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

(upbeat music) >> 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.

(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.

>> 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.

>> 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)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante snowflake's eye-popping ipo this week has the industry buzzing we have had dozens and dozens of inbound pr from firms trying to hook us offering perspectives on the snowflake ipo so they can pitch us on their latest and greatest product people are pumped and why not an event like this doesn't happen very often hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll give you our take on the snowflake ipo and address the many questions that we've been getting on the topic i'm also going to discuss at the end of this segment an angle for getting in on the ground floor and investments which is not for the faint of heart but it's something that i believe is worth talking about now let's first talk about the hottest ipo in software industry history first i want to say congratulations to the many people at snowflake you know the big hitters yeah they're all the news slootman mooglia spicer buffett benioff even scarpelli interestingly you know you don't hear much about the founders they're quite humble and we're going to talk about that in some future episodes but they created snowflake they had the vision and the smarts to bring in operators that could get the company to this point so awesome for them but you know i'm especially happy for the rank and file and the many snowflake people where an event like this it really can be life-changing versus the billionaires on the leaderboard so fantastic for you okay but let's get into the madness as you know by now snowflake ipod at a price of 120. now unless you knew a guy he paid around 245 at the open that's if you got in otherwise you bought at a higher price so you kind of just held your nose and made the trade i guess you know but snowflakes value it went from 33 billion to more than 80 billion in a matter of minutes now there's a lot of finger pointing going on this is this issue that people are claiming that it was underpriced and snowflake left four billion dollars on the table please stop that's just crazy to me snowflakes balance sheet is in great shape thanks to this offering and you know i'm not sure jamming later stage investors even more would have been the right thing to do this was a small float i think it was around 10 percent of the company so you would expect a sharp uptick on day one i had predicted a doubling to a 66 billion dollar valuation and it ended up around 70. now the big question that we now get is is this a fair valuation and can snowflake grow into its value we'll address this in more detail but the short answer is snowflake is overvalued in my opinion right now but it can grow into its valuation and of course as always they're going to be challenges now the other comment we get is yeah but the company is losing tons of money and i say no kidding that's why they're so valuable we've been saying for years that the street right now is rewarding growth because they understand that to compete in software you need to have massive scale so i'm not worried in the least about snowflakes bottom line not yet eventually i'm going to pay much closer attention to operating cash flow but right now i want to see growth i want to see them grow into their valuation now the other common question we get is should i buy when should i buy what are the risks and can snowflake compete with the biggest cloud vendors i'll say this before we get into it and i've said before look it's it's very rare that you're not going to get better buying opportunities than day one of an ipo and i think in this case you will i remember back in 2015 it was i think it was the first calendar for quarter and servicenow missed its earnings and the stock got hit and we had the opportunity to interview frank slootman then ceo of servicenow right after that and i think it's instructive to hear what he said let's listen roll the clip well yeah i think that a lot of the high-flying cloud companies and obviously we're one of them you know we're we're priced to perfection right um and that's that's not an easy place to be for uh for for anybody and you know we're not really focused on that it's it's this is a marathon you know every quarter is one mile marker you can't get too excited about you know one versus the other we're really pacing ourselves we're building you know an enterprise that's going to be here for for a long time you know and after that we saw the stock drop as low as 50 today servicenow is a 450 stock so my point is that snowflake like servicenow is going to be priced to perfection and there will be bumps in the road possibly macro factors or other and if you're a believer you'll have opportunities to get in so be patient now finally i'm going to make some comments later but i'll give you the bumper sticker right now i mean i calculated the weighted average price that the insiders paid on the the s1 that they paid for snowflake and it came out to around six dollars a share and i heard somebody say on tv it was five dollars but my weighted average math got me to six dollars regardless on day one of the ipo the insiders made a 50x return on their investment if you bought on day one you're probably losing some money or maybe about even and there are some ground floor opportunities that exist that are complicated and may be risky but if you're young and motivated or older and have some time to research i think you'll be interested in what i have to say later on all right let's compare snowflake to some other companies on a valuation basis this ought to be interesting so this chart shows some high flyers as compared to snowflake we show the company the trailing 12-month revenue the market cap at the close of the 16th which is the day that snowflake ipod and then we calculate and sort the data on the revenue multiple of the trailing 12 months and the last column is the year-on-year growth rate of the last quarter and i used trailing 12 months because it's simple and it's easy to understand and it makes the revenue multiple bigger so it's more dramatic and many prefer to use a forward revenue uh but that's why i put the growth rate there you can pick your own projected revenue growth and and do the math yourself so let's start with snowflake 400 million dollars in revenue and that's based on a newish pricing model of consumption not a sas subscription that locks you in for a year or two years or three years i love this model because it's true cloud and i've talked about it a while so for a while so i'm not going to dwell on it today but you can see the trailing 12-month revenue multiple is massive and the growth rate is 120 which is very very impressive for a company this size zoom we put zoom in the chart just because why not and and the growth grade is sick so so who knows how that correlates to the revenue multiple but as you can see snowflake actually tops the zoom frothiness on that metric now maybe zoom is undervalued i should take that back let's see i think crowdstrike is really interesting here and as a company that we've been following and talking about quite a bit in my last security breaking analysis they were at a 65 x trailing 12-month revenue multiple and you see how that's jumped since they reported and they beat expectations but they're similar in size to snowflake with a slower growth rate in a lower revenue multiple so there's some correlation between that growth rate and the revenue multiple sort of now snowflake pulled back on day two it was down early uh this morning as you would expect with both the market being off and maybe some profit taking you know if you got in an allocation at 120 why not take some profits and play with house money so snowflake's value is hovering today it actually bounced back is hovering today you're just under 70 billion and that that brings the revenue multiple down a bit but it's still very elevated now if you project 2x growth let's say 100 for next year and the stock stays in some kind of range which i think it likely will you could see snowflake coming down to crowdstrike revenue multiples in 12 months it'll depend of course on snowflakes earnings reports which i'm sure are going to beat estimates for the next several quarters and if if it's growing faster than these others at that time it should command a premium you know wherever the market prices market's going to go up it's going to go down but we'll look at all these companies i think on a relative basis snowflakes still should command a premium at higher growth rates so you can see also in this chart you've got shopify awesome mongodb twilio servicenow and their respective growth rates shopify incredibly impressive [ __ ] and twilio as well servicenow is like the old dog in this mix so that's kind of interesting now the other big question we get is can snowflake grow in to its valuation this is a chart we shared with you a bit ago and it talks to snowflake's total available market and its expansion opportunity there tam expansion this is something we saw slootman execute at servicenow when everybody underestimated that company's value and i'll briefly explain here look snowflake is disrupting the traditional data warehouse and data lake markets data lake spending is relatively small it's under 2 billion but data lakes they're inexpensive and that's what made them attractive the edw market however the enterprise data warehouse market is it's much much larger now traditional edws they're they're big they're slow they're cumbersome they're expensive and they're complicated but they've been operationalized and are critical for companies reporting and basic analytics but they've failed to live up to their promise of the 360 degree view of the customer and real-time analytics you know i had a customer tell me a while ago that my data warehouse it's like a snake swallowing a basketball he gave me example where a change in a regulation this was a financial company it would occur and it would force a change in the data model in their data warehouse and they'd have to ingest all this new data and the data warehouse choked and every time intel came out with a new processor they'd rush out they'd throw more compute at the problem he called this chasing the chips now what snowflake did was to envision a cloud native world where you could bring compute to massive data volumes on an elastic basis and only pay for what you use sounds so simple but technically snowflakes founders and those innovations of that innovation of separating compute from storage to leverage the flexibility of the cloud it really was profound and clearly based on this week's performance was the right call now i'll come back to this in a bit now where we think snowflake is going is to build a data cloud and and you can see this in the chart where your data can be ingested and accessed to perform near real-time analytics with machine learning and ai and snowflake's advantage as we've discussed in the past is that it runs on any cloud and it can ingest data from a variety of sources now there are some challenges here we're not saying that snowflake is going to participate in all these use cases that we show however with its resources now we expect snowflake to create new capabilities organically and then do tuck-in acquisitions that will allow it to attack many more more use cases in adjacent markets and so you look at this chart and the third layer if that's 60 billion it means snowflake needs to extend into the fourth layer because its valuation is already over 60 billion it's not going to get 100 market share so we call this next layer automated decision making this is where real time analytics and systems are making decisions for humans and acting in real time now clearly data is going to be a pretty critical part of this equation now at this point it's unclear that snowflake has the capability to go after this space as much of the data in this area is probably going to live at the edge but snowflake is betting on becoming a data data layer across clouds and presumably at the edge and as you can see this market is enormous so there's no lack of tam in our view for snowflakes that brings us to the other big question around competition everybody's talking about this look a lot of the investment thesis behind snowflakes snowflake is that slootman and his army including cfo mike scarpelli and what they did at servicenow will be repeated scarpelli is this operational guru he keeps the engine running you know with very very tight controls and you know what it's a pretty good bet snoopman and scarpelli and their team i'm not denying that but i will tell you that snowflake's competition is much more capable than what servicenow faced in its early days now here's a picture of some of the key competitors this is one of our favorites the xy graph and on the vertical axis is net score or spending momentum that is etr's version of velocity based on their quarterly surveys now i'm showing july survey october is in the works it's in the field as i speak on the horizontal axis is market share or pervasiveness in the data set so it's a proxy for market share it's it's based on mentions not dollars and and that's why microsoft is so far to the right because they're huge and they're everywhere and they get a lot of mentions the more relevant data to us is the position of snowflake it remains one of the highest net scores in the entire etr survey based not just the database sector aw aws is its biggest competitor because most of snowflake's business runs on aws but google bigquery you can see there is is technically the most capable relative to snowflake because it's a true cloud native database built from the ground up whereas aws took a database that was built for on-prem par excel and brilliantly really made it work in the cloud by re-architecting many of the pieces but it still has legacy parts to it now here's oracle oracle's huge it's slow growth overall but it's making investments in r d we've talked about that a lot and that's going to allow it to hold on to its customers huge base and you can see teradata and cloud era cloudera is a proxy for data lakes which are low cost as i said and cloudera which acquired hortonworks is credited with the commercialization of that whole big datum and hadoop movement and then teradata is in there as well which of course they've been around forever now there are a zillion other database players we've heard a lot of them from a lot of them this week is on that inbound pr that i talked about but these are the ones that we wanted to focus on today the bottom line is we expect snowflakes vertical axis spending momentum to remain elevated and we think it will continue to steadily move to the right now let's drill into this data a bit more here we break down the components of etr's net score and this is specifically for snowflake over time now remember lime green is new adoptions the forest green is spending more relative to last year than more five percent more uh than last year or or greater gray is flat spending the pink is less spending and the bright red is we're leaving the platform the line up top that's netscore which subtracts the red from the green is an indicator of spending velocity the yellow line at the bottom is market market share or pervasiveness in the survey based on mentions now note the the blue text there that's etr's number one takeaway on snowflake two h-20 spending intentions on snowflake continue to trend robustly mostly characterized by high customer acquisition and expansion rates new adoptions market share among all customers is simultaneously growing impressive let's now look at snowflake against the competition in fortune 500 customers now here we show net score or again spending momentum over time