>> 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--

>>Welcome back to super cloud 22, our inaugural event. It's a pilot event here in the cube studios we're live and streaming virtually until we do it in person. Maybe next year. I'm John fury, host of the cube with Dave Lon two great guests, distinguished engineers managers, CTOs investors. Mariana Tessel is a CTO of Intuit ins Ray founder of vertex ventures. Both have a lot of DNA. Founder allow cloud here with mark Andre and Ben Horowitz, a variety of other great ventures you've done. And now you're an investor. Yep. Maria, you've been a seasoned CTO, VP of engineering, VMware Docker Intuit. Now thanks for joining us. >>Absolutely. >>So super cloud is a, is a thing. And apparently it's got a lot of momentum and you guys got stats over there at, at Intuit in, so you're investing and we were challenged on super cloud. Our initial thesis was you build on the clouds, get all that leverage like snowflake, you get a good differentiation and then you compete and then move to other clouds. Now it's becoming a thing where I can do this. Every enterprise could possibly do it. So I want to get your guys thoughts on what you think of super cloud concept and where are the holes in it, what needs to be defined. And so we'll start with you. You've done a lot of cloud things in your day. What >>Do you think? Yeah, it's the whole cloud journey started with a desire to consolidate and desire to actually provide uniformity and, and standards driven ways of doing things. And I think Amazon was a leader there. They helped kind of teach everybody else. You know, when I was in loud cloud, we were trying to do it with proprietary stacks just wouldn't work. But once everyone standardized upon Unix and you know, the chip sets no longer became as relevant. They did a lot of good things there, but what's happened since then is now you've got competing standards at the API layer at the interface layer no longer at the chip set layer, no longer at the operating system layer. Right? So the evolution of the, the, the battles are still there. When you talk about multicloud and super cloud, though, like one of the big things you have to keep in mind is latency is not free. Latency is very expensive and it's getting even more expensive now with, with multi-cloud. So you have to really understand where the separations of boundaries are between your data, your compute, and, and the network is just there as a facilitator to help binding compute and data. Right? And I think there's a lot of bets being made across different vendors like CloudFlare Akamai, as well as Amazon Google Microsoft in terms of how they think we should take computing either to the edge, from the core or back and forth. >>These, this is structural change. I mean, this is structural, >>It's desired by incumbents, but it's not something that I'm seeing from the consumption. I'd love to hear, hear from our end's per perspective, from a consumption point of view, like how much edge computing really matters. Right. >>Mario. >>So I think there's like, there's kind of a, a story of like two, like it's kind of, you can cut it for both edges. No, no pun intended on one end. It is really simplifying to actually go into like a single cloud and standardize on it and just have everything there. But I think what over time companies find is that they end up in multiple clouds, whether like, you know, through acquisitions or through like needing to use a service in another cloud. So you do find yourself in a situation where you have multi multi-cloud and you have to kind of work through it and understand how to make it all like work and latency is an issue, but also for many, many workloads, you can work around it and you can make it work where you have workloads that actually span multiple vendors and clouds. You know, again, having said that, I would say the world is such, that is still a simplifying assumption. When if you go to a single cloud, it's much easier to just go and, and bet on that >>Easier in terms of everything's integrated, IAS works with SAS, they solve a lot of problems. >>Correct. And you can do like for your developers, you can actually provide an environment that's super homogenous, simple. You can use services easily up and down the stack. And, you know, we, we actually made that deliberate decision. When we started migrating to the cloud at the beginning, it was like, oh, let's do like hybrid we'll, you know, make it, so it work anywhere. It was so complicated. It was not worth it. >>When was the, when did you give up, what was the moment? Was there a flash point where you said, oh, this is terrible. This is >>Dead. Yeah. When, when we started to try to make it interoperable and you just see what it requires to do that and the complexity of the architecture that it just became not worth it for the gains you have. >>So speaking obviously as a SAS provider, right. So it just doesn't, it didn't make business case sense for you guys to do that. So it was super cloud. Then an infrastructure thing we just heard from Ben wa deja VI that they're not, they're going beyond instantiating their, their data cloud. They're actually running, you know, their own little snow grid. They called it. And, and then when I asked him, well, what about latency? He said, well, we copied data over, you know, so, okay. That's you have to do, but that's a singular experience with the same governance or the same security. Just wasn't worth it for you guys is what I'm hearing. >>Correct. But again, like for some workload or for some services that we want to use, we are gonna go there and we are gonna then figure out what is the work around the latency issue, whether it's like copy or, you know, redundancy. >>Well, the question I have Dave on snowflake is maybe the question for you and in the panel is snowflake a tan expansion opportunity, or is there a technical reason to go to other clouds? >>I think they wanted to leverage the hyperscale infrastructure globally. And they said that they're out there, it's a free gift. We're gonna go take it. I, I think it started with we're on AWS. Do you think? And then we're on Azure and then we're on Google. And then they said, why don't we just connect all these and make it a singular experience? And yeah, I guess it's a TA expansion as a differentiator and it's, it adds value. Right. If I can share data across that global network, >>We have customers on Azure now, >>Right? Yeah. Yeah. Of course. >>You guys don't need to go CP. What do you think about that? >>Well, I think Snowflake's in a good position cuz they work mostly with analytical workloads and you have capacity. That's always gonna increase like no one subtracts, their analytical workload like ever, right. So there was just compounded growth is like 50% or 80% for, you know, many enterprises despite their best intentions, not to collect more data, they just can't stop doing it. So it's different than if you're like an Oracle or a transactional database where you don't have those, you know, like kind of infinite growth paths. So Snowflake's gonna continue to expand footprint their customers. They don't mind as long as you, they can figure out the, the lowest cost on denominator for, for that. >>Yeah. So it makes sense to be in all the clouds >>For them, for, for them, for sure. Yeah. >>But, but, but Oracle just announced with Microsoft what I would call super cloud, a, a cross cloud database service running on OCI and Azure with very low latency and a database that looks like a, the singular experience. Yeah. With, with a PAs layers >>That lost me after OCI that's >>Okay. You know, but that's the, that's the, the BS answer for all U VCs. The do nobody develops on Oracle? Well, it's a 240 billion market cap company. Show me who you all want be. >>We're gonna talk about SRDF and em C next, you >>All want Oracle. So there we go. You throw that into, you all want Oracle to buy your companies, your funding, you know, cause, cause we all wanna be like Oracle with that kinda cash flow. But, but anyway, >>Here's, here's one thing that I'm noticing that is gonna be really practical. I think for companies that do run SA is because like, you know, you have all these solutions, whether it's like analytics or like monitoring or logging or whatever. And each one of them is very data hungry and all of them have like SAS solutions that end up copy the data, moving data to their cloud, and then they might charge you by the size of your data. It does become kind of overwhelming for companies to use that many tools and basically maybe have that data kind of charge for it, multiple places because you use it for different purposes or just in general, if you have a lot of data, you know, that that is becoming an issue. So that's something that I've noticed in our, in our own kind of, you know, a world, but it's just something that I think companies need to think about how they solve because eventually a lot of companies will say, I cannot have all these solutions, so there's no way I'm gonna be willing to have so many copies of the data and actually pay for that. >>So many times, just something to think about. >>But one of the criticisms of the super cloud concept is that it's just SAS. If I'm running workload on prem and I, and I've got, you know, a connection to the cloud, which you probably do, that's, that's SAS, what's, what's the big deal and that's not anything new or different. So I'd love to get your thoughts on that. But Goldman Sachs, for instance, just announced the service last reinvent with AWS, connecting their tools, their data, and their software from on-prem to AWS, they're offering it as a service. I'm like, Hmm. Kind of looking like Supercloud, but maybe it's just SAS. >>It could be. And like, what I'm talking about is not so much like, you know, like what you wanna connect your data. But the idea is like a lot of the providers of different services, like in the past and, and like higher layer, they're actually COPI the data. They need the data in their cloud or their solution. And it just becomes complicated and expensive is, is kind of like my point. So yes, connecting it like for you to have the data in one place and then be able to connect to it. I think that is a valid, if, if that's kinda what you think about as a super cloud, that is a valid need, I think that companies will >>Have where developers actually want access to tools that might exist. >>Also the key is developers, right? Yeah. Developers decide all decisions, not database on administrators, not, you know, a hundred percent security engineers, not admins. So what's really interesting is where are the developers going next? If you look at the current winners in the current ecosystem, companies like MongoDB, I mean, they capture the minds of yeah. The JavaScript, you know, no JS developers absolutely very early on. And I started catch base and I could tell you like the difference was that capture motion was so important. So developers are basically used to this game-like experience now where they want to see tools that are free, whether it's open source or not, they actually don't care. They just want, and they want it SAS. They want it SAS delivered on demand. Right. And pay as you go. And so there's a lot of these different frameworks coming out next generation, no code, low code, whether it's Java, JavaScript, rust, you know, whatever, you know, go Lang. And there's a lot of people fighting religious wars about how to develop the next kind of modern pattern design pattern. Okay. And that's where a lot of excitement is how we look at like investment opportunities. Like where are those big bets who are, you know, frustrated developers, who are they frustrated, what's wrong with their current environment? You know, do they really enjoy using Kubernetes or trying to use Kubernetes? Yeah. Right. Like developers have a very different view than operator, >>But you mentioned couch base. I mean, I look at couch base what they're doing with Capellas as a form of Supercloud. I mean, I think that's an excellent, they're bringing that out to the edge. We're gonna hear later on from someone from couch base. That's gonna talk about that now. It's kind of a lightweight, you know, sort of, it's gonna be a, a synchronization, but it's the beginning >>A cool new venture deal that I'm not in, but was like duck DB. I'm like, what's duck DB like, well, it's an Emory database that has like this like remote store thing. I'm like, okay, that sounds interesting. Like let's call Mike Olson cuz that sounds like sleepy cat redone red distributed world. But like it's, it's like there's a lot of people refactoring design patterns that we're all grew up with since the popup days of, you know, typical round. Right? >>Yeah. That's the refactory I think that's the big pattern. So I have to ask you guys, what are you guys investing in? We've got a couple minutes left to chat about that. What are you investing at into it from a, from a, a CTO engineering perspective and what are you investing in that feels super cloud like to you? >>Well, the, the thing that like I'm focused on is to make sure that we have absolutely best in the world development environment for our engineers, where it's modern, it's easy to use and it incorporates as many things as we can into that environment. So the engineers don't have to think about it. Like one big example would be security and how we incorporated that into development environment. So again, the engineers don't have to bother with trying to think through how they secure their workloads and every step of the way their other things that we incorporated, whether it's like rollbacks or monitoring or, you know, like baly enough other things. But I think that's really an investment that has panned off for us. We actually started investing in development environment several years ago. We started measure our development velocity and we, it actually went up by six X justly investing. So >>User experience, developer experience and productivity pretty much right. >>Yeah. AB absolutely. Yeah. That's like a big investment area for us that, you know, cloud cloud >>Sounds like super cloudlike factor and I'm assuming it's you're on AWS. >>We are mostly on AWS. Yes. >>And so what are you investing in that from a VC money doling out standpoint? That feels super cloudlike >>So very similar to what we just touched on a lot of developer tool experiences. We have a company that we've invested in called ops level that the service catalogs it's, it's helping, you know, understand your, where your services live and how they could be accessed and, and you know, enterprise kind of that come with that. And then we have a company called Lugo that helps you do serverless debugging container debugging, cuz it turns out debugging distributed, you know, applications is a real problem right now just you can only do so much by log tracing, right? We have a company haven't announced yet that's in the web assembly space. So we're looking at modernizing the next generation past stack and throwing everything out the window, including Java and all of the, you know, current prebuilt components because turns out 90% of enterprise workloads are actually not used. They're they're just policy code. You compiled with they're sitting there as vulnerabilities that no one's actually accessing, but you still have to compile with all of it. So we have a lot of bloatware happening in the enterprise. So we're thinking about how do you skinny that up with the next generation paths that's enterprise capable with security context and frameworks >>Super pass. >>Well, yeah, super pass. That's a kind of good way to, well, is >>It, is it a consistent developer experience across clouds? >>It is. And, and, and, and web assembly is a very raw standard if you can call it that. I mean it's, but it's supported by every modern browser, every major platform, vendor cloud, and Adobe and others, and are using it for their uses. And it's not just about your edge browser compute. It's really, you can take the same framework and compile it down to server side as well as client site, just like JavaScript was a client side tool before it became node. Right. Right. So we're looking at that as a very interesting opportunity. It's very nascent. Yeah. >>Great patterns. Yeah. Well, thanks so much for spending the time outta your busy day. Ariana. Thanks for your commentary. Appreciate your coming on the cubes first in IGUR super cloud event, pilot. Thanks for, for sharing. Thanks for having, thanks for having us. Okay. More coverage here. Super cloud 2022. I'm Jeff David Alane stay with us. We got our cloud ARA panel coming up next.

>>We're back in Boston, the Cube's coverage of AWS reinforced 2022. My name is Dave ante. Steve Malanney is here as the CEO of Aviatrix longtime cube alum sort of collaborator on super cloud. Yeah. Uh, which we have an event, uh, August 9th, which you guys are participating in. So, um, thank you for that. And, yep. Welcome to the cube. >>Yeah. Thank you so great to be here as >>Always back in Boston. Yeah. I'd say good show. Not, not like blow me away. We were AWS, um, summit in New York city three weeks ago. I >>Took, heard it took three hours to get in >>Out control. I heard, well, there were some people two I, maybe three <laugh>, but there was, they expected like maybe nine, 10,000, 19,000 showed up. Now it's a free event. Yeah. 19,000 people. >>Oh, I didn't know it >>Was that many. It was unbelievable. I mean, it was packed. Yeah. You know, so it's a little light here and I think it's cuz you know, everybody's down the Cape, >>There are down the Cape, Rhode Island that's after the fourth. The thing is that we were talking about this. The quality of people are pretty good though. Yeah. Right. This is there's no looky lose it's everybody. That's doing stuff in cloud. They're moving in. This is no longer, Hey, what's this thing called cloud. Right. I remember three, four years ago at AWS. You'd get a lot of that, that kind of stuff. Some the summit meetings and things like that. Now it's, we're a full on deployment mode even >>Here in 2019, the conversation was like, so there's this shared responsibility model and we may have to make sure you understand. I mean, nobody's questioning that today. Yeah. It's more really hardcore best practices and you know how to apply tools. Yeah. You know, dos and don't and so it's a much more sophisticated narrative, I think. Yeah. >>Well, I mean, that's one of the things that Aviatrix does is our whole thing is architecturally. I would say, where does network security belong in the network? It shouldn't be a bolt on it. Shouldn't be something that you add on. It should be something that actually gets integrated into the fabric of the network. So you shouldn't be able to point to network security. It's like, can you point to the network? It's everywhere. Point to air it's everywhere. Network security should be integrated in the fabric and that wasn't done. On-prem that way you steered traffic to this thing called a firewall. But in the cloud, that's not the right architectural way. It it's a choke point. Uh, operationally adds tremendous amount of complexity, which is the whole reason we're going to cloud in the first place is for that agility and the ability to operationally swipe the card and get our developers running to put in these choke points is completely the wrong architecture. So conversations we're having with customers is integrate that security into the fabric of the network. And you get rid of all those, all those operational >>Issues. So explain that how you're not a, a checkpoint, but if you funnel everything into one sort of place >>In the, so we are a networking company, uh, it is uh, cloud networking company. So we, we were born in the cloud cloud native. We, we are not some on-prem networking solution that was jammed in the cloud, uh, wrapped >>In stack wrapped >>In, you know, or like that. No, no, no. And looking for wires, right? That's VM series from Palo. It doesn't even know it's in the cloud. Right. It's looking for wires. Um, and of course multicloud, cuz you know, Larry E said now, could you believe that on stage with sat, Nadela talking about multi-cloud now you really know we've crossed over to this is a, this is a thing, whoever would've thought you'd see that. But anyway, so we're networking. We're cloud networking, of course it's multi-cloud networking and we're gonna integrate these intelligent services into the fabric. And one of those is, is networking. So what happens is you should do security everywhere. So the place to do it is at every single point in the network that you can make a decision and you embed it and actually embed it into the network. So it's that when you're making a decision of does that traffic need to go somewhere or not, you're doing a little bit of security everywhere. And so what, it looks like a giant firewall effectively, but it's actually distributed in software through every single point in a network. >>Can I call it a mesh? >>It's kind of a mesh you can think of. Yeah, it's a fabric. >>Okay. It's >>A, it's a fabric that these advanced services, including security are integrated into that fabric. >>So you've been in networking much of >>Your career career, >>37 years. All your career. Right? So yay. Cisco Palo Alto. Nicera probably missing one or two, but so what do you do with all blue coat? Blue coat? What do you do with all that stuff? That's out there that >>Symantics. >>Yes. <laugh> keep going. >>Yeah, I think that's it. That's >>All I got. Okay. So what do you do with all that stuff? That's that's out there, you rip and replace it. You, >>So in the cloud you mean yeah. >>All this infrastructure that's out there. What is that? Well, you >>Don't have it in the right. And so right now what's happening is people, look, you can't change too many things. If you're a human, you know, they always tell you don't change a job, get married and have a kid or something all in the same year. Like they just, just do one of 'em cuz you it's too much. When people move to the cloud, what they do is they tend to take what they do on Preem and they say, look, I'm gonna change one thing. We're gonna go to the cloud, everything else. I'm gonna keep the same. Cuz I don't wanna change three things. So they kind of lift and shift their same mentality. They take their firewalls, their next gen fire. I want them, they take all the things that they currently do. And they say, I'm gonna try to do that in the cloud. >>It's not really the right way to do it. But sometimes for people that are on-prem people, that's the way to get started and I'll screw it up and not screw it up and, and not change too many things. And look, I'm just used to that. And, and then I'll, then I'll go to change things, to be more cloud native, then I'll realize I can get rid of this and get rid of that and do that. But, but that's where people are. The first thing is bring these things over. We help them do that, right? From a networking perspective, I'll make it easier to bring your old security stuff in. But in parallel to that, we start adding things into the fabric and what's gonna happen is eventually we start adding all these things and things that you can't do separately. We start doing anomaly detection. We start doing behavioral analysis. Why? Because the entire network, we are the data plan. We see everything. And so we can start doing things that a standalone device can't do because not all the traffic steered to them. It can only control what's steered to you. And then eventually what's happening is people look at that device. And then they look at us and then they look at the device and they look at us and they go, why do I have both of this? And we go, I don't know. >>You don't need it. >>Well, can I get rid of that other thing? That's a tool. >>Sure. And there's not a trade off. There's not a trade off. You >>Don't have to. No. Now people rid belts and suspenders. Yeah. Cause it's just, who has, who has enough? Who has too much security buddy? They're gonna, they're gonna do belt suspenders. You know anything they can do. But eventually what will happened is they'll look at what we do and they'll go, that's good enough. That happened to me. When I was at Palo Alto networks, we inserted as a firewall. They kept their existing firewall. They had all these other devices and eventually all those went away and you just had a NextGen >>Firewall just through attrition, >>Through Atian. You're like, you're looking, you go, well, that platform is doing all these functions. Same. Thing's gonna happen to us. The platform of networking's gonna do all your network security devices. So any tool or agent or external, you know, device that you have to steer traffic to ISS gonna go away. You're not gonna need it. >>And, and you talking multi-cloud obviously, >>And then don't wanna do the same thing. Whether man Azure, you know the same. >>Yeah. >>Same, same experie architecture, same experience, same set of services. True. Multi-cloud native. Like you, that's what you want. And oh, by the way, skill, gap, skill shortage is a real thing. And it's getting worse. Cause now with the recession, you think you're gonna be able to add more people. Nope. You're gonna have less people. How do I do this? Any multicloud world with security and all this kind of stuff. You have to put the intelligence in the software, not on your people. Right? >>So speaking of recession. Yep. As a CEO of a well funded company, that's got some momentum. How are you approaching it? Do you have like, did you bring in the war time? Conig I mean, you've been through, you know, downturns before. This is you are you >>I'm on war time already. >>Okay. So yeah. Tell me more about how you you're kind of approaching this >>So recession down. So didn't change what we were doing one bit, because I run it that way from the very beginning. So I've been around 30 years, that's >>Told me he he's like me. You know what he said? >>Yeah. Or maybe >>I'm like, I want be D cuz he said, you know, people talk about, you know, only do things that are absolutely necessary during times like this. I always do things that are only, >>That's all I >>Do necessary. Why would you ever do things that aren't necessary? >><laugh> you'd be surprised. Most companies don't. Yeah. Uh, recession's very good for people like snowflake and for us because we run that way anyway. Mm-hmm <affirmative> um, I, I constantly make decisions that we have to go and dip there's people that aren't right for the business. I move 'em out. Like I don't wait for some like Sequoia stupid rest in peace. The world's ending fire all your people that has no impact on me because I already operated that way. So we, we kind of operate that way and we are, we are like sat Nadel even came out and kind of said, I don't wanna say cloud is recession proof, but it kind of is, is we are so look, our top customer spends 5 million a year. Nothing. We haven't even started yet. David that's minuscule. We're not macro. We're micro 5 million a year for these big enterprises is nothing right. SA Nadel is now starting to count people who do billion dollar agreements with him billion over a period of number of years. Like that's the, the scale we have not even >>Gun billion dollar >>Agreements. We haven't even under begun to understand the scope of what's happening in the cloud. Right. And so yeah, the recession's happening. I don't know. I guess it's impacting somebody. It's not impacting me. It's actually accelerating things because it's a flight to quality and customers go and say, I can't get gear on on-prem anyway, cuz of the, uh, shortage, you know, the, uh, uh, get chips. Um, and that's not the right thing. So guess what the recession says, I'm gonna stop spending more money there and I'm gonna put it into the cloud. >>All right. So you opened up Pandora's box, man. I wanna ask you about your sort of management philosophy. When you come into a company to take, to go lead a company like that. Yeah. How, what, what's your approach to assess the team? Who do you, who do you decide? How do you decide who to keep on the bus? Who to throw off the bus put in the right seats. So how long does that take you? >>Doesn't take long. When I join, we were 30, 30, 8 people. We're now 525. Um, and my view on everything and I I've never met Frank Lubin, but I guarantee you, he has the same philosophy. You have a one year contract me included next year, the board might come to me and say, you were the right CEO for this year. You're not next year. Ben Horowitz taught me that it's a one year contract. There's no multi-year contract. So everybody in the company, including the CEO has a one year >>Contract. So you would say that to the board. Hey, if you can find somebody better, >>If, and, and you know what, I'll be the first one to pull myself, fire myself and say, we're, we're replacing me with somebody better right now. There isn't anybody better. So it's me. So, okay, next year maybe there's somebody better. Or we hit a certain point where I'm not the right guy. I'll I'll, I'll pull myself out as the CEO, but also internally the same thing just because you're the right guy this year. And we hire people for the, what you need to do this year. We're not gonna, we don't hire, oh, like this is the mistake. A lot of companies make, well, we wanna be a billion dollars in sales. So we're gonna go hire some loser from HPE. Who's worked at a company for a billion dollars. And by the way has no idea how they became a billion dollars, right. In revenue or billions of dollars. >>But we're gonna go hire 'em because they must know more than we do. And what every single time you bring them in what you realize, they're idiots. They have no idea how we got to that. And so you, you don't pre-hire for where you want to be. You hire for where you are that year. And then if it's not right, and then if it's not right, you'd be really nice to them. Have great severance packages, be, be respectful for people and be honest with them. I guarantee you Frank, Salman's not, if you're not just have this conversation with a sales guy before I came into here, very straight conversation, Northeast hockey player mentality. We're straight. If you're not working out or I don't think you're doing things right. You're gonna know. And so it's a one year, it's a one year contract. That's what you do. So you don't have time. You don't the luxury of >>Time. So, so that's probably the hardest part of, of any leadership job is, and people don't like confrontation. They like to put it off, but you don't run away from it. It's >>All in a confrontation, right? That's what relationships have built. Why do war buddies hang out with each other? Cuz they've gone through hell, right? It's in the confrontation. And it's, it's actually with customers too, right? If there's an issue, you don't run from it. You actually bring it up in a very straightforward manner and say, Hey, we got a problem, right? They respect you. You respect them, blah, blah, blah. And then you come out of it and go, you know, you have to fight like, look with your wife. You have to fight. If you don't fight, it's not a relationship you've gotta see in that, in that tension is where the relationship's >>Built. See, I should go home and have a fight tonight. You gotta have a fight with your wife. <laugh> you know, you mentioned Satia and Nadella and Larry Ellison. Interesting point. I wanna come back to that. What Oracle did is actually pretty interesting, do we? For their use case? Yeah. You know, it's not your thing. It's like low latency database across clouds. Yeah. Who would ever thought that? But >>We love it. We love it because it drives multi-cloud it drives. Um, and, and, and I actually think we're gonna have multi-cloud applications that are gonna start happening. Um, right now you don't, you have developers that, that, that kind of will use one cloud. But as we start developing and you call it the super cloud, right. When that starts really happening, the infrastructure's gonna allow that networking and network security is that bottom layer that Aviatrix helps once that gets all handled. The app, people are gonna say, so there's no friction. So maybe I can use autonomous database here. I can use this service from GCP. I can use that service and, and put it all into one app. So where's the app run. It's a multicloud app. Doesn't exist today. >>No, that doesn't happen today. >>It's it's happen. It's gonna happen. >>But that's kind of what the vision was. No, seven, eight years ago of what >>It's >>Gonna, that would be, you know, the original premise of hybrid. Right? Right. Um, I think Chuck Hollis, the guy was at EMC at the time he wrote this piece on, he called it private cloud, but he was really describing hybrid cloud application and running in both places that never happened. But it's starting to, I mean, the infrastructure is getting put in place to enable that, I guess is what you're saying. >>Yep. >>Yeah. >>Cool. And multicloud is, is becoming not just four plus one is a lot of enterprises it's becoming plus one, meaning you're gonna have more and more. And then there won't be infrastructure clouds like AWS and so forth, but it's gonna be industry clouds. Right? You've you've talked about that again, back to super clouds. You're gonna have Goldman Sachs creating clouds and you're gonna have AI companies creating clouds. You're gonna have clouds at the edge, you know, for edge computing and all these things all need to be networked with network security integrated. And you mentioned fact >>Aviatrix you mentioned Ben Horowitz, that's mark Andreesen. All, all companies are software companies. All companies are becoming cloud companies. Yeah. Or, or they're missing missing opportunities or they might get disrupted. >>Yeah. Every single company I talk to now, you know, whether you're Heineken, they don't think of themselves as a beer company anymore. We are the most technologically, you know, advanced brewer in the world. Like they all think they're a technology company. Now, whether you're making trucks, whether you're making sneakers, whether you're making beer, you're now a technology company, every single company in >>The world, we are too, we're we're building a media cloud. You're you know, John's, it's a technology company laying that out and yeah. That's we got developers doing that. That's our, that's our future. Yep. You know? Cool. Hey, thanks for coming on, man. Thank you. Great to see you. Thank you for watching. Keep it right there. We'll be back right after this short break. It keeps coverage. AWS reinforced 20, 22 from Boston. Keep it right there. >>You tired? How many interviewed.

