>> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

>> From around the globe, it's the cube, with digital coverage of IBM think 2021 brought to you by IBM. >> Hi everybody, Welcome back to IBM Think 2021. My name is Dave Vellante and you're watching the cubes continuous coverage of this event. We go out to the events, we extract the signal from the noise but doing that virtually for the better part of a 14 months now, we're going to get deeper into application modernization. Marie Ashway is here. She's the director of marketing at Mainline Information Systems and David burrows. Burrows is an account executive at Mainline folks. Welcome to the cube, great to have you on today. >> Thank you. Nice to be here. >> Marie, I want to start with, with Mainline. A lot of people might not be familiar with Mainline but you've transformed over the past five years. I wonder if you could describe that for our audience? >> Yes, we have, indeed we have, Mainline, you know is a 30 plus year company and, and for 30 odd years we had really been focused a lot in hardware, right? Hardware reselling. That's what the market needed. That's what we did a lot of. But then in the past I would say five to eight years, maybe even 10 years we started on this transformation project for the business where we started transforming ourselves into really systems integrators versus just hardware reseller. So now we can go to a client and we can say, Hey now what are you struggling with? Right? What are your business challenges? And then from there we can integrate a solution that might be hardware. It might be software, it might be some services it could be managed services. It could be staffing services could be a number of different things and put all that together and then deliver a complete solution that helps them with their, their business requirements. >> Well, David, that that must've been an interesting transition because what Marie just described as it used to be every opportunity was a nail and whatever box you were selling was the hammer. And that, that has changed dramatically. Of course. So you, you, I wonder what that discussion was like with, with, with clients. You must have heard that early on and said, Uh-Oh this cloud thing is happening. The world is changing. We've got to change too. I wonder if you could chime in on that transformation. >> Yes. That's our, as our clients have been changing what we've been doing is, you know, making sure that we fully understand what's available, not only in the marketplace, but the competition. What, what each industry segment, for example, banking versus insurance versus a utility maybe facing during this this time. And so, you know, being able to transform as a as an accounting dedicated, we've been able to indicate. And so provide solutions as Marie indicated, the large focus over the last five years has been networking and security. As we move more compute to the edge, close to the edge security has been predominant. And so, you know, hardware is really almost commoditized through and through and with the exception of, you know IBM, Z and, and power. And so, you know, we've had to really sellers, you know focus on what customers are dealing with and how they transition. And as we, you know, through COVID, it's actually been a bigger challenge, a bigger focus on security. And I think we'll talk about that a little bit later in more detail >> Let's, let's, let's do that now. So, so Marie, maybe at a high level, you could talk about those challenges that your clients are facing. And then we can sort of double click on how that was exacerbated by, by COVID. And I'm really interested in your perspectives on sort of the post isolation economy and how those challenges are going to shift, but, but maybe maybe kick us off at the high level if you could. >> Sure. So, so, you know, people, companies were moving toward the the whole digital transformation, right? Probably for the past three to four years we started seeing more and more that constantly everybody sees those buzzwords all the time. So clients were shifting in that direction and we were shifting to try to satisfy them with their needs with those solutions but then came COVID and all of a sudden, right. What people were, were planning on doing for the next, let's say five years. I mean, most of the CEO's were saying, yeah we're going to get there in five years. Well, that had to happen. Right. It had to have brakes went on and it had to happen instantaneously. So that put a big change in focus a big change in direction for not only our clients. Right. But for our own folks, folks like David who are trying to service these clients with having to bring them these solutions that we're going to solve their digital business needs today and not five years from now. >> Yeah. So David let's, let's talk about that. I mean, what Marie just described I call it the forced march to digital, because as Marie as you were saying, people were on a digital transformation but there was a little bit of complacency and okay, we'll get there. We're really busy doing some other stuff. And then all of a sudden you've probably seen the meme of the COVID wrecking ball coming, coming into the building the office building and saying, you know, you know, well we're doing fine and all of a sudden, boom the forced COVID comes in. So, so, so so how did that affect your clients and how did you respond? I mean, they're asking for VDI and get me some laptops, I need end point security. And so how did that affect the the application modernization efforts and David maybe you could comment on that. >> So I, I think for, for me, the biggest challenge was all business, the competition within business to survive COVID, you know, they had to put on first thing was how do we get our, our customer supported correctly? And how do we get our workers supported working at home? So the very first thing we did over the initial six months was most companies had to transform immediately within the first 30 to 90 days to allow their workforce to work from home. That happened throughout my, my customer base, both in Southern California, was customers really focused on how do we do business process? How do we compete in this marketplace and get return on investment speed, you know, time to value or what we invest in these COVID times so that we can compete with other businesses that are trying to stay alive through this transition. And, and now, you know, we're seeing on the, on the back end you know, that time, the value in terms of investment is even more important because some businesses have been significantly impacted from knowing cashflow, but you know, certainly in terms of profitability during this time. >> Makes sense. And so, Marie, so we were talking earlier about the sort of the initial path to digital transformation. And I wonder if that's got to be course corrected. I would think we were forced in to compress, you know the digital reality and, and I guess in a way that's good but in a way it was, we probably made a lot of mistakes. It was a bit of a Petri dish. So now as we begin to ,knock on, exit COVID you would think those those imperatives adjust and they start to become aligned. What's your take on that, especially as it relates to application and infrastructure modernization. >> So I would agree with that. I think that there's definitely has to be a little bit of a of a realignment happening. And I know recently I read that 2021 is expected to be a very large year in IT spend because all of those initiatives that CEOs and others were going after pre COVID kind of got put on hold, right. So they could then go focus on all of those digital means that were needed. Like, you know, the CDI, you know, work at home all the security stuff for that. So I think we're going to see, I'm thinking, we're going to see a shift again now, and maybe businesses are going to go back and try to pick up where they were prior to COVID and now start working on more of really of the application modernization initiatives that were in mind. And I know we wanted to talk about that as well because David's been working on quite a bit of