(calm tech music) >> Hello everyone. Welcome back to the AWS Cube coverage of Reinvent 2022. I'm John Fur, host of the Cube. We got a great interview segment here co-creating innovation with E.design. We got Shigeo Kuwabara who is with the President and the Chief Executive Officer E.design Insurance, and Akiko Hora Senior Managing Director Financial Services in Japan Inclusion and Diversity Lead at Accenture Japan. Thank you for joining me today. Thanks for coming on the cube. >> You're welcome, You're welcome, Thank you. >> I love this topic. E.design Create co-creating innovation automobile insurance with a product called "&e" It's cloud-based advanced automobile insurance system you guys built and called Safe Driving Together an initiative that uses data to reduce accidents. So great stuff. So let's get into it. Tell us about eDesign Insurance and your vision behind transforming to insurance tech company. Combining the technology, new type of automobile insurance for a digital age. >> Okay. With the pandemic of Covid 19 dissertation is accelerating at rapid pace everywhere. First, insurance were required to define the kind of easy to use, meaningful service they wanted to offer their customers. eDesign in collaboration with Accenture, sought to redefine the company's mission, vision and values by embracing the customer experience in a new way. While a customer's traditional view of automobile insurance is "just in case" Accenture and eDesign form the view that what customers really want is accident prevention. With a redefined objective of co-creating with customers not only peace of mind in the event of an accident, but also a world without accidents. ANDI developed a service that uses cutting edge digital technologies to create a safer and more secure car experience. >> Akiko talk about from insurance perspective and Accenture you know, we know about FinTech, you got InsureTech this is a segment that's growing rapidly, lot of data lot of new capabilities with the cloud. Can you share your thoughts on this new opportunity? >> This is a new innovation for many insurance client especially who owns, the traditional policyholder and the new generations. So they that give the new experience for customers, it makes a big change for the customer experience, and that eDesign is leading this experience in the world I think. >> Awesome. What are the key features of the advanced cloud-based automobile insurance system you guys call ANDI, and how does it work? >> The most advanced full crowd insurance system in the world and it embraces digital convenience to the fullest with a concept of creating safety with data; ANDI enables that initiative Safe Driving Together. It designs new initiative, aims to use available data to reduce the risk and causes of an accident, and to make society as a whole, as a whole safer and more secure. >> Why did you choose Accenture and AWS for this innovation? What unique value do they bring? >> Good question about Accenture. Accenture supported us in a wide range of areas including business, design, and IT. In addition to the industry knowledge embodiment of vision, and definition requirements. The PMO eliminated communication loss between the business and IT sites, and as a result the development was completed in a short period of time. In addition, Accenture studies in cutting edge digital technologies such as AI and data analysis is necessary to become an insured insurance company. And I appreciate Accenture's ability to provide such capabilities as well. >> Akiko talk about the IOT implementation here. A lot of data, a lot of design work. >> Yeah >> Take us through the experience. >> Okay. >> And how does Amazon and Accenture come together. >> ANDI and to support safe driving with eDesign insurance for the compact IOT car sensor with this size to put free charge for all of the policyholders to use a language mobile app. The system captures capture and monitors the drivers driving data, diagnosed and driving mood, and driving behavior which is safe or not and supports safe driving. In the event of the accident the system automatically detect the impact and can summarize the accident situation which is very difficult for the driver to recognize by themselves, and the location, location data. And many others and driver can then report the accident with single tap on their smartphone, very easy. And request assistance or repair shop on the spot. It's very safe and also very smooth for the giving the good experience for customers. >> I know Accenture has great expertise, that's one. But you have been in both involved in this smart market rollout. Can you explain that? The smart market rollout? >> Yeah, it's, it was very interesting that we we had the very smooth importation with eDesign and especially AWS allow us to give the open and crowd system to strong collaboration with many other ecosystem partners and many AI sensors and many IOT sensors opportunity. That gives us a lot of experience and give more opportunity for an eScape company like eDesign sample, so that can be more smooth and open implementation for the future. >> That's great rollout. You know we love this example of AWS Accenture eDesign co-creation. It reminds me of the big super cloud trend where industries can be refactored and and and scaled up. So how was ANDI built and what were the requirements driving the technical solution? >> We, we, we, we brought, we planned the architecture how that works for the future and especially Kuwabarason and the great leadership. He doesn't like something which already in the market and also which can be more fit for the future, the solution which fit for the future and maybe that can allow market customers to have big experience. That's why we, we choose open crowd, new trend, new digital trend and IOT or whatever. That gives our architecture definition, which can, lead by Kuwabarason with AWS with this crowd solution as well as with very packaged basis and also open connection with many other AI in the new technology. So that's why it can be more, this solution going to be grow more in the future and we will have more surprises in the future. Kuwabarason if you have some add add comment please >> Go Ahead. >> (laughing) >> Go ahead. What's your thought? Share? >> Thank, thank you Horason very good comment (laugh). So in collaboration with Accenture, I could develop our team's capability. Because we are working together like one team. That is a key success factor I think. >> Talk about the customer experience, and the results. What feedback have you received from your customers and what does the data say? >> Okay. One interesting feedback we receive is "I was always concerned about my wife's love of driving, but by showing her the ANDI driving score, I was able to point it out to her objectively, which was very helpful." That was a good feedback. In this way there are many positive feedback about the ability of visualize the safety, and danger of ones own driving. When I hear customers say that they can now drive more safely because they can objectively identify their bad driving through ANDI's safe driving program I feel very happy that we created ANDI >> Kiko your thoughts? >> Yeah, it's, it's very obvious that the customers likes how, customers likes the sensor saying how they are driving and they, they they sense my driving behavior is safe they are going to be confident. If not, they going to be very careful in the future that's happening. And maybe that can be aligned with insurance which eDesign is giving is more they feel more confident to drive in in many areas. And also that can give more opportunity that they can have more new type of insurance and new experience with the car. That's, that's kind of the interesting make up of power of the driving including the sensor would be happening. That can be good news for us and we can be more creative to think about new experience for customers. >> Congratulations for receiving the highest IT grand prize from the IT award sponsored by the Japan Institute of Information Technology. What's next for eDesign? Congratulations. What's next? How do you take it further, to change to transform the insurance business? >> Okay. I believe ANDI's strength lies in its data. By sharing data with our customers in a timely manner we contribute to their safe driving. We hope to work with customers to create a safe driving experience that is based on parts and that can be enjoyed like a game. Furthermore, we would like to create a society and community where accidents are less likely to occur. Based on the accumulated data in cooperation with local governments and other organizations. We'd like to contribute to the realization of such a safe and secure society by acquiring and analyzing solid data through ANDI On what kind of accidents occur and under what circumstances. >> Akiko Big awards. What's next? AWS, Accenture, eDesign take us through the vision. >> Yeah, it's, it's, I'm, I'm looking forward to do to do the next things and actually eDesign have not only auto insurance, they cover more home and also many others. So that can be giving the more safer opportunity for customers. They can leave their home very smoothly and even some disaster happening, they can escape very safely. Whatever happening in the family like childcare or maybe even their pet have some challenges we can take care of them and that's kind of many experience which which can align with eDesign's insurance. Most of the things we can give lot of safe and with data and also some IOT things and also insurance that's giving the more opportunity and something can truly resolve the social issue. That can be many opportunities. So that's why we have some plan. But we like to we like to keep a secret for the next future. >> Safe driving together, unlock benefits by gamifying and creating cloud-based advanced data, IOT sensors, encouraging drivers to work together to be safe. This is very, very an important story and thank you so much for sharing. eDesign, thank you for coming on. Congratulations on your awards, and transforming insurance tech. It should be fun. Not a hassle. Thank you for sharing. >> Thank you very much. >> Very much. >> Okay. eDesign co-creating innovation. This is the story of Cloud Next Generation. I'm John Fur the Cube, part of the AWS Reinvent 2022 Cube coverage here with Accenture. Thanks for watching. (calm tech music)

>>from around the globe. It's the Cube presenting enterprise. Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Hello, everyone, and welcome to our continuing Siri's covering data automation brought to you by Io Tahoe. Today we're gonna look at how to ensure enterprise resilience for hybrid and multi cloud. Let's welcome in age. Eva Hora, who is the CEO of Iota A J. Always good to see you again. Thanks for coming on. >>Great to be back. David Pleasure. >>And he's joined by Fozzy Coons, who is a global principal architect for financial services. The vertical of financial services. That red hat. He's got deep experiences in that sector. Welcome, Fozzie. Good to see you. >>Thank you very much. Happy to be here. >>Fancy. Let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and and how it works. >>Sure, yes. So the hybrid cloud is a 90 architecture that incorporates some degree off workload, possibility, orchestration and management across multiple clouds. Those clouds could be private cloud or public cloud or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand. Allocation of resources across clouds and separate clouds can become hydrate when they're similarly >>interconnected. And >>it is that interconnectivity that allows the workloads workers to be moved and how management can be unified in off the street. You can work and how well you have. These interconnections has a direct impact on how well your hybrid cloud will work. >>Okay, so we'll fancy staying with you for a minute. So in the early days of Cloud that turned private Cloud was thrown a lot around a lot, but often just meant virtualization of an on PREM system and a network connection to the public cloud. Let's bring it forward. What, in your view, does a modern hybrid cloud architecture look like? >>Sure. So for modern public clouds, we see that, um, teams organizations need to focus on the portability off applications across clouds. That's very important, right? And when organizations build applications, they need to build and deploy these applications as small collections off independently, loosely coupled services, and then have those things run on the same operating system which means, in other words, running it on Lenox everywhere and building cloud native applications and being able to manage and orchestrate thes applications with platforms like KUBERNETES or read it open shit, for example. >>Okay, so that Z, that's definitely different from building a monolithic application that's fossilized and and doesn't move. So what are the challenges for customers, you know, to get to that modern cloud? Aziz, you've just described it. Is it skill sets? Is that the ability to leverage things like containers? What's your view there? >>So, I mean, from what we've seen around around the industry, especially around financial services, where I spent most of my time, we see that the first thing that we see is management right now because you have all these clouds and all these applications, you have a massive array off connections off interconnections. You also have massive array off integrations, possibility and resource allocations as well, and then orchestrating all those different moving pieces. Things like storage networks and things like those are really difficult to manage, right? That's one. What s O Management is the first challenge. The second one is workload, placement, placement. Where do you place this? How do you place this cloud? Native applications. Do you or do you keep on site on Prem? And what do you put in the cloud? That is the the the other challenge. The major one. The third one is security. Security now becomes the key challenge and concern for most customers. And we could talk about how hundreds? Yeah, >>we're definitely gonna dig into that. Let's bring a J into the conversation. A J. You know, you and I have talked about this in the past. One of the big problems that virtually every companies face is data fragmentation. Um, talk a little bit about how I owe Tahoe unifies data across both traditional systems legacy systems. And it connects to these modern I t environments. >>Yeah, sure, Dave. I mean, fancy just nailed it. There used to be about data of the volume of data on the different types of data. But as applications become or connected and interconnected at the location of that data really matters how we serve that data up to those those app. So working with red hat in our partnership with Red Hat being able Thio, inject our data Discovery machine learning into these multiple different locations. Would it be in AWS on IBM Cloud or A D. C p R. On Prem being able thio Automate that discovery? I'm pulling that. That single view of where is all my data then allows the CEO to manage cast that can do things like one. I keep the data where it is on premise or in my Oracle Cloud or in my IBM cloud on Connect. The application that needs to feed off that data on the way in which you do that is machine learning. That learns over time is it recognizes different types of data, applies policies to declassify that data. Andi and brings it all together with automation. >>Right? And that's one of the big themes and we've talked about this on earlier episodes. Is really simplification really abstracting a lot of that heavy lifting away so we can focus on things A. J A. Z. You just mentioned e nifaz e. One of the big challenges that, of course, we all talk about his governance across thes disparity data sets. I'm curious as your thoughts. How does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations, which, of course, are are particularly acute within financial services. >>Oh, yeah, Yes. So for banks and the payment providers, like you've just mentioned their insurers and many other financial services firms, Um, you know, they have to adhere Thio standards such as a PC. I. D. S s in Europe. You've got the G g d p g d p r, which requires strange and tracking, reporting documentation. And you know, for them to to remain in compliance and the way we recommend our customers to address these challenges is by having an automation strategy. Right. And that type of strategy can help you to improve the security on compliance off the organization and reduce the risk after the business. Right. And we help organizations build security and compliance from the start without consulting services residencies. We also offer courses that help customers to understand how to address some of these challenges. And that's also we help organizations build security into their applications without open sources. Mueller, where, um, middle offerings and even using a platform like open shift because it allows you to run legacy applications and also continue rights applications in a unified platform right And also that provides you with, you know, with the automation and the truly that you need to continuously monitor, manage and automate the systems for security and compliance >>purposes. Hey, >>Jay, anything. Any color you could add to this conversation? >>Yeah, I'm pleased. Badly brought up Open shift. I mean, we're using open shift to be able. Thio, take that security application of controls to to the data level. It's all about context. So, understanding what data is there being able to assess it to say who should have access to it. Which application permission should be applied to it. Um, that za great combination of Red Hat tonight. Tahoe. >>But what about multi Cloud? Doesn't that complicate the situation even even further? Maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi >>cloud a swell. Yeah, sure. >>Yeah. So the right automation solution, you know, can be the difference between, you know, cultivating an automated enterprise or automation caress. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So that means have an automation solution that provides that provides, um, you know, promotes I t availability and reliability with your platform so that you can provide, you know, enterprise great support, including security and testing, integration and clear roadmaps. The second thing is vendor interoperability interoperability in that you are going to be integrating multiple clouds. So you're going to need a solution that can connect to multiple clouds. Simples lee, right? And with that comes the challenge off maintain ability. So you you you're going to need to look into a automation Ah, solution that that is easy to learn or has an easy learning curve. And then the fourth idea that we tell our customers is scalability in the in the hybrid cloud space scale is >>is >>a big, big deal here, and you need a to deploy an automation solution that can span across the whole enterprise in a constituent, consistent manner, right? And then also, that allows you finally to, uh, integrate the multiple data centers that you have, >>So A J I mean, this is a complicated situation, for if a customer has toe, make sure things work on AWS or azure or Google. Uh, they're gonna spend all their time doing that, huh? What can you add really? To simplify that that multi cloud and hybrid cloud equation? >>Yeah. I could give a few customer examples here Warming a manufacturer that we've worked with to drive that simplification Onda riel bonuses for them is has been a reduction cost. We worked with them late last year to bring the cost bend down by $10 million in 2021 so they could hit that reduced budget. Andre, What we brought to that was the ability thio deploy using open shift templates into their different environments. Where there is on premise on bond or in as you mentioned, a W s. They had G cps well, for their marketing team on a cross, those different platforms being out Thio use a template, use pre built scripts to get up and running in catalog and discover that data within minutes. It takes away the legacy of having teams of people having Thio to jump on workshop cause and I know we're all on a lot of teens. The zoom cause, um, in these current times, they just sent me is in in of hours in the day Thio manually perform all of this. So yeah, working with red hat applying machine learning into those templates those little recipes that we can put that automation toe work, regardless of which location the data is in allows us thio pull that unified view together. Right? >>Thank you, Fozzie. I wanna come back to you. So the early days of cloud, you're in the big apple, you know, financial services. Really well. Cloud was like an evil word within financial services, and obviously that's changed. It's evolved. We talked about the pandemic, has even accelerated that, Um And when you really, you know, dug into it when you talk to customers about their experiences with security in the cloud it was it was not that it wasn't good. It was great, whatever. But it was different. And there's always this issue of skill, lack of skills and multiple tools suck up teams, they're really overburdened. But in the cloud requires new thinking. You've got the shared responsibility model you've got obviously have specific corporate requirements and compliance. So this is even more complicated when you introduce multiple clouds. So what are the differences that you can share from your experience is running on a sort of either on Prem or on a mono cloud, um, or, you know, and versus across clouds. What? What? What do you suggest there? >>Yeah, you know, because of these complexities that you have explained here, Miss Configurations and the inadequate change control the top security threats. So human error is what we want to avoid because is, you know, as your clouds grow with complexity and you put humans in the mix, then the rate off eras is going to increase, and that is going to exposure to security threat. So this is where automation comes in because automation will streamline and increase the consistency off your infrastructure management. Also application development and even security operations to improve in your protection, compliance and change control. So you want to consistently configure resources according to a pre approved um, you know, pre approved policies and you want to proactively maintain a to them in a repeatable fashion over the whole life cycle. And then you also want to rapid the identified system that require patches and and reconfiguration and automate that process off patching and reconfiguring so that you don't have humans doing this type of thing, right? And you want to be able to easily apply patches and change assistant settings. According Thio, Pre defined, based on like explained before, you know, with the pre approved policies and also you want is off auditing and troubleshooting, right? And from a rate of perspective, we provide tools that enable you to do this. We have, for example, a tool called danceable that enables you to automate data center operations and security and also deployment of applications and also obvious shit yourself, you know, automates most of these things and obstruct the human beings from putting their fingers on, causing, uh, potentially introducing errors right now in looking into the new world off multiple clouds and so forth. The difference is that we're seeing here between running a single cloud or on prem is three main areas which is control security and compliance. Right control here it means if your on premise or you have one cloud, um, you know, in most cases you have control over your data and your applications, especially if you're on Prem. However, if you're in the public cloud, there is a difference there. The ownership, it is still yours. But your resources are running on somebody else's or the public clouds. You know, e w s and so forth infrastructure. So people that are going to do this need to really especially banks and governments need to be aware off the regulatory constraints off running, uh, those applications in the public cloud. And we also help customers regionalize some of these choices and also on security. You will see that if you're running on premises or in a single cloud, you have more control, especially if you're on Prem. You can control this sensitive information that you have, however, in the cloud. That's a different situation, especially from personal information of employees and things like that. You need to be really careful off that. And also again, we help you rationalize some of those choices. And then the last one is compliant. Aziz. Well, you see that if you're running on Prem or a single cloud, um, regulations come into play again, right? And if you're running a problem, you have control over that. You can document everything you have access to everything that you need. But if you're gonna go to the public cloud again, you need to think about that. We have automation, and we have standards that can help you, uh, you know, address some of these challenges for security and compliance. >>So that's really strong insights, Potsie. I mean, first of all, answerable has a lot of market momentum. Red hats in a really good job with that acquisition, your point about repeatability is critical because you can't scale otherwise. And then that idea you're you're putting forth about control, security compliance It's so true is I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe a W s is gonna physically secure the, you know, s three, but in the bucket. But we saw so many Miss configurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So this all sounds great. A j. You're sharp, you know, financial background. What about the economics? >>You >>know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. E especially when you think about the work from home pivot and and all the areas that they had toe the holes that they had to fill their, whether it was laptops, you know, new security models, etcetera. So how do organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs so I could, you know, pay it forward or there's a There's a risk reduction angle. What can you share >>their? Yeah. I mean, the perspective I'd like to give here is, um, not being multi cloud is multi copies of an application or data. When I think about 20 years, a lot of the work in financial services I was looking at with managing copies of data that we're feeding different pipelines, different applications. Now what we're saying I talk a lot of the work that we're doing is reducing the number of copies of that data so that if I've got a product lifecycle management set of data, if I'm a manufacturer, I'm just gonna keep that in one location. But across my different clouds, I'm gonna have best of breed applications developed in house third parties in collaboration with my supply chain connecting securely to that. That single version of the truth. What I'm not going to do is to copy that data. So ah, lot of what we're seeing now is that interconnectivity using applications built on kubernetes. Um, that decoupled from the data source that allows us to reduce those copies of data within that you're gaining from the security capability and resilience because you're not leaving yourself open to those multiple copies of data on with that. Couldn't come. Cost, cost of storage on duh cost of compute. So what we're seeing is using multi cloud to leverage the best of what each cloud platform has to offer That goes all the way to Snowflake and Hiroko on Cloud manage databases, too. >>Well, and the people cost to a swell when you think about yes, the copy creep. But then you know when something goes wrong, a human has to come in and figured out um, you brought up snowflake, get this vision of the data cloud, which is, you know, data data. I think this we're gonna be rethinking a j, uh, data architectures in the coming decade where data stays where it belongs. It's distributed, and you're providing access. Like you said, you're separating the data from the applications applications as we talked about with Fozzie. Much more portable. So it Z really the last 10 years will be different than the next 10 years. A. >>J Definitely. I think the people cast election is used. Gone are the days where you needed thio have a dozen people governing managing black policies to data. Ah, lot of that repetitive work. Those tests can be in power automated. We've seen examples in insurance were reduced teams of 15 people working in the the back office China apply security controls compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDP are in CCP a last year, very much the economic effect of reduce headcounts on on enterprises of running lean looking to reduce that cost. This year, we can see that already some of the more proactive cos they're looking at initiatives such as net zero emissions how they use data toe under understand how cape how they can become more have a better social impact. Um, and using data to drive that, and that's across all of their operations and supply chain. So those regulatory compliance issues that may have been external we see similar patterns emerging for internal initiatives that benefiting the environment, social impact and and, of course, course, >>great perspectives. Yeah, Jeff Hammer, Bucker once famously said, The best minds of my generation are trying to get people to click on ads and a J. Those examples that you just gave of, you know, social good and moving. Uh, things forward are really critical. And I think that's where Data is gonna have the biggest societal impact. Okay, guys, great conversation. Thanks so much for coming on the program. Really appreciate your time. Keep it right there from, or insight and conversation around, creating a resilient digital business model. You're watching the >>Cube digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data Lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated, sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands In terms of digital resilience, Sign up for a minimal cost commitment. Free data Health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer Now >>Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iot, Tahoe and Shirish County up in. Who's the vice president and head of U. S. Sales at happiest Minds? Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Trust you guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. >>A former in 2011 Happiest Mind is a born digital born a child company. The reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, Our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 i t services company in the great places to work serving hour glass to ratings off 41 against the rating off. Five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you said you had up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What >>do you what? Your >>day to day focus with customers and partners. What you focused >>on? Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds, you know? Why do you guys choose toe work closely together? >>Very good question. Um, we see Hyo Tahoe on happiest minds as a great mutual fit. A Suresh has said, uh, happiest minds are very agile organization um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. Uh, we're using machine learning algorithms to make data discovery data cataloging, understanding, data done. See, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility that happiest minds have that that's a really nice combination work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said, are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera on. Then finally, I think they're both Challenger brands on happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us at Ideo Tahoe to >>great thank you for that. So Russia, let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see, and maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic, times when you say Dave, customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organisation's trying to adopt onto the digital technologies. Right there has bean lot off data which has been to manage by these customers on There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology, right where we bring in the data. Complaints as a service were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business continuity processes from day one, where we were ableto deliver our services without any interruption to the services. What we were delivered to our customers So that is where the digital resilience with business community process enabled was very helpful for us. Toe enable our customers continue their business without any interruptions during pandemics. >>So I mean, some of the challenges that customers tell me they obviously they had to figure out how to get laptops to remote workers and that that whole remote work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, But it sounds like you've got a digital business. Means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on that, for the first step is to identify the critical data. Right. So we this is a six step process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on see how critical their data is, then we help the customers to strategies that right. The most important thing is to identify the most important critical herself. Data being the most critical assert for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them >>at >>all levels in the organization. That is a P for people to understand the importance off the digital ourselves and then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and a holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time, and finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment, we do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, so this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards their digital journey on. They have to face all these as part off the evolving environment on digital journey. And that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance when when your digital business, you're, as you say, you're a data business, so that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data soldiers. It could be on data basis, or it could be even on the data legs. Or it could be a no even on compromise all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. On finally, we also bringing the automated data governance where we can manage the sensory data policies on their later relationships in terms off mapping on manage their business roots on we drive reputations toe Also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. I'm gonna be great if you had an example is well, but maybe you could pick it up from there, >>John. I mean, at a high level, assertions are clearly articulated. Really? Um, Hyoty, who delivers business agility. So that's by, um accelerating the time to operationalize data, automating, putting in place controls and actually putting helping put in place digital resilience. I mean way if we step back a little bit in time, um, traditional resilience in relation to data often met manually, making multiple copies of the same data. So you have a d b A. They would copy the data to various different places, and then business users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. ONDA course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is. And I realized that expression. They used David the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a p I s on. So you don't have the same need thio to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate and that's really where I attack comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, discovering what's dubica? What's redundant? Uh, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates. With our tire, you could do it really very quickly on you can have tangible results within weeks and months on Ben, you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then, once you've done there. Your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls. Um, on you've got a drug toward the business outcomes. Uh, and it's doing those three things together that really deliver for the customer. >>Thank you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome. And we talked to a number of customers in the Cube, and the conclusion is, it's really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed today. >>Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check. Um, this is a is a 2 to 3 week process, uh, to really quickly start to understand on deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data. Onda. We can very rapidly demonstrate how they discovery those catalog e on understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, And so what we tend to find is that we can very quickly, as I say in the matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on then how they can scale that up, take it into production on, then really understand their data state? Better on build. Um, Brasiliense into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys, great conversation. Thanks so much for coming on the program. Best of luck to you and the partnership Be well, >>Thank you, David Suresh. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban are ongoing Siris on data automation without >>Tahoe, digital resilience, automated compliance, privacy and security for your multi cloud. Congratulations. You're on the journey. You have successfully transformed your organization by moving to a cloud based platform to ensure business continuity in these challenging times. But as you scale your digital activities, there is an inevitable influx of users that outpaces traditional methods of cybersecurity, exposing your data toe underlying threats on making your company susceptible toe ever greater risk to become digitally resilient. Have you applied controls your data continuously throughout the data lifecycle? What are you doing to keep your customer on supply data private and secure? I owe Tahoe's automated sensitive data. Discovery is pre programmed with over 300 existing policies that meet government mandated risk and compliance standards. Thes automate the process of applying policies and controls to your data. Our algorithm driven recommendation engine alerts you to risk exposure at the data level and suggests the appropriate next steps to remain compliant on ensure sensitive data is secure. Unsure about where your organization stands in terms of digital resilience. Sign up for our minimal cost commitment. Free data health check. Let us run our sensitive data discovery on key unmapped data silos and sources to give you a clear understanding of what's in your environment. Book time within Iot. Tahoe Engineer. Now. >>Okay, now we're >>gonna go into the demo. We want to get a better understanding of how you can leverage open shift. And I owe Tahoe to facilitate faster application deployment. Let me pass the mic to Sabetta. Take it away. >>Uh, thanks, Dave. Happy to be here again, Guys, uh, they've mentioned names to be the Davis. I'm the enterprise account executive here. Toyota ho eso Today we just wanted to give you guys a general overview of how we're using open shift. Yeah. Hey, I'm Noah Iota host data operations engineer, working with open ship. And I've been learning the Internets of open shift for, like, the past few months, and I'm here to share. What a plan. Okay, so So before we begin, I'm sure everybody wants to know. Noel, what are the benefits of using open shift. Well, there's five that I can think of a faster time, the operation simplicity, automation control and digital resilience. Okay, so that that's really interesting, because there's an exact same benefits that we had a Tahoe delivered to our customers. But let's start with faster time the operation by running iota. Who on open shift? Is it faster than, let's say, using kubernetes and other platforms >>are >>objective iota. Who is to be accessible across multiple cloud platforms, right? And so by hosting our application and containers were able to achieve this. So to answer your question, it's faster to create and use your application images using container tools like kubernetes with open shift as compared to, like kubernetes with docker cry over container D. Okay, so we got a bit technical there. Can you explain that in a bit more detail? Yeah, there's a bit of vocabulary involved, uh, so basically, containers are used in developing things like databases, Web servers or applications such as I have top. What's great about containers is that they split the workload so developers can select the libraries without breaking anything. And since Hammond's can update the host without interrupting the programmers. Uh, now, open shift works hand in hand with kubernetes to provide a way to build those containers for applications. Okay, got It s basically containers make life easier for developers and system happens. How does open shift differ from other platforms? Well, this kind of leads into the second benefit I want to talk about, which is simplicity. Basically, there's a lot of steps involved with when using kubernetes with docker. But open shift simplifies this with their source to image process that takes the source code and turns it into a container image. But that's not all. Open shift has a lot of automation and features that simplify working with containers, an important one being its Web console. Here. I've set up a light version of open ship called Code Ready Containers, and I was able to set up her application right from the Web console. And I was able to set up this entire thing in Windows, Mac and Lennox. So its environment agnostic in that sense. Okay, so I think I've seen the top left that this is a developers view. What would a systems admin view look like? It's a good question. So here's the administrator view and this kind of ties into the benefit of control. Um, this view gives insights into each one of the applications and containers that are running, and you could make changes without affecting deployment. Andi can also, within this view, set up each layer of security, and there's multiple that you can prop up. But I haven't fully messed around with it because with my luck, I'd probably locked myself out. So that seems pretty secure. Is there a single point security such as you use a log in? Or are there multiple layers of security? Yeah, there are multiple layers of security. There's your user login security groups and general role based access controls. Um, but there's also a ton of layers of security surrounding like the containers themselves. But for the sake of time, I won't get too far into it. Okay, eso you mentioned simplicity In time. The operation is being two of the benefits. You also briefly mention automation. And as you know, automation is the backbone of our platform here, Toyota Ho. So that's certainly grabbed my attention. Can you go a bit more in depth in terms of automation? Open shift provides extensive automation that speeds up that time the operation. Right. So the latest versions of open should come with a built in cryo container engine, which basically means that you get to skip that container engine insulation step and you don't have to, like, log into each individual container host and configure networking, configure registry servers, storage, etcetera. So I'd say, uh, it automates the more boring kind of tedious process is Okay, so I see the iota ho template there. What does it allow me to do? Um, in terms of automation in application development. So we've created an open shift template which contains our application. This allows developers thio instantly, like set up our product within that template. So, Noah Last question. Speaking of vocabulary, you mentioned earlier digital resilience of the term we're hearing, especially in the banking and finance world. Um, it seems from what you described, industries like banking and finance would be more resilient using open shift, Correct. Yeah, In terms of digital resilience, open shift will give you better control over the consumption of resource is each container is using. In addition, the benefit of containers is that, like I mentioned earlier since Hammond's can troubleshoot servers about bringing down the application and if the application does go down is easy to bring it back up using templates and, like the other automation features that open ship provides. Okay, so thanks so much. Know us? So any final thoughts you want to share? Yeah. I just want to give a quick recap with, like, the five benefits that you gained by using open shift. Uh, the five are timeto operation automation, control, security and simplicity. You could deploy applications faster. You could simplify the workload you could automate. A lot of the otherwise tedious processes can maintain full control over your workflow. And you could assert digital resilience within your environment. Guys, >>Thanks for that. Appreciate the demo. Um, I wonder you guys have been talking about the combination of a Iot Tahoe and red hat. Can you tie that in subito Digital resilience >>Specifically? Yeah, sure, Dave eso when we speak to the benefits of security controls in terms of digital resilience at Io Tahoe, we automated detection and apply controls at the data level, so this would provide for more enhanced security. >>Okay, But so if you were trying to do all these things manually. I mean, what what does that do? How much time can I compress? What's the time to value? >>So with our latest versions, Biota we're taking advantage of faster deployment time associated with container ization and kubernetes. So this kind of speeds up the time it takes for customers. Start using our software as they be ableto quickly spin up io towel on their own on premise environment are otherwise in their own cloud environment, like including aws. Assure or call GP on IBM Cloud a quick start templates allow flexibility deploy into multi cloud environments all just using, like, a few clicks. Okay, so so now just quickly add So what we've done iota, Who here is We've really moved our customers away from the whole idea of needing a team of engineers to apply controls to data as compared to other manually driven work flows. Eso with templates, automation, previous policies and data controls. One person can be fully operational within a few hours and achieve results straight out of the box on any cloud. >>Yeah, we've been talking about this theme of abstracting the complexity. That's really what we're seeing is a major trend in in this coming decade. Okay, great. Thanks, Sabina. Noah, How could people get more information or if they have any follow up questions? Where should they go? >>Yeah, sure. They've. I mean, if you guys are interested in learning more, you know, reach out to us at info at iata ho dot com to speak with one of our sales engineers. I mean, we love to hear from you, so book a meeting as soon as you can. All >>right. Thanks, guys. Keep it right there from or cube content with.

