(upbeat music) >> Hey, everyone, welcome back to Las Vegas, "theCube" is on our fourth day of covering AWS re:Invent, live from the Venetian Expo Center. This week has been amazing. We've created a ton of content, as you know, 'cause you've been watching. But, there's been north of 55,000 people here, hundreds of thousands online. We've had amazing conversations across the AWS ecosystem. Lisa Martin, Paul Gillan. Paul, what's your, kind of, take on day four of the conference? It's still highly packed. >> Oh, there's lots of people here. (laughs) >> Yep. Unusual for the final day of a conference. I think Werner Vogels, if I'm pronouncing it right kicked things off today when he talked about asymmetry and how the world is, you know, asymmetric. We build symmetric software, because it's convenient to do so, but asymmetric software actually scales and evolves much better. And I think that that was a conversation starter for a lot of what people are talking about here today, which is how the cloud changes the way we think about building software. >> Absolutely does. >> Our next guest, Holger Mueller, that's one of his key areas of focus. And Holger, welcome, thanks for joining us on the "theCube". >> Thanks for having me. >> What did you take away from the keynote this morning? >> Well, how do you feel on the final day of the marathon, right? We're like 23, 24 miles. Hit the ball yesterday, right? >> We are going strong Holger. And, of course, >> Yeah. >> you guys, we can either talk about business transformation with cloud or the World Cup. >> Or we can do both. >> The World Cup, hands down. World Cup. (Lisa laughs) Germany's out, I'm unbiased now. They just got eliminated. >> Spain is out now. >> What will the U.S. do against Netherlands tomorrow? >> They're going to win. What's your forecast? U.S. will win? >> They're going to win 2 to 1. >> What do you say, 2:1? >> I'm optimistic, but realistic. >> 3? >> I think Netherlands. >> Netherlands will win? >> 2 to nothing. >> Okay, I'll vote for the U.S.. >> Okay, okay >> 3:1 for the U.S.. >> Be optimistic. >> Root for the U.S.. >> Okay, I like that. >> Hope for the best wherever you work. >> Tomorrow you'll see how much soccer experts we are. >> If your prediction was right. (laughs) >> (laughs) Ja, ja. Or yours was right, right, so. Cool, no, but the event, I think the event is great to have 50,000 people. Biggest event of the year again, right? Not yet the 70,000 we had in 2019. But it's great to have the energy. I've never seen the show floor going all the way down like this, right? >> I haven't either. >> I've never seen that. I think it's a record. Often vendors get the space here and they have the keynote area, and the entertainment area, >> Yeah. >> and the food area, and then there's an exposition, right? This is packed. >> It's packed. >> Maybe it'll pay off. >> You don't see the big empty booths that you often see. >> Oh no. >> Exactly, exactly. You know, the white spaces and so on. >> No. >> Right. >> Which is a good thing. >> There's lots of energy, which is great. And today's, of course, the developer day, like you said before, right now Vogels' a rockstar in the developer community, right. Revered visionary on what has been built, right? And he's becoming a little professorial is my feeling, right. He had these moments before too, when it was justifying how AWS moved off the Oracle database about the importance of data warehouses and structures and why DynamoDB is better and so on. But, he had a large part of this too, and this coming right across the keynotes, right? Adam Selipsky talking about Antarctica, right? Scott against almonds and what went wrong. He didn't tell us, by the way, which often the tech winners forget. Scott banked on technology. He had motorized sleds, which failed after three miles. So, that's not the story to tell the technology. Let everything down. Everybody went back to ponies and horses and dogs. >> Maybe goes back to these asynchronous behavior. >> Yeah. >> The way of nature. >> And, yesterday, Swami talking about the bridges, right? The root bridges, right? >> Right. >> So, how could Werner pick up with his video at the beginning. >> Yeah. >> And then talk about space and other things? So I think it's important to educate about event-based architecture, right? And we see this massive transformation. Modern software has to be event based, right? Because, that's how things work and we didn't think like this before. I see this massive transformation in my other research area in other platforms about the HR space, where payrolls are being rebuilt completely. And payroll used to be one of the three peaks of ERP, right? You would size your ERP machine before the cloud to financial close, to run the payroll, and to do an MRP manufacturing run if you're manufacturing. God forbid you run those three at the same time. Your machine wouldn't be able to do that, right? So it was like start the engine, start the boosters, we are running payroll. And now the modern payroll designs like you see from ADP or from Ceridian, they're taking every payroll relevant event. You check in time wise, right? You go overtime, you take a day of vacation and right away they trigger and run the payroll, so it's up to date for you, up to date for you, which, in this economy, is super important, because we have more gig workers, we have more contractors, we have employees who are leaving suddenly, right? The great resignation, which is happening. So, from that perspective, it's the modern way of building software. So it's great to see Werner showing that. The dirty little secrets though is that is more efficient software for the cloud platform vendor too. Takes less resources, gets less committed things, so it's a much more scalable architecture. You can move the events, you can work asynchronously much better. And the biggest showcase, right? What's the biggest transactional showcase for an eventually consistent asynchronous transactional application? I know it's a mouthful, but we at Amazon, AWS, Amazon, right? You buy something on Amazon they tell you it's going to come tomorrow. >> Yep. >> They don't know it's going to come tomorrow by that time, because it's not transactionally consistent, right? We're just making every ERP vendor, who lives in transactional work, having nightmares of course, (Lisa laughs) but for them it's like, yes we have the delivery to promise, a promise to do that, right? But they come back to you and say, "Sorry, we couldn't make it, delivery didn't work and so on. It's going to be a new date. We are out of the product.", right? So these kind of event base asynchronous things are more and more what's going to scale around the world. It's going to be efficient for everybody, it's going to be better customer experience, better employee experience, ultimately better user experience, it's going to be better for the enterprise to build, but we have to learn to build it. So big announcement was to build our environment to build better eventful applications from today. >> Talk about... This is the first re:Invent... Well, actually, I'm sorry, it's the second re:Invent under Adam Selipsky. >> Right. Adam Selipsky, yep. >> But his first year. >> Right >> We're hearing a lot of momentum. What's your takeaway with what he delivered with the direction Amazon is going, their vision? >> Ja, I think compared to the Jassy times, right, we didn't see the hockey stick slide, right? With a number of innovations and releases. That was done in 2019 too, right? So I think it's a more pedestrian pace, which, ultimately, is good for everybody, because it means that when software vendors go slower, they do less width, but more depth. >> Yeah. >> And depth is what customers need. So Amazon's building more on the depth side, which is good news. I also think, and that's not official, right, but Adam Selipsky came from Tableau, right? >> Yeah. So he is a BI analytics guy. So it's no surprise we have three data lake offerings, right? Security data lake, we have a healthcare data lake and we have a supply chain data lake, right? Where all, again, the epigonos mentioned them I was like, "Oh, my god, Amazon's coming to supply chain.", but it's actually data lakes, which is an interesting part. But, I think it's not a surprise that someone who comes heavily out of the analytics BI world, it's off ringside, if I was pitching internally to him maybe I'd do something which he's is familiar with and I think that's what we see in the major announcement of his keynote on Tuesday. >> I mean, speaking of analytics, one of the big announcements early on was Amazon is trying to bridge the gap between Aurora. >> Yep. >> And Redshift. >> Right. >> And setting up for continuous pipelines, continuous integration. >> Right. >> Seems to be a trend that is common to all database players. I mean, Oracle is doing the same thing. SAP is doing the same thing. MariaDB. Do you see the distinction between transactional and analytical databases going away? >> It's coming together, right? Certainly coming together, from that perspective, but there's a fundamental different starting point, right? And with the big idea part, right? The universal database, which does everything for you in one system, whereas the suite of specialized databases, right? Oracle is in the classic Oracle database in the universal database camp. On the other side you have Amazon, which built a database. This is one of the first few Amazon re:Invents. It's my 10th where there was no new database announced. Right? >> No. >> So it was always add another one specially- >> I think they have enough. >> It's a great approach. They have enough, right? So it's a great approach to build something quick, which Amazon is all about. It's not so great when customers want to leverage things. And, ultimately, which I think with Selipsky, AWS is waking up to the enterprise saying, "I have all this different database and what is in them matters to me." >> Yeah. >> "So how can I get this better?" So no surprise between the two most popular database, Aurora and RDS. They're bring together the data with some out of the box parts. I think it's kind of, like, silly when Swami's saying, "Hey, no ETL.". (chuckles) Right? >> Yeah. >> There shouldn't be an ETL from the same vendor, right? There should be data pipes from that perspective anyway. So it looks like, on the overall value proposition database side, AWS is moving closer to the universal database on the Oracle side, right? Because, if you lift, of course, the universal database, under the hood, you see, well, there's different database there, different part there, you do something there, you have to configure stuff, which is also the case but it's one part of it, right, so. >> With that shift, talk about the value that's going to be in it for customers regardless of industry. >> Well, the value for customers is great, because when software vendors, or platform vendors, go in depth, you get more functionality, you get more maturity you get easier ways of setting up the whole things. You get ways of maintaining things. And you, ultimately, get lower TCO to build them, which is super important for enterprise. Because, here, this is the developer cloud, right? Developers love AWS. Developers are scarce, expensive. Might not be want to work for you, right? So developer velocity getting more done with same amount of developers, getting less done, less developers getting more done, is super crucial, super important. So this is all good news for enterprise banking on AWS and then providing them more efficiency, more automation, out of the box. >> Some of your customer conversations this week, talk to us about some of the feedback. What's the common denominator amongst customers right now? >> Customers are excited. First of all, like, first event, again in person, large, right? >> Yeah. >> People can travel, people meet each other, meet in person. They have a good handle around the complexity, which used to be a huge challenge in the past, because people say, "Do I do this?" I know so many CXOs saying, "Yeah, I want to build, say, something in IoT with AWS. The first reference built it like this, the next reference built it completely different. The third one built it completely different again. So now I'm doubting if my team has the skills to build things successfully, because will they be smart enough, like your teams, because there's no repetitiveness and that repetitiveness is going to be very important for AWS to come up with some higher packaging and version numbers.", right? But customers like that message. They like that things are working better together. They're not missing the big announcement, right? One of the traditional things of AWS would be, and they made it even proud, as a system, Jassy was saying, "If we look at the IT spend and we see something which is, like, high margin for us and not served well and we announced something there, right?" So Quick Start, Workspaces, where all liaisons where AWS went after traditional IT spend and had an offering. We haven't had this in 2019, we don't have them in 2020. Last year and didn't have it now. So something is changing on the AWS side. It's a little bit too early to figure out what, but they're not chewing off as many big things as they used in the past. >> Right. >> Yep. >> Did you get the sense that... Keith Townsend, from "The CTO Advisor", was on earlier. >> Yep. >> And he said he's been to many re:Invents, as you have, and he said that he got the sense that this is Amazon's chance to do a victory lap, as he called it. That this is a way for Amazon to reinforce the leadership cloud. >> Ja. >> And really, kind of, establish that nobody can come close to them, nobody can compete with them. >> You don't think that- >> I don't think that's at all... I mean, love Keith, he's a great guy, but I don't think that's the mindset at all, right? So, I mean, Jassy was always saying, "It's still the morning of the day in the cloud.", right? They're far away from being done. They're obsessed over being right. They do more work with the analysts. We think we got something right. And I like the passion, from that perspective. So I think Amazon's far from being complacent and the area, which is the biggest bit, right, the biggest. The only thing where Amazon truly has floundered, always floundered, is the AI space, right? So, 2018, Werner Vogels was doing more technical stuff that "Oh, this is all about linear regression.", right? And Amazon didn't start to put algorithms on silicon, right? And they have a three four trail and they didn't announce anything new here, behind Google who's been doing this for much, much longer than TPU platform, so. >> But they have now. >> They're keen aware. >> Yep. >> They now have three, or they own two of their own hardware platforms for AI. >> Right. >> They support the Intel platform. They seem to be catching up in that area. >> It's very hard to catch up on hardware, right? Because, there's release cycles, right? And just the volume that, just talking about the largest models that we have right now, to do with the language models, and Google is just doing a side note of saying, "Oh, we supported 50 less or 30 less, not little spoken languages, which I've never even heard of, because they're under banked and under supported and here's the language model, right? And I think it's all about little bit the organizational DNA of a company. I'm a strong believer in that. And, you have to remember AWS comes from the retail side, right? >> Yeah. >> Their roll out of data centers follows their retail strategy. Open secret, right? But, the same thing as the scale of the AI is very very different than if you take a look over at Google where it makes sense of the internet, right? The scale right away >> Right. >> is a solution, which is a good solution for some of the DNA of AWS. Also, Microsoft Azure is good. There has no chance to even get off the ship of that at Google, right? And these leaders with Google and it's not getting smaller, right? We didn't hear anything. I mean so much focused on data. Why do they focus so much on data? Because, data is the first step for AI. If AWS was doing a victory lap, data would've been done. They would own data, right? They would have a competitor to BigQuery Omni from the Google side to get data from the different clouds. There's crickets on that topic, right? So I think they know that they're catching up on the AI side, but it's really, really hard. It's not like in software where you can't acquire someone they could acquire in video. >> Not at Core Donovan. >> Might play a game, but that's not a good idea, right? So you can't, there's no shortcuts on the hardware side. As much as I'm a software guy and love software and don't like hardware, it's always a pain, right? There's no shortcuts there and there's nothing, which I think, has a new Artanium instance, of course, certainly, but they're not catching up. The distance is the same, yep. >> One of the things is funny, one of our guests, I think it was Tuesday, it was, it was right after Adam's keynote. >> Sure. >> Said that Adam Selipsky stood up on stage and talked about data for 52 minutes. >> Yeah. Right. >> It was timed, 52 minutes. >> Right. >> Huge emphasis on that. One of the things that Adam said to John Furrier when they were able to sit down >> Yeah >> a week or so ago at an event preview, was that CIOs and CEOs are not coming to Adam to talk about technology. They want to talk about transformation. They want to talk about business transformation. >> Sure, yes, yes. >> Talk to me in our last couple of minutes about what CEOs and CIOs are coming to you saying, "Holger, help us figure this out. We have to transform the business." >> Right. So we advise, I'm going quote our friends at Gartner, once the type A company. So we'll use technology aggressively, right? So take everything in the audience with a grain of salt, followers are the laggards, and so on. So for them, it's really the cusp of doing AI, right? Getting that data together. It has to be in the cloud. We live in the air of infinite computing. The cloud makes computing infinite, both from a storage, from a compute perspective, from an AI perspective, and then define new business models and create new best practices on top of that. Because, in the past, everything was fine out on premise, right? We talked about the (indistinct) size. Now in the cloud, it's just the business model to say, "Do I want to have a little more AI? Do I want a to run a little more? Will it give me the insight in the business?". So, that's the transformation that is happening, really. So, bringing your data together, this live conversation data, but not for bringing the data together. There's often the big win for the business for the first time to see the data. AWS is banking on that. The supply chain product, as an example. So many disparate systems, bring them them together. Big win for the business. But, the win for the business, ultimately, is when you change the paradigm from the user showing up to do something, to software doing stuff for us, right? >> Right. >> We have too much in this operator paradigm. If the user doesn't show up, doesn't find the click, doesn't find where to go, nothing happens. It can't be done in the 21st century, right? Software has to look over your shoulder. >> Good point. >> Understand one for you, autonomous self-driving systems. That's what CXOs, who're future looking, will be talked to come to AWS and all the other cloud vendors. >> Got it, last question for you. We're making a sizzle reel on Instagram. >> Yeah. >> If you had, like, a phrase, like, or a 30 second pitch that would describe re:Invent 2022 in the direction the company's going. What would that elevator pitch say? >> 30 second pitch? >> Yeah. >> All right, just timing. AWS is doing well. It's providing more depth, less breadth. Making things work together. It's catching up in some areas, has some interesting offerings, like the healthcare offering, the security data lake offering, which might change some things in the industry. It's staying the course and it's going strong. >> Ah, beautifully said, Holger. Thank you so much for joining Paul and me. >> Might have been too short. I don't know. (laughs) >> About 10 seconds left over. >> It was perfect, absolutely perfect. >> Thanks for having me. >> Perfect sizzle reel. >> Appreciate it. >> We appreciate your insights, what you're seeing this week, and the direction the company is going. We can't wait to see what happens in the next year. And, yeah. >> Thanks for having me. >> And of course, we've been on so many times. We know we're going to have you back. (laughs) >> Looking forward to it, thank you. >> All right, for Holger Mueller and Paul Gillan, I'm Lisa Martin. You're watching "theCube", the leader in live enterprise and emerging tech coverage. (upbeat music)

>>we're back, we're assessing the as a service space. H. P. S. Green Lake announcements, my name is Dave balanta, you're watching the cube die on Hinchcliffe is here along with Holger muller, these are the constellation kids, extraordinary analysts guys. Great to see you again. I mean it super experienced. You guys, you deal with practitioners, you deal your technologist, you've been following this business for a long time. Diane, We spoke to Holger earlier, I want to start with you uh when you look at this whole trend to as a service, you see a lot of traditional enterprise companies, hard traditionally hardware companies making that move for for a lot of obvious reasons are they sort of replicating in your view, a market that you know well and sas what's your take on how they're doing generally that trend and how HP is >>operating well. Hp has had a unique heritage. They're coming at the whole cloud story and you know the Hyper Scaler story from a different angle than a lot of their competitors and that's mostly a good thing because most of the world is not yet on the cloud, They actually came from H. P. S original world, their line of servers and networks and so on. Um and and so they bring a lot of credibility saying we really understand the world you live in now but we want to take you to that that as a service future. Uh and and you know, since we understand you so well and we also understand where this is going and we can adapt that to that world. Have a very compelling story and I think that with green like you know, was first started about four years ago, it was off to the side uh you know, with all the other offerings now it's it's really grown up, it's matured a lot and I think you know, as we talked about the announcements, we'll see that a lot of key pieces have fallen into place to make it a very compelling hybrid cloud option for the enterprise. >>Let's talk about the announcement. Was there anything in particular that stood out the move to data management? I think it's pretty interesting is a tam expansion strategy. What's your take on the >>announcement? Well, the you know, the unified analytics uh story I think is really important now. That's the technology piece where they say, they say we can give you a data fabric, you can access your data outside of its silos. It doesn't address a lot of the process and cultural issues around data ownership inside the enterprise, but it's you know, having in the actual platform and as you articulating it as a platform, that's one of the things that was also evident, they were getting better and better at saying this is a hybrid cloud platform and it has all the pieces that you would expect, especially the things like being able to bring your data from wherever it is to wherever people needed to be. Uh you know, that's the Holy Grail, so really glad to see that component in particular. I also like the cloud adoption framework saying we understand how to take you from this parochial world of servers that you have and do a cloud date of hybrid world and then maybe eventually get you get you to a public cloud. We understand all the steps and all the components uh I think that's uh you know, I have a study that fully in depth but it seems to have all the moving parts >>chime in anything stand out to, you >>know, I think it's great announcements and the most important things H. P. S and transformation and when you and transformation people realize who you've been, the old and they're here. Maybe the mass of the new but an experienced technology but I will not right away saying oh it's gonna happen right. It's going to happen like this is gonna be done, it's ready, it's materials ready to use and so on. So this is going to give more data points, more proof points, more capabilities that HB is moving away from whatever they were before. That's not even say that to a software services as a service as you mentioned provider. It's >>been challenging, you look at the course of history for companies that try to go from being a hardware company to a software company, uh HP itself, you know, sort of gave up on that IBM you could say, you know semi succeeded but they've they've struggled what's different >>That will spend 30 billion, >>30 >>four. Exactly. So and of course Cisco is making that transition. I mean every traditional large companies in that transition. What about today? Well, first of all, what do you think about HP es, prospects of doing so? And are there things today in the business that make that, you know more faster, whether it's containers or the cloud itself or just the scale of the internet? >>I mean it's fascinating topic, right? And I think many of the traditional players in the space failed because they wanted to mimic the cloud players and they simply couldn't muster up the Capex, which you need to build up public cloud. Right? Because if you think of the public cloud players then didn't put it up for the cloud offering, they put it up because they need themselves right, amazon is an online retailer google as a search and advertising giant Microsoft is organic load from from from office, which they had to bring to the cloud. So it was easier for them to do that. So no wonder they failed. The good news is they haven't lost much of their organic load. Hp customers are still HP customer service, celebrity security in their own premises and now they're bringing the qualities of the cloud as a service, the pay as you go capabilities to the on premise stack, which helps night leader to reduce complexity and go to what everybody in the post pandemic world wants to get to, which is I only pay for what I use and that's super crucial because business goes up and down. We're riding all the waves in a much, much faster way than ever before. Right before we had seven year cycles, it was kind of like cozy almost now we're down to seven weeks, sometimes seven days, sometimes seven hour cycles. And I don't want to pay for it infrastructure, which was great for how my business was two years ago. I want to pay for it as I use it now as a pivot now and I'm going to use >>Diane. How much of this? Thank you for that whole girl. How much of this is what customers want and need versus sort of survival tactics on the vendors >>part. So I think that there, if you look at where customers want to go, they know they have to go cloud, they had to go as a service. Um, and that they need to make multiple steps to get there. And for the most part, I see green light is being a, a highly credible market response to say, you know, we understand IT better, we helped build you guys up over the last 30 years. We can take you the rest of the way, here's all the evidence and the proof points, which I think a lot of the announcements provide uh, and they're very good on cloud native, but the area where the story, um, you may not be the fullest strength it needs to be is around things like multi cloud. So when I talked to almost any large organization C I O. They have all the clouds need to know, how do I make all this fit together? How do I reconcile that? So for the most part, I think it's closely aligned with actual customer requirements and customer needs. I think these have additional steps to go >>is that, do you feel like that's a a priority? In other words, they got to kind of take a linear path. They got to solve the problem for their core customer base or is it, do you feel like that's not even necessarily an aspiration? And it seems like customers, I want them to go. There is what I'm >>inferring that you're, so I do. Well let's go back to the announcement specifically. So there's there are two great operational announcements, one around the cloud physics and the other one around info site. It gives a wealth of data, you know, full stack about how things are operating, where the needs are, how you might be able to get more efficiencies, how you can shut down silicon, you're not using a lot of really great information, but all that has to live with a whole bunch of other consoles and everybody is really craving the single piece of glass. That's what they want is they want to reduce complexity as holder was saying and say, I want to be able to get my arms around my data center and all of my cloud assets. But I don't want to have to check each cloud. I want it in one place. So uh, but it's great to see those announcements position them for that next step. They have these essential components that are that look, you know, uh, they look best to breed in terms of their capabilities are certainly very modern now. They have to get the rest of that story. >>Hope you were mentioning Capex. I added it up I think last year the big four include Alibaba, spent 100 billion on the Capex and generally the traditional on prem players have been defensive around cloud. Not everything is moving to the cloud, we all know that. But I, I see that as a gift in a way that the companies like HP can build on top of into Diane's point that, you know, extend cross clouds out to the edge, which is, you know, a trillion dollar opportunity, which is just just massive. What are your thoughts on HBs opportunities there and chances of maybe breaking away from the pack >>I think definitely well there's no matter pack left, like there's only 23, it's a triumvirate of maybe it's a good thing from a marketing standpoint. There's not a long list of people who give me hardware in my data center. But I think it increases their chances, right? Like I said, it's a transformation, there's more credibility, there's more data point, there's more usage. I can put more workloads on this. And I see, I also will pay attention to that and look at that for the transformation. No question. >>Yeah. And speaking of C. I. O. S. What are you hearing these days? What's their reaction to this whole trend toward as a service? Do they, do they welcome it? Do they feel like okay it's a wait and see. Uh I need more proof points. What's the sentiment? >>Well, you have to divide the Ceo market basically two large groups. One is the the ones that are highly mature. They tend to be in larger organizations are very sophisticated consumers of everything. They see the writing on the wall and that for most things certainly not everything as a service makes the most sense for all the reasons we know, agility and and and speed, you know, time to value scalability, elasticity, all those great things. Uh And then you have the the other side of the market which they really crave control. They have highly parochial worlds that they've built up um that are hard to move to the cloud because they're so complex and intertwined because they haven't had that high maturity. They have a lot of spaghetti architecture. They're not really ready to move the cloud very quickly. So the the second audience though is the largest one and it's uh you know, the hyper scales are probably getting a lot of the first ones. Um, but the bigger markets, really the second one where the folks that need a lot of help and they have a lot of legacy hardware and software that they need to move and that H P. E understands very well. And so I think from that standpoint they're well positioned to take advantage of an untapped market are relatively untapped market in comparison. Hey, >>in our business we all get pulled in different directions because it would get to eat. But what are some of the cool things you guys are working on in your research that you might want people to know about? >>Uh, I just did a market overview for enterprise application platforms. I'm a strong believer that you should not build all your enterprise software yourself, but you can't use everything that you get from your typical SAs provider. So it's focusing on the extent integration and build capabilities. Bill is very, very important to create the differentiation in the marketplace and all the known sauce players basically for their past. Right? My final example is always to speak in cartoons, right? The peanuts, right? There's Linus of this comfort blanket. Right? The past capability of the SARS player is the comfort blanket, right? You don't fit 100% there or you want to build something strategic or we'll never get to that micro vertical. We have a great enterprise application, interesting topic. >>Especially when you see what's happening with Salesforce and Service now trying to be the platform platforms. I have to check that out. How about >>Diane? Well and last year I had a survey conducted a survey with the top 100 C IOS and at least in my view about what they're gonna do to get through this year. And so I'm redoing that again to say, you know, what are they gonna do in 2022? Because there's so many changes in the world and so, you know, last year digital transformation, automation cybersecurity, we're at the top of the list and it'll be very interesting. Cloud was there too in the top five. So we're gonna see what, how it's all going to change because next year is the year of hybrid work where we're all we have to figure out how half of our businesses are in the office and half are at home and how we're gonna connect those together and what tools we're gonna make, that everybody's trying to figure >>out how to get hybrid. Right, so definitely want to check out that research guys. Thanks so much for coming to the cubes. Great to see you. >>Thanks. Thanks Dave >>Welcome. Okay and thank you for watching everybody keep it right there for more great content from H. P. S. Green Lake announcement. You're watching the cube. Mm this wasn't

