear a lot about in, in when companies change that relative to changing human behavior changing technology is somewhat easy but you try to change human behavior and it's wicked. Well, we had this highly motivating force behind it, of the pandemic. So you had a desire on the part of people to change. And as you pointed out, there's also this corresponding thing of, you know, the technology was here. It was right. You've got a fast number of companies delivering some extraordinary solutions. And, you know, I thought it was interesting. I think it was a Kirsten Kliphouse from Google cloud. One of Citrix's partners who said that we're two best of breed companies, Citrix and Google cloud. So I thought that, that coming from Google you know, that is very high praise. So again, I think the guys at Citrix are sort of coming into this at the right time with the right set of outside in-approaches and having that flexibility to say that we're moving into territory nobody's ever been both been in before. So we better be able to move as fast as possible. >> Right. Right. And, and just to keep going down the quote line, you know once everyone is taken care of and you, you deal with the health and safety of your people which is a number one, right? The other thing is the great Winston Churchill quote which has never let a good crisis go to waste. And I think you know, David talked about in that, in his keynote that this is an opportunity, He said to challenge assumptions, challenge the models of the past. So, you know get beyond the technology discussion and use this really as a catalyst to rethink the way that you do things. And, you know, I think it's a really interesting moment because there is no model right? There is no, there is no formula for how do you reopen, there was no playbook for how do you shut down? You know, it was, everybody's figuring it out. And you've got kind of all these concurrent processes happening at the same time as everyone tries to figure it out and come to solutions. But clearly, you know, the path to, to leverage as much as you can, is the cloud and the flexibility of the cloud and, you know the ability to, to expand, add more applications. And so, you know, Citrix again, right place, right time right. Solution, but also you know, taking an aggressive tact to take advantage of this opportunity, both in taking care of their customers, but really it's a real great opportunity for them to change a little bit. >> It is. And Jeff, you know, I think if I could just piggyback on you know, your, your guy there Winston Churchill, one of his other quotes, I love it too. And he said, if find yourself crawling through hell, keep going. And I think so many companies have really had to do that now. It's, it's not ideal. It's not maybe the way they plan it but this is the reality we're facing here in 2020 and a couple of things right? I think it requires a new type of leadership within the customer companies right? What, how the CEO gets engaged in saying, I, I'm not going to relegate this to the CIO for this to happen and something else to the CMO. They've got to be front and center on this because people are pretty smart. And then the heightened sensitivity that everybody in every business has around the world today if you think your CEO is just paying lip service to this stuff about digital transformation and all these changes that everybody's going to make, the people aren't going to buy into it. So you've got the leadership thing happening on the one side and into that it's not a vacuum, but into that void or that opportunity of this unprecedented space that you mentioned come the smart, capable forward-looking technology companies that are less concerned with the stuff that they've dragged along with them for years or decade or more. But instead of trying to say, what is the new stuff that people are going to be desperately in need of and how can I help these customers do things that they never did before? It's going to require me as a tech company to do stuff that I've never done before. So I, I've just been really inspired by seeing a lot of the tech companies doing what they are helping their customers to do which is take a product development cycle, look at all the new stuff that came out around COVID and back to work, workspaces. And so on what Citrix, you know others are doing like this, the product development cycles Jeff, you study this stuff closely. It's, it's almost unimaginable. If you had said that somebody within three months within two months, we're going to have a new suite of product available we would have said it just, it's not possible the nice idea but it can't work, but that's happening now, right? >> Yeah. Isn't it interesting that had you asked them on March 10th, they would have told you it's not possible. And by March 20th, they were doing it. >> Yeah. >> At scale, huge companies. And to your point, I think that the good news is they had kind of their own companies to eat their own dog food and get their own employees you know, working from home and then, you know, bake that into the way that they had their go to market. But let's talk a little bit more specifically about work from home or work from anywhere or the new way to work. And it's funny cause that's been bantered about for, for way too long, but now, now it's here. And most indications are that for many people, many companies are saying you're not going to go back for a while. And even when you do go back it's going to be a lot different. So, you know, the new way to work is really important. And there's so much that goes into that. And one of the big pieces that I'm encouraged to hear is how do you measure work? And, you know, there's a great line I heard where, you know work is an output. It's not a place to go. And, you know, I had Martin Michaelson early on in this thing, and he had the great line, you know it's so easy to fake it at work, you know, just look busy and walk around and go to all the meetings where with a work from home or work from anywhere. What the leadership needs to do is, is a couple of things. One, is measure output right? Not activity. And you know, it's great. People can have dinner with their family or go see the kid's baseball game. Or I guess they don't have a baseball games right now but, you know, measure output, not activity which is, doesn't seem to be that revolutionary. But I think it kind of is. And, and then the other thing is really be an enabler and be a, an unblocker for people in terms of a leadership role right? Get out, help get stuff out of the way. And, but unfortunately, the counter is, you know how many apps does a normal person have to interact with every day? And how many notifications do those apps fire off every day between Slack and Asana and Salesforce and, and texts and tweets and everything else. You know, I think there's a real opportunity to take a whole nother level of productivity improvement by removing these, these silly distractions automating, you know, as much of the crap away as we can to enable people to use their brains and have some quiet time and think about things and deliver much better value than this constant reaction to nonstop notifications. >> Yeah. Yeah. Jeff, you know, I loved your point there about the difference between people's outlook on March 10th versus on March 20th. And I believe that, you know, all limitations are self-imposed, right? We tend to form constructs around how we think and allow those then to shape and often restrict or confine our behavior. And here's an example of the CEO of Novartis Pharmaceutical Company. He said, we have been brought up in the pharmaceutical industry to believe that it is immutable law of physics that it's going to take 12 and a half years and two and a half billion dollars to get a new drug approved. And he said in the past with the technology and the processes and the capabilities that that was true it is not true today yet too often, the pharmaceutical industries behave like those external limitations are put in there. So flip that over to one of the customers that, that was at the Citrix Cloud Summit today Jim Noga, who's the CIO at Mass General Brigham. I thought it was remarkable what he said when you asked about how are things going with this work from home? Well, Jim Noga the CIO there said that we had been averaging before COVID 9,000 virtual visits a month. And he said since then that number has gone up to a quarter of a million virtual visits a month or it's 8,000 a day. So they're doing an a day what they used to do in a month. Like, you said it, you tell them that on March 10th, they're not going to believe it but March 20th, it started to become reality. So I think for the customers, they're going to be more drawn to companies that are willing to say, I see your need. I see how fast you want to move. I see where you need to go and do things you never did before. I'm willing to lock elbows with you, and go in on that. And the tech number is that sort of sit back and say, ah well, I'd like to help you there, but that's not what I do. They're going to get destroyed. They're going to get blown out. And I think over the next year or two, we're going to see this massive forcing function in the tech industry. That's going to separate the companies that are able to move at the pace of market and keep up with their customers versus those that are trapped by their past or by their legacy. And it is, going to be a fascinating talk. >> So I throw on a follow up to make sure I understand that number. Those are patient visits per unit time. >> Yeah. At Mass Brigham. So he said 9,000 virtual visits a month is what they're averaging before COVID. He said, now we're up to 250,000 virtual visits per month. >> Wow. >> So it's 8,000 a day. >> Wow. I mean the thing that highlights to me, Bob, and the fact that we're doing this right now, and none of us had to get on an airplane is, you know, I think when people think back or sit back and look at what does this enable? right? What does digital enable? Instead of saying instead of focusing what we can't do, like we can't go out and get a cup of coffee after this is over and we can't and that would be great and we'd have a good time but conversely, there's so many new things that you can do right? And you can reach so many more people than you could physically. And, and for like, you know, events like the one today. And, you know, we cover events all the time. So many more people can attend if they don't have the expense, of flying to Vegas and they don't have to leave the shop or, you know, whatever the limitations are. And we're seeing massive increases in registrants for virtual events, massive increase in new registrants. Who've never attended the, the events before. So I think he really brings up a good point, which is, you know, focus on what you can do and which is a whole new opportunity a whole new space, if you will, as opposed to continuing to whine about the things that we can't do because we can't do anything about those anyway >> No, and you know, that old line of a wish in one hand and spit in the other and see which one fills up first (laughs) you know, one of the other guests that that was on the Cloud Summit today Jeff, I don't know if you got to see 'em, but Steve Shute from SAP who heads up their entire 40,000 person customer success organization he said this about Citrix. "Citrix workspace is the foundation to provide secure cloud based access for this new generation of remote workers." So you get companies like SAP, and, you know, you want to talk about somebody that has earned its way into the, you know the biggest companies in the world and how they go along. You know, it's pretty powerful. They end up, your point Jeff, about how things have changed, focus on what we can do. The former CEO of SAP, Bill McDermott. He recently said, we think of phones as, you know, devices that help us be more productive. We think of computers as devices that help us be more productive. He said, now the world's going to start thinking of the office or the headquarters. It's a productivity tool. That's all it is. It's not the place that measures Hey, he was only at work, four days today. So, you know, he didn't really contribute. It's going to be a productivity tool. So we're going to look at a lot of concepts and just flip them upside down what they meant in February. Isn't going to to mean that much after this incredible change that we've all been through. >> Right. Right. Another big theme I wanted to touch base with you on it was very evident at the at the show today was multicloud right and hybrid cloud. And, you know, I used to work for Oracle in, in the day. And you know Amazon really changed the game in, in public cloud. The greatest line, one of Jeff's best lines is you know, we had seven year headstart. Nobody even was paying attention to the small book seller in Seattle and they completely changed enterprise technology. But what came across today pretty clearly right? As horses for courses, and really focusing at the application first right? The workload first and where that thing runs and how that thing runs, can be any place in that in a large organization you know, this is pick an airline or, or a big bank right? They're going to have stuff running at Oracle. They're going to have stuff running at AWS. They're going to have stuff running on Google. They're going to to have stuff running in Azure. They're going to have stuff running in their data center. IBM cloud, Ali Baba. I mean there's restrictions for location and, and data sovereigncy and all these things that are driving it. And really, you know, kind of drives this concept where the concept of cloud is kind of simple but the actual execution day to day at the enterprise level and managing and keeping track of this stuff, it is definitely a multicloud hybrid cloud. Pick your, pick your, your adjective but it's definitely not a single cloud world. That's for sure. >> Yeah. Yeah. And Jeff, you know, the Citrix customer that I mentioned earlier, Jim Noga is that the CIO at mass General Brigham, one of the other points he made about this was he said he's been very pleased about some of the contributions that cloud has made in, in, in his hospital organizations, you know transformation, what they've been able today and all the new things that they're capable of doing now that they were not people poor. But he said, you know, cloud is a tool. He said, it's not Nirvana. It's not a place for everything. He said, we have some on-premises systems. He said, they're more valuable now than they were a couple of years ago. And then we've got edge devices and we have something else over here. He said, so I think his point was it's important to put the proper value on cloud for all the things it can do for a specific organization, but not the thing that it's a panacea for everything though, big fan, but also a realist about it. >> Great. >> And so from that to the hybrid stuff and multicloud and I know all the big tech vendors would love it and say Oh no, it's not a multicloud, but just be my cloud. Just, just use my stuff. Everything will be easy, but that's not true. So I think Citrix position itself really well big emphasis on security, big emphasis on the experience that employees need to have. It isn't just sort of like a road war you loose five or seven years ago, as long as he, or she can connect through email and, you know, sending a sales data back and forth, they're all set. Now. It's very different. You've got people sitting in a wildly different environments for, you know, six, eight, 10 hours a day and chunk of an hour or two or three here or there. But that, that seamless experience always dependable, always reliable is just, you know, it can't be compromised. And I just thought you have one you know, high level thought about what happened. It was impressive for me to see that Citrix certainly a fine company put it. It's not one of the biggest tech companies in the world but look at the companies we have, the Microsoft, SAP talking about Google Cloud, AWS, you know, up and down the line. So I just thought it was really impressive how they showed their might as sort of a part of a network effect that is undeniable right now. >> Right. Right. And I think it's driven, you know, we hear over and over right? I mean, co-opertition is a very Silicon Valley thing. And ultimately it's about customer choice and the customer's going to choose you know, kind of by workload, even if you will or by budget as to what they're going to do where so you have to be able to operate in that world or you're going to be you're going to get, you're going to get left out unless you're just super dominant and it's a single application and they built it on you and that's it. But that's not realistic. I want to shift gears a little bit Bob, since I'm so happy to be talking to you on another topic, that's, that's a big mega trend and we're slowly seeing more and more applications. That's machine learning and artificial intelligence and you know, and, and the generic conversations about these remind me of the old big data conversations. It's like okay. So what you know, who cares? It doesn't really matter until you apply it. And with all these new applications and even just around the work from home that we discussed earlier, you know, there's so many opportunities to apply machine learning and AI, to very specific functions and tasks to, again, help people prioritize what they're going to do help people not have to deal with the crap that they shouldn't have to do. And really, you know at a whole another level of, of productivity really, based on a smarter way to help them figure out what am I going to do in my next, my next marginal minute? You know, cause ultimately that's the decision that people make when they're sitting down getting work, done it, how do they do the best work? And I think the AI and machine learning opportunities are gargantuan. >> Jeff. The point you made a few minutes ago about, you know, we tend to overestimate the impact of a new technology in the short term and underestimate it, what it'll be overtime well, we've been doing that with AI for the last 40 years but this is going to be sort of the golden age of it. And one of the reasons why I have been so bullish on cloud is it presents like the perfect delivery system for it. This is we see in medicine, there's sometimes breakthroughs at the laboratory level where they've got the new breakthrough medication but they don't have the bullet. They don't have the delivery system to get it in there, cloud's going to be an accelerator for that. And it gives the tech companies, which and this is going to be very good for customers, every big tech company. Now as a data company, every company says, it's an analytics. Everybody says I'm into AI. Every company says I'm into ML. And in a way that's real good for customers cause the competitive level is going to soar. It's going to bring more choice. As you said, the more customers more types of solutions, more sorts of innovation. And it's also going to be incumbent on those tech vendors. You've got to make it as easy as possible, as fast as possible for these customers to get the benefit of it. I think it was Thomas Kurian, the CEO of Google cloud said, Hey, you know, if, if a shoe company or a retailer or a bank had fantastic expertise in data science, they could go out and hire 200 data scientists do this all themselves. He said, but that's not what they do. And they don't want to do that. >> Right. >> So he said, come to the companies who can do it. And I think that we will see changes in how business works driven by ML and AI, unlike anything that we've ever seen. >> Yeah. >> And that's going to happen over the next 12, 18 months. >> Yeah. Baked into everything. Well, Bob, I really am excited that we finally got to catch up in, in person COVID style. Like I said, I've been following you for a long time. So I just gave you the last word before we sign off. You know, you've been in this business for a long time. You've seen lots and lots of waves. You know, this is just another wave with this, with this, you know, gasoline thrown on the fire with, with COVID in terms of the rate of change. And the, you know there's no more talking, the time to move is now, share kind of your perspective as to kind of where we are. And, you know, we're, we're not that far from flipping the calendar to 2021, which is a good thing you know, as you, as you look forward a little bit you know, what's in your mind, what's getting you excited. What's getting you up in the morning. >> Yeah. Jeff, I guess it comes down to this thing of, we, I think here late in 2020, everybody's got a reason to be pretty proud of what we have done, not only in the last six months but over the last several years, if you look at the improvements that have been made in health care and making it available to more people, in education the things that teenagers or young teenagers or even pre-teenagers can do now to learn and explore the world and communicate with people from all over the globe, there's a lot of great things going on, but I think we're going to look back on this point and say, this was, this was a pivot point here in mid and late 2020, when we stopped letting in some ways, as you described it earlier worrying so much about the things we can't do. And instead put more time into what we can do, what breakthroughs can we make. And I think these things we've talked about with AI and ML are going to be a big part of that, the computer industry or the tech industry, maturing and understanding they're not in charge. It's the customers who are in charge here. And the tech companies have to reorient themselves and reimagine themselves to meet the demands of this new fast changing world. And so I think those are some of the mega trends and more and more Jeff, I think these tech companies are going to say that the customers are demanding that the tech companies give them the gift of speed, give them the gift of engaging with customers in new ways, give them the gift of seeing the world as other people see it rather than just through the narrow lens of, you know sometimes the tech bubble that can percolate somewhere out sometimes out in the Palo Alto area. So I, I'm incredibly optimistic about what the future is going to bring. >> Well, Thank you. Thanks for Bob for sharing your insight. You can follow Bob on Twitter. He's got podcasts, he's very prolific writer and again, really, really a great to meet you in person. And thanks for sharing your thoughts >> Jeff, thanks so much. You guys do a fantastic job and it's been a pleasure to be with you. >> Thank you. Allright. He's Bob Evans. I'm Jeff Frick. You're watching theCube from our Palo Alto studios. Thanks for watching. We'll see you next time. (soft music)

Published Date : Oct 12 2020

SUMMARY :

leaders all around the world. the Cloud Wars Media coming to us. In Pittsburgh today. There's a lot of Fricks And I look forward to our conversation. Cause that's the only time you could get Jeff, you know, I just thought And it's in, you know, Citrix but it's because, you know, And for the most part, you with the cloud, you know, as you've said to rethink the way that you do things. And Jeff, you know, I think that had you asked them and he had the great line, you know and do things you never did before. to make sure I understand that number. So he said 9,000 virtual visits a month And, and for like, you know, No, and you know, that old but the actual execution day to day But he said, you know, cloud is a tool. And so from that to the and the customer's going to choose and this is going to be So he said, come to the And that's going to happen the time to move is now, the narrow lens of, you know great to meet you in person. and it's been a pleasure to be with you. We'll see you next time.

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BJ Gardner and David Zeigenfuss, PLM | VMware Cloud on AWS Update


 

>> From the cube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cube conversation. >> Hi, I'm Stu Miniman And we're digging in with the VMware cloud on AWS update, of course, an important solution set we've been talking about for a couple of years. If you see we've done interviews with some of the VMware and AWS executives, we did a deep dive on some of the technology. And now we get to dig in with one of the users of the technology. Of course, the executive talk about the proof of how many customers have been using it. So happy to welcome to the program I have two guests from PLM insurance. First, sitting right next to me on the screen is BJ Gardner, who's the lead system architect. Next to him is Dave Zeigenfuss, who is a senior systems architect. BJ and Dave, thanks so much for joining us. >> Thank you for having us. >> Thank you for having us. All right. So BJ, just for our audience that does not know, Pennsylvania Lumberman's Mutual Insurance Company, give us a little bit about The company 125 years in history, obvious with the name, it's in the insurance business but help us understand, you know, what your business is and what you and Dave do for the organization. >> Sure, so Pennsylvania Lumbermens has been around for under 125 years, we just celebrated the 100 and 25th year. This February Actually, we are commercial insurance company, property Casualty. And we specialize in the wood niche. So we cover everything from lumber yards to auto fleets that have anything to do with moving wood selling wood. So we're pretty niche, we're pretty specific in our brand. And we're a mutual insurer. We're one of the few if not only one, left that does not offer insurance on mutual space >> Alright, and BJ give us a little bit of snapshot from an IT standpoint, obviously, you're using VMware, cause you're here, talk to us about what data centers and cloud usage looks like for PLM. >> So I've been without Pennsylvania Lumbermens for about 15 years, and we were operating in full on-prem with bare metal servers, and 2007-2008, We started with the VMware product set. And since then we've been moving little by little to the cloud. We have many of our core applications are sitting with vendors in the cloud as of right now, we have a small data center in Philadelphia that is an on prem. And then we have, which we'll talk about, why have cloud data center as a service model with the VMware Certified cloud partner called Faction. And then we also now have our disaster recovery as a cloud product. >> Excellent. Since we're talking about the the VMware cloud on AWS bring us inside a little bit,that DR In this case that you're using. That hybrid model, help tease that out. BJ will Start with you. And I'm sure, Dave will have some color to give after you share. >> Sure, I mean, you know, when you're talking about disaster recovery in general, the need to maintain business continuity, while keeping a lean IT staff and with no extended downtime and data loss is just... it's not an option. You can't afford to be down, you can't afford to lose data. So having a cloud service now for disaster recovery, or at least the concept of that helps us more IT shop, in the way of resources that we just don't have on hand on staff. So, that's, pretty much the biggest goal for us, is to maintain business continuity and you know, with our lean staff at the same time. >> Echoing BJ a bit, having an on prem solution and really, to BJ'S point about our lean staff, It made things quite cumbersome for us with maintaining backups replications and such. There was a lot involved. It was very time consuming. So the handoff to utilizing VMware cloud for our disaster purposes really, really helped that benefit our team as a whole. >> All right, you mentioned your partner on this solution is Faction. Help us understand how you made the decision to go down this path. >> So I can give you a quick... a quick rundown here how Faction came to be. so we're located our corporate is in fellow Philadelphia PA. We occupied two floors in an office building. Our data center was on the one floor we were consolidating. And we moved up to just one single floor. So we basically lost the footprint of the data center. So I went out hunting for co location type vendor, and hooked up with Faction. And yeah, so we've been with Faction for since 2015. We've had their, I call it kind of co lo, plus data centers as a service model, since then, since 2015. And we've been with them doing different initiatives here and there over the years and disaster recovery as a service is now one of them. >> Great, Dave, you've maybe supply a little more color on that piece. >> Yeah, sure. Yeah, the use of VMware cloud with Site Recovery Manager. Again, from a technical standpoint, it was second to none as far as the flexibility it gave us to grow our workloads, to maintain them. Recovery point objective was what really sold me. It allowed us to get extremely granular from a business continuity perspective. And, yeah, I'm a fan. I just, I really like VMware cloud with SRM. It's proven to be top notch. >> Yeah, maybe follow up on that, you've been a VMware customer for a number of years, you're familiar with the tooling, and everything else like that. So, how long did a solution like this take to roll out? >> So, I will guess so, absolutely, there was a good portion from when we started, so you have to kind of put it in perspective, because we had a data center in Atlanta, Georgia, that was our data recovery site with action. So we had a two fold project, we were going into a contract year, a renewal year. And Faction pitched, the AWS VMware on AWS service. So we were decommissioning a data center at the same time as we were rolling it out. So I'll just give you the quick timeline. So November of 2018, was basically the contract negotiations. We finalized everything kind of in February of 2019. As far as kicking off the call on how we are going to actually do the project. Work began around April of 2019. Faction went ahead and set up the AWS DDC environment in early May. Faction builds out the environment for the rest of May. June, we did some non disruptive load testing on the environment in AWS. We set up the replication recovery group build out throughout the summer of 2019. And then we had a full sign off in September 17th actually 2019 so I'll just kind of highlight though, in that process, that it took roughly about four months to do the full build out testing and the Atlanta data center decommissioning. >> Okay, and PJ after having done this, we've now got DR as a Service, what are the hero numbers? Have you reduced their cost savings loannes, How do you report up? The success or result of what you've done so far? >> Yeah, so speaking to that, so when we did the contract negotiation, in November of 2018, one of the things we realized when we were pitching the cloud disaster recovery as a service model, we saw roughly about a 20% annual savings in moving to this cloud service. So, a breakdown of what kind of the savings is it's pretty much in Atlanta we have some resource costs because we're running basically on a pillow type environment with with Baxter. and then we had a circuitry call, so we had a point to point line that would run out to, actually to New Jersey and then down to Atlanta. So we that cost as well. So we saved basically, we ripped out the point circuit And we got we offloaded some resource costs. So, like I said about a roughly about a 20% cost savings. >> Alright, so that that's some of the hard figures. Dave, bring us inside a little bit operationally, obviously, there's got to be a little bit of changes to how you manage things, automation is, has been hot for years, but even more so when you talk about cloud environments. So, how is this deployment, changed what the workers are doing and beyond that? >> Well, it's it's simplified things quite a bit, just by the partnership with Faction and in conjunction with VMware cloud for our disaster recovery solution, It's offered many benefits. For one, we had a primary engineer who left the company, we found some benefits to not having to fill that staff resource, so that that was also a positive from a money aspect. But as far as the day to day functioning where we go about doing things up, it really took things off my plate, off the rest of the teams plate And just really, really gave us a peace of mind as it pertains to our, our infrastructure and our data being secured. >> All right, well, I want to give you both the final word. What learnings do you have out of this? Any best practices you'd share? Or there's also some updates coming, taking VMware being able to take advantage of the latest bare metal offering from Amazon? I'll let you choose maybe BJ, we'll start with you and wrap with you Dave as to that those final words that you would share with your peers >> Yeah, I'll certainly start it off. I mean, coming from my perspective as kind of the manager of the team here, our goal as a company, our goal as an IT shop, our goal as an operations team, is to ensure the company's technology needs, will be met after, in the event of a disaster. And that is the key. You want to protect itself, you want to protect the data, you want to protect the customers. So, in the case of the cloud for us, is maintaining business continuity while reducing physical footprint and keeping the IT operations lean, like I had stated before. And one of the most important things and this is not just about disaster recovery, but establishing good partnerships with vendors, is absolutely imperative. Because I don't care how big your shop is, and again, we're on the small side, obviously, but you can't you can't do it alone. So you need really good strong partnerships and good relationships with them. >> And I would say, make sure you are Identify your critical business workloads. Know your environment, absolutely. It's imperative. Get it, you have to plan efficiently. And by all means, test, test test test, you can't test the solution enough. So that's really about all I have. >> All right, Well, David, BJ, thank you so much for joining us appreciate you sharing your your journey along and wish you the best of luck with the solution going forward. >> Thank you. >> Thank you for having us. >> And thank you for joining us for this update VMware cloud on AWS, be sure to check out the cube.net for all the rest of the coverage we have both in the VMware and AWS ecosystems. I'm Stu Miniman And thank you as always for watching the cube. (upbeat music)

Published Date : Jul 15 2020

SUMMARY :

From the cube studios And now we get to dig in with one and what you and Dave that have anything to do with Alright, and BJ give us and we were operating in full on-prem to give after you share. the need to maintain business continuity, So the handoff to utilizing VMware cloud All right, you mentioned your partner footprint of the data center. more color on that piece. as far as the flexibility it like this take to roll out? And Faction pitched, the one of the things we realized to how you manage things, automation is, But as far as the day to day functioning we'll start with you And that is the key. make sure you are Identify your and wish you the best of luck with the for all the rest of the coverage we have

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Matt Morgan, VMware, and Fred Wurden, AWS | VMware Cloud on AWS Update


 

>> Voiceover: From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi, I'm Stu Miniman, and welcome to this announcement with VMware cloud on AWS update. Happy to welcome back to the program, Matt Morgan. He is the Vice President of global marketing with VMware cloud services. And welcome into the program Fred Wurden, he's the general manager of EC2 enterprise at Amazon Web Services. Thank you so much both for joining us. >> Good to see you Stu. >> Same, thanks Stu. >> Matt, and Fred, the VMware AWS partnership is one that has gotten a lot of attention. I know any time back in the day when we used to go to physical trade shows, I could know when there was a session talking about this because it was usually full and overflowing. When I've written about this topic or doing videos about it it definitely gets quite a lot of attention. So it's been over three years since the partnership was announced but still, when I talk to people, they don't necessarily really understand the depth of the integration and the work that gets done on both sides even though you get clear messages from both Andy Jassy and Pat Gelsinger about how important this is. Matt, maybe start with you and Fred would love your commentary as to this three year partnership and where we are today here in 2020. >> Absolutely, since the initial announcement of the VMware AWS relationships, we have actually built a very special cloud service. And today, we're actually deepening our partnership. In fact, today, VMware goes to market saying that AWS and only AWS is our preferred public cloud partner for all vSphere based workloads. VMware cloud on AWS is a jointly engineered service. Meaning, our product teams our r&d teams are all working together to deliver VMware enterprise class Software Defined data center solution to the AWS cloud. VMware Cloud foundation is the core technology that's behind our service. And it gives us the capability to deliver that same level of infrastructure familiarity and consistency that our customers use today, across every data center location, the edge and of course inside the public cloud. VMware cloud on AWS attracts an enormous amount of interest from customers. And these customers are in every vertical, whether you're speaking of healthcare, media and entertainment, transportation, financial services, manufacturing, energy, government, education, professional services, and of course technology. And together with AWS, we're bringing together services that are being used across the whole portfolio of cloud optionality. This includes cloud migration from whether you're talking about a single app or complete data center, disaster recovery, whether you're talking about replacing a legacy system or building new disaster recovery in the cloud. Data center extension building that hybrid cloud. And of course, modernizing applications which we classify under the term application modernization. >> Great, and Fred from the Amazon side. >> Yeah, the partnership is been fantastic over three years. And I can't express enough how hard it is to actually deliver a simple solution that customers are asking for from all levels of both organizations. And to do that it takes both AWS and VMware to deliver a solution that allows companies to leverage what they know today and extend that into the cloud. And leverage all of the benefits that we're going to go over and a rapid delivery of new features which they haven't had before ever. So it's fantastic a partnership. I love what we've been doing at all levels. And I say it's going to continue. The scale at which we're growing is fantastic. And with that, I'm happy to go over some of the announcements and why we're doing what we're doing which is all based on listening and what our customers want. >> Excellent. Well, Fred, hey, we're glad first of all, that it did not get called VMC on AWS SS. Because we have enough acronyms already in tech. Matt, VMware and AWS, of course, clear leadership in the marketplace. With three years, bring us inside as to you talked about all the verticals that were used, but where's the proof on the adoption of this technology? Love to hear a little bit about that. >> Yeah, absolutely. So we have customer examples across the verticals we spoke of, but it's the customer stories that are the real value demonstrator. Let's pick up a couple of those. IHS market, they were able to move 1000 plus workloads to the public cloud. And that story is kind of common in the world. But what's unique about this particular story is IHS market moved them in just six weeks. If you look at the cloud migration strategy in general, for someone to move that fast with that many workloads, it's unheard of. VMware empowers that because the operating setup that organizations have standardized in their data center is identical in the public cloud. So organizations can move workloads we see them move hundreds of workloads in a week from their data center up to the public cloud. In addition to that, we have customer examples like the Pennsylvania Lumberman's Mutual Insurance Company. They were able to demonstrate 20% cost savings by moving their disaster recovery systems to VMware cloud on AWS. And that was initial savings right off the rip. Other customers like William Hill, George St. PA, Stage Coast, PHS Mortgage, they're all demonstrating the significant value adds when people move over to the public cloud, but leverage that VMware cloud solution. >> And Fred obviously, AWS also plays across these environments. We would like to hear your side too. >> Yeah, a couple examples like S&P global ratings, they spin up a new application environment in a few hours instead of months. Let alone taking all the burden off of their supply chain and management of that. Like Matt said in terms of seeing cost savings. So agility and speed allows them to really focus on their applications and start to modernize and innovate in areas that really differentiate them. They've had 100% uptime for regulatory applications and a 50% improved disaster recovery time. Other customers have built out a disaster recovery plan and then actually spun to VMware cloud on AWS as their primary because they had better performance. So it's the whole range of options in terms of better performance, better TCL and economics and mostly agility on what they can do going forward with applications that may already be built on AWS as well with native services. >> Matt, you touched on some great customer examples, maybe maybe give us some, broad themes as to what are the key drivers as to why customers are adopting VMware cloud on AWS? >> Yeah, absolutely. As with any infrastructure conversation, total cost of ownership is a big piece of the equation. Organizations want to look at their footprint today. They want to look at their footprint next year, and then of course, many years out. So when you look at the public cloud, cloud economics are a big driver. VMware, of course adopts the whole concept of cloud economics whole full horse. Meaning that we give you the capability to recognize the advantages of an apex object model, the ability to have on demand services, the ability to have a managed IaaS, all of that is part and parcel to our service. But on top of that, there's unique capabilities that VMware cloud on AWS delivers that deliver unique economic value. The first is this concept of zero refactoring. Our customers tell us that this alone allows them to eliminate what they call is rework, sometimes called the rework tax. Which prevents organizations from moving applications to the cloud without reworking them, without working their data layer, re architecting how they run, they can move them because the operating layer is consistent. Another area of value that's unique to VMware cloud on AWS is the leverage of existing skill sets. Today's operators are trained on vCenter. They're trained on all the supporting infrastructure around VMware. All of that applies with VMware cloud on AWS. So the ability to translate those skills into a cloud skill set right off the bat is of enormous value. Of course flexibilities another big one, as organizations embrace what it being seen as composite applications, which are applications that span the data center, the public cloud out to the edge. The ability to move logic as needed to be able to have portability is something we deliver. Again, that's an economic value that we are able to provide. Now this has been quantified by third parties. There's been several major third parties, including Forrester, including IDC, that have published value added statements around the total economic impact of VMware cloud on AWS. In fact, just last year, there was a study that was commissioned by Forrester that demonstrated a 59% reoccurring savings in terms of infrastructure and operating savings, compared to an on premise implementation. When you look at migration that accelerates to 69% 'cause organizations can save almost 70% of moving applications by eliminating rework and refactoring. That's an IDC statistic. >> All right Matt. Maybe it would make sense to talk about just overall adoption of the solution. I believe you've got some stats you can share. >> So yeah, if you look at the adoption, we have delivered enormous growth over the last year of the service. Total number of hosts year over year are up 2.5x. Total number of running VMs year over year is actually larger at 3.5x. Which indicates that customers are not just adopting, but they're accelerating their adoption. We now have 21,000 plus number of hands on labs that have been consumed since July of 2019, a year ago. And there are now 300 plus validated technology partner solutions available. And on top of that, 530 channel partners with VMware cloud service competency are now registered and available to assist. These are tremendous statistics for 12 short months. >> Well, congratulations on to both VMware and AWS on that progress. Maybe talk a little bit about trends. Just briefly, if I look over the last three months we've talked about AWS and VMware customers. Obviously, with the global pandemic, there's been certain things that they've needed to rapidly do things like, VDI, end user computing, remote contact centers are something that they need to rapidly expand on. But, is there anything different or general trends that that you would both like to share? Matt, we'll once again, start with you and then Fred get your take on it. >> Yeah, there's a regional school district in the US that in light of COVID, needed to spin up 10,000 plus people working remotely. And by leveraging VMware cloud on AWS, they were able to conduct virtual classrooms in very short order by leveraging this broad scale infrastructure powered by VMware cloud on AWS. Over time, that provided flexibility and agility, but it also reduced their costs. They've been able to eliminate hardware replacement plans that were going to cost significant amount of money. In fact, they're showing and telling us that they're able to save 75% of those forecasted costs. But everything is really about business continuity today. Today's unfortunate economic environment where we're working through this pandemic, this global pandemic, IT organizations and businesses, they're embracing a tried and true understanding of what it means to move to the cloud. But they're embracing it in a more aggressive way because the supply chain has been disrupted. If you think about a traditional supply chain, where organizations have to receive machines, set up those machines, have them wired in have certain people on site to get those machines configured, move application. That's a lot of steps in the process, many of which have been totally disrupted during the pandemic. The idea of VMware cloud on AWS is that you replace an analog supply chain with a digital supply chain. We can now help organizations get new equipment, new capacity, new resources up and running instantly. They don't have to worry about all the steps that were previously required that have been disrupted in a pandemic. The cloud provides that operating environment that maps one for one to the realities of today's world. And they're also able to understand that looking forward, that that setup enables them to be more future ready. Ready for whatever comes next to deliver what the business needs. >> Yeah, there's a number of reasons that you just touched on Matt, that are examples that we can bring out on that elasticity. For example, Penny Mac, anytime there are changes in the market, for example, on either both for VDI or just on processing of loans. When the pandemic hit, a lot of people actually paused on both looking and or changing their patterns. And this solution has been fantastic for either scaling up or scaling down both ways. And they can do it very quickly. They can do it within a number of a variety of means whether it's a single VM, or it's moving an entire migration into VMware cloud on AWS. So great results there. The case studies speak for themselves. There's a lot of examples that we have up on both of our sites. We'd really be good to take a look at those in detail if you're interested, it's fun to see. Helps a lot of people out. >> If I could follow up with you on something here. I want to talk about I go to the cloud, often that movement is step one, how do I take advantage of modernization, whether that be for my application standpoint, or leveraging new services? I wonder you can give me the AWS side there? And, Matt would love to hear how VMware is helping customers along this journey too. >> Well, the first is we want to meet people they're at with their knowledge set and their skill set. And this is a fantastic part. Customers can move quickly with the domain knowledge that they've go. We can assist in translating and making sure that the environment and the STDC is set up in a way that is tailored to what their needs are. Whether it's an extension, or if it's a complete migration of step one. But step two really is once they're leveraging VMware cloud on AWS is they have a lot of needs in terms of their CICD, their development tools, or samples and applications around automation. And we can take and help them with that. That content is already posted on our developer tool site and our developer center for this solution. It really assists them in learning about how to leverage the elasticity and the security and the networking capabilities that allow them to go in and then use all the rest of the rich AWS services as well. So, if you look at some of the things that are coming out for example, VMware Transit Connect. Which allows, a layer three solution to be built on top of our AWS transit gateway so that we can interconnect multiple VPCs in an environment that may be running either software as a solution on AWS or a native application that was built with managed services, completely in sync and in harmony, with VMware cloud on AWS. So that's what's happening at a rapid pace. It allows people to bite off the chunks that they want to modernize and reuse tools that are either familiar with them, and or automation improvements that we've got between code tools across the board. So it's great to see the work that they're doing >> Great, and Matt on the modernization piece. >> Yeah, so our surveys tell us that customers want to modernize their existing applications. But those same customers don't want to start over. So this is an important value proposition that we deliver in partnership with AWS. Organizations can take a business process application, they can migrate it to the cloud, they can extend and reach that application with AWS services. They can extend and reach that applications with additional machine learning capabilities, they can extend it with containerized extensions. They can support a broader modern agenda without having to start over. And I think that that is a value proposition that resonates with everyone, because people often need must leverage what they already have built with what the baseline is for the business itself. In addition to this, composite applications are now becoming the norm. With data and processing being more CO located, end to end Applications often consist of processing and data for certain tasks to be either pushed out to the edge or remain on premises in the data center in addition to the cloud. That value proposition of VMware delivering a hybrid cloud with consistent infrastructure and operations enables those composite applications to be built and deployed in a highly efficient way, which is a big piece to the modernization story. In addition to this with tons of Kubernetes grid as a customer managed option, organizations can run those containerized components right on top of our service, all of which integrates very cleanly with a whole library of services that AWS offers. End to end, you have all the optionality you need plus the speed of migration and capabilities once you get up to the public cloud. >> All right, let's get into the new pieces of the partnership here. Matt, first of all, when I think about VMware cloud on AWS, the customers that I've mostly spoken to over the last couple of years have tended to be some of the larger enterprises. I've heard you're alluding towards some capabilities to the small and medium business. I know I'm looking forward to talking to PLM insurance, one of the companies that are leveraging this solution as part of this announcement. What's new and the impact that this will have on the addressable market that VMware cloud can hit for AWS? >> Yeah, so with this announcement, VMware cloud on AWS, we're extending it to offer three new capabilities. Three new announcements of capabilities. The first one is all about what you just spoke of. Which is about extending the VMware cloud on AWS value proposition to more customers. So currently, customers can spin up production clusters with three hosts are, of course much more than that. But three hosts was kind of the entry level for a production cluster. What we're announcing is the ability to create production clusters with all the capable abilities that go into what we define as a production cluster with just two hosts. That means customers will be able to deploy production environments with two hosts in a cluster, dramatically reducing their costs. In fact, the traditional costs will come down by 33%. So this is all about providing the full capabilities of VMware cloud on AWS, but to be able to do it at a smaller investment envelope. So in addition to this, we're rolling out enhancements to VMware cloud director offering it as a service. VMware cloud director now will deliver multi tenancy to VMware cloud on AWS specifically designed for MSPs. As you know VMware partner ecosystem is filled with managed service providers. We have a mean enormous collection of these that add value on top of VMware cloud on AWS. Here by using VMware vcloud director service, they can deliver multi tenancy to their customers. And this is designed specifically to serve the needs of small to medium sized enterprises. These capabilities enable MSPs to serve those needs and it will be available initially in North America. And this will give them the opportunity to say, hey, if you want to get started on VMware cloud on AWS, we can give you bite sized pools designed specifically for what you need. And this is a very asset light pay as you grow model, which aligns specifically to that market. >> It's fascinating to watch Matt, I think, not that many years ago, if I had attended VMworld and talked to the MSPs. And they talk how deeply they appreciate the VMware partnership and that cloud company was the enemy. And, today AWS and VMware partnering with them, helping to make sure that in this hybrid world that they play a role to help get to the enterprise. Fred, anytime we go to reinvent, new announcements usually come to a huge fanfare, even something like a new bare metal instance. Last year it was the I3en metal instance. People get pretty excited. Help us understand you know what this really means, what advantages it has? Are there any limitations? What should we know about the capabilities AWS has now available to the VMware cloud? >> Well, first off, thanks Stu, I3en is really exciting that we're launching. It will meet the need of storage intensive workloads. And it'll do it far better than what we've had before. It takes advantage of all the learnings and the investments that we put into instances across the board for AWS such as Nitro. If you have, high random IO access, such as needed for relational database or workloads that have additional security that we have baked in, it's going to meet those needs. Compared to I3 metal, it has more memory, more usable, high performance storage and additional security. The example of a yield compared to I3 is about a 22% performance improvement and value. We're delivering four times the raw storage for about 2.2 times the cost. So in essence, you're getting raw storage at half the cost of an I3. So customers are excited. it's one of many instances that we will launch in the future for VMware cloud on AWS. And that's one of the advantages, is people can instantly take advantage of these innovations that we have. Just like we've done across all of the other instance families to meet workloads that customers are talking to us about that they want to run on this platform. >> Excellent, well, we really look forward. I know we're going to have a deep dive with Colbert to go into a little bit under the hood. And as I mentioned, got one of your joint customers PLM Insurance to understand their use case and how they're doing it. Matt and Fred, if you could just give us final takeaway, VMware cloud on AWS, Matt, and then Fred. >> Well, first off, thank you Stu for this opportunity to speak. I always enjoy spending time with you and certainly with Fred. We're just super excited and thrilled about our partnership. VMware couldn't be happier with our partnership with AWS from engineering to marketing, customer experience. Our teams are working together hand in glove to ensure success for our customers. VMware cloud on AWS is a truly unique service. Customers can continue business operations with minimal disruption in case of any uncertain event, they can migrate their workloads fast in a very cost effective manner with minimal risk. And we're really all about helping large enterprises as well as small and medium businesses accelerate their cloud migration and modernization journey. In fact, if you look across the board, we have seen enormous uptake. And now with these new offerings that we talked about, especially the two hosts production cluster, and VMware cloud Director service, we believe we're going to be more attractive to more organizations of various sizes. We're excited about the road ahead. >> And Fred. >> Customers are excited about this road, I would add. One, thank you guys for having us on. It's great to tell this story. The feedback has been phenomenal . The growth in the adoption and what we're seeing in terms of the use cases across the board is much stronger than we could have imagined. So it's really great to see this work that is hard to do to really merge the best of VMware and the best of AWS in a true deep partnership. And that takes work at all layers, whether it's a commerce system integration, or if it's the instance engineering and roadmap work across the board or networking. And customer support across the board for solutions that run on this platform. Both of us are joined to make sure customers are satisfied regardless of what it takes. That's something that no one else has. And it is unique. And it's a long term commitment that we have with each other to do the right thing for the solution. 'Cause we can't do it individually. This is something that truly only a joint partnership as strong as this is, and has gotten stronger can deliver. So we're super excited about it. I think you're going to continue to see the pace of innovation on what we're delivering increase. And so, with that, it's been great to work with VMware on this. It's really fun. >> Well, thank you, Fred. Thank you, Matt. Yeah, congratulation to your team. And of course, love hearing the customer stories and feedback. >> Thank you Stu. >> All right. Be sure to check out the other interviews as part of this announcement and check out theCUBE.net of course, we're covering VMware and AWS deeply including their shows whether they are in person or virtual. I'm Stu Miniman and thank you for watching theCUBE.

