>> Live from San Francisco. It's theCUBE covering IBM Think 2019 brought to you by IBM. >> Welcome back everyone, this is the CUBE's live coverage in San Francisco at Moscone Center for IBM Think 2019. I'm John Furrier with Dave. Volante Dave it's been in AI, it's been cloud, it's been in data changing the game. We've got two great guests here Murali Nemani, CMO of ScienceLogic, your CEO has been on the CUBE before and Joe Damassa who is the VP of strategy and offerings for hybrid cloud service at IBM. Thanks for joining us. >> Welcome. >> Appreciate it. >> Thank you guys. >> Welcome to CUBE. So day four of four days coverage, yes, you can see the messaging settling the feedback settling, AI clearly front and center, role of data in that and then cloud scale across multiple capabilities. Obviously on premise multi cloud is existing already. Software's changing all this. >> Right. >> And so AI impacting operations is key. So how do you guys work together? What's the relationships in ScienceLogic and IBM? Could you just take a minute to explain that? >> I think I mean, clearly, as you talked about the hybrid nature of what we're dealing with, with the complexity of it, it's all going to be about the data. You know, software is great, but it's about software that collects the data, analyzes the data, and gives you the insights so you can actually automate and create value for our clients. So it's really this marriage, it's a technology but it's a technology that allows us to get access to the data so we can make change, it's all about the data. >> And so a lot of what IBM has been doing is building the analytics engines and Watson it's for them. Our partnership has been really building the data and the data lake and the real time aspects of collecting and preparing that data so that you can really get interesting outcomes out of it. So when you think about predictive models, when you think about the the way that data can be applied to doing things like anomaly detection that ultimately accelerate and automate operations. That's where the relationship really starts taking hold. >> So you guys are specialized in AIops and IT apparatus as that transforms with scale and data which you need machine running, you need a kind of gave it automation. >> Yes. >> And which is the devops use of operations is don't go down, right, up and running, high availability. >> Yeah. >> So on the cloud services side, talk about where the rubber is meeting the road from a customer standpoint, because the cultural shift from IT Service Management, IT operations has been this manual, some software here and there, but it's been a process. Older processes change a little bit, but this is a new game. Talk about how you guys are engaging the customers. >> Well, a part of it I mean, it's interesting when you step back and you stop breathing, you're on exhaust in terms of pushing what you're trying to sell and you listen to your customers what we're hearing is that they all understand the destination. They understand they're moving to the cloud, they understand the value that's going to bring, they're having a hard time getting started. It's how do I start the journey ? I've got all of this estate and traditional IT operations capabilities it's kind of move. How do I modernize it? How do I make it so it's portable across different environments. And so when you step back, you know, we basically said, hey, you need the portability of the platform. So what we're doing with Red Hat, what we're doing with IBM, cloud private, it creates that portable containerizing ability to take our existing workloads and start moving them, right. And then the other thing that the clients need are the services. Who's going to help me advise me on what workloads should move, which one shouldn't, most of the staff fails because you move the wrong things. How do you manage that? How do you build it? And then when you're done, and you've got this hybrid complex environment, how do we actually get insights to it and the data I need to operationalize it? How do I do IT apps, when I don't own everything within the four walls of my data set. >> Now, are you guys going to market together? You guys sell each other products, the relationship with ScienceLogic and IBM is it a partnership, is it a joint development? Can you explain a little bit more on how you guys work together? >> Well, we're one of the largest sort of services provider in the industry. So as we bring, our products, our technologies and our capabilities to market, we bring ScienceLogic into those deals, we use ScienceLogic in our services so that we can actually deliver the value to our clients. So it is sort of a co development, co joint partnership plus also our goal to market. >> So you use that as a tool to do discovery and identify the data that's in and the data that we're talking about is everything I need to know about my IT operations, my applications, the dependencies. Maybe you could describe a little bit more. >> Sure if you think about one of the things that Joe was mentioning is, today, the workloads are shifting, you're going from, let's say management performance monitoring and management platforms that you need to evolve from, to incorporate new technologies like containers and microservices and server-less architectures. That's one area of how did the tool sets fundamentally evolve to support the latest technologies that are being deployed? So think about that. Second is, how do you consolidate those set of tools now you're managing? Because you're adopting cloud based technologies or new capabilities, and so get consolidation there. And the third is, these workloads that are now migrating out of your private cloud or private data center into public clouds, right? And then that workload migration, I think it is Forrester level saying, about 20% of the total workloads are currently in some sort of a public cloud environments. So there's a lot of work to do in terms of getting to that tipping point of where workloads are now truly in a multi cloud hybrid cloud. So as IBM accelerates that transition and their core competencies in helping these large enterprises make that transition, you need a common manageable environment, that the common visibility across those workloads. So that's at the heart of what we're pulling, and then the data sets happened to be data sets that are coming either from the application layer, data coming from the log management systems, it could be data coming from a service desk in terms of the kind of CMDB based data sets, and we're building a data lake that ultimately allows you to see across these heterogeneous system. >> It could be service request to get that really touches the business process so you can now start to sort of map the value and how change is going to affect that value, right? >> Yeah, exactly. >> Yeah. >> I mean, what's interesting about ScienceLogic as a partner, it's the breadth of their platform in terms of the different things they can monitor, the depth, the ability to go into containers, and kind of understand what the applications are doing in them and the scale in terms of the types of devices. So when you think about, the types of devices, we're going to have to manage everything from, sensors in an Internet of Things, environment to routers, to sophisticated servers and applications that can be running anywhere, you need the flexibility of the platform that they have in order to be able to deliver that. >> And I think that's a key point when you talking about containers and Kubernetes, we heard your CEO Jeannie remitting mentioned Kubernetes, onstage like, that's great, good time(mumbles) I know no one like Kubernetes now it's mainstream. >> Yeah. >> So this is showing them what's going on the industry which is the on premise decomposition of on premise with cloud private, you guys have. >> Yes. >> Is giving them the ability to use containers to manage their existing stuff and do that work and then have the extension to cloud, public cloud or whatever public cloud. This gives them more mount modern capabilities. So the question is, this change the game we know that but how has it changed AIOps and what does it mean? So I guess the first question is, what is AIOps? And what is this new on premise with cloud private and full public cloud architecture look like in AIOps 2.0? >> So for me, it's a very simple definition. It's really using algorithmic mechanisms, right? Towards automating operations, right? It's a very simple way, simplistic way of looking at it. But ultimately, the end game is to automate operations because you need to move at the pace of business and machine speed. And if you want to go, move in machine speed, you can have, I mean, you can't throw enough humans at this problems, right? Because of the pace of change, the familiarity of the workloads spinning up and sitting down. We have a bank as a customer who turns up containers for every 90 seconds and then turn them down. Just can't keep that in that real time state of change and being able to understand the topological relationships between the application layer and the underlying infrastructure so that you can truly understand the service health because when an application degrades in performance, the biggest issue is a war room's scenario where everyone's saying, it's not me, it's not me and because everyone's green on their front, but it's now how do you get that connective tissue all the way running-- >> Well it's also not only the change, it's also the velocity of data coming off that exhaust or the changes and services is thrown off tons of data that you need machines now I mean, that's kind of the thing. >> Exactly, yeah. And I would add to that, I think part of the definition of AIOps is evolving. We know where we're coming from is more fit for purpose analytics, right? I have this problem, I'm the collect this data, I'm going to put these automations in place too address it. We need to kind of take it data Model approach that says, how do I ingest all of this data? You know, even at the start, when you're looking at which workloads and you're doing discovery and assessment of workloads, that data should go into a data lake that can be used later when you're actually doing the operations and management of those workloads. So what data do we collect at every stage of the migration and the transformation of it, and including the operational data? And then how do we put a form analytics on it, and then get the true insights? I think we're just scratching the surface of applying to AI, because it's all been very narrow cast, narrow focus, I have this problem, I collect this data, I can automate this server, it needs to move much beyond that to it... >> And services are turning up and on and off so fast as a non deterministic angle here, and you got state, non deterministic, I mean, those are hard technical computer science problems to solve >> Yeah. >> That's you don't just put a processor around say, oh, yeah. >> Well, let's back to the the scalability of the platform, the ability in real time to be monitoring and looking at that data and then doing something right. >> All right now, humans aren't completely removed from the equation, right? And so I'm interested in how the humans are digesting and visualizing all this data, especially at this speed there a visualization component? How does that all evolving? >> Yeah, I think that to me I mean, that's part of the biggest challenges. You humans are a, they have to be the ones that kind of analyze what's coming and say, what does this mean when you haven't already algorithmically built it into your automation technology, right? And then they also don't have to be the one to train, the system is doing to actually do it. So one of the things that were are that struggling with not struggling with, we're experimenting with is, how best to visualize this, right? We do some things now, we've got a hybrid cloud management platform, we're teaming with the product guys, and it's the ability to have four consoles. One from a consumption, how do I consume services from Amazon, IBM Cloud on premise, how do I deploy it? So in a Dev apps model, how do I fulfill that very quickly and operational councils, right, and then cost on asset management so you can actually have at glance say, oh, you know, I've got a big Hadoop cluster which been spun up, I'm paying $100,000 for it and it has zero utilization. So how do you visualize that so you can say oh, I'm need to put a rule in that if somebody's spinning something up on, you know, IBM Cloud and they're not using it, I either shut it down, or I sent messages