>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Barcelona, Spain, everyone. It's theCUBE live at MWC '23, day three of four days of CUBE coverage. It's like a cannon of CUBE content coming right at you. I'm Lisa Martin with Dave Nicholson. We've got Dell and VMware here. Going to be talking about the ecosystem partnerships and what they're doing to further organizations in the telco industry. Please welcome Jared Woodrey, Director of Partner Engineering Open Telecom Ecosystem Lab, OTEL. Odded Solomon is here as well, Director of Product Management, VMware Service Provider and Edge Business Unit at VMware. Guys, great to have you on the program. >> Thank you for having me. >> Welcome to theCUBE. So Jared, first question for you. Talk about OTEL. I know there's a big announcement this week, but give the audience context and understanding of what OTEL is and how it works. >> Sure. So the Open Telecom Ecosystem Lab is physically located at Round Rock, Texas, it's the heart and soul of it. But this week we also just announced opening up the Cork, Ireland extension of OTEL. The reason for our existence is to to try and make it as easy as possible for both partners and customers to come together and to re-aggregate this disaggregated ecosystem. So that comes with a number of automation tools and basically just giving a known good testing environment so that tests that happen in our lab are as close to real world as they possibly can be and make it as transparent and open as possible for both partners like VMware as well as customers. >> Odded, talk about what you're doing with Dell and OTEL and give us a customer example of maybe one that you're working with or even even mentioning it by a high level descriptor if you have to. >> Yeah. So we provide a telco cloud platform, which is essentially a vertical in VMware. The telco cloud platform is serving network function vendors, such as Ericsson, Nokia, Mavenir, and so on. What we do with Dell as part of this partnership is essentially complementing the platform with some additional functionality that is not coming out of the box. We used to have a data protection in the past, but this is no longer our main business focus. So we do provide APIs that we can expose and work together with Dell PPDM solution so customer can benefit from this and leverage the partnership and have overall solution that is not coming out of the box from VMware. >> I'm curious, from a VMware perspective. VMware is associated often with the V in VMware, virtualization, and we've seen a transition over time between sort of flavors of virtualization and what is the mix currently today in the telecom space between environments that are leveraging what we would think of as more traditional virtualization with full blown Linux, Windows operating systems in a VM versus the world of containerized microservices? What does that mix look like today? Where do you see it going? >> Yeah, so the VMware telco cloud platform exists for about eight years. And the V started around that time. You might heard about open stack in addition to VMware. So this has definitely helped the network equipment providers with virtualizing their network functions. Those are typically VNF, virtualized network functions, inside the VMs. Essentially we have 4G applications, so core applications, EPC, we have IMS. Those are typically, I would say maybe 80 or 90% of the ecosystem right now. 5G is associated with cloud native network functions. So 5G is getting started now, getting deployed. There is an exponential growth on the core side. Now, when we expand towards the edge of the network we see more potential growth. This is 5G ran, we see the vRAN, we see the open RAN, we see early POCs, we see field trials that are starting. We obviously has production customer now. You just spoke to one. So this is really starting, cloud native is really starting I would say about 10 to 20% of the network functions these days are cloud native. >> Jared, question for you. You mentioned data protection, a huge topic there obviously from a security perspective. Data protection used to be the responsibility of the CSPs. You guys are changing that. Can you talk a little bit about how you're doing that and what Dell's play there is? >> Yeah, so PowerProtect Data Management is a product, but it's produced by Dell. So what this does is it enables data protection over virtual cloud as well as the physical infrastructure of specifically in this case of a telecoms ecosystem. So what this does is enables an ability to rapidly redeploy and back up existing configurations all the way up to the TCP and TCA that pulls the basis of our work here with VMware. >> So you've offloaded that responsibility from the CSPs. You freed them from that. >> So the work that we did, honestly was to make sure that we have a very clear and concise and accurate procedures for how to conduct this as well. And to put this through a realistic and real world as if it was in a telecoms own production network, what did that would actually look like, and what it would take to bring it back up as well. So our responsibility is to make sure that when we when we provide these products to the customers that not only do they work exactly as their intended to, but there is also documentation to help support them and to enable them to have their exact specifications met by as well. >> Got it. So talk about a little bit about OTEL expansion into Cork. What you guys are doing together to enable CSPs here in EMEA? >> Yeah, so the reason why we opened up a facility in Cork Island was to give, for an EMEA audience, for an EMEA CSPs and ability to look and feel and touch some of the products that we're working on. It also just facilitates and ease especially for European-based partners to have a chance to very easily come to a lab environment. The difference though, honestly, is the between Round Rock, Texas and Cork Island is that it's virtually an extension of the same thing. Like the physical locations can make it easier to provide access and obviously to showcase the products that we've developed with partners. But the reality is that it's more than just the physical location. It's more about the ability and ease by which customers and partners can access the labs. >> So we should be expecting a lot of Tito's vodka to be consumed in Cork at some point. Might change the national beverage. >> We do need to have some international exchange. >> Yeah, no, that's good to know. Odded, on the VMware side of things. There's a large group of folks who have VMware skillsets. >> Odded: Correct. >> The telecom industry is moving into this world of the kind of agility that those folks are familiar with. How do people come out of the traditional VMware virtualization world and move into that world of cloud native applications and serve the telecom space? What would your recommendation be? If you were speaking at a VMUG, a VMware Users Group meeting with all of your telecom background, what would you share with them that's critical to understand about how telecom is different, or how telecom's spot in its evolution might be different than the traditional IT space? >> So we're talking about the people with the knowledge and the background of. >> Yeah, I'm a V expert, let's say. And I'm looking into the future and I hear that there are 80,000 people in Barcelona at this event, and I hear that Dell is building optimized infrastructure specifically for telecom, and that VMware is involved. And I'm an expert in VMware and I want to be involved. What do I need to do? I know it's a little bit outside of the box question, but especially against the backdrop of economic headwinds globally, there are a lot of people facing transitions. What are your thoughts there? >> So, first of all, we understand the telco requirements, we understand the telco needs, and we make sure that what we learn from the customers, what we learn from the partners is being built into the VMware products. And simplicity is number one thing that is important for us. We want the customer experience, we want the user experience to be the same as they know even though we are transitioning into cloud native networks that require more frequent upgrades and they have more complexity to be honest. And what we do in our vertical inside VMware we are focusing on automation, telco cloud automation, telco cloud service assurance. Think of it as a wrapper around the SDDC stack that we have from VMware that really simplifies the operations for the telcos because it's really a challenge about skillset. You need to be a DevOps, SRE in order to operate these networks. And things are becoming really complex. We simplify it for them with the same VMware experience. We have a very good ability to do that. We sell products in VMware. Unlike our competition that is mostly selling professional services and support, we try to focus more on the products and delivering the value. Of course, we have services offering because telcos requires some customizations, but we do focus on automation simplicity throughout our staff. >> So just follow up. So in other words the investment in education in this VMware ecosystem absolutely can be extended and applied into the telecom world. I think it's an important thing. >> I was going to add to that. Our engagement in OTEL was also something that we created a solutions brief whether we released from Mobile World Congress this week. But in conjunction with that, we also have a white paper coming out that has a much more expansive explanation and documentation of what it was that we accomplished in the work that we've done together. And that's not something that is going to be a one-off thing. This is something that will stay evergreen that we'll continue to expand both the testing scope as well as the documentation for what this solution looks like and how it can be used as well as documentation on for the V experts for how they can then leverage and realize the the potential for what we're creating together. >> Jared, does Dell look at OTEL as having the potential to facilitate the continued evolution of the actual telco industry? And if so, how? >> Well, I mean, it would be a horrible answer if I were to say no to that. >> Right. >> I think, I honestly believe that one of the most difficult things about this idea of having desired ecosystem is not just trying to put it back together, but then also how to give yourself choice. So each time that you build one of those solution sets like that exists as an island out of all the other possibilities that comes with it. And OTEL seeks to not just be able to facilitate building that first solution set. Like that's what solutions engineering can do. And that's generally done relatively protected and internally. The Open Telecom Ecosystem seeks to build that then to also provide the ability to very easily change specific components of that whether that's a hardware component, a NIC, whether a security pass just came out or a change in either TCP or TCA or we talked a little bit about for this specific engagement that it was done on TCP 2.5. >> Odded: Correct. >> Obviously there's already a 2.7 and 3.0 is coming out. It's not like we're going to sit around and write our coattails of what 2.7 has happened. So this isn't intended to be a one and done thing. So when we talk about trying to make that easier and simpler and de-risk all of the risk that comes from trying to put all these things together, it's not just the the one single solution that you built in the lab. It's what's the next one? And how do I optimize this? And I have specific requirements as a CSP, how can I take something you built that doesn't quite match it, but how do I make that adjustment? So that's what we see to do and make it as easy and as painless as possible. >> What's the engagement model with CSPs? Is it led by Dell only, VMware partner? How does that work? >> Yeah, I can take that. So that depends on the customer, but typically customers they want to choose the cloud vendor. So they come to VMware, we want VMware. Typically, they come from the IT side. They said, "Oh, we want to manage the network side of the house the same way as we manage the IT. We don't want to have special skill sets, special teams." So they move from the IT to the network side and they want VMware there. And then obviously they have an RSP process and they have hardware choices. They can go with Dell, they can go with others. We leverage vSphere, other compatibility. So we can be flexible with the customer choice. And then depending on which customer, how large they are, they select the network equipment provider that the runs on top. We position our platform as multi-vendor. So many of them choose multiple network functions providers. So we work with Dell. So assuming that the customer is choosing Dell. We work very closely with them, offering the best solution for the customer. We work with them sometimes to even design the boxes to make sure that it fits their use cases and to make sure that it works properly. So we have a partnership validation certification end-to-end from the applications all the way down to the hardware. >> It's a fascinating place in history to be right now with 5G. Something that a lot of consumers sort of assume. It's like, "Oh, hey, yeah, we're already there. What's the 6G thing going to look like?" Well, wait a minute, we're just at the beginning stages. And so you talk about disaggregation, re-aggregation, or reintegration, the importance of that. Folks like Dell have experience in that space. Folks at VMware have a lot of experience in the virtualization space, but I heard that VMware is being acquired by Broadcom, if it all goes through, of course. You don't need to comment on it. But you mentioned something, SDDC, software-defined data center. That stack is sometimes misunderstood by the public at large and maybe the folks in the EU, I will editorialize for a moment here. It is eliminating capture in a way by larger hyperscale cloud providers. It absolutely introduces more competition into the market space. So it's interesting to hear Broadcom acknowledging that this is part of the future of VMware, no matter what else happens. These capabilities that spill into the telecom space are something that they say they're going to embrace and extend. I think that's important for anyone who's evaluating this if they're concern. Well, wait a minute. Yeah, when I reintegrate, do I want VMware as part of this mix? Is that an unknown? It's pretty clear that that's something that is part of the future of VMware moving forward. That's my personal opinion based on analysis. But you brought up SDDC, so I wanted to mention that. Again, I'm not going to ask you to get into trouble on that at all. What should we be, from a broad perspective, are there any services, outcomes that are going to come out of all of this work? The agility that's being built by you folks and folks in the open world. Are there any specific things that you personally are excited about? Or when we think about consumer devices, getting data, what are the other kinds of things that this facilitates? Anything cool, either one of you. >> So specific use cases? >> Yeah, anything. It's got to be cool though. If it's not cool we're going to ask you to leave. >> All right. I'll take that challenge. (laughs) I think one of the things that is interesting for something like OTEL as an exist, as being an Open Telecom Ecosystem, there are going to be some CSPs that it's very difficult for them to have this optionality existing for themselves. Especially when you start talking about tailoring it for specific CSPs and their needs. One of the things that becomes much more available to some of the smaller CSPs is the ability to leverage OTEL and basically act as one of their pre-production labs. So this would be something that would be very specific to a customer and we would obviously make sure that it's completely isolated but the intention there would be that it would open up the ability for what would normally take a much longer time period for them to receive some of the benefits of some of the changes that are happening within the industry. But they would have immediate benefit by leveraging specifically looking OTEL to provide them some of their solutions. And I know that you were also looking for specific use cases out of it, but like that's a huge deal for a lot of CSPs around the world that don't have the ability to lay out all the different permutations that they are most interested in and start to put each one of those through a test cycle. A specific use cases for what this looks like is honestly the most exciting that I've seen for right now is on the private 5G networks. Specifically within mining industry, we have a, sorry for the audience, but we have a demo at our booth that starts to lay out exactly how it was deployed and kind of the AB of what this looked like before the world of private 5G for this mining company and what it looks like afterwards. And the ability for both safety, as well as operational costs, as well as their ability to obviously do their job better is night and day. It completely opened up a very analog system and opened up to a very digitalized system. And I would be remiss, I didn't also mention OpenBrew, which is also an example in our booth. >> We saw it last night in action. >> We saw it. >> I hope you did. So OpenBrew is small brewery in Northeast America and we basically took a very manual process of checking temperature and pressure on multiple different tanks along the entire brewing process and digitized everything for them. All of that was enabled by a private 5G deployment that's built on Dell hardware. >> You asked for cool. I think we got it. >> Yeah, it's cool. >> Jared: I think beer. >> Cool brew, yes. >> Root beer, I think is trump card there. >> At least for folks from North America, we like our brew cool. >> Exactly. Guys, thank you so much for joining Dave and me talking about what Dell, OTEL, and VMware are doing together, what you're enabling CSPs to do and achieve. We appreciate your time and your insights. >> Absolutely. >> Thank you. >> All right, our pleasure. For our guests and for Dave Nicholson, I'm Lisa Martin. You watching theCUBE live from MWC '23. Day three of our coverage continues right after a short break. (upbeat music)

(gentle music) >> Okay, welcome back to Supercloud 2, live here in Palo Alto, California for our live stage performance. Supercloud 2 is our second Supercloud event. We're going to get these out as fast as we can every couple months. It's our second one, you'll see two and three this year. I'm John Furrier, my co-host, Dave Vellante. A panel here to break down the Supercloud momentum, the wave, and the developer impact that we bringing back Vittorio Viarengo, who's a VP for Cross-Cloud Services at VMware. Sarbjeet Johal, industry influencer and Analyst at StackPayne, his company, Cube alumni and Influencer. Sarbjeet, great to see you. Vittorio, thanks for coming back. >> Nice to be here. >> My pleasure. >> Vittorio, you just gave a keynote where we unpacked the cross-cloud services, what VMware is doing, how you guys see it, not just from VMware's perspective, but VMware looking out broadly at the industry and developers came up and you were like, "Developers, developer, developers", kind of a goof on the Steve Ballmer famous meme that everyone's seen. This is a huge star, sorry, I mean a big piece of it. The developers are the canary in the coal mines. They're the ones who are being asked to code the digital transformation, which is fully business transformation and with the market the way it is right now in terms of the accelerated technology, every enterprise grade business model's changing. The technology is evolving, the builders are kind of, they want go faster. I'm saying they're stuck in a way, but that's my opinion, but there's a lot of growth. >> Yeah. >> The impact, they got to get released up and let it go. Those developers need to accelerate faster. It's been a big part of productivity, and the conversations we've had. So developer impact is huge in Supercloud. What's your, what do you guys think about this? We'll start with you, Sarbjeet. >> Yeah, actually, developers are the masons of the digital empires I call 'em, right? They lay every brick and build all these big empires. On the left side of the SDLC, or the, you know, when you look at the system operations, developer is number one cost from economic side of things, and from technology side of things, they are tech hungry people. They are developers for that reason because developer nights are long, hours are long, they forget about when to eat, you know, like, I've been a developer, I still code. So you want to keep them happy, you want to hug your developers. We always say that, right? Vittorio said that right earlier. The key is to, in this context, in the Supercloud context, is that developers don't mind mucking around with platforms or APIs or new languages, but they hate the infrastructure part. That's a fact. They don't want to muck around with servers. It's friction for them, it is like they don't want to muck around even with the VMs. So they want the programmability to the nth degree. They want to automate everything, so that's how they think and cloud is the programmable infrastructure, industrialization of infrastructure in many ways. So they are happy with where we are going, and we need more abstraction layers for some developers. By the way, I have this sort of thinking frame for last year or so, not all developers are same, right? So if you are a developer at an ISV, you behave differently. If you are a developer at a typical enterprise, you behave differently or you are forced to behave differently because you're not writing software.- >> Well, developers, developers have changed, I mean, Vittorio, you and I were talking earlier on the keynote, and this is kind of the key point is what is a developer these days? If everything is software enabled, I mean, even hardware interviews we do with Nvidia, and Amazon and other people building silicon, they all say the same thing, "It's software on a chip." So you're seeing the role of software up and down the stack and the role of the stack is changing. The old days of full stack developer, what does that even mean? I mean, the cloud is a half a stack kind of right there. So, you know, developers are certainly more agile, but cloud native, I mean VMware is epitome of operations, IT operations, and the Tan Zoo initiative, you guys started, you went after the developers to look at them, and ask them questions, "What do you need?", "How do you transform the Ops from virtualization?" Again, back to your point, so this hardware abstraction, what is software, what is cloud native? It's kind of messy equation these days. How do you guys grokel with that? >> I would argue that developers don't want the Supercloud. I dropped that up there, so, >> Dave: Why not? >> Because developers, they, once they get comfortable in AWS or Google, because they're doing some AI stuff, which is, you know, very trendy right now, or they are in IBM, any of the IPA scaler, professional developers, system developers, they love that stuff, right? Yeah, they don't, the infrastructure gets in the way, but they're just, the problem is, and I think the Supercloud should be driven by the operators because as we discussed, the operators have been left behind because they're busy with day-to-day jobs, and in most cases IT is centralized, developers are in the business units. >> John: Yeah. >> Right? So they get the mandate from the top, say, "Our bank, they're competing against". They gave teenagers or like young people the ability to do all these new things online, and Venmo and all this integration, where are we? "Oh yeah, we can do it", and then build it, and then deploy it, "Okay, we caught up." but now the operators are back in the private cloud trying to keep the backend system running and so I think the Supercloud is needed for the primarily, initially, for the operators to get in front of the developers, fit in the workflow, but lay the foundation so it is secure.- >> So, so I love this thinking because I love the rift, because the rift points to what is the target audience for the value proposition and if you're a developer, Supercloud enables you so you shouldn't have to deal with Supercloud. >> Exactly. >> What you're saying is get the operating environment or operating system done properly, whether it's architecture, building the platform, this comes back to architecture platform conversations. What is the future platform? Is it a vendor supplied or is it customer created platform? >> Dave: So developers want best to breed, is what you just said. >> Vittorio: Yeah. >> Right and operators, they, 'cause developers don't want to deal with governance, they don't want to deal with security, >> No. >> They don't want to deal with spinning up infrastructure. That's the role of the operator, but that's where Supercloud enables, to John's point, the developer, so to your question, is it a platform where the platform vendor is responsible for the architecture, or there is it an architectural standard that spans multiple clouds that has to emerge? Based on what you just presented earlier, Vittorio, you are the determinant of the architecture. It's got to be open, but you guys determine that, whereas the nirvana is, "Oh no, it's all open, and it just kind of works." >> Yeah, so first of all, let's all level set on one thing. You cannot tell developers what to do. >> Dave: Right, great >> At least great developers, right? Cannot tell them what to do. >> Dave: So that's what, that's the way I want to sort of, >> You can tell 'em what's possible. >> There's a bottle on that >> If you tell 'em what's possible, they'll test it, they'll look at it, but if you try to jam it down their throat, >> Yeah. >> Dave: You can't tell 'em how to do it, just like your point >> Let me answer your answer the question. >> Yeah, yeah. >> So I think we need to build an architect, help them build an architecture, but it cannot be proprietary, has to be built on what works in the cloud and so what works in the cloud today is Kubernetes, is you know, number of different open source project that you need to enable and then provide, use this, but when I first got exposed to Kubernetes, I said, "Hallelujah!" We had a runtime that works the same everywhere only to realize there are 12 different distributions. So that's where we come in, right? And other vendors come in to say, "Hey, no, we can make them all look the same. So you still use Kubernetes, but we give you a place to build, to set those operation policy once so that you don't create friction for the developers because that's the last thing you want to do." >> Yeah, actually, coming back to the same point, not all developers are same, right? So if you're ISV developer, you want to go to the lowest sort of level of the infrastructure and you want to shave off the milliseconds from to get that performance, right? If you're working at AWS, you are doing that. If you're working at scale at Facebook, you're doing that. At Twitter, you're doing that, but when you go to DMV and Kansas City, you're not doing that, right? So your developers are different in nature. They are given certain parameters to work with, certain sort of constraints on the budget side. They are educated at a different level as well. Like they don't go to that end of the degree of sort of automation, if you will. So you cannot have the broad stroking of developers. We are talking about a citizen developer these days. That's a extreme low, >> You mean Low-Code. >> Yeah, Low-Code, No-code, yeah, on the extreme side. On one side, that's citizen developers. On the left side is the professional developers, when you say developers, your mind goes to the professional developers, like the hardcore developers, they love the flexibility, you know, >> John: Well app, developers too, I mean. >> App developers, yeah. >> You're right a lot of, >> Sarbjeet: Infrastructure platform developers, app developers, yes. >> But there are a lot of customers, its a spectrum, you're saying. >> Yes, it's a spectrum >> There's a lot of customers don't want deal with that muck. >> Yeah. >> You know, like you said, AWS, Twitter, the sophisticated developers do, but there's a whole suite of developers out there >> Yeah >> That just want tools that are abstracted. >> Within a company, within a company. Like how I see the Supercloud is there shouldn't be anything which blocks the developers, like their view of the world, of the future. Like if you're blocked as a developer, like something comes in front of you, you are not developer anymore, believe me, (John laughing) so you'll go somewhere else >> John: First of all, I'm, >> You'll leave the company by the way. >> Dave: Yeah, you got to quit >> Yeah, you will quit, you will go where the action is, where there's no sort of blockage there. So like if you put in front of them like a huge amount of a distraction, they don't like it, so they don't, >> Well, the idea of a developer, >> Coming back to that >> Let's get into 'cause you mentioned platform. Get year in the term platform engineering now. >> Yeah. >> Platform developer. You know, I remember back in, and I think there's still a term used today, but when I graduated my computer science degree, we were called "Software engineers," right? Do people use that term "Software engineering", or is it "Software development", or they the same, are