>> From the Silicon Angle Media Office in Boston, Massachusetts, it's the Cube. Now here's your host Stu Miniman. >> Hi, I'm Stu Miniman and welcome to the Cube's Boston area studio. This is a Cube conversation. Happy to welcome to the program first time guest Benjamin Nye, CEO of Turbonomic, a Boston-based company. Ben, thanks so much for joining us. >> Stu, thanks for having me. >> Alright Ben, so as we say, we are fortunate to live in interesting times in our industry. Distributed architectures are what we're all working on, but at the same day, there's a lot of consolidation going on. You know, just put this in context. Just in recent past, IBM spent 34 billion dollars to buy Red Hat. And the reason I bring that up is a lot of people talk about you know, it's a hybrid multi-cloud world. What's going on? The thing I've been saying for a couple of years is as users, two things you need to watch. Care about their data an awful lot. That's what drives businesses. And what drives the data really? It's their applications. >> Perfect. >> And that's where Turbonomic sits. Workload automation is where you are. And that's really the important piece of multi-cloud. Maybe give our audience a little bit of context as to why this really, IBM buying Red Hat fits into the general premise of why Turbonomic exists. >> Super. So the IBM Red Hat combination I think is really all about managing workloads. Turbonomic has always been about managing workloads and actually Red Hat was an investor, is an investor in Turbonomic, particularly for open stack, but more importantly open shift now. When you think about the plethora of workloads, we're gonna have 10 to one number of workloads relative to VMs and so worth when you look at microservices and containers. So when you think about that combination, it's really, it's an important move for IBM and their opportunity to plan hybrid and multi-cloud. They just announced the IBM multi-cloud manager, and then they said wait a minute, we gotta get this thing to scale. Obviously open shift and Red Hat is scale. 8.9 million developers in their community and the opportunity to manage those workloads across on-prim and off in a cloud-native format is critical. So relate that to Turbo. Turbo is really about managing any workload in any environment anywhere at all times. And so we make workloads smart, which is self-managing anywhere real time, which allows the workloads themselves to care for their own performance assurance, policy adherence, and cost effectiveness. And when you can do that, then they can run anywhere. That's what we do. >> Yeah, Ben, bring us inside of customers. When people hear applications and multi-cloud, there was the original thing. Oh well, I'm gonna be able to burst to the cloud. I'm gonna be moving things all the time. Applications usually have data behind them. There's gravity, it's not easy to move them. But I wanna be able to have that flexibility of if I choose a platform, if I move things around, I think back to the storage world. Migration was one of the toughest things out there and something that I spent the most time and energy to constantly deal with. What do you see today when it comes to those applications? How do they think about them? Do they build them one place and they're static? Is it a little bit more modular now when you go to microservices? What do you see and hear? >> Great, so we have over 2,100 accounts today including 20% of the Fortune 500, so a pretty good sample set to be able to describe this. What I find is that CIOs today and meet with many of them, I want either born in the cloud, migrate to the cloud, or run my infrastructure as cloud. And what they mean is they want, they're seeking greater agility and elasticity than they've ever had. And workloads thrive in that environment. So as we decompose the applications and decompose the infrastructure and open it up, there's now more places to run those different workloads and they seek the flexibility to be able to create applications much more quickly, set up environments a lot faster, and then they're more than happy to pay for what they use. But they get tired of the waste candidly of the traditional legacy environments. And so there's a constant evolution for how do I take those workloads and distribute them to the proper location for them to run most performantly, most cost effectively, and obviously with all the compliance requirements of security and data today. >> Yeah, I'm wondering if you could help connect the dots for us. In the industry, we talk a lot about digital transformation. >> Yeah. >> If we said two or three years ago was a lot of buzz around this, when I talk to N users today, it's reality. Absolutely, it's not just, oh I need to be mobile and online and everything. What do you hear and how do my workloads fit into that discussion? >> So it's an awesome subject. When you think about what's going on in the industry today, it's the largest and fastest re-platforming of IT ever. Okay, so when you think about for example at the end of 2017, take away dollars and focus on workloads. There were 220 million workloads. 