 Hello everyone, I'm John Furrier here in the Palo Alto Cube Studios. I'm the co-host of the Cube, also co-founder of SiliconANGLE Media. We're here for some big news from Veritas. We're at Eric Sademan, who's the director of Solutions Marketing for Veritas. Veritas is introducing today and the press release is on the wire of Veritas Predictive Insights. Eric, thanks for coming in today and sharing the news. Absolutely, thanks for having me. So you guys have a unique new thing for Veritas, not new in the industry, but new in capabilities called Predictive Insights. I know Dave Vellante's actually linked on your press release and covered it in Chicago as an embargo. This is exciting news for Veritas because you guys have so much customer install-based, tons of data. Talk about what this product is, what's the news? Well, thanks John. Yeah, actually the news, it's pretty exciting. Our customers are very exciting and receptive about it. What it's actually doing is helping our customers reduce both planned and unplanned downtime. And the way we're doing that is with an analytics engine that we've developed. That's taking all the data from over 15,000 of our appliances around the world. We've been collecting that data for three years. We have hundreds of millions of data points from that. And we're utilizing our own AI ML engines that we've created to be able to predict things in customers' environments that may cause them downtime or outages and fix those before they happen. So that's why our customers are really excited about it. So how much does this cost? Well, it doesn't really cost anything. It's a value add, you know, if our customers are utilizing our Veritas auto support services today, then as of yesterday, the service is turned on and we're already looking at their systems and creating this intelligence on them. So this is immediately value though. So this is a new product from Veritas that takes existing operational data from your customer's environment. You guys are matching in your corpus of metadata. Exactly. Telemetry data, what, hundreds of millions of signals, call center, real log data around real outages and real things, and creating machine learning and AI on top of it to extract value for you guys or for the customer? Well, it's really for the customer. The benefit for the customer is that we have insights into our worldwide universe of customers, but we can look at individual systems and say, why is this one operating differently than the others? And then the machine learning will actually determine that the ones that are operating really well have this patch and this patch installed and those types of things. And then we can apply that learning in that model to a particular customer's system. And they get a dashboard. And they get a dashboard that'll highlight what we call a system reliability score. So there's this, big enterprises, there's a lot of fatigue associated with events that are occurring all the time. You think of an enterprise, when we have customers with many, many just net backup appliances alone, you think of their entire infrastructure and all the alerts that they're getting that creates a lot of fatigue. A lot of things go unfixed because they're minor events, like maybe a patch needs to be installed or for more update while they're fixing the more hair on fire problems. But then ultimately those, what looked like smaller events build up and build up and then they create outages. So what we're able to do is to identify which systems have potential anomalies, highlight those very visually. And then they can drill down and we'll have prescriptive maintenance that can be taken to improve that score. So cyber reliability score, let me just get that in a second. I think that's a big deal. I want to read the press release headline. Veritas Predictive Insights uses artificial intelligence, AI, machine learning, ML to predict and prevent unplanned service. Now, key word there is unplanned service. This is kind of the doomsday scenario for a customer. If they get a large data center or large infrastructure devices, unplanned basically means an outage if something happens, something bad happens. Something bad happens. Something like that. So what you guys are doing is giving them a value-added dashboard that taps into a product. So if, correct me if I'm wrong, but a customer that has Veritas, if they have the products, they get the service. If they become a customer, they now have the capability built in out of the gate. And so they see all this. So you're taking all the data from years of experience, giving them a dashboard to help them look at unplanned downtime type scenarios and give them specific actions to take predictive analytics and prescriptive analytics for them. Exactly. So what we're trying to really achieve for our customers is to use that intelligence and machine learning to identify things that may cause an outage in the future and prevent that outage from occurring, causing that downtime by taking remedial action in advance of that happening. And that's the beauty of predictive insights. That's really what it's providing for our customers. So you guys have this always on feature called auto support feature. Correct. That kicks in and this brings the system to a reliability score, SRS. I think this is important. I want you to explain this. I think this is a trend we're seeing certainly on the cloud side of the market. Google has pioneered this concept called site reliability engineer. Over years of practice how to make their infrastructure work great. So we know that that kind of concept of having reliability, you guys are now giving a score to each appliance. Correct. It's almost like a health detector or like credit score. Definitely. Credit score is a good analogy. So explain SRS. What's it mean for