>> Live, from Los Vegas, it's theCUBE. Covering Vmworld 2018. Brought to you by Vmware and its ecosystem partners. >> Welcome back to our wall-to-wall coverage, here in theCUBE, of Vmworld 2018. We've been here for quite some time. We've got a lot to go, over 90 thought leaders are going to be working with us. I'm Peter Burris, I'm the head of research at Wikibon, and we got a great guest today. Killian Evers is the vice president of CX and UX >> You got it. >> Customer experience, user experience at Veritas. Welcome to theCUBE! >> Thank you so much. It's a pleasure to be here. >> You know, there's so much that you could talk about, when you start talkin' about CX and UX, and a lot of technology people are starting to understand what these things are. A lot of users are startin' to recognize that adoption doesn't happen if you don't make it easy for the user. What's the difference, though, between CX and UX? >> I love that you ask this question. User experience, as you know, it's everything that goes on in terms of a human engaging with technology. Now, when you think about how you engage with your phone, for example, that's a great example of a good user experience. Now, when we apply that user experience, we move beyond it, to customer experience. We are really looking at the customer's entire journey. How do you engage with Veritas? How do you find us, how do you engage with our sales, understand our marketing, buy a product, get support for a product, and upgrade a product, that entire life cycle with all of the best learnings from our user experience? That is customer experience. >> So, if I can kind of encapsulate that, we might think of user experience as the interaction or the quality of the experience you have with the device, or a piece of software, or a machine. Whereas customer experience is the experience you have with the brand that's ultimately delivering that. Is a sales person, is the sales engagement good? Is the support engagement good? It's the whole immersive-- >> Right. >> the degree to which the brand is immersive in how the business operates. So, great, obviously this is an important set of things, but what does the VP of UX/CX do, are you evangelizing this? How is this working out? >> You know, it is a bit of an evangelization role, but more importantly, I think of my job as the customer's advocate. I look at everything with a really critical eye, to make sure that our customers are getting the best experience in everything that Veritas supplies. Everything that we provide is to that mark, that really makes their experience fantastic. That's really my job at the end of the day. So I can be designing, I can be doing research, applying these great principles, redefining products experiences, pushing support, pushing sales. All with an eye to deliver the best for our customers. >> Now, as an analyst, someone who spends her time with large users, helping to make decisions and getting value, one of the biggest challenges, especially as these technologies are more embedded within the business, is how can I encourage everyone in my organization that should adopt a new solution or a new way of doing things, to actually adopt it. And that's much more than the quality of the interface and the software. Is that what you mean? >> Yeah. >> You want to facilitate the process by which your customers-- >> Absolutely. >> Let's talk about that. >> Yeah, let's talk about that, because, you know, the thing is I could make you use something, but that's not going to give you that level of adoption if you want to use something. So it's about getting to that want. Getting to what you, what's your motivation, what's your desire? It's about building that community so that you create that virtuous cycle of wanting to use the software, liking to use the software, continuing to use the product- >> Advocating for using the software. >> Advocating for using that. >> You know, I'll tell you something. I've actually seen a lot of examples where the product was the right product for the solution, the IT organization did a good job of implementing and rolling it out, but ultimately, because they didn't think about that journey process, within their own business-- >> That's right. >> Their customers, their users, ultimately abandoned ... >> Right. >> And so what you're trying to do is making sure that they don't abandon ... >> We don't have that. That's exactly right. >> But Veritas also is very deeply embedded within a whole lot of activities within a business by virtue of what you provide. So how does Veritas' customer experience provide a grow to other Veritas partners that are embedded within the business? >> I love it, and that actually speaks to a couple of different ways. So, one, we have a phenomenal program that we work with our customers, our partners, our end users, to understand what they're facing on a day-to-day basis, understand what's goin' on in their company world, to be able to create that integration. The other thing that might surprise you, considering that you had been talking about customer experience and design ... Let's go to the other end of the spectrum, API First. How do you create those customer interactions? How do you create great experiences? You create great interactions, great engagements, integrations. We have an API First methodology and perspective that we bring to be able to say it's not just about the screen, but it's about how you can integrate with that experience. Between the two of those things, we can create those great experiences from end