80% were still on prim. For all the growth in the cloud, it was still principally an on prim market. When you look now forward, the differential growth rates, 63% average growth across the cloud vendors, alright, in the IAS market. And I'm principally focused on AWS and Ajur. And only 3% growth rate in the on premise market. Down from five years ago and continuing a decline because of the expense, fergility, and poor performance that customers are receiving. So the re-platforming is going on and customers' number one question is, can you help me run my workloads in each of these three environments? So to your point, we're not yet where people are bursting these workloads in between one environment and another. My belief is that will come. But in today's world, you basically re-platform those workloads. You put them in a certain environment, but now you gotta make sure that you run them well performantly and cost effectively in those environments. And that's the digital transformation. >> Okay. So Ben, I think back to my career. If I turn back the clock even two decades, intelligence, automation, things we were talking about, it's different today. When I talk to the people building software, re-platforming, doing these things today, machine learning and AI, whatever favorite buzzword you have in that space is really driving significant changes into this automation space. I think back to early days of Turbonomic. I think about kinda the virtualization environments and the like. How does automation intelligence, how is it different today than it was say, when the company was founded? >> Wow. Well so for one, we've had to expand to this hybrid and multi-cloud world, right? So we've taken our data model which is AI ops, and driven it out to include Ajur and AWS. But the reason would say why. Why is that important? And ultimately, when people talk about AI ops, what they really mean whether it's on prim or off, is resource-aware applications. I can no longer affect performance by manually running around and doing the care and feeding and taking these actions. It's just wasteful. And in the days where people got around that by over-provisioning on prim sometimes as much as 70 or 80% if you look at the resource actually used, it was far too expensive. Now take that to the cloud, to the public cloud, which is a variable cost environment and I pay for that over-provisioning every second of the rest of my life and it's just prohibitive. So if I want to leverage the elasticity and agility of the cloud, I have to do it in a smarter measure and that requires analytics. And that's what Turbonomic provides. >> Yeah and actually I really like the term AI ops. I wonder if you can put a little bit of a point on that because there are many admins and architects out there that they hear automation and AI and say, oh my gosh, am I gonna be put out of a job? I'm doing a lot of these things. Most people we know in IT, they're probably doing way more than they'd like to and not necessarily being as smart with it. So how does the technology plus the people, how does that dynamic change? >> So what's fascinating is if you think about the role of tech, it was to remove some of the labor intensity in business. But when you then looked inside of IT, it's the most labor intensive business you can find, right? So the whole idea was let's not have people doing low value things. Let's do them high value. So today when we virtualize an unpremised estate, we know that we can share it. Run two workloads side by side, but when a workload spikes or a noisy neighbor, we congest the physical infrastructure. What happens then is that it gets so bad that the application SLA breaks. Alerts go off and we take super expensive engineers to go find hopefully troubleshoot and find root cause. And then do a non-disruptive action to move a workload from one host to another. Imagine if you could do that through pure analytics and software. And that's what our AI ops does. What we're allowing is the workloads themselves will pick the resources that are least congested on which to run. And when they do that rather than waiting for it to break and then try and fix it people, we just let it take that action on its own and trigger a V motion and put it into a much happier state. That's how we can assure performance. We'll also check all the compliance and policies that govern those workloads before we make a move so you can always know that you're in keeping with your affinity-in affinity rules, your HADR policies, your data sovereignty, all these different myriad of regulations. Oh and by the way, it'll be a lot more cost effective. >> Alright, Ben, you mentioned V motion. So people that know virtualization, this was kind of magic when we first saw it to be able to give me mobility with my workloads. Help modernize us with cubernetties. Where does that fit in your environment? How does multi-cloud world, as far as I see, cubernetties does not break the laws of physics and allow me to do V motion across multi-clouds. So where does cubernetties fit in your environment? And maybe you can give us a little bit of compare contrast of kinda the virtualization world and cubernetties, where that fits. >> Sure, so we look at containers or the pods, a grouping of containers, as just another form of liquidity that allows workloads to move, alright? And so again we're decomposing applications down to the level of microservices. And now the question you have to ask yourself is when demand increases on an application or on indeed a container, am I to scale up that container or should I clone it and effectively scale it out? And that seems like a simple question, but when you're looking at it at huge amounts of scale, hundreds of containers or pods per workload or per VM, now the