application modernization with a few of his clients as we're seeing again, businesses change. And, and I don't know that all of that changes because of COVID. I think all of that change was for their competitiveness, to get there anyway. So I think that's going to start, as you said before, David I think it's going to start now having to kind of rethink up >> It reminds me of traffic on the M four David have you ever been to driving in in London when it's slingshots? Right? It's that's what's COVID was like Marie, you're absolutely right. Last year IT spend was down 4 to 5% this year. I mean, our prediction is it's going to be in the 6 to 7% range, which, which, which kind of aligns with where Gartner and IDC are based on our surveys. But, you know, back in, in April like I think the 16th of April it was a headline of wall street journal that the China grew 18% GDP in the quarter. So it's very hard to predict, but, but it's coming back you know, we can see that David and so so spending is really going to accelerate. There's probably some pent-up demand for that application modernization. Maybe it's been a little bit neglected as we've done as Maria was saying. And you were saying that work from home. So maybe you could talk a little bit more about the modernization aspects and maybe I'm really interested in the things that you guys deliver in your portfolio with IBM. >> Sure. So what I have customers in multiple phases within this current digital transformation there are customers moving everything to the next gen development which is a fully containerized code. Being able to, you know swiftly go through their development tests and hybrid cloud environments where they're they haven't made an investment yet but they're sampling what it might be like to change into that world. And then there are customers are still in the typical environment, the traditional environment and are looking at what the solutions as far as packages are available for them moving forward. So they can kind of skip over any kind of development and being able to leverage what I call next gen development or next gen systems immediately as you know, you ask, you know, what are the what are the systems that are available? IBM's cloud pack solution set. It provides a portfolio of capabilities both in the application suite, database suite, security. I have customers today leveraging that. And, and so that is one of the first pieces that that customers I see who are on the leading edge or are also kind of trailing, are looking at these cloud bags to be able to go time to market and time to value quickly. >> Yeah. So when I look at your portfolio I just sort of scan the web. David just mentioned Marie, cloud pack. I mean, we're talking software here. You guys do have a lot of expertise in Z, Z Linux, Power. You mentioned is not a commodity. And it's one of the few pieces of hardware that and Z they're not a commodity. Storage, I would think business resiliency fits in there beyond disaster recovery. You Red Hat, we're talking, you know, things like open open shift and Ansible for automation. So these are, these are not your grandfather's main line. These are toolkits are a piece of, you know, parts of the tool bag that you bring to bear to focus on on client outcomes and solutions is am I getting that right? >> Yes, absolutely. Absolutely. And again, right, that goes back to the original opening comment about how we've transformed as a business, right. To become an integrator putting all of these different pieces together. I mean, I know that something that that David recently had worked on, Oh my goodness. If you would have looked at the list of pieces of elements to that solution, it was really quite incredible between open source stuff, you know and a bunch of IBM stuff. Yes. It was some storage and yeah, there was some power. Yes. There was Red Hat. Right. But then there was other stuff, there was VMware there was some things that I can't even remember now all the names to all the components, but it was it was a laundry list. Right. And so that's where though Mainline stepped in and put the pieces together for the customer so that the customer then can get done what they needed to get done, which was which was really solve their business problem which was trying to become more competitive in their market space. >> Okay, David, so when Marie was just staying was basically my takeaway is, is this a system integrator? You've got all these piece parts with these technologies you've got virtualization, you've got automation you've got containers and so forth. And yes, there's there's hardware but there's this integration that has to occur. And your job is to abstract that complexity that underlying complexity away so that the customers can focus on the outcome. Maybe you could talk about that and how you do that. >> Sure. I'll, I'll give you a good example of a recent customer that we work with, who was basically implying, we consider an enterprise data platform that, that was going to rework their entire data warehouse into something that had governance surrounding it where they could validate all the data that was coming into their warehouse. And so we underpinned that with an infrastructure of power. We're running, obviously IBM pack for data with DB two warehouse. We use a combination of that with five-year data flow through IBM with the streaming and the governance IBM governance catalog piece, which is lots of knowledge catalog. So we've been able to take not only what their base requirements were, but all the microservices that are packaged in with cloud pack, all running on open shift which was a great acquisition that IBM did last year. And then they also required other microservices outside to support that environment >> Paint a picture for us as to what the future looks like. It's, it's much different than the past 30 years and bring us home, please. >> Sure. So I think the future for us is to continue to to find all of the solutions that will that will help our customers, you know get to their next steps. Right. And, and there's a lot, as you know did this lots of solutions out there. There's lots of new companies that are popping up all the time. You know, inherently, you know, Mainline is an IBM partner. We've been an IBM partner for 30 plus years since our inception. And that's the base of our business is, is IBM. But, but there are other requirements that are needed by by businesses, by our customers. And that's where we, we reach out and partner up. We probably have gone my goodness 200 plus partnerships with various companies various technology companies that we can then lean on and pull in those ancillary solutions to, to to complete that, that solution for the customer. So I think we're going to continue going down that path. We're going to continue making sure that we're partnered with the, the, the leading technology companies. So we can build that IBM solution for our customer and and bolt on the other pieces that are needed. We're going to continue to grow and enhance our services business because we've got quite a large services business whether it's implementation services, we do manage services we have staffing services. I think you're going to see we're still going to continue to, to grow that business because that is a piece where companies, you know they don't want to worry about running all of that stuff, right. They want to know that their system's going to be running 24 seven. And if there is a bump or a burp or something happens, Hey they could pick up the phone, they can call Mainline. We can help them get things corrected. So I think we're going to still see a lot of that going on as well within our, our, our offerings. >> Excellent. Well, congratulations for making it through that. Not a whole lot, not not every hardware seller reseller made it through and you guys transformed. It's a, it's an inspiring story. Marie, David, thanks so much for coming on the cube. >> Thank you. >> Thank you very much. >> You're really welcome. And thank you for watching everybody. This is Dave Volante in our continuous coverage and the cube of IBM think 2021. Keep it right there.

