(bright upbeat music) >> Hello and welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier here in Palo Alto, California Studio and remoting is a great guest CUBE alumni, co-founder, technical co-founder and she's also the VP of Product at Platform9 Systems. It's a company pioneering Kubernetes infrastructure, been doing it for a long, long time. Madhura Maskasky, thanks for coming on theCUBE. Appreciate you. Thanks for coming on. >> Thank you for having me. Always exciting. >> So I always... I love interviewing you for many reasons. One, you're super smart, but also you're a co-founder, a technical co-founder, so entrepreneur, VP of product. It's hard to do startups. (John laughs) Okay, so everyone who started a company knows how hard it is. It really is and the rewarding too when you're successful. So I want to get your thoughts on what's it like being an entrepreneur, women in tech, some things you've done along the way. Let's get started. How did you get into your career in tech and what made you want to start a company? >> Yeah, so , you know, I got into tech long, long before I decided to start a company. And back when I got in tech it was very clear to me as a direction for my career that I'm never going to start a business. I was very explicit about that because my father was an entrepreneur and I'd seen how rough the journey can be. And then my brother was also and is an entrepreneur. And I think with both of them I'd seen the ups and downs and I had decided to myself and shared with my family that I really want a very well-structured sort of job at a large company type of path for my career. I think the tech path, tech was interesting to me, not because I was interested in programming, et cetera at that time, to be honest. When I picked computer science as a major for myself, it was because most of what you would consider, I guess most of the cool students were picking that as a major, let's just say that. And it sounded very interesting and cool. A lot of people were doing it and that was sort of the top, top choice for people and I decided to follow along. But I did discover after I picked computer science as my major, I remember when I started learning C++ the first time when I got exposure to it, it was just like a light bulb clicking in my head. I just absolutely loved the language, the lower level nature, the power of it, and what you can do with it, the algorithms. So I think it ended up being a really good fit for me. >> Yeah, so it clicked for you. You tried it, it was all the cool kids were doing it. I mean, I can relate, I did the same thing. Next big thing is computer science, you got to be in there, got to be smart. And then you get hooked on it. >> Yeah, exactly. >> What was the next level? Did you find any blockers in your way? Obviously male dominated, it must have been a lot of... How many females were in your class? What was the ratio at that time? >> Yeah, so the ratio was was pretty, pretty, I would say bleak when it comes to women to men. I think computer science at that time was still probably better compared to some of the other majors like mechanical engineering where I remember I had one friend, she was the single girl in an entire class of about at least 120, 130 students or so. So ratio was better for us. I think there were maybe 20, 25 girls in our class. It was a large class and maybe the number of men were maybe three X or four X number of women. So relatively better. Yeah. >> How about the job when you got into the structured big company? How did that go? >> Yeah, so, you know, I think that was a pretty smooth path I would say after, you know, you graduated from undergrad to grad school and then when I got into Oracle first and VMware, I think both companies had the ratios were still, you know, pretty off. And I think they still are to a very large extent in this industry, but I think this industry in my experience does a fantastic job of, you know, bringing everybody and kind of embracing them and treating them at the same level. That was definitely my experience. And so that makes it very easy for self-confidence, for setting up a path for yourself to thrive. So that was it. >> Okay, so you got an undergraduate degree, okay, in computer science and a master's from Stanford in databases and distributed systems. >> That's right. >> So two degrees. Was that part of your pathway or you just decided, "I want to go right into school?" Did it go right after each other? How did that work out? >> Yeah, so when I went into school, undergrad there was no special major and I didn't quite know if I liked a particular subject or set of subjects or not. Even through grad school, first year it wasn't clear to me, but I think in second year I did start realizing that in general I was a fan of backend systems. I was never a front-end person. The backend distributed systems really were of interest to me because there's a lot of complex problems to solve, and especially databases and large scale distributed systems design in the context of database systems, you know, really started becoming a topic of interest for me. And I think luckily enough at Stanford there were just fantastic professors like Mendel Rosenblum who offered operating system class there, then started VMware and later on I was able to join the company and I took his class while at school and it was one of the most fantastic classes I've ever taken. So they really had and probably I think still do a fantastic curriculum when it comes to distributor systems. And I think that probably helped stoke that interest. >> How do you talk to the younger girls out there in elementary school and through? What's the advice as they start to get into computer science, which is changing and still evolving? There's backend, there's front-end, there's AI, there's data science, there's no code, low code, there's cloud. What's your advice when they say what's the playbook? >> Yeah, so I think two things I always say, and I share this with anybody who's looking to get into computer science or engineering for that matter, right? I think one is that it's, you know, it's important to not worry about what that end specialization's going to be, whether it's AI or databases or backend or front-end. It does naturally evolve and you lend yourself to a path where you will understand, you know, which systems, which aspect you like better. But it's very critical to start with getting the fundamentals well, right? Meaning all of the key coursework around algorithm, systems design, architecture, networking, operating system. I think it is just so crucial to understand those well, even though at times you make question is this ever going to be relevant and useful to me later on in my career? It really does end up helping in ways beyond, you know, you can describe. It makes you a much better engineer. So I think that is the most important aspect of, you know, I would think any engineering stream, but definitely true for computer science. Because there's also been a trend more recently, I think, which I'm not a big fan of, of sort of limited scoped learning, which is you decide early on that you're going to be, let's say a front-end engineer, which is fine, you know. Understanding that is great, but if you... I don't think is ideal to let that limit the scope of your learning when you are an undergrad phrase or grad school. Because later on it comes back to sort of bite you in terms of you not being able to completely understand how the systems work. >> It's a systems kind of thinking. You got to have that mindset of, especially now with cloud, you got distributed systems paradigm going to the edge. You got 5G, Mobile World Congress recently happened, you got now all kinds of IOT devices out there, IP of devices at the edge. Distributed computing is only getting more distributed. >> That's right. Yeah, that's exactly right. But the other thing is also happens... That happens in computer science is that the abstraction layers keep raising things up and up and up. Where even if you're operating at a language like Java, which you know, during some of my times of programming there was a period when it was popular, it already abstracts you so far away from the underlying system. So it can become very easier if you're doing, you know, Java script or UI programming that you really have no understanding of what's happening behind the scenes. And I think that can be pretty difficult. >> Yeah. It's easy to lean in and rely too heavily on the abstractions. I want to get your thoughts on blockers. In your career, have you had situations where it's like, "Oh, you're a woman, okay seat at the table, sit on the side." Or maybe people misunderstood your role. How did you deal with that? Did you have any of that? >> Yeah. So, you know, I think... So there's something really kind of personal to me, which I like to share a few times, which I think I believe in pretty strongly. And which is for me, sort of my personal growth began at a very early phase because my dad and he passed away in 2012, but throughout the time when I was growing up, I was his special little girl. And every little thing that I did could be a simple test. You know, not very meaningful but the genuine pride and pleasure that he felt out of me getting great scores in those tests sort of et cetera, and that I could see that in him, and then I wanted to please him. And through him, I think I build that confidence in myself that I am good at things and I can do good. And I think that just set the building blocks for me for the rest of my life, right? So, I believe very strongly that, you know, yes, there are occasions of unfair treatment and et cetera, but for the most part, it comes from within. And if you are able to be a confident person who is kind of leveled and understands and believes in your capabilities, then for the most part, the right things happen around you. So, I believe very strongly in that kind of grounding and in finding a source to get that for yourself. And I think that many women suffer from the biggest challenge, which is not having enough self-confidence. And I've even, you know, with everything that I said, I've myself felt that, experienced that a few times. And then there's a methodical way to get around it. There's processes to, you know, explain to yourself that that's actually not true. That's a fake feeling. So, you know, I think that is the most important aspect for women. >> I love that. Get the confidence. Find the source for the confidence. We've also been hearing about curiosity and building, you mentioned engineering earlier, love that term. Engineering something, like building something. Curiosity, engineering, confidence. This brings me to my next question for you. What do you think the key skills and qualities are needed to succeed in a technical role? And how do you develop to maintain those skills over time? >> Yeah, so I think that it is so critical that you love that technology that you are part of. It is just so important. I mean, I remember as an example, at one point with one of my buddies before we started Platform9, one of my buddies, he's also a fantastic computer scientists from VMware and he loves video games. And so he said, "Hey, why don't we try to, you know, hack up a video game and see if we can take it somewhere?" And so, it sounded cool to me. And then so we started doing things, but you know, something I realized very quickly is that I as a person, I absolutely hate video games. I've never liked them. I don't think that's ever going to change. And so I was miserable. You know, I was trying to understand what's going on, how to build these systems, but I was not enjoying it. So, I'm glad that I decided to not pursue that. So it is just so important that you enjoy whatever aspect of technology that you decide to associate yourself with. I think that takes away 80, 90% of the work. And then I think it's important to inculcate a level of discipline that you are not going to get sort of... You're not going to get jaded or, you know, continue with happy path when doing the same things over and over again, but you're not necessarily challenging yourself, or pushing yourself, or putting yourself in uncomfortable situation. I think a combination of those typically I think works pretty well in any technical career. >> That's a great advice there. I think trying things when you're younger, or even just for play to understand whether you abandon that path is just as important as finding a good path because at least you know that skews the value in favor of the choices. Kind of like math probability. So, great call out there. So I have to ask you the next question, which is, how do you keep up to date given all the changes? You're in the middle of a world where you've seen personal change in the past 10 years from OpenStack to now. Remember those days when I first interviewed you at OpenStack, I think it was 2012 or something like that. Maybe 10 years ago. So much changed. How do you keep up with technologies in your field and resources that you rely on for personal development? >> Yeah, so I think when it comes to, you know, the field and what we are doing for example, I think one of the most important aspect and you know I am product manager and this is something I insist that all the other product managers in our team also do, is that you have to spend 50% of your time talking to prospects, customers, leads, and through those conversations they do a huge favor to you in that they make you aware of the other things that they're keeping an eye on as long as you're doing the right job of asking the right questions and not just, you know, listening in. So I think that to me ends up being one of the biggest sources where you get tidbits of information, new things, et cetera, and then you pursue. To me, that has worked to be a very effective source. And then the second is, you know, reading and keeping up with all of the publications. You guys, you know, create a lot of great material, you interview a lot of people, making sure you are watching those for us you know, and see there's a ton of activities, new projects keeps coming along every few months. So keeping up with that, listening to podcasts around those topics, all of that helps. But I think the first one I think goes in a big way in terms of being aware of what matters to your customers. >> Awesome. Let me ask you a question. What's the most rewarding aspect of your job right now? >> So, I think there are many. So I think I love... I've come to realize that I love, you know, the high that you get out of being an entrepreneur independent of, you know, there's... In terms of success and failure, there's always ups and downs as an entrepreneur, right? But there is this... There's something really alluring about being able to, you know, define, you know, path of your products and in a way that can potentially impact, you know, a number of companies that'll consume your products, employees that work with you. So that is, I think to me, always been the most satisfying path, is what kept me going. I think that is probably first and foremost. And then the projects. You know, there's always new exciting things that we are working on. Even just today, there are certain projects we are working on that I'm super excited about. So I think it's those two things. >> So now we didn't get into how you started. You said you didn't want to do a startup and you got the big company. Your dad, your brother were entrepreneurs. How did you get into it? >> Yeah, so, you know, it was kind of surprising to me as well, but I think I reached a point of VMware after spending about eight years or so where I definitely packed hold and I could have pushed myself by switching to a completely different company or a different organization within VMware. And I was trying all of those paths, interviewed at different companies, et cetera, but nothing felt different enough. And then I think I was very, very fortunate in that my co-founders, Sirish Raghuram, Roopak Parikh, you know, Bich, you've met them, they were kind of all at the same journey in their careers independently at the same time. And so we would all eat lunch together at VMware 'cause we were on the same team and then we just started brainstorming on different ideas during lunchtime. And that's kind of how... And we did that almost for a year. So by the time that the year long period went by, at the end it felt like the most logical, natural next step to leave our job and to, you know, to start off something together. But I think I wouldn't have done that had it not been for my co-founders. >> So you had comfort with the team as you knew each other at VMware, but you were kind of a little early, (laughing) you had a vision. It's kind of playing out now. How do you feel right now as the wave is hitting? Distributed computing, microservices, Kubernetes, I mean, stuff you guys did and were doing. I mean, it didn't play out exactly, but directionally you were right on the line there. How do you feel? >> Yeah. You know, I think that's kind of the challenge and the fun part with the startup journey, right? Which is you can never predict how things are going to go. When we kicked off we thought that OpenStack is going to really take over infrastructure management space and things kind of went differently, but things are going that way now with Kubernetes and distributed infrastructure. And so I think it's been interesting and in every path that you take that does end up not being successful teaches you so much more, right? So I think it's been a very interesting journey. >> Yeah, and I think the cloud, certainly AWS hit that growth right at 2013 through '17, kind of sucked all the oxygen out. But now as it reverts back to this abstraction layer essentially makes things look like private clouds, but they're just essentially DevOps. It's cloud operations, kind of the same thing. >> Yeah, absolutely. And then with the edge things are becoming way more distributed where having a single large cloud provider is becoming even less relevant in that space and having kind of the central SaaS based management model, which is what we pioneered, like you said, we were ahead of the game at that time, is becoming sort of the most obvious choice now. >> Now you look back at your role at Stanford, distributed systems, again, they have world class program there, neural networks, you name it. It's really, really awesome. As well as Cal Berkeley, there was in debates with each other, who's better? But that's a separate interview. Now you got the edge, what are some of the distributed computing challenges right now with now the distributed edge coming online, industrial 5G, data? What do you see as some of the key areas to solve from a problem statement standpoint with edge and as cloud goes on-premises to essentially data center at the edge, apps coming over the top AI enabled. What's your take on that? >> Yeah, so I think... And there's different flavors of edge and the one that we focus on is, you know, what we call thick edge, which is you have this problem of managing thousands of as we call it micro data centers, rather than managing maybe few tens or hundreds of large data centers where the problem just completely shifts on its head, right? And I think it is still an unsolved problem today where whether you are a retailer or a telecommunications vendor, et cetera, managing your footprints of tens of thousands of stores as a retailer is solved in a very archaic way today because the tool set, the traditional management tooling that's designed to manage, let's say your data centers is not quite, you know, it gets retrofitted to manage these environments and it's kind of (indistinct), you know, round hole kind of situation. So I think the top most challenges are being able to manage this large footprint of micro data centers in the most effective way, right? Where you have latency solved, you have the issue of a small footprint of resources at thousands of locations, and how do you fit in your containerized or virtualized or other workloads in the most effective way? To have that solved, you know, you need to have the security aspects around these environments. So there's a number of challenges that kind of go hand-in-hand, like what is the most effective storage which, you know, can still be deployed in that compact environment? And then cost becomes a related point. >> Costs are huge 'cause if you move data, you're going to have cost. If you move compute, it's not as much. If you have an operating system concept, is the data and state or stateless? These are huge problems. This is an operating system, don't you think? >> Yeah, yeah, absolutely. It's a distributed operating system where it's multiple layers, you know, of ways of solving that problem just in the context of data like you said having an intermediate caching layer so that you know, you still do just in time processing at those edge locations and then send some data back and that's where you can incorporate some AI or other technologies, et cetera. So, you know, just data itself is a multi-layer problem there. >> Well, it's great to have you on this program. Advice final question for you, for the folks watching technical degrees, most people are finding out in elementary school, in middle school, a lot more robotics programs, a lot more tech exposure, you know, not just in Silicon Valley, but all around, you're starting to see that. What's your advice for young girls and people who are getting either coming into the workforce re-skilled as they get enter, it's easy to enter now as they stay in and how do they stay in? What's your advice? >> Yeah, so, you know, I think it's the same goal. I have two little daughters and it's the same principle I try to follow with them, which is I want to give them as much exposure as possible without me having any predefined ideas about what you know, they should pursue. But it's I think that exposure that you need to find for yourself one way or the other, because you really never know. Like, you know, my husband landed into computer science through a very, very meandering path, and then he discovered later in his career that it's the absolute calling for him. It's something he's very good at, right? But so... You know, it's... You know, the reason why he thinks he didn't pick that path early is because he didn't quite have that exposure. So it's that exposure to various things, even things you think that you may not be interested in is the most important aspect. And then things just naturally lend themselves. >> Find your calling, superpower, strengths. Know what you don't want to do. (John chuckles) >> Yeah, exactly. >> Great advice. Thank you so much for coming on and contributing to our program for International Women's Day. Great to see you in this context. We'll see you on theCUBE. We'll talk more about Platform9 when we go KubeCon or some other time. But thank you for sharing your personal perspective and experiences for our audience. Thank you. >> Fantastic. Thanks for having me, John. Always great. >> This is theCUBE's coverage of International Women's Day, I'm John Furrier. We're talking to the leaders in the industry, from developers to the boardroom and everything in between and getting the stories out there making an impact. Thanks for watching. (bright upbeat music)

>> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (ambient music) >> Lisa: Hey everyone, welcome back to Barcelona, Spain. It's theCUBE Live at MWC 23. Lisa Martin with Dave Vellante. This is day two of four days of cube coverage but you know that, because you've already been watching yesterday and today. We're going to have a great conversation next with EnterpriseWeb and Red Hat. We've had great conversations the last day and a half about the Telco industry, the challenges, the opportunities. We're going to unpack that from this lens. Please welcome Dave Duggal, founder and CEO of EnterpriseWeb and Azhar Sayeed is here, Senior Director Solution Architecture at Red Hat. >> Guys, it's great to have you on the program. >> Yes. >> Thank you Lisa, >> Great being here with you. >> Dave let's go ahead and start with you. Give the audience an overview of EnterpriseWeb. What kind of business is it? What's the business model? What do you guys do? >> Okay so, EnterpriseWeb is reinventing middleware, right? So the historic middleware was to build vertically integrated stacks, right? And those stacks are now such becoming the rate limiters for interoperability for so the end-to-end solutions that everybody's looking for, right? Red Hat's talking about the unified platform. You guys are talking about Supercloud, EnterpriseWeb addresses that we've built middleware based on serverless architecture, so lightweight, low latency, high performance middleware. And we're working with the world's biggest, we sell through channels and we work through partners like Red Hat Intel, Fortnet, Keysight, Tech Mahindra. So working with some of the biggest players that have recognized the value of our innovation, to deliver transformation to the Telecom industry. >> So what are you guys doing together? Is this, is this an OpenShift play? >> Is it? >> Yeah. >> Yeah, so we've got two projects right her on the floor at MWC throughout the various partners, where EnterpriseWeb is actually providing an application layer, sorry application middleware over Red Hat's, OpenShift and we're essentially generating operators so Red Hat operators, so that all our vendors, and, sorry vendors that we onboard into our catalog can be deployed easily through the OpenShift platform. And we allow those, those vendors to be flexibly composed into network services. So the real challenge for operators historically is that they, they have challenges onboarding the vendors. It takes a long time. Each one of them is a snowflake. They, you know, even though there's standards they don't all observe or follow the same standards. So we make it easier using models, right? For, in a model driven process to on boards or streamline that onboarding process, compose functions into services deploy those services seamlessly through Red Hat's OpenShift, and then manage the, the lifecycle, like the quality of service and the SLAs for those services. >> So Red Hat obviously has pretty prominent Telco business has for a while. Red Hat OpenStack actually is is pretty popular within the Telco business. People thought, "Oh, OpenStack, that's dead." Actually, no, it's actually doing quite well. We see it all over the place where for whatever reason people want to build their own cloud. And, and so, so what's happening in the industry because you have the traditional Telcos we heard in the keynotes that kind of typical narrative about, you know, we can't let the over the top vendors do this again. We're, we're going to be Apifi everything, we're going to monetize this time around, not just with connectivity but the, but the fact is they really don't have a developer community. >> Yes. >> Yet anyway. >> Then you have these disruptors over here that are saying "Yeah, we're going to enable ISVs." How do you see it? What's the landscape look like? Help us understand, you know, what the horses on the track are doing. >> Sure. I think what has happened, Dave, is that the conversation has moved a little bit from where they were just looking at IS infrastructure service with virtual machines and OpenStack, as you mentioned, to how do we move up the value chain and look at different applications. And therein comes the rub, right? You have applications with different requirements, IT network that have various different requirements that are there. So as you start to build those cloud platform, as you start to modernize those set of applications, you then start to look at microservices and how you build them. You need the ability to orchestrate them. So some of those problem statements have moved from not just refactoring those applications, but actually now to how do you reliably deploy, manage in a multicloud multi cluster way. So this conversation around Supercloud or this conversation around multicloud is very >> You could say Supercloud. That's okay >> (Dave Duggal and Azhar laughs) >> It's absolutely very real though. The reason why it's very real is, if you look at transformations around Telco, there are two things that are happening. One, Telco IT, they're looking at partnerships with hybrid cloud, I mean with public cloud players to build a hybrid environment. They're also building their own Telco Cloud environment for their network functions. Now, in both of those spaces, they end up operating two to three different environments themselves. Now how do you create a level of abstraction across those? How do you manage that particular infrastructure? And then how do you orchestrate all of those different workloads? Those are the type of problems that they're actually beginning to solve. So they've moved on from really just putting that virtualizing their application, putting it on OpenStack to now really seriously looking at "How do I build a service?" "How do I leverage the catalog that's available both in my private and public and build an overall service process?" >> And by the way what you just described as hybrid cloud and multicloud is, you know Supercloud is what multicloud should have been. And what, what it originally became is "I run on this cloud and I run on this cloud" and "I run on this cloud and I have a hybrid." And, and Supercloud is meant to create a common experience across those clouds. >> Dave Duggal: Right? >> Thanks to, you know, Supercloud middleware. >> Yeah. >> Right? And, and so that's what you guys do. >> Yeah, exactly. Exactly. Dave, I mean, even the name EnterpriseWeb, you know we started from looking from the application layer down. If you look at it, the last 10 years we've looked from the infrastructure up, right? And now everybody's looking northbound saying "You know what, actually, if I look from the infrastructure up the only thing I'll ever build is silos, right?" And those silos get in the way of the interoperability and the agility the businesses want. So we take the perspective as high level abstractions, common tools, so that if I'm a CXO, I can look down on my environments, right? When I'm really not, I honestly, if I'm an, if I'm a CEO I don't really care or CXO, I don't really care so much about my infrastructure to be honest. I care about my applications and their behavior. I care about my SLAs and my quality of service, right? Those are the things I care about. So I really want an EnterpriseWeb, right? Something that helps me connect all my distributed applications all across all of the environments. So I can have one place a consistency layer that speaks a common language. We know that there's a lot of heterogeneity down all those layers and a lot of complexity down those layers. But the business doesn't care. They don't want to care, right? They want to actually take their applications deploy them where they're the most performant where they're getting the best cost, right? The lowest and maybe sustainability concerns, all those. They want to address those problems, meet their SLAs meet their quality service. And you know what, if it's running on Amazon, great. If it's running on Google Cloud platform, great. If it, you know, we're doing one project right here that we're demonstrating here is with with Amazon Tech Mahindra and OpenShift, where we took a disaggregated 5G core, right? So this is like sort of latest telecom, you know net networking software, right? We're deploying pulling elements of that network across core, across Amazon EKS, OpenShift on Red Hat ROSA, as well as just OpenShift for cloud. And we, through a single pane of deployment and management, we deployed the elements of the 5G core across them and then connected them in an end-to-end process. That's Telco Supercloud. >> Dave Vellante: So that's an O-RAN deployment. >> Yeah that's >> So, the big advantage of that, pardon me, Dave but the big advantage of that is the customer really doesn't care where the components are being served from for them. It's a 5G capability. It happens to sit in different locations. And that's, it's, it's about how do you abstract and how do you manage all those different workloads in a cohesive way? And that's exactly what EnterpriseWeb is bringing to the table. And what we do is we abstract the underlying infrastructure which is the cloud layer. So if, because AWS operating environment is different then private cloud operating environment then Azure environment, you have the networking is set up is different in each one of them. If there is a way you can abstract all of that and present it in a common operating model it becomes a lot easier than for anybody to be able to consume. >> And what a lot of customers tell me is the way they deal with multicloud complexity is they go with mono cloud, right? And so they'll lose out on some of the best services >> Absolutely >> If best of, so that's not >> that's not ideal, but at the end of the day, agree, developers don't want to muck with all the plumbing >> Dave Duggal: Yep. >> They want to write code. >> Azhar: Correct. >> So like I come back to are the traditional Telcos leaning in on a way that they're going to enable ISVs and developers to write on top of those platforms? Or are there sort of new entrance and disruptors? And I know, I know the answer is both >> Dave Duggal: Yep. >> but I feel as though the Telcos still haven't, traditional Telcos haven't tuned in to that developer affinity, but you guys sell to them. >> What, what are you seeing? >> Yeah, so >> What we have seen is there are Telcos fall into several categories there. If you look at the most mature ones, you know they are very eager to move up the value chain. There are some smaller very nimble ones that have actually doing, they're actually doing something really interesting. For example, they've provided sandbox environments to developers to say "Go develop your applications to the sandbox environment." We'll use that to build an net service with you. I can give you some interesting examples across the globe that, where that is happening, right? In AsiaPac, particularly in Australia, ANZ region. There are a couple of providers who have who have done this, but in, in, in a very interesting way. But the challenges to them, why it's not completely open or public yet is primarily because they haven't figured out how to exactly monetize that. And, and that's the reason why. So in the absence of that, what will happen is they they have to rely on the ISV ecosystem to be able to build those capabilities which they can then bring it on as part of the catalog. But in Latin America, I was talking to one of the providers and they said, "Well look we have a public cloud, we have our own public cloud, right?" What we want do is use that to offer localized services not just bring everything in from the top >> But, but we heard from Ericson's CEO they're basically going to monetize it by what I call "gouge", the developers >> (Azhar laughs) >> access to the network telemetry as opposed to saying, "Hey, here's an open platform development on top of it and it will maybe create something like an app store and we'll take a piece of the action." >> So ours, >> to be is a better model. >> Yeah. So that's perfect. Our second project that we're showing here is with Intel, right? So Intel came to us cause they are a reputation for doing advanced automation solutions. They gave us carte blanche in their labs. So this is Intel Network Builders they said pick your partners. And we went with the Red Hat, Fort Net, Keysite this company KX doing AIML. But to address your DevX, here's Intel explicitly wants to get closer to the developers by exposing their APIs, open APIs over their infrastructure. Just like Red Hat has APIs, right? And so they can expose them northbound to developers so developers can leverage and tune their applications, right? But the challenge there is what Intel is doing at the low level network infrastructure, right? Is fundamentally complex, right? What you want is an abstraction layer where develop and this gets to, to your point Dave where you just said like "The developers just want to get their job done." or really they want to focus on the business logic and accelerate that service delivery, right? So the idea here is an EnterpriseWeb they can literally declaratively compose their services, express their intent. "I want this to run optimized for low latency. I want this to run optimized for energy consumption." Right? And that's all they say, right? That's a very high level statement. And then the run time translates it between all the elements that are participating in that service to realize the developer's intent, right? No hands, right? Zero touch, right? So that's now a movement in telecom. So you're right, it's taking a while because these are pretty fundamental shifts, right? But it's intent based networking, right? So it's almost two parts, right? One is you have to have the open APIs, right? So that the infrastructure has to expose its capabilities. Then you need abstractions over the top that make it simple for developers to take, you know, make use of them. >> See, one of the demonstrations we are doing is around AIOps. And I've had literally here on this floor, two conversations around what I call as network as a platform. Although it sounds like a cliche term, that's exactly what Dave was describing in terms of exposing APIs from the infrastructure and utilizing them. So once you get that data, then now you can do analytics and do machine learning to be able to build models and figure out how you can orchestrate better how you can monetize better, how can how you can utilize better, right? So all of those things become important. It's just not about internal optimization but it's also about how do you expose it to third party ecosystem to translate that into better delivery mechanisms or IOT capability and so on. >> But if they're going to charge me for every API call in the network I'm going to go broke (team laughs) >> And I'm going to get really pissed. I mean, I feel like, I'm just running down, Oracle. IBM tried it. Oracle, okay, they got Java, but they don't they don't have developer jobs. VMware, okay? They got Aria. EMC used to have a thing called code. IBM had to buy Red Hat to get to the developer community. (Lisa laughs) >> So I feel like the telcos don't today have those developer shops. So, so they have to partner. [Azhar] Yes. >> With guys like you and then be more open and and let a zillion flowers bloom or else they're going to get disrupted in a big way and they're going to it's going to be a repeat of the over, over the top in, in in a different model that I can't predict. >> Yeah. >> Absolutely true. I mean, look, they cannot be in the connectivity business. Telcos cannot be just in the connectivity business. It's, I think so, you know, >> Dave Vellante: You had a fry a frozen hand (Dave Daggul laughs) >> off that, you know. >> Well, you know, think about they almost have to go become over the top on themselves, right? That's what the cloud guys are doing, right? >> Yeah. >> They're riding over their backbone that by taking a creating a high level abstraction, they in turn abstract away the infrastructure underneath them, right? And that's really the end game >> Right? >> Dave Vellante: Yeah. >> Is because now, >> they're over the top it's their network, it's their infrastructure, right? They don't want to become bid pipes. >> Yep. >> Now you, they can take OpenShift, run that in any cloud. >> Yep. >> Right? >> You can run that in hybrid cloud, enterprise web can do the application layer configuration and management. And together we're running, you know, OSI layers one through seven, east to west, north to south. We're running across the the RAN, the core and the transport. And that is telco super cloud, my friend. >> Yeah. Well, >> (Dave Duggal laughs) >> I'm dominating the conversation cause I love talking super cloud. >> I knew you would. >> So speaking of super superpowers, when you're in customer or prospective customer conversations with providers and they've got, obviously they're they're in this transformative state right now. How, what do you describe as the superpower between Red Hat and EnterpriseWeb in terms of really helping these Telcos transforms. But at the end of the day, the connectivity's there the end user gets what they want, which is I want this to work wherever I am. >> Yeah, yeah. That's a great question, Lisa. So I think the way you could look at it is most software has, has been evolved to be specialized, right? So in Telcos' no different, right? We have this in the enterprise, right? All these specialized stacks, all these components that they wire together in the, in you think of Telco as a sort of a super set of enterprise problems, right? They have all those problems like magnified manyfold, right? And so you have specialized, let's say orchestrators and other tools for every Telco domain for every Telco layer. Now you have a zoo of orchestrators, right? None of them were designed to work together, right? They all speak a specific language, let's say quote unquote for doing a specific purpose. But everything that's interesting in the 21st century is across layers and across domains, right? If a siloed static application, those are dead, right? Nobody's doing those anymore. Even developers don't do those developers are doing composition today. They're not doing, nobody wants to hear about a 6 million lines of code, right? They want to hear, "How did you take these five things and bring 'em together for productive use?" >> Lisa: Right. How did you deliver faster for my enterprise? How did you save me money? How did you create business value? And that's what we're doing together. >> I mean, just to add on to Dave, I was talking to one of the providers, they have more than 30,000 nodes in their infrastructure. When I say no to your servers running, you know, Kubernetes,running open stack, running different components. If try managing that in one single entity, if you will. Not possible. You got to fragment, you got to segment in some way. Now the question is, if you are not exposing that particular infrastructure and the appropriate KPIs and appropriate things, you will not be able to efficiently utilize that across the board. So you need almost a construct that creates like a manager of managers, a hierarchical structure, which would allow you to be more intelligent in terms of how you place those, how you manage that. And so when you ask the question about what's the secret sauce between the two, well this is exactly where EnterpriseWeb brings in that capability to analyze information, be more intelligent about it. And what we do is provide an abstraction of the cloud layer so that they can, you know, then do the right job in terms of making sure that it's appropriate and it's consistent. >> Consistency is key. Guys, thank you so much. It's been a pleasure really digging through EnterpriseWeb. >> Thank you. >> What you're doing >> with Red Hat. How you're helping the organization transform and Supercloud, we can't forget Supercloud. (Dave Vellante laughs) >> Fight Supercloud. Guys, thank you so much for your time. >> Thank you so much Lisa. >> Thank you. >> Thank you guys. >> Very nice. >> Lisa: We really appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage coming to you live from MWC 23. We'll be back after a short break.