question is, okay, whichever way I choose, it can't be right unless I've also factored the imposition I'm putting on the VM in which that container and or pod sits. Because if I'm adding memory in one, I have to add it to the other 'cause I'm stressing the VM differentially, right? Or should I actually clone the VM as well and run that separately? And then there's another layer, the IAS layer. Where should that VM run? In the same host and cluster and data center if it's on prim or in the same availability zone and region if it's off prim? Those questions all the way down the stack are what need to be answered. And no one else has an answer for that. So what we do is we instrument a cubernetties or an open shift or even on the other side a cloud foundry and we actually make the scheduler live and what we call autonomic. Able to interrelate the demand all the way down through the various levels of the stack to assure performance, check the policy, and make sure it's cost effective. And that's what we're doing. So we actually allow the interrelationship between the containers and their schedulers all the way down through the virtual layer and into the physical layer. >> Yeah, that's impressive. You really just did a good job of explaining all of those pieces. One of the challenges when I talk to users, they're having a real hard time keeping up. (laughing) We said I've started to figure out my cloud environment. Oh wait, I need to do things with containers. Oh wait, I hear about the server-less thing. What are some of the big challenges you're hearing from customers? Who do they turn to to help them stay on top of the things that are important for their business? >> So I think finding the sources of information now in the information age when everything has gone to software or virtual or cloud has become harder. You don't get it all from the same one or two monolithic vendors, strategic vendors. I think they have to come to the Cube as an example of where to find this information. That's why we're here. But I think in thinking about this, there's some interesting data points. First on the skills gap, okay, Accentra did a poll of their customer base and found that only 14% of their customers thought they had the requisite skills on staff to warrant their moves to the cloud. Think about that number, so 86% don't. And here's another one. When you get this wrong, there's some fascinating data that says 80% of customers receive a cloud bill north of three times what they expected to spend. Now just think about. Now I don't know which number's bigger frankly, Stu. Is it the 80% or the three times? But there's the conversation. Hey, boss, I just spent the entire annual budget in a little over a quarter. You still wanna get that cup of coffee? (laughing) So the costs of being wrong are enormously expensive. And then imagine if I'm not governing the policies and my workloads wind up in a country that they're not meant to per data sovereignty. And then we get breached. We have a significant problem there from a compliance standpoint. And the beauty is software can manage all this and automation can help alleviate the constrain of the skills gap that's going on. >> Yeah, you're totally right. I think back to five years ago, I was at Amazon Reinvent. And they had a tool that started to monitor a little bit of are you actually using the stuff that you're paying for? And there were customers walking out and saying, I can save 60 to 70% over what I was doing. Thank you Amazon for helping to point that out. When I lived on the data center side and vendors that sold stuff, I couldn't imagine if your sales rep came and said, hey, we deployed this stuff and we know you spent millions of dollars. It seems like we over-provisioned you by two to three x what you expected. You'd be fired. So it was like in Wall Street. Treats Amazon a little bit differently than they do everybody else. So on the one hand, we're making progress. There's lots of software companies like yourself. There's lots of companies helping people to optimize their cost on there. But still, this seems like there's a long way to go to get multi-cloud and the cost of what's going on there under control. Remember the early days? They said cloud was supposed to be simple and cheap and turned out to be neither of those. So Ben, I want to give you the opportunity. What do you see both as an industry and for Turbonomic, what's the next kinda six to 12 months bring? >> Good, can I hit your cloud point first? It's just when you think of Amazon, just to see how the changes. If I go and provision a workload in Amazon EC2 alone, there's 1.7 million different combinations from which I can choose across all the availability zones, all the regions, and all the services. There's 17 families who compute service alone as just one example. So what Amazon looks at Turbonomic and says, you're almost a customer control plane for us. You're gonna understand the demand on the workload, and then you can help the customer, advise the customer which service, which instance types, all the way down through not just compute and memory, but down into network and storage are the ones that we should do. And the reason we can do this so cost effectively is we're doing it on a basis of a consumption plan, not an allocation plan. And Amazon as a retailer in their origin, has cut prices 62 times, so they're very interested in using us as a means of making their customers more cost