(bright music) >> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

from the cube studios in Palo Alto in Boston it's the cube covering the IBM thing brought to you by IBM we're back this is the cubes coverage of the IBM think 20/20 digital experience my name is Dave Volante is a wall-to-wall coverage over the multi-day event Harish promise here he's the general manager of the IBM public cloud rishi welcome back to the cube good to see you sorry we're not face to face but this will do yeah thank you great to see you again as well and you know it is the times what do you do you know I want to start by asking you you did a stint at a large bank I'd love to talk to you about that but but I want to stay focused you said last year on the cube you can't do everything in the public cloud certain things need to remain on Prem I'm interested in how your experience at the large financial institution and your experience generally working with you know your colleagues in in the banking industry how that shaped your vision of the IBM public cloud yeah I think that's a great question you know if you think about trying to transform yourself to a public cloud a lot of people what they try to do is you know they take applications that I've been running their enterprise and they try to redo them in its entirety with micro services using as level services I mean trying to put it all up in the public cloud now you know just think about some of these applications that are running your large institution right some of them will have regulatory ruled around it some of them have latency requirements or low latency requirements I should say some of them need to be close to the back end because that's where the data is so for all these reasons you know you have to think about a holistic cloud picture of which public cloud is you know integral to it but some of the things will need to remain on Prem right so when I build my public cloud out for IBM I kind of keep those in in the back of my mind as I get the team to work on it to ensure that we have the right capabilities on the public cloud and then where it makes sense you know have the right capabilities on the hybrid side as well working with my colleagues in IBM well you know the doc Ovid 19 pandemic that we've been talking to a lot of CISOs and CIOs we had a couple of roundtables with our data partner ETR and it was interesting you know organizations that maybe wouldn't have considered the cloud certainly as aggressively maybe they put some test dev in the cloud but you know have said well we're really reconsidering that one CIO actually said you know I'd love to delete my data center but but to your point you can't just delete the data center um first of all you don't want to necessarily move stuff second of all we've got a lot of experience from a consulting standpoint looking at this if you have to migrate migrates like an evil word especially with mission critical systems if you have to freeze code and you can't upgrade you know for some number of months you may be out of compliance or you're not remaining competitive so you have to really be circumspect and thoughtful with regard to what you do move I wonder if you could comment on that no I completely agree with what you're saying you know if you think about to your point right with Kovac things that really changed I've been speaking with a lot of cloud transformers I would say you know in the various industries but specifically with banks as well and the cloud leader for one of the large European banks said to me he said this was amazing because for four years he's been trying to get his he shows organization and risk and compliance etc to get their heads around moving applications to the cloud and he said that you know one month of kovat and having everyone locked down and home has been able to unblock more than what he's tried in the last four years so that's telling in itself right so look you know I've been working on public clouds for a good long time now both from a provider side as well as a consumer side and while you know you certainly just can't close your data centers that are running your large enterprise overnight you certainly can take a lot of stuff over there and move it to the public cloud in a meaningful fashion where you're able to take the pieces that really iterate more rapidly where you can get the end while keeping your data safe and you know being able to connect back into your back-end systems which will run a lot of your large processes in your enterprise as well so I think there is a balance to be had here and people especially banks I would say haven't been moving so much to the public cloud and I think this is the time where they're starting to realize that there is a time and place for a bunch of applications that can safely move and that gives them the agility and the productivity while everyone's locked at home and I think that's the eye opening so I'd love to have a frank conversation about why the IBM cloud I mean you know you got the the big guys you know Amazon Microsoft and Google maybe not as large people put them sort of in a category of hyper scalars great fair enough that people oftentimes dismiss you know the IBM public cloud however your point that you just made is critical and Ginni Rometty you was the first to kind of make this point Arvin's picked up on it that 80% of the workloads still are on trem and and it's that hard to move stuff that hasn't moved so and that's kind of IBM's wheelhouse I mean let's face it that the hard stuff it's the mission-critical you're kind of running the the banks and the insurance companies and the manufacturers and airlines around the world so what's the what's the case for the IBM cloud why the IBM cloud and why even move that stuff why not just leave it where it is yeah so I think there's a couple of answers here right one of them is the fact that when you talk to the hyper scalars and by the way I can't stress enough or a hyper scaler as well right people have taken a look at iCloud from about two plus years ago which you know at which point in time we were not but we certainly are and we can provision via size and so on and so forth as best as the best guys can so I want to just get that out of the way but to your point you know the reason why you would consider the IBM public cloud is when you talk to the other people they come at it from a very narrow perspective right they think about you know use vs is on x86 using cloud native pass services now you know I want to stress again that we do all three of those things extremely well but if you think about how large enterprises work nothing is as clean as that I did say there is a lot of applications that I've been running your institution that you can just willingly rewrite and then you have bare metal you'll have power systems whether it's AIX or I you'll have some Z in there Z Linux in there and then there's containers and then there's the VMware stack and there's containers running on bare metal containers running on vsi containers running on you know the VMware stack as well as the other architectures that I mentioned so we really meet our customers where they are in their journey and we give them a wide variety of capabilities and choices and flexibility to do their applications on the public cloud and that's what we mean by saying our cloud is enterprise ready as opposed to the nano answer of you'll do everything with vs is x86 and a service yeah I like that and I want to I want to circle back on that thank you for clarifying that point about hyper skills having said that it I've often said and I wonder if you could confirm or deny it's not IBM strategy to go head-to-head on cost per bit even though you you will you'll price it very competitively but your your game is to add value in other ways through your your very large software portfolio through AI things like blockchain and differentiable services that you can layer on top I've often made the point I think a lot of people don't understand that that insulates IBM from a race to the bottom with the alcohol traditional a cloud suppliers I wonder if you could comment yeah you know so I have to stress the point that just because I talk about all our other distinguishing capabilities that people don't walk away with the impression that we don't do what any of the other large cloud service providers do you know to your point we have AI we have IOT we've got a hundred ninety API driven cloud native pass services where you can write a cloud native application just like you build on the hyper scale other hyper scalars as well right so we give nothing away but for us the true value proposition here is to give you all of those capabilities in a very secure environment you know whether it is the fact that we are the only cloud where we don't have access to your data or your code because we have a keep your own key mechanism where we as a cloud service provider have no access to your key nobody else can say that so it is those Enterprise qualities of service and security