(upbeat music) >> In 2010 Wikibon predicted that the all flash data center was coming. The forecast at the time was that flash memory consumer volumes, would drive prices of enterprise flash down faster than those of high spin speed, hard disks. And by mid decade, buyers would opt for flash over 15K HDD for virtually all active data. That call was pretty much dead on and the percentage of flash in the data center continues to accelerate faster than that, of spinning disk. Now, the analyst that made this forecast was David FLoyer and he's with me today, along with Renen Hallak who is the founder and CEO of Vast Data. And they're going to discuss these trends and what it means for the future of data and the data center. Gentlemen, welcome to the program. Thanks for coming on. >> Great to be here. >> Thank you for having me. >> You're very welcome. Now David, let's start with you. You've been looking at this for over a decade and you know, frankly, your predictions have caused some friction, in the marketplace but where do you see things today? >> Well, what I was forecasting was based on the fact that the key driver in any technology is volume, volume reduces the cost over time and the volume comes from the consumers. So flash has been driven over the years by initially by the iPod in 2006 the Nano where Steve Jobs did a great job with Samsung and introducing large volumes of flash. And then the iPhone in 2008. And since then, all of mobile has been flash and mobile has been taking in a greater and greater percentage share. To begin with the PC dropped. But now the PCs are over 90% are using flash when there delivered. So flash has taken over the consumer market, very aggressively and that has driven down the cost of flash much much faster than the declining market of HDD. >> Okay and now, so Renen I wonder if we could come to you, we've got I want you to talk about the innovations that you're doing, but before we get there, talk about why you started Vast. >> Sure, so it was five years ago and it was basically the kill of the hard drive. I think what David is saying resonates very, very well. In fact, if you look at our original presentation for Vast Data. It showed flash and tape. There was no hard drive in the middle. And we said 10 years from now, and this was five years ago. So even the dates match up pretty well. We're not going to have hard drives anymore. Any piece of information that needs to be accessible at all will be on flash and anything that is dormant and never gets read will be on tape. >> So, okay. So we're entering this kind of new phase now, with which is being driven by QLC. David maybe you could give us a quick what is QLC? Just give us a bumper sticker there. >> There's 3D NAND, which is the thing that's growing, very very fast and it's growing on several dimensions. One dimension is the number of layers. Another dimension is the size of each of those pieces. And the third dimension is the number of bits which a QLC is five bits per cell. So those three dimensions have all been improving. And the result of that is that on a wafer of, that you create, more and more data can be stored on the whole wafer on the chip that comes from that wafer. And so QLC is the latest, set of 3D NAND flash NAND flash. That's coming off the lines at the moment. >> Okay, so my understanding is that there's new architectures that are entering the data center space, that could take advantage of QLC enter Vast. Someone said they've rented this, a nice set up for you and maybe before we get into the architecture, can you talk a little bit more about the company? I mean, maybe not everybody's familiar with with Vast, you share why you started it but what can you tell us about the business performance and any metrics you can share would be great? >> Sure, so the company as I said is five years old, about 170, 180 people today. We started selling product just around two years ago and have just hit $150 million in run rate. That's with eight sales people. And so, as you can imagine, there's a lot of demand for flash all the way down the stack in the way that David predicted. >> Wow, okay. So you got pretty comfortable. I think you've got product market fit, right? And now you're going to scale. I would imagine you're going to go after escape velocity and you're going to build your moat. Now part of that, I mean a lot of that is product, right? Product is sales. Those are the cool two golden pillars, but, and David when you think back to your early forecast last decade it was really about block storage. That was really what was under attack. You know, kind of fusion IO got it started with Facebook. They were trying to solve their SQL database performance problems. And then we saw pure storage. They hit escape velocity. They drove a truck through EMC sym metrics HDD based install base which precipitated the acquisition of XtremeIO by EMC. Something Renan knows a little bit about having led development, of the product but flash was late to the NAS party guys, Renan let me start with you. Why is that? And what is the relevance of QLC in that regard? >> The way storage has been always, it looks like a pyramid and you have your block devices up at the top and then your NAS underneath. And today you have object down at the bottom of that pyramid. And the pyramid basically represents capacity and the Y axis is price performance. And so if you could only serve a small subset of the capacity, you would go for block. And that is the subset that needed high performance. But as you go to QLC and PLC will soon follow the price of all flash systems goes down to a point where it can compete on the lower ends of that pyramid. And the capacity grows to a point where there's enough flash to support those workloads. And so now with QLC and a lot of innovation that goes with it it makes sense to build an all flash, NAS and object store. >> Yeah, okay. And David, you and I have talked about the volumes and Renan sort of just alluded to that, the higher volumes of NAS, not to mention the fact that NAS is hard, you know files difficult, but that's another piece of the equation here, isn't it? >> Absolutely, NAS is difficult. It's a large, very large scale. We're talking about petabytes of data. You're talking about very important data. And you're talking about data, which is at the moment very difficult to manage. It takes a lot of people to manage it, takes a lot of resources and it takes up a lot, a lot of space as well. So all of those issues with NAS and complexity is probably the biggest single problem. >> So maybe we could geek out a little bit here. You guys go at it, but Renan talk about the Vast architecture. I presume it was built from the ground up for flash