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

(upbeat music) >> Welcome back to theCUBE's continuing coverage of AWS re:Invent 2021 live from Las Vegas. I'm Lisa Martin. We are doing one of the most important industry events, hybrid events this year with Amazon and its massive ecosystem of partners, some of which are joining me next. We've got two live sets, two remote sets, over 100 guests on the program, I'm going to be talking about the next decade in Cloud innovation. I'm pleased to welcome back Anthony Lye to the program, the Executive Vice President and General Manager of Public Cloud at NetApp. Anthony good to see you. >> Nice to see you again thanks for... >> Nice to see you in person. >> I know... >> It's been a couple of years. And Amiram Shachar is here, the VP and GM of Spot by NetApp, Amiram it's great to have you on the program, welcome. >> Likewise, thank you. >> So the acquisition, the Spot acquisition was during the pandemic mid 2020, Amiram talk to me about that why NetApp, how's it going? Give us the lay of the land. >> I think that's the, it's one of the greatest things that NetApp has done, and I think it's one of the most amazing outcomes we could have as a company. And if you think about it in a first sight, when you look at storage company and compute company, what's the connection? But the thing is that NetApp is a company that is going through a huge transformation into Cloud. And by doing this acquisition, it's really like signaling where it's going. It's going way beyond, and honestly I just wanted to be part of it. >> And what's the customer sentiment been the 18 months or so, post acquisition? >> I think NetApp has done specifically with Anthony leading that acquisition, NetApp has done a phenomenal job of keeping Spot as a business unit, independent business unit. So our customers didn't really feel that something had happened, like the only thing we told them is we're going to have more funding, so. >> I'm sure they like that. Anthony talk to us about NetApp's transformation, transition, Spot as part of that. And then of course, CloudCheckr which acquisition was just announced I believe yesterday? >> We closed on actually November 7th. >> Lisa: Okay. >> So it's almost been a month now since we closed, but I've been at NetApp my gosh, it'll be five years in February. And you know, I think that the company had a real desire to sort of, to re-imagine itself and to sort of to embrace the public Clouds and to give its customers you know, what I think it's done incredibly well is this idea of symmetry. That we wanted to build something on Amazon that was as good or maybe a little bit better than on-premise. And customers really I think appreciated, they appreciate that sort of, that desire for us to do those kinds of things. Now of course, CloudCheckr was my ninth acquisition in four years. Just to sort of, to build on what Amiram said I mean, CloudCheckr we acquired four Spot and we acquired what? Four companies in the last 12 months for Spot. So we really believe that as a company now we can address all of their potential opportunities, whether it's in a legacy application, whether it's a virtual desktop, whether it's a Cloud native application, or we just went and announced Ocean for Apache Spark. So Spot now has an optimization and automation solution for Spark on AWS which we announced, I think just yesterday. >> Correct. >> But I'd like to get both of your perspectives on keeping Spot as a brand, Anthony we'll start with you and then Amiram we'll go to you. >> Amiram is the founder, and he was the CEO of the company and built a fantastic company. And we, NetApp I think has a phenomenal brand, but a brand that's that's associated with the sort of the traditional IT organization. And as you note in the Cloud the buyers are slightly different. They're sort of the application owners, or they operate in a sort of a construct that most people call CloudOps or DevOps. And we felt that Spot represented that new buyer in ways that NetApp didn't and probably couldn't. And so we really liked the idea of having the structure of the big N supported by a little pink and a little blue and a more sort of Cloud native brand. >> And that's key, especially the dynamics in the market that we've seen the last 22 months with the rapid changes, the pivot to Cloud customers that weren't that digital needing to go in that direction to survive in the very beginning, I imagine this was really kind of core to NetApp's strategy, but also helping both of your customers to survive initially and then to be able to thrive and identify some of those key areas where they can cut costs would be a far more efficient. >> Okay I think you are in here, if you were born physical you're now digital, and if you weren't born physical you were born digital. And you know, digital is a very effective medium accelerated by the pandemic because as you said, we couldn't really get close to each other and you just look at the innovation around us here at Amazon, it's just amazing to watch. And we've just been really, really good partners with Amazon now for many, many years. And we continue to see just huge, huge opportunities. >> Well Adam Selipsky this morning in his keynote, one of the partners he called out was NetApp. >> Yeah I know I mean, I'll talk a little bit later on maybe with Yancey and I but you know, Amazon now sells our product. They haven't done that with anybody. So ONTAP is now a product that Amazon sells. >> Lisa: Okay. >> Amazon supports, Amazon bills, Amazon runs. So we've really, really demonstrated I think not just to our customers, that sort of a high rate of innovation and an opportunity to sort of accelerate their businesses, but we've demonstrated it to Amazon themselves, that we can operate like them. And we can develop with them at a speed that they are comfortable with. That maybe a few years ago many people would have doubted that a legacy company could operate this way. >> Right, one of the things we know about Amazon is the speed, but also their focus on the customer it's laser-focused, that whole flywheel of Amazon everything that was being announced this morning was exciting to your point Anthony, but it's also showing how involved the customers and the partners are in the ecosystem and that flywheel. Amiram talk to me from your perspective what are some of the, from a visionary standpoint what are some of the things that you're looking forward to going forward with CloudCheckr, but also knowing how deeply connected and integrated NetApp is with a big powerhouse like AWS? >> Yeah, so a few things about that. I think the first thing is also my take from today, like listening to the keynote and looking at all the new announcements. I think the trend is that deployment to the Cloud is becoming easier, but operations is becoming messier. And I think when we look at our category and where we aspire, where we want to be and where we're going. So I think with the CloudCheckr acquisition. So we're expanding into an area that we haven't been to because there are two categories in Cloud cost, there is optimization and there is cost management. What we've done, what we've built, what we've, the business we had is in the optimization space. It's actively reducing and optimizing resources for customers. And there are very few companies in that category as I can say. But right now we're expanding into that area of cost management, so we can meet our customers sooner and you can see us doing it in multiple areas, not only here, but also if we look at a customer journey in the Cloud, it starts with bring workloads in the Cloud, deploy them, and then secure them, and then automate them and then optimize them. Nobody moves to the Cloud and optimizes. So we're typically meeting customers at the end of their journey, we're meeting customers where they need an optimization and they have everything already set up. And right now with Ocean for Apache Spark, Ocean continuous delivery, Spot security, we're meeting customers sooner in their journey so we can provide a much more holistic solution and platform to customers wherever they are in their migration to the Cloud and scaling into Cloud. And with CloudCheckr also taking us to a whole new world of cost management. So, I think we're scaling and ramping and doing all these things, and it's so amazing to realize that we haven't unleashed even 1% of what we can do. >> Really, so there's much more under the covers that we're still waiting for? >> I think the good news is you know, to comment more on what you said, our roadmaps are now largely being driven by customers. And that's just so refreshing to know that you've not only solved a problem for a particular customer, but the customer wants you to solve more problems and that they trust us to be that sort of organization that can help them. So, we're full steam ahead. You know, we're going to continue to acquire in areas where we think we can get acceleration. But our acquisition of Spot was very much about as Amiram said, bringing not just a great company into the business, but to invest significantly in it. And that's really proven I think to me, as Amiram said, one of the most if not the most successful acquisition NetApp has ever done. >> Well congratulations, that's fantastic. But it also sounds like from that customer focus there's clear, strong alignment with how AWS operates, how it values its customers from NetApp's perspective and I imagine from Spots as well. >> You know, if there's one thing I was really proud of during the acquisition, is I got a phone call from a customer, it's the largest food delivery company in South America, and they were very worried about this acquisition and I asked them why? And they told me, "Because your customer service, Spot's customer service is the best customer service I've ever gotten, and if I'm not going to continue to get this customer service, I need to look how I'm finding another vendor." And they told me that, when they want to even tell AWS like which company they can learn from, they're always pointing at Spot. So, and that was a very refreshing moment for me to realize how much also at Spot we care about our customers, but not only as a gimmick, as something that customer obsession, as something that we really live. And that was interesting to see that, that was a concern by our customers when we got acquired. >> Well that's proof in the pudding, because you're right it's one thing to say, companies can always say, "We're customer obsessed, we're customer first, we're customer focused." It's one thing to say it as a marketing term it's a whole other thing to actually live it and demonstrate it, and actually have people coming to you saying that, "We want to model that." I'm curious Anthony, what did you pull over from that? What has NetApp learned from this? >> I always tell Amiram that the idea was that they would essentially take us over. That you know, we sort of loved their culture, we loved their people and their process. And we literally changed a lot of how NetApp operated to operate along the Spot model. So we really did, as Amiram said earlier on, we let them not just sort of exist, but we let them thrive. And we encourage them to point at other areas that NetApp, that they thought we should change to be more like them. And it's raised the bar across everything we do now. And so, we now have a lot of the Spot business processes, a lot of the Spot cultures sort of seeping into the whole of the company. >> That's a very empathetic approach, and that's one of the things that we've learned in the last year and a half that's been, it's key to leadership, it's key to anything is that empathy. But the ability to recognize where there are things within an organization that can be improved and looking at leaders like Spot to go, "Let's actually make this really symbiotic and bi-directional." And I imagine with CloudCheckr it's going to be the same type of influence? >> Well as I've always said, and I say this to the employees and to the acquisitions that we make, what we are acquiring is people. You know the logo, the software, even in many ways the customer base is really very much I think a function of the people. And we work incredibly hard to retain the people, but we do so by sort of empowering them and encouraging them to lead. We really don't want to have the historical perspective of acquisitions, where big company swamps the little company. And I think we've tried very hard to make that a part of our acquisition strategy. And so CloudCheckr is very early in the process but very much, we're following those things, even Amiram and his team are learning from them. If they're doing something a little better than Spot is, then that's something we'll pick up from them. >> And that's just from a very open cultural perspective, that's a big change for NetApp but it's also a smart way to go, 'cause you're right it's, you're acquiring people. And we often talk about people, process, technology. But it's, sometimes to be honest with you it's rare that we hear companies talking about the people focus as being that's critical. It's because of our people that we have successful support, happy successful customers. So that people focus is (inaudible). >> You know, it's the company and culture is not something you can manufacture. It's something that happens and it happens I think through people. And it's an important thing is, if you can establish an organization with the right kinds of people and again, all credit goes to Amiram as the founder and CEO of the company. I think you sort of demanded a kind of person and a kind of culture that set you apart from so many other companies. >> I think the focus on culture was, I was very obsessed with it from very early on in the process that even Spot investors were very, they were questioning like, how come that you are so much obsessed with culture so early on? And I think it paid off big time. There was a book I read while being a CEO that really helped me to scale from quarter to quarter, because I really believe that as a CEO of a startup, every quarter you're basically applying again to your job because you're getting a new company every quarter. And about people, processes, technology, so at Spot it was a little bit different through the book I read, which is "The Hard Thing About Hard Things" by Ben Horowitz, it's people, product, revenue, PPR. And you need to take care of the people, and if you don't take care of the people, so nothing else matter, like it's nothing else just... >> Right. >> And if the people and the product are not working well, so the revenue are not going to come. So revenue was always for us as something that is coming, it's trailing after a good product and good people. >> I love that, what a great, honest focus and vision you guys both have congratulations on the acquisition, CloudCheckr. But also just the cultural alignment that you've done that's really driven by your people and the customers, it's really refreshing to hear that and congrats on NetApp's continued partnership with AWS. We look forward to having you on again next time we can see you in person and talk more about customer successes. >> Thank you very much for hosting us. >> My pleasure guys. >> Thank you. >> For my guests, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (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 back to Los Angeles. The cube is live. It feels so good to say that. I'm going to say that again. The cube is alive in Los Angeles. We are a coop con cloud native con 21. Lisa Martin with Dave Nicholson. We're talking to storm forge next. Cool name, right? We're going to get to the bottom of that. Please welcome Matt Provo, the founder and CEO of storm forge and Tom Ellery, the SVP of revenue storm forge, guys, welcome to the program. Thanks for having us. So storm forge, you have to say it like that. Like I feel like do you guys wear Storm trooper outfits on Halloween. >> Sometimes Storm trooper? The colors are black. You know, we hit anvils from time to time. >> I thought I, I thought they, that I saw >> Or may not be a heavy metal band that might be infringing on our name. It's all good. That's where we come from. >> I see. So you, so you started the company in 2015. Talk to me about the Genesis of the company. What were some of the gaps in the market that you saw that said we got to come in here and solve this? >> Yeah, so I was fortunate to always know. I think when you start a company, sometimes you, you know exactly the set of problems that you want to go after and potentially why you might be uniquely set up to solve it. What we knew at the beginning was we had a number of really talented data scientists. I was frustrated by the buzzwords around AI and machine learning when under the hood, this really a lot of vaporware. And so at the outset, really the, the point was build something real at the core, connect that to a set of problems that could drive value. And when we looked at really the beginnings of Kubernetes and containerization five, six years ago at its Genesis, we saw just a bunch of opportunity for machine learning, to play the right kind of role if we could build it correctly. And so at the outset it was what's going on. Why are people are people moving content workloads over to containers in the first place? And, you know, because of the flexibility and the portability around Kubernetes, we then ran into quickly its complexity. And within that complexity was really the foundation to set up the company and the solution for prob a set of problems uniquely and most beneficially solved by using machine learning. And so when we sort of brought that together and designed out some ideas, we, we did what any, any founder with a product background would do. We went and talked to a bunch of potential users and kind of tried to validate the problems themselves and, and got a really positive response. So. >> So Tom, from a business perspective, what, what attracted you to this? >> Well, initially I wasn't attracted just, I'll say that just from a startup standpoint. So I've been in the industry for 30 years, I've done six or seven pre IPO companies. I was exiting a private company. I did not want to go do another startup company, but being in the largest enterprise companies for the last 20 years, you see Kubernetes like wildfire in these places. And you knew there was huge amount of complexity and sophistication when they deployed it. So I started talking to Matt early on. He explained what they were doing and how unique the offer was around machine learning. I already knew the problems that customers had at scale with Kubernetes. So it was for me, I said, all right, I'm going to take one more run at this with Matt. I think we're, we're in a great position to differentiate ourselves. So that was really the launch pad for me, was really the technology and the market space. Those, those two things in combination are very exciting for us as a business. >> And, you know, a couple of bottles of amazing wine and a number of dinners that. >> Helps as well. >> That definitely helped twist his arm? >> Now tell us, just really kind of get into the technology. What does it do? How does it help facilitate the Kubernetes environment? >> Yeah, absolutely. So when organizations start moving workloads over to Kubernetes and get their applications up and running, there's a number of amazing organizations, whether it's through cloud providers or otherwise that that sort of solved that day one problem, those challenges. And as I was mentioning, you know, they moved because of flexibility and so developers love it and it starts to create a great experience, but there's these set of expectations. >> Where, where typically are these moving from? What you, what, what are the, what are the top three environments these are, that these are moving out of? >> Yeah. I mean, of course, non containerized environments, more generally. They could be coming from, you know, bare metal environment and it could be coming from kind of a VM driven environment. >> Okay. >> So when you look back at kind of the, the growth and Genesis and of VMs, you see a lot of parallels to what we're seeing now with, with containerization. And so as you move, it's, it's exciting. And then you get smacked in the face with the complexity, for all of the knobs that are able to be turned within a Kubernetes environment. It gives developers a lot of flexibility. These knobs, as you turn them, you have no visibility into how into the impact on the application itself. And so often organizations are become, you know, becoming more agile shipping, you know, shipping code more quickly, but then all of a sudden the, the cloud bill comes and they've, over-provisioned by 80, 90%, the, they didn't need nearly as many resources. And so what we do is we help understand the unique goals and requirements for each of the applications that are running in Kubernetes. And we have machine learning capabilities that can predict very accurately what organizations will need from a resource standpoint, in order to meet their goals, not just from a cost standpoint, but also from a performance standpoint. And so we allow organizations to typically save usually between 40 and 60% off their cloud bill and usually increased performance between 30 and 50%. Historically developers had to choose between cost and performance and their worldview on the application environment was very limited to a small set of what we would call parameters or metrics that they could choose from. And machine learning allows that world to just be blown open and not many humans are, are sophisticated in the way we think about multidimensional math to be able to make those kinds of predictions. You're talking about billions and billions of combinations, not just in a static environment, but an ongoing basis. So our technology sits in the middle of all that chaos and, and allows it to allows organizations just to re reap a whole lot of benefits that they otherwise may not ever find. >> Those numbers that you mentioned were, were big from a cost savings perspective than a performance increased perspective, which is so critical these days is in the last 18 months, we've seen so much change. We've seen massive pivots from companies in every industry to survive first of all, and then to be able to thrive and be able to iterate quickly enough to develop new products and services and get them to market to be competitive. >> Yeah. >> Yeah. Sorry. I mean, the thing that's interesting, there was an article by Andreessen Horowitz. I don't know if you've taken to the cloud paradox. So we actually, if you start looking at that great example would be some of these cloud companies that are growing like astronomical rates, snowflakes, like phenomenal what they're doing, but go look at their cogs and what it's doing. Also, it's growing almost proportionately as the revenues growing. So you need to be able to solve that problem in a way that is sophisticated enough with machine learning algorithms, that people don't have to be in the loop to do it. And that the math can prove out the solution as you go out and scale your environments. And a lot of companies now are all transitioning over SAS based platforms, and they're going to start running into these problems that they go as they go to scale. And those are the areas that we're really focused and concentrating on as an organization. >> As the leader of sales, talk to me about the voice of the customer. What are some- you've been there six months or so we heard, we heard about the wine and the dinners is obvious. >> We haven't done a lot of that over the last 18 months. >> You'll have to make for lost time then >> As soon as he closes more business. >> Oh, oh there we go, we got that on camera! >> There's, there's been three, a market spaces that we've had some really good success in that. So we talked about a SAS marketplace. So there's a company that does Drupal and Matt knows very well up in Boston, Aquia. And they have every customer is a unique snowflake customer. So they need to optimize each of their customers in order to ensure the cost as well as performance for that customer on their site works appropriately. So that's one example of a SAS based company that where we can go in and help them optimize without humans doing the optimization and the math and the machine learning from storm forge doing that. So that's an area, the other area that we've seen some really good traction Cantonese with GSI. So part of our go to market model is with GSI. So if you think about what a GSI does, a lot of times customers are struggling either initially deploying Kubernetes or putting it in for 12, 18 months and realizing we're starting to scale, we got all kinds of performance issues. How do I solve it? A lot of these people go to the Accentures, the cognizance and other ones, and start flying their ninjas into kind of solve the problem. So we're getting a lot of traction with them because they're using our tool as a way to help solve the customer's problems. And they're in the largest enterprise customers as possible. >> So if I'm hearing what you're saying correctly, you're saying that when I deploy server less applications, I may in fact, get a bill for servers that are being used? Is it, is that what you're telling us? >> They're there in fact may be a bill for what was coined as server less. That is very difficult to understand, by the way, >> That's crazy talk, Matt. >> And connect back. >> Yeah. But absolutely we deal with that all the time. It's a, it's a painful process from time to time. >> Have you, have you, have you seen the statistics that's going on with how people, I mean, there was huge inertia from every CIO that you had have a cloud strategy in place. Everyone ran out and had a cloud strategy in place. And then they started deploying on Kubernetes. Now they're realizing, oh wow, we can run it, but it's costing us more than it ever costs us on prem and the operational complexity associated with that. So there's not enough people in the industry to help solve that problem, especially at the grass roots, that's where you need sophisticated solutions like storm forge and machine learning to help solve this at scale problem in a way that humans could never solve. >> And I would, I would just add to that, that the, the same humans managing the Kubernetes application environments today are likely the same humans that we're managing it in a, in a BM world. So there's a huge skills gap. I love what Castin announced at KU KU con this year around their learning environment where it's free. Come learn Kubernetes and this, and we need more of that. There's an enormous skills gap and, and the problems are complex enough in and of themselves. But when we have, when you add that to the skills gap, it it's, it presents a lot of challenges for organizations. >> What are some the ways in which you think that gap can start to be made smaller. >> Yeah. I mean, I think as more workloads get moved over, over, you know, over time, you see, you see more and more people becoming comfortable in an environment where scale is a part of what they have to manage and take care of. I love what the Linux foundation and the CNCF are doing around Kubernetes certifications, you know, more and more training. I think you're going to see training, you know, availability for more and more developers and practitioners be adopted more widely. You know, and I think that, you know, as the tool chain itself hardens within a CCD world in a containerized world, as that hardens, you're going to, you're going to start seeing more and more individuals who are comfortable across all these different tools. If you look at the CNCF landscape, I mean, today compared to four or five years ago, it's growing like crazy. And so, but, but there's also consolidation taking place within the tools. And people have an opportunity to, to learn and gain expertise within us. Which is very marketable by the way, >> Absolutely >> My employees often show me their LinkedIn profiles and remind me of how , how much they're getting recruited, but they've been loyal. So it's been a fantastic. >> Are there are so many parallels when you look at a VM in virtualization and what's happening with covers, obviously all the abstractions and stuff, but there was this whole concept of VM sprawl, you know, maybe 10 years in, if you think about the Kubernetes environment, that is exponentially bigger problem because of how many they're spitting up versus how, how many you spun up in VM. So those things ultimately need to be solved. It's not just going to be solved with people. It needs to be solved with sophisticated software. That's the only way you're going to solve a problem at scale like that. No matter how many people you have in the industry, it's just never going to solve the problem. >> So when you're in customer conversations, Tom, what are you say are like the top three differentiators that really set storm forage apart? >> Well, so the first one is we're very focused on Kubernetes only. So that's all we do is just Kubernetes environment. So we understand not just the applications that run in Kubernetes, but we understand the underlying architectures and techniques, which we think is really important. From a solution standpoint, >> So you're specialists? >> We are absolutely specialists. The other areas obviously are machine learning and the sophistication of our machine learning. And Matt said this really well, early on, I mean, the buzzwords are all out there. You can read them all up, all over the place for the last five to seven year AI and ML. And a lot of them are very hollow, but our whole foundation was based on machine learning and PhDs from Harvard. That's where we came out of from a technology background. So we were solving more, we weren't just solving the Kubernetes problems. We were solving machine learning problems. And so that's another really big area of differential for us. And I think the ability to actually scale and not just deal with small problems, but very large problems, because our focus is the fortune 2000 companies. And most of them have been deploying like financial services and stuff, Kubernetes for three, four or five years. And so they have had scale challenges that they're trying to solve. >> Yeah. It's Lisa and I talk about this concept of machine learning and looking under the covers and trying to find out is the machine really learning? Is it really learning or is it people are telling the machine, you need to do this. If you see that Where's the machine actually making those correlations and doing something intelligently. So can you give us an example of something that is actually happening that's intelligent? >> Well, so the, the, if this, then that problem is actually a huge source of my original frustration for starting the company, because you, you, you tag AI as a buzzword onto a lot of stuff. And we see that growing like crazy. And so I literally at the beginning said, if we can't actually build something real, that solves problems, like we're going to hang it up. And, you know, as Tom said, we came out of Harvard and, you know, there was a challenge initially of, are we just going to build like a really amazing algorithm? That's so heavy, it can never be productized or commercialized and it really should have just stayed in academia. And, you know, I the I, I will say a couple of things. One is I do not believe that that black box AI is a thing. We believe in what we would call human, augmented AI. So we want to empower practitioners and developers into the process instead of automate them out. We just want to give them the information and we want to save time for them and make their lives easier. But there's a kill switch on the technology. They can intervene at any point in time. They can direct the technology as they see fit. And what's really, really interesting is because their worldview of this application environment gets opened up by all the predictions and all of the learning that actually is taking place and, you know, give it because that worldview is open, they then get into a kind of a tinkering or experimental mindset with the technology. And they start thinking about all these other scenarios that they never were able to explore previously with the application. And, and so the machine learning itself is on an ongoing basis. Understanding changes in traffic, understanding and changes, changes in workloads for the application or demand. If you thought about like surge pricing for Uber, you know, because of a, a big game that took place. And you know, that, that change in peaks and valleys in demand, our, our technology not only understands those reactively, but it starts to build models and predict proactively in advance of the events that are going to take place on, on what ne- what kind of resources need to be allocated. And why that's the other piece around it is often solutions are giving you a little bit of a what, but they certainly are not giving you any explanation of the why. So the holy grail really like in our world is kind of truly explainable AI, which we're not there yet. Nobody's there yet. But human augmented AI with, with actual intelligence that's taking place that also is relevant to business outcomes is, is pretty exciting. So that's why where try to operate. >> Very exciting guys. Thanks for joining us, talking to us about storm forage, to feel like we need some store in forge. T-shirts what do you think? >> (unintelligible) >> See, I'm not even asking for the bottle of wine. I liked that idea. I thank Matt and Tom, thank you so much for joining us exciting company. Congratulations on your success. And we look forward to seeing what great things are to come from storm forage. >> Thanks so much for the time. >> Our pleasure. For Dave Nicholson. I'm Lisa Martin. We are alive in Los Angeles, the cube covering Kube con and cloud native con 21 stick around. Dave and I will be right back with our next guest.

