 from Tavern on the Green in Central Park, New York. It's theCUBE, covering Veritas Vision Solution Day. Brought to you by Veritas. Welcome back to New York City, everybody. We're in the heart of Central Park at the Tavern on the Green, beautiful location here. A lot of customers coming in to see and hear Veritas Solution Days. We talked to Scott Gennaro earlier about sort of why these Solution Days, very intimate customer events around the world. David Noy is here. He's the Vice President of Software Defined Storage and Appliances at Veritas. David, thanks for coming on. Well, thanks for having me. You're very welcome. So, wait, Appliances? I thought you guys were a software company. What's going on? We are a software company and we have been a software company for a very long time. We will continue to be a software company for a very long time. But what we find is that, customers oftentimes, they want to deploy software, but then they find that there's a lot of additional challenges that come with that. There's the maintenance of the actual server infrastructure. There's patching of the operating system. There's vulnerabilities that show up. Those additional operational costs sometimes outweigh the benefits of just buying a purpose-built appliance. And those purpose-built appliances can sometimes have workflows built into them that just make them so easy to use that one person could potentially operate petabytes of an appliance versus a whole army of people trying to maintain hundreds or thousands of individual servers. So, you put out a stat this morning which I wasn't aware of. You guys have more than half the market, I think it was an IDC stat, maybe it was Gartner, more than half the market for integrated purpose-built backup appliances. Is that right? That's right. So, for backup appliances, purpose-built backup appliances that actually host the backup software, we have more than 50% market share. People have that much trust in the appliances that we build and find that simplicity so compelling that they want to buy it in that form factor from us. You know, about a decade ago, I wrote a piece in the early days of Wikibon talking about services-oriented storage. And when we think about software-defined storage, what you described today was actually sets of granular services that I can invoke when I need them or not if I don't need them. Very cloud-like. I mean, I could replace the S in software-defined with S in services, and that's your kind of philosophy and approach, isn't it? It is, in fact, what we find is that people want data services on top of that data. When you're protecting enterprise data, and you're protecting exabytes of enterprise data the way the Veritas does, having it just sit there and do nothing is kind of wasteful to a large extent, unless you're just waiting for a disaster to occur or data corruption or something like that. If we can support to think about what are the governance capabilities, lineage, audit, all of the different things that we could potentially build as services that then can be downloaded onto that purpose-built backup appliance, those all become added value to the customer. But what you described was not just another, not just dropping in another stovepipe appliance. You talked about having visibility across the entire portfolio. You really stressed that a lot. You said several times you can't get this from any other backup vendor or any other vendor, really, talk about that a little bit. Well, what's interesting is that, look, from the moment that data is actually born from a primary application, and then it's protected. It's protected into a backup solution, and then it's probably put into some sort of storage solution, maybe a deduplication storage solution, then it's moved to an even cheaper tier and eventually off to the cloud or somewhere else. Each of those are disparate. If we can actually build a connector framework that can actually extract that information and bring it all together so that we can start to make assertions about, hey, how did this data flow? How did it originate? What kind of information do I have? Do I even need it anymore? After seven years, should I purge it or should I delete it? Is it even a risk to my organization to keep it? You can only do that when you can make those associations across the life cycle of that data, and so we track the data through its entire life cycle, and that's only through the integration of all of that product portfolio, and that's something that you're not going to see with the small point solutions that are being built by startups, and it's even very rare to see in some of the larger companies that build these solutions. You know, Dave, I'm glad you mentioned that about getting rid of data, because so often today in the news media and you hear in vendor presentations, people talk about keeping data forever. That's dangerous in a lot of cases. A lot of general counsels out there don't want to keep data forever. There's data that you want to delete if in fact you can because of the compliance risks that it brings to your company. You don't want to keep work in process or some rogue email that floats around the organization. Get rid of that. Keep what you have to and get rid of the rest, right? And then the problem is if you don't know what you have and also you don't know how many places that that data is propagated, how can you possibly delete it all? We've helped customers in some cases, and I'm not going to mention who they are, but we've helped them delete up to 50% of their data after it's aged out. And I've talked to banks before and I've asked them like, hey, after seven years, what do you do with your data? They said, well, we just keep it because we don't know what it was originated for. We don't even know what's in it and therefore it's too risky for us to go and delete, but at the same time, to your point, it may be even too risky to keep. In some cases, it's actually a liability to keep that data. And what's the technology enabler there? Is that your catalog, your sort of copy data management software? So it's a combination of things. The catalog is what helps us understand what we have and where it is and how it's actually moved through that life cycle. And then we have a component called the Veritas Information Classifier and that component allows us to crack open the data and actually determine what's inside, whether it's personally identifiable information, social security numbers. There's a number of different patterns we can look for actually document types and we can actually tag that data and say, hey, this data has information that's pertains to a specific individual. So for example, if I'm following GDPR rules, I can now find out all the data where it's propagated specific to an individual who said now, I want all my stuff deleted. And that's a very powerful technique. So it's not just the data, it's the metadata associated