The Cube presents UI Path Forward five. Brought to you by UI Path. >>Hi, everybody went back live at the Venetian, formerly the Sands Convention Center. Dave Ante with David Nicholson. UI. Paths forward five. This is the fourth forward conference that the Cube has done. So we've seen the ascendancy of UI path, the growth customers. UiPath is one of the first companies to actually come back Post Covid. Last year, 2021 at the Bellagio. They took a chance and it actually worked out great at a couple thousand people there. Lots of customers. We're here with Lauren Joyce, who's the global automation lead at Whirlpool. She's joined by Regener Facade rp, who is the global automation lead at Accenture. Good to see you again. Lauren. Welcome to the Cube first timer. Very much, >>Yes, thank >>You. So you're relatively new to automation, but you, as we were talking, you're a process with talk about the center of excellence that you're building out. What's the importance of that to Whirlpool? >>Absolutely. So we are first looking at automation from our finance organization and they were coming to us with, Hey, here are 12 things we wanna automate. And really what we are finding is that not all of these things were suitable for automation. So we've started on the COE journey of, well, how do we make sure that we're getting the most ROI for our business? Starting with discovery, making sure that what we're automating it makes sense, it's the right process versus just an upgrade or, or retooling set. So for us, especially being a global company, making sure that we had that governance in place, that mindset and what should be automated and when really made sense and helped us on our journey pursuing. >>And, and, and I presume that's where Accenture comes in. I mean, rp, you got deep industry expertise, you've got automation expertise. What role do you play in that prioritization exercise? >>So the, the way we approach any automation implementation is similar to what we did here in our pool. First step is, you know, I call it as knowing where you are in the automation journey. Like what always is, if you don't know where you are on a map, a map won't help you. So baselining the current automation maturity and the current journey where they are. And once you do that, you identify you are not star and prioritization and the goals that are required and then you build a plan. And exactly how we approach in establishing a center of excellence that drives the automation with rigor, knowing where you are and where you want to get to, >>What's the team look like in a, in a, who's on the bus, You know, who's who's, who's in in the circle if you will. How do you com you know, build, you've written about this, it's like a sports team. You put it together, you need be a quarterback, you need a lineman, you need, you know, wide receivers who's on the center of excellence team. >>So the way you always build the center of excellence is making sure that your business partners and the senior leadership team is committed to the entire automation journey. That's the key ingredient for success. Then you build, one of the critical aspect is the talent, the quarterback, you said the talent. In today's world, automation talent is just not about knowing, you know, RPA techniques or you know, process optimization, but it is an end to end technology stack starting from cloud to data to analytics and entire platform capabilities of automation that combined and coupled with change management and how do you drive an enterprise chain management is very, very critical in terms of implementing automation. >>Absolutely. Lauren, I'm curious, did, did Accenture bring UI path to Whirlpool or did you bring, or did you bring Accenture in and UI path in together? How, how did that interaction? >>Yes. So we brought Accenture in and they really helped us along with that journey and they brought UI path to us. Our European business was actually using Blue Prism and that's when we said no, we wanna standardize specifically on UI path and make sure from a global standpoint we're using the same tooling. And that really helped that as we were building our team, we leaned on their expertise and then even we're retooling people within our corporation of, hey, we took our SAP lead, our GCP lead to be our technical architect and and people that could help speak the language and translate from process and explain that doesn't have to be a large project and explain what automation is to help drive return investment for sure. >>Now you're early in, but have you seen results, you know so far? Can you talk about that, quantify it in any way or? >>Absolutely. So we started our journey December of 2020. We've automated about 60 or so bots, but really everything that we've done is based on hours saved. So we're at about 60,000 hours automated and with some of our biggest, like our big box stores and our KitchenAid small appliances, we've even had hard dollar savings that we had a bot that went live about in 60 days. We had a $3 million return and take took out 3000 hours of human interaction. That was great for us. >>So the world's kind of a mess right now. You got supply chain issues, you got inflation, you got a recession, you got the United States. Anyway, you got the Fed trying to figure out, oh there's sling shoting, you know, some people are, you know, really hurting stock market is starting to show that there's a lot of confusion out there. The world is changed quite a bit obviously the last few years. How do you guys see it? What role has, I wonder if both of you could answer, what role has automation played in helping like, for instance, Whirlpool with maybe supply chain problems or maybe bigger forecasting and, and what are you seeing across organizations? But Lauren if you could start. >>Absolutely. So for us being able to show improvement in a six to eight week development cycle and instead of saying here's a heavy dollar investment or a new tooling that you gotta get people resources up to speed on, we can take where we are today, automate save hours where we're getting our employee engagement scores of I'm overworked, I have too much on my plate, how can you help me? And automation is there to support and that's really helped our business one take unnecessary work off their plate and show very quick value add to the business without having to have huge dollar investments in our, I'm you trying to save money. >>Are people, what are you seeing in terms of, so some of the problems that people I see as sign out here said, oh, in inflation at five to 7% go after productivity and make it in 20% gains. I mean, what are you seeing in the field? >>More than ever, More than ever, automation is more relevant now given the current economy environment that we are operating. Because automation always free up or optimizers the capacity that every enterprise has. Optimizing capacity is very important so that you can take your talented employees and the talented resources to do more strategic transformation program, which helps to sustain and stay and scale in your business. So I see that automation playing a significant role to impact business imperative. >>What are some of the common misconceptions? I mean we talk a lot about people's fear of automation. You know, I don't think that's necessarily a misconception. I think a lot of times people are fearful about automating though. Maybe they, they shouldn't be. We had Dentsu on today, DS like, you know, this giant global branding firm and they get a lot of young kids, they're like, No, bring it on. I don't want to do all this mundane stuff. But you know, a lot of folks are are are concerned, but, so that maybe is one misconception. Are there others, Lauren, that you found that you can share? >>I think we were lucky that we didn't necessarily have that fear of being replaced by automation. I think our change management plan really helped drive that. We included some fun things of any time a bot went live you got almost like a birth certificate of here's the process we save for you, here's how it's grown over six, six months, 12 months, 18 months. But I'm not sure if we had any other major gaps like that or or pitfalls >>Or, or p anything that, >>So my philosophy is automation is human plus machine combination. You can't run just, you know, people can't think that, you know, if my task get automated, I lose the, I lose my my jobs. That's not how it works because you, you do need human expertise, competency skills to kind of argument what you do with automation. And most important thing when you do this change is that most of the enterprises do not believe, do not understand that you have to get even process, right? You don't want to, you know, have an inefficient process and put automation on the top of it. Then you just made your inefficiency run more faster. So you need to kind of make sure that you address inefficiency, optimize your process, then infuse automation, then have human plus machine capability to strengthen your automation. >>Is it really that easy? Sounds easy, right? It, >>So from an, from an Accenture perspective, if you're, if you're looking at the market as a whole or looking at industry verticals, what's the difference between an organization that is leveraging automation and an organization that is not leveraging organ leveraging automation? Is there, is there sort of a range of percentage of efficiency that you can put on that? What does it mean for their bottom line? >>Essent, you must have data on this. Yeah, I mean what, >>Yeah, >>Today, today's world in the technology world, every organization understands the importance of automation that's given. That's a table stake. Now, where an organization is in the journey differs some of the enterprises maybe at the beginning of the maturity spectrum. In my book I talk about automation maturity framework wherein there are the initial stages of automation. Some of them are intelligent automation at the end of the spectrum where they're using data cloud and AI to drive the automation journey. But in every enterprise, the key success of automation depends upon whether you do automation and enterprisewide not in a silo in the organization, but if you do enterprise wide apply across, you get a lot more benefits, lot more efficiency to drive. >>Does does automation being more strategic or key? Does it, does it in a way make investments in automation more, more scrutinized or more circumspect? I, I would, I would use the term discretionary. We heard Bobby Patrick today say this is not discretionary, it's strategic to me. If it's strategic it might be a mandate but it's might be something I can kick down the road. What are you seeing there in the field just in terms of overall demand and sentiment? >>Automation today, as I said, is a table stake. When it becomes an integrated DNA of enterprise, it is always, you know, whether you want to call one pillar of strategy, key DNA of your strategic roadmap you are in investments have to be directly proportional to what you want to accomplish as your business KPIs to thrive and deliver your business with. Otherwise, if you do it as like a one off thing, you know you won't get the benefit. Yeah. >>Or from your standpoint, where do you want to take the automation initiative inside a whirlpool? How are you thinking about scaling it? What have you learned that you can apply to driving scale? >>So we put some strict governance in place who weren't just automating everything under the sun cuz >>Wild west >>Yeah, I can't support that. Right? So we made sure that everything had at least less than a one year invest return on investment and 500 hours worth of automation for us to even consider it as part of our coe. So because of that, we do have some automations that would make sense, but that's why we're looking at a citizen development program or low code, no code. What other types of options are there to make sure that it does become a part of our culture and dna that you can automate those even small parts of your workflow to, to make your day better. >>When, when you're looking at those workflows, do you, are you, are you literally looking over someone's shoulder with a stopwatch and measuring, Measuring how time >>And motion studies? No >>Question. Yeah. I mean is it time and motion studies? I mean, is that sort of the entry level data that that you use or is it more, or is it more automated than that? >>I would say it's a little more automated than that, but we do sit down and we ask our business process, show me what this process looks like to you. And then from that we can take some task mining and look at, okay, how long did it take you to do this? How often are you doing it? And then based on how long the automation would take, see how many hours are saved and how many people are doing that same task on a monthly, daily, weekly basis. >>Great. All right guys, thanks so much for coming in the cube and sharing your story. A whirlpool and always love to have Accenture on. You guys got such a massive observation space, global depth of industry. So thank you very much both. Thank you. Thank you. You're very welcome. All right, keep it right there. Dave Nicholson and Dave Ante will be back right to the short break, you watching the cubes coverage of UI path forward. Five live from Las Vegas.

>>we'll go back to the cubes. Coverage of the age of US Executive Summit at Davis. Reinvent made possible by Accenture My name is Dave Volunteer. We're gonna talk about the arm nation advantage, embraced the future of productivity, improve speed quality and customer experience through artificial intelligence. And we herewith Bhaskar goes, Who's the chief strategy Officer X censure in Rajendra RP Prasad is the senior managing director in Global Automation. The Accenture guys walk into the Cube. Get to seal. >>Thank you. >>Hey, congratulations on the new book. I know it's like giving birth, but it's a mini version. If the well, the automation advantage embraced a future of productivity, improve speed, quality and customer experience to artificial intelligence. What inspired you to write this book? Can you tell us a little bit more about it and how businesses are going to be able to take advantage of the information that's in there? Maybe you could start, >>so I think you know, if we say that what inspired as primarily the two things really style, you know, over inspired have to start this project in first of all is the technology change step change in the technology. Second is the mile maturity of the buyer maturity of the market when it's a little more, you know, when I talk about the technology change, automation is nothing new in the industry. In the starting from the Industrial Revolution, always, industry adopted the automation. But last few years would happen. That there is a significant change in the technology in terms of not of new technologies are coming together like cloud data, artificial intelligence, machine learning and they are gearing match you, and that created a huge opportunity in the industry. So that is number one second if fighting the maturity of the buyer. So buyers are always buying automation, adopting the automation. So when I talked to this different by a different industrial wire, suddenly we realise they're not asking about workings automation, how that will help. But primarily they're talking about how they can scaling. They have all have done the pilot, the prototype, how they can take the full advantage in their enterprise through scheme and talking to few client few of our clients, and he realised that it's best to write this boat and film all our clients to take advantage of this new technologies to skill up their business. If I give a little more than inside that one, exactly we are trying to do in this boat primarily, we dealt with three things. One is the individual automation which deals with the human efficiency. Second is the industrial automation who visited a group efficiency. And third is the intelligent automation. We deal city business, official efficiency while business value. So we believe that this is what will really change their business and help our client help the automation. It users to really make clear an impact in their business. >>Yeah, And so you talked about that? The maturity of the customer. And and I like the way you should describe that spectrum ending with intelligent automation. So the point is you not just paving the cow path, if you will, automating processes that maybe were invented decades ago. You're really trying to rethink the best approach. And that's where you going to get the most business value, our peace In thinking about the maturity, I think the a pre pandemic people were maybe a little reluctant s Bhaskar was saying maybe needed some education. But But how? If things change me, obviously the penned Emmick has had a huge impact. It's accelerated things, but but what's changed in the business environment? In terms of the need to implement automation? R. P >>thank you Well, that is an excellent question. As even through the pandemic, most of the enterprises accelerated what I call as the digital transformation, technology transformation and the war all time that it takes to do. The transformation is compressed in our most land prices. Now do compress transformation. The core of it is innovation and innovation, led technology and technology based solutions. To drive this transformation automation. Artificial intelligence becomes hot of what we do while we are implementing this accelerators. Innovation enablers within the enterprises, most of the enterprises prior to the pandemic we're looking automation and I as a solution for cost efficiency. Saving cost in DePina deriving capacity efficiency does if they do the transformation when we press the fast forward but draw the transformation journey liberating automation. What happens is most of the enterprises which the focus from cost efficiency to speed to market application availability and system resiliency at the core. When I speaking to most of the sea woes Corrine Wall in the tech transformation they have now embrace automation and air as a Conan able to bribe this journeys towards, you know, growth, innovation, lead application, availability and transformation and sustainability of the applications through the are A book addresses all of these aspects, including the most important element of which is compute storeys and the enablement that it can accomplish through cloud transformation, cloud computing services and how I I and Michelle learning take log technologies can in a benefit from transformation to the block. In addition, we also heard person talk about automation in the cloud zero automation taking journey towards the cloud on automation Once you're in the clouds, water the philosophy and principles he should be following to drive the motivation. We also provide holy holistic approach to dry automation by focusing process technology that includes talent and change management and also addressing automation culture for the organisations in the way they work as they go forward. >>You mentioned a couple things computing, storage and when we look at our surveys, guys is it is interesting to see em, especially since the pandemic, four items have popped up where all the spending momentum is cloud province reasons scale and in resource and, you know, be able the report to remotely containers because a lot of people have work loads on Prem that they just can automatically move in the company, want to do development in the cloud and maybe connect to some of those on from work clothes. R P A. Which is underscores automation in, of course, and R. P. You mentioned a computing storage and, of course, the other pieces. Data's We have always data, but so my question is, how has the cloud and eight of us specifically influenced changes in automation? In a >>brilliant question and brilliant point, I say no winner. I talked to my clients. One of the things that I always says, Yeah, I I is nothing but y for the data that is the of the data. So that date of place underlying a very critical part of applying intelligence, artificial intelligence and I in the organization's right as the organisation move along their automation journey. Like you said, promoting process automation to contain a realisation to establishing data, building the data cubes and managing the massive data leveraging cloud and how Yebda please can help in a significant way to help the data stratification Dana Enablement data analysis and not data clustering classification All aspects of the what we need to do within the between the data space that helps for the Lord scale automation effort, the cloud and and ablest place a significant role to help accelerate and enable the data part. Once you do that, building mission learning models on the top of it liberating containers clusters develops techniques to drive, you know the principles on the top of it is very makes it easier to drive that on foster enablement advancement through cloud technologists. Alternatively, using automation itself to come enable the cloud transformation data transformation data migration aspects to manage the complexity, speed and scale is very important. The book stresses the very importance of fuelling the motion of the entire organisation to agility, embracing new development methods like automation in the cloud develops Davis a cop's and the importance of oral cloud adoptions that bills the foundational elements of, you know, making sure you're automation and air capabilities are established in a way that it is scalable and sustainable within the organisations as they move forward, >>Right? Thank you for that r p vast crime want to come back to this notion of maturity and and just quite automation. So Andy Jossy made the phrase undifferentiated, heavy lifting popular. But that was largely last decade. Apply to it. And now we're talking about deeper business integration. And so you know, automation certainly is solves the problem of Okay, I can take Monday and cast like provisioning storage in compute and automate that great. But what is some of the business problems, that deeper business integration that we're solving through things? And I want to use the phrase they used earlier intelligent automation? What is that? Can you give an example? >>Let's a very good question as we said, that the automation is a journey, you know, if we talk to any blind, so everybody wants to use data and artificial intelligence to transform their business, so that is very simple. But the point is that you cannot reach their anti unless you follow the steps. So in our book, we have explained that the process that means you know, we defined in a five steps. We said that everybody has to follow the foundation, which is primarily tools driven optimise, which is process drivel. An official see improvement, which is primarily are driven. Then comes predictive capability, the organisation, which is data driven, and then intelligence, which is primarily artificial intelligence driven. Now, when I talked about the use of artificial intelligence and this new intelligent in the business, what the what I mean is basically improved decision making in every level in the organisation and give the example. We have given multiple example in this, both in a very simple example, if I take suppose, a financial secretary organisation, they're selling wealth management product to the client, so they have a number of management product, and they have number of their number of clients a different profile. But now what is happening? This artificial intelligence is helping their agents to target the night product for the night customers. So then, at the success rate is very high. So that is a change that is a change in the way they do business. Now some of the platform companies like Amazon on Netflix. He will see that this this killed is a very native skill for them. They used the artificial intelligence try to use everywhere, but there a lot of other companies who are trying to adopt this killed today. Their fundamental problem is they do not have the right data. They do not have the capability. They do not have all the processes so that they can inject the decision making artificial intelligence capability in every decision making to empower their workforce. And that is what we have written in this book. To provide the guidance to this in this book. How they can use the better business decision improved the create, the more business value using artificial intelligence and intelligent automation. >>Interesting. Bhaskar are gonna stay with you, you know, in their book in the middle of last decade, Erik Brynjolfsson and Andy McAfee wrote the second Machine Age, and they made a point in the book that machines have always replaced humans in instead of various tasks. But for the first time ever, we're seeing machines replacing human in cognitive task that scares a lot of people so hardy you inspire employees to embrace the change that automation can bring. What what are you seeing is the best ways to do that? >>This is a very good question. The intelligent automation implementation is not, Iet Project is primarily change management. It's primarily change in the culture, the people in the organisation into embrace this change and how they will get empowered with the machine. It is not about the replacing people by machine, which has happened historically into the earlier stages of automation, which I explained. But in this intelligent automation, it is basically empowering people to do the better. Dwelled the example. That is the thing we have written in the book about about a newspaper, 100 years old newspaper in Italy. And you know, this industry has gone through multiple automation and changes black and white printing, printing to digital. Everything happened. And now what is happening? They're using artificial intelligence, so they're writers are using those technologies to write faster. So when they are writing immediately, they're getting supported with the later they're supporting with the related article they are supporting with this script, even they're supported to the heading of this article. So the question is that it is not replacing the news, you know, the content writer, but is basically empowering them so that they can produce the better quality of product they can, better writing in a faster time. So is very different approach and that is why is, um, needs a change management and it's a cultural change. >>Garden R P What's it for me? Why should we read the automation advantage? Maybe you can talk about some of the key takeaways and, you know, maybe the best places to start on an automation journey. >>Very will cut the fastest MP, Newer automation journey and Claude Adoption Journey is to start simple and start right if you know what's have free one of the process, Guru says, If you don't know where you are on a map, a map won't help you, so to start right, a company needs to know where they are on a map today, identify the right focus areas, create a clear roadmap and then move forward with the structured approach for successful our option. The other important element is if you automate an inefficient process, we are going to make your inefficiency run more efficiently. So it is very important to baseline, and then I established the baseline and know very or on the journey map. This is one of the key teams we discuss in the Automation Advantis book, with principles and tips and real world examples on how to approach each of these stages. We also stress the importance of building the right architecture is for intelligent automation, cloud enablement, security at the core of automation and the platform centric approach. Leading enterprises can fade out adopters and Iraq, whether they are in the early stages of the automation, journey or surrender advanced stage the formation journey. They can look at the automation advantage book and build and take the best practises and and what is provided as a practical tips within the book to drive there. Automation journey. This also includes importance of having right partners in the cloud space, like a loveliest who can accelerate automation, journey and making sure accompanies cloud migration. Strategy includes automation, automation, lead, yea and data as part of their journey. Management. >>That's great. Good advice there. Bring us home. Maybe you can wrap it up with the final final world. >>So, lefty, keep it very simple. This book will help you to create difference in your business with the power of automation and artificial intelligence. >>That's a simple message and will governor what industry you're in? There is a disruptions scenario for your industry and that disruption scenarios going to involve automation, so you better get ahead of editor game. They're The book is available, of course, at amazon dot com. You can get more information. X censure dot com slash automation advantage. Gosh, thanks so much for coming in the Cube. Really appreciate your time. >>Thank you. Thank >>you. >>Eh? Thank you for watching this episode of the eight of US Executive Summit of reinvent made possible by Accenture. Keep it right there for more discussions that educating spy inspire You're watching the queue.