since you were trying to kill HTD. What else do we need to know? >> It was built for flash. It was also built for Crosspoint which is a new technology that came out from Intel and micron about three years ago. Cross point is basically another level of persistent media above flash and below Ram. But what we really set out to do is, as I said to kill the hard drive, and for that what you need is to get the price parity. And of course, flash and hard drives are not at price parity today. As David said, they probably will be in a few years from now. And so we wanted to, jumpstart that, to accelerate that. And so we spent a lot of time in building a new type of architecture with a lot of new metadata structures and algorithms on top to bring that effective price down to a point where it's competitive today. And in fact, two years ago the way we did it was by going out to talk to these vendors Intel with 3D Crosspoint and QLC flash Mellanox with NVMe over fabrics, and very fast ethernet networks. And we took those building blocks and we thought how can we use this to build a completely different type of architecture, that doesn't just take flash one level down the stack but actually allows us to break that pyramid, to collapse it down and to build a single system that is as fast as your fastest all flash block device or faster but as affordable as your hard drive based archives. And once that happens you don't need to think about storage anymore. You have a single system that's big enough and cheap enough to throw everything at it. And it's fast enough such that everything is accessible as sub-millisecond latencies. The way the architecture is built is pretty much the opposite of the way scale-out storage has been done. It's not based on shared nothing. The way XtremIO was the way Isilon is the way Hadoop and the Google file system are. We're basing it on a concept called Dis-aggregated Shared Everything. And what that means is that we have the media on one set of devices, the logic running in containers, just software and you can scale each of those independently. So you can scale capacity independently from performance and you have this shared metadata space, that all of the containers can see. So the containers don't actually have to talk to each other in the synchronous path. That means that it's much more scalable. You can go up to hundreds of thousands of nodes rather than just a few dozen. It's much more resilient. You can have all of them fail and you still didn't lose any data. And it's much more easy to use to David's point about complexity. >> Thank you for that. And then you, you mentioned up front that you not only built for flash, but built for Crosspoint. So you're using Crosspoint today. It's interesting. There was always been this sort of debate about Crosspoint It's less expensive than Ram, or maybe I got that wrong but it's persistent, >> It is. >> Okay, but it's more expensive than flash. And it was sort of thought it was a fence sitter cause it didn't have the volume but you're using it today successfully. That's interesting. >> We're using it both to offset the deficiencies of the low cost flash. And the nice thing about QLC and PLC is that you get the same levels of read performance as you would from high-end flash. The only difference between high cost and low cost flash today is in right cycles and in right performance. And so Crosspoint helps us offset both of those. We use it as a large right buffer and we use it as a large metadata store. And that allows us not just to arrange the information in a very large persistent right buffer before we need to place it on the low cost flash. But it also allows us to develop new types of metadata structures and algorithms that allow us to make better use of the low cost flash and reduce the effective price down even lower than the rock capacity. >> Very cool. David, what are your thoughts on the architecture? give us kind of the independent perspective >> I think it's brilliant architecture. I'd like to just go one step down on the network side of things. The whole use of NBME over fabric allows the users all of the servers to get any data across this whole network directly to it. So you've got great performance right away across the stack. And then the other thing is that by using RDMA for NASS, you're able, if you need to, to get down in microseconds to the data. So overall that's a thousand times faster than any HDD system could manage. So this architecture really allows an any to any simple, single level of storage which is so much easier to think about, architect use or manage is just so much simpler. >> If you had I mean, I said I don't know if there's an answer to this question but if you had to pick one thing Renan that you really were dogmatic about and you bet on from an architectural standpoint, what would that be? >> I think what we bet on in the early days is the fact that the pyramid doesn't work anymore and that tiering doesn't work anymore. In fact, we stole Johnson and Johnson's tagline No More Tears. Only, It's not spelled the same way. The reason for that is not because of storage. It's because of the applications as we move to applications more and more that are machine-based and machines are now not just generating the data. They're also reading the data and analyzing it and providing insights for humans to consume. Then the workloads changed dramatically. And the one thing that we saw is that you can't choose which pieces of information need to be accessible anymore. These new algorithms, especially around AI and machine learning and deep learning they need fast access to the entirety of the dataset and they want to read it over and over and over again in order to generate those insights. And so that was the driving force behind us building this new type of architecture. And we're seeing every single day when we talk to customers how the old architecture is simply break down in the face of these new applications. >> Very cool speaking of customers. I wonder if you could talk about use cases, customers you know, and this NASS arena maybe you could add some color there. >> Sure, our customers are large in data. We started half a petabyte and we grow into the exabyte range. The system likes to be big as, as it grows it grows super linearly. If you have a 100 nodes or a 1000 nodes you get more than 10X in performance, in capacity efficiency and resilience, et cetera. And so that's where we thrive. And those workloads are today. Mainly analytics workloads, although not entirely. If you look at it geographically we have a lot of life science in Boston research institutes medical imaging, genomics universities pharmaceutical companies here in New York. We