they different? >> Well, >> I think there's a, >> So, who's engineering what? Are they engineering or are they developing? Or both? Well, I think it the, you made a great point. There is a factor of, I had the, I was blessed to work with Adam Bosworth, that is the guy that created some of the abstraction layer, like Visual Basic and Microsoft Access and he had so, he made his whole career thinking about this layer, and he always talk about the professional developers, the developers that, you know, give him a user manual, maybe just go at the APIs, he'll build anything, right, from system engine, go down there, and then through obstruction, you get the more the procedural logic type of engineers, the people that used to be able to write procedural logic and visual basic and so on and so forth. I think those developers right now are a little cut out of the picture. There's some No-code, Low-Code environment that are maybe gain some traction, I caught up with Adam Bosworth two weeks ago in New York and I asked him "What's happening to this higher level developers?" and you know what he is told me, and he is always a little bit out there, so I'm going to use his thought process here. He says, "ChapGPT", I mean, they will get to a point where this high level procedural logic will be written by, >> John: Computers. >> Computers, and so we may not need as many at the high level, but we still need the engineers down there. The point is the operation needs to get in front of them >> But, wait, wait, you seen the ChatGPT meme, I dunno if it's a Dilbert thing where it's like, "Time to tic" >> Yeah, yeah, yeah, I did that >> "Time to develop the code >> Five minutes, time to decode", you know, to debug the codes like five hours. So you know, the whole equation >> Well, this ChatGPT is a hot wave, everyone's been talking about it because I think it illustrates something that's NextGen, feels NextGen, and it's just getting started so it's going to get better. I mean people are throwing stones at it, but I think it's amazing. It's the equivalent of me seeing the browser for the first time, you know, like, "Wow, this is really compelling." This is game-changing, it's not just keyword chat bots. It's like this is real, this is next level, and I think the Supercloud wave that people are getting behind points to that and I think the question of Ops and Dev comes up because I think if you limit the infrastructure opportunity for a developer, I think they're going to be handicapped. I mean that's a general, my opinion, the thesis is you give more aperture to developers, more choice, more capabilities, more good things could happen, policy, and that's why you're seeing the convergence of networking people, virtualization talent, operational talent, get into the conversation because I think it's an infrastructure engineering opportunity. I think this is a seminal moment in a new stack that's emerging from an infrastructure, software virtualization, low-code, no-code layer that will be completely programmable by things like the next Chat GPT or something different, but yet still the mechanics and the plumbing will still need engineering. >> Sarbjeet: Oh yeah. >> So there's still going to be more stuff coming on. >> Yeah, we have, with the cloud, we have made the infrastructure programmable and you give the programmability to the programmer, they will be very creative with that and so we are being very creative with our infrastructure now and on top of that, we are being very creative with the silicone now, right? So we talk about that. That's part of it, by the way. So you write the code to the particle's silicone now, and on the flip side, the silicone is built for certain use cases for AI Inference and all that. >> You saw this at CES? >> Yeah, I saw at CES, the scenario is this, the Bosch, I spoke to Bosch, I spoke to John Deere, I spoke to AWS guys, >> Yeah. >> They were showcasing their technology there and I was spoke to Azure guys as well. So the Bosch is a good example. So they are building, they are right now using AWS. I have that interview on camera, I will put it some sometime later on there online. So they're using AWS on the back end now, but Bosch is the number one, number one or number two depending on what day it is of the year, supplier of the componentry to the auto industry, and they are creating a platform for our auto industry, so is Qualcomm actually by the way, with the Snapdragon. So they told me that customers, their customers, BMW, Audi, all the manufacturers, they demand the diversity of the backend. Like they don't want all, they, all of them don't want to go to AWS. So they want the choice on the backend. So whatever they cook in the middle has to work, they have to sprinkle the data for the data sovereign side because they have Chinese car makers as well, and for, you know, for other reasons, competitive reasons and like use. >> People don't go to, aw, people don't go to AWS either for political reasons or like competitive reasons or specific use cases, but for the most part, generally, I haven't met anyone who hasn't gone first choice with either, but that's me personally. >> No, but they're building. >> Point is the developer wants choice at the back end is what I'm hearing, but then finish that thought. >> Their developers want the choice, they want the choice on the back end, number one, because the customers are asking for, in this case, the customers are asking for it, right? But the customers requirements actually drive, their economics drives that decision making, right? So in the middle they have to, they're forced to cook up some solution which is vendor neutral on the backend or multicloud in nature. So >> Yeah, >> Every >> I mean I think that's nirvana. I don't think, I personally don't see that happening right now. I mean, I don't see the parody with clouds. So I think that's a challenge. I mean, >> Yeah, true. >> I mean the fact of the matter is if the development teams get fragmented, we had this chat with Kit Colbert last time, I think he's going to come on and I think he's going to talk about his keynote in a few, in an hour or so, development teams is this, the cloud is heterogenous, which is great. It's complex, which is challenging. You need skilled engineering to manage these clouds. So if you're a CIO and you go all in on AWS, it's hard. Then to then go out and say, "I want to be completely multi-vendor neutral" that's a tall order on many levels and this is the multicloud challenge, right? So, the question is, what's the strategy for me, the CIO or CISO, what do I do? I mean, to me, I would go all in on one and start getting hedges and start playing and then look at some >> Crystal clear. Crystal clear to me. >> Go ahead. >> If you're a CIO today, you have to build a platform engineering team, no question. 'Cause if we agree that we cannot tell the great developers what to do, we have to create a platform engineering team that using pieces of the Supercloud can build, and let's make this very pragmatic and give examples. First you need to be able to lay down the run time, okay? So you need a way to deploy multiple different Kubernetes environment in depending on the cloud. Okay, now we got that. The second part >> That's like table stakes. >> That are table stake, right? But now what is the advantage of having a Supercloud service to do that is that now you can put a policy in one place and it gets distributed everywhere consistently. So for example, you want to say, "If anybody in this organization across all these different buildings, all these developers don't even know, build a PCI compliant microservice, They can only talk to PCI compliant microservice." Now, I sleep tight. The developers still do that. Of course they're going to get their hands slapped if they don't encrypt some messages and say, "Oh, that should have been encrypted." So number one. The second thing I want to be able to say, "This service that this developer built over there better satisfy this SLA." So if the SLA is not satisfied, boom, I automatically spin up multiple instances to certify the SLA. Developers unencumbered, they don't even know. So this for me is like, CIO build a platform engineering team using one of the many Supercloud services that allow you to do that and lay down. >> And part of that is that the vendor behavior is such, 'cause the incentive is that they don't necessarily always work together. (John chuckling) I'll give you an example, we're going to hear today from Western Union. They're AWS shop, but they want to go to Google, they want to use some of Google's AI tools 'cause they're good and maybe they're even arguably better, but they're also a Snowflake customer and what you'll hear from them is Amazon and Snowflake are working together so that SageMaker can be integrated with Snowflake but Google said, "No, you want to use our AI tools, you got to use BigQuery." >> Yeah. >> Okay. So they say, "Ah, forget it." So if you have a platform engineering team, you can maybe solve some of that vendor friction and get competitive advantage. >> I think that the future proximity concept that I talk about is like, when you're doing one thing, you want to do another thing. Where do you go to get that thing, right? So that is very important. Like your question, John, is that your point is that AWS is ahead of the pack, which is true, right? They have the >> breadth of >> Infrastructure by a lot >> infrastructure service, right? They breadth of services, right? So, how do you, When do you bring in other cloud providers, right? So I believe that you should standardize on one cloud provider, like that's your primary, and for others, bring them in on as needed basis, in the subsection or sub portfolio of your applications or your platforms, what ever you can. >> So yeah, the Google AI example >> Yeah, I mean, >> Or the Microsoft collaboration software example. I mean there's always or the M and A. >> Yeah, but- >> You're going to get to run Windows, you can run Windows on Amazon, so. >> By the way, Supercloud doesn't mean that you cannot do that. So the perfect example is say that you're using Azure because you have a SQL server intensive workload. >> Yep >> And you're using Google for ML, great. If you are using some differentiated feature of this cloud, you'll have to go somewhere and configure this widget, but what you can abstract with the Supercloud is the lifecycle manage of the service that runs on top, right? So how does the service get deployed, right? How do you monitor performance? How do you lifecycle it? How you secure it that you can abstract and that's the value and eventually value will win. So the customers will find what is the values, obstructing in making it uniform or going deeper? >> How about identity? Like take identity for instance, you know, that's an opportunity to abstract. Whether I use Microsoft Identity or Okta, and I can abstract that. >> Yeah, and then we have APIs and standards that we can use so eventually I think where there is enough pain, the right open source will emerge to solve that problem. >> Dave: Yeah, I can use abstract things like object store, right? That's pretty simple. >> But back to the engineering question though, is that developers, developers, developers, one thing about developers psychology is if something's not right, they say, "Go get fixing. I'm not touching it until you fix it." They're very sticky about, if something's not working, they're not going to do it again, right? So you got to get it right for developers. I mean, they'll maybe tolerate something new, but is the "juice worth the squeeze" as they say, right? So you can't go to direct say, "Hey, it's, what's a work in progress? We're going to get our infrastructure together and the world's going to be great for you, but just hang tight." They're going to be like, "Get your shit together then talk to me." So I think that to me is the question. It's an Ops question, but where's that value for the developer in Supercloud where the capabilities are there, there's less friction, it's simpler, it solves the complexity problem. I don't need these high skilled labor to manage Amazon. I got services exposed. >> That's what we talked about earlier. It's like the Walmart example. They basically, they took away from the developer the need to spin up infrastructure and worry about all the governance. I mean, it's not completely there yet. So the developer could focus on what he or she wanted to do. >> But there's a big, like in our industry, there's a big sort of flaw or the contention between developers and operators. Developers want to be on the cutting edge, right? And operators want to be on the stability, you know, like we want governance. >> Yeah, totally. >> Right, so they want to control, developers are like these little bratty kids, right? And they want Legos, like they want toys, right? Some of them want toys by way. They want Legos, they want to build there and they want make a mess out of it. So you got to make sure. My number one advice in this context is that do it up your application portfolio and, or your platform portfolio if you are an ISV, right? So if you are ISV you most probably, you're building a platform these days, do it up in a way that you can say this portion of our applications and our platform will adhere to what you are saying, standardization, you know, like Kubernetes, like slam dunk, you know, it works across clouds and in your data center hybrid, you know, whole nine yards, but there is some subset on the next door systems of innovation. Everybody has, it doesn't matter if you're DMV of Kansas or you are, you know, metaverse, right? Or Meta company, right, which is Facebook, they have it, they are building something new. For that, give them some freedom to choose different things like play with non-standard things. So that is the mantra for moving forward, for any enterprise. >> Do you think developers are happy with the infrastructure now or are they wanting people to get their act together? I mean, what's your reaction, or you think. >> Developers are happy as long as they can do their stuff, which is running code. They want to write code and innovate. So to me, when Ballmer said, "Developer, develop, Developer, what he meant was, all you other people get your act together so these developers can do their thing, and to me the Supercloud is the way for IT to get there and let developer be creative and go fast. Why not, without getting in trouble. >> Okay, let's wrap up this segment with a super clip. Okay, we're going to do a sound bite that we're going to make into a short video for each of you >> All right >> On you guys summarizing why Supercloud's important, why this next wave is relevant for the practitioners, for the industry and we'll turn this into an Instagram reel, YouTube short. So we'll call it a "Super clip. >> Alright, >> Sarbjeet, you want, you want some time to think about it? You want to go first? Vittorio, you want. >> I just didn't mind. (all laughing) >> No, okay, okay. >> I'll do it again. >> Go back. No, we got a fresh one. We'll going to already got that one in the can. >> I'll go. >> Sarbjeet, you go first. >> I'll go >> What's your super clip? >> In software systems, abstraction is your friend. I always say that. Abstraction is your friend, even if you're super professional developer, abstraction is your friend. We saw from the MFC library from C++ days till today. Abstract, use abstraction. Do not try to reinvent what's already being invented. Leverage cloud, leverage the platform side of the cloud. Not just infrastructure service, but platform as a service side of the cloud as well, and Supercloud is a meta platform built on top of these infrastructure services from three or four or five cloud providers. So use that and embrace the programmability, embrace the abstraction layer. That's the key actually, and developers who are true developers or professional developers as you said, they know that. >> Awesome. Great super clip. Vittorio, another shot at the plate here for super clip. Go. >> Multicloud is awesome. There's a reason why multicloud happened, is because gave our developers the ability to innovate fast and ever before. So if you are embarking on a digital transformation journey, which I call a survival journey, if you're not innovating and transforming, you're not going to be around in business three, five years from now. You have to adopt the Supercloud so the developer can be developer and keep building great, innovating digital experiences for your customers and IT can get in front of it and not get in trouble together. >> Building those super apps with Supercloud. That was a great super clip. Vittorio, thank you for sharing. >> Thanks guys. >> Sarbjeet, thanks for coming on talking about the developer impact Supercloud 2. On our next segment, coming up right now, we're going to hear from Walmart enterprise architect, how they are building and they are continuing to innovate, to build their own Supercloud. Really informative, instructive from a practitioner doing it in real time. Be right back with Walmart here in Palo Alto. Thanks for watching. (gentle 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)

Hello and welcome back to Supercloud 2 where we examine the intersection of cloud and data in the 2020s. My name is Dave Vellante. Our Supercloud panel, our power panel is back. Maribel Lopez is the founder and principal analyst at Lopez Research. Sanjeev Mohan is former Gartner analyst and principal at Sanjeev Mohan. And Keith Townsend is the CTO advisor. Folks, welcome back and thanks for your participation today. Good to see you. >> Okay, great. >> Great to see you. >> Thanks. Let me start, Maribel, with you. Bob Muglia, we had a conversation as part of Supercloud the other day. And he said, "Dave, I like the work, you got to simplify this a little bit." So he said, quote, "A Supercloud is a platform." He said, "Think of it as a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." And then Nelu Mihai said, "Well, wait a minute. This is just going to create more stove pipes. We need more standards in an architecture," which is kind of what Berkeley Sky Computing initiative is all about. So there's a sort of a debate going on. Is supercloud an architecture, a platform? Or maybe it's just another buzzword. Maribel, do you have a thought on this? >> Well, the easy answer would be to say it's just a buzzword. And then we could just kill the conversation and be done with it. But I think the term, it's more than that, right? The term actually isn't new. You can go back to at least 2016 and find references to supercloud in Cornell University or assist in other documents. So, having said this, I think we've been talking about Supercloud for a while, so I assume it's more than just a fancy buzzword. But I think it really speaks to that undeniable trend of moving towards an abstraction layer to deal with the chaos of what we consider managing multiple public and private clouds today, right? So one definition of the technology platform speaks to a set of services that allows companies to build and run that technology smoothly without worrying about the underlying infrastructure, which really gets back to something that Bob said. And some of the question is where that lives. And you could call that an abstraction layer. You could call it cross-cloud services, hybrid cloud management. So I see momentum there, like legitimate momentum with enterprise IT buyers that are trying to deal with the fact that they have multiple clouds now. So where I think we're moving is trying to define what are the specific attributes and frameworks of that that would make it so that it could be consistent across clouds. What is that layer? And maybe that's what the supercloud is. But one of the things I struggle with with supercloud is. What are we really trying to do here? Are we trying to create differentiated services in the supercloud layer? Is a supercloud just another variant of what AWS, GCP, or others do? You spoken to Walmart about its cloud native platform, and that's an example of somebody deciding to do it themselves because they need to deal with this today and not wait for some big standards thing to happen. So whatever it is, I do think it's something. I think we're trying to maybe create an architecture out of it would be a better way of saying it so that it does get to those set of principles, but it also needs to be edge aware. I think whenever we talk about supercloud, we're always talking about like the big centralized cloud. And I think we need to think about all the distributed clouds that we're looking at in edge as well. So that might be one of the ways that supercloud evolves. >> So thank you, Maribel. Keith, Brian Gracely, Gracely's law, things kind of repeat themselves. We've seen it all before. And so what Muglia brought to the forefront is this idea of a platform where the platform provider is really responsible for the architecture. Of course, the drawback is then you get a a bunch of stove pipes architectures. But practically speaking, that's kind of the way the industry has always evolved, right? >> So if we look at this from the practitioner's perspective and we talk about platforms, traditionally vendors have provided the platforms for us, whether it's distribution of lineage managed by or provided by Red Hat, Windows, servers, .NET, databases, Oracle. We think of those as platforms, things that are fundamental we can build on top. Supercloud isn't today that. It is a framework or idea, kind of a visionary goal to get to a point that we can have a platform or a framework. But what we're seeing repeated throughout the industry in customers, whether it's the Walmarts that's kind of supersized the idea of supercloud, or if it's regular end user organizations that are coming out with platform groups, groups who normalize cloud native infrastructure, AWS multi-cloud, VMware resources to look like one thing internally to their developers. We're seeing this trend that there's a desire for a platform that provides the capabilities of a supercloud. >> Thank you for that. Sanjeev, we often use Snowflake as a supercloud example, and now would presumably would be a platform with an architecture that's determined by the vendor. Maybe Databricks is pushing for a more open architecture, maybe more of that nirvana that we were talking about before to solve for supercloud. But regardless, the practitioner discussions show. At least currently, there's not a lot of cross-cloud data sharing. I think it could be a killer use case, egress charges or a barrier. But how do you see it? Will that change? Will we hide that underlying complexity and start sharing data across cloud? Is that something that you think Snowflake or others will be able to achieve? >> So I think we are already starting to see some of that happen. Snowflake is definitely one example that gets cited a lot. But even we don't talk about MongoDB in this like, but you could have a MongoDB cluster, for instance, with nodes sitting in different cloud providers. So there are companies that are starting to do it. The advantage that these companies have, let's take Snowflake as an example, it's a centralized proprietary platform. And they are building the capabilities that are needed for supercloud. So they're building things like you can push down your data transformations. They have the entire security and privacy suite. Data ops, they're adding those capabilities. And if I'm not mistaken, it'll be very soon, we will see them offer data observability. So it's all works great as long as you are in one platform. And if you want resilience, then Snowflake, Supercloud, great example. But if your primary goal is to choose the most cost-effective service irrespective of which cloud it sits in, then things start falling sideways. For example, I may be a very big Snowflake user. And I like Snowflake's resilience. I can move from one cloud to another cloud. Snowflake does it for me. But what if I want to train a very large model? Maybe Databricks is a better platform for that. So how do I do move my workload from one platform to another platform? That tooling does not exist. So we need server hybrid, cross-cloud, data ops platform. Walmart has done a great job, but they built it by themselves. Not every company is Walmart. Like Maribel and Keith said, we need standards, we need reference architectures, we need some sort of a cost control. I was just reading recently, Accenture has been public about their AWS bill. Every time they get the bill is tens of millions of lines, tens of millions 'cause there are over thousand teams using AWS. If we have not been able to corral a usage of a single cloud, now we're talking about supercloud, we've got multiple clouds, and hybrid, on-prem, and edge. So till we've got some cross-platform tooling in place, I think this will still take quite some time for it to take shape. >> It's interesting. Maribel, Walmart would tell you that their on-prem infrastructure is cheaper to run than the stuff in the cloud. but at the same time, they want the flexibility and the resiliency of their three-legged stool model. So the point as Sanjeev was making about hybrid. It's an interesting balance, isn't it, between getting your lowest cost and at the same time having best of breed and scale? >> It's basically what you're trying to optimize for, as you said, right? And by the way, to the earlier point, not everybody is at Walmart's scale, so it's not actually cheaper for everybody to have the purchasing power to make the cloud cheaper to have it on-prem. But I think what you see almost every company, large or small, moving towards is this concept of like, where do I find the agility? And is the agility in building the infrastructure for me? And typically, the thing that gives you outside advantage as an organization is not how you constructed your cloud computing infrastructure. It might be how you structured your data analytics as an example, which cloud is related to that. But how do you marry those two things? And getting back to sort of Sanjeev's point. We're in a real struggle now where one hand we want to have best of breed services and on the other hand we want it to be really easy to manage, secure, do data governance. And those two things are really at odds with each other right now. So if you want all the knobs and switches of a service like geospatial analytics and big query, you're going to have to use Google tools, right? Whereas if you want visibility across all the clouds for your application of state and understand the security and governance of that, you're kind of looking for something that's more cross-cloud tooling at that point. But whenever you talk to somebody about cross-cloud tooling, they look at you like that's not really possible. So it's a very interesting time in the market. Now, we're kind of layering this concept of supercloud on it. And some people think supercloud's about basically multi-cloud tooling, and some people think it's about a whole new architectural stack. So we're just not there yet. But it's not all about cost. I mean, cloud has not been about cost for a very, very long time. Cloud has been about how do you really make the most of your data. And this gets back to cross-cloud services like Snowflake. Why did they even exist? They existed because we had data everywhere, but we need to treat data as a unified object so that we can analyze it and get insight from it. And so that's where some of the benefit of these cross-cloud services are moving today. Still a long way to go, though, Dave. >> Keith, I reached out to my friends at ETR given the macro headwinds, And you're right, Maribel, cloud hasn't really been about just about cost savings. But I reached out to the ETR, guys, what's your data show in terms of how customers are dealing with the economic headwinds? And they said, by far, their number one strategy to cut cost is consolidating redundant vendors. And a distant second, but still notable was optimizing cloud costs. Maybe using reserve instances, or using more volume buying. Nowhere in there. And I asked them to, "Could you go look and see if you can find it?" Do we see repatriation? And you hear this a lot. You hear people whispering as analysts, "You better look into that repatriation trend." It's pretty big. You can't find it. But some of the Walmarts in the world, maybe even not repatriating, but they maybe have better cost structure on-prem. Keith, what are you seeing from the practitioners that you talk to in terms of how they're dealing with these headwinds? >> Yeah, I just got into a conversation about this just this morning with (indistinct) who is an analyst over at GigaHome. He's reading the same headlines. Repatriation is happening at large scale. I think this is kind of, we have these quiet terms now. We have quiet quitting, we have quiet hiring. I think we have quiet repatriation. Most people haven't done away with their data centers. They're still there. Whether they're completely on-premises data centers, and they own assets, or they're partnerships with QTX, Equinix, et cetera, they have these private cloud resources. What I'm seeing practically is a rebalancing of workloads. Do I really need to pay AWS for this instance of SAP that's on 24 hours a day versus just having it on-prem, moving it back to my data center? I've talked to quite a few customers who were early on to moving their static SAP workloads onto the public cloud, and they simply moved them back. Surprising, I was at VMware Explore. And we