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