for some of the key competitors and you can see snowflakes net score has actually increased since the april survey again this is the july survey this was taken the april survey was taken at the height of the us lockdown so snowflake's net score is actually higher in the fortune 500 than it was overall which is a good proxy for spend because fortune 500 spends more google mongodb and microsoft also also show meaningful momentum growth since the april survey you know notably aws has come off its elevated levels from last october and april it's still strong but that's something that we're going to continue to watch finally let's look at snowflakes market share or pervasiveness within the big three cloud vendors again this is a cut on the fortune 500 and you can see there are 125 respondents within the big three cloud and the fortune 500 and 21 snowflake respondents within that base of 125 and you can see the steady and consistent growth of share not huge ends but enough to give some confidence in the data now again note the etr callout but this trend is occurring despite the fact that each of the big three cloud vendors has its own competitive offering okay but i want to stress this is not a layup for snowflake as i've said this is not servicenow part two it's a different situation so let's talk about that look the competition here is not bmc which was servicenow's target as much as i love the folks at bmc we're talking here about aws microsoft and google amazon with redshift is dialed into this i've said often that they have copycatted snowflake in many cases and last fall at re invent we heard andy jassy make a big deal about separating compute from storage and he took a kind of a swipe at snowflake without mentioning them by name but let's listen to what andy jassy had had to say and then we'll come back and talk about it play the clip then what we did is because we have nitro like i was talking about earlier we built unique instances that have very fast bandwidth so that if you actually need some of those data from s3 for a query it moves much faster than if you just had to leave it there with without that high speed bandwidth instance and so with ra3s you get to separate your storage from your compute if it turns out by the way on your local ssds that you're not using all the ssd on that local ssd you only pay for what you use so a pretty significant enhancement for customers using redshift at the same time if you think about the prevailing way that people are thinking about separating storage from compute letting people scale separately that way as well as how you're going to do this large-scale compute where you move the storage to the a bunch of awaiting compute nodes there are some issues with this that you got to think about the first is think about how much data you're going to have at the scale that we're at but then just fast forward a few years think about how much data you're going to actually have to move over the network to get to the compute and we so look first of all jassy is awesome he stands up at these events for like reinvent for two hours and it connects trends and business to technology he's got a very deep understanding of the tech he's amazing however what aws has done in separating compute and storage is good but it's not as elegant architecturally as snowflake aws essentially has tiered the storage off the cluster to lower the overall costs but you really you can't turn off the compute completely with snowflake they've truly separated compute and storage and the reason is that redshift is great but it's built on an on-prem architecture that was originally an on-prem architecture that they had to redo so when jassy talks about moving the data to compute what he's really saying is our architecture is such that we had to do this workaround which is actually quite clever but this whole narrative about the prevailing ways to separate compute from storage that's snowflake and moving the data's use the word data's plural to the compute it really doesn't apply to snowflake because they'll just move the compute to the data thank you hadoop for that profound concept now does this mean snowflake is going to cakewalk over redshift not at all aws is going to continue to innovate so snowflake had better keep moving fast multi-cloud new workloads adjacent markets tam expansion etc etc etc microsoft they're huge but as usual there's not a lot to say you know about them they're everywhere they put out 1.0 products they eventually get them right because with their heft they get mulligans that they turn into pars or birdies but i think snowflake is going to bring some innovations to azure and that they're going to get good traction there in my opinion now google bigquery is interesting by all accounts it gets very high technical marks google's playing the long game and i would expect that snowflake is going to have a harder time competing in google cloud than it does within aws and what i'm predicting for azure but we'll see the last point here is that many are talking about the convergence of analytic and operational and transaction databases and the thinking is this doesn't necessarily bode well for specialists like snowflake and i would say a couple of things here first is that while it's definitely true you're not seeing snowflake positioning today as responding at the point of transaction to say for instance influence and order in real time and this may have implications at the edge it's going to have a lot of real-time inferencing but we've learned there are a lot of ways to skin a cat and we see integration layers and innovative approaches emerging in the cloud that could address this gap and present opportunities for snowflake now the other thing i'd say is you know maybe that thinking misses something altogether with the idea of snowflake in that third data layer that we showed you in our tam chart that data as a service layer or data cloud which is maybe a giant opportunity that they are uniquely positioned to address because they're cloud agnostic they've got the vision and they've got the architecture to allow them to very simply ingest data and then serve it up to businesses nonetheless we're going to see this battle continue between what i've often talked about these integrated suites and converged databases in the case of oracle converged pipelines in the case of the cloud guys versus the best of breed players like snowflake we talk about this all the time and there really isn't one single answer it's really horses for courses and customer preferences okay well you know i know you've been waiting for for me to tell you about the angles on ground floor investing and you probably think this is going to be crazy but bear with me and i got to caution you this is a bit tongue-in-cheek and it's one big buyer beware but as i said the insiders on snowflake had a 50x return on day one you probably didn't so i want to talk about the confluence of software engineering crypto cryptography and game theory powered by the underlying value of blockchain and we're talking here about innovations around a new internet in a distributed web or d-web where many distributed computers come together to form one computer that guarantees trust between two or more users for a variety of use cases not just financial store like bitcoin but that too and the motivation behind this is the fact that a small number of companies say five or six today control the internet and have essentially co-opted the major protocols like tcp http smtp pop3 etc etc and these people that we're showing here on this chart they're working on these new innovations there are many of them but i just name a few here olaf carlson we he started poly chain capital to invest in core infrastructure around these new computing paradigms this gentleman mark nadal is someone who's working on new d apps tim berners-lee who invented the internet he's got a project called solid at mit and it emphasizes data ownership and privacy and of course satoshi got it all started when she invented bitcoin and created the notion of fractional shares and by the way the folks at andreessen horowitz are actively making bets in this space so you know maybe this is not so crazy but here's the premise if you're a little guy and you wanted to invest in snowflake you couldn't until late in the game if you wanted to invest in the lamp stack directly in the late 90s there was no way to do that you had to wait for red hat to go public or to get a piece of the linux action but in this world that we're talking about here there are opportunities that are not mainstream and often they're based yes on cryptocurrencies again it's dangerous there are scams and and losers but if you do your homework there are actually vehicles for you to get in on the ground floor and you know some of these innovations are going to take off you could get a 50x or 100 bagger but you have to do your research and there's no guarantee that these innovations are going to be able to take on the big internet giants but there are people really smart technologists and software engineers that are young they're mission driven and they're forming a collective voice against a dystopian future because they want to level the playing field on the internet and this may be the disruptive force that challenges today's giants and if your game i would take a look at the space and see if it's worth throwing a few dollars at okay a little tangent from snowflake but i wanted to put that out there snowflake wow closes its first trading week as a company worth 66 billion dollars roughly the same as goldman sachs worth more than vmware and the list goes on i mean what's what's more is there to say other than remember these episodes are all available as podcasts so please subscribe i publish weekly on wikibon.com and siliconangle.com so please check that out and please comment on my linkedin post or feel free to email me at david.velante at siliconangle.com this is dave vellante for the cube insights powered by etr thanks for watching everyone we'll see you next time you

>> Announcer: Live from Nassau in the Bahamas, it's the Cube. Covering Polycon '18. Brought to you by Polymath. >> Welcome back, everyone. This is the Cube's exclusive coverage. We're live in the Bahamas, here for day two of our wall to wall coverage of Polycon '18. It's a security token conference, securitizing, you know, token economics, cryptography, cryptocurrency. All this is in play. Token economics powering the world. New investors are here. I'm John Furrier, Dave Vellante. Our next guest is Nithin Eapen Who's the Chief Investment Officer for Arcadia Crypto Ventures. Welcome to the Cube. >> Thank you very much gentlemen. >> Thanks for joining us. >> Thanks for coming out. >> Excited to have you on for a couple reasons. One, we've been talking since day one, lot of hallway conversations. Small, intimate conference, so we've had a chance to talk. Folks haven't heard that yet, so let's kind of get some of the key things we discussed. You are very bullish and long on cryptocurrency and Blockchain. You guys are doing a variety of deals. You're also advising companies and you guys are rolling your sleeves up. So kind of interesting dynamics. So take a minute to explain what you guys are doing, your model. >> Okay. >> And we're going to try to get some of your partners on later. You have a great team. >> Yep. >> Experienced pros in investing. And you got wales, you got pros. So you got a nice balance. >> Yes we do. >> So take a minute to explain Arcadia, your approach and philosophy. >> Okay. Okay. So Arcadia Crypto Ventures primarily we are a private fund. We invest other money. We believe in the whole crypto space. We believe this market is expanding and it is growing and it's going to be the biggest thing that ever happened. It's going to be this fusion of internet and PC and mobile. And everything is going to go batshit, okay. We believe in the whole tokenization world. Everything is going to be tokenized. So as a whole, we believe this space is going to go very big. Okay, so that's one piece and because of that, we invest in the space, the whole space. Not one bitcoin or Ethereum, but everything in the space that makes sense. People who have a use case. Now the second piece of it is we advised great founders. We want to get founders to come out and build these new things because this is the new internet of the new era and people have to come out and build these things. And so many of them are traditional businesses and we have to explain to them why this matters, why you should come to this space and be decentralized and reach the whole world. Because initially, the internet came. The idea of the internet was everybody gets information. Now information did get everywhere. You don't have to worry that the mailman is there to deliver your email anymore. Even if it's a Sunday, your mail will get delivered. So that part was good. But now you have these few companies that's holding all your data. It's okay for most people, but they do censor a lot of people. So that is one point. That censorship. We want a censorship-resistant world where everybody's ideas get out. So that way, we believe that's how this whole internet space itself is going to change because of that. See this is if I explained in one word, this is the greatest sociopolitical economic experimental revolution ever that has happened in humankind. >> In the history of the world. I mean this is important. I'd said that on my opening today. >> Uh-huh. >> Dave and I were riffing and Dave and I have always been studying. We've been entre-- We are entrepreneurs. We live in Silken Valleys in Boston and so you seeing structural change going on. So it's not just make money. >> Nope. >> There's mission-based, younger demographics. So you starting to see really great stuff. So I want to ask you specifically, 'cause you guys are unique in the sense that you're investing in a lot of things. But startups, pure-playing startups? >> Which had only one path before, or two paths. >> Right, yeah. >> Cashflow financing and venture capital. >> Okay. >> So that's a startup model. The growing companies that are transform their growth business with token economics, those would have long odds. Those are the best deals. >> Okay. Then there's like the third deal. Well we're out of business, throw the Hail Mary, repivot. (laughs) Right, so categorically, you're starting to see the shape of the kinds of swim lanes of deals. >> Okay. >> Okay, pivoting, that Hail Mary. Okay, you can evaluate that pretty much straight up on that. Startups need nurturing, right? >> Yeah. >> So the VC1 al-oc-chew works really well for startups because of the product market fits going to be developed. You got cloud computing so you can go faster. So you guys are nurturing startups. At the same time, you're also doing growth deals. >> We do. >> Explain the dynamic between those kinds of deals, how you guys approach them. What's the dynamic? What are the key things that you're bringing? Is it just packaging? Is it tech? So on, so forth. >> So with a lot of people, when they are on the advisory side. Primarily we look at the founder and the tech. What are they trying to solve? That is key. If it's a turd, you can't package it. No matter how you package it, that's not going to work. >> You can't package dog you-know-what. >> Yeah, exactly, okay. >> So that's one thing that we look at. The founders and their idea. Now their idea, can it be decentralized? Some models are meant to be centralized maybe so it doesn't work, okay. Like, see it all boils down to-- Let me break it down. We look at it. Okay, do you have an asset? Behind the scenes, is there an asset? Is that asset being transferred among parties? If you have an asset and it's being transferred, is there some central mechanism in between? Because if there is a central mechanism in between, that means you're going to be paying rent to that. Okay, all right. You have these