(upbeat music) >> Welcome back to HPE Discover 2021, theCUBE's virtual coverage, continuous coverage of HPE's Annual Customer Event. My name is Dave Vellante, and we're going to dive into the intersection of high-performance computing, data and AI with Doctor Eng Lim Goh, who's a Senior Vice President and CTO for AI at Hewlett Packard Enterprise. Doctor Goh, great to see you again. Welcome back to theCUBE. >> Hello, Dave, great to talk to you again. >> You might remember last year we talked a lot about Swarm intelligence and how AI is evolving. Of course, you hosted the Day 2 Keynotes here at Discover. And you talked about thriving in the age of insights, and how to craft a data-centric strategy. And you addressed some of the biggest problems, I think organizations face with data. That's, you've got a, data is plentiful, but insights, they're harder to come by. >> Yeah. >> And you really dug into some great examples in retail, banking, in medicine, healthcare and media. But stepping back a little bit we zoomed out on Discover '21. What do you make of the events so far and some of your big takeaways? >> Hmm, well, we started with the insightful question, right, yeah? Data is everywhere then, but we lack the insight. That's also part of the reason why, that's a main reason why Antonio on day one focused and talked about the fact that we are in the now in the age of insight, right? And how to try thrive in that age, in this new age? What I then did on a Day 2 Keynote following Antonio is to talk about the challenges that we need to overcome in order to thrive in this new age. >> So, maybe we could talk a little bit about some of the things that you took away in terms of, I'm specifically interested in some of the barriers to achieving insights. You know customers are drowning in data. What do you hear from customers? What were your takeaway from some of the ones you talked about today? >> Oh, very pertinent question, Dave. You know the two challenges I spoke about, that we need to overcome in order to thrive in this new age. The first one is the current challenge. And that current challenge is, you know, stated is now barriers to insight, when we are awash with data. So that's a statement on how do you overcome those barriers? What are the barriers to insight when we are awash in data? In the Day 2 Keynote, I spoke about three main things. Three main areas that we receive from customers. The first one, the first barrier is in many, with many of our customers, data is siloed, all right. You know, like in a big corporation, you've got data siloed by sales, finance, engineering, manufacturing and so on supply chain and so on. And there's a major effort ongoing in many corporations to build a federation layer above all those silos so that when you build applications above, they can be more intelligent. They can have access to all the different silos of data to get better intelligence and more intelligent applications built. So that was the first barrier we spoke about, you know? Barriers to insight when we are awash with data. The second barrier is that we see amongst our customers is that data is raw and disperse when they are stored. And you know, it's tough to get at, to tough to get a value out of them, right? And in that case, I use the example of, you know, the May 6, 2010 event where the stock market dropped a trillion dollars in terms of minutes. We all know those who are financially attuned with know about this incident but that this is not the only incident. There are many of them out there. And for that particular May 6 event, you know, it took a long time to get insight. Months, yeah, before we, for months we had no insight as to what happened. Why it happened? Right, and there were many other incidences like this and the regulators were looking for that one rule that could mitigate many of these incidences. One of our customers decided to take the hard road they go with the tough data, right? Because data is raw and dispersed. So they went into all the different feeds of financial transaction information, took the tough, you know, took a tough road. And analyze that data took a long time to assemble. And they discovered that there was caught stuffing, right? That people were sending a lot of trades in and then canceling them almost immediately. You have to manipulate the market. And why didn't we see it immediately? Well, the reason is the process reports that everybody sees, the rule in there that says, all trades less than a hundred shares don't need to report in there. And so what people did was sending a lot of less than a hundred shares trades to fly under the radar to do this manipulation. So here is the second barrier, right? Data could be raw and dispersed. Sometimes it's just have to take the hard road and to get insight. And this is one great example. And then the last barrier has to do with sometimes when you start a project to get insight, to get answers and insight, you realize that all the data's around you, but you don't seem to find the right ones to get what you need. You don't seem to get the right ones, yeah? Here we have three quick examples of customers. One was a great example, right? Where they were trying to build a language translator or machine language translator between two languages, right? By not do that, they need to get hundreds of millions of word pairs. You know of one language compare with the corresponding other. Hundreds of millions of them. They say, well, I'm going to get all these word pairs. Someone creative thought of a willing source and a huge, it was a United Nations. You see? So sometimes you think you don't have the right data with you, but there might be another source and a willing one that could give you that data, right? The second one has to do with, there was the sometimes you may just have to generate that data. Interesting one, we had an autonomous car customer that collects all these data from their their cars, right? Massive amounts of data, lots of sensors, collect lots of data. And, you know, but sometimes they don't have the data they need even after collection. For example, they may have collected the data with a car in fine weather and collected the car driving on this highway in rain and also in snow. But never had the opportunity to collect the car in hill because that's a rare occurrence. So instead of waiting for a time where the car can drive in hill, they build a simulation by having the car collected in snow and simulated him. So these are some of the examples where we have customers working to overcome barriers, right? You have barriers that is associated. In fact, that data silo, they federated it. Virus associated with data, that's tough to get at. They just took the hard road, right? And sometimes thirdly, you just have to be creative to get the right data you need. >> Wow! I tell you, I have about a hundred questions based on what you just said, you know? (Dave chuckles) And as a great example, the Flash Crash. In fact, Michael Lewis, wrote about this in his book, the Flash Boys. And essentially, right, it was high frequency traders trying to front run the market and sending into small block trades (Dave chuckles) trying to get sort of front ended. So that's, and they chalked it up to a glitch. Like you said, for months, nobody really knew what it was. So technology got us into this problem. (Dave chuckles) I guess my question is can technology help us get out of the problem? And that maybe is where AI fits in? >> Yes, yes. In fact, a lot of analytics work went in to go back to the raw data that is highly dispersed from different sources, right? Assembled them to see if you can find a material trend, right? You can see lots of trends, right? Like, no, we, if humans look at things that we tend to see patterns in Clouds, right? So sometimes you need to apply statistical analysis math to be sure that what the model is seeing is real, right? And that required, well, that's one area. The second area is you know, when this, there are times when you just need to go through that tough approach to find the answer. Now, the issue comes to mind now is that humans put in the rules to decide what goes into a report that everybody sees. Now, in this case, before the change in the rules, right? But by the way, after the discovery, the authorities changed the rules and all shares, all trades of different any sizes it has to be reported. >> Right. >> Right, yeah? But the rule was applied, you know, I say earlier that shares under a hundred, trades under a hundred shares need not be reported. So, sometimes you just have to understand that reports were decided by humans and for understandable reasons. I mean, they probably didn't wanted a various reasons not to put everything in there. So that people could still read it in a reasonable amount of time. But we need to understand that rules were being put in by humans for the reports we read. And as such, there are times we just need to go back to the raw data. >> I want to ask you... >> Oh, it could be, that it's going to be tough, yeah. >> Yeah, I want to ask you a question about AI as obviously it's in your title and it's something you know a lot about but. And I'm going to make a statement, you tell me if it's on point or off point. So seems that most of the AI going on in the enterprise is modeling data science applied to, you know, troves of data. But there's also a lot of AI going on in consumer. Whether it's, you know, fingerprint technology or facial recognition or natural language processing. Well, two part question will the consumer market, as it has so often in the enterprise sort of inform us is sort of first part. And then, there'll be a shift from sort of modeling if you will to more, you mentioned the autonomous vehicles, more AI inferencing in real time, especially with the Edge. Could you help us understand that better? >> Yeah, this is a great question, right? There are three stages to just simplify. I mean, you know, it's probably more sophisticated than that. But let's just simplify that three stages, right? To building an AI system that ultimately can predict, make a prediction, right? Or to assist you in decision-making. I have an outcome. So you start with the data, massive amounts of data that you have to decide what to feed the machine with. So you feed the machine with this massive chunk of data, and the machine starts to evolve a model based on all the data it's seeing. It starts to evolve, right? To a point that using a test set of data that you have separately kept aside that you know the answer for. Then you test the model, you know? After you've trained it with all that data to see whether its prediction accuracy is high enough. And once you are satisfied with it, you then deploy the model to make the decision. And that's the inference, right? So a lot of times, depending on what we are focusing on, we in data science are, are we working hard on assembling the right data to feed the machine with? That's the data preparation organization work. And then after which you build your models you have to pick the right models for the decisions and prediction you need to make. You pick the right models. And then you start feeding the data with it. Sometimes you pick one model and a prediction isn't that robust. It is good, but then it is not consistent, right? Now what you do is you try another model. So sometimes it gets keep trying different models until you get the right kind, yeah? That gives you a good robust decision-making and prediction. Now, after which, if it's tested well, QA, you will then take that model and deploy it at the Edge. Yeah, and then at the Edge is essentially just looking at new data, applying it to the model that you have trained. And then that model will give you a prediction or a decision, right? So it is these three stages, yeah. But more and more, your question reminds me that more and more people are thinking as the Edge become more and more powerful. Can you also do learning at the Edge? >> Right. >> That's the reason why we spoke about Swarm Learning the last time. Learning at the Edge as a Swarm, right? Because maybe individually, they may not have enough power to do so. But as a Swarm, they may. >> Is that learning from the Edge or learning at the Edge? In other words, is that... >> Yes. >> Yeah. You do understand my question. >> Yes. >> Yeah. (Dave chuckles) >> That's a great question. That's a great question, right? So the quick answer is learning at the Edge, right? And also from the Edge, but the main goal, right? The goal is to learn at the Edge so that you don't have to move the data that Edge sees first back to the Cloud or the Call to do the learning. Because that would be the reason, one of the main reasons why you want to learn at the Edge. Right? So that you don't need to have to send all that data back and assemble it back from all the different Edge devices. Assemble it back to the Cloud Site to do the learning, right? Some on you can learn it and keep the data at the Edge and learn at that point, yeah. >> And then maybe only selectively send. >> Yeah. >> The autonomous vehicle, example you gave is great. 'Cause maybe they're, you know, there may be only persisting. They're not persisting data that is an inclement weather, or when a deer runs across the front. And then maybe they do that and then they send that smaller data setback and maybe that's where it's modeling done but the rest can be done at the Edge. It's a new world that's coming through. Let me ask you a question. Is there a limit to what data should be collected and how it should be collected? >> That's a great question again, yeah. Well, today full of these insightful questions. (Dr. Eng chuckles) That actually touches on the the second challenge, right? How do we, in order to thrive in this new age of insight? The second challenge is our future challenge, right? What do we do for our future? And in there is the statement we make is we have to focus on collecting data strategically for the future of our enterprise. And within that, I talked about what to collect, right? When to organize it when you collect? And then where will your data be going forward that you are collecting from? So what, when, and where? For what data to collect? That was the question you asked, it's a question that different industries have to ask themselves because it will vary, right? Let me give you the, you use the autonomous car example. Let me use that. And we do have this customer collecting massive amounts of data. You know, we're talking about 10 petabytes a day from a fleet of their cars. And these are not production autonomous cars, right? These are training autonomous cars, collecting data so they can train and eventually deploy commercial cars, right? Also this data collection cars, they collect 10, as a fleet of them collect 10 petabytes a day. And then when they came to us, building a storage system you know, to store all of that data, they realized they don't want to afford to store all of it. Now here comes the dilemma, right? What should I, after I spent so much effort building all this cars and sensors and collecting data, I've now decide what to delete. That's a dilemma, right? Now in working with them on this process of trimming down what they collected, you know, I'm constantly reminded of the 60s and 70s, right? To remind myself 60s and 70s, we called a large part of our DNA, junk DNA. >> Yeah. (Dave chuckles) >> Ah! Today, we realized that a large part of that what we call junk has function as valuable function. They are not genes but they regulate the function of genes. You know? So what's junk in yesterday could be valuable today. Or what's junk today could be valuable tomorrow, right? So, there's this tension going on, right? Between you deciding not wanting to afford to store everything that you can get your hands on. But on the other hand, you worry, you ignore the wrong ones, right? You can see this tension in our customers, right? And then it depends on industry here, right? In healthcare they say, I have no choice. I want it all, right? Oh, one very insightful point brought up by one healthcare provider that really touched me was you know, we don't only care. Of course we care a lot. We care a lot about the people we are caring for, right? But who also care for the people we are not caring for? How do we find them? >> Uh-huh. >> Right, and that definitely, they did not just need to collect data that they have with from their patients. They also need to reach out, right? To outside data so that they can figure out who they are not caring for, right? So they want it all. So I asked them, so what do you do with funding if you want it all? They say they have no choice but to figure out a way to fund it and perhaps monetization of what they have now is the way to come around and fund that. Of course, they also come back to us rightfully, that you know we have to then work out a way to help them build a system, you know? So that's healthcare, right? And if you go to other industries like banking, they say they can afford to keep them all. >> Yeah. >> But they are regulated, seemed like healthcare, they are regulated as to privacy and such like. So many examples different industries having different needs but different approaches to what they collect. But there is this constant tension between you perhaps deciding not wanting to fund all of that, all that you can install, right? But on the other hand, you know if you kind of don't want to afford it and decide not to start some. Maybe those some become highly valuable in the future, right? (Dr. Eng chuckles) You worry. >> Well, we can make some assumptions about the future. Can't we? I mean, we know there's going to be a lot more data than we've ever seen before. We know that. We know, well, not withstanding supply constraints and things like NAND. We know the prices of storage is going to continue to decline. We also know and not a lot of people are really talking about this, but the processing power, but the says, Moore's law is dead. Okay, it's waning, but the processing power when you combine the CPUs and NPUs, and GPUs and accelerators and so forth actually is increasing. And so when you think about these use cases at the Edge you're going to have much more processing power. You're going to have cheaper storage and it's going to be less expensive processing. And so as an AI practitioner, what can you do with that? >> Yeah, it's a highly, again, another insightful question that we touched on our Keynote. And that goes up to the why, uh, to the where? Where will your data be? Right? We have one estimate that says that by next year there will be 55 billion connected devices out there, right? 