>>Live from San Francisco. It's the cube covering micron insight 2019 brought to you by micron. >>We'll come back to San Francisco. Everybody wears pier 27. This is the queue. We're following micron insight 2019. Dave Volante with David flora. Theresa Kelly is here. She is the vice president of the CPG consumer products group at my country. So thanks for running over to the cube for a moment. >>Glad to be here. Thank you. So tell us about CPG. What's the, what's the scope? >> So CPG is a consumer products group. We have a crucial Grande that's been around for 23 years. Uh, we sell to you and you and me. And we provide SSD solutions and DRAM solutions. So it could be someone upgrading their computer, it can be someone that is trying to be a gamer because we have high performance DRAM. And today we announced we broke the world record. Yeah. So with a, an AMD platform and ASIS, uh, a team. So the three teams, partners, so pretty excited about that. Tell us about the hard news. What are the announcements that you made? So I just mentioned that we broke the record. So we were able to achieve a, a speed of 6,024 mega transfers with the AMD, um, partnership. And as soon as, so pretty excited about that because that just shows we are, you know, a vertically integrated company and we're great. We've got great product out there and we provide that to the gamers out there and are able to give a group a solution both at the mainstream and the high end performance. >> And then that's a major growth area. That game is, yes, it is a couple of these shows. Yes, yes. Different normal than number audiences they get in person and online. So you got it. >>So when we started the cube, we started on Justin TV, which became, >>which we used to get so much traffic. We're like, where's all this traffic coming from? You know, what it was, it was the gamers, so. Huh. What's the importance of gaming? Well, let's start, >> you mentioned Twitch. We've got one of the teams we sponsor that's a big Twitch, uh, following up there, the energy team. And so they're one of the, uh, both set better happening. So, you know, from a gaming perspective, it, it, it is a very, you know, one of the fastest growing, uh, consumer DRAM markets. And it is something that allows us to put both DRAM and SSD out there to the consumer. We sell to the consumer. We also partner with those that make those platforms. You know, it could be someone upgrading a computer or um, someone that's buying it in the store. So pretty excited about because we have both solutions and are, are both vertically integrated, which no one else has. >>Some gamers need. They need memory, they need need. Joe's about more about the, the crucial brand. You know, you guys are amplifying that know what's behind the brand and what's the brand promise. Yeah, crucial is um, having met with some friends yesterday, they said, you are a trusted brand. We know we're gonna get quality product from you. We ask what do we know now? And we do, we deliver on what we say. We don't make hype news. We very much are able to say we're going to deliver such a product and, and bring that back to you. And we're known for great customer support too. We've spent time over the past 12 months continuing to build out a portfolio for our consumers and they've, the response has been great. Both again on the SSD side and on the DRAM side. So it is, it's a brand that is worldwide. We're across the world. We sell places like Amazon but also a lot in Europe and in Asia. There's still a lot of retail, so we saw to retail too and or@crucial.com so we're provide solutions. >>Well it's good. Yeah. Consumer spending is powering our economy right now, so that's great. Last question is what should we expect going forward? You know, give us some guideposts. >>So you know, we have, as with the announcements today, I mentioned, I hadn't mentioned that the exit was announced today. It's our portable SSD almost twice as fast as any SSD portable SSD out there with that price point. So pretty excited for that. Again, giving great, you know, value for our money with our vertical integration. And we definitely have, um, insights into wine to build, uh, a broader portfolio in time for our consumers and we look to them and where the market's going to provide the solutions. And as mentioned, gaming is very important to us, so we intend to continue to have investments there too. >>Love, it sure is the gift that keeps on giving, right? We keep increasing capacities, lowering costs, and now increasing performance. Theresa, thanks very much for coming on the. Okay. Give right there. We be back shortly. Is this the cube from micron inside 2019.

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 New York it's the cube covering the cube New York City 2018 brought to you by silicon angle media and its ecosystem partners i'm jeff workday Villante we're here nine years our nine years of coverage two days live in New York City and our next two guests shot Mrazek CEO amana stayed at fiendish males CMO mystic good to see you again welcome back thank you bad to be here guys so obviously this show we've been here nine years we were the first original Hadoop world we've seen a change Hadoop was gonna change the world it kind of didn't but we get the idea of it did not it did didn't but it would change our world it brought open source and the notion of low-cost Hardware into the big data game and then the big data became so much more powerful around these new tools but then the cloud comes in full throttles and while they can get horsepower that compute you can stand up infrastructure for analytics all this data goodness starts to change machine learning then becomes the the real utility that's showing this demand for using data right now not the set up using data this is a fundamental big trend so I don't get you guys reaction what do you see this evolving more cloud like how do you guys see the trend in this as data science certainly becoming more mainstream and productivity users to hardcore users and then you got cloud native developers doing things like kubernetes we've heard kubernetes here it's like a cloud is a data science what's going on what's your view of the market so I came from a company that was in an tech and we were built on big data and in looking at how big data is evolved and the movement towards analytics and machine learning it really being enabled by Big Data people have rushed to build these solutions and they've done a great job but it was always about what's the solution to my problem how do i leverage this data and they built out these platforms and in our context what we've seen is that enterprises get to a certain point where they say okay i've got all these different stacks that have been built these apps that have been built to solve my bi and analytics problems but what do I do about how do I manage all these and that's what I encounter my last company where we built everything ourselves and then so wait a minute but what we see at an enterprise level is fascinating because when I go to a large company I go you know we work with no sequel databases and Hadoop and you know how much Couchbase do you have how much Mongo etc the inevitable answer is yes and five of each right and they're cutting to this point where I've got all this distributed data distributed across my organization how am I going to actually manage it and make sure that that data is protected that I can migrate to the cloud or in a hybrid cloud environment and all these questions start to come up at an enterprise level we actually have had some very high-level discussions at a large financial institution here in New York where they literally brought 26 people to the meeting the initial meeting this was literally a second call where we were presenting our capability because they're they're now at the point where it's like this is mission-critical data this is not just some cool stuff somebody built off in one of our divisions it matters to the whole enterprise how do we make sure that data is protected backed up how do we move data around and that's really the the trend that we're tapping into and that the founders of our company saw many years ago and said I need to I need to we need to build a solution around this it's interesting you know you think about network data as a concept or data in general it's kind of got the same concepts we've seen in networking and/or cloud a control plane of some sorts out there and you know we're networking kind of went wrong as the management plane was different than the control plane so management and control or huge issues I mean you bring up this sprawl of data these companies are data full it's not like hey we might have data in the future right they got data now they're like bursting with data one what's the control plane look like what's the management plane look like these are all there's a technical concepts but with that with that in mind this is a big problem what our company is doing right now what are what are some of the steps that are taking now to get a handle on the management the data management it's not just your grandfather's data management so we anymore it's different it looks different your thoughts on on this chain of management so they're approaching the problem now and that's our sweet spot but I don't think they have in their minds yet come to exactly how to solve it it's there's this realization about we need to do this at this point and and and in fact doing it right is something that our founders when they built Lee said look if this problem of data management across big data needs to be solved by a data we're platform built on big data so let's use big data techniques to solve the problem all right so let's before getting some of the solution you guys