>> Narrator: Live from Santa Clara, California, it's The Cube. Covering Open Networking Summit 2017. Brought you to by the Linux Foundation. >> Hey, welcome back everybody. Jeff Frick here with The Cube, along with Scott Raynovich. We're at the Open Networking Summit 2017. Linux Foundation has taken over this show a couple years ago, it's a lot of excitement. A lot of people would say that the networking was kind of the last piece of the puzzle to get software defined, to get open. We're really excited to kick off the show with a really great representative of SDN and everything that it represents. Martin Casado, now with Andreessen Horowitz, Martin, great to see you. >> Hey, I'm super happy to be here. >> So, coming off your keynote, you said it was ten years ago almost to the day that you guys started the adventure called Nicira, which kind of put us where we are now. >> You know, you and I are growing old together here. It has been a decade. I've actually been on The Cube throughout, so I'm very happy to be here. Thanks so much for the intro. >> Absolutely. So, what were your takeaways, Scott, on that keynote? >> It was great, we had some great stuff this morning. Not only was Martin giving the history of Nicira and the origins of SDN and talking about how you made it successful after all these challenges but we also had AT&T unveiling a new incredible white box program, where they're running open networking on their entire network now, so, it was kind of a, I thought, a big day in general to show how far we've gone, right? And you talked a little about that. >> Yeah, listen having come over here since the inception of ONS, what strikes me is, it originally, it was so speculative, it was kind of like wouldn't it be nice and you had all these dreamers. It was largely academics or people from the CTO's office and if you compare those first meetings to now, we're in the industry proper now, right? If you come and you look around, there's huge representation from Telcos, from vendors, from customers, and academics. So, I think we've seen a massive maturation in general. >> I just think I could make a mash-up of all the times we've had you on the Cube table where it's coming! We're almost here! >> Martin: And we're like it's here! >> It's here! But now John Donovan said that their goal, I don't know if it's in the short term or the very near term, is to be over 50 percent software defined, so I guess that's a pretty good definition of being here. >> Yeah, I think so. I think that we're seeing, and I think that the AT&T talk was fantastic, but I think you're seeing this across the industry, which is large customers that have been traditionally conservative, have these targets, and they're actually implementing. I mean, it's one thing to have something on the roadmap. And it's one thing to have something planned. It's another thing to actually start seeing it roll out. >> Jeff: Right. >> Again, this is a process. A lot of my talk was like, how long does it take for an industry to mature? But now, there's many things you can point to that are very real, and I think that was one great example of it. >> Well, the other thing I thought was great in your talk is you mapped out the 10 year journey and you said it so discounts often the hardest part which is changing behavior of the market. That is much harder than the technology and some of the other pieces. >> Right, exactly. So, take this from a technologist standpoint. I basically made a career on making fun of hardware. I'm like, software is so much faster than hardware, and hardware is so slow. But now if I stand back and take a long view, yeah, fine hardware's slower than software, but it's nothing compared to changing organizational behavior or consumer behavior and so, for me it was actually pretty humbling going through this last decade, because you realize that even if you have product market fit, and even if you have a good technical solution, there is a natural law of market physics that you have to overcome a moment of inertia that takes probably a decade, certainly five or six years. >> And that's before things like vendor viability, when you're trying to enter the enterprise space, or legacy infrastructure which is just not getting ripped out, you know? So many hurdles. >> Strictly consumer behavior, right? Consumers are used to doing one thing. I always talk to new entrepreneurs and I say the following: You have two jobs as an entrepreneur. Job number one is you identify a constituency. That constituency wakes up, they think about everything in the world, but they don't think about your thing, so job number one is to get them to think about your thing. That's difficult. It's like Inception. It's like Leonardo DiCaprio Inception. You're putting an idea in somebody's head and then the second thing that you have to do is you have to attach a value to that. So, just because they have the idea doesn't mean that they actually value it. So, you actually have to say, listen, this is worth X amount of dollars. And it turns out that this takes a long time and that's why market category creation is such an effort. That's why it's so neat, we're standing here and we're seeing that this has actually happened, which is fantastic. >> You talked about Nicira, which today, correct me if I'm wrong, it's still the biggest success story in SDN in terms of a startup, you know, 1.3 billion. You talked about different iterations, I think you said, six or seven product iterations and being frustrated at many levels. Did you ever sit there one day and think, "uh, we're going to fail." >> Martin: (laughs) >> Was failure a common- >> Oh man, I don't think there wasn't a quarter when we're like "we're dead." (laughs) By the way, that's every startup. I mean, I'm on- >> Scott: That's just normal, right? >> There's six or seven boards right now, I mean every startup has this oscillator. When we started at Nicira, it was in 2007. And in 2008, the nuclear winter set in, if you remember. The whole economy collapsed, and I think that alone could've killed us. So absolutely, and all startups who do that. But one thing that I never lost faith in was that the problem was real. I wasn't sure we had the right solution or the right approach, and we iterated on that, but I knew there was a real problem here. And when that is kind of a guiding star and a guiding light, we just kept going towards that. I think that's why ultimately we ended up solving the problem we set out to, it was just we took a very crooked path to get there. >> What was the feedback mechanism? Was it like just talking to as many customers as possible or? You talked about the market fit versus the industry fit, how did you gather that information? >> I think in core technical infrastructure, the strategic leaders of a startup have to be piped into the nervous system of both the technology trends and the product market fit. Technology trends because, technology trends provide the momentum for what's going to get adopted and what it looks like. And the product market fit is what is the customer problems that need to be solved. And so I think it's really critical to be deeply into both of those things, which is why things like ONS are so important, because they do kind of find a convergence of both of that. What do customers need but also where's the technology going. >> And it's really neat, that's kind of like the platform versus the application. You're going down the new platform strategy, right? Which is the software-defined networking, but at the end of the day, people buy solutions to their problems that they need to get fixed today. No one's buying a new platform today. >> Yeah, so there's two issues, you're right. There's the technical directions and then the specific applications for that, and one thing I talked about and I really believe is we focus a little bit too much on the technology platform, how those are shifting, early on and less on what the customers need. I don't think you want to 100% flip that, you need to focus on both, but I think that they both should be even-handed. What do customers need and then what is the right technical approach to get there. >> And you also stuck on a couple of really interesting points about decisions. You're going to make a lot mistakes going down the road. But you said, you got to make two or three really good ones and that will make up for a whole lot of little missteps along the path. >> So in retrospect, and this was actually a big a-ha! for me and maybe it's obvious to other people, but this was a big a-ha! to me, even as I was putting together this talk. So, the way venture capital works is you make a lot of bets, but only one in ten will actually produce returns, so you're kind of swinging for the fences and almost all the returns comes from the Googles and the Facebooks and the Ubers and so forth. That's just how it is. Now, as a venture capitalist, you can have a portfolio, you can place ten of those bets in parallel. Going back through all of the slides and everything we've done, I hadn't realized before how similar doing a startup is, which is you make a lot of mistakes in startups, but a few key decisions really drive the strategy. Does that make sense? I always thought maybe you need to do 50/50, or maybe even 80/20, 80% correct and 20 wrong, but it's not that. There's a few key decisions that make it correct, and so the key is you're straddling these two pieces of human nature. On one side, you want to stick with something, you want to make sure that you're not sticking too long with something that isn't going to work, and then the other side you don't want to get rid of something before it's going to work. You want to be both honest with yourself when it's not working and you want to be patient. And if you do that long enough I think that you will find one of the critical decisions to drive the startup forward. >> Yeah, one interesting thing you said, you arrived at a conclusion that the products and individual applications were more important than the platform, and that kind of runs contrary to the meme that you have now where the Harvard Business Review is saying "build a platform, build the next Airbnb." And what you're saying is kind of contrary to that. >> Right, so I went into this with a path from Mindframe, if you look at our original slide deck, which I showed, it was a platform. Now, I think that there's two aspects for this, I think in SDN specifically, there is a reason technically why a platform doesn't work, and the reason for that is networking is about distributed state management, which is very specific to applications. So it's hard for a platform to register that, so technically, I think there's reason for that. From a startup perspective, customers don't buy platforms, customers buy products. I think if you focus on the product, you build a viable business, and then for stickiness you turn that into a platform. But most customers don't know what to do with a platform because that's still a value-add. Products before platforms, I think, is a pretty good adage to live by. >> But design your product with a platform point of view. That way so you can make that switch when that day comes and now you're just adding applications, applications. So, I want to shift gears a little bit just kind of about open source and ONS specifically. We hear time and time again about how open source is such an unbelievable driver of innovation. Think of how your story might have changed if there wasn't, and maybe there was, I wasn't there, something here and how does an open source foundation help drive the faster growth of this space? >> So, I actually think, and I'm probably in the minority of this, but I've always thought that open source does not tend to innovation. That's not like the value of open source is innovation. If you look at most successful open source projects, traditionally they've actually entered mature markets. Linux entered Unix, which is, so I'd say the innovation was Unix not Linux. I would say, Android went into Palm, and Blackberry, and iPhone. I would say MySQL went into Oracle. And so, I think the power and beauty of open source is more on the proliferation of technology and more on the customer adoption, and less on the innovation. But what it's doing is it's driving probably the biggest shift in buying that we've ever seen in IT. So, IT is a 4 trillion dollar market that's this massive market, and right now, in order to sell something, you pretty much have to make it open source or offer it as a service. And the people that buy open source, they do it very different than you traditionally do it. It allows them to get educated on it, it allows them to use it, they get a community as part of it. And that shift from a traditional direct vendor model to that model means a lot of new entrants can come in and offer new things. And so, I think it's very important to have open source, I think it's changing the way people buy things, I think building communities like this is a very critical thing to do, but I do think it's more about go-to-market and actually less about innovation. >> So what does it mean for all these proprietary networking vendors? I mean, are they dead now? >> No, here's actually another really interesting thing, which is I think customers these days like to buy things open source or as a service. Those are the two consumption models. Now, for shipping software, I think shipping closed source software, I think those days are over or they're coming to the end. Like, that's done. But, customers will view, whether it's on-prem or off-prem, an appliance as a service. So, let's say I create MartinHub. So, it's my online service, MartinHub, people like MartinHub. I can sell them that on-premise. Now, MartinHub could be totally closed source, right? Like, Amazon is totally closed source, right? But people still consume it. Because it's a service, they think it's open. And if they want something on-prem, I can deploy that and they still consume it as a service. So, I think the proprietary vendors need to move from shipping closed source software to offering a service, but I think that service can just be on-prem. And I think prem senior shift happens, so I don't think there's going to be like a massive changing of the guard. I do think we're going to see new entrants. I think we're going to see a shift in the market share, but this isn't like a thermonuclear detonation that's going to kill the dinosaurs. (laughs) >> I want to get your take, Martin, on the next big wave that we're seeing which is 5G, and really 5G as an enabler for IoT. So, you've been playing in this space for a while. As you see this next thing getting ready to crest, what are some of your thoughts, also sitting in a VC chair, you probably see all kinds of people looking to take advantage of this thing. >> That's funny. I'm actually going to answer a different question. (laughs) Which is, I-- >> Scott: That's cause 5G doesn't exist yet, right? >> No, I love the question, but it's like, this is really a space that's really near and dear to my heart, which is cellular. And I've actually started looking at it personally, and even in the United States alone, there are something like 20 million people that are under-connected. And I think the only practical way to connect them is to use cellular. And so I've been looking at this problem for about a year, I've actually created a non-profit in it that brings cellular connectivity to indigenous communities. Like, Native American tribes, and so forth. >> Jeff: As the ultimate last mile. >> As the ultimate last mile. Which is interesting, like 5G is fantastic, but if you look at the devices available to these people that have coverage, I think LTE is actually sufficient. So what I'm excited about, and I'm sorry about answering a different question, but it's such a critical point, what I'm excited about is, it used to be 150 thousand dollars to set up a cell tower. Using SDN, I can set up an LTE cell tower for about five thousand dollars and I can use existing fiber at schools as backhaul, so I think now we have these viable deployment models that are relatively cheap that we can actually connect the underprivileged with. And I don't think it's about the next new cellular technology, I think it's actually SDN's impact on the existing one. And that's an area of course that's very personal to me. >> All right, love it. It is as you said, it's repackaging stuff in a slightly different way leveraging the technology to do a new solution. >> And it's truly SDN. If you look at this, there's an LTE stack all in software running on proprietary hardware. I'm sorry, on general purpose hardware that's actually being controlled from Amazon. And again, a factor of ten reduction in the price to set up a cell tower. >> Jeff: Awesome. >> What about the opportunity with Internet of Things and connecting the things with networks' artificial intelligence? >> So, as a venture capitalist, when it comes to networking I'm interested in two areas. One area is networking moving from the machine connecting machines to connecting APIs. So, we're moving up a layer. So we've got microservices, now we need a network to connect those and there're different types of end points, and they require different types of connectivity. But I'm also interested in networks moving out. So, it used to be connecting a bunch of machines but now there's all these new problem domains, the Internet is moving out to interact with the physical world. It's driving cars. It's doing manufacturing, it's doing mining, it's doing forestry. As we reach out to these more mature industries, and different deployment environments, we have to rethink the type of networks to build. So, that's definitely an area that I'm looking at from the startup space. >> What kind of activity's there? I mean, you have guys coming in every day pitching new automated connect-the-car software. >> I think for me it's the most exciting time in IT, right? It's like, the last, say ten fifteen years of the Internet has been the World Wide Web. Which is kind of information processing, it's information in, information out. But because of recent advances in sensors due to the cellphone, the ubiquity of cellphones, the recent advances in AI, the recent advances in robotics, that Internet is now growing hands and eyes and ears. And it's manipulating the physical world. Any industry that's out there, whether it's driving, whether it's farming, is now being automated, so we see all the above. People are coming in, they're changing the way we eat food, they're changing the way we drive cars, they're changing the way we fly airplanes. So, it's almost like IT is the new control layer for the world. >> All right, Martin, thanks again for stopping by. Unfortunately we got to leave it there, we could go all day I'm sure. I'll come up with more good questions for you. >> All right, I really appreciate you taking the time. It's good to see both of you. Thanks very much. >> Absolutely, all right, he's Martin Casado from Andreessen Horowitz. I'm Jeff Frick, along with Scott Raynovich. You're watching The Cube from Open Networking Summit 2017. We'll be back after this short break. Thanks for watching. (mellow music) >> Announcer: Robert Herjavec. >> Man: People obviously know you from Shark Tank, but the Herjavec group has been really laser fo--

(upbeat music) >> You got it, it's theCUBE. We are in Vegas. This is the Cube's live coverage day one of the full event coverage of AWS reInvent '22 from the Venetian Expo Center. Lisa Martin here with Dave Vellante. We love being in Vegas, Dave. >> Well, you know, this is where Super Cloud sort of was born. >> It is. >> Last year, just about a year ago. Steve Mullaney, CEO of of Aviatrix, you know, kind of helped us think it through. And we got some fun stories around. It's happening, but... >> It is happening. We're going to be talking about Super Cloud guys. >> I guess I just did the intro, Steve Mullaney >> You did my intro, don't do it again. >> Sorry I stole that from you, yeah. >> Steve Mullaney, joined just once again, one of our alumni. Steve, great to have you back on the program. >> Thanks for having me back. >> Dave: It's happening. >> It is happening. >> Dave: We talked about a year ago. Net Studio was right there. >> That was two years. Was that year ago, that was a year ago. >> Dave: It was last year. >> Yeah, I leaned over >> What's happening? >> so it's happening. It's happening. You know what, the thing I noticed what's happening now is the maturity of the cloud, right? So, if you think about this whole journey to cloud that has been, what, AWS 12 years. But really over the last few years is when enterprises have really kind of joined that journey. And three or four years ago, and this is why I came out of retirement and went to Aviatrix, was they all said, okay, now we're going to do cloud. You fast forward now three, four years from now, all of a sudden those five-year plans of evacuating the data center, they got one year left, two year left, and they're going, oh crap, we don't have five years anymore. We're, now the maturity's starting to say, we're starting to put more apps into the cloud. We're starting to put business critical apps like SAP into the cloud. This is not just like the low-hanging fruit anymore. So what's happening now is the business criticality, the scale, the maturity. And they're all now starting to hit a lot of limits that have been put into the CSPs that you never used to hit when you didn't have business critical and you didn't have that scale. They were always there. The rocks were always there. Just it was, you never hit 'em. People are starting to hit 'em now. So what's happening now is people are realizing, and I'm going to jump the gun, you asked me for my bumper sticker. The bumper sticker for Aviatrix is, "Good enough is no longer good enough." Now it's funny, it came in a keynote today, but what we see from our customers is it's time to upgrade the native constructs of networking and network security to be enterprise-grade now. It's no longer good enough to just use the native constructs because of a lack of visibility, the lack of controls, the lack of troubleshooting capabilities, all these things. "I now need enterprise grade networking." >> Let me ask you a question 'cause you got a good historical perspective on the industry. When you think about when Maritz was running VMWare. He was like any app, he said basically we're building a software mainframe. And they kind of did that, right? But then they, you know, hit the issue with scale, right? And they can't replicate the cloud. Are there things that we can draw from that experience and apply that to the cloud? What's the same, what's different? >> Oh yeah. So, 1992, do you remember what happened in 1992? I do this, weird German software company called SAP >> Yeah, R3. announced a release as R/3. Which was their first three-tier client-server application of SAP. Before that it ran on mainframes, TCP/IP. Remember that Protocol War? Guess what happened post-1992, everybody goes up like this. Infrastructure completely changes. Cisco, EMC, you name it, builds out these PCE client-server architectures. The WAN changes, MPLS, the campus, everything's home running back to that data center running SAP. That was the last 30 years ago. Great transformation of SAP. They've did it again. It's called S/4Hana. And now it's running and people are switching to S/4Hana and they're moving to the cloud. It's just starting. And that is going to alter how you build infrastructure. And so when you have that, being able to troubleshoot in hours versus minutes is a big deal. This is business critical, millions of dollars. This is not fun and games. So again, back to my, what was good enough for the last three or four years for enterprises no longer good enough, now I'm running business critical apps like SAP, and it's going to completely change infrastructure. That's happening in the cloud right now. And that's obviously a significant seismic shift, but what are some of the barriers that customers have been able to eliminate in order to get there? Or is it just good enough isn't good enough anymore? >> Barriers in terms of, well, I mean >> Lisa: The adoption. Yeah well, I mean, I think it's all the things that they go to cloud is, you know, the complexity, really, it's the agility, right? So the barrier that they have to get over is how do I keep the developer happy because the developer went to the cloud in the first place, why? Swipe the credit card because IT wasn't doing their job, 'cause every time I asked them for something, they said no. So I went around 'em. We need that. That's what they have to overcome in the move to the cloud. That is the obstacle is how do I deliver that visibility, that control, the enterprise, great functionality, but yet give the developer what they want. Because the minute I stop giving them that swipe the card operational model, what do you think they're going to do? They're going to go around me again and I can't, and the enterprise can't have that. >> That's a cultural shift. >> That's the main barrier they've got to overcome. >> Let me ask you another question. Is what we think of as mission critical, the definition changing? I mean, you mentioned SAP, obviously that's mission critical for operations, but you're also seeing new applications being developed in the cloud. >> I would say anything that's, I call business critical, same thing, but it's, business critical is internal to me, like SAP, but also anything customer-facing. That's business critical to me. If that app goes down or it has a problem, I'm not collecting revenue. So, you know, back 30 years ago, we didn't have a lot of customer-facing apps, right? It really was just SAP. I mean there wasn't a heck of a lot of cust- There were customer-facing things. But you didn't have all the digitalization that we have now, like the digital economy, where that's where the real explosion has come, is you think about all the customer-facing applications. And now every enterprise is what? A technology, digital company with a customer-facing and you're trying to get closer and closer to who? The consumer. >> Yeah, self-service. >> Self-service, B2C, everybody wants to do that. Get out of the middle man. And those are business critical applications for people. >> So what's needed under the covers to make all this happen? Give us a little double click on where you guys fit. >> You need consistent architecture. Obviously not just for one cloud, but for any cloud. But even within one cloud, forget multicloud, it gets worst with multicloud. You need a consistent architecture, right? That is automated, that is as code. I can't have the human involved. These are all, this is the API generation, you've got to be able to use automation, Terraform. And all the way from the application development platform you know, through Jenkins and all other software, through CICD pipeline and Terraform, when you, when that developer says, I want infrastructure, it has to go build that infrastructure in real time. And then when it says, I don't need it anymore it's got to take it away. And you cannot have a human involved in that process. That's what's completely changed. And that's what's giving the agility. And that's kind of a cloud model, right? Use software. >> Well, okay, so isn't that what serverless does, right? >> That's part of it. Absolutely. >> But I might still want control sometimes over the runtime if I'm running those mission critical applications. Everything in enterprise is a heterogeneous thing. It's like people, people say, well there's going to, the people going to repatriate back to on-prem, they are not repatriating back to on-prem. >> We were just talking about that, I'm like- >> Steve: It's not going to happen, right? >> It's a myth, it's a myth. >> And there's things that maybe shouldn't have ever gone into the cloud, I get that. Look, do people still have mainframes? Of course. There's certain things that you just, doesn't make sense to move to the new generation. There were things, certain applications that are very static, they weren't dynamic. You know what, keeping it on-prem it's, probably makes sense. So some of those things maybe will go back, but they never should have gone. But we are not repatriating ever, you know, that's not going to happen. >> No I agree. I mean, you know, there was an interesting paper by Andreessen, >> Yeah. >> But, I mean- >> Steve: Yeah it was a little self-serving for some company that need more funding, yeah. You look at the numbers. >> Steve: Yeah. >> It tells the story. It's just not happening. >> No. And the reason is, it's that agility, right? And so that's what people, I would say that what you need to do is, and in order to get that agility, you have to have that consistency. You have to have automation, you have to get these people out of the way. You have to use software, right? So it's that you have that swipe the card operational model for the developers. They don't want to hear the word no. >> Lisa: Right. >> What do you think is going to happen with AWS? Because we heard, I don't know if you heard Selipsky's keynote this morning, but you've probably heard the hallway talk. >> Steve: I did, yeah. >> Okay. You did. So, you know, connecting the dots, you know doubling down on all the primitives, that we expected. We kind of expected more of the higher level stuff, which really didn't see much of that, a little bit. >> Steve: Yeah. So, you know, there's a whole thing about, okay, does the cloud get commoditized? Does it not? I think the secret weapon's the ecosystem, right? Because they're able to sell through with guys like you. Make great margins on that. >> Steve: Yeah, well, yeah. >> What are your thoughts though on the future of AWS? >> IAS is going to get commoditized. So this is the fallacy that a lot of the CSPs have, is they thought that they were going to commoditize enterprise. It never happens that way. What's going to happen is infrastructure as a service, the lower level, which is why you see all the CSPs talking about what? Oracle Cloud, industry cloud. >> Well, sure, absolutely, yeah. >> We got to get to the apps, we got to get to SAP, we got to get to all that, because that's not going to get commoditized, right. But all the infrastructural service where AWS is king that is going to get commoditized, absolutely. >> Okay, so, but historically, you know Cisco's still got 60% plus gross margins. EMC always had good margin. How pure is the lone survivor in Flash? They got 70% gross margins. So infrastructure actually has always been a pretty good business. >> Yeah that's true. But it's a hell of a lot easier, particularly with people like Aviatrix and others that are building these common architectural things that create simplicity and abstract the way the complexities of underneath such that we allow your network to run an AWS, Azure, Google, Oracle, whatever, exactly the same. So it makes it a hell of a lot easier >> Dave: Super cloud. >> to go move. >> But I want to tap your brain because you have a good perspective of this because servers used to be a great margin business too on-prem and now it's not. It's a low margin business 'cause all the margin went to Intel. >> Yeah. But the cloud guys, you know, AWS in particular, makes a ton of dough on servers, so, or compute. So it's going to be interesting to see over time if that gets com- that's why they're going so hard after silicon. >> I think if they can, I think if you can capture the workload. So AWS and everyone else, as another example, this SAP, they call that a gravity workload. You know what gravity workload is? It's a black hole. It drags everything else with it. If you get SAP or Oracle or a mainframe app, it ain't going anywhere. And then what's going to happen is all your other apps are going to follow it. So that's what they're all going to fight for, is type of app. >> You said something earlier about, forget multicloud, for a moment, but, that idea of the super cloud, this abstraction layer, I mean, is that a real business value for customers other than, oh I got all these clouds, I need 'em to work together. You know, from your perspective from Aviatrix perspective, is it an opportunity for you to build on top of that? Or are you just looking at, look, I'm going to do really good work in AWS, in Azure? Now we're making the same experience. >> I hear this every single day from our customers is they look and they say, good enough isn't good enough. I've now hit the point, I'm hitting route limitations. I'm hitting, I'm doing things manually, and that's fine when I don't have that many applications or I don't have mission critical. The dogs are eating the dog food, we're going into the cloud and they're looking and then saying this is not an operational model for me. I've hit the point where I can't keep doing this, I can't throw bodies at this, I need software. And that's the opportunity for us, is they look and they say, I'm doing it in one cloud, but, and there's zero chance I'm going to be able to figure that out in the two or three other clouds. Every enterprise I talk to says multicloud is inevitable. Whether they're in it now, they all know they're going to go, because it's the business units that demand it. It's not the IT teams that demand it, it's the line of business that says, I like GCP for this reason. >> The driver's functionality that they're getting. >> It's the app teams that say, I have this service and GCP's better at it than AWS. >> Yeah, so it's not so much a cost game or the end all coffee mug, right? >> No, no. >> Google does this better than Microsoft, or better than- >> If you asked an IT person, they would rather not have multicloud. They actually tried to fight it. No, why would you want to support four clouds when you could support one right? That's insane. >> Dave and Lisa: Right. If they didn't have a choice and, and so it, the decision was made without them, and actually they weren't even notified until day before. They said, oh, good news, we're going to GCP tomorrow. Well, why wasn't I notified? Well, we're notifying you now. >> Yeah, you would've said, no. >> Steve: This is cloud bottle, let's go. >> Super cloud again. Did you see the Berkeley paper, sky computing I think they call it? Down at Berkeley, yep Dave Linthicum from Deloitte. He's talking about, I think he calls it meta cloud. It's happening. >> Yeah, yeah, yeah. >> It's happening. >> No, and because customers, customers want that. They... >> And talk about some customer example or two that you think really articulates the value of why it's happening and the outcomes that it's generating. >> I mean, I was just talking to Lamb Weston last night. So we had a reception, Lamb Weston, huge, frozen potatoes. They serve like, I dunno, some ungodly percentage of all the french fries to all the fast food. It's unbelievable what they do. Do you know, they have special chemicals they put on the french fries. So when you get your DoorDash, they stay crispy longer. They've invented that patented it. But anyway, it's all these businesses you've never heard of and they do all the, and again, they're moving to SAP or they're actually SAP in the cloud, they're one of the first ones. They did it through Accenture. They're pulling it back off from Accenture. They're not happy with the service they're getting. They're going to use us for their networking and network security because they're going to get that visibility and control back. And they're going to repatriate it back from a managed service and bring it back and run it in-house. And the SAP basis engineers want it to happen because they see the visibility and control that the infrastructure guy's going to get because of us, which leads to, all they care about is uptime and performance. That's it. And they're going to say the infrastructure team's going to lead to better uptime and better performance if it's running on Aviatrix. >> And business performance and uptime, business critical >> That is the business. That is the business. >> It is. So what are some of the things next coming down the pike from Aviatrix? Any secret sauce you can share? >> Lot of secrets. So, two secrets. One, the next thing people really want to do, embedded network security into the network. We've kind of talked about this. You're going to be seeing some things from us. Where does network security belong? In the network. Embedded in the fabric of the network, not as this dumb device called the next-gen firewall that you steer traffic to. It has to be into the fabric of what we do, what we call airspace. You're going to see us talk about that. And then the next thing, back to the maturity of the cloud, as they build out the core, guess what they're doing? It's this thing called edge, Dave, right? And guess what they're going to do? It's not about connecting the cloud to the edge to the cloud with dumb things like SD-WAN, right? Or SaaS. It's actually the other way around. Go into the cloud, turn around, look out at the edge and say, how do I extend the cloud out to the edge, and make it look like a VPC. That's what people are doing. Why, 'cause I want the operational model. I want all the things that I can do in the cloud out at the edge. And everyone knows it's been in networking. I've been in networking for 37 years. He who wins the core does what? Wins the edge, 'cause that's what happens. You do it first in the core and then you want one architecture, one common architecture, one consistent way of doing everything. And that's going to go out to the edge and it's going to look like a VPC from an operational model. >> And Amazon's going to support that, no doubt. >> Yeah, I mean every, you know, every, and then it's just how do you want to go do that? And us as the networking and network security provider, we're getting dragged to the edge by our customer. Because you're my networking provider. And that means, end to end. And they're trying to drag us into on-prem too, yeah. >> Lot's going on, you're going to have to come back- >> Because they want one networking vendor. >> But wait, and you say what? >> We will never do like switches and any of the keep Arista, the Cisco, and all that kind of stuff. But we will start sucking in net flow. We will start doing, from an operational perspective, we will integrate a lot of the things that are happening in on-prem into our- >> No halfway house. >> Copilot. >> No halfway house, no two architectures. But you'll take the data in. >> You want one architecture. >> Yeah. >> Yeah, totally. >> Right play. >> Amazing stuff. >> And he who wins the core, guess what's more strategic to them? What's more strategic on-prem or cloud? Cloud. >> It flipped three years ago. >> Dave: Yeah. >> So he who wins in the clouds going to win everywhere. >> Got it, We'll keep our eyes on that. >> Steve: Cause and effect. >> Thank you so much for joining us. We've got your bumper sticker already. It's been a great pleasure having you on the program. You got to come back, there's so, we've- >> You posting the bumper sticker somewhere? >> Lisa: It's going to be our Instagram. >> Oh really, okay. >> And an Instagram sto- This is new for you guys. Always coming up with new ideas. >> Raising the bar. >> It is, it is. >> Me advance, I mean, come on. >> I love it. >> All right, for our guest Steve Mullaney and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.