to end. So, as an advocate for the customer, you're not just talking to the people who are building the product, you're talking to people who are engaging to talk about the sale, to conduct the sale, throughout the entire journey. >> Exactly. >> Give us a couple of examples of how Veritas has become a better partner to customers as a consequence of taking on this challenge. >> Wow, I have to talk about NetBackup, and specifically our new release of NetBackup 8.1.2. This is our flagship product; we have redesigned this from the ground up. It has the API First methodology. It has all of the integrations. It has a phenomenal experience. We have simplified the ability to create backups. We have simplified the creation process of our protection plans so that everything is seamless. One, two steps; that's it. We have worked through our programs to build this, and to create this overall experience by building it together. We have worked with our customers, with our end users, and partnered with them to create this experience. So that's just one example. And this is the first product coming out of the gate that has this incredible experience. And we're not going to stop there, we're continuing onward. We are thinking about upgrade; we are thinking about sales, marketing, all of those aspects together. >> So the notion of user experience and customer experience, it's interesting, it started in the technology world, when people started talking about personas as the user. >> That's right. >> And then, when we started digitizing marketing through the web, it moved into the marketing world-- >> That's absolutely right. >> And you're started thinking about broader notions of customer engagement. At Veritas, how is that notion of design, design thinking, informing the process of building products that are easy to use, easy to adopt, great time to value, and are going to stick and stay inside a customer organization? >> And that's really part of my internal evangelization. I have really transformed the overall organization at Veritas. We now have a dedicated, centralized customer experience and user experience organization. We work directly and deeply with our engineering, our sales, our marketing partners, our product managers, to infuse design thinking. We've done workshops, we teach on-the-go, to be able to teach that perspective. It's actually something that everyone's hungry for, because once you see it, then you start to know, aha, this is actually better, right? An engineer sees this is a better experience. Everybody wants to provide the best for our customers, so it's somewhat of an easy job, to do the evangelization, because folks are readily adopting it, because it's natural, it's intuitive. >> And look, there's some big, big IT organizations out there that are adopting some of these principles as well. >> Yeah. >> You start talking about Home Depot, and others, very, very successful efforts, their failure rates have gone down dramatically from an adoption standpoint, as they have adopted some of these practices. So, when you think about, ultimately, the impact that it's going to have on Veritas' relationship with its customers, where do you want Veritas to be in three years, as a brand, known for superior user and customer experience? Where do you think it's going to be? How will people reflect that back on Veritas? >> Yeah, so, if I can put on my prediction hats, we are already the number one in NetBackup. We are already the number one backup provider. We're going to be the number one experience provider. That is my goal. >> For? >> For everything that we do. >> Not bad. So, one more question as we think about where this is going. You've been here at Vmworld for at least some period of time. Pat Gelsinger talked significantly about bridging, and the new communities that have to be served, and the role that technology's going to play as we move forward. >> Yep. >> Obviously, for technology to become a bigger feature of people's lives, it's got to be easier, it's got to be more tied into, ultimately, how people live their lives. >> That's right. >> So, when you think about Veritas, you know, Silicon Valley company, been around for a long time, number one in a lot of markets, as you said, how does that end up translating into better community engagement, better customer trust, all these other things that are really, really important? Is this going to create capital that you guys can use to introduce faster products; introduce more functionality; better, richer partnerships? >> Absolutely, so I have to talk to you about our design strategy, because it's really the three pillars that we are building all of our new experiences on. It has to be simple; it has to be easy for everyone to understand, and this is what we were talking about earlier in the day. It has to be intuitive; it has to be based in human interactions, because that just feels intuitive. Technology is not scary; it's not hard. If it's simple, and if it's intuitive, you're going to be able to use it, the adoption rates are going to increase. And finally, it has to be integrated, because if it's not integrated, if it's siloed, the adoption rates are going to go down. No one's going to want to continue to use it. You're not going to build that community. You're not going to build that market share. So, really, my design strategy is based exactly in what you're talking about. It's simple, it's intuitive, and it's integrated. That makes great product. >> And it gets customers excited. >> You got it. >> And it makes them trust the solution so they themselves, there's something in the adoption world called reinvent. >> You got it. >> You want your customers to reinvent on Veritas, and constantly push the envelope of how they're getting value, because that makes you a better company. >> Exactly. >> Alright. Killian Evers, Vice President CX/UX-- >> You got it. >> Veritas. Thanks very much for being on theCUBE. >> Thank you so much, I appreciate it. >> And this is Peter Burris, once again, Chief Research Officer at Wikibon theCUBE. I want to thank you very, very much. This is our last shot of the day. We're going to be doing wall-to-wall coverage tomorrow. Stay here, with theCUBE, more about what's going on in Vmworld. We'll talk to you again. (techno music)