(upbeat music) >> Welcome back to the Cube's coverage of the AWS Executive Summit at AWS re:Invent made possible by Accenture. My name is Dave Vellante. We going to talk about The Automation Advantage, embrace the future of productivity, and improve speed quality and customer experience through artificial intelligence. And we're here with Bhaskar Ghosh who is the Chief Strategy Officer at Accenture and Rajendra 'RP' Prasad who is a Senior Managing Director and Global Automation Lead at Accenture. Guys, welcome to the cube, good to see you. >> Good to see you. >> Hello, David, thank you. >> Hey, congratulations on the new book. I know it's not like giving birth, but it's a mini version if you will. The automation advantage embraced a future of productivity, improved speed, quality, and customer experience through artificial intelligence. What inspired you to write this book? Can you tell us a little bit more about it, and how businesses are going to be able to take advantage of the information that's in there? That's great. Maybe you could start. >> Okay. So I think, you know, if we say that what inspired us, primarily the two things really inspired us to start this project. First of all, is the technology change, step change in the technology. Second is the maturity of the buyer, maturity of the market. So let me explain a little more. When I talk about the technology change, automation is nothing new in the industry, starting from the industrial revolution, always industry adopted the automation. But last few years, what happened, that there is a significant change in the technology in terms of lot of new technologies are coming together like Cloud, Data, Artificial Intelligence, machine learning, and they are getting matured. I think that created a huge opportunity in the industry. So that is number one. Second thing I think the maturity of the buyer. So buyers are always buying the automation, adopting the automation. So when I talk to this different buyer, different industrial buyer, suddenly we realize, they are not asking about what is automation. How that will help. But primarily they're talking about how they can scale it. They have all have done the pilot, the prototype, how they can take the full advantage in that enterprise to scale. And after talking to a few clients, few of our clients, they don't realize that it would be best to write this book and help all our clients to take advantage of this new technologies to scale up their business. If I give them a little more insight that what exactly we are trying to do in this book, primarily we dealt with three things. One is the individual automation, which deals with the human efficiency. Second is the industrial automation, which deals with the group efficiency . And third is the intelligent automation, which deals with the business efficiency or business value. So we believe that, this is what will really change their business and help our client help the automation IT users to really make an impact in their business. >> Yeah, and so you talked about that, the maturity of the customer and I liked the way you sort of described that spectrum ending with intelligent automation. So the point is you're not just paving the cow path if you will, automating processes that maybe were invented decades ago, you're really trying to rethink the best approach. And that's where you going to get the most business value and RP in thinking about the maturity, I think in pre-pandemic, people were maybe a little reluctant or as Bhaskar was saying, maybe needed some education. But how have things changed? Obviously the pandemic has had a huge impact. It's accelerated things. But what's changed in the business environment in terms of the need to implement automation, RP? >> Thank you for that is an excellent question. As we went through the pandemic, most of the enterprises accelerated what I call as the digital transformation. Technology transformation. And the overall time that it takes to do the transformation has compressed. Most of the enterprises now do compress transformation. The core of it is innovation and innovation led technology and technology based solutions. To drive this transformation, automation, artificial intelligence becomes part of what we do, while we are implementing these accelerators, innovation enablers within the enterprises. Most of the enterprises prior to the pandemic, we're looking, automation and AI as a solution for cost efficiency, saving costs and not deriving capacity efficiency as if they do the transformation (indistinct). Let me press the fast forward button through the transformation journey, leveraging automation. What happens is most of the enterprises switch the focus from cost efficiency to speed, to market, application availability and system resiliency are the core. When I speak to most of the CIO's, who are involved in the tech transformation, they now embrace automation and AI as a core enabler to drive this journeys towards, growth, innovation led, application availability and transformation and sustainability of the applications through their journey. Our book addresses, all of these aspects, including the most important element of AI, which is compute, storage and the enablement that it can accomplish through cloud transformation, cloud computing services and how AI and machine learning technologies can benefit from transformation to the cloud. In addition, we also address and talk about automation in the cloud. Automation, taking journey towards the cloud and automation, once you are in the cloud, what are the philosophy and principles you should be following to drive that automation? We also provide holistic approach to drive automation by focusing process technology that includes talent and change management, and also addressing automation culture for the organizations in the way they work as they move forward. >> So you mentioned a couple of things, compute and storage and when we look at our surveys, guys, it's interesting to see, especially since the pandemic, four items have popped up, where all the spending momentum is cloud, but for obvious reasons, scale and resource, and be able to work remotely, contain us because a lot of people have workloads on prem that they just can't automatically move into cloud, but they want to do development in the cloud and maybe connect to some of those on-prem workloads, RPA, which is _automation, and of course, AI. And, RP, you mentioned compute and storage, and of course the other pieces' data. So we have all this data. But so my question is, how has the cloud and AWS specifically influenced changes in automation in AI? >> Brilliant question and brilliant point. I say, whenever I talk to my clients, one of the things that I always say is, AI is nothing but an UI for the data. Let me repeat that, AI is the UI of the data. So that data plays a underlying and very critical part of applied intelligence, artificial intelligence and AI in the organizations, right? As the organization move along their automation journey, like you said, robotic process automation to containerization, to establishing data, building the data cubes and managing the massive data leveraging cloud and how AWS can help in a significant way to help the data stratification, data enablement, data analysis, and data clustering, classification, all aspects of that what we need to do within the data space. That helps for the large scale automation effort. The cloud and AWS plays a significant role to help accelerate and enable the data part. Once you do that, building machine learning models on the top of it, leveraging containers, clusters, DevOps techniques to drive, the AI principles on the top of it is very, it's kind of makes it easier to drive that and foster enablement advancement through cloud technologies. Alternatively, using automation itself to kind of enable the cloud transformation, data transformation, data migration aspects to manage the complexity speed and scale is very important. The book stresses the very importance of fueling the motion of the entire organization through agility, embracing new development, whether it's like automation in the cloud, DevOps, DevSecOps and the importance of oral cloud adoption that builds the foundational elements of making sure your automation and AI capabilities are established in a way that it is scalable and sustainable within the organizations as they move forward. >> Great. Thank you for that, RP. Bhaskar, I want to come back to this notion of maturity and just apply it to automation. So, Andy Jassy made the phrase, undifferentiated heavy lifting popular, but that was largely last decade applied to IT. And now we're talking about deeper business integration. And so, automation certainly solves the problem of, okay, I got to take mundane tasks like provisioning, storage, and compute and automate that. Great. But what are some of the business problems that deeper business integration that we're solving through things that, and I want to use the phrase that you used earlier, intelligent automation. What is that? And can you give an example? >> That's a very good question. As we said, that the automation is a journey. If we talk to any clients, so everybody wants to use data and artificial intelligence to transform their business. So that is very simple, but the point is that you cannot reach there unless you follow the steps. So in our book we have explained the process. That means, we defined in a five steps. We said that everybody has to follow the foundation which is primarily the tools driven, optimize, which is process-driven then efficiency improvement, which is primarily RPA driven, then comes predictive capability, the organization, which is data driven and then intelligence, which is primarily artificial intelligence driven. Now, when I talk about the use of artificial intelligence and this new intelligent ID in the business, what we mean is basically improved decision-making in every level in the organization. I'll give you an example. We have given multiple example in this book and a very simple example if I take. Suppose a financial sector organization, they're selling wealth management product to the clients. So they have a number of wealth management products and they have number, there are number of clients with different profile, but now what is happening, this artificial intelligence is helping their agents to target the right product for the right customer, so that the success rate is very high. So that is a change. That is a change in the way they do business. Now, some of the platform companies like Amazon and Netflix, you will see that this skill is a very native skill for them. They use the artificial intelligence, try to use everywhere. But there are a lot of other companies who are trying to adopt this skill today. Their fundamental problem is that they do not have the right data. They do not have that capability. They do not have all the processes so that they can inject the decision-making artificial intelligence capability in every decision-making to empower their workforce. And that is what we have written in this book to provide the guidance to this in this book. How they can use the better business decision, improve then create the more business value using artificial intelligence and intelligent automation. >> Interesting, Bhaskar, I want to stay with you, in their book, in the middle of last decade, Erik Brynjolfsson and Andy McAfee wrote. The Second Machine Age and they made the point in the book that machines have always replaced humans in sort of various tasks, but for the first time ever, we're seeing, machines replacing humans in cognitive tasks, and that scares a lot of people. So how do you inspire employees to embrace the change that automation can bring? What are you seeing as the best ways to do that? >> That's a very good question. Intelligent automation implementation is not an IT project. It's primarily change management. It's primarily change in the culture. The people in the organization need to embrace this change and how they will get empowered with the machine. It is not about the replacing people by machine, which has happened historically into the earliest stages of automation, which I explained. But in this intelligent automation, it is basically empowering people to do the better job. I will give you example. That is the thing we have written in the book, about a newspaper, a hundred years old newspaper in Italy. And this industry has gone through multiple automation and changes. So black and white printing to color, printing to digital, everything happened. And now what is happening, they are using artificial intelligence, so their writers are using those technologies to write faster, so when they're writing immediately, they are getting supported with the data, they are supporting with the related article. They are supporting with the script, even they're supported with the heading of this article. So the question is that it is not replacing the news, the content writer, but it's basically empowering them so that they can produce the better quality of product, they can be better at writing in a faster time. So it's a very different approach and that is why this needs a change management than a cultural change. >> Got it. RP, what's in it for me? Why should we read the automation advantage? Maybe you could talk about some of the key takeaways and maybe the best places to start on an automation journey. >> Very good question. The fastest step in your automation journey and cloud adoption journey is to start simple and start right. If you know what's happening, one of the process guru says, "If you don't know where you are on a map, a map won't help you." So to start right, a company needs to know where they are on a map today, identify the right focus areas, create a clear roadmap and then move forward with a structured approach for successful adoption. The other important element is if you automate an inefficient process, you are going to make your inefficiency run more efficiently. So it is very important to baseline and establish the baseline and know where you are on the journey map. This is one of the key themes we discuss in the Automation Advantage book. With principles and tips and real world examples on how to approach each of these stages. We also stress the importance of building the right architectures for intelligent automation, cloud enablement, security at the core of automation and the platform centric approach. Leading enterprises can fit on adopters and whether they are in the earlier stages of the automation journey or they're in the advanced stage of automation journey. They can look at the Automation Advantage book and build and take the best practices and what is provided as a practical tips within the book to drive their automation journey. This also includes importance of having right partners in the cloud space like AWS, who can accelerate automation journey and making sure a company's cloud migration strategy includes automation, automation-led AI and data as part of their journey management. >> That's great. Good advice there. But Bhaskar, bring us home, maybe you could wrap it up with the final word. >> So let me keep it very simple. This book will help you to create difference in your business with the power of automation and artificial intelligence. >> That's a simple message. And no matter what industry you're in, there is a disruption scenario for your industry, and that disruption scenario is going to involve automation. So you better get ahead of the game there. The book is available of course, at Amazon.com and you can get more information at accenture.com/automationadvantage. Guys, thanks so much for coming in the Cube. I really appreciate your time. >> Thank you. >> Thank you. >> And thank you for watching this episode of the AWS Executive Summit at re:Invent made possible by Accenture. Keep it right there for more discussions that educate and inspire, you're watching the Cube. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World digital experience brought to you by Dell Technologies. Hey, Welcome back, everybody. Jeffrey here with the Cube. Welcome back to our ongoing coverage of Dell Technology. World 2020. The digital experience, Uh, not in person like nothing this year, 2020. But the digital experience allows to do a lot of things that you couldn't do in person. And we're excited to have our next guest. He is Deepak Prasad, the director of product management for Dell Technologies. Cloud deep. Uh, great to see you. >>Hello, Jeff. Nice to meet you as well. >>You too. So let's let's back up, like, 10,000 square feet, cause you know, Cloud came in with a big giant rage. I guess it's been a while now with AWS and Public Cloud. And people are putting their depth tests on there. And, you know, we've seen this explosion of public cloud, and then we have hybrid cloud and multi cloud. And then, you know, basically people figured out that not everything can go to a public cloud. A lot of stuff. Shouldn't some stuffs gonna stay in data centers? for all different reasons, >>but >>basically it's horses for courses. So we're a little ways into this. How are you guys, Adele, really thinking about Cloud and helping your customers think about what cloud is beyond, you know, kind of the hype. >>Well, that's a great question, Jeff. At Dell, we think of Cloud really as an operating model and as an operating experience rather than a destination. So it's interesting that you bring up Public Cloud and Private Cloud, but we take a step back and think of what does that experience really represent? So if you think off, uh, you know what defines that cloud operating model? It's, ah, democratization of technology. Access off resource is through a p. I s through self service portals ability to pay as you go in a very simplified commerce experience and the agility of cloud. You know, the promise off instant availability of infinite scalability. Now, if if you look at you know the landscape around this until now, that has only been delivered in a consistent way by public cloud vendors, which leads people to believe that really cloud is the destination, not an operating model. But we think that we are capable of bringing those experiences those tenets off the cloud operating model to the on premises experience and really taking location out of the conversation. So this really allows our customers to focus mawr on their workloads than visions. They want to drive, and then they can fit there, uh, requirements their application requirements to the location where those resource is our regardless of having toe worry about it. This is public or private. They will get the same operating experience. They will get the same scalability, the same simplified commerce, the same access Thio resource is >>right. Well, let's talk about some of some of those things because, as you said, there's a lot of behaviors that are involved in cloud and cloud operating. You know, one of the behaviors that I think gave the public cloud an early leg up was just simply provisioning, right? Simply, if somebody needs some capacity, they need some horsepower to get interesting. It would be tested in the early days. No, they didn't have to provision. They didn't have to put in an order with I t and wait for so long to get a box assigned to them or purchased or whatever, right? They just swipe the credit card and went, How have you kind of help People have that kind of ease of use ease of, uh, he's of spin up piece of creation on what the right verb is because I think that's a really core piece of what enabled early cloud adoption. >>No, absolutely, you're spot on. And that was a big part of it that if somebody needed resource is instead of waiting for weeks and months, they could go on and and sign up for those resource and get almost instantaneous access. And we believe that what we're doing in this area is really transforming the business. Today. We can deliver resource is to customers in their data center in 14 days and really are aggressively looking to cut that down further. So what this really means is not just shipping Resource is in 14 days, but actually delivering a cloud experience in the customer's data center or of cola location, whatever, you know, location of their choice in 14 days and making that available to the customers, not just through the traditional procurement process. But we're actually very proud to announce the cloud Council, the Dell Technologies Cloud Council, through which customers can, in a self service way, order those ordered those resource is and have it show up and be operational in their environment in 14 days. So we're really bringing that speed of cloud to the on premise experience, >>right? So how how does it actually work? Do you pre? Do you pre ship some amount of capacity beyond what you believe is currently needed just to kind of forward que you will, if you will capacity. How does it work from from both the implementation strategy in terms of the actual compute and storage capacity, as well as on kind of the purchasing peace? Because those air to kind of very >>different work flows? No, that's a That's a great question. So for us, our strength are really in supply chain management that allows us to build capabilities across the world in areas from where we can ship the customers almost on the on demand basis. So as soon as we get in order that the customer needs a probably probably cloud deployment in a certain location, were able to mobilize those resource is from those locations and have it instance she hated in customers environ. So it's really built a strength off over the years off optimizing supply chain, if you will, and just bring taking that to the next level off. >>Okay, so we don't, >>uh environment we said. Yeah, >>no problem. I was gonna say the another great characteristics of cloud right is is spinning up, which we hear about all the time versus spinning down and write. The easiest example is always use. If you're running, you know, some promotion. If your pizza hut you're running a promotion for the Super Bowl, obviously, right? Your demand for that thing is gonna be huge. You want to spin up to be able to take advantage of all the people cash in their coupon, and then when the Super Bowls over, >>you >>want to spend those resource is down because you're not going to necessarily need that capacity. How do you guys accomplish that type of flexibility in your solution? >>So in our subscription model, we have different ways to address customer environment. So we allow customers to start very small and then and then grow the subscription as the requirements growth and the key thing of our subscription, which is really unique, is the ability to quote Terminate. So, for example, if if a customer started off on the three year subscription with the, uh resource is for, say, 100 virtual machines and somewhere along the way they needed to add resource is for 50 more virtual machines, so they will pay for the 150 virtual machines. But that extra 50 virtual machines does not create an orphan or a child subscription. At the end of three years, everything terminates together, so it really gives them flexibility with, you know, ability to start small and not have to worry about vendor lock in. And now we started off with sort of a reserved instance type off subscription model. But we're definitely bringing usage based models as well, which allows more, even more flexibility with respect to speeding up and speeding down. Right. >>And then what are some of the real specific reasons that people go for this type of solution versus a public cloud where some of the rial inherent advantages of doing this within my own infrastructure, my own data center, my own, you know, kind of virtual four walls, if you will. >>Yeah, you know, we strongly believe that the decision should really be guided by workload requirements. There's certain workloads that work really well in on premises environment. For example, you could take virtual desktop environments V. D. I. That works really well from a performance standpoint in In on premise, environment versus a public cloud environment. Similarly, there are other workloads were not public cloud deniers that that are best suited for public cloud. But it's really it should be something that's that comes from understanding your application. Understanding the leighton see requirements, understanding the data requirements for those applications. You know, what are your egress? Uh, issues. Or, you know, uh, the profile off the workload that you're trying to implement That should really be the driving force in where the workload this place >>and then, uh, tell us a little bit about the partnership with VM Ware because that's a huge asset that you have, you know, now you know, basically side by side and you can leverage the technology as well as a lot of the assets that are envy. And where how does that change? The way you guys have taken the Dell Cloud platform to market >>it really is a a differentiating factor for us. From a technology standpoint, it allows us to bring the best of both worlds best off off the hardware infrastructure as well as the best off the cloud. Stack the cloud software infrastructure together in one cohesive and and well developed package. So, uh, the Dell Technologies Cloud Platform from a technology standpoint is implemented with our VX rail appliances, which is a hyper converge infrastructure as well as VM ware clad foundation from a software standpoint. Now the code developed and jointly engineered capabilities allow for unique, unique feature off. Remember Cloud Foundation, where it can do lifecycle management off the entire stack, both the hardware and the software from a single interface. So it understands Vieques rails and understands the different form where levels and the X, where manager software versions etcetera. And then it would automatically select what is the best and well tested and supported software bundle that could be deployed without causing, you know, typical issues with version mismatches and trying to chase down different hardware compatibility, matrices, etcetera. All of those are eliminated, so it's a integrated lifecycle management experience. That's great. E. I'm sorry I have >>a little bit, a little bit of a lot of here, so I I apologize. >>I >>was just gonna say you've been at this for a while. Your product, you know, product management. So you're really thinking about speeds and feeds and you're thinking about roadmap and futures? I wonder if you can share your perspective on this evolution from kind of this race of to pure public cloud to this. This big discussion I think we had packed Elson. You're talking about a hybrid cloud back at being where 2013. So then, you know kind of this hybrid cloud and multi cloud and really kind of this maturation of this space as we as we've progressed for Ah, while now probably 10 years. >>Yeah. Yeah. And, uh, majority of our customers live in a multi cloud world. They have resource is that they consumed from one or more multi hyper sorry, uh, public cloud vendors and they have one or more on premise vendors as well, For their resource is and managing that complex environment across multiple providers with different skill set different tools, different sls. While it sounds really interesting to, you know, have workload drive your your deployment and place the workloads where they're best suited. It does prevent. It does present a challenge off managing a complex and and getting even more complex by the day, multi cloud environment. And that's where we think we have an advantage. Uh, based on some of the work that we're doing with the Dell Technologies Cloud console to bring a true multi cloud experience to our customers. Not one of the benefits of not being a, you know, a public cloud provider is that we are agnostic toe. All public cloud providers were fully accepting that certain workloads need to live in those environments. And through our cloud council, we will make it easy for customers to manage not only their on premises, assets and on premises. Cloud resource is, but also cloud resource is that reside in multiple public cloud vendors? >>That's good. Yeah, because it helps, right, because they've got stuff everywhere. It's like that, you know, there is no del technology, right? There's a lot of there's a lot of people that work there. There's a lot of project. There's a lot of, you know, kind of pieces to that puzzle. I wonder too. If you could share your perspective on kind of application modernization, right, That's always another big, you know, kind of topic. You should You should you take those old legacy APS. And could you should you try to rebuild them in, um, or cloud native way using containers and and all this flexibility and deploy them or, you know, which one. Should you just leave alone right there, running fine. They've been running fine for a while. They've got some basic core functionality that may be do or don't need toe to kind of modernize if you will. And maybe those resources should be spent on building in a new applications and new kind of areas of competitive differentiation. When you're working with their clients, how do you tell them to think about at modernization? >>Yeah, we looked at it from a business requirement standpoint. Off how what end goals. A customer trying to achieve through that application. And in some cases, you know, on you cover the spectrum, right there. Some cases modernization just means swapping out the hardware and putting it, putting that application on a more modern, more powerful hardware. At the other end, it z you know, going toe assassin model off, you know, everything available through through a cloud application. And in between those two extremities, there's, you know, virtualization that is re factoring this continual ization and micro services based implementation. But it comes down to understanding why that application is meant to deliver for who and what business requirements and business objectives that fulfills. That's how we use as a guiding principle on how to position application modernization to customers. >>All right, that's super helpful, because I'm sure that's a big topic. And, you know, there's probably certain APS that you just should not. You just shouldn't touch. You should probably just even Malone. They're running just fine. Let them do their thing. All >>right, fine. I'm sorry. No. Is this interesting? I was a conversation with the customer just earlier today where they have a portion off their infrastructure of some applications that they absolutely wanted to leave alone and and just change out the underlying hardware. But there are other applications where they really want to adopt, continue ization and re factor those out, rewrite those applications so that they can have more scalability and more flexibility around that. So it really is is determined by the needs. Yeah. >>Um so last question, del Tech world this year was a digital experience, like all the other shows that we've seen here in 2020 just But it's a huge event, right? A big, big show, and we're excited to be back to cover it again. But I'm curious if there's some special announcements within such a big show. Sometimes things get lost a little bit here in there, but any special announcements You want to make sure that get highlighted that people may have missed within this kind of see if content over the last several days >>22 major things that that I'm very excited to share with you One is Dell Technologies Cloud platform. We actually discussing and talking about Dell Technologies cloud platform in the concept off instant capacity blocks. So in the past, we talked about it with respect to notes. Uh, you know, adult technology cloud platform. You can have, you know, so many notes in it to power your your on premises. Cloud resource is but really have changed the conversation and look into how cloud customers air consuming those resource is and we really want to drive focus to that and introduced the concept of instance Capacity blocks instances are think of it as a workload profile, you know, CPU and memory put together and then, uh, in different combinations in a pre defined way to address different workload needs. So this really changes the conversation for our customers that they don't have to worry about designing or or speaking out the hardware platforms, but really understand how many resource is they need, how many, how much you know, processing power, how much memory, how much stories they need and they define their requirements was in those terms, and we will deliver those instance capacity blocks to them in their data centers. So behind the scenes is built by best in class. Uh, you know, hardware from Vieques rails and best in class software from being where, but it's really delivered in terms off instant capacity blocks. The second interesting thing that I wanna share with you and I profession a few times is Dell Technologies Cloud console. We're building this single pane of glass to manage our customers entire journey from on premises to multi cloud hybrid cloud with consistency off. How you can discover services how you can order services and how you can grow your the manager footprint. So those are a couple things from adult technology standpoint that we're really excited to share with people. >>Well, congratulations. I know you've been busting your tail for for quite a while on these types of projects, and it's nice to be able to finally release him out to the world. >>Well, it's just my pleasure. Alright. Thank you very much. >>Well, thank you for stopping by again. Congratulations. And will continue the ongoing coverage of Dell Technology World 2020. The digital experience. I'm Jeff Frick. He's to Park Prasad. You're watching the Cube. See you next time. Thanks for watching.

