>> Announcer: Live from Las Vegas it's the CUBE covering IBM Think 2018. Brought to you by IBM. (upbeat music) >> Welcome back to the CUBE we are live at Day one of IBM Think 2018, I'm Lisa Martin with Dave Vellante we're at Mandalay Bay in Las Vegas, 40 plus thousand people at this event, we're excited to welcome to the CUBE Ashok Reddy the Group GM of DevOps at CA, welcome to the CUBE. >> Great to be here. >> So you were at IBM, you're now at CA, you came over a couple of years ago. Digital business transformation, a buzzword, we talk about it a lot on the CUBE, I want to kind of kick things off with you about what is CA seeing with respect to helping businesses evolve to a digital enterprise? What is a digital enterprise and where does trust come into that as a key enabler? >> Yeah I think that, you know, when you look at the enterprise all businesses today are becoming technology-based businesses, so it doesn't matter what industry you are in, whether you are financial services, garment retail, so every industry's innovation is coming from technology and software. So in that context, if somebody, if I'm a bank today and people used to walk into my, you know use the ATM or they will come into my store, but you may deal with a few hundred or few million people, but now when you become a digital enterprise, you're scaling from a few hundred, a few million to almost a billion people or more who could be accessing your services all the web, all the mobile, as well as now AI as a channel. So how do you actually work, scale the business from just dealing with people who you had prior relationships with to people who have to deal with now billions of people, could be devices and bots, in a very digital world where you don't have prior trust and relationships established. So that's where I think about digital enterprise as who is moving from a traditional way of doing business to now you're scaling to five to six billion people, devices, and everything else, but then the trust comes in because how do you trust whether a user is actually a real user or if I'm a user how do I trust a enterprise because I'm dealing with them virtually. So this really becomes a two-way thing, so it's really that trust becomes much more important. >> I want to come to back to trust in a minute but this whole notion of digital, everybody talks about digital transformation, different things to different people, everybody uses the uberization example, but everybody's trying to get digital right, all the customers that we talk to, the companies that are organizing around it. Do you see that in the marketplace and what is your advice to customers who are tryin' to get it right? >> Yeah I mean, I think it's a great question, I think part of the being digital is really about are you, sometimes people are what I call digital washing things, you basically adopt a few things, but in a true sense of digital, it's all about how do I actually understand the user needs and experimentation? It starts with really, you have a hypothesis and how do I actually go about acquiring new customers and not just a few but where you're trying to acquire millions of them and in a digital world, you are establishing things where we call, you know people talk about there are different channels, right, digital sales and others. Most of the enterprises typically have been dealing with direct relationship, so if I want to now create awareness of my services and products as a company, it's not about direct sales anymore, people are using different means to understand about the products and services themselves. So it becomes more about in that context your sales will have to change in the first place, your marketing has to be about, you know, how do I acquire digital in a channel perspective. So you're to change your processes such that feedback becomes much more important, it's not about just selling, people actually use your product and now you're getting feedback and that needs to be very much faster than what it used to be, because it's all about experience and people are going to change, you know if you don't get a response on your mobile app for a few seconds they're going to switch, it's not that way in a traditional way, right. So the type of things what people do in a digital is quite different than in a traditional way. >> I want to follow that up with an observation, and get CA's point of view, or maybe even your personal point of view. When you think about mobile, social, cloud, SAS, big data, these aren't really discrete industries anymore, they've sort of all come together, and it seems like digital is about these sets of digital services that are built on top of all those things. I mean when you think about even, logging in with LinkedIn, Twitter, or Facebook, I mean those are digital services that we can all access and it seems like disruption is coming from companies who are able to form new businesses leveraging those digital services that are a part of this new fabric that's emerging. So is that a reasonable premise? And where does CA fit in that fabric? >> Yeah, you know I think that's a, you know basically what has happened, right, if I look at more from a applications perspective we have gone from traditional line-server, desktop applications to web to mobile, but now the latest thing is AI, right? It's more like AI first applications, so when I look at a process perspective, the disruptions you are talking about is people used to do waterfall and then it was fast waterfall then agile came in and people are saying, "Okay let me develop," the development become agile, but you need to bring the rest of the organization and that where DevOps came in. But now you're looking at, if I am looking at an application and I want to build an application and get feedback, people who build cloud-first models that's what it work, like whether it's an Amazon or LinkedIn, examples you are giving, but now if the application itself is changing, right? I look at it as like a thermostat, a digital thermostat verses a Nest, when I develop and deploy something quickly, it was still predefined, it's a deterministic application but now with the AI type application where everybody is going towards the application itself starts changing, it starts learning and now it starts going to make decisions so how do you actually develop and deploy, test something which you don't know what it's going to do based on the data and that's really the next paradigm, right? Because the cloud itself is making everybody equal because if everybody uses SAS applications on the cloud so what's a differentiation for a company? So that's where I think we look at it as you really still need to understand your customers, your domain, and being able to understand and learn from them and the specific algorithms or whatever you apply, you train that and how what action you're going to take is where we think CA, when we say transform it's not just about transforming how do you do development and how do you do infrastructure and moving cloud, but just because you become a cloud, everybody can go to cloud and infrastructure, people are providing AWS and Azure and IBM Cloud, then what happens to the companies, right? To me that's where the transformation is the secret sauce of what industry you're in, how you understand your customers and what you're going to do with it. >> Okay so I would agree, cloud, let's call it, let's say cloud is table stakes, right? I mean, it's there, sets of services that anybody can use. Then there's data, that's a little harder, putting data at the core of your enterprise is nontrivial and then applying machine intelligence or AI to that