>>Hello, everyone. Welcome to Entities Summit. My name is Ellen Komarovsky and I will talk about sparks So simple realizable arguments of knowledge. This talk is based on the joint work No, me, Frank, Cody, Freytag and Raphael past. Let me start by telling you what's the same documents are that's the same argument is a special type of interactive protocol between the prove prove er and the verifier who share some instance X, >>which is allegedly in some language. And the goal of the protocol is for the proper toe convince the very far that access indeed in the language for completeness, the guarantees that their guarantees that if X is indeed in the language, the verifier will in the end of the protocol indeed be convinced. On the other hand, for sadness we require that if X is not in the language, that no matter what the proper does, as long as it is bounded to run in polynomial time, the verifier will not be convinced. There is a stronger notion of sadness called an argument of knowledge, which says that the only way for the approval to continue the verifier is by knowing some witness there is a mathematical way to formalize this notion, but I will not get into it for efficiency. And what makes this protocol succinct is that we require the very far is running time and communication complexity between the program, the verifier Toby, both mounted by some political written function in T, where T is the time to verify the empty statement. In terms of the proof is running time, we don't require anything except that it's, for example, in normality. The goal of this work is to improve this polygonal overhead of the prove er, to explain why this is an important task. Let me give you a motivating example, which is just the concept of delegation of computation. So considering some small device, like a laptop or smartphone, that we used to perform some complicated computation which it cannot do. Since it is a big device, it wishes to delegate the computation to some service or cloud to perform the computation for it. Since the small device does not fully trust the service, it may want to ask the device the service to also issue a proof for correctness of the computation. And the problem is that if the proof it takes much more time than just performing the computation. It's not clear that this is something that will be useful in practice thinking. Think off an overhead, which is square of the time it takes to perform the computation. This will become, very quickly a very big number or very, very large delay for generating the We're not the >>first to study this problem. It has been studied for several decades, and at least from a theoretical point of view, the problem is almost solved or essentially solved. We have constructions off argument systems is great overhead, just bottle of arrhythmic multiplicity of overhead. This is obtained by combining efficient disappears. Together with Killian's arguments is there's a >>huge open problem in complexity. Theory of constructing PCP is with constant over namely, running just in linear time in the running, in the running time off just running the computation. But we argued that even if we had such a PCP and the constant was great, let's say it was just too. This would already be too much, because if you delegate the computation to takes a month toe complete, then waiting another month just for the proof might not be so reasonable. There is a solution in the literature for this problem in what we call using what we call a reliable PCP medicine. And I'll show that there is a recipe construction that has the following very useful property. Once you perform the computation itself without the just the computation and write down the computation to blow, then there is the way to generate every simple off the PCP in just only logarithmic time. So this means that you can, in parallel after computing the function itself, you can empire led, compute the whole PCP in just falling over it. Next time this gives you this gives us a great argument system with just t plus Polly locked parallel time instead of three times for luck tea time. But for this we need about the process service, which is prohibitively large. This is where sparks come in. We introduced the notion, or the paradigm off, computing the proof in part to the computation, not after the computation is done slightly more formally. What spark is it's just a succinct argument of knowledge, like what we said before, with the very fired and communication of Leslie being small but now we also require approval for which is super efficient. Namely, it can be paralyzed able. And it has to finish the proof together with the computation in Time T plus volatility, which essentially the best you can hope for. And we want to prefer to do so only with political rhythmic