can talk about this a little bit later on. But our customers, net new, not a lot that were born in the cloud. And they get to this point where their workloads are static. And they look at something like a Kubernetes, or a OpenShift, or VMware Tanzu. And they ask the question, "Do I need the scalability of cloud?" I might consider being a net new VMware customer to deliver this base capability. So are we seeing repatriation as the number one reason? No, I think internal IT operations are just naturally come to this realization. Hey, I have these resources on premises. The private cloud technologies have moved far along enough that I can just simply move this workload back. I'm not calling it repatriation, I'm calling it rightsizing for the operating model that I have. >> Makes sense. Yeah. >> Go ahead. >> If I missed something, Dave, why we are on this topic of repatriation. I'm actually surprised that we are talking about repatriation as a very big thing. I think repatriation is happening, no doubt, but it's such a small percentage of cloud migration that to me it's a rounding error in my opinion. I think there's a bigger problem. The problem is that people don't know where the cost is. If they knew where the cost was being wasted in the cloud, they could do something about it. But if you don't know, then the easy answer is cloud costs a lot and moving it back to on-premises. I mean, take like Capital One as an example. They got rid of all the data centers. Where are they going to repatriate to? They're all in the cloud at this point. So I think my point is that data observability is one of the places that has seen a lot of traction is because of cost. Data observability, when it first came into existence, it was all about data quality. Then it was all about data pipeline reliability. And now, the number one killer use case is FinOps. >> Maribel, you had a comment? >> Yeah, I'm kind of in violent agreement with both Sanjeev and Keith. So what are we seeing here? So the first thing that we see is that many people wildly overspent in the big public cloud. They had stranded cloud credits, so to speak. The second thing is, some of them still had infrastructure that was useful. So why not use it if you find the right workloads to what Keith was talking about, if they were more static workloads, if it was already there? So there is a balancing that's going on. And then I think fundamentally, from a trend standpoint, these things aren't binary. Everybody, for a while, everything was going to go to the public cloud and then people are like, "Oh, it's kind of expensive." Then they're like, "Oh no, they're going to bring it all on-prem 'cause it's really expensive." And it's like, "Well, that doesn't necessarily get me some of the new features and functionalities I might want for some of my new workloads." So I'm going to put the workloads that have a certain set of characteristics that require cloud in the cloud. And if I have enough capability on-prem and enough IT resources to manage certain things on site, then I'm going to do that there 'cause that's a more cost-effective thing for me to do. It's not binary. That's why we went to hybrid. And then we went to multi just to describe the fact that people added multiple public clouds. And now we're talking about super, right? So I don't look at it as a one-size-fits-all for any of this. >> A a number of practitioners leading up to Supercloud2 have told us that they're solving their cloud complexity by going in monocloud. So they're putting on the blinders. Even though across the organization, there's other groups using other clouds. You're like, "In my group, we use AWS, or my group, we use Azure. And those guys over there, they use Google. We just kind of keep it separate." Are you guys hearing this in your view? Is that risky? Are they missing out on some potential to tap best of breed? What do you guys think about that? >> Everybody thinks they're monocloud. Is anybody really monocloud? It's like a group is monocloud, right? >> Right. >> This genie is out of the bottle. We're not putting the genie back in the bottle. You might think your monocloud and you go like three doors down and figure out the guy or gal is on a fundamentally different cloud, running some analytics workload that you didn't know about. So, to Sanjeev's earlier point, they don't even know where their cloud spend is. So I think the concept of monocloud, how that's actually really realized by practitioners is primary and then secondary sources. So they have a primary cloud that they run most of their stuff on, and that they try to optimize. And we still have forked workloads. Somebody decides, "Okay, this SAP runs really well on this, or these analytics workloads run really well on that cloud." And maybe that's how they parse it. But if you really looked at it, there's very few companies, if you really peaked under the hood and did an analysis that you could find an actual monocloud structure. They just want to pull it back in and make it more manageable. And I respect that. You want to do what you can to try to streamline the complexity of that. >> Yeah, we're- >> Sorry, go ahead, Keith. >> Yeah, we're doing this thing where we review AWS service every day. Just in your inbox, learn about a new AWS service cursory. There's 238 AWS products just on the AWS cloud itself. Some of them are redundant, but you get the idea. So the concept of monocloud, I'm in filing agreement with Maribel on this that, yes, a group might say I want a primary cloud. And that primary cloud may be the AWS. But have you tried the licensed Oracle database on AWS? It is really tempting to license Oracle on Oracle Cloud, Microsoft on Microsoft. And I can't get RDS anywhere but Amazon. So while I'm driven to desire the simplicity, the reality is whether be it M&A, licensing, data sovereignty. I am forced into a multi-cloud management style. But I do agree most people kind of do this one, this primary cloud, secondary cloud. And I guarantee you're going to have a third cloud or a fourth cloud whether you want to or not via shadow IT, latency, technical reasons, et cetera. >> Thank you. Sanjeev, you had a comment? >> Yeah, so I just wanted to mention, as an organization, I'm complete agreement, no organization is monocloud, at least if it's a large organization. Large organizations use all kinds of combinations of cloud providers. But when you talk about a single workload, that's where the program arises. As Keith said, the 238 services in AWS. How in the world am I going to be an expert in AWS, but then say let me bring GCP or Azure into a single workload? And that's where I think we probably will still see monocloud as being predominant because the team has developed its expertise on a particular cloud provider, and they just don't have the time of the day to go learn yet another stack. However, there are some interesting things that are happening. For example, if you look at a multi-cloud example where Oracle and Microsoft Azure have that interconnect, so that's a beautiful thing that they've done because now in the newest iteration, it's literally a few clicks. And then behind the scene, your .NET application and your Oracle database in OCI will be configured, the identities in active directory are federated. And you can just start using a database in one cloud, which is OCI, and an application, your .NET in Azure. So till we see this kind of a solution coming out of the providers, I think it's is unrealistic to expect the end users to be able to figure out multiple clouds. >> Well, I have to share with you. I can't remember if he said this on camera or if it was off camera so I'll hold off. I won't tell you who it is, but this individual was sort of complaining a little bit saying, "With AWS, I can take their best AI tools like SageMaker and I can run them on my Snowflake." He said, "I can't do that in Google. Google forces me to go to BigQuery if I want their excellent AI tools." So he was sort of pushing, kind of tweaking a little bit. Some of the vendor talked that, "Oh yeah, we're so customer-focused." Not to pick on Google, but I mean everybody will say that. And then you say, "If you're so customer-focused, why wouldn't you do a ABC?" So it's going to be interesting to see who leads that integration and how broadly it's applied. But I digress. Keith, at our first supercloud event, that was on August 9th. And it was only a few months after Broadcom announced the VMware acquisition. A lot of people, myself included said, "All right, cuts are coming." Generally, Tanzu is probably going to be under the radar, but it's Supercloud 22 and presumably VMware Explore, the company really... Well, certainly the US touted its Tanzu capabilities. I wasn't at VMware Explore Europe, but I bet you heard similar things. Hawk Tan has been blogging and very vocal about cross-cloud services and multi-cloud, which doesn't happen without Tanzu. So what did you hear, Keith, in Europe? What's your latest thinking on VMware's prospects in cross-cloud services/supercloud? >> So I think our friend and Cube, along host still be even more offended at this statement than he was when I sat in the Cube. This was maybe five years ago. There's no company better suited to help industries or companies, cross-cloud chasm than VMware. That's not a compliment. That's a reality of the industry. This is a very difficult, almost intractable problem. What I heard that VMware Europe were customers serious about this problem, even more so than the US data sovereignty is a real problem in the EU. Try being a company in Switzerland and having the Swiss data solvency issues. And there's no local cloud presence there large enough to accommodate your data needs. They had very serious questions about this. I talked to open source project leaders. Open source project leaders were asking me, why should I use the public cloud to host Kubernetes-based workloads, my projects that are building around Kubernetes, and the CNCF infrastructure? Why should I use AWS, Google, or even Azure to host these projects when that's undifferentiated? I know how to run Kubernetes, so why not run it on-premises? I don't want to deal with the hardware problems. So again, really great questions. And then there was always the specter of the problem, I think, we all had with the acquisition of VMware by Broadcom potentially. 4.5 billion in increased profitability in three years is a unbelievable amount of money when you look at the size of the problem. So a lot of the conversation in Europe was about industry at large. How do we do what regulators are asking us to do in a practical way from a true technology sense? Is VMware cross-cloud great? >> Yeah. So, VMware, obviously, to your point. OpenStack is another way of it. Actually, OpenStack, uptake is still alive and well, especially in those regions where there may not be a public cloud, or there's public policy dictating that. Walmart's using OpenStack. As you know in IT, some things never die. Question for Sanjeev. And it relates to this new breed of data apps. And Bob Muglia and Tristan Handy from DBT Labs who are participating in this program really got us thinking about this. You got data that resides in different clouds, it maybe even on-prem. And the machine polls data from different systems. No humans involved, e-commerce, ERP, et cetera. It creates a plan, outcomes. No human involvement. Today, you're on a CRM system, you're inputting, you're doing forms, you're, you're automating processes. We're talking about a new breed of apps. What are your thoughts on this? Is it real? Is it just way off in the distance? How does machine intelligence fit in? And how does supercloud fit? >> So great point. In fact, the data apps that you're talking about, I call them data products. Data products first came into limelight in the last couple of years when Jamal Duggan started talking about data mesh. I am taking data products out of the data mesh concept because data mesh, whether data mesh happens or not is analogous to data products. Data products, basically, are taking a product management view of bringing data from different sources based on what the consumer needs. We were talking earlier today about maybe it's my vacation rentals, or it may be a retail data product, it may be an investment data product. So it's a pre-packaged extraction of data from different sources. But now I have a product that has a whole lifecycle. I can version it. I have new features that get added. And it's a very business data consumer centric. It uses machine learning. For instance, I may be able to tell whether this data product has stale data. Who is using that data? Based on the usage of the data, I may have a new data products that get allocated. I may even have the ability to take existing data products, mash them up into something that I need. So if I'm going to have that kind of power to create a data product, then having a common substrate underneath, it can be very useful. And that could be supercloud where I am making API calls. I don't care where the ERP, the CRM, the survey data, the pricing engine where they sit. For me, there's a logical abstraction. And then I'm building my data product on top of that. So I see a new breed of data products coming out. To answer your question, how early we are or is this even possible? My prediction is that in 2023, we will start seeing more of data products. And then it'll take maybe two to three years for data products to become mainstream. But it's starting this year. >> A subprime mortgages were a data product, definitely were humans involved. All right, let's talk about some of the supercloud, multi-cloud players and what their future looks like. You can kind of pick your favorites. VMware, Snowflake, Databricks, Red Hat, Cisco, Dell, HP, Hashi, IBM, CloudFlare. There's many others. cohesive rubric. Keith, I wanted to start with CloudFlare because they actually use the term supercloud. and just simplifying what they said. They look at it as taking serverless to the max. You write your code and then you can deploy it in seconds worldwide, of course, across the CloudFlare infrastructure. You don't have to spin up containers, you don't go to provision instances. CloudFlare worries about all that infrastructure. What are your thoughts on CloudFlare this approach and their chances to disrupt the current cloud landscape? >> As Larry Ellison said famously once before, the network is the computer, right? I thought that was Scott McNeley. >> It wasn't Scott McNeley. I knew it was on Oracle Align. >> Oracle owns that now, owns that line. >> By purpose or acquisition. >> They should have just called it cloud. >> Yeah, they should have just called it cloud. >> Easier. >> Get ahead. >> But if you think about the CloudFlare capability, CloudFlare in its own right is becoming a decent sized cloud provider. If you have compute out at the edge, when we talk about edge in the sense of CloudFlare and points of presence, literally across the globe, you have all of this excess computer, what do you do with it? First offering, let's disrupt data in the cloud. We can't start the conversation talking about data. When they say we're going to give you object-oriented or object storage in the cloud without egress charges, that's disruptive. That we can start to think about supercloud capability of having compute EC2 run in AWS, pushing and pulling data from CloudFlare. And now, I've disrupted this roach motel data structure, and that I'm freely giving away bandwidth, basically. Well, the next layer is not that much more difficult. And I think part of CloudFlare's serverless approach or supercloud approaches so that they don't have to commit to a certain type of compute. It is advantageous. It is a feature for me to be able to go to EC2 and pick a memory heavy model, or a compute heavy model, or a network heavy model, CloudFlare is taken away those knobs. and I'm just giving code and allowing that to run. CloudFlare has a massive network. If I can put the code closest using the CloudFlare workers, if I can put that code closest to where the data is at or residing, super compelling observation. The question is, does it scale? I don't get the 238 services. While Server List is great, I have to know what I'm going to build. I don't have a Cognito, or RDS, or all these other services that make AWS, GCP, and Azure appealing from a builder's perspective. So it is a very interesting nascent start. It's great because now they can hide compute. If they don't have the capacity, they can outsource that maybe at a cost to one of the other cloud providers, but kind of hiding the compute behind the surplus architecture is a really unique approach. >> Yeah. And they're dipping their toe in the water. And they've announced an object store and a database platform and more to come. We got to wrap. So I wonder, Sanjeev and Maribel, if you could maybe pick some of your favorites from a competitive standpoint. Sanjeev, I felt like just watching Snowflake, I said, okay, in my opinion, they had the right strategy, which was to run on all the clouds, and then try to create that abstraction layer and data sharing across clouds. Even though, let's face it, most of it might be happening across regions if it's happening, but certainly outside of an individual account. But I felt like just observing them that anybody who's traditional on-prem player moving into the clouds or anybody who's a cloud native, it just makes total sense to write to the various clouds. And to the extent that you can simplify that for users, it seems to be a logical strategy. Maybe as I said before, what multi-cloud should have been. But are there companies that you're watching that you think are ahead in the game , or ones that you think are a good model for the future? >> Yes, Snowflake, definitely. In fact, one of the things we have not touched upon very much, and Keith mentioned a little bit, was data sovereignty. Data residency rules can require that certain data should be written into certain region of a certain cloud. And if my cloud provider can abstract that or my database provider, then that's perfect for me. So right now, I see Snowflake is way ahead of this pack. I would not put MongoDB too far behind. They don't really talk about this thing. They are in a different space, but now they have a lakehouse, and they've got all of these other SQL access and new capabilities that they're announcing. So I think they would be quite good with that. Oracle is always a dark forest. Oracle seems to have revived its Cloud Mojo to some extent. And it's doing some interesting stuff. Databricks is the other one. I have not seen Databricks. They've been very focused on lakehouse, unity, data catalog, and some of those pieces. But they would be the obvious challenger. And if they come into this space of supercloud, then they may bring some open source technologies that others can rely on like Delta Lake as a table format. >> Yeah. One of these infrastructure players, Dell, HPE, Cisco, even IBM. I mean, I would be making my infrastructure as programmable and cloud friendly as possible. That seems like table stakes. But Maribel, any companies that stand out to you that we should be paying attention to? >> Well, we already mentioned a bunch of them, so maybe I'll go a slightly different route. I'm watching two companies pretty closely to see what kind of traction they get in their established companies. One we already talked about, which is VMware. And the thing that's interesting about VMware is they're everywhere. And they also have the benefit of having a foot in both camps. If you want to do it the old way, the way you've always done it with VMware, they got all that going on. If you want to try to do a more cross-cloud, multi-cloud native style thing, they're really trying to build tools for that. So I think they have really good access to buyers. And that's one of the reasons why I'm interested in them to see how they progress. The other thing, I think, could be a sleeping horse oddly enough is Google Cloud. They've spent a lot of work and time on Anthos. They really need to create a certain set of differentiators. Well, it's not necessarily in their best interest to be the best multi-cloud player. If they decide that they want to differentiate on a different layer of the stack, let's say they want to be like the person that is really transformative, they talk about transformation cloud with analytics workloads, then maybe they do spend a good deal of time trying to help people abstract all of the other underlying infrastructure and make sure that they get the sexiest, most meaningful workloads into their cloud. So those are two people that you might not have expected me to go with, but I think it's interesting to see not just on the things that might be considered, either startups or more established independent companies, but how some of the traditional providers are trying to reinvent themselves as well. >> I'm glad you brought that up because if you think about what Google's done with Kubernetes. I mean, would Google even be relevant in the cloud without Kubernetes? I could argue both sides of that. But it was quite a gift to the industry. And there's a motivation there to do something unique and different from maybe the other cloud providers. And I'd throw in Red Hat as well. They're obviously a key player and Kubernetes. And Hashi Corp seems to be becoming the standard for application deployment, and terraform, or cross-clouds, and there are many, many others. I know we're leaving lots out, but we're out of time. Folks, I got to thank you so much for your insights and your participation in Supercloud2. Really appreciate it. >> Thank you. >> Thank you. >> Thank you. >> This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more content from Supercloud2.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Recent conversations with IT decision makers show a stark contrast between exiting 2023 versus the mindset when we were leaving 2022. CIOs are generally funding new initiatives by pushing off or cutting lower priority items, while security efforts are still being funded. Those that enable business initiatives that generate revenue or taking priority over cleaning up legacy technical debt. The bottom line is, for the moment, at least, the mindset is not cut everything, rather, it's put a pause on cleaning up legacy hairballs and fund monetization. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we tap recent discussions from two primary sources, year-end ETR roundtables with IT decision makers, and CUBE conversations with data, cloud, and IT architecture practitioners. The sources of data for this breaking analysis come from the following areas. Eric Bradley's recent ETR year end panel featured a financial services DevOps and SRE manager, a CSO in a large hospitality firm, a director of IT for a big tech company, the head of IT infrastructure for a financial firm, and a CTO for global travel enterprise, and for our upcoming Supercloud2 conference on January 17th, which you can register free by the way, at supercloud.world, we've had CUBE conversations with data and cloud practitioners, specifically, heads of data in retail and financial services, a cloud architect and a biotech firm, the director of cloud and data at a large media firm, and the director of engineering at a financial services company. Now we've curated commentary from these sources and now we share them with you today as anecdotal evidence supporting what we've been reporting on in the marketplace for these last couple of quarters. On this program, we've likened the economy to the slingshot effect when you're driving, when you're cruising along at full speed on the highway, and suddenly you see red brake lights up ahead, so, you tap your own brakes and then you speed up again, and traffic is moving along at full speed, so, you think nothing of it, and then, all of a sudden, the same thing happens. You slow down to a crawl and you start wondering, "What the heck is happening?" And you become a lot more cautious about the rate of acceleration when you start moving again. Well, that's the trend in IT spend right now. Back in June, we reported that despite the macro headwinds, CIOs were still expecting 6% to 7% spending growth for 2022. Now that was down from 8%, which we reported at the beginning of 2022. That was before Ukraine, and Fed tightening, but given those two factors, you know that that seemed pretty robust, but throughout the fall, we began reporting consistently declining expectations where CIOs are now saying Q4 will come in at around 3% growth relative to last year, and they're expecting, or should we say hoping that it pops back up in 2023 to 4% to 5%. The recent ETR panelists, when they heard this, are saying based on their businesses and discussions with their peers, they could see low single digit growth for 2023, so, 1%, 2%, 3%, so, this sort of slingshotting, or sometimes we call it a seesaw economy, has caught everyone off guard. Amazon is a good example of this, and there are others, but Amazon entered the pandemic with around 800,000 employees. It doubled that workforce during the pandemic. Now, right before Thanksgiving in 2022, Amazon announced that it was laying off 10,000 employees, and, Jassy, the CEO of Amazon, just last week announced that number is now going to grow to 18,000. Now look, this is a rounding error at Amazon from a headcount standpoint and their headcount remains far above 2019 levels. Its stock price, however, does not and it's back down to 2019 levels. The point is that visibility is very poor right now and it's reflected in that uncertainty. We've seen a lot of layoffs, obviously, the stock market's choppy, et cetera. Now importantly, not everything is on hold, and this downturn is different from previous tech pullbacks in that the speed at which new initiatives can be rolled out is much greater thanks to the cloud, and if you can show a fast return, you're going to get funding. Organizations are pausing on the cleanup of technical debt, unless it's driving fast business value. They're holding off on modernization projects. Those business enablement initiatives are still getting funded. CIOs are finding the money by consolidating redundant vendors, and they're stealing from other pockets of budget, so, it's not surprising that cybersecurity remains the number one technology priority in 2023. We've been reporting that for quite some time now. It's specifically cloud, cloud native security container and API security. That's where all the action is, because there's still holes to plug from that forced march to digital that occurred during COVID. Cloud migration, kind of showing here on number two on this chart, still a high priority, while optimizing cloud spend is definitely a strategy that organizations are taking to cut costs. It's behind consolidating redundant vendors by a long shot. There's very little evidence that cloud repatriation, i.e., moving workloads back on prem is a major cost cutting trend. The data just doesn't show it. What is a trend is getting more real time with analytics, so, companies can do faster and more accurate customer targeting, and they're really prioritizing that, obviously, in this down economy. Real time, we sometimes lose it, what's real time? Real time, we sometimes define as before you lose the customer. Now in the hiring front, customers tell us they're still having a hard time finding qualified site reliability engineers, SREs, Kubernetes expertise, and deep analytics pros. These job markets remain very tight. Let's stay with security for just a moment. We said many times that, prior to COVID, zero trust was this undefined buzzword, and the joke, of course, is, if you ask three people, "What is zero trust?" You're going to get three different answers, but the truth is that virtually every security company that was resisting taking a position on zero trust in an attempt to avoid... They didn't want to get caught up in the buzzword vortex, but they're now really being forced to go there by CISOs, so, there are some good quotes here on cyber that we want to share that came out of the recent conversations that we cited up front. The first one, "Zero trust is the highest ROI, because it enables business transformation." In other words, if I can have good security, I can move fast, it's not a blocker anymore. Second quote here, "ZTA," zero trust architecture, "Is more than securing the perimeter. It encompasses strong authentication and multiple identity layers. It requires taking a software approach to security instead of a hardware focus." The next one, "I'd love to have a security data lake that I could apply to asset management, vulnerability management, incident management, incident response, and all aspects for my security team. I see huge promise in that space," and the last one, I see NLP, natural language processing, as the foundation for email security, so, instead of searching for IP addresses, you can now read emails at light speed and identify phishing threats, so, look at, this is a small snapshot of the mindset around security, but I'll add, when you talk to the likes of CrowdStrike, and Zscaler, and Okta, and Palo Alto Networks, and many other security firms, they're listening to these narratives around zero trust. I'm confident they're working hard on skating to this puck, if you will. A good example is this idea of a security data lake and using analytics to improve security. We're hearing a lot about that. We're hearing architectures, there's