>>live from the Frederick P Rose Hall, home of jazz at Lincoln center in New York, New York. It's the queue at IBM Z. Next redefining digital business. Brought to you by headline sponsor. IBM. >>Hey everyone. We are here live in New York city for the IBM Z system. Special presentation of the cube. I'm John furrier, cofounder SiliconANGLE at my coast. Dave Alante co founder Wiki bond.org. Dave, we are here with gathering Corine, vice president of the Z systems technology. Welcome to the cube. Great to have you. >>Thank you. I'm really glad to be here. It's an exciting day for us. >>We had a great conversation last night. I wanted to just get you introduced to the crowd one year overseeing a lot of the technology side of it. You're involved in the announcement, but uh, you're super technical and uh, and, and the speeds and feeds of this thing are out there. It's in the news, it's in the press, but it's not really getting the justice. And we were talking earlier on our intro about how the main frame is back in modernize, but it's not your grandfather's mainframe. Tell us what's different, what's the performance tech involved, why is it different and what should people be aware of? >>Sure. So this machine really is unmatched. We have tremendous scale performance in multiple dimensions that we can talk through. The IO subsystem provides tremendous value security that's unmatched. So many of the features and attributes to the system just cannot be compared to other platforms. And the Z 13 what we're announcing today evolves and improves so many of those attributes. We really designed the system to support transaction growth from mobility, to do analytics in the system, integrated with the data and the transactions that we can drive insights when they really matter and support it. Cloud delivery. >>So there's two, two threads that are out there in the news that we've wanted to pivot on. One is the digital business model, and that's out in the press release is all the IBM marketing and action digital business. We believe as transformers, that's pretty much something that's gonna be transformative. But performance with the cloud has been touted, Hey, basically unlimited performance with cloud. Think of compute as a not a scarce resource anymore. How do you guys see that? Cause you guys are now pushing performance to a whole nother level. Why can't I just get scale out saying or scale out infrastructure, build data centers. What is this fitted with that mindset or is it, >>yeah, so I, there's, there's performance in so many different dimensions and I'll can talk you through a few of them. So at the, at the heart of the technology in this system, we have tremendous value in from the processor up. So starting at the base technology, we build the microprocessor in 22 nanometer technology, eight cores per chip. We've got four layers of cash integrate on this. More cash that can be accessed from these processor cores then can compare to anything else. Tremendous value. Don't have to go out through IO to memory as frequently as you would have to in other environments. We also have an iOS SIS subsystem that has hundreds of additional processing cores that allows you to drive workload fast through that. Um, so I think it's the, it's, it's the, the, the scale of this system that can allow you to do things in a single footprint that you have to do with a variety of distributed environments separately coupled with unique security features, embedded encryption capability on the processor, PCIE attached, tamper resistance, cryptography, compression engines as so many of these technologies that come together to build a system. >>So IBM went to the, went to the, went to the woodshed back and took all the good technology from the back room cobbled together. Cause you guys have done some pretty amazing things in the, what they call proprietary days, been mainframe back in the sixties seventies eighties and client server a lot of innovation. So you guys, is that true? Would that be an accurate statement? You guys kind of cobbled together and engineered this system with the best >>engineered from, from from soup to nuts, from the casters up. We live, we literally have made innovations at almost every level here in the system. Now it's evolved from previous generations and we have tremendous capabilities in the prior ones as well. But you see across almost every dimension we have improved performance scape scalability capability. Um, and we've done that while opening up the platform. So some of the new capabilities that we're discussing today include enterprise Linux. So Linux on the platform run Linux on many platforms. Linux is Linux, but it's even better on the Z 13 because now you have the scalability, the security, the availability behind it and new open support, we're announcing KVM will be supported on this platform later this year we have OpenStack supported, we're developing an ecosystem around this. We have renouncing Postgres, Docker, no JS support on the mainframe. And that's tremendously exciting because now we're really broadening a user base and allowing users to do a lot more with Linux on the main. >>So one of the big themes that we're hearing today is bringing marrying analytics and transaction systems together. You guys are very excited about that. Uh, one of the, even even the New