out, right, for governance in top of it. So it's putting business rules and logic in terms, in addition to visualization to help automate. >> And Jeannie talked about this at our keynote efficiency versus innovation around how to manage and this is where the scale comes in. Because if you know that something's working, you want to to double down on it, you can then, kind of automate that away and then you just move someone, the humans to something else. This is where the AIOps I think it's going to be, I think, going to change the category. I mean, it's a Gartner Magic Quadrant for the IT operations. >> Right. >> AI potentially decimates that, I mean... >> Yeah, there's this argument that you know, you have these nice quadrants or let's say nicely defined market segments. You have the NPMD, the ITSM, the ITOM, you know, you have APM and so what's happening is in this world of AIOps, none of those D marks really fit anymore because you're seeing the convergence of that. And then the other transition that's happening is this movement from, you know, classic ops or Dev and a dev to Ops, Dev Ops and now dev sec Ops, you know, you're trying to get worlds to converge. And so when we talk about the data and being able to build data models, those data models need to converge across those domains. So a lot of the work we do is collect data sets from log management, from service desk and service management, from APM etc, and then build that data model in real time. So you can.... >> It kind of building an Uber or CMDB or I mean, right? (loud laughter) I mean, do most of your clients have a single CMDB? Probably not, right? >> Yeah. So this is sort of a new guidepost, isn't it? >> Yeah, a part of it is. There are these data puddles if you will, all right data exist in a lot of different places How do you bring them together so you can federate different data sources, different catalogs into a common platform because if a user is trying to decide, okay, should I spin this up on, you know, this environment or that one, you want the full catalog of capabilities that are on premise in your CMDB system with the legacy environment out of the catalogs that may exist on Amazon or Azure, etc and you want data across all that. >> It seems that everything's a data problem now. And datas are being embedded into the applications which are then the workflows are defining infrastructure, architecture, or are sole cloud, multi cloud, whatever the resource is, so we had JPMorgan Chase on top data geek on and she was talking about, we have models for the models and IBM has been talking about this concept of reasoning around the data. This is why I always like the cognition kind of angle of cognitive, because that's not just math, math is math, you do math on, you know, supervised machine learning and knowing processes to be efficient, but the cognition and the reasoning really helps get at that data set, right. So can you guys react to that? I mean, is everything a data problem? Is that how you should look at it and how does reasoning fit into all this? >> Well, I mean, that's back to your point about what is the humans role in this, right. So we're moving in a services business from primarily labor base with tools to make them more efficient to the technology doing the work. But the humans have to then say, when the technology get stumped, what does that mean? So should I build a new, how do I train it better? How do I, you know, take my domain expertise? How do I do the deep analytics to tell me all right, how do I solve those problems in the future? So the role changes I think Jenny talks about in terms of new collar workers. I mean, these are data scientists, these are people that understand the dynamics of the inner relationship of the different data, the data models that need to get built and they are guiding in effect the automation. >> I thought your CTO was on theCUBE talking about, Paul was talking about, you know, take the heavy and Rob Thomas was also on, the GM of the data plus AI team. I think he really nailed it. If you guys to take away the heavy lifting of the setup work then the data science who're actually there to do the reasoning or help assist in managing what's going on and putting guard rails around whatever business policy is. >> Today, I mean, we talked to in this about 79 percent I think it's a gardener stat of 79 percent of the data scientists. And these are these PhDs, they're highly valuable, spend their time collecting, preparing, cleansing those data models, right? So, you're now really applying that PhD level knowledge base towards solving a problem, you're just trying to make sense of the data. So one, do you have a holistic and a few? Two, is there a way to automate those things so you can then apply the human aspects towards the things that Joe was talking about. So that's a big part of what we're trying to come together in terms of the market for. >> Well guys thanks for the insight, thanks for coming on, great job. I think we talked for you know, an hour and on cultural shift because you mentioned the sets in here Ops and devs. It's a melting pot and it's a cultural shifts. I think that topic is worth following up on. But I'll let you guys just get a quick plug for you. I know you going to an event coming up and you got some work. You can talk about what you guys are doing. You got an event coming up, what your pitch, give a quick flag. >> Yeah, so we've got our symposium, which is our big user conference. It's in April. It's right in, it's on April 22 to 23rd to the 25th. It's in downtown Washington DC, Cherry Blossom festival season at the Ritz Carlton. And so a lot of that, we'll have theCUBE there as well. >> Yeah of course. >> So, we're looking forward to it. A lot of great energy to be carried over. >> We love going to the District. (laughs loudly) >> What don't we say, you guys are great, great to visit. So give the plugs with a service you're doing. Just give an update on what you guys are up to. >> Yeah, I think I mean, we're also we're investing the technology when we're full on board with the containerization, as we talked about, we're putting together a services portfolio. I think Jenny mentioned that we're taking a whole bunch of capability across IBM Global Technology Services, Global Business Services, and really coalescing into about, you know, 23 offerings to help customers advise on cloud, move to cloud build for cloud and manage on cloud and then you've seen the announcements here about what we're doing around the multi cloud management system. Those four console I talked about how do we help, you know, put a gearbox in place to manage the complexity of the hybrid nature that our customers are dealing with. >> It seems IBM got clear visibility on what's happening with cloud, cloud private, I think a really big announcement. I think it's not talked about in the show and I'll always kind of mentioned the key linchpin but you see cloud, multi cloud, hybrid cloud, you got AI and you got partnerships, ecosystem now its execution time, right? >> Yeah, exactly and, and frankly, that's the challenge, right? So we used to be able to manage it all on the four runs, right? Your SAP instances was in the data center, your servers were in the data center, your middleware is in the data center. Now I got my applications running in Salesforce.com often software as a service. I've got three or four different infrastructures of service providers. But I still have the legacy that I got to deal with. I mean the integration problems are just tremendous. >> Chairman VP of strategy at IBM hybrid cloud and Murali Nemani, CMO ScienceLogic, AI operations, bringing in hybrid clouds to theCUBE bringing all the coverage day four. I'm with Dave Volante, it's all about cloud AI developers all happening here in San Francisco this week. Stay with us from this short break. (upbeat music)

>> It's been great. >> Robert Herjavec. >> I mean, you guys are excited where you are, no? >> Dancing with the Stars, of course. >> His CUBE alumni. (techno music) Live from Seattle, Washington, it's theCUBE covering KubeCon and CloudNativeCon North America 2018 brought to you by Red Hat, the Cloud Native Computing Foundation, and its ecosystem partners. (crowd talking) >> And welcome back to our live coverage here in Seattle for KubeCon and CloudNativeCon 2018. I'm John Furrier, Stu Miniman, here for three days of wall to wall coverage, 8,000 people up from 4,000 last year. Growing Kubernetes and the Cloud Native ecosystem around KubeCon. Next two guests, John Morello, CTO of Twistlock, hot start-up to the news. And Nanda Kumar, who's a Fellow Systems engineer at Verizon's Global Technology Service. Guys, welcome to theCUBE. >> Thank you. Thanks for having us. >> Congratulations on your news and Kelsey wearing your shirt on theCUBE earlier. (they laugh) >> Thanks for having us. >> So take a minute to explain what you guys do, your story, you guys got to lot of hot things happening. Take a minute to talk about the company's value-- >> Yeah, sure, so we've been around for about four years now or going on four years. We're kind of the first company in this space that's really focused on cloud native cybersecurity. So, the idea is not just to take the existing capabilities that you've had on traditional systems and kind of retrofit them onto this new platform. But really to leverage the way that the cloud native space works, to be able to do security in a different and hopefully a more effective way. Cloud native has this notion of immutability and being able to take the same artifact from development to staging to production. And that enables us to do things in a security fashion that you really haven't been able to do in the past. Like actually be able to enforce security controls at the very beginning of the life cycle of the app. To be able to ensure consistency in your compliance posture all the way through production. And then as we learn things at runtime, to be able to signal that knowledge back to the developer, so they can actually improve the security application in the beginning. We basically have a platform that gives you those capabilities, vulnerability management, compliance, runtime defense, and firewalling across VMs, containers, and serverless across any clouds you have. We're not specific to any one cloud provider-- >> Is like telemetry coming back to the developer in real time? >> Yeah, basically as an example, when you have an application that's deployed, in the old world you as the developer would give the app to an operator, they would deploy it, and maybe weeks later, somebody would scan it, and they'd say you've got these vulnerabilities and then they have to go back and tell somebody to go and fix them. There's a lot of time where you're exposed, there's a lot of cost with that operation. The way that we're able to do it for the vulnerability case is as the developer builds the application, every build they do, Twistlock can scan that and see the vulnerabilities and actually enforce that as a quality gate and say if you've got critical vulnerabilities, you have to fix 'em before you progress. And then as you take that application and move that into test and staging and production, we create this dynamic runtime model that describes basically an implicit allow list of what's normal behaviors. So you don't have to tell us that my web server normally runs in Gen X and listens on port 80, we learn that automatically. We create this reference model where you can understand what's normal and then we automatically prevent anomalies. So unlike that traditional world of security where you had to have a whole bunch of manual rules that try to blacklist every thing that was bad, (John Furrier laughs) we just say, we learn what's good and only allow that. >> It's predictive and prescriptive in one. >> Yeah, exactly. >> What's the role here with Kubernetes, how do you fit into the Kubernetes standardization, momentum? >> For us, we've kind of pre-dated the rise of Kubernetes in some ways, and really supported Kubernetes from the very beginning when the project became popular. Our platform is designed to work as a native cloud native app itself, so when you deploy Twistlock, you run the Twistlock console, our management service and API controller. All that's run just as a cloud native app. You deploy as a replication controller. When you deploy Twistlock defender, our agent effective error, containerized agents to all the nodes where you're writing compute jobs, you run that as a Damon set. So for us, not only do we protect the platform, but we just are a part of the platform. There's nothing abnormal