>>from around the globe. It's the Cube presenting enterprise, Digital resilience on hybrid and multi cloud Brought to You by Iota Ho. Okay, let's now get into the next segment where we'll explore data automation. But from the angle of digital resilience within and as a service consumption model, we're now joined by Yusuf Khan, who heads data services for Iota Ho and Shirish County. Up in Who's the vice president and head of U. S. Sales at happiest Minds. Gents, welcome to the program. Great to have you in the Cube. >>Thank you, David. >>Stretch. You guys talk about happiest minds. This notion of born digital, foreign agile. I like that. But talk about your mission at the company. >>Sure. A former in 2011 Happiest minds Up Born digital born a child company. >>The >>reason is that we are focused on customers. Our customer centric approach on delivering digitals and seamless solutions have helped us be in the race. Along with the Tier one providers, our mission, happiest people, happiest customers is focused to enable customer happiness through people happiness. We have Bean ranked among the top 25 I t services company in the great places to work serving hour glass to ratings off 4.1 against the rating off five is among the job in the Indian nineties services company that >>shows the >>mission on the culture. What we have built on the values, right sharing, mindful, integrity, learning and social on social responsibilities are the core values off our company on. That's where the entire culture of the company has been built. >>That's great. That sounds like a happy place to be. Now you have you head up data services for Iot Tahoe. We've talked in the past. Of course you're out of London. What do you what's your day to day focus with customers and partners? What you focused on? >>Well, David, my team work daily with customers and partners to help them better understand their data, improve their data quality, their data governance on help them make that data more accessible in a self service kind of way. To the stakeholders within those businesses on dis is all a key part of digital resilience that will will come on to talk about but later. You're >>right, e mean, that self service theme is something that we're gonna we're gonna really accelerate this decade, Yussef and so. But I wonder before we get into that, maybe you could talk about the nature of the partnership with happiest minds. You know, why do you guys choose toe work closely together? >>Very good question. Um, we see Io Tahoe on Happiest minds as a great mutual fit. A Suresh has said happiest minds are very agile organization. Um, I think that's one of the key things that attracts their customers on Io. Tahoe is all about automation. We're using machine learning algorithms to make data discovery data cataloging, understanding, data, redundancy, uh, much easier on. We're enabling customers and partners to do it much more quickly. So when you combine our emphasis on automation with the emphasis on agility, the happiest minds have that. That's a really nice combination. Work works very well together, very powerful. I think the other things that a key are both businesses, a serious have said are really innovative digital native type type companies. Um, very focused on newer technologies, the cloud etcetera, uh, on. Then finally, I think that both challenger brands Andi happiest minds have a really positive, fresh ethical approach to people and customers that really resonates with us that I have tied to its >>great thank you for that. So Russia, Let's get into the whole notion of digital resilience. I wanna I wanna sort of set it up with what I see. And maybe you can comment be prior to the pandemic. A lot of customers that kind of equated disaster recovery with their business continuance or business resilient strategy, and that's changed almost overnight. How have you seen your clients respond to that? What? I sometimes called the forced march to become a digital business. And maybe you could talk about some of the challenges that they faced along the way. >>Absolutely. So, uh, especially during this pandemic times when you see Dave customers have been having tough times managing their business. So happiest minds. Being a digital Brazilian company, we were able to react much faster in the industry, apart from the other services company. So one of the key things is the organizations trying to adopt onto the digital technologies right there has bean lot off data which has been to managed by these customers on. There have been lot off threats and risk, which has been to manage by the CEO Seo's so happiest minds digital resilient technology fight the where we're bringing the data complaints as a service, we were ableto manage the resilience much ahead off other competitors in the market. We were ableto bring in our business community processes from day one, where we were ableto deliver our services without any interruption to the services what we were delivering to our customers. >>So >>that is where the digital resilience with business community process enabled was very helpful for us who enable our customers continue there business without any interruptions during pandemics. >>So, I mean, some of the challenges that that customers tell me they obviously had to figure out how to get laptops to remote workers and that that whole remote, you know, work from home pivot figure out how to secure the end points. And, you know, those were kind of looking back there kind of table stakes, but it sounds like you've got a digital business means a data business putting data at the core, I like to say, but so I wonder if you could talk a little bit more about maybe the philosophy you have toward digital resilience in the specific approach you take with clients? >>Absolutely. They seen any organization data becomes. The key on this for the first step is to identify the critical data. Right. So we this is 1/6 process. What we following happiest minds. First of all, we take stock off the current state, though the customers think that they have a clear visibility off their data. How are we do more often assessment from an external point off view on See how critical their data is? Then we help the customers to strategies that right the most important thing is to identify the most important critical herself. Data being the most critical assault for any organization. Identification off the data's key for the customers. Then we help in building a viable operating model to ensure these identified critical assets are secure on monitor dearly so that they are consumed well as well as protected from external threats. Then, as 1/4 step, we try to bring in awareness, toe the people we train them at all levels in the organization. That is a P for people to understand the importance off the residual our cells. And then as 1/5 step, we work as a back up plan in terms of bringing in a very comprehensive and the holistic testing approach on people process as well as in technology. We'll see how the organization can withstand during a crisis time. And finally we do a continuous governance off this data, which is a key right. It is not just a one step process. We set up the environment. We do the initial analysis and set up the strategy on continuously govern this data to ensure that they are not only know managed will secure as well as they also have to meet the compliance requirements off the organization's right. That is where we help organizations toe secure on Meet the regulations off the organizations. As for the privacy laws, >>so >>this is a constant process. It's not on one time effort. We do a constant process because every organization goes towards the digital journey on. They have to face all these as part off the evolving environment on digital journey, and that's where they should be kept ready in terms off. No recovering, rebounding on moving forward if things goes wrong. >>So let's stick on that for a minute, and then I wanna bring yourself into the conversation. So you mentioned compliance and governance. When? When your digital business. Here, as you say, you're a data business. So that brings up issues. Data sovereignty. Uh, there's governance, this compliance. There's things like right to be forgotten. There's data privacy, so many things. These were often kind of afterthoughts for businesses that bolted on, if you will. I know a lot of executives are very much concerned that these air built in on, and it's not a one shot deal. So do you have solutions around compliance and governance? Can you deliver that as a service? Maybe you could talk about some of the specifics there, >>so some of way have offered multiple services. Tow our customers on digital race against. On one of the key service is the data complaints. As a service here we help organizations toe map the key data against the data compliance requirements. Some of the features includes in terms off the continuous discovery off data right, because organizations keep adding on data when they move more digital on helping the helping and understanding the actual data in terms off the residents of data, it could be a heterogeneous data sources. It could be on data basis or it could be even on the data lakes. Or it could be or no even on compromise, all the cloud environment. So identifying the data across the various no heterogeneous environment is very key. Feature off our solution. Once we identify, classify this sensitive data, the data privacy regulations on the traveling laws have to be map based on the business rules. So we define those rules on help map those data so that organizations know how critical their digital assets are. Then we work on a continuous marching off data for anomalies because that's one of the key teachers off the solution, which needs to be implemented on the day to day operational basis. So we're helping monitoring those anomalies off data for data quality management on an ongoing basis. And finally we also bringing the automatic data governance where we can manage the sensory data policies on their data relationships in terms off, mapping on manage their business rules on we drive reputations toe also suggest appropriate actions to the customers. Take on those specific data sets. >>Great. Thank you, Yousef. Thanks for being patient. I want to bring in Iota ho thio discussion and understand where your customers and happiest minds can leverage your data automation capability that you and I have talked about in the past. And I'm gonna be great if you had an example is well, but maybe you could pick it up from there. >>Sure. I mean, at a high level, assertions are clearly articulated. Really? Um, Iota, who delivers business agility. So that's by, um, accelerating the time to operationalize data, automating, putting in place controls and ultimately putting, helping put in place digital resilience. I mean, way if we step back a little bit in time, um, traditional resilience in relation to data are often met manually, making multiple copies of the same data. So you have a DB A. They would copy the data to various different places on business. Users would access it in those functional style owes. And of course, what happened was you ended up with lots of different copies off the same data around the enterprise. Very inefficient. Onda course ultimately, uh, increases your risk profile. Your risk of a data breach. Um, it's very hard to know where everything is, and I realized that expression they used David, the idea of the forced march to digital. So with enterprises that are going on this forced march, what they're finding is they don't have a single version of the truth, and almost nobody has an accurate view of where their critical data is. Then you have containers bond with containers that enables a big leap forward so you could break applications down into micro services. Updates are available via a P I s. And so you don't have the same need to build and to manage multiple copies of the data. So you have an opportunity to just have a single version of the truth. Then your challenge is, how do you deal with these large legacy data states that the service has been referring Thio, where you you have toe consolidate, and that's really where I Tahoe comes in. Um, we massively accelerate that process of putting in a single version of the truth into place. So by automatically discovering the data, um, discovering what's duplicate what's redundant, that means you can consolidate it down to a single trusted version much more quickly. We've seen many customers have tried to do this manually, and it's literally taken years using manual methods to cover even a small percentage of their I T estates with a tire. You could do it really very quickly on you can have tangible results within weeks and months. Um, and then you can apply controls to the data based on context. So who's the user? What's the content? What's the use case? Things like data quality validations or access permissions on. Then once you've done there, your applications and your enterprise are much more secure, much more resilient. As a result, you've got to do these things whilst retaining agility, though. So coming full circle. This is where the partnership with happiest minds really comes in as well. You've got to be agile. You've gotta have controls, um, on you've got a drug towards the business outcomes and it's doing those three things together that really deliver for the customer. Thank >>you. Use f. I mean you and I. In previous episodes, we've looked in detail at the business case. You were just talking about the manual labor involved. We know that you can't scale, but also there's that compression of time. Thio get to the next step in terms of ultimately getting to the outcome and we talked to a number of customers in the Cube. And the conclusion is really consistent that if you could accelerate the time to value, that's the key driver reducing complexity, automating and getting to insights faster. That's where you see telephone numbers in terms of business impact. So my question is, where should customers start? I mean, how can they take advantage of some of these opportunities that we've discussed >>today? Well, we've tried to make that easy for customers. So with our Tahoe and happiest minds, you can very quickly do what we call a data health check on. Dis is a is a 2 to 3 weeks process are two Really quickly start to understand and deliver value from your data. Um, so, iota, who deploys into the customer environment? Data doesn't go anywhere. Um, we would look at a few data sources on a sample of data Onda. We can very rapidly demonstrate how date discovery those catalog e understanding Jupiter data and redundant data can be done. Um, using machine learning, um, on how those problems can be solved. Um, and so what we tend to find is that we can very quickly as I say in a matter of a few weeks, show a customer how they could get toe, um, or Brazilian outcome on. Then how they can scale that up, take it into production on, then really understand their data state Better on build resilience into the enterprise. >>Excellent. There you have it. We'll leave it right there. Guys. Great conversation. Thanks so much for coming on the program. Best of luck to you in the partnership. Be well. >>Thank you, David. Sorry. Thank you. Thank >>you for watching everybody, This is Dave Volonte for the Cuban Are ongoing Siris on data Automation without Tahoe.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon angle. Hello. We wanna welcome back to the Cuban cloud where we're talking to CEOs, C. E. O s, chief technology officers and investors. On the future of Cloud with me is Dave Humphrey, who is the managing director and co head of Private Equity North America at Bain Capital. They've welcome to the Cube. First time, I think. >>First time. Yeah, David, thanks very much for having so >>let's get right into it. As an investor, how are you thinking about the evolution of cloud? When you look back at the last decade, you know it's not gonna be the same, uh, in this coming decade, you know, Thio ironic 2020 is has thrown us into, you know, the accelerated digital transformation and cloud. But how do you look at the evolution of cloud from an investment perspective? What's your thesis? >>That's a great question, David. You know, for us, we're focused on investing in technology and really across the economy. And I'd say the cloud is the overarching trends and dynamic in the technology markets. And really, for two reasons, one is a major shift. Of course, that's going on. But the second and frankly, even more interesting one to us is all the growth that the cloud is creating in the technology marketplace. You know the ship. It has been well covered. But five years ago in 2015, by our analysis, two thirds of all computing workloads were done on premises and Onley. Five years later, that's that's flipped. So two thirds of all computing workloads now done done in the cloud. And, of course, that shift. There's a lot of ramifications as an investor. But even more interesting dust is the growth in technology and the usage of technology that the cloud is creating. So over that same period of time, the total number of computing workloads run has increased by 2.6 times just a five year period time, which is really a a dramatic thing. And it makes sense when you think about all the new software applications that could be created, all the data that could be used by new users and new segments, and the real time inside that could be gleaned from that is that growth that really were focused on investing behind a Z. Investors in technology. You >>know, it's interesting you just took share those numbers and you hear a lot of numbers. I I actually think you you know, you your even being conservative. You know, Ginny Rometty used to talk about 80% of workloads or are still on Prem. Andy Jassy it reinvent said that 96% of spending is still on premises. So that was kind of an interesting stat. And I guess the other thing that I would, I would note is it's not just a share shift. It is. It's not just, you know, the cloud eating away it on Prem. We've clearly seen that, but there's also incremental opportunity as well. If you look at snowflake, for example, and adding value on top of, you know across multiple clouds and creating new markets, so there's there's that, you know, double that 12 punch of stealing share from on Prem but also incremental growth, which is probably accelerated as a result of this, you know, compressed digital transformation. So when you look at the Big Three cloud players, I mean roughly speaking, they probably account for $80 billion in total revenue which I guess is a small portion of the overall I t. Market. So it has a a long way to go. But But what's the best way to get good returns from an investment standpoint without getting clobbered by their tendency to sometimes coop some of the best ideas and put them on their primary services? >>Yeah, absolutely. Well, you know, for us, uh, it really comes back to the same fundamental principles we look for in any investment, which is finding a business that solves a really important problem for its customers and does so in a way that's really advantaged vs competition can and do something that other competitors just can't do, whether those be the hyper scale is that you're describing or, you know, other specialized and focused competitors, and then finding a way that we can partner with those companies to help them to accelerate their growth. So surely the growth of the likes of AWS and Microsoft and Google, as you're describing, has been a profound competitive shift, along with the cloud shift that we've all talked about. And those companies, of course, can offer and do things that you past purveyors of computing couldn't. But fundamentally, they're selling and infrastructure layer, and there is room for all sorts of new competitors and new applications that can do something better than anybody else can. So any company that we're looking at, we're asking ourselves the question. Why are they the best ones to do what they're doing? How could they solve the most problem for their customers and do that in a way that's that's Brazilian and we see lots of those opportunities, >>and I wanna I wanna pick your brain about the Nutanix investment. But before we get there, I wonder if you could just talk about Bain Capital in their their history of investment in both cloud and infrastructure software and and how do those investments? How would they performed? And how do they inform your current thesis? >>Yeah, absolutely. So being Capital was started in in the mid eighties, 1984 actually has a spin out of being a company consulting, and the basic premise was that if we're good at advising and supporting businesses, we should partner with them and invest behind them, and if they do well, we'll do well. And, as I said, focusing on these businesses but do something really valuable for their customers in a riel advantaged way, with some discontinuous growth opportunity that's led us to grow a lot. You know, we started out actually in the venture business and grew into the private equity business. But now we invest across all life stages of companies and all over the world. So we're $105 billion in assets that we managed across 10 lines of business on were truly global. So I think we have about 470 investment professionals and 210 of those at this point are located outside the U. S. One of the really interesting things for us in investing in technology broadly and in infrastructure in the cloud more specifically is that we're able to do that all over the world. And we're able to do that across all the different life stages of companies. We have a thriving venture capital business that really we've been in since the origins of being capital has invested across countless cloud and security and infrastructure businesses taken successful companies public like like solar wind sold companies to strategic and grown businesses. You know, in really thriving ways we have a, um, growth mid market growth technology business that we launched last year. Called their Technology Opportunities Fund. They've made a really interesting cloud based investment in a company called the Cloud Gurus Cloud Guru Excuse me? That trains the next generation of I t professionals to be successful in the club on then, of course, in our private equity business, you know where I spend my time. We are highly focused on technology sector and the the impacts of the cloud in that sector. Broadly, we've invested in many infrastructure businesses, scale businesses like BMC software and Rockets software security businesses like blue coat systems and semantic. And of course, for those big businesses they've got both on premises solutions. They've got cloud solutions, and often we're focused on helping them continue to grow and innovate and take their solutions to the cloud. And then, uh, that's taking us to our most recent investment in Nutanix that we're very excited about it. We think it's truly a growth business in a large market that has an opportunity to capitalize on these trends we're talking about. >>I wonder if you could comment on some of the changes that have occurred. You guys have been in the private equity business for a long time. And if you look at what you know, kind of the early days of private equity, it was all you know, even, uh, suck as much cash out of the company is possible. You know, whatever's left over will figure out what to do with it. It it seems like you know, investors have realized Wow, we can actually, if we put a little investment in and do some engineering and some go to market, we can actually get better multiples. And so you've got the kind of rule of 30 35 40 where he made a plus. Growth is kind of the metric. How do you think about that? And look at that evolution. >>Yeah, you know, it's interesting because in many ways, being capital was started as the antithesis to what to what you're describing. So we started again, as as with a strategic lens and a focus on growth and a focus on if we got the long term and the lasting impact of our business is right, that the returns would would follow. And you're right that the market has evolved in that way. I mean, I think some of the some of the dynamics that we've seen has been certainly growth of the private equity business. It's It's become a much larger piece of the, you know, the capital markets than it was certainly 10 years ago in 20 years ago. Also, with that growth comes the globalization, that business all over the world and the specialization. So you certainly see technology focused firms and technology focused funds in a way that you didn't see, uh, 10 years ago, or certainly 20 years ago actually being capital. Interestingly enough, we had a technology focused fund in 1989 called called Being Information Partners. So we've been focused on the sector for a very long time. But you certainly see ah, lot more technology investors, uh, than than you did you know 10 or 20 years ago? >>How are you thinking about valuations? Thes days? I mean, that is good. It's good to be in tech. It's even better to be in the cloud. You know, Service officer, software Cloud. You know if if if you're looking at, you know some of the companies, especially the work from home pivot. But a lot of that appears to be. You know, many people believe it's going to be permanent. How are you feeling about the both public market and private market valuations in that dynamic? >>Yeah, well, you know, it's it's amazing, right? I don't think any of us in March, when the covert crisis was just emerging, would have anticipated that that come November, the markets, and certainly the technology markets would be even more robust and stronger than than they were say in January February. But I think it's a testament to the resilience of the technology on that just how intricate and intertwined technology has become with our daily lives and and how much companies depend on its use. And frankly, it's been the cove environments that an accelerant for many of the ways in which we depend on technology. So witnessed this interview, of course, through through the through the cloud, and you're seeing the way that we operate our business day to day the way cos they're accessing their data and information. It's only further accelerated the need for technology and the importance of that technology to how how businesses operate. So I think you're seeing that reflected in the market values out there. But, you know, frost work. We're focused on businesses that still have that catalytic opportunity ahead that can more than compensate for for the price of entry. >>So let's talk about this massive investment. You guys made a Nutanix 750 million, I guess, is a small piece of your 105 billion, but still a massive investment. How did that opportunity come to you? What was your thinking? You know, behind that that investment and what are you looking for in terms of the go forward plan and growth plan for 2021 really importantly, beyond. >>Yeah, absolutely. Well, we're thrilled to be partnered with and invested in Nutanix. We think is a terrific company. And, you know, our most recent technology investment and private equity business. It really came about through a proactive efforts that we had in in the spring. Um, you know, we've got a team focused on the technology sector, focused across infrastructure and applications, and, uh, internet and digital media businesses and financial technology. And, uh, you know, through those efforts, we were looking for businesses. Um, that we felt had faced some dislocation and their market values associated with the Koven environment that we're facing but that we thought were really attractive. Business is well positioned, had leading solutions and had substantial and discontinuous growth opportunities. And as we looked through that effort, we really felt that Nutanix stood out just as a core leader and in fact, really the innovator and the inventor of the market in which it competes with a substantial market share in position solving a really important problem for its customers with a big growth opportunity ahead. But, um, the stock price had had come down because the business has been undergoing ah transition, and we didn't think that that was fully understood by by the market. And so way saw an opportunity Thio partner with Nutanix to invest money into the business to help to fund its transition and its growth. Yeah, and Thio to be partners along for all the value the business will will continue to create. We think it's a terrific company, and we're excited to be to be invested >>Well, you and I have talked about this that transition, you know, from a traditional, you know, license model to one That's Anania recurring revenue model, which many companies have gone through. You know, Adobe certainly has done it. Tableau successfully did it. Splunk is kind of in the middle of that transition right now and maybe not well understood. You've got companies like like Data Dog that and snowflake again to doing consumption based pricing. So there's a lot of confusion in the marketplace, and I wonder if you could talk about that transition and why it It was attractive to you to actually, you know, place that bet now? >>Yeah, absolutely. And as you say, a number of companies at this point have been through various forms of this shift, from from selling their technology upfront to selling it over time on, we find that the model of selling the technology over time eyes one that could be powerful. It could be aligning for customers as well as for, uh, vendor of the software solutions. And in Nutanix in particular again, we saw all the ingredients that we think make this an opportunity for for the business again, market leading technology that customers love. That is solving really important problem. The technology, because Nutanix had been grown and bootstrapped under the leadership of, uh, you know of zeros when it was built and founded, had been selling its software together with an appliance, you know, often in a, um, upfront sale Andi has been undergoing under their own initiative transition from selling that software with an appliance to a software based model to one that s'more rattle over time. And, you know, we thought that there was the opportunity to continue that to continue that transition and by doing that, to be able to offer mawr growth and mawr innovation that we could bring to our customers Thio continue to fund the shift. So something that frankly was well underway before we invested. Um, you know, as a za business makes this transition from collecting upfront Thio, you know, thio more evenly. Over time, you know, we saw a potentially use for our capital to help to fund that growth. And we're just focused on being a good partner toe help the company keep investing in abating, as as it contains to do that. >>I was talking to somebody other day, David. I told him I was interviewing you, and I was mentioning the Nutanix investment. I said, I'm definitely gonna cover that as part of this. You know, Cuban Cloud program. And they said Hit Nutanix. That's not cloud. I'm like, Wait a minute, What's cloud? So we heard Andy Jassy reinvent talking a lot about hybrid Antonio Neary, right after HP made its earnings last earnings announcement he came on on, said that well, we heard the big Cloud player talk about hybrid, and so the definition is changing. But so how are you looking at the market? Uh, certainly. There's this hyper converged infrastructure, but there's also this software play. There's this cloud play. Help us squint through how you see that >>absolutely so Nutanix, as you alluded to, pioneered the market for hyper converged infrastructure for bringing computing storage networking together. Uh, you know, often in private cloud environments in a way that was really powerful for for customers. Make, of course, continue to be the leaders in that marketplace. But they've continued to innovate and invest in ways that can solve problems for customers and related problems across the hybrid cloud. So combining both the public cloud with, you know, with that private cloud and across multiple public clouds with things like clusters and lots of innovation that business is doing in partnership with the likes of, um, Amazon and Microsoft and others. And so, yeah, we think that New Chance has a powerful role to play in that hyper cloud world in a multi cloud world. And we're excited toe back on them. >>Well, I think to what maybe people don't understand is that not only is Nutanix, you know, compatible with AWS and compatible with azure and G C. P. But it's actually kind of create a nabs traction layer across those those clouds. Now there's two sides of that debate. Some some will say, Well, that that that has Leighton see issues or yes, it reduces complexity. But at the same time, it doesn't give you that fine grained access. That's kind of the A W s narrative customers, you know, want simplicity. And we're seeing, you know, the uptake across clouds. I have a multipart question for you, Dave. So obviously being very strong and strategy I'm curious is toe how how much you get involved in the operational details. I mean, obviously 750 million u got a state there, but what are the 2 to 2 or three major strategic considerations for not just even just Nutanix but cloud and software infrastructure companies. And and how much focus do you put on the operational and one of the priorities There? >>Absolutely. Well, you know, we pride ourselves in being good partners to our businesses and in helping them to grow, not just with our capital, which I think is, of course, important, but also, you know, with our sweat equity and our and our human capital in our partnership that we could do that in lots of ways is fundamentally about, um, you know, supporting our businesses, however, is needed to help them thio grow. We've been investing in the technology sector, as I described for over over 30 years. And so we've built up a set of capabilities around things like helping toe partner with the sales force of our company is helping them toe, you know, think about the you know, the ways in which they they allocate their, uh their research and development and their in their innovation raised in which they, you know, continue Thio do acquisitions toe. You know, further that pipeline, we support our businesses in lots of ways, but you know we're not engineers were not. Developers, of course, were looking for businesses that are fundamentally great. They've got great technology. They solve problems for customers in a way, you know, that we could never replicate. That's what's the amazing but a business like Nutanix and just over a 10 year period of time, it literally has customer satisfaction levels that we haven't seen from any other. Infrastructures offer company that we've had the, you know, the pleasure of diligence ing over the last several years. So what we're focused on is how can we take those great products and offerings that Nutanix has and continue to support them through the further growth and expansion in areas like, um, you know, the further salesforce investment Thio expand into these new areas like clusters that we were talking about and thinking about, you know, things that they could do toe further expand the strategic hold. Um, And so, you know, we have, ah, large team of being capital. A zai mentioned 260 investment professionals in a private equity business alone. About a third of those are just available to our companies to help support them. Uh, you know, with various initiatives and efforts after after we invest. And we'll certainly, of course, make all of those available to new taxes. Well, somebody >>was asking me the other day, You know, what's hyper converged infrastructure? How did that come about? I was explaining what, Back in the day you had. You buy some servers and some storage and you have a network and you sort of have different teams and you put applicant, You figure out all out and put the applications on top, you know, test it, make sure it all works. And then and then the guys at V. C and VM Ware and Cisco and the M. C. They got together and said, Okay, we're gonna bolt together a bunch of different components and, you know, pre tested. Here you go. Here's a Here's a skew. And then what Nutanix did was actually really transformational and saying, Okay, look, we do this through software on DSO. And now that was what, Late, late two thousands. Now we're sort of entering this new era, this next generation of cloud cross clouds. So I wonder how you think about, you know, based on what you were just talking about the whole notion of M and A versus organic. There's a lot of organic development that needs to be done. But perhaps you could you could buy in or in organically through emanate toe, actually get there faster. How do you think about that balance? >>Look, I I think that that was an articulate, by the way explanation of I think that the origins of hyper converged infrastructure. So I enjoyed that very much. But, you know, I think that with any of our businesses and with Nutanix, we're of course, looking at where we trying to get to in several years and one of the best ways to support the business to get there, you know? Of course, they'll, um you know, primarily that will be through or continued organic investment in the company and all the innovation in the product. Um, that they've been doing will the company contemplate acquisitions toe further achieve the development goals and the objectives for solving pain points for customers to get, you know, to the strategic places they're trying to get to, of course. But you know, it all is a part of the package of of What's it a good fit company and its growth object. >>I mean, with the size of your portfolio, I mean your full stack investor, I would say, Is there any part of the so called tech stack that you won't touch that you would actually, you know, not not walk, but run away from, >>uh well, you know, I wouldn't say that we're running away from, you know, anything but the questions that we're asking ourselves. Our is the technology that we're investing in durable, ISAT advantaged and does have a growing role in the world. And, you know, if if we think that those things are true are absolutely, um, thrilled toe invest behind those things. You know, if if there are things that we feel like you, that's that's not the case, um, you know, then then we would tend toe to shy away from those investments. We've certainly found opportunities and businesses that people perceived as one. But you know, we believe to be another >>Well, so let me ask you specifically about about Nutanix. I mean, clearly, they achieved escape velocity. One of the few companies actually from last decade. It was Nutanix pure, not a whole lot of others. That actually, you know, were ableto maintain independence as a as a public company. What do you see is their durability. Uh, they're they're they're in their moat. If you if you will. >>Yeah, absolutely. Well, clearly, we think that it's a very durable and very advantage business. You know, that's that's the investment. Look, we think that Nutanix has been able to offer the best hyper converged infrastructure product on the market bar None. Um, one that has got the best ease of use Eyes is the most nimble and flexible for for customers. And you just see that, you know, recently and customer feedback And also that plays across very heterogeneous architectures in a way that, you know, it's really, really powerful because of that. You know, we think that their best position to be able to leverage that technology as they have been, uh, to continue to play across both public and private hybrid cloud environments. And so we're excited toe to back them and and that journey it really starts from solving and acute customer pain point, you know, better than anybody else can. And, you know, we're looking to to back them toe continue to expand that vision. >>Yeah, well, I've talked to a lot of Nutanix customers over the years, and that is the fundamental value. Proposition is it's really simple, very high, you know, customer satisfaction. So that makes a lot of sense. Well, Dave, thanks very much for coming on the Cube and participating in the Cuban cloud. Really? Appreciate your perspectives. Wish you best of luck. And hopefully we could do this again in the future. Maybe face to face >>now, face to face, maybe something even know. Dave, I really appreciate it's been a pleasure and good luck with with the rest of your interviews. >>All right. Thank you. We keep it right. Everybody from or Cuban Cloud, this is Dave Volonte. We'll be right back.