>>Oh, welcome back to the cubes coverage of coop con cloud native con 2021. I'm John is the Cuba, David Nicholson, our cloud host analyst, and it's exciting to be back in person in event. So we're back. It's been two years with the cube con and Linux foundation. So scrape, it was a hybrid event and we have a great guest here, Cuban London, Nick Dirk, and CT field CTO of harness and harness.io. The URL love the.io. Good to see you. >>Thank you guys for having me on. I genuinely appreciate >>It. Thanks for coming on. You were a part of our AWS startup showcase, which you guys were featured as a fast growing mature company, uh, as cloud scales, you guys have been doing extremely well. So congratulations. But now we're in reality now, right? So, okay. Cloud native has kind of like, okay, we don't have to sell it anymore. People buying into it. Um, and now operationalizing it with cloud operations, which means you're running stuff, applications and infrastructure is code and it costs money. Yeah. Martine Casada at Andreessen Horowitz. Oh, repatriated from the cloud. So there's a lot of, there's some cost conversations starting to happen. This is what you guys are in the middle of. >>Yeah, absolutely. What's interesting is when you think about it today, we want to shift left. When you want to empower all the engineers, we want to empower people. We're not giving them the data they need, right. They get a call from the CFO 30 days later, as opposed to actually being able to look at what change I did and how it actually affected. And this is what we're bringing in. Allowing people to have is now really empowering. So throughout the whole software delivery life cycle from CGI continuous integration, continuous delivery feature flagging, and even bringing cost modeling and in cloud cost management. And even then being able to shut down, shut down the services that you're not using, how much of that is waste. We talk about it. Every single cloud conference it's how much is waste. And so being able to actually turn those on, use those accordingly and then take advantage of even the cheapest instances when you should. That's really what >>It's so funny. People almost trip over dollars to pick up pennies in the cloud business because they're so focused on innovation that they think, okay, we've got to just innovate at all costs, but at some point you can make it productive for the developers in process in the pipeline to actually manage that. >>That's exactly it. I mean, if you think about it to me in order to breach state continuous delivery, we have to automate everything. Right. But that doesn't mean stop at just delivering, you know, to production. That means to customer, which means we've got to make them happy, but then ultimately all of those resources in dev and QA and staging and UAT, we've sticker those as well. And if we're not being mindful of it, the costs are astronomical, right. And we've seen it time and time again with every company you see, you've seen every article about how they've blown through all their budgets. So bring it to the people that can affect change. That's really the difference, making it visible, looking at it. In-depth not just at the cloud level and all the spend there, but also even at the, uh, thinking about it, the Kubernetes level down to the containers, the pods and understanding where are the resources even inside of the clusters and bringing that as an aggregate, not just for visibility and, and giving recommendations, but now more importantly, because part of a pipeline start taking action. That's where it's interesting. It's not just about being able to see it and understand it and hope, right? Hope is not a strategy acting upon it is what makes it valuable. And that's part of the automate everything. >>Yeah. We'll let that at the Dawn of the age of DevOps, uh, there was a huge incentive for a developer just to get their job done, to seize control of infrastructure, the idea of infrastructure as code, you know, and it's, it's, you know, w when it was being born, it's a fantastic, I've always wondered though, you know, be careful what you wish for. Do you really want all of that responsibility? So we've got responsibility from a compliance and security perspective and of course cost. So, so where do we, where do we go from here, I guess is the question. Yeah. So >>When we look at building this all together, I think when we think about software delivery, everybody wants to go fast. We start with velocity, right? Everybody says, that's where I want to go. And to your point with governance compliance, the next roadblock to hit is weight. In order to go fast, I have to do it appropriately. I've got governing bodies that tell me how this has to work. And that becomes a challenge. >>It slows it down too. It doesn't, I mean, basically people are getting pissed off, right? This is, this general sentiment is, is that developers are moving fast with their code. And then they have to stop. Compliance has to give the green light sometimes days, correct? Uh, it used to be weeks now. It's days, it's still unacceptable. So there's like this always been that tension to the security groups or say it, or finance was like slow down and they actually want to go faster. So that has to be policy-based something. Yep. This is the future. What is your take on that? >>Take on, this is pretty simple. When everybody talks about people, process and technology, it's kind of bogus, right? It's all about confidence. If you're confident that your developers can deploy appropriately and they're not going to do something wrong, you'll let them to play all the time. Well, that requires process. But if you have tooling that literally guarantees your governance, make sure that at no point in time, can any of your developers actually do something wrong. Now you have, >>That's the key. That's the key. That's the key because you're giving them a policy-based guardrails to execute in their programs >>And that's it. So now you can free up all those pieces. So all those bottlenecks, all those waiting all those time, and this is how all of our customers, they move from, you know, change advisory boards that approve deployments. >>Can you give us some, give us some, give us some, uh, customer anecdotal examples of this inaction and kind of the love letters you get, or, or the customer you take us through a use case of how it all. >>So this is one of my favorites. So NCR national cash register. If you slide a credit card at like a Chick-fil-A or a Safeway, right? Um, traditional technology. But what was interesting is they went from doing PCI audit, which would take seven days to go to a PCI audit right now with harness, because, >>And by the way, when you and the seventh, six day, the things that you did on day one change. >>Exactly, exactly. And so now, because of using harness and everything's audited, and all the changes are, are controlled to make sure that developers again, can only do what they're allowed. They only get to broadcast two per production. If they've met all their security requirements, all their compliance, permits, all their quality checks. Now, because of that, they literally gave a re read only view of harness to their auditor. And in three hours it was over. And it's because now we're that evidence file from code commit through to production. Yeah. It's there for point of sale compliant. >>So what is the benefits to them? What's the result saves them time, saves the money. What's the good, the free up more times. I'll see the chops it down. That's the key. >>Yeah. It's actually something we didn't build in like our ROI calculators, which was, we talked to their engineers and we gave them their nights and their weekends back, which I thought was amazing. But Thursday night, when we're doing that deploy, they don't have to be up. Harness is actually managing and understanding, using machine learning to understand what normal looks like. So they don't have to, they don't have to sit and look at the knock or sit in the war room and eat the free pizza. Yeah. Right. And then when those things break, same concept rates aren't as good. So >>I got to ask you, I got you here. You know, as the software development delivery lifecycle is radically being overhauled right now, which people generally agree that that's the case, the old models are, are different. How do you see your vision around AI and automation playing into this? Because you could say, okay, we're going to have different kinds of coding styles. This batch has got an AI block here. It's very Lego block. Like yep. Okay. Services and higher level services in the cloud. What's your reaction to how this impacts automation and >>Sure. So throughout our entire platform, we've designed our AI to take care of the worst parts of anyone's job as Guinea dev ops person. If they love babysitting deployments, they don't harness handles that for them, ask your engineers that they love sitting there waiting for their tests to run. Every time they build, they go get coffee, right. Because we're waiting for all of our tests to run. Y yeah. Right. The reality >>Is sometimes they have to wait days and >>That's it. But like, if I change the gas cap on, uh, on your car, would you expect me to check every light switch and every electronic piece? No. Well, why do we do that with code? And so our AI, our ML is designed to remove all the things that people hate. It's not to remove people's jobs. It's actually to make their jobs much better. >>How do you guys feed the data? What's the training algorithm for that? How does that work? Yeah, >>Actually, it's interesting. A lot of people think it's going to take a ton of time to figure this out. The good news is we start seeing this on the second deployment. On the second bill, we have to have a baseline of what good looks like, and that's where it starts. And it goes from there. And by the way, this isn't a lot of people say AI, and this AML, I teach a class on this because ML is not standard deviation. It's not some checks. So we use a massive amount of machine learning, but we have neural networks to think about things like engineers do. Like if we looked at a log and I saw the same log with two different user IDs, you and I would know, well, it's the same thing. It's just different users, but machine learning models. Don't so we've got to build neural networks to actually think like humans. So that, >>So that's the whole expectation maximization kind of concept of people talk about, >>Well, and that's it because at the end of the day, we're like I said, I'm not trying to take people's jobs. I want to meet. >>Yeah. You want to do the crap work out of the way. And I had to do other redundant, heavy lifting that they have to do every single time we use the cloud way. We've >>Built mechanical muscle in, in the early 19 hundreds. Right. And it made everyone's jobs easier, allowed them to do more with their time. That's exactly what we're doing here. >>I mean, we've seen the big old guys in the industry trying to evolve. You got the hot startups coming out. So you got, you know, adapt or die as classic thing. We've been saying for many years, David on the cube, you know that. So it's like, this is a moment of truth. We're going to see who comes out the other side. How do you, Nick, what would you be your, your kind of guess of when that other side is, when are we gonna know the winners and the losers truly in the sense of where we are now? >>So I think what I've found is that in this space specifically, there's a constant shift and this is something with software. And the problem is, is that we see them come in ebbs and flows, right. And very few times are there businesses that actually carry the model? And what you find is that when they focus on one specific problem, it solves it. Now, if I was working on VMs a few years ago, great, but now we're, we're here at coop con, right? And that's because it's eaten, uh, that side of the world. And so I think it's the companies that can actually grow the test of time and continue to expand to where the problems are. Right. And that's one of the things that I traditionally think about harness and we've done it. We cover our customers where they were, I think the old mainframes, if you had to, where they were, where they are at their traditional, their VM. >>I mean, if you think about it, Nick, it's one of those things where it's like, that's such a common sense way to look at it evolves with a problem. So I ride the right with tech ways. But if you think about the high order bit, here is just applications. We ended the day. Companies have applications that they want to write modern. The applications of their business is going to be codified so that you just work backwards from there. Then you say, okay, what is the infrastructure as code working for me? That's an ethos of dev ops. And that's where we're at. So that's why I think that the cloud need is kind of one already, but we still have the edge devices, more complexity. This is a huge next level conversation at one point is that we just put a hard and top on the complexity. When is that coming? Because the developers are clear. They want to go fast. They want to go shift left and have all that data, get the right analytics, the telemetry and the AI. But it's too complicated still. That is a big problem. >>It's too complicated. You ask for a full-stack developer to also know infrastructure, to also know edge computing. Like it's impossible, right? And this is where tooling helps, right? Because if you can actually parameterize that and make it to the engineers and have to care, they can do what they're best at. Hey, I'm great at turning code in artifact, let them do that and have tooling take care of the rest. This is where our goal is. Again, allow people >>We'll do what they love. And this is kind of the new roles that are changing. What SRE has done. Everyone talks about the SRE and some states just as he had dev ops guy, but it's not just that there's also, uh, different roles emerging. It's, it's an architectural game. At this point, we would say, >>I'd say a hundred percent. And this is where the decisions that you make on are architecturally. If you don't know how to then roll them out, this is what we've seen. Time and time again, you go to these large companies, I've got these great architectures on planning four years later, we haven't reached it because to that point process, >>The process killed them four >>Different new tools throughout the process. Well, yeah. >>So when do we hit peak Kubernetes peak >>Kubernetes? I think we have a bit to go in and I'm excited about the networking space and really what we're doing there and, and bringing that holistic portion of the network, like when Istio was originally released, I thought that was one of the most amazing things, uh, to truly come to it. And I think there's a vast space in networking. Um, and, and so I think in the next few years, we're going to see this, you know, turn into that a hundred percent utilized across the board. This will be that where everyone's workloads continue to exist. Um, somewhat like VMs we're in >>And, and, and no, no fear of developers as code in the very near future. You're talking about automating the mundane. Correct. Uh, there have been stories recently about the three-day workweek, you know, as a, as a fan of, um, utopian science fiction, myself, as opposed to dystopian. Absolutely. I think that, you know, technology does have the opportunity to lift all boats and, uh, and it's, it's not nothing to be afraid of. You know, the fact that I put my dishes in the dishwasher and they run by themselves for three hours. It's a good thing. It's a great thing. >>I don't need to deal with that. Yeah, I agree. No, I think that's, and that's what I said in the beginning. Right. That's really where we can start empowering people. So allow them to do what they're good at and do what they're best at. And if you look at why do people quit? We don't have to go so hard to find. Yeah. Why? Because they're secondary to babysit and implement and they're told everywhere they go, they're not going to have to >>That's the line. And that's all right. We got a break, but it's great insight to have you on the Q one final question for you. Um, I got to ask about the whole data as code something that I've been riffing on for a bunch of years now. And as infrastructures could we get that, but data is now the resource everyone needs, and everyone's trying to, okay, I have the control plane for this and that, but ultimately data cannot be siloed. This is a critical architectural element. How does that get resolved in the land of the competitive advantage and lock in and whatnot? What's your take on that? >>So data's an interesting one because it has, it has gravity and this is the problem. And as we move, as I think you guys know, as you move to the edge as remove, move it places there's insights to be taken at the edge there's insights to be taken as it moves through. And I think what you'll see honestly, going forward is you'll see compute done differently to your point. It needs to be aggregated. It needs to be able to be used together, but I think you'll see people computing it on its way through it. So now even in transport, you'll start seeing insights gained in real time before you can have the larger insights. And I see that happening more and more. Um, and I think ultimately we just want to empower that >>Nick, great to have you on CTO of field CTO of harness and harness.io is a URL. Check it out. Thanks for the insight. Thank you so much. Great comments. Appreciate it. Natural cube analysts right here, Nick, of course, we've got our, our analysts right here, David Nicholson. You're good on your own. I'm John for a, you know, we have the host. Thanks for watching. Stay with two more days of coverage. We'll be back after this short break.

>>it's mhm Okay, we're here in the cube unpacking the HPD Green Lake announcements, Daniel neumann series Principal analyst and founder of your um research Damn. You're good to see you again, >>Dave always going to jump jump on with you. It's good to have a minute sit down. So >>what's your favorite announcement from from Green Lake? What do you, what do you make of what they announced today? >>Well, I love the opportunity for the company to position itself up against a growth monster like snowflake. I mean looking at the ability to handle the breath of the data at scale and offer a data service that can compete in that space. That's exactly the kind of narrative that I think the markets, the outside world is going to want to hear from HP is how you're not just competing with your traditional, the doubles, the Ciscos, the IBM, you're going after the, the mega growth cloud players and data services. And for me that's really attractive because I've been really on top of hb saying, hey, you're doing a lot of the right things, but people have to feel and see the growth. >>To me this is a major move toward the tam expansion strategy. It's kind of the job of every Ceo right, is to expand the tam. And I'm interested to see how HP e plays this and communicates this because, you know, traditionally it's a hardware company, uh moving into data management Data services. That's an enormous market. We'll talk about how important data is but the data management is just huge. And to do it in a cloud like fashion, how do you see that as potentially expanding the total available market for HP? >>Well, first, let's just almost walking back a second, Dave HP is a cloud player. Okay. And that's the story that it is trying to get out there. It is not a hardware player that's tinkering in software. Hp has done software, this isn't its first go. But if you want to be a cloud player, you look at the big hyper scale as you look at the AWS, as you look at the google, you look at as the google built, not just on hardware, it's built that big C and I've had this conversation before, all the things that make up the cloud, it's the hardware, it's the software, it's the services, the platform, you got to put all these things together. And if HP wants to be a public cloud experience, taking advantage of where we're moving with hybrid and offering it private, it has to have that same subset of services. Look at the investment, whether it's been a W S or google or Azure in data services, HP has to be in this space. So, seeing this come to fruition, in my opinion, is directionally the right path, getting it to be well received, winning the right customers and showing the growth from these investments is going to be the next important phase. >>Do you see that as a service model as being more margin friendly for HP and and if so why? Well, I think >>universally we found there's two major improvements that moving to the as a service. One is, it does over time create expanded operational margin. It's just economies of scale. You can utilize every resource more efficiently. Of course there are Capex expenses, You've seen the amount that hyper skeletons have had to spend to expand their their footprints globally. So there is some Capex upfront but that also on the back end creates the depreciation and different bottom line profit creators. At the same time though, as a service is huge for the multiples and evaluation, which by the way is one of the things that has been a real in focus point for H. P. E. Is how does it up that that number, You know, you look at the snowflakes, not even profitable but getting huge. You know, um, you know, huge multiples on revenue. And then you see even the other hyper scale is all getting bigger plays on revenue and on E. P. S. Most of it has to do with the fact that recurring revenue is beloved by investors, but it's also really sticky and creates a ton of stability within the company for the culture of the business to say, hey, we have customers, they're going to stay with us. They're not going anywhere. They're subscribed to our services. They're buying into what we're doing and by the way, net revenue expansion as you get them sticky, you layer in new services. We've seen how this has worked across the board with public cloud, with software with SAS, can HP do it as well? And of course it's been something they're doing, but it's something we need to watch really closely and I think it's an opportunity that the company needs to lean into it. And I think they will, >>you mentioned snowflake a couple times, there's a there's a, there's a discussion in the industry, it was sort of prompted by martin casado and sarah wang about repatriation and particularly as it relates to software, saas companies uh that the the the cloud bill is so high at some point, they're giving away margin, so they're going to have to come back on prem, I'm not sure that to date that has applied to the general audience of customer, although there's a lot of debate as well between the expensive cloud, obviously, you know, egress charges. So it's hard sometimes to squint through that when you think about HP E bringing Green Lake to market at scale bringing repeatable processes, driving automation, etcetera. How do you think that that cloud repatriation argument, which frankly, I haven't seen a huge cloud repatriation in in the macro, but how do you think that will play out over time, Do you feel like the on prem play can be as cost effective or more cost effective or maybe you feel like it is already today? >>Well, I also listen to the injuries and Horowitz uh, repatriation narrative as well. I think there are economies of scale with cloud that companies have to look at closely. But I also think that has a lot to do with why hybrid has been sort of the story of the day. That's why hyper sailors are going on prem or, and that's why I'm primes are moving to the cloud is because it's always going to be some, you know, some group of different placements of workloads to ultimately get to that optimized result. And so, you know, when you look at, you know, sort of what you asked in my opinion, you know, ultimately it's all about the efficiency of your organization trying to accomplish what your business is. And will there be some repatriation of workloads possibly. But there will be a very important hybrid mix. And I think we're gonna continue to see that trend and I think that's exactly where everyone's going in. Hp is going as well. >>All right, then we've got to leave it there. Thanks so much for your insights, appreciate it. We're gonna definitely have you back you and I are going to do some cool stuff together. So we'll talk next time. Thanks all right, and thank you for watching, this is Dave Volonte for the keeps coverage of H P E Green Lakes announcement, keep it right there. Mm

(gentle upbeat music) >> People hate to be sold, but they love to buy. We become what we think about, think, and grow rich. If you want to gather honey, don't kick over the beehive. The world is replete with time-tested advice and motivational ideas for aspiring salespeople, Dale Carnegie, Napoleon Hill, Norman Vincent Peale, Earl Nightingale, and many others have all published classics with guidance that when followed closely, almost always leads to success. More modern personalities have emerged in the internet era, like Tony Robbins, and Gary Vaynerchuk, and Angela Duckworth. But for the most part, they've continued to rely on book publishing, seminars, and high value consulting to peddle their insights and inspire action. Welcome to this video exclusive on theCUBE. This is Dave Vellante, and I'm pleased to welcome back Professor Mark Roberge, who is one of the Managing Directors at Stage 2 Capital, and Paul Fifield, who's the CEO and Co-Founder of Sales Impact Academy. Gentlemen, welcome. Great to see you. >> You too Dave and thanks. >> All right, let's get right into it. Paul, you guys are announcing today a $4 million financing round. It comprises $3 million in a seed round led by Stage 2 and a million dollar in debt financing. So, first of all, congratulations. Paul, why did you start Sales Impact Academy? >> Cool, well, I think my background is sort of two times CRO, so I've built two reasonably successful companies. Built a hundred plus person teams. And so I've got kind of this firsthand experience of having to learn literally everything on the job whilst delivering these very kind of rapid, like achieving these very rapid growth targets. And so when I came out of those two journeys, I literally just started doing some voluntary teaching in and around London where I now live. I spend a bunch of time over in New York, and literally started this because I wanted to sort of kind of give back, but just really wanted to start helping people who were just really, really struggling in high pressure environments. And that's both leadership from sense of revenue leadership people, right down to sort of frontline SDRs. And I think as I started just doing this voluntary teaching, I kind of realized that actually the sort of global education system has done is a massive, massive disservice, right? I actually call it the greatest educational travesty of the last 50 years, where higher education has entirely overlooked sales as a profession. And the knock-on consequences of that have been absolutely disastrous for our profession. Partly that the profession is seen as a bit sort of embarrassing to be a part of. You kind of like go get a sales job if you can't get a degree. But more than that, the core fundamental within revenue teams and within sales people is now completely lacking 'cause there's no structured formal kind of like learning out there. So that's really the problem we're trying to solve on the kind of like the skill side. >> Great. Okay. And mark, always good to have you on, and I got to ask you. So even though, I know this is the wheelhouse for you and your partners, and of course, you've got a deep bench of LPs, but lay out the investment thesis here. What's the core problem that you saw and how are you looking at the market? >> Yeah, sure, Dave. So this one was a special one for me. We've spoken in the past. I mean, just personally I've always had a similar passion to Paul that it's amazing how important sales execution is to all companies, nevermind just the startup ecosystem. And I've always personally been motivated by anything that can help the startup ecosystem increase their success. Part of why I teach at Harvard and try to change some of the stuff that Paul's talking about, which is like, it's amazing how little education is done around sales. But in this particular one, not only personally was I excited about, but from a fun perspective, we've got to look at the economic outcomes. And we've been thinking a lot about the sales tech stack. It's evolved a ton in the last couple of decades. We've gone from the late '90s where every sales VP was just, they had a thing called the CRM that none of their reps even used, right? And we've come so far in 20 years, we've got all these amazing tools that help us cold call, that help us send emails efficiently and automatically and track everything, but nothing's really happened on the education side. And that's really the enormous gap that we've seen is, these organizations being much more proactive around adopting technology that can prove sales execution, but nothing on the education side. And the other piece that we saw is, it's almost like all these companies are reinventing the wheel of looking in the upcoming year, having a dozen sales people to hire, and trying to put together a sales enablement program within their organization to teach salespeople sales 101. Like how to find a champion, how to develop a budget, how to develop sense of urgency. And what Paul and team can do in the first phase of essay, is can sort of centralize that, so that all of these organizations can benefit from the best content and the best instructors for their team. >> So Paul, exactly, thank you, mark. Exactly what do you guys do? What do you sell? I'm curious, is this sort of, I'm thinking in my head, is this E-learning, is it really part of the sales stack? Maybe you could help us understand that better. >> Well, I think this problem of having to upscale teams has been around like forever. And kind of going back to the kind of education problem, it's what's wild is that we would never accept this of our lawyers, our accountants, or HR professionals. Imagine like someone in your finance team arriving on day one and they're searching YouTube to try and work out how to like put a balance sheet together. So it's a chronic, chronic problem. And so the way that we're addressing this, and I think the problem is well understood, but there's always been a terrible market, sort of product market fit for how the problem gets solved. So as mark was saying, typically it's in-house revenue leaders who themselves have got massive gaps in their knowledge, hack together some internal learning that is just pretty poor, 'cause it's not really their skillset. The other alternative is bringing in really expensive consultants, but they're consultants with a very single worldview and the complexity of a modern revenue organization is very, very high these days. And so one consultant is not going to really kind of like cover every topic you need. And then there's the kind of like fairly old fashioned sales training companies that just come in, one big hit, super expensive and then sort of leave again. So the sort of product market fit to solve, has always been a bit pretty bad. So what we've done is we've created a subscription model. We've essentially productized skills development. The way that we've done that is we teach live instruction. So one of the big challenges Andreessen Horowitz put a post out around this so quite recently, one of the big problems of online learning is that this kind of huge repository of online learning, which puts all the onus on the learner to have the discipline to go through these courses and consume them in an on-demand way is actually they're pretty ineffective. We see sort of completion rates of like 7 to 8%. So we've always gone from a live instruction model. So the sort of ingredients are the absolute very best people in the world in their very specific skill teaching live classes just two hours per week. So we're not overwhelming the learners who are already in work, and they have targets, and they've got a lot of pressure. And we have courses that last maybe four to like 12 hours over two to sort of six to seven weeks. So highly practical live instruction. We have 70, 80, sometimes even 90% completion rates of the sort of live class experience, and then teams then rapidly put that best practice into practice and see amazing results in things like top of funnel, or conversion, or retention. >> So live is compulsory and I presume on-demand? If you want to refresh you have an on demand option? >> Yeah, everything's recorded, so you can kind of catch up on a class if you've missed it, But that live instruction is powerful because it's kind of in your calendar, right? So you show up. But the really powerful thing, actually, is that entire teams within companies can actually learn at exactly the same pace. So we teach it eight o'clock Pacific, 11 o'clock Eastern, >> 4: 00 PM in the UK, and 5:00 PM Europe. So your entire European and North American teams can literally learn in the same class with a world-class expert, like a Mark, or like a Kevin Dorsey, or like Greg Holmes from Zoom. And you're learning from these incredible people. Class finishes, teams can come back together, talk about this incredible best practice they've just learned, and then immediately put it into practice. And that's where we're seeing these incredible, kind of almost instant impact on performance at real scale. >> So, Mark, in thinking about your investment, you must've been thinking about, okay, how do we scale this thing? You've got an instructor component, you've got this live piece. How are you thinking about that at scale? >> Yeah, there's a lot of different business model options there. And I actually think multiple of them are achievable in the longer term. That's something we've been working with Paul quite a bit, is like, they're all quite compelling. So just trying to think about which two to start with. But I think you've seen a lot of this in education models today. Is a mixture of on-demand with prerecorded. And so I think that will be the starting point. And I think from a scalability standpoint, we were also, we don't always try to do this with our investments, but clearly our LP base or limited partner base was going to be a key ingredient to at least the first cycle of this business. You know, our VC firm's backed by over 250 CRO CMOs heads of customer success, all of which are prospective instructors, prospective content developers, and prospective customers. So that was a little nicety around the scale and investment thesis for this one. >> And what's in it for them? I mean, they get paid. Obviously, you have a stake in the game, but what's in it for the instructors. They get paid on a sort of a per course basis? How does that model work? >> Yeah, we have a development fee for each kind of hour of teaching that gets created So we've mapped out a pretty significant curriculum. And we have about 250 hours of life teaching now already written. We actually think it's going to be about 3000 hours of learning before you get even close to a complete curriculum for every aspect of a revenue organization from revenue operations, to customer success, to marketing, to sales, to leadership, and management. But we have a development fee per class, and we have a teaching fee as well. >> Yeah, so, I mean, I think you guys, it's really an underserved market, and then when you think about it, most organizations, they just don't invest in training. And so, I mean, I would think you'd want to take it, I don't know what the right number is, 5, 10% of your sales budget and actually put it on this and the return would be enormous. How do you guys think about the market size? Like I said before, is it E-learning, is it part of the CRM stack? How do you size this market? >> Well, I think for us it's service to people. A highly skilled sales rep with an email address, a phone and a spreadsheet would do really well, okay? You don't need this world-class tech stack to do well in sales. You need the skills to be able to do the job. But the reverse, that's not true, right? An unskilled person with a world-class tech stack won't do well. And so fundamentally, the skill level of your team is the number one most important thing to get right to be successful in revenue. But as I said before, the product market for it to solve that problem, has been pretty terrible. So we see ourselves 100%. And so if you're looking at like a com, you look at Gong, who we've just signed as a customer, which is fantastic. Gong has a technology that helps salespeople do better through call recording. You have Outreach, who is also a customer. They have technologies that help SDRs be more efficient in outreach. And now you have Sales Impact Academy, and we help with skills development of your team, of the entirety of your revenue function. So we absolutely see ourselves as a key part of that stack. In terms of the TAM, 60 million people in sales are on, according to LinkedIn. You're probably talking 150 million people in go to market to include all of the different roles. 50% of the world's companies are B2B. The TAM is huge. But what blows my mind, and this kind of goes back to this why the global education system has overlooked this because essentially if half the world's companies are B2B, that's probably a proxy for the half of the world's GDP, Half of the world's economic growth is relying on the revenue function of half the world's companies, and they don't really know what they're doing, (laughs) which is absolutely staggering. And if we can solve that in a meaningfully meaningful way at massive scale, then the impact should be absolutely enormous. >> So, Mark, no lack of TAM. I know that you guys at Stage 2, you're also very much focused on the metrics. You have a fundamental philosophy that your product market fit and retention should come before hyper growth. So what were the metrics that enticed you to make this investment? >> Yeah, it's a good question, Dave, 'cause that's where we always look first, which I think is a little different than most early stage investors. There's a big, I guess, meme, triple, triple, double, double that's popular in Silicon Valley these days, which refers to triple your revenue in year one, triple your revenue in year two, double in year three, and four, and five. And that type of a hyper growth is critical, but it's often jumped too quickly in our opinion. That there's a premature victory called on product market fit, which kills a larger percentage of businesses than is necessary. And so with all our investments, we look very heavily first at user engagement, any early indicators of user retention. And the numbers were just off the charts for SIA in terms of the customers, in terms of the NPS scores that they were getting on their sessions, in terms of the completion rate on their courses, in terms of the customers that started with a couple of seats and expanded to more seats once they got a taste of the program. So that's where we look first as a strong foundation to build a scalable business, and it was off the charts positive for SIA. >> So how about the competition? If I Google sales training software, I'll get like dozens of companies. Lessonly, and MindTickle, or Brainshark will come up, that's not really a fit. So how do you think about the competition? How are you different? >> Yeah, well, one thing we try and avoid is any reference to sales training, 'cause that really sort of speaks to this very old kind of fashioned way of doing this. And I actually think that from a pure pedagogy perspective, so from a pure learning design perspective, the old fashioned way of doing sales training was pull a whole team off site, usually in a really terrible hotel with no windows for a day or two. And that's it, that's your learning experience. And that's not how human beings learn, right? So just even if the content was fantastic, the learning experience was so terrible, it was just very kind of ineffective. So we sort of avoid kind of like sales training, The likes of MindTickle, we're actually talking to them at the moment about a partnership there. They're a platform play, and we're certainly building a platform, but we're very much about the live instruction and creating the biggest curriculum and the broadest curriculum on the internet, in the world, basically, for revenue teams. So the competition is kind of interesting 'cause there is not really a direct subscription-based live like learning offering out there. There's some similar ish companies. I honestly think at the moment it's kind of status quo. We're genuinely creating a new category of in-work learning for revenue teams. And so we're in this kind of semi and sort of evangelical sort of phase. So really, status quo is one of the biggest sort of competitors. But if you think about some of those old, old fashioned sort of Miller Heimans, and then perhaps even like Sandlers, there's an analogy perhaps here, which is kind of interesting, which is a little bit like Siebel and Salesforce in the sort of late '90s, where in Siebel you have this kind of old way of doing things. It was a little bit ineffective. It was really expensive. Not accessible to a huge space of the market. And Salesforce came along and said, "Hey, we're going to create this cool thing. It's going to be through the browser, it's going to be accessible to everyone, and it's going to be really, really effective." And so there's some really kind of interesting parallels almost between like Siebel and Salesforce and what we're doing to completely kind of upend the sort of the old fashioned way of delivering sort of sales training, if you like. >> And your target customer profile is, you're selling to teams, right? B2B teams, right? It's not for individuals. Is that correct, Paul? >> Currently. Yeah, yeah. So currently we've got a big foothold in series A to series B. So broadly speaking out, our target market currently is really fast growth technology companies. That's the sector that we're really focusing on. We've got a very good strong foothold in series A series B companies. We've now won some much larger later stage companies. We've actually even won a couple of corporates, I can't say names yet, but names that are very, very, very familiar and we're incredibly excited by them, which could end up being thousand plus seat deals 'cause we do this on a per seat basis. But yeah, very much at the moment it's fast growth tech companies, and we're sort of moving up the chain towards enterprise. >> And how do you deal with the sort of maturity curve, if you will, of your students? You've got some that are brand new, just fresh out of school. You've got others that are more seasoned. What do you do, pop them into different points of the curriculum? How do you handle it? >> Yeah we have, I'll say we have about 30 courses right now. We have about another 15 in development where post this fundraise, we want to be able to get to around about 20 courses that we're developing every quarter and getting out to market. So we're literally, we've sort of identified about 20 to 25 key roles across everything within revenue. That's, let's say revenue ops, customer success, account management, sales, engineering, all these different kinds of roles. And we are literally plotting the sort of skills development for these individuals over multiple, multiple years. And I think what we've never ceases to amaze me is actually the breadth of learning in revenue is absolutely enormous. And what kind of just makes you laugh is, this is all of this knowledge that we're now creating it's what companies just hope that their teams somehow acquire through osmosis, through blogs, through events. And it's just kind of crazy that there is... It's absolutely insane that we don't already exist, basically. >> And if I understand it correctly, just from looking at your website, you've got the entry level package. I think it's up to 15 seats, and then you scale up from there, correct? Is it sort of as a seat-based license model? >> Yeah, it's a seat-based model, as Mark mentioned. In some cases we sell, let's say 20 or $30,000 deal out the gate and that's most of the team. That will be maybe a series A, series B deal, but then we've got these land and expand models that are working tremendously well. We have seven, eight customers in Q1 that have doubled their spend Q2. That's the impact that they're seeing. And our net revenue retention number for Q2 is looking like it's going to be 177% to think exceeds companies like Snowflakes. Well, our underlying retention metrics, because people are seeing this incredible impact on teams and performance, is really, really strong. >> That's a nice metric compare with Snowflake (Paul laughs) It's all right. (Dave and Paul laugh) >> So, Mark, this is a larger investment for Stage 2 You guys have been growing and sort of upping your game. And maybe talk about that a little bit. >> Yeah, we're in the middle of Fund II right now. So, Fund I was in 2018. We were doing smaller checks. It was our first time out of the gate. The mission has really taken of, our LP base has really taken off. And so this deal looks a lot like more like our second fund. We'll actually make an announcement in a few weeks now that we've closed that out. But it's a much larger fund and our first investments should be in that 2 to $3 million range. >> Hey, Paul, what are you going to do with the money? What are the use of funds? >> Put it on black, (chuckles) we're going to like- (Dave laughs) >> Saratoga is open. (laughs) (Mark laughs) >> We're going to, look, the curriculum development for us is absolutely everything, but we're also going to be investing in building our own technology platform as well. And there are some other really important aspects to the kind of overall offering. We're looking at building an assessment tool so we can actually kind of like start to assess skills across teams. We certify every course has an exam, so we want to get more robust around the certification as well, because we're hoping that our certification becomes the global standard in understanding for the first time in the industry what individual competencies and skills people have, which will be huge. So we have a broad range of things that we want to start initiating now. But I just wanted to quickly say Stage 2 has been nothing short of incredible in every kind of which way. Of course, this investment, the fit is kind of insane, but the LPs have been extraordinary in helping. We've got a huge number of them are now customers very quickly. Mark and the team are helping enormously on our own kind of like go to market and metrics. I've been doing this for 20 years. I've raised over 100 million myself in venture capital. I've never known a venture capital firm with such value add like ever, or even heard of other people getting the kind of value add that we're getting. So I just wanted to a quick shout out for Stage 2. >> Quite a testimony of you guys. Definitely Stage 2 punches above its weight. Guys, we'll leave it there. Thanks so much for coming on. Good luck and we'll be watching. Appreciate your time. >> Thanks, Dave. >> Thank you very much. >> All right, thank you everybody for watching this Cube conversation. This is Dave Vellante, and we'll see you next time.