things. Okay, great. Now you have your asset. Do you have that in between party? But in some of them, let's say you have money in your pocket. You walk, it falls down. Somebody else pick ups the money. It's his. It's a bearer asset, okay? So that's where bitcoin solved a very big problem. It was bearer asset. >> Unless they hack your wallet, then they take your money. >> Right. That happens in real life too, right? Somebody can take money from your wallet. So it can happen in bitcoin. They can hack your wallet. All right. So bitcoin was solving that problem. Now the second piece is a registered asset. And I mean by registered asset is take your car. You buy your car, you go to the DMV, stand in line, register. There's a record of data at the DMV in their central database. If somebody steals your car, the car is still not his. It's only if they can change the record over there in DMV. Then it becomes his. Now there maybe you do want the DMV to be there. Or maybe we can-- But the DMV being there, now you have a problem. They're going to charge you rent and they can decide, oh you know what? John, I'm not going to give him a license or a car in the state of California. They can decide, right? So that is where now you decide do you want to go the centralized route or the decentralized route? So we break it down to the asset. >> So there could be a fit for decentralized. I get that. >> Yeah. >> Let me ask you a tactical question, because I know a lot of entrepreneurs out there. They're watching and they'll hear this. A big strategic decision up front is, obviously, token selection. >> So it's pretty clear that security token works really well for funding and whatnot. Then there's a role for security tokens. I mean utility tokens. >> Yes. >> So do people, should they start from a risk management standpoint, a new company. So let's just say we had an existing business. Entrepreneur says, "Hey, you know what? We're doing well. We're doing 10 million dollars in revenue and I want to do tokenize 'cause we're a decentralized business. That's a perfect fit." Do they start a new company or do they just use the security token with their existing stable company? >> I would suggest, usually at that time, that's more of a legal question at that time. I don't know if I'm a lawyer to answer that. I tell them, you have a business. The business model is going well. If you're happy with it, let that be there. Make a new company. If your business model was not doing good, you might as well start from there because you figure out it's not working. But again, at that time, we tried to come up with this question. Are you trying to put the old wine in a new bottle kind of thing? If the wine is old, it ain't going to work. You have to get to that realization. So, here. >> People are being sued. So mainly the legal question is do I want to risk being. >> All right, let me hop in here. I wanted to ask, go back to something you said about censorship. I had this conversation with my kid the other day. I was explaining Google essentially censors your search results based on what they think you're going to click on. >> They do that. >> He's like no and then he thought about it and he's like okay, yeah they kind of do that. Okay, so that's an underpinning of we're going to take back the internet, right? >> Yeah. >> Okay, I just wanted to sort of clarify that. From an investment philosophy standpoint, you're technical, yet you don't exclusively vet or invest in infrastructure protocols and dig deep into what-- You read the white papers, but there are some folks out there hedge funds, et cetera. All they do is just invest in utility tokens. They're trying to invest in stuff that's going to be infrastructure for the next internet. Your philosophy is different. You're saying, we talked about this, we don't really know what's going to win, but we make prudent investments in areas that we think will win. We like to spread it around a little bit. Why that philosophy? May reduce your return, but it also reduces your risk. Maybe you could describe that a little bit. >> Sure. See, in general, picking winners in the long run has been-- It's a proved fact that nobody could pick winners. Like if you take active hedge fund managers. Active hedge fund managers, in the long run, if you take 10 to 20 years, they lag the S and P. So if you had money, if you give it to an active hedge fund manager, and so that you just had to buy the S and P, you will have beaten 93%. >> That's Buffet's advice. Buy an S and P 500. >> Buffet made a bet for a billion dollars or something where, you know. So take Warren Buffet for that matter, his fund is lagging too. In reality, all his stock investments are down. He put it in IBM at $200 after eight years, it's at the 143 or something, right? So realistically,-- There's a lot of luck element, okay. You can do all of the analysis and you could still end up buying Enron, Lehman, and Bear Stearns, right? >> Right, yeah. >> And at that time, see they were using some models that they knew 'til then. Most people, investment comes from, you have this background that you know, okay this is what I look at. Cash flow, discounted cash flow. Great. If that is there, price to earnings, I'm going to buy. But then an Amazon came, most of the traditional investors never invested in Amazon. They were like, it's a loss- making company. They never going to survive. But they forgot the fact that companies like that there's this network effect and once the people are there, at any point, Jeff Bezos can just turn off the switch and take off the discount. You're not going to change your shopping from Amazon at that point because this month I lost my 15%. We're so used to it so people missed that. Nowadays they see that, but when it came to Blockchain they're like, oh, no, no, this is a fad. That's what most people said. >> So we talked about discounted cashflow as a classic valuation method. I see guys trying to do DCF on these investments. I mean, we were joking about that. (laughs) How do you-- What's your reaction to that? >> If anybody's saying that if they come to me and I'm like you-- I don't know what Kool-Aid do you drink at that point because what cashflow are they discounting? There's no cashflow. It's not like you're going to get dividends from these tokens. There's no dividends. It's like can you find out how many people are going to use it. What is the network effect? And again, for that, a lot of people are coming with a lot of these matrices or matrix right now. But I think even that, they're trying to retrofit into it. They're like, oh I can use this matrix. But, really we don't know. >> So people tend to want metrics. Dave and I talk about this all the time. When people part with their money, they need to know what they're betting on. So the question is when you look at investments, when you spend cash, when you write checks, what is your valuation technique? Do you look for the l-- How do you play that long game? What's the criteria? Besides like the normal stuff like founders, disruptive, like you got to write the check, let's say. Okay, buying a token. It's got to be worth something in the future, obviously. >> So we look at that space, where invariably they are trying to disrupt. Is there a big market? And even if it's a niche market, okay? So we're doing an error chain token. It's a very niche market. It's just the pilot, the maintenance folks, and the charter people, or the plain charter guys. It's a very small market, but that's good enough. It's very niche. They can have an ecosystem between themselves rather than being incentivized to long game miles and stuff like that, right? It doesn't have to be a very big market. We just look at it, okay. Founder is good, he has an idea, it is a space that can be decentralized and people can come in and they feel that they're part of the ecosystem. See the whole thing with the token economy and a traditional economy like let's say I'm spending money to buy a stock. So I buy stock. As an investor, what do I want? I want maximum returns. The employee, he wants to get maximum pay. And the consumer who's buying the product, he wants to get it at the cheapest price. So there's a-- It start aligned, okay? The moment you give 'em the cheapest price, my profits go down. If I increase the employees' salary, my profits go down. So we are all three of us are totally misaligned. >> If I for an important point, do you favor certain asset classes, you know, token, security tokens, or utility tokens, or you looking for equity? I mean, maybe just ... >> Right now, we've moved away from the whole equity bonds, or any of those things. We are totally concentrated on the utility or security tokens. We don't mind if it's a security token or utility token. >> And if it's a security token, are you looking for dividends, are you looking for >> At that point it's some kind of dividend. >> So you're not expecting equity as part of that security token? >> No, I like to expect equity, but if they are saying okay my token, if people buy and if they pay me $10, and out of that you're going to get $1 back, okay that's fine. We don't mind that as long as it's legal and all those things we're fine because it just makes the process easier. Earlier you invest and you didn't know when you could get out of your investment. At this point, it's become so liquid, at any point of time within two or three months, the token is less to people are either buying and selling. We know, otherwise, earlier when we used to do Ren Chain investments, we would get into our product, have it it's time seven to 10 years to get out. And in the meanwhile, they say great stories. Oh we're doing great. Who do I check with that we are doing great? I'm not getting any dividends. Nobody's buying this from me. How do I know? Where am I? I really don't know. I can make these values up and on my Excel sheet and say okay we valuing this company at a billion. >> So your technique is to say okay look at the equity plays the long game. You need an exit on liquidity, either M and A or IPO. >> Yes. >> Now you have a new liquidity market, so you play the game differently. I won't say spray and pray, but you have multiple bets going on so you can monitor liquidity opportunity. So that's a new calculation. >> And it's a great calculation, also. Because see we're in the market and now we know at any point of time, we don't have things on our books that are like we don't know what the value is. We know what that price is because the market is there, the exchange is there. What other people are willing to pay for us doesn't surprise. It's like saying my house is worth a million dollars. Actually it might be worth to me. It depends on what people are willing to pay me. >> Right exactly. >> If I have to synthesize this, you're taking high frequency trading techniques with classic venture investing, handling token from those two perspectives. >> Yes. >> High frequency trading meaning I'm looking at volatility and then option to abandon and get rid of whatever or whatever. >> The only thing is, we're not exiting our positions. We are in the long game. We believe the score market is supposed to at least reach eight trillion. When we started this whole investing, at that time, the whole market was at six billion and we said okay this market, based on our thesis, is supposed to reach eight trillion. Until then, we keep buying, okay? >> But to your HFT, you're not really arbitraging. >> No, no, we're not doing any of those. Because see >> They're applying real time techniques to token evaluations so they're game is try to get into a winner. >> Yes. >> With some tokens. >> A lot of the funds, they're doing this arbitrage more. They're trying to do arbitrage. But the problem is they're missing the big picture that way. So, arbitrage works in a very tight market. So S and P, let's say, somebody's doing 5% return on S and P. The guy with a arbitrage is coming and saying I made five point three, 5.5% or 6%. That's great in the equity world. Now, I want returns last year are 10 x or 30 x or 50 x. And somebody comes and tells me I made an extra 0.2%, doesn't really matter to me. I'm like instead of wasting that time doing arbitrage and paying taxes, I might just hold it. >> You believe in the fundamentals. >> You guys are in New York. Obviously, Arcadia Crypto Ventures, that's how they get ahold of you guys. Final question for you to end the segment. As new real pros come in, and let's take New York as a since you're in New York. The New York crowd comes in or the Silken Valley comes crowd existing market players other markets come in here. How important is optics packaging and compatibility with the sector, meaning I just can't throw my weight around on the hedge fund scene. We do it this way, I got money. Because people here have money. So what's the dynamic of pros coming in, we're seeing institutional folks come in, we're seeing real pros come in. They've never been to Burning Man. So, you know, they get that Burning Man culture exists, but this is not a Burning Man industry. >> Right, right. >> Business doesn't run like Burning Man. Maybe it should, that's a debate we'll have. Your take. >> So the new funds that are coming in, so they have a fear that they have missed out. They are missing the picture that this is just the beginning. So they've seen that this industry has gone from six billion to 500 billion in a year or year and a half. They're like, oh my god, I missed it. >> It's got to be over. >> So I have to write these big checks to get this. We don't write big checks. We write much smaller checks because we believe that if a founder is raising money, he has to raise it through small checks from everybody. That means all those people are really interested in this. And they're all of them really want the token to go up. Whether it's the investor, the user, and the employee who is working there because all of them they're interests are aligned. The moment you give a big check, so let's say you could raise 10 million from 10,000 people or you could raise it from one person. So when the big check is there, let's say I go to raise my money. There's this fund who's missed it and he says here's 10 million dollars. Okay, now I've got me and the fund and my tokens. Nobody else knows about my tokens. My tokens are as good as valueless. Now the funders looking okay, I need to exit. Nobody knows about my tokens. The fund is the only guy who has my tokens, he's trying to exit. Obviously the market is going to crash. There's no market. And he's like why did I get into this. So he missed that point that you need people around you. It's not just you alone. See, earlier days when ... >> This is your point about understanding how token economics works. >> Yes. >> So having more people in actually creates a game mechanic for trading. >> Because then you know that you're not the only guy interested in this. And earlier venture capital space there were these bunch of few venture capitals who wanted to capture that whole thing and tried to sell it to the next guy. Here, I'm what I'm saying is, we all have to come in together. We all can be together at the same price, which is good because the small person has, the common man has a chance to be a VC right now. Earlier you could never be a VC. I could only see Google, after IPO. I could never get it at what KPCB or Sequoia got it at. I had to wait 'til they got through CDA, CDB, which they bought at five cents. I would get at about $40 maybe. In this case, the big fund has a lot more money than me, but I can have my small 5,000 or 10,000. I can invest in the ICO. >> If you picked the right spot and you were there at the right place, the right time. 'Cause you are seeing guys come in and try to buy up all the tokens early on. >> They're trying to do that. They don't get it, but they will understand. So it is a learning (mumbles). Even they will evolve. They're like okay this is not how it works. And you have to make mistakes. >> Sorry, got to ask you one final, final since you brought it up. More people the better. So we're hearing rumors inside the hallways here that big wales are buying full allocations and then sharing them with all their friends. >> Possible, it is possible. >> We see some of that behavior. Dave calls it steel on steel, you know. Groups, you know. I'm going to take this whole deal down. We see that in venture capital. Used to be syndicates. Now you seeing Andreessen Horowitz doing the whole deals. That kind of creates some alienation, my opinion, but what's your take on that? I'm a big wale. I'm taking down the whole allocation. >> It's okay. Some of those things are going to happen, okay. It is fine. The only problem is usually when that happens the big wale who takes it he will realize very quickly. >> He's got to get more people. >> He needs more people otherwise he might be able to exit to his five buddies who were always taking it from him. Now those guys, they also have to exit at some point. Nobody knows about the product. Might as well just take a small piece, even the founders in this case typically in a token model. Founders who've taken 20% or 10% have done better than founders who took 60% of the whole tokens. >> Right. Nithin, great to have you on. Love your business model. Arcadia Crypto Ventures. They got real pros, they got a wale, they got people who know what they're doing, and they're active. They understand the ethos. I think you guys are well-aligned and you're not trying to come in and saying this is how we did it in New York before. You get the culture. You're aligned and you're making investments. Great perspective. Thanks for sharing. >> Thank you so much. >> This is the Cube, bringing the investor perspective live here in the Bahamas. More exclusive Cube coverage. Token economics, huge opportunity for entrepreneurs and investors to create value and capture it. That's Blockchain, that's crypto, that's token economics. I'm John with Dave Vallante. We'll be back with more coverage after this short break. (futuristic digital music)

