(upbeat music) >> Welcome back to Supercloud 22. I'm John Furrier, your host of "The Cube." We're here for a live performance in studio bringing all the thought leaders around this concept of Supercloud, which is a consortium of the smartest people in the industry, the the Cloudaratti some say, or just people in the field building out next generation Cloud technologies for businesses, for the industry, you know, software meets infrastructure at scale and platforms. All great stuff. We have an expert here, Cube alumni and friend of ours, Howie Xu, VP of machine learning and AI at Zscaler, hugely successful company, platform, whatever you want to call it. They're definitely super clouding in their own. Howie, great to see you. Thanks for spending time with us to unpack and grock the direction of the industry that we see. We call it Supercloud. >> Hey, John, great to be back. I'm expecting a nice very educational and interesting conversation here again. >> Yeah, well, you know, one of the things I love talking with you about is you're deep on the technology side, as well as you got the historian view like we do. We've seen the movies before, we've seen the patterns, and now we're seeing structural change that has happened, that's cloud. Thank you very much, AWS. And as your GCP and others. Now we're seeing structural change happening in real time and we want to talk about it as it's happening. This is the purpose of this event. And that is that Cloud is one. Okay, great Cloud operations, on premises and Edge are emerging. Software is open source. It's the perfect storm for innovation and new things are emerging. You're seeing companies like Snowflake, and Databricks, and Zscaler all building great products. But now it's not one thing anymore. It's a lot of things going on. So what is your take on Supercloud? How do you see this evolving? What is some of the structural change that's happening in your mind? >> Yeah, so when you first reached out a few weeks ago about this event, I was like, "Hey, what is Supercloud." I know you tweeted a little bit here and there, but I never really, you know, double clicked, right. So I actually listened to some of your episodes you know, the previous conversations. You know, I would say the way you define Supercloud is it's not just the multi-cloud. The multi-Cloud is probably one aspect of it, right. You know, it's actually more beyond that, right. You know, a little bit, you know, towards past, a little bit more towards the flexibility, and then, you know, including, and also you want to include the on-prem, the edge, not just the Big 3 cloud, right. So there is a lot of the, let's say hybrid, more inclusive, right. So, the way I look at it is it's now very different from my imagination of where the Cloud would be, should be 10, 12 years ago. Because, you know, at that time it was, you know, on-prem dominant and then we say, hey, let's go cloud. I never for a second thought, you know, we would've ditch the on-prem completely, right. You know, on-prem has its own value. It's own kind of characteristics we wanted to keep, right. But the way we went for the last 10 years is, hey, Cloud, Cloud everywhere. We embrace Cloud. You know, the way I look at architecture is always very much like a pendulum, right? We swung from decentralized in the mainframe days, you know back in the days, to more distributed, right, PC, kind of a architecture, you know, servers in your own data center. And then to the now, the Cloud, the Big 3 Cloud in particular, right. I think in the next 10, 15, 20 years, it will swing back to more decentralized, more distributed architecture again. Every time you have a swing, because there is some fundamental reason behind that, we all knew the reason behind the current swing to the Cloud. It's because hey, the on-prem data center was too complex, right. You know, too expensive, right. You know, it would've take at least the six months to get any business application going, right. So compared to Cloud, a swipe a credit card, frictionless, you know, pay as you go, it's so great. But I think we are going to see more and more reason for people to say, "Hey, I need a architecture the other way around because of the decentralized the use case," right. Web3 is one example. Even though Web3 is still, you know, emerging right, very, very early days. But that could be one reason, right? You mentioned the Zscaler is kind of a Supercloud of its own, right? We always embrace public Cloud, but a lot of the workloads is actually on our own, you know, within our own data center. We take advantage of the elasticity of the public Cloud, right. But we also get a value, get a performance of our private Cloud. So I want to say a company like Zscaler taking advantage of the Supercloud already, but there will be more and more use cases taking advantage. >> And the use cases are key. Let me just go back and share something we had on the panel earlier in the day, the Cloudaratti Panel. Back in 2008, a bunch of us were getting together and we kind of were riffing, oh yeah, the future's going to be web services and Clouds will talk to each other, workloads can work across this (indistinct) abstraction layer, APIs is going to be talking to each other. A little bit early but we tried to think about it in terms of the preferred architecture. Okay, way too early. Yeah. AWS was just getting going, really kind of pumping on all cylinders there, getting that trajectory up. But it was use case driven. The nirvana never happened. I mean, we were talking Supercloud back then with the Cloudaratti group and we were thinking, okay, hey this is cool. But it was just an evolutionary thing. So I want to get your reaction. Today, the use cases are different. It's not just developers deploying on public Cloud to get all those greatness and goodness of the Cloud, to your point about Zscaler and others, there's on premises use cases and edge use cases emerging. 5g is right there. That's going to explode. So, the use cases now are all Cloud based. Again, this is an input into what we're seeing around Supercloud. How do you see that? What's your reaction to that? And how do you see that evolving so that the methodologies and all the taxonomies are in place for the right solution? >> Right, I mean, you know, some of the use cases are already here, you know, have been here for the last few years. And again, I mentioned a Zscaler, right. The reason that a Zscaler needs the on-prem version of it is because it's impossible to route all the traffic to the Big 3 Cloud, because they're still far away. Sometimes you need the presence much closer to you in order for you to get the level of the performance latency you want, right. So that's why Zscaler has, you know, so many data center of our own instead of leveraging the public Cloud, you know, for most part. However, public Cloud is still super important for Zscaler. I can tell you a story, right. You know, two years ago, you know, at the beginning of the pandemics, everyone started working from home suddenly, right. You are talking about Fortune 500 companies with 200,000 employees, suddenly having 200,000 employees working from home. Their VPN architecture is not going to support that kind of the workload, right? Even Zscaler's own architecture or the presence is not enough. So overnight we just, having so many new workloads, to support this work from home, the zero trust network for our customers, literally overnight. So it wouldn't have happened without public Cloud. So we took advantage of the public Cloud. Yet at the same time, for many, many use cases that Zscaler is paying attention to in terms of the zero trust architecture, the latency, the latency guarantee aspect, the cost is so important. So we kind of take it advantage of both. >> Yeah, definitely. >> Today you may say, hey, you know, Zscaler is one of the, not a majority of the companies in terms of the Cloud adoption or public Cloud adoption, right. But I can say that, yeah, that's because it's more infrastructure, security infrastructure. It's a little bit different for some of the communication applications, right. Why not just support everything on the public Cloud? That's doable today. However, moving forward next to 5, 10, 15 years, we expect to see Web3 kind of the use cases to grow more and more. In those kind of decentralized use cases, I can totally see that we, you know, the on-prim presence is very important. >> Yeah. One of the things we're seeing with Supercloud that we're kind of seeing clarity on is that there's a lot of seamless execution around, less friction around areas that require a PhD or hard work. And you're seeing specialty Superclouds, apps, identity data security. You're also seeing vertical clouds, Goldman Sachs doing financial applications. I'm sure there'll be some insurance. People in these verse. Building on top of the CapEx on one Cloud really fast and moving to others. So that's clearly a trend. The interesting thing I want to get your thoughts on, Howie, on an architectural basis is in Cloud, public Cloud generally, SaaS depends on IAS. So there's an interplay between SaaS and the infrastructures of service and pass as well. But SaaS and IAS, they solve a lot of the problems. You mentioned latency. How do you see the interplay of these Superclouds that utilize the SaaS IS relationship to solve technical problems? So in architecturally, that's been a tight integration on these Clouds, but now as you get more complexity with Supercloud, how do you see SaaS applications changing? >> Yeah, I view the Supercloud is actually reduced the complexity. The reason I'm saying that is, think about it in the world where you have predominantly public Cloud kind of the architecture, right? 10 years ago, AWS has probably 20 services. Now they probably have, you know, more than 1,000 services. Same thing with Azure, same thing with GCP. I mean, who can make sense out of it, right. You know, if you just consume the eyes or the Big 3 Cloud service as is. You know, you need a PhD these days to make sense all of them. So the way I think about Supercloud or where, you know it is going, is it has to provide more simplicity, a better way for people to make sense out of it, right. Cause if I'm an architecture and I have to think, hey, this is a public Cloud, this is a multi-Cloud, and by the way, certain things need to be run on the on-prem. And how do I deal with the uniform nature of it? My mind would blow up. So I need a higher level abstraction. That higher level abstraction will hide the complexity of the where it is, which vendor. It will only tell me the service level, right. You know, we always say, you know, the Cloud is like electricity. I only wanted to know is that like 110 volt or 220, 240, whatever that is. I don't really want to know more than that, right. So I want to say a key requirement for the Supercloud is it's reduced the complexity, higher level abstraction. It has to be like that. >> And operational consistencies at the bottom. Howie, we have one minute left. I want to get your thoughts. I'd like you to share what you're working on that you're excited about. It doesn't have to be with Zscaler. As you see the Supercloud trend emerging, this is the next generation Cloud, Cloud 2.0, whatever we want to call it, it's happening. It's changing. It's getting better. What are you excited about? What do you see as really key inflection point variables in this big wave? >> Yeah. One of the things I really like, what I heard from you in the past about Supercloud is a Supercloud is not just a one Cloud or one vendor. It's almost like every company should have its own Supercloud, right. You're talking about JP Morgan, Goldman Sachs of the world, that they need to have their own Supercloud. Zscaler and their security vendors, they may have their own Cloud. So I think every Fortune 500, Fortune 2,000 companies will have its own Supercloud. So I'm excited about that. So why that's important? We also say that, you know, in the next 10, 20 years, AI machine learning is going to help us a lot, right. So without Supercloud, it's very hard to do AI machine learning. 'Cause if you don't have a place that you know where the data is, and then it's pretty hard. And in the context of Supercloud, I totally foresee that the AI model will follow the data. If the data is in the cloud, it will go there. If the data is on-prem, it will go there. And then the Supercloud will hide the complexity of it. So if you ask me, my passion is leveraging AI machine learning to change the world, but Supercloud will make that easier, right. If you think about why Google, Facebook of the world, are able to leverage AI better than 99% of the rest of the world, because they figure out the Supercloud for themselves, right. And I think now it's the time for the rest of the Fortune 500, of Fortune 2,000 company to figure out its own Supercloud strategy. What is my Supercloud? I need to have my own Supercloud. Each company needs to have its own Supercloud. That's how I see it. >> Howie, always great to have you on. Thanks so much for spending the time and weighing in on this really important topic. We're going to be opening this up. It's not over. We're going to continue to watch the change as it unfolds and get an open community perspective. Thank you so much for being a great expert in our network and community. We really appreciate your time. >> Thank you for having me. >> Okay. Okay, that's it. We'll be up with more coverage here, Supercloud event, after this short break. I'm John Furrier, host of "The Cube." Thanks for watching. (upbeat music)

(upbeat jazz music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California. This is a CUBEConversation. >> Hello everyone, welcome to this special CUBEConversation. I'm John Furrier in theCUBE Studios in Palo Alto, California. We're excited to have a great tech talk here with good friend Howie Xu, who's currently the Vice President of Machine Learning and AI at Zscaler. Formally an entrepreneur, which he sold his company Zscaler. Before that entrepreneur resident Greylock. Before that VMWare, a variety of other endeavors. Howie and I, we've known each other for a while. Great to have you come in and chat about-- >> Great to be here! >> The Zoom, Zscaler, these are the new breed modern era companies, SaaS business models. Really interesting and this is something that we were talking about on email and over text, is our topic. >> Yeah. >> Thanks for coming in. >> Great. >> So you've seen the waves at VMWare, you saw the rapid growth there. And now, you work for Zscaler which is experiencing rapid growth. You saw Zoom go public, and I just interviewed Michael Dell. We were commenting about that on text as well. He said these big markets that have big total addressable dollars associated with them are ripe for disruption. They used to have high barriers to entry in the old ways to look at it, but now with cloud and with SaaS, with data, there's different innovation speeds. This has become a big deal. Talk about your view on this. >> Well to me, when Zoom and then Zscaler founded, many years ago, no one believed that they would become this big, right? When Zoom founded, they were plenty of the conference, free even, software available out there. When Jay founded Zscaler people thought, "Well, there was enough security companies, security solutions." Clearly, they defied conventional wisdom and then they just fought on and they saw something that other people didn't see which is precisely what you were talking about. The SaaS is so different, right? The business model, the innovation speed, the data driven kind of the thing, it's so different. A lot of people say, "Hey what's the difference "between SaaS versus the convention? "Isn't that just moving that thing over to the cloud?" I actually used to think that way too, right? Isn't that just the virtual price, moving on to Amazon Cloud? After living and breathing in SaaS company and then also observing that in the VC industry as well. It's just totally different, day and night different. >> Well I wanted to get into this with you 'cause I think you bring some good perspective onto these insights and to the rocket success of say Zoom and Zscaler, but Zoom in particular, recent successful IPO. Among the recent class this past quarter. Zoom, Lyft, Uber. Zoom is standing out. They're getting profitable. This is video conferencing. You know in the old days if someone said, "Hey, I want to compete with video conferences." Well, the barriers are actually too high, but they took a very innovative approach. Cloud, data, simplicity, and the big 800 pound gorilla was the WebEx's of the world. Who was defined, divine for sharing slides, not so much pure video. (laughing) >> Yeah. >> They really innovated the focus, the speed of success. Unprecedented, in my opinion. I think this is a huge success of what the opportunities are for entrepreneurs. >> Yeah, I think on the surface, right? If you ask Eric he would tell you that, look the WebEx was designed for sharing slides, and then the Zoom was designed from ground up for video sharing, or the video conferencing, so it's very different and it requires different architecture. So that's very true. But I think there is a more fundamental to that. The more fundamental for that is, there are a few things. One is the product, the life cycle is very different. How do you approach the customer? The release cycle, the sort of the feedback loop, right? Much tighter feedback loop, much faster feedback loop between the customer and you. The release cost is much lower now as a SaaS product. So, innovation is just accelerated because it's SaaS, because it's a true SaaS. >> And this is a unique thing, you said before, SaaS isn't just lifting a on-premises workload and moving it to the cloud. It's a completely different mindset. Talk about this dynamic, because it affords new kinds of risk taking. You and I were talking about before we came on camera, share your insight on that. >> Well, you know, as kind of the traditional software you have a release cycle, you want it to have a release date, right? And then once the product is in customer hand, if you have a bug, if you have something, it's so costly to change it, right? But as a SaaS, the form factor, you can take a little bit more risk. You can even give that feature set to 10% of your audience. Not the entire set of the audience. You can do those kind of magic, so you can accelerate the innovation and as a shrink-wrapped software the traditional way. You have one shot, if that software is not good, then you are toast. >> So you can move quicker. You can push code, you don't have the on-premise dynamics. >> Yeah, the innovation and then risk taking are kind of correlated, right? Relatively more risk, the more you are willing to take risk, relatively you can take more innovation. So, that's the thing. >> Well, you and I were talking, and one of the key things that you have been talking about publicly, and amongst friends, is innovation speed. Everyone wants the innovation fever. "I got to win to innovate, digital transformation, rah rah." Easier said then done. Innovation speed is critical with cloud and SaaS, why? What's the formula there for innovation speed? >> Well, one thing we discussed, the release cycle. For a, not necessarily for Zoom and Zscaler, but you know for SaaS in general, its possible for you to have daily, weekly, monthly release. Traditional software, there is no way you can do that but that's just the release cycles of that. The other thing is, you can actually take a risk. You can say, "Hey I want you to try to raise 1% of the customer and then see how they are going to react to this." But in the traditional way you have product manager debating for six months, six years on whether or how to do things. Here, let's not debate, let's just see. >> Let's ship it. >> Right, ship it. >> And Reid Hoffman always says, "If he's not embarrassed by your first shipment then you're not doing it properly." Which begs the question, I want to get your thoughts on this because, again with VMware, you saw how early that worked and their transforming cloud is now here unlike when they started the company. What is the right way to do it? And what's the wrong way to do it? When you look at an entrepreneur or a friend, who's trying to get a business off the ground, SaaS business, when you look at what they're doing, and you look at their mechanisms and how they're organizing their team, their code. What jumps out at you as the wrong way, and what's the right way? >> Well, the, I think the coach is really it, right? You know, the kind of the coach of incremental success and the fast iteration is the culture for a SaaS company, right? For the traditional one, you cannot afford to do that, because once you make a small mistake, you are toast. So I think, you know, that the culture difference, you really want it to have faster iteration basically. >> And that also comes down to the team, the people, right? >> Yes. >> The people selection. >> Yes, if you are kind of used to the waterfall thing, it's pretty hard to adapt to this kind of the SaaS world. >> And what's your advice to entrepreneurs? Reset, because if you say speed is of the essence, resetting is probably something that's not hard to do, then. >> Well, I wouldn't say easy, but not easy-- >> I hate to use the word pivot, but you know, resetting means okay, stop, rebuild. >> I think one way to think about it is actually looking at it and how to build enterprise software, like the consumer sort of product way, right? If you think of Facebook or Google, the traditional Google, of course Google now has enterprise product, but the traditional sort of, the Google, Facebook, kind of the product, it's more for consumers to consume. I mean they are fast iterations. How often? What's the criteria to release a product? Enterprise product is getting towards there. You need that kind of the thing, so, if you don't know how to do it look at a Facebook, how Facebook, of course Facebook and YouTube pulled the other way around, they need to care more about the privacy, care about more stability. So I think you are seeing the the two sides of the world, the enterprise side and the consumer side. They are learning from each other. >> Well, I want to get to the enterprise talk track in a second, because I think you can give a lot of insight, so I want to stay on SaaS cloud native or cloud specifically, 'cause that's where SaaS really shines when you're really talking about cloud scale. Data, you're doing AI now, and you and I have both talked about data many times. >> Yes. >> You know I'm a data hardcore person. I love data. I think software and data, I wrote a blog post in 2007, that says data is the new developer kit. The word "developer kit" was used back then. You're now seeing where data is part of the developer's piece of their value creation. Highly addressable, available, usable, not stored in some silo unaddressable, high latency to get it. How important is the data for the SaaS piece? Because that's where to make these kind of changes you're talking about, you need the data, data's giving you insights, that's something that's near and dear to your heart. Explain your vision of the role of data. >> Yeah, I think, you touched up on it. If you want to make sense out of something, you need the data, right? And if it's not SaaS, I would go, maybe a more extreme way, but it's not clear to me the data's even useful to you 'cause you know the data may be for some large software company, they may have hundreds of thousands of customers out there, but the data is spread around. I mean how are you going to train a model with all the data spread around hundreds of thousands of locations? So the real, the correct, or the optimal way, is actually the SaaS model, you actually have the data with you and then you kind of leverage the data. So I would say this is actually another benefit of the SaaS, why SaaS is going to change the world or eat the world. It owns the data for real, right? The data may be not the private data, but it's actually could be a behavior data. How people are reacting to your features. From VMware days we wanted to know, is people even using this feature? How often people use this feature? You know people are always debating, "Hey what's the maximum policy we need to give this and that?" But in the SaaS world, no debate just look at it. We always say, "Don't listen to what customers are wanting you to do." But watch how they do things, so that you can sort of understand, what product you want to develop, right? Here you actually can really watch how customers using your product. Don't listen to them, if you listen to them you will give them a faster horse as we all knew. >> But what's important about the data discussion, because, a security person would say, "Hey if you put into one spot, I can hack it." But, it's not just people's names, it's other data. It's gesture data, it's usage data, so you're not talking about sign in data, it's data. >> It could be the behavior, it could be second order data. Do people use my product, that's my data. That's something I wanted to know, I'm not necessarily talking about peeking into people's email, no. It's actually the thing surrounding it. >> It's looking for the good things in the data. All right, let's talk about the customer alignment and customer expectations, you know customer user experience is driven by customer's expectations usually, right? As expectations change. And I think the Zoom thing jumped out at me, the Zoom IPO and their great success and were a customer as well, is that they really nailed the expectation of the user and cloud certainly helped them get that speed, but this is a key thing, if you could just deliver a great experience. >> Yeah. >> For those customers, you can actually win big part of the market. >> Yeah, if you Google, Eric. Eric doesn't speak to me as much, but if you Google Eric. >> We'll get him on theCUBE. >> What's sort of the jump? Hopefully I can help you to bring him here too. But what's going to be obvious if you Google search Eric he is sort of the notion of customer successes, my success. If customer is happy, I'm going to happy. So, my happiness hinges on the customer's happiness. So that's, kind of very important because only the SaaS model made that more natural. In traditional model, whether traditional on prime or we're not, you sort of celebrate when you have customer signing your PO and then you don't hear from the sales guy or three years, the sales guy may move on to another company, you don't know, right? But for the SaaS, it doesn't stop when sign the PO. You actually have to earn customers' happiness every single day. >> Adoption's critical. >> Yeah, customer success is important and then that's kind of the, so there is a huge alignment, very interesting alignment between customer's happiness, customer success, customer adoption of your product and you're sort of, the success, right? 'Cause you know, when I came to Zscaler, one of our first meeting is about, okay, we had a lot of customer interest us. They sign a PO. How to get them ramp up the actual first use, right? So, that kind of conversation doesn't happen in the traditional software company. You sign a PO. If the customer doesn't use your product for another 18 month which is actually quite normal, no one is going to jump up and say, "This is crazy!" Right? >> You know, we're going to do that on our Part Two, about the impact of the enterprise. But you made up a good point there, I want to just close out our last talk point is, the data driving the experience isn't like the old way of throw in, get the PO and celebrate. You got to, kind of, keep that going. The enterprise is changing and the enterprise has a tsunami of onboarding of new types of developers. In some cases they grow. We just had Cisco inside here on theCUBE this morning. They're turning network guys into programmers from CL command line prompt dudes to gals to coders. You're seeing developers now enter the enterprise to build the apps so there's now a digital transformation initiative for enterprises to be, I guess, SaaS-like. But it's hard. >> Yeah, I think that's, you know, this is part of the digital transformation. Every company, Fortune 500 or Fortune 2000 company need to do it, right? So, another interesting part is, when they do this on this journey of digitalization, you cannot possibly build all the infrastructure yourself. You will have to consume public cloud, you know sometimes private and hybrid cloud, and you are actually going to consume lots of the SaaS, right? Whether Zoom, the Zscaler, or the PagerDuty, I mean you are not going to be all those thing from scratch but you want it to have a very good, sort of the stack on top of it and how you going to take advantage of the SaaS, is a very interesting aspect. >> Well in Part Two of our chat, when we come back on our next discussion, I want to get into the enterprise. But to wrap up Part One here, innovation speed, leveraging data and the beautiful risk taking and benefits of SaaS. Large scale, fast, high value, target and developing an app or a venture. >> Yeah. >> What is your advice to entrepreneurs out there and/or someone who's doing a digital transformation? Where they want to leverage Saas, what's the playbook, what's the starting point, what's your advice? >> Well, there are a number of things. One, there are so many SaaS companies out there taking advantage of them, right? In the old days you have to hire email admins, you have to do this. Nowadays, all the SaaS, that's your kind of, you only need to worry about the business logic, you have some unique insight in the business and then just have, hire programmers to codify that and then the rest will magically happen because of the public cloud, because of the SaaS. So, be very mindful about the new environment you are in, that's number one. The second thing I want to say is, how do you look at AI technology? The older way is program something in a definitive way. I think there will be a limit for that. It has taken the software industry a long way to where we are. But, if you look at the next 20 years, I think a lot of the lift is going to be done by the AI Center. But it's not going to be easy to be done, you have to think about your data strategy, where are you going to have the massive, sustainable, unique, ideally even labeled data. If you don't have the labeled data, you have to have the strategy. How are you going to have some unique model with the data you have? So, the data strategy, right? So, essentially, how to take advantage of the cloud? How to take advantage of the data? And then on top of that you are going to do something that's solving an unmet um-- >> Customer problem. >> Customer problem. >> An acute landing spot in the market place. >> Unmet need. >> In a big market. >> In a big, well, in a big market. >> There it is. >> Even if there is already a mature solution I bet, since those mature solutions would not develop from that native cloud era, and the native AI era. You have plenty of opportunities. >> Howie, you and I are on the same page on this, I have been saying it truly believe we are living in an entrepreneurial era where, with your advice and what you just laid out, the better mousetrap can take down a big market. >> And, I'm hopeful that you will also disrupt the media business, you know we're-- >> Don't tell anyone! (laughing) We're still going to do that top secret of Silent Running. Howie, we're going to get Part Two. We're going to dig Deep into the enterprise, because the enterprise now has an opportunity in the first historic time in tech history, to use tools and technologies to completely reset and re-architect for this kind of capability. >> Absolutely. >> So, we'll hit that in Part Two. >> I'm super passionate about it too. >> Howie Xu, here inside theCUBE. Friend of theCUBE, legend in the industry. Great entrepreneur and technologist here, sharing CUBEConversation. I'm John Furrier, thanks for watching. (upbeat jazz music)