that you have to do. You deploy it and manage it like you would any other Kubernetes application. >> All right, Nanda, let's pull you into the conversation here. >> Sure. Verizon, obviously most people know, explain what your group does, how cloud native fits into what you're doing. >> I'm part of the Global Technology Services organization. Verizon, as you probably know, is a mixed bag of different types of businesses brought together, wireless being the most prominent one that most of you know about it. But we also have other solutions, like our file solutions. And recently with our acquisition of Yahoo, which is gold, and so forth. Verizon is actually on a major transformation journey. Our transformation journey spans around a five year program. We are in year number three of this transformation and cloud native and cloud technology is a very foundational aspect for us as part of this transformation. I was just chatting with John earlier. Opportunity like this doesn't come that often because we are in a perfect intersection of where automation and Verizon is doing a cloud migration and then you have these cloud native technologies that have been made available. Where it's Kubernetes, container, and so forth. So that mesh of the opportunity to migrate. And as you migrate, you're taking advantage of these technologies, and modernizing your application stack is a big win. >> Okay, can you connect for us the intersection of what you were just talking about and 5G, which is you know, really going to be a huge impact on everything happening in telecommunications. >> Yeah, the whole idea about 5G for us is it's not just the next generation of technology. It's all about the human element ability of it. Basically it means we want to make sure that the technology is used to solve real human problems and the technology is capable of doing that. Be it whether it's a life science or be it in transportation and so forth. We really want to make sure that the technology is being used to solve real human problems and to enable the consumption of this technology. We won't take advantage of cloud native services to support it. >> Help boil it down for us because, just in general, you say even domestically, I think it's like 40% of the U.S. population doesn't have access to broadband. Those of us at the conference here understand that wireless isn't always reliable. 5G silver bullet, everybody's going to have infinite bandwidth everywhere, right? >> Absolutely. (Stu laughs) And that's the valued proposition of the technology that it brings to the table. I know the spread of the technology is going to vary depending upon the commercialization of the product, the solution, and so forth. But the reality is in the new world that we live in, it is not just one piece of technology that's going to make it. It's going to be a mesh of the new technologies like 5G with a combination of WiFi and so forth. All of this coming together. It all comes down to fundamentally what are the use cases or what type of solutions are you going to go after and how it's going to make sense. >> How has cloud native in this transformation changed how you guys make investments? Obviously, the security equation's paramount. Central to the that, lot of data. How is the investments and how you guys are building out changed? Obviously you're looking at re-imagining operations, security, et cetera et cetera. How's that going to shape for you guys-- >> One of the things that Nanda and I were talking about earlier that not because of cloud native but it's enabled by cloud native. I think you look at almost all organizations today, and to reuse that phrase that Andreessen quoted about softwaring the world. It really is a true thing. Unlike in the past where IT had been this cost center that most organizations sought to strangle out and reduce as much as possible, I think most, at least modern companies that will be successful in the future, realize that that's part of their competitive advantage. It's not just about providing an app because your competitor has an app, it's about providing a better experience so that you're driving more revenue, having a better relationship, a longer term deeper relationship with that customer. Like we were talking about, in his case, if they build kind of a minimal application or minimal experience for their customers, their customers may choose to go to AT&T or whomever else if they can feel like hey, it's easier for me to work with them. I get better data, I can use my systems more easily. If you have that inflection point where people are having to really invest in building better software, better industry specific software, you need those tools of mass innovation to do that. And that's what cloud native really is. It's about being able to take and innovate and iterate on those innovations much more rapidly than you've been able to do in the past. And so it's really this confluence of those two trends that make this space as big as it is. That's why we have so many people here at KubeCon. >> Oh, you go faster too. The investment in apps, your applications, faster. And your talking about your security solution replaces the old way of hey, is there a problem, we'll patch it. >> It also has to get away from that approach where people took in the past where security was always this friction. It was this impediment, you know, you wanted to deploy something and you had to go through the security review and create all this rules and it was a hassle and slowed things down. If that's your approach to security, you're going to be at a fundamental conflict to this new approach. >> I think you'll be out of business personally, I think that ship has sailed, that's dead. We see the breaches every day, you see on all the dark webs who've been harvesting all that. IoT though is a different kind of animal. How are you guys looking at the IoT equation because that's a good use case for cloud? You can push now compute to the edge, you don't have to move data around. Certainly you guys are in the telecom business, you know what that means, so latency matters. How are you looking at the edge, IoT, and where does security fit into that? >> In terms of IoT, I think as you mentioned, there are going to be use cases where IoT's going to be very critical. There are two paradigms to the concept of the mobile edge compute. One is for the IoT use cases, the other could be even for like AR/VR is a good example. You want the compute to be so fast where you want responses immediately based on the location you are and so forth. So that's a very important foundation that we're working on and making that a reality for our organization to come use it. And of course any solution that we provide, security needs to be baked into it, because that's going to be foundation for how to-- >> Back to your 5G point, that's great back haul too for those devices. That one at least. If they want to send data back or interface with the edge, and power and compute, you need power and connectivity. >> Yep, exactly, very true. >> What's next, I guess? If you look forward, where's this journey going? How does this partnership help solve things? >> I think the key to any successful transformation is you got to take into consideration your current landscape. You certainly can have a broad vision of where the future is and so forth, but if you can't build the bridge between where we are and where we need to go, that's going to be a very challenging space so when you look at the cloud native technologies, we look at making it operational efficiency for us. In terms of how do we do our operations, like the earlier question we talked about, what is changing for us? Our operation's getting better. Our security portion is getting better because we're now shifting more of this to left. Which means as the workloads are being built and so forth. We're taking into consideration how it's going to run, where it's going to run and so forth. So that's going to create the savings and operational efficiency, which then allows us to take that and transform it into how do we focus on more modern technologies and modern solutions and so forth. >> Customer satisfaction. >> And customer satisfaction. >> Those are the top line business for every new model. >> So I got to ask, how is it going with Twistlock? Where's their role in your transformation? It's on the security side? >> Mm-hmm. >> Where do they play into your mix? >> So when we rolled out our solution for our Kubernetes platform, we certainly want to make sure that, to John's earlier point, where we can shift left and really look at security wholistically. And the only way you could do that is you need to capture the essence or integrate security as the project's being built. Because today we do have a security portion, but it's kind of where you have it during the development phase or during operations or doing it on time. You're not able to stitch it together. But with container and Kubernetes, you now have the advantage of really knowing what is end to end. And that is where our partnership with Twistlock has to be able to oversee that and provide that insight on what is running, where it's running, what levels exist, and how do we fix it. >> It kind of makes sense too. We've talked for years, the perimeter is dead. You guys are addressing security upfront at the application level where it's coding. This is working out for you guys well? >> Yep, and that's been a big shift in fact for why they've been successful with this transformation. Because we know have inside steward and everybody in the organization has a line off-site to what's going on, where things are running and so forth. It's been a great partnership. >> John, talk about this dynamic 'cause this is really kind of compelling because we've heard, "Oh, yeah, we're throwing everything "against the wall in security." And everyone always says, "Hey, the perimeter is dead "and you got to start with security in mind from day one." Well, I mean, what is day one? The minute you start coding, right? >> I get your overall point about the perimeter being dead. I would actually rephrase it a bit and say, "The perimeter being dissolved." And I think that's really a more probably accurate way to look at it. What used to be this very tightly defined like, we deploy things in this network or even VPC and it's got this control around it. Whereas a lot of customers today we see choosing an intentional multi-cloud strategy. They want to preserve the ability to have some leverage, not just with Amazon, but with Azure, or with Google, or whomever it may be on-premises. And when you have that model where you've got infrastructure and multiple regions, multiple different providers, you no longer have that very clean separation between what's yours and what's kind of out on the outside. And so one of the things that we really think is important is to be able to bring the perimeter to the application. So the way that we look at protecting the application is around the app itself, regardless of what the underlying compute platform is, the cloud, the region, it's really about protecting the app. You learn how those different microservices normally communicate with each other. You only allow that normal good communication unless you can really constrain a blast radius if you do have some kind of compromise in the future. And the minute you really try to mitigate that compromise is to again find those vulnerabilities as you develop the app, and prevent them in development before they ever get out to production. >> And that's a super smart approach, I love that. I think it's a winner, congratulations. Final question, what's the prediction for multi-cloud in 2019? Since you brought it up, multi-cloud seems to be the hot thing. What's your prediction 2019? It becomes a conversation? It becomes practice? >> I would say at this point, it already is practice in most organizations. And I would say that in 2019, you'll see that become something that's accepted not just as an option but as really the preferred, the better operational model. So you're able to choose technology platforms and operational approaches that are designed to work in a model in which you have multiple providers. Because you have a dependency layer that you can take now with Kubernetes and containers that's universal across those. Theoretically, you could have always taken a VM you put in ager and moved it to AWS, but it was really difficult and painful and hard to do that. If you do that well with Kubernetes, it's really pretty straightforward to deploy an application across multiple providers or multiple regions of the same provider even. And I think you'll see that become a more real thing in 2019 because it gives you as a company, or you as a customer, more leverage to be able to choose the services and negotiate the rates that you want with your provider. >> And if you move security to the app level like you guys are doing, you take away all that extra work around how to send policy and make it dynamic. >> Exactly. Our customers may have one Twistlock environment that manages things in Azure and AWS and GCP and on-premises and that's fine because we care about protecting the app not the interlying infrastructure. >> You agree? >> Absolutely, I think that's going to be the case even from our perspective. You're always going to look for where is the best place around these workloads and in a cost-effective way and secure manner. And as long as you're a single-controlled plane that you can manage it, I think the multi-cloud is going to be the ideal-- >> Make it easier to operate, standard language for developers, lock in security at the front end. >> That's right. >> Good stuff. Guys thanks for coming out. >> Sure. >> Appreciate the insight. Smart commentary here on security, cloud native, Kubernetes, I'll break it down here on theCUBE. I'm John Furrier, Stu Miniman, stay with us. More day one coverage of three days of live coverage here in Seattle for KubeCon and CloudNativeCon. We'll be right back. (upbeat music)