>>The Cube presents UI Path Forward five. Brought to you by UI Path. >>Welcome back to The Cube's, continuous coverage with day two of UI Path forward. Five. My name is Dave Ante. I'm here with my co-host Dave Nicholson. And you are watching The Cube. It's all about the robots, the automations, the transformations and beyond. Audi Gana is here. She's group executive at Vodacom and Niva is back. She's senior director of telecommunications industry for UiPath. Ladies, welcome to the Cube. >>I thank you very much. >>So Vodacom a leading telco in in Africa across the continent. Tell us more about the company. >>The company is a traditionally telecommunications company, but our vision 2025 is first to transition from being a telco to a technology company. So you'll find that a lot of the use cases that we've actually started embarking on, combined the combination of telco and FinTech. And we've got a lot of RPA bot also supporting the FinTech platform, which is quite a major step in our strategy. >>So, you know, it's interesting Mark Andreessen's famous comment, Every company's a software company. I like to think every company's a technology company, technology driven. So what does that actually mean for you? Is it like a split brain between FinTech? Cuz it's pretty clear that FinTech is always a highly, you know, technology oriented and telecom. Are they sort of together driving a, a technology business? How does that >>Work? It's, it's a, it's a converge use of the technology to add value to the customer. So what we wanna do is to get to the point where we have converged services where the Telecommunicate, cuz at the end of the day in the African market, you'll find that there's a lot of markets that are unbanked. So you find that a cell phone is a means of communication and a a mobile platform for the users. So it's a natural progression for our company to actually play in both spaces. And I think one of the things I find quite interesting is the levels of trust that a lot of citizens have in our financial platform. In that even some of the governments are paying social grants using the platform. And so it almost becomes, without the phones a lot of people cannot function type of scenario. >>Nevas is your role a global role? >>Yes, it is a global role. >>Okay. So it's interesting cause you're I think based down under, right? I am. Is that true? Okay. Obviously spent some time in, in, in the African continent. How are you, what are you seeing in terms of the, the trends in, in telecommunications that, and are you noticing there's gotta be differences across different regions? You know, a lot of times you hear, oh no, there's really kind of a global world out and I know it is, but telco seems to be one of the industries that has some uniqueness within the different breaches. What are you seeing? >>Look, we are privileged to work with more than 200 telecoms around the world. But clearly from a technology perspective, there are some regions that have embraced technology sooner than the others, particularly when it comes to automation. Now we do have use cases with all of them that we are, you know, the 200 we are working with. But the extent to which they become strategic partners, Varie is, you know, what I find is in, in the US we are doing a lot in the customer experience space with the telecoms in aj it's more back of house. And with telecoms like Vodacom, it's really strategic. You know, automation is being applied practically in every facet of work. And you know, sometimes that could be because the demand is just so great for connectivity, you know, at times there's a skills gap, but it does vary. But what's reassuring is that there is a journey and you know, at this event what I have seen is telecoms wanting to learn from other telecoms. And I must say Artie has been in huge demand. We did about 22 meetings yesterday with others wanting to know, which again is that strategic trend. >>Artie, my understanding is you've been at this for a while, this automation journey for quite some time and p i pass. Interesting. I mean it's a company that's founded in 2005 and kind of did sort of its own thing for a long time and then realized it had lightning in a bottle Yeah. For a mid last decade. But my understanding is you've seen it all. You've seen the, the legacy platforms. And so tell me about your personal journey with automation and then the companies. >>Okay, so there's the automation pre rpa, which was strangely enough, I come from banking, got a finance degree, did automated ations in one of the bigger banks. And somehow I transitioned. And I mean from a history perspective, the one of the previous platforms, which was the biggest one at the time, that's where I got to learn about rpa. And then there's another vendor that we then use in another company. So this is almost my third vendor that I'm experiencing in the RPA space. Having joined RPA space in 2015, apparently I'm kind of a veteran, >>So, So what are you seeing is what's the difference between, I mean let's call UI path, that was sort of a modern focus on simple to deploy. That's really how they get started when I first found them. How do you compare what UiPath has? And there are others, there are other modern platforms to sort of the legacy platforms. What's the >>Difference? I think it's the diversity and the applicability of the technology across multiple industries is something that still amazes me up until today. Because the kind of customers I've been meeting today, I, I would not, I met a guy who owns an ice cream company and I'm like, where would automation come in here? But he's actually quite a big customer of, of UiPath, you know. So I think that's one thing I appreciate. I think the ease of use, it has actually allowed for a lot of people to be part of the digital transformation. I think in the his, in the past technology has been seen as something that was a bit elite and that you needed to have X amount of skills and level of education. Whereas the RPA industry has almost bridged that gap in actually bringing along as many people in the journey in terms of digital transformation. And the fourth industrial revolution is now starting to become more inclusive >>Horizontal across industries. >>Yeah. >>So Vodacom headquartered in South Africa. Okay. But presence throughout the continent. Yes. I imagine that various geographies have various twists and quirks to them and different needs. But as a general premise, the African continent has led the rest of the world in terms of embracing these little mobile devices for the most mission. Critical from a personal perspective things, right? Yeah. So if you, if you're already trusting all of your finances and even interaction with your government from a financial perspective. Yeah. When you say technology platform technology is moving forward, what's more critical from that? Or how do you, how do you, how do you branch off from that? What are some of the other things that you can share with us that you're looking towards in the future that may, that that may trickle over here eventually? >>So I think what one of the things we started playing around with quite well is actually the convergence of machine learning, AI and rpa. You would find that a lot of research will tell you that this is the future of the automation and for us, we are actually living the future in that we have civil use cases that are actually extracting a lot of business value. Where we've realized that RPA in of itself, and this is obviously oversimplifying the technology is almost the unlimited hands on keyboards that you could ever have, right? And then machine learning and AI almost the becomes the unlimited brains. So when you then combine the tool, you almost have this strong technology that can revolutionize how we operate and service our customers. >>Well how do, how does that translate? Can you translate that into a user experience at this point? So I mean, we're talking about people who they, they have a motor license, they don't have a desktop computer at home. Yeah. This is their portal into the world. >>So you find that if you're speaking pure telco, and I'm obviously over simplifying there some nowhere an engineer, right? But I think at, at a very simplified level, there's a lot of legacy technology that is used in the telco space and you'll find that because of that, there's a lot of lack of integration. And you'll find that the reasons why a lot of customers call corners is because there's poor integration in a lot of instances. And it's, it's, it's, it's ad hoc. So it's not as if the system is failed completely. So what we've now done is to try and see how do we use machine learning to pick up on those anomalies on the network, right? And because each time something breaks, right, it's almost a fixed way to fix it and therefore the machine learning picking up there normally almost the hands over to the RPA bot to fix the problem within the network element. But that means is that from a customer experience perspective, instead of you actually realizing there's a problem, we've fixed it before you even know that there's a problem. And therefore, and as you can imagine, it means that you then call the course into less because now you don't have the reason to complain because we've proactively identified the problem and we proactively use RPA then to fix it. So we almost have the almost like a self-healing element in within the, the, the RPA AI space. >>You know, I think of, we don't talk about the data, we haven't talked about the data much this week. I think in many respects this industry is, is data industry. Our automation is all about what you can do with the data. You said unlimited hands, unlimited brains. Cuz to me you have unlimited data and a lot of times you just can't handle it. Yeah. So what's the data angle on all this? >>So firstly, I know a lot of people will say data is the new oil. No, >>Right? So I would never >>Say that. I always though, I think I always ask people if I give you a bucket of brain crude oil, right? What are you gonna do with it? Right? Right. And similar to data, right? So I want to almost equate data to that crude oil element, but if you don't know how to refine it, process it, get it to be reliable, it's very useless in of its natural sense. So I think one of the things we've realized is that leveraging of the analogy of the, the machine learning in the brain, if you are in the sales space, you forever trying to push new sales, right? And then chances are when a customer leaves you, you are almost in a reactor state. So, and I imagine a world where you could proactively identify a customer with the propensity to leave your company because a lot of customers don't just, they are situations where they'll be walking down the street competitor calls them, they leave, not because they were unhappy, but a lot of customers actually had several engagements with us that were not pleasant, whatever the definition is. >>So we then saw there was almost five types of attributes that resulted in customers leaving us. So what then that said was imagine if you are an account manager, right? And you got told UiPath P two I limited has experienced 1, 2, 3, 4. Right? Actually, please go engage with them because something is happening. It means that as an account manager, you are then equipped to have a meaningful engagement with the customer because you're saying, hi UiPath, I see you've had X amount of job calls and you've had x amount of complaints in our call center. What is happening is it could be, could be your network, maybe the tower where you are, do you, And then the conversation becomes so meaningful. And I think even during covid what we found is lot of customers started using less of our data, not because they were unhappy, but it became an affordability thing, right? >>Because this is a thousands and thousands of, of data elements and pieces around Yeah. About customer transactions. There's no way one human would be able to go through all of the data and make me meaningful decisions out of it. So we then found that some customers were complaining about affordability. So we then built another model that says if an account manager is talking to a customer and they're struggling from an affordability perspective, what's the next best offer you can make to your customer while you're engaging? And then if in, if, if now your UiPath takes up that offer, then you'd find that the bot does the post engagement provisioning on the system. Because now if you then said, I've only, I can only afford 10 lines, but only pay 10 gigs, but not 10 lines and 20 gigs, that is at least better than us losing the customer. >>Yeah. Right? And we offering them almost a downward migration type of situation. Then the bot does that on the system. So you would find that we almost playing in the space of a human, human centered, intelligent automation where machine learning becomes the brain, the person is amplified in how they operate at the customer. And then the RPA bot becomes the hands that executes on that. And as the account manager you focusing on engagement and convincing, which is really what people are great and selling as opposed to going through all of the pro cause VOCA is a lot of products. So as opposed to having a person going through the products and trying to find the best product for you, you know, so we, we are using machine learning to assist the >>Humans. I I mean in every, every interaction is consistent in that case. I know I sometimes have to call three or four times to find a professional that knows enough that can help me. Yes. Such a frustrating thing as a consumer. So you are, are you, you're attacking churn with automation. So we haven't even talked about how you guys are working together, your journey and all that stuff, but, but how are you guys working here? What are you, what are you doing? You know, in addition to what you just described with with ui. iPad? >>So I think my portfolio's quite wide. So I am, my team is in every single vertical in the organization from customer care to the consumer enterprise business units to finance technology, network compliance. And we do all of this in about six countries, right? So one of the things we've actually realized is that if we are looking at customer service, we wanted to understand why do customers call us? And I think I came from a point of ignorance because I'm not from telco, so I actually realized that if we're talking billing and finance revenue assurance, customers call us because we build them arly. But technically speaking it's our systems that there's something that resulted in the customer calling us. So why do we not know about our own systems? Why are we waiting for the customers to call us? And literally those are the questions I was asking cuz I felt like why are we, why are we waiting for the customers to call us? >>So we then then found a way to try and see within the billing systems where do the breakages happen, right? So that we fix them before the customer has to call us again. So then again from a billing perspective, it means that cuz it the billing element can come in two ways where we are giving you a service and not charging you for it. We then have revenue leakage or we, you are consuming something and we are overcharging you. Then you call us and say, Whatcom is stealing my data. Yeah, you're right out there. I promise you nobody wakes up in the morning and wants to take one gig of your data. So it almost becomes a day integrity initiative that results in good customer service but then result in eradication of course. As opposed to us waiting for customers to tell us what the problem is and trying to help them fast. Cuz that's generally always been what I've picked up the energy around customer service. How do we help you fast? I'm saying why must you call us when our systems had fail that? So we almost trying to see how do we use the technology internally to give customers a better experience and then also have the financial benefits that we are now starting to see happening in the, >>What's the scope of, of your like how many automations, how many bots? Can you give us a sense >>Of this? So right now I think we over on with all of the four, five countries that we are in, we over 400 bots. Wow. Okay. So we started in 2004 years ago, this is my fourth year in Voca. We, and we are not using just one product with UiPath. It became a platform because as we became across more kinds of problems, I think what I've appreciated about part is how we've actually created a partnership. Instead of them trying to sell me products for the sake of consuming products, it became a, this is my problem, right? And then somehow they would whip out the product that solves my problem type of thing. So it became a ecosystem of solutions that >>You must love hanging out with Artie. >>I absolutely do and love, you know, I've spent a career in telecommunications myself and you know, the best days were when you could deliver an outstanding customer experience. And as you can see from what Artie has achieved when you were more proactive and predictive, you can serve your customers so much more effectively and that just lift the morale of the team because we all, you know, have this purpose in doing our jobs. But this is automation and AI built into every part of that customer journey. So end to end, you know, the customer's much happier. You know there's a problem before the customer knows you can solve the problem in most cases before they even know. And that's just what we are all in business to do to make things better. >>Great story. Thank you so much for sharing. Appreciate coming back >>In the queue. Thank you very much. Thank >>You. Thank you for watching. Keep it right there. Don't forget, go to silicon angle.com, all the news, go to the cube.net. You'll see me all these videos are available on demand as well as the other events that we do. Dave VTE for Dave Nicholson. Keep it right there. Right back at forward five UI.

[Music] we're here with steve melanie the president and ceo of aviatrix steve john and i started this whole super cloud narrative as a way to describe that something different is happening specifically within the aws ecosystem but more broadly across the cloud landscape at re invent last year you and i spoke on the cube and you said one of your investors guy named nick sterile said to you at the show it's happening steve welcome to the cube what's happening what did nick mean by that yeah we were we were just getting ready to go on and i leaned over and he looked at me and he whispered in my ear and said it's happening he said it just like that and and you're right it was it was kind of funny and we talked about that and what he means is enterprises you know this is why i went to aviatrix three and a half years ago is the the the flip switch for enterprises and they said now we mean it we've been talking about cloud for 12 years or 15 years now we mean it we are digitally transforming we are the movement to cloud is going to make that happen and oh by the way of course it's multi-cloud because enterprises put workloads where they run best where they have the best security the best performance the best cost and the business is driving this transformation and they decide that i'm going to use that azure and another business unit decides i'm using google and another one says i'm using aws and so of course it's going to be multi-cloud and i think we're going to start seeing actual multi-cloud applications once that infrastructure and you know you call it the super cloud once that starts getting built developers are going to go wait a minute so i can pick this feature from google and and that service from azure and that service from aws easily without any hesitation once that happens they're going to start really developing today there aren't multi-cloud applications but but but the what's happening is the enterprise embracing public cloud they're using multiple clouds many of them call it four plus one right they're four different public clouds plus what they have on prem that to me is what's happening i am now re-architecting my enterprise infrastructure from applications all the way down to the network and i am embracing uh uh public clouds in that in that process so i mean you nailed us so many things in there i mean digitally transforming to me this is the digital transformation it's leveraging embracing the capex from the hyperscalers now you know people in the industry we're not trying to do what gartner does and create a new category per se but we do use super cloud as a metaphor so i don't expect necessarily vendors to use it or not but but i and i get that but when you talk about multi-cloud what specifically is new in other words what you touched on some of this stuff what constitutes a modern multi-cloud or what we would call a super cloud you know network architecture what are the salient attributes yeah i would say today so two years ago there was no such thing even as multiple clouds it was aws let's be clear everything was aws and for people to even back then two three years ago to even envision that there would be anything else other than aws people couldn't even envision now people kind of go yeah that was done we now see that we're going to use multiple clouds we're going to use azure we're going to use gcp and we're going to use this and we'll guess we're going to use oracle and even ollie cloud we're going to use five or four or five different public clouds what's but that would be i think of as multiple clouds but from an i.t perspective they need to be able to support all those clouds in these shared services and what they're going to do i actually think we're starting and you may have hit on something in the super cloud or i know you've talked about metacloud that that's got bad connotations for facebook i know everybody's like no please not another meta thing but there is that concept of this abstracted layer above you know writing we call it you know altitude you know aviatrix everything's you know riding above the clouds right that that that common abstracted layer this application infrastructure that runs the application that rides above all the different public clouds and i think once we do that you know dave what's going to happen is i think really what's going to happen is you're going to start seeing these these multi-cloud applications which to my knowledge really doesn't exist today i i think that might be the next phase and in order for that to happen you have to have all of the infrastructure be multi-cloud meaning not just networking and network security from from from aviation but you need snowflake you need hashtag you need datadog you need all the new horsemen of the new multi-cloud which isn't the old guys right this is all new people aviatrix dashie snowflake datadonk you name it that are going to be able to deliver all this multi-cloud cross-cloud wherever you want to talk about it such that application development and deployment can happen seamlessly and frictionlessly across multi-cloud once that happens the entire stack then you're going to start seeing and that to me starts enabling this what you guys call you know the super cloud the meta cloud the whatever cloud but that then rides above all the individual clouds that that's going to start getting a whole new realm of application development in my mind so we've got some work to do to basic do some basic blocking and tackling then the application developers can really build on top of that so so some of the skeptics on on this topic would ask how do you envision this changing networking versus it just being a bolt-on to existing fossilized network infrastructure in other words yeah how do we get from point a where we are today to point b you know so-called networking so we can actually build those uh super cloud applications yeah so you know what it is it's interesting because it goes back to my background at nasira and what we used to talk about then it isn't about managing complexity it's about creating simplicity it's very different and when you put the intelligence into the software right this is what computer science is all about we're turning networking into computer science when you create an abstraction layer we are not just an overlay day we dave we actually integrate in with the native services of the cloud we are not managing the complexity of these multi-clouds we are using it you know controlling the native constructs adding our own intelligence to this and then creating what is basically simplification for the people above it so we're simplifying things not just managing the complexity that's how you get the agility for cloud that's how you get to be able to do this because if all you are is a veneer on top of complexity you're just hiding complexity you're not creating simplicity and what happens is it actually probably gets more complex because if all you're doing is hiding the bad stuff you're not getting rid of it i love that i love that we're doing that at the networking and network security layer you're going to see snowflake and datadog and other people do it at their layers you know i reminds of a conversation i had with cause the one of the founders of pure storage who they're all about simplicity this idea of of creating simplicity versus like you said just creating you know a way to handle the complexity compare you know pure storage with the sort of old legacy emc storage devices and that's what you had you had you you had emc managing the complexity at pure storage disrupting by creating simplicity so what are the challenges of creating that simplicity and delivering that seamless experience that continuous experience across cloud is it engineering is it mindset is it culture is it technology what is it well i mean look at look you see the recession that we're we're hitting you see there is a significant problem that we have in the general it industry right now and it's called skills gap skills shortage it's two problems we don't have enough people and we don't have enough people that know cloud and the reason is everybody on the same tuesday three and a half years ago all said now i mean i'm moving the cloud we're a technology company we don't make sneakers anymore we don't make beer we're a technology company and we're going to digitally transform and we're going to move the cloud guess what three years ago there were probably seven people that understood cloud now everyone on the same tuesday morning all decides to try to hire those same seven people there's just not enough people around so you're going to need software and you're going to have to put the intelligence into the software because you're not going to be able to a hire those people and b even if you hire them you can't keep them as soon as they learn cloud guess what happens dave they're off they're on to the next job at the next highest bidder so how are you going to handle that you have to have software that intelligent software that is going to simplify things for you we have people managing massive multi-cloud network and network security people with two people on-prem they got hundreds right you it's not about taking that complex model that it had on-prem and jam it into the cloud you don't have the people to do it and you're not going to get the people to do it you know i want to ask you yeah so i want to ask you about the go to market challenges because we our industry gets a bad rap for for selling we're really good at selling and then but but actually delivering what we sell sometimes we fall down there so so i love tom sweet as cfo of of dell he talks about the the say do ratio uh how that's actually got to be low but you know but you know what i mean uh the math the fraction guy right so but do do what you say you're going to do are there specific go to market challenges related to this type of cross cloud selling where you can set you have to set the customer's expectations because what you're describing is not going to happen overnight it's a journey but how do you handle that go to market challenge in terms of setting those customer expectations and actually delivering what you say you can sell and selling enough to actually have a successful business um so i think everything's outside in so so i think the the what really is exciting to me about this cloud computing model that with the transformation that we're going through is it is business-led and it is led by the ceo and it is led by the business units they run the business it is all about agility is about enabling my developers and it's all about driving the business market share revenue all these kind of things you know the last transformation of mainframe to on to pc client server was led by technologists it wasn't led by the business and it was it was really hard to tie that to the business so then so this is great because we can look at the initiatives you can look at the the the initiatives of the ceo in your company and now as an i.t person you can tie to that and they're going to have two or three or four initiatives and you can actually map it to that so that's where we start is let's look at what the c your ceo cares about he cares about this he cares about that he cares about driving revenue he cares about agility of getting new applications out to the market sooner to get more revenue there's this and oh by the way transfer made transforming your infrastructure to the cloud is the number one thing so it's all about agility so guess what you need to be able to respond to that immediately because tomorrow the business is going to go to you and say great news dave we're moving to gcp wait what no one told me about that well we're telling you now and uh you need to be ready tomorrow and if you're sitting there and you're tied to the low-level constructs and all you know is aws well i don't have those people and even if i have even if i could hire them i'm not allowed to because i can't hire anybody how am i going to respond to the business and the needs of the business now all of a sudden i'm in the way as the infrastructure team of the ceo's goals because we decided we need to we need to get the ai capabilities of gcp and we're moving to gcp or i just did a big deal with gcp and uh miraculously they said i need to run on gcp right i did a big deal with google right guess what comes along with that oh you're moving to gcp great the business says we're moving to gcp and the i.t guys are sitting there going well no one told me well sorry so it's all about agility it's all about that and the and and complexity is the killer to agility this is all about business they're going to come to you and say we just acquired a company we need to integrate them oh but they got they use the same ip address range as we do there's overlapping ips and oh by the way they're in a different cloud how do i do that no one cares the business doesn't care they're like me they're very impatient get it done or we'll find someone who will yeah so you've got to get ahead of that and so when we in terms of when we talk to customers that's what we do this isn't just about defenses this is about making you get promoted making you do good for your company such that you can respond to that and maybe even enable the company to go do that like we're going to enable people to do true multi-cloud applications because the infrastructure has to come first right you you put the foundation in your big skyscraper like the crew behind me and the plumbing before you start building the floors right so infrastructure comes first then comes then comes the applications yeah so you know again some people call it super cloud like us multi-cloud 2.0 but the the real mega trend that i see steve and i'd love you to bottom line this and bring us home is you know andreessen's all companies are software companies it's like version 2.0 of that and the applications that are going to be built on that top this tie into the digital transformations it was goldman it's jpmc it's walmart it's capital one b of a oracle's acquisition of cerner is going to be really interesting to see these super clouds form within industries bringing their data their tooling and their specific software expertise built on top of that hyperscale infrastructure and infrastructure for companies like yours so bottom line is stephen steve what's the future of cloud how do you see it the future is n plus one so two years ago people had one plus one i had what i had on prem and then what i had in aws they today if you talk to an enterprise they'll have what they call four plus one right which is four public clouds plus what i have on prem it's going to n plus one right and what's going to happen is exactly what you said you're going to have industry clouds you're going to the the multi-cloud aspect of it is going to end it's not going to go from four to one some people think oh it's not going to be four it's going down to one or two bs it's going to end it's going to a lot as they start extending to the edge and they start integrating out to the to the branch offices it's not going to be about that branch offer so that edge iot or edge computing or data centers or campus connecting into the cloud it's going to be the other way around the cloud is going to extend to those areas and you're going to have ai clouds you know whether it's you know ultra beauty who's a customer of ours who's starting to roll out ar and vr out to their retail stores to show you know makeup and this and the other thing these are new applications transformations are always driven by new applications that don't exist this isn't about lift and shift of the existing applications the 10x tam in this market is going to becomes all the new things that's where the explosion is going to happen and you're going to see end level those those branch offices are going to look like clouds and they're going to need to be stitched together and treated like one infrastructure so it's going to go from four plus one to n plus one and that's what you're gonna want as an enterprise i'm gonna want n clouds so we're gonna see an explosion it's not going to be four it's going to be end now at the end underneath all of that will be leveraging and effectively commoditizing the existing csps yeah and but you're going to have an explosion of people commoditizing them and just like the goldmans and the industry clubs are going to do they're going to build their own eye as well right no way no way it's that's what's going to happen it's going to be a 10x on what we saw last decade with sas it's all going to happen around clouds and supercloud steve malini thanks so much for coming back in the cube and helping us sort of formulate this thinking i mean it really started with with with you and myself and john and nick and really trying to think this through and watching this unfold before our eyes so great to have you back thank you yeah it's fun thanks for having me are you welcome but keep it right there for more action from super cloud 22 be right back [Music] you