Published Date : Jul 15 2020

SUMMARY :

leaders all around the world, He is the Vice President of the integration and of the VMware AWS relationships, And leverage all of the benefits in the marketplace. of common in the world. And Fred obviously, AWS also plays and start to modernize So the ability to translate those skills sense to talk about just of hands on labs that have on to both VMware and AWS And they're also able to There's a lot of examples that we have up the cloud, often that movement that is tailored to what their needs are. the modernization piece. In addition to this with of the partnership here. the opportunity to say, that they play a role to across all of the other to go into a little bit under the hood. for this opportunity to speak. that we have with each other Yeah, congratulation to your team. Be sure to check out the

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Ben Nelson, Minerva Project | CUBE Conversation March 2020


 

(upbeat electronic music) >> Announcer: From the CUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hey welcome back already, Jeff Frick here with theCUBE. We're in our Palo Alto studios today having a Cube conversation. You know nobody can really travel, conference seasons are all kind of on hold, or going to digital, so there's a lot of interesting stuff going on. But thankfully we've got the capability to invite some of our community in. We're really interested in hearing from some of the leaders that we have in the community about what's going on in their world and you know, what they're telling their people. And what can we learn. So we're excited to have a good friend of mine who went to business school together, God it seems like it was over 20 years ago. He's Ben Nelson, the chairman and CEO of the Minerva Project. Ben great to see you and welcome. >> Thanks so much, great to be here. >> Yeah. So, you have always been kind of a trailblazer, I mean way back in the day I think that you've only had like two jobs in all this time, you know. (laughing) You know kind of changing the world of digital photography. >> Yeah three or four, three or four. >> Three or four. >> Yeah. (laughing) >> And after a really long run, you made this move to start something new in education. >> Yeah. >> Education's a big hairy monster. There's a lot of angles. And you started the Minerva Project, and I can't believe I looked before we got on today that that was nine years ago. So tell us about the Minerva Project, how you got started, kind of what's the mission, and then we'll get into it. >> Yeah so Minerva exists and it sounds somewhat lofty for an organization, but we do exist to serve this mission which is to nurture critical wisdom for the sake of the world. We think a wiser world is a better world. We think that really wisdom is the core goal of education and we decided that higher education is the area that is both most in need of transformation and also one that we're most capable of influencing. And so we set about actually creating our own university demonstrating an example of what a university can do. And then, helping tool other institutions to follow in those footsteps. >> Yeah it's a really interesting take. There's often times we're told if a time traveler came here from 1776, right, and walked around and would look at the way we drive, look at the way we communicate, look at the way we transact business. All these things would be so new and novel inventive. If you walked them over to Stanford or Harvard he'd feel right at home, you know. >> Yeah. >> So the education is still kind of locked in to this way that it's always been. So for you to kind of take a new approach, I mean I guess it did take actually starting your own school to be able to execute and leverage some of these new methods and tools, versus trying to move what is a pretty, you know, kind of hard to move institutional base. >> Yeah absolutely. And it's also you know, because we have to remember that universities as an institution started before the printing press. So if you go and talk to pretty much any university president, and ask him or her what is the mission of a university, generically, forget you know your university or what have you. They'll say, "Well generically universities exist "to create and disseminate knowledge." That's why they've been founded 1000 years ago and that's why they exist today. And you know, creation of knowledge I think there's a good argument to be made that the research mission of a university is important for the advancement of society and that it needs to be supported. Certainly directly in that regard. So much of you know the innovation that we benefit from today came from university labs and research. That's an important factor. But the dissemination of knowledge is a bit of an odd thing. I guess before the printing press, sure, yeah, I mean kind of hard to disseminate knowledge except for if you gather a whole bunch of people in a room and talk at them. Maybe they scribble notes very quickly. Well that's a decent way of disseminating knowledge because they can you know, one mouth and many pieces of paper and then they can read it later or study it. I guess that makes sense it's somewhat efficient. But after the printing press and certainly after the internet, the concept of a university needing to disseminate knowledge as it's core mission seems kind of crazy. It can't be that that's what universities are for. But effectively they're still structured in that way. And I don't think any university president when actually challenged in that way would argue the point. They would say, "Oh yes of course, "well what we really need to do is teach people "how to use knowledge or evaluate knowledge "or make sure that we communicate effectively "or understand how that knowledge can interact "with other pieces of knowledge and you know, "create new ways of thinking, et cetera." But that isn't the dissemination of knowledge. And that isn't the way that universities are actually structured. >> But it's funny that you say that. Even before you get to whether they should be still trying to disseminate knowledge, they're not even using the new tools now that they had the printing press that come along. (laughing) To disseminate knowledge. You know it's really interesting as we're going through this time right now with the coronavirus and a lot of things that were kind of traditional are moving in to digital and this new tool called Zoom which never fails to amaze me how many people are having their first Zoom call ever, right. >> Right, right. >> Ever, right I mean how long ago was Skype, how long ago was WebX. These tools have been around for a really interesting time, a long time. But now, you know, kind of a critical mass of technology that anybody can flip their laptop up, or their phone and go. You know you guys just in terms of a pure kind of tools play you know took advantage of the things that are available here in 2020 and 2019. So I wonder if you can share with the folks that don't have experience kind of using remote learning and remote access, you know what are some of the lessons you learned what are some of the best practice. What should people kind of think about what's capable and the things you can do with digital tools that you can't do when you're trying to get everybody in a classroom together at the same time. >> Right, so I think first and foremost, there's kind of the nuts and bolts. The basics. Right. So one of the things that you know, education environments have always been able to get away with is when you've got everyone in a room and you know, you're kind of cutting them off from the rest of life, you sometimes don't realize that you're talking into thin air, right. That maybe speaking students are not listening, they're not absorbing what you're saying. But you know they have to show up, at least in K 12, and higher ed they don't bother showing up and so the 15 people who do wind up showing up from the 100 person lecture I guess you do you say, "Oh at least they're listening." But the reality is that when you're online, you're competing with everything. You're competing with the next tab, you're competing with just not showing up. It's so much easier to just, you know, open up some game or something, some YouTube video. And so you've got to make this engaging. And making it engaging isn't about being entertaining. And that's actually one of the major problems of assessing who is a good professor and who isn't. You know people look at student reviews, right. They say, "Oh, you know such and such "was such a great professor." But when you actually track student reviews of professors to learning outcomes, there's a slight negative correlation. Right which means that the better the students believe the professor is actually that is an indicator that they've learned a little bit less. >> Right. >> That's really bizarre, intuitively. But when you actually think about it deeply, you realize that entertaining students isn't the job of a professor. It's actually teaching them. It's actually getting them to think through the material. And learning is hard, it's not easy. So you have to bring some of those techniques of engagement into online. And you can do that but it requires a lot of interactivity. So that's aspect number one. But really the much bigger idea isn't that you just do what you do offline and then put it online, right. Technology isn't at it's best when it mimics what you do without it, right. Technology didn't build an exact replica of the horse. >> Right, right. >> And said you know, ride that. Right. It doesn't make any sense, right. Instead, what technology should do is things you cannot do offline. One of the things that worked 300, 400 years ago is that you could study a subject matter in full. One professor, one teacher could teach you pretty much everything that people needed to know in a given field. In fact, the fields themselves were collapsed, right. Science, mathematics, you know, ethics were all put under this idea called philosophy. Philosophy was everything. Right. And so there's really we didn't have much to learn. But today, because we have so much information and so many tools to be able to process through that information, what happens is that education gets atomized. And you know you go through a college education you're you know, being taught by 25, 30 some different professors. But one professor really has no idea what you've learned previously. Even when they're in a 101, 102 sequence. How many times have we been in kind of the 102 class where in the first month all the professor did was repeat what happened in the 101 class because they didn't feel comfortable that you actually learned it. Or if the professor before them taught it the way they wanted it taught. >> Right, right. >> And that's because education is done offline with no data. If you actually have education in a data rich environment you can actually design cross cutting curriculum. You can shift the professor's role from disseminating knowledge to actually having students or mentoring students and guiding them in how to apply that knowledge. And so, once you have institutional views of curricula, you can use technology to deliver an institution wide education. Not by teaching you a way of thinking or a set of content, but giving you a set of tools that broadly any professor can agree on, and then apply them to whatever context professors want to present. And that creates a much more holistic education, and it's one that only can be done using technology. >> Ben that was a mouthful. You got into all kinds of good stuff there. (laughing) So let's break some of it down. That was fascinating. I mean I think you know the asynchronous versus synchronous opportunity if you will, to as you said kind of atomize education to the creation of content right the distribution of content and more importantly the consumption of content. Because why should I have to change my day if the person I want to hear is only available next Tuesday at noon pacific, right. It makes no sense anymore. And the long tail opportunities for this content that lives out there forever is pretty interesting. But it's a very interesting you know, kind of point of view if you assume that all the knowledge is already out there and now your job as an educator is to help train people to critically think about what's out there. How do I incorporate that, what are the things I should be thinking about when I'm integrating that into my decision. It's a very different way. And as you said, everything is an alt tab away. Literally the whole world is an alt tab away from that webinar. (laughing) Very good stuff. >> Exactly right. >> And the other piece I want to get your take on is really kind of lifetime learning. And I didn't know that you guys were you know kind of applying some of your principles oh my goodness where you actually measure effectiveness of teaching. And measure how long people hang out in the class. And measure whether it's good or not. But you're applying this really now in helping companies do digital transformation. And I think, you know, coming at that approach from a shift in thinking is really a different approach. I was just looking at an Andy Jassy keynote from a couple years ago yesterday, and he talked about the A number one thing in digital transformation is a buy in at senior leadership and a top down priority. So you know, what do you see in some of your engagements, how are you applying some of this principles to help people think about change differently? >> Yeah you know I think recessions are a very telling time for corporate learning. Right. And if you notice, what is the first budget that gets cut when economic times get tough it's the you know employee learning and development. Right. Those budgets just get decimated. Right off the bat. And that's primarily because employees don't see much value out of it, and employers don't really measure the impact of those things. No one's saying, "Oh my God, 'this is such an incredible program. "My employees were able to do x before this program, 'and then they were able to do one point five x afterward." You know, if people had that kind of training program in the traditional system, then they would be multi-billion dollar behemoths in the space. And there really are not. And that's because again, most of education is done in content land. And it's usually very expensive, and the results are not very good. Instead, if you actually think about learning tools as opposed to information, and then applying those tools in your core business, all of a sudden you can actually see transformation. And so when we do executive education programs as an example, you know we ask our learner how much of what you've learned can you apply to your job tomorrow? Right. And we see an overwhelming majority of our students are saying something like more than 80 to 90% of what they learned they can apply immediately. >> Wow, that's impressive. >> That's useful. >> Right. And why do you think is it just kind of institutional stuck in the mud? Is it the wrong incentive structure? I mean why you're talking about very simple stuff right. >> Yeah. >> Why don't you actually measure outcomes and adjust accordingly, you know. Use a data centric methodology to improve things over time, you know. Use digital tools in way that they can get you more than you can do in a physical space. I mean is it just inertia? I mean I really think this is a watershed moment because now everybody is forced into using these tools. Right. And there's a lot of, you know kind of psychology around habits and habit forming. >> Right, exactly. >> And if you do something for a certain amount of time every single day you know it becomes a habit. And if these stay in place orders which in my mind I think we are going to be doing it for a while, kind of change people's behavior and the way they use technology to interact with other folks. You know it could be a real, you know, kind of turning point in everyone's opening eyes that digital is different than physical. It's not exactly the same. There are some things in physical that are just better, but, you know there's a whole realm of things in digital that you cannot do when you're bound by time, location, and space. >> Exactly right. That's right. And I think the reason that it's so difficult to shift the system is because the training of people in the system, and I'm speaking specifically about higher education, really has nothing to do with education. Think about how a university professor becomes a university professor. How do they show up in a classroom? They get a bachelor's degree, where they don't learn anything about how to teach or how the mind works. They get a PhD, in which they learn nothing about how to teach or how the mind works. They do a post-doctoral research fellowship where they research in their field, right. Then they become an associate professor or an assistant professor and non-tenure, right. And in order to get tenure they've got seven years in order to make it on a publishing track, because how they teach is irrelevant. And they don't get any formal training on how to teach or how the brain works, right. Then they become you know, a junior tenured professor. A full tenured professor, right. And then maybe they become an administrator. Right. And so if you think about it, all they know is their field. And I've had conversations with academics which are to me befuddling, in the sense that you know they'll say, "Oh, you know, "everyone should learn how to think "like a historian. "Oh no everybody should learn to think "like an economist. "Everyone should learn to think "like a physicist." And you kind of unpack it, you say, "Well why?" And it's, "Oh well because we deploy pools "that nobody else deploys and it's so great." Right. And so it's OK give me an example. I had this conversation with a university president who was a historian. And that president said, "Look, you know, "what we do is we look at you know, "primary source materials hundreds of years ago "and learn to interpret what they say to us "and ascertain truth from that. "That's an incredibly important skill." I said, "OK, so what you're saying is you "examine evidence and evaluate that evidence "to see what it can actually tell you. "Isn't that what every single scientist, "social scientist, no matter what field they're in does? "Isn't that what a physicist does? "Isn't that what an economist does? "Isn't that what a psychologist does? "Right, isn't that what an English professor does?" Right actually thinking about I remember I took a mini module when I was an undergraduate with Rebecca Bushnell who is a literature professor, eventually became the dean of the college of arts and science at the University of Pennsylvania. And, we basically looked at a text written 400 years before, and tried to figure out what parts of the text were written by the author, what were transcription errors, and what was censored. That's looking at evidence. >> Right, right. >> This was an English professor. It's the exact same process. But because people know about it in their field and they think the only way to get to it is through their field, as opposed to teaching the tool, it can't get out of their own way. >> Yeah. >> And that's why I think education is so stuck right now. >> Yeah. That's crazy. And you know we're all victims of kind of the context in which we look through everything, and the lens in which we apply to everything that we see which is you know one of my things that there isn't really a kind of a truth it's what is your interpretation. And that's really you know, what is in your head. But I want to close it out. And Ben I really appreciate your time today. It's been a great conversation. And really kind of take it back to your mission which is around critical thinking. You know there's a lot of conversation lately, you know, this kind of rush to STEM as the thing. And there's certainly a lot of great job opportunities coming out of school if you're a data scientist and you can write in R. But what I think is a more interesting conversation is to get out of your own way. You know is the critical thinking as you know the AI and RPA and all these other things kind of take over more of these tasks and really this higher order need for people to think through complex problems. >> Right. >> I mean like we're going through today. Thank God people who are qualified and can see ahead and saw an exponential curve potential just really causing serious damage when we're still to head into this thing to take aggressive action. Dr. Sarah Cody here locally here you know, telling the San Jose Sharks you can't play. You know that is not an easy decision. But thankfully they did and they had the data. But really just your kind of thoughts on why you prioritize on critical thinking and you know can what you see with your students when they get out into the real world applying critical thinking not necessarily equations. >> Yeah look I think there's no better demonstration of how important critical thinking is than when you look at the kinds of advances that STEM is trying to make. Right. What happens any time we get a demonstration of the power of artificial intelligence, right. You remember a few years ago when Microsoft released it's AI engine. Right. Smartest engineers working on it, and all of a sudden it you know spat back misogynist racist types of perspectives. Why? The training set was garbage. It wasn't that the technology was bad, actually it was amazing technology. But the people who were writing it couldn't think. They didn't know how to think two steps ahead and say, "Wait a second, if we train "the information, kind of the random comments "we see on the internet, you know, "who bothers to write anonymomys comments?" Trolls, right. And so if we train it on a troll data set, it'll become an artificial intelligent troll. Right. It doesn't take a lot of critical thinking to actually realize that, but it takes some. >> Right. >> Right. And when you focus merely on those technical skills what you wind up doing is wasting it. Right. And so if you ground people in critical thinking, and we see this with our graduate. You know we graduated our very first class in May. And we had what as far as I can tell is the best graduate school placement of any graduating class in the country. As far as the quality of offers they got. We had a 94% placement rate in jobs in graduate positions. Which I think is tied with the very best ivy league institutions. And the kinds of jobs that the students are getting and six months into them the kinds of reviews that their employers are giving us looks nothing like a recent undergraduate. These are oftentimes types of jobs that are unavailable to recent undergraduates. And you know we had one student recently actually just told me, fresh in my mind, even though he was the youngest person in his company, when the CEO of his company has a strategic question he comes to him. And when he's in a meeting, full of PhDs, everybody looks to him to run the meeting and set the agenda. He's six months out of undergrad, right. And you know I can give you story after story after story about each and every one of these graduate. And it's not because they were born with it. They actually had a wise education. >> Yeah. Ben well that's a great story. And we'll leave it there. Congratulations again to you and the team at Minerva and what you've built and your first graduating class. Great accomplishment and really great to catch up, it's been too long. And when this is all over we'll have to get together and have an adult beverage. >> That would be wonderful. >> All right Ben thanks a lot. >> Thanks so much Jeff. >> All right. You've been watching theCUBE. Great check in with Ben Nelson. Thanks for watching. Everybody stay safe and we'll see you next time. (upbeat electronic music)

Published Date : Mar 31 2020

SUMMARY :

all around the world, this is a CUBE conversation. Ben great to see you and welcome. You know kind of changing the world Yeah. you made this move to start something new in education. And you started the Minerva Project, And so we set about actually creating he'd feel right at home, you know. you know, kind of hard to move institutional base. And it's also you know, because we have to remember But it's funny that you say that. and the things you can do with digital tools So one of the things that you know, But really the much bigger idea isn't that you just And you know you go through a college education And so, once you have institutional views of curricula, And as you said, everything is an alt tab away. And I didn't know that you guys it's the you know employee learning and development. And why do you think is it just kind of And there's a lot of, you know kind of psychology in digital that you cannot do when you're bound And that president said, "Look, you know, It's the exact same process. And that's really you know, what is in your head. and you know can what you see with your students "we see on the internet, you know, And you know I can give you story after story after story Congratulations again to you and the team Everybody stay safe and we'll see you next time.

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Donnie Williams, Scott Equipment & Eric Herzog, IBM | Cisco Live EU 2019


 

(funky upbeat music) >> Live from Barcelona, Spain. It's theCUBE covering Cisco Live! Europe. Brought to you by Cisco and its ecosystem partners. >> Welcome back to Barcelona everybody we're wrapping up day one of Cisco Live! Barcelona CUBE coverage. I'm Dave Vellante, he's Stu Miniman. You're watching theCUBE, the leader in live tech coverage. Donnie Williams is the IT Director at Scott Equipment out of Louisiana and Eric Herzog is back. He's the CMO of IBM Storage. Gentlemen, good to see you, welcome. >> Thank you. >> Thank you for having us. >> You're very welcome. So tell us about Scott Equipment. What do you guys do? What's the company all about? >> We're a heavy equipment dealer, so we've been in the business for 80 years, privately owned company. And so we started out in farm implement 80 years ago by the founder Tom Scott which is where the name Scott Equipment comes from. And so we transitioned over the years to construction equipment and we're now, so back in 2014 we sold all of our, the farm stores that handle all of that equipment, and now we're strictly servicing the construction industry and petrochemical industry. >> So you're a dealer of large equipment. And you service it as well, or? >> Yes we service it. We're primarily a rental company first. Then we also sell what we rent. We service it and it also parts as well. >> So we're talking massive? >> Yes big. If you think, one of our main clients is Volvo which if you've seen the show Gold Rush, that Volvo equipment that you see there, that's what we sell. >> It's incredible machines. >> Yeah, yeah they are I had a chance to play with one. I went to a Shippensburg Pennsylvania where their North America office is and had a chance to play with their largest excavator. That was fun. >> So is a lot of you IT centered on sort of the maintenance business and the service business or? >> Yes. Mostly Mirror is like a car dealership. So like I said, we do sale service, parts, all of that. >> So the business flow starts after the sale is made, obviously. >> Exactly, yes, we sell, yeah, exactly. We get the equipment out there in the territory and then the revenue continues to come in. >> So what are some of the challenges, the external challenges that are driving your business? >> So really, our, the whole heavy equipment industry is, is kind of behind the times in my, from a dealership perspective. From a manufacturer perspective. They're somewhat up with technology, especially Volvo, but from a dealership, they're mainly privately owned, so they're not, there's not a whole lot of resources in technology. That's not a focus for them. They're focused on the business side of it, so. When I first started at the company 10, 11 years ago now, there was one guy servicing 600 employees. And it was-- >> One IT person? >> One IT person. So, as you can imagine, it was a nightmare. I mean it's not the guy's fault. I don't blame him at all. It's just the way that they had done business and not changed. >> He was a bummed out IT person. >> Yeah, right exactly, yeah. >> Now how'd you guys find them? >> So they're a customer of ours for the verses stack. We have a partner that they've been buying their IBM and their Cisco gear from, and then when they were doing a modernization effort, the reseller talked to Scott and said, Donnie, what d'ya think? How about doing this converge infrastructure. Easier to employ at sep-tor. So it all came through their existing channel partner that they were using for both IBM gear and Cisco gear. >> So you wanted a solution that one guy could run, right? >> We've now at least grown that, our company to, now we have six total in our department. So we've changed a lot since I started 11 years ago. >> And what are they spending their time doing? >> Primarily, we do a lot of help desk, assistant administration, we do mostly, my focus is to make sure that our employees are satisfied so they can take care of the customer. And that's the primary goal and along with that comes systems administration, as well, so. >> But you know, a full stack like this. I mean the joke. You need more than one person. >> Right. But it's going to be simplified, you know what you're buying, >> Right, exactly. >> It's predictable, and therefore, you shouldn't need to be seen on a day to day basis. >> Yes, I like keeping things simple, simple as possible. So, that makes my job easier, it makes my team's job easier, as well. >> So what kind of things are you driving? Is it, ya know, data protection? Is it, what sort of, you know, use cases do you have on your stack? >> We're from our, we're servicing on our, with Cisco, I'm sorry, verses stack. It's mostly it's all private cloud. We're servicing applications that supplement our core ERP system. So, we have reporting solutions. When we first bought the verses stack, we were considering moving to another ERP system, and we would have that infrastructure in place to migrate to that. So we still have that, actually, element table as an option for us. >> The migration to a new ERP system? >> Yes. >> We should talk afterwords. >> We're avoiding that all costs. >> Right, well, of course. You don't want to convert if you don't have to. Yeah but sometimes it's a business case. Sometimes it's hard to make. We'll talk. >> Exactly. >> Cloud in your future or present? >> We're doing some-- >> SAS stuff, or? >> Yeah a little of that. I mean anything. I mean things that make sense for us to do cloud. Security services. We're doing, of course, probably the most common is hosting email. We're doing a lot of that. Share point. That type of solution in the cloud. >> How long you've been with the company? >> 11 years. >> 11 years, okay, so, thinking about the last decade, I mean a lot has changed. >> Yes. >> What are you most proud of? What's like your biggest success that you can share with us? >> Really building the IT department and bringing our company into the 21st century from a technology perspective. I mean, like I said, we had one person that was handling it. It was really impossible. I mean, you couldn't depend on one person and expect the company to survive long term. >> Yeah, that one person had to say no a lot. >> Exactly, right. He just couldn't get everything done. >> So, really that modernization and that's kind of where you guys came in, right? >> IT modernization play. The verses stack is heavily used for that and, you know, as we've said on the earlier interview, we had a CSPN. We've also used it to go to the next level from an IT transformation to the future. 'Cause in that case, as you know, that was a CSP who uses it to service, you know, hundreds of customers all across the UK in a service model. And in this case, this is more of a IT modernization, take the old stuff, upgrade it to what it was. They even had an old IBM blade servers. That's old this stuff was. Old XE6 Blade servers that must've been 10 years old before they went to the verses stack. >> How many people in the company? Roughly? >> Right now, we've actually sold off side since I've been with the company, we've sold off some of our nonperforming business units. We're probably roughly around 550 now. >> Okay. >> So I mean, we're actually more profitable now than we were 11 years ago. We have less employees, but our profitability is actually exceeded. >> Theme of simplification. >> Exactly, right. >> So what's the biggest challenge you face as the head of IT, today? >> The biggest, probably the biggest challenge would be me wanting to implement technologies that are not ready. I want to have the competitive edge of the industry. I want to be able to be ahead of the curve. And that's probably the biggest challenge. >> And you're saying you can't because the tech isn't ready? Or it's a skills issue? >> It's just the industry. Just trying to work with vendors and getting them to be ready for, I say vendors, manufacturers. They're our vendors. To get them to, and know their dealers as well. To all be acceptable to the technology's that's been there 20 years. >> What would you say is the top, number one, or the top things IBM has done to make your life easier? And what's the one thing they could to do that they're not doing that could make your life easier? What's the, start with what they've done. You know what the success is that have helped. >> Really, we've been a longtime IBM customer. We have not just the verses stack, but we also have the power system, which actually runs our core ERP. >> Ah, okay, so. >> So I mean, we've had long standing relationship with IBM. Reliability is there. The trust is there, as well. >> Yeah, long term partnership. Alright, what's the one thing they could do? If you could wave a wand and you said, IBM will to X, what would x be to make your life better? >> Cut the price. >> Ah, here we go! (all laughing) I should've prefaced that soon! Besides cut the price. Alright we'll leave it there on that topic. But you know, the power system thing brings up, you know, our friend Bob Piccano's running the cognitive systems group now. You guys doing some stuff with AI. Maybe talk about that a little bit. >> So what we've done is two things. First of all, we've imbued inside of our systems AI all over the place. So for example, we tier data which can do not only to own array, but literally to 440 arrays that have someone else's logo on them. It's all AI done. So when the data's hot, it's on the fastest tier. So if you have 15,000 RPM drives and 7,200 RPM drives, it goes to 15,000 when it cools off. AI automatically moves it. The storage admin does nothing. You don't set palsies AI takes care of it. We have Flash, and you have hard drives. Same thing. It'll move around. And you could have an IBM array talking to an EMC array. So all sorts of technology that we've implemented that's AI in the box. Then on top of that, what we've done is come up with a series of AI reference architectures for storage as one of the critical elements of the platform. So what we've done is create what we call a data pipeline. It involves not only our storage arrays, but four pieces or our software, spectrum scale, which is giant scale off file system, in fact, the two fastest supercomputers in the world have almost half an exabyte of that software, storage with that software. Our spectrum discover, which we announced in CUBE 4, which is all about better management of metadata. So, for AI workloads, big data analytic workloads, the data scientist doesn't prep the data. They can actually talk to what we do, and you can create all these metadata templates, and then boom, they run an AI workload on Thursday, and then run an analytic workload on Friday, but all automated. Our archive, and then our cloud object storage. So, all that is really, think about it more as an oval, because when you're doing an AI system, you're constantly learning. So the thing you got to do is, one, you've got to have high performance and be able to handle the analytics which you we do on Flash. 'Kay, so the Flash is connected. You've got to be able to move the data around and part of the thing with the Spectrum Discover is that we can talk through an API, to a piece of AI software, to piece of analytic software, to a piece of big data software. And they can literally go through that API, create templates for the metadata, and then automatically suck what they need into their app and then munge it and then spew it back out. And then obviously on the archive side, want to be able quickly recall the data because if you think about an AI system, it's like a human. So let's give you my Russian example. So I'm old enough, when I was a kid, there were bomb shelters in my neighborhood that people dug in the backyard. Then we have, you know, Nixon lighting up the Chinese. Then we have Reagan and Gorbachev. Next thing you know, the wall comes down, right? Then the next thing you know, there's no longer a Soviet Union. All of a sudden, ah, the Russians might be getting a little aggressive even though they're no longer communist, and now you see, depending on which political party, that they're totally against us, or they're totally helping us, but, you know, if they really were hacking systems, whatever political party you're in, they really were hacking our systems trying to manipulate the election. Pro or con, the point is that's kind of like a cyber attack. And that's not a good thing. So we learn and it changes. So an AI system needs to understand and change, constantly learn, if all of a sudden you have flying cars, that's going to be different than a car with tires. Now a lot of it may be the same. The interior, all the amenities, but the engines going to be different, and there are companies, including the big three, four, five, auto, who are actually working on flying cars. Who knows if it'll happen, but the AI system needs to understand and learn that and constantly learn. And so, the foundation has to heavily resilient, heavily performant, heavily available, last thing you want is an AI system going down on you. Especially if you're in healthcare, or big giant manufacturing, like Volvo, his customer. When they're building those cranes and things, they must cost 50, 60 million dollars. If that assembly line goes down, it's probably a big deal for them. So you need AI systems that always keep your other systems up and running. So you have to have that solid foundation of storage underneath. >> Awesome, alright, we got to leave it there. Give the customer the last word. Donnie, first time in Barcelona, right? >> Yes it is. >> How are you finding the show and the city? >> Oh it's awesome. This is my fifth Cisco Live. First time in Europe, so yeah. Enjoying it. >> Good, good. Well thank you guys for coming to theCUBE. >> Great thank you for coming. >> Thank you! >> Really appreciate it. >> You're welcome. Alright keep it right there everybody. We'll be back to wrap day one Cisco Live! Barcelona. You're watching theCUBE. (techno music)

Published Date : Jan 30 2019

SUMMARY :

Brought to you by Cisco and its ecosystem partners. Donnie Williams is the IT Director at Scott Equipment What's the company all about? the farm stores that handle all of that equipment, And you service it as well, or? Then we also sell what we rent. Gold Rush, that Volvo equipment that you see there, and had a chance to play with their largest excavator. So like I said, we do sale service, So the business flow We get the equipment out there is kind of behind the times in my, I mean it's not the guy's fault. the reseller talked to Scott and said, So we've changed a lot since I started 11 years ago. And that's the primary goal I mean the joke. you know what you're buying, you shouldn't need to be seen on a day to day basis. So, that makes my job easier, So we still have that, actually, You don't want to convert if you don't have to. probably the most common is hosting email. I mean a lot has changed. and expect the company to survive long term. Exactly, right. 'Cause in that case, as you know, since I've been with the company, So I mean, we're actually more profitable now And that's probably the biggest challenge. It's just the industry. or the top things IBM has done We have not just the verses stack, So I mean, we've had and you said, IBM will to X, But you know, the power system thing So the thing you got to do is, one, Give the customer the last word. This is my fifth Cisco Live. Well thank you guys for coming to theCUBE. We'll be back to wrap day one Cisco Live!

