from Yorktown Heights New York it's the queue coverings IBM cloud innovation be brought to you by IBM hi I'm Peter Burris and we have wrapped our the cubes coverage of IBM innovation day here at the Thomas J Watson Research Center in Yorktown Heights now for anybody that's been in the industry for a while you know that this is one of the mecca's of the computing industry this is where an enormous number of innovations have taken place innovations about relating to semiconductor processes and you know CPU architectures innovations relating to middleware and innovations relating to database management and very importantly innovations relating to how customers and companies engage to be more successful with technology and in many respects that's really what's happening with the overall drive to cloud is to bring closer together that invention that takes place and pushes forward what technology can do and then a delivery model that's focused on ensuring the customers can actually more easily do it and IBM is absolutely part of that conversation we'll be going forward especially as we think about how those high-value legacy applications are going to be employed within a cloud context to further drive transaction capabilities with event capabilities in the cloud we've had some great conversations we've heard for example from Hilary hunter who's a CTO here at cloud infrastructure about the new role that opend plays within innovation how IBM is trying to further leverage that with the Red Hat acquisition we've had great conversations with Jason McGee talking about how the developer mindsets evolving in response to some new innovations with cloud we've heard from a number of other individuals I won't list them all but if I were trying to summarize the three points that I think kept coming through it's number one the cloud does force changes to the way you think about business problems and methods tooling and approaches for doing that are starting to mature very rapidly Micro services for an example for example is not just a technology it's also an approach to thinking about a problem and that informs everything I did the second thing that we've heard is that can't just talk about greenfield applications we've had this enormous investment in applications have been running businesses for a long time of those applications tend to be very stateful they tend to be very database driven they tend to be very operational in nature those applications have to move forward if nothing more from at least from a management standpoint how can we bring a management mindset an operating model of the cloud to start to channel or structure change and evolve how we manage those applications but ultimately bring new classes of services to those applications I think the last one that we've heard over and over and over it that this really is gonna require a strong community we have to take a community approach to invention you have to take a community approach to innovation and the social change is required to take advantage of technology and achieve the business outcomes that we want and if one thing has come through loud and clear through all the conversations is that that this year IBM think or I didn't think 2019 San Francisco is gonna be a great place to be able to get together with peers and have those conversations and think about the outcomes that enterprises want to achieve and then talk to people that can actually help you get there and one of the things that I find interesting about think this year is that the industry's changing we're seeing new rules or evolution of roles and an evolution of how those roles work together and think is actually starting to reflect that it's manifesting itself itself there's a couple of campuses one that's focused more on data and AI a very very natural binding or combining and one that's focused more on infrastructure and cloud again very natural so I hope to see be able to carry on and continue these conversations we've had today at IBM think and hope to see you there as well so once again this is Peter Burris Ricky bond the cube from the IBM from the from the illustrious from the vaunted Thomas J Watson Research Center in Yorktown Heights thanks very much for watching the cube today [Music]

>> From Yorktown Heights, New York, it's theCUBE, covering IBM Cloud Innovation Day. Brought to you by IBM. >> Hi, I'm Peter Burris from Wikibon, and you're watching theCUBE being broadcast from IBM Innovation Day at the Thomas J. Watson Research Lab in beautiful Yorktown, New York. And we've had a number of great conversations thus far, we've got some more on the horizon, stay with us. Now, we've got Jim Comfort. Jim Comfort is the General Manager of Hybrid Cloud Services at IBM. Jim, welcome to theCUBE. >> Thank you, Peter, glad to be here. >> So, Jim, what does Hybrid Cloud Services as a group do? >> Actually, we run infrastructure for clients. That's our business, but we help you advise, build and manage private cloud. Advise, build and manage consumption of public cloud, Azure, Google, IBM, and we help you manage and stitch all of that together. >> So a lot of people think of cloud and they think of this monolithic thing. "If I go to the cloud, suddenly my business has changed." But there's more to it than that. There's a number of different things that a business has to be successful at to succeed at getting to the cloud. What is your perspective on that? >> Well, I completely agree. And this is kind of my first conversation with clients is, you need a business strategy, but to execute that strategy you have to realize it will touch most everything in your business. It'll touch infrastructure, it'll touch applications, it'll touch your dev ops, or your development process morph to dev ops. It'll touch your operations very profoundly, this whole SRE thought, and it will test your data