have a lot of financials, hedge funds, Analyzing everything from satellite imagery to trade data to Twitter feeds out in California. A lot of AI, autonomous driving vehicles as well as media and entertainment both generation of films like animation, as well as content distribution are being done on top of best. >> Great thank you and David, when you look at the forecast that you've made over the years and when I imagine that they match nicely with your assumptions. And so, okay, I get that, but that doesn't, not everybody agrees, David. I mean, certainly the HDD guys don't agree but they, they're obviously fighting to hang on to their awesome run for 50 years, but as well there's others to do in hybrids and the like, and they kind of challenge your assumptions and you don't have a dog in this fight. We just want the truth and try to do our best to report it. But let me start with this. One of the things I've seen is that you're comparing deduped and compressed flash with raw HDD. Is that true or false? >> It's in terms of the fundamentals of the forecast, et cetera, it's false. What I'm taking is the new egg price. And I did it this morning and I looked up a two terabyte disc drive, NAS disc drive. I think it was $54. And if you look at the cost of a a NAND for two terabytes, it's about $200. So it's a four to one ratio. >> So, >> So and that's coming down from what people saw last year, which was five or six and every year has been, that ratio has been coming down. >> The ratio between the cost Delta, between HDD is still cheaper. So Renan I wonder one of the other things that Floyer has said is that because of the advantages of flash, not only performance but also data sharing, et cetera, which really drives other factors like TCO. That it doesn't have to be at parody in order for customers to consume that. I certainly saw that on my laptop, I could have got more storage and it could have been cheaper for per bit for my laptop. I took the flash. I mean, no problem. That that was an intelligence test but what are you seeing from customers? And by the way Floyer I think is forecasting by what, 2026 there will be actually a raw to raw crossover. So then it's game over. But what are you seeing in terms of what customers are telling you or any evidence you have that it doesn't have to be, even that customers actually get more value even if it's more expensive from flash, what are you seeing? >> Yeah in the enterprise space customers aren't buying raw flash they're buying storage systems. And so even if the raw numbers flash versus hard drive are still not there there is a lot of things that can be done at the system level to equalize those two. In fact, a lot of our IP is based on that we are taking flash today is, as David said more expensive than hard drives, but at the system level it doesn't remain more expensive. And the reason for that is storage systems waste space. They waste it on metadata, they waste it on redundancy. We built our new metadata structures, such that they everything lives in Crosspoint and is so much smaller because of the way Crosspoint is accessible at byte level granularity, we built our erasure codes in a way where you can sustain 10, 20, 30 drive failures but you only pay two or 1% in overhead. We built our data reduction mechanisms such that they can reduce down data even if the application has already compressed it and already de-duplicated it. And so there's a lot of innovation that can happen at the software level as part of this new direct dis-aggregated shared everything architecture that allows us to bridge that cost gap today without having customers do fancy TCO calculations. And of course, as prices of flash over the next few years continue declining, all of those advantages remain and it will just widen the gap between hard drives and flash. And there really is no advantage to hard drives once the price thing is solved. >> So thank you. So David, the other thing I've seen around these forecasts is that the comments that you can't really data reduce effectively hard disk. And I understand why the overhead and of course you can in flash you can use all kinds of data reduction techniques and not affect performance, or it's not even noticeable like put the cloud guys, do it upstream. Others do it upstream. What's your comment on that? >> Yes, if you take sequential data and you do a lot of work upfront you can write out in very lot big blocks and that's a perfect sequentially, good way of doing it. The challenge for the HDD people is if they go for that for that sort of sequential type of application that the cheapest way of doing that is to use tape which comes back to the discussion that the two things that are going to remain are tape and flash. So that part of the HDD market in my assertion will go towards tape and tape libraries. And those are serving very well at the moment. >> Yeah I mean, It's just the economics of tape are really attractive. I just feel like I've said this many times that the marketing of tape is lacking. Like I'd like to see, better thinking around how it could play. Cause I think customers have this perception tape, but there's actually a lot of value there. I want to carry on, >> Small point there. Yeah, I mean, there's an opportunity in the same way that Vast have created an architecture for flash. There's an opportunity out there for the tech people with flash to make an architecture that allows you to take that workload and really lower the price, enormously. >> You've called it Flape >> Flape yes. >> There's some interesting metadata opportunities there but we won't go into that. And then David, I want to ask you about NAND shortages. We saw this in 2016 and 2017. A lot of people saying there's an NAND shortage again. So that's a flaw in your forecast prices of you're assuming prices of flash continue to come down faster than those of HDD but the shortages of NAND could be problematic. What do you say to that? >> Well, I've looked at that in some detail and one of the big, important things is what's happening in the flash market and the Chinese, YMTC Chinese company has introduced a lot more volume into the market. They're making 100,000 wafers a month for this year. That's around six to 8% of market of NAND at this year, as a result, Samsung, micron, Intel, Hynix they're all increasing their volumes of NAND so that they're all investing. So I don't see that NAND itself is going to be a problem. There is certainly a shortage of processor chips which drive the intelligence in the NAND itself. But that's a problem for everybody. That's a problem for cars. It's a problem for disk drives. >> You could argue that's going to create an oversupply, potentially. Let's not go