number off processors. You can also extend the definition to handling computations, which are to begin with a paralyze herbal. But I will not touch upon this. In the stock, you can see the paper. For the >>girls, we have two main results. The first main result is the construction of an interactive spark. It's just four rounds, and it is assumes Onley collisions is not hash functions. The second result is a non interactive spark. This result also assumes career resistant hash functions and in addition, the existence off any snark and namely succinct, non interactive argument of college that does not have to be a super efficient in terms of programming time. Slightly more generally, the two theories follow from >>combined framework, which takes essentially any argument of knowledge and turns it into a spark by assuming on a collision system, hash functions and maybe the multi behind the construction could be viewed as a trade off between computation time and process. Source. Winston. She ate theorem one using Killings protocol, which is an argument of knowledge, which is a four round argument of knowledge. And we insensate you're into using its not which is an argument knowledge. Just by definition, let me tell you what are the main ideas underlying our construction before telling you to control the ideas. Let me make some simplifying assumptions. The first assumption I will only be talking about the non interactive regime. The second example assumption is that I'm going to assume snark, which is a non interactive 16 argument of knowledge. And then we'll assume that's not the snark which is super efficient. So it will consumed other time to t for computation that takes 20 so almost what we want, but just not yet, not not yet there. I will assume that the computation that we want to perform a sequential and additionally I will assume that the computation has no >>space, namely its ah, or it has very low space. So think about the sequential computation, which MM doesn't have a lot of space or even zero for the for the time being, I would like to discuss how to simplify, how to remove this simplifying assumptions. So the starting idea is based on two works off a nettle and duckling. It'll from a couple of years ago. And here's how it works. So >>remember, we want toe performative time. Computation generated proof and we need to finish roughly by time. T. So the idea is to run half of the computation, which is what we can afford because we have a snark that can generate a proof in additional to over two steps so we can run the complete half of the computation and prove that half of the computation all in time T. And the idea is that now we can recursive Lee computer improve the rest of the computation in Parliament. Here's how it looks like. So you run half of the computation, started proof, and then you run a quarter of the remaining half of the remaining computation, which is a quarter of the original one, and prove it. And in parallel again, you take another eighth of the computation, which is one half of what's left and so on. And so forth. As you can see, that eventually will finish the whole computation. And you only need something like logarithmic Lee. Many parallel processors and the communication complexity and verifies running time only grow by algorithmic >>factor. So this is the main idea. Let's go back to the simplifying assumptions we have. So the first one was that I'm only gonna talk about the new interactive regime. You have to believe me that the same ideas extend to the interactive case, which is a little bit more massive with notation. But the ideas extent so I will not talk about it anymore. The second assumption I had was that I have a super efficient start, so it had over had two T >>40 time computation again. You have to believe me that if you work out the math, then the ideas extend to starts with quasi linear overhead. Namely, starts that working time tee times, Polly locked e and then the result extends to any snark because of a result because of a previous work will be tense. Kettle, who showed that a snark with the proof it runs in polynomial time can be generically translated into a snark where the programs in quasi linear with quasi linear overhead. So this gives a result from any stark not only from pretty efficient starts. The last bullet was about the fact that we're dealing with only with sequential Ram computations. And again, you have to believe me that the ideas can be extended toe tyrants And the last assumption which is the focus of this work is how to get rid of the small space assumption. This is what I'm gonna be talking next. Let's see what goes wrong. If the if the computation has space, remember what we did in the previous. In a couple of slides ago, the construction was toe perform. Half of the computation prove it and then half of the remaining computation prove it. And >>so on. If you write down the statement that each of these proofs proofs, it's something like that a machine m on input X executed for some number of steps starting from some state ended at some other state. And if you notice the statement itself depends on the space of the computation, well and therefore, if the space of the computation is nontrivial, the statements are large and therefore the communication will be large and therefore the very fire will have toe be running time, proportional to the space and so on. So we don't even get a saint argument if we do it. Neighborly. Here's a solution for this problem. You can say, Well, you don't have to include the space