>>Yeah. >>Hello. Welcome to the Special Cube conversation here in Palo Alto, California. I'm John for a host of the Cube. We have a conversation around a I for the enterprise. What this means I got two great guests. John Finelli, Vice President, virtual GPU at NVIDIA and Maurizio D V D C T o University of Pisa in Italy. Uh, Practitioner, customer partner, um, got VM world coming up. A lot of action happening in the enterprise. John. Great to see you. Nice to meet you. Remotely coming in from Italy for this remote. >>John. Thanks for having us on again. >>Yeah. Nice to meet >>you. I wish we could be in person face to face, but that's coming soon. Hopefully, John, you were talking. We were just talking about before we came on camera about AI for the enterprise. And the last time I saw you in person was in Cuba interview. We were talking about some of the work you guys were doing in AI. It's gotten so much stronger and broader and the execution of an video, the success you're having set the table for us. What is the ai for the enterprise conversation frame? >>Sure. So, um, we, uh we've been working with enterprises today on how they can deliver a I or explore AI or get involved in a I, um uh, in a standard way in the way that they're used to managing and operating their data centre. Um, writing on top of you know, they're Dell servers with B M or V sphere. Um, so that AI feels like a standard workload that night organisation can deliver to their engineers and data scientists. And then the flip side of that, of course, is ensuring that engineers and data scientists get the workloads position to them or have access to them in the way that they need them. So it's no longer a trouble ticket that you have to submit to, I t and you know, count the hours or days or weeks until you you can get new hardware, right By being able to pull it into the mainstream data centre. I can enable self service provisioning for those folks. So we actually we make a I more consumable or easier to manage for I t administrators and then for the engineers and the data scientists, etcetera. We make it easy for them to get access to those resources so they can get to their work right away. >>Quite progress in the past two years. Congratulations on that and looking. It's only the beginning is Day one Mercy. I want to ask you about what's going on as the CTO University piece of what's happening down there. Tell us a little bit about what's going on. You have the centre of excellence there. What does that mean? What does that include? >>Uh, you know, uh, University of Peace. Are you one of one of the biggest and oldest in Italy? Uh, if you have to give you some numbers is around 50 K students and 3000 staff between, uh, professors resurgence and that cabinet receive staff. So I we are looking into data operation of the centres and especially supports for scientific computing. And, uh, this is our our daily work. Let's say this, uh, taking us a lot of times, but, you know, we are able to, uh, reserve a merchant percentage of our time, Uh, for r and D, And this is where the centre of excellence is, Uh, is coming out. Uh, so we are always looking into new kinds of technologies that we can put together to build new solutions to do next generation computing gas. We always say we are looking for the right partners to do things together. And at the end of the day is the work that is good for us is good for our partners and typically, uh, ends in a production system for our university. So is the evolution of the scientific computing environment that we have. >>Yeah. And you guys have a great track record and reputation of, you know, R and D, testing software, hardware combinations and sharing those best practises, you know, with covid impact in the world. Certainly we see it on the supply chain side. Uh, and John, we heard Jensen, your CEO and video talk multiple keynotes. Now about software, uh, and video being a software company. Dell, you mentioned Dale and VM Ware. You know, Covid has brought this virtualisation world back. And now hybrid. Those are words that we used basically in the text industry. Now it's you're hearing hybrid and virtualisation kicked around in real world. So it's ironic that vm ware and El, uh, and the Cube eventually all of us together doing more virtual stuff. So with covid impacting the world, how does that change you guys? Because software is more important. You gotta leverage the hardware you got, Whether it's Dell or in the cloud, this is a huge change. >>Yeah. So, uh, as you mentioned organisations and enterprises, you know, they're looking at things differently now, Um, you know, the idea of hybrid. You know, when you talk to tech folks and we think about hybrid, we always think about you know, how the different technology works. Um, what we're hearing from customers is hybrid, you know, effectively translates into, you know, two days in the office, three days remote, you know, in the future when they actually start going back to the office. So hybrid work is actually driving the need for hybrid I t. Or or the ability to share resources more effectively. Um, And to think about having resources wherever you are, whether you're working from home or you're in the office that day, you need to