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright upbeat music) >> Good morning everyone. Welcome to theCUBE. We are live at MWC '23 in Barcelona, Spain. I'm Lisa Martin, and I'm going to have a great conversation next with our esteemed CUBE analyst, Dave Nicholson. Dave, great to have you here. Great to be working this event with you. >> Good to be here with you, Lisa. >> So there are, good to be here with you and about 80,000 people. >> Dave: That's right. >> Virtually and and physically. And it's jammed in, and this is the most jammed show I've seen in years. >> Dave: It's crazy. >> So much going on in the telecom industry. What are some of your expectations for what you're going to hear and see at this year's event? >> So, I expect to hear a lot about 5G. Specifically 5G private networks, and the disaggregation of the hardware and software stacks that have driven telecom for decades. So we're at this transition into 5G. From a consumer perspective, we feel like, oh well 5G has been around for years. In terms of where it's actually been deployed, we're just at the beginning stages of that. >> Right, right. Talk about the changing of the stack. You know, the disaggregation. Why now is it too late? And what are the advantages? That it's going to enable telcos to move faster, I imagine? >> Yeah, so it's really analogous to what we see in the general IT industry that we cover so much. The move to cloud, sometimes you're gaining performance. You're always gaining agility and flexibility. A big concern of the legacy telecom providers is going to be maintaining availability, reliability against a backdrop of increasing agility in the direction that they want to go. So that's going to be the conversation. It's going to be the old school folks, who are interested in maintaining primarily availability and performance, excuse me, contrasted with the open source, OpenStack providers, who are going to be saying, hey this is a path to the future. Without that path to the future, things will stagnate. >> Talk about some of those OpenStack providers. I imagine those are some of the folks that we know quite well? >> Sure, sure. Yeah, so someone like Dell, for example. They're perfectly positioned at this sort of crossroads, because Dell has been creating "cloud stacks," that will live sometimes on-premises. And those stacks of infrastructure, based on cots, commercial off-the-shelf components, integrated within an ecosystem can live at the edge, at literally the base of transmitter towers. So when you think about this whole concept of RAN or a radio access network, think of a cellular tower with an antenna and a transmitter. The transmitter might live on that tower, or it might live in pieces at the base of the tower. But there's always at that base of the tower, forget about the acronyms, it's a box of stuff, teleco stuff. All of these things historically have been integrated into single packages. >> Right. >> For good reason. >> Right. >> Think back to a mainframe, where it was utterly, absolutely reliable. We moved, in the general IT space, from the era of the mainframe to the world of client server, through virtualization, containerization. That exact transition is happening in the world of telecom right now. >> Why is it finally happening now? It seems a bit late, given that in our consumer lives, we have this expectation that we could be mobile 24 by seven. >> Right. Well it's because, first of all, we get mad if a call doesn't go through. How often, when you make, when you try to make a cellular call or when you try to send a text, how often does it not work? >> I can count on one hand. >> Right, rarely. >> Right. >> Now, you may be in an area that has spotty coverage. But when you're in an area where you have coverage it just works all of the time. And you expect it to work all of the time. And the miracle of the services that have been delivered to us over the last decade has really kind of blunted the need for next generation stuff. Well, we're at this transition point. And 5G as a technology enables so much more bandwidth. Think of it as, you know, throughput bandwidth latency. It allows the kind of performance characteristics so that things can be delivered that couldn't be delivered in the past. Virtual reality, augmented reality. We're already seeing you know 4K data streams to our phones. So, it's sort of lagged because of our expectations for absolute, rock solid, reliability. >> Yeah. >> The technology is ahead of that area now. And so this question is how do you navigate from utter reliability to awesome openness without sacrificing performance and reliability? >> Well, and also from a stack perspective, from looking at desegregation, and the opportunities there are for the telcos, but also the public cloud providers, are they friends, are they foes? What's the relationship like? >> They're going to be frenemies. >> Lisa: Frenemies? >> Yeah, coopetition is going to be the word of the day again. Yeah because when you think of a cloud, most people automatically think off-premises. >> Lisa: Yes. >> Maybe they even think automatically you know, hyper scale or Azure, GCP, AWS. In this case, it really is a question of cloud as an operating model. Cloud facilitating agility, cloud adopting cloud native architecture from a software perspective, so that you can rapidly deploy net new capabilities into an environment. You can't do that with proprietary closed systems that might use a waterfall development process and take years to develop. You and I have covered the Kubernetes world pretty closely. And what's the big thing that we hear constantly? The hunger, the thirst for human resources, >> Right. >> people who can actually work in this world of containerization. >> Yes, yes. >> Well guess what? In the macroeconomic environment, a lot of folks in the IT space have recently been disrupted. This is a place to look, if you have that skillset. Look at the telecom space, because they need people who are forward thinking in the era of cloud. But this concept of cloud is really, it's going to be, the telcos are both competing and partnering with what we think of as the traditional, hyper scale public cloud providers. >> And what do you think, one of the things that we know at MWC '23 is virtually every industry is represented here. Every vertical is here, whether it's a sports arena, or a retail outlet, or a manufacturer. Every organization, every industry needs to have networks that deliver what they need to do but also enable them to move faster and deliver what the end user wants. What are some of the industries that you think are really ripe for this disruption? And the ability to use private 5G networks, for example? >> Well, so it's interesting, you mentioned private 5G networks. I think a good example of the transition that's underway is this, the move to 4K video. So, you get a high definition television. The first time you see a 720p TV, it's like oh my gosh, amazing. Then we get 1080p, then it's 4K. People get 4K TVs, they bring them home, and there's no content. >> No. >> The first content, was it from your cable provider? No. >> Yeah. >> Was it over the air? ABC, NBC, CBS? No, it was YouTube. YouTube delivered the first reliable 4K content, over the internet. Similarly, everything comes to us now to our mobile devices. So we're not accessing the world around us so much from a desktop or even a laptop. It's mobile. So if you want to communicate with a customer, it's mobile. If you're creating a private 5G network, you now are standing something up that is net new in a greenfield environment. And you can deploy agility and functionality that the large scale telecom providers can't, because of the massive investment they might need. So the irony is, you have a factory that sits on 20 acres and you have folks traveling around, if you create a private 5G network, it might become, it might be more feature rich than what your employees are used to being able to access through their personal mobile devices. >> Wow. >> Yeah, because you're starting net new, you have the luxury of starting greenfield, as opposed to the responsibility and legacy for supporting a massive system that exists already. >> So then, what's in it for the existing incumbent telcos from an advantage opportunity perspective? Because you mentioned frenemies, coopetition. >> Right. >> There's irony there, as you talked about. >> Right, well you could look at it as either opportunity or headache. And it's both. Because they have very, very real SLAs that they need to meet. >> Right. >> Very, very real expectations that have been set in terms of reliability, availability, and performance. So they can't slip off of that. Making that transition is, I think going to be driven by economics, because the idea of having things be open means that there's competition for every part of the stack. There will be a critical role for integration vendors. Folks like Dell, and the ecosystems that they're creating around this will be critical, because often you would prefer to have one back to pat or one throat to choke instead of many. So, you still want to have that centralized entity to go to when something goes wrong. >> Right. >> Or when you want to implement something new. So, for the incumbents, it's a classic example of what you do in the face of disruption. How do you leverage technology? In my role as adjunct faculty at the Wharton CTO Academy, we talk about the CTO mindset. And the idea that your role is to leverage technology, in the service of your organization's mission, whatever that organization and mission is. So from a telecom provider perspective, they need to stay on top of this. >> Yes. >> Or they will be disrupted. >> Right. >> It's fascinating to think of how this disruption's taking place. >> Lisa: They have no choice, if they want to survive. >> No, yeah they have no choice. >> Lisa: In the next few years. >> They have no choice, but they'll come along, kicking and screaming. I'm sure if you had someone sitting here in the industry, they'd say, well, no, no, no, no, no. >> Yeah, of course. >> We love it! It's like, yeah, well but you're going to have to make some painful changes to adopt these things. >> What are some of the opportunities for those folks like Dell that you mentioned, in terms of coming in, being able to disrupt that stack, open things up? Great opportunities for the Dells, and other similar organizations to really start gaining a bigger foothold in the telecom industry, I imagine. >> Well, I look at it through the lens of sort of traditional IT and the transitions that we've been watching for the last couple of decades. It's exactly the same. I mean you, there is a parallel. It is like coming out of the mainframe era to the client server era. So, you know, we went in that transition, it was mainframe operating systems, very, very closed systems to more slightly opened. You know, the worlds of SUN and SGI and HP, and the likes, transitioned to kind of Microsoft based software running with like Dell hardware. >> Yeah. >> And, that stack is now getting deployed into one of the remaining legacy environments which is the telco space. So, the opportunity for Dell is pretty massive because on some fronts they're competing with the move to proper off-premises public cloud. >> Right. >> In this case, they are the future for telecom as opposed to sort of representing legacy, compared to some of the other cloud opportunities that are out there. >> So ultimately, what does a modern telecom network look like? I imagine, cloud native? Distributed? >> Yeah, yeah. So, traditionally, like I said, you've got the tower and the transmitters and the computer hardware that's running it. Those are then networked together. So you can sort of think of it as leaves on a twig, on a branch, on a tree. Eventually it gets into a core network, where there is terrestrial line communication and or communication up to satellites. And that's all been humming along just fine, making the transition from 3G to 4G to 5G. But, the real transition from a cloud perspective is this idea that you're taking these proprietary systems, disaggrevating, disaggrevating them and disaggregating them, carving them up into pieces where now you're introducing virtualization. So there's a VMware play here. Some things are virtualized using that stack. I think more often we're going to be talking about containerized and truly cloud native stacks. So instead of having the proprietary stack, where all the hardware and software is designed together. Now you're going to have Dell servers running some execution layer, orchestration layer, for cloud native, containerized applications and microservices. And that's the way things are going to be developed. >> And who, from a stakeholder perspective is involved here? 'Cause one of the things that I'm hearing is with this disaggregation of the staff, which is a huge change, what you're articulated, that's already happened at enterprise IT, change management is a hard thing to do. If they want to be successful, and well not just survive, they want to thrive. I'm just imagining, who are the stakeholders that are involved in having to push those incumbents to make these decisions, to move faster, to become agile, to compete. >> So, I remember when VMware had the problem that anytime they suggested introducing a hypervisor to to virtualize a physical machine and then run software on top or an operating system on top, and then applications, the big question the customer would have was, well is Microsoft going to support that? What if I can't get support from Microsoft? I dunno if I can do this. Within about a year of those conversations taking place, the question was, can I run this in my production environment? So it was, can I get support in my test environment too? Can I please run this in production? >> Yeah. >> And so, there are folks in the kind of legacy telecom world who are going to be afraid. It's, whatever the dynamic is, there is a no one ever got fired for buying from fill in the blank >> Exactly, yep. >> in the telecom space. >> Yeah, yeah. >> Because they would buy a consolidated, aggregated stack. >> Right. >> And, if something went wrong they could say, boom, blame you. And yeah, that stack doesn't lend itself to the kind of pace of change. >> Right. >> So it doesn't necessarily need the same kind of change management. Or at least it's very, very centralized. >> Okay. Okay. >> We're getting into the brave new world of things where if you let them spin out of control, you can have big problems. And that's where the folks like Dell come in, to make sure that yes, disaggregated, yes best of commercial off-the-shelf stuff, but also the best in terms of performance and reliability and availability. >> Yeah. >> So, that's the execution part, you must execute flawlessly. >> It sounds like from a thematic perspective, the theme of MWC '23 is velocity. But it seems like an underlying theme under that, or maybe an overlying theme is disruption. It's going to be so interesting, we're only on day one. We just started our coverage. Four days of wall to wall coverage on theCUBE. Excited to hear what you're excited about, what you learn over the next few days. We get to host some segments together. >> Yeah. >> But it seems like disruption is the overall theme. And it's going to be so interesting to see how this industry evolves, what the opportunities are, what the coopetition opportunities are. We're going to be learning a lot this week. I'm excited. >> Yeah, and what's fascinating to me about this whole thing is we talk about this, all of this tumultuous, disruptive stuff that's happening. For the average consumer, they're never going to be aware of it. >> Nope. >> Dave: They're just going to see services piled on top of services. >> Which is what we want. >> There are billions of people with mobile devices and the hundreds of billions, I don't know, trillions I guess at some point of connected devices at the edge. >> Lisa: Yes, yes. >> The whole concept of the internet of things. We'll sort of be blissfully unaware of what's happening at the middle. But there's a lot of action there. So we're going to be focusing on that action that's going on. In, you know, in in the middle of it. >> Yeah. >> But there's also some cool consumer stuff out here. >> There is. >> I know I'm going to be checking out the augmented reality and virtual reality stuff. >> Yeah, yeah. Well it's all about that customer experience. We expect things right away, 24/7, wherever we are in the world. And it's enabling that to make that happen. >> Yeah. >> Dave, thank you so much for really sharing what you think you're excited about for the event and some of the trends in telecom. It sounds like it's such an interesting time to be unpacking this. >> It's going to be a great week. >> It is going to be a great week. All right, for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage, covering day one of MWC '23. Stick around. We'll be back with our next guest in just a minute. (bright music resumes) (music fades out)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Welcome to the Fira in Barcelona, everybody. This is theCUBE's coverage of MWC 23, day one of that coverage. We have four days of wall-to-wall action going on, the place is going crazy. I'm here with Dave Nicholson, Lisa Martin is also in the house. Today's ecosystem day, and we're really excited to have Manish Singh who's the CTO of the Telecom Systems Business unit at Dell Technologies. He's joined by Doug Wolf who's the head of strategy for the Telecom Systems Business unit at Dell. Gents, welcome. What a show. I mean really the first major MWC or used to be Mobile World Congress since you guys have launched your telecom business, you kind of did that sort of in the Covid transition, but really exciting, obviously a huge, huge venue to match the huge market. So Manish, how did you guys get into this? What did you see? What was the overall thinking to get Dell into this business? >> Manish: Yeah, well, I mean just to start with you know, if you look at the telecom ecosystem today, the service providers in particular, they are looking for network transformation, driving more disaggregation into their network so that they can get better utilization of the infrastructure, but then also get more agility, more cloud native characteristics onto their, for their networks in particular. And then further on, it's important for them to really start to accelerate the pace of innovation on the networks itself, to start more supply chain diversity, that's one of the challenges that they've been having. And so there've been all these market forces that have been really getting these service providers to really start to transform the way they have built the infrastructure in the past, which was legacy monolithic architectures to more cloud native disaggregated. And from a Dell perspective, you know, that really gives us the permission to play, to really, given all the expertise on the work we have done in the IT with all the IT transformations to leverage all that expertise and bring that to the service providers and really help them in accelerating their network transformation. So that's where the journey started. We've been obviously ever since then working on expanding the product portfolio on our compute platforms to bring Teleco great compute platforms with more capabilities than we can talk about that. But then working with partners and building the ecosystem to again create this disaggregated and open ecosystem that will be more cloud native and really meet the objective that the service providers are after. >> Dave Vellante: Great, thank you. So, Doug the strategy obviously is to attack this market, as Manish said, from an open standpoint, that's sort of new territory. It's like a little bit like the wild, wild west. So maybe you could double click on what Manish was saying from a, from a strategy standpoint, yes, the Telecos need to be more flexible, they need to be more open, but they also need this reliability piece. So talk about that from a strategy standpoint of what you guys saw. >> Doug: Yeah, absolutely. As Manish mentioned, you know, Dell getting into open systems isn't something new. You know, Dell has been kind of playing in that world for years and years, but the opportunity in Telecom that came was opening of the RAN, the core network, the edge, all of these with 5G really created a wide opening for us. So we started developing products and solutions, you know, built our first Telecom grade servers for open RAN over the last year, we'll talk about those at the show. But you know, as, as Manish mentioned, an open ecosystem is new to Telecom. I've been in the Telecom business along with Manish for, you know, 25 plus years and this is a new thing that they're embarking on. So started with virtualization about five, six years ago, and now moving to cloud native architectures on the core, suddenly there's this need to have multiple parties partner really well, share specifications, and put that together for an operator to consume. And I think that's just the start of really where all the challenges are and the opportunities that we see. >> Where are we in this transition cycle? When the average consumer hears 5G, feels like it's been around for a long time because it was hyped beforehand. >> Doug: Yeah. >> If you're talking about moving to an open infrastructure model from a proprietary closed model, when is the opportunity for Dell to become part of that? Is it, are there specific sites that have already transitioned to 5G, therefore they've either made the decision to be open or not? Or are there places where the 5G transition has taken place, and they might then make a transition to open brand with 5G? Where, where are we in that cycle? What does the opportunity look like? >> I'll kind of take it from the typology of the operator, and I'm sure Manish will build on this, but if I look back on the core, started to get virtualized you know, back around 2015-16 with some of the lead operators like AT&T et cetera. So Dell has been partnering with those operators for some years. So it really, it's happening on the core, but it's moving with 5G to more of a cloud-like architecture, number one. And number two, they're going beyond just virtualizing the network. You know, they previously had used OpenStack and most of them are migrating to more of a cloud native architecture that Manish mentioned. And that is a bit different in terms of there's more software vendors in that ecosystem because the software is disaggregated also. So Dell's been playing in the core for a number of years, but we brought out new solutions we've announced at the show for the core. And the parts that are really starting that transition of maybe where the core was back in 2015 is on the RAN and on the edge in particular. >> Because NFV kind of predated the ascendancy of cloud. >> Exactly, yeah. >> Right, so it really didn't have the impact that people had hoped. And there's some, when you look back, 'cause it's not same wine, new bottle as the open systems movement, there are a lot of similarities but you know, you mentioned cloud, and cloud native, you really didn't have, back in the nineties, true engineered systems. You didn't really have AI that, you know, to speak of at the sort of volume of the data that we have. So Manish, from a CTO's perspective, how are you attacking some of those differences in bringing that to market? >> Manish: Yeah, I mean, I think you touched on some very important points there. So first of all, the duck's point, a lot of this transformation started in the core, right? And as the technology evolution progress, the opportunities opened up. It has now come into the edge and the radio access network as well, in particular with open RAN. And so when we talk about the disaggregation of the infrastructure from the software itself and an open ecosystem, this now starts to create the opportunity to accelerate innovation. And I really want to pick up on the point that you'd said on AI, for example. AI and machine learning bring a whole new set of capabilities and opportunities for these service providers to drive better optimization, better performance, better sustainability and energy efficiency on their infrastructure, on and on and on. But to really tap into these technologies, they really need to open that up to third parties implementation solutions that are coming up. And again, the end objective remains to accelerate that innovation. Now that said, all these things need to be brought together, right? And delivered and deployed in the network without any degradation in the KPIs and actually improving the performance on different vectors, right? So this is what the current state of play is. And with this aggregation I'm definitely a believer that all these new technologies, including AI, machine learning, and there's a whole area, host area of problems that can be solved and attacked and are actually getting attacked by applying AI and machine learning onto these networks. >> Open obviously is good. Nobody's ever going to, you know, argue that open is a bad thing. It's like democracy is a good thing, right? At least amongst us. And so, but, the RAN, the open RAN, has to be as reliable and performant, right, as these, closed networks. Or maybe not, maybe it doesn't have to be identical. Just has to be close enough in order for that tipping point to occur. Is that a fair summarization? What are you guys hearing from carriers in terms of their willingness to sort of put their toe in the water and, and what could we expect in terms of the maturity model of, of open RAN and adoption? >> Right, so I mean I think on, on performance that, that's a tough one. I think the operators will demand performance and you've seen experiments, you've really seen more of the Greenfield operators kind of launch. >> Okay. >> Doug: Open RAN or vRAN type solutions. >> So they're going to disrupt. >> Doug: Yeah, they're going to disrupt. >> Yeah. >> Doug: And there's flexibility in an open RAN architecture also for 5G that they, that they're interested in and I think the Brownfield operators are too, but let's say maybe the Greenfield jump first in terms of doing that from a mass deployment perspective. But I still think that it's going to be critical to meet very similar SLAs and end user performance. And, you know, I think that's where, you know, maturity of that model is what's required. I think Brownfield operators are conservative in terms of, you know, going with something they know, but the opportunities and the benefits of that architecture and building new flexible, potentially cost advantaged over time solutions, that's what the, where the real interest is going forward. >> And new services that you can introduce much more quickly. You know, the interesting thing about Dell to me, you don't compete with the carriers, the public cloud vendors though, the carriers are concerned about them sort of doing an end run on them. So you provide a potential partnership for the carriers that's non-threatening, right? 'Cause you're, you're an arms dealer, you're selling hardware and software, right? But, but how do you see that? Because we heard in the keynote today, one of the Teleco, I think it was the chairman of Telefonica said, you know, cloud guys can't do this alone. You know, they need, you know, this massive, you know, build out. And so, what do you think about that in terms of your relationship with the carriers not being threatening? I mean versus say potentially the cloud guys, who are also your partners, I understand, it's a really interesting dynamic, isn't it? >> Manish: Yeah, I mean I think, you know, I mean, the way I look at it, the carriers actually need someone like Dell who really come in who can bring in the right capabilities, the right infrastructure, but also bring in the ecosystem together and deliver a performance solution that they can deploy and that they can trust, number one. Number two, to your point on cloud, I mean, from a Dell perspective, you know, we announced our Dell Telecom Multicloud Foundation and as part of that last year in September, we announced what we call is the Dell Telecom Infrastructure Blocks. The first one we announced with Wind River, and this is, think of it as the, you know, hardware and the cashier all pre-integrated with lot of automation around it, factory integrated, you know, delivered to customers in an integrated model with all the licenses, everything. And so it starts to solve the day zero, day one, day two integration deployment and then lifecycle management for them. So to broaden the discussion, our view is it's a multicloud world, the future is multicloud where you can have different clouds which can be optimized for different workloads. So for example, while our work with Wind River initially was very focused on virtualization of the radio access network, we just announced our infrastructure block with Red Hat, which is very much targeted and optimized for core network and edge, right? So, you know, there are different workflows which will require different capabilities also. And so, you know, again, we are bringing those things to these service providers to again, bring those cloud characteristics and cloud native architecture for their network. >> And It's going to be hybrid, to your point. >> David N.: And you, just hit on something, you said cloud characteristics. >> Yeah. >> If you look at this through the lens of kind of the general world of IT, sometimes when people hear the word cloud, they immediately leap to the idea that it's a hyperscale cloud provider. In this scenario we're talking about radio towers that have intelligence living on them and physically at the base. And so the cloud characteristics that you're delivering might be living physically in these remote locations all over the place, is that correct? >> Yeah, I mean that, that's true. That will definitely happen over time. But I think, I think we've seen the hyperscalers enter, you know, public cloud providers, enter at the edge and they're dabbling maybe with private, but I think the public RAN is another further challenge. I think that maybe a little bit down the road for them. So I think that is a different characteristic that you're talking about managing the macro RAN environment. >> Manish: If I may just add one more perspective of this cloud, and I mean, again, the hyperscale cloud, right? I mean that world's been great when you can centralize a lot of compute capability and you can then start to, you know, do workload aggregation and use the infrastructure more efficient. When it comes to Telecom, it is inherently it distributed architecture where you have access, you talked about radio access, your port, and it is inherently distributed because it has to provide the coverage and capacity. And so, you know, it does require different kind of capabilities when you're going out and about, and this is where I was talking about things like, you know, we just talked, we just have been working on our bare metal orchestration, right? This is what we are bringing is a capability where you can actually have distributed infrastructure, you can deploy, you can actually manage, do lifecycle management, in a distributed multicloud form. So it does require, you know, different set of capabilities that need to be enabled. >> Some, when talking about cloud, would argue that it's always been information technology, it always will be information technology, and especially as what we might refer to as public cloud or hyperscale cloud providers, are delivering things essentially on premises. It's like, well, is that cloud? Because it feels like some of those players are going to be delivering physical infrastructure outside of their own data centers in order to address this. It seems the nature, the nature of the beast is that some of these things need to be distributed. So it seems perfectly situated for Dell. That's why you guys are both at Dell now and not working for other Telecom places, right? >> Exactly. Exactly, yes. >> It's definitely an exciting space. It's transformed, the networks are under transformation and I do think that Dell's very well positioned to, to really help the customers, the service providers in accelerating their transformation journey with an open ecosystem. >> Dave V.: You've got the brand, and the breadth, and the resources to actually attract an ecosystem. But I wonder if you could sort of take us through your strategy of ecosystem, the challenges that you've seen in developing that ecosystem and what the vision is that ultimately, what's the outcome going to be of that open ecosystem? >> Yeah, I can start. So maybe just to give you the big picture, right? I mean the big picture, is disaggregation with performance, right, TCO models to the service providers, right? And it starts at the infrastructure layer, builds on bringing these cloud capabilities, the cast layer, right? Bringing the right accelerators. All of this requires to pull the ecosystem. So give you an example on the infrastructure in a Teleco grade servers like XR8000 with Sapphire, the new intel processors that we've just announced, and an extended array of servers. These are Teleco grade, short depth, et cetera. You know, the Teleco great characteristic. Working with the partners like Marvel for bringing in the accelerators in there, that's important to again, drive the performance and optimize for the TCO. Working then with partners like Wind River, Red Hat, et cetera, to bring in the cast capabilities so you can start to see how this ecosystem starts to build up. And then very recently we announced our private 5G solution with AirSpan and Expeto on the core site. So bringing those workloads together. Similarly, we have an open RAN solution we announce with Fujitsu. So it's, it's open, it's disaggregated, but bringing all these together. And one of the last things I would say is, you know, to make all this happen and make all of these, we've also been putting together our OTEL, our open Telecom ecosystem lab, which is very much geared, really gives this open ecosystem a playground where they can come in and do all that heavy lifting, which is anyways required, to do the integration, optimization, and board. So put all these capabilities in place, but the end goal, the end vision again, is that cloud native disaggregated infrastructure that starts to innovate at the speed of software and scales at the speed of cloud. >> And this is different than the nineties. You didn't have something like OTEL back then, you know, you didn't have the developer ecosystem that you have today because on top of everything that you just said, Manish, are new workloads and new applications that are going to be developed. Doug, anything you'd add to what Manish said? >> Doug: Yeah, I mean, as Manish said, I think adding to the infrastructure layers, which are, you know, critical for us to, to help integrate, right? Because we kind of took a vertical Teleco stack and we've disaggregated it, and it's gotten a little bit more complex. So our Solutions Dell Technology infrastructure block, and our lab infrastructure with OTEL, helps put those pieces together. But without the software players in this, you know, that's what we really do, I think in OTEL. And that's just starting to grow. So integrating with those software providers with that integration is something that the operators need. So we fill a gap there in terms of either providing engineered solutions so they can readily build on or actually bringing in that software provider. And I think that's what you're going to see more from us going forward is just extending that ecosystem even further. More software players effectively. >> In thinking about O-RAN, are they, is it possible to have the low latency, the high performance, the reliability capabilities that carriers are used to and the flexibility? Or can you sort of prioritize one over the other from a go to market and rollout standpoint and optimize one, maybe get a foothold in the market? How do you see that balance? >> Manish: Oh the answer is absolutely yes you can have both We are on that journey, we are on that journey. This is where all these things I was talking about in terms of the right kind of accelerators, right kind of capabilities on the infrastructure, obviously retargeting the software, there are certain changes, et cetera that need to be done on the software itself to make it more cloud native. And then building all the surrounding capabilities around the CICD pipeline and all where it's not just day zero or day one that you're doing the cloud-like lifecycle management of this infrastructure. But the answer to your point, yes, absolutely. It's possible, the technology is there, and the ecosystem is coming together, and that's the direction. Now, are there challenges? Absolutely there are challenges, but directionally that's the direction the industry is moving to. >> Dave V.: I guess my question, Manish, is do they have to go in lockstep? Because I would argue that the public cloud when it first came out wasn't nearly as functional as what I could get from my own data center in terms of recovery, you know, backup and recovery is a perfect example and it took, you know, a decade plus to get there. But it was the flexibility, and the openness, and the developer affinity, the programmability, that attracted people. Do you see O-RAN following a similar path? Or does it, my question is does it have to have that carrier class reliability