(up-tempo electronic music) >> Announcer: From Gillette Stadium in Foxborough, Massachusetts, it's theCUBE. Covering VTUG Winter Warmer 2018, presented by siliconANGLE. (electronic music) >> Hi, I'm Stu Miniman, and this is theCUBE's coverage of VTUG Winter Warmer 2018. Happy to welcome to the program first-time guest Kevin Kotecki, who's the Vice President of Sales at Igneous Systems, Kevin, thanks for joining us. >> Yeah, thanks for having me. >> Alright, so we've been talking to Igneous since really the early days, we've known some of the founders of the team. Before we get into it, tell us a little bit about your background, how long you've been with Igneous, and kind of your day-to-day activities there. >> Yeah, so I've been with Igneous for three years now, so very early stage. Came in pre-product, pre-revenue, been working with our earliest stage prospective customers and our earliest customers from day one. So, I've had the pleasure over the last few months of building out the Sales Organization more broadly, the Marketing Organization growing as well, as we have achieved that product/market fit that every start-up's looking for, and going out and solving those problems at scale across the country and having the feet on the street to help with that. >> Yeah, you know, it's interesting, we talk a lot on this program about these user groups. They're great for the users to get education; it's also a great place for hiring. I've helped lots of friends at this specific event, talked to a number of companies that are like, Oh yeah, we're hiring SEs. Everybody is hiring SEs. >> Yes, indeed. >> And I'm sure you're probably doing some interviews >> We are, yeah. While you're here. But, I love to watch the maturing of start-ups. A number of companies I met here at the first time, Igneous has been supportive of this event for a number of years. What brings Igneous, what are some of the key objectives coming to an event like this? >> Yeah, so with VTUG's Winter Warmer, it's an opportunity to see customers first and foremost, and interact with the local Boston companies that are here, that fit the profile and have the problems that we solve. But it's also an opportunity to see our partners and to have visibility in the community and show that support of the local business community as well. >> Alright, so let's talk about Igneous. At the show, it's the changing dynamics of what's happening in the world of virtualization, what's happening in cloud. Igneous sits in those spaces, and how does it differentiate itself from this massive market of cloud and storage and everything that's going out there? >> Yeah, good question. At a high level, what we do is we help organizations manage their unstructured data wherever it may be, when that unstructured data is at scale and begins to break traditional paradigms for doing so. And, the specific problems that we solve start with data protection, day one. It's a great way to help customers get insight into their full suite of unstructured file data and build an index around that that's extensible and powers their other services like archive, like end-user search and restore, and also feeds into our policy engine that helps customers tier data to the public cloud, and specifically to cost-appropriate cloud products, like Amazon Glacier, like Azure Archive. So that intersection that we sit in between cloud and storage and all of that is really around delivering the entire experience as a service and solving, day one, very difficult data protection problems. >> When talking about things like scale, can you quantify for us what's kind of the low bar for your customers? Where does it start and how big is big? >> For us, a minimum starting point would be a few hundred terabytes of file data. >> Okay, which is not that big, right? >> Yeah, in today's world, not so much, but it certainly does bring clarity to the type of customers that we can help. And really, we're not focused on on structured data, right? We believe that there are a lot of great solutions out there for protecting databases and a virtualized infrastructure, and that's not what we do. We partner with those folks. As far as how big is big, our largest customers have approximately 100 petabytes of file data, and so approaching kind of the top end of what customers have still on-premise today. >> Great. Sounds like you can start with, I mean, most customers are going to have that kind of data. Do you find maybe it's because it's unstructured, there's plenty of companies that might not fit in your bucket? And then, you've got plenty of headroom for scale, is what I'm hearing. >> Correct, and architecturally that headroom is built in day one. I think the focus from a customer standpoint around unstructured data is, if we quantify and qualify what that data is and where it comes from, it's really machine-generated data at scale, it's application-generated data at scale, and so the types of industries where we're really doing well are, call it, electronic design and automation, whether that's in the semiconductor space or in engineering use cases, it's in media and entertainment, a traditional place that has large-scale file data. It's in legal services, it's in proprietary trading, it's in all the places where that data exits. But then, it's also in bioinformatics, where genome sequencers and next-generation 3D microscopes are producing those kinds of data sets. And so, not every organization is in that boat today, right, and so we're really working at machine scales as opposed to human scale data creation. >> Yeah, and it really goes back. I think of when object storage was first discussed, you described it really well, people data versus machine data. All the industries that you went through, there's just the growth portfolio that I have to do things, and how do I take that from being, Oh my gosh, this is a challenge, to How do I make an opportunity, how do I leverage that data, how do I use it? >> It's about monetizing the data, right, and if it's just simply data that you're storing, then there's less incentive to invest in platforms that allow the extensibility of that data, to comb through it and be integrated into other applications, other use cases that can be monetized, right. And if we come back to some of the core problems that we really solve and get us to demonstrate the value of the product and of the approach to customers, it does indeed start with data protection, day one. And so, many of our customers today are protecting their data in a traditional paradigm, whether that be NDMP to tape or just working within backup windows where the goal as an IT Organization is to not impact your end users, and their ability to create the type of data that they can then monetize. So whether that's an engineering organization that's writing code or creating designs, whatever it may be, the goal is to be behind the scenes. And so when the scale of data creation, when the density of the file data that is being created creates challenges for those traditional architectures, whether that be around metadata management or some other challenge of scale, that's where we come in and we shine. And so we start day one focusing on customers' hardest problems as it relates to file data at scale and protecting it. And then, once that data's on our system, the power of that platform, the power of the microservices-driven architecture that we've spoken about here on past interviews, the power of the extensible, you know, compute context, if you will, that can then integrate into other applications and be leveraged for also very tangible things, like archive and reducing your spend on primary storage, and also integrating with the cloud. >> Kevin, one of the things that we've looked at is inside an organization, a lot of times, this paradigm shift also goes with, Organizationally, who owns this? When I think about a lot of the applications, it would be application owner that has the problem, but isn't connected necessarily with the storage admin or virtualization admin or cloud architect. How does Igneous, how do you get involved there and how do you help companies work through some of those organizational dynamics? So that's been one of the most satisfying elements over the last year or so of successfully solving customer problems, has been actually seeing the closer marriage of those three entities within organizations. So again, the application owner, the backup or disaster recovery owner, and the storage owner. And so, the most tangible example I can give is, in a world where backups were impacting end users, in this case an engineering organization that would experience latency in their application and then the work they were trying to do, traditionally their first order, or I guess their first solution was to contact the backup team and say, Hey, are you running a backup, and if so, kill it because you're impacting my ability to do my job. And then the storage folks of course were experiencing pain around trying to manage the scale of the infrastructure to support that engineering organization. And so in our approach, we don't impact the end users in any way, and we provide continuous and automated protection, which allows those data protection team members to focus on other things that are higher-order priorities than sitting there managing, actively managing, a backup window or a backup itself. That's something software does for them now, and the end users no longer complain, and therefore their daily interaction with IT as it relates to data protection is less colored by the IT impacting