acquisitions in that regard, and so, that's becoming real, and there are many other examples, because data is at the heart of digital business. This is the next area that we want to talk about. It's obvious that data, as a topic, gets a lot of mind share amongst practitioners, but getting data right is still really hard. It's a challenge for most organizations to get ROI and expected return out of data. Most companies still put data at the periphery of their businesses. It's not at the core. Data lives within silos or different business units, different clouds, it's on-prem, and increasingly it's at the edge, and it seems like the problem is getting worse before it gets better, so, here are some instructive comments from our recent conversations. The first one, "We're publishing events onto Kafka, having those events be processed by Dataproc." Dataproc is a Google managed service to run Hadoop, and Spark, and Flank, and Presto, and a bunch of other open source tools. We're putting them into the appropriate storage models within Google, and then normalize the data into BigQuery, and only then can you take advantage of tools like ThoughtSpot, so, here's a company like ThoughtSpot, and they're all about simplifying data, democratizing data, but to get there, you have to go through some pretty complex processes, so, this is a good example. All right, another comment. "In order to use Google's AI tools, we have to put the data into BigQuery. They haven't integrated in the way AWS and Snowflake have with SageMaker. Moving the data is too expensive, time consuming, and risky," so, I'll just say this, sharing data is a killer super cloud use case, and firms like Snowflake are on top of it, but it's still not pretty across clouds, and Google's posture seems to be, "We're going to let our database product competitiveness drive the strategy first, and the ecosystem is going to take a backseat." Now, in a way, I get it, owning the database is critical, and Google doesn't want to capitulate on that front. Look, BigQuery is really good and competitive, but you can't help but roll your eyes when a CEO stands up, and look, I'm not calling out Thomas Kurian, every CEO does this, and talks about how important their customers are, and they'll do whatever is right by the customer, so, look, I'm telling you, I'm rolling my eyes on that. Now let me also comment, AWS has figured this out. They're killing it in database. If you take Redshift for example, it's still growing, as is Aurora, really fast growing services and other data stores, but AWS realizes it can make more money in the long-term partnering with the Snowflakes and Databricks of the world, and other ecosystem vendors versus sub optimizing their relationships with partners and customers in order to sell more of their own homegrown tools. I get it. It's hard not to feature your own product. IBM chose OS/2 over Windows, and tried for years to popularize it. It failed. Lotus, go back way back to Lotus 1, 2, and 3, they refused to run on Windows when it first came out. They were running on DEC VAX. Many of you young people in the United States have never even heard of DEC VAX. IBM wanted to run every everything only in its cloud, the same with Oracle, originally. VMware, as you might recall, tried to build its own cloud, but, eventually, when the market speaks and reveals what seems to be obvious to analysts, years before, the vendors come around, they face reality, and they stop wasting money, fighting a losing battle. "The trend is your friend," as the saying goes. All right, last pull quote on data, "The hardest part is transformations, moving traditional Informatica, Teradata, or Oracle infrastructure to something more modern and real time, and that's why people still run apps in COBOL. In IT, we rarely get rid of stuff, rather we add on another coat of paint until the wood rots out or the roof is going to cave in. All right, the last key finding we want to highlight is going to bring us back to the cloud repatriation myth. Followers of this program know it's a real sore spot with us. We've heard the stories about repatriation, we've read the thoughtful articles from VCs on the subject, we've been whispered to by vendors that you should investigate this trend. It's really happening, but the data simply doesn't support it. Here's the question that was posed to these practitioners. If you had unlimited budget and the economy miraculously flipped, what initiatives would you tackle first? Where would you really lean into? The first answer, "I'd rip out legacy on-prem infrastructure and move to the cloud even faster," so, the thing here is, look, maybe renting infrastructure is more expensive than owning, maybe, but if I can optimize my rental with better utilization, turn off compute, use things like serverless, get on a steeper and higher performance over time, and lower cost Silicon curve with things like Graviton, tap best of breed tools in AI, and other areas that make my business more competitive. Move faster, fail faster, experiment more quickly, and cheaply, what's that worth? Even the most hard-o CFOs understand the business benefits far outweigh the possible added cost per gigabyte, and, again, I stress "possible." Okay, other interesting comments from practitioners. "I'd hire 50 more data engineers and accelerate our real-time data capabilities to better target customers." Real-time is becoming a thing. AI is being injected into data and apps to make faster decisions, perhaps, with less or even no human involvement. That's on the rise. Next quote, "I'd like to focus on resolving the concerns around cloud data compliance," so, again, despite the risks of data being spread out in different clouds, organizations realize cloud is a given, and they want to find ways to make it work better, not move away from it. The same thing in the next one, "I would automate the data analytics pipeline and focus on a safer way to share data across the states without moving it," and, finally, "The way I'm addressing complexity is to standardize on a single cloud." MonoCloud is actually a thing. We're hearing this more and more. Yes, my company has multiple clouds, but in my group, we've standardized on a single cloud to simplify things, and this is a somewhat dangerous trend, because it's creating even more silos and it's an opportunity that needs to be addressed, and that's why we've been talking so much about supercloud is a cross-cloud, unifying, architectural framework, or, perhaps, it's a platform. In fact, that's a question that we will be exploring later this month at Supercloud2 live from our Palo Alto Studios. Is supercloud an architecture or is it a platform? And in this program, we're featuring technologists, analysts, practitioners to explore the intersection between data and cloud and the future of cloud computing, so, you don't want to miss this opportunity. Go to supercloud.world. You can register for free and participate in the event directly. All right, thanks for listening. That's a wrap. I'd like to thank Alex Myerson, who's on production and manages our podcast, Ken Schiffman as well, Kristen Martin and Cheryl Knight, they helped get the word out on social media, and in our newsletters, and Rob Hof is our editor-in-chief over at siliconangle.com. He does some great editing. Thank you, all. Remember, all these episodes are available as podcasts wherever you listen. All you've got to do is search "breaking analysis podcasts." I publish each week on wikibon.com and siliconangle.com where you can email me directly at david.vellante@siliconangle.com or DM me, @Dante, or comment on our LinkedIn posts. By all means, check out etr.ai. They get the best survey data in the enterprise tech business. We'll be doing our annual predictions post in a few weeks, once the data comes out from the January survey. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, everybody, and we'll see you next time on "Breaking Analysis." (upbeat music)

>>The Cube presents Ignite 22, brought to you by Palo Alto Networks. >>Welcome back everyone. Happy afternoon. It's Lisa Martin and Dave Valante of the Cube. We are live at MGM Grand. This is Palo Alto Ignite 22, our second day of coverage. Dave, we've had some amazing conversations, as we always do on the queue, but cybersecurity one of my favorite topics. So interesting to hear what Palo Alto Networks is doing, how it's differentiating itself and how it's ecosystem is >>Growing. Yeah, well one of the things I always, I often use ServiceNow as a reference example. I go back to 2013, had a kind of a tiny ecosystem and then sort of watched it grow. And one of those key signs was when the global system integrators actually began to lean in Accenture, obviously world class, one of the, you know, definitely in the top, you know, they talk about top five QBs, Accenture, you know, top five GSI easily. >>Yep. So, and in fact, Accenture, we've got Rex Stex in here, senior managing director at Accenture Security. You guys have been the GSI partner of the year for Palo Alto Networks for four years in a row, six years plus strong partnership. Give us a little flavor and history of the pan of the Palo Alto partnership with et cetera. >>I think, you know, we started early, right? And I think as they've evolved, we've evolved our partnership with them and as they've gone, you know, to more of a software footprint with, you know, around cloud security and network security and sassy, we've, we've seen a lot of growth and we're super excited about the opportunity that's ahead of us and the meaningful outcomes that we've been providing our clients as it relates to, you know, vendor consolidation, toll consolidation, tech debt reduction. You know, there's a lot of opportunity here to simplify our clients' lives with them. And that's something we're super excited about. >>Simplification, consolidation, been a theme of the last couple of days. Talk about some of the joint accomplishments that you guys have achieved. I know that you developed a lot of offers across all of Palo Alto Network's, GTMs, what are some of the highlights that come to mind? I >>Think one of the things that we're most excited about, you know, that being client specific is what we've been able to do on, on, on the network side with sasi and, and zero trust, network access. You know, as when Covid hit, there was a lot of change that happened with remote workforce and, you know, clients couldn't log in because their VPNs were crashing left and right. And so we were able to, you know, go in and help stand up, you know, this, you know, zero trust network infrastructure and help our clients get back online and get their employees back to work in a productive manner. And then it's evolved with the hybrid work model over time. And so it's, it's been a, that's probably the most gratifying cause there was a real crisis at, at a certain point in time, you know, a couple years ago were >>There Rex, were there unintended consequences of that, you know, rapid, we were forced, you know, the forced march to digital in terms of just multiple tools, plugging holes, and then sort of stepping back, you know, post isolation economy saying, okay, hey, we got through this, but now we need to take a new direction, new >>Strategy. I think that there, there isn't an intended consequence if you look at, most clients have, I saw a number 76, we counted as around 80 different security vendors and tools that they managed because a lot of people went and went after best of breed type capabilities. And, and so what we've seen now is, is the need to, you know, rationalize that, you know, their, their infrastructure and their, and their capability and, and consolidate and reduce that and, and move to, you know, more of what I would call platform providers. Cause if you may have, when you have 80 products, you have 80 integrations, 80 points of failure, and it gets very complex and, you know, there's a lot of finger pointing. And so as we're starting to see clients take a step back and say, Hey, look, if I, you know, spend the time to, you know, I call it modernization, but you know, modernize my security infrastructure and footprint focused around, you know, automation, orchestration, leveraging, you know, true ml and I know there's are buzzwords, but, you know, but you know, using 'em in, in, in the proper fashion, right? >>They, they can, you know, reduce that footprint, save a bunch of money, right? And, and, and drive that cost savings and then help scale their business. Cuz you have all these different vendors and what security is typically in the digital footprint is the slowdown, right? We, we've typically been the bottleneck in the past. And what we're seeing with, with, with what, you know, we've been very focused on is helping our clients scale their security footprints and their infrastructure and, you know, through automation orchestration, I i, I always say some folks do it your mess for less with labor arbitrage and bodies, but they're not enough security people in the world to do this. And so we're very focused on automation and orchestration and driving that into, into the market. >>Yeah. So you don't want to be in the business of, of filling those holes with labor. >>Exactly. You >>Want to actually get paid for outcomes. >>A hundred percent. And everything we've done is we've tried to simplify things not only for, you know, big Accenture, but even for our clients so that, you know, we can be focused on business outcomes, not necessarily technology outcomes. Cuz doing technology for the sake of technology. Is that unintended consequence that you described earlier, >>Speaking of transformation and outcomes I should say, what are you hearing most from CIOs and CISOs in terms of what they need now to be able to transform, to deliver the business outcomes so that they can become secure data companies regardless of industry? Yep. >>I think the, the biggest thing we're seeing right now is the need to, you know, leverage true automation and orchestration. We have to break the headcount model. There's not enough security professionals in the world to do, you know, to solve the world's problems. In order to scale that, you know, it's one of the reasons we're, you know, partnering with Palo Alto is because of, you know, the capabilities and the investments they've made in innovation to help drive that automation and orchestration through, you know, numerous capabilities from stock transformation to to to sassy cloud security, et cetera. But our clients need scale. They need to be able to go fast and net pace and they need to, they need to do it with confidence securely. And that, that's one of the big focuses. But the other focus is, is we're starting to see a need to, you know, vendor consolidation in the market. You've seen the acquisitions, I'm sure you've talked to people in over the last couple days. You know, there's, there's a, a tremendous amount of consolidation going around. And what our clients, you know, are asking for is, Hey, I need to reduce the number of vendors I interact with. I need to simplify my infrastructure, I need to focus on automation and, and orchestration from that perspective, >>What's happening with multi-cloud? What are you hearing from from customers? You know, we hear a lot of the, the, the conversations about, oh it's, you know, it's, and I agree by the way, multi-cloud is kind of a symptom of multi-vendor, you know, Chuck Whittens thing about multi-cloud by default versus design, you know, it's good, good line and I think rings true, but, but what a customer's telling you in terms of the real challenges generally and then specifically around security. >>I think it's, you know, each cloud service product has their own security capabilities and security models and, and, and being able to train the people to be able to manage those different models. I think that's where, you know, tools like, you know, Prisma Cloud for instance come in and help clients be able to manage the security and compliance of those infrastructures in, in a way to do that. And then to be able to manage applications security consistently, right? It's not just the cloud itself, but it's actually the applications that may, you know, cross, you know, be for, for resiliency but you know, be in, you know, multi-cloud, you know, multiple clouds and being able to make sure you have consistent security across those. And I think, you know, one of the things that it's permeated is, is just the, with data and identity and, and you know, cloud infrastructure and tolerance management, it's been a big problem cuz it's like the wild, wild west. I always look, when I look at identity and the cloud and how it's done, it, it looks like 1995 identity. It's, it's, it's ridiculously backwards. And so, you know, we've seen things like, you know, keem that have come into play to help manage those relationships and, and simplify it across multiple clouds consistently, if that makes sense. >>Yep. >>You, you mentioned Prisma Cloud most recently Accenture and Palo Alto developed the Secure Cloud Express. Correct. Can you talk to us a little bit about what that is and what outcomes is it gonna enable? Yeah, >>So great question and we're pretty excited about this cuz what we did with that was we manage cloud, you know, our cloud environments for numerous customers. So we've developed hundreds of policies that, you know, we implemented in Prisma Cloud to manage, you know, multiple clients, our internal infrastructure. And what we did was we said, well, most of our clients have to build those from scratch. So what we said is we will come in, in the best of week of time and come in and, and do a data-driven exercise to show our clients, you know, where where they sit from a, from a security perspective as it relates leveraging Prisma cloud and, and those policies that we've created. And what, what that has led to is another step, which is where we're focused on auto remediation. So, you know, when you, when you get, when you get the findings, then what do you do with them, right? If you have hundreds or thousands in some cases we've had clients with 1100 findings and they just sit there and they go, whoa, you know, so to speak. And so what we've done is we try to take those highest, most frequent findings and build securities code to auto remediate those for clients so they can choose to implement that and work down those, you know, findings very quickly, which helps, you know, drive more value out of, out of their prisma cloud >>Purchases. Accenture obviously has deep industry expertise around the globe. What are you seeing in terms of industries actually? So as they digitize not just their IT transformation but a business transformation, there are starting to see companies, financial services in particular bring their business to their cloud, sify their business. And specifically I'm interested in what's happening at the edge with operations technology. We just talked about healthcare and and medical devices. What's happening there? How connected or disconnected is that to the rest of the estate, the multi-cloud on-prem, et cetera? I >>Mean, I think OT is, is fairly disconnected, right? Sure. From, from that perspective, obviously, but I, I, I think what we're starting to see is an uptick, you know, on, I think secure edge and Sassy will come to OT cause it's a better way. Because what happens is if someone, you know, gets into the network, they can traverse it, right? And if they can apply those zero trust principles to ot, which is you're talking to people that have been, you know, wearing hard hats Yeah. And engineers, that's a big shift for them. And so, but I think that you'll start to see that play more prevalence, you know, with the industries like, you know, financial services, we're seeing a huge uptick in cloud adoption, right? They were, they were slow to do it, but now they're, they're going at pace and faster than most, right? Yeah, sure. And I think, you know, healthcare is a, is another big one where we've seen a lot of migration and a lot of need for multi-cloud. Cuz you know, some, they may be running their analytics on, you know, Google and, and their workloads on Azure, right? Or aws. And so you're starting to see a lot of people leveraging the best of what each cloud provider does well >>From that. And, and just an aside on that Palo Alto survey, we saw construction was one of the hardest hit industries. Yeah. Which I, I was like, what? And then of course it's because they're not really focused on security. They're focused on building stuff. No, >>It's really interesting. We're working with a large builder, I can't say the name, but one of the things that they're looking to do is, you know, they're moving to the cloud and they're building the capability to manage some of the, you know, largest skyscrapers in the world, but also manage the OT sensors and also do selling that creating another business, not only just managing those buildings, but managing other people's buildings for them and ha and selling security as a service for that because they built that capability around their devices and, and, and switches, hvac, et cetera. Do, >>Do you think that because I mean, you know, the operations technology, they're engineers and they're hardcore, like, don't touch my stuff. Exactly. And so do you feel like as, I mean I know that business has kind of done a reach around everything, you know, be becoming connected, but do you feel like they're gonna be more on top of it then, then, then sort of the, the broad commercial market has been? Or is it gonna be wild West all over again? >>My hope is that, you know, us as gsi, you know, my fellow GSIs, that we will help our clients make the better decisions this time around and, and not go to the wild, wild west. And you know, we see a lot of it in manufacturing, you know, if you saw, you know, with the, you know, the invasion Ukraine, you know, one of the big groups that was hit was manufacturing, right? There was factory shut down all over the world, you know, and, and so, you know, and that is an OT environment, but I, you know, what we've seen is them are, you know, those clients take more serious steps to protect those environments cuz they're on, you know, windows 10 servers running, you know, large machines. So we're starting to see a lot more care and feeding in into those environments as well. >>Can I ask you a question about the conversations that you're having? That survey that Dave mentioned, it's was released yesterday. There's a board behind us, what's next in cyber? That was the survey and amazing data that came from it. Like 96% of organizations have been hit by at least one attack in the last year. They were surprised that the number was that high, but we know that no industry, no company is safe. But one of the things that the survey found that, that surprised me was that we always say, oh, security is a board level conversation. We know that to some degree. But what they found was lack of alignment between the board and the executive level. In your Accenture's relationships, I know you guys have deep relationships across organizations and their boards. Can you help bring the board together with the executives and, and really not just talk about cybersecurity, but really develop a cybersecurity transformation strategy that actually delivers resilience? >>Yeah, no ab absolutely. And we've, we, we actually took a step back and, and reorganized our business this last year. And one of those areas that we focused on was within strategy and the C-suite agenda, right? And we actually published looking at gia, it was either the CEO handbook, I think it's what we called it, but they helped them and board be able to, you know, drive more meaningful conversations that relates to risk and and whatnot. And so we're very focused on that right now. And it's, we need to up-level our conversations within the organization. Cause even the buyers in these large, you know, two years ago was mainly the cso, now we're dealing with the cio, CTOs, cfo because these are, you know, meaningful business conversations, right? That are driving business outcomes and security needs to be a business enabler, not, not a a, a bottleneck >>Is the chief data officer starting to emerge as, as we see, you know, Nikesh said yesterday in his keynote and we talked about it with him when he was here, security is a data problem. >>Yep. It is. It's a huge data problem. And we're starting to, you know, I think we've talked a lot about zero trust, but zero trust data is, is a, is a significant problem, right? Because that you talk about the wild, wild west is we see clients that have people that have in, you know, they, they have access to, you know, what we call dev development environment data, right? But then you find out that they can hop four levels over into production data and this been exposed to, you know, the wrong people, you know, not focused on that least privileged aspect. I think data's a real problem, you know, per na kesha's statement in the cloud. It's something that really needs to be addressed. And I think we're starting to see a lot of innovation around that area. Cuz what typical data security has always been, I have all these problems, it creates, I call it noise, right? I got thousands of findings and then just, you know, need just sit there and they go, what do I do? Right? It's too much. And so I think there, there's gonna be more intelligence around that and more, you know, what I call auto remediation, right? Being able to remediate those findings quickly from from that >>Perspective. I've been watching this board behind us. Yeah. It's this what's next in cyber. And people come in and they write, it's just been growing, you know, all week and somebody just wrote sock transformation. Yeah. We were just sort of talking about earlier what, what, in your estimation, what percent of organizations that you target. I understand that you're not going after the, you know, mom and pop organizations, but what percent of that, you know, fat middle and the tip of the pyramid, that a euro, that's your sweet spot. What percent of those organizations don't have a sock? >>I mean, most every organization has a sock. You know, I talked to, you know, CISOs of large financial service organization, they said, do we even need a sock anymore? It could be a virtual sock so to speak, but I think, you know, am was SOC transformation. I think we could potentially head to something like that. But you know, but what's really been strange is there's been, you know, what we call soar, right? Security, you know, orchestration, automation, whatever. And what another, >>Another acronym, their >>Acronym that I security that I might brain is >>Hold apologize. >>But you know, they've, people have never really driven the value out of it because they build these automation playbooks and, and for one company to do it and build 20 of 'em or 30 of 'em to ha it doesn't pay off in the long run. And what we're starting to see is people, you know, bring to the table more crowdsource these capabilities so that they can scale those sock transformations. Cause it's really about, you know, orchestration and automation. That's where, you know, nirvana comes in because it's not about people with headsets on looking at, you know, 20 screens. It's not helpful, right? The humans, we make mistakes. And so if we can automate as much of that as possible, get rid of the false positives, leverage AI and and ML to do that. And I think we're starting to see, you know, what I would call more advanced AI and ml. I think in the early days in security, AI and ML was very nascent and, and, and now you're starting to see, you know, more powerful concepts come in better learning, better outcomes out of that. >>Well, it was a lot of modeling in the cloud still is, but it's increasingly going toward real time inference and that's, you know, game changing. >>Agreed. >>Last question for you. What's are some of the things that are next on the plate for Accenture and Palo Networks? What's next up? >>I think, you know, we're very focused on, on Sassy right now in, in the market. And I think we think that is, you know, I think both of us think that's the next big wave, right? Because I think what we learned out of, you know, these last two and a half, three years is that these concepts work, but they can actually scale out to drive significant cost savings. I mean, if you look at Accenture, you know, we don't have a a network backbone anymore. We're pure cloud wan, right? We're leveraging the internet for that. And I think that and what we're trying to do with Palo Alto and driving, you know, cloud WAN and Sassy as a service, I think will be super, super meaningful. And, and, and, and >>Well that's interesting. That has implications for a number of companies out >>There. Yeah. Well I think, you know, it's obviously the, you know, it, it's a, it is a big implication for a lot of, a lot of, you know, our customers even, right? Yeah. And so we have to be very careful and thoughtful about how we work to make that happen over time. >>Right. A lot of opportunity. Rex, thank you so much for joining us on the program and really dissecting what Accenture and Palo Alto are doing, all the value in it for organizations across industries. We appreciate your insights. Yep. >>Thank you >>For Rex Dexon and Dave Valante. I'm Lisa Martin, you're watching the Cubes stick around. Dave and I will be right back with our next guest. This is the Cube, the leader in live, emerging and enterprise tech coverage.