>>Live from San Diego, California It's the Q covering Koopa and Cloud Native Cot brought to you by Red Cloud, Native Computing Pounding and its ecosystem March. >>Welcome back to the Cube here at Q. Khan Club native Khan, 2019 in San Diego, California Instrumental in my co host is Jon Cryer and first of all, happy to welcome back to the program. Diane Mueller, who is the technical of the tech lead of cloud native technology. I'm sorry. I'm getting the wrong That's director of community development Red Hat, because renew. Goodbye is the technical lead of cognitive technologies at in video game to the end of day one. I've got three days. I gotta make sure >>you get a little more Red Bull in the conversation. >>All right, well, there's definitely a lot of energy. Most people we don't even need Red Bull here because we're a day one. But Diane, we're going to start a day zero. So, you know, you know, you've got a good group of community of geeks when they're like Oh, yeah, let me fly in a day early and do like 1/2 day or full day of deep dives. There So the Red Hat team decided to bring everybody on a boat, I guess. >>Yeah. So, um, open ships Commons gathering for this coup con we hosted at on the inspiration Hornblower. We had about 560 people on a boat. I promised them that it wouldn't leave the dock, but we deal still have a little bit of that weight going on every time one of the big military boats came by. And so people were like a little, you know, by the end of the day, but from 8 a.m. in the morning till 8 p.m. In the evening, we just gathered had some amazing deep dives. There was unbelievable conversations onstage offstage on we had, ah, wonderful conversation with some of the new Dev ops folks that have just come on board. That's a metaphor for navigation and Coop gone. And and for events, you know, Andrew Cliche for John Willis, the inevitable Crispin Ella, who runs Open Innovation Labs, and J Bloom have all just formed the global Transformation Office. I love that title on dhe. They're gonna be helping Thio preach the gospel of Cultural Dev ops and agile transformation from a red hat office From now going on, there was a wonderful conversation. I felt privileged to actually get to moderate it and then just amazing people coming forward and sharing their stories. It was a great session. Steve Dake, who's with IBM doing all the SDO stuff? Did you know I've never seen SDO done so well, Deployment explains so well and all of the contents gonna be recorded and up on Aaron. We streamed it live on Facebook. But I'm still, like reeling from the amount of information overload. And I think that's the nice thing about doing a day zero event is that it's a smaller group of people. So we had 600 people register, but I think was 560 something. People show up and we got that facial recognition so that now when they're traveling through the hallways here with 12,000 other people, that go Oh, you were in the room. I met you there. And that's really the whole purpose for comments. Events? >>Yeah, I tell you, this is definitely one of those shows that it doesn't take long where I say, Hey, my brain is full. Can I go home. Now. You know I love your first impressions of Q Khan. Did you get to go to the day zero event And, uh, what sort of things have you been seeing? So >>I've been mostly I went to the lightning talks, which were amazing. Anything? Definitely. There. A number of shout outs to the GPU one, of course. Uh, friend in video. But I definitely enjoyed, for example, of the amazing D. M s one, the one about operators. And generally all of them were very high quality. >>Is this your first Q? Khan, >>I've been there. I've been a year. This is my third con. I've been accused in Europe in the past. Send you an >>old hat old hand at this. Well, before we get into the operator framework and I wanna love to dig into this, I just wanted to ask one more thought. Thought about open shift, Commons, The Commons in general, the relationship between open shift, the the offering. And then Okay, the comments and okay, D and then maybe the announcement about about Okay. Dee da da i o >>s. Oh, a couple of things happened yesterday. Yesterday we dropped. Okay, D for the Alfa release. So anyone who wants to test that out and try it out it's an all operators based a deployment of open shift, which is what open ship for is. It's all a slightly new architectural deployment methodology based on the operator framework, and we've been working very diligently. Thio populate operator hub dot io, which is where all of the upstream projects that have operators like the one that Reynolds has created for in the videos GP use are being hosted so that anyone could deploy them, whether on open shift or any kubernetes so that that dropped. And yesterday we dropped um, and announced Open Sourcing Quay as project quay dot io. So there's a lot of Io is going on here, but project dia dot io is, um, it's a fulfillment, really, of a commitment by Red Hat that whenever we do an acquisition and the poor folks have been their acquired by Cora West's and Cora Weston acquired by Red Hat in an IBM there. And so in the interim, they've been diligently working away to make the code available as open source. And that hit last week and, um, to some really interesting and users that are coming up and now looking forward to having them to contribute to that project as well. But I think the operator framework really has been a big thing that we've been really hearing, getting a lot of uptake on. It's been the new pattern for deploying applications or service is on getting things beyond just a basic install of a service on open shift or any kubernetes. And that's really where one of the exciting things yesterday on we were talking, you know, and I were talking about this earlier was that Exxon Mobil sent a data scientist to the open ship Commons, Audrey Resnick, who gave this amazing presentation about Jupiter Hub, deeper notebooks, deploying them and how like open shift and the advent of operators for things like GP use is really helping them enable data scientists to do their work. Because a lot of the stuff that data signs it's do is almost disposable. They'll run an experiment. Maybe they don't get the result they want, and then it just goes away, which is perfect for a kubernetes workload. But there are other things you need, like a Jeep use and work that video has been doing to enable that on open shift has been just really very helpful. And it was It was a great talk, but we were talking about it from the first day. Signs don't want to know anything about what's under the hood. They just want to run their experiments. So, >>you know, let's like to understand how you got involved in the creation of the operator. >>So generally, if we take a step back and look a bit at what we're trying to do is with a I am l and generally like EJ infrastructure and five G. We're seeing a lot of people. They're trying to build and run applications. Whether it's in data Center at the and we're trying to do here with this operator is to bring GPS to enterprise communities. And this is what we're working with. Red Hat. And this is where, for example, things like the op Agrestic A helps us a lot. So what we've built is this video Gee, few operator that space on the upper air sdk where it wants us to multiple phases to in the first space, for example, install all the components that a data scientist were generally a GPU cluster of might want to need. Whether it's the NVIDIA driver, the container runtime, the community's device again feast do is as you go on and build an infrastructure. You want to be able to have the automation that is here and, more importantly, the update part. So being able to update your different components, face three is generally being able to have a life cycle. So as you manage multiple machines, these are going to get into different states. Some of them are gonna fail, being able to get from these bad states to good states. How do you recover from them? It's super helpful. And then last one is monitoring, which is being able to actually given sites dr users. So the upper here is decay has helped us a lot here, just laying out these different state slips. And in a way, it's done the same thing as what we're trying to do for our customers. The different data scientists, which is basically get out of our way and allow us to focus on core business value. So the operator, who basically takes care of things that are pretty cool as an engineer I lost due to your election. But it doesn't really help me to focus on like my core business value. How do I do with the updates, >>you know? Can I step back one second, maybe go up a level? The problem here is that each physical machine has only ah limited number of NVIDIA. GPU is there and you've got a bunch of containers that maybe spawning on different machines. And so they have to figure out, Do I have a GPU? Can I grab one? And if I'm using it, I assume I have to reserve it and other people can't use and then I have to give it up. Is that is that the problem we're solving here? So this is >>a problem that we've worked with communities community so that like the whole resource management, it's something that is integrated almost first class, citizen in communities, being able to advertise the number of deep, use their your cluster and used and then being able to actually run or schedule these containers. The interesting components that were also recently added are, for example, the monitoring being able to see that a specific Jupiter notebook is using this much of GP utilization. So these air supercool like features that have been coming in the past two years in communities and which red hat has been super helpful, at least in these discussions pushing these different features forward so that we see better enterprise support. Yeah, >>I think the thing with with operators and the operator lifecycle management part of it is really trying to get to Day two. So lots of different methodologies, whether it's danceable or python or job or or UH, that's helm or anything else that can get you an insult of a service or an application or something. And in Stan, she ate it. But and the operator and we support all of that with SD case to help people. But what we're trying to do is bridge the to this day to stuff So Thea, you know, to get people to auto pilot, you know, and there's a whole capacity maturity model that if you go to operator hab dot io, you can see different operators are a different stages of the game. So it's been it's been interesting to work with people to see Theo ah ha moment when they realize Oh, I could do this and then I can walk away. And then if that pod that cluster dies, it'll just you know, I love the word automatically, but they, you know, it's really the goal is to help alleviate the hands on part of Day two and get more automation into the service's and applications we deploy >>right and when they when they this is created. Of course it works well with open shift, but it also works for any kubernetes >>correct operator. HAB Daddio. Everything in there runs on any kubernetes, and that's really the goal is to be ableto take stuff in a hybrid cloud model. You want to be able to run it anywhere you want, so we want people to be unable to do it anywhere. >>So if this really should be an enabler for everything that it's Vinny has been doing to be fully cloud native, Yes, >>I think completely arable here is this is a new attack. Of course, this is a bit there's a lot of complexity, and this is where we're working towards is reducing the complexity and making true that people there. Dan did that a scientist air machine learning engineers are able to focus on their core business. >>You watch all of the different service is in the different things that the data scientists are using. They don't I really want to know what's under under the hood. They would like to just open up a Jupiter Hub notebook, have everything there. They need, train their models, have them run. And then after they're done, they're done and it goes away. And hopefully they remember to turn off the Jeep, use in the woods or wherever it is, and they don't keep getting billed for it. But that's the real beauty of it is that they don't have to worry so much anymore about that. And we've got a whole nice life cycle with source to image or us to I. And they could just quickly build on deploy its been, you know, it's near and dear to my heart, the machine learning the eyesight of stuff. It is one of the more interesting, you know, it's the catchy thing, but the work was, but people are really doing it today, and it's been we had 23 weeks ago in San Francisco, we had a whole open ship comments gathering just on a I and ML and you know, it was amazing to hear. I think that's the most redeeming thing or most rewarding thing rather for people who are working on Kubernetes is to have the folks who are doing workloads come and say, Wow, you know, this is what we're doing because we don't get to see that all the time. And it was pretty amazing. And it's been, you know, makes it all worthwhile. So >>Diane Renaud, thank you so much for the update. Congratulations on the launch of the operators and look forward to hearing more in the future. >>All right >>to >>be here >>for John Troy runs to minimum. More coverage here from Q. Khan Club native Khan, 2019. Thanks for watching. Thank you.

>> Live from Seattle, Washington, it's theCUBE, covering KubeCon, and CloudNativeCon North America 2018. Brought to you by Red Hat, the CloudNative Computing Foundation, and the Antigo System Partners. >> Hey, welcome back everyone live here in Seattle for the theCUBE's coverage of KubeCon and CloundNativeCon 2018. I'm John Furrier, theCUBE with Stu Miniman, breaking down all the action. Three days of coverage, we're in day two. A lot of action at Open-source. 8,000 attendees, up from 4,000 North America, they were in China, they were all over Europe. The community's growing in a massive way. We had two great guests from Red Hat, all making it happen, part of the community. We've got Diane Mueller, whose theCUBE alumni director of community development, many times on theCUBE, good to see you, and Rob Szumski, principal product manager, both at Red Hat. Guys, thanks for coming on. Great to see you again. >> Yeah, glad to be here. - Great to be here. >> So the world's changing a lot, and there was some news recently around Red Hat. I can't remember what it was. Recently, something big news, but you guys have been big players in Open-source for years. We always cover it, we always wax on about the origination of it and how the evolution, but the CloudNative piece has gotten so real, and your role in it particularly, we've had many conversations, going maybe back to the OpenStack days of how OpenShift was developing, then the bet on Kubernetes that you made, Core OS acquisition, those two things I think, to me, at least from my perspective, really catalyzed a lot of things at the right time, right? So, from there, just a lot of things has just been happening really in a good way. Big tail wind for you guys, CloudNative app developers are using Open-source, CI/CD pipeline, and then also policy based up under the hood, completely big shift in moving the game down the field. So big congratulations first of all. But what's new? What's the update? >> The update is Operators. I think the next big thing that we are really focusing on, and that's a game changer for all the second day operations type things, and we'll make Rob talk about it in detail, is the rise of Kubernetes' Operators. It's not a scary thing, it's not like terminator day, or anything like that, but it is really the thing that helps us make the service catalogs, the Kubernetes marketplaces really accessible to all of the data bases as a service, and all of the other things, and takes out some of the complexity of delivering applications and database  as a Service to anybody running Kubernetes anywhere. >> Take a minute to explain Operator, real quick, and then we can jump into it, because I think this is a fundamental trend, that we're seeing. Developer trend is pretty obvious, it's been that word for awhile, CloudScale, ML, machine learning, and all the goodness around application development, but the Operator side of it has been an IT thing. But now you guys have a different, a new approach that's winning. What is it? What is Operator? >> Well, it's Kubernetes that has the approach, and I'll let you-- >> Yeah, so it's basically like the rise of containers was great, because you could take a single container and package an application and give to somebody, and know that they can run it successfully. And Operator does that for a distributed system in the exact same way. So you're using all the Kubernetes primitives, so you're not reinventing service discovery, and seeker management, and all that. And you can give somebody an entire Kafka stack, or a machine learning stack, or whatever it is, these very complex distributed systems, and have them run it without having to be an expert. They need to know Kafka at a high level, but not exactly all the underpinnings of it, because that's all baked in the software. >> And the benefit and the impact of the organization is what? >> And just to clarify, so this was added in, I believe Kubernetes is like 1.7, it's something that's in there, it's not something Red Hat specific- >> Yeah, it's like-- >> So you're extending Kubernetes so that you have a custom resource definition, which is an extensible mechanism for saying, hey, I've got a deployment or a staple set, but what if I want to have a new object called a MongoDB? That knows how to deploy, and manage, and upgrade MongoDB. So that's the extension mechanism that we're using. >> Yeah, so you got to think, there's certain applications that this is going to make, just a lot easier how I manage them, deploy them, things like that. Any specific examples you want to share as to-- >> All the clustered data bases. >> There's a lot of the application side in this model have been very excited about this. >> So its all the vendors and partners that want a hybrid Cloud story, just targeting Kubernetes, and we're using Kubernetes under the hood, and then everybody wants to run like a staple data base tier, whether that's Mongo and Couchbase, and Cassandra, whatever. And these are all distributed systems. >> Alright, so I want you to just perch, you said a hybrid Cloud. Explain that model, because there's just something in general discussion that is hybrid or multi means I'm running multiple places, I'm not necessarily stretching an application, but I have instances there, just want to make sure we're on the same page. >> So this would be more the compatibility that you're programming against when you're building an operator, is Kubernetes. It's not a Cloud offering, it's not OpenShift, so you're just targeting Kubernetes, and so you can run MongoDB on prem, in the Cloud, and have it function the exact same, by standing up one of these Operators. And then if that Operator has higher level constructs for how to do multi-cluster aware data rebalancing, you can take advantage of that too. >> And the Open-source status of this product is what? >> It's all Open-source, it's all in the github repos, there's a Google group for Operator framework, that anyone can come and participate in. We hold SIG meetings on the third Friday of every month, 9 a.m. Pacific Time, and it's a completely Open-source project. There's a whole framework around it, so there's the Operator SDK, the Operator Lifecycle Management, and Operator metering, all the tooling there to help people build and manage these Operators, and it's all being built out there in the open with the community's support and feedback loops. >> What's the feedback? What's the top feedback you guys are getting right now? Seeing right now? >> I have to say, this is really, like I've been hanging out with you guys like for the past three, four months on this topic, trying to get my head around it and everything, and we came here and we had two sessions, an intro session and a deep dive session, intro yesterday, deep dive today. Today's deep dive, the room was about 250 people, and they're were people outside of it-- >> Security guards blocking people from coming in. >> Nobody could come in and it's like, it's insane. It's like, everybody needs these things, and everybody wants to figure out that, and when you ask people in the room whose building one, half the room raises their hands. It's just crazy. This thing crept up on us really, maybe not on Core OS, okay, it crept up on me very quickly, and it's very rapid adoption. We have a Kubernetes Operators workshop on Friday, so not only do we have pre-conference days of like OpenShift Cons that are huge now, but now we're starting to book end, CNCF events and put on other things, just because, and that, we had 100 seats that we were hoping we would fill, and it sold out in like minutes once it got in there, and there's a waiting list of like 300 people. It is like one of, aside from Knative, and all the other wonderful hot things too, it is one of the most interesting developments I think right now. >> Thirst for the content. Would it impact? >> Yeah, and you can get all of the documentation is out there now, and people are already building them. We have a list of 50 community Operators. It's just, it's phenomenal how quickly it's growing. >> You know, Diane and Rob, it's funny because you know, we do so many of these theCUBE interviews, and this is our 10th year doing theCUBE coming up, and I remember the conversations going back in the OpenStack days, we would ask questions like, if you had a magic wand, what would you like, hope to have happened, right? And you know, those are parts of the evolution, where it's like, it's aspirational, things are being built. It seems now with Kubernetes, it's almost like, wait a minute, it's actually, this is like the goodness is so compelling, above and below Kubernetes that it's almost like uncomprehendible. You think about, oh this is actually happening. Finally the kinds of steady state kind of operational things that have been a pain in the butt for years-- >> Yeah, the toil, it's gone, for the most part. >> Yeah. >> So Rob, I've been having a lot of just thinking back to, you're employee number two at Core OS, when I first talked to Core OS, it was, we're going to build all of these individual tools, and we're going to Open-source them, and it's going to be good. We watched this just rising ecosystem and the CNCF, and it feels like what's nice and what's different that I see, compared to some previous things, is it's not one product or even a small group of companies. It's, I have this tool kit, and some of them work together, but many of them are independently used. We've talked to your peers earlier about it, etCD. etCD is totally stand alone, doesn't need to be Kubernetes. What have you seen, if you go back to that original vision, would Core OS just been, part of this whole ecosystem, and done it, if this was available, and has this delivering on a promise that your team had hoped to work on? >> Yeah, so we've always filled in where we see gaps, and so something like etCD, the concept is not new, and it comes from Google, and they have a system internally, and as Brandon got up on stage and said, we needed that coordinate, reboot, to grow out, to cluster of machines. It didn't exist so we had to build it. Same thing with how we wanted to manage Linux. There was no distro that even resembled what we were doing. Wanted to do automatic upgrades, people thought that was crazy, so we had to go build it. And so, but we always adopted the best of breed technology, when it existed. In our early bet Kubernetes, we just saw, this is the thing, and went for it. I don't even remember what version, but it was months and months before it was zero point oh, or one point oh, so it was, we've been doing it forever. And you just see the right thing, and it's the little nugget that you need, and if you don't see it, then you build it. >> What are you surprised about Rob, in terms of the ecosystem now, you mentioned some goodness is happening, still a lot more to do, visibility around value creation, you're starting to see spots where value can be created in the ecosystem, which is great. Still more work areas, but what's surprising you? What do you see as opportunities, challenges? Your thoughts, because this vision of ease of use and programmability, is happening, right? So there's still more work to do. What's your vision there? What's your thoughts? >> I mean, I think self service is key, so this is like the rise of the Cloud comes from self service for developers, and Kubernetes gives you the right abstraction, where self service for VM's, like OpenStack, which is not quite at the level of what you want. You don't want a VM, you actually wanted a place to deploy an application, you wanted load balancing, you wanted service discovery, you didn't want like a bare Ubuntu VM, and so Kubernetes raises you up to where you're productive, and then it's about building stuff on top. But what's interesting, in the space is, we're still kind of competing on Kubernetes installers, and stuff like that, so we're not even really into like the phase where people are being super productive on the platform, other than these leading companies. So I think we'll democratize that, and we'll have a whole new landscape. >> And so 2019 you see as what being a key theme for Kubernetes? >> I think it'll be Core stuff built on top, like all the serverless frameworks, a bunch of container natives storage solutions, solving some of these problems that folks are reaching out to external machine learning, but bringing that onto the cluster, GPU support, that type of stuff. It's all about the workloads. >> And tradition end users, you have a huge install base, with Red Hat, well documented, as the end users start coming in and looking at CloudNative, and doing a reimagine of their environment, whether it's IT span, IT investments, to have a run their coding and the deployments. It's going to change. 2019's going to have an impact on what I call mainstream enterprise, for lack of a better description. What's the impact of those guys, 'cause now, they now have head room, they can do more, what's the main stream enterprise look like right now with the impact of Kubernetes? >> I think they're going to start deploying applications and get like lower the time to business value, much, much lower. And I was just talking to a customer, and they ordered bare metal machines like a year ago, and they're still not racked and in the data center. And so people are still getting over that type of stuff, but once you have like a shared Kubernetes layer, you can onboard teams like crazy. I mean, name spaces are free, quote, unquote, and you can get 35 engineering teams on a Kubernetes cluster super easy. >> So they can ramp up in development teams basically, as they bring value in-house, versus outsourcing everything. They start getting development teams, this is where the action is. >> I think you're also going to see the rise of those end users contributing back things, to the Kubernetes community and as Lyft, and Uber, and everybody are great examples of that. Uber with Jaeger, and Lyft is, we were just in the Operators thing, and they raised their hand that they are about to Open-source it, a few Operators that they're building and stuff, and you're just going to see people that you didn't normally see. Often these large foundation driven things are vendor driven, but I think what you see here, is the end user community is now embracing the Open-source, is getting the legal teams there, allowing them to share their things, because one, they get more people to maintain them, and more people working on them, but it's really I think the rise of the end user we'll see, as they start participating more and more in here. And that's the promise of Open-source. >> And that's where CNCF really made it's bones. It wasn't really vendor led per se, it was really end users, the guys building out their stuff for the first time. You see Lyft for instance, great example, you guys did a Core OS, this is like the new generational model. Final question before we break. I want to get this out there. Get a plug in for Red Hat. What are you guys, what's the focus for the show? What's the news? What's the big story for Red Hat here at KubeCon this year? >> I think it's Operators, that's what we're here talking about. It's a really big push to once again get smarter workloads onto the cluster. We've got a really great hybrid story, we've got a really great over the air upgrade story that we're bringing from some of the Core OS technology, and then the next thing is, once it's easy to run 35 clusters, we need a bunch of workloads to put on there. And so we want to save folks from the toil of running all those workloads as well, just like we did at the cluster level. >> Awesome. >> Well put. I couldn't add more. One of the things that Core OS did, you hit the nail on the head earlier, is when there was something missing, they helped us build it, and with the Operator SDK, and the Lifecycle Management, and the metering, and whatever else the tooling is, they have really been inspirational inside of Red Hat. And so they filled a number of gaps, and it's just been all Operators all the time right now. >> It's great when a plan comes together. You guys got a great tail wind. Congratulations on all the success, and it's just the beginning of the wave. It's theCUBE, covering the wave of innovation here at KubeCon CloudNativeCon 2018, we'll be back with more live coverage. Day two of Three days of Kube Coverage. We'll be right back. (upbeat music)

>> Narrator: From Copenhagen, Denmark, it's theCUBE, covering KubeCon, and CloudNativeCon Europe 2018. Brought to you by the Cloud Native Computing Foundation, and its ecosystem partners. >> Okay, welcome back, everyone, live coverage here in theCUBE, in Europe, at Copenhagen, Denmark for KubeCon Europe 2018. This is theCUBE. We have the CNCF, at the Cloud Native Computing Foundation, part of the Linux Foundation. I'm John Furrier, co-host of theCUBE, with Lauren Cooney, the founder of SparkLabs, new venture around open source and innovation. Our analysts here, today with theCUBE, and our two guests are Michael Hausenblas, who's the direct developer advocate at Red Hat. Diane Meuller's the director of community development at Red Hat, talking about OpenShift, Red Hat, and just the rise and success of OpenShift. It's been really well-documented here on theCUBE, but certainly, in the industry, everyone's taking notice. Great to see you again, welcome to theCUBE, good to see you. >> Thank you. >> And wonderful to be here again. >> So, first of all, a lot of big news going on. CoreOS is now part of Red Hat, so that's exciting. I haven't had a chance to talk to you guys about that yet here on theCUBE, but great, great puzzle piece from the industry there for you guys, congratulations. >> Yeah, it's been a wonderful collaboration, having the CoreOS team as part of the Red Hat, and the OpenShift team, it's just a perfect fit. And the team from CoreOS, they've always been my favorite people. Alright, and Brandon Philips and the team over there are just awesome. And to have the expertise from Tectonics, the operator framework, which you'll hear more about here at KubeCon EU this week, to have Quay under the wings of Red Hat now, and Quay is a registry with OpenShift or with any other Kubernetes, you know, the stuff that they brought to the table, and the expertise, as well as the wonderful culture that they had, it was such a perfect fit with OpenShift. >> And you know, you guys bring a lot to the table, too. And I was, I mean, I've been kind of critical of CoreOS in the past, in a good way, 'cause I love those guys. I had good chats with them over the years, but they were so pure open-source guys, like Red Hat. >> Diane: Well, there's nothing wrong with being pure open-source. (laughing) >> No, no, I'm cool with that, but you guys have perfected the business more, you have great customers. So one of the things that they were always strong at was the open-source piece but when you start to monetize, and you start to get into the commercialization, it's hard for a start-up to be both, pure open-source and to monetize. You guys now have it together, >> Yeah. >> Great fit. >> So, it's a wonderful thing. We, on the OpenShift side, we have the OpenShift Commons, which is our open-source community, and we've sort of flipped the model of community development and that's at Red Hat. And one of the things is, they've been really strong, CoreOS, with their open-source projects, whether etcd, or you know, a whole myriad of other things. >> Well, let's double down on that. I want to get your thoughts. What is this OpenShift Commons? Take a minute to talk about what you guys had. You had an event Monday. It was the word on the streets, here in the hallways, is very positive. Take a minute to explain what happened, what's going on with that program? >> So OpenShift Commons is the open-source community around OpenShift Origin, but it also includes all the upstream projects that we collaborate with, with everybody from the Kubernetes world, from the Promytheus, all the CNCF project leads, all kinds of people from the upstream projects that are part of the OpenShift Ecosystem, as well as all the service providers and partners, who are doing wonderful things, and all the hosts, like Google, and you know, Microsoft Azure folks are in there. But, we've kind of flipped the model of community development on its head. In the past, if you were a community manager, which is what I started out as, you were trying to get people to contribute to your own code base. And here, because there's so much cross-community collaboration going on, we've got people working on Kubernetes. We got Kubernetes people making commits to Origin. We work on the OCI Foundation, trying to get the container stuff all figured out. >> So when you say you flipped the model, you mean there's now multiple-project contributions going on, or? >> Yeah, we've got our fingers in lots of pies now, and we have to, the collaboration has to be open, and there has to be a lot of communication. So the OpenShift Commons is really about creating those peer-to-peer networks. We do a lot of stuff virtual. I host my own OpenShift Commons briefings twice a week, and I could probably go to three or four days a week, and do it, because there's so much information. There's a fire hose of new stuff, new features, new releases, and stuff. Michael just did one on FAS. You did one before for the machine-learning Saigon OpenShift on Callum. >> Hold on, I want to just get your thoughts, Michael, on this, because what came up yesterday on theCUBE, was integration glue layers are really important. So I can see the connection here. Having this Commons model allows people to kind of cross-pollenate, one. Two, talk about integration, because we've got Promytheus, I might use KubeFlow. So there's new things happening. What does this mean for the integration piece? Good for it, or accelerating it? What's your thoughts? >> Right, right, right. So, I mainly work upstream which means when it is KubeFlow and other projects. And for me, these kind of areas where you can bring together both, the developers, and the end users, which is super important for us to get the feedback to see where we really are struggling. We hear a lot from those people that meet there, what their pinpoints are. And that is the best way to essentially shape the agenda, to say, well, maybe let's prioritize this over this other feature. And as you mention, integration being one big part, and Functions and Service being, could be considered as the visual basics of applications for Cloud Native Computing. It can act as this kind of glue between different things there. And I'm super excited about Commons. That's for me a great place to actually meet these people, and talk with them. >> So the Commons is almost a cross-pollination of folks that are actually using the code, building the code, and they see other projects that makes sense to contribute to, and so it's an alignment where you allow for that cross-pollination. >> It's a huge series of conversations, and one of the things that is really important to all of the projects is, as Michael said, is getting that feedback from production deployments. People who are working on stuff. So we have, I think we're at around 375 organizational