[Music] welcome to the great super cloud debate a power panel of three top technology industry analysts maribel lopez is here she's the founder and principal analyst at lopez research keith townsend is ceo and founder of the cto advisor and sanjeev mohan is principal at sanjmo super cloud is a term that we've used to describe the future of cloud architectures the idea is that super clouds are built on top of hyperscaler capex infrastructure and the idea is it goes beyond multi-cloud the premise being that multi-cloud is primarily a symptom of multi-vendor or m a or both and results in more stove we're going to talk about that super cloud's meant to connote a new architecture that leverages the underlying primitives of hyperscale clouds but hides and abstracts that complexity of each of their respective clouds and adds new value on top of that with services and a continuous experience a similar or identical experience across more than one cloud people may say hey that's multi-cloud we're going to talk about that as well so with that as brief background um i'd like to first welcome our painless guys thanks so much for coming on thecube it's great to see you all again great to be here thank you to be here so i'm going to start with maribel you know what i just described what's your reaction to that is it just like what like cloud is supposed to be is that really what multi-cloud is do you agree with the premise that multi-cloud has really been you know what like chuck whitten from dell calls it it's been multi-cloud by default i call it a symptom of multi-vendor what's your take on on what this is oh wow dave another term here we go right more more to define for people but okay the reality is i agree that it's time for something new something evolved right whether we call that super cloud or something else i you know i don't want to really debate the term but we need to move beyond where we are today in multi-cloud and into if we want to call it cloud 5 multi-cloud 2 whatever we want to call it i believe that we're at the next generation that we have to define what that next generation is but if you think about it we went from public to private to hybrid to multi and every time you have a discussion with somebody about cloud you spend 10 minutes defining what you're talking about so this doesn't seem any different to me so let's just go with super cloud for the moment and see where we go and you know if you're interested after everybody else makes their comments i got a few thoughts about what super cloud might mean as well yeah great so i and i agree with you when we like i said in a recent post you could call it cl cloud you know multi-cloud 2.0 but it's something different is happening and sanjeev i know you're not a you're not a big fan of buzz words either but i wonder if you could weigh in on this topic uh you mean by the way sanjeev is at the mit cdo iq conference a great conference uh in boston uh and so he's it's a public place so we're going to have i think you viewed his line when he's not speaking please go ahead yeah so you know i come from a pedigree of uh being an analyst of uh firms that love inventing new terms i am not a big fan of inventing new terms i feel that when we come up with a new term i spend all my time standing on a stage trying to define what it is it takes me away from trying to solve the problem so so i'm you know i find these terms to be uh words of convenience like for example big data you know big data to me may not mean anything but big data connotes some of this modern way of handling vast volumes of data that traditional systems could not handle so from that point of view i'm i'm completely okay with super cloud but just inventing a new term is what i have called in my previous sessions tyranny of jargons where we have just too many jargons and uh and they resonate with i.t people they do not resonate with the business people business people care about the problem they don't care about what we and i t called them yeah and i think this is a really important point that you make and by the way we're not trying to create a new industry category per se yeah we leave that to gartner that's why actually i like super cloud because nobody's going to use that no vendor's going to use the term super cloud it's just too buzzy so so but but but it brings up the point about practitioners and so keith i want to bring you in so the what we've talked about and i'll just sort of share some some thoughts on the problems that we see and and get keith get your practitioner view most clouds most companies use multiple clouds we all kind of agree on that i think and largely these clouds operate in silos and they have their own development environment their own operating environment different apis different primitives and the functionality of a particular cloud doesn't necessarily extend to other clouds so the problem is that increases friction for customers increases cost increases security risk and so there's this promise maribel multi-cloud 2.0 that's going to solve that problem so keith my question to you is is is that an accurate description of the problem that practitioners face today do what did i miss and i wonder if you could elaborate so i think we'll get into some of the detail later on why this is a problem specifically around technologies but if we think about it in the abstract most customers have their hands full dealing with one cloud like we'll you know through m a and such and you zoom in and you look at companies that have multiple clouds or multi-cloud from result of mma mna m a activity you'll see that most of that is in silos so organizationally the customer may have multiple clouds but sub orchid silos they're generally a single silo in a single cloud so as you think about being able to take advantage of of tooling across the multicloud of what dave you guys are calling the super cloud this becomes a serious problem it's just a skill problem it's too much capability uh across too many things that look completely different than another okay so dave can i pick up on that please i'd love i was gonna just go to you maribel please chime in here okay so if we think about what we're talking about with super cloud and what keith just mentioned remember when we went to see tcp ip and the whole idea was like how do we get computers to talk to each other in a more standardized way how do we get data to move in a more standardized way i think that the problem we have with multi-cloud right now is that we don't have that so i think that's sort of a ground level of getting us to your super cloud premise is that and and you know google's tried it with anthony's like everybody every hyperscaler has tried their like right one to run anywhere but that abstraction layer you talk about what whatever we want to call it is super necessary and it's sort of the foundation so if you really think about it we've spent like 15 years or so building out all the various components of cloud and now's the time to take it so that cloud is actually more of an operating model versus a place there's at least a base level of it that is vendor neutral and then to your point the value that's going to be built on top of that you know people been trying to commoditize the basic infrastructure for a while now and i think that's what you're seeing in your super cloud multi-cloud whatever you want to call it the infrastructure is the infrastructure and then what would have been traditionally that past layer and above is where we're going to start to see some real innovation but we still haven't gotten to that point where you can do visibility observability manageability across that really complex cloud stack that we have the reason i the reason i love that tcpip example hm is because it changed the industry and it had an ecosystem effect in sanjiv the the the example that i first example that i used was snowflake a company that you're very familiar with that is sort of hiding all that complexity and right and so we're not there yet but please chime in on this topic uh you gotta you gotta view it again uh after you building upon what maribel said you know to me uh this sounds like a multi-cloud operating system where uh you know you need that kind of a common uh set of primitives and layers because if you go in in the typical multi-cloud process you've got multiple identities and you can't have that you how can you govern if i'm if i have multiple identities i don't have observability i don't know what's going on across my different stacks so to me super cloud is that call it single pane of glass or or one way through which i'm unifying my experience my my technology interfaces my integration and uh and i as an end user don't even care which uh which cloud i'm in it makes no difference to me it makes a difference to the vendor the vendor may say this is coming from aws and this is coming from gcp or azure but to the end user it is a consistent experience with consistent id and and observability and governance so that to me makes it a big difference and so one of floyer's contribution conversation was in order to have a super cloud you got to have a super pass i'm like oh boy people are going to love that but the point being that that allows a consistent developer experience and to maribel's earlier point about tcp it explodes the ecosystem because the ecosystem can now write to that super pass if you will those apis so keith do you do do you buy that number one and number two do you see that industries financial services and healthcare are actually going to be on clouds or what we call super clouds so sanjeev hit on a really key aspect of this is identity let's make this real they you love talk about data collaboration i love senji's point on the business user kind of doesn't care if this is aws versus super cloud versus etc i was collaborating with the client and he wanted to send video file and the video file uh his organization's access control policy didn't allow him to upload or share the file from their preferred platform so he had to go out to another cloud provider and create yet another identity for that data on the cloud same data different identity a proper super cloud will enable me to simply say as a end user here's a set of data or data sets and i want to share a collaboration a collaborator and that requires cross identity across multiple clouds so even before we get to the past layer and the apis we have to solve the most basic problem which is data how do we stop data scientists from shipping snowballs to a location because we can't figure out the identity the we're duplicating the same data within the same cloud because we can't share identity across customer accounts or etc we we have to solve these basic thoughts before we get to supercloud otherwise we get to us a turtles all the way down thing so we'll get into snowflake and what snowflake can do but that's what happens when i want to share my snowflake data across multiple clouds to a different platform yeah you have to go inside the snowflake cloud which leads right so i would say to keith's question sanjeev snowflake i think is solving that problem but then he brings up the other problem which is what if i want to share share data outside the snowflake cloud so that gets to the point of visit open is it closed and so sanji chime in on the sort of snowflake example and in maribel i wonder if there are networking examples because that's that's keith's saying you got to fix the plumbing before you get these higher level abstractions but sanji first yeah so i so i actually want to go and talk a little bit about network but from a data and analytics point of view so i never built upon what what keith said so i i want to give an example let's say i am getting fantastic web logs i and i know who uh uh how much time they're spending on my web pages and which pages they're looking at so i have all of that now all of that is going into cloud a now it turns out that i use google analytics or maybe i use adobe's you know analytics uh suite now that is giving me the business view and i'm trying to do customer journey analytics and guess what i now have two separate identities two separate products two separate clouds if i and i as an id person no problem i can solve any problem by writing tons of code but why would i do that if i can have that super pass or a multi-cloud layout where i've got like a single way of looking at my network traffic my customer metrics and i can do my customer journey analytics it solves a huge problem and then i can share that data with my with my partners so they can see data about their products which is a combination of data from different uh clouds great thank you uh maribel please i think we're having a lord of the rings moment here with the run one room to rule them all concept and i'm not sure that anybody's actually incented to do that right so i think there's two levels of the stack i think in the basic we're talking a lot about we don't have the basic fundamentals of how do you move data authenticate data secure data do data lineage all that stuff across different clouds right we haven't even spoken right now i feel like we're really just talking about the public cloud venue and we haven't even pulled in the fact that people are doing hybrid cloud right so hybrid cloud you know then you're talking about you've got hardware vendors and you've got hyperscaler vendors and there's two or three different ways of doing things so i honestly think that something will emerge like if we think about where we are in technology today it's almost like we need back to that operating system that sanji was talking about like we need a next generation operating system like nobody wants to build the cloud mouse driver of the 21st century over and over again right we need something like that as a foundation layer but then on top of it you know there's obviously a lot of opportunity to build differentiation like when i think back on what happened with cloud amazon remained aws remained very powerful and popular because people invested in building things on amazon right they created a platform and it took a while for anybody else to catch up to that or to have that kind of presence and i still feel that way when i talk to companies but having said that i talked to retail the other day and they were like hey we spent a long time building an abstraction layer on top of the clouds so that our developers could basically write once and run anywhere but they were a massive global presence retailer that's not something that everybody can do so i think that we are still missing a gap i don't know if that exactly answers your question but i i do feel like we're kind of in this chicken and egg thing which comes first and nobody wants to necessarily invest in like oh well you know amazon has built a way to do this so we're all just going to do it the amazon way right it seems like that's not going to work either but i think you bring up a really important point which there is going to be no one ring to rule them all you're going to have you know vmware is going to solve its multi-cloud problem snowflake's going to do a very has a very specific you know purpose-built system for it itself databricks is going to do its thing and it's going to be you know more open source i would companies like aviatrix i would say cisco even is going to go out and solve this problem dell showed at uh at dell tech world a thing called uh project alpine which is basically storage across clouds they're going to be many super clouds we're going to get maybe super cloud stove pipes but but the point is however for a specific problem in a set of use cases they will be addressing those and solving incremental value so keith maybe we won't have that single cloud operating you know system but we'll have multiple ones what are your thoughts on that yeah we're definitely going to have multiple ones uh the there is no um there is no community large enough or influential enough to push a design take maribel's example of the mega retailer they've solved it but they're not going to that's that's competitive that's their competitive advantage they're not going to share that with the rest of us and open source that and force that upon the industry via just agreement from everyone else so we're not going to get uh the level of collaboration either originated by the cloud provider originated from user groups that solves this problem big for us we will get silos in which this problem is solved we'll get groups working together inside of maybe uh industry or subgroups within the industry to say that hey we're going to share or federate identity across our three or four or five or a dozen organizations we'll be able to share data we're going to solve that data problem but in the same individual organizations in another part of the super cloud problem are going to again just be silos i can't uh i can't run machine learning against my web assets for the community group that i run because that's not part of the working group that solved a different data science problem so yes we're going to have these uh bifurcations and forks within the super cloud the question is where is the focus for each individual organization where do i point my smart people and what problems they solve okay i want to throw out a premise and get you guys reaction to it because i think this again i go back to the maribel's tcpip example it changed the industry it opened up an ecosystem and to me this is what digital transformation is all about you've got now industry participants marc andreessen says every company is a software company you've now got industry participants and here's some examples it's not i wouldn't call them true super clouds yet but walmart's doing their hybrid thing with azure you got goldman sachs announced at the last reinvent and it's going to take its tools its software its data and which is on-prem and connect that to the aws cloud and actually deliver a service capital one we saw sanjiv at the snowflake summit is is taking their tooling and doing it now granted just within snowflake and aws but i fully expect them to expand that across other clouds these are industry examples capital one software is the name of the division that are now it's to the re reason why i don't get so worried that we're not solving the lord of the rings problem that maribel mentioned is because it opens up tremendous opportunities for companies we got like just under five minutes left i want to throw that out there and see what you guys think yeah i would just i want to build upon what maribel said i love what she said you're not going to build a mouse driver so if multi-cloud supercloud is a multi-cloud os the mouse driver would be identity or maybe it's data quality and to teach point that data quality is not going to come from a single vendor that is going to come from a different vendor whose job is to to harmonize data because there might be data might be for the same identity but it may be a different granularity level so you cannot just mix and match so you need to have some sort of like resolution and that is is an example of a driver for multi-cloud interesting okay so you know octa might be the identity cloud or z scaler might be the security cloud or calibre has its cloud etc any thoughts on that keith or maribel yeah so let's talk about where the practical challenges run into this we did some really great research that was sponsored by one of the large cloud providers in which we took all we looked at all the vmware cloud solutions when i say vmware cloud vmware has a lot of products across multi-cloud now in the rock broadcloud portfolio but we're talking about the og solution vmware vsphere it would seem like on paper if i put vmware vsphere in each cloud that is therefore a super cloud i think we would all agree to that in principle what we found in our research was that when we put hands on keyboard the differences of the clouds show themselves in the training gap and that skills gap between the clouds show themselves if i needed to expose less our favorite friend a friend a tc pip address to the public internet that is a different process on each one of the clouds that needs to be done on each one of the clouds and not abstracted in vmware vsphere so as we look at the nuance yes we can give the big controls but where the capital ones the uh jp morgan chase just spent two billion dollars on this type of capability where the spin effort is done is taking it from that 80 percent to that 90 95 experience and that's where the effort and money is spent on that last mile maribel we're out of time but please you know bring us home give us your closing thoughts hey i think we're still going to be working on what the multi-cloud thing is for a while and you know super cloud i think is a direction of the future of cloud computing but we got some real problems to solve around authentication uh identity data lineage data security so i think those are going to be sort of the tactical things that we're working on for the next couple years right guys always a pleasure having you on the cube i hope we see you around keith i understand you're you're bringing your airstream to vmworld or vmware explorer putting it on the on the floor i can't wait to see that and uh mrs cto advisor i'm sure we'll be uh by your side so looking forward to that hopefully sanjeev and maribel we'll see you uh on the circuit as well yes hope to see you there right looking forward to hopefully even doing some content with you guys at vmware explorer too awesome looking forward all right keep it right there for more content from super cloud 22 right back [Music] you

welcome back to thecube's live coverage coming to you from the big apple in new york city we're talking all things aws summit but right now i've got two powerhouses you know them you love them john furrier dave vellante going to be talking about super cloud guys we've been talking a lot about this there's a big event coming up on the cube august 9th and i gotta start dave with you because we talk about it pretty much in every interview where it's relevant why super cloud yeah so john furrier years ago started a tradition lisa prior to aws which was to lay down the expectation for our audiences what they should be looking for at aws reinvent okay john when did that start 2012 2013. actually 2013 was our first but 2015 was the first time when we get access to andy jassy who wasn't doing any briefings and we realized that the whole industry started looking at amazon web services as a structural forcing function of massive change uh some say inflection point we were saying complete redefinition so you wrote the trillion dollar baby yeah right which actually turns into probably multi-trillion dollars we got it right on that one surprisingly it was pretty obvious so every year since then john has published the seminal article prior to reinvent so this year we were talking we're coming out of the isolation economy and john hedwig also also adam silevski was the new ceo so we had a one-on-one with adam that's right and then that's where the convergence between andy jassy and adam celebski kicked in which is essentially those guys work together even though they he went off and boomerang back in as they say in aws but what's interesting was is that adam zluski's point of view piggyback jassy but he had a different twist yeah some so you know low you know people who didn't have really a lot of thought into it said oh he's copying microsoft moving up the stack we're like no no no no no something structural is happening again and so john wrote the piece and he started sharing it we're collaborating he said hey dave take a take a look add your perspectives and then jerry chen had just written castles in the cloud and he talked about sub-markets and we were sort of noodling and one of the other things was in 2018 2019 around that time at aws re invent there was this friction between like snowflake and aws because redshift separated compute from storage which was snowflake's whole thing now fast forward to 2021 after we're leaving you know the covert economy by the way everyone was complaining they are asking jassy are you competing with your ecosystem the classic right trope and then in in remember jason used to use cloudera as the example i would like to maybe pick a better example snowflake became that example and what the transition was it went from hey we're kind of competitive for sure there's a lot of examples but it went from we're competitive they're stealing our stuff to you know what we're making so much money building on top of aws specifically but also the clouds and cross clouds so we said there's something new happening in the ecosystem and then just it popped up this term super cloud came up to connote a layer that floats above the hyperscale capex not is it's not pass it's not sas it's the combination of the of those things on top of a new digital infrastructure and we chose the term super cloud we liked it better than multi-cloud because multiplayer at least one other point too i think four or five years earlier dave and i across not just aws reinvent all of our other events we were speculating that there might be a tier two cloud service provider models and we've talked with intel about this and others just kind of like evaluating it staring at it and we met by tier two like maybe competing against amazon but what happened was it wasn't a tier two cloud it was a super cloud built on the capex of aws which means initially was a company didn't have to build aws to be like aws and everybody wanted to be like aws so we saw the emergence of the smart companies saying hey let's refactor our business model in the category or industry scope and to dominate with cloud scale and they did it that then continued that was the premise of chen's post which was kind of rift on the cube initially which is you can have a moat in a castle in the cloud and have a competitive advantage and a sustainable differentiation model and that's exactly what's happening and then you introduce the edge and hybrid you now have a cloud operating model that that super cloud extends as a substrate across all environments so it's not multi-cloud which sounds broken and like put it distance jointed joint barriers hybrid cloud which is the hybrid operating model at scale and you don't have to be amazon to take advantage of all the value creation since they took care of the capex now they win too on the other side because because they're selling ec2 and storage and ml and ai and this is new and this is information that people don't might not know about internally at aws there was a debate dave okay i heard this from sources do we go all in and compete and just own the whole category or open the ecosystem and coexist with [ __ ] why do we have these other companies or snowflake and guess what the decision was let's make it open ecosystem and let's have our own offerings as well and let the winner take off smart because they can't hire enough people and we just had aws and snowflake on the cube a few weeks ago talking about the partnership the co-op petition the value in it but what's been driving it is the voice of the customer but i want to ask you paint the picture for the audience of the critical key components of super cloud what are those yeah so i think first and foremost super cloud as john was saying it's not multi-cloud chuck whitten had a great phrase at dell tech world he said multi-cloud by default right versus multi-cloud by design and multi-cloud has been by default it's been this sort of i run in aws and i run my stack in azure or i run my stack in gcp and it works or i wrap my stack in a container and host it in the cloud that's what multi-cloud has been so the first sort of concept is it's a layer that that abstracts the underlying complexity of all the clouds all the primitives uh it takes advantage of maybe graviton or microsoft tooling hides all that and builds new value on top of that the other piece of of super cloud is it's ecosystem driven really interesting story you just told because literally amazon can't hire everybody right so they have to rely on the ecosystem for feature acceleration so it's it also includes a path layer a super pass layer we call it because you need to develop applications that are specific to the problem that the super cloud is solving so it's not a generic path like openshift it's specific to whether it's snowflake or [ __ ] or aviatrix so that developers can actually build on top of and not have to worry about that underlying and also there's some people that are criticizing um what we're doing in a good way because we want to have an open concept sure but here's the thing that a lot of people don't understand they're criticizing or trying to kind of shoot holes in our new structural change that we're identifying to comparing it to old that's like saying mainframe and mini computers it's like saying well the mainframe does it this way therefore there's no way that's going to be legitimate so the old thinking dave is from people that have no real foresight in the new model right and so they don't really get it right so what i'm saying is that we look at structural change structural change is structural change it either happens or it doesn't so what we're observing is the fact that a snowflake didn't design their solution to be multi-cloud they did it all on aws and then said hey why would we why are we going to stop there let's go to azure because microsoft's got a boatload of customers because they have a vertically stacking integration for their install base so if i'm snowflake why wouldn't i be on azure and the same for gcp and the same for other things so this idea that you can get the value of an amp what amazon did leverage and all that value without paying for it up front is a huge dynamic and that's not just saying oh that's cloud that's saying i have a cloud-like scale cloud-like value proposition which which will look like an ecosystem so to me the acid test is if i build on top of say [ __ ] or say snowflake or super cloud by default i'm either a category leader i own the data at scale or i'm sharing data at scale and i have an ecosystem people are building on top of me so that's a platform so that's really difficult so what's happening is these ecosystem partners are taking advantage as john said of all the hyperscale capex and they're building out their version of a distributed global system and then the other attribute of super cloud is it's got metadata management capability in other words it knows if i'm optimizing for latency where in the super cloud to get the data or how to protect privacy or sovereignty or how many copies to make to have the proper data protection or where the air gap should be for ransomware so these are examples of very specific purpose-built super clouds that are filling gaps that the hyperscalers aren't going after what's a good example of a specific super cloud that you think really articulates what you guys are talking about i think there are a lot of them i think snowflake is a really good example i think vmware is building a multi-cloud management system i think aviatrix and virtual you know private cloud networking and for high performance networking i think to a certain extent what oracle is doing with azure is is is definitely looks like a super cloud i think what capital one is doing by building on to taking their own tools and and and moving that to snowflake now that they're not cross-cloud yet but i predict that they will be of i think uh what veeam is doing in data protection uh dell what they showed at dell tech world with project alpine these are all early examples of super well here's an indicator here's how you look at the example so to me if you're just lifting and shifting that was the first gen cloud that's not changing the business model so i think the number one thing to look at is is the company whether they're in a vertical like insurance or fintech or financial are they refactoring their spend not as an i.t cost but as a refactoring of their business model yes like what snowflake did dave or they say okay i'm gonna change how i operate not change my business model per se or not my business identity if i'm gonna provide financial services i don't have to spend capex it's operating expenses i get the capex leverage i redefine i get the data at scale and now i become a service provider to everybody else because scale will determine the power law of who wins in the verticals and in the industry so we believe that snowflake is a data warehouse in the cloud they call it a data cloud now i don't think snowflake would like that dave i call them a data warehouse no a super data cloud but but so the other key here is you know the old saying that andreessen came up with i guess with every company's a software company well what does that mean it means every company software company every company is going digital well how are they going to do that they're going to do that by taking their business their data their tooling their proprietary you know moat and moving that to the cloud so they can compete at scale every company should be if they're not thinking about doing a super cloud well walmart i think i think andreessen's wrong i think i would revise and say that andreessen and the brain trust at andreas and horowitz is that that's no longer irrelevant every company isn't a software company the software industry is called open source everybody is an open source company and every company will be at super cloud that survives yeah to me to me if you're not looking at super cloud as a strategy to get value and refactor your business model take advantage of what you're paying it for but you're paying now in a new way you're building out value so that's you're either going to be a super cloud or get services from a super cloud so if you're not it's like the old joke dave if you're at the table and you don't know who the sucker is it's probably you right so if you're looking at the marketplace you're saying if i'm not a super cloud i'm probably gonna have to work with one because they're gonna have the data they're gonna have the insights they're gonna have the scale they're going to have the castle in the cloud and they will be called a super cloud so in customer conversations helping customers identify workloads to move to the cloud what are the ideal workloads and services to run in super cloud so i honestly think virtually any workload could be a candidate and i think that it's really the business that they're in that's going to define the workload i'll say what i mean so there's certain businesses where low latency high performance transactions are going to matter that's you know kind of the oracle's business there's certain businesses like snowflake where data sharing is the objective how do i share data in a governed way in a secure way in any location across the world that i can monetize so that's their objective you take a data protection company like veeam