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Donnie Williams & Eric Herzog | Cisco Live EU 2019


 

>> Live from Barcelona, Spain. It's the cue covering Sisqo Live Europe, brought to you by Cisco and its ecosystem partners. Welcome back >> to Barcelona. Everybody would adapt. Wrapping up day one of Sisqo live Barcelona Cube coverage. I'm David. Long day. He's stupid men. You're watching the Cube. The leader in live tech coverage. Donnie Williams is it director at Scott Equipment out of Louisiana. And Eric hurts August back. He's the CMO of IBM storage. Gentlemen, good to see you. Welcome. >> Thank you for having us. >> You're very welcome. So tell us about Scott equipment. What do you guys do? Look, what's the company all about were >> a heavy equipment dealer, So we've been we've been in the business for eighty years, privately owned company. And so we're we're We started out and farm implement eighty years ago by the founder, Thomas Scott, which is where the name Scott equipment comes from. And so we transition over the years, Teo construction equipment, Andi were now back in two thousand fourteen, we sold all of our the farm stores that handled all of that equipment. And now we're We're strictly servicing the construction industry and petrochemical in >> history. So your dealer of exactly what equipment and your services as well? >> Yes. We service that we were primarily a rental company. First then then we We also sell what we rent. We service service it and and also parts as well. So we're talking massive? Yes, they got. If you if you think our one of our main lines is Volvo, which you have you have you seen the show? Gold rush that that Volvo equipment you see there, that's that's what we sell. So is incredible machine. Yeah, Yeah, they are. Hada chance tio to play with one. I went Teo Shippensburg, Pennsylvania. Where were their North America offices and had a chance to play with their largest excavator? That was That was >> fun. So is a lot of your Senate on sort of the maintenance business in the service business? >> Yes. So we were just mostly. Mirror is like a car dealership. If if you so we were like I said, we do sale service parts, all of that. >> So the business flow starts after the sale is made on >> exactly. Yes. We still like, Yeah, exactly. We get. We get equipment out there in the in the in the territory, and then the revenue continues tio to come in. >> So what are some of the challenges? The external challenges that are driving your business? You really >> are. The whole heavy equipment industry is It's kind of behind the times in my from a dealership perspective from from a manufacturer perspective there. They're somewhat up with technology, especially especially Volvo. But from a dealership there, there might mainly privately owned. So they're not there's not a whole lot of resource is in, and ah, in technology they don't. That's not a focus for them that they're they're focused on the business side of it. So what? We we're not When I first started the company ten, eleven years ago, now there was one guy servicing six hundred employees and and it was one eyed person, one i t person. So, as you can imagine, it was, it was a nightmare. Go. I mean, it's not the guy's fault. I don't blame him at all. Is this Is this the way that they had done business and not change bombed out, >> right? Exactly. Yeah. Guys >> find them. >> So their customer of ours for the versus stack, we have, ah, partner that they've been buying their IBM in their Cisco gear from. And then when they were doing a modernization effort, the reseller talk to Scott and said, Dani, what do you think? How about doing this? Converge infrastructure. Easier to play. It's after. So it all came through their existing channel. Part of that they were using for both IBM gear and Cisco Gear. >> So you wanted a solution. That one guy could run, right? We've now at least growing that company to house. We have six total in our in our department. So we've changed a lot since I started the eleven years ago. >> And why are they spending their time doing what? Premier >> Li? We do a lot of help desk on systems administration way do mostly, uh, are My focus is to make sure that our employees are satisfied that so they could take care of the customer, and that's that's the primary goal. And along with that comes comes systems administration. A cz. Well, so, But, >> you know, a full stack like this. I mean, the joke. You need more than one person, but it's going to be simplified. You know what you're buying, right? Predictable. And therefore, you shouldn't need to be seen on a basis. >> Yes, I like keeping things simple. Simple as possible. So that makes that makes my job easier. It makes my team's job easier. What >> kind of >> things you driving? Is it? You know, data protection, is it? You know what? What? What? What sort of, you know, use cases do you have on your stack >> on that Were from our were servicing on our with Francisco verse. Sorry versus stack. We are mostly it is all profit cloud were servicing applications. That's the supplement. Our court system. So we have reporting solutions. We were when we first bought it. The vs stack way were considering moving to another Air P system. Oh, and we would have that that infrastructure in place tio migrate to that. So we see what we still have that that actually on the table as a as an option >> for us, but the migration to a new Europe E system. Yes, we should talk afterwards. No, you >> were warning that it >> all about you. Of course, you don't want to convert if you don't have to write. But sometimes there's a business case. Sometimes it's hard to make you talk. Cloud in your in your future president were doing some that's ass stuff. >> Yeah, a little of that. I mean, anything. I mean things that that makes sense for us to to cloud I security services we're doing. Of course, probably most common is hosting email. Were doing a lot of that share point that that type of solution in the cloud >> How long you been with the company? Eleven years. Eleven years. Okay, So, thinking about the last decade, I mean, it's a lot of lot has changed. Yes. What's your What do you most proud of? What you like your biggest success that you can share with us. Oh, >> really? Building my the that dude the I T department and bringing our company into the twenty first system century from a from a technology perspective. I mean, like I said, we had one person that was that was handing. It was really impossible. I mean, you couldn't depend. Depends on one person. And and and, yeah, expect the company's or saw survive long term. Yeah, That one person had to say no a lot. Exactly. Right. Why would he? Just couldn't get everything >> done right? So that really that modernization? Yes, I know where you guys >> can. Ninety Mater, My team modernization play. The versus stack is heavily used for that. And, you know, as we said, on the earlier and every we had to see ESPN, we've also used it to do you know, to the next level from a night transformation to the future. Because in that case, as you know that was a CSP who uses it to service. You know, hundreds of customers all across the UK in a service model. And in this case, this is more of a mighty modernization. Take the old stuff, upgraded to what it was. They even have old IBM blade servers. That's how old the stuff wass old, actually, six played servers that must have been ten years old before they went to the Versus Stack. >> How many people in the company >> right now? We've actually sold off side since I've been with the company we sold off. Some of our non performing business units were probably roughly around five hundred fifty now. Okay, so I mean, we're Ah, we're actually more profitable now than we were eleven years ago from Ah, I mean, we have less employees, but our profitability is actually exceeded >> the name of simplification. Exactly. Right. So what's the biggest challenge you face Is the head of it today? The biggest, Probably >> the biggest challenge would be me wanting to implement technologies. They're not really not ready. I want it. I want tohave the competitive edge, that of the industry. I want to be able to be ahead of of the ahead of the curve. Uh, and that's probably the probably biggest challenge. And you're >> saying you can't Because the tech is ready or skills >> is just is just the industry just trying Teo. I work with vendors and getting getting them to be ready for I say, vendors, manufacturers, they're our vendors. Toe Get them Tio and other dealers as well. Teo Teo Albee. Acceptable to technology that's been there twenty years. >> What would you say is the but the top number one or the top things that IBM has done to make your life easier? And what's the one thing they could do that they're they're not doing that could make your life easier. What's the start with what they've done? You know whether successes, you know that >> really? Really. I mean, we've been a long time IBM customer. We have not, not just the versus Stack, but we also have the power system, which were actually runs are our core AARP. Um, okay. And so that we had long standing relationship with IBM, and the reliability is there. The trust is, >> there's well, a long term partnership. But what's the one thing they could do? One thing that you could If you could wave a wand and IBM will do x what would x B to make your life better? Uh, cut the price way. Go >> way. I should have prefaced that something that size >> on that topic. But you know, the power system thing brings up. You know, our friend Bob. Pity on who's running the cognitive systems group now You guys do with some stuff in a I talked about that a little bit. >> So what we've done is two things. First of all, we've been beauty inside of our system's ai ai all over the place. So, for example, we tear data which can weaken due not only to our own array, but literally two four hundred forty rays that have someone else's logo on them. It's all a eye dunce. When the data is hot, it's on the fastest here. So if you have fifteen thousand rpm drives in seventeen hundred rpm drives, it goes to fifteen thousand. When it cools off A. I automatically moves that the storage admin does nothing. You don't set policies, A takes care. We have flash and you have hard drive's same thing. It'll move around and you could have on IBM array talking to any AMC array. So all sorts of technology that we implement, that's a I in the box. Then, on top of that, what we've done is come up with a Siri's of a reference architectures for storage, as one of the critical elements in the platform. So we've done is create what we call a data pipeline. It involves not only our storage raise, but four pieces of our software spectrum scale, which is giant scale out file system, in fact, to fastest super computers in the world have almost half an exabyte of that software storage. With that software, our spectrum discover which we announced in queue for which is all about better management of metadata. So for a I workloads, big get anally work loves the data scientist doesn't prep the data. They can actually talk to what we do, and you could create all these meditate a template, then boom. They run a a ay workload on Thursday and then run a analytic workload on Friday. But all automated our archive and then our cloud objects towards. So all that is really think about it. Maura's an oval because when you're doing an A I system, you're constantly learning. So the thing you got to do is one you've got to have high performance and be ableto handle the analytics, which we do on flash. Okay, so the flashes connected, you've got to be able to move the date around. And part of thing with the spectrum Discover is that we can talk through an A P I to a piece of a AI software two piece of analytic software to piece of big data software, and they can literally go through that. AP I create templates for the metadata and then automatically suck what they need into their app and then munge it and then spirit back out and then obviously on the archives side, you want to be able to quickly recall the data, because if you think about a I system, it's like a human. So it's giving my Russian example. So I'm old enough. When I was a kid, there were bomb shelters in my neighborhood that people dug in the backyard. Then we have, you know, Nixon lightening up with the Chinese and we have Reagan and Gorbachev next, You know, the wall comes down right then. Next thing you know, there's no longer Soviet Union. All of a sudden, no, the Russians might get a little aggressive, even though they're no longer communist. And now, you see, depending on which political party. Either they're totally against us where they're totally helping us. But, you know, if they really were hacking systems whose whatever political party urine, they really were hacking our system, tried to manipulate the election pro or con. The point is, that's kind of like a cyber attack, and that's not a good thing. So we learn and it changes. So when a I system needs to understand and change constantly, learn. If all of a sudden you have flying cars, that's going to be different than a car with tires. Now, a lot of it, maybe the same, the interior, all the amenities. But the engine is going to be different. And there are companies, including the big Big three, four five who are actually working on flying cars, knows it will happen. But the A I system needs to understand and learn that and constantly learning. So the foundation has to be heavily resilient, heavily performance, heavily available, lasting one is an A I system going down on you, especially if you're in health care or big giant manufacturing. Like Volvo, his customer. When they're building those cranes and things, they must cost fifty sixty million dollars at that assembly line goes down its prey a big deal for them. So you need a I systems that always keep your other systems up and running. So you have to have that solid foundation storage underneath. >> Awesome. All right, we got to leave it there. Give the customer the last word. Donnie. First time in Barcelona, right? Yes. It ISS how you find in the show and the >> syphilis is awesome. This's my, actually my fifth, uh, Cisco lifers our first time in Europe, so yeah, enjoying it. >> Good. Good. Well, thank you, guys. For German of the >> correct. Thank you. Have you appreciate it? >> You're welcome. Alright. Keep right there, everybody. We'll be back to rap Day one. Sisqo live Barcelona watching you.

Published Date : Jan 29 2019

SUMMARY :

Sisqo Live Europe, brought to you by Cisco and its ecosystem partners. He's the CMO of IBM storage. What do you guys do? the construction industry and petrochemical in So your dealer of exactly what equipment and your services as well? Gold rush that that Volvo equipment you see there, that's that's what we sell. So is a lot of your Senate on sort of the maintenance If if you so we were like I said, we do sale service parts, the in the in the territory, and then the revenue continues tio to Go. I mean, it's not the guy's fault. right? to Scott and said, Dani, what do you think? So you wanted a solution. We do a lot of help desk on systems And therefore, you shouldn't need to be seen on a basis. So that makes that makes my job So we see what we still have that that actually on the table as a as an option No, you Sometimes it's hard to make you talk. Were doing a lot of that share point that that type of solution in the cloud What you like your biggest success that you can share with us. I mean, you couldn't depend. to do you know, to the next level from a night transformation to the future. now than we were eleven years ago from Ah, I mean, we have less employees, So what's the biggest challenge you Uh, and that's probably the probably biggest challenge. is just is just the industry just trying Teo. You know whether successes, you know that And so that we had long standing relationship with IBM, One thing that you could If you could I should have prefaced that something that size But you know, the power system thing brings up. So the thing you got to do is one you've It ISS how you find in the show and the uh, Cisco lifers our first time in Europe, so yeah, For German of the Have you appreciate it? We'll be back to rap Day one.

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Sameer Nori, Cohesity | Microsoft Ignite 2018


 

>> Live from Orlando, Florida, it's theCUBE, covering Microsoft Ignite. Brought to you by Cohesity and theCUBE's ecosystem partners. >> Welcome back everyone to theCUBE's live coverage of Microsoft Ignite. I'm your host, Rebecca Knight, along with my co-host Stu Miniman. We're joined by Sameer Nori, he is the director of product marketing at Cohesity. Thanks so much for coming on theCUBE, Sameer. >> Thanks Rebecca, and thanks Stu, and thanks for having me on theCUBE. I'm exciting to be here. >> So you are a tech veteran you've been in this industry for a long time, you've worked at a lot of kinds of companies, what drew you to Cohesity? >> That's a great question, so when I was at MAPR, and as you are familiar, MAPR sits at the intersection of big data and storage, and what I saw very interesting and fascinating about Cohesity was a similar hypothesis in terms of, having built its own file system but then really applying it to a different realm of the market, in terms of secondary data and applications starting with backup as the foundation. And as you are aware, analytics is a part of our road map and a solution that we enabled. But you know, some starter things there, but that's kind of actually what really drove me and the opportunity to really try and be part of another hybrid company and apply my experience from prior industries into different segments. >> So you lead outbound marketing for Cohesity's Cloud Solutions, tell our viewers a little about what you do, and what your day is like? >> Sure, so my day oscillates and changes between developing value prop and messaging for our solutions, working with customers to understand their pain points and challenges, being able to translate that into tangible benefits for customers to parley off of, and then really enabling and working with our sales teams closely to help them, arm them with the necessary things they need to go succeed in the market. >> Sameer you've got an interesting space, questions I think we all get in the industry is, things are changing a lot, what do I do with my applications? If you look at the enterprise, most enterprises have hundreds, if not thousands of applications, and it's not a trivial thing to say, oh well, yeah we'll just put everything in the cloud, that'll be real easy, right? You've got SaaS, Microsoft opened the door of the flood gates really pushing everybody to Office 365 to SaaS-ify a lot of what you are doing. Public cloud is a big growth and then private cloud really modernizing the environment, what are you seeing and hearing from customers as to how they deal with the portfolio of their applications mobility of what they're doing? Where does Cohesity play and advise and help with those solutions? >> Sure, that's a great question too. So I think really what we see from customers is a combination of a couple of things. As you said, they've got thousands or probably hundreds of applications, they are not going to take a big chunk of those and just move them to the cloud as is, right? You got to select the right workloads and the right data and do the assessment and the viability fit, in terms of what makes sense. I think where our sweet spot really is is kind of back to what I said earlier. Really sort of using back up as the foundation for what customers can do and our core hypothesis has always been that backup should not be just an insurance policy. You can do a whole lot more with it. So what we see customers doing is taking their backups on premises, which are often times just idle with alternative solutions, reusing them in the cloud for test dev purposes, where it makes sense. So the easy way to convert formats, so if you are in VMDK format to the VHD format in Azure. Spin it up, run your test of processes. At the end when you're done, you can move those things back on premises and really use it in that context. So for us really I think it's a combination of assessing the right use case and the right application of the workload. And then making that, helping customers with understanding that and making that shift in that case. >> So talk a little bit about the biggest customer pain points and how you develop the right solution for them in this customized and tailored way. >> Sure, so I think for us, from our perspective, what we are seeing with challenges, customers their back up data is sitting idle. It's shocking actually sometimes to hear that, if we're talking to IT and storage teams, and the application test and development teams with their peers, they often have to wait weeks, or sometimes even months, to get a copy of data that they need. I think in today's world that shouldn't be the case, right? Our value prop really there is to help eliminate those expensive copies of data that are getting made. And because our platform is so purpose built and agile with the effect of reusing that backup data for test dev, that's actually where we really see the sweet spot coming together. Customers have even asked us, for example in our UI, can you actually provision test dev data and make it more self-service in nature right from that view point. I think that is something we are looking into. Into what makes sense there from a capability. But that's kind of really actually where we see the challenge and how we are enabling customers into solving that. >> Yeah Sameer, I want to go back to something you said at the beginning about the premise of, I've got all my applications, and I'm going to have intelligence, usually called machine learning and the like. How are these going to come together? We hear Microsoft really talking about that's the future. Satya Nadella is well-known, you know AI, AI, AI, is one of the main things that he talks about. How is that similar with the Cohesity division? >> Yeah, so I think when we think about the application world and how we are taking advantage of things, like AI and machine learning. Our recently announced capability and product are on Helios, which is from our perspective the global management piece to manage all your secondary apps. We've injected machine learning and AI capabilities there to help customers with smart assistant type of mode and capability to help them predict their, how much, when they need more capacity. Smart alerts to tell them what's happening in their system. And that's kind of both on premises and in the cloud. For us really, I think where we see specifically AI and machine learning coming together. I think as customers are injecting those in the applications they are using. I think definitely the data side of it and how that effects the underlying data landscape will make a difference, in terms of how we accommodate that. But I think from a core ML and AI perspective, Helios is our focal point in terms of what we are doing to bring those capabilities to bear. >> So what has the customer response been to them? It sounds very cool. Are customers using it? Are they finding that it is being very, that it is helping them a lot, in terms of, as you said, notifying if they need more capacity. >> Yeah, so I think it's early days for us when it comes to Helios, right? It's a pretty new product, but we're working with customers actively, especially our existing base, to get them really on board with a product and really the service. Be able to collect and assimilate all of their data, and help them with the usage of it. I think the more data we collect, as you know with machine learning and AI, the more data you collect the richer sample set you have. You can do a whole lot more with it. I think when it comes to the application side of it, the discussion we had earlier on application mobility and making that. I think the University of Pennsylvania is an interesting example of a customer we have where they have about forty different websites internally and externally. They had a planned power, building shutdown for like a day. They had a problem where they couldn't get to recreate those sites easily from their prior infrastructure. So our CloudSpin capability, which is what really helps customers take their on premises VMs and reuse them in the cloud, really came to their rescue with helping them very easily make these websites quickly operational. For them it's been a few simple clicks, and then when they are done with that, when the disaster, in this case, a planned disaster was done, they both go back to their operational on premises. So that's I think a great example of our capabilities coming to light, and really shining in the app mobility arena. But also actually spill over in a sort of disaster recovery. >> Sameer, I'm curious. One of the other things in the application space is a lot of the new appplications, call them cloud native apps if you will, what are you hearing from customers, and does Cohesity, is there something different about new type of architectures and how that ties into Cohesity's solutions? >> Yeah, absolutely so I think what we are seeing from customers is when it comes to everything that's our applications born in the cloud. Often times I think what we see as backup is kind of actually a rear guard, it's not even thought of in the context of cloud native. I think we see that being a challenge because customers, I think what they've with backup in the cloud today, they've got either a combination of manual scripts, they've got some, you know, processes they're running there. There is a lack of automation. So we have actually integrated with the snapshot API of Azure, for instance, and Azure disks. We bring through a combination of what we do on the platform side and that integration we're actually able to bring enterprise class backup capabilities to that cloud native app. The backup they can experience there. So that's kind of I think where we are looking actually to do more, in terms of that. I think we are starting to see more demand, in terms of more cloud native backup as it relates to applications that are more born in the cloud. I think with us the beauty is it's a single platform that's going to work on premises and in the cloud. And not have a separate solution that's quote unquote, just for the cloud versus one that's for on premises. >> One of the biggest challenges that so many companies have regardless of their industry is getting employees to adopt new technologies. I'm wondering how closely you work with your customers to make sure that there is a wide spread adoption and a real embrace of the Cohesity solutions. >> Sure, I think to me what's fascinating is a big value prop and message for our customers with us is the simplicity. That ranges all the way from the way they can do their upgrades with us. The way actually our interface presents itself. So in most cases, actually I think what we've heard from customers is with little to minimal training they're able to actually get up and going with Cohesity. That actually speaks volumes, to the fact, in terms of how the product and the UI and everything else was designed. We definitely have a support and services team that is, as we are starting to grow more enterprise and work with larger customers, it's starting to have those programs in place to enable customers to get up to speed quickly. But actually, in often times, more often than not, it's more the case of, I could just set it up get it up and going and I'm off to the races. >> Sameer, it's our first time here at Microsoft Ignite, over 30,000 people are here, 5,000 organizations, what takeaways do you have for people that haven't been able to attend this show? What have you seen so far? >> Sure, no, I think what I've seen is that from our viewpoint, we've seen lot of customers. We've had some great sessions with customers. We've got a couple more coming up. I think the hybrid cloud message is definitely mainstream, right? I think for customers who are not taking advantage of the services that A, Microsoft has to offer, and then B, others ISVs like us plug into that ecosystem very closely. I think customers definitely should be embracing that in full steam and moving forward with their hybrid cloud initiatives. >> Great, well Sameer, thank you so much for coming on theCUBE, it was great having you. >> Thanks, Rebecca. Thanks, Stu, I appreciate it. >> I'm Rebecca Knight, for Stu Miniman We will have more from Microsoft Ignite in just a little bit. (upbeat music)

Published Date : Sep 25 2018

SUMMARY :

Brought to you by Cohesity and theCUBE's ecosystem partners. he is the director of product marketing at Cohesity. I'm exciting to be here. and the opportunity to really try for customers to parley off of, to Office 365 to SaaS-ify a lot of what you are doing. is kind of back to what I said earlier. So talk a little bit about the biggest customer and the application test and development teams and I'm going to have intelligence, and how that effects the underlying data landscape So what has the customer response been to them? and really the service. is a lot of the new appplications, because customers, I think what they've with backup and a real embrace of the Cohesity solutions. to actually get up and going with Cohesity. Sure, no, I think what I've seen is that Great, well Sameer, thank you so much Thanks, Rebecca. in just a little bit.

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Lynn Lucas, Cohesity | Microsoft Ignite 2018


 

(energetic music) >> Live from Orlando Florida, it's theCUBE, covering Microsoft Ignite. Brought to you by Cohesity, and theCUBE's ecosystem partners. >> Welcome back everyone, to theCUBE's live coverage of Microsoft Ignite here in Orlando, Florida. I'm your host, Rebecca Knight, along with my cohost, Stu Miniman. We're joined by Lynn Lucas. She is the CMO of Cohesity. Thanks so much for coming on the program, Lynn. >> Oh, just so excited to be here with you guys and host you in the Cohesity booth for the first time at Microsoft Ignite. >> It's been a lot of fun. There's a lot of buzz around here, and it's fun to be right, to be your neighbor. Exactly. >> Great. >> So today, there's been a lot of news, some new exciting announcements of integrations with Microsoft. I wonder if you can walk our viewers a little bit through what Cohesity announced today. >> Absolutely. So, we have been partners with Microsoft for some time, and today, we announced extensions to our capabilities with Microsoft Azure and Office 365. So Cohesity now extends data protection and backup for Office 365, including granular recovery of mailboxes and granular search for discovery purposes. We also have extended our integration with the Azure data box, and we also are increasing our DR capabilities for our customers with Azure so we now have fail back from the Azure Cloud for disaster recovery purposes. So, just continuing to see tremendous growth, hundreds of Microsoft customers with Cohesity, and these new capabilities are going to expand the possibilities for them. >> Lynn, it's an interesting conversation these days 'cause, you know, in our research, and we've talked about this, data's at the center of everything, and the challenge for customers is data's everywhere. You look here at the Microsoft show, well, I've got all my traditional stuff, I've got my SaaS stuff, my PubliCloud stuff, now Edge with the data box things there. Microsoft plays across there, and it sounds like Cohesity is playing in all of these areas, too. >> Absolutely, and I thought, you know, Sacha did such a good job in the keynote yesterday of really laying out the imperative for digital transformation, data being at the heart of it, but also laying out one of the key challenges which he pointed out, which is the data silos. And, I think Cohesity is right smack in the center of that conversation because we've always been about consolidating secondary data silos. And, you know, our partnership with Microsoft, really, I think, reinforces what they've been talking about, which is also a hybrid strategy that the bulk of customers that we talk to see that their data is going to be on premise, it's going to be in the cloud, and increasingly, it's goinna at the Edge, and we span all of those locations to create this one operating environment so that things like the new open data initiative, I think, will be much easier for customers because they won't be wondering, well, is my data all in one place to be operated on? >> So, talk about the problem of the data silos, because, as you said, it's one of the biggest challenges that companies face today. They are data rich and yet, this data's here and this data's here. Can you describe a little bit about what kind of problems this is for companies, and why this matters? >> So, I think it's just something folks are starting to really get a handle on. As I talked to individual folks here at the show, you'd be surprised at how many aren't even really sure, maybe, how many islands they have, you know, so, even mapping where is all my data, I think, is a capability that many organizations are still getting their arms around. And the challenge, of course, is that in today's world, it's very expensive to move large data sets, and so you want to bring compute to the data, which is what a hyper-convergence in Cohesity is about. And, when you look at the imperatives at the board level, the CEO level, they increasingly see that data becomes really the true competitive advantage for most organizations, and yet, if they can't operate or bring compute to that data and do something with it, they're really at a handicap. We call, you know, some of the newer companies are kind of data-centric or data natives, the Air BNB's, the, maybe, Netflixes of the world, not everyone aspires to be them. As well, not everyone has the resources that those companies may have had or just stay short period of time. Most organizations have the benefit of years of data. We want to level the playing field and allow them to become competitive with their data by providing that single foundation. >> Yeah, Lynn, it's a big show here. They said thirty thousand people and a really diverse ecosystem. What really surprised me is the spectrum of customers that you have here. I mean, we know Microsoft has a long history in higher education. We spoke to one of your customers, Brown University, and of course, long history they have with Microsoft. What are some of the things that you're hearing from customers, maybe, what's different at this show than some of the other, cloud and kind of younger shows that we might go to. This show's been around about almost thirty years now, so. >> Yeah, you know, isn't it, you know, I hate to give our ages but, I think we've been doing this for a while now, right? And Microsoft has been part of the IT ecosystem in a major way, and it's great to see the vibrancy here and how they're talking about AI and ML and moving forward with it. You know, what strikes me here is that a lot of the organizations here are now really understanding the pragmatism of having a hybrid strategy of what makes sense in the cloud as well as what may continue to be on prem for them. I think we complement that well. I'm really excited, too, about the idea that we are going to be using machine learning to be doing a lot more that humans simply can't keep up with in terms of the data growth and then doing something productive with that. And I think that's a conversation that we're just tapping the surface of here at this show. >> Yeah, you've said something that really resonated with me. You know, we have people that have been in the industry a while and, I look at you, your founder, Mohit, and this isn't his first rodeo. He'd been looking at data back from a couple of generations of solutions, and people are very excited. Machine learning, as you said, we used to talk about automation and intelligence around this environment. Now, I lived in the storage industry for quite a while, and we've talked about it but it feels more real when I talk to the architects and the people building this stuff. They are just so excited about what we will be able to do today that we talked about a decade or so ago but now really can make reality for customers. >> No, absolutely, and I think, you know, we have our own investment in that. Helios, which we announced just last month, you know, provides that machine learning capability because what we hear from our customers is what they love is the ability to have simplicity because, let's face it, IT environments continue to grow in complexity. They're looking for ways to subtract that complexity so they can apply their talents to solving the primary mission, as I call it, of their organization, whether that be public sector or private sector, adoing that in a simpler way. You know, look, one of the great stories that one of our customers is talking about here is how Cohesity helped him with a standard thing that most IT organizations have, which is, we're going to do a power shut down and we've got to perform a DR failover, and this particular organization, University of Pennsylvania Annenberg, had a set of twelve websites which, the professors and the students rely on, and it was going to take them literally almost a month to try to move them, and they didn't have that kind of time, and with Cohesity, with our DR capabilities, he was able to do that literally with a few clicks, kept the community of professors and students happy, and didn't spend, more importantly, twenty days trying to rebuild websites for a standard IT event, right? That's the kind of real life story in terms of what IT gets back that they can invest in other more important focus areas for their business. >> Well, for their business and also, just for their lives giving people their time back, their weekends back, their time at night >> Weekends and nights, right? >> With their families, yeah. >> We all need that. >> Satya Nadella is such a proponent of an improving workplace productivity, even five percent, he says, can make this big difference. Can you talk a little bit about how you view that workplace productivity at Cohesity and your approach to giving people either time to concentrate on more value for their companies or just their lives? >> So, again, a super story that we have from another customer that is here at Microsoft, and is an Azure customer, and a Cohesity customer. HKS, one of the world's most respected architectural firms, designed AT&T Stadium, there's a new major pediatric hospital going in in Dubai. They operate in ninety-four countries with remote designers and architects, and because of their inefficient backup processes and archive processes, they literally were having their associates have to work weekends as well as losing time on their projects, and time is money, and they, you know, in some cases, are penalized if they don't make certain dates. And so, I think, these are really pragmatic examples. On average here, pulling some of the folks here, I've heard that they can get a day a week back, sometimes for their administrator who now doesn't have to do repetitive manual tasks anymore. >> One of the things we always love digging into is, you talk about people's jobs and some of the new careers that are happening. We talked to one guest earlier this week. He said, if you're a customer and you learn Azure as what you're doing, like, you're resume is gold. We've talked to, and the really early Edge, like site reliability engineering, he said, don't put SRE on your resume or every recruiter will be calling you up and you won't even be able to answer your phone. Cohesity, you're doing a bit of hiring also. Maybe you could talk about- >> We are! >> What are you seeing from customers and what are you looking for internally? >> We have tremendous good fortune, we grew three hundred percent in revenues year over year, we're hiring in our RTP offices, in our San Jose, in India, around the globe. You know, we look for the best and the brightest, a lot of engineering talent, marketing talent as well, really, across the board but, you know, I think to the point you just made for the IT folks that are here, looking forward as to how you are going to help your business with your data infrastructure or data flows throughout their organization is, to me, where some of the career movement is happening when you hear the talk about how important it is to so many aspects of the business. >> And what are the sort of challenges that you're having with hiring, or are you? I mean, you're a red hot company, but, are you finding it difficult to find the kind of skills, the kind of talent that you want? I mean, what is, what's the candidate pool like? >> You know, so, I think what's really interesting, we are red hot, we have a lot of applicants so, I'd say, in general, no, we're very blessed that way. I think, though, more businesses, including ours, are finding it's difficult to get, say, those data scientists, right? Some of these also front end or back end developers, you know, it's not just the technical companies that are recruiting for that anymore. It's not just the Cohesitys and the Microsofts that are looking for that talent, but it's now also the Netflixes or, you know, the eBays, et cetera, right? They are all looking for the type of talent that we are and so, in general, I think that this bodes well for young people or folks really anywhere in their career watching about, thinking about, where the talent needs are, and there's a lot of activity and interest in people with those kinds of skills. >> You know, let me just follow up on that. So, Cohesity is a Silicon Valley-based company but, as you mentioned, you've got an RTP location. We've seen quite a lot of Silicon Valley-based companies that are starting to do a lot more hiring outside 'cause it's, I'm going to be honest, really expensive to live in the valley these days. So, any commentary on that dynamic? >> Well, you know, I think you're in Boston, not the lowest cost market either in the country. >> True, it's true! >> Yeah, you know, I think with a lot of the technology that's out there, you know, people don't have to be co-located, and we certainly also look to develop and invest in other communities around the globe, so we're not looking solely in San Jose but also in RTP, we've got headquarters in Europe as well as, of course, in India. So we look for talent everywhere, and, my own personal team, you know, I have folks basically around the US as well as across parts of the globe because talent, in many cases, is what matters and where you are physically, you know, some of the great technology that's out there can help break down those barriers of time and distance. >> Finally, this conference, it's thirty thousand people from five thousand different companies around the world. What is going to be, I mean, we're only on day two, but, what's been your big take-away so far? What's the vibe you're getting here at Ignite? >> You know, the vibe has been one of energy, of excitement. I've talked to a lot of folks from around the globe. I've been actually, pretty amazed at some of the people from different countries around the globe that are here, which is fantastic to see that draw in, and I feel like there's a general sense of excitement that technology and what Microsoft's doing can help solve some of the bigger challenges that are here, in the world, and for their own businesses, and we really look forward to Cohesity helping them lay that great data infrastructure foundation, consolidate their silos and help them build a foundation for, you know, doing more with their data. >> Great. Lynn Lucas, thank you so much for coming on theCube. It was great, great talking to you. >> Thank you. >> I'm Rebecca Knight for Stu Miniman. We will have more from Microsoft Ignite and theCube's live coverage coming up in just a little bit. (electronic music)

Published Date : Sep 25 2018

SUMMARY :

Brought to you by Cohesity, She is the CMO of Cohesity. Oh, just so excited to be here with you guys and host you and it's fun to be right, to be your neighbor. I wonder if you can walk our viewers a little bit and these new capabilities are going to expand and the challenge for customers is data's everywhere. that the bulk of customers that we talk to So, talk about the problem of the data silos, and allow them to become competitive with their data and of course, long history they have with Microsoft. is that a lot of the organizations here and the people building this stuff. No, absolutely, and I think, you know, Can you talk a little bit about how you view and they, you know, in some cases, are penalized and some of the new careers that are happening. I think to the point you just made for the IT folks but it's now also the Netflixes or, you know, the eBays, that are starting to do a lot more hiring outside Well, you know, I think you're in Boston, of the technology that's out there, you know, What's the vibe you're getting here at Ignite? that are here, in the world, and for their own businesses, Lynn Lucas, thank you so much and theCube's live coverage coming up in just a little bit.