55 billion, right? What's the population of the world? Well, of the other 10 billion? But this thing is 55 billion. (Dave chuckles) Right? And many of them, most of them can collect data. So what do you do? Right? So the amount of data that's going to come in, it's going to way exceed, right? Drop in storage costs are increasing compute power. >> Right. >> Right. So what's the answer, right? So the answer must be knowing that we don't, and even a drop in price and increase in bandwidth, it will overwhelm the, 5G, it will overwhelm 5G, right? Given the amount of 55 billion of them collecting. So the answer must be that there needs to be a balance between you needing to bring all of that data from the 55 billion devices of the data back to a central, as a bunch of central cost. Because you may not be able to afford to do that. Firstly bandwidth, even with 5G and as the, when you'll still be too expensive given the number of devices out there. You know given storage costs dropping is still be too expensive to try and install them all. So the answer must be to start, at least to mitigate from to, some leave most a lot of the data out there, right? And only send back the pertinent ones, as you said before. But then if you did that then how are we going to do machine learning at the Core and the Cloud Site, if you don't have all the data? You want rich data to train with, right? Sometimes you want to mix up the positive type data and the negative type data. So you can train the machine in a more balanced way. So the answer must be eventually, right? As we move forward with these huge number of devices all at the Edge to do machine learning at the Edge. Today we don't even have power, right? The Edge typically is characterized by a lower energy capability and therefore lower compute power. But soon, you know? Even with low energy, they can do more with compute power improving in energy efficiency, right? So learning at the Edge, today we do inference at the Edge. So we data, model, deploy and you do inference there is. That's what we do today. But more and more, I believe given a massive amount of data at the Edge, you have to start doing machine learning at the Edge. And when you don't have enough power then you aggregate multiple devices, compute power into a Swarm and learn as a Swarm, yeah. >> Oh, interesting. So now of course, if I were sitting and fly on the wall and the HPE board meeting I said, okay, HPE is a leading provider of compute. How do you take advantage of that? I mean, we're going, I know it's future but you must be thinking about that and participating in those markets. I know today you are, you have, you know, Edge line and other products. But there's, it seems to me that it's not the general purpose that we've known in the past. It's a new type of specialized computing. How are you thinking about participating in that opportunity for the customers? >> Hmm, the wall will have to have a balance, right? Where today the default, well, the more common mode is to collect the data from the Edge and train at some centralized location or number of centralized location. Going forward, given the proliferation of the Edge devices, we'll need a balance, we need both. We need capability at the Cloud Site, right? And it has to be hybrid. And then we need capability on the Edge side that we need to build systems that on one hand is an Edge adapter, right? Meaning they environmentally adapted because the Edge differently are on it, a lot of times on the outside. They need to be packaging adapted and also power adapted, right? Because typically many of these devices are battery powered. Right? So you have to build systems that adapts to it. But at the same time, they must not be custom. That's my belief. It must be using standard processes and standard operating system so that they can run a rich set of applications. So yes, that's also the insight for that Antonio announced in 2018. For the next four years from 2018, right? $4 billion invested to strengthen our Edge portfolio. >> Uh-huh. >> Edge product lines. >> Right. >> Uh-huh, Edge solutions. >> I could, Doctor Goh, I could go on for hours with you. You're just such a great guest. Let's close. What are you most excited about in the future of, certainly HPE, but the industry in general? >> Yeah, I think the excitement is the customers, right? The diversity of customers and the diversity in the way they have approached different problems of data strategy. So the excitement is around data strategy, right? Just like, you know, the statement made for us was so was profound, right? And Antonio said, we are in the age of insight powered by data. That's the first line, right? The line that comes after that is as such we are becoming more and more data centric with data that currency. Now the next step is even more profound. That is, you know, we are going as far as saying that, you know, data should not be treated as cost anymore. No, right? But instead as an investment in a new asset class called data with value on our balance sheet. This is a step change, right? Right, in thinking that is going to change the way we look at data, the way we value it. So that's a statement. (Dr. Eng chuckles) This is the exciting thing, because for me a CTO of AI, right? A machine is only as intelligent as the data you feed it with. Data is a source of the machine learning to be intelligent. Right? (Dr. Eng chuckles) So, that's why when the people start to value data, right? And say that it is an investment when we collect it it is very positive for AI. Because an AI system gets intelligent, get more intelligence because it has huge amounts of data and a diversity of data. >> Yeah. >> So it'd be great, if the community values data. >> Well, you certainly see it in the valuations of many companies these days. And I think increasingly you see it on the income statement. You know data products and people monetizing data services. And yeah, maybe eventually you'll see it in the balance sheet. I know Doug Laney, when he was at Gartner Group, wrote a book about this and a lot of people are thinking about it. That's a big change, isn't it? >> Yeah, yeah. >> Dr. Goh... (Dave chuckles) >> The question is the process and methods in valuation. Right? >> Yeah, right. >> But I believe we will get there. We need to get started. And then we'll get there. I believe, yeah. >> Doctor Goh, it's always my pleasure. >> And then the AI will benefit greatly from it. >> Oh, yeah, no doubt. People will better understand how to align, you know some of these technology investments. Dr. Goh, great to see you again. Thanks so much for coming back in theCUBE. It's been a real pleasure. >> Yes, a system is only as smart as the data you feed it with. (Dave chuckles) (Dr. Eng laughs) >> Excellent. We'll leave it there. Thank you for spending some time with us and keep it right there for more great interviews from HPE Discover 21. This is Dave Vellante for theCUBE, the leader in Enterprise Tech Coverage. We'll be right back. (upbeat music)

>> Introducer: From the CUBE studios in Palo Alto and in Boston connecting with thought leaders all around the world. This is a CUBE Conversation. >> Hi everybody this is Dave Volante. Welcome to the special CUBE Conversation. I'm really excited to invite in my mentor and friend. We go way back. Fred Moore is here. He's the president of Horizon Information Strategies. We going to talk about managing data in the zettabyte era. Fred, I think when we first met, we were talking about like the megabyte era. >> Right, exactly. I think back then we had, you know, maybe 10 bytes in our telephone and one on the wristwatch, you know, but now you can put a whole data center in a single cartridge of tape and take off. Things that really changed. >> It's pretty amazing. And of course, for those who don't know Fred, he was the first a systems engineer at Storage Tech. And as I said, somebody who taught me a lot in my early days, of course he's very famous for the term that everybody uses today. Backup is one thing, recovery is everything. And Fred just wrote, you know, this fantastic paper. He's done this year after year after year. He's just dug in, he's a clear thinker, strategic planner with a technical bent in a business bent. You're like one of those five tool baseball players, Fred. But tell me about this paper. Why, did you write it? >> Well, the reason I wrote that is there's been so much focus in the last year or so on the archive component of the storage hierarchy. And the thing that's happening, we're generating data lots faster than we're analyzing it. So it's piling up being unanalyzed and sitting basically untapped for years at a time. So that has posed a big challenge for people. The other thing that got me deeper into this last year was the Hyperscale market. They are, those people are so big in terms of footprint and infrastructure that they can no longer keep everything on disk. It's just economically not possible. The energy consumption per disk, the infrastructure costs, the frequency of, you know, taking a disc out every three, four or five years for just for replacement, has made it very difficult to do that. So Hyperscale has gone to tape in a big way, and it's kind of where most of the tape business in the future is going to wind up in these Hyperscale businesses. >> Right. >> We know tape doesn't exist in the home. It doesn't exist in a small data center. It's only a large scale data center technology, but that whole cosmos led me into the archive space and in a need for a new archive technology beyond tape. >> So, I want to set up the premise here. Just going to pull this out of your paper. It says a 60% of all data is archival, and could reach 80% or more by 2024, making archival data by far the largest storage class. And given this trajectory, the traditional storage hierarchy paradigm is going to to need to disrupt itself. And quickly we're going to talk about that. That really is the premise of your paper here, isn't it? >> It is, you know, to do all this with traditional technologies is going to get very painful for a variety of reasons. So the stage is set for a new tier and a new technology to appear in the next five years. Fortunately, I'm actually working with somebody who is after this in a big way, and in a different way than what you and I know. So I think there is some hope here that we can redefine and really add a new tier down at the bottom. You see it kind of emerging on that picture of the deep archive tier it's. Beginning to show up now and it's, you know, infinite storage. I mean, if you look at major league sports, the world series and Superbowl, you know, that data will never be deleted. It'll be here forever. It'll be used periodically based on circumstances. >> Yeah, well, we've got that pyramid chart up here. I mean, you invented this chart, essentially. At least you were the first person that ever showed it to me. I honestly think that you first created this concept where you had a high performance tier, and a high cost per bit, and then an archive tier. Maybe it wasn't this granular, you know, back in the '70s and '80s? But it's constantly been changing with different media types and different use cases. >> You know, you're right. I mean, and you all know this because you know, when storage deck introduced the nearline architecture, nearline set in between online and offline storage, we called it nearline, and trademarked that term. So that was the tape library concept to move data from offline status to online status, with a robotic library. So that brought up that third tier online, nearline, and offline, but you're right. This pyramid has evolved and morphed into several things. And, you know, I keep it alive. Somebody said, I'll have a pyramid on my tombstone instead of my name when I go down. (both chuckles) But it's really the heart and soul of the infrastructure for data. And then out of this comes all the management and security, the deletion, the immutable storage concepts, the whole thing starts here. So it's like your house, you got to have a foundation, then you can build everything on top of it. >> Well, and as you pointed out in your paper, a minute ago, it always comes down to economics. So I want to bring up the sort of 10 year expected cost of ownership the TCO for the three levels you got all disk, you got all cloud and you got LTO and you got the different aspects of the cost. The purple is always the biggest piece of cost. It's the labor costs. But of course, you know, in cloud, you've got the big media cost because they've done so much automation. I wonder if you could take us through this slide, what are the key takeaways there? >> Well, you know the thing that hurts here with all these technologies is, as you can see up on top up there, what the key issues are with this and the staff and personnel. So the less people you have to manage data, the better off you are. And then, you know, it's pretty high for disk compared to a lot of things to do on desk, but lack of manage a lot of, you know, sadly what you and I had to deal with years ago and provision kind of, I mean, a lot of this stuff is just labor intensive. The further you get, the further down the pyramid and you also get less labor intensive storage. And that helps then you get a lower cost for energy and cost of ownership. The TCO thing is kind of taking on a new meaning. I hate to put up a TCO chart in some regards, because it's all based on what your input variables are. So you can decide something different, but we've tried to normalize all kinds of pricing and come up with everything. And the cloud is a big question for most people as to how does it stack up. And if you don't ever touch the data in the cloud, you know, the price comes way down. If you want to start moving data in and out of the cloud, you're going to have to ante up in a big way like that. But, you know we're going to see dollar a terabyte storage prices down at the bottom of this pyramid here in the next five years. But hey, you can get down to four or five terabyte with drives media in libraries tape, just entire flash and certainly higher than that. But you know, we're going to have the race to a dollar a terabyte, total TCO cost here in 2025. >> So when Amazon announced, they just announced a glacier. Everybody said, okay, what is that? Is that tape is that, you know, this spun down disk, cause it took a while to get it back. But you're kind of seeing that tape technology as you said, really move into the Hyperscale space and that's going to accommodate this massive, you know, lower part of the pyramid, isn't it? >> Exactly. Yeah. And we don't have a spin down disk solution today. I was actually on the board of a company that started that called Copay and years ago, right up here near Boulder. >> You watch him (both chuckles) You absolutely right. And a few other people that, you know also, but the spin down disk never made it. And you know, you can spin up and down on a desk on your desktop computer, but doing that in a data center, then on a fiber channel drive never made it. So we don't have a spin down disk to do that. The archive space is kind of dominated by very high capacity disc and then tape. And most of the archive data in the world today, unfortunately sits on display. It's not used and spinning seven by 24, three 65 and not touch much. So that's a bad economic move, but customers just found that easier to handle by doing that then going back to tape. So we've got a lot of data stored in the wrong place from a total economics point of view. >> But the Hyperscalers are solving this problem, or they're not through automation. And, you know, you referenced storage, tiering, really trying to take the labor cost out. How are they doing? Are they doing a good job? >> They've done really well taking the labor costs down, I mean, they have optimized every screw, nut and bolt in the 42 chassis that you could imagine to make it as clean as possible to do that. So they've done a whole lot to bring that cost down, but still the magnitude of these data centers, we're going to finish the year 2020 with about 570 Hyperscale data centers. So it's going right now around the world. You know, each one of these things is 350 400,000 square feet, and up of race wars space. And the economics just don't allow you to keep putting inactive data on spinning disk. We don't have to spin down disk, tape You know, I feel like the only guy in the industry that says this sometimes, but, you know, tapes had a, you know, a renaissance. That people don't appreciate in terms of reliability, throughput, you know, tapes three orders of reliability higher than disc right now. And most people don't know this. So tape's viable, the Hyperscalers see that. And read one Hyperscalers or you know, by over a million pieces of LTO tape last year alone. Just to handle this, you know, be the pressure valve to take all of this inactive stuff off of the gigantic disc farms that they have. >> Well, so let's talk about that a little bit. So you just try to keep it simple. You've got, you know, flash disk and tape. It feels like disc is getting squeezed. We know what flash has done in terms of eating into disc. And you see in that, in the storage market generally, it's soft right now. And I've posited that a lot of that is the headroom that data centers have with flash, is they don't have to buy spindles anymore for performance reasons. And the market is soft. Only pure is showing consistent growth, and ends up a little bit, cause because of mainframe, you've got Dell popping back and forth, but generally speaking, the primary storage market is not a great place to be right now, all the actions and sort of secondary storage and data protection. And so just going to get squeezed, and you mentioned tape, you said that if your only person talking about it, but you said in your paper, you know, it's sequential. So time to first bite is, is sometimes problematic, but you can front end a tape with cash. You can use algorithms and, you know, smart scans and to really address that problem. And dramatically lower the cost. Plus you could do things like you tell me Fred, you're the technologists here, but you're going to have multiple heads things that you can't necessarily do in a hermetically sealed disc drive. >> (chuckles) You can. And what you just described is called the active archive layer in the pyramid. So when you front end a tape library with a disk array for a cash buffer, you create an active archive and that data will sit in there three or four or five days before it gets demoted based on inactivity. So, you know for repetitive use and you're going to get dislike performance for tape data, and that's the same cash in concept that deserve systems had 30 years ago. So that does work and the active archive has got a lot of momentum right now. There's right here near me, where I live in Boulder. We have the Active Archive Alliances headquarters, and I get to do their annual report every year. And this whole active archives thing is a big way to make and overcome that time, the first bike problem that we've had in tape. And we'll have for quite a while. >> In your paper, you've talked about some of the use cases and workloads and you laid out, you know basically taking the pyramid and saying, okay based on the workload, some certain percentage should be up at the top of the pyramid for the high performance stuff. And of course lower for the, you know, the less, you know, important traditional workloads, et cetera. And it was striking to see the Delta between annual, the highest performance we had 70% , I think was up in the top of the pyramid versus, you know the last use case. So in you're talking about what it costs to store a zettabyte in services is that if I talk about 108 million at the high end versus a about 11 or 12 million, so huge Delta 10 X Delta between the top and the bottom based on those, you know allocations based on the workload. >> Yeah, I tried to get at the value of tiered storage based on your individual workload in your business. So I looked at five different workloads, the top one that you referenced. That was in there at 108 million, you know, is the HPC market. I mean, when I visited a few of the HPC people, you know, their DOD agencies in many cases, you know that and I threw the pyramid up. The first thing they would say our permanents inverted. You know (chuckles), all of our archive data is about 10%. You know, we were all flash as much as we can. And we have a little bit archived, we're in constant. Simulation and compute mode and producing results like crazy from the data. So we do an IO, bring in maybe a whole file at a time and compute for minutes before we come up with an answer. So just the reverse. And then I got to look into all the different workloads talking to people, and that's how we develop these profiles. >> So let's pull up this future of the storage hierarchy, was again kind of of talks to the premise of your paper. Walk us through this like, what changes should we be expecting, and you got air gap in here. We're going to, I'm going to ask you about remastering and lifespan, but take us through this. >> Yeah, you know, the traditional chart that you had up on the first big year had four tiers, you know, two disturbs and solid state at the top. And then the big archive tier, which is kind of everything falling down into tape at this point. But you know again, tape has some challenges. You know time to first bite and sequential access on. And then when we couple using tape or disc as an archive, most of that data that's archival is captured as unstructured data. So we don't have, we don't have tags, we don't have metadata, we don't have indices, and that has led to the movement for object storage, to be a primary, maybe in the next five years, the primary format in store archived data, because it's got all that information inside of it. So now we have a way to search things and we can get to objects, but in the interim, you know, it's hard to find and search out things that are unstructured and, you know, most estimates would say 80% of the world's data is at least that much is unstructured. So archives are hard to find once you store it, there's one storing is one thing, retrieving it is another