that we bring to the table and the other architectures and the other you know constructs around bare metal and containers etc that distinguishes us further right and that's how it really so these are really important points that you're making and I know I'm kind of bringing out probably parts of the landscape that IBM generally doesn't want to talk about but I think it's important again to have that frank conversation because I think a lot of people misunderstand IBM is in the cloud game not only in the cloud game to your point but has very competitive you know from an infrastructure standpoint so many companies in the last decade we saw HP tried to get in they exited very quickly Joe to cheese's the CEO of EMC said we will be in the cloud you know they're buying mozi and you know exiting that so Dell right now doesn't you know it won't have a cloud play VMware tried to get in and now its course big partner of yours so you got in and that to me is critical just in terms of positioning for the next decade and beyond and and the other piece of differentiation that I want to drill into is the financial services cloud so what is that you obviously have a strong background there let's let's dig into that a little bit yeah if you look at the way most banks or actually every bank uses a public cloud is they build guardrail right they build guardrails from where their data center ends to where the public cloud begins but once you get into the public cloud then it really depends on the security that the cloud service providers provide and the csps will tell you that they have a lot of secure mechanisms there but if you ever speak with a bang you know they will never put their highly confidential data bearing apps with PII on a public cloud because they don't feel that the security that the cloud service providers provide is good enough for them to be able to put it there safely number one and number two prove to their regulators that they are in fact and compliant so what we've done is we work with a Bank of America and now you know a whole bunch of other banks that I'm not allowed to mention by name as yet where we're building a series of controls right these are both controls during your dev Sakharov cycle when you're building your app and another 400-plus controlled and the runtime that allow you is the bank to securely take your apps that have highly confidential data in III and put it on the public cloud and will give you the right things whether it's the isolation of the control plane and the data plane or it's their data loss prevention mechanisms the right auditing points the right logging points the right monitoring points the right reporting data sovereignty so we have controls built into the cloud that enable you to do all of this now banks will be quick to tell you that the onus of proof is on them alone to the regulators and we can claim that for them and they're absolutely right but today they spend hundreds of millions of dollars collecting all of that in providing that proof to the regulators you use our cloud we automate a whole bunch of that so you're not number one as a bank trying to implement these controls on a public cloud because that's not your job that's not your core expertise and number two when you actually build these compliance report you spending you know millions and millions of dollars trying to put it together whether compliance regulator will say yes this is okay we automate a large part of that for you and I think that's the key is the key issue we're solving you I want to follow up and just make sure I understand it is when I talk to executives in the financial services industry and other industries those they'll say things like look it's not that the cloud security is is bad it's just that I can't map the edicts of my organization into it certainly easily or even at all because I'm getting a sort of standard set of capabilities and it may not fit with what I need what I'm what I what I'm hearing is that IBM you know you guys are enterprise-c you used the specials but but so that's part of it but you also said you know they feel sometimes the cloud is that the security is not good enough and I want to understand what that is specifically if IBM is doing something differently so two things there one is your willingness whether it's auditability transparency mapping to corporate edicts and it may be other things that you're doing that make it better relative to go together yeah absolutely so one of the things is as I mentioned it's the mechanisms like keep your own key which is fundamental to building some of these compliance safeguards in but the the fundamental different thing we've done here is we work with the Bank of America and we've defined these controls to use your language that maps to their edicts right which should map to every banks edicts no you know there'll be a couple of extra controls here or there but largely they're all regulated by the same regulator so what satisfies one bang for the most part satisfies every other bank of the US as well right and so specifically what we've done is we've built those controls whether they are preventative controls or compensating controls in the CI CD pipeline as well as in the runtime on the cloud and that gives them a path to automation to produce the right results and the right reports to their auditors and that's really what we've helped them do so I know I'm pushing you here a little bit I'm gonna keep pushing if that's okay I was a great conversation when when IBM completed the acquisition of Red Hat you know the marketing was all about cloud cloud cloud and I came out and said yeah okay fine but what it's really about is application modernization that's the near-term opportunity for IBM you certainly saw that in the last earnings report where I think you're working with a hundred plus you know clients in terms of their application modernization so I said that is the way in which this thing becomes a creative which by the way it's already a creative and from a cash cash flow standpoint but but but but I'm gonna press you on on the cloud piece so talk about Red Hat and why it is cloud in terms of a cloud play yeah so you know this is the power of Red Hat and the IBM public cloud and of course Red Hat works or the other cloud print service providers as well so if you think about modernizing your application you know the industry pretty much has standardized around containers right as the best way to modernize their applications and those containers are orchestrated by kubernetes that's the orchestrator that's basically won the battle and Red Hat has OpenShift which is a industry-leading capability you know it's a coupon IDs control plane that manages containers and we from IBM we've put our content we've read backer a content into containers and we've made it run on an open ship and we have a cloud managed open ship server on the IBM public cloud as well as an on-prem that really helps bring our content to people who are trying to modernize their applications now think about an application that most people try to modernize you know the rough rule of thumb about 20 to 25 percent of it there's application code that is the onus is on the client to go and modernize that and they've chosen containers and turbidities and the other 75 to 80% arguably is middleware that they've got right and we've really tected in refactor that middleware into containers managed by open ship and we've done 80% of the work for them so that's how this whole thing comes together and you can run that on Prem you can run it on the IBM public cloud and I give you a cloud managed openshift service to do that effectively honor so that's interesting yeah that's very interesting I think there are you know probably at least three sort of foundational platforms one is obviously easy mainframe it's still much of IBM's customer base you know the tied to the Z and it drives all kinds of other software and so what the second is middleware to your point and you're saying you refactored and I think the third really is your choice of hybrid cloud strategy you kind of made the point you threw an on-prem it's to me it's that end-to-end that's your opportunity and your challenge if you can show people that look we've got this cloud-like experience of from cloud all the way to RM multi clouds that is a winning strategy it's jump ball right now nobody really owns that space and I think IBM's intent is to try to go after that I think you've called it a trillion-dollar market opportunity and it's obviously growing yes that's exactly right and the P spot so that I've been describing to you the you know the way people modernize our applications all fit very nicely into that now if you speak with the analysts they're going towards a whole different category called distributed cloud which basically means you know how do you bring these capabilities that run on your public cloud do on-prem and do other people's clouds and you know what I hinted at here is that's exactly where we're going with our set