>> 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)

(upbeat digital music) >> Hi, welcome to a CUBE conversation with Wikibon. I'm Peter Burris, the chief research officer of Wikibon and our goal with these CUBE conversations is try to bring you some of the finest minds in the technology industry to try to talk about some of the most pressing problems facing digital businesses as they transform in an increasingly chaotic world. We're very lucky today to have a couple of great thinkers, both from IBM. Ed Walsh is the general manager of storage at IBM and Eric Herzog runs product management for the storage group at IBM. Welcome to the CUBE conversation today. >> It's always nice, thank you for having us. >> So, guys you've been running around Silicon Valley today telling your story, we've got a couple of questions. Wikibon likes to talk about the relationship between data and digital business. A lot of people will wonder what digital business is. We say that the difference between digital business and business is how do you use your data assets. Now, that's a stance that I think is becoming a little bit more vogue in the market place today, but that means that storage has a slightly different role to play when we think about how we protect, secure, sustain those data assets. Do you subscribe to this? Is that how you're looking at it? And is that relevant to the conversation that you're having with customers? >> I haven't heard of that way, but it actually makes a lot of sense and you can jump in as well Eric, but I would say, however you look at your data, if a digital business is leveraging their data it makes a lot of sense. We use different, I would say metaphors, one would be your data assets are your oil, he who refines it gets value, so if you get insights from it. So, if you're not using that, you are kind of putting yourself at a disadvantage. We also see a lot of what I'll say is established companies getting disrupted by you know, true disrupters using the technology and insights of data to disrupt incumbency. You know, we'll call the Uber of my business, it's almost like a verb these days, is disrupting me, they're using technology against me, so, the key thing, the best defense is actually using technology, getting insights and then driving new business. But data alone, you need the right infrastructure, either on prem or in the cloud and put the right analytics and insight to it. So, I would agree completely and I would also say, you know, well, think about it, eighty per cent of data is behind your data, you know, it's not searchable by the web, it's how to leverage your data assets in combination with other things to get true insights. Outside data, different things on AI and really get true insights then map them into your business. So, I would agree with that, I haven't heard that way but I would agree with that, it's a good definition of digital business. >> Well, what we're seeing is for companies that are really leveraging the data, it's their life blood and the issue is data is not small anymore, it's oceans of data. Whether that be things from the Internet of Things, grabbing things, for example, all the tell-cos have sensors all over all of their assets and they're trying to keep the tell-co up and going. And it doesn't just have to be a giant tell-co, small companies have reams and reams of data, it's an ocean and if they're not mining that ocean, if they're not swimming through that ocean correctly, the next thing you know, the competitor disrupts them and that is their power, it's the ability to harness these oceans of data and use that data in a way that allows them to get competitive advantage. So, people thing of storage as just a way to sort of place your data but storage can be an active part of how you increase the value of that data and gain insights as Ed was pointing out. >> Well, I think, well we totally agree with you by the way, I think it's an important point. In fact, the observation that we've made is the difference between data as fuel, or the reason why it sometimes falls down, or the way I understand it, I don't think it's a decent enough metaphor, is that unlike fuel, data can be reused multiple times. >> Ed: Good point. >> And it makes the whole point that you're bringing up Eric, about the idea that you combine insights from a lot of different places with your data and storage has to play an active role in that process. But it also says something about, the idea of storage as kind of something you put over there, it's standalone, I mean, it used to be we worried about systems integration a lot, now, open systems kind of changed that, we just presumed that it was all going to come together. Now, IBM has been around for a long time and has lived in both worlds. What do you think the role of systems integration is going to be as we think about storage, the need to do a better job at protecting and sustaining our data assets, especially given the speed and uncertainty with which the world is changing and the dependency it has on data these days. >> Ed: You want to take that first? >> Well, let me give you a real time example. One of the things IBM just introduced last week, was a very powerful new mainframe, one of the key tenants of that mainframe, is the ability to secure data end to end, from the day the transaction starts, with no impacts, so, while they're doing transactions, millions and billions of transactions on the server farm, it's encrypted from day one but it eventually ends up on storage and storage has to extend that encryption, so that when you put the data at rest while you're analyzing the data, you've got it encrypted, when you're putting it at rest, it's encrypted, when you pull it back because you've run analytics multiple times, the data is encrypted. Eventually, certain data sets, like take finance, healthcare, does end up on