(upbeat music) >> Okay, welcome back everyone at Supercloud 2 event, live here in Palo Alto, theCUBE Studios live stage performance, virtually syndicating it all over the world. I'm John Furrier with Dave Vellante here as Cube alumni, and special influencer guest, Howie Xu, VP of Machine Learning and Zscaler, also part-time as a CUBE analyst 'cause he is that good. Comes on all the time. You're basically a CUBE analyst as well. Thanks for coming on. >> Thanks for inviting me. >> John: Technically, you're not really a CUBE analyst, but you're kind of like a CUBE analyst. >> Happy New Year to everyone. >> Dave: Great to see you. >> Great to see you, Dave and John. >> John: We've been talking about ChatGPT online. You wrote a great post about it being more like Amazon, not like Google. >> Howie: More than just Google Search. >> More than Google Search. Oh, it's going to compete with Google Search, which it kind of does a little bit, but more its infrastructure. So a clever point, good segue into this conversation, because this is kind of the beginning of these kinds of next gen things we're going to see. Things where it's like an obvious next gen, it's getting real. Kind of like seeing the browser for the first time, Mosaic browser. Whoa, this internet thing's real. I think this is that moment and Supercloud like enablement is coming. So this has been a big part of the Supercloud kind of theme. >> Yeah, you talk about Supercloud, you talk about, you know, AI, ChatGPT. I really think the ChatGPT is really another Netscape moment, the browser moment. Because if you think about internet technology, right? It was brewing for 20 years before early 90s. Not until you had a, you know, browser, people realize, "Wow, this is how wonderful this technology could do." Right? You know, all the wonderful things. Then you have Yahoo and Amazon. I think we have brewing, you know, the AI technology for, you know, quite some time. Even then, you know, neural networks, deep learning. But not until ChatGPT came along, people realize, "Wow, you know, the user interface, user experience could be that great," right? So I really think, you know, if you look at the last 30 years, there is a browser moment, there is iPhone moment. I think ChatGPT moment is as big as those. >> Dave: What do you see as the intersection of things like ChatGPT and the Supercloud? Of course, the media's going to focus, journalists are going to focus on all the negatives and the privacy. Okay. You know we're going to get by that, right? Always do. Where do you see the Supercloud and sort of the distributed data fitting in with ChatGPT? Does it use that as a data source? What's the link? >> Howie: I think there are number of use cases. One of the use cases, we talked about why we even have Supercloud because of the complexity, because of the, you know, heterogeneous nature of different clouds. In order for me as a developer, in order for me to create applications, I have so many things to worry about, right? It's a complexity. But with ChatGPT, with the AI, I don't have to worry about it, right? Those kind of details will be taken care of by, you know, the underlying layer. So we have been talking about on this show, you know, over the last, what, year or so about the Supercloud, hey, defining that, you know, API layer spanning across, you know, multiple clouds. I think that will be happening. However, for a lot of the things, that will be more hidden, right? A lot of that will be automated by the bots. You know, we were just talking about it right before the show. One of the profound statement I heard from Adrian Cockcroft about 10 years ago was, "Hey Howie, you know, at Netflix, right? You know, IT is just one API call away." That's a profound statement I heard about a decade ago. I think next decade, right? You know, the IT is just one English language away, right? So when it's one English language away, it's no longer as important, API this, API that. You still need API just like hardware, right? You still need all of those things. That's going to be more hidden. The high level thing will be more, you know, English language or the language, right? Any language for that matter. >> Dave: And so through language, you'll tap services that live across the Supercloud, is what you're saying? >> Howie: You just tell what you want, what you desire, right? You know, the bots will help you to figure out where the complexity is, right? You know, like you said, a lot of criticism about, "Hey, ChatGPT doesn't do this, doesn't do that." But if you think about how to break things down, right? For instance, right, you know, ChatGPT doesn't have Microsoft stock price today, obviously, right? However, you can ask ChatGPT to write a program for you, retrieve the Microsoft stock price, (laughs) and then just run it, right? >> Dave: Yeah. >> So the thing to think about- >> John: It's only going to get better. It's only going to get better. >> The thing people kind of unfairly criticize ChatGPT is it doesn't do this. But can you not break down humans' task into smaller things and get complex things to be done by the ChatGPT? I think we are there already, you know- >> John: That to me is the real game changer. That's the assembly of atomic elements at the top of the stack, whether the interface is voice or some programmatic gesture based thing, you know, wave your hand or- >> Howie: One of the analogy I used in my blog was, you know, each person, each professional now is a quarterback. And we suddenly have, you know, a lot more linebacks or you know, any backs to work for you, right? For free even, right? You know, and then that's sort of, you should think about it. You are the quarterback of your day-to-day job, right? Your job is not to do everything manually yourself. >> Dave: You call the play- >> Yes. >> Dave: And they execute. Do your job. >> Yes, exactly. >> Yeah, all the players are there. All the elves are in the North Pole making the toys, Dave, as we say. But this is the thing, I want to get your point. This change is going to require a new kind of infrastructure software relationship, a new kind of operating runtime, a new kind of assembler, a new kind of loader link things. This very operating systems kind of concepts. >> Data intensive, right? How to process the data, how to, you know, process so gigantic data in parallel, right? That's actually a tough job, right? So if you think about ChatGPT, why OpenAI is ahead of the game, right? You know, Google may not want to acknowledge it, right? It's not necessarily they do, you know, not have enough data scientist, but the software engineering pieces, you know, behind it, right? To train the model, to actually do all those things in parallel, to do all those things in a cost effective way. So I think, you know, a lot of those still- >> Let me ask you a question. Let me ask you a question because we've had this conversation privately, but I want to do it while we're on stage here. Where are all the alpha geeks and developers and creators and entrepreneurs going to gravitate to? You know, in every wave, you see it in crypto, all the alphas went into crypto. Now I think with ChatGPT, you're going to start to see, like, "Wow, it's that moment." A lot of people are going to, you know, scrum and do startups. CTOs will invent stuff. There's a lot of invention, a lot of computer science and customer requirements to figure out. That's new. Where are the alpha entrepreneurs going to go to? What do you think they're going to gravitate to? If you could point to the next layer to enable this super environment, super app environment, Supercloud. 'Cause there's a lot to do to enable what you just said. >> Howie: Right. You know, if you think about using internet as the analogy, right? You know, in the early 90s, internet came along, browser came along. You had two kind of companies, right? One is Amazon, the other one is walmart.com. And then there were company, like maybe GE or whatnot, right? Really didn't take advantage of internet that much. I think, you know, for entrepreneurs, suddenly created the Yahoo, Amazon of the ChatGPT native era. That's what we should be all excited about. But for most of the Fortune 500 companies, your job is to surviving sort of the big revolution. So you at least need to do your walmart.com sooner than later, right? (laughs) So not be like GE, right? You know, hand waving, hey, I do a lot of the internet, but you know, when you look back last 20, 30 years, what did they do much with leveraging the- >> So you think they're going to jump in, they're going to build service companies or SaaS tech companies or Supercloud companies? >> Howie: Okay, so there are two type of opportunities from that perspective. One is, you know, the OpenAI ish kind of the companies, I think the OpenAI, the game is still open, right? You know, it's really Close AI today. (laughs) >> John: There's room for competition, you mean? >> There's room for competition, right. You know, you can still spend you know, 50, $100 million to build something interesting. You know, there are company like Cohere and so on and so on. There are a bunch of companies, I think there is that. And then there are companies who's going to leverage those sort of the new AI primitives. I think, you know, we have been talking about AI forever, but finally, finally, it's no longer just good, but also super useful. I think, you know, the time is now. >> John: And if you have the cloud behind you, what do you make the Amazon do differently? 'Cause Amazon Web Services is only going to grow with this. It's not going to get smaller. There's more horsepower to handle, there's more needs. >> Howie: Well, Microsoft already showed what's the future, right? You know, you know, yes, there is a kind of the container, you know, the serverless that will continue to grow. But the future is really not about- >> John: Microsoft's shown the future? >> Well, showing that, you know, working with OpenAI, right? >> Oh okay. >> They already said that, you know, we are going to have ChatGPT service. >> $10 billion, I think they're putting it. >> $10 billion putting, and also open up the Open API services, right? You know, I actually made a prediction that Microsoft future hinges on OpenAI. I think, you know- >> John: They believe that $10 billion bet. >> Dave: Yeah. $10 billion bet. So I want to ask you a question. It's somewhat academic, but it's relevant. For a number of years, it looked like having first mover advantage wasn't an advantage. PCs, spreadsheets, the browser, right? Social media, Friendster, right? Mobile. Apple wasn't first to mobile. But that's somewhat changed. The cloud, AWS was first. You could debate whether or not, but AWS okay, they have first mover advantage. Crypto, Bitcoin, first mover advantage. Do you think OpenAI will have first mover advantage? >> It certainly has its advantage today. I think it's year two. I mean, I think the game is still out there, right? You know, we're still in the first inning, early inning of the game. So I don't think that the game is over for the rest of the players, whether the big players or the OpenAI kind of the, sort of competitors. So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest, to get, you know, another shot to the OpenAI sort of the level?" You know, I did a- (laughs) >> Line up. >> That's classic VC. "How much does it cost me to replicate?" >> I'm pretty sure he asked the question to a bunch of guys, right? >> Good luck with that. (laughs) >> So we kind of did some napkin- >> What'd you come up with? (laughs) >> $100 million is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So 100 million. >> John: Hundreds of millions. >> Yeah, yeah, yeah. 100 million order of magnitude is what I came up with. You know, we can get into details, you know, in other sort of the time, but- >> Dave: That's actually not that much if you think about it. >> Howie: Exactly. So when he heard me articulating why is that, you know, he's thinking, right? You know, he actually, you know, asked me, "Hey, you know, there's this company. Do you happen to know this company? Can I reach out?" You know, those things. So I truly believe it's not a billion or 10 billion issue, it's more like 100. >> John: And also, your other point about referencing the internet revolution as a good comparable. The other thing there is online user population was a big driver of the growth of that. So what's the equivalent here for online user population for AI? Is it more apps, more users? I mean, we're still early on, it's first inning. >> Yeah. We're kind of the, you know- >> What's the key metric for success of this sector? Do you have a read on that? >> I think the, you know, the number of users is a good metrics, but I think it's going to be a lot of people are going to use AI services without even knowing they're using it, right? You know, I think a lot of the applications are being already built on top of OpenAI, and then they are kind of, you know, help people to do marketing, legal documents, you know, so they're already inherently OpenAI kind of the users already. So I think yeah. >> Well, Howie, we've got to wrap, but I really appreciate you coming on. I want to give you a last minute to wrap up here. In your experience, and you've seen many waves of innovation. You've even had your hands in a lot of the big waves past three inflection points. And obviously, machine learning you're doing now, you're deep end. Why is this Supercloud movement, this wave of Supercloud and the discussion of this next inflection point, why is it so important? For the folks watching, why should they be paying attention to this particular moment in time? Could you share your super clip on Supercloud? >> Howie: Right. So this is simple from my point of view. So why do you even have cloud to begin with, right? IT is too complex, too complex to operate or too expensive. So there's a newer model. There is a better model, right? Let someone else operate it, there is elasticity out of it, right? That's great. Until you have multiple vendors, right? Many vendors even, you know, we're talking about kind of how to make multiple vendors look like the same, but frankly speaking, even one vendor has, you know, thousand services. Now it's kind of getting, what Kid was talking about what, cloud chaos, right? It's the evolution. You know, the history repeats itself, right? You know, you have, you know, next great things and then too many great things, and then people need to sort of abstract this out. So it's almost that you must do this. But I think how to abstract this out is something that at this time, AI is going to help a lot, right? You know, like I mentioned, right? A lot of the abstraction, you don't have to think about API anymore. I bet 10 years from now, you know, IT is one language away, not API away. So think about that world, right? So Supercloud in, in my opinion, sure, you kind of abstract things out. You have, you know, consistent layers. But who's going to do that? Is that like we all agreed upon the model, agreed upon those APIs? Not necessary. There are certain, you know, truth in that, but there are other truths, let bots take care of, right? Whether you know, I want some X happens, whether it's going to be done by Azure, by AWS, by GCP, bots will figure out at a given time with certain contacts with your security requirement, posture requirement. I'll think that out. >> John: That's awesome. And you know, Dave, you and I have been talking about this. We think scale is the new ratification. If you have first mover advantage, I'll see the benefit, but scale is a huge thing. OpenAI, AWS. >> Howie: Yeah. Every day, we are using OpenAI. Today, we are labeling data for them. So you know, that's a little bit of the- (laughs) >> John: Yeah. >> First mover advantage that other people don't have, right? So it's kind of scary. So I'm very sure that Google is a little bit- (laughs) >> When we do our super AI event, you're definitely going to be keynoting. (laughs) >> Howie: I think, you know, we're talking about Supercloud, you know, before long, we are going to talk about super intelligent cloud. (laughs) >> I'm super excited, Howie, about this. Thanks for coming on. Great to see you, Howie Xu. Always a great analyst for us contributing to the community. VP of Machine Learning and Zscaler, industry legend and friend of theCUBE. Thanks for coming on and sharing really, really great advice and insight into what this next wave means. This Supercloud is the next wave. "If you're not on it, you're driftwood," says Pat Gelsinger. So you're going to see a lot more discussion. We'll be back more here live in Palo Alto after this short break. >> Thank you. (upbeat music)

(upbeat music) >> Hello and welcome back to theCUBE. We're here in Palo Alto, California. I'm your host, John Furrier with a special guest here in the studio. As part of our Cloud Native SecurityCon Coverage we had an opportunity to bring in Jon Turow who is the partner at Madrona Venture Partners formerly with AWS and to talk about machine learning, foundational models, and how the future of AI is going to be impacted by some of the innovation around what's going on in the industry. ChatGPT has taken the world by storm. A million downloads, fastest to the million downloads there. Before some were saying it's just a gimmick. Others saying it's a game changer. Jon's here to break it down, and great to have you on. Thanks for coming in. >> Thanks John. Glad to be here. >> Thanks for coming on. So first of all, I'm glad you're here. First of all, because two things. One, you were formerly with AWS, got a lot of experience running projects at AWS. Now a partner at Madrona, a great firm doing great deals, and they had this future at modern application kind of thesis. Now you are putting out some content recently around foundational models. You're deep into computer vision. You were the IoT general manager at AWS among other things, Greengrass. So you know a lot about data. You know a lot about some of this automation, some of the edge stuff. You've been in the middle of all these kind of areas that now seem to be the next wave coming. So I wanted to ask you what your thoughts are of how the machine learning and this new automation wave is coming in, this AI tools are coming out. Is it a platform? Is it going to be smarter? What feeds AI? What's your take on this whole foundational big movement into AI? What's your general reaction to all this? >> So, thanks, Jon, again for having me here. Really excited to talk about these things. AI has been coming for a long time. It's been kind of the next big thing. Always just over the horizon for quite some time. And we've seen really compelling applications in generations before and until now. Amazon and AWS have introduced a lot of them. My firm, Madrona Venture Group has invested in some of those early players as well. But what we're seeing now is something categorically different. That's really exciting and feels like a durable change. And I can try and explain what that is. We have these really large models that are useful in a general way. They can be applied to a lot of different tasks beyond the specific task that the designers envisioned. That makes them more flexible, that makes them more useful for building applications than what we've seen before. And so that, we can talk about the depths of it, but in a nutshell, that's why I think people are really excited. >> And I think one of the things that you wrote about that jumped out at me is that this seems to be this moment where there's been a multiple decades of nerds and computer scientists and programmers and data thinkers around waiting for AI to blossom. And it's like they're scratching that itch. Every year is going to be, and it's like the bottleneck's always been compute power. And we've seen other areas, genome sequencing, all kinds of high computation things where required high forms computing. But now there's no real bottleneck to compute. You got cloud. And so you're starting to see the emergence of a massive acceleration of where AI's been and where it needs to be going. Now, it's almost like it's got a reboot. It's almost a renaissance in the AI community with a whole nother macro environmental things happening. Cloud, younger generation, applications proliferate from mobile to cloud native. It's the perfect storm for this kind of moment to switch over. Am I overreading that? Is that right? >> You're right. And it's been cooking for a cycle or two. And let me try and explain why that is. We have cloud and AWS launch in whatever it was, 2006, and offered more compute to more people than really was possible before. Initially that was about taking existing applications and running them more easily in a bigger scale. But in that period of time what's also become possible is new kinds of computation that really weren't practical or even possible without that vast amount of compute. And so one result that came of that is something called the transformer AI model architecture. And Google came out with that, published a paper in 2017. And what that says is, with a transformer model you can actually train an arbitrarily large amount of data into a model, and see what happens. That's what Google demonstrated in 2017. The what happens is the really exciting part because when you do that, what you start to see, when models exceed a certain size that we had never really seen before all of a sudden they get what we call emerging capabilities of complex reasoning and reasoning outside a domain and reasoning with data. The kinds of things that people describe as spooky when they play with something like ChatGPT. That's the underlying term. We don't as an industry quite know why it happens or how it happens, but we can measure that it does. So cloud enables new kinds of math and science. New kinds of math and science allow new kinds of experimentation. And that experimentation has led to this new generation of models. >> So one of the debates we had on theCUBE at our Supercloud event last month was, what's the barriers to entry for say OpenAI, for instance? Obviously, I weighed in aggressively and said, "The barriers for getting into cloud are high because all the CapEx." And Howie Xu formerly VMware, now at ZScaler, he's an AI machine learning guy. He was like, "Well, you can spend $100 million and replicate it." I saw a quote that set up for 180,000 I can get this other package. What's the barriers to entry? Is ChatGPT or OpenAI, does it have sustainability? Is it easy to get into? What is the market like for AI? I mean, because a lot of entrepreneurs are jumping in. I mean, I just read a story today. San Francisco's got more inbound migration because of the AI action happening, Seattle's booming, Boston with MIT's been working on neural networks for generations. That's what we've found the answer. Get off the neural network, Boston jump on the AI bus. So there's total excitement for this. People are enthusiastic around this area. >> You can think of an iPhone versus Android tension that's happening today. In the iPhone world, there are proprietary models from OpenAI who you might consider as the leader. There's Cohere, there's AI21, there's Anthropic, Google's going to have their own, and a few others. These are proprietary models that developers can build on top of, get started really quickly. They're measured to have the highest accuracy and the highest performance today. That's the proprietary side. On the other side, there is an open source part of the world. These are a proliferation of model architectures that developers and practitioners can take off the shelf and train themselves. Typically found in Hugging face. What people seem to think is that the accuracy and performance of the open source models is something like 18 to 20 months behind the accuracy and performance of the proprietary models. But on the other hand, there's infinite flexibility for teams that are capable enough. So you're going to see teams choose sides based on whether they want speed or flexibility. >> That's interesting. And that brings up a point I was talking to a startup and the debate was, do you abstract away from the hardware and be software-defined or software-led on the AI side and let the hardware side just extremely accelerate on its own, 'cause it's flywheel? So again, back to proprietary, that's with hardware kind of bundled in, bolted on. Is it accelerator or is it bolted on or is it part of it? So to me, I think that the big struggle in understanding this is that which one will end up being right. I mean, is it a beta max versus VHS kind of thing going on? Or iPhone, Android, I mean iPhone makes a lot of sense, but if you're Apple, but is there an Apple moment in the machine learning? >> In proprietary models, here does seem to be a jump ball. That there's going to be a virtuous flywheel that emerges that, for example, all these excitement about ChatGPT. What's really exciting about it is it's really easy to use. The technology isn't so different from what we've seen before even from OpenAI. You mentioned a million users in a short period of time, all providing training data for OpenAI that makes their underlying models, their next generation even better. So it's not unreasonable to guess that there's going to be power laws that emerge on the proprietary side. What I think history has shown is that iPhone, Android, Windows, Linux, there seems to be gravity towards this yin and yang. And my guess, and what other people seem to think is going to be the case is that we're going to continue to see these two poles of AI. >> So let's get into the relationship with data because I've been emerging myself with ChatGPT, fascinated by the ease of use, yes, but also the fidelity of how you query it. And I felt like when I was doing writing SQL back in the eighties and nineties where SQL was emerging. You had to be really a guru at the SQL to get the answers you wanted. It seems like the querying into ChatGPT is a good thing if you know how to talk to it. Labeling whether your input is and it does a great job if you feed it right. If you ask a generic questions like Google. It's like a Google search. It gives you great format, sounds credible, but the facts are kind of wrong. >> That's right. >> That's where general consensus is coming on. So what does that mean? That means people are on one hand saying, "Ah, it's bullshit 'cause it's wrong." But I look at, I'm like, "Wow, that's that's compelling." 