members, so there's... >> John: What percentage of end-user organizations, do you think? >> It's probably about 50/50. You know, you can go to Commons.OpenShift.org, and look up the participants list. I'm behind a little bit in getting everybody in there, but-- >> John: So it's a good healthy dose of end-users? >> It's a good healthy dose of end-users. There's some special interest groups. Our special interest groups are more around used cases. So, we just hosted a machine-learning reception two nights ago, and we had about 200 people in the room. I'd say 50% of them were from the KubeFlow community, and the other 50% were users, or people who are building frameworks for our people to run on OpenShift. And so our goal, as always, is to make OpenShift the optimal, the best place to run your, in this case, machine-learning workloads, or-- >> And I think that's super critical, because one of the things that I've been following a little bit, and you know, I have your blog entry in front of me, is the operator framework, and really what you're trying to do with that framework, and how it's progressing, and where it's going, and really, if you can talk a little bit about what you're doing there, I think that would be great for our viewers. >> So what I'm going to do is I'm going to make sure you get Brandon Philips here, on your KubeFlow, sometime this week, 'cause I don't want to steal the thunder from his keynote tomorrow morning-- >> Lauren: Well, drop a couple hints. (laughs) >> John: Share a little bit, come on. >> So the operator stuff that CoreOS, and they brought it to the table, so it's really their baby. They had done a lot of work to make sure that they had first-class access to be able to inject things into Kubernetes itself, and make it run. And they're going to do a better technical talk on it than I am, and make things run. And so that what they've done is they've opened up and created an STK for operators, so other people can build more. And we think, this is a tipping point for Kubernetes, and I really don't want to steal any thunder here, or get in over my head, is the other part of it, too. >> I think Brandon is the right person to talk about that. >> Brandon, we'll drag Brandon over here. >> I'm super excited about it, but let's-- >> Yeah, let's talk about why you're super excited about it. Is there anything you can kind of tell us in terms of what? >> Enables people to run any kind of workload in communities, in a reliable automated fashion. So you bring the experience that human operators have into software. So you automate that application, which makes it even more suitable to run your enterprise application that so far might have not been the best place to run. >> Lauren: That's great, yeah. >> And yeah, I'm also looking forward to Brandon explaining the details there. >> So I think it's great hearing about that, and we talk a lot about how it's great for users. It's great, you know, operators, developers, how they're building things out, and things along those lines. But one of the things that we are not hearing a ton about here, and we want to hear more about, is security. Security is increasingly important. You know, we're hearing bits and pieces but nothing's really kind of coming together here and what're your thoughts on that? >> Security, I was recently, when I blogged about it, and people on Twitter said, well, is that really true that, you know, couldn't this secure body fall? It's like, well, all the pieces are there. You need to be aware of it. You need to know what you're doing. But it is there, right? All the defaults might not be as you would expect it, but you can enable it. And I think we did a lot of innovations there, as well. With our back, and security context, and so on. And, actually, Liz Rice and myself are working on putting the security cookbook, and for a variety that will come out later this year. We're trying to document the best practice, because it is early days, and it's quite a range of things. From building container images in a secure way, to excess control, and so on, so there's a lot of stuff (mumbles). >> What're some of the end-user feedback sessions, or feedback data that you're getting from these sessions? What is some of the things you guys are hearing? What's the patterns? What's the things that are boiling up to the top? >> Well, there's so many. I mean, this conference is one of those ones where it's a cornucopia of talks, and trying to, I just wrote a little blog post called, The Hitchhiker's Guide to KubeCon. It's on blog.openshift.com. And because, you could spend all of your time here in a different track, and never leave it, like Security 1, or in Operations 1, or-- >> John: There's a lot of great content. >> I think the Istio stuff is probably the hottest thing I'm hearing people going to. There was a great deep-dive training session, hands-on on Monday, here, that got incredible feedback. IBM and Google did that one. We had a lot of customer talks and hands-on training sessions on Monday. Here, there are pretty much, there's a great talk coming up this afternoon, on Kube Controllers that Magic... I think that's at 11:45-ish. There are a lot of the stuff around Service Fish, and service brokers, is really kind of the hot thing that people are looking for to get implemented. And we've got a lot of people from Red Hat working on that. There's, oh man, there's etcd updtes, there's a bazillion things going-- >> John: It's exploding big time here. >> Yeah. >> No doubt about it. >> The number one thing that I'm seeing last couple of months, being onsite with customers, and also here, is that given that Kubernetes is now the defective standard of container authorization, people are much more willing to go all-in, you know? >> Yeah. >> A lot of folks were on the fence, for a couple of years, going like, which one's going to make it? Now, it's kind of like, this is a given. You couldn't, you know, just as Linux is everywhere on the servers, that's the same with Kubernetes, and people are now happy to really invest, to like, okay, let's do it now, let's go all in. >> Yeah, and, what we're hearing, too, just stepping back and looking at the big picture is we see the trend, kind of hearing and connecting the dots, as the number of nodes is going to expand significantly. I mean, Sterring was on stage yesterday, and we heard their, and still small, not a lot of huge, not a lot on a large scale. So, we think that the scale question is coming quickly. >> Well, I think it already came, alright? In the machine-learning reception that we had at night, one of the gentleman, Willem Bookwalter, from Microsoft, and Diane Feddema, from Red Hat, and a whole lot of people are talking about how do we get, because machine-learning workloads, have such huge work, you know, GPU, and Google has their TPU requirements to get to scale, to run these things, that people are already pushing the envelope on Kubernetes. Jeremy Eater from Red Hat has done some incredible performance management work. And on the CNCF blog, they've posted all of that. To get the optimal performance, and to get the scale, is now, I think, one of the next big things, and there's a lot of talks that are on that. >> Yeah, and that's Istio's kind of big service mesh opportunity there, is to bring that to the next level. >> To the next level, you know, there's going to be a lot of things that people are going to experience trying to get the most out of their clusters, but also, I think we're still at the edge of that. I mean, someone said something about getting to 2,500 nodes. And I'm like, thinking, that's just the beginning, baby. >> Yeah, it's going to be more, add a couple zeroes. I got to ask you guys, I got to put you both on the spot here, because it's what we do on theCUBE. You guys are great supporters of theCUBE. We appreciate that, but we've had many conversations over the years with OpenShift, going back to OpenStacks, I don't know what year it was, maybe 2012, or I don't know. I forget what year it was. Now, the success of OpenShift was really interesting. You guys took this to a whole 'nother level. What's the reaction? Are you, as you look back now on where you were with OpenShift and where you are today, do you pinch yourself and say, damn? Or what's your view? >> Red Hat made a big bet on Kubernetes three years ago, three and a half years ago, when people thought we were crazy. You know, they hadn't seen it. They didn't understand what Google was trying to open-source, and some of the engineers inside of Red Hat, Clayton Coleman, Matt Hicks, a lot of great people, saw what was coming, reached out, worked with Google. And the rest of us were like, well, what about Ruby and Rails, and Mongo DB, and you know, doing all this stuff? And like, we invested so much in gears and cartridges. And then, once they explained it, and once Google really open-sourced the whole thing, making that bet as a company, and pivoting on that dime, and making version 3.0 of OpenShift and OpenShift Origin, as a Kubernetes-based platform, as a service, and then, switching over to being a container platform, that was a huge thing. And if you had talked to me back then, three years ago, it was kind of like, is this the right way to go? But, then, you know, okay. >> Well, it's important to history to document that point, because I remember we talked about it. And one of the things, you guys made a good bet, and people were scratching their head, at that time. >> Oh yeah. >> Big time. But also, you've got to give credit to the community, because the leaders in the community recognized the importance of Kubernetes early on. We've been in those conversations, and said, hey, you know, we can't screw this up, because it was an opportunity. People saw the vision, and saw it as a great opportunity. >> I think, as much as I like the technical bits, as an engineer, the API being written and go, and so on, I really think the community, that is what really makes the difference. >> Yeah, absolutely does. >> If you compare it with others, they're also successful. But here with CNCF, all the projects, all the people coming together, and I love the community, I really-- >> It's a case study of how to execute, in my opinion. You guys did a great job in your role, and the people didn't get in the way and try to mess it up. Great smart people understood it, shepherded it through, let it grow. >> And it really is kudos to the Kubernetes community, and the CNCF, for incubating all of this wonderful cross-community collaboration. They do a great job with their ambassadors program. The Kubernetes community does amazing stuff around their SIGs, and making sure that projects get correctly incubated. You know, they're not afraid to rejig the processes. They've just done a wonderful thing, changing the way that new projects come into the Kubernetes, and I think that willingness to learn, learn from mistakes, to evolve, is something that's really kind of unique to the whole new way of thinking about open-source now, and that's the change that we've seen. >> And open-source, open movements, always have a defining moment. You know, the OSI model, remember? That stack never got fully standardized but it stopped at a really important point. PCPIP, IP became really important. The crazy improbability world, CISCO, as we know, and others. This is that kind of moment where there's going to be a massive wealth creation, value creation opportunity because you have people getting behind something, as a de facto standard. And then, there's a lot of edge work around it that can be innovated on. I think, to me, this is going to be one of those moments we look back on. >> Yeah, and I think it's that willingness to adjust the processes, to work with the community, and you know, that Kubernetes, the ethos that's around this project, we've learned from a lot of other foundations' mistakes. You know, not that they're better or worse, but we've learned that you could see the way we're bringing in new projects, and adding them on. We took a step back as a community, and said okay, this is, we're getting too many, too soon, too fast. And maybe, this is not quite the right way to go. And rather than doing the big tent umbrella approach, we've actually starting doing some really re-thinking of our processes, and the governing board and the TOC of the CNCF, have done an awesome job getting that done. >> When you got lightning in a bottle, you stop and you package it up, and you run with it, so congratulations. Red Hat Summit next week, we'll be there, theCUBE. >> Oh yeah. >> Looking forward to going deep on this. >> Well, the OpenShift Commons Gathering is the day before Red Hat Summit. We've completely sold out, so sorry, there's a waitlist. We've gone from being, our first one, I think we had 150 people come. There's over 700 people now coming to the Gathering one, and 25 customers with production deployments speaking. This is the day before Red Hat Summit. And I lost count of how many OpenShift stories are being told at Red Hat Summit. It's going to be a crazy, jetlag-y week, next week, so-- >> Congratulations, you guys got a spring in your step, well done. OpenShift going to the next level, certainly the industry and Kubernetes, a service mesh as Istio. Lot of great coverage here in theCUBE, here in Europe for KubeCon 2018 in Copenhagen, Denmark. I'm John Furrier, and Lauren Cooney, the founder of SparkLabs. I'm with theCUBE, we'll be back with more live coverage. Stay with us! Day Two, here at KubeCon, we'll be right back. (upbeat techno music)

>> Live from Boston, Massachusetts, it's the CUBE covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back to the CUBE's live coverage of the IBM CDO Strategy Summit here in Boston, Massachusetts. I'm your host, Rebecca Knight, along with my co-host Dave Vellante. We're joined by Mark Lack. He is the Strategy Analytics and Business Intelligence Manager at Mueller Inc. Thanks so much for joining us, Mark. >> Thank you for the invite. >> So why don't you tell our viewers a little bit about Mueller and about what you do there. >> Sure, Mueller Inc. is based in the southwest. Ballinger, Texas, to be specific. And, I don't expect anybody, unless they Google it right now, would be able to find that city. But that's where our corporate headquarters and our main manufacturing plant has been. And, we are a company that manufactures and retails steel building products. So, if you think of a warehouse, or a backyard building or even a metal roof, or even I was looking downtown, or downstairs, earlier today, this building is made out of big steel girders. We take those and form them into a product that a customer can use for storage or for living or for any of whatever their use happens to be. Typically, it might be agricultural, but you also find it in very, very large buildings. Mueller is a retailer that happens to manufacture its products. Now, that's a very important distinction, because the company, up until about 15, 20 years ago, viewed itself as a manufacturer that just happened to retail its products. And so when you take the change in the emphasis, your business changes. The way you approach your customers, the way you approach your products, the way you market yourself, is completely different from one side to the other. We've been in business since 1930s, been around for a very long time. It's a family owned business that has it's culture and it's success rooted in West Texas. We have 40 locations all over the southwest. We're headquartered in Ballinger, Texas. We're as far east as Oak Grove, Louisiana and as far west with locations as Albuquerque, New Mexico. >> So you do cognitive analytics for Mueller, so tell our viewers a little bit about what you do there. >> Sure. Mueller has always been on the forefront of technology. Not for technology's sake, but really for effectiveness and efficiency's sake. So Mueller did business process reengineering when it was common for much larger organizations to do. But Mueller took it under as the reality for us to manage our business in the future. We need to have the professional tools to be able to do this. So we set on in our industry using technology in novel ways that our competition just doesn't do. So with the implementation of technology, what you have is a lot of data that comes along. And so we've been very effective using it for our balance scorecard to report metrics and keep the organization on track with that. Giving information back to various parts of the organization and then also creating an analytics platform and program that allows us to really dive deep into the organization and the data and everything that's being thrown off from modern technology. So cognitive analytics. This is something, as you hear about in technology today is, from the robots to artificial intelligence. Cognitive analytics, I think is for us a better way of looking at it of augmented intelligence. We have all of this data, we have these wonderful systems that help give us information to give us the answers we need on our business processes. We have some predictive analytics that help us to identify the challenges going ahead. What we don't have is the deep dive into using these technologies of cognitive to take all of this big data and find answers to situations that it would take a hundred people a hundred years to find out to be able to mine through. So the cognitive analytics is our new direction of analytics, and to be honest with you it's really the natural progression from our traditional analytic system. So as I said before, we have the regular analytics, we have the predictive analytics. As we get into cognitive, this is the next generation of how do we take this data that we have, that's coming at a volume and a velocity and a variety that is so difficult to look at as it is in a spreadsheet, and offload this onto system that can help us to interpret, give us some answers that we can then judge and then make decisions from. >> So, as you said, you have a lot of data. You got customer data, you got supply chain data, you got product data, you got sales data, retail location data. What's the data architecture look like? I mean, some data is more important than other data. How did you approach this opportunity? >> So, a few years ago I went to the first World of Watson, which was in New York. There was about a thousand attendees and Ginni Rometty had had this great presentation and it was very inspiring and she asked, "What will you do with Watson?" And at the time I had no idea what we were going to do with Watson, and so I sat on the plane on the way back and I thought through what are the business case scenarios that we can use to use artificial intelligence in a steel building company in Ballinger, Texas. Don't forget the irony of that part. As we're going to to go back to start using cognitive. So I thought through this and I went to our owner and we had many, many conversations on cognitive. You had the jeopardy, the Watson championship and you started thinking about all of these systems. But the real question was how could we take a new technology and apply it to our existing business to make a difference? And I'm getting to the answer to your question on how it got structured. So we went down the path of investigating Watson, and we've realized that the cognitive is part of our future. And so we plan on leveraging cognitive in many ways. We'd like to see it sales effectiveness, operations effectiveness, transportation effectiveness. There are all sorts of great ideas that we have. One of the challenges we have, and the reason I'm here at the CDO Summit, is when we start to look at our data, the question is are we cognitive ready? And I'll be honest to you, we are for today for a sliver of what cognitive capability is. As you've always heard the numbers 80% of your data is in unstructured format. So we have lots and lots of unstructured data. We have a lot of structured data. When it comes to the analytics around our structured data, we're pretty good, but when you start talking about unstructured data, how do we now take this to add to our structured data and then have a more complete picture of the problem that we're searching? So what I'm hoping to gain here at the CDO Summit is talking to some of these world-class leaders in data operations and data management to help understand what their pain points were. Learn from them so I can take that back and help to architect what our needs are so that we can take advantage of this entire cognitive future that's... >> So you're precognitive. So cognitive ready, let's unpack that a little bit. That means, that what you've got a level of confidence in the data quality? You've got an understanding of how to secure it, govern it, who gets access to it? What does that mean, being cognitive ready? >> So it's going to to be all of those. All of the above. First is, do you have the data? And we all have data, whether it's in spreedsheet on our systems, whether it's in our mobile phone, whether it's on our websites, whether it's in our EIP systems, and I can keep going on >> You got data. >> We have data, but the question is, do we have access to the data? And if you talk to some people, well sure, we have access to the data. Just tell me what data you want and I'll get you access. Okay, well, that is one answer to a much larger problem, because that's only going to give you what your asking for. What the cognitive future is promising for us is we may not know the questions to ask. I think that's the difference between traditional analytics and then the cognitive analytics. One of the benefits of cognitive will be the fact that cognitive will give answers to questions that we're never asked. And so now that this happens, what do we do with it? You know, when we start thinking about having attacking a problem, you know, being data ready, having the data there, that's part of the problem. And I think most companies say we're pretty good with our data. But with the 80% that we don't have access to, the real question is, are we missing that crucial piece of information that prevents us from making the right decision at the right time? And so our approach, and what I'm going to go back with, is understanding the data architecture that those who have gone before me that I can pick up and bring back to my organization and help us to implement that in a way that will make it cognitive ready for the future. You know, it's not just the access to the data; it's having the data. And I had lunch a few years ago with Steve Mills who was a senior executive for IBM, and one of the people at lunch was bold enough to ask him, "How do we know what data to capture?" And he said, very bluntly, "All of it." Now this was about five years ago. So, back then, you're shaking your heads saying, "We don't have storage capabilities. "We don't have the ability to store all these data." But he had already seen the future, and what he was telling us right then was all of it is going to be valuable. So where we are today, we think we know what data's valuable. But cognitive's going to help us to understand what other data might me valuable as well. >> So I'm interested in your job from the perspective of the organizational change. And you work for, as you said, a small family-owned company. Smallish of family-owned company. And we've heard a lot of today about the business transformation, the technology involved, and how that has really changed dramatically over the last decade. But then, there's also this other piece which is the social and cultural change within these organizations. Can you describe your experience in terms of how your colleagues interpret your world? >> You're asking me those questions 'cause you can see the bruises from whatever I have to accomplish. (laughter) You know, within an organization, one of the benefits of working that I found at Muller, and it's a family organization, is that those who work there, and I've been there for 18 years, and I'm still considered a newcomer to the organization right after 18 years. But we're not there unless we have a strong commitment to the organization and to the culture of the company. So, while we may not always agree as to what the future needs to hold, okay? We all understand we need to do what's best for this company for its long term survival. At the end of the day, that's what we're there to do. So culturally, when you first come up with saying you're going to do artificial intelligence, you know, you got a lot of head-scratching, especially in West Texas. I have a hard time explaining even to those around me what it is that I do. But, once you start telling the story that we have data, we have lots of data, and that there might be information in that data that we don't know now but in the future we may have, and so, it's important for us to capture that data and store it. Whether or not we know that there's immediate value, we know there's some value, okay? And if we can take that leap that there's going to be some value, and we're here with the help of the organization faces, we know that there are challenges to every organization. We're a still building company in Ballinger, Texas. Now I know I keep saying that, but what if a company like Uber comes up with metal building and all of a sudden, we have new challenges that we never thought we'd face? Many organizations that have been up, industries that have been in upheaval from these changes in either technology access or a new idea that splits the difference. We want to make sure we can stay ahead, and so when we start talking about that from a culture, we're here for the long term value of the company. We're committed to this organization, so what it do we need to do? And so, you know, the term "out of the box thinking" is something that sometimes we have to do. That doesn't mean it's easy. It doesn't mean that we all immediately say, "Aha! This is what we're going to do." It takes convincing. It takes a lot of conversation, and it takes a lot of political capital to show that what it is that we're going to do is going to make sense and use a lot of good examples. >> Well, and you come to tongue-in-cheek about people rolling their eyes about AI and so forth, but any manufacturer who sees 3D printing and the way it's evolved goes "Wow!" And then the data that you can capture from that, so, I wanted to ask you, when you talk to your colleagues and people are afraid that robots are going to take over the world and so forth, but what are the things that when you think about augmented intelligence that, you know, where do the machines leave off and the humans pick up? What kinds of things do humans do in your world that machines don't do that well? >> So, you know, if I go back and think about analytics, for example, there's a lot of time collecting data, storing data, translating data, creating contract to retrieve that data, putting that data into a beautiful report and then handing it out. Think of all that time that it takes to get there, right? A lot of people who are in analytics think that they're adding value by doing it. But to be honest with you, they're not. There's no value in the construct. And so, what the value is in the interpretation of that data. So what do computers do well and what do we do well? We do well at interpreting what those findings tell us. If we can offload those transactions back to a machine that can set the data for us, automatically construct the data, put it into a situation for us that can then allow us to then interpret the results? Then we're spending the majority of our time adding value by interpreting and making changes with the company versus spending that same time going back and constructing something that may or may not be something that may add value. So we spend 80% of our time creating data for a report. The report, now we have to test the report to determine, can I communicate this the right way? You have machine learning now and you have tools that will then take this data and say, "Oh, this is numerical data. "This looks like general ledger data. This is the type of way this data should be displayed." So I don't have to think of a graph. It suggests one for me. So what it does is then allow me to interpret the results, not worry about the construct. >> So you can focus on the things that humans do well. But the other thing I want to talk to you about is the talent issue. I mean you guys, you've mentioned before that you're based in West Texas and you are working on a real vanguard in your industry. As I said, you were someone who is thinking about whether or not Uber is going to say, "Let's make steel buildings." I mean, is that a problem that you're facing, that your company is facing? >> Well, there is no joke, right, that the fact of the future's going to have a man and a dog. And the man's job is to feed the dog, and the dog's job is to bite the man if he tries to touch any of the machinery, right? So, I don't think that we're there. The jobs aren't going to be eliminated to where people are not able to add value. But finding a talent, back to your question, is the expectation that we have of talent, it is scarce. Finding people that have the skills to now interpret the data, so you can find people that have a lot of time that can do any of those steps in between. But now, what's happened is, you want people to add value, not create constructs that don't add the value. So the type of talent that you look for are people who can interpret this information to give us the better answers that we need for the organization to thrive. And that's really where I see the talent shifting is on more forward-looking, outcome-based, value-based decision making, not as much on the development of items that could be offloaded to a machine. >> Yeah, I mean, interpretation, creativity, ideation. I mean, machines have always replaced humans. We've talked about this on The Cube before, but the first time in human history, machines are replacing humans in cognitive functions. I mean, you gave an example of the workflow of developing a report, which... >> Kenney Company can relate to, yeah. >> But yeah, 10 years ago, that was like super valuable. Today it's like, "Let's automate that." >> Well, but the challenge I think where people have is where do they add value? What is the problem that we're trying to solve? It's where do we add value. If we add value creating the construct, you aren't going to be employed, because something else is going to do that. >> But if you add value on focusing on the output and being able to interpret that output in a way that adds value to your company, you'll be employed forever. So, you know, people that can solve problems, take the information, make decisions, make suggestions that are going to make the company better, will always be employed. But it's the people who think they add value flipping a switch or programming a lever, now, they think their value's very important there, but I think what we have to do and it behooves us, is to translate those jobs into where do you add value? Where is the most important thing you need to be doing for the success of this company? And that I think is really the future. >> Are you... We haven't asked any IoT questions today. I want to ask you, are you sort of digitizing, instrumenting for your customers the end products of what you guys produce, and how was that creating data? >> You know, we haven't, we talked about it. We don't have products that, we're not selling things that are machinery that might break down and give us information, and so, we're building final products that are there, that people will then do different things with. So, IoT hasn't worked for us from a product standpoint, but we are looking at our various machinery and making sure that we have understanding as to those events that are causing a break down. One of the challenges we have in our industry is if we have a line that manufactures apart, if it goes down, okay, now it shuts everything down. So we have a duplicate, which can get very expensive. We have duplicates of everything, and how many duplicates do you need to have to make sure you have duplicates of the duplicates? So if we can start to look at the state of this coming from our machinery, and use that as a predictor, then we can use that, and so you have sort of an IoT thing there by looking at the data that's there. But is it feeding back into our normal reporting systems? It's not necessarily like it is from a smartphone are enabled like that. >> No, but it's anticipating a potential outage. >> Sure. >> And avoiding that. Yeah, great. >> Well Mark, thanks so much for coming on The Cube. It was wonderful conversation. >> Thank you. >> I'm Rebecca Knight with Dave Vellante. We will have more from the CDO Summit just after this. (upbeat music)