effective so that they're indeed paying for what they use, but not paying for what they don't use. They've recognized us as giving us the migration tools competency, as well as the third party cloud management competencies that frankly are very rare in the marketplace. And recognize that those are because production apps are now running at Amazon like never before. Ajur, Microsoft Ajur is not to be missed on this one, right? So they've said we too wanna make sure that we have cost effective operations. And what they've described is when a customer moves to Ajur, that's a Ajur customer at ACA. But then they need to make sure that they're growing inside of Ajur and there's a magic number of 5,000 dollars a month. If they exceed that, then they're Ajur for life, okay? The problem becomes if they pause and they say, wow this is expensive or this isn't quite right. Now they just lost a year of growth. And so the whole opportunity with Ajur and they actually resell our assessment products for migration planning as well as the optimization thereafter. And the whole idea is to make sure again customers are only paying for what they use. So both of these platforms in the cloud are super aggressive with one another, but also relative to the un-prim legacy environments to make sure that the workloads are coming into their arena. And if you look at the value of that, they round numbers about three to 6,000 dollars a year per workload. We have three million smart workloads that we manage today at Turbonomic. Think what that's worth in the realm of the prize at the public cloud vendors and it's a really interesting thing. And we'll help the customers get there most cost effectively as they can. >> Alright, so back to looking forward. Would love to hear your thoughts on just what customers need broadly and then some of the areas that we should look for Turbonomic in the future. >> Okay, so I think you're gonna continue to see customers look for outlets for this decomposed application as we've described it. So microservices, containers, and VMs running in multiple different environments. We believe that the next one, so today in market we have STDC, the software defined data center and virtualization. We have IAS and PASS in the public and hybrid cloud worlds. The next one we believe will be as applications at the edge become less pedestrian, more strategic and more operationally intensive, then you're talking about Amazon Prime delivery or your driverless cars or things along those lines. You're going to see that the edge really is gonna require the cell tower to become the next generation data center. You're gonna see compute memory and storage and networking on the cell tower because I need to process and I can't take the latency of going back to the core, be it cloud core or on premise core. And so you'll do both, but you'll need that edge processing. Okay, what we look at is if that's the modern data center, and you have processing needs there that are critical for those applications that are yet to be born, then our belief is you're gonna need workload automation software because you can't put people on every single cell tower in America or the rest of the world. So, this is sort of a confirming trend to us that we know we're in the right direction. Always focus on the workloads, not the infrastructure. If you make the application workloads perform, then the business will run well regardless of where they perform. And in some environments like a modern day cell tower, they're just not gonna be the opportunity to put people in manual response to a break fix problem set at the edge. So that's kinda where we see these things headed. >> Alright, well Ben Nye, pleasure to catch up with you. Thanks so much for giving us the update on where the industry is and Turbonomic specifically. And thank you so much for watching. Be sure to check out theCube.net for all of our coverage. Of course we're at all the big cloud shows including AWS Reinvent and CubeCon in Seattle later this year. So thank you so much for watching the Cube. (gentle music)

>> Announcer: Live, from Las Vegas, it's The Cube! Covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to the Aria Hotel in Las Vegas, everybody. We are covering Veritas Vision 2017, and this is The Cube, the leader in live tech coverage. My name is Dave Vellante, with Stu Miniman and Mike Palmer is here, he's the Executive Vice President and Chief Product Officer at Veritas. Mike, thanks for coming to The Cube. >> Thank you for having me here. >> Great keynote, yesterday. We see hundreds, if not thousands of these discussions, and talking head presentations, and yours was hilarious. Let's set up for the people who didn't see it, yesterday. Mike gets up there, and he's talking about the, there's a video that's playing about the end of the world. And the basic theme is that you didn't take care of your data, and now the world's coming to an end. Las Vegas was in shambles, and there were waterfalls running through the hotels, drones attacking people, and then you picked it up from there and then took it into, just a really funny soliloquy. But, where'd you come up with that idea? And, how do you think, I thought it went great, but how did you feel afterwards? >> Well, I can take only partial credit. I have an amazing creative team, and when you work at a company that's been doing, you know, large-scale enterprise data-center stuff, we know that part of our