'Cause if you feed it the right data, so now we're in the data modeling here, so the role of data's going to be critical. Is there a data operating system emerging? Because if this thing continues to go the way it's going you can almost imagine as you would look at companies to invest in. Who's going to be right on this? What's going to scale? What's sustainable? What could build a durable company? It might not look what like what people think it is. I mean, I remember when Google started everyone thought it was the worst search engine because it wasn't a portal. But it was the best organic search on the planet became successful. So I'm trying to figure out like, okay, how do you read this? How do you read the tea leaves? >> Yeah. There are a few different ways that companies can differentiate themselves. Teams with galactic capabilities to take an open source model and then change the architecture and retrain and go down to the silicon. They can do things that might not have been possible for other teams to do. There's a company that that we're proud to be investors in called RunwayML that provides video accelerated, sorry, AI accelerated video editing capabilities. They were used in everything, everywhere all at once and some others. In order to build RunwayML, they needed a vision of what the future was going to look like and they needed to make deep contributions to the science that was going to enable all that. But not every team has those capabilities, maybe nor should they. So as far as how other teams are going to differentiate there's a couple of things that they can do. One is called prompt engineering where they shape on behalf of their own users exactly how the prompt to get fed to the underlying model. It's not clear whether that's going to be a durable problem or whether like Google, we consumers are going to start to get more intuitive about this. That's one. The second is what's called information retrieval. How can I get information about the world outside, information from a database or a data store or whatever service into these models so they can reason about them. And the third is, this is going to sound funny, but attribution. Just like you would do in a news report or an academic paper. If you can state where your facts are coming from, the downstream consumer or the human being who has to use that information actually is going to be able to make better sense of it and rely better on it. So that's prompt engineering, that's retrieval, and that's attribution. >> So that brings me to my next point I want to dig in on is the foundational model stack that you published. And I'll start by saying that with ChatGPT, if you take out the naysayers who are like throwing cold water on it about being a gimmick or whatever, and then you got the other side, I would call the alpha nerds who are like they can see, "Wow, this is amazing." This is truly NextGen. This isn't yesterday's chatbot nonsense. They're like, they're all over it. It's that everybody's using it right now in every vertical. I heard someone using it for security logs. I heard a data center, hardware vendor using it for pushing out appsec review updates. I mean, I've heard corner cases. We're using it for theCUBE to put our metadata in. So there's a horizontal use case of value. So to me that tells me it's a market there. So when you have horizontal scalability in the use case you're going to have a stack. So you publish this stack and it has an application at the top, applications like Jasper out there. You're seeing ChatGPT. But you go after the bottom, you got silicon, cloud, foundational model operations, the foundational models themselves, tooling, sources, actions. Where'd you get this from? How'd you put this together? Did you just work backwards from the startups or was there a thesis behind this? Could you share your thoughts behind this foundational model stack? >> Sure. Well, I'm a recovering product manager and my job that I think about as a product manager is who is my customer and what problem he wants to solve. And so to put myself in the mindset of an application developer and a founder who is actually my customer as a partner at Madrona, I think about what technology and resources does she need to be really powerful, to be able to take a brilliant idea, and actually bring that to life. And if you spend time with that community, which I do and I've met with hundreds of founders now who are trying to do exactly this, you can see that the stack is emerging. In fact, we first drew it in, not in January 2023, but October 2022. And if you look at the difference between the October '22 and January '23 stacks you're going to see that holes in the stack that we identified in October around tooling and around foundation model ops and the rest are organically starting to get filled because of how much demand from the developers at the top of the stack. >> If you look at the young generation coming out and even some of the analysts, I was just reading an analyst report on who's following the whole data stacks area, Databricks, Snowflake, there's variety of analytics, realtime AI, data's hot. There's a lot of engineers coming out that were either data scientists or I would call data platform engineering folks are becoming very key resources in this area. What's the skillset emerging and what's the mindset of that entrepreneur that sees the opportunity? How does these startups come together? Is there a pattern in the formation? Is there a pattern in the competency or proficiency around the talent behind these ventures? >> Yes. I would say there's two groups. The first is a very distinct pattern, John. For the past 10 years or a little more we've seen a pattern of democratization of ML where more and more people had access to this powerful science and technology. And since about 2017, with the rise of the transformer architecture in these foundation models, that pattern has reversed. All of a sudden what has become broader access is now shrinking to a pretty small group of scientists who can actually train and manipulate the architectures of these models themselves. So that's one. And what that means is the teams who can do that have huge ability to make the future happen in ways that other people don't have access to yet. That's one. The second is there is a broader population of people who by definition has even more collective imagination 'cause there's even more people who sees what should be possible and can use things like the proprietary models, like the OpenAI models that are available off the shelf and try to create something that maybe nobody has seen before. And when they do that, Jasper AI is a great example of that. Jasper AI is a company that creates marketing copy automatically with generative models such as GPT-3. They do that and it's really useful and it's almost fun for a marketer to use that. But there are going to be questions of how they can defend that against someone else who has access to the same technology. It's a different population of founders who has to find other sources of differentiation without being able to go all the way down to the the silicon and the science. >> Yeah, and it's going to be also opportunity recognition is one thing. Building a viable venture product market fit. You got competition. And so when things get crowded you got to have some differentiation. I think that's going to be the key. And that's where I was trying to figure out and I think data with scale I think are big ones. Where's the vulnerability in the stack in terms of gaps? Where's the white space? I shouldn't say vulnerability. I should say where's the opportunity, where's the white space in the stack that you see opportunities for entrepreneurs to attack? >> I would say there's two. At the application level, there is almost infinite opportunity, John, because almost every kind of application is about to be reimagined or disrupted with a new generation that takes advantage of this really powerful new technology. And so if there is a kind of application in almost any vertical, it's hard to rule something out. Almost any vertical that a founder wishes she had created the original app in, well, now it's her time. So that's one. The second is, if you look at the tooling layer that we discussed, tooling is a really powerful way that you can provide more flexibility to app developers to get more differentiation for themselves. And the tooling layer is still forming. This is the interface between the models themselves and the applications. Tools that help bring in data, as you mentioned, connect to external actions, bring context across multiple calls, chain together multiple models. These kinds of things, there's huge opportunity there. >> Well, Jon, I really appreciate you coming in. I had a couple more questions, but I will take a minute to read some of your bios for the audience and we'll get into, I won't embarrass you, but I want to set the context. You said you were recovering product manager, 10 plus years at AWS. Obviously, recovering from AWS, which is a whole nother dimension of recovering. In all seriousness, I talked to Andy Jassy around that time and Dr. Matt Wood and it was about that time when AI was just getting on the radar when they started. So you guys started seeing the wave coming in early on. So I remember at that time as Amazon was starting to grow significantly and even just stock price and overall growth. From a tech perspective, it was pretty clear what was coming, so you were there when this tsunami hit. >> Jon: That's right. >> And you had a front row seat building tech, you were led the product teams for Computer Vision AI, Textract, AI intelligence for document processing, recognition for image and video analysis. You wrote the business product plan for AWS IoT and Greengrass, which we've covered a lot in theCUBE, which extends out to the whole edge thing. So you know a lot about AI/ML, edge computing, IOT, messaging, which I call the law of small numbers that scale become big. This is a big new thing. So as a former AWS leader who's been there and at Madrona, what's your investment thesis as you start to peruse the landscape and talk to entrepreneurs as you got the stack? What's the big picture? What are you looking for? What's the thesis? How do you see this next five years emerging? >> Five years is a really long time given some of this science is only six months out. I'll start with some, no pun intended, some foundational things. And we can talk about some implications of the technology. The basics are the same as they've always been. We want, what I like to call customers with their hair on fire. So they have problems, so urgent they'll buy half a product. The joke is if your hair is on fire you might want a bucket of cold water, but you'll take a tennis racket and you'll beat yourself over the head to put the fire out. You want those customers 'cause they'll meet you more than halfway. And when you find them, you can obsess about them and you can get better every day. So we want customers with their hair on fire. We want founders who have empathy for those customers, understand what is going to be required to serve them really well, and have what I like to call founder-market fit to be able to build the products that those customers are going to need. >> And because that's a good strategy from an emerging, not yet fully baked out requirements definition. >> Jon: That's right. >> Enough where directionally they're leaning in, more than in, they're part of the product development process. >> That's right. And when you're doing early stage development, which is where I personally spend a lot of my time at the seed and A and a little bit beyond that stage often that's going to be what you have to go on because the future is going to be so complex that you can't see the curves beyond it. But if you have customers with their hair on fire and talented founders who have the capability to serve those customers, that's got me interested. >> So if I'm an entrepreneur, I walk in and say, "I have customers that have their hair on fire." What kind of checks do you write? What's the kind of the average you're seeing for seed and series? Probably seed, seed rounds and series As. >> It can depend. I have seen seed rounds of double digit million dollars. I have seen seed rounds much smaller than that. It really depends on what is going to be the right thing for these founders to prove out the hypothesis that they're testing that says, "Look, we have this customer with her hair on fire. We think we can build at least a tennis racket that she can use to start beating herself over the head and put the fire out. And then we're going to have something really interesting that we can scale up from there and we can make the future happen. >> So it sounds like your advice to founders is go out and find some customers, show them a product, don't obsess over full completion, get some sort of vibe on fit and go from there. >> Yeah, and I think by the time founders come to me they may not have a product, they may not have a deck, but if they have a customer with her hair on fire, then I'm really interested. >> Well, I always love the professional services angle on these markets. You go in and you get some business and you understand it. Walk away if you don't like it, but you see the hair on fire, then you go in product mode. >> That's right. >> All Right, Jon, thank you for coming on theCUBE. Really appreciate you stopping by the studio and good luck on your investments. Great to see you. >> You too. >> Thanks for coming on. >> Thank you, Jon. >> CUBE coverage here at Palo Alto. I'm John Furrier, your host. More coverage with CUBE Conversations after this break. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

>> Welcome back everyone to the closing remarks here before we kick off our ecosystem portion of the program. We're live in Palo Alto for theCUBE special presentation of Supercloud 2. It's the second edition, the first one was in August. I'm John Furrier with Dave Vellante. Here to wrap up with our special guest analyst George Gilbert, investor and industry legend former colleague of ours, analyst at Wikibon. George great to see you. Dave, you know, wrapping up this day what in a phenomenal program. We had a contribution from industry vendors, industry experts, practitioners and customers building and redefining their company's business model. Rolling out technology for Supercloud and multicloud and ultimately changing how they do data. And data was the theme today. So very, very great program. Before we jump into our favorite parts let's give a shout out to the folks who make this possible. Free contents our mission. We'll always stay true to that mission. We want to thank VMware, alkira, ChaosSearch, prosimo for being sponsors of this great program. We will have Supercloud 3 coming up in a month or so, or two months. We'll see. Or sooner, we don't know. But it'll be more about security, but a lot more momentum. Okay, so that's... >> And don't forget too that this program not going to end now. We've got a whole ecosystem speaks track so stay tuned for that. >> John: Yeah, we got another 20 interviews. Feels like it. >> Well, you're going to hear from Saks, Veronika Durgin. You're going to hear from Western Union, Harveer Singh. You're going to hear from Ionis Pharmaceuticals, Nick Taylor. Brian Gracely chimes in on Supecloud. So he's the man behind the cloud cast. >> Yeah, and you know, the practitioners again, pay attention to also to the cloud networking interviews. Lot of change going on there that's going to be disruptive and actually change the landscape as well. Again, as Supercloud progresses to be the next big thing. If you're not on this next wave, you'll drift what, as Pat Gelsinger says. >> Yep. >> To kick off the closing segments, George, Dave, this is a wave that's been identified. Again, people debate the word all you want Supercloud. It is a gateway to multicloud eventually it is the standard for new applications, new ways to do data. There's new computer science being generated and customer requirements being addressed. So it's the confluence of, you know, tectonic plates shifting in the industry, new computer science seeing things like AI and machine learning and data at the center of it and new infrastructure all kind of coming together. So, to me, that's my takeaway so far. That is the big story and it's going to change society and ultimately the business models of these companies. >> Well, we've had 10, you know, you think about it we came out of the financial crisis. We've had 10, 12 years despite the Covid of tech success, right? And just now CIOs are starting to hit the brakes. And so my point is you've had all this innovation building up for a decade and you've got this massive ecosystem that is running on the cloud and the ecosystem is saying, hey, we can have even more value by tapping best of of breed across clouds. And you've got customers saying, hey, we need help. We want to do more and we want to point our business and our intellectual property, our software tooling at our customers and monetize our data. So you have all these forces coming together and it's sort of entering a new era. >> George, I want to go to you for a second because you are big contributor to this event. Your interview with Bob Moglia with Dave was I thought a watershed moment for me to hear that the data apps, how databases are being rethought because we've been seeing a diversity of databases with Amazon Web services, you know, promoting no one database rules of the world. Now it's not one database kind of architecture that's puling these new apps. What's your takeaway from this event? >> So if you keep your eye on this North Star where instead of building apps that are based on code you're building apps that are defined by data coming off of things that are linked to the real world like people, places, things and activities. Then the idea is, and the example we use is, you know, Uber but it could be, you know, amazon.com is defined by stuff coming off data in the Amazon ecosystem or marketplace. And then the question is, and everyone was talking at different angles on this, which was, where's the data live? How much do you hide from the developer? You know, and when can you offer that? You know, and you started with Walmart which was describing apps, traditional apps that are just code. And frankly that's easier to make that cross cloud and you know, essentially location independent. As soon as you have data you need data management technology that a customer does not have the sophistication to build. And then the argument was like, so how much can you hide from the developer who's building data apps? Tristan's version was you take the modern data stack and you start adding these APIs that define business concepts like bookings, billings and revenue, you know, or in the Uber example like drivers and riders, you know, and ETA's and prices. But those things execute still on the data warehouse or data lakehouse. Then Bob Muglia was saying you're not really hiding enough from the developer because you still got to say how to do all that. And his vision is not only do you hide where the data is but you hide how to sort of get at all that code by just saying what you want. You define how a car and how a driver and how a rider works. And then those things automatically figure out underneath the cover. >> So huge challenges, right? There's governance, there's security, they could be big blockers to, you know, the Supercloud but the industry's going to be attacking that problem. >> Well, what's your take? What's your favorite segment? Zhamak Dehghani came on, she's starting in that company, exclusive news. That was big notable moment for theCUBE. She launched her company. She pioneered the data mesh concept. And I think what George is saying and what data mesh points to is something that we've been saying for a long time. That data is now going to flip the script on how apps behave. And the Uber example I think is illustrated 'cause people can relate to Uber. But imagine that for every business whether it's a manufacturing business or retail or oil and gas or FinTech, they can look at their business like a game almost gamify it with data, riders, cars you know, moving data around the value of data. This is something that Adam Selipsky teased out at AWS, Dave. So what's your takeaway from this Supercloud? Where are we in your mind? Well big thing is data products and decentralizing your data architecture, but putting data in the hands of domain experts who can actually monetize the data. And I think that's, to me that's really exciting. Because look, data products financial industry has always been doing building data products. Mortgage backed securities is a data product. But why should the financial industry have all the fun? I mean virtually every organization can tap its ecosystem build data products, take its internal IP and processes and software and point it to the world and actually begin to make money out of it. >> Okay, so let's go around the horn. I'll start, I'll get you guys some time to think. Next question, what did you learn today? I learned that I think it's an infrastructure game and talking to Kit Colbert at VMware, I think it's all about infrastructure refactoring and I think the data's going to be an ingredient that's going to be operating system like. I think you're going to see the infrastructure influencing operations that will enable Superclouds to be real. And developers won't even know what a Supercloud is because they'll be using it. It's the operations focus is going to be very critical. Just like DevOps movements started Cloud native I think you're going to see a data native movement and I think infrastructure is critical as people go to the next level. That's my big takeaway today. And I'll say the data conversation is at the center. I think security, data are going to be always active horizontally scalable concepts, but every company's going to reset their infrastructure, how it looks and if it's not set up for data and or things that there need to be agile on, it's going to be a non-starter. So I think that's the cloud NextGen, distributed computing. >> I mean, what came into focus for me was I think the hyperscaler is going to continue to do their thing, you know, and be very, very successful and they're each coming at it from different approaches. We talk about this all the time in theCUBE. Amazon the best infrastructure, you know, Google's got its you know, data and AI thing and it's playing catch up and Microsoft's got this massive estate. Okay, cool. Check. The next wave of innovation which is coming from data, I've always said follow the data. That's where the where the money's going to be is going to come from other places. People want to be able to, organizations want to be able to share data across clouds across their organization, outside of their ecosystem and make money with that data sharing. They don't want to FTP it anymore. I got it. You take it. They want to work with live data in real time and I think the edge, we didn't talk much about the edge today is going to even take that to a new level real time inferencing at the edge, AI and and being able to do new things with data that we haven't even seen. But playing around with ChatGPT, it's blowing our mind. And I think you're right, it's like when we first saw the browser, holy crap, this is going to change the world. >> Yeah. And the ChatGPT by the way is going to create a wave of machine learning and data refactoring for sure. But also Howie Liu had an interesting comment, he was asked by a VC how much to replicate that and he said it's in the hundreds of millions, not billions. Now if you asked that same question how much does it cost to replicate AWS? The CapEx alone is unstoppable, they're already done. So, you know, the hyperscalers are going to continue to boom. I think they're going to drive the infrastructure. I think Amazon's going to be really strong at silicon and physics and squeeze every ounce atom out of every physical thing and then get latency as your bottleneck and the rest is all going to be... >> That never blew me away, a hundred million to create kind of an open AI, you know, competitor. Look at companies like Lacework. >> John: Some people have that much cash on the balance sheet. >> These are security companies that have raised a billion dollars, right? To compete. You know, so... >> If you're not shifting left what do you do with data, shift up? >> But, you know. >> What did you learn, George? >> I'm listening to you and I think you're helping me crystallize something which is the software infrastructure to enable the data apps is wide open. The way Zhamak described it is like if you want a data product like a sales and operation plan, that is built on other data products, like a sales plan which has a forecast in it, it has a production plan, it has a procurement plan and then a sales and operation plan is actually a composition of all those and they call each other. Now in her current platform, you need to expose to the developer a certain amount of mechanics on how to move all that data, when to move it. Like what happens if something fails. Now Muglia is saying I can hide that completely. So all you have to say is what you want and the underlying machinery takes care of everything. The problem is Muglia stuff is still a few years off. And Tristan is saying, I can give you much of that today but it's got to run in the data warehouse. So this trade offs all different ways. But again, I agree with you that the Cloud platform vendors or the ecosystem participants who can run across Cloud platforms and private infrastructure will be the next platform. And then the cloud platform is sort of where you run the big honking centralized stuff where someone else manages the operations. >> Sounds like middleware to me, Dave >> And key is, I'll just end with this. The key is being able to get to the data, whether it's in a data warehouse or a data lake or a S3 bucket or an object store, Oracle database, whatever. It's got to be inclusive that is critical to execute on the vision that you just talked about 'cause that data's in different systems and you're not going to put it all into some new system. >> So creating middleware in the cloud that sounds what it sounds like to me. >> It's like, you discovered PaaS >> It's a super PaaS. >> But it's platform services 'cause PaaS connotes like a tightly integrated platform. >> Well this is the real thing that's going on. We're going to see how this evolves. George, great to have you on, Dave. Thanks for the summary. I enjoyed this segment a lot today. This ends our stage performance live here in Palo Alto. As you know, we're live stage performance and syndicate out virtually. Our afternoon program's going to kick in now you're going to hear some great interviews. We got ChaosSearch. Defining the network Supercloud from prosimo. Future of Cloud Network, alkira. We got Saks, a retail company here, Veronika Durgin. We got Dave with Western Union. So a lot of customers, a pharmaceutical company Warner Brothers, Discovery, media company. And then you know, what is really needed for Supercloud, good panels. So stay with us for the afternoon program. That's part two of Supercloud 2. This is a wrap up for our stage live performance. I'm John Furrier with Dave Vellante and George Gilbert here wrapping up. Thanks for watching and enjoy the program. (bright music)

(upbeat electronic music) >> Welcome back to everyone, to "theCUBE's" coverage here in Seattle, Washington for Amazon Web Services Partner Marketplace Seller Conference, combining their partner network with Marketplace forming a new organization called AWS Partner Organization. This is "theCUBE" coverage. I'm John Furrier, your host. We've got great "Cube" alumni here from Zscaler, a very successful cloud company doing great work. Stelio D'Alo, senior director of cloud business development and Raveesh Chugh, VP of Public Cloud Partnerships at Zscaler. Welcome back to "theCUBE." Good to see you guys. Thanks for coming on. >> Thank you. >> Thanks having us, John. >> So we've been doing a lot of coverage of Zscaler, what a great success story. I mean, the numbers are great. The business performance, it's in the top two, three, one, two, three in all metrics on public companies, SaaS. So you guys, check. Good job. >> Yes, thank you. >> So you guys have done a good job. Now you're here, selling through the Marketplace. You guys are a world class performing company in cloud SaaS, so you're in the front lines doing well. Now, Marketplace is a procurement front end opportunity for people to buy. Hey, self-service, buy and put things together. Sounds novel, what a great concept. Great cloud life. >> Yes. >> You guys are participating and now sellers are coming together. The merger of the public, the partner network with Marketplace. It feels like this is a second act for AWS to go to the next level. They got their training wheels done with partners. Now they're going to the next level. What do you guys think about this? >> Well, I think you're right, John. I think it is very much something that is in keeping with the way AWS does business. Very Amazonian, they're working back from the customer. What we're seeing is, our customers and in general, the market is gravitating towards purchase mechanisms and route to market that just are lower friction. So in the same way that companies are going through their digital transformations now, really modernizing the way they host applications and they reach the internet. They're also modernizing on the purchasing side, which is super exciting, because we're all motivated to help customers with that agility. >> You know, it's fun to watch and again I'm being really candid and props to you guys as a company. Now, everyone else is kind of following that. Okay, lift and shift, check, doing some things. Now they go, whoa, I can really build on this. People are building their own apps for their companies. Going to build their own stuff. They're going to use piece parts. They're going to put it together in a really scalable way. That's the new normal. Okay, so now they go okay, I'm going to just buy through the market, I get purchasing power. So you guys have been a real leader with AWS. Can you share what you guys are doing in the Marketplace? I think you guys are a nice example of how to execute the Marketplace. Take us through. What are you guys offering there? What's the contract look like? Is it multi-pronged? What's the approach? What do customers get if they go to the marketplace for Zscaler? >> Yeah, so it's been a very exciting story and been a very pleasing one for us with AWS marketplace. We see a huge growth potentially. There are more than 350,000 customers that are actively buying through Marketplace today. We expect that number to grow to around a million customers by the next, I would say, five to ten years and we want to be part of this wave. We see AWS Marketplace to be a channel where not only our resalers or our channel partners can come and transact, but also our GSIs like Accenture want to transact through this channel. We are doing a lot, in terms of bringing new customers through Marketplace, who want to not only close their deals, but close it in the next few hours. That's the beauty of Marketplace, the agility, the flexibility in terms of pricing that it provides to ISVs like us. If a customer wants to delay their payments by a couple of quarters, Marketplace supports that. If a customer wants to do monthly payments, Marketplace supports that. We are seeing lot of customers, big customers, that have signed EDPs, enterprise discount plans with AWS. These are multi-year cloud commits coming to us and saying we can retire our EDPs with AWS if we transact your solution through AWS Marketplace. So what we have done, as of today, we have all of our production services enabled through AWS Marketplace. What that means for customers, they can now retire their EDPs by buying Zscaler products through AWS Marketplace and in return get the full benefit of maximizing their EDP commits with AWS. >> So you guys are fully committed, no toe on the water, as we heard. You guys are all in. >> Absolutely, that's exactly the way to put it. We're all in, all of our solutions are available in the marketplace. As you mentioned, we're a SaaS provider. So we're one of the vendors in the Marketplace that have SaaS solutions. So unlike a lot of customers and even the market in general, associate the Marketplace for historical reasons, the way it started with a lot of monthly subscriptions and just dipping your toe in it from a consumer perspective. Whereas we're doing multimillion dollar, multi-year SaaS contracts. So the most complicated kinds of transactions you'd normally associate with enterprise software, we're doing in very low friction ways. >> On the Zscaler side going in low friction. >> Yep, yeah, that's right. >> How about the customer experience? >> So it is primarily the the customer that experiences. >> Driving it? >> Yeah, they're driving it and it's because rather than traditional methods of going through paperwork, purchase orders- >> What are some of the things that customers are saying about this, bcause I see two benefits, I'll say that. The friction, it's a channel, okay, for Zscaler. Let's be clear, but now you have a customer who's got a lot of Amazon. They're a trusted partner too. So why wouldn't they want to have one point of contact to use their purchasing power and you guys are okay with that. >> We're absolutely okay with it. The reason being, we're still doing the transaction and we can do the transaction with our... We're a channel first company, so that's another important distinction of how people tend to think of the Marketplace. We go through channel. A lot of our transactions are with traditional channel partners and you'd be surprised the kinds of, even the Telcos, carrier providers, are starting to embrace Marketplace. So from a customer perspective, it's less paperwork, less legal work. >> Yeah, I'd love to get your reaction to something, because I think this highlights to me what we've been reporting on with "theCUBE" with super cloud and other trends that are different in a good way. Taking it to the next level and that is that if you look at Zscaler, SaaS, SaaS is self-service, the scale, there's efficiencies. Marketplace first started out as a self-service catalog, a website, you know, click and choose, but now it's a different. He calls it a supply chain, like the CICD pipeline of buying software. He mentions that, there's also services. He put the Channel partners can come in. The GSIs, global system integrators can come in. So it's more than just a catalog now. It's kind of self-service procurement more than it is just a catalog of buy stuff. >> Yes, so yeah, I feel CEOs, CSOs of today should understand what Marketplace brings to the bear in terms of different kinds of services or Zscaler solutions that they can acquire through Marketplace and other ISV solutions, for that matter. I feel like we are at a point, after the pandemic, where there'll be a lot of digital exploration and companies can do more in terms of not just Marketplace, but also including the channel partners as part of deals. So you talked about channel conflict. AWS addressed this by bringing a program called CPPO in the picture, Channel Partner