>> Narrator: Live from Nassau in the Bahamas. It's The Cube! Covering PolyCon 18. Brought to you by PolyMath. >> Welcome back everyone, we're live here in the Bahamas with The Cube's exclusive coverage of PolyCon 18, I'm John Furrier with my co-host Dave Vellante, both co-founders of SiliconANGLE. We start our coverage of the crypto-currency ICO, blockchain, decentralized world internet that it is becoming. It's the beginning of our tour, 2018. Our next guest is Hartej Sawhney who's the advisor at Pink Sky Capital, but also the co-founder of Hosho.io. Welcome to The Cube. >> Thank you so much. >> Hey thanks for coming on. Thanks for coming on. >> Thanks guys. >> We had a great chat last night, and you do some real good work. You're one of the smartest guys in the business. Got a great reputation. A lot of good stuff going on. So, take a minute to talk about who you are, what you're working on, what you're doing, and the projects you're involved in. >> So first of all, thank you so much for having me, it's really exciting to see the progress of high-quality content being created in the space. So my name is Hartej Sawhney. We have a team based in Las Vegas. I've been based in Las Vegas for about five years. But I was born and raised in central New Jersey, in Princeton. And my co-founder is Yo Sup Quan. We started this company about seven months ago and my co-founder's background was he's the co-founder of Coin Sighter in Exchange out of New York, which exited to Kraken. After that he started Launch Key which exited to Iovation. And prior to this company, my previous company was Zuldi, Z-U-L-D-I .com where we had a mobile point of sale system specifically for high volume food and beverage companies and businesses. So we were focused on Fintech and mobile point of sale and payment processing. So both of us have a unique background in both Fintech and cyber-security and my co-founder Yo, he's a managing partner of a crypto hedge fund named Pink Sky Capital. And he was doing diligence for Pink Sky, and he realized that the quality of the smart contracts he was seeing for deals that he wanted to participate as an investor in, and I'm an advisor in that hedge fund, we both realized that essentially the quality of these smart contracts is extremely low. And that there was nobody in this space that we saw laser focused on just blockchain security. And all the solutions that would be entailed in there. And so we began focusing on just auditing smart contracts, doing a line-by-line code review of each smart contract that's written, conducting a GAS analysis, and conducting a static analysis, making sure that the smart contract does what the white paper says, and then putting a seal of approval on that smart contract to mitigate risk. So that the code has not been changed once we've done an analysis of it, that there's no security vulnerabilities in this code, and that we can mitigate the risks for exchanges and for investors that someone has done a thorough code analysis of this. That there's no chance that this is going to be hacked, that money won't be stolen, money won't be lost, and that there's no chance of a security vulnerability on this. And we put our company's name and reputation on this. >> And what was the problem that is the alternative to that? Was there just poorly written code? Was it updated code? Was it gas was too expensive? They were doing off-chain transactions. I mean what are some of the dynamics that lead you guys down this path? I mean this makes sense. You're kind of underwriting the code, or you're ensuring it or I don't know what you call it, but essentially verifying it. What was the problem? And what were some of the use cases of problems? >> I would say that the underlying problem today in this whole industry, of the blockchain space, is that the most commonly found blockchain is Ethereum. The language behind Ethereum is called Solidity. Solidity is a brand new software language that very few people in the world are sufficient programmers in Solidity. On top of that, Solidity is updated, as a language on a weekly basis. So there are a very limited number of engineers in the world who are full-stack engineers, that have studied and understand Solidity, that have a security background, and have a QA mindset. Everything that I just said does exist on this Earth today and if it does, there's a chance that that person has made too much money to want to get out of bed. Because Ethereum's price has gone up. So the quality of smart contracts that we're seeing being written by even development shops, the developers building them are actually not full-stack engineers, they're web developers who have learned the language Solidity and so thus we believe that the quality of the code has been significantly low. We're finding lots of critical vulnerabilities. In fact, 100% of the time that Hosho has audited code for a smart contract, we have found at least a couple of vulnerabilities. Even as a second or the third auditor after other companies conduct an audit, we always find a vulnerability. >> And is it correct that Solidity is much more easy to work with than say, Bitcoin scripting language, so you can do a lot more with it, so you're getting a lot more, I don't want to say rogue code, but maybe that's what it is. Is that right? Is that the nature of the theory? >> Compared to Bitcoin script, yes. But compared to JavaScript, no. Because Fortune 500 companies have rooms full of Java engineers, Java developers. And now the newer blockchains are being written, are being written on in block JavaScript, right? So you have IBM's Hyperledger program, you have EOS, you have ICX, Cardano, Stellar, Waves, Neo, there's so many new projects that are coming, that all of them are flexing about the same thing. Including Rootstock, RSK. RSK is a project where they're allowing smart contracts to be tied to the Bitcoin blockchain for the first time ever. Right, so Fortune 500 companies may take advantage of the fact that they have Java developers to take advantage of already, that already work for them, who could easily write to a new blockchain, and possibly these new blockchains are more enterprise grade and able to take more institutional capital. But only time will tell. And us as the auditor, we want to see more code from these newer blockchains, and we want to see more developers actually put in commits. Because it's what matters the most, is where are the developers putting in commits and right now maximum developers are on the Ethereum blockchain. >> Is that, the numbers I mean. Just take a step there. So the theory of blockchain. Percentage of developers vis-a-vis other platforms percentages-- >> By far the most is on developed on Ethereum. >> And in terms of code, obviously the efficiencies that are not yet realized, 'cause there's not enough cycles of coding going on, it's evolution, right? >> Yes. >> Seems to be the problem, wouldn't you say? So a combination of full-stack developer requirements, >> Yes. >> To people who aren't proficient in all levels of the stack. >> Yes. >> Just are inefficient in the coding. It's not a ding on the developers, it's just they're writing code and they miss something, right? Or maybe they're not sufficient in the language-- >> It's a new language. The functions are being updated on a weekly basis, so sometimes you copied and pasted a part of another contract, that came from a very sophisticated project, so they'll say to us, well we copied and pasted this portion from EOS, so it should be great. But what that's leading to is either A, they're using a function that's now outdated, or B, by copying and pasting someone else's code from their smart contract, this smart contract is no longer doing what you intended it to do. >> So now Hartej, how much of your capability is human versus machine? >> Yeah I was going to ask that. >> ML, AI type stuff? >> So we're increasingly becoming automated, but because of the over, there's so much demand in the space. And we've had so much demand to consistently conduct audits, it's tough to pull my engineers away from conducting an audit to work on the tooling to automate the audit, right? And so we are building a lot of proprietary tooling to speed up the process, to automate conducting a GAS analysis, where we make sure you're not clogging up the blockchain by using too much GAS. Static analysis, we're trying to automate that as fast as possible. But what's a bit more difficult to automate, at least right now, is when we have a qualified full-stack engineer read the white paper or the source of truth and make sure the smart contract actually does it, that is, it's a bit longer tail where you're leveraging machine learning and AI to make that fully automated. (talking over each other) >> But maybe is that, I'm sorry John. Is that the long term model or do you think you can actually, I mean there's people that say augmented intelligence is going to be a combination of humans and machines, what do you think? >> I think it's going to be a combination for a long time. Every single day that we audit code, our process gets faster and faster and faster because once we find a vulnerability, finding that same vulnerability next time will be faster and easier and faster and easier. And so as time goes on, we see it as, since the bundle of our work today is ICOs, token generation events, there are ERC 20 tokens on the Ethereum blockchain. And we don't know how long this party will last. Like maybe in a couple years or a couple months, we have a big twist in the ICO space that the numbers will drastically go down. The long tail of Hosho's business for us, is to keep track of people writing smart contracts, period. But we think they are going to become more functional smart contracts where the entire business is on a smart contract and they've cut out sophisticated middle men. Right and it may be less ICOs, and in those cases I mean, if you're a publicly traded company, and you're going from R&D phase where you wrote a smart contract and now actually going to deploy it, I think the publicly traded company's going to do three to five audits. They're going to do multiple audits and take security as a very major concern. And in the space today, security is not being discussed nearly as much as it should. We have the best hedge funds cutting checks into companies, before the smart contract is even written, let alone audited. And so we're trying to partner with all the biggest hedge funds and tell the hedge funds to mandate that if you cut a check into a company that is going to do a token generation event, that they need to guarantee that they're going to at least value security, both in-house for the company and for the smart contract that's going to be written. >> How much do you charge for this? I mean just ballpark. Is it a range of purchase price, sales price? What's the average engagement go for, is it on a scope of work? Statement of work? Or is it license? I mean how does it work? >> So first it depends is it a penetration test of the website or the exchange? Penetration testing of exchanges are far more complex than just a website. Or if it's a smart contract audit, is it an ICO or is it a functional smart contract? In either case for the smart contract audit, we have to build a long set of custom tooling to attack each and every smart contract. So it's definitely very case-by-case. But a ballpark that we could maybe give is somewhere around the lines of 10 to 15 thousand dollars per 100 lines of functional code. And we ask for about three weeks of lead time for both a smart contract audit and a penetration test. And surprisingly in this space, some of the highest caliber companies and high caliber projects with the best teams, are coming to us far too late to get a security audit and a penetration test. So after months of fundraising and a private pre-sale and another pre-sale, and going and throwing parties and events and conferences to increase the excitement for participating in their token sale, what we think is the most important part, the security audit for a smart contract is left to the last week before your ICO. And a ridiculous number of companies are coming to us within seven days of the token sale, >> John: Scrambling. >> Scrambling, and we're saying but we've seen you at seven conferences, I think that we need to delay your ICO by two or three weeks. We can assure you that all of your investors will say thank you for valuing security, because this is irreversible. Once this goes live and the smart contract is deployed. >> Horse is out of the barn. >> It's irreversible. >> Right right. >> And once we seal the code, no one should touch it. >> It's always the case with security, it's bolted on at the last minute. >> It's like back road recovery too, oh we'll just back it up. It's an architectural decision we should have made that months ago. So question for you, the smart contract, because again I'm just getting my wires crossed, 'cause there's levels of smart contracts. So if we, hypothetical ICO or we're doing smart contracts for our audience that's going to come out soon. But see that's more transactional. There's security token sales, >> Yes. >> That are essentially, can be ERC 20 tokens, and that's not huge numbers. It could be big, but not massive. Not a lot transaction costs. That's a contract, right? That's a smart contract? >> People are writing smart contracts to conduct a token generational event, most commonly for an ERC 20 token, that's correct. >> Okay so that's the big, I call that the big enchilada. That's the big-- >> Right now that is the most important, the most common. >> Okay so as you go in the future, I can envision a day where in our community, people going to be doing smart contracts peer-to-peer. >> Sure. >> How does that work? Is that a boiler plate? Is is audited, then it's going to be audited every time? Do the smart contracts get smaller? I mean what's your vision