York times article referenced this, people are somewhat confused about this because other people talk about doing it. We go to the Hadoop world, you know, we talked big data, spark in memory databases, SAP doing their stuff with Hannah. What's different about what Z systems are doing? >>That's a great question. So today many users are moving data off of platforms, including the mainframe to do their analytics. Moving back on this ETL process, extract, transform load. It's incredibly expensive, cumbersome copies of that data. You have redundancy, you have security risk, tremendous complexity to manage. And it's totally unnecessary today because you can do that analytics now on the system Z platform, driving tremendous capability insights that can be done within the transaction and integrated where the transactions and the data live. So much more value to do that. And we've built up a portfolio of capabilities and some of them are new. We're an announcing as part of today's event as well that can allow us to do transformation of the data analytics of that data. And it, and it's, it's at every level, right? We have embedded analytics, accelerators in the process or a new engine we call Cindy single instruction. Multiple data allows you to do, uh, a mathematical, uh, vector processing. >>Let's drill down on that. I want to get your particular on this. You have the in process or stuff is compelling to me. I like, I want to drill down on that. Get technical. Right now all the rage is in memory in memory. She's not even on the big data. Spark has got traction for the analytics. DTL thing is a huge problem. I think that's 100% accurate across the board. We hear that all the time. But what's going on in the process server because you guys have advanced not just in memory, it's in processor. What is that architecture, what are the, some of the tech features and why is that different than just saying, Hey, I'm doing a lot of in memory. >>So, so the process or has um, a deeper and richer cash hierarchy, um, than, than we see in other environments. That means we have four layers of cash. Two of those cash layers are embedded within the processor core itself. They're private to the core. The next layer is on the processor chip and it's shared amongst all those cores. And the fourth layer on a herder, right, is on a separate chip. It's huge. It's embedded DRAM technology. It's a tremendously large cash and we've expanded that, which means you don't have to go out to memory nearly as frequently because you, >>you stayed in the yard that stayed in the yard today in memory is state of the art today. You guys have taken it advanced inside the core. What kind of performances that dude, what's the, what's the advantage? >>There's huge performance advantages to that. We see, we see, we can do, uh, analytics. Numbers are something like 17 times faster than comparable solutions. Being able to bring those analytics into the system for insights when you need them, right? To be able to do faster of scoring of transactions, to be able to do faster fraud detection with so many applications. So many industries are looking to be able to bring these insights faster, more co-located with the data and not have to wait the latency associated with moving data off and, and, and doing some sort of analysis on data that's stale. How that's not interesting. We really want to be able to to integrate that where the data and the transactions live and we can now do that on the. >>So in memory obviously is awesome, right? You can go much faster. A best IO is no IO as gene Amdahl would say, but if something goes wrong and you have to flush the memory in reload >>everything, it's problematic. How does IBM address that? So to minimize that problem relative to we hear you hear complaints and other architectures that that that's problematic. How do you solve that problem or have you solved that problem? >>Well, you know, I think it's a combination of, of the cash, the memory and the analytics capabilities, the resiliency of the system. So you worry about machines going down, failures and we've built in security, reliability, redundancy at every level to prevent failures. We have diagnostic capabilities, things like the IBM Z aware solution, right? This is a solution that's been used to monitor the system behavior so that you can identify anomalous behaviors before you have a problem that's been available with cos. now we're extending that to Linux for the first time. We have solutions like disaster recovery, continuous availability solutions like the GDPs, uh, it's now extended to be a virtual appliance for Linux. So I, there's so many features and functions. This system allow you to have a much more robust, capable, >>popular is Linux. Can you quantify that? You guys talk a lot about Linux and can you give us some percentage? >>Linux has been around for 15 years on the mainframe and um, we have a very good user adoption. We're, we're, we're seeing a large fraction of our clients are running Linux either all by itself or in concert with Zoes. >>So double digit workloads. >>Yeah, it's a very, it's a very significant fraction of the myths in the field today. >>God, I don't want to get a personal perspective from you on some things. One, you went, uh, you have an applied physics degree from Yale, master's from an applied