archive. But guess what, it still needs to be encrypted. So, that's an example of how the complete systems integration, from the server, through to primary storage, through the archive, is just one example of how storage plays a critical role in extending everything across this entire matrix of systems integration, not just one point thing, but across an integrated solution and of course in this case, it's secure transactions, it's analysis of incredible amounts of insight and of course with the IBM Z mainframe, is incredible power and speed, yet at the same time, keeping that data safe, while it's doing all the analytics. So, that's a very strong story, but that's just one example of how storage plays a critical role in this complete integration of data, with a full systems infrastructure. >> And maybe I could add to that. So, that's a good example of on prem that also can be hosted in the cloud, but if you think of system integration, you're data is critical, you need access to it to actually do the analytic workload, the cognitive workloads on top of it. It can be on prem or in the cloud or actually split between, so, you do need to know you're relying on your cloud infrastructure to give you that enterprise class, not only performance but availability. But it also matters, but it's no longer you as an individual company putting that together. But it does matter, the infrastructure does matter how they get that performance. Also, you mentioned security and protection, which is where IBM's cloud comes in. >> Well, it's interesting to us that, it's almost natural to expect that the proper cloud companies are going to do deep integration. I mean their talking about going all the way down to FPGAs. As long as they are able to handle or provide, you know, a set of interfaces that are natural and reasonable from an overall workload standpoint. I would expect that we'd see the same type of thing happen in a lot of different on premise systems too. So, the notion of integration, I think you guys agree, is an important trend where it's appropriate and where it's adding value and should not be discounted just because it doesn't comply with some definition of open this, that or the other thing as it has in the past. >> Oh, agreed, yeah, in end systems, especially when you're looking at availability, performance, which you're talking about your asset as being your data and getting insights. If it's just sitting there, it's not very valuable, in fact you could say it's actually exposure, but if you're leveraging it, getting insights and driving your business, it's very valuable, right. So, you just need to make sure the infrastructure has either hyper cloud or in the cloud that allows you to do that, right. But security is becoming more and more a big issue. So, I would agree. >> Well, that raises the next question, so, again, as long as we're focused on the data as the asset and not the underlying hardware as the asset then I think we're in good shape. But it does raise the next question. As we think about converged infrastructure and hyper converge infrastructure and storage, compute, network and other elements coming together successfully, what will be the role of storage in the future? I mean, storage is not just that thing that sits over in there with the data on it. It is playing a much more active role in encryption, in compression, in duplication, in how it prepares data to be used by any number of different applications. How do you foresee the role of storage evolving over the next few years? >> I'm sure I can jump in, do you want to take a shot? >> Well, yeah, I think one of the key things you've got to realize is the role of storage is to sort of offload somethings from the primary CPU. So, for example, if you've got oceans of data, what if we can track all that metadata for you, so when the system or the cloud looked for data, it could search everything whether that was 20 million lung cancer pictures, whether that be MRI, whether that be the old style X-ray. Go back 20 years, if all that metadata is attached then the CPU from a server perspective to run the analytics workloads is offloaded and the storage is performing a valuable function of tracking all of that metadata, so that when the server does its analytics and then has to reiterate several times for example, Watson, IBM Watson, is a very intuitive element that analyzes, learns, analyzes, learns, analyzes and keeps going to get, and it's used in oncology, Watson is used in financial services and so if you could offload that metadata analysis to the storage where it's actually acting almost as if it's a sub compute element and handling that offloading the CPU, then more time is spent with Watson, looking at the financial data, looking at that medical data and storage can become a very valuable resource in this future world of this intense data analytics, the machine learning, the artificial intelligence, that systems are going to provide on premises through a cloud infrastructure storage. That's just one example how storage as an intelligent storage vehicle is offloading things from the CPU or from the cloud onto the storage and helping it become more productive and the data be more valuable that much faster. >> I would agree and I think storage has always been evolving, right. So, storage has gravity, it has value. If you think of storage as where you store data, it's going to change architecturally. You mentioned a hyper converge, you mentioned converge, you mentioned cloud, we talked about what we can do with the mainframe, it's all about how do you get the right accessibility and performance, but it will change. It will change rather dramatically, just think of what's going to go on with, we'll say the traditional, modernizing traditional workload, what you do with VMware, and the arrays are getting much more complex, you can also do software