there, but you know what at the end of the day it comes back to the customer and all this stuff. It's interesting. I love talking about the architecture but it's really all about customer value. And so, so Renan, I want you to sort of close there. What should customers be paying attention to? And what should observers of Vast Data really watch as indicators for progress for you guys milestones and things in the market that we should be paying attention to but start with the customers. What's your advice to them? >> Sure, for any customer that I talked to I always ask the same thing. Imagine where you'll be five years from now because you're making an investment now that is at least five years long. In our case, we guaranteed the lifespan of the devices for a decade, such that you know that it's going to be there for you and imagine what is going to happen over those next five years. What we're seeing in most customers is that they have a lot of doormen data and with the advances in analytics and AI they want to make use of that data. They want to turn it from a cost center to a profit center and to gain insight from that data and to improve their business based on that information that they have the same way the hyperscalers are doing in order to do that, you need one thing you need fast access to all of that information. Once you have that, you have the foundation to step into this next generation type world where you can actually make money off of your information. And the best way to get very, very fast access to all of your information is to put it on Vast media like flash and Crosspoint. If I can give one example, Hedge Funds. Hedge funds do a lot of back-testing on Vast. And what makes sense for them is to test as much information back as they possibly can but because of storage limitations, they can't do that. And the other thing that's important to them is to have a real-time experience to be able to run those simulations in a few minutes and not as a batch process overnight, but because of storage limitations, they can't do that either. The third thing is if you have many different applications and many different users on the same system they usually step on each other's toes. And so the Vast architecture is solves those three problems. It allows you a lot of information very fast access and fast processing an amazing quality of service where different users of the system don't even notice that somebody else is accessing the same piece of information. And so Hedge Funds is one example. Any one of these verticals that make use of a lot of information will benefit from this architecture in this system. And if it doesn't cost any more, there's really no real reason delay this transition into all flash. >> Excellent very clear thinking. Thanks for laying that out. And what about, you know, things that we should how should we judge you? What are the things that we should watch? >> I think the most important way to judge us is to look at customer adoption and what we're seeing and what we're showing investors is a very high net dollar retention number. What that means is basically a customer buys a piece of kit today, how much more will they buy over the next year, over the next two years? And we're seeing them buy more than three times more, within a year of the initial purchase. And we see more than 90% of them buying more within that first year. And that to me indicates that we're solving a real problem and that they're making strategic decisions to stop buying any other type of storage system. And to just put everything on Vast over the next few years we're going to expand beyond just storage services and provide a full stack for these AI applications. We'll expand into other areas of infrastructure and develop the best possible vertically integrated system to allow those new applications to thrive. >> Nice, yeah. Think investors love that lifetime value story. If you can get above 3X of the customer acquisition cost is to IPO in the way. Guys hey, thanks so much for coming to the Cube. We had a great conversation and really appreciate your time. >> Thank you. >> Thank you. >> All right, Thanks for watching everybody. This is Dave Volante for the Cube. We'll see you next time. (gentle music)

>> (Announcer) Live, from Las Vegas it's the Cube. Covering VM World 2018. Brought to you by VM Ware and it's ecosystem partners. >> Welcome back to the Cube's continuing coverage of VM World 2018, I'm Lisa Marin, with Dave Vellante >> Hey, Lisa. >> Dave, day three, we have had tremendous guests the last couple of days. And we're- a lot of alumni, a lot of new guests, another alumni joining us, Calline Sanchez, vice president of IMB Enterprise System Storage. Welcome back, Calline, it's great to have you here. >> No, thank you very much for letting me be here. >> And I want to congratulate Calline, because she was just named for the Tucson Hispanic Chamber of Commerce, 2018 Businesswoman of the Year. Just a few weeks ago. Amazing. >> Lovin' Tucson, by the way. >> Thank you. >> U of A. >> Yes. >> Bear Down. >> I appreciate the Wildcats reference, so, >> Haha. >> No doubt. And so, this Saturday, oh, I'm sorry. This Saturday, the first game, so- >> My daughter is a freshman at U of A, Hi, Pilar, I love you, baby. Good luck. You're going to crush it, I know you are. >> Haha. >> Dad of the year going on here. So, just before we get into all the storage stuff- >> Yeah. >> They're doing a, they're honoring you, just in about a month and a half or so, with this- >> Yeah. Yes, and I'm very excited about that. Just like you were saying with the community aspect, it's a high-touch award, and I was very thankful for it, because they gave me specific examples of, what I've done in Southern Arizona, in Tucson in particular, that they'll name. For instance, Excite for Girls, and things like that. >> That's awesome. >> Girls in STEM, right? >> Congratulations, that's fantastic. >> We need more inspiration, so, it's great that we, >> Ah, thank you. >> Now count you as one of our distinguished alumni. So, let's talk about what going on at IMB. Here we are at VM World 2018, we're hearing Dave, numbers of upwards of 21,000 people that have been here the last few days. 100,000 more engaging with, expecting to engage with the live streaming and the on demand experiences. What's going on with IBM, you know, from a revenue perspective, a growth perspective? What is exciting you about where you are today? >> So, I will talk in particular about storage. I'm really, really proud about this, being that we work in partnership with, like, Ed Walsh, and then also Eric Herzog. They've inspired me to get closer to building solutions with our end users. So we meet and work with