Private Offers. What that does is, we are not only bringing all our channel partners into deals. For renewals as well, they're the partner of record and they get paid alongside with the customer. So AWS does all the heavy lifting, in terms of disbursements of payments to us, to the channel partner, so it's a win-win situation for all. >> I mean, private offers and co-sale has been very popular. >> It has been, and that is our bread and butter in the Marketplace. Again, we do primarily three year contracts and so private offers work super well. A nice thing for us as a vendor is it provides a great amount of flexibility. Private Offer gives you a lot of optionality, in terms of how the constructs of the deal and whether or not you're working with a partner, how the partner is utilizing as well to resell to the end user. So, we've always talked about AWS giving IT agility. This gives purchasing and finance business agility. >> Yeah, and I think this comes up a lot. I just noticed this happening a lot more, where you see dedicated sessions, not just on DevOps and all the goodies of the cloud, financial strategy. >> Yeah. >> Seeing a lot more conversation around how to operationalize the business transactions in the cloud. >> Absolutely. >> This is the new, I mean it's not new, it's been thrown around, but not at a tech conference. You don't see that. So I got to ask you guys, what's the message to the CISOs and executives watching the business people about Zscaler in the Marketplace? What should they be looking at? What is the pitch for Zscaler for the Marketplace buyer? >> So I would say that we are a cloud-delivered network security service. We have been in this game for more than a decade. We have years of early head start with lots of features and functionality versus our competitors. If customers were to move into AWS Cloud, they can get rid of their next-gen firewalls and just have all the traffic routed through our Zscaler internet access and use Zscaler private access for accessing their private applications. We feel we have done everything in our capacity, in terms of enabling customers through Marketplace and will continue to participate in more features and functionality that Marketplace has to offer. We would like these customers to take advantage of their EDPs as well as their retirement and spend for the multi-commit through AWS Marketplace. Learn about what we have to offer and how we can really expedite the motion for them, if they want to procure our solutions through Marketplace >> You know, we're seeing an ability for them to get more creative, more progressive in terms of the purchasing. We're also doing, we're really excited about the ability to serve multiple markets. So we've had an immense amount of success in commercial. We also are seeing increasing amount of public sector, US federal government agencies that want to procure this way as well for the same reasons. So there's a lot of innovation going on. >> So you have the FedRAMP going on, you got all those certifications. >> Exactly right. So we are the first cloud-native solution to provide IL5 ATO, as well as FedRAMP pie and we make that all available, GSA schedule pricing through the AWS Marketplace, again through FSIs and other resellers. >> Public private partnerships have been a big factor, having that span of capability. I got to ask you about, this is a cool conversation, because now you're like, okay, I'm selling through the Marketplace. Companies themselves are changing how they operate. They don't just buy software that we used to use. So general purpose, bundled stuff. Oh yeah, I'm buying this product, because this has got a great solution and I have to get forced to use this firewall, because I bought this over here. That's not how companies are architecting and developing their businesses. It's no longer buying IT. They're building their company digitally. They have to be the application. So they're not sitting around, saying hey, can I get a solution? They're building and architecting their solution. This is kind of like the new enterprise that no one's talking about. They kind of, got to do their own work. >> Yes. >> There's no general purpose solution that maps every company. So they got to pick the best piece parts and integrate them. >> Yes and I feel- >> Do you guys agree with that? >> Yeah, I agree with that and customers don't want to go for point solutions anymore. They want to go with a platform approach. They want go with a vendor that can not only cut down their vendors from multi-dozens to maybe a dozen or less and that's where, you know, we kind of have pivoted to the platform-centric approach, where we not only help customers with Cloud Network Security, but we also help customers with Cloud Native Application Protection Platform that we just recently launched. It's going by the name of the different elements, including Cloud Security Posture Management, Cloud Identity Event Management and so we are continuously doing more and more on the configuration and vulnerability side space. So if a customer has an AWS S3 bucket that is opened it can be detected and can be remediated. So all of those proactive steps we are taking, in terms of enhancing our portfolio, but we have come a long way as a company, as a platform that we have evolved in the Marketplace. >> What's the hottest product? >> The hottest product? >> In Marketplace right now. >> Well, the fastest growing products include our digital experience products and we have new Cloud Protection. So we've got Posture and Workload Protection as well and those are the fastest growing. For AWS customers a strong affinity also for ZPA, which provides you zero trust access to your workloads on AWS. So those are all the most popular in Marketplace. >> Yeah. >> So I would like to add that we recently launched and this has been a few years, a couple of years. We launched a product called Zscaler Digital X, the ZDX. >> Mm-hmm. >> What that product does is, let's say you're making a Zoom call and your WiFi network is laggy or it's a Zoom server that's laggy. It kind of detects where is the problem and it further tells the IT department you need to fix either the server on which Zoom is running, or fix your home network. So that is the beauty of the product. So I think we are seeing massive growth with some of our new editions in the portfolio, which is a long time coming. >> Yeah and certainly a lot of growth opportunities for you guys, as you come in. Where do you see Zscaler's big growth coming from product-wise? What's the big push? Actually, this is great upside for you here. >> Yeah. >> On the go to market side. Where's the big growth for Zscaler right now? So I think we are focused as a company on zero trust architecture. We want to securely connect users to apps, apps to apps, workloads to workloads and machines to machines. We want to give customers an experience where they have direct access to the apps that's hidden from the outside world and they can securely connect to the apps in a very succinct fashion. The user experience is second to none. A lot of customers use us on the Microsoft Office 365 side, where they see a lag in connecting to Microsoft Office 365 directly. They use the IE service to securely connect. >> Yeah, latency kills. >> Microsoft Office 365. >> Latency kills, as we always say, you know and security, you got to look at the pattern, you want to see that data. >> Yeah, and emerging use cases, there is an immense amount of white space and upside for us as well in emerging use cases, like OT, 5G, IOT. >> Yeah. >> Federal government, DOD. >> Oh god, tactical edge government. >> Security at the edge, absolutely, yeah. >> Where's the big edge? What's the edge challenge right now, if you have to put your finger on the edge, because right now that's the hot area, we're watching that. It's going to be highly contested. It's not yet clear, I mean certainly hybrid is the operating model, cloud, distributing, computing, but edge has got unique things that you can't really point to on premises that's the same. It's highly dynamic, you need high bandwidth, low latency, compute at the edge. The data has to be processed right there. What's the big thing at the edge right now? >> Well, so that's probably an emerging answer. I mean, we're working with our customers, they're inventing and they're kind of finding the use cases for those edge, but one of the good things about Zscaler is that we are able to, we've got low latency at the edge. We're able to work as a computer at the edge. We work on Outpost, Snowball, Snowcone, the Snow devices. So we can be wherever our customers need us. Mobile devices, there are a lot of applications where we've got to be either on embedded devices, on tractors, providing security for those IOT devices. So we're pretty comfortable with where we are being the- >> So that's why you guys are financially doing so well, performance wise. I got to ask you though, because I think that brings up the great point. If this is why I like the Marketplace, if I'm a customer, the edge is highly dynamic. It's changing all the time. I don't want to wait to buy something. If I got my solution architects on a product, I need to know I'm going to have zero trust built in and I need to push the button on Zscaler. I don't want to wait. So how does the procurement side impact? What have you guys seen? Share your thoughts on how Marketplace is working from the procurement standpoint, because it seems to me to be fast. Is that right, or is it still slow on their side? On the buyer side, because this to me would be a benefit to developers, if we say, hey, the procurement can just go really fast. I don't want to go through a bunch of PO approvals or slow meetings. >> It can be, that manifests itself in several ways, John. It can be, for instance, somebody wants to do a POC and traditionally you could take any amount of time to get budget approval, take it through. What if you had a pre-approved cloud budget and that was spent primarily through AWS Marketplace, because it's consolidated data on your AWS invoice. The ability to purchase a POC on the Marketplace could be done literally within minutes of the decision being made to go forward with it. So that's kind of a front end, you know, early stage use case. We've got examples we didn't talk about on our recent earnings call of how we have helped customers bring in their procurement with large million dollar, multimillion dollar deals. Even when a resaler's been involved, one of our resaler partners. Being able to accelerate deals, because there's so much less legal work and traditional bureaucratic effort. >> Agility. >> That agility purchasing process has allowed our customers to pull into the quarter, or the end of month, or end of quarter for them, deals that would've otherwise not been able to be done. >> So this is a great example of where you can set policy and kind of create some guard rails around innovation and integration deals, knowing if it's something that the edge is happening, say okay, here's some budget. We approved it, or Amazon gives credits and partnership going on. Then I'd say, hey, well green light this, not to exceed a million dollars, or whatever number in their range and then let people have the freedom to execute. >> You're absolutely right, so from the purchasing side, it does give them that agility. It eliminates a lot of the processes that would push out a purchase in actual execution past when the business decision is made and quite frankly, to be honest, AWS has been very accommodative. They're a great partner. They've invested a lot in Marketplace, Marketplace programs, to help customers do the right thing and do it more quickly as well as vendors like us to help our customers make the decisions they need to. >> Rising tide, a rising tide floats all boats and you guys are a great example of an independent company. Highly successful on your own. >> Yep. >> Certainly the numbers are clear. Wall Street loves Zscaler and economics are great. >> Our customer CSAT numbers are off the scale as well. >> Customers are great and now you've got the Marketplace. This is again, a new normal. A new kind of ecosystem is developing where it's not like the old monolithic ecosystems. The value creation and extraction is happening differently now. It's kind of interesting. >> Yes and I feel we have a long way to go, but what I can tell you is that Zscaler is in this for the long run. We are seeing some of the competitors erupt in the space as well, but they have a long way to go. What we have built requires years worth of R&D and features and thousands of customer's use cases which kind of lead to something what Zscaler has come up with today. What we have is very unique and is going to continuously be an innovation in the market in the years to come. In terms of being more cloud-savvy or more cloud-focused or more cloud-native than what the market has seen so far in the form of next-gen firewalls. >> I know you guys have got a lot of AI work. We've had many conversations with Howie over there. Great stuff and really appreciate you guys participating in our super cloud event we had and we'll see more of that where we're talking about the next generation clouds, really enabling that new disruptive, open-spanning capabilities across multiple environments to run cloud-native modern applications at scale and secure. Appreciate your time to come on "theCUBE". >> Thank you. >> Thank you very much. >> Thanks for having us. >> Thanks, I totally appreciate it. Zscaler, leading company here on "theCUBE" talking about their relationship with Marketplace as they continue to grow and succeed as technology goes to the next level in the cloud. Of course "theCUBE's" covering it here in Seattle. I'm John Furrier, your host. Thanks for watching. (peaceful electronic music)

(upbeat electronic music) >> Welcome back to everyone, to "theCUBE's" coverage here in Seattle, Washington for Amazon Web Services Partner Marketplace Seller Conference, combining their partner network with Marketplace forming a new organization called AWS Partner Organization. This is "theCUBE" coverage. I'm John Furrier, your host. We've got great "Cube" alumni here from Zscaler, a very successful cloud company doing great work. Stelio D'Alo, senior director of cloud business development and Raveesh Chugh, VP of Public Cloud Partnerships at Zscaler. Welcome back to "theCUBE." Good to see you guys. Thanks for coming on. >> Thank you. >> Thanks having us, John. >> So we've been doing a lot of coverage of Zscaler, what a great success story. I mean, the numbers are great. The business performance, it's in the top two, three, one, two, three in all metrics on public companies, SaaS. So you guys, check. Good job. >> Yes, thank you. >> So you guys have done a good job. Now you're here, selling through the Marketplace. You guys are a world class performing company in cloud SaaS, so you're in the front lines doing well. Now, Marketplace is a procurement front end opportunity for people to buy. Hey, self-service, buy and put things together. Sounds novel, what a great concept. Great cloud life. >> Yes. >> You guys are participating and now sellers are coming together. The merger of the public, the partner network with Marketplace. It feels like this is a second act for AWS to go to the next level. They got their training wheels done with partners. Now they're going to the next level. What do you guys think about this? >> Well, I think you're right, John. I think it is very much something that is in keeping with the way AWS does business. Very Amazonian, they're working back from the customer. What we're seeing is, our customers and in general, the market is gravitating towards purchase mechanisms and route to market that just are lower friction. So in the same way that companies are going through their digital transformations now, really modernizing the way they host applications and they reach the internet. They're also modernizing on the purchasing side, which is super exciting, because we're all motivated to help customers with that agility. >> You know, it's fun to watch and again I'm being really candid and props to you guys as a company. Now, everyone else is kind of following that. Okay, lift and shift, check, doing some things. Now they go, whoa, I can really build on this. People are building their own apps for their companies. Going to build their own stuff. They're going to use piece parts. They're going to put it together in a really scalable way. That's the new normal. Okay, so now they go okay, I'm going to just buy through the market, I get purchasing power. So you guys have been a real leader with AWS. Can you share what you guys are doing in the Marketplace? I think you guys are a nice example of how to execute the Marketplace. Take us through. What are you guys offering there? What's the contract look like? Is it multi-pronged? What's the approach? What do customers get if they go to the marketplace for Zscaler? >> Yeah, so it's been a very exciting story and been a very pleasing one for us with AWS marketplace. We see a huge growth potentially. There are more than 350,000 customers that are actively buying through Marketplace today. We expect that number to grow to around a million customers by the next, I would say, five to ten years and we want to be part of this wave. We see AWS Marketplace to be a channel where not only our resalers or our channel partners can come and transact, but also our GSIs like Accenture want to transact through this channel. We are doing a lot, in terms of bringing new customers through Marketplace, who want to not only close their deals, but close it in the next few hours. That's the beauty of Marketplace, the agility, the flexibility in terms of pricing that it provides to ISVs like us. If a customer wants to delay their payments by a couple of quarters, Marketplace supports that. If a customer wants to do monthly payments, Marketplace supports that. We are seeing lot of customers, big customers, that have signed EDPs, enterprise discount plans with AWS. These are multi-year cloud commits coming to us and saying we can retire our EDPs with AWS if we transact your solution through AWS Marketplace. So what we have done, as of today, we have all of our production services enabled through AWS Marketplace. What that means for customers, they can now retire their EDPs by buying Zscaler products through AWS Marketplace and in return get the full benefit of maximizing their EDP commits with AWS. >> So you guys are fully committed, no toe on the water, as we heard. You guys are all in. >> Absolutely, that's exactly the way to put it. We're all in, all of our solutions are available in the marketplace. As you mentioned, we're a SaaS provider. So we're one of the vendors in the Marketplace that have SaaS solutions. So unlike a lot of customers and even the market in general, associate the Marketplace for historical reasons, the way it started with a lot of monthly subscriptions and just dipping your toe in it from a consumer perspective. Whereas we're doing multimillion dollar, multi-year SaaS contracts. So the most complicated kinds of transactions you'd normally associate with enterprise software, we're doing in very low friction ways. >> On the Zscaler side going in low friction. >> Yep, yeah, that's right. >> How about the customer experience? >> So it is primarily the the customer that experiences. >> Driving it? >> Yeah, they're driving it and it's because rather than traditional methods of going through paperwork, purchase orders- >> What are some of the things that customers are saying about this, bcause I see two benefits, I'll say that. The friction, it's a channel, okay, for Zscaler. Let's be clear, but now you have a customer who's got a lot of Amazon. They're a trusted partner too. So why wouldn't they want to have one point of contact to use their purchasing power and you guys are okay with that. >> We're absolutely okay with it. The reason being, we're still doing the transaction and we can do the transaction with our... We're a channel first company, so that's another important distinction of how people tend to think of the Marketplace. We go through channel. A lot of our transactions are with traditional channel partners and you'd be surprised the kinds of, even the Telcos, carrier providers, are starting to embrace Marketplace. So from a customer perspective, it's less paperwork, less legal work. >> Yeah, I'd love to get your reaction to something, because I think this highlights to me what we've been reporting on with "theCUBE" with super cloud and other trends that are different in a good way. Taking it to the next level and that is that if you look at Zscaler, SaaS, SaaS is self-service, the scale, there's efficiencies. Marketplace first started out as a self-service catalog, a website, you know, click and choose, but now it's a different. He calls it a supply chain, like the CICD pipeline of buying software. He mentions that, there's also services. He put the Channel partners can come in. The GSIs, global system integrators can come in. So it's more than just a catalog now. It's kind of self-service procurement more than it is just a catalog of buy stuff. >> Yes, so yeah, I feel CEOs, CSOs of today should understand what Marketplace brings to the bear in terms of different kinds of services or Zscaler solutions that they can acquire through Marketplace and other ISV solutions, for that matter. I feel like we are at a point, after the pandemic, where there'll be a lot of digital exploration and companies can do more in terms of not just Marketplace, but also including the channel partners as part of deals. So you talked about channel conflict. AWS addressed this by bringing a program called CPPO in the picture, Channel Partner Private Offers. What that does is, we are not only bringing all our channel partners into deals. For renewals as well, they're the partner of record and they get paid alongside with the customer. So AWS does all the heavy lifting, in terms of disbursements of payments to us, to the channel partner, so it's a win-win situation for all. >> I mean, private offers and co-sale has been very popular. >> It has been, and that is our bread and butter in the Marketplace. Again, we do primarily three year contracts and so private offers work super well. A nice thing for us as a vendor is it provides a great amount of flexibility. Private Offer gives you a lot of optionality, in terms of how the constructs of the deal and whether or not you're working with a partner, how the partner is utilizing as well to resell to the end user. So, we've always talked about AWS giving IT agility. This gives purchasing and finance business agility. >> Yeah, and I think this comes up a lot. I just noticed this happening a lot more, where you see dedicated sessions, not just on DevOps and all the goodies of the cloud, financial strategy. >> Yeah. >> Seeing a lot more conversation around how to operationalize the business transactions in the cloud. >> Absolutely. >> This is the new, I mean it's not new, it's been thrown around, but not at a tech conference. You don't see that. So I got to ask you guys, what's the message to the CISOs and executives watching the business people about Zscaler in the Marketplace? What should they be looking at? What is the pitch for Zscaler for the Marketplace buyer? >> So I would say that we are a cloud-delivered network security service. We have been in this game for more than a decade. We have years of early head start with lots of features and functionality versus our competitors. If customers were to move into AWS Cloud, they can get rid of their next-gen firewalls and just have all the traffic routed through our Zscaler internet access and use Zscaler private access for accessing their private applications. We feel we have done everything in our capacity, in terms of enabling customers through Marketplace and will continue to participate in more features and functionality that Marketplace has to offer. We would like these customers to take advantage of their EDPs as well as their retirement and spend for the multi-commit through AWS Marketplace. Learn about what we have to offer and how we can really expedite the motion for them, if they want to procure our solutions through Marketplace >> You know, we're seeing an ability for them to get more creative, more progressive in terms of the purchasing. We're also doing, we're really excited about the ability to serve multiple markets. So we've had an immense amount of success in commercial. We also are seeing increasing amount of public sector, US federal government agencies that want to procure this way as well for the same reasons. So there's a lot of innovation going on. >> So you have the FedRAMP going on, you got all those certifications. >> Exactly right. So we are the first cloud-native solution to provide IL5 ATO, as well as FedRAMP pie and we make that all available, GSA schedule pricing through the AWS Marketplace, again through FSIs and other resellers. >> Public private partnerships have been a big factor, having that span of capability. I got to ask you about, this is a cool conversation, because now you're like, okay, I'm selling through the Marketplace. Companies themselves are changing how they operate. They don't just buy software that we used to use. So general purpose, bundled stuff. Oh yeah, I'm buying this product, because this has got a great solution and I have to get forced to use this firewall, because I bought this over here. That's not how companies are architecting and developing their businesses. It's no longer buying IT. They're building their company digitally. They have to be the application. So they're not sitting around, saying hey, can I get a solution? They're building and architecting their solution. This is kind of like the new enterprise that no one's talking about. They kind of, got to do their own work. >> Yes. >> There's no general purpose solution that maps every company. So they got to pick the best piece parts and integrate them. >> Yes and I feel- >> Do you guys agree with that? >> Yeah, I agree with that and customers don't want to go for point solutions anymore. They want to go with a platform approach. They want go with a vendor that can not only cut down their vendors from multi-dozens to maybe a dozen or less and that's where, you know, we kind of have pivoted to the platform-centric approach, where we not only help customers with Cloud Network Security, but we also help customers with Cloud Native Application Protection Platform that we just recently launched. It's going by the name of the different elements, including Cloud Security Posture Management, Cloud Identity Event Management and so we are continuously doing more and more on the configuration and vulnerability side space. So if a customer has an AWS S3 bucket that is opened it can be detected and can be remediated. So all of those proactive steps we are taking, in terms of enhancing our portfolio, but we have come a long way as a company, as a platform that we have evolved in the Marketplace. >> What's the hottest product? >> The hottest product? >> In Marketplace right now. >> Well, the fastest growing products include our digital experience products and we have new Cloud Protection. So we've got Posture and Workload Protection as well and those are the fastest growing. For AWS customers a strong affinity also for ZPA, which provides you zero trust access to your workloads on AWS. So those are all the most popular in Marketplace. >> Yeah. >> So I would like to add that we recently launched and this has been a few years, a couple of years. We launched a product called Zscaler Digital X, the ZDX. >> Mm-hmm. >> What that product does is, let's say you're making a Zoom call and your WiFi network is laggy or it's a Zoom server that's laggy. It kind of detects where is the problem and it further tells the IT department you need to fix either the server on which Zoom is running, or fix your home network. So that is the beauty of the product. So I think we are seeing massive growth with some of our new editions in the portfolio, which is a long time coming. >> Yeah and certainly a lot of growth opportunities for you guys, as you come in. Where do you see Zscaler's big growth coming from product-wise? What's the big push? Actually, this is great upside for you here. >> Yeah. >> On the go to market side. Where's the big growth for Zscaler right now? So I think we are focused as a company on zero trust architecture. We want to securely connect users to apps, apps to apps, workloads to workloads and machines to machines. We want to give customers an experience where they have direct access to the apps that's hidden from the outside world and they can securely connect to the apps in a very succinct fashion. The user experience is second to none. A lot of customers use us on the Microsoft Office 365 side, where they see a lag in connecting to Microsoft Office 365 directly. They use the IE service to securely connect. >> Yeah, latency kills. >> Microsoft Office 365. >> Latency kills, as we always say, you know and security, you got to look at the pattern, you want to see that data. >> Yeah, and emerging use cases, there is an immense amount of white space and upside for us as well in emerging use cases, like OT, 5G, IOT. >> Yeah. >> Federal government, DOD. >> Oh god, tactical edge government. >> Security at the edge, absolutely, yeah. >> Where's the big edge? What's the edge challenge right now, if you have to put your finger on the edge, because right now that's the hot area, we're watching that. It's going to be highly contested. It's not yet clear, I mean certainly hybrid is the operating model, cloud, distributing, computing, but edge has got unique things that you can't really point to on premises that's the same. It's highly dynamic, you need high bandwidth, low latency, compute at the edge. The data has to be processed right there. What's the big thing at the edge right now? >> Well, so that's probably an emerging answer. I mean, we're working with our customers, they're inventing and they're kind of finding the use cases for those edge, but one of the good things about Zscaler is that we are able to, we've got low latency at the edge. We're able to work as a computer at the edge. We work on Outpost, Snowball, Snowcone, the Snow devices. So we can be wherever our customers need us. Mobile devices, there are a lot of applications where we've got to be either on embedded devices, on tractors, providing security for those IOT devices. So we're pretty comfortable with where we are being the- >> So that's why you guys are financially doing so well, performance wise. I got to ask you though, because I think that brings up the great point. If this is why I like the Marketplace, if I'm a customer, the edge is highly dynamic. It's changing all the time. I don't want to wait to buy something. If I got my solution architects on a product, I need to know I'm going to have zero trust built in and I need to push the button on Zscaler. I don't want to wait. So how does the procurement side impact? What have you guys seen? Share your thoughts on how Marketplace is working from the procurement standpoint, because it seems to me to be fast. Is that right, or is it still slow on their side? On the buyer side, because this to me would be a benefit to developers, if we say, hey, the procurement can just go really fast. I don't want to go through a bunch of PO approvals or slow meetings. >> It can be, that manifests itself in several ways, John. It can be, for instance, somebody wants to do a POC and traditionally you could take any amount of time to get budget approval, take it through. What if you had a pre-approved cloud budget and that was spent primarily through AWS Marketplace, because it's consolidated data on your AWS invoice. The ability to purchase a POC on the Marketplace could be done literally within minutes of the decision being made to go forward with it. So that's kind of a front end, you know, early stage use case. We've got examples we didn't talk about on our recent earnings call of how we have helped customers bring in their procurement with large million dollar, multimillion dollar deals. Even when a resaler's been involved, one of our resaler partners. Being able to accelerate deals, because there's so much less legal work and traditional bureaucratic effort. >> Agility. >> That agility purchasing process has allowed our customers to pull into the quarter, or the end of month, or end of quarter for them, deals that would've otherwise not been able to be done. >> So this is a great example of where you can set policy and kind of create some guard rails around innovation and integration deals, knowing if it's something that the edge is happening, say okay, here's some budget. We approved it, or Amazon gives credits and partnership going on. Then I'd say, hey, well green light this, not to exceed a million dollars, or whatever number in their range and then let people have the freedom to execute. >> You're absolutely right, so from the purchasing side, it does give them that agility. It eliminates a lot of the processes that would push out a purchase in actual execution past when the business decision is made and quite frankly, to be honest, AWS has been very accommodative. They're a great partner. They've invested a lot in Marketplace, Marketplace programs, to help customers do the right thing and do it more quickly as well as vendors like us to help our customers make the decisions they need to. >> Rising tide, a rising tide floats all boats and you guys are a great example of an independent company. Highly successful on your own. >> Yep. >> Certainly the numbers are clear. Wall Street loves Zscaler and economics are great. >> Our customer CSAT numbers are off the scale as well. >> Customers are great and now you've got the Marketplace. This is again, a new normal. A new kind of ecosystem is developing where it's not like the old monolithic ecosystems. The value creation and extraction is happening differently now. It's kind of interesting. >> Yes and I feel we have a long way to go, but what I can tell you is that Zscaler is in this for the long run. We are seeing some of the competitors erupt in the space as well, but they have a long way to go. What we have built requires years worth of R&D and features and thousands of customer's use cases which kind of lead to something what Zscaler has come up with today. What we have is very unique and is going to continuously be an innovation in the market in the years to come. In terms of being more cloud-savvy or more cloud-focused or more cloud-native than what the market has seen so far in the form of next-gen firewalls. >> I know you guys have got a lot of AI work. We've had many conversations with Howie over there. Great stuff and really appreciate you guys participating in our super cloud event we had and we'll see more of that where we're talking about the next generation clouds, really enabling that new disruptive, open-spanning capabilities across multiple environments to run cloud-native modern applications at scale and secure. Appreciate your time to come on "theCUBE". >> Thank you. >> Thank you very much. >> Thanks for having us. >> Thanks, I totally appreciate it. Zscaler, leading company here on "theCUBE" talking about their relationship with Marketplace as they continue to grow and succeed as technology goes to the next level in the cloud. Of course "theCUBE's" covering it here in Seattle. I'm John Furrier, your host. Thanks for watching. (peaceful electronic music)