today? >> David N.: Everything on day one, does it have to have everything on day one? >> Yeah, I mean, I would say, you know, like again, the Greenfield operators I think we're, we're willing do a little bit more experimentation. I think the operators, Brownfield operators that have existing, you know, deployments, they're going to want to be closer. But I think there's room for innovation here. And clearly, you know, Manish came from, from Meta and we're, we've been very involved with TIP, we're very involved with the O-RAN alliance, and as Manish mentioned, with all those accelerators that we're working with on our infrastructure, that is a space that we're trying to help move the ball forward. So I think you're seeing deployments from mainstream operators, but it's maybe not in, you know, downtown New York deployment, they're more rural deployments. I think that's getting at, you know, kind of your question is there's maybe a little bit more flexibility there, they get to experiment with the technology and the flexibility and then I think it will start to evolve >> Dave V.: And that's where the disruption's going to come from, I think. >> David N.: Well, where was the first place you could get reliable 4K streaming of video content? It wasn't ABC, CBS, NBC. It was YouTube. >> Right. >> So is it possible that when you say Greenfield, are a lot of those going to be what we refer to as private 5G networks where someone may set up a private 5G network that has more functions and capabilities than the public network? >> That's exactly where I was going is that, you know, that that's why you're seeing us getting very active in 5G solutions that Manish mentioned with, you know, Expeto and AirSpan. There's more of those that we haven't publicly announced. So I think you'll be seeing more announcements from us, but that is really, you know, a new opportunity. And there's spectrum there also, right? I mean, there's public and private spectrum. We plan to work directly with the operators and do it in their spectrum when needed. But we also have solutions that will do it, you know, on non-public spectrum. >> So let's close out, oh go ahead. You you have something to add there? >> I'm just going to add one more point to Doug's point, right? Is if you look on the private 5G and the end customer, it's the enterprise, right? And they're, they're not a service provider. They're not a carrier. They're more used to deploying, you know, enterprise infrastructure, maintaining, managing that. So, you know, private 5G, especially with this open ecosystem and with all the open run capabilities, it naturally tends to, you know, blend itself very well to meet those requirements that the enterprise would have. >> And people should not think of private 5G as a sort of a replacement for wifi, right? It's to to deal with those, you know, intense situations that can afford the additional cost, but absolutely require the reliability and the performance and, you know, never go down type of scenario. Is that right? >> Doug: And low latencies usually, the primary characteristics, you know, for things like Industry 4.0 manufacturing requirements, those are tough SLAs. They're just, they're different than the operator SLAs for coverage and, you know, cell performance. They're now, you know, Five9 type characteristics, but on a manufacturing floor. >> That's why we don't use wifi on theCUBE to broadcast, we need a hard line. >> Yeah, but why wouldn't it replace wifi over time? I mean, you know, I still have a home phone number that's hardwired to align, but it goes to a voicemail. We don't even have handset anymore for it, yeah. >> I think, well, unless the cost can come down, but I think that wifi is flexible, it's cheap. It's, it's kind of perfect for that. >> Manish: And it's good technology. >> Dave V.: And it works great. >> David N.: For now, for now. >> Dave V.: But you wouldn't want it in those situations, and you're arguing that maybe. >> I'm saying eventually, what, put a sim in a device, I don't know, you know, but why not? >> Yeah, I mean, you know, and Dell offers, you know, from our laptop, you know, our client side, we do offer wifi, we do offer 4G and 5G solutions. And I think those, you know, it's a volume and scale issue, I think for the cost structure you're talking about. >> Manish: Come to our booth and see the connected laptop. >> Dave V.: Well let's, let's close on that. Why don't you guys talk a little bit about what you're going on at the show, I did go by the booth, you got a whole big lineup of servers. You got some, you know, cool devices going on. So give us the rundown and you know, let's end with the takeaways here. >> The simple rundown, a broad range of new powered servers, broad range addressing core, edge, RAN, optimized for those with all the different kind of acceleration capabilities. You can see that, you can see infrastructure blocks. These are with Wind River, with Red Hat. You can see OTEL, the open telecom ecosystem lab where all that playground, the integration, the real work, the real sausage makings happening. And then you will see some interesting solutions in terms of co-creation that we are doing, right? So you, you will see all of that and not to forget the connected laptops. >> Dave V.: Yeah, yeah, cool. >> Doug: Yeah and, we mentioned it before, but just to add on, I think, you know, for private 5G, you know, we've announced a few offers here at the show with partners. So with Expeto and AirSpan in particular, and I think, you know, I just want to emphasize the partnerships that we're doing. You know, we're doing some, you know, fundamental integration on infrastructure, bare metal and different options for the operators to get engineered systems. But building on that ecosystem is really, the move to cloud native is where Dell is trying to get in front of. And we're offering solutions and a much larger ecosystem to go after it. >> Dave V.: Great. Manish and Doug, thanks for coming on the program. It was great to have you, awesome discussion. >> Thank you for having us. >> Thanks for having us. >> All right, Dave Vellante for Dave Nicholson and Lisa Martin. We're seeing the disaggregation of the Teleco network into open ecosystems with integration from companies like Dell and others. Keep it right there for theCUBE's coverage of MWC 23. We'll be right back. (upbeat tech 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. >> While never really meant to be a consumer tech event, the rapid ascendancy of smartphones sucked much of the air out of Mobile World Congress over the years, now MWC. And while the device manufacturers continue to have a major presence at the show, the maturity of intelligent devices, longer life cycles, and the disaggregation of the network stack, have put enterprise technologies front and center in the telco business. Semiconductor manufacturers, network equipment players, infrastructure companies, cloud vendors, software providers, and a spate of startups are eyeing the trillion dollar plus communications industry as one of the next big things to watch this decade. Hello, and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we bring you part two of our ongoing coverage of MWC '23, with some new data on enterprise players specifically in large telco environments, a brief glimpse at some of the pre-announcement news and corresponding themes ahead of MWC, and some of the key announcement areas we'll be watching at the show on theCUBE. Now, last week we shared some ETR data that showed how traditional enterprise tech players were performing, specifically within the telecoms vertical. Here's a new look at that data from ETR, which isolates the same companies, but cuts the data for what ETR calls large telco. The N in this cut is 196, down from 288 last week when we included all company sizes in the dataset. Now remember the two dimensions here, on the y-axis is net score, or spending momentum, and on the x-axis is pervasiveness in the data set. The table insert in the upper left informs how the dots and companies are plotted, and that red dotted line, the horizontal line at 40%, that indicates a highly elevated net score. Now while the data are not dramatically different in terms of relative positioning, there are a couple of changes at the margin. So just going down the list and focusing on net score. Azure is comparable, but slightly lower in this sector in the large telco than it was overall. Google Cloud comes in at number two, and basically swapped places with AWS, which drops slightly in the large telco relative to overall telco. Snowflake is also slightly down by one percentage point, but maintains its position. Remember Snowflake, overall, its net score is much, much higher when measuring across all verticals. Snowflake comes down in telco, and relative to overall, a little bit down in large telco, but it's making some moves to attack this market that we'll talk about in a moment. Next are Red Hat OpenStack and Databricks. About the same in large tech telco as they were an overall telco. Then there's Dell next that has a big presence at MWC and is getting serious about driving 16G adoption, and new servers, and edge servers, and other partnerships. Cisco and Red Hat OpenShift basically swapped spots when moving from all telco to large telco, as Cisco drops and Red Hat bumps up a bit. And VMware dropped about four percentage points in large telco. Accenture moved up dramatically, about nine percentage points in big telco, large telco relative to all telco. HPE dropped a couple of percentage points. Oracle stayed about the same. And IBM surprisingly dropped by about five points. So look, I understand not a ton of change in terms of spending momentum in the large sector versus telco overall, but some deltas. The bottom line for enterprise players is one, they're just getting started in this new disruption journey that they're on as the stack disaggregates. Two, all these players have experience in delivering horizontal solutions, but now working with partners and identifying big problems to be solved, and three, many of these companies are generally not the fastest moving firms relative to smaller disruptive disruptors. Now, cloud has been an exception in fairness. But the good news for the legacy infrastructure and IT companies is that the telco transformation and the 5G buildout is going to take years. So it's moving at a pace that is very favorable to many of these companies. Okay, so looking at just some of the pre-announcement highlights that have hit the wire this week, I want to give you a glimpse of the diversity of innovation that is occurring in the telecommunication space. You got semiconductor manufacturers, device makers, network equipment players, carriers, cloud vendors, enterprise tech companies, software companies, startups. Now we've included, you'll see in this list, we've included OpeRAN, that logo, because there's so much buzz around the topic and we're going to come back to that. But suffice it to say, there's no way we can cover all the announcements from the 2000 plus exhibitors at the show. So we're going to cherry pick here and make a few call outs. Hewlett Packard Enterprise announced an acquisition of an Italian private cellular network company called AthoNet. Zeus Kerravala wrote about it on SiliconANGLE if you want more details. Now interestingly, HPE has a partnership with Solana, which also does private 5G. But according to Zeus, Solona is more of an out-of-the-box solution, whereas AthoNet is designed for the core and requires more integration. And as you'll see in a moment, there's going to be a lot of talk at the show about private network. There's going to be a lot of news there from other competitors, and we're going to be watching that closely. And while many are concerned about the P5G, private 5G, encroaching on wifi, Kerravala doesn't see it that way. Rather, he feels that these private networks are really designed for more industrial, and you know mission critical environments, like factories, and warehouses that are run by robots, et cetera. 'Cause these can justify the increased expense of private networks. Whereas wifi remains a very low cost and flexible option for, you know, whatever offices and homes. Now, over to Dell. Dell announced its intent to go hard after opening up the telco network with the announcement that in the second half of this year it's going to begin shipping its infrastructure blocks for Red Hat. Remember it's like kind of the converged infrastructure for telco with a more open ecosystem and sort of more flexible, you know, more mature engineered system. Dell has also announced a range of PowerEdge servers for a variety of use cases. A big wide line bringing forth its 16G portfolio and aiming squarely at the telco space. Dell also announced, here we go, a private wireless offering with airspan, and Expedo, and a solution with AthoNet, the company HPE announced it was purchasing. So I guess Dell and HPE are now partnering up in the private wireless space, and yes, hell is freezing over folks. We'll see where that relationship goes in the mid- to long-term. Dell also announced new lab and certification capabilities, which we said last week was going to be critical for the further adoption of open ecosystem technology. So props to Dell for, you know, putting real emphasis and investment in that. AWS also made a number of announcements in this space including private wireless solutions and associated managed services. AWS named Deutsche Telekom, Orange, T-Mobile, Telefonica, and some others as partners. And AWS announced the stepped up partnership, specifically with T-Mobile, to bring AWS services to T-Mobile's network portfolio. Snowflake, back to Snowflake, announced its telecom data cloud. Remember we showed the data earlier, it's Snowflake not as strong in the telco sector, but they're continuing to move toward this go-to market alignment within key industries, realigning their go-to market by vertical. It also announced that AT&T, and a number of other partners, are collaborating to break down data silos specifically in telco. Look, essentially, this is Snowflake taking its core value prop to the telco vertical and forming key partnerships that resonate in the space. So think simplification, breaking down silos, data sharing, eventually data monetization. Samsung previewed its future capability to allow smartphones to access satellite services, something Apple has previously done. AMD, Intel, Marvell, Qualcomm, are all in the act, all the semiconductor players. Qualcomm for example, announced along with Telefonica, and Erickson, a 5G millimeter network that will be showcased in Spain at the event this coming week using Qualcomm Snapdragon chipset platform, based on none other than Arm technology. Of course, Arm we said is going to dominate the edge, and is is clearly doing so. It's got the volume advantage over, you know, traditional Intel, you know, X86 architectures. And it's no surprise that Microsoft is touting its open AI relationship. You're going to hear a lot of AI talk at this conference as is AI is now, you know, is the now topic. All right, we could go on and on and on. There's just so much going on at Mobile World Congress or MWC, that we just wanted to give you a glimpse of some of the highlights that we've been watching. Which brings us to the key topics and issues that we'll be exploring at MWC next week. We touched on some of this last week. A big topic of conversation will of course be, you know, 5G. Is it ever going to become real? Is it, is anybody ever going to make money at 5G? There's so much excitement around and anticipation around 5G. It has not lived up to the hype, but that's because the rollout, as we've previous reported, is going to take years. And part of that rollout is going to rely on the disaggregation of the hardened telco stack, as we reported last week and in previous Breaking Analysis episodes. OpenRAN is a big component of that evolution. You know, as our RAN intelligent controllers, RICs, which essentially the brain of OpenRAN, if you will. Now as we build out 5G networks at massive scale and accommodate unprecedented volumes of data and apply compute-hungry AI to all this data, the issue of energy efficiency is going to be front and center. It has to be. Not only is it a, you know, hot political issue, the reality is that improving power efficiency is compulsory or the whole vision of telco's future is going to come crashing down. So chip manufacturers, equipment makers, cloud providers, everybody is going to be doubling down and clicking on this topic. Let's talk about AI. AI as we said, it is the hot topic right now, but it is happening not only in consumer, with things like ChatGPT. And think about the theme of this Breaking Analysis in the enterprise, AI in the enterprise cannot be ChatGPT. It cannot be error prone the way ChatGPT is. It has to be clean, reliable, governed, accurate. It's got to be ethical. It's got to be trusted. Okay, we're going to have Zeus Kerravala on the show next week and definitely want to get his take on private networks and how they're going to impact wifi. You know, will private networks cannibalize wifi? If not, why not? He wrote about this again on SiliconANGLE if you want more details, and we're going to unpack that on theCUBE this week. And finally, as always we'll be following the data flows to understand where and how telcos, cloud players, startups, software companies, disruptors, legacy companies, end customers, how are they going to make money from new data opportunities? 'Cause we often say in theCUBE, don't ever bet against data. All right, that's a wrap for today. Remember theCUBE is going to be on location at MWC 2023 next week. We got a great set. We're in the walkway in between halls four and five, right in Congress Square, stand CS-60. Look for us, we got a full schedule. If you got a great story or you have news, stop by. We're going to try to get you on the program. I'll be there with Lisa Martin, co-hosting, David Nicholson as well, and the entire CUBE crew, so don't forget to come by and see us. I want to thank Alex Myerson, who's on production and manages the podcast, and Ken Schiffman, as well, in our Boston studio. Kristen Martin and Cheryl Knight help 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 right, remember all these episodes they are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. I publish each week on Wikibon.com and SiliconANGLE.com. All the video content is available on demand at theCUBE.net, or you can email me directly if you want to get in touch David.Vellante@SiliconANGLE.com or DM me @DVellante, or comment on our LinkedIn posts. And please do check out ETR.ai for the best 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 week at Mobile World Congress '23, MWC '23, or next time on Breaking Analysis. (bright 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. >> The world's leading telcos are trying to shed the stigma of being monopolies lacking innovation. Telcos have been great at operational efficiency and connectivity and living off of transmission, and the costs and expenses or revenue associated with that transmission. But in a world beyond telephone poles and basic wireless and mobile services, how will telcos modernize and become more agile and monetize new opportunities brought about by 5G and private wireless and a spate of new innovations and infrastructure, cloud data and apps? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis and ahead of Mobile World Congress or now, MWC23, we explore the evolution of the telco business and how the industry is in many ways, mimicking transformations that took place decades ago in enterprise IT. We'll model some of the traditional enterprise vendors using ETR data and investigate how they're faring in the telecommunications sector, and we'll pose some of the key issues facing the industry this decade. First, let's take a look at what the GSMA has in store for MWC23. GSMA is the host of what used to be called Mobile World Congress. They've set the theme for this year's event as "Velocity" and they've rebranded MWC to reflect the fact that mobile technology is only one part of the story. MWC has become one of the world's premier events highlighting innovations not only in Telco, mobile and 5G, but the collision between cloud, infrastructure, apps, private networks, smart industries, machine intelligence, and AI, and more. MWC comprises an enormous ecosystem of service providers, technology companies, and firms from virtually every industry including sports and entertainment. And as well, GSMA, along with its venue partner at the Fira Barcelona, have placed a major emphasis on sustainability and public and private partnerships. Virtually every industry will be represented at the event because every industry is impacted by the trends and opportunities in this space. GSMA has said it expects 80,000 attendees at MWC this year, not quite back to 2019 levels, but trending in that direction. Of course, attendance from Chinese participants has historically been very high at the show, and obviously the continued travel issues from that region are affecting the overall attendance, but still very strong. And despite these concerns, Huawei, the giant Chinese technology company. has the largest physical presence of any exhibitor at the show. And finally, GSMA estimates that more than $300 million in economic benefit will result from the event which takes place at the end of February and early March. And The Cube will be back at MWC this year with a major presence thanks to our anchor sponsor, Dell Technologies and other supporters of our content program, including Enterprise Web, ArcaOS, VMware, Snowflake, Cisco, AWS, and others. And one of the areas we're interested in exploring is the evolution of the telco stack. It's a topic that's often talked about and one that we've observed taking place in the 1990s when the vertically integrated IBM mainframe monopoly gave way to a disintegrated and horizontal industry structure. And in many ways, the same thing is happening today in telecommunications, which is shown on the left-hand side of this diagram. Historically, telcos have relied on a hardened, integrated, and incredibly reliable, and secure set of hardware and software services that have been fully vetted and tested, and certified, and relied upon for decades. And at the top of that stack on the left are the crown jewels of the telco stack, the operational support systems and the business support systems. For the OSS, we're talking about things like network management, network operations, service delivery, quality of service, fulfillment assurance, and things like that. For the BSS systems, these refer to customer-facing elements of the stack, like revenue, order management, what products they sell, billing, and customer service. And what we're seeing is telcos have been really good at operational efficiency and making money off of transport and connectivity, but they've lacked the innovation in services and applications. They own the pipes and that works well, but others, be the over-the-top content companies, or private network providers and increasingly, cloud providers have been able to bypass the telcos, reach around them, if you will, and drive innovation. And so, the right-most diagram speaks to the need to disaggregate pieces of the stack. And while the similarities to the 1990s in enterprise IT are greater than the differences, there are things that are different. For example, the granularity of hardware infrastructure will not likely be as high where competition occurred back in the 90s at every layer of the value chain with very little infrastructure integration. That of course changed in the 2010s with converged infrastructure and hyper-converged and also software defined. So, that's one difference. And the advent of cloud, containers, microservices, and AI, none of that was really a major factor in the disintegration of legacy IT. And that probably means that disruptors can move even faster than did the likes of Intel and Microsoft, Oracle, Cisco, and the Seagates of the 1990s. As well, while many of the products and services will come from traditional enterprise IT names like Dell, HPE, Cisco, Red Hat, VMware, AWS, Microsoft, Google, et cetera, many of the names are going to be different and come from traditional network equipment providers. These are names like Ericsson and Huawei, and Nokia, and other names, like Wind River, and Rakuten, and Dish Networks. And there are enormous opportunities in data to help telecom companies and their competitors go beyond telemetry data into more advanced analytics and data monetization. There's also going to be an entirely new set of apps based on the workloads and use cases ranging from hospitals, sports arenas, race tracks, shipping ports, you name it. Virtually every vertical will participate in this transformation as the industry evolves its focus toward innovation, agility, and open ecosystems. Now remember, this is not a binary state. There are going to be greenfield companies disrupting the apple cart, but the incumbent telcos are going to have to continue to ensure newer systems work with their legacy infrastructure, in their OSS and BSS existing systems. And as we know, this is not going to be an overnight task. Integration is a difficult thing, transformations, migrations. So that's what makes this all so interesting because others can come in with Greenfield and potentially disrupt. There'll be interesting partnerships and ecosystems will form and coalitions will also form. Now, we mentioned that several traditional enterprise companies are or will be playing in this space. Now, ETR doesn't have a ton of data on specific telecom equipment and software providers, but it does have some interesting data that we cut for this breaking analysis. What we're showing here in this graphic is some of the names that we've followed over the years and how they're faring. Specifically, we did the cut within the telco sector. So the Y-axis here shows net score or spending velocity. And the horizontal axis, that shows the presence or pervasiveness in the data set. And that table insert in the upper left, that informs as to how the dots are plotted. You know, the two columns there, net score and the ends. And that red-dotted line, that horizontal line at 40%, that is an indicator of a highly elevated level. Anything above that, we consider quite outstanding. And what we'll do now is we'll comment on some of the cohorts and share with you how they're doing in telecommunications, and that sector, that vertical relative to their position overall in the data set. Let's start with the public cloud players. They're prominent in every industry. Telcos, telecommunications is no exception and it's quite an interesting cohort here. On the one hand, they can help telecommunication firms modernize and become more agile by eliminating the heavy lifting and you know, all the cloud, you know, value prop, data center costs, and the cloud benefits. At the same time, public cloud players are bringing their services to the edge, building out their own global networks and are a disruptive force to traditional telcos. All right, let's talk about Azure first. Their net score is basically identical to telco relative to its overall average. AWS's net score is higher in telco by just a few percentage points. Google Cloud platform is eight percentage points higher in telco with a 53% net score. So all three hyperscalers have an equal or stronger presence in telco than their average overall. Okay, let's look at the traditional enterprise hardware and software infrastructure cohort. Dell, Cisco, HPE, Red Hat, VMware, and Oracle. We've highlighted in this chart just as sort of indicators or proxies. Dell's net score's 10 percentage points higher in telco than its overall average. Interesting. Cisco's is a bit higher. HPE's is actually lower by about nine percentage points in the ETR survey, and VMware's is lower by about four percentage points. Now, Red Hat is really interesting. OpenStack, as we've previously reported is popular with telcos who want to build out their own private cloud. And the data shows that Red Hat OpenStack's net score is 15 percentage points higher in the telco sector than its overall average. OpenShift, on the other hand, has a net score that's four percentage points lower in telco than its overall average. So this to us talks to the pace of adoption of microservices and containers. You know, it's going to happen, but it's going to happen more slowly. Finally, Oracle's spending momentum is somewhat lower in the sector than its average, despite the firm having a decent telco business. IBM and Accenture, heavy services companies are both lower in this sector than their average. And real quickly, snowflake's net score is much lower by about 12 percentage points relative to its very high average net score of 62%. But we look for them to be a player in this space as telcos need to modernize their analytics stack and share data in a governed manner. Databricks' net score is also much lower than its average by about 13 points. And same, I would expect them to be a player as open architectures and cloud gains steam in telco. All right, let's close out now on what we're going to be talking about at MWC23 and some of the key issues that we'll be unpacking. We've talked about stack disaggregation in this breaking analysis, but the key here will be the pace at which it will reach the operational efficiency and reliability of closed stacks. Telcos, you know, in a large part, they're engineering heavy firms and much of their work takes place, kind of in the basement, in the dark. It's not really a big public hype machine, and they tend to move slowly and cautiously. While they understand the importance of agility, they're going to be careful because, you know, it's in their DNA. And so at the same time, if they don't move fast enough, they're going to get hurt and disrupted by competitors. So that's going to be a topic of conversation, and we'll be looking for proof points. And the other comment I'll make is around integration. Telcos because of their conservatism will benefit from better testing and those firms that can innovate on the testing front and have labs and certifications and innovate at that level, with an ecosystem are going to be in a better position. Because open sometimes means wild west. So the more players like Dell, HPE, Cisco, Red Hat, et cetera, that do that and align with their ecosystems and provide those resources, the faster adoption is going to go. So we'll be looking for, you know, who's actually doing that, Open RAN or Radio Access Networks. That fits in this discussion because O-RAN is an emerging network architecture. It essentially enables the use of open technologies from an ecosystem and over time, look at O-RAN is going to be open, but the questions, you know, a lot of questions remain as to when it will be able to deliver the operational efficiency of traditional RAN. Got some interesting dynamics going on. Rakuten is a company that's working hard on this problem, really focusing on operational efficiency. Then you got Dish Networks. They're also embracing O-RAN. They're coming at it more from service innovation. So that's something that we'll be monitoring and unpacking. We're going to look at cloud as a disruptor. On the one hand, cloud can help drive agility, as we said earlier and optionality, and innovation for incumbent telcos. But the flip side is going to also do the same for startups trying to disrupt and cloud attracts startups. While some of the telcos are actually embracing the cloud, many are being cautious. So that's going to be an interesting topic of discussion. And there's private wireless networks and 5G, and hyperlocal private networks, they're being deployed, you know, at the edge. This idea of open edge is also a really hot topic and this trend is going to accelerate. You know, the importance here is that the use cases are going to be widely varied. The needs of a hospital are going to be different than those of a sports venue are different from a remote drilling location, and energy or a concert venue. Things like real-time AI inference and data flows are going to bring new services and monetization opportunities. And many firms are going to be bypassing traditional telecommunications networks to build these out. Satellites as well, we're going to see, you know, in this decade, you're going to have, you're going to look down at Google Earth and you're going to see real-time. You know, today you see snapshots and so, lots of innovations going in that space. So how is this going to disrupt industries and traditional industry structures? Now, as always, we'll be looking at data angles, right? 'Cause it's in The Cube's DNA to follow the data and what opportunities and risks data brings. The Cube is going to be on location at MWC23 at the end of the month. We got a great set. We're in the walkway between halls four and five, right in Congress Square, it's booths CS60. So we'll have a full, they're called Stan CS60. We have a full schedule. I'm going to be there with Lisa Martin, Dave Nicholson and the entire Cube crew, so don't forget to stop by. All right, that's a wrap. I want to thank 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 Hof is our editor-in-chief over at Silicon Angle, does some great stuff for us. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search "Breaking Analysis" podcasts I publish each week on wikibon.com and silicon angle.com. And all the video content is available on demand at thecube.net. You can email me directly at david.vellante@silicon angle.com. You can DM me at dvellante or comment on my LinkedIn post. Please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for The Cube Insights powered by ETR. Thanks for watching and we'll see you at Mobile World Congress, and/or at next time on "Breaking Analysis." (bright music) (bright music fades)

(upbeat music) >> Okay, welcome back everyone. I'm John Furrier here in theCUBE, in Palo Alto for "CUBE Conversation" with Chris Jones, Director of Product Management at Platform9. I've got a series of questions, had a great conversation earlier. Chris, I have a couple questions for you, what do you think? >> Let's do it, John. >> Okay, how does Platform9 Solution, you- can it be used on any infrastructure anywhere, cloud, edge, on-premise? >> It can, that's the beauty of our control plane, right? It was born in the cloud, and we primarily deliver that SaaS, which allows it to work in your data center, on bare metal, on VMs, or with public cloud infrastructure. We now give you the ability to take that control plane, install it in your data center, and then use it with anything, or even in air gap. And that includes capabilities with bare metal orchestration as well. >> Second question. How does Platform9 ensure maximum uptime, and proactive issue resolution? >> Oh, that's a good question. So if you come to Platform nine we're going to talk about always on assurance. What is driving that is a system of three components around self-healing, monitoring, and proactive assistance. So our software will heal broken things on nodes, right? If something stops running that should be running, it will attempt to restart that. We also have monitoring that's deployed with everything. So you build a cluster in AWS, well, we put open source monitoring agents, that are actually Prometheus, on every single node. That means it's resilient, right? So if you lose a node, you don't lose monitoring. But that data importantly comes back to our control plane, and that's the control plane that you can put in your data center as well. That data is what alerts us, and you as a user, anytime of the day that something's going wrong. Let's say etcd latency, good example, etcd is going slow. We'll find out, we might not be able to take restorative action immediately, but we're definitely going to reach out and say,, "You have a problem, let's get ahead of this and let's prevent that from becoming a bigger problem." And that's what we're delivering. When we say always on assurance, we're talking about self-healing, we're talking about remote monitoring, we're talking about being proactive with our customers, not waiting for the phone call or the support desk ticket saying, "Oh we think something's not working." Or worse, the customer has an outage. >> Awesome. Thanks for sharing. Can you explain the process for implementing Platform9 within a company's existing infrastructure. >> Are we doing air gap, or on-prem or SaaS approached? SaaS approach I think is by far the easiest, right? We can build a dedicated Platform9 control plane instance in a manner of minutes, for any customer. So when we do a proof of concept or onboarding, we just literally put in an email address, put in the name you want for your fully qualified domain name, and your instance is up. From that point onwards, the user can just log in, and using our CLI, talk to any number of, say, virtual machines, or physical servers in their environment for, you know, doing this in a data center or colo, and say, "I want these to be my Kubernetes control plane nodes. Here's the five of them. Here's the VIP for the load balancing, the API server and here are all of my compute nodes." And that CLI will work with the SaaS control plane, and go and build the cluster. That's as simple as it, CentOS, Ubuntu, just plain old operating system. Our software takes care of all the prerequisites, installing all the pieces, putting down MetalLB, CoreDNS, Metrics Server, Kubernetes dashboard, etcd backups. You built some servers. That's essentially what you've done, and the rest is being handled by Platform9. It's as simple as that. >> Great, thanks for that. What are the two traditional paths for companies considering the cloud native journey? The two paths. >> The traditional paths. I think that's your engineering team running so fast that before you even realize that you've got, you know, 10 EKS clusters. Or, hey, we can do this. You know, I've got the I can build it mentality. Let's go DIY completely open source Kubernetes on our infrastructure, and we're going to piecemeal build it all up together. They're, I think the pathways that people traditionally look at this journey, as opposed to having that third alternative saying can I just consume it on my infrastructure, be it cloud or on-premise or at the edge. >> Third is the new way, you guys do that. >> That's been our focus since the company was, you know, brought together back in the open OpenStack days. >> Awesome, what's the makeup of your customer base? Is there a certain pattern to the size or environments that you guys work with? Is there a pattern or consistency to your customer base? >> It's a spread, right? We've got large enterprises like Juniper, and we go all the way down to people with 20, 30, 50 nodes in total. We've got people in banking and finance, we've got things all the way through to telecommunications and storage infrastructure. >> What's your favorite feature of Platform9? >> My favorite feature? You know, if I ask, should I say this as a pre-sales engineer, let me show you a favorite thing. My immediate response is, I should never do this. (John laughs) To me it's just being able to define my cluster and say, go. And in five minutes I have that environment, I can see everything that's running, right? It's all unified, it's one spot, right? I'm a cluster admin. I said I wanted three control plane, 25 workers. Here's the infrastructure, it creates it, and once it's built, I can see everything that's running, right? All the applications that are there. One UI, I don't have to go click around. I'm not trying to solve things or download things. It's the fact that it's unified and just delivered in one hit. >> What is the one thing that people should know about Platform9 that they might not know about it? >> I think it's that we help developers and engineers as much as we can help our operations teams. I think, for a long time we've sort of targeted that user and said, hey, we, we really help you. It's like, but why are they doing this? Why are they building any infrastructure or any cloud platform? Well, it's to run applications and services, to help their customers, but how do they get there? There's people building and writing those things, and we're helping them, right? For the last two years, we've been really focused on making it simple, and I think that's an important thing to know. >> Chris, thanks so much, appreciate it. >> Yeah, thank you, John. >> Okay, that's theCUBE Q&A session here with Platform9. I'm John Furrier, thanks for watching. (light music)