>>The cube at IBM. Impact 2014 is brought to you by headline sponsor. IBM. Here are your hosts, John furrier and Paul Gillin. >>Hey, welcome back everyone. This is Silicon angle's the cube. It's our flagship program. We go out to the events district as soon from the noise. We're ending out day two of two days of wall to wall coverage with myself and Paul Galen. Uh, 10 to six 30 every day. I'm just, we'll take as much as we can just to get the data. Share that with you. Restrict the signal from the noise. I'm John furrier the bonus look at angle Miko is Paul Gilliam and our special guests, Holger Mueller, Mueller from constellation research analyst covering the space. Ray Wang was here earlier. You've been here for the duration. Um, we're going to break down the event. We'll do a wrap up here. Uh, we have huge impact event for 9,000 people. Uh, Paul, I want to go to you first and get your take on just the past two days. And we've got a lot of Kool-Aid injection attempts for Kool-Aid injection, but IBM people were very, very candid. I mean, I didn't find it, uh, very forceful at all from IBM. They're pragmatic. What's your thoughts on it? >>I think pragmatism is, is what I take away, John, if it gets a good, that's a good word for it. Uh, what I saw was a, uh, not a blockbuster. Uh, there was not a lot of, of, uh, of hype and overstatement about what the company was doing. I was impressed with Steve mills, but our interview with him yesterday, we asked about blockbuster acquisitions and he said basically, why, why, I mean, why should we take on a big acquisition that is going to create a headache, uh, for us in integrating into your organization? Let's focus on the spots where we have gaps and let's fill those. And that's really what they've, you know, they really have put their money where their mouth is and doing these 150 or more acquisitions over the last, uh, three or four years. Um, I think that the, the one question that I would have, I don't think there's any doubt about IBM's commitment to cloud as the future about their investment in big data analytics. They certainly have put their money where their mouth is. They're over $25 billion invested in big data analytics. One question I have coming out of this conference is about power and about the decision to exit the x86 market and really create confusion in a part of their business partners, their customers about about how they're going to fill that gap and where are they going to go for their actually needs and the power. Clearly power eight clearly is the future. It's the will fill that role in the IBM portfolio, but they've got to act fast. >>Do you think there's a ripple effect then so that that move I'll see cause a ripple effect in their ecosystem? >>Well, I was talking to a, I've talked to two IBM partners today, fairly large IBM partners and both of them have expressed that their customers are suffering some whiplash right now because all of a sudden the x86 option from IBM has gone away. And so it's frozen there. Their purchasing process and some of them are going to HP, some of them are looking at other providers. Um, I don't think IBM really has has told a coherent story to the markets yet about how >>and power's new. So they've got to prop that up. So you, so you're saying is okay, HP is going to get some new sales out of this, so frozen the for IBM and yet the power story's probably not clear. Is that what you're hearing? >>I don't think the power story is clear. I mean certainly it was news to me that IBM is taking on Intel at the, at this event and I was surprised that, that, >>that that was a surprise. Hold on, I've got to go to you because we've been sitting here the Cuban, we've been having all the execs come here and we've been getting briefed here in the cube. Shared that with the audience. You've been out on the ground, we've bumped into you guys, all, all the other analysts and all the briefings you've been in, the private sessions you've been in the rooms you've been, you've been, you've been out, out in the trenches there. What have you, what are you finding, what have you been hearing and what are the, some of the soundbites that you could share with the audience? It's not the classic God, Yemen, what are the differences? >>The Austin executives in cloud pedal, can you give me your body language? He had impact one year ago because they didn't have self layer at a time, didn't want to immediately actionable to do something involving what? A difference things. What in itself is fine, but I agree with what you said before is the messaging is they don't tell the customers, here's where we are right now. Take you by the hand. It's going to be from your door. And there's something called VMs. >>So it's very interesting. I mean I would consider IBM finalized the acquisition only last July. It's only been nine months since was acquired. Everything is software now. It leads me to think of who acquired who IBM acquired a software or did soflar actually acquire IBM because it seems to, SoftLayer is so strategic. IBM's cloud strategy going forward. >>Very strategic. I think it's probably why most transformative seemed like the Nexans agenda. And you've heard me say assault on a single thing. who makes it seven or eight weeks ago? It's moving very far. >>What do you think about the social business? Is that hanging together, that story? Hang on. It's obviously relevant direction. It's kind of a smarter planet positioning. Certainly businesses will be social. Are you seeing any meat on the bone there? On the collaboration side, >>one of the weakest parts, they have to be built again. Those again, they also have an additional for HR, which was this position, this stuff. It's definitely something which gives different change. >>I have to say, John, I was struck by the lack of discussion of social business in the opening keynote in particular a mobile mobile, big data. I mean that that came across very clear, but I've been accustomed to hearing that the social business rugby, they didn't, it didn't come out of this conference. >>Yeah. I mean my take on that was, is that >>I think it's pretty late. I don't think there's a lot of meat in the bone with the social, and I'll tell you why. I think it's like it's like the destination everyone wants to go to, but there's no really engine yet. Right. I think there's a lot of bicycle riding when they need a car. Right? So the infrastructure is just not is too embryonic, if you will. A lot of manual stuff going on. Even the analytics and you know you're seeing in the leaderboard here in the social media side and big data analytics. Certainly there are some core engine parts around IBM, but that social engine, I just don't see it happening. You risk requires a new kind of automation. It's got some real times, but I think that this is some, some nice bright spots. I love the streams. I love this zone's concept that we heard from Watson foundations. >>I think that is something that they need to pull out the war chest there and bring that front and center. I think the thinking about data as zones is really compelling and then I'll see mobile, they've got all the messaging on that and to give IBM to the benefit of the doubt. I mean they have a story now that they have a revenue generating story with cloud and with big data and social was never a revenue generating story. That's a software story. It's not big. It's not big dollars. And they've got something now that really they're really can drive. >>I'll tell you Chris Kristin from mobile first. She was very impressive and, and I'll tell you that social is being worked on. So I put the people are getting it. I mean IBM 100% gets social. I think the, the, it's not a gimmick to them. It's not like, Oh, we got some social media stuff. I think in the DNA of their soul, they, they come from that background of social. So I give them high marks on that. I just don't see the engine yet. I'm looking for analytics. I'm looking for a couple of eight cylinders. I just don't see it yet. You know, the engine, the engines, lupus and she wants to build the next generation of education. Big data, tons of mobile as the shoulder equivalent to social. I'm skeptical. I'm skeptical on Bloomix. I'll tell you why. I'm not skeptical. I shouldn't say that. >>It's going to get some plane mail for that. Okay. I'll say I'll see what's out there. I'll say it. I'm skeptical of Blumix because it could be a Wright brothers situation. Okay, look, I'm wrong guys building the wrong airplane. So the question is they might be on the wrong side of history if they don't watch the open source foundations because here's the problem. I have a blue mix, gets rushed to the market. Certainly IBM has got muscle solutions together. No doubt debting on cloud Foundry is really a risk and although people are pumping it up and it's got some momentum, they don't have a big community, they have a lot of marketing behind it and I know Jane's Wars over there is doing a great job and I'm Josh McKinsey over there with piston cloud. It'll behind it. It has all the elements of open collaboration and architecture or collaboration. However, if it's not a done deal yet in my mind, so that's a, that is a risk factor in my my mind. >>We've met a number of amazing, maybe you can help to do, to put these in order, a number of new concepts out there. We've got Bloomex the soft player, and we've got the marketplace, and these are all three concepts that approval, which is a subset of which, what's the hierarchy of these different platforms? >>That's hopefully, that's definitely at the bottom. The gives >>us visibility. You talk about the CIO and CSI all the time. Something you securities on every stupid LCO one on OCS and the marketplace. Basically naming the applications. Who would folded? IBM. IBM would have to meet opensource platform as a service. >>Well, it's not, even though it's not even open source and doing a deal with about foundries, so, so they've got, I think they're going in the middle. Where's their angle on that? But again, I like, again, the developer story's good, the people are solid. So I think it's not a fail of my, in my mind that all the messaging is great. But you know, we went to red hat summit, you know, they have a very active community, multiple generations in the data center, in the Indiana prize with Linux and, and open, you know, they're open, open shift is interesting. It's got traction and it's got legit traction. So that's one area. The other area I liked with Steve mills was he's very candid about this turf. They're staking out. Clearly the cloud game is up, is there is hardcore for them and in the IBM flavor enterprise cloud, they want to win the enterprise cloud. They clearly see Amazon, they see Amazon and its rhetoric and Grant's narrative and rhetoric against Amazon was interesting saying that there's more links on SoftLayer and Amazon. Now if you count links, then I think that number is skewed. So it's, you know, there's still a little bit of gamification going to have to dig into that. I didn't want to call him out on that, but know there's also a hosting business versus, you know, cloud parse the numbers. But what's your take on Amazon soft layer kind of comparison. >>It's, it's fundamentally different, right? Mustn't all shows everything. Why did see retailers moves is what to entirely use this software, gives them that visibility machine, this accommodation more conservatively knowing that I buy them, I can see that I can even go and physically touch that machine and I can only did the slowly into any cloud virtualization shed everything. >>Oh, Paul, I gotta say my favorite interview and I want to get your take on this. It was a Grady food. She was sat down with us and talk with us earlier today. IBM fell up, walks on water with an IBM Aussie legend in the computer industry. Just riveting conversation. I mean, it was really just getting started. I mean, it felt like we were like, you know, going into cruising altitude and then he just walked away. So they w what's your take on that conversation? >>Well, I mean, certainly he, uh, the gritty boujee interview, he gave us the best story of, of the two days, which is, uh, they're being in the hospital for open heart surgery, looking up, seeing the equipment, and it's going to be used to go into his chest and open his heart and knowing that he knows the people who program that, that equipment and they programmed it using a methodology that he invented. Uh, that, that, that's a remarkable story. But I think, uh, uh, the fact that that a great igloo can have a job at a company like IBM is a tribute to IBM. The fact that they can employ people like that who don't have a hard revenue responsibility. He's not a P. and. L, he's just, he's just a genius and he's a legend and he's an IBM to its crude, finds a place for people like that all throughout his organization. >>And that's why they never lost their soul in my opinion. You look at what HP and IBM, you know, IBM had a lot of reorganizations, a lot of pivots, so to speak, a lot of battleship that's turned this in way. But you know, for the most part they kept their R and D culture. >>But there's an interesting analogy too. Do you remember the case methodology was mutual support of them within the finance language that you mailed something because it was all about images, right? You would use this, this methodology, different vendors that were prior to the transport itself. Then I've yet to that credit, bring it together. bring and did a great service to all for software engineering. And maybe it's the same thing at the end, can play around diversity. >>You've got to give IBM process a great point. Earlier we, Steve mills made a similar reference around, it wasn't animosity, it was more of Hey, we've helped make Intel a big business, but the PC revolution, you know, where, what's in it for us? Right? You know, where's our, you know, help us out, throw us a bone. Or you know, you say you yell to Microsoft to go of course with the licensing fee with Gates, but this is the point, the unification story and with grays here, you know IBM has some real good cultural, you know industry Goodwill, you agree >>true North for IBM is the Antal quest customer. They'll do what's right where the money and the budget of the enterprise customers and press most want compatibility. They don't want to have staff, of course they want to have investment protection >>guys. I'd be able to do a good job of defining that as their cloud strategy that clearly are not going head to head with Amazon. It's a hybrid cloud strategy. They want to, they see the enterprise customers that legacy as as an asset and it's something they want to build on. Of course the risk of that is that Amazon right now is the pure play. It has all the momentum. It has all the buzz and and being tied to a legacy is not always the greatest thing in this industry, but from a practical revenue generating standpoint, it's pretty good. >>Hey guys, let's go down and wrap up here and get your final thoughts on the event. Um, and let's just go by the numbers, kind of the key things that IBM was promoting and then our kind of scorecard on kind of where they, where they kind of played out and new things that popped out of the woodwork that got your attention. You see the PO, the power systems thing was big on their messaging. Um, the big data story continues to be part of it. Blue mix central to the operations and the openness. You had a lot of open, open openness in their messaging and for the most part that's pretty much it. Um, well Watson, yeah, continue. Agents got up to Watson. >>Wow. A lot of news still to come out of Watson I think in many ways that is their, is their ACE in the hole and then that is their diamond. Any other thoughts? >>Well, what I missed is, which I think sets IBM apart from this vision, which is the idea of the API. Everybody else at that pure name stops the platform or says, I'm going to build like the org, I'm going to build you. That's a clear differentiator on the IBM side, which you still have to build part. They still have to figure out granularity surface that sets them apart that they have to give one. >>Yeah, and I think I give him an a plus on messaging. I think they're on all the right fault lines on the tectonic shifts that we're seeing. Everyone, I asked every every guest interview, what's the game changing moment? Why is it so important? And almost consistently the answers were, you know, we're living in a time of fast change data, you know, efficiency spare or you're going to be left behind. This is the confluence of all these trends, these fall lines. So I think IBM is sitting on these fall lines. Now the question is how fast can they cobbled together the tooling from the machineries that they have built over the years. Going back to the mainframe anniversary, it's out there. A lot of acquisitions, but, but so far the story and the story >>take the customer by the hand. That's the main challenge. I see. This wasn't often we do in Mexico, they want zero due to two times or they're chilling their conferences. It's the customer event and you know, and it's 9,000 people somehow have to do something to just show, right? So why is my wave from like distinguished so forth and so and so into? Well Lou mentioned, sure for the cloud, but how do we get there, right? What can we use, what am I SS and leverage? How do I call >>guys, really appreciate the commentary. Uh, this is going to be a wrap for us when just do a shout out to Matt, Greg and Patrick here doing a great job with the production here in the cube team and we have another cube team actually doing a simultaneous cube up in San Francisco service. Now you guys have done a great job here. And also shout out to Bert Latta Moore who's been doing a great job of live tweeting and help moderate the proud show, which was really a huge success and a great crowd chat this time. Hopefully we'll get some more influencers thought leaders in there for the next event and of course want to thank Paul Gillen for being an amazing cohost on this trip. Uh, I thought the questions and the and the cadence was fantastic. The guests were happy and hold there. Thank you for coming in on our wrap up. >>Really appreciate it. Constellation research. Uh, this is the cube. We are wrapping it up here at the IBM impact event here live in Las Vegas. It's the cube John furrier with Paul Gillen saying goodbye and see it. Our next event and stay tuned if it's look at angel dot DV cause we have continuous coverage of service now and tomorrow we will be broadcasting and commentating on the Facebook developer conference in San Francisco. We're running here, Mark Zuckerberg and all Facebook's developers and all their developer programs rolling out. So watch SiliconANGLE TV for that as well. Again, the cube is growing with thanks to you watching and thanks to all of our friends in the industry. Thanks for watching..

>> From "theCube" Studios in Palo Alto in Boston bringing you data-driven insights from "theCube" and ETR. This is "Breaking Analysis" with Dave Vellante. >> As an independent pure play company, Palo Alto Networks has earned its status as the leader in security. You can measure this in a variety of ways. Revenue, market cap, execution, ethos, and most importantly, conversations with customers generally. In CISO specifically, who consistently affirm this position. The company's on track to double its revenues in fiscal year 23 relative to fiscal year 2020. Despite macro headwinds, which are likely to carry through next year, Palo Alto owes its position to a clarity of vision and strong execution on a TAM expansion strategy through acquisitions and integration into its cloud and SaaS offerings. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR and this breaking analysis and ahead of Palo Alto Ignite the company's user conference, we bring you the next chapter on top of the last week's cybersecurity update. We're going to dig into the ETR data on Palo Alto Networks as we promised and provide a glimpse of what we're going to look for at "Ignite" and posit what Palo Alto needs to do to stay on top of the hill. Now, the challenges for cybersecurity professionals. Dead simple to understand. Solving it, not so much. This is a taxonomic eye test, if you will, from Optiv. It's one of our favorite artifacts to make the point the cybersecurity landscape is a mosaic of stovepipes. Security professionals have to work with dozens of tools many legacy combined with shiny new toys to try and keep up with the relentless pace of innovation catalyzed by the incredibly capable well-funded and motivated adversaries. Cybersecurity is an anomalous market in that the leaders have low single digit market shares. Think about that. Cisco at one point held 60% market share in the networking business and it's still deep into the 40s. Oracle captures around 30% of database market revenue. EMC and storage at its peak had more than 30% of that market. Even Dell's PC market shares, you know, in the mid 20s or even over that from a revenue standpoint. So cybersecurity from a market share standpoint is even more fragmented perhaps than the software industry. Okay, you get the point. So despite its position as the number one player Palo Alto might have maybe three maybe 4% of the total market, depending on what you use as your denominator, but just a tiny slice. So how is it that we can sit here and declare Palo Alto as the undisputed leader? Well, we probably wouldn't go that far. They probably have quite a bit of competition. But this CISO from a recent ETR round table discussion with our friend Eric Bradley, summed up Palo Alto's allure. We thought pretty well. The question was why Palo Alto Networks? Here's the answer. Because of its completeness as a platform, its ability to integrate with its own products or they acquire, integrate then rebrand them as their own. We've looked at other vendors we just didn't think they were as mature and we already had implemented some of the Palo Alto tools like the firewalls and stuff and we thought why not go holistically with the vendor a single throat to choke, if you will, if stuff goes wrong. And I think that was probably the primary driver and familiarity with the tools and the resources that they provided. Now here's another stat from ETR's Eric Bradley. He gave us a glimpse of the January survey that's in the field now. The percent of IT buyers stating that they plan to consolidate redundant vendors, it went from 34% in the October survey and now stands at 44%. So we fo we feel this bodes well for consolidators like Palo Alto networks. And the same is true from Microsoft's kind of good enough approach. It should also be true for CrowdStrike although last quarter we saw softness reported on in their SMB market, whereas interestingly MongoDB actually saw consistent strength from its SMB and its self-serve. So that's something that we're watching very closely. Now, Palo Alto Networks has held up better than most of its peers in the stock market. So let's take a look at that real quick. This chart gives you a sense of how well. It's a one year comparison of Palo Alto with the bug ETF. That's the cyber basket that we like to compare often CrowdStrike, Zscaler, and Okta. Now remember Palo Alto, they didn't run up as much as CrowdStrike, ZS and Okta during the pandemic but you can see it's now down unquote only 9% for the year. Whereas the cyber basket ETF is off 27% roughly in line with the NASDAQ. We're not showing that CrowdStrike down 44%, Zscaler down 61% and Okta off a whopping 72% in the past 12 months. Now as we've indicated, Palo Alto is making a strong case for consolidating point tools and we think it will have a much harder time getting customers to switch off of big platforms like Cisco who's another leader in network security. But based on the fragmentation in the market there's plenty of room to grow in our view. We asked breaking analysis contributor Chip Simington for his take on the technicals of the stock and he said that despite Palo Alto's leadership position it doesn't seem to make much difference these days. It's all about interest rates. And even though this name has performed better than its peers, it looks like the stock wants to keep testing its 52 week lows, but he thinks Palo Alto got oversold during the last big selloff. And the fact that the company's free cash flow is so strong probably keeps it at the one 50 level or above maybe bouncing around there for a while. If it breaks through that under to the downside it's ne next test is at that low of around one 40 level. So thanks for that, Chip. Now having get that out of the way as we said on the previous chart Palo Alto has strong opinions, it's founder and CTO, Nir Zuk, is extremely clear on that point of view. So let's take a look at how Palo Alto got to where it is today and how we think you should think about his future. The company was founded around 18 years ago as a network security company focused on what they called NextGen firewalls. Now, what Palo Alto did was different. They didn't try to stuff a bunch of functionality inside of a hardware box. Rather they layered network security functions on top of its firewalls and delivered value as a service through software running at the time in its own cloud. So pretty obvious today, but forward thinking for the time and now they've moved to a more true cloud native platform and much more activity in the public cloud. In February, 2020, right before the pandemic we reported on the divergence in market values between Palo Alto and Fort Net and we cited some challenges that Palo Alto was happening having transitioning to a cloud native model. And at the time we said we were confident that Palo Alto would make it through the knot hole. And you could see from the previous chart that it has. So the company's architectural approach was to do the heavy lifting in the cloud. And this eliminates the need for customers to deploy sensors on prem or proxies on prem or sandboxes on prem sandboxes, you know for instance are vulnerable to overwhelming attacks. Think about it, if you're a sandbox is on prem you're not going to be updating that every day. No way. You're probably not going to updated even every week or every month. And if the capacity of your sandbox is let's say 20,000 files an hour you know a hacker's just going to turn up the volume, it'll overwhelm you. They'll send a hundred thousand emails attachments into your sandbox and they'll choke you out and then they'll have the run of the house while you're trying to recover. Now the cloud doesn't completely prevent that but what it does, it definitely increases the hacker's cost. So they're going to probably hit some easier targets and that's kind of the objective of security firms. You know, increase the denominator on the ROI. All right, the next thing that Palo Alto did is start acquiring aggressively, I think we counted 17 or 18 acquisitions to expand the TAM beyond network security into endpoint CASB, PaaS security, IaaS security, container security, serverless security, incident response, SD WAN, CICD pipeline security, attack service management, supply chain security. Just recently with the acquisition of Cider Security and Palo Alto by all accounts takes the time to integrate into its cloud and SaaS platform called Prisma. Unlike many acquisitive companies in the past EMC was a really good example where you ended up with a kind of a Franken portfolio. Now all this leads us to believe that Palo Alto wants to be the consolidator and is in a good position to do so. But beyond that, as multi-cloud becomes more prevalent and more of a strategy customers tell us they want a consistent experience across clouds. And is going to be the same by the way with IoT. So of the next wave here. Customers don't want another stove pipe. So we think Palo Alto is in a good position to build what we call the security super cloud that layer above the clouds that brings a common experience for devs and operational teams. So of course the obvious question is this, can Palo Alto networks continue on this path of acquire and integrate and still maintain best of breed status? Can it? Will it? Does it even have to? As Holger Mueller of Constellation Research and I talk about all the time integrated suites seem to always beat best of breed in the long run. We'll come back to that. Now, this next graphic that we're going to show you underscores this question about portfolio. Here's a picture and I don't expect you to digest it all but it's a screen grab of Palo Alto's product and solutions portfolios, network cloud, network security rather, cloud security, Sassy, CNAP, endpoint unit 42 which is their threat intelligence platform and every imaginable security service and solution for customers. Well, maybe not every, I'm sure there's more to come like supply chain with the recent Cider acquisition and maybe more IoT beyond ZingBox and earlier acquisition but we're sure there will be more in the future both organic and inorganic. Okay, let's bring in more of the ETR survey data. For those of you who don't know ETR, they are the number one enterprise data platform surveying thousands of end customers every quarter with additional drill down surveys and customer round tables just an awesome SaaS enabled platform. And here's a view that shows net score or spending momentum on the vertical axis in provision or presence within the ETR data set on the horizontal axis. You see that red dotted line at 40%. Anything at or over that indicates a highly elevated net score. And as you can see Palo Alto is right on that line just under. And I'll give you another glimpse it looks like Palo Alto despite the macro may even just edge up a bit in the next survey based on the glimpse that Eric gave us. Now those colored bars in the bottom right corner they show the breakdown of Palo Alto's net score and underscore the methodology that ETR uses. The lime green is new customer adoptions, that's 7%. The forest green at 38% represents the percent of customers that are spending 6% or more on Palo Alto solutions. The gray is at that 40 or 8% that's flat spending plus or minus 5%. The pinkish at 5% is spending is down on Palo Alto network products by 6% or worse. And the bright red at only 2% is churn or defections. Very low single digit numbers for Palo Alto, that's a real positive. What you do is you subtract the red from the green and you get a net score of 38% which is very good for a company of Palo Alto size. And we'll note this is based on just under 400 responses in the ETR survey that are Palo Alto customers out of around 1300 in the total survey. It's a really good representation of Palo Alto. And you can see the other leading companies like CrowdStrike, Okta, Zscaler, Forte, Cisco they loom large with similar aspirations. Well maybe not so much Okta. They don't necessarily rule want to rule the world. They want to rule identity and of course the ever ubiquitous Microsoft in the upper right. Now drilling deeper into the ETR data, let's look at how Palo Alto has progressed over the last three surveys in terms of market presence in the survey. This view of the data shows provision in the data going back to October, 2021, that's the gray bars. The blue is July 22 and the yellow is the latest survey from October, 2022. Remember, the January survey is currently in the field. Now the leftmost set of data there show size a company. The middle set of data shows the industry for a select number of industries in the right most shows, geographic region. Notice anything, yes, Palo Alto up across the board relative to both this past summer and last fall. So that's pretty impressive. Palo Alto network CEO, Nikesh Aurora, stressed on the last earnings call that the company is seeing somewhat elongated deal approvals and sometimes splitting up size of deals. He's stressed that certain industries like energy, government and financial services continue to spend. But we would expect even a pullback there as companies get more conservative. But the point is that Nikesh talked about how they're hiring more sales pros to work the pipeline because they understand that they have to work harder to pull deals forward 'cause they got to get more approvals and they got to increase the volume that's coming through the pipeline to account for the possibility that certain companies are going to split up the deals, you know, large deals they want to split into to smaller bite size chunks. So they're really going hard after they go to market expansion to account for that. All right, so we're going to wrap by sharing what we expect and what we're going to probe for at Palo Alto Ignite next week, Lisa Martin and I will be hosting "theCube" and here's what we'll be looking for. First, it's a four day event at the MGM with the meat of the program on days two and three. That's day two was the big keynote. That's when we'll start our broadcasting, we're going for two days. Now our understanding is we've never done Palo Alto Ignite before but our understanding it's a pretty technically oriented crowd that's going to be eager to hear what CTO and founder Nir Zuk has to say. And as well CEO Nikesh Aurora and as in addition to longtime friend of "theCube" and current president, BJ Jenkins, he's going to be speaking. Wendy Whitmore runs Unit 42 and is going to be several other high profile Palo Alto execs, as well, Thomas Kurian from Google is a featured speaker. Lee Claridge, who is Palo Alto's, chief product officer we think is going to be giving the audience heavy doses of Prisma Cloud and Cortex enhancements. Now, Cortex, you might remember, came from an acquisition and does threat detection and attack surface management. And we're going to hear a lot about we think about security automation. So we'll be listening for how Cortex has been integrated and what kind of uptake that it's getting. We've done some, you know, modeling in from the ETR. Guys have done some modeling of cortex, you know looks like it's got a lot of upside and through the Palo Alto go to market machine, you know could really pick up momentum. That's something that we'll be probing for. Now, one of the other things that we'll be watching is pricing. We want to talk to customers about their spend optimization, their spending patterns, their vendor consolidation strategies. Look, Palo Alto is a premium offering. It charges for value. It's expensive. So we also want to understand what kind of switching costs are customers willing to absorb and how onerous they are and what's the business case look like? How are they thinking about that business case. We also want to understand and really probe on how will Palo Alto maintain best of breed as it continues to acquire and integrate to expand its TAM and appeal as that one-stop shop. You know, can it do that as we talked about before. And will it do that? There's also an interesting tension going on sort of changing subjects here in security. There's a guy named Edward Hellekey who's been in "theCube" before. He hasn't been in "theCube" in a while but he's a security pro who has educated us on the nuances of protecting data privacy, public policy, how it varies by region and how complicated it is relative to security. Because securities you technically you have to show a chain of custody that proves unequivocally, for example that data has been deleted or scrubbed or that metadata does. It doesn't include any residual private data that violates the laws, the local laws. And the tension is this, you need good data and lots of it to have good security, really the more the better. But government policy is often at odds in a major blocker to sharing data and it's getting more so. So we want to understand this tension and how companies like Palo Alto are dealing with it. Our customers testing public policy in courts we think not quite yet, our government's making exceptions and policies like GDPR that favor security over data privacy. What are the trade-offs there? And finally, one theme of this breaking analysis is what does Palo Alto have to do to stay on top? And we would sum it up with three words. Ecosystem, ecosystem, ecosystem. And we said this at CrowdStrike Falcon in September that the one concern we had was the pace of ecosystem development for CrowdStrike. Is collaboration possible with competitors? Is being adopted aggressively? Is Palo Alto being adopted aggressively by global system integrators? What's the uptake there? What about developers? Look, the hallmark of a cloud company which Palo Alto is a cloud security company is a thriving ecosystem that has entries into and exits from its platform. So we'll be looking at what that ecosystem looks like how vibrant and inclusive it is where the public clouds fit and whether Palo Alto Networks can really become the security super cloud. Okay, that's a wrap stop by next week. If you're in Vegas, say hello to "theCube" team. We have an unbelievable lineup on the program. Now if you're not there, check out our coverage on theCube.net. I want to thank Eric Bradley for sharing a glimpse on short notice of the upcoming survey from ETR and his thoughts. And as always, thanks to Chip Symington for his sharp comments. Want to thank Alex Morrison, who's on production and manages the podcast Ken Schiffman as well in our Boston studio, Kristen Martin and Cheryl Knight they help get the word out on social and of course in our newsletters, Rob Hoof, is our editor in chief over at Silicon Angle who does some awesome editing, thank you to all. Remember all these episodes they're available as podcasts. Wherever you listen, all you got to do is search "Breaking Analysis" podcasts. I publish each week on wikibon.com and silicon angle.com where you can email me at david.valante@siliconangle.com or dm me at D Valante or comment on our LinkedIn post. And please do check out etr.ai. They've got the best survey data in the enterprise tech business. This is Dave Valante for "theCube" Insights powered by ETR. Thanks for watching. We'll see you next week on "Ignite" or next time on "Breaking Analysis". (upbeat music)

>>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.