defined arrays which allows you to have just more flexibility and deployment but in the new workloads, where you're looking at high performance data analytics or doing things that you can actually expand out and leverage the cloud, that becomes much more of a software only play, it's still storage. The bits and bytes might be on, it's going to be typically on Flash in my opinion, both on prem or off prem, but how do you move that data? How do you keep accessibility? How do you secure that data? So, how do you make sure you have it in the right place where you can actually get the right performance? And that's where storage is always going to evolve. So, it doesn't matter if it's in this array, in a file system, in what we call a big storage ray, or it's in the cloud, it's about how do you monitor it and manage that through its full life cycle. >> So, it sounds like you're suggesting, and again, I think we agree, is that storage used to be the place where you put stuff, and it's becoming increasingly where you run data related services. Whether those services are associated with security or prepping data or protecting data or moving data as effectively as possible, increasingly the storage resources are becoming the mechanism by which we are handling these strategic data services, is that right? >> Yeah, so, think of it this way, in the old model, storage was somewhat passive, it's a place where you store the data, in the new world model, storage is actually active, it's active in moving the data, in helping analyzing the data like for example in that metadata example I just gave, so, storage is not a passive device any more. Storage is an active element of the entire analytic, machine learning, artificial intelligence process, so you can get real insights. If you just relied on the CPU to do that, not going to happen, so the storage is now an active participant in this end to end solution that extends from on premise into the cloud, as you guys have called it, the true private cloud, >> Right. >> Right, from Wikibon. The storage is active in that versus being just a passive tool, now it's very active and the intelligence, and some of the things we've done with cognitive storage at the IBM site allows the data, like our spectrum scale product, which is heavily involved in giant, hundreds of petabyte analytic workloads today in production in major enterprises across the globe as well as in high performance computer environments, extend from on premise onto cloud, but that storage is active not passive as it was in the old days. >> So, you mentioned cloud, so, we're pretty strong believers in this notion of true private cloud, which is the idea that instead of thinking ultimately about, in the industry that the architecture is going to remove all the data to the cloud, that increasingly, it's going to be moved cloud services down to the data and do things differently and that seems to be, people seem to be, that seems to be resonating with folks. The question that I have then is, when we think about that, where is the data going to be located, that's going to have a major effect on where the workloads actually run? I've had three conversations with three different CIOs in the last six weeks, and they all said, I'm thinking differently and instead of thinking about moving data up to the cloud, I'm now thinking about how do I ensure that I always have control over my data, even if it's running in the cloud because I'm afraid that if I move everything into the cloud, when I do have to bring it back, it's going to be such a huge capital expense, that everybody is going to say no and I can't do it. So, it's almost like, maybe I'll do some stuff in the cloud, but I'll do backup, restore, or have protection on site. What do you think the role of storage is going to be as we think about multi-cloud and being able to do end to end, developing and putting various applications in various places. >> So, you brought up a couple of topics there right, so, your concept and your research on true private cloud actually, I find resonates amazingly well with clients. In fact, a lot of clients are trying to figure out how to leverage cloud, if they have a lot of data on premises and they want to leverage that, so, the way I explain to clients, everyone wants to do everything they can do in the public cloud, all the agility, all the consumption model, all the dev ops models and they just want to do that on premises, so, it's really an agility statement, but then extend to have the right workloads working the right hyper cloud on their demand. But that brings a whole bunch of things. So, the best use case, and now I'll get into the multi-cloud but, the one use case that all of these companies, why did you end up going to Amazon or what not, and then what it gets down to, developers. Developers were able to swipe a credit card or whatever, put their credentials in, swipe a credit card, do one line of code, spin up an environment, one line of code, spin down an environment or they'd boot Chef and Puppet and that would do the API calls, but they are able to do things very quickly. Try that in the enterprise. I mean literally, they would have to go, do a ticket, talk to Joe IT, which they don't want to do, it takes a lot of time, it takes best case about a week, four to five days, and worse case up to three weeks to provision that environment. If you're doing agile development, it literally breaks the process of doing anything agile. So, you're not going to do it, you're forced, you're absolutely forced to go away. So, what we're doing is, we're doing an investment on prem to do exactly, bring the agility, for example, the idea of a swipe our credit card, we have a process, oh, sorry, a software product across, it's an API automation layer, across all of our storage, that gives you the last mile. How do you literally give API templates to your developers that they can literally one line of code, spin it up, one line of code, spin it down, and that works across all our storage devices? But it took investment, and another layer in API automation that the storage team sets up tablets enabled to hey, gold, silver, bronze, provision your own storage, but in the enterprise way, or like a developer, or a gold DBA, hey spin up an environment for a test dev, but what we're able to do is a simple line of code will spin up a system, which could be, let's say, four, five servers, last good snapshot from production that's been data masked the way you need to do it. 