have access to the same resources. And that's where you know the the ability to virtualize those resources and provide that access makes that hybrid part seamless >>mercy What's your world has really changed. You have students and faculty. You know, Things used to be easy in the old days. Physical in this network. That network now virtual there. You must really be having him having impact. >>Yeah, we have. We have. Of course. As you can imagine, a big impact, Uh, in any kind of the i t offering, uh, from, uh, design new networking technologies, deploying new networking technologies, uh, new kind of operation we find. We found it at them. We were not able anymore to do burr metal operations directly, but, uh, from the i t point of view, uh, we were how can I say prepared in the sense that, uh, we ran from three or four years parallel, uh, environment. We have bare metal and virtual. So as you can imagine, traditional bare metal HPC cluster D g d g X machines, uh, multi GPU s and so on. But in parallel, we have developed, uh, visual environment that at the beginning was, as you can imagine, used, uh, for traditional enterprise application, or VD. I, uh, we have a significant significant arise on a farm with the grid for remote desktop remote pull station that we are using for, for example, uh, developing a virtual classroom or visual go stations. And so this is was typical the typical operation that we did the individual world. But in the same infrastructure, we were able to develop first HPC individual borders of utilisation of the HPC resources for our researchers and, uh, at the end, ai ai offering and ai, uh, software for our for our researchers, you can imagine our vehicle infrastructure as a sort of white board where we are able to design new solution, uh, in a fast way without losing too much performance. And in the case of the AI, we will see that we the performance are almost the same at the bare metal. But with all the flexibility that we needed in the covid 19 world and in the future world, too. >>So a couple things that I want to get John's thoughts as well performance you mentioned you mentioned hybrid virtual. How does VM Ware and NVIDIA fit into all this as you put this together, okay, because you bring up performance. That's now table stakes. He's leading scale and performance are really on the table. everyone's looking at it. How does VM ware an NVIDIA John fit in with the university's work? >>Sure. So, um, I think you're right when it comes to, uh, you know, enterprises or mainstream enterprises beginning their initial foray into into a I, um there are, of course, as performance in scale and also kind of ease of use and familiarity are all kind of things that come into play in terms of when an enterprise starts to think about it. And, um, we have a history with VM Ware working on this technology. So in 2019, we introduced our virtual compute server with VM Ware, which allowed us to effectively virtual is the Cuda Compute driver at last year's VM World in 2020 the CEOs of both companies got together and made an announcement that we were going to bring a I R entire video AI platform to the Enterprise on top of the sphere. And we did that, Um, starting in March this year, we we we finalise that with the introduction of GM wears V, Sphere seven, update two and the early access at the time of NVIDIA ai Enterprise. And, um, we have now gone to production with both of those products. And so customers, Um, like the University of Pisa are now using our production capabilities. And, um, whenever you virtualize in particular and in something like a I where performances is really important. Um, the first question that comes up is, uh doesn't work and And how quickly does it work Or or, you know, from an I t audience? A lot of times you get the How much did it slow down? And and and so we We've worked really closely from an NVIDIA software perspective and a bm wear perspective. And we really talk about in media enterprise with these fair seven as optimist, certified and supported. And the net of that is, we've been able to run the standard industry benchmarks for single node as well as multi note performance, with about maybe potentially a 2% degradation in performance, depending on the workload. Of course, it's very different, but but effectively being able to trade that performance for the accessibility, the ease of use, um, and even using things like we realise, automation for self service for the data scientists, Um and so that's kind of how we've been pulling it together for the market. >>Great stuff. Well, I got to ask you. I mean, people have that reaction of about the performance. I think you're being polite. Um, around how you said that shows the expectation. It's kind of sceptical, uh, and so I got to ask you, the impact of this is pretty significant. What is it now that customers can do that? They couldn't or couldn't feel they had before? Because if the expectations as well as it worked well, I mean, there's a fast means. It works, but like performance is always concerned. What's different now? What what's the bottom line impact on what country do now that they couldn't do before. >>So the bottom line impact is that AI is now accessible for the enterprise across