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. As I've said many times on the Cube for years, decades, even we've marched to the cadence of Moore's law, relying on the doubling of performance every 18 months or so. But no longer is this the mainspring of innovation for technology. Rather, it's the combination of data applying machine intelligence and the cloud supported by the relentless reduction of the cost of compute and storage and the build out of a massively distributed computer network. Very importantly, in the last several years, alternative processors have emerged to support offloading work and performing specific Test GP use of the most widely known example of this trend, with the ascendancy of in video for certain applications like gaming and crypto mining and, more recently, machine learning. But in the middle of last decade, we saw the early development focused on the DPU, the data processing unit, which is projected to make a huge impact on data centers in the coming years. As we move into the next era of Cloud. And with me is deep. Sindhu, who's this co founder and CEO of Fungible, a company specializing in the design and development of GPU deep Welcome to the Cube. Great to see you. >>Thank you, Dave. And thank you for having me. >>You're very welcome. So okay, my first question is, don't CPUs and GP use process data already? Why do we need a DPU? >>Um you know that that is a natural question to ask on. CPUs have been around in one form or another for almost, you know, 55 maybe 60 years. And, uh, you know, this is when general purpose computing was invented, and essentially all CPI use went to x 80 60 x 86 architecture. Uh, by and large arm, of course, is used very heavily in mobile computing, but x 86 primarily used in data center, which is our focus. Um, now, you can understand that that architectural off general purpose CPUs has been refined heavily by some of the smartest people on the planet. And for the longest time, uh, improvements you refer the Moore's Law, which is really the improvements off the price performance off silicon over time. Um, that, combined with architectural improvements, was the thing that was pushing us forward. Well, what has happened is that the architectural refinements are more or less done. Uh, you're not going to get very much. You're not going to squeeze more blood out of that storm from the general purpose computer architectures. What has also happened over the last decade is that Moore's law, which is essentially the doubling off the number of transistors, um, on a chip has slowed down considerably on and to the point where you're only getting maybe 10 20% improvements every generation in speed off the grandest er. If that. And what's happening also is that the spacing between successive generations of technology is actually increasing from 2, 2.5 years to now three, maybe even four years. And this is because we are reaching some physical limits in Seamus. Thes limits are well recognized, and we have to understand that these limits apply not just to general purpose if use, but they also apply to GP use now. General purpose, if used, do one kind of confrontation. They really general on bacon do lots and lots of different things. It is actually a very, very powerful engine, Um, and then the problem is it's not powerful enough to handle all computations. So this is why you ended up having a different kind of processor called the GPU, which specializes in executing vector floating point arithmetic operations much, much better than CPL. Maybe 2030 40 times better. Well, GPS have now been around for probably 15, 20 years, mostly addressing graphics computations. But recently, in the last decade or so, they have been used heavily for AI and analytics computations. So now the question is, why do you need another specialized engine called the DPU? Well, I started down this journey about almost eight years ago, and I recognize I was still at Juniper Networks, which is another company that I found it. I recognize that in the data center, um, as the workload changes due to addressing Mawr and Mawr, larger and larger corpus is of data number one. And as people use scale out as the standard technique for building applications, what happens is that the amount of East West traffic increases greatly. And what happens is that you now have a new type off workload which is coming, and today probably 30% off the workload in a data center is what we call data centric. I want to give you some examples of what is the data centric E? >>Well, I wonder if I could interrupt you for a second, because Because I want you to. I want those examples, and I want you to tie it into the cloud because that's kind of the topic that we're talking about today and how you see that evolving. It's a key question that we're trying to answer in this program. Of course, Early Cloud was about infrastructure, a little compute storage, networking. And now we have to get to your point all this data in the cloud and we're seeing, by the way, the definition of cloud expand into this distributed or I think the term you use is disaggregated network of computers. So you're a technology visionary, And I wonder, you know how you see that evolving and then please work in your examples of that critical workload that data centric workload >>absolutely happy to do that. So, you know, if you look at the architectural off cloud data centers, um, the single most important invention was scale out scale out off identical or near identical servers, all connected to a standard i p Internet network. That's that's the architectural. Now, the building blocks of this architecture er is, uh, Internet switches, which make up the network i p Internet switches. And then the servers all built using general purpose X 86 CPUs with D ram with SSD with hard drives all connected, uh, inside the CPU. Now, the fact that you scale these, uh, server nodes as they're called out, um, was very, very important in addressing the problem of how do you build very large scale infrastructure using general purpose computer? But this architectures, Dave, is it compute centric architectures and the reason it's a compute centric architectures. If you open this a server node, what you see is a connection to the network, typically with a simple network interface card. And then you have CP use, which are in the middle of the action. Not only are the CPUs processing the application workload, but they're processing all of the aisle workload, what we call data centric workload. And so when you connect SSD and hard drives and GPU that everything to the CPU, um, as well as to the network, you can now imagine that the CPUs is doing to functions it z running the applications, but it's also playing traffic cop for the I O. So every Io has to go to the CPU and you're executing instructions typically in the operating system, and you're interrupting the CPU many, many millions of times a second now. General Purpose CPUs and the architecture of the CPS was never designed to play traffic cop, because the traffic cop function is a function that requires you to be interrupted very, very frequently. So it's. It's critical that in this new architecture, where there's a lot of data, a lot of East West traffic, the percentage of work clothes, which is data centric, has gone from maybe 1 to 2% to 30 to 40%. I'll give you some numbers, which are absolutely stunning if you go back to, say, 1987 and which is, which is the year in which I bought my first personal computer. Um, the network was some 30 times slower. Then the CPI. The CPI was running at 50 megahertz. The network was running at three megabits per second. Well, today the network runs at 100 gigabits per second and the CPU clock speed off. A single core is about 3 to 2.3 gigahertz. So you've seen that there is a 600 x change in the ratio off I'll to compute just the raw clock speed. Now you can tell me that. Hey, um, typical CPUs have lots of lots, of course, but even when you factor that in, there's bean close toe two orders of magnitude change in the amount of ill to compute. There is no way toe address that without changing the architectures on this is where the DPU comes in on the DPU actually solves two fundamental problems in cloud data centers on these air. Fundamental. There's no escaping it, no amount off. Clever marketing is going to get around these problems. Problem number one is that in a compute centric cloud architectures the interactions between server notes are very inefficient. Okay, that's number one problem number one. Problem number two is that these data center computations and I'll give you those four examples the network stack, the storage stack, the virtualization stack and the security stack. Those four examples are executed very inefficiently by CBS. Needless to say that that if you try to execute these on GPS, you'll run into the same problem, probably even worse because GPS are not good at executing these data centric computations. So when U. S o What we were looking to do it fungible is to solve these two basic problems and you don't solve them by by just using taking older architectures off the shelf and applying them to these problems because this is what people have been doing for the for the last 40 years. So what we did was we created this new microprocessor that we call the DPU from ground doctor is a clean sheet design and it solve those two problems. Fundamental. >>So I want to get into that. But I just want to stop you for a second and just ask you a basic question, which is so if I understand it correctly, if I just took the traditional scale out, If I scale out compute and storage, you're saying I'm gonna hit a diminishing returns, It z Not only is it not going to scale linear linearly, I'm gonna get inefficiencies. And that's really the problem that you're solving. Is that correct? >>That is correct. And you know this problem uh, the workloads that we have today are very data heavy. You take a I, for example, you take analytics, for example. It's well known that for a I training, the larger the corpus of data relevant data that you're training on, the better the result. So you can imagine where this is going to go, especially when people have figured out a formula that, hey, the more data I collect, I can use those insights to make money. >>Yeah, this is why this is why I wanted to talk to you, because the last 10 years we've been collecting all this data. Now I want to bring in some other data that you actually shared with me beforehand. Some market trends that you guys cited in your research and the first thing people said is they want to improve their infrastructure on. They want to do that by moving to the cloud, and they also there was a security angle there as well. That's a whole nother topic. We could discuss the other staff that jumped out at me. There's 80% of the customers that you surveyed said they'll be augmenting their X 86 CPUs with alternative processing technology. So that's sort of, you know, I know it's self serving, but z right on the conversation we're having. So I >>want to >>understand the architecture. Er, aan den, how you've approached this, You've you've said you've clearly laid out the X 86 is not going to solve this problem. And even GP use are not going to solve this problem. So help us understand the architecture and how you do solve this problem. >>I'll be I'll be very happy to remember I use this term traffic cough. Andi, I use this term very specifically because, uh, first let me define what I mean by a data centric computation because that's the essence off the problem resolved. Remember, I said two problems. One is we execute data centric work clothes, at least in order of magnitude, more efficiently than CPUs or GPS, probably 30 times more efficiently on. The second thing is that we allow notes to interact with each other over the network much, much more efficiently. Okay, so let's keep those two things in mind. So first, let's look at the data centric piece, the data centric piece, um, for for workload to qualify as being data centric. Four things have to be true. First of all, it needs to come over the network in the form of packets. Well, this is all workloads, so I'm not saying anything new. Secondly, uh, this workload is heavily multiplex in that there are many, many, many computations that are happening concurrently. Thousands of them. Yeah, that's number two. So a lot of multiplexing number three is that this workload is state fel. In other words, you have to you can't process back. It's out of order. You have to do them in order because you're terminating network sessions on the last one Is that when you look at the actual computation, the ratio off I Oto arithmetic is medium to high. When you put all four of them together, you actually have a data centric workout, right? And this workload is terrible for general purpose, C p s not only the general purpose, C p is not executed properly. The application that is running on the CPU also suffers because data center workloads are interfering workloads. So unless you designed specifically to them, you're going to be in trouble. So what did we do? Well, what we did was our architecture consists off very, very heavily multi threaded, general purpose CPUs combined with very heavily threaded specific accelerators. I'll give you examples of some some of those accelerators, um, de Emma accelerators, then radio coding accelerators, compression accelerators, crypto accelerators, um, compression accelerators, thes air, just something. And then look up accelerators. These air functions that if you do not specialized, you're not going to execute them efficiently. But you cannot just put accelerators in there. These accelerators have to be multi threaded to handle. You know, we have something like 1000 different threads inside our DPU toe address. These many, many, many computations that are happening concurrently but handle them efficiently. Now, the thing that that is very important to understand is that given the paucity off transistors, I know that we have hundreds of billions of transistors on a chip. But the problem is that those transistors are used very inefficiently today. If the architecture, the architecture of the CPU or GPU, what we have done is we've improved the efficiency of those transistors by 30 times. Yeah, so you can use >>the real estate. You can use their real estate more effectively, >>much more effectively because we were not trying to solve a general purpose computing problem. Because if you do that, you know, we're gonna end up in the same bucket where General Focus CPS are today. We were trying to solve the specific problem off data centric computations on off improving the note to note efficiency. So let me go to Point number two, because that's equally important, because in a scale out architecture, the whole idea is that I have many, many notes and they're connected over a high performance network. It might be shocking for your listeners to hear that these networks today run at a utilization of no more than 20 to 25%. Question is why? Well, the reason is that if I tried to run them faster than that, you start to get back. It drops because there are some fundamental problems caused by congestion on the network, which are unsolved as we speak today. There only one solution, which is to use DCP well. DCP is a well known is part of the D. C. P I. P. Suite. DCP was never designed to handle the agencies and speeds inside data center. It's a wonderful protocol, but it was invented 42 year 43 years ago, now >>very reliable and tested and proven. It's got a good track record, but you're a >>very good track record, unfortunately, eats a lot off CPU cycles. So if you take the idea behind TCP and you say, Okay, what's the essence of TCP? How would you apply to the data center? That's what we've done with what we call F C P, which is a fabric control protocol which we intend toe open way. Intend to publish standards on make it open. And when you do that and you you embed F c p in hardware on top of his standard I P Internet network, you end up with the ability to run at very large scale networks where the utilization of the network is 90 to 95% not 20 to 25% on you end up with solving problems of congestion at the same time. Now, why is this important today that zall geek speak so far? But the reason this stuff is important is that it such a network allows you to disaggregate pool and then virtualized, the most important and expensive resource is in the data center. What are those? It's computer on one side, storage on the other side. And increasingly even things like the Ram wants to be disaggregated in food. Well, if I put everything inside a general purpose server, the problem is that those resource is get stranded because they're they're stuck behind the CPI. Well, once you disaggregate those resources and we're saying hyper disaggregate, the meaning, the hyper and the hyper disaggregate simply means that you can disaggregate almost all the resources >>and then you're gonna re aggregate them, right? I mean, that's >>obviously exactly and the network is the key helping. So the reason the company is called fungible is because we are able to disaggregate virtualized and then pull those resources and you can get, you know, four uh, eso scale out cos you know the large aws Google, etcetera. They have been doing this aggregation and pulling for some time, but because they've been using a compute centric architecture, er that this aggregation is not nearly as efficient as we could make on their off by about a factor of three. When you look at enterprise companies, they're off by any other factor of four. Because the utilization of enterprises typically around 8% off overall infrastructure, the utilization the cloud for A W S and G, C, P and Microsoft is closer to 35 to 40%. So there is a factor off almost, uh, 4 to 8, which you can gain by disaggregated and pulling. >>Okay, so I wanna interrupt again. So thes hyper scaler zehr smart. A lot of engineers and we've seen them. Yeah, you're right. They're using ah, lot of general purpose. But we've seen them, uh, move Make moves toward GP use and and embrace things like arm eso I know, I know you can't name names but you would think that this is with all the data that's in the cloud again Our topic today you would think the hyper scaler zehr all over this >>all the hyper scale is recognized it that the problems that we have articulated are important ones on they're trying to solve them. Uh, with the resource is that they have on all the clever people that they have. So these air recognized problems. However, please note that each of these hyper scale er's has their own legacy now they've been around for 10, 15 years, and so they're not in a position to all of a sudden turn on a dime. This is what happens to all companies at some >>point. Have technical debt. You mean they >>have? I'm not going to say they have technical debt, but they have a certain way of doing things on. They are in love with the compute centric way of doing things. And eventually it will be understood that you need a third element called the DPU to address these problems. Now, of course, you heard the term smart neck, and all your listeners must have heard that term. Well, a smart thing is not a deep you what a smart Nick is. It's simply taking general purpose arm cores put in the network interface on a PC interface and integrating them all in the same chip and separating them from the CPI. So this does solve the problem. It solves the problem off the data centric workload, interfering with the application work, work. Good job. But it does not address the architectural problem. How to execute data centric workloads efficiently. >>Yeah, it reminds me. It reminds me of you I I understand what you're saying. I was gonna ask you about smart. Next. It does. It's almost like a bridge or a Band Aid. It's always reminds me of >>funny >>of throwing, you know, a flash storage on Ah, a disc system that was designed for spinning disk gave you something, but it doesn't solve the fundamental problem. I don't know if it's a valid analogy, but we've seen this in computing for a long time. >>Yeah, this analogy is close because, you know. Okay, so let's let's take hyper scaler X. Okay, one name names. Um, you find that, you know, half my CPUs are twiddling their thumbs because they're executing this data centric workload. Well, what are you going to do? All your code is written in, uh, C c plus plus, um, on x 86. Well, the easiest thing to do is to separate the cores that run this workload. Put it on a different Let's say we use arm simply because you know x 86 licenses are not available to people to build their own CPUs. So arm was available, so they put a bunch of encores. Let's stick a PC. I express and network interface on you. Port that quote from X 86 Tow arm. Not difficult to do, but it does yield you results on, By the way, if, for example, um, this hyper scaler X shall we call them if they're able to remove 20% of the workload from general purpose CPUs? That's worth billions of dollars. So of course you're going to do that. It requires relatively little innovation other than toe for quote from one place to another place. >>That's what that's what. But that's what I'm saying. I mean, I would think again. The hyper scale is why Why can't they just, you know, do some work and do some engineering and and then give you a call and say, Okay, we're gonna We're gonna attack these workloads together. You know, that's similar to how they brought in GP use. And you're right. It's it's worth billions of dollars. You could see when when the hyper scale is Microsoft and and Azure, uh, and and AWS both announced, I think they depreciated servers now instead of four years. It's five years, and it dropped, like a billion dollars to their bottom line. But why not just work directly with you guys. I mean, Z the logical play. >>Some of them are working with us. So it's not to say that they're not working with us. So you know, all of the hyper scale is they recognize that the technology that we're building is a fundamental that we have something really special, and moreover, it's fully programmable. So you know, the whole trick is you can actually build a lump of hardware that is fixed function. But the difficulty is that in the place where the DPU would sit, which is on the boundary off a server, and the network is literally on that boundary, that place the functionality needs to be programmable. And so the whole trick is how do you come up with an architectural where the functionality is programmable? But it is also very high speed for this particular set of applications. So the analogy with GPS is nearly perfect because GP use, and particularly in video that's implemented or they invented coulda, which is a programming language for GPS on it made them easy to use mirror fully programmable without compromising performance. Well, this is what we're doing with DP use. We've invented a new architectures. We've made them very easy to program. And they're these workloads or not, Workload. The computation that I talked about, which is security virtualization storage and then network. Those four are quintessential examples off data centric, foreclosed on. They're not going away. In fact, they're becoming more and more and more important over time. >>I'm very excited for you guys, I think, and really appreciate deep we're gonna have you back because I really want to get into some of the secret sauce you talked about these accelerators, Erasure coding, crypto accelerators. I want to understand that. I know there's envy me in here. There's a lot of hardware and software and intellectual property, but we're seeing this notion of programmable infrastructure extending now, uh, into this domain, this build out of this I like this term dis aggregated, massive disaggregated network s so hyper disaggregated. Even better. And I would say this on way. I gotta go. But what got us here the last decade is not the same is what's gonna take us through the next decade. Pretty Thanks. Thanks so much for coming on the cube. It's a great company. >>You have it It's really a pleasure to speak with you and get the message of fungible out there. >>E promise. Well, I promise we'll have you back and keep it right there. Everybody, we got more great content coming your way on the Cube on Cloud, This is David. Won't stay right there.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon Angle. Hi, I'm stupid, man. And welcome back to the Cube on Cloud. We're talking about developers. And while so many people remember the mean from 2010 of Steve Balmer jumping around on stage development developers and developers, uh, many people know what really important is really important about developers. They probably read the 2013 book called The New King Makers by Stephen O. Grady. And I'm really happy to welcome to the program. Rachel Stevens, who is an industry analyst with Red Monk who was co founded by the aforementioned Stephen O. Grady. Rachel, Great to see you. Thank you so much for joining us. >>Thank you so much for having me. I'm excited to be here. >>Well, I've had the opportunity, Thio read some of what you've done. We've interacted on social media. We've got to talk events back when we used to do those in people. And >>I'm so >>glad that you get to come on the program especially. You were the ones I reached out. When we have this developer track, um, if you could just give our audience a little bit about your background. You know, that developer cred that you have Because as I joke, I've got a closet full of hoodies. But, you know, I'm an infrastructure guy by training I've been learning about, you know, containers and serverless and all this stuff for years. But I'm not myself much of developer. I've touched a thing or two in the years. >>Yeah. So happy to be here. Red Monk has been around since 2002 and have kind of been beating that developer drum ever since then, kind of as the company, The founder, Stephen James, notice that the decision making that developers was really a driver for what was actually ending up in the Enterprise. And as even more true, as cloud came onto, the scene is open source exploded, and I think it's become a lot more of a common view now. But in those early days, it was probably a little bit more of a controversial opinion, but I have been with the firm for coming up on five years now. My work is an industry analyst. We kind of help people understand, bottoms up technology, adoption trends, so that that's where I spend my time focusing is what's getting used in the enterprise. Why, what kind of trends are happening? So, yeah, that's where we all come from. That's the history of Red Monk in 30 seconds. >>Awesome. Rachel, you talk about the enterprise and developers For the longest time. I just said there was this huge gap you talk about. Bottoms up. It's like, well, developers use the tools that they want If they don't have to, they don't pay for anything. And the general I t. And the business sides of the house were like, I don't know, We don't know what those people in the corner we're doing, you know, it's important and things like that. But today it feels like that that's closed a bunch. Where are we? In your estimation, you know, our developers do they have a clear seat at the table? The title we have for this is whether the Enterprise Developer is its enterprise development oxymoron. In 2020 and 2021 >>I think enterprise developers have a lot more practical authority than people give them credit for, especially if you're kind of looking at that old view of the world where everything is driven by a buyer decision or kind of this top down purchasing motion. And we've really seen that authority of what is getting used and why change a lot in the last year. In the last decade, even more of people who are able to choose the tools that meet the job bring in tools, regardless of whether they maybe have that official approval through the right channels because of the convenience of trying to get things up and running. We are asking developers to do so much right now and to go faster and thio shifting things left. And so the things that they are responsible for incorporating into the way they are building APS is growing. And so, as we are asking developers to do more and to do more quickly, um, the tools that they need to do those, um, tasks to get these APS built is that the decision making us fall into them? This is what I need. This is what needs to come in, and so we're seeing. Basically, the tools that enterprise is air using are the tools that developers want to be using, and they kind of just find their way into the enterprise. >>Now I want to key off what you were talking about. Just developers were being asked to do Mawr and Mawr. We've seen these pendulum swings in technology. There was a time where it was like, Well, I'll outsource it because that'll be easier and maybe it'll be less expensive. And number one we found it necessarily. It wasn't necessarily cheaper. And number two, I couldn't make changes, and I didn't understand what was happening. So when when I talked to Enterprises today, absolutely. I need to have skills that's internally. I need to be able to respond to things fast, and therefore I need skills that I need people that can build what they have. What what do you see? What are those skill sets that are so important today? Uh, you know, we've talked so many times over the years is to you know, there's there's the skills gap. We don't have enough data scientists. We don't have enough developers way. We don't have any of these things. So what do we have and where things trending? >>Yeah, it's It's one of those things for developers where they both have probably the most full tool set that we've seen in this industry in terms of things that are available to them. But it's also really hard because it also indicates that there is just this fragmentation at every level of the stack. And there's this explosion of choice and decisions that is happening up and down the stack of how are we going to build things? And so it's really tricky to be a developer these days and that you are making a lot of decisions and you are wiring a lot of things together and you have to be able to navigate a lot of things. E think. One of the things that is interesting here is that we have seen the phrase like Full stack developer really carried a lot of panache, maybe earlier this decade and has kind of fallen away. Just because we've realized that it's impossible for anybody to be ableto spanned this whole broad spectrum of all of the things we're asking people to dio. So we're seeing this explosion of choice, which is meaning that there is a little bit more focused and where developers are trying to actually figure out what is my niche. What is it that I'm supposed to focus on. And so it's really just this balancing of act of trying to see this big picture of how to get this all put together and also have this focused area realizing that you have to specialize at some point. >>Rachel is such a great point there. We've actually seen that Cambrian explosion of developer tools that are out there. If you go to the CFCF landscape and look at everything out there or goto any of your public cloud providers, there's no way that anybody even working for those companies no good portion of the tools that are out there so nobody could be a master of everything. How about from a cloud standpoint, you know, there is the discussion of, you know what do I shift? Left What? You know, Can I just say, Okay, this piece of it, it could be a manage service. I don't need to think about it versus what skills that I need to have in house. What is it that's important. And obviously, you know, a zoo analyst. We know it varies greatly across companies, but you know what? What are some of those top things that we need to make sure that enterprises have skill set and the tools in house that they should understand. And what can they push off to their platform of choice? >>Yeah, I think your comment about managed services is really pressing because one of the trends that we're watching closely, it's just this rise of manage services. And it kind of ties back into the concept you had before about like, what an I team. That's they have, like the Nicholas Carr. I t doesn't matter, and we're pushing this all the way. And then we realized, Oh, we've got to bring that all back. Um, but we also realize that we really want as enterprises want to be spending our time doing differentiated work and wiring together, your entire infrastructure isn't necessarily differentiated for a lot of companies. And so it's trying to find this mix of where can I push my abstraction higher or to find a manage service that can do something for me? And we're seeing that happen in all levels of the stack. And so what we're seeing is this rise of composite APS where we're going to say, Okay, I'm gonna pull in back end AP ice from a whole bunch of tools like twilio or stripe or all zero where algo Leah, all of those things are great tools that I can incorporate into my app. And I can have this great user, um, interface that I can use. And then I don't have to worry quite so much about building it all myself. But I am responsible for wiring at all together. So I think it's that wire together set of interest that is happening for developers as the tool set that they are spending a lot of time with. So we see the manage services being important. Um played an important role in how absent composed, and it's the composition of that APs that is happening internally. >>What one of the one of the regular research items that I see a red monk is you know what languages you know. Where are the trends going? There's been relative stability, but then something's changed. You know, I look at the tools that you mentioned Full stack developer. I talked to a full stack developer a couple of years ago, and he's like like like terror form is my life and I love everything and I've used it forever. And that was 18 months, Andi. I kind of laugh because it's like, OK, I managed. I measure a lot of the technology that I used in the decades. Um, not that await. This came out six months ago and it's kind of mature. And of course, you know, C I C d. Come on. If it's six weeks old, it's probably gone through a lot of generations. So what do you see? Do you have any research that you can share as to looking forward? What are the You know what the skill sets we need? How should we be training our force? What do >>we need to >>be looking at in this kind of next decade of cloud? >>Yeah. So when when you spoke about languages, we dio a semi annual review of language usage as a sign on get hub and in discussion as seen on stack overflow, which we fully recognize is not a perfect representation of how these languages are used in the broader world. But those air data sets that we have access to that are relatively large and open eso just before anyone writes me angry letters that that's not the way that we should be doing it, Um, but one of the things that we've seen over time is that there is a lot of relative stability in those top tier languages in terms of how they are used, and there's some movement at the bottom. But the trends we're seeing where the languages are moving is type safety and having a safer language and the communities that are building upon other communities. So things like, um, we're seeing Scotland that is able to kind of piggyback off of being a jvm based language and having that support from Google. Or we're seeing typescript where it can piggyback off of the breath of deployment of JavaScript, things like that. So those things where were combining together multiple trends that developers are interested in the same time combined with an ecosystem that's already rich and full. And so we're seeing that there's definitely still movement in languages that people are interested in, but also, language on its own is probably pretty stable. So, like as you start to make language choices as a developer, that's not where we're seeing a ton of like turnover language frameworks on the other hand, like if you're a JavaScript developer and all of a sudden there's just explosion of frameworks that you need to choose from, that may be a different story, a lot more turnover there and harder to predict. But language trends are a little bit more stable over >>time, changing over time. You know, Boy, I I got to dig into, you know, relatively Recently I went down like the jam stack. Uh, ecosystem. I've been digging into a serverless for a number of years. What's your take on that? There's certain people. I talked to him. They're like, I don't even need to be a code. Or I could be a marketing person. And I can get things done when I talked to some developers there like a citizen developers. They're not developers. Come on, you know, I really need to be able to do this, so I'll give you your choices, toe. You know, serverless and some of these trends to kind of ext fan. You know who can you know? Code and development. >>Yeah. So for both translate jam stack and serve Ellis, One of the things that we see kind of early in the iteration of a technology is that it is definitely not going to be the right tool for every app. And the number of APS that they approach will fit for will grow as the tool develops. And you add more functionality over time and all of these platforms expand the capability, but definitely not the correct tool choice in every case. That said, we do watch both of those areas with extreme interest in terms of what this next generation of APS can look like and probably will look like in a lot of cases. And I think that it is super interesting to think about who gets to build these APs, because I e. I think one of the things that we probably haven't landed on the right language yet is what that what we should call these people because I don't think anyone associates themselves as a low code person. Like if you're someone from marketing and all of a sudden you can build something technical, that's really cool, and you're excited about that. Nobody else on your team could build. You're not walking around saying I am a low code marketing person like that, that that's that's that's demeaning. Like you're like. No, I'm