thing. And that's led to the formation of another layer in the story tier. It's going to be data that doesn't have to be remastered or converted to a new technology. in the case of the disc, every three, four or five years or tape drive every eight, maybe 10 years take large lost. Kate Media can go 30 years, but with all new modern tape media, but unfortunately, you know, the underlying drive doesn't go back that far, you can't support that many different versions. So the media life is actually longer than it needs to be. So the stage is set for a new technology to appear down here to deal with this archives. So it'll have faster access will not need to be remastered every five or 10 years, but you'll have, you know, a 50 year life in here. And I believe me, I've been looking for a long time to be able find something like this. And, you know we have a shot at this now, and I'm actually working with the technology that could pull this off. >> Well, it's interesting also as well, you calling out the air gap and the chart we go back to our mainframe guesses, is not a lot we haven't seen before, you know, maybe data D duplication, but you know, the adversary has become a lot more sophisticated. And so air gaps and, you know, ransomware on everybody's mind today, but you've sort of highlighted three layers of the pyramid that are actually candidates for that air gapping. >> Yeah. The active archive up there, of course, you know, with the disk and tape combined, then just pure tape. And then this new technology, which can be removable. You know, when you have removability you create an air gap. little did we know when you and I met that removability would be important to take. We thought we were trying to get rid of the Chevy truck access method, and now without electricity with a terrorist attack and pandemic or whatever. The fastest way to move data is put it on a truck and get it out of town. So that has got renewed life right now. Removability much to my shock from where we started. >> You talked about remastering and you said it's a costly labor intensive process that typically migrates previously archived data to new media every five to 10 years. First of all, explain why you have to do that and how a data center operators can solve that problem. >> Yeah. And let's start with data where most of it sits today on described, you know it describes useful life is four to five years before it either fails or is replaced. That's pretty much common now. So then they have to start replacing these things. And that means you have to copy, you know, read the data off the disk and write it somewhere else, big data move. And as the years go by that amount of data to revamp or gets bigger and bigger. So, I mean, you can do the math as you well know, you want to move, you know, 50 petabytes of data. It's going to take several weeks to do that electronically. So this gets to be a real time consuming effort. So most data centers that I've seen will keep about one fifth of their disposal every year migrating to a new technology, just kind of rolling forward as they go like that rather than do the whole thing every five years. So that's the new build in the disc world. And then for tape the drive stay in there longer, you know the LTO family drives a good read. You know two generations back from the current one that's been there. They cut that off a year ago. They'll go back to something like this soon. But you know, you can go into 10 years on a tape drive. The media life because of very unfair right media, which was already oxidized the last 30 years or more. The old media metal particle was not oxidized. So, you know, the oxidized flake, the particles would fall off people will say shit. I've had this in here eight years, you know, and it's kind flake it I put it back in. So that didn't work well. But now that we had various Verite Media, it was all oxidized, the media lives skyrocket. So that was the whole trick with tape to get into something that was preoxidized before time could cause it to decay. So the remastering is a lot, is less on tape by two to one to three to one, but still when you've got petabytes, maybe an exabyte sitting on tape in the future, that's going to take a long time to do that. >> Right. >> So remastering you'd love a way to scale capacity without having to continue to move the data to something new ever so often. >> So my last question is you've , you know, you went from a technical role into a strategic planning role, which of course the more technical you are in that role, the better off you're going to be. You don't understand that the guardrails, but you've always had a sort of telescope in the industry and you close the paper and it's kind of where I want to end here on, you know, what's ahead. And you talk about some of the technologies that obviously have legs, like three D NAND and obviously magnetic storage. You got optical in here, but then you've got all these other ones that you even mentioned, you know, don't hold your breath waiting for these multilayer photonics and dedic DNA. What class media, holographic storage, quantum storage we do a lot about quantum. What should we be thinking about and expecting as observers as to, you know, new technologies that might drive some innovation in the storage business? >> Well, I've listed the ones that are in the lab that have any life at all, right on this paper. So, you know can kind of take your pick at what goes on there. I mean, optical disk has not made it in the data center. We talked about it for 35 years. We invested in it in storage deck and never saw the light of day. You know, optical disk has remained an entertainment technology throughout the last 35 years. And the bigger rate is very low compared to data center technology. So, you know optical would have to take a huge step going forward. We got a lot of legs left in the solid state business. That's really active SSB, the whole nonvolatile memory spaces. Probably not 45% of the total disc shipments in terms of units, from what it was at it's high and in 2010. Unbelievable though. You know, in disc shipment 650 million drives a year announced just under 400, 35,400. So flashes has taken this stuff away, like crazy. Tape shouldn't be taking just away, but the tape industry doesn't do a very effective job of marketing itself. Most people still don't know what's going on with tape. They're still looking out of the roof, still looking out of the rear view mirror at a tape, as opposed to the front windshield. We see all the new things that have happened. So, you know they have bad memories of taping the past load stretch, edge damage tape, wouldn't work a tear or anything like that. It was a problem. Oh, that's pretty well gone away now. In a moderate tape is a whole different ball game, but most people don't know that. So, you know tapes going to have to struggle with access time and sequential reality. They've done a few things to come over excess time and the order request now to take the optimizer based on physical movement on the tape that can take out 50% of your access time for multiple requests on a cartridge. The one on here that's got the most promise right now would be a version of a multilayer photonic storage, which is. I would say sort like optical, but, you know, with data center, class characteristics, multi-layer recording capability on that random access, which tape doesn't have. And, you know, I would say that's probably the one that you would want to take some look at going forward like this. The others are highly specular. You know, we've been talking about DNA since we were kids. So we don't have a DNA product out here yet. You know, it's access times eight hours. It's probably not going to work for us. That's your, that's not your deep archive anymore. That's your time capsule storage. >> Yeah, right. >> Lock the earth. So, I mean, I think you kind of see what's here. I mean, the chances are it's still going to be the magnetic technologies tape disc, and then the solid state number and stuff. >> Right. >> But these are the ones that I'm tracking and looking at, trying to have worked with a few of the companies that are in this. Future list and I'd love to see something breakthrough out there, but it's like, we've always said about a holographic storage. For example, you know, there's been more written about it than there's ever been written on it. (both chuckles) >> Well, the paper's called Reinventing Archival Storage. You can get it on your website I presume Fredhorizon.com >> Yep, absolutely. >> Awesome. >> Fred Moore, great to see you again. Thanks so much for coming on the CUBE. >> My pleasure, Dave. Thanks a lot. Great job. >> All right. And thank you for watching everybody. This is Dave Volante for the CUBE. We'll see you next time. (upbeat music)

>> Announcer: From CUBE studios in Palo Alto, in Boston connecting with thought leaders all around the world, this is a CUBE conversation. >> Hello everybody and welcome to this CUBE conversation, you know in our last breaking analysis we worked with ETR and they put out a new forecast on IT spending for 2020. The consensus coming into 2020 was for 4% increase, based on the survey work they've done with CIO's it's now down to 0%. Surprisingly about 40% of the the CIO's and IT practitioners that they interviewed said they expected no change in IT budget for 2020. A surprising 21% say they actually expect to increase spending as a result of work from home infrastructure. Still a very large portion of the survey sample said they're going to decrease spending and that's why they're now calling, ETR's calling for a flat spending in 2020. Clearly one of the challenges or those companies that are exposed to supply chain disruptions, whether it's manufacturing or retail or certain CPG or industrial. And with me today to talk about specifically supply chain within the storage market and within pure storage is Mike Fitzgerald, who's the VP of Operations at Pure. Mike thanks so much for coming on and talking about this important topic. No thank you Dave. Good to see you and good afternoon and good morning. >> So take us through what your seeing, well first of all what's your roll? VP of operations, your in charge of supply chain is that correct? >> Yeah, I have all of the supply chain, all of the manufacturing logistics, distribution network at PURE. >> So what's going on with, what are you seeing in the industry, talking to your colleagues. I'm sure that your discussing this with your peers. Give us the high level and the macro and then we'll get into what's going on with PURE specifically. >> Well certainly they're you know within early January we started to hear whispers out of the parties that there were going to be some potential implications with the supply chain. So at that point in time we did a lot of actions and activated at PURE to try to stay ahead of that with speed being gone of the key things that we wanted to make sure we we're focusing on. But the industry as a whole, there was a lot of focus over the last several months in how do we make sure that not only do we understand what our risk is in the Far East/China but how do we mitigate that risk? And then as we transpired and things have gotten to where we are now, the risk has become more of a global risk in terms of a supply chain management role. >> So is it really was it the exposure to China? Was it really NAND supply? Because that's been sort of zigging and zagging for the last you know several periods. Can you give us a little more color on really what you were paying attention to in terms of some of those hotspots? >> Yeah well one of the things we tried to do early on is the design of our supply chain at PURE, we've tried to diversify that. We've got a portfolio-based foot print across the globe. Early on we took a lot of steps to minimize the amount of reliance on China. A lot of that was driven by tariff implications but certainly it's become our friend as we've gotten into the situation with the COVID. So lot of actions and activity in that space to make sure that we've got a responsive supply chain in place from a global perspective. On the NAND there's a lot of discussion , lot of actions and activities in relationship to NAND, certainly with the rising price, the market demands, whats going on with the supply versus demand ratios , but one of the things that we have a huge advantage of at PURE is that we build our own SSDs. So NAND is a component is what we're buying which is not directly related to what I'll call China shortages. A lot of the NAND that's not built in China that we consume and put into our SSDs. >> So are you saying PURE's not having any kind of supply chain disruption or your managing that? What are you doing there specifically and how much of that is just sort of reduced demand versus so your approach, the supply chain? Can you address that? >> Yeah we are not seeing a reduced demand right now. One thing, kind of an overarching statement is we have plenty of supply available right now. We are, our portfolio is at standard lead time and so we've got product in place as a matter of fact we've seen an uptick in some of the demand streams, specifically in VDI, as well as PURE as-a-Service in less human element. The VDI certainly for the work-from-home type of scenarios. We're actually seeing what I would call a more of an increase in demand with shorter lead times bribing us to put product onsite in emergency situations. >> That's interesting because a lot of suppliers that I've talked to have said look we are going to manage this by communicating increased lead time to our customers. Your saying PURE is actually seeing the opposite. You've got good supply and your seeing strong demand and your able to meet either on time or even at an accelerated pace? Did I get that right? >> Yeah absolutely Dave, actually over the last three days, the weekend, we've had three separate installs in the locations on an emergency basis where we've responded in less than 24 hours and gotten product onsite, installed and saved the customers from running into situations where their work from home staff was not able to come up. >> You know Mike, you've obviously got a lot of experience in this space, operations and supply chain, you've done this for awhile. PURE as a company does a lot of things differently, I've been following them since the early days of PURE but I have to be honest I've never really dug into PURE's supply chain you know approach in any differentiation you have there. How would you compare PURE's approach to others that you've seen in the industry's maybe historically or what your seeing today. What are you guys doing that's different? >> We've designed our supply chain to be a responsive supply chain. With the recognition we're growing roughly 20% year-over-year. We're leaning into the supply chain to be able to not only be enable that growth but be able to enable surge. So some of the things that we do in designing the responsive supply chain, we talked earlier about making sure we have the right manufacturing footprint and that we've got the right risk mitigation so that we can have that portfolio coach related to diversity in this footprint but we've actually staged material in the supply chain intentionally to enable us to be able to surge in response to demand increases. We've done the same with capacity. So we've actually leaned into our network and increased capacity to be able to absorb surges in demand which is certainly paying off for us now in this situation where early on in January we started seeing the signs that we we're going to have some demand constraints. So we went out and placed buys, we went long is probably the best way to put it and try to make sure that we were stocking up accordingly. So that if indeed there was a constraint that happened or constrained environment that we had product available and that's what's paying off for us right now. >> Mike is that a brute force decision making process? In other words is it more gut feel from your tribal knowledge and experience at this? Are you using analytics in anyway to inform sort of where to turn those knobs? >> Well it's a little of both Dave, some of it is I've been in this game for awhile, I've seen these before. So we knew early on that it was time to pull the trigger. So we did. One of the advantages we've got at PURE is that we're a small team, we're a nimble team, decisions can be made today and implemented this afternoon and that is basically the way that we did it. We got the right stakeholders together we made some conscious decisions on what we were going to do to try to mitigate the risk going forward. Pulled the trigger and now we have supply available and we continue to ship. >> I wonder if we could talk a little bit about, I'll come back to that, VDI. As I said at the top of this we saw from the ETR survey data that work from home was one of the few areas that was really you know picking up. And it wasn't just video conferencing it was VPN, it was networking bandwidth, it was security infrastructure to support that work from home capability etcetera. And obviously VDI is part of that. I wonder if you could talk a little bit more about that, not only in terms of what your seeing for your customers but what is PURE doing just in terms of you know, remote support and other things. Where are you focused there? >> Two things, I'll talk about the VDI solution. We've got solutions certainly that we're offering into the marketplace, we've had as I said a significant uptick in demand and I think many would say that storage is the backbone of an effective VDI solution, that's what we do for a living. We've also got several different solutions that we're implementing or having customers implement and simplify. The implementation of the VDI. And one of our key things is we're simple, we're easy, we can put things in place quickly. As I said we're loading data centers in hours versus days. The other question Dave about the support and I'll view that in two different areas. One the implementation of existing product, or the support related to that. Our support network is 100% up and running right now, we have componentry, we've actually forward stock incremental a componentry into the depots to make sure that we're able to support our key customers. One of the motto's that we've got is "We're an essential business that is in the business of supporting other essential businesses." Critical infrastructure, focusing on that to make sure that if for some reason we lose a logistics channel in the country that we've got components there so that the support infrastructure stays in place so we're able to keep our customers up and running. >> So I wonder if you could talk a little bit about some of the assumptions that your making. We have a saying sometimes hope for the best plan for the worst. In your business that's probably apropos. What are some of the assumptions your making just in terms of you know planning for the worst. >> We're doing, early on it was all about making sure that you could get blind side on supply and making sure that we've got capacity available. We did a lot of work on making sure that our alternate site across the globes were able to absorb what we couldn't get out of our China suppliers for the time being when we got the constraints there. But at the same time we are now recognizing as the COVID expands, the COVID, excuse me the incident that we're in now, that there may be some demand delay or demand destruction in the future. So what is our risk profile in relation to that? So that's something we're doing as well but right now we're more focused on what's it going to take to make sure we've got supply available to customers that need supplying now? >> So what are the, I mean I'm sure you've got a lot of KPI's but if you had to really focus in on the top ones, the two or three that your really focused on you know you look at every morning when you wake up. Where's your focus in terms of KPI's? >> Right now its, we're in a different environment than we were in let's say three months ago. And right now it's product availability. And that's in responsiveness to customer needs. In a normal environment I'd say its cost, quality and delivery, that's a typical supply chain mantra. The three legs of the stool. But right now certainly we're not minimizing the of having to have excellent quality but what we're really focused on now is making sure we are providing product into critical infrastructure, essential customer sites, so it's all about availability. I'd say the majority of my day is focusing on what do we need to do to make sure we got product available for the market place. >> Well Mike, we're seeing you know the people around the world, not only in United States but globally respond to this crisis we're all doing our own part. Clearly your, I assume before you we're waking up that assumes you we're sleeping but I know your not getting much sleep but I want to thank you for coming on and sharing with is some of the things that are going on with PURE. You know keep up the great work, your customers need this, I mean storage is part of critical infrastructure and really appreciate all the effort. Thanks to you and all the team at PURE. >> Well thank you Dave, I appreciate it, have a great day. >> You too, it's great to have you. Thank you everybody for watching. We'll keep broadcasting here daily from the CUBE studios, this is Dave Vellante. This CUBE conversation we'll see ya. (bouncy music)

