(upbeat music) >> Welcome back to theCUBE's coverage of Women in Data Science 2023 live from Stanford University. This is Lisa Martin. My co-host is Tracy Yuan. We're excited to be having great conversations all day but you know, 'cause you've been watching. We've been interviewing some very inspiring women and some men as well, talking about all of the amazing applications of data science. You're not going to want to miss this next conversation. Our guest is Gabriela de Queiroz, Principal Cloud Advocate Manager of Microsoft. Welcome, Gabriela. We're excited to have you. >> Thank you very much. I'm so excited to be talking to you. >> Yeah, you're on theCUBE. >> Yeah, finally. (Lisa laughing) Like a dream come true. (laughs) >> I know and we love that. We're so thrilled to have you. So you have a ton of experience in the data space. I was doing some research on you. You've worked in software, financial advertisement, health. Talk to us a little bit about you. What's your background in? >> So I was trained in statistics. So I'm a statistician and then I worked in epidemiology. I worked with air pollution and public health. So I was a researcher before moving into the industry. So as I was talking today, the weekly paths, it's exactly who I am. I went back and forth and back and forth and stopped and tried something else until I figured out that I want to do data science and that I want to do different things because with data science we can... The beauty of data science is that you can move across domains. So I worked in healthcare, financial, and then different technology companies. >> Well the nice thing, one of the exciting things that data science, that I geek out about and Tracy knows 'cause we've been talking about this all day, it's just all the different, to your point, diverse, pun intended, applications of data science. You know, this morning we were talking about, we had the VP of data science from Meta as a keynote. She came to theCUBE talking and really kind of explaining from a content perspective, from a monetization perspective, and of course so many people in the world are users of Facebook. It makes it tangible. But we also heard today conversations about the applications of data science in police violence, in climate change. We're in California, we're expecting a massive rainstorm and we don't know what to do when it rains or snows. But climate change is real. Everyone's talking about it, and there's data science at its foundation. That's one of the things that I love. But you also have a lot of experience building diverse teams. Talk a little bit about that. You've created some very sophisticated data science solutions. Talk about your recommendation to others to build diverse teams. What's in it for them? And maybe share some data science project or two that you really found inspirational. >> Yeah, absolutely. So I do love building teams. Every time I'm given the task of building teams, I feel the luckiest person in the world because you have the option to pick like different backgrounds and all the diverse set of like people that you can find. I don't think it's easy, like people say, yeah, it's very hard. You have to be intentional. You have to go from the very first part when you are writing the job description through the interview process. So you have to be very intentional in every step. And you have to think through when you are doing that. And I love, like my last team, we had like 10 people and we were so diverse. Like just talking about languages. We had like 15 languages inside a team. So how beautiful it is. Like all different backgrounds, like myself as a statistician, but we had people from engineering background, biology, languages, and so on. So it's, yeah, like every time thinking about building a team, if you wanted your team to be diverse, you need to be intentional. >> I'm so glad you brought up that intention point because that is the fundamental requirement really is to build it with intention. >> Exactly, and I love to hear like how there's different languages. So like I'm assuming, or like different backgrounds, I'm assuming everybody just zig zags their way into the team and now you're all women in data science and I think that's so precious. >> Exactly. And not only woman, right. >> Tracy: Not only woman, you're right. >> The team was diverse not only in terms of like gender, but like background, ethnicity, and spoken languages, and language that they use to program and backgrounds. Like as I mentioned, not everybody did the statistics in school or computer science. And it was like one of my best teams was when we had this combination also like things that I'm good at the other person is not as good and we have this knowledge sharing all the time. Every day I would feel like I'm learning something. In a small talk or if I was reviewing something, there was always something new because of like the richness of the diverse set of people that were in your team. >> Well what you've done is so impressive, because not only have you been intentional with it, but you sound like the hallmark of a great leader of someone who hires and builds teams to fill gaps. They don't have to know less than I do for me to be the leader. They have to have different skills, different areas of expertise. That is really, honestly Gabriela, that's the hallmark of a great leader. And that's not easy to come by. So tell me, who were some of your mentors and sponsors along the way that maybe influenced you in that direction? Or is that just who you are? >> That's a great question. And I joke that I want to be the role model that I never had, right. So growing up, I didn't have anyone that I could see other than my mom probably or my sister. But there was no one that I could see, I want to become that person one day. And once I was tracing my path, I started to see people looking at me and like, you inspire me so much, and I'm like, oh wow, this is amazing and I want to do do this over and over and over again. So I want to be that person to inspire others. And no matter, like I'll be like a VP, CEO, whoever, you know, I want to be, I want to keep inspiring people because that's so valuable. >> Lisa: Oh, that's huge. >> And I feel like when we grow professionally and then go to the next level, we sometimes we lose that, you know, thing that's essential. And I think also like, it's part of who I am as I was building and all my experiences as I was going through, I became what I mentioned is unique person that I think we all are unique somehow. >> You're a rockstar. Isn't she a rockstar? >> You dropping quotes out. >> I'm loving this. I'm like, I've inspired Gabriela. (Gabriela laughing) >> Oh my God. But yeah, 'cause we were asking our other guests about the same question, like, who are your role models? And then we're