their ability to do their job through the data protection approaches that they're using today. >> When it comes to some high-level data protection secondary storage, there's a lot of players out there, and many of them, it's like, Data Domain? Very different from a rubric or cohesity. Where does Igneous fit in kind of the spectrum of what's going on? What are some of the companies that you're running up against that make sense for you, as opposed to which ones that we're just in the wrong conversation here? >> So the clear line of delineation between us and most of the other new entrants and traditional entrants in the field is that we're only focused on file data. We believe that the growth of unstructured data is unbounded and will continue to be unbounded and will break traditional architectural paradigms. And so that's the problem that we're specifically focused on, is how to help customers manage and protect that. Therefore, we're not focused on protecting structured data, databases, and VMs; that's not our point of entry. What that does do within that space is create a lot of opportunities for partnership, where our architectural approach is unique and is something that is very difficult to pull off if your day-one focus is on protecting virtual machines. It's not easy for you step up to the plate and protect two, three petabytes of file data, right? And so that's an opportunity for best-to-breed solutions where the customer can have the best data protection and two vendors in place for those kinds of use cases. >> Okay, Kevin I want to give you the final word. Maybe do you have a customer story? You talked a little bit about the organizational piece, but what's a customer story that you could relate that people might find interesting? >> Being in Boston, and having Boston be such a hotbed of bioinformatics, one of our recent customers is leveraging new 3D microscope technology to do very important research on the human body and disease and things of that nature, and that produces petabyte-scale data, even once it's been processed. And so what we're helping them do is both protect that and minimize their cost of implementing primary storage, minimize their cost around data protection, and not have to implement, or put IT folks in play, to manage that whole process. It's all very automated in this deployment. But then also, even more importantly, is from a collaborative standpoint they leverage us to tier to the cloud to then move that data and then share that data with their other collaborating investigators, and then also meet grant requirements of publishing their findings in a publicly available, downloadable format. And so, that end-to-end ability to provide a solution for customers that have unique challenges in creating large-scale file data has been really satisfying. >> Well Kevin Kotecki, appreciate all the updates. As we've been saying for the last couple years, data is at the center of it, and needs change from that kind of challenges around data to huge opportunities out there. Congrats on all the success. >> Thanks you, thank you very much, appreciate it. >> Lots more coverage here at the VTUG 2018. I'm Stu Miniman. You're watching theCUBE. (up-tempo electronic music)

>> Announcer: Live from Las Vegas, it's The Cube. Covering AWS re:Invent, 2017. Presented by AWS, Intel, and our ecosystem of partners. >> Welcome back to Las Vegas. We are live here on The Cube continuing our coverage of re:Invent. The AWS, the big tent. As we were just talking about with our guest, Justin Moore and John Walls here. Your hosts here on The Cube and we're joined by Kiran Bhageshpur, who's the CEO of Igneous Systems and Kiran, thanks for being with us here on the Cube. Good to see you. >> Great to be here. >> Now we were talking about, you know, this is the big tent now. Didn't used to be that way, right? >> Nope, nope. >> It wasn't that long ago this was, I wouldn't say a specialty show, but you said this has certainly taken on a very different vibe, a very different feel. I mean, explain that a little bit before we get into Igneous and what you're doing here. >> Absolutely. I was first here in 2012, I believe it was the first year they had AWS at re:Invent and it was a very different feel, much smaller, maybe about 6,000 or so people. Mostly engineers, hardcore engineers who were discovering this new cool set of toys, if you will, or tools that was quite revolutionary and niche at that time. Fast forward now. It's much more of a mainstream show. It's much more corporate IT, lots and lots of large enterprises are present out here. There still is a lot of developers, but it's more the devops, more people who are operationalizing this rather than building on it for the very first time. So big change from early stage to very mainstream right now. >> And Justin, you made a comment. I mean, to the extent of a jacket, I've got a suit and tie, a jacket. We've all been to shows where maybe the wardrobe was maybe a little different, but this is illustrative of, again, of the maturation of the marketplace and expansion of the marketplace. >> Yeah, you go to some of the developer conferences and you see a lot more people with spiked purple hair and then utilikilts. I've yet to see a single utilikilt here at the show so it does feel, unlike at previous years where there's been, again, a lot more engineers and people are still here in hoodies and casual clothes, but there are a lot more suits. There's clearly a lot more money here and it's become a little more corporate. It'd be interesting to see how it transitions over the next couple of years whether Amazon or AWS is able to maintain that kind of developer vibe as all of these other companies come in and start to see actually, this is a pretty robust and mature ecosystem now. >> Yeah. >> Yeah. And obviously, the expansion reflects that. You're here exhibiting for the first time. >> Yes we are. >> Your booth back at K37 if you're here at the show. Kudos to Igneous. Let's talk a little bit about what you do and why are you here? Who are you trying to talk to this weekend and why does this week matter? >> That's great. So what we do, Igneous is an early stage company. We have launched our company a year ago. We have a bunch of customers right now sort of growing very nicely at this stage and what we do is enable businesses, enterprises with lots and lots of file data on premises as well as in the public cloud to better manage and have a handle on this. So our customers tend to be businesses with sort of literally billions of files, hundreds of petabyte or dozens of petabytes spread across a lot of systems traditional, legacy that hook, attach to a system on premises and what they are seeing in their growth is they're going from one data center to multiple data centers within their own infrastructure and now to multiple clouds and as this core asset, data continues to grow. They look to folks like us to help manage that better. So the very first thing we do is we enable them to back up and protect all this data on premises into public clouds like AWS so we literally have scalable solutions which go into their data center, talk to all of their filers as they're called, interrogate all of that data, and create a copy of that into AWS S30 glacier. >> Yeah. There's a lot of companies who are struggling with the idea. Two things really. One is being able to manage data everywhere because data has gravity as people like to say, but also this multi-cloud idea and being able to manage my data in multiple physical locations. Some of it will be on my own site. Some of it will be in Collo. Some of it will be in one or as you say multiple clouds. That really hybrid IT way of things. What are you seeing as the driver behind that need to have this data in multiple locations? >> Yeah, that's a great question. For the things that we see is, look, things have remained on premises. It's not gone away and things continue to grow on premises and Amazon recognizes that. That's why you see starting last year into this year a lot more push into hybrid clouds, if you will. You saw that with the big partnership with Vmware and so on. So that's continuing to grow, but in the same time, they're having new applications being born in the cloud or leveraging the cloud. So one thing which is very common for a lot of our customers is they have infrastructure on premises which is already paid for and continues to grow, but they want to leverage the public clouds, AWS, for its elasticity and its agility to be able to burst into it and use it as they see fit. Now to do that, you require agility of applications and data between on premises and the public clouds and say AWS. So that's kind of where, you know, we come in to go help them in that and the other thing we're also seeing is customers are not in a single cloud. Even if they started in one place, they're starting to exist in multiple different locations. Good example will be in, you know, most of our customers tell us that, say, a Google cloud has the advantage for things like AI and machine learning whereas Amazon has the more mature infrastructure. So they might quite have a lot of infrastructure and data on premises as well as on Amazon, but they might be running a bunch of new applications which are leveraging the machine-learning APIs and Google Cloud. But then how do you get the data from on premises Amazon cloud into Google Cloud, use it but not leave it around and triple pay for it all around so that's really the management challenge. >> Yeah so you mentioned a particular use case there that happened