>>Hello everyone. Welcome back to the Cube's Live coverage. I'm John Fur, host of the Cube. We got two sets here, three sets total. Another one in the executive center. It's our 10th year covering AWS Reinvent. I remember 2013 like it was yesterday. You know, now it's a massive of people buying out restaurants. 35,000 people now it's 55,000, soon to be 70,000 back. Great event. Continuing to set the standard in the industry. We had an amazing guest here, Leah Bibo, vice President of Product Marketing. She's in charge of the messaging, the product, overseeing how these products gonna market. Leah, great to see you. Thanks for joining me on the Cube today. >>Absolutely. It's great to be here. It's also my 10 reinvent, so it's, it's been a wild ride. >>Absolutely. Yeah. You and I were talking before we came on camera, how much we love products and yes, this is a product-centric company, has been from day one and you know, over the years watching the announcements, the tsunami of announcements, just all the innovation that's come out from AWS over the years has been staggering to say the least. Everyone always jokes about, oh my God, 5,000 new announcements, over 200 services you're managing and you're marketing them. It's pretty crazy right now. And Adam, as he comes on, as I called them, the solutions CEO on my piece I wrote on Friday, we're in an era where solutions, the products are enabling more solutions. Unpack the messaging around this cuz this is really big moment for aws. >>Absolutely. Well, I'll say first of all that we are a customer focused company that happens to be really good at innovating incredible products and services for our customers. So today the, the energy in the room and what Adam talked about, I think is focused on a few great things for customers that are really important for transformation. So we talked a lot about best price performance for workloads and we talked about extreme workloads, but if you think about the work that we've been doing to innovate on the silicon side, we're really talking about with Graviton all your workloads and getting really great price performance for all of them. You know, we came out with graviton three 25% faster than graviton two, also 60% more energy efficient. We talked about something that is emerging that I think is gonna be really big, which is simulation and really the ability to model these complex worlds and all the little interactions, which I think, you know, in the future as we have more complex environments like 3D simulation is gonna be a bigger part of every, every business's >>Business. You know, just as an aside, we were talking on the analyst segment that speeds and feeds are back and the old days and the data center days was like, we don't wanna talk about speeds and feeds about solutions and you know, the outcomes when you get the cloud, it was like, okay, get the workloads over there, but people want faster and lower cost performance workloads gotta be running at at high performance. And, and there's a real discussion around those. Let's unpack security data performance. What, what does that mean for customers? Because again, I get the workloads run fast. That's great. What else is behind the curtain, so to speak from a customer standpoint? >>Absolutely. Well I think if you're gonna move all your workloads to the cloud, you know, security is a really big area that's important. It's important to every one of our enterprise companies customers. Actually it's important to all of our customers and we've been working, you know, since the beginning of AWS to really create and build the most secure global infrastructure. And you know, as our customers have moved mission critical workloads, we've built out a lot more capabilities and now we have a whole portfolio of security services. And what we announced today is kind of game changing. The service called Security Lake, which brings together, you know, an ecosystem of security data in a format that's open. So you can share data between all of these sources and it's gonna give folks the opportunity to really be able to analyze data, find threats faster, and just kind of know their security posture. And I think, you know, as we talked about today, you don't wanna think about the cloud as unfathomable, the unfathomable, you really need to know that security. And I think that like a lot of things we discussed, security is a data opportunity, right? And I think we, we had a section on on data, but really if you look at the keynote across security, across solutions, across the purpose built things we made, it's all, it all comes down to data and it's really the, the transformational element that our customers >>Are. I mean the data secured is very integral part good call out there. And I, I wanna just double down on that real quick because I remember in 2014 I interviewed Steven Schmidt when he was the CSOs and back then in 2014, if you remember the conversation was this, the clouds not secure, gotta be on premises. Now in today's keynote, Adam says, and he laid out the whole global security footprint. There's a lot going on that Amazon has now become more secure than on-prem. He actually made that statement. So, and then plus you got thousands of security partners, third party partners, you got the open cyber security framework which you guys co-found with all the other, so you got securities not as a team sport, this is what they, they said yes, yes. What does that mean for customers? Because now this is a big deal. >>Well I think for customers, I mean it means nothing but goodness, right? But all of these thousands of security partners have really innovated and created solutions that our customers are using. But they all have different types of data in different silos. And to really get a full picture bringing all that data together is really important. And it's not easy today. You know, log data from different sources, data from detection services and really what customers want is an easier way to get it all together. Which is why we have the open OCS F and really analyze using the tools of their choice. And whether that's AWS tools for analytics or it's tools from our partners, customers need to be able to make that choice so that they can feel like their applications and their workloads are the most secure on aws. >>You know, I've been very impressed with guard duty and I've been following Merit Bear's blogs on online. She's in the security team, she's amazing. Shout out to her. She's been pushing guard duty for a long time now there's big news around guard duty. So you got EKS protection, you know, at Coan this was the biggest cloud native issue, the runtime of Kubernetes and inside the container and outside the container detection of threats, right? As a real software supply chain concern. How are you guys marketing that? This is a huge announcement. EKS protection I know is very nuanced but it's pretty big deal. >>It is a big deal. It is a big deal. And guard duty has been kind of like a quiet service that maybe you don't hear a lot about, but has been really, really popular with our customers. Adam mentioned that 85% of, you know, our top 2000 customers are using guard duty today. And it was a big moment. We launched EKS protection, you know, a little bit earlier and the customer uptake on that has been really incredible. And it is because you can protect your Kubernetes cluster, which is really important because so many customers are, you know, part of their migration to the cloud is containers. Yeah. And so we're pretty excited that now we can answer that question of what's going on inside the container. And so you have both, yeah, right. You know that your Kubernetes pluses are good and you know what's going on inside the container and it's just more threats that you can detect and protect >>Yourself from. You know, as an aside, I'm sure you're watching this, but you know, we go to a lot of events, you know, the C I C D pipeline as developers are getting higher velocity coding, it has moved in because of DevOps on the cloud into the C I C D pipeline. So you're seeing that developer takes some of those IT roles in the coding workflow, hence the, the shift left and or container security, which you guys now, now and are driving towards. But the security and the data teams are emerging as a very key element inside the organizational structure. When I sat down with Adam, one of the things he was very adamant about in my conversation was not just digital transformation, business transformation, structural organizational moves are making where it's not a department anymore, it is the company, a technology is the company when you transform. Absolutely. So digital is the process, business is the outcome. This is a really huge message. What's your reaction to that? What's, what can you share extra cuz that's, this is a big part of the thing. He hit it right outta the gate on the front end of the keynote. >>Absolutely. Absolutely. I mean I think, you know, companies have been migrating to the cloud for a while, but I think that this time that we're going through has really accelerated that migration And as part of that, you know, digital transformation has become real for a lot of companies. And it is true what Adam said there is technology transformation involved, there's data transformation involved, but it, it is transforming businesses. And I think if you look at some of the things that Adam talked about, you know, aws, supply chain, security Lake, aws clean rooms, and Omic, aws, omic, you know, those are all examples of data and the ability to work with data transforming different lines of business within a company, transforming horizontal processes like contact centers and like supply chain and also, you know, going into vertical specific solutions. So what it means is that as technology becomes more pervasive, as data becomes more pervasive, businesses are transforming and that means that a lot more people are going to use the cloud and interact with the cloud and they might not want to or be able to kind of use our building blocks. And so what's really exciting that what we're able to do is make cloud more accessible to lines of business folks to analysts, to security folks. So >>It's, yeah, and that's, and that's why I was calling my this this new trend I see as Amazon Classic, my words, not your words, I call the, hey there was classic cloud and then you got the next gen clown, the new next generation. And I was talking with Adrian Cockcroft, former aws, so he's now retired, he's gonna come on later today. He and I were talking, he use this thing of you got a bag of Legos aka primitives or a toy that's been assembled for you glued together, ones out of the box, but they're not mutually exclusive. You can build a durable application and foundation with the building blocks more durable. You can manage it, refine it, but you got the solution that breaks. You don't have as much flexibility but you gotta replace it. That's okay too. So like this is now kind of a new portfolio approach to the cloud. It's very interesting and I think, I think, I think that's what I took away from the keynote is that you can have both. >>Yes, absolutely. You can do both. I mean, we're gonna go full throttle on releasing innovations and pushing the envelope on compute and storage and databases and our core services because they matter. And having, you know, the choice to choose from a wide range of options. I mean that's what, that's what customers need. You know, if you're gonna run hpc, you're gonna run machine learning and you're gonna run your SAP applications or your Windows applications, you need choice of what you know, specific type of instance and compute capabilities. You need to get the price performance. It's, it's definitely not a one size fits all. It's a 600 instance type. Size fits all maybe. >>Exactly. And you got a lot of instance and we'll get to that in a second. Yeah, I love the themes. I love this keynote themes you had like at first space, but I get the whole data, then you look at it, you can look at it differently. Really good metaphor, the ocean one I love with the security because he mentioned you can have the confidence to explore go deep snorkeling versus scuba and knowing how much oxygen you have. I mean, so really cool metaphor made me think very provocative. So again, this is kind of why people go to AWS because you now have these, these abilities to do things differently, depend on the context of what products you're working with. Yes. Explain why that was the core theme. Was there any rationale behind that? Was it just how you guys saw it? I mean that was pretty clever. >>Well, I think that, you know, we're, we're talking about environments and I think in this world, you know, there's uncertainty in a lot of places and we really feel like all of us need to be prepared for different types of environments. And so we wanted to explore what that could look like. And I think, you know, we're fascinated by space and the vastness and it is very much like the world of data. I don't know about you, but I actually scuba dive. So I love the depths of the ocean. I loved working on that part. There's extremes, extreme workloads like hpc, extreme workloads like machine learning with the growing models and there's an imagination, which is also one of my favorite areas to explore. >>Yeah. And you use the Antarctica one for about the whole environment and extreme conditions. That's good in the performance. And I love that piece of it. And I want to get into the, some of the things I love the speeds and fee. I think the, the big innovation with the silicon we've been covering as, you know, like a blanket. The, he's got the GRAVITON three 25% faster than GRAVITON two, the C seven GN network intense workloads. This is kind of a big deal. I mean this is one of those things where it might not get picked up in the major press, but the network use cases are significant. Nira has been successful. Share your thoughts on these kinds of innovations because they look kind of small, but they're not, they're >>Big, they're not small for sure, especially at the scale that our customers are, are, are running their applications. Like every little optimization that you can get really makes a huge difference. And I think it's exciting. I mean you hit on, you kind of hit on it when we've been working on silicon for a while now we know that, you know, if we're gonna keep pushing the element, the envelope in these areas, we had to, we had to go down to the silicon. And I think that Nitro has really been what's kind of been a breakthrough for us. You know, reinventing that virtualization layer, offloading security and storage and networking to special purpose chips. And I think that it's not just in the area of network optimization, right? You saw training optimized instances and inference optimized instances and HPC optimized instances. So yeah, we are kind of looking at all the extremes of, of what customers want to do. >>I know you can't talk about the future, but I can almost connect the dots as you're talking. It's like, hmm, specialized instances, specialized chips, maybe programmability of workload, smart intelligence, generative AI, weaving in there. A lot of kind of cool things I can see around the corner around generative AI automation. Hey, go to this instance with that go here. This is kind of what I see kind of coming around the corner. >>And we have some of that with our instance optimizers, our cost optimizer products where, you know, we wanna help customers find the best instance for their workload, get the best utilization they possibly can, you know, cut costs, but still have the great performance. So I don't, I don't know about your future, John, it sounds great, but we have, you know, we're taking steps in that direction today. >>Still look in this code that's gonna be on this code. Okay. Any, okay, I wanna give you one final question. Well, well two questions. One was a comment Adam made, I'd love to get your reaction if you want to tighten your bell, come to the cloud. I thought that was a very interesting nuance. A lot of economic pressure. Cloud is an opportunity to get agile, time to value faster. We had Zs carve cube analyst who's with us earlier said, the more you spend on the cloud, the more you save. That was his line, which I thought was very smart. Spending more doesn't mean you're gonna lose money, means you can save money too. So a lot of cost optimization discussions. Absolutely. Hey, your belt come to the cloud. What does he mean by that? >>Well I think that in, in times where, you know, there's uncertainty and economic conditions, it is, it's really, you know, you sometimes wanna pull back kind of, you know, batten down the hatches. But the cloud really, and we saw this with C you know, if you, if you move to the cloud, not only can you cut costs, but you put yourself in this position where you can continue to innovate and you can be agile and you can be prepared for whatever environment you're in so that you know when things go back or you have a customer needs that and innovation that goes off like you, you can accelerate back up really, really quickly. And I think we talked about Airbnb, that example of how, you know, in, in that really tough time of covid when travel industry wasn't happening so much, you know, they were able to scale back and save money. And then at the same time when, you know, Airbnb's kind of once again travel came back, they were in a position to really, really quickly change with the, the customer needs. >>You know, Lee, it's always great talking with you. You got a lot of energy, you're so smart and we both love products and you're leading the product marketing. We have an Instagram challenge here on the cube. I'm gonna put you on the spot here. Oh my gosh. It's called Instagram. We called a bumper sticker section. We used to call it what's the bumper sticker for reinvent. But we kind of modernized that. If you were gonna do an Instagram reel right now, what would be the Instagram reel for reinvent Keynote day one. As we look for, we got Verner, we'll probably talk about productivity with developers. What's the Instagram reel for reinvent? >>Wow. That means I have to get short with it, right? I am, I'm not always, that's still wrong answer. Yeah, well I think, you know, this is really big day one, so it's excitement, it's, we're glad to be here. We have a lot coming for you. We're super excited. And if you think about it, it's price, performance, it's data, it's security and it's solutions for purpose-built use cases. >>Great job. Congratulations. I love the message. I love how you guys had the theme. I thought it was great. And it's great to see Amazon continue to innovate with, with the, with the, with the innovation on the product side. But as we get into transformation, starting to see these solutions and the ecosystem is thriving and looking forward to hearing the, the new partner, chief Aruba tomorrow. Absolutely. See what she's got a new plan apparently unveiling. So exciting. Everyone's pretty excited. Thanks for coming >>On. Great. Great. Thanks for having >>Me. All right. Leah, here in the cube. You are the cube, the leader in tech coverage. I'm John Fur, your host. More live coverage after the short break. We'll be right back here. Day two of the cube, day one of reinvent. Lot of great action. Three, four days of wall to wall coverage. We'll be right back.

foreign continued coverage of AWS re invent my name is Savannah Peterson and I am very excited to be joined by two brilliant blokes in the space of efficiency and performance whether you're on Prem or in the cloud today's discussion is going to be fascinating please welcome Brad and Simon to the show how are you Simon coming in from the UK how you feeling well thank you excellent and Brad we have you coming in from Seattle how are you this morning doing fine thank you excellent and feeling bookish given your background love that I know that you both really care about efficiency and performance it's a very hot topic both of the show and in the industry right now I'm curious I'm going to open it up with you Simon what challenges and I think you've actually continued to tackle these throughout the course of your career what challenges were you facing and wanting to solve when you started yellow dog um really we're just looking at cloud and coming from an on-premise environment really wanted to be able to make accessing Cloud particularly a volume to be simple and straightforward um if you look at today at the number of instance types available from the major Cloud providers there's more than seven thousand different instance types whereas on-prem you go along you select your processes you select your systems it's already be really easy when you hit the cloud you've just got this amazing amount of choice so really it was all about how can you make Intelligent Decisions for you know are you going to run your workload how to match it with what you've got on premise and that was really the inspiration for Rafael so staying there for just a second what does yellow dog provide customers is a SAS system so um you get to it by accessing through the yellow platform and what it allows people to do is to be able to make Intelligent Decisions about where to run their workload would that be on premise or in the cloud it has a wealth of information it understands the costs the performance the latency and the availability of every different instance type in all different clouds it really allows people to uh to be able to make use of that information provision exactly what they need and to be able to run their workloads yeah it also includes a provisioner and it also includes a scheduler as well which is a cloud native scheduler so it's designed to be able to cope with um with cloud in terms of things like spots and interruptions and be able to uh to reschedule and fail over between clouds if there's ever need to do so yeah that sounds incredible and I know this means a lot for partners like AMD Brad talk to me about the partnership and what this means for AMD for your customers yeah absolutely it you know we're excited to be aligned with the uh with a company like yellow dog it's it's um you know the the importance of compute is becoming more and more prevalent every day and it's it's always been top of mind but especially now when you think about what the uh what the economy and the rest of the world is kind of facing over the next you know probably a year or longer it's so important that um that you're able to maximize your dollars and your spend and doing away with uh with uh with absolute certainty that you've got the right type of people behind you uh ensuring that you're your dollars are being spent very wisely and the great thing about yell dogs that they have tremendous insight into uh into cost optimization computer optimization across the entire Globe their their indexes is quite remarkable and what it does is it allows uh customers to actually see just how performant and cost efficient AMD is so it allows us to really put our best foot forward and and gives customers a chance to understand something that they probably weren't uh more familiar with the fact that uh that AMD uh is a tremendous a tremendous value in the marketplace yeah and and uh Simon can you tell us a little bit more about the yellow dog index I'm glad you brought that up Brad yes the yellow index is uh is essentially it's live it's available for anyone to access you can just go to index.yam.tech and you'll be able to see pretty much every single instance type that's available from all the major Cloud providers and be able to make your selection are you looking for GPU type nodes are you looking for AMD processors are you looking just for performance essentially what you're able to do is create a live view of effectively what's available in different data centers around the world and the price at this moment in time also just uh as Brad mentioned in terms of you know cost efficiency and uh and being taking green values seriously as we should we should do the yellow index also has the ability to be able to see at that point in time where the best place to be at a runner job is based upon the lowest carbon impact of running at this moment in time and that for many organizations gives an amazing Insight in not just about being able to find the the understand fishing processes but being able to ensure the greenest energy possible is powering that process when you want to be able to run your workload it's so powerful what you just said and I think when we exactly it's not just about it's not just about power but it's about place when we are are looking at Global Computing at scale what I know that there's ESG advantages in and ESG being a very hot topic when we're talking about AMW on AWS and and and leveraging tools like yellow dog what other sorts of advantages Beyond being least carbon impactful can your Mutual customers benefit from so it's not like I say there's many other features you know a very important thing when you're running a high performance Computing workload is being able to match the instruction set that you're running on premise and then being able to use that in the cloud as well and also to be able to make Intelligent Decisions of where should something run should would something be more efficient um to build on premise should we always try and maximize our on-premise resources before going into the cloud there's a lot about being able to just be able to make decisions and yellow itself it makes thousands of decisions per second to be in a workout where the the best and most optimized places to to run your workload yeah so Brad you work with a lot of companies at scale what type of scale is possible when leveraging Technologies like AMD and yellow dog combined well you know I love the fact that you mentioned uh you know HPC and it's one of the areas that actually is most exciting for for me personally and for and for AMD with the combination of yellow dog and AWS and AWS launched the very first HPC uh instance type last year and you know we're we're we haven't even begun to answer a question we haven't gotten to see um the full-scale capability in the cloud when it comes to these uh these very coordinated and very refined workloads that are running at massive scale and and uh you know we've got some some products we'll be launched in the near future as well that are incredibly performant and you know to be honest I don't think I don't think we have even come close to seeing the scale relative to somebody's very optimized workloads in HPC uh that that we're capable of so um we're excited we're excited for the next few years to see how how we can wrap in um some of the tremendous success that AMD has had on-prem in these these these massive compute centers and replicating that same success inside AWS with companies like yellow dog it's uh it we're excited to see what uh what's what's going to come forward can you give us a preview of anything on the record that gets you really excited about the future I was going to ask you what what had you looking forward to 2023 and Beyond but nothing well not nothing official of course uh but um I will say this you know AMD has recently successful had the launch for Genoa uh it's our next next-gen release and it is um it is proving to be it absolutely is the dominant compute engine it at this point that exists and you know when you start to couple that with the the prowess of AWS you know you could see that over time becoming something potentially that um you know um can really start to change the compute landscape quite a bit so we're hopeful that you know in the future we'll have something along those lines uh with AWS and others and um we're very uh we're very bullish in that area love it uh Simon what about you you've been passionate about low carbon I.T for a long time is carbon neutral Tech in our future what I realize is a bold and lofty claim for you but feel free to give us any of your future predictions um yeah so well I started here trying to build solutions for you know many years ago so 2006 um I was part of a team that launched the the world's lowest powered Windows PC that was actually based on the AMD technology back then so uh you can tell that AMD have been working on a low power for us for a long time in terms of carbon neutral yes I think um certainly there's a there's a few data centers around the world now that are getting very close to uh to carbon neutral some of which may have already achieved it so that's really interesting but so you know the the second part of that is really the the manufacturer of everything that goes into those Services systems and being able to to get to uh you know a net zero on those over a period of time and when we do that which is yeah not without challenges but but certainly possible then we really will have carbon neutral I.T which will be uh a benefit to everyone you know mankind itself yeah casual statement and I have to say that I wholeheartedly agree I think that it's one of the greater challenges of Our Generation especially as what we're able to do in HPC in particular since we're talking about it is only going to grow and scale and magnitude and the amount of data that we have to organize certain process is is wild even today so I love that I'm curious is there anything that you can share with us that's in the pipeline for Yellow Dog anything coming up in the future that's very exciting um so we're coming up very soon um we're going to release something called um version 4 again log which contains um what we call a resource framework which is all about making sure you've got everything you need before you run a job either on-prem or in the cloud so that might be anything from making sure you've got the right licenses making sure that your data is all in the right location making sure you've got all aspects of your workflow ready before you start launching compute and start really but you know burning through dollars with computer could potentially sat there uh not not doing anything until other tasks keep catch up so we're really excited about this new V4 release which will uh which will come out very soon awesome we can't wait to learn more about that hopefully here again on the cube Brad what do Partnerships with companies like yellowdog meme for you and for the customers that you're able to serve yeah it's it's incredibly important I it's you know there's one of the difficulties in in compute that we have today especially in Cloud compute there's there's so much available at this point I mean there was a point in time it was very simple and straightforward it's not even close to being that anymore green so you know one of the things I love about yellow dog itself is actually it does a great they do a great job of making very complex situations and environments fairly simple to understand especially from a business perspective and so one of the things that we love about it is it actually helps our customers you know the AMD direct customers better understand how to properly use our technology and to get the most out of it and so it's difficult for us to articulate that message because you know we are a Semiconductor Company so sometimes it's a little tough to be able to articulate workloads and applications in the way that our customer base will be able to understand but you know it's it's so critical to have companies like yellow dog in the middle that can actually you know make that translation for us directly to the customer um you know and and especially too when you start thinking about ESG and environmental relationships and I'd like to make a comment and one of the things that is fantastic about AMD AWS and yellow we all share the same Mission and we're very public about those missions about just being better to the to the planet and um you know AMD has taken some very aggressive uh targets through 2025 much beyond anything that the industry has expected and you know because of that we are you know we are the most um we are the most power efficient xa6 product on the marketplace and it's not even close and you know I look forward to the day when uh you know you start looking at instance types inside these public Cloud providers in conjunction with the old dog and you can actually even start to see maybe potentially what that carbon footprint is based on those decisions you make on compute and um you know considering that more than half to spend for everybody is generally compute in these environments it's critical to really know what your true impact in the world is and um it's just one of the best parts about a partnership like this oh what a wonderful note to close on and I love both the Synergy between all the partners on a technology level but most importantly on a mission level because none of it matters if we don't have a planet that we can continue to innovate on so I'm I'm really grateful that you're both here fighting a good fight working together and also making a lot of information available for companies of all different sizes as they're navigating very complex decision trees in and operating their stack so thank you both Simon and Brad I really appreciate your time it's been incredibly insightful and thank you to our audience for tuning in to our continuing coverage of AWS re invent here on thecube my name is Savannah Peterson and I look forward to learning more with you soon foreign [Music]