(light music) >> Welcome back to Supercloud 22. I'm John Furrier, host of theCUBE. We're here Palo Alto for a big event. Supercloud 22, we've got a great ecosystem conversation here. Ramesh Prabagaran, who's the co-founder and CEO, Prosimo. Ramesh, great to see you. Thanks for coming on. >> Thanks for having me, John. >> So, I wanted to bring you in because we've had previous CUBE conversations around cloud networking, latency, you also have some, some pedigree, Viptela. The folks in the industry know that's been a deep tech company. >> Yep. >> You have been around the block. You've seen the movie before. You've seen the tech trends. You've seen the hype. You've seen the fluff. Where's the meat on the bone with Supercloud in your opinion? >> So it, it starts with what enterprises are struggling with, right? And if you take a very simple example, it's actually quite fresh in my mind because I was just having this conversation this morning. A large bank has an application sitting in AWS, right? And they have to provide the application access to the treasury, to their suppliers, to ticker feeds, to all their downstream partners, and so on and so forth. Guess what? They don't control, where all those things are. They're in very different regions and very different clouds. And so you, whether you like it or not, you have a problem here, right? And so it starts with, for the particular bank, what are the capabilities that they need, right? And so AWS provides a whole host of native capabilities, but they still need to build a few more things on top. So going by, essentially the definition of Supercloud, even within a single cloud you need to build a few more capabilities on top. That gets worsened by the fact that now you need to provide access to various other clouds, various other regions and, and so forth. So, whether we like it or not, this movie is here to stay. >> What's the difference between Supercloud and multi-cloud? Because multi-cloud, I've been saying, is not necessarily a market yet. >> Correct, yes. So, Supercloud is essentially the cloud native capabilities provided by the hyperscalers, get you probably 30, 40% of the way, right? But then, in order to deliver on a care about, right? In our case, from a cloud networking standpoint, that is experience, that's performance, reliability, zero trust access, and then so forth. You have to take that a little bit further, and so we have vendors, like us, that actually build capabilities on top of the hyperscalers, right? Now, even if you think of a single cloud, how you build that is different on AWS than it's on Azure, than on GCP. But do the customers care? No, they want to be able to consume it in exactly the same way across all of them. So, whether it's multi-cloud or a single cloud, you have a problem that is white space on top of the hyperscalers capabilities that you just need to build. >> And what problems is it solving today? Because again, I, again, multi-cloud, I've yet seen the problem. I kind of get what's happening. Multiple clouds do exist. Use cases matter, maybe best debri, but they're standalone. They're not really interoperating, so to speak. So people have been successful on, on public cloud. >> That's correct, yes. >> For use cases? >> Absolutely. So even if you take a single cloud, for example, right? You have multiple problems to, to address. So let's take the example of, I have users coming from various different regions, around the globe, and I have apps that are spread, maybe not across like all clouds, but single cloud, maybe multiple regions, right? Now, I have a reach problem, which is, I need to go from where the user is to where the application is sitting. I have an experience problem because if my spinning wheel shows up, I'm going to go crazy. I have a security problem because I want to make sure it's only me that have access to it, right? But does the cloud provider solve for this entirely? No, they give you the nuts, the bolts, or what we call ours essentially, what you need is a, is a latte. They give you really nice coffee beans, not just one flavor, 20 flavors of those. They give you raw sugar and a few other things. They give you five different flavors of milk, but you got to make your own latte. So, that's what we do. >> And this is where the infrastructure transformation's happening. >> Exactly. >> And the super paz layer, as Dave Vellante and I have talked about in cloud, is you have to integrate a native cloud. >> Correct. >> Which is beautiful. It's integrated, everything works together, there's a lot of lattes to be made or espressos. >> Exactly. >> I mean, tons of great things there. So, big check marks, double check, gold star for AWS. >> Correct. >> All good. Now, on premises, we've found that hybrid is a steady state. >> Exactly. >> Okay, that's cloud operations. Now, you got the edge. Where does the Supercloud strategy come in? For the folks watching there, it's like, "Hey, okay, I get that." "But I don't want to just buy into another vendor's hype." >> Absolutely. >> "I got to build my own cloud," to your point about the lattes. >> Correct. >> They have to make their own infrastructure an application environment to power the developer. >> Exactly. And, and hybrid is here to stay as, as you pointed out, right, John? So, I have my data center and let's say when most folks start out they start to like a single region of a single cloud, right? And what are you most concerned about there? Hey, can I migrate? Can I start to build applications in the public cloud, right? And all you care about is can you talk back into my data center? Like, as long as some basic hygiene is there that's all they care about, right? The problem happens when you go from, kind of, the first five EC2 instances to 50 to a hundred, then you have a few other things that you need to care about, right? That's really kind of where the, the Supercloud capabilities start to come in, right? Because you have the cloud native things you can make that work for the first few days, but then after that you need augmented capabilities. >> So Ramesh, some people will say, "Hey, John, Supercloud okay, it's funny, ha ha ha." But isn't it just SAS? >> No, SAS is a delivery mechanism, right? And so, so there is the capability and that is how do you want to consume, right? And so capabilities or cloud native capabilities or piece of software capabilities or (unintelligible) cluster form factor and so forth. How do you want to consume? Maybe it's a package form factor, it is a size, it could even be passive if it's sitting in the, in the element, and then so forth, right? And so you really want to distinguish those two. And, and, and that's how we see the, the industry evolve. >> Can Superclouds be specialty clouds? Like is Snowflake a Supercloud? Is Goldman Sachs financial cloud a Supercloud? >> Absolutely, right. So Supercloud is not like a, a conglomeration of multiple capabilities, right? It can be for a specific use case, it can be for a specific functionality. So we, we consider our capabilities by the definition as a Supercloud in, in networking, right? In cloud networking, in Prosimo. So, does that solve the entirety of what I want to do in the cloud? No, absolutely not. There's data, there's computers, a whole bunch of other things, but for a specialty you do have some Supercloud. >> Yeah, in fact, I had a note here. I was going to ask you will, when will there be specialty clouds, apps, identity, data, security, nteworking, we will see those? >> Absolutely, yeah. And, and those are slowly starting to brew, right? So you have, you have identity as one, you have networking as one, you have the zero trust piece as, as another one, you have data as a, as another one. So when all these things come together, absolutely. That's what, that's what enterprise customers care about. >> So I love infrastructure as code, that drove a lot of the evolution and revolution of DevOps. When are we going to see security as code and network as code? Or is it there? >> No networkers code, for sure. It's already, it's already there. It's probably in its early innings, I would say, but we are starting to see that already. The reason for that is really simple. Enough CIOs have yelled at their networking teams to say, "my app guys can get this done three," "four times a day, you get this done once a week." Right? And so, that has actually driven quite a bit of innovation, >> It's slow, >> It's slow, right? And so that's driven quite a bit of innovation. It all starts with, hey, can I build a Terraform provider and then just integrate into Terraform? But it doesn't, it doesn't stop there, right? There's a whole bunch of additional capabilities, a day in troubleshooting, a whole bunch of things that need to come together. But I would say networkers code has already started to, to, to take ship. >> Which, that's a great point about specialty clouds. What about vertical clouds too? 'Cause you got insurance, oil and gas, FinTech. Both sides of the stack can have specialty clouds. >> Absolutely, yeah. So, it, what's driving specialty clouds, right? Some of it is compliance, mainly because you just have to shard the data, and when you shard the data, the entirety gets, gets sharded, right? Some of it driven by use case, because some are a little more serverless, service mesh and intelligence focused, some are a little more infrastructure focused. So you do see that taking off. I would say we've seen a whole lot more, kind of, on the horizontal side, less on the vertical side, but that's really happening, right? >> Yeah, I think that, to me, indicates a Supercloud. The fact that the diversity of the application on the clouds themselves, someone could be spending, say, Liberty Mutual or Goldman Sachs. They were once spending that as CapEx. >> Exactly. >> Now it's OPEX, so they become a service provider. So, if you have scale with data and expertise, you become a Supercloud by default. And you don't have to pay for the CapEx, >> Yeah. You're already paying in. >> Exactly, yeah. >> And that's what snowflake basically did with data warehouse. >> That's right, yeah. >> I mean they're basically a data warehouse. Refactored on the cloud and then go, "whoa, let's go to Azure." >> Yeah. And, and where does that data decide do you ask that question? No, right? You just assume that, hey, retrospective of it's a single cloud, multiple regions, it's there. If it's stretched to multiple clouds, yes, it's just there, but you, you talk about like that. >> In our cloud already panel earlier, we talked about how companies are going fast on one native cloud, 'cause they don't want to have multiple development teams and different ops teams. They go all in say, hey, mostly AWS wins this, unless it's specially Azure productivity software or SQL database, go hard in on Amazon, get speed and velocity, get that flywheel, win, get scale, get value. Then go to Azure, provide that same value to that marketplace and other clouds. Then the next dot to connect is, can the customer have the same experience across the clouds? That's where it gets interesting. What's your thoughts on that? >> Actually, it gets interesting even when they go from a single cloud in a single region to multiple regions, right? And the, the more spread out the regions are, you have requirements around application performance, application experience and so forth. So, suddenly the networking conversation starts to become an experience and a performance conversation. The security conversation starts to become a zero trust conversation and so forth. And so you, you do see that, that interesting shift that's happening. >> Of course. >> Exactly. And then that gets worsened by the fact that now you have multiple clouds, multiple regions, and then... >> So you got regions, clouds, >> and then you have edge locations now. >> And edge. >> You mentioned edge. >> This, this is why I think multi-cloud is BS, because this is all coming so fast. You got to get your Supercloud first. >> Exactly. >> Then you extend into, what it looks like a multi-vendor or multifaceted environment that should be automated by that time. >> Exactly. >> So it's evolutionary, we're not there yet. >> Exactly. >> So you agree, no market yet? >> That's right, yes. So unless it's like the super large enterprises where we have seen a really good mix of multiple different clouds or super large enterprises where each business unit is free to choose the cloud of their choice for the application developers because they just like a certain cloud, right? >> Or negotiations. >> Or negotiations, right? Exactly, so there you find yourself in a healthy mix. It's not like you're 80, 10, 10. It's, it's a healthy mix of three different clouds, right? But vast majority of the enterprises, they have a concerted strategy, I have a primary cloud 'cause that's where two, two big CEOs shake hands and assign multi billion dollar deals, right? >> It's just a song with Howie Shute, who's now a Zscaler, former VMware. Probably know Howie, he's a legend in the community as well. We were talking about the old days of the data center and you remember that? We'll go back to our, into our, you know, historical views of experience. Back when the data center became popular this was the glass house. Mainframes to mini computers. It became a complex environment. You had to have pretty much a PhD or serious networking or some sort of technical background. And then IT was born, the local area networks, the mini computers, and the PCs change that dynamic. IT was born. Okay, and let's just say it, most IT guys aren't PhDs. >> Exactly. >> So what's happened there is democratization and the operations side of that wave. We're kind of going th&rough it now, don't ya think, with cloud? Like, you got to be super smart to wrangle the data. I mean, some of the data pipelining stuff is super complex, after Snowflake and data bricks. >> Absolutely. And largely depends on the maturity, right? Like, so once you pass a certain scale in the cloud the care abouts start to be very different. The care abouts are, how can I operate this at scale? Because I might have started off with a relatively inefficient infrastructure, right? But now if I start to operate that at scale with like thousands of VPCs and so forth, somebody is looking at an AWS bill there and going, "ah, no, no, no, we're not going to do that." >> We're getting to the good part now. So, so here's where I wanted to get to, 'Cause we're kind of getting there, The proof points of Supercloud is IT like operations, >> Correct. >> Easy. >> Yep. >> Not overstaffed and maybe an SRE model one too many. >> Yeah, exactly. >> What are the proof points do you see that would be evidence that Supercloud is working? >> So in a well functional model where we have seen enterprises take the applications that they care about and then move that into the public cloud or build it organically. If they have staffed their team, I think a good leading indicator is that they have staffed the team so that there are a bunch of guys who understand what it means for cloud native capabilities. There are a bunch of guys who then put it together and then you look at the care abouts, right? Ultimately at the end of the day, the goal, if you go higher up in the layers, is it about application experience? Is it about kind of reducing the blast radius of my security? Is it about my data cleanliness and, and hygiene? You don't care about kind of how the pipelining works underneath the covers or how do I put a transit gateway and this and that together? No, that's not what you care about. You care about kind of the outcomes and, and- >> Palmer (unintelligible) that VMware, when he was there. You just say the hardened top, no one talks about what's in an Intel processor. I mean it's just works. >> Exactly, yeah. And it's what applications you build on top of that Intel processor that actually makes it more powerful, right? And so the first evidence I would say is kind of how is the team structured? The second evidence would be kind of what, what are the care abouts for the guys that are building these applications, right? Because even the application developers more than the application, they care about kind of, is it helping? Is it delivering on the experience? Is it being used the way it's supposed to? >> Is it value? >> Exactly, right? And those are not areas that the cloud providers are solely focused on, right? Like you don't see an AWS or an Azure dashboard show that particular thing for the entirety of the application, they'll tell you for the ATR services that you, that you use, here's the SLA for each one of these services. >> And that's where the customer has to build it. >> Exactly right. Now, does that give you the full picture? No, it doesn't. Somebody has to pull this together. Somebody has to aggregate this together and then make sense as to whether this is working or not, right? So whether you call it Supercloud, or whether you call it kind of the care abouts on top of the cloud native stuff, they're all the same. I'm glad you guys came up with a, with a name for this. And I think it's going to be here to stay. >> Well, thank you for sharing your expertise. You got a great background in this area and you got, I think you guys are right on the front wave of this new change. I think a little bit early, but that's good, but don't be too early. >> Yeah, exactly. No, and, and, and that's really important, right, John? So, you don't want to be too early. You certainly don't want to be too late, but at the same time, the pace at which things are evolving are fast enough that you, you will see. I think when, if we have this conversation even three months from now, it might be a very different conversation. >> Yeah, people want to go fast and they don't want to get stuck with a vendor. They made a bad choice that slows 'em down 'cause they got problems to solve, things to build. >> Yeah, exactly. >> Ramesh, thanks for coming on, Supercloud 22, we're breaking it all down. We're exposing it out to everyone. We're discussing it. We're going to challenge it. But ultimately it is a thing. Supercloud 22. Thanks for watching. >> Wonderful, thanks John. (light music)

(gentle upbeat music) >> Welcome back everyone, to "theCUBE"'s live stage performance here in Palo Alto, California at "theCUBE" Studios. I'm John Furrier with Dave Vellante, kicking off our first inaugural Supercloud event. It's an editorial event, we wanted to bring together the best in the business, the smartest, the biggest, the up-and-coming startups, venture capitalists, everybody, to weigh in on this new Supercloud trend, this structural change in the cloud computing business. We're about to run the Ecosystem Speaks, which is a bunch of pre-recorded companies that wanted to get their voices on the record, so stay tuned for the rest of the day. We'll be replaying all that content and they're going to be having some really good commentary and hear what they have to say. I had a chance to interview and so did Dave. Dave, this is our closing segment where we kind of unpack everything or kind of digest and report. So much to kind of digest from the conversations today, a wide range of commentary from Supercloud operating system to developers who are in charge to maybe it's an ops problem or maybe Oracle's a Supercloud. I mean, that was debated. So so much discussion, lot to unpack. What was your favorite moments? >> Well, before I get to that, I think, I go back to something that happened at re:Invent last year. Nick Sturiale came up, Steve Mullaney from Aviatrix; we're going to hear from him shortly in the Ecosystem Speaks. Nick Sturiale's VC said "it's happening"! And what he was talking about is this ecosystem is exploding. They're building infrastructure or capabilities on top of the CapEx infrastructure. So, I think it is happening. I think we confirmed today that Supercloud is a thing. It's a very immature thing. And I think the other thing, John is that, it seems to me that the further you go up the stack, the weaker the business case gets for doing Supercloud. We heard from Marianna Tessel, it's like, "Eh, you know, we can- it was easier to just do it all on one cloud." This is a point that, Adrian Cockcroft just made on the panel and so I think that when you break out the pieces of the stack, I think very clearly the infrastructure layer, what we heard from Confluent and HashiCorp, and certainly VMware, there's a real problem there. There's a real need at the infrastructure layer and then even at the data layer, I think Benoit Dageville did a great job of- You know, I was peppering him with all my questions, which I basically was going through, the Supercloud definition and they ticked the box on pretty much every one of 'em as did, by the way Ali Ghodsi you know, the big difference there is the philosophy of Republicans and Democrats- got open versus closed, not to apply that to either one side, but you know what I mean! >> And the similarities are probably greater than differences. >> Berkely, I would probably put them on the- >> Yeah, we'll put them on the Democrat side we'll make Snowflake the Republicans. But so- but as we say there's a lot of similarities as well in terms of what their objectives are. So, I mean, I thought it was a great program and a really good start to, you know, an industry- You brought up the point about the industry consortium, asked Kit Colbert- >> Yep. >> If he thought that was something that was viable and what'd they say? That hyperscale should lead it? >> Yeah, they said hyperscale should lead it and there also should be an industry consortium to get the voices out there. And I think VMware is very humble in how they're putting out their white paper because I think they know that they can't do it all and that they do not have a great track record relative to cloud. And I think, but they have a great track record of loyal installed base ops people using VMware vSphere all the time. >> Yeah. >> So I think they need a catapult moment where they can catapult to the cloud native which they've been working on for years under Raghu and the team. So the question on VMware is in the light of Broadcom, okay, acquisition of VMware, this is an opportunity or it might not be an opportunity or it might be a spin-out or something, I just think VMware's got way too much engineering culture to be ignored, Dave. And I think- well, I'm going to watch this very closely because they can pull off some sort of rallying moment. I think they could. And then you hear the upstarts like Platform9, Rafay Systems and others they're all like, "Yes, we need to unify behind something. There needs to be some sort of standard". You know, we heard the argument of you know, more standards bodies type thing. So, it's interesting, maybe "theCUBE" could be that but we're going to certainly keep the conversation going. >> I thought one of the most memorable statements was Vittorio who said we- for VMware, we want our cake, we want to eat it too and we want to lose weight. So they have a lot of that aspirations there! (John laughs) >> And then I thought, Adrian Cockcroft said you know, the devs, they want to get married. They were marrying everybody, and then the ops team, they have to deal with the divorce. >> Yeah. >> And I thought that was poignant. It's like, they want consistency, they want standards, they got to be able to scale And Lori MacVittie, I'm not sure you agree with this, I'd have to think about it, but she was basically saying, all we've talked about is devs devs devs for the last 10 years, going forward we're going to be talking about ops. >> Yeah, and I think one of the things I learned from this day and looking back, and some kind of- I've been sauteing through all the interviews. If you zoom out, for me it was the epiphany of developers are still in charge. And I've said, you know, the developers are doing great, it's an ops security thing. Not sure I see that the way I was seeing before. I think what I learned was the refactoring pattern that's emerging, In Sik Rhee brought this up from Vertex Ventures with Marianna Tessel, it's a nuanced point but I think he's right on which is the pattern that's emerging is developers want ease-of-use tooling, they're driving the change and I think the developers in the devs ops ethos- it's never going to be separate. It's going to be DevOps. That means developers are driving operations and then security. So what I learned was it's not ops teams leveling up, it's devs redefining what ops is. >> Mm. And I think that to me is where Supercloud's going to be interesting- >> Forcing that. >> Yeah. >> Forcing the change because the structural change is open sources thriving, devs are still in charge and they still want more developers, Vittorio "we need more developers", right? So the developers are in charge and that's clear. Now, if that happens- if you believe that to be true the domino effect of that is going to be amazing because then everyone who gets on the wrong side of history, on the ops and security side, is going to be fighting a trend that may not be fight-able, you know, it might be inevitable. And so the winners are the ones that are refactoring their business like Snowflake. Snowflake is a data warehouse that had nothing to do with Amazon at first. It was the developers who said "I'm going to refactor data warehouse on AWS". That is a developer-driven refactorization and a business model. So I think that's the pattern I'm seeing is that this concept refactoring, patterns and the developer trajectory is critical. >> I thought there was another great comment. Maribel Lopez, her Lord of the Rings comment: "there will be no one ring to rule them all". Now at the same time, Kit Colbert, you know what we asked him straight out, "are you the- do you want to be the, the Supercloud OS?" and he basically said, "yeah, we do". Now, of course they're confined to their world, which is a pretty substantial world. I think, John, the reason why Maribel is so correct is security. I think security's a really hard problem to solve. You've got cloud as the first layer of defense and now you've got multiple clouds, multiple layers of defense, multiple shared responsibility models. You've got different tools for XDR, for identity, for governance, for privacy all within those different clouds. I mean, that really is a confusing picture. And I think the hardest- one of the hardest parts of Supercloud to solve. >> Yeah, and I thought the security founder Gee Rittenhouse, Piyush Sharrma from Accurics, which sold to Tenable, and Tony Kueh, former head of product at VMware. >> Right. >> Who's now an investor kind of looking for his next gig or what he is going to do next. He's obviously been extremely successful. They brought up the, the OS factor. Another point that they made I thought was interesting is that a lot of the things to do to solve the complexity is not doable. >> Yeah. >> It's too much work. So managed services might field the bit. So, and Chris Hoff mentioned on the Clouderati segment that the higher level services being a managed