>>When Oracle acquired my SQL via the Sun acquisition, nobody really thought the company would put much effort into the platform preferring to focus all the wood behind its leading Oracle database, Arrow pun intended. But two years ago, Oracle surprised many folks by announcing my SQL Heatwave a new database as a service with a massively parallel hybrid Columbia in Mary Mary architecture that brings together transactional and analytic data in a single platform. Welcome to our latest database, power panel on the cube. My name is Dave Ante, and today we're gonna discuss Oracle's MySQL Heat Wave with a who's who of cloud database industry analysts. Holgar Mueller is with Constellation Research. Mark Stammer is the Dragon Slayer and Wikibon contributor. And Ron Westfall is with Fu Chim Research. Gentlemen, welcome back to the Cube. Always a pleasure to have you on. Thanks for having us. Great to be here. >>So we've had a number of of deep dive interviews on the Cube with Nip and Aggarwal. You guys know him? He's a senior vice president of MySQL, Heatwave Development at Oracle. I think you just saw him at Oracle Cloud World and he's come on to describe this is gonna, I'll call it a shock and awe feature additions to to heatwave. You know, the company's clearly putting r and d into the platform and I think at at cloud world we saw like the fifth major release since 2020 when they first announced MySQL heat wave. So just listing a few, they, they got, they taken, brought in analytics machine learning, they got autopilot for machine learning, which is automation onto the basic o l TP functionality of the database. And it's been interesting to watch Oracle's converge database strategy. We've contrasted that amongst ourselves. Love to get your thoughts on Amazon's get the right tool for the right job approach. >>Are they gonna have to change that? You know, Amazon's got the specialized databases, it's just, you know, the both companies are doing well. It just shows there are a lot of ways to, to skin a cat cuz you see some traction in the market in, in both approaches. So today we're gonna focus on the latest heat wave announcements and we're gonna talk about multi-cloud with a native MySQL heat wave implementation, which is available on aws MySQL heat wave for Azure via the Oracle Microsoft interconnect. This kind of cool hybrid action that they got going. Sometimes we call it super cloud. And then we're gonna dive into my SQL Heatwave Lake house, which allows users to process and query data across MyQ databases as heatwave databases, as well as object stores. So, and then we've got, heatwave has been announced on AWS and, and, and Azure, they're available now and Lake House I believe is in beta and I think it's coming out the second half of next year. So again, all of our guests are fresh off of Oracle Cloud world in Las Vegas. So they got the latest scoop. Guys, I'm done talking. Let's get into it. Mark, maybe you could start us off, what's your opinion of my SQL Heatwaves competitive position? When you think about what AWS is doing, you know, Google is, you know, we heard Google Cloud next recently, we heard about all their data innovations. You got, obviously Azure's got a big portfolio, snowflakes doing well in the market. What's your take? >>Well, first let's look at it from the point of view that AWS is the market leader in cloud and cloud services. They own somewhere between 30 to 50% depending on who you read of the market. And then you have Azure as number two and after that it falls off. There's gcp, Google Cloud platform, which is further way down the list and then Oracle and IBM and Alibaba. So when you look at AWS and you and Azure saying, hey, these are the market leaders in the cloud, then you start looking at it and saying, if I am going to provide a service that competes with the service they have, if I can make it available in their cloud, it means that I can be more competitive. And if I'm compelling and compelling means at least twice the performance or functionality or both at half the price, I should be able to gain market share. >>And that's what Oracle's done. They've taken a superior product in my SQL heat wave, which is faster, lower cost does more for a lot less at the end of the day and they make it available to the users of those clouds. You avoid this little thing called egress fees, you avoid the issue of having to migrate from one cloud to another and suddenly you have a very compelling offer. So I look at what Oracle's doing with MyQ and it feels like, I'm gonna use a word term, a flanking maneuver to their competition. They're offering a better service on their platforms. >>All right, so thank you for that. Holger, we've seen this sort of cadence, I sort of referenced it up front a little bit and they sat on MySQL for a decade, then all of a sudden we see this rush of announcements. Why did it take so long? And and more importantly is Oracle, are they developing the right features that cloud database customers are looking for in your view? >>Yeah, great question, but first of all, in your interview you said it's the edit analytics, right? Analytics is kind of like a marketing buzzword. Reports can be analytics, right? The interesting thing, which they did, the first thing they, they, they crossed the chasm between OTP and all up, right? In the same database, right? So major engineering feed very much what customers want and it's all about creating Bellevue for customers, which, which I think is the part why they go into the multi-cloud and why they add these capabilities. And they certainly with the AI capabilities, it's kind of like getting it into an autonomous field, self-driving field now with the lake cost capabilities and meeting customers where they are, like Mark has talked about the e risk costs in the cloud. So that that's a significant advantage, creating value for customers and that's what at the end of the day matters. >>And I believe strongly that long term it's gonna be ones who create better value for customers who will get more of their money From that perspective, why then take them so long? I think it's a great question. I think largely he mentioned the gentleman Nial, it's largely to who leads a product. I used to build products too, so maybe I'm a little fooling myself here, but that made the difference in my view, right? So since he's been charged, he's been building things faster than the rest of the competition, than my SQL space, which in hindsight we thought was a hot and smoking innovation phase. It kind of like was a little self complacent when it comes to the traditional borders of where, where people think, where things are separated between OTP and ola or as an example of adjacent support, right? Structured documents, whereas unstructured documents or databases and all of that has been collapsed and brought together for building a more powerful database for customers. >>So I mean it's certainly, you know, when, when Oracle talks about the competitors, you know, the competitors are in the, I always say they're, if the Oracle talks about you and knows you're doing well, so they talk a lot about aws, talk a little bit about Snowflake, you know, sort of Google, they have partnerships with Azure, but, but in, so I'm presuming that the response in MySQL heatwave was really in, in response to what they were seeing from those big competitors. But then you had Maria DB coming out, you know, the day that that Oracle acquired Sun and, and launching and going after the MySQL base. So it's, I'm, I'm interested and we'll talk about this later and what you guys think AWS and Google and Azure and Snowflake and how they're gonna respond. But, but before I do that, Ron, I want to ask you, you, you, you can get, you know, pretty technical and you've probably seen the benchmarks. >>I know you have Oracle makes a big deal out of it, publishes its benchmarks, makes some transparent on on GI GitHub. Larry Ellison talked about this in his keynote at Cloud World. What are the benchmarks show in general? I mean, when you, when you're new to the market, you gotta have a story like Mark was saying, you gotta be two x you know, the performance at half the cost or you better be or you're not gonna get any market share. So, and, and you know, oftentimes companies don't publish market benchmarks when they're leading. They do it when they, they need to gain share. So what do you make of the benchmarks? Have their, any results that were surprising to you? Have, you know, they been challenged by the competitors. Is it just a bunch of kind of desperate bench marketing to make some noise in the market or you know, are they real? What's your view? >>Well, from my perspective, I think they have the validity. And to your point, I believe that when it comes to competitor responses, that has not really happened. Nobody has like pulled down the information that's on GitHub and said, Oh, here are our price performance results. And they counter oracles. In fact, I think part of the reason why that hasn't happened is that there's the risk if Oracle's coming out and saying, Hey, we can deliver 17 times better query performance using our capabilities versus say, Snowflake when it comes to, you know, the Lakehouse platform and Snowflake turns around and says it's actually only 15 times better during performance, that's not exactly an effective maneuver. And so I think this is really to oracle's credit and I think it's refreshing because these differentiators are significant. We're not talking, you know, like 1.2% differences. We're talking 17 fold differences, we're talking six fold differences depending on, you know, where the spotlight is being shined and so forth. >>And so I think this is actually something that is actually too good to believe initially at first blush. If I'm a cloud database decision maker, I really have to prioritize this. I really would know, pay a lot more attention to this. And that's why I posed the question to Oracle and others like, okay, if these differentiators are so significant, why isn't the needle moving a bit more? And it's for, you know, some of the usual reasons. One is really deep discounting coming from, you know, the other players that's really kind of, you know, marketing 1 0 1, this is something you need to do when there's a real competitive threat to keep, you know, a customer in your own customer base. Plus there is the usual fear and uncertainty about moving from one platform to another. But I think, you know, the traction, the momentum is, is shifting an Oracle's favor. I think we saw that in the Q1 efforts, for example, where Oracle cloud grew 44% and that it generated, you know, 4.8 billion and revenue if I recall correctly. And so, so all these are demonstrating that's Oracle is making, I think many of the right moves, publishing these figures for anybody to look at from their own perspective is something that is, I think, good for the market and I think it's just gonna continue to pay dividends for Oracle down the horizon as you know, competition intens plots. So if I were in, >>Dave, can I, Dave, can I interject something and, and what Ron just said there? Yeah, please go ahead. A couple things here, one discounting, which is a common practice when you have a real threat, as Ron pointed out, isn't going to help much in this situation simply because you can't discount to the point where you improve your performance and the performance is a huge differentiator. You may be able to get your price down, but the problem that most of them have is they don't have an integrated product service. They don't have an integrated O L T P O L A P M L N data lake. Even if you cut out two of them, they don't have any of them integrated. They have multiple services that are required separate integration and that can't be overcome with discounting. And the, they, you have to pay for each one of these. And oh, by the way, as you grow, the discounts go away. So that's a, it's a minor important detail. >>So, so that's a TCO question mark, right? And I know you look at this a lot, if I had that kind of price performance advantage, I would be pounding tco, especially if I need two separate databases to do the job. That one can do, that's gonna be, the TCO numbers are gonna be off the chart or maybe down the chart, which you want. Have you looked at this and how does it compare with, you know, the big cloud guys, for example, >>I've looked at it in depth, in fact, I'm working on another TCO on this arena, but you can find it on Wiki bod in which I compared TCO for MySEQ Heat wave versus Aurora plus Redshift plus ML plus Blue. I've compared it against gcps services, Azure services, Snowflake with other services. And there's just no comparison. The, the TCO differences are huge. More importantly, thefor, the, the TCO per performance is huge. We're talking in some cases multiple orders of magnitude, but at least an order of magnitude difference. So discounting isn't gonna help you much at the end of the day, it's only going to lower your cost a little, but it doesn't improve the automation, it doesn't improve the performance, it doesn't improve the time to insight, it doesn't improve all those things that you want out of a database or multiple databases because you >>Can't discount yourself to a higher value proposition. >>So what about, I wonder ho if you could chime in on the developer angle. You, you followed that, that market. How do these innovations from heatwave, I think you used the term developer velocity. I've heard you used that before. Yeah, I mean, look, Oracle owns Java, okay, so it, it's, you know, most popular, you know, programming language in the world, blah, blah blah. But it does it have the, the minds and hearts of, of developers and does, where does heatwave fit into that equation? >>I think heatwave is gaining quickly mindshare on the developer side, right? It's not the traditional no sequel database which grew up, there's a traditional mistrust of oracles to developers to what was happening to open source when gets acquired. Like in the case of Oracle versus Java and where my sql, right? And, but we know it's not a good competitive strategy to, to bank on Oracle screwing up because it hasn't worked not on Java known my sequel, right? And for developers, it's, once you get to know a technology product and you can do more, it becomes kind of like a Swiss army knife and you can build more use case, you can build more powerful applications. That's super, super important because you don't have to get certified in multiple databases. You, you are fast at getting things done, you achieve fire, develop velocity, and the managers are happy because they don't have to license more things, send you to more trainings, have more risk of something not being delivered, right? >>So it's really the, we see the suite where this best of breed play happening here, which in general was happening before already with Oracle's flagship database. Whereas those Amazon as an example, right? And now the interesting thing is every step away Oracle was always a one database company that can be only one and they're now generally talking about heat web and that two database company with different market spaces, but same value proposition of integrating more things very, very quickly to have a universal database that I call, they call the converge database for all the needs of an enterprise to run certain application use cases. And that's what's attractive to developers. >>It's, it's ironic isn't it? I mean I, you know, the rumor was the TK Thomas Curian left Oracle cuz he wanted to put Oracle database on other clouds and other places. And maybe that was the rift. Maybe there was, I'm sure there was other things, but, but Oracle clearly is now trying to expand its Tam Ron with, with heatwave into aws, into Azure. How do you think Oracle's gonna do, you were at a cloud world, what was the sentiment from customers and the independent analyst? Is this just Oracle trying to screw with the competition, create a little diversion? Or is this, you know, serious business for Oracle? What do you think? >>No, I think it has lakes. I think it's definitely, again, attriting to Oracle's overall ability to differentiate not only my SQL heat wave, but its overall portfolio. And I think the fact that they do have the alliance with the Azure in place, that this is definitely demonstrating their commitment to meeting the multi-cloud needs of its customers as well as what we pointed to in terms of the fact that they're now offering, you know, MySQL capabilities within AWS natively and that it can now perform AWS's own offering. And I think this is all demonstrating that Oracle is, you know, not letting up, they're not resting on its laurels. That's clearly we are living in a multi-cloud world, so why not just make it more easy for customers to be able to use cloud databases according to their own specific, specific needs. And I think, you know, to holder's point, I think that definitely lines with being able to bring on more application developers to leverage these capabilities. >>I think one important announcement that's related to all this was the JSON relational duality capabilities where now it's a lot easier for application developers to use a language that they're very familiar with a JS O and not have to worry about going into relational databases to store their J S O N application coding. So this is, I think an example of the innovation that's enhancing the overall Oracle portfolio and certainly all the work with machine learning is definitely paying dividends as well. And as a result, I see Oracle continue to make these inroads that we pointed to. But I agree with Mark, you know, the short term discounting is just a stall tag. This is not denying the fact that Oracle is being able to not only deliver price performance differentiators that are dramatic, but also meeting a wide range of needs for customers out there that aren't just limited device performance consideration. >>Being able to support multi-cloud according to customer needs. Being able to reach out to the application developer community and address a very specific challenge that has plagued them for many years now. So bring it all together. Yeah, I see this as just enabling Oracles who ring true with customers. That the customers that were there were basically all of them, even though not all of them are going to be saying the same things, they're all basically saying positive feedback. And likewise, I think the analyst community is seeing this. It's always refreshing to be able to talk to customers directly and at Oracle cloud there was a litany of them and so this is just a difference maker as well as being able to talk to strategic partners. The nvidia, I think partnerships also testament to Oracle's ongoing ability to, you know, make the ecosystem more user friendly for the customers out there. >>Yeah, it's interesting when you get these all in one tools, you know, the Swiss Army knife, you expect that it's not able to be best of breed. That's the kind of surprising thing that I'm hearing about, about heatwave. I want to, I want to talk about Lake House because when I think of Lake House, I think data bricks, and to my knowledge data bricks hasn't been in the sites of Oracle yet. Maybe they're next, but, but Oracle claims that MySQL, heatwave, Lakehouse is a breakthrough in terms of capacity and performance. Mark, what are your thoughts on that? Can you double click on, on Lakehouse Oracle's claims for things like query performance and data loading? What does it mean for the market? Is Oracle really leading in, in the lake house competitive landscape? What are your thoughts? >>Well, but name in the game is what are the problems you're solving for the customer? More importantly, are those problems urgent or important? If they're urgent, customers wanna solve 'em. Now if they're important, they might get around to them. So you look at what they're doing with Lake House or previous to that machine learning or previous to that automation or previous to that O L A with O ltp and they're merging all this capability together. If you look at Snowflake or data bricks, they're tacking one problem. You look at MyQ heat wave, they're tacking multiple problems. So when you say, yeah, their queries are much better against the lake house in combination with other analytics in combination with O ltp and the fact that there are no ETLs. So you're getting all this done in real time. So it's, it's doing the query cross, cross everything in real time. >>You're solving multiple user and developer problems, you're increasing their ability to get insight faster, you're having shorter response times. So yeah, they really are solving urgent problems for customers. And by putting it where the customer lives, this is the brilliance of actually being multicloud. And I know I'm backing up here a second, but by making it work in AWS and Azure where people already live, where they already have applications, what they're saying is, we're bringing it to you. You don't have to come to us to get these, these benefits, this value overall, I think it's a brilliant strategy. I give Nip and Argo wallet a huge, huge kudos for what he's doing there. So yes, what they're doing with the lake house is going to put notice on data bricks and Snowflake and everyone else for that matter. Well >>Those are guys that whole ago you, you and I have talked about this. Those are, those are the guys that are doing sort of the best of breed. You know, they're really focused and they, you know, tend to do well at least out of the gate. Now you got Oracle's converged philosophy, obviously with Oracle database. We've seen that now it's kicking in gear with, with heatwave, you know, this whole thing of sweets versus best of breed. I mean the long term, you know, customers tend to migrate towards suite, but the new shiny toy tends to get the growth. How do you think this is gonna play out in cloud database? >>Well, it's the forever never ending story, right? And in software right suite, whereas best of breed and so far in the long run suites have always won, right? So, and sometimes they struggle again because the inherent problem of sweets is you build something larger, it has more complexity and that means your cycles to get everything working together to integrate the test that roll it out, certify whatever it is, takes you longer, right? And that's not the case. It's a fascinating part of what the effort around my SQL heat wave is that the team is out executing the previous best of breed data, bringing us something together. Now if they can maintain that pace, that's something to to, to be seen. But it, the strategy, like what Mark was saying, bring the software to the data is of course interesting and unique and totally an Oracle issue in the past, right? >>Yeah. But it had to be in your database on oci. And but at, that's an interesting part. The interesting thing on the Lake health side is, right, there's three key benefits of a lakehouse. The first one is better reporting analytics, bring more rich information together, like make the, the, the case for silicon angle, right? We want to see engagements for this video, we want to know what's happening. That's a mixed transactional video media use case, right? Typical Lakehouse use case. The next one is to build more rich applications, transactional applications which have video and these elements in there, which are the engaging one. And the third one, and that's where I'm a little critical and concerned, is it's really the base platform for artificial intelligence, right? To run deep learning to run things automatically because they have all the data in one place can create in one way. >>And that's where Oracle, I know that Ron talked about Invidia for a moment, but that's where Oracle doesn't have the strongest best story. Nonetheless, the two other main use cases of the lake house are very strong, very well only concern is four 50 terabyte sounds long. It's an arbitrary limitation. Yeah, sounds as big. So for the start, and it's the first word, they can make that bigger. You don't want your lake house to be limited and the terabyte sizes or any even petabyte size because you want to have the certainty. I can put everything in there that I think it might be relevant without knowing what questions to ask and query those questions. >>Yeah. And you know, in the early days of no schema on right, it just became a mess. But now technology has evolved to allow us to actually get more value out of that data. Data lake. Data swamp is, you know, not much more, more, more, more logical. But, and I want to get in, in a moment, I want to come back to how you think the competitors are gonna respond. Are they gonna have to sort of do a more of a converged approach? AWS in particular? But before I do, Ron, I want to ask you a question about autopilot because I heard Larry Ellison's keynote and he was talking about how, you know, most security issues are human errors with autonomy and autonomous database and things like autopilot. We take care of that. It's like autonomous vehicles, they're gonna be safer. And I went, well maybe, maybe someday. So Oracle really tries to emphasize this, that every time you see an announcement from Oracle, they talk about new, you know, autonomous capabilities. It, how legit is it? Do people care? What about, you know, what's new for heatwave Lakehouse? How much of a differentiator, Ron, do you really think autopilot is in this cloud database space? >>Yeah, I think it will definitely enhance the overall proposition. I don't think people are gonna buy, you know, lake house exclusively cause of autopilot capabilities, but when they look at the overall picture, I think it will be an added capability bonus to Oracle's benefit. And yeah, I think it's kind of one of these age old questions, how much do you automate and what is the bounce to strike? And I think we all understand with the automatic car, autonomous car analogy that there are limitations to being able to use that. However, I think it's a tool that basically every organization out there needs to at least have or at least evaluate because it goes to the point of it helps with ease of use, it helps make automation more balanced in terms of, you know, being able to test, all right, let's automate this process and see if it works well, then we can go on and switch on on autopilot for other processes. >>And then, you know, that allows, for example, the specialists to spend more time on business use cases versus, you know, manual maintenance of, of the cloud database and so forth. So I think that actually is a, a legitimate value proposition. I think it's just gonna be a case by case basis. Some organizations are gonna be more aggressive with putting automation throughout their processes throughout their organization. Others are gonna be more cautious. But it's gonna be, again, something that will help the overall Oracle proposition. And something that I think will be used with caution by many organizations, but other organizations are gonna like, hey, great, this is something that is really answering a real problem. And that is just easing the use of these databases, but also being able to better handle the automation capabilities and benefits that come with it without having, you know, a major screwup happened and the process of transitioning to more automated capabilities. >>Now, I didn't attend cloud world, it's just too many red eyes, you know, recently, so I passed. But one of the things I like to do at those events is talk to customers, you know, in the spirit of the truth, you know, they, you know, you'd have the hallway, you know, track and to talk to customers and they say, Hey, you know, here's the good, the bad and the ugly. So did you guys, did you talk to any customers my SQL Heatwave customers at, at cloud world? And and what did you learn? I don't know, Mark, did you, did you have any luck and, and having some, some private conversations? >>Yeah, I had quite a few private conversations. The one thing before I get to that, I want disagree with one point Ron made, I do believe there are customers out there buying the heat wave service, the MySEQ heat wave server service because of autopilot. Because autopilot is really revolutionary in many ways in the sense for the MySEQ developer in that it, it auto provisions, it auto parallel loads, IT auto data places it auto shape predictions. It can tell you what machine learning models are going to tell you, gonna give you your best results. And, and candidly, I've yet to meet a DBA who didn't wanna give up pedantic tasks that are pain in the kahoo, which they'd rather not do and if it's long as it was done right for them. So yes, I do think people are buying it because of autopilot and that's based on some of the conversations I had with customers at Oracle Cloud World. >>In fact, it was like, yeah, that's great, yeah, we get fantastic performance, but this really makes my life easier and I've yet to meet a DBA who didn't want to make their life easier. And it does. So yeah, I've talked to a few of them. They were excited. I asked them if they ran into any bugs, were there any difficulties in moving to it? And the answer was no. In both cases, it's interesting to note, my sequel is the most popular database on the planet. Well, some will argue that it's neck and neck with SQL Server, but if you add in Mariah DB and ProCon db, which