with that data as well. That's, I think, is a unique capability in terms of being integrated into a solution. And so that's cool. I also want to talk about Acme Financial Services, this artificial company or a real company, but anonymized company that you talked about. Moving to your system, your appliance based system, they were able to reduce TCO by 40%. Shave two thirds of their hardware infrastructure away. Come back to that, as I have sort of a tongue-in-cheek there. Get rid of tape, at least where possible. No new tape, I think is what you said. That's right. And then save $20 million a year in reduced downtime costs. So my tongue-in-cheek is, everybody remembers the no hardware agenda of signs, you know, I live in Massachusetts. So we used to see those right next to the EMC facilities. And you're only a hardware agenda, it seems, with your appliance, is to get rid of hardware. That's right, it's exactly right. Look, we are actually putting out technology that allows you to take 10 heads or 10 servers and consolidate it down to two or three to make the total cost of ownership for your product less because at the end of the day, it's in our benefit, right? We're a software vendor. We want to maintain ourselves as a software vendor. We want to take hardware out of the equation to the extent that's possible, but we don't want to do it at the expense of simplicity. And so striking that balance is what's most important. And you also have talked about a little, you showed a little leg, if you will, on a roadmap. That's right. One of the things that struck me, and it's sort of there today, but even more in the future, is the ability to scale, compute, and storage independently in more granular chunks. Explain what that is and why that's important to customers. Well, you know, if you think about it, the way that these integrated backup appliances work or even just disk-based backup appliances, they just grow and grow and grow to a certain capacity, they scale up and scale up. And at some point, the performance just starts to tank and taper off. So what if you could actually grow them almost in a node-based architecture? Think about its compute and storage that you grow together. And as you add more compute, you add more storage. And so that means that I can do more microservices or I can provide better deduplication, but my deduplication doesn't slow down when I go from two petabyte to four petabyte because my compute has actually grown in lockstep with my storage. You made a big deal about eliminating tape where possible and you also, and I want to push at this a little bit, talked about the economics of your solution relative to tape. I was somewhat surprised because conventional wisdom would say tape is pennies on the dollar compared to disk-based solutions. How is it that you're able to make that claim? Well, there's a couple of different things that come to play. Number one is that, again, through the cloud catalyst capability of NetBackup, we can actually keep data deduplicated before we send it to our disk-based solution, which means that it stays, in some cases, 50 to one deduplicated. And you're not necessarily going to get that capability on tape. So you don't have to rehydrate? Don't have to rehydrate. So if you're talking about pennies, well, multiply that by 50 because if your data deduplicates that much, that's the kind of thing you're talking about. The second part is the operational cost of actually maintaining tape. Now, if I'm keeping data for seven years, 30 years, the lifetime of a patient, that tape infrastructure ages out and I'm doing tape migrations all the time. Those are not cheap. And sometimes the tape infrastructure is not even available anymore. Yeah, the compatibility is not there. That's right. The other thing is, well, the other thing is the network cost, right? If you're going to be pushing stuff over the network, it can be a bigger network. And you're pushing bigger things over the network, you have more network infrastructure, just for the purposes of moving data from one tier to another tier, it's wasteful. If you talk about the Flex Appliance, what I took away from that is it allows for services-oriented deployment, fast migration, it allows you to test out new services to see whether or not you like it. What is the customer have to do to exploit that capability? Today, the customer would buy our high-end backup appliance, which is the 5340. They would buy the Flex software, which is a software package that allows them to basically augment that appliance so that it can actually maintain that catalog and then quickly deploy them, those services. As I showed in the demo, in three minutes or less, we can deploy a service from the service catalog. In the future, you should expect that we will begin to build that into all of our appliances. That's just the way of doing things. It becomes a service-oriented architecture, and that catalog is just going to be a natural way of us operating. Okay, I want to also ask you about another capability that you discussed, which was your ability to look across the portfolio and identify predictive failures. So, everybody talks about machine intelligence being used in that use case, IOT, you hear about that a lot. What are you guys doing and what's unique? Well, you know, in some cases, what we're doing is not completely unique. I mean, there's some companies that have done this pretty well. They've done it for their own point solutions. I think where it gets interesting is when you say, look, we're not just building a point solution. We have a number of different products, again, for the entire lifecycle of data from the moment it's born. And if I can integrate all of the telemetry that I get from those different products, I can now start to get predictive about things that might have happened not just at one stage within one product, but might happen down the road. When I go to move it into my long-term retention, is my long-term retention ready for it? Is it going to impact the performance of my long-term retention solution? And so therefore, should I think about scaling on my long-term retention solution, independent of, you know, ahead of the actual growth of my purpose-built backup appliance, right? So it's that portfolio view that makes it so powerful. Right, so okay, two things, actually. The portfolio view and also the full lifecycle view as well, which is something you've been hitting on, not just a point product. All right, David, I know you're jamming a lot of customer conversations here in New York, so I got to let you go, but thanks so much for stopping by theCUBE. Appreciate it. Hey, my pleasure. I really appreciate your time, thanks. Okay, you're welcome. All right, keep it right there, everybody. You're watching theCUBE live from Veritas Solution Days in New York City, right in the heart of Central Park. We'll be right back after this short break. Thank you.