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Eric Herzog, IBM Storage Systems | VMworld 2018


 

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and it's ecosystem partners. >> Welcome back to theCUBE. We are continuing our coverage of VMworld 2018 day 3. I'm Lisa Martin, with two very stylish men next to me. I'm quite impressed. Dave Vellante, my esteemed co-host. >> Oh shucks. >> Rocking the salmon, King Salmon Vellante. And The Zog is back, Eric Herzog. Great to have you back. I was looking at you on Twitter and you have been on theCUBE 17 times. Is this 18 or 19? >> You know, I think Dave said I was on one of the very first CUBEs way back in 2010. So I've been on a few. >> That's a whole other criteria of VIP level. Well thank you for coming back. You have been, not only is he, you can't do a CUBE without Eric Herzog. You've been everywhere all over VMworld. I saw you're speaking at IBM booth on VMware and IBM, you're at Cisco, you're giving sessions. How do you fit it all in and still have time for us? >> Well, I always make time for theCUBE. >> Always? Thank you, thanks for that. >> Always make time for you guys. Love talking to CUBE. You guys have been very helpful. We appreciate everything that you do. Love doing shows, love 'em. I may be 60 years old, but I'm really 18 down underneath, so if I only sleep three hours a night, not a problem. >> What do you love about them? I mean, is it? >> Number one is meeting customers. Customers and channel partners, right? Well, all of the employees of all the various companies here get a paycheck from whoever that may be, me, IBM, someone from other companies, people from VMware. That's not who pays your salary. It's the end-users and the channel partners, if they buy through the channel. They're the ones that really pay your salary. So being close to the customers and the partners is number one. Second thing, of course, is seeing all the cool technology. You know, seeing what's going on, what's hot, what can we leverage from our perspective, what can we tie ourselves to. So for example, the hot things, that IBM's really been doing from a storage perspective. Cloud and modern data protection. Those are the two big things we've been focused on for the last couple of years. And how do we integrate our storage solutions and our modern data protection with cloud infrastructure, and then also how do we, if you're not in the cloud, how do we help customers protect their data better in a modern way and reuse their secondary data, instead of making 27,000 copies of the same data. >> So when theCUBE first started at VMworld, modern data protection at the time was dealing with the lack of physical resources, 'cause you went from 10 servers down to one, and you didn't have all that excess capacity to do a run up back up job anymore. Today, modern data protection is all around cloud and multi-cloud and software defined, so I wonder if you can help us sort of paint a picture of what modern data protection is for IBM? >> Sure, I think there's a couple, couple aspects too. So, first of all, you have to support the cloud, and that's two ways. So for us, several of our backup products are used by cloud service providers. In some cases they use our name, and say, "Featuring IBM Spectrum Protect or Spectrum Protect Plus." Other cases, they have their own brand but it's our software underneath the hood so that if the end user is backing up to their cloud, they're actually using our software. So that's item number one. The second thing is you need to make sure that your traditional storage software can TEAR to the cloud, can migrate data to the cloud, can transparently move data to the cloud in an automated fashion using AI. So using artificial intelligent when the data's hot if you connote a target, and that target could be a cloud, and when the data's hot it TEARs the data to the cloud. Sorry, when it's cold. When it's hot it pulls it back in and that needs to be all automated through AI base. So we've done both, we have our backup software which is available from several cloud providers as a backup as a service, we also offer it through the cloud so IBM Cloud actually sells spectrum protect backup as a service solution All of our primary storage software and even our spectrum scale software can automatically TEAR data to a cloud target device. >> Eric I got to ask you so TEARing used to be predominantly, correct me if you disagree but, it used be a one way trip to the bit-bucket. You just described going there and coming back. Has cloud changed that because of big data, analytics? Where people want to pull back data increasingly? >> So I think of a couple of things. So first of all, there's no doubt that the world is data driven. The most valuable asset isn't gold, it's not silver, it is absolutely not oil, it's not diamonds. It is data. And it doesn't matter whether you're one of the largest banks in the world, you're in manufacturing, you're in the government, or whether you're Herzog's barn grill. The data is your most valuable asset. What you do with your customer data, how you manage your business, what you do with your supply chain if your a services company, how are you servicing, what are you charging, what are you billing, all of that is the most critical thing that you have. So in a data driven world, its critical that you use the data. And that also means that because of valued data, when you backup the data or you snapshot or replicate the data, you now created a secondary copy. Well what if you could use it to do tests? What if you could use it to do big data analytics? What if you could use it for DevOps? So instead of making one copy for tests, one copy for disaster recovery, one copy for this, and have basically a plethora of copies all over the place, with what we've provided in modern data protection, you can use a backup, you can use a snap or a replica, and you can use that to do tests or development or to do big data analytics. And using that one copy not making multiple copies. So that's- >> I just want to pick up on something you said there's going to be some folks in our audience like, "yeah yeah we hear that data is more valuable than oil or more valuable than gold, et cetera, more valuable than platinum." There's evidence, if you look at the market value of the top five companies, Apple, Facebook, Microsoft, Google, and Amazon, they've surpassed the banks, they've surpassed the energy companies, and I would argue its cuz of data. People are recognizing that they're data companies, you agree? >> But if you look at that name the only one that actually builds anything of substance, as a fair amount of their volume of revenue, is Apple. >> Is Apple, right. >> Amazon doesn't, they ship stuff. Facebook clearly doesn't, Google has a few things but not really builds stuff its really about the data. Absolutely and if your a more traditional company like a bank or someone building the table. Whoever builds this table if they have their act together and they're using that data right, they're building the table cheaper than anyone else, they're shipping it to theCUBE cheaper than anyone else could ship it to you. They got more colors because they know what their doing. And they ship you the right color table and they don't screw it up and send you a black table when you want it this color table because black won't show up on theCUBE very well. The more you do that the more money you make. Even something as simple as a table manufacturer. And that's all about the data and how you use that data. >> So Eric you love talking with customers which is great as the CMO for IBM storage. Got to talk to those customers. Let's talk about how you're seeing customers take the efficiencies of what IBM is doing with data protection, storage, et cetera. to be able to harness the power of AI, the superpowers that Pat Gelsinger talked about on Monday, and transform their businesses. Give us some of your favorite customer examples where its really revolutionary. >> So we had a great example today, we did a panel with a bunch of end users as part of the show agenda. And one of the customers is a provider of softwares of service to universities and schools. 45,000 customers between the universities, junior colleges, schools districts, et cetera. In North America so Canada and the U.S. And they are doing softwares of service so for them performance is critical, they can't go down. All of the college bookstores, if you go into a college bookstore, all of the infrastructure behind that is them. So they're called Follet. So a couple of things, one because they're doing softwares of service and managing all that. Its critical, can't go down. Got to be available, it's got to be performant, it's got to be resilient, it's got to be reliable. So that's how the storage melds in. From modern data protection the way it melds in is how many books did Dave buy? What did Eric buy? Oh is Dave buying a used book? Or is Eric buying a new book? Okay say we know that the propensity is certain of members of the community. I went to UC Davis, University of California Davis, are going to buy used books, Dave, whereas Herzog's going to buy new. They can figure that out, how many used books they need, how many new books they need, that's all about efficiency and how they make more money. What are the store hours? Certain universities it's this, other universities it's that. What do they do in the winter time? At UC Davis you can go in the winter time, I know you went to school in Boston its probably snowing, no one's going in the bookstore in the wintertime. >> Trend towards book rentals, how do we capitalize on that? >> That's all they do. One of the things they talked about was how they always have to protect that data and back it up. The other thing they talked about was they have to assume a lot of capacity. So what they do is they bought assuming they would have to refresh in 18 months. And because our storage arrays have a ton of different data reduction technology whether that be block, D2, compression, et cetera. And they have petabytes of data. Petabytes. 12 Petabytes. They've actually calculated it out they won't need to buy new storage for 36 months instead of 18 so they just saved on CapX. Through the intelligence of the storage. So in that case you've got both modern data protection and you've got a storage message. One of our other customers who's a public reference, not here at the show, which is a hospital, they were backing up all their data, both cloud and on premise with our backup software, and they went down and their entire system went down and they didn't lose one stitch of data and its a hospital. It's a teaching hospital, think they're in Pennsylvania, and in the public reference in the video he said, "and we went down and off that backup we were able to get all of the data back. We didn't lose any patient data, we didn't lose any research data, we didn't lose any billing data, if you break your arm they do bill you, they didn't lose anything." >> That's not just money, that's lives so that's huge. >> Absolutely. >> I want to ask you about you know that table example you were giving, and we were talking about the big five companies in terms of market cap being data orientated. There seems to be a gap between those sort of traditional companies and those data companies and that gap tends to be the data is often is often in silos its human expertise or expertise around a bottling plant or the manufacturing plant or whatever it is versus a data model with humans who understand how to leverage that data. Do you see, whether its through new data protection techniques or other storage techniques that IBM is working on, ways to help customers break down those data silos so they can become more digital and be able to take advantage of data? >> So I think there's a couple of things. So first of all at the very tactical level we provide this automated IA based data TEARing. We can tear from anything to anything so we can take data from an IBM array and TEAR it to an EMC array. We can take data from an EMC array and TEAR it to a net app array. A net app array to a Tachi array, an HP array back to our array, so we can do this transparent data move based on hot and cold. Not only does that allow you to control CapX and OpX you can move the data from array to array, and once you move that data set it might be working that other array could be hooked up to a different set of servers through the SAN that's running a different workload and then takes that dataset and use it with that other piece of software out on the server side. So that's item number one. Item number two is IBM not just in the storage but overall has a global program where IBM is promoting, through universities all over the world, data scientists. Part of that is training data scientists not only how to do the science of data and analyzing data and mining data and doing it, but to break down those walls. The value is more there. And we also have from a storage perspective some products are spectrum scale products, one of our customers who's one of the largest banks in the world they run 300,000 servers attached to a giant spectrum scale repository, petabytes and petabytes, and they do real time data analytics to see if Dave Vellante or Lisa's credit card was stolen. >> Thank you! >> Oh yes, thank you! >> So that's real world analytics they run but they need petabytes of data. And then with our IBM cloud object storage technology where we have several customers at the exabyte level in production with an exabyte of data, you put the data out when its cold but guess what, if you want to mine it you might want to pull it back and guess what, you can TEAR data from spectrum scale to IBM cloud object storage and then spectrum scale can pull it back in to do the big data analytic workloads. >> And that AI you're using is it heavy open source? Is there a little bit of Watson sprinkled in there? >> It's stuff the storage division developed years ago and then has peppered in the AI based technology into that software to determine when the dataset is hot or cold and then move it back or forth. We also do the old style, so if you go back 10 years ago, the automation of storage was policy based. So we had it way back when which was if the data is 30 days old move it to this array. >> The old HSM kind of... >> Yeah and it was automated so once it hit 30 days, but now what we've done is, we started with that, what I would call automation, and now we've moved that to AI. And by the way, if you still want to do it the old way and say move this data when its 60 days old, you can still do that. But the modern way is let the storage figure out for you and move it back and forth whether it be to the cloud or whether it be on premises. >> So it's intelligent hierarchical storage management? So if the characteristics change the system knows what to do as opposed to- >> So when it's hot it'll pull the data back into flash, for example, when its cold it'll put it out to cloud, it'll put it out to tape or it'll put it out to slow hard drives, either way. >> Alright Eric, so we're almost out of time here. You've been at IBM a long time, IBM's been around a long time, you said you even have customers at exabyte scale. I'm hearing heterogeneity, customer choice, but if I'm a small hospital in the middle of America and I have choice with data protection vendors, storage vendors, some smaller than IBM that might be able to move faster, what are the top three differentiators of why I would want to go with IBM's storage solutions? >> Sure so the first thing is our broad portfolio. Whether it be file block or object, whether it be modern data protection, whether it be archiving if you still want to use tape, we're the number one provider of tape in the world and we sell gobs of it to the web scale guys. >> Of course you do. >> They're the guys that buy it. >> Cuz its cost effective. >> So we've got one throat to choke, all of it talks to each other, and happens to work with all the cloud vendors not just IBM cloud. We work with Amazon, we work with Microsoft, we work with Google, and we work with IBM's own cloud. So we can work with anything. That's out of mind. Second thing, for smaller shops we have a network of business partners all over the world, some of them even deal with the big global Fortune 500 and others deal with small accounts. And then really the third thing is that IBM makes sure that our stuff works with everyone else's stuff. Whether that be cloud, our spectrum tech software which has been around for years and is the leading enterprise backup package, the bulk of what it backs up is not IBM storage. The vast bulk of it is from two of the competitors on the floor of this show, they also back up our stuff too. And we backup everyone's. There's probably 20 storage vendors we backup every one of their data. So if someone buys storage from XYZ, call me, we can back it up. If someone buys it from one of the big competitors we back it up, from us we back it up. So the fact that our software works with everyone's gear is of an advantage for both the small shop and the big shop. We make sure that our software, whether its embedded in our arrays or whether we sell it as just a pieces storage software and we are the number one storage software provider on the planet as well, we can meet the needs of any company big or small because we have this flexibility of working with our stuff and working with everybody else stuff and most of the other guys don't do that. If its a small shop their stuff usually only works with their stuff. >> And from a support perspective, you play with everybody? >> Global network. I mean we're known for our support whether it be IBM direct or what we do with our partners all the partners are certified, its a big certification process, and if they can't certify the product they can't sell IBM's stuff. That's just how we operate. Other people, if they can move a lot of boxes but they don't have anyone pick up the phone or can come out to Dave's house to install, they let them sell, we don't do that at IBM. We don't use those box mover types we go for guys that add value and know how to work with the cloud, know how to do hybrid cloud. One of our resellers designed a Watson based AI system that's used in bottle factories. Packaging. Beer, soda, milk, and it can figure out if its full or not full, if the bottle or can or carton is damaged. And they used Watson to do it. Now they're regular resell. They resell all the storage, they resell our power, they resell mainframe, but they've gone into the software development side using this Watson thing and they're selling a full solution with the software included to bottling plants all over the world. >> Wow, Eric. This has been a super charged conversation. Thanks for stopping by and talking with Dave and me about not just your excitement about talking with customers but really how IBM is really empowering customers of any size worldwide to succeed. We know we'll see you again soon but thanks for stopping by a couple of times this week. >> Great well thank you. Thank you, really appreciate the time. >> And the outfit choices are just on point guys, you blend well too. For Eric, Dave Vellante, I am Lisa Martin, you're watching theCUBE live from VMworld 2018 day 3. Stick around, we'll be back with our next guest after a short break. (electro music)

Published Date : Aug 29 2018

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Brought to you by VMware Welcome back to theCUBE. Great to have you back. So I've been on a few. you can't do a CUBE without Eric Herzog. Thank you, thanks for that. We appreciate everything that you do. and the partners is number one. and you didn't have all TEARs the data to the cloud. Eric I got to ask you so all of that is the most of the top five companies, But if you look at that name the more money you make. the efficiencies of what IBM all of the infrastructure and in the public reference That's not just money, and that gap tends to be the So first of all at the very tactical level the big data analytic workloads. if the data is 30 days And by the way, if you still pull the data back into flash, in the middle of America Sure so the first thing and most of the other guys don't do that. and know how to work with the cloud, We know we'll see you again Thank you, really appreciate the time. And the outfit choices

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Eric Herzog, IBM Storage Stystems | VMworld 2018


 

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and it's ecosystem partners. >> Welcome back to theCUBE. We are continuing our coverage of VMworld 2018 day 3. I'm Lisa Martin, with two very stylish men next to me. I'm quite impressed. Dave Vellante, my esteemed co-host. >> Oh shucks. >> Rocking the salmon, King Salmon Vellante. And The Zog is back, Eric Herzog. Great to have you back. I was looking at you on Twitter and you have been on theCUBE 17 times. Is this 18 or 19? >> You know, I think Dave said I was on one of the very first CUBEs way back in 2010. So I've been on a few. >> That's a whole other criteria of VIP level. Well thank you for coming back. You have been, not only is he, you can't do a CUBE without Eric Herzog. You've been everywhere all over VMworld. I saw you're speaking at IBM booth on VMware and IBM, you're at Cisco, you're giving sessions. How do you fit it all in and still have time for us? >> Well, I always make time for theCUBE. >> Always? Thank you, thanks for that. >> Always make time for you guys. Love talking to CUBE. You guys have been very helpful. We appreciate everything that you do. Love doing shows, love 'em. I may be 60 years old, but I'm really 18 down underneath, so if I only sleep three hours a night, not a problem. >> What do you love about them? I mean, is it? >> Number one is meeting customers. Customers and channel partners, right? Well, all of the employees of all the various companies here get a paycheck from whoever that may be, me, IBM, someone from other companies, people from VMware. That's not who pays your salary. It's the end-users and the channel partners, if they buy through the channel. They're the ones that really pay your salary. So being close to the customers and the partners is number one. Second thing, of course, is seeing all the cool technology. You know, seeing what's going on, what's hot, what can we leverage from our perspective, what can we tie ourselves to. So for example, the hot things, that IBM's really been doing from a storage perspective. Cloud and modern data protection. Those are the two big things we've been focused on for the last couple of years. And how do we integrate our storage solutions and our modern data protection with cloud infrastructure, and then also how do we, if you're not in the cloud, how do we help customers protect their data better in a modern way and reuse their secondary data, instead of making 27,000 copies of the same data. >> So when theCUBE first started at VMworld, modern data protection at the time was dealing with the lack of physical resources, 'cause you went from 10 servers down to one, and you didn't have all that excess capacity to do a run up back up job anymore. Today, modern data protection is all around cloud and multi-cloud and software defined, so I wonder if you can help us sort of paint a picture of what modern data protection is for IBM? >> Sure, I think there's a couple, couple aspects too. So, first of all, you have to support the cloud, and that's two ways. So for us, several of our backup products are used by cloud service providers. In some cases they use our name, and say, "Featuring IBM Spectrum Protect or Spectrum Protect Plus." Other cases, they have their own brand but it's our software underneath the hood so that if the end user is backing up to their cloud, they're actually using our software. So that's item number one. The second thing is you need to make sure that your traditional storage software can TEAR to the cloud, can migrate data to the cloud, can transparently move data to the cloud in an automated fashion using AI. So using artificial intelligent when the data's hot if you connote a target, and that target could be a cloud, and when the data's hot it TEARs the data to the cloud. Sorry, when it's cold. When it's hot it pulls it back in and that needs to be all automated through AI base. So we've done both, we have our backup software which is available from several cloud providers as a backup as a service, we also offer it through the cloud so IBM Cloud actually sells spectrum protect backup as a service solution All of our primary storage software and even our spectrum scale software can automatically TEAR data to a cloud target device. >> Eric I got to ask you so TEARing used to be predominantly, correct me if you disagree but, it used be a one way trip to the bit-bucket. You just described going there and coming back. Has cloud changed that because of big data, analytics? Where people want to pull back data increasingly? >> So I think of a couple of things. So first of all, there's no doubt that the world is data driven. The most valuable asset isn't gold, it's not silver, it is absolutely not oil, it's not diamonds. It is data. And it doesn't matter whether you're one of the largest banks in the world, you're in manufacturing, you're in the government, or whether you're Herzog's barn grill. The data is your most valuable asset. What you do with your customer data, how you manage your business, what you do with your supply chain if your a services company, how are you servicing, what are you charging, what are you billing, all of that is the most critical thing that you have. So in a data driven world, its critical that you use the data. And that also means that because of valued data, when you backup the data or you snapshot or replicate the data, you now created a secondary copy. Well what if you could use it to do tests? What if you could use it to do big data analytics? What if you could use it for DevOps? So instead of making one copy for tests, one copy for disaster recovery, one copy for this, and have basically a plethora of copies all over the place, with what we've provided in modern data protection, you can use a backup, you can use a snap or a replica, and you can use that to do tests or development or to do big data analytics. And using that one copy not making multiple copies. So that's- >> I just want to pick up on something you said there's going to be some folks in our audience like, "yeah yeah we hear that data is more valuable than oil or more valuable than gold, et cetera, more valuable than platinum." There's evidence, if you look at the market value of the top five companies, Apple, Facebook, Microsoft, Google, and Amazon, they've surpassed the banks, they've surpassed the energy companies, and I would argue its cuz of data. People are recognizing that they're data companies, you agree? >> But if you look at that name the only one that actually builds anything of substance, as a fair amount of their volume of revenue, is Apple. >> Is Apple, right. >> Amazon doesn't, they ship stuff. Facebook clearly doesn't, Google has a few things but not really builds stuff its really about the data. Absolutely and if your a more traditional company like a bank or someone building the table. Whoever builds this table if they have their act together and they're using that data right, they're building the table cheaper than anyone else, they're shipping it to theCUBE cheaper than anyone else could ship it to you. They got more colors because they know what their doing. And they ship you the right color table and they don't screw it up and send you a black table when you want it this color table because black won't show up on theCUBE very well. The more you do that the more money you make. Even something as simple as a table manufacturer. And that's all about the data and how you use that data. >> So Eric you love talking with customers which is great as the CMO for IBM storage. Got to talk to those customers. Let's talk about how you're seeing customers take the efficiencies of what IBM is doing with data protection, storage, et cetera. to be able to harness the power of AI, the superpowers that Pat Gelsinger talked about on Monday, and transform their businesses. Give us some of your favorite customer examples where its really revolutionary. >> So we had a great example today, we did a panel with a bunch of end users as part of the show agenda. And one of the customers is a provider of softwares of service to universities and schools. 45,000 customers between the universities, junior colleges, schools districts, et cetera. In North America so Canada and the U.S. And they are doing softwares of service so for them performance is critical, they can't go down. All of the college bookstores, if you go into a college bookstore, all of the infrastructure behind that is them. So they're called Follet. So a couple of things, one because they're doing softwares of service and managing all that. Its critical, can't go down. Got to be available, it's got to be performant, it's got to be resilient, it's got to be reliable. So that's how the storage melds in. From modern data protection the way it melds in is how many books did Dave buy? What did Eric buy? Oh is Dave buying a used book? Or is Eric buying a new book? Okay say we know that the propensity is certain of members of the community. I went to UC Davis, University of California Davis, are going to buy used books, Dave, whereas Herzog's going to buy new. They can figure that out, how many used books they need, how many new books they need, that's all about efficiency and how they make more money. What are the store hours? Certain universities it's this, other universities it's that. What do they do in the winter time? At UC Davis you can go in the winter time, I know you went to school in Boston its probably snowing, no one's going in the bookstore in the wintertime. >> Trend towards book rentals, how do we capitalize on that? >> That's all they do. One of the things they talked about was how they always have to protect that data and back it up. The other thing they talked about was they have to assume a lot of capacity. So what they do is they bought assuming they would have to refresh in 18 months. And because our storage arrays have a ton of different data reduction technology whether that be block, D2, compression, et cetera. And they have petabytes of data. Petabytes. 12 Petabytes. They've actually calculated it out they won't need to buy new storage for 36 months instead of 18 so they just saved on CapX. Through the intelligence of the storage. So in that case you've got both modern data protection and you've got a storage message. One of our other customers who's a public reference, not here at the show, which is a hospital, they were backing up all their data, both cloud and on premise with our backup software, and they went down and their entire system went down and they didn't lose one stitch of data and its a hospital. It's a teaching hospital, think they're in Pennsylvania, and in the public reference in the video he said, "and we went down and off that backup we were able to get all of the data back. We didn't lose any patient data, we didn't lose any research data, we didn't lose any billing data, if you break your arm they do bill you, they didn't lose anything." >> That's not just money, that's lives so that's huge. >> Absolutely. >> I want to ask you about you know that table example you were giving, and we were talking about the big five companies in terms of market cap being data orientated. There seems to be a gap between those sort of traditional companies and those data companies and that gap tends to be the data is often is often in silos its human expertise or expertise around a bottling plant or the manufacturing plant or whatever it is versus a data model with humans who understand how to leverage that data. Do you see, whether its through new data protection techniques or other storage techniques that IBM is working on, ways to help customers break down those data silos so they can become more digital and be able to take advantage of data? >> So I think there's a couple of things. So first of all at the very tactical level we provide this automated IA based data TEARing. We can tear from anything to anything so we can take data from an IBM array and TEAR it to an EMC array. We can take data from an EMC array and TEAR it to a net app array. A net app array to a Tachi array, an HP array back to our array, so we can do this transparent data move based on hot and cold. Not only does that allow you to control CapX and OpX you can move the data from array to array, and once you move that data set it might be working that other array could be hooked up to a different set of servers through the SAN that's running a different workload and then takes that dataset and use it with that other piece of software out on the server side. So that's item number one. Item number two is IBM not just in the storage but overall has a global program where IBM is promoting, through universities all over the world, data scientists. Part of that is training data scientists not only how to do the science of data and analyzing data and mining data and doing it, but to break down those walls. The value is more there. And we also have from a storage perspective some products are spectrum scale products, one of our customers who's one of the largest banks in the world they run 300,000 servers attached to a giant spectrum scale repository, petabytes and petabytes, and they do real time data analytics to see if Dave Vellante or Lisa's credit card was stolen. >> Thank you! >> Oh yes, thank you! >> So that's real world analytics they run but they need petabytes of data. And then with our IBM cloud object storage technology where we have several customers at the exabyte level in production with an exabyte of data, you put the data out when its cold but guess what, if you want to mine it you might want to pull it back and guess what, you can TEAR data from spectrum scale to IBM cloud object storage and then spectrum scale can pull it back in to do the big data analytic workloads. >> And that AI you're using is it heavy open source? Is there a little bit of Watson sprinkled in there? >> It's stuff the storage division developed years ago and then has peppered in the AI based technology into that software to determine when the dataset is hot or cold and then move it back or forth. We also do the old style, so if you go back 10 years ago, the automation of storage was policy based. So we had it way back when which was if the data is 30 days old move it to this array. >> The old HSM kind of... >> Yeah and it was automated so once it hit 30 days, but now what we've done is, we started with that, what I would call automation, and now we've moved that to AI. And by the way, if you still want to do it the old way and say move this data when its 60 days old, you can still do that. But the modern way is let the storage figure out for you and move it back and forth whether it be to the cloud or whether it be on premises. >> So it's intelligent hierarchical storage management? So if the characteristics change the system knows what to do as opposed to- >> So when it's hot it'll pull the data back into flash, for example, when its cold it'll put it out to cloud, it'll put it out to tape or it'll put it out to slow hard drives, either way. >> Alright Eric, so we're almost out of time here. You've been at IBM a long time, IBM's been around a long time, you said you even have customers at exabyte scale. I'm hearing heterogeneity, customer choice, but if I'm a small hospital in the middle of America and I have choice with data protection vendors, storage vendors, some smaller than IBM that might be able to move faster, what are the top three differentiators of why I would want to go with IBM's storage solutions? >> Sure so the first thing is our broad portfolio. Whether it be file block or object, whether it be modern data protection, whether it be archiving if you still want to use tape, we're the number one provider of tape in the world and we sell gobs of it to the web scale guys. >> Of course you do. >> They're the guys that buy it. >> Cuz its cost effective. >> So we've got one throat to choke, all of it talks to each other, and happens to work with all the cloud vendors not just IBM cloud. We work with Amazon, we work with Microsoft, we work with Google, and we work with IBM's own cloud. So we can work with anything. That's out of mind. Second thing, for smaller shops we have a network of business partners all over the world, some of them even deal with the big global Fortune 500 and others deal with small accounts. And then really the third thing is that IBM makes sure that our stuff works with everyone else's stuff. Whether that be cloud, our spectrum tech software which has been around for years and is the leading enterprise backup package, the bulk of what it backs up is not IBM storage. The vast bulk of it is from two of the competitors on the floor of this show, they also back up our stuff too. And we backup everyone's. There's probably 20 storage vendors we backup every one of their data. So if someone buys storage from XYZ, call me, we can back it up. If someone buys it from one of the big competitors we back it up, from us we back it up. So the fact that our software works with everyone's gear is of an advantage for both the small shop and the big shop. We make sure that our software, whether its embedded in our arrays or whether we sell it as just a pieces storage software and we are the number one storage software provider on the planet as well, we can meet the needs of any company big or small because we have this flexibility of working with our stuff and working with everybody else stuff and most of the other guys don't do that. If its a small shop their stuff usually only works with their stuff. >> And from a support perspective, you play with everybody? >> Global network. I mean we're known for our support whether it be IBM direct or what we do with our partners all the partners are certified, its a big certification process, and if they can't certify the product they can't sell IBM's stuff. That's just how we operate. Other people, if they can move a lot of boxes but they don't have anyone pick up the phone or can come out to Dave's house to install, they let them sell, we don't do that at IBM. We don't use those box mover types we go for guys that add value and know how to work with the cloud, know how to do hybrid cloud. One of our resellers designed a Watson based AI system that's used in bottle factories. Packaging. Beer, soda, milk, and it can figure out if its full or not full, if the bottle or can or carton is damaged. And they used Watson to do it. Now they're regular resell. They resell all the storage, they resell our power, they resell mainframe, but they've gone into the software development side using this Watson thing and they're selling a full solution with the software included to bottling plants all over the world. >> Wow, Eric. This has been a super charged conversation. Thanks for stopping by and talking with Dave and me about not just your excitement about talking with customers but really how IBM is really empowering customers of any size worldwide to succeed. We know we'll see you again soon but thanks for stopping by a couple of times this week. >> Great well thank you. Thank you, really appreciate the time. >> And the outfit choices are just on point guys, you blend well too. For Eric, Dave Vellante, I am Lisa Martin, you're watching theCUBE live from VMworld 2018 day 3. Stick around, we'll be back with our next guest after a short break. (electro music)

Published Date : Aug 28 2018

SUMMARY :

Brought to you by VMware Welcome back to theCUBE. Great to have you back. So I've been on a few. you can't do a CUBE without Eric Herzog. Thank you, thanks for that. We appreciate everything that you do. and the partners is number one. and you didn't have all TEARs the data to the cloud. Eric I got to ask you so all of that is the most of the top five companies, But if you look at that name the more money you make. the efficiencies of what IBM all of the infrastructure and in the public reference That's not just money, and that gap tends to be the So first of all at the very tactical level the big data analytic workloads. if the data is 30 days And by the way, if you still pull the data back into flash, in the middle of America Sure so the first thing and most of the other guys don't do that. and know how to work with the cloud, We know we'll see you again Thank you, really appreciate the time. And the outfit choices

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John White, Expedient | ZertoCON 2018


 

(light techno music) >> Announcer: Live from Boston, Massachusetts, it's The Cube. Covering ZertoCon 2018. Brought to you by Zerto. >> This is The Cube. We're at ZeratoCon 2018, Hines Convention Center in Boston. My name's Paul Gillin. My guest is John White, the VP of Product Strategy at Expedient. Why don't you start off by giving us just the elevator pitch on what Expedient is all about. >> Sure, Expedient is a cloud-service provider as well as managed service provider, and we also have data centers that we operate here mainly on the east coast. We have seven cities and 11 data centers. Those are in Boston here, locally as well as Baltimore, Maryland, Pittsburgh, Pennsylvania, Cleveland, Columbus, Indianapolis, and Memphis, Tennessee. And then we actually, we'll put our private cloud services really anywhere. So we actually will put 'em on the customer's premises to meet that need as well as in partner data centers anywhere over the world, if they have to deal with compliance, security, whatever it might be, we'll go and tackle those problems for them. So our goal is to be an infrastructure as a service provider for, you know, really all the enterprise. >> So, when would a company do business with you verses a Microsoft or an Amazon? >> Yeah, so, if you kind of look at really three ways to kind of go cloud, right? You can still do it yourself. You can build some cloud-based services. And that's, again, you're in it on your own. You can go all the way to the extreme, which is the AWS or the Azures, and that's more, again, you're kind of in a do-it-yourself type of mentality. And your support structure there is a little bit different. It's maybe a little bit more mechanical, a little bit more robotical. If you need help in transitioning and figuring out where your workload should sit, and maybe creating more of a hybrid cloud so it's maybe on your premises, it's inside one of our data centers, and then maybe it's even in one of those AWS or Azures. You're going to work with a company like Expedient to go and help you figure out where you should put your workloads, first off. And then how to create that long-term strategy so you get the best of all worlds that are out there, not just one prescriptive cloud. >> So, you're kind of a high-touch cloud provider then. >> Very, very high touch, yeah. Our whole product service is actually a la carte menus. So you pick and choose what you want. We can manage servers, we can provide virtual infrastructure, we can do things like DR as a service, backups as a service, all those pieces. So you build, basically, your perfect IT strategy with us. And then direct connects into AWS and Azure and some other cool products coming soon to kind of make your life a little bit easier, consuming and running your work loads in public clouds. >> Well we hear a lot these days about multi-cloud, about customers wanting to shift their work load seamlessly around between multiple back-end cloud providers. Certainly vendors talk about that a lot. Do you hear customers talking about it? >> Yeah, we have some customers starting to talk about it. And, you know, in the beginning, they just wanted to see, okay, I'm running workloads in AWS, I'm running workloads in Expedient, I'm multi-cloud. And then they start to understand. well, our management's really hard. And the network's really hard, and the security's really hard. And we're doing backups another way than we've done it traditionally. And we're helping customers bridge that gap and saying, we can take some of the security policies that we've been running internally in our data center, and maybe you've been doing inside your data center, and take those out into the public cloud. Simplifying things with networking. We're a pretty big VM or NXS shop. So doing something where you can create tagging and policies local inside the Expedient data center, and then being able to translate those up into AWS and Azure, to make it, basically, one seamless network, is really, really big and key for our customers. It's something that I think is still new. We have a handful of customers that we're working on a lot of cool research projects on. But I think it's going to be something that's going to be the dominant force here in the next few years. >> You mention disaster recovery as a service. Now is that where Zerto fits into your plan? >> Correct, yeah. We've been working with Zerto for quite some time now really since they were just comin' to Boston. And we worked and spent a ton of time with them getting them to understand the needs of service providers, 'cause they were traditionally enterprise focused. And that partnership that we've built over the years has done tremendous value for not only our customers but our businesses. And we've actually had two year-over-year growth for the last three years with them. And actually, we just won the Service Partner Growth Partner of the Year Award with them. So we're creating some pretty cool solutions around DR as a service, and taking some of our network background and actually simplifying DR for our customers that way. So, we use Zerto as well as VM Ware, and some of our own product connectivity, NSX, to actually simplify the package of DR to get the recovery time objective down into 10, 15 minutes, instead of four hours or eight hours or multiple days that really most people are experiencing right now. >> So when you look at the landscape, there are a lot of disaster recovery solution providers you could've worked with. What does Zerto do that's really different? >> The part, well, on a technology wise, watching them take a look at the change block that's occurring that's out of the VM1 environment, making an agnostic from a storage layer, that was really big for us in the beginning on the technical tip-in. And then the partnership, as of late, really since the beginning, was the big value differentiator that we just couldn't find in other companies that're out there. We locked arms with their product management team and their product strategy team right away. We gave them literally two sheets of paper and said these are the things we need to be successful as a service provider using your software. They went down, checked 'em all off. We started goin' at it, and we started then growing that year-over-year for the last three years. So, it's been an amazing partnership. They have a strategic team that understands where the marketing industry's going. And we're going to use them, and leverage them, as much as we possibly can to help out our customers, give 'em the best outcomes they can possibly get. >> When your customers talk to you about backup, where do you see them going? Where is that market headed? >> So backup, traditional backup is something we've been doin' for quite some time. We do petabytes of backups every year for customers. Still using tape, believe it or not, as well. We have a lot of discs-- >> Tape will never die. >> Tape is still out there. I actually have a bumper sticker that I think EMC made when they bought Avamar saying Tape is Dead. And I don't think it's going to die anytime soon. >> Mainframe was dead, too. >> Yeah, right, mainframe has been dead and we still roll new ones into our data centers on a regular basis and then put cloud beside it. But on the backup side of it, if you look at some of the new disasters, right? Look at Atlanta. Their disaster was different. It wasn't a natural disaster, it was a-- >> Radsomeware attack. >> Ransomeware attack. Right, that's a new disaster. We're going to find new disasters, and you can't go and restore back from 24 hours ago and think that that's good. We don't live in that world anymore. It needs to be from five minutes, seven minutes, 30 minutes, whatever it might be. So, we use their journaling today to actually get those quick recoveries. And if they can extend that out, I think it's going to be pretty powerful for customers to say, okay, I want to go back to two years, three days, and six hours from now. And say, gimme that point in time, snap. That's the way I want to actually restore that data. Succeeding in that vision I think will definitely change the game for how we actually look at doing backup and restores in the future. >> A lot of talk at this conference about resilience. >> John: Um hmm. >> Is that a concept that you think customers, your customers, have really internalized? They understand what that means? >> They're getting it, yeah, definitely. I mean, DR even was something that we had to kind of walk them into. But now, if they have an outage, it's not just money that they're losing. It's the reputation. And as we all know now, reputation is key. And you look at Twitter. When somebody has an outage, or has a problem, I mean, their users essentially just blow 'em up and there's memes and all kinds of other stuff. There's a lot of funny ones for the airlines, from Delta and Southwest havin' those challenges. And so, our customers today are realizing that yeah, we can't go a day or two without having service to our customers. We can maybe go a minute or two, but that's about it. We need to make sure we're being resilient with our data. We need to make sure we're protecting it, we'll be able to create ways to quickly roll it back to make sure our customers are up on line. Because they just can't go down anymore. >> How important is security as a driver of resilience and spending on disaster recovery now? >> Yeah, security is definitely, with being able to quickly restore from like a ransomware, it's startin' to bring that infrastructure that has been, security's been a little different there, and where network security's been a little bit different, kind of bringing them together to create, say, we need to have a full package. We not only need to figure out how we're blocking it at the edge and blocking it internally east west, but we need to figure out, if we're going to get breached, 'cause we're going to get breached, how can we quickly restore from that? How can we make sure we're not being held ransom for Bitcoin or whatever the next currency's going to be that they're going to be held ransom for that they just can't pay because maybe it would knock them out of business. >> So, John, Expedient, being a small, specialized cloud service provider, you're kind of dancing with elephants when you're out there with Amazon and Microsoft. What's the secret? What keeps you guys successful and how do you keep viable? >> There's a lot of different things. I think the way we focus on technologies is a little bit unique. I mean, we're there to design the best technical solution for that customer. And not maybe fit them into a one-size-fits-all outfit. The other side of it is, a lot of our customers like the local touch and feel. Majority of our customers are at and around our data centers. That way they can get to learn the facility, they can, even if they're running cloud services with us, they know where it lives. That maybe eases their minds from a compliance standpoint, security standpoint. Or just in a trust, saying, I'm going to take my data that's been living inside of my data center, that's key to my business, and I'm going to give it to somebody, I at least want a face and a name so I can know who to call and who to talk to if there is ever a problem. >> Face to face still matters. >> It does, and I think it's always going to matter. And I think we're always going to have some sort of high interaction with every enterprise out there. And that's what they're going to need. 'Cause this stuff can never commoditize all the way. Creating the solution is still hard. Maybe the bits and pieces underneath it are a little bit easier, but the whole packages is going to always be unique and really hard to define in a one-size-fits-all for a lot of those enterprises. >> John White, thanks so much for joining us. >> Thanks for having me. >> We'll be back from Zertocon 2018 here in Boston. I'm Paul Gillin, this is The Cube. (light techno music)

Published Date : May 24 2018

SUMMARY :

Brought to you by Zerto. just the elevator pitch on what the customer's premises to meet that need And then how to create that long-term strategy to kind of make your life a little bit easier, Well we hear a lot these days about multi-cloud, And then they start to understand. Now is that where Zerto fits into your plan? Service Partner Growth Partner of the Year Award with them. So when you look at the landscape, and said these are the things we need We have a lot of discs-- And I don't think it's going to die anytime soon. But on the backup side of it, I think it's going to be pretty powerful We need to make sure we're being resilient We not only need to figure out how we're and how do you keep viable? a lot of our customers like the local touch and feel. and really hard to define in a We'll be back from Zertocon 2018 here in Boston.