technical. I'm a technical market, or look what I just did. And if you're someone who codes professionally for a living like and you use a low code tool to get something out the door quickly and >>you don't >>wanna demean and said, Oh, that was I did a low code that just like everybody, is just trying to solve problems. And everybody, um, is trying to figure out how to do things in the most effective way possible and making trade offs all the time. And so I don't think that the language of low code really is anything that resonates with any of the actual users of low code tools. And so I think that's something that we as an industry need toe work on finding the correct language because it doesn't feel like we've landed there yet. >>Yeah, Rachel, what? Want to get your take on just careers for developers now to think about in 2020 everyone is distributed. Lots of conversations about where we work. Can we bring the remote? Many of the developers I talked to already were remote. I had the chance that interview that the head of remote. Forget lab. They're over 1000 people and they're fully remote. So, you know, remote. Absolutely a thing for developers. But if you talk about careers, it is no longer, you know. Oh, hey, here's my CV. It's I'm on git Hub. You can see the code I've done. We haven't talked about open source yet, so give us your take on kind of developers today. Career paths. Andi. Kind of the the online community there. >>Yeah, this could be a whole own conversation. We'll try to figure out my points. Um, so I think one of the things that we are trying to figure out in terms of balance is how much are we expecting people to have done on the side? It's like a side project Hustle versus doing, exclusively getting your job done and not worrying too much about how many green squares you have on your get hub profile. And I think it's a really emotional and fraught discussion and a lot of quarters because it can be exclusionary for people saying that you you need to be spending your time on the side working on this open source project because there are people who have very different life circumstances, like if you're someone who already has kids or you're doing elder care or you are working another job and trying to transition into becoming a developer, it's a lot to ask. These people toe also have a side hustle. That said, it is probably working on open source, having an understanding of how tools are done. Having this, um, this experience and skills that you can point to and contributions you can point Teoh is probably one of the cleaner ways that you can start to move in the industry and break through to the industry because you can show your skills two other employers you can kind of maybe make your way in is a junior developer because you worked on a project and you make those connections. And so it's really still again. It's one of those balancing act things where there's not a perfect answer because there really is to correct sides of this argument. And both of those things are true. At the same time where it's it's hard to figure out what that early career path maybe looks like, or even advancing in a career path If you're already a developer, it's It's tricky. >>Well, I want to get your take on something to you know, I think back to you know, I go back a decade or two I started working with about 20 years ago. Back in the crazy days were just Colonel Daughter Warg and, you know, patches everywhere and lots of different companies trying to figure out what they would be doing on most of the people contributing to the free software before we're calling it open source. Most of the time, it was their side Hustle was the thing they're doing. What was their passion? Project? I've seen some research in the last year or so that says the majority of people that are contributing to open source are doing it for their day job. Obviously, there's a lot of big companies. There's plenty of small companies. When I goto the Linux Foundation shows. I mean, you've got whole companies that are you know, that that's their whole business. So I want to get your take on, you know, you know, governance, you know, contribution from the individual versus companies. You know, there's a lot of change going on there. The public cloud their impact on what's happening open source. What are you seeing there? And you know what's good? What's bad? What do we need to do better as a community? >>Yeah. E think the governance of open source projects is definitely a live conversation that we're having right now about what does this need to look like? What role do companies need to be having and how things are put together is a contribution or leadership position in the name of the individual or the name of the company. Like all of these air live conversations that are ongoing and a lot of communities e think one of the things that is interesting overall, though, is just watching if you're if you're taking a really zoomed out view of what open source looks like where it was at one point, um, deemed a cancer by one of the vendors in the space, and now it is something that is just absolutely an inherent part of most well tech vendors and and users is an important part of how they are building and using software today, like open source is really an integral tool. And what is happening in the enterprise and what's being built in the enterprise. And so I think that it is a natural thing that this conversation is evolving in terms of what is the enterprises role here and how are we supposed to govern for that? And e don't think that we have landed on all the correct answers yet. But I think that just looking at that long view, it makes sense that this is an area where we are spending some time focusing >>So Rachel without giving away state secrets. We know read Monk, you do lots of consulting out there. What advice do you give to the industry? We said we're making progress. There's good things there. But if we say okay, I wanna at 2030 look back and say, Boy, this is wonderful for developers. You know, everything is going good. What things have we done along the way? Where have we made progress? >>Yeah, I think I think it kind of ties back to the earlier discussion we were having around composite APS and thinking about what that developer experience looks like. I think that right now it is incredibly difficult for developers to be wiring everything together and There's just so much for developers to dio to actually get all of these APs from source to production. So when we talk with our customers, a lot of our time is spent thinking, How can you not only solve this individual piece of the puzzle, but how can you figure out how to fit it into this broader picture of what it is the developers air trying to accomplish? How can you think about where your ATF, It's not on your tool or you your project? Whatever it is that you are working on, how does this fit? Not only in terms of your one unique problem space, but where does this problem space fit in the broader landscape? Because I think that's going to be a really key element of what the developer experience looks like in the next decade. Is trying to help people actually get everything wired together in a coherent way. >>Rachel. No shortage of work to do there really appreciate you joining us. Thrilled to have you finally as a cube. Alumni. Thanks so much for joining. >>Thank you for having me. I appreciate it. >>All right. Thank you for joining us. This is the developer content for the cube on cloud, I'm stew minimum, and as always, thank you for watching the Cube.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle in 2000 >>nine. Hal Varian, Google's chief economist, said that statisticians would be the sexiest job in the coming decade. The modern big data movement >>really >>took off later in the following year. After the Second Hadoop World, which was hosted by Claudette Cloudera in New York City. Jeff Ham Abakar famously declared to me and John further in the Cube that the best minds of his generation, we're trying to figure out how to get people to click on ads. And he said that sucks. The industry was abuzz with the realization that data was the new competitive weapon. Hadoop was heralded as the new data management paradigm. Now, what actually transpired Over the next 10 years on Lee, a small handful of companies could really master the complexities of big data and attract the data science talent really necessary to realize massive returns as well. Back then, Cloud was in the early stages of its adoption. When you think about it at the beginning of the last decade and as the years passed, Maurin Mawr data got moved to the cloud and the number of data sources absolutely exploded. Experimentation accelerated, as did the pace of change. Complexity just overwhelmed big data infrastructures and data teams, leading to a continuous stream of incremental technical improvements designed to try and keep pace things like data Lakes, data hubs, new open source projects, new tools which piled on even Mawr complexity. And as we reported, we believe what's needed is a comm pleat bit flip and how we approach data architectures. Our next guest is Jean Marc de Connie, who is the director of emerging technologies That thought works. John Mark is a software engineer, architect, thought leader and adviser to some of the world's most prominent enterprises. She's, in my view, one of the foremost advocates for rethinking and changing the way we create and manage data architectures. Favoring a decentralized over monolithic structure and elevating domain knowledge is a primary criterion. And how we organize so called big data teams and platforms. Chamakh. Welcome to the Cube. It's a pleasure to have you on the program. >>Hi, David. This wonderful to be here. >>Well, okay, so >>you're >>pretty outspoken about the need for a paradigm shift in how we manage our data and our platforms that scale. Why do you feel we need such a radical change? What's your thoughts there? >>Well, I think if you just look back over the last decades you gave us, you know, a summary of what happened since 2000 and 10. But if even if we go before then what we have done over the last few decades is basically repeating and, as you mentioned, incrementally improving how we've managed data based on a certain assumptions around. As you mentioned, centralization data has to be in one place so we can get value from it. But if you look at the parallel movement off our industry in general since the birth of Internet, we are actually moving towards decentralization. If we think today, like if this move data side, if he said the only way Web would work the only way we get access to you know various applications on the Web pages is to centralize it. We would laugh at that idea, but for some reason we don't. We don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, you know, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organization there beyond the bounds of organization. And then look back and say Okay, if that's the trend off our industry in general, Um, given the fabric of computation and data that we put in, you know globally in place, then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me, that requires a paradigm shift, a full stack from how we organize our organizations, how we organize our teams, how we, you know, put a technology in place, um, to to look at it from a decentralized angle. >>Okay, so let's let's unpack that a little bit. I mean, you've spoken about and written that today's big architecture and you basically just mentioned that it's flawed, So I wanna bring up. I love your diagrams of a simple diagram, guys, if you could bring up ah, figure one. So on the left here we're adjusting data from the operational systems and other enterprise data sets and, of course, external data. We cleanse it, you know, you've gotta do the do the quality thing and then serve them up to the business. So So what's wrong with that picture that we just described and give granted? It's a simplified form. >>Yeah, quite a few things. So, yeah, I would flip the question may be back to you or the audience if we said that. You know, there are so many sources off the data on the Actually, the data comes from systems and from teams that are very diverse in terms off domains. Right? Domain. If if you just think about, I don't know retail, Uh, the the E Commerce versus Order Management versus customer This is a very diverse domains. The data comes from many different diverse domains. And then we expect to put them under the control off a centralized team, a centralized system. And I know that centralization. Probably if you zoom out, it's centralized. If you zoom in it z compartmentalized based on functions that we can talk about that and we assume that the centralized model will be served, you know, getting that data, making sense of it, cleansing and transforming it then to satisfy in need of very diverse set of consumers without really understanding the domains, because the teams responsible for it or not close to the source of the data. So there is a bit of it, um, cognitive gap and domain understanding Gap, um, you know, without really understanding of how the data is going to be used, I've talked to numerous. When we came to this, I came up with the idea. I talked to a lot of data teams globally just to see, you know, what are the pain points? How are they doing it? And one thing that was evident in all of those conversations that they actually didn't know after they built these pipelines and put the data in whether the data warehouse tables or like, they didn't know how the data was being used. But yet the responsible for making the data available for these diverse set of these cases, So s centralized system. A monolithic system often is a bottleneck. So what you find is, a lot of the teams are struggling with satisfying the needs of the consumers, the struggling with really understanding the data. The domain knowledge is lost there is a los off understanding and kind of in that in that transformation. Often, you know, we end up training machine learning models on data that is not really representative off the reality off the business. And then we put them to production and they don't work because the semantic and the same tax off the data gets lost within that translation. So we're struggling with finding people thio, you know, to manage a centralized system because there's still the technology is fairly, in my opinion, fairly low level and exposes the users of those technologies. I said, Let's say warehouse a lot off, you know, complexity. So in summary, I think it's a bottleneck is not gonna, you know, satisfy the pace of change, of pace, of innovation and the pace of, you know, availability of sources. Um, it's disconnected and fragmented, even though the centralizes disconnected and fragmented from where the data comes from and where the data gets used on is managed by, you know, a team off hyper specialized people that you know, they're struggling to understand the actual value of the data, the actual format of the data, so it's not gonna get us where our aspirations and ambitions need to be. >>Yes. So the big data platform is essentially I think you call it, uh, context agnostic. And so is data becomes, you know, more important, our lives. You've got all these new data sources, you know, injected into the system. Experimentation as we said it with the cloud becomes much, much easier. So one of the blockers that you've started, you just mentioned it is you've got these hyper specialized roles the data engineer, the quality engineer, data scientists and and the It's illusory. I mean, it's like an illusion. These guys air, they seemingly they're independent and in scale independently. But I think you've made the point that in fact, they can't that a change in the data source has an effect across the entire data lifecycle entire data pipeline. So maybe you could maybe you could add some color to why that's problematic for some of the organizations that you work with and maybe give some examples. >>Yeah, absolutely so in fact, that initially the hypothesis around that image came from a Siris of requests that we received from our both large scale and progressive clients and progressive in terms of their investment in data architectures. So this is where clients that they were there were larger scale. They had divers and reached out of domains. Some of them were big technology tech companies. Some of them were retail companies, big health care companies. So they had that diversity off the data and the number off. You know, the sources of the domains they had invested for quite a few years in, you know, generations. If they had multi generations of proprietary data warehouses on print that they were moving to cloud, they had moved to the barriers, you know, revisions of the Hadoop clusters and they were moving to the cloud. And they the challenges that they were facing were simply there were not like, if I want to just, like, you know, simplifying in one phrase, they were not getting value from the data that they were collecting. There were continuously struggling Thio shift the culture because there was so much friction between all of these three phases of both consumption of the data and transformation and making it available consumption from sources and then providing it and serving it to the consumer. So that whole process was full of friction. Everybody was unhappy. So its bottom line is that you're collecting all this data. There is delay. There is lack of trust in the data itself because the data is not representative of the reality has gone through a transformation. But people that didn't understand really what the data was got delayed on bond. So there is no trust. It's hard to get to the data. It's hard to create. Ultimately, it's hard to create value from the data, and people are working really hard and under a lot of pressure. But it's still, you know, struggling. So we often you know, our solutions like we are. You know, Technologies will often pointed to technology. So we go. Okay, This this version of you know, some some proprietary data warehouse we're using is not the right thing. We should go to the cloud, and that certainly will solve our problems. Right? Or warehouse wasn't a good one. Let's make a deal Lake version. So instead of you know, extracting and then transforming and loading into the little bits. And that transformation is that, you know, heavy process, because you fundamentally made an assumption using warehouses that if I transform this data into this multi dimensional, perfectly designed schema that then everybody can run whatever choir they want that's gonna solve. You know everybody's problem, but in reality it doesn't because you you are delayed and there is no universal model that serves everybody's need. Everybody that needs the divers data scientists necessarily don't don't like the perfectly modeled data. They're looking for both signals and the noise. So then, you know, we've We've just gone from, uh, et elles to let's say now to Lake, which is okay, let's move the transformation to the to the last mile. Let's just get load the data into, uh into the object stores into semi structured files and get the data. Scientists use it, but they're still struggling because the problems that we mentioned eso then with the solution. What is the solution? Well, next generation data platform, let's put it on the cloud, and we sell clients that actually had gone through, you know, a year or multiple years of migration to the cloud. But with it was great. 18 months I've seen, you know, nine months migrations of the warehouse versus two year migrations of the various data sources to the clubhouse. But ultimately, the result is the same on satisfy frustrated data users, data providers, um, you know, with lack of ability to innovate quickly on relevant data and have have have an experience that they deserve toe have have a delightful experience off discovering and exploring data that they trust. And all of that was still a missed so something something else more fundamentally needed to change than just the technology. >>So then the linchpin to your scenario is this notion of context and you you pointed out you made the other observation that look, we've made our operational systems context aware. But our data platforms are not on bond like CRM system sales guys very comfortable with what's in the CRM system. They own the data. So let's talk about the answer that you and your colleagues are proposing. You're essentially flipping the architecture whereby those domain knowledge workers, the builders, if you will, of data products or data services there now, first class citizens in the data flow and they're injecting by design domain knowledge into the system. So So I wanna put up another one of your charts. Guys, bring up the figure to their, um it talks about, you know, convergence. You showed data distributed domain, dream and architecture. Er this self serve platform design and this notion of product thinking. So maybe you could explain why this approach is is so desirable, in your view, >>sure. The motivation and inspiration for the approach came from studying what has happened over the last few decades in operational systems. We had a very similar problem prior to micro services with monolithic systems, monolithic systems where you know the bottleneck. Um, the changes we needed to make was always, you know, our fellow Noto, how the architecture was centralized and we found a nice nation. I'm not saying this is the perfect way of decoupling a monolith, but it's a way that currently where we are in our journey to become data driven, um is a nice place to be, um, which is distribution or decomposition off your system as well as organization. I think when we whenever we talk about systems, we've got to talk about people and teams that's responsible for managing those systems. So the decomposition off the systems and the teams on the data around domains because that's how today we are decoupling our business, right? We're decoupling our businesses around domains, and that's a that's a good thing and that What does that do really for us? What it does? Is it localizes change to the bounded context of fact business. It creates clear boundary and interfaces and contracts between the rest of the universe of the organization on that particular team, so removes the friction that often we have for both managing the change and both serving data or capability. So it's the first principle of data meshes. Let's decouple this world off analytical data the same to mirror the same way we have to couple their systems and teams and business why data is any different. And the moment you do that, So you, the moment you bring the ownership to people who understands the data best, then you get questions that well, how is that any different from silence that's connected databases that we have today and nobody can get to the data? So then the rest of the principles is really to address all of the challenges that comes with this first principle of decomposition around domain Context on the second principle is well, we have to expect a certain level off quality and accountability and responsibility for the teams that provide the data. So let's bring product thinking and treating data as a product to the data that these teams now, um share and let's put accountability around. And we need a new set of incentives and metrics for domain teams to share the data. We need to have a new set off kind of quality metrics that define what it means for the data to be a product. And we can go through that conversation perhaps later eso then the second principle is okay. The teams now that are responsible, the domain teams responsible for the analytical data need to provide that data with a certain level of quality and assurance. Let's call that a product and bring products thinking to that. And then the next question you get asked off by C. E. O s or city or the people who build the infrastructure and, you know, spend the money. They said, Well, it's actually quite complex to manage big data, and now we're We want everybody, every independent team to manage the full stack of, you know, storage and computation and pipelines and, you know, access, control and all of that. And that's well, we have solved that problem in operational world. And that requires really a new level of platform thinking toe provide infrastructure and tooling to the domain teams to now be able to manage and serve their big data. And that I think that requires reimagining the world of our tooling and technology. But for now, let's just assume that we need a new level of abstraction to hide away ton of complexity that unnecessarily people get exposed to and that that's the third principle of creating Selves of infrastructure, um, to allow autonomous teams to build their domains. But then the last pillar, the last you know, fundamental pillar is okay. Once you distributed problem into a smaller problems that you found yourself with another set of problems, which is how I'm gonna connect this data, how I'm gonna you know, that the insights happens and emerges from the interconnection of the data domains right? It does not necessarily locked into one domain. So the concerns around interoperability and standardization and getting value as a result of composition and interconnection of these domains requires a new approach to governance. And we have to think about governance very differently based on a Federated model and based on a computational model. Like once we have this powerful self serve platform, we can computational e automate a lot of governance decisions. Um, that security decisions and policy decisions that applies to you know, this fabric of mesh not just a single domain or not in a centralized. Also, really. As you mentioned that the most important component of the emissions distribution of ownership and distribution of architecture and data the rest of them is to solve all the problems that come with that. >>So very powerful guys. We actually have a picture of what Jamaat just described. Bring up, bring up figure three, if you would tell me it. Essentially, you're advocating for the pushing of the pipeline and all its various functions into the lines of business and abstracting that complexity of the underlying infrastructure, which you kind of show here in this figure, data infrastructure is a platform down below. And you know what I love about this Jama is it to me, it underscores the data is not the new oil because I could put oil in my car I can put in my house, but I can't put the same court in both places. But I think you call it polyglot data, which is really different forms, batch or whatever. But the same data data doesn't follow the laws of scarcity. I can use the same data for many, many uses, and that's what this sort of graphic shows. And then you brought in the really important, you know, sticking problem, which is that you know the governance which is now not a command and control. It's it's Federated governance. So maybe you could add some thoughts on that. >>Sure, absolutely. It's one of those I think I keep referring to data much as a paradigm shift. And it's not just to make it sound ground and, you know, like, kind of ground and exciting or in court. And it's really because I want to point out, we need to question every moment when we make a decision around how we're going to design security or governance or modeling off the data, we need to reflect and go back and say, um, I applying some of my cognitive biases around how I have worked for the last 40 years, I have seen it work. Or do I do I really need to question. And we do need to question the way we have applied governance. I think at the end of the day, the rule of the data governance and objective remains the same. I mean, we all want quality data accessible to a diverse set of users. And these users now have different personas, like David, Personal data, analyst data, scientists, data application, Um, you know, user, very diverse personal. So at the end of the day, we want quality data accessible to them, um, trustworthy in in an easy consumable way. Um, however, how we get there looks very different in as you mentioned that the governance model in the old world has been very commander control, very centralized. Um, you know, they were responsible for quality. They were responsible for certification off the data, you know, applying making sure the data complies. But also such regulations Make sure you know, data gets discovered and made available in the world of the data mesh. Really. The job of the data governance as a function becomes finding that equilibrium between what decisions need to be um, you know, made and enforced globally. And what decisions need to be made locally so that we can have an interoperable measure. If data sets that can move fast and can change fast like it's really about instead of hardest, you know, kind of putting the putting those systems in a straitjacket of being constant and don't change, embrace, change and continuous change of landscape because that's that's just the reality we can't escape. So the role of governance really the governance model called Federated and Computational. And by that I mean, um, every domain needs to have a representative in the governance team. So the role of the data or domain data product owner who really were understand the data that domain really well but also wears that hacks of a product owner. It is an important role that had has to have a representation in the governance. So it's a federation off domains coming together, plus the SMEs and people have, you know, subject matter. Experts who understands the regulations in that environmental understands the data security concerns, but instead off trying to enforce and do this as a central team. They make decisions as what need to be standardized, what need to be enforced. And let's push that into that computational E and in an automated fashion into the into the camp platform itself. For example, instead of trying to do that, you know, be part of the data quality pipeline and inject ourselves as people in that process, let's actually, as a group, define what constitutes quality, like, how do we measure quality? And then let's automate that and let Z codify that into the platform so that every native products will have a C I City pipeline on as part of that pipeline. Those quality metrics gets validated and every day to product needs to publish those SLOC or service level objectives. So you know, whatever we choose as a measure of quality, maybe it's the, you know, the integrity of the data, the delay in the data, the liveliness of it, whatever the are the decisions that you're making, let's codify that. So it's, um, it's really, um, the role of the governance. The objectives of the governance team tried to satisfies the same, but how they do it. It is very, very different. I wrote a new article recently trying to explain the logical architecture that would emerge from applying these principles. And I put a kind of light table to compare and contrast the roll off the You know how we do governance today versus how we will do it differently to just give people a flavor of what does it mean to embrace the centralization? And what does it mean to embrace change and continuous change? Eso hopefully that that that could be helpful. >>Yes, very so many questions I haven't but the point you make it to data quality. Sometimes I feel like quality is the end game. Where is the end game? Should be how fast you could go from idea to monetization with the data service. What happens again? You sort of address this, but what happens to the underlying infrastructure? I mean, spinning a PC to S and S three buckets and my pie torches and tensor flows. And where does that that lives in the business? And who's responsible for that? >>Yeah, that's I'm glad you're asking this question. Maybe because, um, I truly believe we need to re imagine that world. I think there are many pieces that we can use Aziz utilities on foundational pieces, but I but I can see for myself a 5 to 7 year roadmap of building this new tooling. I think, in terms of the ownership, the question around ownership, if that would remains with the platform team, but and perhaps the domain agnostic, technology focused team right that there are providing instead of products themselves. And but the products are the users off those products are data product developers, right? Data domain teams that now have really high expectations in terms of low friction in terms of lead time to create a new data product. Eso We need a new set off tooling, and I think with the language needs to shift from, You know, I need a storage buckets. So I need a storage account. So I need a cluster to run my, you know, spark jobs, too. Here's the declaration of my data products. This is where the data for it will come from. This is the data that I want to serve. These are the policies that I need toe apply in terms of perhaps encryption or access control. Um, go make it happen. Platform, go provision, Everything that I mean so that as a data product developer. All I can focus on is the data itself, representation of semantic and representation of the syntax. And make sure that data meets the quality that I have that I have to assure and it's available. The rest of provisioning of everything that sits underneath will have to get taken care of by the platform. And that's what I mean by requires a re imagination and in fact, Andi, there will be a data platform team, the data platform teams that we set up for our clients. In fact, themselves have a favorite of complexity. Internally, they divide into multiple teams multiple planes, eso there would be a plane, as in a group of capabilities that satisfied that data product developer experience, there would be a set of capabilities that deal with those need a greatly underlying utilities. I call it at this point, utilities, because to me that the level of abstraction of the platform is to go higher than where it is. So what we call platform today are a set of utilities will be continuing to using will be continuing to using object storage, will continue using relation of databases and so on so there will be a plane and a group of people responsible for that. There will be a group of people responsible for capabilities that you know enable the mesh level functionality, for example, be able to correlate and connects. And query data from multiple knows. That's a measure level capability to be able to discover and explore the measure data products as a measure of capability. So it would be set of teams as part of platforms with a strong again platform product thinking embedded and product ownership embedded into that. To satisfy the experience of this now business oriented domain data team teams s way have a lot of work to do. >>I could go on. Unfortunately, we're out of time. But I guess my first I want to tell people there's two pieces that you put out so far. One is, uh, how to move beyond a monolithic data lake to a distributed data mesh. You guys should read that in a data mesh principles and logical architectures kind of part two. I guess my last question in the very limited time we have is our organization is ready for this. >>E think the desire is there I've bean overwhelmed with number off large and medium and small and private and public governments and federal, you know, organizations that reached out to us globally. I mean, it's not This is this is a global movement and I'm humbled by the response of the industry. I think they're the desire is there. The pains are really people acknowledge that something needs to change. Here s so that's the first step. I think that awareness isa spreading organizations. They're more and more becoming aware. In fact, many technology providers are reach out to us asking what you know, what shall we do? Because our clients are asking us, You know, people are already asking We need the data vision. We need the tooling to support. It s oh, that awareness is there In terms of the first step of being ready, However, the ingredients of a successful transformation requires top down and bottom up support. So it requires, you know, support from Chief Data Analytics officers or above the most successful clients that we have with data. Make sure the ones that you know the CEOs have made a statement that, you know, we want to change the experience of every single customer using data and we're going to do, we're going to commit to this. So the investment and support, you know, exists from top to all layers. The engineers are excited that maybe perhaps the traditional data teams are open to change. So there are a lot of ingredients. Substance to transformation is to come together. Um, are we really ready for it? I think I think the pioneers, perhaps the innovators. If you think about that innovation, careful. My doctors, probably pioneers and innovators and leaders. Doctors are making making move towards it. And hopefully, as the technology becomes more available, organizations that are less or in, you know, engineering oriented, they don't have the capability in house today, but they can buy it. They would come next. Maybe those are not the ones who aren't quite ready for it because the technology is not readily available. Requires, you know, internal investment today. >>I think you're right on. I think the leaders are gonna lead in hard, and they're gonna show us the path over the next several years. And I think the the end of this decade is gonna be defined a lot differently than the beginning. Jammeh. Thanks so much for coming in. The Cuban. Participate in the >>program. Pleasure head. >>Alright, Keep it right. Everybody went back right after this short break.