their objective is to protect data so they have very specific objectives that ultimately dictate what the workload looks like couchbase is another one they they in my opinion are doing some of the most interesting things at the edge because this is where when you when you really push companies in the cloud including the hyperscalers when they get out to the far edge it starts to get a little squishy couchbase actually is developing capabilities to do that and that's to me that's the big wild card john i think you described it accurately the cloud is expanding you've got public clouds no longer just remote services you're including on-prem and now expanding out to the near edge and the deep what do you call it deep edge or far edge lower sousa called the tiny edge right deep edge well i mean look at look at amazon's outpost announcement to me hp e is opportunity dell has opportunities the hardware box guys companies they have an opportunity to be that gear to be an outpost to be their own output they get better stacks they have better gear they just got to run cloud on it yeah right that's an edge node right so so that's that would be part of the super cloud so this is where i think people that are looking at the old models like operating systems or systems mindsets from the 80s they look they're not understanding the new architecture what i would say to them is yeah i hear what you're saying but the structural change is the nodes on the network distributed computing if you will is going to run hybrid cloud all the way across the fact that it's multiple clouds is just coincidence on who's got the best capex value that people build on for their super cloud capability so why wouldn't i be on azure if microsoft's going to give me all their customers that are running office 365 and teams great if i want to be on amazon's kind of sweet which is their ecosystem why wouldn't i want to tap into that so again you can patch it all together in the super cloud so i think the future will be distributed computing cloud architecture end to end and and we felt that was different from multi-cloud you know if you want to call it multi-cloud 2.0 that's fine but you know frankly you know sometimes we get criticized for not defining it tightly enough but we continue to evolve that definition i've never really seen a great definition from multi-cloud i think multi-cloud by default was the definition i run in multiple clouds you know it works in azure it's not a strategy it's a broken name it's a symptom right it's a symptom of multi-vendor is really what multi-cloud has been and so we felt like it was a new term of examples look what we're talking about snowflake data bricks databricks another good one these are these are examples goldman sachs and we felt like the term immediately connotes something bigger something that sits above the clouds and is part of a digital platform you know the people poo poo the metaverse because it's really you know not well defined but every 15 or 20 years this industry goes through dave let me ask you a question so uh lisa you too if i'm in the insurance vertical uh and i'm a i'm an insurance company i have competitors my customers can go there and and do business with that company and you know and they all know that they go to the same conferences but in that sector now you have new dynamics your i.t spend isn't going to keep the lights on and make your apps work your back-end systems and your mobile app to get your whatever now it's like i have cloud scale so what if i refactored my business model become a super cloud and become the major primary service provider to all the competitors and the people that are the the the channel partners of the of the ecosystem that means that company could change the category totally okay and become the dominant category leader literally in two three years if i'm geico okay i i got business in the cloud because i got the app and i'm doing transactions on geico but with all the data that they're collecting there's adjacent businesses that they can get into maybe they're in the safety business maybe they can sell data to governments maybe they can inform logistics and highway you know patterns roll up all the people that don't have the same scale they have and service them with that data and they get subscription revenue and they can build on top of the geico super insurance cloud right yes it's it's unlimited opportunity that's why it's but the multi-trillion dollar baby so talk to us you've done an amazing job of talking which i know you would of why super cloud what it is the critical components the key workloads great examples talk to us in our last few minutes about the event the cube on super cloud august 9th what's the audience going to who are they going to hear from what are they going to learn yeah so august 9th live out of our palo alto studio we're going to have a program that's going to run from 9 a.m to 1 p.m and we're going to have a number of industry luminaries in there uh kit colbert from from vmware is going to talk about you know their strategy uh benoit de javille uh from snowflake is going to is going to be there of g written house of sky-high security um i i i don't want to give it away but i think steve mullaney is going to come on adrian uh cockroft is coming on the panel keith townsend sanjeev mohan will be on so we'll be running that live and also we'll be bringing in pre-recorded interviews that we'll have prior to the show that will run post the live event it's really a pilot virtual event we want to do a physical event we're thinking but the pilot is to bring our trusted friends together they're credible that have industry experience to try to understand the scope of what we're talking about and open it up and help flesh out the definition make it an open model where we can it's not just our opinion we're observing identifying the structural changes but bringing in smart people our smart friends and companies are saying yeah we get behind this because it has it has legs for a reason so we're gonna zoom out and let people participate and let the conversation and the community drive the content and that is super important to the cube as you know dave but i think that's what's going on lisa is that it's a pilot if it has legs we'll do a physical event certainly we're getting phones to bring it off the hook for sponsors so we don't want to go and go all in on sponsorships right now because it's not about money making it's about getting that super cloud clarity around to help companies yeah we want to evolve the concept and and bring in outside perspectives well the community is one of the best places to do that absolutely organic it's an organic community where i mean people want to find out what's going on with the best practices of how to transform a business and right now digital transformation is not just getting digitized it's taking advantage of the technology to leapfrog the competition so all the successful people we talked to at least have the same common theme i'm changing my game but not changing my game to the customer i'm just going to do it differently better faster cheaper more efficient and have higher margins and beat the competition that's the company doesn't want to beat the competition go to thecube.net if you're not all they're all ready to register for the cube on supercloud august 9th 9am pacific you won't want to miss it for john furrier and dave vellante i'm lisa martin we're all coming at you from new york city at aws summit 22. i'll be right back with our next guest [Music] you

(bright upbeat music) >> We're back at the Red Hat Summit at the Seaport in Boston, theCUBE's coverage. This is day two. Dave Vellante and Paul Gillin. Chris Wright is here, the chief technology officer at Red Hat. Chris, welcome back to theCUBE. Good to see you. >> Yeah, likewise. Thanks for having me. >> You're very welcome. So, you were saying today in your keynote. We got a lot of ground to cover here, Chris. You were saying that, you know, software, Andreessen's software is eating the world. Software ate the world, is what you said. And now we have to think about AI. AI is eating the world. What does that mean? What's the implication for customers and developers? >> Well, a lot of implications. I mean, to start with, just acknowledging that software isn't this future dream. It is the reality of how businesses run today. It's an important part of understanding what you need to invest in to make yourself successful, essentially, as a software company, where all companies are building technology to differentiate themselves. Take that, all that discipline, everything we've learned in that context, bring in AI. So, we have a whole new set of skills to learn, tools to create and discipline processes to build around delivering data-driven value into the company, just the way we've built software value into companies. >> I'm going to cut right to the chase because I would say data is eating software. Data and AI, to me, are like, you know, kissing cousins. So here's what I want to ask you as a technologist. So we have the application development stack, if you will. And it's separate from the data and analytics stack. All we talk about is injecting AI into applications, making them data-driven. You just used that term. But they're totally two totally separate stacks, organizationally and technically. Are those worlds coming together? Do they have to come together in order for the AI vision to be real? >> Absolutely, so, totally agree with you on the data piece. It's inextricably linked to AI and analytics and all of the, kind of, machine learning that goes on in creating intelligence for applications. The application connection to a machine learning model is fundamental. So, you got to think about not just the software developer or the data scientist, but also there's a line of business in there that's saying, "Here's the business outcomes I'm looking for." It's that trifecta that has to come together to make advancements and really make change in the business. So, you know, some of the folks we had on stage today were talking about exactly that. Which is, how do you bring together those three different roles? And there's technology that can help bridge gaps. So, we look at what we call intelligent applications. Embed intelligence into the application. That means you surface a machine learning model with APIs to make it accessible into applications, so that developers can query a machine learning model. You need to do that with some discipline and rigor around, you know, what does it mean to develop this thing and life cycle it and integrate it into this bigger picture. >> So the technology is capable of coming together. You know, Amanda Purnell is coming on next. >> Oh, great. >> 'Cause she was talking about, you know, getting, you know, insights in the hands of nurses and they're not coders. >> That's right. >> But they need data. But I feel like it's, well, I feel very strongly that it's an organizational challenge, more so. I think you're confirming. It's not really a technical challenge. I can insert a column into the application development stack and bring TensorFlow in or AI or data, whatever it is. It's not a technical issue. Is that fair? >> Well, there are some technical challenges. So, for example, data scientists. Kind of a scarce kind of skillset within any business. So, how do you scale data scientists into the developer population? Which will be a large population within an organization. So, there's tools that we can use to bring those worlds together. So, you know, it's not just TensorFlow but it's the entire workflow and platform of how you share the data, the data training models and then just deploying models into a runtime production environment. That looks similar to software development processes but it's slightly different. So, that's where a common platform can help bridge the gaps between that developer world and the data science world. >> Where is Red Hat's position in this evolving AI stack? I mean, you're not into developing tool sets like TensorFlow, right? >> Yeah, that's right. If you think about a lot of what we do, it's aggregate content together, bring a distribution of tools, giving flexibility to the user. Whether that's a developer, a system administrator, or a data scientist. So our role here is, one, make sure we work with our hardware partners to create accelerated environments for AI. So, that's sort of an enablement thing. The other is bring together those disparate tools into a workflow and give a platform that enables data scientists to choose which, is it PyTorch, is it TensorFlow? What's the best tool for you? And assemble that tool into your workflow and then proceed training, doing inference, and, you know, tuning and lather, rinse, repeat. >> So, to make your platform then, as receptive as possible, right? You're not trying to pick winners in what languages to work with or what frameworks? >> Yeah, that's right. I mean, picking winners is difficult. The world changes so rapidly. So we make big bets on key areas and certainly TensorFlow would be a great example. A lot of community attraction there. But our goal isn't to say that's the one tool that everybody should use. It's just one of the many tools in your toolbox. >> There are risks of not pursuing this, from an organization's perspective. A customer, they kind of get complacent and, you know, they could get disrupted, but there's also an industry risk. If the industry can't deliver this capability, what are the implications if the industry doesn't step up? I believe the industry will, just 'cause it always does. But what about customer complacency? We certainly saw that a lot with digital transformation and COVID sort of forced us to march to digital. What should we be thinking about of the implications of not leaning in? >> Well, I think that the disruption piece is key because there's always that spectrum of businesses. Some are more leaning in, invested in the future. Some are more laggards and kind of wait and see. Those leaning in tend to be separating themselves, wheat from the chaff. So, that's an important way to look at it. Also, if you think about it, many data science experiments fail within businesses. I think part of that is not having the rigor and discipline around connecting, not just the tools and data scientists together, but also looking at what business outcomes are you trying to drive? If you don't bring those things together then it sort of can be too academic and the business doesn't see the value. And so there's also the question of transparency. How do you understand why is a model predicting you should take a certain action or do a certain thing? As an industry, I think we need to focus on bringing tools together, bringing data together, and building better transparency into how models work. >> There's also a lot of activity around governance right now, AI governance. Particularly removing bias from ML models. Is that something that you are guiding your customers on? Or, how important do you feel this is at this point of AI's development? >> It's really important. I mean, the challenge is finding it and understanding, you know, we bring data that maybe already carrying a bias into a training process and building a model around that. How do you understand what the bias is in that model? There's a lot of open questions there and academic research to try to understand how you can ferret out, you know, essentially biased data and make it less biased or unbiased. Our role is really just bringing the toolset together so that you have the ability to do that as a business. So, we're not necessarily building the next machine learning algorithm or models or ways of building transparency into models, as much as building the platform and bringing the tools together that can give you that for your own organization. >> So, it brings up the question of architectures. I've been sort of a casual or even active observer of data architectures over the last, whatever, 15 years. They've been really centralized. Our data teams are highly specialized. You mentioned data scientists, but there's data engineers and there's data analysts and very hyper specialized roles that don't really scale that well. So there seems to be a move, talk about edge. We're going to talk about edge. The ultimate edge, which is space, very cool. But data is distributed by its very nature. We have this tendency to try to force it into this, you know, monolithic system. And I know that's a pejorative, but for good reason. So I feel like there's this push in organizations to enable scale, to decentralize data architectures. Okay, great. And put data in the hands of those business owners that you talked about earlier. The domain experts that have business context. Two things, two problems that brings up, is you need infrastructure that's self-service, in that instance. And you need, to your point, automated and computational governance. Those are real challenges. What do you see in terms of the trends to decentralize data architectures? Is it even feasible that everybody wants a single version of the truth, centralized data team, right? And they seem to be at odds. >> Yeah, well I think we're coming from a history informed by centralization. That's what we understand. That's what we kind of gravitate towards, but the reality, as you put it, the world's just distributed. So, what we can do is look at federation. So, it's not necessarily centralization but create connections between data sources which requires some policy and governance. Like, who gets access to what? And also think about those domain experts maybe being the primary source of surfacing a model that you don't necessarily have to know how it was trained or what the internals are. You're using it more to query it as a, you know, the domain expert produces this model, you're in a different part of the organization just leveraging some work that somebody else has done. Which is how we build software, reusable components in software. So, you know, I think building that mindset into data and the whole process of creating value from data is going to be a really critical part of how we roll forward. >> So, there are two things in your keynote. One, that I was kind of in awe of. You wanted to be an astronaut when you were a kid. You know, I mean, I watched the moon landing and I was like, "I'm never going up into space." So, I'm in awe of that. >> Oh, I got the space helmet picture and all that. >> That's awesome, really, you know, hat's off to you. The other one really pissed me off, which was that you're a better skier 'cause you got some device in your boot. >> Oh, it's amazing. >> And the reason it angered me is 'cause I feel like it's the mathematicians taking over baseball, you know. Now, you're saying, you're a better skier because of that. But those are two great edge examples and there's a billion of them, right? So, talk about your edge strategy. Kind of, your passion there, how you see that all evolving. >> Well, first of all, we see the edge as a fundamental part of the future of computing. So in that centralization, decentralization pendulum swing, we're definitely on the path towards distributed computing and that is edge and that's because of data. And also because of the compute capabilities that we have in hardware. Hardware gets more capable, lower power, can bring certain types of accelerators into the mix. And you really create this world where what's happening in a virtual context and what's happening in a physical context can come together through this distributed computing system. Our view is, that's hybrid. That's what we've been working on for years. Just the difference was maybe, originally it was focused on data center, cloud, multi-cloud and now we're just extending that view out to the edge and you need the same kind of consistency for development, for operations, in the edge that you do in that hybrid world. So that's really where we're placing our focus and then it gets into all the different use cases. And you know, really, that's the fun part. >> I'd like to shift gears a little bit 'cause another remarkable statistic you cited during your keynote was, it was a Forrester study that said 99% of all applications now have open source in them. What are the implications of that for those who are building applications? In terms of license compliance and more importantly, I think, confidence in the code that they're borrowing from open source projects. >> Well, I think, first and foremost, it says open source has won. We see that that was audited code bases which means there's mission critical code bases. We see that it's pervasive, it's absolutely everywhere. And that means developers are pulling dependencies into their applications based on all of the genius that's happening in open source communities. Which I think we should celebrate. Right after we're finished celebrating we got to look at what are the implications, right? And that shows up as, are there security vulnerabilities that become ubiquitous because we're using similar dependencies? What is your process for vetting code that you bring into your organization and push into production? You know that process for the code you author, what about your dependencies? And I think that's an important part of understanding and certainly there are some license implications. What are you required to do when you use that code? You've been given that code on a license from the open source community, are you compliant with that license? Some of those are reasonably well understood. Some of those are, you know, newer to the enterprise. So I think we have to look at this holistically and really help enterprises build safe application code that goes into production and runs their business. >> We saw Intel up in the keynotes today. We heard from Nvidia, both companies are coming on. We know you've done a lot of work with ARM over the years. I think Graviton was one of the announcements this week. So, love to see that. I want to run something by you as a technologist. The premise is, you know, we used to live in this CPU centric world. We marched to the cadence of Moore's Law and now we're seeing the combinatorial factors of CPU, GPU, NPU, accelerators and other supporting components. With IO and controllers and NICs all adding up. It seems like we're shifting from a processor centric world to a connect centric world on the hardware side. That first of all, do you buy that premise? And does hardware matter anymore with all the cloud? >> Hardware totally matters. I mean the cloud tried to convince us that hardware doesn't matter and it actually failed. And the reason I say that is because if you go to a cloud, you'll find 100s of different instance types that are all reflections of different types of assemblies of hardware. Faster IO, better storage, certain sizes of memory. All of that is a reflection of, applications need certain types of environments for acceleration, for performance, to do their job. Now I do think there's an element of, we're decomposing compute into all of these different sort of accelerators and the only way to bring that back together is connectivity through the network. But there's also SOCs when you get to the edge where you can integrate the entire system onto a pretty small device. I think the important part here is, we're leveraging hardware to do interesting work on behalf of applications that makes hardware exciting. And as an operating system geek, I couldn't be more thrilled, because that's what we do. We enable hardware, we get down into the bits and bytes and poke registers and bring things to life. There's a lot happening in the hardware world and applications can't always follow it directly. They need that level of indirection through a software abstraction and that's really what we're bringing to life here. >> We've seen now hardware specific AI, you know, AI chips and AI SOCs emerge. How do you make decisions about what you're going to support or do you try to support all of them? >> Well, we definitely have a breadth view of support and we're also just driven by customer demand. Where our customers are interested we work closely with our partners. We understand what their roadmaps are. We plan together ahead of time and we know where they're making investments and we work with our customers. What are the best chips that support their business needs and we focus there first but it ends up being a pretty broad list of hardware that we support. >> I could pick your brain for an hour. We didn't even get into super cloud, Chris. But, thanks so much for coming on theCUBE. It's great to have you. >> Absolutely, thanks for having me. >> All right. Thank you for watching. Keep it right there. Paul Gillin, Dave Vellante, theCUBE's live coverage of Red Hat Summit 2022 from Boston. We'll be right back. (mellow 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)

(upbeat music) >> Welcome, everyone, to theCUBE's presentation of the AWS Startup Showcase. And this episode two of season two is called "Data as Code," the ongoing series covering exciting new startups in the AWS ecosystem. I'm John Furrier, your host of theCUBE. Today, we're excited to be joined by Jon Dahl, who is the co-founder and CEO of MUX, a hot new startup building cloud video for developers, video with data. John, great to see you. We did an interview on theCube Conversation. Went into big detail of the awesomeness of your company and the trend that you're on. Welcome back. >> Thank you, glad to be here. >> So, video is everywhere, and video for pivot to video, you hear all these kind of terms in the industry, but now more than ever, video is everywhere and people are building with it, and it's becoming part of the developer experience in applications. So people have to stand up video into their code fast, and data is code, video is data. So you guys are specializing this. Take us through that dynamic. >> Yeah, so video clearly is a growing part of how people are building applications. We see a lot of trends of categories that did not involve video in the past making a major move towards video. I think what Peloton did five years ago to the world of fitness, that was not really a big category. Now video fitness is a huge thing. Video in education, video in business settings, video in a lot of places. I think Marc Andreessen famously said, "Software is eating the world" as a pretty, pretty good indicator of what the internet is actually doing to the economy. I think there's a lot of ways in which video right now is eating software. So categories that we're not video first are becoming video first. And that's what we help with. >> It's not obvious to like most software developers when they think about video, video industries, it's industry shows around video, NAB, others. People know, the video folks know what's going on in video, but when you start to bring it mainstream, it becomes an expectation in the apps. And it's not that easy, it's almost a provision video is hard for a developer 'cause you got to know the full, I guess, stack of video. That's like low level and then kind of just basic high level, just play something. So, in between, this is a media stack kind of dynamic. Can you talk about how hard it is to build video for developers? How is it going to become easier? >> Yeah, I mean, I've lived this story for too long, maybe 13 years now, when I first build my first video stack. And, you know, I'll sometimes say, I think it's kind of a miracle every time a video plays on the internet because the internet is not a medium designed for video. It's been hijacked by video, video is 70% of internet traffic today in an unreliable, sort of untrusted network space, which is totally different than how television used to work or cable or things like that. So yeah, so video is hard because there's so many problems from top to bottom that need to be solved to make video work. So you have to worry about video compression encoding, which is a complicated topic in itself. You have to worry about delivering video around the world at scale, delivering it at low cost, at low latency, with good performance, you have to worry about devices and how every device, Android, iOS, web, TVs, every device handles video differently and so there's a lot of work there. And at the end of the day, these are kind of unofficial standards that everyone's using. So one of the miracles is like, if you want to watch a video, somehow you have to get like Apple and Google to agree on things, which is not always easy. And so there's just so many layers of complexity that are behind it. I think one way to think about it is, if you want to put an image online, you just put an image online. And if you want to put video online, you build complex software, and that's the exact problem that MUX was started to help solve. >> It's interesting you guys have almost creating a whole new category around video infrastructure. And as you look at, you mentioned stack, video stack. I'm looking at a market where the notion of a media stack is developing, and you're seeing these verticals having similar dynamics with cloud. And if you go back to the early days of cloud computing, what was the developer experience or entrepreneurial experience, you had to actually do a lot of stuff before you even do anything, provision a server. And this has all kind of been covered in great detail in the glory of Agile and whatnot. It was expensive, and you had that actually engineer before you could even stand up any code. Now you got video that same thing's happening. So the developers have two choices, go do a bunch of stuff complex, building their own infrastructure, which is like building a data center, or lean in on MUX and say, "Hey, thank you for doing all that years of experience building out the stacks to take that hard part away," but using APIs that they have. This is a developer focused problem that you guys are solving. >> Yeah, that's right. my last company was a company called Zencoder, that was an API to video encoding. So it was kind of an API to a small part of what MUX does today, just one of those problems. And I think the thing that we got right at Zencoder, that we're doing again here at MUX, was building four developers first. So our number one persona is a software developer. Not necessarily a video expert, just we think any developer should be able to build with video. It shouldn't be like, yeah, got to go be a specialist to use this technology, because it should become just of the internet. Video should just be something that any developer can work with. So yeah, so we build for developers first, which means we spend a lot of time thinking about API design, we spend a lot of time thinking about documentation, transparent pricing, the right features, great support and all those kind of things that tend to be characteristics of good developer companies. >> Tell me about the pipe lining of the products. I'm a developer, I work for a company, my boss is putting pressure on me. We need video, we have all this library, it's all stacking up. We hired some people, they left. Where's the video, we've stored it somewhere. I mean, it's a nightmare, right? So I'm like, okay, I'm cloud native, I got an API. I need to get my product to market fast, 'cause that is what Agile developers want. So how do you describe that acceleration for time to market? You mentioned you guys are API first, video first. How do these customers get their product into the market as fast as possible? >> Yeah, well, I mean the first thing we do is we put what we think is probably on average, three to four months of hard engineering work behind a single API call. So if you want to build a video platform, we tell our customers like, "Hey, you can do that." You probably need a team, you probably need video experts on your team so hire them or train them. And then it takes several months just to kind of to get video flowing. One API call at MUX gives you on-demand video or live video that works at scale, works around the world with good performance, good reliability, a rich feature set. So maybe just a couple specific examples, we worked with Robin Hood a few years ago to bring video into their newsfeed, which was hugely successful for them. And they went from talking to us for the first time to a big launch in, I think it was three months, but the actual code time there was like really short. I want to say they had like a proof of concept up and running in a couple days, and then the full launch in three months. Another customer of ours, Bandcamp, I think switched from a legacy provider to MUX in two weeks in band. So one of the big advantages of going a little bit higher in the abstraction layer than just building it yourself is that time to market. >> Talk about this notion of video pipeline 'cause I know I've heard people I talk about, "Hey, I just want to get my product out there. I don't want to get stuck in the weeds on video pipeline." What does that mean for folks that aren't understanding the nuances of video? >> Yeah, I mean, it's all the steps that it takes to publish video. So from ingesting the video, if it's live video from making sure that you have secure, reliable ingest of that live feed potentially around the world to the transcoding, which is we talked a little bit about, but it is a, you know, on its own is a massively complicated problem. And doing that, well, doing that well is hard. Part of the reason it's hard is you really have to know where you're publishing too. And you might want to transcode video differently for different devices, for different types of content. You know, the pipeline typically would also include all of the workflow items you want to do with the video. You want to thumbnail a video, you want clip, create clips of the video, maybe you want to restream the video to Facebook or Twitter or a social platform. You want to archive the video, you want it to be available for downloads after an event. If it's just a, if it's a VOD upload, if it's not live in the first place. You have all those things and you might want to do simulated live with the video. You might want to actually record something and then play it back as a live stream. So, the pipeline Ty typically refers to everything from the ingest of the video to the time that the bits are delivered to a device. >> You know, I hear a lot of people talking about video these days, whether it's events, training, just want peer to peer experience, video is powerful, but customers want to own their own platform, right? They want to have the infrastructure as a service. They kind of want platform as a service, this is cloud talk now, but they want to have their own capability to build it out. This allows them to get what they want. And so you see this, like, is it SaaS? Is it platform? People want customization? So kind of the general purpose video solution does it really exist or doesn't? I mean, 'cause this is the question. Can I just buy software and work or is it going to be customized