>>live from San Francisco. It's the Q covering Micron Insight 2019 to You by Micron. >>Welcome back to San Francisco, everybody. We're here. Appear 27 covering the micron inside. 2019. I'm David Lot day with my co host, David Flores. Sanjay Moreau chose here. He's the president and CEO of Micron. Sanjay, great to see you again. Good to >>see you, too. >>I love the show because you guys are a highly technical company. You get you get down in the weeds and talk about nano meters and cycles and things like that. But we're here talking about technology, how it's changing people's lives. I mean, you see, that is your mission. So tell us a year on what's new from this >>event. You new at this event is so many new products that we announced today. You know, you see, Micron, I'd like to say that my clone 41 year old, but it has a new heart beat and you see that new heartbeat coming through New innovations, new products, you know, several new solid state drive solutions. Breakthrough speeds portable. SSD renounced our tent, a security solution as well as demonstrated test platform a platform for deep learning algorithms to be applied, enabling influence at EJ. So you see my front continuing to focus on driving high value solutions, engaging deeper with the ecosystem, engaging with our customers to understand what are the main points off the future and bringing innovative technology solutions. And, of course, during the course of last year in a while it was a year where memory pricing went down substantially because of some excess supply forces demand. But my crone, actually in that year produced the second best year in the history of the company. And during the year, he also had the second best year for free class cash flow for the company, >>about $13 billion in nearly 12 months. I want to get into some of that. But before I do our industry and you know this well has marched to the cadence of Moore's law for decades and decades of that has been the innovation engine. It no longer is. You talked about that on your panel today, the innovation engine is now data applying machine intelligence and a I and machine learning to that data scaling with cloud. Now the edge comes into a whole new innovation cocktail. I wonder if you could comment on that in terms of what it means for your business. >>So, yes, in terms of innovation, challenges you to Morse law scaling, but also the workloads that are there today, driving the eye of the future required, nor the solutions of yesterday. They require new, innovative architectures. I like to call them be spoke processors like you have a new custom suit for that fits a particular individual. Now baseball processors that actually meet needs off the specific workloads. But what is important is that as these new innovations, new architectures proliferate through the ecosystem. Memory and storage is key because the trends off the eye, after all, are about drawing deeper insight and creating greater value from all the data that billions of devices the coyote devices are creating around the world. So tremendous support unity for memory and storage. We are focused on bringing solutions with Denham with flash that meet the needs of our customers in terms of performance be announced today. You know the highest clocking speed for our ballistics. Dylan. You know, a delight to the gamers, but we also announce new SS D's for enterprise application, we announce a three d cross point x 100 solid state drive with the fastest in the industry kind of performance. So these are the kind of things were focused on. Yes, technology is getting more complex in and, you know, event from 64 layers to 96 layers. And next year, going 228 layers on Dedham side were the first ones to introduce the ones e technology Norden the industry and actually forced ones to start shipping already in production in the industry. This one z dina nor has the smallest feature size. So these are new, exciting things that are happening at my crime. >>I mean, Sanjay's right. They see all these alternative processes going on. You see, cos tech companies building their own custom silicon, right? I mean, >>so yes, way we're seeing these hybrid solutions being put together on dhe, seeing that the rise of new players completely like arm, for example, now taking a more and more important part in that. So But I'd like to just ask one question on three D cross point that that was an interesting one. How you gonna get volume in that is there going to be through working with some of these other vendors? Because Intel have just combined it with The process is essentially, Are you looking at new ways that you can use that at the lower end to get volume up? >>Where's that fit in your overall strategy? >>Certainly, as we said in the memory hierarchy, TV Cross Point fits in very nicely between NAND on one end and Di Dam on the other end city cost point as a persistent memory gives the benefit that it has capacities, ship densities that can be higher than Denham. Yet it has performance that is close to Denham and much faster than then. And it has the persistence, the non volatility that man has as well. So you can imagine with those kind of attributes, it will have exciting new opportunities in the future. But these new technologies do take several years before they become mainstream technologies. This is still early innings for three D plus point technology. Be engaged with the ecosystem partners with the customers in terms of understanding how this will fit in best in terms of their data center applications. This is what we have started working on This is what we announced the product. And we'll, of course, continue to evolve. The road map are pretty cross point technology. I just also want to touch upon what you said that Yes, you do see that compute now is not being just done like yesterday with CP use. Yes, you do have that idea of solutions. Si pues gp used tp use a six and f bjs. And here's some of the social media giants and those tech giants that are driving innovation in various industry segments, including transportation. They have their own silicon, you know, to address their deep learning requirements, and that creates new. Unfortunately, for us, this is what we call putting silicon back into Silicon Valley. Silicon is driving the innovations today that are coming out of Silicon Valley, regardless off world and market segment and Member Lee and storage is very much at the heart is at the center of yours. >>So you know I want to retire about vertical integration and one of my business early business heroes was Al Shugart. When I was a young puppet, i d. C. And he educated me on the importance of vertical integration and his market, which of course, was spinning destroys heads, media, etcetera. That was a game changer for that that you know, emerging company at the time. See gate. How is vertical? What your philosophy and vertical integration And how does it affect your business and your customers? >>So vertical indication enables us to bring value to our customers, bring greater value to our customers. We have a massive scale off manufacturing that is built on a very comprehensive and actually the world's most unique technology platform. Now taking this vertical integration of the technology platform manufacturing scales off, you know, more than six million acres a year and extending it to controller and form their expertise deep packaging expertise to bring high bandwidth Delia memory solutions for data center applications as well. A solid state drives and multi chip manage nan solutions for smartphone and automotive applications. These are just examples off how we're leveraging our vertical integration, extending it into controllers and firmware and packaging and assembly capability to really bring a diverse and expanded product for a full year to the market, do air just the markets needs from cloud to the edge. And now we're extending our work till indication capabilities even deeper from we have gone from silicon two solutions and now going from also silicon. Two solutions to system and software working with customers to understand water, the hardware and software intricacies involved that can help bring out even more power from the memory as they look at, you know, driving their deep learning algorithms for training as well as for influence. I think this is the vertical integration on build on the most unique platform of technologies. Nobody else in the world has Denham, NAND and CD cross point now building vertical indication on this gives us tremendous defense created opportunity to bring value to our cast. >>A troll more value or being able leveraged. I wanna ask you about your business. You mentioned a record number two free cash flow year for you guys. Two summers ago, I listened to you at the analyst, the Wall Street analyst meetings in you. We're very much aware of the demand and supply pending imbalance that was coming. And you said at the time we're gonna manage through that much better than we have. Historically, it reminds me of airlines when you go when you fly now there's no empty seats, so and you've done a masterful job. The stock prices stayed up. Now, granted, you know you've reduced share count. But how have you done that? What is the new discipline that has allowed you to navigate through those icebergs? >>Soviet Full focus on accelerating our technology development. We're focused on making, for example, technology development exploration. I mentioned earlier being the forest to the market with one C D M, which has the smallest feature size, right. That ability to accelerate technology development and deploy it in production to meet our CUSTOMERSNEEDS gives us ability to manage cost reduction ability as well. So Micron has actually in terms of cost reductions on a year over year basis has led the industry both on the same side as well as the NAN site. This has contributed to stronger financial performance of the company. During 2019 there, prices came down due to some excess supply in the industry, and yet Micron, due to its healthy cost position, was able to produce better financial results as well. Another very important element is increasing the mics off high value solutions, infusing the mics off SS D's and Managed man for mobile applications, as well as bringing more high performance memory to the Bennett, did a memory to the benefit of our customers. High value solutions, Cost positioning, technology acceleration. These have bean the elements that will give us long lasting advantage in terms of continuing to weather the potential ups and downs in our industry. And, you know, yes, we're proud of the fact that, unlike in the past, in an environment like will be experienced in 2019 with respect to price declines, Micron would have had media challenges Micron actually delivered, as I said, the second best year in terms of revenues profits as well as free cash flow. And I want to highlight that we narrowed the gap with our competitors. We narrow the gap with our competitors in terms of orbital margin again as a result, off a stronger, more diversified high value product portfolio and our cost reduction capabilities. >>Yeah, and you've also done a great job communicating to Wall Street. So my last question I know you gotta go is around tech for good. Mark Betty of's been really front center on this. You said that are really jar job is to make lives better, because I still say your job is to increase shareholder value as well. Whoa is the CEO who Mrs 4/4 in a row, but then points to tech for good at the same time. New new workers millennials expect checked for good. How do you see those fitting together? What's your philosophy? There >>were very passionate at Micron that it is important for us that we support the communities that be working where our team members 11. Yes, we want to dry for betterment of humanity through bringing the benefit off our technologies and products, you know? And of course, you see your life's changed with the benefit of more memory and storage, whether it is in your smart home or your smartphone or all of the benefits that you're getting from advances in technology today. But we also absolutely have a social responsibility going from customers to communities, really making sure that we had a good corporate citizen. So at my crone, philanthropy is important doing this year. A microloan foundation is matching our team members contributions, and through that through our team member contributions as well as our match, we have given two and 1/2 $1,000,000 to the communities during the course of the year. We have also supported several new initiatives related to stem education as well as basic human needs again in all the countries and sites where micro nasty members. And actually Micron Foundation has given $11 million during our fiscal year 2019 for supporting various causes toward basic human needs, as well as advancement of science, technology and generating and map. And, most importantly, microphone team members more white have contributed 165,000 hours in community giving, volunteering activities, and we are trying to continue to take our engagement with the community to the next level. I considered it very, very important that and our responsibility that is not only about producing best business results, but we need to help our communities and people in need get to the next level off betterment as well. And it's part of there's diversity and inclusion and equality is a very, very important initiative at the company as well. And we're making tremendous progress in that respect as well. That's >>a great story, Sanjay. Thanks. Um I know you're super busy. Get a bunch of customers to see you're an awesome CEO and doing a great job. Really appreciate you taking the time to come on the Cube. Thank you. Thank you >>for being here with you today. >>Fantastic. All right. Thank you for watching. Everybody will be right back with our next guest. Live from Micron inside. 2019. You're watching the Cube?

>> Announcer: From Austin, Texas it's The Cube covering Pure Storage Accelerate 2019, brought to you by Pure Storage. >> Good morning. From Austin, Texas, Lisa Martin with Dave Vellante at Pure Accelerate 2019. This is our second day. We just came from a very cool, interesting, keynote, Dave whenever there's astronauts my inner NASA geek from the early 2000s. She just comes right back up Leland Melvin was on >> Amazing, right? >> With a phenomenal story. Talking about technology and the feeling of innovation but also a great story of inspiration from a steam perspective science, technology, engineering, arts, math, I loved that and, >> Dave: And fun >> Very fun. But also... >> One of the better talks I've ever seen >> It really was. It had so many elements that I think you didn't have to be a NASA fan or a NASA geek or a space geek to appreciate the all of the lessons that Leland Melvin learned along the way that he really is inspiring, everybody the audience to take note of. It was I thought it was... >> And incredibly accomplished, right? I mean scientist, MIT engineer, played in the NFL, went to space, he had some really fun stuff when they were, you know, messing around with with gravity. >> Lisa: Yes. >> I never knew you could do that. He had like this water. >> Lisa: Water, yeah. >> Bubble. >> I'd never seen that before and they were throwing M&M's inside (laughter) and he, you know consumed it choked on it, which is pretty funny. >> Yeah, well it was near and dear to me. I worked with NASA my first job out of grad school. >> Dave: Really? >> I did, and managed biological pilots that flew on the space shuttle and the mission that the he talked about that didn't land, Colombia. That was the mission that I worked on. So when he talked about that countdown clock going positive. I was there on the runway with that. So for me, it just struck a chord of, >> Dave: so this is of course the 50th anniversary of the moonwalk. And you know I have this thing about watches, kind of like what you have with shoes (chuckles) >> Lisa: Hey, handbags. >> Is that not true? Oh, It's handbags for you? (laughing) >> Dave: I know this really that was a terrible thing for me to say. >> That's okay. >> Dave: You have great shoes so I just I just assumed that not good to make assumptions. So I bought a moon watch this year which was the watch that Neil Armstrong used to not the exact one but similar one, right? >> Lisa: Yeah. And it actually has an acrylic face because they're afraid if it cracked in space you'd have glass all over the place. [Lisa] Right. So that's a little nostalgia there. >> Well one of the main things too as you look at the mission that President John F. Kennedy established in the 60's for getting a man in space in that 10-year period. That being accomplished and kind of a parallel with what Pure Storage has done in its first 10 years of tremendous innovation. This keynote again Day 2, standing room only at least about 3000 people or so here. Storage as James Governor said, your friend and also who keynoted after Leland this morning you know, (mumbles) Software's eating the world storage is eating the world we have to have secure locations to store all this data so that we can extract maximum value from it. So nice parallel between the space program and Pure Storage. >> James is really good, isn't he? I mean he had to follow Leland and I mean again one of the better talks I've ever heard, but James is very strong, he's funny, he's witty he's he cuts to the chase. >> Lisa: Yes. >> He always tells it like it is. He's a very Monkchips is very focused on developers and they do a really good job there, one of the things he talked about was S3 and how Amazon uses this working backwards methodology which maybe a lot of people don't know about but what they do is they write and rewrite and rewrite and vet and rewrite the press release before they announce the product and even before they develop the products they write the press release and then they work backwards from there. So this is the outcome that we are trying to achieve, and it's very disciplined process that they use and as he said they may revise it hundreds and hundreds of times and he put up Andy Jassy's quote from 2004, around S3. That actually surprised me. 2000...Maybe I read it wrong. >> Lisa: No, it was 2004. >> Because S3 came out after EC2 which was 2006 so I don't know. Maybe I'm getting my dates wrong or I think James actually got his dates wrong but who knows, maybe you know what? Maybe he got a copy of that from the internal working document, working backwards doc that could be what it was but again the point being they envisioned this simple storage that developers didn't have to think about >> Lisa: Right. >> That was virtually unlimited in capacity, highly available and you know, dirt cheap which is what people want and so he talked about that and then he gave a little history of the Dell technology families and I tweeted out this in a funny little you know basically pivotal VM ware EMC and Dell and their history Dell was basically IPO 1984 and then today. There was a few things in between I know but he's got a great perspective on things and I think it resonated with the audience then he talked a lot about Kubernetes jokingly tongue-in-cheek how Kubernetes everybody thought was going to kill VMware but his big takeaway was look you got all these skills of (mumbles) Skills, core database skills, I would even add to that you know understanding how storage works and I