are forks of MySQL, then yeah, by far and away it's the most popular. And as a result of that, everybody for the most part has typically a my sequel database somewhere in their organization. So this is a brilliant situation for anybody going after MyQ, but especially for heat wave. And the customers I talk to love it. I didn't find anybody complaining about it. And >>What about the migration? We talked about TCO earlier. Did your t does your TCO analysis include the migration cost or do you kind of conveniently leave that out or what? >>Well, when you look at migration costs, there are different kinds of migration costs. By the way, the worst job in the data center is the data migration manager. Forget it, no other job is as bad as that one. You get no attaboys for doing it. Right? And then when you screw up, oh boy. So in real terms, anything that can limit data migration is a good thing. And when you look at Data Lake, that limits data migration. So if you're already a MySEQ user, this is a pure MySQL as far as you're concerned. It's just a, a simple transition from one to the other. You may wanna make sure nothing broke and every you, all your tables are correct and your schema's, okay, but it's all the same. So it's a simple migration. So it's pretty much a non-event, right? When you migrate data from an O LTP to an O L A P, that's an ETL and that's gonna take time. >>But you don't have to do that with my SQL heat wave. So that's gone when you start talking about machine learning, again, you may have an etl, you may not, depending on the circumstances, but again, with my SQL heat wave, you don't, and you don't have duplicate storage, you don't have to copy it from one storage container to another to be able to be used in a different database, which by the way, ultimately adds much more cost than just the other service. So yeah, I looked at the migration and again, the users I talked to said it was a non-event. It was literally moving from one physical machine to another. If they had a new version of MySEQ running on something else and just wanted to migrate it over or just hook it up or just connect it to the data, it worked just fine. >>Okay, so every day it sounds like you guys feel, and we've certainly heard this, my colleague David Foyer, the semi-retired David Foyer was always very high on heatwave. So I think you knows got some real legitimacy here coming from a standing start, but I wanna talk about the competition, how they're likely to respond. I mean, if your AWS and you got heatwave is now in your cloud, so there's some good aspects of that. The database guys might not like that, but the infrastructure guys probably love it. Hey, more ways to sell, you know, EC two and graviton, but you're gonna, the database guys in AWS are gonna respond. They're gonna say, Hey, we got Redshift, we got aqua. What's your thoughts on, on not only how that's gonna resonate with customers, but I'm interested in what you guys think will a, I never say never about aws, you know, and are they gonna try to build, in your view a converged Oola and o LTP database? You know, Snowflake is taking an ecosystem approach. They've added in transactional capabilities to the portfolio so they're not standing still. What do you guys see in the competitive landscape in that regard going forward? Maybe Holger, you could start us off and anybody else who wants to can chime in, >>Happy to, you mentioned Snowflake last, we'll start there. I think Snowflake is imitating that strategy, right? That building out original data warehouse and the clouds tasking project to really proposition to have other data available there because AI is relevant for everybody. Ultimately people keep data in the cloud for ultimately running ai. So you see the same suite kind of like level strategy, it's gonna be a little harder because of the original positioning. How much would people know that you're doing other stuff? And I just, as a former developer manager of developers, I just don't see the speed at the moment happening at Snowflake to become really competitive to Oracle. On the flip side, putting my Oracle hat on for a moment back to you, Mark and Iran, right? What could Oracle still add? Because the, the big big things, right? The traditional chasms in the database world, they have built everything, right? >>So I, I really scratched my hat and gave Nipon a hard time at Cloud world say like, what could you be building? Destiny was very conservative. Let's get the Lakehouse thing done, it's gonna spring next year, right? And the AWS is really hard because AWS value proposition is these small innovation teams, right? That they build two pizza teams, which can be fit by two pizzas, not large teams, right? And you need suites to large teams to build these suites with lots of functionalities to make sure they work together. They're consistent, they have the same UX on the administration side, they can consume the same way, they have the same API registry, can't even stop going where the synergy comes to play over suite. So, so it's gonna be really, really hard for them to change that. But AWS super pragmatic. They're always by themselves that they'll listen to customers if they learn from customers suite as a proposition. I would not be surprised if AWS trying to bring things closer together, being morely together. >>Yeah. Well how about, can we talk about multicloud if, if, again, Oracle is very on on Oracle as you said before, but let's look forward, you know, half a year or a year. What do you think about Oracle's moves in, in multicloud in terms of what kind of penetration they're gonna have in the marketplace? You saw a lot of presentations at at cloud world, you know, we've looked pretty closely at the, the Microsoft Azure deal. I think that's really interesting. I've, I've called it a little bit of early days of a super cloud. What impact do you think this is gonna have on, on the marketplace? But, but both. And think about it within Oracle's customer base, I have no doubt they'll do great there. But what about beyond its existing install base? What do you guys think? >>Ryan, do you wanna jump on that? Go ahead. Go ahead Ryan. No, no, no, >>That's an excellent point. I think it aligns with what we've been talking about in terms of Lakehouse. I think Lake House will enable Oracle to pull more customers, more bicycle customers onto the Oracle platforms. And I think we're seeing all the signs pointing toward Oracle being able to make more inroads into the overall market. And that includes garnishing customers from the leaders in, in other words, because they are, you know, coming in as a innovator, a an alternative to, you know, the AWS proposition, the Google cloud proposition that they have less to lose and there's a result they can really drive the multi-cloud messaging to resonate with not only their existing customers, but also to be able to, to that question, Dave's posing actually garnish customers onto their platform. And, and that includes naturally my sequel but also OCI and so forth. So that's how I'm seeing this playing out. I think, you know, again, Oracle's reporting is indicating that, and I think what we saw, Oracle Cloud world is definitely validating the idea that Oracle can make more waves in the overall market in this regard. >>You know, I, I've floated this idea of Super cloud, it's kind of tongue in cheek, but, but there, I think there is some merit to it in terms of building on top of hyperscale infrastructure and abstracting some of the, that complexity. And one of the things that I'm most interested in is industry clouds and an Oracle acquisition of Cerner. I was struck by Larry Ellison's keynote, it was like, I don't know, an hour and a half and an hour and 15 minutes was focused on healthcare transformation. Well, >>So vertical, >>Right? And so, yeah, so you got Oracle's, you know, got some industry chops and you, and then you think about what they're building with, with not only oci, but then you got, you know, MyQ, you can now run in dedicated regions. You got ADB on on Exadata cloud to customer, you can put that OnPrem in in your data center and you look at what the other hyperscalers are, are doing. I I say other hyperscalers, I've always said Oracle's not really a hyperscaler, but they got a cloud so they're in the game. But you can't get, you know, big query OnPrem, you look at outposts, it's very limited in terms of, you know, the database support and again, that that will will evolve. But now you got Oracle's got, they announced Alloy, we can white label their cloud. So I'm interested in what you guys think about these moves, especially the industry cloud. We see, you know, Walmart is doing sort of their own cloud. You got Goldman Sachs doing a cloud. Do you, you guys, what do you think about that and what role does Oracle play? Any thoughts? >>Yeah, let me lemme jump on that for a moment. Now, especially with the MyQ, by making that available in multiple clouds, what they're doing is this follows the philosophy they've had the past with doing cloud, a customer taking the application and the data and putting it where the customer lives. If it's on premise, it's on premise. If it's in the cloud, it's in the cloud. By making the mice equal heat wave, essentially a plug compatible with any other mice equal as far as your, your database is concern and then giving you that integration with O L A P and ML and Data Lake and everything else, then what you've got is a compelling offering. You're making it easier for the customer to use. So I look the difference between MyQ and the Oracle database, MyQ is going to capture market more market share for them. >>You're not gonna find a lot of new users for the Oracle debate database. Yeah, there are always gonna be new users, don't get me wrong, but it's not gonna be a huge growth. Whereas my SQL heatwave is probably gonna be a major growth engine for Oracle going forward. Not just in their own cloud, but in AWS and in Azure and on premise over time that eventually it'll get there. It's not there now, but it will, they're doing the right thing on that basis. They're taking the services and when you talk about multicloud and making them available where the customer wants them, not forcing them to go where you want them, if that makes sense. And as far as where they're going in the future, I think they're gonna take a page outta what they've done with the Oracle database. They'll add things like JSON and XML and time series and spatial over time they'll make it a, a complete converged database like they did with the Oracle database. The difference being Oracle database will scale bigger and will have more transactions and be somewhat faster. And my SQL will be, for anyone who's not on the Oracle database, they're, they're not stupid, that's for sure. >>They've done Jason already. Right. But I give you that they could add graph and time series, right. Since eat with, Right, Right. Yeah, that's something absolutely right. That's, that's >>A sort of a logical move, right? >>Right. But that's, that's some kid ourselves, right? I mean has worked in Oracle's favor, right? 10 x 20 x, the amount of r and d, which is in the MyQ space, has been poured at trying to snatch workloads away from Oracle by starting with IBM 30 years ago, 20 years ago, Microsoft and, and, and, and didn't work, right? Database applications are extremely sticky when they run, you don't want to touch SIM and grow them, right? So that doesn't mean that heat phase is not an attractive offering, but it will be net new things, right? And what works in my SQL heat wave heat phases favor a little bit is it's not the massive enterprise applications which have like we the nails like, like you might be only running 30% or Oracle, but the connections and the interfaces into that is, is like 70, 80% of your enterprise. >>You take it out and it's like the spaghetti ball where you say, ah, no I really don't, don't want to do all that. Right? You don't, don't have that massive part with the equals heat phase sequel kind of like database which are more smaller tactical in comparison, but still I, I don't see them taking so much share. They will be growing because of a attractive value proposition quickly on the, the multi-cloud, right? I think it's not really multi-cloud. If you give people the chance to run your offering on different clouds, right? You can run it there. The multi-cloud advantages when the Uber offering comes out, which allows you to do things across those installations, right? I can migrate data, I can create data across something like Google has done with B query Omni, I can run predictive models or even make iron models in different place and distribute them, right? And Oracle is paving the road for that, but being available on these clouds. But the multi-cloud capability of database which knows I'm running on different clouds that is still yet to be built there. >>Yeah. And >>That the problem with >>That, that's the super cloud concept that I flowed and I I've always said kinda snowflake with a single global instance is sort of, you know, headed in that direction and maybe has a league. What's the issue with that mark? >>Yeah, the problem with the, with that version, the multi-cloud is clouds to charge egress fees. As long as they charge egress fees to move data between clouds, it's gonna make it very difficult to do a real multi-cloud implementation. Even Snowflake, which runs multi-cloud, has to pass out on the egress fees of their customer when data moves between clouds. And that's really expensive. I mean there, there is one customer I talked to who is beta testing for them, the MySQL heatwave and aws. The only reason they didn't want to do that until it was running on AWS is the egress fees were so great to move it to OCI that they couldn't afford it. Yeah. Egress fees are the big issue but, >>But Mark the, the point might be you might wanna root query and only get the results set back, right was much more tinier, which been the answer before for low latency between the class A problem, which we sometimes still have but mostly don't have. Right? And I think in general this with fees coming down based on the Oracle general E with fee move and it's very hard to justify those, right? But, but it's, it's not about moving data as a multi-cloud high value use case. It's about doing intelligent things with that data, right? Putting into other places, replicating it, what I'm saying the same thing what you said before, running remote queries on that, analyzing it, running AI on it, running AI models on that. That's the interesting thing. Cross administered in the same way. Taking things out, making sure compliance happens. Making sure when Ron says I don't want to be American anymore, I want to be in the European cloud that is gets migrated, right? So tho those are the interesting value use case which are really, really hard for enterprise to program hand by hand by developers and they would love to have out of the box and that's yet the innovation to come to, we have to come to see. But the first step to get there is that your software runs in multiple clouds and that's what Oracle's doing so well with my SQL >>Guys. Amazing. >>Go ahead. Yeah. >>Yeah. >>For example, >>Amazing amount of data knowledge and, and brain power in this market. Guys, I really want to thank you for coming on to the cube. Ron Holger. Mark, always a pleasure to have you on. Really appreciate your time. >>Well all the last names we're very happy for Romanic last and moderator. Thanks Dave for moderating us. All right, >>We'll see. We'll see you guys around. Safe travels to all and thank you for watching this power panel, The Truth About My SQL Heat Wave on the cube. Your leader in enterprise and emerging tech coverage.

>>Hello everyone Welcome to the cubes coverage of cubic on cloud native come here in person in L A 2021. I'm john ferrier, host of the Cuban Dave Nicholson host cloud host for the cube and of course former host of the cube steve minutemen. Now at red hat stew, we do our normal keynote reviews. We had to have you come back first while hazard and red hat >>john it's phenomenal. Great to see you nice to have Dave be on the program here too. It's been awesome. So yeah, a year and a day since I joined Red hat and uh, I do miss you guys always enjoyed doing the interviews in the cube. But you know, we're still in the community and still interacting lots, >>but we love you too. And Davis, your new replacement and covering the cloud angles. He's gonna bring little stew mo jokes of the interview but still, we've always done the wrap up has always been our favorite interviews to do an analysis of the keynote because let's face it, that's where all the action is. Of course we bring the commentary, but this year it's important because it's the first time we've had an event in two years too. So a lot of people, you know, aren't saying this on camera a lot, but they're kind of nervous. They're worried they're weirded out. We're back in person again. What do I feel? I haven't seen people, I've been working with people online. This is the top story. >>Yeah, john I thought they did a really good job in the keynote this morning. Normally, I mean this community in general is good with inclusion. Part of that inclusion is hey, what are you comfortable with if your remote? We still love you and it's okay. And if you're here in person, you might see there's wrist bands of green, yellow, red as in like, hey, you okay with a handshake. You want to do there or stay the f away from me because I'm not really that comfortable yet being here and it's whatever you're comfortable with. That's okay. >>I think the inclusion and the whole respect for the individual code of conduct, C N C. F and limits Foundation has been on the front end of all those trends. I love how they're taking it to a whole nother level. David, I want to get your take because now with multi cloud, we heard the same message over and over again that hey, open winds, okay. Open winds and still changing fast. What's your take? >>Open absolutely wins. It's uh, it's the present. It's the future. I know in some of the conversations we've had with folks looking back over the last seven years, a lot of things have changed. Um, whenever I think of open source anything, I go back to the foundations of Lennox and I remember a time when you had to reboot a Linux server to re scan a scuzzy bus to add a new storage device and we all sort of put our penguin hats on and kind of ignored that for a while. And uh, and, and as things are developed, we keep coming into these new situations. Multi cluster management was a big, big point of conversation in the keynote today. It's fascinating when you start thinking about something that was once sort of a back room science experiment. Absolutely. It's the center of the enterprise now from a software >>from an open tour standpoint security has been one of those front and center things. One of the day, zero events that got a lot of buzz coming at the beginning of the week was secure supply chain. So with the Solar Wind act going in there, you know, we remember cloud, wait, can I trust it with the security? Open source right now. Open source and security go together. Open source and the security in the cloud all go together. So you know that that wave of open source, obviously one of the things that brought me to red hat, I'd had a couple of decades, you know, working within the enterprise and open source and that that adoption curve which went through a few bumps in the road over time and it took time. But today, I mean open sources have given this show in this ecosystem are such proof >>points of a couple things. I noticed one, I want to do a shout out for the folks who put a nice tribute for dan Kaminsky who has passed away and we miss him. We saw on the Cube 2019, I believe he's on the Cube that year with Adam on big influence, but the inclusiveness do and the community is changing. I think security has changed a lot and I want to get your guys take on this. Security has forced a lot of things happen faster data, open data. Okay. And kubernetes to get hardened faster stew. I know your team's working on it. We know what Azure and amazon is working on it. What do you guys think about how security's been forcing the advances in kubernetes and making that stable? >>Yeah. So john security, you know, is job one, it is everyone's responsibility. We talk about it from a container and kubernetes standpoint. We think we have a relatively good handle on what's happening in the kubernetes space red hat, we made an acquisition earlier this year of stack rocks, which was one of the leading kubernetes native security pieces. But you know, john we know security isn't just a moat anymore in a wall that you put up every single piece. You need to think about it. Um, I've got a person from the stack rocks acquisition actually on my team now and have told him like hey, you need to cross train all of us. We need to understand this more from a marketing standpoint, we need to talk about it from a developer standpoint. We need to have consideration of it. It's no longer, hey, it works okay on my machine. Come on, It needs to go to production. We all know this shift left is something we've been talking about for many years. So yes, security, security, security, we cannot overemphasize how important is um, you know, when it comes to cooper, I think, you know, were relatively mature, we're crossing the chasm, the adoption numbers are there, so it's not an impediment anymore. >>It's totally next level. I don't agree with this too. David, get your thoughts on this whole adoption um, roadmap that put it together, one of the working groups that we interviewed has got that kind of navigate, kinda like trailheads for salesforce, but that speaks to the adoption by mainstream enterprises, not the hard core, >>you know, >>us devops guys, but like it goes into mainstream main main street enterprise had I. T. Department and security groups there, like we got a program faster. How do you see the cloud guys in this ecosystem competing and making that go faster. >>So it's been interesting over the last decade or more often, technology has been ahead of people's comfort level with that technology for obvious reasons, it's not just something went wrong, it's something went wrong. I lost my job. Really, really bad things happened. So we tend to be conservative. Rightfully so in the sometimes there are these seminal moments where a shift happens go back sort of analogous go back to a time when people's main concern with VM ware was how can I get support from Microsoft and all of a sudden it went from that within weeks to how can I deploy this in my enterprise very, very quickly. And I'm fascinated by this concept of locking down the supply chain of code, uh sort of analogous to https, secure, http. It's the idea of making sure that these blocks of code are validated and secure as they get implemented. You mentioned, you mentioned things like cluster and pad's security and infrastructure security. >>Well, David, you brought up a really good point. So get off is the instance creation of that. How can I have my infrastructure as code? How can I make sure that I don't have drift? It's because I could just, it'll live and get hub and therefore it's version controlled. If I try to do something, it will validate that it's there and keep me on version because we know john we talked about it for years on the cube, we've gone beyond human scale if I don't build automation into it, if I don't have the guard rails in place because humans will mess things up so we need to make sure that we have the processes and the automation in place and kubernetes was built for that automation at its core, putting in, we've seen get up the Argosy, D was only went graduated, you know, the one dato was supported as coupon europe. Earlier this year, we already had a number of our customers deploying it using it. Talking publicly >>about it too. I want to get the kid apps angle and that's a good call out there and, and mainly because when we were on the cute, when you work, you post with with us, we were always cheerleading for Cuban. It we love because we've been here every single coupon. We were one saying this is gonna be big trust us and it is, it happens to so, but now we've been kind of, we don't have to sell it anymore. We don't, I mean not that we're selling it, but like we don't have to be a proponent of something we knew was going to happen, it happened. You're now work for a vendor red hat you talk to customers. What is that next level conversation look like now that they know it's real, they have to do it. How is the tops and then modern applications development, changing. What are your observations? Can you share with us from a redhead perspective as someone who's talking to customers, you know, what does real look like? >>Yeah. So get off is a great example of that. So, you know, certain of our government agencies that we work with, you know, obviously very secured about, you know, we want zero trust who do we put in charge of things. So if they can have, you know that that source of truth and know that that is maintained and lockdown and not await some admin is gonna mess something up on us either maliciously or oops, by accident or anything in between. That's why they were pushing that adoption of that kind of technology. So absolutely they, for the most part john they don't want to have to think about the infrastructure piece anymore. What if developers want the old past days was I want to be able to, you know, write once deploy anywhere, live anywhere, containers helps that a little bit. We even have in the container space. Now you can, you can use a service deployment model with Okay. Natives, the big open source project that, you know, VM ware ourselves are working on google's involved in it. So, you know, having us be able to focus on the business and not, you know, running the plumbing anymore. >>That's exactly, that's exactly, that's what we're so psyched for. Okay guys, let's wrap this up and and review the keynote day will start with you. What do you think of the keynote? What were the highlights? What do you take away from the taste keynote? >>So you touched on a couple of things, uh inclusion from all sorts of different angles. Really impressive. This sort of easing back into the world of being face to face. I think they're doing a fantastic job at that. The thing that struck me was something I mentioned earlier. Um moving into multi cluster management in a way that really speaks to enterprise deployments and the complexity of enterprise deployments moving forward? It's not just, it's not just, I'm a developer, I'm using resources in the cloud. I'm doing things this way, the rest of the enterprises doing it a legacy way. It's really an acknowledgement that these things are coming together increasingly. That's what really struck me >>to do. What's your takeaway from the end? >>So there's been a discussion in the industry, you know, what do the next million cloud customers look like we've crossed the chasm on kubernetes. One of the things they announced the keynote is they have a new associate level certification because I tell you before the keynote, I stopped by the breakfast area, saturday table, talk to a couple people. One guy was like, hey, I'm been on amazon for a bunch of years, but I'm a kubernetes newbie, I'm here to learn about that. It's not the same person that five years ago was like, I'm gonna grab all these projects and pull them down from getting, build my stack and you know, have a platform team to manage it from a red hat standpoint, we're delivering our biggest growth areas in cloud services where hey, I've got an SRE team, they can manage all that because can you do it? Sure you got people maybe you'll hire him, but wouldn't you rather have them work on, you know, that security initiative or that new application or some of these pieces, you know, what can you shift to your vendor? What can you offload from your team because we know the only constant is that things are gonna there's gonna be gonna be new pieces and I don't want to have to look at, oh there's another 20 new projects and how does that fit? Can I have a partner or consultant in sc that can help me integrate that into my environment when it makes sense for me because otherwise, oh my God, cloud, So much innovation. How do I grasp what I want? >>Great stuff guys, I would just say my summary is that okay? I'm excited this community has broken through the pandemic and survived and thrived people were working together during the pandemic. It's like a V. I. P. Event here. So that my keynote epiphany was this is like the who's who some big players are here. I saw Bill Vaz from amazon on the on the ground floor on monday night, He's number two at a W. S. I saw some top Vcs here. Microsoft IBM red hat the whole way tracks back. Whole track is back and it's a hybrid event. So I think we're here for the long haul with hybrid events where you can see a lot more in person, V. I. P. Like vibe people are doing deals. It feels alive too and it's all open. So it's all cool. And again, the team at C. N. C. F. They do an exceptional job of inclusion and making people feel safe and cool. So, great job. Thanks for coming on. I appreciate it. Good stuff. Okay. The keynote review from the cube Stupid Man shot for Dave Nicholson. Thanks for watching >>mm mm mm.