physics from Stanford, PhD, applied physics from Stanford and all the congratulations by the way, you're super smart means you, it means you can get to the schools you means you're, you're smart. But the rage is software defined, right? So I want you to tell us from your perspective being in applied physics, the advances in Silicon is really being engineered now. So is it the combination of that software defined? What's your perspective? What should people know about the tech at the physics side of it? Cause you can't change physics know the other day, but Silicon is doing some good stuff. So talk about that, that convergence between the physics, Silicon and software. >>Yeah, that's a, that's a great question. So I think what sets us apart here with the mainframe is our ability to integrate across that stack. So you're right, Silicon Silicon piece of 22 nanometers Silicon, we can all do similar things with it, but when you co optimize what you do with that Silicon with high-performance system design, with innovations at every level, from where operating systems software, you can build an end to end solution that's unmatched. And with an IBM, we, we, we do that. We really have an opportunity to collaborate across the stack. So can we put things in the operating system? It can take advantage of something that's in that hardware and being able to do that gives us a unique opportunity. And we've done that here, right? Whether it's the Cyndi accelerator and having our software capabilities or see Plex optimizes a Java, be able to take advantage of what's in that, uh, in that microprocessor, we see that with new instructions that we offer here that can be taken advantage of compilers that optimize for what's in the technology. So I think it's that, it's that co optimization across the stack. You're right, software as a user, you see the software, you see the solution, you see the capability at the machine. But to get that you need the infrastructure underneath it, you need the capabilities that can be exploited by the software. And that's why that, >>and we're seeing that in dev ops right now with the dev ops movement. You're seeing, I want to abstract away the complexities of infrastructure and have software be more optimized. And here you guys are changing the state of the art in with the in-memory to in processor architecture, but also you're enabling developers and software to work effectively. >>Right? And I think about cloud service delivery, right? You know, and we would love to be able to offer end users it as a service so we can access the mainframe. All of those qualities of service that we know and love about the mainframe without the complexity and can do that. Technologies like Zoes connect and Blumix with system Z mobile first platform, allowing you to connect from systems, engagements, the six systems of Rutgers deploy Z services. So you can, we were trying to help our clients to be able to not be cost centers for their, uh, for their firms but to provide value added services. And that can be done with the capabilities on the main. >>So no, Docker, OpenStack KVM, obviously we talked about Linux. What does that mean from a business standpoint, from the perspective of running applications? Can you sort of walk us through what you expect clients to do or what >>it's, it's, it's all about standardization and really expanding an ecosystem for users on the platform. And we want anybody running Linux anywhere to be able to run it on, run their applications, develop their applications on the mainframe. And to be able to take advantage of the consolidation opportunities driven by the scale the platform and be able to drive unmatched end to end security solutions on this plot. Right? It's, it's a combination of enabling an ecosystem to be able to do what users expect to be able to do. And that ecosystem continues to evolve. It's very rapidly changing. We know we have to respond, but we want to make sure that we are providing the capabilities that developers and users expect on the platform. And I think we've taken a tremendous leap at the Z 13 to be able to do that. >>So obviously Linux opened up. That was the starting point. Right? Um, what do you expect with the sort of new open innovations? Will you pull in more workloads, more applications or, >>I certainly believe we will. And you know, new workloads on the platform. This is, this is a, an evolution for us and we continue to see the opportunity to bring new workloads to the platform. Things, support of, of, of Linux. And the expanding ecosystem there helps us to do that effectively. We see that, whether it's um, the, the, the transaction growth from mobile and being able to say, what does that mean for the mainframe? How can we not just respond to that but take advantage, enable new opportunities there. And I, so I think absolutely Linux will help us to grow workloads to get into new spaces and really continue to modernize the mainframe. >>John and I were talking at the open Paul Moritz at the time, CEO of VMware in 2009. So we are going to build a software mainframe. Um, interesting, very bold statement. Don't, where's he working on pivotal? Do you have a software mainframe? Have you already built it? >>I don't think you can have software that running on something. And so the mainframe is not a piece of hardware. The