to use Google. So AI and machine learning is something and I'm hearing that in talking to customers myself that they like to use different cloud for different reasons. So what are some of the workloads that you're seeing from customers who are needing to put their data not just on site, but they say, you know what, I want to burst into the cloud, I want to use some of that elasticity that cloud is so great at. What are some of the workloads that you're seeing them use your product for? >> Yeah, I'll give you a great example. Let's take the word of the movie world, right? So lots of it is all digital right now. The data is created and you're gonna go create heavily CGI or computer generated effects using lots and lots of computer cores. What you come to is at the end of the movie, there's a crunch time where they need way more compute than they have available within their data centers. In fact, in the past, there used to be a vibrant side business where little boutique companies would rent you servers and they would literally carve that into your data center for six weeks and take it away again so now that's gone and you'd rather use the public cloud, you use Amazon and EC2 instances for that workload. That's a good example which everybody can relate to. Hey, it's crunch time, movie's coming up for release. I have a lot more work to do, but that pattern exists in pretty much every industry whether it's drug discovery or electronic design. Everywhere, there is a need to grow burst beyond what you have available and that kind of drives the adoption for workflows which already exist on premise to also adopt a cloud. >> Yeah. >> You got it. >> What manageability. I mean, talking about multi-cloud. >> Kiran: Yeah. >> And obviously as you parcel out your assets, you decide what data's gonna reside in what environment managing all that and then managing the cost of all that. I mean how do you keep up corale on that and also help your clients get a handle on where their data's going, 'cause yeah. I don't know, right? >> So that's what we exist to do which is help customers manage this data asset that they have across multiple locations no matter where it lives. The first thing we do in our journey with our customer is just back that stuff up which is all on premises into the cloud so it gets a copy of the dat into the public cloud. Now that enables workflows like being able to use the cloud for disaster recovery or use the clouds for burst computing very well. But it's just beyond that. It's also how do you get the data, where it lives, which could be on premise, on a T01 filer to where it ends to be. Perhaps the public cloud for a back-up deal or a burst-use case or perhaps into a separate cloud for using machine learning and when you do this, how do you ensure you have one copy, one protected copy of the data, not three or four every place? In fact, if you look at the world today on premises, already customers will tell us they have hundreds of systems that it's not infrequent that hey, they have infrastructure say in Santa Clara as well as Israel and it's a same copy which exists in both places because they have no way of globally looking at this in one single way. >> That's kind of what we do is hey, what are your data assets, where do they live, how do we ensure you have one copy of it or n copies as you desire but not a proliferation of that dataset, three how do we get the data from where it lives to where it's needed in a programatic, systematic way that your end user can sort of you know, help themselves too rather than requiring an IT trouble ticket and somebody going through a manual process. So those are sort of good sets of early things we are helping customers out with. The other thing that goes into here and this is where the cloud comes in again is we had targeted customers who are looking at literally billions, tens of billions of files, hundreds of petabytes, tens of petabytes to 100 of petabytes of data spread across many locations and many hundreds of systems. How do you get your hand, your head around that? It's beyond human scale and it's only possible with software and sort of machine learning if you want to use the buzzword and that's the sort of next place where you come in and provide a human comprehensible structure for the sort of data which continues to grow and it's important because this is core assets for businesses today. >> Yeah we were discussing this earlier, both of us, actually. It's that idea of automation because humans don't scale. >> Yeah. >> So when you have these billions of files as you're talking about, that's just not trackable for humans to deal with. So what are some of the automation and autonomous systems capabilities that Igneous has? >> So the first thing we do is go ahead and ensure your automatically and at scale, being able to discover all of that data, right? So think of, you know, if you look in the consumer world, really what the web is goes and crawls every website and indexes all of the data. Well we do that except within the enterprise for the unstructured file data, which happens to live on a net app filer or a Dell cluster or maybe it's living in AWS inside S3 where we go crawl all over that, index, all of that and give you a view into that. That's the first level, simple way of doing that. But then the next level beyond that is if you can give a level of structure on that because it's not useful to just find it. You wanna know what you have or where you have it, how it's changing, who is accessing it, what applications are accessing your data? What applications are modifying your data? Today, that is an extremely manual process within businesses. >> Yeah. In order to make sense of that, again, you're trying to appeal to developers. What APIs and sort of programmatic aspect do you have for that rather than having to employ 1,900 humans who would all have to sit there and drive around with, going through interfaces? >> So since our customers tend to be sort of more on the business side of IT today who are trying to go understand about this data, the interfaces we provide them is clearly the higher level abstraction of what the data looks like of how they want to interact with that, but everything you do in the modern world is API enabled and the vision is clearly to go expose all of this through API such that customers, developers within their organization can go consume it. >> So before we let you go, I want to talk about your presence here, the decision to exhibit. It's not a light one, I know that. At the end of the day, when you walk out of here on Thursday, what do you want to accomplish and I guess from the, in terms of the kinds of audience that you're hoping to be exposed to, who would that be? >> So the customers, the prospects we talk to are typically businesses, enterprises with lots and lots of unstructured data so people in the media world, in the design world, any form of design that is electronic and automated to. You know, geospatial imagining. All of these folks and they are all present here this year. This is the show to be, you know. In the past, it used to be Microsoft PDC, it was RealWorld, it was Oracle World. Today it is AWS re:Invent and they're all here and for us, it's success if we walk out of this being exposed to a whole bunch of people. We as a smaller organization could not have had immediate access to without coming to this show and that's what I think we get out of here. >> Well, good luck on the next three days. It sounds like you're off to a great start in the right place at the right time. >> Yes, indeed. >> And we wish you all the best down the road. >> Thank you. >> Kiran thank you for being here. >> Thank you very much. >> Live on the Cube, you're watching us here at re:Invent where it's AWS's big show here in Las Vegas back with more live coverage in just a moment. (energetic music)

>> Announcer: Live from Gillette Stadium in Foxboro, Massachusetts, it's theCUBE, covering #VTUG's New England Winner Warmer 2017. Now, your host, Stu Miniman. >> And we're back, with SiliconANGLE Media's presentation of theCUBE, we're the worldwide leader in enterprise tech coverage, happy to welcome back to the program, Steve Pao, who's the CMO of Igneous Systems, Steve flew out from Seattle here to, welcome to the home of the New England Patriots. >> Oh my gosh. Number 12, number 12! >> The 12 man representing here, you've got, I have to say, I almost canceled my season tickets when Pete Carroll was our coach, so, luckily he's worked out better for you than he did for us. My wife's a Brown fan, she says the same thing about Bill Belichick. So, it's the coaching fraternity is kind of like the tech world, it's a small group, you all kind of get to know each other and move around, so, thanks for joining us. >> Yes, well thanks for having me! >> Alright, so Steve, we've been talking to you guys since you were coming out of Stealth, why don't you give our audience, what's the update on Igneous? >> Okay, well for those of you who don't know us, what Igneous really does is we offer an onsite private cloud storage service, and that's our first offering, it's part of our greater mission of providing true cloud for local data, and what we basically offer today is an unstructured data store that's completely delivered as a service, we take our own equipment, we install it, we monitor it, we manage it, we even refresh it when necessary, and all the customer has to do is really subscribe, and that's it. It's all pay-as-you-go, and it's all zero touch for the customer. We launched back in October, as you