are doing take a minute to explain what you guys are doing for the company the mission you know the value proposition status what do you guys do how are people gonna consume your product I mean take a particular type gen simple elevator pitch and we were enterprise data management focused specific than had you been no sequel so everyone's familiar with the traditional space of data management in the relational space relational world very large market very mature market well we're tapping into is what John was just saying which is you've got this proliferation but Dupin no sequel and people are hitting the wall they're hitting the ceiling because they don't have the same level of operational tools that they need to be able to mainstream these deployments whether it's data protection whether it's orchestration whether it's migration whatever the case may be so what we do that's essentially our value prophecy at a management for a Dupin no sequel we help organizations essentially drive that control plane really around three buckets data protection if it's business critical I got to protect it okay disaster recovery falls into protection bucket good old stuff everyone's familiar with but not in Hadoop in no single space orchestrations the second big bucket for us which is I'm moving to an agile development model how do i do things like automated test dev how do i do things like GD are the compliance management how do i do things like cloud migration you tut you know john touched on this one before a really interesting trend that we're seeing is you said what are customers doing they're trying to create a unified taxonomy they're trying to create a unified data strategy which is why 26 people end up in the but in lieu of that there's this huge opportunity because of what they need they know that it's got to be protected and they have 12 different platforms and they also want to be able to do things like one Cosmo I'm on go today but I'll be cosmos tomorrow I'm a dupe today but I might be HD inside tomorrow I want to just move from one to the other I want to be able to do intelligence so essentially the problem that we solve is we give them that agility and we give them that protection as they're sort of figuring this all out so we have this right you basically come in and say look it you can have whatever platform you want for your day there whether it's Hadoop and with most equals get unstructured and structured data together which makes sense but protections specifically does it have to morph and get swapped out based upon a decision correct make well now we're focused specifically Hadoop and no sequel so we would not be playing like if you we're not the 21st vendor to be helping s AP and Oracle you know customers backup their data it's basically if your Hadoop renewal sequel that's the platform regardless of what Hadoop distribution you're doing or where it's no see you know change out your piece what they do as they evolve and are correct I feel exactly right you're filling white space right because when this whole movement started it was like you were saying commodity Hardware yeah and you had this this idea of pushing code to data and oh hey his life is so easy and all of a sudden there's no governance there's no data protection no business continuity is all his enterprise stuff I didn't you heard for a long time people were gonna bring enterprise grade to Hadoop but they really didn't focus on the data protection space correct or the orchestra either was in those buckets and you touch them just the last piece of that puzzle value wise is on the machine learning piece yeah we do protection we do orchestration and we're bringing machine learning to bear to automate protection what amazing we hear a lot and that's a huge concern because the HDFS clusters need to talk speech out there right so there's a lot of nuances and Hadoop that are great but also can create headache from a user human standpoint because you need exact errors can get folded I gotta write scripts it creates a huge problem on multiple fronts the whole notion of being eventually being clustered in the first base being eventually consistent in the second place it creates a huge opportunity for us because this notion of being a legs we get the question asked the question why well you know there are a lot of traditional vendors they're just getting into the space and then what do that that's actually good because it rises you know rises all boats if you will because we think we've got a pretty significant technology mode around our ability to provide protection orchestration for eventually consistent clustered environments which is radically different than the traditional I love the story about the 26 people showing them me take me through what happened because that's kind of like what your jonquil fishbowl what do they do it they sit in their auditing they take a node so they really raising their hand they peppering you with questions what what happened in that meeting tell us so so it's an interesting microcosm what's happening in these organizations because as the various divisions and kind of like the federated IT structure started building their own stuff and I think the cloud enabled that it's like you know basically giving a the middle finger to central IT and so I can do all this stuff myself and then the organization gets to this realization of like no we need a central way to approach data management so in this meeting basically so we had an initial meeting with a couple of senior people and said we are we are going about consolidating how we manage all this data across all these platforms we want you to come in and present so when we presented there was a lot of engagement a lot of questions you could also see people still though there's an element of I want to protect my world and so this organizational dynamic plays out but you know when you're at a fortune 50 company and data is everything there's the central control starts to assert itself again and that's what we saw in this because the consequences of not addressing it is what is potentially massive data you know data loss loss of millions hundreds of millions of dollars you know data is the gold now right is the new oil so the central organizations are starting to assert that so we say that see that playing out and that's why all these people were in this meeting which is good in a way because then we're not like okay we got to sell ten different groups or ten different organizations it's actually being so there's there's kind of this pull back to the center it's happened in the no sequel world of your perspectives on this I mean early on you had guys like Mongo took off because it was so simple to use and capture unstructured data and now you're hearing everybody's talking about you know acid compliance and enterprise you know great capabilities that's got to be a tailwind for you guys could you bring it in the data protection and orchestration component but yeah what do you see it in that world what do you guys support today and maybe give us a glimpse of the future sure so that what we see as well a couple different things we are we are agnostic to the databases in the sense that we are definitely in Switzerland we were we you know we support all commerce so it's you know it's follow the follow the follow of the market share if you will Cassandra Mongo couch data stacks right on down the line on the no sequel side and what's interesting so they have very there have all varying degrees of maturity in terms of what their enterprise capabilities are some of them offer sort of rudimentary backup type stuff some fancy they have more backup versus others but at the end of the day you know their core differentiation they each it's fascinating to each have sort of a unique value prop in terms of what they're good at so it's a very fragmented market so that's a challenge that's an opportunity for us but it's a challenge from a marketplace networkers they've got to carve out there they all want the biggest slice of the pie but it's very fragmented because each of them is good at doing something slightly different yeah okay and so that like the the situation described before is they've got yes so you got one of everything yeah so they've got 19 different backup and recovery right coordinate processes approach or the or nothing or scripting law so that they do have to they've got a zillion steps associated with that and they're all scripted and so their probability of a failure you know very you drop a mirror that's a human error to is another problem and you use the word tailwind and I think that's very appropriate because with most of these vendors they're there they've got their hands full just moving their database features forward right you know where the engagement so when we can come in and actually help them with a customer who's now like okay great thank you database platform what do you do for backup well we have a rudimentary thing we should belong with it but there is one of our partners a manas who can provide these like robust enterprise it really helps them so with some of those vendors were actually a lot of partner traction because they see it's like that's not what their their strength is and they got to focus on moving their database so I'll give you some stats I'm writing a piece right now a traditional enterprise back in recovery but I wonder if you could comment on how it applies to your world so these are these are research that David flora did and some survey work that we've done on average of global 2000 organizations will have 50 to 80 steps associated with its backup and recovery processes and they're generally automated with scripts which of course a fragile yeah right and their prefer own to era and it's basically because