governance and management as well as your security and compliance. So that's the scope that you have to comprehend. >> But most people, they start with perhaps the infrastructure first and end up with the data last. Is that the right way to think about this? >> I agree, many do, and actually I have not seen many build-it-they-will-come strategies succeed. And so what I really look for is, do you understand the business drivers? Top-line revenue growth, new markets, new insights, new data, and from that can you derive a technology strategy? What I've seen happen in many cases is, if you start from the bottom up you'll be trapped in what I call the religious wars of technology that never end. >> And most people, a lot of folks start from the bottom up, because they start from the technology side of the business. >> Correct. >> Are you seeing more business people getting engaged, and conceptualizing what the strategy needs to be? >> I am, and it starts on both sides. The business people will say, "I need to move faster than you can move, so I'm going to do something different," and the IT people will say, "I can do that for you, here's what you need." The two signatures of the most successful transformations are does the line of business and the IT have the relationship to collaborate so they actually learn together? And then if they have that, have they actually created a team that understands the new as well as they understand the existing or the old, so they can actually understand what's real, what's not, where's the hype, what really happens. And then they get into the rational, real planning decision. >> So as you think about some of the assessment challenges, because you said you go through the assessment process, what are some of the key questions that a client should start with as they think about undertaking this journey? >> Well, number one is start with the business driver. I said that already, but you have to start with understanding what you're trying to accomplish so you can make choices. And the other is, start small enough and get to the end of something so that you know what the reality is, and that's where our, this is where we bring in our methods. When you hear us talk about the garage method, you hear us talk about MVPs and all the language everyone wants to use. We like to start with something, and start that iterative cycle of learning. That's the key. >> So with an iterative cycle of learning, in many respects this whole notion of agility is predicated on this idea of being agile or iterative. But it's also empirical, knowing what the data is, knowing what the data says, and being opportunistic. How does a customer balance that as they get going, say early on in the cloud journey? >> I think, again, most of what we're talking about in digital transformations is new insights that will help your business. That could be from data that you had, it could be new data. And if they think about it, what insights am I looking for? What new experience am I trying to create, and what do I need to do that? Then you start to get people to step back and think, well, what are all the possibilities? And now, how do we tackle that? So it starts from realizing, what insight am I looking for? >> So there's a lot of invention happening in the industry. >> Oh, yeah. >> And enormous new things being created. Customers are being overwhelmed at trying to adopt them. The innovation side, the social side of effecting a change in the business. You mentioned some of the markers for success and putting together the strategy. Go forward a little bit. What are some of the companies that have successfully gotten to that end stage maturity doing differently? >> We have a number of very good ones. I mean, a very clear one in my mind is American Airlines, where they were really trying to change the experience. They had three distinct things that had grown up over time, the mobile experience, the kiosk experience and the Web experience. Three completely different things. They brought it together, converged it, modernized it, and now completely changed the experience and the speed with which they can now act on what they see for their clients or for their customers, all of us. But also as they get new ideas, the speed and the velocity that they can bring those in is phenomenal. >> And that improves their ecosystem, their ability to work with a lot of others as well. >> Their ecosystem, how to work with others, how to bring in new ideas. And this is all, for them it's all about client satisfaction and service to their end client, to the end user. That's what it was. It had a lot of technology dimensions, but they were very clear the experience they were trying to attack. >> So next February, IBM Think, 30-plus thousand people descending upon San Francisco. You guys are taking it over. What kind of conversations are going to be on your agenda as you work with customers and partners to get this message out? >> Well, it's really two things. I often joke the blessing and curse of IBM is the breadth of our portfolio. It's a very large place, but we actually have a very simple, clear way to talk to, advise, move, build and manage. Those are the steps you need in your journey. Now, which journey for you, which type of thing. But that, we have clarity on that, and I think you'll see that displayed at Think and get to understand it. The other thing is that we have a lot of experiential and real practical, we've made this happen for many large clients at scale, and I think that what we want people to understand is we can help you that same way. It's really pretty simple. >> Jim Comfort, General Manager Hybrid Cloud Services at IBM. Thanks for being on theCUBE. >> Thank you, Peter. >> And we'll be back momentarily with more from theCUBE at IBM Innovation Day here at the Thomas J. Watson Research Center in New York.