in the whole space. In the statement, you can include only a digest of the space. Think about some hash function of the space. So indeed, you can modify the statement to not include the space, but only a digest. And now the statement will be a little bit more complicated. It will be that there exists some initial state end state such that there hush is consistent with digest in the statement. And if you run the machine M for K state and for K steps starting from the initial space, you end up with the final space. So this is great. It indeed solves the communication complexity problem in the very far complexity problem. But notice that from the proof for site, we didn't actually do anything because we just move, pushed the complexity in tow. The weakness. So the proof is running. Time is still very large with this solution. Yeah. Our final solution, if in a very high level, is to compress the witness. So instead of using the whole space is the witness. We will be using the computation itself in the computation that we ran as the witness. So now the statement will be off the same form, so it will still be. It will still consist off to digests and machine. But now the the witness will be not the whole state. But it will be the case steps that we performed. Namely, it will be that there exists case steps that I performed such that if I run >>the machine m on this case steps and I started with a digest and I just start and I applied this case steps on the digest. I will end up with the Final Digest. In order to implement this, we need some sort off a nap. Datable digest. This is not really hard, not so hard to obtain because you could just do something like a miracle tree. It's not hard to see that you can add the locations in the medical tree quite efficiently. But the problem is that we need toe toe to compute those updates. Not only not only we need toe be ableto update the hash browns, the hush or the largest which don't also be able to compute the updates in parallel to the computation. And to this end, we introduce a variant of Merkle trees and show how to perform all of those updates level by level in the in the Merkel tree in a pipeline in fashion. So namely, we push the updates off the digest in toe the Merkel tree, one after the other without waiting for the previous ones to end. And here we're using the tree structure off Merkle trees. So that's all I'm gonna say about the protocol. I'm just gonna end with showing you how the final protocol looks like We run case steps of computations. Okay, one steps of computation and we compute the K updates for those case steps in violent the computation. So every time we run a step of computation, we also update start an update off our digest. And once we are finished computing all the updates, we can start running a proof using those updates as witness and were forcibly continuing this way as a conclusion this results with the spark namely 1/16 argument system with the proof is running Time t plus for you Look, team and no times and all we need is something like quality of arrhythmic number of processors. E would like to mention that this is a theoretical result and by no means should be should be taken as a za practical thing that should be implemented. But I think that it is important to work on it. And there is a lot of interesting questions on how to make this really practical and useful. So with that, I'm gonna end and thank you so much for inviting me and enjoy the sandwich.

>> Live, from Las Vegas. It's theCUBE! Covering VMworld 2018. Brought to you by VMware. And, it's ecosystem partners. >> Welcome back to theCUBE's coverage of VMworld 2018 in Las Vegas. Third day, some of us, our voices are a little bit rough. But, we've still got a lot of stuff to do, and summit people are still looking quite good. I'm Stu Miniman, my co-host, Justin Warren. Now talking about our current guest who, you know, came in looking great, good energy, Jyothi Swaroop, welcome back to the program. You're the vice president of Global Marketing with Veritas. >> Thanks Stu, thanks for those kind words. I mean, I'm just joining the party here, in terms of good-looking guys. So it's, it's not unique to me at all. >> Yeah, you know, didn't have as much, you know, time to spend on our hair this morning. >> (laughs) Hey I wake up this way. >> That's odd, alright. >> So do I. (everybody laughs) >> Alright, so Jyothi, first of all, VMworld, you know this ecosystem. There's a good energy at the show, what's been your impression so far? >> Look, I mean, haven't been on the other side, right? I've actually having worked for Dell EMC in the past, and, you know, being part of organizing an event like this It's great to see the VMworld, the diaspora expanding with every year, and how they've reinvented themselves. In every three to four years people were like, "Oh, VMworld's going away, VMworld is not relevant anymore." But it's been amazing to see the evolution of VMware, and how they've reinvented themselves, what they're doing with AWS et cetera. And at Veritas, we're trying to map to that strategy we're going where the buck's going right? So, we're literally map into everything VMworld's doing with their customers, which tends to be a lot of our customers. There's a significant overlap between Veritas' customers and VMware install base. >> Yeah, I absolutely, I mean, we talk about things like software to find these days, and especially like in the storage world, I mean, Veritas were like, was the original in that space. When you, oh how do I get software