data, to learn, to improve, and to have a culture of speed and DevOps, that's the hard part. So that's where CA fits, is that right? >> Ashok: Yeah you know I think so. >> Maybe you could add some color. >> Exactly right so from a data perspective part of it comes from, you know when you are collecting all this information from different companies and people, privacy becomes a big issue, right? So how do you make sure that the data somebody gives you is private and you're not sharing it with somebody else? And people are sharing personal information here, including the IP addresses, where you are located, if you think about all of us, there is so much information about us available. But how do you make sure that that's private? And it's almost like I use an example of somebody gives you a credit card information on the digital world, it's almost like you are going, it's like somebody giving you a wallet and you're looking at their entire wallet just because they gave you a credit card, right? So we need to make sure that we actually are focusing on the privacy, so we actually help customers around making sure that data what's private, and whether it's data in rest or in data in motion, and there's lots of laws like GDPR and others where, in Europe for example, right, you can't have the data leave a particular country or a data center, so how do you make sure that happens? And the second part is, in machine learning there's so much bias in the data, the machine learning is nothing but computational statistics and it's going to come up with a signal based on the data you provide. What if there is data is biased? There's a lot of bias in the data and now how do you know whether you can prevent the, you know the bias in the data? And then you know we have a lot of other things, but it's about the speed and agility, but also how do I test things? And make sure that, you know, the data itself is one aspect but the services are available to you 24 by seven anytime anywhere. >> With respect to some of the announcements that have come out already from IBM, related to cloud, related to AI, you mentioned security, what excites you in your role as the group GM for DevOps in terms of the directions that they're going and especially where AI is concerned? >> No, you know I think IBM you know when I look at through all the way when the first tunnels to the Jeopardy and the Watson, I think there has been so much of innovations and a lot, and of course there has been a lot of hype also, but I think now you are getting to a point where there is significant progress in both machine learning as well as applying deep learning and some of the things that are solving real-world problems like healthcare, right? You're trying to solve, people talk about AI well it's going to take away jobs, but I think it's not taking away jobs it's the tasks people won't do, most people have a lot of tasks, mundane tasks, but if you are able to solve the world's biggest problems some healthcare related, you're finding people who are disabilities and a lot of things around, if you look at the automation which is creating really new opportunities for many people to focus on the higher value things. So I think the IBM has brought together industry focus, which is great, it's not just about technology but let me go and look at healthcare industry, the supply-chain with blockchain, right? I think the combination of blockchain with AI and machine learning is also changing the whole aspects of what we knew, the trust comes back into this because you know IBM is announcing with the hyperledger, something around zero knowledge proof which is really around, if you are somebody who is let's say you're under 21, you look like you're somebody who is under 21. >> Lisa: Thank you. >> And if somebody has to check your proof of age on a, somebody not knowing you on the web or on the digital world, how do they verify that? Without you giving too much information. So that's something where, it's like zero knowledge proof, so that's being built into the blockchain, so things like that, combining blockchain and now with the mainframe that is a z14, which has highest levels of encryption. So you can really start providing a true system of trust and a digital trust for, both from a user's perspective as well as enterprises. >> Yeah the whole KYC, know your customer, is just exploding in terms of interest and importance and you guys are obviously, it sounds like you're participating there directly. >> Yeah we are launching a bunch of this mainframe as a service for that to help customers because we also have problems with people retiring on the mainframe and they don't understand so what we're doing is to bring a notion of how do I use the tools I already know, like opensource tools or whatever, so we have an initiative for Brightside which is really help developers use the things that they already know but underneath the covers they're actually building things for the mainframe. So that solves the problem of knowing the mainframe but don't make mainframe different. >> So on, kind of closing things out, from an innovation perspective, one of the things that you talked about with automation, and we heard this earlier Dave from KPMG, is that machine learning and AI are actually going to be enablers of a lot of things including new opportunities, new careers paths, et cetera, rather than looking at it as oh there's going to take away humans for jobs, I thought that was interesting that you brought that up. Talk to us about the innovation, the culture of innovation, at CA, how is the culture enabling you to do your job better and really work with customers in a symbiotic way to really understand what problems need to be solved? What's the innovation culture like? >> Yeah I mean that's actually you know we actually have a, we've created a more like a incubation program, a startup within CA, and one of the things we have done is if anybody has a really good idea to solve a customer outcome, we kind of go through this whole like a mini while process and they actually come in and pitch the idea, then we actually fund those as a separate start ups within the company, we have more than 15 startups, some of them are graduated, either they, we buy them internally from a different business unit or we can even we take them public to other companies, right? So we have done that, which is energized a lot of the people like they can become their own founders and they can bring the innovations. But within even the product development teams we do a lot of hackathons and being able to use AI and machine learning and blockchain, we are basically build up machine learning first culture, so everybody from people who have been there for 30 years to people who are just come in are all learn this and they're looking at what are the type of things I can apply AI for my data to improve how I can look at patterns and improve the automation. But there is also, as applications become AI first, how can kind of help customers around that? So I think it's a exciting time for everybody and we are seeing that are already in terms of the numbers of innovations and patterns we're finding. >> Well Ashok, thanks so much for sharing your insights and what's going on with IBM in CA, we thank you so much for your time. >> Oh great, thank you for having me on. >> We want to thank you for watching the CUBE. We are live at Day one of IBM's inaugural Think event, I'm Lisa Martin with Dave Vellante, stick around Dave and I are going to be right back with our final guest and then we'll do a wrap of the exciting things that we've heard today. We'll be right back. (upbeat music)