>> Narrator: From around the globe, it's theCube. With digital coverage of VMworld 2020. Brought to you by VMware and its ecosystem partners. >> Hello, and welcome back to theCube virtual coverage of VMworld 2020. I'm John Furrier, host of theCube. VMworld's not in person this year, it's on the virtual internet. A lot of content, check it out, vmworld.com, a lot of great stuff, online demos, and a lot of great keynotes. Here we got a great conversation to unpack, the NVIDIA, the AI and all things Cloud Native. With Krish Prasad, who's the SVP and GM of Cloud Platform, Business Unit, and Manuvir Das head of enterprise computing at NVIDIA. Gentlemen, great to see you virtually. Thanks for joining me on the virtual Cube, for the virtual VMworld 2020. >> Thank you John. >> Pleasure to be here. >> Quite a world. And I think one of the things that obviously we've been talking about all year since COVID is the acceleration of this virtualized environment with media and everyone working at home remote. Really puts the pressure on digital transformation Has been well discussed and documented. You guys have some big news, obviously on the main stage NVIDIA CEO, Jensen there legend. And of course, you know, big momentum with with AI and GPUs and all things, you know, computing. Krish, what are your announcements today? You got some big news. Could you take a minute to explain the big announcements today? >> Yeah, John. So today we want to make two major announcements regarding our partnership with NVIDIA. So let's take the first one, and talk through it and then we can get to the second announcement later. In the first one, as you well know, NVIDIA is the leader in AI and VMware as the leader in virtualization and cloud. This announcement is about us teaming up, deliver a jointly engineered solution to the market to bring AI to every enterprise. So as you well know, VMware has more than 300,000 customers worldwide. And we believe that this solution would enable our customers to transform their data centers or AI applications running on top of their virtualized VMware infrastructure that they already have. And we think that this is going to vastly accelerate the adoption of AI and essentially democratize AI in the enterprise. >> Why AI? Why now Manuvir? Obviously we know the GPUs have set the table for many cool things, from mining Bitcoin to really providing a great user experience. But AI has been a big driver. Why now? Why VMware now? >> Yes. Yeah. And I think it's important to understand this is about AI more than even about GPUs, you know. This is a great moment in time where AI has finally come to life, because the hardware and software has come together to make it possible. And if you just look at industries and different parts of life, how is AI impacting? So for example, if you're a company on the internet doing business, everything you do revolves around making recommendations to your customers about what they should do next. This is based on AI. Think about the world we live in today, with the importance of healthcare, drug discovery, finding vaccines for something like COVID. That work is dramatically accelerated if you use AI. And what we've been doing in NVIDIA over the years is, we started with the hardware technology with the GPU, the Parallel Processor, if you will, that could really make these algorithms real. And then we worked very hard on building up the ecosystem. You know, we have 2 million developers today who work with NVIDIA AI. That's thousands of companies that are using AI today. But then if you think about what Krish said, you know about the number of customers that VMware has, which is in the hundreds of thousands, the opportunity before us really now is, how do we democratize this? How do we take this power of AI, that makes every customer and every person better and put it in the hands of every enterprise customer? And we need a great vehicle for that, and that vehicle is VMware. >> Guys, before we get to the next question, I would just want to get your personal take on this, because again, we've talked many times, both of you've been on theCube on this topic. But now I want to highlight, you mentioned the GPU that's hardware. This is software. VMware had hardware partners and then still software's driving it. Software's driving everything. Whether it's something in space, it's an IOT device or anything at the edge of the network. Software, is the value. This has become so obvious. Just share your personal take on this for folks who are now seeing this for the first time. >> Yeah. I mean, I'll give you my take first. I'm a software guy by background, I learned a few years ago for the first time that an array is a storage device and not a data structure in programming. And that was a shock to my system. Definitely the world is based on algorithms. Algorithms are implemented in software. Great hardware enables those algorithms. >> Krish, your thoughts. we live we're living in the future right now. >> Yeah, yeah. I would say that, I mean, the developers are becoming the center. They are actually driving the transformation in this industry, right? It's all about the application development, it's all about software, the infrastructure itself is becoming software defined. And the reason for that is you want the developers to be able to craft the infrastructure the way they need for the applications to run on top of. So it's all about software like I said. >> Software defined. Yeah, just want to get that quick self-congratulatory high five amongst ourselves virtually. (laughs) Congratulations. >> Exactly. >> Krish, last time we spoke at VMworld, we were obviously in person, but we talked about Tanzu and vSphere. Okay, you had Project Pacific. Does this expand? Does this announcement expand on that offering? >> Absolutely. As you know John, for the past several years, VMware has been on this journey to define the Hybrid Cloud Infrastructure, right? Essentially is the software stack that we have, which will enable our customers to provide a cloud operating model to their developers, irrespective of where they want to land their workloads. Whether they want to land their workloads On-Premise, or if they want it to be on top of AWS, Google, Azure, VMware stack is already running across all of them as you well know. And in addition to that, we have around, you know, 4,000, 5,000 service providers who are also running our Platform to deliver cloud services to their customers. So as part of that journey, last year, we took the Platform and we added one further element to it. Traditionally, our platform has been used by customers for running via VMs. Last year, we natively integrated Kubernetes into our platform. This was the big re architecture of vSphere, as we talked about. That was delivered to the market. And essentially now customers can use the same platform to run Kubernetes, Containers and VM workloads. The exact same platform, it is operationally the same. So the same skillsets, tools and processes can be used to run Kubernetes as well as VM applications. And the same platform runs, whether you want to run it On-Premise or in any of the clouds, as we talked about before. So that vastly simplifies the operational complexity that our customers have to deal with. And this is the next chapter in that journey, by doing the same thing for AI workload. >> You guys had great success with these Co-Engineering joined efforts. VMware and now with NVIDIA is interesting. It's very relevant and is very cool. So it's cool and relevant, so check, check. Manuvir, talk about this, because how do you bring that vision to the enterprises? >> Yeah, John, I think, you know, it's important to understand there is some real deep Computer Science here between the Engineers at VMware and NVIDIA. Just to lay that out, you can think of this as a three layer stack, right? The first thing that you need is, clearly you need the hardware that is capable of running these algorithms, that's what the GPU enable. Then you need a great software stack for AI, all the right Algorithmics that take advantage of that hardware. This is actually where NVIDIA spends most of its effort today. People may sometimes think of NVIDIA as a GPU company, but we have much more a software company now, where we have over the years created a body of work of all of the software that it actually takes to do good AI. But then how do you marry the software stack with the hardware? You need a platform in the middle that supports the applications and consumes the hardware and exposes it properly. And that's where vSphere, you know, as Krish described with either VMs or Containers comes into the picture. So the Computer Science here is, to wire all these things up together with the right algorithmics so that you get real acceleration. So as examples of early work that the two teams have done together, we have workloads in healthcare, for example. In cancer detection, where the acceleration we get with this new stack is 30X, right? The workload is running 30 times faster than it was running before this integration just on CPUs. >> Great performance increase again. You guys are hiring a lot of software developers. I can attest to knowing folks in Silicon Valley and around the world. So I know you guys are bringing the software jobs to the table on a great product by the way, so congratulations. Krish, Democratization of AI for the enterprise. This is a liberating opportunity, because one of the things we've heard from your customers and also from VMware, but mostly from the customer's successes, is that there's two types of extremes. There's the, I'm going to modernize my business, certainly COVID forcing companies, whether they're airlines or whatever, not a lot going on, they have an opportunity to modernize, to essentially modern apps that are getting a tailwind from these new digital transformation accelerated. How does AI democratize this? Cause you got people and you've got technology. (laughs) Right? So share your thoughts on how you see this democratizing. >> That's a very good question. I think if you look at how people are running AI applications today, like you go to an enterprise, you would see that there is a silo of bare metal sun works on the side, where the AI stack is run. And you have people with specialized skills and different tools and utilities that manage that environment. And that is what is standing in the way of AI taking off in the enterprise, right? It is not the use case. There are all these use cases which are mission critical that all companies want to do, right? Worldwide, that has been the case. It is about the complexity of life that is standing in the way. So what we are doing with this is we are saying, "hey, that whole solution stack that Manuvir talked about, is integrated into the VMware Virtualized Infrastructure." Whether it's On-Prem or in the cloud. And you can manage that environment with the exact same tools and processes and skills that you traditionally had for running any other application on VMware infrastructure. So, you don't need to have anything special to run this. And that's what is going to give us the acceleration that we talked about and essentially hive the Democratization of AI. >> That's a great point. I just want to highlight that and call that out, because AI's every use case. You could almost say theCube could have AI and we do actually have a little bit of AI and some of our transcriptions and work. But it's not so much just use cases, it's actually not just saying you got to do it. So taking down that blocker, the complexity, certainly is the key. And that's a great point. We're going to call that out after. Alright, let's move on to the second part of the announcement. Krish Project Monterey. This is a big deal. And it looks like a, you know, kind of this elusive, it's architectural thing, but it's directionally really strategic for VMware. Could you take a minute to explain this announcement? Frame this for us. >> Absolutely. I think John, you remember Pat got on stage last year at Vmworld and said, you know, "we are undertaking the biggest re architecture of the vSphere platform in the last 10 years." And he was talking about natively embedding Kubernetes, in vSphere, right? Remember Tanzu and Project Pacific. This year we are announcing Project Monterrey. It's a project that is significant with several partners in the industry, along with NVIDIA was one of the key partners. And what we are doing is we are reimagination of the data center for the next generation applications. And at the center of it, what we are going to do is rearchitect vSphere and ESX. So that the ESX can normally run on the CPU, but it'll also run on the Smart Mix. And what this gives us is the whole, let's say data center, infrastructure type services to be offloaded from running on the CPU onto the Smart Mix. So what does this provide the applications? The applications then will perform better. And secondly, it provides an extra layer of security for the next generation applications. Now we are not going to stop there. We are going to use this architecture and extended it so that we can finally eliminate one of the big silos that exist in the enterprise, which is the bare metal silo. Right? Today we have virtualized environments and bare metal, and what this architecture will do is bring those bare metal environments also under ESX management. So you ESX will manage environments which are virtualized and environments which are running bare metal OS. And so that's one big breakthrough and simplification for the elimination of silo or the elimination of, you know, specialized skills to keep it running. And lastly, but most importantly, where we are going with this. That just on the question you asked us earlier about software defined and developers being in control. Where we want to go with this is give developers, the application developers, the ability to really define and create their run time on the Fly, dynamically. So think about it. If dynamically they're able to describe how the application should run. And the infrastructure essentially kind of attaches computer resources on the Fly, whether they are sitting in the same server or somewhere in the network as pools of resources. Bring it all together and compose the runtime environment for them. That's going to be huge. And they won't be constrained anymore by the resources that are tied to the physical server that they are running on. And that's the vision of where we are taking it. It is going to be the next big change in the industry in terms of enterprise computing. >> Sounds like an Operating System to me. Yeah. Run time, assembly orchestration, all these things coming together, exciting stuff. Looking forward to digging in more after Vmworld. Manuvir, how does this connect to NVIDIA and AI? Tie that together for us. >> Yeah, It's an interesting question, because you would think, you know, okay, so NVIDIA this GPU company or this AI company. But you have to remember that INVIDIA is also a networking company. Because friends at Mellanox joined us not that long ago. And the interesting thing is that there's a Yin and Yang here, because, Krish described the software vision, which is brilliant. And what this does is it imposes a lot on the host CPU of the server to do. And so what we've be doing in parallel is developing hardware. A new kind of "Nick", if you will, we call it a DPU or a Data Processing Unit or a Smart Nick that is capable of hosting all this stuff. So, amusingly when Krish and I started talking, we exchanged slides and we basically had the same diagram for our vision of where things go with that software, the infrastructure software being offloaded, data center infrastructure on a chip, if you will. Right? And so it's a very natural confluence. We are very excited to be part of this, >> Yeah. >> Monterey program with Krish and his team. And we think our DPU, which is called the NVIDIA BlueField-2, is a pretty good device to empower the work that Krish's team is doing. >> Guys it's awesome stuff. And I got to say, you know, I've been covering Vmworld now 11 years with theCube, and I've known VMware since its founding, just the evolution. And just recently before VMworld, you know, you saw the biggest IPO in the history of Wall Street, Snowflake an Enterprise Data Cloud Company. The number one IPO ever. Enterprise tech is so exciting. This is really awesome. And NVIDIA obviously well known, great brand. You own some chip company as well, and get processors and data and software. Guys, customers are going to be very interested in this, so what should customers do to find out more? Obviously you've got Project Monterey, strategic direction, right? Framed perfectly. You got this announcement. If I'm a customer, how do I get involved? How do I learn more? And what's in it for me. >> Yeah, John, I would say, sorry, go ahead, Krish. >> No, I was just going to say sorry Manuvir. I was just going to say like a lot of these discussions are going to be happening, there are going to be panel discussions there are going to be presentations at Vmworld. So I would encourage customers to really look at these topics around Project Monterey and also about the AI work we are doing with NVIDIA and attend those sessions and be active and we will have a ways for them to connect with us in terms of our early access programs and whatnot. And then as Manuvir was about to say, I think Manuvir, I will give it to you about GTC. >> Yeah, I think right after that, we have the NVIDIA conference, which is GTC, where we'll also go over this. And I think some of this work is a lot closer to hand than people might imagine. So I would encourage watching all the sessions and learning more about how to get started. >> Yeah, great stuff. And just for the folks @vmworld.com watching, Cloud City's got 60 solution demos, go look for the sessions. You got the EX, the expert sessions, Raghu, Joe Beda amongst other people from VMware are going to be there. And of course, a lot of action on the content. Guys, thanks so much for coming on. Congratulations on the news, big news. NVIDIA on the Bay in Virtual stage here at VMworld. And of course you're in theCube. Thanks for coming. Appreciate it. >> Thank you for having us. Okay. >> Thank you very much. >> This is Cube's coverage of VMworld 2020 virtual. I'm John Furrier, host of theCube virtual, here in Palo Alto, California for VMworld 2020. Thanks for watching. (upbeat music)

>> Narrator: From around the globe it's theCUBE, covering HPE Discover Virtual Experience brought to you by HPE. >> Hi everybody. Welcome back. This is Dave Vellante for theCUBE, and this is our coverage of discover 2020, the virtual experience of HPE discover. We've done many, many discoveries, as usually we're on the show floor, theCUBE has been virtualized and we talk a lot at HPE discovers, a lot of storage and server and infrastructure and networking which is great. But the conversation we're going to have now is really, we're going to be talking about helping the world solve some big problems. And I'm very excited to welcome back to theCUBE Dr. Eng Lim Goh. He's a senior vice president of and CTO for AI, at HPE. Hello, Dr. Goh. Great to see you again. >> Hello. Thank you for having us, Dave. >> You're welcome. And then our next guest is Professor Joachim Schultze, who is the Professor for Genomics, and Immunoregulation at the university of Bonn amongst other things Professor, welcome. >> Thank you all. Welcome. >> And then Prasad Shastry, is the Chief Technologist for the India Advanced Development Center at HPE. Welcome, Prasad. Great to see you. >> Thank you. Thanks for having me. >> So guys, we have a CUBE first. I don't believe we've ever had of three guests in three separate times zones. I'm in a fourth time zone. (guests chuckling) So I'm in Boston. Dr. Goh, you're in Singapore, Professor Schultze, you're in Germany and Prasad, you're in India. So, we've got four different time zones. Plus our studio in Palo Alto. Who's running this program. So we've got actually got five times zones, a CUBE first. >> Amazing. >> Very good. (Prasad chuckles) >> Such as the world we live in. So we're going to talk about some of the big problems. I mean, here's the thing we're obviously in the middle of this pandemic, we're thinking about the post isolation economy, et cetera. People compare obviously no surprise to the Spanish flu early part of last century. They talk about the great depression, but the big difference this time is technology. Technology has completely changed the way in which we've approached this pandemic. And we're going to talk about that. Dr. Goh, I want to start with you. You've done a lot of work on this topic of swarm learning. If we could, (mumbles) my limited knowledge of this is we're kind of borrowing from nature. You think about, bees looking for a hive as sort of independent agents, but somehow they come together and communicate, but tell us what do we need to know about swarm learning and how it relates to artificial intelligence and we'll get into it. >> Oh, Dave, that's a great analogy using swarm of bees. That's exactly what we do at HPE. So let's use the of here. When deploying artificial intelligence, a hospital does machine learning of the outpatient data that could be biased, due to demographics and the types of cases they see more also. Sharing patient data across different hospitals to remove this bias is limited, given privacy or even sovereignty the restrictions, right? Like for example, across countries in the EU. HPE, so I'm learning fixers this by allowing each hospital, let's still continue learning locally, but at each cycle we collect the lumped weights of the neural networks, average them and sending it back down to older hospitals. And after a few cycles of doing this, all the hospitals would have learned from each other, removing biases without having to share any private patient data. That's the key. So, the ability to allow you to learn from everybody without having to share your private patients. That's swarm learning, >> And part of the key to that privacy is blockchain, correct? I mean, you you've been too involved in blockchain and invented some things in blockchain and that's part of the privacy angle, is it not? >> Yes, yes, absolutely. There are different ways of doing this kind of distributed learning, which swarm learning is over many of the other distributed learning methods. Require you to have some central control. Right? So, Prasad, and the team and us came up together. We have a method where you would, instead of central control, use blockchain to do this coordination. So, there is no more a central control or coordinator, especially important if you want to have a truly distributed swamp type learning system. >> Yeah, no need for so-called trusted third party or adjudicator. Okay. Professor Schultze, let's go to you. You're essentially the use case of this swarm learning application. Tell us a little bit more about what you do and how you're applying this concept. >> I'm actually by training a physician, although I haven't seen patients for a very long time. I'm interested in bringing new technologies to what we call precision medicine. So, new technologies both from the laboratories, but also from computational sciences, married them. And then I basically allow precision medicine, which is a medicine that is built on new measurements, many measurements of molecular phenotypes, how we call them. So, basically that process on different levels, for example, the genome or genes that are transcribed from the genome. We have thousands of such data and we have to make sense out of this. This can only be done by computation. And as we discussed already one of the hope for the future is that the new wave of developments in artificial intelligence and machine learning. We can make more sense out of this huge data that we generate right now in medicine. And that's what we're interesting in to find out how can we leverage these new technologies to build a new diagnostics, new therapy outcome predictors. So, to know the patient benefits from a disease, from a diagnostics or a therapy or not, and that's what we are doing for the last 10 years. The most exciting thing I have been  through in the last three, four, five years is really when HPE introduced us to swarm learning. >> Okay and Prasad, you've been helping Professor Schultze, actually implements swarm learning for specific use cases that we're going to talk about COVID, but maybe describe a little bit about what you've been or your participation in this whole equation. >> Yep, thank. As Dr Eng Lim Goh, mentioned. So, we have used blockchain as a backbone to implement the decentralized network. And through that we're enabling a privacy preserved these centralized network without having any control points, as Professor explained in terms of depression medicines. So, one of the use case we are looking at he's looking at the blood transcriptomes, think of it, different hospitals having a different set of transcriptome data, which they cannot share due to the privacy regulations. And now each of those hospitals, will clean the model depending upon their local data, which is available in that hospital. And shared the learnings coming out of that training with the other hospitals. And we played to over several cycles to merge all these learnings and then finally get into a global model. So, through that we are able to kind of get into a model which provides the performance is equal of collecting all the data into a central repository and trying to do it. And we could really think of when we are doing it, them, could be multiple kinds of challenges. So, it's good to do decentralized learning. But what about if you have a non ID type of data, what about if there is a dropout in the network connections? What about if there are some of the compute nodes we just practice or probably they're not seeing sufficient amount of data. So, that's something we tried to build into the swarm learning framework. You'll handle the scenarios of having non ID data. All in a simple word we could call it as seeing having the biases. An example, one of the hospital might see EPR trying to, look at, in terms of let's say the tumors, how many number of cases and whereas the other hospital might have very less number of cases. So, if you have kind of implemented some techniques in terms of doing the merging or providing the way that different kind of weights or the tuneable parameters to overcome these set of challenges in the swarm learning. >> And Professor Schultze, you you've applied this to really try to better understand and attack the COVID pandemic, can you describe in more detail your goals there and what you've actually done and accomplished? >> Yeah. So, we have actually really done it for COVID. The reason why we really were trying to do this already now is that we have to generate it to these transcriptomes from COVID-19 patients ourselves. And we realized that the scene of the disease is so strong and so unique compared to other infectious diseases, which we looked at in some detail that we felt that the blood transcriptome would be good starting point actually to identify patients. But maybe even more important to identify those with severe diseases. So, if you can identify them early enough that'd be basically could care for those more and find particular for those treatments and therapies. And the reason why we could do that is because we also had some other test cases done before. So, we used the time wisely with large data sets that we had collected beforehand. So, use cases learned how to apply swarm learning, and we are now basically ready to test directly with COVID-19. So, this is really a step wise process, although it was extremely fast, it was still a step wise probably we're guided by data where we had much more knowledge of which was with the black leukemia. So, we