>> From the CUBE Studios in Palo Alto in Boston, bringing you data driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> A better than expected earnings report in late August got people excited about Snowflake again, but the negative sentiment in the market is weighed heavily on virtually all growth tech stocks and Snowflake is no exception. As we've stressed many times the company's management is on a long term mission to dramatically simplify the way organizations use data. Snowflake is tapping into a multi hundred billion dollar total available market and continues to grow at a rapid pace. In our view, Snowflake is embarking on its third major wave of innovation data apps, while its first and second waves are still bearing significant fruit. Now for short term traders focused on the next 90 or 180 days, that probably doesn't matter. But those taking a longer view are asking, "Should we still be optimistic about the future of this high flyer or is it just another over hyped tech play?" Hello and welcome to this week's Wiki Bond Cube Insights powered by ETR. Snowflake's Quarter just ended. And in this breaking analysis we take a look at the most recent survey data from ETR to see what clues and nuggets we can extract to predict the near term future in the long term outlook for Snowflake which is going to announce its earnings at the end of this month. Okay, so you know the story. If you've been investor in Snowflake this year, it's been painful. We said at IPO, "If you really want to own this stock on day one, just hold your nose and buy it." But like most IPOs we said there will be likely a better entry point in the future, and not surprisingly that's been the case. Snowflake IPOed a price of 120, which you couldn't touch on day one unless you got into a friends and family Delio. And if you did, you're still up 5% or so. So congratulations. But at one point last year you were up well over 200%. That's been the nature of this volatile stock, and I certainly can't help you with the timing of the market. But longer term Snowflake is targeting 10 billion in revenue for fiscal year 2028. A big number. Is it achievable? Is it big enough? Tell you what, let's come back to that. Now shorter term, our expert trader and breaking analysis contributor Chip Simonton said he got out of the stock a while ago after having taken a shot at what turned out to be a bear market rally. He pointed out that the stock had been bouncing around the 150 level for the last few months and broke that to the downside last Friday. So he'd expect 150 is where the stock is going to find resistance on the way back up, but there's no sign of support right now. He said maybe at 120, which was the July low and of course the IPO price that we just talked about. Now, perhaps earnings will be a catalyst, when Snowflake announces on November 30th, but until the mentality toward growth tech changes, nothing's likely to change dramatically according to Simonton. So now that we have that out of the way, let's take a look at the spending data for Snowflake in the ETR survey. Here's a chart that shows the time series breakdown of snowflake's net score going back to the October, 2021 survey. Now at that time, Snowflake's net score stood at a robust 77%. And remember, net score is a measure of spending velocity. It's a proprietary network, and ETR derives it from a quarterly survey of IT buyers and asks the respondents, "Are you adopting the platform new? Are you spending 6% or more? Is you're spending flat? Is you're spending down 6% or worse? Or are you leaving the platform decommissioning?" You subtract the percent of customers that are spending less or churning from those that are spending more and adopting or adopting and you get a net score. And that's expressed as a percentage of customers responding. In this chart we show Snowflake's in out of the total survey which ranges... The total survey ranges between 1,200 and 1,400 each quarter. And the very last column... Oh sorry, very last row, we show the number of Snowflake respondents that are coming in the survey from the Fortune 500 and the Global 2000. Those are two very important Snowflake constituencies. Now what this data tells us is that Snowflake exited 2021 with very strong momentum in a net score of 82%, which is off the charts and it was actually accelerating from the previous survey. Now by April that sentiment had flipped and Snowflake came down to earth with a 68% net score. Still highly elevated relative to its peers, but meaningfully down. Why was that? Because we saw a drop in new ads and an increase in flat spend. Then into the July and most recent October surveys, you saw a significant drop in the percentage of customers that were spending more. Now, notably, the percentage of customers who are contemplating adding the platform is actually staying pretty strong, but it is off a bit this past survey. And combined with a slight uptick in planned churn, net score is now down to 60%. That uptick from 0% and 1% and then 3%, it's still small, but that net score at 60% is still 20 percentage points higher than our highly elevated benchmark of 40% as you recall from listening to earlier breaking analysis. That 40% range is we consider a milestone. Anything above that is actually quite strong. But again, Snowflake is down and coming back to churn, while 3% churn is very low, in previous quarters we've seen Snowflake 0% or 1% decommissions. Now the last thing to note in this chart is the meaningful uptick in survey respondents that are citing, they're using the Snowflake platform. That's up to 212 in the survey. So look, it's hard to imagine that Snowflake doesn't feel the softening in the market like everyone else. Snowflake is guiding for around 60% growth in product revenue against the tough compare from a year ago with a 2% operating margin. So like every company, the reaction of the street is going to come down to how accurate or conservative the guide is from their CFO. Now, earlier this year, Snowflake acquired a company called Streamlit for around $800 million. Streamlit is an open source Python library and it makes it easier to build data apps with machine learning, obviously a huge trend. And like Snowflake, generally its focus is on simplifying the complex, in this case making data science easier to integrate into data apps that business people can use. So we were excited this summer in the July ETR survey to see that they added some nice data and pick on Streamlit, which we're showing here in comparison to Snowflake's core business on the left hand side. That's the data warehousing, the Streamlit pieces on the right hand side. And we show again net score over time from the previous survey for Snowflake's core database and data warehouse offering again on the left as compared to a Streamlit on the right. Snowflake's core product had 194 responses in the October, 22 survey, Streamlit had an end of 73, which is up from 52 in the July survey. So significant uptick of people responding that they're doing business in adopting Streamlit. That was pretty impressive to us. And it's hard to see, but the net scores stayed pretty constant for Streamlit at 51%. It was 52% I think in the previous quarter, well over that magic 40% mark. But when you blend it with Snowflake, it does sort of bring things down a little bit. Now there are two key points here. One is that the acquisition seems to have gained exposure right out of the gate as evidenced by the large number of responses. And two, the spending momentum. Again while it's lower than Snowflake overall, and when you blend it with Snowflake it does pull it down, it's very healthy and steady. Now let's do a little pure comparison with some of our favorite names in this space. This chart shows net score or spending velocity in the Y-axis, an overlap or presence, pervasiveness if you will, in the data set on the X-axis. That red dotted line again is that 40% highly elevated net score that we like to talk about. And that table inserted informs us as to how the companies are plotted, where the dots set up, the net score, the ins. And we're comparing a number of database players, although just a caution, Oracle includes all of Oracle including its apps. But we just put it in there for reference because it is the leader in database. Right off the bat, Snowflake jumps out with a net score of 64%. The 60% from the earlier chart, again included Streamlit. So you can see its core database, data warehouse business actually is higher than the total company average that we showed you before 'cause the Streamlit is blended in. So when you separate it out, Streamlit is right on top of data bricks. Isn't that ironic? Only Snowflake and Databricks in this selection of names are above the 40% level. You see Mongo and Couchbase, they know they're solid and Teradata cloud actually showing pretty well compared to some of the earlier survey results. Now let's isolate on the database data platform sector and see how that shapes up. And for this analysis, same XY dimensions, we've added the big giants, AWS and Microsoft and Google. And notice that those three plus Snowflake are just at or above the 40% line. Snowflake continues to lead by a significant margin in spending momentum and it keeps creeping to the right. That's that end that we talked about earlier. Now here's an interesting tidbit. Snowflake is often asked, and I've asked them myself many times, "How are you faring relative to AWS, Microsoft and Google, these big whales with Redshift and Synapse and Big Query?" And Snowflake has been telling folks that 80% of its business comes from AWS. And when Microsoft heard that, they said, "Whoa, wait a minute, Snowflake, let's partner up." 'Cause Microsoft is smart, and they understand that the market is enormous. And if they could do better with Snowflake, one, they may steal some business from AWS. And two, even if Snowflake is winning against some of the Microsoft database products, if it wins on Azure, Microsoft is going to sell more compute and more storage, more AI tools, more other stuff to these customers. Now AWS is really aggressive from a partnering standpoint with Snowflake. They're openly negotiating, not openly, but they're negotiating better prices. They're realizing that when it comes to data, the cheaper that you make the offering, the more people are going to consume. At scale economies and operating leverage are really powerful things at volume that kick in. Now Microsoft, they're coming along, they obviously get it, but Google is seemingly resistant to that type of go to market partnership. Rather than lean into Snowflake as a great partner Google's field force is kind of fighting fashion. Google itself at Cloud next heavily messaged what they call the open data cloud, which is a direct rip off of Snowflake. So what can we say about Google? They continue to be kind of behind the curve when it comes to go to market. Now just a brief aside on the competitive posture. I've seen Slootman, Frank Slootman, CEO of Snowflake in action with his prior companies and how he depositioned the competition. At Data Domain, he eviscerated a company called Avamar with their, what he called their expensive and slow post process architecture. I think he actually called it garbage, if I recall at one conference I heard him speak at. And that sort of destroyed BMC when he was at ServiceNow, kind of positioning them as the equivalent of the department of motor vehicles. And so it's interesting to hear how Snowflake openly talks about the data platforms of AWS, Microsoft, Google, and data bricks. I'll give you this sort of short bumper sticker. Redshift is just an on-prem database that AWS morphed to the cloud, which by the way is kind of true. They actually did a brilliant job of it, but it's basically a fact. Microsoft Excel, a collection of legacy databases, which also kind of morphed to run in the cloud. And even Big Query, which is considered cloud native by many if not most, is being positioned by Snowflake as originally an on-prem database to support Google's ad business, maybe. And data bricks is for those people smart enough to get it to Berkeley that love complexity. And now Snowflake doesn't, they don't mention Berkeley as far as I know. That's my addition. But you get the point. And the interesting thing about Databricks and Snowflake is a while ago in the cube I said that there was a new workload type emerging around data where you have AWS cloud, Snowflake obviously for the cloud database and Databricks data for the data science and EML, you bring those things together and there's this new workload emerging that's going to be very powerful in the future. And it's interesting to see now the aspirations of all three of these platforms are colliding. That's quite a dynamic, especially when you see both Snowflake and Databricks putting venture money and getting their hooks into the loyalties of the same companies like DBT labs and Calibra. Anyway, Snowflake's posture is that we are the pioneer in cloud native data warehouse, data sharing and now data apps. And our platform is designed for business people that want simplicity. The other guys, yes, they're formidable, but we Snowflake have an architectural lead and of course we run in multiple clouds. So it's pretty strong positioning or depositioning, you have to admit. Now I'm not sure I agree with the big query knockoffs completely. I think that's a bit of a stretch, but snowflake, as we see in the ETR survey data is winning. So in thinking about the longer term future, let's talk about what's different with Snowflake, where it's headed and what the opportunities are for the company. Snowflake put itself on the map by focusing on simplifying data analytics. What's interesting about that is the company's founders are as you probably know from Oracle. And rather than focusing on transactional data, which is Oracle's sweet spot, the stuff they worked on when they were at Oracle, the founder said, "We're going to go somewhere else. We're going to attack the data warehousing problem and the data analytics problem." And they completely re-imagined the database and how it could be applied to solve those challenges and reimagine what was possible if you had virtually unlimited compute and storage capacity. And of course Snowflake became famous for separating the compute from storage and being able to completely shut down compute so you didn't have to pay for it when you're not using it. And the ability to have multiple clusters hit the same data without making endless copies and a consumption/cloud pricing model. And then of course everyone on the planet realized, "Wow, that's a pretty good idea." Every venture capitalist in Silicon Valley has been funding companies to copy that move. And that today has pretty much become mainstream in table stakes. But I would argue that Snowflake not only had the lead, but when you look at how others are approaching this problem, it's not necessarily as clean and as elegant. Some of the startups, the early startups I think get it and maybe had an advantage of starting later, which can be a disadvantage too. But AWS is a good example of what I'm saying here. Is its version of separating compute from storage was an afterthought and it's good, it's... Given what they had it was actually quite clever and customers like it, but it's more of a, "Okay, we're going to tier to storage to lower cost, we're going to sort of dial down the compute not completely, we're not going to shut it off, we're going to minimize the compute required." It's really not true as separation is like for instance Snowflake has. But having said that, we're talking about competitors with lots of resources and cohort offerings. And so I don't want to make this necessarily all about the product, but all things being equal architecture matters, okay? So that's the cloud S-curve, the first one we're showing. Snowflake's still on that S-curve, and in and of itself it's got legs, but it's not what's going to power the company to 10 billion. The next S-curve we denote is the multi-cloud in the middle. And now while 80% of Snowflake's revenue is AWS, Microsoft is ramping up and Google, well, we'll see. But the interesting part of that curve is data sharing, and this idea of data clean rooms. I mean it really should be called the data sharing curve, but I have my reasons for calling it multi-cloud. And this is all about network effects and data gravity, and you're seeing this play out today, especially in industries like financial services and healthcare and government that are highly regulated verticals where folks are super paranoid about compliance. There not going to share data if they're going to get sued for it, if they're going to be in the front page of the Wall Street Journal for some kind of privacy breach. And what Snowflake has done is said, "Put all the data in our cloud." Now, of course now that triggers a lot of people because it's a walled garden, okay? It is. That's the trade off. It's not the Wild West, it's not Windows, it's Mac, it's more controlled. But the idea is that as different parts of the organization or even partners begin to share data that they need, it's got to be governed, it's got to be secure, it's got to be compliant, it's got to be trusted. So Snowflake introduced the idea of, they call these things stable edges. I think that's the term that they use. And they track a metric around stable edges. And so a stable edge, or think of it as a persistent edge is an ongoing relationship between two parties that last for some period of time, more than a month. It's not just a one shot deal, one a done type of, "Oh guys shared it for a day, done." It sent you an FTP, it's done. No, it's got to have trajectory over time. Four weeks or six weeks or some period of time that's meaningful. And that metric is growing. Now I think sort of a different metric that they track. I think around 20% of Snowflake customers are actively sharing data today and then they track the number of those edge relationships that exist. So that's something that's unique. Because again, most data sharing is all about making copies of data. That's great for storage companies, it's bad for auditors, and it's bad for compliance officers. And that trend is just starting out, that middle S-curve, it's going to kind of hit the base of that steep part of the S-curve and it's going to have legs through this decade we think. And then finally the third wave that we show here is what we call super cloud. That's why I called it multi-cloud before, so it could invoke super cloud. The idea that you've built a PAS layer that is purpose built for a specific objective, and in this case it's building data apps that are cloud native, shareable and governed. And is a long-term trend that's going to take some time to develop. I mean, application development platforms can take five to 10 years to mature and gain significant adoption, but this one's unique. This is a critical play for Snowflake. If it's going to compete with the big cloud players, it has to have an app development framework like Snowpark. It has to accommodate new data types like transactional data. That's why it announced this thing called UniStore last June, Snowflake a summit. And the pattern that's forming here is Snowflake is building layer upon layer with its architecture at the core. It's not currently anyway, it's not going out and saying, "All right, we're going to buy a company that's got to another billion dollars in revenue and that's how we're going to get to 10 billion." So it's not buying its way into new markets through revenue. It's actually buying smaller companies that can complement Snowflake and that it can turn into revenue for growth that fit in to the data cloud. Now as to the 10 billion by fiscal year 28, is that achievable? That's the question. Yeah, I think so. Would the momentum resources go to market product and management prowess that Snowflake has? Yes, it's definitely achievable. And one could argue to $10 billion is too conservative. Indeed, Snowflake CFO, Mike Scarpelli will fully admit his forecaster built on existing offerings. He's not including revenue as I understand it from all the new stuff that's in the pipeline because he doesn't know what it's going to look like. He doesn't know what the adoption is going to look like. He doesn't have data on that adoption, not just yet anyway. And now of course things can change quite dramatically. It's possible that is forecast for existing businesses don't materialize or competition picks them off or a company like Databricks actually is able in the longer term replicate the functionality of Snowflake with open source technologies, which would be a very competitive source of innovation. But in our view, there's plenty of room for growth, the market is enormous and the real key is, can and will Snowflake deliver on the promises of simplifying data? Of course we've heard this before from data warehouse, the data mars and data legs and master data management and ETLs and data movers and data copiers and Hadoop and a raft of technologies that have not lived up to expectations. And we've also, by the way, seen some tremendous successes in the software business with the likes of ServiceNow and Salesforce. So will Snowflake be the next great software name and hit that 10 billion magic mark? I think so. Let's reconnect in 2028 and see. Okay, we'll leave it there today. I want to thank Chip Simonton for his input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hove is our Editor in Chief over at Silicon Angle. He does some great editing for us. Check it out for all the news. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch David.vallante@siliconangle.com. DM me @dvellante or comment on our LinkedIn post. And please do check out etr.ai, they've got the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching, thanks for listening and we'll see you next time on breaking analysis. (upbeat music)

>>Hey guys and girls, welcome back to Motor City, Lisa Martin here with John Furrier on the Cube's third day of coverage of Coon Cloud Native Con North America. John, we've had some great conversations over the last two and a half days. We've been talking about identity and security management as a critical need for enterprises within the cloud native space. We're gonna have another quick conversation >>On that. Yeah, we got a great segment coming up from someone who's been in the industry, a long time expert, running a great company. Now it's gonna be one of those pieces that fits into what we call super cloud. Others are calling cloud operating system. Some are calling just Cloud 2.0, 3.0. But there's definitely a major trend happening around how cloud is going Next generation. We've been covering it. So this segment should be >>Great. Let's unpack those trends. One of our alumni is back with us, O Rika Zi, co-founder and CEO of Aerio. Omri. Great to have you back on the >>Cube. Thank you. Great to be here. >>So identity move to the cloud, Access authorization did not talk to us about why you found it assertive, what you guys are doing and how you're flipping that script. >>Yeah, so back 15 years ago, I helped start Azure at Microsoft. You know, one of the first few folks that you know, really focused on enterprise services within the Azure family. And at the time I was working for the guy who ran all of Windows server and you know, active directory. He called it the linchpin workload for the Windows Server franchise, like big words. But what he meant was we had 95% market share and all of these new SAS applications like ServiceNow and you know, Workday and salesforce.com, they had to invent login and they had to invent access control. And so we were like, well, we're gonna lose it unless we figure out how to replace active directory. And that's how Azure Active Directory was born. And the first thing that we had to do as an industry was fix identity, right? Yeah. So, you know, we worked on things like oof Two and Open, Id Connect and SAML and Jot as an industry and now 15 years later, no one has to go build login if you don't want to, right? You have companies like Odd Zero and Okta and one login Ping ID that solve that problem solve single sign-on, on the web. But access Control hasn't really moved forward at all in the last 15 years. And so my co-founder and I who were both involved in the early beginnings of Azure Active directory, wanted to go back to that problem. And that problem is even bigger than identity and it's far from >>Solved. Yeah, this is huge. I think, you know, self-service has been a developer thing that's, everyone knows developer productivity, we've all experienced click sign in with your LinkedIn or Twitter or Google or Apple handle. So that's single sign on check. Now the security conversation kicks in. If you look at with this no perimeter and cloud, now you've got multi-cloud or super cloud on the horizon. You've got all kinds of opportunities to innovate on the security paradigm. I think this is kind of where I'm hearing the most conversation around access control as well as operationally eliminating a lot of potential problems. So there's one clean up the siloed or fragmented access and two streamlined for security. What's your reaction to that? Do you agree? And if not, where, where am I missing that? >>Yeah, absolutely. If you look at the life of an IT pro, you know, back in the two thousands they had, you know, l d or active directory, they add in one place to configure groups and they'd map users to groups. And groups typically corresponded to roles and business applications. And it was clunky, but life was pretty simple. And now they live in dozens or hundreds of different admin consoles. So misconfigurations are rampant and over provisioning is a real problem. If you look at zero trust and the principle of lease privilege, you know, all these applications have these course grained permissions. And so when you have a breach, and it's not a matter of if, it's a matter of when you wanna limit the blast radius of you know what happened, and you can't do that unless you have fine grained access control. So all those, you know, all those reasons together are forcing us as an industry to come to terms with the fact that we really need to revisit access control and bring it to the age of cloud. >>You guys recently, just this week I saw the blog on Topaz. Congratulations. Thank you. Talk to us about what that is and some of the gaps that's gonna help sarto to fill for what's out there in the marketplace. >>Yeah, so right now there really isn't a way to go build fine grains policy based real time access control based on open source, right? We have the open policy agent, which is a great decision engine, but really optimized for infrastructure scenarios like Kubernetes admission control. And then on the other hand, you have this new, you know, generation of access control ideas. This model called relationship based access control that was popularized by Google Zanzibar system. So Zanzibar is how they do access control for Google Docs and Google Drive. If you've ever kind of looked at a Google Doc and you know you're a viewer or an owner or a commenter, Zanzibar is the system behind it. And so what we've done is we've married these two things together. We have a policy based system, OPPA based system, and at the same time we've brought together a directory, an embedded directory in Topaz that allows you to answer questions like, does this user have this permission on this object? And bringing it all together, making it open sources a real game changer from our perspective, real >>Game changer. That's good to hear. What are some of the key use cases that it's gonna help your customers address? >>So a lot of our customers really like the idea of policy based access management, but they don't know how to bring data to that decision engine. And so we basically have a, you know, a, a very opinionated way of how to model that data. So you import data out of your identity providers. So you connect us to Okta or oze or Azure, Azure Active directory. And so now you have the user data, you can define groups and then you can define, you know, your object hierarchy, your domain model. So let's say you have an applicant tracking system, you have nouns like job, you know, know job descriptions or candidates. And so you wanna model these things and you want to be able to say who has access to, you know, the candidates for this job, for example. Those are the kinds of rules that people can express really easily in Topaz and in assertive. >>What are some of the challenges that are happening right now that dissolve? What, what are you looking at to solve? Is it complexity, sprawl, logic problems? What's the main problem set you guys >>See? Yeah, so as organizations grow and they have more and more microservices, each one of these microservices does authorization differently. And so it's impossible to reason about the full surface area of, you know, permissions in your application. And more and more of these organizations are saying, You know what, we need a standard layer for this. So it's not just Google with Zanzibar, it's Intuit with Oddy, it's Carta with their own oddy system, it's Netflix, you know, it's Airbnb with heed. All of them are now talking about how they solve access control extracted into its own service to basically manage complexity and regain agility. The other thing is all about, you know, time to market and, and tco. >>So, so how do you work with those services? Do you replace them, you unify them? What is the approach that you're taking? >>So basically these organizations are saying, you know what? We want one access control service. We want all of our microservices to call that thing instead of having to roll out our own. And so we, you know, give you the guts for that service, right? Topaz is basically the way that you're gonna go implement an access control service without having to go build it the same way that you know, large companies like Airbnb or Google or, or a car to >>Have. What's the competition look like for you guys? I'm not really seeing a lot of competition out there. Are there competitors? Are there different approaches? What makes you different? >>Yeah, so I would say that, you know, the biggest competitor is roll your own. So a lot of these companies that find us, they say, We're sick and tired of investing 2, 3, 4 engineers, five engineers on this thing. You know, it's the gift that keeps on giving. We have to maintain this thing and so we can, we can use your solution at a fraction of the cost a, a fifth, a 10th of what it would cost us to maintain it locally. There are others like Sty for example, you know, they are in the space, but more in on the infrastructure side. So they solve the problem of Kubernetes submission control or things like that. So >>Rolling your own, there's a couple problems there. One is do they get all the corner cases who built a they still, it's a company. Exactly. It's heavy lifting, it's undifferentiated, you just gotta check the box. So probably will be not optimized. >>That's right. As Bezo says, only focus on the things that make your beer taste better. And access control is one of those things. It's part of your security, you know, posture, it's a critical thing to get right, but you know, I wanna work on access control, said no developer ever, right? So it's kind of like this boring, you know, like back office thing that you need to do. And so we give you the mechanisms to be able to build it securely and robustly. >>Do you have a, a customer story example that is one of your go-tos that really highlights how you're improving developer productivity? >>Yeah, so we have a couple of them actually. So there's the largest third party B2B marketplace in the us. Free retail. Instead of building their own, they actually brought in aer. And what they wanted to do with AER was be the authorization layer for both their externally facing applications as well as their internal apps. So basically every one of their applications now hooks up to AER to do authorization. They define users and groups and roles and permissions in one place and then every application can actually plug into that instead of having to roll out their own. >>I'd like to switch gears if you don't mind. I get first of all, great update on the company and progress. I'd like to get your thoughts on the cloud computing market. Obviously you were your legendary position, Azure, I mean look at the, look at the progress over the past few years. Just been spectacular from Microsoft and you set the table there. Amazon web service is still, you know, thundering away even though earnings came out, the market's kind of soft still. You know, you see the cloud hyperscalers just continuing to differentiate from software to chips. Yep. Across the board. So the hyperscalers kicking ass taking names, doing great Microsoft right up there. What's the future? Cuz you now have the conversation where, okay, we're calling it super cloud, somebody calling multi-cloud, somebody calling it distributed computing, whatever you wanna call it. The old is now new again, it just looks different as cloud becomes now the next computer industry, >>You got an operating system, you got applications, you got hardware, I mean it's all kind of playing out just on a massive global scale, but you got regions, you got all kinds of connected systems edge. What's your vision on how this plays out? Because things are starting to fall into place. Web assembly to me just points to, you know, app servers are coming back, middleware, Kubernetes containers, VMs are gonna still be there. So you got the progression. What's your, what's your take on this? How would you share, share your thoughts to a friend or the industry, the audience? So what's going on? What's, what's happening right now? What's, what's going on? >>Yeah, it's funny because you know, I remember doing this quite a few years ago with you probably in, you know, 2015 and we were talking about, back then we called it hybrid cloud, right? And it was a vision, but it is actually what's going on. It just took longer for it to get here, right? So back then, you know, the big debate was public cloud or private cloud and you know, back when we were, you know, talking about these ideas, you know, we said, well you know, some applications will always stay on-prem and some applications will move to the cloud. I was just talking to a big bank and they basically said, look, our stated objective now is to move everything we can to the public cloud and we still have a large private cloud investment that will never go away. And so now we have essentially this big operating system that can, you know, abstract all of this stuff. So we have developer platforms that can, you know, sit on top of all these different pieces of infrastructure and you know, kind of based on policy decide where these applications are gonna be scheduled. So, you know, the >>Operating schedule shows like an operating system function. >>Exactly. I mean like we now, we used to have schedulers for one CPU or you know, one box, then we had schedulers for, you know, kind of like a whole cluster and now we have schedulers across the world. >>Yeah. My final question before we kind of get run outta time is what's your thoughts on web assembly? Cuz that's getting a lot of hype here again to kind of look at this next evolution again that's lighter weight kind of feels like an app server kind of direction. What's your, what's your, it's hyped up now, what's your take on that? >>Yeah, it's interesting. I mean back, you know, what's, what's old is new again, right? So, you know, I remember back in the late nineties we got really excited about, you know, JVMs and you know, this notion of right once run anywhere and yeah, you know, I would say that web assembly provides a pretty exciting, you know, window into that where you can take the, you know, sandboxing technology from the JavaScript world, from the browser essentially. And you can, you know, compile an application down to web assembly and have it real, really truly portable. So, you know, we see for example, policies in our world, you know, with opa, one of the hottest things is to take these policies and can compile them to web assemblies so you can actually execute them at the edge, you know, wherever it is that you have a web assembly runtime. >>And so, you know, I was just talking to Scott over at Docker and you know, they're excited about kind of bringing Docker packaging, OCI packaging to web assemblies. So we're gonna see a convergence of all these technologies right now. They're kind of each, each of our, each of them are in a silo, but you know, like we'll see a lot of the patterns, like for example, OCI is gonna become the packaging format for web assemblies as it is becoming the packaging format for policies. So we did the same thing. We basically said, you know what, we want these policies to be packaged as OCI assembly so that you can sign them with cosign and bring the entire ecosystem of tools to bear on OCI packages. So convergence is I think what >>We're, and love, I love your attitude too because it's the open source community and the developers who are actually voting on the quote defacto standard. Yes. You know, if it doesn't work, right, know people know about it. Exactly. It's actually a great new production system. >>So great momentum going on to the press released earlier this week, clearly filling the gaps there that, that you and your, your co-founder saw a long time ago. What's next for the assertive business? Are you hiring? What's going on there? >>Yeah, we are really excited about launching commercially at the end of this year. So one of the things that we were, we wanted to do that we had a promise around and we delivered on our promise was open sourcing our edge authorizer. That was a huge thing for us. And we've now completed, you know, pretty much all the big pieces for AER and now it's time to commercially launch launch. We already have customers in production, you know, design partners, and you know, next year is gonna be the year to really drive commercialization. >>All right. We will be watching this space ery. Thank you so much for joining John and me on the keep. Great to have you back on the program. >>Thank you so much. It was a pleasure. >>Our pleasure as well For our guest and John Furrier, I'm Lisa Martin, you're watching The Cube Live. Michelle floor of Con Cloud Native Con 22. This is day three of our coverage. We will be back with more coverage after a short break. See that.