there. Called their mainstream data centre, enterprises typically use consistent building blocks like the Dell VX rail products, right where they have to use servers that are common standard across the data centre. And now, with NVIDIA Enterprise and B M R V sphere, they're able to manage their AI in the same way that they're used to managing their data centre today. So there's no retraining. There's no separate clusters. There isn't like a shadow I t. So this really allows an enterprise to efficiently deploy um, and cost effectively Deploy it, uh, it without because there's no performance degradation without compromising what their their their data scientists and researchers are looking for. And then the flip side is for the data science and researcher, um, using some of the self service automation that I spoke about earlier, they're able to get a virtual machine today that maybe as a half a GPU as their models grow, they do more exploring. They might get a full GPU or or to GPS in a virtual machine. And their environment doesn't change because it's all connected to the back end storage. And so for the for the developer and the researcher, um, it makes it seamless. So it's really kind of a win for both Nike and for the user. And again, University of Pisa is doing some amazing things in terms of the workloads that they're doing, Um, and, uh and, uh, and are validating that performance. >>Weigh in on this. Share your opinion on or your reaction to that, What you can do now that you couldn't do before. Could you share your experience? >>Our experience is, uh, of course, if you if you go to your, uh, data scientists or researchers, the idea of, uh, sacrificing four months to flexibility at the beginning is not so well accepted. It's okay for, uh, for the Eid management, As John was saying, you have people that is know how to deal with the virtual infrastructure, so nothing changed for them. But at the end of the day, we were able to, uh, uh, test with our data. Scientists are researchers veteran The performance of us almost similar around really 95% of the performance for the internal developer developer to our work clothes. So we are not dealing with benchmarks. We have some, uh, work clothes that are internally developed and apply to healthcare music generator or some other strange project that we have inside and were able to show that the performance on the beautiful and their metal world were almost the same. We, the addition that individual world, you are much more flexible. You are able to reconfigure every finger very fast. You are able to design solution for your researcher, uh, in a more flexible way. An effective way we are. We were able to use the latest technologies from Dell Technologies and Vidia. You can imagine from the latest power edge the latest cuts from NVIDIA. The latest network cards from NVIDIA, like the blue Field to the latest, uh, switches to set up an infrastructure that at the end of the day is our winning platform for our that aside, >>a great collaboration. Congratulations. Exciting. Um, get the latest and greatest and and get the new benchmarks out their new playbooks. New best practises. I do have to ask you marriage, if you don't mind me asking why Look at virtualizing ai workloads. What's the motivation? Why did you look at virtualizing ai work clothes? >>Oh, for the sake of flexibility Because, you know, uh, in the latest couple of years, the ai resources are never enough. So we are. If you go after the bare metal, uh, installation, you are going into, uh, a world that is developing very fastly. But of course, you can afford all the bare metal, uh, infrastructure that your data scientists are asking for. So, uh, we decided to integrate our view. Dual infrastructure with AI, uh, resources in order to be able to, uh, use in different ways in a more flexible way. Of course. Uh, we have a We have a two parallels world. We still have a bare metal infrastructure. We are growing the bare metal infrastructure. But at the same time, we are growing our vehicle infrastructure because it's flexible, because we because our our stuff, people are happy about how the platform behaviour and they know how to deal them so they don't have to learn anything new. So it's a sort of comfort zone for everybody. >>I mean, no one ever got hurt virtualizing things that makes it makes things go better faster building on on that workloads. John, I gotta ask you, you're on the end video side. You You see this real up close than video? Why do people look at virtualizing ai workloads is the unification benefit. I mean, ai implies a lot of things, implies you have access to data. It implies that silos don't exist. I mean, that doesn't mean that's hard. I mean, is this real people actually looking at this? How is it working? >>Yeah. So? So again, um you know for all the benefits and activity today AI brings a I can be pretty complex, right? It's complex software to set up and to manage. And, um, within the day I enterprise, we're really focusing in on ensuring that it's easier for organisations to use. For example Um, you know, I mentioned you know, we we had introduced a virtual compute server bcs, um uh, two years ago and and that that has seen some some really interesting