had worked on that for years. We had collected many data. So, we could really simulate a Swarm learning very nicely. And based on all the experience we get and gain together with Prasad, and his team, we could quickly then also apply that knowledge to the data that are coming now from COVID-19 patients. >> So, Dr. Goh, it really comes back to how we apply machine intelligence to the data, and this is such an interesting use case. I mean, the United States, we have 50 different States with 50 different policies, different counties. We certainly have differences around the world in terms of how people are approaching this pandemic. And so the data is very rich and varied. Let's talk about that dynamic. >> Yeah. If you, for the listeners who are or viewers who are new to this, right? The workflow could be a patient comes in, you take the blood, and you send it through an analysis? DNA is made up of genes and our genes express, right? They express in two steps the first they transcribe, then they translate. But what we are analyzing is the middle step, the transcription stage. And tens of thousands of these Transcripts that are produced after the analysis of the blood. The thing is, can we find in the tens of thousands of items, right? Or biomarkers a signature that tells us, this is COVID-19 and how serious it is for this patient, right? Now, the data is enormous, right? For every patient. And then you have a collection of patients in each hospitals that have a certain demographic. And then you have also a number of hospitals around. The point is how'd you get to share all that data in order to have good training of your machine? The ACO is of course a know privacy of data, right? And as such, how do you then share that information if privacy restricts you from sharing the data? So in this case, swarm learning only shares the learnings, not the private patient data. So we hope this approach would allow all the different hospitals to come together and unite sharing the learnings removing biases so that we have high accuracy in our prediction as well at the same time, maintaining privacy. >> It's really well explained. And I would like to add at least for the European union, that this is extremely important because the lawmakers have clearly stated, and the governments that even non of these crisis conditions, they will not minimize the rules of privacy laws, their compliance to privacy laws has to stay as high as outside of the pandemic. And I think there's good reasons for that, because if you lower the bond, now, why shouldn't you lower the bar in other times as well? And I think that was a wise decision, yes. If you would see in the medical field, how difficult it is to discuss, how do we share the data fast enough? I think swarm learning is really an amazing solution to that. Yeah, because this discussion is gone basically. Now we can discuss about how we do learning together. I'd rather than discussing what would be a lengthy procedure to go towards sharing. Which is very difficult under the current privacy laws. So, I think that's why I was so excited when I learned about it, the first place with faster, we can do things that otherwise are either not possible or would take forever. And for a crisis that's key. That's absolutely key. >> And is the byproduct. It's also the fact that all the data stay where they are at the different hospitals with no movement. >> Yeah. Yeah. >> Learn locally but only shared the learnings. >> Right. Very important in the EU of course, even in the United States, People are debating. What about contact tracing and using technology and cell phones, and smartphones to do that. Beside, I don't know what the situation is like in India, but nonetheless, that Dr. Goh's point about just sharing the learnings, bubbling it up, trickling just kind of metadata. If you will, back down, protects us. But at the same time, it allows us to iterate and improve the models. And so, that's a key part of this, the starting point and the conclusions that we draw from the models they're going to, and we've seen this with the pandemic, it changes daily, certainly weekly, but even daily. We continuously improve the conclusions and the models don't we. >> Absolutely, as Dr. Goh explained well. So, we could look at like they have the clinics or the testing centers, which are done in the remote places or wherever. So, we could collect those data at the time. And then if we could run it to the transcripting kind of a sequencing. And then as in, when we learn to these new samples and the new pieces all of them put kind of, how is that in the local data participate in the kind of use swarm learning, not just within the state or in a country could participate into an swarm learning globally to share all this data, which is coming up in a new way, and then also implement some kind of continuous learning to pick up the new signals or the new insight. It comes a bit new set of data and also help to immediately deploy it back into the inference or into the practice of identification. To do these, I think one of the key things which we have realized is to making it very simple. It's making it simple, to convert the machine learning models into the swarm learning, because we know that our subject matter experts who are going to develop these models on their choice of platforms and also making it simple to integrate into that complete machine learning workflow from the time of collecting a data pre processing and then doing the model training and then putting it onto inferencing and looking performance. So, we have kept that in the mind from the beginning while developing it. So, we kind of developed it as a plug able microservices kind of packed data with containers. So the whole library could be given it as a container with a kind of a decentralized management command controls, which would help to manage the whole swarm network and to start and initiate and children enrollment of new hospitals or the new nodes into the swarm network. At the same time, we also looked into the task of the data scientists and then try to make it very, very easy for them to take their existing models and convert that into the swarm learning frameworks so that they can convert or enabled they're models to participate in a decentralized learning. So, we have made it to a set callable rest APIs. And I could say that the example, which we are working with the Professor either in the case of leukemia or in the COVID kind of things. The noodle network model. So we're kind of using the 10 layer neural network things. We could convert that into the swarm model with less than 10 lines of code changes. So, that's kind of a simply three we are looking at so that it helps to make it quicker, faster and loaded the benefits. >> So, that's an exciting thing here Dr. Goh is, this is not an R and D project. This is something that you're actually, implementing in a real world, even though it's a narrow example, but there are so many other examples that I'd love to talk about, but please, you had a comment. >> Yes. The key thing here is that in addition to allowing privacy to be kept at each hospital, you also have the issue of different hospitals having day to day skewed differently. Right? For example, a demographics could be that this hospital is seeing a lot more younger patients, and other hospitals seeing a lot more older patients. Right? And then if you are doing machine learning in isolation then your machine might be better at recognizing the condition in the younger population, but not older and vice versa by using this approach of swarm learning, we then have the biases removed so that both hospitals can detect for younger and older population. All right. So, this is an important point, right? The ability to remove biases here. And you can see biases in the different hospitals because of the type of cases they see and the demographics. Now, the other point that's very important to reemphasize is what precise Professor Schultze mentioned, right? It's how we made it very easy to implement this.Right? This started out being so, for example, each hospital has their own neural network and they training their own. All you do is we come in, as Pasad mentioned, change a few lines of code in the original, machine learning model. And now you're part of the collective swarm. This is how we want to easy to implement so that we can get again, as I like to call, hospitals of the world to uniting. >> Yeah. >> Without sharing private patient data. So, let's double click on that Professor. So, tell us about sort of your team, how you're taking advantage of this Dr. Goh, just describe, sort of the simplicity, but what are the skills that you need to take advantage of this? What's your team look like? >> Yeah. So, we actually have a team that's comes from physicians to biologists, from medical experts up to computational scientists. So, we have early on invested in having these interdisciplinary research teams so that we can actually spend the whole spectrum. So, people know about the medicine they know about them the biological basics, but they also know how to implement such new technology. So, they are probably a little bit spearheading that, but this is the way to go in the future. And I see that with many institutions going this way many other groups are going into this direction because finally medicine understands that without computational sciences, without artificial intelligence and machine learning, we will not answer those questions with this large data that we're using. So, I'm here fine. But I also realize that when we entered this project, we had basically our model, we had our machine learning model from the leukemia's, and it really took almost no efforts to get this into the swarm. So, we were really ready to go in very short time, but I also would like to say, and then it goes towards the bias that is existing in medicine between different places. Dr. Goh said this very nicely. It's one aspect is the patient and so on, but also the techniques, how we do clinical essays, we're using different robots a bit. Using different automates to do the analysis. And we actually try to find out what the Swan learning is doing if we actually provide such a bias by prep itself. So, I did the following thing. We know that there's different ways of measuring these transcriptomes. And we actually simulated that two hospitals had an older technology and a third hospital had a much newer technology, which is good for understanding the biology and the diseases. But it is the new technology is prone for not being able anymore to generate data that can be used to learn and then predicting the old technology. So, there was basically, it's deteriorating, if you do take the new one and you'll make a classifier model and you try old data, it doesn't work anymore. So, that's a very hard challenge. We knew it didn't work anymore in the old way. So, we've pushed it into swarm learning and to swarm recognize that, and it didn't take care of it. It didn't care anymore because the results were even better by bringing everything together. I was astonished. I mean, it's absolutely amazing. That's although we knew about this limitations on that one hospital data, this form basically could deal with it. I think there's more to learn about these advantages. Yeah. And I'm very excited. It's not only a transcriptome that people do. I hope we can very soon do it with imaging or the DCNE has 10 sites in Germany connected to 10 university hospitals. There's a lot of imaging data, CT scans and MRIs, Rachel Grimes. And this is the next next domain in medicine that we would like to apply as well as running. Absolutely. >> Well, it's very exciting being able to bring this to the clinical world And make it in sort of an ongoing learnings. I mean, you think about, again, coming back to the pandemic, initially, we thought putting people on ventilators was the right thing to do. We learned, okay. Maybe, maybe not so much the efficacy of vaccines and other therapeutics. It's going to be really interesting to see how those play out. My understanding is that the vaccines coming out of China, or built to for speed, get to market fast, be interested in U.S. Maybe, try to build vaccines that are maybe more longterm effective. Let's see if that actually occurs some of those other biases and tests that we can do. That is a very exciting, continuous use case. Isn't it? >> Yeah, I think so. Go ahead. >> Yes. I, in fact, we have another project ongoing to use a transcriptome data and other data like metabolic and cytokines that data, all these biomarkers from the blood, right? Volunteers during a clinical trial. But the whole idea of looking at all those biomarkers, we talking tens of thousands of them, the same thing again, and then see if we can streamline it clinical trials by looking at it data and training with that data. So again, here you go. Right? We have very good that we have many vaccines on. In candidates out there right now, the next long pole in the tenth is the clinical trial. And we are working on that also by applying the same concept. Yeah. But for clinical trials. >> Right. And then Prasad, it seems to me that this is a good, an example of sort of an edge use case. Right? You've got a lot of distributed data. And I know you've spoken in the past about the edge generally, where data lives bringing moving data back to sort of the centralized model. But of course you don't want to move data if you don't have to real time AI inferencing at the edge. So, what are you thinking in terms of other other edge use cases that were there swarm learning can be applied. >> Yeah, that's a great point. We could kind of look at this both in the medical and also in the other fields, as we talked about Professor just mentioned about this radiographs and then probably, Using this with a medical image data, think of it as a scenario in the future. So, if we could have an edge note sitting next to these medical imaging systems, very close to that. And then as in when this the systems producers, the medical immediate speed could be an X-ray or a CT scan or MRI scan types of thing. The system next to that, sitting on the attached to that. From the modernity is already built with the swarm lending. It can do the inferencing. And also with the new setup data, if it looks some kind of an outlier sees the new or images are probably a new signals. It could use that new data to initiate another round up as form learning with all the involved or the other medical images across the globe. So, all this can happen without really sharing any of the raw data outside of the systems but just getting the inferencing and then trying to make all of these systems to come together and try to build a better model. >> So, the last question. Yeah. >> If I may, we got to wrap, but I mean, I first, I think we've heard about swarm learning, maybe read about it probably 30 years ago and then just ignored it and forgot about it. And now here we are today, blockchain of course, first heard about with Bitcoin and you're seeing all kinds of really interesting examples, but Dr. Goh, start with you. This is really an exciting area, and we're just getting started. Where do you see swarm learning, by let's say the end of the decade, what are the possibilities? >> Yeah. You could see this being applied in many other industries, right? So, we've spoken about life sciences, to the healthcare industry or you can't imagine the scenario of manufacturing where a decade from now you have intelligent robots that can learn from looking at across men building a product and then to replicate it, right? By just looking, listening, learning and imagine now you have multiple of these robots, all sharing their learnings across boundaries, right? Across state boundaries, across country boundaries provided you allow that without having to share what they are seeing. Right? They can share, what they have lunch learnt You see, that's the difference without having to need to share what they see and hear, they can share what they have learned across all the different robots around the world. Right? All in the community that you allow, you mentioned that time, right? That will even in manufacturing, you get intelligent robots learning from each other. >> Professor, I wonder if as a practitioner, if you could sort of lay out your vision for where you see something like this going in the future, >> I'll stay with the medical field at the moment being, although I agree, it will be in many other areas, medicine has two traditions for sure. One is learning from each other. So, that's an old tradition in medicine for thousands of years, but what's interesting and that's even more in the modern times, we have no traditional sharing data. It's just not really inherent to medicine. So, that's the mindset. So yes, learning from each other is fine, but sharing data is not so fine, but swarm learning deals with that, we can still learn from each other. We can, help each other by learning and this time by machine learning. We don't have to actually dealing with the data sharing anymore because that's that's us. So for me, it's a really perfect situation. Medicine could benefit dramatically from that because it goes along the traditions and that's very often very important to get adopted. And on top of that, what also is not seen very well in medicine is that there's a hierarchy in the sense of serious certain institutions rule others and swarm learning is exactly helping us there because it democratizes, onboarding everybody. And even if you're not sort of a small entity or a small institutional or small hospital, you could become remembering the swarm and you will become as a member important. And there is no no central institution that actually rules everything. But this democratization, I really laugh, I have to say, >> Pasad, we'll give you the final word. I mean, your job is very helping to apply these technologies to solve problems. what's your vision or for this. >> Yeah. I think Professor mentioned about one of the very key points to use saying that democratization of BI I'd like to just expand a little bit. So, it has a very profound application. So, Dr. Goh, mentioned about, the manufacturing. So, if you look at any field, it could be health science, manufacturing, autonomous vehicles and those to the democratization, and also using that a blockchain, we are kind of building a framework also to incentivize the people who own certain set of data and then bring the insight from the data into the table for doing and swarm learning. So, we could build some kind of alternative monetization framework or an incentivization framework on top of the existing fund learning stuff, which we are working on to enable the participants to bring their data or insight and then get rewarded accordingly kind of a thing. So, if you look at eventually, we could completely make dais a democratized AI, with having the complete monitorization incentivization system which is built into that. You may call the parties to seamlessly work together. >> So, I think this is just a fabulous example of we hear a lot in the media about, the tech backlash breaking up big tech but how tech has disrupted our lives. But this is a great example of tech for good and responsible tech for good. And if you think about this pandemic, if there's one thing that it's taught us is that disruptions outside of technology, pandemics or natural disasters or climate change, et cetera, are probably going to be the bigger disruptions then technology yet technology is going to help us solve those problems and address those disruptions. Gentlemen, I really appreciate you coming on theCUBE and sharing this great example and wish you best of luck in your endeavors. >> Thank you. >> Thank you. >> Thank you for having me. >> And thank you everybody for watching. This is theCUBE's coverage of HPE discover 2020, the virtual experience. We'll be right back right after this short break. (upbeat music)

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. Alright, welcome back to help us dig into this discussion and happy to welcome to the program. Chris Prasad. He is the senior vice president and general manager of the V Sphere business And just Simon, chief technologist for the high performance computing group. Both of them with VM ware. Gentlemen, thanks so much for joining. >>Thank you for having us. >>All right, Krish. When VM Ware made the bit fusion acquisition, everybody was looking the You know what this will do for this space GP use? We're talking about things like AI and ML. So bring us up to speed. As to, you know, the news today is the what being worth doing with fusion. >>Yeah. Today we have a big announcement. I'm excited to announce that, you know, we're taking the next big step in the AI ml and more than application strategy. With the launch off bit fusion, we just now being fully integrated with the V Sphere seven black home and we'll be releasing this very shortly to the market. As you said when we acquired institution a year ago, we had a showcase that's capable base as part of the normal event. And at that time we laid out a strategy that part of our institution as the cornerstone off our capabilities in the platform in the Iot space. Since then, we have had many customers. Take a look at the technology and we have had feedback from them as well as from partners and analysts. And the feedback has been tremendous. >>Excellent. Well, Chris, what does this then mean for customers, you know, what's the value proposition? That diffusion brings the visa versa? >>Yeah, if you look at our customers, they are in the midst of a big ah journey in digital transformation. And basically, what that means is customers are building a ton of applications, and most of those applications have some kind of data analytics or machine learning embedded in it. And what this is doing is that in the harbor and infrastructure industry, this is driving a lot of innovation. So you see the admin off a lot off specialized accelerators, custom a six FPs. And of course, the views being used to accelerate the special algorithms that these ai ml type applications need And, um, unfortunately, customer environment. Most of these specialized accelerators in a bare metal kind of set up. So they're not taking advantage off optimization and everything that it brings to that. Also, with fusion launched today, we are essentially doing the accelerator space. What we need to compute several years ago. And that is, um, essentially bringing organization to the accent leaders. But we take it one step further, which is, you know, we use the customers the ability to pull these accelerators and essentially going to be a couple of from the server so you can have a pool of these accelerators sitting in the network, and customers are able to then target their workloads and share the accelerators, get better utilization, drive a lot of cost improvements and, in essence, have a smaller pool that they can use for a whole bunch of different applications across the enterprise. That is a huge enabler for our customers. And that's the tremendous positive feedback that we get getting both from customers as well. >>Excellent. Well, I'm glad we've got Josh here to dig into some of the pieces, but before we get to you they got Chris. Uh, part of this announcement is the partnership of VM Ware in Dell. So tell us about what the partnership is in the solutions for for this long. >>Yeah. We have been working with the Dell in the in the AI and ML space for a long time. We have, ah, good partnership there. This just takes the partnership to the next level, and we will have, ah, execution solution support in some of the key. I am. It'll targeted the words like the sea for 1 40 the r 7 40 Those are the centers that would be partnering with them on and providing solutions. >>Okay, Tough. Take us in a little bit further as how you know the mechanisms of diffusion work. >>Yeah, that's a great question. So think of it this way. There there is a client component that we're using in a server component. The server component is running on a machine that actually has the physical GP use installed in it. The client machine, which is running the bit fusion client software, is where the user, the data scientist, is actually running their machine machine learning application. But there's no GPU actually in that host. And what is happening with fusion technology is that it is essentially intercepting the Cuda calls that are being made by that machine learning application and promoting those protocols over to the bit fusion server and then injecting them into the local GPU on the server. So it's actually, you know, we call it into a position in the ability that remote these protocols, but it's actually much more sophisticated than that. There are a lot of underlying capabilities that are being deployed in terms of optimization who takes maximum advantage of the, uh, the networking link that's it between the client machine and the server machine. But given all of that, once we've done it with diffusion, it's now possible for the data scientist either consume multiple GP use for single GPU use or even fractional GP use across that interconnected using the using technology. >>Okay, maybe it would help illustrate some of these technologies. If you got a couple of customers. >>Yeah, sure. So one example would be a retail customer. I'm thinking of who is. Actually it's ah grocery chain that is deploying ah, large number of video cameras into their into their stores in order to do things like, um, watch for pilfering, uh, identify when storage store shelves could be restocked and even looking for cases where, for example, maybe a customer has fallen down in denial on someone needs to go and help those multiple video streams and then multiple applications that are being run that part are consuming the data from those video screens and doing analytics and ml on them would be perfectly suited for this type of environment where you would like to be ableto have these multiple independent applications running. But having them be able to efficiently share the hardware resources of the GP is another example would be retailers who are deploying ML our check out registers who helped reduce fraud customers who are buying, buying things with, uh, fake barcodes, for example. So in that case, you would not necessarily want to deploy ah single dedicated GPU for every single check out line. Instead, what you would prefer to do is have a full set of resource. Is that each inference operation that's occurring within each one of those check out lines but then consume collectively. That would be two examples of the use of this wonderful in technology. >>Okay, great. So, Josh, last question for you is this technology is this only for use and anything else? You can give us a little bit of a look forward as to what we should be expecting from the big fusion technology. >>Yeah. So currently, the target is specifically NVIDIA gpu use with Buddha. Ah, the team, actually, even prior to acquisition had done some work on enablement of PJs. And also, I have done some work on open CL, which is more open standard for device access. So what you will see over time is an expansion of the diffusion capabilities to embrace devices like F PJs of the domain. Specific. A six that was referring to earlier will roll out over time, but we are starting with the NVIDIA GPU, which totally makes sense, since that is the primary hardware acceleration. And for deep learning currently >>excellent. Well, John and Chris, thank you so much for the updates to the audience. If you're watching this live leads growing, the crowd chat out Im to ask your questions. This page, if you're watching this on demand, you can also go to crowdchat dot net slash make ai really to be able to see the conversation that we had. Thanks so much for joy. Yeah, yeah, yeah, >>yeah.