mainframe's a solution. It's a platform that includes technology, infrastructure, hardware and the software capabilities that run on it. And as I said, I think it's the integration that the co optimization across that really provides value to clients. I don't know how you can have a software solution without some fundamental infrastructure that gives you the qualities of service. That's so much of the inherent security availability. All of that is >>that's a marketing. It didn't, it didn't pan out. The vision was beautiful and putting a great PowerPoint together. he went to pivotal now, but I think what's happening is what you're, what you're talking about is it's distributed mainframe capability. The scale out open source movement has driven the wannabe mainframe market to explode. And so what now you look at Amazon, you can Google look at these, these power data centers. They are mainframes. In essence, they are centralized places. Well, they want to say the cloud is a software mainframe. Software runs on these data centers. So instead of having rack and stack, uh, three x86 processors, you just drop into mainframe or God box as I call it. And you have this monster box that's highly optimized and then you could have clusters of other stuff around it. Your argument is the integration is what, what makes the difference that end. And so Amazon makes their own gear, right? We know that now they don't do open compute. They're making their own gear. So people who want to be Amazon would probably go to some kind of hybrid mainframe. Like they're not making their own. 70 makes sense of that cause Amazon, I mean they purpose built their own boxes. They are building their own point though, right? I mean to the outside of the box. Right. >>The way I see it as is for for mission critical applications where you cannot support any downtime, you want to have a system that's built from the ground up for pure availability for security and we have that right? We have a system that you can prevent failures, right? We have redundancy at so many levels. We have, we have, you know, if a transaction, different model rate, you win when you take money out of your account or when you transfer money more potently into your account, you need to make sure it's there, right? You want to know that with a hundred percent confidence and to do that I would expect you feel more confident running that >>credit card transactions, same game all over again. Mission critical versus non mission critical, I mean internet of things. But what's not mission critical is my follow up question here of things. Some sensors data that's passive. I, if it's running my airplane, ass running your temperature. Oh, you're down for 10 minutes. I mean, yeah, >>there were some times that we would accept, accepts and downs. >>Lumpy. No, it's really about lumpy SLA performing. Amazon gets away with that because the economics are fantastic, right? So you can't be lumpy and bank transaction. What about costs versus, Oh mainframe. So expensive, so expensive. You guys put out some TCO data that suggest it's less expensive. Help us get through that. >>Yeah, so, so I think when we look at total cost of ownership, we're often looking at the savings to administration and the management of the complexity of sprawl. And with the mainframe, because you have such scale and what you can include in it in a single footprint, you can now consolidate so much into this literally very small environment and the cost savings because of the integration capabilities, because of the performance that you can contain within this box, you see end-to-end cost savings for our clients. And in that, that the break even point is not so large. Right. And so you talked about mission critical. If you're doing your mission critical work on your mainframe and you have other things that you need to do that aren't, you don't consider perhaps as mission critical, you have an opportunity to consolidate. You can do that all on the same platform. You're, you're not, you know, we, we can run with tremendous utilization. You can, you want to use these machines for all their work. >>So sorry. So a follow up on that. So the stickiness then AKA lock-in used to be, I got a bunch of COBOL code that won't run anywhere else. He got me, I got to keep buying Mayfair. I was just saying now the stickiness is for the types of workloads that your clients are running. It is cheaper. That's your, >>it's cheaper. And I think it has unmatched capability, availability, security features that you can't find in other solutions. >>And if you had to, in theory you could replicate it, but it would just be so expensive with people. >>In theory, I, okay. But I think some the fundamental technologies and solutions across that stack, who else can do that? Right. Okay. Can integrate solutions in the hardware and all the way up that stack. And, and I, I don't know anyone else, >>tell me what, tell me what, in your opinion, what gets you most excited about this technology platform? I mean, is there a couple things? Just are one thing saying >>that is so game changing. I'm super excited by this. Um, I can't sleep at night. I'm intoxicated technically. I mean, what gets you jazzed up on this? >>Well, I, I'll tell you, it's, today's a really proud day. I have to say being here and being a part of this launch, you