service and differentiating around the service could be the key competitive advantage for whoever does it. >> I think the other thing is Chris Hoff said "yeah, well, Web 3, metaverse, you know, DAO, Superclouds" you know, "Stupercloud" he called it and this bring up- It resonates because one of the criticisms that Charles Fitzgerald laid on us was, well, it doesn't help to throw out another term. I actually think it does help. And I think the reason it does help is because it's getting people to think. When you ask people about Supercloud, they automatically- it resonates with them. They play back what they think is the future of cloud. So Supercloud really talks to the future of cloud. There's a lot of aspects to it that need to be further defined, further thought out and we're getting to the point now where we- we can start- begin to say, okay that is Supercloud or that isn't Supercloud. >> I think that's really right on. I think Supercloud at the end of the day, for me from the simplest way to describe it is making sure that the developer experience is so good that the operations just happen. And Marianna Tessel said, she's investing in making their developer experience high velocity, very easy. So if you do that, you have to run on premise and on the cloud. So hybrid really is where Supercloud is going right now. It's not multi-cloud. Multi-cloud was- that was debunked on this session today. I thought that was clear. >> Yeah. Yeah, I mean I think- >> It's not about multi-cloud. It's about operationally seamless operations across environments, public cloud to on-premise, basically. >> I think we got consensus across the board that multi-cloud, you know, is a symptom Chuck Whitten's thing of multi-cloud by default versus multi- multi-cloud has not been a strategy, Kit Colbert said, up until the last couple of years. Yeah, because people said, "oh we got all these multiple clouds, what do we do with it?" and we got this mess that we have to solve. Whereas, I think Supercloud is something that is a strategy and then the other nuance that I keep bringing up is it's industries that are- as part of their digital transformation, are building clouds. Now, whether or not they become superclouds, I'm not convinced. I mean, what Goldman Sachs is doing, you know, with AWS, what Walmart's doing with Azure connecting their on-prem tools to those public clouds, you know, is that a supercloud? I mean, we're going to have to go back and really look at that definition. Or is it just kind of a SAS that spans on-prem and cloud. So, as I said, the further you go up the stack, the business case seems to wane a little bit but there's no question in my mind that from an infrastructure standpoint, to your point about operations, there's a real requirement for super- what we call Supercloud. >> Well, we're going to keep the conversation going, Dave. I want to put a shout out to our founding supporters of this initiative. Again, we put this together really fast kind of like a pilot series, an inaugural event. We want to have a face-to-face event as an industry event. Want to thank the founding supporters. These are the people who donated their time, their resource to contribute content, ideas and some cash, not everyone has committed some financial contribution but we want to recognize the names here. VMware, Intuit, Red Hat, Snowflake, Aisera, Alteryx, Confluent, Couchbase, Nutanix, Rafay Systems, Skyhigh Security, Aviatrix, Zscaler, Platform9, HashiCorp, F5 and all the media partners. Without their support, this wouldn't have happened. And there are more people that wanted to weigh in. There was more demand than we could pull off. We'll certainly continue the Supercloud conversation series here on "theCUBE" and we'll add more people in. And now, after this session, the Ecosystem Speaks session, we're going to run all the videos of the big name companies. We have the Nutanix CEOs weighing in, Aviatrix to name a few. >> Yeah. Let me, let me chime in, I mean you got Couchbase talking about Edge, Platform 9's going to be on, you know, everybody, you know Insig was poopoo-ing Oracle, but you know, Oracle and Azure, what they did, two technical guys, developers are coming on, we dig into what they did. Howie Xu from Zscaler, Paula Hansen is going to talk about going to market in the multi-cloud world. You mentioned Rajiv, the CEO of Nutanix, Ramesh is going to talk about multi-cloud infrastructure. So that's going to run now for, you know, quite some time here and some of the pre-record so super excited about that and I just want to thank the crew. I hope guys, I hope you have a list of credits there's too many of you to mention, but you know, awesome jobs really appreciate the work that you did in a very short amount of time. >> Well, I'm excited. I learned a lot and my takeaway was that Supercloud's a thing, there's a kind of sense that people want to talk about it and have real conversations, not BS or FUD. They want to have real substantive conversations and we're going to enable that on "theCUBE". Dave, final thoughts for you. >> Well, I mean, as I say, we put this together very quickly. It was really a phenomenal, you know, enlightening experience. I think it confirmed a lot of the concepts and the premises that we've put forth, that David Floyer helped evolve, that a lot of these analysts have helped evolve, that even Charles Fitzgerald with his antagonism helped to really sharpen our knives. So, you know, thank you Charles. And- >> I like his blog, by the I'm a reader- >> Yeah, absolutely. And it was great to be back in Palo Alto. It was my first time back since pre-COVID, so, you know, great job. >> All right. I want to thank all the crew and everyone. Thanks for watching this first, inaugural Supercloud event. We are definitely going to be doing more of these. So stay tuned, maybe face-to-face in person. I'm John Furrier with Dave Vellante now for the Ecosystem chiming in, and they're going to speak and share their thoughts here with "theCUBE" our first live stage performance event in our studio. Thanks for watching. (gentle upbeat music)

>>from around the globe. It's the Cube presenting Cuban cloud brought >>to you by silicon angle. Okay, we're back. Here. Live Cuban Cloud. And this is Dave. Want with my co host, John Ferrier Were all remote. We're getting into the analyst power half hour. Really pleased to have Maribel Lopez here. She's the principal and founder of Lopez Research and Zias Caraballo, who is the principal and founder of ZK research. Guys, great to see you. Let's get into it. How you doing? >>Great. How you been? Good, >>thanks. Really good. John's hanging in there quarantining and, uh, all healthy, So I hope you guys are too. Hey, Mary, But let's start with you. You know, here we are on 2021 you know, just exited one of the strangest years, if not the strangest year of our lives. But looking back in the past decade of cloud and we're looking forward. How do you see that? Where do we come from? Where we at and where we going >>When we obviously started with the whole let's build a public cloud and everything was about public cloud. Uh, then we went thio the notion of private cloud than we had hybrid cloud and multi cloud. So we've done a lot of different clouds right now. And I think where we are today is that there's a healthy recognition on the cloud computing providers that you need to give it to the customers the way they want it, not the way you've decided to build it. So how do you meet them where they are so that they can have a cloud like experience wherever they want their data to be? >>Yes and yes, you've, you know, observed, This is well, in the early days of cloud, you heard a lot of rhetoric. It was private cloud And and then now we're, you know, hearing a lot of multi cloud and so forth. But initially, a lot of the traditional vendors kind of pooh poohed it. They called us analysts. We said we were all cloud crazy, but they seem to have got their religion. >>Well, everything. Everyone's got a definition of cloud, but I actually think we are right in the midst of another transformation of clouds Miracle talked about. We went from, you know, private clouds, which is really hosting the public cloud to multi cloud hybrid cloud. And if you look at the last post that put on Silicon Angle, which was talking about five acquisition of Volterra, I actually think we're in the midst of the transition to what's called distributed Club, where if you look at modernized cloud apps today, they're actually made up of services from different clouds on also distributed edge locations. And that's gonna have a pretty profound impact on the way we build out, because those distributed edges be a telco edge, cellular vagina. Th whatever the services that lived there are much more ephemeral in nature, right? So the way we secure the way we connect changes quite a bit. But I think that the great thing about Cloud is we've seen several several evolutionary changes. So what the definition is and we're going through that now, which is which is pretty cool to think about, right? It's not a static thing. Um, it's, uh, you know, it's a it's an ongoing transition. But I think, uh, you know, we're moving into this distributed Cloudera, which to me is a lot more complex than what we're dealing with in the Palace. >>I'm actually pretty excited about that because I think that this move toe edge and the distribution that you've talked about, it's like we now have processing everywhere. We've got it on devices, we've got it in, cars were moving, the data centers closer and closer to where the action's happening. And I think that's gonna be a huge trend for 2021. Is that distributed that you were talking about a lot of edge discussion? You >>know what? The >>reason we're doing This, too, is we want. It's not just we're moving the data closer to the user, right? And some. If you think you brought up the autonomous vehicle right in the car being an edge, you think of the data that generates right? There's some things such as the decision to stop or not right that should be done in car. I don't wanna transport that data all the way back to Google him back to decide whether I want to stop. You could also use the same data determine whether drivers driving safely for insurance purposes, right? So the same data give me located at the edge or in a centralized cloud for different purposes, and I think that's what you know, kind of cool about this is we're being able to use our data and much different ways. Now. >>You know, it's interesting is it's so complex. It's mind blowing because this is distributed computing. Everyone kind of agrees this is where it is. But if you think about the complexity and I want to get your guys reaction to this because you know some of the like side fringe trend discussions are data sovereignty, misinformation as a vulnerability. Okay, you get the chips now you got gravitas on with Amazon in front. Apple's got their own chips. Intel is gonna do a whole new direction. So you've got tons of computer. And then you mentioned the ephemeral nature. How do you manage those? What's the observe ability look like? They're what's the trust equation? So all these things kind of play into it. It sounds almost mind blowing, just even thinking about it. But how do you guys, this analyst tryto understand where someone's either blowing bullshit or kind of like has the real deal? Because all those things come into play? I mean, you could have a misinformation campaign targeting the car. Let's say Hey, you know that that data is needs to be. This is this is misinformation who's a >>in a lot of ways, this creates almost unprecedented opportunity now for for starts and for companies to transform right. The fundamental tenet of my research has always been share shifts happen when markets transition and we're in the middle of the big one. If the computer resource is we're using, John and the application resource will be using or ephemeral nature than all the things that surrounded the way we secured the way we connect. Those also have to be equal, equally agile, right, So you can't have, you know, you think of a micro services based application being secured with traditional firewalls, right? Just the amount of, or even virtual the way that the length of time it takes to spend those things up is way too long. So in many ways, this distributed cloud change changes everything in I T. And that that includes all of the services in the the infrastructure that we used to secure and connect. And that's a that is a profound change, and you mentioned the observe ability. You're right. That's another thing that the traditional observe ability tools are based on static maps and things and, you know, traditional up, down and we don't. Things go up and down so quickly now that that that those don't make any sense. So I think we are going to see quite a rise in different types of management tools and the way they look at things to be much more. I suppose you know Angela also So we can measure things that currently aren't measurable. >>So you're talking about the entire stack. Really? Changing is really what you're inferring anyway from your commentary. And that would include the programming model as well, wouldn't it? >>Absolutely. Yeah. You know, the thing that is really interesting about where we have been versus where we're going is we spent a lot of time talking about virtual izing hardware and moving that around. And what does that look like? And that, and creating that is more of a software paradigm. And the thing we're talking about now is what is cloud is an operating model look like? What is the manageability of that? What is the security of that? What? You know, we've talked a lot about containers and moving into a different you know, Dev suck ups and all those different trends that we've been talking about, like now we're doing them. So we've only got into the first crank of that. And I think every technology vendor we talked to now has to address how are they going to do a highly distributed management and security landscape? Like, what are they gonna layer on top of that? Because it's not just about Oh, I've taken Iraq of something server storage, compute and virtualized it. I now have to create a new operating model around it. In a way, we're almost redoing what the OS I stack looks like and what the software and solutions are for that. >>So >>it was really Hold on, hold on, hold on their lengthened. Because that side stack that came up earlier today, Mayor. But we're talking about Yeah, we were riffing on the OSC model, but back in the day and we were comparing the S n a definite the, you know, the proprietary protocol stacks that they were out there and someone >>said Amazon's S N a. Is that recall? E think that's what you said? >>No, no. Someone in the chest. That's a comment like Amazon's proprietary meaning, their scale. And I said, Oh, that means there s n a But if you think about it, that's kind of almost that can hang. Hang together. If the kubernetes is like a new connective tissue, is that the TCP pipe moment? Because I think Os I kind of was standardizing at the lower end of the stack Ethernet token ring. You know, the data link layer physical layer and that when you got to the TCP layer and really magic happened right to me, that's when Cisco's happened and everything started happening then and then. It kind of stopped because the application is kinda maintain their peace there. A little history there, but like that's kind of happening now. If you think about it and then you put me a factor in the edge, it just kind of really explodes it. So who's gonna write that software? E >>think you know, Dave, your your dad doesn't change what you build ups. It's already changed in the consumer world, you look atyou, no uber and Waze and things like that. Those absolute already highly decomposed applications that make a P I calls and DNS calls from dozens of different resource is already right. We just haven't really brought that into the enterprise space. There's a number, you know, what kind of you know knew were born in the cloud companies that have that have done that. But they're they're very few and far between today. And John, your point about the connectivity. We do need to think about connectivity at the network layer. Still, obviously, But now we're creating that standardization that standardized connectivity all the way a player seven. So you look at a lot of the, you know, one of the big things that was a PDP. I calls right, you know, from different cloud services. And so we do need to standardize in every layer and then stitch that together. So that does make It does make things a lot more complicated. Now I'm not saying Don't do it because you can do a whole lot more with absolute than you could ever do before. It's just that we kind of cranked up the level of complexity here, and flowered isn't just a single thing anymore, right? That's that. That's what we're talking about here It's a collection of edges and private clouds and public clouds. They all have to be stitched together at every layer in orderto work. >>So I was I was talking a few CEOs earlier in the day. We had we had them on, I was asking them. Okay, So how do you How do you approach this complexity? Do you build that abstraction layer? Do you rely on someone like Microsoft to build that abstraction layer? Doesn't appear that Amazon's gonna do it, you know? Where does that come from? Or is it or is it dozens of abstraction layers? And one of the CEO said, Look, it's on us. We have to figure out, you know, we get this a p I economy, but But you guys were talking about a mawr complicated environment, uh, moving so so fast. Eso if if my enterprise looks like my my iPhone APs. Yes, maybe it's simpler on an individual at basis, but its app creep and my application portfolio grows. Maybe they talk to each other a little bit better. But that level of complexity is something that that that users are gonna have to deal >>with what you thought. So I think quite what Zs was trying to get it and correct me if I'm wrong. Zia's right. We've got to the part where we've broken down what was a traditional application, right? And now we've gotten into a P. I calls, and we have to think about different things. Like we have to think about how we secure those a p I s right. That becomes a new criteria that we're looking at. How do we manage them? How do they have a life cycle? So what was the life cycle of, say, an application is now the life cycle of components and so that's a That's a pretty complex thing. So it's not so much that you're getting app creep, but you're definitely rethinking how you want to design your applications and services and some of those you're gonna do yourself and a lot of them are going to say it's too complicated. I'm just going to go to some kind of SAS cloud offering for that and let it go. But I think that many of the larger companies I speak to are looking for a larger company to help them build some kind of framework to migrate from what they've used with them to what they need tohave going forward. >>Yeah, I think. Where the complexities. John, You asked who who creates the normalization layer? You know, obviously, if you look to the cloud providers A W s does a great job of stitching together all things AWS and Microsoft does a great job of stitching together all things Microsoft right in saying with Google. >>But >>then they don't. But if if I want to do some Microsoft to Amazon or Google Toe Microsoft, you know, connectivity, they don't help so much of that. And that's where the third party vendors that you know aviatrix on the network side will tear of the security side of companies like that. Even Cisco's been doing a lot of work with those companies, and so what we what we don't really have And we probably won't for a while if somebody is gonna stitch everything together at every >>you >>know, at every layer. So Andi and I do think we do get after it. Maribel, I think if you look at the world of consumer APS, we moved to a lot more kind of purpose built almost throwaway apps. They serve a purpose or to use them for a while. Then you stop using them. And in the enterprise space, we really haven't kind of converted to them modeling on the mobile side. But I think that's coming. Well, >>I think with micro APS, right, that that was kind of the issue with micro APS. It's like, Oh, I'm not gonna build a full scale out that's gonna take too long. I'm just gonna create this little workflow, and we're gonna have, like, 200 work flows on someone's phone. And I think we did that. And not everybody did it, though, to your point. So I do think that some people that are a little late to the game might end up in in that app creep. But, hey, listen, this is a fabulous opportunity that just, you know, throw a lot of stuff out and do it differently. What What? I think what I hear people struggling with ah lot is be to get it to work. It typically is something that is more vertically integrated. So are you buying all into a Microsoft all you're buying all into an Amazon and people are starting to get a little fear about doing the full scale buy into any specific platform yet. In absence of that, they can't get anything to work. >>Yeah, So I think again what? What I'm hearing from from practitioners, I'm gonna put a micro serve. And I think I think, uh, Mirabelle, this is what you're implying. I'm gonna put a micro services layer. Oh, my, my. If I can't get rid of them, If I can't get rid of my oracle, you know, workloads. I'm gonna connect them to my modernize them with a layer, and I'm gonna impart build that. I'm gonna, you know, partner to get that done. But that seems to be a a critical path forward. If I don't take that step, gonna be stuck in the path in the past and not be able to move forward. >>Yeah, absolutely. I mean, you do have to bridge to the past. You you aren't gonna throw everything out right away. That's just you can't. You can't drive the bus and take the wheels off that the same time. Maybe one wheel, but not all four of them at the same time. So I think that this this concept of what are the technologies and services that you use to make sure you can keep operational, but that you're not just putting on Lee new workloads into the cloud or new workloads as decomposed APS that you're really starting to think about. What do I want to keep in whatever I want to get rid of many of the companies you speak Thio. They have thousands of applications. So are they going to do this for thousands of applications? Are they gonna take this as an opportunity to streamline? Yeah, >>well, a lot of legacy never goes away, right? And I was how companies make this transition is gonna be interesting because there's no there's no really the fact away I was I was talking to this one company. This is New York Bank, and they've broken their I t division down into modern I t and legacy I t. And so modern. Everything is cloud first. And so imagine me, the CEO of Legacy i e 02 miracles. But what they're doing, if they're driving the old bus >>and >>then they're building a new bus and parallel and eventually, you know, slowly they take seats out of the old bus and they take, you know, the seat and and they eventually start stripping away things. That old bus, >>But >>that old bus is going to keep running for a long time. And so stitching the those different worlds together is where a lot of especially big organizations that really can't commit to everything in the cloud are gonna struggle. But it is a It is a whole new world. And like I said, I think it creates so much opportunity for people. You know, e >>whole bus thing reminds me that movie speed when they drive around 55 miles an hour, just put it out to the airport and just blew up E >>got But you know, we all we all say that things were going to go away. But to Zia's point, you know, nothing goes away. We're still in 2021 talking about mainframes just as an aside, right? So I think we're going to continue tohave some legacy in the network. But the But the issue is ah, lot will change around that, and they're gonna be some people. They're gonna make a lot of money selling little startups that Just do one specific piece of that. You know, we just automation of X. Oh, >>yeah, that's a great vertical thing. This is the This is the distributed network argument, right? If you have a note in the network and you could put a containerized environment around it with some micro services um, connective tissue glue layer, if you will software abstract away some integration points, it's a note on the network. So if in mainframe or whatever, it's just I mean makes the argument right, it's not core. You're not building a platform around the mainframe, but if it's punching out, I bank jobs from IBM kicks or something, you know, whatever, Right? So >>And if those were those workloads probably aren't gonna move anywhere, right, they're not. Is there a point in putting those in the cloud? You could say Just leave them where they are. Put a connection to the past Bridge. >>Remember that bank when you talk about bank guy we interviewed in the off the record after the Cube interviews like, Yeah, I'm still running the mainframe, so I never get rid of. I love it. Run our kicks job. I would never think about moving that thing. >>There was a large, large non US bank who said I buy. I buy the next IBM mainframe sight unseen. Andi, he's got no choice. They just write the check. >>But milliseconds is like millions of dollars of millisecond for him on his back, >>so those aren't going anywhere. But then, but then, but they're not growing right. It's just static. >>No, no, that markets not growing its's, in fact. But you could make a lot of money and monetizing the legacy, right? So there are vendors that will do that. But I do think if you look at the well, we've already seen a pretty big transition here. If you look at the growth in a company like twilio, right, that it obviates the need for a company to rack and stack your own phone system to be able to do, um, you know, calling from mobile lapse or even messaging. Now you just do a P. I calls. Um, you know, it allows in a lot of ways that this new world we live in democratizes development, and so any you know, two people in the garage can start up a company and have a service up and running another time at all, and that creates competitiveness. You know much more competitiveness than we've ever had before, which is good for the entire industry. And, you know, because that keeps the bigger companies on their toes and they're always looking over their shoulder. You know what, the banks you're looking at? The venues and companies like that Brian figure out a way to monetize. So I think what we're, you know well, that old stuff never going away. The new stuff is where the competitive screen competitiveness screen. >>It's interesting. Um IDs Avery. Earlier today, I was talking about no code in loco development, how it's different from the old four g l days where we didn't actually expand the base of developers. Now we are to your point is really is democratizing and, >>well, everybody's a developer. It could be a developer, right? A lot of these tools were written in a way that line of business people create their own APs to point and click interface is, and so the barrier. It reminds me of when, when I started my career, I was a I. I used to code and HTML build websites and then went to five years. People using drag and drop interface is right, so that that kind of job went away because it became so easy to dio. >>Yeah, >>sorry. A >>data e was going to say, I think we're getting to the part. We're just starting to talk about data, right? So, you know, when you think of twilio, that's like a service. It's connecting you to specific data. When you think of Snowflake, you know, there's been all these kinds of companies that have crept up into the landscape to feel like a very specific void. And so now the Now the question is, if it's really all about the data, they're going to be new companies that get built that are just focusing on different aspects of how that data secured, how that data is transferred, how that data. You know what happens to that data, because and and does that shift the balance of power about it being out of like, Oh, I've created these data centers with large recommend stack ums that are virtualized thio. A whole other set of you know this is a big software play. It's all about software. >>Well, we just heard from Jim Octagon e You guys talking earlier about just distributed system. She basically laid down that look. Our data architectures air flawed there monolithic. And data by its very nature is distributed so that she's putting forth the whole new paradigm around distributed decentralized data models, >>which Howie shoe is just talking about. Who's gonna build the visual studio for data, right? So programmatic. Kind of thinking around data >>I didn't >>gathering. We didn't touch on because >>I do think there's >>an opportunity for that for, you know, data governance and data ownership and data transport. But it's also the analytics of it. Most companies don't have the in house, um, you know, data scientists to build on a I algorithms. Right. So you're gonna start seeing, you know, cos pop up to do very specific types of data. I don't know if you saw this morning, um, you know, uniforms bought this company that does, you know, video emotion detection so they could tell on the video whether somebody's paying attention, Not right. And so that's something that it would be eso hard for a company to build that in house. But I think what you're going to see is a rise in these, you know, these types of companies that help with specific types of analytics. And then you drop you pull those in his resource is into your application. And so it's not only the storage and the governance of the data, but also the analytics and the analytics. Frankly, there were a lot of the, uh, differentiation for companies is gonna come from. I know Maribel has written a lot on a I, as have I, and I think that's one of the more exciting areas to look at this year. >>I actually want to rip off your point because I think it's really important because where we left off in 2020 was yes, there was hybrid cloud, but we just started to see the era of the vertical eyes cloud the cloud for something you know, the cloud for finance, the cloud for health care, the telco and edge cloud, right? So when you start doing that, it becomes much more about what is the specialized stream that we're looking at. So what's a specialized analytic stream? What's a specialized security stack stream? Right? So until now, like everything was just trying to get to what I would call horizontal parody where you took the things you had before you replicated them in a new world with, like, some different software, but it was still kind of the same. And now we're saying, OK, let's try Thio. Let's try to move out of everything, just being a generic sort of cloud set of services and being more total cloud services. >>That is the evolution of everything technology, the first movement. Everything doing technology is we try and make the old thing the new thing look like the old thing, right? First PCs was a mainframe emulator. We took our virtual servers and we made them look like physical service, then eventually figure out, Oh, there's a whole bunch of other stuff that I could do then I couldn't do before. And that's the part we're trying to hop into now. Right? Is like, Oh, now that I've gone cloud native, what can I do that I couldn't do before? Right? So we're just we're sort of hitting that inflection point. That's when you're really going to see the growth takeoff. But for whatever reason, and i t. All we ever do is we're trying to replicate the old until we figure out the old didn't really work, and we should do something new. >>Well, let me throw something old and controversial. Controversial old but old old trope out there. Consumerism ation of I t. I mean, if you think about what year was first year you heard that term, was it 15 years ago? 20 years ago. When did that first >>podcast? Yeah, so that was a long time ago >>way. So if you think about it like, it kind of is happening. And what does it mean, right? Come. What does What does that actually mean in today's world Doesn't exist. >>Well, you heard you heard. Like Fred Luddy, whose founder of service now saying that was his dream to bring consumer like experiences to the enterprise will. Well, it didn't really happen. I mean, service not pretty. Pretty complicated compared toa what? We know what we do here, but so it's It's evolving. >>Yeah, I think there's also the enterprise ation of consumer technology that John the companies, you know, you look a zoom. They came to market with a highly consumer facing product, realized it didn't have the security tools, you know, to really be corporate great. And then they had to go invest a bunch of money in that. So, you know, I think that waken swing the pendulum all the way over to the consumer side, but that that kind of failed us, right? So now we're trying to bring it back to center a little bit where we blend the two together. >>Cloud kind of brings that I never looked at that way. That's interesting and surprising of consumer. Yeah, that's >>alright, guys. Hey, we gotta wrap Zs, Maribel. Always a pleasure having you guys on great great insights from the half hour flies by. Thanks so much. We appreciate it. >>Thank >>you guys. >>Alright, keep it right there. Mortgage rate content coming from the Cuban Cloud Day Volonte with John Ferrier and a whole lineup still to come Keep right there.