on that? Because we are envisioning a day where people in our audience will say hey Hartej, let's do a white paper together, let's write it together, have a handshake, do a smart contract click, click. Lock it in. And charge a dollar a download, get a million downloads, we split it. >> I envision a day where you can have a more drag and drop smart contract and not need a technical developer to be a full-stack engineer to have to write your smart contract. Yes I totally envision that day. >> John: But that's not today. >> We are very far from that today. >> Dave, kill that project. >> We're so far, we're very far from that. We're light years far from that. >> Okay well look. If we can't eliminate the full-stack engineers, I'm okay with that. Can we eliminate the lawyers? At least minimize them. >> We can minimize them possibly, but we have five stacks of lawyers for our company, I don't see them going anywhere. We need lawyers all the time. >> I see that in the press sometimes, yeah it's going to get disrupted. I don't see it happening. Okay we were having a great conversation off-camera about what makes a good ICO. You see, you have a huge observation space. And you were very opinionated. A lot of companies are out there just floating a token because they're trying to raise money. And they could do the same thing with Ethereum or Bitcoin. >> That's correct. >> Your thoughts? >> My thoughts are that it's very important for companies who are sophisticated, I think, to start by giving away a little bit of equity in the business. And that if you want to be in the blockchain space, and you really firmly believe you have a model to have a token within a decentralized application, I would still start by finding quality investors in the space, in the world. They might be still in Silicon Valley. Silicon Valley didn't just disappear overnight now that the blockchain is out. I am all for the fact that Silicon Valley no longer has as much of a grip on tech because of their blockchain world. And they're not seeing as much deal flow, and there's not as much reliance on venture capitalists, that's exciting to me. But let's not forget the value, that top-tier VCs like Andreessen Horowitz and Vinod Khosla. and Fintech VCs like Commerce Ventures and Nyca Partners in New York, Propel VC, these are good Fintech VC arms that continue to time and time again add immense value to companies. >> And they have networks. They add value. >> They have strong-valued networks, but they're just not going to disappear. And those VCs, if they've invested into a company, took a board seat, fostered their growth, taught them what it means to actually be a real business that's growing at 7-15% week over week, maybe two years down the line, after they've given away a board seat to someone like Nyca Partners, I would be interested in understanding what your token economics look like. Now that you have a revenue generating business, how you've placed a token model into this already running business that makes 25 to 50 grand a month and you have a team of 10, self-sustaining themselves off of revenue. Much more intriguing of a conversation. What's happening today in the space is, hey my buddy Jim and Steve and I came up with an idea for this business. There's going to be a token, and we're starting a private pre-sale tomorrow. I'm going to give you 300% bonus and will you be my advisor? And they're going to start raising capital because of an idea. You know what we used to say in the Silicon Valley startup world, you can raise on just a PowerPoint. I think in the blockchain world, you could raise on just an idea? And then maybe a white paper? And the white paper is one page? And so you've raised a bunch of capital, you have a white paper. >> Now you got to build it. >> Now you got to build, you got to write a smart contract, you got to build it, you got to do it, and then everyone loses excitement and it goes back to our previous conversation the development talent. So, another thing not being discussed in the space is company employee retention, right? So if you have a growing number of ICOs, that have very large budgets because investors have found a way to sink millions of dollars into a company early, you've got $5 million in the hands of a company to start, well this company can afford to pay someone a very ridiculous salary to come join them to write the smart contract now. So they could offer an engineer 500 Eth a month to come join them for three months. So you have good engineers just bouncing from one ICO to the next and as soon as the ICO goes live, they quit. This is a problem to companies who are-- >> It's migration, out migration. >> How do you retain, even capital? >> Companies like Hosho, ShapeShift, companies that are selling picks and shovels of the industry, that want to be household names in the space, we have to really think about how we're going to retain our employees in the space. >> So the recruitment and bringing on the new generation, we were also talking off camera about Bill Tye and the younger generation and kind of riffing on the notion that, because there is a new set of mission-driven developers and builders, on the business side as well. Your thoughts and reaction to what you see and what you see that's good and what you see that we need more of? >> So the most powerful thing in the blockchain space that I think is so exciting is that you have a lot of people between the age of 25 and 35 that don't come from money, that didn't go to Stanford, didn't go to Y Combinator, they're probably not white, from-- >> John: Ivy League schools. >> Ivy League schools. I'm not trying to make it about race, but if you're a white male and went to Stanford and went to Y Combinator, chances of you raising VC money on sand hill are a lot higher, right? And you have a guy looking like me who didn't go to Stanford, doesn't come from money, running up and down sand hill, I have personally faced that battle and it wasn't easy. And we were based in Vegas and so being based in Vegas, I'd also have to deal with so why do you live in Vegas? When are you going to move to Silicon Valley? And if we invest in you, you're going to open an office in sand hill right? And now in the blockchain world, what's exciting is you have so many heavy-hitters running as founders, some of the most successful companies in the space, who don't come from money and a big prestigious background, but they're honest, they're hard-working, they're putting in 12 to 15 hours of work every single day, seven days a week. And to space, six weeks is like six years. And we all have a level of trust that goes back to times when we were all running struggling startups. And so our bond is, to me, even more significant than what must have been between Keith Rabois and Peter Thiel in the PayPal Mafia. We have our own mafias being formed of much stronger bonds of younger people who will be able to share much more significant deal flow so if the PayPal Mafia was able to join forces to punch out companies like eBay and Square, wait 'til companies in this space, we have young, heavy-hitters right now who are non-reliant on some of the more traditional older folks. Wait 'til you see what happens in the next couple years. >> Hartej, great conversation. And I want to get one more question in. We've seen Keiretsu Forum, mafias, teams more than ever as community becomes an integral part of vetting and by the way trust, you have unwritten rules. I mean baseball, Dave and I used to do sports analogies. >> Self-governance. >> Reggie Jackson talked about unwritten rules and it works. If you beam the batter, the other guy, your best star, your side's going to get beamed. That's an unwritten rule. These are what keeps things going, balanced through the course of a season. What are the unwritten rules in the Ethos right now? >> Honesty, transparency, and that's the key. We need self-governance. This is a very unregulated market. There's rules being broken by people who are ignorant to the rules. The most common rule I've seen being broken is by people who are not broker dealers, running around fundraising capital, they don't even know what an institutional advisor license is. They don't know what a Series 7 and a Series 63 is. I asked a guy just last night, he said I'm pooling capital, I'm syndicating, let me know if you want in on the deal. And I said when did you take your Series 7? He goes what's that? Get away from me. You're an American, you need to look up what US securities laws are and make sure that you're playing by the rules and if someone who doesn't know the rules has entered our inner circle of investors, of advisors, of people sharing deal flow, we have a good network of people that are closing the loop for companies, whether it's lawyers, investors, exchanges, security auditors, people who write smart contracts, dev shops, people who write white papers, PR marketing, people who do the road show, there's a full circle-- >> So people are actually doing work to put into the community, to know your neighbor if you will, know the deals that are going down, to identify potential trip wires that are being established by either bad actors or-- >> KYC, AML, this is a new space that's also attracting people that have a criminal background. Right? And that's just a harsh reality of the space. That in the United States if you have a felony on your record, maybe getting a job has become really difficult and you figured let's do an ICO, no one's going to check my record. That is a reality of the space. Another reality is the money that was invested into this entire ICO clean. Right, that's a massive issue for the US government right now. It's been less than 15 hours since the SEC has issued actually subpoenas to people on this exact topic, today. >> This is a great topic, we'd like to do more on. >> Dozens of them. >> We'd like to continue to keep in touch with you on The Cube. Obviously you're welcome anytime, loved your insight. Certainly we'd love to have you be an advisor on our mission, you're welcome anytime. >> For sure, let's talk about it. Come out to Las Vegas. Hosho's always happy to host you. >> John And Dave: We're there all the time. >> The Cube lives at the sands. >> It's our second home. >> Come by Hosho's office and let us know. Vegas is our home. We are hosting a conference in Vegas after DEFCON. So DEFCON is the biggest security conference in the world. You have the best black hats and white hats show up as security experts in Vegas and right on the tail end of it, Hosho's going to host a very exclusive invite-only conference. >> What's it called? Just Hosho Conference? >> Just Blockchain. It'll be called the just, it'll be by the Just Blockchain Group and Hosho's the main backer behind it. >> Well we appreciate your integrity and your sharing here on The Cube, and again you're paying it forward in the community, that's great. Ethos we love that. That's our mission here, paying it forward content. Here in the Bahamas. Live coverage here at PolyCon 18. We're talking about securitized token, a decentralized future for awesome things happening. I'm Jeff Furrier, Dave Vellante. We'll be back with more after this short break. (upbeat music)

(electronic music) >> Narrator: From the SiliconANGLE Media office in Boston Massachusetts, it's the CUBE. Now here are your hosts, Dave Vellante and Stu Miniman. >> Cloud is dead, it's all going to the edge. Or is it? Hi everybody, this is Dave Vellante and I'm here with Stu Miniman. Stu, where does this come from, this narrative that the cloud is over? >> Well Dave, you know, clouds had a good run, right? It's been over a decade. You know, Amazon's dominance in the marketplace but Peter Levine from Andreessen Horowitz did an article where he said, cloud is dead, the edge is killing the dead. The Edge is killing the cloud and really we're talking about IoT and IoT's huge opportunity. Wikibon, Dave we've been tracking for many years. We did you know the original forecast for the Industrial Internet and obviously there's going to be lots more devices at the edge so huge opportunity, huge growth, intelligence all over the place. But in our viewpoint Dave, it doesn't mean that cloud goes away. You know, we've been talking about distributed architectures now for a long time. The cloud is really at the core of this building services that surround the globe, live in just hundreds of places for all these companies so it's nuanced. And just as the cloud didn't overnight kill the data center and lots of discussion as to what lives in the data center, the edge does not kill the cloud and it's really, we're seeing some major transitions pull and push from some of these technologies. A lot of challenges and lots to dig into. >> So I've read Peter Levine's piece, I thought was very thought-provoking and quite well done. And of course, he's coming at that from the standpoint of a venture capitalist, all right. Do I want to start you know, do I want to pour money into the trend that is now the mainstream? Or do I want to get ahead of it? So I think that's what that was all about but here's my question Stu is, in your opinion will the activity that occurs at the edge, will it actually drive more demand from the cloud? So today we're seeing the infrastructure, the service business is growing at what? Thirty five percent? Forty percent? >> Sure, sure. Amazon's growing at the you know, 35 to 40 percent. Google, Microsoft are growing double that right now but overall you're right. >> Yeah, okay and so, and then of course the enterprise players are flat if they're lucky. So my question is will the edge actually be a tailwind for the cloud, in your opinion? >> Yeah, so first on your comment there from an investment standpoint, totally can understand why edge is greenfield opportunity. Lots of different places that I can place bets and probably can win as opposed to if I think that today I'm going to compete against the hyperscale cloud guys. You know, they're pouring 10 billion dollars a year into their infrastructure. They have huge massive employment so the bar to entry is a lot higher. I'm sorry, the second piece was? >> So will the edge drive more demand for the cloud? >> Yeah, absolutely. I think it does Dave because you know, let's take something like autonomous vehicles. Something that we talk about. I need intelligence of the edge. I can't wait for some instruction to go back to the cloud before my Tesla plows into an individual. I need to know that it's there but the models themselves, really I've got all the compute in the cloud. This is where I'm going to train all of my models but I need to be able to update and push those to the edge. If I think about a lot of the industrial applications. Flying a plane is, you know, things need to happen locally but all the anomalies and new things that we run into there's certain pieces that need to be updated to the cloud. So you know, it's kind of a multi-layer. If we look at how much data will there be at the edge, well there's probably going to be more data at the edge than there will be in the central cloud. But how much activity, how much compute do I need, how much things do I need to actually work on. The cloud is probably going to be that central computer still and it's not just a computer, as I said, a distributed architecture. That's where, you know. When we've looked at big data in the early days Dave, when we can put those data lines in the cloud. I've got thousands or millions of compute cycles that I can throw at this at such a lower price and use that there as opposed to at the edge especially. What kind of connectivity do I have? Am i isolated from those other pieces? If you go back to my premise of we're building distributed architectures, the edge is still very early. How do I make sure I secure that? Do I have the network? There's lots of things that I'm going to build in a tiny little component and have that be there. And there's lots of hardware innovation going on at that edge