>>The Cube presents UI Path Forward five. Brought to you by UI Path. >>Hi everybody. Welcome back to Las Vegas. You're watching the Cube's coverage of UI Path Forward. Five. We reach cruising altitude on day two. Christina Seacrest is here. She's the process Artificial intelligence and automation GPS automation leader at ey. And Bob PCIs, executive director for Intelligent Automation for the state of Tennessee. Folks, welcome to the cube. Thank you for Adam. >>Good >>To have you. Okay, I don't know if I messed up that title, Christina, but it's kind of interesting. You got process, you got ai, you got automation, you got gps. What's your role? >>I have a lot of rules, so thank you for that. Yeah, so my focus is first and foremost automation. So how do you get things like UI path into our clients, but also I focus specifically in our government and public sector clients. So sled specifically. So state local education. So that's why I'm here with the state of Tennessee. And then we also like to take it beyond automation. So how do you bring an artificial intelligence and all the technologies that come with that. So really full end to end spectrum of >>Automation. So Bob, when you think about the sort of the, the factors that are driving your organization of, how did you describe that, Those sort of external factors that inform your strategy. What, what's, what are the catalysts for how you determine to deploy technology? >>Well, it was primarily that we know tendency has a tendency to provide good customer service, but we want to get to a great status best in class, if you will. And we had an external advisory review where it said, Hey, you know, we could make automation to improve our customer experience. And so that was like a directive of the, the state leaders to go across the board and automate all processes statewide, starting with the 23 executive agencies. >>So where's the focus from that standpoint? Is it on just providing better interfaces to your constituents, your customers? Is it cutting costs or you actually have more budget to invest? Kind of a combination of >>Those? Yeah, so it's, it's really both qualitative and quantitative, right? So quantitative is where we're able to reduce hours and therefore we can redirect people to more less mundane work, if you will. And then qualitative is where we're able to reduce the errors, improve data quality, reduce cycle time for our citizens, you know, when they're making requests, et cetera. So it's, I think it's a combination of both of those quantitative and qualitative metrics that we are mandated in, in micromanaged, quite frankly to, to bring, make those >>Numbers. So I'm from Massachusetts, when I go to a a mass.gov website, I say, all this was done in the 1990s and you could just see where the different stovepipes were, were. But then every now and then you'll hit one and you'll say, Wow, okay, this is up to, it's such a great experience. And then the flip side of that is you want your employees to be happy and not have to do all this mundane work so you can retain the best people. You don't have to. So you're living that in, in state and, and local. So where did you start your automation journey? What role did EY play? Let's go. Yeah, >>Sure. So I, I, I think the thought for process automation was probably three or four years ago, but then we started the program about 18 months ago and there was a lot of, let's say behind the scenes work before we could bring EY in, you know, like what resources was I gonna have in, in the state that were gonna help me address all of the agency simultaneously, right? Cuz normally you'll see a project that'll do be more siloed across the state and say, we're gonna do this agency, we're gonna do this division. Well, you have 40 other agencies that are, you know, the momentum is it's just gonna fall, it wayside. So how we looked at it was let's blanket it and go across all 23 agencies at the same time, you know, identify common processes that are used across 40 divisions, for example, right? >>So, so what we basically did is we procured the software, you know, did the contracts, and then it was really about, I designed, I'm gonna say a multistream approach where they were, we could run multiple work streams, independent define all the architectures, required dev tests, production, the disaster recovery at the same time in parallel developed the center of excellence, the operation model, the processes, methodologies. And the third one was, let's go out to a few divisions, business administration, health, you know, health, human resources, and be able to do a process inventory to see what was there. And then based on that, there's all this theory of well let's do a proof of concept. Let's do a proof of technology, let's do apply. Well, the bottom line is rpa technology's been around for a long time. It's proven there's nothing to prove. But really what was important to prove before we decided to go, you know, full tilt was, you know, develop a proof of perceived business value. >>Are we gonna bring in the, the business value, the hours and the qu qualitative metrics that is expected by our ex executive team, The leadership, we were able to do that, you know, with the help of help of ey, we built out the prototypes and we got the green light to go forward, got ey to start, and then we just basically went pedal to the metal. We had our foundation already defined. We built up the architecture in less than one to two months. Now, in, in a public sector or private sector, it's just not heard of, right? But we have a tendency with EYs technical team, myself, we look around the, the road around the rock instead, the rock in the road, right? So we ended up coming up with a very unique, very easy to easy to handle architecture that was very scalable. And then were able to hit the ground running and deploy in production by December where head of >>Was EY involved in the whole, you know, dev test production, dr. Center of excellence, the, the process inventory or did you bring them in? Did you kind of do that internally then bring EY in for the proof of >>Value? EY was actually awarded the contract for soup to nuts, basically the first phase, which was those four work streams I told you about. And they worked with myself and the state of Tennessee infrastructure architecture teams. We needed to get these things defined and signed off the architecture so we could expedite getting them built out. And then they, and they basically ran all four work streams, you know, the process, inventory, the prototype, the, the proof of perceived business value, the building out the center of excellence, working with myself. And, and this wasn't just us in a, a vacuum, we ended up having to, I mean, I could do the strategy, I could do the technology and I could said the roadmap and all the good stuff, but we had to actually meet with a lot of the state or tendency organizations on change management. How do we end up putting this process or an automation in the middle of the, the normal traditional process, right? So there was a lot of interaction there and getting their feedback and then tweaking our operational model based on feedback from the state of Tennessee. So it was all very collective collaborative. I think that would be the keyword is collaborative and then building out everything. So then, and then we ended up going to the next way where they knew so much and we were, we had such a tight timeframe that we continued with ey. >>So Christina, Bob mentioned center of excellence a couple of times in the state of Tennessee, but then beyond state of Tennessee, other organizations you've worked with in this space, what's the relationship between center of excellence and this thing we've been hearing about over the last couple of days, the citizen developer has that been, has, has, has that been leveraged in the state of Tennessee? Bob, have you seen that leveraged in other places? Christina? What's that relationship look like? >>Yeah, so we don't leverage that, that model yet we have centralized model and there's reasons for that. So we don't end up having maverick's, runoff runoffs have one off, have, you know, have a a UI path version or down this division or have another RPA tool in another division, right? So then all of a sudden we're, we have a maintenance nightmare. Manageability nightmare. So we basically, you know, I I I negotiate an ELA with UI path, so therefore if anyone wants to go do another automation on another division, or they would basically follow our model, our design, our coe, our quality gates. We we're the gatekeepers to bring into production. >>Got it. Now, yeah. Now Christina, what's your perspective? Because I can imagine Nashville and Memphis might have very different ideas about a lot of things. Yeah. Little Tennessee reference there, but what, what, what about what, what about other places are you, are you seeing the citizen developer leveraged in, in some kinds of places more than others or >>What? Yeah. Yeah. And that's part of, because of the foundation we're building. Yeah. So we laid, you know, when, when Bob talks about the first phase of eight weeks, that was amazingly fast, even in that's ridiculous. Spoke about it to say you're gonna lay these four foundations. I was excited, like, I was like, wow, this, this is a very serious client. They wanna go fast and they wanna get that momentum, but the AUM was laid out so we could propel ourselves. So we are at 40 automations right now. We're in the works of creating 80 more automations in this next year. We'll be at 120 really quickly. The AUM is critical. And I will say at a client, I've, I've worked with over 50 clients on automation programs. The way state of Tennessee treats the aom and they abide by it, it is the living document of how you go and go fast. Got it. And the one thing I would say is it's also allowed us to have such immense quality. So I always talk about you put in forward, you put in another 80, we're at 98% uptime on all our automations, meaning they don't go down. And that's because of the AOM we set up. And the natural progression is going to be how do you take it to citizen developer? How do you take it to, we call, you know, process automation plus, >>But methodically, methodically, not just throwing it out at the beginning and, and hoping the chaos >>Works. Exactly. Exactly. And >>The ratio of of bots to automations, is that one to one or you have automation? Oh no, the single bot is doing multiple. So how many bots are you talking about? >>We're doing, Bob, you're gonna answer this better than I will, but the efficiency is amazing. We've been pushing that. >>So our ratio now, cause we have a high density architecture we put in is four bots, excuse me, four processes. The one bot and four bots, The one virtual machine EC two server. Right? So it's four to one, four to one. Now what we're going to get by next summer, we'll do more analysis. We'll probably get the six to one, six to one that's made serious shrinkage of our footprint from a machine, you know, management perspective from 60 down to seven right now we're gonna add the next chunk. We add another 80 automations in FIS gear 24. We're only gonna add two more bot, two more servers. Right? So that's only 10 running like close to 200 bucks. >>And, and is doing this on prem in the cloud? >>No, our, the architecture's fully >>Oh, cloud based >>Ct. Yeah. So we use UiPath SAS model. Yeah. Right. So that handles the orchestrator, the attended bots, all the other tooling you need automation hub, process minor et etc. Etc. Cetera. And then on the state side in aws we have, we use unattended bots, cert bots that have to go down into the legacy systems, et cetera. And they're sitting on EC two instances. >>Was there, was there a security not hole that you had to get through internally? What was that like? >>No, actually we, we, we were lock and step with the security team on this. I mean, there are some standards and templates and you know, what we had to follow, you know, but they're doing an assessment every single release, they do assessments on little bots, what systems it's activating or are accessing, et cetera. The data, because you have fedra data of FTI data, you know, in the public sector to make sure we're not touching it. >>Do you guys golf? >>I do, yeah. Not Well, yes, >>If you mean I I like golf but not don't golf well, but so you know what, what a mulligan is. If you had a Mulligan right, for the state of Tennessee, what'd you learn? What would you do differently? You know, what are some of the gotchas you see maybe Christina in, in other customers and then maybe specifically state of Tennessee, >>Right? I would say, you know, it is the intangibles. So when we talk about our clients that go fast and go big, like state of Tennessee, it's because that, that we call it phase zero that gets done that Bob did. It's about making sure you've got the sponsorship. So we've got executive sponsorship all the way up. You've got amazing stakeholder engagement. So you're communicating the value of what we're trying to do. And you're, you're showing them the value. We have been really focused on the return on investment and we'll talk a little bit about that, but it's how do you make sure that when you do, you know, states are different with those agencies, you have such an opportunity to maximize return on investment if you do it right, because you're not talking about automation in one agency, you're talking it across multiple agencies. We call that the multiplier effect. And that's huge. And if you understand that and how to actually apply that, the value you get is amazing. So I, I don't, I can't say there's a mulligan here, Bob, you may think of some, I know on other clients, if you don't line up your stakeholders and you don't set the expectations early on, you meander and you may get five, six automations in over the year. You know, when I go to clients and say, we're doing 40, we're doing 80, they're like, >>Wow, that's the, but that's the bottom line. Gotcha. Is if you, if you want to have an operational impact and have multiple zeros, you gotta go through that process that you said up front. >>Exactly. A >>Anything you do differently, Bob? >>Well, I I what I do differently, I mean, I think, I mean we, we did get executive sponsorship, you know, and in one area, but we still have to go out to all the 23 agencies and get, and bring awareness and kind of like set the hook to bring 'em in, right? Bring 'em to the, to the, to the lake. Right. And, and I think if, if it was more of a blanket top down, getting every agency to agree to, you know, in investigate automation, it would've been a lot easier. So we're, we're, we're getting it done. We've gone through 13 agencies already and less than a year, all of our releases are sprinkling across multiple agencies. So it's not like a silo. I'll look at that. Everyone at every agency is being impacted. So I think that's great. But I, I think our, our Mueller now is just trying to make sure we have enough backlog to do the next sprints. >>Is it, you know, the ROI on these initiatives is, is, is so clear and so fast. Is it self-funding? Is there gain sharing or do you just give business, give money back to the state and have to scramble for more? Do you get to, you know, get a lick off that cone? >>Unfortunately we don't, but I, I, I try to see if we could get some property like, nah, we don't do that. It's all cost, cost based. But, but our ROI is very attractive, I think for, for doing a whole state, you know, transformation. I think our ROI is three and a half to four years. Right. And that's pretty mind blowing. Even if you look at private sector or, I, I think some of the, the key things which people are noticing, even though we're in public sector, we're we are very nimble. This project is extremely nimble. We've had people come in, exactly, we need this, so we're gonna get penalized. Okay, knock it out in four hours, four days. Right? So it's that nimbleness that you just don't hear of even in private sector or public sector. And we're just able to do that for all the collaboration we do across ey, across myself and across all the other organizations that I, that I kind of drag along or what have, >>What do you, what do you, do you see any limits to the opportunities here? I mean, is this a decade long opportunity? Is you have that much runway >>Or that's just not my dna, so we're gonna, we're gonna probably do it like in four years, but Well, when >>You say do it, I mean, will you be done at that point? Or do you see the weight, >>Look at, you know, we could boil the ocean and I think this is one of the reasons why we're successful is we could boil the ocean and and be, it will be 10 attended 20 year program. Yeah. Okay. Or we looked at it, we had some of EY guys look at it and say, I said, what's the 25 80 rule? Meaning, you know, give me, So if we had 500 processes, tell me how many processes will gimme 80% of the hours. And it was 125, it was a 25 80 rule. I said, that's what we're doing it, we're doing, we're gonna do the 80% of the hours quantifiably. Now when we're done with that pass, then we'll have those other ones that are bringing 20% of the hours, that's when we might be bringing citizens in. That's what we're bringing state workers in. But at that same time, we will be going back in the wave and doing advanced ai. Right. Or advance ia, in other words. So right now we do rpa, ocr, icr, but you know, there's NL ml nps, there's virtual agents and stuff. So that's like the wave we're gonna do through the ones we've already gone through. Got it. Right. So it'll probably be a two or three wave or iterations. >>Cool. Guys, thanks so much for coming into the cube. Great story. Really appreciate you taking us through it. Thank you so much for having us. You're very welcome. All right, keep it right there. Dave Nicholson. The Dave ante. We back at UI path forward five from the Venetian in Las Vegas. Keep it right there.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's day one coverage of HPE discover 22 live from the Venetian in Las Vegas. I got a power panel here, Lisa Martin, with Dave Valante, John furrier, Holger Mueller also joins us. We are gonna wrap this, like you've never seen a rap before guys. Lot of momentum today, lot, lot of excitement, about 8,000 or so customers, partners, HPE leaders here. Holger. Let's go ahead and start with you. What are some of the things that you heard felt saw observed today on day one? >>Yeah, it's great to be back in person. Right? 8,000 people events are rare. Uh, I'm not sure. Have you been to more than 8,000? <laugh> yeah, yeah. Okay. This year, this year. I mean, historically, yes, but, um, >>Snowflake was 10. Yeah. >>So, oh, wow. Okay. So 8,000 was my, >>Cisco was, they said 15, >>But is my, my 8,000, my record, I let us down with 7,000 kind of like, but it's in the Florida swarm. It's not nicely. Like, and there's >>Usually what SFI, there's usually >>20, 20, 30, 40, 50. I remember 50 in the nineties. Right. That was a different time. But yeah. Interesting. Yeah. Interesting what people do and it depends how much time there is to come. Right. And know that it happens. Right. But yeah, no, I think it's interesting. We, we had a good two analyst track today. Um, interesting. Like HPE is kind of like back not being your grandfather's HPE to a certain point. One of the key stats. I know Dave always for the stats, right. Is what I found really interesting that over two third of GreenLake revenue is software and services. Now a love to know how much of that services, how much of that software. But I mean, I, I, I, provocate some, one to ones, the HP executives saying, Hey, you're a hardware company. Right. And they didn't even come back. Right. But Antonio said, no, two thirds is, uh, software and services. Right. That's interesting. They passed the one exabyte, uh, being managed, uh, as a, as a hallmark. Right. I was surprised only 120,000 users if I had to remember the number. Right, right. So that doesn't seem a terrible high amount of number of users. Right. So, but that's, that's, that's promising. >>So what software is in there, cuz it's gotta be mostly services. >>Right? Well it's the 70 plus cloud services, right. That everybody's talking about where the added eight of them shockingly back up and recovery, I thought that was done at launch. Right. >>Still who >>Keep recycling storage and you back. But now it's real. Yeah. >>But the company who knows the enterprise, right. HPE, what I've been doing before with no backup and recovery GreenLake. So that was kind of like, okay, we really want to do this now and nearly, and then say like, oh, by the way, we've been doing this all the time. Yeah. >>Oh, what's your take on the installed base of HP. We had that conversation, the, uh, kickoff or on who's their target, what's the target audience environment look like. It certainly is changing. Right? If it's software and services, GreenLake is resonating. Yeah. Um, ecosystems responding. What's their customers cuz managed services are up too Kubernetes, all the managed services what's what's it like what's their it transformation base look like >>Much of it is of course install base, right? The trusted 20, 30 plus year old HP customer. Who's keeping doing stuff of HP. Right. And call it GreenLake. They've been for so many name changes. It doesn't really matter. And it's kind of like nice that you get the consume pain only what you consume. Right. I get the cloud broad to me then the general markets, of course, people who still need to run stuff on premises. Right. And there's three reasons of doing this performance, right. Because we know the speed of light is relative. If you're in the Southern hemisphere and even your email servers in Northern hemisphere, it takes a moment for your email to arrive. It's a very different user experience. Um, local legislation for data, residency privacy. And then, I mean Charles Phillips who we all know, right. Former president of uh, info nicely always said, Hey, if the CIOs over 50, I don't have to sell qu. Right. So there is not invented. I'm not gonna do cloud here. And now I've kind of like clouded with something like HP GreenLake. That's the customers. And then of course procurement is a big friend, right? Yeah. Because when you do hardware refresh, right. You have to have two or three competitors who are the two or three competitors left. Right. There's Dell. Yeah. And then maybe Lenovo. Right? So, so like a >>Little bit channels, the strength, the procurement physicians of strength, of course install base question. Do you think they have a Microsoft opportunity where, what 365 was Microsoft had office before 365, but they brought in the cloud and then everything changed. Does HP have that same opportunity with kind of the GreenLake, you know, model with their existing stuff. >>It has a GreenLake opportunity, but there's not much software left. It's a very different situation like Microsoft. Right? So, uh, which green, which HP could bring along to say, now run it with us better in the cloud because they've been selling much of it. Most of it, of their software portfolio, which they bought as an HP in the past. Right. So I don't see that happening so much, but GreenLake as a platform itself course interesting because enterprise need a modern container based platform. >>I want, I want to double click on this a little bit because the way I see it is HP is going to its installed base. I think you guys are right on say, this is how we're doing business now. Yeah. You know, come on along. But my sense is, some customers don't want to do the consumption model. There are actually some customers that say, Hey, of course I got, I don't have a cash port problem. I wanna pay for it up front and leave me alone. >>I've been doing this since 50 years. Nice. As I changed it, now <laugh> two know >>Money's wants to do it. And I don't wanna rent because rental's more expensive and blah, blah, blah. So do you see that in the customer base that, that some are pushing back? >>Of course, look, I have a German accent, right? So I go there regularly and uh, the Germans are like worried about doing anything in the cloud. And if you go to a board in Germany and say, Hey, we can pay our usual hardware, refresh, CapEx as usual, or should we bug consumption? And they might know what we are running. <laugh> so not whole, no offense against the Germans out. The German parts are there, but many of them will say, Hey, so this is change with COVID. Right. Which is super interesting. Right? So the, the traditional boards non-technical have been hearing about this cloud variable cost OPEX to CapEx and all of a sudden there's so much CapEx, right. Office buildings, which are not being used truck fleets. So there's a whole new sensitivity by traditional non-technical boards towards CapEx, which now the light bulb went on and say, oh, that's the cloud thing about also. So we have to find a way to get our cost structure, to ramp up and ramp down as our business might be ramping up through COVID through now inflation fears, recession, fears, and so on. >>So, okay. HP's, HP's made the statement that anything you can do in the cloud you can do in GreenLake. Yes. And I've said you can't run on snowflake. You can't run Mongo Atlas, you can't run data bricks, but that's okay. That's fine. Let's be, I think they're talking about, there's >>A short list of things. I think they're talking about the, their >>Stuff, their, >>The operating experience. So we've got single sign on through a URL, right. Uh, you've got, you know, some level of consistency in terms of policy. It's unclear exactly what that is. You've got storage backup. Dr. What, some other services, seven other services. If you had to sort of take your best guess as to where HP is now and peg it toward where Amazon was in which year? >>20 14, 20 14. >>Yeah. Where they had their first conference or the second we invent here with 3000 people and they were thinking, Hey, we're big. Yeah. >>Yeah. And I think GreenLake is the building blocks. So they quite that's the >>Building. Right? I mean similar. >>Okay. Well, I mean they had E C, Q and S3 and SQS, right. That was the core. And then the rest of those services were, I mean, base stock was one of that first came in behind and >>In fairness, the industry has advanced since then, Kubernetes is further along. And so HPE can take advantage of that. But in terms of just the basic platform, I, I would agree. I think it's >>Well, I mean, I think, I mean the software, question's a big one. I wanna bring up because the question is, is that software is getting the world. Hardware is really software scales, everything, data, the edge story. I love their story. I think HP story is wonderful Aruba, you know, hybrid cloud, good story, edge edge. But if you look under the covers, it's weak, right? It's like, it's not software. They don't have enough software juice, but the ecosystem opportunity to me is where you plug and play. So HP knows that game. But if you look historically over the past 25 years, HP now HPE, they understand plug and play interoperability. So the question is, can they thread the needle >>Right. >>Between filling the gaps on the software? Yeah. With partners, >>Can they get the partners? Right. And which have been long, long time. Right. For a long time, HP has been the number one