>>Good afternoon, friends. My name is Savannah Peterson here in the Cube Studios live from Detroit, Michigan, where we're at Cuban and Cloud Native Foundation, Cloud Native Con all week. Our last interview of the day served me a real treat and one that I wasn't expecting. It turns out that I am in the presence of two caddies. It's a literal episode of Caddy Shack up here on Cube. John Furrier. I don't think the audience knows that you were a caddy. Tell us about your caddy days. >>I used to caddy when I was a kid at the local country club every weekend. This is amazing. Double loops every weekend. Make some bang, two bags on each shoulder. Caddying for the members where you're going. Now I'm >>On show. Just, just really impressive >>Now. Now I'm caddying for the cube where I caddy all this great content out to the audience. >>He's carrying the story of emerging brands and established companies on their cloud journey. I love it. John, well played. I don't wanna waste any more of this really wonderful individual's time, but since we now have a new trend of talking about everyone's Twitter handle here on the cube, this may be my favorite one of the day, if not Q4 so far. Drew, not reply. AKA Drew ne Drew Nielsen, excuse me, there is here with us from Teleport. Drew, thanks so much for being here. >>Oh, thanks for having me. It's great to be here. >>And so you were a caddy on a whole different level. Can you tell us >>About that? Yeah, so I was in university and I got tired after two years and didn't have a car in LA and met a pro golfer at a golf course and took two years off and traveled around caddying for him and tried to get 'em through Q School. >>This is, this is fantastic. So if you're in school and your parents are telling you to continue going to school, know that you can drop out and be a caddy and still be a very successful television personality. Like both of the gentlemen at some point. >>Well, I never said my parents like >>That decision, but we'll keep our day jobs. Yeah, exactly. And one of them is Cloud Native Security. The hottest topic here at the show. Yep. I want to get into it. You guys are doing some really cool things. Are we? We hear Zero Trust, you know, ransomware and we even, I even talked with the CEO of Dockets morning about container security issues. Sure. There's a lot going on. So you guys are in the middle of teleport. You guys have a unique solution. Tell us what you guys got going on. What do you guys do? What's the solution and what's the problem you solve? >>So Teleport is the first and only identity native infrastructure access solution in the market. So breaking that down, what that really means is identity native being the combination of secret list, getting rid of passwords, Pam Vaults, Key Vaults, Yeah. Passwords written down. Basically the number one source of breach. And 50 to 80% of breaches, depending on whose numbers you want to believe are how organizations get hacked. >>But it's not password 1 23 isn't protecting >>Cisco >>Right >>Now. Well, if you think about when you're securing infrastructure and the second component being zero trust, which assumes the network is completely insecure, right? But everything is validated. Resource to resource security is validated, You know, it assumes work from anywhere. It assumes the security comes back to that resource. And we take the combination of those two into identity, native access where we cryptographically ev, validate identity, but more importantly, we make an absolutely frictionless experience. So engineers can access infrastructure from anywhere at any time. >>I'm just flashing on my roommates, checking their little code, changing Bob login, you know, dongle essentially, and how frustrating that always was. I mean, talk about interrupting workflow was something that's obviously necessary, but >>Well, I mean, talk about frustration if I'm an engineer. Yeah, absolutely. You know, back in the day when you had these three tier monolithic applications, it was kind of simple. But now as you've got modern application development environments Yeah, multi-cloud, hybrid cloud, whatever marketing term around how you talk about this, expanding sort of disparate infrastructure. Engineers are sitting there going from system to system to machine to database to application. I mean, not even a conversation on Kubernetes yet. Yeah. And it's just, you know, every time you pull an engineer or a developer to go to a vault to pull something out, you're pulling them out for 10 minutes. Now, applications today have hundreds of systems, hundreds of microservices. I mean 30 of these a day and nine minutes, 270 minutes times 60. And they also >>Do the math. Well, there's not only that, there's also the breach from manual error. I forgot to change the password. What is that password? I left it open, I left it on >>Cognitive load. >>I mean, it's the manual piece. But even think about it, TR security has to be transparent and engineers are really smart people. And I've talked to a number of organizations who are like, yeah, we've tried to implement security solutions and they fail. Why? They're too disruptive. They're not transparent. And engineers will work their way around them. They'll write it down, they'll do a workaround, they'll backdoor it something. >>All right. So talk about how it works. But I, I mean, I'm getting the big picture here. I love this. Breaking down the silos, making engineers lives easier, more productive. Clearly the theme, everyone they want, they be gonna need. Whoever does that will win it all. How's it work? I mean, you deploying something, is it code, is it in line? It's, >>It's two binaries that you download and really it starts with the core being the identity native access proxy. Okay. So that proxy, I mean, if you look at like the zero trust principles, it all starts with a proxy. Everything connects into that proxy where all the access is gated, it's validated. And you know, from there we have an authorization engine. So we will be the single source of truth for all access across your entire infrastructure. So we bring machines, engineers, databases, applications, Kubernetes, Linux, Windows, we don't care. And we basically take that into a single architecture and single access platform that essentially secures your entire infrastructure. But more importantly, you can do audit. So for all of the organizations that are dealing with FedRAMP, pci, hipaa, we have a complete audit trail down to a YouTube style playback. >>Oh, interesting. We're we're California and ccpa. >>Oh, gdpr. >>Yeah, exactly. It, it, it's, it's a whole shebang. So I, I love, and John, maybe you've heard this term a lot more than I have, but identity native is relatively new to me as as a term. And I suspect you have a very distinct way of defining identity. How do you guys define identity internally? >>So identity is something that is cryptographically validated. It is something you have. So it's not enough. If you look at, you know, credentials today, everyone's like, Oh, I log into my computer, but that's my identity. No, it's not. Right. Those are attributes. Those are something that is secret for a period of time until you write it down. But I can't change my fingerprint. Right. And now I >>Was just >>Thinking of, well no, perfect case in point with touch ID on your meth there. Yeah. It's like when we deliver that cryptographically validated identity, we use these secure modules in like modern laptops or servers. Yeah. To store that identity so that even if you're sitting in front of your computer, you can't get to it. But more importantly, if somebody were to take that and try to be you and try to log in with your fingerprint, it's >>Not, I'm not gonna lie, I love the apple finger thing, you know, it's like, you know, space recognition, like it's really awesome. >>It save me a lot of time. I mean, even when you go through customs and they do the face scan now it actually knows who you are, which is pretty wild in the last time you wanna provide ones. But it just shifted over like maybe three months ago. Well, >>As long as no one chops your finger off like they do in the James Bond movies. >>I mean, we try and keep it a light and fluffy here on the queue, but you know, do a finger teams, we can talk about that >>Too. >>Gabby, I was thinking more minority report, >>But you >>Knows that's exactly what I, what I think of >>Hit that one outta bounds. So I gotta ask, because you said you're targeting engineers, not IT departments. What's, is that, because I in your mind it is now the engineers or what's the, is always the solution more >>Targeted? Well, if you really look at who's dealing with infrastructure on a day-to-day basis, those are DevOps individuals. Those are infrastructure teams, Those are site reliability engineering. And when it, they're the ones who are not only managing the infrastructure, but they're also dealing with the code on it and everything else. And for us, that is who is our primary customer and that's who's doing >>It. What's the biggest problem that you're solving in this use case? Because you guys are nailing it. What's the problem that your identity native solution solves? >>You know, right out of the backs we remove the number one source of breach. And that is taking passwords, secrets and, and keys off the board. That deals with most of the problem right there. But there are really two problems that organizations face. One is scaling. So as you scale, you get more secrets, you get more keys, you get all these things that is all increasing your attack vector in real time. Oh >>Yeah. Across teams locations. I can't even >>Take your pick. Yeah, it's across clouds, right? Any of it >>On-prem doesn't. >>Yeah. Any of it. We, and we allow you to scale, but do it securely and the security is transparent and your engineers will absolutely love it. What's the most important thing about this product Engineers. Absolutely. >>What are they saying? What are some of those examples? Anecdotally, pull boats out from engineering. >>You're too, we should have invent, we should have invented this ourselves. Or you know, we have run into a lot of customers who have tried to home brew this and they're like, you know, we spend an in nor not of hours on it >>And IT or they got legacy from like Microsoft or other solutions. >>Sure, yeah. Any, but a lot of 'em is just like, I wish I had done it myself. Or you know, this is what security should be. >>It makes so much sense and it gives that the team such a peace of mind. I mean, you never know when a breach is gonna come, especially >>It's peace of mind. But I think for engineers, a lot of times it deals with the security problem. Yeah. Takes it off the table so they can do their jobs. Yeah. With zero friction. Yeah. And you know, it's all about speed. It's all about velocity. You know, go fast, go fast, go fast. And that's what we enable >>Some of the benefits to them is they get to save time, focus more on, on task that they need to work on. >>Exactly. >>And get the >>Job done. And on top of it, they answer the audit and compliance mail every time it comes. >>Yeah. Why are people huge? Honestly, why are people doing this? Because, I mean, identity is just such an hard nut to crack. Everyone's got their silos, Vendors having clouds have 'em. Identity is the most fragmented thing on >>The planet. And it has been fragmented ever since my first RSA conference. >>I know. So will we ever get this do over? Is there a driver? Is there a market force? Is this the time? >>I think the move to modern applications and to multi-cloud is driving this because as those application stacks get more verticalized, you just, you cannot deal with the productivity >>Here. And of course the next big thing is super cloud and that's coming fast. Savannah, you know, You know that's Rocket. >>John is gonna be the thought leader and keyword leader of the word super cloud. >>Super Cloud is enabling super services as the cloud cast. Brian Gracely pointed out on his Sunday podcast of which if that happens, Super Cloud will enable super apps in a new architectural >>List. Please don't, and it'll be super, just don't. >>Okay. Right. So what are you guys up to next? What's the big hot spot for the company? What are you guys doing? What are you guys, What's the idea guys hiring? You put the plug in. >>You know, right now we are focused on delivering the best identity, native access platform that we can. And we will continue to support our customers that want to use Kubernetes, that want to use any different type of infrastructure. Whether that's Linux, Windows applications or databases. Wherever they are. >>Are, are your customers all of a similar DNA or are you >>No, they're all over the map. They range everything from tech companies to financial services to, you know, fractional property. >>You seem like someone everyone would need. >>Absolutely. >>And I'm not just saying that to be a really clean endorsement from the Cube, but >>If you were doing DevOps Yeah. And any type of forward-leaning shift, left engineering, you need us because we are basically making security as code a reality across your entire infrastructure. >>Love this. What about the team dna? Are you in a scale growth stage right now? What's going on? Absolutely. Sounds I was gonna say, but I feel like you would have >>To be. Yeah, we're doing, we're, we have a very positive outlook and you know, even though the economic time is what it is, we're doing very well meeting. >>How's the location? Where's the location of the headquarters now? With remote work is pretty much virtual. >>Probably. We're based in downtown Oakland, California. >>Woohoo. Bay area representing on this stage right now. >>Nice. Yeah, we have a beautiful office right in downtown Oakland and yeah, it's been great. Awesome. >>Love that. And are you hiring right now? I bet people might be. I feel like some of our cube watchers are here waiting to figure out their next big play. So love to hear that. Absolutely love to hear that. Besides Drew, not reply, if people want to join your team or say hello to you and tell you how brilliant you looked up here, or ask about your caddy days and maybe venture a guest to who that golfer may have been that you were CAD Inc. For, what are the best ways for them to get in touch with you? >>You can find me on LinkedIn. >>Great. Fantastic. John, anything else >>From you? Yeah, I mean, I just think security is paramount. This is just another example of where the innovation has to kind of break through without good identity, everything could cripple. Then you start getting into the silos and you can start getting into, you know, tracking it. You got error user errors, you got, you know, one of the biggest security risks. People just leave systems open, they don't even know it's there. So like, I mean this is just, just identity is the critical linchpin to, to solve for in security to me. And that's totally >>Agree. We even have a lot of customers who use us just to access basic cloud consoles. Yeah. >>So I was actually just gonna drive there a little bit because I think that, I'm curious, it feels like a solution for obviously complex systems and stacks, but given the utility and what sounds like an extreme ease of use, I would imagine people use this for day-to-day stuff within their, >>We have customers who use it to access their AWS consoles. We have customers who use it to access Grafana dashboards. You know, for, since we're sitting here at coupon accessing a Lens Rancher, all of the amazing DevOps tools that are out there. >>Well, I mean true. I mean, you think about all the reasons why people don't adopt this new federated approach or is because the IT guys did it and the world we're moving into, the developers are in charge. And so we're seeing the trend where developers are taking the DevOps and the data and the security teams are now starting to reset the guardrails. What's your >>Reaction to that? Well, you know, I would say that >>Over the top, >>Well I would say that you know, your DevOps teams and your infrastructure teams and your engineers, they are the new king makers. Yeah. Straight up. Full stop. >>You heard it first folks. >>And that's >>A headline right >>There. That is a headline. I mean, they are the new king makers and, but they are being forced to do it as securely as possible. And our job is really to make that as easy and as frictionless as possible. >>Awesome. >>And it sounds like you're absolutely nailing it. Drew, thank you so much for being on the show. Thanks for having today. This has been an absolute pleasure, John, as usual a joy. And thank all of you for tuning in to the Cube Live here at CU Con from Detroit, Michigan. We look forward to catching you for day two tomorrow.

(upbeat music) >> Welcome back, everyone. Live coverage here at KubeCon + CloudNativeCon here in Detroit, Michigan. I'm John Furrier, your host of theCUBE for special one-on-one conversation with Scott Johnston, who's the CEO of Docker, CUBE alumni, been around the industry, multiple cycles of innovation, leading one of the most important companies in today's industry inflection point as Docker what they've done since they're, I would say restart from the old Docker to the new Docker, now modern, and the center of the conversation with containers driving the growth of Kubernetes. Scott, great to see you. Thanks for coming on theCUBE. >> John, thanks for the invite. Glad to be here. >> You guys have had great success this year with extensions. Docker as a business model's grown. Congratulations, you guys are monetizing well. Pushing up over 50 million. >> Thank you. >> I hear over pushing a hundred million maybe. What the year to the ground will tell me, but it's good sign. Plus you've got the community and nurturing of the ecosystem continuing to power away and open source is not stopping. It's thundering away growth. Younger generation coming in. >> That's right. >> Developer tool chain that you have has become consistent. Almost de facto standard. Others are coming in the market. A lot of competition emerging. You got a lot going on right now. What's going on? >> Well, I know it's fantastic time in our industry. Like all companies are becoming software companies. That means they need to build new applications. That means they need developers to be productive and to be safely productive. And we, and this wonderful CNCF ecosystem are right in the middle of that trend, so it's fantastic. >> So you have millions of developers using Docker. >> Tens of millions. >> Tens of millions of developed Docker and as the market's changing, I was commenting before we came on camera, and I'd love to get your reaction, comment on it. You guys represent the modernization of containers, open source. You haven't really changed how open source works, but you've kind of modernized it. You're starting to see developers at the front lines, more and more power going to developers. >> Scott: That's right. >> They want self-service. They vote with their code. >> That's right. >> They vote with their actions. >> Scott: That's right. >> And if you take digital transformation to its conclusion, it's not IT serves the business or it's a department, the company is IT. >> That's right. >> The company is the application, which means developers are running everything. >> Yes, yes. I mean, one of the jokes, not jokes in the valley is that Tesla is in a car company. Tesla is a computer company that happens to have wheels on the computer. And I think we can smile at that, but there's so many businesses, particularly during COVID, that realize that. What happened during COCID? If you're going to the movies, nope, you're now going to Netflix. If you're going to the gym, now you're doing Peloton. So this realization that like I have to have a digital game, not just on the side, but it has to be the forefront of my business and drive my business. That realization is now any industry, any company across the board. >> We've been reporting aggressively for past three years now. Even now we're calling some things supercloud. If companies, if they don't realize that IT is not a department, they will probably be out of business. >> That's a hundred percent. >> It's going to transform into full on invisible infrastructure. Infrastructure as code, whatever you want to call that going, configuration, operations, developers will set the pace. This has a lot to do with some of your success. You're at the beginning of it. This is just the beginning. What can you talk about that in your mind is contributing to the success of Docker? I know you're going to say team, everything, I get that, but like what specifically in the industry is driving Docker's success right now? >> Well, it did. We did have a fantastic team. We do have a fantastic team and that is one of the reasons, primary reasons our success. But what is also happening, John, is because there's a demand for applications, I'll just throw it out there. 750 million new applications are coming in the market in the next two years. That is more applications that have been developed in the entire 40 years history of IT. So just think about the productivity demands that are coming at developers. And then you also see the need to do so safely, meaning ship quickly, but ship safely. And yet 90 some percent of every application consists of open source components that are now on attack surface for criminals. And so typically our industry has had to say one or the other, okay, you can ship quickly but not safely, or you can ship safely, but it's not going to go fast. And one of the reasons I think Docker is where it is today is that we're able to offer both. We're able to unlock that you can ship quickly, safely using Docker, using the Docker toolchain, using integrations we have with all the wonderful partners here at CNCF that is unique. And that's a big reason why we're seeing the success we're seeing. >> And you're probably pleased with extensions this year. >> Yes. >> The performance of extensions that you launched at DockerCon '22. >> Yes. Well, extensions are part of that story and that developers have multiple tools. They want choice, developers like choice to be productive and Docker is part of that, but it's not the only solution. And so Docker extensions allow the monitoring providers and the observability and if you want a separate Kubernetes stack, like all of that flexibility, extensions allows. And again, offers the power and the innovation of this ecosystem to be used in a Docker development and context. >> Well, I want to get into some of the details of some of your products and how they're evolving. But first I want to get your thoughts on the trend line here that we reported at the opening segment. The hot story is WebAssembly, the Wasm, which really got a lot of traction or interest. People enthous about it. >> Interest, yeah. >> Lot of enthusiasm. Confidence we'll see how that evolves, but a lot of enthusiasm for sure. I've never seen something this hyped up since Envoy, in my opinion. So a lot of interest from developers. What is Wasm or WebAssembly is actually what it is, but Wasm is the codeword or nickname. What is Wasm? >> So in brief, WebAssembly is a new application type, full stop. And it's just enough of the components that you need and it's just a binary format that is very, very secure. And so it's lightweight, it's fast and secure. And so it opens up a lot of interesting use cases for developer, particularly on the edge. Another use case for Wasm is in the browser. Again, lightweight, fast, secure also. >> John: Sounds like an app server to me. >> And so we think it's a very, very interesting trend. And you ask, Okay, what's Docker's role in that? Well, Docker has been around eight years now, eight plus years, tens of millions developers using it. They've already made investments in skills, talent, automation, toolchains, pipelines. And Docker started with Linux containers as we know, then brought that same experience to Windows containers, then brought it to serverless functions. About 25% of Amazon Lambdas are OCI image containers. And so we were seeing that trend. We were also seeing the community actually without any prompting from us, start to fork and play with Docker and apply it to Wasm. And we're like, Huh, that's interesting. What if we helped get behind that trend, such that you changed just one line of a Docker file, now you're able to produce Wasm objects instead of Linux containers and just bring that same easy to use. >> So that's not a competition to Docker's? >> Not a competition at all. In fact, very complimentary. We showed off on Monday at the Wasm day, how in the same Docker compose application, multi-service application. One service is delivered via Linux container, Another service is delivered via Wasm. >> And Wasm is what? Multiple languages? 'Cause what is it? >> Yes. So the binary can be compiled from multiple languages. So RAS, JavaScript, on and on and on. At the end of the day, it's a smaller binary that provides a function, typically a single function that you can stand up and deploy on an edge. You can stand up and deploy on the server side or stand up and deploy on the browser. >> So from a container standpoint, from your customer standpoint, what a Linux container is is a similar thing to what a Wasm container is. >> They could implement the same function. That's right. Now a Linux container can have more capabilities that a function might not have, but that's. >> John: From a workflow standpoint. >> That's right. And that's more of a use case by use case standpoint. What we serve is we serve developers and we started out serving developers with Linux containers, then Windows containers, then Lambdas, now Wasm. Whatever other use case, what other application type comes along, we want to be there to serve developers. >> So one of the things I want to get your thoughts on, because this has come up in a couple CUBE interviews before, and we were talking before we came on camera, is developers want ease of use and simplicity. They don't want more steps to do things. They don't want things harder. >> That's right. So the classic innovation is reduce the time it takes to do something, reduce the steps, make it easier. That's a formula of success. >> Scott: That's right. >> When you start adding more toolchains into the mix, you get tool sprawl. So that's not really, that's antithesis to developer. So the argument is, okay, do I have to use a new tool chain for Wasm? Is that a fact or no? >> That's exactly right. That was what we were seeing and we thought, well, how can Docker help with this situation? And Docker can help by bringing the same existing toolchain that developers are already familiar with. The same automation, the same pipelines. And just by changing a line of Docker file, changing a single line of composed file, now they get the power of Wasm unlocked in the very same tools they were using before. >> So your position is, hey, don't adopt some toolchain for Wasm. You can just do it in line with Docker. >> No need to, no need to. We're providing it right there out of the box, ready for them. >> That's raise and extend, as they would say, build Microsoft strategy there. That's nice. Okay, so let's get back into like the secure trusted 'cause that was another theme at DockerCon. We covered that deeply. Software supply chain, I was commenting on my intro with Savannah and Lisa that at some point open source means so plentiful. You might not have to write code. You got to glue together. So as code proliferates, the question what's in there? >> That's right. This is what they call the software supply chain. You've been all over this. Where are we with this? Is it harder now? Is it easier? Was there progress? Take us through what's the state of the art. I think we're early on this one, John, in the industry because I think the realization of how much open source is inside a given app is just now hitting consciousness. And so the data we have is that for any given application, anywhere from 75 to 85% is actually not unique to the developer or the organization. It's open source components that they have put together. And it's really down to that last 15, 25%, which is their own unique code that they're adding on top of all this open source code. So right there, it's like, aha, that's a pretty interesting profile or distribution of value, which means those open source components, where are they finding them? How are they integrating them? How do they know those open source components are going to be supported and trusted and secured? And that's the challenge for us as an industry right now is to make it just obvious where to get the components, how safe they are, who's standing behind them, and how easy it is to assemble them into a working application. >> All right. So the question that I had specifically on security 'cause this had come up before. All good on the trusted and I think that message is evergreen. It's a north star. That's a north star for you. How are you making images more secure and how are you enabling organizations to identify security issues in containers? Can you share your strategy and thoughts on that particular point? >> Yes. So there's a range of things in the secure software supply chain and it starts with, are you starting with trusted open source components that you know have support, that you know are secured? So in Docker Hub today, we have 14 million applications, but a subset of that, we've worked with the upstream providers to basically designate as trusted open source content. So this is the Docker official images, Docker verified publisher images, Docker sponsored open source. And those different categories have levels of certification assurance that they must go through. Generate an SBOM, so you know what's inside that container. It has to be scanned by a scanning tool and those scanning results have to be made available. >> John: Are you guys scanning that? >> So we provide a scanner, they can use another scanner as long as they publish the results of that scan. And then the whole thing is signed. >> Are you publishing the results on your side too? >> Yeah, we published our results through an open database that's accessible to all. >> Free. >> Free, a hundred percent free. You come in and you can see every image on hub. >> So I'm a user, for free I can see security vulnerabilities that are out there that have been identified. >> By version, by layer, all the way through. And you can see tracking all the way back to the package that's upstream. So you know how to remediate and we provide recommendations on how to remediate that with the latest version. >> John: And you don't charge for that. >> We don't charge for that. We do not charge for that. And so that's the trusted upstream. >> So organization can look at the scan, they can look at the scan data and hopefully, what happens if they're not scanned? >> So we provide scanning tools both for the local environments for Docker Desktop, as well as for hub. So if you want to do your own scan, so for example, when you're that developer adding the 15, 25%, you got to scan your stuff as well. Not just leave it up to the already scanned components. And so we provide tools there. We also provide tools to track the packages that that developer might be including in their custom code, all the way back upstream to whatever MPM repo or what have you that they picked up. And then if there's a CVE 30 days later, we also track that as well. We say, Hey, that package was was safe 29 days ago, but today CVE just came out, better upgrade to the latest version and get that out there. So basically if you get down to it, it's like start with trusted components and then have observability not just on the moment. >> And scan all the time. >> Scan all the time and scanning gives you that observability and importantly not just at that moment, but through the lifecycle of the application, through lifecycle of the artifact. So end-to-end 24/7 observability of the state of your supply chain. That's what's key, John. >> That's the best practice. >> That's the key. That's the key. >> Awesome, I agree. That's great. Well, I'm glad we've dug into that's super important. Obviously organizations can get that scanning that's exceed the vulnerabilities, that can take action. That's going to be a big focus here for you, security. It's not going to stop, is it? >> It's never going to stop because criminals are incentive to keep attacking. And so it's the gift that keeps on giving, if you will. >> Okay, so let's get into some of the products. Docker Desktop seems to be doing well. Docker Hub has always been a staple of it. And how's that going? >> Yeah, Docker Hub has 18 million monthly actives hitting it and that's growing by double digits year over year. And what they're finding, going back to our previous thread, John, is that they're coming there for the trusted content. In fact, those three categories that I referenced earlier are about 2000 applications of the 14 million. And yet they represent 56% of the 15 billion downloads a month from Docker Hub. Meaning developers are identifying that, hey, I want trusted source. We raise those in the search results and we have a visual cue. And so that's the big driver of hub's growth right now, is I want trusted content, where do I go? I go to Hub, download that trusted open source and I'm ready to go. >> I have been seeing some chatter on the internet and some people's sharing that they're looking at other places, besides hub, to do some things. What's your message to folks out there around Docker Hub? Why Docker Hub and desktop together? 