the customer and what's the impact on them? Yeah. So I don't know if you ever, like maybe utilize one of those credit scoring apps or something like that where it's monitoring your credit from three different agencies or whatever. That's kind of what we're doing. Only the data sets are coming from a much broader set of appliances, right? But we're showing you your system reliability score, credit score if you will. And then we're showing you very prescriptively the processes you can take to improve your credit score if you will or your system's health and reliability. So that might be installing a firmware patch, installing a software update, things of that nature, replacing some drives that may fail in the future. And all of those steps will then increase that. And also you see the hacking world, you know that the biggest, one of the biggest parts of security breaches is not loading a patch. Yeah. Unplanned, unforeseen things are, some sort of thing goes on, hurricane, wildfire, you never know what's going to happen. So you got to be prepared for those kinds of infrastructure chains or whatever. So I get that. So the operator's going to have a nice dashboard. I totally buy that. I want to get into the impact to the more than the business side. How does this help the business owner that's at your customer? Does this help them with planning, refresh rates, total cost of ownership? Can you just talk about the impact of how this data relates to their job because I'd be like, what's in it for me? Yeah, no, exactly. And there's really three key areas that we're addressing for our customers. I mean, the first one is around improving their operational efficiency, right? Again, reducing that alert fatigue and make it easier on the infrastructure management to do their job with less headaches, with less dashboards, lighting apps. So it's very, very prescriptive on highlighting what needs to be done and helping them through that process. The other areas around the prescriptive fault, potential fault detection and fixing those anomalies before they can actually cause a downtime event, right? Doing that in advance. So that's reducing the planned and unplanned downtime, which can be significant in terms of cost to your business. And one of the analysts states that there's 20 million a year in costs associated with downtime events like that. And that varies by industry, right? That's a dart at the board. It's a big number. It's a big number. It's a big number. You can pick your number, right? It's huge. And then the third area is really around helping our customers have better predictability into what their utilization requirements are. So the benefit there is really helping them improve their ROI on our appliances, because now they don't have to overbuy and overprovision, say capacity, because we can show them the trend data, amount of efficiency they're getting from Ddupe, and they can right size their appliances in terms of performance and capacity, and then we can warn them in advance. That's a real big thing, because what's happening there is proactive. It's very proactive. It's not reactive. It's exactly. You can solve them on the reactive side, because you can just fix it. But then the proactive side is weirdly where things break as you blow over capacity. You might want to add more. Yeah, believe it or not, those types of things have caused downtime events in our customers where they're assuming their backups are going to complete, as an example with net backup appliances, and yet they're out of capacity at the last moment, and that's a fire drill for them. So we can show them out 30, 60, 90 days what their utilization is, and then a threshold as at this point in time, you're going to have potential outage, some kind of problem. And so we recommend that you add this capacity. Before Eric, talk about the customer reaction. As you guys actually announced today, you talked to customers all the time. When you showed customers in pre-launch, what were some of the feedback you guys heard? What were the key areas? What did they hone in on? What was the key things about the predictive insights that made them get jazzed up about this? Yeah, so it's really, I would say, covers the two key areas that I already mentioned. One of them is helping prevent unplanned downtime. That's a big concern for our customers in any industry. And this is going to be able to help them overcome that kind of rear view mirror look as to what's happening in the data center and fixing a problem after it's occurred. Now they'll be able to be in advance of that and a limit or at least significantly reduce those types of issues. And then the other one is helping again in that event fatigue at the operational model. That's where we've gotten the best feedback. So I've got to ask you a hard question, which is, hey, predictive analytics has been around for a while, pretty descriptive. Why now? What's different about this opportunity? Obviously free is good, because your customers get turned on pretty quickly. They get the benefits immediately and net new customers get it. I mean, I get that piece. But what's different about you guys with this versus what might be out in the market? Yeah, I would say the key differentiation is, is that we have this very, very large universe of installed based systems that we've been gathering data on for over three years now. So the more data you have, the more data points you have, the better results you'll get from a machine learning type of environment. And we're still collecting data, both from the machines that are coming in from the telemetry data, as well as from our service personnel. So that right off the bat makes our kind of solution unique in others that may have been like out sooner in that we've developed a rich data set that is being applied