of all this complexity there's a 1 in 4 chance of encountering an error on recovery which is obviously going to lead to longer outages and you know if you look at I mean the average cost the downtime for a typical global global 2000 companies between 75 thousand and two hundred fifteen thousand dollars an hour right now I don't know is your world because it's data it's all digitally the worst built as a source is it probably higher end of the spectrum all those numbers go AHA all those numbers go up and here's why all those metrics tie back to a monolithic architecture the world is now micro services based apps and you're running these applications in clusters and distributor architectures drop a note which is common I mean think you know you're talking about you're talking about commodity hardware to come out of the infrastructure it's completely normal to drop notes drops off you just add one back in everything keeps going on if your script expects five nodes and now there's four everything goes sideways so the probability I would I don't have the same stats back but it's worse because the the likelihood of error based upon configuration changes something as simple as that and you said micro-services was interesting to is is that now is it just a data lake kind of idea of storing data and a new cluster with microservices now you're having data that's an input to another app check so now so that the level of outage 7so mole severity is multiple because there could be a revenue-generating app at good young some sort of recommendation engine for e-commerce or something yeah something that's important like sorry you can't get your bank balance right now can't you any transfers because the hadoo closes down okay this is pretty big yes so it's a little bit different than say oh well to have a guy go out there and add a new server maybe a little bit different yeah and this is the you know this is the type of those are the types of stats that organizations that we're talking to now are caring a lot more it speaks to the market maturity do you run into the problem of you know it's insurance yeah and so they don't want to pay for insurance but a big theme in that you know the traditional enterprises how do we get more out of this data whether it's helping manage you know this I guess where that that's where your orchestration comes in cloud management maybe cloud migration maybe talk about some of the non insurance value add to our components and how that's resonating with with cost yeah yeah I so I'll jump in but the yeah the non protection stuff the orchestration bucket we're actually seeing it comes back to the to the problem sting we just said before which is they don't have it's not a monolithic stack it's a micro services based stack they've got multiple data sources they've got multiple data types it's sort of a it's the it's the byproduct of essentially putting power into into divisions hands to drive these different data strategies so you know the whole cloud let me double click on cloud migrations is a is a huge value problem that we have we talked about this notion of being data where so the ability to I'm here today but I want to be somewhere else tomorrow is a very strong operational argument that we hear from customers that we also also hear from the SI community because they hear it from the other community the other piece of that puzzle is you also hear that from the cloud folks because you've got multiple data for platforms that you're dealing with that you need agility to move around and the second piece is you've got the cloud obviously there's a massive migration to the cloud particularly with the dubidouxs sequel workloads so how do I streamline that process how do I provide the agility to be able to go from point A to point B just from of migration standpoint so that's a very very important use case for us has a lot of strategic value like it's coming it's sort of the markets talking to us like no no no we have this is him but we have to be able to do this and then simple things like not simple but you know automated test step is a big deal for us everybody's moved agile development so they want to spin up you know I don't want it I don't want to basically I want 10% of my data set I want to mask out my PII data I want to spin it up on Azure and I want to do that automatically every hour because I'm gonna run 16 I'm gonna run six builds today clouds certainly accelerates your opportunity big-time it forces everything to the table right yeah everybody's you can't hide anymore right what are you gonna do right you gotta answer the questions these are the questions so okay my final question I want to get on the table is for you in the segment is the product strategy how you guys looking at as an assassin gonna be software on premise cloud how's that look at how people consume the OP the offering and to opportunities because you guys are a young growing company you're kind of good good time you don't have the dog'll or the bagging it's Hadoop has changed a lot certainly there's a use case that neurons getting behind but clouds now a factor that product strategy and then when you're in deal why are you being called in why would someone want to call you rotor signs that would say you know call you guys up when with it when would a customer see signals and what signals would that be and to give you guys a ring or a digital connection product so the primary use cases are talking about recovery there's also data migration and the test step we have a big account right now that we're in final negotiations with where their primary use case is they're they're in health care and it's all about privacy and they need to securely mask and subset the data to your specific question around how are we getting called in basically you've got two things you've got the the administrators either the database architect or the IT or infrastructure people who are saying okay I need a backup solution I'm at a point now where I really need to protect my data as one and then there's this other track which is these higher-level strategic discussions where we're called in like the twenty six person meeting it's like okay we need an enterprise-wide data strategy so we're kind of attacking it both at the use case and at the higher level strategic and and and obviously the more we can drive that strategic discussion and get more of people wanting to talk to us about that that's gonna be better for our business and the stakeholders in that strategic discussion or whomever CIT is involved CIO maybe use their chief data officer and yeah database architect enterprise architecture head of enterprise architecture you know various flavors but you basically it kind of ways comes down to like two polls there's somebody who's kind of owns infrastructure and then there's somebody who kind of owns the data so it could be a chief data officer data architect or whatever depending on the scale of your and they're calling you because they're full they had to move the production workloads or they have production workloads that are from a bond from what uncared-for undershirt or is that the main reason they're in pain or you're the aspirin are you more others like we had a day loss and we didn't have any point in time recovery and that's what you guys provide so we don't want to go through this again so that's that's a huge impetus for us it is all about to your point it is mature its production workloads I mean the simple qualifying are you are you running a duper no sequel yes are you running in production yes you have a backup strategy sort of tip of the spear now to just briefly answer your question before we before we run out of time so it's an it's it's not a SAS basement we're software-defined solution will run in bare mantle running VMs will run in the cloud as your Google whatever you want to run on so we run anywhere you want we're sorry for be fine we use any storage that you want and basically it's an annual subscription base so it's not a SAS consumption model that may come down the road but it's basically in a license that you buy deploy it wherever you want customers choose what to do basically customers can do you know it's complete flexible flexible but back to you so let's go back to something you said you said they didn't have a point in time recovery what their point in time recovery was their last full backup or they just didn't have one or they just didn't have one all of the above you know see we've seen both yeah there's a market maturity issues so it's represented yeah you know that a lot its clustered I you know I just replicate my data and replication is not earth and truth be told my old company that was our approach we had a script but still it was like and the key thing is even if you write that script as you point out before the whole recovery thing so you know having a recovery sandbox is really in thing about this we designed everything exactly extract the value and show the use case prove it out yeah dupes real the history is repeating itself in that regard if you refuel a tional space there's a very in correlation to the Delton between the database platforms of the data mention logical hence they are involved coming in okay let's look at this in the big picture let's dad what's the recovery strategy how we gonna scale this exactly it's just a product Carson so your granularity for a point in time is you offer any point in time any point in time is varying and we'll have more news on that in the next couple weeks okay mantas data here inside the cube hot new startup growing companies really solving a real need need in the marketplace you're kind of an aspirant today but you know growth opportunity for as they scale up so congratulations good luck with the opportunity to secure bringing you live coverage here is part of Cuban YC our ninth year covering the big data ecosystem starting originally 2010 with a dupe world now it's a machine learning Hadoop clusters going at the production guys thanks for coming I really appreciate it this is the cube thanks for watching day one we'll be here all day tomorrow stay with us for more tomorrow be right back tomorrow I'll see you tomorrow