recall, and one of the things that I think that it's been really great since launching is that we've really started to see how customers that didn't know us are actually really evaluating, really, I think, the convergence of two trends, one is there's this data growth, data trend that goes on, and pretty much everybody we talk to, citing data growth rates on the order of doubling every three years, where IT budgets are growing less than 5% a year, so there's this mismatch where, basically everybody's hitting this juncture that what they used to do can't work because the data's growing faster than the budget. And at the same time, there's this data growth that's actually happening, and the data growth is not from relational databases and structured data, but rather, a lot of new applications that are logging sensor data that are supporting machine learning, AI, really, it's machine-generated data being analyzed by machines, with humans really just training the AI and the machine learning. >> Yes, Steve, I want to unpack that a little bit, let's talk it, because many of us that watch storage, it's been like, well the storage industry, it needs to change, it's not about selling boxes, it's not about capacity, and even on unstructured data, it was kind of like, okay well, what's creating data and what's actually valuable? How much is it just, do I stick it on a cheap tier, what do I actually do with it, what's interesting you guys do, some of those use cases, throughout machine learning, machine data, things like sensors, every time I hear that word, that IoT buzzword kind of pops into our head, but maybe you could talk to some of those, what's bringing customers, what's that driving challenge that they have, that you're helping to solve, that's different from the way storage has been done for many years? >> Yeah, I think, that's a great question, and I think that there's just been a real transition, and I think the transition has been largely created by the kinds of data that we want to manage and that we want to curate, and as we're seeing these sort of large unstructured data sets, it starts with the data, so as an example, you take equipment that used to exist in the past, like let's say in scientific computing. You used to have flow cytometers, which were just time-series data, and then what's now happened is is associate with ever flow cytometers, now a real-time video feed. When you look at the old world of microscopy, what you used to do is you used to flash freeze a sample, and basically take a picture of it, and now what you can do with lattice light-sheet microscopy is you can actually look at cells in vivo, while they're alive, and you can, I've personally gotten to watch a T cell move through a collagen matrix, and that's all microscopy, but generating orders of magnitude more data. That is, we're looking at these very, very different data sets, we're looking at very, very different kinds of computing, and what that requires is very, very different kind of infrastructure. And so, the infrastructure has just had to get a lot more intelligent, and the architecture has had to get a lot different, and what we've noticed is is that, that a lot of the patterns that are actually being built in the public cloud as they've taken kind of a fresh look at the computing models, have really become appropriate for this new kind of computing, and we don't see that on the premises, and that's really what we set out to go do. >> Yeah, it's interesting, it's probably the wrong term, but it sounds like we're describing kind of object storage 2.0. 1.0, I remember this healthcare use cases, everybody, when I was doing radiology, when you're doing certain healthcare and sciences, I need metadata, I need to understand that, but now there's just orders of magnitude more data, and technologies are making, it's denser, prices have come down, so the idea has been around for a little bit while, but it sounds like the technology's matured to allow kind of an explosion-- >> Well, and it's just a computing model, it's like one of these things where we're really, because of the emergence of microservices, one of the things that we've seen is applications want a restful interaction with the storage layer, and so, so it turns out that that tends to be very, very perfect for a cloud-like implementation where you can actually implement high volume, unstructured data really, really well via a restful API, where in the old world of POSIX semantics and that kind of transactional model, you just lost scalability. Either you had a lot of proprietary hardware, with that VRAM, you had proprietary interconnects data with things like InfiniBand, and nowadays, being able to loosely couple distributed systems is really the name of the game, and that's ultimately what we aim to build at Igneous, and that's all the technology, in terms of our commercial offering, the customer doesn't care what's behind it, but fundamentally, what you're looking for is the scalability and resilience that the cloud offers by doing that on premises. >> Yeah, so Steve, we had a really interesting crowd chat about a month or so ago talking about hybrid cloud, and the thing I've been saying for the last, probably year, is, as customers try to figure out what goes where in the cloud environment, you know, I've got SaaS, I've got public out of, I've got my private cloud, it's follow the data and follow the applications. In the cloud, things like mobile and even some video streaming, I think we understand how to do that, but why does on-premises make sense for your customers, your workloads, and your solution? >> Yeah, absolutely, and so, first, a little bit on hybrid cloud, there are kind of two different definitions of hybrid cloud, one is kind of the AWS VMWare scheme where what you're really looking to do is run your old stuff that you were running on-prem, in the public cloud, and you call that hybrid. But there's another way to look at it, which is to say, hey, let's take a look at the computing patterns that are being run in the public cloud, how do I bring that down to the premises? And the reason that you might want to do that is, it's really twofold, one is the gravity of the data, so it might just be that the datasets are too big to move back and forth over very thin internet pipes, and so you want to actually keep the data close to its source. The other is something that we've seen, which is really more of a preference, which is that while I think that cloud technologies actually have a lot of capability for security, there are a lot more hoops for folks to run through to ensure that they're compliant with their own internal policies, and where they've already set out a set of policies for how they run the stuff behind the firewall, sometimes it's just simpler for them to actually keep all of the data on the premises, and not actually have to worry about some of the issues in tracking, and compliance issues associated with how you move the data around. >> Yeah. One of the things we've heard from users is when they use public cloud, one of the things they really like is, sometimes the CFO's not fully onboard, but buying things as a service, so, they want to understand predictability, but they want to buy it as a service, understand, how does your solution fit into that kind of paradigm? >> That's great, I think our solution fits into both trends really, really well, because what we're really offering, we talked a little bit about technology, but really fundamentally, we're offering a service, and so when Igneous goes to a customer, our interaction is as a service. Customers interact with our service via APIs, and they get a bill for a subscription, and so it's an as-a-service model, you don't buy hardware, you don't install software, you don't have systems to manage. At the same time, there is a predictability that's a little bit of the downside of the public cloud, because there's a fee, generally, to access your data at a storage, and often, when people don't actually understand their data access and their data movement patterns, the costs of running applications in public cloud become quite unpredictable, and you actually don't run into that unpredictability with a solution like Igneous, because our data is on your local area network, and we don't charge you to access the data that's on your own network. >> So, I've come to an event like this, if I'm thinking about my storage today, the conversation in the marketplace has been, well, the new choices out there is, there's, the HCI, the hyper-convergence infrastructure, and there's flash, the AFA devices out there. And of course, even the lines between those are blurring, because I can have an all-flash configuration of hyper-converged, and some of the all-flasher a things are getting converged and put into more things, how do you help customers as the, what's the bullet point as to, well, this is for this kind of application, this is for this solution, and hey, there's this whole new category that you need to be thinking about. >> Yeah, I think that's perfect, and I think the real trick here is is that there's a difference between your hot tier and your flash tier, and your capacity tier, and fundamentally, the flash tier is really good when Time To First Byte is very important, so that might be for your relational database applications and things of that sort, where there tends to be a lot of searching through an index, and so you've got a lot of low-latency requirements. And then on the other hand, what you have is a capacity tier, they may be your video surveillance, they