always joke if your career is based on managing lawns you might want to rethink your career. But his point was which I liked was look all those skills you've learned are valuable but you now have to step up your game and learn new skills. You have to build on top of those skills so the history you have and the knowledge that you've built up is very valuable but it's not going to propel you to the next decade and so I thought that was a good takeaway and it was an excellent talk. >> So looking back at the conversations yesterday the press releases that came out the advancements of what Pure is doing, with AWS, with Nvidia, with the AI data-hub for example, delivering more of their portfolio as a service to allow businesses whether it's a law-firm like we talked to yesterday utility or Mercedes AMG Petronas Motor-sport, to be able to access data securely, incredibly quickly, recover it restore it absolutely critical and really can be game-changing depending on the type of organization. I want to get your perspectives on some of the things you heard anecdotally yesterday after we wrapped in terms of the atmosphere, the vibe, the thoughts on Pure's next 10 years. >> Yeah, so several things, just some commentary so it's always good at night you go around you get a lot of data we sometimes call it metadata. I think one of the more interesting announcements to me was the block-storage on AWS. I don't necessarily think that this is going to be a huge product near term for Pure in terms of meaningful revenue, but I think it's interesting that they're embracing the trend of the Cloud and are actually architecting Cloud solutions using Amazon services and blending in their own super gluing their own, I mean it's not really superglue but blending in their own software for their customers to extend. Now, you know some of the nuances I don't think they are going to have they have better right performance I think they'll have better read performance clearly they have better availability I think it's going to be a little bit more expensive. All these things are TBD that's just my take based on looking at what I've seen and talking to some people but to me the important thing is that Pure's embracing that Cloud model. Historically, companies that are trying to defend an existing business, they retreat. You know, they denigrate they don't embrace. We know that Pure's going to make more money on pram than it does in the Cloud. At least I think. And so it's to their advantage for companies to stay on-prem but at the same time they understand that trend is your friend and they're embracing that so that was kind of one thing. The second thing I learned is Charlie Giancarlo spent a lot of time with them last night as did you. He's a bit of a policy wonk in very certain narrow areas. He shared with me some of the policy work that he's done around IP protection and not necessarily though on the side that you would think. You would think that okay IP protection that's a good thing but a lot of the laws that were trying to be promoted for IP protection were there to help big companies essentially crush small companies so he fought against that. He shared with me some things around net neutrality. You would think you know you think you know which side of net neutrality he'd be on not necessarily so he had some really interesting perspectives on that. We also talked to and I won't share the name of the company but a very large financial institution that's that's betting a lot on Pure was very interesting to me. This is one of the brand names everybody would know it if you heard it. And their head of storage infrastructure was here, at the show. Now I know this individual and this person doesn't go to a lot of shows >> Maybe a couple a year. >> This person chose to come to this show because they're making an investment in Pure. In a fairly big way and they spent a lot of time with Pure management, expressing their desires as part of an executive form that Pure holds they didn't really market that a lot they didn't really tell us too much about it because it was a little private thing but I happen to know this individual and and I learned several things. They like Pure a lot, they use it for a lot of their workloads, but they have a lot of other storage, they can't necessarily get rid of that other storage for a lot of reasons. Inertia, technical debt, good tickets at the baseball game, all kinds of politics going on there. I also asked specifically about some hybrid companies products where the the cost structure's a little bit better so this gets me to flash array C and we talked to Charlie Giancarlo about this about his flash prices come down and it and opens up new markets. I got some other data yesterday and today that you know that flash array C is not going to be quite priced we don't think as well as hybrid arrays closing the gap it's between one and one and a quarter, one and a half dollars per gigabyte whereas hybrid arrays you are seeing half that, 70 cents a gigabyte. Sometimes as low as 60 cents a gigabyte. Sometimes higher, sometimes high as a dollar but the average around 65-70 cents a gigabyte so there's still a gap there. Flash prices have to come down further. Another thing I learned I'm going to just keep going. >> Lisa: Go ahead! >> The other thing I learned is that China is really building a lot of fab capacity in NAND to try to take out the thumb-drive market-place so they are going to go after the low-end. So companies like Samsung and Toshiba, Toshiba just renamed the company, I can't remember the name of the company but Micron and the NAND flash NAND manufacturers are going to have to now go use their capacity and go after the enterprise because China fab is going to crush the low-end and bomb the low-end pricing. Somebody else told me about a third of flash consumption is in China now. So interesting things going on there. So near term, flash array C is not going to just crush spinning disk and hybrid, it's going to get closer and it's going to slowly eat away at that as NAND prices come down it really could more rapidly eat away at that. So I just learned some other stuff too but I'll take a breath. (laughter) >> So one of the things I think we are resounding with it we heard not just yesterday on the program day but even last night at the executive event we were at is that from this large financial services company that you mentioned, Pure storage is a strategic partner to many organizations from small to large that is incredibly valued to your point the Shuttleman only goes to maybe a couple of events a year and this is one of them? >> Dave: Right. >> This is a company that in its first 10 years has embraced competition head on and I loved how you talked about yesterday 10 years ago they just drove a truck through EMC's market and sort of ripping and replacing. They're bold but they're also doing it in a way that's very methodical. They're working on bringing you know changing companies' perspectives of even backup data as becoming an asset to put it on flash. Because if you can't rapidly restore that, if there's an outage whether it is an attack or it's unintentional human related, that data can't be recovered quickly, you're in a big big problem. And so them as a strategic component of this isn't in any industry I think it was a very resounding sentiment that I heard and felt yesterday. >> Yeah, this ties into tam expansion of what we talked to Charlie Giancarlo about new workloads with AI as an example flash or AC lowering prices will open up those some of those new workloads data protection backup is clearly an opportunity and I think it's interesting, you're seeing a lot of companies now announce a lot of vendors announce flash based recovery systems I'll call them recovery systems because I don't even consider them backup anymore it's not about backup, it's about recovery. Oracle was actually one of the first to use that kind of concept with the zero data loss recovery appliance they call it recovery. So it's all about fast and near instantaneous recovery. Why is that important? It's because it's companies move toward a digital transformation and what does that mean? And what is a digital business? Digital business is all about how you use data and leveraging data in new ways to create new value to monetise or cut cost. And so being able to have access to that data and recover from any inaccess to that data in a split-second is crucial. So Pure can participate in that, now Pure's not alone You know, it's no coincidence that Veritas and Veeam and Cohesity and Rubrik they work with Pure, they work with HPE. They work with a lot of the big players and so but so Pure has to you know, has some work to do to win its fair share. Staying on backup for a moment, you know it's interesting to see, behind us, Veritas and Veeam have the biggest sort of presence here. Rubrik has a presence here. I'm sure Cohesity is here maybe someway, somehow but I haven't seen them >> I haven't either. >> Maybe they're not here. I'll have to check that up, but you know Veeam is actually doing very well particularly with lower ASPs we know that about Veeam. They've always come at it from the mid-market and SMB. Whereas Cohesity and Rubrik and Veritas traditionally are coming at it from a higher-end. Certainly Cohesity and Rubrik on higher ASPs. Veeam's doing very well with Pure. They're also doing very well with HPE which is interesting. Cohesity announced a deal with HPE recently I don't know, about six months ago somebody thought "Oh maybe Veeaam's on the outs." No, Veeam's doing very well with HPE. It's different parts of the organization. One works with the server group, one works with the storage group and both companies are actually doing quite well I actually think Veeam is ahead of the curve 'cause they've been working with HPE for quite some time and they're doing very well in the Pure base. By partnering with companies, Pure is able to enter that market much in the same way that NetApp did in the early days. They have a very tight relationship for example with Commvault. So, the other thing I was talking to Keith Townsend last night totally not secretor but he's talking about Outpost and how Amazon is going to be challenged to service Outpost Outpost is the on-prem Amazon stack, that VMware and Amazon announced that they're co-marketing. So who is going to service outpost? It's not going to be Amazon, that's not their game in professional service. It's going to have to be the ecosystem, the large SIs or the Vars the partners, VMware partners 'cause that's not Vmwares play either. So Keith Townsend's premise, I'd love to have him on The Cube to talk about this, is they're going to have trouble scaling Outpost because of that service issue. Believe it or not when we come to these conferences, we talk about other things than just, Pure. There's a lot of stuff going on. New Relic is happening this week. Oracle open world is going on this week. John Furrier just got back from AWS Bahrain, and of course we're here at Pure Accelerate. >> We are and this is our second day of two days of coverage. We've got Coz on next who I think has never been on The Cube. >> Dave: Not to my knowledge. >> We've got Kix on later. A great lineup, more customers Rob Lee is going to be on. So we're going to be digging more into Pure's Cloud strategy, the next ten years, how they're going to accelerate that and pack it into the next couple of years. >> I'll tell you one of the things I want to do, Lisa. I'll just call it out. An individual from Dell EMC wrote a blog ahead of Pure Accelerate I think it was last week, about four or five days ago and this individual called out like one, two, three, four.... five things that we should ask Pure so we should ask them, we should ask Coz we should ask Kix. There was criticism, of course they're biased. These guys they always fight. >> Lisa: Naturally. >> They have these internecine wars. >> Lisa: Yep. >> Sometimes I like to call them... no I won't say it. So scale out, question mark there we want to ask Coz about that and Kix. Pure uses proprietary flash modules. They do that because it allows them to do things that you can't do with off-the-shelf flash. I want to ask and challenge them that. I want to ask about their philosophy on tiering. They don't really believe in tiering, why not? I want to understand that better. They've made some acquisitions, Compuverde is one acquisition, it's a file system. What does that mean for flash play? >> Now we didn't hear anything about that yesterday, so that's a good point that we should dig into that. >> Yeah, so we'll bring that up. And then the Evergreen competitors hate Evergreen because Pure was first with it they caught everybody off guard. I said it yesterday, competitors hate Evergreen because competitors live off of maintenance and if you're not on their maintenance they just keep jacking up the maintenance prices and if you don't move to the new system, maintenance just keeps getting more and more and more and more expensive and so they force you, you're locked in. Force you to move. Pure introduced this different model. You pay for the CapEx up front and then, you know, after three years you get a controller swap. You know, so... >> To your point competitors hate it, customers love it. We heard a lot about that yesterday, we've got a couple more customers on our packed program today, Dave so let's get right to it! >> Great. >> Let's wrap up so we can get Coz on stage. >> Dave: Alright, awesome. >> Alright, for Dave Vellante. I'm Lisa Martin, you're watching The Cube from Pure Accelerate 2019, day two. Stick around 'Coz' John Colgrove, CTO, founder of Pure, will be on next. (upbeat music)

>> Live from San Diego, California It's the queue covering Sisqo Live US 2019 Tio by Cisco and its ecosystem barkers. >> Welcome back. It's the Cube here at Cisco Live, San Diego 2019 times. Two minute My co host is Day Volante. First, I want to welcome back custom dos Katie, who is the vice president. Product management with Cisco Compute. We talked with him a lot about Piper Flex anywhere in Barcelona. Wanna welcome to the program of first time guests Laura Crone, who's the vice president of sales and marketing group in NSG sales and marketing at Intel. Laura, thanks so much for joining us, All right, So since Katie has been our program, let let's start with you. You know, we know, you know. We've watched, you know, Cisco UCS and that compute, you know, since it rolled out for about a decade ago. Now on DH, you know Intel always up on stage with Cisco talking about the latest enhancements everywhere I go this year, people are talking about obtained and how technologies like envy me are baking in tow. The environment storage class memories, you know, coming there. So you know, let's start with kind of intel. What's happening in your world and you know your activities. Francisco live >> great. So I'm glad to hear you've heard a lot about octane because I have some marketing of my organization. So obtain is the first new memory architecture er in over 25 years. And it is different than Nanda, right? It is you, Khun, right? Data to the silicon that is programs faster and has greater endurance. So when you think of obtain its fast like D ram But it's persistent, like nay on three D now. And it has some industry leading combinations of capabilities such a cz high throughput, high endurance, high quality of service and low latent see. And for a storage device, what could be better than having fast performance and hi consistency. Oh, >> Laura's you say? Yeah, but 25 years since this move. You know, I remember when I when I started working with Dave, it was, you know, how do we get out of you know, the horrible, scuzzy stack is what we had lived on for decades there. And finally, Now it feels like we're coming through the clearing and there is just going to be wave after wave of new technologies that air free to get us high performance low latent c on the like. >> Yeah, And I think the other big part of that which is part of Cisco's hyper flex all in Vienna, is the envy me standards. So, you know, we've lived in a world of legacy satya controllers, which created a lot of bottlenecks and the performance Now that the industry is moving toe envy me, that even opens up it. Mohr And so, as we were developing, obtain, we knew we had Teo go move the industry to a new protocol. Otherwise, that pairing was not going to be very successful. >> Alright, so Katie all envy me, tell more. >> So we come here and we talk about all the cool innovations we do within the company. And then sometimes you come here and we talk about all the cool innovation we do with our partners, our technology partner, that intel being a fantastic technology partner, obviously being the server business, you've got a partner with intel on. We've really going away that across the walls ofthe two organizations to bring, uh, just do to life, right? So Cisco 80 I hyper flex is one of the products >> we >> talked about in the past. Hyper Flex, all in Miami that uses Intel's obtain technology is, well, it's Intel's three demand all envy me devices to power really the fastest workloads that customers want to put on this device. So you talked about free envy me. Pricing is getting to a point where it becomes that much more accessible to youth, ese for powering databases for par like those those work clothes required that leyton see characteristics and acquire those I ops on DH. That's what we've enabled with Cisco Hyper Flex collaborating with Intel of Envy Me portfolio. >> Remember when I started in the business, somebody was sharing with me to educate me on the head? A pyramid? Think of the period is a storage hierarchy. And at the top of it, was it actually an Intel solid state device, which back then was not It was volatile, right? So you had to put, you know, backup power supplies on it. Uh, so but any rate and then with all this memory architecture coming and flash towards people have been saying, well, it's going to flatten that pyramid. But now, with obtain. You're seeing the reemergence of that periods of that pyramid. So help us understand, sort of where it fits from a supplier standpoint and a no yam and ultimate customer. Because if I understand it, so obtain is faster than NAND, but it's going to be more expensive, but it's slower than D Ram, but it's cheaper, right? So where does it fit? What, the use cases? Where does it fit in that hierarchy? Maybe. >> Yeah. So if you think about the hierarchy at the very top is D RAM, which is going to be your fastest lowest Leighton see product. But right below that is obtained. Persistent memory, the dims and you get greater density because that's one of the challenges with the Ram is they're not dense enough, nor are they affordable enough, right? And so you get that creates a new tear in the store tire curry. Go below that and you have obtain assist ease, which bring even mohr density. So we go up to a 1.5 terabyte in a obtain sst, uh, and you that now get performance for your storage and memory expansion. Then you have three Dean and and then even below that, you have three thing and Q l c, which gives you cost effective, high density capacity. And then below that is the old fashioned hard disk drive. And then magnet. Yeah, you start inserting all these tears that give architects and both hardware and software an opportunity. Teo rethink how they wantto do storage. >> So the demand for this granularity obviously coming from your your buyers, your direct bars and your customers. So what does it do for you and specifically your customers? >> Yeah. So the name of the game is performance and the ability to have in a land where things are not very predictable, the ability to support any thing that the your end customers may throw at you if you're a 90 department. That may mean a bur internal of, uh, data scientist team are traditional architect off a traditional application. Now, what Intel and Cisco can do together is truly unique because we control all parts of the stack, everything from the sober itself to the to the storage devices to the distributed file system that sits on top ofit. So, for example, in Etienne, hyper flecks were using obtain as a cashing here on because we write the distributed file system. We can speak in a balance between what we put in the cash in care how it moved out data to the non cashing 3 90 year, as as Intel came out with their latest processors that support memory class torched last memory. We