talking about how like it's very important for women to see that there is a representation, that there is someone they look up to and they want to be. And so that like, it motivates them to stay in this field and to start in this field to begin with. So yeah, I think like you are definitely filling a void and for all these women who dream to be in data science. And I think that's just amazing. >> And you're a founder too. In 2012, you founded R Ladies. Talk a little bit about that. This is present in more than 200 cities in 55 plus countries. Talk about R Ladies and maybe the catalyst to launch it. >> Yes, so you always start, so I'm from Brazil, I always talk about this because it's such, again, I grew up over there. So I was there my whole life and then I moved to here, Silicon Valley. And when I moved to San Francisco, like the doors opened. So many things happening in the city. That was back in 2012. Data science was exploding. And I found out something about Meetup.com, it's a website that you can join and go in all these events. And I was going to this event and I joke that it was kind of like going to the Disneyland, where you don't know if I should go that direction or the other direction. >> Yeah, yeah. >> And I was like, should I go and learn about data visualization? Should I go and learn about SQL or should I go and learn about Hadoop, right? So I would go every day to those meetups. And I was a student back then, so you know, the budget was very restricted as a student. So we don't have much to spend. And then they would serve dinner and you would learn for free. And then I got to a point where I was like, hey, they are doing all of this as a volunteer. Like they are running this meetup and events for free. And I felt like it's a cycle. I need to do something, right. I'm taking all this in. I'm having this huge opportunity to be here. I want to give back. So that's what how everything started. I was like, no, I have to think about something. I need to think about something that I can give back. And I was using R back then and I'm like how about I do something with R. I love R, I'm so passionate about R, what about if I create a community around R but not a regular community, because by going to this events, I felt that as a Latina and as a woman, I was always in the corner and I was not being able to participate and to, you know, be myself and to network and ask questions. I would be in the corner. So I said to myself, what about if I do something where everybody feel included, where everybody can participate, can share, can ask questions without judgment? So that's how R ladies all came together. >> That's awesome. >> Talk about intentions, like you have to, you had that go in mind, but yeah, I wanted to dive a little bit into R. So could you please talk more about where did the passion for R come from, and like how did the special connection between you and R the language, like born, how did that come from? >> It was not a love at first sight. >> No. >> Not at all. Not at all. Because that was back in Brazil. So all the documentation were in English, all the tutorials, only two. We had like very few tutorials. It was not like nowadays that we have so many tutorials and courses. There were like two tutorials, other documentation in English. So it's was hard for me like as someone that didn't know much English to go through the language and then to learn to program was not easy task. But then as I was going through the language and learning and reading books and finding the people behind the language, I don't know how I felt in love. And then when I came to to San Francisco, I saw some of like the main contributors who are speaking in person and I'm like, wow, they are like humans. I don't know, it was like, I have no idea why I had this love. But I think the the people and then the community was the thing that kept me with the R language. >> Yeah, the community factors is so important. And it's so, at WIDS it's so palpable. I mean I literally walk in the door, every WIDS I've done, I think I've been doing them for theCUBE since 2017. theCUBE has been here since the beginning in 2015 with our co-founders. But you walk in, you get this sense of belonging. And this sense of I can do anything, why not? Why not me? Look at her up there, and now look at you speaking in the technical talk today on theCUBE. So inspiring. One of the things that I always think is you can't be what you can't see. We need to be able to see more people that look like you and sound like you and like me and like you as well. And WIDS gives us that opportunity, which is fantastic, but it's also helping to move the needle, really. And I was looking at some of the Anitab.org stats just yesterday about 2022. And they're showing, you know, the percentage of females in technical roles has been hovering around 25% for a while. It's a little higher now. I think it's 27.6 according to any to Anitab. We're seeing more women hired in roles. But what are the challenges, and I would love to get your advice on this, for those that might be in this situation is attrition, women who are leaving roles. What would your advice be to a woman who might be trying to navigate family and work and career ladder to stay in that role and keep pushing forward? >> I'll go back to the community. If you don't have a community around you, it's so hard to navigate. >> That's a great point. >> You are lonely. There is no one that you can bounce ideas off, that you can share what you are feeling or like that you can learn as well. So sometimes you feel like you are the only person that is going through that problem or like, you maybe have a family or you are planning to have a family and you have to make a decision. But you've never seen anyone going through this. So when you have a community, you see people like you, right. So that's where we were saying about having different people and people like you so they can share as well. And you feel like, oh yeah, so they went through this, they succeed. I can also go through this and succeed. So I think the attrition problem is still big problem. And I'm sure will be worse now with everything that is happening in Tech with layoffs. >> Yes and the great resignation. >> Yeah. >> We are going back, you know, a few steps, like a lot of like advancements that we did. I feel like we are going back unfortunately, but I always tell this, make sure that you have a community. Make sure that you have a mentor. Make sure that you have someone or some people, not only one mentor, different mentors, that can support you through this trajectory. Because it's not easy. But there are a lot of us out there. >> There really are. And that's a great point. I love everything about the community. It's all about that network effect and feeling like you