always? How do you see that? Because this becomes a huge discussion point. Is it a SaaS product or someone's going to make a SaaS product? >> Yeah, so I think one of the most important elements of designing any software, but especially when you get into infrastructure is choosing an abstraction level. So if you think of computing, you can go all the way down to building a data center, you can go all the way down to getting a colo and racking a server like maybe some of us used to do, who are older than others. And that's one way to run a server. On the other extreme, you have just think of the early days of cloud competing, you had app engine, which was a really fantastic, really incredible product. It was one push deploy of, I think Python code, if I remember correctly, and everything just worked. But right in the middle of those, you had EC2, which was, EC2 is basically an API to a server. And it turns out that that abstraction level, not Colo, not the full app engine kind of platform, but the API to virtual server was the right abstraction level for maybe the last 15 years. Maybe now some of the higher level application platforms are doing really well, maybe the needs will shift. But I think that's a little bit of how we think about video. What developers want is an API to video. They don't want an API to the building blocks of video, an API to transcoding, to video storage, to edge caching. They want an API to video. On the other extreme, they don't want a big application that's a drop in white label video in a box like a Shopify kind of thing. Shopify is great, but developers don't want to build on top of Shopify. In the payments world developers want Stripe. And that abstraction level of the API to the actual thing you're getting tends to be the abstraction level that developers want to build on. And the reason for that is, it's the most productive layer to build on. You get maximum flexibility and also maximum velocity when you have that API directly to a function like video. So, we like to tell our customers like you, you own your video when you build on top of MUX, you have full control over everything, how it's stored, when it's stored, where it goes, how it's published, we handle all of the hard technology and we give our customers all of the flexibility in terms of designing their products. >> I want to get back some use case, but you brought that up I might as well just jump to my next point. I'd like you to come back and circle back on some references 'cause I know you have some. You said building on infrastructure that you own, this is a fundamental cloud concept. You mentioned API to a server for the nerds out there that know that that's cool, but the people who aren't super nerdy, that means you're basically got an interface into a server behind the scenes. You're doing the same for video. So, that is a big thing around building services. So what wide range of services can we expect beyond MUX? If I'm going to have an API to video, what could I do possibly? >> What sort of experience could you build? >> Yes, I got a team of developers saying I'm all in API to video, I don't want to do all that transit got straight there, I want to build experiences, video experiences on my app. >> Yeah, I mean, I think, one way to think about it is that, what's the range of key use cases that people do with video? We tend to think about six at MUX, one is kind of the places where the content is, the prop. So one of the things that use video is you can create great video. Think of online courses or fitness or entertainment or news or things like that. That's kind of the first thing everyone thinks of, when you think video, you think Netflix, and that's great. But we see a lot of really interesting uses of video in the world of social media. So customers of ours like Visco, which is an incredible photo sharing application, really for photographers who really care about the craft. And they were able to bring video in and bring that same kind of Visco experience to video using MUX. We think about B2B tools, videos. When you think about it, all video is, is a high bandwidth way of communicating. And so customers are as like HubSpot use video for the marketing platform, for business collaboration, you'll see a lot of growth of video in terms of helping businesses engage their customers or engage with their employees. We see live events obviously have been a massive category over the last few years. You know, we were all forced into a world where we had to do live events two years ago, but I think now we're reemerging into a world where the online part of a conference will be just as important as the in-person component of a conference. So that's another big use case we see. >> Well, full disclosure, if you're watching this live right now, it's being powered by MUX. So shout out, we use MUX on theCUBE platform that you're experiencing in this. Actually in real time, 'cause this is one application, there's many more. So video as code, is data as code is the theme, that's going to bring up the data ops. Video also is code because (laughs) it's just like you said, it's just communicating, but it gets converted to data. So data ops, video ops could be its own new category. What's your reaction to that? >> Yeah, I mean, I think, I have a couple thoughts on that. The first thought is, video is a way that, because the way that companies interact with customers or users, it's really important to have good monitoring and analytics of your video. And so the first product we ever built was actually a product called MUX video, sorry, MUX data, which is the best way to monitor a video platform at scale. So we work with a lot of the big broadcasters, we work with like CBS and Fox Sports and Discovery. We work with big tech companies like Reddit and Vimeo to help them monitor their video. And you just get a huge amount of insight when you look at robust analytics about video delivery that you can use to optimize performance, to make sure that streaming works well globally, especially in hard to reach places or on every device. That's we actually build a MUX data platform first because when we started MUX, we spent time with some of our friends at companies like YouTube and Netflix, and got to know how they use data to power their video platforms. And they do really sophisticated things with data to ensure that their streams well, and we wanted to build the product that would help everyone else do that. So, that's one use. I think the other obvious use is just really understanding what people are doing with their video, who's watching what, what's engaging, those kind of things. >> Yeah, data is definitely there. You guys mentioned some great brands that are working with you guys, and they're doing it because of the developer experience. And I'd like you to explain, if you don't mind, in your words, why is the MUX developer experience so good? What are some of the results you're seeing from your customers? What are they saying to you? Obviously when you win, you get good feedback. What are some of the things that they're saying and what specific develop experiences do they like the best? >> Yeah, I mean, I think that the most gratifying thing about being a startup founder is when your customers like what you're doing. And so we get a lot of this, but it's always, we always pay attention to what customers say. But yeah, people, the number one thing developers say when they think about MUX is that the developer experience is great. I think when they say that, what they mean is two things, first is it's easy to work with, which helps them move faster, software velocity is so important. Every company in the world is investing and wants to move quickly and to build quickly. And so if you can help a team speed up, that's massively valuable. The second thing I think when people like our developer experience is, you know, in a lot of ways that think that we get out of the way and we let them do what they want to do. So well, designed APIs are a key part of that, coming back to abstraction, making sure that you're not forcing customers into decisions that they actually want to make themselves. Like, if our video player only had one design, that that would not be, that would not work for most developers, 'cause developers want to bring their own design and style and workflow and feel to their video. And so, yeah, so I think the way we do that is just think comprehensively about how APIs are designed, think about the workflows that users are trying to accomplish with video, and make sure that we have the right APIs, make sure they're the right information, we have the right webhooks, we have the right SDKs, all of those things in place so that they can build what they want. >> We were just having a conversation on theCUBE, Dave Vellante and I, and our team, and I'd love to get you a reaction to this. And it's more and more, a riff real quick. We're seeing a trend where video as code, data as code, media stack, where you're starting to see the emergence of the media developer, where the application of media looks a lot like kind of software developer, where the app, media as an app. It could be a chat, it could be a peer to peer video, it could be part of an event platform, but with all the recent advances, in UX designers, coders, the front end looks like an emergence of these creators that are essentially media developers for all intent and purpose, they're coding media. What's your reaction to that? How do you see that evolving? >> I think the. >> Or do you agree with it? >> It's okay. >> Yeah, yeah. >> Well, I think a couple things. I think one thing, I think this goes along through saying, but maybe it's disagreement, is that we don't think you should have to be an expert at video or at media to create and produce or create and publish good video, good audio, good images, those kind of things. And so, you know, I think if you look at software overall, I think of 10 years ago, the kind of DevOps movement, where there was kind of a movement away from specialization in software where the same software developer could build and deploy the same software developer maybe could do front end and back end. And we want to bring that to video as well. So you don't have to be a specialist to do it. On the other hand, I do think that investments and tooling, all the way from video creation, which is not our world, but there's a lot of amazing companies out there that are making it easier to produce video, to shoot video, to edit, a lot of interesting innovations there all the way to what we do, which is helping people stream and publish video and video experiences. You know, I think another way about it is, that tool set and companies doing that let anyone be a media developer, which I think is important. >> It's like DevOps turning into low-code, no-code, eventually it's just composability almost like just, you know, "Hey Siri, give me some video." That kind of thing. Final question for you why I got you here, at the end of the day, the decision between a lot of people's build versus buy, "I got to get a developer. Why not just roll my own?" You mentioned data center, "I want to build a data center." So why MUX versus do it yourself? >> Yeah, I mean, part of the reason we started this company is we have a pretty, pretty strong opinion on this. When you think about it, when we started MUX five years ago, six years ago, if you were a developer and you wanted to accept credit cards, if you wanted to bring payment processing into your application, you didn't go build a payment gateway. You just probably used Stripe. And if you wanted to send text messages, you didn't build your own SMS gateway, you probably used Twilio. But if you were a developer and you wanted to stream video, you built your own video gateway, you built your own video application, which was really complex. Like we talked about, you know, probably three, four months of work to get something basic up and running, probably not live video that's probably only on demand video at that point. And you get no benefit by doing it yourself. You're no better than anyone else because you rolled your own video stack. What you get is risk that you might not do a good job, maybe you do worse than your competitors, and you also get distraction where you've just taken, you take 10 engineers and 10 sprints and you apply it to a problem that doesn't actually really give you differentiated value to your users. So we started MUX so that people would not have to do that. It's fine if you want to build your own video platform, once you get to a certain scale, if you can afford a dozen engineers for a VOD platform and you have some really massively differentiated use case, you know, maybe, live is, I don't know, I don't have the rule of thumb, live videos maybe five times harder than on demand video to work with. But you know, in general, like there's such a shortage of software engineers today and software engineers have, frankly, are in such high demand. Like you see what happens in the marketplace and the hiring markets, how competitive it is. You need to use your software team where they're maximally effective, and where they're maximally effective is building differentiation into your products for your customers. And video is just not that, like very few companies actually differentiate on their video technology. So we want to be that team for everyone else. We're 200 people building the absolute best video infrastructure as APIs for developers and making that available to everyone else. >> John, great to have you on with the showcase, love the company, love what you guys do. Video as code, data as code, great stuff. Final plug for the company, for the developers out there and prospects watching for MUX, why should they go to MUX? What are you guys up to? What's the big benefit? >> I mean, first, just check us out. Try try our APIs, read our docs, talk to our support team. We put a lot of work into making our platform the best, you know, as you dig deeper, I think you'd be looking at the performance around, the global performance of what we do, looking at our analytics stack and the insight you get into video streaming. We have an emerging open source video player that's really exciting, and I think is going to be the direction that open source players go for the next decade. And then, you know, we're a quickly growing team. We're 60 people at the beginning of last year. You know, we're one 50 at the beginning of this year, and we're going to a add, we're going to grow really quickly again this year. And this whole team is dedicated to building the best video structure for developers. >> Great job, Jon. Thank you so much for spending the time sharing the story of MUX here on the show, Amazon Startup Showcase season two, episode two, thanks so much. >> Thank you, John. >> Okay, I'm John Furrier, your host of theCUBE. This is season two, episode two, the ongoing series cover the most exciting startups from the AWS Cloud Ecosystem. Talking data analytics here, video cloud, video as a service, video infrastructure, video APIs, hottest thing going on right now, and you're watching it live here on theCUBE. Thanks for watching. (upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> The pandemic has changed the way we think about and predict the future. As we enter the third year of a global pandemic, we see the significant impact that it's had on technology strategy, spending patterns, and company fortunes Much has changed. And while many of these changes were forced reactions to a new abnormal, the trends that we've seen over the past 24 months have become more entrenched, and point to the way that's coming ahead in the technology business. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we welcome our partner and colleague and business friend, Erik Porter Bradley, as we deliver what's becoming an annual tradition for Erik and me, our predictions for Enterprise Technology in 2022 and beyond Erik, welcome. Thanks for taking some time out. >> Thank you, Dave. Luckily we did pretty well last year, so we were able to do this again. So hopefully we can keep that momentum going. >> Yeah, you know, I want to mention that, you know, we get a lot of inbound predictions from companies and PR firms that help shape our thinking. But one of the main objectives that we have is we try to make predictions that can be measured. That's why we use a lot of data. Now not all will necessarily fit that parameter, but if you've seen the grading of our 2021 predictions that Erik and I did, you'll see we do a pretty good job of trying to put forth prognostications that can be declared correct or not, you know, as black and white as possible. Now let's get right into it. Our first prediction, we're going to go run into spending, something that ETR surveys for quarterly. And we've reported extensively on this. We're calling for tech spending to increase somewhere around 8% in 2022, we can see there on the slide, Erik, we predicted spending last year would increase by 4% IDC. Last check was came in at five and a half percent. Gardner was somewhat higher, but in general, you know, not too bad, but looking ahead, we're seeing an acceleration from the ETR September surveys, as you can see in the yellow versus the blue bar in this chart, many of the SMBs that were hard hit by the pandemic are picking up spending again. And the ETR data is showing acceleration above the mean for industries like energy, utilities, retail, and services, and also, notably, in the Forbes largest 225 private companies. These are companies like Mars or Koch industries. They're predicting well above average spending for 2022. So Erik, please weigh in here. >> Yeah, a lot to bring up on this one, I'm going to be quick. So 1200 respondents on this, over a third of which were at the C-suite level. So really good data that we brought in, the usual bucket of, you know, fortune 500, global 2000 make up the meat of that median, but it's 8.3% and rising with momentum as we see. What's really interesting right now is that energy and utilities. This is usually like, you know, an orphan stock dividend type of play. You don't see them at the highest point of tech spending. And the reason why right now is really because this state of tech infrastructure in our energy infrastructure needs help. And it's obvious, remember the Florida municipality break reach last year? When they took over the water systems or they had the ability to? And this is a real issue, you know, there's bad nation state actors out there, and I'm no alarmist, but the energy and utility has to spend this money to keep up. It's really important. And then you also hit on the retail consumer. Obviously what's happened, the work from home shift created a shop from home shift, and the trends that are happening right now in retail. If you don't spend and keep up, you're not going to be around much longer. So I think the really two interesting things here to call out are energy utilities, usually a laggard in IT spend and it's leading, and also retail consumer, a lot of changes happening. >> Yeah. Great stuff. I mean, I recall when we entered the pandemic, really ETR was the first to emphasize the impact that work from home was going to have, so I really put a lot of weight on this data. Okay. Our next prediction is we're going to get into security, it's one of our favorite topics. And that is that the number one priority that needs to be addressed by organizations in 2022 is security and you can see, in this slide, the degree to which security is top of mind, relative to some other pretty important areas like cloud, productivity, data, and automation, and some others. Now people may say, "Oh, this is obvious." But I'm going to add some context here, Erik, and then bring you in. First, organizations, they don't have unlimited budgets. And there are a lot of competing priorities for dollars, especially with the digital transformation mandate. And depending on the size of the company, this data will vary. For example, while security is still number one at the largest public companies, and those are of course of the biggest spenders, it's not nearly as pronounced as it is on average, or in, for example, mid-sized companies and government agencies. And this is because midsized companies or smaller companies, they don't have the resources that larger companies do. Larger companies have done a better job of securing their infrastructure. So these mid-size firms are playing catch up and the data suggests cyber is even a bigger priority there, gaps that they have to fill, you know, going forward. And that's why we think there's going to be more demand for MSSPs, managed security service providers. And we may even see some IPO action there. And then of course, Erik, you and I have talked about events like the SolarWinds Hack, there's more ransomware attacks, other vulnerabilities. Just recently, like Log4j in December. All of this has heightened concerns. Now I want to talk a little bit more about how we measure this, you know, relatively, okay, it's an obvious prediction, but let's stick our necks out a little bit. And so in addition to the rise of managed security services, we're calling for M&A and/or IPOs, we've specified some names here on this chart, and we're also pointing to the digital supply chain as an area of emphasis. Again, Log4j really shone that under a light. And this is going to help the likes of Auth0, which is now Okta, SailPoint, which is called out on this chart, and some others. We're calling some winners in end point security. Erik, you're going to talk about sort of that lifecycle, that transformation that we're seeing, that migration to new endpoint technologies that are going to benefit from this reset refresh cycle. So Erik, weigh in here, let's talk about some of the elements of this prediction and some of the names on that chart. >> Yeah, certainly. I'm going to start right with Log4j top of mind. And the reason why is because we're seeing a real paradigm shift here where things are no longer being attacked at the network layer, they're being attacked at the application layer, and in the application stack itself. And that is a huge shift left. And that's taking in DevSecOps now as a real priority in 2022. That's a real paradigm shift over the last 20 years. That's not where attacks used to come from. And this is going to have a lot of changes. You called out a bunch of names in there that are, they're either going to work. I would add to that list Wiz. I would add Orca Security. Two names in our emerging technology study, in addition to the ones you added that are involved in cloud security and container security. These names are either going to get gobbled up. So the traditional legacy names are going to have to start writing checks and, you know, legacy is not fair, but they're in the data center, right? They're, on-prem, they're not cloud native. So these are the names that money is going to be flowing to. So they're either going to get gobbled up, or we're going to see some IPO's. And on the other thing I want to talk about too, is what you mentioned. We have CrowdStrike on that list, We have SentinalOne on the list. Everyone knows them. Our data was so strong on Tanium that we actually went positive for the first time just today, just this morning, where that was released. The trifecta of these are so important because of what you mentioned, under resourcing. We can't have security just tell us when something happens, it has to automate, and it has to respond. So in this next generation of EDR and XDR, an automated response has to happen because people are under-resourced, salaries are really high, there's a skill shortage out there. Security has to become responsive. It can't just monitor anymore. >> Yeah. Great. And we should call out too. So we named some names, Snyk, Aqua, Arctic Wolf, Lacework, Netskope, Illumio. These are all sort of IPO, or possibly even M&A candidates. All right. Our next prediction goes right to the way we work. Again, something that ETR has been on for awhile. We're calling for a major rethink in remote work for 2022. We had predicted last year that by the end of 2021, there'd be a larger return to the office with the norm being around a third of workers permanently remote. And of course the variants changed that equation and, you know, gave more time for people to think about this idea of hybrid work and that's really come in to focus. So we're predicting that is going to overtake fully remote as the dominant work model with only about a third of the workers back in the office full-time. And Erik, we expect a somewhat lower percentage to be fully remote. It's now sort of dipped under 30%, at around 29%, but it's still significantly higher than the historical average of around 15 to 16%. So still a major change, but this idea of hybrid and getting hybrid right, has really come into focus. Hasn't it? >> Yeah. It's here to stay. There's no doubt about it. We started this in March of 2020, as soon as the virus hit. This is the 10th iteration of the survey. No one, no one ever thought we'd see a number where only 34% of people were going to be in office permanently. That's a permanent number. They're expecting only a third of the workers to ever come back fully in office. And against that, there's 63% that are saying their permanent workforce is going to be either fully remote or hybrid. And this, I can't really explain how big of a paradigm shift this is. Since the start of the industrial revolution, people leave their house and go to work. Now they're saying that's not going to happen. The economic impact here is so broad, on so many different areas And, you know, the reason is like, why not? Right? The productivity increase is real. We're seeing the productivity increase. Enterprises are spending on collaboration tools, productivity tools, We're seeing an increased perception in productivity of their workforce. And the CFOs can cut down an expense item. I just don't see a reason why this would end, you know, I think it's going to continue. And I also want to point out these results, as high as they are, were before the Omicron wave hit us. I can only imagine what these results would have been if we had sent the survey out just two or three weeks later. >> Yeah. That's a great point. Okay. Next prediction, we're going to look at the supply chain, specifically in how it's affecting some of the hardware spending and cloud strategies in the future. So in this chart, ETRS buyers, have you experienced problems procuring hardware as a result of supply chain issues? And, you know, despite the fact that some companies are, you know, I would call out Dell, for example, doing really well in terms of delivering, you can see that in the numbers, it's pretty clear, there's been an impact. And that's not not an across the board, you know, thing where vendors are able to deliver, especially acute in PCs, but also pronounced in networking, also in firewall servers and storage. And what's interesting is how companies are responding and reacting. So first, you know, I'm going to call the laptop and PC demand staying well above pre-COVID norms. It had peaked in 2012. Pre-pandemic it kept dropping and dropping and dropping, in terms of, you know, unit volume, where the market was contracting. And we think can continue to grow this year in double digits in 2022. But what's interesting, Erik, is when you survey customers, is despite the difficulty they're having in procuring network hardware, there's as much of a migration away from existing networks to the cloud. You could probably comment on that. Their networks are more fossilized, but when it comes to firewalls and servers and storage, there's a much higher propensity to move to the cloud. 30% of customers that ETR surveyed will replace security appliances with cloud services and 41% and 34% respectively will move to cloud compute and storage in 2022. So cloud's relentless march on traditional on-prem models continues. Erik, what do you make of this data? Please weigh in on this prediction. >> As if we needed another reason to go to the cloud. Right here, here it is yet again. So this was added to the survey by client demand. They were asking about the procurement difficulties, the supply chain issues, and how it was impacting our community. So this is the first time we ran it. And it really was interesting to see, you know, the move there. And storage particularly I found interesting because it correlated with a huge jump that we saw on one of our vendor names, which was Rubrik, had the highest net score that it's ever had. So clearly we're seeing some correlation with some of these names that are there, you know, really well positioned to take storage, to take data into the cloud. So again, you didn't need another reason to, you know, hasten this digital transformation, but here we are, we have it yet again, and I don't see it slowing down anytime soon. >> You know, that's a really good point. I mean, it's not necessarily bad news for the... I mean, obviously you wish that it had no change, would be great, but things, you know, always going to change. So we'll talk about this a little bit later when we get into the Supercloud conversation, but this is an opportunity for people who embrace the cloud. So we'll come back to that. And I want to hang on cloud a bit and share some recent projections that we've made. The next prediction is the big four cloud players are going to surpass 167 billion, an IaaS and PaaS revenue in 2022. We track this. Observers of this program know that we try to create an apples to apples comparison between AWS, Azure, GCP and Alibaba in IaaS and PaaS. So we're calling for 38% revenue growth in 2022, which is astounding for such a massive market. You know, AWS is probably not going to hit a hundred billion dollar run rate, but they're going to be close this year. And we're going to get there by 2023, you know they're going to surpass that. Azure continues to close the gap. Now they're about two thirds of the size of AWS and Google, we think is going to surpass Alibaba and take the number three spot. Erik, anything you'd like to add here? >> Yeah, first of all, just on a sector level, we saw our sector, new survey net score on cloud jumped another 10%. It was already really high at 48. Went up to 53. This train is not slowing down anytime soon. And we even added an edge compute type of player, like CloudFlare into our cloud bucket this year. And it debuted with a net score of almost 60. So this is really an area that's expanding, not just the big three, but everywhere. We even saw Oracle and IBM jump up. So even they're having success, taking some of their on-prem customers and then selling them to their cloud services. This is a massive opportunity and it's not changing anytime soon, it's going to continue. >> And I think the operative word there is opportunity. So, you know, the next prediction is something that we've been having fun with and that's this Supercloud becomes a thing. Now, the reason I say we've been having fun is we put this concept of Supercloud out and it's become a bit of a controversy. First, you know, what the heck's the Supercloud right? It's sort of a buzz-wordy term, but there really is, we believe, a thing here. We think there needs to be a rethinking or at least an evolution of the term multi-cloud. And what we mean is that in our view, you know, multicloud from a vendor perspective was really cloud compatibility. It wasn't marketed that way, but that's what it was. Either a vendor would containerize its legacy stack, shove it into the cloud, or a company, you know, they'd do the work, they'd build a cloud native service on one of the big clouds and they did do it for AWS, and then Azure, and then Google. But there really wasn't much, if any, leverage across clouds. Now from a buyer perspective, we've always said multicloud was a symptom of multi-vendor, meaning I got different workloads, running in different clouds, or I bought a company and they run on Azure, and I do a lot of work on AWS, but generally it wasn't necessarily a prescribed strategy to build value on top of hyperscale infrastructure. There certainly was somewhat of a, you know, reducing lock-in and hedging the risk. But we're talking about something more here. We're talking about building value on top of the hyperscale gift of hundreds of billions of dollars in CapEx. So in addition, we're not just talking about transforming IT, which is what the last 10 years of cloud have been like. And, you know, doing work in the cloud because it's cheaper or simpler or more agile, all of those things. So that's beginning to change. And this chart shows some of the technology vendors that are leaning toward this Supercloud vision, in our view, building on top of the hyperscalers that are highlighted in red. Now, Jerry Chan at Greylock, they wrote a piece called Castles in the Cloud. It got our thinking going, and he and the team at Greylock, they're building out a database of all the cloud services and all the sub-markets in cloud. And that got us thinking that there's a higher level of abstraction coalescing in the market, where there's tight integration of services across clouds, but the underlying complexity is hidden, and there's an identical experience across clouds, and even, in my dreams, on-prem for some platforms, so what's new or new-ish and evolving are things like location independence, you've got to include the edge on that, metadata services to optimize locality of reference and data source awareness, governance, privacy, you know, application independent and dependent, actually, recovery across clouds. So we're seeing this evolve. And in our view, the two biggest things that are new are the technology is evolving, where you're seeing services truly integrate cross-cloud. And the other big change is digital transformation, where there's this new innovation curve developing, and it's not just about making your IT better. It's about SaaS-ifying and automating your entire company workflows. So Supercloud, it's not just a vendor thing to us. It's the evolution of, you know, the, the Marc Andreessen quote, "Every company will be a SaaS company." Every company will deliver capabilities that can be consumed as cloud services. So Erik, the chart shows spending momentum on the y-axis and net score, or presence in the ETR data center, or market share on the x-axis. We've talked about snowflake as the poster child for this concept where the vision is you're in their cloud and sharing data in that safe place. Maybe you could make some comments, you know, what do you think of this Supercloud concept and this change that we're sensing in the market? >> Well, I think you did a great job describing the concept. So maybe I'll support it a little bit on the vendor level and then kind of give examples of the ones that are doing it. You stole the lead there with Snowflake, right? There is no better example than what we've seen with what Snowflake can do. Cross-portability in