support that now we can engineer this whole system and to end so that we can deliver to customers the innovation that Intel is bringing to the table in a way that's consumable by their, uh, one more thing I'll throw out there. So technology is great, but it needs to be resilient because I D departments will occasionally yank out the wrong wire. They are barely yank out the wrong drive. One of the things that we work together with Intel What? How do we court rise into this? How to be with reliability, availability, serviceability? How do we prevent against accidental removal or accidental insertion on DH? Some of those go innovations have let Teo asked, getting out in the market a hyper flecked system that uses these technologies in a way that's really usable by teens in our customs. I'd >> love to double click on that in the context of envy. Envy? What you guys were talking about, You mentioned horrible storage deck. I think he called it the horrible, scuzzy stack. And Laura, you were talking about the You know, the cheap and deep now is a spinning disk. So my understanding is that you've got a lot of overhead in the traditional scuzzy protocol, but nobody ever noticed because you had this mechanical device. Now, with flash storage, it all becomes exposed. And VM e allows just a like a bat phone. Right? Okay, so correct me where I got that wrong, But maybe you could give us the perspective. You know what? Why Envy Emmy is important from your standpoint. And how are you guys using it? >> Yeah, I think envy and me is just a much faster protocol. And you're absolutely right. We have a graph that we show of the old world and how much overhead there is all the way down to when you have obtained in a dim solution with no overhead octane assist. E still has a tiny bit, but there's a graph that shows all of that Leyton C is removed when you deploy, obtain so envy me gives you much greater band with right. The CPU is not bottlenecked, and you get greater CPU efficiency when you have a faster interface like and >> and like hyper flexes taking advantage of this house. Oh, >> yeah? Let me give you a couple of examples. So anything performance, the first thing that comes to mind is databases. So for those kinds of workloads, this system gets about 25% better performance. Next thing that comes to mind is people really don't know what they're gonna put on the system. So sometimes they put databases, sometimes put mixed workloads. So when we look at mixed workloads way get about 65% or so better I ops, we get 37% better lately sees. So even in a mixed I opened Wyman wherever have databases you may have a Web theory may have other things. This thing is definite resilient to handle the workload. So it's it just opens up the splatter abuse cases. >> So any other questions I had was specific to obtain. D ram has consumer applications, as does Flash Anand was obtained. Have similar consumer applications can achieve that volume so that the prices, you can come down, not free, but continue to sort of drive the curves. >> Eso When we look at the overall tam, we see the tam growing out over time. I don't know exactly when it crosses. Over the volume are the bits of the ram, but we absolutely see it growing over time. And as a technology ramps, it'll have a you know, it costs ramping curves. Well, >> it'll follow that curve. Okay, good. >> Yeah, Just Katie. Give us a little bit. Broad view of hyper flex here. Att? The show, people, you know, play any labs with the brand new obtained pieces or what? What other highlights that you and the team have this week? >> Yeah, absolutely. So in in Barcelona, we talked about high, perfect for all that is live today. So in the show floor, people can look at the hyper flex at the edge combined with S t one. How do you control How did deploy thousands of edge locations from a centralized location to the part of the inner side which cloud based management too? So that whole experience is unable. Now, at the other end of the spectrum is how do we drive even more performance. So we were always, always the performance leader. Now we're comparing ourselves to ourselves to behavior 35% better than our previous all flash. With the innovation Intel is bringing to the table, some of the other pieces are actually use cases. So there's a big hospital chain where my kids go toe goto, get treated and look and see the doctor. There are lots of medical use cases which require epic the medical software company to power it, whether it is the end terminals or it is the back and database. So that epic hyperspace and happy cachet those have been out be invalidated on hyper flex, using the technology that we just talked about around update on doll in via me that can get me there is that much more power. That means that when my my doctor and the nurse pulls off, the records don't show up fast. But all the medical records, all of those other high performance seeking applications also run that much more streamlined, so I would encourage people little water solution. We've got a tremendous set off demos out there to go up there and check us out >> and there's a great white paper out on this, right? That e g s >> e g is made one of the a company that I've seen benchmarking Ah, a hyper flex. >> So whatever Elaborate where they do a lab report or >> it's what they do is they bench around different hyper converge infrastructure vendors. So they did this first time around and they and they said, Well, we could pack that much more We EMS on a on a hyper flex with rotating drives. And then they did it again And I said, Well, now that you got all flash Well, deacon, you got now the performance and the ladies see leadership and then they did it again and they said, Well, hang on, you you've kind of left the competition that does that. That's not going to make a pretty chart to show when we compare your all in Miami against your hyper so many. When you get that good, you compare against yourselves. We've been the performance theater on the estate has been doing the >> data obtained. The next generation added up, >> and this is what a database workload. OK, nowyou bringing obtain a little toast to the latest report >> has that measures >> measures obtain against are all flash report and then also ship or measure across vendors. So >> where can I get this? Is at some party or website or >> it's off all of this. All of this is off off the Cisco Hyper Flex website on artist go dot com. But F is the companies that want to go directly to their about getting a more >> I guess final final question for you is you know, I think back the early is ucs. It was the memory enhancements that they had that allowed the dentist virtual ization in the industry back when it started. It sounds like we're just taking that to the next level with this next generation of solutions. What what else would you out about? The relationship with Cisco and Intel? >> Eso, Intel and Cisco worked together for years right innovation around the CPU and the platform, and it's super exciting to be expanding our relationship to storage. And I'm even more excited that the Cisco hyper flex solution is endorsing Intel obtain and three thing and and we're seeing great examples of really use workloads where are in customers can benefit from this technology. >> Katie Laura. Thanks so much for the update. Congratulations on the progress that you've made so far for David Dante on Student, and we'll be back with more coverage here. It's just go live 2019 in San Diego. Thanks for watching the cue >> theme.

>> (enchanted music) >> Hi, I'm Peter Burris and welcome to another CUBE Conversation from our awesome Palo Alto Studios. We've got a great conversation today. We're going to be talking about flash memory, other types of memory, classes of applications, future of how computing is going to be made more valuable to people and how it's going to affect us all. And to do that we've got Scott Nelson who's the Senior Vice President and GM of the memory unit at Toshiba Memory America. And Doug Wong who's a member of the technical staff also at Toshiba Memory America. Gentlemen, welcome to the CUBE >> Thank you >> Here's where I want to start. That when you think about where we are today in computing and digital devices, etc., a lot of that has been made possible by new memory technologies, and let me explain what I mean. For a long, time storage was how we persisted data. We wrote transactions to data and we kept it there so we could go back and review it if we wanted to. But something happened in the last dozen years or so, it happened before then but it's really taken off, where we're using semi-conductor memory which allows us to think about how we're going to deliver data to different classes of devices, both the consumer and the enterprise. First off, what do you think about that and what's Toshiba's association with these semi-conductor memories been? Why don't we start with you. >> So, appreciate the observation and I think that you're spot on. So, roughly 35 years ago Toshiba had the vision of a non-volatile storage device. So, we brought to market, we invented NOR flash in 1984. And then later the market wanted something that was higher density, so we developed NAND flash technology, which was invented in 1987. So, that was kind of the genesis of this whole flash revolution that's really been disruptive to the industry as we see it today. >> So, added up, it didn't start off in large data centers. It started off in kind of almost unassuming devices associated with particular classes of file. What were they? >> So, it was very disruptive technology. So the first application for the flash technology was actually replacing audio tape and the phone answering machine. And then it evolved beyond that into replacing digital film. Kept going replacing cassette tapes and then if you look at today it enabled the thin and light that we see with the portability of the notebooks and the laptops. The mobility of content with our pictures, and our videos and our music. And then today, the smart phone, that wouldn't really be without the flash technology that's necessary that gives us all of the high density storage that we see. >> So, this suggests a pretty expansive role of semi-conductive related memory. Give us a little sense of where is the technology today? >> Well, the technology today is evolving. So, originally floating-gate flash was the primary type of flash that we created. It's called two-dimensional, cleaner, floating-gate flash. And that existed from the beginning all the way through maybe to 2015 or so. But, it was not possible to really shrink flash any further to increase the density. >> In the 2D form? >> In the 2D form, exactly. So, we to move to a 3D technology. Now Toshiba presented the world's first research papers on 3D flash back in 2007, but at that time it was not necessary to actually use 3D technology at that time. When it became difficult to increase the density of flash further that's when we actually moved to production of our 3D flash memory which we call BiCS flash. And BiCS stands for bit column stacked flash and that's our trade name for our 3D memory. >> So, we're now in 3D memory technology because we're creating more data and the applications are demanding more data, both for customer experience and new classes of application. So, when we think about those applications Toshiba used to have to go to people and tell them how they could use this technology and now you've got an enormous number of designers coming to you. Doug, what are some of the applications that you're anticipating hearing about that's driving the demand for these technologies? >> Well, beyond the existing applications, such as personal information appliances like laptops and portables, and also in data centers which is actually a large part of our business as well. We also see emerging technologies as becoming eventual large users of flash memory. Things like autonomous vehicles or augmented or virtual reality. Or even the emerging IOT infrastructure and that's necessary to support all these portable devices. So these are devices that currently aren't using large amounts of flash, but are going to be in the future. Especially as the flash memory gets more dense, and less expensive. >> So there's an enormous range of applications on the horizon. Going to drive greater demand for flash, but there's some business challenges of achieving that demand. We've seen periodic challenges of supply, price volatility. Scott, when we think about Toshiba as a leader in sustaining a kind of good flow of technology into these applications, what is Toshiba doing to continue to satisfy customer demand, sustain that leadership in this flash marketplace? >> So, first off as Doug had mentioned the floating-gate technology has reached its ability to scale in a meaningful way. And so the other part of that also, is the limitation on the dye density so the market demand for these applications are asking for a higher density, higher performance, lower latency type of applications. And so because floating-gate has reached the end of its usefulness in terms of being able to scale, that brought about the 3D. And so the 3D, that gives us our higher density and then along with the performance it enables these applications. So, from Toshiba's point, we are seeing that migration that is happening today. So, the floating-gate is migrating over to the 3D. It's not to say that floating-gate demand will go away. There's a lot of applications that require the lower density. But certainly the higher density where you need a dye level 256 512 giga bit even up to terabit of data. That's where the 3D's go into play. Second to that really goes into the cap back. So, obviously that requires a significant amount of cap backs not only on the development but also in terms of capacity. And that, of course, is very important to our customers and to the industry as a whole for the assurance of supply. >> So, we're looking so Toshiba's value to the marketplace is both in creating these new technologies, filling out a product line, but also stepping up and establishing the capacity through significant capital investments in a lot of places around the globe to ensure that the supply is there for the future. >> Exactly right. You know, Toshiba is the most experienced flash vendor out there and so we led the industry in terms of the floating-gate technology and we are technology leaders; industry's migrating into the 3D. And so, with that, we continue with a significant capital investment to maintain our presence in the industry as a leader. >> So, when we think about leadership, we think about leadership both in consumer markets, because volume is crucial to sustaining these investments, generating returns, but I also want to spend just a second talking about the enterprise as well. What types of enterprise relationships do you guys envision? And what types of applications do you think are going to be made possible by the continued exploitation of flash in some of these big applications that we're building? Doug, what do you think? >> Well, I think that new types of flash will be necessary for new, emerging applications such as AI or instant recognition of images. So, we are working on next generation flash technology. So, historically flash was designed for lowest cost per bit. So that's how flash began to take over the market for storage from hard drives. But there are a class of applications that do require very low latencies. In other words, they want faster performance. So we are working on a new flash technology that actually optimizes performance over cost. And that is actually a new change to the flash memory landscape. And as you alluded to earlier there's a lot of differentiation in flash now to address specific market segments. So that's what we are working on, actually. Now, generically, these new non-volatile memory technologies are called storage class memories. And they include things like optimized flash or potentially face change memories resistive memories. But all these memories, even though they're slower than say the volatile memories such as D-ram and S-ram they are, number one they're non-volatiles which means they can learn and they can store data for the future. So we believe that this class of memory is going to become more important in the future to address things like learning systems and AI. >> Because you can't learn what you can't remember. >> Exactly. >> I heard somebody say that once. In fact, I've got to give credit. That came straight from Doug. So, if we think about looking forward the challenges that we face ultimately is have the capital structure necessary to build these things. The right relationships with the designers necessary to provide guidance and suggest about the new cost of applications, and the ability to consistently deliver into this. Especially for some of these new applications as we look forward. Do you guys anticipate that there will be in the next few years, particular moments or particular application forms that are going to just kick a lot of or further kick some of the new designs, some of the new technologies into higher gear? Is there something autonomous vehicles or something that's just going to catalyze a whole new way of thinking about the role that memory plays in computing and in devices? >> Well, I think that building off of a lot of the applications that are utilizing NAND technology that we're going to see now we have the enterprise, we have the data center that's really starting to take off to adopt the value proposition of NAND. And as Doug had mentioned when we get into the autonomous vehicle we get into AI or we get into VR a lot of applications to come will be utilizing the high-density, low-latency that the flash offers for storage. >> Excellent. Gentlemen, thanks very much for being on the CUBE. Great conversation about Toshiba's role in semi-conductor memory, flash memory, and future leadership as well. >> Thank you, Peter. >> Scott Nelson is the Senior Vice President and GM of the memory unit at Toshiba Memory America. Doug Wong is a member of the tactical staff at Toshiba Memory America. I'm Peter Burris. Thanks once again for watching the CUBE. (enchanted music)