[Music] from the cube studios in Palo Alto in Boston it's the cube covering the IBM thing brought to you by IBM hi everybody this is David Lally you're watching the cube and our multi day coverage of the IBM think Digital 20/20 experience the event experienced wall-to-wall coverage prasad saccharine is here he's the senior managing director at Accenture technology great to see you thanks for coming on for Sun and thank you for having me there pleasure to be on very welcome so um I'm looking at your bio here you're responsible for the relationship with with IBM Red Hat so I'm interested in that and you're driving the Accenture intelligent cloud and engineering practice so we got a lot to talk about here let's start with Red Hat obviously it's probably the most important in at least new part of IBM so here you're in the right spot what's going on with with with Red Hat these days in your practice there oh yeah so you know Red Hat is a extremely important part of our practice I am very much focused on what Accenture does within the hybrid cloud space for our clients and red hat with OpenShift is you know the most powerful platform that there is out there today in helping our clients both innovate in the new as they expand in what they're doing digitally as well as move and modernize some of the equipment they have you know from existing history you know I went when the Red Hat deal was completed I did a little braking analysis my sort of weekly editorial segment and I said you know this this Red Hat acquisition openshift is the linchpin and I went right there right we just went it was all about application modernization and hybrid cloud bringing that cloud experience to on-prem or cross clouds and so that it was always my take you know there was a lot of sort of marketing around cloud generally but but more specifically it's a to me it was always about that application modernization so I'm curious as to how your your clients have responded to that and you know whether or not I'm sort of on the right track there yeah I think there are multiple factors I mean if you look at just broadly the areas I think there are three areas the first as you correctly said there is application modernization so our clients are looking at the amount of technical debt that they have and their legacy systems they're looking to you know modernize the right parts of their legacy estate you know one looking at the trade-off around the costs as well as the performance so Red Hat and open ship really gives them the platform that allows them to do that and make take their journey forward from an app mod perspective onto the clouds and you know the various public clouds the second area is actually in greenfield development so as clients are building new applications they want to be able to you know build applications that they can run across you know multiple platforms whether it's private cloud or public cloud and particularly in areas like Europe I think this is particularly significant and we can talk about that in some more detail and then the third area which is emerging as you know is is the whole area of edge and IOT which is going to actually move a lot of the computer way from the central clouds into the into the edge and you know obviously open ship is going to play a big part there as well bringing all all the three parts of the enterprise as it were you know the edge and the cloud as well as all of the legacy and private estates that exist today so to talk more about Europe what's going on there is that a GDP or a related thing a country you know in country may keep the data in country what is the issue there yeah it's a little bit of board I you know if you look at particularly financial services but certainly other industries as well the regulator's are extremely focused on making sure that you know the right balance is being struck even if you're using public clouds you know they are going to talk about the amount of public cloud usage that can be for every application the various applications that have to be actually running on a private cloud estate so in a scenario like that you will really want to be able to build applications that you can run across you know multiple different platforms and you know open ship gives you the answer to be able to do that to be able to you know have a policy based approach where you know certain workloads can be working on your private cloud and certainly you can move it out to you know public cloud when the need arises result explain the edge angle is that about bringing a programmability or the cloud model to the data at the edge you can explain that more detail sure sure and you know the edge and IOT and the Internet of Things impacts different industries differently you know I can talk about you know since we mentioned financial services let me bring up insurance for example you look at autonomous you know cars and you know self driven vehicles and so on as their going to change daily life what happens in those cases is that you want a lot of that data to be processed at the vehicle level so at the edge rather than a lot of processing happening across the network you know up at the central crowd and then coming back down to the vehicle because the latency just doesn't allow these these sorts of applications to happen you look at multiple industries that are really being impacted by the edge and so as that starts to become more prevalent and about 50 to 60 percent of a lot of this compute moves off of the central cloud through various education what you really want to have is like the versions of these platforms running on those particular devices and the rest of it running either on your private or your central clouds so you have to be able to use and move a lot of these applications which are container base you know platform you know Ginni Rometty now arvind talked about how the only 20% of the workloads have moved to the cloud it's they're really difficult to move workloads that are sort of the next next wave how do you see that evolving from Accenture perspective I think I think you have I mean you get your technology agnostic right I mean you really you know you're not a purveyor of hardware or software and so how do you see as a kind of a quasi-independent here how do you see that that hybrid cloud that cloud journey playing out yeah I think you know the we have the same number by the way I mean we see about when we talk to our clients and we've surveyed several CEOs and CIOs the number we we arrive at is that about 20 percent I think of workloads having moved to the cloud now a lot of that has been SAS based you know they've taken a lot of functions that could really be satified so to speak now comes the part around really taking portions of your legacy estate that you need to move to the cloud whether you're going to do it as a pass or an i as you know doesn't really matter and then you know weave into that the requirements around data privacy around compliance around high performance etc which might either take you to a private cloud type of orientation or take it to various public clouds so there's a lot of that work be done so what we are doing with many of our clients is really working with them taking a lot of our tools we have a tool that that we use called my nav which allows you to really assess a client's legacy estate and figure out you know what part of it that really we should be modernizing and which of the partners brilliant that we need to be working with to be able to modernize that aspect in concurrence with that is all of the new development that's happening on the cloud native development which is naturally glowing going into you know a lot of these public as well as private cloud so a lot of that work the next you know let's say 30 to 40 percent over the next few years is going to be a lot of work that happens and that's going to be heavier lifting as compared to you know the initial 20% that is half of it well heavy heavy lifting is kind of your area of expertise and we think about Accenture deep industry expertise global presence I mean as does IBM empiricist essaouira your relationship with IBM what what's the partnership like maybe you could describe sort of where you guys complement each other I know you compete in certain segments but where do you complement each other you know like you pointed out earlier Dave you know we are we're very much technology agnostic we have been on a public cloud journey for the last several years and really built our skills and our you know support around that what the hyper scale is we're doing in the market as hybrid cloud has evolved over the last you know couple of years especially we see that open shift and Red Hat and IBM you know play a big part in you know in this part of the journey as well as IBM public cloud we see you know the use of IBM public cloud continue to increase in the market so all of these you know companies I think play a very important role in what our clients want to do to take their journeys to the cloud forward so you know we're trying to piece all of that together to to have the right you know solutions to our clients and really brings together I think the aspects one is you know country specific requirements the second is the specific industry that you're talking about and you know the third is technology so really it's a it's an intersection of region technology as well as industry it's something that you know we're naturally good at we have several clients where we do a lot of you know a lot we have deep existing relationships and we certainly partner with IBM very closely we are the largest system integrator of all of IBM software products globally outside of IBM themselves and we've been that maintaining that status for many years we've been doing the same on the Red Hat side so as IBM and Red Hat come together I think at many of our clients we're a very natural consultant and systems integrator for or IBM rather we haven't talked much about multi-cloud this week I know Stu minimun my colleague has been hosting the Red Hat summit and it talked a lot about it but again I want to tap you're sort of you know that you're agnostic brain you look at the landscape and you've got different suppliers coming at it from different angles right AWS won't use the term via Microsoft obviously has a good story there you know Google with anthos etc VMware wants its piece of the pie iBM is kind of to me one of the most interesting with red hat of course because not only does it have its own cloud but it's very aggressive around supporting multiple clouds it's it it seems to be you know intent on doing whatever the client wants clearly that's your business I wonder what you can share with us about your thoughts on on multi cloud specifically yeah absolutely I think you know multi cloud is certainly where a lot of our clients are at and they've started the multi cloud journey you know you know a few years ago they have gone with more than you know maybe one hyper scaler although they have had you know just few workloads perhaps in in in multiple of them and really focused on one of them but as they start increasing the percentage of work that they're doing within the within the clouds they start looking at a lot of these clouds for very specific reason and most of our clients end up using food with P public clouds and when I look at the public cloud certainly you mentioned all of them AWS Microsoft Azure Google you know to the GCP product as well as you know IBM with IBM's public cloud and then with OpenShift really being able to run across all of these public clouds allow you allows you to actually design you know micro services based applications that are containerized and you can you know pretty much run them across whichever cloud you want and this is where we really you know work with our clients to really understand their need and to help them with you know the specific clouds that we won't be working with and which applications really should reside where makes sense for them and like I said from a Europe perspective you know with gdpr etc I think that journey is a little bit you know further advanced than it is perhaps in other places other parts of the world but we're seeing you know much more use of multi-cloud in addition to of course sass and increase user way Superdog your role is global obviously not just yes not just us right pan-pan the world or is it US and Europe no it is its global so it's us Europe as well as what we call the growth market so it includes China then is that correct or yes yeah so okay so now you got Alibaba you know you're playing there that's yet another cloud and so and what your one of the roles that you play as a systems integrator and somebody who's you know trying to trust it is you help customers pick the right workload for the right you know infrastructure and make it work obviously and help them de-risk one of the things we've noted is you know going back to the 80/20 or 20 has moved 80 hasn't it's the hard stuff it's that a lot of that mission-critical stuff hasn't moved in mate may never move but some of it will it just seems to us that you know moving the mission critical workloads is very risky and so what you want to do is make sure that you D risk that maybe keep it on you know if it's an IBM mission-critical workload maybe IBM's got ways to keep it safe in the IBM cloud and you know cross connect them etc I wonder what your thoughts are on moving what has heretofore been hard to move workloads does it make sense to put them in the cloud or does it make sense to put a brick wall around them and leave them on Prem I know it depends but but but maybe you could frame that for us sure absolutely so we have you know a concept that we call digital decoupling and what that really entails is is to take a look at these monolithic applications that are running you know on the back end and then we look at certain speech ER extraction that you know you can you can perform take those features out especially things that will give you access to digital channels you know rewrite those applications containerize them and then be able to run them on on multiple clouds and we've been doing that with you know many clients for example you know large hotel chains where we've taken a lot of that functionality containerized it run it on public clouds and it's only the final commit after you go through the process of figuring out you know what kind of room do you want picking out the various features it's not till the final commit that that happens on the mainframe side so feature extraction through digital decoupling I think offers you tremendous offloading of a lot of those features as well as processing onto the public cloud certainly iBM is also looking at many in many ways in which they can move some of these core functions as well on to their public cloud so I think the journey continues like you said you know it may not be ever that you have a hundred percent of the processing that happens on the public cloud and again we have to take a look at the amount of work that there is the risk reward the cost that it will take and you know with the enormous amount of functionality that has to take place this is where we have to advise our clients on you know the journey as well as the order in which via TP for the landscape we talked earlier about edge you're talking about multiple clouds you've got on-prem you've got mission critical workloads and you mentioned you know containers people want portability of course containers are necessary ingredient of that portability but it's insufficient and so you just see complexity increasing as we as we proceed down this cloud journey you've got to secure those those those those containers and and micro services sometimes aren't so micro you've you've got to make them work across cloud so it seems to me that you guys and your your clients get a lot of work to do which is which is a good thing as long as they make the business case and it's adding value to the organization yeah absolutely and then this is where you know you take certain functions I think you have a lot of sass options particularly around certain things that you're doing that tend to be you know commoditized so to speak certain other functions where you don't need perhaps their elasticity either about offers so you can have you know past solutions that you can build more quickly but then you want other solutions that need to be more mission-critical more resilient and in certainly movement elastic and that's where you know you look at you know producing micro-services containerized applications that you can really burst across you know multiple clouds and so on so these are all part of the architectures that we're building designing and implementing a wrapper Versailles where can I go to get more info on this whole topic from you know a hybrid cloud perspective as well as a public cloud perspective we go to Accenture comm and you do go to the cloud section there's a lot of information as well as credentials and white papers that you'd be able to access and also gives you access to specific people that you can you know reach out to and contact and get for the information on what they've been able to do very interesting conversation prasad and it's great to see you guys working very closely with with IBM i love it two global companies deep industry expertise solving hard problems so thanks so much for coming with you Naruto thank you so much for doing this very welcome and thank you for watching everybody this is Dave Volante and it's a wall-to-wall coverage of the IBM digital event experience around think 2020 we're right back right at this short break you're watching the Hume [Music] you

[Music] hello and welcome to the Palo Alto students leaky bomb John Farrar we're here for a special cube conversation and special report big news from VMware discuss the launch of the availability of vSphere 7 I'm here with Chris Prasad SVP and general manager of the vSphere business and cloud platform business unit and Paul Turner VP a VP of Product Management guys thanks for coming in and talking about the big news thank you for having us you guys announced some interesting things back in march around containers kubernetes and the vSphere Chris just about the hard news what's being announced today we are announcing the general availability of vSphere 7 John it's by far the biggest release that we have done in the last 10 years we previewed it this project Pacific a few months ago with this release we are putting kubernetes native support into the vSphere platform what that allows us to do is give customers the ability to run both modern applications based on kubernetes and containers as well as traditional VM based applications on the same platform and it also allows the IT departments to provide their developers cloud operating model using the VMware cloud foundation that is powered by this release this is a key part of our tansu portfolio of solutions and products that we announced this year and it is star gated fully at the developers of modern applications and the specific news is vSphere 7 is general available generally vSphere 7 yes ok that so let's on the trend line here the relevance is what what's the big trend line that this is riding obviously we saw the announcements at VMware last year and throughout the year there's a lot of buzz pascal sternness says there's a big wave here with kubernetes what does this announcement mean you guys with the marketplace trend yeah so what kubernetes is really about is people trying to have an agile operation they're trying to modernize their IT applications and they the best way to do that is build off your current platform expand it and make it a an innovative a agile platform for you to run kubernetes applications and VM applications together I'm not just that customers are also looking at being able to manage a hybrid cloud environment both on pram and public cloud together so they want to be able to evolve and modernize their application stack but modernize their infrastructure stack which means hybrid cloud operations with innovative applications kubernetes or container based applications on VMs what's excited about this trend increase we were talking with us at vmworld last year and we've had many conversations around cloud native but you're seeing cloud native becoming the operating model for modern business I mean this is really the move to the cloud if you look at the successful enterprises and even the suppliers the on-premises piece if not move to the cloud native marketplace technologies the on premise isn't effective so it's not so much on premises going away we know it's not but it's turning into cloud native this is the move to the cloud generally this is a big wave yeah absolutely I mean if John if you think about it on-premise we have significant market share by far the leader in the market and so what we are trying to do with this is to allow customers to use the current platform they are using but bring their application modern application development on top of the same platform today customers tend to set up stacks which are different right so you have a kubernetes stack you have a stack for the traditional applications you have operators and administrators who are specialized in kubernetes on one side and you have the traditional VM operators on the other side with this move what we are saying is that you can be on the same common platform you can have the same administrators who are used to administering the environment that you already had and at the same time offer the developers what they like which is kubernetes dial-tone that they can come and deploy their applications on the same platform that you use for traditional applications yeah Paul Paul Pat said kuba is gonna be the dial tone on the Internet most Millennials might even know what dial tone is but if what he meant is is that's the key fabric that's gonna work a straight and you know we've heard over the years skill gap skill gap not a lot of skills out there but when you look at the reality of skills gap it's really about skills gaps and shortages not enough people most CIOs and chief information security are so that we talk to you say I don't want to fork my development teams I don't want to have three separate teams so I don't have to I I want to have automation I want an operating model that's not gonna be fragmented this kind of speaks to this whole idea of you know interoperability and multi-cloud this seems to be the next big way behind ibrid I think it I think it is the next big wake the the thing that customers are looking for is a cloud operating model they like the ability for developers to be able to invoke new services on demand in a very agile way and we want to bring that cloud operating model to on-prem to Google cloud to Amazon Cloud to Microsoft cloud to any of our VC peepee partners you get the same cloud operating experience and it's all driven by a kubernetes based dial-tone it's effective and available within this platform so by bringing a single infrastructure platform that can one run in this hybrid manner and give you the cloud operating agility that developers are looking for that's what's key in version seven says Pat Kelsey near me when he says dial tone of the internet kubernetes does he mean always on or what does he mean specifically just that it's always available what's what's is what's the meaning behind that that phrase no I the first thing he means is that developers can come to the infrastructure which is the VMware cloud foundation and be able to work with a set of api's that are kubernetes api s-- so developers understand that they are looking for that they understand that dial tone right and you come to our VMware cloud foundation once across all these clouds you get the same API said that you can use to deploy that application okay so let's get into the value here of vSphere seven how does VMware vSphere seven specifically help customers isn't just bolting on kubernetes to vSphere some will say is it that's simple or used whether you're running product management no it's not that easy it's yeah some people say hey use bolton kubernetes on vSphere it's it's not that easy so so one of the things if if anybody's actually tried deploying kubernetes first it's highly complicated um so so definitely one of the things that we're bringing is you call it a Bolton but it's certainly not like that we are making it incredibly simple you talked about IT operational shortages customers want to be able to deploy kubernetes environments in a very simple way the easiest way that we can you can do that is take your existing environment that are out ninety percent of IT and just turn on turn on the kubernetes dial tone and it is as simple as that now it's much more than that in version seven as well we're bringing in a couple things that are very important