'Cause you don't just give developers the whole database. But then literally, that becomes a template that with roll base access again credentials, the developer or Chef or Puppet natively can literally, one line of code, spin up an environment, and one line of code, spin it down. The benefit is, on premises you actually have your data. So, unlike on the, in Amazon, you're spinning things up, spinning things down but it's not really running on what your production data looks like, you're literally able to keep that up to the last night's data or the weekend before, but again with all the data masking. But you can literally show, so, our investment thesis is we need to work on the next level of automation to allow people to truly do everything they can do in the public cloud on private and we're making a lot of investment to do that. So, it's actually one of our biggest investment thesis and it really plays out well as far as clientele. You mentioned the next thing, and you can jump in on both of these, but you also mentioned the next thing is, well, now, a true private cloud allows you to easily extend to these different clouds, well, then how do you keep track of where that is? How do you have, each one of the different clouds will have their own SLAs but how do you manage it? How do you think through security? How do you know you're getting the right SLAs? And where do you put the right things for the right places? And there's management stacks that do that, with software defined storage which all of our products allow you to do, we can run an extension of your device in any of the major public clouds and manage that securely. And I can add a couple more but do you want to jump in. >> Yeah. I think the key thing here is you've got to be able, in a true private cloud, the enterprise is mimicking what an Amazon or IBM cloud division does, right? Except they're doing it in their own walls, on their own premises, now that maybe spread across the world if it's a global enterprise, but it's v will, it's there version of IBM cloud. But they want to be able to burst out. So, all of our software defined storage and even our array storage is designed so that, if they need to move data from on premise to IBM cloud, from on premise to Azure, from on premise to Amazon, they can transparently move that data. In fact, we can set up that they can automatically tier the data, when the data gets cold, boom, they dump it off to IBM cloud. Now, with the data that's in the private cloud on premises if you will, but, a private cloud that they configure, is there for them to use and they take their access out for those, and by the way, talking to the chief security officer and the chief legal officer, they figure out what work loads is it okay to put out there in IBM cloud. And that way they have total control but they have the flexibility of going out to the cloud all done with the storage in an automated fashion. I think the key thing from a true private cloud perspective is storage as well as network and server infrastructure, they want it to be as automated as possible. They had the big town turn at 2008, yes, IT spend is back up, head count is back up, but when you look inside the envelope of head count, there aren't forty storage guys at XYZ Global Enterprise, there is twenty, they are now hired forty people, so, they got forty people back, but the other twenty went to test and dev. They are not doing storage now. So, those twenty guys need to be fully automated to support all these extra developers in a global enterprise and even smaller counts now need that, so the true private cloud, mimics IBM cloud, mimics Azure, mimics Amazon and all those public cloud providers will tell you, they make their business by making sure it's automated, although why is it so, they won't make any money. So, the private cloud does the same thing. >> And those twenty guys are now, as you said earlier, managing oceans of data where the business has no specific visibility in how that data is going to create value in the future. It's an extremely complex arena. So, with that in mind, you guys have been invited to speak to the board of directors of one of the large enterprise clients about the value that storage will play in a digital business, what are some of the things that you tell them? >> So, let me take that one first. >> Sure. >> I think a couple of things. First of all, storage is not passive the way it used to be, you need to think of it as an active element in your cloud strategy to keep your data whole, to keep your data secure and most importantly, to make sure your data offers value. So, for example, you need to use All Flash, why? Well, because it needs to be instantaneous. It needs to connect right into that CPU as fast as possible to suck the data in so you can analyze it and the guys who analyze the data faster, for example, in dark trading and financials, if you're slower, you lose ten million dollars, or a hundred million dollars, so storage is critical in that, so you want to A, let the board of directors know that storage is a critical component, because it's not just passive, you know, like we said before, it's active. So, storage is an intelligence not dumb and people view storage