platform under ICP, right? Same thing. You get certified for running this. Right. I know from my own history, uh, I joined Oracle last century and the big thing was, let's get your eBusiness suite certified on HP. Right? Like as if somebody would buy H Oracle work for them, right. This 20 years ago, server >>The original exit data was HP. Oracle. >>Exactly. Exactly. So there's this thinking that's there. But I think the key thing is we know that all modern forget about the hardware form in the platforms, right? All modern software has to move to containers and snowflake runs in containers. You mentioned that, right? Yeah. If customers force snowflake and HPE to the table, right, there will be a way to make it work. Right. And which will help HPE to be the partner open part will bring the software. >>I, I think it's, I think that's an opportunity because that changes the game and agility and speed. If HP plays their differentiation, right. Which we asked on their opening segment, what's their differentiation. They got size scale channel, >>What to the enterprise. And then the big benefit is this workload portability thing. Right? You understand what is run in the public cloud? I need to run it local. For whatever reason, performance, local residency of data. I can move that. There that's the big benefit to the ISVs, the sales vendors as well. >>But they have to have a stronger data platform story in my that's right. Opinion. I mean, you can run Oracle and HPE, but there's no reason they shouldn't be able to do a deal with, with snowflake. I mean, we saw it with Dell. Yep. We saw it with, with, with pure and I, if our HPE I'd be saying, Hey, because the way the snowflake deal worked, you probably know this is your reading data into the cloud. The compute actually occurs in the cloud viral HB going snowflake saying we can separate compute and storage. Right. And we have GreenLake. We have on demand. Why don't we run the compute on-prem and make it a full class, first class citizen, right. For all of our customers data. And that would be really innovative. And I think Mongo would be another, they've got OnPrem. >>And the question is, how many, how many snowflake customers are telling snowflake? Can I run you on premise? And how much defo open years will they hear from that? Right? This is >>Why would they deal Dell? That >>Deal though, with that, they did a deal. >>I think they did that deal because the customer came to them and said, you don't exactly that deal. We're gonna spend the >>Snowflake >>Customers think crazy things happen, right? Even, even put an Oracle database in a Microsoft Azure data center, right. Would off who, what as >>Possible snowflake, >>Oracle. So on, Aw, the >>Snow, the snowflakes in the world have to make a decision. Dave on, is it all snowflake all the time? Because what the reality is, and I think, again, this comes back down to the, the track that HP could go up or down is gonna be about software. Open source is now the software industry. There's no such thing as proprietary software, in my opinion, relatively speaking, cloud scale and integrated, integrated integration software is proprietary. The workflows are proprietary. So if they can get that right with the partners, I would focus on that. I think they can tap open source, look at Amazon with open source. They sucked it up and they integrated it in. No, no. So integration is the deal, not >>Software first, but Snowflake's made the call. You were there, Lisa. They basically saying it's we have, you have to be in snowflake in order to get the governance and the scalability, all that other wonderful stuff. Oh, but we we'll do Apache iceberg. We'll we'll open it up. We'll do Python. Yeah. >>But you can't do it data clean room unless you are in snowflake. Exactly. Snowflake on snowflake. >>Exactly. >>But got it. Isn't that? What you heard from AWS all the time till they came out outposts, right? I mean, snowflake is a market leader for what they're doing. Right. So that they want to change their platform. I mean, kudos to them. They don't need to change the platform. They will be the last to change their platform to a ne to anything on premises. Right. But I think the trend already shows that it's going that way. >>Well, if you look at outpost is an signal, Dave, the success of outpost launched what four years ago, they announced it. >>What >>EKS is beating, what outpost is doing. Outpost is there. There's not a lot of buzz and talk to the insiders and the open source community, uh, EKS and containers. To your point mm-hmm <affirmative> is moving faster on, I won't say commodity hardware, but like could be white box or HP, Dell, whatever it's gonna be that scale differentiation and the edge story is, is a good one. And I think with what we're seeing in the market now it's the industrial edge. The back office was gen one cloud back office data center. Now it's hybrid. The focus will be industrial edge machine learning and AI, and they have it here. And there's some, some early conversations with, uh, I heard it from, uh, this morning, you guys interviewed, uh, uh, John Schultz, right? With the world economic 4k birth Butterfield. She was amazing. And then you had Justin bring up a Hoar, bring up quantum. Yes. That is a differentiator. >>HP. >>Yes. Yeah. You, they have the computing shops. They had the R and D can they bring it to the table >>As, as HPC, right. To what they Schultz for of uh, the frontier system. Right. So very impressed. >>So the ecosystem is the key for them is because that's how they're gonna fill the gaps. They can't, they can't only, >>They could, they could high HPC edge piece. I wouldn't count 'em out of that game yet. If you co-locate a box, I'll use the word box, particularly at a telco tower. That's a data center. Yep. Right. If done properly. Yep. So, you know, what outpost was supposed to do actually is a hybrid opportunity. Aruba >>Gives them a unique, >>But the key thing is right. It's a yin and yang, right? It's the ecosystem it's partners to bring those software workload. Absolutely. Right. But HPE has to keep the platform attractive enough. Right. And the key thing there is that you have this workload capability thing that you can bring things, which you've built yourself. I mean, look at the telcos right. Network function, visualization, thousands of man, years into these projects. Right. So if I can't bring it to your edge box, no, I'm not trying to get to your Xbox. Right. >>Hold I gotta ask you since in the Dave too, since you guys both here and Lisa, you know, I said on the opening, they have serious customers and those customers have serious problems, cyber security, ransomware. So yeah. I teach transformation now. Industrial transformation machine learning, check, check, check. Oh, sounds good. But at the end of the day, their customers have some serious problems. Right? Cyber, this is, this is high stakes poker. Yeah. What do you think HP's position for in the security? You mentioned containers, you got all this stuff, you got open source, supply chain, you have to left supply chain issues. What is their position with security? Cuz that's the big one. >>I, I think they have to have a mature attitude that customers expect from HPE. Right? I don't have to educate HP on security. So they have to have the partner offerings again. We're back at the ecosystem to have what probably you have. So bring your own security apart from what they have to have out of the box to do business with them. This is why the shocker this morning was back up in recovery coming. <laugh> it's kind like important for that. Right? Well >>That's, that's, that's more ransomware and the >>More skeleton skeletons in the closet there, which customers should check of course. But I think the expectations HP understands that and brings it along either from partner or natively. >>I, I think it's, I think it's services. I think point next is the point of integration for their security. That's why two thirds is software and services. A lot of that is services, right? You know, you need security, we'll help you get there. We people trust HP >>Here, but we have nothing against point next or any professional service. They're all hardworking. But if I will have to rely on humans for my cyber security strategy on a daily level, I'm getting gray hair and I little gray hair >>Red. Okay. I that's, >>But >>I think, but I do think that's the camera strategy. I mean, I'm sure there's a lot of that stuff that's beginning to be designed in, but I, my guess is a lot of it is services. >>Well, you got the Aruba. Part of the booth was packed. Aruba's there. You mentioned that earlier. Is that good enough? Because the word zero trust is kicked around a lot. On one hand, on the other hand, other conversations, it's all about trust. So supply chain and software is trusting trust, trust and verified. So you got this whole mentality of perimeter gone mentality. It's zero trust. And if you've got software trust, interesting thoughts there, how do you reconcile zero trust? And then I need trust. What's what's you? What are you seeing older on that? Because I ask people all the time, they're like, uh, I'm zero trust or is it trust? >>Yeah. The middle ground. Right? Trusted. The meantime people are man manipulating what's happening in your runtime containers. Right? So, uh, drift control is a new password there that you check what's in your runtime containers, which supposedly impenetrable, but people finding ways to hack them. So we'll see this cat and mouse game going on all the time. Yeah. Yeah. There's always gonna be the need for being in a secure, good environment from that perspective. Absolutely. But the key is edge has to be more than Aruba, right? If yeah. HV goes away and says, oh yeah, we can manage your edge with our Aruba devices. That's not enough. It's the virtual probability. And you said the important thing before it's about the data, right? Because the dirty secret of containers is yeah, I move the code, but what enterprise code works without data, right? You can't say as enterprise, okay, we're done for the day check tomorrow. We didn't persist your data, auditor customer. We don't have your data anymore. So filling a way to transport the data. And there just one last thought, right? They have a super interesting asset. They want break lands for the venerable map R right. Which wrote their own storage drivers and gives you the chance to potentially do something in that area, which I'm personally excited about. But we'll see what happens. >>I mean, I think the holy grail is can I, can I put my data into a cloud who's ever, you know, call it a super cloud and can I, is it secure? Is it governed? Can I share it and be confident that it's discoverable and that the, the person I give it to has the right to use it. Yeah. And, and it's the correct data. There's not like a zillion copies running. That's the holy grail. And I, I think the answer today is no, you can, you can do that maybe inside of AWS or maybe inside of Azure, look maybe certainly inside of snowflake, can you do that inside a GreenLake? Well, you probably can inside a GreenLake, but then when you put it into the cloud, is it cross cloud? Is it really out to the edge? And that's where it starts to break down, but that's where the work is to be done. That's >>The one Exide is in there already. Right. So men being men. Yeah. >>But okay. But it it's in there. Yeah. Okay. What do you do with it? Can you share that data? What can you actually automate governance? Right? Uh, is that data discoverable? Are there multiple copies of that data? What's the, you know, master copy. Here's >>A question. You guys, here's a question for you guys analyst, what do you think the psychology is of the CIO or CSO when HP comes into town with GreenLake, uh, and they say, what's your relationship with the hyperscalers? Cause I'm a CIO. I got my environment. I might be CapEx centric or Hey, I'm open model. Open-minded to an operating model. Every one of these enterprises has a cloud relationship. Yeah. Yeah. What's the dynamic. What do you think the psychology is of the CIO when they're rationalizing their, their trajectory, their architecture, cloud, native scale integration with HPE GreenLake or >>HP service. I think she or he hears defensiveness from HPE. I think she hears HPE or he hears HPE coming in and saying, you don't need to go to the cloud. You know, you could keep it right here. I, I don't think that's the right posture. I think it should be. We are your cloud. And we can manage whether it's OnPrem hybrid in AWS, Azure, Google, across those clouds. And we have an edge story that should be the vision that they put forth. That's the super cloud vision, but I don't hear it >>From these guys. What do you think psycho, do you agree with that? >>I'm totally to make, sorry to be boring, but I totally agree with, uh, Dave on that. Right? So the, the, the multi-cloud capability from a trusted large company has worked for anybody up and down the stack. Right? You can look historically for, uh, past layers with cloud Foundry, right? It's history vulnerable. You can look for DevOps of Hashi coop. You can look for database with MongoDB right now. So if HPE provides that data access, right, with all the problems of data gravity and egres cost and the workability, they will be doing really, really well, but we need to hear it more, right. We didn't hear much software today in the keynote. Right. >>Do they have a competitive offering vis-a-vis or Azure? >>The question is, will it be an HPE offering or will, or the software platform, one of the offerings and you as customer can plug and play, right. Will software be a differentiator for HP, right. And will be close, proprietary to the point to again, be open enough for it, or will they get that R and D format that, or will they just say, okay, ES MES here on the side, your choice, and you can use OpenShift or whatever, we don't matter. That's >>The, that's the key question. That's the key question. Is it because it is a competitive strategy? Is it highly differentiated? Oracle is a highly differentiated strategy, right? Is Dell highly differentiated? Eh, Dell differentiates based on its breadth. What? >>Right. Well, let's try for the control plane too. Dell wants to be an, >>Their, their vision is differentiated. Okay. But their execution today is not >>High. All right. Let me throw, let me throw this out at you then. I'm I'm, I'm sorry. I'm I'm HPE. I wanna be the glue layer. Is that, does that fly? >>What >>Do you mean? The group glue layer? I'll I wanna be, you can do Amazon, but I wanna be the glue layer between the clouds and our GreenLake will. >>What's the, what's the incremental value that, that glue provides, >>Provides comfort and reliability and control for the single pane of glass for AWS >>And comes back to the data. In my opinion. Yeah. >>There, there there's glue levels on the data level. Yeah. And there's glue levels on API level. Right. And there's different vendors in the different spaces. Right. Um, I think HPE will want to play on the data side. We heard lots of data stuff. We >>Hear that, >>But we have to see it. Exactly. >>Yeah. But it's, it's lacking today. And so, Hey, you know, you guys know better than I APIs can be fragile and they can be, there's a lot of diversity in terms of the quality of APIs and the documentation, how they work, how mature they are, what, how, what kind of performance they can provide and recoverability. And so just saying, oh wow. We are living the API economy. You know, the it's gonna take time to brew, chime in here. Hi. >><laugh> oh, so guys, you've all been covering HPE for a long time. You know, when Antonio stood up on stage three years ago and said by 2022, and here we are, we're gonna be delivering everything as a service. He's saying we've, we've done it, but, and we're a new company. Do you guys agree with that? >>Definitely. >>I, yes. Yes. With the caveat, I think, yes. The COVID pandemic slowed them down a lot because, um, that gave a tailwind to the hyperscalers, um, because of the, the force of massive O under forecasting working at home. I mean, everyone I talked to was like, no one forecasted a hundred percent work at home, the, um, the CapEx investments. So I think that was an opportunity that they'd be much farther along if there's no COVID people >>Thought it wasn't impossible. Yeah. But so we had the old work from home thing right. Where people trying to get people fired at IBM and Yahoo. Right. So I would've this question covering the HR side and my other hat on. Right. And I would ask CHS let's assume, because I didn't know about COVID shame on me. Right. I said, big California, earthquake breaks. Right. Nobody gets hurt, but all the buildings have to be retrofitted and checked for seism logic down. So everybody's working from home, ask CHS, what kind of productivity gap hit would you get by forcing everybody working from home with the office unsafe? So one, one gentleman, I won't know him, his name, he said 20% and the other one's going ha you're smoking. It's 40 50%. We need to be in the office. We need to meet it first night. And now we went for this exercise. Luckily not with the California. Right. Well, through the price of COVID and we've seen what it can do to, to productivity well, >>The productivity, but also the impact. So like with all the, um, stories we've done over two years, the people that want came out ahead were the ones that had good cloud action. They were already in the cloud. So I, I think they're definitely in different company in the sense of they, I give 'em a pass. I think they're definitely a new company and I'm not gonna judge 'em on. I think they're doing great. But I think pandemic definitely slowed 'em down that about >>It. So I have a different take on this. I think. So we've go back a little history. I mean, you' said this, I steal your line. Meg Whitman took one for the Silicon valley team. Right. She came in. I don't think she ever was excited that I, that you said, you said that, and I think you wrote >>Up, get tape on that one. She >>Had to figure out how do I deal with this mess? I have EDS. I got PC. >>She never should have spun off the PC, but >>Okay. But >>Me, >>Yeah, you can, you certainly could listen. Maybe, maybe Gerstner never should have gone all in on services and IBM would dominate something other than mainframes. They had think pads even for a while, but, but, but so she had that mess to deal with. She dealt with it and however, they dealt with it, Antonio came in, he, he, and he said, all right, we're gonna focus the company. And we're gonna focus the mission on not the machine. Remember those yeah. Presentations, but you just make your eyes glaze over. We're going all in on Azure service >>And edge. He was all on. >>We're gonna build our own cloud. We acquired Aruba. He made some acquisitions in HPC to help differentiate. Yep. And they are definitely a much more focused company now. And unfortunately I wish Antonio would CEO in 2015, cuz that's really when this should have started. >>Yeah. And then, and if you remember back then, Dave, we were interviewing Docker with DevOps teams. They had composability, they were on hybrid really early. I think they might have even coined the term hybrid before VMware tri-state credit for it. But they were first on hybrid. They had DevOps, they had infrastructure risk code. >>HPE had an HP had an awesome cloud team. Yeah. But, and then, and then they tried to go public cloud. Yeah. You know, and then, you know, just made them, I mean, it was just a mess. The focus >>Is there. I give them huge props. And I think, I think the GreenLake to me is exciting here because it's much better than it was two years ago. When, when we talked to, when we started, it's >>Starting to get real. >>It's, it's a real thing. And I think the, the tell will be partners. If they make that right, can pull their different >>Ecosystem, >>Their scale and their customers and fill the software gas with partners mm-hmm <affirmative> and then create that integration opportunity. It's gonna be a home run if they don't do that, they're gonna miss the operating, >>But they have to have their own to your point. They have to have their own software innovation. >>They have to good infrastructure ways to build applications. I don't wanna build with somebody else. I don't wanna take a Microsoft stack on open source stack. I'm not sure if it's gonna work with HP. So they have to have an app dev answer. I absolutely agree with that. And the, the big thing for the partners is, which is a good thing, right? Yep. HPE will not move into applications. Right? You don't have to have the fear of where Microsoft is with their vocal large. Right. If AWS kind of like comes up with APIs and manufacturing, right. Google the same thing with their vertical push. Right. So HPE will not have the CapEx, but >>Application, >>As I SV making them, the partner, the bonus of being able to on premise is an attractive >>Part. That's a great point. >>Hold. So that's an inflection point for next 12 months to watch what we see absolutely running on GreenLake. >>Yeah. And I think one of the things that came out of the, the last couple events this past year, and I'll bring this up, we'll table it and we'll watch it. And it's early in this, I think this is like even, not even the first inning, the machine learning AI impact to the industrial piece. I think we're gonna see a, a brand new era of accelerated digital transformation on the industrial physical world, back office, cloud data center, accounting, all the stuff. That's applications, the app, the real world from space to like robotics. I think that HP edge opportunity is gonna be visible and different. >>So guys, Antonio Neri is on tomorrow. This is only day one. If you can imagine this power panel on day one, can you imagine tomorrow? What is your last question for each of you? What is your, what, what question would you want to ask him tomorrow? Hold start with you. >>How is HPE winning in the long run? Because we know their on premise market will shrink, right? And they can out execute Dell. They can out execute Lenovo. They can out Cisco and get a bigger share of the shrinking market. But that's the long term strategy, right? So why should I buy HPE stock now and have a good return put in the, in the safe and forget about it and have a great return 20 years from now? What's the really long term strategy might be unfair because they, they ran in survival mode to a certain point out of the mass post equipment situation. But what is really the long term strategy? Is it more on the hardware side? Is it gonna go on the HPE, the frontier side? It's gonna be a DNA question, which I would ask Antonio. >>John, >>I would ask him what relative to the macro conditions relative to their customer base, I'd say, cuz the customers are the scoreboard. Can they create a value proposition with their, I use the Microsoft 365 example how they kind of went to the cloud. So my question would be Antonio, what is your core value proposition to CIOs out there who want to transform and take a step function, increase for value with HPE? Tell me that story. I wanna hear. And I don't want to hear, oh, we got a portfolio and no, what value are you enabling your customers to do? >>What and what should that value be? >>I think it's gonna be what we were kind of riffing on, which is you have to provide either what their product market fit needs are, which is, are you solving a problem? Is it a pain point is a growth driver. Uh, and what's the, what's that tailwind. And it's obviously we know at cloud we know edge. The story is great, but what's the value proposition. But by going with HPE, you get X, Y, and Z. If they can explain that clearly with real, so qualitative and quantitative data it's home >>Run. He had a great line of the analyst summit today where somebody asking questions, I'm just listening to the customer. So be ready for this Steve jobs photo, listening to the customer. You can't build something great listening to the customer. You'll be good for the next quarter. The next exponential >>Say, what are the customers saying? <laugh> >>So I would make an observation. And my question would, so my observation would be cloud is growing collectively at 35%. It's, you know, it's approaching 200 billion with a big, big four. If you include Alibaba, IBM has actually said, Hey, we're gonna gr they've promised 6% growth. Uh, Cisco I think is at eight or 9% growth. Dow's growing in double digits. Antonio and HPE have promised three to 4% growth. So what do you have to do to actually accelerate growth? Because three to 4%, my view, not enough to answer Holger's question is why should I buy HPE stock? Well, >>If they have product, if they have customer and there's demand and traction to me, that's going to drive the growth numbers. And I think the weak side of the forecast means that they don't have that fit yet. >>Yeah. So what has to happen for them to get above five, 6% growth? >>That's what we're gonna analyze. I mean, I, I mean, I don't have an answer for that. I wish I had a better answer. I'd tell them <laugh> but I feel, it feels, it feels like, you know, HP has an opportunity to say here's the new HPE. Yeah. Okay. And this is what we stand for. And here's the one thing that we're going to do that consistently drives value for you, the customer. And that's gonna have to come into some, either architectural cloud shift or a data thing, or we are your store for blank. >>All of the above. >>I guess the other question is, would, would you know, he won't answer a rude question, would suspending things like dividends and stock buybacks and putting it into R and D. I would definitely, if you have confidence in the market and you know what to do, why wouldn't you just accelerate R and D and put the money there? IBM, since 2007, IBM spent is the last stat. And I'm looking go in 2007, IBM way, outspent, Google, and Amazon and R and D and, and CapEx two, by the way. Yep. Subsequent to that, they've spent, I believe it's the numbers close to 200 billion on stock buyback and dividends. They could have owned cloud. And so look at this business, the technology business by and large is driven by innovation. Yeah. And so how do you innovate if >>You have I'm buying, I'm buying HP because they're reliable high quality and they have the outcomes that I want. Oh, >>Buy their products and services. I'm not sure I'd buy the stock. Yeah. >>Yeah. But she has to answer ultimately, because a public company. Right. So >>Right. It's this job. Yeah. >>Never a dull moment with the three of you around <laugh> guys. Thank you so much for sharing your insights, your, an analysis from day one. I can't imagine what day two is gonna bring tomorrow. Debut and I are gonna be anchoring here. We've got a jam packed day, lots going on, hearing from the ecosystem from leadership. As we mentioned, Antonio is gonna be Tony >>Alma Russo. I'm dying. Dr. >>EDMA as well as on the CTO gonna be another action pack day. I'm excited for it, guys. Thanks so much for sharing your insights and for letting me join this power panel. >>Great. Great to be here. >>Power panel plus me. All right. For Holger, John and Dave, I'm Lisa, you're watching the cube our day one coverage of HPE discover wraps right now. Don't go anywhere, cuz we'll see you tomorrow for day two, live from Vegas, have a good night.