to the machine learning. And hence our results out the gate are very, very good. And you're using that, you're not actually charging for it. So that is another big one. That's true too. Yeah. So let's get into the specifics on the rollout. This is a digital transformation table steak. You guys are checking it. It's a big box here. This is good. And it gives your products some capability and leverage that metadata. And that is what this data driven world's about. And certainly IOT is going to even make this even more of a table steak. On the rollout side, it's all appliances, veritas, and then software only and then you're going to go beyond veritas. Is that right? Explain that. And what does that mean? So I get the appliances. What does software only mean? And what is beyond veritas? Yeah, so just to reiterate today, it's of our appliances only, but many of our customers consume our solutions of software and they're putting it on there, bring your own server model, probably about 40% of our customers. So we believe we can add this type of capability to be able to provide insights into our software that's installed on independent third party hardware as well. Maybe some of the capabilities won't be as rich, but we're going to start building those capabilities over time and try to bring in that data and help those customers that are software only. And that's on the roadmap. That's on the roadmap. Because there's not to be able to. Okay, beyond veritas. Yeah, so obviously many of our customers today are protecting data on-prem, protecting data in the cloud or some kind of hybrid model. And we support, we don't really care whether the customers want to store their data. We're capable of protecting it and helping them achieve whatever those cloud type of initiatives are in their environment. So an obvious next step would be to, hey, how can we bring this to help you know where your data is located and how it's working in those environments? Is that backup going to be able to be restored as an example? So we're looking at future capabilities to add on to this. There's going to be huge value to our customers. This is great news. Thanks for coming in and sharing. We really appreciate it. I want to get your thoughts on some observations that we've been making. Certainly the cube coverage of veritas has been increased. Dave Vellante has been out on the road with the team. I looked at some of the new backup recovery versions looking new UI, everything's kind of a new veritas going on here. That is. What's the vibe going on in veritas? What's new about veritas for the folks watching now and saying, this is really cool. Veritas is cool and relevant right now. You guys, products are product market fit. You just got kind of a new veritas vibe going on. What's it all about? Share your thoughts. Yeah, so I think there's, you know, some people call us legacy, right? But I don't think that's necessarily a bad term, right? I mean, like when I'm gone, I hope I've left a legacy, right? That's worthwhile. And so we have that legacy, which is great because we've been adding this value for customers many, many years, right? But what's new and exciting, I think for us, is that we're able to provide solutions that are very, very simple to utilize. Very easy to accommodate whatever their requirements are, whether it's on-prem, hybrid, or in the cloud. We don't really care. So we've kind of progressed, I would say, into a very, very modern architecture for what we're doing and meeting the requirements today of what our customers are doing as well as looking forward. And this predictive insights piece, I think it's just another manifestation of how we're progressing as a company, what we can bring to bear today on current problems in the data center and also looking out in terms of, you know, where the future requirements are as well. I'm ready for those. Well, legacy is a great word, I love you thinking about that, because it's a double-edged sword. If you're a legacy and you don't do anything and you rest on your legacy, and you're just milking that until the legacy's dry. But if you look at what Microsoft's done, they're a classic vert as a legacy vendor. Office was shrink-wrapped software, Satya Nutella comes over, and now they're the darling of cloud. They've shifted their product and execution to be what customers want, which is cloud. Now they've got Office 365, Azure's been repurposed. There's some stuff that's still working on it, but clearly cleared the runway. And, you know, Oracle, not so much, Microsoft has. So this is a veritas kind of vibe that's going on. Similarly, to Microsoft, you guys are looking at, hey, we got install base, we're going to use that and leverage the assets of that install base, that legacy, harness it and make it part of the digital transformation. Is that kind of that vibe? Yeah, no, exactly. And I think Microsoft's a great example. I mean, we're in tight partnership with Azure, as a matter of fact. I just came from one of our Vision Solutions days where a gentleman from Azure shared the stage with us and talking about our partnerships and all that. So I mean, great example, right? But we're bringing those capabilities into the cloud era, if you will. We have solutions that run natively in cloud help that environment. Making the transition, a digital transformation. Veritas, the new Veritas, they got the solutions that are cloud enabled, using data for the benefit of the customer, not just trying to bolt it on and make more money. They're actually bringing value to the install base and changing the game up. Eric Seedman here inside theCUBE, Director of Solutions Marketing and Veritas, part of theCUBE conversation, part of their news coverage of their predictive insights. I'm John Furrier here in the Palo Alto Studios. Thanks for watching.