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle, everybody to Cuban cloud. My name is Dave Volonte, and I'll be here throughout the day with my co host, John Ferrier, who was quarantined in an undisclosed location in California. He's all good. Don't worry. Just precautionary. John, how are you doing? >>Hey, great to see you. John. Quarantine. My youngest daughter had covitz, so contact tracing. I was negative in quarantine at a friend's location. All good. >>Well, we wish you the best. Yeah, well, right. I mean, you know what's it like, John? I mean, you're away from your family. Your basically shut in, right? I mean, you go out for a walk, but you're really not in any contact with anybody. >>Correct? Yeah. I mean, basically just isolation, Um, pretty much what everyone's been kind of living on, kind of suffering through, but hopefully the vaccines are being distributed. You know, one of the things we talked about it reinvent the Amazon's cloud conference. Was the vaccine on, but just the whole workflow around that it's gonna get better. It's kind of really sucky. Here in the California area, they haven't done a good job, a lot of criticism around, how that's rolling out. And, you know, Amazon is now offering to help now that there's a new regime in the U. S. Government S o. You know, something to talk about, But certainly this has been a terrible time for Cove it and everyone in the deaths involved. But it's it's essentially pulled back the covers, if you will, on technology and you're seeing everything. Society. In fact, um, well, that's big tech MIT disinformation campaigns. All these vulnerabilities and cyber, um, accelerated digital transformation. We'll talk about a lot today, but yeah, it's totally changed the world. And I think we're in a new generation. I think this is a real inflection point, Dave. You know, modern society and the geo political impact of this is significant. You know, one of the benefits of being quarantined you'd be hanging out on these clubhouse APS, uh, late at night, listening to experts talk about what's going on, and it's interesting what's happening with with things like water and, you know, the island of Taiwan and China and U. S. Sovereignty, data, sovereignty, misinformation. So much going on to talk about. And, uh, meanwhile, companies like Mark injuries in BC firm starting a media company. What's going on? Hell freezing over. So >>we're gonna be talking about a lot of that stuff today. I mean, Cuba on cloud. It's our very first virtual editorial event we're trying to do is bring together our community. It's a it's an open forum and we're we're running the day on our 3 65 software platform. So we got a great lineup. We got CEO Seo's data Practitioners. We got a hard core technologies coming in, cloud experts, investors. We got some analysts coming in and we're creating this day long Siri's. And we've got a number of sessions that we've developed and we're gonna unpack. The future of Cloud computing in the coming decade is, John said, we're gonna talk about some of the public policy new administration. What does that mean for tech and for big tech in General? John, what can you add to that? >>Well, I think one of the things that we talked about Cove in this personal impact to me but other people as well. One of the things that people are craving right now is information factual information, truth texture that we call it. But hear this event for us, Davis, our first inaugural editorial event. Robbo, Kristen, Nicole, the entire Cube team Silicon angle, really trying to put together Morva cadence we're gonna doom or of these events where we can put out feature the best people in our community that have great fresh voices. You know, we do interview the big names Andy Jassy, Michael Dell, the billionaires with people making things happen. But it's often the people under there that are the rial newsmakers amid savory, for instance, that Google one of the most impressive technical people, he's gotta talk. He's gonna present democratization of software development in many Mawr riel people making things happen. And I think there's a communal element. We're going to do more of these. Obviously, we have, uh, no events to go to with the Cube. So we have the cube virtual software that we have been building and over years and now perfecting and we're gonna introduce that we're gonna put it to work, their dog footing it. We're gonna put that software toe work. We're gonna do a lot mawr virtual events like this Cuban cloud Cuban startup Cuban raising money. Cuban healthcare, Cuban venture capital. Always think we could do anything. Question is, what's the right story? What's the most important stories? Who's telling it and increase the aperture of the lens of the industry that we have and and expose that and fastest possible. That's what this software, you'll see more of it. So it's super exciting. We're gonna add new features like pulling people up on stage, Um, kind of bring on the clubhouse vibe and more of a community interaction with people to meet each other, and we'll roll those out. But the goal here is to just showcase it's cloud story in a way from people that are living it and providing value. So enjoy the day is gonna be chock full of presentations. We're gonna have moderated chat in these sessions, so it's an all day event so people can come in, drop out, and also that's everything's on demand immediately after the time slot. But you >>want to >>participate, come into the time slot into the cube room or breakout session. Whatever you wanna call it, it's a cube room, and the people in there chatting and having a watch party. So >>when you're in that home page when you're watching, there's a hero video there. Beneath that, there's a calendar, and you'll see that red line is that red horizontal line of vertical line is rather, it's a linear clock that will show you where we are in the day. If you click on any one of those sessions that will take you into the chat, we'll take you through those in a moment and share with you some of the guests that we have upcoming and and take you through the day what I wanted to do. John is trying to set the stage for the conversations that folks are gonna here today. And to do that, I wanna ask the guys to bring up a graphic. And I want to talk to you, John, about the progression of cloud over time and maybe go back to the beginning and review the evolution of cloud and then really talk a little bit about where we think it Z headed. So, guys, if you bring up that graphic when a W S announced s three, it was March of 2000 and six. And as you recall, John you know, nobody really. In the vendor and user community. They didn't really pay too much attention to that. And then later that year, in August, it announced E C two people really started. They started to think about a new model of computing, but they were largely, you know, chicken tires. And it was kind of bleeding edge developers that really leaned in. Um what? What were you thinking at the time? When when you saw, uh, s three e c to this retail company coming into the tech world? >>I mean, I thought it was totally crap. I'm like, this is terrible. But then at that time, I was thinking working on I was in between kind of start ups and I didn't have a lot of seed funding. And then I realized the C two was freaking awesome. But I'm like, Holy shit, this is really great because I don't need to pay a lot of cash, the Provisional Data center, or get a server. Or, you know, at that time, state of the art startup move was to buy a super micro box or some sort of power server. Um, it was well past the whole proprietary thing. But you have to assemble probably anyone with 5 to 8 grand box and go in, and we'll put a couple ghetto rack, which is basically, uh, you know, you put it into some coasting location. It's like with everybody else in the tech ghetto of hosting, still paying monthly fees and then maintaining it and provisioning that's just to get started. And then Amazon was just really easy. And then from there you just It was just awesome. I just knew Amazon would be great. They had a lot of things that they had to fix. You know, custom domains and user interface Council got better and better, but it was awesome. >>Well, what we really saw the cloud take hold from my perspective anyway, was the financial crisis in, you know, 709 It put cloud on the radar of a number of CFOs and, of course, shadow I T departments. They wanted to get stuff done and and take I t in in in, ah, pecs, bite sized chunks. So it really was. There's cloud awakening and we came out of that financial crisis, and this we're now in this 10 year plus boom um, you know, notwithstanding obviously the economic crisis with cove it. But much of it was powered by the cloud in the decade. I would say it was really about I t transformation. And it kind of ironic, if you will, because the pandemic it hits at the beginning of this decade, >>and it >>creates this mandate to go digital. So you've you've said a lot. John has pulled forward. It's accelerated this industry transformation. Everybody talks about that, but and we've highlighted it here in this graphic. It probably would have taken several more years to mature. But overnight you had this forced march to digital. And if you weren't a digital business, you were kind of out of business. And and so it's sort of here to stay. How do you see >>You >>know what this evolution and what we can expect in the coming decades? E think it's safe to say the last 10 years defined by you know, I t transformation. That's not gonna be the same in the coming years. How do you see it? >>It's interesting. I think the big tech companies are on, but I think this past election, the United States shows um, the power that technology has. And if you look at some of the main trends in the enterprise specifically around what clouds accelerating, I call the second wave of innovations coming where, um, it's different. It's not what people expect. Its edge edge computing, for instance, has talked about a lot. But industrial i o t. Is really where we've had a lot of problems lately in terms of hacks and malware and just just overall vulnerabilities, whether it's supply chain vulnerabilities, toe actual disinformation, you know, you know, vulnerabilities inside these networks s I think this network effects, it's gonna be a huge thing. I think the impact that tech will have on society and global society geopolitical things gonna be also another one. Um, I think the modern application development of how applications were written with data, you know, we always been saying this day from the beginning of the Cube data is his integral part of the development process. And I think more than ever, when you think about cloud and edge and this distributed computing paradigm, that cloud is now going next level with is the software and how it's written will be different. You gotta handle things like, where's the compute component? Is it gonna be at the edge with all the server chips, innovations that Amazon apple intel of doing, you're gonna have compute right at the edge, industrial and kind of human edge. How does that work? What's Leighton see to that? It's it really is an edge game. So to me, software has to be written holistically in a system's impact on the way. Now that's not necessarily nude in the computer science and in the tech field, it's just gonna be deployed differently. So that's a complete rewrite, in my opinion of the software applications. Which is why you're seeing Amazon Google VM Ware really pushing Cooper Netease and these service messes in the micro Services because super critical of this technology become smarter, automated, autonomous. And that's completely different paradigm in the old full stack developer, you know, kind of model. You know, the full stack developer, his ancient. There's no such thing as a full stack developer anymore, in my opinion, because it's a half a stack because the cloud takes up the other half. But no one wants to be called the half stack developer because it doesn't sound as good as Full Stack, but really Cloud has eliminated the technology complexity of what a full stack developer used to dio. Now you can manage it and do things with it, so you know, there's some work to done, but the heavy lifting but taking care of it's the top of the stack that I think is gonna be a really critical component. >>Yeah, and that that sort of automation and machine intelligence layer is really at the top of the stack. This this thing becomes ubiquitous, and we now start to build businesses and new processes on top of it. I wanna I wanna take a look at the Big Three and guys, Can we bring up the other The next graphic, which is an estimate of what the revenue looks like for the for the Big three. And John, this is I asked and past spend for the Big Three Cloud players. And it's It's an estimate that we're gonna update after earning seasons, and I wanna point a couple things out here. First is if you look at the combined revenue production of the Big Three last year, it's almost 80 billion in infrastructure spend. I mean, think about that. That Z was that incremental spend? No. It really has caused a lot of consolidation in the on Prem data center business for guys like Dell. And, you know, um, see, now, part of the LHP split up IBM Oracle. I mean, it's etcetera. They've all felt this sea change, and they had to respond to it. I think the second thing is you can see on this data. Um, it's true that azure and G C P they seem to be growing faster than a W s. We don't know the exact numbers >>because >>A W S is the only company that really provides a clean view of i s and pass. Whereas Microsoft and Google, they kind of hide the ball in their numbers. I mean, I don't blame them because they're behind, but they do leave breadcrumbs and clues about growth rates and so forth. And so we have other means of estimating, but it's it's undeniable that azure is catching up. I mean, it's still quite distance the third thing, and before I want to get your input here, John is this is nuanced. But despite the fact that Azure and Google the growing faster than a W s. You can see those growth rates. A W s I'll call this out is the only company by our estimates that grew its business sequentially last quarter. Now, in and of itself, that's not significant. But what is significant is because AWS is so large there $45 billion last year, even if the slower growth rates it's able to grow mawr and absolute terms than its competitors, who are basically flat to down sequentially by our estimates. Eso So that's something that I think is important to point out. Everybody focuses on the growth rates, but it's you gotta look at also the absolute dollars and, well, nonetheless, Microsoft in particular, they're they're closing the gap steadily, and and we should talk more about the competitive dynamics. But I'd love to get your take on on all this, John. >>Well, I mean, the clouds are gonna win right now. Big time with the one the political climate is gonna be favoring Big check. But more importantly, with just talking about covert impact and celebrating the digital transformation is gonna create a massive rising tide. It's already happening. It's happening it's happening. And again, this shift in programming, uh, models are gonna really kinda accelerating, create new great growth. So there's no doubt in my mind of all three you're gonna win big, uh, in the future, they're just different, You know, the way they're going to market position themselves, they have to be. Google has to be a little bit different than Amazon because they're smaller and they also have different capabilities, then trying to catch up. So if you're Google or Microsoft, you have to have a competitive strategy to decide. How do I wanna ride the tide If you will put the rising tide? Well, if I'm Amazon, I mean, if I'm Microsoft and Google, I'm not going to try to go frontal and try to copy Amazon because Amazon is just pounding lead of features and scale and they're different. They were, I would say, take advantage of the first mover of pure public cloud. They really awesome. It passed and I, as they've integrated in Gardner, now reports and integrated I as and passed components. So Gardner finally got their act together and said, Hey, this is really one thing. SAS is completely different animal now Microsoft Super Smart because they I think they played the right card. They have a huge installed base converted to keep office 3 65 and move sequel server and all their core jewels into the cloud as fast as possible, clarified while filling in the gaps on the product side to be cloud. So you know, as you're doing trends job, they're just it's just pedal as fast as you can. But Microsoft is really in. The strategy is just go faster trying. Keep pedaling fast, get the features, feature velocity and try to make it high quality. Google is a little bit different. They have a little power base in terms of their network of strong, and they have a lot of other big data capabilities, so they have to use those to their advantage. So there is. There is there is competitive strategy game application happening with these companies. It's not like apples, the apples, In my opinion, it never has been, and I think that's funny that people talk about it that way. >>Well, you're bringing up some great points. I want guys bring up the next graphic because a lot of things that John just said are really relevant here. And what we're showing is that's a survey. Data from E. T. R R Data partners, like 1400 plus CEOs and I T buyers and on the vertical axis is this thing called Net score, which is a measure of spending momentum. And the horizontal axis is is what's called market share. It's a measure of the pervasiveness or, you know, number of mentions in the data set. There's a couple of key points I wanna I wanna pick up on relative to what John just said. So you see A W S and Microsoft? They stand alone. I mean, they're the hyper scale er's. They're far ahead of the pack and frankly, they have fall down, toe, lose their lead. They spend a lot on Capex. They got the flywheel effects going. They got both spending velocity and large market shares, and so, but they're taking a different approach. John, you're right there living off of their SAS, the state, their software state, Andi, they're they're building that in to their cloud. So they got their sort of a captive base of Microsoft customers. So they've got that advantage. They also as we'll hear from from Microsoft today. They they're building mawr abstraction layers. Andy Jassy has said We don't wanna be in that abstraction layer business. We wanna have access to those, you know, fine grain primitives and eso at an AP level. So so we can move fast with the market. But but But so those air sort of different philosophies, John? >>Yeah. I mean, you know, people who know me know that I love Amazon. I think their product is superior at many levels on in its way that that has advantages again. They have a great sass and ecosystem. They don't really have their own SAS play, although they're trying to add some stuff on. I've been kind of critical of Microsoft in the past, but one thing I'm not critical of Microsoft, and people can get this wrong in the marketplace. Actually, in the journalism world and also in just some other analysts, Microsoft has always had large scale eso to say that Microsoft never had scale on that Amazon owned the monopoly on our franchise on scales wrong. Microsoft had scale from day one. Their business was always large scale global. They've always had infrastructure with MSN and their search and the distributive how they distribute browsers and multiple countries. Remember they had the lock on the operating system and the browser for until the government stepped in in 1997. And since 1997 Microsoft never ever not invested in infrastructure and scale. So that whole premise that they don't compete well there is wrong. And I think that chart demonstrates that there, in there in the hyper scale leadership category, hands down the question that I have. Is that there not as good and making that scale integrate in because they have that legacy cards. This is the classic innovator's dilemma. Clay Christensen, right? So I think they're doing a good job. I think their strategy sound. They're moving as fast as they can. But then you know they're not gonna come out and say We don't have the best cloud. Um, that's not a marketing strategy. Have to kind of hide in this and get better and then double down on where they're winning, which is. Clients are converting from their legacy at the speed of Microsoft, and they have a huge client base, So that's why they're stopping so high That's why they're so good. >>Well, I'm gonna I'm gonna give you a little preview. I talked to gear up your f Who's gonna come on today and you'll see I I asked him because the criticism of Microsoft is they're, you know, they're just good enough. And so I asked him, Are you better than good enough? You know, those are fighting words if you're inside of Microsoft, but so you'll you'll have to wait to see his answer. Now, if you guys, if you could bring that that graphic back up I wanted to get into the hybrid zone. You know where the field is. Always got >>some questions coming in on chat, Dave. So we'll get to those >>great Awesome. So just just real quick Here you see this hybrid zone, this the field is bunched up, and the other companies who have a large on Prem presence and have been forced to initiate some kind of coherent cloud strategy included. There is Michael Michael, multi Cloud, and Google's there, too, because they're far behind and they got to take a different approach than a W s. But as you can see, so there's some real progress here. VM ware cloud on AWS stands out, as does red hat open shift. You got VM Ware Cloud, which is a VCF Cloud Foundation, even Dell's cloud. And you'd expect HP with Green Lake to be picking up momentum in the future quarters. And you've got IBM and Oracle, which there you go with the innovator's dilemma. But there, at least in the cloud game, and we can talk about that. But so, John, you know, to your point, you've gotta have different strategies. You're you're not going to take out the big too. So you gotta play, connect your print your on Prem to your cloud, your hybrid multi cloud and try to create new opportunities and new value there. >>Yeah, I mean, I think we'll get to the question, but just that point. I think this Zeri Chen's come on the Cube many times. We're trying to get him to come on lunch today with Features startup, but he's always said on the Q B is a V C at Greylock great firm. Jerry's Cloud genius. He's been there, but he made a point many, many years ago. It's not a winner. Take all the winner. Take most, and the Big Three maybe put four or five in there. We'll take most of the markets here. But I think one of the things that people are missing and aren't talking about Dave is that there's going to be a second tier cloud, large scale model. I don't want to say tear to cloud. It's coming to sound like a sub sub cloud, but a new category of cloud on cloud, right? So meaning if you get a snowflake, did I think this is a tale? Sign to what's coming. VM Ware Cloud is a native has had huge success, mainly because Amazon is essentially enabling them to be successful. So I think is going to be a wave of a more of a channel model of indirect cloud build out where companies like the Cube, potentially for media or others, will build clouds on top of the cloud. So if Google, Microsoft and Amazon, whoever is the first one to really enable that okay, we'll do extremely well because that means you can compete with their scale and create differentiation on top. So what snowflake did is all on Amazon now. They kind of should go to azure because it's, you know, politically correct that have multiple clouds and distribution and business model shifts. But to get that kind of performance they just wrote on Amazon. So there's nothing wrong with that. Because you're getting paid is variable. It's cap ex op X nice categorization. So I think that's the way that we're watching. I think it's super valuable, I think will create some surprises in terms of who might come out of the woodwork on be a leader in a category. Well, >>your timing is perfect, John and we do have some questions in the chat. But before we get to that, I want to bring in Sargi Joe Hall, who's a contributor to to our community. Sargi. Can you hear us? All right, so we got, uh, while >>bringing in Sarpy. Let's go down from the questions. So the first question, Um, we'll still we'll get the student second. The first question. But Ronald ask, Can a vendor in 2021 exist without a hybrid cloud story? Well, story and capabilities. Yes, they could live with. They have to have a story. >>Well, And if they don't own a public cloud? No. No, they absolutely cannot. Uh hey, Sergey. How you doing, man? Good to see you. So, folks, let me let me bring in Sergeant Kohala. He's a He's a cloud architect. He's a practitioner, He's worked in as a technologist. And there's a frequent guest on on the Cube. Good to see you, my friend. Thanks for taking the time with us. >>And good to see you guys to >>us. So we were kind of riffing on the competitive landscape we got. We got so much to talk about this, like, it's a number of questions coming in. Um, but Sargi we wanna talk about you know, what's happening here in Cloud Land? Let's get right into it. I mean, what do you guys see? I mean, we got yesterday. New regime, new inaug inauguration. Do you do you expect public policy? You'll start with you Sargi to have What kind of effect do you think public policy will have on, you know, cloud generally specifically, the big tech companies, the tech lash. Is it gonna be more of the same? Or do you see a big difference coming? >>I think that there will be some changing narrative. I believe on that. is mainly, um, from the regulators side. A lot has happened in one month, right? So people, I think are losing faith in high tech in a certain way. I mean, it doesn't, uh, e think it matters with camp. You belong to left or right kind of thing. Right? But parlor getting booted out from Italy s. I think that was huge. Um, like, how do you know that if a cloud provider will not boot you out? Um, like, what is that line where you draw the line? What are the rules? I think that discussion has to take place. Another thing which has happened in the last 23 months is is the solar winds hack, right? So not us not sort acknowledging that I was Russia and then wish you watching it now, new administration might have a different sort of Boston on that. I think that's huge. I think public public private partnership in security arena will emerge this year. We have to address that. Yeah, I think it's not changing. Uh, >>economics economy >>will change gradually. You know, we're coming out off pandemic. The money is still cheap on debt will not be cheap. for long. I think m and a activity really will pick up. So those are my sort of high level, Uh, >>thank you. I wanna come back to them. And because there's a question that chat about him in a But, John, how do you see it? Do you think Amazon and Google on a slippery slope booting parlor off? I mean, how do they adjudicate between? Well, what's happening in parlor? Uh, anything could happen on clubhouse. Who knows? I mean, can you use a I to find that stuff? >>Well, that's I mean, the Amazons, right? Hiding right there bunkered in right now from that bad, bad situation. Because again, like people we said Amazon, these all three cloud players win in the current environment. Okay, Who wins with the U. S. With the way we are China, Russia, cloud players. Okay, let's face it, that's the reality. So if I wanted to reset the world stage, you know what better way than the, you know, change over the United States economy, put people out of work, make people scared, and then reset the entire global landscape and control all with cash? That's, you know, conspiracy theory. >>So you see the riches, you see the riches, get the rich, get richer. >>Yeah, well, that's well, that's that. That's kind of what's happening, right? So if you start getting into this idea that you can't actually have an app on site because the reason now I'm not gonna I don't know the particular parlor, but apparently there was a reason. But this is dangerous, right? So what? What that's gonna do is and whether it's right or wrong or not, whether political opinion is it means that they were essentially taken offline by people that weren't voted for that. Weren't that when people didn't vote for So that's not a democracy, right? So that's that's a different kind of regime. What it's also going to do is you also have this groundswell of decentralized thinking, right. So you have a whole wave of crypto and decentralized, um, cyber punks out there who want to decentralize it. So all of this stuff in January has created a huge counterculture, and I had predicted this so many times in the Cube. David counterculture is coming and and you already have this kind of counterculture between centralized and decentralized thinking and so I think the Amazon's move is dangerous at a fundamental level. Because if you can't get it, if you can't get buy domain names and you're completely blackballed by by organized players, that's a Mafia, in my opinion. So, uh, and that and it's also fuels the decentralized move because people say, Hey, if that could be done to them, it could be done to me. Just the fact that it could be done will promote a swing in the other direction. I >>mean, independent of of, you know, again, somebody said your political views. I mean Parlor would say, Hey, we're trying to clean this stuff up now. Maybe they didn't do it fast enough, but you think about how new parlor is. You think about the early days of Twitter and Facebook, so they were sort of at a disadvantage. Trying to >>have it was it was partly was what it was. It was a right wing stand up job of standing up something quick. Their security was terrible. If you look at me and Cory Quinn on be great to have him, and he did a great analysis on this, because if you look the lawsuit was just terrible. Security was just a half, asshole. >>Well, and the experience was horrible. I mean, it's not It was not a great app, but But, like you said, it was a quick stew. Hand up, you know, for an agenda. But nonetheless, you know, to start, get to your point earlier. It's like, you know, Are they gonna, you know, shut me down? If I say something that's, you know, out of line, or how do I control that? >>Yeah, I remember, like, 2019, we involved closing sort of remarks. I was there. I was saying that these companies are gonna be too big to fail. And also, they're too big for other nations to do business with. In a way, I think MNCs are running the show worldwide. They're running the government's. They are way. Have seen the proof of that in us this year. Late last year and this year, um, Twitter last night blocked Chinese Ambassador E in us. Um, from there, you know, platform last night and I was like, What? What's going on? So, like, we used to we used to say, like the Chinese company, tech companies are in bed with the Chinese government. Right. Remember that? And now and now, Actually, I think Chinese people can say the same thing about us companies. Uh, it's not a good thing. >>Well, let's >>get some question. >>Let's get some questions from the chat. Yeah. Thank you. One is on M and a subject you mentioned them in a Who do you see is possible emanate targets. I mean, I could throw a couple out there. Um, you know, some of the cdn players, maybe aka my You know, I like I like Hashi Corp. I think they're doing some really interesting things. What do you see? >>Nothing. Hashi Corp. And anybody who's doing things in the periphery is a candidate for many by the big guys, you know, by the hyper scholars and number two tier two or five hyper scholars. Right. Uh, that's why sales forces of the world and stuff like that. Um, some some companies, which I thought there will be a target, Sort of. I mean, they target they're getting too big, because off their evaluations, I think how she Corpuz one, um, >>and >>their bunch in the networking space. Uh, well, Tara, if I say the right that was acquired by at five this week, this week or last week, Actually, last week for $500 million. Um, I know they're founder. So, like I found that, Yeah, there's a lot going on on the on the network side on the anything to do with data. Uh, that those air too hard areas in the cloud arena >>data, data protection, John, any any anything you could adhere. >>And I think I mean, I think ej ej is gonna be where the gaps are. And I think m and a activity is gonna be where again, the bigger too big to fail would agree with you on that one. But we're gonna look at white Spaces and say a white space for Amazon is like a monster space for a start up. Right? So you're gonna have these huge white spaces opportunities, and I think it's gonna be an M and a opportunity big time start ups to get bought in. Given the speed on, I think you're gonna see it around databases and around some of these new service meshes and micro services. I mean, >>they there's a There's a question here, somebody's that dons asking why is Google who has the most pervasive tech infrastructure on the planet. Not at the same level of other to hyper scale is I'll give you my two cents is because it took him a long time to get their heads out of their ads. I wrote a piece of around that a while ago on they just they figured out how to learn the enterprise. I mean, John, you've made this point a number of times, but they just and I got a late start. >>Yeah, they're adding a lot of people. If you look at their who their hiring on the Google Cloud, they're adding a lot of enterprise chops in there. They realized this years ago, and we've talked to many of the top leaders, although Curry and hasn't yet sit down with us. Um, don't know what he's hiding or waiting for, but they're clearly not geared up to chicken Pete. You can see it with some some of the things that they're doing, but I mean competed the level of Amazon, but they have strength and they're playing their strength, but they definitely recognize that they didn't have the enterprise motions and people in the DNA and that David takes time people in the enterprise. It's not for the faint of heart. It's unique details that are different. You can't just, you know, swing the Google playbook and saying We're gonna home The enterprises are text grade. They knew that years ago. So I think you're going to see a good year for Google. I think you'll see a lot of change. Um, they got great people in there. On the product marketing side is Dev Solution Architects, and then the SRE model that they have perfected has been strong. And I think security is an area that they could really had a lot of value it. So, um always been a big fan of their huge network and all the intelligence they have that they could bring to bear on security. >>Yeah, I think Google's problem main problem that to actually there many, but one is that they don't They don't have the boots on the ground as compared to um, Microsoft, especially an Amazon actually had a similar problem, but they had a wide breath off their product portfolio. I always talk about feature proximity in cloud context, like if you're doing one thing. You wanna do another thing? And how do you go get that feature? Do you go to another cloud writer or it's right there where you are. So I think Amazon has the feature proximity and they also have, uh, aske Compared to Google, there's skills gravity. Larger people are trained on AWS. I think Google is trying there. So second problem Google is having is that that they're they're more focused on, I believe, um, on the data science part on their sort of skipping the cool components sort of off the cloud, if you will. The where the workloads needs, you know, basic stuff, right? That's like your compute storage and network. And that has to be well, talk through e think e think they will do good. >>Well, so later today, Paul Dillon sits down with Mids Avery of Google used to be in Oracle. He's with Google now, and he's gonna push him on on the numbers. You know, you're a distant third. Does that matter? And of course, you know, you're just a preview of it's gonna say, Well, no, we don't really pay attention to that stuff. But, John, you said something earlier that. I think Jerry Chen made this comment that, you know, Is it a winner? Take all? No, but it's a winner. Take a lot. You know the number two is going to get a big chunk of the pie. It appears that the markets big enough for three. But do you? Does Google have to really dramatically close the gap on be a much, much closer, you know, to the to the leaders in orderto to compete in this race? Or can they just kind of continue to bump along, siphon off the ad revenue? Put it out there? I mean, I >>definitely can compete. I think that's like Google's in it. Then it they're not. They're not caving, right? >>So But But I wrote I wrote recently that I thought they should even even put mawr oven emphasis on the cloud. I mean, maybe maybe they're already, you know, doubling down triple down. I just I think that is a multi trillion dollar, you know, future for the industry. And, you know, I think Google, believe it or not, could even do more. Now. Maybe there's just so much you could dio. >>There's a lot of challenges with these company, especially Google. They're in Silicon Valley. We have a big Social Justice warrior mentality. Um, there's a big debate going on the in the back channels of the tech scene here, and that is that if you want to be successful in cloud, you have to have a good edge strategy, and that involves surveillance, use of data and pushing the privacy limits. Right? So you know, Google has people within the country that will protest contract because AI is being used for war. Yet we have the most unstable geopolitical seen that I've ever witnessed in my lifetime going on right now. So, um, don't >>you think that's what happened with parlor? I mean, Rob Hope said, Hey, bar is pretty high to kick somebody off your platform. The parlor went over the line, but I would also think that a lot of the employees, whether it's Google AWS as well, said, Hey, why are we supporting you know this and so to your point about social justice, I mean, that's not something. That >>parlor was not just social justice. They were trying to throw the government. That's Rob e. I think they were in there to get selfies and being protesters. But apparently there was evidence from what I heard in some of these clubhouse, uh, private chats. Waas. There was overwhelming evidence on parlor. >>Yeah, but my point is that the employee backlash was also a factor. That's that's all I'm saying. >>Well, we have Google is your Google and you have employees to say we will boycott and walk out if you bid on that jet I contract for instance, right, But Microsoft one from maybe >>so. I mean, that's well, >>I think I think Tom Poole's making a really good point here, which is a Google is an alternative. Thio aws. The last Google cloud next that we were asked at they had is all virtual issue. But I saw a lot of I T practitioners in the audience looking around for an alternative to a W s just seeing, though, we could talk about Mano Cloud or Multi Cloud, and Andy Jassy has his his narrative around, and he's true when somebody goes multiple clouds, they put you know most of their eggs in one basket. Nonetheless, I think you know, Google's got a lot of people interested in, particularly in the analytic side, um, in in an alternative, hedging their bets eso and particularly use cases, so they should be able to do so. I guess my the bottom line here is the markets big enough to have Really? You don't have to be the Jack Welch. I gotta be number one and number two in the market. Is that the conclusion here? >>I think so. But the data gravity and the skills gravity are playing against them. Another problem, which I didn't want a couple of earlier was Google Eyes is that they have to boot out AWS wherever they go. Right? That is a huge challenge. Um, most off the most off the Fortune 2000 companies are already using AWS in one way or another. Right? So they are the multi cloud kind of player. Another one, you know, and just pure purely somebody going 200% Google Cloud. Uh, those cases are kind of pure, if you will. >>I think it's gonna be absolutely multi cloud. I think it's gonna be a time where you looked at the marketplace and you're gonna think in terms of disaster recovery, model of cloud or just fault tolerant capabilities or, you know, look at the parlor, the next parlor. Or what if Amazon wakes up one day and said, Hey, I don't like the cubes commentary on their virtual events, so shut them down. We should have a fail over to Google Cloud should Microsoft and Option. And one of people in Microsoft ecosystem wants to buy services from us. We have toe kind of co locate there. So these are all open questions that are gonna be the that will become certain