>>from the bellagio Hotel >>in Las Vegas. >>It's the >>cube covering >>Ui Path forward. >>Four brought to >>you by Ui Path. >>Welcome back to Las Vegas. The cube is here. We've been here for two days covering Ui Path Forward for lisa martin here with David Monty. We've talked about automation and many industries. Now this segment is going to focus on automation and healthcare. We've got two guests joining us Jim Petrosea Cto of Blue Cross, Blue Shield and Gadget. Dhaliwal. The global C. I. O. Industry lead at you. I pass guys welcome to the program. Thank you. So let's start unpacking from the CTO level and the ceo level the agenda for automation. Jim let's start with you. What does that look like >>for us. It's actually pretty strategic and part of as we think about digital and what digital transformation means, it actually plays a pretty key role. Um There are a lot of processes that can be very manual within a big organization like Blue cross and Blue shield and to be able to streamline that and take away kind of what I would call the mundane work. Right? The the you know, going through a spreadsheet and then typing it into the screen, there are a lot of processes like that that are legacy. But what if you could take that away um and actually create a better work experience for the people that work there right? And and focus on higher value type uh type things and it's really key. And it really It goes down to our our business folks right? There are a lot of things we can drive with automation. We started a program um in 2019. Um that's been quite successful. We now have 250 box, we measure what we call annualized efficiency gains. So how much efficiency are we getting by these bots? So the bots are doing um this repetitive work that people would do. Um And what we're finding is, you know, we've got about $11 million in any wise efficiency gain through the process and we're just getting started. Um But we're all we're not stopping there too though, we're enabling citizen developers. So we're saying, hey business, if you want to automate, you know, parts of your job, we're gonna help you do that. So we've got about 60 people that were training. Um We run bad Ethan's where they come together and they actually create bots uh And it's really really creating some some impact and buzz in our business >>anywhere from your lens, where does automation fit within the C. I. O. S. Agenda? And how do you work together in unison with the C. T. O. To help roll this out across the enterprise? >>Yeah, no, definitely. And in fact as a part of introduction, I can actually share that. How I'm wearing a Ceo had within your path since I'm just joining join path and I'm actually now helping a client ceos in their automation strategy but I was a deputy ceo in my prior role at L. A. County where actually I ran the automation strategy. So if we look at from our organization perspective B complex as L. A County which is such a Federated organization. From a Ceo perspective, the way we look at the strategy is it's always driven by the business goals of the city or a county and we typically drive into three different areas. One is how we can transform our operational processes so that we can save the tax dollars. It's all about doing more with the less dollars. And then second is about how we can transform our residents experience because end of the day it is all about how we can improve the quality of life for our residents. So we've got 10 million people for L. A. County, the largest populous county in us. So it was an uphill task to serve that such a diverse population need and that the third area is about how to transform the new business models because as we are moving away from a government centric approach to the residents centric approach, you really need to come up with a new digital solutions. And Ceo is in the center of all these three elements when you look at it. So it's a very appear to us to keep keep improving your efficiency and then at a time keep adding the new digital solutions and that's where automation strategy is kind of a horizontal strategy which enables all these components. So what I hear from >>that is alignment with the business. Yeah. Right. Change management. Absolutely. That's like really fundamental and then see IOS this this agent of transformation uh you can see or she has a horizontal purview across the organization now now jim the cto role is the automation at blue cross blue shield lead by you or you there to make sure the technology plugs into your enterprise architecture. What's your shoulder? >>You know? Uh my my role is really to drive uh what I'll call technology enabled business change. Right. So I actually uh started our our automation journey uh at hc sc and I did that by partnering with our business. Um There was actually a lot of buzz around automation and there were actually some small pockets of it, none of it was enterprise scale. Um Right. And we really wanted to go big in this and and working with the business sponsors, they saw value in it. Um and we've you know, we've generated um a lot of uh efficiency, better quality of work because of it but but I very closely had a partner with our business, we have a committee that is lead of business folks that I facilitate. So I view my role as an enabler, um we have to communicate the change management pieces is huge. Uh the education just having a common vernacular on what is automation mean, Right, because everybody interpreted it differently um and then being able to do it at an enterprise scale is quite challenging. Um You know, I I really enjoyed um one of the key notes, I don't know if you had a chance to see shankar by Duncan from the hidden brain, right? But he talked a lot about the brain aspect and how do you get people to change? And and that's a large part of it. There's a lot about technology, but there's really a lot about being a change agent um and and really working very closely with your business, >>how does one measure? I'm hearing a lot time saved. Our saved. How does one measure that and quantify the dollar impact, which by the way, I'm on record as saying the soft dollars are way bigger. And but when you're talking to the, you know, the bottom line CFO and it's all about, you know, the cash flow, whatever is, how do you measure that? >>I can take it. So we, what we do is as we define these use cases right? We we go through an actual structure product process where we we gather them. Um we then rate them and we actually prioritize them based on those that are going to have the greatest impact. Um and we can tell based on, you know, what is the manual effort today. So we understand there are X number of people that do this X number of days and we think this body can take that some load off of them. Right? Um So we we go in with the business case. Um And then the Ui Path platform actually allows us to measure well, how much is that pot running? Right. So we can actually sit there and say, well we wanted that thing to run 10 hours a day and it did and it's generated this kind of efficiency because otherwise the human would have had to do that work. >>So the business case is kind of redeploying >>human. It really is is really maximizing human capital and make and and you know really using because the bots do repetitive stuff really well. They don't do higher level thinking and and we don't view it as replacing people, we view it as augmenting and actually making them more efficient and more effective at what, how do you get the dollars out of that? Well, a couple of ways. Right. And so one of the things we've we've done is we we create and measure the efficiency our business users and financed by the way is one of our bigger ones. And the CFO is one of the sponsors of the program, um can decide how to reinvest it in a lot of cases it is actually cost avoidance as we grow, literally being able to grow without adding staff. I mean that's very measurable. Um in some cases it is actually taking, you know cost out um in in certain cases, but a lot of times that's just through attrition, right? You don't back fill positions, you let it happen naturally. Um and and then there's just things that happen to your business that you have to respond to give you a great example, state of texas, um passes what's the equivalent of the no surprise attack. But they did it there before the federal government did it. Um but it requires a lot of processes to be put in place, because now you have providers and payers having to deal with disputes, right? It actually generates a boatload of work. And we thought there might be, you know, 5000 of these in the first year, where there were 21,000 in the first year. And so far this year we're doubling that amount, right. We were able to use automation to respond to that without having to add a bunch of stuff. If we had to add staff for that, it would have literally been, you know, maybe hundreds of people, right? And but now, you know, there's, you can clearly put a value on it and it's millions of dollars a year, that we would have otherwise had to expect. >>The reason I'm harping on this lease is because I've been through a lot of cycles, as you know, and after the dot com boom, the the cost avoidance meant not writing the check to the software company, right? And that's what nick Carr wrote this, i. T matter. And then, and then, you know, post the financial crisis, we've entered uh a decade plus of awareness on the impact of technology. And I wonder if it's, I think this, I think this the cycle is changing I think. And I wonder if you have an opinion here where people, I think organizations are going to look at Technology completely different than they did like in the early 2000s when it was just easy to cut. >>No, I think the other point I will add to it. I agree with the gym. So we typically look at our away but it doesn't always have to be the cost. Right? If you look from the outcomes of the value, there are other measures also right? If you look at the how automation was able to help in the Covid generate. It was never about costs at that time. It was about a human lives. So you always may not be able to quantify it what you look at. Okay. What how are we maximizing the value or what kind of situations where we are and where we may not even have a human power to do that work. And we are running against the time. It could be the compliance needs. I'll give example of our covid use case which was pretty big success uh within L. A. County we deployed bots for the covid contact tracing program. So we were actually interviewing all the people who were testing positive so that we actually can keep track of them and then bring back that data within our HR so that our criminologists actually can look at the trends and see how we are doing as a county as compared to other counties and nationally. And we were in the peak, we were interviewing about 5000 people a day And we had to process that data manually into our nature and we deployed 15 members to do that. And they were doing like about 600 interviews a day. So every day we had a backlog of 2500 interviews. So it is not about a cost saving or a dollar value here because nobody planned for these unplanned events and now we don't have a time and money to find more data entry operators and parts were able to actually clear up all the backlog. So the value which we were able to bring it is way beyond the cost element. >>I I believe that 100% and I've been fighting this battle for a long time and it's easier to fight now because we're in this economic cycle even despite the pandemic, but I think it can be quantified. I honestly believe it can be tied to the income statement or in the case of a public sector, it could be tied to the budget and the mission how that budget supports the mission of the company. But I really believe it. And and I've always said that those soft factors are dwarf the cost savings, but sometimes, you know, sometimes the CFO doesn't listen, you know, because he or she has to cut. I think automation could change that >>for public sector. We look at how we can do more about it. So it's because we don't look at bottom line, it's about the tax dollars, we have limited dollars, but how we can maximize the value which we are giving to residents, it is not about a profit for us. We look at the different lens when it comes to the commercial >>Side, it's similar for us. So as a as a health care pair, because we're a mutual right? Our members and we have 17 million of them are really the folks that own the company and we're very purpose driven. Our our purpose is to do everything in our power to stand by members in sickness and in health. So how do you get the highest quality, cost effective health care for them? So if automation allows you to be more effective and actually keep that cost down, that means you can cover more people and provide higher quality care to our members. So that's really the driver for mission driven, >>I was gonna ask you as a member as one of your 17 million members, what are some of the ways in which automation is benefiting me? >>Um you know, a number of different ways. First off, you know, um it lowers our administrative costs, right? So that means we can actually lower our rights as as we go out and and and work with folks? That's probably the the the the bottom line impact, but we're also automating processes uh to to make it easier for the member. Right? Uh the example I used earlier was the equivalent of no surprises. Right. How do we take the member out of the middle of this dispute between, you know, out of network providers and the payer and just make it go away. Right, and we take care of it. Um but that that creates potentially administrative burden on our side, but we want to keep their costs down and we do it efficiently using it. So there's a number of use cases that we've we've done across, you know, different parts of our business. We automate a lot of our customer service, right? When you call um there's bots in the background that are helping that that agent do their job. And what that means is you're on the show, you're on the phone a lot shorter of a period of time. And that agent can be more concise and more accurate in answering your question. >>So your employee experience is dramatically improved, as is the member experience? >>Yes, they go hand in hand. They do go hand, unhappy members means unhappy employees, 100% >>mentioned scale before, you said you can't scale in this particular, the departmental pockets. Talk about scale a little bit. I'm curious as to how important cloud is to scale. Is it not matter. Can you scale without cloud? What are the other dimensions of scale? >>Well, you know, especially with my CTO had, we're we're pushing very heavily to cloud. We view ourselves as a cloud first. We want to do things in a cloud versus our own data centers, partially because of the scale that it gives us. But because we're healthcare, we have to do it very securely. So. We are very meticulous about guarding our data, how we encrypt information um, not only in our data center but in the cloud and controlling the keys and having all the controls in place. You know, the C. So and I are probably the best friends right now in the company because we have to do it together and you have to take that that security mind set up front. Right cloud first. Put security first with it. Um, so we're moving what we can to the cloud because we think it's just going to give us better scale as we grow and better economics overall, >>Any thoughts on that? I think a similar thoughts but if we look from L. A. county because of the sheer volume itself because the data which we are talking about. We had 40 departments within the county. Each department is serving a different business purpose for the resident beit voting or B justice or being social services and all and the amount of data which we are generating for 10 million residents and the amount of duplicate asi which it comes out because it's a very government centering model. You have a different systems and they may not be talking to each other. The amount of diplomacy and identity delicacy which we are creating and as we are enabling the interoperability between these functions to give us seamless experience keeping security in mind so fully agree on that because the end of the day we have to ensure that customer guarantee but it's a sheer volume that as and when we are adding these data sets and the patient's data as well as the residents data and now we have started adding a machine data because we have deployed so many IOT solutions so the data which is coming from those machines, the logs and all its exponential so that's where the scale comes into picture and how we can ensure that we are future ready for the upscale which we need and that's where cloud ability definitely helps a lot. >>What do you mean by future ready? >>So if you look at from a future smart city or a smart community perspective, imagine when machines are everywhere machines and IOT solutions are deployed, beat even healthcare, your bad information, you're even patient information, everything is interconnected and amount of data which is getting generated in that your automobile they're going to start talking to entertainment or we have to potentially track a single resident might be going same person going to the justice or maybe same person might be having a mental health issues, A same person might be looking for a social services, how we're going to connect those dots and what all systems they are touching. So all that interconnections needs to happen. So that exponential increase of data is a future readiness, which I'm talking about. Are we future ready from a technology perspective? Are we future ready from the other ecosystem perspective and how and how we're gonna manage those situations? Uh, so those are the things which we >>look at it and it's a it's a multiplier to, right? We all have this influx of information and you need to figure out what to do with it. Right. This is where artificial intelligence, machine learning is so important. But you also have interoperability standards that are coming. So now we're we have this massive data that each of our organizations have. But now you have interoperability which is a good thing for the member saying now I need to be able to share that data. Yeah, I wanted to ask you about >>that because a lot of changes in health care, um, are meaningful use. You have to show that to get paid but the standards weren't mature. Right? And so now that's changing what role does automation play in facilitating those standards. >>So, you know, we're big, big supporters of the fire standard that's out there um to in order to be able to support the standards and and create a P. I. S. And and pull together the information. What what will happen sometimes in the background is there's actually um artificial intelligence, machine learning models that create algorithms right? The output of that though often has to be active. Now a person can do something with that information or a vodka. Right? So when you start taking the ideal of artificial intelligence and now you have a robotic process that can use that to pull together the information and assimilated in a way to make it higher quality. But now it's available. It's kind of in the background. You don't see it but it's there helping. >>What are some of the things that you see? I know we're out of time but I just have a couple more questions. Some of the things that you see here we are you I path forward for we're in person. This is a bold company that's growing very quickly. Some of the announcements that were made, what are what are some of your reaction to that? And how do you see it helping move blue crush blue shield forward even >>faster. Well you know a lot of the announcements in terms of some of the features that that they've added around their robotics processing are great right? The fact that they're in the cloud and and some of the capabilities and and and better ability to to support that the process mining is key. Right. In order for abouts to be effective, you have to understand your process and you just don't want to necessarily automate the bad practices. Right? So you want to take a look at those processes to figure out how you can automate things smartly. Um and some of their capabilities around that are very interesting. We're going to explore that quite a bit but but I think they're the ambition here is beyond robotics. Right. It's actually creating um you know, applications that actually are using bots in the background which is very intriguing and has a lot of potential potentially to drive even more digital transformation. This can really affect all of our workers and allow us to take digital solutions out to the market a lot faster >>and to see what was going to ask you, you are here for four weeks at UI Path, you got to meet a lot of your colleagues, which is great. But what about this company attracted you to leave your former role and come over here to the technology vendor side. >>Well, I think I was able to achieve the similar role within L. A. County, able to establish the automation practice and achieve the maturity, able to stand up things and I feel that this is the same practitioner activity which I can actually take it back to the other clients ceos because of one thing which I really like about your hypothesis. RP is just a small component of it. I really want to change that mindset that we have to start looking ui path as an end to end full automation enterprise solution and it is not only the business automation, it's the idea automation and it's a plus combination and whether we are developing a new industry solutions with our partners to help the different industry segments and we actually helping Ceo in the center of it because Ceo is the one who is driving the automation, enabling the business automation and actually managing the automation ceo and the governess. So CEO is in left and center of it and my role is to ensure that I actually help those Ceos to make successful and get that maturity and you will path as a platform is giving that ability of length and breath and that's what is really fascinating me and I'm really looking forward that how that spectrum is changing that we are getting matured in a process mining area and how we are expanding our horizons to look at the whole automation suit, not just the R. P. Product and that's something which I'm really looking forward and seeing that how we're going to continue expanding other magic quadrants and we're actually going to give the seamless experience so the client doesn't have to worry about okay for this, I have to pick this and further, I have to pick something else >>that's seamless experience is absolutely table stakes these days. Guys, we're out of time. But thank you so much for joining. David me, talking about automation and health care. Your recommendations for best practices, how to go about doing that and and the change management piece. That's a critical piece. We appreciate your time. >>Thanks for having. Thank >>you. Our pleasure for day Volonte. I'm lisa martin live in las Vegas. The cubes coverage of you a path forward for continues next. Mhm. Mhm mm.

>>Hello. And we're here at the cube startup showcase made possible by a Ws. Thanks so much for joining us today. You know when Jim McDaid Ghani was formulating her ideas around data mesh, She wasn't the only one thinking about decentralized data architecture. Hello, Fresh was going into hyper growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of last decade, Hello Fresh relied on a monolithic data architecture and the internal team. It had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture which possessed many principles of so called data mesh even though they didn't use that term. Specifically, the company is a strong example of an early but practical pioneer of data mission. Now there are many practitioners and stakeholders involved in evolving the company's data architecture, many of whom are listed here on this on the slide to are highlighted in red are joining us today, we're really excited to welcome into the cube Clements cheese, the Global Senior Director for Data at Hello Fresh and christoph Nevada who's the Global Senior Director of data also, of course. Hello Fresh folks. Welcome. Thanks so much for making some time today and sharing your story. >>Thank you very much. Hey >>steve. All right, let's start with Hello Fresh. You guys are number one in the world in your field, you deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling christoph. Tell us a little bit more about your company and its vision. >>Yeah. Should I start or Clements maybe maybe take over the first piece because Clements has actually been a longer trajectory yet have a fresh. >>Yeah go ahead. Climate change. I mean yes about approximately six years ago I joined handle fresh and I didn't think about the startup I was joining would eventually I. P. O. And just two years later and the freshman public and approximately three years and 10 months after. Hello fresh was listed on the German stock exchange which was just last week. Hello Fresh was included in the Ducks Germany's leading stock market index and debt to mind a great great milestone and I'm really looking forward and I'm very excited for the future for the future for head of fashion. All our data. Um the vision that we have is to become the world's leading food solution group and there's a lot of attractive opportunities. So recently we did lounge and expand Norway. This was in july and earlier this year we launched the U. S. Brand green >>chef in the U. K. As >>well. We're committed to launch continuously different geographies in the next coming years and have a strong pipe ahead of us with the acquisition of ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. We're diversifying our offer now reaching even more and more untapped customer segments and increase our total addressable market. So by offering customers and growing range of different alternatives to shop food and consumer meals. We are charging towards this vision and the school to become the world's leading integrated food solutions group. >>Love it. You guys are on a rocket ship, you're really transforming the industry and as you expand your tam it brings us to sort of the data as a as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company specifically as it relates to your data journey. You began as a start up. You had a basic architecture like everyone. You made extensive use of spreadsheets. You built a Hadoop based system that started to grow and when the company I. P. O. You really started to explode. So maybe describe that journey from a data perspective. >>Yes they saw Hello fresh by 2015 approximately had evolved what amount of classical centralized management set up. So we grew very organically over the years and there were a lot of very smart people around the globe. Really building the company and building our infrastructure. Um This also means that there were a small number of internal and external sources. Data sources and a centralized the I team with a number of people producing different reports, different dashboards and products for our executives for example of our different operations teams, christian company's performance and knowledge was transferred um just via talking to each other face to face conversations and the people in the data where's team were considered as the data wizard or as the E. T. L. Wizard. Very classical challenges. And those et al. Reserves indicated the kind of like a silent knowledge of data management. Right? Um so a central data whereas team then was responsible for different type of verticals and different domains, different geographies and all this setup gave us to the beginning the flexibility to grow fast as a company in 2015 >>christoph anything that might add to that. >>Yes. Um Not expected to that one but as as clement says it right, this was kind of set up that actually work for us quite a while. And then in 2017 when L. A. Freshman public, the company also grew rapidly and just to give you an idea how that looked like. As was that the tech department self actually increased from about 40 people to almost 300 engineers And the same way as a business units as Clemens has described, also grew sustainable, sustainably. So we continue to launch hello fresh and new countries launching brands like every plate and also acquired other brands like much of a factor and with that grows also from a data perspective the number of data requests that centrally we're getting become more and more and more and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very or basically get a very deep understanding about the business. And also suffered a lot from this context switching back and forth, essentially there to prioritize across our product request from our physical product, digital product from the physical from sorry, from the marketing perspective and also from the central reporting uh teams. And in a nutshell this was very hard for these people. And this that also to a situation that, let's say the solution that we have became not really optimal. So in a nutshell, the central function became a bottleneck and slowdown of all the innovation of the company. >>It's a classic case, isn't it? I mean Clements, you see you see the central team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own hands. And then of course I I. T. And the technical team is called in later to clean up the mess. Uh maybe, I mean was that maybe I'm overstating it, but that's a common situation, isn't it? >>Yeah. Uh This is what exactly happened. Right. So um we had a bottleneck, we have the central teams, there was always a little of tension um analytics teams then started in this business domains like marketing, trade chain, finance, HR and so on. Started really to build their own data solutions at some point you have to get the ball rolling right and then continue the trajectory um which means then that the data pipelines didn't meet the engineering standards. And um there was an increased need for maintenance and support from central teams. Hence over time the knowledge about those pipelines and how to maintain a particular uh infrastructure for example left the company such that most of those data assets and data sets are turned into a huge step with decreasing data quality um also decrease the lack of trust, decreasing transparency. And this was increasing challenge where majority of time was spent in meeting rooms to align on on data quality for example. >>Yeah. And and the point you were making christoph about context switching and this is this is a point that Jemaah makes quite often is we've we've we've contextualized are operational systems like our sales systems, our marketing system but not our our data system. So you're asking the data team, Okay. Be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it start stop, start, stop, it's a paper cut environment and it's just not as productive. But but on the flip side of that is when you think about a centralized organization you think, hey this is going to be a very efficient way, a cross functional team to support the organization but it's not necessarily the highest velocity, most effective organizational structure. >>Yeah, so so I agree with that. Is that up to a certain scale, a centralized function has a lot of advantages, right? That's clear for everyone which would go to some kind of expert team. However, if you see that you actually would like to accelerate that and specific and this hyper growth, right, you wanna actually have autonomy and certain teams and move the teams or let's say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load and you can either internally start splitting your team into a different kind of sub teams focusing on different areas. However, that is then again, just adding another peace where actually collaboration needs to happen busy external sees, so why not bridging that gap immediately and actually move these teams and to end into into the function themselves. So maybe just to continue what, what was Clements was saying and this is actually where over. So Clements, my journey started to become one joint journey. So Clements was coming actually from one of these teams to build their own solutions. I was basically having the platform team called database housed in these days and in 2019 where basically the situation become more and more serious, I would say so more and more people have recognized that this model doesn't really scale In 2019, basically the leadership of the company came together and I identified data as a key strategic asset and what we mean by that, that if we leverage data in a proper way, it gives us a unique competitive advantage which could help us to, to support and actually fully automated our decision making process across the entire value chain. So what we're, what we're trying to do now or what we should be aiming for is that Hello, Fresh is able to build data products that have a purpose. We're moving away from the idea. Data is just a by problem products, we have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to for the company as a business, we also want to provide them as a trust versi asset to the rest of the organization. We say there's the best customer experience, but at least in a way that users can easily discover, understand and security access high quality data. >>Yeah, so and and and Clements, when you c J Maxx writing, you see, you know, she has the four pillars and and the principles as practitioners you look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's and that's where the devil meets the details. So it's the four, you know, the decentralized data ownership data as a product, which we'll talk about a little bit self serve, which you guys have spent a lot of time on inclement your wheelhouse which is which is governance and a Federated governance model. And it's almost like if you if you achieve the first two then you have to solve for the second to it almost creates a new challenges but maybe you could talk about that a little bit as to how it relates to Hello fresh. >>Yes. So christophe mentioned that we identified economic challenge beforehand and for how can we actually decentralized and actually empower the different colleagues of ours. This was more a we realized that it was more an organizational or a cultural change and this is something that somebody also mentioned I think thought words mentioned one of the white papers, it's more of a organizational or cultural impact and we kicked off a um faced reorganization or different phases we're currently and um in the middle of still but we kicked off different phases of organizational reconstruct oring reorganization, try unlock this data at scale. And the idea was really moving away from um ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do, what shall we do? This is value creation and how, which is capability building and both are equal in authority. This actually then creates a high urge and collaboration and this collaboration breaks up the different silos that were built and of course this also includes different needs of stuffing forward teams stuffing with more, let's say data scientists or data engineers, data professionals into those business domains and hence also more capability building. Um Okay, >>go ahead. Sorry. >>So back to Tzemach did johnny. So we the idea also Then crossed over when she published her papers in May 2019 and we thought well The four colors that she described um we're around decentralized data ownership, product data as a product mindset, we have a self service infrastructure and as you mentioned, Federated confidential governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then leads to a not only organisational restructure but also in completely new approach of how we need to manage data, show data. >>Got it. Okay, so your business is is exploding. Your data team will have to become domain experts in too many areas, constantly contact switching as we said, people started to take things into their own hands. So again we said classic story but but you didn't let it get out of control and that's important. So we actually have a picture of kind of where you're going today and it's evolved into this Pat, if you could bring up the picture with the the elephant here we go. So I would talk a little bit about the architecture, doesn't show it here, the spreadsheet era but christoph maybe you can talk about that. It does show the Hadoop monolith which exists today. I think that's in a managed managed hosting service, but but you you preserve that piece of it, but if I understand it correctly, everything is evolving to the cloud, I think you're running a lot of this or all of it in A W. S. Uh you've got everybody's got their own data sources, uh you've got a data hub which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure. That is really not the focus of this conversation today. But the key here, if I understand it correctly is these domains are autonomous and not only that this required technical thinking, but really supportive organizational mindset, which we're gonna talk about today. But christoph maybe you could address, you know, at a high level some of the architectural evolution that you guys went through. >>Yeah, sure. Yeah, maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning with the model is on the operation of playing right? Actually, it wasn't just one model is both to one for the back end and one for the for the front and and or analytical plane was essentially a couple of spreadsheets and I think there's nothing wrong with spreadsheets, right, allows you to store information, it allows you to transform data allows you to share this information. It allows you to visualize this data, but all the kind of that's not actually separating concern right? Everything in one tool. And this means that obviously not scalable, right? You reach the point where this kind of management set up in or data management of isn't one tool reached elements. So what we have started is we've created our data lake as we have seen here on Youtube. And this at the very beginning actually reflected very much our operational populace on top of that. We used impala is a data warehouse, but there was not really a distinction between borders, our data warehouse and borders our data like the impala was used as a kind of those as the kind of engine to create a warehouse and data like construct itself and this organic growth actually led to a situation as I think it's it's clear now that we had to centralized model is for all the domains that will really lose kimball modeling standards. There was no uniformity used actually build in house uh ways of building materialized use abuse that we have used for the presentation layer, there was a lot of duplication of effort and in the end essentially they were missing feedbacks, food, which helped us to to improve of what we are filled. So in the end, in the natural, as we have said, the lack of trust and that's basically what the starting point for us to understand. Okay, how can we move away and there are a lot of different things that you can discuss of apart from this organizational structure that we have said, okay, we have these three or four pillars from from Denmark. However, there's also the next extra question around how do we implement our talking about actual right, what are the implications on that level? And I think that is there's something that we are that we are currently still in progress. >>Got it. Okay, so I wonder if we could talk about switch gears a little bit and talk about the organizational and cultural challenges that you faced. What were those conversations like? Uh let's dig into that a little bit. I want to get into governance as well. >>The conversations on the cultural change. I mean yes, we went through a hyper growth for the last year since obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company which then results that collaboration uh >>got a bit more difficult. Of course >>there are times and changes, you have different different artifacts that you were created um and documentation that were flying around. Um so we were we had to build the company from scratch right? Um Of course this then resulted always this tension which I described before, but the most important part here is that data has always been a very important factor at l a fresh and we collected >>more of this >>data and continued to improve use data to improve the different key areas of our business. >>Um even >>when organizational struggles, the central organizational struggles data somehow always helped us to go through this this kind of change. Right? Um in the end those decentralized teams in our local geography ease started with solutions that serve the business which was very very important otherwise wouldn't be at the place where we are today but they did by all late best practices and standards and I always used sport analogy Dave So like any sport, there are different rules and regulations that need to be followed. These rules are defined by calling the sports association and this is what you can think about data governance and compliance team. Now we add the players to it who need to follow those rules and bite by them. This is what we then called data management. Now we have the different players and professionals, they need to be trained and understand the strategy and it rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in a different domains. And one of our mission of our data literacy program for example is to really empower >>every employee at hello >>fresh everyone to make the right data informs decisions by providing data education that scaled by royal Entry team. Then this can be different things, different things like including data capabilities, um, with the learning paths for example. Right? So help them to create and deploy data products connecting data producers and data consumers and create a common sense and more understanding of each other's dependencies, which is important, for example, S. S. L. O. State of contracts and etcetera. Um, people getting more of a sense of ownership and responsibility. Of course, we have to define what it means, what does ownership means? But the responsibility means. But we're teaching this to our colleagues via individual learning patterns and help them up skill to use. Also, there's shared infrastructure and those self self service applications and overall to summarize, we're still in this progress of of, of learning, we are still learning as well. So learning never stops the tele fish, but we are really trying this um, to make it as much fun as possible. And in the end we all know user behavior has changed through positive experience. Uh, so instead of having massive training programs over endless courses of workshops, um, leaving our new journalists and colleagues confused and overwhelmed. >>We're applying um, >>game ification, right? So split different levels of certification where our colleagues can access, have had access points, they can earn badges along the way, which then simplifies the process of learning and engagement of the users and this is what we see in surveys, for example, where our employees that your justification approach a lot and are even competing to collect Those learning path batteries to become the # one on the leader board. >>I love the game ification, we've seen it work so well and so many different industries, not the least of which is crypto so you've identified some of the process gaps uh that you, you saw it is gloss over them. Sometimes I say paved the cow path. You didn't try to force, in other words, a new architecture into the legacy processes. You really have to rethink your approach to data management. So what what did that entail? >>Um, to rethink the way of data management. 