(upbeat music) >> Hi everyone. Welcome back to this Cube conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE." Got a great conversation around Cloud Native, Cloud Native Journey, how enterprises are looking at Cloud Native and putting it all together. And it comes down to operations, developer productivity, and security. It's the hottest topic in technology. We got Chris Jones here in the studio, director of Product Management for Platform9. Chris, thanks for coming in. >> Hey, thanks. >> So when we always chat about, when we're at KubeCon. KubeConEU is coming up and in a few, in a few months, the number one conversation is developer productivity. And the developers are driving all the standards. It's interesting to see how they just throw everything out there and whatever gets adopted ends up becoming the standard, not the old school way of kind of getting stuff done. So that's cool. Security Kubernetes and Containers are all kind of now that next level. So you're starting to see the early adopters moving to the mainstream. Enterprises, a variety of different approaches. You guys are at the center of this. We've had a couple conversations with your CEO and your tech team over there. What are you seeing? You're building the products. What's the core product focus right now for Platform9? What are you guys aiming for? >> The core is that blend of enabling your infrastructure and PlatformOps or DevOps teams to be able to go fast and run in a stable environment, but at the same time enable developers. We don't want people going back to what I've been calling Shadow IT 2.0. It's, hey, I've been told to do something. I kicked off this Container initiative. I need to run my software somewhere. I'm just going to go figure it out. We want to keep those people productive. At the same time we want to enable velocity for our operations teams, be it PlatformOps or DevOps. >> Take us through in your mind and how you see the industry rolling out this Cloud Native journey. Where do you see customers out there? Because DevOps have been around, DevSecOps is rocking, you're seeing AI, hot trend now. Developers are still in charge. Is there a change to the infrastructure of how developers get their coding done and the infrastructure, setting up the DevOps is key, but when you add the Cloud Native journey for an enterprise, what changes? What is the, what is the, I guess what is the Cloud Native journey for an enterprise these days? >> The Cloud Native journey or the change? When- >> Let's start with the, let's start with what they want to do. What's the goal and then how does that happen? >> I think the goal is that promise land. Increased resiliency, better scalability, and overall reduced costs. I've gone from physical to virtual that gave me a higher level of density, packing of resources. I'm moving to Containers. I'm removing that OS layer again. I'm getting a better density again, but all of a sudden I'm running Kubernetes. What does that, what does that fundamentally do to my operations? Does it magically give me scalability and resiliency? Or do I need to change what I'm running and how it's running so it fits that infrastructure? And that's the reality, is you can't just take a Container and drop it into Kubernetes and say, hey, I'm now Cloud Native. I've got reduced cost, or I've got better resiliency. There's things that your engineering teams need to do to make sure that application is a Cloud Native. And then there's what I think is one of the largest shifts of virtual machines to containers. When I was in the world of application performance monitoring, we would see customers saying, well, my engineering team have this Java app, and they said it needs a VM with 12 gig of RAM and eight cores, and that's what we gave it. But it's running slow. I'm working with the application team and you can see it's running slow. And they're like, well, it's got all of its resources. One of those nice features of virtualization is over provisioning. So the infrastructure team would say, well, we gave it, we gave it all a RAM it needed. And what's wrong with that being over provisioned? It's like, well, Java expects that RAM to be there. Now all of a sudden, when you move to the world of containers, what we've got is that's not a set resource limit, really is like it used to be in a VM, right? When you set it for a container, your application teams really need to be paying attention to your resource limits and constraints within the world of Kubernetes. So instead of just being able to say, hey, I'm throwing over the fence and now it's just going to run on a VM, and that VMs got everything it needs. It's now really running on more, much more of a shared infrastructure where limits and constraints are going to impact the neighbors. They are going to impact who's making that decision around resourcing. Because that Kubernetes concept of over provisioning and the virtualization concept of over provisioning are not the same. So when I look at this problem, it's like, well, what changed? Well, I'll do my scale tests as an application developer and tester, and I'd see what resources it needs. I asked for that in the VM, that sets the high watermark, job's done. Well, Kubernetes, it's no longer a VM, it's a Kubernetes manifest. And well, who owns that? Who's writing it? Who's setting those limits? To me, that should be the application team. But then when it goes into operations world, they're like, well, that's now us. Can we change those? So it's that amalgamation of the two that is saying, I'm a developer. I used to pay attention, but now I need to pay attention. And an infrastructure person saying, I used to just give 'em what they wanted, but now I really need to know what they've wanted, because it's going to potentially have a catastrophic impact on what I'm running. >> So what's the impact for the developer? Because, infrastructure's code is what everybody wants. The developer just wants to get the code going and they got to pay attention to all these things, or don't they? Is that where you guys come in? How do you guys see the problem? Actually scope the problem that you guys solve? 'Cause I think you're getting at I think the core issue here, which is, I've got Kubernetes, I've got containers, I've got developer productivity that I want to focus on. What's the problem that you guys solve? >> Platform operation teams that are adopting Cloud Native in their environment, they've got that steep learning curve of Kubernetes plus this fundamental change of how an app runs. What we're doing is taking away the burden of needing to operate and run Kubernetes and giving them the choice of the flexibility of infrastructure and location. Be that an air gap environment like a, let's say a telco provider that needs to run a containerized network function and containerized workloads for 5G. That's one thing that we can deploy and achieve in a completely inaccessible environment all the way through to Platform9 running traditionally as SaaS, as we were born, that's remotely managing and controlling your Kubernetes environments on-premise AWS. That hybrid cloud experience that could be also Bare Metal, but it's our platform running your environments with our support there, 24 by seven, that's proactively reaching out. So it's removing a lot of that burden and the complications that come along with operating the environment and standing it up, which means all of a sudden your DevOps and platform operations teams can go and work with your engineers and application developers and say, hey, let's get, let's focus on the stuff that, that we need to be focused on, which is running our business and providing a service to our customers. Not figuring out how to upgrade a Kubernetes cluster, add new nodes, and configure all of the low level. >> I mean there are, that's operations that just needs to work. And sounds like as they get into the Cloud Native kind of ops, there's a lot of stuff that kind of goes wrong. Or you go, oops, what do we buy into? Because the CIOs, let's go, let's go Cloud Native. We want to, we got to get set up for the future. We're going to be Cloud Native, not just lift and shift and we're going to actually build it out right. Okay, that sounds good. And when we have to actually get done. >> Chris: Yeah. >> You got to spin things up and stand up the infrastructure. What specifically use case do you guys see that emerges for Platform9 when people call you up and you go talk to customers and prospects? What's the one thing or use case or cases that you guys see that you guys solve the best? >> So I think one of the, one of the, I guess new use cases that are coming up now, everyone's talking about economic pressures. I think the, the tap blows open, just get it done. CIO is saying let's modernize, let's use the cloud. Now all of a sudden they're recognizing, well wait, we're spending a lot of money now. We've opened that tap all the way, what do we do? So now they're looking at ways to control that spend. So we're seeing that as a big emerging trend. What we're also sort of seeing is people looking at their data centers and saying, well, I've got this huge legacy environment that's running a hypervisor. It's running VMs. Can we still actually do what we need to do? Can we modernize? Can we start this Cloud Native journey without leaving our data centers, our co-locations? Or if I do want to reduce costs, is that that thing that says maybe I'm repatriating or doing a reverse migration? Do I have to go back to my data center or are there other alternatives? And we're seeing that trend a lot. And our roadmap and what we have in the product today was specifically built to handle those, those occurrences. So we brought in KubeVirt in terms of virtualization. We have a long legacy doing OpenStack and private clouds. And we've worked with a lot of those users and customers that we have and asked the questions, what's important? And today, when we look at the world of Cloud Native, you can run virtualization within Kubernetes. So you can, instead of running two separate platforms, you can have one. So all of a sudden, if you're looking to modernize, you can start on that new infrastructure stack that can run anywhere, Kubernetes, and you can start bringing VMs over there as you are containerizing at the same time. So now you can keep your application operations in one environment. And this also helps if you're trying to reduce costs. If you really are saying, we put that Dev environment in AWS, we've got a huge amount of velocity out of it now, can we do that elsewhere? Is there a co-location we can go to? Is there a provider that we can go to where we can run that infrastructure or run the Kubernetes, but not have to run the infrastructure? >> It's going to be interesting too, when you see the Edge come online, you start, we've got Mobile World Congress coming up, KubeCon events we're going to be at, the conversation is not just about public cloud. And you guys obviously solve a lot of do-it-yourself implementation hassles that emerge when people try to kind of stand up their own environment. And we hear from developers consistency between code, managing new updates, making sure everything is all solid so they can go fast. That's the goal. And that, and then people can get standardized on that. But as you get public cloud and do it yourself, kind of brings up like, okay, there's some gaps there as the architecture changes to be more distributed computing, Edge, on-premises cloud, it's cloud operations. So that's cool for DevOps and Cloud Native. How do you guys differentiate from say, some the public cloud opportunities and the folks who are doing it themselves? How do you guys fit in that world and what's the pitch or what's the story? >> The fit that we look at is that third alternative. Let's get your team focused on what's high value to your business and let us deliver that public cloud experience on your infrastructure or in the public cloud, which gives you that ability to still be flexible if you want to make choices to run consistently for your developers in two different locations. So as I touched on earlier, instead of saying go figure out Kubernetes, how do you upgrade a hundred worker nodes in place upgrade. We've solved that problem. That's what we do every single day of the week. Don't go and try to figure out how to upgrade a cluster and then upgrade all of the, what I call Kubernetes friends, your core DNSs, your metrics server, your Kubernetes dashboard. These are all things that we package, we test, we version. So when you click upgrade, we've already handled that entire process. So it's saying don't have your team focused on that lower level piece of work. Get them focused on what is important, which is your business services. >> Yeah, the infrastructure and getting that stood up. I mean, I think the thing that's interesting, if you look at the market right now, you mentioned cost savings and recovery, obviously kind of a recession. I mean, people are tightening their belts for sure. I don't think the digital transformation and Cloud Native spend is going to plummet. It's going to probably be on hold and be squeezed a little bit. But to your point, people are refactoring looking at how to get the best out of what they got. It's not just open the tap of spend the cash like it used to be. Yeah, a couple months, even a couple years ago. So okay, I get that. But then you look at the what's coming, AI. You're seeing all the new data infrastructure that's coming. The containers, Kubernetes stuff, got to get stood up pretty quickly and it's got to be reliable. So to your point, the teams need to get done with this and move on to the next thing. >> Chris: Yeah, yeah, yeah. >> 'Cause there's more coming. I mean, there's a lot coming for the apps that are building in Data Native, AI-Native, Cloud Native. So it seems that this Kubernetes thing needs to get solved. Is that kind of what you guys are focused on right now? >> So, I mean to use a customer, we have a customer that's in AI/ML and they run their platform at customer sites and that's hardware bound. You can't run AI machine learning on anything anywhere. Well, with Platform9 they can. So we're enabling them to deliver services into their customers that's running their AI/ML platform in their customer's data centers anywhere in the world on hardware that is purpose-built for running that workload. They're not Kubernetes experts. That's what we are. We're bringing them that ability to focus on what's important and just delivering their business services whilst they're enabling our team. And our 24 by seven proactive management are always on assurance to keep that up and running for them. So when something goes bump at the night at 2:00am, our guys get woken up. They're the ones that are reaching out to the customer saying, your environments have a problem, we're taking these actions to fix it. Obviously sometimes, especially if it is running on Bare Metal, there's things you can't do remotely. So you might need someone to go and do that. But even when that happens, you're not by yourself. You're not sitting there like I did when I worked for a bank in one of my first jobs, three o'clock in the morning saying, wow, our end of day processing is stuck. Who else am I waking up? Right? >> Exactly, yeah. Got to get that cash going. But this is a great use case. I want to get to the customer. What do some of the successful customers say to you for the folks watching that aren't yet a customer of Platform9, what are some of the accolades and comments or anecdotes that you guys hear from customers that you have? >> It just works, which I think is probably one of the best ones you can get. Customers coming back and being able to show to their business that they've delivered growth, like business growth and productivity growth and keeping their organization size the same. So we started on our containerization journey. We went to Kubernetes. We've deployed all these new workloads and our operations team is still six people. We're doing way more with growth less, and I think that's also talking to the strength that we're bringing, 'cause we're, we're augmenting that team. They're spending less time on the really low level stuff and automating a lot of the growth activity that's involved. So when it comes to being able to grow their business, they can just focus on that, not- >> Well you guys do the heavy lifting, keep on top of the Kubernetes, make sure that all the versions are all done. Everything's stable and consistent so they can go on and do the build out and provide their services. That seems to be what you guys are best at. >> Correct, correct. >> And so what's on the roadmap? You have the product, direct product management, you get the keys to the kingdom. What is, what is the focus? What's your focus right now? Obviously Kubernetes is growing up, Containers. We've been hearing a lot at the last KubeCon about the security containers is getting better. You've seen verification, a lot more standards around some things. What are you focused on right now for at a product over there? >> Edge is a really big focus for us. And I think in Edge you can look at it in two ways. The mantra that I drive is Edge must be remote. If you can't do something remotely at the Edge, you are using a human being, that's not Edge. Our Edge management capabilities and being in the market for over two years are a hundred percent remote. You want to stand up a store, you just ship the server in there, it gets racked, the rest of it's remote. Imagine a store manager in, I don't know, KFC, just plugging in the server, putting in the ethernet cable, pressing the power button. The rest of all that provisioning for that Cloud Native stack, Kubernetes, KubeVirt for virtualization is done remotely. So we're continuing to focus on that. The next piece that is related to that is allowing people to run Platform9 SaaS in their data centers. So we do ag app today and we've had a really strong focus on telecommunications and the containerized network functions that come along with that. So this next piece is saying, we're bringing what we run as SaaS into your data center, so then you can run it. 'Cause there are many people out there that are saying, we want these capabilities and we want everything that the Platform9 control plane brings and simplifies. But unfortunately, regulatory compliance reasons means that we can't leverage SaaS. So they might be using a cloud, but they're saying that's still our infrastructure. We're still closed that network down, or they're still on-prem. So they're two big priorities for us this year. And that on-premise experiences is paramount, even to the point that we will be delivering a way that when you run an on-premise, you can still say, wait a second, well I can send outbound alerts to Platform9. So their support team can still be proactively helping me as much as they could, even though I'm running Platform9s control plane. So it's sort of giving that blend of two experiences. They're big, they're big priorities. And the third pillar is all around virtualization. It's saying if you have economic pressures, then I think it's important to look at what you're spending today and realistically say, can that be reduced? And I think hypervisors and virtualization is something that should be looked at, because if you can actually reduce that spend, you can bring in some modernization at the same time. Let's take some of those nos that exist that are two years into their five year hardware life cycle. Let's turn that into a Cloud Native environment, which is enabling your modernization in place. It's giving your engineers and application developers the new toys, the new experiences, and then you can start running some of those virtualized workloads with KubeVirt, there. So you're reducing cost and you're modernizing at the same time with your existing infrastructure. >> You know Chris, the topic of this content series that we're doing with you guys is finding the right path, trusting the right path to Cloud Native. What does that mean? I mean, if you had to kind of summarize that phrase, trusting the right path to Cloud Native, what does that mean? It mean in terms of architecture, is it deployment? Is it operations? What's the underlying main theme of that quote? What's the, what's? How would you talk to a customer and say, what does that mean if someone said, "Hey, what does that right path mean?" >> I think the right path means focusing on what you should be focusing on. I know I've said it a hundred times, but if your entire operations team is trying to figure out the nuts and bolts of Kubernetes and getting three months into a journey and discovering, ah, I need Metrics Server to make something function. I want to use Horizontal Pod Autoscaler or Vertical Pod Autoscaler and I need this other thing, now I need to manage that. That's not the right path. That's literally learning what other people have been learning for the last five, seven years that have been focused on Kubernetes solely. So the why- >> There's been a lot of grind. People have been grinding it out. I mean, that's what you're talking about here. They've been standing up the, when Kubernetes started, it was all the promise. >> Chris: Yep. >> And essentially manually kind of getting in in the weeds and configuring it. Now it's matured up. They want stability. >> Chris: Yeah. >> Not everyone can get down and dirty with Kubernetes. It's not something that people want to generally do unless you're totally into it, right? Like I mean, I mean ops teams, I mean, yeah. You know what I mean? It's not like it's heavy lifting. Yeah, it's important. Just got to get it going. >> Yeah, I mean if you're deploying with Platform9, your Ops teams can tinker to their hearts content. We're completely compliant upstream Kubernetes. You can go and change an API server flag, let's go and mess with the scheduler, because we want to. You can still do that, but don't, don't have your team investing in all this time to figure it out. It's been figured out. >> John: Got it. >> Get them focused on enabling velocity for your business. >> So it's not build, but run. >> Chris: Correct? >> Or run Kubernetes, not necessarily figure out how to kind of get it all, consume it out. >> You know we've talked to a lot of customers out there that are saying, "I want to be able to deliver a service to my users." Our response is, "Cool, let us run it. You consume it, therefore deliver it." And we're solving that in one hit versus figuring out how to first run it, then operate it, then turn that into a consumable service. >> So the alternative Platform9 is what? They got to do it themselves or use the Cloud or what's the, what's the alternative for the customer for not using Platform9? Hiring more people to kind of work on it? What's the? >> People, building that kind of PaaS experience? Something that I've been very passionate about for the past year is looking at that world of sort of GitOps and what that means. And if you go out there and you sort of start asking the question what's happening? Just generally with Kubernetes as well and GitOps in that scope, then you'll hear some people saying, well, I'm making it PaaS, because Kubernetes is too complicated for my developers and we need to give them something. There's some great material out there from the likes of Intuit and Adobe where for two big contributors to Argo and the Argo projects, they almost have, well they do have, different experiences. One is saying, we went down the PaaS route and it failed. The other one is saying, well we've built a really stable PaaS and it's working. What are they trying to do? They're trying to deliver an outcome to make it easy to use and consume Kubernetes. So you could go out there and say, hey, I'm going to build a Kubernetes cluster. Sounds like Argo CD is a great way to expose that to my developers so they can use Kubernetes without having to use Kubernetes and start automating things. That is an approach, but you're going to be going completely open source and you're going to have to bring in all the individual components, or you could just lay that, lay it down, and consume it as a service and not have to- >> And mentioned to it. They were the ones who kind of brought that into the open. >> They did. Inuit is the primary contributor to the Argo set of products. >> How has that been received in the market? I mean, they had the event at the Computer History Museum last fall. What's the momentum there? What's the big takeaway from that project? >> Growth. To me, growth. I mean go and track the stars on that one. It's just, it's growth. It's unlocking machine learning. Argo workflows can do more than just make things happen. Argo CD I think the approach they're taking is, hey let's make this simple to use, which I think can be lost. And I think credit where credit's due, they're really pushing to bring in a lot of capabilities to make it easier to work with applications and microservices on Kubernetes. It's not just that, hey, here's a GitOps tool. It can take something from a Git repo and deploy it and maybe prioritize it and help you scale your operations from that perspective. It's taking a step back and saying, well how did we get to production in the first place? And what can be done down there to help as well? I think it's growth expansion of features. They had a huge release just come out in, I think it was 2.6, that brought in things that as a product manager that I don't often look at like really deep technical things and say wow, that's powerful. But they have, they've got some great features in that release that really do solve real problems. >> And as the product, as the product person, who's the target buyer for you? Who's the customer? Who's making that? And you got decision maker, influencer, and recommender. Take us through the customer persona for you guys. >> So that Platform Ops, DevOps space, right, the people that need to be delivering Containers as a service out to their organization. But then it's also important to say, well who else are our primary users? And that's developers, engineers, right? They shouldn't have to say, oh well I have access to a Kubernetes cluster. Do I have to use kubectl or do I need to go find some other tool? No, they can just log to Platform9. It's integrated with your enterprise id. >> They're the end customer at the end of the day, they're the user. >> Yeah, yeah. They can log in. And they can see the clusters you've given them access to as a Platform Ops Administrator. >> So job well done for you guys. And your mind is the developers are moving 'em fast, coding and happy. >> Chris: Yeah, yeah. >> And and from a customer standpoint, you reduce the maintenance cost, because you keep the Ops smoother, so you got efficiency and maintenance costs kind of reduced or is that kind of the benefits? >> Yeah, yep, yeah. And at two o'clock in the morning when things go inevitably wrong, they're not there by themselves, and we're proactively working with them. >> And that's the uptime issue. >> That is the uptime issue. And Cloud doesn't solve that, right? Everyone experienced that Clouds can go down, entire regions can go offline. That's happened to all Cloud providers. And what do you do then? Kubernetes isn't your recovery plan. It's part of it, right, but it's that piece. >> You know Chris, to wrap up this interview, I will say that "theCUBE" is 12 years old now. We've been to OpenStack early days. We had you guys on when we were covering OpenStack and now Cloud has just been booming. You got AI around the corner, AI Ops, now you got all this new data infrastructure, it's just amazing Cloud growth, Cloud Native, Security Native, Cloud Native, Data Native, AI Native. It's going to be all, this is the new app environment, but there's also existing infrastructure. So going back to OpenStack, rolling our own cloud, building your own cloud, building infrastructure cloud, in a cloud way, is what the pioneers have done. I mean this is what we're at. Now we're at this scale next level, abstracted away and make it operational. It seems to be the key focus. We look at CNCF at KubeCon and what they're doing with the cloud SecurityCon, it's all about operations. >> Chris: Yep, right. >> Ops and you know, that's going to sound counterintuitive 'cause it's a developer open source environment, but you're starting to see that Ops focus in a good way. >> Chris: Yeah, yeah, yeah. >> Infrastructure as code way. >> Chris: Yep. >> What's your reaction to that? How would you summarize where we are in the industry relative to, am I getting, am I getting it right there? Is that the right view? What am I missing? What's the current state of the next level, NextGen infrastructure? >> It's a good question. When I think back to sort of late 2019, I sort of had this aha moment as I saw what really truly is delivering infrastructure as code happening at Platform9. There's an open source project Ironic, which is now also available within Kubernetes that is Metal Kubed that automates Bare Metal as code, which means you can go from an empty server, lay down your operating system, lay down Kubernetes, and you've just done everything delivered to your customer as code with a Cloud Native platform. That to me was sort of the biggest realization that I had as I was moving into this industry was, wait, it's there. This can be done. And the evolution of tooling and operations is getting to the point where that can be achieved and it's focused on by a number of different open source projects. Not just Ironic and and Metal Kubed, but that's a huge win. That is truly getting your infrastructure. >> John: That's an inflection point, really. >> Yeah. >> If you think about it, 'cause that's one of the problems. We had with the Bare Metal piece was the automation and also making it Cloud Ops, cloud operations. >> Right, yeah. I mean, one of the things that I think Ironic did really well was saying let's just treat that piece of Bare Metal like a Cloud VM or an instance. If you got a problem with it, just give the person using it or whatever's using it, a new one and reimage it. Just tell it to reimage itself and it'll just (snaps fingers) go. You can do self-service with it. In Platform9, if you log in to our SaaS Ironic, you can go and say, I want that physical server to myself, because I've got a giant workload, or let's turn it into a Kubernetes cluster. That whole thing is automated. To me that's infrastructure as code. I think one of the other important things that's happening at the same time is we're seeing GitOps, we're seeing things like Terraform. I think it's important for organizations to look at what they have and ask, am I using tools that are fit for tomorrow or am I using tools that are yesterday's tools to solve tomorrow's problems? And when especially it comes to modernizing infrastructure as code, I think that's a big piece to look at. >> Do you see Terraform as old or new? >> I see Terraform as old. It's a fantastic tool, capable of many great things and it can work with basically every single provider out there on the planet. It is able to do things. Is it best fit to run in a GitOps methodology? I don't think it is quite at that point. In fact, if you went and looked at Flux, Flux has ways that make Terraform GitOps compliant, which is absolutely fantastic. It's using two tools, the best of breeds, which is solving that tomorrow problem with tomorrow solutions. >> Is the new solutions old versus new. I like this old way, new way. I mean, Terraform is not that old and it's been around for about eight years or so, whatever. But HashiCorp is doing a great job with that. I mean, so okay with Terraform, what's the new address? Is it more complex environments? Because Terraform made sense when you had basic DevOps, but now it sounds like there's a whole another level of complexity. >> I got to say. >> New tools. >> That kind of amalgamation of that application into infrastructure. Now my app team is paying way more attention to that manifest file, which is what GitOps is trying to solve. Let's templatize things. Let's version control our manifest, be it helm, customize, or just a straight up Kubernetes manifest file, plain and boring. Let's get that version controlled. Let's make sure that we know what is there, why it was changed. Let's get some auditability and things like that. And then let's get that deployment all automated. So that's predicated on the cluster existing. Well why can't we do the same thing with the cluster, the inception problem. So even if you're in public cloud, the question is like, well what's calling that API to call that thing to happen? Where is that file living? How well can I manage that in a large team? Oh my God, something just changed. Who changed it? Where is that file? And I think that's one of big, the big pieces to be sold. >> Yeah, and you talk about Edge too and on-premises. I think one of the things I'm observing and certainly when DevOps was rocking and rolling and infrastructures code was like the real push, it was pretty much the public cloud, right? >> Chris: Yep. >> And you did Cloud Native and you had stuff on-premises. Yeah you did some lifting and shifting in the cloud, but the cool stuff was going in the public cloud and you ran DevOps. Okay, now you got on-premise cloud operation and Edge. Is that the new DevOps? I mean 'cause what you're kind of getting at with old new, old new Terraform example is an interesting point, because you're pointing out potentially that that was good DevOps back in the day or it still is. >> Chris: It is, I was going to say. >> But depending on how you define what DevOps is. So if you say, I got the new DevOps with public on-premise and Edge, that's just not all public cloud, that's essentially distributed Cloud Native. >> Correct. Is that the new DevOps in your mind or is that? How would you, or is that oversimplifying it? >> Or is that that term where everyone's saying Platform Ops, right? Has it shifted? >> Well you bring up a good point about Terraform. I mean Terraform is well proven. People love it. It's got great use cases and now there seems to be new things happening. We call things like super cloud emerging, which is multicloud and abstraction layers. So you're starting to see stuff being abstracted away for the benefits of moving to the next level, so teams don't get stuck doing the same old thing. They can move on. Like what you guys are doing with Platform9 is providing a service so that teams don't have to do it. >> Correct, yeah. >> That makes a lot of sense, So you just, now it's running and then they move on to the next thing. >> Chris: Yeah, right. >> So what is that next thing? >> I think Edge is a big part of that next thing. The propensity for someone to put up with a delay, I think it's gone. For some reason, we've all become fairly short-tempered, Short fused. You know, I click the button, it should happen now, type people. And for better or worse, hopefully it gets better and we all become a bit more patient. But how do I get more effective and efficient at delivering that to that really demanding- >> I think you bring up a great point. I mean, it's not just people are getting short-tempered. I think it's more of applications are being deployed faster, security is more exposed if they don't see things quicker. You got data now infrastructure scaling up massively. So, there's a double-edged swords to scale. >> Chris: Yeah, yeah. I mean, maintenance, downtime, uptime, security. So yeah, I think there's a tension around, and one hand enthusiasm around pushing a lot of code and new apps. But is the confidence truly there? It's interesting one little, (snaps finger) supply chain software, look at Container Security for instance. >> Yeah, yeah. It's big. I mean it was codified. >> Do you agree that people, that's kind of an issue right now. >> Yeah, and it was, I mean even the supply chain has been codified by the US federal government saying there's things we need to improve. We don't want to see software being a point of vulnerability, and software includes that whole process of getting it to a running point. >> It's funny you mentioned remote and one of the thing things that you're passionate about, certainly Edge has to be remote. You don't want to roll a truck or labor at the Edge. But I was doing a conversation with, at Rebars last year about space. It's hard to do brake fix on space. It's hard to do a, to roll a someone to configure satellite, right? Right? >> Chris: Yeah. >> So Kubernetes is in space. We're seeing a lot of Cloud Native stuff in apps, in space, so just an example. This highlights the fact that it's got to be automated. Is there a machine learning AI angle with all this ChatGPT talk going on? You see all the AI going the next level. Some pretty cool stuff and it's only, I know it's the beginning, but I've heard people using some of the new machine learning, large language models, large foundational models in areas I've never heard of. Machine learning and data centers, machine learning and configuration management, a lot of different ways. How do you see as the product person, you incorporating the AI piece into the products for Platform9? >> I think that's a lot about looking at the telemetry and the information that we get back and to use one of those like old idle terms, that continuous improvement loop to feed it back in. And I think that's really where machine learning to start with comes into effect. As we run across all these customers, our system that helps at two o'clock in the morning has that telemetry, it's got that data. We can see what's changing and what's happening. So it's writing the right algorithms, creating the right machine learning to- >> So training will work for you guys. You have enough data and the telemetry to do get that training data. >> Yeah, obviously there's a lot of investment required to get there, but that is something that ultimately that could be achieved with what we see in operating people's environments. >> Great. Chris, great to have you here in the studio. Going wide ranging conversation on Kubernetes and Platform9. I guess my final question would be how do you look at the next five years out there? Because you got to run the product management, you got to have that 20 mile steer, you got to look at the customers, you got to look at what's going on in the engineering and you got to kind of have that arc. This is the right path kind of view. What's the five year arc look like for you guys? How do you see this playing out? 