the cloud, the ability to be able to be, you know, completely agnostic, but then build those services on top. They're better than anything they could offer. And it's not just there. I mean, you mentioned edge compute, that's a whole nother layer where this is coming in. And CloudFlare, the momentum there is out of control. I mean, this is a company that started off just doing CDN and trying to compete with Okta Mite. And now they're giving you a full soup to nuts with security and actual edge compute layer, but it's a fantastic company. What they're doing, it's another great example of what you're seeing here. I'm going to call out HashiCorp as well. They're more of an infrastructure services, a little bit more of an open-source freemium model, but what they're doing as well is completely cloud agnostic. It's dynamic. It doesn't care if you're in a container, it doesn't matter where you are. They recently IPO'd and they're down 25%, but their data looks so good across both of our emerging technology and TISA survey. It's certainly another name that's playing on this. And another one that we mentioned as well is Rubrik. If you need storage, compute, and in the cloud layer and you need to be agnostic to it, they're another one that's really playing in this space. So I think it's a great concept you're bringing up. I think it's one that's here to stay and there's certainly a lot of vendors that fit into what you're describing. >> Excellent. Thank you. All right, let's shift to data. The next prediction, it might be a little tough to measure. Before I said we're trying to be a little black and white here, but it relates to Data Mesh, which is, the ideas behind that term were created by Zhamak Dehghani of ThoughtWorks. And we see Data Mesh is really gaining momentum in 2022, but it's largely going to be, we think, confined to a more narrow scope. Now, the impetus for change in data architecture in many companies really stems from the fact that their Hadoop infrastructure really didn't solve their data problems and they struggle to get more value out of their data investments. Data Mesh prescribes a shift to a decentralized architecture in domain ownership of data and a shift to data product thinking, beyond data for analytics, but data products and services that can be monetized. Now this a very powerful in our view, but they're difficult for organizations to get their heads around and further decentralization creates the need for a self-service platform and federated data governance that can be automated. And not a lot of standards around this. So it's going to take some time. At our power panel a couple of weeks ago on data management, Tony Baer predicted a backlash on Data Mesh. And I don't think it's going to be so much of a backlash, but rather the adoption will be more limited. Most implementations we think are going to use a starting point of AWS and they'll enable domains to access and control their own data lakes. And while that is a very small slice of the Data Mesh vision, I think it's going to be a starting point. And the last thing I'll say is, this is going to take a decade to evolve, but I think it's the right direction. And whether it's a data lake or a data warehouse or a data hub or an S3 bucket, these are really, the concept is, they'll eventually just become nodes on the data mesh that are discoverable and access is governed. And so the idea is that the stranglehold that the data pipeline and process and hyper-specialized roles that they have on data agility is going to evolve. And decentralized architectures and the democratization of data will eventually become a norm for a lot of different use cases. And Erik, I wonder if you'd add anything to this. >> Yeah. There's a lot to add there. The first thing that jumped out to me was that that mention of the word backlash you said, and you said it's not really a backlash, but what it could be is these are new words trying to solve an old problem. And I do think sometimes the industry will notice that right away and maybe that'll be a little pushback. And the problems are what you already mentioned, right? We're trying to get to an area where we can have more assets in our data site, more deliverable, and more usable and relevant to the business. And you mentioned that as self-service with governance laid on top. And that's really what we're trying to get to. Now, there's a lot of ways you can get there. Data fabric is really the technical aspect and data mesh is really more about the people, the process, and the governance, but the two of those need to meet, in order to make that happen. And as far as tools, you know, there's even cataloging names like Informatica that play in this, right? Istio plays in this, Snowflake plays in this. So there's a lot of different tools that will support it. But I think you're right in calling out AWS, right? They have AWS Lake, they have AWS Glue. They have so much that's trying to drive this. But I think the really important thing to keep here is what you said. It's going to be a decade long journey. And by the way, we're on the shoulders of giants a decade ago that have even gotten us to this point to talk about these new words because this has been an ongoing type of issue, but ultimately, no matter which vendors you use, this is going to come down to your data governance plan and the data literacy in your business. This is really about workflows and people as much as it is tools. So, you know, the new term of data mesh is wonderful, but you still have to have the people and the governance and the processes in place to get there. >> Great, thank you for that, Erik. Some great points. All right, for the next prediction, we're going to shine the spotlight on two of our favorite topics, Snowflake and Databricks, and the prediction here is that, of course, Databricks is going to IPO this year, as expected. Everybody sort of expects that. And while, but the prediction really is, well, while these two companies are facing off already in the market, they're also going to compete with each other for M&A, especially as Databricks, you know, after the IPO, you're going to have, you know, more prominence and a war chest. So first, these companies, they're both looking pretty good, the same XY graph with spending velocity and presence and market share on the horizontal axis. And both Snowflake and Databricks are well above that magic 40% red dotted line, the elevated line, to us. And for context, we've included a few other firms. So you can see kind of what a good position these two companies are really in, especially, I mean, Snowflake, wow, it just keeps moving to the right on this horizontal picture, but maintaining the next net score in the Y axis. Amazing. So, but here's the thing, Databricks is using the term Lakehouse implying that it has the best of data lakes and data warehouses. And Snowflake has the vision of the data cloud and data sharing. And Snowflake, they've nailed analytics, and now they're moving into data science in the domain of Databricks. Databricks, on the other hand, has nailed data science and is moving into the domain of Snowflake, in the data warehouse and analytics space. But to really make this seamless, there has to be a semantic layer between these two worlds and they're either going to build it or buy it or both. And there are other areas like data clean rooms and privacy and data prep and governance and machine learning tooling and AI, all that stuff. So the prediction is they'll not only compete in the market, but they'll step up and in their competition for M&A, especially after the Databricks IPO. We've listed some target names here, like Atscale, you know, Iguazio, Infosum, Habu, Immuta, and I'm sure there are many, many others. Erik, you care to comment? >> Yeah. I remember a year ago when we were talking Snowflake when they first came out and you, and I said, "I'm shocked if they don't use this war chest of money" "and start going after more" "because we know Slootman, we have so much respect for him." "We've seen his playbook." And I'm actually a little bit surprised that here we are, at 12 months later, and he hasn't spent that money yet. So I think this prediction's just spot on. To talk a little bit about the data side, Snowflake is in rarefied air. It's all by itself. It is the number one net score in our entire TISA universe. It is absolutely incredible. There's almost no negative intentions. Global 2000 organizations are increasing their spend on it. We maintain our positive outlook. It's really just, you know, stands alone. Databricks, however, also has one of the highest overall net sentiments in the entire universe, not just its area. And this is the first time we're coming up positive on this name as well. It looks like it's not slowing down. Really interesting comment you made though that we normally hear from our end-user commentary in our panels and our interviews. Databricks is really more used for the data science side. The MLAI is where it's best positioned in our survey. So it might still have some catching up to do to really have that caliber of usability that you know Snowflake is seeing right now. That's snowflake having its own marketplace. There's just a lot more to Snowflake right now than there is Databricks. But I do think you're right. These two massive vendors are sort of heading towards a collision course, and it'll be very interesting to see how they deploy their cash. I think Snowflake, with their incredible management and leadership, probably will make the first move. >> Well, I think you're right on that. And by the way, I'll just add, you know, Databricks has basically said, hey, it's going to be easier for us to come from data lakes into data warehouse. I'm not sure I buy that. I think, again, that semantic layer is a missing ingredient. So it's going to be really interesting to see how this plays out. And to your point, you know, Snowflake's got the war chest, they got the momentum, they've got the public presence now since November, 2020. And so, you know, they're probably going to start making some aggressive moves. Anyway, next prediction is something, Erik, that you and I have talked about many, many times, and that is observability. I know it's one of your favorite topics. And we see this world screaming for more consolidation it's going all in on cloud native. These legacy stacks, they're fighting to stay relevant, but the direction is pretty clear. And the same XY graph lays out the players in the field, with some of the new entrants that we've also highlighted, like Observe and Honeycomb and ChaosSearch that we've talked about. Erik, we put a big red target around Splunk because everyone wants their gold. So please give us your thoughts. >> Oh man, I feel like I've been saying negative things about Splunk for too long. I've got a bad rap on this name. The Splunk shareholders come after me all the time. Listen, it really comes down to this. They're a fantastic company that was designed to do logging and monitoring and had some great tool sets around what you could do with it. But they were designed for the data center. They were designed for prem. The world we're in now is so dynamic. Everything I hear from our end user community is that all net new workloads will be going to cloud native players. It's that simple. So Splunk has entrenched. It's going to continue doing what it's doing and it does it really, really well. But if you're doing something new, the new workloads are going to be in a dynamic environment and that's going to go to the cloud native players. And in our data, it is extremely clear that that means Datadog and Elastic. They are by far number one and two in net score, increase rates, adoption rates. It's not even close. Even New Relic actually is starting to, you know, entrench itself really well. We saw New Relic's adoption's going up, which is super important because they went to that freemium model, you know, to try to get their little bit of an entrenched customer base and that's working as well. And then you made a great list here, of all the new entrants, but it goes beyond this. There's so many more. In our emerging technology survey, we're seeing Century, Catchpoint, Securonix, Lucid Works. There are so many options in this space. And let's not forget, the biggest data that we're seeing is with Grafana. And Grafana labs as yet to turn on their enterprise. Elastic did it, why can't Grafana labs do it? They have an enterprise stack. So when you look at how crowded this space is, there has to be consolidation. I recently hosted a panel and every single guy on that panel said, "Please give me a consolidation." Because they're the end users trying to actually deploy these and it's getting a little bit confusing. >> Great. Thank you for that. Okay. Last prediction. Erik, might be a little out of your wheelhouse, but you know, you might have some thoughts on it. And that's a hybrid events become the new digital model and a new category in 2022. You got these pure play digital or virtual events. They're going to take a back seat to in-person hybrids. The virtual experience will eventually give way to metaverse experiences and that's going to take some time, but the physical hybrid is going to drive it. And metaverse is ultimately going to define the virtual experience because the virtual experience today is not great. Nobody likes virtual. And hybrid is going to become the business model. Today's pure virtual experience has to evolve, you know, theCUBE first delivered hybrid mid last decade, but nobody really wanted it. We did Mobile World Congress last summer in Barcelona in an amazing hybrid model, which we're showing in some of the pictures here. Alex, if you don't mind bringing that back up. And every physical event that we're we're doing now has a hybrid and virtual component, including the pre-records. You can see in our studios, you see that the green screen. I don't know. Erik, what do you think about, you know, the Zoom fatigue and all this. I know you host regular events with your round tables, but what are your thoughts? >> Well, first of all, I think you and your company here have just done an amazing job on this. So that's really your expertise. I spent 20 years of my career hosting intimate wall street idea dinners. So I'm better at navigating a wine list than I am navigating a conference floor. But I will say that, you know, the trend just goes along with what we saw. If 35% are going to be fully remote. If 70% are going to be hybrid, then our events are going to be as well. I used to host round table dinners on, you know, one or two nights a week. Now those have gone virtual. They're now panels. They're now one-on-one interviews. You know, we do chats. We do submitted questions. We do what we can, but there's no reason that this is going to change anytime soon. I think you're spot on here. >> Yeah. Great. All right. So there you have it, Erik and I, Listen, we always love the feedback. Love to know what you think. Thank you, Erik, for your partnership, your collaboration, and love doing these predictions with you. >> Yeah. I always enjoy them too. And I'm actually happy. Last year you made us do a baker's dozen, so thanks for keeping it to 10 this year. >> (laughs) We've got a lot to say. I know, you know, we cut out. We didn't do much on crypto. We didn't really talk about SaaS. I mean, I got some thoughts there. We didn't really do much on containers and AI. >> You want to keep going? I've got another 10 for you. >> RPA...All right, we'll have you back and then let's do that. All right. All right. Don't forget, these episodes are all available as podcasts, wherever you listen, all you can do is search Breaking Analysis podcast. Check out ETR's website at etr.plus, they've got a new website out. It's the best data in the industry, and we publish a full report every week on wikibon.com and siliconangle.com. You can always reach out on email, David.Vellante@siliconangle.com I'm @DVellante on Twitter. Comment on our LinkedIn posts. This is Dave Vellante for the Cube Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (mellow music)

(upbeat music) >> Hi, everyone, welcome back to theCUBE's coverage of AWS re:Invent 2021. We're wrapping up four days of coverage, two sets. Two remote sets, one in Boston, one in Palo Alto. And really, it's a pleasure to introduce Benoit Dageville. He's the Press Co-founder of Snowflake and President of Products. Benoit, thanks for taking some time out and coming to theCUBE. >> Yeah, thank you for having me, Dave. >> You know, it's really a pleasure. We've been watching Snowflake since, maybe not 2012, but mid last decade you hit our radar. We said, "Wow, this company is going to go places." And yeah, we made that call correctly. But it's been a pleasure to sort of follow you. We've talked a little bit remotely. I kind of want to go back to some of the fundamentals. First of all, I wanted mention your earnings last night. If you guys didn't see it, again, triple digit growth, $1.8 billion RPO, cashflow actually looking pretty good. So, pretty amazing. Oh, and 173% NRR, you know, wow. And Mike Scarpelli is kind of bummed that you did so well. And I know why, right? Because it's going to be at some point, and he dials it down for the expectations and Wall Street says, "Oh, he's sandbagging." And then at some point you're actually going to meet expectations and people are going to go, "Oh, they met expectations." But anyway, he's a smart guy, he know what he's doing. (Benoit laughing) I loved it, it was so funny listening to him last night. But anyway, I want to go back to, when I talked to practitioners about data warehousing pre-cloud, they would say sound bites like, it's like a snake swallowing a basketball, they would tell me. And the other thing they said, "We just chased the chips. Every time a new Intel chip comes out, we have to bring in new servers, and we're struggling." The cloud changed all that. Your vision and Terry's vision changed all that. Maybe go back to the fundamentals of what you saw. >> Yeah, we really wanted to address what we call the data challenges. And if you remember at that time, data challenge was first of the volume of data, machine-generated data. So it was way more than just structured data, right? Machine-generated data is weblogs, and it's at petabyte scale. And there was no good solution for that type of data. Big data was not a great solution, Hadoop was really bad. And there was no good solution for that. So we thought we should do something for big data. The other aspect was concurrency, right? Everyone wants to use these data analytic platform in an enterprise, right? And you have more and more workload running against the same data, and the systems that were built were not scaling for these workloads. So you had to silo data, right? That's the only way big enterprise could deal with that, is to create many different silos, Oracle, Teradata, data mass, you would hear data mass. All of it was to afloat, right, this data? And then there was the, what do we call, data sharing. How to get access to data which is not born inside the enterprise, right? So with Terry, we wanted to solve all these challenges and we thought the only way to solve it was the cloud. And the cloud has really two free aspects. One is the elasticity, for all of a sudden, you can run every workload that you want concurrently, in parallel, on different computer resources, and you can run them against the same data. So this is kind of the data lake model, if you want. At the same time, you can, in the cloud, create a service. So you can remove complexity from users and make it really easy for new workloads to be added to the system, because you can manage, you can create a managed service, where all the sudden our customers, they don't need to manage infrastructure, they don't need to patch, they don't need to tune. Everything is done by Snowflake, the service, and they can just load in and run their query. And the third aspect is really collaboration. Is how to connect data sets together. And that's almost a new product for Snowflake, this data sharing. So we really at Snowflake was all about combining big data and data warehouse in one system in the cloud, and have only one single system where you can put all your data and all your workload. >> So you weren't necessarily trying to solve the data warehouse problem, you were trying to solve a data problem. And then it just so happened data warehouse was a logical entry point for you. >> It's really not that. Yes, we wanted to solve the data problem. And for us big data was a really important problem to solve. So from day one, Snowflake was all about machine generated data, petabyte scale, but we wanted to do it right. And for us, right was not compromising on data warehouse principle, which is a CDT of transaction, which is really fast response time, and which is also simplicity. So as I said, we wanted to solve kind of all the problems at the time of volume of data, concurrency, and these sharing aspects. >> This was 2012. You knew at that time that Hadoop wasn't going to be the answer. >> No, I mean, we were really, I mean, everyone knew that. Everyone knew Hadoop was really bad. You know, complex to manage, really slow. It had good aspects, right? This was the only system that could manage petabyte scale data sets. That's the only thing- >> Cheaply. >> Yeah, and cheaply which was good. And we wanted really to do that, plus have all the good attributes of data warehouse system. And at the same time, we wanted to build a system where if you are data warehouse customer, if you are coming from Teradata, you can migrate to Snowflake and you will get to a system which is faster than what you had on-premise, right. That's why it's pretty cool. So we wanted to do big data without compromising on data warehouse. >> So several years ago we looked at the hyperscalers and said, "Wow, last year they spent $100 billion in CapEx." And so, we started to think about this abstraction layer. And then we saw what you guys announced with the data cloud. We call it super clouds. And we see that as exactly what you're building. So that's clearly not just a data warehouse or database, it's technology that really hides the underlying complexity of all those clouds, and it allows you to have federated governance and data sharing, all those things. Can you talk about sort of how you think about that architecture? >> So for me, what I say is that really Snowflake is the worldwide web of data. And we are indeed a super cloud, or we are super-posed to the infrastructure cloud, which is our friends at Amazon, and of course, Azure, I mean, Microsoft and Google. And as any cloud, we have regions, Snowflake regions all over the world, and located on different cloud providers. At the same time, our platform is global in the sense that every region interconnects with all the other regions, this is our snow grid and data mesh, if you want. So that as an organization you can have your presence on several Snowflake region. It doesn't matter which cloud provider, so you can mix AWS with Azure. You can use our cloud like that. And indeed you can, this is a cloud where you can store your data, that's the thing that really matters, and data is structured, but it's machine structure, as I say, machine generated, petabyte scale, but there's also unstructured, right? We have added support for images, text, videos, where you can process this data in our system, and that's the workload spout. And workload, what is very important is that you can run this workload, any number of workloads. So the number of workloads is effectively unlimited with Snowflake because each workload can have its dedicated set of compute resources all operating on the same data set. And the type of workloads is also very important. It's not only about dashboards and data warehouse, it's data engineering, it's data science, it's building application. We have many of our customers who are building full-scale cloud applications on top of Snowflake. >> Yeah so the other thing, if you're not familiar with Snowflake, I don't know, maybe your head has been in the sand for a while, but separating compute and storage, I don't know if you were the first, but you were certainly the first to popularize it. And that allowed you to solve that chasing the chips problem and the swallowing the basketball, right? Because you have virtually infinite resources now at your disposal. >> Yeah, this is really the concurrency challenge that I was mentioning. Everyone wants to access the data. And of course, if everyone runs on the same set of compute resources, you have a bottleneck. So Snowflake was really about this multi-workload. We call it Multi-Cluster Shared Data Architecture. But it's not difficult to run multiple cluster if you don't have consistency of data. So how to do that while maintaining transactional property of data as CDT, right? You cannot modify data from different clusters. And when you commit, every other cluster will immediately see the change, right, as if everyone was running on the same cluster. So that was the challenge that we solve when we started Snowflake. >> Used the term data mesh. What is data mesh to Snowflake? Is it a concept, is it fabric? >> No, it's a very interesting point. As much as we like to centralize data, this becomes a bottleneck, right? When you are a large organization with different independent units, everyone wants to manage their own data and they have domain-specific expertise about that data. So having it centralized in IT is not practical. At the same time, you really want to be able to connect these different data sets together and join different data together, right? So that's the data mesh architecture. Each data set is managed independently by business owners, and then there is a contract which is exposed to others, and you can combine. And Snowflake architectures with data sharing, right. Data sharing that can happen within an organization, or across organization, allows you to connect any data with any other data on our platform. >> Yeah, so when I first heard that term, you guys using the term data mesh, I got very excited because it was kind of the data mesh is, my view, anyway, is going to be the fundamental architecture of this decade and beyond. And the principles, if I understand it correctly, you're applying the principles of Jim Octagon's data mesh within Snowflake. So decentralized data doesn't have to be physically in one place. Logically it's in the data cloud. >> It's logically decentralized, right? It's independently managed, and the reason, right, is the data that you need to use is not produced by your, even if in your company you want to centralize the data and having only one organization, let's say IT managing that, let's say, pretend. Yet you need to connect with other datasets, which is managed by other organizations. So by nature, the data that you use cannot be centralized, right? So now that you have this principle, if you have a platform where you can store all the data, wherever it is, and you can connect these data very seamlessly, then we can use that platform for your enterprise, right? To have different business units independently manage their data sets, connects these together so that as a company you have a 360 view of your customers, for example. But you can expand that outside of your enterprise and connect with data sets, which are from your vertical, for example, financial data set that you don't have in your company, or any public data set. >> And the other key principles, I think, that you've touched on really is the line of business now. Increasingly they're building data products that are creating value, and then also there's a self-service component. Assuming there's the fourth principle, governance. You got to have federated governance. And it seems like you've kind of ticked the boxes, more than tick the boxes, but engineered a solution to solve for those. >> No, it's very true. So Snowflake was really built to be really simple to use. And you're right. Our vision was, it would be more than IT, right? Who is going to use Snowflake is going now to be business unit, because you do not have to manage infrastructure. You do not have to patch. You do not have to do these things that business cannot do. You just have to load your data and run your queries, and run your applications. So now business can directly use Snowflake and create value from that. And yes, you're right, then connect that data with other data sets and to get maximum insights. >> Can you please talk about some of the things you do with AWS here at the event. I'm interested in what you're doing with your machine learning initiatives that you've recently announced, the AI piece. >> Yes, so one key aspects is data is not only about SQL, right? We started with SQL, but we expanded our platform to what we call data programmability, which is really about running program at scale across a large volume of data. And this was made popular with a programming model which was introduced by Pendal, DataFrames. Later taken by Spark, and now we have DataFrames in Snowflake, Where we are different than other systems, is that these DataFrame programs, which are in Python, or Java, or Scala, you program with data. These DataFrames are compiled to our single execution platforms. So we have one single execution platform, which is a data flow execution platform, which can run both SQL very efficiently, as I said, data warehouse speed, and also these very complex programs running Python and Java against this data. And this is a single platform. You don't need to use two different systems. >> Now so, you kind of really attack the traditional analytics base. People said, "Wow, Snowflake's really easy." Now you're injecting AI and machine intelligence. I see Databricks coming at it from the other angle. They started with machine learning, now they're sort of going after the analytics. Does there need to be a semantic layer to connect, 'cause it's the same raw data. Does there need to be a semantic layer to connect those two worlds? >> Yes, and that's what we are doing in our platform. And that's very novel to Snowflake. As I said, you interact with data in different program. You pick your program. You are a SQL programmer, use SQL. You are a Python programmer, use DataFrames with Python. It doesn't really matter. And then the semantic layer is our compiler and our processing engine, is going to translate both your program and my program in Python, your program in SQL, to the same execution platform and to the same programming language that Snowflake internally, we don't expose our programming language, but it's a data flow programming language that our execution platform executes. So at the end, we might execute exactly the same program, potentially. And that's very important because we spent all our IP and all our time, engineering time to optimize this platform, to make it the fastest platform. And we want to use that platform for any type of workloads, whether it's data programs or SQL. >> Now, you and Terry were at Oracle, so you know a lot about bench marketing. As Larry would stand up and say, "We killed the competition." You guys are probably behind it, right. So you know all about that. >> We are very behind it. >> So you know a lot about that. I've had some experience, I'm not a technologist, but I'm an observer and analyst. You have to take benchmarking with a very big grain of salt. So you guys have generally stayed away from that. Databricks came out and they came up with all these benchmarks. So you had to respond, because otherwise it's out there. Now you reran the benchmarks, you took out the materialized views and all the expensive stuff that they included in your cost, your price performance, but then you wrote, I thought, a very cogent blog. Maybe you could talk about sort of why you did that and your general philosophy around bench marketing. >> Yeah, from day one, with Terry we say never again we will participate in this really stupid benchmark war, because it's really not in the interest of customers. And we have been really at the frontline of that war with Terry, both of us, really doing special tricks, right? And optimizing this query to death, this query that no one runs apart from the synthetic benchmark. We optimize them to death to have the best number when we were at Oracle. And we decided that this is really not helping customers in the end. So we said, with Snowflake, we'll not do that. And actually, we are not the only one not to do that. If you look at who has published TPC-DS, you will see no one, none of the big vendors. It's not because they cannot run TPC-DS, Oracle can run it, I know that. And all the other big data warehouse vendor can, but it's something of a little bit of past. And TPC was really important at some point, and is not really relevant now. So we are not going to compete. And that's what we said is basically now our blog. We are not interesting in participating in this war. We want to invest our engineering effort and our IP in solving real world issues and performance issues that we have. And we want to improve our engine for these real world customers. And the nice thing with Snowflake, because it's a service, we see exactly all the queries that our customers are executing. So we know where we are struggling as a system, and that's where we want to invest and we want to improve. And if you look at many announcements that we made, it's all about under-the-cover improving Snowflake and getting the benefit of this improvement to our customer. So that was the message of that blog. And yes, the message was okay. Mr. Databricks, it's nice, and it's perfect that, I mean, everyone makes a decision, right? We made the decision not to participate. Databricks made another decision, which is very fine, and that's fine that they publish their number on their system. Where it is not fine is that they published number using Snowflake and misrepresenting our performance. And that's what we wanted also to correct. >> Yeah, well, thank you for going into that. I know it's, look, leaders don't necessarily have to get involved in that mudslide. (crosstalk) Enough said about that, so that's cool. I want to ask you, I interviewed Frank last spring, right after the lockdown, he was kind enough to come on virtually, and I asked him about on-prem. And he was, you know Frank, he doesn't mix words, He said, "We're not getting into a halfway house. That's not going to happen." And of course, you really can't do what you do on-prem. You can't separate compute, some have tried, but it's not the same. But at the same time that you see like Andreessen comes out with this blog that says a huge portion of your cost of goods sold is going to be the cloud, so you're going to have to repatriate. Help me square that circle. Is it cloud forever? Is it will you never say never? What can you share of that? >> I will never say never, it's not my style. I always say you can always change your mind, and maybe different factors can change your mind. What was true at some point might not be true at a later point. But as of now, I don't see any reason for us to go on-premise. As you mentioned at the beginning, right, Snowflake is growing like crazy. The world is moving to the cloud. I think maybe it goes both ways, but I would say 90% or 99% of the world is moving to the cloud. Maybe 1% is coming back for some very specific reasons. I don't think that the world is going to move back on-premise. So in the end we might miss a small percentage of the workload that will stay on-premise and that's okay. >> And as well, if you dig into some of the financial statements you'll see, read the notes where you've renegotiated, right? We're talking big numbers. Hundreds and hundreds of millions of dollars of cost reduction, actually more, over a 10 year period. Billions of your cloud bills. So the cloud suppliers, they don't want to lose you as a customer, right? You're one of their biggest customer. So it's awesome. Last question is kind of, your work now is to really drive the data cloud, get adoption up, build that supercloud, we call it. Maybe you could talk a little bit about how you see the future. >> The future is really broadened, the scope of Snowflake, and really, I would say the marketplace, and data sharing, and services, which are directly built natively on Snowflake and are shared through our platform, and can operate, it can mix data on provider-side with data on consumer-side, and creating this collaboration within the Snowflake data cloud, I think is really the future. And we are really only scratching the surface of that. And you can see the enthusiasm of Snowflake data cloud and vertical industry We have nuanced the final show data cloud. Industry, complete vertical industry, latching on that concept and collaborating via Snowflake, which was not possible before. And I think you talked about machine learning, for example. Machine learning, collaboration through machine learning, the ones who are building this advanced model might not be the same as the one who are consuming this model, right? It might be this collaboration between expertise and consumer of that expertise. So we are really at the beginning of this interconnected world. And to me the world wide web of data that we are creating is really going to be amazing. And it's all about connecting. >> And I'm glad you mentioned the ecosystem. I didn't give enough attention to that. Because as a cloud provider, which essentially you are, you've got to have a strong ecosystem. That's a hallmark of cloud. And then the other, vertical, that we didn't touch on, is media and entertainment. A lot of direct-to-consumer. I think healthcare is going to be a huge vertical for you guys. All right we got to go, Terry. Thanks so much for coming on "theCUBE." I really appreciate you. >> Thanks, Dave. >> And thank you for watching. This a wrap from AWS re:Invent 2021. "theCUBE," the leader in global tech coverage. We'll see you next time. (upbeat music)