adoption. Some, uh, enterprise use cases. But what we found is that at the driver level, um, it still wasn't accessible for the majority of enterprises. And so what we've done is we've built upon that with NVIDIA Enterprise and we're bringing in pre built containers that remove some of the complexities. You know, AI has a lot of open source components and trying to ensure that all the open source dependencies are resolved so you can get the AI developers and researchers and data scientists. Actually doing their work can be complex. And so what we've done is we've brought these pre built containers that allow you to do everything from your initial data preparation data science, using things like video rapids, um, to do your training, using pytorch and tensorflow to optimise those models using tensor rt and then to deploy them using what we call in video Triton Server Inference in server. Really helping that ai loop become accessible, that ai workflow as something that an enterprise can manage as part of their common core infrastructure >>having the performance and the tools available? It's just a huge godsend people love. That only makes them more productive and again scales of existing stuff. Okay, great stuff. Great insight. I have to ask, What's next one's collaboration? This is one of those better together situations. It's working. Um, Mauricio, what's next for your collaboration with Dell VM Ware and video? >>We will not be for sure. We will not stop here. Uh, we are just starting working on new things, looking for new development, uh, looking for the next beast. Come, uh, you know, the digital world is something that is moving very fast. Uh, and we are We will not We will not stop here because because they, um the outcome of this work has been a very big for for our research group. And what John was saying This the fact that all the software stock for AI are simplified is something that has been, uh, accepted. Very well, of course you can imagine researching is developing new things. But for people that needs, uh, integrated workflow. The work that NVIDIA has done in the development of software package in developing containers, that gives the end user, uh, the capabilities of running their workloads is really something that some years ago it was unbelievable. Now, everything is really is really easy to manage. >>John mentioned open source, obviously a big part of this. What are you going to? Quick, Quick follow if you don't mind. Are you going to share your results so people can can look at this so they can have an easier path to AI? >>Oh, yes, of course. All the all the work, The work that is done at an ideal level from University of Visa is here to be shared. So we we as, uh, as much as we have time to write down we are. We are trying to find a way to share the results of the work that we're doing with our partner, Dell and NVIDIA. So for sure will be shared >>well, except we'll get that link in the comments, John, your thoughts. Final thoughts on the on the on the collaboration, uh, with the University of Pisa and Delvian, where in the video is is all go next? >>Sure. So So with University of Pisa, We're you know, we're absolutely, uh, you know, grateful to Morocco and his team for the work they're doing and the feedback they're sharing with us. Um, we're learning a lot from them in terms of things we can do better and things that we can add to the product. So that's a fantastic collaboration. Um, I believe that Mauricio has a session at the M World. So if you want to actually learn about some of the workloads, um, you know, they're doing, like, music generation. They're doing, you know, covid 19 research. They're doing deep, multi level, uh, deep learning training. So there's some really interesting work there, and so we want to continue that partnership. University of Pisa, um, again, across all four of us, uh, university, NVIDIA, Dell and VM Ware. And then on the tech side, you know, for our enterprise customers, um, you know, one of the things that we actually didn't speak much about was, um I mentioned that the product is optimised certified and supported, and I think that support cannot be understated. Right? So as enterprises start to move into these new areas, they want to know that they can pick up the phone and call in video or VM ware. Adele, and they're going to get support for these new workloads as they're running them. Um, we were also continuing, uh, you know, to to think about we spent a lot of time today on, like, the developer side of things and developing ai. But the flip side of that, of course, is that when those ai apps are available or ai enhanced apps, right, Pretty much every enterprise app today is adding a I capabilities all of our partners in the enterprise software space and so you can think of a beady eye enterprises having a runtime component so that as you deploy your applications into the data centre, they're going to be automatically take advantage of the GPS that you have there. And so we're seeing this, uh, future as you're talking about the collaboration going forward, where the standard data centre building block still maintains and is going to be something like a VX rail two U server. But instead of just being CPU storage and RAM, they're all going