>> Announcer: Live from Barcelona, Spain it's theCUBE covering Cisco Live 2018. Brought to you by Cisco, Veeam, and theCUBE's ecosystem partners. >> Hello everyone and welcome back. This is theCUBE live here in Barcelona for Cisco Live Europe. I'm John Furrier, the co-host of theCUBE, with Stu Miniman analyst at Wikibon, covering networking storage and all infrastructure cloud. Stu Miniman, Stu. Our next guest is Eric Herzog, who's the Chief Marketing Officer at IBM Storage Systems. Eric, CUBE alumni, he's been on so many times I can't even count. You get the special VIP badge. We're here breaking down all the top stories at Cisco Live in Europe, kicking off 2018. Although it's the European show, not the big show, certainly kicking off the year with a lot of new concepts that aren't necessarily new, but they're innovative. Eric, welcome to theCUBE again. >> Well, thank you. We always love participating in theCUBE. IBM is a strong supporter of theCUBE and all the things you do for us, so thank you very much for having us again. >> A lot of great thought leadership from IBM, really appreciate you guys' support over the years. But now we're in a sea change. IBM had their first quarter of great results, and that will be well-reported on SiliconANGLE, but the sea change is happening. You've been living this generation, you've seen couple cycles in the past. Cisco putting forth a vision of the future, which is pretty right on. They were right on Internet of Things ten years ago, they had it all right, but they're a networking company that's transformed up the stack over the years. Now on the front lines of no perimeter, okay, more security challenges, cloud big whales with no networking and storage. You're in the middle of it. Break it down. Why is Cisco Live so important now than ever before? >> Well, for us it's very important because one, we have a strategic relationship with Cisco, the Storage Division does a product with Cisco called the VersaStack, converged infrastructure, and in fact one of our key constituents for the VersaStack are MSPs and CSPs, which is a key constituent of Cisco, especially with their emphasis on the cloud. Second thing for us is IBM storage has gone heavily cloud. So going heavily cloud with our software, in addition to what we do with our solutions as a foundation for CSPs and MSPs. Just what we've integrated into our software-defined storage for cloud makes Cisco Live an ideal venue for us, and Cisco an ideal partner. >> So I've got to ask you, we've had conversations on theCUBE before, they're all on youtube.com/siliconangle, just search Eric Herzog, you'll find them. But I want to recycle this one point and get your comments and reaction here in Barcelona. You guys have transformed with software at IBM big-time with storage. Okay, you're positioned well for the cloud. What's the most important thing that companies have to do, like IBM and Cisco, to play an innovator role in the cloud game as we have software at the center of the value proposition? >> Well I think the key thing is, when you look at cloud infrastructure, first of all, the cloud's got to run on something. So you need some sort of structural, infrastructure foundation. Servers, networking, and compute. So at IBM and with Cisco, we're positioning ourselves as the ideal rock-solid foundation for the cloud building, if you will. So that's item number one. Item number two, our software in particular can survive, not only on premises, but can bridge and go from on-premise to a public cloud, creating a hybrid infrastructure, and that allows us to also run cloud instantiation. Several of our products are available from IBM Cloud Division, Amazon offers some of the IBM storage software, over three hundred cloud service providers, smaller ones, offer IBM Spectrum Protect as a back-up service. So we've already morphed into storage software, either A, bridging the cloud in a hybrid config, or being used by cloud providers as some of their storage offerings for end-users and businesses. >> Eric, wanted to get to, one of the partnership areas that you've talked about with Cisco is VersaStack. We've talked with you a number of times about converged infrastructure, that partnership, Cisco UCS taking all the virtualization. The buzz in the market, there's a lot of discussion, oh it's hyper-converged, it's cloud. Why is converged infrastructure still relevant today? >> Well, when you look at the analysts that track the numbers, you can see that the overall converged market is growing and hyper-converged is viewed as a subset. When you look at those numbers, this year close to 17 billion US, about 75% of it is still standard converged versus hyper-converged. One of the other differences, it's the right tool for the right job. So customers need to go in eyes open. So when you do a hyper-converged infrastructure, by the way IBM offers a hyper-converged infrastructure currently with Nutanix, so we actually have both, the Nutanix partnership offering hyper-converged and a partnership with Cisco on standard converged. It's really, how do you size the right tool for the right job? And one of the negatives of hyper-converged, very easy to deploy, that's great, but one of the negatives is every time you need more storage, you have to add more server. Every time you need more server, you add more storage. With this traditional converged infrastructure, you can add servers only, or networking only, or storage only. So I think when you're in certain configurations, workloads, and applications, hyper-converged is the right solution, IBM's got a solution. In other situations, particularly as your middle-sized and bigger apps, regular converged is better 'cause you can basically parse and size up or down compute, networking, and the storage independent of each other, whereas in hyper-converged you have to do it at the same time. And that's a negative where you're either over-buying your storage when you don't need it, or you're over-buying your compute when you don't need it. With standard converged, you don't have that issue. You buy what you need when you need it. But I think most big companies, for sure, have certain workloads that are best with hyper-converged, and we've got that, and other workloads that are best with converged, and we have that as well. >> Okay, the other big growth area in storage for the last bunch of years has been flash. IBM's got a strong position in all-flash arrays. What's new there, how are some of the technologies changing? Any impact on the network that we should be really understanding at this show? >> Sure, so couple things. So first of all, we just brought out some very high-density all-flash arrays in Q4. We can put 220 terabytes in two rack U, which is a building block that we use in several different of our all-flash configurations, including our all-flash VersaStack. The other thing we do is we embed software-defined storage on our, software-defined storage actually on our physical all-flash arrays. Most companies don't do that, so they've got an all-flash offering and if they have a software-defined offering it's actually a different piece of software. For us it's the same, so it's easier to deploy, it's easier to train, it's easier to license, it's easier for a reseller to sell if you happen to be using a reseller. And the other thing is it's battle-hardened, because it's not only standalone software, but it's actually on the arrays as well. So from a test infrastructure quality issue, versus other vendors that have certain software that goes on their all-flash array, and then a different set of software for all software-defined. It doesn't make logical sense when you can cover it with one thing. So that's an important difference for us, and a big innovator. I think the last thing you're going to see that does impact networking is the rise of NVMe over fabrics. IBM did a statement of direction last May outlining what we're doing. We did a public demonstration of an InfiniBand fabric at the AI summit in New York in December, and we will be having an announcement around NVMe fabrics on the 20th of February. So stay tuned to hear us then. We'll be launching some more NVMe with fabric infrastructure at that time. >> Eric, I just, people that have been watching, there's been a lot of discussion about NVMe for a number of years, and NVMe over fabric more recently. How big a deal is this for the industry? You've seen many of these waves. Is this transformational or is it, you know, every storage company I talk to is working on this, so how's it going to be differentiated? What should users be looking to be able to, who do they partner with, how do they choose that solution, and when's it going to be ready? >> So first of all, I view it as an evolution, okay. If you take storage in general, arrays, you know we used to do punch cards. I'm old enough I remember using punch cards at the University of California. Then, it all went to tape. And if you look at old Schwarzenegger movies from the 80s, I love Schwarzenegger spy movies, what's there? IBM systems with big IBM tape, and not for back-up, for primary storage. Then in the late-80s, early-90s, IBM and a few other vendors came out with hard drive-based arrays that got hooked up to mainframes and then obviously into minis and to the rise of the LAN. Those have given away to all-flash arrays. From a connectivity perspective, you've had SCSI, you had ultra SCSI, you had ultra fast SCSI, ultra fast wide SCSI. Then you had fiber channel. So now as an infrastructure both in an array, as a connectivity between storage and the CPUs used in an array system, will be NVMe, and then you're going to have NVMe running over fabrics. So I view this as an evolution, right? >> John: What's the driver, performance or flexibility? >> A little bit of both. So from the in-box perspective, inside of an array solution, the major chip manufacturers are putting NVMe to increase the speed from storage going into the CPUs. So that will benefit the performance to the end-user for applications, workloads, and use cases. Then what they've done is Intel has pushed, with all the industry, IBM's a member of the NVMe consortium as well, has pushed using the NVMe protocol over fabrics, which also gives some added performance over fabric networks as well. So you've got it, but again I view this again as evolution, because punch cards, tape was faster, hard drive arrays were faster than tape, then flash arrays are faster, now you're going to have NVMe in the flash array, and also NVMe over fabric with connecting all-flash array. >> So I have to ask you the real question that's on everyone's mind that's out there, because storage is one of those areas that you never see it stopping. There's always venture back start-ups, you see new hot start-ups coming out of the woodwork, and there's been some failures lately and some blame NVMe's innovation to kind of killing some start-ups, I won't name names. But the real issue is the lines that were once blurred are now forming, and there's the wrong side of history and the right side of history. So I've got to ask you, what's going to be the right side of history in the storage architecture that people need to get onto to win in the