(upbeat music) >> Okay, we're back here at theCUBE on this floor in CLOUD CITY, the center of all the action at Mobile World Congress. I'm John Brown your host. Michael current CTO of Virta San is here with me remote because this is a virtual event as well, this is a hybrid event. The first industry hybrid event, Greg would be back in real life on the floor, Michael, you coming in remotely. Thanks for joining us here in the cube in cloud city. >> Thanks for having me and said the beer. >> We were just talking on camera about. He went to Michigan and football, all that good time while we were waiting from Adam to pseudo great stuff, but let's get into what you guys are doing. You've got a great cloud news, we're going to get to, but take a minute to explain what you guys do first. >> So Virtasant helps organizations of any size thrive in the cloud. So we have a unique combination of proprietary technologies, such as our cloud optimization platform that we'll talk about in a minute and a global team of experts that helps companies make the most of the cloud from getting to the cloud and building the cloud to optimizing the cloud all the way to managing the cloud at scale. >> Well, you got a lot of experience dealing with the enterprise, a lot of customer growth over the years, great leader. The cloud dynamic here is the big story at mobile world congress, this year, the change over, I won't say change over per se, but certainly the shift or growth of cloud on top of telco, you guys have some news here at mobile world congress. Let's share the news, what's the big scoop? >> So we have an automated cloud optimization platform that helps companies automatically understand your usage patterns and do spend fully, automatically. And we focus first on AWS is the biggest cloud provider, but starting this week, we wanted announces we're actually going live with our GCP product, which means people who are on the GCP cloud platform can now leverage our platform to constantly understand usage patterns and spend and automatically take action to reduce spend. So we typically see customers save over 50% when they use our platform. So now GCP customers can take advantage of the same capabilities that our AWS customers take advantage of every day. >> Talk about the relationships as you get deeper. And this seems to be the pattern I want to just unpack it. You don't mind a little bit the relationship with Google and this announcement and Amazon you're tightly coupled with them, is it more integration? Talk about what makes these deals different and special for your customers? What's what's, what's about them. What's the big deal? >> Well, I think for us, obviously we think that, you know, the public cloud's the future, right? And obviously cloud city and all the different companies there agree with us, and we think that much like, you know, you don't, you don't generate your own electricity. We don't think you're going to generate you're to you're going to build your own technology infrastructure. For the most part, we think that pretty much all compute will be in the public cloud. And obviously AWS is the market leader in the largest cloud provider in the, but you know, GCP, especially with telecom has some compelling offerings. And we think that, you know, organizations are going to want choice. Many will go multicloud, meaning they'll have 1, 2, 3 of the big providers and move workloads across those. But even those who choose one cloud provider, you know, each cloud provider has their strengths and different companies will choose different providers. And they're all, you know, they've all got strong capabilities and their uniqueness. So we want to make sure that whether, you know, an organization goes across all cloud providers or they choose one that we can support them no matter what the workloads look like, and so for us, you know, developing deep relationships with each of the public cloud providers, but also, you know, expanding our full set of capabilities to support all of them is critically important because we do think that there's going to be, you know, a handful of large public cloud providers and obviously AWS and GCP are among them. >> Yeah, I mean, I talk to people all the time and even, you know, we're an Amazon customer, pretty robust cloud in the bills out of control is what's, what's this charge for it. There's more services to tap into, you know, it's like first one's on me, you know? And then next thing you know, you're, you're consuming a hell of a lot of new services, but there's value there and there's breaths a minute for the cloud, we all love that. But just as a random aside here, I want to get your thoughts real quick, if you don't mind, this idea of a cloud economist has become part of a new role in an organization, certainly SRS is DevOps. Then you starting to get into people who actually can squint through the data and understand the consumption and be more on the economics side, because people are changing how they report their earnings. They're changing how they report their KPIs based upon the usage and costs, and... What, is this real? what's your thoughts on that? I know that's a little random, but I want to get your, get your thoughts on that. >> Well, yeah, it's interesting that that's been a development. What I will say is, you know, the economics of cloud are complicated and they're still changing and still emerging, so I think that's probably more of a reaction to how dynamic the environment is then kind of a long-term trend. I mean, admittedly for us we hope that, you know, a lot of that analysis and the data that's required and will be provided by our platform. So you can think about it as, you know, a digital or AI powered cloud economist. So I don't, I don't know, hopefully our customers can use the platform and get everything they need and they won't need to go out and hire a cloud economist. That sounds expensive. >> Well, I think one of the things that sounds like great opportunities to make that go away, where you don't have to waste a resource to go through the cost side. I want to get your thoughts on this. This comes up all the time, certainly on Twitter, I'm always riffing on it. It comes up on a lot of my interviews and private chats with people about their, their cloud architecture, spend can get out of control pretty quickly. And data is a big part of it. Moving data is always going to be... Especially Amazon and Google, moving data in and out of the cloud is great. Now with the edge, I just talked to Bill Vass at a Amazon web service. He's the VP of engineering. You can literally bring the cloud to the edge and all the clouds are going to be doing this, these edge hubs. So that's going to process data at the edge, but it's also going to open up more services, right? So, you know, it's complicated enough as it is, spend is getting out of control. And it's only seems to be getting out of control even more. How do you talk to customers? I'd want to not be afraid they want to jump in, but they also want to have a hedge. Yeah, what's your, what's your take on your story? >> I think there's a lot of debate right now as to whether or not, you know, moving to the cloud from a cost perspective is cost-effective or more costly. And there's a pretty healthy debate going on at the moment. I think that the reality is, you know, yes, the cloud makes it easier for you to take on new services and bring on new things, and that of course drives spend, but it also unlocks incredible possibilities. What we try to do is help organizations take advantage of those possibilities and kind of the capabilities of the cloud while managing spend, and it's a complex problem, but it's a solvable problem. So for us, we think that, you know the job of the cloud providers is to, you know, continue to innovate and continue to bring more and more capability to bear so that organizations can transform through technology, the job of the teams using that technologies is to really leverage those capabilities, to build and to innovate and to serve their customers. And what we want to do is enable them to do that in a cost-effective manner, and we believe, and we have data to prove that if you do public cloud, right, it's cheaper because you know, those, those organizations, you know, much like, you know, at the turn of the industrial revolution, factories used to have their own power plants because you couldn't effectively reliably and kind of cost-effectively generate power at scale. Obviously no one does that now. And I think with the cloud providers, that's the same thing. I mean, they're investing in proprietary hardware, tons of software, tons of automation. They're highly secure. You know, at the end of the day, they're going to always be able to provide a given capability at a lower cost point. Like, of course they need to make profit. So there's a bit of margin in there, but, you know, at the end of the day, we think that both the flexibility and capability of it combined with their ability to operate at scale gives you a better value proposition, especially if you do it right. And that's what we want to focus on is, you know, the answer is there. You just need the right data and the right intelligence to find it. >> Totally, I totally agree with you. In fact, I had a big debate with Martine Casada at Andreessen Horowitz about cloud repatriation, and he was calling his paradigm. Do you focus on the cost or the revenue? And obviously they have Dropbox, which is a big example of that, and I even interviewed the Zynga guys and they actually went back to Amazon, although they didn't report that, but I'm a big believer that if you can't get the new revenue, then you're in cosmos then, and there are the issues, but again, I don't want to go there right now. I'll talk about that another time, but I want to get your, I want to get the playbook, so first of all, I love what you do, I think it's an opportunity to take that heavy lifting away from customers around understanding cost optimization. A lot of people don't know how to do it. So take us through a playbook. What are some best practices that you guys have seen to help people figure this out? What do you say to somebody, help me, Michael, I'm in a world of hurt, what do I do? What's the playbook? Can you give some examples of day in the life? >> Sure, so I think, I think the first thing is know what you're spending money on which sounds obvious, but you know, there's cloud environments are complicated, especially at scale. There's hundreds of thousands of skews and lots of different usage patterns. And I think the first thing is understand what you're spending money on. Number two is understand what you're getting for that spend. So, you know, what value are you driving with that spend? And then number three is put the information in the hands of the people who can do something about it. And I think that is, is one of the things that we really focus on is, you know, we built our product from an engineering focus first. It was engineers solving the problem of understanding how to keep cloud costs in control. And so our whole principle is give the people, working with the technology, the data to make good decisions and give them the power to act on it. And so, you know, a lot of companies say, "Oh, we're spending more over here. Or maybe we should look at that." But, but what we believe is actually be specific, where are you spending money? Where exactly are you spending too much? And what should you do about that? And give that information to the people who can take action, which are the engineers. And then lastly make it important in the organization because there's a ton of competing priorities. And what we've found is that, you know, where there's leadership support there's results. And so I think if you do those four things, you know, results will follow. Now, obviously, you know, you need to understand specific utilization patterns and know what to do with different kinds of resources and all of that stuff is complicated, but there are certainly solutions out there. Ours included who helped you with that. So if you get the other four things, right, plus you have some help, you can keep it under control and actually not just keep it under control, but operate in an environment that's much cheaper than hosting all this technology yourself and much more flexible. >> That's a great point, I mean, the fact that you mentioned earlier, the engineering piece that is so true people I've talked to, you mean our experiences and it's pretty common. The DevOps team tends to get involved in things like making sure you're buying reserve instances or all kinds of ways to optimize patterns, and that's also an issue, right? I mean, first of all, it makes sense that they're doing it, but also engineering time is being spent on essentially accounting at that point. Demonstrates the shift, I'm not saying it's good or bad. I'm just saying that got to be realistic. It's a time sink for the engineering when they're not engineering accounting, or should they, this is a legit question, it's not so much they should or shouldn't, I mean, if you say to someone, "Hey, you're paid to build and write software and you're spending your time solving accounting problems." That's obviously a mismatch. But when you talk about SREs and DevOps, Michael, it's kind of what might not be a bad thing, right? I mean, so how do people react to that? Are they kind of scratching their head on the same way? Or are you guys the solution to that? >> Well, I think that at first they are, but for us, at least it's, you know, we don't want them trying to understand the intricacies of a savings plan or understanding kind of the different options for compute instances. What we want them to do is we give them all the information. So our approach is give them all the information. They need to quickly make a decision, let them make a decision, like push a button and then let the change happen automatically. So if you think about it, you know, the amount of time they spend is, is a minute. That's the goal because then we can use their expertise. So it's not a finance person or an accountant doing research and making decisions that may or may not make technical sense and then looping in a bunch of people and they all talk, and then all that, that kind of whole process it's now here is a data-driven observation and recommendation. You have context to say yes or no, if you push the button and then you say, yes, then, you know, the change happens. If you say, no, the system learns. >> It's building right into the pipeline and they're shifting left to security, it's the same concept. It's really a great thing. I really think you're onto something big.,I love this story. It's kind of one of those things where reality's there. Michael, we've got 30 seconds left. I want to get your thoughts to share what put a plug in for the company, what you guys are doing, what are you looking at higher? You got a 30 second plug, go plug the company, what do you got? >> Well, you know, we think that, you know, for any organization, big or small, trying to make the most of the public cloud and be cloud first, you know, we, we bring a unique set of expertise, automation, and technology capabilities to bear, to help them thrive in the cloud and make the most of it. So, you know, obviously we would love to work with any company that, that wants to be cloud first and fully embrace the public cloud. I think we've got all the tools to help them thrive. >> Yeah, and I think, I think the confluence of business logic technology engineering working together is a home run. It's only going to get more stronger, so congratulations. Thanks for coming on theCUBE. >> Thank you. >> Adam, back to you in the studio for more action, theCUBE is out, we'll see you later.

>> Hi, I'm Natalie Ehrlich and welcome to the AWS startup showcase presented by The Cube. We have an amazing lineup of great guests who will share their insights on the latest innovations and solutions and leveraging cloud scale data in AI, security and life sciences. And now we're joined by the co-founders and co-CEOs of The Cube, Dave Vellante and John Furrier. Thank you gentlemen for joining me. >> Hey Natalie. >> Hey Natalie. >> How are you doing. Hey John. >> Well, I'd love to get your insights here, let's kick it off and what are you looking forward to. >> Dave, I think one of the things that we've been doing on the cube for 11 years is looking at the signal in the marketplace. I wanted to focus on this because AI is cutting across all industries. So we're seeing that with cybersecurity and life sciences, it's the first time we've had a life sciences track in the showcase, which is amazing because it shows that growth of the cloud scale. So I'm super excited by that. And I think that's going to showcase some new business models and of course the keynotes Ali Ghodsi, who's the CEO Data bricks pushing a billion dollars in revenue, clear validation that startups can go from zero to a billion dollars in revenues. So that should be really interesting. And of course the top venture capitalists coming in to talk about what the enterprise dynamics are all about. And what about you, Dave? >> You know, I thought it was an interesting mix and choice of startups. When you think about, you know, AI security and healthcare, and I've been thinking about that. Healthcare is the perfect industry, it is ripe for disruption. If you think about healthcare, you know, we all complain how expensive it is not transparent. There's a lot of discussion about, you know, can everybody have equal access that certainly with COVID the staff is burned out. There's a real divergence and diversity of the quality of healthcare and you know, it all results in patients not being happy, and I mean, if you had to do an NPS score on the patients and healthcare will be pretty low, John, you know. So when I think about, you know, AI and security in the context of healthcare in cloud, I ask questions like when are machines going to be able to better meet or make better diagnoses than doctors? And that's starting. I mean, it's really in assistance putting into play today. But I think when you think about cheaper and more accurate image analysis, when you think about the overall patient experience and trust and personalized medicine, self-service, you know, remote medicine that we've seen during the COVID pandemic, disease tracking, language translation, I mean, there are so many things where the cloud and data, and then it can help. And then at the end of it, it's all about, okay, how do I authenticate? How do I deal with privacy and personal information and tamper resistance? And that's where the security play comes in. So it's a very interesting mix of startups. I think that I'm really looking forward to hearing from... >> You know Natalie one of the things we talked about, some of these companies, Dave, we've talked a lot of these companies and to me the business model innovations that are coming out of two factors, the pandemic is kind of coming to an end so that accelerated and really showed who had the right stuff in my opinion. So you were either on the wrong side or right side of history when it comes to the pandemic and as we look back, as we come out of it with clear growth in certain companies and certain companies that adopted let's say cloud. And the other one is cloud scale. So the focus of these startup showcases is really to focus on how startups can align with the enterprise buyers and create the new kind of refactoring business models to go from, you know, a re-pivot or refactoring to more value. And the other thing that's interesting is that the business model isn't just for the good guys. If you look at say ransomware, for instance, the business model of hackers is gone completely amazing too. They're kicking it but in terms of revenue, they have their own they're well-funded machines on how to extort cash from companies. So there's a lot of security issues around the business model as well. So to me, the business model innovation with cloud-scale tech, with the pandemic forcing function, you've seen a lot of new kinds of decision-making in enterprises. You seeing how enterprise buyers are changing their decision criteria, and frankly their existing suppliers. So if you're an old guard supplier, you're going to be potentially out because if you didn't deliver during the pandemic, this is the issue that everyone's talking about. And it's kind of not publicized in the press very much, but this is actually happening. >> Well thank you both very much for joining me to kick off our AWS startup showcase. Now we're going to go to our very special guest Ali Ghodsi and John Furrier will seat with him for a fireside chat and Dave and I will see you on the other side. >> Okay, Ali great to see you. Thanks for coming on our AWS startup showcase, our second edition, second batch, season two, whatever we want to call it it's our second version of this new series where we feature, you know, the hottest startups coming out of the AWS ecosystem. And you're one of them, I've been there, but you're not a startup anymore, you're here pushing serious success on the revenue side and company. Congratulations and great to see you. >> Likewise. Thank you so much, good to see you again. >> You know I remember the first time we chatted on The Cube, you weren't really doing much software revenue, you were really talking about the new revolution in data. And you were all in on cloud. And I will say that from day one, you were always adamant that it was cloud cloud scale before anyone was really talking about it. And at that time it was on premises with Hadoop and those kinds of things. You saw that early. I remember that conversation, boy, that bet paid out great. So congratulations. >> Thank you so much. >> So I've got to ask you to jump right in. Enterprises are making decisions differently now and you are an example of that company that has gone from literally zero software sales to pushing a billion dollars as it's being reported. Certainly the success of Data bricks has been written about, but what's not written about is the success of how you guys align with the changing criteria for the enterprise customer. Take us through that and these companies here are aligning the same thing and enterprises want to change. They want to be in the right side of history. What's the success formula? >> Yeah. I mean, basically what we always did was look a few years out, the how can we help these enterprises, future proof, what they're trying to achieve, right? They have, you know, 30 years of legacy software and, you know baggage, and they have compliance and regulations, how do we help them move to the future? So we try to identify those kinds of secular trends that we think are going to maybe you see them a little bit right now, cloud was one of them, but it gets more and more and more. So we identified those and there were sort of three or four of those that we kind of latched onto. And then every year the passes, we're a little bit more right. Cause it's a secular trend in the market. And then eventually, it becomes a force that you can't kind of fight anymore. >> Yeah. And I just want to put a plug for your clubhouse talks with Andreessen Horowitz. You're always on clubhouse talking about, you know, I won't say the killer instinct, but being a CEO in a time where there's so much change going on, you're constantly under pressure. It's a lonely job at the top, I know that, but you've made some good calls. What was some of the key moments that you can point to, where you were like, okay, the wave is coming in now, we'd better get on it. What were some of those key decisions? Cause a lot of these startups want to be in your position, and a lot of buyers want to take advantage of the technology that's coming. They got to figure it out. What was some of those key inflection points for you? >> So if you're just listening to what everybody's saying, you're going to miss those trends. So then you're just going with the stream. So, Juan you mentioned that cloud. Cloud was a thing at the time, we thought it's going to be the thing that takes over everything. Today it's actually multi-cloud. So multi-cloud is a thing, it's more and more people are thinking, wow, I'm paying a lot's to the cloud vendors, do I want to buy more from them or do I want to have some optionality? So that's one. Two, open. They're worried about lock-in, you know, lock-in has happened for many, many decades. So they want open architectures, open source, open standards. So that's the second one that we bet on. The third one, which you know, initially wasn't sort of super obvious was AI and machine learning. Now it's super obvious, everybody's talking about it. But when we started, it was kind of called artificial intelligence referred to robotics, and machine learning wasn't a term that people really knew about. Today, it's sort of, everybody's doing machine learning and AI. So betting on those future trends, those secular trends as we call them super critical. >> And one of the things that I want to get your thoughts on is this idea of re-platforming versus refactoring. You see a lot being talked about in some of these, what does that even mean? It's people trying to figure that out. Re-platforming I get the cloud scale. But as you look at the cloud benefits, what do you say to customers out there and enterprises that are trying to use the benefits of the cloud? Say data for instance, in the middle of how could they be thinking about refactoring? And how can they make a better selection on suppliers? I mean, how do you know it used to be RFP, you deliver these speeds and feeds and you get selected. Now I think there's a little bit different science and methodology behind it. What's your thoughts on this refactoring as a buyer? What do I got to do? >> Well, I mean let's start with you said RFP and so on. Times have changed. Back in the day, you had to kind of sign up for something and then much later you're going to get it. So then you have to go through this arduous process. In the cloud, would pay us to go model elasticity and so on. You can kind of try your way to it. You can try before you buy. And you can use more and more. You can gradually, you don't need to go in all in and you know, say we commit to 50,000,000 and six months later to find out that wow, this stuff has got shelf where it doesn't work. So that's one thing that has changed it's beneficial. But the second thing is, don't just mimic what you had on prem in the cloud. So that's what this refactoring is about. If you had, you know, Hadoop data lake, now you're just going to have an S3 data lake. If you had an on-prem data warehouse now you just going to have a cloud data warehouse. You're just repeating what you did on prem in the cloud, architected for the future. And you know, for us, the most important thing that we say is that this lake house paradigm is a cloud native way of organizing your data. That's different from how you would do things on premises. So think through what's the right way of doing it in the cloud. Don't just try to copy paste what you had on premises in the cloud. >> It's interesting one of the things that we're observing and I'd love to get your reaction to this. Dave a lot** and I have been reporting on it is, two personas in the enterprise are changing their organization. One is I call IT ops or there's an SRE role developing. And the data teams are being dismantled and being kind of sprinkled through into other teams is this notion of data, pipelining being part of workflows, not just the department. Are you seeing organizational shifts in how people are organizing their resources, their human resources to take advantage of say that the data problems that are need to being solved with machine learning and whatnot and cloud-scale? >> Yeah, absolutely. So you're right. SRE became a thing, lots of DevOps people. It was because when the cloud vendors launched their infrastructure as a service to stitch all these things together and get it all working you needed a lot of devOps people. But now things are maturing. So, you know, with vendors like Data bricks and other multi-cloud vendors, you can actually get much higher level services where you don't need to necessarily have lots of lots of DevOps people that are themselves trying to stitch together lots of services to make this work. So that's one trend. But secondly, you're seeing more data teams being sort of completely ubiquitous in these organizations. Before it used to be you have one data team and then we'll have data and AI and we'll be done. ' It's a one and done. But that's not how it works. That's not how Google, Facebook, Twitter did it, they had data throughout the organization. Every BU was empowered. It's sales, it's marketing, it's finance, it's engineering. So how do you embed all those data teams and make them actually run fast? And you know, there's this concept of a data mesh which is super important where you can actually decentralize and enable all these teams to focus on their domains and run super fast. And that's really enabled by this Lake house paradigm in the cloud that we're talking about. Where you're open, you're basing it on open standards. You have flexibility in the data types and how they're going to store their data. So you kind of provide a lot of that flexibility, but at the same time, you have sort of centralized governance for it. So absolutely things are changing in the market. >> Well, you're just the professor, the masterclass right here is amazing. Thanks for sharing that insight. You're always got to go out of date and that's why we have you on here. You're amazing, great resource for the community. Ransomware is a huge problem, it's now the government's focus. We're being attacked and we don't know where it's coming from. This business models around cyber that's expanding rapidly. There's real revenue behind it. There's a data problem. It's not just a security problem. So one of the themes in all of these startup showcases is data is ubiquitous in the value propositions. One of them is ransomware. What's your thoughts on ransomware? Is it a data problem? Does cloud help? Some are saying that cloud's got better security with ransomware, then say on premise. What's your vision of how you see this ransomware problem being addressed besides the government taking over? >> Yeah, that's a great question. Let me start by saying, you know, we're a data company, right? And if you say you're a data company, you might as well just said, we're a privacy company, right? It's like some people say, well, what do you think about privacy? Do you guys even do privacy? We're a data company. So yeah, we're a privacy company as well. Like you can't talk about data without talking about privacy. With every customer, with every enterprise. So that's obviously top of mind for us. I do think that in the cloud, security is much better because, you know, vendors like us, we're investing so much resources into security and making sure that we harden the infrastructure and, you know, by actually having all of this infrastructure, we can monitor it, detect if something is, you know, an attack is happening, and we can immediately sort of stop it. So that's different from when it's on prem, you have kind of like the separated duties where the software vendor, which would have been us, doesn't really see what's happening in the data center. So, you know, there's an IT team that didn't develop the software is responsible for the security. So I think things are much better now. I think we're much better set up, but of course, things like cryptocurrencies and so on are making it easier for people to sort of hide. There decentralized networks. So, you know, the attackers are getting more and more sophisticated as well. So that's definitely something that's super important. It's super top of mind. We're all investing heavily into security and privacy because, you know, that's going to be super critical going forward. >> Yeah, we got to move that red line, and figure that out and get more intelligence. Decentralized trends not going away it's going to be more of that, less of the centralized. But centralized does come into play with data. It's a mix, it's not mutually exclusive. And I'll get your thoughts on this. Architectural question with, you know, 5G and the edge coming. Amazon's got that outpost stringent, the wavelength, you're seeing mobile world Congress coming up in this month. The focus on processing data at the edge is a huge issue. And enterprises are now going to be commercial part of that. So architecture decisions are being made in enterprises right now. And this is a big issue. So you mentioned multi-cloud, so tools versus platforms. Now I'm an enterprise buyer and there's no more RFPs. I got all this new choices for startups and growing companies to choose from that are cloud native. I got all kinds of new challenges and opportunities. How do I build my architecture so I don't foreclose a future opportunity. >> Yeah, as I said, look, you're actually right. Cloud is becoming even more and more something that everybody's adopting, but at the same time, there is this thing that the edge is also more and more important. And the connectivity between those two and making sure that you can really do that efficiently. My ask from enterprises, and I think this is top of mind for all the enterprise architects is, choose open because that way you can avoid locking yourself in. So that's one thing that's really, really important. In the past, you know, all these vendors that locked you in, and then you try to move off of them, they were highly innovative back in the day. In the 80's and the 90's, there were the best companies. You gave them all your data and it was fantastic. But then because you were locked in, they didn't need to innovate anymore. And you know, they focused on margins instead. And then over time, the innovation stopped and now you were kind of locked in. So I think openness is really important. I think preserving optionality with multi-cloud because we see the different clouds have different strengths and weaknesses and it changes over time. All right. Early on AWS was the only game that either showed up with much better security, active directory, and so on. Now Google with AI capabilities, which one's going to win, which