>> From York Town Heights, New York, it's theCUBE covering IBM Cloud Analyst Summit, brought to you by IBM. (techy music) >> Hi, welcome back, I'm Peter Burris of theCUBE, and we're having conversations here at the IBM Innovation Day at the Thomas J. Watson Research Lab in York Town Heights, New York. We've got a great conversation. Don Bolia is the general manager of cloud developer services at IBM, welcome to theCUBE, Don. >> Thank you very much. >> Or should I say welcome back to theCUBE? >> (chuckling) Yes, thank you. >> So, Don, we were talking with one of your colleagues, Hillery Hunter, who's the CTO-- >> Mm-hm. >> Of here at the cloud infrastructure team, and about the fact that everybody's talking about the rate of growth of data, and nobody's really discussing the rate of growth of software, which is perhaps even more important, ultimately, to business. What is that rate of growth look like, and how is it related to the role of cloud? >> Yeah, so it's a great question. I mean, with my role as kind of owner of our platform services from the cloud perspective, one of the things we've noticed over the last probably five or 10 years is just a massive rate and pace change with respect to iteration on the software development cycle. So, they started with mobile, I would say, and then has moved to cloud since then, where you know, the expectation is everything is updating all the time, you know, everyday, all times of the day. Within our own Kubernetes and container service, as an example, we push over 500 updates a week to that software stack on behalf of our customers, and so I think there's a rate and pace of how things are changing from that perspective, but then there's also the fact that everybody's leveraging those services to then build the next generation of software. So, in our case we have a set of base services that I provide for things like containers that then the Watson team, for example, uses to build their microservices, which are then, you know, realized as machine learning and other types of services that they provide. So, you see the stacking of software, if you will, from you know, the high iteration rate at the bottom all the way to the next level and the next level, and the ability to unlock value now is something that happens in, you know, hours in some cases, or a couple of days, whereas before just provisioning the software would've taken months, and so we're really seeing just a whole change in the way people can develop things and how quickly they can get to the end result. >> Now, we're here at the Thomas J. Watson Research Lab, and downstairs is this wall of all IBM fellows, and one of them E.F. Codd, the famous originator of database and the role that SQL played, et cetera-- >> Mm-hm. >> In relational database technology. He wrote a seminal paper back in the early 1970s about how the notion of developer was going to evolve over time, and he might've been a little aggressive in thinking that we were going to end up with these citizens developers than we actually happened, but we are seeing the role of developer changing, and we are seeing new classes of professionals become more developer-like. >> Mm-hm. >> How is that relationship changing the way that we think of developer services that you serve? >> Yeah, it's a great question. I think, first of all, software is sort of invading almost every single industry, and so, you know, people have got to have some amount of those skills to be able to function in kind of the optimal way for whatever industry they're in. So, what we're seeing is that as we've built more and more foundational services, the act of actually creating something new is more about stitching together, composing, orchestrating a set of things, as opposed to really building from scratch everything from the ground up, and you know, things like our Watson services are a great example, right? The ability to tap into something like that with a couple lines of code in an hour, as opposed to what would've taken, you know, months, years, whatever, and even really, frankly, been out of the reach of most developers to begin with is now something you can have somebody come in and do, you know, with a fairly low level of skill and get a good result on the outside. >> So, we've got more demand for code as we move to digital business, more people participating in that process, cloud also enables paths, a lot of new classes of tools that are going to increase the productivity-- >> Yep. >> Including automated code generation. How is the process, how is that tool set evolving, especially as it pertains to the cloud? >> Yeah, so I think one of the mantras of cloud is automation, and in order to standardize and automate, that's really how you get to the kind of scale that we would see in, say, a public cloud like the IBM cloud. So, it really is kind of a fundamental premise of anything you do has to be something that you automate, and so we've seen a whole class of tools, to your points, really start to emerge, which allow people to get that kind of, you know, automated capability. So, nobody thinks of, for example, creating a, you know, a build pipeline these days without using a set of tools. You know, often they're opensource tools, and there's a lot of choice within that whole spectrum of tools, and we support a bunch of different varieties, but you would never think today of having a build process that isn't totally automated, right, that can't be instantly recreated. Even the whole process of how you deploy code in a cloud these days is sort of an assumption that you can destroy that and restart at any point, and in order to do that, you really need the automation behind that, so I think it's a base premise now. I don't think you can really be at the velocity that people are expecting out of software without having a totally automated process to go through that. >> So, any digital business strategy presumes that data's an asset, and things that are related to data are assets, including software in many... Well, software is data when you come right down to it. >> Mm-hm. >> And we want to exploit that data and generate new sources of value out of that data, and that's one of the predicates of digital business, but at the same time we also want to protect those attributes of data-- >> Mm-hm. >> That are our IP, our enterprise's distinction. As we move forward with software, how do we reconcile that tension between more openness and generating a community that's capable of improving things, while at the same time ensuring that we've got good control over our IP where it actually does create a business differentiation? >> Now, that's right, and you're right, data's king. So, you know, the software can do, you know, a set of things, but most of the time it's operating on a set of that data, and that data's where the true value that you can unlock comes from. Our policy, from