too. >> Okay, so let's talk about how this plays out a little bit and you're talking about a distributed model and it's really to me a distributed data model. The research analysts at Wikibon have envisioned this three-tier data model where you've got data at the edge, which you may or may not persist. You've got some kind of consolidation or aggregation layer where it's you know, it's kind of between the edge and the deep data center and then you've got the cloud. Now that cloud can be an on-prem cloud or it could be the public cloud. So that data model, how do you see that playing out with regard to the adoption of cloud, the morphing of cloud and the edge and the traditional data center? >> Yeah we've been talking about intelligent devices at the edge for a couple decades now. I mean, I remember I built a house in like 1999 and the smart home was already something that people were talking about then. Today, great, I've got you know. I've got my Nest if I have, I probably have smart assistants. There's a lot of things I love-- >> Alexa. >> Saw on Twitter today, somebody's talking like I'm waiting for my light bulbs to update their firmware from the latest push so, some of its coming but it's just this slow gradual adoption. So there's the consumer piece and then there's the business aspect. So, you know, we are still really really early in some of these exciting edge uses. Talk about the enterprise. They're all working on their strategy for how devices and how they're going to work through IoT but you know this is not something that's going to happen overnight. It's they're figuring out their partnerships, they're figuring out where they work, and that three-tiered model that you talked about. My cloud provider, absolutely hugely important for how I do that and I really see it Dave, not as an or but it's an and. So I need to understand where I collect my data, where it's at certain aspects are going to live, and the public cloud players are spending a lot of time working on on that intelligence, the intelligence layer. >> And Stu, I should mention, so far we're talking about really, the infrastructure as a service layer comprises database and middleware. We haven't really addressed the the SAS space and we're not going to go deep into that but just to say. I mean look, packaged software as we knew it is dead, right? SAS is where all the action is. It's the highest growth area, it's the highest value area, so we'll cover that in another segment. So we're really talking about that, the stack up to the middleware, the database, and obviously the infrastructures as a service. So when you think about the players here, let's start with AWS. You've been to I think, every AWS re:Invent maybe, with the exception of one. You've seen the evolution. I was just down in D.C. the other day and they have this chart on the wall, which is their releases, their functional releases by year. It's just, it's overwhelming what they've done. So they're obviously the leader. I saw a recent Gartner Magic Quadrant. It looked like, I tweeted it, it looked like Ronnie Turcotte looking back on Secretariat from the Belmont and whatever it was. 1978, I think it was. (laughs) 31 lengths. I mean, massive domination in the infrastructure as a service space. What do you see going on? >> Yeah so, Dave, absolutely. Today the cloud is, it's Amazon's market out there. Interestingly if you say, okay what's some of the biggest threats in the infrastructure as a service? Well, maybe China, Dave. You know, Alibaba was one that you look at there. But huge opportunity for what's happened at the edge. If you talk about intelligence, you talk about AI, talk about machine learning. Google is actually the company that most people will talk about it, can kind of have a leadership. Heck, I've even seen discussion that maybe we need antitrust to look at Google because they're going to lock things up. You know, they have Android, they have Google Home, they have all these various pieces. But we know Dave, they are far behind Amazon in the public cloud market and Amazon has done a lot, especially over the last two years. You're right, I've been to every Amazon re:Invent except for the first one and the last two years, really seen a maturation of that growth. Not just you know, devices and partnerships there but how do they bring their intelligence and push that out to the edge so things like their serverless technology, which is Lambda. They have Lambda Greengrass that can put to the edge. The serverless is pervading all of their solutions. They've got like the Aurora database-- >> And serverless is profound, not just that from the standpoint of application development but just an entire new business model is emerging on top of serverless and Lambda really started all that but but carry on. >> Yeah and when you look in and you say okay, what better use case than IoT for, well I need infrastructure but I only need it when I need it and I want to call it for when it's there. So that kind of model where I should be able to build by the microsecond and only use what I need. That's something that Amazon is at the forefront, clear leadership position there and they should be able to plug in and if they can extend that out to the edge, starting new partnerships. Like the VMware partnerships, interesting. Red Hat's another partnership they have with OpenShift to be able to get that out to more environments and Amazon has a tremendous ecosystem out there and absolutely is on their radar as to how their-- >> They're crushing it So we were at Google Next last year. Big push, verbally anyway, to the enterprise. They've been making some progress, they're hiring a lot of people out of formerly Cisco, EMC, folks that understand the enterprise but beyond sort of the AI and sort of data analytics, what kind of progress has Google made relative to the leader? >> So in general, enterprise infrastructure service, they haven't made as much progress as most of us watching would expect them to make. But Dave, you mentioned something, data. I mean, at the center of everything we're talking about is the data. So in some ways is Google you know, come on Google, they're smarter than the rest of us. They're skating to where the puck is Dave and infrastructure services, last decades argument if it's the data and the intelligence, Google's got just brilliant people. They're working at the some of these amazing environments. You look at things like Google's Spanner. This is distributed architecture. Say how do I plug in all of these devices and help the work in a distributed gradual work well. You know, heck, I'd be reading the whitepapers that Google's doing in understanding that they might be really well positioned in this 3D chess match that were playing. >> Your eyes might bleed. (laughs) I've read the Google Spanner, I was very excited about it. Understood, you know, a little bit of it. Okay, let's talk about Microsoft. They're really of the big cloud guys. They're really the one that has a partnership strategy to do both on-prem and public cloud. What are your thoughts on that now that sort of Azure stack is starting to roll out with some key partners? >> Yeah absolutely, it's the one that you know. Dave, if you use your analogy looking back, it's like well the next one, it's gaining a little bit, gaining a little bit but still far back. There is Microsoft. Where Microsoft has done best of course is their portfolio of business applications that they have. That they've really turned the green light on for enterprises to adopt SAS with Office 365. Azure stack, it's early days still but companies that use Microsoft, they trust Microsoft. Microsoft's done phenomenal working with developers over the last couple of years. Very prominent like the Kubernetes shows that I've been attending recently. They've absolutely got a play for serverless that we were talking about. I'm not as up to speed as to where Microsoft sits for kind of the IoT edge discussions. >> But you know they're playing there. >> Yeah, absolutely. I mean, Microsoft does identity better than anyone. Active Directory is still the standard in enterprises today. So you know, I worry that Microsoft could be caught in the middle. If Google's making the play for what's next, Microsoft is still chasing a little bit what Amazon's already winning. >> Okay and then we don't have enough time to really talk about China, you mentioned it before. Alibaba's you know, legit. Tencent, Baidu obviously with their captive market in China, they're going to do a lot of business and they're going to move a lot of compute and storage and networking but maybe address that in another segment. I want to talk about the traditional enterprise players. Dell EMC, IBM, HPE, Cisco, where do they stand? We talk a lot at Wikibond about true private cloud. The notion that you can't just stick all your data into the public cloud. Andy Jassy may disagree with that but there are practical realities and certainly when you talk to CIOs they they underscore that. But that notion of true private cloud hasn't allowed these companies to really grow. Now of course IBM and Oracle, I didn't mention Oracle, have a different strategy and Oracle's strategy is even more different. So let's sort of run through them. Let's take the arms dealers. Dell EMC, HPE, Cisco, maybe you put Lenovo in there. What's their cloud strategy? >> Well first of all Dave I think most of them, they went through a number of bumps along the road trying to figure out what their cloud strategy is. Most of them, especially let's take, if you take the compute or server side of the business, they are suppliers to all the service providers trying to get into the hyperscalers. Most of them have, they all have some partnership with Microsoft. There's a Assure stack and they're saying, okay hey, if I want an HPE server in my own data center and in Azure, Microsoft's going to be happy to provide that for you. But David, it's not really competing against infrastructure as a service and the bigger question is as that market has kind of flattened out and we kind of understand it, where is the opportunity for them in IoT. We saw, you know Dave. Last five years or so, can I have a consumer business and an enterprise business in the same? HPE tore those two apart. Michael Dell has kept them together. IBM spun off to Lenovo everything that was on the more consumer side of the business. Where will they play or will companies like Google, like Apple, the ones that you know, Dave. They are spending huge amounts of money in chips. Look at Google and what they're doing with TP use. Look at Apple, I believe it was, there was an Israeli company that they bought and they're making chips there. There's a different need at the edge and sure, company like Dell can create that but will they have the margin, will they have the software, will they have the ecosystem to be able to compete there? Cisco, I haven't seen on the compute side, them going down that path but I was at Cisco Live and a big talk there. I really like the opening keynote and we had a sit down on the CUBE with the executive, it said really if I look out to like 2030. If Cisco still successful and we're thinking about them, we don't think of them as a network company anymore. They are a software company and therefore, things like collaboration, things like how it's kind of a new version of networking that's not on ports and boxes. But really as I think about my data, think about my privacy and security, Cisco absolutely has a play there. They've done some very large acquisitions in that space and they've got some deep expertise there. >> But again, Dell, HPE, Cisco, predominantly arms dealers. Obviously don't have, HPE at one point had a public cloud, they've pulled back. HP's cloud play really is cloud technology partners that they acquire. That at least gives them a revenue stream into the cloud. Now maybe-- >> But it's a consultancy. >> It's a consultancy, maybe it's a one-way trip to the cloud but I will say this about CTP. What it does is it gives HPE a footprint in that business and to the extent that they're a trusted service provider for companies trying to move into the cloud. They can maybe be in the catbird seat for the on-prem business but again, largely an arms dealer. it's going to be a lower margin business certainly than IBM and Oracle, which have applications. They own their own public cloud with the Oracle public cloud and IBM cloud, formerly SoftLayer, which was a two billion dollar acquisition several years ago. So those companies from a participation standpoint, even a tiny market share is compared to Amazon, Google, and Microsoft. They're at least in that cloud game and they're somewhat insulated from that disruption because of their software business and their large install base. Okay, I want to sort of end with, sort of where we started. You know, the Peter Levine comment, cloud is dead, it's all going to the edge. I actually think the cloud era, it's kind of, it's here, we're kind of. It's kind of playing out as many of us had expected over the last five years. You know what blew me away? Is Alexa, who would have thought that Amazon would be a leader in this sort of natural language processing marketplace, right? You would have thought it would come from, certainly Google with all the the search capability. You would have thought Apple with Siri, you know compared to Alexa. So my point is Amazon is able to do that because it's got a data model. It's a data company, all these companies, including Apple, Google, Microsoft, Amazon, Facebook. The largest market cap companies in the world, they have data at the core. Data is foundational for those companies and that's why they are in such a good position to disrupt. So cloud, SAS, mobile, social, big data, to me still these are kind of the last 10 years. The next 10 years are going to be about AI, machine intelligence, deep learning, machine learning, cognitive. We're trying to even get the names right but it starts with the data. So let me put forth the premise and get your commentary. and tie it back in the cloud. So the innovation, in the next 10 years is going to come from data and to the extent that your data is not in silos, you're going to be in a much better position than if it is. Number two is your application of artificial intelligence, you know whatever term you want to use, machine intelligence, etc. Data plus AI, plus I'll bring it back to cloud, cloud economics. If you don't have those cloud economics then you're going to be at a disadvantage of innovation. So let's talk about what we mean by cloud economics. You're talking about the API economy, talking about global scale, always on. Very importantly something we've talked about for years, virtually zero marginal costs at volume, which you're never going to get on-prem because this creates a network effect. And the other thing it does from an innovation context, it attracts startups. Or startups saying, hey I want to build on-prem. No, they don't want to build in the cloud. So it's data plus artificial intelligence plus cloud economics that's going to drive innovation in the next ten years. What are your thoughts? >> Yeah Dave, absolutely. Something I've been saying for the last couple of years, we watched kind of the the customer flywheel that the public clouds have. Data is that next flywheel so companies that can capture that. You mentioned Amazon and Alexa, one of the reasons that Amazon can basically sell that as a loss is lots of those people, they're all Amazon Prime customers and they're ordering more things from Amazon and they're getting so much data that drive all of those other services. Where is Amazon going to threaten in the future? Everywhere. It is basically what they see. The thing we didn't discuss there Dave, you know I love your premise there, is it's technology plus people. What's going to happen with jobs? You and I did the sessions with Andy McAfee and Eril Brynjolfsson, it's racing with the machine. Where is, we know that people plus machines always beat so we spent the last five years talking about data scientist, the growth of developers and developers and the new king makers. So you know what are those new jobs, what are those new roles that are going to help build the solutions where people plus machine will win and what does that kind of next generation of workforce going to look like? >> Well I want to add to that Stu, I'm glad you brought that up. So a friend of mine David Michelle is just about to publish a new book called Seeing Digital. And in that book, I got an advance copy, in there he talks about companies that have data at their core and with human expertise around the data but if you think about the vast majority of companies, it's human expertise and the data is kind of bolted on. And the data lives in silos. Those companies are in a much more vulnerable position in terms of being disrupted, than the ones that have a data model that everybody has access to with human expertise around it. And so when you think about digital disruption, no industry is safe in my opinion, and every industry has kind of its unique attributes. You know, obviously publishing and books and music have disrupted very quickly. Insurance hasn't been disrupted, banking hasn't been disrupted, although blockchain it's probably going to affect that. So again, coming back to this tail-end premise is the next 10 years is going to be about that digital disruption. And it's real, it's not just a bunch of buzzwords, a cloud is obviously a key component, if not the key component of the underlying infrastructure with a lot of activity in terms of business models being built on top. All right Stu, thank you for your perspectives. Thanks for covering this. We will be looking for this video, the outputs, the clips from that. Thanks for watching everybody. This is Dave Vellante with Stu Miniman, we'll see you next time. (electronic music)