100%. So if I take the example of Revolution, Industrial Revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. Um, so we needed to establish a new set of cross functional business processes to run faster, dry faster, um, more robustly and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector with internal, I'm always referring to the data operations around new things like data catalog, how to identify >>ownership, >>how to change ownership, how to certify data assets, everything around classical software development, which we know apply to data. This this is similar to a new thinking, right? Um deployment, versioning, QA all the different things, ingestion policies, policing procedures, all the things that suffer. Development has been doing. We do it now with data as well. And in simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes and as a creation as management and as a consumption. >>So data has become kind of the new development kit. If you will um I want to shift gears and talk about the notion of data product and, and we have a slide uh that we pulled from your deck and I'd like to unpack it a little bit. Uh I'll just, if you can bring that up, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems where customers, both internal and external. So pretty straightforward. I know you've gone much deeper and you're thinking and into your organization, but how do you think about that And how do you determine for instance who owns what? How did you get everybody to agree? >>I can take that one. Um, maybe let me start with the data product. So I think um that's an ongoing debate. Right? And I think the debate itself is an important piece here, right? That visit the debate, you clarify what we actually mean by that product and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say okay that our product is something which is important for the company has come to its value what you mean by that. Okay, it's it's a solution to a customer problem that delivers ideally maximum value to the business. And yes, it leverages the power of data and we have a couple of examples but it had a fresh year, the historical and classical ones around dashboards for example, to monitor or error rates but also more sophisticated ways for example to incorporate machine learning algorithms in our recipe recommendations. However, I think the important aspects of the data product is a there is an owner, right? There's someone accountable for making sure that the product that we are providing is actually served and is maintained and there are, there is someone who is making sure that this actually keeps the value of that problem thing combined with the idea of the proper documentation, like a product description, right that people understand how to use their bodies is about and related to that peace is the idea of it is a purpose. Right? You need to understand or ask ourselves, Okay, why does this thing exist does it provide the value that you think it does. That leads into a good understanding about the life cycle of the data product and life cycle what we mean? Okay from the beginning from the creation you need to have a good understanding, we need to collect feedback, we need to learn about that. We need to rework and actually finally also to think about okay benefits time to decommission piece. So overall, I think the core of the data product is product thinking 11 right that we start the point is the starting point needs to be the problem and not the solution and this is essentially what we have seen what was missing but brought us to this kind of data spaghetti that we have built there in in Russia, essentially we built at certain data assets, develop in isolation and continuously patch the solution just to fulfill these articles that we got and actually these aren't really understanding of the stakeholder needs and the interesting piece as a result in duplication of work and this is not just frustrating and probably not the most efficient way how the company should work. But also if I build the same that assets but slightly different assumption across the company and multiple teams that leads to data inconsistency and imagine the following too narrow you as a management for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kind of grass, different kind of data and numbers and in the end you do not know which ones to trust. So there's actually much more ambiguity and you do not know actually is a noise for times of observing or is it just actually is there actually a signal that I'm looking for? And the same is if I'm running in a B test right, I have a new future, I would like to understand what has it been the business impact of this feature. I run that specific source in an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you've seen in a B test is actually not what you see then in production typical thing then is you're asking some analytics tend to actually do a deep dive to understand where the discrepancies are coming from. The worst case scenario. Again, there's a different kind of source. So in the end it's a pretty frustrating scenario and that's actually based of time of people that have to identify the root cause of this divergence. So in a nutshell, the highest degree of consistency is actually achieved that people are just reusing Dallas assets and also in the media talk that we have given right, we we start trying to establish this approach for a B testing. So we have a team but just providing or is kind of owning their target metric associated business teams and they're providing that as a product also to other services including the A B testing team, they'll be testing team can use this information defines an interface is okay I'm joining this information that the metadata of an experiment and in the end after the assignment after this data collection face, they can easily add a graph to the dashboard. Just group by the >>Beatles Hungarian. >>And we have seen that also in other companies. So it's not just a nice dream that we have right. I have actually worked in other companies where we worked on search and we established a complete KPI pipeline that was computing all this information. And this information was hosted by the team and it was used for everything A B test and deep dives and and regular reporting. So uh just one of the second the important piece now, why I'm coming back to that is that requires that we are treating this data as a product right? If you want to have multiple people using the things that I am owning and building, we have to provide this as a trust mercy asset and in a way that it's easy for people to discover and actually work with. >>Yeah. And coming back to that. So this is to me this is why I get so excited about data mesh because I really do think it's the right direction for organizations. When people hear data product they say well, what does that mean? Uh but then when you start to sort of define it as you did, it's it's using data to add value, that could be cutting costs, that could be generating revenue, it could be actually directly you're creating a product that you monetize, So it's sort of in the eyes of the beholder. But I think the other point that we've made is you made it earlier on to and again, context. So when you have a centralized data team and you have all these P NL managers a lot of times they'll question the data because they don't own it. They're like wait a minute. If they don't, if it doesn't agree with their agenda, they'll attack the data. But if they own the data then they're responsible for defending that and that is a mindset change, that's really important. Um And I'm curious uh is how you got to, you know, that ownership? Was it a was it a top down with somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what in other words, you know, did you get, how did you get the business to take ownership of the data and what is owning? You know, the data actually mean? >>That's a very good question. Dave I think this is one of the pieces where I think we have a lot of learnings and basically if you ask me how we could start the feeling. I think that would be the first piece. Maybe we need to start to really think about how that should be approached if it stopped his ownership. Right? It means somehow that the team has a responsibility to host and self the data efforts to minimum acceptable standards. This minimum dependencies up and down string. The interesting piece has been looking backwards. What what's happening is that under that definition has actually process that we have to go through is not actually transferring ownership from the central team to the distributor teams. But actually most cases to establish ownership, I make this difference because saying we have to transfer ownership actually would erroneously suggests that the data set was owned before. But this platform team, yes, they had the capability to make the changes on data pipelines, but actually the analytics team, they're always the ones who had the business understands, you use cases and but no one actually, but it's actually expensive expected. So we had to go through this very lengthy process and establishing ownership. We have done that, as in the beginning, very naively. They have started, here's a document here, all the data assets, what is probably the nearest neighbor who can actually take care of that and then we we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent over years and these people who have built this thing have already left the company. So there's actually not a nice thing that is that you want to see and people build up a certain resistance, e even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, but what needs to happen as first, the company needs to really understand what our core business concept that they have, they need to have this mapping from. These are the core business concept that we have. These are the domain teams who are owning this concept and then actually link that to the to the assets and integrated better with both understanding how we can evolve actually, the data assets and new data build things new in the in this piece in the domain. But also how can we address reduction of technical death and stabilizing what we have already. >>Thank you for that christoph. So I want to turn a direction here and talk about governance and I know that's an area that's passionate, you're passionate about. Uh I pulled this slide from your deck, which I kind of messed up a little bit sorry for that, but but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks. But it's one of the most challenging aspects of data mesh, if you're going to decentralize you, you quickly realize this could be the Wild West as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy, compliance etcetera. So, so how did you approach this? >>It's yeah, it's about connecting those dots. Right. So the aim of the data governance program is about the autonomy of every team was still ensuring that everybody has the right interoperability. So when we want to move from the Wild West riding horses to a civilised way of transport, um you can take the example of modern street traffic, like when all participants can manoeuvre independently and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights in the different signals. Um, so likewise as a business and Hello Fresh, we do operate autonomously and consequently need to follow those external and internal rules and standards to set forth by the redistribution in which we operate so in order to prevent a car crash, we need to at least ensure compliance with regulations to account for society's and our customers increasing concern with data protection and privacy. So teaching and advocating this advantage, realizing this to everyone in the company um was a key community communication strategy and of course, I mean I mentioned data privacy external factors, the same goes for internal regulations and processes to help our colleagues to adapt to this very new environment. So when I mentioned before the new way of thinking the new way of um dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. Um in a nutshell then this means the data governance provides a framework for managing our people the processes and technology and culture around our data traffic. And those components must come together in order to have this effective program providing at least a common denominator, especially critical for shared dataset, which we have across our different geographies managed and shared applications on shared infrastructure and applications and is then consumed by centralized processes um for example, master data, everything and all the metrics and KPI s which are also used for a central steering. Um it's a big change day. Right. And our ultimate goal is to have this noninvasive, Federated um ultimatum and computational governance and for that we can't just talk about it. We actually have to go deep and use case by use case and Qc buy PVC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status by identifying together with the business teams with the different domains have a risk assessment for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of illiteracy comes into place where we go in and trade based on the findings based on the most valuable use case um and based on that help our teams to do this change to increase um their capability just a little bit more and once they hand holding. But a lot of guidance >>can I kind of kind of trying to quickly David will allow me I mean there's there's a lot of governance piece but I think um that is important. And if you're talking about documentation for example, yes, we can go from team to team and tell these people how you have to document your data and data catalog or you have to establish data contracts and so on the force. But if you would like to build data products at scale following actual governance, we need to think about automation right. We need to think about a lot of things that we can learn from engineering before. And that starts with simple things like if we would like to build up trust in our data products, right, and actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do and we should probably think about what we can copy and one example might be. So the level of service level agreements, service level objectives. So that level indicators right, that represent on on an engineering level, right? If we're providing services there representing the promises we made to our customers or consumers, these are the internal objectives that help us to keep those promises. And actually these are the way of how we are tracking ourselves, how we are doing. And this is just one example of that thing. The Federated Governor governance comes into play right. In an ideal world, we should not just talk about data as a product but also data product. That's code that we say, okay, as most as much as possible. Right? Give the engineers the tool that they are familiar basis and actually not ask the product managers for example to document their data assets in the data catalog but make it part of the configuration. Have this as a, as a C D C I, a continuous delivery pipeline as we typically see another engineering task through and services we say, okay, there is configuration, we can think about pr I can think about data quality monitoring, we can think about um the ingestion data catalog and so on and forest, I think ideally in the data product will become of a certain templates that can be deployed and are actually rejected or verified at build time before we actually make them deploy them to production. >>Yeah, So it's like devoPS for data product um so I'm envisioning almost a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where there's there's learning, there's literacy, there's training, education, there's kind of self governance and then there's some kind of oversight, some a lot of manual stuff going on and then you you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >>Yeah, I would rather think think about automation as early as possible in the way and yes, there needs to be certain rules but then actually start actually use case by use case. Is there anything that small piece that we can already automate? It's as possible. Roll that out and then actually extended step by step, >>is there a role though that adjudicates that? Is there a central Chief state officer who is responsible for making sure people are complying or is it how do you handle that? >>I mean from a from a from a platform perspective, yes, we have a centralized team to uh implement certain pieces they'll be saying are important and actually would like to implement. However, that is actually working very closely with the governance department. So it's Clements piece to understand and defy the policies that needs to be implemented. >>So Clements essentially it's it's your responsibility to make sure that the policy is being followed. And then as you were saying, christoph trying to compress the time to automation as fast as possible percent. >>So >>it's really it's uh >>what needs to be really clear that it's always a split effort, Right? So you can't just do one thing or the other thing, but everything really goes hand in hand because for the right automation for the right engineering tooling, we need to have the transparency first. Uh I mean code needs to be coded so we kind of need to operate on the same level with the right understanding. So there's actually two things that are important which is one its policies and guidelines, but not only that because more importantly or even well equally important to align with the end user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >>Got it. So just a couple more questions because we gotta wrap I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment but but major learnings, we've got some of the challenges that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks. But my question, I mean this is the advice for your peers question if you had to do it differently if you had a do over or a Mulligan as we like to say for you golfers, what would you do differently? Yeah, >>I mean can we start with from a from the transformational challenge that understanding that it's also high load of cultural change. I think this is this is important that a particular communication strategy needs to be put into place and people really need to be um supported. Right? So it's not that we go in and say well we have to change towards data mesh but naturally it's in human nature, you know, we're kind of resistance to to change right? Her speech uncomfortable. So we need to take that away by training and by communicating um chris we're gonna add something to that >>and definitely I think the point that I have also made before right we need to acknowledge that data mesh is an architecture of scale, right? You're looking for something which is necessary by huge companies who are vulnerable, data productive scale. I mean Dave you mentioned it right, there are a lot of advantages to have a centralized team but at some point it may make sense to actually decentralized here and at this point right? If you think about data Mash, you have to recognize that you're not building something on a green field. And I think there's a big learning which is also reflected here on the slide is don't underestimate your baggage. It's typically you come to a point where the old model doesn't doesn't broke anymore and has had a fresh right? We lost our trust in our data and actually we have seen certain risks that we're slowing down our innovation so we triggered that this was triggering the need to actually change something. So this transition implies that you typically have a lot of technical debt accumulated over years and I think what we have learned is that potentially we have decentralized some assets to earlier, this is not actually taking into account the maturity of the team where we are actually distributed to and now we actually in the face of correcting pieces of that one. Right? But I think if you if you if you start from scratch you have to understand, okay, is are my team is actually ready for taking on this new uh, this news capabilities and you have to make sure that business decentralization, you build up these >>capabilities and the >>teams and as Clements has mentioned, right, make sure that you take the people on your journey. I think these are the pieces that also here, it comes with this knowledge gap, right? That we need to think about hiring and literacy the technical depth I just talked about and I think the last piece that I would add now which is not here on the flight deck is also from our perspective, we started on the analytical layer because that's kind of where things are exploding, right, this is the thing that people feel the pain but I think a lot of the efforts that we have started to actually modernize the current state uh, towards data product towards data Mash. We've understood that it always comes down basically to a proper shape of our operational plane and I think what needs to happen is is I think we got through a lot of pains but the learning here is this need to really be a commitment from the company that needs to happen and to act. >>I think that point that last point you made it so critical because I I hear a lot from the vendor community about how they're gonna make analytics better and that's that's not unimportant, but but through data product thinking and decentralized data organizations really have to operationalize in order to scale. So these decisions around data architecture an organization, their fundamental and lasting, it's not necessarily about an individual project are why they're gonna be project sub projects within this architecture. But the architectural decision itself is an organizational, its cultural and what's the best approach to support your business at scale. It really speaks to to to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data driven driven companies is yields tremendous results. So I'll ask each of you to give give us your final thoughts and then we'll wrap maybe >>maybe it quickly, please. Yeah, maybe just just jumping on this piece that you have mentioned, right, the target architecture. If we talk about these pieces right, people often have this picture of mind like OK, there are different kind of stages, we have sources, we have actually ingestion layer, we have historical transformation presentation layer and then we're basically putting a lot of technology on top of that kind of our target architecture. However, I think what we really need to make sure is that we have these different kind of viewers, right? We need to understand what are actually the capabilities that we need in our new goals. How does it look and feel from the different kind of personas and experience view? And then finally, that should actually go to the to the target architecture from a technical perspective um maybe just to give an outlook but what we're what we're planning to do, how we want to move that forward. We have actually based on our strategy in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data, cultural, data literacy, data organizational structure and so on that. We're talking about governance as Clements has actually mentioned that, right, compliance, governance, data management and so on. You talk about technology and I think we could talk for hours for that one. It's around data platform, better science platform and then finally also about enablement through data, meaning we need to understand that a quality data accessibility and the science and data monetization. >>Great, thank you christophe clement. Once you bring us home give us your final thoughts. >>Can't can just agree with christoph that uh important is to understand what kind of maturity people have to understand what the maturity level, where the company where where people organization is and really understand what does kind of some kind of a change replies to that those four pillars for example, um what needs to be taken first and this is not very clear from the very first beginning of course them it's kind of like Greenfield you come up with must wins to come up with things that we really want to do out of theory and out of different white papers. Um only if you really start conducting the first initiatives you do understand. Okay, where we have to put the starts together and where do I missed out on one of those four different pillars? People, process technology and governance. Right? And then that kind of an integration. Doing step by step, small steps by small steps not boiling the ocean where you're capable ready to identify the gaps and see where either you can fill um the gaps are where you have to increase maturity first and train people or increase your text text, >>you know Hello Fresh is an excellent example of a company that is innovating. It was not born in Silicon Valley which I love. It's a global company. Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? >>Yes, >>definitely. We do >>uh as many rights as was one of these aspects distributing. And actually we are hiring as an entire company specifically for data. I think there are a lot of open roles serious. Please visit or our page from better engineering, data, product management and Clemens has a lot of rules that you can speak about. But yes >>guys, thanks so much for sharing with the cube audience, your, your pioneers and we look forward to collaborations in the future to track progress and really want to thank you for your time. >>Thank you very much. Thank you very much. Dave >>thank you for watching the cubes startup showcase made possible by A W. S. This is Dave Volonte. We'll see you next time. >>Yeah.

>>mhm >>mm >>Hello and welcome back to HPD discovered 2021. My name is Dave Volonte and we're going to dig into H P E. Green Lake, we've heard a lot about this, we want to find out how real it is and test a little bit of how how can help solve your business problems. We also want to understand Green Lake relative to the competition. HPV was the first, as you probably know to declare it all in with an as a service model and virtually every major infrastructure player has now followed suit. So we want to hear from HP directly how it's different from the competition, where it's innovating and that means we're gonna poke a little bit of customer examples and how the partner ecosystem is adopting and responding to Green Lake and with me is the right person to do this is keith White, who is the senior Vice President General Manager of the Green Lake cloud services business unit at HP, keith, great to see you, thanks for coming back to the cube. >>Okay, fantastic to see you as always. So thanks so much for having me. >>Yeah, it's our pleasure. So look, we're hearing a lot leading up to discover and at this event about Green Lake you got momentum now, everybody's excited about it. What's driving demand? Where's the excitement coming from? >>No, it's a great question. And you know, the reality is customers are expecting this cloud experience, right? So they they've been using the public cloud, they've been engaging on that front and this cloud experience is really driven, a pretty high amount of customer expectations, make itself served, make it automated, make it easy to consume, only want to pay for what I'm using and then manage it all for me on the back end. But 60 to 70% of apps and data will stay on prem per Gardner and I D. C. And so give me that experience on prem. And so that's why I think Green Lake has gotten so much interest, so much positive growth and momentum is because we're bringing that cloud experience to our customers in their data center, in their Coehlo or at the edge and that's where they want to see it just as much. And so since the world is now hybrid, we have a fantastic solution for folks. >>So you, you were first in this game and so you took some arrows and I'm interested in how Green Lake has evolved, Take us through the journey maybe what were some of the bumps in the road that you had to overcome? Maybe how it compares with the competition. Maybe some of the things that they're going to have to go through as well to get to the point where you are. >>No, it's true. And you know, the great thing is HP as a company is really moving to be much more of a cloud services and software company. And you know, we're seeing this from our competition, as you mentioned, have followed suit. But in essence, you know, you have to move from just sort of providing lease type financing type scenarios for our customers into truly delivering that cloud experience. And that's what's been so exciting over this last year is we've gone from just the basic cloud services, compute storage, networking and VMS to really providing containers as a service, bare metal as a service. Uh, machine learning ops, S. A P V. D I. You know, we've now created a set of workloads and as you heard it discover we're now delivering industry solutions, so electronic medical records for hospitals or high delivery payment transaction processing for, for financial, so that the challenge of moving from just sort of leasing basic capabilities to a true cloud experience that again pay as I go, fully automated self serve, all managed for me has really been a challenge and it's exciting, it's exciting to see customers jump on and really sort of lean in and see the business value that comes from having that level of solution >>keith, am I correct in that pretty much every large tech company has a services arm and they could, they could sort of brute force, some kind of cloud like experience and that's kind of what people have done historically the layer in a financial like leasing financial as you said and and but every situation was unique, it was kind of a snowflake if you will and you guys are probably there a few years ago as well and so I'm interested in sort of how you evolved beyond that. Was it a mindset was a technology, was it sort of cultural? You know, it came from the top as well, but maybe you could describe that a little bit. >>Yeah, the ship comes from our customers because what's happening is customers no longer trying to buy component parts. They're saying it's really about Tesla's like, hey, I want you to deliver this for me. In essence, we're running the data center for them now. We're running their machine learning operations environment for them. Now, you know, we're migrating their mainframe over now. And so what's happening is these sls are really, what matters to customers like that? It's not so much about, hey, what are the speeds and feeds and this and that? And so yes, you can sort of brute force that piece of it. But what you really are having to do is create this deep partnership and relationship with your customer to truly understand their business challenges and then provide them with that capability. Now I think the things that's exciting is yes, the public cloud gives you some some significant benefits for certain workloads and certain capabilities. But what we're hearing from customers is hey, I want to have much more control over my data center. I want to ensure that it has the security required. I want to make sure that I can make the adjustments necessary and so you're doing all that at a lower cost with open platform that I can use a variety of tools and other applications just makes it that much more powerful. So I think that's what we're seeing is we're getting into what our customers really requiring and then you know the most interesting thing is how do you make it work with my entire environment because I am running Azure and I am running A W. S. And I am running google and I'm running some other things. And so how does this cloud really helped me bring all those together to really govern that hybrid estate? And that's where I think Green Lake has really shine. >>So it kind of part of the secret sauce is automation because you've got to be, you still have, you have to be competitive, you know, at least within reason to cloud cost, sometimes it's going to be less expensive, maybe sometimes it can be more expensive. You've got some advantages in certain cases where, you know, there's government governance things and and you know, we don't have to go through all that, but there's the automation but you've got to be profitable at this too. So there's the automation, there's the tooling, there's the openness. So, so that was really a key part of it. Is it not that sort of automating? >>That's right. Automation is key as is really understanding what that customer environment is and optimizing for that piece of it. And so as you heard, we're really excited to announce our Green Lake Lighthouse, which is really providing workload optimized systems that are fully managed for them that provide that capability to run multiple workloads for that customer. But at the same time, to your point, there's a lot of charges that happened on the public cloud side. So, you know, data is the new, you know, gold if you will right, everyone's trying to monetize their data, trying to use it to make decisions and really understand what's happening across their environment and in the cloud. You know, if you put it up in the cloud, you have to pay to get it out. The egress charges can be significant and it's also a bit slower at times because of the latency that happens across that that that connection. And so we are now in a situation where we're seeing a lot of customers that are really trying to analyze their data, leveraging our HPC systems, leveraging our machine learning operation systems in order to really get that data happening, Getting the dancers out much, much faster and a much lower cost than what it would cost them to do that in the cloud. >>So you have some experience at this now. I wonder if we could dig into the customers how customers are using Green Lake. Maybe you can give some examples of success. >>Yeah. Yeah, no. You know it's exciting because you know first off everyone's looking at their digital transformation and that means something different for every single customer, so really understanding what they're trying to do from a transformation standpoint and then saying, okay, well how can we bring a solution to help accelerate that? To help be uh, you know, more connected to your customers to help improve your product delivery. We went to Lyondellbasell for example, one of the largest manufacturers in the world. And you know, they said, hey look, we don't want to run our data center anymore. Most most customers are trying to get out of the data center management business and they're saying, hey, run this for me, uh let me free up resources to go focus on things that really can drive additional value for our customers instead of keeping the lights on patching, blah blah blah. So we have taken their entire environment and moved it to a Coehlo and we're managing it now for them. And so in essence we freed up not just a ton of resources, but they have also been able to drop their carbon footprint, which is also this whole sustainability push is significant as well. And then you look at a customer like care stream, one of the largest medical diagnostic companies in the world, saying hey we gotta be able to allow our doctors to be able to um analyze and diagnose things much much faster through our X ray systems and through our diagnostic machines. And so they have implemented our machine learning operations scenario to dramatically speed up those types of capabilities. So as you go down the list and you start to see these customers really um leveraging technology to meet that digital transformation, saving costs, moving their business forward, creating new business models. It's just, it's really exciting. >>What about partners keith? How how have they responded? I mean, on the one hand, you know, that's great opportunities for them, you know, they're they're transforming their own business model. On the other hand, you know, maybe they were comfortable with the old model, they got a big house, nice, nice boat, you >>know? >>But how are they changing their their their business and how are they leaning in >>similar to what we're seeing? The opportunity for partners is dramatic, right? Because what happens is you have to have a very different relationship with your customer to truly understand their digital transformation. Their business challenges the problems that they're having to address. And so where we're seeing partners really, really sort of the opportunity is where there's the services and that sort of deeper relationship piece of it. So in essence, it's creating much more opportunity because the white spaces dramatic we're seeing, I want to say it's in the 30 to $40 billion worth of market opportunity as we move into an as a service on prem world. So they're seeing that opportunity. They're seeing the ability to add services on top of that and deepen the relationship with our customers. And you know, it's it's from my SVS. We're working closely with S. A. P. For example, to deliver their new rise private cloud customer edition. We're working closely with loosest, for example, who is doing a lot of payment processing type scenarios Nutanix and their database as a service scenario and Splunk because again, we went back to the data piece and these guys are doing so much big data type implementations for risk analytics and and regulatory type scenarios. It's just significant. And so because there's such a push to keep things on prem to have the security to reduce the latency to get rid of the egress charges and everything else. There's just a significant white space for both our partners and then from our distributors and resellers, they're getting to change their business model again, to get much deeper in that relationship with our customers >>to be Green Lake is, I mean it's H. P. E. As a service, it's your platform. And so I wonder if you can think about how you're thinking about uh, share with us, How you think about platform innovation? Um, you've got the pricing model, you know, flex up, flex down. Is there other technology we should know about and other things that are going to move you forward in this battle for the next great hybrid cloud and edge platform? >>Yeah, it's a great push because if you think about it, we are Green Lake is the edge to cloud platform And in essence because we have such a strong edge capability with the arab acquisition we made a few years back. That's really significant momentum with the Silver Peak acquisition to give us SD when you've got that edge connectivity all the way up to our high performance computing. And so you'll see us deliver high performance computing as a service. We're announcing that here at discover um you'll see us announced, you know, machine learning ops I mentioned ASAP, but also a virtual desktops. I think the pandemic has brought a lot more work from home type scenarios and customers really want to have that secure desktop. And so, working with partners like Citrix and Nutanix and and VM ware and Crew were able to provide that again, unique scenario for our customers. And so, um, yeah, the innovation is going to keep coming. You know, I mentioned bare metal as a service because many people are starting to really leverage the metal that's out there. You're seeing us also engaged with folks like intel on our silicon on demand. So this is a really exciting technology because what it allows us to do is turn on cores when we need them. So hey, I need additional capacity. I need some power. Let's turn on some cores. But then I turn off those cores when I'm not using them. You go to a software core based software pricing model, like an oracle or a sequel server. I'm saving dramatic cost now because I don't have to pay for all the cores that are on the system. I'm only paying the licenses for the ones that I use. And so that should bring dramatic cost savings to our customers as well. So we're looking from the silicon all the way up. Uh you know, you hear us talk about project Aurora, which is our security capability. We're looking at the silicon level, but we're also looking at the the container and bare metal and then obviously the workloads in the industry solution. So we're sprinting forward. We're listening to our customers were taking their feedback. We're seeing what they're prioritizing and because we have that tight relationship with them as we help move them to the direction they want to go, it's giving us a ton of fantastic inside information for what really matters. >>Right, Thank you for that. So, I want to ask you about data. A lot of organizations are kind of rethinking their ideal data architecture, their organization. They're they're they're seeing the amount of data that is potentially going to be created at the edge, thinking about ai inference and influencing at the edge and maybe reimagining their data organization in this age of insight. I wonder how Green Lake fits into that. How are you thinking about the new era of data and specifically Green Lakes role? >>Yeah, you mentioned the age of insights and and it really is right. So we've moved sort of as the next phase of digital transformation is basically saying, hey look, I've got all this data. I've got to first get my arms around my data estate because in essence it's in all these different pockets around. And so Green Lake gives you that ability to really get that data estate established. Then