live from San Francisco it's the queue covering micron insight 2018 brought to you by micron welcome to San Francisco everybody this is the cube the leader in live tech coverage my name is Dave Volante I'm here with my co-host David flora this is our special presentation of micron insight 18 hashtag micron insight 18 where the theme is accelerated intelligence the blending together of memory storage and artificial intelligence micron is a 40 year old company there's a dominant player in the DRAM marketplace years and years ago they used to be 1920 manufacturers of DRAM there's really three companies now that dominate that market they own 96% of it micron Samsung and Toshiba I believe right is the third one and and so microns is 30 billion dollar company they've got about a 50 billion just under 50 billion dollar market cap growing like crazy 70% of their business comes from DRAM the balance comes from alternative storage and other memory systems that they built and traditionally David memories have been a very cyclical business micron number two semiconductor manufacturer worldwide behind Intel obviously competing with a lot of overseas players and micron is putting forth the premise that they've begun to be able to dampen the fluctuations the peaks in the valleys in this business why because first of all the capital expense required to participate in this business is enormous that's why somebody companies have been shaken out and secondly the technology transitions are getting much much more difficult and so the premise that micron put forth in May at their financial analyst conference is that the cyclic allottee of this business is starting to moderate we've certainly seen this in some regards in the last several years with component shortages it's been a boon to Microsoft's financials the stock you know up until recently have been been climbing like crazy this is a company that has literally last quarter had seventy percent gross margins in its in business it's not and much much you know and if you look at the SSD business the flash business smaller gross margin maybe 48 50 percent they're gonna start blending those together and reporting on a blended basis I think they don't want Michael Dell you know advertising to Michael Dell that we're getting 70% gross margins on T Ram so they're gonna stop giving that guidance out excessively B to thwart competition but really it's probably examination probably something that's not sustainable but David so we're seeing sort of moderation and supply growth we're seeing a very well-run company this company is growing like crazy let me break down some of the businesses and I want to bring you into the conversation the compute and networking business very strong a grew at 53 percent year-over-year the mobile business up sixty percent last year Mobile's taking tons of of memory of course and and storage the embedded business which is sort of automobiles and and industrial markets is up about 12% and the storage business unit actually is gonna flat to down they expect growth but you know the stores business has been you know a bit of a challenge for them even though you know they're doing very well and they're gaining share they've gone through some transitions that we'll talk about to some of the executives here but but David the theme really is about about bringing artificial intelligence to the world and the intersection between AI and memory and storage obviously you need memory obviously you need storage to make AI happen and you know micron in the value chain at the lowest level is right there making tons of money shipping a lot of product driving a lot of innovation and competing very effectively so your thoughts on micron and right those are this event my car crushing it I mean the the growth in in in their revenues from DRAM with 70 percent year-on-year last four quarters to the four quarters before that was 70 percent desam that's actually was it's 70 percent of their business it was about 50 percent 47 to 50 percent growth so yeah well for the DRAM piece of the business well NAND is about 25 26 percent of the business and and growing you know about 20% a year yeah I think they're on the calling it's tiny but so the the figures the we're using a even better than that so I think as it fundamentally they're crushing it from from a business perspective and they're in as you said in a very good place because as AI takes place as what I call the matrix applications are coming on board that's a virtual reality augmented reality the the modern gaming machines all of these types of compute and then on top of that IOT as well with all the sensors and and the requirements of memory and and compute very very close to the Census themselves all of these different areas are relying on AI to make a difference of lying on that type of workload that matrix workload and some of the figures is very interesting to look at when you're looking at new workloads you need at least around six times as much DRAM and and and more storage as well more and Nan storage as well six times you're talking about the ratio between storage and the if you can take traditional processing you need for a tree you need six times that's interesting figure and and similarly with an and and and the on top of that when you're looking at graphics work all the graphics work that's very very bandwidth intensive and that requires the very latest technology and again premium technology to go into the graphics side of things as well so they are in a the right place at the right time in terms of the speed of which memory is is developing and the opportunities to make a difference so if you think about some of the tail winds and headwinds in their business there's a lot of tailwind I mean they're manufacturing efficiencies they're really started to see a flywheel effect there and they're did micron has made a lot of investment in of technology transitions what's happening is the bit density growth for each new technology transfer transition is starting to moderate presumably Moore's Law story to moderate right is what's really going on there and but they've really done a good job of investing in technology transitions ahead of their competition and so they're getting some good returns on that investment investment they lead in a lot of these markets they're a very well-run company pricing has been pretty firm for them over the last several years so that's been a nice tailwind and supply has been short in the last several years now they're the the headwinds are there are CPU shortages in the marketplace today and so if you can't can't get the CPU you can't necessarily make the box you can't ship the PC or you can't you know you need you need CPU memory and storage to go together and as a result there's a pending oversupply it looks like and so they're having to manage some of that inventory import tariffs from China not you know that's a I would say huge deal for these guys is something they can manage but you know president Trump's tariff posture it doesn't help a company like micron their tax rate is much higher this year than it was last year it's about going from 4% to like 28% and so those are some of the the headwinds and that's ahead the stock moderate a little bit but the stock has been on fire for the last several years and the company has done very very well cash flow is it's nine billion free cash flow which is important because they have to spend eight billion dollars a year more even they're growing that capex spending from 8 billion this year to 10 and a half billion next year so you get a sense of the various to entry in this marketplace it takes a lot of tenacity which I like micron is exhibited over the last 40 years when you think about all the ebbs and flows but the big changes are this used to be kind of driven by pcs it used to be a PC centered world and now we're seeing a much more diverse customer customer base probably driven by mobile no question about it the data center guys the big hyper scale is the autonomous vehicle folks the industrial internet edge computing they all need memory they all need storage the other piece of this is the transition from spinning hard disk to flash even though it's not a majority of their business today micron is in a very well position very well positioned to take advantage of that David something that you were the first in the industry to call he was a very first analyst that said that SSD flash is going to replace spinning disk it's clearly happening and it happened first in laptops and it's clearly happening in the in the data center you know with some exceptions but generally speaking that trend is pretty substantial you don't absolutely the that the technology changes we keep on saying each year we've witnessed the the most change in technology that we've ever seen and next year it gets faster and it gets faster it's absolutely amazing I think there's another area coming into play when you're looking at the traditional marketplaces they were the PC and the servers that's what we're most of the of the DRAM went we're seeing a change with mobile taking an increasing portion of that you're looking at PCs now they're introducing the the arm pcs as well and then grow ARM processors in the PCs so and that's growing very fast as as well and we're predicting that will go fast and we're looking at also at a very aggressive entry into the market place of ARM processors in general all the way through from from from the edge all the way through up to the top and therefore there's and those are really being designed for this matrix computing I was talking about met much more attention to parallelism to the ability to have GPUs inside it neural networks inside it that is that change and that that that requirement to fit in with this new way of doing is is a fantastic opportunity and they have an opportunity really to lead and powering some of these new workload so we're gonna be unpacking this all all day here at micron inside hashtag micron insight 18 you're watching the cube Dave Volante for David floor we'll be right back right after this short break

>> Live from San Francisco, it's theCUBE, covering Micron Insight 2018. Brought to you by Micron. >> Welcome back to the Embarcadero everybody here in the heart of San Francisco. Actually at the bay of San Francisco. Golden Gate Bridge is that way, financial district over there, Nob Hill right up the street. You're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante, this is David Floyer, and we're covering the Micron Insight 2018 event. People are starting to filter in. Any minute now we're going to start the keynotes from the executives. A lot of buzz going on, Derek Dicker is here. He's the corporate vice-president and general manager of the storage business unit emerging activity within Micron, great to see you again. >> Thank you very much for having me. It's a pleasure to be here. >> You're very welcome, yeah, so Micron used to be just a straight memory company. We're hearing, we heard at the investor day in May how you guys are diversifying, finding new use cases, new applications, you run the storage business, and of course David Floyer was one of the first, the first, in my opinion, to predict the demise of the hard disk, spinning disk, and it's a tailwind for you guys, but Derek, take us through your business unit, your role, and let's get into it. >> Sure, that sounds great. I appreciate the opportunity again to be here. The storage business unit within Micron is actually comprised across a couple of product areas. Primarily NAND and NAND components, and then also SSDs, solid state drives. As we like to say, and we've talked a bit more about it since Sanjay's arrival, we have a pretty material focus on accelerating what we call high value solutions. It's a big focus of ours, so not only are we developing the core technology in memory and storage, but we're attempting to build more and more products that add value to our customers in the S-System space. But that's generally the storage business focus. Within the company, we have three other business units that focus on compute and networking memory as well as the embedded business unit and then the mobile business unit. >> Talk about some of the big trends that you see, I mean, we've talked about for years, the all-flash data center. We clearly see that in the customers that we work with. Some of the spinning disk guys don't necessarily fully buy into that, but even they have been investing in flash technologies. What are you seeing? >> I tell you, there is no better time, in my opinion, than to be in the memory and storage industry. When you look at what the trends are that are coming out in time. If you go and you stare at how memory and storage has evolved just going back into the 80s or the PC era, a $35 billion average size of the total market. You get into the mobile space, when mobile era started with smart phones, we were looking at a $62 billion-ish, and then in '17 we cleared $120 billion in size of the market, and we actually see a lot of secular trends that are going to continue to take us forward. A couple of things that are particularly noteworthy for us. The first one is the emergence of artificial intelligence, and machine learning, and deep learning. We're going to hear quite a bit about it here at the event. But in terms of a value driver for the consumption of both memory, DRAM, as well as storage, we see it going phenomenally up in content in every server that's purchased out in time. That's one, I think with the evolution of 5G out in time, we're also going to see that smart phone devices are going to end up having more memory to add features like facial recognition we see today, becoming mainstream, multiple cameras, that drives more DRAM content, but then also on top of that, storage is increasing. We're seeing, even today, a terabyte being put into some of the high-end phones, and we know that that's going to waterfall out in time. So I think if you look at this combination of what's happening both in the devices, you look at what's happening in the infrastructure, then you couple that with the processing that needs to happen, it's just an awesome time to be affiliated with memory and storage. >> Yeah, well, I've been following this LAN marketplace for the last, almost 10 years isn't it? More than that. And it's just broken through completely in the last two or three years. What are your thoughts about pushing compute closer and closer to that memory, adding to, for example, the SSDs, the capability of doing smart work? It's very very close to where the data is originally going to be placed? >> It's a great area of quite a bit of R&D work that's going on right now, and I actually think I view this as kind of two stages. One is there's the proliferation of solid state, as you suggested, it's been coming over time. I actually see it increasing dramatically as we look forward, and one of the key technologies that I think is going to enable that is QLC. The fact that we're now at a point where we're putting four bits per cell into devices, SSDs are starting to show up, I think that just creates even more opportunity. And I'll talk a little bit about that in just a minute, but I want to answer your direct question as to how that's changing with AnIML. But I think the ability, once solid state is prolific, to be able to architect systems where you can actually have processing take place closer to the media is a very interesting area. It's right with a ton of research going on right now. People are just starting to implement it. I think there's quite a bit of potential sitting behind it. You know, our focus, of course, is we're deploying, and as quickly as we can, on two vectors. One is, how do we proliferate more solid state into the market as an industry, and the second is how do we add value when we build those solid state drives, so I think it's definitely very viable. >> Let's talk about the significance of QLC. David, your forecasts early on were very aggressive in terms of pricing declines for flash. We kind of, maybe got caught off, a little bit surprised by the-- >> I think we were caught off by the demand. >> Well the demand, but also the supply constraints kept prices up. >> Yeah. >> Okay so, it didn't actually happen as fast. How does QLC change that, Derek, and what's the significance of it? >> Well, the thing that I think is most exciting for us as Micron is we actually ended up delivering the world's first QLC device. It put a terabit of data on a single die, which was unprecedented, but then in addition to that, what we did was we actually built a solid state drive called the 5210 ION. This is a standard drive. It's the worlds first SSD built on the technology, and by being able to develop a solution early on, it allowed us to go engage with customers and find where the right workloads were where we could add the most value. QLC technology actually is perfectly aligned for super read intensive, very read intensive environments, and if you look at what's happening in the data center, we're actually seeing more and more workloads move into more read intensive workloads, and a good chunk of that is just because there's analytics going on. The data's being collected. It's being housed in on place, but as we've talked about quite a bit here at the event, we want to be able to deliver insight out of that data, which means we're going to be reading it quite a bit, and massaging it, and performing analytics on it. And what we're now seeing is what, in the days of the past, was a four to one read to write ratio, we're seeing as high as 5,000 to one and in some cases a million to one. So we get these heavily read intensive workloads coupled with the technology that's optimized for it. It's more power efficient than what rotating media solutions offer in certain workloads, we're starting to see these tremendous values coming out of these early engagements that we're having with customers. >> And does that have implications for longevity, or do you just make an assumption that the read/write ratio is still going to be more write intensive in terms of wear leveling and things like that? How does it change the reliability, if you will, of the technology? >> Actually the beauty is, we're able to deliver an enterprise class SSD with these read/write capabilities that are affiliated with these read intensive solutions, and we can fit within the workloads and the needs that people are talking about. So the drive writes per day that are required in a machine learning infrastructure, we believe we can address with QLC. Same thing with Hadoop style clusters and Ceph clusters. We've actually, as we've gone out and engaged each of our earlier customers, we're able to crank out reference architecture documents that we're now posting to our websites, and we're describing how we can actually leverage this technology to allow us to, in some cases, we'll better optimize where an SSD was used before. But in many, many cases we're actually in the process of displacing hard disk drives. >> So what are the limits of this QLC? How many more bits can we add? How many more layers can we add? >> So, it's actually a great question, David. In terms of what does a roadmap look like. I've been asked in the recent several hours, what the longevity for NAND looks like. And what I'll tell you is this, QLC NAND is just getting its start. What comes after that in terms of bits per cell, I don't think anybody's made any broad claims on. But from a layer stacking perspective, which is kind of the dimension upon which the industry is growing, for the foreseeable future, we see nothing that encumbers us from going substantially higher and higher layer count. Which I think is going to be great for our industry because it's going to allow us to deliver more bits in a given device, and hopefully, that'll allow us to get into markets that, historically, we haven't been able to approach. If you think about the demand elasticity dynamic that occur when we start to bring more and more costs down, the number of applications open up, not unlike the machine learning workloads I just mentioned or Hadoop workloads. We're starting to see more and more thirst and interest for replacing with solid state, just because it's more power efficient, allows for a cost structure that's better, and gives better performance too. >> I'm fond of saying that data's plentiful, insights aren't. You guys are a $30 billion company now. You're making some interesting announcements today that we're going to hear about a little later on that I won't divulge right now, but you're putting your hands in a lot of different places. When you're that size of a company, you can't help but, as you mentioned before, adding more value, becoming more of a systems focus. How do you help the industry go from just raw data to insights? What's your role in that? >> Oh, it's a phenomenal question and this is a major focus of the company. Not just in our business unit, but across all of the different business units in the company. We have a huge focus on sitting down with our customers and getting closer and closer to understanding what their workload needs are, where their paying points are, and then working with them to find solutions, and the beautiful part about it is, as Micron, we're the only company in the world that can combine together a 3D XPoint set of technologies, a NAND set of technologies, a DRAM set of technologies. We go sit down and talk about these challenges with those in mind, plus the emerging memories that we're developing to go develop better and better solutions. But after we're able to come to a solution, we put together a reference architecture, and we deploy it broadly. >> We've been trying to squint through 3D Xpoint and understand the right fit. It seems to us that one of the big advantages of flash was it had the, had this behind it. (laughs) It had the consumer volumes, thank you Steve Jobs. It's unclear whether or not 3D Xpoint will have that, maybe have the same, sort of, cost advantages, but the same time, it sounds like there's new and emerging applications. Like I said, we're trying to figure out. Have you guys figured out yet? You're obviously betting big on the technology. Help us understand where the fit is. >> Sure, I think, you know, if I look back in time, just at the storage hierarchy alone, I don't think the memory hierarchy's any different. You have these portions of the market where you build out hard disk drives, and we had DRAM before, and SSDs came along, and people started asking, not unlike several years back when we talked about the early parts. Hey, how big is this going to get? Cost structures may be prohibitive. But as innovation unfurled, the more time and investment got placed into it, we found new workloads, new use cases we were able to drive costs out, and we ended up slotting in solid state drives squarely. I think this is another tier of memory and storage. That's the beauty of the 3D XP technology. There's both memory semantics and storage semantics that are available for use. I think we're still scratching the surface on the early days, but I love what we're seeing from the customer base that we're engaging and targeting in this space. >> And people will pay up for that performance capability relative to flash. They'll pay down relative to DRAM. Is it, are you seeing a gradience for like the hyperscalers, for example, or is it, maybe the industrial internet? Where are you seeing the. >> It's fair, actually I think, you know, it's probably reasonable to say that, you know, the challenges of inserting a new memory tier into a system requires new programming algorithms, new APIs and interface. There's a lot of ecosystem that needs to be there, as well as, not to mention, you've got to have an ecosystem to go put memory products into a server, for instance, or any other platform. I think we're still early days of enabling all of this. And I also believe we're going to learn more and more where the value of this sits as we put it out there in a cost effective fashion. So I would say that people who control software environments are very, very well suited for this because they can take advantage of some of those challenges without having to have a whole ecosystem in place. I think there's going to be a continued ramp in acceleration as an industry we go build out that ecosystem. >> Well it's been amazing to watch Micron the last several years, I mean, the last several decades. When you were just a pure memory manufacturer which was diversified, you know, gorilla in this space. (laughs) You guys are really an extremely well run company. I mean, your financials have born that out. You're really transparent to the street providing great guidance and congratulations on all of the success. I'm looking forward to watching in the future. >> Oh thank you so much. It's a privilege to be part of the company, and I really appreciate your time today. >> Our pleasure, thanks for coming on theCUBE. All right, keep it right there everybody. We'll be back with our next guest right after this short break. You're watching theCUBE from Micron Insight 2018. (upbeat techno music)