may be your large, unstructured documents, they may be your censor data, and in those contexts, you don't necessarily need the Time To First Byte, what you really need is capacity throughput, and so the overhead of setting up, for example, a restful connection is not significant when compared to the amount of data that actually needs to go through the system, and that's actually where restful semantics actually gets superior to positive semantics, when you have very, very large, unstructured data sets. Hyper-converge is actually a little bit of a different world, and I think that while hyper-converge has worked out pretty well, I think, for virtualization workloads, we've really found that when it comes to these very, very large unstructured data sets, hyper-converge isn't necessarily always the way to go, you tend to find a utilization issue between your compute and your storage layers, where you have to actually think about how you're balancing all this stuff, and so, really, the world that we've really seen emerge as new applications come forward, is there's really a trend to write microservices that are stateless, and to have them talk to a stateful layer, that's why in the public cloud, there's a pattern of having things like elastic container services talking to an S3, and we definitely see on premises that same type of things that's going to emerge. There's going to be some time to get there, admittedly, as I was mentioning kind of at the beginning, we've seen this really interesting set of interest patterns, one is from the folks who are developing these new applications that are utilizing unstructured data, there's a lot of interest we're getting right now from IT folks that are just getting started with object storage to do secondary workloads, to do backups, to do archives, and it's been interesting that we've been getting a lot of interest in our service as a new way to approach some of these data protection workflows. >> Alright, so Steve, last question I've got for you, came out of Stealth Q4 last year, what do we look for in 2017 from Igneous? >> Yeah, so I think that you'll see it on both of those fronts, I think that one thing that's going to be seen in 2017 is a lot more development on our side around building up a tool chain for folks to use for a data protection tier, and so, we've got a new offering coming online, we're calling it Igneous Insights, which provides information about what's currently on your primary storage tiers, we've got a whole set of replication services, they're coming up to do backup, archive, things like replication to the cloud, but what we're also really moving forward with is a lot of what's needed in the tool chain to really support hybrid and multi-clouds, so how you facilitate the data movement in and out of the cloud, as well how you do the auditing and management of the data, no matter where it lives. >> Alright, Steve Pao, really appreciate you catching up, and if you want to find out more about this category, check out cube365.net/trueprivatecloud, that's C-U-B-E, number 365.net/trueprivatecloud, which has resources from the whole industry, including from Igneous, including from Wikibon and theCUBE, as to what's happening kind of this true private cloud, hybrid cloud environment. We'll be back with lots more coverage here, thanks for watching theCUBE. (electronic music) >> Announcer: Since the dawn of the cloud, theCUBE has been there.

(uplifting music) >> Narrator: Partners. Now, here are your hosts, John Furrier and Stu Miniman. >> US Amazon Web Services re:Invent 2016 their annual conference. 32,000 people, record setting number. I'm John Furrier, Stu Miniman co-host in theCUBE for three days of wall-to-wall coverage. Day two, day one of the conference our next guest is Kiran Bhageshpur, who's the CEO and co-founder of Igneous Systems. He was a hot startup in the, I don't want to say storage area, kind of disrupting storage in a new way. Kiran great to see you, thanks for coming on theCUBE. >> Thanks a lot, glad to be here, John. >> So, you're living the dream the cloud dream, it's not a nightmare for you because you're one of the progressive new ways. I want to get your thoughts on Andy Jassy's Keynote because he really lays out the new mindset of the cloud. Your startup that you founded with your team is doing something kind of, I won't say contrarian, some might say contrarian, but contrarians usually become the big winners, like Amazon was a contrarian now they're obviously the winning. So, take a minute to explain what you guys are doing. You're funded by Madrona Ventures and NEA, New Enterprise Associates, great backers, smart. Your track record at Isilon, you know the business. Take a minute to describe what you guys are doing. >> Great, yes I will. So, Igneous Systems was founded to really deliver cloud services to the enterprise data center for data-centric workloads. So what to we mean by that? With cloud services, just like with Amazon, customers don't buy hardware, license software. They do not monitor or manage your infrastructure. They consume it across API and they pay for it by the drip rather than the drink. Similarly, the same case with us but we make that all available within a customer's data center itself. And we focus on sort of data-centric, data heavy workloads. I don't know whether you saw James Hamilton's-- >> Yeah. >> Speech yesterday, but he also talked about the same thing that Mary Meeker talked about earlier this year which is an overwhelming amount of data generated today is machine generated and machine consumed and that's growing really rapidly. And our view is the same techniques that have made Amazon so powerful and so valuable are needed out at the edge or on-premise, close to where users and machines are generating and using the data. So that's kind of what we do. Very much the cloud model taken out to the enterprise data center. So, think of it as a hybrid. >> Kiran, let's talk about storage and where it lives because I think something that many people miss is that cloud typically starts with very compute heavy types of applications and we know that data is tough to move. I mean, Amazon rolled out a truck to show how they move 100 petabyes. And not just to show it, this is a new product they had 'cause customers do want to be able to migrate data and that's really tough and takes a lot of time. You mentioned IoT at the edge, they announced kind of query services on your data up in S3, so what are you hearing from customers? You know, kind of large data from your previous jobs. Where's the data living, where's data being created, where does data need to be worked on and how does that play into what you're doing? >> That's a great question Stu. What we find with customers, especially the one's with large and growing data sets is there is still a challenge of not just how to go store it but how to go process that on the fly. On a camera today or a next generation microscope could produce tens of terabytes of data per hour and that is not stuff that you can move across the internet to the cloud. And so the ask and the call from customers is to be able to go ingest that, curate that, process that locally and the cloud still has a very compelling role to play as a distribution mechanism and for a sharing mechanism of that data. I found it pretty wild that a big part of Andy Jassy's Keynote was for the first time they talked about hybrid and acknowledged the fact that it is the cloud and cloud-like techniques out in the enterprise data center. So, I look at that as hugely validating what we have been talking about which is bringing cloud native paradigms into the enterprise data center. >> Let's talk about that operational model because what you're highlighting and what Jassy pointed out is an operational model now for IT. >> Kiran: Yep. >> How are you guys creating value for customers? And be specific, is it, 'cause the on-prem is not going away, we've talked about this before and certainly VMware sees the cloud but also on-prem too. What is the value for customers? Because now this operational model of on the cloud is there, one way-- >> Yes. >> But how do I get cloud inside my data center? >> The way we do that is, very similar to the cloud operating model, right? So, we sell customers essentially an annual subscription service and that service is delivered using appliances that are purpose-built. Think of it as, like snowball, if you will, that goes into the customers data centers fully managed by our software running in our cloud. So, for a customer point of view, it happens to live within their data center, but they are consuming it pretty much the same way that they would consume a cloud service. That's the value, it's the same tool chains, the same programming paradigms that they are used to with, say, a native OS. But within their data centers at lower latencies addressing the same things that Andy Jassy brought up, which is you need a truck to go move large amounts of data. >> Well, I want to also bring up James Hamilton's presentation. You mentioned that yesterday one of the key points he made was that scaling up for these peak loads like they have on the Friday's, their Prime Friday spikes, they do instantly and elastic is a big deal we know that. His point though was they would have to provision on bare metal or in the data center months in advance to even rationalize what that peak could be which still is an unknown number. So, the scale point and provisioning is a huge headache for customers, so that's why that's relevant. How do you guys answer that claim when