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Harjot Gill & Rajiv Mirani, Nutanix | Nutanix .NEXT 2018


 

>> Announcer: Live from New Orleans, Louisiana it's the Cube, covering Dot Next Conference 2018. Brought to you by Nutanix. >> Welcome back, I'm Stu Miniman here at the Cube in New Orleans, the Nutanix Dot Next Conference. Joining me is Keith Townsend, going wall-to-wall with interviews for two days. And going to dig into some really geeky techy stuff, Micro segmentation and the like. Happy to welcome to the program two first-time guests, Harjot Gill, who is the Senior Director of product and engineering at Nutanix and Rajiv Mirani, who's the CTO of Cloud Platform. Thank you both for joining us. >> Both: Thanks, thanks for having us. >> Alright, so Rajiv you've been with Nutanix for a bit, so we're going to get Harjot first. So we beat four acquisitions that Nutanix has made in the software space in the last year or so. One of them was Netsil. >> Harjot: Yes. >> So bring us back. You were and are the CEO of the Netsil Group. Tell us, kind of, a why of the company, size of the team, things like that. >> That's good yeah, so previously, as I was co-founder and CEO of Netsil, which I don't know whether you noticed, is listen spelled backwards. And, essentially, it was like microservices analytics platform and the core technology of Nexus was, where designers at University of Pennsylvania in the research group. That's where most of my team came from. It's a really small team, like just 10 engineers, who took on this like very interesting challenge in the industry as micro services were taking off, applications were, like, ported to modern platforms, like kubernetes. We saw an opportunity to take, like, a network centric approach in doing performance analysis and liability analysis. And the product that we built is very interesting. It can be thought of as, like, Google Maps for your cloud applications just like Splunk, in the past, was Google search for data center. So we came up with this concept where you can, like, visualize different abstractions and different virtualization layers of your application delivery. And that was our product. >> Alright, Rajiv, we've been talking about the, really, expansion of services that you're offering. You know, security and networking, obviously a big space. So first of all, not not a Stanford team that you brought in but University of Pennsylvania. Explain a little bit for us justification, how Netsil fits in with the Nutanix portfolio. >> Yeah, the Netsil Technology is unique in many different ways and we actually see a lot of different applications for it. The core product that they have today, the way they do performance monitoring by staying just on the network, not installing any host agents. It's pretty unusual. It's something that we really liked about the technology. The fact that they can do this at layer seven can actually look at application data to deep packet inspection at line speed. It's even more impressive. And they really build at the scale out architecture based on Harjot's research work. We looked at that and we said, "hey look, this can be used for performance monitoring, it can be used for application discovery, it can be used for security operations." There's just so many different directions we can take this in. And it's a great team that's built it with a relatively small number of people. We want these guys to be working with us not not as a separate company. And it moved very quickly. The acquisition happened quite quickly. We talked a little bit this morning about how they're going to use it for micro segmentation but there's many other use cases we see coming down the pike. >> So let's talk a little bit about the enterprise of applicability. You know, when you guys looked at it, you mainly looked at containers and the challenges of a micro, i'm sorry, of multi services and basically twelve fact applications. >> Harjot: Yeah. >> How is that applicable to the typical enterprise, which 90% of their applications are modern lifts. Same capability? What what capabilities are you bringing to Bear for traditional application? >> It's pretty applicable everywhere because network is a very stable source of truth, like what remains constant in the legacy as well as in the new world is your TCP/IP stack. And it's a very stable source of truth to tap into. So one of the value proposition that Netsil had with an offer very, like, the early enterprise customers that we signed up, was helping them migrate from this monolithic architectures to micro services. And their existing tools on the market, if you look at APM tools or even the logging tools, were inadequate when taking them on this journey. And you can think of Netsil as a very pervasive solution. I mean, the analogy that I usually give people is, like drones versus troops on the ground. Where Netsil can quickly set up, like a breadth of coverage in any environment, whether it's like Legacy or micro services, you are covered. And and then once you find issues in your environment with security issues or performance issues, you can systematically drill in. Either add more instrumentation creating or add policies with micro segmentation. That was the whole idea. So there was a gap in the market for this kind of a tool. >> So let's talk about integration of Nutanix. One of the, what I'm calling, first principles for Nutanix is, push button one click easy. >> [Harjot And Rajiv] Yes. >> What does the Netsil application look like in a Nutanix environment to the Nutanix administrator? >> So let's take the micro segmentation example again, right. So today, if you were to micro segment an existing application, it's pretty hard to know where to begin. So Netsil described it as a hairy problem but we know he likes hair. But what Netsil does is it takes all the data it's gathering from the network and it gives you all this visibility into how every part of your application is interacting with each other. You can group it in different ways, so it's not just about VMs talking to Vms. If you have a micro services based application, that's actually very little value. You really want, which services are talking to each service or even more, which service tiers are talking to which service tiers. But gathering all that data, we can actually fully automate the creation of micro segmentation policies for existing applications. So today what we saw was more of a manual thing. We've set it up previously. It's just that we haven't enough time to do integration yet. You expect that to become completely automated. Similarly with the remediation stuff, the troubleshooting stuff. We have it integrated with the Netsil technology, with the machine learning things that we have been working on. Once we do that, we can explain a lot more automated insights into your applications, integrated alert system, integrated with our metrics and stat systems. So a lot of work to do but a lot of potential for this technology, I think. >> So yeah, so it actually does solve this chicken and an egg problem, as Rajiv said, with actually making micro segmentation operational by first discovering these ground field apps and then suggesting policies, right? And all the goodness of Netsil will be brought on to, like, products like Prism, where out-of-the-box, Netsil can provide visibility and metrics for workloads such as VDI and all the packaged applications and all the Mongo Db and all of the stuff that is hosted on top of Nutanix platform and selling it to the same ID ops. >> Harjot, the space you're playing in is really changing so so fast. >> Harjot: Yes it is. >> Talk about micro segmentation and containers and serverless and the like. What, at its core, will allow your product to be able to stay up with the pace of change? >> So the code of the product, as I mentioned, I mean, it's network based, so one of the things, like, you get with that is, like, it's a very stable source of truth. So your languages keep evolving. So in if you look at the, I mean, this mind-boggling introduction of, like, open source technologies into enterprise environments, which you don't control what languages they are written in. And your developers are like picking up the latest and greatest tools. So in that world the core of the technology, which is like network based, still works the same and that allows us to be ,like, really future-proof this thing here. >> Languages of frameworks change. The network protocols are much more stable. >> Yet, to some people's chagrin, the protocols don't change. So let's talk a little bit about products and overlap of products. One of the, I think, confusing points, or can be confusing, is where Netsil fits in when it comes to Comm and overall to Zai. Where, where's the interaction and overlap or what's the relative? >> Yeah, so you can think of every workload in the cloud as a coup de loop, observe, orient, decide, and act. Now what Comm helps the customer is to like act faster, right. Whereas Netsil comes in and provides the observe and the orient piece. So it's all part of the same workload workflow. If you are an IT ops person, you need tools to observe and help orient, so you can decide faster. And tools like Comm and kubernetes, in the future, with one click, just a few clicks, you can make massive changes to your cloud infrastructure. But without observability you are just flying blind. That's where Netsil comes in. So that's why, as you've said, as Rajiv said, like it's going to enhance a lot of areas within Nutanix and, possibly like, even continue selling as a multi cloud monitoring solution. >> Just as we do brownfield input for micro segmentation, you can imagine that it would be a great great product for Comm as well. Being able to do brownfield import of applications and making them into Comm blueprints. >> Yeah, Rajiv, you've had some pent up demand from customers for the micro segmentation piece but give us a little bit.. You said there's other applications, what should we be expecting to see from the Netsil product line? >> So as CTU I can talk future, so let me tell you some stuff on the kubernete timelines. One great area for us to explore is around security operations. Since since Netsil is already in the net world looking at all traffic, it can easily establish a baseline, of which Vms, which containers normally talk to each other. What kind of requests to make. And it's registered at layer seven, so it can even go and look into what kind of API endpoints are normally called. And once it's base-lined this, detecting variation, selecting violations is going to be relatively simple. So we can alert on security violations, unusual behavior, services making calls to services that shouldn't be making calls to. All that kind of stuff. So that's one area for us to explore. We talked about Comm, so Comm can benefit greatly by being able to import brownfield applications into the Comm umbrella, making blueprints out of them. There's integrations with Prism Pro, which will enable the kind of metrics that Netsil is collecting and integrating it to what Prism Pro already does, putting into one single framework, adding it to capacity planning, adding in all the Prism Pro features that we have. So there's a lot of stuff we can do. >> So that's an awful lot of data. Where's this stored and what's the engine behind it? >> That's a great question. Actually, Netsil not only innovated in this unique way of collecting, we also invented a lot in-time series databases. So the back end of Netsil is powered by a database called Apache Druid, which is an OLAP time series database. So it can ingest that scale and you can run complex queries in sub-second latency XQ. So it can like summarize billions of data points at sub-second latencies. And the third thing that Netsil innovated is, in the visualizations. We are talking about, like, visualizing this complex data that is coming from these modern transforming environments. That's another area where Netsil innovated with this Maps interface to summarize and build easy-to-understand visualizations on your complex infrastructure. >> Now I'm scared that my head would explode but I would love to get you guys on with Satyam and talk through what additional data and when it comes to IOT machine learning, what additional insights. Quick question, are you guys working with Satyam at all at this point? >> We've started, like, understanding the lay of the land, so we're, like, still getting introduced to a lot of teams. As you guys know, these Nutanix is now growing very rapidly, there's so many areas to, like, learn about. And we are primarily working with a micro segmentation team right now but going forward, you will see Netsil's goodness being brought into other areas at Nutanix. >> Yeah, Rajiv one question I have from a software standpoint in general, where does AI fit into, you know, what you're doing with Zai and Comm? >> Yes, so for all of them, you know, we're using machine learning fairly extensively today to even do basic things like capacity planning, the what-if modeling that we've been doing. But to go beyond machine learning, if we actually invest in building an AI platform, I feel we can do a lot more in terms of root cause analysis and mediation, troubleshooting of applications, finding performance bottlenecks automatically. Essentially, really making that invisible infrastructure dream come true. We're close, we're not quite there yet. >> Yeah, and it's really about, like, getting quality data in without friction. So you have, like, AI is now being commoditized in the industry like all the algorithms are now like mainstream. So the biggest challenge has always been how do you go and capture the data at low friction? That's what Netsil brings onboard. >> Yeah, I'm super excited for the micro segmentation. Let's talk about what if customers... What has been the customer reaction to Netsil and just the new capability? >> We see a lot of excitement. This is micro segmentation barely been out, what, a couple of months at this point? And we already have fairly large customers deploying it out there, and a lot of demand for proof of concepts and so on at this point. It was very clear to us from the beginning that when people were looking at other SDN solutions, the number one use case they were using in the enterprise was for micro segmentation. So we took that, we made it as simple as we could. In true Nutanix fashion we said, "okay, let's make micro segmentation as one-click as we can." And it's been gratifying, I think, to see the initial reaction. In fact, some of the initial feedback we've gotten has been along the lines of, this is almost too simple. >> So one of the challenges that we've had in Enterprise is hybrid cloud. When you look at a EC2 instance and you have an internal database and the two communicate, that EC2 instance is ephemeral, we don't know how to handle that. Does Netsil address that challenge at all? >> It does, in fact, it's been designed for even a faster moving world of containers. I'll give you an example of kubernetes, it is, I mean, a similar example. So next Hill installs as a daemon set on kubernetes experiencing structure insertion. You are, like, independently inserting without developers. And as soon as it is installed, it's not just looking at packets, it's also like tapping into docker socket for metadata. So as soon as containers go up and down, new ones brought up, it actually pulls the metadata, the container IDs, the service IDs, kubernetes, pod names and whatnot. And then measures that to the metrics that we are collecting. So that in the UI, as you saw in the demo today, you're not so much slicing and dicing by IP addresses. You're slicing and dicing by that service tax, so your BMS can come and go, containers can come and go. But we are looking at the behavior of this group of cattle, and you know the cattle versus pets analogy, the whole idea in the new world is, to like, create these services as the new pets and your cattle are ephemeral, and the whole idea that Netsil can discover micro-services, discover the boundary of micro services by looking at layer 7 behavior and by smartly grouping things based on the behavior. So we know exactly what a MySQL database and different installations of MySQL look like based on the behavior and the query behavior, and group them together. >> So enforcement. And is that at the bot level or is that at the container level? >> So on the enforcement side, Netsil is mostly on the visibility. So on the micro segmentation side there is... >> Today micro-segmentation, of which for Vms as we build out our next version of container services, we are looking into building a micro segmentation for kubernetes as well, and that will be at the bot level. >> Alright Kieth, I'm looking forward to this is CTO advisor podcast, digging a little bit more into micro-segmentation. It may be Rajiv and.. >> We'll have them on for sure. >> ...and Harjot can stop by so time. But thank you gentlemen so much for coming. Congratulations on the update. Looking forward to hearing more. Keith and I have a little bit more here left of day one of Nutanix dot next 2018. I'm Stu Miniman, Kieth Townsend. Thank you for watching the Cube. (Electronic Music)

Published Date : May 9 2018

SUMMARY :

Brought to you by Nutanix. in New Orleans, the Nutanix Dot Next Conference. in the software space in the last year or so. size of the team, things like that. So we came up with this concept where you can, like, So first of all, not not a Stanford team that you brought in Yeah, the Netsil Technology is unique the enterprise of applicability. How is that applicable to the typical enterprise, And and then once you find issues in your environment So let's talk about integration of Nutanix. So let's take the micro segmentation example again, right. and all the Mongo Db and all of the stuff Harjot, the space you're playing in and serverless and the like. So the code of the product, as I mentioned, Languages of frameworks change. and overall to Zai. So it's all part of the same workload workflow. you can imagine that it would be a great great product from customers for the micro segmentation piece adding in all the Prism Pro features that we have. So that's an awful lot of data. So the back end of Netsil is powered by a database but I would love to get you guys on with Satyam And we are primarily working with the what-if modeling that we've been doing. So the biggest challenge has always been What has been the customer reaction to Netsil So we took that, we made it as simple as we could. So one of the challenges that we've had in Enterprise So that in the UI, as you saw in the demo today, And is that at the bot level So on the micro segmentation side there is... and that will be at the bot level. to this is CTO advisor podcast, Congratulations on the update.

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Nutanix .Next | NOLA | Day 1 | AM Keynote


 