of capabilities and that is a technical journey I mean kubernetes is necessary but insufficient condition to have that sort of Nirvana of this distributed massive distributed system bring in edge edge systems as well so this is a you know at least a multi-year maybe even a decade-long journey there's a lot of work to be done there what would you say are their strategic imperatives for IBM cloud over the next several years so I think for us really it is you know building on this notion of the distributed cloud as I talked about it is you know fully building out the FSS cloud most of which we've already done and you know some of these things will never be at end of job because regulations keep changing and you keep adding to it and so you have to keep adding to it as well so a focus on FSS to begin with but then also to other industries as well right because there are other regulated industries here that can benefit from the same kind of automation that we're doing for FSS so we'll certainly do that and we're in a good position because it's not only our technology but it's our services practice it's a premonitory that deals with regulators etc so we have the whole package so we want to continue to build out on that branch into other industry verticals using our industry expertise across the board services product everything and then of course you know if there's one thing I BM has market permission for it is understanding the enterprise and building a secure product so we clearly want to evolve on that as well the IBM is a lot of arrows in its quiver including as we discuss cloud you know you just got to get her done as they say so iris thanks so much for coming to the cute great discussion appreciate your your transparency and and stay well Thank You YouTube thank you so much re welcome and thank you for watching everybody this is the cubes coverage of the IBM pink 2020 digital event experience we'll be right back right after this short break [Music]

(energetic music) >> From Washington D.C., It's theCUBE! Covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> Welcome back to TheCUBE's coverage of ScienceLogic Symposium 2019, I'm Stu Miniman, and we're here at the Ritz-Carlton in Washington, D.C. Happy to welcome to the program two first-time guests from ScienceLogic, to my left is Leslie Minnix-Wolfe, who is the Senior Director of Product Marketing. And to her left, is Russ Elsner, who's the Senior Director of Product Strategy. Thank you so much for joining us. >> Thank you sir. >> Good, good to be here. >> All right, so Leslie let's start with you. Talk a lot about the product, a whole lot of announcements, Big Ben on the keynote this morning. Everybody's in, getting a little bit more of injection in the keynote today. Tell us a little bit about your roll, what you work on inside of ScienceLogic. >> Okay, so I am basically responsible for enterprise product marketing. So my job is to spin the story and help our sales guys successfully sell the product. >> All right, and Russ. >> I'm part of the product strategy team. So, I have product management responsibilities. I work a lot with the analytics and applications. And I spend a lot of time in the field with our customers. >> All right so, Leslie let's start with enterprise, the keynote this morning. The themes that I hear at many of the shows, you know we talk about things like digital transformation. But, we know the only constant in our environment is change. You know, it's good. I've actually talked to a couple of your customers and one of them this morning he's like "Look, most people don't like change. "I do, I'm embracing it I'm digging in, It's good." But, you know, we have arguments sometimes in analyst circles. And it's like are customers moving any faster. My peers that have been in the industry longer, they're like, Hogwash Stu. They never move faster they don't want change, we can't get them to move anything. I'm like, come on, if they don't the alternative is often, You're going to be... You know, you're competitors are going to take advantage of data and do things better. So, bring us a little bit of insight as what you're hearing from your customers both here and in your day to day. >> Sure, yeah, change is constant now and so one of the big challenges that our customers are facing is how do I keep up with it. The traditional manual processes that they've had in place for years are just not sufficient anymore. So they're looking for ways to move faster, to automate some of the processes that they've been doing manually. To find ways to free up resources to focus on things that do require a human to be involved. But they really need to have more automation in their day to day operations. >> All right, so Russ when I look at this space you know, tooling, monitoring has been something that in my career, has been a little bit messy. (laughter) Guess a little bit of an understatement even. It's an interesting... When I look at, kind of, that balance between what's happening in the infrastructure space and the application space. I went through, one of your partners over here is like "from legacy to server lists and how many weeks." (laughter) And I'm like okay that sounds good on a slide but, these things take awhile. >> Absolutely. Bring us inside a little bit, kind of the the application space an how that marries with the underlying pieces and monitoring. >> Yeah, you have a lot of transformations happening. There's a lot of new technologies and trends happening. You hear about server lists or containers or microservices. And that does represent a part of the application world. There are applications being written with those technologies. But, one of the things is that those applications don't live in isolation. It's that there part of broader business services and we're not rewriting everything and so the new shiny application and the new framework has to work with the old legacy application. So, a big piece of what we see is how do we collapse those different silos of information? How do we merge that data into something meaningful? You can have the greatest Kubernetes based microservice application but, if it requires a SAP instance it's on PRIM it's on Bare Metal. Those things need to work together. So, how do you work with an environment that's like that? Enterprise, just by it's nature is incredibly heterogeneous, lot's of different technologies and that's not going to change. >> Yeah. It's going to be that way. >> You're preaching to the choir, here. You know, IT it always seems additive the answer is always and. And, unfortunately, nothing ever dies. By the way you want to run that wonderful Kubernetes Docker stuff and everything. I could do it on a mainframe with Z Linux. So, from that environment to the latest greatest hypercloud environment >> Right. Talk a little bit about your customers. Most of them probably have hundreds of applications. They're working through that portfolio. What goes where, how do I manage all of those various pieces, and not kill my staff? (laughter) One of the things we're spending a lot of time with this, is that obviously, we come from a background of infrastructure management. So, we understand the different technologies different layers and the heterogeneous nature and on top of that runs application. So they have their own data and there's APM space. So we're seeing a lot of interest in the work we're doing with taking our view of the infrastructure and marrying it to the application view that we're getting from tools like Appdynamics or Dynatrace or New Relic. And so, we're able to take that data and leverage it on top of the infrastructure to give you a single view which aids in root cause analysis, capacity planning and all the different things that people want to do. Which lead us to automation. So, this idea of merging data from lots of sources is a big theme for us. >> All right so, Leslie who are some of the key constituents that you're talking to, to messaging to. In the industry we talked about silos for so many time. And now it's like oh, we're going to get architects and generalists. And you know cloud changes everything, yes and no. (laughter) We understand where budgets sit for most CIO's today. So, bring us inside what you're seeing. >> Sure. Yeah, we're seeing a tremendous change. Where before we use to talk more to the infrastructure team, to the folks managing the servers, the storage the network. We're really seeing a broader audience. And a multiple constituent. We're looking at directors, VP's, CIO's, CEO's, architects. We're starting to see more people that are tools managers, folks that are involved in the application side of the house. So, it's really diverged. So, you're not going in and talking to one person you're talking to lots of different teams, lots of different organizations that need to work together. To Russ's point in about being able to bring all this data together. As you bring it together, those different stakeholders have more visibility into each others areas. And they also have a better