>> Narrator: Live from Las Vegas, it's theCube covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. (upbeat music) >> Okay, welcome back everyone. We're here live in Las Vegas. This is theCube's exclusive coverage of Amazon Web Services re:Invent 2017, our fifth year covering AWS re:Invent. I'm John Furrier the founder of SiliconANGLE Media with my co-host Stu Miniman. I'm so excited 45,000 people and boy, I remember when it was just a small, little, fast-growing company. We're here with Teresa Carlson who's been here with us the whole way. She's a Senior Vice President of Public Sector. Teresa, welcome to theCube, good to see you. >> I'm always glad to be here on theCube. >> So, you've been running public sector, you've been really, I've gotta say, I gave a tweet, not to sound that I'm fawning over you right now, but you've really grown the business in a significant way. As Andy was saying, a meaningful way. Take us through, because it's almost mind-blowing. We have already had a few guests on theCube. I went to your breakfast. You are changing the game, but not without scar tissue. You've done a lot of hard work to get there, so, one, congratulations, but give us a state-of-the-union right now for public sector, because you're winning, you're doing great, but it wasn't easy. >> No, it's not been easy, but it's been a lot of fun. I mean, it's been a lot of fun, in fact, as you said, this is our sixth year of doing re:Invent and yesterday or two days ago, we had a public sector breakfast and it was so full, we got shut down by the fire marshal. So that is when you know you've got customers and partners showing up, because they want to be there. We have grown significantly and that has been through the work of both working with customers and partners on security, compliance, policy, acquisition vehicles, to just make sure that we have the right balance of everything needed to really drive and grow the business in the right way. As I've talked about we didn't leave any stone unturned. We had to really go through all the hard processes to do this right and I think it really has paid off because you never want to take short-cuts. You wanna make sure you're doing the right thing in order for customers to have better technology, for us to help drive good government, good education. >> I gotta say, one of the big trends we're seeing here on siliconANGLE, theCube, and Wikibon is the public-private Partnerships are accelerating. You're seeing public sector help on security to the private sector, private sector helping government move faster and so you're seeing a balance and an equilibrium coming together, but also old guard companies sometimes have a federal division or a separate DNA culture. You guys don't, you have one culture at Amazon, but the striking thing for me, is that you're now enabling companies to get into public sector that couldn't before. So I wanted to ask you specifically, is it like that now, we're you're starting to see new people come in with solutions because you guys have done that heavy lifting where before they'd have to wait in line, get certified, are we seeing new solutions, are you enabling that, is that actually happening? >> It absolutely is happening and we never forget our roots of start-ups here at AWS, because they are really a huge reason why we exist and for public sector, I saw a change in my previous life I never had venture capitalists or private equity firms come and say we want our companies in government. We are creating new education tech companies, which was really not even heard of. >> It's a growth strategy for them. >> It's a huge growth strategy, so venture capitalist and private equity like Andreessen Horowitz, Madrona, C5, Bridgewater, we see tons and they come to us saying, we have this portfolio, can you help us talk to them about how they get into government? As a result of that, we do sales and marketing, we work with them on FedRAMP I-E slash security compliance. We ensure that they understand the elements and components of how they work in government and by the way, government loves that we are bringing in innovative new technologies. We can also do that through the marketplace, the AWS marketplace, which allows them to move faster, be more agile, and start getting that business. >> Teresa, I'm wondering if you could share a little more. You talk about innovation, we've been lovin' for years, I love when I talk about regional governments, education, you get non-profits under your umbrella, where it used to be, I didn't have the budget, I can't move fast. Now, we're seeing some great innovation from the private side as well as well as some of the public-private interactions. >> Definitely, in fact, I was in California about a month ago where we announced an innovation center with California Polytechnic University, CalPoly and the president there, Jeff Armstrong, it is amazing, they literally had been looking at what AWS was doing and they took the pillars that they'd been seeing us talk about for public sector and they created an innovation center to work on these opportunities and challenges and just as in public safety, health, agri, sex trafficking and child exploitation, through seeing what Thorn was doing in the International Center for Missing and Exploited Children. >> How is this leveling the playing field? Because everyone, citizens at least in the United States, I'm sure it's happening in other markets as well, they want the government to move faster. And you guys are like the freight train that's out of control speed-wise, just more and more services. How does the government keep up? Because I would imagine that if I am a government official or I'm the public sector, oh my God, I can't handle Amazon. I can't ride that beast, it's too strong. I mean do they say that, is that the wrong vibe, or are they more hey I want you to do, is it more your flywheel, do they have to get involved? What's the relation, what's the sentiment of the government? >> Well, they wanna move fast. In fact, in the U.S. government, the White House does have an entire initiative now on modernization. You're seeing countries like the U.K government go cloud native. You saw the country of Bahrain which is going all-in in the cloud and they've already established new policies and a cloud-first policy of moving. But I would tell you, if you look at groups like the intelligence community in the U.S. government, we just announced our secret region and that allows them to have top-secret capabilities, secret, unclassified in our GovCloud, so they have capabilities across the entire spectrum of workloads and what they've always said to us and our other customers is can we build cloud tools, can we build a cloud? Yes, but can we innovate at the rate and speed you're innovating? No, because we provide them innovation ahead of their demand. >> Yeah, Teresa, I remember when GovCloud launched and it was, like, wow, this is like AWS isn't just like a monolithic service around the globe and everything. It seems like secret region goes along that line. How does the dynamic between AWS as a whole and what you're doing in your organization, how do you work through that and kinda balance, I want services around the globe, yet meet the needs of your clients. >> On the GovCloud region, that was our first entre into doing something unique for government. That region has grown 185% every year since 2011 and we just announced a second region on the east coast for GovCloud, U.S. GovCloud. The interaction with our services team is amazing. Charlie Bell who runs all of our services, we have a tight relationship, we talk to our government customers in these regions, understand their priorities, then we roll them out and it's really that simple. They get the exact same thing in their classified regions as we give our other customers, it's just their network. >> Well, you got the date set, I'm looking at my picture here I took, June 20th and 21st, save the date, AWS Public Sector Summit, #AWSPSSummit as it's called on Twitter hashtag. Every year, you started out in a little conference room, in a ballroom, bigger hotel, now the convention center. Massive growth. >> And theCube was there this year, which I was happy. >> That makes it legitimate, and theCube's there, we'll be there this year, >> Good, yes. >> But of course, this is the growth. V.C.s, private equity, this is a growth market, this is not a unique, siloed market anymore. You guys have leveled the silos within Amazon, I mean you never had silos, but you are now agile to come to the government. What's next for you? You've done a great job, you're now cruising altitude, what's your growth strategy for Public Sector Summit, how are you going to take it to the next level? >> Well, even though we have grown a lot, thank you to our customers and partners, we really are just scratching the surface. It is day one still for us. Our customers are really just still getting going on a lot of mission critical workloads. They're moving in things they really hadn't thought about. They're starting to do things like higher more developers in government, so they can take advantage of the tools used, a lot you saw yesterday. But additionally, what we're seeing is we are spending a lot of time going into countries around the world, helping countries set a strategy for digital transformation. New jobs growth, new companies, economic development, how do they train and educate for a cloud-based workforce, we call it and that's really fun to go in and tell governments, look you really have to prepare your country for a digital transformation and again if you look at groups like Bahrain, what the U.K have done, they are doing that and they are making a massive transformation around this. >> Final question for you, what are you most proud of looking back since you joined AWS seven years ago. I think it was seven years ago you started? >> Yep, seven years ago this month. >> Congratulations, so what are you most proud of and then two, what do you think about the most as you execute day-to-day in growing the business? >> Well, I would say the fact that I have had an amazing brand to work with out of the gate Amazon was such a great brand, and the fact that, again, based on think big, Andy Jassy's leadership, really he and I having a conversation together saying, we can change the world and make it a better place and you've heard me say a lot in my openings, we have two themes that we talk about in public sector, which is paving the way for disruptive innovation and making the world a better place. And if I look back, it's really the things that we're helping to do this that we are driving new policies, companies are seeing results, agencies, and we are making the world a better place. I would say that's humbling and amazing and we're just getting going. >> As a chief of public sector, you're like, you've seen it grow and you're running it every day and you have a great team, do you ever have a pinch me moment once in a while? Kind of say, wow, what have you done? >> Well, I think the pinch me moments are when I hear the customers and partners tell me how fast they're moving and the results they have. We always have a goal of really working with our mission partners and we've hired now more than 17,000 veterans at Amazon and growing. It's things like that that we can do to really help that transformation and not just talk the talk, but walk the walk as a company. I would say for where we wanna go and what I sort of worry about our growth, I guess I worry and stay up a little late at night to make sure that we keep our hiring bar high, that we really maintain our focus on customer obsession, >> John: Security. >> Security is always on my mind. >> Do you sleep at all it must keep you up late a lot. >> No, I don't really, no. But the last thing I would say is just really thinking through ensuring that we're continually pushing hard, that we have a little bit of sharp elbows, going in we're trying to change policy, we don't give up on the things that really matter for doing this massive transformation, for countries, for state and local agencies, for feds, for educational institutions around cloud transformation. >> I really respect your results and I love your hard-charging style. It's fantastic, your success obviously speaks for itself. We'll see you at the Summit in June. This is theCube, Teresa Carlson The Chief of the Public Sector business, she's the Vice President of Public Sector. I'm John Furrier, Stu Miniman. More live coverage here at AWS re:Invent after this short break. (upbeat music)