I want to take and get the answers in the analytics out of it. And then I want to monetize that data either out to my customer set or out to my industry or out to other scenarios as well. And so as we start to deliver our develops capability, our ai and analytics capabilities through HPC. And it's an open platform. So it allows data scientists to easy boot up easily boot up a cluster with which to do their models and their training and their algorithms. But we can also then use and Estancia at that into the business decisions that our customers are trying to make again without the significant cost that they're seeing on that on the public cloud side and in a very secure way because they have the data exactly where they need it. You'll see us continue to do sort of disaster recovery and data protection and those types of scenarios both with our partners and from H P E. So it's exciting to just understand that now you're going to have the tools and resources so you can actually focus on those business outcomes versus how do I protect the data? Where do I start, how do I get my model set up, etcetera. All that becomes automated and self service. You mentioned earlier >>When you talk to customers Keith one of the big sort of challenges that you're addressing. What's the typical, there was no typical but the but the real nuts that they're trying to crack is it financial? We want to move from Capex to opec's is that hey we want this cloud model but we can't do it in the public cloud for a variety of reasons, edicts, organization leaders or we want to modernize our our state. What are the real sort of sticking points that you're addressing with Green Lake? >>Yeah, I think it's threefold and you sort of touched on those. So one is, it really does start with modernization. Hey, you know, we've got to take costs out of the equation. We've got to reduce our carbon footprint. We've got to automate these things because we have limited resources and how do we maximize the ones that we have? And so I mentioned earlier, getting out of the data center, modernizing our apps, really monetizing our data. So I think that's number one. Number two is what you said as well, which is, hey look, I don't need to have all these capital assets. I don't want to be in charge of managing all all these assets. I just want the capability and so being able to sell them that service that says, hey, we can, we can do X number of desktops for your V. D. I. We can run your S. A. P. Environment or we can make sure that you have the, the analytics structure set up to be able to run your models that becomes super compelling and it frees up a lot of resources in cash on that front as well. And then I think the third thing is what you said, which is the world is hybrid. And so I need to find out what's going to run best in my on prem environment and what's going to run best up in the cloud. And I want to be able to optimize that so that I'm not wasting costs in one place or the other, and I want to be able to govern and govern that holistically. So I have the ability to see what's happening end to end across that so I can manage my business most effectively. So I think those are the three big things that people are really excited about with Green Lake as they enable those things. Um and you know, the reality is that it also means that they have a new partner to help them really think through how can they move forward? So it's not them by themselves. Uh It's really in a one plus one equals three type scenario and then you bring the ecosystem in and now you've got, you know, things working really well. So, >>so big enterprise tech, it's like, it's like the NFL is a sort of a copycat league. And so what, you know what I'm saying? But you guys all got >>big, yeah, >>you've got great resources, hey, this West Coast office exactly is gonna work. We're gonna get a short passing game going. And so that happened. So I feel like, okay, you've raised the bar now on as a service and that's gonna become table stakes. Um you know, it's got a lot of work to get there. I know, and it's a it's a journey, but but when you think about the future uh for H. P. E. Uh what's exciting you the most? >>I think what's exciting me the most is this the reaction that we're seeing with customers because in essence it gets them out of the bits and bytes and speeds and feeds and you know, um >>you >>know, component goo and really gets into business value, business outcomes sls and, and that's what they're looking for because what they're trying to do is break out of, you know that day to day and be able to really focus on the future and where they're going. So I think that's one, I think the second big thing is as you see all these things come together, um you know, we're able to basically provide customers with, I would say a mindset that's like, hey, I can do this holistically, but I can always pick and choose the best that I want and if I ramp up, I have capacity. If I ramp down, I don't have to pay for first scenarios. And so I'm getting the best of both worlds across that piece of it. And then third is I mentioned it earlier. But this whole relationship thing is so important because you know, this isn't about technology anymore. As much as it it is about what's the value that you're going to get out of that technology. And how does that help us move the company and the world forward? Like I love the fact that H. P. E. Was so involved in this pandemic. >>You know, >>with our systems were able to actually uh to run a set of of algorithms and analysis on how to, you know, find a vaccine on how to how to address the things that are going forward. You've seen us now up in space and as we, we broaden our frontier and so as a company you're seeing technology turned into things that are truly helping the world go forward. I think that's exciting as well. >>Yeah. Space. It's like the ultimate edge. >>I >>like you said to me if I take it, it's not not about ports and Mick, nips and gigabytes anymore. It's about the outcome. You mentioned before the S L. A. Um, you know, the thing about, you know, think about virtual, it's great. We have to get in the plane. Its downside. We all know we can't hang out, you know, afterwards, you know, have a drink or you know, chit chat about what's going on in the world, but we can't reach a lot more people. But the other downside of virtual is, you know, you don't have the hallway track. It's not like, hey, did you check out that, that demo on IOT? It's really cool. Where is that? So give us the hallway track. How can folks learn more about discover where would you direct folks? >>You bet. You know, I'm doing a full spot. Obviously let me start with at the top right Antonio Neri our ceo he's going to lay out the whole strategy and then I'll have a spotlight. It's about a 30 minute deep dive on all of these things that that you and I just talked about and then we've got a bunch of breakout sessions were doing some with our partners like Nutanix and others, um, Microsoft as well as we talk about, we didn't really touch on that, but you know, we have a strong partnership with the hyper scholars with Microsoft and with others because in essence customers are expecting an integrated solution that's hybrid. And so, you know, we're showcasing all of that with the with the discover breakouts as well and they're available on demand. We have a huge opportunity with respect to that, so really excited and you know, frankly we're here to help, like I hope people understand this is our opportunity to help you be successful and so please know that our ears are wide open to hear what the challenges are and we're ready to help customers as they needed. >>I'm glad you mentioned the partnership with Microsoft and other hyper skills. I feel like keith, the the Hyper scale is giving us a gift. They've spent last year they spent over $100 billion on Capex build out. That is like, it's like the internet. Thank you. >>Now we're gonna build on >>top of it, we're gonna build an abstraction layer that hides all that underlying complexity. We're gonna connect things and and that's really your job. That's really kind of what you're bringing to the table I think with Green Lake and some of these innovations. So >>I really >>appreciate it. Go ahead please. >>I appreciate the time as well. It's always a pleasure and it's always exciting to get a chance to share with you and and as always, any time you don't want me back, I'm happy to happy to join. Alright, >>would love to do that. So appreciate that. And thank you for spending some time with us. Stay tuned for more great coverage from HPD discovered 21 everything is available on demand as well as the that is the other good thing about virtually go back and watch all this content. This is Dave Volonte for the cube the leader in enterprise tech coverage. Be right back

>>Hello and welcome to the cubes coverage of dr khan 2021. I'm john Kerry, host of the cube agent I own L. C. Ceo and co founder chairman of Morantes cube alumni Adrian Great to see you. Thanks for coming on the cube here for dr khan coverage. Good to see you. Hey >>john nice to see. You gotta do. >>So obviously open source innovation continues. You guys are at the forefront of it. Great to see you what's new Miranda's, give us the update on what's happening. >>Well, I mean what's, what's interesting is we've had one of the best years ever last year and it's very much more continuous, you know, into this year. It's pretty fantastic. We wanted about 160 new customers. Kubernetes is definitely on a tear. We see customers doing bigger and bigger and more exciting things, which is absolutely great to say lens is getting tremendous destruction and I think we have a five fold increase in user base within a year. So it's a lot of fun Right now, customers are definitely pushing the boundaries of what benefits can do. And they want to get the cloud native infrastructure and they want to get there faster and they want to be big and exciting things. And we are so happy to be part of the right. >>You guys are investing in brand new open source solutions for customers. Give us an update on on why and why do they matter for your customer? >>Well, there are, let me unpack this a little bit and there are really two elements to this. One is wide. Open Source and what's new. What matters. So the open source is not new, but open source is being embraced more and more heavily. Bye bye companies everywhere because just a very flexible and cost efficient and highly innovative way to to use innovation and to continue software and a lot of innovation these days is happening the open source communities, which is why it's super exciting for many, many users now. What's new with us? I think there are two really terrific things that we brought the market that we see, get a lot of interest and attention from our customers and create value. One is this idea of delivering, including the infrastructure that's been in space as a service for some of the largest news cases out there. Very large enterprises. We want to have a cloud experience on prime just like they have it in public clouds. That is absolutely fantastic. And that's new and different and very, very exciting. Customs. The second thing that's new and compelling and exciting is the is lands which is this kubernetes, i. e. that has empowered in the meantime, close to 180,000 communities, developers around the world to make it much much easier to take advantage of genetics. So you can think of it as a I. D. And a D. Bugger for anybody who is using genetics on public clouds or on on private infrastructure. That is getting tremendous traction and adoption. >>The interest in kubernetes has been unbelievable. I mean in coop con we saw kubernetes almost become boring in the sense of like it's everyone's using it and there's still now it's enabling a lot more cloud native development. Why does that lens matter what is the benefit? Because that's that's a killer opportunity because kubernetes is actively being adopted. The general consensus is it's delivering the value. >>Yeah. So let me unpack this in two aspects why Wise Bennett is important, why people adopting it and then how it lands adding value on top of it for people who want to use humanity's common. It is tremendously important is because it solves some very, very fundamental problems for developers and operators when building cloud native applications. These are problems that are very essential to actually operating in production but are really unpleasant people to solve, like availability, scalability, reusability of services. So all of that with amenities comes right out of the box and developers no longer have to worry about it. And at the same time, the benefits gives you a standard where you can build apps on public clouds and then move them on prem or build them on trend with them on public clouds and anywhere in between. So it gives a kind of this universal cloud native standard that you as a developer can rely on. And that's extremely valuable for developers. We all remember from the java times when java came online, people really value this idea of white ones run anywhere and that's exactly what benefits does for you in a clown in the world. So it's extremely screaming valuable for people. Um now how does let's add value in this context is also very exciting. So what's happening when you build these applications on a minute? This is that you have many, many services which interact with each other in fairly complex and sometimes unpredictable ways and they're also very much interact with the infrastructure. So you have you can you can imagine kind of this jungle this label building of many different cloud native services working together to build your app, run your app well, how are you going to navigate that and debug that as a developer as you build and optimize your code. So what lengths does it gives you kind of like a real time poppet of pounds of console. You can imagine like you're a fighter pilot in this jet and you have all these instruments kind of coming out here and gives you like this fantastic real time situational awareness. So you can very quickly figure out what is it that you need to do? Either fixing a bug in your application or optimize the performance of the code of making more your rival fixing security issues. And it makes it extremely easy for developers to use. Right? But this tradition has been hard to use complicated, this makes it super fast, easy, have a lot of fun. >>You know, that is really the great theme about this conference this year and your point exactly is developer experience making it simpler and easier. Okay. And innovative is really hits the mark on productivity. I mean and that's really been a key part. So I think that's why I think people are so excited about kubernetes because it's not like some other technologies that had all the setup requirement and making things easier to get stood up and manage. Its huge. So congratulations. A great point, great call out there, great insight. The next question to ask you is you guys have coined the term software factory. Um, yeah, this kind of plays into this. If you have all the services, you can roll them up together with lens and those tools, it's gonna be easier, more productive. So that means it's more software, open source is the software factory to what does that term mean? And how >>it is leverage. Yeah, So here's what it means to us. And so, as you know, today, Soft is being produced by two groups working together to build software, uh, certainly the poor people are the developments, these are the people who create the core functionality. Imagine all the software should be architected and ultimately ship the code right? And maintain the code, but the developers today don't operate just by themselves. They have their psychics, they have their friends for often platform engineering and platform engineers. These are the people who are helping developers, you know, make some of the most important choices as to which platform states we should use, which services they should use, how they should think about governance. How should they think about cloud infrastructure they should use, which open source libraries they should use. How often they should be fresh those libraries and support. So this platform engineers create if you want the factory, the substrate and the automation, which allows these developers to be highly productive. And the analogy want to make is the chip design, right. If you imagine ship design today, you take advantage of a lot of software, a lot of tooling and a lot of free package libraries. You get your job done, you're not doing it by yourself. Uh just wiring transistors together or logical elements. You do it using a massive amount of automation and software, like recent polls. So that's that's what we aim to provide you to customers because what we discovered is that customers, I don't want to be in the business of buildings off the factories, They don't want to be in the business or building platform engineering teams. If they can avoid it, they just do it because they have no choice. But it's difficult for them to do. It's cumbersome, it's expensive. It's a one off. It really doesn't create any unique business value because the platform engineering for a bank is very similar to the platform engineering for, let's say, an oil gas company or the insurance company. Um So we do it for them turnkey as a service. So they can be focusing on what Madison's for that. >>That's a great inside. I love that platform engineering, enabling software developers because, you know, look at sas throwing features together. Being a feature developer is cool. And and and the old days of platform was the full stack developer. And now you have this notion of platform as a service in a way, in this kind of new way. What's different agents? You've seen these waves of innovation? Certainly an open source that we've been covering your career for over a decade uh with more Anderson and open stick and others. This idea of a platform that enables software. What's changed now about this new substrate, you mentioned what's different than the old platform model? >>Uh That's a wonderful question. Uh a couple of things are different. So the first thing that's different is the openness and uh, and that everything is based on open source frameworks as opposed to platforms that we that are highly opinionated and, and I lock in. So I think that's that's a very, very fundamental difference. If you're looking at the initial kind of platform as a service approaches, there were there were extremely opinionated and very rigid and not always open source or just a combination between open source and proprietary. So that's one very big difference. The second very big difference is the emphasis on, and it goes along with the first one, the emphasis on um, multi cloud and infrastructure independence, where a platform is not wedded to a particular stack, where it's a AWS stack or a uh, an Azure stack or the EMR stack. And, and but it's truly a layer above. That's completely open source center. >>Yeah. >>And the third thing that is different is the idea that it's not just the software, the software alone will not do the job, you need the software and the content and the support and the expertise. If you're looking at how platform engineering is done at the large company like Apple, for example, facebook, it's really always the combination of those three things. It's the automation framework, the software, It's the content, the open source libraries or any other libraries that you create. And then it's the expertise that goes all this together and it's being offered to developers to be able to take advantage of this like soft factory. So I think these are the major differences in terms of where we are today was five years ago, 10 years ago. >>Thank you for unpacking that for I think that's a great uh great captures the shift and value. This brings up my next uh question for you because you know, you take that to the next level. DeVOps is now also graduating to a whole another level. The future of devops uh and software engineering more and more around kubernetes and your tools like lens and others managing the point. What is the new role of devops? Obviously Deb see cops but devops is now changing to What's the future of devops in your opinion? >>Well, I believe that there is going to become more and more integrated where our option is going to become uh something like Zero Arts, where are you going to be fully automated And something that's being delivered entirely through software and developers will be able to focus entirely, on, on creating and shipping code. I think that's the major, that's a major change that's happening. The problem is still yet I think to be solved like 100% correctly is the challenge of the last mile. like deploying that code on on on the infrastructure and making sure that he's performing correctly to the sls and optimizing everything. I also believe that the complexity veneta is very powerful by the same time offers a lot of room for complexity. There are many knobs and dials that you can turn in these microservices based architecture. And what we're discovering now is that this complexity kind of exceeds the ability of the individual developer or even a group of developers who constantly optimize things. So I believe what we will see is a I machine learning, taking charge of optimizing a lot of parameters, operating parameters around the applications and that unemployment benefits to ensure those applications perform to the expectations of the illness. And that might mean performing to a very high standard security. Or it might mean performing to a very a low latency in certain geography. Might mean performing too a very low cost structure that you can expect and those things can change over time. Right? So this challenge of operating an application introduction Burnett is substrate is I think dramatically higher than on just additional cloud infrastructure or virtualization. Because you have so many services inter operating with each other and so many different parameters you can set for machine learning and Ai >>I love the machine learning. Ai and I'd love to just get your thoughts on because I love the Zero ops narrative Because that's day one zero ops now that you're here day to being discussed and people are also hyping up, you know, ai Ops and other things. But you know this notion of day to, okay, I'm shipping stuff in the cloud and I have to have zero ops on day 234 et cetera. Uh, what's your take on that? Because that seems to be a hot air that customers and enterprises are getting in and understanding the new wave, writing it and then going, wait a minute pushing new code that's breaking something over there I built months ago. So this is just notion of day to obstacle. But again, if you want to be zero ops, it's gonna be every day. >>Oh, I think you hit the nail on the head. I don't think there's going to be a difference between they want the zero they want and today chair, I think every day is going to be the zero. And the reason for that is because people will be shipping all the time. So your application will change all the time. So the application will always be fresh, so it will always be there zero. So zero ops has to be there all the time. Not just in the birthday. >>Great slogan! Every day is day zero, which means it's going well. I mean there's no no problems. So I gotta ask you the question was one of the big things that's coming up as well as this idea of an SRE not new to devops world, but as enterprises start to get into an SRE role where with hybrid and now edge becoming people not just industrial, um there's been a lot of activity going on a distributed basis. So you're gonna need to have this kind of notion of large scale and 00 ops, which essentially means automation, all those things you mentioned, >>not everyone can >>afford that. Um Not every company can afford to have you know hardcore devops groups to manage and their release process, all that stuff. So how are you helping customers and how do you see this problem being solved? Because this is the accelerant people want, they want the the easy button, they want the zero ops but they just they don't they can't pipeline people fast enough to do this role. >>Yeah. What you're describing is the central differentiator we bring to customers is this idea of as a service experience with guaranteed outcomes. So that's what makes us different versus the traditional enterprise infrastructure software model where people just consume software vendors and system integrate themselves and then are in charge of operations themselves and carrying the technical risks themselves. We deliver everything as a service with guaranteed outcomes through the through cloud native experience. That means guaranteed as L. A. Is predictable outcomes, continuous updates, continuous upgrades. Your on prem infrastructure or your edge infrastructure is going to look and feel and behave exactly like a public cloud experience where you're not going to have to worry about sRS or maintaining the underlying being delivered to you as a service. That's a big part, that's a central part of what makes us different in this space. >>That's great value proposition. Can you just expand give an example of a use case where you guys are doing that? Because this is something that I'm seeing a lot of people looking to go faster. You know speed is good but also it could kill right? So you can break things if you go to a. >>Yeah absolutely. I can give you several examples where we're doing this um very exciting company. So one companies booking dot com booking dot com as a massive on from infrastructure but they also massive public cloud consumer. And they decided they want to bring their own infrastructure to the cloud level of automation, cloud level Sophistication, in other words, they want to have their Aws on brand, they wanted to the old, so eccentric and we're delivering this to them with very high in the cell is exactly as a service turnkey Where there is nothing for them to system in grade or to tune and optimize and operate is being really operating 24/7 guaranteed sls and outcomes by us. Well, combination of soft film expertise that we have at massive scale and to the standards of booking dot com. This is one example, another example and this is a very large company um is the opposite side of the spectrum. You know, because they're not called Mexico super successful. Soft as a service company in the security space, growing in leaps and bounds in very high technical demands and security demands. And they want to have an on prem and cloud infrastructure to complement public clouds. Why? Because security is very important to them. Latency is very important to them. Control the customer experience is very important to them. Cost is very important to them. So for that reason they want that in a network of data centers around the globe And we provide that for them. Turnkey as a service than before seven, which enables them to focus 100% on building their own sense on their the functionality which matters to their customers and not have to worry about the underlying cloud infrastructure in their data centers. All of that gets provided to them has guaranteed about experience to their end users. So this would be the examples where we're doing a >>great service. People are looking for a great job. Adrian, Great to see you. Thank you for coming on the cube here, doc are gone 2021. Um, take a minute to put a plug in for the company. What are you guys up to? What you're looking for hiring? I'll see. You got great tracks with customers, congratulates on lens. Um give a quick update on what's going >>on. Happy happy to give it up in the company. So he, here are the highlights. It was super excited about about what we achieved last year and then what we're up to this year. So last year, what we're proud of is despite Covid, we haven't laid off a single person. We kept all the staff and we hired staff. We have gained 160 new customers, many of them, some of the world's largest and best companies and 300 of all existing customers have expanded their business with us last year, which is fantastic. We also had a very strong financial physical cash flow positive. It was a tremendous, tremendous here for us. Uh, this year is very much growth here for us and we would incredible focus on customer outcomes and customer experience. So what we are really, really digging in super hard on is to give the customers the technology and the services that enable them to get to ship software faster and easier to dramatically increase the productivity of dissolved the development efforts on any cloud infrastructure on crime and public clouds using containers and is and to do that as scale. So we're extremely focused on customer outcomes, custom experience and then the innovation is required to make that happen. So you will continue to see a lot of innovation around lens. So the last better release of lens that we brought about has now a cloud service and have a lot of feature where you can share all your cloud automation with your bodies, in, in uh, in uh, in your development team. So the lens used to be a single user product. Now it's a multi user and team based product, which is fantastic, continues to grow very quickly. And then container cloud as a service. Uh, it's a very big part that we're meeting on the infrastructure side. Are you get quite >>the open source cloud company. Adrian. Congratulations. We've been again following even on the many waves of innovation. Open stack, large scale open source software. Congratulations. >>Uh chris >>Thank you very much for coming on the cube. >>Yeah. >>Okay. Dr khan 2021 cube coverage. I'm john furrier here where the Gi Enel Ceo, co founder and chairman of Miranda's sharing his perspective on the open source innovation with their process and also key trends in the industry that is changing the game in accelerating cloud value cloud scales. Cloud native applications. Thanks for watching. Mhm.

>>From around the globe. It's the Cube with digital coverage of IBM think 2021 brought to you >>by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual. I'm john ferrier host of the Q. We've got a great guest here brian Bouchard, co founder president and ceo of Allah credit brian, great to see you um promoting it all the way from Puerto rico to Palo Alto. >>Great to >>see. First of all. Thanks for having me. I really appreciate the opportunity. >>Yeah great, Great to see you. Thanks for coming on. Um first of all, before we get into what you guys do and how this all ties in to think what do you guys do? It Alex Burnett, Why the name uh is good, you're at the top of the list and alphabetically, but tell us the secret behind the name and what you guys do. >>So first of all, a crochet is based on the root word alacrity, which means a prompt and will prompt a joyous prompt itude excuse me to achieve a common goal. So we ultimately our network of >>individuals with >>the traits of alacrity. So eloquent. So that's our name. >>Great. So what's your relation with IBM and how you guys been able to leverage the partnership program in the marketplace take us through the relationship >>so Well, first of all, L. A. Quartet is a platinum IBM business partner and was awarded recently the 2020 IBM north american Partner of the Year award. And we were selected among 1600 other business partners across North America. We've been actually a consulting an IT. consulting company for almost 20 years now and we were founded in 2002 in Palo Alto. And we have focused specifically on cybersecurity since 2013. What is >>Right, what are some of the things you guys are working on? Because obviously, you know, the business is hot right now, everyone's kind of looking at Covid saying we're gonna double down on the most critical projects and no time for leisurely activities when it comes to I T and cloud scale projects, you know, mission critical stuff is happening. What are you guys working on? >>So we're focused on cybersecurity. Our our security services really complement IBM suite of security solutions and cover the full spectrum from our research and penetration testing, which helps identify vulnerabilities before it reach occurs. And we also have managed security services which helps prevent detect and remediate attacks in real time. >>And then finally, we also have a security staffing division and a software resale division which kind of rounds out the full amount of offerings that we have to provide protection for our clients. >>What are some of the biggest challenges you guys have as a business and house IBM helping you address those? >>Well, as you know, john, we all know that the importance of cyber security in today's world, so it's increasing in both demand and importance and it's not expected to wait any time soon. Cyber attacks are on the rise and there's >>no >>Uh there's no expected end in sight to this and in fact just this week on 60 minutes, uh, the Jay Powell, the chairman of the Federal Reserve Board, he noted that cyber attacks were the number one threat to the stability of the US. economy. >>Also this week, >>a public school in Buffalo new york was hacked with ransomware >>and the school, this uh, >>the school district is just contemplating you're paying the ransom to the hackers. So there's literally thousands of these attacks happening every day, whether it's in a local school district or state government or an enterprise, even if you don't hear about them, they're happening. And adding to the complexity that the cyber Attackers pose is the complexity of the actual cybersecurity tools themselves. There isn't a single solution provider or single technology that could ensure a company security. Our customers need to work with many different companies and disconnected tools and processes to build an individual strategy that can adequately protect their organizations. >>You know, I love this conversation whenever I talked to practitioners, uh, cybersecurity, you know, first of all, they're super smart, usually cyber punks, and they also have some kind of eclectic background, but more importantly, is that there's different approaches in terms of what you hear. Do you do you put more if you add more firefighters so to speak, to put out the fires and solve the problems? Or do you spend your time preventing the fires from happening in the first place? You know, and you know, the buildings are burning down, Don't make a fire fire uh don't make would make fire resistance, you know, more of a priority. So there's less fires, not firefighters. So it's that balance. You throw more firefighters at the problem or do you make the supply or the material, the business fireproof? What's your take on that? >>Well, it kind of works >>both ways. I mean, we've seen customers want to, they really want choice. They >>wanna, in some >>cases they want to be the firefighter and in some cases they want the firefighter to come in and solve their problems. So >>the common problem set that we're seeing with our our customers encounter is that they struggle one with too many disparate tools and then they also have too much data being collected by all these disparate tools and then they have a lack of talent in their environment to manage their environment. So what we've done at Lacqua net is we've taken our cybersecurity practice and we've really uh specifically tailored our offerings to address these court challenges. So first to address the too many disparate tools problem, uh We've been recommending that our clients look at security platforms like the IBM cloud pack for security. The IBM cloud fax for security is built on a security platform that allows interoperability across various security tools using open standards. So our customers have been responding extremely positively to this approach and look at it as a way to future proof their investments >>and begin taking advantage of >>interoperability with >>hand tools integration. >>Talk about what you see your business going with with this because you know there's not a shortage of of need um demand. Um How are you guys flexing with the market? Uh What's the strategy are you going to use technology enablement? You're gonna more human driven brian how do you see your business of unfolding >>Well? Actually really good. We're doing very well. I mean obviously we've made the top business partner for IBM in 2020. Um we have some significant growth and a lot of interest I think we really attacked the market in a good strategy which was to help defragment the market if you will. There's a lot of point solutions and a lot of point vendors that you know they they spent uh specialize in one piece of the whole problem and what we've decided to do is find them the highest party list. Every see so and see IO has a tick list. So >>they have that >>you know uh first thing we need we need a sim we need a E. D. >>Are we need a >>managed service? We need um what's the third solution that we're doing? So we need some new talent in house. So we actually have the added that as well. So we added a security staffing uh division to help that piece of it as well. So to give you an idea of the cybersecurity market size, It was valued at 150 billion in 2019. And that is expected to grow to 300 billion by 2027. >>And Akron is well positioned to consolidate the many fragmented aspects of the security marketplace and offer our customers more integrated and easier to manage solutions. And we will continue to help our customers select the best suite of solutions to address all types of cyber security, cyber security threats. >>You know, it's such a really important point you're making because, you know, the tools just piled up in the tool shed, I call it like that, It's like, it's like you don't even know what's in there anymore and then you've got to support them, then the world's changed, get cloud native, the service area is increasing and then the CSOs are also challenged. Do I have any clouds? Do I build on? Do I optimize my development teams for AWS or Azure? Now, that's kind of a factor. So you have all this tooling going on? They're building their own stuff, they're building their own core competency. And yet the sea so still needs to be like maintaining kind of like a relevance list. That's almost like a stock market for the, for the products you're providing, that it sounds like you're providing that kind of service. >>Uh, yeah, as well. Right? We distill all of the products that are out there, there's thousands of cybersecurity products out there in the marketplace and we kind of do all that distillation for the customer we find using, you know, using a combination of things we use uh Forrester and Gartner and all the market analysts to shortlist are, are solutions that we offer customers. But then we also use our experience. And so through since 2013, we've been deploying these solutions across organizations and corporations across America and we've gained a large body of experience and we can take that experience and knowledge to our customers and help them make some good decisions. So they don't have to make them go through the pitfalls that many companies do when selecting these types of solutions. >>Well, congratulations, got a great business and uh you know, that's just a basic, starts making things easier for the sea. So more so they can be safe and secure in their environment. It's funny, you know, cyber warfare, you know the private company have to fight their own battles, going to build their own armies. Certainly the government's not helping them and they're confused even know how to handle all this stuff. So they didn't they need your service. I'm just curious as this continues to unfold and you start to see much more of a holistic view. What's the IBM angle in here? Why are you such a big partner of theirs? Is it because their customers are working with you? They're bringing you into business? Is it because you have an affinity towards some of their products? What's the connection with IBM, >>all of the above? So >>I think it probably started with our affinity to IBM P radar products and we have a we have a lot of expertise in that in that solution. Um, so >>that's that's where it >>started. And then I think I B. M. S leadership in this space has been, Yeah, >>remarkable. Really. So like what's happening now with the IBM compaq for security, building a security platform to allow all these points solutions to work together. Uh that's the road map we want to put our customers on because we believe that's the that's the future for this, this uh, this marketplace >>and the vision of hybrid cloud having that underpinning be with red hat, it's a Lennox Colonel model of >>all things you can you can run it on. Sure. I've been plowed uh aws it's portable. Yeah. All this openness, as you probably know, uh, cybersecurity is really a laggard in the security and the information technology space as far as adopting open standards and IBM is I think leading that charge and you'll be able to have a force multiplier >>uh >>with open standards in the space. >>Open innovation with open source is incredible. I mean if you if if open source can embrace a common platform and build that kind of control, playing and openness to allow thriving companies to just build out, then you have an entire hybrid distributed >>architecture. Yeah, well, I think companies want to use the best in breed. So when we, when we show these solutions to customers, they want the best in breed, they always say, I don't, when it comes to security, they don't want second best. They want the best that's out there because they're securing their crown jewels. So that makes sense. Um, so the problem is having all these different disparate solutions that are all top in their category, none of them talk to each other so we need to address that problem because without that being solved this is just going to be a more, it's going to compound the complexity of the problems we solve day to day, >>awesome, congratulations brian, great story. Um you know entrepreneur built a great business over the years um I think the products amazing, I think that's exactly what the market needs and it just shows you what the ecosystems all about. This is the power of the ecosystem. You know 1000 flowers are blooming, you got a great product. IBM is helping as well. Good partnership network effect builds in and and still a lot more to do. Congratulations. >>Absolutely. Okay thank you very much >>brian thanks >>for coming on the q appreciate it. I'm Sean Fourier with IBM thinks 2021 virtual coverage. Thanks for watching. Mhm.