out of hardware? It's like Veritas was the no-hardware-agenda company. So at this show, the last few years, you know, data, you know, data protection, multi-cloud, and how that impacts data, have been, big themes. Tell us how that ties in to what you're hearing from customers, and what you do at Veritas. >> Yeah, absolutely. So, you know, the two words that come out are data management, right? So, increasingly yes, we are in a multi-cloud world. Everybody will tell you that there are at least, four to four and a half clouds on average, that most of our enterprise customers use. And when I say that, it doesn't mean public clouds only, obviously right? There are SAS portals that people access, there are actual Infrastructure as a Service public clouds that people access. So, it's a combination of those. At Veritas, what we want to do is we want to focus on the one of the most important elements of managing data, which is protected. Right? Look, recently, you know, there have been news about you know, large transportation companies, I won't say which type, but, transportation companies, you know, being grounded. Because their clouds were not up. Or, you know, data wasn't protected enough. Not because the planes or the trains weren't working well, they were working fantastically well. It's just because their systems were not up, they weren't protected, they weren't backed-up. They just trusted their cloud vendors, or, whoever else to manage it for them. Doesn't work that way, right? You are responsible, if you actually read through some of the contracts that are out there from multi-cloud vendors or cloud vendors, it will clearly say, "You, Mr. Customer are responsible for your own data protection." So that's where Veritas comes in. So, we help customers protect their data where it's at. Whether it's in a public cloud environment, whether it's virtualized through VMware, or with some physical servers, right? And we've been doing this for 30 years. >> Yeah. And I've used NetBackup for many many years, I have a long heritage and even before that, Veritas was pretty much the standard for the way that we did all kinds of storage and data management, as to your point there. So, give us a bit, some examples of, of what customers are doing with Veritas in this new year of cloud, and data could be anywhere. >> Absolutely. So I think the first step to all of this, is visibility. A lot of people don't talk about data visibility enough. Why don't they talk about it enough? Is because most of the management and visibility tools that companies have these days or vendors have, are limited to their own infrastructures. So they're basically IT ops tools, right? To help manage their particular software-defined infrastructure, or a hardware box, et cetera. They're not really trying to be Switzerland for everybody. At Veritas we have this unique honor almost of being the Switzerland. Everybody wants to work with us, has worked with us for the last 30 years. We don't really come out there and say, "We're competing against every infrastructure company out there.", no. We're very good at data protection, we've extended our leadership from data protection to software-defined storage, as two talked about earlier on, we launched our portfolio three years ago, and Gartner has published the fact that we're number one in software-defined storage market share, already, in three years. Because, it's in our DNA. We build the first software-defined product, and we used that, back in the Veritas Oracle Sun Microsystem days, VOS, as it was called. And we've used that DNA to build this out and extend our data-protection into storage. And that's why I said it's visibility, protection, and then storage. And that storage could be anywhere. >> Yeah, Jyothi, one of the challenges that we have in the industry is you say, NetBackup has, you know, a long history, decades out there. People be like, "Oh well, you know, I was using it for a while but then something changed, then you know, I haven't looked at it in five years, ten years." So tell us why, you know, the NetBackup of the day isn't you know, our father's NetBackup. >> Oh great question, I love that question, right? So, it's not your father's net back up, clearly. Look, NetBackups has been great for your what we call traditional workloads, for the last, what, 25 years. Oracle, you know, SQL, we've done phenomenal with that. But the world has moved on. The world's move to NoSQL. The world's moved to Hadoop. The world's moved to a lot of unstructured data-related infrastructure. >> We're talking about RDS at this show, so... >> Exactly. You know, and NetBackup has had to evolve as well. Look, I'm an engineer. I know how difficult it is to take a product that's 20, 25 years old. And to kind of make it relevant to today's workloads. And we did take our time. So until our last week's launch of NetBackup, the latest version, you know, we didn't go out there and market ourselves as the modern workloads' data protector. We did market ourselves as, "Hey listen, your mission critical workloads that still run on Oracle et cetera, yes then backup is the product for you. But we do have other data management technologies that will support you." But today, I'm very happy to announce that we've not only, kind of, we protect most modern workloads, but we've simplified the UX as well. So, I'll make a comment on the market. Before I get into NetBackup again. So, if you notice there's a lot of money being raised in the data protection space. A lot of new vendors that have come out