>> PA Announcer: Off the plastic tab, and we'll turn on the colors. Welcome to New Orleans. ♪ This is it ♪ ♪ The part when I say I don't want ya ♪ ♪ I'm stronger than I've been before ♪ ♪ This is the part when I set your free ♪ (New Orleans jazz music) ("When the Saints Go Marching In") (rock music) >> PA Announcer: Ladies and gentleman, would you please welcome state of Louisiana chief design officer Matthew Vince and Choice Hotels director of infrastructure services Stacy Nigh. (rock music) >> Well good morning New Orleans, and welcome to my home state. My name is Matt Vince. I'm the chief design office for state of Louisiana. And it's my pleasure to welcome you all to .Next 2018. State of Louisiana is currently re-architecting our cloud infrastructure and Nutanix is the first domino to fall in our strategy to deliver better services to our citizens. >> And I'd like to second that warm welcome. I'm Stacy Nigh director of infrastructure services for Choice Hotels International. Now you may think you know Choice, but we don't own hotels. We're a technology company. And Nutanix is helping us innovate the way we operate to support our franchisees. This is my first visit to New Orleans and my first .Next. >> Well Stacy, you're in for a treat. New Orleans is known for its fabulous food and its marvelous music, but most importantly the free spirit. >> Well I can't wait, and speaking of free, it's my pleasure to introduce the Nutanix Freedom video, enjoy. ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ Ah, ah, ♪ ♪ Ah, ah, ♪ ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ I'm free, I'm free, I'm free, I'm free ♪ ♪ Gritting your teeth, you hold onto me ♪ ♪ It's never enough, I'm never complete ♪ ♪ Tell me to prove, expect me to lose ♪ ♪ I push it away, I'm trying to move ♪ ♪ I'm desperate to run, I'm desperate to leave ♪ ♪ If I lose it all, at least I'll be free ♪ ♪ Ah, ah ♪ ♪ Ah, ah ♪ ♪ Hallelujah, I'm free ♪ >> PA Announcer: Ladies and gentlemen, please welcome chief marketing officer Ben Gibson ♪ Ah, ah ♪ ♪ Ah, ah ♪ ♪ Hallelujah, I'm free ♪ >> Welcome, good morning. >> Audience: Good morning. >> And welcome to .Next 2018. There's no better way to open up a .Next conference than by hearing from two of our great customers. And Matthew, thank you for welcoming us to this beautiful, your beautiful state and city. And Stacy, this is your first .Next, and I know she's not alone because guess what It's my first .Next too. And I come properly attired. In the front row, you can see my Nutanix socks, and I think my Nutanix blue suit. And I know I'm not alone. I think over 5,000 people in attendance here today are also first timers at .Next. And if you are here for the first time, it's in the morning, let's get moving. I want you to stand up, so we can officially welcome you into the fold. Everyone stand up, first time. All right, welcome. (audience clapping) So you are all joining not just a conference here. This is truly a community. This is a community of the best and brightest in our industry I will humbly say that are coming together to share best ideas, to learn what's happening next, and in particular it's about forwarding not only your projects and your priorities but your careers. There's so much change happening in this industry. It's an opportunity to learn what's coming down the road and learn how you can best position yourself for this whole new world that's happening around cloud computing and modernizing data center environments. And this is not just a community, this is a movement. And it's a movement that started quite awhile ago, but the first .Next conference was in the quiet little town of Miami, and there was about 800 of you in attendance or so. So who in this hall here were at that first .Next conference in Miami? Let me hear from you. (audience members cheering) Yep, well to all of you grizzled veterans of the .Next experience, welcome back. You have started a movement that has grown and this year across many different .Next conferences all over the world, over 20,000 of your community members have come together. And we like to do it in distributed architecture fashion just like here in Nutanix. And so we've spread this movement all over the world with .Next conferences. And this is surging. We're also seeing just today the current count 61,000 certifications and climbing. Our Next community, close to 70,000 active members of our online community because .Next is about this big moment, and it's about every other day and every other week of the year, how we come together and explore. And my favorite stat of all. Here today in this hall amongst the record 5,500 registrations to .Next 2018 representing 71 countries in whole. So it's a global movement. Everyone, welcome. And you know when I got in Sunday night, I was looking at the tweets and the excitement was starting to build and started to see people like Adile coming from Casablanca. Adile wherever you are, welcome buddy. That's a long trip. Thank you so much for coming and being here with us today. I saw other folks coming from Geneva, from Denmark, from Japan, all over the world coming together for this moment. And we are accomplishing phenomenal things together. Because of your trust in us, and because of some early risk candidly that we have all taken together, we've created a movement in the market around modernizing data center environments, radically simplifying how we operate in the services we deliver to our businesses everyday. And this is a movement that we don't just know about this, but the industry is really taking notice. I love this chart. This is Gartner's inaugural hyperconvergence infrastructure magic quadrant chart. And I think if you see where Nutanix is positioned on there, I think you can agree that's a rout, that's a homerun, that's a mic drop so to speak. What do you guys think? (audience clapping) But here's the thing. It says Nutanix up there. We can honestly say this is a win for this hall here. Because, again, without your trust in us and what we've accomplished together and your partnership with us, we're not there. But we are there, and it is thanks to everyone in this hall. Together we have created, expanded, and truly made this market. Congratulations. And you know what, I think we're just getting started. The same innovation, the same catalyst that we drove into the market to converge storage network compute, the next horizon is around multi-cloud. The next horizon is around whether by accident or on purpose the strong move with different workloads moving into public cloud, some into private cloud moving back and forth, the promise of application mobility, the right workload on the right cloud platform with the right economics. Economics is key here. If any of you have a teenager out there, and they have a hold of your credit card, and they're doing something online or the like. You get some surprises at the end of the month. And that surprise comes in the form of spiraling public cloud costs. And this isn't to say we're not going to see a lot of workloads born and running in public cloud, but the opportunity is for us to take a path that regains control over infrastructure, regain control over workloads and where they're run. And the way I look at it for everyone in this hall, it's a journey we're on. It starts with modernizing those data center environments, continues with embracing the full cloud stack and the compelling opportunity to deliver that consumer experience to rapidly offer up enterprise compute services to your internal clients, lines of businesses and then out into the market. It's then about how you standardize across an enterprise cloud environment, that you're not just the infrastructure but the management, the automation, the control, and running any tier one application. I hear this everyday, and I've heard this a lot already this week about customers who are all in with this approach and running those tier one applications on Nutanix. And then it's the promise of not only hyperconverging infrastructure but hyperconverging multiple clouds. And if we do that, this journey the way we see it what we are doing is building your enterprise cloud. And your enterprise cloud is about the private cloud. It's about expanding and managing and taking back control of how you determine what workload to run where, and to make sure there's strong governance and control. And you're radically simplifying what could be an awfully complicated scenario if you don't reclaim and put your arms around that opportunity. Now how do we do this different than anyone else? And this is going to be a big theme that you're going to see from my good friend Sunil and his good friends on the product team. What are we doing together? We're taking all of that legacy complexity, that friction, that inability to be able to move fast because you're chained to old legacy environments. I'm talking to folks that have applications that are 40 years old, and they are concerned to touch them because they're not sure if they can react if their infrastructure can meet the demands of a new, modernized workload. We're making all that complexity invisible. And if all of that is invisible, it allows you to focus on what's next. And that indeed is the spirit of this conference. So if the what is enterprise cloud, and the how we do it different is by making infrastructure invisible, data centers, clouds, then why are we all here today? What is the binding principle that spiritually, that emotionally brings us all together? And we think it's a very simple, powerful word, and that word is freedom. And when we think about freedom, we think about as we work together the freedom to build the data center that you've always wanted to build. It's about freedom to run the applications where you choose based on the information and the context that wasn't available before. It's about the freedom of choice to choose the right cloud platform for the right application, and again to avoid a lot of these spiraling costs in unanticipated surprises whether it be around security, whether it be around economics or governance that come to the forefront. It's about the freedom to invent. It's why we got into this industry in the first place. We want to create. We want to build things not keep the lights on, not be chained to mundane tasks day by day. And it's about the freedom to play. And I hear this time and time again. My favorite tweet from a Nutanix customer to this day is just updated a lot of nodes at 38,000 feed on United Wifi, on my way to spend vacation with my family. Freedom to play. This to me is emotionally what brings us all together and what you saw with the Freedom video earlier, and what you see here is this new story because we want to go out and spread the word and not only talk about the enterprise cloud, not only talk about how we do it better, but talk about why it's so compelling to be a part of this hall here today. Now just one note of housekeeping for everyone out there in case I don't want anyone to take a wrong turn as they come to this beautiful convention center here today. A lot of freedom going on in this convention center. As luck may have it, there's another conference going on a little bit down that way based on another high growth, disruptive industry. Now MJBizCon Next, and by coincidence it's also called next. And I have to admire the creativity. I have to admire that we do share a, hey, high growth business model here. And in case you're not quite sure what this conference is about. I'm the head of marketing here. I have to show the tagline of this. And I read the tagline from license to launch and beyond, the future of the, now if I can replace that blank with our industry, I don't know, to me it sounds like a new, cool Sunil product launch. Maybe launching a new subscription service or the like. Stay tuned, you never know. I think they're going to have a good time over there. I know we're going to have a wonderful week here both to learn as well as have a lot of fun particularly in our customer appreciation event tonight. I want to spend a very few important moments on .Heart. .Heart is Nutanix's initiative to promote diversity in the technology arena. In particular, we have a focus on advancing the careers of women and young girls that we want to encourage to move into STEM and high tech careers. You have the opportunity to engage this week with this important initiative. Please role the video, and let's learn more about how you can do so. >> Video Plays (electronic music) >> So all of you have received these .Heart tokens. You have the freedom to go and choose which of the four deserving charities can receive donations to really advance our cause. So I thank you for your engagement there. And this community is behind .Heart. And it's a very important one. So thank you for that. .Next is not the community, the moment it is without our wonderful partners. These are our amazing sponsors. Yes, it's about sponsorship. It's also about how we integrate together, how we innovate together, and we're about an open community. And so I want to thank all of these names up here for your wonderful sponsorship of this event. I encourage everyone here in this room to spend time, get acquainted, get reacquainted, learn how we can make wonderful music happen together, wonderful music here in New Orleans happen together. .Next isn't .Next with a few cool surprises. Surprise number one, we have a contest. This is a still shot from the Freedom video you saw right before I came on. We have strategically placed a lucky seven Nutanix Easter eggs in this video. And if you go to Nutanix.com/freedom, watch the video. You may have to use the little scrubbing feature to slow down 'cause some of these happen quickly. You're going to find some fun, clever Easter eggs. List all seven, tweet that out, or as many as you can, tweet that out with hashtag nextconf, C, O, N, F, and we'll have a random drawing for an all expenses paid free trip to .Next 2019. And just to make sure everyone understands Easter egg concept. There's an eighth one here that's actually someone that's quite famous in our circles. If you see on this still shot, there's someone in the back there with a red jacket on. That's not just anyone. We're targeting in here. That is our very own Julie O'Brien, our senior vice president of corporate marketing. And you're going to hear from Julie later on here at .Next. But Julie and her team are the engine and the creativity behind not only our new Freedom campaign but more importantly everything that you experience here this week. Julie and her team are amazing, and we can't wait for you to experience what they've pulled together for you. Another surprise, if you go and visit our Freedom booths and share your stories. So they're like video booths, you share your success stories, your partnerships, your journey that I talked about, you will be entered to win a beautiful Nutanix brand compliant, look at those beautiful colors, bicycle. And it's not just any bicycle. It's a beautiful bicycle made by our beautiful customer Trek. I actually have a Trek bike. I love cycling. Unfortunately, I'm not eligible, but all of you are. So please share your stories in the Freedom Nutanix's booths and put yourself in the running, or in the cycling to get this prize. One more thing I wanted to share here. Yesterday we had a great time. We had our inaugural Nutanix hackathon. This hackathon brought together folks that were in devops practices, many of you that are in this room. We sold out. We thought maybe we'd get four or five teams. We had to shutdown at 14 teams that were paired together with a Nutanix mentor, and you coded. You used our REST APIs. You built new apps that integrated in with Prism and Clam. And it was wonderful to see this. Everyone I talked to had a great time on this. We had three winners. In third place, we had team Copper or team bronze, but team Copper. Silver, Not That Special, they're very humble kind of like one of our key mission statements. And the grand prize winner was We Did It All for the Cookies. And you saw them coming in on our Mardi Gras float here. We Did It All for Cookies, they did this very creative job. They leveraged an Apple Watch. They were lighting up VMs at a moments notice utilizing a lot of their coding skills. Congratulations to all three, first, second, and third all receive $2,500. And then each of them, then were able to choose a charity to deliver another $2,500 including Ronald McDonald House for the winner, we did it all for the McDonald Land cookies, I suppose, to move forward. So look for us to do more of these kinds of events because we want to bring together infrastructure and application development, and this is a great, I think, start for us in this community to be able to do so. With that, who's ready to hear form Dheeraj? You ready to hear from Dheeraj? (audience clapping) I'm ready to hear from Dheeraj, and not just 'cause I work for him. It is my distinct pleasure to welcome on the stage our CEO, cofounder and chairman Dheeraj Pandey. ("Free" by Broods) ♪ Hallelujah, I'm free ♪ >> Thank you Ben and good morning everyone. >> Audience: Good morning. >> Thank you so much for being here. It's just such an elation when I'm thinking about the Mardi Gras crowd that came here, the partners, the customers, the NTCs. I mean there's some great NTCs up there I could relate to because they're on Slack as well. How many of you are in Slack Nutanix internal Slack channel? Probably 5%, would love to actually see this community grow from here 'cause this is not the only even we would love to meet you. We would love to actually do this in a real time bite size communication on our own internal Slack channel itself. Now today, we're going to talk about a lot of things, but a lot of hard things, a lot of things that take time to build and have evolved as the industry itself has evolved. And one of the hard things that I want to talk about is multi-cloud. Multi-cloud is a really hard problem 'cause it's full of paradoxes. It's really about doing things that you believe are opposites of each other. It's about frictionless, but it's also about governance. It's about being simple, and it's also about being secure at the same time. It's about delight, it's about reducing waste, it's about owning, and renting, and finally it's also about core and edge. How do you really make this big at a core data center whether it's public or private? Or how do you really shrink it down to one or two nodes at the edge because that's where your machines are, that's where your people are? So this is a really hard problem. And as you hear from Sunil and the gang there, you'll realize how we've actually evolved our solutions to really cater to some of these. One of the approaches that we have used to really solve some of these hard problems is to have machines do more, and I said a lot of things in those four words, have machines do more. Because if you double-click on that sentence, it really means we're letting design be at the core of this. And how do you really design data centers, how do you really design products for the data center that hush all the escalations, the details, the complexities, use machine-learning and AI and you know figure our anomaly detection and correlations and patter matching? There's a ton of things that you need to do to really have machines do more. But along the way, the important lesson is to make machines invisible because when machines become invisible, it actually makes something else visible. It makes you visible. It makes governance visible. It makes applications visible, and it makes services visible. A lot of things, it makes teams visible, careers visible. So while we're really talking about invisibility of machines, we're talking about visibility of people. And that's how we really brought all of you together in this conference as well because it makes all of us shine including our products, and your careers, and your teams as well. And I try to define the word customer success. You know it's one of the favorite words that I'm actually using. We've just hired a great leader in customer success recently who's really going to focus on this relatively hard problem, yet another hard problem of customer success. We think that customer success, true customer success is possible when we have machines tend towards invisibility. But along the way when we do that, make humans tend towards freedom. So that's the real connection, the yin-yang of machines and humans that Nutanix is really all about. And that's why design is at the core of this company. And when I say design, I mean reducing friction. And it's really about reducing friction. And everything we do, the most mundane of things which could be about migrating applications, spinning up VMs, self-service portals, automatic upgrades, and automatic scale out, and all the things we do is about reducing friction which really makes machines become invisible and humans gain freedom. Now one of the other convictions we have is how all of us are really tied at the hip. You know our success is tied to your success. If we make you successful, and when I say you, I really mean Main Street. Main Street being customers, and partners, and employees. If we make all of you successful, then we automatically become successful. And very coincidentally, Main Street and Wall Street are also tied in that very same relation as well. If we do a great job at Main Street, I think the Wall Street customer, i.e. the investor, will take care of itself. You'll have you know taken care of their success if we took care of Main Street success itself. And that's the narrative that our CFO Dustin Williams actually went and painted to our Wall Street investors two months ago at our investor day conference. We talked about a $3 billion number. We said look as a company, as a software company, we can go and achieve $3 billion in billings three years from now. And it was a telling moment for the company. It was really about talking about where we could be three years from now. But it was not based on a hunch. It was based on what we thought was customer success. Now realize that $3 billion in pure software. There's only 10 to 15 companies in the world that actually have that kind of software billings number itself. But at the core of this confidence was customer success, was the fact that we were doing a really good job of not over promising and under delivering but under promising starting with small systems and growing the trust of the customers over time. And this is one of the statistics we actually talk about is repeat business. The first dollar that a Global 2000 customer spends in Nutanix, and if we go and increase their trust 15 times by year six, and we hope to actually get 17 1/2 and 19 times more trust in the years seven and eight. It's very similar numbers for non Global 2000 as well. Again, we go and really hustle for customer success, start small, have you not worry about paying millions of dollars upfront. You know start with systems that pay as they grow, you pay as they grow, and that's the way we gain trust. We have the same non Global 2000 pay $6 1/2 for the first dollar they've actually spent on us. And with this, I think the most telling moment was when Dustin concluded. And this is key to this audience here as well. Is how the current cohorts which is this audience here and many of them were not here will actually carry the weight of $3 billion, more than 50% of it if we did a great job of customer success. If we were humble and honest and we really figured out what it meant to take care of you, and if we really understood what starting small was and having to gain the trust with you over time, we think that more than 50% of that billings will actually come from this audience here without even looking at new logos outside. So that's the trust of customer success for us, and it takes care of pretty much every customer not just the Main Street customer. It takes care of Wall Street customer. It takes care of employees. It takes care of partners as well. Now before I talk about technology and products, I want to take a step back 'cause many of you are new in this audience. And I think that it behooves us to really talk about the history of this company. Like we've done a lot of things that started out as science projects. In fact, I see some tweets out there and people actually laugh at Nutanix cloud. And this is where we were in 2012. So if you take a step back and think about where the company was almost seven, eight years ago, we were up against giants. There was a $30 billion industry around network attached storage, and storage area networks and blade servers, and hypervisors, and systems management software and so on. So what did we start out with? Very simple premise that we will collapse the architecture of the data center because three tier is wasteful and three tier is not delightful. It was a very simple hunch, we said we'll take rack mount servers, we'll put a layer of software on top of it, and that layer of software back then only did storage. It didn't do networks and security, and it ran on top of a well known hypervisor from VMware. And we said there's one non negotiable thing. The fact that the design must change. The control plane for this data center cannot be the old control plane. It has to be rethought through, and that's why Prism came about. Now we went and hustled hard to add more things to it. We said we need to make this diverse because it can't just be for one application. We need to make it CPU heavy, and memory heavy, and storage heavy, and flash heavy and so on. And we built a highly configurable HCI. Now all of them are actually configurable as you know of today. And this was not just innovation in technologies, it was innovation in business and sizing, capacity planning, quote to cash business processes. A lot of stuff that we had to do to make this highly configurable, so you can really scale capacity and performance independent of each other. Then in 2014, we did something that was very counterintuitive, but we've done this on, and on, and on again. People said why are you disrupting yourself? You know you've been doing a good job of shipping appliances, but we also had the conviction that HCI was not about hardware. It was about a form factor, but it was really about an operating system. And we started to compete with ourselves when we said you know what we'll do arm's length distribution, we'll do arm's length delivery of products when we give our software to our Dell partner, to Dell as a partner, a loyal partner. But at the same time, it was actually seen with a lot of skepticism. You know these guys are wondering how to really make themselves vanish because they're competing with themselves. But we also knew that if we didn't compete with ourselves someone else will. Now one of the most controversial decisions was really going and doing yet another hypervisor. In the year 2015, it was really preposterous to build yet another hypervisor. It was a very mature market. This was coming probably 15 years too late to the market, or at least 10 years too late to market. And most people said it shouldn't be done because hypervisor is a commodity. And that's the word we latched on to. That this commodity should not have to be paid for. It shouldn't have a team of people managing it. It should actually be part of your overall stack, but it should be invisible. Just like storage needs to be invisible, virtualization needs to be invisible. But it was a bold step, and I think you know at least when we look at our current numbers, 1/3rd of our customers are actually using AHV. At least every quarter that we look at it, our new deployments, at least 35% of it is actually being used on AHV itself. And again, a very preposterous thing to have said five years ago, four years ago to where we've actually come. Thank you so much for all of you who've believed in the fact that virtualization software must be invisible and therefore we should actually try out something that is called AHV today. Now we went and added Lenovo to our OEM mix, started to become even more of a software company in the year 2016. Went and added HP and Cisco in some of very large deals that we talk about in earnings call, our HP deals and Cisco deals. And some very large customers who have procured ELAs from us, enterprise license agreements from us where they want to mix and match hardware. They want to mix Dell hardware with HP hardware but have common standard Nutanix entitlements. And finally, I think this was another one of those moments where we say why should HCI be only limited to X86. You know this operating systems deserves to run on a non X86 architecture as well. And that gave birth to this idea of HCI and Power Systems from IBM. And we've done a great job of really innovating with them in the last three, four quarters. Some amazing innovation that has come out where you can now run AIX 7.x on Nutanix. And for the first time in the history of data center, you can actually have a single software not just a data plane but a control plane where you can manage an IBM farm, an Power farm, and open Power farm and an X86 farm from the same control plane and have you know the IBM farm feed storage to an Intel compute farm and vice versa. So really good things that we've actually done. Now along the way, something else was going on while we were really busy building the private cloud, we knew there was a new consumption model on computing itself. People were renting computing using credit cards. This is the era of the millennials. They were like really want to bypass people because at the end of the day, you know why can't computing be consumed the way like eCommerce is? And that devops movement made us realize that we need to add to our stack. That stack will now have other computing clouds that is AWS and Azure and GCP now. So similar to the way we did Prism. You know Prism was really about going and making hypervisors invisible. You know we went ahead and said we'll add Calm to our portfolio because Calm is now going to be what Prism was to us back when we were really dealing with multi hypervisor world. Now it's going to be multi-cloud world. You know it's one of those things we had a gut around, and we really come to expect a lot of feedback and real innovation. I mean yesterday when we had the hackathon. The center, the epicenter of the discussion was Calm, was how do you automate on multiple clouds without having to write a single line of code? So we've come a long way since the acquisition of Calm two years ago. I think it's going to be a strong pillar in our overall product portfolio itself. Now the word multi-cloud is going to be used and over used. In fact, it's going to be blurring its lines with the idea of hyperconvergence of clouds, you know what does it mean. We just hope that hyperconvergence, the way it's called today will morph to become hyperconverged clouds not just hyperconverged boxes which is a software defined infrastructure definition itself. But let's focus on the why of multi-cloud. Why do we think it can't all go into a public cloud itself? The one big reason is just laws of the land. There's data sovereignty and computing sovereignty, regulations and compliance because of which you need to be in where the government with the regulations where the compliance rules want you to be. And by the way, that's just one reason why the cloud will have to disperse itself. It can't just be 10, 20 large data centers around the world itself because you have 200 plus countries and half of computing actually gets done outside the US itself. So it's a really important, very relevant point about the why of multi-cloud. The second one is just simple laws of physics. You know if there're machines at the edge, and they're producing so much data, you can't bring all the data to the compute. You have to take the compute which is stateless, it's an app. You take the app to where the data is because the network is the enemy. The network has always been the enemy. And when we thought we've made fatter networks, you've just produced more data as well. So this just goes without saying that you take something that's stateless that's without gravity, that's lightweight which is compute and the application and push it close to where the data itself is. And the third one which is related is just latency reasons you know? And it's not just about machine latency and electrons transferring over the speed light, and you can't defy the speed of light. It's also about human latency. It's also about multiple teams saying we need to federate and delegate, and we need to push things down to where the teams are as opposed to having to expect everybody to come to a very large computing power itself. So all the ways, the way they are, there will be at least three different ways of looking at multi-cloud itself. There's a centralized core cloud. We all go and relate to this because we've seen large data centers and so on. And that's the back office workhorse. It will crunch numbers. It will do processing. It will do a ton of things that will go and produce results for you know how we run our businesses, but there's also the dispersal of the cloud, so ROBO cloud. And this is the front office server that's really serving. It's a cloud that's going to serve people. It's going to be closer to people, and that's what a ROBO cloud is. We have a ton of customers out here who actually use Nutanix and the ROBO environments themselves as one node, two node, three node, five node servers, and it just collapses the entire server closet room in these ROBOs into something really, really small and minuscule. And finally, there's going to be another dispersed edge cloud because that's where the machines are, that's where the data is. And there's going to be an IOT machine fog because we need to miniaturize computing to something even smaller, maybe something that can really land in the palm in a mini server which is a PC like server, but you need to run everything that's enterprise grade. You should be able to go and upgrade them and monitor them and analyze them. You know do enough computing up there, maybe event-based processing that can actually happen. In fact, there's some great innovation that we've done at the edge with IOTs that I'd love for all of you to actually attend some sessions around as well. So with that being said, we have a hole in the stack. And that hole is probably one of the hardest problems that we've been trying to solve for the last two years. And Sunil will talk a lot about that. This idea of hybrid. The hybrid of multi-cloud is one of the hardest problems. Why? Because we're talking about really blurring the lines with owning and renting where you have a single-tenant environment which is your data center, and a multi-tenant environment which is the service providers data center, and the two must look like the same. And the two must look like the same is that hard a problem not just for burst out capacity, not just for security, not just for identity but also for networks. Like how do you blur the lines between networks? How do you blur the lines for storage? How do you really blur the lines for a single pane of glass where you can think of availability zones that look highly symmetric even though they're not because one of 'em is owned by you, and it's single-tenant. The other one is not owned by you, that's multi-tenant itself. So there's some really hard problems in hybrid that you'll hear Sunil talk about and the team. And some great strides that we've actually made in the last 12 months of really working on Xi itself. And that completes the picture now in terms of how we believe the state of computing will be going forward. So what are the must haves of a multi-cloud operating system? We talked about marketplace which is catalogs and automation. There's a ton of orchestration that needs to be done for multi-cloud to come together because now you have a self-service portal which is providing an eCommerce view. It's really about you know getting to do a lot of requests and workflows without having people come in the way, without even having tickets. There's no need for tickets if you can really start to think like a self-service portal as if you're just transacting eCommerce with machines and portals themselves. Obviously the next one is networking security. You need to blur the lines between on-prem and off-prem itself. These two play a huge role. And there's going to be a ton of details that you'll see Sunil talk about. But finally, what I want to focus on the rest of the talk itself here is what governance and compliance. This is a hard problem, and it's a hard problem because things have evolved. So I'm going to take a step back. Last 30 years of computing, how have consumption models changed? So think about it. 30 years ago, we were making decisions for 10 plus years, you know? Mainframe, at least 10 years, probably 20 plus years worth of decisions. These were decisions that were extremely waterfall-ish. Make 10s of millions of dollars worth of investment for a device that we'd buy for at least 10 to 20 years. Now as we moved to client-server, that thing actually shrunk. Now you're talking about five years worth of decisions, and these things were smaller. So there's a little bit more velocity in our decisions. We were not making as waterfall-ish decision as we used to with mainframes. But still five years, talk about virtualized, three tier, maybe three to five year decisions. You know they're still relatively big decisions that we were making with computer and storage and SAN fabrics and virtualization software and systems management software and so on. And here comes Nutanix, and we said no, no. We need to make it smaller. It has to become smaller because you know we need to make more agile decisions. We need to add machines every week, every month as opposed to adding you know machines every three to five years. And we need to be able to upgrade them, you know any point in time. You can do the upgrades every month if you had to, every week if you had to and so on. So really about more agility. And yet, we were not complete because there's another evolution going on, off-prem in the public cloud where people are going and doing reserved instances. But more than that, they were doing on demand stuff which no the decision was days to weeks. Some of these things that unitive compute was being rented for days to weeks, not years. And if you needed something more, you'd shift a little to the left and use reserved instances. And then spot pricing, you could do spot pricing for hours and finally lambda functions. Now you could to function as a service where things could actually be running only for minutes not even hours. So as you can see, there's a wide spectrum where when you move to the right, you get more elasticity, and when you move to the left, you're talking about predictable decision making. And in fact, it goes from minutes on one side to 10s of years on the other itself. And we hope to actually go and blur the lines between where NTNX is today where you see Nutanix right now to where we really want to be with reserved instances and on demand. And that's the real ask of Nutanix. How do you take care of this discontinuity? Because when you're owning things, you actually end up here, and when you're renting things, you end up here. What does it mean to really blur the lines between these two because people do want to make decisions that are better than reserved instance in the public cloud. We'll talk about why reserved instances which looks like a proxy for Nutanix it's still very, very wasteful even though you might think it's delightful, it's very, very wasteful. So what does it mean for on-prem and off-prem? You know you talk about cost governance, there's security compliance. These high velocity decisions we're actually making you know where sometimes you could be right with cost but wrong on security, but sometimes you could be right in security but wrong on cost. We need to really figure out how machines make some of these decisions for us, how software helps us decide do we have the right balance between cost, governance, and security compliance itself? And to get it right, we have introduced our first SAS service called Beam. And to talk more about Beam, I want to introduce Vijay Rayapati who's the general manager of Beam engineering to come up on stage and talk about Beam itself. Thank you Vijay. (rock music) So you've been here a couple of months now? >> Yes. >> At the same time, you spent the last seven, eight years really handling AWS. Tell us more about it. >> Yeah so we spent a lot of time trying to understand the last five years at Minjar you know how customers are really consuming in this new world for their workloads. So essentially what we tried to do is understand the consumption models, workload patterns, and also build algorithms and apply intelligence to say how can we lower this cost and you know improve compliance of their workloads.? And now with Nutanix what we're trying to do is how can we converge this consumption, right? Because what happens here is most customers start with on demand kind of consumption thinking it's really easy, but the total cost of ownership is so high as the workload elasticity increases, people go towards spot or a scaling, but then you need a lot more automation that something like Calm can help them. But predictability of the workload increases, then you need to move towards reserved instances, right to lower costs. >> And those are some of the things that you go and advise with some of the software that you folks have actually written. >> But there's a lot of waste even in the reserved instances because what happens it while customers make these commitments for a year or three years, what we see across, like we track a billion dollars in public cloud consumption you know as a Beam, and customers use 20%, 25% of utilization of their commitments, right? So how can you really apply, take the data of consumption you know apply intelligence to essentially reduce their you know overall cost of ownership. >> You said something that's very telling. You said reserved instances even though they're supposed to save are still only 20%, 25% utilized. >> Yes, because the workloads are very dynamic. And the next thing is you can't do hot add CPU or hot add memory because you're buying them for peak capacity. There is no convergence of scaling that apart from the scaling as another node. >> So you actually sized it for peak, but then using 20%, 30%, you're still paying for the peak. >> That's right. >> Dheeraj: That can actually add up. >> That's what we're trying to say. How can we deliver visibility across clouds? You know how can we deliver optimization across clouds and consumption models and bring the control while retaining that agility and demand elasticity? >> That's great. So you want to show us something? >> Yeah absolutely. So this is Beam as just Dheeraj outlined, our first SAS service. And this is my first .Next. And you know glad to be here. So what you see here is a global consumption you know for a business across different clouds. Whether that's in a public cloud like Amazon, or Azure, or Nutanix. We kind of bring the consumption together for the month, the recent month across your accounts and services and apply intelligence to say you know what is your spent efficiency across these clouds? Essentially there's a lot of intelligence that goes in to detect your workloads and consumption model to say if you're spending $100, how efficiently are you spending? How can you increase that? >> So you have a centralized view where you're looking at multiple clouds, and you know you talk about maybe you can take an example of an account and start looking at it? >> Yes, let's go into a cloud provider like you know for this business, let's go and take a loot at what's happening inside an Amazon cloud. Here we get into the deeper details of what's happening with the consumption of a specific services as well as the utilization of both on demand and RI. You know what can you do to lower your cost and detect your spend efficiency of a dollar to see you know are there resources that are provisioned by teams for applications that are not being used, or are there resources that we should go and rightsize because you know we have all this monitoring data, configuration data that we crunch through to basically detect this? >> You think there's billions of events that you look at everyday. You're already looking at a billon dollars worth of AWS spend. >> Right, right. >> So billions of events, billing, metering events every year to really figure out and optimize for them. >> So what we have here is a very popular international government organization. >> Dheeraj: Wow, so it looks like Russians are everywhere, the cloud is everywhere actually. >> Yes, it's quite popular. So when you bring your master account into Beam, we kind of detect all the linked accounts you know under that. Then you can go and take a look at not just at the organization level within it an account level. >> So these are child objects, you know. >> That's right. >> You can think of them as ephemeral accounts that you create because you don't want to be on the record when you're doing spams on Facebook for example. >> Right, let's go and take a look at what's happening inside a Facebook ad spend account. So we have you know consumption of the services. Let's go deeper into compute consumption, and you kind of see a trendline. You can do a lot of computing. As you see, looks like one campaign has ended. They started another campaign. >> Dheeraj: It looks like they're not stopping yet, man. There's a lot of money being made in Facebook right now. (Vijay laughing) >> So not only just get visibility at you know compute as a service inside a cloud provider, you can go deeper inside compute and say you know what is a service that I'm really consuming inside compute along with the CPUs n'stuff, right? What is my data transfer? You know what is my network? What is my load blancers? So essentially you get a very deeper visibility you know as a service right. Because we have three goals for Beam. How can we deliver visibility across clouds? How can we deliver visibility across services? And how can we deliver, then optimization? >> Well I think one thing that I just want to point out is how this SAS application was an extremely teachable moment for me to learn about the different resources that people could use about the public cloud. So all of you who actually have not gone deep enough into the idea of public cloud. This could be a great app for you to learn about things, the resources, you know things that you could do to save and security and things of that nature. >> Yeah. And we really believe in creating the single pane view you know to mange your optimization of a public cloud. You know as Ben spoke about as a business, you need to have freedom to use any cloud. And that's what Beam delivers. How can you make the right decision for the right workload to use any of the cloud of your choice? >> Dheeraj: How 'about databases? You talked about compute as well but are there other things we could look at? >> Vijay: Yes, let's go and take a look at database consumption. What you see here is they're using inside Facebook ad spending, they're using all databases except Oracle. >> Dheeraj: Wow, looks like Oracle sales folks have been active in Russia as well. (Vijay laughing) >> So what we're seeing here is a global view of you know what is your spend efficiency and which is kind of a scorecard for your business for the dollars that you're spending. And the great thing is Beam kind of brings together you know through its intelligence and algorithms to detect you know how can you rightsize resources and how can you eliminate things that you're not using? And we deliver and one click fix, right? Let's go and take a look at resources that are maybe provisioned for storage and not being used. We deliver the seamless one-click philosophy that Nutanix has to eliminate it. >> So one click, you can actually just pick some of these wasteful things that might be looking delightful because using public cloud, using credit cards, you can go in and just say click fix, and it takes care of things. >> Yeah, and not only remove the resources that are unused, but it can go and rightsize resources across your compute databases, load balancers, even past services, right? And this is where the power of it kind of comes for a business whether you're using on-prem and off-prem. You know how can you really converge that consumption across both? >> Dheeraj: So do you have something for Nutanix too? >> Vijay: Yes, so we have basically been working on Nutanix with something that we're going to deliver you know later this year. As you can see here, we're bringing together the consumption for the Nutanix, you know the services that you're using, the licensing and capacity that is available. And how can you also go and optimize within Nutanix environments >> That's great. >> for the next workload. Now let me quickly show you what we have on the compliance side. This is an extremely powerful thing that we've been working on for many years. What we deliver here just like in cost governance, a global view of your compliance across cloud providers. And the most powerful thing is you can go into a cloud provider, get the next level of visibility across cloud regimes for hundreds of policies. Not just policies but those policies across different regulatory compliances like HIPA, PCI, CAS. And that's very powerful because-- >> So you're saying a lot of what you folks have done is codified these compliance checks in software to make sure that people can sleep better at night knowing that it's PCI, and HIPA, and all that compliance actually comes together? >> And you can build this not just by cloud accounts, you can build them across cloud accounts which is what we call security centers. Essentially you can go and take a deeper look at you know the things. We do a whole full body scan for your cloud infrastructure whether it's AWS Amazon or Azure, and you can go and now, again, click to fix things. You know that had been probably provisioned that are violating the security compliance rules that should be there. Again, we have the same one-click philosophy to say how can you really remove things. >> So again, similar to save, you're saying you can go and fix some of these security issues by just doing one click. >> Absolutely. So the idea is how can we give our people the freedom to get visibility and use the right cloud and take the decisions instantly through one click. That's what Beam delivers you know today. And you know get really excited, and it's available at beam.nutanix.com. >> Our first SAS service, ladies and gentleman. Thank you so much for doing this, Vijay. It looks like there's going to be a talk here at 10:30. You'll talk more about the midterm elections there probably? >> Yes, so you can go and write your own security compliances as well. You know within Beam, and a lot of powerful things you can do. >> Awesome, thank you so much, Vijay. I really appreciate it. (audience clapping) So as you see, there's a lot of work that we're doing to really make multi-cloud which is a hard problem. You know think about working the whole body of it and what about cost governance? What about security compliance? Obviously what about hybrid networks, and security, and storage, you know compute, many of the things that you've actually heard from us, but we're taking it to a level where the business users can now understand the implications. A CFO's office can understand the implications of waste and delight. So what does customer success mean to us? You know again, my favorite word in a long, long time is really go and figure out how do you make you, the customer, become operationally efficient. You know there's a lot of stuff that we deliver through software that's completely uncovered. It's so latent, you don't even know you have it, but you've paid for it. So you've got to figure out what does it mean for you to really become operationally efficient, organizationally proficient. And it's really important for training, education, stuff that you know you're people might think it's so awkward to do in Nutanix, but it could've been way simpler if you just told you a place where you can go and read about it. Of course, I can just use one click here as opposed to doing things the old way. But most importantly to make it financially accountable. So the end in all this is, again, one of the things that I think about all the time in building this company because obviously there's a lot of stuff that we want to do to create orphans, you know things above the line and top line and everything else. There's also a bottom line. Delight and waste are two sides of the same coin. You know when we're talking about developers who seek delight with public cloud at the same time you're looking at IT folks who're trying to figure out governance. They're like look you know the CFOs office, the CIOs office, they're trying to figure out how to curb waste. These two things have to go hand in hand in this era of multi-cloud where we're talking about frictionless consumption but also governance that looks invisible. So I think, at the end of the day, this company will do a lot of stuff around one-click delight but also go and figure out how do you reduce waste because there's so much waste including folks there who actually own Nutanix. There's so much software entitlement. There's so much waste in the public cloud itself that if we don't go and put our arms around, it will not lead to customer success. So to talk more about this, the idea of delight and the idea of waste, I'd like to bring on board a person who I think you know many of you actually have talked about it have delightful hair but probably wasted jokes. But I think has wasted hair and delightful jokes. So ladies and gentlemen, you make the call. You're the jury. Sunil R.M.J. Potti. ("Free" by Broods) >> So that was the first time I came out from the bottom of a screen on a stage. I actually now know what it feels to be like a gopher. Who's that laughing loudly at the back? Okay, do we have the... Let's see. Okay, great. We're about 15 minutes late, so that means we're running right on time. That's normally how we roll at this conference. And we have about three customers and four demos. Like I think there's about three plus six, about nine folks coming onstage. So we'll have our own version of the parade as well on the main stage for the next 70 minutes. So let's just jump right into it. I think we've been pretty consistent in terms of our longterm plans since we started the company. And it's become a lot more clearer over the last few years about our plans to essentially make computing invisible as Dheeraj mentioned. We're doing this across multiple acts. We started with HCI. We call it making infrastructure invisible. We extended that to making data centers invisible. And then now we're in this mode of essentially extending it to converging clouds so that you can actually converge your consumption models. And so today's conference and essentially the theme that you're going to be seeing throughout the breakout sessions is about a journey towards invisible clouds, but make sure that you internalize the fact that we're investing heavily in each of the three phases. It's just not about the hybrid cloud with Nutanix, it's about actually finishing the job about making infrastructure invisible, expanding that to kind of go after the full data center, and then of course embark on some real meaningful things around invisible clouds, okay? And to start the session, I think you know the part that I wanted to make sure that we are all on the same page because most of us in the room are still probably in this phase of the journey which is about invisible infrastructure. And there the three key products and especially two of them that most of you guys know are Acropolis and Prism. And they're sort of like the bedrock of our company. You know especially Acropolis which is about the web scale architecture. Prism is about consumer grade design. And with Acropolis now being really mature. It's in the seventh year of innovation. We still have more than half of our company in terms of R and D spend still on Acropolis and Prism. So our core product is still sort of where we think we have a significant differentiation on. We're not going to let our foot off the peddle there. You know every time somebody comes to me and says look there's a new HCI render popping out or an existing HCI render out there, I ask a simple question to our customers saying show me 100 customers with 100 node deployments, and it will be very hard to find any other render out there that does the same thing. And that's the power of Acropolis the code platform. And then it's you know the fact that the velocity associated with Acropolis continues to be on a fast pace. We came out with various new capabilities in 5.5 and 5.6, and one of the most complicated things to get right was the fact to shrink our three node cluster to a one node, two node deployment. Most of you actually had requirements on remote office, branch office, or the edge that actually allowed us to kind of give us you know sort of like the impetus to kind of go design some new capabilities into our core OS to get this out. And associated with Acropolis and expanding into Prism, as you will see, the first couple of years of Prism was all about refactoring the user interface, doing a good job with automation. But more and more of the investments around Prism is going to be based on machine learning. And you've seen some variants of that over the last 12 months, and I can tell you that in the next 12 to 24 months, most of our investments around infrastructure operations are going to be driven by AI techniques starting with most of our R and D spend also going into machine-learning algorithms. So when you talk about all the enhancements that have come on with Prism whether it be formed by you know the management console changing to become much more automated, whether now we give you automatic rightsizing, anomaly detection, or a series of functionality that have gone into it, the real core sort of capabilities that we're putting into Prism and Acropolis are probably best served by looking at the quality of the product. You probably have seen this slide before. We started showing the number of nodes shipped by Nutanix two years ago at this conference. It was about 35,000 plus nodes at that time. And since then, obviously we've you know continued to grow. And we would draw this line which was about enterprise class quality. That for the number of bugs found as a percentage of nodes shipped, there's a certain line that's drawn. World class companies do about probably 2% to 3%, number of CFDs per node shipped. And we were just broken that number two years ago. And to give you guys an idea of how that curve has shown up, it's now currently at .95%. And so along with velocity, you know this focus on being true to our roots of reliability and stability continues to be, you know it's an internal challenge, but it's also some of the things that we keep a real focus on. And so between Acropolis and Prism, that's sort of like our core focus areas to sort of give us the confidence that look we have this really high bar that we're sort of keeping ourselves accountable to which is about being the most advanced enterprise cloud OS on the planet. And we will keep it this way for the next 10 years. And to complement that, over a period of time of course, we've added a series of services. So these are services not just for VMs but also for files, blocks, containers, but all being delivered in that single one-click operations fashion. And to really talk more about it, and actually probably to show you the real deal there it's my great pleasure to call our own version of Moses inside the company, most of you guys know him as Steve Poitras. Come on up, Steve. (audience clapping) (rock music) >> Thanks Sunil. >> You barely fit in that door, man. Okay, so what are we going to talk about today, Steve? >> Absolutely. So when we think about when Nutanix first got started, it was really focused around VDI deployments, smaller workloads. However over time as we've evolved the product, added additional capabilities and features, that's grown from VDI to business critical applications as well as cloud native apps. So let's go ahead and take a look. >> Sunil: And we'll start with like Oracle? >> Yeah, that's one of the key ones. So here we can see our Prism central user interface, and we can see our Thor cluster obviously speaking to the Avengers theme here. We can see this is doing right around 400,000 IOPs at around 360 microseconds latency. Now obviously Prism central allows you to mange all of your Nutanix deployments, but this is just running on one single Nutanix cluster. So if we hop over here to our explore tab, we can see we have a few categories. We have some Kubernetes, some AFS, some Xen desktop as well as Oracle RAC. Now if we hope over to Oracle RAC, we're running a SLOB workload here. So obviously with Oracle enterprise applications performance, consistency, and extremely low latency are very critical. So with this SLOB workload, we're running right around 300 microseconds of latency. >> Sunil: So this is what, how many node Oracle RAC cluster is this? >> Steve: This is a six node Oracle RAC deployment. >> Sunil: Got it. And so what has gone into the product in recent releases to kind of make this happen? >> Yeah so obviously on the hardware front, there's been a lot of evolutions in storage mediums. So with the introduction of NVME, persistent memory technologies like 3D XPoint, that's meant storage media has become a lot faster. Now to allow you to full take advantage of that, that's where we've had to do a lot of optimizations within the storage stack. So with AHV, we have what we call AHV turbo mode which allows you to full take advantage of those faster storage mediums at that much lower latency. And then obviously on the networking front, technologies such as RDMA can be leveraged to optimize that network stack. >> Got it. So that was Oracle RAC running on a you know Nutanix cluster. It used to be a big deal a couple of years ago. Now we've got many customers doing that. On the same environment though, we're going to show you is the advent of actually putting file services in the same scale out environment. And you know many of you in the audience probably know about AFS. We released it about 12 to 14 months ago. It's been one of our most popular new products of all time within Nutanix's history. And we had SMB support was for user file shares, VDI deployments, and it took awhile to bake, to get to scale and reliability. And then in the last release, in the recent release that we just shipped, we now added NFS for support so that we can no go after the full scale file server consolidation. So let's take a look at some of that stuff. >> Yep, let's do it. So hopping back over to Prism, we can see our four cluster here. Overall cluster-wide latency right around 360 microseconds. Now we'll hop down to our file server section. So here we can see we have our Next A File Server hosting right about 16.2 million files. Now if you look at our shares and exports, we can see we have a mix of different shares. So one of the shares that you see there is home directories. This is an SMB share which is actually mapped and being leveraged by our VDI desktops for home folders, user profiles, things of that nature. We can also see this Oracle backup share here which is exposed to our rack host via NFS. So RMAN is actually leveraging this to provide native database backups. >> Got it. So Oracle VMs, backup using files, or for any other file share requirements with AFS. Do we have the cluster also showing, I know, so I saw some Kubernetes as well on it. Let's talk about what we're thinking of doing there. >> Yep, let's do it. So if we think about cloud, cloud's obviously a big buzz word, so is containers in Kubernetes. So with ACS 1.0 what we did is we introduced native support for Docker integration. >> And pause there. And we screwed up. (laughing) So just like the market took a left turn on Kubernetes, obviously we realized that, and now we're working on ACS 2.0 which is what we're going to talk about, right? >> Exactly. So with ACS 2.0, we've introduced native Kubernetes support. Now when I think about Kubernetes, there's really two core areas that come to mind. The first one is around native integration. So with that, we have our Kubernetes volume integration, we're obviously doing a lot of work on the networking front, and we'll continue to push there from an integration point of view. Now the other piece is around the actual deployment of Kubernetes. When we think about a lot of Nutanix administrators or IT admins, they may have never deployed Kubernetes before, so this could be a very daunting task. And true to the Nutanix nature, we not only want to make our platform simple and intuitive, we also want to do this for any ecosystem products. So with ACS 2.0, we've simplified the full Kubernetes deployment and switching over to our ACS two interface, we can see this create cluster button. Now this actually pops up a full wizard. This wizard will actually walk you through the full deployment process, gather the necessary inputs for you, and in a matter of a few clicks and a few minutes, we have a full Kubernetes deployment fully provisioned, the masters, the workers, all the networking fully done for you, very simple and intuitive. Now if we hop back over to Prism, we can see we have this ACS2 Kubernetes category. Clicking on that, we can see we have eight instances of virtual machines. And here are Kubernetes virtual machines which have actually been deployed as part of this ACS2 installer. Now one of the nice things is it makes the IT administrator's job very simple and easy to do. The deployment straightforward monitoring and management very straightforward and simple. Now for the developer, the application architect, or engineers, they interface and interact with Kubernetes just like they would traditionally on any platform. >> Got it. So the goal of ACS is to ensure that the developer ecosystem still uses whatever tools that they are you know preferring while at that same time allowing this consolidation of containers along with VMs all on that same, single runtime, right? So that's ACS. And then if you think about where the OS is going, there's still some open space at the end. And open space has always been look if you just look at a public cloud, you look at blocks, files, containers, the most obvious sort of storage function that's left is objects. And that's the last horizon for us in completing the storage stack. And we're going to show you for the first time a preview of an upcoming product called the Acropolis Object Storage Services Stack. So let's talk a little bit about it and then maybe show the demo. >> Yeah, so just like we provided file services with AFS, block services with ABS, with OSS or Object Storage Services, we provide native object storage, compatibility and capability within the Nutanix platform. Now this provides a very simply common S3 API. So any integrations you've done with S3 especially Kubernetes, you can actually leverage that out of the box when you've deployed this. Now if we hop back over to Prism, I'll go here to my object stores menu. And here we can see we have two existing object storage instances which are running. So you can deploy however many of these as you wanted to. Now just like the Kubernetes deployment, deploying a new object instance is very simple and easy to do. So here I'll actually name this instance Thor's Hammer. >> You do know he loses it, right? He hasn't seen the movies yet. >> Yeah, I don't want any spoilers yet. So once we specified the name, we can choose our capacity. So here we'll just specify a large instance or type. Obviously this could be any amount or storage. So if you have a 200 node Nutanix cluster with petabytes worth of data, you could do that as well. Once we've selected that, we'll select our expected performance. And this is going to be the number of concurrent gets and puts. So essentially how many operations per second we want this instance to be able to facilitate. Once we've done that, the platform will actually automatically determine how many virtual machines it needs to deploy as well as the resources and specs for those. And once we've done that, we'll go ahead and click save. Now here we can see it's actually going through doing the deployment of the virtual machines, applying any necessary configuration, and in the matter of a few clicks and a few seconds, we actually have this Thor's Hammer object storage instance which is up and running. Now if we hop over to one of our existing object storage instances, we can see this has three buckets. So one for Kafka-queue, I'm actually using this for my Kafka cluster where I have right around 62 million objects all storing ProtoBus. The second one there is Spark. So I actually have a Spark cluster running on our Kubernetes deployed instance via ACS 2.0. Now this is doing analytics on top of this data using S3 as a storage backend. Now for these objects, we support native versioning, native object encryption as well as worm compliancy. So if you want to have expiry periods, retention intervals, that sort of thing, we can do all that. >> Got it. So essentially what we've just shown you is with upcoming objects as well