>>from >>around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel AWS and our community partners. >>Hey, welcome back. You're ready, Jeffrey here with the Cube coming to you from our Palo Alto studios with our continuing coverage of aws reinvent 2020 the virtual event. We're excited to be back. We've been coming to reinvent for years and years and years, I think since 2013 1st years virtual But that's the way it is. And we're gonna jump into Cloud and government and D o d. And we're really excited to have our next guest. You know a lot about the topic. We have Robert Grote. He is the VP of technology and strategy from spark Tronics coming to us from Virginia. Great to see you, Robert. >>Great. Thank you. >>And joining him is Anthony Voltaggio, the CTO of Smartronix. Anthony. Good to see you as well. Thank you. Great. So let's jump into it. I think Rob, we had you on a couple of years ago. I I looked it up. It was early October 18 and you guys were getting a lot of success with cloud in government and I think it was before the Jedi and all that other stuff was going down. Two years is forever in cloud time. I wonder if you could just share a little bit about how the market has changed since I think it was February or March of 2018 to now late November 2020 in terms of cloud and government and Department of Defense. And you're highly regulated customers. >>Sure, I think one of the things that's changed is that security certainly used to be a headwind on bond. Now we're actually seeing it more of a tailwind where our customers, especially are heavily regulated, compliance driven customers in the public sector and the D. O. D are really looking at new ways of embracing the value of the cloud. So one of the things that has changed is that maybe two years ago, we were looking at How do we move digital estate from on premise into the cloud environment? We're now we're looking at. How do we actually achieve value in the cloud? How do we allow our customers to optimize their portfolio? How do they modernize their application footprint in a in a secure way and some of the things that we focused on, particularly smartronix, is how do we remove that friction that exists when a new kind of legacy customer really wants to transform the way that they deliver services. So we built, uh, capabilities that really allow them to more rapidly migrate their services into the cloud environment. We created and have an 80 0, now for a cloud assured manage services, which means that our customers who want to meet the rigorous security mandates now have that ability to utilize our services when they're deploying these services. And it really enables them to focus on the development of the modernization, you know, versus having to do the cumbersome components of security compliance and operation on def. You if you look at what we're trying to build and trying Thio intersect with where our customers we're going, they really want to get to that pace of innovation that the cloud provides. Um, you know, I think I've said this before to the Cube that the slope of disruption is correlated to the pace of innovation. And if you continue to build technical debt like our customers may have done in the past, they're gonna fall behind and it might be okay, um, for, you know, Blockbuster to fall behind the Netflix or for uber disrupted industry. But for our customers, there's national security consequences when they fall behind. So we've got to create a platform and a capability that enables them to innovate on, deliver very agile services rapidly. >>And then I wanna go. I wanna go to you because I think Robin, in your last interview, talked about your customers very secure, highly regulated, compliance driven environments. Right? And? And to be clear, you guys sell a lot to Department of Defense and all the various branches of the U. S. Military etcetera. You know, Anthony, a lot of talk of digital transformation on the commercial side and and people going right And then, of course, all the jokes and memes about Covic, you know, being the accelerator to that for >>your >>customers. The accelerators thio at modernization in the digital transformation are very different. It's not about necessarily the competitors down the street, but it's about some nasty competitors that want to cause this real harm. How how have they adopted? You know, kind of this this digital transformation and what's different in terms of accelerating it in your customer base. >>We're looking our defense customers and national security customers. Absolutely. The velocity and scale of cloud is becoming an enabler again. Looking at those information work was that they have looking at the nation state adversaries that we're facing right now. Information is information warfare. So if we're not ready to scale, innovate at much higher velocity than we have in the past, we're gonna become victim to those attacks. Methodologies that score matters of using so that the scale and power of the cloud as well is that tailwind of all these authorized services that are offered by Amazon that are already at the federal federal high and D o D. Impact. Those for higher, up to impact level six really, really enable them to go ahead and meet that mission. But mad and speed and agility. They need toe mash that for necessary, >>right? Well lets you just talked about impact level, and I want to dig into that for a little bit because in doing research on you guys and a lot of the solutions that customers you talk about, there's there's constant conversation about these impact levels Impact level for impact level five Impact Level six Again. It's highly regulated industry. You guys have a very, very high bar that you have to hit in your solutions. What does impact level mean and why is it important? And how are you basically working your way up the chart, which I assume is a much more impactful? Not not no pun intended, but much more significant solution delivery. >>So impact levels really have to do with information risk. So what is the level of information that that system is processing? So as you move up the impact levels, that information becomes more more critical to national security. So on impact Level four system may have to do with standard mission operations and Ministry of Task, etcetera, where when you go up the staff to impeccable five and even to impact level six or higher, you're really dealing with, let's say, in the d. O d, uh, perspective, the horror fighter eso. Now you're dealing with where that war fighters deployed the capabilities of the water fighter that they're leveraging To fight that battle against the adversary eso you have to put more and more rigorous controls around that information to ensure the adversaries can gain the tactical advantage over our war fighters. >>It's really interesting. You know how all these systems are really designed? Uh, toe work together. And as you said, kind of for that, that warfighter, if you you know, you you watch anything on defense, it's kind of the point into the stick, but there's a whole lot of support behind that behind that person at the very end to help them get the information to be successful in their job and support them. Um, etcetera. But I'm curious. Have you seen a change in attitude in terms of not only the data and the information in the systems as a support for the war fighter, but in fact, that data itself being a significant asset as well as a significant target, probably bigger and more valuable than an aircraft carrier or any other kind of traditional defense assets? >>Yeah, I would say we've definitely seen that change. Our our our customers air really looking at data and aggregate and when you're when you're building a cloud profile when you're building a portfolio systems, um, and it's all in a single type environment or an enclave where you can unlock the value of that data, the aggregate of all of those applications. The aggregate of that data has increased value, and that allows you to do a lot more things with it. Allows you to innovate a lot. Mawr toe. Learn more about that data on We're seeing our customers really looking at. How can they unlock that value? Whether it's looking at improving the supply chain, looking at data feeds that they're able to aggregate from commercial sources as well as sources that they're getting in a distributed fashion or whether it's just, you know, looking at, how can they improve the efficiency of of delivering services to the to the warfighter? Um, it really is about unlocking that value of data. So that's why it's also important that we have capabilities that protect that data. And then we provide more capabilities that allow our customers to be able to leverage as the C. S. P s as AWS innovates. Allow them to leverage these new capabilities much more rapidly than they could in the past, >>right? Well, and you talk about technical debt and you know there's kind of technical dead and There's application dead, and there's kind of application portfolio stuff that that you have right that may or may not work well, that's probably running and has been running for years. That doesn't necessarily all have to be modernized. You said Sometimes you know it's it's best to leave. Leave it as it lies. How are you helping people figure out? You know what, what to modernize, what to leave it as as it is. And then you know, or you know how much effort should really be spent on new on new applications and new development. You know, taking taking advantage of the latest because that's kind of a tricky portfolio strategy. And as you said, there's a whole lot of legacy stuff that's still running in those old data centers. >>You mentioned the key word there and that strategy. Our our customers are looking to us to help them evaluate their portfolio, determine what things that they should be doing next, the sequencing events and how they can unlock some of those values in the cloud. So, you know, one of the things that we talk about is that ability to even if you're taking stuff from a legacy environment and moving that estate into the cloud. There's certain things that you can do to opportunistically re factor and get value out of the cloud. You don't have to rewrite the application every time there's things that you can do to just re factor. Um, and one of those components is that when you look at cloud and you look at the a p I nature of the cloud, um, transparency is the gift of the cloud. And automation is how you get value out of that gift. And when when you look at how automation and transparency you're kind of tied together for our customers and you look at the fact that again everything's in a P I based, you know, with, you know, full non repudiation who made that call when they made that call? You've got an ability to create this autonomic response system, and this is This is a key part of application modernization, giving that customer the ability to rapidly respond to an event, create automation, create run books, use you know, advanced technologies like machine learning for anomaly detection, create, you know, security orchestration, all of those components when you could build that framework. Then your customers can even take some of their legacy assets and be able to utilize, you know, the high value of the cloud and respond to events much faster and in, um, or automated an autonomic manner. >>I love that transparency in automation. And I want to go back to you. Anthony, you've been doing this for a long time. Um, you didn't have these tools at your disposal before, and you didn't have necessarily the automation that you have before. And I think more importantly, you know, interesting thing that Rob you touched on on on your earlier interview a couple of years back, you know, kind of this scale learning something identified by by Bill Chamorro's I once in terms of calling it out where you learn something in one place and you can apply that learning, you know, across many, many places. And then the other piece. I want you to comment on its automation because, as we know, a lot of errors happen from silly things, fat fingers, bad copy paste, putting in a wrong config code. This that and the other. So, by adding mawr and Mawr automation and continuing to kind of remove potential little slip ups that can cause big big problems. It's a really different world that you've got in the tools that you have in your portfolio to offer these solutions up to your clients >>absolutely again, as we've learned MAWR Maura about these repeatable patterns that have happened across our different customers. That allows us to create that run book automation library that then allows our team and our capabilities scale across multiple workloads and kind of like Robert identified earlier. There's a lot of these cognitive services, and I'll take Amazon a specific example. Guard duty. It is a very innovative capability with M. L. A. I behind it that allow you to look at these access patterns and communication patterns of these application workloads and quickly identify threats. But the automation and road book and orchestration that you can build behind this then allows you to leverage that library to immediately respond to these events. When you see a threat and you see that pattern, your your ability to rapidly respond to that and mitigate that threat, Israel allows your business and information systems continue providing no the primary business use case and again in our GOP customer. National security system. Customers dividing to the warfighter complete their mission. >>Yeah, well, what a good and let you give. Give a plug for some of your processes and techniques. You have something that you call fast, um, to help people, you know, go through this decision process. And I think, as you said, Rob, you know, you gotta have some strategy before you start making some decisions. And also, this thing that we're seeing out there called the shift left. Um, what does that mean to you? What does it mean to your customers? Why is that important? Why should people know about it? Start with you, Rob. >>So what? We notice we've been doing cloud services, you know, since 2009, Really? One of the first eight of us public sector partners delivering the first capabilities to that market. And what we noticed is that ah, lot of organizations found it easy to move one or two workloads into the cloud. But they struggled in making a cloud, a true enterprise asset. So we took a step back and we created something that we call foundational agile strategic transformation. And that's fast. It's a It's a program that we developed that allows complex organizations. Security minded organizations understand What are all the foundational things that need to be in place to really treat cloud as an enterprise asset? And it covers much more than just the technical components. It covers the organizational components. It covers all the stakeholders around security. But one of the key things that we've changed in the past couple of years is how do we not only look at, you know, leveraging the cloud is an enterprise asset, But how do we allow them to accelerate how they can get the value out of the cloud, modernize their applications, create thes capabilities? And the shift left component of fast is providing as much capability all the way down to where the developer is, where you have maybe dead set cops when it used to be a developer on one side and operations on the other. Security is kind of a binding function. Now we're talking about how can we create more capability, right at the point of development? How can we shift that capability? And I think the role of the managed service provider is to enable that in an organization provide capability, provide operations capability but also help them in a You know, we use the term SRE quite a bit. Site reliability, engineering. How can we really help them continuously optimize their portfolio and build a set of capabilities and services? So when they're building new applications, they're not adding to their technical debt. >>That's great and so and so, so important. And it's just been so interesting. Toe watch again. A security specifically for Public Cloud in AWS has become from you know, what was potentially a concern and a headwind to now being a tailwind. And all you have to do is go to go to some of the the architectural keynotes my some of my favorites and see the scale in massive investments that they can put into infrastructure. And they can put into security that no single company, unless you have the biggest, biggest ones you know, can possibly invested to be able to leverage that opportunity. And obviously, Teresa Carlson and the Public Sector team have done a really good job and giving you guys the solutions that satisfy the very tight requirements that you're very important customers have. So it's really a great story and really enjoy learning mawr and continued success to you guys And, uh, and your teams and your importance, your customers and all the important stuff that they protect for us. Uh, eso thank you very much. All right. Thank you. All right, well, signing off. That's Robert and Anthony. I'm Jeff. You're watching the Cube. Ongoing coverage of aws reinvent 2020. Thanks for watching. See you next time. Thank you.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, okay. Welcome back to the cubes. Live coverage here. Reinvent 2020 for a W s amazing content happening here within across the industry on digital transformation and more, more important than ever in the public sector has been mawr impacted by anyone during the cove and pandemic. And we're here remotely with the Cube Virtual because of the pandemic. Got a great guest, Kim, a jurist. She's the leader on the U. S. Education, state and local government for a W s public sector Kim, great to see you. Thanks for coming on. Remotely, at least we get to have a remote interview. >>Well, thank you for taking the time. This is This is our world these days, so it's good to be able to connect. >>Well, thanks for coming on. We're doing some specialty programming around public sector, mainly because it's such an important area. Uh, Andy Jassy Esquina, which is for the best conference at large at reinvent talks broadly, but I think it highlights what's going on in your world and that is this facing the truth. Um, this digital transformation has been forced upon us. It's accelerated and it's get busy, busy building or get busy figuring out how it might unwind and mawr education virtual remote if we >>didn't >>have video conference, and this could have been a disaster even further, but certainly has impacted everybody in the government education. How is it impacting share with us? What's going on? >>You know, I think that difficult partisans. When we turned on the news early days there in Cove it it was clear that students weren't learning and citizens couldn't get in contact with their government to ask for support. Um, I would say it was that moment in time where the technical debt that whether your state, local or education, you had to quickly realized that you need to connect with your students and your citizens. But I take a look at how quickly they were able to turn across the US Many of them realized what usually took years, literally turned into innovating overnight to support students as well as those filing for on unemployment claims. And I think that's what we heard a lot of, and those were some of the opportunities that Amazon really took, uh, to our customers said, Hey, we can help you solve these problems with great services such as connect >>you know, Connect came up in the keynote multiple times, and he really spend time on that as a as a disruption slash enabler for value. Can you share how cloud has scaled up some of your customers? I know connects, been pretty prominent in the public sector for Covic support and really has changed in saves lives in many cases. Can you share an example of how it's worked out? >>Absolutely. I mean, Rhode Island is is a great example. They use Amazon connect. They helped the state literally address this massive surgeon of unemployment insurance applications due to Cova 19. But literally the call times and the vines were cut down in What they were able to do is answer the call, not just have it be on a fast busy or a disconnect. Whether it was Department of Labor at Rhode Island, whether it was the state of Kentucky or the state of West Virginia, all those authorities use had to deal with that surge, and they were able to do it successfully and literally, in some cases, overnight to support citizens. That's how quickly they were able to innovate and hit those call centers, Um, effectively. But it's not just about the call center, because keep in mind they would go into those call centers with connect. They were able to actually take those calls from home, and we saw that in education as well. Take a look at L. A unified school district. What they had to do to quickly transition from in person training to supporting these students remotely. They had to do it overnight, and they use connect their asses well, not only to support the students, the teachers or the staff, but they took that opportunity to really continue educating and continue serving. >>You know, one of the things I was talking anti about in my one on one interview before reinvent was necessity is the mother of all invention in these days, and I think that came from a quote from one of your customers, like interviewed when asked, You know how the innovation strategy come about, and that's what they said. They said we needed it really bad, and we had to move quickly and then Andy said in his keynote that everything is on full display right now, meaning that the pandemic is forced one and you can see who's winning and who's not based on where they are in the cloud journey. So have to ask you leaderships a big part of this. What is the trend that you're seeing within your world because, you know, government not known for moving fast. And this is a speed game at this point. Healthcare. A big part of that. You got education. Government. What's >>the >>leadership mindset on innovating right now? And can you share because, yeah, you got some easy, you know, examples. Now the point is, hey, way have connect with people were like productivity opportunity that's now the new normal. So even in life does come back. There's new new things that have been discovered. Is that resonating with your your customers? And can you share the leadership mindset? >>Absolutely. So make no mistake. It was never a question of if it was a question of when the pandemic clearly is accelerating it. But, you know, we've been working with over 6500 government agencies and collaborating with them to really focus on some of their mission critical, um called based services. So and this is the new normal. They recognize it. And it's the foundation that during the pandemic that it's been said to say, Hey, we're going to push and we're gonna push quicker because they were actually able to demonstrate that they could do it. I'll give you an example. It's It's a heartbreaking one from my perspective. Being a mom, um, l. A. County Department of Child and Family Services, They operated their analog child protection hotline. Now the numbers are are unfortunate and staggering. But when you took a look at the peak before the pandemic, the call center received as many as 21,000 reports of child abuse and neglect in a month. During those pick times, up to 100 staff members would log in and literally take 120 back to back calls per hour. Now, when you think about that legacy environment with Amazon connect, they were able to continue the service, continue the support to help these Children and available 24 7, and they were able to do it from their homes. So e mean it gives me chills, just thinking about three unfortunate situations. But they were able to quickly move and and continue to support. Yeah, >>and the thing to I want to just bring up also had a customer I interviewed from Canada. I think they were partner with a censure. They had unemployment checks, they couldn't get out, and entitlement things that were literally checks and connect stood up that in like, record time. He was convinced. He's like he was kind of Amazon fan, but he was kind of still out of Amazon. He was like, I'm convinced we're gonna use Amazon going forward. It was a tipping point for him. There's a lot of these tipping points going on right now. This has been a big theme of this reinvent so far. Yeah, cloud transition, two full cloud value. This is the new normal What? What what what can clients get when they have budget or trying to get budget when they say the benefit? The clouds are what? >>Well, I mean again, use another use case. I'll go back to another example in L. A county. So when you think about l. A county itself, um, I won't give you the exact numbers because I don't know him off the top, but approximately 10 million residents and employs over 100,000 staff again. Look at the cost savings that they saw. So, you know, technical data is a problem. Being able to invest is a challenge because of budgets, but they were able to save 60% in one year from there on prem environment and licensing costs. But the cost is one piece. If you could take 17% fewer calls and you're solving those challenges by using a i N M l. Through the technology of what they were gathering through those calls, it made a huge impact and improved their service to their citizens. So you know it. The cost savings air there. And there are so many examples that states air, recognizing that they need to move quicker because they could take advantage of those costs, especially with some of the budget challenges we're going to see across the U. S. >>And the machine learning examples are off the charts. So, Kim, I gotta ask, you going forward now in reinvent what's the big focus for you and your teams and your customers because you guys are very customer focused. You're working backers from the customers. We hear that on and on what is going on in your customer base? One of the priorities, >>um, priorities for us will always remain on the mission to which our customers are focusing on. If we think about education, the question is, how are they re imagining the the delivery and the success in this new world that we're dealing with? So we'll continue to work and innovate with our partners and with amazing All right, a text that are in our business take a look at blackboard, right? They were able to scale 50 times their normal capacity globally, literally within 24 hours they're looking at How do they continue to innovate to serve? We're gonna work with K through 12 through academic medical centers and research, because when you think about what we need is we need to find that vaccine we need to find the ability to treat and serve. We're focused on those missions with the states, the research and the education teams. >>It's been unusual year learning is changing remote learning, remote work, the workforce, the workplace, the workloads. They're all changing. Onda clouds a big part of it. Um, final question for you. What's the take away for reinvent this year means different. You mentioned some of those highlights. What's the big take away for your audience? >>I think for state local education is it's available. It's now, and they have to serve their students and citizens quit. Um, what they've been able to do in the cloud again? A zay said at the start of the interview. They can now do overnight within minutes and hours and and support their citizens. And they have to do it quickly. So, >>uh, coyote to coyote goodness for the state and local governments to >>absolutely it's going to continue. And I think the important part is focused on the opportunity of innovating and supporting the mission >>Can Great to see you. Thanks for the insight. Thanks for the update. Appreciate it. We'll be following it. A lot of great successes. You guys have been having the Cuban involved in a bunch of them and we'll continue to follow the transformation. Thanks for coming on. >>Thank you. Enjoy Sena. >>Okay. This is the Cube Virtual. I'm John for your host. Thanks for watching more coverage. Walter Wall reinvent 2020 Virtual. Thanks for watching. Yeah,

>>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. Live coverage here for eight of us. Reinvent 2020. Virtual normally were on the show floor getting all of the interviews and talking about the top newsmakers and we have one of them here on the Cube were remote. I'm John for your host of the Cube. George Ellis Eros, GM and director of product manager for AWS. Talking about Wavelength George. Welcome to the remote Cube Cube. Virtual. Thanks for coming on. >>Good to be here. Thanks for having a John >>Eso Andy's Kino. One of the highlights last year, I pointed out that the five g thing is gonna be huge with the L A Wavelength Metro thing going on this year. Same thing. Mawr Proofpoint S'more expansion. Take us through what was announced this year. What's the big update on wavelength? >>Yes, so John Wavelength essentially brings a W services at the edge of the five G network, allowing our AWS customers and developers to reach their own end users and devices. Five devices with very low latency enabling a number off emerging applications ranging from industrial automation and I O. T. All the way to weigh AR VR smart cities, connected vehicles and much more this year we announced earlier in the year the general availability of wavelength in two locations one in the Bay Area and one in the Boston area. And since then we've seen we've been growing with Verizon or five D partner in the U. S. And and increasing that coverage in multiple off the larger U. S cities, including Miami and D. C in New York. And we launched Las Vegas yesterday at Andy's keynote with Verizon. We also announced that we are going toe to have a global footprint with K d D I in Japan launching a wavelength in Tokyo with SK detail SK Telecom in in South Korea or launching indigestion and with Vodafone in London >>so significant its expansion. Um, we used to call these points of presence back in the old days. I don't know what you call them now. I guess they're just zones like you calling them zones, but this really is gonna be a critical edge network, part of the edge, whether it's stadiums, metro area things and the density and the group is awesome. And everyone loves at about five gs. More of a business at less consumer. When you think about it, what has been some of the response as you guys had deployed mawr, What's the feedback? Um, can you take us through what the response has been? What's it been like? What have been some of the observations? >>Yeah, customers air really excited with the promise of five G and really excited to get their hands on these new capabilities that we're offering. Um, And they're telling us, you know, some consistent feedback that we're getting is that they're telling us that they love that they can use the same A W s, a P I S and tools and services that they used today in the region to get their hands on this new capabilities. So that's being pretty pretty consistent. Feedback these off use and the you know, Sometimes customers tell us that within a day they are able to deploy their applications in web. So that's a that's pretty consistent there. We've seen customers across a number of areas arranging, you know, from from manufacturing to healthcare to a ar and VR and broadcasting and live streaming all the way to smart cities and and connected vehicles. So a number of customers in these areas are using wavelength. Some of my favorite you know, examples are in in actually connected vehicles where you really can see that future materialized. You get, you know, customers like LG that are building the completely secularized vehicle, tow everything platform, and customers like safari that allow multiple devices to do, you know, talkto the Waveland, the closest Waveland Zone process. All of those device data streams at the edge. And then, um, it back. You know messages to the drivers, like for emergency situations, or even construct full dynamic maps for consumption off the off the vehicle themselves. >>I mean, it's absolutely awesome. And, you know, one of things that someone Dave Brown yesterday around the C two and the trend with smaller compute. You have the compute relationship at the edge to moving back and forth so I can see those dots connecting and looking forward to see how that plays out. Sure, and it will enable more capabilities. I do want to get your your thoughts, or you could just for the audience and our perspective just define the difference between wavelength and local zones because we know what regions are. Amazon regions are well understood all around the world. But now you have this new concept called locals owns part of wavelength, not part of wavelengths. Are they different technology? Can you just explain? Take him in to exclaim wavelength versus local zones how they work together? >>Yeah, So let me take a step back at AWS. Basically, what we're trying to do is we're trying to enable our customers to reach their end users with low latency and great performance, wherever those end users are and whatever network they're they're using to get connected, whether that's the five g mobile network with the Internet or in I o t Network. So we have a number of products that help our customers do that. And we expect, like, in months off other areas of the AWS platform, that customers are gonna pick and twos and mix and match and combine some of these products toe master