'Cause KubeCon is coming up and we're you seeing Kubernetes kind of break away with security? They had, they didn't call it KubeCon Security, they call it CloudNativeSecurityCon, they just had in Seattle inaugural events seemed to go well. So security is kind of breaking out and you got Kubernetes. It's getting bigger. Certainly not going away, but what's your five year arc of of how Platform9 and Kubernetes and Ops evolve? >> It's to stay on that theme, it's focusing on what is most important to our users and getting them to a point where they can just consume it, so they're not having to operate it. So it's finding those big items and bringing that into our platform. It's something that's consumable, that's just taken care of, that's tested with each release. So it's simplifying operations more and more. We've always said freedom in cloud computing. Well we started on, we started on OpenStack and made that simple. Stable, easy, you just have it, it works. We're doing that with Kubernetes. We're expanding out that user, right, we're saying bring your developers in, they can download their Kube conflict. They can see those Containers that are running there. They can access the events, the log files. They can log in and build a VM using KubeVirt. They're self servicing. So it's alleviating pressures off of the Ops team, removing the help desk systems that people still seem to rely on. So it's like what comes into that field that is the next biggest issue? Is it things like CI/CD? Is it simplifying GitOps? Is it bringing in security capabilities to talk to that? Or is that a piece that is a best of breed? Is there a reason that it's been spun out to its own conference? Is this something that deserves a focus that should be a specialized capability instead of tooling and vendors that we work with, that we partner with, that could be brought in as a service. I think it's looking at those trends and making sure that what we bring in has the biggest impact to our users. >> That's awesome. Thanks for coming in. I'll give you the last word. Put a plug in for Platform9 for the people who are watching. What should they know about Platform9 that they might not know about it or what should? When should they call you guys and when should they engage? Take a take a minute to give the plug. >> The plug. I think it's, if your operations team is focused on building Kubernetes, stop. That shouldn't be the cloud. That shouldn't be in the Edge, that shouldn't be at the data center. They should be consuming it. If your engineering teams are all trying different ways and doing different things to use and consume Cloud Native services and Kubernetes, they shouldn't be. You want consistency. That's how you get economies of scale. Provide them with a simple platform that's integrated with all of your enterprise identity where they can just start consuming instead of having to solve these problems themselves. It's those, it's those two personas, right? Where the problems manifest. What are my operations teams doing, and are they delivering to my company or are they building infrastructure again? And are my engineers sprinting or crawling? 'Cause if they're not sprinting, you should be asked the question, do I have the right Cloud Native tooling in my environment and how can I get them back? >> I think it's developer productivity, uptime, security are the tell signs. You get that done. That's the goal of what you guys are doing, your mission. >> Chris: Yep. >> Great to have you on, Chris. Thanks for coming on. Appreciate it. >> Chris: Thanks very much. 0 Okay, this is "theCUBE" here, finding the right path to Cloud Native. I'm John Furrier, host of "theCUBE." Thanks for watching. (upbeat music)

>> Welcome back to SuperCloud2. This is Dave Vellante, and we're here with Jack Greenfield. He's the Vice President of Enterprise Architecture and the Chief Architect for the global technology platform at Walmart. Jack, I want to thank you for coming on the program. Really appreciate your time. >> Glad to be here, Dave. Thanks for inviting me and appreciate the opportunity to chat with you. >> Yeah, it's our pleasure. Now we call what you've built a SuperCloud. That's our term, not yours, but how would you describe the Walmart Cloud Native Platform? >> So WCNP, as the acronym goes, is essentially an implementation of Kubernetes for the Walmart ecosystem. And what that means is that we've taken Kubernetes off the shelf as open source, and we have integrated it with a number of foundational services that provide other aspects of our computational environment. So Kubernetes off the shelf doesn't do everything. It does a lot. In particular the orchestration of containers, but it delegates through API a lot of key functions. So for example, secret management, traffic management, there's a need for telemetry and observability at a scale beyond what you get from raw Kubernetes. That is to say, harvesting the metrics that are coming out of Kubernetes and processing them, storing them in time series databases, dashboarding them, and so on. There's also an angle to Kubernetes that gets a lot of attention in the daily DevOps routine, that's not really part of the open source deliverable itself, and that is the DevOps sort of CICD pipeline-oriented lifecycle. And that is something else that we've added and integrated nicely. And then one more piece of this picture is that within a Kubernetes cluster, there's a function that is critical to allowing services to discover each other and integrate with each other securely and with proper configuration provided by the concept of a service mesh. So Istio, Linkerd, these are examples of service mesh technologies. And we have gone ahead and integrated actually those two. There's more than those two, but we've integrated those two with Kubernetes. So the net effect is that when a developer within Walmart is going to build an application, they don't have to think about all those other capabilities where they come from or how they're provided. Those are already present, and the way the CICD pipelines are set up, it's already sort of in the picture, and there are configuration points that they can take advantage of in the primary YAML and a couple of other pieces of config that we supply where they can tune it. But at the end of the day, it offloads an awful lot of work for them, having to stand up and operate those services, fail them over properly, and make them robust. All of that's provided for. >> Yeah, you know, developers often complain they spend too much time wrangling and doing things that aren't productive. So I wonder if you could talk about the high level business goals of the initiative in terms of the hardcore benefits. Was the real impetus to tap into best of breed cloud services? Were you trying to cut costs? Maybe gain negotiating leverage with the cloud guys? Resiliency, you know, I know was a major theme. Maybe you could give us a sense of kind of the anatomy of the decision making process that went in. >> Sure, and in the course of answering your question, I think I'm going to introduce the concept of our triplet architecture which we haven't yet touched on in the interview here. First off, just to sort of wrap up the motivation for WCNP itself which is kind of orthogonal to the triplet architecture. It can exist with or without it. Currently does exist with it, which is key, and I'll get to that in a moment. The key drivers, business drivers for WCNP were developer productivity by offloading the kinds of concerns that we've just discussed. Number two, improving resiliency, that is to say reducing opportunity for human error. One of the challenges you tend to run into in a large enterprise is what we call snowflakes, lots of gratuitously different workloads, projects, configurations to the extent that by developing and using WCNP and continuing to evolve it as we have, we end up with cookie cutter like consistency across our workloads which is super valuable when it comes to building tools or building services to automate operations that would otherwise be manual. When everything is pretty much done the same way, that becomes much simpler. Another key motivation for WCNP was the ability to abstract from the underlying cloud provider. And this is going to lead to a discussion of our triplet architecture. At the end of the day, when one works directly with an underlying cloud provider, one ends up taking a lot of dependencies on that particular cloud provider. Those dependencies can be valuable. For example, there are best of breed services like say Cloud Spanner offered by Google or say Cosmos DB offered by Microsoft that one wants to use and one is willing to take the dependency on the cloud provider to get that functionality because it's unique and valuable. On the other hand, one doesn't want to take dependencies on a cloud provider that don't add a lot of value. And with Kubernetes, we have the opportunity, and this is a large part of how Kubernetes was designed and why it is the way it is, we have the opportunity to sort of abstract from the underlying cloud provider for stateless workloads on compute. And so what this lets us do is build container-based applications that can run without change on different cloud provider infrastructure. So the same applications can run on WCNP over Azure, WCNP over GCP, or WCNP over the Walmart private cloud. And we have a private cloud. Our private cloud is OpenStack based and it gives us some significant cost advantages as well as control advantages. So to your point, in terms of business motivation, there's a key cost driver here, which is that we can use our own private cloud when it's advantageous and then use the public cloud provider capabilities when we need to. A key place with this comes into play is with elasticity. So while the private cloud is much more cost effective for us to run and use, it isn't as elastic as what the cloud providers offer, right? We don't have essentially unlimited scale. We have large scale, but the public cloud providers are elastic in the extreme which is a very powerful capability. So what we're able to do is burst, and we use this term bursting workloads into the public cloud from the private cloud to take advantage of the elasticity they offer and then fall back into the private cloud when the traffic load diminishes to the point where we don't need that elastic capability, elastic capacity at low cost. And this is a very important paradigm that I think is going to be very commonplace ultimately as the industry evolves. Private cloud is easier to operate and less expensive, and yet the public cloud provider capabilities are difficult to match. >> And the triplet, the tri is your on-prem private cloud and the two public clouds that you mentioned, is that right? >> That is correct. And we actually have an architecture in which we operate all three of those cloud platforms in close proximity with one another in three different major regions in the US. So we have east, west, and central. And in each of those regions, we have all three cloud providers. And the way it's configured, those data centers are within 10 milliseconds of each other, meaning that it's of negligible cost to interact between them. And this allows us to be fairly agnostic to where a particular workload is running. >> Does a human make that decision, Jack or is there some intelligence in the system that determines that? >> That's a really great question, Dave. And it's a great question because we're at the cusp of that transition. So currently humans make that decision. Humans choose to deploy workloads into a particular region and a particular provider within that region. That said, we're actively developing patterns and practices that will allow us to automate the placement of the workloads for a variety of criteria. For example, if in a particular region, a particular provider is heavily overloaded and is unable to provide the level of service that's expected through our SLAs, we could choose to fail workloads over from that cloud provider to a different one within the same region. But that's manual today. We do that, but people do it. Okay, we'd like to get to where that happens automatically. In the same way, we'd like to be able to automate the failovers, both for high availability and sort of the heavier disaster recovery model between, within a region between providers and even within a provider between the availability zones that are there, but also between regions for the sort of heavier disaster recovery or maintenance driven realignment of workload placement. Today, that's all manual. So we have people moving workloads from region A to region B or data center A to data center B. It's clean because of the abstraction. The workloads don't have to know or care, but there are latency considerations that come into play, and the humans have to be cognizant of those. And automating that can help ensure that we get the best performance and the best reliability. >> But you're developing the dataset to actually, I would imagine, be able to make those decisions in an automated fashion over time anyway. Is that a fair assumption? >> It is, and that's what we're actively developing right now. So if you were to look at us today, we have these nice abstractions and APIs in place, but people run that machine, if you will, moving toward a world where that machine is fully automated. >> What exactly are you abstracting? Is it sort of the deployment model or, you know, are you able to abstract, I'm just making this up like Azure functions and GCP functions so that you can sort of run them, you know, with a consistent experience. What exactly are you abstracting and how difficult was it to achieve that objective technically? >> that's a good question. What we're abstracting is the Kubernetes node construct. That is to say a cluster of Kubernetes nodes which are typically VMs, although they can run bare metal in certain contexts, is something that typically to stand up requires knowledge of the underlying cloud provider. So for example, with GCP, you would use GKE to set up a Kubernetes cluster, and in Azure, you'd use AKS. We are actually abstracting that aspect of things so that the developers standing up applications don't have to know what the underlying cluster management provider is. They don't have to know if it's GCP, AKS or our own Walmart private cloud. Now, in terms of functions like Azure functions that you've mentioned there, we haven't done that yet. That's another piece that we have sort of on our radar screen that, we'd like to get to is serverless approach, and the Knative work from Google and the Azure functions, those are things that we see good opportunity to use for a whole variety of use cases. But right now we're not doing much with that. We're strictly container based right now, and we do have some VMs that are running in sort of more of a traditional model. So our stateful workloads are primarily VM based, but for serverless, that's an opportunity for us to take some of these stateless workloads and turn them into cloud functions. >> Well, and that's another cost lever that you can pull down the road that's going to drop right to the bottom line. Do you see a day or maybe you're doing it today, but I'd be surprised, but where you build applications that actually span multiple clouds or is there, in your view, always going to be a direct one-to-one mapping between where an application runs and the specific cloud platform? >> That's a really great question. Well, yes and no. So today, application development teams choose a cloud provider to deploy to and a location to deploy to, and they have to get involved in moving an application like we talked about today. That said, the bursting capability that I mentioned previously is something that is a step in the direction of automatic migration. That is to say we're migrating workload to different locations automatically. Currently, the prototypes we've been developing and that we think are going to eventually make their way into production are leveraging Istio to assess the load incoming on a particular cluster and start shedding that load into a different location. Right now, the configuration of that is still manual, but there's another opportunity for automation there. And I think a key piece of this is that down the road, well, that's a, sort of a small step in the direction of an application being multi provider. We expect to see really an abstraction of the fact that there is a triplet even. So the workloads are moving around according to whatever the control plane decides is necessary based on a whole variety of inputs. And at that point, you will have true multi-cloud applications, applications that are distributed across the different providers and in a way that application developers don't have to think about. >> So Walmart's been a leader, Jack, in using data for competitive advantages for decades. It's kind of been a poster child for that. You've got a mountain of IP in the form of data, tools, applications best practices that until the cloud came out was all On Prem. But I'm really interested in this idea of building a Walmart ecosystem, which obviously you have. Do you see a day or maybe you're even doing it today where you take what we call the Walmart SuperCloud, WCNP in your words, and point or turn that toward an external world or your ecosystem, you know, supporting those partners or customers that could drive new revenue streams, you know directly from the platform? >> Great questions, Dave. So there's really two things to say here. The first is that with respect to data, our data workloads are primarily VM basis. I've mentioned before some VMware, some straight open stack. But the key here is that WCNP and Kubernetes are very powerful for stateless workloads, but for stateful workloads tend to be still climbing a bit of a growth curve in the industry. So our data workloads are not primarily based on WCNP. They're VM based. Now that said, there is opportunity to make some progress there, and we are looking at ways to move things into containers that are currently running in VMs which are stateful. The other question you asked is related to how we expose data to third parties and also functionality. Right now we do have in-house, for our own use, a very robust data architecture, and we have followed the sort of domain-oriented data architecture guidance from Martin Fowler. And we have data lakes in which we collect data from all the transactional systems and which we can then use and do use to build models which are then used in our applications. But right now we're not exposing the data directly to customers as a product. That's an interesting direction that's been talked about and may happen at some point, but right now that's internal. What we are exposing to customers is applications. So we're offering our global integrated fulfillment capabilities, our order picking and curbside pickup capabilities, and our cloud powered checkout capabilities to third parties. And this means we're standing up our own internal applications as externally facing SaaS applications which can serve our partners' customers. >> Yeah, of course, Martin Fowler really first introduced to the world Zhamak Dehghani's data mesh concept and this whole idea of data products and domain oriented thinking. Zhamak Dehghani, by the way, is a speaker at our event as well. Last question I had is edge, and how you think about the edge? You know, the stores are an edge. Are you putting resources there that sort of mirror this this triplet model? Or is it better to consolidate things in the cloud? I know there are trade-offs in terms of latency. How are you thinking about that? >> All really good questions. It's a challenging area as you can imagine because edges are subject to disconnection, right? Or reduced connection. So we do place the same architecture at the edge. So WCNP runs at the edge, and an application that's designed to run at WCNP can run at the edge. That said, there are a number of very specific considerations that come up when running at the edge, such as the possibility of disconnection or degraded connectivity. And so one of the challenges we have faced and have grappled with and done a good job of I think is dealing with the fact that applications go offline and come back online and have to reconnect and resynchronize, the sort of online offline capability is something that can be quite challenging. And we have a couple of application architectures that sort of form the two core sets of patterns that we use. One is an offline/online synchronization architecture where we discover that we've come back online, and we understand the differences between the online dataset and the offline dataset and how they have to be reconciled. The other is a message-based architecture. And here in our health and wellness domain, we've developed applications that are queue based. So they're essentially business processes that consist of multiple steps where each step has its own queue. And what that allows us to do is devote whatever bandwidth we do have to those pieces of the process that are most latency sensitive and allow the queue lengths to increase in parts of the process that are not latency sensitive, knowing that they will eventually catch up when the bandwidth is restored. And to put that in a little bit of context, we have fiber lengths to all of our locations, and we have I'll just use a round number, 10-ish thousand locations. It's larger than that, but that's the ballpark, and we have fiber to all of them, but when the fiber is disconnected, When the disconnection happens, we're able to fall back to 5G and to Starlink. Starlink is preferred. It's a higher bandwidth. 5G if that fails. But in each of those cases, the bandwidth drops significantly. And so the applications have to be intelligent about throttling back the traffic that isn't essential, so that it can push the essential traffic in those lower bandwidth scenarios. >> So much technology to support this amazing business which started in the early 1960s. Jack, unfortunately, we're out of time. I would love to have you back or some members of your team and drill into how you're using open source, but really thank you so much for explaining the approach that you've taken and participating in SuperCloud2. >> You're very welcome, Dave, and we're happy to come back and talk about other aspects of what we do. For example, we could talk more about the data lakes and the data mesh that we have in place. We could talk more about the directions we might go with serverless. So please look us up again. Happy to chat. >> I'm going to take you up on that, Jack. All right. This is Dave Vellante for John Furrier and the Cube community. Keep it right there for more action from SuperCloud2. (upbeat music)

>> John: Hello and welcome to this cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great conversation on making machine learning easier and more affordable in an era where everybody wants more machine learning and AI. We're featuring Neural Magic with the CEO is also Cube alumni, Brian Steve. CEO, Great to see you Brian. Thanks for coming on this cube conversation. Talk about machine learning. >> Brian: Hey John, happy to be here again. >> John: What a buzz that's going on right now? Machine learning, one of the hottest topics, AI front and center, kind of going mainstream. We're seeing the success of the, of the kind of NextGen capabilities in the enterprise and in apps. It's a really exciting time. So perfect timing. Great, great to have this conversation. Let's start with taking a minute to explain what you guys are doing over there at Neural Magic. I know there's some history there, neural networks, MIT. But the, the convergence of what's going on, this big wave hitting, it's an exciting time for you guys. Take a minute to explain the company and your mission. >> Brian: Sure, sure, sure. So, as you said, the company's Neural Magic and spun out at MIT four plus years ago, along with some people and, and some intellectual property. And you summarize it better than I can cause you said, we're just trying to make, you know, AI that much easier. And so, but like another level of specificity around it is. You know, in the world you have a lot of like data scientists really focusing on making AI work for whatever their use case is. And then the next phase of that, then they're looking at optimizing the models that they built. And then it's not good enough just to work on models. You got to put 'em into production. So, what we do is we make it easier to optimize the models that have been developed and trained and then trying to make it super simple when it comes time to deploying those in production and managing them. >> Brian: You know, we've seen this movie before with the cloud. You start to see abstractions come out. Data science we saw like was like the, the secret art of being like a data scientist now democratization of data. You're kind of seeing a similar wave with machine learning models, foundational models, some call it developers are getting involved. Model complexity's still there, but, but it's getting easier. There's almost like the democratization happening. You got complexity, you got deployment, it's challenges, cost, you got developers involved. So it's like how do you grow it? How do you get more horsepower? And then how do you make developers productive, right? So like, this seems to be the thread. So, so where, where do you see this going? Because there's going to be a massive demand for, I want to do more with my machine learning. But what's the data source? What's the formatting? This kind of a stack develop, what, what are you guys doing to address this? Can you take us through and demystify this, this wave that's hitting, that everyone's seeing? >> Brian: Yeah. Now like you said, like, you know, the democratization of all of it. And that brings me all the way back to like the roots of open source, right? When you think about like, like back in the day you had to build your own tech stack yourself. A lot of people probably probably don't remember that. And then you went, you're building, you're always starting on a body of code or a module that was out there with open source. And I think that's what I equate to where AI has gotten to with what you were talking about the foundational models that didn't really exist years ago. So you really were like putting the layers of your models together in the formulas and it was a lot of heavy lifting. And so there was so much time spent on development. With far too few success cases, you know, to get into production to solve like a business stereo technical need. But as these, what's happening is as these models are becoming foundational. It's meaning people don't have to start from scratch. They're actually able to, you know, the avant-garde now is start with existing model that almost does what you want, but then applying your data set to it. So it's, you know, it's really the industry moving forward. And then we, you know, and, and the best thing about it is open source plays a new dimension, but this time, you know, in the, in the realm of AI. And so to us though, like, you know, I've been like, I spent a career focusing on, I think on like the, not just the technical side, but the consumption of the technology and how it's still way too hard for somebody to actually like, operationalize technology that all those vendors throw at them. So I've always been like empathetic the user around like, you know what their job is once you give them great technology. And so it's still too difficult even with the foundational models because what happens is there's really this impedance mismatch between the development of the model and then where, where the model has to live and run and be deployed and the life cycle of the model, if you will. And so what we've done in our research is we've developed techniques to introduce what's known as sparsity into a machine learning model. It's already been developed and trained. And what that sparsity does is that unlocks by making that model so much smaller. So in many cases we can make a model 90 to 95% smaller, even smaller than that in research. So, and, and so by doing that, we do that in a way that preserves all the accuracy out of the foundational model as you talked about. So now all of a sudden you get this much smaller model just as accurate. And then the even more exciting part about it is we developed a software-based engine called Deep Source. And what that, what the Inference Runtime does is takes that now sparsified model and it runs it, but because you sparsified it, it only needs a fraction of the compute that it, that it would've needed otherwise. So what we've done is make these models much faster, much smaller, and then by pairing that with an inference runtime, you now can actually deploy that model anywhere you want on commodity hardware, right? So X 86 in the cloud, X 86 in the data center arm at the edge, it's like this massive unlock that happens because you get the, the state-of-the-art models, but you get 'em, you know, on the IT assets and the commodity infrastructure. That is where all the applications are running today. >> John: I want to get into the inference piece and the deep sparse you mentioned, but I first have to ask, you mentioned open source, Dave and I with some fellow cube alumnis. We're having a chat about, you know, the iPhone and Android moment where you got proprietary versus open source. You got a similar thing happening with some of these machine learning modules where there's a lot of proprietary things happening and there's open source movement is growing. So is there a balance there? Are they all trying to do the same thing? Is it more like a chip, you know, silicons involved, all kinds of things going on that are really fascinating from a science. What's your, what's your reaction to that? >> Brian: I think it's like anything that, you know, the way we talk about AI you think had been around for decades, but the reality is it's been some of the deep learning models. When we first, when we first started taking models that the brain team was working on at Google and billing APIs around them on Google Cloud where the first cloud to even have AI services was 2015, 2016. So when you think about it, it's really been what, 6 years since like this thing is even getting lift off. So I think with that, everybody's throwing everything at it. You know, there's tons of funded hardware thrown at specialty for training or inference new companies. There's legacy companies that are getting into like AI now and whether it's a, you know, a CPU company that's now building specialized ASEX for training. There's new tech stacks proprietary software and there's a ton of asset service. So it really is, you know, what's gone from nascent 8 years ago is the wild, wild west out there. So there's a, there's a little bit of everything right now and I think that makes sense because at the early part of any industry it really becomes really specialized. And that's the, you know, showing my age of like, you know, the early pilot of the two thousands, you know, red Hat people weren't running X 86 in enterprise back then and they thought it was a toy and they certainly weren't running open source, but you really, and it made sense that they weren't because it didn't deliver what they needed to at that time. So they needed specialty stacks, they needed expensive, they needed expensive hardware that did what an Oracle database needed to do. They needed proprietary software. But what happens is that commoditizes through both hardware and through open source and the same thing's really just starting with with AI. >> John: Yeah. And I think that's a great point before we to call that out because in any industry timing's everything, right? I mean I remember back in the 80s, late 80s and 90s, AI, you know, stuff was going on and it just wasn't, there wasn't enough horsepower, there wasn't enough tech. >> Brian: Yep. >> John: You mentioned some of the processing. So AI is this industry that has all these experts who have been itch scratching that itch for decades. And now with cloud and custom silicon. The tech fundamental at the lower end of the stack, if you will, on the performance side is significantly more performant. It's there you got more capabilities. >> Brian: Yeah. >> John: Now you're kicking into more software, faster software. So it just seems like we're at a tipping point where finally it's here, like that AI moment or machine learning and now data is, is involved. So this is where organizations I see really jumping in with the CEO mandate. Hey team, make ML work for us. Go figure it out. It's got to be an advantage for us. >> Brian: Yeah. >> John: So now they go, okay boss, we will. So what, what do they do? What's the steps does an enterprise take to get machine learning into their organizations? Cause you know, it's coming down from the boards, you know, how does this work for rob? >> Brian: Yeah. Like the, you know, the, what we're seeing is it's like anything, like it's, whether that was source adoption or whether that was cloud adoption, it always starts usually with one person. And increasingly it is the CEO, which realizes they're getting further behind the competition because they're not leaning in, you know, faster. But typically it really