our clients to build up cloud deployment solutions, in partnership with VM Ware, and we enable things like, okay, so there's tape, and then there's cloud-to-tier, so there's fundamental solutions out there in the marketplace that we as developers want to go and play with. It's almost like a great big sandbox. So to speak. >> So, I've got to ask you, because, I mean, everybody in storage says, well, Tape, tape is dead. And every time I see you we talk about tape. We talk about FLAPE. We talk about innovations that are coming to tape. You're a technologist. Right, you just said, as a developer we love to- dot-dot-dot. So, what is it about things like tape, things like mainframe, DS8000, these technologies that have, tried, true, running businesses, what is about those that excite you as a developer? >> Everything old is new again, >> Yeah, right. >> If we just go back to the basics of like, table stakes, right? Security is table stakes, right? Delivering on-time quality releases with optimizers like, tier-to-cloud, things like that. That's fundamental for us. Now, as it relates to tape, so, everything old is new again, like I mentioned a moment ago. Tape was the first device to fully encrypt. So every drive, if it fell off the truck, it was fully encrypted. So, tape is actually training the rest of our portfolio in similar skills, on how we do the end-to-end encryption elements. So, right now with DS8000, we're working in partnership with system Z, to deliver pervasive encryption. >> I got to ask you, so as a development executive, I see you at a lot of these shows. You like coming here? A lot of times, development execs want to, sort of, stay in the lab. But you're out and about, talking to customers. What are you learning? What is that about you that draws you to these shows? >> I was afraid that WE as a lab team would not be relevant unless we have conversations with end users, partners. You know, to really substantiate what's possible from being innovative. So, I would say, number one is relevance, and I felt like, I wanted to more social, because, I'm definitely in some cases, an introvert, though I'm looking above my shoes. That's I'm wearing- >> That's the definition, of an introvert and an extrovert in the tech world. You know that the difference is, right? >> I don't. >> An introvert looks at his or her own shoes, an extrovert looks at your shoes. >> Well, there you go. I've been looking at some shoes- >> Alright, so you're, you're extrovert oriented out here, what are you learning at VM World? what are the customers saying? What are they asking you for? What are you going to take back to the lab? >> A single pane of glass associated with what we intend with like, v-stream, or some of the aspects of automation, with regards to cloud deployment, to make it, like, completely- connected. If that, so to speak. And what I think is really great about all of that is I hate to put it this way, it's very iTunes like. Where it's like, sticky, and it's easy to use, or and, by the way, it's not so expensive, at least to start up. So, a lot of the discussions we've been having are with the various vendors on the expo floor, that they want to build solutions. IBM solutions associate with the cloud, and then the AWS guys, we meet with them. And they're like, well, how are, how can we ensure that we live in an interconnected data-centric world? And so that's what I think is very exciting is that, it's this idea of coopetition. Let's all be well connected, and do it well. >> Let's talk about the customer collaboration, as you mentioned, everything old is new again, we see that, in every aspect of life. Tape, mainframe, but you talked about we need to be relevant, but also need to developing solutions that you end user customers need to solve their business problems. How are you collaborating with customers to stay relevant, and to ensure that their businesses are able to take advantage of the super powers that Pat Gelsinger talked about on Monday, AI, machine learning, emerging technologies, what's that collaboration like? >> I would say the biggest collaborations that I've been participating recently is with cloud servers providers. And they appreciate the economics of physical media, or tape. And so, they think to themselves or they know the data, it's like, okay, less than a half-cent per gig, that's a big deal, right? So, and then we have discussions about total cost of ownership, aspects like that. So the partnership is also, how do we serve the data? And really having discussions about the data. And then, if evaluating the various work streams where, we would want to serve appropriately based on whatever specific cloud infrastructure. And then, also, taking a step back, we have to be interconnected. There's no question. So, I would say the number one set of skills our end users are working with right now happen to be the cloud service providers. >> What are some of the big business benefits that they're achieving, we think, new business models, new revenue streams, market expansion. What are some of the things that you're proud of that IBM storage solutions are helping your customers to deliver? >> Going to tape, it's the economics, yes. It's the security based on encryption, yes. And then also, the other aspect of, is, we're serving big data. I mean, it's like we're having discussions about they're going to grow to, zettabytes by 2020, things like that. I never thought in my life, especially as an engineering student, or in computer science, I would ever be talking about this big of data. And now we're here. And so, we're learning how to enable in partnership with clients, what would be the right, or appropriate solution. >> So, I'm searching our video library, because somebody said this week something that was really interesting to me and I wanted to get your perspective from a development mind, someone who's technical. We're hearing a lot about migrating to the cloud. And how easy that is. And then, I think it was Pat Gelsinger said, there's three laws. There's the law of physics, the laws of a company, and the law of the land. And, those are immutable, generally. But I want to ask you about the laws of physics. So, in terms of just moving data into the cloud, we talk about petabyte, exabytes, there's so much data. How feasible is it for a customer to move data, and just stuff it all into the cloud, and what are you doing to either help them do that, or bring the cloud experience to their data? >> Depending on the client interests of on-prem, off-prem, or hybrid, right? We work to evaluate APIs in collaborations, so we enable a streamline, so it's not only just understanding the components of the cloud deployment, but it's also partnering