an IBM perspective, has always been that, you know, your data is yours, and to your point, this IP that you may want to protect, and we try to give you the tools to do that, and so a lot of our philosophy, within the cloud in particular, is around things like Bring Your Own Key, where you have control of the keys that encrypt that data that's in the cloud. In fact, we would like to be totally out of that loop, quite frankly, and have it be something that is controlled by our clients, and that they can, you know, get the value they're looking for, and so we'll never have a situation where one of our services is, you know, using or acting on data that is really, you know, not ours to use, and so that's been a fundamental premise of the cloud as we go forward, and again, we continue to provide a set of tools that really let you manage that, and to your point, you know, not everything gets managed at the same level. Some things are highly protected, and therefore have, you know, layers and layers of security policy around them, and there's other examples where, you know, you're relatively able to make that open through a set of APIs, for example, and let everybody have access it. From our perspective, though, that's really a client choice, and so for us it's about giving the right tools so that they can do the job they need to do. >> February 2019, San Francisco, IBM's taking over San Francisco with the IBM THINK show. What types of conversations are you looking forward to having with customers? What excites you about the 2019 version? >> Yeah, so I mean it's a great venue. It is absolutely, you know, something that I look forward to every year. I know my team looks forward to it, as well. I mean, the amount of interaction we get with clients... I mean, it's really all about the client stories, so you know, what are they able to do, in my case, with our cloud services. What can I learn about what they've done, and how, you know, can we then leverage that to make our services better, and so, you know, to me it's all about, you know, what you can learn from others, and it's a great form to be able to do that and there's a lot of great things that, you know, you can dive deep on. You get access to a lot of the IBM technical experts, so I have all of my, you know, fellows and distinguished engineers there, you know, on hand, and just great conversations. There's always great insights that you get from it, highly recommend it. >> Don Bolia, IBM general manager of cloud developer services, thanks very much for being on theCUBE. >> Thank you. >> Once again, we'll be back from IBM Innovation Day here at Thomas J. Watson Research Center in York Town Heights, talk to you soon. (techy music)

>> From Yorktown Heights, New York, it's theCUBE, covering IBM Cloud Innovation Day, brought to you by IBM. >> I'm Peter Burris of Wikibon. Welcome back to IBM Innovation Day, covered by theCUBE, from beautiful Yorktown Heights, New York, Thomas J. Watson Research Center. A lot of great conversations about the journey to the cloud and what it means, and we're going to have another one here with Denis Kennelly, who is the General Manager of Cloud Integration in IBM. Denis, welcome to theCUBE. >> Thank you, Peter, and welcome to Yorktown also. >> I love it here. So, very quickly, what does the GM of Cloud Integration do? >> Yeah, so, I suppose we start from the beginning, right? So I am responsible for a lot of what we call the traditional IBM middleware. So these are brands that are known to the industry and to our customers, things like WebSphere, Message Queue, or MQ, as we know it, which is kind of the core foundation stones for a lot of IT today that's out there in the industry. And it's not just about, you know, sometimes people talk about this legacy, but this is what all the systems run on today. And also, I'm involved in the whole journey of moving that middleware to the cloud and enabling customers to get on that journey to cloud. And it's not just to a cloud, because your typical enterprise today has probably on average about five different clouds, and clouds, as we know them as the IS players of the past, but also when we talk about cloud, we also think about things like SaaS properties and applications of that regard. So it's helping customers go from that traditional IT infrastructure and on their journey to the cloud. That's what I do. >> So utilizing these enterprise-ready technologies that have driven the enterprise, bringing them to the cloud as services, but also making sure that the stuff that's currently installed can engage and integrate the cloud from a management service standpoint as well. >> Absolutely, because customers have made a huge investment in this middleware, and a lot of the transactions, and a lot of the security, and a lot of the risks set in these systems, and they have served us very well for many decades. Now, as we start to move to the cloud, it isn't a binary switch. It's going to be a transition over time, and today, I think we're about 20% into that journey. I would say we've done some of the easier parts. Now we're getting into some of the more complex and some of the more difficult problems. And kind of one of the underlying pieces of technology we're using to enable customers to do that is container technology. So we've made the decision to use containers right across our middleware, our software. So what I mean by that is we've taken all our software and it's running on containers today, and that's a key enabler to make this happen, because containers give you that flexibility and that openness to run on different targeted environments and be able to run on different clouds at the end of the day. >> The model by which developers thought about integration would be through a transaction. Generally pretty stateful. So, I'll put something in a queue, I'll wait for a response, guaranteed delivery. Now we're moving to a world, containers, a lot more reliance on stateless interactions. It means we're being driven mainly by events. I'm thinking in terms of events. Talk about how that is changing the way we think about the role of middleware or the role of integration amongst all these different possible services. >> Yeah, it's a great point. I mean, so if you think about containers, we think about stateless, and we think about microservices, and we talk about event-based applications, so a lot of those front ends are on that today and building on those technologies. So you've got to enable the new developers to build in that way. Now, how do you integrate that with that backend, right? Because at the end of the day, these transactions are running in the backend, and you really want to enable, as part of the transformation, you want to open up those backends to those new developers and to those new customer insights, because what is digital transformation? It's about putting the customer at