comes down to like a really strong practitioner that's inside the organization, right? And, that realizes that the number one goal isn't doing more and just training more models and and necessarily being proprietary about it. It's really around understanding the art of the possible. Something that's grounded in the art of the possible, what, what deep learning can do today and what business outcomes you can deliver, you know, if you can employ. And then there's well proven paths through that. It's just that because of where it's been, it's not that industrialized today. It's very much, you know, you see ML project by ML project is very snowflakey, right? And that was kind of the early days of open source as well. And so, we're just starting to get to the point where it's getting easier, it's getting more industrialized, there's less steps, there's less burdensome on developers, there's less burdensome on, on the deployment side. And we're trying to bring that, that whole last mile by saying, you know what? Deploying deep learning and AI models should be as easy as the as to deploy your application, right? You shouldn't have to take an extra step to deploy an AI model. It shouldn't have to require a new hardware, it shouldn't require a new process, a new DevOps model. It should be as simple as what you're already doing. >> John: What is the best practice for companies to effectively bring an acceptable level of machine learning and performance into their organizations? >> Brian: Yeah, I think like the, the number one start is like what you hinted at before is they, they have to know the use case. They have to, in most cases, you're going to find across every industry you know, that that problem's been tackled by some company, right? And then you have to have the best practice around fine-tuning the models already exist. So fine tuning that existing model. That foundational model on your unique dataset. You, you know, if you are in medical instruments, it's not good enough to identify that it's a medical instrument in the picture. You got to know what type of medical instrument. So there's always a fine tuning step. And so we've created open source tools that make it easy for you to do two things at once. You can fine tune that existing foundational model, whether that's in the language space or whether that's in the vision space. You can fine tune that on your dataset. And at the same time you get an optimized model that comes out the other end. So you get kind of both things. So you, you no longer have to worry about you're, we're freeing you from worrying about the complexity of that transfer learning, if you will. And we're freeing you from worrying about, well where am I going to deploy the model? Where does it need to be? Does it need to be on a device, an edge, a data center, a cloud edge? What kind of hardware is it? Is there enough hardware there? We're liberating you from all of that. Because what you want, what you can count on is there'll always be commodity capability, commodity CPUs where you want to deploy in abundance cause that's where your application is. And so all of a sudden we're just freeing you of that, of that whole step. >> John: Okay. Let's get into deep sparse because you mentioned that earlier. What inspired the creation of deep sparse and how does it differ from any other solutions in the market that are out there? >> Brian: Sure. So, so where unique is it? It starts by, by two things. One is what the industry's pretty good at from the optimization side is they're good at like this thing called quantization, which turns like, you know, big numbers into small numbers, lower precision. So a 32 bit representation of a, of AI weight into a bit. And they're good at like cutting out layers, which also takes away accuracy. What we've figured out is to take those, the industry techniques for those that are best practice, but we combined it with unstructured varsity. So by reducing that model by 90 to 95% in size, that's great because it's made it smaller. But we've taken that when it's the deep sparse engine, when you deploy it that looks at that model and says, because it's so much smaller, I no longer have to run the part of the model that's been essentially sparsified. So what that's done is, it's meant that you no longer need a supercomputer to run models because there's not nearly as much math and processing as there was before the model was optimized. So now what happens is, every CPU platform out there has, has an enormous amount of compute because we've sparsified the rest of it away. So you can pick a, you can pick your, your laptop and you have enough compute to run state-of-the-art models. The second thing that, and you need a software engine to do that cause it ignores the parts of the models. It doesn't need to run, which is what like specialized hardware can't do. The second part is it's then turned into a memory efficiency problem. So it's really around just getting memory, getting the models loaded into the cash of the computer and keeping it there. Never having to go back out to memory. So, so our techniques are both, we reduce the model size and then we only run the part of the model that matters and then we keep it all in cash. And so what that does is it gets us to like these, these low, low latency faster and we're able to increase, you know, the CPU processing by an order magnitude. >> John: Yeah. That low latency is key. And you got developers, you know, co coding super fast. We'll get to the developer angle in a second. I want to just follow up on this, this motivation behind the, the deep sparse because you know, as we were talking earlier before we came on camera about the old days, I mean, not too long ago, virtualization and VMware abstracted away the os from, from the hardware rights and the server virtualization changed the game. >> Brian: Yeah. >> John: And that basically invented cloud computing as we know it today. So, so we see that abstraction. >> Brian: Yeah. >> John: There seems to be a motivation behind abstracting the way the machine learning models away from the hardware. And that seems to be bringing advantages to the AI growth. Can you elaborate on, is that true? And it's, what's your comment? >> Brian: It's true. I think it's true for us. I don't think the industry's there yet, honestly. Cause I think the industry still is of that mindset that if I took, if it took these expensive GPUs to train my model, then I want to run my model on those same expensive GPUs. Because there's often like not a separation between the people that are developing AI and the people that have to manage and deploy at where you need it. So the reality is, is that that's everything that we're after. Like, do we decrease the cost? Yes. Do we make the models smaller? Yes. Do we make them faster? A yes. But I think the most amazing power is that we've turned AI into a docker based microservice. And so like who in the industry wants to deploy their apps the old way on a os without virtualization, without docker, without Kubernetes, without microservices, without service mesh without serverless. You want all those tools for your apps by converting AI models. So they can be run inside a docker container with no apologies around latency and performance cause it's faster. You get the best of that whole world that you just talked about, which is, you know, what we're calling, you know, software delivered AI. So now the AI lives in the same world. Organizations that have gone through that digital cloud transformation with their app infrastructure. AI fits into that world. >> John: And this is where the abstraction concepts matter. When you have these inflection points, the convergence of compute data, machine learning that powers AI, it really becomes a developer opportunity. Because now applications and businesses, when they actually go through the digital transformation, their businesses are completely transformed. There is no IT. Developers are the application. They are the company, right? So AI will be part of whatever business or app will be out there. So there is a application developer angle here. Brian, can you explain >> Brian: Oh completely. >> John: how they're going to use this? Because you mentioned docker container microservice, I mean this really is an insane flipping of the script for developers. >> Brian: Yeah. >> John: So what's that look like? >> Brian: Well speak, it's because like AI's kind of, I mean, again, like it's come so fast. So you figure there's my app team and here's my AI team, right? And they're in different places and the AI team is dragging in specialized infrastructure in support of that as well. And that's not how app developers think. Like they've ran on fungible infrastructure that subtracted and virtualized forever, right? And so what we've done is we've, in addition to fitting into that world that they, that they like, we've also made it simple for them for they don't have to be a machine learning engineer to be able to experiment with these foundational models and transfer learning 'em. We've done that. So they can do that in a couple of commands and it has a simple API that they can either link to their application directly as a library to make difference calls or they can stand it up as a standalone, you know, scale up, scale out inference server. They get two choices. But it really fits into that, you know, you know that world that the modern developer, whether they're just using Python or C or otherwise, we made it just simple. So as opposed to like Go learn something else, they kind of don't have to. So in a way though, it's made it. It's almost made it hard because people expect when we talk to 'em for the first time to be the old way. Like, how do you look like a piece of hardware? Are you compatible with my existing hardware that runs ML? Like, no, we're, we're not. Because you don't need that stack anymore. All you need is a library called to make your prediction and that's it. That's it. >> John: Well, I mean, we were joking on Twitter the other day with someone saying, is AI a pet or a cattle? Right? Because they love their, their AI bots right now. So, so I'd say pet there. But you look at a lot of, there's going to be a lot of AI. So on a more serious note, you mentioned in microservices, will deep sparse have an API for developers? And how does that look like? What do I do? >> Brian: Yeah. >> John: tell me what my, as a developer, what's the roadmap look like? What's the >> Brian: Yeah, it, it really looks, it really can go in both modes. It can go in a standalone server mode where it handles, you know, rest API and it can scale out with ES as the workload comes up and scale back and like try to make hardware do that. Hardware may scale back, but it's just sitting there dormant, you know, so with this, it scales the same way your application needs to. And then for a developer, they basically just, they just, the PIP install de sparse, you know, has one commanded to do an install, and then they do two calls, really. The first call is a library call that the app makes to create the model. And models really already trained, but they, it's called a model create call. And the second command they do is they make a call to do a prediction. And it's as simple as that. So it's, it's AI's as simple as using any other library that the developers are already using, which I, which sounds hard to fathom because it is just so simplified. >> John: Software delivered AI. Okay, that's a cool thing. I believe in it personally. I think that's the way to go. I think there's going to be plenty of hardware options if you look at the advances of cloud players that got more silicon coming out. Yeah. More GPU. I mean, there's more instance, I mean, everything's out there right now. So the question is how does that evolve in your mind? Because that's seems to be key. You have open source projects emerging. What, what path does this take? Is there a parallel mental model that you see, Brian, that is similar? You mentioned open source earlier. Is it more like a VMware virtualization thing or is it more of a cloud thing? Is there Yeah. Is it going to evolve in a, in a trajectory that looks similar to what we might've seen in the past? >> Brian: Yeah, we're, you know, when I, when when I got involved with the company, what I, when I thought about it and I was reasoning about it, like, do you, you know, you want to, like, we all do when you want to join something full-time. I thought about it and said, where will the industry eventually get to? Right? To fully realize the value of, of deep learning and what's plausible as it evolves. And to me, like I, I know it's the old adage of, you know, you know, software, its hardware, cloudy software. But it truly was like, you know, we can solve these problems in software. Like there's nothing special that's happening at the hardware layer and the processing AI. The reality is that it's just early in the industry. So the view that that we had was like, this is eventually the best place where the industry will be, is the liberation of being able to run AI anywhere. Like you're really not democratizing, you democratize the model. But if you can't run the model anywhere you want because these models are getting bigger and bigger with these large language models, then you're kind of not democratizing. And if you got to go and like by a cluster to run this thing on. So the democratization comes by if all of a sudden that model can be consumed anywhere on demand without planning, without provisioning, wherever infrastructure is. And so I think that's with or without Neural Magic, that's where the industry will go and will get to. I think we're the leaders, leaders in getting it there. It's right because we're more advanced on these techniques. >> John: Yeah. And your background too. You've seen OpenStack, pre-cloud, you saw open source grow and still exponentially growing. And so you have the same similar dynamic with machine learning models growing. And they're also segmenting into almost a, an ML stack or foundational model as we talk about. So you're starting to see the formation of tooling inference. So a lot of components coming. It's almost a stack, it's almost a, it literally is like an operating system problem space, you know? How do you run things, how do you link things? How do you bring things together? Is that what's going on here? Is this like a data modeling operating environment kind of red hat type thing going on? Like. >> Brian: Yeah. Yeah. Like I think there is, you know, I thought about that too. And I think there is the role of like distribution, because the industrialization not happening fast enough of this. Like, can I go back to like every customers, every, every user does it in their own kind of way. Like it's not, everyone's a little bit of a snowflake. And I think that's okay. There's definitely plenty of companies that want to come in and say, well, this is the way it's going to be and we industrialize it as long as you do it our way. The reality is technology doesn't get industrialized by one company just saying, do it our way. And so that's why like we've taken the approach through open source by saying like, Hey, you haven't really industrialized it if you said. We made it simple, but you always got to run AI here. Yeah, right. You only like really industrialize it if you break it down into components that are simple to use and they work integrated in the stack the way you want them to. And so to me, that first principles was getting thing into microservices and dockers that could be run on VMware, OpenShare on the cloud in the edge. And so that's the, that's the real part that we're happening with. The other part, like I do agree, like I think it's going to quickly move into less about the model. Less about the training of the model and the transfer learning, you know, the data set of the model. We're taking away the complexity of optimization. Giving liberating deployment to be anywhere. And I think the last mile, John is going to be around the ML ops around that. Because it's easy to think of like soft now that it's just a software problem, we've turned it into a software problem. So it's easy to think of software as like kind of a point release, but that's not the reality, right? It's a life cycle. And it's, and so I think ML very much brings in the what is the lifecycle of that deployment? And, you know, you get into more interesting conversations, to be honest than like, once you've deployed in a docking container is around like model drift and accuracy and the dataset changes and the user changes is how do you become from an ML perspective of where of that sending signal back retraining. And, and that's where I think a lot of the, in more of the innovation's going to start to move there. >> John: Yeah. And software also, the software problem, the software opportunity as well is developer focused. And if you look at the cloud native landscape now, similar stacks developing a lot of components. A lot of things to, to stitch together a lot of things that are automating under the hood. A lot of developer productivity conversations. I think this is going to go down that same road. I want to get your thoughts because developers will set the pace. And this is something that's clear in this next wave developer productivity. They're the defacto standards bodies. They will decide what microservices check, API check. Now, skill gap is going to be a problem because it's relatively new. So model sprawl, model sizes, proprietary versus open. There has to be a way to kind of crunch that down into a, like a DevOps, like just make it, get the developer out of the, the muck. So what's your view? Are we early days like that? Or what's the young kid in college studying CS or whatever degree who comes into this with, with both feet? What are they doing? >> Brian: I'll probably say like the, the non-popular answer to that. A little bit is it's happening so fast that it's going to get kind of boring fast. Meaning like, yeah, you could go to school and go to MIT, right? Sorry. Like, and you could get a hold through end like becoming a model architect, like inventing the next model, right? And the layers and combining 'em and et cetera, et cetera. And then what operators and, and building a model that's bigger than the last one and trains faster, right? And there will be those people, right? That actually, like they're building the engines the same way. You know, I grew up as an infrastructure software developer. There's not a lot of companies that hire those anymore because they're all sitting inside of three big clouds. Yeah. Right? So you better be a good app developer, but I think what you're going to see is before you had to be everything, you had to be the, if you were going to use infrastructure, you had to know how to build infrastructure. And I think the same thing's true around is quickly exiting ML is to be able to use ML in your company, you better be like, great at every aspect of ML, including every intricacy inside of the model and every operation's doing, that's quickly changing. Like, you're going to start with a starting point. You know, in the future you're not going to be like cracking open these GPT models, you're going to just be pulling them off the shelf, fine tuning 'em and go. You don't have to invent it. You don't have to understand it. And I think that's going to be a pivot point, you know, in the industry between, you know, what's the future? What's, what's the future of a, a data scientist? ML engineer researcher look like? >> John: I think that's, the outcome's going to be determined. I mean, you mentioned, you know, doing it yourself what an SRE is for a Google with the servers scale's huge. So yeah, it might have to, at the beginning get boring, you get obsolete quickly, but that means it's progressing. So, The scale becomes huge. And that's where I think it's going to be interesting when we see that scale. >> Brian: Yep. Yeah, I think that's right. I think that's right. And we always, and, and what I've always said, and much the, again, the distribute into my ML team is that I want every developer to be as adept at being able take advantage of ML as non ML engineer, right? It's got to be that simple. And I think, I think it's getting there. I really do. >> John: Well, Brian, great, great to have you on theCUBE here on this cube conversation. As part of the startup showcase that's coming up. You're going to be featured. Or your company would featured on the upcoming ABRA startup showcase on making machine learning easier and more affordable as more machine learning models come in. You guys got deep sparse and some great technology. We're going to dig into that next time. I'll give you the final word right now. What do you see for the company? What are you guys looking for? Give a plug for the company right now. >> Brian: Oh, give a plug that I haven't already doubled in as the plug. >> John: You're hiring engineers, I assume from MIT and other places. >> Brian: Yep. I think like the, the biggest thing is like, like we're on the developer side. We're here to make this easy. The majority of inference today is, is on CPUs already, believe it or not, as much as kind of, we like to talk about hardware and specialized hardware. The majority is already on CPUs. We're basically bringing 95% cost savings to CPUs through this acceleration. So, but we're trying to do it in a way that makes it community first. So I think the, the shout out would be come find the Neural Magic community and engage with us and you'll find, you know, a thousand other like-minded people in Slack that are willing to help you as well as our engineers. And, and let's, let's go take on some successful AI deployments. >> John: Exciting times. This is, I think one of the pivotal moments, NextGen data, machine learning, and now starting to see AI not be that chat bot, just, you know, customer support or some basic natural language processing thing. You're starting to see real innovation. Brian Stevens, CEO of Neural Magic, bringing the magic here. Thanks for the time. Great conversation. >> Brian: Thanks John. >> John: Thanks for joining me. >> Brian: Cheers. Thank you. >> John: Okay. I'm John Furrier, host of theCUBE here in Palo Alto, California for this cube conversation with Brian Stevens. Thanks for watching.

>> John Furrier: Hello, welcome back to theCUBE's coverage of Cloud Native Security Con 2023 North America the inaugural event. I'm John Furrier, host of theCUBE, along with Dave Alonte and Lisa Martin covering from the studio. But we have on location Emmy Eide, who is with Red Hat, director of Supply Chain Security. Emmy, great to have you on from location. Thanks for joining us. >> Emmy Eide: Yeah, thank you. >> So everyone wants to know this event is new, it's an aural event, cloud native con, coup con. Very successful. Was this event successful? They all want to know what's going on there. What's the vibe? What's the tracks like? Is it different? Why this event? Was it successful? What's different? >> Yeah, I've really enjoyed being here. The food is wonderful. There's also quite a few vendors here that are just some really cool emerging technologies coming out and a lot from open source, which is really cool to see as well. The talks are very interesting. It's really, they're very diverse in subject but still all security related which is really cool to see. And there's also a lot of different perspectives of how to approach security problems and the people behind them, which I love to see. And it's very nice to hear the different innovative ideas that we can go about doing security. >> We heard from some startups as well that they're very happy with the, with the decision to have a dedicated event. Red Hat is no stranger to open source. Obviously coup con, you guys are very successful there in cloud native con, Now the security con. Why do you think they did this? What's the vibe? What's the rationale? What's your take on this? And what's different from a topic standpoint? >> For non-security specific like events? Is that what you mean? >> What's different from coup con, cloud native con, and here at the cloud native security con? Obviously security's the focus. Is it just deeper dives? Is it more under the hood? Is it root problems or is this beyond Kubernetes? What's the focus, I guess. People want to know, you know, why the new event? >> I mean, there's a lot of focus on supply chain security, right? Like that's the hot topic in security right now. So that's been a huge focus. I can't speak to the differences of those other conferences. I haven't been able to attend them. But I will say that having a security specific conference, it really focuses on the open community and how technology is evolving, and how do you apply security. It's not just talking about tools which I think other conferences tend to focus on just the tools and you can really, I think, get lost in that as someone trying to learn about security or trying to even implement security, but they talk about what it takes to implement those tools, What's behind the people behind implementing those tools? >> Let's get into some of the key topics that we've identified and get your reaction. One, supply chain security, which I know you'll give a lot of commentary on 'cause that's your focus. Also we heard, like, Liz Rice talking about the extended Berkeley packet filtering. Okay, that's big. You know, your root kernel management, that's big. Developer productivity was kind of implied around removing the blockers of security, making it, you know, more aligned with developer first mentality. So that seems to be our takeaway. What's your reaction to those things? You see the same thing? >> I don't have a specific reaction to those things. >> Do you see the same thing happening on the ground there? Are they covering supply? >> Oh, yeah. >> Those three things are they the big focus? >> Yeah. Yeah, I think it's all of those things kind of like wrapped into one, right? But yeah, there's... I'm not sure how to answer your question. >> Well, let's jump into supply chain for instance. 'Cause that has come up a lot. >> Sure. >> What's the focus there on the supply chain security? Is it SBOMs? Is it the container security? What's the key conversations and topics being discussed around supply chain security? >> Well, I think there's a lot of laughter around SBOM right now because no one can really define it, specifically, and everyone's talking about it. So there's, there's a lot more than just the SBOM conversation. We're talking about like full end-to-end development process and that whole software supply chain that goes with it. So there's everything from infrastructure, security, all the way through to like signing transparency logs. Really the full gambit of supply chain, which is is really neat to see because it is such a broad topic. I think a lot of folks now are involved in supply chain security in some way. And so just kind of bringing that to the surface of what are the different people that are involved in this space, thinking about, what's on the top of their mind when it comes to supply chain security. >> How would you scope the order of magnitude of the uptick in supply chain attacks? Is it pretty heavy right now or is it, you know, people with the hair on fire or is it... What's the, give us the taste of the temperature in the room on the supply chain attacks? >> I think most of the folks who are involved in the space understand just that it's increasing. I mean, like, what is it? A 742% increase average annual year, year over year in supply chain attacks. So the amount of attacks increasing is a little daunting, right, for most of us. But it is what it is. So I think most of us right now are just trying to come together to say, "What are you doing that works? This is what I'm doing that works." And in all the different facets of that. 'cause I think we try to throw, we try to throw tools at a lot of problems and this problem is so big and broad reaching that we really are needing to share best practices as a community and as a security community. So this has been, this conference has been really great for that. >> Yeah, I've heard that a lot. You know, too many tools, not enough platform thinking, not enough architecture, needs some structure. Are you seeing any best practice around frameworks and structure around how to start getting in and and building out more of a better approach or posture? I mean, what's that, what's the, what's the state of the union for supply chain, how to handle that? >> Well, I talked about that a little bit in my my keynote that I gave, actually, which was about... And I've heard other other leaders talk about it too. And obviously it keyed my ear just because I'm so passionate about it, about partnership. So you know, empathetic security where the security team that's enforcing the policies, creating the policies, guidelines is working with the teams that are actually doing the production and the development, hand-in-hand, right? Like I can sit there and tell you, "Hey, you have all these problems and here's your security checklist or framework you need to follow." But that's not going to do them any good and it's going to create a ton of holes, right? So actually partnering with them helping them to understand the risks that are associated with their very specific need and use case, because every product has a different kind of quirk to it, right? Like how it's being developed. It might use a different tool and if I sit there and say, "Hey, you need to log on to this, you need to like make your tool work this platform over here and it's not compatible." I'm going to have to completely reframe how I'm doing productization. I need to know that as a security practitioner because me disrupting productization is not something that I should be doing. And I've heard a couple a couple of folks kind of talking about that, the people aspect behind how we implement these tools, the frameworks and the platforms, and how do we draw out risk, right? Like how do we talk about risk with these teams and really make them understand so it's part of their core culture in their understanding. So when they go back to their, when they go back and having to make decisions without me in the room they know they can make those business decisions with the risk as part of that decision. >> I love that empathetic angle because that's really going to, what needs to happen. It's not just, "Hey, that's your department, see you later." Or not even having a knowledge of the information. This idea of team construction, team management is a huge cultural shift. I'm sure the reaction was very positive. How do you explain that to an organization that's out there? Like how do you... what's the first three steps you got to take? Is there anything that you can share for advice people watch you saying, "Yeah we need to we need to change how our teams operate and interact with each other." >> Yeah, I think the first step is to take a good hard look at yourself. And if you are standing there on an ivory tower with a clipboard, you're probably doing it wrong. Check the box security is never going to be any way that works long term. It's going to take you a long time to implement any changes. At Red Hat, we did not look ourselves. You know, we've been doing a lot of great things in supply chain security for a while, but really taking that look and saying, "How can we be more empathetic leaders in the security space?" So we looked at that, then you say, "Okay, what is my my rate of change going to happen?" So if I need to make so many security changes explaining to these organizations, you're actually going to go faster. We improved our efficiency by 2000% just by doing that, just by creating this more empathetic. So why it seems like it's more hands-on, so it's going to be harder, it's easy to send out an email and say, "Hey, meet the security standard, right?" That might seem like the easy way 'cause you don't have time to engage. It's so much faster if you actually engage and share that message and have a a common understanding between the teams that like, "I'm here to deliver a product, so is the security team. The security team's here to deliver that same product and I want to help you do it in a trusted way." Right? >> Yeah. Dave Alonte, my co-host, was just on a session. We were talking together about security teams jumping on every team and putting a C on their jersey to be like the captain of the intramural team, and being involved, and it goes beyond just like the checklist, like you said, "Oh, I got the SBOM list of materials and I got a code scanning thing." That's not enough, is what we're hearing. >> No. >> Is there a framework or a methodology to go beyond that? You got the empathetic, that's really kind of team issue. You got to go beyond some of the tactical things. What's next beyond, you got the empathy and what's that framework structure when you say where you say anything there? >> So what do you do after you have the empathy, right? >> Yeah. >> I would say Salsa is a good place to start, the software levels. Supply chain levels for software artifacts. It's a mouthful. That's a really good maturity framework to start with. No matter what size organization you have, they're just going to be coming out here soon with version one. They release 0.1 a few months back. That's a really good place to give yourself a gut check of where you are in maturity and where you can go, what are best practices. And then there's the SSDF, which is the Secure Software Development framework. I think NIST wrote that one. But that is also a really, a really good framework and they map really well to each other, actually, When you work through Salsa, you're actually working through the SSDF requirements. >> Awesome. Well, great to have you on and great to get that that knowledge. I have to ask you like coup con, I remember when it started in Seattle, their first coup con events, right? Kind of small, similar to this one, but there's a lot of end user activities. Certainly the CNCF kind of was coming together like right after that. What's the end user activity like there this week? That seems to always been the driver of these events. It's a little bit organic. You got some of the key experts coming together, focus. Have you observed any end user activity in terms of contributions, participation? What's the story on the end user piece there? Is it heavy? Is it light? What's the... >> Um, yeah... It seems moderate. I guess somewhere in the middle. I would say largely heavy, but there's definitely participation. There is a lot of communing and networking happening between different organizations to partner together, which is important. But I haven't really paid attention much to like the Twitter side of this. >> Yeah, you've been busy doing the keynotes. How's Red Hat doing all this? You guys have been great positioned with the cloud native movement. Been following the Red Hat's moves since OpenStack days. Really good, good line of product, good open source, Mojo, of course. Good product mix, right, and relevant. Where's the security focus here? Obviously, you guys are clearly focused on security. How's the Red Hat story going on over there? >> There was yesterday a really good talk that explains that super well. It was given by a Red Hatter, connecting all of the open source projects we've been a part of and kind of explaining them. And obviously again, I'm keying in 'cause it's a supply chain kind of conversation, but I'd recommend that anyone who's going to go back and watch these on YouTube to check that one out just to see kind of how we're approaching the security space as well as how we contribute back to the community in that way. >> Awesome. Great to have you on. Final word, I'll give you the final word. What's the big buzz on supply chain? How would you peg the progress there? Feeling good about where things are? What's the current progress on supply chain security? >> I think that it has opened up a lot of doors for communication between security organizations that have tended to be closed. I'm in product security. Product securities, information securities tend to not speak externally about what we're doing. So you don't want to, you know, look bad or you don't want to expose any risk that we have, right? But it is, I think, necessary to open those lines of communication, to be able to start tackling this. It's a big problem throughout all of our industries, and if one supply chain is attacked and those products are used in someone else's supply chain, that can continue, right? So I think it's good. We have a lot of work to do as an industry and the advancements in technology is going to make that a little bit more complicated. But I'm excited for it. >> You can just throw AI at it. That's the big, everyone's doing AI. Just throw AI at it, it'll solve it. Isn't that the new thing? >> I do secure AI though. >> Super important. I love what you're doing there. Supply chain, open source needs, supply chain security. Open source needs this big time. It has to be there. Thank you for the work that you do. Really appreciate you coming on. Thank you. >> Yeah, thanks for having me. >> Yeah, good stuff. Supply chain, critical to open source growth. Open source is going to be the key to success in the future with automation and AI right around the corner. And that's important. This theCUBE covers from cloud native con, security con in North America, 2023. I'm John Furrier. Thanks for watching.