pretty quickly, which is, you know, can a company diversify their computing An i t. In a way that works. And I think the momentum around Cooper Netease you're seeing as a great connective tissue between, you know, having applications work between clouds. Right? Well, directionally correct, in my opinion, because if I'm a company, why wouldn't I wanna have choice? So >>let's talk about this. The data is mixed on that. I'll share some data, meaty our data with you. About half the companies will say Yeah, we're spreading the wealth around to multiple clouds. Okay, That's one thing will come back to that. About the other half were saying, Yeah, we're predominantly mono cloud we didn't have. The resource is. But what I think going forward is that that what multi cloud really becomes. And I think John, you mentioned Snowflake before. I think that's an indicator of what what true multi cloud is going to look like. And what Snowflake is doing is they're building abstraction, layer across clouds. Ed Walsh would say, I'm standing on the shoulders of Giants, so they're basically following points of presence around the globe and building their own cloud. They call it a data cloud with a global mesh. We'll hear more about that later today, but you sign on to that cloud. So they're saying, Hey, we're gonna build value because so many of Amazon's not gonna build that abstraction layer across multi clouds, at least not in the near term. So that's a really opportunity for >>people. I mean, I don't want to sound like I'm dating myself, but you know the date ourselves, David. I remember back in the eighties, when you had open systems movement, right? The part of the whole Revolution OS I open systems interconnect model. At that time, the networking stacks for S N A. For IBM, decadent for deck we all know that was a proprietary stack and then incomes TCP I p Now os I never really happened on all seven layers, but the bottom layers standardized. Okay, that was huge. So I think if you look at a W s or some of the comments in the chat AWS is could be the s n a. Depends how you're looking at it, right? And you could say they're open. But in a way, they want more Amazon. So Amazon's not out there saying we love multi cloud. Why would they promote multi cloud? They are a one of the clouds they want. >>That's interesting, John. And then subject is a cloud architect. I mean, it's it is not trivial to make You're a data cloud. If you're snowflake, work on AWS work on Google. Work on Azure. Be seamless. I mean, certainly the marketing says that, but technically, that's not trivial. You know, there are latent see issues. Uh, you know, So that's gonna take a while to develop. What? Do your thoughts there? >>I think that multi cloud for for same workload and multi cloud for different workloads are two different things. Like we usually put multiple er in one bucket, right? So I think you're right. If you're trying to do multi cloud for the same workload, that's it. That's Ah, complex, uh, problem to solve architecturally, right. You have to have a common ap ice and common, you know, control playing, if you will. And we don't have that yet, and then we will not have that for a for at least one other couple of years. So, uh, if you if you want to do that, then you have to go to the lower, lowest common denominator in technical sort of stock, if you will. And then you're not leveraging the best of the breed technology off their from different vendors, right? I believe that's a hard problem to solve. And in another thing, is that that that I always say this? I'm always on the death side, you know, developer side, I think, uh, two deaths. Public cloud is a proxy for innovative culture. Right. So there's a catch phrase I have come up with today during shower eso. I think that is true. And then people who are companies who use the best of the breed technologies, they can attract the these developers and developers are the Mazen's off This digital sort of empires, amazingly, is happening there. Right there they are the Mazen's right. They head on the bricks. I think if you don't appeal to developers, if you don't but extensive for, like, force behind educating the market, you can't you can't >>put off. It's the same game Stepping story was seeing some check comments. Uh, guard. She's, uh, linked in friend of mine. She said, Microsoft, If you go back and look at the Microsoft early days to the developer Point they were, they made their phones with developers. They were a software company s Oh, hey, >>forget developers, developers, developers. >>You were if you were in the developer ecosystem, you were treated his gold. You were part of the family. If you were outside that world, you were competitors, and that was ruthless times back then. But they again they had. That was where it was today. Look at where the software defined businesses and starve it, saying it's all about being developer lead in this new way to program, right? So the cloud next Gen Cloud is going to look a lot like next Gen Developer and all the different tools and techniques they're gonna change. So I think, yes, this kind of developer ecosystem will be harnessed, and that's the power source. It's just gonna look different. So, >>Justin, Justin in the chat has a comment. I just want to answer the question about elastic thoughts on elastic. Um, I tell you, elastic has momentum uh, doing doing very well in the market place. Thea Elk Stack is a great alternative that people are looking thio relative to Splunk. Who people complain about the pricing. Of course it's plunks got the easy button, but it is getting increasingly expensive. The problem with elk stack is you know, it's open source. It gets complicated. You got a shard, the databases you gotta manage. It s Oh, that's what Ed Walsh's company chaos searches is all about. But elastic has some riel mo mentum in the marketplace right now. >>Yeah, you know, other things that coming on the chat understands what I was saying about the open systems is kubernetes. I always felt was that is a bad metaphor. But they're with me. That was the TCP I peep In this modern era, C t c p I p created that that the disruptor to the S N A s and the network protocols that were proprietary. So what KUBERNETES is doing is creating a connective tissue between clouds and letting the open source community fill in the gaps in the middle, where kind of way kind of probably a bad analogy. But that's where the disruption is. And if you look at what's happened since Kubernetes was put out there, what it's become kind of de facto and standard in the sense that everyone's rallying around it. Same exact thing happened with TCP was people were trashing it. It is terrible, you know it's not. Of course they were trashed because it was open. So I find that to be very interesting. >>Yeah, that's a good >>analogy. E. Thinks the R C a cable. I used the R C. A cable analogy like the VCRs. When they started, they, every VC had had their own cable, and they will work on Lee with that sort of plan of TV and the R C. A cable came and then now you can put any TV with any VCR, and the VCR industry took off. There's so many examples out there around, uh, standards And how standards can, you know, flair that fire, if you will, on dio for an industry to go sort of wild. And another trend guys I'm seeing is that from the consumer side. And let's talk a little bit on the consuming side. Um, is that the The difference wouldn't be to B and B to C is blood blurred because even the physical products are connected to the end user Like my door lock, the August door lock I didn't just put got get the door lock and forget about that. Like I I value the expedience it gives me or problems that gives me on daily basis. So I'm close to that vendor, right? So So the middle men, uh, middle people are getting removed from from the producer off the technology or the product to the consumer. Even even the sort of big grocery players they have their APs now, uh, how do you buy stuff and how it's delivered and all that stuff that experience matters in that context, I think, um, having, uh, to be able to sell to thes enterprises from the Cloud writer Breuder's. They have to have these case studies or all these sample sort off reference architectures and stuff like that. I think whoever has that mawr pushed that way, they are doing better like that. Amazon is Amazon. Because of that reason, I think they have lot off sort off use cases about on top of them. And they themselves do retail like crazy. Right? So and other things at all s. So I think that's a big trend. >>Great. Great points are being one of things. There's a question in there about from, uh, Yaden. Who says, uh, I like the developer Lead cloud movement, But what is the criticality of the executive audience when educating the marketplace? Um, this comes up a lot in some of my conversations around automation. So automation has been a big wave to automate this automate everything. And then everything is a service has become kind of kind of the the executive suite. Kind of like conversation we need to make everything is a service in our business. You seeing people move to that cloud model. Okay, so the executives think everything is a services business strategy, which it is on some level, but then, when they say Take that hill, do it. Developers. It's not that easy. And this is where a lot of our cube conversations over the past few months have been, especially during the cova with cute virtual. This has come up a lot, Dave this idea, and start being around. It's easy to say everything is a service but will implement it. It's really hard, and I think that's where the developer lead Connection is where the executive have to understand that in order to just say it and do it are two different things. That digital transformation. That's a big part of it. So I think that you're gonna see a lot of education this year around what it means to actually do that and how to implement it. >>I'd like to comment on the as a service and subject. Get your take on it. I mean, I think you're seeing, for instance, with HP Green Lake, Dell's come out with Apex. You know IBM as its utility model. These companies were basically taking a page out of what I what I would call a flawed SAS model. If you look at the SAS players, whether it's salesforce or workday, service now s a P oracle. These models are They're really They're not cloud pricing models. They're they're basically you got to commit to a term one year, two year, three year. We'll give you a discount if you commit to the longer term. But you're locked in on you. You probably pay upfront. Or maybe you pay quarterly. That's not a cloud pricing model. And that's why I mean, they're flawed. You're seeing companies like Data Dog, for example. Snowflake is another one, and they're beginning to price on a consumption basis. And that is, I think, one of the big changes that we're going to see this decade is that true cloud? You know, pay by the drink pricing model and to your point, john toe, actually implement. That is, you're gonna need a whole new layer across your company on it is quite complicated it not even to mention how you compensate salespeople, etcetera. The a p. I s of your product. I mean, it is that, but that is a big sea change that I see coming. Subject your >>thoughts. Yeah, I think like you couldn't see it. And like some things for this big tech exacts are hidden in the plain >>sight, right? >>They don't see it. They they have blind spots, like Look at that. Look at Amazon. They went from Melissa and 200 millisecond building on several s, Right, Right. And then here you are, like you're saying, pay us for the whole year. If you don't use the cloud, you lose it or will pay by month. Poor user and all that stuff like that that those a role models, I think these players will be forced to use that term pricing like poor minute or for a second, poor user. That way, I think the Salesforce moral is hybrid. They're struggling in a way. I think they're trying to bring the platform by doing, you know, acquisition after acquisition to be a platform for other people to build on top off. But they're having a little trouble there because because off there, such pricing and little closeness, if you will. And, uh, again, I'm coming, going, going back to developers like, if you are not appealing to developers who are writing the latest and greatest code and it is open enough, by the way open and open source are two different things that we all know that. So if your platform is not open enough, you will have you know, some problems in closing the deals. >>E. I want to just bring up a question on chat around from Justin didn't fitness. Who says can you touch on the vertical clouds? Has your offering this and great question Great CP announcing Retail cloud inventions IBM Athena Okay, I'm a huge on this point because I think this I'm not saying this for years. Cloud computing is about horizontal scalability and vertical specialization, and that's absolutely clear, and you see all the clouds doing it. The vertical rollouts is where the high fidelity data is, and with machine learning and AI efforts coming out, that's accelerated benefits. There you have tow, have the vertical focus. I think it's super smart that clouds will have some sort of vertical engine, if you will in the clouds and build on top of a control playing. Whether that's data or whatever, this is clearly the winning formula. If you look at all the successful kind of ai implementations, the ones that have access to the most data will get the most value. So, um if you're gonna have a data driven cloud you have tow, have this vertical feeling, Um, in terms of verticals, the data on DSO I think that's super important again, just generally is a strategy. I think Google doing a retail about a super smart because their whole pitches were not Amazon on. Some people say we're not Google, depending on where you look at. So every of these big players, they have dominance in the areas, and that's scarce. Companies and some companies will never go to Amazon for that reason. Or some people never go to Google for other reasons. I know people who are in the ad tech. This is a black and we're not. We're not going to Google. So again, it is what it is. But this idea of vertical specialization relevant in super >>forts, I want to bring to point out to sessions that are going on today on great points. I'm glad you asked that question. One is Alan. As he kicks off at 1 p.m. Eastern time in the transformation track, he's gonna talk a lot about the coming power of ecosystems and and we've talked about this a lot. That that that to compete with Amazon, Google Azure, you've gotta have some kind of specialization and vertical specialization is a good one. But of course, you see in the big Big three also get into that. But so he's talking at one o'clock and then it at 3 36 PM You know this times are strange, but e can explain that later Hillary Hunter is talking about she's the CTO IBM I B M's ah Financial Cloud, which is another really good example of specifying vertical requirements and serving. You know, an audience subject. I think you have some thoughts on this. >>Actually, I lost my thought. E >>think the other piece of that is data. I mean, to the extent that you could build an ecosystem coming back to Alan Nancy's premise around data that >>billions of dollars in >>their day there's billions of dollars and that's the title of the session. But we did the trillion dollar baby post with Jazzy and said Cloud is gonna be a trillion dollars right? >>And and the point of Alan Answer session is he's thinking from an individual firm. Forget the millions that you're gonna save shifting to the cloud on cost. There's billions in ecosystems and operating models. That's >>absolutely the business value. Now going back to my half stack full stack developer, is the business value. I've been talking about this on the clubhouses a lot this past month is for the entrepreneurs out there the the activity in the business value. That's the new the new intellectual property is the business logic, right? So if you could see innovations in how work streams and workflow is gonna be a configured differently, you have now large scale cloud specialization with data, you can move quickly and take territory. That's much different scenario than a decade ago, >>at the point I was trying to make earlier was which I know I remember, is that that having the horizontal sort of features is very important, as compared to having vertical focus. You know, you're you're more healthcare focused like you. You have that sort of needs, if you will, and you and our auto or financials and stuff like that. What Google is trying to do, I think that's it. That's a good thing. Do cook up the reference architectures, but it's a bad thing in a way that you drive drive away some developers who are most of the developers at 80 plus percent, developers are horizontal like you. Look at the look into the psyche of a developer like you move from company to company. And only few developers will say I will stay only in health care, right? So I will only stay in order or something of that, right? So they you have to have these horizontal capabilities which can be applied anywhere on then. On top >>of that, I think that's true. Sorry, but I'll take a little bit different. Take on that. I would say yes, that's true. But remember, remember the old school application developer Someone was just called in Application developer. All they did was develop applications, right? They pick the framework, they did it right? So I think we're going to see more of that is just now mawr of Under the Covers developers. You've got mawr suffer defined networking and software, defined storage servers and cloud kubernetes. And it's kind of like under the hood. But you got your, you know, classic application developer. I think you're gonna see him. A lot of that come back in a way that's like I don't care about anything else. And that's the promise of cloud infrastructure is code. So I think this both. >>Hey, I worked. >>I worked at people solved and and I still today I say into into this context, I say E r P s are the ultimate low code. No code sort of thing is right. And what the problem is, they couldn't evolve. They couldn't make it. Lightweight, right? Eso um I used to write applications with drag and drop, you know, stuff. Right? But But I was miserable as a developer. I didn't Didn't want to be in the applications division off PeopleSoft. I wanted to be on the tools division. There were two divisions in most of these big companies ASAP. Oracle. Uh, like companies that divisions right? One is the cooking up the tools. One is cooking up the applications. The basketball was always gonna go to the tooling. Hey, >>guys, I'm sorry. We're almost out of time. I always wanted to t some of the sections of the day. First of all, we got Holder Mueller coming on at lunch for a power half hour. Um, you'll you'll notice when you go back to the home page. You'll notice that calendar, that linear clock that we talked about that start times are kind of weird like, for instance, an appendix coming on at 1 24. And that's because these air prerecorded assets and rather than having a bunch of dead air, we're just streaming one to the other. So so she's gonna talk about people, process and technology. We got Kathy Southwick, whose uh, Silicon Valley CEO Dan Sheehan was the CEO of Dunkin Brands and and he was actually the c 00 So it's C A CEO connecting the dots to the business. Daniel Dienes is the CEO of you I path. He's coming on a 2:47 p.m. East Coast time one of the hottest companies, probably the fastest growing software company in history. We got a guy from Bain coming on Dave Humphrey, who invested $750 million in Nutanix. He'll explain why and then, ironically, Dheeraj Pandey stew, Minuteman. Our friend interviewed him. That's 3 35. 1 of the sessions are most excited about today is John McD agony at 403 p. M. East Coast time, she's gonna talk about how to fix broken data architectures, really forward thinking stuff. And then that's the So that's the transformation track on the future of cloud track. We start off with the Big Three Milan Thompson Bukovec. At one oclock, she runs a W s storage business. Then I mentioned gig therapy wrath at 1. 30. He runs Azure is analytics. Business is awesome. Paul Dillon then talks about, um, IDs Avery at 1 59. And then our friends to, um, talks about interview Simon Crosby. I think I think that's it. I think we're going on to our next session. All right, so keep it right there. Thanks for watching the Cuban cloud. Uh huh.

>>from around the globe. It's the Cube presenting Cuban cloud brought >>to you by silicon angle. Okay, we're back. Here. Live Cuban Cloud. And this is Dave. Want with my co host, John Ferrier Were all remote. We're getting into the analyst power half hour. Really pleased to have Maribel Lopez here. She's the principal and founder of Lopez Research and Zias Caraballo, who is the principal and founder of ZK research. Guys, great to see you. Let's get into it. How you doing? >>Great. How you been? Good, >>thanks. Really good. John's hanging in there quarantining and, uh, all healthy, So I hope you guys are too. Hey, Mary, But let's start with you. You know, here we are on 2021 you know, just exited one of the strangest years, if not the strangest year of our lives. But looking back in the past decade of cloud and we're looking forward. How do you see that? Where do we come from? Where we at and where we going >>When we obviously started with the whole let's build a public cloud and everything was about public cloud. Uh, then we went thio the notion of private cloud than we had hybrid cloud and multi cloud. So we've done a lot of different clouds right now. And I think where we are today is that there's a healthy recognition on the cloud computing providers that you need to give it to the customers the way they want it, not the way you've decided to build it. So how do you meet them where they are so that they can have a cloud like experience wherever they want their data to be? >>Yes and yes, you've, you know, observed, This is well, in the early days of cloud, you heard a lot of rhetoric. It was private cloud And and then now we're, you know, hearing a lot of multi cloud and so forth. But initially, a lot of the traditional vendors kind of pooh poohed it. They called us analysts. We said we were all cloud crazy, but they seem to have got their religion. >>Well, everything. Everyone's got a definition of cloud, but I actually think we are right in the midst of another transformation of clouds Miracle talked about. We went from, you know, private clouds, which is really hosting the public cloud to multi cloud hybrid cloud. And if you look at the last post that put on Silicon Angle, which was talking about five acquisition of Volterra, I actually think we're in the midst of the transition to what's called distributed Club, where if you look at modernized cloud apps today, they're actually made up of services from different clouds on also distributed edge locations. And that's gonna have a pretty profound impact on the way we build out, because those distributed edges be a telco edge, cellular vagina. Th whatever the services that lived there are much more ephemeral in nature, right? So the way we secure the way we connect changes quite a bit. But I think that the great thing about Cloud is we've seen several several evolutionary changes. So what the definition is and we're going through that now, which is which is pretty cool to think about, right? It's not a static thing. Um, it's, uh, you know, it's a it's an ongoing transition. But I think, uh, you know, we're moving into this distributed Cloudera, which to me is a lot more complex than what we're dealing with in the Palace. >>I'm actually pretty excited about that because I think that this move toe edge and the distribution that you've talked about, it's like we now have processing everywhere. We've got it on devices, we've got it in, cars were moving, the data centers closer and closer to where the action's happening. And I think that's gonna be a huge trend for 2021. Is that distributed that you were talking about a lot of edge discussion? You >>know what? The >>reason we're doing This, too, is we want. It's not just we're moving the data closer to the user, right? And some. If you think you brought up the autonomous vehicle right in the car being an edge, you think of the data that generates right? There's some things such as the decision to stop or not right that should be done in car. I don't wanna transport that data all the way back to Google him back to decide whether I want to stop. You could also use the same data determine whether drivers driving safely for insurance purposes, right? So the same data give me located at the edge or in a centralized cloud for different purposes, and I think that's what you know, kind of cool about this is we're being able to use our data and much different ways. Now. >>You know, it's interesting is it's so complex. It's mind blowing because this is distributed computing. Everyone kind of agrees this is where it is. But if you think about the complexity and I want to get your guys reaction to this because you know some of the like side fringe trend discussions are data sovereignty, misinformation as a vulnerability. Okay, you get the chips now you got gravitas on with Amazon in front. Apple's got their own chips. Intel is gonna do a whole new direction. So you've got tons of computer. And then you mentioned the ephemeral nature. How do you manage those? What's the observe ability look like? They're what's the trust equation? So all these things kind of play into it. It sounds almost mind blowing, just even thinking about it. But how do you guys, this analyst tryto understand where someone's either blowing bullshit or kind of like has the real deal? Because all those things come into play? I mean, you could have a misinformation campaign targeting the car. Let's say Hey, you know that that data is needs to be. This is this is misinformation who's a >>in a lot of ways, this creates almost unprecedented opportunity now for for starts and for companies to transform right. The fundamental tenet of my research has always been share shifts happen when markets transition and we're in the middle of the big one. If the computer resource is we're using, John and the application resource will be using or ephemeral nature than all the things that surrounded the way we secured the way we connect. Those also have to be equal, equally agile, right, So you can't have, you know, you think of a micro services based application being secured with traditional firewalls, right? Just the amount of, or even virtual the way that the length of time it takes to spend those things up is way too long. So in many ways, this distributed cloud change changes everything in I T. And that that includes all of the services in the the infrastructure that we used to secure and connect. And that's a that is a profound change, and you mentioned the observe ability. You're right. That's another thing that the traditional observe ability tools are based on static maps and things and, you know, traditional up, down and we don't. Things go up and down so quickly now that that that those don't make any sense. So I think we are going to see quite a rise in different types of management tools and the way they look at things to be much more. I suppose you know Angela also So we can measure things that currently aren't measurable. >>So you're talking about the entire stack. Really? Changing is really what you're inferring anyway from your commentary. And that would include the programming model as well, wouldn't it? >>Absolutely. Yeah. You know, the thing that is really interesting about where we have been versus where we're going is we spent a lot of time talking about virtual izing hardware and moving that around. And what does that look like? And that, and creating that is more of a software paradigm. And the thing we're talking about now is what is cloud is an operating model look like? What is the manageability of that? What is the security of that? What? You know, we've talked a lot about containers and moving into a different you know, Dev suck ups and all those different trends that we've been talking about, like now we're doing them. So we've only got into the first crank of that. And I think every technology vendor we talked to now has to address how are they going to do a highly distributed management and security landscape? Like, what are they gonna layer on top of that? Because it's not just about Oh, I've taken Iraq of something server storage, compute and virtualized it. I now have to create a new operating model around it. In a way, we're almost redoing what the OS I stack looks like and what the software and solutions are for that. >>So >>it was really Hold on, hold on, hold on their lengthened. Because that side stack that came up earlier today, Mayor. But we're talking about Yeah, we were riffing on the OSC model, but back in the day and we were comparing the S n a definite the, you know, the proprietary protocol stacks that they were out there and someone >>said Amazon's S N a. Is that recall? E think that's what you said? >>No, no. Someone in the chest. That's a comment like Amazon's proprietary meaning, their scale. And I said, Oh, that means there s n a But if you think about it, that's kind of almost that can hang. Hang together. If the kubernetes is like a new connective tissue, is that the TCP pipe moment? Because I think Os I kind of was standardizing at the lower end of the stack Ethernet token ring. You know, the data link layer physical layer and that when you got to the TCP layer and really magic happened right to me, that's when Cisco's happened and everything started happening then and then. It kind of stopped because the application is kinda maintain their peace there. A little history there, but like that's kind of happening now. If you think about it and then you put me a factor in the edge, it just kind of really explodes it. So who's gonna write that software? E >>think you know, Dave, your your dad doesn't change what you build ups. It's already changed in the consumer world, you look atyou, no uber and Waze and things like that. Those absolute already highly decomposed applications that make a P I calls and DNS calls from dozens of different resource is already right. We just haven't really brought that into the enterprise space. There's a number, you know, what kind of you know knew were born in the cloud companies that have that have done that. But they're they're very few and far between today. And John, your point about the connectivity. We do need to think about connectivity at the network layer. Still, obviously, But now we're creating that standardization that standardized connectivity all the way a player seven. So you look at a lot of the, you know, one of the big things that was a PDP. I calls right, you know, from different cloud services. And so we do need to standardize in every layer and then stitch that together. So that does make It does make things a lot more complicated. Now I'm not saying Don't do it because you can do a whole lot more with absolute than you could ever do before. It's just that we kind of cranked up the level of complexity here, and flowered isn't just a single thing anymore, right? That's that. That's what we're talking about here It's a collection of edges and private clouds and public clouds. They all have to be stitched together at every layer in orderto work. >>So I was I was talking a few CEOs earlier in the day. We had we had them on, I was asking them. Okay, So how do you How do you approach this complexity? Do you build that abstraction layer? Do you rely on someone like Microsoft to build that abstraction layer? Doesn't appear that Amazon's gonna do it, you know? Where does that come from? Or is it or is it dozens of abstraction layers? And one of the CEO said, Look, it's on us. We have to figure out, you know, we get this a p I economy, but But you guys were talking about a mawr complicated environment, uh, moving so so fast. Eso if if my enterprise looks like my my iPhone APs. Yes, maybe it's simpler on an individual at basis, but its app creep and my application portfolio grows. Maybe they talk to each other a little bit better. But that level of complexity is something that that that users are gonna have to deal >>with what you thought. So I think quite what Zs was trying to get it and correct me if I'm wrong. Zia's right. We've got to the part where we've broken down what was a traditional application, right? And now we've gotten into a P. I calls, and we have to think about different things. Like we have to think about how we secure those a p I s right. That becomes a new criteria that we're looking at. How do we manage them? How do they have a life cycle? So what was the life cycle of, say, an application is now the life cycle of components and so that's a That's a pretty complex thing. So it's not so much that you're getting app creep, but you're definitely rethinking how you want to design your applications and services and some of those you're gonna do yourself and a lot of them are going to say it's too complicated. I'm just going to go to some kind of SAS cloud offering for that and let it go. But I think that many of the larger companies I speak to are looking for a larger company to help them build some kind of framework to migrate from what they've used with them to what they need tohave going forward. >>Yeah, I think. Where the complexities. John, You asked who who creates the normalization layer? You know, obviously, if you look to the cloud providers A W s does a great job of stitching together all things AWS and Microsoft does a great job of stitching together all things Microsoft right in saying with Google. >>But >>then they don't. But if if I want to do some Microsoft to Amazon or Google Toe Microsoft, you know, connectivity, they don't help so much of that. And that's where the third party vendors that you know aviatrix on the network side will tear of the security side of companies like that. Even Cisco's been doing a lot of work with those companies, and so what we what we don't really have And we probably won't for a while if somebody is gonna stitch everything together at every >>you >>know, at every layer. So Andi and I do think we do get after it. Maribel, I think if you look at the world of consumer APS, we moved to a lot more kind of purpose built almost throwaway apps. They serve a purpose or to use them for a while. Then you stop using them. And in the enterprise space, we really haven't kind of converted to them modeling on the mobile side. But I think that's coming. Well, >>I think with micro APS, right, that that was kind of the issue with micro APS. It's like, Oh, I'm not gonna build a full scale out that's gonna take too long. I'm just gonna create this little workflow, and we're gonna have, like, 200 work flows on someone's phone. And I think we did that. And not everybody did it, though, to your point. So I do think that some people that are a little late to the game might end up in in that app creep. But, hey, listen, this is a fabulous opportunity that just, you know, throw a lot of stuff out and do it differently. What What? I think what I hear people struggling with ah lot is be to get it to work. It typically is something that is more vertically integrated. So are you buying all into a Microsoft all you're buying all into an Amazon and people are starting to get a little fear about doing the full scale buy into any specific platform yet. In absence of that, they can't get anything to work. >>Yeah, So I think again what? What I'm hearing from from practitioners, I'm gonna put a micro serve. And I think I think, uh, Mirabelle, this is what you're implying. I'm gonna put a micro services layer. Oh, my, my. If I can't get rid of them, If I can't get rid of my oracle, you know, workloads. I'm gonna connect them to my modernize them with a layer, and I'm gonna impart build that. I'm gonna, you know, partner to get that done. But that seems to be a a critical path forward. If I don't take that step, gonna be stuck in the path in the past and not be able to move forward. >>Yeah, absolutely. I mean, you do have to bridge to the past. You you aren't gonna throw everything out right away. That's just you can't. You can't drive the bus and take the wheels off that the same time. Maybe one wheel, but not all four of them at the same time. So I think that this this concept of what are the technologies and services that you use to make sure you can keep operational, but that you're not just putting on Lee new workloads into the cloud or new workloads as decomposed APS that you're really starting to think about. What do I want to keep in whatever I want to get rid of many of the companies you speak Thio. They have thousands of applications. So are they going to do this for thousands of applications? Are they gonna take this as an opportunity to streamline? Yeah, >>well, a lot of legacy never goes away, right? And I was how companies make this transition is gonna be interesting because there's no there's no really the fact away I was I was talking to this one company. This is New York Bank, and they've broken their I t division down into modern I t and legacy I t. And so modern. Everything is cloud first. And so imagine me, the CEO of Legacy i e 02 miracles. But what they're doing, if they're driving the old bus >>and >>then they're building a new bus and parallel and eventually, you know, slowly they take seats out of the old bus and they take, you know, the seat and and they eventually start stripping away things. That old bus, >>But >>that old bus is going to keep running for a long time. And so stitching the those different worlds together is where a lot of especially big organizations that really can't commit to everything in the cloud are gonna struggle. But it is a It is a whole new world. And like I said, I think it creates so much opportunity for people. You know, e >>whole bus thing reminds me that movie speed when they drive around 55 miles an hour, just put it out to the airport and just blew up E >>got But you know, we all we all say that things were going to go away. But to Zia's point, you know, nothing goes away. We're still in 2021 talking about mainframes just as an aside, right? So I think we're going to continue tohave some legacy in the network. But the But the issue is ah, lot will change around that, and they're gonna be some people. They're gonna make a lot of money selling little startups that Just do one specific piece of that. You know, we just automation of X. Oh, >>yeah, that's a great vertical thing. This is the This is the distributed network argument, right? If you have a note in the network and you could put a containerized environment around it with some micro services um, connective tissue glue layer, if you will software abstract away some integration points, it's a note on the network. So if in mainframe or whatever, it's just I mean makes the argument right, it's not core. You're not building a platform around the mainframe, but if it's punching out, I bank jobs from IBM kicks or something, you know, whatever, Right? So >>And if those were those workloads probably aren't gonna move anywhere, right, they're not. Is there a point in putting those in the