the middle and enable insights on those customers, and enable rapid development of those applications. So at the core of that is integration, and integration is not just message-based integration. It's being able to take those backend transactions and surface them up through APIs, not just the standard APIs as we think of maybe as web services, but event-based probability models, and event-based APIs also, and doing that in a consistent and a secure manner, because if you have all these complex transactional systems, who has access to that data? Who has access to make those transactions? Who can, at certain levels, et cetera, and we really have to do that in a secure and a consistent manner across these environments is critical to what we do. >> So, can you give us some examples of some customers that are successfully transitioning their backend systems to these new technologies in a way that protects the backend system, makes it economical to do so, in other words, doesn't force change, but can utilize some of these new integration technologies to make both the new investments more valuable but also the backends more valuable too. >> Yeah, I mean, if you think of, I'll give you an example of a customer, American Airlines, in the airline industry, right? So, if you think about travel and airline travel in times past, you know, you made a reservation maybe through an agent and you booked the flight from A to B. Today, you have your cellphone, you get regular updates on your flights. If you're delayed, you're possibly offered re-routing options, et cetera, right, so there's a classic example of how digital has transformed the airline industry and the airline booking industry. If your flight, you know, if there's weather patterns, et cetera, how you can get real time updates on your flights. So, okay, that's all happening on the front end, on your cellphone, or your tablet, or whatever, but the backend booking system is still a transactional-based system that says, Peter is on this flight going from A to B at this time, et cetera. So, that's an example of how we have modernized an application and we have worked with American Airlines to make that happen, to give you that kind of 360 view as a customer, where you bring in together flight information, weather information, rating information, because we'll offer you different alternatives in terms of if you need to rebook in the event of something going on, and at the backend, there's still a transaction that says, book Peter on this flight from A to B, and that's a real life example of a transformation, how we've integrated those two worlds there. >> So if we go back five or six, or more than that, say 10, 15 years, in the days of MQ, for example, the people who were developing, and setting up those systems, and administering and managing those systems were a relatively specialized group. Today, the whole concept of DevOps in many respects is borrowing from much of the stuff that those folks did many, many years ago as infrastructure builders, or developers, as I call them. How does that group move into this new world of integration in the cloud? >> Yeah, so, I think first of all, the rate and pace has multiplied, right, so the rate and pace of which we make changes to the system has multiplied. I mean, maybe traditionally, we run in changes maybe once a month. We have things like change control windows. Things were very well controlled, et cetera, right? But at the end of the day, it doesn't meet the needs of today and what we need to do in a digital world. So today, we're running in changes on the hour. So now, you're faced with a challenge, right? So when you make changes, how do you know that the system is still performing, is still operating at the level you need it to operate on? You start to think about security and you start to think about, okay, I've made a change, have I introduced vulnerabilities into the system? You've got to, you know, in the past, these were all separate groups and almost islands within the operation center, where you have the developer, who kind of over to all the code, and then operations looked at it and see how it's performed, and security checked for compliance, et cetera, and they were kind of three different islands of personas or groups within the organization. Today, that's really collapsing into one organization. The developer is responsible for making sure the change gets in, for making sure the change performs, and is also security compliant. And we call this the role of the SRE, or the systems reliability engineer, and really bringing those two worlds together into one persona, and it's not just one persona but having the systems on the inside to make that happen. And that's critical in how management is changing and the management of these systems is changing, and how the skill level is needed in this new world. >> So Denis, one more question. In a few months, IBM Think is going to take over San Francisco, February 2019, >> Looking forward to it. >> 3,000 people. Talk to us a little bit about what gets you excited about Think, and what kind of conversations you hope to be having while you're there. >> Yeah, well, you know, this is the one time of the year where all of IBM comes together, and it's new this year that we're going to San Francisco, and in particular, in our cloud business, which I'll talk about, which really encompasses everything we're talking about here, which is our middleware business and also how we move customers to the cloud, and really engaging with customers in those conversations. And this is the one time of the year where all of IBM comes together, and where you can see the full breadth of our capabilities all the ways from our systems, and the hardware, down at that level, at the chip level, right through to the middleware and the software to our cloud, and actually engaging with customers, and really understanding what the customer needs are, and making sure that what we are working on is meeting those customer needs, and of course, if we need to adapt or change, and take that feedback back into the organization, so we do that in real time. It's a very exciting time for us. It's a week in the year that I really look forward to, because that's where all of IBM comes together, including our services, et cetera, and where we actually have conversations with key customers and partners and really understanding what's going on in the industry and how we can help people on this journey to the cloud that I talked about. >> Denis Kennelly, IBM General Manager of Cloud Integration, thanks very much for being on theCUBE. >> Thank you, Peter. And once again, this is Peter Burris. We're signing off from the IBM Innovation Day, here at the Thomas J. Watson Research Center in Yorktown Heights. Thank you very much for watching. Let's carry on these conversations about cloud and the future of computing.