>> Live from Las Vegas, it's theCUBE covering Informatica World 2019. Brought to you by Informatica. >> Welcome everyone, you are watching theCUBE. We are kicking off a two-day event here at Informatica World 2019 in Las Vegas. I'm your host, and I'm co-hosting along with John Furrier. It's great to have you. Great to be here. >> Great to see you again. >> So, Informatica is really sitting in the sweet spot of a fast-growing area of technology, cloud and big data. I want to ask you a big question. Where is the market? What do you see happening in this sweet spot area? >> Well we're here in Informatica World. I think it's our fourth Cube coverage. We've been following these guys since they've gone private two years ago in depth. Interesting changeover. They went private just like Michael Dell did with Dell Technologies. And then they went public in great performance. We said at that time, if they can go private with the product skills that they have in their senior leadership, they could do well. And they've been on the same trend line, which has been really positive data. Now data is the hottest thing on the planet. This is the theme of the industry. Data is everything. Machine learning needs data. Data feeds machine learning. Machine learning feeds AI. This is a core innovator. Now the challenge is on the enterprise side is that data is structured. It's in all these different databases. So in an enterprise, data's kind of has all these legacy structures and legacy systems. And the cloud for instance. Cloud is where SaaS wins. And SaaS winners like Zoom Communications, Air BNB, you name all those successful cloud data companies. Data's at the heart of their value proposition. And data is unencumbered. There's no restrictions. They use data, data as analysis. They look at customer behavior, AB testing. So data is the heart of innovation. This is Informatica's plan here. CLAIRE is their AI product. Their theme is kind of clever. CLAIRE starts here. And this is really the focus for Informatica. Their opportunity is to be that independent vendor supplier, the Switzerland as it has been called, the neutral third party to bring data together On Premise and Cloud. That's what they're saying. That's their opportunity. The challenges are high. The data business is being regulated. We talk about it last time. You know, privacy, GDPR one-year anniversary, Microsoft's calling for more privacy. As more regulation comes in, that puts more restrictions on data. That requires more software. That creates overhead. Overhead is not good for SaaS business models. And that is where the conflict is. This is the opportunity, and if they can overcome that as a supplier, then they can do well. And data growth is just massive. Cloud, IoT Edge, you name it. Data is the center of the value proposition. >> Well, and we're going to have a lot of great guests on the program this week, in particular we're going to have Sally Jenkins talking about these four customer journeys that the customers are going on. And in fact data governance and privacy is one of the big tenants. So, they are making, they are saying this is our wheelhouse. We can do this. We can help you do this. >> Well, the thing is we're going to ask every guest the question of the week is What's the skill gaps? Because digital transformation although very relevant is only as good as the people and the culture that's behind it. And that's a theme that we hear all throughout our different CUBE events. If people have the culture for it, they could do it. DevOps is another word that has been kicked around. But ultimately if you don't have the people and just machines, it's really going to be a tough balance to strike. You need the machines, you need the data, you need the people. And this is where the challenge is in the industry. I think the skill gaps is a huge problem for digital transformation. It's to me the big blocker in seeing innovation accelerate. So customers are now having that journey. They're starting, they really think about how to architect their enterprise with an On Premise, with a Legacy and Cloud Native with full SaaS. And the companies that can get to a SaaS business model, managing the On-Premise's legacy will have a winning shot at taking new market share or top one down incumbents in leadership positions. >> I'm really excited about this idea. Asking people about the skill gap and where the next generation of jobs are going to be in big data. I saw a statistic, a survey from Google, 94% of IT managers can't find qualified candidates for open Cloud roles. That is-that's astonishing. I also saw an interesting quote from Tim Cook, who recently said that half of Apple's new hires are not going to have a college degree this year. He said when our own founder didn't have one. It kind of really shows you what you can do. >> It's really early. >> You might not need this degree. >> First of all, it's really, first of all I agree that degrees don't really matter. In some cases, old degrees might not apply to the new jobs. I'll give you an example. My daughter just graduated from Cal Berkeley this week. And they had the inaugural class of data, data science, data analytics. For the first time, first graduating class. That's a tell-sign that we're at the early, early stages. But data science can come from anyone. You could be, you know, anthropologist, you could be any any skill. You can solve a problem, you're good at math. You can see the big picture. You're seeing data science really becoming a career. And again, there's just not enough job openings. And data science isn't just for the data jockeys out there who just want to do data. There's cyber security, huge data-driven. Everything is data-driven. The big growth area in the enterprise is the IoT, the Edge. As devices come online for manufacturing to oil rigs to wind farms. The edge computing is a huge thing. And that's a data problem. Everything is a data problem. So this is where the industry is focused I think Informatica was really on it early. And now everyone's jumping in. You got Amazon, Google, Microsoft, the big cloud players, and you got all the existing incumbent enterprise suppliers all putting data at the center-value proposition. You know you got a lot of competition now for Informatica, and they have to make some good moves here. And what I'm going to be looking for here, Rebecca, is how they transform as a company. Because I think that they have to be an integration company. They want to be that Switzerland. They got to integrate to all the clouds. They got to integrate to all the different platforms and environments on the enterprise and create that one operating model. And this is something they say they want to do, and we're going to ask them. >> And you not only called them Switzerland, they've called themselves Switzerland. And so I think that they are. They do want that. They want that for themselves. They want they are having these partnerships with all of the major cloud providers. So, you said this is what you're going to be asking. This is what you're going to be looking for. What is it that you think will set them apart? >> I think ultimately I think Informatica's got a great management team when it comes to product and engineering. One of the things I've been impressed with is they get the product around data. The only thing I think that could be a headwind for them as a challenge is this regulatory environment. I brought that up earlier. I think this could be a challenge and an opportunity, and it could be the difference maker because there's no question that their value proposition or how they're dealing with data management, their deals we're going to hear about with the cloud and all of the new innovation they have with CLAIRE and AI. Certainly that's good. But if you don't have data-feeding machine learning, and the data's hard to get at, and it's regulated, you got clouds with geographies and countries have new regulations. This is a complicated problem. If they could create software to make that easier and create an abstraction layer and use the power of the cloud, I think they could have a winning formula. So to me, that's a killer opportunity. And then making data work for SaaS-oriented business models, On-Premise and in the cloud. >> I think you're absolutely right and we heard Anil Chakravarthy say this today. Data needs the machine learning an AI, AI machine learning need data. And any application of AI and machine learning is only as good as the data that's been collected. So, the other big challenge is what I think is going to be really exciting about for this show is seeing all of these use cases. In industry after industry we are seeing applications of AI and machine learning transforming business models and approaches and leadership and big ideas around these important game-changers in our industry. >> Yeah, one of the things that's interesting I had an interview with in the city of Howie Xu, who's formally VMWare engineer, entrepreneur, sold his company to Zscaler. He's an AI guy, and we talked about the SaaS business model. And one of the things that's key is if you don't have the data feeding the SaaS, it's not going to work, so to me if they could get that data back in to the system quicker with all that regulation, that's going to be a game changer. And I think they got to start thinking how they can show the customer proof points. That's going to be interesting when the customers start adapting in that scale. >> And as we've also said many times on theCUBE the governance is kind of a mess itself. I mean Washington doesn't quite know what to do with this and how to regulate it. How do you think that these technology companies should be working with Washington on this? >> Well that's a loaded question. First of all, I think the government is not the bellwether for technology innovation. In fact, I think innovation is stifled by too much regulation. There's got to have a balance there. One of the things that's positive is in the cyber-security area you see private, public partnerships go on where there's some joint sharing. I think cloud is going to be a catalyst. We're going to have the VP of marketing from Amazon web services on, I'm going to ask him that direct question. This is where the action is. So I think this notion of collaboration the enterprise and cloud players is going to be key because if you look at like just how search engines used to work back in the old days, if it was not encumbered by all this legacy infrastructure in the enterprise, it works great. The more you add complexity to things, the more you need software. The more you need software, you need horsepower to compute. You need more storage. So all these things are creating a different environment than it was just three years ago. So, you know can they adjust, can the industry shape itself out? I think the industry needs to lead here, not the government. >> What about the idea of Informatica working together with customers and making sure that they are in fact deriving value? Because I mean I think that's the other thing is that all of these companies know they need to have an AI strategy, they need to be using more machine learning. It's very complicated as you said. But then there's this question of am I really going to see a return of investment on this? >> Well, I think Informatica can do a good job working with cloud architecture and looking at because you got again IoT edge is coming around the corner. But if they can nail the architecture On-Premises and Cloud, that is a great start. The second thing that Informatica can help customers at, and this is a customer challenge, is where do you store the data? Because moving data around is very expensive. So this scenario is where you want it all on the cloud. This scenario is where you want it all On Premise. And this scenario is where you want it on both locations. And then with the edge, you want to move data I mean compute to where the data is. So, data becomes a very critical piece of the overall architecture and whoever can build this operating system's mindset will have a winning formula, and again being neutral is a critical strategy. And the more Informatica can help enterprise be more like consumer companies, the better. If you look at Slack for instance, it's an IPO candidate coming out very popular. It's just a chat kind of message board app. What made Slack successful is that they built connectors and APIs into all different tools. If Informatica could do that, that would be a winning formula because they want to be data brokering, they want to be data connecting, and they want to feed the applications and machine learning data. If they can't get data to the machine learning and AI, the AI will not be sufficient. And that will be a problem. >> Well, this is all the things we are going to be talking about over these next two days. John, I look forward to it. I'm Rebecca Knight, you are watching theCUBE. (lighthearted techno music)

>> live from Boston, Massachusetts. It's the queue covering your red. Have some twenty nineteen brought to you by bread hat. >> Well, good afternoon. Where you might be watching us here on the Cube. We are live in Boston. Is we wrap up our coverage headed toward the homestretch? You might say of Red had Summit twenty nineteen. Want was to Mittleman. I'm John Walls. And thank you for joining us here. We're now joined by Ah, Louise, right. Bower, who was the vice president and chief technical strategists and head of innovation lab at Dinah Trees. And always good to see you today. Thanks for being with us. Hello. Thanks for having me s O software intelligence that that's your your primary focus. You've got headquarters here in the Boston area back in Austria. Tell a little bit about it. You would, Dina Trace. And I guess first off, what this news this week has met to you in terms of the release is and then maybe what you're doing in general. You know what Dina Trace is all about? >> Yes. Oh, that phrase has been around for, like quite a time. Started out as an a P M. Company. like fourteen years ago have been reinventing ourselves over and over again on DH. So we move from the traditional monitoring approach. So the innovation we had in the very beginning when we launched the first product was really would be practical, pure passer. The ability trace and went that way a lot about facing racing, like becoming super cool for micro services. So it would be like the first teacher we could be burying, doing, tracing before it was cool, like forty, fifty years ago. And then I was were involving the product more, more Skilling into bigger and bigger environments. So what's bigger and bigger mean? I remember in the beginning when we were working on environments who we're talking about, like one hundred host has a big environment like five hundred told that that's a big environment today, we say, for even one hundred thousand toast. Okay, it's a big environment, but they can't get even bigger then. The massive change was really for us five years ago, where way implemented our entire product offering, built the new Dina trays, Mr Focus, that we realize that okay, it's data and between people date and having them analyzed data is nice, but it's only getting you so far. So the more complex the replication get, more data you get to analyze. And it's just more exponentially scaling how many people you would need to deal with this. And that's why five years ago, we started to incorporate a I into our new court platform, then for automatic problem analysis. That's also where we're not just BPM. That's just what we call like the Dogg Tools data on glass tools to show a lot of data. Do some analysis on top of it. But it don't help you, too, really resolve a problem. So we used build in the eye, and that automatic would cause analysis again. Next teacher doing Aye, aye ops, affordable school like five years ago. Andi. The latest evolution. We also so again, and not a change in the way people are using monitoring tools. Um, we've invested a lot into building out in AP eyes don't see monitoring tools like be the Martin still here and the application over there, but having them monitoring who being highly integrated into the fabric fire eyes. So we have, As of today, eighty percent of our customers are using the product also via reprise, but tying them into operational automation. What we heard even today in the keynote here about a ABS and Howie iop starts to control and manage that form. More is becoming the intelligence or the back plane behind a modern native stack. >> So we have Chris right on. Who was in the keynote this morning? Came on our program this morning, too, when we talked about just the rippling effects of distributed architectures. I look at my applications there, you know, going to micro service architectures. You look at where's customers data? Well, lots of stuff all over the clouds and sass, and that has a ripple. Effect it to your space. You know, I hear observe, ability monitoring, you know, hack even bring up, like, you know, the civilised world. It becomes a whole separate meeting. So Donna Trace has been going through a transformation. You know, give >> us a >> point check ins to you know, where your customers are, how you're helping them move through this modernization and, you know, move to distributed architectures where that fits in >> so that their customers we focus on mostly are like Fortune five hundred customers who we work with. And obviously they have everything that exists on the planet. When we talk about self for like even from the mainframe to cloud native to serve less, as you mentioned here. And they were in this transition process right now, like modernizing their applications, which, as a necessity, we all want to move fast. There we want therefore flexible architects is we want to build more enough innovative products but at the same time to realize that this is also a message business risk behind following this approach. Think about you in the role of the CEO and say where we're going to modernize our architecture. We're going to rebuild everything we platform and so forth. You can if you succeed. Everybody would say you had. Yes, you did what you had to do. I mean, sorry if you failed, you failed. It's s so for them, it's a It's a big risk to move down that route and retired to take that risk out of the process as much as possible. Really Starting, obviously was monitoring their traditional sex, as they have to today, but really supporting that along that entire journey to a cloud native architecture er, starting with what we referred to as our support for monoliths to micro service architecture's. So Theodore is basically you don't want to rip apart the replication and figure out how it's going to work in my purse services world. But we have to technology that's called smart scape smart. Skip Moelis bills a real time, all of your entire data center and old applications running into it. And it was virtually that sect. You're marvelous, you came. How would they look like in a microt services architecture without catching any codes and then making it work? So once you've done this once, you've decided to move there the next step? Obviously, yes, you could have rebuilt that application. Usually we see applications with micro services architectures being significantly Mohr complex or more distributed by the sign that a traditional that you might have Web server application, Teo Database Server. Now you might be talking about maybe two hundred micro services or more so twenty times ranges. Writer on this under under lower bound here, which means that your traditional operational approach up okay, it's either the database of observer. The application server doesn't work anymore. on top of this. You did all of this to deploy fast. Like for like, bi weekly releases, even maybe daily off, like a smaller granularity. So you were reading a lot of entropy to that system and you have to analyze way more data. Did he ever had to do before? And this is where we kind of getting to the level where theoretically humans could do it. But it would just take us too long where the Holy I ops capability come in where we let let the machines that a monitoring tto take care of it at that level. So we helping them to operation US thieves processes and then really supporting them along the whole journey, where every customer we talked like this vision. But we're also here today in the keynote of an autonomous cloud and with carbonated, we already made a great step in this direction, looking at the interest, actually, like today say, I need five replicas off this container. I don't know, given that it's does it open shift and specifically here, it's going to happen. But if we move to the application layer is a lot, that has to be done and it has to make it easier for people to do. And that's where we tied into the entire customers. Ecosystem toe, automate like their cloud environment and have actually built a practice around which we call autonomous cloud management that we have been working with with customers on to enable them to achieve this over time. But it's going to be a lot maturity there. >> Yes, I mean, so what it talked about that you know, a CIA autonomous cloud management. What exactly you know, is that and how are you bringing that to your customer >> base? Autonomous Cloud Management resulted out off two different areas. The first one was when we were implement re implementing our platform. What I mentioned before, one step for us was to move to the SAS platform, and we looked at all the operation practices that were around back then, you know, we don't want to tell the doc I really don't want to do it. Like having people twenty four seven look at dashboards, then goingto a wicky, then reading a description of how to fix the problem. If you're the engineer, that why why do we do this this way? Must make any sense. So we developed our own practice, which we referred to as no wops. I know it doesn't mean that you're not doing operations. That would be pretty crazy, but not doing this traditional Naga type of operation, sitting there staring at a screen twenty four seven and then mentally executing any operation. So we had our own practice that we've built around it and, quite frankly, which has spilled it because we needed it for ourselves, and then we kept talking to customers and partisan, he says. Really cool what you did there like, Oh, how did you do this? What's like yourself? Respect behind this and what does the practices? What do your process? What's the culture change? So we were engaging with some customers, and then we were seeing that some of our customers back then, even we're doing bits and pieces off. This isthe well because there's a lot of practice and a lot of knowledge around. How did the autonomous count management and at the same time that we talked about the other customers who not yet on a charity who definitely want to get there? But I'm not quite sure how to do it, and I don't want to figure it out themselves. So we thought, Okay, let's take all of these best practices that we have and build more or less a methodology around it. How to make this actually works like how to do this. We really broke it down into, like, individual sprints to distance sprint one that distance sprint to to really have the results within three months, six months, twelve months. Whatever the cases that you want to run on. And then we realised talking to customers. This by itself isn't still enough. So that's why we started to open up this to an entire ecosystem. So WeII brought ecosystem partners along, like working closely with read a lot of our companies, but also system integrators who can help us. We speak of projects because we as a company, our software companies were not a services are consulting company, and we do support customer that some of those engagement. But if you think of like a really Fortune five hundred company that's a multi approaches, it will keep hundreds of people busy. So to recap like built in methodology, we built ecosystem to deliver on that promise at scale. And now the last step was we were doing this. We also built like a reference architecture for it, and I was just in an eternal ideas. So how do we, like structure this building reference architecture and then realized Okay, It's kind of like super helpful for customers. So that is why we don't decided to open source this reference architecture this fabric as well, too, like the tires after community, so they can also use it. So technically, stability is three pieces. It's the methodology, it's the ecosystem. And it's like the reference architecture that you can work with to help you, Chief. Go. >> All right, um, tell us how your a I fit into this. I've heard some analyst firms are saying, you know, some of the next generation of your space could be a I ops. Do you consider yourselves moving in that direction, or do you have some counter view on that? >> I think today a lot of things ar e I upset my now b a i ops, and it's a very undefined goal. This mentioned earlier. We decided to have aye aye based algorithms as powerful platform five years ago and nobody back then was talking about the layoffs. Funny story. Some of our competitors even told us you can't use the eye for monitoring just like totally stupid that there are other companies that they were doing it. But again, so the whole industry is learning here. I think it's really about data analysis. If you look at, if you scare the bigger and bigger environment, you really have to look at the process off what human operations people are doing on. There's obviously some hard decisions that you have to take their have. You have to work with teams to resolve our problems. But the biggest portion is really data analysis interpretation, right and a lot of this can be put into, and a I component that doesn't What's the Dyna trees, eh? I does it more. This is like your saree in codes, so to speak, which is able to find what's broken in the education, what was related to an issue in the application and being able to automatically find the root cause. Very importantly, we're kind of like opinionated and how in a I for operational practices should be working because one thing you don't want it serious you want? Don't want it happening. Iop system tell you well, you should. We start this service because some neural and that were told to do so. That's a building, a lot of confidence. That's why our approach is really tio follow. Like what we call a deterministic a pia a sari. And hey, I did it able to explain back to the user White came to a certain conclusion. So why should their we sort this herb is west of the rollback, this deployment or why that's the I b. Believe that if I fixed this problem, then like the bigger problem will be solved. So that's our approach, Teo T. I actually started like, roughly four years ago, five years ago, even a bit more than that on you. And I think that have a lot of experience, really rolling it out its scale and seeing it will help people because the next the ultimate next question, without always Scott Wass. If you wanna know what the problem is, why don't you fix it? And that's exactly the conversation you want to have, maybe just briefly at here, because it usually comes up okay, f a I and isat replacing people's jobs? I don't think so. We also heard it in the keynote today from Chris. It's augmenting our capabilities. There's hard decisions that you have to take, but just going through tons and tons of data. It's not going to your isn't very often when we talked at operations team or almost every time. First of all, you can't hire enough people anyways to get all the old done that's on your plate. Secondly, um, just by the amount of data and the time that I had to react. It's just long with a human understanding scenario way. Do this demo on self healing, often application. Where were deployed, something broken into production and have it being rolled back and we can do fifty one seconds. No human can do it that fast. That's just what pure, softer automation can do for you. So I think that then you can focus on other areas and more important, new project with us people in on the off space. What's what the three projects that you want to work and you never have time to work out and usually come up with the list. Yet this is what we give you back that time to work on exactly the things that move your business forwards. You >> said fifty one seconds. You've never seen Stew in action. You still have a lot of confidence. >> Well, we we love the machine, enhance human intelligence. You're definitely We could all use those machines to help us all get away from the drudgery and be able to do more. >> Always safe travels. Thanks for being with us. Headed back to Austria. Say, hide all your folks back in Austria, right There always is on his way home on his way to the airport. Thank you for being with us here on the Cube. Thanks. Appreciate the time our coverage continues here. Red hat some twenty nineteen. You're watching the cube?