you also have to be able to manage at scale just like you would in the cloud you want to be able to have infrastructure almost self manage and upgrade and lifecycle manage itself and so we're bringing in a new way of managing infrastructure so that you can manage just large scale environments both on-premise and public cloud environments and scale and then associated with that as well is you must make it secure so there's a lot of enhancements we're building into the platform around what we call intrinsic security which is how can we actually build in truly a trusted platform for your developers and IT yeah I mean I was just going to touch on your point about the shortage of IT staff and how we are addressing that here the the way we are addressing that is that the IT administrators that are used to administering vSphere can continue to administer this enhanced platform with kubernetes the same way they administered the older releases so they don't have to learn anything new they are just working the same way we are not changing any tools process technologies it was before same as it was before more capable dealer and developers can come in and they see new capabilities around kubernetes so it's best of both worlds and what was the pain point that you guys are so obviously the ease-of-use is critical Asti operationally I get that as you look at the cloud native developer Saiga's infrastructure as code means as app developers on the other side taking advantage of it what's the real pain point that you guys are solving with vSphere 7 so I think it's it's it's multiple factors so so first is we've we've talked about agility a few times right there is DevOps is a real trend inside an IT organizations they need to be able to build and deliver applications much quicker they need to be able to respond to the business and to do that what they are doing is they need infrastructure that is on demand so what what we're really doing in the core kubernetes kind of enablement is allowing that on-demand fulfillment of infrastructure so you get that agility that you need but it's it's not just tied to modern applications it's also your all of your existing business applications and your modern applications on one platform which means that you know you've got a very simple and and low-cost way of managing large-scale IT infrastructure so that's that's a huge piece as well and and then I I do want to emphasize a couple of other things it's it we're also bringing in new capabilities for AI and ML applications for sa P Hana databases where we can actually scale to some of the largest business applications out there and you have all of the capabilities like like the GPU awareness and FPGA where FPGA awareness that we built into the platform so that you can truly run this as the fastest accelerated platform for your most extreme applications so you've got the ability to run those applications as well as your kubernetes and container based applications that's the accelerate application innovation piece of the announcement right that's right yeah it's it's it's quite powerful that we've actually brought in you know basically new hardware awareness into the product and expose that to your developers whether that's through containers or through VMs which I want to get your thoughts on the ecosystem and then in the community but I want to just dig into one feature you mentioned I get the lifestyle improvement a life cycle improvement I get the application acceleration innovation but the intrinsic security is interesting could you take a minute explain what that is yeah so there's there's a few different aspects one is looking at how can we actually provide a trusted environment and that means that you need to have a way that the key management that even your administrator is not able to get keys to the kingdom as we would call it you you want to have a controlled environment that you know some of the worst security challenges inside and some of the companies has been your in choler internal IT staff so you've got to have a way that you can run a trusted environment and independent we've got these fair trust authority that we released in version 7 that actually gives you a a secure environment for actually managing your keys to the kingdom effectively your certificates so you've got this you know continuous runtime now not only that we've actually gone and taken our carbon black features and we're actually building in full support for carbon black into the platform so that you've got negative security of even your application ecosystem yeah that's been coming up a lot in conversations the carbon black in the security piece chrishelle see these fear everywhere having that operating model makes a lot of sense but you have a lot of touch points you got cloud hyper scale is that the edge you got partners so the other dominant market share and private cloud we are on Amazon as you well know as your Google IBM cloud Oracle cloud so all the major clouds there is a vSphere stack running so it allows customers if you think about it right it allows customers to have the same operating model irrespective of where their workload is residing they can set policies compliance security they said it once it applies to all their environments across this hybrid cloud and it's all fun a supported by our VMware cloud foundation which is powered by vSphere 7 yeah I think having that the cloud is API based having connection points and having that reliable easy to use is critical operating model all right guys so let's summarize the announcement what do you guys take dare take away from this vSphere 7 what is the bottom line what's what's it really mean I I think what we're if we look at it for developers we are democratizing kubernetes we already are in ninety percent of IT environments out there are running vSphere we are bringing to every one of those vSphere environments and all of the virtual infrastructure administrators they can now manage kubernetes environments you can you can manage it by simply upgrading your environment that's a really nice position rather than having independent kind of environments you need to manage so so I think that's that is one of the key things that's in here the other thing though is there is I don't think any other platform out there that other than vSphere that can run in your data center in Google's in Amazon's in Microsoft's in you know thousands of VC PP partners you have one hybrid platform that you can run with and that's got operational benefits that's got efficiency benefits that's got agility benefits yeah I just add to that and say that look we want to meet customers where they are in their journey and we want to enable them to make business decisions without technology getting in the way and I think the announcement that we made today with vSphere 7 is going to help them accelerate their digital transformation journey without making trade-offs on people process and technology and there's more to come look we're laser focused on making our platform the best in the industry for running all kinds of applications and the best platform for a hybrid and multi cloud and so you'll see more capabilities coming in the future stay tuned well one final question on this news announcement which is this awesome vSphere core product for you guys if I'm the customer tell me why it's gonna be important five years from now because of what I just said it is the only platform that is going to be running across all the public clouds right which will allow you to an operational model that is consistent across the clouds so think about it if you go to Amazon native and then you have orc Lord in Azure you're going to have different tools different processes different people trained to work with those clouds but when you come to VMware and you use our cloud foundation you have one operating model across all these environments and that's going to be game-changing great stuff great stuff thanks for unpacking that for us graduates on the insulin thank you at vSphere 7 News special report here inside the cube conversation I'm John Ferger thanks for watching [Music]

>>Yeah, yeah, yeah, yeah, yeah. >>Welcome to this Special Cube conversation. We're gonna unpack and have a casual conversation around the big news that VM Ware just announced the sphere 7.7 point. Oh, or V. Sphere seven. Chris Prasad, senior vice president, General manager of the Sphere Cloud Platform Business unit. Paul Turner, VP of product. Guys, we just chatted about the big news. Congratulations. Um, the bottom line, if I'm a customer, I'm moving into the cloud. I see this as really an either an enabler or blocker. You guys actually think it's an enabler? Um, I'm not saying it's a blocker, but as a customer, I just need to know, Is it going to help me go faster? I'm going cloud, Which means I've been told I got to get on the cloud you got Amazon might have azure or multiple clouds with workloads sitting around. I gotta pull them all together and make them work. But right now, I just got to get my operations cloud native necessarily kind of pressure point. >>Oh, for sure. One of the biggest drivers that you see happen in the industry right now is kubernetes. Why? Why is kubernetes taking off communities taking off because it gives you cloud independence. It gives you the ability to run with same operating model, whether it's in Google Cloud, Amazon's Cloud, Microsoft Cloud or any other cloud service. What we're doing with version seven instruction bring that same kubernetes cloud independent operating model directly in divisor. So now all of your infrastructure platforms that are out there, 90% of I T environments are all kubernetes ready platforms on. That's really powerful. So what we've done is just taken a totally different kind of, um ah, scope on how cloud should be Cloud should be any cloud. It should be independent of one particular flavor of it and on developers should be able to work then in a much more agile way. >>You just see, I've been following VM where you know my career since it was founded. And, you know, with the Cube coverage over the years is they see the innovation. You guys do a lot of great stuff. Of course, we keep on our teams to minimum. And David Lantz he made some good calls with these v san. We saw the early stuff with V Cloud Air Kind of saw that kind of going in this direction, But it's been really innovation going on around you guys. I'll see with NSX has exploded and V Sphere has been the core thing. As you guys look at the cloud model, you guys made some good moves with Amazon. I've always felt that you guys could be that Switzerland that that layer of connection points between as enterprise really moved from old way of provisioning, too much more seamless operating model where they have a deal with cyber security. They gotta deal with all the stuff that's going to come from APS that's going to come from the APP store. When you bought Hep D Oh, I was like, That's actually really smart move. You started bringing that cloud native vibe into V sphere, and that's what's essentially happening here. Isn't it? >>Exactly. This is like the the coming out party for that, like it's V Sphere having all the hefty oh goodness embedded in it. And what they would see is that because we have such a huge presence in the on Prem space, this provides the fastest bad for customers to get to the cloud. So today I mean this? I don't want this point to be lost on the today. You know, we are running the same VM Ware Cloud Foundation, our on Prem on Amazon in Google and many of the same code base. Same code base, right? It's the exact same thing. So now what does that give you as a customer? It gives you the same operational model across all these clouds. Because customers today, we thought that they're setting up set of processes and tools or Amazon. Then you go to Azure. You're doing a different set than their training people to do that. And, you know, you could get into compliance and other issues where things fall through the cracks. Right? When you do that here, the same platform you said your policies wants it applies to all the clouds. You can move your workloads between clouds, right? That's a V motion. Essentially, we don't know the >>last kept on that one, but that's ideal would be crippled >>today. It is happening today and we have thousands of other partners which are the tier two service providers who are all also offering that. So we have a huge grab off these providers are in which we live in the same platform. >>Yeah, I want to add something else, actually, to that as well. Which is? This is an open platform, which is really powerful, right? This is based on kubernetes for developers, which means you can run on the V sphere platform, and that is a hybrid infrastructure that is the most ubiquitous infrastructure out there. But if you actually want to take your application actually deployed onto a native application Native Cloud, you can do that as well. Um, and so it's very important for us to keep the platform open while making broadest available on >>Dev ops. I mean, first, I totally agree. I think open wins, But the end of the day, I think this operating consistency is a big story because it's kind of like nuance. But it is really the most important customers care about, because if you're operating successfully seamlessly across cloud, it's better. So the question I have on the Dev Op side because the dream has always been infrastructure as code. So are you guys there with this? Do you consider this V Sphere seven kind of infrastructures code from a developer? Is it all being taken care of. How close are we in your mind's eye to infrastructure as code. >>Now it's 100% there. I mean, we made the announcement around Hangzhou, which is a set off other products and capabilities that we add to what the sphere has and that whole stack. And the solution is for this targeted at the modern developer. So we have all the capabilities that the developers need to do infrastructure as scored, to deploy their applications and deployed across all these clouds. >>And I want I want to add to that the infrastructure as code really has two parts to it. We look at how do I provide the developers infrastructure's code, which is what we're doing with kubernetes enablement and we have our V San product is available. In fact, all storage services from V sphere available through that andare NSX services are available through kubernetes. So you've got full infrastructures code for developers. But infrastructures code also means how do you deploy large scale infrastructures and manage them as code? How do people actually manage the operations and the deployment of services? And so you're right in your admin team actually have a full layer of enhanced lifecycle management provisioning off configurations and settings across infrastructure. All of that is now managed, as >>that's almost under the hood kind of stuff. But that's important because networking is going to play a big role in all of this from a security standpoint and also compute storage. Pretty much looking, looking good, but networking becomes a huge part of what's under the hood. >>Yeah, I mean, look at networking is what enables us to connect all these clouds together, right? And NSX being the underlying platform for us enables us to have one single layer across all these clouds with the same operating model. So NSX is very critical. >>I want to get your guys thoughts on some little history lesson here or scar tissue, as we say in the industry. You know, I remember back during the Hadoop days, 2010 the big data movement hit, and it was just going to save us all. It's gonna be great, but what ended up happening was this very hard to stand up these clusters and what happened was the commitment the vision was there, but it was just really hard to manage and stand up clusters and hire people to do this. So it has some use cases, but it just really kind of fell down. We saw Open Stack have a similar trajectory where good on paper, things had used cases. But it's just so hard to manage the trends. We're moving very, very fast. Cloud was here. Cloud Computing kind of took everyone by storm and just got rid of all those things. And so they kind of dying. >>No. But if you think about why open Stack didn't go anywhere in the end, it's because of the operational complexity right? It took a lot to set it up, and he had essentially invest a lot more than keeping it running right. And then what we're doing is saying you don't have to worry about that aspect because it's built into the platform that you already know, right? So we have taken that complexity out completely, and so you just have this fear. The administrators know how to set up and run and do life cycle, and this year, and you get kubernetes, go >>back to my original question. If that's the case, which, by the way, I think that's the way to think about it. Then I found the customer acceleration. I can draft up with the movement of cloud as fast as I can Go is having any kind of blockers. >>Fastest lamb like cloud >>ran to the cloud >>and fastest fastest ramp to a cloud operating model, which means that all of your developers can now actually run as quickly as they can, building their applications independent of I t. In a much more dynamic way. So you want to move to that cloud operating model. That's why Kubernetes is so important on the infrastructure side. We've actually, of course, made it a much easier platform to manage. But but it's the agility that matters. >>You guys have done some great innovation. I think you've got a good ear to the market, made some good moves. Looking good. This is a great vision. I got to get your guys take on the edge. Big discussion. Five g. Certain years love that kind of vision. But the end of the day and edge. Now, if you talk about cloud operations, everything's an edge, right? So what does edge mean for V sphere? How do you guys look at the edge of the network. And as these applications with the sensors or whatever happening at the edges, How does this V Sphere look at that? How do you guys look? >>So, uh, for let me just I would say that, you know, we we have, ah, data center edge, right? We just think of it as, um, retail stores, Starbucks, right. They have a kind of a mini data center application running there. That's one kind of edge that people talk about. Then you have the kind of the telco edge, but a lot of the crossing of the five year data is happening, right? Where the cell tower, Selden. We're done. And then you have the devices. You just the cars, the You know what you have at home and we're not right. And then and we can play across all of these because we have the platform. I don't know if you know, but ah, v sphere, as the platform is, is embedded in many devices today. It's in the army. It's embarking leaders it. So it has a form factor that can live in all these devices. We certainly play in the data center, so we're well suited to play the >>piece for anywhere. >>Yeah, that is exactly right. >>I think we're already We're already at the data center edge, as we've talked about that is, it's a very common deployment use case for earlier versions of the sphere, and it will continue to be the value that you guys it's not not new at all. I think the telco edge is actually a very interesting one, particularly the five G switch over. So you know what's happening. There is. There's a whole radio access networks and you're looking at the V Ron as a big initiative there. Which is how do we bring virtualization as a service they're into into those networks? Container deployments becomes very important as well. So we actually have a platform with version seven that actually can give the telco edge and five G network deployments a much more secure, predictable runtime environment. So that's really powerful as well. And it's containers and VMS because many of those applications that are deployed a telco edge our container based applications. >>It's interesting, you know, we talk about stacks in our last segment and you guys talking about the news and now having all these stacks later on. But think about the evolution of the industry with cloud. A whole new sets of services are emerging mentioned Telco Edge. So it just looks different. What's the same kind of open model that open systems brought us, but just a little bit different? It's a distributed cloud security computer, same concepts, new new capabilities. >>Not just to add to that, I mean the biggest innovation John is happening in the hardware layer by the computer, sort of getting disaggregated. There is a lot of acceleration that is going on that are specialized chips, a six effigies that are being built into the servers and and memory's getting pulled outside because the interconnect is getting fast enough for those things to happen. And so a lot of the innovation that we do as a platform that we didn't talk about much today is really a data layer, because we had to virtual eyes all of that and provide it to the level. Of course, >>yeah, it's great. It's a great architecture. I think I just add more complexity that's coming and you guys can help. Abstract away is you just look at cybersecurity and the role of data. You got to get in front of all these these trends to get that automation dev ops going because without any automation and software is just people can't handle the inbounds. It's a big problem. >>Yeah, you really need, um, your platforms to provide intrinsic security. It shouldn't be. It shouldn't be an option. It shouldn't be something the developers need to worry about. It should be something that's just part of the platform. And that's one of the things that we see is critical and actually built into Visa or seven. And you've seen that we've made a number of acquisitions recently. Actually, in the security piece, it's it's so that we can purposely build into your runtime environment, which is your VM environment container environment that we're running. We actually build in intrinsic security would build in a dynamic checking off the scope of an application in real time. Um, while those applications running, which is very key. >>Paul, >>Thanks for sharing all that great stuff. I want to get one final thought for both of you before we wrap up is we've been seeing and we've been reporting kind of the three ways of the cloud wave one was public. We all kind of know how that turned out. Awesome Cloud Native Born in the Cloud Wave two is well right now with a lot of intensity hybrid that's got a range of definitions. And then the third wave that's coming fast is multi cloud. So I want to get your thoughts on hybrid. A lot of energy, a lot of spend a lot of dollars investment in hard causing people in hybrid. I know we have different definitions. Is also different versions of hybrid. How do you define hybrid? And how does that become a path to the next wave? Or is it a path of next wave? What's your take? >>So it's absolutely the bad the next, I would say the hybrid, in our view, is the same platform running on which cloud do you want to use in our platform, as we talked about spans all the major clouds today giving the same operating model, and that's what we view as the hybrid cloud story. But the next one is the ability to mix native cloud workloads and services with that, and we already have a set of products and services that target that it's the times. A portfolio that I talked about is all focused on the multi cloud journey. So we kind of support both, and we're looking forward and aggressively going after the multi cloud. >>I think it's important to think of them as is completely complimentary of each other, right? A hybrid infrastructure platforms. So you know, a single I T organization can actually have one operating experience for their entire infrastructure, independent of Cloud Private Cloud Public Cloud Services. But Multi Cloud is about developers. It's about developers able to deploy their applications on any cloud environment that they need to, and they don't need to worry about infrastructure. So hybrid cloud is really about, ah, hybrid infrastructure that we can deploy everywhere, multi cloud and the services that we're providing to developers is all about how you could be independent of any cloud deployment that you want. It could be a hybrid infrastructure you deploy on. It could be on a standard public cloud service, >>and what's interesting is not. Not not all clouds are created equal. I mean, Amazon has much more capability in Azure and Google, but they're finding their swim lanes. But again it's all about the workload. The workload decides which cloud to work on. And that's right. You guys just agnostic? Yes, For the operator. Well, well, Thanks for the insight, guys. Appreciate you did a little post wrap of the news. Thanks for hiring. Thank you. Big news. These fear seven Q breakdown here. I'm John Furrier. Thanks for watching, >>right? Yeah.