(upbeat music) >> Everybody welcome back to theCUBE, continuous coverage of AWS 2021. This is the biggest hybrid event of the year, theCUBEs ninth year covering AWS re:Invent. My name is Dave Vellante. Arwa Kaddoura is here CUBE alumni, chief revenue officer now of InfluxData and Brian Mullen, who's the chief marketing officer. Folks good to see you. >> Thanks for having us. >> Dave: All right, great to see you face to face. >> It's great to meet you in person finally. >> So Brian, tell us about InfluxData. People might not be familiar with the company. >> Sure, yes. InfluxData, we're the company behind a pretty well-known project called Influx DB. And we're a platform for handling time series data. And so what time series data is, is really it's any, we think of it as any data that's stamped in time in some way. That could be every second, every two minutes, every five minutes, every nanosecond, whatever it might be. And typically that data comes from, you know, of course, sources and the sources are, you know, they could be things in the physical world like devices and sensors, you know, temperature gauges, batteries. Also things in the virtual world and, you know, software that you're building and running in the cloud, you know, containers, microservices, virtual machines. So all of these, whether in the physical world or the virtual world are kind of generating a lot of time series data and our platforms are designed specifically to handle that. >> Yeah so, lots to unpack here Arwa, I mean, I've kind of followed you since we met on virtually. Kind of followed your career and I know when you choose to come to a company, you start with the customer that's what your that's your... Those are your peeps. >> Arwa: Absolutely. >> So what was it that drew you to InfluxData, the customers were telling you? >> Yeah, I think what I saw happening from a marketplace is a few paradigm shifts, right? And the first paradigm shift is obviously what the cloud is enabling, right? So everything that we used to take for granted, when you know, Andreessen Horowitz said, "software was eating the world", right? And then we moved into apps are eating the world. And now you look at the cloud infrastructure that, you know, folks like AWS have empowered, they've allowed services like ours and databases, and sort of querying capabilities like Influx DB to basically run at a scale that we never would have been able to do. Just sort of with, you know, you host it yourself type of a situation. And then the other thing that it's enabled is again, if you go back to sort of database history, relational, right? Was humongous, totally transformed what we could do in terms of transactional systems. Then you moved into sort of the big data, the Hadoops, the search, right. The elastic. And now what we're seeing is time series is becoming the new paradigm. That's enabling a whole set of new use cases that have never been enabled before, right? So people that are generating these large volumes of data, like Brian talked about and needing a platform that can ingest millions of points per second. And then the ability to query that in real time in order to take that action and in order to power things like ML and things like sort of, you know, autonomous type capabilities now need this type of capability. So that's all to know >> Okay so, it's the real timeness, right? It's the use cases. Maybe you could talk a little bit more about those use cases and--- >> Sure, sure. So, yeah so we have kind of thinking about things as both the kind of virtual world where people are pulling data off of sources that are in infrastructure, software infrastructure. We have a number like PayPal is a customer of ours, and Apple. They pull a time series data from the infrastructure that runs their payments platform. So you can imagine the volume that they're dealing with. Think about how much data you might have in like a regular relational scenario now multiply every that, every piece of data times however, often you're looking at it. Every one second, every 10 minutes, whatever it might be. You're talking about an order of magnitude, larger volume, higher volume of data. And so the tools that people were using were just not really equipped to handle that kind of volume, which is unique to time series. So we have customers like PayPal in kind of the software infrastructure side. We also have quite a bit of activity among customers on the IOT side. So Tesla is a customer they're pulling telematics and battery data off of the vehicle, pulling that back into their cloud platform. Nest is also our customer. So we're pretty used to seeing, you know, connected thermostats in homes. Think of all the data that's coming from those individual units and their, it's all time series data and they're pulling it into their platform using Influx. >> So, that's interesting. So Tesla take that example they will maybe persist some of the data, maybe not all of it. It's a femoral and end up putting some of it back to the cloud, probably a small portion percentage wise but it's a huge amount of data of data, right? >> Brian: Yeah. >> So, if they might want to track some anomalies okay, capture every time animal runs across, you know, and put that back into the cloud. So where do you guys fit in that analysis and what makes you sort of the best platform for time series data base. >> Yeah, it's interesting you say that because it is a femoral and there are really two parts of it. This is one of the reasons that time series is such a challenge to handle with something that's not really designed to handle it. In a moment, in that minute, in the last hour, you have, you really want to see all the data you want all of what's happening and have full context for what's going on and seeing these fluctuations but then maybe a day later, a week later, you may not care about that level of fidelity. And so you down sample it, you have like a, kind of more of a summarized view of what happened in that moment. So being able to kind of toggle between high fidelity and low fidelity, it's a super hard problem to solve. And so our platform Influx DB really allows you to do that. >> So-- >> And that is different from relational databases, which are great at ingesting, but not great at kicking data out. >> Right. >> And I think what you're pointing to is in order to optimize these platforms, you have to ingest and get rid of data as quickly as you can. And that is not something that a traditional database can do. >> So, who do you sell to? Who's your ideal customer profile? I mean, pretty diverse. >> Yeah, It, so it tends to focus on builders, right? And builders is now obviously a much wider audience, right? We used to say developers, right. Highly technical folks that are building applications. And part of what we love about InfluxData is we're not necessarily trying to only make it for the most sophisticated builders, right? We are trying to allow you to build an application with the minimum amount of code and the greatest amount of integrations, right. So we really power you to do more with less and get rid of unnecessary code or, you know, give you that simplicity. Because for us, it's all about speed to market. You want an application, you have an idea of what it is that you're trying to measure or monitor or instrument, right? We give you the tools, we give you the integrations. We allow you to have to work in the IDE that you prefer. We just launched VS Code Integration, for example. And that then allows these technical audiences that are solving really hard problems, right? With today's technologies to really take our product to market very quickly. >> So, I want to follow up on that. So I like the term builder. It's an AWS kind of popularized that term, but there's sort of two vectors of that. There's the hardcore developers, but there's also increasingly domain experts that are building data products and then more generalists. And I think you're saying you serve both of those, but you do integrations that maybe make it easier for the latter. And of course, if the former wants to go crazy they can. Is that a right understanding? >> Yes absolutely. It is about accessibility and meeting developers where they are. For example, you probably still need a solid technical foundation to use a product like ours, but increasingly we're also investing in education, in videos and templates. Again, integrations that make it easier for people to maybe just bring a visualization layer that they themselves don't have to build. So it is about accessibility, but yes obviously with builders they're a technical foundation is pretty important. But, you know, right now we're at almost 500,000 active instances of Influx DB sort of being out there in the wild. So that to me shows, that it's a pretty wide variety of audiences that are using us. >> So, you're obviously part of the AWS ecosystem, help us understand that partnership they announced today of Serverless for Kinesis. Like, what does that mean to you as you compliment that, is that competitive? Maybe you can address that. >> Yeah, so we're a long-time partner of AWS. We've been in the partner network for several years now. And we think about it now in a couple of ways. First it's an important channel, go to market channel for us with our customers. So as you know, like AWS is an ecosystem unto itself and so many developers, many of these builders are building their applications for their own end users in, on AWS, in that ecosystem. And so it's important for us to number one, have an offering that allows them to put Influx on that bill so we're offered in the marketplace. You can sign up for and purchase and pay for Influx DB cloud using or via AWS marketplace. And then as Arwa mentioned, we have a number of integrations with all the kind of adjacent products and services from Amazon that many of our developers are using. And so when we think about kind of quote and quote, going to where the developer, meeting developers where they are that's an important part of it. If you're an AWS focused developer, then we want to give you not only an easy way to pay for and use our product but also an easy way to integrate it into all the other things that you're using. >> And I think it was 2012, it might've even been 11 on theCUBE, Jerry Chen of Greylock. We were asking him, you think AWS is going to move up the stack and develop applications. He said, no I don't think so. I think they're going to enable developers and builders to do that and then they'll compete with the traditional SaaS vendors. And that's proved to be true, at least thus far. You never say never with AWS. But then recently he wrote a piece called "Castles on the Cloud." And the premise was essentially the ISV's will build on top of clouds. And that seems to be what you're doing with Influx DB. Maybe you could tell us a little bit more about that. We call it super clouds. >> Arwa: That's right. >> you know, leveraging the 100 billion dollars a year that the hyperscalers spend to develop an abstraction layer that solves a particular problem but maybe you could describe what that is from your perspective, Influx DB. >> Yeah, well increasingly we grew up originally as an open source software company. >> Dave: Yeah, right. >> People downloaded the download Influx DB ran it locally on a laptop, put up on the server. And, you know, that's our kind of origin as a company, but increasingly what we recognize is our customers, our developers were building on the building in and on the cloud. And so it was really important for us to kind of meet them there. And so we think about, first of all, offering a product that is easily consumed in the cloud and really just allows them to essentially hit an end point. So with Influx DB cloud, they really have, don't have to worry about any of that kind of deployment and operation of a cluster or anything like that. Really, they just from a usage perspective, just pay for three things. The first is data in, how much data are you putting in? Second is query count. How many queries are you making against? And then third is storage. How much data do you have and how long are you storing it? And really, it's a pretty simple proposition for the developer to kind of see and understand what their costs are going to be as they grow their workload. >> So it's a managed service is that right? >> Brian: It is a managed service. >> Okay and how do you guys price? Is it kind of usage based. >> Total usage based, yeah, again data ingestion. We've got the query count and the storage that Brian talked about, but to your point, back to the sort of what the hyperscalers are doing in terms of creating this global infrastructure that can easily be tapped into. We then extend above that, right? We effectively become a platform as a service builder tool. Many of our customers actually use InfluxData to then power their own products, which they then commercialize into a SaaS application. Right, we've got customers that are doing, you know, Kubernetes monitoring or DevOps monitoring solutions, right? That monitor, you know, people's infrastructure or web applications or any of those things. We've got people building us into, you know, Industrial IoT such as PTC's ThingWorx, right? Where they've developed their own platform >> Dave: Very cool. >> Completely backed up by our time series database, right. Rather than them having to build everything, we become that key ingredient. And then of course the fully cloud managed service means that they could go to market that much quicker. Nobody's for procuring servers, nobody is managing, you know, security patches any of that, it's all fully done for you. And it scales up beautifully, which is the key. And to some of our customers, they also want to scale up or down, right. They know when their peak hours are or peak times they need something that can handle that load. >> So looking ahead to next year, so anyway, I'm glad AWS decided to do re:Invent live. (Arwa mumbling) >> You know, that's weird, right? We thought in June, at Mobile World Congress, we were going to, it was going to be the gateway to returning but who knows? It's like two steps forward, one step back. One step forward, two steps back but we're at least moving in the right direction. So what about for you guys InfluxData? Looking ahead for the coming year, Brian, what can we expect? You know, give us a little view of sharp view of (mumbles) >> Well kind of a keeping in the theme of meeting developers where they are, we want to build out more in the Amazon ecosystem. So more integrations, more kind of ease of use for kind of adjacent products. Another is just availability. So we've been, we're now on actually three clouds. In addition to AWS, we're on Azure and Google cloud, but now expanding horizontally and showing up so we can meet our customers that are working in Europe, expanding into Asia-Pacific which we did earlier this year. And so I think we'll continue to expand the platform globally to bring it closer to where our customers are. >> Arwa: Can I. >> All right go ahead, please. >> And I would say also the hybrid capabilities probably will also be important, right? Some of our customers run certain workloads locally and then other workloads in the cloud. That ability to have that seamless experience regardless, I think is another really critical advancement that we're continuing to invest in. So that as far as the customer is concerned, it's just an API endpoint and it doesn't matter where they're deploying. >> So where do they go, can they download a freebie version? Give us the last word. >> They go to influxdata.com. We do have a free account that anyone can sign up for. It's again, fully cloud hosted and managed. It's a great place to get started. Just learn more about our capabilities and if you're here at AWS re:Invent, we'd love to see you as well. >> Check it out. All right, guys thanks for coming on theCUBEs. >> Thank you. >> Dave: Great to see you. >> All right, thank you. >> Awesome. >> All right, and thank you for watching. Keep it right there. This is Dave Vellante for theCUBEs coverage of AWS re:Invent 2021. You're watching the leader in high-tech coverage. (upbeat music)

>>Welcome everybody to the cubes live coverage of AWS reinvent 2021. We're here in the main hall. Yes, this is a physical event. It's a hybrid event, probably the industry's most important hybrid event in the year. We're super excited to be here. Of course, last year during the lockdown, reinvent was purely virtual. This year. They go in hybrid 20 plus thousand people. I hear the whisper numbers like 25, 20 7,000 hundreds of thousands of people online. The cubes here, two sets, we've got two remote studios, super excited. I'd like to introduce my co-host David Nicholson. He'll be here all week with us. Uh, John furrier is also here, Lisa Martin for the cubes wall-to-wall coverage. And we're so psyched to start off this session with Kenneth Chestnut. Who's the head of technology partnerships at Stripe. Stripe's an amazing company, Ken. Great to see you. Thanks for coming on. >>Thanks for having me, Dave and David. I greatly appreciate it. How about this? >>Right. Finally live event. We've done a few. We probably done four or five this year, but >>It's good to be back in person. It is. Yeah, absolutely. It's >>A Stripe. I mean, wow. Can a powering the new economy. Tell us a little bit more for those people who may not be familiar with Stripe. They probably use it without even knowing it when they sign it away. Yeah. So tell us about the >>Well, uh, Stripe was founded in 2010 by two brothers, Patrick and John Colson. And really it was from their first business and realizing how hard it was to actually charge for things on online. Um, you had to acquire a relationship with, uh, with a gateway provider to accept payments. You had to acquire a relationship with a, with a acquiring bank. Um, and you had to do that for each and every country that you wanted to service. Uh, so the same way that AWS reduced the barrier in terms of not having to procure, spend millions of dollars on storage, computers, networking, uh, effectively, what we we've done at Stripe is reduce the barriers around economic infrastructure, accepting payments online, >>Use that undifferentiated heavy lifting for payments. So describe Ken, what it was like kind of pre Stripe. You would literally have to install servers, get storage and put, put software on there, get a database. And then what if you had any money left over, you can actually do some business, but, but describe the sort of what the experience is like with Stripe. >>Sure. So, uh, the R R with, with Stripe, we literally talk about seven lines of code. So we, we allow any developer to, um, uh, provide a set of APIs for any developer to accept payments on online. And we do the undifferentiated heavy lifting in terms of accepting payments, accepting those payments, processing them revenue, reporting, and reconciliation, um, all ensuring compliance and security. Um, so it's like you said, uh, taking care of the undifferentiated heavy lifting are around accepting payments online in the enabling >>The enabler. There is the cloud. I mean, it was 2009, 2010. You guys were founded, the cloud was only like three years old. Right. And so you had to really sort of take a chance on leveraging the cloud or maybe early on you just installed it yourself and said, this isn't going to scale. So maybe tell us how you sort of leverage the cloud. >>Sure. Um, so we're a long time, uh, AWS, uh, customer and user, um, uh, back in the early days of, of Stripe in the early days of, of AWS. And we've just grown, uh, with, with AWS and the ecosystem. And it's interesting because a lot of, uh, a lot of the companies that have been built on, on AWS and grown to be successful, they're also Stripe customers as well. So they use Stripe for their economic infrastructure. >>We use Stripe, we run our company on AWS and we use Stripe. It it's true. The integration took like minutes. It was so simple. Hey it, test it, make sure it scales. But so what, what's the stack look like? What is there, is there such thing as a payment stack? What's the technology stuff? >>Sure. So we initially started with payments and being able to accept payments, uh, on online. Uh we've we brought in out our, our, our Stripe product portfolio now to effectively provide economic, uh, infrastructure for the internet. So that could be accepting payments. Uh, it could be setting up marketplaces. So companies like Lyft and Deliveroo, uh, use Stripe to power their marketplaces with their, with their drivers and, and, um, uh, delivers, um, uh, we provide, uh, a product called radar that, uh, that, um, prevents fraud, uh, around, around the globe. Um, based upon the data that we're seeing from our, from our customers, um, we have, uh, issuing and treasury so that companies can provide their users or their merchants with banking services. So loans, uh, issuing credit cards. So we we've really broadened out the product portfolio of Stripe to provide sort of economic infrastructure for the internet. So >>We talked about strike being in the cloud from an infrastructure perspective and how that enables certain things, but that in and of itself, doesn't change the dynamics around sovereignty and governance from country to country. Sure. Uh, I imagine that the global nature of AWS sort of dovetails with your strategy, but how, how do you address that? It's one thing to tell me in Northern California, you can process payments for me, but now globally go across 150 countries. How do you make that work? Yeah, >>Uh, absolutely. So we, we establish relationships, uh, within, within each company country that we operate in we're in about 47, uh, countries, uh, today, um, and that's rapidly expanding so that companies can, can process or accept payments and do, uh, financial transactions within, within, within those countries. So we're in 47 countries today. We, we accept a multitude of different payment, uh, different currencies, different payment types. So the U S is very, uh, credit card focused. But if you go to other, other parts of the globe, it could be a debit cards. It could be, um, uh, wallets, uh, uh, Google pay, Ali pay, uh, others. So really it's, uh, providing sort of the payment methods that users prefer in, in the different countries, uh, and meeting and meeting those users where, where they are. >>Are you out of the box compliant? What integration is required to do that? Uh, what about things like data sovereignty, is that taken care of by the cloud provider or you guys, and where, w w where does, where does AWS end and you guys pick up? Yes, >>We're, we're PCI compliant. Um, we, we leverage AWS as our, as our infrastructure, um, to grow, grow and scale. So, um, one of the things that we're, we're proud of is, uh, through, throughout 2020 and 2021, we've, we've had 11 nines of, uh, of, of, uh, or five nines of uptime, um, even through, um, uh, black Friday and cyber Monday. So providing AWS provides that, that infrastructure, which we built on top of to provide, uh, you know, five nines of uptime for our, for our users. >>You describe in more detail, Kenya, your ecosystem. I mean, you're responsible for tech partnerships. What does that ecosystem, how I paint a picture of it? >>Sure. So, um, uh, a number of users want to be able to use Stripe with, with their other, uh, it infrastructure and, and their business processes. So a customer may start, uh, with a salesperson may start with a quote or order, uh, in, in Salesforce, want to automate the invoicing and billing and payment of that with, with Stripe and then, uh, reconcile re revenue and an ERP solution like SAP or Oracle or NetSuite or into it, um, in the case of, of small, medium businesses. So really, um, what we're focused on is building out that, that ecosystem to allow, uh, um, our, our customers to streamline their business processes, um, and, and integrate Stripe into their existing it infrastructure and, and business processes. >>You mentioned a lot of different services, but broadly speaking, if I think about payments, correct me if I'm wrong, but you were one of the early, uh, sort of software companies, if I can call you that, um, platforms, whatever, but to really focus on a usage based pricing, but how do I, how do I engage with you? What's, what's the pricing model. Maybe you could describe that a little. >>Sure. So the pricing model is very, very transparent. Uh, it's on, it's on the website. So, uh, we, we take a, um, a percentage of each transaction. So literally you can, you can set up a, a Stripe account it's self-service, um, uh, we, we take a 2.9% plus 30 cents on every, uh, Tran transaction. Um, we don't, you don't start getting, um, uh, charged until, uh, you start accepting payments from your, from your customers or from your users. >>Um, can you give us a sense of the business scope, maybe any metrics you can share, customers, whatever. >>Sure. So there's a couple of things we can share publicly, just in terms of the size of the business. I think since, uh, since 2020, uh, more than 2 million businesses have launched on, on Stripe. Uh, so, uh, 2 million in, in, in, in 2020, um, we've, uh, uh, in the past 12 months, we've, uh, uh, uh, processed over 173 billion, uh, API calls. Uh, we do we process about, um, uh, hundreds of billions of, of, of, uh, payment volume, uh, every, every year. Um, if you look at sort of the macros of the business, the business is growing faster than the broader e-commerce space. So the amount of payment volume that we did in this past year is more than the entire industry did when Patrick and John founded the company. And in 2010, just to give you a, uh, an idea of the, the, the size of the business and sort of the pace of the business >>You're growing as e-commerce grows, but you're also stealing share from other sort of traditional payment systems. Okay. So that's a nice flywheel effect. And of course, Stripe's a private company they've raised well over a billion dollars of Peter teal, and it wasn't original founders, so are funders. So, you know, that's, he's talking scale. I want to go back to something you said about radar. Sure. So there's tech in your stack fraud detection, right. So some of >>That in machine learning, right. >>So, and so you guys, I mean, are you a technology company, are you a F a FinTech company? What are you? >>We're a software company. We provide software and we provide technology for developers, uh, to make online businesses and make, uh, uh, commerce, uh, more seamless and more frictionless >>Cloud-first API first. I mean, maybe describe how that is different maybe than, you know, the technical debt that's been built up over, you know, decades with traditional payment systems. >>Yes, it's very similar to the early, earlier days of AWS where a lot of tech forward companies leveraged Stripe, um, to, um, whether it be large enterprises to transform their businesses and move online, or, or, uh, uh, startups and developers that want to, uh, start a new business online and, and do that, uh, as quickly and seamlessly as possible. So it's, it's quite the gamut from large enterprises that are digitally transforming themselves companies like Marske and, and NASDAQ and others, as well as, uh, um, startups and developers that have started their businesses and born on born on Stripe. So >>When you talk about a startup, how small of an entity makes sense, uh, when you think of, if you look at, from an economic perspective, lowering the friction associated with transactions can lift up a large part of the world with sort of, you know, w with very, very small businesses. Is that something that this is all about? >>Yeah, absolutely. So, like I said, you know, two, 2 million business have sub launched on, on, on Stripe, uh, in, in the past year. And, and those businesses vary, but it could be literally a, a developer or a, uh, uh, a small, uh, SMB that wants to be able to accept payments on online. And it can just set up a Stripe account and start accepting payments. >>Yeah. So this is not a one hit wonder, um, lay out the vision for Stripe, right? I mean, you're, you're a platform, uh, you're, you're becoming a fundamental ingredient of the digital economy sounds pre pandemic. That was all a bunch of buzzwords, but today we all know how important that is, but what lay out the vision for us can, >>Yeah, it really are. The mission of Stripe is to grow the GDP of the internet. Um, and, and so what that means is, uh, more and more our, our, our basic belief is more and more and more businesses, uh, will, will, uh, go, go online, uh, with, uh, with the pandemic that that was, uh, accelerated. But I think that the general trend of businesses moving online, uh, will continue to accelerate, and we want to provide, uh, economic infrastructure to support those businesses. Um, you know, um, uh, uh, Andreessen talked about sort of software, software eating the world well fit. Our belief has FinTech is eating software. So in, in the fullness of time, I think the opportunity is for, uh, any, any company to be a financial services company. And we want to empower any company that wants to, or any user that wants to be a financial services company to, to provide the economic infrastructure for them to do so. >>And, and, you know, I mean your data company in that sense, you're moving bits around, you know, and those datas, I like to say data's eating software, you know, cause really you gotta have your data act together. Absolutely. And that's an evolving, I mean, you guys started to, to 2010, I would imagine your data strategy has evolved quite dramatically. Yeah. >>It's a great, it's a great call out Dave. Uh, one of our other products is a product called Sigma. So Sigma allows, uh, merchants or our customers to query payment and transaction data. So they want to be able to understand who, who, who are their customers, what are the payment methods that those customers prefer in different countries, in different regions? Um, so we're, we're starting to have some interesting use cases, um, working with, with AWS and other partners when you can start combining payment and transaction data in Stripe with other data to understand customer segmentation, customer 360 lifetime value of a customer customer acquisition costs, being able to close the books faster in your ERP, because you can apply that payment and transaction data to your general ledger to, to close the books faster at the end of the month or at the end of the, at the end of the year. So, uh, yeah, we we're, um, uh, as, as more and more companies are using Stripe, um, they want to be able to take advantage of that data and combine it with other, other sources of data to drive business. >>Yeah. You mentioned some of those key metrics that are, that are so important to companies today. I'll give you the last word re-invent this hall is packed, um, a little bit surprising, frankly, you know, but, uh, but exciting. Uh, what are you looking forward to this? >>Yeah, I'm just looking forward to meeting people in person again, it's, uh, it's great to be here and, and, you know, uh, uh, we have a strong relationship with AWS. We have lots of partners in, in, in common here, uh, as well, both consulting partners and technology partners. So really looking forward to meeting with partners and customers, and especially as we, as we plan for next year and, uh, launching our, our, our partner program beginning of next year. Uh, there's a lot of, uh, uh, groundwork and things to learn from, from here. As we, as we, we, we, we launch our, our, our partner business formula next >>I'll bet. Looking forward to that, Ken, thanks so much for coming to the cure. You so much. It was great to have a chat at the time. All right. And we want to thank our sponsors, uh, AWS, of course, and also AMD who's making the editorial segments that we bring you this week possible for Dave Nicholson. I'm Dave Volante. You're watching the cube at AWS reinvent 2021. Keep it right there, right back.