historically as dumb, so, storage is active, storage is intelligent, storage is a critical element of your infrastructure, both in your private club, but also, for what you do to cut costs, when you do go to public club for certain workloads, and so you need to view storage as a more holistic part of how you handle your data, how you harvest the values of the oceans, okay, if you're going to be fishing, you better make sure you get a lot of fish, if you're going to feed the populous, and the more you do, I think of course, you've got to be all that you protected, and you want to be able to secure everything, you can't do that if storage is just dumb and passive. So, the board of directors, they need to see as data is your life blood, data is your gold, you have to mine that data and storage helps you do that. It's not just a place you stick it. It's not a vault to stick the gold in later. It's helping you mine the gold, refine the gold, get the value out of that gold. How do you do 24 karat versus 18 or versus 14? What do you charge for that? Storage can actually help you do all that analysis. Because it's an active element. >> Peter: What would you say Ed? >> I would agree with everything you said and I would actually play it back to how you started this conversation, which is, you know, that digital business is he who uses his data right. So, I'd probably start there and I used the classic metaphor of your data is oil and he who refines it gets the value of it and I agree it's not a perfect metaphor but it's really about getting insight and leveraging that insight and that does translate to a couple of things, right, so, it does matter that you have it secure but it also matters that you have the right performance either on premises or in the cloud and get the right insights. Typically, the right insights is leveraging the data behind your firewall, which is your proprietary data, which is eighty per cent of data in the world is just not available to a public search engine, it's behind the firewall, and by the way, when you're looking at your business, you might want to combine it with different things, like we talk a lot about our Watson, our ability to do, you know, let's say, your in healthcare and then you could bring up oncology, so, Watson and oncology can help you with your data, or the weather channel, we can bring the weather into a lot of different applications. So, you want to leverage other data sets that are publicly available, but also your private data scenarios and get unique insights to it and you want to work with someone that those insights are actually yours, which is really where IBM differentiates their cloud from everything else, so, you want to bring in AI or cognitive, but we actually have cognitive based upon industry, we've actually trained, the thing between cognitive and AI is actually you have to train cognitive, it actually has to learn. But once it learns, it's able to give you very interesting, you know, insights to your data. We do it by industry, which is a very compelling way to deal with data, and the other thing is, you want to protect your data, either on prem, it's not only protection as far as, if you have a failure or you come back up and running, so, recovery, resiliency, but as much also in security, so, you need to secure it throughout. And then the other thing I'd kind of highlight is, more compliance and everyone doesn't want to talk about compliance but the price of compliance is nothing compared to the price of if you get audited and you have to get compliance back, and prove that, just do it right from day one, and you need to be looking data that you're doing on premises or in the cloud, especially multi-cloud, you need to keep compliance and ownership of the data, because it is a high regulated environment and you're seeing new things coming out in Europe. >> Peter: Absolutely. >> You really need to be on top of it, because the cost of that compliance, it might seem, jeez, that seems like a lot, but it's nothing compared to if you, after a law suit or something, you have to come back from it. That's what I would normally talk to a board about. >> So, Ed, you been back at IBM or at IBM now for a while, it's about a year. >> Sure, yeah. >> About five quarters or so, something like that? >> Four quarters. >> Four quarters. And you've had a chance to look at the assets that IBM has. Now, IBM has obviously been a leader in the tech industry and is going to remain so for a long time. But what will IBM be as a leader in the storage industry? What does leadership mean to IBM? It's kind of the one IBM specific question I'm asking but I think it's important, what is IBM leadership going to be in storage? >> So I think, and maybe it gets to the hypothesis of why I came to IBM, you know, to be honest I think IBM helps people get from where they are to where they want to get to and it helps them do that in what I'll say is risk reduced steps. But very few companies have the breadth of portfolio or capabilities like what we have in cloud and cognitive than IBM. I also think storage as an industry, is going through a major change. It might be the next era is about data, but as far as the storage industry, it's in a lot of changes, so, I think it's a, I use the term big boy game, because it's not about doing the next array which we do, it's as much applying the right analytics and understanding the true flow of data and the right security to do it effectively. When I looked at coming to IBM, I kind of did four things. I think it does play to where our vision is, right. I actually think it is changing and our clients are being disrupted and they are looking for a partner to help them. And it's not just disruption of technology or consolidation or price pressures, but they're being disrupted by these, you know, the Uber of my business is XYZ, it's a verb, so, I keep on