>>Bach from Las Vegas. It's the cube covering AWS executive summit brought to you by extension. >>Welcome back and good morning. Welcome to the cubes live coverage of the Accenture executive summit here at AWS reinvent. I'm your host, Rebecca Knight. We are joined by pre-saved Sanker and he is the senior managing director global lead intelligent cloud infrastructure. Welcome back on the queue. Thanks so much for coming on. And Larry soccer, global managing director infrastructure services domains and strategy. Thank you so much. So we're talking today about hybrid cloud, the best of both worlds. As we say on the cube. It's a multicloud world. But I want to start with you Prisaad. What is driving clients to move to the cloud? What are you hearing from CEOs? What keeps them up at night? >>So I think, you know, you've got to a point with our clients where they're really trying to get the power of the cloud to the enterprises. So there are multiple things that they're trying to do. First, they're trying to really get the innovation that cloud provides in driving their digital transformation. The second is taking advantage of the cost savings that cloud can provide. So there are multiple aspects of how they use cloud. The first would be using SAS type applications. So for example it is faults.com or Workday and things like that. The second is using the power of providers like AWS really to drive what they can do from cloud native perspective in building new applications. And the third is just taking existing applications that aren't legacy and either re hosting them or refactoring them as an adjusting them to some extent and then hosting them on again, clouds like AWS. So that is a multiyear journey that all our clients are on. And you know, as Accenture we're helping them identify what needs to go first, what needs to go next and help them in that journey. >>And what is, what is the compelling force? Is it that they want to save cut costs? Is it that they want to be more innovative and they view this innovation in the cloud as the key to it? >>It's a combination of both. It's innovation is absolutely number one. Secondly, it is speed to market. The ability to get your product out there very quickly is second and the third is at the end of the day, you know data centers are going to go away and we're going to all recite in the cloud in some form or fashion, whether it's public or private. And which is why this whole topic of hybrid and multi-cloud is becoming so important today. >>So Larry, why hybrid cloud though? Why? Why can't we just go all in on private and public? Sorry. >>Interesting. I mean the, the real driver and Prisaad touched on it there. The real driver to get to, to AWS and to, to the hyperscalers really is around the innovation cycles. You know the passes, the services that they can do and that drives innovation. The speed to, to get there as important, it gives you a way of quickly scaling, which you know, if I really want to build out an application fast, a great way to get there and is obviously the consumption economics. How do I shift from cap ex topics? So that's driving the cloud native that push into, into the wallet of public. At the same time, our clients do have a number of requirements that really make them look and rethink and figure out how to evolve their data centers first. The first ones were regulatory, so you think about when you were the pharmaceutical GXP compliance, HIPAA in the healthcare side of things, you know, GDPR, so I've got companies that regulate that regulatory. >>What was perceived as a barrier, particularly in some of the more difficult regulatory environment and while the public providers are really evolving and starting to get better regulatory posture is at the same time a lot of our clients were making investment and decide, Hey, how do I really build my private cloud? I'm another big driver that people continue to look at private clouds, whether they're in their data centers or increasingly moving Nikolas is to scale up architectures like high terabyte HANA. If I want a 64 terabyte HANA deployment, while while the AWS footprints get bigger and bigger, sometimes just performance and tuning for those high scale an environment is a big deal. Article article racks, a great example where it's not only do you have something in a highly tuned environment but be given, given some of the licensing arbitrage stuff, it makes it extremely difficult. >>And in a big part of it is data gravity. If I've got these big data sets, if you think about fraud analysis in Hadoop clusters for credit card processing, where I've got high terabyte HANA database, I've got 20 or 30 applications that need to access that data. I can't really put it over a wide area network due to latency. And you know, the cost of moving data around. So what you ultimately end up with is applications clustered around lakes, big pockets of data. And I think that's where we're ending up. And that will be across a hybrid architecture. So that's, we call it, you know, as you look at balancing your apps and your data across public private solutions. That's why we view hybrid as the way that most of our clients are going, given the scale and the amount of applications and data they have. So that's what we refer to as the best of both worlds for hybrid. >>So I saw you nodding a lot. Allow what he was saying for sod. How do you, I mean, as you said, it's a balancing act in terms of how you set your strategy. How do you recommend companies go about thinking in terms of how they allocate their, their cloud? >>Yeah, so I think, you know, we have particular really, really take an application centric approach. Um, you know, I'll go back a couple of years, uh, when our clients were really looking to, uh, really use the public cloud and then they've signed up with one or more public cloud providers and then they, you know, move some applications and then some of them have actually taken a step back. In fact, there's a very global investment bank that I've been working with, um, who, who are taking that approach initially. And now what they've done in working with us is taking a very application centric approach. So we studied their entire suite of applications, understand from a regulatory perspective, from a compliance perspective, from a perspective of security. And this is a global bank. So there are different rules in Europe versus the United States. And so on. So based upon all that we come up with an approach on ward should reside in a private cloud as opposed to orchard resided in a public cloud. >>And you know, obviously there are multiple providers that are reasons to go with more than one cloud from a public perspective, et cetera. So we advise them on that. And then once we're able to do that, then we chart the journey on, you know, what application gets moved and when, and certain applications are very important to them from a performance perspective and they need to scale up and so on. So in those cases, you know, we treat them differently in certain other application cases, you know, we moved them onto a pass and in some other cases, you know, we just move these application into new what's available from a SAS perspective. So really it's a very much an application centric approach on where the workloads, >>is it a living and breathing thing. I mean, we talk about cloud being this journey. It's not a destination. Does this change over time? I mean, it absolutely does. I mean, it's constantly evolving. You know? Did you date or patterns are coming out there? And it was interesting like if you have, a couple of years ago, all we talked about was the app. How are you going to modernize this six or seminars when you get re-imagined in there. But all of a sudden a lot of the conversation shifting, shifting to my data strategy, where did this data reside? Particularly as the data sets get larger and that's moving from what was very centralized in the public data centers into much more distributed architecture. So we see it evolving very quickly. And even with a single application, a great example with a global hotel, they had a reservation system that was strategic application running on an old IBM mainframe. >>They were finding it was just taking too long to get innovative and agile to really support the new mobile applications, their web channels. So they looked at the, Hey, if I were just re-imagine, rewrite this, you know, go put it up in Amazon hot, how long would it take? How much would it cost? They found it was even going to be two or three years and they didn't have the luxury to wait, so they basically wrap that application with API APIs. They expose it with microservices and then developed a cloud native front end with the database cache new technologies that they can now drop every three or four days. They can now get a new mobile application, so you've got agile delivery, they've still got the legacy stuff there. The data's still there now. Now when you go against their web and mobile application, you, you're actually browsing against that new cloud native, you know the database cache. >>When you look at rates and rooms, et cetera, it's only when you transact and reserve the room that it goes back to the main frame. So you agile delivery, they get a lot of the benefits there and then they can offload a lot of the processing on the mainframe. It's only read all the reads up front now and slowly deprecate that over time. Now they, they're now that very interesting hybrid deployment architectures. They, they have a container approach. This database caches, they have two clusters. Those containers running on private cloud, on VMware, and then one running in AWS so they're now can optimize across the public and or hybrid footprint. You know how they do this over the time they then look to evolve that application and started an introduce serverless. So starting to take advantage of Lambda. So there even within a single application you can see it's constantly evolving. They starting in an advantage of the next evolution. So the next one to move beyond containers into more serverless. >>So I mean you both have just given me terrific examples. Your years in financial services, years as a, as a hotel chain. How do you develop best practices? I mean when you're working with clients or really is it case by case? I mean you talked about the decisions and the allocation of cloud. Of course there are regulatory constraints for each company, but are there industry wide best practices? Absolutely. Absolutely. >>I do want to hear, sure. So I'll start with financial services as an example. So if you take the world of banking or insurance, there's obviously, you know, regulatory requirements, compliance requirements that they have to look at. And also if you look at, for example, in banking, a lot of it is very mainframe based. You know, they have very old core banking systems, which is not possible to really move all of that onto public cloud necessarily. And maybe the business case isn't even there. So we have to take a digital decoupling type of approach and figure out, you know, how do we take some of the best bits and then put that on public cloud while still keeping some of the major amount of data is still on the legacy side. So I think it's really an industry specific approach, which on top of which you have to layer on what the local requirements are. >>Yeah, absolutely. I mean, so I spent a lot of work with the life sciences department ceuticals and GXP compliance rules the day there. So how did they start to, they started off, you know, how do we get to private clouds that look and feel a lot like public and then start to move and test the test the waters as they start to migrate into the AWS as a little world. So it is very regular industry specific. So we've, we basically developed a library of this is how you know, this is how you solve for banking, you know, the retail bank on a mainframe, how do I do similar pattern to that hotel front ends. Reinsurance is actually very similar to a lot of, lot of the logic on mainframe. It doesn't make sense to rewrite. There's not enough value in that if I can wrap it in microservices and move out. So that clouds, I mean their roadmaps, obviously every given the scale and complexity of our clients, everyone's going to be slightly different. But they're patterns that are very industry specific. And it gets getting even more interesting as we start to get in, move into IOT and edge. Because when you get into like the, the connected oil and gas or connected mine, all of a sudden it becomes extremely verticalized in industry and industry. >>So the hybrid Creek solves a lot of problems, but I imagine it also creates some other challenges too. What are the challenges and how do you counteract them? Do you want to start Larry? >>Yeah, sure. I mean it's not just hybrid. I think it's, we have much more complex architectures. So with all the power of digital decoupling, you know, creating microservices architectures, being able to pick best of breed services as everything becomes much more dynamic and ephemeral. So we moving for a world where a server in a virtual machine would be up for like 12 months or 15 months to containers that have lifespans of minutes or hours or even seconds now managed in a much more dynamic way with Kubernetes. So that that hotel was 15,000 containers managed by Kubernetes optimized over that environment and even more with serverless. So you've got a very complex environment to manage. And I think as our clients start to really evolve that the application portfolios, you know, SAS cloud, native wrapping legacy, the ability to then seamlessly manage across that environment and optimize and, and even the optimization in the old days we used to optimize around one or two dimensions was a cost or performance and SLA is now we've got to simultaneously take this very complex environment and optimize across performance, service levels, security, compliance and cost. >>So it's not just about cost optimization and they offset each other. If I'm optimizing for performance and service levels, my cost probably goes up. So it becomes a very complex problem. So spend a lot of time looking first. First starting with the operating model, you'd got to operate differently. How do you really get dev sec ops involved so that operations and security baked in, right? When you do the analysis so you're not building something that can't be secure operated and then really transforming the people, right? I mean the one of the hardest thing and place where our clients struggle the most is how do they upskill their organization, change the culture, the behavior. Because great example is we look at how we operate cloud and infrastructure. We want to turn all operators from eyes on glass looking at consoles into developers who are writing the next analytic algorithms to figure out predictive operation, to doing the automation script, to take, to remove mistakes, streamline drive agility, and reduce costs. And ultimately to tune the AI engines that are going to need it to do that. Complex optimization across very, very, very complex architectures. >>So you're talking about the people and the change management. I want to ask about innovation within Accenture and AWS. We heard Andy Jassy this morning in his fireside chat talk about how the company is now obviously a ginormous company, but how it really still has this startup mentality and how and how and what he does to ensure that innovation is still a priority, a relentless focus on the customer, de-centralized nature of the organization. Really focusing on what you're good at, knowing what's in your wheelhouse, how do you think about innovation and hadn't then how do you help clients make sure that they are bringing people along and as you said, give, giving them the sort of developer mindset. Do you want to, >>yeah, so that's absolutely important for us, innovation is very much part of our culture. When I look at my own group, which is intelligent cloud and infrastructure, what we do is we have 30,000 people who are working everyday at our clients and in many ways they understand the client's landscape even better than anybody else because they're working there every day. So some of the things that we do with our clients, our innovation forums where our people bring forward ideas to suggest to clients. So this is something that we do on a regular basis, take it to our clients, CEOs, and invariably several of these ideas actually get put into their whole plan for the following year. So we go innovate with our clients. We've created several digital studios and liquid studios in multiple locations. We've got several of them across the globe. So we bring our clients in for design thinking workshops, suggest ideas and you know, and await with them on things that we can take forward. >>Yeah, and just just to further that, I mean we've always driven it an innovation agenda. We always try and figure out what's next, where do we invest? What's the next bet? I mean, even going back to our cloud first days, I mean we've always been pushing the envelope. I think what Prisaad hit on is a really a step change for us in how we engage. I think in the past we'd come in as the consultants present, et cetera. And I think our clients are bright people. So actually engaging with them and more design thinking. I, we acquired a bunch of digital studios, Fjord and stuff, and I think they've infused this culture of coasts, co-sourcing, collaboration, and creating together. And the dynamic just changes and it's fantastic when the client then is in the room. They own it with you, they close, co-creating. And I think we've been spending a lot of time on how do we transform how we interact and engage with our clients in a much more collaborative way. And it's really changed the changes your relationship with them >>and the technology enables that to Larry and Priscilla, thank you so much for coming on the cube. A really great conversation. Thank you, Rebecca. I'm Rebecca night's stay tuned for more of the cubes live coverage of the Accenture executive summit. Coming up in just a little bit.

>>Bach from Las Vegas. It's the cube covering AWS executive summit brought to you by extension. >>Welcome back everyone to the cubes live coverage of the Accenture executive summit here at the Venetian in Las Vegas. We are part of AWS reinvent. I'm your host, Rebecca Knight. We are joined by two guests for this segment. We have Prisaad Sanker and he is a senior managing director global ICI lead. Thank you so much for coming on the show. Personal and Larry soccer, global managing director ICI offerings. Thank you so much for coming on Larry. So present to minister with you this week marks the one year anniversary of intelligent cloud infrastructure, a group that you lead at Accenture. Tell us a little bit more about, about, first of all why this group was formed and the journey you've had this year, the highest, the highs and lows. >>Sure, sure. So first, first of all, thank you for having us. Um, so as you mentioned, December 1st will be one year of having formed this group. And the reason we did that was because all of our clients are going through a journey of digital transformation. And it's very important for us to be able to support that journey. So there are different elements that we have to bring together around cloud as well as infrastructure. So we brought together this group, which was actually in different parts of Accenture as one particular group, and we call it intelligent cloud. And infrastructure consists of 30,000 people pretty much in every part of the world supporting all different industries. And this is a way for us to bring together not just cloud computing, but also areas like networking, workplace, digital, other digital businesses that we need to be able to support in order to be able to help our clients through their journey of transformation. >>So this, this group was formed at a time of tremendous change and upheaval and the landscape. Talk to us a little bit about, we hear so much about digital transformation, our company's ready. What's the, let us into the client mindset. >>Yeah. So what happens is, you know, different industries obviously are progressing at different speeds. All of our clients are always worried about being disrupted within their industries, either by an existing competitor all by a completely new competitor that doesn't exist. You know, all the stories about, you know, the big companies that existed and almost vanished overnight. So that's something that keeps CEOs and CIO is awake at night just worrying about that. And so digital transformation is very important for them to be relevant to their client. It's all about bringing new products to their clients and also the speed with which they can actually do that. It's no longer enough to be a fast follower. You have to be an innovator. And cloud is the way that this innovation will happen for our clients. And so it's very important for us to be able to bring our group together. We are able to support that journey for our clients. Leary >>want to bring you into this conversation a little bit. It'd be what will be required for enterprises to make this big transition. I mean, he was talking about how you need to be an innovator. You can't just be a fast follower. >> Well, I mean a lot of times I look at it just given the size, the scale of most of our clients who are really up market, most of them don't have the option to just do a rip and replace and just reinvent themselves completely. So it really is how do I very rapidly modernize and transform my business to take advantage of it? And it really needs to start with your application landscape and end data. So how do I start to look at all the possibilities of the AWS is and start to re-imagine, reinvent Duke, use cloud native technologies. Also a significant amount of their estates are already running in legacy environments. >>We get the mainframe or other environments. How do you digitally decouple those so that you can extract value out of that? And ultimately those decisions of apps and data that are going to drive cloud deployments and architectures and data gravity really becomes the key decision factor to decide where do I place this day? And it was a great example today if you saw Jesse's keynote, he announced Achla where they're actually starting to look at how do I move compute and the processing closer to the actual datasets. So actually inverting the problem and moving closer to the data. And then we see that trend starting to proliferate on the other part of the keynote that was very interesting was the five G announcement. And first you heard about AWS pushing into local zones where they were getting much distributing it out closer to them, reduce latency and really starting to push out. >>So ultimately we seen the whole landscape being transformed by data, these new application architectures and where that data resides and out to traditional world that we've known of hybrid with public and private is really transforming with the Amazon outputs, with the BMCs and stuff like that into much more one about shared and dedicated infrastructure. Then the big, the next real big thing that starts to happen then is this whole explosion of IOT. So as price performance goes down with Moore's law, we can start to see a lot more cost effective IOT solutions. And all of a sudden a world that was very centralized, you know, running up in the, in the world of the Amazons had the public cloud is not going to be much more distributed to a lot more of that compute over time gets moved out there. So we've seen a very rapidly evolving landscape. Apps and data are ultimately driving our cloud clients cloud and infrastructure investments. And they're really just trying to figure out how they can rapidly transform their environments to take advantage of this new landscape. >> So both of you are describing this exceedingly complex environment that is changing dizzying speed. I mean, just even this morning, but the Andy Jassy on stage for three hours with all of the new products and services that AWS has coming out with. What is AWS? What is ICI and Accenture doing to help clients navigate this, this, this, this landscape? Prisaad you know, our >>team is, it's not just enough for infrastructure and cloud to be a horizontal function as it used to be. We feel that, you know, one of the things that Accenture really brings to the table is our industry differentiation. Spent a lot of time analyzing the industries that our clients are in. So we've actually changed the team of ICI to be three different things. The first is to be industry led, so it's no longer good enough to be a horizontal function. We have to understand the needs of each industry and really look at how cloud and infrastructure will support that industry. The second is all about intelligence. And Larry just talked about the proliferation of data, but it's also bringing artificial intelligence, making networks much more smart, you know, really infusing intelligence into everything we do. And the third is the concept of being invisible because our clients are expecting infrastructure to just be there all the time. >>They don't really have to understand how it works, but it has to be there. It's just like going to into room and turning on a switch and you expect electricity to be there. So infrastructure has to be very much like, because it has to be ubiquitous, it has to be just available all the time. So those are the things that we are trying to bring to our clients to make it very specific for and very industry specific for for our clients. And this goes into areas like cloud computing. It goes into 5g edge is going to be a big part of what is going to happen in various industries. And as Larry talked about, IOT devices are going to be just proliferating. It's going to be billions of IOT devices. There's trillions of dollars being spent. In fact, I think the spend on IOT is probably bigger than any other area that I have seen probably in my working lifetime. So it's going to be an exciting time to come for us. >>I mean, we tend to think about artificial intelligence as this futuristic Jetsons kind of thing, but really it's, it's here. And now, Larry, can you talk a little bit about how companies are using AI and having an impact already on their businesses? I mean obviously you see a lot of AI being used for different use cases. We saw some great examples today in Jesse's keynote and we're seeing a use for video analytics for example. And AI to try to figure out predictive maintenance type activity. So there's obviously a lot of business use cases. I think what's interesting from our perspective as well is a lot of the operational use cases. So if you take a look at it with all these new innovations, the rapid pace of change that we're seeing with cloud infrastructure, that application landscape, we've started to rely pretty heavily first on analytics to how do we, how do we figure out what's going on, how do we operate efficiently, how do we make sure we don't put the businesses grist, you know, really pivoting from reactive to proactive and predictive operations. >>We've obviously automated everything as much as we can. I've see AI actually playing a very interesting role in how we optimize these environments over time. So as you get a much more complex environment, much more dynamic, and with containers, Coobernetti's, serverless compute dynamic networks that Prisaad was talking about with software defined networking, AI is going to be the only way we can tune and optimize that over time. So you've obviously got all the business use cases that we see in healthcare that we see in mining, predictive operations and stuff like that. But how we actually use AI internally is going to be critical to how we actually be able to manage cloud and infrastructure and really optimize it over time. >>W what is the client? What's, what's on your minds of your customers right now? We know that only 20% of companies out there have really adopted the cloud. Two thirds have really yet to capture the benefits of the cloud. What are you hearing from them? What are they saying to you? What are their pain points? >>So I think, you know, all of our clients realize that ultimately the cloud is going to be where they will be at. You know, data centers are existing today, but at some point, you know, everybody's going to move to the cloud. Most of our clients have taken the easier workloads and you know, the easy part has already been done. That's the first 20% but 80% of the work still remains. And that's the more complicated work that has to come. So they're looking to us to give them the right solutions. And then there's a variety of other factors to be considered. For example, they have to look at security issues. They have to understand that, you know, there are data privacy aspects to be considered. So really it's a question of matching the right private and public options. And as Larry also mentioned, probably only 30 40% of the data will actually sit in the central cloud. Most of the other data is actually gonna move out to the edge with IOT devices and so on. So data gravity, where does your dataset, where does your compute sit? And Andy talked about it as well today in his keynote address. These are all things that are going to keep evolving and I think that's going to really change the landscape. >>I think they, I think they all see the power of cloud. I mean, which in my mind it's really around the innovation cycles. You know, what you look at the pace that they're innovating with with RDS and Redshift. So they all see that power. I think the biggest thing, they struggle with our skills. And culture because how do you upskill, retrain the organization, everything from the new technologies, how to architect in the new world where it's very ephemeral, dynamic, a serverless world. How do you start to adopt those technologies? How do you operationalize it? How do you go beyond just agile and really do true dev sec ops where you're integrating security and operations built in from the ground floor. And a lot of times he's a cultural change is one of the things we see in cloud and infrastructure operations for example, is how do you take develop operators who used to be eyes on glass, looking at console's turn them into developers where they, you know, they're writing the next analytic algorithms to get to predictive there they're automating automation scripts to improve operations and ultimately tuning the AI engines that optimize it. >>And I think that skills and culture barrier is probably the hardest thing for them to overcome. And how do you just, you can't just go to the cloud, you've got to behave differently. It really have to transform how you use it, how you operate and really transform the organization and culture. >>So these change management challenges, where do you even start? Because as you said, the adopting the technology is almost the easy part, or at least the most straightforward, but really getting everyone on board and really changing people's mindsets and mentalities and dispositions and the way that they collaborate with each other and collaborate cross-functionally. So what have you learned within ICI to, to help companies? And what's your advice? >>I think, I think there are three aspects that you have to get right. In fact, I was talking to one of the CEOs of a very large client of ours, and I think you have to get three things right and you've got to get them aligned and moving at the same time. The first obviously is the technology. So you have to understand what makes sense for you, for your industry. Make the right bets because if you make a wrong decision, then you know you're going to set yourself back. So getting the technology right obviously is important. The second is operating model, making sure that you get that the right operating model in place and kicked off right, right upfront. And the third, like Larry said, is transforming your workforce. So making sure that people are, you know, have all the right skill sets when you actually have the operating model and the technology ready. So it's very important to bring all those three aspects together and a company like Accenture, with our background around consulting, around change management, around technology, we're uniquely positioned understanding our client's industries and really bringing all of those three aspects together so that we're able to position our clients to take that journey forward. >>Larry, in terms of next year's Excenture executive summit, look into your crystal ball. You've already talked about a lot of emerging technologies, IOT, edge computing have talked a lot about AI. Of course. What do you think are going to be the hot topics? Looking ahead this this year in ice with an ICI, you >>touched on earlier, I think everyone's going to be talking about data gravity. As you get these bigger and bigger data sets, it becomes, you know, the network's always going to be the bottleneck. So even with Moore's law, stretching from 18 months to 24 the amount of data we produce, particularly with IOT and edge, is really going to transform things. And even though we've got massive network upgrades like 5g coming along, it will never be enough. I mean, that comes along every 12 years. We're seeing a doubling of price performance who competed? I think data gravity, you can start to see a very different landscape where it used to be public and private and now edge is really going to be obliterated to much more seamless architecture. Then there was a lot of the keynote today, and if you start to take a look at local zones and some of the announcements today, they were ready. Amazon was heading there with green Greengrass so you can have much more seamlessness. And how do I get compute closer to the processing? You're gonna be talking a lot about clustering, clustering, compute around datasets versus the other way around. So I think we're gonna see, and I think that's going to happen pretty fast. Usually a lot of this stuff we've been talking about IOT for years. I do think we're on the tipping point. I think we're about to see exponential growth just as price performance >>comes together. Some of the technologies had gotten gotten there, but, but I think that the whole focus on data and data gravity is what you're going to hear a lot about next year. I can't wait to hear the AWS reinvent band. Do a little pink Floyd or something like that for data gravity. We'll Larry and Prisaad. Thank you so much for coming on the cube. It was a pleasure having you on. Thanks for Brooke. I'm Rebecca night's stay tuned for more of the cubes live coverage of the Accenture executive summit.