belong- >> That's all WIDS is about. >> Yeah. >> Yes. Absolutely. >> Like coming over here, it's like seeing the old friends again. It's like I'm so glad that I'm coming because I'm all my old friends that I only see like maybe once a year. >> Tracy: Reunion. >> Yeah, exactly. And I feel like that our tank get, you know- >> Lisa: Replenished. >> Exactly. For the rest of the year. >> Yes. >> Oh, that's precious. >> I love that. >> I agree with that. I think one of the things that when I say, you know, you can't see, I think, well, how many females in technology would I be able to recognize? And of course you can be female technology working in the healthcare sector or working in finance or manufacturing, but, you know, we need to be able to have more that we can see and identify. And one of the things that I recently found out, I was telling Tracy this earlier that I geeked out about was finding out that the CTO of Open AI, ChatGPT, is a female. I'm like, (gasps) why aren't we talking about this more? She was profiled on Fast Company. I've seen a few pieces on her, Mira Murati. But we're hearing so much about ChatJTP being... ChatGPT, I always get that wrong, about being like, likening it to the launch of the iPhone, which revolutionized mobile and connectivity. And here we have a female in the technical role. Let's put her on a pedestal because that is hugely inspiring. >> Exactly, like let's bring everybody to the front. >> Yes. >> Right. >> And let's have them talk to us because like, you didn't know. I didn't know probably about this, right. You didn't know. Like, we don't know about this. It's kind of like we are hidden. We need to give them the spotlight. Every woman to give the spotlight, so they can keep aspiring the new generation. >> Or Susan Wojcicki who ran, how long does she run YouTube? All the YouTube influencers that probably have no idea who are influential for whatever they're doing on YouTube in different social platforms that don't realize, do you realize there was a female behind the helm that for a long time that turned it into what it is today? That's outstanding. Why aren't we talking about this more? >> How about Megan Smith, was the first CTO on the Obama administration. >> That's right. I knew it had to do with Obama. Couldn't remember. Yes. Let's let's find more pedestals. But organizations like WIDS, your involvement as a speaker, showing more people you can be this because you can see it, >> Yeah, exactly. is the right direction that will help hopefully bring us back to some of the pre-pandemic levels, and keep moving forward because there's so much potential with data science that can impact everyone's lives. I always think, you know, we have this expectation that we have our mobile phone and we can get whatever we want wherever we are in the world and whatever time of day it is. And that's all data driven. The regular average person that's not in tech thinks about data as a, well I'm paying for it. What's all these data charges? But it's powering the world. It's powering those experiences that we all want as consumers or in our business lives or we expect to be able to do a transaction, whether it's something in a CRM system or an Uber transaction like that, and have the app respond, maybe even know me a little bit better than I know myself. And that's all data. So I think we're just at the precipice of the massive impact that data science will make in our lives. And luckily we have leaders like you who can help navigate us along this path. >> Thank you. >> What advice for, last question for you is advice for those in the audience who might be nervous or maybe lack a little bit of confidence to go I really like data science, or I really like engineering, but I don't see a lot of me out there. What would you say to them? >> Especially for people who are from like a non-linear track where like going onto that track. >> Yeah, I would say keep going. Keep going. I don't think it's easy. It's not easy. But keep going because the more you go the more, again, you advance and there are opportunities out there. Sometimes it takes a little bit, but just keep going. Keep going and following your dreams, that you get there, right. So again, data science, such a broad field that doesn't require you to come from a specific background. And I think the beauty of data science exactly is this is like the combination, the most successful data science teams are the teams that have all these different backgrounds. So if you think that we as data scientists, we started programming when we were nine, that's not true, right. You can be 30, 40, shifting careers, starting to program right now. It doesn't matter. Like you get there no matter how old you are. And no matter what's your background. >> There's no limit. >> There was no limits. >> I love that, Gabriela, >> Thank so much. for inspiring. I know you inspired me. I'm pretty sure you probably inspired Tracy with your story. And sometimes like what you just said, you have to be your own mentor and that's okay. Because eventually you're going to turn into a mentor for many, many others and sounds like you're already paving that path and we so appreciate it. You are now officially a CUBE alumni. >> Yes. Thank you. >> Yay. We've loved having you. Thank you so much for your time. >> Thank you. Thank you. >> For our guest and for Tracy's Yuan, this is Lisa Martin. We are live at WIDS 23, the eighth annual Women in Data Science Conference at Stanford. Stick around. Our next guest joins us in just a few minutes. (upbeat music)

(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)

(soft music) >> Announcer: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Spain, everybody. We're here at the Fira in MWC23. Is just an amazing day. This place is packed. They said 80,000 people. I think it might even be a few more walk-ins. I'm Dave Vellante, Lisa Martin is here, David Nicholson. But right now we have the Analyst Hot Takes with three friends of theCUBE. Chris Lewis is back again with me in the co-host seat. Zeus Kerravala, analyst extraordinaire. Great to see you, Z. and Sarbjeet SJ Johal. Good to see you again, theCUBE contributor. And that's my new name for him. He says that is his nickname. Guys, thanks for coming back on. We got the all male panel, sorry, but it is what it is. So Z, is this the first time you've been on it at MWC. Take aways from the show, Hot Takes. What are you seeing? Same wine, new bottle? >> In a lot of ways, yeah. I mean, I was talking to somebody this earlier that if you had come from like MWC five years ago to this year, a lot of the themes are the same. Telco transformation, cloud. I mean, 5G is a little new. Sustainability is certainly a newer theme here. But I think it highlights just the difficulty I think the telcos have in making this