obligation for our audience is kind of making it more palpable for them, making it feel a little bit more, bringing the emotion to it. So we want to have a little bit of excitement in there. But at the same time, we have a real message, you know, and hopefully that came across, too. >> It did, and then, you know, but again, a lot of good humor, the megabytes, gigabytes, you know, up to zetabytes, yadabytes, Mike Tyson-bytes, on and on and on. (laughing) Very clever, so congratulations on that... >> Mike: Oh, thanks! >> We really enjoyed it. Mixed things up a little bit. So, and again, very transparent. We talked about the UX, not the best. You're not happy with it. >> Mike: Right. >> And again, very transparent about that, I think that's a theme of many successful companies, today. But, so, let's start with, sort of, what does it take as the Chief Product Officer, to transform a company from somebody who's been around since 1983, into a modern, you know, cloud-like, hyper-scale, you know, set of service and software offerings. >> That's a big question, but I can tell you the first thing that it takes, the most important thing that it takes, is the best engineering team in the world. You can do a lot of things around the outside, we need to fix our UX, we know that, often considered that to be the kitchens and bathrooms of our house remodel. But if your foundation's broken, if your framing isn't there, you really don't have much of an asset to put on the market. We have a great engineering team, we are releasing products at a velocity that is incomparable in the enterprise ISV space, and we're super proud of that. So I think that's the number one thing. I think number two is the other thing, that we're the envy of the industry, for, and that is, an amazing install-base of customers. Very hard to name a fortune 2000 company that isn't a significant customer of Veritas, so we have a great basis to collaborate and innovate. You know, the rest, we know we have some work to do as we bring it into the modern age. You know, we talked a lot about the fact that workloads are changing in data centers, architectures are changing, we're establishing new partnerships with some of the sponsors that you see here today, like Microsoft, like Google, like IBM, and Oracle, and others. And, you know, it takes a village and they're helping us move into the next 10 years. >> Stu: You know, Mike, talk a little bit about the transition from, you know, software that lived on servers, to now, well, cloud is just isn't somebody else's servers, I think, is the word for that. >> Mike: Right. >> You know, it definitely, we've talked many times this week, you know, Veritas was software-defined before there was such a thing, used to be the FUD from the traditional players, that it was like, oh, you can't trust stuff like that, and now, of course, they're all software-defined and, you know, talking about that, too, so, what does that mean, going to kind of, being completely agnostic, for where things lived, and some of the intricacies of trying to work with, you know, some of the big and small cloud-players? >> A lot of questions in there, and I think David Noy, who I know you guys are going to talk to later, is going to talk a bit more specifically about this, but one of the first things you have to keep in mind, is if you're building software to be software-defined, then you have to build it without considering the hardware platform that you may deliver it on. And I think that's where some of our competitors get it wrong, they can say that they're software-defined, but the litmus test is, can I really pick up this software without modification, and go run it in one of those hyper-scalers? Or put it on one of the white boxes that I went into the market and procured and integrated myself? Veritas has been doing that for a long time. In fact, if you really look at Veritas's core, we're an integrator. We've been an integrator of applications, through the protection space, in our file-system and our info-scale technologies, we are integrators of operating systems, when you look at hyper-scalers, they're just the next operating system. Someone else's hardware, as you said. So we look to protect our customers in terms of their choices, make flexibility a real part of the multi-cloud architecture they're putting together, still doing the things we do well with protection, and ultimately layer on that last little bit when we're talking software-defined and that is not just focus on the infrastructure, but really aspire to this, how do I better manage data and get value from data? >> You know, Mike, I want to dig one level deeper on that. So, the cloud providers, it's all well and good to say, yeah, I'm agnostic, but each of them have their own little nuances. It's, at least today, it's not like, oh, I choose today to wake up and this one has cheaper prices, and it's not a commodity, it's not a utility, and each one of them have services that they want you to integrate with, have to have deeper, how do you balance that, you know, integration, how much work's done, where the customers are pulling you, how does that product portfolio get put together? >> That's an excellent question and I will be fully honest, that a year ago we thought about the answer to that question very differently than we do today. You know, a year ago, I think we were somewhat naive, and thought, hey, we're going to throw a thin layer of capability on top of