>> from atop the Salesforce Tower in downtown San Francisco. It's the Q covering Accenture Innovation Date brought to you by ex center >> Hey, welcome back Your body jefe Rick here from the Cube were high atop San Francisco in the essential innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. They worry about security and all kinds of other things. So centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but you're absolutely Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to which all of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know, you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in here, and everyone all right, everyone's >> had a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember We used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service. Now I mean, we went through on premise collaboration, email todo 360 5 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really start to see some scale around it >> and tell me if you agree. I think really, what? The sales forces of the world and the service now is of the world off. 3 65 kind of broke down some of those initial barriers which were all really about security and security. Security secure. It's always too here where now security is actually probably an attribute >> and loud can brink Absolutely. In fact, I'm in those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service. Now to put you know instances on Prime, and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know, there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when you happen to sail sports, it's a lot harder. And so you know. So I think that security problems, I've certainly got away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it's all by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the public domain, right? Not public. >> I think it also help them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So Let's back up 1/2 a step cause then, as you said, a bunch of stuff then went into Public Cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be. Um, but then we ran into a whole new home, Those of issues, right, Which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds there certain attributes that you need to think about and yet from the application point of view, before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How, after they think about what to deploy where I >> think I'll start in the, You know, Larry has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspectives. You got to take a look at you know where your applications have to live water. What are some of the data implications on the applications or do you have by way of regulatory and compliance issues? Or do you have to do as faras performance because certain applications have to be in a high performance environment? Certain other applications don't think a lot of these factors will then drive where these applications need to recite. And then what we're seeing in today's world is really accomplish. Complex, um, situation where you have a lot of legacy, but you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know, clients typically have application portfolios ranging from 520,000 applications. And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms. Guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications going to evolve with its 520,000 and determined hey, and usually using some like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi in and, you know, hybrid cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, et cetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we're gonna modernize that >> it hadn't had a you segment. That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size? Where they should be focusing on. Yes, >> it. Typically, what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications have moved to sass certain other applications you moved past. So you know, you're basically doing the re factoring and the modernization, and then certain others, you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, where is cost savings? Where is, uh, this is just old and where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. >> If >> you could go back three or four years and we had there was a lot of CEO discussions around cost savings. I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get, get new capabilities, market faster to change my customer experience. So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. So we're seeing a huge shift in emphasis or focus at least starting with, you know, how do I get better business agility outta leverage to cloud and cloud native development to get there upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress, So obviously cost still remains a factor, but we seem much more, you know, much more emphasis on agility, you know, enabling the business on giving the right service levels of right experience to the user. Little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds. Easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define them? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talk to my clients and our partners, I think we're all starting to come toe. You know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific workload >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera, so that's the innovations. There obviously agility. You could spend up environments very quickly which is, you know, one of the big benefits of it. The consumption economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it performance, you know, if you think the public world, you know, although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business critical workloads like that article, article rack. You know, the Duke clusters everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terrified Hana database, you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The Laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, You know, as we start to look at the world a lot, there's a ton of Could still living in, You know, whether it's you, Nick system, that IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right. And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take the reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or every three or four days for my mobile application and It's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, but we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're saying is this emerging approach where I can start to take advantage of the innovation cycles that land is that you know, the red shifts the azure functions of the public world. But then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip data that I need to worry about GDP are you know, the whole set of regular two requirements Over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're Still not a number of clients are still, you know, not 100% comfortable from rail client's perspective. >> Gotta meet Teresa Carlson. She'll change him. Who runs that AWS Public Sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this thing. This hotel example that you use because it's is, you know, kind of break in the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move Works fine. Be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where but finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it, the business value, replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and you know the micro service's architecture now. D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The the innovation cycles by public. Bye bye. Wrapping my legacy environment >> in person, you rated jump in and I'll give you something to react to, Which is which is the single glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications and the thing that you just described and everyone wants to be that single pane of glass Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you will Yeah, >> I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers. Goto private cloud and so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, the cantinas and Cuban Edie's. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients. >> Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promise of cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that one application for the hotel, they're actually started, and they've got some actually, now running a native us of their containers and looking at serverless. So you gonna even a single application can span that and one of things we've seen is is first. You know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application. You know, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talked it. It's a very well, despite the power, very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, application service is teams that do the application manager an optimization cloud infrastructure, you know, how do we get better alignment that are embedded security, You know, how do you know what are managed to Security Service's and bringing those together? And then what we did was we looked at, you know, we got very aggressive of cloud for a strategy and, you know, how do we manage the world of public. But when looking at the public providers of hyper scale er's and how they hit incredible degrees of automation, we really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys they're doing that? We came up with this concept We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy environment and started looking say OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl and >> my business is so unique. The Larry no business out there has the same process that we have. So we started make you know how to be >> standardized like center hybrid cloud solution apart with HP. Envy em where we, you know, how do we that was an example. So we can get thio because you can't automate unless you standardise. So that was the first thing you know, standardizing service catalog. Standardizing that, um, you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now, but truly putting the security and and operations into Deb set cops of bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're writing the automation script to take work, you know, test work out. Right. And over time, they'll be tuned in the air. Aye, aye. Engines to really optimize the environment and then finally has presided. Looted thio. Is that the platforms that control planes? That doing that? So, you know, we What we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms and then the application teams with it with our my wizard framework, and we've been starting to bring that together. You know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide, you know, automation Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a iob is right. I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops, that's what we use. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control, I reporting et cetera. Right >> Exactly. Then can plug in and integrate, you know, third party tools. I had to do some strategic function. >> I'm just I'm just >> curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app. Some of them are coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds, that just with the wrong it was just the wrong application? The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, >> I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options, like Aunt Ours and out pulls and other stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that and you see many more options around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, you know, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know, that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed that look >> e. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were big cap ex businesses, and all of a sudden they're using this consumption consumption model. And they weren't really They didn't have a function to go and look at the thousands or millions of lines of it, right? You know, as your statement, exactly think they misjudged, you know, some of the scale on B e e. I mean, that's one of the reasons we started. It's got to be an application lead modernization that really that will dictate that. And I think in many cases, people didn't may not have thought through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. You know, I've got a 64 terabyte hana, and that's the core. My crown jewels. That data, you know, how do I get that to tensorflow? How'd I get that >> right? But if Andy was >> here, though, Andy would say, we'll send down the snow. The snow came from which virgin snow plows Snowball snowball. Well, they're snowballs. But we've seen the >> hold of a truck killer >> that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they you know they're pushing. Get that date end in this single source course than to move it, change it, you know you run it. All these micro lines of billing statement take >> the hotel. I mean, their data stolen the mainframe. So if they may want need to expose it? Yeah, they have a database cash, and they move it out. You know, the particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue. Because no matter how much you know, while Moore's law might be might have elongated from 18 to 24 months, the network will always be the bottle, Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better than network becomes more of a bottleneck. Conned. That's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get. Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith o r. Right Or, you know, highlight and see type or so egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know that That's been a big issue. >> You know, it's funny, I think, and I think a lot of the issue, obviously complexity building. It's a totally different building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it. And they're running in the data center in this kind of this. Turn it on, turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But but the kind of clothes on our conversation I won't talk about a I and applied a I. CoSine is a lot of talk in the market place, but a time machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. Yeah, yeah, >> absolutely completely agree with you in fact. Ah, essential. We actually referred to the Seoul area as Applied intelligence. Ah, and that's our guy, right? And, uh, it is absolutely to add more and more automation Move everything Maur toe where it's being run by the machine rather than, you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environment is important, right? What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken routing, et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space. Less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, and then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate ones who then tune the aye aye engines that will manage our environment, right. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement between >> when the best thing to you. Then you have dynamic optimization can. You might be up to my tanks at us right now, but you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending >> when you got you got to see them >> together with it. And multi dimension optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the table. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you. Raise Prasad is Larry. I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower. Theis Center. Innovation have in San Francisco. Thanks for watching. We'll see you next time

>> Hey, welcome back. Your body, Jefe Rick here from the Cube were high atop San Francisco in the century innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. There were about security and all kinds of other things, so centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but yeah, absolutely. Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to reach. All of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in >> everyone's, you know, everyone's got a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember we used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service now. I mean, we've went through on premise collaboration, email thio 3 65 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really started. See some scale around it. >> And I think and tell me if you agree, I think really, what? The sales forces of the world and and the service now is of the world office 3 65 kind of broke down some of those initial beers, which are all really about security and security, security, security, Always to hear where now security is actually probably an attributes and loud can brink. >> Absolutely. In fact, I mean, those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service Now to put, you know, instances on prime and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when Europe into sales force, it's a lot harder. And so you know. So I think that security problems have certainly gone away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it sold by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the in the public domain, right? Not public. >> And I think it also helped them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So let's back up 1/2 a step, because then, as you said, a bunch of stuff then went into public cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be, Um, but then we ran into a whole new host of issues, right, which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds. There's certain attributes is that you need to think about and yet from the application point of view before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How should they think about what to deploy where I think >> I'll start in? The military has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspective. You go to take a look at you know where your applications have to live water. What are some of the data implications on the applications, or do you have by way of regulatory and compliance issues, or do you have to do as faras performance because certain applications have to be in a high performance environment. Certain other applications don't think a lot of these factors will. Then Dr where these applications need to recite and then what we think in today's world is really accomplish. Complex, um, situation where you have a lot of legacy. But you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know how clients typically have application portfolios ranging from 520,000 applications? And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms, guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications gonna evolve with its 520,000 and determined hey, and usually using some, like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And, you know, I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi and, you know, every cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, etcetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we gonna modernize that >> it had. And how do you segment? That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size where they should be focusing on us? >> So typically what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications he moved to sass certain other applications you move to pass. So you know, you're basically doing the re factoring and the modernization and then certain others you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have to initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, um, where is cost savings? Where is, uh, this is just old. And where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. If >> you could go back through four years and we had there was a lot of CEO discussions around cost savings, I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get getting your capabilities to market faster, to change my customer experience. So So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. We're seeing a huge shift in emphasis or focus at least starting with, you know, how'd I get better business agility outta leverage to cloud and cloud native development to get their upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress. So So Obviously, cost still remains a factor, but we seem much more for, you know, much more emphasis on agility, you know, enabling the business on, given the right service levels of right experience to the user, little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds, easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define him? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talked more clients and our partners, I think we're all starting to, you know, come to ah, you know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific look >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera. So that's the innovations there obviously agility. You could spend up environments very quickly, which is, you know, one of the big benefits of it. The consumption, economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it, um, performance if you think the public world, you know, Although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business. Critical workloads like that article, article rack, the Duke clusters, everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terabyte Hana database you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, you know, as we start to look at the world a lot, there's a ton of code still living in, You know, whether it's you, nick system, just IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right? And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take their reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now, when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or everything three or four days for my mobile application. And it's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, But we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're seeing is this emerging approach where I can start to take advantage of the innovation cycles. The land is that, you know, the red shifts the functions of the public world, but then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip, a data that I need to worry about GDP are there, you know, the whole set of regular two requirements. Now, over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're still not a number of clients are still, you know, not 100% comfortable from my client's perspective. >> Gotta meet Teresa Carlson. She'll change him, runs that AWS public sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this in this hotel example that you use because it's is, you know, kind of breaking the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move. Works fine, be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where? But finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it the business value of replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and in a micro service's architecture now D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The innovation cycles by public. Bye bye. Wrapping my legacy environment >> and percent you raided, jump in and I'll give you something to react to, Which is which is the single planet glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications in the and the thing that you just described and everyone wants to be that single pane of glass. Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you will Yeah, >> I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers go to private cloud. And so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, cantinas and Cuba needs. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients, >> right? Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promises, cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that that one application for the hotel, they're actually started in. They've got some, actually, now running a native us of their containers and looking at surveillance. So you're gonna even a single application can span that. And one of things we've seen is is first, you know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM, where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talk to it. It's a very well. Despite the power, it's a very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, Application Service's teams that do that Application manager, an optimization cloud infrastructure. How do we get better alignment that are embedded security, You know, how do you know what are managed to security service is bringing those together. And then what we did was we looked at, you know, we got very aggressive with cloud for a strategy and, you know, how do we manage the world of public? But when looking at the public providers of hyper scale, er's and how they hit Incredible degrees of automation. We really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys we're doing that We came up with this concept. We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy, environment, and start a look and say, OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl >> and my business is so unique. The Larry no business out there has the same process that way. So >> we started make you know how to be standardized like center hybrid cloud solution important with hp envy And where we how do we that was an example of so we can get to you because you can't automate unless you standardise. So that was the first thing you know, standardizing our service catalog. Standardizing that, um you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now. But truly putting the security and and operations into Deb said cops are bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re Skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're riding the automation script to take work, you know, test work out right. And over time they'll be tuning the aye aye engines to really optimize environment. And then finally, has Prasad alluded to Is that the platforms that control planes? That doing that? So, you know what we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms, and then the application teams with it with my wizard framework, and we started to bring that together you know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide. You know, it's automation. Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a I ops, right? I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops. That's what we you A ups. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control? Aye, aye. Reporting et cetera. Right? >> Exactly. Then can plug in and integrate, you know, third party tools to do straight functions. >> I'm just I'm just curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app, something we're coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds that just with the wrong. It was just the wrong application. The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options like an tars and out pulls an actor stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that, then you see many more options around around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed. That left >> E. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were a big cap ex businesses, and all of a sudden they're using this consumption, you know, consumption model. And they went, really, they didn't have a function to go and look at be thousands or millions of lines of it, right? You know, as your statement Exactly. I think they misjudged, you know, some of the scale on Do you know e? I mean, that's one of the reasons we started. It's got to be an application led, you know, modernization, that really that will dictate that. And I think In many cases, people didn't. May not have thought Through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. And if I've got a 64 terabyte Hana and that's the core, my crown jewels that data, you know, how do I get that to tensorflow? How'd I get that? >> Right? But if Andy was here, though, and he would say we'll send down the stove, the snow came from which virgin snow plows? Snowball Snowball. Well, they're snowballs. But I have seen the whole truck killer that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they, you know, they're pushing. Get that date end in this single source. Of course. Then to move it, change it. You know, you run into all these micro lines of billing statement, take >> the hotel. I mean, their data stolen the mainframe, so if they anyone need to expose it, Yeah, they have a database cash, and they move it out, You know, particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue because no matter how much you know, while Moore's Law might be might have elongated from 18 to 24 months, the network will always be the bottle Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better. The network becomes more of a bottleneck. And that's a It's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith. Oh, all right. Or, you know, highlight and see type. Also, egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know, that's being a big issue, >> you know, it's funny, I think, and I think a lot of the the issue, obviously complexity building. It's a totally from building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it and they're running in the data center in this kind of this. Turn it on, Turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But it kind of close on our conversation. I won't talk about a I and applied a Iot because he has a lot of talk in the market place. But, hey, I'm machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. Yeah, yeah, >> absolutely. Completely agree with you. In fact, attack sensual. We actually refer to this whole area as applied intelligence on That's our guy, right? And it is absolutely to add more and more automation move everything Maur toe where it's being run by the machine rather than you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environments comported right. What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken rounding et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space, less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, And then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate one too. Then tune the aye aye engines that will manage our environment. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement. You know, between >> when the best thing to you, then you have dynamic optimization. Could you might be optimizing eggs at us right now. But you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending when you got me. They got to see them >> together with you and multi dimension. Optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the tables. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you, Grace. Besides Larry, I'm Jeff. 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