transformation. And I think, in some ways, I've been unfair to them in some degree 'cause I've picked on them in the past for not moving fast enough. These are, you know, I think these kind of big transformations almost take like a perfect storm of things that come together to happen, right? And so, in the past, we had technologies that maybe might have lowered opex, but they're hard to deploy. They're vertically integrated. We didn't have the software stacks. But it appears today that between the cloudification of, you know, going to cloud native, the software stacks, the APIs, the ecosystems, I think we're actually in a position to see this industry finally move forward. >> Yeah, and Chris, I mean, you have served this industry for a long time. And you know, when you, when you do that, you get briefed as an analyst, you actually realize, wow, there's a lot of really smart people here, and they're actually, they have challenges, they're working through it. So Zeus was saying he's been tough on the industry. You know, what do you think about how the telcos have evolved in the last five years? >> I think they've changed enormously. I think the problem we have is we're always looking for the great change, the big step change, and there is no big step change in a way. What telcos deliver to us as individuals, businesses, society, the connectivity piece, that's changed. We get better and better and more reliable connectivity. We're shunting a load more capacity through. What I think has really changed is their attitude to their suppliers, their attitude to their partners, and their attitude to the ecosystem in which they play. Understanding that connectivity is not the end game. Connectivity is part of the emerging end game where it will include storage, compute, connect, and analytics and everything else. So I think the realization that they are not playing their own game anymore, it's a much more open game. And some things they will continue to do, some things they'll stop doing. We've seen them withdraw from moving into adjacent markets as much as we used to see. So a lot of them in the past went off to try and do movies, media, and a lot went way way into business IT stuff. They've mainly pulled back from that, and they're focusing on, and let's face it, it's not just a 5G show. The fixed environment is unbelievably important. We saw that during the pandemic. Having that fixed broadband connection using wifi, combining with cellular. We love it. But the problem as an industry is that the users often don't even know the connectivity's there. They only know when it doesn't work, right? >> If it's not media and it's not business services, what is it? >> Well, in my view, it will be enabling third parties to deliver the services that will include media, that will include business services. So embedding the connectivity all the way into the application that gets delivered or embedding it so the quality mechanism deliver the gaming much more accurately or, I'm not a gamer, so I can't comment on that. But no, the video quality if you want to have a high quality video will come through better. >> And those cohorts will pay for that value? >> Somebody will pay somewhere along the line. >> Seems fuzzy to me. >> Me too. >> I do think it's use case dependent. Like you look at all the work Verizon did at the Super Bowl this year, that's a perfect case where they could have upsold. >> Explain that. I'm not familiar with it. >> So Verizon provided all the 5G in the Super Bowl. They provided a lot of, they provided private connectivity for the coaches to talk to the sidelines. And that's a mission critical application, right? In the NFL, if one side can't talk, the other side gets shut down. You can't communicate with the quarterback or the coaches. There's a lot of risk at that. So, but you know, there's a case there, though, I think where they could have even made that fan facing. Right? And if you're paying 2000 bucks to go to a game, would you pay 50 bucks more to have a higher tier of bandwidth so you can post things on social? People that go there, they want people to know they were there. >> Every football game you go to, you can't use your cell. >> Analyst: Yeah, I know, right? >> All right, let's talk about developers because we saw the eight APIs come out. I think ISVs are going to be a big part of this. But it's like Dee Arthur said. Hey, eight's better than zero, I guess. Okay, so, but so the innovation is going to come from ISVs and developers, but what are your hot takes from this show and now day two, we're a day and a half in, almost two days in. >> Yeah, yeah. There's a thing that we have talked, I mentioned many times is skills gravity, right? Skills have gravity, and also, to outcompete, you have to also educate. That's another theme actually of my talks is, or my research is that to puts your technology out there to the practitioners, you have to educate them. And that's the only way to democratize your technology. What telcos have been doing is they have been stuck to the proprietary software and proprietary hardware for too long, from Nokia's of the world and other vendors like that. So now with the open sourcing of some of the components and a few others, right? And they're open source space and antenna, you know? Antennas are becoming software now. So with the invent of these things, which is open source, it helps us democratize that to the other sort of skirts of the practitioners, if you will. And that will bring in more applications first into the IOT space, and then maybe into the core sort of California, if you will. >> So what does a telco developer look like? I mean, all the blockchain developers and crypto developers are moving into generative AI, right? So maybe those worlds come together. >> You'd like to think though that the developers would understand everything's network centric today. So you'd like to think they'd understand that how the network responds, you know, you'd take a simple app like Zoom or something. If it notices the bandwidth changes, it should knock down the resolution. If it goes up it, then you can add different features and things and you can make apps a lot smarter that way. >> Well, G2 was saying today that they did a deal with Mercedes, you know this probably better than I do, where they're going to embed WebEx in the car. And if you're driving, it'll shut off the camera. >> Of course. >> I'm like, okay. >> I'll give you a better example though. >> But that's my point. Like, isn't there more that we can do? >> You noticed down on the SKT stand the little helicopter. That's a vertical lift helicopter. So it's an electric vertical lift helicopter. Just think of that for a second. And then think of the connectivity to control that, to securely control that. And then I was recently at an event with Zeus actually where we saw an air traffic control system where there was no people manning the tower. It was managed by someone remotely with all the cameras around them. So managing all of those different elements, we call it IOT, but actually it's way more than what we thought of as IOT. All those components connecting, communicating securely and safely. 