one's going to be better. Actually, probably all three are going to be around. So having that optionality that you can pick between the three and then artificial intelligence. I think that's going to be the key to the future. You know, you asked about security earlier. That's how people detect zero day attacks, right? You ask about the edge, same thing there, that's where the predictions are going to happen. So make sure that you invest in AI and artificial intelligence very early on because it's not something you can just bolt on later on and have a little data team somewhere that then now you have AI and it's one and done. >> All right. Great insight. I've got to ask you, the folks may or may not know, but you're a professor at Berkeley as well, done a lot of great work. That's where you kind of came out of when Data bricks was formed. And the Berkeley basically was it invented distributed computing back in the 80's. I remember I was breaking in when Unix was proprietary, when software wasn't open you actually had the deal that under the table to get code. Now it's all open. Isn't the internet now with distributed computing and how interconnects are happening. I mean, the internet didn't break during the pandemic, which proves the benefit of the internet. And that's a positive. But as you start seeing edge, it's essentially distributed computing. So I got to ask you from a computer science standpoint. What do you see as the key learnings or connect the dots for how this distributed model will work? I see hybrids clearly, hybrid cloud is clearly the operating model but if you take it to the next level of distributed computing, what are some of the key things that you look for in the next five years as this starts to be completely interoperable, obviously software is going to drive a lot of it. What's your vision on that? >> Yeah, I mean, you know, so Berkeley, you're right for the gigs, you know, there was a now project 20, 30 years ago that basically is how we do things. There was a project on how you search in the very early on with Inktomi that became how Google and everybody else to search today. So workday was super, super early, sometimes way too early. And that was actually the mistake. Was that they were so early that people said that that stuff doesn't work. And then 20 years later you were invented. So I think 2009, Berkeley published just above the clouds saying the cloud is the future. At that time, most industry leaders said, that's just, you know, that doesn't work. Today, recently they published a research paper called, Sky Computing. So sky computing is what you get above the clouds, right? So we have the cloud as the future, the next level after that is the sky. That's one on top of them. That's what multi-cloud is. So that's a lot of the research at Berkeley, you know, into distributed systems labs is about this. And we're excited about that. Then we're one of the sky computing vendors out there. So I think you're going to see much more innovation happening at the sky level than at the compute level where you needed all those DevOps and SRE people to like, you know, build everything manually themselves. I can just see the memes now coming Ali, sky net, star track. You've got space too, by the way, space is another frontier that is seeing a lot of action going on because now the surface area of data with satellites is huge. So again, I know you guys are doing a lot of business with folks in that vertical where you starting to see real time data acquisition coming from these satellites. What's your take on the whole space as the, not the final frontier, but certainly as a new congested and contested space for, for data? >> Well, I mean, as a data vendor, we see a lot of, you know, alternative data sources coming in and people aren't using machine learning< AI to eat out signal out of the, you know, massive amounts of imagery that's coming out of these satellites. So that's actually a pretty common in FinTech, which is a vertical for us. And also sort of in the public sector, lots of, lots of, lots of satellites, imagery data that's coming. And these are massive volumes. I mean, it's like huge data sets and it's a super, super exciting what they can do. Like, you know, extracting signal from the satellite imagery is, and you know, being able to handle that amount of data, it's a challenge for all the companies that we work with. So we're excited about that too. I mean, definitely that's a trend that's going to continue. >> All right. I'm super excited for you. And thanks for coming on The Cube here for our keynote. I got to ask you a final question. As you think about the future, I see your company has achieved great success in a very short time, and again, you guys done the work, I've been following your company as you know. We've been been breaking that Data bricks story for a long time. I've been excited by it, but now what's changed. You got to start thinking about the next 20 miles stair when you look at, you know, the sky computing, you're thinking about these new architectures. As the CEO, your job is to one, not run out of money which you don't have to worry about that anymore, so hiring. And then, you got to figure out that next 20 miles stair as a company. What's that going on in your mind? Take us through your mindset of what's next. And what do you see out in that landscape? >> Yeah, so what I mentioned around Sky company optionality around multi-cloud, you're going to see a lot of capabilities around that. Like how do you get multi-cloud disaster recovery? How do you leverage the best of all the clouds while at the same time not having to just pick one? So there's a lot of innovation there that, you know, we haven't announced yet, but you're going to see a lot of it over the next many years. Things that you can do when you have the optionality across the different parts. And the second thing that's really exciting for us is bringing AI to the masses. Democratizing data and AI. So how can you actually apply machine learning to machine learning? How can you automate machine learning? Today machine learning is still quite complicated and it's pretty advanced. It's not going to be that way 10 years from now. It's going to be very simple. Everybody's going to have it at their fingertips. So how do we apply machine learning to machine learning? It's called auto ML, automatic, you know, machine learning. So that's an area, and that's not something that can be done with, right? But the goal is to eventually be able to automate a way the whole machine learning engineer and the machine learning data scientist altogether. >> You know it's really fun and talking with you is that, you know, for years we've been talking about this inside the ropes, inside the industry, around the future. Now people starting to get some visibility, the pandemics forced that. You seeing the bad projects being exposed. It's like the tide pulled out and you see all the scabs and bad projects that were justified old guard technologies. If you get it right you're on a good wave. And this is clearly what we're seeing. And you guys example of that. So as enterprises realize this, that they're going to have to look double down on the right projects and probably trash the bad projects, new criteria, how should people be thinking about buying? Because again, we talked about the RFP before. I want to kind of circle back because this is something that people are trying to figure out. You seeing, you know, organic, you come in freemium models as cloud scale becomes the advantage in the lock-in frankly seems to be the value proposition. The more value you provide, the more lock-in you get. Which sounds like that's the way it should be versus proprietary, you know, protocols. The protocol is value. How should enterprises organize their teams? Is it end to end workflows? Is it, and how should they evaluate the criteria for these technologies that they want to buy? >> Yeah, that's a great question. So I, you know, it's very simple, try to future proof your decision-making. Make sure that whatever you're doing is not blocking your in. So whatever decision you're making, what if the world changes in five years, make sure that if you making a mistake now, that's not going to bite you in about five years later. So how do you do that? Well, open source is great. If you're leveraging open-source, you can try it out already. You don't even need to talk to any vendor. Your teams can already download it and try it out and get some value out of it. If you're in the cloud, this pay as you go models, you don't have to do a big RFP and commit big. You can try it, pay the vendor, pay as you go, $10, $15. It doesn't need to be a million dollar contract and slowly grow as you're providing value. And then make sure that you're not just locking yourself in to one cloud or, you know, one particular vendor. As much as possible preserve your optionality because then that's not a one-way door. If it turns out later you want to do something else, you can, you know, pick other things as well. You're not locked in. So that's what I would say. Keep that top of mind that you're not locking yourself into a particular decision that you made today, that you might regret in five years. >> I really appreciate you coming on and sharing your with our community and The Cube. And as always great to see you. I really enjoy your clubhouse talks, and I really appreciate how you give back to the community. And I want to thank you for coming on and taking the time with us today. >> Thanks John, always appreciate talking to you. >> Okay Ali Ghodsi, CEO of Data bricks, a success story that proves the validation of cloud scale, open and create value, values the new lock-in. So Natalie, back to you for continuing coverage. >> That was a terrific interview John, but I'd love to get Dave's insights first. What were your takeaways, Dave? >> Well, if we have more time I'll tell you how Data bricks got to where they are today, but I'll say this, the most important thing to me that Allie said was he conveyed a very clear understanding of what data companies are outright and are getting ready. Talked about four things. There's not one data team, there's many data teams. And he talked about data is decentralized, and data has to have context and that context lives in the business. He said, look, think about it. The way that the data companies would get it right, they get data in teams and sales and marketing and finance and engineering. They all have their own data and data teams. And he referred to that as a data mesh. That's a term that is your mock, the Gany coined and the warehouse of the data lake it's merely a node in that global message. It meshes discoverable, he talked about federated governance, and Data bricks, they're breaking the model of shoving everything into a single repository and trying to make that the so-called single version of the truth. Rather what they're doing, which is right on is putting data in the hands of the business owners. And that's how true data companies do. And the last thing you talked about with sky computing, which I loved, it's that future layer, we talked about multi-cloud a lot that abstracts the underlying complexity of the technical details of the cloud and creates additional value on top. I always say that the cloud players like Amazon have given the gift to the world of 100 billion dollars a year they spend in CapEx. Thank you. Now we're going to innovate on top of it. Yeah. And I think the refactoring... >> Hope by John. >> That was great insight and I totally agree. The refactoring piece too was key, he brought that home. But to me, I think Data bricks that Ali shared there and why he's been open and sharing a lot of his insights and the community. But what he's not saying, cause he's humble and polite is they cracked the code on the enterprise, Dave. And to Dave's points exactly reason why they did it, they saw an opportunity to make it easier, at that time had dupe was the rage, and they just made it easier. They was smart, they made good bets, they had a good formula and they cracked the code with the enterprise. They brought it in and they brought value. And see that's the key to the cloud as Dave pointed out. You get replatform with the cloud, then you refactor. And I think he pointed out the multi-cloud and that really kind of teases out the whole future and landscape, which is essentially distributed computing. And I think, you know, companies are starting to figure that out with hybrid and this on premises and now super edge I call it, with 5G coming. So it's just pretty incredible. >> Yeah. Data bricks, IPO is coming and people should know. I mean, what everybody, they created spark as you know John and everybody thought they were going to do is mimic red hat and sell subscriptions and support. They didn't, they developed a managed service and they embedded AI tools to simplify data science. So to your point, enterprises could buy instead of build, we know this. Enterprises will spend money to make things simpler. They don't have the resources, and so this was what they got right was really embedding that, making a building a managed service, not mimicking the kind of the red hat model, but actually creating a new value layer there. And that's big part of their success. >> If I could just add one thing Natalie to that Dave saying is really right on. And as an enterprise buyer, if we go the other side of the equation, it used to be that you had to be a known company, get PR, you fill out RFPs, you had to meet all the speeds. It's like going to the airport and get a swab test, and get a COVID test and all kinds of mechanisms to like block you and filter you. Most of the biggest success stories that have created the most value for enterprises have been the companies that nobody's understood. And Andy Jazz's famous quote of, you know, being misunderstood is actually a good thing. Data bricks was very misunderstood at the beginning and no one kind of knew who they were but they did it right. And so the enterprise buyers out there, don't be afraid to test the startups because you know the next Data bricks is out there. And I think that's where I see the psychology changing from the old IT buyers, Dave. It's like, okay, let's let's test this company. And there's plenty of ways to do that. He illuminated those premium, small pilots, you don't need to go on these big things. So I think that is going to be a shift in how companies going to evaluate startups. >> Yeah. Think about it this way. Why should the large banks and insurance companies and big manufacturers and pharma companies, governments, why should they burn resources managing containers and figuring out data science tools if they can just tap into solutions like Data bricks which is an AI platform in the cloud and let the experts manage all that stuff. Think about how much money in time that saves enterprises. >> Yeah, I mean, we've got 15 companies here we're showcasing this batch and this season if you call it. That episode we are going to call it? They're awesome. Right? And the next 15 will be the same. And these companies could be the next billion dollar revenue generator because the cloud enables that day. I think that's the exciting part. >> Well thank you both so much for these insights. Really appreciate it. AWS startup showcase highlights the innovation that helps startups succeed. And no one knows that better than our very next guest, Jeff Barr. Welcome to the show and I will send this interview now to Dave and John and see you just in the bit. >> Okay, hey Jeff, great to see you. Thanks for coming on again. >> Great to be back. >> So this is a regular community segment with Jeff Barr who's a legend in the industry. Everyone knows your name. Everyone knows that. Congratulations on your recent blog posts we have reading. Tons of news, I want to get your update because 5G has been all over the news, mobile world congress is right around the corner. I know Bill Vass was a keynote out there, virtual keynote. There's a lot of Amazon discussion around the edge with wavelength. Specifically, this is the outpost piece. And I know there is news I want to get to, but the top of mind is there's massive Amazon expansion and the cloud is going to the edge, it's here. What's up with wavelength. Take us through the, I call it the power edge, the super edge. >> Well, I'm really excited about this mostly because it gives a lot more choice and flexibility and options to our customers. This idea that with wavelength we announced quite some time ago, at least quite some time ago if we think in cloud years. We announced that we would be working with 5G providers all over the world to basically put AWS in the telecom providers data centers or telecom centers, so that as their customers build apps, that those apps would take advantage of the low latency, the high bandwidth, the reliability of 5G, be able to get to some compute and storage services that are incredibly close geographically and latency wise to the compute and storage that is just going to give customers this new power and say, well, what are the cool things we can build? >> Do you see any correlation between wavelength and some of the early Amazon services? Because to me, my gut feels like there's so much headroom there. I mean, I was just riffing on the notion of low latency packets. I mean, just think about the applications, gaming and VR, and metaverse kind of cool stuff like that where having the edge be that how much power there. It just feels like a new, it feels like a new AWS. I mean, what's your take? You've seen the evolutions and the growth of a lot of the key services. Like EC2 and SA3. >> So welcome to my life. And so to me, the way I always think about this is it's like when I go to a home improvement store and I wander through the aisles and I often wonder through with no particular thing that I actually need, but I just go there and say, wow, they've got this and they've got this, they've got this other interesting thing. And I just let my creativity run wild. And instead of trying to solve a problem, I'm saying, well, if I had these different parts, well, what could I actually build with them? And I really think that this breadth of different services and locations and options and communication technologies. I suspect a lot of our customers and customers to be and are in this the same mode where they're saying, I've got all this awesomeness at my fingertips, what might I be able to do with it? >> He reminds me when Fry's was around in Palo Alto, that store is no longer here but it used to be back in the day when it was good. It was you go in and just kind of spend hours and then next thing you know, you built a compute. Like what, I didn't come in here, whether it gets some cables. Now I got a motherboard. >> I clearly remember Fry's and before that there was the weird stuff warehouse was another really cool place to hang out if you remember that. >> Yeah I do. >> I wonder if I could jump in and you guys talking about the edge and Jeff I wanted to ask you about something that is, I think people are starting to really understand and appreciate what you did with the entrepreneur acquisition, what you do with nitro and graviton, and really driving costs down, driving performance up. I mean, there's like a compute Renaissance. And I wonder if you could talk about the importance of that at the edge, because it's got to be low power, it has to be low cost. You got to be doing processing at the edge. What's your take on how that's evolving? >> Certainly so you're totally right that we started working with and then ultimately acquired Annapurna labs in Israel a couple of years ago. I've worked directly with those folks and it's really awesome to see what they've been able to do. Just really saying, let's look at all of these different aspects of building the cloud that were once effectively kind of somewhat software intensive and say, where does it make sense to actually design build fabricate, deploy custom Silicon? So from putting up the system to doing all kinds of additional kinds of security checks, to running local IO devices, running the NBME as fast as possible to support the EBS. Each of those things has been a contributing factor to not just the power of the hardware itself, but what I'm seeing and have seen for the last probably two or three years at this point is the pace of innovation on instance types just continues to get faster and faster. And it's not just cranking out new instance types because we can, it's because our awesomely diverse base of customers keeps coming to us and saying, well, we're happy with what we have so far, but here's this really interesting new use case. And we needed a different ratio of memory to CPU, or we need more cores based on the amount of memory, or we needed a lot of IO bandwidth. And having that nitro as the base lets us really, I don't want to say plug and play, cause I haven't actually built this myself, but it seems like they can actually put the different elements together, very very quickly and then come up with new instance types that just our customers say, yeah, that's exactly what I asked for and be able to just do this entire range of from like micro and nano sized all the way up to incredibly large with incredible just to me like, when we talk about terabytes of memory that are just like actually just RAM memory. It's like, that's just an inconceivably large number by the standards of where I started out in my career. So it's all putting this power in customer hands. >> You used the term plug and play, but it does give you that nitro gives you that optionality. And then other thing that to me is really exciting is the way in which ISVs are writing to whatever's underneath. So you're making that, you know, transparent to the users so I can choose as a customer, the best price performance for my workload and that that's just going to grow that ISV portfolio. >> I think it's really important to be accurate and detailed and as thorough as possible as we launch each one of these new instance types with like what kind of processor is in there and what clock speed does it run at? What kind of, you know, how much memory do we have? What are the, just the ins and outs, and is it Intel or arm or AMD based? It's such an interesting to me contrast. I can still remember back in the very very early days of back, you know, going back almost 15 years at this point and effectively everybody said, well, not everybody. A few people looked and said, yeah, we kind of get the value here. Some people said, this just sounds like a bunch of generic hardware, just kind of generic hardware in Iraq. And even back then it was something that we were very careful with to design and optimize for use cases. But this idea that is generic is so, so, so incredibly inaccurate that I think people are now getting this. And it's okay. It's fine too, not just for the cloud, but for very specific kinds of workloads and use cases. >> And you guys have announced obviously the performance improvements on a lamb** does getting faster, you got the per billing, second billings on windows and SQL server on ECE too**. So I mean, obviously everyone kind of gets that, that's been your DNA, keep making it faster, cheaper, better, easier to use. But the other area I want to get your thoughts on because this is also more on the footprint side, is that the regions and local regions. So you've got more region news, take us through the update on the expansion on the footprint of AWS because you know, a startup can come in and these 15 companies that are here, they're global with AWS, right? So this is a major benefit for customers around the world. And you know, Ali from Data bricks mentioned privacy. Everyone's a privacy company now. So the huge issue, take us through the news on the region. >> Sure, so the two most recent regions that we announced are in the UAE and in Israel. And we generally like to pre-announce these anywhere from six months to two years at a time because we do know that the customers want to start making longer term plans to where they can start thinking about where they can do their computing, where they can store their data. I think at this point we now have seven regions under construction. And, again it's all about customer trice. Sometimes it's because they have very specific reasons where for based on local laws, based on national laws, that they must compute and restore within a particular geographic area. Other times I say, well, a lot of our customers are in this part of the world. Why don't we pick a region that is as close to that part of the world as possible. And one really important thing that I always like to remind our customers of in my audience is, anything that you choose to put in a region, stays in that region unless you very explicitly take an action that says I'd like to replicate it somewhere else. So if someone says, I want to store data in the US, or I want to store it in Frankfurt, or I want to store it in Sao Paulo, or I want to store it in Tokyo or Osaka. They get to make that very specific choice. We give them a lot of tools to help copy and replicate and do cross region operations of various sorts. But at the heart, the customer gets to choose those locations. And that in the early days I think there was this weird sense that you would, you'd put things in the cloud that would just mysteriously just kind of propagate all over the world. That's never been true, and we're very very clear on that. And I just always like to reinforce that point. >> That's great stuff, Jeff. Great to have you on again as a regular update here, just for the folks watching and don't know Jeff he'd been blogging and sharing. He'd been the one man media band for Amazon it's early days. Now he's got departments, he's got peoples on doing videos. It's an immediate franchise in and of itself, but without your rough days we wouldn't have gotten all the great news we subscribe to. We watch all the blog posts. It's essentially the flow coming out of AWS which is just a tsunami of a new announcements. Always great to read, must read. Jeff, thanks for coming on, really appreciate it. That's great. >> Thank you John, great to catch up as always. >> Jeff Barr with AWS again, and follow his stuff. He's got a great audience and community. They talk back, they collaborate and they're highly engaged. So check out Jeff's blog and his social presence. All right, Natalie, back to you for more coverage. >> Terrific. Well, did you guys know that Jeff took a three week AWS road trip across 15 cities in America to meet with cloud computing enthusiasts? 5,500 miles he drove, really incredible I didn't realize that. Let's unpack that interview though. What stood out to you John? >> I think Jeff, Barr's an example of what I call direct to audience a business model. He's been doing it from the beginning and I've been following his career. I remember back in the day when Amazon was started, he was always building stuff. He's a builder, he's classic. And he's been there from the beginning. At the beginning he was just the blog and it became a huge audience. It's now morphed into, he was power blogging so hard. He has now support and he still does it now. It's basically the conduit for information coming out of Amazon. I think Jeff has single-handedly made Amazon so successful at the community developer level, and that's the startup action happened and that got them going. And I think he deserves a lot of the success for AWS. >> And Dave, how about you? What is your reaction? >> Well I think you know, and everybody knows about the cloud and back stop X** and agility, and you know, eliminating the undifferentiated, heavy lifting and all that stuff. And one of the things that's often overlooked which is why I'm excited to be part of this program is the innovation. And the innovation comes from startups, and startups start in the cloud. And so I think that that's part of the flywheel effect. You just don't see a lot of startups these days saying, okay, I'm going to do something that's outside of the cloud. There are some, but for the most part, you know, if you saw in software, you're starting in the cloud, it's so capital efficient. I think that's one thing, I've throughout my career. I've been obsessed with every part of the stack from whether it's, you know, close to the business process with the applications. And right now I'm really obsessed with the plumbing, which is why I was excited to talk about, you know, the Annapurna acquisition. Amazon bought and a part of the $350 million, it's reported, you know, maybe a little bit more, but that isn't an amazing acquisition. And the reason why that's so important is because Amazon is continuing to drive costs down, drive performance up. And in my opinion, leaving a lot of the traditional players in their dust, especially when it comes to the power and cooling. You have often overlooked things. And the other piece of the interview was that Amazon is actually getting ISVs to write to these new platforms so that you don't have to worry about there's the software run on this chip or that chip, or x86 or arm or whatever it is. It runs. And so I can choose the best price performance. And that's where people don't, they misunderstand, you always say it John, just said that people are misunderstood. I think they misunderstand, they confused, you know, the price of the cloud with the cost of the cloud. They ignore all the labor costs that are associated with that. And so, you know, there's a lot of discussion now about the cloud tax. I just think the pace is accelerating. The gap is not closing, it's widening. >> If you look at the one question I asked them about wavelength and I had a follow up there when I said, you know, we riff on it and you see, he lit up like he beam was beaming because he said something interesting. It's not that there's a problem to solve at this opportunity. And he conveyed it to like I said, walking through Fry's. But like, you go into a store and he's a builder. So he sees opportunity. And this comes back down to the Martine Casada paradox posts he wrote about do you optimize for CapEx or future revenue? And I think the tell sign is at the wavelength edge piece is going to be so creative and that's going to open up massive opportunities. I think that's the place to watch. That's the place I'm watching. And I think startups going to come out of the woodwork because that's where the action will be. And that's just Amazon at the edge, I mean, that's just cloud at the edge. I think that is going to be very effective. And his that's a little TeleSign, he kind of revealed a little bit there, a lot there with that comment. >> Well that's a to be continued conversation. >> Indeed, I would love to introduce our next guest. We actually have Soma on the line. He's the managing director at Madrona venture group. Thank you Soma very much for coming for our keynote program. >> Thank you Natalie and I'm great to be here and will have the opportunity to spend some time with you all. >> Well, you have a long to nerd history in the enterprise. How would you define the modern enterprise also known as cloud scale? >> Yeah, so I would say I have, first of all, like, you know, we've all heard this now for the last, you know, say 10 years or so. Like, software is eating the world. Okay. Put it another way, we think about like, hey, every enterprise is a software company first and foremost. Okay. And companies that truly internalize that, that truly think about that, and truly act that way are going to start up, continue running well and things that don't internalize that, and don't do that are going to be left behind sooner than later. Right. And the last few years you start off thing and not take it to the next level and talk about like, not every enterprise is not going through a digital transformation. Okay. So when you sort of think about the world from that lens. Okay. Modern enterprise has to think about like, and I am first and foremost, a technology company. I may be in the business of making a car art, you know, manufacturing paper, or like you know, manufacturing some healthcare products or what have you got out there. But technology and software is what is going to give me a unique, differentiated advantage that's going to let me do what I need to do for my customers in the best possible way [Indistinct]. So that sort of level of focus, level of execution, has to be there in a modern enterprise. The other thing is like not every modern enterprise needs to think about regular. I'm competing for talent, not anymore with my peers in my industry. I'm competing for technology talent and software talent with the top five technology companies in the world. Whether it is Amazon or Facebook or Microsoft or Google, or what have you cannot think, right? So you really have to have that mindset, and then everything flows from that. >> So I got to ask you on the enterprise side again, you've seen many ways of innovation. You've got, you know, been in the industry for many, many years. The old way was enterprises want the best proven product and the startups want that lucrative contract. Right? Yeah. And get that beach in. And it used to be, and we addressed this in our earlier keynote with Ali and how it's changing, the buyers are changing because the cloud has enabled this new kind of execution. I call it agile, call it what you want. Developers are driving modern applications, so enterprises are still, there's no, the playbooks evolving. Right? So we see that with the pandemic, people had needs, urgent needs, and they tried new stuff and it worked. The parachute opened as they say. So how do you look at this as you look at stars, you're investing in and you're coaching them. What's the playbook? What's the secret sauce of how to crack the enterprise code today. And if you're an enterprise buyer, what do I need to do? I want to be more agile. Is there a clear path? Is there's a TSA to let stuff go through faster? I mean, what is the modern playbook for buying and being a supplier? >> That's a fantastic question, John, because I think that sort of playbook is changing, even as we speak here currently. A couple of key things to understand first of all is like, you know, decision-making inside an enterprise is getting more and more de-centralized. Particularly decisions around what