>> Narrator: From theCUBE Studios in Palo Alto and Boston bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante >> Enterprise tech practitioners, like most of us they want to make their lives easier so they can focus on delivering more value to their businesses. And to do so, they want to tap best of breed services in the public cloud, but at the same time connect their on-prem intellectual property to emerging applications which drive top line revenue and bottom line profits. But creating a consistent experience across clouds and on-prem estates has been an elusive capability for most organizations, forcing trade-offs and injecting friction into the system. The need to create seamless experiences is clear and the technology industry is starting to respond with platforms, architectures, and visions of what we've called the Supercloud. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis we give you a preview of Supercloud 2, the second event of its kind that we've had on the topic. Yes, folks that's right Supercloud 2 is here. As of this recording, it's just about four days away 33 guests, 21 sessions, combining live discussions and fireside chats from theCUBE's Palo Alto Studio with prerecorded conversations on the future of cloud and data. You can register for free at supercloud.world. And we are super excited about the Supercloud 2 lineup of guests whereas Supercloud 22 in August, was all about refining the definition of Supercloud testing its technical feasibility and understanding various deployment models. Supercloud 2 features practitioners, technologists and analysts discussing what customers need with real-world examples of Supercloud and will expose thinking around a new breed of cross-cloud apps, data apps, if you will that change the way machines and humans interact with each other. Now the example we'd use if you think about applications today, say a CRM system, sales reps, what are they doing? They're entering data into opportunities they're choosing products they're importing contacts, et cetera. And sure the machine can then take all that data and spit out a forecast by rep, by region, by product, et cetera. But today's applications are largely about filling in forms and or codifying processes. In the future, the Supercloud community sees a new breed of applications emerging where data resides on different clouds, in different data storages, databases, Lakehouse, et cetera. And the machine uses AI to inspect the e-commerce system the inventory data, supply chain information and other systems, and puts together a plan without any human intervention whatsoever. Think about a system that orchestrates people, places and things like an Uber for business. So at Supercloud 2, you'll hear about this vision along with some of today's challenges facing practitioners. Zhamak Dehghani, the founder of Data Mesh is a headliner. Kit Colbert also is headlining. He laid out at the first Supercloud an initial architecture for what that's going to look like. That was last August. And he's going to present his most current thinking on the topic. Veronika Durgin of Sachs will be featured and talk about data sharing across clouds and you know what she needs in the future. One of the main highlights of Supercloud 2 is a dive into Walmart's Supercloud. Other featured practitioners include Western Union Ionis Pharmaceuticals, Warner Media. We've got deep, deep technology dives with folks like Bob Muglia, David Flynn Tristan Handy of DBT Labs, Nir Zuk, the founder of Palo Alto Networks focused on security. Thomas Hazel, who's going to talk about a new type of database for Supercloud. It's several analysts including Keith Townsend Maribel Lopez, George Gilbert, Sanjeev Mohan and so many more guests, we don't have time to list them all. They're all up on supercloud.world with a full agenda, so you can check that out. Now let's take a look at some of the things that we're exploring in more detail starting with the Walmart Cloud native platform, they call it WCNP. We definitely see this as a Supercloud and we dig into it with Jack Greenfield. He's the head of architecture at Walmart. Here's a quote from Jack. "WCNP is an implementation of Kubernetes for the Walmart ecosystem. We've taken Kubernetes off the shelf as open source." By the way, they do the same thing with OpenStack. "And we have integrated it with a number of foundational services that provide other aspects of our computational environment. Kubernetes off the shelf doesn't do everything." And so what Walmart chose to do, they took a do-it-yourself approach to build a Supercloud for a variety of reasons that Jack will explain, along with Walmart's so-called triplet architecture connecting on-prem, Azure and GCP. No surprise, there's no Amazon at Walmart for obvious reasons. And what they do is they create a common experience for devs across clouds. Jack is going to talk about how Walmart is evolving its Supercloud in the future. You don't want to miss that. Now, next, let's take a look at how Veronica Durgin of SAKS thinks about data sharing across clouds. Data sharing we think is a potential killer use case for Supercloud. In fact, let's hear it in Veronica's own words. Please play the clip. >> How do we talk to each other? And more importantly, how do we data share? You know, I work with data, you know this is what I do. So if you know I want to get data from a company that's using, say Google, how do we share it in a smooth way where it doesn't have to be this crazy I don't know, SFTP file moving? So that's where I think Supercloud comes to me in my mind, is like practical applications. How do we create that mesh, that network that we can easily share data with each other? >> Now data mesh is a possible architectural approach that will enable more facile data sharing and the monetization of data products. You'll hear Zhamak Dehghani live in studio talking about what standards are missing to make this vision a reality across the Supercloud. Now one of the other things that we're really excited about is digging deeper into the right approach for Supercloud adoption. And we're going to share a preview of a debate that's going on right now in the community. Bob Muglia, former CEO of Snowflake and Microsoft Exec was kind enough to spend some time looking at the community's supercloud definition and he felt that it needed to be simplified. So in near real time he came up with the following definition that we're showing here. I'll read it. "A Supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." So not only did Bob simplify the initial definition he's stressed that the Supercloud is a platform versus an architecture implying that the platform provider eg Snowflake, VMware, Databricks, Cohesity, et cetera is responsible for determining the architecture. Now interestingly in the shared Google doc that the working group uses to collaborate on the supercloud de definition, Dr. Nelu Mihai who is actually building a Supercloud responded as follows to Bob's assertion "We need to avoid creating many Supercloud platforms with their own architectures. If we do that, then we create other proprietary clouds on top of existing ones. We need to define an architecture of how Supercloud interfaces with all other clouds. What is the information model? What is the execution model and how users will interact with Supercloud?" What does this seemingly nuanced point tell us and why does it matter? Well, history suggests that de facto standards will emerge more quickly to resolve real world practitioner problems and catch on more quickly than consensus-based architectures and standards-based architectures. But in the long run, the ladder may serve customers better. So we'll be exploring this topic in more detail in Supercloud 2, and of course we'd love to hear what you think platform, architecture, both? Now one of the real technical gurus that we'll have in studio at Supercloud two is David Flynn. He's one of the people behind the the movement that enabled enterprise flash adoption, that craze. And he did that with Fusion IO and he is now working on a system to enable read write data access to any user in any application in any data center or on any cloud anywhere. So think of this company as a Supercloud enabler. Allow me to share an excerpt from a conversation David Flore and I had with David Flynn last year. He as well gave a lot of thought to the Supercloud definition and was really helpful with an opinionated point of view. He said something to us that was, we thought relevant. "What is the operating system for a decentralized cloud? The main two functions of an operating system or an operating environment are one the process scheduler and two, the file system. The strongest argument for supercloud is made when you go down to the platform layer and talk about it as an operating environment on which you can run all forms of applications." So a couple of implications here that will be exploring with David Flynn in studio. First we're inferring from his comment that he's in the platform camp where the platform owner is responsible for the architecture and there are obviously trade-offs there and benefits but we'll have to clarify that with him. And second, he's basically saying, you kill the concept the further you move up the stack. So the weak, the further you move the stack the weaker the supercloud argument becomes because it's just becoming SaaS. Now this is something we're going to explore to better understand is thinking on this, but also whether the existing notion of SaaS is changing and whether or not a new breed of Supercloud apps will emerge. Which brings us to this really interesting fellow that George Gilbert and I RIFed with ahead of Supercloud two. Tristan Handy, he's the founder and CEO of DBT Labs and he has a highly opinionated and technical mind. Here's what he said, "One of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse inside of your data lake. These are core concepts that the business should be able to create applications around very easily. In fact, that's not the case because it involves a lot of data engineering pipeline and other work to make these available. So if you really want to make it easy to create these data experiences for users you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes and they don't need to." A lot of implications to this statement that will explore at Supercloud two versus Jamma Dani's data mesh comes into play here with her critique of hyper specialized data pipeline experts with little or no domain knowledge. Also the need for simplified self-service infrastructure which Kit Colbert is likely going to touch upon. Veronica Durgin of SAKS and her ideal state for data shearing along with Harveer Singh of Western Union. They got to deal with 200 locations around the world in data privacy issues, data sovereignty how do you share data safely? Same with Nick Taylor of Ionis Pharmaceutical. And not to blow your mind but Thomas Hazel and Bob Muglia deposit that to make data apps a reality across the Supercloud you have to rethink everything. You can't just let in memory databases and caching architectures take care of everything in a brute force manner. Rather you have to get down to really detailed levels even things like how data is laid out on disk, ie flash and think about rewriting applications for the Supercloud and the MLAI era. All of this and more at Supercloud two which wouldn't be complete without some data. So we pinged our friends from ETR Eric Bradley and Darren Bramberm to see if they had any data on Supercloud that we could tap. And so we're going to be analyzing a number of the players as well at Supercloud two. Now, many of you are familiar with this graphic here we show some of the players involved in delivering or enabling Supercloud-like capabilities. On the Y axis is spending momentum and on the horizontal accesses market presence or pervasiveness in the data. So netscore versus what they call overlap or end in the data. And the table insert shows how the dots are plotted now not to steal ETR's thunder but the first point is you really can't have supercloud without the hyperscale cloud platforms which is shown on this graphic. But the exciting aspect of Supercloud is the opportunity to build value on top of that hyperscale infrastructure. Snowflake here continues to show strong spending velocity as those Databricks, Hashi, Rubrik. VMware Tanzu, which we all put under the magnifying glass after the Broadcom announcements, is also showing momentum. Unfortunately due to a scheduling conflict we weren't able to get Red Hat on the program but they're clearly a player here. And we've put Cohesity and Veeam on the chart as well because backup is a likely use case across clouds and on-premises. And now one other call out that we drill down on at Supercloud two is CloudFlare, which actually uses the term supercloud maybe in a different way. They look at Supercloud really as you know, serverless on steroids. And so the data brains at ETR will have more to say on this topic at Supercloud two along with many others. Okay, so why should you attend Supercloud two? What's in it for me kind of thing? So first of all, if you're a practitioner and you want to understand what the possibilities are for doing cross-cloud services for monetizing data how your peers are doing data sharing, how some of your peers are actually building out a Supercloud you're going to get real world input from practitioners. If you're a technologist, you're trying to figure out various ways to solve problems around data, data sharing, cross-cloud service deployment there's going to be a number of deep technology experts that are going to share how they're doing it. We're also going to drill down with Walmart into a practical example of Supercloud with some other examples of how practitioners are dealing with cross-cloud complexity. Some of them, by the way, are kind of thrown up their hands and saying, Hey, we're going mono cloud. And we'll talk about the potential implications and dangers and risks of doing that. And also some of the benefits. You know, there's a question, right? Is Supercloud the same wine new bottle or is it truly something different that can drive substantive business value? So look, go to Supercloud.world it's January 17th at 9:00 AM Pacific. You can register for free and participate directly in the program. Okay, that's a wrap. I want to give a shout out to the Supercloud supporters. VMware has been a great partner as our anchor sponsor Chaos Search Proximo, and Alura as well. For contributing to the effort I want to thank Alex Myerson who's on production and manages the podcast. Ken Schiffman is his supporting cast as well. Kristen Martin and Cheryl Knight to help get the word out on social media and at our newsletters. And Rob Ho is our editor-in-chief over at Silicon Angle. Thank you all. Remember, these episodes are all available as podcast. Wherever you listen we really appreciate the support that you've given. We just saw some stats from from Buzz Sprout, we hit the top 25% we're almost at 400,000 downloads last year. So really appreciate your participation. All you got to do is search Breaking Analysis podcast and you'll find those I publish each week on wikibon.com and siliconangle.com. Or if you want to get ahold of me you can email me directly at David.Vellante@siliconangle.com or dm me DVellante or comment on our LinkedIn post. I want you to check out etr.ai. They've got the best 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 week at Supercloud two or next time on breaking analysis. (light 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.

>> Welcome back to SuperCloud2. This is Dave Vellante, and we're here with Jack Greenfield. He's the Vice President of Enterprise Architecture and the Chief Architect for the global technology platform at Walmart. Jack, I want to thank you for coming on the program. Really appreciate your time. >> Glad to be here, Dave. Thanks for inviting me and appreciate the opportunity to chat with you. >> Yeah, it's our pleasure. Now we call what you've built a SuperCloud. That's our term, not yours, but how would you describe the Walmart Cloud Native Platform? >> So WCNP, as the acronym goes, is essentially an implementation of Kubernetes for the Walmart ecosystem. And what that means is that we've taken Kubernetes off the shelf as open source, and we have integrated it with a number of foundational services that provide other aspects of our computational environment. So Kubernetes off the shelf doesn't do everything. It does a lot. In particular the orchestration of containers, but it delegates through API a lot of key functions. So for example, secret management, traffic management, there's a need for telemetry and observability at a scale beyond what you get from raw Kubernetes. That is to say, harvesting the metrics that are coming out of Kubernetes and processing them, storing them in time series databases, dashboarding them, and so on. There's also an angle to Kubernetes that gets a lot of attention in the daily DevOps routine, that's not really part of the open source deliverable itself, and that is the DevOps sort of CICD pipeline-oriented lifecycle. And that is something else that we've added and integrated nicely. And then one more piece of this picture is that within a Kubernetes cluster, there's a function that is critical to allowing services to discover each other and integrate with each other securely and with proper configuration provided by the concept of a service mesh. So Istio, Linkerd, these are examples of service mesh technologies. And we have gone ahead and integrated actually those two. There's more than those two, but we've integrated those two with Kubernetes. So the net effect is that when a developer within Walmart is going to build an application, they don't have to think about all those other capabilities where they come from or how they're provided. Those are already present, and the way the CICD pipelines are set up, it's already sort of in the picture, and there are configuration points that they can take advantage of in the primary YAML and a couple of other pieces of config that we supply where they can tune it. But at the end of the day, it offloads an awful lot of work for them, having to stand up and operate those services, fail them over properly, and make them robust. All of that's provided for. >> Yeah, you know, developers often complain they spend too much time wrangling and doing things that aren't productive. So I wonder if you could talk about the high level business goals of the initiative in terms of the hardcore benefits. Was the real impetus to tap into best of breed cloud services? Were you trying to cut costs? Maybe gain negotiating leverage with the cloud guys? Resiliency, you know, I know was a major theme. Maybe you could give us a sense of kind of the anatomy of the decision making process that went in. >> Sure, and in the course of answering your question, I think I'm going to introduce the concept of our triplet architecture which we haven't yet touched on in the interview here. First off, just to sort of wrap up the motivation for WCNP itself which is kind of orthogonal to the triplet architecture. It can exist with or without it. Currently does exist with it, which is key, and I'll get to that in a moment. The key drivers, business drivers for WCNP were developer productivity by offloading the kinds of concerns that we've just discussed. Number two, improving resiliency, that is to say reducing opportunity for human error. One of the challenges you tend to run into in a large enterprise is what we call snowflakes, lots of gratuitously different workloads, projects, configurations to the extent that by developing and using WCNP and continuing to evolve it as we have, we end up with cookie cutter like consistency across our workloads which is super valuable when it comes to building tools or building services to automate operations that would otherwise be manual. When everything is pretty much done the same way, that becomes much simpler. Another key motivation for WCNP was the ability to abstract from the underlying cloud provider. And this is going to lead to a discussion of our triplet architecture. At the end of the day, when one works directly with an underlying cloud provider, one ends up taking a lot of dependencies on that particular cloud provider. Those dependencies can be valuable. For example, there are best of breed services like say Cloud Spanner offered by Google or say Cosmos DB offered by Microsoft that one wants to use and one is willing to take the dependency on the cloud provider to get that functionality because it's unique and valuable. On the other hand, one doesn't want to take dependencies on a cloud provider that don't add a lot of value. And with Kubernetes, we have the opportunity, and this is a large part of how Kubernetes was designed and why it is the way it is, we have the opportunity to sort of abstract from the underlying cloud provider for stateless workloads on compute. And so what this lets us do is build container-based applications that can run without change on different cloud provider infrastructure. So the same applications can run on WCNP over Azure, WCNP over GCP, or WCNP over the Walmart private cloud. And we have a private cloud. Our private cloud is OpenStack based and it gives us some significant cost advantages as well as control advantages. So to your point, in terms of business motivation, there's a key cost driver here, which is that we can use our own private cloud when it's advantageous and then use the public cloud provider capabilities when we need to. A key place with this comes into play is with elasticity. So while the private cloud is much more cost effective for us to run and use, it isn't as elastic as what the cloud providers offer, right? We don't have essentially unlimited scale. We have large scale, but the public cloud providers are elastic in the extreme which is a very powerful capability. So what we're able to do is burst, and we use this term bursting workloads into the public cloud from the private cloud to take advantage of the elasticity they offer and then fall back into the private cloud when the traffic load diminishes to the point where we don't need that elastic capability, elastic capacity at low cost. And this is a very important paradigm that I think is going to be very commonplace ultimately as the industry evolves. Private cloud is easier to operate and less expensive, and yet the public cloud provider capabilities are difficult to match. >> And the triplet, the tri is your on-prem private cloud and the two public clouds that you mentioned, is that right? >> That is correct. And we actually have an architecture in which we operate all three of those cloud platforms in close proximity with one another in three different major regions in the US. So we have east, west, and central. And in each of those regions, we have all three cloud providers. And the way it's configured, those data centers are within 10 milliseconds of each other, meaning that it's of negligible cost to interact between them. And this allows us to be fairly agnostic to where a particular workload is running. >> Does a human make that decision, Jack or is there some intelligence in the system that determines that? >> That's a really great question, Dave. And it's a great question because we're at the cusp of that transition. So currently humans make that decision. Humans choose to deploy workloads into a particular region and a particular provider within that region. That said, we're actively developing patterns and practices that will allow us to automate the placement of the workloads for a variety of criteria. For example, if in a particular region, a particular provider is heavily overloaded and is unable to provide the level of service that's expected through our SLAs, we could choose to fail workloads over from that cloud provider to a different one within the same region. But that's manual today. We do that, but people do it. Okay, we'd like to get to where that happens automatically. In the same way, we'd like to be able to automate the failovers, both for high availability and sort of the heavier disaster recovery model between, within a region between providers and even within a provider between the availability zones that are there, but also between regions for the sort of heavier disaster recovery or maintenance driven realignment of workload placement. Today, that's all manual. So we have people moving workloads from region A to region B or data center A to data center B. It's clean because of the abstraction. The workloads don't have to know or care, but there are latency considerations that come into play, and the humans have to be cognizant of those. And automating that can help ensure that we get the best performance and the best reliability. >> But you're developing the dataset to actually, I would imagine, be able to make those decisions in an automated fashion over time anyway. Is that a fair assumption? >> It is, and that's what we're actively developing right now. So if you were to look at us today, we have these nice abstractions and APIs in place, but people run that machine, if you will, moving toward a world where that machine is fully automated. >> What exactly are you abstracting? Is it sort of the deployment model or, you know, are you able to abstract, I'm just making this up like Azure functions and GCP functions so that you can sort of run them, you know, with a consistent experience. What exactly are you abstracting and how difficult was it to achieve that objective technically? >> that's a good question. What we're abstracting is the Kubernetes node construct. That is to say a cluster of Kubernetes nodes which are typically VMs, although they can run bare metal in certain contexts, is something that typically to stand up requires knowledge of the underlying cloud provider. So for example, with GCP, you would use GKE to set up a Kubernetes cluster, and in Azure, you'd use AKS. We are actually abstracting that aspect of things so that the developers standing up applications don't have to know what the underlying cluster management provider is. They don't have to know if it's GCP, AKS or our own Walmart private cloud. Now, in terms of functions like Azure functions that you've mentioned there, we haven't done that yet. That's another piece that we have sort of on our radar screen that, we'd like to get to is serverless approach, and the Knative work from Google and the Azure functions, those are things that we see good opportunity to use for a whole variety of use cases. But right now we're not doing much with that. We're strictly container based right now, and we do have some VMs that are running in sort of more of a traditional model. So our stateful workloads are primarily VM based, but for serverless, that's an opportunity for us to take some of these stateless workloads and turn them into cloud functions. >> Well, and that's another cost lever that you can pull down the road that's going to drop right to the bottom line. Do you see a day or maybe you're doing it today, but I'd be surprised, but where you build applications that actually span multiple clouds or is there, in your view, always going to be a direct one-to-one mapping between where an application runs and the specific cloud platform? >> That's a really great question. Well, yes and no. So today, application development teams choose a cloud provider to deploy to and a location to deploy to, and they have to get involved in moving an application like we talked about today. That said, the bursting capability that I mentioned previously is something that is a step in the direction of automatic migration. That is to say we're migrating workload to different locations automatically. Currently, the prototypes we've been developing and that we think are going to eventually make their way into production are leveraging Istio to assess the load incoming on a particular cluster and start shedding that load into a different location. Right now, the configuration of that is still manual, but there's another opportunity for automation there. And I think a key piece of this is that down the road, well, that's a, sort of a small step in the direction of an application being multi provider. We expect to see really an abstraction of the fact that there is a triplet even. So the workloads are moving around according to whatever the control plane decides is necessary based on a whole variety of inputs. And at that point, you will have true multi-cloud applications, applications that are distributed across the different providers and in a way that application developers don't have to think about. >> So Walmart's been a leader, Jack, in using data for competitive advantages for decades. It's kind of been a poster child for that. You've got a mountain of IP in the form of data, tools, applications best practices that until the cloud came out was all On Prem. But I'm really interested in this idea of building a Walmart ecosystem, which obviously you have. Do you see a day or maybe you're even doing it today where you take what we call the Walmart SuperCloud, WCNP in your words, and point or turn that toward an external world or your ecosystem, you know, supporting those partners or customers that could drive new revenue streams, you know directly from the platform? >> Great question, Steve. So there's really two things to say here. The first is that with respect to data, our data workloads are primarily VM basis. I've mentioned before some VMware, some straight open stack. But the key here is that WCNP and Kubernetes are very powerful for stateless workloads, but for stateful workloads tend to be still climbing a bit of a growth curve in the industry. So our data workloads are not primarily based on WCNP. They're VM based. Now that said, there is opportunity to make some progress there, and we are looking at ways to move things into containers that are currently running in VMs which are stateful. The other question you asked is related to how we expose data to third parties and also functionality. Right now we do have in-house, for our own use, a very robust data architecture, and we have followed the sort of domain-oriented data architecture guidance from Martin Fowler. And we have data lakes in which we collect data from all the transactional systems and which we can then use and do use to build models which are then used in our applications. But right now we're not exposing the data directly to customers as a product. That's an interesting direction that's been talked about and may happen at some point, but right now that's internal. What we are exposing to customers is applications. So we're offering our global integrated fulfillment capabilities, our order picking and curbside pickup capabilities, and our cloud powered checkout capabilities to third parties. And this means we're standing up our own internal applications as externally facing SaaS applications which can serve our partners' customers. >> Yeah, of course, Martin Fowler really first introduced to the world Zhamak Dehghani's data mesh concept and this whole idea of data products and domain oriented thinking. Zhamak Dehghani, by the way, is a speaker at our event as well. Last question I had is edge, and how you think about the edge? You know, the stores are an edge. Are you putting resources there that sort of mirror this this triplet model? Or is it better to consolidate things in the cloud? I know there are trade-offs in terms of latency. How are you thinking about that? >> All really good questions. It's a challenging area as you can imagine because edges are subject to disconnection, right? Or reduced connection. So we do place the same architecture at the edge. So WCNP runs at the edge, and an application that's designed to run at WCNP can run at the edge. That said, there are a number of very specific considerations that come up when running at the edge, such as the possibility of disconnection or degraded connectivity. And so one of the challenges we have faced and have grappled with and done a good job of I think is dealing with the fact that applications go offline and come back online and have to reconnect and resynchronize, the sort of online offline capability is something that can be quite challenging. And we have a couple of application architectures that sort of form the two core sets of patterns that we use. One is an offline/online synchronization architecture where we discover that we've come back online, and we understand the differences between the online dataset and the offline dataset and how they have to be reconciled. The other is a message-based architecture. And here in our health and wellness domain, we've developed applications that are queue based. So they're essentially business processes that consist of multiple steps where each step has its own queue. And what that allows us to do is devote whatever bandwidth we do have to those pieces of the process that are most latency sensitive and allow the queue lengths to increase in parts of the process that are not latency sensitive, knowing that they will eventually catch up when the bandwidth is restored. And to put that in a little bit of context, we have fiber lengths to all of our locations, and we have I'll just use a round number, 10-ish thousand locations. It's larger than that, but that's the ballpark, and we have fiber to all of them, but when the fiber is disconnected, and it does get disconnected on a regular basis. In fact, I forget the exact number, but some several dozen locations get disconnected daily just by virtue of the fact that there's construction going on and things are happening in the real world. When the disconnection happens, we're able to fall back to 5G and to Starlink. Starlink is preferred. It's a higher bandwidth. 5G if that fails. But in each of those cases, the bandwidth drops significantly. And so the applications have to be intelligent about throttling back the traffic that isn't essential, so that it can push the essential traffic in those lower bandwidth scenarios. >> So much technology to support this amazing business which started in the early 1960s. Jack, unfortunately, we're out of time. I would love to have you back or some members of your team and drill into how you're using open source, but really thank you so much for explaining the approach that you've taken and participating in SuperCloud2. >> You're very welcome, Dave, and we're happy to come back and talk about other aspects of what we do. For example, we could talk more about the data lakes and the data mesh that we have in place. We could talk more about the directions we might go with serverless. So please look us up again. Happy to chat. >> I'm going to take you up on that, Jack. All right. This is Dave Vellante for John Furrier and the Cube community. Keep it right there for more action from SuperCloud2. (upbeat music)