'Cause I don't want that helicopter to come down on my head, do you? (men laugh) >> Especially if you're in there. (men laugh) >> Okay, so you mentioned sustainability. Everybody's talking about power. I don't know if you guys have a lot of experience around TCO, but I'm trying to get to, well, is this just because energy costs are so high, and then when the energy becomes cheap again, nobody's going to pay any attention to it? Or is this the real deal? >> So one of the issues around the, if we want to experience all that connectivity locally or that helicopter wants to have that connectivity, we have to ultimately build denser, more reliable networks. So there's a CapEx, we're going to put more base stations in place. We need more fiber in the ground to support them. Therefore, the energy consumption will go up. So we need to be more efficient in the use of energy. Simple as that. >> How much of the operating expense is energy? Like what percent of it? Is it 10%? Is it 20%? Is it, does anybody know? >> It depends who you ask and it depends on the- >> I can't get an answer to that. I mean, in the enterprise- >> Analyst: The data centers? >> Yeah, the data centers. >> We have the numbers. I think 10 to 15%. >> It's 10 to 12%, something like that. Is it much higher? >> I've got feeling it's 30%. >> Okay, so if it's 30%, that's pretty good. >> I do think we have to get better at understanding how to measure too. You know, like I was talking with John Davidson at Sysco about this that every rev of silicon they come out with uses more power, but it's a lot more dense. So at the surface, you go, well, that's using a lot more power. But you can consolidate 10 switches down to two switches. >> Well, Intel was on early and talking about how they can intelligently control the cores. >> But it's based off workload, right? That's the thing. So what are you running over it? You know, and so, I don't think our industry measures that very well. I think we look at things kind of boxed by box versus look at total consumption. >> Well, somebody else in theCUBE was saying they go full throttle. That the networks just say just full throttle everything. And that obviously has to change from the power consumption standpoint. >> Obviously sustainability and sensory or sensors from IOT side, they go hand in hand. Just simple examples like, you know, lights in the restrooms, like in public areas. Somebody goes in there and just only then turns. The same concept is being applied to servers and compute and storage and every aspects and to networks as well. >> Cell tower. >> Yeah. >> Cut 'em off, right? >> Like the serverless telco? (crosstalk) >> Cell towers. >> Well, no, I'm saying, right, but like serverless, you're not paying for the compute when you're not using it, you know? >> It is serverless from the economics point of view. Yes, it's like that, you know? It goes to the lowest level almost like sleep on our laptops, sleep level when you need more power, more compute. >> I mean, some of that stuff's been in networking equipment for a long time, it just never really got turned on. >> I want to ask you about private networks. You wrote a piece, Athenet was acquired by HPE right after Dell announced a relationship with Athenet, which was kind of, that was kind of funny. And so a good move, good judo move by by HP. I asked Dell about it, and they said, look, we're open. They said the right things. We'll see, but I think it's up to HP. >> Well, and the network inside Dell is. >> Yeah, okay, so. Okay, cool. So, but you said something in that article you wrote on Silicon Angle that a lot of people feel like P5G is going to basically replace wireless or cannibalize wireless. You said you didn't agree with that. Explain why? >> Analyst: Wifi. >> Wifi, sorry, I said wireless. >> No, that's, I mean that's ridiculous. Pat Gelsinger said that in his last VMware, which I thought was completely irresponsible. >> That it was going to cannibalize? >> Cannibalize wifi globally is what he said, right? Now he had Verizon on stage with him, so. >> Analyst: Wifi's too inexpensive and flexible. >> Wifi's cheap- >> Analyst: It's going to embed really well. Embedded in that. >> It's reached near ubiquity. It's unlicensed. So a lot of businesses don't want to manage their own spectrum, right? And it's great for this, right? >> Analyst: It does the job. >> For casual connectivity. >> Not today. >> Well, it does for the most part. Right now- >> For the most part. But never at these events. >> If it's engineered correctly, it will. Right? Where you need private 5G is when reliability is an absolute must. So, Chris, you and I visited the Port of Rotterdam, right? So they're putting 5G, private 5G there, but there's metal containers everywhere, right? And that's going to disrupt it. And so there are certain use cases where it makes sense. >> I've been in your basement, and you got some pretty intense equipment in there. You have private 5G in there. >> But for carpeted offices, it does not make sense to bring private. The economics don't make any sense. And you know, it runs hot. >> So where's it going to be used? Give us some examples of where we should be looking for. >> The early ones are obviously in mining, and you say in ports, in airports. It broadens cities because you've got so many moving parts in there, and always think about it, very expensive moving parts. The cranes in the port are normally expensive piece of kits. You're moving that, all that logistics around. So managing that over a distance where the wifi won't work over the distance. And in mining, we're going to see enormous expensive trucks moving around trying to- >> I think a great new use case though, so the Cleveland Browns actually the first NFL team to use it for facial recognition to enter the stadium. So instead of having to even pull your phone out, it says, hey Dave Vellante. You've got four tickets, can we check you all in? And you just walk through. You could apply that to airports. You could do put that in a hotel. You could walk up and check in. >> Analyst: Retail. >> Yeah, retail. And so I think video, realtime video analytics, I think it's a perfect use case for that. >> But you don't need 5G to do that. You could do that through another mechanism, couldn't you? >> You could do wire depending on how mobile you want to do it. Like in a stadium, you're pulling those things in and out all the time. You're moving 'em around and