technology to use and what solutions to use to be able to do what people need to do. That decision making is no longer sort of, you know, all done like the CEO's office or the CTO's office kind of thing. Developers are more and more like you rightly said, like sort of the central of the workflow and the decision making process. So it'll be who both the enterprises, as well as the startups to really understand that. So what does it mean now from a startup perspective, from a startup perspective, it means like, right. In addition to thinking about like hey, not do I go create an enterprise sales post, do I sell to the enterprise like what I might have done in the past? Is that the best way of moving forward, or should I be thinking about a product led growth go to market initiative? You know, build a product that is easy to use, that made self serve really works, you know, get the developers to start using to see the value to fall in love with the product and then you think about like hey, how do I go translate that into a contract with enterprise. Right? And more and more what I call particularly, you know, startups and technology companies that are focused on the developer audience are thinking about like, you know, how do I have a bottom up go to market motion? And sometime I may sort of, you know, overlap that with the top down enterprise sales motion that we know that has been going on for many, many years or decades kind of thing. But really this product led growth bottom up a go to market motion is something that we are seeing on the rise. I would say they're going to have more than half the startup that we come across today, have that in some way shape or form. And so the enterprise also needs to understand this, the CIO or the CTO needs to know that like hey, I'm not decision-making is getting de-centralized. I need to empower my engineers and my engineering managers and my engineering leaders to be able to make the right decision and trust them. I'm going to give them some guard rails so that I don't find myself in a soup, you know, sometime down the road. But once I give them the guard rails, I'm going to enable people to make the decisions. People who are closer to the problem, to make the right decision. >> Well Soma, what are some of the ways that startups can accelerate their enterprise penetration? >> I think that's another good question. First of all, you need to think about like, Hey, what are enterprises wanting to rec? Okay. If you start off take like two steps back and think about what the enterprise is really think about it going. I'm a software company, but I'm really manufacturing paper. What do I do? Right? The core thing that most enterprises care about is like, hey, how do I better engage with my customers? How do I better serve my customers? And how do I do it in the most optimal way? At the end of the day that's what like most enterprises really care about. So startups need to understand, what are the problems that the enterprise is trying to solve? What kind of tools and platform technologies and infrastructure support, and, you know, everything else that they need to be able to do what they need to do and what only they can do in the most optimal way. Right? So to the extent you are providing either a tool or platform or some technology that is going to enable your enterprise to make progress on what they want to do, you're going to get more traction within the enterprise. In other words, stop thinking about technology, and start thinking about the customer problem that they want to solve. And the more you anchor your company, and more you anchor your conversation with the customer around that, the more the enterprise is going to get excited about wanting to work with you. >> So I got to ask you on the enterprise and developer equation because CSOs and CXOs, depending who you talk to have that same answer. Oh yeah. In the 90's and 2000's, we kind of didn't, we throttled down, we were using the legacy developer tools and cloud came and then we had to rebuild and we didn't really know what to do. So you seeing a shift, and this is kind of been going on for at least the past five to eight years, a lot more developers being hired yet. I mean, at FinTech is clearly a vertical, they always had developers and everyone had developers, but there's a fast ramp up of developers now and the role of open source has changed. Just looking at the participation. They're not just consuming open source, open source is part of the business model for mainstream enterprises. How is this, first of all, do you agree? And if so, how has this changed the course of an enterprise human resource selection? How they're organized? What's your vision on that? >> Yeah. So as I mentioned earlier, John, in my mind the first thing is, and this sort of, you know, like you said financial services has always been sort of hiring people [Indistinct]. And this is like five-year old story. So bear with me I'll tell you the firewall story and then come to I was trying to, the cloud CIO or the Goldman Sachs. Okay. And this is five years ago when people were still like, hey, is this cloud thing real and now is cloud going to take over the world? You know, am I really ready to put my data in the cloud? So there are a lot of questions and conversations can affect. The CIO of Goldman Sachs told me two things that I remember to this day. One is, hey, we've got a internal edict. That we made a decision that in the next five years, everything in Goldman Sachs is going to be on the public law. And I literally jumped out of the chair and I said like now are you going to get there? And then he laughed and said like now it really doesn't matter whether we get there or not. We want to set the tone, set the direction for the organization that hey, public cloud is here. Public cloud is there. And we need to like, you know, move as fast as we realistically can and think about all the financial regulations and security and privacy. And all these things that we care about deeply. But given all of that, the world is going towards public load and we better be on the leading edge as opposed to the lagging edge. And the second thing he said, like we're talking about like hey, how are you hiring, you know, engineers at Goldman Sachs Canada? And he said like in hey, I sort of, my team goes out to the top 20 schools in the US. And the people we really compete with are, and he was saying this, Hey, we don't compete with JP Morgan or Morgan Stanley, or pick any of your favorite financial institutions. We really think about like, hey, we want to get the best talent into Goldman Sachs out of these schools. And we really compete head to head with Google. We compete head to head with Microsoft. We compete head to head with Facebook. And we know that the caliber of people that we want to get is no different than what these companies want. If you want to continue being a successful, leading it, you know, financial services player. That sort of tells you what's going on. You also talked a little bit about like hey, open source is here to stay. What does that really mean kind of thing. In my mind like now, you can tell me that I can have from given my pedigree at Microsoft, I can tell you that we were the first embraces of open source in this world. So I'll say that right off the bat. But having said that we did in our turn around and said like, hey, this open source is real, this open source is going to be great. How can we embrace and how can we participate? And you fast forward to today, like in a Microsoft is probably as good as open source as probably any other large company I would say. Right? Including like the work that the company has done in terms of acquiring GitHub and letting it stay true to its original promise of open source and community can I think, right? I think Microsoft has come a long way kind of thing. But the thing that like in all these enterprises need to think about is you want your developers to have access to the latest and greatest tools. To the latest and greatest that the software can provide. And you really don't want your engineers to be reinventing the wheel all the time. So there is something available in the open source world. Go ahead, please set up, think about whether that makes sense for you to use it. And likewise, if you think that is something you can contribute to the open source work, go ahead and do that. So it's really a two way somebody Arctic relationship that enterprises need to have, and they need to enable their developers to want to have that symbiotic relationship. >> Soma, fantastic insights. Thank you so much for joining our keynote program. >> Thank you Natalie and thank you John. It was always fun to chat with you guys. Thank you. >> Thank you. >> John we would love to get your quick insight on that. >> Well I think first of all, he's a prolific investor the great from Madrona venture partners, which is well known in the tech circles. They're in Seattle, which is in the hub of I call cloud city. You've got Amazon and Microsoft there. He'd been at Microsoft and he knows the developer ecosystem. And reason why I like his perspective is that he understands the value of having developers as a core competency in Microsoft. That's their DNA. You look at Microsoft, their number one thing from day one besides software was developers. That was their army, the thousand centurions that one won everything for them. That has shifted. And he brought up open source, and .net and how they've embraced Linux, but something that tele before he became CEO, we interviewed him in the cube at an Xcel partners event at Stanford. He was open before he was CEO. He was talking about opening up. They opened up a lot of their open source infrastructure projects to the open compute foundation early. So they had already had that going and at that price, since that time, the stock price of Microsoft has skyrocketed because as Ali said, open always wins. And I think that is what you see here, and as an investor now he's picking in startups and investing in them. He's got to read the tea leaves. He's got to be in the right side of history. So he brings a great perspective because he sees the old way and he understands the new way. That is the key for success we've seen in the enterprise and with the startups. The people who get the future, and can create the value are going to win. >> Yeah, really excellent point. And just really quickly. What do you think were some of our greatest hits on this hour of programming? >> Well first of all I'm really impressed that Ali took the time to come join us because I know he's super busy. I think they're at a $28 billion valuation now they're pushing a billion dollars in revenue, gap revenue. And again, just a few short years ago, they had zero software revenue. So of these 15 companies we're showcasing today, you know, there's a next Data bricks in there. They're all going to be successful. They already are successful. And they're all on this rocket ship trajectory. Ali is smart, he's also got the advantage of being part of that Berkeley community which they're early on a lot of things now. Being early means you're wrong a lot, but you're also right, and you're right big. So Berkeley and Stanford obviously big areas here in the bay area as research. He is smart, He's got a great team and he's really open. So having him share his best practices, I thought that was a great highlight. Of course, Jeff Barr highlighting some of the insights that he brings and honestly having a perspective of a VC. And we're going to have Peter Wagner from wing VC who's a classic enterprise investors, super smart. So he'll add some insight. Of course, one of the community session, whenever our influencers coming on, it's our beat coming on at the end, as well as Katie Drucker. Another Madrona person is going to talk about growth hacking, growth strategies, but yeah, sights Raleigh coming on. >> Terrific, well thank you so much for those insights and thank you to everyone who is watching the first hour of our live coverage of the AWS startup showcase for myself, Natalie Ehrlich, John, for your and Dave Vellante we want to thank you very much for watching and do stay tuned for more amazing content, as well as a special live segment that John Furrier is going to be hosting. It takes place at 12:30 PM Pacific time, and it's called cracking the code, lessons learned on how enterprise buyers evaluate new startups. Don't go anywhere.

(upbeat music) >> Welcome to this special cloud virtual event, theCUBE on cloud. This is our continuing editorial series of the most important stories in cloud. We're going to explore the cutting edge most relevant technologies and companies that will impact business and society. We have special guests from Jeff Barr, Michael Liebow, Jerry Chen, Ben Haynes, Michael skulk, Mike Feinstein from AWS all today are presenting the top startups in the AWS ecosystem. This is the AWS showcase of startups. I'm showing with Dave Vellante. Dave great to see you. >> Hey John. Great to be here. Thanks for having me. >> So awesome day today. We're going to feature a 10 grade companies amplitude, auto grid, big ID, cordial Dremio Kong, multicloud, Reltio stardog wire wheel, companies that we've talked to. We've researched. And they're going to present today from 10 for the rest of the day. What's your thoughts? >> Well, John, a lot of these companies were just sort of last decade, they really, were keyer kicker mode, experimentation mode. Now they're well on their way to hitting escape velocity which is very exciting. And they're hitting tens of millions dollars of ARR, many are planning IPO's and it's just it's really great to see what the cloud has enabled and we're going to dig into that very deeply today. So I'm super excited. >> Before we jump into the keynote (mumbles) our non Huff from AWS up on stage Jeremy is the brains behind this program that we're doing. We're going to do this quarterly. Jeremy great to see you, you're in the global startups program at AWS. Your job is to keep the crops growing, keep the startups going and keep the flow of innovation. Thanks for joining us. >> Yeah. Made it to startup showcase day. I'm super excited. And as you mentioned my team the global startup program team, we kind of provide white glove service for VC backed startups and help them with go to market activities. Co-selling with AWS and we've been looking for ways to highlight all the great work they're doing and partnering with you guys has been tremendous. You guys really know how to bring their stories to life. So super excited about all the partner sessions today. >> Well, I really appreciate the vision and working with Amazon this is like truly a bar raiser from theCUBE virtual perspective, using the virtual we can get more content, more flow and great to have you on and bring that the top hot startups around data, data ops. Certainly the most important story in tech is cloud scale with data. You you can't look around and seeing more innovation happening. So I really appreciate the work. Thanks for coming on. >> Yeah, and don't forget, we're making this a quarterly series. So the next one we've already been working on it. The next one is Wednesday, June 16th. So mark your calendars, but super excited to continue doing these showcases with you guys in the future. >> Thanks for coming on Jeremy. I really appreciate it,. Dave so I want to just quick quickly before we get Jeff up here, Jeff Barr who's a luminary guests for us this week who has been in the industry has been there from the beginning of AWS the role of data, and what's happened in cloud. And we've been watching the evolution of Amazon web services from the beginning, from the startup market to dominate in the enterprise. If you look at the top 10 enterprise companies Amazon wasn't on that list in 2010 they weren't even bringing the top 10 Andy Jassy's keynote at reinvent this past year. Highlighted that fact, I think they were number five or four as vendor in just AWS. So interesting to see that you've been reporting and doing a lot of analysis on the role of data. What's your analysis for these startups and as businesses need to embrace the new technologies and be on the right side of history not part of that old guard, incumbent failed model. >> Well, I think again, if you look back on the early days of cloud, it was really about storage and networking and compute infrastructure. And then we collected all this data and now you're seeing the next generation of innovation and value. We're going to talk to Michael Liebow about this is really if you look at all the value points in the leavers, it's all around data and data is going through a massive change in the way that we think about it, that we talk about it. And you hear that a lot. Obviously you talk about the volumes, the giant volumes but there's something else going on as AWS brings the cloud to the edge. And of course it looks at the data centers, just another edge device, data is getting highly decentralized. And what we're seeing is data getting into the hands of business owners and data product builders. I think we're going to see a new parlance emerge and that's where you're seeing the competitive advantage. And if you look at all the real winners these days in the marketplace especially in the digital with COVID, it all comes back to the data. And we're going to talk about that a lot today. >> One of the things that's coming up in all of our cube interviews, certainly we've seen, I mean we've had a great observation space across all the ecosystems, but the clear thing that's coming out of COVID is speed, agility, scale, and data. If you don't have that data you are going to be a non-player. And I think I heard some industry people talking about the future of how the stock market's going to work and that if you're not truly in market with an AI or machine learning data value play you probably will be shorted on the stock market or delisted. I think people are looking at that as a table stakes competitive advantage item, where if you don't have some sort of data competitive strategy you're going to be either delisted or sold short. And that's, I don't think delisted but the point is this table-stakes Dave. >> Well, I think too, I think the whole language the lingua franca of data is changing. We talk about data as an asset all the time, but you think about it now, what do we do with assets? We protect it, we hide it. And we kind of we don't share it. But then on the other hand, everybody talks about sharing the data and that is a huge trend in the marketplace. And so I think that everybody is really starting to rethink the whole concept of data, what it is, its value and how we think about it, talk about it, share it make it accessible, and at the same time, protect it and make it governed. And I think you're seeing, computational governance and automation really hidden. Couldn't do this without the cloud. I mean, that's the bottom line. >> Well, I'm super excited to have Jeff Barr here from AWS as our special keynote guests. I've been following Jeff's career for a long, long time. He's a luminaries, he's a technical, he's in the industry. He's part of the community, he's been there from the beginning AWS just celebrate its 15th birthday as he was blogging hard. He's been a hardcore blogger. I think Jeff, you had one of the original ping service. If I remember correctly, you were part of the web services foundational kind of present at creation. No better guests to have you Jeff thanks for coming up on our stage. >> John and Dave really happy to be here. >> So I got to ask you, you've been blogging hard for the past decade or so, going hard and your job has evolved from blogging about what's new with Amazon. A couple of building blocks a few services to last reinvent them. You must have put out I don't know how many blog posts did you put out last year at every event? I mean, it must have been a zillion. >> Not quite a zillion. I think I personally wrote somewhere between 20 and 25 including quite a few that I did in the month or so run up to reinvent and it's always intense, but it's always really, really fun. >> So I've got to ask you in the past couple of years, I mean I quoted Andy Jassy's keynote where we highlight in 2010 Amazon wasn't even on the top 10 enterprise players. Now in the top five, you've seen the evolution. What is the big takeaway from your standpoint as you look at the enterprise going from Amazon really dominating the start of a year startups today, you're in the cloud, you're born in the cloud. There's advantage to that. Now enterprises are kind of being reborn in the cloud at the same time, they're building these new use cases rejuvenating themselves and having innovation strategy. What's your takeaway? >> So I love to work with our customers and one of the things that I hear over and over again and especially the last year or two is really the value that they're placing on building a workforce that has really strong cloud skills. They're investing in education. They're focusing on this neat phrase that I learned in Australia called upskilling and saying let's take our set of employees and improve their skill base. I hear companies really saying we're going to go cloud first. We're going to be cloud native. We're going to really embrace it, adopt the full set of cloud services and APIs. And I also see that they're really looking at cloud as part of often a bigger picture. They often use the phrase digital transformation, in Amazon terms we'd say they're thinking big. They're really looking beyond where they are and who they are to what they could be and what they could grow into. Really putting a lot of energy and creativity into thinking forward in that way. >> I wonder Jeff, if you could talk about sort of how people are thinking about the future of cloud if you look at where the spending action is obviously you see it in cloud computing. We've seen that as the move to digital, serverless Lambda is huge. If you look at the data it's off the charts, machine learning and AI also up there containers and of course, automation, AWS leads in all of those. And they portend a different sort of programming model a different way of thinking about how to deploy workloads and applications maybe different than the early days of cloud. What's driving that generally and I'm interested in serverless specifically. And how do you see the next several years folding out? >> Well, they always say that the future is the hardest thing to predict but when I talked to our enterprise customers the two really big things that I see is there's this focus that says we need to really, we're not simply like hosting the website or running the MRP. I'm working with one customer in particular where they say, well, we're going to start on the factory floor all the way up to the boardroom effectively from IOT and sensors on the factory floor to feed all the data into machine learning. So they understand that the factory is running really well to actually doing planning and inventory maintenance to putting it on the website to drive the analytics, to then saying, okay, well how do we know that we're building the right product mix? How do we know that we're getting it out through the right channels? How are our customers doing? So they're really saying there's so many different services available to us in the cloud and they're relatively easy and straightforward to deploy. They really don't think in the old days as we talked about earlier that the old days where these multi-year planning and deployment cycles, now it's much more straightforward. It's like let's see what we can do today. And this week and this month, and from idea to some initial results is a much, much shorter turnaround. So they can iterate a lot more quickly which is just always known to produce better results. >> Well, Jeff and the spirit of the 15th birthday of AWS a lot of services have been built from the original three. I believe it was the core building blocks and there's been a lot of history and it's kind of like there was a key decoupling of compute from storage, those innovations what's the most important architectural change if any has happened or built upon those building blocks with AWS that you could share with companies out there as many people are coming into the cloud not just lifting and shifting and having that innovation but really building cloud native and now hybrid full cloud operations, day two operations. However you want to look at it. That's a big thing. What architecturally has changed that's been innovative from those original building blocks? >> Well, I think that the basic architecture has proven to be very, very resilient. When I wrote about the 15 year birthday of Amazon S3 a couple of weeks ago one thing that I thought was really incredible was the fact that the same APIs that you could have used 15 years ago they all still work. The put, the get, the list, the delete, the permissions management, every last one of those were chosen with extreme care. And so they all still work. So one of the things you think about when you put APIs out there is in Amazon terms we always talk about going through a one-way door and a one way door says, once you do it you're committed for the indefinite future. And so you we're very happy to do that but we take those steps with extreme care. And so those basic building blocks so the original S3 APIs, the original EC2 APIs and the model, all those things really worked. But now they're running at this just insane scale. One thing that blows me away I routinely hear my colleagues talking about petabytes and exabytes, and we throw around trillions and quadrillions like they're pennies. It's kind of amazing. Sometimes when you hear the scale of requests per day or request per month, and the orders of magnitude are you can't map them back to reality anymore. They're simply like literally astronomical. >> If I can just jump in real quick Dave before you ask Jeff, I was watching the Jeff Bezos interview in 1999 that's been going around on LinkedIn in a 60 minutes interview. The interviewer says you are reporting that you can store a gigabyte of customer data from all their purchases. What are you going to do with that? He basically nailed the answer. This is in 99. We're going to use that data to create, that was only a gig. >> Well one of the things that is interesting to me guys, is if you look at again, the early days of cloud, of course I always talked about that in small companies like ours John could have now access to information technology that only big companies could get access to. And now you've seen we just going to talk about it today. All these startups rise up and reach viability. But at the same time, Jeff you've seen big companies get the aha moment on cloud and competition drives urgency and that drives innovation. And so now you see everybody is doing cloud, it's a mandate. And so the expectation is a lot more innovation, experimentation and speed from all ends. It's really exciting to see. >> I know this sounds hackneyed and overused but it really, really still feels just like day one. We're 15 plus years into this. I still wake up every morning, like, wow what is the coolest thing that I'm going to get to learn about and write about today? We have the most amazing customers, one of the things that is great when you're so well connected to your customers, they keep telling you about their dreams, their aspirations, their use cases. And we can just take that and say we can actually build awesome things to help you address those use cases from the ground on up, from building custom hardware things like the nitro system, the graviton to the machine learning inferencing and training chips where we have such insight into customer use cases because we have these awesome customers that we can make these incredible pieces of hardware and software to really address those use cases. >> I'm glad you brought that up. This is another big change, right? You're getting the early days of cloud like, oh, Amazon they're just using off the shelf components. They're not buying these big refrigerator sized disc drives. And now you're developing all this custom Silicon and vertical integration in certain aspects of your business. And that's because workload is demanding. You've got to get more specialized in a lot of cases. >> Indeed they do. And if you watch Peter DeSantis' keynote at re-invent he talked about the fact that we're researching ways to make better cement that actually produces less carbon dioxide. So we're now literally at the from the ground on up level of construction. >> Jeff, I want to get a question from the crowd here. We got, (mumbles) who's a good friend of theCUBE cloud Arate from the beginning. He asked you, he wants to know if you'd like to share Amazon's edge aspirations. He says, he goes, I mean, roadmaps. I go, first of all, he's not going to talk about the roadmaps, but what can you share? I mean, obviously the edge is key. Outpost has been all in the news. You obviously at CloudOps is not a boundary. It's a distributed network. What's your response to-- >> Well, the funny thing is we don't generally have technology roadmaps inside the company. The roadmap is always listen really well to customers not just where they are, but the customers are just so great at saying, this is where we'd like to go. And when we hear edge, the customers don't generally come to us and say edge, they say we need as low latency as possible between where the action happens within our factory floors and our own offices and where we might be able to compute, analyze, store make decisions. And so that's resulted in things like outposts where we can put outposts in their own data center or their own field office, wavelength, where we're working with 5G telecom providers to put computing storage in the carrier hubs of the various 5G providers. Again, with reducing latency, we've been doing things like local zones, where we put zones in an increasing number of cities across the country with the goal of just reducing the average latency between the vast majority of customers and AWS resources. So instead of thinking edge, we really think in terms of how do we make sure that our customers can realize their dreams. >> Staying on the flywheel that AWS has built on ship stuff faster, make things faster, smaller, cheaper, great mission. I want to ask you about the working backwards document. I know it's been getting a lot of public awareness. I've been, that's all I've learned in interviewing Amazon folks. They always work backwards. I always mentioned the customer and all the interviews. So you've got a couple of customer references in there check the box there for you. But working backwards has become kind of a guiding principles, almost like a Harvard Business School case study approach to management. As you guys look at this working backwards and ex Amazonians have written books about it now so people can go look at, it's a really good methodology. Take us back to how you guys work back from the customers because here we're featuring 10 startups. So companies that are out there and Andy has been preaching this to customers. You should think about working backwards because it's so fast. These companies are going into this enterprise market your ecosystem of startups to provide value. What things are you seeing that customers need to think about to work backwards from their customer? How do you see that? 