[Music] hello and welcome to this power panel where we go deep with three storage industry vets two from infinidat in an analyst view to find out what's happening in the high-end storage business and what's new with infinidat which has recently added significant depth to its executive ranks and we're going to review the progress on infinidat's infinibox ssa a low-latency all-solid state system designed for the most intensive enterprise workloads to do that we're joined by phil bullinger the chief executive officer of it finidet ken steinhardt is the field cto at infinidat and we bring in the analyst view with eric bergener who's the vice president of research infrastructure systems platforms and technologies group at idc all three cube alums gents welcome back to the cube good to see you thanks very much dave good to be here thanks david as always a pleasure phil let me start with you as i mentioned up top you've been top grading your team we covered the herzog news beefing up your marketing and also upping your game and emea and apj go to market recently give us the business update on the company since you became ceo earlier this year yeah dave i'd be happy to you know the uh i joined the company in january and it's been a it's been a fast 11 months uh exciting exciting times at infinidad as you know really beginning last fall the company has gone through quite a renaissance a change in the executive leadership team uh i was really excited to join the company we brought on you know a new cfo new chief human resources officer new chief legal officer operations head of operations and most recently as has been you know widely reported we brought in eric to head up our marketing organization as a cmo and then last week richard bradbury in in london to head up international sales so very excited about the team we brought together it's uh it's resulted in or it's been the culmination of a lot of work this year to accelerate the growth of infinidat and that's exactly what we've done it's the company has posted quarter after quarter of significant revenue growth we've been accelerating our rate and pace of adding large new fortune 500 global 2000 accounts and the results show it definitely the one of the most exciting things i think this year has been infinidat has pretty rapidly evolved from a single product line uh company around the infinibox architecture which is what made us unique at the start and still makes us very unique as a company and we've really expanded out from there on that same common software-defined architecture to the ssa the solid state array which we're going to talk about in some in some depth today and then our backup appliance our data protection appliance as well all running the same software and what we see now in the field uh many customers are expanding quickly beyond you know the traditional infinibox business uh to the other parts of our portfolio and our sales teams in turn are expanding their selling motion from kind of an infinibox approach to a portfolio approach and it's it's really helping accelerate the growth of the company yeah that's great to hear you really got a deep bench and of course you you know a lot of people in the industry so you're tapping a lot of your your colleagues okay let's get into the market i want to bring in uh the analyst perspective eric can you give us some context when we talk about things like ultra low latency storage what's the market look like to you help us understand the profile of the customer the workloads the market segment if you would well you bet so i'll start off with a macro trend which is clearly there's more real-time data being captured every year in fact by 2024 24 of all of the data captured and stored will be real-time and that puts very different performance requirements on the storage infrastructure than what we've seen in years past a lot of this is driven by digital transformation we've seen new workload types come in big data analytics real-time big data analytics and obviously we've got legacy workloads that need to be handled as well one other trend i'll mention that is really pointing up this need for low latency consistent low latency is workload consolidation we're seeing a lot of enterprises look to move to fewer storage platforms consolidate more storage workloads onto fewer systems and to do that they really need low latency consistent low latency platforms to be able to achieve that and continue to meet their service level agreements great thank you for that all right ken let's bring you into the conversation steiny what are the business impacts of of latency i want you to help us understand when and why is high latency a problem what are the positive impacts of having a consistent low latency uh opportunity or option and what kind of workloads and customers need that right the world has really changed i mean when when dinosaurs like me started in this industry the only people that really knew about performance were the people in the data center and then as things moved into online computing over the years then people within your own organization would care about performance if things weren't going well and it was really the erp revolution the 1990s that sort of opened uh people's eyes to the need for performance particularly for storage performance where now it's not just your internal users but your suppliers are now seeing what your systems look like fast forward to today in a web-based internet world everyone can see with customer facing applications whether you're delivering what they want or not and to answer your question it really comes down to competitive differentiation for the users that can deliver a better user customer experience if you and i'm sure everybody can relate if you go online and try to place an order especially with the holiday season coming up if there's one particular site that is able to give you instantaneous response you're more likely to do business there than somebody where you're going to be waiting and it literally is that simple it used to be that we cared about bandwidth and we used to care about ios per second and the third attribute latency really has become the only one that really matters going forward we found that most customers tell us that these days almost anyone can meet their requirements for bandwidth and ios per second with very few outlying cases where that's not true but the ever unachievable zero latency instantaneous response that's always going to be able to give people competitive differentiation in everything that they do and whoever can provide that is going to be in a very good position to help them serve their customers better yeah eric that stat you threw out of 24 real time uh and that that sort of underscores the need but phil i wonder how how this fits if you could talk about how that fits into your tam expansion strategy i think that's the job of of every ceo is to think about the expanding the tam it seems like you know a lot of people might say it's not necessarily the largest market but it's strategic and maybe opens up some downstream opportunities is that how you're thinking about it or based on what ken just said you expect this to to grow over time oh we definitely expect it to grow uh dave you know the the history of infinidat has been around our infinibox product targeting the primary storage market at the at the higher end of that market you know it's we've enjoyed operating in a eight nine 10 billion dollar tan through the years and that it continues to grow and we continue to outpace market growth within that tam which is exciting what this uh what the ssa really does is it opens up a tier of workload performance that we see more and more emerging in the primary data center the infinibox classic infinibox architecture we have very very fast as we say it typically outperforms most of our all-flash uh array competitors but clearly there there are a tier of workloads that are growing in the data center that require very very tight tail latencies and and that segment is certainly growing it's where some of the most demanding workloads are on the infinibox ssa was really built to expand our participation in those segments of the market and as i mentioned up front at the same time also taking that that software architecture and moving it into the the data protection space as well which is a whole nother market space that we're opening up for the company so we really see our tam this year with more of the this portfolio approach expanding quite a bit eric how how do you see it well those real-time applications that you talked about that require that consistent ultra-low latency grow kind of in in parallel with that that time curve you know will they become a bigger part of that the the overall storage team and and the workload mix how does idc see it yeah so so they actually are going to be growing over time and a lot of that's driven by the fact of the expectations that um steinhart mentioned a little bit earlier just on the part of customers right what they expect when they interact with your i.t infrastructure so we see that absolutely growing going forward i will make a quick comment about you know when all flash arrays first hit back in 2012 um in the 10 years since they started shipping they now generate over 80 of the primary revenues out there in in the primary storage arena so clearly they've taken over an interesting aspect of what's going on here is that a lot of companies now write rfps specifically requiring an all-flash array and what's going to be interesting for infinidat is despite the fact that they could deliver better performance than many of those systems in the past they couldn't really go after the business where that rfp was written for an afa spec well now they'll certainly have the opportunity to do that in my estimation that's going to give them access to about an additional 5 billion in tam by 2025 so this is big for them as a company yeah that's a 50 increase in tamp so okay well eric you just set up my my follow-up question to you ken was going to be the tougher questions uh which we've you and i have had some healthy debates about this but i know you'll have answers so so for years you've argued that your cached architecture and magic sauce algorithms if i caught that could outperform all flash arrays we're using spinning disks so eric talked about the sort of check off item but are there other reasons for the change of heart why and why does the world need another afa doesn't this cut against your petabyte scale messaging i wonder if you could sort of add some color to that sure a great question and the good news is infinibox still does typically outperform all flash arrays but usually that's for average of latency performance and we're tending to get because we're a a caching architecture not a tiered architecture and we're caching to dram which is an order of magnitude faster than flash or even storage class memory technologies it's our software magic and that software defined storage approach that we've had that now effectively is extended to solid state arrays and some customers told us that you know we love your performance it's incredible but if you could let us effectively be confident that we're seeing you know some millisecond sub half millisecond performance consistently for every single io you're going to give us competitive differentiation and this is one of the reasons why we chose to call the product a solid state array as opposed to merely an all-flash array the more common ubiquitous term and it's because we're not dependent on a specific technology we're using dram we can use virtually any technology on the back end and in this case we've chosen to use flash but it's the software that is able to provide that caching to the front end dram that makes things different so that's one aspect is it's the software that really makes the difference it's been the software all along and still on this architecture still mentions going to across the multiple products it's still the software it's also that in that class of ultra high performance architecturally because it is based on the infinibox architecture we're able to deliver 100 availability which is another aspect that the market has evolved to come to expect and it's not rocket science or magic how we do it the godfather of computer science john von neumann all the way back in the 1950s theorized all the way back then that the right way to do ultra high availability and integrity in i.t systems of any type is in threes triple redundancy and in our case amazingly we're the only architecture that uses triple redundant active active components for every single mission critical component on the system and that gives a level of confidence to people from an availability perspective to go with that performance that is just unmatched in the market and then bring all of that together with a set it and forget it mentality for ease of use and simplicity of management and as phil mentioned being able to have a single architecture that can address now not only the ultra high performance but across the entire swath of as eric mentioned consolidation which is a key aspect as well driving this in addition to those real-time applications that he mentioned and even being able to take it down into our our infiniguard data protection device but all with the same common base of software common interface common user experience and unmatched availability and we've got something that we really think people are going to like and they've certainly been proving that of late well i was going to ask you you know what makes the the infinibox ssa different but i think you just laid it out but your contention is this is totally unique in the marketplace is that right ken yes indeed this is a unique architecture and i i literally as a computer scientist myself truly am genuinely surprised that no other vendor in the market has taken the wisdom of the godfather of computer science john von neumann and put it into practice except in the storage world for this particular architecture which transcends our entire realm all the way from the performance down to the data protection phil i mean you have a very wide observation space in this industry and a good strong historical perspective do you think the expectations for performance and this notion of ultra low latencies you know becoming more demanding is is there a parallel so first of all why is that we've talked about a little bit but is there a parallel to the way availability remember you could have escalated over the years um because it was such a problem and now it's really become table stakes and that last mile is so hard but what are your thoughts on that i i think i think absolutely dave you know the the hallmark of infinidat is this white glove concierge level customer experience that we deliver and it's it's affirmed uh year after year in unsolicited enterprise customer feedback uh above every other competitor in our space uh infinidat sets itself apart for this um and i think that's a big part of what continues to drive and fuel the growth and success of the company i just want to touch on a couple things that ken and and eric mentioned the ssa absolutely opens up our tan because we get to we get a lot more at bats now but i think a lot of the industry looks at infinidat as well those guys are are hard drive zealots right they've their architecture is all based on rotating disk that's what they believe in and it's a hybrid versus afa world out there and they were increasingly not on the right bus and that's just absolutely not true in that our our neural cache and what ken talked about what made us unique at the start i think actually only increasingly differentiates us going forward in terms of the the set it and forget it the intelligence of our architecture the ability of that dram based cache to adapt so dynamically without any knobs and and configuration changes to massive changes in workload scale and user scale and it does it with no drama in fact most of our customers the most common feedback we get is that your platform just kind of disappears into our data infrastructure we don't think about it we don't worry about it when we install an infiniti an infinidat rack our intentions are never to come back you know we're not there showing up with trays of disk under our arms trying to upgrade a mission-critical platform that's just not our model what the ssa does is it gives our customers choice it's not about infinidat saying that used to be the shiny object now this is our new shiny object please everybody now go buy that what where where we position our ssa is it's a it's a tco latency sla choice that they can make between exactly identical customer experiences so instead of an old hybrid and a new afa we've got that same software architecture set it and forget it the neural cache and customers can choose what back-end persistent store they want based on the tco and the sla that they want to deliver to a given set of applications so probably the most significant thing that i've seen happen in the last six months at infinidat is a lot of our largest customers the the fortune 15s the fortune 50s the fortune 100s who have been long-standing infinidat customers are now on almost every sort of re-tranche of or trancha purchase orders into us we're now seeing a mix we're seeing a mix of some ssa and some classic infinibox because they're mixing and matching in a given data center down a given row these applications need this sla these applications need this la and we're able to give them that choice and frankly we don't we don't intentionally try to steer them one direction or the other they they're smart they do the math they can pick and choose what experience they want knowing that irrespective of what front door they go through into the infinidat portfolio they're going to get that same experience so i'm hearing it's not just a an rfp check off item it's more than that the market is heading in that direction eric's data on on real time and we're certainly seeing that the data-driven applications the injection of ai and you know systems making decisions in in real time um and i i'm also hearing phil that you're building on your core principles i'm hearing the white glove service the media agnostic the set it and forget it sort of principles that you guys were founded on is you're carrying that through to this this opportunity we absolutely are in the reason and you ask a good question before and i want to more completely answer it i think availability and customer experience are incredibly important today more so than ever because data center economics and data center efficiency um are more important than ever before is as customers evaluate what workloads belong in the public cloud what workloads do i want on-prem irrespective of those decisions they're trying to optimize their their operational expenses their capex expenses and so one thing that infinidat has always excelled at is consolidation bringing multiple users multiple workloads into the same common platform in the data center it says floor space and watts and and uh you know storage administration resources but to do consolidation well you've got to be incredibly reliable and incredibly predictable without a lot of fuss and drama associated with it and so i think the thing that has made infinidat really strong through the years with being a very good consolidation platform is more important now than ever before in in the enterprise storage space because it is really about data center efficiency and uh administration efficiency associated with that yeah thank you for that phil now actually ken let me come back to you i want to ask you a question about consolidation and you and i and and doc our business friend rest his soul have had some some great conversations about this over time but but as you consolidate people are sometimes worried about the blast radius could you address that concern sure well um phil alluded to software and uh it is the cornerstone of everything we bring to the table and it's not just that deep learning that transcends all the intelligence phil talked about in terms of that full wide range of product it's also protection of data across multiple sites and in multiple ways so we were very fortunate in that when we started to create this product since it is a modern product we got to start with a clean sheet of paper and basically look at everything that had been done before and even with some of the very people who created some of the original software for replication in the market were able to then say if i could do it again how would i do it today and how would it be better so we started with local replication and snapshot technology which is the foundation for being able to do full active active replication across two sites today where you can have true zero rpo no data loss even in the face of any kind of failure of a site of a server of a network of a storage device of a connection as well as zero rto immediate consistent operation with no human intervention and we can extend from that out to remote sites literally anywhere in the world in multiples where you can have additional copies of information and at any of them you can be using not only for protection against natural disasters and floods and things like that but from a cyber security perspective immutable snapshots being able to provide data that you know the bad actors can't compromise in multiple locations so we can protect today against virtually any kind of failure scenario across the swath of infinibox or infinibox ssa you can even connect infinite boxes and infinibox ssas because they are the same architecture exactly as phil said what we're seeing is people deploying mostly infinibox because it addresses the wide swath from a consolidation perspective and usually just infinibox ssa for those ultra high performance environments but the beauty of it is it looks feels runs and operates as that one single simple environment that's set it and forget it and just let it run okay so you can consolidate with with confidence uh let's end with the the independent analyst perspective eric you know how do you see this offering what do you think it means for the market is this a new category is it an extension to an existing space how do you look at that uh so i don't see it as a new category i mean it clearly falls into the current definition of afas i think it's more important from the point of view of the customer base that likes this architecture likes the availability the functionality the flexibility that it brings to the table and they can leverage it with tier zero workloads which was something that in the past they didn't have that latency consistency to do that you know i'll just make one one final comment on the software side as well so the reason software is eating the world mark andreessen is basically because of the flexibility the ease of use and the economics and if you take a look at how this particular vendor infinidat designed their product with a software-based definition they were able to swap out underneath and create a different set of characteristics with this new platform because of the flexibility in the software design and that's critical one if you think about how software is dominating so today for 2021 68 of the revenue in the external storage market that's the size of the software defined storage market that's going to be going to almost 80 by 2024 so clearly things are moving in the direction of systems that are defined in a software-defined manner yeah and data is eating software which is why you're going to need ultra low latency um okay we got to wrap it eric you've just published a piece uh this summer called enterprise storage vendor infinidat expands total available market opportunities with all flash system introduction i'm sure they can get that on your website here's a little graphic that shows you how to get that but so guys thanks so much for coming on the cube congratulations on the progress and uh we'll be watching thanks steve thanks very much dave thank you as always a pleasure all right thank you for watching this cube conversation everybody this is dave vellante and we'll see you next time [Music] you

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante five publicly traded u.s based companies have market valuations over or just near a trillion dollars as of october 29th apple and microsoft topped the list each with 2.5 trillion followed by alphabet at 2 trillion amazon at 1.7 and facebook now meta at just under a trillion off from a tie of 1.1 trillion prior to its recent troubles these companies have reached extraordinary levels of success and power what if anything could disrupt their market dominance in his book seeing digital author david micheller made three key points that i want to call out first in the technology industry disruptions of the norm the waves of mainframes minis pcs mobile and the internet all saw new companies emerge and power structures that dwarfed previous eras of innovation is that dynamic changing second every industry has a disruption scenario not just the technology industry and third silicon valley broadly defined to include seattle or at least amazon has a dual disruption agenda the first being horizontally disrupting the technology industry and the second as digital disruptors in virtually any industry how relevant is that to the future power structure of the digital industry generally in amazon specifically hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we welcome in author speaker researcher and thought leader david michela to assess what could possibly disrupt today's trillionaire companies and we're going to start with amazon dave good to see you welcome thanks dave good to see you yeah so dave approached us about a month or so ago he was working on these disruption scenarios and we agreed to make this a community research project where we're going to tap the knowledge of the cube crowd and its adjacent communities and to that end we're initiating a community survey that asks folks to rate the likelihood of seven plus one disruption scenarios so we have a slide here that sort of shows what that survey structure is going to look like and so as i say there's seven plus another one which is kind of an open open-ended and we're going to start with amazon as the disruptee so dave you've been writing about the technology industry for decades and digital disruption and china and automation and hundreds of other topics what prompted you to start this project yeah it's a great question you know as you said that the whole history of our business has been you know every decade or so you have a new set of leaders ibm digital microsoft the internet companies etc but when i started looking at it you know that seems in some ways to have actually stopped that you know microsoft is now 40 years old amazon is what 1995 is getting towards 30. you know google's been a dominant company for 20 years and you know apple of course and facebook more recently so so whatever reason this sort of longevity of these firms has been longer than we've seen in the past so i sort of say well is there anything that's going to change that so part of it and we'll get into it is what could happen to disrupt those big five but then the sort of second question was well maybe the uh disruptive energies of the of the tech business have moved elsewhere they've moved to crypto currencies or they've moved to tesla and so you start to sort of broaden your sense of disruption and when you talked about that dual disruption agenda that whole ability of tech to disrupt other sectors banking health care insurance automobiles whatever is sort of a second wave of disruption so uh we started coming out all right what sort of scenarios are we really looking at over say for the 2020s what might shake up the big five as we know them and how might disruption spread to sort of more industry specific parts of the world and that was really the the genesis of the project and really just my own thinking of all right what scenarios can i come up with and then reaching out to companies like yourselves to figure out okay how can we get more input on that how can we crowdsource it how can we get a sense of of what the community thinks of all this it's great love it and as you know we're very open to do that so we're going to crowdsource this we're going to open it up to virtually anyone and use multiple channels so let's go through some of the scenarios all of them actually and explain the reasoning behind their inclusion the first one the govern government mandated separation divestment and or limits on amazon's cloud computing retail media credit card and or in-house product groups it probably no coincidence that this was the first one you chose today but why start here well i think the government interest in doing something to get back at big tech is is pretty clear and probably one of the few things that has bipartisan support in washington these days and also government interventions have always been an enormous part of the tech industry's history the the antitrust efforts against ibm and att in particular and more recently microsoft a smaller one but it's it's always been there there's a vibe to do it now and when you look at all the big ones but particularly amazon you can see that potential divestments and breakups are sitting there right in front of you the separation of retail and aws uh perhaps breaking out credit card or music or media businesses these sorts of things are all on the surface at least relatively clean things to do and i think when you look at the formation of an alphabet or a meta those companies themselves are starting to see their own businesses as consisting of multiple firms yeah so i just want to kind of drill into the cloud piece just to emphasize the importance of aws in the context of amazon amazon announced earnings thursday night after the close aws is now a 64 billion revenue run rate company and they're growing at 39 percent year over year that's actually an accelerated growth rate from q3 2020 when the company was grew at 29 it's astounding think about a company this size moreover aws accounted for more than actually but 100 of amazon's operating profit last quarter so the aws cloud is obviously crucial as a funding vehicle and ecosystem accelerant for amazon and i just wanted to share some data points dave before we move on to these other scenarios yeah and just on that uh i think that is the fundamental point it's very easy to see aws on its own as a powerhouse but i think you know if you figure how much freedom aws money has given the retail business or the credit card business or the music businesses to launch themselves and to essentially make no money for very long periods of time uh you see that you know if you're a walmart trying to compete with amazon as a retailer well that money from aws is is an awful big problem and and so when they look at separation that's the sort of stuff people talk about right so i just want to i want to put that into context just in in terms of the the cloud business so this chart is one from our etr surveys that isolates the four hyperscale cloud providers and adds in oracle and ibm we both own public clouds but don't you know don't have nearly the the scale we don't have apple or facebook they have clouds as well and we can talk about that in a moment but the chart shows net score or spending momentum on the vertical axis and market share or pervasiveness in the survey on the horizontal axis it's it's really mentioned share not dollar market share but it's an indicator and the red line is an indicator of elevated spending momentum and you can see azure and aws they're up and to the right i mean amazon is 64 billion you know uh azure will claim larger because they're including their application business but just their their their i asked business obviously smaller than amazon's but you can see in the survey the respondents define cloud they include that sas business so they they both impressively have this high spending momentum on the vertical axis well above that 40 line despite their size google obviously well behind those to the left and then alibaba which has a small sample in the etr survey it's you know it's not as prominent in china but even though it's ias cloud businesses larger than google's by probably a couple billion dollars now the point is these four hyperscalers and there really are only four in my view anyway they have a presence that allows them to build new businesses and disrupt ecosystems and enact that dual disruption agenda should they choose to do so at least in the case of amazon oracle and ibm are not in a position to do that it's not part of their agenda they don't they don't have that scale but dave can you talk about your dual disruption scenario very clearly amazon fits in there and i would think alibaba as well but what about microsoft facebook apple google yeah i mean you know people often say what's the biggest difference between microsoft and amazon from from a cloud point of view and the answer is pretty clear that microsoft goes out of its way to assure its customers that it really doesn't have any interest in competing directly about them so you don't see microsoft going into the retail business or the banking business or the healthcare business all that seriously in contrast that's really what amazon is all about is taking its capabilities to essentially any industry it likes and therefore as one is as great as the service aws provides it's often being provided to people who amazon is actually competing with at least some degree or another and you know that's a huge part of microsoft's sales pitch and it's certainly a potential vulnerability down the road uh it's very hard in the end to be an essential supplier and a direct competitor at the same time but so far they've managed to do that yeah so we put together just another sort of aside here this little thought experiment to see what aws would look like as a separate entity and so it's a chart that looks at a number of tech companies and lays out their revenue run rate the growth rates gross margin probably should have done operating margin might have been more relevant but market cap and revenue multiple again given the size of aws at 64 billion run rate and accelerating growth trajectory it's just it's remarkable and so we we figured this out based on industry norms and today's valuations it's not inconceivable that aws could be you know in the trillionaire club or close to it so based on that discussion we had earlier amazon amazon's dual disruption agenda being funded by empowered by aws as we just discussed dave yeah and just keep in mind nothing that you or i are saying are predictions or saying that anything is going to happen they are possible scenarios of what might happen that seem to make some plausible sense so that when amazon is making the sort of profits that it's making aws naturally that's going to attract other companies because there's margin to to be had there and similarly you know look at uh you look at microsoft for all those years the profits it made in windows or in office software allowed it to do all kinds of other things and essentially that's what amazon is doing today but if a google or a microsoft could cut into those profits through some sort of aggressive pricing and perhaps we'll talk about that you know that would have a lot of impact on amazon as a whole all right so let's quickly go through the other description scenarios and maybe make some comments the next one sort of major companies increasingly choose to do their own cloud computing and or sell their products directly for competitive cost security or other reasons so dave i saw this and look at a company like walmart and others no way they're going to run their business on aws walmart as we know is building out its own cloud and maybe it doesn't have the size of a hyperscaler but it's very large it's got the technical chops it can most likely do it a lot cheaper than renting cloud space what was your thinking in this scenario yeah the broader thing here is essentially one of that computing paradigms have been proven to go in cycles you know a long time ago people shared computers and called timeshare and then people ran their own and now they're sharing again through the cloud and who knows it's possible that the cycle could shift again through some innovation and you know a lot of companies today look at the bills they're getting for cloud or for various sas services and some of them are pretty high and a lot of them will look at and say hey maybe we actually can do some of this stuff cheaper so the scenario is that essentially the the cycle shifts once again uh and it makes more sense to do stuff in-house again that's not a prediction but uh certainly something that's happened before and couldn't plausibly happen again yeah there's a lot of discussion about that in the industry of martine casado and sarah wong wrote that piece about the you know the trillion dollar basically sucking sound basically saying the the scenario was the the the premise rather was the that that sas companies their cost of goods sold are increasingly going to be you know chewed up by cloud costs and then of course mark andreessen says every company is going to be a sas company so as the sassification of business occurs that's something to consider okay next scenario is environmental policies raise costs change packaging delivery recycling rules and or consumer preferences can you comment dave on your thinking on this scenario yeah first i'll just back up a bit we're used to thinking of technology is the great disrupter and clearly that's still important but there are now other forces out there china which will talk about uh the environment uh various cultural forces and and here with the environment you see all kinds of things that could change that you know if you look at amazon and its model of very high levels of packaging lots of delivery vehicles and all the things it is doing are those necessarily the best environmentally and will there potentially be various taxes carbon metrics or things that might work against that model and tend to favor more traditional stores where people go to pick them up that seems to be a plausible scenario and i think everybody here knows that desire to do something in the in the climate environmental spaces is pretty strong and you know if you look at you know just throws aside the recycling industry itself has arguably been quite a failure in that much of what is so-called recycled is basically put in tankers and shipped to the third world which no longer wants it uh and so the backlog of packaging and concerns about packaging and uh what to do with all that you know those those issues are rising and and will be real and i i don't know whether amazon has a good answer to that they're you know they obviously are very aware of it they're working very hard to do everything they can in that space but their fundamental model of essentially packaging every good in its own little box or envelope or whatever is arguably not the greenest way of doing business got it thank you so okay so the next one is price in slash trade wars with the u.s and or china cloud and e-commerce giant so protectionism favors national players so we talking here about for example google bombing prices or alibaba or trade policy making it difficult for amazon to do business in certain parts of the world can you add some color on this one yeah all those things and i would just start with with china itself you know you could argue that covet has been the biggest disruptor of the last couple years but if you look out the next five or eight you had to look at all these things you'd probably say china the size of the chinese market the power of its vendors players like alibaba clearly can rival amazon in many different ways uh you know it's no secret that it'd be hard for amazon to they're not going to be a big success in china uh but you can see it in harder ways that you imagine across asia or other markets where alibaba is strong and you're in today's sort of environment where there's scarce goods and maybe certain products well maybe they go chinese may probably go to alibaba first and you want to buy that product well amazon doesn't have it but alibaba has it you know those sort of scenarios if you get into a sharp trade war with china or even if the current tensions continue it's quite easy to see how that could uh play some havoc with amazon's supply chains in many ways the whole amazon retail model is based on a steady flow of goods manufactured in china and that clearly is not as stable as it was right got it the next one actually caught my attention and this is a big part of the reason why we want to survey the community to see how plausible folks think this is in its its technology related scenario so that would potentially disrupt aws and by fault by default hit amazon so that's major computing innovations such as quantum edge machine machine would obsolete today's cloud architectures okay so so here what you're thinking just as aws changed the game in i.t some future innovations or new business models that we haven't conceived yet could disrupt the prevailing cloud computing model right yeah absolutely i mean you know again we'll go back to where we started that new technologies have always been the main disruptors and here we're looking at some potentially very powerful uh new technologies you know your guess is good in mind about what's gonna happen with quantum is clearly a very different way of computing quite possibly led by other vendors possibly even led by china which would be a huge issue you look at the cloud well cloud's not very good at sort of edge stuff or machine to a machine stuff or sort of near field things out cars in the highway talking to each other uh you know again amazon's totally aware of these things and they are working on it but they have a huge investment in other ways of doing things and historically that inertia that need to protect existing bases of activity and practices has made it difficult for a lot of companies to adjust to new things and so that could happen again uh and there's certainly a puzzle but yeah in all these cases so far amazon has been aware of it is trying to do it but you can still see the scenario playing out and in a truly disruptive technology it's not always possible for the incumbent to effectively cope with it okay the next scenario speaks to i think some of the work that you've done in automation and related areas software replaces centralized warehouses as delivery services are directly connected to suppliers and factories so dave this is like cut out the middle man right software and automation changes the nature of the route absolutely i mean you know in a world of ubiquitous delivery services and product standardization metrics and products being built and shipped from all over the world the concept of running them all through a centralized warehouse is at least at a minimum uh seems like something that might be uh obsoleted and replaced and you know imagine if google built a significant taxonomy of of core products that could be traced directly to where they are either manufactured supplied or brought into the country from whatever company that tries to sell them and the delivery service connected directly to that uh and so that model has always been out there i think at various times people have looked at it it hasn't happened so far and i think amazon itself is is is looking at this particularly as it gets more into food that the idea of shipping all fresh food any sort of centralized warehouse is a pretty bad idea uh and so you know that model of software essentially replacing giant automated warehouses uh is out there and and seems to me uh likely and i just say that you know alibaba for the record doesn't really use that warehouse model it uses a network of suppliers and does it that way and and there do seem to be uh some efficiencies that would likely come with that the next one is was really interesting from a historian's perspective and it's the penultimate uh scenario and that's the proverbial self-inflicted wound and you and i certainly remember ibm's you know fateful decision to outsource the microprocessor and operating system to intel and and and and and microsoft sorry ibm's decision to do that lotus you might recall it refused to allow 123 to run on windows back in the day novell buying word perfect jim barksdale a lot of young people the audience won't of course remember this but jim barksdale poo-pooing microsoft's decision to bundle internet explorer into the operating system all those were kind of self-inflicted or blind spots so this one is complacency arrogance blindness abuse of power loss of trust so much more than the examples i gave consumer and or employee backlash you're seeing some of that at facebook now and i guess this is taking their eye off the customer ball losing the day zero in amazon's case forgetting that customer obsession formula they're working backwards culture and i think this is a big reason why andy jassy was put in charge so this wouldn't happen but we've seen time and time again as the examples i just gave blind spots have absolutely killed companies haven't they dave absolutely he listed many of the most famous but perhaps my favorite of all was kennels and the founder of digital equipment corporation one of the great tech visionaries of his time who stated over and over again why would anybody want a home computer or eunuch's snake oil was his other beautiful all of those things and and so there's the blindness uh there's the area ibm who just came to the view that they and att both came to the view that they were invincible and nothing could ever crack their control of their customer base so we've seen all that i think uh more recently i think some of these things can actually go from the bottom up and you know what's happening to facebook today well they're being hurt by former employees speaking out uh you know this never really happened too much to in the ibm and t days but people calling into question amazon's work labor practices and such things is certainly a possible scenario and the whole sort of you know in the end you know people talk about a cultural backlash against technology i'm not sure i believe it'll happen but it certainly is possible that people will start to rebel against these firms you see it more likely with facebook is fairly well along there uh amazon's still popular but you know in the end and as you i think you said the the core thing that companies routinely fail on is they lose their customer focus and they get caught up in other things their financial numbers their their power inside their position of their company but they they lose track of staying close to the customer has need and terrific job of staying close to the customers over the years uh so if anyone you know was maybe less vulnerable that they they would be well along that that line but it can happen to anyone and new management is often you know one of the real tests and there's many examples of that through history when a new executive comes in will they have that same focus that same thing particularly you know as the first generation's employees get wealthy and retired in a new set of people come in you know you look at microsoft the new people who came in well they're not going to be multi-millionaires they may have missed the great runs they're there to work and and the culture of companies changes when you get to that state the m is not that there yet but you can envision that comings soon enough so you know cultural issues have always been a factor and it's hard to imagine there won't be some sort of factor going forward well and you know you talk about that the the succession of founders and ceos i mean that's what to me makes microsoft so astounding because during the bomber years it was unclear that they were ever going to become relevant again and so nadella has done a masterful job but of course they had the margins from the pc software business that allowed them to buy that time but look at intel and the troubles it's going through uh and so many other examples of companies that just sort of said all right well we're going to pack it in and either sell the company or which is again what i think makes think companies like oracle and dell which you know founder-led ceos not ceo in the case of oracle but still running the business uh so quite uh significant yeah yeah and you know we've talked a lot about things that might hurt answers but you gotta recognize how in many ways how amazing they are and most tech companies a lot of them anyways have essentially been one trick ponies i mean google still makes overwhelming amount of its money selling ads and the things it's tried to do in cars and healthcare and various things you know they've often struggled you know apple still makes the core of its money around it's it's cell phone platform amazon's one of the few that continually generates entirely new huge businesses and and you have to give them an enormous amount of credit for that you know microsoft uh was a they failed repeatedly over and over again with internet stuff and phone stuff and all these things and it really wasn't until you know satya came in and really focused on their customers and their need for enterprise services that he that he really got the company on the right track so you know amazon has always been good listeners customers and if they continue to do so it bodes well but history says other stuff comes along okay and the last scenario is open-ended dave included uh you know what did we miss is there another scenario that we haven't put forth that you could feel it could be disruptive to amazon right i mean you've got to have the at least what'd we miss yeah i mean you know these are things that me and you and i just sort of made up the top of our head these are things we see that that might happen but you know in your huge audience of people in this community every day i'm sure there are other people out there who have thoughts of what might shake things up or even doing things that might shake things up already uh and you know one of the things you do for you guys is get this sort of material out there and and see what ideas surface so hopefully people will uh participate in this and we'll see what comes out of it all right so what happens from here is we're going to publish the the link to the survey in this video description and in our posts we ask you to take the survey please tell your friends we're going to publish the results as always we do in an open and free david michelle thanks so much for putting your brain power on this and collaborating with us i'm really excited to see the results and and and run through the other giants with you as well once we see what this survey says yeah thanks david great and yeah if we can make this one work be fun to do it for for google and microsoft and facebook and apple and see where it all goes thanks a lot all right okay that's it for today remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast i publish each week on wikibon.com and siliconangle.com etr.plus is where all the cool survey data lives they just dropped their october survey with some great findings so do check that out you can reach me on twitter at d velante he's at d michelle or comment on my linkedin post or email me at david.vellante at siliconangle.com this is dave vellante for dave michelle thanks for watching thecube insights powered by etr be well and we'll see you next time