things, so. >> Yeah, but you're coming in at a static point. >> I'll take the contrary view here. >> See, we can't even agree on that. (men laugh) >> Yeah, I love it. Let's go. >> I believe the reliability of connection is very important, right? And the moving parts. What are the moving parts in wifi? We have the NIC card, you know, the wifi card in these suckers, right? In a machine, you know? They're bigger in size, and the radios for 5G are smaller in size. So neutralization is important part of the whole sort of progress to future, right? >> I think 5G costs as well. Yes, cost as well. But cost, we know that it goes down with time, right? We're already talking about 60, and the 5G stuff will be good. >> Actually, sorry, so one of the big boom areas at the moment is 4G LTE because the component price has come down so much, so it is affordable, you can afford to bring it all together. People don't, because we're still on 5G, if 5G standalone everywhere, you're not going to get a consistent service. So those components are unbelievably important. The skillsets of the people doing integration to bring them all together, unbelievably important. And the business case within the business. So I was talking to one of the heads of one of the big retail outlets in the UK, and I said, when are you going to do 5G in the stores? He said, well, why would I tear out all the wifi? I've got perfectly functioning wifi. >> Yeah, that's true. It's already there. But I think the technology which disappears in front of you, that's the best technology. Like you don't worry about it. You don't think it's there. Wifi, we think we think about that like it's there. >> And I do think wifi 5G switching's got to get easier too. Like for most users, you don't know which is better. You don't even know how to test it. And to your point, it does need to be invisible where the user doesn't need to think about it, right? >> Invisible. See, we came back to invisible. We talked about that yesterday. Telecom should be invisible. >> And it should be, you know? You don't want to be thinking about telecom, but at the same time, telecoms want to be more visible. They want to be visible like Netflix, don't they? I still don't see the path. It's fuzzy to me the path of how they're not going to repeat what happened with the over the top providers if they're invisible. >> Well, if you think about what telcos delivers to consumers, to businesses, then extending that connectivity into your home to help you support secure and extend your connection into Zeus's basement, whatever it is. Obviously that's- >> His awesome setup down there. >> And then in the business environment, there's a big change going on from the old NPLS networks, the old rigid structures of networks to SD1 where the control point is moved outside, which can be under control of the telco, could be under the control of a third party integrator. So there's a lot changing. I think we obsess about the relative role of the telco. The demand is phenomenal for connectivity. So address that, fulfill that. And if they do that, then they'll start to build trust in other areas. >> But don't you think they're going to address that and fulfill that? I mean, they're good at it. That's their wheelhouse. >> And it's a 1.6 trillion market, right? So it's not to be sniffed at. That's fixed on mobile together, obviously. But no, it's a big market. And do we keep changing? As long as the service is good, we don't move away from it. >> So back to the APIs, the eight APIs, right? >> I mean- >> Eight APIs is a joke actually almost. I think they released it too early. The release release on the main stage, you know? Like, what? What is this, right? But of course they will grow into hundreds and thousands of APIs. But they have to spend a lot of time and effort in that sort of context. >> I'd actually like to see the GSMA work with like AWS and Microsoft and VMware and software companies and create some standardization across their APIs. >> Yeah. >> I spoke to them yes- >> We're trying to reinvent them. >> Is that not what they're doing? >> No, they said we are not in the business of a defining standards. And they used a different term, not standard. I mean, seriously. I was like, are you kidding me? >> Let's face it, there aren't just eight APIs out there. There's so many of them. The TM forum's been defining when it's open data architecture. You know, the telcos themselves are defining them. The standards we talked about too earlier with Danielle. There's a lot of APIs out there, but the consistency of APIs, so we can bring them together, to bring all the different services together that will support us in our different lives is really important. I think telcos will do it, it's in their interest to do it. >> All right, guys, we got to wrap. Let's go around the horn here, starting with Chris, Zeus, and then Sarbjeet, just bring us home. Number one hot take from Mobile World Congress MWC23 day two. >> My favorite hot take is the willingness of all the participants who have been traditional telco players who looked inwardly at the industry looking outside for help for partnerships, and to build an ecosystem, a more open ecosystem, which will address our requirements. >> Zeus? >> Yeah, I was going to talk about ecosystem. I think for the first time ever, when I've met with the telcos here, I think they're actually, I don't think they know how to get there yet, but they're at least aware of the fact that they need to understand how to build a big ecosystem around them. So if you think back like 50 years ago, IBM and compute was the center of everything in your company, and then the ecosystem surrounded it. I think today with digital transformation being network centric, the telcos actually have the opportunity to be that center of excellence, and then build an ecosystem around them. I think the SIs are actually in a really interesting place to help them do that 'cause they understand everything top to bottom that I, you know, pre pandemic, I'm not sure the telcos were really understand. I think they understand it today, I'm just not sure they know how to get there. . >> Sarbjeet? >> I've seen the lot of RN demos and testing companies and I'm amazed by it. Everything is turning into software, almost everything. The parts which are not turned into software. I mean every, they will soon. But everybody says that we need the hardware to run something, right? But that hardware, in my view, is getting miniaturized, and it's becoming smaller and smaller. The antennas are becoming smaller. The equipment is getting smaller. That means the cost on the physicality of the assets is going down. But the cost on the software side will go up for telcos in future. And telco is a messy business. Not everybody can do it. So only few will survive, I believe. So