future? >> So, there's a couple key points. One, all storage infrastructure and storage software needs to interface with cloud infrastructure. Got to be hybrid, if you have a software play like we do, where the software, such as our Spectrum Scale or our Spectrum Protect or Spectrum Protect Plus, can exist as a cloud service through a service rider, that's where you want to be. You don't want to have just a standard array and that's all you sell. So you want to have an array business, you want to make sure that's highly performant, you want to make sure that's the position, and the infrastructure underneath clouds, which means not only very fast, but also incredibly resilient. And that includes both cloud configs and AI. If you're going to do real-time AI, if you're going to do dark trading on Wall Street using AI instead of human beings, A, if the storage isn't really fast you're going to miss a 10 million dollar, hundred million dollar transaction. Second thing, if it's not resilient and always available, you're really in trouble. And god forbid when they bring AI to healthcare, and I mean AI in the operating room, boy if that storage fails when I'm on the table, wow. That's not going to be good. So those are the things you got to integrate with in the future. AI and cloud, whether it's software-defined in the array space, or if you're like IBM in both markets. >> John: Performance and resilient. >> Performance and resiliency is critical. >> All right, so Eric I have a non-storage question for you. >> Eric: Absolutely. >> So you've got the CMO hat for a division of IBM. You've been CMO of a start-up, you've been in this industry for a while. What's the changing role of the CMO in today's digital world? >> So I think the key thing is digital is a critical method of the overall marketing mix. And everything needs to reinforce everything. So let's take an example. One of the large storage websites and magazines recently announced that IBM is a finalist for four product-of-the-year awards. Two for all-flash arrays and two for software-defined storage. So guess what we've done? We've amplified it over LinkedIn, over IBM Facebook, through our Twitter handle, we leverage that. We use it at trade shows. So digital is A, the first foray, right? People look on your website and look at what you're doing socially before they even decide, should I really call them up, or should I really go to their booth a trade show? >> So discovery and learning is happening online. >> Discovery and learning, but even progression. We just, I just happened to tweet and LinkedIn this morning, Clarinet, a large European cloud MSP and CSP, just selected IBM all-flash arrays, IBM Spectrum Protect, and IBM Spectrum Virtualize for their cloud infrastructure. And obviously their target, they sell to end-users and companies, right? But the key thing is we tweeted it, we linked it in, we're going to use it here at the show, we're going to use it in PR efforts. So digital is a critical element of the marketing mix, it's not a fad. It also can be a lead dog. So if you're going to a trade show, you should tweet about it and link it in, just the way you guys do. We all knew you were coming to this show, we know you're going to IBM Think, we know you're going to VM World and Oracle, all these great shows. How do we find out? We follow you on social media and on the digital market space, so it's critical. >> And video, video a big role in - >> Video is critical. We use your videos all the time, obviously. I always tweet them and link them in once I'm posted. >> Clip and stick is the new buzzword. Clip 'em and stick 'em. Our new clipper tool, you've seen that. >> (laughs) Yes, I have. So it's really critical, though, that, you can, and remember, I'm like one of the oldest guys in the storage business, I'm 60 years old, I've been doing this 32 years, seven start-ups, EMC, IBM twice, Mac store Seagate, so I've done big and small. This is a sea change transformation in marketing. The key thing is you have to make it not stand on its own, integrate everything. PR, analyst relations, digital in everything you do, digital with shows and how you integrate the whole buyer's journey, and put it together. And people are using digital more and more, in fact I saw a survey from a biz school, 75% of people are looking at you digitally before they ever even call you up or call one of your resellers if you use the channel, to talk about your products. That's a sea change. >> You guys do a great job with content marketing, hats off to you guys. All right, final question for you, take a minute to just quickly explain the relationship that IBM has with Cisco and the importance of it, specifically what you guys are doing with them, how you guys go on to market to customers, and what's the impact to the customer. >> So, first of all, we have a very broad relationship with Cisco, Obviously I'm the CMO of the Storage Division, so I focus on storage, but several other divisions of IBM have powerful relationships. The IoT group, the Collaboration group. Cisco's one of our valued partners. We don't have networking products, so our Global Technology Services Division is one of the largest resellers of Cisco in the world, whether it be networking, servers, converge, what-have-you, so it's a strong, powerful relationship. From an end-user perspective, the importance is they know that the two companies are working together hand-in-glove. Sometimes you have two companies where you buy solutions from the A and B, and A and B don't even talk to each other, and yes they both go to the PlugFest or the Compatibility Lab, but they don't really work together, and their technology doesn't work together. IBM and Cisco have gone well beyond that to make sure that we work closely together in all of the divisions, including the storage division, with our Cisco-validated designs. And then lastly, whether it's delivered through the direct sales model or through the valued business partners that IBM and Cisco share, it's critical the end-user know, and the partners know, they're getting something that works together and doesn't just have the works option. It's tightly-honed and finely-integrated, whether it be storage or the IoT Division, the Collaboration Division, Cisco is a heavy proponent of IBM Security Division. >> Product teams work together? >> Yeah, all the product teams work together, trade APIs back and forth, not just doing the, and let's go do a test, compatibility test. Which everybody does that, but we go well beyond that with IBM and Cisco together. >> And it's a key relationship for you guys? >> Key relationship for the Storage Division, as well as for many of the other divisions of IBM, it's a critical relationship with Cisco. >> All right, Eric Herzog, Chief Marketing Officer for the Storage Systems group at IBM. It's theCUBE live coverage in Barcelona, I'm John Furrier, Stu Miniman, back with more from Barcelona Cisco Live Europe after this short break. (upbeat techno music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering Interconnect 2017. Brought to you by IBM. >> Hey, welcome back everyone. We're live here in Las Vegas at the Mandalay Bay for IBM InterConnect 2017 exclusive Cube coverage. I'm John Furrier, my co-host Dave Vellante, our next guest Dr. Angel Diaz who is the vice president of developer technology. Also you know him from the open source world. Great to see you again. >> Nice to see you. Thanks for spending time with us. >> Thank you. >> Boy, Blockchain, open source, booming, cloud-native, booming, hybrid cloud, brute force but rolling strong. Enterprise strong, if you will, as your CEO Ginni Rometty started talking about yesterday. Give us the update on what's going on with the technology and developers because this is something that you guys, you personally, have been spending a lot of time with. Developer traction, what's the update? >> Well you know if you look at history there's been this democratization of technology. Right, everything from object oriented programming to the internet where we realize if we created open communities you can build more skill, more value, create more innovation. And each one of these layers you create abstractions. You reduce the concept count of what developers need to know to get work done and it's all about getting work done faster. So, you know, we've been systematically around cloud, data, and AI, working really hard to make sure that you have open source communities to support those. Whether it's in things like compute, storage, and network, platform as a service like say Cloud Foundry, what we're doing around the open container initiatives and the Cloud Native Computing Foundation to all the things you see in the data space and everywhere else. So it's real exciting and it's real important for developers. >> So two hot trends that we're tracking obviously, one's pretty obvious. That's machine learning in cloud. Really hand and glove together. You see machine learning really powering the AI, hitting IOT all the way up to apps and wearables and what not, autonomous vehicles. Goes on and on. The other one is Kubernetes, and Kubernetes, the rise of Kubernetes has really brought the containers to a whole nother level around multi-cloud. People might not know it, but you are involved in the CNCF formation, which is Kubernetes movement, which was KubeCon, then it became part of the Linux Foundation. So, IBM has had their hand in these two trends pretty heavily. >> Angel: Oh yeah, absolutely. >> Give the perspective, because the Kubernetes one, in particular, we'll come back to the machine learning, but Kubernetes is powering a whole nother abstraction layer around helping containers go to the next level with microservices, where the develop equation has changed. It's not just the person writing code anymore, a person writing code throws off an application that has it's own life in relationship to other services in the community, which also has analytics tied to it. So, you're seeing a changing dynamic on this potential with Kubernetes. How important is Kubernetes, and what is the real impact? >> No, it is important. And what there actually is, there's a couple of, I think, application or architecture trends that are fundamentally changing how we build applications. So one of them I'll call, let's call it Code First. This is where you don't even think about the Kubernetes layer. All you do is you want to write your code and you want to deploy your code, and you want it to run. That's kind of the platform. Something like Cloud Foundry addresses the Code First approach. Then there's the whole event-drive architecture world. Serverless, right? Where it has a particular use case, event-driven, standing, stuff up and down, dealing with many types of inputs, running rules. Then you have, let's say the more transactional type applications. Microservices, right? These three thing, when combined allows you to kind of break the shackles of the monolith of old application architectures, and build things the way that best suit your application model, and then come together in much more coherent way. Specifically in Kubernetes, and that whole container stuff. You think think about it, initially, when, containers have been around a long time, as we all know, and Docker did a great job in making container accessible and easy, right? And we worked really closely with them to create some multisource activities around the base container definitions, the open container initiative in the Linux Foundation. But of course, that wasn't enough. We need to then start to build the management and the orchestration around that. So we teamed up with others and started to kind of build this Kubernetes-based community. You know, Docker just recently brought ContainerD into the CNCF, as well, as another layer. They are within the equation. But by building this, it's almost just Russian doll of capability, right, you know, you're able to go from one paradigm, whether it's a serverless paradigm running containers, or having your microservices become use in serverless or having Code First kick off something, you can have these things work well together. And I think that's the most exciting part of what we're doing at Kubernetes, what we're doing in serverless, and what we're doing, say, in this Code First world. >> So, development's always been kind of an art form. How is that art form evolving and changing as these trends that you're describing-- >> Oh, that's a great, I love that. 