with all elements of the entire ecosystem's stack. So, it depends but we really start with the client's end use case. What do you want? What kind of security do you want? Are you okay with off-prem, public clouds? Or, maybe it's specific data, how do we go about managing the data so we secure it, like, we bucket-ize it. So those are some of the discussions we've been having on the floor, here, at VM world, but also, within our labs, and also with the clients directly. >> You know what I love about that answer? I'll translate it. It's not a biz- it's not a technical problem, Dave, it's a business problem, >> Yes. >> Is really what you're tell me. >> And that's a fundament- you asked the question before. That's fundamentally why I am here. >> Right. >> I don't believe we can live in this world anymore, where it's like, we build it, and then they come. >> Field of Dreams does not exist anymore. >> Yeah. And so, now we've got to have conversations with our end users, to develop, what we've going to put on the roadmap. And so I always felt like, okay, well, when I'd see the roadmap in the lab, I'm like, okay, well, who wants this? Who asked for this, right? And those ended up becoming some of my fundamental questions. So then, I started to come here, or conferences like this, because I could have those conversations with the end users and partners. >> That's interesting, who wants this? Who needs this? What problems does it solve? Why us, why now? Those are the kinds of things you're asking. >> Let's talk about why us? IBM has been around for a very long time. What do you think, again, in this got to be relevant, we need it to be really defined by customer needs and uses. Everything old is new again. What, in your opinion, makes, why should a customer go, in my VM environment, IBM. >> I'm going to start with why I even personally want to remain with IBM. It's a great big candy store. >> Haha. >> And what I have to remind myself is, just don't eat too much, right? And, by the way, I still eat way too much. But what's great about it is, it's a sandbox, so, I can talk to you software engineers one day, who are telling me about certain APIs they're building in Python. Then, oh, by the way, I meet with a mechanical set of engineers, cuz they want to enable robot arms. Oh, and by the way, should we have a discussion on microcode and firmware for the entire stack. So I take a step back, and I'm thinking, Wow- the only set of conversation I really prior was not having, is about services. And to me, services is like the wrapping paper, for a present that you're about to receive. And really understanding the overall, end-to-end stack infrastructure. So, I believe from an IBM perspective, it's the ecosystem. It's a great big candy store. Just don't eat too much. >> Haha. So, how do you spend your time? Do you spend your time thinking, collaborating with team on, architecture, on, vision, on, northstar, writing code. How do you spend your time day-to-day? >> Can I say, all of the above? And, the vast majority, right now, really just making sure we're relevant in the marketplace, so that we re-fresh the right amount of cycles. So, right now, what we're going to be doing in 2019, we're going to be talking about it right now. Architecting what the future looks like. And that's part of the reason why I'm here at VM World 2018, is I'm wanting to verify my roadmap. Am I taking the right approach with the extended team? Cuz it is team, and I work with them. These engineers and scientists are so right, and have great ideas. Let's just make sure they're great ideas that will keep us relevant and keep us paid. >> So, have you gotten that validation, in the last few days at VM World? >> Give me one more day. >> Haha. Well, Calline, thanks so much for stopping by and sharing. Not only what IBM is doing to continue to innovate and stay relevant, but also what's exciting to you- >> Yeah. >> About working for IBM, and again, Congrats on getting the award. >> Yes, and thank you very much for highlighting that, cuz it's, I'm very excited as just an individual, it's like, it was unexpected. >> Well, you're representing women in tech, women in STEM, it's awesome, congratulations. >> Thank you very much. >> We're really happy. >> And, by the way, I'll definitely reach out to your daughter at some point. >> Oh, great. >> Say, hey, let's go to a tailgate. >> Love it. >> I won't corrupt. >> Haha. Fantastic, Calline, thank you so much for your time. I'm Lisa Martin with Dave Vellante. We want to thank you for watching the Cube, we are in day three of our continue coverage from VM World 2018. Stick around, we'll be right back with our next guest.

(upbeat techno music) >> Announcer: Live from Las Vegas, it's theCUBE covering InterConnect 2017, brought to you by IBM. >> Okay, welcome back, everyone. We are here live in Las Vegas for IBM InterConnect 2017. This is theCUBE's coverage of IBM InterConnect. I'm John Furrier, my cohost, Dave Vellante. We have Calline Sanchez, Vice President of IBM Enterprise, Storage Development at IBM. We had an interview at VMworld last year about tape, making tape cool. Great to see you again. >> Thank you. Thank you for welcoming me back, so I guess I wasn't too bad last time. >> No, you're good. >> Calline: Right? >> We love tapes. The tape culture out there, there's a tape community. >> Calline: Yes! >> Tape has been dead forever. It's going to die this year is what everyone always predicted. They're going to die next year. It never dies. Tape it always around, and Dave and I, you know, we see this all the time. >> Calline: Yeah, it's back. >> It's cool. It's relevant, and it's the east expensive storage... >> That is correct. >> Out there. So what's the update? What's cool about tape this year? >> So, I think when I was speaking to you earlier, you talked about flape, what we're doing with Flash and actual tape. So in partnership with our micro-coders, our engineers and scientists we partner with in Tucson, Arizona, with a team in Zurich in research, to really figure out what we're doing with flape. And by the way, flape is a cool name, right? It's a very developer name. >> Well, you know, Wikibon coined that term. That was David Floyer. >> Oh, really. >> The Flash plus tape. Yes. But the premise was that there's not a lot of innovation going on in disc drive heads. >> Calline: Correct. >> And they're hermetically sealed, whereas in tape, you can do a lot more, more bandwidth, and you can do some cool stuff with search, right? >> Yes. >> And new tape formats. >> Calline: Right. >> Right, so that's all coming together, and are you... Is there software now associated with that index so you can more quickly search? >> So we have created a