there right? And what's the message they use? The messages of, that of simplicity. Because they can't come out to gate and say, "We're the most reliable, scalable, product that's being used by the, by 86% of the Fortune 500." They can't say that throughout the gates. So what do they use, they say, "We're simpler to use. We're not about job security, we're going to cater to you Mr. Customer, three clicks to Nirvana.", right? That's literally what the message is. So what we try to do with NetBackup is, look, we are the king of scale. We're the king of reliability. We know that. So we've completely modernized, Killian was here at theCUBE yesterday and she's the Head of User Experience. So we created an entire team for user experience alone, and we've simplified all of the operations on NetBackup. So if you're a VMware admin or a backup admin, or a storage admin, it doesn't really matter. Looks, feels the same, and you get three clicks to value. Right, even if you don't reach Nirvana, you get three clicks to value. With everything you do. So we've really simplified the operations, we continue to be the king of scale, we continue to be deployed at multi-terabyte scale, and that innovation's going to roll on. >> That's a really encouraging thing to hear, because, I mean, all of the new vendors as, a good point that you make there is it, they can't reduplicate that idea. We have 10 years of history, or 25 years of history. So, we've been doing this for a long time. And that means that you can trust us with your data. If anything, that you need from a data-protection vendor is, the ability to trust them, that when I go to try to recover my data, it'll be there and it will work. You've fixed that. You've been doing that for such a long time. So now you're just, updating the software to be able to make it easy to use, doing some of the new things, well of course anyone needs to be able to adapt and do some of the new things. So the fact that you're adding some of these features, so maybe you could give us a bit of a flavor of some of the changes that people would notice in, from, if you've experienced that backup before, what does it actually look like now? >> So, for those NetBackup admins that have been using NetBackup for decades now, right? They will, cannot be used to the Windows interfaces where it's a file structure and things have to be dragged and dropped and things like that. But if they go to the new interface now, it's available for download of our website, it's literally just all tiles and buttons and clicks. The new user experience that you expect from an iPhone, that's exactly what we put into NetBackup 812. Now the other thing I want to talk about is, we spoke to about, I think I've personally spoken about 15 customers at this show. Day one and day two. They said, "While the simplification is great Jyothi, we're actually looking ahead already. We're looking ahead to machine learning and AI where, I want your software, tell me when jobs are going to fail." I don't want an alert when the job has fail, and then I have to do something about it. Yeah, it's cool that I can pull my phone up or my iPad up and take actions right away, and make sure data is protected. But I really would love for, you know, your software to predict when something's going to fail. Help me, warn me to take action in advance. If not, take action yourself, for the simple job failures that you can take action on, based on policy driven actions, right? So that's essentially what our customers are asking for and that's what we've been incorporated into 812. >> Yeah, Jyothi, great stuff. What I want to step up level for a second here, and what you're hearing from customers about kind of the challenges and opportunities with data, and maybe start with, we spent the last year, or year and a half, hearing a lot about the impending GDPR, it doesn't feel like it ended up being like the Y2K, you know, scramble at the last minute, couple of lawsuits against like Google and Facebook. But other than that, I haven't heard nearly as much since we passed, you know, that deadline earlier this year. Start there as the update and tell me what else is facing customers into kind of their challenges. >> Sure. Look, if I have to use a loose analogy here, I considered GDPR as, filing your taxes. Most people wait 'til the last day, right, and they get extensions, if things are not right, et cetera. But having said that, filing taxes is one of the most important things you do, right? So, as a corporation this is very similar. Most corporations, you know, want to wait to see if there are others that will take missed steps, and they can learn from that. There's nothing wrong with that. But a lot of the Fortune 500 customers that we deal with, take GDPR extremely seriously. Yes, you mentioned a couple of companies that have been fined, or are being investigated, et cetera. Nobody wants to be in that book, right? You know, a large company can take a little, a fine of some magnitude, but a smaller to medium business company, that could be you know-- >> That could end the business. >> That could end the business for them. And they don't want that. So a lot of these customers are taking GDPR seriously, but what is different to what we expected, not just as Veritas but as an industry is they're taking a consultative approach to this GDPR. It's not a product-based approach. There's no magic bullet, like, I buy three products and stitch them together and I'm GDPR compliant. They're taking a very consultative approach looking at their