saying that, but clients in every industry getting disrupted, so, if they're hesitant, if they are on their heels, they're not able to lean in and technology is the worst thing they could do. So, what they need is a partner that knows, and kind of has the right vision and capabilities to lean forward and with confidence, move forward. IBM has a history of going era to era with clients, that's the first thing, and we calmly do it and clients trust that we know where we're going. And that's a lot to do with our primary research, looking out there. Second thing, I think we have the right vision, the cloud and cognitive vision, no one argues with me, how do you get the insight to your data and that matters. You're definition of a digital business is right on. He who uses their data to their advantage is really a digital business, and is at an advantage by that. Three, it's broad portfolio, so, storage with the broadest portfolio in the industry, and you need that because as we help clients, it's not helping them with the next storage array, it's helping them, here's your business, and it's different for everyone, here's where you want to go to as far as your infrastructure and transformation and I help you get there over time. That takes a broad portfolio, not only in storage, but also overall, the right services, the right software. Analytics becomes a big thing, we're the number one company in analytics and that comes to bear for all our clients, but also have the right services, capabilities going forward. And then, I actually think where IBM storage allows you to lean in is really the biggest thing. We're going to help you simplify so you can lean in, with confidence, because that's what everyone is looking for. A partner to allow you to get there. And very few companies are positioned as well as IBM storage to do that. And I know I'm taking credit for a lot of IBM pieces, but that's a strength, because that's leverage of using an overall company to help you industry by industry, with industry vertical knowledge, really help you lean in, with confidence, so you can grow your business and transform. >> Well, let me build on that, because, at the end of the day, your ability to make these kind of commitments to your customers is a function of your ability to make these commitments to IBM and other IBMers history of keeping the commitments that they make to each other. So, IBM as a culture, and I've been around for a long time, worked with a lot of clients with these things, up and down, good and bad at a product level, but your absolutely right, IBM has a track record of saying here's where we're going, if you want to come with us, we're going to get you there and during periods of significant disruption, that's not a bad type of partner to have. >> I'd use the term people kind of say sometimes it's trust. They trust us to get there, and I think their trust is well placed, again I came from the outside a year ago. We're the last company with primary research, right, and so you have to say, where is it going. We actually do primary research to, there's a reason we've been able to go era to era as a company for a hundred plus years, it's because we actually do that and allow people to go era to era. I know we, sometimes IBM downplays it, I actually think it's a strength. >> Well, the Watson Research Center in many respects is creating the new eras and has for many years and is doing so today too. >> Help clients through those eras without leaving you behind, which is something that's rare, you don't see it, our competitors don't have that and I think that's a big thing. >> Alright, so I'm going to close it here. Ed Walsh, GM of storage at IBM. Eric Herzog, runs product marketing for the storage group at IBM, I want to thank you very much for being part of this CUBE conversation. >> Yeah, thank you. >> As we try to bring the experts that matter and they're going to have a consequential impact on how the industry evolves. Thank you very much for joining us for this Wikibon CUBE conversation. I'm Peter Burris, until we talk again. (upbeat digital music)

>> Narrator: Live from Nice, France. It's theCUBE covering .NEXT conference 2017 Europe brought to you by Nutanix. Hi, I'm Stu Miniman and this is theCUBE's coverage of Nutanix .NEXT. So there's a lot of executives from Nutanix we've had on the program many times. People who've been in job for quite a long time. So Lou Attanasio is the Chief Revenue Officer of Nutanix, and might hold the record for the shortest time in a new job before coming on theCUBE. I love it. Lou, it's like less than a week, right? It's less, five days. Five days? This is the fifth day. All right, so thank you so much for joining us. >> Lou: Nah, it's my pleasure, actually. So for our audience, give us a little bit about your background-- Sure. What brought you to Nutanix? That's a good question. The new IPO company. So I've been in the IT industry quite a long time. To give you a little history, started out actually at IBM, at their Watson Research Center in Yorktown Heights. I had a great span. I was everything from research to a systems engineer to, in sales for a long time. Had many positions, and was there for 38 years at IBM. It was a good run. My last job at IBM was the GM for their cloud software business, and I also had mainframe software reporting to me, and it was a great team. Then, you know, it was time. There was some things that, you always want to see how you could do outside IBM, outside the mothership. I still have blue in my blood, but I went to another company,, an enterprise cloud data management company, Informatica, and had an incredibly good run there. Quite frankly, I wasn't looking for a job. You can probably tell, I'm not a job hopper, and an opportunity came about. And I'll answer your second, why Nutanix. Someone reached and said, hey, a CEO of an incredible