the clouds, and in effect commoditize them ourselves, and hope our customers just move around as if there were no underlying services. And obviously if you're a cloud-provider, that is not an approach that you're a big fan of. (laughing) And frankly, it's a disservice to the customers, because they are building some really valuable services, and they are differentiating themselves. Our approach has changed, our approach today is a very deep-level integration with each cloud provider, and the specialization they're bringing to the market, without sacrificing the portability, without sacrificing the built-in protections that the cloud providers aren't putting on their platforms and don't want to put on their platforms. And again going back to this idea of data, ultimately, if it's someone else's hardware, in effect, in some cases, someone else's application, it's always your data, and how we are servicing that data is really the key. >> So, that's really hard work. In a lot of cases, you have to interface with very low-level, primitive APIs from the cloud service providers. How do you, sort of, balance your resources, or a portion of your resources, between doing that, because you guys, I call it the compatibility matrix, all kinds of data stores, all kinds of clouds, every one of those is engineering resources. And it seems that's a key part of your strategy, but you got to be sacrificing something, which is maybe, you know, the next widget on your existing products. How do you think about proportioning those? >> You know, at Veritas, in a way, the emergence of the cloud ecosystem actually improves that situation for us. We're carrying 30 years of operating systems that have come and gone, that have incremented versions, and our customers often strand or isolate single examples of those boxes, from 20 years ago that they expect us to test all of our software against, on their behalf. (laughing) For example, right, and so when you look at where we are today, there are five or 10 cloud providers, versus hundreds of operating system versions, and application, we have no problem supporting the proliferation in cloud, we actually welcome the ability to support those... >> Stu: You're much happier with the one version of AJUR, as opposed to the old Patch Monday. >> Exactly right, and you know, they upgrade the whole thing at once... >> Yeah. >> They issue a couple new services, and we adapt 'em, no problem. >> Am I thinking about it the wrong way? Because, while that's true, and I understand that, but within an individual cloud, you could have 15 data services. I think about AWS data services, their data pipeline is increasingly complex, so. Doesn't that complexity scale in a different direction? >> Mike: It scales differently for sure, but I would give a lot of credit to the cloud providers, because they're taking a lot of the regression testing that we used to have to do, for example, with application providers and operating system providers who didn't think about us when they were building their products. The cloud providers take accountability for regression testing all of the things that they release to their customers. So when we adopt an API, we're fully confident that that API works in the context of that cloud environment. So that's off our plate. It really isolates the need for us to simply test that API against our environment. >> Dave: OK, so much more stable and predictable environment for you. I want to ask you, I've heard the term modern data protection a lot, what is modern data protection? Everyone wants to be next-gen, how do you define modern data protection? >> Mike: And this is something we're super passionate about, because our industry has been around for quite a long time, and you get terms thrown out there, like legacy or modern, and everyone's fighting for brand recognition, and kind of, end of the growth spaces in the market. For us, it actually is very simple. We recognize that there are a lot of different techniques to protect data, we think of these protection schemes like lots of different insurance policies, and lots of different tools in your toolbox. Where Veritas is going to win, and continues to win, is that we can offer our customers all of those techniques. We're not trying to convince them that one technique is so much more special than another one, that they need to diversify and create complexity in their environment, so we talk about modern data protection as the ability to choose snapshots, or back-ups, or copy data management, or workload migration, in the future there will be other ways to do this: continuous data protection, or scale-out platforms for cloud providers. These are just techniques inside of a Veritas portfolio, as opposed to stand-alone companies that create complexity for our customers. So, modernization is choice. >> Dave: OK, so you have this awesome install-base. Bill Coleman said to us yesterday, in response to a similar but related question, that it's ours to lose. And the question that we have is, as you look at that install base, you got to get them onto this modern data platform. How do you do that? Do you write some abstraction layer? You talked about that thin layer in the cloud, you must have thought about doing that. Is that what you're doing? How is that going? What does that journey look like? >> Mike: You know, that is one of the most fundamental strategy questions for Veritas. And one of the things we recognized early