>> Narrator: Live from Orlando, Florida, it's theCUBE covering ServiceNOW Knowledge17, brought to you by ServiceNOW. >> Dave: We're back, this is theCUBE, the leader in live tech coverage. We go out to the events and we extract the signal from the noise. I'm Dave Vellante with Jeff Frick. Farrell Hough is here she's the general manager of the service management business unit at ServiceNOW, great to see you. >> Farrell: Yes, great to see you, thanks for having me. >> Dave: Awesome, you're welcome. Awesome keynote this morning, you have your baby, which is ITSM, we know, but at the financial analyst meeting and you know, you represent today's keynote, you represented, you know, more than just ITSM, which is, you know, good. But let's start there, so, awesome keynote, lot of energy, so much meat (chuckles). >> Farrell: Yes. >> Dave: In Jakarta. >> Farrell: Absolutely. We have been busy, for sure, in our IT portfolio. In ITSM we really spent a lot of time and energy in giving back to our customer base and making sure that critical capabilities and features in ITSM, have a lot of depth behind them as well. So making sure service level management's solid, service catalog, which is 99% adopted across our customer base, servicing over half a million end users, that making sure that that's solid. And then additionally, making it really easy for new customers to join onto ITSM as well by giving out of the box best practices and a guided set up format like a wizard format that they can within just a couple of hours stand up a brand new incident management process prescribed by ServiceNOW and feel confident in what they're getting. >> Dave: Yeah, so I didn't realize the number was that high in terms of adoption of service catalog. What do you see for CMDB, I mean, when you first started following ServiceNOW it was mixed, 'cause it kind of gets political, but now, today, when you talk to customers it's like, oh yeah that's a big initiative of ours, or we're already there, or what do you see? >> Farrell: Absolutely. I don't have the exact percentage in front of me but I believe that it's upwards of 70% adoption in our customer base. And that is a difference from where we were in the past, for sure. >> Dave: Which is like the mainspring of innovation, 'cause once you get there, with service catalog and CMDB-- >> Farrell: Yep, you get all your assets in there, you get all your services defined, it's go time. >> Dave: Then your operating leverage is huge in terms of when you bring out new function and the impact on the organization, the business impact, can be really enormous. >> Farrell: Absolutely. >> Jeff: And best practice out of the box is a huge, huge coo, everyone we've talked to, you know, they're smart enough now to now customization is bad. Keep it to a minimum, keep it to a minimum, do config but not customizations, so that all those upgrades are easier, easier, easier. So to come out of the box with an integrated best practices workflow, great, great solutions for the customers to get up and running quickly. >> Farrell: It is, and you know, they're asking for prescription, and we're going to give it to them. We've got our own services arm, we have a partner community, we know between all of us in this huge ecosystem what's working and what's not, and we're going to put it in the product and make sure our customers, existing and new, get best practice out of the box. >> Dave: So, kind of three areas you talked about today: service management, we just touched on, we didn't talk about the surveys, but that's cool, that's a nice little feature you guys have added. >> Farrell: Oh yes, that's right. >> Dave: So, you have new and improved surveys. Operations managements, so that's ITOM piece right? >> Farrell: Yep. >> Dave: And then business management. So give us the high level on office management. >> Farrell: I will, yeah, sure. So we announced this year that we're putting out the cloud management platform, and the adoption of cloud is long past it's tipping point. We're seeing cloud being adopted everywhere and cloud resources are extremely easy to procure, stand up, and use, and IT may or may not know about it. And that becomes just a huge problem in terms of cost and even in terms of security and compliance and when we're able to-- we made an acquisition roughly a year ago, the ITOM team, and this is basically the next generation cloud management platform, where now you're able to have a cloud portal where a end user can go and consume and, just like a service catalog, they're going to have a service catalog of cloud services that you've already provisioned very easily with the drag and drop interface, that accounts for all your policy already in those services. And so it makes it very very easy for the business to continue to operate at the pace and the skill that they need to, but for IT to make sure that we have the consistency and the compliance that we need to protect the business overall and manage cost, all with a really great user experience at the same time. So we're thrilled to be able to put out a cloud management platform. And then the second major thing that came out in the IT operations management space was around service mapping. When we went to market with service mapping it was for all on prem services and mapping out what that looked like. This time around we're just bookending it and kind of closing the gap and saying okay, let's look at what's off prem, and let's look what's in the cloud. So you get a holistic view and are able to discover resources in the cloud and on prem as well and you get that holistic view of your services mapped going forward. >> Dave: So I have to ask you, so we're always asking, when ServiceNOW gets into HR, it's like oh does ServiceNOW compete with Workday, no. And when ServiceNOW gets into security, it's like does ServiceNOW compete with FireEyes, et cetera, no no. Now when you talk about this multi-cloud, sort of mapping visibility, there's a lot of talk about, we call it sometimes inter-clouding and inter-cloud management, how far to do you go into that, I mean, can I actually orchestrate across clouds? Is it just giving you visibility, well not just, but, how should I think about the positioning of ServiceNOW in that space of cloud management? >> Farrell: We're out there to create flexibility for customers and we'll start to make it happen that you can orchestrate across different clouds regardless of what they look like. We're not totally there yet, but that's the direction it's going. >> Dave: Well nobody's there. >> Farrell: Yep. >> Dave: This is jump all for the industry. And it's got to be a huge market, I mean, everybody's doing multi-clouds. In fact somebody told me, today David Flora told me in Europe there was a mandate in the banking sector that you have to have a second source for cloud. >> Jeff: Oh really? >> Dave: Yeah, I don't know the context, but good news for the cloud vendors, right? Good news for somebody-- >> Farrell: Exactly. >> Dave: --who manages that. So, okay, and now what about, are we done with ops-- >> Farrell: That was operations management, yep done with that. >> Dave: And then how about business management? >> Farrell: Alright, on the business management side, the big news if the software asset management. We're able to deliver another new product this year, and that's really going to put a lot of power back in the hands of IT. You're no longer caught on your heels with a software audit, realizing you're out of compliance. We struggle with visibility and understanding where are all these software assets, who are they allocated to, are they actually using them, how much is it costing us, and when we're able to have visualization to that because it's on the ServiceNOW platform and we understand where all those items exist, we're able to go in and very easily reclaim licenses, or reallocate them, and to me that's found money. And I just love that. I think that's going to be great, and guess what? You want to find your sourcing for your next IT project it's right there. >> Jeff: Right, right, and you're being humble. I mean that was the thing where the biggest roar came up from the crowd, without a doubt. Super, super well received. >> Dave: We were talking to CJ this morning about how it works and you get the platform, the platform comes out with all these features, and then the business units take advantage of those features. Now of course he described it differently, he said you start with the customer, and then you figure out what to put in the platform knowing that the business units are going to take advantage of it. But when you think about intelligent automation you gave an example of predictive maintenance today, so that's a use case for that so called AI or deep learning, machine learning. So talk about that a little bit. And then I want to get into the DX continuum piece as well. >> Farrell: Yeah, absolutely. When we're sitting on this data set that our customers have and they want us to take advantage of it for them, on their behalf, we're able to go back and apply algorithms to those data sets to say what's the norm? And did it have a good outcome? And all that data is in there, we're able to model it now, you're not having to go do that in some--export that into some other system to try to figure out, with some advanced analytics, what's that looking like, you're able to be able