that's what- >> Software defined telco. So I'm on a mission. I'm looking for the monetization path. And what I haven't seen yet is, you know, you want to follow the money, follow the data, I say. So next two days, I'm going to be looking for that data play, that potential, the way in which this industry is going to break down the data silos I think there's potential goldmine there, but I haven't figured out yet. >> That's a subject for another day. >> Guys, thanks so much for coming on. You guys are extraordinary partners of theCUBE friends, and great analysts and congratulations and thank you for all you do. Really appreciate it. >> Analyst: Thank you. >> Thanks a lot. >> All right, this is a wrap on day two MWC 23. Go to siliconangle.com for all the news. Where Rob Hope and team are just covering all the news. John Furrier is in the Palo Alto studio. We're rocking all that news, taking all that news and putting it on video. Go to theCUBE.net, you'll see everything on demand. Thanks for watching. This is a wrap on day two. We'll see you tomorrow. (soft music)

(bright upbeat melody) >> Hello everyone, welcome back to Supercloud2. I'm John Furrier, my co-host Dave Vellante, here at theCUBE in Palo Alto, California, for our live stage performance all day for Supercloud2. Unpacking this next generation movement in cloud computing. Dave, Supercloud1 was in August. We had great response and acceleration of that momentum. We had some haters too. We had some folks out there throwing shade on this. But at the same time, a lot of leaders came out of the woodwork, a lot of practitioners. And this Supercloud2 event I think will expose and illustrate some of the examples of what's happening in the industry and more importantly, kind of where it's going. >> Well it's great to be back in our studios in Palo Alto, John. Seems like just yesterday was August 9th, where the community was really refining the definition of Super Cloud. We were identifying the essential characteristics, with some of the leading technologists in Silicon Valley. We were digging into the deployment models. Whereas this Supercloud, Supercloud2 is really taking a practitioner view. We're going to hear from Walmart today. They've built a Supercloud. They called it the Walmart Cloud native platform. We're going to hear from other data practitioners, like Saks. We're going to hear from Western Union. They've got 200 locations around the world, how they're dealing with data sovereignty. And of course we've got some local technologists and practitioners coming in, analysts, consultants, theCUBE community. I'm really excited to be here. >> And we've got some great keynotes from executives at VMware. We're going to expose some of the things that they're working on around cross cloud services, which leads into multicloud. I think the practitioner angle highlights my favorite part of this program, 'cause you're starting to see the builders, a term coined by Andy Jassy, early days of AWS. That builder movement has been continuing to go. And you're seeing the enterprise, global enterprises adopt this builder mentality with Cloud Native. This is going to power the next generation global economy. And I think the role of the cloud computing vendors like AWS, Azure, Google, Alibaba are going to be the source engine of innovation. And what gets built on top of and with the clouds will be a big significant market value for all businesses and their business models. So I think the market wants the supercloud, the business models are pointing to Supercloud. The technology needs supercloud. And society, from an economic standpoint and from a use case standpoint, needs supercloud. You're seeing it today. Everyone's talking about chat GPT. This is an example of what will come out of this next generation and it's just getting started. So to me, you're either on the supercloud side of the camp or you're on the old school, hugging onto the old school mentality of wait a minute, that's cloud computing. So I think if you're not on the super cloud wave, you're going to be driftwood. And that's a term coined by Pat Gelsinger. And this is really the reality. Are you on the super cloud side? Or are you on the old huggin' the old model? And that's going to be a determinant. And you're going to see who's going to be the players on that, Dave. This is going to be a real big year. >> Everybody's heard the phrase follow the money. Well, my philosophy is follow the data. And that's a big part of what Supercloud2 is, because the data is where the money is across the clouds. And people want more simplicity, or greater simplicity across the clouds. So it's really, there's two forces here. You've got the ecosystem that's saying, hey the hyperscalers, they've done a great job but there's problems that they're not solving. So we're going to lean in and solve those problems. At the same time, you have the practitioners saying we have multicloud, we have to deal with this, help us. It's got to be simpler. Because we want to share data across clouds. We want to build data products, we want to monetize and drive revenue and cut costs. >> This is the key thing. The builder movement is hitting a wall, and that wall will be broken down because the business models of the companies themselves are demanding that the value from the data with security has to be embedded. So I think you're going to see a big year this next year or so where the builders will accelerate through this next generation, supercloud wave, will be a builder's wave for business. And I think that's going to be the nuance here. And all the people that are on the side of Supercloud are all pro-business, pro-technology. The ones that aren't are like, wait a minute I used to do things differently. They're stuck. And so I think this is going to be a question of are we stuck? Are builders accelerating? Will the business models develop around it? That's digital transformation. At the end of the day, the market's speaking, Dave. The market wants more. Chat GPT, you're seeing AI starting to flourish, powered by data. It's unstoppable, supercloud's unstoppable. >> One of our headliners today is Zhamak Dehghani, the creator of Data Mesh. We've got some news around her. She's going to be live in studio. Super excited about that. Kit Colbert in Supercloud, the first Supercloud in last August, laid out an initial architecture for Supercloud. He's going to advance that today, tell us what's changed, and really dig into and really talk about the meat on the bone, if you will. And we've got some other technologists that are coming in saying, Hey, is it a platform? Is it an architecture? What's the right model here? So we're going to debate that a little bit today. >> And before we close, I'll just say look at the guests, look at the talk tracks. You're seeing a diversity