you say, "Hey, I need stuff to be done fast, "I don't have time to provision"? How do you guys, do you address that at all? How do you talk to that specific point? >> We take care of the provisioning and the additional expansion and shrinking of capacity within the customer's data center, because just like Amazon monitors their infrastructure users in the data center, we do that for our infrastructure within the customer's data center, and therefore we can react to go scale up or scale down. But then there's another point to the whole thing, which is the interesting thing is the elasticity is much more important for compute as opposed to data. Data just linearly grows, you never throw that stuff away. The things that you captured, the processing is highly elastic and you might want to do some additional processing and burst out and so on. So, that's another aspect of hybrid we see with our customers which is, I want my work flow here, I want to be able to burst out to the public cloud for that peak capacity that I don't want to have infrastructure locally for. >> So Kiran, sorry. So James Hamilton's presentation talks a lot about, just that hyper scale. They claim they've got the most scale and therefore nobody else should do anything because oversimplifying a little bit, but we've got the best price, we've got the whole stack, give you all the solutions. You talk to enterprises. Scale means different things for different applications for what I need to get done, what I have. What does that really mean to you? How does that hybrid piece fit in to the whole scale discussion? >> So, a lot of what we do is really ride on the coattails of the Amazon and the Google and the Microsoft because everyone has access to the same raw components, hard drives and CPUs and so on and so forth. And then the question is how do you go assemble those in a form factor that is appropriate for that particular use case? If you're going to go build a data center that's one level of scale, but if you look at a vast majority of applications and enterprises, their scales are much smaller. So, we literally look at taking a rack of infrastructure which might have, say, 40 servers and a couple of switches in sheet metal and shrinking that to a 4U form factor which has got 60 of our nano servers which has got switches and has got sheet metal. So, it's shrinking the whole thing down. The economy's of scale are still quite compelling because we use the exact same raw materials from the same suppliers to the cloud guys, right? And the real difference in cost is how things are put together and how they are operationalized. In which case, we are much more like Amazon than not. >> The other thing that's really interesting to watch, if you look at Amazon's storage move, is storage is in a silo, they've now got all these services that I can start doing this. How does the enterprise look at that? How does the solution like yours enable us to be able to use our data more? >> I absolutely think there is a palpable need for and desire for those sorts of new paradigms in the enterprise data center too because what you can do with not just storage but with lambda and with a bunch of other advanced services on top of that, what that really does is allows enterprises and customers to just focus on what is differentiated to them. This is the whole low-code, no-code moment, if you will, right, movement, and that's a compelling trend. It is something that we've actively embraced. We've got our architecture enables that on day one and that's kind of the way you're going to go build applications now onwards. >> So will we see lambda functions calling things on your end? >> Stay tuned. I think my, yeah, stay tuned. >> That's a smile, that's a yes. (laughs) Talk about the drivers in your business, 'cause you guys are new, you're a startup. For the folks watching you're making some bets, big bets obviously funded by some pretty big venture capitalists out there. What is your big bet? Is it true private cloud is going to emerge on-premise? Is the bet that cloud adoption with scalable compute and storage is going to be unmanaged or manageless or serverless, what's the big bet? >> So our bet is the cloud is going to win and I mean the cloud paradigm, which means consuming infrastructure by the drip rather than the drink across APIs. Flexibility, agility is going to win. One answer which is very compelling is the public cloud today. We believe that similar patterns will exist on the on-premise world and we believe we are very well positioned to supply that thing. And the infrastructure which shrinks would be very traditional infrastructure and software technology stacks which has really existed in the enterprise data center for the last 20 years. That will shrink and everything will look similar as in highly flexible, highly scalable, very easy to go put things together and you're going to have very similar patterns in both the public cloud and within your data center. >> Our Wikibon research team is looking at the practitioner side of the market. One of the things they're observing is, among a lot of things, is that you're seeing AWS teams come together. We're seeing Accenture was on earlier talking about the same dynamic. That's the pattern that we're seeing is these teams are coming together, some handful of people, the pizza box teams-- >> Yep. >> As Jeff Bezos calls it, growing into fully functional bigger teams. So, depending upon that progression, what's your advice to practitioners? And how do you add value into this momentum of as they scratch their head go, "Okay, we're going to go to the cloud"? So they know that's the mandate. How do you help them and why should they look at your solution and where do you fit into that? >> So one of the things customers and partners tell us is we are a great on-ramp to the cloud if you will. Everybody wants to embrace the new programming patterns, new programming paradigms and many people have taken that big leap and done the full shift in one step. You've heard Finra, you've heard Capital One all of these guys talk, but not everyone is that far out there. So what we sort of become for these folks is a stepping stone. We are on-premise. It allows them to get used to it. They start using the same patterns that can scale there. There can decide what workflows remain local and why and what go there, and that's our view. We very much live in they hybrid world to burst out to the world, bring it back as appropriate. >> Kiran thanks so much for coming on theCUBE, we really appreciate it, we're getting the break but I do want to ask one personal question. You're back in the entrepreneurial zeal again, you've got the startup, you have some capital but you're not loaded with cash, a good amount to achieve what you need to do. What's it like for you right now? I mean, what do you believe in? What's your guiding principles and what's it like to get back on the entrepreneurial treadmill again? >> You know, it's actually quite exhilarating and liberating to be back in a startup environment because it forces you to focus on what is important what is urgent and important at all points in time, and a guiding principle for us is less is more. Let's be driven by customers and do what is required there and then slowly extend that out. And actually, being a startup and not having infinite money to throw like, large legacy players would frees you from trying to do too many things and focus on only what is important and that's really key to success. >> And how are you making the decisions as an executive like, product-wise? Is it more agile, are you guys doubling down? >> Very, very agile, we can move very quickly. Since we are delivering a service, we are continuously updating infrastructure just like Amazon does within their data center so we can turn around very, very quickly. So I'm very impressed the fact that the Amazon rolls out 1,000 new features this year, but I can see how that is possible at scale and that's what we're doing. >> At Isilon you were very successful scaling up that generation of web scale, we saw that with Facebook and the Apples of the world. What's different now than then? Just in the short years between the web scalers dominating to now full Multi-Cloud, Hybrid Cloud cloud. In your mind, what's different about the landscape out there? Share your thoughts. >> I think there's a couple of things. One of them is Isilon was incredible, was a very useful infrastructure, was something that was easy to deploy, but it was still that something you built, you managed, you owned, if you will. The big transition is away from that, from build to consume and not worry about that infrastructure at all. And that is not something that you can retrofit into an existing architecture, you have to start from scratch to go do that. So, that's the biggest number one. Two, second one is just the scale is bigger. You heard Andy Jassy talk about the exobyte moving problem and he commented on the fact that exobytes are not all that rare and he's true because you go back 10 years ago, maybe four companies had an exobyte problem. It's now a lot more than that. And so the scale is two or three orders of magnitude larger than when Isilon was growing up. >> Scales at table stakes and consumption of infrastructure, that's a dev-ops ethos gone mainstream. >> Yes. >> Thanks so much for sharing. We're live here in Las Vegas for Amazon re:Invent. I'm John Furrier, Stu Miniman, we're back with more live coverage, three days of wall-to-wall coverage. theCUBE will be right back. (upbeat electronic music) (relaxing guitar music)