to go with CPU, GPU, storage and RAM. And that's going to be the norm. And every enterprise application is going to be infused with AI and be able to take advantage of GPS in that scenario. >>Great stuff, ai for the enterprise. This is a great QB conversation. Just the beginning. We'll be having more of these virtualizing ai workloads is real impacts data scientists impacts that compute the edge, all aspects of the new environment we're all living in. John. Great to see you, Maurizio here to meet you and all the way in Italy looking for the meeting in person and good luck in your session. I just got a note here on the session. It's at VM World. Uh, it's session 22 63 I believe, um And so if anyone's watching, Want to check that out? Um, love to hear more. Thanks for coming on. Appreciate it. >>Thanks for having us. Thanks to >>its acute conversation. I'm John for your host. Thanks for watching. We'll talk to you soon. Yeah,

(intense orchestral music) >> Welcome back everybody, Jeff Frick here with theCUBE, we're in our Palo Alto studio havin' a CUBEConversation, we're getting ready for the madness of the fall conference season to hit us full force, so we're excited to have things a little bit quiet this week and have a special guest, he's Jed Ayres, he is the North American CEO, and the Global CMO for IGEL, great to see you. >> Well, great to be here, thanks for inviting me, I know a lot of luminaries in the tech industry have sat in this chair so, >> That's right. >> It's an honor to have a chance to chat with you today. >> Well thank you, I appreciate that. So give a, for the people that aren't familiar with IGEL, give us kind of the IGEL 101. >> Yeah, so I wasn't actually that familiar with IGEL two years ago, and I've spent, you know over a decade in the end user compute space, so they were a little bit of a mystery I think to most people in the US; however, the companies been around for over 20 years, they're actually the number one Thin Client player in Germany since 2006. So what they really specialize in is a Linux, read-only operating system, that's fused to a management console that just really works for these cloud delivered desktops and applications, right? And so, a little bit shrouded in sort of this world of Thin Client hardware, but the company is really a software company. And so, the opportunity for me was to really help them build their US operation, but probably more importantly, put the right sort of US marketing prowess and kind of English first, we got out and kind of re-wrote their marketing playbook, and we really have exposed the IP of this beautiful, light, Linux OS, and the management tool which you know couldn't have been at a better time in terms of what's happening in the industry. >> So just to call those three things out specifically, so it's a light OS, that's Linux based, for x86 devices, >> Exactly. >> And so you're workin' with Citrix and VMware, and a lot of those platforms. >> I mean there's 17 different protocols that it works with out of the box, so, really when you think about you know Microsoft RDP, Parallels, Ericom, some of the, some things that you know, back in the history of end user compute, we still, out of the box, are synced up with those technologies. But the primary ones today are Citrix, and VMware, and Microsoft, and yeah we'll soon be doing some things with Amazon as well workin' with them to be their first Linux client for workspaces, so. >> So, we talked a little bit before we turned the cameras on, you know the bring your own device thing, we saw it first in mobile phones in a big, big way, you know people are bringing their laptops and all kinds of interesting stuff. At the same time you've got kind of this cloud move with the centralized control, and you don't have all this kind of rogue stuff, and you know some of the clouds like I don't have the right excel spreadsheet on this laptop, it's on my home desktop. So you guys are kind of riding that wave, but enabling a really interesting play on it, you enable a BYOD, but you actually have an opportunity to basically supplant that, overlay, I don't know what's the right verb, to enable a secure, lightweight, centralized control. >> Yeah, so there's really three ways to get this operating system, right? You can get it on the traditional hardware form factors that you find for most Thin Clients, right, we've got kind of a entry level, mid, high-level all in one. And then we have the ability to convert a device, so we would actually wipe the entire operating system off the device, and just, you'll have a last boot to the IGEL OS. But then, really what, two years ago we came out with this, and this is what we call the UD Pocket, it's about the size of your thumbnail, it's a hardened USB read-only stick, it has the same OS that the hardware has and the converter software has, it's just a bootable, right? So I could plug this into that laptop you have there, and you would boot to a secure Linux operating system, and we'd point it to whatever cloud delivery service that you're, you know, theCUBE was using, so if it was Citrix or VMware, so. Yeah, this has opened up a lot of new use cases, it's sort of changed how people think about Thin Clients too right, you sort of think Thin