understanding of what the impact is when something goes down in the infrastructure, how it effects the app and vice versa. >> Leslie, the other thing I'm wondering if you can help me squint through, when I looked at the landscape, it's, you know, my ITSM's I've got my logging, I've got all my various tools and silos. When I hear something like, actually, your CEO Dave just said "Oh, we just had a customer that replaced 50 tools." with there it's like, How do you target that? How does a customer know that they have a solution that they have a challenge that you fit, Because, you understand, you can't be all things to all people. You've got certain partners that might claim that kind of thing. >> Right But, where you fit in the marketplace how do you balance that? >> Well, so I think what we're seeing now is that there have been some big players for a long time. What we refer to fondly as the Big Four. And those companies really haven't evolved to the extent that they can support the latest technology. Certainly at the speed with which organizations are adopting them. So, they might be able to support some of the legacy but they've really become so cumbersome, so complicated and difficult to maintain people are wanting to move away from them. I would say five years ago, most organizations weren't willing to move down that path. But with some of the recent acquisitions, The Broadcom acquisition, Microfocus acquisition. You're seeing that more organizations are looking to replace those tools in their entirety. And as a result of that they're looking at how can I minimize my tool set. I'm not going to get rid of everything and only have one vendor. But, how do I pick the right tools and bring them together. And this is one of the areas where we do extremely well in that we can bring in data, we can integrate in other tools, we can give you the full picture. But, we're kind of that hub, that central. And I think we heard that earlier today from Bailey at Cisco, where he talked about ScienceLogic is really the core to their monitoring and management environment, because we're bringing the data and we're feeding the data in to other systems as well as managing it within ScienceLogic. >> Russ, I actually heard, data was emphasized more that I expect. I know enough about the management and monitoring space. We understand data was important to that, I'm a networking guy by background, we've been talking about leveraging the data for network and using some automation and things like that but it's a little bit different. Can you talk some about those relationships to data? We understand data's going to be everywhere and customers actually wrapping my arms around it make sure I can manage it, compliance and to hopefully get value out of that is one of the most important things in today. >> Absolutely, so one of the things we stress a lot when we talk about data, it use to be that data was hard to come by. We were data poor and so how do we get... We don't have a probe there so how do we get this data, Do we need agent? That's different now, data is... We are drowning in data, we have so much data. So, really the key is to give that data context. And so for us that means a lot of structure, and topology and dependencies across the layers of abstraction, across the application. And we think that's really the key to taking this, just vast unstructured mess of data that isn't useful to the business and actually be able to take... Apply analytics, and actually take action, and ultimately drive automation by learning and maintaining that structure in real time automatically, because that's something a human can't do. So, you need machine help, you need to automate that. >> So, Leslie, there was in the keynote this morning that to start discussion of the AI Ops maturity model >> Right >> And one of the things struck me is there was not a single person in the poll that said, yes I've gone fully automated. And first, there's the maturity of the technology, the term and where we are. But, there's also that, let's put it on the table. That fear sometimes, is to "Oh my gosh, the machines are taking our jobs" (laughter) You know, we laugh, but it is something that needs to be addressed. How are you addressing that, Where are your customers with at least that willingness, because I use to run operations for a number of years, and I told my team, look you're going to have more work next year, and you're going to have more things change, so if you can't simplify, automate. Get rid of things, I've got to have somebody helping me, and boy those robots would be a good help there. >> What we're seeing is, I mean let's be real, people don't like to do the mundane tasks, right. So you think about, When you report an issue to the service desk. Do you really want to open that ticket? Do you want to enter in all that information yourself? Do you want to provide all the details that they need in order to help you? No. People don't do it they put in the bare minimum and then what ends up happening is there's this back and forth, as they try collect more information. It's things like that, that you want to automate. You want to be able to take that burden off of the individuals And do the things, or at least allow them to do the things that they really need to do. The things that require their intelligence. So, we can do things like clean up storage disk space when your starting to run out of disk space. Or we can restart a service, or we might apply a configuration change that we know that is inconsistent in environment. So, there's lots of things like that that you can automate without actually replacing the individual. You're just freeing them up to do more high level thinking. >> Russ, anything else along the automation line. Great customer examples or any successes that you've seen that are worth sharing? >> Yeah, automation also comes in the form of connecting the breadcrumbs. So, we have a great example. A customer we worked with, they had an EPM tool, one of the great ones, you know, top of the magic quadrant kind of thing, and it kept on reporting code problems. The applications going down, affecting revenue, huge visibility. And it's saying code problem, code problem ,code problem. But the problem is jumping around. Sometimes it's here, sometimes it's there. So, it seemed like a ghost. So, when we connected that data, the APN data with the V center data and the network data what it turned out was, there was a packet loss in the hypervisor. So, it was actually network outage that was manifesting itself as a code problem, and as soon as they saw that, they said what's causing that network problem? They immediately found a big spike of traffic and were able to solve it. They always had the data. They had the network data, they had the VMware data they had the JVM data. They didn't know to connect the dots. And so, by us putting it right next to each other we connected the dots, and it was a human ultimately that said I know what's wrong, I can fix that. But it took them 30 seconds to solve a problem that they had been chasing after for months. That's a form of automation too is get the information to the human, so that they can make a smart decision. That's automation just as much as rebooting a >> Exactly server or cleaning a disk >> Well right, It's The Hitchhikers Guide to the Galaxy. Sometimes, the answers are easy if I know what question to ask. >> Exactly, yes. (laughter) >> And that's something we've seen from data scientists too. That's what their expertise is, is to help find that. All right, Leslie give us a little view forward. We heard a little bit, so many integrations, the AI ops journey. What should customers be looking for forward? What are they asking you, to help bring them along that journey? >> Oh gosh. They're asking us to make it easier on all counts. Whether it's easier to collect the data, easier to add the context to the data, easier to analyze the data. So, we're putting more and more analytics into our platform. So that their not having to do a lot of the analysis themselves. There's, as you said earlier, there's the folks that are afraid they're going to lose their job because the robots or the machines are taking over. That's not really where I see it. It's just that we're bringing the automation in ways and the analytics in ways that they don't want to have to do, so that they can look at it and solve the really gnarly problems and start focusing on areas that are not necessarily going to be automatable or predictable. It's the things that are unusual that their going to have to get involved in as opposed to the things that are traditional and constant. So, Russ, I'd love for you to comment on the same question. And just a little bit of feedback I got talking to some of the customers is they like directionally where it's going, but the term they through out was dynamic. Because, if you talk about cloud you talk about containers. Down the road things like serverless. It's if it pulls every five minutes it's probably out of date. >> oh, Absolutely. I