(energetic music playing) >> Hi, I'm Stu Miniman here at the Silicon Ango Media Office in Palo Alto, happy to welcome back to the program Kiran Bhageshpur, who is the CEO of Igneous Systems. Kiron, great to see you. >> Great to see you again, Stu. >> Alright, so we've been really busy at theCUBE looking at so many big trends, and of course, really looking at kind of massively scalable distributed type of architectures are something we've been looking at, and something I know Igneous has been doing since the earliest days. But, the exact focus of what you've been working on, I think's changed a little bit since you first came out of Stealth and we've been looking at what your doing. So, why don't you bring our audience up to speed. >> Love to do that. It's not changed so much as expanded if you will. We launched, I believe I was here last, in October of last year, just as we were getting ready to launch. And, at that time, we launched the company and the platform, which the beginning services was object of the service, televert as a service and the enterprise data center. And, that was just the beginning. We've gone on since then, expanded the number of native services available, but really what we have done is built applications on top of that. So, the first application that we have developed and deployed at customers is backup and archive for massive file systems. So, we are talking about people who have terabytes of data, billions of files, spread across hundreds of systems. So, that's kind of been a pretty exciting thing, and it's a very unique set of challenges both for customers and for us to go forward. >> So, it's interesting, just step back for a second, object storage is something. If you talk to anybody that's a storage technologist they're like absolutely the way we need to architect things. But, usually we tend to get away from talking about object storage itself, and truly what do I do with it, what are those applications, what are those use cases. So, there's still object underneath it if I understand it right, it's just you're getting closer, moving up the stack a little bit, and getting closer to what your customers were asking for. >> Absolutely. The underlying infrastructure is still a collection of cloud services, not just object and S3, but a bunch of other services, which are very API compatible with the cloud, but, really, that doesn't matter because those are just tools. What matters is what are you doing with that, and what we are doing to begin with is really backup, archive, and discovery of massive files inside the enterprise. >> Alright, so there're some backup we've been doing for a long time, but backup has been broken. We were at the VM world show, there was a lot of buzz around some of the new companies, sometimes they called them secondary storage; you know, Rubric, Cohesity, Veem who everybody knows from the virtualization world, why don't you tell us are you part of kind of a similar wave? How do you kind of compare and contrast that to some of those other players? >> Great question. It's similar, but quite different. So, if you look at Rubric or Veem, for example, Veem really came about by doing tight integration with Veemware and doing a Veemware specific backup, which was the right technology, the right time for VMS and virtualization. Similarly, Rubric, and for that matter Cohesity, are really re-imagining data protection primarily for structured workflows, databases, physical servers, VMS, tightly integrating it and re-imagining how that feels from an experience point of view. We are really looking explicitly at unstructured data. This is data which lives on network devices from a net-app or a deliMC or a whole bunch of others and the content is really digital assets. It's data that could be media data, it could be microscopy imaging, it could be design data for a variety of work flows and this stuff continues to grow. It is monotonically increasing in every place, whether it is on premises or on the cloud or the edge, and protecting and managing this data is really a challenge and getting worse for customers. >> Yeah, the word that keeps coming up a lot is data. And, one of the things I know we've been excited about storage use to be about storing it. Now when we're talking about data, how do I leverage it? How do I get get value out of it? How do I discover different pieces of it? How have you been seeing these changes, your background you worked on some of the scale-out NASA solutions in the past, so how do we see kind of, unlocking the value of data? >> Yeah, you are absolutely right. If you go back 10 years ago, the real problem with how do I store all of this data, today there are plenty of solutions for ways you store data, especially on the primary teir, right? The challenge is really getting data from where it lives to where it's needed, whether it is backing it up or archiving it into the cloud. Being able to automatically discover things about it. Simple things like how is it growing, who is using it, how big is it, how much of it is what size of data? What about things you can infer about it by looking at the type of data it is. This is what now becomes valuable because if you look at the data sets and sizes, even modest size businesses today will have para bytes of data, billions of files, and that's challenging for any system system to go, sort of understand, unless you build it as a part of the platform. >> Okay, how about organizationally? Yah know, one of the other shifts we've seen is, you know, it used to be the storage administrator. How do I, how do I grow, how do I manage it, how do I have all of my protections and things set? A lot of the types of applications you are using are closer to the business, this is what runs the business. The business user needs to be involved. How are you setting your solution up to, you know, do what the business user needs? >> Great, yeah that's a good question. Today if you look at this data sets, this is not stuff that is an IT application. It's an end-user business focused application where they research in a life sciences world, or its designed in an electronic design world, right? And in all of these cases, essentially the end-user cares, because this data is critical to their daily working, working experience. Now, IT is clearly involved; it's a clear sort of partner of the business unit and actually operationalizing this data and making it easier to go consume. But now, it's really a joint thing, the final decision maker is always the end-user. In fact, we find ourselves in multiple places where we talk to IT, and talk to the IT teams. They get excited, but very quickly they bring in the end-users to make certain, whether the end-users are researchers or software developers, or even (mumbles) to make it so that they're comfortable with what we're talking about and they get really excited and that's sort of the starting point for our deployments. >> Yeah, we saw a similar dynamic between the business and the IT when we talked about cloud. And when I talked cloud I specifically mean public cloud and your customers, I have to imagine, they're all using public cloud in one way or another. Maybe, explain that dynamic how public cloud fits in with what your doing and how some of those IT and business people. >> Right. Look, cloud is simply the most disruptive trend in the last 10 years. In fact, you have to go back to Veemware, and Veemware's virtualization to see another trend of that magnitude. And all of our customers are embracing the cloud. They are wanting to go adopt cloud patterns, if you will. But the 180 over there massively challenged is around large data sets. Think about it, if you have terabytes of data that continues to grow, it's billion of files, it's spread across multiple geographies and dozens to hundreds of systems, it's a challenge to go leverage this in the cloud. So they're looking to ask, to be able to go chart the journey from all on premise, to a true hybrid world where they can use those cloud patterns much more effectively. >> Yah know I'm curious, and maybe it doesn't fit exactly for what Igneous is doing today. But, we've been talking about the data center versus the public cloud and a lot of those environments. I talked to some companies, that, you know, when I'm building those data legs, I'm doing that in the public cloud too. Then the discussion that's come up a lot in the past year, is Edge; so, IOT applications, we know we're going to have orders of magnitude more devices, and there's going to be a lot of data but the requirement for the data center versus the public cloud versus the Edge are very different. How does Igneous look at that? How are you having those discussions? Customers, how do they get their arms around all the various places of data?