to say very clearly, listen, here's what the normal pattern of behavior is, and establish that for everything else going forward. So it becomes really clear where outliers exist and what suspect events or suspect alerts look like in your environment and then you can fire off a process to say look, this looks like a problem, and with certain signposts associated to it, go ahead and automatically open up that incident. You apply it to change management where you're talking about predictive maintenance. Something has enough failures automatically schedule a change window or decommission it, fail it over, back it out, move it out of the way, so that it's not causing a problem anymore. We put so much on humans to do for so long because the technology wasn't there to allow us to do it, well it's time, it's here now. And so we can take some of the burden away. >> Dave: I just had a thought, we talk in this industry so much about consumerization of IT and trying to mimic consumers, Fred Luddy talks about all the time. What you just described, I thought about an experience of an iPhone user, and anytime you do a migration, my wife just migrated from an android to an iPhone, what question was asked, is it backed up? What you just described is proactive. You're way beyond is it backed up, you're at the point of, we're going to just eliminate any possibility of a disruption. So I guess my question there is, is enterprise IT finally, not only catching up, but in some regards surpassing, this consumerization trend? >> Farrell: Hey, I think there's an opportunity to leapfrog, all the way, and I'm behind a 100%. I do, I think exactly that. And why not get way out ahead and over our skis with that and over-deliver and show that yep, we can see what's coming, we're sitting on all this data. When you choose to go to the cloud, and all that data is accessible, and you're on a single platform, it's all intermingled. You're not having to stitch together, create a data lake that's got all these different integrations pulling data and trying to sort it out from there with some data scientists or some business analysts looking at it, you're now able to lean in way more with your operation and really start to take care of it and truly own it. >> Jeff: I was just going to say my favorite part of your keynote today was kind of teeing off what you said, which is using machine learning and artificial intelligence on relatively simple looking processes that are painful, cumbersome, and horrible, like categorization, prioritization, assignment, to take the first swag, let the machine take the first swag at that stuff, and take that burden off the person because it's tedious, it's cumbersome, and it's painful, so it's this really elegant use of machine learning and AI, which is talked about all the time, on a relatively, again, simple looking activity, that just delivers tremendous value. >> Farrell: Yeah, I'm really really excited about that part because there's a lot of mystic and-- ah, I don't know what the right word is, maybe misunderstanding potentially, which can lead to mistrust of AI and machine learning and what's really going to come of it. And when we're able to say using supervised machine learning, which is the model that we're going after with the auto-classification, you can work with customers to be able to to let them tune the level of accuracy that they are comfortable with. And so you're building trust right away with a really simple example of auto-classification or auto-categorization, that is so frustrating for both parties. The person who is filing the incident, and the for the person who's going to be supporting and fulfilling on that incident as well. And I just love that fact that we can start to dip our toe into this pool and wade in and create trust along the way so we don't leave anyone behind or create mistrust in our user-base that we're just trying to get rid of them in some capacity or pull the wool over their eyes, we're not and we're going to be really transparent about in the way we do it and I think that's phenomenal. >> Jeff: And it's dynamic right, so it continues to learn. You have Spotify, you have a playlist, I like this, I don't like this, the playlist hopefully gets better, so. >> Farrell: That's right, because it took your input. >> Jeff: Correct, right. >> Farrell: And so taking input from the end users is going to then help train that system over time, that's correct. >> Dave: I got so many questions for you. (Jeff laughs) >> Farrell: Okay! Give 'em to me. >> Dave: So the auto-classification piece, that comes from the DX continuum acquisition-- >> Farrell: It does, yes. >> Dave: So explain that, I know you guys re-platformed everything, but what did that give you and let's get into auto-classification a little bit. >> Farrell: Okay, well it gave us some incredibly talented smart engineers and some really great intellectual property in terms of algorithms that we are able to now apply. When we re-platform something we're making sure that it works in the ServiceNOW platform stack and that it is going to be available and pervasive for every application that gets built on top of the platform. >> Dave: Okay so, you had said before, we're not just building a data lake, which, I want to talk to you about that too, 'cause a date lake as we know turns into a data swamp and it's just a mess and then you got to really do a lot of heavy lifting. >> Farrell: Smelly, don't like that. >> Dave: Right? Not good. So-- >> Jeff: Scary critters. >> Dave: You're auto-classifying at the point of creation I presume, or use of that data set. So how does that all work? How is it being applied? Where do you see customers getting value out of this? Explain that a little. >> Farrell: Well really I see in the ITSM side and the IT Space and in the ITSM side specifically, anything that you've got to apply a drop down field to, whether you're an end customer doing it through a service portal, or you're an IT worker, too, like let's help those guys out, why not? Anytime you need to fill out a field through a drop down mechanism, it's one discreet set of values, that's a candidate there. Now you want to have a large data set, which is why incidents, incident category, or assignment, assignment group, or what skill set might be required to work that particular incident, works because there's tons and tons and tons of incidents out there so we have lots of examples around what it could possibly be. And then that's what the data model would be built on. This auto-classification is not meant for the obscure or the random or the infrequent. So when we're talking about high volumes that a service desk sees, this is the perfect setup to apply it. >> Dave: So how will it work? I'll have a corpus of data with a bunch of incidents and I'll just sort of tell the machine go classify this? >> Dave: And it'll do some kind of process? >> Farrell: You're going to have a set of data a portion of the records you're going to use for the training model, the other portion you're going to leave behind, almost as the control group. And you're going to go apply the algorithms to that training set of data and it's going to start to learn and you're going to tell it what fields you want it to learn from and pay attention to and spit a model out on the other side on and it's going to crunch through all that data and it's going to give you a model on the other side, and you'll look at it and see if you agree, and then you're going to take that model and you'll apply it to that control set and you're going to look at what level of accuracy came out on the other side and you'll decide with that data set what accuracy level you want to have. For me, 70% accuracy will work for me on password reset. 'Cause, in all likelihood, what's it going to be? But maybe for a VPN issue I want 90%. You'll be able to start applying accuracy by category to then tune in exactly how you want things to work to make sure you get that good user experience. >> Dave: And then you'll continue to train that model and iterate. >> Farrell: Yes, absolutely. And you'll be able to train it and often as you like. I mean on demand, like yep, I want to train it again. And when you have a service desk worker who goes back in and re-categorizes, because yeah, that wasn't quite right, that's just the same thing as clicking the like button, thumbs up, thumbs down, on Spotify. You're right that you've just given it feedback. When you train it again, it takes that feedback into account. >> Dave: And then the subsequent incidents get auto-classified. >> Farrell: They get the learning. They get the learning. There's not magical learning that happens in this particular case, the technology's not evolved to that state, there's no unicorn back there that's doing all the learning for you. It takes feedback and it'll take some tuning, but hopefully in being able to make the feedback mechanism very easy, the tuning happens naturally, therefore the model gets better over time. >> Dave: Well it's a great use case because it's relatively narrow, and you have tons of data, and it can be implemented right away. >> Jeff: And like you said, even if it just helps you partially down the road, it's better than zero down the road, especially these repeatable processes that have to happen over and over and over, it's like oh please shoot me, this is the work that machines are supposed to do because it's mundane and repeatable and-- >> Farrell: Mind-numbing. >> Jeff: Mind-numbing, thank you. Let me get to solving the customer problem. >> Farrell: That's right. >> Dave: Okay so when we first encountered ServiceNOW we did our first Knowledge, it was from 2013, and it was at the height of the big data sort of hype-cycle. And so we would ask, of course we asked, well what about