remember back when we talked big data, real time was one of those misnomers that got thrown out there. Really, what we always said is what real time needs to mean is the data in the right place to the right people to solve the issue >> Absolutely. >> Exactly. So, where do you guys see this directionally, and how do you get more dynamic? >> Well see, dynamic exists in a bunch of different ways. How immediate is the data? How accurate is the dependency map, and that's changing and shifting all the time. So, we have to keep that up to date automatically in our product. It's also the analytics that get applied the recommendations you make. And one of the things you can talk to data scientists and they can build a model, train a model, test a model and find something. But if they find something that was true three weeks ago it's irrelevant. So, we need to build systems that can do this in real time. That they can in real time, meaning, gather data in real time, understand the context in real time, recognize the behavior and make a recommendation or take an action. There's a lot of stuff that we have to do to get there. We have a lot of the pieces in place, it's a really cool time in the industry right now because, we have the tools we have the technology. And it's a need that needs to be filled. That's really where we're spending our energy is completing that loop. Closed loop system that can help humans do their jobs better and in a more automated way. >> Awesome. Well, Leslie and Russ, thanks so much for sharing your visibility into what customers are doing and the progress with your platforms. >> All right, thank you Stu. >> And we'll be back with more coverage here from ScienceLogic Symposium 2019. I'm Stu Miniman, and thank you for watching theCUBE. (energetic music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to theCUBE live at the inaugural IBM Think 2018 event. I'm Lisa Martin with Dave Vellante. Excited to be joined by a guest from down under, Garrett McDonald, the head of Enterprise Architecture at the Department of Human Services in Australia. Welcome to theCUBE. >> Thank you very much. >> Great to have you. So tell us about the Department of Human Services, DHS. You guys touch 99 percent of the Australian population. >> Yeah, we do. We sit within federal government, we're a large service delivery organization. So through a range of programs and services we touch pretty much every Australian citizen on an annual basis. And within our organization we're responsible for delivery of our national social welfare system, and that picks up people pretty much across the entire course of their lives at different points, we're also responsible for delivering the federally administered portion of our national health system, and that picks up pretty much every Australian every time you go to a doctor, a pharmacy, a hospital, a path lab, indirectly both the provider and the citizen are engaging with our services. We're responsible for running the child support system, but then we also provide IT services for other government departments, so we implement and operate for the Department of Veterans Affairs, and also the National Disability Insurance Agency. And then finally we also run Whole-of-government capabilities, so DHS we operate the myGov platform, that's a Whole-of-government capability for citizens who government authentication and within out program we have 12 million active users and that number continues to grow year on year, and that's the way that you access authenticated services for most of the major interactions that a citizen would have online with government. >> And your role is formerly CTO, right? >> Yep. >> You've got a new role. Can you explain it? >> Yeah, I'm a bit of a jack-of-all-trades within the senior executive at DHS, I've had roles in ICT infrastructure, the role of CTO, the role of national manager for Enterprise Architecture, and I've also had application delivery roles as well. >> Okay, so let's get into the healthcare talk because the drivers in that industry are so interesting, you've got privacy issues, in this country it's HIPAA, I'm sure you're got similar restrictions on data. Um, what's driving your business? You've got that regulation environment plus you've got the whole digital disruption thing going on. You've got cloud, private cloud, what's driving your organization from a technology perspective? >> I think there's two main factors there. We have changing citizen expectations, like we've got this continued explosion in the rate of changing technology, and through that people are becoming increasingly comfortable with the integration of technology in their lives, we've got people who are living their lives through social media platforms and have come to expect a particular user experience when engaging through those platforms, and they're now expecting the same experience when they interact with government. How do I get that slick user experience, how do I take the friction out of the engagement, and how do I take the burden out of having to interact with government? But at the same time, given we are a government agency and we do have data holdings across the entire Australian population, whether it's social welfare, whether it's health or a range of other services, there's this very very high focus on how do we maintain privacy and security of data. >> Yeah, I can't imagine the volumes of transactional data for 12 million people. What are some of the things that DHS is using or leveraging that relationship with IBM for to manage these massive volumes of data? You mentioned like different types of healthcare security requirements alone. What is that like? >> We've been using IBM as our dominant security partner for quite some years now, and it's been the use of data power appliances and ISM power appliances out at the edge to get the traffic into the organization. We're deploying Qradar as our Next Gen SIEM and we're slowly transitioning over to that. And then as we work out way through the mid-range platform through our investment in the power fleet and back to our System Z, we've been using Db2 on Z for quite some years in the health domain to provide that security, the reliability and the performance that we need to service the workloads that hit us on a day-to-day basis. >> So you got a little IoT thing going on. Right? You got the edge, you got the mainframe, you got Db2. Talk a little bit about how, because you've been a customer for a long time, talk about how that platform has evolved. Edge data, modernization of the mainframe, whether it's Linux, blockchain, AI, discuss that a little bit. >> Okay, so over the past three years we've been developing our Next Gen infrastructure strategy. And that really started off around about three years ago, we decided to converge on Enterprise Linux as our preferred operating system. We had probably five or six operating systems in use prior to that, and by converging down on Linux it's given us a, the ability to run same operating system whether it's on x86, on Power, or Z Linux, and that's allowed us to develop a broader range of people with deep skills in Linux, and that's really then given us a common platform upon which we can build an elastic private cloud to service our Next Gen application workloads. >> Now you've talked off-camera. No public cloud. Public cloud bad word (laughs) But you've chosen not to. Maybe discuss why and what you're doing to get cloud-like experiences. >> Yeah, so we are building out a private cloud and we do have a view towards public cloud at a point in the future, but given mandatory requirements we need to comply with within the Australian government around the use of the Cloud, given the sensitivity of the data that we hold. At this point we're holding all data on premise. >> Can we talk a little bit more about what you guys are doing with analytics and how you're using that to have a positive social impact for these 12 million Australians? >> Yeah, we've got a few initiatives on the go there. On how do we apply whether it's machine learning, AI, predictive analytics, or just Next Gen advanced analytics on how do we change the way we're delivering services to the citizens of Australia, how do we make it a more dynamic user experience, how do we make it more tailored? And on here that we're exploring at the moment is this considerable flexibility in our systems and how citizens can engage with them, so for example in the social welfare space we have a requirement for you to provide an estimate of the income you expect to learn over the next 12 months, and then based on what you actually earn through the year there can be an end-of-year true-up. Right, so that creates a situation where if you overestimate at the start of the year you can end up with an overpayment at the end of the year and we need to recover that. So what we're looking at doing is well how do we deploy predictive analytics so that we can take a look an an individual's circumstances and say well, what do we think the probability is that