management layer that supports what we intend with flape, and also across the tape portfolio to really consume applications at a higher level to enable what we need to do with our consumability, not only from a tape perspective, but also with Flash. >> Right, so the economics really still favor tape. Flape, Flash supports the speed, so it starts to encroach on some of that long-term archiving. >> Which is important based on archive, 'cause, well, aren't we all data hoarders? We like to keep our data and archive it and stage it off, whatever it is. It could be based on what we're doing with tape and also, you know, hard disc drives. Some clients that I work with substantiate archive data to cheap drives as well. So hopefully, eventually, the transition will be to enable what we want to do with Flash, once Flash of course is a cheaper or a stronger price competitive thing. So, bridging though to, from our last conversation, believe me, tape is sexy, so I'm telling the audience here, it's like, hello, if you're not talking about tape, well, where have you been? But at the same time, I want to talk about Flash, and what we do with DS8000. So we have an enterprise monolithic system that covers like six nines of availability, that substantiates what we do in the Flash market, and we just recently announced, from enterprise down to entry, so mid-range as well as entry devices, that are all Flash. So we care more, from an IBM perspective, on what we're doing associated with the Flash investment. Friends of mine like Erik Herzog, I'm sure, get on stage with you to talk about like, IBM is focusing on Flash. It's relevant to us. It's relevant to our clients. >> And the software, too. Very software-driven. Flash is key, but you're bringing this capacity at this... What was it, six nines? >> Yep. >> I mean... >> It's reliability. >> I mean that's just like, just dump all the data. That's a perfect scenario. >> Yes, and it's a beautiful thing. In addition to what Flash does, from an engineering perspective... Forgive me, I'm going to be a geek for a moment, is that it allows us to in the lab to focus on other things, so basically, that latency or the chase for performance equals more, more meaning that we can focus more on what it means to develop optimizers, like, for instance, EasyTier, et cetera, to really enable a better benefit. Also some of those engineers and scientists allow us to focus more on flape as well. >> So explain that concept. Okay, latency equals more. What specifically do you mean, like the latency on the devices, \the data movement, just double down on that for a second. >> So, from a performance perspective, we have to work around bottlenecks. That was where our focus was, but now, with Flash, we worry less about those individual components from a reliability perspective as well as chasing latency or performance measurements based on IOPS, and in order to do that, we don't have to worry about it as much anymore from an engineering standpoint. So it allows us the time to really focus on what matters next, like the value that we could think of that we could benefit clients with regards to advanced technologies, technologies of value. >> Like what? What does that free you? It liberates both creativity... >> Calline: Data and analytics. >> Really, okay. >> Calline: So like, for instance, the expo floor associated with Interconnect, you meet all these people that talk about how data matters. Well, it's the intelligence around data, and so we want to figure out how to harness that data and drive out the intelligence so that the smarts associated with the data, and that's what it allows us to talk about. >> Yeah, so let's keep on that theme of business impact, we were talking about latency before. Everybody knows Flash is fast. You're implying, or I'm inferring from your statements that it's still more expensive. >> Calline: Correct. >> However, you got data reduction technologies and you have this data sharing notion. In other words, I can share much more data with the same copy out of a Flash. That has an impact on developer productivity, which ripples through on innovation. >> Calline: Yes, correct. >> Are you seeing that have business impacts within your client base? >> Yes. So, for instance, at first, we started to talk about, from an engineering perspective, compression and deduplication, how to be much more efficient with that data storage. And then afterwards, we started to talk about, well, you know, we had to move quickly to serve our clients associated with those feature functions, and now we're about talking about how we harness or archive, you know, how we enable big data, and also the IT aspect, the intelligence of the data, and how we can translate that to improving client value. For example, I just saw on the expo floor, partnered with Glassbeam, and with the... I did basically a meeting with Glassbeam on the floor to talk about what we've done with them in partnership to harness the power of data. >> Dave: What is Glassbeam? >> So Glassbeam is basically makes sense of the mess of data that we just have out there and makes it much more intelligent. So, it allows their system, their algorithms, to ingest data and better understand where we're at with that data, no different than what we do with Watson as well. So, that, from a Watson perspective, you ingest the data and you can provide additional smartness about that data as well as the intelligence of. >> And what kind of data are we talking about here? Structured data, unstructured data? >> Structured data, and specifically associated with Glassbeam, it was all about really bringing in the plumbing of data for our clients worldwide. So, clients experience our systems worldwide associated DS8000, and we wanted to better be in a position to serve our clients adequately, and what I mean by that is they could have an error that occurred or we want to be proactive with them based on Call Home, and also some of the heartbeat information we get based on the systems, and we want to adequately share with them that. So, you as a client could, I could send you a really beautiful, simple email or communication, maybe it's a tweet that basically says, hey, there's something we're worried about, and we've got to proactively address it, ASAP. >> Well, and there's all kinds of metrics buried in those files, right? There's utilization data, there's data on the effectiveness of thin provisioning, you mentioned compression, deduplication... >> Calline: Yes. >> I mean, I don't know what else is in there. It's probably a ton more stuff, obviously problems that occur. So have you been able to get to the point where you could be anticipatory and head off, you know, front run some of those