'Cause I always think of ourselves as computer science artists. You and I haven't spoken about that. That's awesome. Yeah, because, you know, it is an art form, right? Your screen is your canvas, right, and colors are the services that you can bring in to build, and the API calls, right? And what's great is that your canvas never ends, because you have, say, a cloud infrastructure, which is infinitely scalable or something, right? So, yeah. But the definition of the developer is changing because we're kind of in this next phase of lowering concept count. Remember I told you this lowering of concept count. You know, I love those O'Reilly books. The little cute animals. You know, as a developer today, you don't have to buy as many of those books, because a lot of it is done in the API calls that you've used. You don't write sorting algorithms anymore. Guess what, you don't need to do speech to text algorithms. You don't need to do some analysis algorithms. So the developer is becoming a cognitive developer and a data science developer, in addition to a application developer. And that is the future. And it's really important that folks skill up. Because the demand has increased dramatically in those areas, and the need has increased as well. So it's very exciting. >> So the thing about that, that point about cognitive developer, is that in the API calls, and the reason why we don't buy all those books is, the codes out there are already in open source and machine learning is a great example, if you look at what machine learning is doing. 'Cause now you have machine learning. It used to be an art and a science. You had to be a great computer scientist and understand algorithms, and almost have that artistic view. But now, as more and more machine learning comes out, you can still write custom machine learning, but still build on libraries that are already out there. >> Exactly. So what does that do? That reduces the time it takes to get something done. And it increases the quality of what you're building, right? Because, you know, this subroutine or this library has been used by thousands and thousands of other people, it's probably going to work pretty well for your use case, right? But I can stress the importance of this moment you brought up. The cognitive data application developer coming together. You know, when the Web happened, the development market blew up in orders of magnitude. Because everybody's is sort of learning HTML, CSS, Javascript, you know, J2E, whatever. All the things they needed to build, you know, Web Uize and transactional applications. Two phase commit apps in the back, right? Here we are again, and it's starting to explode with the microservices, et cetera, all the stuff you mentioned, but when you add cognitive and data to the equation, it's just going to be a bigger explosion than the Web days. >> So we were talking with some of the guys from IBM's GBS, the Global Business Services, and the GTS, Global Technology Services, and interesting things coming out. So if you take what you're saying forward, and you open innovation model, you got business model stacks and technology stacks. So process, stacks, you know, business process, and then technology, and they now have to go hand-in-hand. So if you take what you're saying about, you know, open source, open all of this innovation, and add say, Blockchain to it, you now have another developer type. So the cognitive piece is also contributing to what looks like to be a home run with Blockchain going open source, with the ledger. So now you have the process and the stacks coming together. So now, it's almost the Holy Grail. It used to be this, "Hey, those business processor guys, they did stuff, and then the guys coded it out, built stacks. Now they're interdependent a bit. >> Yeah. Well I mean, what's interesting to me about Blockchain, I always think of, at this point about business processes, you know, business processes have always been hard to change, right? You know, once you have partners in your ecosystem, it's hard to change. Things like APIs and all the technology allows it to be much quicker now. But with Blockchain, you don't need a human involved in the decision of who's in your partner network as long as they're trusted, right? I remember when Jerry Cuomo and Chris Ferris, in my team, he's the chairman of the Blockchain, of the hyperledger group, we're talking initially when we kind of brought it to the Linux Foundation. We were talking a lot about transactions, because you know, that was one of the initial use cases. But we always kind of new that there's a lot of other use cases for this, right, in addition to that. I mean, you know, the government of China is using Blockchain to deal with carbon emissions. And they have, essentially, an economy where folks can trade, essentially, carbon units to make sure that as an industry segment, they don't go over, as an example. So you can have people coming in and out of your business process in a much more fluid way. What fascinates me about Blockchain, and it's a great point, is it takes the whole ecosystem to another level because now that they've made Blockchain successful, ecosystem component's huge. That's a community model, that's just like open source. So now you've got the confluence of open source software, now with people in writing just software, and now microservices that interact with other microservices. Not agile within a company, agile within other developers. >> Angel: Right. >> So you have a data piece that ties that together, but you also have the process and potential business model disruption, a Blockchain. So those two things are interesting to me. But it's a community role. In your expert opinion on the community piece, how do you think the community will evolve to this new dynamic? Do you think it's going to take the same straight line growth of open source, do you think there's going to be a different twist to it? You mentioned this new persona is already developing with cognitive. How do you see that happening? >> Yes, I do. There's two, let's say three points. The first on circling the community, what we've been trying to do, architecturally, is build an open innovation platform. So all these elements that make up cloud, data, AI, are open so that people can innovate, skills can grow, anything, grow faster. So the communities are actually working together. So you see lots of intralocks and subcommittees and subgroups within teams, right? Just say this kind of nesting of technology. So I think that's one megatrend that will continue-- >> Integrated communities, basically. >> Integrated communities. They do their own thing. >> Yeah. >> But to your point earlier, they don't reinvent the wheel. If I'm in Cloud Foundry and I need a container model, why am I going to create my own? I'll just use the open compute initiative container model, you know what I'm saying? >> Dave: And the integration point is that collaboration-- >> Is that collaboration, right. And so we've started to see this a lot, and I think that's the next megatrend. The second is, we just look at developers. In all this conversation, we've been talking about the what? All the technology. But the most important thing, even more so than all of this stuff, is the how. How do I actually use the technology? What is the development methodology of how I add scale, build these applications? People call that DevOp, you know, that whole area. We at IBM announced about a year and a half ago, at Gene Kim's summit, he does DevOps, the garage method, and we open sourced it, which is a methodology of how you apply Agile and all the stuff we've learned in open source, to actually using this technology in a productive way at scale. Often times people talk about working in theses little squads and so forth, but once you hire, say you've got 10 people in San Francisco, and you're going to hire one in San Ramon, that person might as well be on Mars. Because if you're not on the team there, you're not in the decision process. Well, that's not reality. Open source is not that way, the world doesn't behave that way. So this is the methodology that we talked about. The how is really important. And then the third thing, is, if you can help developers, interlock communities, teach them about the how to do this effectively, then they want samples to fork and go. Technology journeys, physical code. So what you're start to see a lot of us in open source, and even IBM, is provide starters that show people how to use the technology, add the methodology, and then help them on their journey to get value. >> So at the base level, there's a whole new set of skills that are emerging. You mentioned the O'Reilly books before, it was sort of a sequential learning process, and it seems very nonlinear now, so what do you recommend for people, how do they go about capturing knowledge, where do they start? >> I think there's probably two or three places. The first one is directly in the open source communities. You go to any open source community and there's a plethora of information, but more so, if you hang out in the right places, you know, IRC channels or wherever, people are more than willing to help you. So you can get education for free if you participate and contribute and become a good member of a community. And, in fact, from a career perspective today, that's what developers want. They want that feeling of being part of something. They want the merit badge that you get for being a core committer, the pride that comes with that. And frankly, the marketability of yourself as a developer, so that's probably the first place. The second is, look, at IBM, we spend a huge amount of time trying to help developers be productive, especially in open source, as we started this conversation. So we have a place, developer.ibm.com. You go there and you can get links to all the relevant open source communities in this open innovation platform that I've talked about. You can see the methodologies that I spoke about that is open. And then you could also get these starter code journeys that I spoke about, to help you get started. So that's one place-- >> That's coming out in April, right? >> That's right. >> The journeys. >> Yeah, but you can go now and start looking at that, at developer.ibm.com, and not all of it is IBM content. This is not IBM propaganda here, right? It is-- >> John: Real world examples. >> Real world examples, it's real open source communities that either we've helped, we've shepherded along. And it is a great place, at least, to get your head around the space and then you can subset it, right? >> Yeah. So tell us about, at the last couple of minutes we have, what IBM's doing right now from a technology, and for developers, what are you guys doing to help developers today, give the message from what IBM's doing. What are you guys doing? What's your North Star? What's the vision and some of the things you're doing in the marketplace people can get involved in? You mentioned the garage as one. I'm sure there's others. >> Yeah, I mean look, we are m6anically focused on helping developers get value, get stuff done. That's what they want to do, that's what our clients want to do, and that's what turns us on. You build your art, you talk, you're going back to art, you build your drawing, you want to look at it. You want it to be beautiful. You want others to admire it, right? So if we could help you do that, you'll be better for it, and we will be better for it. >> As long as they don't eat their ear, then they're going to be fine. >> It's subjective, but give value of what they do. So how do they give value? They give value by open technologies and how we've built, essentially, cloud, data, AI, right? So art, arts technology adds value. We get value out of the methodology. We help them do this, it's around DevOps, tooling around it, and then these starters, these on-ramps, right, to getting started. >> I got to ask you my final question, a more personal one, and Dave and I talk about this all the time off camera, being an older guy, computer science guy, you're seeing stuff now that was once a major barrier, whether it's getting access to massive compute, machine learning, libraries, the composability of the building blocks that are out there, to create art, if you will, it's phenomenal. To me, it's just like the most amazing time to be be a computer scientist, or in tech, in general, building stuff. So I'm going to ask you, what are you jazzed up about? Looking back, in today's world, the young guns that are coming onto the scene not knowing that we walked barefoot in the snow to school, back in the old days. This is like, it's a pretty awesome environment right now. Give us personal color on your take on that, the change and the opportunity. >> Yeah, so