data, what about big data? The response was always well we got a lot of data and we're looking at that. But now we're here. And you mentioned earlier, it's not some data lake that you're processing as offloading your data warehouse, so what are you doing in that space? So it's not a data lake, it's a corpus of data and you're basically applying these AI and intelligent automation models to, can you explain a little bit about how that works? >> Farrell: Sure, well first off we won't do anything, we have to have our customer's permission to be able to use their data, they showed interest in machine learning services then they will give us permission to leverage their data and all customer data is separated too, within their own instance, within their own database, there's no co-mingling of data, so there will be no data lake whatsoever. But what we are able to do, and it's on a personal level, which I just love, because that's who we are as a company, that we're offering personalized supervised machine learning, personalized auto-classification, we're not taking all the data of all of our customers, kind of aggregating it up and then building models against that, and then saying oh I think this model would pertain to you and then it's only 25% accurate or even relevant. We're building a model very specific to you. And working with your data set and we have access to it, with your permission, and we'll go build that model, using the training set as we described, and then go test it out, and then help you go re-deploy it. So we'll pull that data into a central instance, help retrain it, and then move it back into your instance so that model is always constantly tuned and then you get to decide when you retrain it. >> Dave: So who's we in that example? You have a team of data scientists that do this? >> Farrell: This will be in our platform team. It's a platform service. You don't need data scientists to, I would say on the customer side, maybe if they were wanting to interpret some of that data or do something with it maybe they'd have a data scientist. This is just tried and true engineering and having a good service model behind it, it's just a central instance. >> Jeff: Do--I'm sorry, I interrupted. >> Farrell: No, I was just going to say through our acquisition DX Continuum, those engineers are building those training models and will keep them up to date, but they're not literally turning a crank when that data comes in and it'll be-- >> Dave: So it's a model that they apply, it scales, it's part of the service. Now you iterate that over time-- >> Farrell: That's right. >> Dave: But it's the-- >> Farrell: And you can build out other training models. So we just talked about auto-classification for instant, but this can extend in other areas as well. >> Jeff: Well I was going to say, do you think it's an opportunity for the ecosystem that has specialty expertise around, pick your favorite topic area, we're talking to someone about oil and gas earlier today, that they know what the model is way beyond just simple correlation to take in this and it flow and predict that, I think the example was that the well cap's going to break, or whatever. So do you see that potentially as an ecosystem contribution as well around more specific use cases? >> Farrell: Well I think that would be super cool. If we had customers of similar ilk, whatever that looked like, wanting to collaborate and share and crowdsource something for a greater good that wasn't competitive, I think that that would be amazing to be able to do that. And we would be able to facilitate it. We don't have any current plans to do that right now but I could absolutely see it. >> Dave: Well we've talked about the ecosystem through for years, to see it just burgeoning and awesome story. Thank you for coming on theCUBE and doing a brain dump on us and educating us. >> Farrell: Yeah, thank you so much-- >> Jeff: You really had a great opening line, "exciting time to be in IT," that was your opening line, the key night, I know you've got the excitement >> Farrell: It is! This is the best time to be in IT. I mean oh my gosh, it's fabulous. >> Dave: You're exploding. Alright Farrell, thanks very much. >> Farrell: Alright, thank you. >> Dave: Alright, keep it right there buddy, we'll be back with our next guest, theCUBE, we're live from Orlando, be right back. (techno music)

hi this is David flora back at the open power foundation conference here in San Jose and with me I've got Erin Sullivan who is a distinguished engineer at Rackspace welcome our thank you so what do you think of the conference so far it's amazing it's grown so much in the last year 15 designs to almost 60 in a year and lots of system launches yeah very impressed well one of the things that has been announced today which was caught my eye in a big big way was the agreement so the announcement that you and Google have can you paint a little more put a little more light on that announcement yeah sure so Rackspace and Google started working together when Rackspace was developing barrel I of course Google had already had their system available at the time and our collaboration just on what we had with barrel I was very positive we were just kind of looking to trade notes and you know share our experience and a few months ago we got back in touch and said hey this was ministers posit enough we should think about doing the next one together from the start and so that's basically what we're doing now we're going to do a power 9 system that comes in multiple mechanical form factors but just one motherboard and we're going to like we did with barrel I we're going to contribute that to open compute when we're finished out of the Open Compute foundation part of the OpenStack yes heart of the open power founder that's right open everything open ever yeah yeah excellent so what about the barreleye that you also announced some things about today can you what is barrel i and what's what's what's different about it so so paralyzed named after a fish that's got a transparent body most of our servers are named after we thought having a server that was fully open would be great to have that name barrel I just entered its first data center shipments it's headed to our Virginia data centers right now and in a few months we expect we will begin providing services to customers on it so that's the progress on barrel I so far we contributed to open compute about 2-3 months ago now and it was accepted so the specifications are online and if you look around the show floor here you will see there are other companies that have put their brand on it or something else and are also taking at the market which is exactly what we hope for great well I've got a question which is why have you why have you put these resources into barrel I and in the future into the power 9 etc what are you looking for that's different about open power that for example you couldn't get with a standard x86 server yeah so I know it gets to be tired and people get tired of hearing the word open but really even with open compute and OpenStack the freedom that comes with developing in that particular universe is really significant before open power even started there were parts of the system we really wish we could get into in an open way where we could develop and share instead of just doing it all on our own and having open power come in the first place fit that but then we also have this problem this Moore's Law problem and the types of changes that we're going to have to implement as an industry to continue to accelerate and and and get higher performance computing and more efficient computing over the next year's they're really huge challenges they go from the chips all the way to the top of the stack and if you don't have the chip part open and you don't have the firmware part open it becomes really difficult to collaborate you can't bring to bear the sort of force of the world software developers onto it you end up in these little silos and niches so for us beryl I provides a lot of value as a business and it has a great influence on the industry at large and so wills IOUs the power 9 system Google but it also is there as a platform for developers to begin to start wrapping their minds around these new problems and opportunities that we have and if it's not done in the open these types of software aren't really scalable across the whole industry that that's a very interesting answer indeed and as you say um does laura has come to a screeching halt from the point of Mount of power per CPU is still going on in terms of the number of transistors etc that you can have what are the what are the things you as a distinguished engineer what are the things that really are most important about the power architecture that allow you to develop these new ways of doing things yeah I think it's it depends on the type of your business you're in but in our business I think in many cloud service providers and in some other environments certainly some HPC and a lot of enterprise the performance of a single core is still really important and it will continue to be for as long as we can keep getting more performance out of a single core so power provided a great platform with a very powerful core and it also has a huge number of threads per core so you get a little bit of the best of both worlds there and you need a really powerful core you have it if you want to spread your load really wide over a more cloudy webby type application you get to use all those threads and there's all that memory bandwidth and so forth so so that was the benefit of power in general and then we run out of core performance and those cycles per you know CPU aren't going up and maybe we can't even scale cores like we used to anymore which is coming in a few years I the the fact that the platform is open in areas that others aren't allows us to bend the rules about how components communicate and we cut out a lot of overhead between them so that's a sort of software in silicon type argument you want to bring the software closer to the silicon yeah closer and in many cases to do the same work that we do today like that's the hard part is people think it's all about genomics or oil and gas or something it's the same work but you know we've already demonstrated that open harcum you it is demonstrated that there are certain workloads that are very common today that you can boost tenfold or more simply by reintegrating your software tighter the hardware right you pull out overhead that we were fine with when Moore's Law is working but now we got to do something yeah great well thanks very much indeed for for being here and thanks very much for watching