>> Narrator: Live from Las Vegas, it's the Cube, covering VMWorld 2017. Brought to you by VMWare and its ecosystem partners. (bright music) >> Hi, I'm Stu Miniman with the Cube, here with my guest host, Justin Warren. Happy to have a returning Cube alum, but in a different role then we had. It's been a few years. Tal Klein, who is the author of The Punch Escrow. >> Au-tor, please. No, I'm just kidding. (laughing) Tal, thanks so much for joining us. It's great for you to be able to find time to hang out with the tech geeks rather than all the Hollywood people that you've been with recently. (laughing) >> You guys are more interesting. (laughing) >> Well thank you for saying that. So last time we interviewed you, you were working for a sizable tech company. You were talking about things like, you know, virtualization, everything like that. Your Twitter handle's VirtualTal. So how does a guy like that become not only an author but an author that's been optioned for a movie, which those of us that, you know, are geeks and everything are looking at, as a matter of fact, Pac Elsiger this morning said, "we are seeing science fiction become science fact." >> That's right. >> Stu: So tell us a little of the journey. >> Yeah, cool, I hope you read the book. (laughing) I don't know, the journey is really about marketing, right? Cause a lot of times when we talk about virtual, like, in fact last time I was on the Cube, we were talking about the idea that desktops could be virtual. Cause back then it was still this, you know, almost hypothetical notion, like could desktops be virtual, and so today, you know, so much of our life is virtual. So much of the things that we do are not actually direct. I was watching this great video by Apple's new augmented reality product, where you sit in the restaurant and you look at it with your iPad, and it's your plate, and you can just shift the menu items, and you see the menu items on your plate in the context of the restaurant and your seat and the person you're sitting across from. So I think the future is now. >> Yeah, it reminds of, you know, the movie Wall-E, the animated one. We're all going to be sitting in chairs with our devices or Ready Player One, you know, very popular sci-fi book that's being done by Speilberg, I believe. >> Yes, yeah, very exciting. >> Tell us a little bit about your book, you know, we talked, when I was younger and used to read a lot of sci-fi, it was like, what stuff had they done 50 years ago that now's reality, and what stuff had they predicted, like, you know, we're going to go away from currency and go digital currency, and it's like we're almost there. But we still don't have flying cars. >> Yeah, we're, I mean, the main problem with flying cars is that we need pilots. And I think actually we're very close to flying cars, cause once we have self-driving vehicles and we no longer need to worry about it being a person behind the joystick, then we're in really good shape. That's really the issue, you know, the problem with flying cars is that we are so incompetent at driving and or flying. That's not our core competency, so let's just put things that do understand how to make those things happen and eliminate us from the equation. >> Everything is a people problem. >> Yeah, so when I wrote the book, Punch Escrow, Punch Escrow, (laughing) when I wrote the book, I really thought about all the things that I read growing up in science fiction, you know, things like teleportation, things like nanotechnology, things like digital currency, you know, how do we make those, how do we present those in a viable way that doesn't seem too science fictiony. Like one of the things I really get when people read the book is it feels really near-future, even though it's set like 100 plus years in the future, all the concepts in it feel very pragmatic or within reach, you know? >> Yeah, absolutely. It's interesting, we look at, you know, what things happen in a couple of years and what things take a long time. So artificial intelligence, machine learning, it's not like these are new concepts, you know? I read a great book by, you know, it was Isaacson, The Innovators. You go back to like Aida Lovelace, and the idea of what a machine or computer would be able to do. So 100 years from now, what's real, what's not real? We still all have jobs or something? >> We have jobs but different. Remember, I don't know if you're a historian, but back in the industrial age, there was a whole bunch of people screaming doom and gloom. In fact, if we go way back to the age of the Luddites, who just hated machines of any kind. I think that in general, we don't like, you know, we're scared of change. So I do think a lot of the jobs that exist today are going to be done by machines or code. That doesn't mean the jobs are going away. It means jobs are changing. A lot of the jobs that people have today didn't exist in the industrial age. So I think that we have to accept that we are going to be pragmatic enough to accept the fact that humans will continue to evolve as the infrastructure powering our world evolves, you know? We talk about living in the age of the quantified self, right? There's a whole bunch that we don't understand how to do yet. For example, I can think of a whole industry that tethers my FitBit to my nutrition. You know, like there's so much opportunity that for us to say, oh that's going to be the end of jobs, or the end of innovation or the end of capitalism, is insane. I think this just ushers in a whole new age of opportunity. And that's me, I'm just an optimist that way, you know. >> So the Luddites did famously try to destroy the machines. But the thing is, the Luddites weren't wrong. They did lose their jobs. So what about the people whose jobs are replaced, as you say net new, there's a net new number of jobs. But specific individuals, like people who manufacture cars for example, lose their jobs because a robot can do that job safer and better and faster than a human can do it. So what do we do with those humans? Because how do we get people to have new jobs and retrain themselves? >> I address some of these notions in the book. For example, one of the weird things that we're suffering from is the lack of welders in society today, cause welding has become this weird thing that we don't think we need people for, so people don't really get trained up in it because, you know, machines do a lot of welding but there's actually specialty welding that machines can't do. So I think the people who are really good at the things that they do will continue to have careers. I think their careers will become more niche. Therefore they'll be able to create, to demand a higher wage for it because almost like a carpenter, you know, a specialist carpenter will be able to earn a much higher wage today by having fewer customers who want really custom carpentry versus things that can be carved up by a machine. So I think what we end up seeing is that it's not that those jobs go away. It's they become more specialized. People still want Rolls Royces. People still want McLarens. Those are not done by machines. Those are hand-made, you know? >> That's an interesting point, so the value of something being hand-made becomes, instead of it being a worse product, it's actually- >> Tal: That's a big concept in the book. >> Oh okay, right. >> A big concept in the book is that we place a lot of value on the uniqueness of an object. And that parlays in multiple ways. So one of the examples that I use in the book is the value of a Big Mac actually coming from McDonald's. Like, you can make a Big Mac. We know the recipe for a Big Mac. But there is a weird sort of nacent value to getting a Big Mac from McDonald's. It's something in our brain that clicks that tethers it to an originality. Diamonds, another really good example. Or you know, we know there's synthetic diamonds. We still want the ones that get mined in the cave. Why? We don't know. Right, they're just special. >> Because De Beers still has really good marketing. (laughing) >> So I think there's- >> That's interesting, so the concept of uniqueness, which again comes to scarcity and so on. As an author, someone who is no doubt, signed a lot of his book, that means that that book is unique because it's signed by the author, unlike something which is mass produced and there is hopefully thousands and thousands of copies that you sell. >> Going into this, I actually thought about that a lot. And that's why I've created like multiple editions of the book. So like the first 500 people who pre-ordered it, they get like a special edition of the book that's like stamped and all this kind of stuff. I even used different pens. (laughs) I appreciate that because I'm also a collector. I collect music, I collect books. And you know, so I see those aspects in myself. So I know what I value about them, you know? >> And the crossover between music and books is interesting. So as someone who has a musical background, I know that there's a lot of musicians who'll come out with special editions, and you know, because this is an age where we can download it. You can download the book. Do you think there is something, is there something that is intrinsic to having a physical object in a virtual world? >> I think to our generation, yes. I'm not so sure about millennials, when they grow up. But there are, for example, I'm going to see U2 next week, I'm very lucky to see that. But part of the U2 buying experience, to get access to the presale, you need to be part of their fan club. To be a part of their fan club, you need to get, you get like a whole bunch of limited edition posters, limited edition vinyl, and all this kind of stuff. So there's an experience. It's no longer just about going to see U2 at a concert. There's like the entire package of you being a special U2 fan. And they surround it with uniqueness. It's not necessarily limited, but there's an enhanced experience that can't just be, it's not just about you having a ticket to a single concert. >> Justin: Yeah, okay. >> I'm curious, the genre, if you'd call it, is hard science fiction. >> Yes. >> The challenge with that is, you know, what is an extension of what we're doing, and what is fiction? And people probably poke at that. Have you had any interesting experience, things like that? I mean, I've listened to a lot of stuff like Andy Weir, like let the community give feedback before he created the final The Martian. (laughing) But so yeah, what's it like, cause we can, the geeks can be really harsh. >> Yes, I've learned from my Reddit experience that, so what's really funny about it is the first draft of this novel was hard as nails. It was crazy. And my publisher read it, and it would have made all the hard science fiction guys super happy. My publisher read it, he was like, you've written a really great hard science fiction book, and all five people who read it are going to love it. (laughing) You know, but like, I came here with my buddy Danny. He couldn't even get through the first three pages of it. He's like, he wanted to read it. So part of working through the editorial process is saying, look, I care a lot about the science because one of my deep goals is to write a STEM-oriented book that gets people excited about technology and present the future as not a dystopian place. And so I wanted the science to be there and have a sort of gravity to the narrative. But yeah, it's tough. I worked with a physicist, a biologist, a geneticist, an anthropologist, and a lawyer. (laughs) Just to try to figure out, how do we carve out, you know, what does the future look like, what does the evolution of each individual sciences, we talked about the mosquitoes, right? You know, we're already doing a lot of crazy stuff with mosquitoes. We're modifying them so that the males mate with females that carry the Zika virus, you know, give birth to offspring that never reach maturity. I mean, this is just crazy, it's science fiction. And now that they're working on modifying female mosquitoes into vaccine carriers instead of disease carriers. I mean, this is science fiction, right? Like who believes this stuff? It's crazy. >> Christopher is amazing. >> Yeah, I've loved, there's been a bunch of movies recently that have kind of helped to educate on STEM some, you know, Martian got a lot of people excited, you know, Hidden Figures, the one that I could being my kids that are teenagers now into it and they get excited, oh, science is great. So the movie, how much will you be involved? You know, what can you share about that experience, too, so far? >> It's been, it's very surreal. That's the word is use to describe it, the honest, god's honest truth, I mean. I've been very lucky in that my representation in Hollywood is this rock-solid guy called Howie Sanders. And he's this bigger-than-life Hollywood agent guy. He's hooked me up, we've made a lot of business decisions that we're focused less on the money and more on the team, which is nice to be, like when you're in your 40s and you're more financially settled, you're not in the kind of situation where you might be in your 20s and just going to sign the first deal that people give you. So we really focused on hooking up with like the director, James Bovin is, you know, he's the guy who co-created Flight of the Concords. He did the Muppets movie, you know, Alice Through the Looking Glass. Really professional guy but also really understands the tone of the book, which is like humorous, you know, kind of sarcastic. It's not just about the technology. It's also about the characters. Same thing with the production team. The two producers, Mandeville Productions, I was just talking to Todd Lieberman, and we're talking about just what is augmented reality, like how does it look like on the screen? So I'm not- >> It's not going to look like Blade Runner is what I'm hearing. >> (laughs) I don't know. It's going to look real. I imagine, I don't know, they're going to make whatever movie they're going to make, but their perspective, one of the things we talked about is keeping the movie very grounded. Like you know, one of the big questions they ask first going into it is before we even had any sort of movie discussions is like is this more of like a Looper, Gattica, or District Nine, or is it more like The Fifth Element, you know, I mean, is it like, do you want it to be this sort of grounded movie that feels authentic and real and near future or do you want this to be like completely alien and weird and out of it. And the story is more grounded. So I think a lot, hopefully what we display on the screen will not feel that far away from reality. >> Okay, yeah. >> You do marketing in your day job. >> I do. >> I'm curious as you look at this, kind of the balance of educating, reaching a broad audience, you have passion for STEM, what's your thoughts around that? Is it, I worry there's so much general, like television or things like that, when I see the science stuff, it like makes me groan. Because you know, it's like I don't understand that. >> I am the worst, because I got a security background too, so that's the one I get scrambled on. The war, I mean, like. >> Wait, thank goodness I updated my firewall settings because I saved the world from terrorists. >> Hang on, we're breaking through the first firewall. Now we're through the second firewall. (laughing) Now we're going through the third firewall, like 15 firewalls. And let me upload the virus, like all that stuff. It's difficult for me. I think that, you know, hopefully, there's also a group in Hollywood called the Hollywood Science and Entertainment Exchange. And they're a group of scientists who work with film makers on, you know, reigning things in. And film makers don't usually take all their advice, i.e. Interstellar, (laughing) but you know, I think (laughing) in many cases there's some really good ideas that come to play into it that hopefully bring up, like I think Jarvis for example, in Iron Man or the Avengers is a really cool implementation of what the future of AI systems might be like. And I know they used the Hollywood Science Exchange to figure out how is that going to work? And I think the marketing aspect is, you know, the reason I came up with the idea for this book is because my CEO of a company I used to work for, he had this whole conversation about teleportation, like teleportation was impossible. And he's like, it's not because the science, yes, the science is a problem right now, but we'll get over it. The main issue is that nobody would ever step foot into a device that vaporizes them and then printed them out somewhere else. And I said, well that's great, cause that's a marketing problem. (laughing) >> Yeah, you're dead every time you do it. But it's the same you, I can't tell the difference. >> Well, you say you're dead, I'm saying you're just moving. (laughing) >> Artificial intelligence, you know, kind of a big gap between the hype to where we need to go. What's your thoughts on that space in general? >> I think that we have, it's a great question because I feel like that's a term that gets thrown around a lot, and I think as a result it's becoming watered down. So you've this sort of artificial intelligence that comes with like, you know, Google building an app that can beat the world's best Go player, which is a really, really difficult puzzle. The problem is, that app can do one thing, and that's play Go. You put in it a chess game, and it's like I don't know what's going on. >> It's a very specialized kind of intelligence, yeah. >> Now with Open AI, you know, they just had some pretty interesting implementations where they actually played video games with a real live competition and won. Again, you know, but without the smack talk, which really I think would add a lot. Now you got to get an AI to smack talk. So I think the problem is we haven't figured out a really good way of creating a general purpose AI. And there's a lot of parallels to the evolution of computing in general because if you look at how computers were before we had general purpose operating systems like Unix, every computer was built to do a very, very specific function, and that's kind of what AI is right now. So we're still waiting to have a sort of general purpose AI that can do a lot of specialized activities. >> Even most robots are still very single-purpose today. >> That's the fundamental problem. But you're seeing the Cambridge guys are working on sort of the bipedal robot that can do lots of things. And Siri's getting better, Cortana's getting better, Watson's getting better, but we're not there. We still need to find a really good way of integrating deep knowledge with general purpose conversational AI. Cause that's really what you need to like, Stu, what do you need? Here, let me give it to you, you know? >> Do you draw a distinction between AI that's able to simply sort of react as a fairly complex machine or something that can create new things and add something? >> That's in the book as well. So the fundamental thing that I don't think we get around even in the future is giving computers the ability to actually come up with new ideas. There's actually a career, the main job of the protagonist in the book, his job is a salter. And his job is to salt AI algorithms to introduce entropy so they can come up with new ideas. >> Okay, interesting. >> So based off the sort of chaos theory. >> Like chaos monkey, right? >> Yeah. And that's really what you're trying to do is like, okay, react to things that are happening because you can't just come up with them on their own. There's a whole, I don't want to bore you, but there's a whole bunch of stuff in the book about how that works. >> It's like hand-carving ideas that are then mass produced by machines. >> Yeah, I don't know if you guys are going to have Simon Crosby on here, he's kind of like an expert on that. He was the Dean of Kings College, which is where Turing came from. So he really knows a lot about that. He's got a lot of strong ideas about it. But I learned a lot from him in that regard. There's a lot of like, the snarky spirit of Simon Crosby lives on in my book somewhere. But he's just funny cause he's, coming from that field, he immediately sees a lot of BS right off the bat, whenever anybody's presenting. He's got like the ability to just cut through it. Because he understands what it would actually take to make that happen, you know? So I tried to preserve some of that in the book. >> That is refreshing in the tech industry. >> So Tal, I need to let you, you know, wrap this up. Give us a plug for the book, tell us, when are we going to be able to see this on the big screen? >> I don't know about the big screen, but the Punch Escrow is now available. You can get it on Amazon, Barnes and Noble, anywhere books are sold. It's been optioned by Lionsgate. The director attached to it is James Bovin, production team is Mandeville Productions. I'm very excited about it. Go check it out. It's a pretty quick read, reads like a technothriller. It's not too hard. And it's fun for the whole family. I think one of the coolest things about it is that the feedback I've been getting has been that it really is appealing to everybody. I've got mother-in-laws reading it, you know, it's pretty cool. Initially I sold it, my initial audience is like us, but it's kind of cool, like, Stu will finish the book, he'll give it to, you know, wife, daughter, anything, and they're really digging it. So it's kind of fun. >> Justin: Thanks a lot. >> Tal Klein, really appreciate you coming. Congratulations on the book, we look forward to the movie. Maybe, you know, we'll get the Cube involved down the road. (laughing) >> And we're giving away 75 copies of it here at Lakeside booth, if you guys want to come. >> Tal Klein, author of The Punch Escrow, also CMO of Lakeside, who is here in the thing. But yeah, (laughing) a lot of stuff. Justin and I will be back with more coverage here from VMWorld 2017. You're watching the Cube. (bright music)