>> From Yorktown Heights, New York, it's theCUBE, covering IBM Cloud Analyst Summit, brought to you by IBM. >> Hi, I'm Wikibon's Peter Burris. Welcome back to theCUBE coverage of IBM Innovation Day, here at the Thomas J. Watson Research Center in Yorktown Heights, New York. Great series of conversations, and this next one also is going to be a great conversation, with Jason McGee, who's an IBM Fellow, VP and CTO of Cloud Platform here at IBM. Jason, welcome to theCUBE. >> Thanks for having me. >> So, we've had a lot of great conversations about what does open mean, where is the cloud going, what is the role of developers in this whole thing, but I want to dig a little bit deeper into this kind of core question. The cloud suggests a new model for computing. I would also think that would mean that there's a new model for development on the horizon. >> Yeah, absolutely. >> Can you talk to us a little bit about that? >> Yeah, sure, I mean, I think that's absolutely true. I think one of the core things that people are trying to get out of cloud these days is development velocity, you know. For many years, of course, one of the key pressures in IT has been how do I do stuff more quickly, and that's gone through many iterations over time, but I think cloud today, people are really trying to figure out how to leverage cloud as a platform for speed of development, and the combination of services on cloud, and new development models like microservices, and new technologies like containers are all kind of contributing elements in helping people solve this problem, how do I build stuff more quickly. >> So, with all that new technology, is a new mindset required? Does somebody think about the problem differently, does somebody break the problem down differently? How do you start with that notion of looking at a business requirement or business outcome, and translate it into the technology? We used to just create code. Now we're doing something different. >> Yeah, I think the first thing you have to do is think about how to organize people. You know, software development at the end of the day is a sport amongst people and you have to think about how to break up the problem, and so, like microservices, a lot of us think of microservices as a technology. It's not really a technology, it's really a philosophy about how to attack a problem with a group of people, it's about how to organize, and its fundamental idea is break it into independent parts, and allow a small team of people to not only develop that part but to own it end-to-end, you know, like the old development model was development, test, production, hand it over the wall to operations. The new model is break it into small problems and then have a team own the whole thing end-to-end, and with that new organizational philosophy comes new architectures for apps, new technologies to help you do that, and new platforms to run things on. >> So, as we think about that, that suggests that the approach to software from a licensing standpoint, from what are you buying, what are you installing is also going to change. How do you foresee, and what is IBM preparing customers for in this kind of new world where software is a service coming from a lot of different places as opposed to a license with, you know, 800 million lines of code or eight billion lines of code behind it? >> Yeah, it's interesting. I think these new ideas are enabled by things like cloud. Part of the reason that cloud has enabled this new model to be feasible is because you get, for example, consumption-based pricing. You can use a wide variety of technologies, you can pick the right tool for the job, you can pay for just what you use, and therefore, the old models of static software licensing and big platforms can start to fade away as these small teams are able to kind of pick the right tool for the job, and that wouldn't be possible in a world without like, as a service delivery, and meter pricing, and things like that, because you would have to consolidate to fewer choices and buy bigger chunks of things. >> As you said, microservices is more of a philosophical approach to how you think about software, and it's also predicated on that wonderful notion of REST. A great paper was written a number of years ago on APIs. IBM has kind of an interesting role in the industry, though. IBM has got to bring a whole bunch of customers with highly stateful applications forward into the cloud. Kubernetes, great for stateful. How are we going to address that tension between the stateless world of greenfield applications and the stateful legacy that has to move into this new world? >> Yeah, I'm glad you brought that up. I mean, I think a lot of times new trends emerge and it's easy to ignore the past, but the lesson I've learnt in over 20 years in IT is like, nothing ever goes away, right, and so you have to not only define the future, but you have to figure out how to help people get there. I actually think part of the reason technologies like Kubernetes are so dominant right now is because they actually do a reasonable job at both. You know, Kubernetes and containers are a great platform for the kind of new architectures and for adopting these new methodologies we're talking about, but they can also accommodate the existing apps, and you can move existing apps into these new platforms, and so, that helps give people a path. They can move something they have and then slowly re-factor it, or they can move something they have and build new things around it, and they could do all that with platforms like Kubernetes as an enabler, right? And it's been interesting to watch. Like, at IBM, we obviously make Kubernetes available, both in our public and private clouds, but we're also big users, and we run all of our cloud services on that platform. Stateful databases, AI and machine learning workloads, analytics platforms, stateless web apps, like, the whole lot, we've been able to run on a platform like that. >> Talk to me a little bit about this notion of cloud operating model and how we manage that, because it seems to me as though the user adoption of a lot of these new technologies are going to be facilitated if we can put forward a management platform that uses those technologies to manage those technologies. What's the relationship there between the evolution of management? Is that a leading edge of how we are going to see people adopt some of these technologies? >> It's certainly a very kind of critical component of the story. I mean, if you really believe in the idea that where we want to move to is this kind of microservice model of small teams that run things