first of all, when you mentioned older guys, you were referring to yourselves, right? Because this is my first year at IBM. I just graduated, there's nothing old here, guys. >> John: You could still go to, come on (laughs). >> What does that mean? Look you know, there's two things I'm going to say. Two sides of the equation. First of all, the fundamentals of computer science never go away. I still teach, undergrad seminars and so forth, and you have to know the fundamentals of computer science. That does not go away because you can write bad code. No matter what you're doing or how many abstractions you have, there are fundamental principles you need to understand. And that guides you in building better art, okay? Now putting that aside, there is less that you need to know all the time, to get your job done. And what excites me the most, so back when we worked on the Web in the early 90s, and the markup languages, right, and I see some in the audience there, Arno, hey, Arno, who helped author some of the original Web standards with me, and he was with the W3C. The use cases for math, for the Web, was to disseminate physics, that's why Tim did it, right? The use case for XML. I was co-chair of the mathematical markup language. That was a use case for XML. We had no idea that we would be using these same protocols, to power all the apps on your phone. I could not imagine that, okay? If I would have, trust me, I would have done something. We didn't know. So what excites me the most is not being able to imagine what people will be able to create. Because we are so much more advanced than we were there, in terms of levels of abstraction. That's what's, that's the exciting part. >> All right. Dr. Angel Diaz, great to have you on theCUBE. Great inspiration. Great time to be a developer. Great time to be building stuff. IOT, we didn't even get to IOT, I mean, the prospects of what's happening in industrialization, I mean, just pretty amazing. Augmented intelligence, artificial intelligence, machine learning, really the perfect storm for innovation. Obviously, all in the open. >> Angel: Yes. Awesome stuff. Thanks for coming on the theCUBE. Really appreciate it. >> Thank you guys, appreciate it. >> IBM, making it happen with developers. Always have been. Big open source proponents. And now they got the tools, they got the garages for building. I'm John Furrier, stay with us, there's some great interviews. Be right back with more after this short break. (tech music)

>> live from Boston, Massachusetts. It's the Cube covering IBM Chief Data Officer Strategy Summit brought to you by IBM. Now, here are your hosts. Day Volante and Stew Minimum. >> Welcome back to Boston, everybody. This is the Cube, the worldwide leader in live tech coverage. Stillman and I have pleased to have Jean Kolker on a Cuba lem. Uh, he's IBM vice president and chief data officer of the Global Technology Services division. And Seth Dobrin who's the Director of Digital Strategies. That Monsanto. You may have seen them in the news lately. Gentlemen. Welcome to the Cube, Jean. Welcome back. Good to see you guys again. Thanks. Thank you. So let's start with the customer. Seth, Let's, uh, tell us about what you're doing here, and then we'll get into your role. >> Yes. So, you know, the CDO summit has been going on for a couple of years now, and I've been lucky enoughto be participating for a couple of a year and 1/2 or so, Um, and you know, really, the nice thing about the summit is is the interaction with piers, um, and the interaction and networking with people who are facing similar challenges from a similar perspective. >> Yes, kind of a relatively new Roland topic, one that's evolved, Gene. We talked about this before, but now you've come from industry into, ah, non regulated environment. Now what's happened like >> so I think the deal is that way. We're developing some approaches, and we get in some successes in regulated environment. Right? And now I feel with And we were being client off IBM for years, right? Using their technology's approaches. Right? So and now I feel it's time for me personally to move on something different and tried to serve our power. I mean, IBM clients respected off in this striking from healthcare, but their approaches, you know, and what IBM can do for clients go across the different industries, right? And doing it. That skill that's very beneficial, I think, for >> clients. So Monsanto obviously guys do a lot of stuff in the physical world. Yeah, you're the head of digital strategy. So what does that entail? What is Monte Santo doing for digital? >> Yes, so, you know, for as head of digital strategies for Monsanto, really? My role is to number one. Help Monsanto internally reposition itself so that we behave and act like a digital companies, so leveraging data and analytics and also the cultural shifts associated with being more digital, which is that whole kind like you start out this conversation with the whole customer first approach. So what is the real impact toe? What we're doing to our customers on driving that and then based on on those things, how can we create new business opportunities for us as a company? Um, and how can we even create new adjacent markets or new revenues in adjacent areas based on technologies and things we already have existing within the company? >> It was the scope of analytics, customer engagement of digital experiences, all of the above, so that the scope is >> really looking at our portfolio across the gamut on DH, seeing how we can better serve our customers and society leveraging what we're doing today. So it's really leveraging the re use factor of the whole digital concept. Right? So we have analytics for geospatial, right? Big part of agriculture is geospatial. Are there other adjacent areas that we could apply some of that technology? Some of that learning? Can we monetize those data? We monetize the the outputs of those models based on that, Or is there just a whole new way of doing business as a company? Because we're in this digital era >> this way? Talked about a lot of the companies that have CEOs today are highly regulated. What are you learning from them? What's what's different? Kind of a new organization. You know, it might be an opportunity for you that they don't have. And, you know, do you have a CDO yet or is that something you're planning on having? >> Yes, So we don't have a CDO We do have someone acts as an essential. he's a defacto CEO, he has all of the data organizations on his team. Um, it's very recent for Monsanto, Um, and and so I think, you know, in terms of from the regular, what can we learn from, you know, there there are. It's about half financial people have non financial people, are half heavily regulated industries, and I think, you know, on the surface you would. You would think that, you know, there was not a lot of overlap, but I think the level of rigor that needs to go into governance in a financial institution that same thought process. Khun really be used as a way Teo really enable Maur R and D. Mohr you know, growth centered companies to be able to use data more broadly and so thinking of governance not as as a roadblock or inhibitor, but really thinking about governance is an enabler. How does it enable us to be more agile as it enable us to beam or innovative? Right? If if people in the company there's data that people could get access to by unknown process of known condition, right, good, bad, ugly. As long as people know they can do things more quickly because the data is there, it's available. It's curated. And if they shouldn't have access it under their current situation, what do they need to do to be able to access that data? Right. So if I would need If I'm a data scientist and I want to access data about my customers, what can I can't? What can and can't I do with that data? Number one doesn't have to be DEA Nana Mayes, right? Or if I want to access in, it's current form. What steps do I need to go through? What types of approval do I need to do to do to access that data? So it's really about removing roadblocks through governance instead of putting him in place. >> Gina, I'm curious. You know, we've been digging into you know, IBM has a very multifaceted role here. You know how much of this is platforms? How much of it is? You know, education and services. How much of it is, you know, being part of the data that your your customers you're using? >> Uh so I think actually, that different approaches to this issues. My take is basically we need Teo. I think that with even cognitive here, right and data is new natural resource worldwide, right? So data service, cognitive za za service. I think this is where you know IBM is coming from. And the BM is, you know, tradition. It was not like that, but it's under a lot of transformation as we speak. A lot of new people coming in a lot off innovation happening as we speak along. This line's off new times because cognitive with something, really you right, and it's just getting started. Data's a service is really new. It's just getting started. So there's a lot to do. And I think my role specifically global technology services is you know, ah, largest by having your union that IBM, you're 30 plus 1,000,000,000 answered You okay? And we support a lot of different industries basically going across all different types of industries how to transition from offerings to new business offerings, service, integrated services. I think that's the key for us. >> Just curious, you know? Where's Monsanto with kind of the adoption of cognitive, You know what? Where are you in that journey? >> Um, so we are actually a fairly advanced in the journey In terms of using analytics. I wouldn't say that we're using cognitive per se. Um, we do use a lot of machine learning. We have some applications that on the back end run on a I So some form of artificial or formal artificial intelligence, that machine learning. Um, we haven't really gotten into what, you know, what? IBM defined his cognitive in terms of systems that you can interact with in a natural, normal course of doing voice on DH that you spend a whole lot of time constantly teaching. But we do use like I said, artificial intelligence. >> Jean I'm interested in the organizational aspects. So we have Inderpal on before. He's the global CDO, your divisional CDO you've got a matrix into your leadership within the Global Services division as well as into the chief date officer for all of IBM. Okay, Sounds sounds reasonable. He laid out for us a really excellent sort of set of a framework, if you will. This is interval. Yeah, I understand your data strategy. Identify your data store says, make those data sources trusted. And then those air sequential activities. And in parallel, uh, you have to partner with line of business. And then you got to get into the human resource planning and development piece that has to start right away. So that's the framework. Sensible framework. A lot of thought, I'm sure, went into it and a lot of depth and meaning behind it. How does that framework translate into the division? Is it's sort of a plug and play and or is there their divisional goals that are create dissonance? Can you >> basically, you know, I'm only 100 plus days in my journey with an IBM right? But I can feel that the global technology services is transforming itself into integrated services business. Okay, so it's thiss framework you just described is very applicable to this, right? So basically what we're trying to do, we're trying to become I mean, it was the case before for many industries, for many of our clients. But we I want to transform ourselves into trusted broker. So what they need to do and this framework help is helping tremendously, because again, there's things we can do in concert, you know, one after another, right to control other and things we can do in parallel. So we trying those things to be put on the agenda for our global technology services, okay. And and this is new for them in some respects. But some respects it's kind of what they were doing before, but with new emphasis on data's A service cognitive as a service, you know, major thing for one of the major things for global technology services delivery. So cognitive delivery. That's kind of new type off business offerings which we need to work on how to make it truly, you know, once a sense, you know, automated another sense, you know, cognitive and deliver to our clients some you value and on value compared to what was done up until recently. What >> do you mean by cognitive delivery? Explained that. >> Yeah, so basically in in plain English. So what's right