Client, kiosk task worker, not necessarily the CEO of a company or a knowledge worker, or a physician running an emergency room might want to have their own device, same device they use at home. So yeah, this has opened up a lot of interesting use cases: contractors, interns, we even see it being used for people in environments, in hospitals, where they keep a stash of these, for high availability, I guess ransomware. Right, you've seen these hospitals basically being attacked, what they would do is go and put these in, boot to a secondary epic or server environment, and you know this is kind of their way of not knowing which device is infected, they can just easily bypass that device, boot to this read-only operating system. >> It's a real game changer in terms of opening up >> It really is. >> Not only, not only, removing all the vulnerabilities that come with with kind of a classic laptop situation, but even giving the things new life, right, enabling them to kind of be reborn, really as a Thin, or excuse me as a light client. >> Yeah, we see three reasons why people are are buying IGEL today. And it's fun for me 'cause I get go out you know talk to a lot of customers and partners, you know we're 100% partner oriented organization, which is fun for me since I spent 20 years as a partner. But what's been really fun is that it's a C-level conversation, you wouldn't think Thin Client, I can go talk to a CEO or a CFO or a CIO, but this is a game changer. And it's really three things, right, we can save people money, which people like that, right, when you can save a company from having to go purchase 5000 new endpoints; we just had a hospital in Texas, they were about to buy 5000 new endpoints, that's about five million dollars, right? We walked in and sold them 5000 convertor licenses, for about a half a million dollars, so they saved four and a half million dollars in not having to buy new hardware. And then, you know the second piece is the operational headcount savings. When you think about managing Windows today, it's you know maybe great organizations one person can do 500 devices maybe; if you're lucky and you really have all the right tools. With IGEL we have numbers like one person managing 30000 devices, in retail, you know places where you don't have a lot of smart hands. And then the third reason why, you know we can talk to a lot of CSOs now too, right, as people are gravitating towards Linux, because of the challenges with Windows, and managing Windows, and securing windows. And Linux, when I first started people said kind of don't talk about Linux, you know, it's maybe kind of a bad word and people get you know scared. Today we walk in and we lead with this is a very mature Linux operating system, and we have a fantastic security roadmap... >> And 20 years of history, right? So you've got institutional, a foundation that you can build off of. It's funny on the Linux thing right, 'cause I'm sure they said the same thing when they wanted to roll Linux into the data centers back in the day. >> Exactly. (Jeff laughs) Yeah, this is the year where we believe, and IDC is tracking this pretty closely, that this is the year where on the endpoints of this Thin Client, you're going to see Windows is going to be surpassed by Linux; and that tracker that IDC does doesn't even track the ones that are being repurposed, right, where Linux is going in because it's going in on old hardware. So just on the new hardware it's going to be about 40% Linux and 40% Windows, and then there's you know some other you know operating systems out there, but. Yeah, this is, this is an exciting time to be in this space, right? We look at the challenges of managing Windows 10, we look at the security issues of GDPR, you know and people are just really gravitating towards towards this idea of a Linux OS. >> Right. It's funny, it's not, not directly related, but corollary, you know as Google really pushes Chromebooks as part of their enterprise play as a much more secure platform with central control, and in fact I think Diane mentioned at the Google Cloud show that we use like 37 different basically online applications to get work done these days, whether you're in your Salesforce application, or Marketo, or Gmail Suite, or you know. So we're all basically browser based application delivery, so it really does open up this opportunity for the incline 'cause you don't really need that much function, >> Exactly. >> But you know it's serving up that central HTTP. >> I talk to people all the time who have fancy, thousands of dollar laptops, and their like, all they do is hit a browser, right? And the reality is, is that's where we're going right, it's a pane of glass accessing data somewhere else, an application somewhere else right? But the underlying operating system still needs to be secured. If you look at sort of the priorities of CIOs today, endpoint--securities number one right, and inside of that it's typically endpoint security, as you know the most important piece of it right? And so that's really where IGEL is having a wonderful time taking tremendous market share, you know we've moved, in just the time that I've been in the US, from seven to three, just in the sort of hardware part of it. And