from the noise it's the cube covering vmworld 2015 brought to you by vmware and it's ecosystem sponsors and now your host dave vellante we're back at Moscone everybody this is the cube SiliconANGLE Wikibon it's continuous production of vmworld 2015 we're riding the data wave Eric Harris dog is here he's a vice president marketing IBM storage in the Hawaiian shirt great to see you again my friend well Dave thank you very much as I keep telling people it's not about data lakes people have oceans a day to these days yes I oceans a day to dos today that oceans a data now so what's the story get the Hawaiian shirt on what do you got going on across the straw our big thing really is oceans of data so between all the solutions we have from a storage solution set a platform computing environment our joint deal that we do with Cisco with what we call the versus stack and our spectrum family of software now our customers are saying everything's going digital and it doesn't matter whether you're a global enterprise a midsize company or even an SMB with everything going digital it isn't about lakes of data it's about oceans of data so let's start maybe at the versus stack as a hyper converge is sort of taken the world by storm you're seeing vmware's obviously talking about it you got a bunch of startups talking about it when you guys made the move to to sell the the server business the x86 server business to lenovo BNT the acquisition of B&C went with it opened up whole new opportunities for IBM from a partnership standpoint and one of the first guys you went to a cisco so talk about that well we've had a great partnership with Cisco we deliver the versus tak through our mutual channel partners so globally so we have channel partners in all of the gos that are selling the versus stack solution we started originally with our v7000 product which allows us to not only provide a strong mid to your offering but because of our integration of our spectrum virtualized actually will virtualize heterogeneous torso over 300 arrays from our competitors can be virtualized giving any data center or cloud deployment single way to replicate single way to snapshot and of course a single way actually my great dinner which is a huge issue obviously in big deployment well and the same volume controller was really the first platform to do that that was the right gold standard and the whole the original you know tier 1 tier two storage sort of was defined by the sand volume controller kept really now you've built those capabilities into an end to the array so we started with our v7000 storwize was the first with a versus tack we announced last week two new versions one hour v nine thousand which incorporates that same value of the sand volume controller but an all-flash array okay that product is been incredibly successful for us we have thousands of customers we have deployed more petabytes than anyone in the industry and more units than anyone in the issue for you know some of those analysts that track the number side of the business we've done more than any pricing it right is what you're telling me we are definitely pricing it right we do north petabytes more minutes and more units than anybody by far but not the most revenue second most revenue so you well we're a fair price for a fair job as opposed to a high price for okay job that's what we believe in delivering more value for the money so we've got that so that opens up heavy virtualized environments heavy cloud environments big data analytics all those applications were all flash high-end Oracle deployments SP Hana configs all those sort of things are ideal same time you brought in the v5000 at the lower entry place of the mid-tier and it's with the UCS mini from Cisco so it gives you a lower entry price and allows a couple things one you can go in department until deployments a big enterprise to you can go into remote office deployments and also of large enterprise but three it allows you to take the value of a converged infrastructure down into smaller customers because it's a lower entry price point it's got all the value of the virtualization engine we have in all of our V family of products that v5 to be seven in the v9 all flash but it's at a much lower price point with a lower cost UCS mini and a lower cost switch infrastructure from from Cisco so it's a great solution for those big offices but again remote and department level and ideal though to move converged infrastructure down into smaller companies so so cisco has been incredibly successful with that space when Cisco first came out I a misunderstood I said how they going to fall flat in their face and servers and I was totally wrong about that because I didn't understand that they were trying to change the game what's it like partnering with those guys and how is it added value to your business well it's been very strong for us one they've got an excellent channel two they have a great direct sales model as does IBM three we've been partnering them for ages and ages and ages in fact in the 90s we sold a bunch of our networking technology to Cisco and is now deployed by Cisco so some of the networking technology at Cisco puts out there to the to their end users to their channel partners into you know their big telcos that actually came from IBM when we sold our networking division to Cisco in the mid-90s so strong partnership ever since then so let's talk more about the portfolio particularly i'm sickly interested in the whole TSM vs TSM came over to the storage group which thrilled me i think there was a great move by IBM to do that whoever made that decision smart move how has that affected having that storage software capability embedded into the storage business how has that affected your ability to go to market well it's been great so that's our spectrum family there are six elements to that spectrum protect which used to be TSM spectrum control which used to be the tsc product spectrum virtualized which is a software version of the sand volume controller so you can get as a software-only solution spectrum archive spectrum accelerate which is a scale-out block solution think of it as a software version of our XIV platform but software only and spectrum scale which gives incredible scale-out nas capability in fact spectrum scale has a number of customers in the enterprise side not in the HPC market but in global enterprises over 100 petabytes and we even have one customer that has one exabyte in production under spectrum scale exabyte one exabyte in production and not an hpc customer or not not one of the big universities not one of the think tanks but a commercial large global fortune 500 company we an exabyte with spectrum scale so so talk a little bit more about the strategy I think people all times misunderstand IBM's approach they say okay IBM getting out of the hardware business which they think Inferno must get another storage business you're not get out of the storage business obviously they hired hogging store oh so talk more about the strategy and how you're you know pursuing that yeah well I'd say a couple things so first of all our commitment to storage is very strong we're investing a billion in all flash technology and a billion in spectrum software in addition to our normal engineering development for our store wise family and our other members of our products that we've already had so a billion extra in flash and a billion extra in our software family in addition to that we've got a method of consumption that we're looking at so some end users want a full storage solution our ds8000 our flash systems are storwize some customers want to move to the software-defined storage and in several cases such as XIV software only spectrum virtualize okay we've got a number of different ways that you can consume the product and then lastly in several of the products such as spectrum scale spectrum accelerate and a lite version of spectrum control that we call spectrum control storage insights available through a cloud consumption model so if the customer wants a comprehensive solution we have it if the customer wants software-defined storage we have it if the customer wants integrated infrastructure with our vs stack we have it and if the customer wants a cloud storage model of consumption we have that too and quite honestly we think in bigger accounts they may have multiple consumption models for example core data center might go for a full storage solution but guess what the cloud solutions would be ideal for a remote or branch office so talk to me more about the cloud you're talking about the SoftLayer we here we go to the IBM shows you a soft layer of bluemix you know so a lot of money or the devops crowd what's going on bactrim accelerate spectrum scale and spectrum control are all available as a soft layer offering they are not targeting test and Dev they are not targeting you