(upbeat music) >> The stampede to cloud and massive VC investments has led to the emergence of a new generation of object store based data lakes. And with them two important trends, actually three important trends. First, a new category that combines data lakes and data warehouses aka the lakehouse is emerged as a leading contender to be the data platform of the future. And this novelty touts the ability to address data engineering, data science, and data warehouse workloads on a single shared data platform. The other major trend we've seen is query engines and broader data fabric virtualization platforms have embraced NextGen data lakes as platforms for SQL centric business intelligence workloads, reducing, or somebody even claim eliminating the need for separate data warehouses. Pretty bold. However, cloud data warehouses have added complimentary technologies to bridge the gaps with lakehouses. And the third is many, if not most customers that are embracing the so-called data fabric or data mesh architectures. They're looking at data lakes as a fundamental component of their strategies, and they're trying to evolve them to be more capable, hence the interest in lakehouse, but at the same time, they don't want to, or can't abandon their data warehouse estate. As such we see a battle royale is brewing between cloud data warehouses and cloud lakehouses. Is it possible to do it all with one cloud center analytical data platform? Well, we're going to find out. My name is Dave Vellante and welcome to the data platform's power panel on theCUBE. Our next episode in a series where we gather some of the industry's top analysts to talk about one of our favorite topics, data. In today's session, we'll discuss trends, emerging options, and the trade offs of various approaches and we'll name names. Joining us today are Sanjeev Mohan, who's the principal at SanjMo, Tony Baers, principal at dbInsight. And Doug Henschen is the vice president and principal analyst at Constellation Research. Guys, welcome back to theCUBE. Great to see you again. >> Thank guys. Thank you. >> Thank you. >> So it's early June and we're gearing up with two major conferences, there's several database conferences, but two in particular that were very interested in, Snowflake Summit and Databricks Data and AI Summit. Doug let's start off with you and then Tony and Sanjeev, if you could kindly weigh in. Where did this all start, Doug? The notion of lakehouse. And let's talk about what exactly we mean by lakehouse. Go ahead. >> Yeah, well you nailed it in your intro. One platform to address BI data science, data engineering, fewer platforms, less cost, less complexity, very compelling. You can credit Databricks for coining the term lakehouse back in 2020, but it's really a much older idea. You can go back to Cloudera introducing their Impala database in 2012. That was a database on top of Hadoop. And indeed in that last decade, by the middle of that last decade, there were several SQL on Hadoop products, open standards like Apache Drill. And at the same time, the database vendors were trying to respond to this interest in machine learning and the data science. So they were adding SQL extensions, the likes Hudi and Vertical we're adding SQL extensions to support the data science. But then later in that decade with the shift to cloud and object storage, you saw the vendor shift to this whole cloud, and object storage idea. So you have in the database camp Snowflake introduce Snowpark to try to address the data science needs. They introduced that in 2020 and last year they announced support for Python. You also had Oracle, SAP jumped on this lakehouse idea last year, supporting both the lake and warehouse single vendor, not necessarily quite single platform. Google very recently also jumped on the bandwagon. And then you also mentioned, the SQL engine camp, the Dremios, the Ahanas, the Starbursts, really doing two things, a fabric for distributed access to many data sources, but also very firmly planning that idea that you can just have the lake and we'll help you do the BI workloads on that. And then of course, the data lake camp with the Databricks and Clouderas providing a warehouse style deployments on top of their lake platforms. >> Okay, thanks, Doug. I'd be remiss those of you who me know that I typically write my own intros. This time my colleagues fed me a lot of that material. So thank you. You guys make it easy. But Tony, give us your thoughts on this intro. >> Right. Well, I very much agree with both of you, which may not make for the most exciting television in terms of that it has been an evolution just like Doug said. I mean, for instance, just to give an example when Teradata bought AfterData was initially seen as a hardware platform play. In the end, it was basically, it was all those after functions that made a lot of sort of big data analytics accessible to SQL. (clears throat) And so what I really see just in a more simpler definition or functional definition, the data lakehouse is really an attempt by the data lake folks to make the data lake friendlier territory to the SQL folks, and also to get into friendly territory, to all the data stewards, who are basically concerned about the sprawl and the lack of control in governance in the data lake. So it's really kind of a continuing of an ongoing trend that being said, there's no action without counter action. And of course, at the other end of the spectrum, we also see a lot of the data warehouses starting to edit things like in database machine learning. So they're certainly not surrendering without a fight. Again, as Doug was mentioning, this has been part of a continual blending of platforms that we've seen over the years that we first saw in the Hadoop years with SQL on Hadoop and data warehouses starting to reach out to cloud storage or should say the HDFS and then with the cloud then going cloud native and therefore trying to break the silos down even further. >> Now, thank you. And Sanjeev, data lakes, when we first heard about them, there were such a compelling name, and then we realized all the problems associated with them. So pick it up from there. What would you add to Doug and Tony? >> I would say, these are excellent points that Doug and Tony have brought to light. The concept of lakehouse was going on to your point, Dave, a long time ago, long before the tone was invented. For example, in Uber, Uber was trying to do a mix of Hadoop and Vertical because what they really needed were transactional capabilities that Hadoop did not have. So they weren't calling it the lakehouse, they were using multiple technologies, but now they're able to collapse it into a single data store that we call lakehouse. Data lakes, excellent at batch processing large volumes of data, but they don't have the real time capabilities such as change data capture, doing inserts and updates. So this is why lakehouse has become so important because they give us these transactional capabilities. >> Great. So I'm interested, the name is great, lakehouse. The concept is powerful, but I get concerned that it's a lot of marketing hype behind it. So I want to examine that a bit deeper. How mature is the concept of lakehouse? Are there practical examples that really exist in the real world that are driving business results for practitioners? Tony, maybe you could kick that off. >> Well, put it this way. I think what's interesting is that both data lakes and data warehouse that each had to extend themselves. To believe the Databricks hype it's that this was just a natural extension of the data lake. In point of fact, Databricks had to go outside its core technology of Spark to make the lakehouse possible. And it's a very similar type of thing on the part with data warehouse folks, in terms of that they've had to go beyond SQL, In the case of Databricks. There have been a number of incremental improvements to Delta lake, to basically make the table format more performative, for instance. But the other thing, I think the most dramatic change in all that is in their SQL engine and they had to essentially pretty much abandon Spark SQL because it really, in off itself Spark SQL is essentially stop gap solution. And if they wanted to really address that crowd, they had to totally reinvent SQL or at least their SQL engine. And so Databricks SQL is not Spark SQL, it is not Spark, it's basically SQL that it's adapted to run in a Spark environment, but the underlying engine is C++, it's not scale or anything like that. So Databricks had to take a major detour outside of its core platform to do this. So to answer your question, this is not mature because these are all basically kind of, even though the idea of blending platforms has been going on for well over a decade, I would say that the current iteration is still fairly immature. And in the cloud, I could see a further evolution of this because if you think through cloud native architecture where you're essentially abstracting compute from data, there is no reason why, if let's say you are dealing with say, the same basically data targets say cloud storage, cloud object storage that you might not apportion the task to different compute engines. And so therefore you could have, for instance, let's say you're Google, you could have BigQuery, perform basically the types of the analytics, the SQL analytics that would be associated with the data warehouse and you could have BigQuery ML that does some in database machine learning, but at the same time for another part of the query, which might involve, let's say some deep learning, just for example, you might go out to let's say the serverless spark service or the data proc. And there's no reason why Google could not blend all those into a coherent offering that's basically all triggered through microservices. And I just gave Google as an example, if you could generalize that with all the other cloud or all the other third party vendors. So I think we're still very early in the game in terms of maturity of data lakehouses. >> Thanks, Tony. So Sanjeev, is this all hype? What are your thoughts? >> It's not hype, but completely agree. It's not mature yet. Lakehouses have still a lot of work to do, so what I'm now starting to see is that the world is dividing into two camps. On one hand, there are people who don't want to deal with the operational aspects of vast amounts of data. They are the ones who are going for BigQuery, Redshift, Snowflake, Synapse, and so on because they want the platform to handle all the data modeling, access control, performance enhancements, but these are trade off. If you go with these platforms, then you are giving up on vendor neutrality. On the other side are those who have engineering skills. They want the independence. In other words, they don't want vendor lock in. They want to transform their data into any number of use cases, especially data science, machine learning use case. What they want is agility via open file formats using any compute engine. So why do I say lakehouses are not mature? Well, cloud data warehouses they provide you an excellent user experience. That is the main reason why Snowflake took off. If you have thousands of cables, it takes minutes to get them started, uploaded into your warehouse and start experimentation. Table formats are far more resonating with the community than file formats. But once the cost goes up of cloud data warehouse, then the organization start exploring lakehouses. But the problem is lakehouses still need to do a lot of work on metadata. Apache Hive was a fantastic first attempt at it. Even today Apache Hive is still very strong, but it's all technical metadata and it has so many different restrictions. That's why we see Databricks is investing into something called Unity Catalog. Hopefully we'll hear more about Unity Catalog at the end of the month. But there's a second problem. I just want to mention, and that is lack of standards. All these open source vendors, they're running, what I call ego projects. You see on LinkedIn, they're constantly battling with each other, but end user doesn't care. End user wants a problem to be solved. They want to use Trino, Dremio, Spark from EMR, Databricks, Ahana, DaaS, Frink, Athena. But the problem is that we don't have common standards. >> Right. Thanks. So Doug, I worry sometimes. I mean, I look at the space, we've debated for years, best of breed versus the full suite. You see AWS with whatever, 12 different plus data stores and different APIs and primitives. You got Oracle putting everything into its database. It's actually done some interesting things with MySQL HeatWave, so maybe there's proof points there, but Snowflake really good at data warehouse, simplifying data warehouse. Databricks, really good at making lakehouses actually more functional. Can one platform do it all? >> Well in a word, I can't be best at breed at all things. I think the upshot of and cogen analysis from Sanjeev there, the database, the vendors coming out of the database tradition, they excel at the SQL. They're extending it into data science, but when it comes to unstructured data, data science, ML AI often a compromise, the data lake crowd, the Databricks and such. They've struggled to completely displace the data warehouse when it really gets to the tough SLAs, they acknowledge that there's still a role for the warehouse. Maybe you can size down the warehouse and offload some of the BI workloads and maybe and some of these SQL engines, good for ad hoc, minimize data movement. But really when you get to the deep service level, a requirement, the high concurrency, the high query workloads, you end up creating something that's warehouse like. >> Where do you guys think this market is headed? What's going to take hold? Which projects are going to fade away? You got some things in Apache projects like Hudi and Iceberg, where do they fit Sanjeev? Do you have any thoughts on that? >> So thank you, Dave. So I feel that table formats are starting to mature. There is a lot of work that's being done. We will not have a single product or single platform. We'll have a mixture. So I see a lot of Apache Iceberg in the news. Apache Iceberg is really innovating. Their focus is on a table format, but then Delta and Apache Hudi are doing a lot of deep engineering work. For example, how do you handle high concurrency when there are multiple rights going on? Do you version your Parquet files or how do you do your upcerts basically? So different focus, at the end of the day, the end user will decide what is the right platform, but we are going to have multiple formats living with us for a long time. >> Doug is Iceberg in your view, something that's going to address some of those gaps in standards that Sanjeev was talking about earlier? >> Yeah, Delta lake, Hudi, Iceberg, they all address this need for consistency and scalability, Delta lake open technically, but open for access. I don't hear about Delta lakes in any worlds, but Databricks, hearing a lot of buzz about Apache Iceberg. End users want an open performance standard. And most recently Google embraced Iceberg for its recent a big lake, their stab at having supporting both lakes and warehouses on one conjoined platform. >> And Tony, of course, you remember the early days of the sort of big data movement you had MapR was the most closed. You had Horton works the most open. You had Cloudera in between. There was always this kind of contest as to who's the most open. Does that matter? Are we going to see a repeat of that here? >> I think it's spheres of influence, I think, and Doug very much was kind of referring to this. I would call it kind of like the MongoDB syndrome, which is that you have... and I'm talking about MongoDB before they changed their license, open source project, but very much associated with MongoDB, which basically, pretty much controlled most of the contributions made decisions. And I think Databricks has the same iron cloud hold on Delta lake, but still the market is pretty much associated Delta lake as the Databricks, open source project. I mean, Iceberg is probably further advanced than Hudi in terms of mind share. And so what I see that's breaking down to is essentially, basically the Databricks open source versus the everything else open source, the community open source. So I see it's a very similar type of breakdown that I see repeating itself here. >> So by the way, Mongo has a conference next week, another data platform is kind of not really relevant to this discussion totally. But in the sense it is because there's a lot of discussion on earnings calls these last couple of weeks about consumption and who's exposed, obviously people are concerned about Snowflake's consumption model. Mongo is maybe less exposed because Atlas is prominent in the portfolio, blah, blah, blah. But I wanted to bring up the little bit of controversy that we saw come out of the Snowflake earnings call, where the ever core analyst asked Frank Klutman about discretionary spend. And Frank basically said, look, we're not discretionary. We are deeply operationalized. Whereas he kind of poo-pooed the lakehouse or the data lake, et cetera, saying, oh yeah, data scientists will pull files out and play with them. That's really not our business. Do any of you have comments on that? Help us swing through that controversy. Who wants to take that one? >> Let's put it this way. The SQL folks are from Venus and the data scientists are from Mars. So it means it really comes down to it, sort that type of perception. The fact is, is that, traditionally with analytics, it was very SQL oriented and that basically the quants were kind of off in their corner, where they're using SaaS or where they're using Teradata. It's really a great leveler today, which is that, I mean basic Python it's become arguably one of the most popular programming languages, depending on what month you're looking at, at the title index. And of course, obviously SQL is, as I tell the MongoDB folks, SQL is not going away. You have a large skills base out there. And so basically I see this breaking down to essentially, you're going to have each group that's going to have its own natural preferences for its home turf. And the fact that basically, let's say the Python and scale of folks are using Databricks does not make them any less operational or machine critical than the SQL folks. >> Anybody else want to chime in on that one? >> Yeah, I totally agree with that. Python support in Snowflake is very nascent with all of Snowpark, all of the things outside of SQL, they're very much relying on partners too and make things possible and make data science possible. And it's very early days. I think the bottom line, what we're going to see is each of these camps is going to keep working on doing better at the thing that they don't do today, or they're new to, but they're not going to nail it. They're not going to be best of breed on both sides. So the SQL centric companies and shops are going to do more data science on their database centric platform. That data science driven companies might be doing more BI on their leagues with those vendors and the companies that have highly distributed data, they're going to add fabrics, and maybe offload more of their BI onto those engines, like Dremio and Starburst. >> So I've asked you this before, but I'll ask you Sanjeev. 'Cause Snowflake and Databricks are such great examples 'cause you have the data engineering crowd trying to go into data warehousing and you have the data warehousing guys trying to go into the lake territory. Snowflake has $5 billion in the balance sheet and I've asked you before, I ask you again, doesn't there has to be a semantic layer between these two worlds? Does Snowflake go out and do M&A and maybe buy ad scale or a data mirror? Or is that just sort of a bandaid? What are your thoughts on that Sanjeev? >> I think semantic layer is the metadata. The business metadata is extremely important. At the end of the day, the business folks, they'd rather go to the business metadata than have to figure out, for example, like let's say, I want to update somebody's email address and we have a lot of overhead with data residency laws and all that. I want my platform to give me the business metadata so I can write my business logic without having to worry about which database, which location. So having that semantic layer is extremely important. In fact, now we are taking it to the next level. Now we are saying that it's not just a semantic layer, it's all my KPIs, all my calculations. So how can I make those calculations independent of the compute engine, independent of the BI tool and make them fungible. So more disaggregation of the stack, but it gives us more best of breed products that the customers have to worry about. >> So I want to ask you about the stack, the modern data stack, if you will. And we always talk about injecting machine intelligence, AI into applications, making them more data driven. But when you look at the application development stack, it's separate, the database is tends to be separate from the data and analytics stack. Do those two worlds have to come together in the modern data world? And what does that look like organizationally? >> So organizationally even technically I think it is starting to happen. Microservices architecture was a first attempt to bring the application and the data world together, but they are fundamentally different things. For example, if an application crashes, that's horrible, but Kubernetes will self heal and it'll bring the application back up. But if a database crashes and corrupts your data, we have a huge problem. So that's why they have traditionally been two different stacks. They are starting to come together, especially with data ops, for instance, versioning of the way we write business logic. It used to be, a business logic was highly embedded into our database of choice, but now we are disaggregating that using GitHub, CICD the whole DevOps tool chain. So data is catching up to the way applications are. >> We also have databases, that trans analytical databases that's a little bit of what the story is with MongoDB next week with adding more analytical capabilities. But I think companies that talk about that are always careful to couch it as operational analytics, not the warehouse level workloads. So we're making progress, but I think there's always going to be, or there will long be a separate analytical data platform. >> Until data mesh takes over. (all laughing) Not opening a can of worms. >> Well, but wait, I know it's out of scope here, but wouldn't data mesh say, hey, do take your best of breed to Doug's earlier point. You can't be best of breed at everything, wouldn't data mesh advocate, data lakes do your data lake thing, data warehouse, do your data lake, then you're just a node on the mesh. (Tony laughs) Now you need separate data stores and you need separate teams. >> To my point. >> I think, I mean, put it this way. (laughs) Data mesh itself is a logical view of the world. The data mesh is not necessarily on the lake or on the warehouse. I think for me, the fear there is more in terms of, the silos of governance that could happen and the silo views of the world, how we redefine. And that's why and I want to go back to something what Sanjeev said, which is that it's going to be raising the importance of the semantic layer. Now does Snowflake that opens a couple of Pandora's boxes here, which is one, does Snowflake dare go into that space or do they risk basically alienating basically their partner ecosystem, which is a key part of their whole appeal, which is best of breed. They're kind of the same situation that Informatica was where in the early 2000s, when Informatica briefly flirted with analytic applications and realized that was not a good idea, need to redouble down on their core, which was data integration. The other thing though, that raises the importance of and this is where the best of breed comes in, is the data fabric. My contention is that and whether you use employee data mesh practice or not, if you do employee data mesh, you need data fabric. If you deploy data fabric, you don't necessarily need to practice data mesh. But data fabric at its core and admittedly it's a category that's still very poorly defined and evolving, but at its core, we're talking about a common meta data back plane, something that we used to talk about with master data management, this would be something that would be more what I would say basically, mutable, that would be more evolving, basically using, let's say, machine learning to kind of, so that we don't have to predefine rules or predefine what the world looks like. But so I think in the long run, what this really means is that whichever way we implement on whichever physical platform we implement, we need to all be speaking the same metadata language. And I think at the end of the day, regardless of whether it's a lake, warehouse or a lakehouse, we need common metadata. >> Doug, can I come back to something you pointed out? That those talking about bringing analytic and transaction databases together, you had talked about operationalizing those and the caution there. Educate me on MySQL HeatWave. I was surprised when Oracle put so much effort in that, and you may or may not be familiar with it, but a lot of folks have talked about that. Now it's got nowhere in the market, that no market share, but a lot of we've seen these benchmarks from Oracle. How real is that bringing together those two worlds and eliminating ETL? >> Yeah, I have to defer on that one. That's my colleague, Holger Mueller. He wrote the report on that. He's way deep on it and I'm not going to mock him. >> I wonder if that is something, how real that is or if it's just Oracle marketing, anybody have any thoughts on that? >> I'm pretty familiar with HeatWave. It's essentially Oracle doing what, I mean, there's kind of a parallel with what Google's doing with AlloyDB. It's an operational database that will have some embedded analytics. And it's also something which I expect to start seeing with MongoDB. And I think basically, Doug and Sanjeev were kind of referring to this before about basically kind of like the operational analytics, that are basically embedded within an operational database. The idea here is that the last thing you want to do with an operational database is slow it down. So you're not going to be doing very complex deep learning or anything like that, but you might be doing things like classification, you might be doing some predictives. In other words, we've just concluded a transaction with this customer, but was it less than what we were expecting? What does that mean in terms of, is this customer likely to turn? I think we're going to be seeing a lot of that. And I think that's what a lot of what MySQL HeatWave is all about. Whether Oracle has any presence in the market now it's still a pretty new announcement, but the other thing that kind of goes against Oracle, (laughs) that they had to battle against is that even though they own MySQL and run the open source project, everybody else, in terms of the actual commercial implementation it's associated with everybody else. And the popular perception has been that MySQL has been basically kind of like a sidelight for Oracle. And so it's on Oracles shoulders to prove that they're damn serious about it. >> There's no coincidence that MariaDB was launched the day that Oracle acquired Sun. Sanjeev, I wonder if we could come back to a topic that we discussed earlier, which is this notion of consumption, obviously Wall Street's very concerned about it. Snowflake dropped prices last week. I've always felt like, hey, the consumption model is the right model. I can dial it down in when I need to, of course, the street freaks out. What are your thoughts on just pricing, the consumption model? What's the right model for companies, for customers? >> Consumption model is here to stay. What I would like to see, and I think is an ideal situation and actually plays into the lakehouse concept is that, I have my data in some open format, maybe it's Parquet or CSV or JSON, Avro, and I can bring whatever engine is the best engine for my workloads, bring it on, pay for consumption, and then shut it down. And by the way, that could be Cloudera. We don't talk about Cloudera very much, but it could be one business unit wants to use Athena. Another business unit wants to use some other Trino let's say or Dremio. So every business unit is working on the same data set, see that's critical, but that data set is maybe in their VPC and they bring any compute engine, you pay for the use, shut it down. That then you're getting value and you're only paying for consumption. It's not like, I left a cluster running by mistake, so there have to be guardrails. The reason FinOps is so big is because it's very easy for me to run a Cartesian joint in the cloud and get a $10,000 bill. >> This looks like it's been a sort of a victim of its own success in some ways, they made it so easy to spin up single note instances, multi note instances. And back in the day when compute was scarce and costly, those database engines optimized every last bit so they could get as much workload as possible out of every instance. Today, it's really easy to spin up a new node, a new multi node cluster. So that freedom has meant many more nodes that aren't necessarily getting that utilization. So Snowflake has been doing a lot to add reporting, monitoring, dashboards around the utilization of all the nodes and multi node instances that have spun up. And meanwhile, we're seeing some of the traditional on-prem databases that are moving into the cloud, trying to offer that freedom. And I think they're going to have that same discovery that the cost surprises are going to follow as they make it easy to spin up new instances. >> Yeah, a lot of money went into this market over the last decade, separating compute from storage, moving to the cloud. I'm glad you mentioned Cloudera Sanjeev, 'cause they got it all started, the kind of big data movement. We don't talk about them that much. Sometimes I wonder if it's because when they merged Hortonworks and Cloudera, they dead ended both platforms, but then they did invest in a more modern platform. But what's the future of Cloudera? What are you seeing out there? >> Cloudera has a good product. I have to say the problem in our space is that there're way too many companies, there's way too much noise. We are expecting the end users to parse it out or we expecting analyst firms to boil it down. So I think marketing becomes a big problem. As far as technology is concerned, I think Cloudera did turn their selves around and Tony, I know you, you talked to them quite frequently. I think they have quite a comprehensive offering for a long time actually. They've created Kudu, so they got operational, they have Hadoop, they have an operational data warehouse, they're migrated to the cloud. They are in hybrid multi-cloud environment. Lot of cloud data warehouses are not hybrid. They're only in the cloud. >> Right. I think what Cloudera has done the most successful has been in the transition to the cloud and the fact that they're giving their customers more OnRamps to it, more hybrid OnRamps. So I give them a lot of credit there. They're also have been trying to position themselves as being the most price friendly in terms of that we will put more guardrails and governors on it. I mean, part of that could be spin. But on the other hand, they don't have the same vested interest in compute cycles as say, AWS would have with EMR. That being said, yes, Cloudera does it, I think its most powerful appeal so of that, it almost sounds in a way, I don't want to cast them as a legacy system. But the fact is they do have a huge landed legacy on-prem and still significant potential to land and expand that to the cloud. That being said, even though Cloudera is multifunction, I think it certainly has its strengths and weaknesses. And the fact this is that yes, Cloudera has an operational database or an operational data store with a kind of like the outgrowth of age base, but Cloudera is still based, primarily known for the deep analytics, the operational database nobody's going to buy Cloudera or Cloudera data platform strictly for the operational database. They may use it as an add-on, just in the same way that a lot of customers have used let's say Teradata basically to do some machine learning or let's say, Snowflake to parse through JSON. Again, it's not an indictment or anything like that, but the fact is obviously they do have their strengths and their weaknesses. I think their greatest opportunity is with their existing base because that base has a lot invested and vested. And the fact is they do have a hybrid path that a lot of the others lack. >> And of course being on the quarterly shock clock was not a good place to be under the microscope for Cloudera and now they at least can refactor the business accordingly. I'm glad you mentioned hybrid too. We saw Snowflake last month, did a deal with Dell whereby non-native Snowflake data could access on-prem object store from Dell. They announced a similar thing with pure storage. What do you guys make of that? Is that just... How significant will that be? Will customers actually do that? I think they're using either materialized views or extended tables. >> There are data rated and residency requirements. There are desires to have these platforms in your own data center. And finally they capitulated, I mean, Frank Klutman is famous for saying to be very focused and earlier, not many months ago, they called the going on-prem as a distraction, but clearly there's enough demand and certainly government contracts any company that has data residency requirements, it's a real need. So they finally addressed it. >> Yeah, I'll bet dollars to donuts, there was an EBC session and some big customer said, if you don't do this, we ain't doing business with you. And that was like, okay, we'll do it. >> So Dave, I have to say, earlier on you had brought this point, how Frank Klutman was poo-pooing data science workloads. On your show, about a year or so ago, he said, we are never going to on-prem. He burnt that bridge. (Tony laughs) That was on your show. >> I remember exactly the statement because it was interesting. He said, we're never going to do the halfway house. And I think what he meant is we're not going to bring the Snowflake architecture to run on-prem because it defeats the elasticity of the cloud. So this was kind of a capitulation in a way. But I think it still preserves his original intent sort of, I don't know. >> The point here is that every vendor will poo-poo whatever they don't have until they do have it. >> Yes. >> And then it'd be like, oh, we are all in, we've always been doing this. We have always supported this and now we are doing it better than others. >> Look, it was the same type of shock wave that we felt basically when AWS at the last moment at one of their reinvents, oh, by the way, we're going to introduce outposts. And the analyst group is typically pre briefed about a week or two ahead under NDA and that was not part of it. And when they dropped, they just casually dropped that in the analyst session. It's like, you could have heard the sound of lots of analysts changing their diapers at that point. >> (laughs) I remember that. And a props to Andy Jassy who once, many times actually told us, never say never when it comes to AWS. So guys, I know we got to run. We got some hard stops. Maybe you could each give us your final thoughts, Doug start us off and then-- >> Sure. Well, we've got the Snowflake Summit coming up. I'll be looking for customers that are really doing data science, that are really employing Python through Snowflake, through Snowpark. And then a couple weeks later, we've got Databricks with their Data and AI Summit in San Francisco. I'll be looking for customers that are really doing considerable BI workloads. Last year I did a market overview of this analytical data platform space, 14 vendors, eight of them claim to support lakehouse, both sides of the camp, Databricks customer had 32, their top customer that they could site was unnamed. It had 32 concurrent users doing 15,000 queries per hour. That's good but it's not up to the most demanding BI SQL workloads. And they acknowledged that and said, they need to keep working that. Snowflake asked for their biggest data science customer, they cited Kabura, 400 terabytes, 8,500 users, 400,000 data engineering jobs per day. I took the data engineering job to be probably SQL centric, ETL style transformation work. So I want to see the real use of the Python, how much Snowpark has grown as a way to support data science. >> Great. Tony. >> Actually of all things. And certainly, I'll also be looking for similar things in what Doug is saying, but I think sort of like, kind of out of left field, I'm interested to see what MongoDB is going to start to say about operational analytics, 'cause I mean, they're into this conquer the world strategy. We can be all things to all people. Okay, if that's the case, what's going to be a case with basically, putting in some inline analytics, what are you going to be doing with your query engine? So that's actually kind of an interesting thing we're looking for next week. >> Great. Sanjeev. >> So I'll be at MongoDB world, Snowflake and Databricks and very interested in seeing, but since Tony brought up MongoDB, I see that even the databases are shifting tremendously. They are addressing both the hashtag use case online, transactional and analytical. I'm also seeing that these databases started in, let's say in case of MySQL HeatWave, as relational or in MongoDB as document, but now they've added graph, they've added time series, they've added geospatial and they just keep adding more and more data structures and really making these databases multifunctional. So very interesting. >> It gets back to our discussion of best of breed, versus all in one. And it's likely Mongo's path or part of their strategy of course, is through developers. They're very developer focused. So we'll be looking for that. And guys, I'll be there as well. I'm hoping that we maybe have some extra time on theCUBE, so please stop by and we can maybe chat a little bit. Guys as always, fantastic. Thank you so much, Doug, Tony, Sanjeev, and let's do this again. >> It's been a pleasure. >> All right and thank you for watching. This is Dave Vellante for theCUBE and the excellent analyst. We'll see you next time. (upbeat music)

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