that the same OS can now support VMs, files, objects, containers, all on the same one click operational fabric. And so that's in some way the real power of Nutanix is to still keep that consistency, scalability in place as we're covering each and every workload inside the enterprise. So before Steve gets off stage though, I wanted to talk to you guys a little bit about something that you know how many of you been to our Nutanix headquarters in San Jose, California? A few. I know there's like, I don't know, 4,000 or 5,000 people here. If you do come to the office, you know when you land in San Jose Airport on the way to longterm parking, you'll pass our office. It's that close. And if you come to the fourth floor, you know one of the cubes that's where I sit. In the cube beside me is Steve. Steve sits in the cube beside me. And when I first joined the company, three or four years ago, and Steve's if you go to his cube, it no longer looks like this, but it used to have a lot of this stuff. It was like big containers of this. I remember the first time. Since I started joking about it, he started reducing it. And then Steve eventually got married much to our surprise. (audience laughing) Much to his wife's surprise. And then he also had a baby as a bigger surprise. And if you come over to our office, and we welcome you, and you come to the fourth floor, find my cube or you'll find Steve's Cube, it now looks like this. Okay, so thanks a lot, my man. >> Cool, thank you. >> Thanks so much. (audience clapping) >> So single OS, any workload. And like Steve who's been with us for awhile, it's my great pleasure to invite one of our favorite customers, CSC Karen who's also been with us for three to four years. And I'll share some fond memories about how she's been with the company for awhile, how as partners we've really done a lot together. So without any further ado, let me bring up Karen. Come on up, Karen. (rock music) >> Thank you for having me. >> Yeah, thank you. So I remember, so how many of you guys were with Nutanix first .Next in Miami? I know there was a question like that asked last time. Not too many. You missed it. We wished we could go back to that. We wouldn't fit 3/4s of this crowd. But Karen was our first customer in the keynote in 2015. And we had just talked about that story at that time where you're just become a customer. Do you want to give us some recap of that? >> Sure. So when we made the decision to move to hyperconverged infrastructure and chose Nutanix as our partner, we rapidly started to deploy. And what I mean by that is Sunil and some of the Nutanix executives had come out to visit with us and talk about their product on a Tuesday. And on a Wednesday after making the decision, I picked up the phone and said you know what I've got to deploy for my VDI cluster. So four nodes showed up on Thursday. And from the time it was plugged in to moving over 300 VDIs and 50 terabytes of storage and turning it over for the business for use was less than three days. So it was really excellent testament to how simple it is to start, and deploy, and utilize the Nutanix infrastructure. Now part of that was the delight that we experienced from our customers after that deployment. So we got phone calls where people were saying this report it used to take so long that I'd got out and get a cup of coffee and come back, and read an article, and do some email, and then finally it would finish. Those reports are running in milliseconds now. It's one click. It's very, very simple, and we've delighted our customers. Now across that journey, we have gone from the simple workloads like VDIs to the much more complex workloads around Splunk and Hadoop. And what's really interesting about our Splunk deployment is we're handling over a billion events being logged everyday. And the deployment is smaller than what we had with a three tiered infrastructure. So when you hear people talk about waste and getting that out and getting to an invisible environment where you're just able to run it, that's what we were able to achieve both with everything that we're running from our public facing websites to the back office operations that we're using which include Splunk and even most recently our Cloudera and Hadoop infrastructure. What it does is it's got 30 crawlers that go out on the internet and start bringing data back. So it comes back with over two terabytes of data everyday. And then that environment, ingests that data, does work against it, and responds to the business. And that again is something that's smaller than what we had on traditional infrastructure, and it's faster and more stable. >> Got it. And it covers a lot of use cases as well. You want to speak a few words on that? >> So the use cases, we're 90%, 95% deployed on Nutanix, and we're covering all of our use cases. So whether that's a customer facing app or a back office application. And what are business is doing is it's handling large portfolios of data for fortune 500 companies and law firms. And these applications are all running with improved stability, reliability, and performance on the Nutanix infrastructure. >> And the plan going forward? >> So the plan going forward, you actually asked me that in Miami, and it's go global. So when we started in Miami and that first deployment, we had four nodes. We now have 283 nodes around the world, and we started with about 50 terabytes of data. We've now got 3.8 petabytes of data. And we're deployed across four data centers and six remote offices. And people ask me often what is the value that we achieved? So simplification. It's all just easier, and it's all less expensive. Being able to scale with the business. So our Cloudera environment ended up with one day where it spiked to 1,000 times more load, 1,000 times, and it just responded. We had rally cries around improved productivity by six times. So 600% improved productivity, and we were able to actually achieve that. The numbers you just saw on the slide that was very, very fast was we calculated a 40% reduction in total cost of ownership. We've exceeded that. And when we talk about waste, that other number on the board there is when I saved the company one hour of maintenance activity or unplanned downtime in a month which we're now able to do the majority of our maintenance activities without disrupting any of our business solutions, I'm saving $750,000 each time I save that one hour. >> Wow. All right, Karen from CSE. Thank you so much. That was great. Thank you. I mean you know some of these data points frankly as I started talking to Karen as well as some other customers are pretty amazing in terms of the genuine value beyond financial value. Kind of like the emotional sort of benefits that good products deliver to some of our customers. And I think that's one of the core things that we take back into engineering is to keep ourselves honest on either velocity or quality even hiring people and so forth. Is to actually the more we touch customers lives, the more we touch our partner's lives, the more it allows us to ensure that we can put ourselves in their shoes to kind of make sure that we're doing the right thing in terms of the product. So that was the first part, invisible infrastructure. And our goal, as we've always talked about, our true North is to make sure that this single OS can be an exact replica, a truly modern, thoughtful but original design that brings the power of public cloud this AWS or GCP like architectures into your mainstream enterprises. And so when we take that to the next level which is about expanding the scope to go beyond invisible infrastructure to invisible data centers, it starts with a few things. Obviously, it starts with virtualization and a level of intelligent management, extends to automation, and then as we'll talk about, we have to embark on encompassing the network. And that's what we'll talk about with Flow. But to start this, let me again go back to one of our core products which is the bedrock of our you know opinionated design inside this company which is Prism and Acropolis. And Prism provides, I mentioned, comes with a ton of machine-learning based intelligence built into the product in 5.6 we've done a ton of work. In fact, a lot of features are coming out now because now that PC, Prism Central that you know has been decoupled from our mainstream release strain and will continue to release on its own cadence. And the same thing when you actually flip it to AHV on its own train. Now AHV, two years ago it was all about can I use AHV for VDI? Can I use AHV for ROBO? Now I'm pretty clear about where you cannot use AHV. If you need memory overcome it, stay with VMware or something. If you need, you know Metro, stay with another technology, else it's game on, right? And if you really look at the adoption of AHV in the mainstream enterprise, the customers now speak for themselves. These are all examples of large global enterprises with multimillion dollar ELAs in play that have now been switched over. Like I'll give you a simple example here, and there's lots of these that I'm sure many of you who are in the audience that are in this camp, but when you look at the breakout sessions in the pods, you'll get a sense of this. But I'll give you one simple example. If you look at the online payment company. I'm pretty sure everybody's used this at one time or the other. They had the world's largest private cloud on open stack, 21,000 nodes. And they were actually public about it three or four years ago. And in the last year and a half, they put us through a rigorous VOC testing scale, hardening, and it's a full blown AHV only stack. And they've started cutting over. Obviously they're not there yet completely, but they're now literally in hundreds of nodes of deployment of Nutanix with AHV as their primary operating system. So it is primetime from a deployment perspective. And with that as the base, no cloud is complete without actually having self-service provisioning that truly drives one-click automation, and can you do that in this consumer grade design? And Calm was acquired, as you guys know, in 2016. We had a choice of taking Calm. It was reasonably feature complete. It supported multiple clouds. It supported ESX, it supported Brownfield, It supported AHV. I mean they'd already done the integration with Nutanix even before the acquisition. And we had a choice. The choice was go down the path of dynamic ops or some other products where you took it for revenue or for acceleration, you plopped it into the ecosystem and sold it at this power sucking alien on top of our stack, right? Or we took a step back, re-engineered the product, kept some of the core essence like the workflow engine which was good, the automation, the object model and all, but refactored it to make it look like a natural extension of our operating system. And that's what we did with Calm. And we just launched it in December, and it's been one of our most popular new products now that's flying off the shelves. If you saw the number of registrants, I got a notification of this for the breakout sessions, the number one session that has been preregistered with over 500 people, the first two sessions are around Calm. And justifiably so because it just as it lives up to its promise, and it'll take its time to kind of get to all the bells and whistles, all the capabilities that have come through with AHV or Acropolis in the past. But the feature functionality, the product market fit associated with Calm is dead on from what the feedback that we can receive. And so Calm itself is on its own rapid cadence. We had AWS and AHV in the first release. Three or four months later, we now added ESX support. We added GCP support and a whole bunch of other capabilities, and I think the essence of Calm is if you can combine Calm and along with private cloud automation but also extend it to multi-cloud automation, it really sets Nutanix on its first genuine path towards multi-cloud. But then, as I said, if you really fixate on a software defined data center message, we're not complete as a full blown AWS or GCP like IA stack until we do the last horizon of networking. And you probably heard me say this before. You heard Dheeraj and others talk about it before is our problem in networking isn't the same in storage. Because the data plane in networking works. Good L2 switches from Cisco, Arista, and so forth, but the real problem networking is in the control plane. When something goes wrong at a VM level in Nutanix, you're able to identify whether it's a storage problem or a compute problem, but we don't know whether it's a VLAN that's mis-configured, or there've been some packets dropped at the top of the rack. Well that all ends now with Flow. And with Flow, essentially what we've now done is take the work that we've been working on to create built-in visibility, put some network automation so that you can actually provision VLANs when you provision VMs. And then augment it with micro segmentation policies all built in this easy to use, consume fashion. But we didn't stop there because we've been talking about Flow, at least the capabilities, over the last year. We spent significant resources building it. But we realized that we needed an additional thing to augment its value because the world of applications especially discovering application topologies is a heady problem. And if we didn't address that, we wouldn't be fulfilling on this ambition of providing one-click network segmentation. And so that's where Netsil comes in. Netsil might seem on the surface yet another next generation application performance management tool. But the innovations that came from Netsil started off at the research project at the University of Pennsylvania. And in fact, most of the team right now that's at Nutanix is from the U Penn research group. And they took a really original, fresh look at how do you sit in a network in a scale out fashion but still reverse engineer the packets, the flow through you, and then recreate this application topology. And recreate this not just on Nutanix, but do it seamlessly across multiple clouds. And to talk about the power of Flow augmented with Netsil, let's bring Rajiv back on stage, Rajiv. >> How you doing? >> Okay so we're going to start with some Netsil stuff, right? >> Yeah, let's talk about Netsil and some of the amazing capabilities this acquisition's bringing to Nutanix. First of all as you mentioned, Netsil's completely non invasive. So it installs on the network, it does all its magic from there. There're no host agents, non of the complexity and compatibility issues that entails. It's also monitoring the network at layer seven. So it's actually doing a deep packet inspection on all your application data, and can give you insights into services and APIs which is very important for modern applications and the way they behave. To do all this of course performance is key. So Netsil's built around a completely distributed architecture scaled to really large workloads. Very exciting technology. We're going to use it in many different ways at Nutanix. And to give you a flavor of that, let me show you how we're thinking of integrating Flow and Nestil together, so micro segmentation and Netsil. So to do that, we install Netsil in one of our Google accounts. And that's what's up here now. It went out there. It discovered all the VMs we're running on that account. It created a map essentially of all their interactions, and you can see it's like a Google Maps view. I can zoom into it. I can look at various things running. I can see lots of HTTP servers over here, some databases. >> Sunil: And it also has stats, right? You can go, it actually-- >> It does. We can take a look at that for a second. There are some stats you can look at right away here. Things like transactions per second and latencies and so on. But if I wanted to micro segment this application, it's not really clear how to do so. There's no real pattern over here. Taking the Google Maps analogy a little further, this kind of looks like the backstreets of Cairo or something. So let's do this step by step. Let me first filter down to one application. Right now I'm looking at about three or four different applications. And Netsil integrates with the metadata. So this is that the clouds provide. So I can search all the tags that I have. So by doing that, I can zoom in on just the financial application. And when I do this, the view gets a little bit simpler, but there's still no real pattern. It's not clear how to micro segment this, right? And this is where the power of Netsil comes in. This is a fairly naive view. This is what tool operating at layer four just looking at ports and TCP traffic would give you. But by doing deep packet inspection, Netsil can get into the services layer. So instead of grouping these interactions by hostname, let's group them by service. So you go service tier. And now you can see this is a much simpler picture. Now I have some patterns. I have a couple of load balancers, an HA proxy and an Nginx. I have a web application front end. I have some application servers running authentication services, search services, et cetera, a database, and a database replica. I could go ahead and micro segment at this point. It's quite possible to do it at this point. But this is almost too granular a view. We actually don't usually want to micro segment at individual service level. You think more in terms of application tiers, the tiers that different services belong to. So let me go ahead and group this differently. Let me group this by app tier. And when I do that, a really simple picture emerges. I have a load balancing tier talking to a web application front end tier, an API tier, and a database tier. Four tiers in my application. And this is something I can work with. This is something that I can micro segment fairly easily. So let's switch over to-- >> Before we dot that though, do you guys see how he gave himself the pseudonym called Dom Toretto? >> Focus Sunil, focus. >> Yeah, for those guys, you know that's not the Avengers theme, man, that's the Fast and Furious theme. >> Rajiv: I think a year ahead. This is next years theme. >> Got it, okay. So before we cut over from Netsil to Flow, do we want to talk a few words about the power of Flow, and what's available in 5.6? >> Sure so Flow's been around since the 5.6 release. Actually some of the functionality came in before that. So it's got invisibility into the network. It helps you debug problems with WLANs and so on. We had a lot of orchestration with other third party vendors with load balancers, with switches to make publishing much simpler. And then of course with our most recent release, we GA'ed our micro segmentation capabilities. And that of course is the most important feature we have in Flow right now. And if you look at how Flow policy is set up, it looks very similar to what we just saw with Netsil. So we have load blancer talking to a web app, API, database. It's almost identical to what we saw just a moment ago. So while this policy was created manually, it is something that we can automate. And it is something that we will do in future releases. Right now, it's of course not been integrated at that level yet. So this was created manually. So one thing you'll notice over here is that the database tier doesn't get any direct traffic from the internet. All internet traffic goes to the load balancer, only specific services then talk to the database. So this policy right now is in monitoring mode. It's not actually being enforced. So let's see what happens if I try to attack the database, I start a hack against the database. And I have my trusty brute force password script over here. It's trying the most common passwords against the database. And if I happen to choose a dictionary word or left the default passwords on, eventually it will log into the database. And when I go back over here in Flow what happens is it actually detects there's now an ongoing a flow, a flow that's outside of policy that's shown up. And it shows this in yellow. So right alongside the policy, I can visualize all the noncompliant flows. This makes it really easy for me now to make decisions, does this flow should it be part of the policy, should it not? In this particular case, obviously it should not be part of the policy. So let me just switch from monitoring mode to enforcement mode. I'll apply the policy, give it a second to propagate. The flow goes away. And if I go back to my script, you can see now the socket's timing out. I can no longer connect to the database. >> Sunil: Got it. So that's like one click segmentation and play right now? >> Absolutely. It's really, really simple. You can compare it to other products in the space. You can't get simpler than this. >> Got it. Why don't we got back and talk a little bit more about, so that's Flow. It's shipping now in 5.6 obviously. It'll come integrated with Netsil functionality as well as a variety of other enhancements in that next few releases. But Netsil does more than just simple topology discovery, right? >> Absolutely. So Netsil's actually gathering a lot of metrics from your network, from your host, all this goes through a data pipeline. It gets processed over there and then gets captured in a time series database. And then we can slice and dice that in various different ways. It can be used for all kinds of insights. So let's see how our application's behaving. So let me say I want to go into the API layer over here. And I instantly get a variety of metrics on how the application's behaving. I get the most requested endpoints. I get the average latency. It looks reasonably good. I get the average latency of the slowest endpoints. If I was having a performance problem, I would know exactly where to go focus on. Right now, things look very good, so we won't focus on that. But scrolling back up, I notice that we have a fairly high error rate happening. We have like 11.35% of our HTTP requests are generating errors, and that deserves some attention. And if I scroll down again, and I see the top five status codes I'm getting, almost 10% of my requests are generating 500 errors, HTTP 500 errors which are internal server errors. So there's something going on that's wrong with this application. So let's dig a little bit deeper into that. Let me go into my analytics workbench over here. And what I've plotted over here is how my HTTP requests are behaving over time. Let me filter down to just the 500 ones. That will make it easier. And I want the 500s. And I'll also group this by the service tier so that I can see which services are causing the problem. And the better view for this would be a bar graph. Yes, so once I do this, you can see that all the errors, all the 500 errors that we're seeing have been caused by the authentication service. So something's obviously wrong with that part of my application. I can go look at whether Active Directory is misbehaving and so on. So very quickly from a broad problem that I was getting a high HTTP error rate. In fact, usually you will discover there's this customer complaining about a lot of errors happening in your application. You can quickly narrow down to exactly what the cause was. >> Got it. This is what we mean by hyperconvergence of the network which is if you can truly isolate network related problems and associate them with the rest of the hyperconvergence infrastructure, then we've essentially started making real progress towards the next level of hyperconvergence. Anyway, thanks a lot, man. Great job. >> Thanks, man. (audience clapping) >> So to talk about this evolution from invisible infrastructure to invisible data centers is another customer of ours that has embarked on this journey. And you know it's not just using Nutanix but a variety of other tools to actually fulfill sort of like the ambition of a full blown cloud stack within a financial organization. And to talk more about that, let me call Vijay onstage. Come on up, Vijay. (rock music) >> Hey. >> Thank you, sir. So Vijay looks way better in real life than in a picture by the way. >> Except a little bit of gray. >> Unlike me. So tell me a little bit about this cloud initiative. >> Yeah. So we've won the best cloud initiative twice now hosted by Incisive media a large magazine. It's basically they host a bunch of you know various buy side, sell side, and you can submit projects in various categories. So we've won the best cloud twice now, 2015 and 2017. The 2017 award is when you know as part of our private cloud journey we were laying the foundation for our private cloud which is 100% based on hyperconverged infrastructure. So that was that award. And then 2017, we've kind of built on that foundation and built more developer-centric next gen app services like PAS, CAS, SDN, SDS, CICD, et cetera. So we've built a lot of those services on, and the second award was really related to that. >> Got it. And a lot of this was obviously based on an infrastructure strategy with some guiding principles that you guys had about three or four years ago if I remember. >> Yeah, this is a great slide. I use it very often. At the core of our infrastructure strategy is how do we run IT as a business? I talk about this with my teams, they were very familiar with this. That's the mindset that I instill within the teams. The mission, the challenge is the same which is how do we scale infrastructure while reducing total cost of ownership, improving time to market, improving client experience and while we're doing that not lose sight of reliability, stability, and security? That's the mission. Those are some of our guiding principles. Whenever we take on some large technology investments, we take 'em through those lenses. Obviously Nutanix went through those lenses when we invested in you guys many, many years ago. And you guys checked all the boxes. And you know initiatives change year on year, the mission remains the same. And more recently, the last few years, we've been focused on converged platforms, converged teams. We've actually reorganized our teams and aligned them closer to the platforms moving closer to an SRE like concept. >> And then you've built out a full stack now across computer storage, networking, all the way with various use cases in play? >> Yeah, and we're aggressively moving towards PAS, CAS as our method of either developing brand new cloud native applications or even containerizing existing applications. So the stack you know obviously built on Nutanix, SDS for software fine storage, compute and networking we've got SDN turned on. We've got, again, PAS and CAS built on this platform. And then finally, we've hooked our CICD tooling onto this. And again, the big picture was always frictionless infrastructure which we're very close to now. You know 100% of our code deployments into this environment are automated. >> Got it. And so what's the net, net in terms of obviously the business takeaway here? >> Yeah so at Northern we don't do tech for tech. It has to be some business benefits, client benefits. There has to be some outcomes that we measure ourselves against, and these are some great metrics or great ways to look at if we're getting the outcomes from the investments we're making. So for example, infrastructure scale while reducing total cost of ownership. We're very focused on total cost of ownership. We, for example, there was a build team that was very focus on building servers, deploying applications. That team's gone down from I think 40, 45 people to about 15 people as one example, one metric. Another metric for reducing TCO is we've been able to absorb additional capacity without increasing operating expenses. So you're actually building capacity in scale within your operating model. So that's another example. Another example, right here you see on the screen. Faster time to market. We've got various types of applications at any given point that we're deploying. There's a next gen cloud native which go directly on PAS. But then a majority of the applications still need the traditional IS components. The time to market to deploy a complex multi environment, multi data center application, we've taken that down by 60%. So we can deliver server same day, but we can deliver entire environments, you know add it to backup, add it to DNS, and fully compliant within a couple of weeks which is you know something we measure very closely. >> Great job, man. I mean that's a compelling I think results. And in the journey obviously you got promoted a few times. >> Yep. >> All right, congratulations again. >> Thank you. >> Thanks Vijay. >> Hey Vijay, come back here. Actually we forgot our joke. So razzled by his data points there. So you're supposed to wear some shoes, right? >> I know my inner glitch. I was going to wear those sneakers, but I forgot them at the office maybe for the right reasons. But the story behind those florescent sneakers, I see they're focused on my shoes. But I picked those up two years ago at a Next event, and not my style. I took 'em to my office. They've been sitting in my office for the last couple years. >> Who's received shoes like these by the way? I'm sure you guys have received shoes like these. There's some real fans there. >> So again, I'm sure many of you liked them. I had 'em in my office. I've offered it to so many of my engineers. Are you size 11? Do you want these? And they're unclaimed? >> So that's the only feature of Nutanix that you-- >> That's the only thing that hasn't worked, other than that things are going extremely well. >> Good job, man. Thanks a lot. >> Thanks. >> Thanks Vijay. So as we get to the final phase which is obviously as we embark on this multi-cloud journey and the complexity that comes with it which Dheeraj hinted towards in his session. You know we have to take a cautious, thoughtful approach here because we don't want to over set expectations because this will take us five, 10 years to really do a good job like we've done in the first act. And the good news is that the market is also really, really early here. It's just a fact. And so we've taken a tiered approach to it as we'll start the discussion with multi-cloud operations, and we've talked about the stack in the prior session which is about look across new clouds. So it's no longer Nutanix, Dell, Lenova, HP, Cisco as the new quote, unquote platforms. It's Nutanix, Xi, GCP, AWS, Azure as the new platforms. That's how we're designing the fabric going forward. On top of that, you obviously have the hybrid OS both on the data plane side and control plane side. Then what you're seeing with the advent of Calm doing a marketplace and automation as well as Beam doing governance and compliance is the fact that you'll see more and more such capabilities of multi-cloud operations burnt into the platform. And example of that is Calm with the new 5.7 release that they had. Launch supports multiple clouds both inside and outside, but the fundamental premise of Calm in the multi-cloud use case is to enable you to choose the right cloud for the right workload. That's the automation part. On the governance part, and this we kind of went through in the last half an hour with Dheeraj and Vijay on stage is something that's even more, if I can call it, you know first order because you get the provisioning and operations second. The first order is to say look whatever my developers have consumed off public cloud, I just need to first get our arm around to make sure that you know what am I spending, am I secure, and then when I get comfortable, then I am able to actually expand on it. And that's the power of Beam. And both Beam and Calm will be the yin and yang for us in our multi-cloud portfolio. And we'll have new products to complement that down the road, right? But along the way, that's the whole private cloud, public cloud. They're the two ends of the barbell, and over time, and we've been working on Xi for awhile, is this conviction that we've built talking to many customers that there needs to be another type of cloud. And this type of a cloud has to feel like a public cloud. It has to be architected like a public cloud, be consumed like a public cloud, but it needs to be an extension of my data center. It should not require any changes to my tooling. It should not require and changes to my operational infrastructure, and it should not require lift and shift, and that's a super hard problem. And this problem is something that a chunk of our R and D team has been burning the midnight wick on for the last year and a half. Because look this is not about taking our current OS which does a good job of scaling and plopping it into a Equinix or a third party data center and calling it a hybrid cloud. This is about rebuilding things in the OS so that we can deliver a true hybrid cloud, but at the same time, give those functionality back on premises so that even if you don't have a hybrid cloud, if you just have your own data centers, you'll still need new services like DR. And if you think about it, what are we doing? We're building a full blown multi-tenant virtual network designed in a modern way. Think about this SDN 2.0 because we have 10 years worth of looking backwards on how GCP has done it, or how Amazon has done it, and now sort of embodying some of that so that we can actually give it as part of this cloud, but do it in a way that's a seamless extension of the data center, and then at the same time, provide new services that have never been delivered before. Everyone obviously does failover and failback in DR it just takes months to do it. Our goal is to do it in hours or minutes. But even things such as test. Imagine doing a DR test on demand for you business needs in the middle of the day. And that's the real bar that we've set for Xi that we are working towards in early access later this summer with GA later in the year. And to talk more about this, let me invite some of our core architects working on it, Melina and Rajiv. (rock music) Good to see you guys. >> You're messing up the names again. >> Oh Rajiv, Vinny, same thing, man. >> You need to back up your memory from Xi. >> Yeah, we should. Okay, so what are we going to talk about, Vinny? >> Yeah, exactly. So today we're going to talk about how Xi is pushing the envelope and beyond the state of the art as you were saying in the industry. As part of that, there's a whole bunch of things that we have done starting with taking a private cloud, seamlessly extending it to the public cloud, and then creating a hybrid cloud experience with one-click delight. We're going to show that. We've done a whole bunch of engineering work on making sure the operations and the tooling is identical on both sides. When you graduate from a private cloud to a hybrid cloud environment, you don't want the environments to be different. So we've copied the environment for you with zero manual intervention. And finally, building on top of that, we are delivering DR as a service with unprecedented simplicity with one-click failover, one-click failback. We're going to show you one click test today. So Melina, why don't we start with showing how you go from a private cloud, seamlessly extend it to consume Xi. >> Sounds good, thanks Vinny. Right now, you're looking at my Prism interface for my on premises cluster. In one-click, I'm going to be able to extend that to my Xi cloud services account. I'm doing this using my my Nutanix credential and a password manager. >> Vinny: So here as you notice all the Nutanix customers we have today, we have created an account for them in Xi by default. So you don't have to log in somewhere and create an account. It's there by default. >> Melina: And just like that we've gone ahead and extended my data center. But let's go take a look at the Xi side and log in again with my my Nutanix credentials. We'll see what we have over here. We're going to be able to see two availability zones, one for on premises and one for Xi right here. >> Vinny: Yeah as you see, using a log in account that you already knew mynutanix.com and 30 seconds in, you can see that you have a hybrid cloud view already. You have a private cloud availability zone that's your own Prism central data center view, and then a Xi availability zone. >> Sunil: Got it. >> Melina: Exactly. But of course we want to extend my network connection from on premises to my Xi networks as well. So let's take a look at our options there. We have two ways of doing this. Both are one-click experience. With direct connect, you can create a dedicated network connection between both environments, or VPN you can use a public internet and a VPN service. Let's go ahead and enable VPN in this environment. Here we have two options for how we want to enable our VPN. We can bring our own VPN and connect it, or we will deploy a VPN for you on premises. We'll do the option where we deploy the VPN in one-click. >> And this is another small sign or feature that we're building net new as part of Xi, but will be burned into our core Acropolis OS so that we can also be delivering this as a stand alone product for on premises deployment as well, right? So that's one of the other things to note as you guys look at the Xi functionality. The goal is to keep the OS capabilities the same on both sides. So even if I'm building a quote, unquote multi data center cloud, but it's just a private cloud, you'll still get all the benefits of Xi but in house. >> Exactly. And on this second step of the wizard, there's a few inputs around how you want the gateway configured, your VLAN information and routing and protocol configuration details. Let's go ahead and save it. >> Vinny: So right now, you know what's happening is we're taking the private network that our customers have on premises and extending it to a multi-tenant public cloud such that our customers can use their IP addresses, the subnets, and bring their own IP. And that is another step towards making sure the operation and tooling is kept consistent on both sides. >> Melina: Exactly. And just while you guys were talking, the VPN was successfully created on premises. And we can see the details right here. You can track details like the status of the connection, the gateway, as well as bandwidth information right in the same UI. >> Vinny: And networking is just tip of the iceberg of what we've had to work on to make sure that you get a consistent experience on both sides. So Melina, why don't we show some of the other things we've done? >> Melina: Sure, to talk about how we preserve entities from my on-premises to Xi, it's better to use my production environment. And first thing you might notice is the log in screen's a little bit different. But that's because I'm logging in using my ADFS credentials. The first thing we preserved was our users. In production, I'm running AD obviously on-prem. And now we can log in here with the same set of credentials. Let me just refresh this. >> And this is the Active Directory credential that our customers would have. They use it on-premises. And we allow the setting to be set on the Xi cloud services as well, so it's the same set of users that can access both sides. >> Got it. There's always going to be some networking problem onstage. It's meant to happen. >> There you go. >> Just launching it again here. I think it maybe timed out. This is a good sign that we're running on time with this presentation. >> Yeah, yeah, we're running ahead of time. >> Move the demos quicker, then we'll time out. So essentially when you log into Xi, you'll be able to see what are the environment capabilities that we have copied to the Xi environment. So for example, you just saw that the same user is being used to log in. But after the use logs in, you'll be able to see their images, for example, copied to the Xi side. You'll be able to see their policies and categories. You know when you define these policies on premises, you spend a lot of effort and create them. And now when you're extending to the public cloud, you don't want to do it again, right? So we've done a whole lot of syncing mechanisms making sure that the two sides are consistent. >> Got it. And on top of these policies, the next step is to also show capabilities to actually do failover and failback, but also do integrated testing as part of this compatibility. >> So one is you know just the basic job of making the environments consistent on two sides, but then it's also now talking about the data part, and that's what DR is about. So if you have a workload running on premises, we can take the data and replicate it using your policies that we've already synced. Once the data is available on the Xi side, at that point, you have to define a run book. And the run book essentially it's a recovery plan. And that says okay I already have the backups of my VMs in case of disaster. I can take my recovery plan and hit you know either failover or maybe a test. And then my application comes up. First of all, you'll talk about the boot order for your VMs to come up. You'll talk about networking mapping. Like when I'm running on-prem, you're using a particular subnet. You have an option of using the same subnet on the Xi side. >> Melina: There you go. >> What happened? >> Sunil: It's finally working.? >> Melina: Yeah. >> Vinny, you can stop talking. (audience clapping) By the way, this is logging into a live Xi data center. We have two regions West Coat, two data centers East Coast, two data centers. So everything that you're seeing is essentially coming off the mainstream Xi profile. >> Vinny: Melina, why don't we show the recovery plan. That's the most interesting piece here. >> Sure. The recovery plan is set up to help you specify how you want to recover your applications in the event of a failover or a test failover. And it specifies all sorts of details like the boot sequence for the VMs as well as network mappings. Some of the network mappings are things like the production network I have running on premises and how it maps to my production network on Xi or the test network to the test network. What's really cool here though is we're actually automatically creating your subnets on Xi from your on premises subnets. All that's part of the recovery plan. While we're on the screen, take a note of the .100 IP address. That's a floating IP address that I have set up to ensure that I'm going to be able to access my three tier web app that I have protected with this plan after a failover. So I'll be able to access it from the public internet really easily from my phone or check that it's all running. >> Right, so given how we make the environment consistent on both sides, now we're able to create a very simple DR experience including failover in one-click, failback. But we're going to show you test now. So Melina, let's talk about test because that's one of the most common operations you would do. Like some of our customers do it every month. But usually it's very hard. So let's see how the experience looks like in what we built. >> Sure. Test and failover are both one-click experiences as you know and come to expect from Nutanix. You can see it's failing over from my primary location to my recovery location. Now what we're doing right now is we're running a series of validation checks because we want to make sure that you have your network configured properly, and there's other configuration details in place for the test to be successful. Looks like the failover was initiated successfully. Now while that failover's happening though, let's make sure that I'm going to be able to access my three tier web app once it fails over. We'll do that by looking at my network policies that I've configured on my test network. Because I want to access the application from the public internet but only port 80. And if we look here under our policies, you can see I have port 80 open to permit. So that's good. And if I needed to create a new one, I could in one click. But it looks like we're good to go. Let's go back and check the status of my recovery plan. We click in, and what's really cool here is you can actually see the individual tasks as they're being completed from that initial validation test to individual VMs being powered on as part of the recovery plan. >> And to give you guys an idea behind the scenes, the entire recovery plan is actually a set of workflows that are built on Calm's automation engine. So this is an example of where we're taking some of power of workflow and automation that Clam has come to be really strong at and burning that into how we actually operationalize many of these workflows for Xi. >> And so great, while you were explaining that, my three tier web app has restarted here on Xi right in front of you. And you can see here there's a floating IP that I mentioned early that .100 IP address. But let's go ahead and launch the console and make sure the application started up correctly. >> Vinny: Yeah, so that .100 IP address is a floating IP that's a publicly visible IP. So it's listed here, 206.80.146.100. And that's essentially anybody in the audience here can go use your laptop or your cell phone and hit that and start to work. >> Yeah so by the way, just to give you guys an idea while you guys maybe use the IP to kind of hit it, is a real set of VMs that we've just failed over from Nutanix's corporate data center into our West region. >> And this is running live on the Xi cloud. >> Yeah, you guys should all go and vote. I'm a little biased towards Xi, so vote for Xi. But all of them are really good features. >> Scroll up a little bit. Let's see where Xi is. >> Oh Xi's here. I'll scroll down a little bit, but keep the... >> Vinny: Yes. >> Sunil: You guys written a block or something? >> Melina: Oh good, it looks like Xi's winning. >> Sunil: Okay, great job, Melina. Thank you so much. >> Thank you, Melina. >> Melina: Thanks. >> Thank you, great job. Cool and calm under pressure. That's good. So that was Xi. What's something that you know we've been doing around you know in addition to taking say our own extended enterprise public cloud with Xi. You know we do recognize that there are a ton of workloads that are going to be residing on AWS, GCP, Azure. And to sort of really assist in the try and call it transformation of enterprises to choose the right cloud for the right workload. If you guys remember, we actually invested in a tool over last year which became actually quite like one of those products that took off based on you know groundswell movement. Most of you guys started using it. It's essentially extract for VMs. And it was this product that's obviously free. It's a tool. But it enables customers to really save tons of time to actually migrate from legacy environments to Nutanix. So we took that same framework, obviously re-platformed it for the multi-cloud world to kind of solve the problem of migrating from AWS or GCP to Nutanix or vice versa. >> Right, so you know, Sunil as you said, moving from a private cloud to the public cloud is a lift and shift, and it's a hard you know operation. But moving back is not only expensive, it's a very hard problem. None of the cloud vendors provide change block tracking capability. And what that means is when you have to move back from the cloud, you have an extended period of downtime because there's now way of figuring out what's changing while you're moving. So you have to keep it down. So what we've done with our app mobility product is we have made sure that, one, it's extremely simple to move back. Two, that the downtime that you'll have is as small as possible. So let me show you what we've done. >> Got it. >> So here is our app mobility capability. As you can see, on the left hand side we have a source environment and target environment. So I'm calling my AWS environment Asgard. And I can add more environments. It's very simple. I can select AWS and then put in my credentials for AWS. It essentially goes and discovers all the VMs that are running and all the regions that they're running. Target environment, this is my Nutanix environment. I call it Earth. And I can add target environment similarly, IP address and credentials, and we do the rest. Right, okay. Now migration plans. I have Bifrost one as my migration plan, and this is how migration works. First you create a plan and then say start seeding. And what it does is takes a snapshot of what's running in the cloud and starts migrating it to on-prem. Once it is an on-prem and the difference between the two sides is minimal, it says I'm ready to cutover. At that time, you move it. But let me show you how you'd create a new migration plan. So let me name it, Bifrost 2. Okay so what I have to do is select a region, so US West 1, and target Earth as my cluster. This is my storage container there. And very quickly you can see these are the VMs that are running in US West 1 in AWS. I can select SQL server one and two, go to next. Right now it's looking at the target Nutanix environment and seeing it had enough space or not. Once that's good, it gives me an option. And this is the step where it enables the Nutanix service of change block tracking overlaid on top of the cloud. There are two options one is automatic where you'll give us the credentials for your VMs, and we'll inject our capability there. Or manually you could do. You could copy the command either in a windows VM or Linux VM and run it once on the VM. And change block tracking since then in enabled. Everything is seamless after that. Hit next. >> And while Vinny's setting it up, he said a few things there. I don't know if you guys caught it. One of the hardest problems in enabling seamless migration from public cloud to on-prem which makes it harder than the other way around is the fact that public cloud doesn't have things like change block tracking. You can't get delta copies. So one of the core innovations being built in this app mobility product is to provide that overlay capability across multiple clouds. >> Yeah, and the last step here was to select the target network where the VMs will come up on the Nutanix environment, and this is a summary of the migration plan. You can start it or just save it. I'm saving it because it takes time to do the seeding. I have the other plan which I'll actually show the cutover with. Okay so now this is Bifrost 1. It's ready to cutover. We started it four hours ago. And here you can see there's a SQL server 003. Okay, now I would like to show the AWS environment. As you can see, SQL server 003. This VM is actually running in AWS right now. And if you go to the Prism environment, and if my login works, right? So we can go into the virtual machine view, tables, and you see the VM is not there. Okay, so we go back to this, and we can hit cutover. So this is essentially telling our system, okay now it the time. Quiesce the VM running in AWS, take the last bit of changes that you have to the database, ship it to on-prem, and in on-prem now start you know configure the target VM and start bringing it up. So let's go and look at AWS and refresh that screen. And you should see, okay so the SQL server is now stopping. So that means it has quiesced and stopping the VM there. If you go back and look at the migration plan that we had, it says it's completed. So it has actually migrated all the data to the on-prem side. Go here on-prem, you see the production SQL server is running already. I can click launch console, and let's see. The Windows VM is already booting up. >> So essentially what Vinny just showed was a live cutover of an AWS VM to Nutanix on-premises. >> Yeah, and what we have done. (audience clapping) So essentially, this is about making two things possible, making it simple to migrate from cloud to on-prem, and making it painless so that the downtime you have is very minimal. >> Got it, great job, Vinny. I won't forget your name again. So last step. So to really talk about this, one of our favorite partners and customers has been in the cloud environment for a long time. And you know Jason who's the CTO of Cyxtera. And he'll introduce who Cyxtera is. Most of you guys are probably either using their assets or not without knowing their you know the new name. But is someone that was in the cloud before it was called cloud as one of the original founders and technologists behind Terremark, and then later as one of the chief architects of VMware's cloud. And then they started this new company about a year or so ago which I'll let Jason talk about. This journey that he's going to talk about is how a partner, slash customer is working with us to deliver net new transformations around the traditional industry of colo. Okay, to talk more about it, Jason, why don't you come up on stage, man? (rock music) Thank you, sir. All right so Cyxtera obviously a lot of people don't know the name. Maybe just give a 10 second summary of why you're so big already. >> Sure, so Cyxtera was formed, as you said, about a year ago through the acquisition of the CenturyLink data centers. >> Sunil: Which includes Savvis and a whole bunch of other assets. >> Yeah, there's a long history of those data centers, but we have all of them now as well as the software companies owned by Medina capital. So we're like the world's biggest startup now. So we have over 50 data centers around the world, about 3,500 customers, and a portfolio of security and analytics software. >> Sunil: Got it, and so you have this strategy of what we're calling revolutionizing colo deliver a cloud based-- >> Yeah so, colo hasn't really changed a lot in the last 20 years. And to be fair, a lot of what happens in data centers has to have a person physically go and do it. But there are some things that we can simplify and automate. So we want to make things more software driven, so that's what we're doing with the Cyxtera extensible data center or CXD. And to do that, we're deploying software defined networks in our facilities and developing automations so customers can go and provision data center services and the network connectivity through a portal or through REST APIs. >> Got it, and what's different now? I know there's a whole bunch of benefits with the integrated platform that one would not get in the traditional kind of on demand data center environment. >> Sure. So one of the first services we're launching on CXD is compute on demand, and it's powered by Nutanix. And we had to pick an HCI partner to launch with. And we looked at players in the space. And as you mentioned, there's actually a lot of them, more than I thought. And we had a lot of conversations, did a lot of testing in the lab, and Nutanix really stood out as the best choice. You know Nutanix has a lot of focus on things like ease of deployment. So it's very simple for us to automate deploying compute for customers. So we can use foundation APIs to go configure the servers, and then we turn those over to the customer which they can then manage through Prism. And something important to keep in mind here is that you know this isn't a manged service. This isn't infrastructure as a service. The customer has complete control over the Nutanix platform. So we're turning that over to them. It's connected to their network. They're using their IP addresses, you know their tools and processes to operate this. So it was really important for the platform we picked to have a really good self-service story for things like you know lifecycle management. So with one-click upgrade, customers have total control over patches and upgrades. They don't have to call us to do it. You know they can drive that themselves. >> Got it. Any other final words around like what do you see of the partnership going forward? >> Well you know I think this would be a great platform for Xi, so I think we should probably talk about that. >> Yeah, yeah, we should talk about that separately. Thanks a lot, Jason. >> Thanks. >> All right, man. (audience clapping) So as we look at the full journey now between obviously from invisible infrastructure to invisible clouds, you know there is one thing though to take away beyond many updates that we've had so far. And the fact is that everything that I've talked about so far is about completing a full blown true IA stack from all the way from compute to storage, to vitualization, containers to network services, and so forth. But every public cloud, a true cloud in that sense, has a full blown layer of services that's set on top either for traditional workloads or for new workloads, whether it be machine-learning, whether it be big data, you know name it, right? And in the enterprise, if you think about it, many of these services are being provisioned or provided through a bunch of our partners. Like we have partnerships with Cloudera for big data and so forth. But then based on some customer feedback and a lot of attention from what we've seen in the industry go out, just like AWS, and GCP, and Azure, it's time for Nutanix to have an opinionated view of the past stack. It's time for us to kind of move up the stack with our own offering that obviously adds value but provides some of our core competencies in data and takes it to the next level. And it's in that sense that we're actually launching Nutanix Era to simplify one of the hardest problems in enterprise IT and short of saving you from true Oracle licensing, it solves various other Oracle problems which is about truly simplifying databases much like what RDS did on AWS, imagine enterprise RDS on demand where you can provision, lifecycle manage your database with one-click. And to talk about this powerful new functionality, let me invite Bala and John on stage to give you one final demo. (rock music) Good to see you guys. >> Yep, thank you. >> All right, so we've got lots of folks here. They're all anxious to get to the next level. So this demo, really rock it. So what are we going to talk about? We're going to start with say maybe some database provisioning? Do you want to set it up? >> We have one dream, Sunil, one single dream to pass you off, that is what Nutanix is today for IT apps, we want to recreate that magic for devops and get back those weekends and freedom to DBAs. >> Got it. Let's start with, what, provisioning? >> Bala: Yep, John. >> Yeah, we're going to get in provisioning. So provisioning databases inside the enterprise is a significant undertaking that usually involves a myriad of resources and could take days. It doesn't get any easier after that for the longterm maintence with things like upgrades and environment refreshes and so on. Bala and team have been working on this challenge for quite awhile now. So we've architected Nutanix Era to cater to these enterprise use cases and make it one-click like you said. And Bala and I are so excited to finally show this to the world. We think it's actually Nutanix's best kept secrets. >> Got it, all right man, let's take a look at it. >> So we're going to be provisioning a sales database today. It's a four-step workflow. The first part is choosing our database engine. And since it's our sales database, we want it to be highly available. So we'll do a two node rack configuration. From there, it asks us where we want to land this service. We can either land it on an existing service that's already been provisioned, or if we're starting net new or for whatever reason, we can create a new service for it. The key thing here is we're not asking anybody how to do the work, we're asking what work you want done. And the other key thing here is we've architected this concept called profiles. So you tell us how much resources you need as well as what network type you want and what software revision you want. This is actually controlled by the DBAs. So DBAs, and compute administrators, and network administrators, so they can set their standards without having a DBA. >> Sunil: Got it, okay, let's take a look. >> John: So if we go to the next piece here, it's going to personalize their database. The key thing here, again, is that we're not asking you how many data files you want or anything in that regard. So we're going to be provisioning this to Nutanix's best practices. And the key thing there is just like these past services you don't have to read dozens of pages of best practice guides, it just does what's best for the platform. >> Sunil: Got it. And so these are a multitude of provisioning steps that normally one would take I guess hours if not days to provision and Oracle RAC data. >> John: Yeah, across multiple teams too. So if you think about the lifecycle especially if you have onshore and offshore resources, I mean this might even be longer than days. >> Sunil: Got it. And then there are a few steps here, and we'll lead into potentially the Time Machine construct too? >> John: Yeah, so since this is a critical database, we want data protection. So we're going to be delivering that through a feature called Time Machines. We'll leave this at the defaults for now, but the key thing to not here is we've got SLAs that deliver both continuous data protection as well as telescoping checkpoints for historical recovery. >> Sunil: Got it. So that's provisioning. We've kicked off Oracle, what, two node database and so forth? >> John: Yep, two node database. So we've got a handful of tasks that this is going to automate. We'll check back in in a few minutes. >> Got it. Why don't we talk about the other aspects then, Bala, maybe around, one of the things that, you know and I know many of you guys have seen this, is the fact that if you look at database especially Oracle but in general even SQL and so forth is the fact that look if you really simplified it to a developer, it should be as simple as I copy my production database, and I paste it to create my own dev instance. And whenever I need it, I need to obviously do it the opposite way, right? So that was the goal that we set ahead for us to actually deliver this new past service around Era for our customers. So you want to talk a little bit more about it? >> Sure Sunil. If you look at most of the data management functionality, they're pretty much like flavors of copy paste operations on database entities. But the trouble is the seemingly simple, innocuous operations of our daily lives becomes the most dreaded, complex, long running, error prone operations in data center. So we actually planned to tame this complexity and bring consumer grade simplicity to these operations, also make these clones extremely efficient without compromising the quality of service. And the best part is, the customers can enjoy these services not only for databases running on Nutanix, but also for databases running on third party systems. >> Got it. So let's take a look at this functionality of I guess snapshoting, clone and recovery that you've now built into the product. >> Right. So now if you see the core feature of this whole product is something we call Time Machine. Time Machine lets the database administrators actually capture the database tape to the granularity of seconds and also lets them create clones, refresh them to any point in time, and also recover the databases if the databases are running on the same Nutanix platform. Let's take a look at the demo with the Time Machine. So here is our customer relationship database management database which is about 2.3 terabytes. If you see, the Time Machine has been active about four months, and SLA has been set for continuously code revision of 30 days and then slowly tapers off 30 days of daily backup and weekly backups and so on, so forth. On the right hand side, you will see different colors. The green color is pretty much your continuously code revision, what we call them. That lets you to go back to any point in time to the granularity of seconds within those 30 days. And then the discreet code revision lets you go back to any snapshot of the backup that is maintained there kind of stuff. In a way, you see this Time Machine is pretty much like your modern day car with self driving ability. All you need to do is set the goals, and the Time Machine will do whatever is needed to reach up to the goal kind of stuff. >> Sunil: So why don't we quickly do a snapshot? >> Bala: Yeah, some of these times you need to create a snapshot for backup purposes, Time Machine has manual controls. All you need to do is give it a snapshot name. And then you have the ability to actually persist this snapshot data into a third party or object store so that your durability and that global data access requirements are met kind of stuff. So we kick off a snapshot operation. Let's look at what it is doing. If you see what is the snapshot operation that this is going through, there is a step called quiescing the databases. Basically, we're using application-centric APIs, and here it's actually RMAN of Oracle. We are using the RMan of Oracle to quiesce the database and performing application consistent storage snapshots with Nutanix technology. Basically we are fusing application-centric and then Nutanix platform and quiescing it. Just for a data point, if you have to use traditional technology and create a backup for this kind of size, it takes over four to six hours, whereas on Nutanix it's going to be a matter of seconds. So it almost looks like snapshot is done. This is full sensitive backup. You can pretty much use it for database restore kind of stuff. Maybe we'll do a clone demo and see how it goes. >> John: Yeah, let's go check it out. >> Bala: So for clone, again through the simplicity of command Z command, all you need to do is pick the time of your choice maybe around three o'clock in the morning today. >> John: Yeah, let's go with 3:02. >> Bala: 3:02, okay. >> John: Yeah, why not? >> Bala: You select the time, all you need to do is click on the clone. And most of the inputs that are needed for the clone process will be defaulted intelligently by us, right? And you have to make two choices that is where do you want this clone to be created with a brand new VM database server, or do you want to place that in your existing server? So we'll go with a brand new server, and then all you need to do is just give the password for you new clone database, and then clone it kind of stuff. >> Sunil: And this is an example of personalizing the database so a developer can do that. >> Bala: Right. So here is the clone kicking in. And what this is trying to do is actually it's creating a database VM and then registering the database, restoring the snapshot, and then recoding the logs up to three o'clock in the morning like what we just saw that, and then actually giving back the database to the requester kind of stuff. >> Maybe one finally thing, John. Do you want to show us the provision database that we kicked off? >> Yeah, it looks like it just finished a few seconds ago. So you can see all the tasks that we were talking about here before from creating the virtual infrastructure, and provisioning the database infrastructure, and configuring data protection. So I can go access this database now. >> Again, just to highlight this, guys. What we just showed you is an Oracle two node instance provisioned live in a few minutes on Nutanix. And this is something that even in a public cloud when you go to RDS on AWS or anything like that, you still can't provision Oracle RAC by the way, right? But that's what you've seen now, and that's what the power of Nutanix Era is. Okay, all right? >> Thank you. >> Thanks. (audience clapping) >> And one final thing around, obviously when we're building this, it's built as a past service. It's not meant just for operational benefits. And so one of the core design principles has been around being API first. You want to show that a little bit? >> Absolutely, Sunil, this whole product is built on API fist architecture. Pretty much what we have seen today and all the functionality that we've been able to show today, everything is built on Rest APIs, and you can pretty much integrate with service now architecture and give you your devops experience for your customers. We do have a plan for full fledged self-service portal eventually, and then make it as a proper service. >> Got it, great job, Bala. >> Thank you. >> Thanks, John. Good stuff, man. >> Thanks. >> All right. (audience clapping) So with Nutanix Era being this one-click provisioning, lifecycle management powered by APIs, I think what we're going to see is the fact that a lot of the products that we've talked about so far while you know I've talked about things like Calm, Flow, AHV functionality that have all been released in 5.5, 5.6, a bunch of the other stuff are also coming shortly. So I would strongly encourage you guys to kind of space 'em, you know most of these products that we've talked about, in fact, all of the products that we've talked about are going to be in the breakout sessions. We're going to go deep into them in the demos as well as in the pods. So spend some quality time not just on the stuff that's been shipping but also stuff that's coming out. And so one thing to keep in mind to sort of takeaway is that we're doing this all obviously with freedom as the goal. But from the products side, it has to be driven by choice whether the choice is based on platforms, it's based on hypervisors, whether it's based on consumption models and eventually even though we're starting with the management plane, eventually we'll go with the data plane of how do I actually provide a multi-cloud choice as well. And so when we wrap things up, and we look at the five freedoms that Ben talked about. Don't forget the sixth freedom especially after six to seven p.m. where the whole goal as a Nutanix family and extended family make sure we mix it up. Okay, thank you so much, and we'll see you around. (audience clapping) >> PA Announcer: Ladies and gentlemen, this concludes our morning keynote session. Breakouts will begin in 15 minutes. ♪ To do what I want ♪