we're just having a lot of fun growing an organization that's, you know and you're growin' in triple digits, it's kind of a Cinderella moment for your career, right, so. >> Plus different kind of challenges. (laughs) >> Exactly. Exactly. >> So is there a particular vertical, is there a particular kind of business group within the companies that you guys use as a point of entry? Or, I mean how do you, what's kind of your go-to-market, >> Yeah, so there's some very specific-- >> 'cause it's a huge opportunity right. >> Yeah, very specific verticals where we're having great success in: hospitals are number one, we've sold to 143 hospitals in the US, if you can believe that, and we're in pretty, and that was just last year. >> 140? Just in a typical, typical, average, whatever metric you want to use, is how many OS's going into a hospital? >> I mean, last quarter we sold about 10000 into one hospital, you know it's usually anywhere from 2500 to 5000, 10000. And then you know these hospitals are all merging with each other, that's another value of IGEL is that they're all kind of combing, and as they combine, IGEL can take all this heterogeneous hardware, heterogeneous operating systems, homogenize it, make it easy to manage and secure. >> Putting it all back in the same spot. >> So yeah, it's definitely healthcare, healthcare's number one, but we're also doing very well in retail, very well in finance, kind of banks, really well in higher education; and like I said, we're getting to talk to at the C-level, right, they really love the savings, right? Not only are the saving on the hardware, but they can get rid of antivirus, disk encryption, they can redeploy people to do things other than patching devices. We have some brilliant things in terms of the technology; you mentioned we have the IP of 20 years, the three guys who wrote the code at the very beginning of the 20 years ago actually they were with an IGEL version before the current iteration. So literally in the end of the '90s they were, idea was let's build an operating system for the internet, which you know they may have been a bit ahead of their time in 1999, but those three guys are actually still in the building. There's a hundred engineers in Germany that are sort of iterating on this and solving for this problem, and I think they've, you know now with the US operation and the new marketing, we're kind of, it's just a perfect storm I would say. >> And then with 5G and again the increasing importance of cloud-based applications, whether it be Salesforce, or whether it be, whatever that's delivered through Amazon, I mean you guys are in a very good spot. >> Yeah, and it's, I would tell you it's not just about, you know it's this operating system fused to a management console, but then it's sort of the curation of that, right? Like okay, every 12 weeks I'm going to push you a new OS, and I have an elegant way to get that to 10's of thousands of devices. So we're also starting to see managed service providers, right, the guys that are under contract to manage millions of devices. You know the DxEs and Wipros and IBM Global Services, those guys are starting to really look at IGEL also, right, 'cause, for the same reasons the enterprises who are managing large environments; so that's been an exciting part of our growth as well. >> Yeah, and that's another huge validation point, 'cause those guys don't make small bets, they only make big bets. >> Exactly and market's sort of hardened into their architecture, which is great. >> Alright, Jed, well it sounds like a great story, and we look forward to watching it unfold over the next couple years. >> Yeah! Well hopefully, for those of the people who are out watchin' we'd love to have them come by; we're doing an event in Las Vegas inside the Mandalay Bay, at VMworld, we actually have our own event, rightfully called disrupt. And we're going to be there from the 26th to the 29th, and-- >> What venue? >> In the Border Grill, so we actually taken over this restaurant, that's kind of like right you know in the footpath of-- >> In the hallway, right? >> In the hallway yeah. >> That's the inside, I know exactly where that is. >> So yeah, we're actually takin' a page out of your book, we're going to have a little EUC TV, so we'll be interviewing people about you know what they're doing to solve for their end user compute challenges, and talkin' to the ecosystem; we have an innovation theater in the Border Grill, we're going to throw a pool party at the end, out at one of those beautiful pools that no one ever gets to go to in Vegas. (both laugh) >> We look at it though as we walk just past the Border Grill, you can find a long beautiful look at that pool. >> So we're going to try to take advantage of it, although it'll be a bit hot out there, yeah it's a hundred plus degrees in Vegas this time of year, but we're going to have some fun. You know, you got to do that a little bit, work hard, play hard. >> Alright, we'll see ya in Vegas in a couple weeks! >> Yep! Look forward to it. >> Thanks for stopping by. >> Thanks very much. >> Alright he's Jed, I'm Jeff, you're watchin' the CUBEConversation from our Palo Alto studios, thanks for watchin', I'll see ya next time. (intense orchestral music)