data, especially companies that have existed for many years, it's really hard for them to go back. The data sitting on some archaic systems, they really don't know, you know, how do I delete? I mean, if Stu was a European citizen for example, and he said, "Hey listen, X, Y and Z company, I want you to delete everything you have on me." It's sitting on some mainframe or bunch of tape, et cetera. There's no way for them to get that out, and Stu's able to sue them if they're not able to take action by X number of months or years. So, you know, it's an interesting but a very important challenge for companies. >> We're experiencing some of those challenges here in Australia as well, which is not actually subject to GDPR, but there's certainly a lot of a, a lot of legislators and a lot of other organizations looking at it, particularly if they're global organizations, they do need to be compliant. It applies to EU citizens, so, if we have EU citizens and you have systems in another country, then you need to actually deal with GDPR issues even though you're not part of the EU. So a lot of organizations are grappling with that. So, maybe you could give us a bit more of an indication of how Veritas is helping those customers to grapple with that situation. >> Yeah, absolutely you're right. So, as long as you have a connection to the EU, whether through a customer or through some sort of a transaction, you're already part of the GDPR compliance initiative. Right, that's what customers need to realize if they haven't already, that's number one. Number two is going back to my original point about visibility. Compliance has been a thing for a long time. GDPR's yet another new thing that are on compliance. So if you don't have end to end visibility into your infrastructure, and if your data is not classified, and it's not classified on ingest going forward. Look, yes I made a big deal about the fact that over the third, last 30 years we've created on our data, and we put it away in archaic systems, but if you consider that as a percentage of the amount of data that we have today, it's very small. What they should be most worried about as customers is, what they're going to create in the future. So the classification of the data has to happen on ingest. As soon as it comes from a Hadoop system, et cetera, needs to be classified, this is ROT data, right? This is redundant, obsolete, et cetera, I need it classified this data has PII information, so I need to put it separately. I can't just ship everything off for the cloud. So that's what we help with Veritas. Our products help you classify the data on ingest. Right, so you can actually tier this data to the right, you know, storage mechanisms, and have visibility, end to end visibility of that data. Globally. And then you can actually take actions when you have that visibility, you can actually say, "You know what, I don't need six petabytes of browsing history, of the 100,000 employees that I have. They've literally gone Amazon and bought diapers for their babies or whatever. I don't really need to store that stuff. I can just delete it, boop and it's gone right?" Customers don't have that confidence today 'coz they don't have that visibility. >> Jyothi last thing I want to have you help us cover is, we know Veritas has a long history. Learned a lot I think being inside Symantec, now coming out. Bring us up to speed as to kind of Veritas today, position in the marketplace, what the customers are coming to you at this show and outside this show for specifically. >> Absolutely. So, Veritas continues to be the leader in data-protection. That's not going away, that is still at the heart of everything we do, right? Whether it's NetBackup, or other products that we put out to market, it will still be at the core of everything we do. We protect the customer's most valuable data. From the Fortune 500 all the way down to the SMB level, right? That's number one. Number two, we're extending that leadership into new areas like software-defined storage. We're already number one in market share for that. We're going to continue to work on our archiving business, we're number one in there as well, according to Gartner. Right? So the three key areas that we're already in, we're number one. The next area we're going into is, you know, paper over rocks. We want to get into the data management business because we realized, we are the true Switzerland of infrastructure. There are very few companies that, you know, would say, "Okay, I'm competing head-to-head with Veritas and a lot of thing, I don't want to work with them." Right, unless you're a core data protection vendor. Everybody else wants to work with it. We have partnerships with all the major public cloud vendors, to VMware, to you know, on-prem traditional vendors, who you might even consider as competition. They all want to work with us because we sit on top of the most number of exabytes of data in the world. We protect the most number of exabytes of data. So there's a lot we can do with that data. Protection is not enough. Our next step in this journey is to make management, visibility, and compliance on top of that data, a lot easier for our customers. >> Alright, so if you're to sum it up in one word, is this still Veritasome? >> It's Veritasome. It's very very Veritasome. >> Alright, well we've been having an awesome week here at VMworld. Jyothi Swaroop, thank you for the update with Veritas for Justin Warren, I'm Stu Miniman. We hope you've had an awesome time watching theCUBE. (techno music)