themselves, then you get into the question of, all right, well, if you have eight people whose job is to run something in production, they need to be able to do that efficiently, right? You can't have complex operational processes, you need a lot of really good tools, it needs to be really easy for them, 'cause you're asking people to have a really vast set of knowledge, and so, it's driving the evolution of management philosophies. You're seeing new technologies, like SDO, for example, emerge, which are allowing like an application person to define policy about security, and access, and networking that normally would've required like a network expert to go to. >> And more, which makes it a very powerful platform. >> Powerful platform, right, but I think it's coming out of this realization that like, if that small team of people ever want to sleep, and when they have to run things, they're going to need tools to help them do that. So it's been interesting to watch that kind of circular evolution of these different domains. >> So, 20 years of experience from web-sphere forward. Let's think about the next five years. Where is the biggest innovation going to happen in software? >> Well, I mean, there's the obvious stuff around the application of AI, but the part that I'm most excited about is I think we've been on an arc over the last 20 years, to make the application the center of IT. You know, historically, infrastructure has been the center of IT. You start a project, you buy a server, you install an operating system, you set up management tools. >> That's been a big asset. >> The center has been the infrastructure and you build your way up. And I think as velocity has become dominant, we've been trying to flip it and say, I'm building an app. Let me focus on the app, and focus on what the app needs, and drive the requirements down, and I don't think we're done yet. I think there's a lot more to do there, but that's the path we're on. I think over the next five years, we'll really get there, where as an app team, I don't really have to think about infrastructure, and I can have the system adapt to the needs of the application. >> Do you foresee a point where the data and the application are increasingly and further broken apart? >> The data and the application? I don't know that they're going to be further broken apart, but I think we'll see more kind of intelligent scheduling and combinations of those things, like there are cases where the data needs to be king, and the application needs to come to the data, and vice versa, and historically, the data world and the app world have been pretty separate, right, and you know, again, if we think teams are going to run their things, then just like they're doing ops and dev, they're going to have to do apps and data, right, and so, there's an opportunity there to bring those worlds closer. I see some of it, but, you know, Kubernetes as an example, as a common operational platform for both kinds of systems, but there's more, for sure. >> So bring it together when it makes the most amount of sense, keep it separate when other people need to use the data. >> Stop assuming you have specialists in every technology, and assume you have a multi-disciplinary team that has to run it all. >> All right, Jason, one more question. February, San Francisco, IBM takes it over with IBM Think. A lot of users, a lot of new questions being raised, a lot of opportunity for learning, a lot of opportunity for networking. What are you hoping to accomplish? What conversations do you want to have at Think? >> Yeah, I'm really excited, I think, to have conversations with clients about how they're actually adapting to this new world. I think sometimes the biggest challenge is not technology, but how organizations assimilate these ideas, and so, I'm excited for the conversations with customers about what problems they're solving, sharing those experiences with each other, and also practitioners. I think we've moved into a world where IT is dominated by the people who actually do the work, by the practitioners, and I really hope to see a lot of them show up at Think in February and share with us what they're doing. >> Jason McGee, IBM Fellow, VP, CTO, Cloud Platform here at IBM. Thanks very much for being on theCUBE. >> Thank you. >> And once again, this is Peter Burris from the Thomas J. Watson Research Center in Yorktown Heights. You've been watching theCUBE. Stay tuned. (techno music)

(digital music) >> From Yorktown Heights, New York It's theCUBE! Covering IBM Cloud Innovation Day. Brought to you by IBM. >> Hi, it's Wikibon's Peter Burris again. We're broadcasting on The Cube from IBM Innovation Day at the Thomas J Watson Research Laboratory in Yorktown Heights, New York. Have a number of great conversations, and we got a great one right now. Rob Thomas, who's the General Manager of IBM Analytics, welcome back to theCUBE. >> Thanks Peter, great to see you. Thanks for coming out here to the woods. >> Oh, well it's not that bad. I actually live not to far from here. Interesting Rob, I was driving up the Taconic Parkway and I realized I hadn't been on it in 40 years, so. >> Is that right? (laugh) >> Very exciting. So Rob let's talk IBM analytics and some of the changes that are taking place. Specifically, how are customers thinking about achieving their AI outcomes. What's that ladder look like? >> Yeah. We call it the AI ladder. Which is basically all the steps that a client has to take to get to get to an AI future, is the best way I would describe it. From how you collect data, to how you organize your data. How you analyze your data, start to put machine learning into motion. How you infuse your data, meaning you can take any insights, infuse it into other applications. Those are the basic building blocks of this laddered AI. 81 percent of clients that start to do something with AI, they realize their first issue is a data issue. They can't find the data, they don't have the data. The AI ladder's about taking care of the data problem so you can focus on where the value is, the AI pieces. >> So, AI is a pretty broad, hairy topic today. What are customers learning about AI? What kind of experience are they gaining? How is it sharpening their thoughts and their pencils, as they think about what kind of outcomes they want to achieve? >> You know, its... For some reason, it's a bit of a mystical topic, but to me AI is actually quite simple. I'd like to say AI is not magic. Some people think it's a magical black box. You just, you know, put a few inputs in, you sit around and magic happens. It's not that, it's real work, it's real