>> Voiceover: Live from Las Vegas, it's the CUBE. Covering AWS re:Invent 2017, presented by AWS, Intel and our ecosystem of partners. >> Hey welcome back to AWS Reinvent 2017. I'm Lisa Martin, very well-caffeinated today, so is David Floyer, we're really excited to be joined by two newcomers to the CUBE. We have Ryan Baxter, the director of cloud and verticals from Micron, welcome. >> Thank you. And Mo Farhat, director of SSD business line management, a marketing guy, welcome guys. >> Ryan: Thank you. >> Mo: Thank you, thank you. >> So Micron, a 35-year-old business. You must have seen massive changes in the last 35 years, but tell us what you guys are doing with AWS. What's exciting you about the announcements coming out, how are you partnering with them? >> Well, as you're seeing around you today, the rise of hyper scale is the true story in IT. And we're closely engaged with AWS to support their storage, memory, and emerging memory technologies as well. And we're tremendously excited by the potential that AWS that can bring to the market and is bringing to the market today. >> So let's unwrap that a little bit more. One of the things that seems to be happening is that the traditional nexus of networking, storage, going all the through the central processor is breaking up. >> Mo: Right. >> And you've got some very interesting stuff with the NVDIMMS. Can you talk a little bit about that and what does it mean to architecture? >> Sure, so I don't know what line isn't blurring these days, when it comes to computing, so we are certainly developing and pushing and product today called NVDIMM. It is the first example of persistent memory which we believe will really usher in a completely new model, and really a way of thinking about, the way folks do compute. It really requires some change on the system side, but the advantages are significant. With just a little bit of investment in terms of adjustments and software, and the way you use hardware, what you can gain from a performance perspective is enormous. >> By having large amounts of D-RAM and behind it, a large amount of Nand storage, and that combination of the two together on the same piece that goes in the computer suddenly multiplies by, how many, 10 times? >> Oh gosh, at least an order of magnitude. We're pretty excited about where this can go, and obviously it doesn't come for free. There will be some investment as far as the application stack, and how things need to change from a hardware enablement perspective, but yeah, things are changing very quickly. The traditional model of really memory and storage is very much at risk and very much blurring these days, and we're excited about where it's going. >> So let's talk about the SSDs. I've been following the flash market for a long time, and saying what a difference it makes to applications in the amount of data that they can get into them, both from the memory side and the storage side. So what's happening on the SSD side? What are you focusing on? >> Well what's most exciting about the developments in SSD today isn't just that they're accelerating existing workloads, but they're enabling all new workloads. Things like real-time analytics to drive our AI engines have revolutionary potential for our daily lives, and not just in the data center. And so when we take a look at what's happening in the SSD market today, the big story is the ramp in adoption in PCIE-connected or NVME SSDs. And we believe that we're at a turning point right now you know, led by AWS and other hyperscalers, and truly driving this adoption. And what NVME allows you to do is really harness the inherent parallelism of solid memory technology, solid state memory technology, and enable better control, enable lower latency, higher throughput and really move away from the legacy IO stack that was built for the hard drive era. Or as we like to call it at Micron, spinning rust. >> Ryan: Yeah. (laughs) >> And that's really amazing, isn't it? If you can have real-time analytics connecting to systems of record at the same time, that ushers in a complete, what we call at Wikibon, systems of intelligence, a completely new way of being able to provide much, much more data to those systems and drive productivity by an order, again, really very high level's difference of the type of applications that you can have. So let me ask you, this is a lot of change that we talked about, where we're taking out the network side, we're taking out the storage side, and the memory side. What's some of the most important things about getting this to happen over the next few years? >> Right, well I think, I'll start I guess. One of the most important things in our minds is paying attention to the customers, and really what drives them, what provides the most value for their deployments in the cloud. We have the privilege of working with folks like AWS because these customers, at the end of the day, challenge us to be better. They challenge us to maintain or improve our quality levels. They challenge us to be more flexible from a go-to-market and business model perspective. And frankly, a lot of the features that they're looking at incorporating into otherwise standard products today, actually end up finding their way into the next generation products that we design tomorrow. So it informs a lot of the way we need to think about traditional memory and storage models in the future. >> What about the standards that are required? >> The standards? >> Yeah. >> Yeah so, the standards bodies are alive and well, and are absolutely necessary for what we need to do to push our products into the market on a daily basis. Oftentimes those standards are too rigid, or not feature-laden enough to be able to get enough benefit for the particular end customer. So in those cases, we're sort of having to bend the model a little bit. Our products are based on a relatively straightforward set of foundational standards, but from there, we listen to the customer to enable new features, new capability of our otherwise standard products. >> Absolutely and in fact, Micron today is really working with our customers up front in helping drive the standards, with deep technical engagement on next generation, NVME features, as well as next generation form factors. You know, really our technology leadership in D-RAM, Nand, everything in between really positions Micron very strongly to shape the future here, and we can't do it without strong customer engagement, and we're really very excited about the potential for a future here. >> Yeah. >> Fantastic. >> How does the standards focus that you guys have, how does that set Micron apart from your competition? >> Well it helps us be a good player in the industry. It helps cement leadership. It allows us to have a playing field that goes to the benefit of our customers, our partners, and delivering predictability to the market, delivering overall lower cost to the market, and all the other ancillary benefits, that agreement our standards provide. >> I loved what you talked about with respect to working together in partnership with your customers. We hear a lot about that from AWS. They're very customer-centric. There was an article on siliconangle.com this morning, it was the third installation of John Furrier's exclusive with Andy Jassy. And I love their kind of backwards approach to product development. Which is really is surprisingly still revolutionary. The customer is such a driving force into what Amazon has become, and it sounds like what you're both saying, that's really very much paralleled at Micron. >> Absolutely, you know leading is hard. When you're firmly looking forward and really blazing new trails in technology, in our product set here, and really driving the revolution towards the solid state data center. You can't do it looking in the rear view mirror. You've got to go in collaboration. It's really some of the most exciting things that we do here is really enabling our customers to succeed. >> And your focus at the moment, I'm putting words in your mouth, I presume that's really weird that cloud providers, the hyperscale people like AWS, like Microsoft, like Google, are those sort of where you're starting the conversations and then that will come down into the enterprise as well after that. Is that the model? >> You know, we provide solutions to a broad range of customers. >> Okay, yeah. >> There is no doubt that hyperscale is in the driver's seat in terms of demand now and into the future for IT technology of all stripes. So we're very focused on it. >> Yeah and there are cloud models that obviously are heavily supported by our OEM customers as well. So maintaining engagement and really being best in class in their eyes is also extremely important for us. >> So this event, I actually heard this morning, 44,000 people here across the entire Strip. Last year, it was around 30,000 or so. How does this massive momentum that AWS has, how does that inspire Micron, and what can people see, feel, touch and experience at your booth here in the expo? >> Again, the growth in the number of attendees is nothing compared to the growth in AWS's business overall. These numbers are truly inspiring. They're changing the landscape of IT today, and so you know, encourage everybody to come by our booth and look at the variety of solutions that we have, both on the SSD side, memory side, as well as the all-popular NVDIMMs. >> And I think what events like this help to do is mobilize 44,000 of the brightest people in the world that come from all different walks of life, not just from a technical perspective, but software, hardware, application-oriented marketing to really have a meeting of the minds, if you will. And it really does, it challenges the traditional way of thinking of how we design our solutions, and how we support customers like AWS. >> Well guys, thank you so much for stopping by and chatting with David and me. >> Thank you very much. >> Really exciting to hear what you guys are doing, and we wish you continued success. >> Thank you very much. >> Thank you, Lisa. (crosstalk) >> For Mo and Ryan, and my co-host David Floyer, I am Lisa Martin, you're watching the CUBE live on Day 2 at SWA 2017 re:Invent. Stick around, we'll be right back. (electronic music)

(exciting, upbeat music) >> (Announcer) Live from Orlando, Florida. It's theCUBE, covering ServiceNow Knowledge '17. Brought to you by ServiceNow. >> We're back. Dave Vellante with Jeff Frick. This is theCube and we're here at ServiceNow Knowledge '17. Stanley Toh is here, he's the Global IT Director at semiconductor manufacturer Broadcom. Stanley, thanks for coming to theCUBE. >> Nice to be here. >> So, semiconductor, hot space right now. Things are going crazy and it's a good market, booming. That's good, it's always good to be in a hot space. But we're here at Knowledge. Maybe talk a little bit about your role, and then we'll get into what you're doing with ServiceNow. >> Sure. You're right. Semiconductor is booming. But we don't do anything sexy. Everything is components that go into your iPhones and stuff like that. They do the sexy stuff. We do the thing that make it work. So, I'm the what we call the Enterprise and User Services Director, so basically anything that touches the end user, from the help desk to collaboration to your PC support desk, everything is under. Basically anything that touches the end user, even onboarding, and then, now with the latest, we actually moved our old customer support portal to even ServiceNow CSM. >> Okay, so what led you to ServiceNow? Maybe take us back, and take us through the before and the after. >> Okay. Broadcom Limited, before we changed our name to Broadcom, we were Avago Technologies. We are very cloud centric. Anything that we can move to the cloud, we moved to the cloud. So we were the first multi-billion dollar company to move to Google, back in 2007. That was 10 years ago. And then we never stopped since. We have Opta, we have Workday. And if you look at it, all this cloud technology works so well with ServiceNow. And ServiceNow is a platform that has all the API and connectors to all these other cloud platforms. So, when we were looking and evaluating, first as just the ITSM replacement, we selected ServiceNow because of the ease of integration. But as we get into ServiceNow, and as we learn ServiceNow, we found that it's not just an ITSM platform. You can use it for HR, for finance, for legal, for facilities. Recently, probably about six months ago, we launched the HR module. And then three weeks ago, we went live with a CSM portal for the external customer. >> When you say you go back to 2007 with Google, you're talking about what, Google Docs? >> Everything. >> Dave: Everything. >> Email, calendar, docs, sites, Drive, but it was unknown. >> Dave: All the productivity stuff. >> Everything. >> Dave: Outsourced stuff. >> They were unknown then, >> Jeff: Right, right, right. >> And it's a risk. >> So what was the conversation to take that risk? Because obviously there was a lot of concern at the enterprise level on some of these cloud services beyond test/dev in the early days. Obviously you made the right bet, it worked out pretty well. (Stanley laughing) But I'm curious, what were the conversations and why did you ultimately decide to make that bet? >> Okay. So 2007 was just after the downturn. >> Jeff: Right. >> So everyone was looking at cost, at supportability. But at the same time, the mobile phone, the smart phone is just exploding in the market. So we want something that is very flexible, very scalable, and very easy to integrate, plus also give you mobility. So that's why we went with Google as the first cloud platform, but then we started adding. So right now, we can basically do everything on your smart phone. We have Opta as our single sign-on. From one portal, I go everywhere. >> Dave: Okay, so that's good. So you talked about some of the criteria for the platform. How has that affected how you do business, how you do IT business? >> See, IT has always been looked upon as a cost center. And we are always slow, legacy system, hard to use, we don't listen to you. (Jeff laughing) >> Dave: What do those guys do? >> You know, why are we paying those guys, right? And then you look at all the consumer stuff. They are sexy, they are mobile, they have pretty pictures. Now all your internal users want the same experience. So, the experience has changed. The old UNIX command key doesn't work anymore. They want something touch, GUI, mobile. They want the feel, the color, you know. >> That might be the best description (Stanley laughing) of the consumerization of IT, Dave, that we've ever had on theCUBE. >> It's really honest. Coming from an IT person, it is, it is honest. And now you've driven ServiceNow into other areas beyond IT. >> Stanley: Yes. >> You mentioned HR. >> HR. We went live six months ago. >> Okay. And these other areas, are you thinking about it, looking at it, or? >> So we are also looking with legal, because they have a lot of legal documents and NDAs and stuff like that. And ServiceNow have a very nice integration to DocuSign and Vox. So we are looking at that. But the latest one, we went live three weeks ago, is the CSM, the customer support management portal. And that one actually replaced one of our legacy system that has a stack of sixteen application running. And we collapsed that, and went live on ServiceNow CSM three weeks ago. >> And what has been, two impacts - the business impact, and, I'm curious, is it the culture impact. You sort of set it up as the attitude. We had fun with it, but it's true. What's the business impact? And what has the cultural impact been? >> The last few years, we have been doing a lot of acquisition. So we have been bringing in a lot of new BU's. Business units. And they want things to move fast, and we want to integrate them into one brand. So speed and agility is key when you do acquisitions. So that's why we are moving into a platform where we can integrate all these new companies easily. We found that in ServiceNow and we can integrate them. So for example, when we acquired Broadcom Corporation, they have 18,000 employees. We onboarded them on day one, and usually when you do an acquisition, they don't give you the employee information until the last minute. Two days, all I need, is to bring them all on, onboarded into my collaboration suite. I only need two days of the information, and on day one, Turn it on, they are live. Their information is in, they have an email account. All their information is in ServiceNow. They call one help desk, they call our help desk, they get all the help and services. So it's fully integrated on day one itself. >> And you guys also own LSI now, right? >> Yes, LSI. >> Emulex? >> Emulex, PLX. >> PLX. >> The latest acquisition is Brocade, which we will close in the summer. And then, the rumored Toshiba NAND business. So, yeah, we are doing a lot of acquisitions. >> Yeah, quite a roll-up there. >> Correct. So as you can see, they are all very different companies. So when they come in, they have different culture. They have different workflow, they have different processes. But if you integrate them into a platform that we are very familiar right now, it's the consumerized look and feel, it's very easy to bring them in. >> And that is the cultural change that has occurred. >> Yes, it's a huge, >> So do people love IT now? >> They still hate IT. (Jeff and Dave laughing) They still say iT is a cost center. But right now, they are coming around. They see that we are bringing value to them. So right now, IT is just not to provide you the basic. IT is to enable the business to be better and more competitive. >> A true partner for the business. >> Yes, correct. >> Stanley, thanks very much for coming to theCUBE. It was great to hear your story, we appreciate it. >> Stanley: Thanks for having me. >> You're welcome. All right, keep it right there, buddy. We'll be back with our next guest. This is theCUBE, we're live from ServiceNow Knowledge '17. We'll be right back. (upbeat music)