problems? >> So our end goal is to build an autonomic system, an autonomic system that has the brain to self-heal, and that's what we want to focus on in the future. Now, are we there yet? No, we're not, but what we're doing with Watson or Glassbeam or some of these optimizers, these tools, to build better systems, it something that we're doing associated with building the future of an autonomic system. >> I mean, one of the things John and I have been talking about with this, you know, Jenny was talking about cognitive to the core this morning... >> Yep. >> And this cognitive world we live in. >> Just a whole new set of metrics emerging and KPIs. I mean, you mentioned self-healing. We still, to this day track, availability, and okay, the light on the server versus the application, things like that. >> Calline: Yeah. >> We see, and I wonder if you could comment on this, a whole new set of KPIs emerging from the infrastructure standpoint of, you know, what percent of the problems were self-healed... >> Calline: Yes. >> How can we affect that and increase that and what are we doing with that free time? Are you hearing from that clients, that they're changing or adding to the metrics, KPIs that they're entering? >> Yes, so first, am I hearing from clients on that? Yes. So it's always these questions of like, okay, so from a cognition perspective, cognitive focus, what are you going to do to help us to self-heal as well as how do you build in the intelligence based on artificial intelligence to really self-heal, and that's one of the focuses we're working on. >> So what's the coolest thing happening now, 'cause last time, I loved the conscious we had about capacity and stuff that I learned was all the engineering, just to squeeze more out of... 'Cause the tape is a great thing, but reliability is killer. You got some great reliability, so it's a good solution, but there's always the engineering side of it that's science. What's going on that you guys are kind of digging away at, pounding away at for tech that people might not know about for tape? >> So, using the cognitive systems or AI as the foundation, we're thinking about how to build in intelligence within our systems, and the way to do that is the reason why I keep focusing on this word, autonomic. How do we build a true autonomic system? It's almost like a system that has its own brain, right? And that chip set that exists inside associated with DS8000 is like power devices, right, whether it's six-core, eight-core, whatever, how big of a brain do you want is kind of a discussion to have, but what's important about that is we really want to figure out how to be smart enough to self-heal, and we don't know how to do that just yet, and it's going to be, just like you had mentioned, all this information and pulling it in to really determine how we go about doing so. >> So that's kind of near-term, those are sort of... Maybe in the binoculars you can start to see how you can utilize analytics and cognitive to do some of that self-healing. I wanted to ask you a sort of telescope question. We heard Jenny talk today about quantum. What are your thoughts on that in terms of the implications for storage? >> My thoughts on quantum. So first of all, let's figure out how to harness the science of quantum computing, right? So that's the first fundamental step, like, I don't know, first step of the twelve-step problem, realizing you have a challenge, right? (Dave laughs) So, from that, it's like really realize that and recognize that, and IBM is working on what we're doing with quantum computing. As far as how it relates specifically to storage, so, we think it could be a benefit with relates to DS8000 tape as well, because think about it. Tape, as far as the library side, that's what we did is we built out infrastructure that really harnessed this aspect of data and did it in the cheapest way possible, energy-efficient way possible, so I think quantum, from our perspective, is like a leapfrog into the future of what we enable with some of our thinking there. And Jenny and team as well as her senior leadership are influencing how we should think about quantum computing as it relates to storage. So, I say the next time that we meet, you should probably ask that question of me again, like how far along are you? >> Dave: Deal. >> Step one and a half or two of the twelve-step program? >> I would say one and a half. >> Dave: Go ahead, sorry. >> No, go ahead. >> I wanted to ask you about when Ed Walsh took over. >> By the way, I like the two of you competing on questions. (all laugh) >> We both like to talk. >> We can't get enough tape. (all laugh) >> We have tape everywhere, look at it. Taping down the lights... >> So, here's my question, Calline. So when Ed Walsh took over the GM of the Storage Division, I asked him this. IBM's always had a rich heritage of R&D and development. However, my comment was, sometimes it was sort of development for development's sake, and I feel like, and he sort of said this. One of my missions is to get, you know, align engineering with, you know, go to market, get stuff out of the pipeline, into the market sooner. From an engineering perspective, have you guys begun to do that? What changes have you affected? Are you seeing the effects of that sort of initiative? >> So, when have an agility process within IBM Development that was, basically Ed Walsh was a huge advocate for that, supported it, and his intent is for us the push all of this wonderful IP that we build in-house to the marketplace as quickly as possible. So I say at this moment, we're there. I just, right now, he's, in the nicest way possible, and the most charming way, telling me, it's like, you're not fast enough. (men laugh) Right? And that's a good thing. That means that there's more innovation, more intellectual property we can put into the marketplace, faster, quicker whatever that means, in larger increments, versus it being me... Previously, I would tell you, it's like, so DS8000, I may deliver that to you, target-wise, 12 months from now. That's not good enough anymore. >> So Ed's coming on tomorrow, so we'll ask him how Calline's doing maybe. (all laugh) We'll put him on the spot and you on the spot at the same time, if you don't mind. >> Oh yeah, no problem. >> Calline, it's always great to chat with you, love these conversations, thanks for coming on theCUBE, sharing the insights on the tape, the DS8000. Appreciate it. >> Thank you very much. >> And it's theCUBE live here in Las Vegas for IBM InterConnect. I'm John Furrier with Dave Vellante. You're watching theCUBE. Stay with us, we've got more great interviews for the rest of the day and all day tomorrow. We'll be right back. (upbeat techno music)