'Cause you've been on the community side, you see the tech side customers have to move fast and work backwards. What are the things that they need to focus on? What's your observation? >> So there's actually a brand new book called "Working Backwards," which I actually learned a lot about our own company from simply reading the book. And I think to me, a principal part of learning backward it's really about humility and being able to be a great listener. So you don't walk into a customer meeting ready to just broadcast the latest and greatest that we've been working on. You walk in and say, I'm here from AWS and I simply want to learn more about who you are, what you're doing. And most importantly, what do you want to do that we're not able to help you with right now? And then once we hear those kinds of things we don't simply write down kind of a bullet item of AWS needs to improve. It's this very active listening process. Tell me a little bit more about this challenge and if we solve it in this way or this way which one's a better fit for your needs. And then a typical AWS launch, we might talk to between 50 and 100 customers in depth to make sure that we have that detailed understanding of what they would like to do. We can't always meet all the needs of these customers but the idea is let's see what is the common base that we can address first. And then once we get that first iteration out there, let's keep listening, let's keep making it better and better and better as quickly. >> A lot of people might poopoo that John but I got to tell you, John, you will remember this the first time we ever met Andy Jassy face-to-face. I was in the room, you were on the speaker phone. We were building an app on AWS at the time. And he was asking you John, for feedback. And he was probing and he pulled out his notebook. He was writing down and he wasn't just superficial questions. He was like, well, why'd you do it that way? And he really wanted to dig. So this is cultural. >> Yeah. I mean, that's the classic Amazon. And that's the best thing about it is that you can go from zero startups zero stage startup to traction. And that was the premise of the cloud. Jeff, I want to get your thoughts and commentary on this love to get your opinion. You've seen this grow from the beginning. And I remember 'cause I've been playing with AWS since the beginning as well. And it says as an entrepreneur I remember my first EC2 instance that didn't even have custom domain support. It was the long URL. You seen the startups and now that we've been 15 years in, you see Dropbox was it just a startup back in the day. I remember these startups that when they were coming they were all born on Amazon, right? These big now unicorns, you were there when these guys were just developers and these gals. So what's it like, I mean, you see just the growth like here's a couple of people with them ideas rubbing nickels together, making magic happen who knows what's going to turn into, you've been there. What's it been like? >> It's been a really unique journey. And to me like the privilege of a lifetime, honestly I've like, you always want to be part of something amazing and you aspire to it and you study hard and you work hard and you always think, okay, somewhere in this universe something really cool is about to happen. And if you're really, really lucky and just a million great pieces of luck like lineup in series, sometimes it actually all works out and you get to be part of something like this when it does you don't always fully appreciate just how awesome it is from the inside, because you're just there just like feeding the machine and you are just doing your job just as fast as you possibly can. And in my case, it was listening to teams and writing blog posts about their launches and sharing them on social media, going out and speaking, you do it, you do it as quickly as possible. You're kind of running your whole life as you're doing that as well. And suddenly you just take a little step back and say, wow we did this kind of amazing thing, but we don't tend to like relax and say, okay, we've done it at Amazon. We get to a certain point. We recognize it. And five minutes later, we're like, okay, let's do the next amazingly good thing. But it's been this just unique privilege and something that I never thought I'd be fortunate enough to be a part of. >> Well, then the last few minutes we have Jeff I really appreciate you taking the time to spend with us for this inaugural launch of theCUBE on cloud startup showcase. We are showcasing 10 startups here from your ecosystem. And a lot of people who know AWS for the folks that don't you guys pride yourself on community and ecosystem the global startups program that Jeremy and his team are running. You guys nurture these startups. You want them to be successful. They're vectoring out into the marketplace with growth strategy, helping customers. What's your take on this ecosystem? As customers are out there listening to this what's your advice to them? How should they engage? Why is these sets of start-ups so important? >> Well, I totally love startups and I've spent time in several startups. I've spent other time consulting with them. And I think we're in this incredible time now wheres, it's so easy and straightforward to get those basic resources, to get your compute, to get your storage, to get your databases, to get your machine learning and to take that and to really focus on your customers and to build what you want. And we see this actual exponential growth. And we see these startups that find something to do. They listen to one of their customers, they build that solution. And they're just that feedback cycle gets started. It's really incredible. And I love to see the energy of these startups. I love to hear from them. And at any point if we've got an AWS powered startup and they build something awesome and want to share it with me, I'm all ears. I love to hear about them. Emails, Twitter mentions, whatever I'll just love to hear about all this energy all those great success with our startups. >> Jeff Barr, thank you for coming on. And congratulations, please pass on to Andy Jassy who's going to take over for Jeff Bezos and I saw the big news that he's picking a successor an Amazonian coming back into the fold, Adam. So congratulations on that. >> I will definitely pass on your congratulations to Andy and I worked with Adam in the past when AWS was just getting started and really looking forward to seeing him again, welcoming back and working with him. >> All right, Jeff Barr with AWS guys check out his Twitter and all the social coordinates. He is pumping out all the resources you need to know about if you're a developer or you're an enterprise looking to go to the next level, next generation, modern infrastructure. Thanks Jeff for coming on. Really appreciate it. Our next guests want to bring up stage Michael Liebow from McKinsey cube alumni, who is a great guest who is very timely in his McKinsey role with a paper he and his colleagues put out called cloud's trillion dollar prize up for grabs. Michael, thank you for coming up on stage with Dave and I. >> Hey, great to be here, John. Thank you. >> One of the things I loved about this and why I wanted you to come on was not only is the report awesome. And Dave has got a zillion questions, he want us to drill into. But in 2015, we wrote a story called Andy Jassy trillion dollar baby on Forbes, and then on medium and silken angle where we were the first ones to profile Andy Jassy and talk about this trillion dollar term. And Dave came up with the calculation and people thought we were crazy. What are you talking about trillion dollar opportunity. That was in 2015. You guys have put this together with a serious research report with methodology and you left a lot on the table. I noticed in the report you didn't even have a whole section quantified. So I think just scratching the surface trillion. I'd be a little light, Dave, so let's dig into it, Michael thanks for coming on. >> Well, and I got to say, Michael that John's a trillion dollar baby was revenue. Yours is EBITDA. So we're talking about seven to X, seven to eight X. What we were talking back then, but great job on the report. Fantastic work. >> Thank you. >> So tell us about the report gives a quick lowdown. I got some questions. You guys are unlocking the value drivers but give us a quick overview of this report that people can get for free. So everyone who's registered will get a copy but give us a quick rundown. >> Great. Well the question I think that has bothered all of us for a long time is what's the business value of cloud and how do you quantify it? How do you specify it? Because a lot of people talk around the infrastructure or technical value of cloud but that actually is a big problem because it just scratches the surface of the potential of what cloud can mean. And we focus around the fortune 500. So we had to box us in somewhat. And so focusing on the fortune 500 and fast forwarding to 2030, we put out this number that there's over a trillion dollars worth of value. And we did a lot of analysis using research from a variety of partners, using third-party research, primary research in order to come up with this view. So the business value is two X the technical value of cloud. And as you just pointed out, there is a whole unlock of additional value where organizations can pioneer on some of the newest technologies. And so AWS and others are creating platforms in order to do not just machine learning and analytics and IOT, but also for quantum or mixed reality for blockchain. And so organizations specific around the fortune 500 that aren't leveraging these capabilities today are going to get left behind. And that's the message we were trying to deliver that if you're not doing this and doing this with purpose and with great execution, that others, whether it's others in your industry or upstarts who were motioning into your industry, because as you say cloud democratizes compute, it provides these capabilities and small companies with talent. And that's what the skills can leverage these capabilities ahead of slow moving incumbents. And I think that was the critical component. So that gives you the framework. We can deep dive based on your questions. >> Well before we get into the deep dive, I want to ask you we have startups being showcased here as part of the, it will showcase, they're coming out of the ecosystem. They have a lot of certification from Amazon and they're secure, which is a big issue. Enterprises that you guys talk to McKinsey speaks directly to I call the boardroom CXOs, the top executives. Are they realizing that the scale and timing of this agility window? I mean, you want to go through these key areas that you would break out but as startups become more relevant the boardrooms that are making these big decisions realize that their businesses are up for grabs. Do they realize that all this wealth is shifting? And do they see the role of startups helping them? How did you guys come out of them and report on that piece? >> Well in terms of the whole notion, we came up with this framework which looked at the opportunity. We talked about it in terms of three dimensions, rejuvenate, innovate and pioneer. And so from the standpoint of a board they're more than focused on not just efficiency and cost reduction basically tied to nation, but innovation tied to analytics tied to machine learning, tied to IOT, tied to two key attributes of cloud speed and scale. And one of the things that we did in the paper was leverage case examples from across industry, across-region there's 17 different case examples. My three favorite is one is Moderna. So software for life couldn't have delivered the vaccine as fast as they did without cloud. My second example was Goldman Sachs got into consumer banking is the platform behind the Apple card couldn't have done it without leveraging cloud. And the third example, particularly in early days of the pandemic was Zoom that added five to 6,000 servers a night in order to scale to meet the demand. And so all three of those examples, plus the other 14 just indicate in business terms what the potential is and to convince boards and the C-suite that if you're not doing this, and we have some recommendations in terms of what CEOs should do in order to leverage this but to really take advantage of those capabilities. >> Michael, I think it's important to point out the approach at sometimes it gets a little wonky on the methodology but having done a lot of these types of studies and observed there's a lot of superficial studies out there, a lot of times people will do, they'll go I'll talk to a customer. What kind of ROI did you get? And boom, that's the value study. You took a different approach. You have benchmark data, you talked to a lot of companies. You obviously have a lot of financial data. You use some third-party data, you built models, you bounded it. And ultimately when you do these things you have to ascribe a value contribution to the cloud component because fortunate 500 companies are going to grow even if there were no cloud. And the way you did that is again, you talk to people you model things, and it's a very detailed study. And I think it's worth pointing out that this was not just hey what'd you get from going to cloud before and after. This was a very detailed deep dive with really a lot of good background work going into it. >> Yeah, we're very fortunate to have the McKinsey Global Institute which has done extensive studies in these areas. So there was a base of knowledge that we could leverage. In fact, we looked at over 700 use cases across 19 industries in order to unpack the value that cloud contributed to those use cases. And so getting down to that level of specificity really, I think helps build it from the bottom up and then using cloud measures or KPIs that indicate the value like how much faster you can deploy, how much faster you can develop. So these are things that help to kind of inform the overall model. >> Yeah. Again, having done hundreds, if not thousands of these types of things, when you start talking to people the patterns emerge, I want to ask you there's an exhibit tool in here, which is right on those use cases, retail, healthcare, high-tech oil and gas banking, and a lot of examples. And I went through them all and virtually every single one of them from a value contribution standpoint the unlocking value came down to data large data sets, document analysis, converting sentiment analysis, analytics. I mean, it really does come down to the data. And I wonder if you could comment on that and why is it that cloud is enabled that? >> Well, it goes back to scale. And I think the word that I would use would be data gravity because we're talking about massive amounts of data. So as you go through those kind of three dimensions in terms of rejuvenation one of the things you can do as you optimize and clarify and build better resiliency the thing that comes into play I think is to have clean data and data that's available in multiple places that you can create an underlying platform in order to leverage the services, the capabilities around, building out that structure. >> And then if I may, so you had this again I want to stress as EBITDA. It's not a revenue and it's the EBITDA potential as a result of leveraging cloud. And you listed a number of industries. And I wonder if you could comment on the patterns that you saw. I mean, it doesn't seem to be as simple as Negroponte bits versus Adam's in terms of your ability to unlock value. What are the patterns that you saw there and why are the ones that have so much potential why are they at the top of the list? >> Well, I mean, they're ranked based on impact. So the five greatest industries and again, aligned by the fortune 500. So it's interesting when you start to unpack it that way high-tech oil, gas, retail, healthcare, insurance and banking, right? Top. And so we did look at the different solutions that were in that, tried to decipher what was fully unlocked by cloud, what was accelerated by cloud and what was perhaps in this timeframe remaining on premise. And so we kind of step by step, expert by expert, use case by use case deciphered of the 700, how that applied. >> So how should practitioners within organizations business but how should they use this data? What would you recommend, in terms of how they think about it, how they apply it to their business, how they communicate? >> Well, I think clearly what came out was a set of best practices for what organizations that were leveraging cloud and getting the kind of business return, three things stood out, execution, experience and excellence. And so for under execution it's not just the transaction, you're not just buying cloud you're changing their operating model. And so if the organization isn't kind of retooling the model, the processes, the workflows in order to support creating the roles then they aren't going to be able, they aren't going to be successful. In terms of experience, that's all about hands-on. And so you have to dive in, you have to start you have to apply yourself, you have to gain that applied knowledge. And so if you're not gaining that experience, you're not going to move forward. And then in terms of excellence, and it was mentioned earlier by Jeff re-skilling, up-skilling, if you're not committed to your workforce and pushing certification, pushing training in order to really evolve your workforce or your ways of working you're not going to leverage cloud. So those three best practices really came up on top in terms of what a mature cloud adopter looks like. >> That's awesome. Michael, thank you for coming on. Really appreciate it. Last question I have for you as we wrap up this trillion dollar segment upon intended is the cloud mindset. You mentioned partnering and scaling up. The role of the enterprise and business is to partner with the technologists, not just the technologies but the companies talk about this cloud native mindset because it's not just lift and shift and run apps. And I have an IT optimization issue. It's about innovating next gen solutions and you're seeing it in public sector. You're seeing it in the commercial sector, all areas where the relationship with partners and companies and startups in particular, this is the startup showcase. These are startups are more relevant than ever as the tide is shifting to a new generation of companies. >> Yeah, so a lot of think about an engine. A lot of things have to work in order to produce the kind of results that we're talking about. Brad, you're more than fair share or unfair share of trillion dollars. And so CEOs need to lead this in bold fashion. Number one, they need to craft the moonshot or the Marshot. They have to set that goal, that aspiration. And it has to be a stretch goal for the organization because cloud is the only way to enable that achievement of that aspiration that's number one, number two, they really need a hardheaded economic case. It has to be defined in terms of what the expectation is going to be. So it's not loose. It's very, very well and defined. And in some respects time box what can we do here? I would say the cloud data, your organization has to move in an agile fashion training DevOps, and the fourth thing, and this is where the startups come in is the cloud platform. There has to be an underlying platform that supports those aspirations. It's an art, it's not just an architecture. It's a living, breathing live service with integrations, with standardization, with self service that enables this whole program. >> Awesome, Michael, thank you for coming on and sharing the McKinsey perspective. The report, the clouds trillion dollar prize is up for grabs. Everyone who's registered for this event will get a copy. We will appreciate it's also on the website. We'll make sure everyone gets a copy. Thanks for coming, I appreciate it. Thank you. >> Thanks, Michael. >> Okay, Dave, big discussion there. Trillion dollar baby. That's the cloud. That's Jassy. Now he's going to be the CEO of AWS. They have a new CEO they announced. So that's going to be good for Amazon's kind of got clarity on the succession to Jassy, trusted soldier. The ecosystem is big for Amazon. Unlike Microsoft, they have the different view, right? They have some apps, but they're cultivating as many startups and enterprises as possible in the cloud. And no better reason to change gears here and get a venture capitalist in here. And a friend of theCUBE, Jerry Chen let's bring them up on stage. Jerry Chen, great to see you partner at Greylock making all the big investments. Good to see you >> John hey, Dave it's great to be here with you guys. Happy marks.Can you see that? >> Hey Jerry, good to see you man >> So Jerry, our first inaugural AWS startup showcase we'll be doing these quarterly and we're going to be featuring the best of the best, you're investing in all the hot startups. We've been tracking your careers from the beginning. You're a good friend of theCUBE. Always got great commentary. Why are startups more important than ever before? Because in the old days we've talked about theCUBE before startups had to go through certain certifications and you've got tire kicking, you got to go through IT. It's like going through security at the airport, take your shoes off, put your belt on thing. I mean, all kinds of things now different. The world has changed. What's your take? >> I think startups have always been a great way for experimentation, right? It's either new technologies, new business models, new markets they can move faster, the experiment, and a lot of startups don't work, unfortunately, but a lot of them turned to be multi-billion dollar companies. I thing startup is more important because as we come out COVID and economy is recovery is a great way for individuals, engineers, for companies for different markets to try different things out. And I think startups are running multiple experiments at the same time across the globe trying to figure how to do things better, faster, cheaper. >> And McKinsey points out this use case of rejuvenate, which is essentially retool pivot essentially get your costs down or and the next innovation here where there's Tam there's trillion dollars on unlock value and where the bulk of it is is the innovation, the new use cases and existing new use cases. This is where the enterprises really have an opportunity. Could you share your thoughts as you invest in the startups to attack these new waves these new areas where it may not look the same as before, what's your assessment of this kind of innovation, these new use cases? >> I think we talked last time about kind of changing the COVID the past year and there's been acceleration of things like how we work, education, medicine all these things are going online. So I think that's very clear. The first wave of innovation is like, hey things we didn't think we could be possible, like working remotely, e-commerce everywhere, telemedicine, tele-education, that's happening. I think the second order of fact now is okay as enterprises realize that this is the new reality everything is digital, everything is in the cloud and everything's going to be more kind of electronic relation with the customers. I think that we're rethinking what does it mean to be a business? What does it mean to be a bank? What does it mean to be a car company or an energy company? What does it mean to be a retailer? Right? So I think the rethinking that brands are now global, brands are all online. And they now have relationships with the customers directly. So I think if you are a business now, you have to re experiment or rethink about your business model. If you thought you were a Nike selling shoes to the retailers, like half of Nike's revenue is now digital right all online. So instead of selling sneakers through stores they're now a direct to consumer brand. And so I think every business is going to rethink about what the AR. Airbnb is like are they in the travel business or the experience business, right? Airlines, what business are they in? >> Yeah, theCUBE we're direct to consumer virtual totally opened up our business model. Dave, the cloud premise is interesting now. I mean, let's reset this where we are, right? Andy Jassy always talks about the old guard, new guard. Okay we've been there done that, even though they still have a lot of Oracle inside AWS which we were joking the other day, but this new modern era coming out of COVID Jerry brings this up. These startups are going to be relevant take territory down in the enterprises as new things develop. What's your premise of the cloud and AWS prospect? >> Well, so Jerry, I want to to ask you. >> Jerry: Yeah. >> The other night, last Thursday, I think we were in Clubhouse. Ben Horowitz was on and Martine Casado was laying out this sort of premise about cloud startups saying basically at some point they're going to have to repatriate because of the Amazon VIG. I mean, I'm paraphrasing and I guess the premise was that there's this variable cost that grows as you scale but I kind of shook my head and I went back. You saw, I put it out on Twitter a clip that we had the a couple of years ago and I don't think, I certainly didn't see it that way. Maybe I'm getting it wrong but what's your take on that? I just don't see a snowflake ever saying, okay we're going to go build our own data center or we're going to repatriate 'cause they're going to end up like service now and have this high cost infrastructure. What do you think? >> Yeah, look, I think Martin is an old friend from VMware and he's brilliant. He has placed a lot of insights. There is some insights around, at some point a scale, use of startup can probably run things more cost-effectively in your own data center, right? But I think that's fewer companies more the vast majority, right? At some point, but number two, to your point, Dave going on premise versus your own data center are two different things. So on premise in a customer's environment versus your own data center are two different worlds. So at some point some scale, a lot of the large SaaS companies run their own data centers that makes sense, Facebook and Google they're at scale, they run their own data centers, going on premise or customer's environment like a fortune 100 bank or something like that. That's a different story. There are reasons to do that around compliance or data gravity, Dave, but Amazon's costs, I don't think is a legitimate reason. Like if price is an issue that could be solved much faster than architectural decisions or tech stacks, right? Once you're on the cloud I think the thesis, the conversation we had like a year ago was the way you build apps are very different in the cloud and the way built apps on premise, right? You have assume storage, networking and compute elasticity that's independent each other. You don't really get that in a customer's data center or their own environment even with all the new technologies. So you can't really go from cloud back to on-premise because the way you build your apps look very, very different. So I would say for sure at some scale run your own data center that's why the hyperscale guys do that. On-premise for customers, data gravity, compliance governance, great reasons to go on premise but for vast majority of startups and vast majority of customers, the network effects you get for being in the cloud, the network effects you get from having everything in this alas cloud service I think outweighs any of the costs. >> I couldn't agree more and that's where the data is, at the way I look at it is your technology spend is going to be some percentage of revenue and it's going to be generally flat over time and you're going to have to manage it whether it's in the cloud or it's on prem John. >> Yeah, we had a quote on theCUBE on the conscious that had Jerry I want to get your reaction to this. The executive said, if you don't have an AI strategy built into your value proposition you will be shorted as a stock on wall street. And I even went further. So you'll probably be delisted cause you won't be performing with a tongue in cheek comment. But the reality is that that's indicating that everyone has to have AI in their thing. Mainly as a reality, what's your take on that? I know you've got a lot of investments in this area as AI becomes beyond fashion and becomes table stakes. Where are we on that spectrum? And how does that impact business and society as that becomes a key part of the stack and application stack? >> Yeah, I think John you've seen AI machine learning turn out to be some kind of novelty thing that a bunch of CS professors working on years ago to a funnel piece of every application. So I would say the statement of the sentiment's directionally correct that 20 years ago if you didn't have a web strategy or a website as a company, your company be sure it, right? If you didn't have kind of a internet website, you weren't real company. Likewise, if you don't use AI now to power your applications or machine learning in some form or fashion for sure you'd be at a competitive disadvantage to everyone else. And just like if you're not using software intelligently or the cloud intelligently your stock as a company is going to underperform the rest of the market. And the cloud guys on the startups that we're backing are making AI so accessible and so easy for developers today that it's really easy to use some level of machine learning, any applications, if you're not doing that it's like not having a website in 1999. >> Yeah. So let's get into that whole operation side. So what would you be your advice to the enterprises that are watching and people who are making decisions on architecture and how they roll out their business model or value proposition? How should they look at AI and operations? I mean big theme is day two operations. You've got IT service management, all these things are being disrupted. What's the operational impact to this? What's your view on that? >> So I think two things, one thing that you and Dave both talked about operation is the key, I mean, operations is not just the guts of the business but the actual people running the business, right? And so we forget that one of the values are going to cloud, one of the values of giving these services is you not only have a different technology stack, all the bits, you have a different human stack meaning the people running your cloud, running your data center are now effectively outsource to Amazon, Google or Azure, right? Which I think a big part of the Amazon VIG as Dave said, is so eloquently on Twitter per se, right? You're really paying for those folks like carry pagers. Now take that to the next level. Operations is human beings, people intelligently trying to figure out how my business can run better, right? And that's either accelerate revenue or decrease costs, improve my margin. So if you want to use machine learning, I would say there's two areas to think about. One is how I think about customers, right? So we both talked about the amount of data being generated around enterprise individuals. So intelligently use machine learning how to serve my customers better, then number two AI and machine learning internally how to run my business better, right? Can I take cost out? Can I optimize supply chain? Can I use my warehouses more efficiently my logistics more efficiently? So one is how do I use AI learning to be a more familiar more customer oriented and number two, how can I take cost out be more efficient as a company, by writing AI internally from finance ops, et cetera. >> So, Jerry, I wonder if I could ask you a little different subject but a question on tactical valuations how coupled or decoupled are private company valuations from the public markets. You're seeing the public markets everybody's freaking out 'cause interest rates are going to go up. So the future value of cash flows are lower. Does that trickle in quickly into the private markets? Or is it a whole different dynamic? >> If I could weigh in poly for some private markets Dave I would have a different job than I do today. I think the reality is in the long run it doesn't matter as much as long as you're investing early. Now that's an easy answer say, boats have to fall away. Yes, interest rates will probably go up because they're hard to go lower, right? They're effectively almost zero to negative right now in most of the developed world, but at the end of the day, I'm not going to trade my Twilio shares or Salesforce shares for like a 1% yield bond, right? I'm going to hold the high growth tech stocks because regardless of what interest rates you're giving me 1%, 2%, 3%, I'm still going to beat that with a top tech performers, Snowflake, Twilio Hashi Corp, bunch of the private companies out there I think are elastic. They're going to have a great 10, 15 year run. And in the Greylock portfolio like the things we're investing in, I'm super bullish on from Roxanne to Kronos fear, to true era in the AI space. I think in the long run, next 10 years these things will outperform the market that said, right valuation prices have gone up and down and they will in our careers, they have. In the careers we've been covering tech. So I do believe that they're high now they'll come down for sure. Will they go back up again? Definitely, right? But as long as you're betting these macro waves I think we're all be good. >> Great answer as usual. Would you trade them for NFTs Jerry? >> That $69 million people piece of artwork look, I mean, I'm a longterm believer in kind of IP and property rights in the blockchain, right? And I'm waiting for theCUBE to mint this video as the NFT, when we do this guys, we'll mint this video's NFT and see how much people pay for the original Dave, John, Jerry (mumbles). >> Hey, you know what? We can probably get some good bang for that. Hey it's all about this next Jerry. Jerry, great to have you on, final question as we got this one minute left what's your advice to the people out there that either engaging with these innovative startups, we're going to feature startups every quarter from the in the Amazon ecosystem, they are going to be adding value. What's the advice to the enterprises that are engaging startups, the approach, posture, what's your advice. >> Yeah, when I talk to CIOs and large enterprises, they often are wary like, hey, when do I engage a startup? How, what businesses, and is it risky or low risk? Now I say, just like any career managing, just like any investment you're making in a big, small company you should have a budget or set of projects. And then I want to say to a CIO, Hey, every priority on your wish list, go use the startup, right? I mean, that would be 10 for 10 projects, 10 startups. Probably too much risk for a lot of tech companies. But we would say to most CIOs and executives, look, there are strategic initiatives in your business that you want to accelerate. And I would take the time to invest in one or two startups each quarter selectively, right? Use the time, focus on fewer startups, go deep with them because we can actually be game changers in terms of inflecting your business. And what I mean by that is don't pick too many startups because you can't devote the time, but don't pick zero startups because you're going to be left behind, right? It'd be shorted as a stock by the John, Dave and Jerry hedge fund apparently but pick a handful of startups in your strategic areas, in your top tier three things. These really, these could be accelerators for your career. >> I have to ask you real quick while you're here. We've got a couple minutes left on startups that are building apps. I've seen DevOps and the infrastructure as code movement has gone full mainstream. That's really what we're living right now. That kind of first-generation commercialization of DevOps. Now DevSecOps, what are the trends that you've seen that's different from say a couple of years ago now that we're in COVID around how apps are being built? Is it security? Is it the data integration? What can you share as a key app stack impact (mumbles)? >> Yeah, I think there're two things one is security is always been a top priority. I think that was the only going forward period, right? Security for sure. That's why you said that DevOps, DevSecOps like security is often overlooked but I think increasingly could be more important. The second thing is I think we talked about Dave mentioned earlier just the data around customers, the data on premise or the cloud, and there's a ton of data out there. We keep saying this over and over again like data's new oil, et cetera. It's evolving and not changing because the way we're using data finding data is changing in terms of sources of data we're using and discovering and also speed of data, right? In terms of going from Basser real-time is changing. The speed of business has changed to go faster. So I think these are all things that we're thinking about. So both security and how you use your data faster and better. >> Yeah you were in theCUBE a number of years ago and I remember either John or I asked you about you think Amazon is going to go up the stack and start developing applications and your answer was you know what I think no, I think they're going to enable a new set of disruptors to come in and disrupt the SaaS world. And I think that's largely playing out. And one of the interesting things about Adam Selipsky appointment to the CEO, he comes from Tableau. He really helped Tableau go from that sort of old guard model to an ARR model obviously executed a great exit to Salesforce. And now I see companies like Salesforce and service now and Workday is potential for your scenario to really play out. They've got in my view anyway, outdated pricing models. You look at what's how Snowflake's pricing and the consumption basis, same with Datadog same with Stripe and new startups seem to really be a leading into the consumption-based pricing model. So how do you, what are your thoughts on that? And maybe thoughts on Adam and thoughts on SaaS disruption? >> I think my thesis still holds that. I don't think Selipsky Adam is going to go into the app space aggressively. I think Amazon wants to enable next generation apps and seeing some of the new service that they're doing is they're kind of deconstructing apps, right? They're deconstructing the parts of CRM or e-commerce and they're offering them as services. So I think you're going to see Amazon continue to say, hey we're the core parts of an app like payments or custom prediction or some machine learning things around applications you want to buy bacon, they're going to turn those things to the API and sell those services, right? So you look at things like Stripe, Twilio which are two of the biggest companies out there. They're not apps themselves, they're the components of the app, right? Either e-commerce or messaging communications. So I can see Amazon going down that path. I think Adam is a great choice, right? He was a longterm early AWS exact from the early days latent to your point Dave really helped take Tableau into kind of a cloud business acquired by Salesforce work there for a few years under Benioff the guy who created quote unquote cloud and now him coming home again and back to Amazon. So I think it'll be exciting to see how Adam runs the business. >> And John I think he's the perfect choice because he's got operations chops and he knows how to... He can help the startups disrupt. >> Yeah, and he's been a trusted soldier of Jassy from the beginning, he knows the DNA. He's got some CEO outside experience. I think that was the key he knows. And he's not going to give up Amazon speed, but this is baby, right? So he's got him in charge and he's a trusted lieutenant. >> You think. Yeah, you think he's going to hold the mic? >> Yeah. We got to go. Jerry Chen thank you very much for coming on. Really appreciate it. Great to see you. Thanks for coming on our inaugural cube on cloud AWS startup event. Now for the 10 startups, enjoy the sessions at 12:30 Pacific, we're going to have the closing keynote. I'm John Ferry for Dave Vellante and our special guests, thanks for watching and enjoy the rest of the day and the 10 startups. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> Last year in 2020 it was good to be in tech and even better to be in the cloud, as organizations had to rely on remote cloud services to keep things running. We believe that tech spending will increase seven to 8% in 2021. But we don't expect investments in cloud computing to sharply attenuate, when workers head back to the office. It's not a zero sum game, and we believe that pent up demand in on-prem data centers will complement those areas of high growth that we saw last year, namely cloud, AI, security, data and automation. Hello everyone, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis we'll provide our take on the latest ETR COVID survey, and share why we think the tech boom will continue, well into the future. So let's take a look at the state of tech spending. Fitch Ratings has upped its outlook for global GDP to 6.1% for January's 5.3% projection. We've always expected tech spending to outperform GDP by at least 100 to 200 basis points, so we think 2021 could see 8% growth for the tech sector. That's a massive swing from last year's,5% contraction, and it's being powered by spending in North America, a return of small businesses, and, the massive fiscal stimulus injection from the U.S led central bank actions. As we'll show you, the ETR survey data suggests that cloud spending is here to stay, and a dollar spent back in the data center doesn't necessarily mean less spending on digital initiatives, generally and cloud specifically. Moreover, we see pent up demand for core on-prem data center infrastructure, especially networking. Now one caveat, is we continue to have concerns for the macro on-prem data storage sector. There are pockets of positivity, for example, pure storage seems to have accelerating momentum. But generally the data suggests the cloud and flash headroom, continue, to pressure spending on storage. Now we don't expect the stock market's current rotation out of tech. We don't expect that that changes the fundamental spending dynamic. We see cloud, AI and ML, RPA, cybersecurity and collaboration investments still hovering above, that 40% net score. Actually cybersecurity is not quite there, but it is a priority area for CIOs. We'll talk about that more later. And we expect that those high growth sectors will stay steady in ETRs April survey along with continued spending on application modernization in the form of containers. Now let me take a moment to comment on the recent action in tech stocks. If you've been following the market, you know that the rate on the 10-year Treasury note has been rising. This is important, because the 10 years of benchmark, and it affects other interest rates. As interest rates rise, high growth tech stocks, they become less attractive. And that's why there's been a rotation, out of the big tech high flyer names of 2020. So why do high growth stocks become less attractive to investors when interest rates rise? Well, it's because investors are betting on the future value of cash flows for these companies, and when interest rates go up, the future values of those cash flows shrink, making the valuations less attractive. Let's take an example. Snowflake is a company with a higher revenue multiple than pretty much any other stock, out there in the tech industry. Revenues at the company are growing more than 100%, last quarter, and they're projected to have a revenue of a billion dollars next year. Now on March 8th, Snowflake was valued at around $80 billion and was trading at roughly 75x forward revenue. Today, toward the middle the end of March. Snowflake is valued at about 50 billion or roughly 45x forward revenue. So lower growth companies that throw off more cash today, become more attractive in a rising rate climate because, the cash they throw off today is more valuable than it was in a low rate environment. The cash is there today versus, a high flying tech company where the cash is coming down the road and doesn't have to be discounted on a net present value basis. So the point is, this is really about math, not about fundamental changes in spending. Now the ETR spending data has shown, consistent upward momentum, and that cycle is continuing, leading to our sanguine outlook for the sector. This chart here shows the progression of CIO expectations on spending over time, relative to previous years. And you can see the steady growth in expectations each quarter, hitting 6% growth in 2021 versus 2020 for the full year. ETR estimates show and they do this with a 95% confidence level, that spending is going to be up between 5.1 to 6.8% this year. We are even more up optimistic accounting for recent upward revisions in GDP. And spending outside the purview of traditional IT, which we think will be a tailwind, due to digital initiatives and shadow tech spending. ETR covers some of that, but it is really a CIO heavy survey. So there's some parts that we think can grow even faster, than ETR survey suggests. Now the positive spending outlook, it's broad based across virtually all industries that ETR tracks. Government spending leads the pack by a wide margin, which probably gives you a little bit of heartburn. I know it does for me, yikes. Healthcare is interesting. Perhaps due to pent up demand, healthcare has been so busy saving lives, that it has some holes to fill. But look at the sectors at 5% or above. Only education really lags notably. Even energy which got crushed last year, showing a nice rebound. Now let's take a look at some of the strategies that organizations have employed during COVID, and see how they've changed. Look, the picture is actually quite positive in our view. This data shows the responses over five survey snapshots, starting in March of 2020. Most people are still working from home that really hasn't changed much. But we're finally seeing some loosening of the travel restrictions imposed last year, is a notable drop in canceled business trips. It's still high, but it's very promising trend. Quick aside, looks like Mobile World Congress is happening in late June in Barcelona. The host of the conference just held a show in Shanghai and 20,000 attendees showed up. theCube is planning to be there in Barcelona along with TelcoDr, Who took over Ericsson's 65,000 square foot space, when Ericsson tapped out of the conference. We are good together we're going to lay out the future of the digital telco, in a hybrid: physical slash virtual event. With the ecosystem of telcos, cloud, 5G and software communities. We're very excited to be at the heart of reinventing the event experience for the coming decade. Okay, back to the data. Hiring freezes, way down. Look at new IT deployments near flat from last quarter, with big uptick from a year ago. Layoffs, trending downward, that's really a positive. Hiring momentum is there. So really positive signs for tech in this data. Now let's take a look at the work from home, survey data. We've been sharing this for several quarters now, remember, the data showed that pre pandemic around 15 to 16% of employees worked remotely. And we had been sharing the CIO is expected that figure to slowly decline from the 70% pandemic levels and come into the spring in the summer, hovering in the 50% range. But then eventually landing in the mid 30s. Now the current survey shows 31%. So, essentially, it's exactly double from the pre COVID levels. It's going to be really interesting to see because across the board organizations are reporting, big increases in productivity as a result of how they've responded to COVID in the remote work practices and the infrastructure that's been put in place. And look, a lot of workers are expecting to stay remote. So we'll see where this actually lands. My personal feelings, the number is going to be higher than the low 30s. Perhaps well into the mid to upper 30s. Now let's take a look at the cloud and on-prem MCS. So were a little bit out on a limb here with a can't have a cake and eat it too scenario. Meaning pent up demand for data center infrastructure on-prem is going to combine with the productivity benefits of cloud in the digital imperative. So that means that technology budgets are going to get a bigger piece of the overall spending pie, relative to other initiatives. At least for the near term. ETR asked respondents about how the return to physical, is going to impact on-prem architectures and applications. You can see 63% of the respondents, had a cloud friendly answer, as shown in the first two bars. Whereas 30% had an on-prem friendly answer, as shown in the next three bars. Now, what stands out, is that only 5% of respondents plan to increase their on-prem spend to above pre COVID levels. Sarbjeet Johal pinged me last night and asked me to jump into a clubhouse session with Martin Casado and the other guys from Andreessen Horowitz. They were having this conversation about the coming cloud backlash. And how cloud native companies are spending so much, too much, in their opinion, on AWS and other clouds. And at some point, as they scale, they're going to have to claw back technology infrastructure on-prem, due to their AWS vague. I don't know. This data, it certainly does not suggest that that is happening today. So the cloud vendors, they keep getting more volume, you would think they're going to have better prices and better economies of scales than we'll see on-prem. And as we pointed out, the repatriation narrative that you hear from many on-prem vendors is kind of dubious. Look, if AWS Azure, and Google can't provide IT infrastructure and better security than I can on-prem, then something is amiss. Now however, they are creating an oligopoly. And if they get too greedy and get hooked on the margin crack, of cloud, they'd better be careful, or they're going to become the next regulated utility? So, it's going to be interesting to see if the Andreessen scenario has (laughs) legs, maybe they have another agenda, maybe a lot of their portfolio companies, have ideas are around doing things to help on-prem? Why are we so optimistic that we'll see a stronger 2021 on-prem spend if the cloud continues to command so much attention? Well, first, because nearly 20% of customers say there will be an uptick in on-prem spending. Second, we saw in 2020, that the big on-prem players, Dell, VMware, Oracle, and SAP in particular, and even IBM made it through, okay. And they've managed to figure out how to work through the crisis. And finally, we think that the lines between on-prem and cloud, and hybrid and cross cloud and edge will blur over the next five years. We've talked about this a lot, that abstraction layer that we see coming, and there's some real value opportunities there. It'll take some time. But we do see there, that the traditional vendors, are going to attack those new opportunities and create value across clouds and hybrid systems and out to the edge. Now, as those demarcation lines become more gray, a hybrid world is emerging that is going to require hardware and software investments that reduce latency and are proximate to users buildings and distributed infrastructure. So we see spending in certain key areas, continuing to be strong across the board, will require connecting on-prem to cloud in edge workloads. Here's where it CIOs see the action, asked to cite the technologies that will get the most attention in the next 12 months. These seven stood out among the rest. No surprise that cyber comes out as top priority, with cloud pretty high as well. But interesting to see the uptick in collaboration in networking. Execs are seeing the importance of collaboration technologies for remote workers. No doubt, there's lots of Microsoft Teams in that bar. But there's some pent up demand it seems for networking, we find that very interesting. Now, just to put this in context, in a spending context. We'll share a graphic from a previous breaking analysis episode. This chart shows the net score or spending momentum on the vertical axis. And the market share or pervasiveness in the ETR data set on the horizontal axis. The big four areas of spend momentum are cloud, ML and AI, containers in RPA. This is from the January survey, we don't expect a big change in the upcoming April data, we'll see. But these four stand out above the 40% line that we've highlighted, which to us is an indicator of elevated momentum. Now, note on the horizontal axis only cloud, cloud is the only sector that enjoys both greater than 60% market share on the x axis, and is above the 40% net score line and the y axis. So even though security is a top priority as we were talking about earlier. It competes with other budget items, still right there certainly on the horizontal axis, but it competes with other initiatives for that spend momentum. Okay, so key takeaways. Seven to 8% tech spending growth expected for 2021. Cloud is leading the charge, it's big and it has spending momentum, so we don't expect a big rotation out of cloud back to on-prem. Now, having said that, we think on-prem will benefit from a return to a post isolation economy. Because of that pent up demand. But we caution we think there are some headwinds, particularly in the storage sector. Rotation away from tech in the stock market is not based on a fundamental change in spending in our view, or demand, rather it's stock market valuation math. So there should be some good buying opportunities for you in the coming months. As money moves out of tech into those value stocks. But the market is very hard to predict. Oh 2020 was easy to make money. All you had to do is buy high growth and momentum tech stocks on dips. 2021 It's not that simple. So you got to do your homework. And as we always like to stress, formulate a thesis and give it time to work for you. Iterate and improve when you feel like it's not working for you. But stay current, and be true to your strategy. Okay, that's it for today. Remember, these episodes are all available as podcasts wherever you listen. So please subscribe. I publish weekly in siliconangle.com and wikibond.com and always appreciate the comments on LinkedIn. You can DM me @dvellante or email me at david.vellante@siliconangle.com. Don't forget to check out etr.plus where all the survey data science actually resides. Some really interesting things that they're about to launch. So do follow that. This is Dave vellante. Thanks for watching theCube Insights powered by ETR. Good health to you, be safe and we'll see you next time.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCube and ETR, this is Breaking Analysis with Dave Vellante. >> When a piece of digital art sells for $69.3 million, more than has ever been paid for works, by Gauguin or Salvador Dali, making it created the third most expensive living artists in the world. One can't help but take notice and ask, what is going on? The latest craze around NFTs may feel a bit bubblicious, but it's yet another sign, that the digital age is now fully upon us. Hello and welcome to this week's Wikibon's CUBE insights, powered by ETR. In this Breaking Analysis, we want to take a look at some of the trends, that may be difficult for observers and investors to understand, but we think offer significant insights to the future and possibly some opportunities for young investors many of whom are fans of this program. And how the trends may relate to enterprise tech. Okay, so this guy Beeple is now the hottest artist on the planet. That's his Twitter profile. That picture on the inset. His name is Mike Winkelmann. He is actually a normal looking dude, but that's the picture he chose for his Twitter. This collage reminds me of the Million Dollar Homepage. You may already know the story, but many of you may not. Back in 2005 a college kid from England named Alex Tew, T-E-W created The Million Dollar Homepage to fund his education. And his idea was to create a website with a million pixels, and sell ads at a dollar for each pixel. Guess how much money he raised. A million bucks, right? No, wrong. He raised $1,037,100. How so you ask? Well, he auctioned off the last 1000 pixels on eBay, which fetched an additional $38,000. Crazy, right? Well, maybe not. Pretty creative in a way, way early sign of things to come. Now, I'm not going to go deep into NFTs, and explain the justification behind them. There's a lot of material that's been published that can do justice to the topic better than I can. But here are the basics, NFTs stands for Non-Fungible Tokens. They are digital representations of assets that exist in a blockchain. Now, each token as a unique and immutable identifier, and it uses cryptography to ensure its authenticity. NFTs by the name, they're not fungible. So, unlike Bitcoin, Ethereum or other cryptocurrencies, which can be traded on a like-for-like basis, in other words, if you and I each own one bitcoin we know exactly how much each of our bitcoins is worth at any point of time. Non-Fungible Tokens each have their own unique values. So, they're not comparable on a like-to-like basis. But what's the point of this? Well, NFTs can be applied to any property, identities tweets, videos, we're seeing collectables, digital art, pretty much anything. And it's really. The use cases are unlimited. And NFTs can streamline transactions, and they can be bought and sold very efficiently without the need for a trusted third party involved. Now, the other benefit is the probability of fraud, is greatly reduced. So where do NFTs fit as an asset class? Well, they're definitely a new type of asset. And again, I'm not going to try to justify their existence, but I want to talk about the choices, that investors have in the market today. The other day, I was on a call with Jay Po. He is a VC and a Principal at a company called Stage 2 Capital. He's a former Bessemer VC and one of the sharper investors around. And he was talking about the choices that investors have and he gave a nice example that I want to share with you and try to apply here. Now, as an investor, you have alternatives, of course we're showing here a few with their year to date charts. Now, as an example, you can buy Amazon stock. Now, if you bought just about exactly a year ago you did really well, you probably saw around an 80% return or more. But if you want to jump in today, your mindset might be, hmm, well, okay. Amazon, they're going to be around for a long time, so it's kind of low risk and I like the stock, but you're probably going to get, well let's say, maybe a 10% annual return over the longterm, 15% or maybe less maybe single digits, but, maybe more than that but it's unlikely that any kind of reasonable timeframe within any reasonable timeframe you're going to get a 10X return. In order to get that type of return on invested capital, Amazon would have to become a $16 trillion valued company. So, you sit there, you asked yourself, what's the probability that Amazon goes out of business? Well, that's pretty low, right? And what are the chances it becomes a $16 trillion company over the next several years? Well, it's probably more likely that it continues to grow at that more stable rate that I talked about. Okay, now let's talk about Snowflake. Now, as you know, we've covered the company quite extensively. We watched this company grow from an early stage startup and then saw its valuation increase steadily as a private company, but you know, even early last year it was valued around $12 billion, I think in February, and as late as mid September right before the IPO news hit that Marc Benioff and Warren Buffett were going to put in $250 million each at the IPO or just after the IPO and it was projected that Snowflake's valuation could go over $20 billion at that point. And on day one after the IPO Snowflake, closed worth more than $50 billion, the stock opened at 120, but unless you knew a guy, you had to hold your nose and buy on day one. And you know, maybe got it at 240, maybe you got it at 250, you might have got it at higher and at the time you might recall, I said, You're likely going to get a better price than on day one, which is usually the case with most IPOs, stock today's around 230. But you look at Snowflake today and if you want to buy in, you look at it and say, Okay, well I like the company, it's probably still overvalued, but I can see the company's value growing substantially over the next several years, maybe doubling in the near to midterm [mumbles] hit more than a hundred billion dollar valuation back as recently as December, so that's certainly feasible. The company is not likely to flame out because it's highly valued, I have to probably be patient for a couple of years. But you know, let's say I liked the management, I liked the company, maybe the company gets into the $200 billion range over time and I can make a decent return, but to get a 10X return on Snowflake you have to get to a valuation of over a half a trillion. Now, to get there, if it gets there it's going to become one of the next great software companies of our time. And you know, frankly if it gets there I think it's going to go to a trillion. So, if that's what your bet is then you know, you would be happy with that of course. But what's the likelihood? As an investor you have to evaluate that, what's the probability? So, it's a lower risk investment in Snowflake but maybe more likely that Snowflake, you know, they run into competition or the market shifts, maybe they get into the $200 billion range, but it really has to transform the industry execute for you to get in to that 10 bagger territory. Okay, now let's look at a different asset that is cryptocurrency called Compound, way more risky. But Compound is a decentralized protocol that allows you to lend and borrow cryptocurrencies. Now, I'm not saying go out and buy compound but just as a thought exercise is it's got an asset here with a lower valuation, probably much higher upside, but much higher risk. But so for Compound to get to 10X return it's got to get to $20 billion valuation. Now, maybe compound isn't the right asset for your cup of tea, but there are many cryptos that have made it that far and if you do your research and your homework you could find a project that's much, much earlier stage that yes, is higher risk but has a much higher upside that you can participate in. So, this is how investors, all investors really look at their choices and make decisions. And the more sophisticated investors, they're going to use detailed metrics and analyze things like MOIC, Multiple on Invested Capital and IRR, which is Internal Rate of Return, do TAM analysis, Total Available Market. They're going to look at competition. They're going to look at detailed company models in ARR and Churn rates and so forth. But one of the things we really want to talk about today and we brought this up at the snowflake IPO is if you were Buffet or Benioff and you had to, you know, quarter of a dollars to put in you could get an almost guaranteed return with your late in the game, but pre IPO money or a look if you were Mike Speiser or one of the earlier VCs or even someone like Jeremy Burton who was part of the inside network you could get stock or options, much cheaper. You get a 5X, 10X, 50X or even North of a hundred X return like the early VCs who took a big risk. But chances are, you're not one of these in one of these categories. So how can you as a little guy participate in something big and you might remember at the time of the snowflake IPO we showed you this picture, who are these people, Olaf Carlson-Wee, Chris Dixon, this girl Sono. And of course Tim Berners-Lee, you know, that these are some of the folks that inspired me personally to pay attention to crypto. And I want to share the premise that caught my attention. It was this. Think about the early days of the internet. If you saw what Berners-Lee was working on or Linus Torvalds, in one to invest in the internet, you really couldn't. I mean, you couldn't invest in Linux or TCP/IP or HTTP. Suppose you could have invested in Cisco after its IPO that would have paid off pretty big time, for sure. You know, he could have waited for the Netscape IPO but the core infrastructure of the internet was fundamentally not directly a candidate for investment by you or really, you know, by anybody. And Satya Nadella said the other day we have reached maximum centralization. The main protocols of the internet were largely funded by the government and they've been co-opted by the giants. But with crypto, you actually can invest in core infrastructure technologies that are building out a decentralized internet, a new internet, you know call it web three Datto. It's a big part of the investment thesis behind what Carlson-wee is doing. And Andreessen Horowitz they have two crypto funds. They've raised more than $800 million to invest and you should read the firm's crypto investment thesis and maybe even take their crypto startup classes and some great content there. Now, one of the people that I haven't mentioned in this picture is Camila Russo. She's a journalist she's turned into hardcore crypto author is doing great job explaining the white hot defining space or decentralized finance. If you're just at read her work and educate yourself and learn more about the future and be happy perhaps you'll find some 10X or even hundred X opportunities. So look, there's so much innovation going around going on around blockchain and crypto. I mean, you could listen to Warren Buffet and Janet Yellen who implied this is all going to end badly. But while look, these individuals they're smart people. I don't think they would be my go-to source on understanding the potential of the technology and the future of what it could bring. Now, we've talked earlier at the, at the start here about NFTs. DeFi is one of the most interesting and disruptive trends to FinTech, names like Celsius, Nexo, BlockFi. BlockFi let's actually the average person participate in liquidity pools is actually quite interesting. Crypto is going mainstream Tesla, micro strategy putting Bitcoin on their balance sheets. We have a 2017 Jamie diamond. He called Bitcoin a tulip bulb like fraud, yet just the other day JPM announced a structured investment vehicle to give its clients a basket of stocks that have exposure to crypto, PayPal allowing customers to buy, sell, and Hodl crypto. You can trade crypto on Robin Hood. Central banks are talking about launching digital currencies. I talked about the Fedcoin for a number of years and why not? Coinbase is doing an IPO will give it a value of over a hundred billion. Wow, that sounds frothy, but still big names like Mark Cuban and Jamaat palliate Patiala have been active in crypto for a while. Gronk is getting into NFTs. So it goes to have a little bit of that bubble feel to it. But look often when tech bubbles burst they shake out the pretenders but if there's real tech involved, some contenders emerge. So, and they often do so as dominant players. And I really believe that the innovation around crypto is going to be sustained. Now, there is a new web being built out. So if you want to participate, you got to do some research figure out things like how PolkaWorks, make a call on whether you think avalanche is an Ethereum killer dig in and find out about new projects and form a thesis. And you may, as a small player be able to find some big winners, but look you do have to be careful. There was a lot of fraud during the ICO. Craze is your risk. So understand the Tokenomics and maybe as importantly the Pump-a-nomics, because they certainly loom as dangers. This is not for the faint of heart but because I believe it involves real tech. I like it way better than Reddit stocks like GameStop for example, now not to diss Reddit. There's some good information on Reddit. If you're patient, you can find it. And there's lots of good information flowing on Discord. There's people flocking to Telegram as a hedge against big tech. Maybe there's all sounds crazy. And you know what, if you've grown up in a privileged household and you have a US Education you know, maybe it is nuts and a bit too risky for you. But if you're one of the many people who haven't been able to participate in these elite circles there are things going on, especially outside of the US that are democratizing investment opportunities. And I think that's pretty cool. You just got to be careful. So, this is a bit off topic from our typical focus and ETR survey analysis. So let's bring this back to the enterprise because there's a lot going on there as well with blockchain. Now let me first share some quotes on blockchain from a few ETR Venn Roundtables. First comment is from a CIO to diversified holdings company who says correctly, blockchain will hit the finance industry first but there are use cases in healthcare given the privacy and security concerns and logistics to ensure provenance and reduce fraud. And to that individual's point about finance. This is from the CTO of a major financial platform. We're really taking a look at payments. Yeah. Do you think traditional banks are going to lose control of the payment systems? Well, not without a fight, I guess, but look there's some real disruption possibilities here. And just last comment from a government CIO says, we're going to wait until the big platform players they get into their software. And so that is happening Oracle, IBM, VMware, Microsoft, AWS Cisco, they all have blockchain initiatives going on, now by the way, none of these tech companies wants to talk about crypto. They try to distance themselves from that topic which is understandable, I guess, but I'll tell you there's far more innovation going on in crypto than there is in enterprise tech companies at this point. But I predict that the crypto innovations will absolutely be seeping into enterprise tech players over time. But for now the cloud players, they want to support developers who are building out this new internet. The database is certainly a logical place to support a mutable transactions which allow people to do business one-on-one and have total confidence that the source hasn't been hacked or changed and infrastructure to support smart contracts. We've seen that. The use cases in the enterprise are endless asset tracking data access, food, tracking, maintenance, KYC or know your customer, there's applications in different industries, telecoms, oil and gas on and on and on. So look, think of NFTs as a signal crypto craziness is a signal. It's a signal as to how IT in other parts of companies and their data might be organized, managed and tracked and protected, and very importantly, valued. Look today. There's a lot of memes. Crypto kitties, art, of course money as well. Money is the killer app for blockchain, but in the future the underlying technology of blockchain and the many percolating innovations around it could become I think will become a fundamental component of a new digital economy. So get on board, do some research and learn for yourself. Okay, that's it for today. Remember all of these episodes they're available as podcasts, wherever you listen. I publish weekly on wikibon.com and siliconangle.com. Please feel free to comment on my LinkedIn post or tweet me @dvellante or email me at david.vellante@siliconangle.com. Don't forget to check out etr.plus for all the survey action and data science. This is Dave Vellante for theCUBE Insights powered by ETR. Be well, be careful out there in crypto land. Thanks for watching. We'll see you next time. (soft music)