cloud? You could say Just leave them where they are. Put a connection to the past Bridge. >>Remember that bank when you talk about bank guy we interviewed in the off the record after the Cube interviews like, Yeah, I'm still running the mainframe, so I never get rid of. I love it. Run our kicks job. I would never think about moving that thing. >>There was a large, large non US bank who said I buy. I buy the next IBM mainframe sight unseen. Andi, he's got no choice. They just write the check. >>But milliseconds is like millions of dollars of millisecond for him on his back, >>so those aren't going anywhere. But then, but then, but they're not growing right. It's just static. >>No, no, that markets not growing its's, in fact. But you could make a lot of money and monetizing the legacy, right? So there are vendors that will do that. But I do think if you look at the well, we've already seen a pretty big transition here. If you look at the growth in a company like twilio, right, that it obviates the need for a company to rack and stack your own phone system to be able to do, um, you know, calling from mobile lapse or even messaging. Now you just do a P. I calls. Um, you know, it allows in a lot of ways that this new world we live in democratizes development, and so any you know, two people in the garage can start up a company and have a service up and running another time at all, and that creates competitiveness. You know much more competitiveness than we've ever had before, which is good for the entire industry. And, you know, because that keeps the bigger companies on their toes and they're always looking over their shoulder. You know what, the banks you're looking at? The venues and companies like that Brian figure out a way to monetize. So I think what we're, you know well, that old stuff never going away. The new stuff is where the competitive screen competitiveness screen. >>It's interesting. Um IDs Avery. Earlier today, I was talking about no code in loco development, how it's different from the old four g l days where we didn't actually expand the base of developers. Now we are to your point is really is democratizing and, >>well, everybody's a developer. It could be a developer, right? A lot of these tools were written in a way that line of business people create their own APs to point and click interface is, and so the barrier. It reminds me of when, when I started my career, I was a I. I used to code and HTML build websites and then went to five years. People using drag and drop interface is right, so that that kind of job went away because it became so easy to dio. >>Yeah, >>sorry. A >>data e was going to say, I think we're getting to the part. We're just starting to talk about data, right? So, you know, when you think of twilio, that's like a service. It's connecting you to specific data. When you think of Snowflake, you know, there's been all these kinds of companies that have crept up into the landscape to feel like a very specific void. And so now the Now the question is, if it's really all about the data, they're going to be new companies that get built that are just focusing on different aspects of how that data secured, how that data is transferred, how that data. You know what happens to that data, because and and does that shift the balance of power about it being out of like, Oh, I've created these data centers with large recommend stack ums that are virtualized thio. A whole other set of you know this is a big software play. It's all about software. >>Well, we just heard from Jim Octagon e You guys talking earlier about just distributed system. She basically laid down that look. Our data architectures air flawed there monolithic. And data by its very nature is distributed so that she's putting forth the whole new paradigm around distributed decentralized data models, >>which Howie shoe is just talking about. Who's gonna build the visual studio for data, right? So programmatic. Kind of thinking around data >>I didn't >>gathering. We didn't touch on because >>I do think there's >>an opportunity for that for, you know, data governance and data ownership and data transport. But it's also the analytics of it. Most companies don't have the in house, um, you know, data scientists to build on a I algorithms. Right. So you're gonna start seeing, you know, cos pop up to do very specific types of data. I don't know if you saw this morning, um, you know, uniforms bought this company that does, you know, video emotion detection so they could tell on the video whether somebody's paying attention, Not right. And so that's something that it would be eso hard for a company to build that in house. But I think what you're going to see is a rise in these, you know, these types of companies that help with specific types of analytics. And then you drop you pull those in his resource is into your application. And so it's not only the storage and the governance of the data, but also the analytics and the analytics. Frankly, there were a lot of the, uh, differentiation for companies is gonna come from. I know Maribel has written a lot on a I, as have I, and I think that's one of the more exciting areas to look at this year. >>I actually want to rip off your point because I think it's really important because where we left off in 2020 was yes, there was hybrid cloud, but we just started to see the era of the vertical eyes cloud the cloud for something you know, the cloud for finance, the cloud for health care, the telco and edge cloud, right? So when you start doing that, it becomes much more about what is the specialized stream that we're looking at. So what's a specialized analytic stream? What's a specialized security stack stream? Right? So until now, like everything was just trying to get to what I would call horizontal parody where you took the things you had before you replicated them in a new world with, like, some different software, but it was still kind of the same. And now we're saying, OK, let's try Thio. Let's try to move out of everything, just being a generic sort of cloud set of services and being more total cloud services. >>That is the evolution of everything technology, the first movement. Everything doing technology is we try and make the old thing the new thing look like the old thing, right? First PCs was a mainframe emulator. We took our virtual servers and we made them look like physical service, then eventually figure out, Oh, there's a whole bunch of other stuff that I could do then I couldn't do before. And that's the part we're trying to hop into now. Right? Is like, Oh, now that I've gone cloud native, what can I do that I couldn't do before? Right? So we're just we're sort of hitting that inflection point. That's when you're really going to see the growth takeoff. But for whatever reason, and i t. All we ever do is we're trying to replicate the old until we figure out the old didn't really work, and we should do something new. >>Well, let me throw something old and controversial. Controversial old but old old trope out there. Consumerism ation of I t. I mean, if you think about what year was first year you heard that term, was it 15 years ago? 20 years ago. When did that first >>podcast? Yeah, so that was a long time ago >>way. So if you think about it like, it kind of is happening. And what does it mean, right? Come. What does What does that actually mean in today's world Doesn't exist. >>Well, you heard you heard. Like Fred Luddy, whose founder of service now saying that was his dream to bring consumer like experiences to the enterprise will. Well, it didn't really happen. I mean, service not pretty. Pretty complicated compared toa what? We know what we do here, but so it's It's evolving. >>Yeah, I think there's also the enterprise ation of consumer technology that John the companies, you know, you look a zoom. They came to market with a highly consumer facing product, realized it didn't have the security tools, you know, to really be corporate great. And then they had to go invest a bunch of money in that. So, you know, I think that waken swing the pendulum all the way over to the consumer side, but that that kind of failed us, right? So now we're trying to bring it back to center a little bit where we blend the two together. >>Cloud kind of brings that I never looked at that way. That's interesting and surprising of consumer. Yeah, that's >>alright, guys. Hey, we gotta wrap Zs, Maribel. Always a pleasure having you guys on great great insights from the half hour flies by. Thanks so much. We appreciate it. >>Thank >>you guys. >>Alright, keep it right there. Mortgage rate content coming from the Cuban Cloud Day Volonte with John Ferrier and a whole lineup still to come Keep right there.

>>from around the globe. It's the Cube presenting Cuban Cloud brought to you by Silicon Angle. >>Welcome back to the Cubes. Special Presentation on the Future of Cloud. Three years ago, Alan Nance said to me that in order to really take advantage of Cloud and Dr Billions of dollars of value, you have to change the operating model. I've never forgotten that statement have explored it from many angles over the last three years. In fact, it was one of the motivations for me actually running this program for our audience. Of course with me is Alan Nance. He's a change agent. He's led transformations that large organizations, including I N G Bank, Royal, Philips, Barclays Bank and many others. He's also a co founder of Citrus Collab. Alan, great to see you. Thanks for coming on the program. >>Thanks for having me again there. >>All right. So when we were preparing for this interview you shared with me the following you said enterprise, I t often hasn't really tapped the true powers that are available to them to make real connections to take advantage of that opportunity. Connections to the business, That is What >>do >>you mean by that. >>Well, I think, you know, we've been saying for quite a long time that enterprise. It is certainly a big part of our past in technology. But you know, just how much is it going to be in the future on, you know, enterprise, I t has had a difficult time under The pressure's off being a centralized organization with large expanse of large Catholics, while at the same time we see obviously the digital operations growing oftentimes in separate reporting structures and closer to the business on. And what I'm thinking right now is enterprise i t. If it has made this transition to cloud operating models, whether they are proprietary or whether they are public cloud, there's a huge opportunity for enterprise. I t. Thio connect the dots in a way that no other part of the organization can do that. And when they connect those dots working closely with the business, they unleash a huge amount of value that is beyond things like efficiency or things like just just just providing cloud computing to be flexible. It has to be much more about value generation. Andi. I think that a lot of leaders of enterprise I t have not really grasped that, Andi. I think that's the opportunity is sitting right in front of them right now. >>You know what I've seen lately? I wonder if you could. Comment is You know, obviously we always talk about the stove pipes, but you've you've seen, you know, the CEO, >>the chief >>data officer that you just mentioned the chief digital officer, the chief information security officer. They've largely been in their own silos. I'm definitely seeing a move to bring those together. I'm seeing a lot of CDOs and CEO roles come together and even the chief information or the head of security reporting up into that where there's there seems to be as your sort of suggesting just a lot more visibility across the entire organization. Is it Is it an organizational issue? Is it? Ah, is it a mindset? But only if you could comment. >>Well, I would say it zits, two or three different things, but certainly it's an organizational issue. But I think it starts off with a cultural issue. Andi, I think what you're seeing, and if you look at the more progressive companies that you see, I think you are also seeing a new emergence off the enlightened technology leader s O. With all respect to me and my generation, our tenure as the owners off the large enterprise, it is coming to an end. And we grew up trying to master the complexity of the off the silos. As you so definitely pointed out, we were battling this falling technology, trying to get it under control, trying to get the costs down, trying to reduce Catholics. And a lot of that was focused on the partnerships that we had with technology suppliers on DSO. That mindset of being engineers struggling for control. Having your most important part of being a technology company itself that now I think is giving way is giving way to a new generation of technology leaders who haven't grown up with that culture. Onda. Oftentimes what I see is that the new enlightened CEOs are female, and they are coming into the role outside of the regular promotion change. So they're coming to these rolls through finance H R marketing on their bringing. A different focus on the focus is much more about how do we work together to create an amazing experience for our employees and for our customers on an experience that drives value. So I think there's a reset in the culture. And clearly, when you start talking about creating a value chain to improve experience, you're also talking about bringing people together from different multidisciplinary backgrounds to make that happen. >>Well, that's kind of, you know, it makes me think about Amazon's mantra of working backwards. You know, start with the experience and and and a lot of a lot of CEOs that I know would love tow beam or involved in the business. But they're just so busy trying to keep the lights on like you said, trying to manage vendors. And like, you know, I had a discussion the other day, Allen with an individual. We were talking about how you know, you got a shift from a product mindset to a platform mindset. But you know, you've said that that platform thinking you're always ahead of the game platform, thinking it needs to make way for ecosystem thinking, you know, unless you're Internet giant scale business like Amazon or Spotify, you said you're gonna be in a niche market if you really don't tap that ecosystem again. If you could explain what you mean by that. >>I think right now if this movement to experience is fundamental, right? So Joe Pine and Gilmore wrote about the experience economy as far back in 1990. But the things that they predicted then are here now. And so what we're now seeing is that consumers have choice. Employees have choice. I think the pandemic has accelerated that. And so what happens when you, when you when you put an enterprise under that type of external pressure, is that it fragments and even fragment into ways it can fragment dysfunctional E so that every silo tries to go into a a defensive mode protective mode? That's obviously the wrong way to go. But the fragmentation that's exciting is when it fragments into ecosystems that are actually working together to solve an experience problem. And those are not platforms. They're too big, you know, When I was Phillips, I was very enthusiastic about working on this connected health care platform, but I think what I started to realize was it takes too much time. It requires too much investment on you are bringing people to you based on your capability. Where is what the market needs is much more agile than that. So if we look in health care, for instance, and you want to connect patients at home with patient with the doctors in the hospital, in the old model you so I'm gonna build a platform for this. I'm gonna have doctors with a certain competence and they're gonna be connecting into this. And so are the patients in some way. And so are the insurers. I think what you're going to see now is different. We're going to say, Let's get together A small team that understands it's called, For instance, let's get a an insurance provider. Let's get a health care operator. Let's get a healthcare tech company on. Let's pull their data in a way that helps us to create solutions now that that can roll out in 30 60 or 90 days. And the thing that that makes that possible is the move to the public crowd because now there are so many specialized supplier, specialized skill sets available that you can connect to through Amazon through Google, through through azure that that these these things that we usedto I think we're very, very difficult are now much easier. I don't want to minimize the effort, but these things are on the table right now. Thio Revalue. >>So you're also a technologist and I wanna ask you and and everybody always says, it's the technology is easy part. It's the people in the process and, you know, way we can all agree on that. However, sometimes technology could be a blocker. And the example that you just mentioned, I have a couple of takeaways from that. First of all, you know the platform thinking it sounds like it's more command and control, and you're advocating for Let's get the ecosystem who are closest to the problem. To solve those problems, however, they decide and leverage the cloud. So my question is from a technology standpoint, does that echo have system have to be on the same cloud with the state of today's technology? Can it be across clouds can be there pieces on Prem? What's your thinking on that? >>I think I think exactly the opposite. It cannot be monolithic and centralized. It's just not practical because that was that was that would cause you too much time on interoperability and who owns what you see The power behind experience is data. And so the most important technical part of this is dealing with data liquidity. So the data that for instance, um, somebody like Kaiser has or the the Harvard Health Care have or the Philips have that's not going to be put into a central place. But for the ecosystem mobilization, there will be subsets of that data flowing between those parties. So the technical, the heart there is how do we manage data liquidity? How do we manage the security around the data liquidity on How do we also understand that what we're building is going to be ever changing and maybe temporary, because on idea may not work, eh? So you've got this idea that the timeliness is very, very important. The duration is very uncertain. The motor the energy for this is data liquidity data transfer, data sharing. But the vehicle is the combination off. Probably crowd in my mind. >>Somebody said to me, Hey, that data is like water. It'll go. It'll go where it wants to go where it needs to go. You can't try to control it. It's let it go. Uh, now, of course, many organizations, particularly large incumbent organizations there. They have many, many data pipelines. They have many processes, many roles, and they're struggling toe actually kind of inject automation into those pipelines. Maybe that's machine intelligence, uh, really doom or data sharing across that pipeline and and ultimately compress the end and cycle. Time to go from raw data insights that are actionable. What are you seeing there and what's your advice? >>Well, I think the the you make some really good points. But what I hear also a little bit in your observation is you're still observing Enterprises on the end of the focus of the enterprise has been on optimizing the processes within the boundaries of its own system. That's why we have s a P. And that's why we have a sales force and, to some degree, even service. Now it's all been about optimizing how we move data, how we create products and services on. That's not the game. Now that's not an important game. Three important game right now is how do I connect to my employees? How do I connect to my customers in a way that provides them a memorable experience? And the realization is we've seen this already a manufacturing for some years. I can't be allowed things to people. So I have to understand where the first part of data comes in. I have to understand who this person is that I am trying to target. Who is the person that needs this memorable experience on what is that memorable experience gonna look like? And I'm going to need my data. But I'm also going to need the data of other actors in that ecosystem. And then I'm gonna have to build that ecosystem really quickly to take advantage off the system. So this throws a monkey wrench in traditional ideas of standardization. It throws a monkey wrench in the idea that enterprise I t is about efficiency on. But if I may, I just want to come back to the day I because I think we're looking in the wrong places. Things like a I let me give you an example. Today there are 2.2 million people working in call centers around the world. If we imagine that they work in three shifts, that means that any one time there are 700,000 people on the phone to a customer on that customer is calling that company because they're vested. They're calling them with advice. They're calling them with a question. They're calling them with a complaint. It is the most important source off valuable data that any company has. And yet what have we done with that? What we've done with that is we have attacked it with efficiency. So instead of saying these are the most valuable sources of information, let's use a I to to tag the sentiment in the recordings that we make with our most valuable stakeholders on this and analyze them for trends, ideas, things that need to change. We don't do that. What we do is we were going to give every call agent two minutes to get them off the phone. For God's sake, don't ask so many import difficult questions. Don't spend money talking to the customer. Try to make them happy so they get a score and say they hire you at the end of the core and then you're done. So so where the AI and automation needs to come in is not in improving efficiency but in mining value. And the real opportunity with a I Is that Joe Pine says this. If you are able to understand the customer rather than interpret them, that is so valuable to the customer that they will pay money for that. I think that's where the whole focus needs to be in this new teaming of enterprise I t. And that's true business. >>It's a great observations. I think we can all relate to that in your call center example, or you've been in a restaurant. You're trying to turn the tables fast and get you out of there. And that's the last time you ever go to that restaurant and you're you're taking that notion of systems thinking and broadening it to ecosystems thinking. And you've said ecosystems have a better chance of success when they're used to stage an experience for whether it's the employees for the brand and of course, the customer and the partners. >>That's it. That's exactly yet. So every technology leader should be asking themselves what contribution can can my and my organization makes of this movement because the business understands the problem, they don't understand how to solve it, and we've chosen a different dialogues. We've been talking a lot about what cloud could do and the functionality that clown has and the potential that clown has on those aerial good things. But it really comes together now when we work together and we, as the technology group brings in, they know how we know how toe connect quickly through the public cloud. We know how to do that in a secure way. We know how to manage data, liquidity at scale, and we can stand these things up through our, you know, our new learning of agile and devils we can stand. These ecosystems are fairly quickly now. There's still a whole bunch of culture between different businesses that have to work together through the idea that I have to protect my data rather than serve the customer. But once you get past that, there's a whole new conversation enterprise. It you can have that, I think, gives them a new lease of life, new value. And I just think it's a really, really exciting time. Yes, >>so you're seeing the intersection of a lot of different things. You talk about cloud as you know, an enabler for sure, and that's great. We could talk about that, but you've got this what you're referring to before is, you know, maybe you're in a niche market, but you have your marketplace and like you're saying, you can actually use that through an ecosystem to really leave her a much, much broader available market and then vector that into the experience economy. You know, we talk about subscriptions, the AP economy. That really is new thinking, >>yes, and I think what you're seeing here is it zits, not radical. Inasmuch as all of these ideas have been around, some of them have been around since the nineties. But what's radical is the way in which we can now mix and match these technologies to make this happen. That's gone so quickly on, I would argue to you, and I've argued this before. Scale scale is a concept within an organization is dead. It doesn't give you enough value. It gives you enough efficiency, and it gives you a cloud. But it doesn't give you three opportunity to target the niche experiences that you need to do. So. If we start to think off an organization as a a combination off known and unknown potential ecosystems, you start to build a different operating model, a different architectural idea you start to look outside more than you start to look insight. Which is why the cultural change that we were talking about just now goes hand in hand with this because people have to be comfortable thinking in ecosystems that may not yet exist on partnering with people where they bring to the table there, you know, 2030 years of experience in a new and different way. >>Let me make sure I understand that. So you're basically if I understand you're saying that if you're sort of end goal is scale and efficiency at scale, you're you're gonna have a vanilla solution for your customers and your ecosystem. Whereas if you will allow this outside in thinking to come in, you're gonna be able to actually customize those experience experiences and get the value of scale and efficiency. >>Right? So, I mean, Rory Sutherland, who is ah, big finger in the in. The marketing world has always said, ultimately, scale standardization and best practice lead to mediocrity because you are not focused on the most important thing for your employees or your brand, or you're you're focused on the efficiency factors on. They create very little value in fact, we know that they subvert value. So, yes, we need to have a very big mindset change. >>Yeah, You're a top line thinker, Allen. And and always at the forefront. I really appreciate you coming on to the to the Cuban. Participate in this program. Give us the last word. So if you're a change agent, I wanna I'm an organization, and I want to inject this type of change. Where do I >>start? Well, I think it starts by identifying. Are we going to? Is it are we gonna work on the employee experience? Do we feel that we have a model where the employees that are on stage with customers are so important that the focus has to be employees? We go down that route and we look at what happened to the pandemic. What type of experiences are we going to bring to those employees around their ability to have flow in their work, to get returned on energy, to excite the customers? Let's do that. Let's figure out what experience are we driving now? What does that experience need to be if we're the customer side? As I said, let's look ALS. The sources of information that we already have. You know, I know companies to spend hundreds of millions a year trying to figure out what consumers what. And yet if we look in their call centers, you will call up and and they will say to Your call may be recorded for quality purposes and training on this is not true. Less than 10% of those calls that ever listened to on if they are listening to its compliance that's driving that, not the burning desire to better understand the consumer. So if we change that, then we say Okay, so what can we change? What is the experience that we are now able to stage with all we know and with all weaken dio on debts? Start there. Let's start with what is the experience you want to stage? What's the experience landscape look like now? And who do we bring together to make that happen? >>Allen. Fantastic. Having you back in the Cube, it's always a pleasure. And, uh, and thanks so much for participating. >>Thank you, Dave. It's always a pleasure to speak with you. >>Thank you. Everybody, this is Dave Volonte. The Cuban cloud will be right back right after this short break. Stay with

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon angle. The cube on cloud continues. We're here with Anna Pinza, who is the chief development officer and Anna Plan. We've been unpacking the future of Cloud. We've heard from a number of CEOs how they're thinking about Cloud in the coming decade. And first of all, Anna, welcome back to the Cube. Thanks for participating. It's great to see you again. >>It's great to see you, Dave. And I'm so excited to be here with you again, so hopefully we'll be doing this soon. >>I hope in 2021 will be able to be face to face everybody. Oh, no. A lot of respect. You think about the CEO role, something that you're intimately familiar with its unique because she or he has a very wide observation space across the company. You know, where is the GM or a business line manager there, You know, most concerned with their respective business, the CEO, they're gonna worry about the whole enchilada. And we've heard a lot in this program about digital transformation. We've heard a lot, of course, in the past couple of years, a lot of it was lip service, but but digital transformation, it's no longer optional. What's changed, in your view, in the way that businesses air going about it? >>You know, Dave, I mean, from my perspective, it's interesting. And this year in particular has been really telling for us, right? So I think before many companies were thinking about Hey, I wanna be online, I wanna grow my revenues, you know, with with digital I wanna have a presence. But what's happened actually this year with covert in particular, is that it's gone from being kind of a good to have, you know, to really ah, fundamental necessity. We must have it. And so when I talked to CEOs today, they're really thinking about different kinds of things than before, not just going digital, but how do I enable um, my people toe work remotely right? I've got to enable that how doe I bring the agility and the flexibility that I need in our business, especially with these new ways of working right? How do I look at business resiliency? You know, not just from a you know, something happens, and then how do I recover from it? But also how do I help our, You know, our company and our people then actually spring forward and grow from where we are. So it's gone from a a topic that was happening at the CEO, maybe at the business level. But now it's really also a fundamental CEO and board conversation. And so now we're seeing the CEO is having to present two boards. You know, what is our digital transformation? Are our digital strategy. So I wonder what >>you've seen in that regard. I'm interested in what role cloud plays and supporting those digital initiatives. But more specifically, you know, cloud migration came, you know, off the charts in terms of interest because of co vid. But you had those that that were, you know, deep into cloud had a lot of experience of those maybe not as much. Are you seeing any kind of schism in the marketplace where there's maybe a great advantage to those who really had years of experience on may be a disadvantage to those who didn't or is there kind of an equilibrium you're seeing in the market place? How do you see that playing out? >>Yeah. I mean, you know, What I'm seeing is that I think there used to be a spectrum of CEOs and effect, you know, the ones that were kind of a little bit, you know, you know, forward, ahead on the cloud, both on cloud infrastructure as well, Assassin. Right. And what are the services that we have? And then there were some that were really, um, you know, trying to think about what's the security, you know, implications of the cloud. And, you know, is it more expensive? And you know, So there was this spectrum of CEOs and I think now what's happened is there's such a business imperative that I think CEO s air saying, Look, I'm either gonna survive, you know, in this new world with the agility and the flexibility that I need And so cloud, you know, I'm seeing a lot of CEO is really saying Okay, Cloud is not just fashionable, but it z in and a necessity, right? And we must on we must do it. And I think frankly, the c e. O. S that don't embrace the cloud and that level of agility are going to struggle, right? It's a it's really a personal imperative. for a CEO in addition to sort of for the company. So >>a lot of times we talk about, you know, the three dimensions of people, process and technology, and I'm interested in your thoughts on how cloud has affected those traditional structures and the value chains. I mean, you've got some people are really good a text. Some people are really good at people. Some people are really good at process. Has the cloud affected that is, it upended? It changed it in any way. >>Yeah. I mean, let's let's, like, unpack that a little bit. You know, Dave, because if you think about process, I mean, one of the interesting things about the cloud is that And if you think about the cloud as going all the way from, like I as their sort of infrastructure all the way up the stack toe, actually providing business processes embedded, you know, in in a fast service, then from a process perspective and for CEOs, it's really upended how they think about business process reengineering in their companies. Um, if I think even, you know, five years ago, where you would have ah whole organization, that's, you know, focused on business process reengineering You do that? It takes a long time. You know, you get a consultant, maybe to help you, and then you work through that process. If you look at a SAS service like Anna plan today, where we our goal is, for example, toe orchestrate business performance. We were assassin business planning platform. We've incorporated into our platform that business process. Right. So the role of the CEO relative to business process and effect changes Right now, it's about how the leverage, ah, cloud infrastructure, and then how do you enable the customization is on top of that. But generally speaking, that's a lot easier than having to think about re engineering the whole company. Um, if you think about the technology stock, obviously the cloud, uh, embeds a lot of technology, you know, in the cloud. Right. So you have a lot of native services that are available to you. Um, that is awesome from a talent perspective, you know, because before, maybe you need to have, you know, needed to have database experts or, you know, kubernetes experts. And not that we don't need those today. But many of those capabilities come native in the cloud today. So, in effect, how it helps the CEO is to provide sort of this ecosystem of talent kind of embedded in what the cloud provider does. Right? So >>I wondered. So stay on that for a minute. So remember, before Amazon announced a W s and whether 2006 it was CEO said to me, >>Yeah, I'm thinking >>about maybe I don't need to run my own email, right? So because you have to have seen the SAS ification of of of businesses, which to your point, you know, makes things, uh, simpler and that I can focus on other areas and not to worry about, you know, managing infrastructure to support APS. At the same time you've had this proliferation of cloud you mentioned, of course, that you're with Anna Plan. You see, you got work day, you got Salesforce. You've got service now Oracle, APS and and people struggle. Okay, how do I get these things Talking to whether there's that worried about that data layer. So there's this new level of complexity. How do you see that playing out in the next decade? >>Yeah. You know, we used to say that, you know, we sort of, um, shift. What we do at a certain level and now is an organization we start to look at kind of higher value outcomes, right. And so I see that happening. And you're absolutely right. The conversations that I have with customers now are Hey, um, you know, there's things that are enabled by the cloud, and then on top of that, you need a set of a P i s or connectors or ways to get data in and out, you know, in and out of a particular system or ways to link. In our case, we're linking with Salesforce toe, Anna plan, toe workday or other tools, right? And so you start to think more about the business outcome that you want. The CEO needs to be focused on that, um, instead of maybe, uh, sort of the fundamentals of the technology. Those come, you know, those come for you, and then it's really more about the partnership with the business side. Right to say Okay, what is it that you're trying to do and can I enable that through my you know, cloud architectures, the work days, you know, the adobes or or the sales forces of the world. So I think the conversation is changing. And from my perspective, what's really cool about that is, um it brings the CEO Thio, you know, really makes the CEO of business and thought leader a strategic leader, right, Because, uh, the I t shop is not just talking tech, you know, the top shop has toe talk a lot more about the outcome that they're trying to deliver. >>So I mean, in the early days of cloud, I just wanna pick up on what you just said. I mean, a lot of people in I t's saw the cloud is a threat to their livelihood. And e think I'm inferring from your statements that were largely through that dynamic. And the CEO is now really trying to make the cloud platform for transformation and monetization or whatever other organizational goal might be saving lives or better government. Is >>that sort >>of how you see it, that the role has changed to that? >>I know. I mean, I talked to so many companies, and it's still we're still going through that transition, so I don't think we're completely over the hump of, you know, cloud all day everywhere but a same time. Um, I think what the CEO so really focused on these days is really around business, agility and business outcomes for their partners. By the way, that's one of the things. The second thing, especially these days, is around people, you know, collaboration, communication. How do we, you know, facilitate interaction of people, whether inside or outside of the company on DSO? You know, that's, um that's a very different conversation for the CEO. It doesn't mean that we're not still having the basic conversation of how safe is the cloud. What security do you have built into the cloud, Right, Andi? But I think, frankly, Dave, that we've across the chasm where before it used to be. Hey, I'm a lot more secure on Prem and, you know, given the tremendous focus of the cloud providers and says companies have put on security, um, I see many more companies, you know, feeling very at ease and in fact, telling their organizations right, we actually need to switch to the cloud, including large. Um, you know, large companies that have compliance issues, you know, or like large financial companies. Many of those are making that switch as well. Well, >>it's interesting talk about security, but I think it's kind of a two edged sword, right? Because I think a lot of frankly, I think a lot of executives early