know, personally having been a part of the development, been an IBM for 15 years. I spent the last eight years doing hardware development, including building components and key parts of the system. And now to see us bring that to market and with the value that I know we're bringing to clients, it's, it get, I, I get a little choked up. I truly, honestly, I truly, honestly feel really, really proud about what we've done. Um, so in terms of what is most exciting, um, I think the analytics story is incredibly powerful and I think being able to take a bunch of the technologies that we've built up over time, including some of the new capabilities like in database transformation and advanced analytics that we'll be continuing to roll out over the course of this year. I think this can be really transformative and I think we can help our clients to take advantage of that. I think they will see tremendous value to their business. We'll be able to do things that we simply couldn't do with the old model of moving data off and, and having the latency that comes with that. So I'm really excited about that >>nice platform, not just a repackaging of mainframe. Okay, great. So second, final question from me I want to ask you is two perspectives on, um, the environment, the society we live in. So first let's talk it CIO, CEO, what mindset should they be in as this new transformation? The digital businesses upon them and they have the ability to rearchitect now with mainframe and cloud and data centers. What should they be thinking about as someone who has a PhD in applied physics, been working on this killer system? What is the, what's the moonshot for that CIO and, and how should they be thinking about their architecture right now? >>So I think CEO's need to be thinking about what is a good solution for the variety of problems that they have in their shops and not segment those as we've often seen. Um, you have the x86 distributed world and maybe you have a main frame this and that. I begin to think about this more holistically about the set of challenges you need to go address as a business. And what capabilities do you want to bring to bear to solve those problems? I think that when you think about it that way, you get away from good enough solutions. You get away from some of this, um, mindset that you have about this only plays over there. And this only plays over there. And I think you open yourself up for new possibilities that can drive tremendous value to their businesses. And we can think differently about how to use technology, drive efficiency, drive performance, and real value. >>Last night at dinner, we, we all, we all have families and kids. Um, and you know, even there's a lot of talk about software driving the world these days. And it is, software's amazing. It's great. Best time to be a software developer. Since I've been programming since I was in college and, and it's so much so awesome with open source. However, there's a real culture hacker culture now with hardware. So, um, what's your advice to young people out there? You know, middle schoolers or parents that have kids in middle school for women, young girls, young boys with this. Now you've got drones, you've got hackers, raspberry pie, these kinds of things are going on. You've got kind of this Homebrew computer mindset. These young kids, they don't even know what Apple butter >>I would say it is, it is so exciting. Uh, the, the, the engineering world, the technology challenges, hardware or software. And I wouldn't even differentiate. I think we have a tremendous opportunity to do new and exciting things here. Um, I would say to young girls and boys don't opt out too soon. That means take your classes, studying math and science in school and keep it as an option because you might find when you're in high school or college or beyond, that you really want to do this cool stuff. And if you haven't taken the basics, you, you find yourselves not in a position to be able to, to, to, to team and build great things and deliver new products and provide a lot of value. So I think it's a really exciting area. And I've been >>it's a research as I'm seeing like this. I mean I went to the 30th anniversary for apples Macintosh in Cupertino last year and that whole Homebrew computer club was a hacker culture. You know, the misfits, if you will. And a coder camp. >>I think that think there are people who grow up in, always know that they want to be the engineer, the software developer. And that's great. And then there are others of us, and I'll put myself in that in that space that you may have a lot of different interests. And what has drawn me to engineering and to the, the work that we do here is has been the, the ability to solve tough problems, to, to do something you've never, no one has ever done before, to team with fantastically smart people and to build new technology. I think it's an incredibly exciting space and I encourage people to think about that opportunity >>from a person who has a PhD in applied physics. That's awesome. Thank Kevin. Thanks for joining us here inside the queue, VP of systems. Again, great time to be a software build. Great time to be making hardware and solutions. This is the cue. We're excited to be live in New York city. I'm John furry with Dave Alante. We'll be right back. This rep break.