know just the bluemix out these are targeting core data center they could be testing dev or they could be remote office branch office opportunities for large enterprises that want to spend a full storage solution and spend that money on the core data center but for the remote office have spectrum scale delivered over softlayer an ideal solution and various consumption models which ever fits their need so David flora just wrote a piece on Wikibon calm of talking about latency and capacity storage at a very high level sort of segmenting the market those ways it's sort of sizing it up and projecting some of the trends and obviously latency storage he's thinking you know more flash oriented capacity storage more more disk spinning disk and tape is that a reasonable way to look at the business and how does it apply to your portfolio so we do think that's a reasonable way to look at it you have if you will a performance segment and a capacity segment depending the number of things that people need to really look at when they buy storage first of all I'm a storage guy for 30 years no one cares about storage it's all about the data it's all about the data that your storage optimizes it's about the workload the activation the use case for me I do too but unfortunately almost every time you know see how it's going to say almost every CIO is a software guy so it's how does the storage optimize my software environment and that's what's critical to them so we see certain applications that are very performance exit certain SLA s they need to meet we have some that are medium sensitive and we have some that of course are very capacity oriented which is our spectrum scale one exabyte with a single customer now that's capacity that's an ocean of data but we also have solutions we're able to put it together so for example in a lot of data analytics workloads that would run in spectrum scale we actually sell a lot of our all flash flash systems use the flash to ingest the data use flash to manage the metadata use the flash to run the search engine in a big giant config such as that and when you're running an analytics workload you run the analytics workload on that flash yet you're really doing a very large deployment hundreds of petabytes to an exabyte with our spectrum scale so we see if you will a continuum and the key thing as IBM offers all of the various piece parts to any level of the continuum and in that example I just gave combining high performance and deep high capacity software in a single solution to meet a business I mean IBM is an unbelievable company think about Watson cloud bluemix the analytics business deep deep heavy rd z mainframe so you got all the pieces how is the storage business how can it better leverage those other pieces and and is it or is it is it relevant or is it just just take the storage hill so we see our storage products as integrating with our other so for example we do a lot of deals where they buy a mainframe in our ds8000 sure we offer integrated infrastructure not only with cisco but actually with the power family as well it's called pure power and that has an integrated v7000 with a power server and we're looking at deepening that relationship as well a lot of analytics were lot alex workloads going scale so whether they buy the big insights whether they use in Watson we've got several customers use Watson but by flash systems because it's obviously very compute intensive so they use flash systems to do that so you know we fit in at the same time we have plenty of customers that don't buy anything else from IBM and just buy storage so we are appealing to a very broad audience those that are traditional IBM shops that by a lot of different products from IBM and those that go in fact one of our public references general mills they had not bought anything from any division of IBM for 50 years and one of our channel partners in Minnesota we are able to get in there with our XIV product and now not only do they buy XIV and some spectrum protect for backup but they've actually started to buy some other technology from IBM and for 50 years they bought nothing from IBM from any division so in that case storage led the way so again in certain accounts we're in there with the ds8000 and Z or were in there with Watson and flash systems and other accounts were pioneering and in some cases we're the only product they buy they don't buy from IBM we will meet whichever need they have now in periods in the last I mean it's been Evan flow in the storage business for IBM periods the last decade IBM deep rd but the products couldn't seem to go to market now you shared with me under under NDA so we can't talk about it in detail but shared with me the roadmap and and the product roadmap is accelerating from release maybe it's just my impression from what I'm used to should we expect to see a much more you know steady cadence of product delivery from IBM going forward absolutely so keeping in our spirit of oceans we ride the wave we don't fight the way and in today's era in any era of high-tech not just in store it doesn't matter whether storage whether its servers whether it's web to know whatever it is it's all about innovation and doing it quickly so we're going to ride that wave of innovation we're going to have a regular cadence of releases we released four different members of spectrum plus two verses stocks and next quarter you'll see five really five major product releases in one quarter and then in q1 you're going to see another three so we're making sure that as this trajectory of innovation hits all of high tech in all segments that IBM storage is not going to be left behind and we're going to continue to innovate on an accelerated pace that pace is is really important you know IBM again spends a lot of money on R&D it's key to get that product into the pipeline let's talk about vmware and vmworld obviously we're here at vmworld so on vmware very important constituency a lot of customers you got a you got to talk to vmware if you want to be in the data center today what is your strategy around vmware specifically but also generally as it relates to multi cloud environments whether it's your own cloud or other clouds OpenStack or what if you could talk about those so let's take virtualization first so we support a number of different hypervisors we support VMware extensively we support hyper-v we support kvm we support ovm we support open initiatives like OpenStack cinder we support Hadoop we have Hadoop connectors in many of our products so whether it's a cloud deployment or a virtual deployment we want to make sure we support everybody for example spectrum protect was announced last week with support for softlayer as a target device basically a tier well guess what in 1h we're going to support amazon and as you're not just softlayer so again we want to make sure we support everything with VMware specifically for the first time ever VMware has invited IBM storage on stave at three questions iBM has done things in the server world in the past but we have never ever ever been invited by VMware to their technical sessions in fact when is it five o'clock today it's called Project capstone which they publicly announced last week and it's about deploying Oracle environments in VMware virtualization it's a partnership with VMware with IBM flash systems all flash and with HP superdome servers and that's going to be on stage at five o'clock today here at moscone center awesome so we're starting to see a tighter relationship with with VMware building out the portfolio what do you say to the customer says yeah I hear you but vmware's doing all this sort of interesting stuff around things like v san what do you what do you tell a customer you know what about that so we see the San as it you know in this era of behemoths everyone is your partner everyone is your competitor but we work with Intel all the time other divisions of IBM think Intel's a major competitor some of our server division work with some of our storage competitors so we think you know we will work with everyone and while we work with VMware a number of angles so if he sounds a little bit of a competitor that's fine and we see an open space for all of the solutions in the market today we got to leave it there the last question so take us through sort of your objectives for IBM storage over the you know near and midterm what do you what should we be well so our big thing is to make sure we keep the cadence up there's so much development going on whether that be in software defined and integrated infrastructure in all flash in all the areas that we are going to make sure that we continue to develop in every area we've got the billion dollars in all flash in the billion dollars in software to find we are going to spend it and we're going to bring those products to market that fit the need so that the oceans of data that everyone is dealing with can be handled appropriately cost-effectively and quite honestly that oceans of data it's about the business value of the data not the storage underneath so we're going to make sure that for all those oceans a data we will allow them to drive real business value and make sure that those data oceans are protected meet their SLA s and are always available to their end user base I love it yet the Steve Mills billion-dollar playbook obviously worked in Linux it was well over a billion in analytics business IBM's a leader they're applying it to flash great acquisition of Texas memory systems you become a leader they're now going after the software to find Eric Herzog thanks very much for coming to the cubes great very much we love to have all right everybody will be back with our next guest right after this World we're live from vmworld and Moscone keep right there you