welcome back to the cube's presentation of the aws executive summit at re invent 2021 made possible by accenture my name is dave vellante we're going to look at how digital infrastructure is helping to transform consumer experiences specifically how an insurance company is changing its industry by incentivizing and rewarding consumers who change their behavior to live healthier lives a real passion of of mine and getting to the really root cause of health with me now are simon guest who's the chief executive officer of generality vitality gmbh and niels mueller who's the managing director at the cloud first application engineering lead for the european market at accenture gentlemen welcome to the cube thanks for having us you're very welcome simon generally vitality it's a really interesting concept that you guys have envisioned and now put into practice tell us how does it all work sure no problem and thanks for for having us on dave it's a pleasure to be here so look uh generally vitality is in its uh it's core pretty simple concepts so it's uh it's a program that you have on your phone and the idea of this program is that it's a it's a wellness coach for you as an individual and it's going to help you to understand your health and where you are in terms of the state of your health at the moment and it's going to take you on a journey to improve your your lifestyle and your wellness and hopefully help you to lead a healthier and a more sort of mindful life i guess is is the best way of summarizing it from um from our point of view with insurance company of course you know our historical role has always been to uh be the company that's there if something goes wrong you know so if unfortunately you pass away or you have sickness in your in your life or in your family's life that's that's historically been our role but what we see with generality vitality is something a little bit different so it's a program that really is uh supposed to be with you every day of your life to help you to live a healthier life it's something that we already have in in four european markets in fact in five from this week i'm a little bit behind the time so we're live already in in germany in france in austria and italy and in spain and fundamentally what we what we do dave is too is to say to customers look if you want to understand your health if you want to improve it by moving a little bit more by visiting the doctor more by eating healthier by healthy choices on a daily basis we're going to help you to do that and we're going to incentivize you for going on this journey and making healthy choices and we're going to reward you for for doing the same so you know we partner up with with great companies like garmin like adidas like big brands that are let's say invested in this health and wellness space so that we can produce really an ecosystem for customers that's all about live well make good choices be healthy have an insurance company that partners you along that journey and if you do that we're going to reward you for for that so you know we're here not just in the difficult times which of course is one of our main roles but we're here as a partner as a lifetime partner to you too to help you feel better and live a better life i love it i mean it sounds so simple but but it's i'm sure it's very complicated to to make the technology simple for the user you've got mobile involved you've got the back end and we're going to get into some of the tech but first i want to understand the member engagement and some of the lifestyle changes simon that you've analyzed what's the feedback that you're getting from your customers what does the data tell you how do the incentives work as well what what is the incentive for the the member to actually do the right thing sure look i think actually the the covered uh situation that we've had in the last sort of two years has really crystallized the fact that this is something that we really ought to be doing and something that our customers really value so i mean look just to give you a bit of a sort of information about how it works for for customers so what we try to do with them is is to get customers to understand uh their current health situation you know using their phone so uh you know we ask our customers to go through a sort of health assessment around how they live what they eat how they sleep you know and to go through that sort of process uh and to give them what a vitality age which is a sort of uh you know sort of actuarial comparison with their real age so i'm i'm 45 but unfortunately my my vitality age is 49 and it means i have some work to do to bring that back together uh and what we see is that you know two-thirds of our customers take this test every year because they want to see how they are progressing on an annual basis in terms of living a healthier life and if what if what they are doing is having an impact on their life expectancy and their lifespan and their health span so how long are they going to live healthier for so you see them really engaging in this in this approach of understanding their current situation then what we know actually because the program is built around this model that uh really activity and moving and exercise is the biggest contributor to living a healthier life we know that the majority of deaths are caused by lifestyle illness is like you know poor nutrition and smoking and drinking alcohol and not exercising and so a lot of the program is really built around getting people to move more and it's not about being an athlete it's about you know getting off the the underground one station earlier walking home or making sure you do your 10 000 steps a day and what we see is that that sort of 40 of our customers are on a regularly basis linking either their phone or their their exercise device to our program and downloading that data so that they can see how how much they are exercising and at the same time what we do is we set we set our customers weekly challenges to say look if you can move a little bit more than last week we are going to to reward you for that and we see that you know almost half of our customers are achieving this weekly goal every week and it's really a fantastic level of engagement that normally is an insurer uh we don't see the way the rewards work is is pretty simple it's similar in a way to an airline program so every good choice you make every activity you do every piece of good food that you eat when you check your on your health situation we'll give you points and the more points you get you go through through a sort of status approach of starting off at the bottom status and ending up at a gold and then a platinum status and the the higher up you get in the status that the higher the value of the rewards that we give you so almost a quarter of our customers now and this is accelerated through provide they've reached that platinum status so they are the most engaged customers that we we have and those ones who are really engaging in the in the program and what we really try to create is this sort of virtuous circle that says if you live well you make good choices you improve your health you you progress through the program and we give you better and stronger and more uh valuable rewards for for doing that and some of those rewards are are around health and wellness so it might be that you get you get a discount on on gym gear from adidas it might be that you get a discount on a uh on a device from garmin or it might be actually on other things so we also give people amazon vouchers we also give people uh discounts on holidays and another thing that we we did actually in the last year which we found really powerful is that we've given the opportunity for our customers to convert those rewards into charitable donations because we we work in generality with a with a sort of um campaign called the human safety net which is helping out the poorest people in society and some what our customers do a lot of the time is instead of taking those financial rewards for themselves they convert it into a charitable donation so we're actually also thinking wellness and feeling good and insurance and some societal good so we're really trying to create a virtuous circle of uh of engagement with our customers i mean that's a powerful cocktail i love it you got the the data because if i see the data then i can change my behavior you got the gamification piece you actually have you know hard dollar rewards you could give those to charities and and you've got the the most important which is priceless can't put a value on good health i got one more question for simon and niels i'd love you to chime in as well on this question how did you guys decide simon to engage with accenture and aws and the cloud to build out this platform what's the story behind that collaboration was there unique value that you saw that that you wanted to tap that you feel like they bring to the table what was your experience yeah look i mean we worked at accenture as well because the the the sort of construct of this vitality proposition is a pretty a pretty complex one so you mentioned that the idea is simple but the the build is not so uh is not so simple and that that's the case so accenture's been part of that journey uh from the beginning they're one of the partners that we work with but specifically around the topic of rewards uh you know we're we're a primarily european focused organization but when you take those countries that i mentioned even though we're next to each other geographically we're quite diverse and what we wanted to create was really a sustainable and reusable and consistent customer experience that allowed us to go and get to market with an increasing amount of efficiency and and to do that we needed to work with somebody who understood our business has this historical let's say investment in in the vitality concept so so knows how to bring it to life but that what then could really support us in making uh what can be a complex piece of work as simple and as as replicable as possible across multiple markets because we don't want to go reinventing the wheel every time we do we move to a new market so we need to find a balance between having a consistent product a consistent technology offer a consistent customer experience with the fact that we we operate in quite diverse markets so this was let's say the the reason for more deeply engaging with accenture on this journey thank you very much niels why don't you comment on on that as well i'd love to to get your thoughts and and really really it's kind of your role here i mean accenture global si deep expertise in industry but also technology what are your thoughts on this topic yeah i'd love to love to comment so when we started the journey it was pretty clear from the outset that we would need to build this on cloud in order to get this scalability and this ability to roll out to different markets have a central solution that can act as a template for the different markets but then also have the opportunity to localize different languages different partners for the rewards there's different reward partners in the different markets so we needed to build in an asset basically that could work as a tempos centrally standardizing things but also leaving enough flexibility to to then localize in the individual markets and if we talk about some of the more specific requirements so one one thing that gave us headaches in the beginning was the authentication of the users because each of the markets has their own systems of record where the basically the authentication needs to happen and we somehow needed to still find a holistic solution that comes through the central platform and we were able to do that at the end through the aws cognito service sort of wrapping the individual markets uh local idp systems and by now we've even extended that solution to have a standalone cloud native kind of idp solution in place for markets that do not have a local idp solution in place or don't want to use it for for this purpose yeah so you had you had data you have you had the integration you've got local laws you mentioned the flexibility you're building ecosystems that are unique to the to the local uh both language and and cultures uh please you had another comment i interrupted you yeah i know i just wanted to expand basically on the on the requirements so that was the central one being able to roll this out in a standardized way across the markets but then there were further requirements for example like being able to operate that platform with very low operations overhead there is no large i.t team behind generally vitality that you know works to serve us or can can act as this itis backbone support so we needed to have basically a solution that runs itself that runs on autopilot and that was another big big driver for first of all going to cloud but second of all making specific choices within cloud so we specifically chose to build this as a cloud native solution using for example manage database services you know with automatic backup with automatic ability to restore data that scales automatically that you know has all this built in which usually maybe a database administrator would take care of and we applied that concept basically to every component to everything we looked at we we applied this requirement of how can this run on autopilot how can we make this as much managed by itself within the cloud as possible and then land it on these services and for example we also used the the api gateway from from aws for our api services that also came in handy when for example we had some response time issues with the third party we needed to call and then we could just with a flick of a button basically introduce caching on the level of the api gateway and really improve the user experience because the data you know wasn't updated so much so it was easier to cache so these are all experiences i think that that proved in the end that we made the right choices here and the requirements that that drove that to to have a good user experience niels would you say that the architecture is is a sort of a data architecture specifically is it a decentralized data architecture with sort of federated you know centralized governance or is it more of a centralized view what if you could talk about that yeah it's it's actually a centralized platform basically so the core product is the same for all the markets and we run them as different tenants basically on top of that infrastructure so the data is separated in a way obviously by the different tenants but it's in a central place and we can analyze it in a central fashion if if the need arises from from the business and the reason i ask that simon is because essentially i look at this as a as largely a data offering for your customers and so niels you were talking about the local language and simon as well i would imagine that that the local business lines have specific requirements and specific data requirements and so you've got to build an architecture that is flexible enough to meet those needs yet at the same time can ensure data quality and governance and security that's not a trivial challenge i wonder if you both could comment on that yeah maybe maybe i'll give a start and then simon can chime in so um what we're specifically doing is managing the rewards experience right so so our solution will take care of tracking what rewards have been earned for what customer what rewards have been redeemed what rewards can be unlocked on the next level and we we foreshadow a little bit to to motivate to incentivize the customer and as that data sits in an aws database in a tenant by tenant fashion and you can run analysis on top of that maybe what you're getting into is also the let's say the exercise data the fitness device tracking data that is not specifically part of what my team has built but i'm sure simon can comment a little bit on that angle as well yeah please yeah sure sure yeah sure so look i think them the topic of data and how we use it uh in our business is a very is very interesting one because it's um it's not historically being seen let's say as the remit of insurers to go beyond the you know the the data that you need to underwrite policies or process claims or whatever it might be but actually we see that this is a whole point around being able to create some shared value in in this kind of product and and what i mean by that is uh look if you are a customer and you're buying an insurance policy it might be a life insurance or health insurance policy from from generali and we are giving you access to this uh to this program and through that program you are living a healthier life and that might have a you know a positive impact on generali in terms of you know maybe we're going to increase our market share or maybe we're going to lower claims or we're going to generate value out of that then one of the points of this program is that we then share that value back with customers through the rewards on the platform that we that we've built here and of course being able to understand that data and to quantify it and to value that data is an important part of the of the the different stages of how you of how much value you are creating and it's also interesting to know that you know in a couple of our markets we we operate in the corporate space so not with retail customers but with with organizations and one of the reasons that those companies give vitality to their employees is that they want to see things like the improved health of a workforce they want to see higher presenteeism lower absenteeism of employees and of course being able to demonstrate that there's a sort of correlation between participation in the vitality program and things like that is also is also important and as we've said the markets are very different so we need to be able to to take the data uh that we have out of the vitality program uh and be able in in the company that that i'm managing to to interpret that data so that in our insurance businesses we are able to make good decisions about the kind of insurance products we i think what's interesting to uh to make clear is that actually that the kind of health data that we generate stays purely within the vitality business itself and what we do inside the vitality business is to analyze that data and say okay is this is this also helping our insurance businesses to to drive uh yeah you know better top line and bottom line in the in the relevant business lines and this is different per company and per mark so yeah being able to interrogate that data understand it apply it in different markets and different uh distribution systems and different kinds of approaches to insurance is an is an important one yes it's an excellent example of a digital business in in you know we talk about digital transformation what does that mean this is what it means i i'd love i mean it must be really interesting board discussions because you're transforming an industry you're lowering overall cost i mean if people are getting less sick that's more profit for your company and you can choose to invest that in new products you can give back some to your corporate clients you can play that balancing act you can gain market share and and you've got some knobs to turn some levers uh for your stakeholders which is which is awesome neil something that i'm interested in i mean it must have been really important for you to figure out how to determine and measure success i mean you're obviously removed it's up it's up to generality vitality to get adoption for for their customers but at the same time the efficacy of your solution is going to determine you know the ease of of of delivery and consumption so so how did you map to the specific goals what were some of the key kpis in terms of mapping to their you know aggressive goals besides the things we already touched on i think one thing i would mention is the timeline right so we we started the team ramping in january or february and then within six months basically we had the solution built and then we went through a extensive test phase and within the next six months we had the product rolled out to three markets so this speed to value speed to market that we were able to achieve i think is one of the key um key criteria that also simon and team gave to us right there was a timeline and that timeline was not going to move so we needed to make a plan adjust to that timeline and i think it's both a testament to to the team's work that they did that we made this timeline but it also is enabled by technologies like cloud i have to say if i go back five years ten years if if you had to build in a solution like this on a corporate data center across so many different markets and each managed locally there would have been no way to do this in 12 months right that's for sure yeah i mean simon you're a technology company i mean insurance has always been a tech heavy company but but as niels just mentioned if you had to do that with it departments in each region so my question is is now you've got this it's almost like non-recurring engineering costs you've got that it took one year to actually get the first one done how fast are you able to launch into new markets just from a technology perspective not withstanding any you know local regulations and figuring out to go to market is that compressed yeah so if you are specifically technology-wise i think we would be able to set up a new market including localizations that often involves translation of because in europe you have all the different languages and so on at i would say four to six weeks we probably could stand up a localized solution in reality it takes more like six to nine months to get it rolled out because there's many other things involved obviously but just our piece of the solution we can pretty quickly localize it to a new market but but simon that means that you can spend time on those other factors you don't have to really worry so much about the technology and so you've launched in multiple european markets what do you see for the future of this program come to america you know you can fight you can find that this program in america dave but with one of our competitors we're not we're not operating so much in uh but you can find it if you want to become a customer for sure but yes you're right so look i think from from our perspective uh you know to put this kind of business into a new market it's not it's not an easy thing because what we're doing is not offering it just as a as a service on a standalone basis to customers we want to link it with with insurance business in the end we are an insurance business and we want to to see the value that comes from that so there's you know there's a lot of effort that has to go into making sure that we land it in the right way also from a customer publishing point of view with our distribution and they are they are quite different so so yeah look coming to the question of what's next i mean it comes in three stages for me so as i mentioned we are uh in five markets already uh in next in the first half of 2022 we'll also come to to the czech republic and poland uh which we're excited to to do and that will that will basically mean that we we have this business in in the seven main uh general markets in europe related to life and health business which is the most natural uh let's say fit for something like vitality then you know the next the sort of second part of that is to say okay look we have a program that's very heavily focused around uh activity and rewards and that that's a good place to start but you know wellness these days is not just about you know can you move a bit more than you did historically it's also about mental well-being it's about sleeping good it's about mindfulness it's about being able to have a more holistic approach to well-being and and covert has taught us and customer feedback has taught us actually that this is something where we need to to go and here we need to have the technology to move there as well so to be able to work with partners that are not just based on on on physical activity but also also on mindfulness so this is how one other way we'll develop the proposition and i think the third one which is more strategic and and we are you know really looking into is there's clearly something in the whole uh perception of incentives and rewards which drives a level of engagement between an insurer like generali and its customers that it hasn't had historically so i think we need to learn you know forget you know forgetting about the specific one of vitality being a wellness program but if there's an insurer there's a role for us to play where we offer incentives to customers to do something in a specific way and reward them for doing that and it creates value for us as an insurer then then this is probably you know a place we want to investigate more and to be able to do that in in other areas means we need to have the technology available that is as i said before replicable faster market can adapt quickly to to other ideas that we have so we can go and test those in in different markets so yes we have to we have to complete our scope on vitality we have to get that to scale and be able to manage all of this data at scale all of those rewards at real scale and uh to have the technology that allows us to do that without without thinking about it too much and then to say okay how do we widen the proposition and how do we take the concept of vitality that sits behind vitality to see if we can apply it to other areas of our business and that's really what the future is is going to look like for us you know the the isolation era really taught us that if you're not a digital business you're out of business and pre-kov a lot of these stories were kind of buried uh but the companies that have invested in digital are now thriving and this is an awesome example jeff another point is that jeff amebacher one of the founders of cloudera early facebook employee famously said about 10 12 years ago the best and greatest engineering minds of our my generation are trying to figure out how to get people to click on ads and this is a wonderful example of how to use data to change people's lives so guys congratulations best of luck really awesome example of applying technology to create an important societal outcome really appreciate you your time on the cube thank you thanks bye-bye all right and thanks for watching this segment of thecube's presentation of the aws executive summit at reinvent 2021 made possible by accenture keep it right there for more deep dives [Music] you

>> Welcome back to The Cube's coverage of HPE's GreenLake announcements. My name is Dave Vellante and you're watching the Cube. I'm here with Holger Mueller, who is an analyst at Constellation Research. And Matt Maccaux is the global field CTO of Ezmeral software at HPE. We're going to talk data. Gents, great to see you. >> Holger: Great to be here. >> So, Holger, what do you see happening in the data market? Obviously data's hot, you know, digital, I call it the force marks to digital. Everybody realizes wow, digital business, that's a data business. We've got to get our data act together. What do you see in the market is the big trends, the big waves? >> We are all young enough or old enough to remember when people were saying data is the new oil, right? Nothing has changed, right? Data is the key ingredient, which matters to enterprise, which they have to store, which they have to enrich, which they have to use for their decision-making. It's the foundation of everything. If you want to go into machine learning or (indistinct) It's growing very fast, right? We have the capability now to look at all the data in enterprise, which weren't able 10 years ago to do that. So data is main center to everything. >> Yeah, it's even more valuable than oil, I think, right? 'Cause with oil, you can only use once. Data, you can, it's kind of polyglot. I can go in different directions and it's amazing, right? >> It's the beauty of digital products, right? They don't get consumed, right? They don't get fired up, right? And no carbon footprint, right? "Oh wait, wait, we have to think about carbon footprint." Different story, right? So to get to the data, you have to spend some energy. >> So it's that simple, right? I mean, it really is. Data is fundamental. It's got to be at the core. And so Matt, what are you guys announcing today, and how does that play into what Holger just said? >> What we're announcing today is that organizations no longer need to make a difficult choice. Prior to today, organizations were thinking if I'm going to do advanced machine learning and really exploit my data, I have to go to the cloud. But all my data's still on premises because of privacy rules, industry rules. And so what we're announcing today, through GreenLake Services, is a cloud services way to deliver that same cloud-based analytical capability. Machine learning, data engineering, through hybrid analytics. It's a unified platform to tie together everything from data engineering to advance data science. And we're also announcing the world's first Kubernetes native object store, that is hybrid cloud enabled. Which means you can keep your data connected across clouds in a data fabric, or Dave, as you say, mesh. >> Okay, can we dig into that a little bit? So, you're essentially saying that, so you're going to have data in both places, right? Public cloud, edge, on-prem, and you're saying, HPE is announcing a capability to connect them, I think you used the term fabric. I'm cool, by the way, with the term fabric, we can, we'll parse that out another time. >> I love for you to discuss textiles. Fabrics vs. mesh. For me, every fabric breaks down to mesh if you put it on a microscope. It's the same thing. >> Oh wow, now that's really, that's too detailed for my brain, right this moment. But, you're saying you can connect all those different estates because data by its very nature is everywhere. You're going to unify that, and what, that can manage that through sort of a single view? >> That's right. So, the management is centralized. We need to be able to know where our data is being provisioned. But again, we don't want organizations to feel like they have to make the trade off. If they want to use cloud surface A in Azure, and cloud surface B in GCP, why not connect them together? Why not allow the data to remain in sync or not, through a distributed fabric? Because we use that term fabric over and over again. But the idea is let the data be where it most naturally makes sense, and exploit it. Monetization is an old tool, but exploit it in a way that works best for your users and applications. >> In sync or not, that's interesting. So it's my choice? >> That's right. Because the back of an automobile could be a teeny tiny, small edge location. It's not always going to be in sync until it connects back up with a training facility. But we still need to be able to manage that. And maybe that data gets persisted to a core data center. Maybe it gets pushed to the cloud, but we still need to know where that data is, where it came from, its lineage, what quality it has, what security we're going to wrap around that, that all should be part of this fabric. >> Okay. So, you've got essentially a governance model, at least maybe you're working toward that, and maybe it's not all baked today, but that's the north star. Is this fabric connect, single management view, governed in a federated fashion? >> Right. And it's available through the most common API's that these applications are already written in. So, everybody today's talking S3. I've got to get all of my data, I need to put it into an object store, it needs to be S3 compatible. So, we are extending this capability to be S3 native. But it's optimized for performance. Today, when you put data in an object store, it's kind of one size fits all. Well, we know for those streaming analytical capabilities, those high performance workloads, it needs to be tuned for that. So, how about I give you a very small object on the very fastest disk in your data center and maybe that cheaper location somewhere else. And so we're giving you that balance as part of the overall management estate. >> Holger, what's your take on this? I mean, Frank Slootman says we'll never, we're not going halfway house. We're never going to do on-prem, we're only in the cloud. So that basically says, okay, he's ignoring a pretty large market by choice. You're not, Matt, you must love those words. But what do you see as the public cloud players, kind of the moves on-prem, particularly in this realm? >> Well, we've seen lots of cloud players who were only cloud coming back towards on-premise, right? We call it the next generation compute platform where I can move data and workloads between on-premise and ideally, multiple clouds, right? Because I don't want to be logged into public cloud vendors. And we see two trends, right? One trend is the traditional hardware supplier of on-premise has not scaled to cloud technology in terms of big data analytics. They just missed the boat for that in the past, this is changing. You guys are a traditional player and changing this, so congratulations. The other thing, is there's been no innovation for the on-premise tech stack, right? The only technology stack to run modern application has been invested for a long time in the cloud. So what we see since two, three years, right? With the first one being Google with Kubernetes, that are good at GKE on-premise, then onto us, right? Bringing their tech stack with compromises to on-premises, right? Acknowledging exactly what we're talking about, the data is everywhere, data is important. Data gravity is there, right? It's just the network's fault, where the networks are too slow, right? If you could just move everything anywhere we want like juggling two balls, then we'd be in different place. But that's the not enough investment for the traditional IT players for that stack, and the modern stack being there. And now every public cloud player has an on-premise offering with different flavors, different capabilities. >> I want to give you guys Dave's story of kind of history and you can kind of course correct, and tell me how this, Matt, maybe fits into what's happened with customers. So, you know, before Hadoop, obviously you had to buy a big Oracle database and you know, you running Unix, and you buy some big storage subsystem if you had any money left over, you know, you maybe, you know, do some actual analytics. But then Hadoop comes in, lowers the cost, and then S3 kneecaps the entire Hadoop market, right? >> I wouldn't say that, I wouldn't agree. Sorry to jump on your history. Because the fascinating thing, what Hadoop brought to the enterprise for the first time, you're absolutely right, affordable, right, to do that. But it's not only about affordability because S3 as the affordability. The big thing is you can store information without knowing how to analyze it, right? So, you mentioned Snowflake, right? Before, it was like an Oracle database. It was Starschema for data warehouse, and so on. You had to make decisions how to store that data because compute capabilities, storage capabilities, were too limited, right? That's what Hadoop blew away. >> I agree, no schema on, right. But then that created data lakes, which create a data swamps, and that whole mess, and then Spark comes in and help clean it out, okay, fine. So, we're cool with that. But the early days of Hadoop, you had, companies would have a Hadoop monolith, they probably had their data catalog in Excel or Google sheets, right? And so now, my question to you, Matt, is there's a lot of customers that are still in that world. What do they do? They got an option to go to the cloud. I'm hearing that you're giving them another option? >> That's right. So we know that data is going to move to the cloud, as I mentioned. So let's keep that data in sync, and governed, and secured, like you expect. But for the data that can't move, let's bring those cloud native services to your data center. And so that's a big part of this announcement is this unified analytics. So that you can continue to run the tools that you want to today while bringing those next generation tools based on Apache Spark, using libraries like Delta Lake so you can go anything from Tableaux through Presto sequel, to advance machine learning in your Jupiter notebooks on-premises where you know your data is secured. And if it happens to sit in existing Hadoop data lake, that's fine too. We don't want our customers to have to make that trade off as they go from one to the other. Let's give you the best of both worlds, or as they say, you can eat your cake and have it too. >> Okay, so. Now let's talk about sort of developers on-prem, right? They've been kind of... If they really wanted to go cloud native, they had to go to the cloud. Do you feel like this changes the game? Do on-prem developers, do they want that capability? Will they lean into that capability? Or will they say no, no, the cloud is cool. What's your take? >> I love developers, right? But it's about who makes the decision, who pays the developers, right? So the CXOs in the enterprises, they need exactly, this is why we call the next-gen computing platform, that you can move your code assets. It's very hard to build software, so it's very valuable to an enterprise. I don't want to have limited to one single location or certain computing infrastructure, right? Luckily, we have Kubernetes to be able to move that, but I want to be able to deploy it on-premise if I have to. I want to deploy it, would be able to deploy in the multiple clouds which are available. And that's the key part. And that makes developers happy too, because the code you write has got to run multiple places. So you can build more code, better code, instead of building the same thing multiple places, because a little compiler change here, a little compiler change there. Nobody wants to do portability testing and rewriting, recertified for certain platforms. >> The head of application development or application architecture and the business are ultimately going to dictate that, number one. Number two, you're saying that developers shouldn't care because it can write once, run anywhere. >> That is the promise, and that's the interesting thing which is available now, 'cause people know, thanks to Kubernetes as a container platform and the abstraction which containers provide, and that makes everybody's life easier. But it goes much more higher than the Head of Apps, right? This is the digital transformation strategy, the next generation application the company has to build as a response to a pandemic, as a pivot, as digital transformation, as digital disruption capability. >> I mean, I see a lot of organizations basically modernizing by building some kind of abstraction to their backend systems, modernizing it through cloud native, and then saying, hey, as you were saying Holger, run it anywhere you want, or connect to those cloud apps, or connect across clouds, connect to other on-prem apps, and eventually out to the edge. Is that what you see? >> It's so much easier said than done though. Organizations have struggled so much with this, especially as we start talking about those data intensive app and workloads. Kubernetes and Hadoop? Up until now, organizations haven't been able to deploy those services. So, what we're offering as part of these GreenLake unified analytics services, a Kubernetes runtime. It's not ours. It's top of branch open source. And open source operators like Apache Spark, bringing in Delta Lake libraries, so that if your developer does want to use cloud native tools to build those next generation advanced analytics applications, but prod is still on-premises, they should just be able to pick that code up, and because we are deploying 100% open-source frameworks, the code should run as is. >> So, it seems like the strategy is to basically build, now that's what GreenLake is, right? It's a cloud. It's like, hey, here's your options, use whatever you want. >> Well, and it's your cloud. That's, what's so important about GreenLake, is it's your cloud, in your data center or co-lo, with your data, your tools, and your code. And again, we know that organizations are going to go to a multi or hybrid cloud location and through our management capabilities, we can reach out if you don't want us to control those, not necessarily, that's okay, but we should at least be able to monitor and audit the data that sits in those other locations, the applications that are running, maybe I register your GKE cluster. I don't manage it, but at least through a central pane of glass, I can tell the Head of Applications, what that person's utilization is across these environments. >> You know, and you said something, Matt, that struck, resonated with me, which is this is not trivial. I mean, not as simple to do. I mean what you see, you see a lot of customers or companies, what they're doing, vendors, they'll wrap their stack in Kubernetes, shove it in the cloud, it's essentially hosted stack, right? And, you're kind of taking a different approach. You're saying, hey, we're essentially building a cloud that's going to connect all these estates. And the key is you're going to have to keep, and you are, I think that's probably part of the reason why we're here, announcing stuff very quickly. A lot of innovation has to come out to satisfy that demand that you're essentially talking about. >> Because we've oversimplified things with containers, right? Because containers don't have what matters for data, and what matters for enterprise, which is persistence, right? I have to be able to turn my systems down, or I don't know when I'm going to use that data, but it has to stay there. And that's not solved in the container world by itself. And that's what's coming now, the heavy lifting is done by people like HPE, to provide that persistence of the data across the different deployment platforms. And then, there's just a need to modernize my on-premise platforms. Right? I can't run on a server which is two, three years old, right? It's no longer safe, it doesn't have trusted identity, all the good stuff that you need these days, right? It cannot be operated remotely, or whatever happens there, where there's two, three years, is long enough for a server to have run their course, right? >> Well you're a software guy, you hate hardware anyway, so just abstract that hardware complexity away from you. >> Hardware is the necessary evil, right? It's like TSA. I want to go somewhere, but I have to go through TSA. >> But that's a key point, let me buy a service, if I need compute, give it to me. And if I don't, I don't want to hear about it, right? And that's kind of the direction that you're headed. >> That's right. >> Holger: That's what you're offering. >> That's right, and specifically the services. So GreenLake's been offering infrastructure, virtual machines, IaaS, as a service. And we want to stop talking about that underlying capability because it's a dial tone now. What organizations and these developers want is the service. Give me a service or a function, like I get in the cloud, but I need to get going today. I need it within my security parameters, access to my data, my tools, so I can get going as quickly as possible. And then beyond that, we're going to give you that cloud billing practices. Because, just because you're deploying a cloud native service, if you're still still being deployed via CapEx, you're not solving a lot of problems. So we also need to have that cloud billing model. >> Great. Well Holger, we'll give you the last word, bring us home. >> It's very interesting to have the cloud qualities of subscription-based pricing maintained by HPE as the cloud vendor from somewhere else. And that gives you that flexibility. And that's very important because data is essential to enterprise processes. And there's three reasons why data doesn't go to the cloud, right? We know that. It's privacy residency requirement, there is no cloud infrastructure in the country. It's performance, because network latency plays a role, right? Especially for critical appraisal. And then there's not invented here, right? Remember Charles Phillips saying how old the CIO is? I know if they're going to go to the cloud or not, right? So, it was not invented here. These are the things which keep data on-premise. You know that load, and HP is coming on with a very interesting offering. >> It's physics, it's laws, it's politics, and sometimes it's cost, right? Sometimes it's too expensive to move and migrate. Guys, thanks so much. Great to see you both. >> Matt: Dave, it's always a pleasure. All right, and thank you for watching the Cubes continuous coverage of HPE's big GreenLake announcements. Keep it right there for more great content. (calm music begins)