'Cause you mentioned the toolchain before, but those two areas, I know they've been around for a while, you continue to work on them. What's the message to the folks out there about stay with the hub? >> Sure. I mean the beauty of our ecosystem is that it's interoperable. The standards for build, share and run, we're all using them here at CNCF. So yes, there's other registries. What we would say is we have the 18 million monthly active that are pulling, we have the worldwide distribution that is 24/7 high, five nines reliability, and frankly, we're there to provide choice. And so yes, we have have our trusted content, but for example, the Tanzu apps, they also distribute through us. Red Hat applications also distribute through us because we have the reach and the distribution and offer developers choice of Dockers content, choice of Red Hats content, choice of VMware's, choice of Bitnami, so on so forth. So come to the hub for the distribution to reach and that the requirements we have for security that we put in place for our publishers, give users and publishers an extra degree of assurance. >> So the Docker Hub is an important part of the system? >> Scott: Yes, very much so. >> And desktop, what's new with desktop? >> So desktop of course is the other end of the spectrum. So if trusted components start up on Docker Hub, developers are pulling them down to the desktop to start assembling their application. And so the desktop gives that developer all the tools he or she needs to build that modern application. So you can have your build tooling, your debug tooling, your IDE sitting alongside there, your Docker run, your Docker compose up. And so the loop that we see happening is the dev will have a database they download from hub, a front-end, they'll add their code to it and they'll just rapidly iterate. They'll make a change, stand it up, do a unit test, and when they're satisfied do a git commit, off it goes into production. >> And your goal obviously is to have developers stay with Docker for their toolchain, their experience, make it their home base. >> And their trusted content. That's right. And the trusted content and the extensions are part of that. 'Cause the extensions provide complimentary tooling for that local experience. >> You guys have done an amazing job. I want to give you personal props. I've been following Docker from the beginning when they had the pivot, they sold the enterprise to Mirantis, went back to the roots, modernized, riding the wave. You guys are having a good time. I got to ask the question 'cause people always want to know 'cause open source is about transparency. How you guys making your money? Business is good. How's that work and what was the lucky, what was the not lucky strike, but what was the aha moment? What was the trigger that just made you just kick in this new monetization growth wave? >> So the monetization is per seat, per developer seat. And that changed in November 2019. We were pricing on the server side before, and as you said, we sold that off. And what changed is some of the trends we were talking about that the realization by all organizations that they had to become software companies. And Docker provided the productivity in an engineered desktop product and the trusted content, it provided the productivity safely to developers. And frankly then we priced it at a rate that is very reasonable from an economic standpoint. If you look at developer productivity, developers are paid anywhere from 150 to 300 to 400, 500,000 even higher. >> But when you're paying your developers that much, then productivity is a premium. And what we were asking for from companies from a licensing standpoint was really a modest relative to the making those developers product. >> It's not like Oracle. I mean talk about extracting the value out of the customer. But your point is your positioning is always stay quarter of the open source, but for companies that adopt the structural change to be developer first, a software company, there's a premium to pay because you devalue there. >> And need the tooling to roll it out at scales. So the companies are paying us. They're rolling it out to tens of thousand developers, John. So they need management, they need visibility, they need guardrails that are all around the desktop. So, but just to put a stat on it, so to your point about open source and the freemium wheel working, of our 13 million Docker accounts, 12 are free, about a million are paid for accounts. And that's by design because the open source. >> And you're not gouging developers per se, it's just, not gouging anyone, but you're not taking money out of their hands. It's the company. >> If the company is paying for their productivity so that they can build safely. >> More goodness more for the developer. >> That's right. That's right. >> Gouging would be more like the Oracle strategy. Don't comment. You don't need to comment. I keep saying that, but it's not like you're taxing. It's not a heavy. >> No, $5 a month, $9 a month, $24 a month depending on level. >> But I think the big aha to me and in my opinion is that you nailed the structural change culturally for a company. If they adopt the software ecosystem approach for transforming their business, they got to pay for it. So like a workflow, it's a developer. >> It's another tool. I mean, do they pay for their spreadsheet software? Do they pay for their back office ERP software? They do >> That's my point. >> to make those people popular or sorry, make those people successful, those employees successful. This is a developer tool to make developer successful. >> It's a great, great business model. Congratulations. What's next for you guys? What are you looking for? You just had your community events, you got DockerCon coming up next year. What's on the horizon for you? Put a plugin for the company. What are you looking for? Hiring? >> Yeah, so we're growing like gangbusters. We grew from 60 with the reset. We're now above 300 and we're continuing to grow despite this economic climate. Like our customers are very much investing in software capabilities. So that means they're investing in Docker. So we're looking for roles across the board, software engineers, product managers, designers, marketing, sales, customer success. So if you're interested, please reach out. The next year is going to be really interesting because we're bringing to market products that are doubling down on these areas, doubling down a developer productivity, doubling down on safety to make it even more just automatic that developers just build so they don't have to think about it. They don't need a new tool just to be safer. We hinted a bit about automating SBOM creation. You can see more of that pull through. And in particular, developers want to make the right decision. Everyone comes to work wanting to make the right decision. But what they often lack is context. They often lack like, well, is this bit of code safe or not? Or is this package that I just downloaded over here safe or not? And so you're going to see us roll out additional capabilities that give them very explicit contextual guidance of like, should you use this or not? Or here's a better version over here, a safer version over there. So stay tuned for some exciting stuff. >> It's going to be a massive developer growth wave coming even bigger we've ever seen. Final questions just while I got you here. Where do you see WebAssembly, Wasm going? If you had to throw a dart at the board out a couple years, what does it turn into? >> Yeah, so I think it's super exciting. Super exciting, John. And there's three use cases today. There's browser, there's edge, and there's service side in the data center of the cloud. We see the edge taking off in the next couple years. It's just such a straight line through from what they're doing today and the value that standing up a single service on the edge go. The service side needs some work on the Wasm runtime. The Wasm runtime is not multi-threaded today. And so there's some deep, deep technical work that's going on. The community's doing a fantastic job, but that'll take a while to play through. Browsers also making good progress. There's a component model that Wasm's working on that'll really ignite the industry. That is going to take another couple years as well. So I'd say let's start with the edge use case. Let's get everyone excited about that value proposition. And these other two use cases will come along. >> It'll all work itself out in the wash as open source always does. Scott Johnston, the Chief Executive Officer at Docker. Took over at the reset, kicking butt and taking names. Congratulations. You guys are doing great. Continue to power the developer movement. Thanks for coming on. >> John, thanks so much. Pleasure to be here. >> We're bringing you all the action here. Extracting the signal from the noise. I'm John Furrier, day one of three days of wall-to-wall live coverages. We'll be back for our next guest after this short break. (gentle music)

(upbeat music) >> Welcome back to Chicago, guys and gals. Lisa Martin here in Chicago with Ansible Fest 2022 with John Furrier. John, we've had great conversations. This is day two of our coverage. We were here yesterday. >> Yeah. >> We're here today. We've gotten to talk with great folks in the Ansible community, the partner ecosystem customers. We've broken some news that they've talked about. Now we're going to talk about industrial automation, IT/OT convergence. What excites you about this conversation? >> Yeah, this is going to be a great segment. This is one of the feature keynote presenters, customer Rockwell. Huge in OT, IT, edge, robotics, plants, equipment. Everything that we probably have, they do. This guest has really great story about what's cutting edge and what's relevant in the edge and IT slash automation area. Super relevant. Looking forward to the segment. >> Yes, please welcome David Rapini, the Global PlantPAx business manager at Rockwell Automation. David, great to have you on theCUBE. >> Thank you. Nice to be here. >> Give the audience a bit of an overview of Rockwell Automation and then let's dig into what you guys are doing there. >> Sure. Rockwell Automation probably is the largest global automation provider of equipment focused exclusively on automation. About 22,000 employees. About 7 billion kind of revenue numbers. We make, basically, controllers for the automation industry, industrialized software, power drives, you know, of the robotics content, smart cart kind of applications. >> Lisa: And what are your key industries that you're covering? >> Wow, so that's a broad market. So we do a lot of different industries. So we cover, obviously, oil and gas, life science, water, wastewater. We do automotive. So just about any industry, actually. Any place that needs industrial automation covering any type of manufacturing process or any type of process application. We're pretty much there. >> John: You know, it's interesting, IOT has been a word, in and of things, light bulb, wearables, industrial IOT where you're in is a really key space. It's physical plants. Sometimes it's sensitive critical infrastructure for governments, businesses. >> David: Exactly. >> I mean there's running stuff. >> David: Definitely. >> This is huge. >> Yeah, and it's a big area for us, like getting that data, you know, everybody talks about analytics and what the world's going to be happening to in that IT, OT space. And Rockwell's really well positioned at that lower level where we actually own the data, create the data for all that analytics that you're talking about. >> What was your main message today on stage? I want to replay that here and then get into it because I think this is really, we're starting to see, real traction in adoption, in automation, cloud scale, edges happening, exploding. What was your key message on stage today? >> Yeah, I think it's that the world's really changing in that space. You know, five years ago you would have had a completely different message around, you know that connectivity and having that content actually delivered to that space and having, like even the connectivity to that OT space makes people uncomfortable in that world because there's obviously moving pieces, you know, damage to equipment, you know God forbid any types of explosions or things like that on bad environmental type conditions. So we're working in that space to really make those connections much more open and now that those connections are starting to happen and we're getting more and more comfort with that, in that layer, there's a lot more we can do in that space which is kind of why we're here. >> And talk about why Ansible and what it's going to be able to unlock for Rockwell to be able to achieve. >> Sure. There's a lot of areas that we want to play with, but our, in Ansible but our first targets are really our, primarily our servers. So there's a lot of edge based servers out there, you know, we call them a pass server, which is a process automation system server. And there's an engineering workstation operator, which are those main core servers. Some of them are redundant, you know, the OT guys to them it's a burden to manage that content. They're good at making, you know, oil and gas they know how to do water wastewater. They know how to build cars. But managing servers, you know, not in their wheelhouse. >> John: Not in their wheelhouse.(laughs) >> Exactly. Right. So having that capability and that connection to get down there gives us some power with Ansible to go ahead and start building them initially. So making that initial builds out of the gate. That makes them really consistent and built together, so every application looks and feels the same and they know what they're going to get when their servers power up. So that's a big one. But, but just maintain them, keeping them patched, you know keeping security vulnerabilities down. You know, I was in a facility not long ago that was still running Windows 2000. Right. So, you know, they have an application there that's just working. It works. They don't want to touch it and it's been running for 20 years, so why touch it? Right. So this was going to kind of hopefully break that challenge. >> Make sure that you keep that password handy. (laughs) >> David: Yeah, exactly right. (laughs) >> We've had (indistinct) people leave. What about the security aspect is OT has been locked down, mindset, hardened, end to end, supply chains, vetted. Everything's kind of tight on the old OT model. Relatively secure when you get to IT, you mentioned vulnerabilities but the innovation's there too. So how does that reconcile for you? What's your reaction to that? >> Yeah, we see a big move there, right? So it used to be they were always head head to head butting heads IT, OT, you know it focuses on, you know, keeping the system secure keeping the data down, locked down, and reliable. OT focuses more on production, right? Making sure they hit their numbers in the production. So oftentimes, you know, having it push out a patch in the middle of production line in the middle of a day and rebooting a server shuts down production and you know, that those kind of conflicts. Yeah, exactly. So those conflicts were, were pretty common. There's still a lot of that there, but it's getting better. Yeah, right. And I see more and more of that working together as a team to, to solve a lot of those challenges. And honestly, I keep going back to the analytics angle and the diagnostics and that world of deep data, you know, big data kind of mining, you know, without the IT space to cover that the cloud data storage, the horsepower. >> If you had to kind of like rank the complexity 'cause we were just talking before you came on about things got to get complex before they can get simpler 'cause the inflection points bring that new capability. What's some of the complexities that you're seeing that are going to be either abstracted away or solved with some of these new technologies like Ansible and others that are coming fast? Cause at the end of the day it's got to still be easier. It's not going to be hard. That can't be harder. >> Yeah. So I'll give you a real world example that's a little embarrassing. So today we deliver our past servers as a solution and we we provide that as a VM image that people start with as the first building block. But once you start to deploy that and actually connect it with the rest of the infrastructure, hook it up to our factory talk directory, hook it up to the DNS service, once you start doing all that work it's about 700 mouse clicks that somebody has to know what they're doing to actually spin it up the rest of the way and get it connected with Ansible. We're cutting that number like in half is the hope. So, and, and we're going to continue to expand that and make it even less work for the users to >> Talk about skill gap issue. The training alone on that is to have the right people. >> That's the second big piece, right? So, so those OT people typically don't have that skill set. So you have to have a fairly high skilled level person to do that work. We're hoping to take that, that work off of them and put that on on answer. >> Yeah, that sounds pretty consistent. Do you think, is that the, kind of the consistency of the problem space is that the OT just has a different goal and they just need something to be invisible and easy, like electricity? >> Yeah, I think so. Especially in this world, right? In that OT space, right in in that IT space. Sorry. Yeah, so, so managing servers and things like that it's just is not what they want to want to deal with and it's not what they went to school for and it's not what they're doing when their job when they get hired. Right. Yeah. >> It sounds to me like Rockwell Automation is a facilitator of the IT and OT folks coming together and actually working better together, maybe understanding each other's requirements, goals, objectives. >> Most definitely. So we have, you know we are offering a lot of cloud content now. We're continuing to expand that content. We're working with a lot of different IT departments and OT departments to try to marriage those two groups together to try to bring that stuff together. We have a partnership with Cisco where we actually, you know, industrialize you know, some of their switch components and sell that as as part of our content and that relationship gives us a big inroad with a lot of the IT departments. >> That's important to have that be able to speak the language of both sides. >> Yeah, definitely. Right. Knowing and understanding the terminology and just being able to know the challenges that IT guys face as well as the OTs is really a big component of what we do. >> You know, one of the questions I wanted to ask and 'cause the keynote was very cool, but you made a comment that your claim to fame was that you wrote the code for the Spider-Man ride at Universal. Tell a story. How does that work? I'm just, I've rode them many times. So take us through that little journey. >> Yeah, so I, every time people ask me what we do for a living and automation, you know, I can talk about, you know, making cars and things like that, but it doesn't ring troops. So I did do a lot of work on Spider-Man Ride which is at Universal Studios, you know it was a real challenge, making sure you know how that connections actually work and make, I did most of the motion control content for that to make the movements of the cars, you know, seamless with the backgrounds. Definitely a lot of fun. So those kind of projects are rare but they're really fun when you get those. >> I hope you have a free pass for any time you want to go on it. >> I don't, unfortunately. >> Oh, you should. >> I try to get in the backrooms all the time at that facility but it's rare to hear. >> I mean it's like, it's a high end rollercoaster machine. It's like, I mean that is this robotics, industrial cause, this, I mean it's an intense ride. >> It is, and you know, you never move more than like eight feet on that whole ride and it feels like you've dropped, you know 2000 feet out of the sky on some of that content. So it's really amazing. I will say it's a little dated. I've been writing on the part of my team worked on the the Harry Potter rides, which are much next generation. >> I couldn't get on that one, line was too long. >> It's a long way, but it's worth it. >> Dave I asked you a question on the future for people watching who are new observing industrial IOT. What's the most important story going on in your world today? Is it the transformation? Is it the standards? Is it the security? What's, what are the top two or three things that are going on that are really transformative right now in automating at the edge? >> I really want to say that it's standardization. It's about using open standards and standard protocols to deliver content in a reusable fashion. So, you know, having custom proprietary content like a lot of automation suppliers or even like a lot of other industries, it's hard to maintain. It doesn't work well with other products. It's great 'cause you can do a lot of flexibility what you want to do, but at the end of the day it's about keeping the thing running and hooking it up to other components so that open standards based solution you'll see us spending more energy on you know, part of the Ansible open community thing is nice in that space as well. And you'll see us doing more stuff in that place that, that play. >> Talk about your influence there in the community. You know, we, we've been talking the last couple of days about Ansible is nothing if not the power of the community, the collaboration within. Talk about being able to influence that and what that means to you personally as well as to Rockwell. >> Yeah, so open communities are big for us. We have, you know, obviously a customer advisory boards and things like that that we deal with but we also have an open community forum where people can share dialogues and share ideas. We have large events, we have a process solution users group events where we bring in, you know hundreds not thousands of engineering people to to talk to all of these problems that they're facing. And it's not a Rockwell event it's a, you know, community event, right. Where we actually are talking about, you know what industry problem people are seeing. And a lot of the IT OT convergence thing is really top of mind. A lot of people say no minds especially the cybersecurity content. >> What are some of the things that you heard the last couple of days, announcement wise? Obviously big news coming out today that excites you about the direction that Ansible's going and how it's responding to the community. >> Yeah, I think a lot of their feedback that they get and sitting a lot of these sessions, they get a lot of interesting feedback from their customer base. And reacting to that I think is very high on their priority list. And what I've been seeing here, you know, some of the AI stuff that they were showing on automatically, like defining some of the scripts for their code that intelligence behind a lot of that content was amazing. I see a lot of that moving forward. And we're heading the same direction at Rockwell as well with more AI in our company. >> The data's a big story too coming out of all the devices, analytics, great stuff. >> Yeah, I'm pulling that data up into the cloud space and trying to do something valuable with all that data. It's, you know, we've had big data for a long time. It's just figuring out analytics and how to actually act on that data and get it back into the control to do something with. >> It's all getting aside. My serious question on this is that, you know is it the year finally OT and IT converge? Seems like it's been trying for about a decade. >> Yeah, that's a tough one to answer. So I would say it's not there yet. I think there's still a lot of conflict in that space. You know, the OT guys still have a long history of that space, but as you see more retirement and more people phasing out of that and younger crowds coming in, you know the automation space is ripe for that kind of transition because coming out of college, you know jumping into automation isn't always the top of the notch. A lot of people want to go work at the big Amazons or wherever. >> A lot, a lot of stuff going on in space. It's pretty cool. A lot of physical, I've seen a lot more machine learning and physical devices in the industry we've been reporting on. It's interesting. I think it's close to a tipping point because we saw machine learning and the trivial apps like chat bots never really took off, yep. Just expert systems basically, but they're not really going the next level. So now they are, you're starting to see more, you know of wisdom projects, you know, different models being adopted. So I see AI now kind of kicking up similar to OT IT. >> Yeah, most definitely. You know, we have a lot of projects in that space like doing predictive analysis on, let's just say something simple like a pump, right? If you have pumps out there that are running for years and years, but you notice that there's a trend that on day 305 or whatever you know, a bearing starts to fail all the time. You know, that kind of analytics can start doing predictive maintenance content and start pushing out work orders in advance before the things fail because downtime costs millions of dollars for these maintenance. >> Downtime also incidents, right? So you never know, right? >> Exactly. Right, right. So it's good to have that safety net at least from a manufacturing perspective. >> Final question for me. What's the most exciting thing going on in your world right now if you had to kind of pick one thing that you're most jazzed up about? >> I have to say, you know, Rockwell's doing a big shift to cloud-based content and more big data numbers like we were just talking about for that AI. That complexity of what you can do with AI and the value that you can do to like just, you know if I can make quality of a product a half a percent better that's millions of dollars for my customer and I see us doing a lot of work in that space and moving that forward. That's big for me, I think. >> And what are some of that, my last question is what are some of the impacts that customers can expect from that? >> Yeah, so everything from downtime to product quality to increasing production rates and volumes of data that come out. You know, we do something called model predictive control that does, you know, very tight control on control loops to improve like just the general product quality with a lot of the big data numbers that are coming in on that. So you'll see us moving more in that space too to improve you know, product quality and then downtime. >> And really driving outcomes, business outcomes for your customers. David, thank you so much for joining us on the program, sharing what Rockwell Automation is doing. We appreciate your insights, your time and we want to keep watching to see what comes next. >> Sure. Glad to be here. It's great. Thank you very much. >> Our pleasure. For our guest, our John Furrier. I'm Lisa Martin. You've watched theCUBE Live in Chicago, Ansible Fest 2022. Thanks for watching. (gentle music)