you may end up with an inadvertent overpayment, and how can we engage with you proactively throughout the year to help true that up so that you don't reach the end of the year and have an overpayment that we need to recover. >> So I wonder if we could talk about the data model. You talk about analytics, but what about the data model? As you get pressure from, you know, digital, let's call it. And healthcare is an industry that really hasn't been dramatically or radically transformed. It hasn't been Uberized. But the data model has largely been siloed, at least in my experience working with the healthcare industry. What's the situation in Australia, and specifically with regard to how do you get your data model in shape to be able to leverage it for this digital world? And I know you're coming at it from a standpoint of infrastructure, but maybe you could provide that context. >> Well, given for privacy reasons we continue to maintain a pretty strong degree of separation between categories of health data for a citizen, and we also have an initiative being deployed nationally around an electronic health record that the citizen is able to control, right, so when you create your citizen record, health record, there is a portion of data that is uploaded from our systems into that health record, and then a citizen can opt in around, well what information when you visit the general practitioner is available in that health record. When you go to a specialist you're able to control through privacy settings what information you're willing to share, so it's still a federated model, but there's a very, very strong focus on well how do we put controls in place so that the citizen is in control of their data. >> I want to follow up in that, this is really important, so okay, if I hear you correctly, the citizen essentially has access to and controls his or her own healthcare information. >> Yeah, that's right. And they're able to control what information are they willing to share with a given health practitioner. >> And it's pretty facile, it's easy for the citizen to do that. >> Yeah. >> And you are the trusted third party, is that right? Or -- >> It's a federated model, so we are a contributor to that service. We provide some of the functionality, we feed some of the data in, but we do have another entity that controls the overarching federation. >> Do you, is there a discussion going on around blockchain? I mean could you apply blockchain to sort of eliminate the need for that third party? And have a trustless sort of network? What's the discussion like there? >> We've been maintaining a watching brief on blockchain for a good couple of years now. We've been trying to explore, well how do we find an initial use case where we can potentially apply block chain where it provides a value and it meets the risk profile. And given it does need to be a distributed ledger, how do we find the right combination of parties where we can undertake a joint proof of technology to identify can we make this work. So not so much in HealthSpace, there are other areas where we're exploring at the moment. >> Okay, so you see the potential of just trying to figure out where it applies? >> Yeah, absolutely, and we're also watching the market to see well what's going to become the dominant distribution, how a regulatory framework's going to catch up and ensure that, you know apart from the technical implementation how do we make sure that it's governed, it's administered -- >> Do you own any Bitcoin? No, I'm just kidding. (laughter) How do you like in the Melbourne Cup? So, let's talk a little bit about the things that excite you as a technologist. We talked about a bunch of them, cloud, AI, blockchain, what gets you excited? >> I think the AI and machine learning is a wonderful area of emerging technology. So we've also been pushing quite hard with virtual assistants over the past two to three years, and we have six virtual assistants in the production environment. And those span both the unauthenticated citizen space, how do we assist them in finding information about the social welfare system, once you authenticate we have some additional virtual assistants that help guide you through the process, and then we've also been deploying virtual assistants into the staff-facing side. Now we have one there, she's been in production around about 18 months, and we've got very very complex social welfare legislation, policy, business rules, and when you're on the front line and you have a customer sitting in front of you those circumstances can be really quite complex. And you need to very quickly work through what areas of the policy are relevant, how do I apply them, how does this line up with the legislation, so what we've done is we've put a virtual assistant in place, it's a chat-based VA, and you can ask the virtual assistant some quite complex questions and we've had a 95 percent success rate on the virtual assistant answering a query on the first point of contact without the need to escalate to a subject matter expert and we figure that if we saved, we've had it round about a million questions answered in the last year, and if you think that each one of those probably saves around three minutes of time, engaging in SME, giving them the context and then sorting through to an answer, that's three million minutes of effort that our staff have been able to apply to ensuring that we get the best outcome for our citizen rather than working through how do I find the right answer. So that's a bit of a game-changer for us. >> What are some of the things that you're, related to AI, machine learning, cloud, that you're excited about learning this week at the inaugural IBM Think? And how it may really help your government as a service initiative, et cetera. >> Yeah, so I think I see a lot more potential in the space between say machine learning and predictive analytics. On based on what we know about an individual and based on what we know about similar individuals, how do we help guide that individual back to self-sufficiency? Right, so for many many years we've been highly effective and very efficient at the delivery of our services, but ultimately if we can get someone back to self-sufficiency, they're engaged in society, they're contributing to the economy, and I think that puts everyone in a pretty good place. >> Alright, so I got to ask you, I know again, architecture and infrastructure person, but I always ask everybody in your field. How long before machines are going to be able to make better diagnoses than doctors? >> Uh, not so sure about doctors, but within our space our focus has been on how do we use artificial intelligence and machine learning to augment human capability? Like, the focus is on within our business lines within our business lines we have room for discretion and human judgment. Right, so, we don't expect that the machines will be making the decisions, but given the complexity and the volume of the policy and legislation, we do think there's a considerable opportunity to use that technology to allow an individual to make the most informed and the most consistent and the most accurate decision. >> So then in your term you don't see that as a plausible scenario? >> No. >> Maybe not in our lifetime. >> As I said the focus is very much on, well, how do we augment human capability with emerging technology. >> So Garrett, last question and we've got about a minute left. What are some of the things that you are excited about in your new role as head of Enterprise Architecture for 2018 that you see by the end by the time we get to December, your summertime, that you will have wanted to achieve? >> Okay, so, over the last roughly two years I've been developing the future state technology design that will reshape out social welfare system for probably the next 30 years. This is a generational refresh we're undertaking in that space, so I think it's been a hard slog getting to this point, we're now starting to build on our new digital engagement layer, we've got a new enrichment layer starting to come to life where we do put that machine learning and AI in place and then we're also starting to rebuild the core of our social welfare system, so this is the year for me where we go from planning through to execution, and it brings me an immense sense of pleasure and pride to see the work that you've been pouring yourself into for many years start to come to fruition, start to engage with citizens, start to engage with other government agencies, and start to deliver the value that we know that it's capable of delivering. >> Well, sounds like a very exciting year ahead. We want to thank you so much, Garrett, for stopping by theCUBE and sharing the insights, what you guys are doing to help impact the lives of 12 million Australians. >> Thank you very much. >> Have a great event. >> Thank you. >> And for Dave Vellante I'm Lisa Martin. You're watching theCUBE's live coverage of the inaugural IBM Think 2018. Stick around, we'll be back with our next guest after a short break.