now happening? Usually when you have a large systems  computer IT system, which are basically supporting lot of in this is a lot of organizations corporations, right? You know, it's really done like this. So it's people run technology assistant, okay? And you know what Of decisions off course being made by people, But some of the decisions can be, you know, simple decisions. Right? Decisions, which can be automated, can standardize, normalize can be done now by technology, okay and people going to be used for more complex decisions, right? It's basically you're going toe. It turned from people around technology assisted toa technology to technology around people assisted. OK, that's very different. Very proposition, right? So, again, it's not about eliminating jobs, it's very different. It's taken off, you know, routine and automata ble part off the business right to technology and given options and, you know, basically options to choose for more complex decision making to people. That's kind of I would say approach. >> It's about scale and the scale to, of course, IBM. When when Gerstner made the decision, Tio so organized as a services company, IBM came became a global leader, if not the global leader but a services business. Hard to scale. You could scare with bodies, and the bigger it gets, the more complicated it gets, the more expensive it gets. So you saying, If I understand correctly, the IBM is using cognitive and software essentially to scale its services business where possible, assisted by humans. >> So that's exactly the deal. So and this is very different. Very proposition, toe say, compared what was happening recently or earlier? Always. You know other. You know, players. We're not building your shiny and much more powerful and cognitive, you know, empowered mouse trap. No, we're trying to become trusted broker, OK, and how to do that at scale. That's an open, interesting question, but we think that this transition from you know people around technology assisted Teo technology around people assisted. That's the way to go. >> So what does that mean to you? How does that resonate? >> Yeah, you know, I think it brings up a good point actually, you know, if you think of the whole litany of the scope of of analytics, you have everything from kind of describing what happened in the past All that to cognitive. Um, and I think you need to I understand the power of each of those and what they shouldn't should be used for. A lot of people talk. You talk. People talk a lot about predictive analytics, right? And when you hear predictive analytics, that's really where you start doing things that fully automate processes that really enable you to replace decisions that people make right, I think. But those air mohr transactional type decisions, right? More binary type decisions. As you get into things where you can apply binary or I'm sorry, you can apply cognitive. You're moving away from those mohr binary decisions. There's more transactional decisions, and you're moving mohr towards a situation where, yes, the system, the silicon brain right, is giving you some advice on the types of decisions that you should make, based on the amount of information that it could absorb that you can't even fathom absorbing. But they're still needs really some human judgment involved, right? Some some understanding of the contacts outside of what? The computer, Khun Gay. And I think that's really where something like cognitive comes in. And so you talk about, you know, in this in this move to have, you know, computer run, human assisted right. There's a whole lot of descriptive and predictive and even prescriptive analytics that are going on before you get to that cognitive decision but enables the people to make more value added decisions, right? So really enabling the people to truly add value toe. What the data and the analytics have said instead of thinking about it, is replacing people because you're never going to replace you. Never gonna replace people. You know, I think I've heard people at some of these conferences talking about, Well, no cognitive and a I is going to get rid of data scientist. I don't I don't buy that. I think it's really gonna enable data scientist to do more valuable, more incredible things >> than they could do today way. Talked about this a lot to do. I mean, machines, through the course of history, have always replaced human tasks, right, and it's all about you know, what's next for the human and I mean, you know, with physical labor, you know, driving stakes or whatever it is. You know, we've seen that. But now, for the first time ever, you're seeing cognitive, cognitive assisted, you know, functions come into play and it's it's new. It's a new innovation curve. It's not Moore's law anymore. That's driving innovation. It's how we interact with systems and cognitive systems one >> tonight. And I think, you know, I think you hit on a good point there when you said in driving innovation, you know, I've run, you know, large scale, automated process is where the goal was to reduce the number of people involved. And those were like you said, physical task that people are doing we're talking about here is replacing intellectual tasks, right or not replacing but freeing up the intellectual capacity that is going into solving intellectual tasks to enable that capacity to focus on more innovative things, right? We can teach a computer, Teo, explain ah, an area to us or give us some advice on something. I don't know that in the next 10 years, we're gonna be able to teach a computer to innovate, and we can free up the smart minds today that are focusing on How do we make a decision? Two. How do we be more innovative in leveraging this decision and applying this decision? That's a huge win, and it's not about replacing that person. It's about freeing their time up to do more valuable things. >> Yes, sure. So, for example, from my previous experience writing healthcare So physicians, right now you know, basically, it's basically impossible for human individuals, right to keep up with spaced of changes and innovations happening in health care and and by medical areas. Right? So in a few years it looks like there was some numbers that estimate that in three days you're going to, you know, have much more information for several years produced during three days. What was done by several years prior to that point. So it's basically becomes inhuman to keep up with all these innovations, right? Because of that decision is going to be not, you know, optimal decisions. So what we'd like to be doing right toe empower individuals make this decision more, you know, correctly, it was alternatives, right? That's about empowering people. It's not about just taken, which is can be done through this process is all this information and get in the routine stuff out of their plate, which is completely full. >> There was a stat. I think it was last year at IBM Insight. Exact numbers, but it's something like a physician would have to read 1,500 periodic ALS a week just to keep up with the new data innovations. I mean, that's virtually impossible. That something that you're obviously pointing, pointing Watson that, I mean, But there are mundane examples, right? So you go to the airport now, you don't need a person that the agent to give you. Ah, boarding pass. It's on your phone already. You get there. Okay, so that's that's That's a mundane example we're talking about set significantly more complicated things. And so what's The gate is the gate. Creativity is it is an education, you know, because these are step functions in value creation. >> You know, I think that's ah, what? The gate is a question I haven't really thought too much about. You know, when I approach it, you know the thinking Mohr from you know, not so much. What's the gate? But where? Where can this ad the most value um So maybe maybe I have thought about it. And the gate is value, um, and and its value both in terms of, you know, like the physician example where, you know, physicians, looking at images. And I mean, I don't even know what the error rate is when someone evaluates and memory or something. And I probably don't want Oh, right. So, getting some advice there, the value may not be monetary, but to me, it's a lot more than monetary, right. If I'm a patient on DH, there's a lot of examples like that. And other places, you know, that are in various industries. That I think that's that's the gate >> is why the value you just hit on you because you are a heat seeking value missile inside of your organisation. What? So what skill sets do you have? Where did you come from? That you have this capability? Was your experience, your education, your fortitude, >> While the answer's yes, tell all of them. Um, you know, I'm a scientist by training my backgrounds in statistical genetics. Um, and I've kind of worked through the business. I came up through the RND organization with him on Santo over the last. Almost exactly 10 years now, Andi, I've had lots of opportunities to leverage. Um, you know, Data and analytics have changed how the company operates on. I'm lucky because I'm in a company right now. That is extremely science driven, right? Monsanto is a science based company. And so being in a company like that, you don't face to your question about financial industry. I don't think you face the same barriers and Monsanto about using data and analytics in the same way you may in a financial types that you've got company >> within my experience. 50% of diagnosis being proven incorrect. Okay, so 50% 05 0/2 summation. You go to your physician twice. Once you on average, you get in wrong diagnosis. We don't know which one, by the way. Definitely need some someone. Garrett A cz Individuals as humans, we do need some help. Us cognitive, and it goes across different industries. Right, technologist? So if your server is down, you know you shouldn't worry about it because there is like system, you know, Abbas system enough, right? So think about how you can do that scale, and then, you know start imagined future, which going to be very empowering. >> So I used to get a second opinion, and now the opinion comprises thousands, millions, maybe tens of millions of opinions. Is that right? >> It's a try exactly and scale ofthe data accumulation, which you're going to help us to solve. This problem is enormous. So we need to keep up with that scale, you know, and do it properly exactly for business. Very proposition. >> Let's talk about the role of the CDO and where you see that evolving how it relates to the role of the CIA. We've had this conversation frequently, but is I'm wondering if the narratives changing right? Because it was. It's been fuzzy when we first met a couple years ago that that was still a hot topic. When I first started covering this. This this topic, it was really fuzzy. Has it come in two more clarity lately in terms of the role of the CDO versus the CIA over the CTO, its chief digital officer, we starting to see these roles? Are they more than just sort of buzzwords or grey? You know, areas. >> I think there's some clarity happening already. So, for example, there is much more acceptance for cheap date. Office of Chief Analytics Officer Teo, Chief Digital officer. Right, in addition to CEO. So basically station similar to what was with Serious 20 plus years ago and CEO Row in one sentence from my viewpoint would be How you going using leverage in it. Empower your business. Very proposition with CDO is the same was data how using data leverage and data, your date and your client's data. You, Khun, bring new value to your clients and businesses. That's kind ofthe I would say differential >> last word, you know, And you think you know I'm not a CDO. But if you think about the concept of establishing a role like that, I think I think the name is great because that what it demonstrates is support from leadership, that this is important. And I think even if you don't have the name in the organization like it, like in Monsanto, you know, we still have that executive management level support to the data and analytics, our first class citizens and their important, and we're going to run our business that way. I think that's really what's important is are you able to build the culture that enable you to leverage the maximum capability Data and analytics. That's really what matters. >> All right, We'll leave it there. Seth Gene, thank you very much for coming that you really appreciate your time. Thank you. Alright. Keep it right there, Buddy Stew and I'll be back. This is the IBM Chief Data Officer Summit. We're live from Boston right back.