>> Narrator: Live from Las Vegas, it's the CUBE, covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Live here in Las Vegas is the CUBE's exclusive coverage of AWS re:Invent 2017, our fifth year of covering the massive growth of Amazon Web Services. I'm John Furrier, cofounder of SiliconANGLE Media, Inc. with my cohost, Keith Townsend, CTO advisor. We've got two amazing guests here from Druva, a hot startup, a hot company. Guss Gustafson is the executive chairman of the board, and Matt Morgan is the chief marketing officer at Druva. Been on the CUBE but many times. We've had you in the studio. You guys are doing extremely well. You've always got some news for us, always executing. You are like the Amazon of your sector. You've always got stuff going on, what's up? Tell us, share the news. >> Super excited about announcing a new technology, a new product line. It's called Druva Apollo, and Druva Apollo basically completes the cloud data protection story, so as you guys know, we've wrapped endpoints with data protection and data management, and we call it data management as a service. We've wrapped servers with the data management as a service. We took the data, we've protected within the cloud, but with Druva Apollo, what we've announced is cloud-to-cloud data protection, meaning that data that's born inside an EC2 existence, for example, can be wrapped with the same data protection and management as we do for endpoints and the servers. It really is an extension of the platform. Now you can start looking at the data holistically, any data, no matter if it's on the endpoint, the server, or now, within the cloud can be protected within the same controlled data set, getting the full global D2 technology, plus the governance and intelligence capability. I'm really excited about this announcement. >> Now, I want to ask a question on that, because one of the things we talked about in the past on is the cloud has changed the game around perimeter, no more perimeter. >> Right. >> There is no wall from the cloud, a lot of holes to get in there if you are a hacker, but you have a product leadership, but and ease-of-use. One of the things that the cloud is the ability to acquire the resources, right? The server list is out there, how do you guys compete in this now potentially data protection-less world, or is that a term? I mean, you've got to be seamless, but you've got to have good tech. How do you guys do both of those? >> I think you actually just underscore the paradigm shift that's happening. We used to think of data being localized to a server, to a machine, and you had to protect that machine. You wanted to, quote, backup hard drive if you will. Well, data is now in a serverless environment. It's in the air, it's in the cloud, it's tied to applications that may or may not be running within a specific instance. You don't have the control factors, right? >> John: Or some other database. >> That's exactly right. >> Mobile databases now. >> That's exactly the point, right? What we are doing is, because we are stateless, because we exist on these multiple planes, you can have a much more universal conversation around data protection and management, but there is another big "ah-hah" about moving to the cloud for data protection and management, and it's all about ease-of-use and simplicity. Now with a single login, with a single set of credentials, I can access and search across massive data sets that could contain all my endpoints, or it could contain multiple servers, or now it can contain cloud-to-cloud data protected instances. This is a very big deal. Think about the past. If I was a classic hardware acquisition play where I purchased specific silos of data storage or secondary storage, I needed to manage each and every one, and there could be hundreds. I would need to manage hundreds of logins. I had to keep them all up to date. All of that is gone with Druva. >> Let's talk about user experience. This is a developer-focused conference. >> Matt: Totally. >> I'm amazed at the number of shorts and hoodies I've seen (laughing) At a proper enterprise conference. >> John: It's a developer conference turned enterprise. >> Yes, developer conference-- >> Not an enterprise conference. (talking over each other) unlike everybody else. >> The infrastructure company having a hackerthon, for example, but developers don't care about servers. They care about data and interacting with that data. >> Matt: That's right. >> What is the developer experience for recovering and protecting data within Druva? Do they have to go through some backup grandfather-son, son-father set up to back up data? What is the experience? >> There are some vendors that actually still require that. (laughing) Some of them have acted like it's a breakthrough to put it in an appliance, but at the end of the day, it's the same conversation. It's just a localized piece of hardware. Druva's conversation is very different. Data protection is all about where that date is going to be managed and stored, and how you connect it up to the service. By being stateless, we've created an entire architecture that allows all of that data to be collected centrally. Once it's there, the developer has the capability to access it, but the real value comes on the governance side, and on the legal side, so if I'm in a situation where I need to manage critical corporate IP, and know it's protected, and and now I have an audit trail on that data, who has touched it, what they did with it, where it was copied. I have that information. I can search for that information. So it moves a little bit beyond a classic developer point of view and extends that data control to the other players. >> Gus, I want to get your take on this because you are the chairman of the board, but also you have a lot of industry experience. We are seeing a shift in the business now where scale of the cloud is causing a lot of disruption. You guys are taking advantage of it at Druva, but also you are seeing some deviants in Silicon Valley, in our backyard. You've got startups that were born before 2012 with the "go big or go home" attitude, Andreessen Horowitz in Sequoia writing fat checks, $100 million. They can't scale up to compete against this other scale. They got out-scaled, so they end up getting acquired, you know, accu-hired. Barracuda's going private. A gem in the valley, great company, no cloud strategy, so scale is dessimating and creating value at the same time. How should businesses look at this business model paradigm shift where it's not go big or go home, it's find a spot in the ecosystem (laughing) and milk it, or get a position. You can't compete. It's hard to compete against scale. >> Scale, you are right, the whole scale paradigm has now gone from-- it's beyond comprehension, to be honest with you. I think the other thing that we've learned, and this is how Druva looks at this, you can't compress experience. You can't compress learning and application of learning, and so for eight years plus we've been at this game thinking about scale, and in some cases, to be quite blunt, we experience it with our customers because there is no predetermined path in a lot of these things, but for companies of scale today, I think you would have to have a cloud-first mentality. That's what Druva brought to the party. I think we are seeing a lot of people that have looked at this and said, "How do I actually get all the way over here?" Our message is really simple. Let's just get started. Whatever applications or use cases it is to get started, whether it is endpoint, whether it's a server, cloud apps, but we've thought about and built the vision around the entire end-to-end strategy, so we will bump into things at scale. We will figure out how to handle those. We recently brought on board a customer with 75,000 employees, another one with another 50,000, and we've done this before, but those are new layers of scale. >> John : You guys are taking a pragmatic approach. >> We are. >> You guys aren't trying to overbuild, get over your skis, or whatever people call it, but don't create a situation where there is diseconomies. Leverage what you've got, and know your place in the world. >> If you don't mind, I'll just make a comment on the funding round we just received. We just received $80 million in net new funds. It was a preemptive interest in investing in the company. Quite honestly, we could have potentially taken more, but the focuses are on executing what we can actually do today. >> More discipline too. The less capital you take-- >> There is that. >> The more discipline. >> There is that, but you know when you think about the growth and the opportunity, in large part for us, it's all about staying pragmatic-focused and executing well on what is ahead of us. >> The product market fit is always one they talk about with the funding, but also it's the sales channels. If you try to compete with sales, say Amazon for instance, others have tried, it's hard. I know a few companies getting bought up by private equity left and right because they just, size wise, can never get there. >> Gus: Right. >> You guys are inside the tornado, as Jeffrey Moore would say, which is kind of the strategy for you guys. You get in the cloud, you've got product discipline. How is it going on the sales side? What are some of the metrics you are seeing? Any success metrics you can share customer success? >> Yeah, absolutely, and you know for us, AWS is a strategic partner and a great partner in terms of the alliance that we have around bring in net new customers to the cloud, working with them, et cetera, so in the last six months we've added 300 net new enterprise customers. That brings our total to well over 4,000 enterprise customers, and we've done that by, again, staying very focused around that first bite, a very simple approach, and then once people start, they see how simple it is, so you had asked about the developer experience, Keith, it is so simple. In some cases what we say in their actual experience is they don't believe us. When Matt was talking about the "ah-hah" moment, once they experience it, they continue to build, and build, and build. >> So the developers, again, we've talked about this because we are at a developer conference, they just want to solve problems. One of the things that we've always kind of harped on developers about, and Matt, you talked about this a little bit with governance, with data governance, GDPR is coming to be fully enforced May of next year. >> Matt: That's right. >> Very serious consequences for companies that don't kind of handle that. Have you guys seen an uptick in conversations around GDPR with customers and how Druva helps to mitigate some of the challenges around GDPR? >> Keith, one of the most amazing things that's come out of GDPR is the rise of this new executive persona, the chief data protection officer. >> John: Oh, another one! >> For a vendor that's in the data protection business, it is wonderful to have a C-level executive responsible for the value that we deliver. >> Some of the penalties is 4% of revenue. >> How many chiefs will there be these days? >> Well that is true, there are a lot of chiefs. >> There's a lot of chiefs in the kitchen. >> There are a lot of chiefs. >> More than Indians. Oh you guys are the-- >> Yeah, I'm going to defend the chief data protection officer. >> Keith: Yeah, we will keep that one. >> I'll keep that one. (laughing) You keep in mind that the risks that people are dealing with, and GDPR is an extension of extending individual rights to the data sets that are collected on them. The idea of the right to be forgotten. >> You guys have challenges not even within the customers, the external customers, but an organization with 75,000 users, they have rights in themselves, so there is this differentiation between protect internal corporate data and that policy, and keeping that data. If I'm a developer searching for data, I'm just searching for data, so how do I control, what's the controls available for making sure that that doesn't go afoul of GDPR? >> Absolutely, so we have phenomenal security capabilities that are built into our product both from an identification point of view giving rights and privileges, as well as protecting that data from any third-party access. All of this information is going to be compliant with these regulations beyond GDPR. There is enormous regulations around data that require us to keep our security levels as high as we go. In fact, we would argue that AWS itself is now typically more secure, more secure than your classic data set. >> Yeah, they've done the work. >> So we are building on top of the AWS security framework which gives you even better security, and because, this is important, it's off-site, logically by conception of the cloud, we also add immutability, so when you think about ransomware, ransomware is not going to crawl up to the cloud in the classic way that you would have the type of infections that have happened. Druva is going to give you the capability to ensure that that data is whole, and you can recover from those types of malware attacks. It's a little bit of a pivot from GDPR, but I think all of this stuff around data risks are related. >> Talking about the government, public sector market, you guys just got FedRAMP approved. >> Yes. >> It's a big certification. Congratulations. >> Thank you. >> What does that mean for your business? More customers coming in on the public-sector side? >> Public-sector is off the charts for us. The FedRAMP ATO certification, we are the only data protection vendor that has that, and it gives us the capability to qualify for data protection possibilities within the public-sector. I don't know if, Gus, you want to comment anymore on that. >> John: Visa cross is gonna love that. >> It's a massive market opportunity. It also puts you at a higher level in terms of, obviously, the security capabilities that they went through and tested to give us the ATO, which is the authority to operate in the FedRAMP sector. It opens up a tremendous amount of opportunity. When you look at, kind of, the Fortune one as far as US government, this is a massive opportunity for us. >> Well, save the date in Washington DC. This morning they announced the AWS Public Sector Summit on June 20th and 21st. The CUBE will be there. I've got the verbal. Well, we already have the deal with Theresa Carlson. The CUBE will be there probably with two sets too. That's turned into a re:Invent. It grew from a hotel room two years ago, to a ball room, to now the convention center, and they're expecting again, this year in DC, Amazon Public Sector Summit, everything, nonprofits, gov cloud, huge. >> Yeah, it's amazing. AWS has become the 21st-century operating system, and at first it was for individuals or small businesses, but now it is the enterprise. Look around, right? We are all re-platforming, if you will, to be able to provide this architecture as the best possibility. >> So you're betting on Amazon? >> Absolutely. >> Other clouds? >> So we are a multi-cloud provider. We have a solution that also runs on Microsoft Dejour. There's lots of customers that choose Dejour. They are Microsoft customers. They're customers that enjoy the different data centers that Microsoft offers, but the vast majority of our customers really embrace the AWS solution. >> You'll protect whatever the customer needs. Whatever environment they have, you'll support the major platforms? >> We're gonna support either one, and you've got to realize the idea of different data centers that are localized to different countries give you different soverignty options with Microsoft you may not get with AWS, at least not today. >> Yeah, and same with Google too. Google has not a big presence outside the US. >> That's right. >> So they're limited. >> So data protection is starting to become a catch-all term. The, what, $80 million in funding the last round? >> Gus: Yes. >> It's not just about data protection, but now multi-cloud data mobility. Being able to take my data, my hybrid IT data and move it to where I need to move it to. Can you talk about Druva's capability when it comes to data mobility? >> One of the most popular use cases of the acquisition of the Druva technology is all around MNA. The opportunity to bring in data from a variety of different endpoints and bring their customers new companies that are being acquired into the fold. You have all kinds of governance capabilities you could do on that data, and you could prevent the typical data leakage. The employee turnover, where people basically walk out the door. They take their hard drive with them, or take the computer. It's not being tracked, and you don't know what data was there, and you can't track it. With Druva, you have that data. They can take the hard drive. You know exactly what they took. You have information, and you have saved that IP for the company, and you gained that. If I'm acquiring a company, that information obviously is important to me. >> Thanks Gus, thanks for coming on the CUBE, thanks for the update. Congratulations on all the business success and public sector is right around the corner as well, another growing market. Back up and recovery data protection is hot in the cloud, it's hard to do. These guys have got a great solution in Druva. It's the CUBE bringing you more live coverage. We're taking a short break. We'll be right back with our next guest. Stay with us.