computer science. It's about how do I put, you know, how do I build models? Put models into production? Most models, when they go into production, are not that good, so how do I continually train and retrain those models? Then the AI aspect is about how do I bring human features to that? How do I integrate that with natural language, or with speech recognition, or with image recognition. So, when you get under the covers, it's actually not that mystical. It's about basic building blocks that help you start to achieve business outcomes. >> It's got to be very practical, otherwise the business has a hard time ultimately adopting it, but you mentioned a number of different... I especially like the 'add the human features' to it of the natural language. It also suggests that the skill set of AI starts to evolve as companies mature up this ladder. How is that starting to change? >> That's still one of the biggest gaps, I would say. Skill sets around the modern languages of data science that lead to AI: Python, AR, Scala, as an example of a few. That's still a bit of a gap. Our focus has been how do we make tools that anybody can use. So if you've grown up doing SPSS or SaaS, something like that, how do you adopt those skills for the open world of data science? That can make a big difference. On the human features point, we've actually built applications to try to make that piece easy. Great example is with Royal Bank of Scotland where we've created a solution called Watson Assistant which is basically how do we arm their call center representatives to be much more intelligent and engaging with clients, predicting what clients may do. Those types of applications package up the human features and the components I talked about, makes it really easy to get AI into production. >> Now many years ago, the genius Turing, noted the notion of the Turing machine where you couldn't tell the difference between the human and a machine from an engagement standpoint. We're actually starting to see that happen in some important ways. You mentioned the call center. >> Yep. >> How are technologies and agency coming together? By that I mean, the rate at which businesses are actually applying AI to act as an agent for them in front of customers? >> I think it's slow. What I encourage clients to do is, you have to do a massive number of experiments. So don't talk to me about the one or two AI projects you're doing, I'm thinking like hundreds. I was with a bank last week in Japan, and they're comment was in the last year they've done a hundred different AI projects. These are not one year long projects with hundreds of people. It's like, let's do a bunch of small experiments. You have to be comfortable that probably half of your experiments are going to fail, that's okay. The goal is how do you increase your win rate. Do you learn from the ones that work, and from the ones that don't work, so that you can apply those. This is all, to me at this stage, is about experimentation. Any enterprise right now, has to be thinking in terms of hundreds of experiments, not one, not two or 'Hey, should we do that project?' Think in terms of hundreds of experiments. You're going to learn a lot when you do that. >> But as you said earlier, AI is not magic and it's grounded in something, and it's increasingly obvious that it's grounded in analytics. So what is the relationship between AI analytics, and what types of analytics are capable of creating value independent of AI? >> So if you think about how I kind of decomposed AI, talked about human features, I talked about, it kind of starts with a model, you train the model. The model is only as good as the data that you feed it. So, that assumes that one, that your data's not locked into a bunch of different silos. It assumes that your data is actually governed. You have a data catalog or that type of capability. If you have those basics in place, once you have a single instantiation of your data, it becomes very easy to train models, and you can find that the more that you feed it, the better the model's going to get, the better your business outcomes are going to get. That's our whole strategy around IBM Cloud Private for Data. Basically, one environment, a console for all your data, build a model here, train it in all your data, no matter where it is, it's pretty powerful. >> Let me pick up on that where it is, 'cause it's becoming increasingly obvious, at least to us and our clients, that the world is not going to move all the data over to a central location. The data is going to be increasingly distributed closer to the sources, closer to where the action is. How does AI and that notion of increasing distributed data going to work together for clients. >> So we've just released what's called IBM Data Virtualization this month, and it is a leapfrog in terms of data virtualization technology. So the idea is leave your data where ever it is, it could be in a data center, it could be on a different data center, it could be on an automobile if you're an automobile manufacturer. We can federate data from anywhere, take advantage of processing power on the edge. So we're breaking down that problem. Which is, the initial analytics problem was before I do this I've got to bring all my data to one place. It's not a good use of money. It's a lot of time and it's a lot of money. So we're saying leave your data where it is, we will virtualize your data from wherever it may be. >> That's really cool. What was it called again? >> IBM Data Virtualization and it's part of IBM Cloud Private for Data. It's a feature in that. >> Excellent, so one last question Rob. February's coming up, IBM Think San Francisco thirty plus thousand people, what kind of conversations do you anticipate having with you customers, your partners, as they try to learn, experiment, take away actions that they can take to achieve their outcomes? >> I want to have this AI experimentation discussion. I will be encouraging every client, let's talk about hundreds of experiments not 5. Let's talk about what we can get started on now. Technology's incredibly cheap to get started and do something, and it's all about rate and pace, and trying a bunch of things. That's what I'm going to be encouraging. The clients that you're going to see on stage there are the ones that have adopted this mentality in the last year and they've got some great successes to show. >> Rob Thomas, general manager IBM Analytics, thanks again for being on theCUBE. >> Thanks Peter. >> Once again this is Peter Buriss of Wikibon, from IBM Innovation Day, Thomas J Watson Research Center. We'll be back in a moment. (techno beat)