Published Date : May 9 2018

SUMMARY :

PA Announcer: Off the plastic tab, would you please welcome state of Louisiana And it's my pleasure to welcome you all to And I'd like to second that warm welcome. the free spirit. the Nutanix Freedom video, enjoy. And I read the tagline from license to launch You have the freedom to go and choose and having to gain the trust with you over time, At the same time, you spent the last seven, eight years and apply intelligence to say how can we lower that you go and advise with some of the software to essentially reduce their you know they're supposed to save are still only 20%, 25% utilized. And the next thing is you can't do So you actually sized it for peak, and bring the control while retaining that agility So you want to show us something? And you know glad to be here. to see you know are there resources that you look at everyday. So billions of events, billing, metering events So what we have here is a very popular are everywhere, the cloud is everywhere actually. So when you bring your master account that you create because you don't want So we have you know consumption of the services. There's a lot of money being made So not only just get visibility at you know compute So all of you who actually have not gone the single pane view you know to mange What you see here is they're using have been active in Russia as well. to detect you know how can you rightsize So one click, you can actually just pick Yeah, and not only remove the resources the consumption for the Nutanix, you know the services And the most powerful thing is you can go to say how can you really remove things. So again, similar to save, you're saying So the idea is how can we give our people It looks like there's going to be a talk here at 10:30. Yes, so you can go and write your own security So the end in all this is, again, one of the things And to start the session, I think you know the part You barely fit in that door, man. that's grown from VDI to business critical So if we hop over here to our explore tab, in recent releases to kind of make this happen? Now to allow you to full take advantage of that, On the same environment though, we're going to show you So one of the shares that you see there is home directories. Do we have the cluster also showing, So if we think about cloud, cloud's obviously a big So just like the market took a left turn on Kubernetes, Now for the developer, the application architect, So the goal of ACS is to ensure So you can deploy however many of these He hasn't seen the movies yet. And this is going to be the number And if you come over to our office, and we welcome you, Thanks so much. And like Steve who's been with us for awhile, So I remember, so how many of you guys And the deployment is smaller than what we had And it covers a lot of use cases as well. So the use cases, we're 90%, 95% deployed on Nutanix, So the plan going forward, you actually asked And the same thing when you actually flip it to AHV And to give you a flavor of that, let me show you And now you can see this is a much simpler picture. Yeah, for those guys, you know that's not the Avengers This is next years theme. So before we cut over from Netsil to Flow, And that of course is the most important So that's like one click segmentation and play right now? You can compare it to other products in the space. in that next few releases. And if I scroll down again, and I see the top five of the network which is if you can truly isolate (audience clapping) And you know it's not just using Nutanix than in a picture by the way. So tell me a little bit about this cloud initiative. and the second award was really related to that. And a lot of this was obviously based on an infrastructure And you know initiatives change year on year, So the stack you know obviously built on Nutanix, of obviously the business takeaway here? There has to be some outcomes that we measure And in the journey obviously you got So you're supposed to wear some shoes, right? for the last couple years. I'm sure you guys have received shoes like these. So again, I'm sure many of you liked them. That's the only thing that hasn't worked, Thanks a lot. is to enable you to choose the right cloud Yeah, we should. of the art as you were saying in the industry. that to my Xi cloud services account. So you don't have to log in somewhere and create an account. But let's go take a look at the Xi side that you already knew mynutanix.com and 30 seconds in, or we will deploy a VPN for you on premises. So that's one of the other things to note the gateway configured, your VLAN information Vinny: So right now, you know what's happening is And just while you guys were talking, of the other things we've done? And first thing you might notice is And we allow the setting to be set on the Xi cloud services There's always going to be some networking problem onstage. This is a good sign that we're running So for example, you just saw that the same user is to also show capabilities to actually do failover And that says okay I already have the backups is essentially coming off the mainstream Xi profile. That's the most interesting piece here. or the test network to the test network. So let's see how the experience looks like details in place for the test to be successful. And to give you guys an idea behind the scenes, And so great, while you were explaining that, And that's essentially anybody in the audience here Yeah so by the way, just to give you guys Yeah, you guys should all go and vote. Let's see where Xi is. I'll scroll down a little bit, but keep the... Thank you so much. What's something that you know we've been doing And what that means is when you have And very quickly you can see these are the VMs So one of the core innovations being built So that means it has quiesced and stopping the VM there. So essentially what Vinny just showed and making it painless so that the downtime you have And you know Jason who's the CTO of Cyxtera. of the CenturyLink data centers. bunch of other assets. So we have over 50 data centers around the world, And to be fair, a lot of what happens in data centers in the traditional kind of on demand is that you know this isn't a manged service. of the partnership going forward? Well you know I think this would be Thanks a lot, Jason. And in the enterprise, if you think about it, We're going to start with say maybe some to pass you off, that is what Nutanix is Got it. And Bala and I are so excited to finally show this And the other key thing here is we've architected And the key thing there is just like these past services if not days to provision and Oracle RAC data. So if you think about the lifecycle And then there are a few steps here, but the key thing to not here is we've got So that's provisioning. that this is going to automate. is the fact that if you look at database And the best part is, the customers So let's take a look at this functionality On the right hand side, you will see different colors. And then you have the ability to actually persist of command Z command, all you need to do Bala: You select the time, all you need the database so a developer can do that. back the database to the requester kind of stuff. Do you want to show us the provision database So you can see all the tasks that we were talking about here What we just showed you is an Oracle two node instance (audience clapping) And so one of the core design principles and all the functionality that we've been able Good stuff, man. But from the products side, it has to be driven by choice PA Announcer: Ladies and gentlemen,

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Sue Morrow, United Methodist Homes | VTUG Winter Warmer 2018


 

>> Narrator: From Gillette Stadium in Foxborough, Massachusets, it's theCUBE, covering VTUG Winter Warmer 2018. Presented by SiliconANGLE. (upbeat music) >> I'm Stu Miniman and this is theCUBE's fifth year at the VTUG Winter Warmer. 2018 is the 12th year of this event, always love when we get to talk to some of the users at the conference which's why I'm really happy to introduce to our audience Sue Morrow, who is a network manager at United Methodist Homes. Thanks for joining me Sue. >> No problem. >> First, tell me a little bit about yourself and what brings you all the way from Upstate New York to come to the VTUG. >> Well, I like to go to conferences whenever I can continue my education in IT. I grew up with computers in my house in the '80s. My dad was a physics teacher and a scientist so we always had a Commodore 64 or an Amiga in our house, growing up, when most people had Atari, we had computers. >> Totally, so Commodore 64, classic. I myself was a Tandy Radioshack, the TRS-80 Model III. So, in a similar era. >> Yep, I actually took a basic coding class on a TRS-80 when I was around 10, I think. Anyway, grew up with computers and somehow stumbled into IT later in life. So, that's why I'm here. >> United Methodist Homes, tell us just a little bit about what the mission of the company is. >> United Methodist Homes is a longterm care corporation. We have four facilities, two in the Binghamton area and two in Northeastern Pennsylvania. We have all levels of care from nursing homes, skilled care, up to independent living, and everything in between. >> Okay, and as network manager, what's under your purview? >> Well, it's kind of a silly title, actually. In longterm care or in healthcare or nonprofits, as we are, you often wear many hats and so that's, sort of, a weird title for me, but I supervise our help desk which we serve centrally from our corporate office. We serve about 600 actual computer users and, all in total, about 1200 employees who interface with the technology, in some way. So, I supervise the help desk, I make sure our network is running well. IT has changed over the years so that we're now providing more of a service and making sure that everything is up and running, network-wise, for everyone instead of keeping our servers running all the time. >> Yeah, reminds me of the old saying, it was like oh, the network is the computer, things like that, so you've got both ends of it. >> Sue: Yes. >> What kind of things are you looking at from a technology standpoint when you come to event like this? Did you catch some of the keynotes this morning, there was a broad spectrum? >> Yes. >> What are the kind of things that you're digging in to and find interesting? >> Yeah, the keynotes are really interesting. I think the first one that I went to with Luigi and Chris was great just to, kind of, expand your thinking about your own career personally, and where you want to go with your life was really interesting. I also watched Randall do his coding which is completely outside of what I do everyday, but was fascinating. And then the last major keynote was fantastic. I think that from my perspective in my company, we're kind of small and we don't do a whole lot of, we don't run apps and things like that, so the things that we have ritualized is mostly storage, so I'm looking at better ways that we can manage our storage and stuff. Most of the applications that we run now are SAS applications hosted by somebody else and their cloud, or a public cloud, or wherever, so I'm not so much looking at the cloud technologies like more businesses are that are providing an application for their company. >> It sounds like cloud and SAS's being a part of the overall strategy, have you been seeing that dynamic change in your company? How does it impact what you're doing or is it just a separate organization. >> It's definitely been a shift in the last few years, we used to run all of our applications in-house. Longterm care has caught up now, with the hospitals, so we have our electronic medical record which is a hosted application, whereas, up until five years ago, that was an on-premises application that we hosted and had to run and maintain, and update and upgrade, and make sure was available. That is definitely been a shift, that everything is now hosted. So we just make sure that our network is up and running and support our users and all of their issues when they break things, flip their screens, drop something, provide hardware for them all that sorts of stuff. >> The constant pace of innovation change. On the news this week they were saying, okay, medical records on your iPhone is up for debate. Does regulation impact your day to day activities and what are some of the challenges in that area? >> Absolutely. One of the other things we have to do is interface with the providers. We have medical providers that come in from the outside and they need to access our EMR also, so we need to provide access for them on, sometimes, whatever device they bring in, which is not always compatible, so we have a whole other set of challenges there. Where we can manage our computers for our employees by pushing out policies and things that are required for the application. When someone comes in from the outside, it isn't, necessarily, setup right, so we have that other set of challenges, and regulation-wise, yes. The government is always pushing out new and updated regulations for healthcare and we have to keep on top of that too. Of course, we have HIPAA concerns and things like that, which is also comes into play when you're talking about cloud host, and any hosted application. We have to be concerned about HIPAA, as well. >> Yeah, wondering when I look at the space that you're in, the ultimate goal is you want the patients, the people at your company, be able to spend more time, help them, not be caught up in the technology of things. Could you, maybe, talk a little bit about that dynamic? >> Yeah, one of the things that I always say is, we need to give our employees the tools that they need to do their job most efficiently. A nurse needs to be ready to go at the beginning of her shift on her laptop, ready to pass meds, and when they can't remember their password or that computer isn't working, my team needs to work as quickly as we can to get them back to work. We serve our users, really. We're not there being all techy. They want us to fix them and get them back to work, and that's what we do. We put tools in their hands, any device that they need to make them more efficient. I try hard to provide a variety of devices, people have different preferences on how they do their work. Some people prefer a laptop, some people prefer to stand at a wall-mounted touchscreen and document, some people want to carry a tablet with them. I try to provide a range of devices so that they can have whatever suits them and makes them most comfortable to get their job done. >> Love that, it's not, necessarily, about the cool or trendier thing, it's about getting business done, helping, and in you're case, enabling your employees to really help the people that are there. Anything you want to highlight as to things you're excited to look at this show, or just technology in general? >> I'm just kind of here for the general nature of it. I enjoy the networking and getting to talk to people, and keeping current in what's happening in the industry and my career, so that's why I come. >> Alright, well Sue Morrow, really appreciate you coming, sharing with our audience. >> Absolutely. >> User groups like this, all about the users. Happy to have lots of them on the program, so big thanks to the VTUG group for bringing us some great guests. We'll be back with more coverage here. I'm Stu Miniman, you're watching theCUBE. 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Data Science for All: It's a Whole New Game


 

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

Published Date : Nov 1 2017

SUMMARY :

Today the ability to extract value from data is becoming a shared mission. And for all of you during the program, I want to remind you to join that conversation on And when you and I chatted about it. And the scale and complexity of the data that organizations are having to deal with has It's challenging in the world of unmanageable. And they have to find a way. AI. And it's incredible that this buzz word is happening. And to get to an AI future, you have to lay a data foundation today. And four is you got to expand job roles in the organization. First pillar in this you just discussed. And now you get to where we are today. And if you don't have a strategy for how you acquire that and manage it, you're not going And the way I think about that is it's really about moving from static data repositories And we continue with the architecture. So you need a way to federate data across different environments. So we've laid out what you need for driving automation. And so when you think about the real use cases that are driving return on investment today, Let's go ahead and come back to something that you mentioned earlier because it's fascinating And so the new job roles is about how does everybody have data first in their mind? Everybody in the company has to be data literate. So overall, group effort, has to be a common goal, and we all need to be data literate But at the end of the day, it's kind of not an easy task. It's not easy but it's maybe not as big of a shift as you would think. It's interesting to hear you say essentially you need to train everyone though across the And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. And I've heard that the placement behind those jobs, people graduating with the MS is high. Let me get back to something else you touched on earlier because you mentioned that a number They produce a lot of the shows that I'm sure you watch Katie. And this is a good example. So they have to optimize every aspect of their business from marketing campaigns to promotions And so, as we talk to clients we think about how do you start down this path now, even It's analytics first to the data, not the other way around. We as a practice, we say you want to bring data to where the data sits. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. Female preferred, on the cover of Vogue. And how does it change everything? And while it's important to recognize this critical skill set, you can't just limit it And we call it clickers and coders. [Katie] I like that. And there's not a lot of things available today that do that. Because I hear you talking about the data scientists role and how it's critical to success, And my view is if you have the right platform, it enables the organization to collaborate. And every organization needs to think about what are the skills that are critical? Use this as your chance to reinvent IT. And I can tell you even personally being effected by how important the analysis is in working And think about if you don't do something. And now we're going to get to the fun hands on part of our story. And then how do you move analytics closer to your data? And in here I can see that JP Morgan is calling for a US dollar rebound in the second half But then where it gets interesting is you go to the bottom. data, his stock portfolios, and browsing behavior to build a model which can predict his affinity And so, as a financial adviser, you look at this and you say, all right, we know he loves And I want to do that by picking a auto stock which has got negative correlation with Ferrari. Cause you start clicking that and immediately we're getting instant answers of what's happening. And what I see here instantly is that Honda has got a negative correlation with Ferrari, As a financial adviser, you wouldn't think about federating data, machine learning, pretty And drive the machine learning into the appliance. And even score hundreds of customers for their affinities on a daily basis. And then you see when you deploy analytics next to your data, even a financial adviser, And as a data science leader or data scientist, you have a lot of the same concerns. But you guys each have so many unique roles in your business life. And just by looking at the demand of companies that wants us to help them go through this And I think the whole ROI of data is that you can now understand people's relationships Well you can have all the data in the world, and I think it speaks to, if you're not doing And I think that that's one of the things that customers are coming to us for, right? And Nir, this is something you work with a lot. And the companies that are not like that. Tricia, companies have to deal with data behind the firewall and in the new multi cloud And so that's why I think it's really important to understand that when you implement big And how are the clients, how are the users actually interacting with the system? And right now the way I see teams being set up inside companies is that they're creating But in order to actually see all of the RY behind the data, you also have to have a creative That's one of the things that we see a lot. So a lot of the training we do is sort of data engineers. And I think that's a very strong point when it comes to the data analysis side. And that's where you need the human element to come back in and say okay, look, you're And the people who are really great at providing that human intelligence are social scientists. the talent piece is actually the most important crucial hard to get. It may be to take folks internally who have a lot of that domain knowledge that you have And from data scientist to machine learner. And what I explain to them is look, you're still making decisions in the same way. And I mean, just to give you an example, we are partnering with one of the major cloud And what you're talking about with culture is really where I think we're talking about And I think that communication between the technical stakeholders and management You guys made this way too easy. I want to leave you with an opportunity to, anything you want to add to this conversation? I think one thing to conclude is to say that companies that are not data driven is And thank you guys again for joining us. And we're going to turn our attention to how you can deliver on what they're talking about And finally how you could build models anywhere and employ them close to where your data is. And thanks to Siva for taking us through it. You got to break it down for me cause I think we zoom out and see the big picture. And we saw some new capabilities that help companies avoid lock-in, where you can import And as a data scientist, you stop feeling like you're falling behind. We met backstage. And I go to you to talk about sports because-- And what it brings. And the reason being that sports consists of problems that have rules. And I was going to save the baseball question for later. Probably one of the best of all time. FiveThirtyEight has the Dodgers with a 60% chance of winning. So you have two teams that are about equal. It's like the first World Series in I think 56 years or something where you have two 100 And that you can be the best pitcher in the world, but guess what? And when does it ruin the sport? So we can talk at great length about what tools do you then apply when you have those And the reason being that A) he kind of knows how to position himself in the first place. And I imagine they're all different as well. But you really have seen a lot of breakthroughs in the last couple of years. You're known for your work in politics though. What was the most notable thing that came out of any of your predictions? And so, being aware of the limitations to some extent intrinsically in elections when It would be interesting to kind of peek back the curtain, understand how you operate but But you don't want to be inaccurate because that's your credibility. I think on average, speed is a little bit overrated in journalism. And there's got to be more time spent on stories if I can speak subjectively. And so we have people that come in, we hire most of our people actually from journalism. And so the kind of combination of needing, not having that much tolerance for mistakes, Because you do have to hit this balance. And so you try to hire well. And your perspective on that in general. But by the way, one thing that happens when you share your data or you share your thinking And you have a good intuition for hey, this looks a little bit out of line to me. And I think kind of what you learn is like, hey if there's something that bothers me, It's like oh, if I cross the street in .2-- I mean, I'm like-- But no, part of it's like you don't want to waste time on unimportant decisions, right? We want better. It's like both the chicken and the pasta are going to be really darn good, right? Serious and business, how organizations in the last three to five years have just And man, the quality of the interns we get has improved so much in four years. But when you're seeing these big organizations, ESPN as perfect example, moving more towards But the point is that the reason to be out in front of the problem is so you give yourself Final question for you as we run out of time. And so you're parsing through many, many, many lines of code. You can do better than that. You know, we tried to figure out where the best burrito in America was a few years Nate, thank you so much for joining us. I thought we were going to chat World Series, you know. And also the gallery is open until eight p.m. with demos and activations. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your

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Reggie Jackson | SAP SapphireNow 2016


 

(mumbling) >> Voiceover: Covering Sapphire now. Headline sponsored by SAP HANA Cloud, the leader in platform as a service. With support from Console Inc., the cloud internet company. Now, here are your hosts, John Furrier and Peter Burris. >> We are here live at SAP Sapphire. This is SiliconANGLE Media's The Cube. It's our flagship program. We go out to the events and extract the signal to noise and want to do a shoutout to our sponsors SAP HANA Cloud and Console Inc. at console cloud, connecting the clouds together. I'm John Furrier with my co-host Peter Burris. Our next guest is Reggie Jackson, winner, athlete, tech athlete now, entrepreneur, overall great guy, and a cube alumni. Four years ago, we interviewed him here at SAP Sapphire. Welcome back, Reggie, to The Cube. Thanks for coming on. John, thank you very much. It's good to be here with old friends. We were havin' a little conversation about baseball there, but good to see you guys. Yeah, and obviously, the baseball, we were just talkin' about the whole fisticuffs and the glee of the grand slam walk-off. >> Reggie: Good stuff, good stuff. >> It's a good pivot point in some of the things that you're workin' on in here, the conversations in the tech world, which is social media and that notion of celebrating in a world of Instagram and Snapchat and social media. Certainly, ya flip the bat, the views go up. But then, baseball has these (laughing) unwritten rules, right. So does corporations. And so we're now a new era. Is baseball safe now with these unwritten rules and should they maintain those, certain things that have kept the game in balance? But yet with social media, the players are their own brand. And you certainly were a brand, even back in your day, which is a pioneer. What's your thoughts on that? >> You know John, Peter, I don't like the idea of someone going out of their way to promote their brand. Some of the great brands to me in history, Babe Ruth, Ty Cobb, the great Jim Brown, Joe Montana, Michael Jordan. And Michael Jordan would be a prominent example where technology and TV enhanced who he was. And he had someone behind him to enhance his brand, Nike, Phil Knight, who was a real pioneer. I'm not so in favor, I'm not in favor at all of someone manufacturing themselves as a brand. And I hear players talk about their brand and about trying to create something. If you're great, if you deserve it, I don't think Stephen Curry works on his brand. I think he works on bein' a great player. I think he works on bein' a great teammate. I think he does his best to maximize his skill set. And he's nothing but a gentleman along the way. He'll celebrate with joy once in awhile, with the Curry moves, which we've come to recognize. But for guys that talk about the manufacturing of their brand, there's something about it that's manufactured. It's not real, it's false. And I don't like it. I think it's okay, the Snapchats and the Google+ and all of the stuff, Twitter and Facebook and all that stuff, all of the things that go along with trying to create some hubbub, etc. I'm okay with that. >> So you're saying if it's not deserved. People are overplaying their hand before earning it. >> A lot of it, John, a lot of it. Joe Montana didn't work on his brand, he was great. Jim Brown didn't work on his brand, he was great. I don't want to use Jimmy Brown. I want to use Montana because even young people today will know Joe Montana. Tom Brady, Peyton Manning, they're not about their brand. They're about being classy, being great, being part of a team, being a leader, presenting themselves as something that's respected in the NFL, across the United States. Go ahead, Pete. >> So even though it's cheaper to get your name out there, you still believe in let your performance speak for itself. >> You got to be real about it. Ya got to be who you are. If you're not a great player, get out of the way. Get out of the space. So manufacturing your brand. I played with the Yankees. I was in the era of Cosell and Billy Martin and George Steinbrenner. We won championships with the team. I was part of something that helped me become recognized. And so in our era, the Sandy Koufax's became brands because they were associated with greatness around them. They stood out and so they earned that tremendous brand. >> We were just watching Graig Nettles gettin' taken out by George Brett in that big game and also the pine tar, we kind of gettin' some good laughs at it. You look at the balance of personalities. Certainly, Brett and Nettles and your team and you had a great personality, winning championships. Worked together as a team. And so I want to ask you that question about the balance, about the in baseball, certainly, the unwritten rules are a legacy and that has worked. And now in a era of personalities, in some cases, people self-promoting themselves, people are questioning that. Your thoughts on that because that applies to business too 'cause tech athletes or business athletes have a team, there are some unwritten rules. Thoughts on this baseball debate about unwritten rules. >> Pete and John, I'll try to correlate it between some tech giants that have a brand. I just left a guy with a brand, Bill McDermott, that runs SAP. Even Hasso, the boss. The face now of SAP is Bill McDermott. Dapper, slender, stylish, bright. It comes across well. So maintaining that brand, to me, relates to SAP, bills a great image for it. He's stylish, he's smooth, he's smart. He's about people. He presents himself with care. So that is a brand. I don't think it's manufactured. That's who he is in real life. If you take a look, and I'll go back to Steph Curry because that name resonates and everyone recognize it. That style of cool, that style of control, that style of team and care. And he presents to us all that he cares about us, the fan, his team, his family. And so those are things and I think you can go from the tech world. Bill Gates had a brand. Brilliant, somewhat reclusive, concerned about the world, concerned about the country, concerned about his company. And so that resonated it Microsoft because that's who he really was. Some of the people today don't really recognize that Jobs was thrown out of Apple. He was pushed out. All of his brilliance, which was marketing. And the gentleman there that really was the mind for the company, Steve Wozniak, happens to be here at SAP Sapphire. Today, I think he speaks. But those brands were real, not manufactured. And so, in today's world, I think you can manufacture a brand. And then all of a sudden, it'll crumble. It'll go away in the future. But the great brands of whether it's Jackie Robinson or whether it's Jack Welch or whether it's George Steinbrenner and the Yankee brand, those brands were real. They were not manufactured. Those guys were eccentric. They were brilliant. Go ahead. >> And also, they work hard. And I want to point out a comment you made yesterday here at the event. You were asked a question up on stage about that moment when you hit the home runs. I think we talked about it last time. I don't necessarily want to talk about the home runs. But you made a comment I'd like you to expand on and share with the audience. 'Cause you said, "I worked hard," but that day during warm-ups, you had batting practice. You made a comment that you were in the zone. So working hard and being great as it leads up to that. But also, in the moment, 'cause that's a theme these days, in the moment, being ready and prepared. Share your thoughts on what you meant by you had a great batting practice and you just felt it. >> I'm going to take it to what you say is in the moment. I remember when I was talkin' about it yesterday, which you reference to, when I had such a fantastic batting practice. I walked by a coupla sports writers in that era. Really well-known guys, Dave Anderson, New York Times. I can't think of his name right now, but it'll come to me, of the Daily News. It was like hey man. >> John: You were rockin' it out there. >> I kind of hope I didn't leave it out here. (laughing) That was in the moment and at the same time, >> I mean, you were crushing it. >> Yes, when the game started, I got back in that moment. I got back in what was live, what was now, what was going on. Certainly, I think our world now with the instant gratification of sending out a message or tweeting to someone or whatever certainly in the moment is about what our youth is and who we are today as a country, as a universe. >> But you didn't make that up. You worked hard, but you pulled it together in the moment. >> A comment with that is I went and did something with ESPN earlier this year in San Francisco, in Oakland with Stephen Curry. They said, "Reggie, we want ya to come up "and watch his practice, his pre-game." And it was very similar to your batting practice, where people come out and watch, etc. And so I was looking forward to it and I like to go to the games about an hour and a half or two hours early so I can see warm-up and see some of the guys and say hello. And I got a chance to watch Steph Curry. I know his dad. And happened to be the first time I went this year, the dad, Carolina, the Panthers were in town. Not the Panthers. Come on, help me, help me, help me. >> Peter: The Wizards? >> No, no, no, the Carolina. >> Peter: Carolina Panthers. >> The Carolina Hornets. >> John: Hornets. >> Were there and I know his dad, Dell Curry. And we talked a little bit. But then, Steph came out and I watched him. And I watched the dribbling exhibition. I watched the going between the legs and behind the back and the fancy passing, etc. And I watched the shots, the high-arcing threes, the normal trajectory threes, the high shots off the backboard and things like that that he did. The left-handed shots, the right-handed shots. And the guy asked me what I thought of the show. And I said, "Well, it's a cool show, "but I'm going to see all that tonight." And me watching him, the behind the backs, the between the legs, the passes, the high-arching shots from three, the high-arching touches off the glass. He does all that. >> John: He brought it into the game. >> Yeah, I said so, (laughing) >> Peter: That is his game. >> It's not a show, but that's his game. >> So Reggie, you did an interesting promotion, Reggie's Garage, where you bought a virtual reality camera and you created a really nice show of your garage demonstrating your love >> Reggie: 360. >> Peter: of cars, 360. Talk a little bit about that. And then if ya get a second, imagine what baseball's going to be like as that technology becomes available and how some of the conversation that we're having about authenticity, the fan coming into the game. >> An experience. >> Is going to change baseball. Start with the garage and how that went and then how ya think that's going to translate into baseball, if you've had any thoughts on that. >> In the technology that was used, certainly I enjoyed it. While I was doing it, I noticed where the cameras were in different spots. There was one on the floor of my car. There was one in the backseat. And then there was someone following us as closely as they could. But you could see everything. You'd see the shift and you could see my feet. It was like you were with me. When we did the 360 inside the garage as well, you could listen to me and then you could use your finger and spin around. And they had these special headset and special glasses that you could look around, just with your headset on, and see all around the room. Behind you, in front of you. And so it's an experience that I think is going to become part of who we are as a nation, who we are as a people watching television, that you're going to really feel like you're in the room. I think it's going to be exciting. And I think it's going to be fun. And when you're talking about products, when you're talking about my website, if you will, with the focus on automotive parts, where a guy can go in and shop and get any part he wants for a vehicle, you really can build a complete car from my website. You can buy a frame. You can buy body parts. You can buy a horn, an engine, brakes, tires, grills, turn signals, the whole nine yards. And it gives you an experience through 360 video of really walking into the store, walking into the building, walking into the stadium and looking around to see the hot dog stand, see the dugout, see the pitcher and the hitter, to see the parts in the garage, to see the cars and take a look and view at everything that's there. >> How are players going to react to havin' the fans virtually right there with them? >> I don't think it bothers you. I don't think ya notice. I don't think they'll show anything that will affect the player that he's going to be concerned about. I think you'd have to be sensitive if they start microphoning, start micing up and then the looseness of the language would impact. So I don't think they'll go that far. But I do think the more that you can see, the more attractive the game becomes, the more interested that you can get people. When I broadcast baseball for ABC back in the 80's, I always tried to broadcast for the lady of the house, while she worked, while she cooked the meal, she didn't have time to think about a backup slider or the fastball that painted the outside corner, the changeup, etc., the sinker. I tried to broadcast for her interpretation so I could attract another fan to the game. So I think that the technology and the viewing that you'll see from behind home plate, from under the player's feet while he's running down the bases and the slides and things of that nature, Pete, I think are going to be exciting for the fan and it'll attract more fans, attract a new type of television it's going to produce, etc. So it's exciting. >> Reggie, thanks for comin' on The Cube again. Appreciate your time. I ask ya final two questions that I want to get your thoughts on. One is obviously the cars. Reggie's Garage is goin' great. And you shared with us last time on The Cube, it's on YouTube, about you when you grew up and decide football and baseball. But when you were growin' up, what was your favorite car? What was that car that you wanted that was out of reach? That car that was your hot rod? And then the second question is, we'll get to the second question. Answer that one first. What was you dream car at the time? How did ya get >> Reggie: The dream car >> John: hooked on this? >> at the time. I had a '55 Chevrolet that I bought from a buddy by the name of Ronny Fog. I don't even know if he's still around anymore. Out of Pennsylvania. I had $300 and my dad gave me $200. I'd saved up mine from workin' for my dad. But my dream car was I went to school with a guy named Wayne Gethman and another guy named Irwin Croyes. I don't know Wayne Gethman anymore. But from the age of 16, I reengaged with Irwin Croyes, who happens to be a business investing type guy in the city of Philadelphia, right where we're still from. He's a car collector. And he drove a '62 Corvette and so did Wayne Gethman. And I always wanted one. And I now happen to have four. (laughing) >> He who get the most toys wins. Final question, 'cause you're such a legend and you're awesome and you're doin' so much work. And you're very active, engaged, appreciate that. Advice to young athletes coming up, whether they're also in business or a tech athlete or a business athlete. But the sports athletes today got travel ball, you got all this stuff goin' on. The idols like Stephen Curry are lookin' great. Great role models now emerging. What advice do you give them? >> John's got a freshman in high school. I got a junior in high school. What would ya say to 'em? >> You know, I'll tell ya. When you're young, the people you want to listen to are Mom and Dad. No one, and I'll say this to any child from the age of eight or nine years old, five, six years old to 17, 18, 19, 20, all the way up, now my daughter's 25. All the way up to the end of your parents' days. No one cares for you more than your mother or your father. Any parent, whether it's a job or whether their success in life, number one in that man or woman, mom or dad, number one in their life is their children. And so for kids, I say if there's any person you're going to listen to for advice in any path you want to walk down, it's the one that your parents talk to you about or how they show you. That is what I would leave as being most important. For kids, anything, idea that you have that you believe you can do, whether it's the athlete like Stephen Curry that has created shots and done things on the basketball court that he envisioned, that he thought about. Or whether it's the next Steve Jobs who happens to be Mark Zuckerman, who I don't know Mark is 30 years old yet. >> John: He just turned 30. >> It's an idea. He's born around the same time. He's born this week. His birthday is in this week. My birthday's tomorrow. >> John: Happy birthday. >> But thank you. Anything that you can think of in today's world of technology. With places like Silicon Valley where they take dreams and create foundations for them. I had a dream about a website that would sell automotive parts and you could go to my site and buy anything for your car. We've got about 75,000 items now. We'll get to 180,000 in a few months. We'll get to a half a million as soon as my technology is ready for it. But we have things to pay attention to and look into and issues to make sure that we iron out that aren't there for our consumer, for ease of navigation, ease of consumption and purchasing. Any idea that you have, take time to dream. It's much more so than taking time to dream when I was a young kid. Because my father would say, "Stop daydreamin' "and wastin' time." >> John: Get to work. >> Reggie: In today's world, for our children, I say take time to create a vision or to create something new. And go to someone that's in the tech world and they'll figure out a way of helping you manifest it into something that's a reality. >> Listen to your parents, kids. And folks out there, dream, build the foundation, go for it. Reggie Jackson, congratulations for being a Cube alumni again, multi-return. >> Peter: Thank you very much. >> John: Appreciate it. Congratulate on all your continued success. You're a legend. Great to have you on. And thanks so much for comin' on The Cube. >> Peter: And happy 70th birthday. >> John, Pete, always a pleasure. >> John: Happy birthday. >> Thank you very much. >> Have some cake for Reggie. It's The Cube, live here in Orlando. Bringin' all the action here on The Cube. I'm John Furrier with Peter Burris with Reggie Jackson. We'll be right back. (electronic music)

Published Date : May 17 2016

SUMMARY :

the leader in platform as a service. and extract the signal to noise in some of the things that Some of the great brands to me in history, So you're saying if it's not deserved. that's respected in the NFL, to get your name out there, Ya got to be who you are. And so I want to ask you that question And the gentleman there that really was But also, in the moment, 'cause that's I can't think of his name right now, and at the same time, I got back in that moment. But you didn't make that up. And I got a chance to watch Steph Curry. And the guy asked me what and how some of the conversation Is going to change baseball. And I think it's going to be fun. But I do think the more that you can see, And you shared with us And I now happen to have four. But the sports athletes I got a junior in high school. it's the one that your He's born around the same time. Anything that you can think of I say take time to create a vision build the foundation, go for it. Great to have you on. Bringin' all the action here on The Cube.

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