company wants to just have a conversation with you. Frankly, I said no, (Stu laughs) and I have to be real honest with you, Dheeraj was pretty persistent, and we had a meeting. It was on a Sunday, and we spent four hours together. There was something very interesting about that meeting and it really kind of got my head spinned a little bit. In the four hours, we spent probably about two and half hours talking about family, but it wasn't just biological family. He talked about his team and the employees as his family, and then, that wasn't enough, then he talked about his clients and how they were family, and once I started realizing that, that's the kind of company that I was used to, that really cared about its people, that great products don't make great companies, great people make great companies. It was instantaneous, I realized that this is a company that was pretty special. Dheeraj was very special, and that's the reason why I came. Yeah, I think back to Dheerj's first keynote at the Nutanix show in Miami, the first one. I've been at all five of the Nutanix .NEXT events, and he got up on stage and spent time, I think he called it his constituencies. There's the employees, there's the partners, customers, of course, very important, and then he said, you know, not too distant future I'll have a new constituency, kind of alluding to going public eventually, and of course, we're there. So as Chief Revenue Officer, paint us a picture as to which of these constituencies do you actually interact with and-- It would really be all. Yeah. I mean, listen, the growth path that Nutanix is on right now is incredibly steep. I've been fortunate to have some very large teams and some big responsibilities in the past, and so my job is to do two things. One is obviously continue the growth, but also make sure that the foundation upon which this growth I going is solid. You need a good foundation, you know? So that's where I'm going to be first focusing. I'm not coming in here with any preconceived notion, and I've told my team this, is that, I'm not coming in here and saying, ah, we got to change everything. They're doin' pretty damn good on their own. They don't need me to change things. But what they do need is to make sure that that growth can continue, and that we put infrastructure and things in place to continue to help with that, and that's really what I'm spending time with. So my first week has been listening to the field teams and gettin' to know them and getting them to know me, but also probably the most important is I've been listening to clients, and I've never been part of any company where I've seen more clients who have more passion for the products that Nutanix has. It surprised me, and I shouldn't have been surprised, in what was told to me, but everything that has been told to me has come to fruition. So one of the things that you talk about, change, Nutanix is making some of their own changes themselves with how they're putting together, their expanding the product line, some of the go-to market pieces. Just had a conversation with Sudheesh yesterday, had a conversation with Dheeraj on theCUBE. Talked about how the goal for Nutanix has become an iconic software company. Right. And there's been things out in the financial news talking about, okay, does Nutanix become a software only company? So if, hypothetically that happened, what does that mean from a revenue, margin, growth, sales, I mean, that has a pretty big ripple effect. Yeah but, I would say this, if you look at any of the companies, IBM, if you look at how they've changed from a hardware company to a services company and then a software company and now it's a cognitive company, every company has gone through, and you need to change. Any company that stays in one place for too long will get crushed in the environment that we have. The beautiful thing about this coming into more of a software business is that now we can give our clients choice. Clients don't want us to go in there and say, you must do it this way and you have to do it this way. The fact that we're givin' 'em choice on the hypervisor, on the ability to run on multiple hardware. If a company's already invested in company that already has a different set of hardware, and then all of a sudden we introduce a new hardware, that just puts more burden on them. So I think that the, and, by the way, as you probably know, software has some very good profit margins. Yeah. And I'm not here to tell you what those profit margins are, but history has shown that it's a good thing for a business as a whole, and I think that the strategy that the board and Dheeraj is on, I think it's the absolute right one. All right, Lou, what about scaling sales? Whether the software piece being a piece of it, but how do you look at that from a philosophical standpoint? We're at an international event here. I've been watching Nutanix since it was a couple dozen people, and now it's 2,800 people. How do you look at growing sales direct, indirect, and that piece of the business? Sure, so one of the things that I think is unique here is that all our business goes through partners, so there's no real channel conflict and I think that's a great thing. I mean, I will tell you that I think the team, the growth that they've been on and the amount of reps and technical teams and everyone they've hired over the last couple years, I tell you what, in my first five days here I could tell ya, they've done a really, really good job. My hat's off to the team. Our job is to continue that momentum, and one of the key things is going to be enablement. We got to make sure that the people we bring in here, you know, I have a saying, and I'll continue to use it. It's, average is no longer good enough. We can't be average, not to compete in the marketplace that we're in. So my job is to make sure that we bring in the