days used security as a way to sort of kick the can >>down the road. But >>the reality was cloud, you know better. Worse you could make that argument is different. And so, you know, different concerns people. But it's still a the end of the day. Bad security practices Trump, >>you >>know, good security. And so that's what we've seen so many times that shared responsibility model on DSO. People are still >>learning there, so >>so security is almost this beast in and of itself. I'm interested in your thoughts on on the priorities. I mean, >>our >>customers are they streamlining their their tech investments? I mean, the major focus, as you pointed out on Cloud, has been it's a driver of agility and shifting. Resource is as we talked about. But there's this constant cost pressure, you know, the procurement. Looking at the Amazon Bill, Uh, do you see ah lot of the same going forward? Or do you think the value equation is shifting such that there'll be Maybe, you know, I t is less cost pressure is always gonna be cost pressure. I know, but But more value producer, >>I think I think you're right. I mean, I see it and I see it. Over the last six months, I've seen it really accelerate where CEOs are thinking about three things and one is business resiliency. When I talk about business resiliency, I talk about the ability to recover from crap that happens. You know, where you know, whether it's pandemics or, you know, global events and shifts that companies have to accommodate. Right? So that's one thing that I see them thinking about. The second one that we talked about a little bit is just agility. You know, I see them really focused on that. And the cloud enables that. And, you know, the third one in conversations is really speed innovation, because, um, you know, when companies air talking to cloud providers and particularly SAS cos what I see them talking about is Look, I've got this particular need and it would take me, you know, two years to do it with a legacy player because of, you know, I've got to do this on Prem. But you have the fundamentals built in. And I think I could do it with you in three months. So I think, you know, business Resiliency both to grow and toe recover from stuff. Um, agility and innovation are really three fundamental levers that I see for movement, uh, movement to the cloud. Right? Andi, any one of those that these days I mean, it's funny, uh, depending on who you talk Thio. Any one of those can propel a CEO to make a choice to make that choice. And when they have all of that together, um, they have a lot more, um, lift in effect As a CEO, they have a lot more leverage, right in terms of what they could do for their companies. Well, >>let's stay on innovation. I mean innovation. I've said many times in tech, >>you >>know, for decades it came, came from Moore's Law, it seems, seems so nineties to even say that it's true. So what's going to drive innovation in the in the coming years? I'm interested in your perspective on how machine intelligence and a I n m l on cloud, of course, play into that innovation agenda. >>Yeah. I mean, it's it's interesting, You know, I see it a lot in our business with Anna plan. Um, innovation comes from the ability to bring instead of what you do internally and match it with what's available in the external world. Right? And you mentioned it earlier. Data, You know, data is like the new currency. That's that's, like software, you know, eats the world. Now we talk about data, right? And, um and I think what's really going to drive innovation is being able to have access to the world's data once the company builds this digital DNA, You know, this digital foundation and puts, you know and is able to have access to that data, Then you start to make decisions. You know, you start Thio offer services. Um, you start thio, bring intelligence. Um, that wasn't available before, right? And, um, that's a really powerful thing for any company, whether you're doing, you know, forecasting. And you need to sort of bring the world's data. Whether you're a agricultural company, we talking. And in these days, um, innovation comes in the form of speed, you know, being able to just deliver something new to an audience faster. So to me, the cloud enables, You know, all of that the ability Thio bring in data. And then on top of that, I mean, think about all the A i m l innovation that's happening around the world. We we just launched an offer, actually, um, to be able to dio forecasting intelligent forecasting on top of the cloud we partner with with a W s forecast for that, Um, if we didn't have a cloud platform, you know, to do that and instead of a p i s you know, being digital that way really enables us, uh, the opportunity Thio toe match. You know, one plus one equals one, you know, 100. Really? And bringing the power of that to get to companies together to be ableto enable that type of innovation. >>Well, that that that's interesting. It reminds me of my friends. Ed Walsh is the CEO of a startup called Chaos Search. And you use the statement. He said, where we're standing on the shoulders of the giants, you know what you know, trying not trying to recreate it. And I think you know, you got what you just said is the same thing. You're sort of relying on others to build out cloud infrastructure. So there's a totally left field question. When you hear all the talks about breaking up big tech I >>want Is that a >>relevant to you? Because you figured okay, the clouds gonna be there. It's maybe more about search or it's about, you know, Facebook or, you know, Amazon's dominance. Interestingly, Microsoft's really not in those discussions anymore. They were the center of it >>back. No, no. >>But as a head of development for a company, does that even factor into the equation? And you're kind of not worry about that? >>No. I mean, I'll be honest for me personally. What I do is I compartmentalize my world, right. In a sense, I view I view the partnerships and we have partnerships with Google and AWS and Microsoft and others, Right? So, um, I view those as part of a non opportunity to really provide on ecosystem set of solutions right to customers and those air very powerful. I think those partnerships enable companies like ours, like Sasse companies, to innovate faster, right? And so I compartmentalize and I say those things are are wonderful. I don't know why you would want to break up those companies at the same time. Um, you know, part of what you're referring Thio, you know, has to do with, um more the social and the consumer elements of what's going on. But as a business leader, um, I really I really focused on what the power is, particularly in the enterprise. What is it that we can do for global enterprise companies? And at least in my mind, those two things tend to be separate. >>Couple of things, you said they're triggered my mind. One was ecosystems. We've been talking about data. One of our guests on this program, Alan Nance, has been talking about ecosystems and the power of ecosystems. And I definitely see Cloud is a platform to allow data sharing across those those clouds and then to form ecosystems and share data in ways that we really couldn't have, you know, half a decade or even you no longer ago. And that seems to be where ah lot of the innovation is going to occur. Some of the people talk about the flywheel effect, but it's the power of many versus the resource is of, you know, a few. >>And I'm such a big believer in the ecosystem play. And part of that is because, um, frankly, even over the last 20 years, that the skills that are required and the knowledge that required that is required is so specialized. Dave, you know, if you think about, you know, a I m l and all the algorithms that we need to know when the innovation that's happening there. And so I really don't think that there's any one company that can serve a customer alone, right? And if you think about it from a customer perspective, you know they're made up of their business is made up of needs from a lot of different parties that they're putting together, you know, to accommodate their business outcome. And so the only way to play right now in tech is is in a collaborative way in an ecosystem way. I think the mawr that companies like ours worked with other companies on these partnerships. And frankly, by the way, I think in the past, many companies that have made bold announcements and they would say, Oh, you know, I'm partnering with so and so and I've got this great partner, you know, partnership. And then nothing would happen. You know, like it was just a lot of, you know, talk. But I think what's actually happening now and it's enabled by the cloud, is, um, we have much more of a show me culture, right? We can we can actually say. Okay, well, let's say, uh, Anna plan is partnering with Google. Show me. You know, show me what you're actually doing. And I see our customers, um, asking for references of how these ecosystem partnerships air playing. Um, and, uh, because these stories air out there mawr, I think partnerships are actually much more feasible and and really and pragmatic. Yeah. >>Anna, we call those Barney deals, you know, I love you. You love me, would do a press release, and then nothing ever happens. >>That's right. That's right. And I think that Z that's not gonna work. Going forward day, right? People are asking for a lot more transparency. And so when we think about ecosystems, they really want the meat on the bone, right? They don't want just, uh, announcements that don't really help their business move forward. Yeah, >>And you know the other thing to the come back to data. It's always comes back to data, right? Every conversation. But the data that's created out of that ecosystem is gonna throw off, you know, new capabilities and new data products, data services. And that, to me, is a really exciting, you know, new chapter, I think of cloud. >>Yeah, and it's interesting. You know, the conversations I'm having now are are about data and believe it or not, also about metadata, right? Because people are trying to analyze what's happening with the cloud. You know, among cloud providers what our customers doing with the data, right? How are they using data? How often are they accessing data? Um, security. You know, from that perspective, looking at who's accessing? Accessing what? So, um, the data conversation in the metadata conversation are truly enabled by the cloud and their their key. And they weren't that easy to do in a prior, you know, legacy sort of environment. There's >>a great point. I'm glad you brought that up, because legacy, environment, all the all that metadata that data about the data is locked inside of these systems. And if you're gonna go across clouds and you're gonna have it secure and govern. You've gotta have that metadata visibility and a point of control that actually can see that and and can manage it. So thank you for that at that point. And thank you for coming on the on the Cuban participating. The Cuban cloud has been great having you. >>Thank you so much for having me. It's been a pleasure. >>Alright, Keep it right there. Everybody mawr from the Cuban cloud right after this short break.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 >>sponsored by >>Intel and AWS. Yeah, Welcome back to the cubes. Ongoing coverage of aws reinvent virtual the Cuba has gone virtual to. We're gonna talk about machine intelligence, cloud and transformation in healthcare. An industry that is rapidly evolving and reinventing itself to provide better quality care faster and more accurate diagnoses. And this has to be done at lower cost. And with me to talk about This is Dr Taha. Awesome. Who? Who is the director of machine learning at Amazon Web services? Doctor, good to see you again. Thanks for coming on. >>Thank you so much. Good to see Dave. >>Yeah, last time we talked, I think it was a couple of years ago. We remember we were talking about Amazon. Comprehend medical. And, of course, you've been so called so called raising the bar, so to speak, Over the past 24 months, you made some announcements today, including Amazon Health Lake, which we're gonna talk about. Tell us about it. >>Well, we're really excited about eso our customers. Amazon Half Lake, a new hip eligible service for health care providers health insurance companies and pharmaceutical companies to securely store, transform Aquarian, analyze health data in the cloud at petabytes scale, a Amazon health lake uses machine learning models trained to automatically understand context and extract meaningful data from medical data from raw, disparate information such as medications, procedures, Um, and diagnosis. Um Therefore, revolutionizing a process that was traditionally manual Arab prone and highly costly requires a lot of expertise on teams within these organizations. What healthcare Catholic does is it tags and indexes every piece of information on then structure in an open standard. The fire standard, or that's the fast healthcare interoperability resource, is in order to provide a complete view 360 degree view of each patient in a consistent way so you'll be able to curry and share that data securely. It also integrates with other machine learning services and a lot of services that AWS offers, such as Amazon Quicksight or Amazon sage maker. In order to visualize and understand the relationships in the data identify trends, Andi also make predictions. The other great benefit is since the Amazon health lake automatically structures all the health care organizations data into open standard. The fire industry format. The information now can be easily and securely shared between systems. Health systems onda with third party applications. So eso providers, health care providers will will enjoy the ability to collaborate more effectively with each other but also allowing patients and federal access to their medical information. >>I think now, so one of things that people are gonna ask is Okay, wait a minute. Hip eligible Is that like cable ready or HD ready? And but people need to understand that it's a shared responsibility. But you can't come out of the box and be HIPPA compliant there a number of things and processes, uh, that that your customer has to do. Maybe you could explain that a little >>bit. Absolutely. I mean, in practice a little bit. This is a very, very important thing, and and it's something that we really fully baked into the service and how we built Also the service, especially dealing with health care information. First off, AWS, as you know, is vigilant about customers, privacy and security. It is job zero for us. Your data and Health Lake is secure, compliant, and auditable data version is enabled to protect um, the data against any accident collision, for example, and per fire sophistication. If you are to delete one piece of data, it will be version it will be on Lee. Hidden from analysis is a result not believed from the service. So your dad is always encrypted on by using your own customer. Manage key in a keys in a single tenant. Architectures is another added benefit to provide the additional level of protection when the data is access and search for example, every time inquiry a value, for example, someone's glucose level if the data is encrypted and decrypted and and and and so on and so forth. So, additionally, this system in a single tenant architectures so that that way the data, uh, the key. The same key is not shared across multiple customers. So you're saying full ownership and control of your data along with the ability to encrypt, protect move, deleted in alignment with organization, security and policies. Now a little bit about the hip eligibility. It's a term that AWS uses eso for customers storing protected health information or P h. I A. DBS by its business associate agreement on also Business Associate amendment require customers to encrypt data addressed in transit when they're using area services. There are over 100 services today. They're hip eligible, including the Amazon. Health like this is very important, especially for, uh enabling discovered entities and their business associates subject to HIPAA regulations, and is be able to kind of and this shared model between what a the best protection and services and how it can process and store and managed ph I. But there's additional level of compliance is required on the on the customer side, um, about you know, anywhere from physical security thio how each application can be built, which is no different than how you manage it. For example, today in your own that data center, what not? But this is why many cats, growing number of health care providers, um, players as well as I, because professionals are using AWS utility based cloud services today to process, store and transmit pH. I. >>So tell us more about who was gonna benefit from this new capability, what types of organizations and would be some of the outcomes for for for patients, >>absolutely every healthcare provider today, or a payer like a health insurance company or a life. Science companies such as Pharma Company is just trying to solve the problem of organizing instruction their data. Because if you do, you make better sense of this information from better patient support decisions. Design better clinical trials, operate more efficiently, understand population health trends on be able them to share that that security. It's really all starts with making sense of that of that data. And those are the ultimate customers that we're trying to empower with the Amazon Amazon Health Lake. Um, >>well, And of course, there's downstream benefits for the patient. Absolutely. That's ultimately what we're trying to get to. I mean, absolutely. I mean, I set up front. I mean, it's it's everybody you know, feels the pain of high health care costs. A lot of times you're trying to get to see a doctor, and it it takes a long time now, especially with with covitz so and much of this, oftentimes it's even hard to get access to your own data s. So I think you're really trying to attack that problem. Aren't >>you absolutely give you a couple of examples like I mean, today, the most widely used clinical models, uh, in practice to predict. Let's say someone's disease risk lack personalization. Um, it's you and I can be lumped in the same in the same bucket, for example, based on a few attributes that common, UM, data elements or data points, which is problematic also because the resulting models produce are imprecise. However, if you look at an individual's medical records, for example, you know a diabetic type two diabetic patients there, if you look at the entire history and from all this information coming to them, whether it's doctor knows medication dosages, which line of treatment the second line treatment, uh, continuous monitoring of glucose and that sort of thing is over hundreds. You know, there are hundreds of thousands of data points in their entire medical history, but none of this is used today. At the point of care on. You want all this information to be organized, aggregated, structured in a way that you will be able to build even better models easily queried this information, aan den observed the health of the individual in comparison with the rest of the population because at that point you'll be able to make those personalized decisions and then also for patient engagement with the health lake ability to now emit data back on dshea air securely the a p i s that conform to the fire standard. So third party applications can be built also, um, Thio provide the access whether that's for analytics or digital health application, for example, a patient accident, that information all that is very, very, very important. Because ultimately you wanna, um, get at better care of these these populations better. In Roma, clinical trials reduce duplicative tests and waste and health care systems. All that comes when you have your entire information available in a way that structured and normalize on be able to Korean and analyze andan the seamless integration between the health lake and the arrest of the services like Amazon sage maker. You can really start to understand relationships and meaning of the information, build better, better decision support models and predictive models at the individual on a population level. >>Yeah, right. You talked about all this data that's not not really used on. It's because it's not accessible. I presume it's not in in one place that somebody can analyze its not standardized. It's not normalized. Uh, is that >>right, that is the biggest. That is the biggest challenge for every healthcare provider, pair or life science organization today. If you look at this data, it's difficult to work with. Medical health. Data is really different that I siloed spread out across multiple systems, and it's sort of not incompatible formats. If you look at the last decade, I mean, one of the greatest things is we witnessed a great transformation healthcare towards digitization of the record. But your data is scattered across many of these systems anywhere from found your family history, the clinical observation, diagnosis and treatment. When you see the vast majority of that data is contained in unstructured medical records like Dr Notes P. D efs of insurance, um, of laboratory reports or insurance claims and forms with the With With Covad, we've seen in quite a bit of uptake of digital sort of, um uh, delivery of care such as telemedicine and recorded audios and videos, X rays and images, uh, the large propagation of digital health, APS and and digital assistances and on and wearables and as well as these sort of monitors like glucose, monitor or not, data come in all shapes and form and form and start across all these things. It's a huge heavy lift for any health care organization to be able to aggregate normalized stored securely on. Then also be able to kind of analyze this information and structure in a way that zizi to scale. Um uh, with regards, Thio, the kind of problems that you're going after. >>Well, Dr Cox, who We have to leave it there. Thank you so much. I have been saying for years in the Cube. When is it? That machine's gonna be able to make it make better diagnoses than doctors. Maybe that's the wrong question. Maybe it's machines helping doctors make faster and more accurate diagnoses and lowering our costs. Thanks so much for coming. >>Thank you very much. Appreciate it. Thank you. >>Thank you for watching everybody keep it right there. This is Dave Volonte. We'll be back with more coverage of aws reinvent 2020. You virtual right after this short break

>>from around the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of BTC company. We're live today really live TV, which is the heritage of the Cuban. Now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Fribourg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors which develops neutron detective detection systems. Yet you want to know if early if neutrons and radiation or in places where you don't want them, so this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yes. As you said, the Bio Hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers in by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities do their experiments in better ways in ways that they couldn't do before >>in this edition was launched five years ago. It >>was announced at the end of 2016, and we actually started operations in the beginning of 2017, which is when I joined um, so this is our third year. >>And how's how's it going? How does it work? I mean, these things >>take time. It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow from the beginning. I was employee number 12, I think eso When I came in, it was just a nem p off his building and MP labs. And very quickly we had something running about from anything. Eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now, with co vid, um, we've been able to do a lot of very cool work, um, very being of the pandemic In March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project. Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down, we could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the road, 150,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which, at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created a testing system that will serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down, >>right? Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe you describe a little bit more about silver side detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part. Thio Keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by a port border crossing Places like that they can help make sure that people aren't smuggling, shall we say, very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you can do things like but a detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's It's much more than you know, whatever fighting terrorism, it's there's a riel edge, or I kind of i o t application for what you guys do. >>You do both Zito shares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville city schools for about 11 or 12 years. I started their teaching, Um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering. And, um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outside was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building up a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more more students in stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John her stock and integrate Grayson about this is do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or, you know, diverse base and And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career. And sometimes that that funnels kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO. We're trying to push back how we expose students to engineering and to stem fields as early as possible, and we've definitely seen the fruits of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club That eventually is what led our engineering programs that sort of baked into the DNA and also are a big public school. And we have about 50% of the students are under the poverty line, and we should I mean, Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids and or the program and be successful, >>that's phenomenal. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd. And they have my back. And I think in many ways, the products that you build, you know, our similar I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, So there are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do Onda. We also have ah lot of outreach to researchers and scientists trying to help them support the work they're doing, um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication then would have been done previous technologies. Mhm. You know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston. But another one that was held, uh, of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than there would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the forced march to digital. Thanks to cove it I think that's just gonna continue. Thio grow Raphael one. If you could describe the process that you used to better understand diseases and what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um, in a way that foster So the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology how the human body functions and especially how the cells in the human body function on how they're organized to create teachers in the body. Um, and then it has the set of platforms. Um, mind is one of them by engineering that are all technology. Read it. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientists on. We have a genomics platform. That is all about sequencing DNA in our DNA. Um, and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and the little technologies to marry computation on microscope. So, um, the scientists said the agenda and the platforms we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on. I have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O, for example, my team was able to build pretty quickly a machine to automatically purified proteins, and it's being used to purify all these different important proteins in the cove. It virus the SARS cov to virus on Dwyer, sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. So some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, God s o mat. I mean, you gotta be listening to this in thinking about, Okay? Some. Someday your students are gonna be working at organizations like Like like Bio Hub and Silver Side. And you know, a lot of young people that just have I don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than, you know, the financial angles and that z e I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order We nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering is about making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so, um do Yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like Day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining eventually you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line By Jeff Hammond Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. E. I think we're really generally generationally finally, at the point where you know young students and engineering and really you know it passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that, but I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. But very quickly my engineers started loving it. Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed, and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Um, now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes that something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic. Especially now with Kobe, that we have to have all the remote meetings, eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody remembers, what they are, the person left and now nobody knows which version is the right one m s with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home. And they need a virtual private network and all of that mess disappears. I just simply give give a personal account on shape. And then, magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way, that is absolutely fantastic. >>Rafael, what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know, some of the traditional cloud stuff and I'm curious as to how How whether any of those act manifested were they really that you had to manage? What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team? to learn to use the system like it and buy into it because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some serving on site, but that that's kind of an outdated concept, right? So that took a little bit of a mind shift. But very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive like I don't worry about that. Why would I worry about my cat on on shape? Right is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, their concern was the learning curve right is like how is he will be for everybody to and for me to learn it on whether it had all of the features that we needed and there were a few features that I actually discussed with, um uh, Cody at on shape on. They were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah. >>Great. Thank you for that, Phillip. What's your experience been? Maybe you could take us through your journey with on shape? >>Sure. So we've been we've been using on shaped Silver Side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so and we make anything from detectors that would go into backpacks? Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design, have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new. How we congrats modules from things that we already have. Put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing. And I really don't want to design in any other platform after after getting on Lee a little bit familiar with it. >>You know, it's funny, right? I will have the speed of technology progression. I was explaining to some young guns the other day how e used to have a daytime er and that was my life. And if I lost that day, timer, I was dead. And I don't know how we weigh existed without, you know, Google Maps. Eso did we get anywhere? I don't know, but, uh, but so So, Matt, you know, it's interesting to think about, um, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month It's through the roof in. But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of k 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that that was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um, and so one of my dreams and it was always just a crazy dream. And I was the way I would always pitcher in my school system and say someday I'm gonna have a kid on a school issued chromebook in subsidized housing on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and, you know, march in, um, you said the forced march the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing. Cad March 14th. Those kids were at home on their school shoot chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of the cat. And there's so much about it, E >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer. I mean, maybe insulting to the engineers in the room, but but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software. And so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud >>Philip or Rafael anything. Your dad, >>I think I mean yeah, that that that combination of cloud based cat and then three D printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think there's a dream for kids Thio to be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino and all of these electronic things that live. Kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip Way >>had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development and support world right ahead, which was cool, but also a That's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based. It's an important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see See what your students are gonna be doing, uh, in there home classrooms on their chromebooks now and what they do. Building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because yeah, I think that project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on. And I think he will give the kids a much better flavor What engineering is really about. Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept, and they are there. But I think the most important thing is just that. Hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform and I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in a modern era. And so that's, you know, it is the Google docks. And so the fact that collaboration and version ing and link sharing is, and, like, platform agnostic abilities the fact that that seems to be just built into the nature of the thing so far, that's super exciting as far as things that it to go from there, Um, I don't know. >>Other than price, >>you can't say I >>can't say lower price. >>Yeah, so far on a PTC s that worked with us. Really well, so I'm not complaining. There. You there? >>Yeah. Yeah. No Gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Um, something that was cool. They just integrated Cem markup capability In the last release that took, we were doing that anyway, but we were doing it outside of on shapes, and now we get to streamline our workflow and put it in the CAD system where we're making those changes anyway, when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you. >>I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with comics necessities that regenerating the document takes a little longer than I would like to. It's not a serious issue, but anyway, I'm being spoiled, >>you know. That's good. I've been doing this a long time and I like toe Ask that question of practitioners and to me, it it's a signal like when you're nit picking and that you're struggling to knit. Pick that to me is a sign of a successful product. And And I wonder, I don't know, uh, have the deep dive into the architecture, But are things like alternative processors? You're seeing them hit the market in a big way. Uh, you know, maybe a helping address the challenge, But I'm gonna ask you the big, chewy question now, then would maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics. Obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good can be applied to some of the the problems that that you all are passionate about? Big question. But who wants toe start >>not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics education is the case If you wanna if you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think stem is key to that. I mean, all of the, ah lot of the well being that we have today and then industrialized countries, thanks to science and technology, right, improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything they had? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody doing ableto pull together instead of pulling, pulling separately and to be able to spur the idea is onwards. So that's where I think the education side is really exciting. What Matt is doing and and it just kind of collaboration in general when we could do provide tools to help people do good work? Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings places in Africa, Southeast Asia, South America so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shaped and is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them. Andi, that's amazing. Right? To have somebody you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine. Right? Because, um, you know, they have a three d printer. You can you just give them the design and say, like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also so super important, I think, for any of these efforts to improve, um, some of the hardest part was in the world from climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, that point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. Uh, the answer is education and public policy. That really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we can. If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. What can you tell me? >>Um, absolutely. Like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can, to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope to look at a sample from a patient that's very powerful, and I we don't do this. But I have read quite a bit about how certain places air, using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off. A person would have never thought off, but that are incredibly light ink earlier strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular, >>yet another, uh, advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at or like Raphael said. I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is aws re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know, Amazon has sage maker Google's got, you know, embedded you no ML and big query. Certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software products by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these are the anomalies you need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that air going to result in, uh in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans, air biased and humans build models, so models are inherently biased. But then software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. You're welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back