-- >> Right. You're absolutely right. The requirements are different, as in the public cloud is this massive hyper-scale, always available. The enterprise is a smaller version of that. And the Edge has a very different physical characteristics. But, what we believe is important is the same patterns, the same API's are available everywhere. And if you look at what the big public cloud providers are doing, Amazon with, you know, Snowball, and Green Grass, they're trying to go move their API's out and we completely embrace that trend. And, that's one of the reasons we built our platform to be API compatible with the cloud, with a variety of the cloud services. Because that means the services we run can run in the enterprise data center or in the public cloud or on the Edge all on a platform which is appropriate for the three. >> Yeah, and, to drill down to specifically, you say API compatible, that's S3, that's fully compatible. And do we have an API creep every cloud seems to have not only one API but many API's especially our friends at Amazon, what are you seeing out there, and what is the breath of offering they have today? >> Yeah, so, its SS3 is a constant storage leg is the obvious one, but the ones we did not talk about the last time were things like index store. So this is the equal of Amazon's dynamoDB, or Azure's table store the ability to go store a massive amount of index. But it's not just that. It's also the ability to go around compute, close to the data, which boils down to Cubanaties and containers. So all these three are part of our on the line platform. We don't talk about that to customers except after they become customers; we really focus on the application which is back up, archive, and discovery of all of their file data. >> Yeah, Kiran, take me inside the customers you are talking to; a lot of times we're like, I hear this term secondary storage out there and I worked on converge and hyper-converge stuff, you know, those terms are something that customers hear about after awhile, but they don't solve the problem. What, can you help translate for us, what's going on in your customers and why is secondary storage important to them? What's different than traditional back up, and how do you fit in? >> Right, so if you look at all of these guys, the data, the fundamental truth is data sets are growing and they are growing monotonically. Every year it is more. We've talked to folks where in the two years that we've spent as we were growing up as a company, they've sort of essentially had a 40 percent growth in their on search data sets, right? So then, the question is a couple of things. One, they clearly realize that not all of that stuff needs to live, or should live, on high performance, relatively expensive primary tiers. Right? That's the first set of piece. But the question is, how do you find out, what is active what is not active and how do you move it to the appropriate place; so this is sort of trend line and this is the patterns that they are living with. What we do is go in, very simply start off by saying, lets go find all of your filers, you know some of them, some of them you may not even know about, and let's go automatically back-up all of the data, and give you intelligence about all that. What is sort of simple intelligence. The intelligence could be how infrequently are these data sets changing, how frequently are parts of this data being accessed or modified by your applications. So that's sort of first part of this. And when this drives to is, not only does this reduce the cost of backup, which is really an insurance policy, it makes possible a bunch of intelligence about the data itself which is the beginnings of, sort of appropriately staging data on the right infrastructure. >> Alright. Kiran, you've had a number of customers since the early days talk to us a little bit about the journey you've been going on with them. How many of them have been pulling you towards the direction you are now going? What's their response been? To I guess what you call it, kind of storage as a service? >> Yeah, you know people love the whole concept of our offering as a service; initially when we talked of customers they kind of a little skeptical of our ability to go do this but they very quickly fall in love with that. It's pretty amazing. What's not to like about infrastructure that is inside your data center but that you do not have to manage at all? And when I say do not manage, people don't even look at things like drives or CPUs or network. That's not the world they live in. They live in the world of what's logically important to them, which if my backup's running, is my data being archived, how quickly is my data growing, who is accessing this data? And so on, and it goes to the next level, which is they don't have to go to manage things like software updates, just like you don't know what version of Gmail you're running or you do not know what version of S3 is being used in the cloud. Our customers don't know what version it is. Is it API level compatible or is it guarantee the services are not interrupted; and they absolutely love that aspect once they get used to it. We tell our customers, "You don't call us, we call you if there is an issue." And we're living up to that and they are pretty jazzed about that. >> Yeah, I love that. Kind of the version control thing is something we said is something, is cloud experience is actually what we want. (Mumbles) when we wrote true private cloud is exactly that; you don't know or care what version of Azure you're running, you assume that they're going to test that out and do that. Can you give us any kind of concrete examples, customers, love if you can share any names, but a lot of your customers are quite big, but what are the concrete results? What are they seeing, any good stories you can share? >> Yeah! So I give you an example of one of our largest customers, can't mention the name, but it is a large tech company in California. There's a lot of large tech companies in California-- (giggles) >> There's a bunch, yeah. >> Well, lets go through the South in California. And, these folks had an enormous amount of data. We started off by telling them, "Hey give us your most "complex systems, the ones that you are not able "to go back up today." And we started with their file systems, which were literally had this thing called file density, which is an enormous number of files in a relatively small amount of storage. So you're talking about a billion plus files and terabytes of data, and this is things that they had never been able to back up and we go off and we were able to go back it up and completely system protect. So, that's an example of a used case where we can go to a customer and allow them to accomplish what they cannot do today just from a basic back-up point of view. And, take it to the next level. In fact they did this great demo for their internal teams where they showed how easy it is to search through this data and essentially accomplish in seconds what typically, in their current world, takes hours to do. >> Okay, yeah, that's great. Yeah, sounds like you have some really good interesting, large companies there. Is that, what's the typical profile you see? Is it really companies that have specific challenges because they've got the massive scale? How far down does this scale? >> So. Uh, that's a common question that comes along. And the way I like to answer that is we are applicable to people with lots of data. It turns out it could be much smaller companies with lots of data, so we've got customers who are in the hundreds of people only world-wide, maybe two or three locations, but they are really looking at a multi-terabyte sized data problem. Similar data density problem. In fact, another one that we are working with has got 300 million files and a terabyte of data. How do you back it up? How do you go discover information about that? That's what we solve, and for these smaller companies which still have the problem, they are actually starting to find out about us and come to us. Which is really gratifying. >> Okay, well you seem pretty excited about it, about the space, what's exciting you the most about where we are today with the technology. >> The really sure is, people talk about data and they immediately go to databases, they talk about virtualization and physical servers. But that's not where the data lives. The data hasn't lived there for over a decade. And more and more of the data lives outside in files and object and there is this sort of ability to go understand that better, manage that better, protect that better and last but not least, provide intelligence to users because this data is something they care about. People are not keeping this because somebody else told them to; it is their life blood. It is their sort of livlihood, if you will, from a company point of view, and helping customers be able to go take that to the next level will bring this sort of cloud patterns to these used cases. That's pretty exciting. >> Yeah, absolutely! Want to sort of give you the final word. I hear this and I think about, you know, the whole wave of big data, what we're starting to talk about, you know, continuously with AI and ML really it is about unlocking data, so huge opportunities going forward. Any of the other trends outside what we've discussed already that you want to give us for a final word? >> You know, the last thing that I say is it is about data. It is about complete automation all across the, across the sky, weather it is storing, managing, or deriving intelligence and the reason you want to go automate all that stuff using intelligence in the software systems itself is simply because it's too large. There's no other way to go do it. And last, but not the least, all of the stuff has to be offered as a service because the cloud has gotten people really hooked on this sort of, comparatively, easy world of not having to go managing infrastructure. And I think those are the three things we should, we hold by. >> Alright, Kiran Bhageshpur, I really appreciate the update on Igneus systems. Absolutely customers dealing with massive amounts of data, how do I unlock the value of that without having to be down in the guts which has really been the history of storage. I'm Stu Miniman, thanks so much for watching theCUBE. (energetic music playing)