use case. So when you're talking about wavelength and local zones, wavelength is about five g. There is obviously a lot off excitement as you said yourself about five g about the promise off those higher throughput. They're Lowell agencies. You know, the large number of devices supported and with wavelengths were enabling our customers toe to make the most of that. You know, of the five G technology and toe work on these emerging new use cases and applications that we talked about When it comes to local zones, we're talking more about extending AWS out two more locations. So if you think about you mentioned AWS regions, we have 24 regions in another five coming. Those are worldwide and enabled most of our customers to run their workloads. You know all of their workloads with low latency and adequate performance across the world. But we are hearing from customers that they want AWS in more locations. So local zones basically bring a W S extend those regions to more locations by bringing a W s closer to population I t and industrial centers. You know, l A is a great example of that. We launched the lay last year toe to local zones in L. A and toe toe a mainly at the media and entertainment customers that are, you know, in the L. A Metro, and we've seen customers like Netflix, for example, moving their artist workstations to the local zones. If they were to move that somewhere, you know, to the cloud somewhere further out the Laden's, he might have been too much for their ass artists work clothes and having some local AWS in the L. A. Metro allows them to finally move those workstation to the cloud while preserving that user experience. You know, interacting with the workstations that's happened. The cloud. >>So just like in conceptualizing is local zone, like a base station is in the metro point of physical location. Is it outpost on steroids? Been trying to get the feel for what it is >>you can think off regions consisting off availability zones. So these are, you know, data center clusters that deliver AWS services. So a local zone is much like an availability zone. But instead of being co located with the rest of the region, is in another locations that, for example, in L. A. Rather than being, you know, in in Virginia, let's say, um, they are internally. We use the same technology that we use for outpost, I suppose, is another great example of how AWS is getting closer to customers for on premises. Deployments were using much of the same technology that you you probably know as Nitro System and a number of other kind of technology that we've been working on for years, actually, toe make all this possible. >>You know, anyone who's been to a football game or any kind of stadium knows you got a great WiFi signal, but you get terrible bandwidth that is essentially kind of the back hall component for the telecom geeks out there. This is kind of what we're talking about here, right? We're talking about more of an expansionary at that edge on throughput, not just signal. So there's, you know, there's there's a wireless signal, and it's like really conductivity riel functionality for applications. >>Yeah, and many. Many of those use case that we're talking about are about, you know, immersive experiences for for end users. So with five t, you get that increasing throughput, you can get up to 10 GPS. You know, it is much higher with what you get 40. You also get lower latents is, but in order to really get make the most out of five G. You need to have the cloud services closer to the end user. So that's what Wavelength is doing is bringing all of those cloud services closer to the end user and combined with five G delivers on these on these applications. You know, um, a couple of customers are actually doing very, very, very exciting things on immersive application, our own immersive experiences. Um, why be VR is a customer that's working on wavelength today to deliver a full 3 60 video off sports events, and it's like you're there. They basically take all of those video streams. They process them in the waving zone and then put them back down to your to your VR headset. But don't you have seen those? We are headsets there, these bulky, awkward, big things because we can do a lot of the processing now at the edge rather than on the heads of itself. We are envisioning that these headsets will Will will string down to something that's indistinguishable potential from, you know, your glasses, making that user experience much better. >>Yeah, from anything from first responders toe large gatherings of people having immersive experiences, it's only gonna get better. Jorge. Thanks for coming on. The Cuban explaining wavelength graduates on the news and expansion. A lot more cities. Um, what's your take for reinvent while I got you? What's the big take away for you this year? Obviously. Virtual, but what's the big moment for you? >>Well, I think that the big moment for me is that we're continuing to, you know, to deliver for our customers. Obviously, a very difficult year for everyone and being able to, you know, with our help off our customers and our partners deliver on the reinvent promised this year as well. It is really impressed for >>me. All right. Great to have you on. Congratulations on local news. Great to see Andy pumping up wavelength. Ah, lot more work. We'll check in with you throughout the year. A lot to talk about. A lot of societal issues and certainly a lot of a lot of controversy as well as tech for good, great stuff. Thanks for coming. I appreciate it. >>Thanks for having me. Thanks. >>Okay, That's the cube. Virtual. I'm John for your host. Thanks for watching. We'll be back with more coverage from reinvent 2023 weeks of coverage. Walter Wall here in the Cube. Thanks for watching. Yeah,

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah. Welcome to the cubes. Virtual coverage of 80 was reinvent 2020. I'm John for your host. We are the Cube virtual not there in person, but we're doing remote, as is a W s. Although there there on stage live. And we're here with Dave Brown, Vice President of the Sea, to compute. Great to see you again. Great keynote last night, kicking off everything for the opening night. Great stuff. >>Yeah, well, John, it's always good to be on the Cuban. Thanks for having me back. >>You know, you're in the hot seat these days in the sense of there's so much going on. I mean, Andy, that could do a three week announcement. Keynote. It was like in three hours of nonstop you take a break to go The bathroom. You missed two announcements, right? So, so much going on. You opened up reinvent 2020 with your announcement ec2 of mac instances. And there was a ton of compute. And the theme was really you know, reinventing and reimagining compute both. I want to get into that. But let's start with the hard news. Tell me about the Mac instances. Um, you had a great use case there, That kind of illustrated in your talk. But where is this coming from? It's obviously Mac developers are big, but is this market something that you guys saw from customers or was a necessity? Take us through the thinking around the Mac instance. Easy to for Mac instances, um are going for >>absolutely absolutely So I mean me personally Matthews, a longtime Matthews that we've often thought about. Could we ever bring Mac OS to AWS? Right This thing we've spoken about on and off for many, many years and, you know, it was about a year and a half about two years ago. You know, we're always hearing new use cases from customers, and that's kind of what we're doing. So we're saying what a customer is trying to do that we don't support today, and how would we support them in that? And we started a year from customers that they have been able to successfully migrate all of the AWS workloads to AWS. So most of the server workloads to AWS and then they've got this Mac bold workload that they just weren't able to bring to us. We just didn't support Max into. It was a great example who I had on stage with me last night where you know, they over the last couple of years have been moving Ah, lot of their workloads to AWS. And and then they had these Mac money sitting around that they had to manage themselves. And so we said, could we actually do this? And so that was the one thing the customer ask. And the other thing that we realized was with the nitro system in the work that we've been doing there over the last, you know, six years, seven years since 2012, Really? And just where we are from the From nitro system point of view, we were able to wrap a Mac money without making any changes to it with nitro cards plugging a FireWire to the thunderbolt port and and and actually control that device. And so it means that you get the best of Apple hardware, which is what Apple's all about is the hard way that they make and the way that their software works with it. together with the nitric system and the cards around that inte integrating with the rest of AWS. So we're giving you, you know, high speed secure networking. We're giving you great access to elastic block store Was just integrates natively into the magma Nias? Well, a So we realized that the technology was there, the customer asked, was there and then obviously went to Apple and worked with them very closely to make it happen. And so that's kind of how it all came together. And I was incredibly excited to announce it last night. And the feedback today has just been amazing. A lot of excitement. >>Yeah, take me through the use case because, you know, obviously there's two trends going on. There's custom chips and server list kind of thing happening where you guys, I mean, really doing a good job of the eye as layer, innovating there and then platform as a service. All that software on top. I totally get that. You could see that happening. Chips custom ships to Intel, A, M, D. And others. Now you got Mac hardware. Where's the innovation use case because one would start would say, Hey, why don't you care about whether it's Mac hardware or not. Because I'm server lists. I should be programming the infrastructure actually be getting compute generically. Where does the Mac tying come in? Because that's the first question I was thinking of was, I'm a Mac user. I love Mac, but I'm also got some windows actually going on now. And ultimately, do I really care if it's compute? What's your reaction to that? Yeah, >>absolutely. I mean, if you look at Apple's ecosystem today, right, they have millions of applications in the APP store. They have 28 million developers worldwide, actually building those applications just incredible. And many of those applications, all these millions in the In the APP store itself, there's many more applications that are both by enterprises and companies, right? We have an application that we use internally at Amazon is available on my phone. That's not in the APP store, and you know, many companies are doing that and to build applications for the ecosystem, they have to be built on Mac hardware. And that's just how Apple works, right? So if you wanna build for iPad or iPhone or even Apple TV and Apple watch, you have to build those applications on a Mac. And so what we see companies doing is, you know, the old develop a meme off. Well, it works on my computer, right when you build something, you don't wanna be bullied on your local laptop for production. So they typically have a fleet of machines that they either under somebody's desk or in a data center somewhere that they use for for building these Mac applications. And so it's not possible to build a Mac application on anything other than a Mac itself. And we when we looked at it, we really didn't feel that virtualization made sense, right? Apple? I mean, they have some some virtualization that they're able to do within Mac OS itself. But if you think about how do we solve the customer use case, it's really bringing apple hardware too easy to to solve the problem and giving customers that exactly same exact same experience that they have on prep. And if you look into it like that, models just worked right. We gave them better access. Uh, you know, they've been using that data which you normally say, Hey, don't don't run production workloads on a beta. But you know, I found out if I interview with the BPS at Intuit critique that they've actually moved 80% of their production pulled wear clothes too easy to already to run on the Mac instances. And so that, and that's in the space of two months. And so, just as seamless ability to move because it's the same hardware is kind of what we were going >>after. Great, thanks for sharing that and say, one thing I wanna point out is Mac does have their own chips as well. They're going custom chips. Amazon's going custom chips. And I think I think you nailed what I was trying to understand, which is this developer community for Mac. And there's some things that are purpose built for Mac devices. So on Mac ecosystem, get the marketplace as well as you know, that that was the hardware PCs and devices, and they're only doing more and more. So this brings me to the i o t. Um, piece of it, because Apple does make devices that people wear and I watch is, um, iPhones. I mean, they're not computers anymore. They're everything. So this kind of brings up the edge conversation. So whether it's an iPhone or a five G in a Metro or I'm a stadium watching a football game and there's some sensor camera vision industrial thing there, this is the new normal. This is where you guys are kind of eating, eating up the software side that that business, because there's new capabilities here. Can you explain how compute he's, particularly C two gets to the edges because no one wants to move data around. They wanna move, compute, not data, because data is expensive and it's and it's fat. So we we talked about that we keep on years ago, but you gotta move. Compute. So how does that work Take us through your vision? >>Absolutely. And this is This is a massively growing area for us. I mean, you mentioned Apple's new M one silicon Apple silicon that they just launched a swell, and we're super excited about Apple's been doing there. We've been doing the same thing with our grab. It's on two processor and really saving customers. An incredible amount on price performance. Tried customers moving and getting 40% improvement and price performance just by moving to grab it on too. It's just incredible. Um, in terms of the edge, you know, we started this journey. We started this journey quite some time ago and bringing, you know, Lambda functions to cloudwatch and things like that. How do we bring compute to the edge? We took a look at five G, which I think it's gonna feel a lot of this right if if we look at our cell phones today was actually just talking to the Apple team yesterday with the iPhone, only came out, you know, 13 years ago. It's kind of amazing to think just how much progress we've had and what four g did for the device that's in our pocket in terms of, you know, just how much we rely on that today and what we get. Well, five g is just a step function in both in terms of latency, but also in terms of throughput. And so, you know, one of the projects we announced last year with Verizon and we now Andy announced this morning we're also gonna be rolling out with Katy D I and SK Telecom and Vodafone next year. Um is a project always like that brings aws compute to the edge of the telco network. And so with Verizon, we now have eight locations around the U. S. Where we have AWS compute capacity. And what I mean by that is literally C five instances uh, G four GPU instances for customers that want to do influence and graphics processing on the edge. And that's embedded into the five G network on DSO customers. You know, we've got a number of customers that are doing a lot of interesting things with five G in the sports area, where they have five G cameras that are, you know, submitted directly to wavelength. We no longer need to drive a truck to a stadium to record a game. You just have five G cameras, um, to, you know, automated factories where they doing robotics in factories and yet really low latency. And they don't want the computer, the factory they wanted in five G and so just exciting area for us. That's growing really, really quickly. Thea Other thing we did is obviously with local zones. We launched our first local zones in L a X last year, Los Angeles on that's being used by the movie industry, so you know right now is a lot of exciting up and running off the covert and shut down for a period of time and filming the next release of all of our favorite episodes and across all of these various streaming platforms. And a lot of that work is actually the post production is being done on on AWS on G four instances within the Los Angeles region. So, you know, very low agency for colorization animation, special effects, all that sort of things happening there. What we heard from a lot of customers was they loved outposts as well, which is our offering to put a server into a data center. And you heard from riot games in Andy's Keynote, where they actually bought a number of outposts and put them all over the U. S. And also other places of the world to really lower the Leighton see for their latest game. And so what Andy also just announced is the availability off three additional local zones. So Atlanta, Miami and Houston Sorry, Boston Miami in Houston available today, and then additional 12 available local zones next year, and what that does is that sort of spreads AWS capacity compute capacity at the edge in all of our major metropolitan hubs all of their capacities on the AWS backbone as well, but brings customers that low latency connectivity that they're looking for. Gaming developers were, you know, every every millisecond counts in terms of gameplay on so super excited to be going after that use case, which I think, you know, it's difficult to tell what the next 10 years is gonna be like. But I think Layton's he's gonna have a big part to play in the types of applications we see on our phones going forward. >>Great stuff, final question for you as we wrap up, obviously with virtualization with virtualization. But you know, the cove it is. And he pointed out, People are gonna change, is gonna be winners and losers. He kind of clearly pointed out, But the people who do lean into the cloud who have been on the cloud or taking advantage of the tail winds of cove in because of the capabilities there are two bills air higher, and you should be happy for that. But they're also gonna have more demand for you to say, Hey, I need more services. So How do you speak to those people who are leaning in who are leveraging, more, compute? What should they be looking at? What kinds of services should be connecting into compute? How should they be thinking about the future of compute so that they can take advantage of those capabilities? The lower costs, higher performance? What things are complementary for these customers as they come in, not toe dip in the water kind of things against really driving. And what do they need? >>Yeah, absolutely. And this has been a big focus on us. You know, things has bean, as I cover in my keynote, which leadership session that I'm doing tomorrow Wednesday. You know, a lot of this year has been helping customers through covert and what covert is meant for their business. Whether that is cost savings for many of them or whether it's just demand, you know that they've never experienced are expected before. I mean, we've been incredibly hard at work in servicing those customers, right? I actually catch up with Scott Sikora. In my keynote. He leads our capacity team. We talked through what it meant and how we actually provided the capacity that our customers needed during Colbert Times. But for a customer moving to us, the first thing is obviously we wanna find ways to make them very successful in the cloud, but more importantly, lower price performance for them. So what we wanted to do is give them the best possible performance that's available at the lowest possible cost. And if you look at a number of the announcements that Andy made today, you know whether it's our latest graviton processor where you can, you know, when you move to arm. I think customers often overestimate how much work it will be to move to arm. And when I talked to them after they have moved, that's ahead. Wasn't actually that much work. We actually got it up and running relatively quickly. So what's simpler than people expect? But that's an opportunity to save 40% on price performance. You know these new newer workloads like our graphics. We just launched a new G four a D, which is an AMG based GPU solution, the first time we have had an AMG GPU on the EEC too. And that's also looking to say, if you know upwards of 40% price performance of other GPU offering so just incredibly exciting for graphics, work, clothes and then in the machine learning space. Like I think, if you know, machine learning is just become the new normal, like everybody is doing it. And you know, just three years ago, everybody was thinking about whether they should do it. How would how they would use it Now that it's a lot of companies are doing it. It's really How do you How do I use it more? And that comes down to again saving costs. And so what we know with without Inferential Chip and then the new Habbaniya chip we just announced it with with the work with Intel that we're doing and then a new trainee, um, ship for training, training. We're really working to lower the cost of machine learning. And so, like we've seen many customers like Alexa was a great use case the other day. Being able to lower the cost of inference for Alexa by 35% again just helps customers, you know, move to the cloud. But I mean, just generally, you know, we're trying to support customers everywhere where there were, you know, if there are many customers are in their own data centers looking to move to AWS. You know, we have great models that can support them with our existing compute. A new savings plan offering we announced last year just great for saving costs on getting the price down So a lot. You can look at it. You know, I could go on forever. Really. It >>Certainly it's certainly is MAWR. We'll we'll do a deeper dive follow up after reinvent, but it is a wake up call. As I wrote in my post, um, for a cloud on Finally, I've been saying this for years. Horizontal scalability is a disruption on the infrastructure side, but you've got vertical specialization with data to create great modern apse of machine learning. And I actually playing out in full display here is Andy said, um, net right now. So all this benefits and all these opportunities to disrupt horizontally and then leverage the data all tied together, all coming together. You're clear. Leading the team. Great Brown, vice president of E C. Two in charge of the team that's driving the future. Compute. Thanks for coming on The Cube Cube Live coverage. Thanks. >>Thanks for having me. >>Okay. I'm John for the Q back for more live coverage after this short break

>>from around the globe. It's >>the Cube with digital coverage of Dev >>Ops Virtual Forum Brought to You by Broadcom. Welcome to Broadcom, Step Ups, Virtual Forum I and Lisa Martin and I'm joined by another Martin very socially. Distance from me all the way. Coming from Birmingham, England, is Glynn Martin, head of Q. A transformation at BT Glenn. It's great to have you on the program. >>Thank you, Lisa. I'm looking forward, Toa. >>As we said before, we went live to Martin's for the price of one in one segment. So this is gonna be an interesting segment, Guesses. What we're gonna do is Glen's gonna give us a really kind of deep inside out view of Dev ops. From an evolution perspective, Soglo's Let's start transformation is at the heart of what you dio. It's obviously been a very transformative year. How have the events of this year affected the transformation that you are so responsible for driving? >>Yeah. Thank you, Leigh. So I mean, yeah, it has been a difficult year Bond, although working for BT, which is ah, global telecommunications company. Relatively resilient, I suppose, as an industry through covert, it obviously still has been affected and has got its challenges on bond. If anything is actually caused us to accelerate of our transformation journey, you know, we had to do some great things during this time around. You know, in the UK for our emergency and health workers give them unlimited data and for vulnerable people to support them and that spent that we've had to deliver changes quickly. Um, but what? We want to be able to do it, deliver those kind of changes quickly, but sustainably for everything that we do, not just because there's an emergency eso we were already on the kind of journey to by John, but ever so ever more important now that we are what we're able to do, those that kind of work, do it more quickly on. But it works because the implications of it not working is could be terrible in terms of, you know, we've been supporting testing centers, new hospitals to treat covert patients, so we need to get it right and therefore the coverage of what we do, the quality of what we do and how quickly we do. It really has taken on a new scowling what was already a very competitive market within the telco industry within the UK. Um, you know, what I would say is that you know, we are under pressure to deliver more value, but we have small cost challenges. We have to obviously deal with the fact that you know, Cove in 19 has hit most industries kind of revenues and profits. So we've got this kind of paradox between having less cost, but they're having to deliver more value quicker on bond, you know, to higher quality. So, yeah, certainly the finances is on our minds. And that's why we need flexible models, cost models that allow us to kind of do growth. But we get that growth by showing that we're delivering value, especially in, you know, these times when there are financial challenges on companies. >>So one of the things that I want to ask you about again looking at, develops from the inside out on the evolution that you've seen you talked about the speed of things really accelerating in this last nine months or so. When we think Dev ops, we think speed. But one of the things I love to get your perspective on we've talked about in a number of the segments that we've done for this event is cultural change. What are some of the things that scene there as as needing to get, as you said, get things right but done so quickly to support essential businesses, essential workers? How have you seen that cultural shift? >>Yeah, I think you know, before, you know, test test team saw themselves of this part of the software delivery cycle. Andi, actually, now, really, our customers were expecting their quality and to deliver for our customers what they want. Quality has to be ingrained throughout the life cycle. Obviously that you know, there's lots of buzzwords like shift left. How do you do? Shift left testing. But for me, that's really instilling quality and given capabilities shared capabilities throughout the life cycle. That Dr you know, Dr Automation drive improvements. I always say that you know, you're only as good as your lowest common denominator on one thing that we're finding on our Dev Ops Journey Waas that we were you know, we would be trying thio do certain things quicker and had automated build automated tests. But if we were taking weeks to create test scripts or we were taking weeks to manly craft data, and even then when we had taken so long to do it that the coverage was quite poor and that led to lots of defects later in the lifecycle or even in in our production environment, we just couldn't afford to do that. And actually, you know, focusing on continuous testing over the last 9 to 12 months has really given us the ability Thio delivered quickly across the the whole life cycle and therefore actually go from doing a kind of semi agile kind of thing where we did you use the stories we did a few of the kind of, you know, as our ceremonies. But we weren't really deploying any quicker into production because, you know, our stakeholders were scared that we didn't have the same control that we had when we had more water for releases. And, you know, when way didn't think ourselves. So we've done a lot of work on every aspect, especially from a testing point of view, every aspect of every activity, rather than just looking at automated test, you know, whether it is actually creating the test in the first place, Whether it's doing security testing earlier in the light and performance testing. Learn the life cycle, etcetera. So, yeah, it Z It's been a riel key thing that for for C T for us to drive, develops, >>talk to me a little bit about your team. What are some of the shifts in terms of expectations that you're experiencing and how your team interacts with the internal folks from pipeline through life cycle? >>Yeah, we've done a lot of work on this, you know, there's a thing. I think people were pretty quiet. Customer experience. Gap. It reminds me of a cart, a Gilbert cartoon where, you know, we start with the requirements here on Do you know, we almost like a Chinese whisper effects and what we deliver eyes completely, completely different. So we think the testing team or the the delivery team, you know, you know, you think they've done a great job. This is what it said in the acceptance criteria, but then our customers the same Well, actually, that's not working. This isn't working, you know, on there's this kind of gap Way had a great launched this year of actual Requirement Society, one of the board common tools Onda that for the first time in in since I remember actually working within B. T, I had customers saying to may, Wow, you know, we want more of this. We want more projects, um, to have a actual requirements design on it because it allowed us to actually work with the business collaboratively. I mean, we talk about collaboration, but how do you actually, you know, do that have something that both the business on technical people can understand? And we've actually been working with the business using at our requirement. Designer Thio, you know, really look about what the requirements are. Tease out requirements to the hadn't even thought off and making sure that we've got high levels of test coverage. And so what we actually deliver at the end of it, not only have you been able Thio generate test more quickly, but we've got much higher test coverage and also can more smartly, you're using the kind of AI within the tour and with some of the other kind of pipeline tools actually deliver to choose the right tests on the bar, still actually doing a risk based testing approach. So that's been a great launched this year, but just the start of many kind of things that we're >>doing. But what I hear in that Glenn is a lot of positives that have come out of a very challenging situation. Uh, talk to me about it and I like that perspective. This is a very challenging time for everybody in the world, but it sounds like from a collaboration, perspective is you're right. We talk about that a lot critical with Dev Ops. But those challenges there you guys were able to overcome those pretty quickly. What other challenges did you face and figure out quickly enough to be able to pit it so fast? >>I mean, you talked about culture. I mean, you know, Bt is like most come countries companies. So, um, is very siloed. You know, we're still trying to work to become closer as a company. So I think there's a lot of challenges around. How do you integrate with other tools? How do you integrate with you know, the various different technologies and bt we have 58 different whitey stacks? That's not systems that stacks all of those stacks of can have, you know, hundreds of systems on we're trying to. We're gonna drive at the moment a simplified program where we're trying Thio, you know, reduce that number 2 14 stacks. And even then they'll be complexity behind the scenes that that we will be challenged. Maurin Mawr As we go forward, how do you actually hired that to our users on as an I T organization? How do we make ourselves Lena so that even when we you know, we've still got some of that legacy and we'll never fully get rid of it on that's the kind of trade off that we have to make. How do we actually deal with that and and hide that for my users a say and and and drive those programs so we can actually accelerate change. So we take, you know, reduce that kind of waste, and that kind of legacy costs out of our business. You know, the other thing is, well, beating. And I'm sure you know telecoms probably no difference to insurance or finance we've got You know, when you take the number of products that we do and then you combine them, the permutations are tens and hundreds of thousands of products. So we as a business to trying to simplify. We are trying Thio do that in a natural way and haven't trying to do agile in the proper way, you know, and really actually work it paste really deliver value. So I think what we're looking Maura, Maura, at the moment is actually, um is more value focus? Before we used to deliver changes, sometimes into production, someone had a great idea or it was a great idea nine months ago or 12 months ago. But actually, then we end up deploying it. And then we look at the the the users, you know, the usage of that product of that application or whatever it is on. It's not being used for six months, so we're getting much we haven't got, you know, because of the last 12 months, we certainly