on, is that while we do have an amazing install base of customers, and those customers are hyper-scaled themselves, you're talking about customers with tens of thousands of servers running our software, both on the storage and the protection site, so the thing that we cannot ask them to do is continuously upgrade their environment to take advantage of new features. We will put out one-to-two major releases of our software, particularly on a protection side, annually. But we're innovating at a far greater pace than that, so we've made some conscious choices to create new architectures for our customer that are workload-specific, so Cloud Point, being a great example, coming out in July, our Object Store announcements, underpinning our next generation protection solutions. So they have modern storage capabilities, our second example. But pulling them together is where only Veritas can offer a customer a complete catalog of that data. So, combining your net back-up catalog with Cloud Point, for example, with your storage, with what you've put into cloud, provides a customer, for the first time, kind of a complete view of the secondary estate. And so, as long as we get that right, we don't have to upgrade, we don't have to seed, what we have to do is enable our customers, through simple adoption of new tools, provide that visibility over the top, and I think that they'll be good to go. >> So that's kind of like a, I think of a term, backward compatibility, is essentially what you're providing for your install base, is that right? >> Mike: That's exactly right. Providing, and this is where API-based infrastructure and service-driven architectures help us a lot. We don't have to fully instantiate a code-base every time that we want to offer a service to a customer. >> Dave: There aren't many independent, in fact there aren't any independent, is one, two-and-a-half billion dollar software companies in your space, but there are many emerging guys, who are getting a lot of attention, well-funded, some, you know, hitting that kind of, 100 million dollar revenue mark, at least it appears that way. How do you look at those guys? What do you learn from them? You know, Branson said today, you know, you learn by listening and watching, in this case. You're watching the market, obviously, what are you seeing there, it's the hottest space in the infrastructure market right now, is your space and security. Are the two, you know, smoking hot spaces. What are you observing, and what are you learning? >> And I think the direct answer to your question is probably the user. You know, and I think that's the lesson of the industry even over the last 15 years, is that when a new workload arises, it's creating a new user inside the enterprise IT department. And that user often gets to determine all of the services that they need to make themselves successful. If that is a cloud workload, and they need availability services, or they need protection services, they want that to integrate in the same place that they buy in provision their cloud workload. If it's a container workload it's the same. We saw the rise of some of our competitors that got to multi-hundred million dollar revenue streams, by focusing on a single user, and a single type of transaction, with a single type of interface. And Veritas kind of lost its way, I think, a little bit, back in that time. So what we are watching today, is who are our users? What workloads are emerging? What sort of interfaces do we need to develop for those users? Which is why we made our UX statements as strongly as we did. We're committed to those. That is going to be the future of Veritas, it's serving the broadening user-base inside of enterprise. >> Dave: You're seeing a lot of discussion in the industry around design thinking, I know we're out of time, here, but, you know, you see companies, like, for instance, Charles Phillips's company, Infor, bought a company called Hook and Loop, and they're all about design, and, how is design thinking fitting into your, sort of, UX/UI plans? >> I mean, the parlance that we use internally is jobs to be done. Right, we clearly want to create a very consistent user experience, and look and feel, we want our customers to be proud to be Veritas customers. But we have to be super cognizant of, what is the job they're trying to get accomplished? And allow the system to be designed around accommodating that. If that is, I want three workflows in three steps or less, can I do that? It could be, I have a very complicated job and I want the ability to control very granular things, do I have an interface to do that? So, if we know the user and the job to be done, we can create a consistent look and feel, I think that we are, we're going to not only ride the wave, of change inside of our particular industry, but I think we're going to wind up in a consolidation space where we're a big winner. >> All right, last question, the bumper sticker on Vision 2017, as the trucks are pulling away from the area, what's the bumper sticker? >> Mike: Secondary data is your most under-utilized asset, and a platform provider is what you need to take advantage of it. >> Dave: All right, Mike, thanks very much for coming to The Cube. Congratulations, and good luck. >> Thank you for having me. >> All right, you're welcome, keep right there, buddy, Stu and I will be back with our next guest. The Cube, live we're live from Veritas Vision 2017. Be right back.