(bright upbeat music) >> Greetings, brilliant community and thank you so much for tuning in to theCUBE here for the last three days where we've been live from Detroit, Michigan. I've had the pleasure of spending this week with Lisa Martin and John Furrier. Thank you both so much for hanging out, for inviting me into the CUBE family. It's our first show together, it's been wonderful. >> Thank you. >> You nailed it. >> Oh thanks, sweetheart. >> Great job. Great job team, well done. Free wall to wall coverage, it's what we do. We stay till everyone else-- >> Savannah: 100 percent. >> Everyone else leaves, till they pull the plug. >> Lisa: Till they turn the lights out. We're still there. >> Literally. >> Literally last night. >> Still broadcasting. >> Whatever takes to get the stories and get 'em out there at scale. >> Yeah. >> Great time. >> 33. 33 different segments too. Very impressive. John, I'm curious, you're a trend watcher and you've been at every single KubeCon. >> Yep. >> What are the trends this year? Give us the breakdown. >> I think CNCF does this, it's a hard job to balance all the stakeholders. So one, congratulations to the CNCF for another great KubeCon and CloudNativeCon. It is really hard to balance bringing in the experts who, as time goes by, seven years we've been all of, as you said, you get experts, you get seniority, and people who can be mentors, 60% new people. You have vendors who are sponsoring and there's always people complaining and bitching and moaning. They want this, they want that. It's always hard and they always do a good job of balancing it. We're lucky that we get to scale the stories with CUBE and that's been great. We had some great stories here, but it's a great community and again, they're inclusive. As I've said before, we've talked about it. This year though is an inflection point in my opinion, because you're seeing the developer ecosystem growing so fast. It's global. You're seeing events pop up, you're seeing derivative events. CNCF is at the center point and they have to maintain the culture of developer experts, maintainers, while balancing the newbies. And that's going to be >> Savannah: Mm-hmm. really hard. And they've done a great job. We had a great conversation with them. So great job. And I think it's going to continue. I think the attendance metric is a little bit of a false positive. There's a lot of online people who didn't come to Detroit this year. And I think maybe the combination of the venue, the city, or just Covid preferences may not look good on paper, on the numbers 'cause it's not a major step up in attendance. It's still bigger, but the community, I think, is going to continue to grow. I'm bullish on it. >> Yeah, I mean at least we did see double the number of people that we had in Los Angeles. Very curious. I think Amsterdam, where we'll be next with CNCF in the spring, in April. I think that's actually going to be a better pulse check. We'll be in Europe, we'll see what's going on. >> John: Totally. >> I mean, who doesn't like Amsterdam in the springtime? Lisa, what have been some of your observations? >> Oh, so many observations. The evolution of the conference, the hallway track conversations really shifting towards adjusting to the enterprise. The enterprise momentum that we saw here as well. We had on the show, Ford. >> Savannah: Yes. We had MassMutual, we had ING, that was today. Home Depot is here. We are seeing all these big companies that we know and love, become software companies right before our eyes. >> Yeah. Well, and I think we forget that software powers our entire world. And so of course they're going to have to be here. So much running on Kubernetes. It's on-prem, it's at the edge, it's everywhere. It's exciting. Woo, I'm excited. John, what do you think is the number one story? This is your question. I love asking you this question. What is the number one story out KubeCon? >> Well, I think the top story is a combination of two things. One is the evolution of Cloud Native. We're starting to see web assembly. That's a big hyped up area. It got a lot of attention. >> Savannah: Yeah. That's kind of teething out the future. >> Savannah: Rightfully so. The future of this kind of lightweight. You got the heavy duty VMs, you got Kubernetes and containers, and now this web assembly, shows a trajectory of apps, server-like environment. And then the big story is security. Software supply chain is, to me, was the number one consistent theme. At almost all the interviews, in the containers, and the workflows, >> Savannah: Very hot. software supply chain is real. The CD Foundation mentioned >> Savannah: Mm-hmm. >> they had 16,000 vulnerabilities identified in their code base. They were going to automate that. So again, >> Savannah: That was wild. >> That's the top story. The growth of open source exposes potential vulnerabilities with security. So software supply chain gets my vote. >> Did you hear anything that surprised you? You guys did this great preview of what you thought we were going to hear and see and feel and touch at KubeCon, CloudNativeCon 2022. You talked about, for example, the, you know, healthcare financial services being early adopters of this. Anything surprise either one of you in terms of what you predicted versus what we saw? Savannah, let's start with you. >> You know what really surprised me, and this is ironic, so I'm a community gal by trade. But I was really just impressed by the energy that everyone brought here and the desire to help. The thing about the open source community that always strikes me is, I mean 187 different countries participating. You've got, I believe it's something like 175,000 people contributing to the 140 projects plus that CNCF is working on. But that culture of collaboration extends far beyond just the CNCF projects. Everyone here is keen to help each other. We had the conversation just before about the teaching and the learnings that are going on here. They brought in Detroit's students to come and learn, which is just the most heartwarming story out of this entire thing. And I think it's just the authenticity of everyone in this community and their passion. Even though I know it's here, it still surprises me to see it in the flesh. Especially in a place like Detroit. >> It's nice. >> Yeah. >> It's so nice to see it. And you bring up a good point. It's very authentic. >> Savannah: It's super authentic. >> I mean, what surprised me is one, the Wasm, or web assembly. I didn't see that coming at the scale of the conversation. It sucked a lot of options out of the room in my opinion, still hyped up. But this looks like it's got a good trajectory. I like that. The other thing that surprised me that was a learning was my interview with Solo.io, Idit, and Brian Gracely, because he's a CUBE alumni and former host of theCUBE, and analyst at Wikibon, was how their go-to-market was an example of a modern company in Covid with a clean sheet of paper and smart people, they're just doing things different. They're in Slack with their customers. And I walked away with, "Wow that's like a playbook that's not, was never, in the go-to-market VC-backed company playbook." I thought that was, for me, a personal walk away saying that's important. I like how they did that. And there's a lot of companies I think could learn from that. Especially as the recession comes where partnering with customers has always been a top priority. And how they did that was very clever, very effective, very efficient. So I walked away with that saying, "I think that's going to be a standard." So that was a pleasant surprise. >> That was a great surprise. Also, that's a female-founded company, which is obviously not super common. And the growth that they've experienced, to your point, really being catalyzed by Covid, is incredibly impressive. I mean they have some massive brand name customers, Amex, BMW for example. >> Savannah: Yeah. >> Great point. >> And I interviewed her years ago and I remember saying to myself, "Wow, she's impressive." I liked her. She's a player. A player for sure. And she's got confidence. Even on the interview she said, "We're just better, we have better product." And I just like the point of view. Very customer-focused but confident. And I just took, that's again, a great company. And again, I'm not surprised that Brian Gracely left Red Hat to go work there. So yeah, great, great call there. And of course other things that weren't surprising that I predicted, Red Hat continued to invest. They continue to bring people on theCUBE, they support theCUBE but more importantly they have a good strategy. They're in that multicloud positioning. They're going to have an opportunity to get a bite at the apple. And I what I call the supercloud. As enterprises try to go and be mainstream, Cloud Native, they're going to need some help. And Red Hat is always has the large enterprise customers. >> Savannah: What surprised you, Lisa? >> Oh my gosh, so many things. I think some of the memorable conversations that we had. I love talking with some of the enterprises that we mentioned, ING Bank for example. You know, or institutions that have been around for 100 plus years. >> Savannah: Oh, yeah. To see not only how much they've innovated and stayed relevant to meet the demands of the consumer, which are only increasing, but they're doing so while fostering a culture of innovation and a culture that allows these technology leaders to really grow within the organization. That was a really refreshing conversation that I think we had. 'Cause you can kind of >> Savannah: Absolutely. think about these old stodgy companies. Nah, of course they're going to digitize. >> Thinking about working for the bank, I think it's boring. >> Right? >> Yeah. And they were talking about, in fact, those great t-shirts that they had on, >> Yeah, yeah, yeah, yeah. were all about getting more people to understand how fun it is to work in tech for ING Bank in different industries. You don't just have to work for the big tech companies to be doing really cool stuff in technology. >> What I really liked about this show is we had two female hosts. >> Savannah: Yeah. >> How about that? Come on. >> Hey, well done, well done on your recruitment there, champ. >> Yes, thank you boss. (John laughs) >> And not to mention we have a really all-star production team. I do just want to give them a little shout out. To all the wonderful folks behind the lines here. (people clapping) >> John: Brendan. Good job. >> Yeah. Without Brendan, Anderson, Noah, and Andrew, we would be-- >> Of course Frank Faye holding it back there too. >> Yeah, >> Of course, Frank. >> I mean, without the business development wheels on the ship we'd really be in an unfortunate spot. I almost just swore on television. We're not going to do that. >> It's okay. No one's regulating. >> Yeah. (all laugh) >> Elon Musk just took over Twitter. >> It was a close call. >> That's right! >> It's going to be a hellscape. >> Yeah, I mean it's, shit's on fire. So we'll just see what happens next. I do, I really want to talk about this because I think it's really special. It's an ethos and some magic has happened here. Let's talk about Detroit. Let's talk about what it means to be here. We saw so many, and I can't stress this enough, but I think it really matters. There was a commitment to celebrating place here. Lisa, did you notice this too? >> Absolutely. And it surprised me because we just don't see that at conferences. >> Yeah. We're so used to going to the same places. >> Right. >> Vegas. Vegas, Vegas. More Vegas. >> Your tone-- >> San Francisco >> (both laugh) sums up my feelings. Yes. >> Right? >> Yeah. And, well, it's almost robotic but, and the fact that we're like, oh Detroit, really? But there was so much love for this city and recognizing and supporting its residents that we just don't see at conferences. You uncovered a lot of that with your swag-savvy segments, >> Savannah: Yeah. >> And you got more of that to talk about today. >> Don't worry, it's coming. Yeah. (laughs) >> What about you? Have you enjoyed Detroit? I know you hadn't been here in a long time, when we did our intro session. >> I think it's a bold move for the CNCF to come here and celebrate. What they did, from teaching the kids in the city some tech, they had a session. I thought that was good. >> Savannah: Loved that. I think it was a risky move because a lot of people, like, weren't sure if they were going to fly to Detroit. So some say it might impact the attendance. I thought they did a good job. Their theme, Road Ahead. Nice tie in. >> Savannah: Yeah. And so I think I enjoyed Detroit. The weather was great. It didn't rain. Nice breeze outside. >> Yeah. >> The weather was great, the restaurants are phenomenal. So Detroit's a good city. I missed some hockey games. I'd love to see the Red Wings play. Missed that game. But we always come back. >> I think it's really special. I mean, every time I talked to a company about their swag, that had sourced it locally, there was a real reason for this story. I mean even with Kasten in that last segment when I noticed that they had done Carhartt beanies, Carhartt being a Michigan company. They said, "I'm so glad you noticed. That's why we did it." And I think that type of, the community commitment to place, it all comes back to community. One of the bigger themes of the show. But that passion and that support, we need more of that. >> Lisa: Yeah. >> And the thing about the guests we've had this past three days have been phenomenal. We had a diverse set of companies, individuals come on theCUBE, you know, from Scott Johnston at Docker. A really one on one. We had a great intense conversation. >> Savannah: Great way to kick it off. >> We shared a lot of inside baseball, about Docker, super important company. You know, impressed with companies like Platform9 it's been around since the OpenStack days who are now in a relevant position. Rafi Systems, hot startup, they don't have a lot of resources, a lot of guerilla marketing going on. So I love to see the mix of startups really contributing. The big players are here. So it's a real great mix of companies. And I thought the interviews were phenomenal, like you said, Ford. We had, Kubia launched on theCUBE. >> Savannah: Yes. >> That's-- >> We snooped the location for KubeCon North America. >> You did? >> Chicago, everyone. In case you missed it, Bianca was nice enough to share that with us. >> We had Sarbjeet Johal, CUBE analyst came on, Keith Townsend, yesterday with you guys. >> We had like analyst speed dating last night. (all laugh) >> How'd that go? (laughs) >> It was actually great. One of the things that they-- >> Did they hug and kiss at the end? >> Here's the funny thing is that they were debating the size of the CNC app. One thinks it's too big, one thinks it's too small. And I thought, is John Goldilocks? (John laughs) >> Savannah: Yeah. >> What is John going to think about that? >> Well I loved that segment. I thought, 'cause Keith and Sarbjeet argue with each other on Twitter all the time. And I heard Keith say before, he went, "Yeah let's have it out on theCUBE." So that was fun to watch. >> Thank you for creating this forum for us to have that kind of discourse. >> Lisa: Yes, thank you. >> Well, it wouldn't be possible without the sponsors. Want to thank the CNCF. >> Absolutely. >> And all the ecosystem partners and sponsors that make theCUBE possible. We love doing this. We love getting the stories. No story's too small for theCUBE. We'll go with it. Do whatever it takes. And if it wasn't for the sponsors, the community wouldn't get all the great knowledge. So, and thank you guys. >> Hey. Yeah, we're, we're happy to be here. Speaking of sponsors and vendors, should we talk a little swag? >> Yeah. >> What do you guys think? All right. Okay. So now this is becoming a tradition on theCUBE so I'm very delighted, the savvy swag segment. I do think it's interesting though. I mean, it's not, this isn't just me shouting out folks and showing off t-shirts and socks. It's about standing out from the noise. There's a lot of players in this space. We got a lot of CNCF projects and one of the ways to catch the attention of people walking the show floor is to have interesting swag. So we looked for the most unique swag on Wednesday and I hadn't found this yet, but I do just want to bring it up. Oops, I think I might have just dropped it. This is cute. Is, most random swag of the entire show goes to this toothbrush. I don't really have more in terms of the pitch there because this is just random. (Lisa laughs) >> But so, everyone needs that. >> John: So what's their tagline? >> And you forget these. >> Yeah, so the idea was to brush your cloud bills. So I think they're reducing the cost of-- >> Kind of a hygiene angle. >> Yeah, yeah. Very much a hygiene angle, which I found a little ironic in this crowd to be completely honest with you. >> John: Don't leave the lights on theCUBE. That's what they say. >> Yeah. >> I mean we are theCUBE so it would be unjust of me not to show you a Rubik's cube. This is actually one of those speed cubes. I'm not going to be able to solve this for you with one hand on camera, but apparently someone did it in 17 seconds at the booth. Knowing this audience, not surprising to me at all. Today we are, and yesterday, was the t-shirt contest. Best t-shirt contest. Today we really dove into the socks. So this is, I noticed this trend at KubeCon in Los Angeles last year. Lots of different socks, clouds obviously a theme for the cloud. I'm just going to lay these out. Lots of gamers in the house. Not surprising. Here on this one. >> John: Level up. >> Got to level up. I love these 'cause they say, "It's not a bug." And anyone who's coded has obviously had to deal with that. We've got, so Star Wars is a huge theme here. There's Lego sets. >> John: I think it's Star Trek. But. >> That's Star Trek? >> John: That's okay. >> Could be both. (Lisa laughs) >> John: Nevermind, I don't want to. >> You can flex your nerd and geek with us anytime you want, John. I don't mind getting corrected. I'm all about, I'm all about the truth. >> Star Trek. Star Wars. Okay, we're all the same. Okay, go ahead. >> Yeah, no, no, this is great. Slim.ai was nice enough to host us for dinner on Tuesday night. These are their lovely cloud socks. You can see Cloud Native, obviously Cloud Native Foundation, cloud socks, whole theme here. But if we're going to narrow it down to some champions, I love these little bee elephants from Raft. And when I went up to these guys, I actually probably would've called these my personal winner. They said, again, so community focused and humble here at CNCF, they said that Wiz was actually the champion according to the community. These unicorn socks are pretty excellent. And I have to say the branding is flawless. So we'll go ahead and give Wiz the win on the best sock contest. >> John: For the win. >> Yeah, Wiz for the win. However, the thing that I am probably going to use the most is this really dope Detroit snapback from Kasten. So I'm going to be rocking this from now on for the rest of the segment as well. And I feel great about this snapback. >> Looks great. Looks good on you. >> Yeah. >> Thanks John. (John laughs) >> So what are we expecting between now and KubeCon in Amsterdam? >> Well, I think it's going to be great to see how they, the European side, it's a chill show. It's great. Brings in the European audience from the global perspective. I always love the EU shows because one, it's a great destination. Amsterdam's going to be a great location. >> Savannah: I'm pumped. >> The American crowd loves going over there. All the event cities that they choose are always awesome. I missed Valencia cause I got Covid. I'm really bummed about that. But I love the European shows. It's just a little bit, it's high intensity, but it's the European chill. They got a little bit more of that siesta vibe going on. >> Yeah. >> And it's just awesome. >> Yeah, >> And I think that the mojo that carried throughout this week, it's really challenging to not only have a show that's five days, >> but to go through all week, >> Savannah: Seriously. >> to a Friday at 4:00 PM Eastern Time, and still have the people here, the energy and all the collaboration. >> Savannah: Yeah. >> The conversations that are still happening. I think we're going to see a lot more innovation come spring 2023. >> Savannah: Mm-hmm. >> Yeah. >> So should we do a bet, somebody's got to buy dinner? Who, well, I guess the folks who lose this will buy dinner for the other one. How many attendees do you think we'll see in Amsterdam? So we had 4,000, >> Oh, I'm going to lose this one. >> roughly in Los Angeles. Priyanka was nice enough to share with us, there was 8,000 here in Detroit. And I'm talking in person, we're not going to meddle this with the online. >> 6500. >> Lisa: I was going to say six, six K. >> I'm going 12,000. >> Ooh! >> I'm going to go ahead and go big I'm going to go opposite Price Is Right. >> One dollar. >> Yeah. (all laugh) That's exactly where I was driving with it. I'm going, I'm going absolutely all in. I think the momentum here is building. I think if we look at the numbers from-- >> John: You could go Family Feud >> Yeah, yeah, exactly. And they mentioned that they had 11,000 people who have taken their Kubernetes course in that first year. If that's a benchmark and an indicator, we've got the veteran players here. But I do think that, I personally think that the hype of Kubernetes has actually preceded adoption. If you look at the data and now we're finally tipping over. I think the last two years we were on the fringe and right now we're there. It's great. (voice blares loudly on loudspeaker) >> Well, on that note (all laugh) On that note, actually, on that note, as we are talking, so I got to give cred to my cohosts. We deal with a lot of background noise here on theCUBE. It is a live show floor. There's literally someone on an e-scooter behind me. There's been Pong going on in the background. The sound will haunt the three of us for the rest of our lives, as well as the production crew. (Lisa laughs) And, and just as we're sitting here doing this segment last night, they turned the lights off on us, today they're letting everyone know that the event is over. So on that note, I just want to say, Lisa, thank you so much. Such a warm welcome to the team. >> Thank you. >> John, what would we do without you? >> You did an amazing job. First CUBE, three days. It's a big show. You got staying power, I got to say. >> Lisa: Absolutely. >> Look at that. Not bad. >> You said it on camera now. >> Not bad. >> So you all are stuck with me. (all laugh) >> A plus. Great job to the team. Again, we do so much flow here. Brandon, Team, Andrew, Noah, Anderson, Frank. >> They're doing our hair, they're touching up makeup. They're helping me clean my teeth, staying hydrated. >> We look good because of you. >> And the guests. Thanks for coming on and spending time with us. And of course the sponsors, again, we can't do it without the sponsors. If you're watching this and you're a sponsor, support theCUBE, it helps people get what they need. And also we're do a lot more segments around community and a lot more educational stuff. >> Savannah: Yeah. So we're going to do a lot more in the EU and beyond. So thank you. >> Yeah, thank you. And thank you to everyone. Thank you to the community, thank you to theCUBE community and thank you for tuning in, making it possible for us to have somebody to talk to on the other side of the camera. My name is Savannah Peterson for the last time in Detroit, Michigan. Thanks for tuning into theCUBE. >> Okay, we're done. (bright upbeat music)

>>Set restaurants. And who says TEUs had got a little ass more skin in the game for us, in charge of his destiny? You guys are excited. Robert Worship is Chief Alumni. >>My name is Dave Ante, and I'm a long time industry analyst. So when you're as old as I am, you've seen a lot of transitions. Everybody talks about industry cycles and waves. I've seen many, many waves. Met a lot of industry executives and of a little bit of a, an industry historian. When you interview many thousands of people, probably five or 6,000 people as I have over the last half of a decade, you get to interact with a lot of people's knowledge and you begin to develop patterns. And so that's sort of what I bring is, is an ability to catalyze the conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody's expert at something. Everybody's passionate about something and has real deep knowledge about that's something well, we wanna focus in on that area and extract that knowledge and share it with our communities. This is Dave Ante. Thanks for watching the Cube. >>Hello everyone and welcome back to the Cube where we are streaming live this week from CubeCon. I am Savannah Peterson and I am joined by an absolutely stellar lineup of cube brilliance this afternoon. To my left, a familiar face, Lisa Martin. Lisa, how you feeling? End of day two. >>Excellent. It was so much fun today. The buzz started yesterday, the momentum, the swell, and we only heard even more greatness today. >>Yeah, yeah, abs, absolutely. You know, I, I sometimes think we've hit an energy cliff, but it feels like the energy is just >>Continuous. Well, I think we're gonna, we're gonna slide right into tomorrow. >>Yeah, me too. I love it. And we've got two fantastic analysts with us today, Sarge and Keith. Thank you both for joining us. We feel so lucky today. >>Great being back on. >>Thanks for having us. Yeah, Yeah. It's nice to have you back on the show. We were, had you yesterday, but I miss hosting with you. It's been a while. >>It has been a while. We haven't done anything in since, Since pre >>Pandemic, right? Yeah, I think you're >>Right. Four times there >>Be four times back in the day. >>We, I always enjoy whole thing, Lisa, cuz she's so well prepared. I don't have to do any research when I come >>Home. >>Lisa will bring up some, Oh, sorry. Jeep, I see that in 2008 you won this award for Yeah. Being just excellent and I, I'm like, Oh >>Yeah. All right Keith. So, >>So did you do his analysis? >>Yeah, it's all done. Yeah. Great. He only part, he's not sitting next to me too. We can't see it, so it's gonna be like a magic crystal bell. Right. So a lot of people here. You got some stats in terms of the attendees compared >>To last year? Yeah, Priyanka told us we were double last year up to 8,000. We also got the scoop earlier that 2023 is gonna be in Chicago, which is very exciting. >>Oh, that is, is nice. Yeah, >>We got to break that here. >>Excellent. Keith, talk to us about what some of the things are that you've seen the last couple of days. The momentum. What's the vibe? I saw your tweet about the top three things you were being asked. Kubernetes was not one of them. >>Kubernetes were, was not one of 'em. This conference is starting to, it, it still feels very different than a vendor conference. The keynote is kind of, you know, kind of all over the place talking about projects, but the hallway track has been, you know, I've, this is maybe my fifth or sixth CU con in person. And the hallway track is different. It's less about projects and more about how, how do we adjust to the enterprise? How do we Yes. Actually do enterprise things. And it has been amazing watching this community grow. I'm gonna say grow up and mature. Yes. You know, you know, they're not wearing ties yet, but they are definitely understanding kind of the, the friction of implementing new technology in, in an enterprise. >>Yeah. So ge what's your, what's been your take, We were with you yesterday. What's been the take today to take aways? >>NOMA has changed since yesterday, but a few things I think I, I missed talking about that yesterday were that, first of all, let's just talk about Amazon. Amazon earnings came out, it spooked the market and I think it's relevant in this context as well, because they're number one cloud provider. Yeah. And all, I mean, almost all of these technologies on the back of us here, they are related to cloud, right? So it will have some impact on these. Like we have to analyze that. Like will it make the open source go faster or slower in, in lieu of the fact that the, the cloud growth is slowing. Right? So that's, that's one thing that's put that's put that aside. I've been thinking about the, the future of Kubernetes. What is the future of Kubernetes? And in that context, I was thinking like, you know, I think in, when I put a pointer there, I think in tangents, like, what else is around this thing? So I think CN CNCF has been writing the success of Kubernetes. They are, that was their number one flagship project, if you will. And it was mature enough to stand on its own. It it was Google, it's Google's Borg dub da Kubernetes. It's a genericized version of that. Right? So folks who do tech deep down, they know that, Right. So I think it's easier to stand with a solid, you know, project. But when the newer projects come in, then your medal will get tested at cncf. Right. >>And cncf, I mean they've got over 140 projects Yeah. Right now. So there's definitely much beyond >>Kubernetes. Yeah. So they, I have numbers there. 18 graduated, right, 37 in incubation and then 81 in Sandbox stage. They have three stages, right. So it's, they have a lot to chew on and the more they take on, the less, you know, quality you get goes into it. Who is, who's putting the money behind it? Which vendors are sponsoring like cncf, like how they're getting funded up. I think it >>Something I pay attention to as well. Yeah. Yeah. Lisa, I know you've got >>Some insight. Those are the things I was thinking about today. >>I gotta ask you, what's your take on what Keith said? Are you also seeing the maturation of the enterprise here at at coupon? >>Yes, I am actually, when you say enterprise versus what's the other side? Startups, right? Yeah. So startups start using open source a lot more earlier or lot more than enterprises. The enterprise is what they need. Number one thing is the, for their production workloads, they want a vendor sporting them. I said that yesterday as well, right? So it depend depending on the size of the enterprise. If you're a big shop, definitely if you have one of the 500 or Fortune five hundreds and your tech savvy shop, then you can absorb the open source directly coming from the open source sort of universe right. Coming to you. But if you are the second tier of enterprise, you want to go to a provider which is managed service provider, or it can be cloud service provider in this case. Yep. Most of the cloud service providers have multiple versions of Kubernetes, for example. >>I'm not talking about Kubernetes only, but like, but that is one example, right? So at Amazon you can get five different flavors of Kubernetes, right? Fully manage, have, manage all kind of stuff. So people don't have bandwidth to manage that stuff locally. You have to patch it, you have to roll in the new, you know, updates and all that stuff. Like, it's a lot of work for many. So CNCF actually is formed for that reason. Like the, the charter is to bring the quality to open source. Like in other companies they have the release process and they, the stringent guidelines and QA and all that stuff. So is is something ready for production? That's the question when it comes to any software, right? So they do that kind of work and, and, and they have these buckets defined at high level, but it needs more >>Work. Yeah. So one of the things that, you know, kind of stood out to me, I have good friend in the community, Alex Ellis, who does open Fast. It's a serverless platform, great platform. Two years ago or in 2019, there was a serverless day date. And in serverless day you had K Native, you had Open Pass, you had Ws, which is supported by IBM completely, not CNCF platforms. K native came into the CNCF full when Google donated the project a few months ago or a couple of years ago, now all of a sudden there's a K native day. Yes. Not a serverless day, it's a K native day. And I asked the, the CNCF event folks like, what happened to Serverless Day? I missed having open at serverless day. And you know, they, they came out and said, you know what, K native got big enough. >>They came in and I think Red Hat and Google wanted to sponsor a K native day. So serverless day went away. So I think what what I'm interested in and over the next couple of years is, is they're gonna be pushback from the C against the cncf. Is the CNCF now too big? Is it now the gatekeeper for do I have to be one of those 147 projects, right? In order enough to get my project noticed the open, fast, great project. I don't think Al Alex has any desire to have his project hosted by cncf, but it probably deserves, you know, shoulder left recognition with that. So I'm pushing to happen to say, okay, if this is open community, this is open source. If CNC is the place to have the cloud native conversation, what about the projects that's not cncf? Like how do we have that conversation when we don't have the power of a Google right. Or a, or a Lenox, et cetera, or a Lenox Foundation. So GE what, >>What are your thoughts on that? Is, is CNC too big? >>I don't think it's too big. I think it's too small to handle the, what we are doing in open source, right? So it's a bottle. It can become a bottleneck. Okay. I think too big in a way that yeah, it has, it has, it has power from that point of view. It has that cloud, if you will. The people listen to it. If it's CNCF project or this must be good, it's like in, in incubators. Like if you are y white Combinator, you know, company, it must be good. You know, I mean, may not be >>True, but, >>Oh, I think there's a bold assumption there though. I mean, I think everyone's just trying to do the best they can. And when we're evaluating projects, a very different origin and background, it's incredibly hard. Very c and staff is a staff of 30 people. They've got 180,000 people that are contributing to these projects and a thousand maintainers that they're trying to uphold. I think the challenge is actually really great. And to me, I actually look at events as an illustration of, you know, what's the culture and the health of an organization. If I were to evaluate CNCF based on that, I'd say we're very healthy right now. I would say that we're in a good spot. There's a lot of momentum. >>Yeah. I, I think CNCF is very healthy. I'm, I'm appreciative for it being here. I love coupon. It's becoming the, the facto conference to have this conversation has >>A totally >>Different vibe to other, It's a totally different vibe. Yeah. There needs to be a conduit and truth be told, enterprise buyers, to subject's point, this is something that we do absolutely agree on, on enterprise buyers. We want someone to pick winners and losers. We do, we, we don't want a box of Lego dumped on our, the middle of our table. We want somebody to have sorted that out. So while there may be five or six different service mesh solutions, at least the cncf, I can go there and say, Oh, I'll pick between the three or four that are most popular. And it, it's a place to curate. But I think with that curation comes the other side of it. Of how do we, how, you know, without the big corporate sponsor, how do I get my project pushed up? Right? Elevated. Elevated, Yep. And, and put onto the show floor. You know, another way that projects get noticed is that startups will adopt them, Push them. They may not even be, I don't, my CNCF project may not, my product may not even be based on the CNCF product. But the new stack has a booth, Ford has a booth. Nothing to do with a individual prod up, but promoting open source. What happens when you're not sponsored? >>I gotta ask you guys, what do you disagree on? >>Oh, so what, what do we disagree on? So I'm of the mindset, I can, I can say this, I I believe hybrid infrastructure is the future of it. Bar none. If I built my infrastructure, if I built my application in the cloud 10 years ago and I'm still building net new applications, I have stuff that I built 10 years ago that looks a lot like on-prem, what do I do with it? I can't modernize it cuz I don't have the developers to do it. I need to stick that somewhere. And where I'm going to stick that at is probably a hybrid infrastructure. So colo, I'm not gonna go back to the data center, but I'm, I'm gonna look, pick up something that looks very much like the data center and I'm saying embrace that it's the future. And if you're Boeing and you have, and Boeing is a member, cncf, that's a whole nother topic. If you have as 400 s, hpu X, et cetera, stick that stuff. Colo, build new stuff, but, and, and continue to support OpenStack, et cetera, et cetera. Because that's the future. Hybrid is the future. >>And sub g agree, disagree. >>I okay. Hybrid. Nobody can deny that the hybrid is the reality, not the future. It's a reality right now. It's, it's a necessity right now you can't do without it. Right. And okay, hybrid is very relative term. You can be like 10% here, 90% still hybrid, right? So the data center is shrinking and it will keep shrinking. Right? And >>So if by whole is the data center shrinking? >>This is where >>Quick one quick getting guys for it. How is growing by a clip? Yeah, but there's no data supporting. David Lym just came out for a report I think last year that showed that the data center is holding steady, holding steady, not growing, but not shrinking. >>Who sponsored that study? Wait, hold on. So the, that's a question, right? So more than 1 million data centers have been closed. I have, I can dig that through number through somebody like some organizations we published that maybe they're cloud, you know, people only. So the, when you get these kind of statements like it, it can be very skewed statements, right. But if you have seen the, the scene out there, which you have, I know, but I have also seen a lot of data centers walk the floor of, you know, a hundred thousand servers in a data center. I cannot imagine us consuming the infrastructure the way we were going into the future of co Okay. With, with one caveat actually. I am not big fan of like broad strokes. Like make a blanket statement. Oh no, data center's dead. Or if you are, >>That's how you get those esty headlines now. Yeah, I know. >>I'm all about to >>Put a stake in the ground. >>Actually. The, I think that you get more intelligence from the new end, right? A small little details if you will. If you're golden gold manak or Bank of America, you have so many data centers and you will still have data centers because performance matters to you, right? Your late latency matters for applications. But if you are even a Fortune 500 company on the lower end and or a healthcare vertical, right? That your situation is different. If you are a high, you know, growth startup, your situation is different, right? You will be a hundred percent cloud. So cloud gives you velocity, the, the, the pace of change, the pace of experimentation that actually you are buying innovation through cloud. It's proxy for innovation. And that's how I see it. But if you have, if you're stuck with older applications, I totally understand. >>Yeah. So the >>We need that OnPrem. Yeah, >>Well I think the, the bring your fuel sober, what we agree is that cloud is the place where innovation happens. Okay? At some point innovation becomes legacy debt and you have thus hybrid, you are not going to keep your old applications up to date forever. The, the, the math just doesn't add up. And where I differ in opinion is that not everyone needs innovation to keep moving. They need innovation for a period of time and then they need steady state. So Sergeant, we >>Argue about this. I have a, I >>Love this debate though. I say it's efficiency and stability also plays an important role. I see exactly what you're talking about. No, it's >>Great. I have a counter to that. Let me tell you >>Why. Let's >>Hear it. Because if you look at the storage only, right? Just storage. Just take storage computer network for, for a minute. There three cost reps in, in infrastructure, right? So storage earlier, early on there was one tier of storage. You say pay the same price, then now there are like five storage tiers, right? What I'm trying to say is the market sets the price, the market will tell you where this whole thing will go, but I know their margins are high in cloud, 20 plus percent and margin will shrink as, as we go forward. That means the, the cloud will become cheaper relative to on-prem. It, it, in some cases it's already cheaper. But even if it's a stable workload, even in that case, we will have a lower tier of service. I mean, you, you can't argue with me that the cloud versus your data center, they are on the same tier of services. Like cloud is a better, you know, product than your data center. Hands off. >>I love it. We, we are gonna relish in the debates between the two of you. Mic drops. The energy is great. I love it. Perspective. It's not like any of us can quite see through the crystal ball that we have very informed opinions, which is super exciting. Yeah. Lisa, any last thoughts today? >>Just love, I love the debate as well. That, and that's, that's part of what being in this community is all about. So sharing about, sharing opinions, expressing opinions. That's how it grows. That's how, that's how we innovate. Yeah. Obviously we need the cloud, but that's how we innovate. That's how we grow. Yeah. And we've seen that demonstrated the last couple days and I and your, your takes here on the Cuban on Twitter. Brilliant. >>Thank you. I absolutely love it. I'm gonna close this out with a really important analysis on the swag of the show. Yes. And if you know, yesterday we were looking at what is the weirdest swag or most unique swag We had that bucket hat that took the grand prize. Today we're gonna focus on something that's actually quite cool. A lot of the vendors here have really dedicated their swag to being local to Detroit. Very specific in their sourcing. Sonotype here has COOs. They're beautiful. You can't quite feel this flannel, but it's very legit hand sound here in Michigan. I can't say that I've been to too many conferences, if any, where there was this kind of commitment to localizing and sourcing swag from around the corner. We also see this with the Intel booth. They've got screen printers out here doing custom hoodies on spot. >>Oh fun. They're even like appropriately sized. They had local artists do these designs and if you're like me and you care about what's on your wrist, you're familiar with Shinola. This is one of my favorite swags that's available. There is a contest. Oh going on. Hello here. Yeah, so if you are Atan, make sure that you go and check this out. The we, I talked about this on the show. We've had the founder on the show or the CEO and yeah, I mean Shine is just full of class as since we are in Detroit as well. One of the fun themes is cars. >>Yes. >>And Storm Forge, who are also on the show, is actually giving away an Aston Martin, which is very exciting. Not exactly manufactured in Detroit. However, still very cool on the car front and >>The double oh seven version named the best I >>Know in the sixties. It's love it. It's very cool. Two quick last things. We talk about it a lot on the show. Every company now wants to be a software company. Yep. On that vein, and keeping up with my hat theme, the Home Depot is here because they want everybody to know that they in fact are a technology company, which is very cool. They have over 500,000 employees. You can imagine there's a lot of technology that has to go into keeping Napa. Absolutely. Yep. Wild to think about. And then last, but not at least very quick, rapid fire, best t-shirt contest. If you've ever ran to one of these events, there are a ton of T-shirts out there. I rate them on two things. Wittiest line and softness. If you combine the two, you'll really be our grand champion for the year. I'm just gonna hold these up and set them down for your laughs. Not afraid to commit, which is pretty great. This is another one designed by locals here. Detroit Code City. Oh, love it. This one made me chuckle the most. Kiss my cash. >>Oh, that's >>Good. These are also really nice and soft, which is fantastic. Also high on the softness category is this Op Sarah one. I also like their bird logo. These guys, there's just, you know, just real nice touch. So unfortunately, if you have the fumble, you're not here with us, live in Detroit. At least you're gonna get taste of the swag. I taste of the stories and some smiles hear from those of us on the cube. Thank you both so much for being here with us. Lisa, thanks for another fabulous day. Got it, girl. My name's Savannah Peterson. Thank you for joining us from Detroit. We're the cube and we can't wait to see you tomorrow.