haven't got room for that kind of waste and you know, the for not really understanding the value of changes that we we are doing. So I think that's the most important thing at the moment is really taken that waste out. You know, there's lots of focus on things like flow management. What bits of the our process are actually taking too long, and we've We've started on that journey, but we've got a hell of a long way to go, you know, But that that involves looking every aspect off the kind of software delivery cycle. >>What are some? Because that that going from, what, 58 i t stocks down to 14 or whatever it's going to be go simplifying is sounds magical. Took everybody. It's a big challenge. What are some of the core technology capabilities that you see really as kind of essential for enabling that with this new way that you're working? >>Yeah. I mean, I think we've started on a continuous testing journey, and I think that's just the start. I mean, that's really, as I say, looking at every aspect off, you know, from a Q, a point of view. It's every aspect of what we dio. But it's also looking at, you know, we're starting to branch into more like a AI ops and, you know, really, the full life cycle on. But, you know, that's just a stepping stone onto, you know, I think oughta Nomics is the way forward, right? You know all of this kind of stuff that happens um, you know, monitoring, you know, monitoring systems, what's happening in production had to be feed that back. How do you get to a point where actually we think about a change on then suddenly it's in production safely. Or if it's not going to safety, it's automatically backing out. So, you know, it's a very, very long journey. But if we want Thio, you know, in a world where the pace is ever increasing the demands of the team and you know, with the pressures on at the moment where with we're being asked to do things, you know more efficiently Ondas leaving as possible. We need to be, you know, thinking about every part of the process. And how do we put the kind of stepping stones in players to lead us to a more automated kind of, you know, their future? >>Do you feel that that plant outcomes are starting to align with what's delivered? Given this massive shift that you're experiencing, >>I think it's starting to, and I think you know, Azzawi. Look at more of a value based approach on. Do you know a Zeiss? A princess was a kind of flight management. I think that's that will become ever evermore important. So I think it's starting to people. Certainly realized that, you know, people teams need to work together. You know, the kind of the cousin between business and ICT, especially as we go Teoh Mawr kind of sad space solutions, low cold solutions. You know there's not such a gap anymore. Actually, some of our business partners expects to be much more tech savvy. Eso I think you know, this is what we have to kind of appreciate. What is I ts role? How do we give the capabilities become more for centers of excellence rather than actually doing Mount amount of work And for May and from a testing point of view, you know, amount, amount of testing, actually, how do we automate that? How do we actually generate that instead of created? I think that's the kind of challenge going forward. >>What are some? As we look forward, what are some of the things that you would like to see implemented or deployed in the next say, 6 to 12 months as we hopefully round a corner with this pandemic? >>Yeah, I think you know, certainly for for where we are as a company from a Q A perspective. We are. Yeah, there's certain bits that we do Well, you know, we've started creating continuous delivery. A day evokes pipelines. Um, there's still manual aspects of that. So, you know, certainly for May I I've challenged my team with saying, How do we do an automated journey? So if I, you know, I put a requirement injera or value whoever it is, that's why. Then click a button on bond, you know, with either zero touch of one touch, then put that into production and have confidence that that has been done safely on that it works. And what happens if it doesn't work? So you know, that's that's the next in the next few months, that's what our concentration is about. But it's also about decision making, you know, how do we actually understand those value judgements? And I think there's lots of the things Dev ops, ai ops, kind of always that aspects of business operations. I think it's about having the information in one place to make those kind of decisions. How does it all tied together, as I say, even still with kind of Dev ops, we've still got elements within my company where we've got lots of different organizations doing some doing similar kind of things but the walking of working in silos Still. So I think, having a eye ops Aziz becomes more and more to the fore as we go to the cloud. And that's what we need to. You know, we're still very early on in our cloud journey, you know. So we need to make sure the technologies work with Cloud as well as you kind of legacy systems. But it's about bringing that all together and having a full visible pipeline. Everybody can see and make decisions against >>you said the word confidence, which jumped out at me right away. Because absolutely, you've gotta have be able to have confidence in what your team is delivering and how it's impacting the business and those customers. Last question for you is how would you advise your peers in a similar situation to leverage technology automation, for example, dev ops to be able to gain the confidence that they're making the right decisions for their business? >>Yeah, I mean, I think the the approach that we've taken actually is not started with technology we've actually taken human centered design a za core principle of what we dio within the i t part of BT. So by using humans tend to design. That means we talked to our customers. We understand their pain points, we map out their current processes on. But when we mapped out, those processes also understand their aspirations as well, you know, Where do they want to be in six months? You know, Do they want to be more agile and you know, or do they want Teoh? Is this apart their business that they want thio run better? We have to Then look at why that's not running well and then see what solutions are out there. We've been lucky that, you know, with our partnership with Broadcom within the P l. A. A lot of the tortures and the P l. A have directly answered some of the businesses problems. But I think by having those conversations and actually engaging with the business, um, you know, especially if the business hold the purse strings, which is you know, in some companies, including as they do there is that kind of, you know, almost by understanding their their pain points and then saying This is how we can solve your problem We've tended to be much more successful than trying Thio impose something and say We're here to technology that they don't quite understand doesn't really understand how it could have resonate with their problems. So I think that's the heart of it is really about, you know, getting looking at the data, looking at the processes, looking at where the kind of waste is on. Then actually then looking at the right solutions. And as I say, continuous testing is a massive for us. We've also got a good relationship with capitals looking at visual ai on. Actually, there's a common theme through that, and I mean, AI is becoming more and more prevalent, and I know yeah, sometimes what is A I and people have kind of the semantics of it. Is it true, ai or not? But yes, certainly, you know, AI and machine learning is becoming more and more prevalent in the way that we work, and it's allowing us to be much more effective, the quicker and what we do on being more accurate. You know, whether it's finding defects, running the right tests or, you know, being able to anticipate problems before they're happening in a production environment. >>Welcome. Thank you so much for giving us this sort of insight. Outlook at Dev Ops, sharing the successes that you're having taking those challenges, converting them toe opportunities and forgiving folks who might be in your shoes or maybe slightly behind advice. I'm sure they appreciate it. We appreciate your time. >>It's been an absolute pleasure, Really. Thank you for inviting me of Extremely enjoyed it. So thank you ever so much. >>Excellent. Me too. I've learned a lot for Glynn Martin and Lisa Martin. You're watching the Cube?

>>thank you. You know, haven't been in technology my entire career. Uh, technology and data has really evolved from being the province of a few and an organization to frankly being critical to everyone's business outcomes. Now, every business leader really needs to embrace data analytics and technology. We've been talking about digital transformation. Probably the last 57 years we've all talked about disruptor be disrupted. At the core of that digital transformation is the use of data, data and analytics that we derive insights from and actually improve our decision making by driving a differentiated experience and capability into market. So Data has involved as being, I would say, almost tactical in some sense over my technology career to really being a strategic asset of what we leverage personally in our own careers, but also what we must leverage as companies to drive a differentiated capability to experience and remain relative in the market today. Mhm. >>No. Yeah, I I agree with Lisa. It has definitely become a the lifeblood of every business, right? It used to be that there were a few companies in the business of technology. Every business is now a technology business. Every business is a data business. It is the way that they go to market, shaped the market and serve their clients. Whether you're in construction, whether you're in retail, whether you're in health care doesn't matter. Right? Data is necessary for every business to survive and thrive. And I remember at the beginning my career It was you know, data was always important, but it waas about storing data. It was about giving people individual reports. It was about supplying that data toe one person or one business unit in silos, and it then evolved right over the course of time into integrating data and to saying, Alright, how does one piece of data correlate to the other? And how can I get insights out of that data now? It's gone to the point of how do I use that data to predict the future? How do I use that data toe automate the future? How do I use that data? Not just for humans to make decisions, but for other machines to make decisions right, which is a big leap, Onda big change and how we use data, how we analyze data and how we use it for insights and evolving our businesses. Yeah. >>Yeah. Well, since I'm on the snowflake board, I'll talk a little bit about the snowflake data cloud. You know, we're getting your company's data out of the silos that exist all over your organization. We're bringing third party data into combined with your own data, and we're wrapping a governance structure around it and feeding it out to your employees so that they can get their jobs done. And it's a simple is that, uh I think we've all seen the pandemic accelerate the digitization of our work. And if you ever doubted that the future of work is here, it is here. And companies are scrambling to catch up by providing the right amount of data, uh, collaboration tools, workflow tools for their workers to get their jobs done. You know, it used to be as prior, people have mentioned that in order thio work with data. You have to be a data scientist. But, you know, I was an auditor back in the day, and we used to work on 16 columns, spreadsheets. And now, if you're an accounting major coming out of college, joining an auditing firm, you have to be checked and data savvy because you're going to be extracting, manipulating, analyzing and auditing data that massive amounts of data that sit in your client's I T systems. I'm on the board of Warby Parker, and you might think that their most valuable asset is their amazing frame collection. But it's actually their data. There are 360 degree view of the customer, and so, if you're a merchant or urine strategy or marketing or talent or the co CEO, you're using data every day in your work. And so I think it's going to become a ubiquitous skill that any anyone who's a knowledge worker has to be able to work with. Data. >>Yeah, absolutely. You know, most enterprises today are, I would say, hybrid multi cloud enterprises. What does that mean? That means that we have data sitting on Prem. We have data sitting in public clouds through software. As a service applications. We have a data everywhere. Most enterprises have data everywhere. Certainly those that have owned infrastructure or weren't born on the web. One of the areas that I love that data cloud is addressing is the area around data portability and mobility because I have data sitting in various locations through my enterprise. How doe I aggregate that data to really drive meaningful insights out of that data to drive better business outcomes and a blue shield of California. One of our key initiatives is what we call an experience cube. What does that mean? It means how doe I drive transparency of data between providers, members and payers so that not only do I reduce overhead on providers and provide them a better experience our hospital systems or doctors, But ultimately, how do we have the member have at their power of their fingertips the value of their data holistically so that we're making better decisions about their health care? You know, one of the things Teresa was talking about was the use of this data, and I would drive to data democratization. We got to put the power of data into the hands of everyone, not just data scientists. Yes, we need those data scientists to help us build a I models to really drive and tackle these tough hold, tougher challenges, business problems that we may have in our environments. But everybody in the company, both on the I T side both on the business side really need to understand. Of how do we become a data insights driven enterprise? Put the power of the data into everyone's hands so that we can accelerate capabilities right and leverage that data toe ultimately drive better business results. So as a leader, as a technology leader, part of our responsibility, our leadership, is to help our companies do that. And that's really one of the exciting things that I'm doing in my role now at Blue Shield of California took, >>oh, great question. And I am so passionate about this for ah, lot of reasons, not the least of which is I have two daughters of my own. Andi, I know how important it is for women and young girls. Toe actually start early in their love for technology and data and all things digital, right? So I think it's one very important to start early start in early education, building confidence of young girls that they can do this showing them role models. You know, we have Deloitte just partnered with L. A B engineer toe actually make comic books centered around young girls and boys in the early elementary age to talk about how heroes and text solve everyday problems on DSO, really helping to get people's minds around Tech is not just in the back office coating on a computer. Tech is about solving problems together. That helped us a citizens as customers, right and as humanity s. So I think that's important. I also think we have to expand that definition of tech. As we just said. It's not just about right database design. It's not just about, you know, Java and python coding. It's about design. It's about the human machine interfaces. It's about how do you use it to solve real problems and getting people to think in that kind of mindset makes it more attractive and exciting. And lastly, I'd say, Look, we have a absolute imperative to get a diverse population of people, not just women but minorities. You know, those with other types of backgrounds, disabilities, etcetera involved because this data is being used to drive decision making, and if we're all involved right and how that data makes decisions, it can lead to unnatural biases that no one intended but can happen just because we haven't involved a diverse enough group of people around it. Absolutely. Lisa. Curious about your thoughts on this? >>I agree with everything that she has said. I've been passionate about this area. I think it starts with First. We need more role models way. Need more role models as women, uh, in these leadership roles throughout various sectors, and it really is. It starts with us and helping to pull other women forward. So I think certainly it's part of my responsibility. I think all of us as female executives that if you have exceeded the table toe leverage that seat at the table to drive change, to bring more women forward, more diversity forward into the board room and into our executive suites. I also want to touch on a point that she had made about women were the largest consumer group in the company. Um, yet we're consumers, but we're not builders. This is why it's so important that we start changing that perception of what tech is, and I agree that it starts with their young girls. We know the data shows that we lose our young girls by middle school. Very heavy peer pressure. It's not so cool to be smart to do robotics or be good in math and science. We start losing our girls in middle school, so they're not prepared when they go to high school. And they're not taking those classes in order to major in these stem fields in college. So we have to start the pipeline early, Um, with our girls. And then I also think it's a measure of what your boards air doing. What is the executive leadership in your goals around diversity and inclusion? How do we invite more diverse population to the decision making table? So it's really a combination of effort. One of the things that certainly is concerning to me is during this pandemic. I think we're losing one in four women in the workforce now because of all the demands that our families are having to navigate through through this pandemic. The last statistic I saw in the last four months is we've lost 850,000 women in the workforce. This pipeline is critical to making that change in these leadership positions. What? Yeah, >>um, I'd encourage you to view to become an active sponsor. Research shows that women and minorities are less likely to be sponsored than white men. Sponsorship is a much more active form than mentorship. Sponsorship involves helping someone identify career opportunities and actively advocating for them in those roles. Opening your network, giving very candid feedback. And we need men to participate to. There are not enough women in tech to pull forward and sponsor the high potential women that are in our pipelines. And so we need you to be part of the solution. >>Let's say Look around your teams, see who's on them and make deliberate decisions about diversifying those teams as positions. Open up. Make sure that you have a diverse set of candidates. Make sure that there are women that are part of that team on DNA. Make sure that you are actually hiring and putting people into positions based on potential, not just experience. >>Wow, it's hard Thio with Nishida and with Tricia shared, I think we're very powerful actions. I think it starts with us, uh, taken action at our own table, making sure you're driving diverse panels and hiring um, setting goals for the company. Having your board engaged in holding us accountable and driving to those goals will help us all see a better outcome with more women at the executive table and diverse populations. >>Yeah, but

>>Hi, everyone. This is L. A from Visa Research today. I would like to tell you about my work with Salim. Earlier. Took from Boston University about how to construct group with invisible inversion from heart problems on ice Arjuna graphs over I say model E eso Let me start this talk by tell you, uh, what is a group with invisible inversion? A group was invisible Inversion is defined by Hulkenberg and Mona In 2003 It says a representation off a group should satisfy two properties. The first is literally that inversion. It's heart. Namely that giving an including off group element X computing Uh, the including off its inverse his heart. The second is that the composition is still easy, namely given the including off X and Y computing the including off X plus y is easy here we're seeing. Plus, is the group operation. So let me explain this definition by going through our favorite example where discreet log it's hard, namely in the Multiplicity group of finance field. We include a group element A as G today, namely, put it into the exponents and more, uh, cute. So given G energy today finding a it's hard. So this group representation at least satisfy one way, as you mean this great look. It's hard. So let's look at at whether this a group satisfied group was invisible inversion. So it turns out it is not because given due to the A finding G to the minus A, it's still easy. So if we say this is the representation off the universe, then computing this reputation is simple. So this is a no example. Off group was invisible invasion. So the work off Falkenburg and Mona started by looking. How can we find group was invisible inversion? And what are the applications off such a group? Representation, >>It turns out, in their sisters. They did not find any group reputation representation that satisfy this property. But instead they find out that if you can find such a group and then they they have >>a cryptographic applications, namely building direct directed transitive signatures a year later in the work off Iraq at or they also find that if you can have this kind of group with invisible inversion there, you can also construct broadcast encryption with a small overhead, and this is before we know how to construct the broadcast encryption with small overhead over Terry's elliptic curve. Paris. So let's look at another attempt off constructing group with invisible inversion. So instead off defining. Still, let's look at a group where we put >>the including in the exponents and instead of defining due to the minus A as the inversion Let's define due to the one over a as the the inverse off do today. So it turns out you can also define that. And it happens that in many groups, minimally, if you more, uh, some special value a que then given G energy to the A, then competing due to the one over A is also conjectured to be hard. But if you define the group element in the experiment in that way, then multiplication in >>the group exponents is also hard, and so we cannot compose. So this is another no example where group inversion is actually difficult to compute. But composition is difficult to compute, uh, either. So for this kind of group, they cannot use this to build directly transitive signatures or broadcast encryption. So now let's make this attempt, uh, visible by allowing thio. So so thio have ability to compute composition. Namely, we represent the including off A as the follows. So first we help you today >>and then we also give an office Kate the circuit which contains a and n such that I take a group element X, and it can output due to the to a model end. So it turns out giving this circuit you have a feasibility off doing composition and in the work off yamakawa at all to show that if and that the underlying off station is io and assuming and it's an R s a moderately then Thistle >>is actually a good construction off group with invisible university. So technically, assuming I oh, we have already know candidates for group was in physical inversion. Uh, but that work still leaves the open problem off constructing group with invisible inversion without using general purpose sophistication. And in this talk, I would like to talk to tell you about a group was inversion candidate from some new certainly problems And the brief logic off this talk is the following. So elliptical insurgencies can be represented by graph, uh, and the graphs has a ship off volcanoes. For example, this one if you look imagine you're looking for a volcano from top to down and this is the Creator, and this is like the direction off going down the volcano. And arguably this is the reason which attracts me to looking to. I certainly problems, and also I certainly graphs can be an I certainly can be used to represent a group called Idea Class Group >>and then eventually we will find some group >>problems on this graph, which we conjecture to be hard. And they use map thes harness to the harness off inverting group elements in the ideal classroom. So this will be the high level overview off this talk. >>So what are a little bit curve? Assertiveness? So to talk about elliptic curve, I certainly okay spend the whole day talking about its mathematical definition and the many backgrounds off elliptic curve. But today we only have 15 minutes. So instead, let me just to give you a highlight help have overview off what I certain this and I certainly is a mapping from when a little bit of curve to another, and I certainly is an interesting equivalence relation between elliptic curves. It's interesting in its mathematical theory, over a finite field and elliptic curve can be identified by its J environment. And later, >>when we talk about elliptic, curve will think about their represented by their environment, which is a number in the finance field >>and given to elliptic curves and namely, given their environments, we can efficiently decide whether these two groups assertiveness, namely in polynomial time. And given these backgrounds, let me now jump to the exciting volcanoes. So it turns out >>the relation among I certainly occurred. Assertiveness curbs can be represented by the I certainly graphs, which looks like volcanoes. So let's first look at the graph on the left and let's fix a degree for that. I certainly so I certainly has different degrees. So let's for simplicity. Think about their crimes. So let's fix a degree Air say equals 23 >>and we will let each of the note in the graph to represent a different elliptic curve, namely a different Jane environment, and each is represent an air degree by certainly so if you fix the degree ill and I certainly is their religions, uh, they just look like what I said, like what kind of going from top to bottom and if, let's say, fix all the >>elliptic curve on the creator or, in general, all the elliptic curves on the same layer off the volcano, Then you allowed to have different degrees. So this is degree L and this is degree M, etcetera, etcetera. And then the graph actually looks like it's almost fully connected. Eso imagine all of them are connected by different degrees. And the graph structure is actually described not too long ago in the pH. Diseases off Davico Hell in 1996 and later it gets popularized in a paper in 2002 because they say, Hey, this looks like a volcano. So now the I certainly will. Kind of is they used in many reference by according the graph. >>So let me tell you a little bit more about the relation off. I certainly and the idea class group. So the short story is, if you fix a layer on the uncertainty graph, say the creator. So actually, all the notes has a 1 to 1 mapping to the group element in an ideal >>class group. The foremost Siri is the ideal class group acts on the, uh, set off a surgeon is which have the same in the more it is a Marine. But we will not go into their, uh in the talk today. So let me give you a simple example. So this is, ah, concrete representation off an ideal class group off seven group elements. And if we fix a J zero j environment off one off the grade curve, let's say this guy represents the identity in the idea class group. And then we let J one to represent one off the class group elements. Then it's inverse is just going one step back from the origin in the opposite direction S O. This is a very important picture we will use exactly the J environments to represent and the idea class group elements eso This is exactly the reputation we're gonna take, except we're gonna work with over the icy modeling. So after giving some mathematical background off elliptical by certainly in a certain graph now, let's talk about competition of problems >>and before jumping into I say model E, let me start from the, uh, more traditionally studied. I certainly problems over the finite field. The first problem is if I fix a degree, air and I give you a J environment off elliptic curve. Ast one off the note. That's first. Take an easy question. Is it easy to find all off? >>It's certainly neighbors off degree will say there is a polynomial. >>The answer is yes. And the technically there are two different ways. Uh, I will not go to the details off what they are, but what we need to know is they require serving, uh, polynomial off degree or air squares. Let's look at another problem that so imagine I select to random >>curves from an I certainly graph. So think about this. Uncertainty graph is defined over a large field, and they are super polynomial limited graphs off them. I'm choosing to random curves. >>The question is, can you find out an explicit I Certainly between them naming and Emily passed from one to the other. It turns out this >>problem is conjecture to be hard even for quantum computers, and this is exactly what was used in the post to quantum key exchange proposals in those works. So they have different structures could aside the seaside. They're just a different types off in the book is a Marine off the question is off the same nature finding and passed from one curve to the other. So these are not relevant to our work. But I would like to introduce them for for some background, off the history off. I certainly problems, >>So you have a work we need to >>study. I certainly problems over in, I say endogenous. And so the first question is even how to define. And I certainly, uh oh, and I certainly graph over the ring like, uh, over and I say modular. Same. So >>there is a general way off defining it in the special case. So in this talk, I will just talk about the special case because this is easier to understand. So think about I have the have the ability off peaking too. I certainly volcan als over multi and multi cube. That has exactly the same structure. And then I just use a C a c r T composition to stick them together. So namely a J >>zero. The value is the CRT off the J zero over. They're over the small fields P and the Cube and the N S equals to P times Q. And by the way, thes gene variants will be exactly the way to represent an ideal class group off such a size in this example is the ideal class group off, uh, with discriminate minus 250 bucks. Okay, so now let's look at what this magical over this representation. So let's look at back to the problem we start from namely, finding all the insurgents neighbors at this time over. And I see model E eso. I give you the J environment off easier and ask you to find a one off the its neighbors finding the J environment off one off its neighbors. So it turns out, even this problem is hard. And actually, we can prove this problem is as hard as factory and naive. Way off. Explaining off What's going on is that the two methods that work over the finite field that doesn't work anymore, since they both required to solve high degree polynomial model end, and that this is hard where when end is in, I certainly I say modelers. So to be useful for constructing a group off invisible inversion, we actually need to look at this called a joint neighbors. Such problems, namely, if I give you a curve zero, which represents the identity, then another crib, which represents a the group element. Your task is to find its inverse namely one off the E two candidate beneath zero. Yeah, eso it turns out this problem. We also conjectured to it to be hard and we don't know how to base it on how this a factoring, uh, again, the not even reason is the way to solve it over the finite field doesn't work because they both required to solve polynomial off degree higher than one over in i. C model is. And this is exactly the reason that we believe the group inversion is hard over deserve visitation Now. Finally, we also would like to remind the readers that for death according to the definition off group with invisible inversion, we would also like the group elements to be easy to compose. No, that's not. Make another observation that over. If you're finding the joint neighbor off, I certainly off different degree. Say, if I give you a J invent off Iwan and Jane Barrett off you to ask you to find the J environment off the three and they happened to off co prime degree I. Certainly then there is a way to find their joint neighbor because they're cold prime. And there's only one solution to solving the modular polynomial that I haven't defined out. But this is the way we make sure that composition is easy. Normally we output, including that are a cold prime so that they can be composed to summarize that we propose a group candidate group with invisible inversion from any particular I. Certainly it requires a chapter because you need to know the prime factors off. I seem odd early to set up the whole system and generated the including in our me assumption is that certain joint neighbors such problem on the I certainly graphs defined over S a moderately it's hard again group within physical inversion has the application of constructing broadcasting, corruption directed transitive signatures, and it's a very interesting problem to explore