very best people we can, both on the technical side, on the channel side, on the sales side, the leadership side. And fortunately, what an incredible good base that I have to work off of because a lot of 'em are already here. Yeah. When I think about the slice of money, there's the partners on the technology side, you've got the OEMs, you've got a pretty large ecosystem of software partners helping out here. You've got the channel and you've got Nutanix. How do you balance that? How do you look at growing that and keeping all those various constituencies-- The interesting thing is, for any company and for any ones that I've been part of, the number one reason why anyone loses, the number one reason why you lose is you're not there. So you need to have routes to market. No matter how big of a sales team I have, I'll never be able to have the reach, and more importantly, the relationships that some of these partners have had for some of their clients for years and years and years. So my job and our job is to take advantage of those relationships and to give them the technology to help solve some of their clients' problems. So I think we're well positioned, and I want to use all the different routes to market, no matter where we are in different parts of the world. Some I may use more of in some areas, and also, I don't believe in, you know, we're a US-based company but I don't believe in, oh, well this is the way we're going to do it, and then go out to all the different geographies and say, well this is how we're doin' it. I like to listen, because things that are done in Europe, in EMEA, are going to be very different than what we do in AP, and I really want to make sure that each of those geographies can work the system culturally and business-wise for their geography. I treat my field leaders as CEOs of their own business, and I'll give them the tools that they need to be successful. Yeah, how do you deal with the lumpiness of the business, especially, I think, dealing with certain partners? You kind of got the end of quarter, end of year that comes onto those-- Yeah, well it's interesting. I think most of the lumpiness in most businesses is due to ELAs. ELAs, I always say it's a drug. It's drug that's tough to get off of, because you can have one really big quarter and because you did a couple ELAs and then others. I have to admit, this company is not on a, not been doin' it. Our whole premise is, start small and you can go in and then you can grow. Where other companies, it's, we're going to get you into a big ELA, and then we're going to trap you into that ELA. You'll never be able to get out of it because the penalties will be so high. And then you have a customer who, frankly, they have your products but they don't really want your products, but they have to have your products. We'd rather have them want our products and grow small and then grow big, so I think right now, any company, by the way, will have some lumps here and there, and we'll get a big deal now and then and sometimes it's tough. But the growth that they're on, I anticipate bein' a little less of that, and my view is, get that steady growth, no lumps. I think that we're positioned to do that. Yeah. Any commentary on kind of, just global economic conditions? How that plays into things? I've had many conversations with Dheeraj about kind of the timing of the IPO and the challenging of it, and he was like, well, we're going to go out, so in the long it doesn't matter really whether it was a down month or quarter. Right. Up, or anything like that. But there's a lot of uncertainty in the world these days, so how does that impact your thinking? Yeah but I, you know what, there's always uncertainty now. I think the interesting part is, we're so well positioned that we can actually, even if economic businesses are down or economy's down, I think that some of the solutions that we have, in some cases provide such great value that they could save money, so I think we're in a much better position even in a down economy. So, listen, I've been in businesses we've done really well when economies are down and when the economy's up. You just got to keep the focus. You can't keep changing strategy every time you hear a news report. If you stay to your goal, you keep pushin' on the goal, you got great leadership, and that's how great businesses are done. Okay, so Lou, want to just give you the final word. Sure. You've been, I think, in learning and listening mode for a lot of it. Anything we should be looking for, that we should be looking differently from Nutanix kind of over the next six to 12 months? I would just say this, the best thing I could say is, you're going to get more of the same. That's great news. More of the same means we're going to continue the growth that we've been on. I think that you're going to see, that comment of average is no longer good enough, we want to make sure that everything that we do, we're the very best at it. I think we have some of the best programmers and development people in the world. I think that we have incredibly good visionaries. We've got people who are backing us, we've got momentum, both on the press, oh, with our customers, probably most important is our customers. And then I also, before I came here I looked at all the commentary that employees have about the company, so all the way around I couldn't be more honored to be part of this team, and I'm proud to be part of it and I hope to add value to the team moving forward. All right, well, Lou Attanasio, in addition to being new to Nutanix, you're now a CUBE alumni too. So thank you so much for joining us. Of course. Look forward to catching up with you again once you've dug in a little bit more. That sounds good, thank you very much. All right, so I'm Stu Miniman. We'll be back with lots more coverage here. You're watching theCUBE. (upbeat music)