of startups doing cloud networking, you're seeing big practitioners building their own thing, being builders for business value and business model advantages. And you got companies like VMware, who have been on the wave of virtualization. So the, everyone who's involved in super cloud, they're seeing it, they're on the front lines. They're seeing the trend. They are riding that wave. And they have, they're bringing data to the table. So to me, you look at who's involved and you judge it that way. To me, that's the way I look at this. And because we're making it open, Supercloud is going to continue to be debated. But more importantly, the results are going to come in. The market supports it, the business needs it, tech's there, and will it happen? So I think the builders movement, Dave, is going to be big to watch. And then ultimately how that business transformation kicks in, and I think those are the two variables that I would watch on Supercloud. >> Our mission has always been around free content, giving back to the community. So I really want to thank our sponsors today. We've had a great partnership with VMware, who's not only contributed some financial support, but also great content. Alkira, ChaosSearch, prosimo, all phenomenal, allowing us to achieve our mission of serving our audiences and really trying to give more than we take from. >> Free content, that's our mission. Dave, great to kick it off. Kickin' off Supercloud2 all day, we've got some great programs here. We've got VMware coming up next. We have Victoria Viering, who's been on before. He's got a great vision for cross cloud service. We're getting also a keynote with Kit Colbert, who's going to lay out the fragmentation and the benefits that that solves, from solvent fragmentation and silos, breaking down the silos and bringing multicloud future to the table via Super Cloud. So stay with us. We'll be right back after this short break. (bright upbeat music) (music fades)

(upbeat jingle) >> Cameraman: Just look, Mike. >> Good afternoon everyone, and welcome back to Supercomputing. We're live here with theCUBE in Dallas. I'm joined by my cohost, David. Wonderful to be sharing the afternoon with you. And we are going to be kicking things off with a very thrilling discussion from two important thought leaders at Dell. Bhavesh and Shreya, thank you so much for being on the show. Welcome. How you doing? How does it feel to be at Supercomputing? >> Pretty good. We really enjoying the show and enjoying a lot of customer conversations ongoing. >> Yeah. Are most of your customers here? >> Yes. Most of the customers are, mostly in the Hyatt over there and a lot of discussions ongoing. >> Yeah. Must be nice to see everybody show off. Are you enjoying the show so far, Shreya? >> Yeah, I missed this for two years and so it's nice to be back and meeting people in person. >> Yeah, definitely. We all missed it. So, it's been a very exciting week for Dell. Do you want to talk about what you're most excited about in the announcement portfolio that we saw yesterday? >> Absolutely. >> Go for it, Shreya. >> Yeah, so, you know, before we get into the portfolio side of the house, you know, we really wanted to, kind of, share our thoughts, in terms of, you know, what is it that's, kind of, moving HPC and supercomputing, you know, for a long time- >> Stock trends >> For a long time HPC and supercomputing has been driven by packing the racks, you know, maximizing the performance. And as the work that Bhavesh and I have been doing over the last, you know, couple of generations, we're seeing an emerging trend and that is the thermal dissipated power is actually exploding. And so the idea of packing the racks is now turning into, how do you maximize your performance, but are able to deliver the infrastructure in that limited kilowatts per rack that you have in your data center. >> So I, it's been interesting walking around the show seeing how many businesses associated with cooling- >> Savannah: So many. >> are here. And it's funny to see, they open up the cabinet, and it's almost 19th-century-looking technology. It's pipes and pumps and- >> Savannah: And very industrial-like. >> Yeah, very, very industrial-looking. Yeah, and I think, so that's where the, the trends are more in the power and cooling. That is what everybody is trying to solve from an industry perspective. And what we did when we looked at our portfolio, what we want to bring up in this timeframe for targeting more the HPC and AI space. There are a couple of vectors we had to look at. We had to look at cooling, we had to look at power where the trends are happening. We had to look at, what are the data center needs showing up, be it in the cooler space, be it in the HPC space, be it in the large install happening out there. So, looking at those trends and then factoring in, how do you build a node out? We said, okay, we need to diversify and build out an infrastructure. And that's what me and Shreya looked into, not only looking at the silicon diversity showing up, but more looking at, okay, there is this power, there is this cooling, there is silicon diversity. Now, how do you start packing it up and bringing it to the marketplace? So, kind of, those are some of the trends that we captured. And that's what you see, kind of, in the exhibit floor today, even. >> And Dell technology supports both, liquid cooling, air cooling. Do you have a preference? Is it more just a customer-based? >> It is going to be, and Shreya can allude to it, it's more workload and application-focused. That is what we want to be thinking about. And it's not going to be siloed into, okay, is we going to be just targeting air-cooling, we wanted to target a breadth between air to liquid. And that's how we built into our portfolio when we looked at our GPUs. >> To add to that, if we look at our customer landscape, we see that there's a peak between 35 to 45 kilowatts per rack. We see another peak at 60, we see another peak at 80, and we've got selects, you know, very specialized customers above hundred kilowatts per rack. And so, if we take that 35 to 45 kilowatts per rack, you know, you can pack maybe three or four of these chassis, right? And so, to what Bhavesh is saying, we're really trying to provide the flexibility for what our customers can deliver in their data centers. Whether it be at the 35 end where air cooling may make complete sense. As you get above 45 and above, maybe that's the time to pivot to a liquid-cool solution. >> So, you said that there, so there are situations where you could have 90 kilowatts being consumed by a rack of equipment. So, I live in California where we are very, very closely attuned to things like the price for a kilowatt hour of electricity. >> Seriously. >> And I'm kind of an electric car nerd, so, for the folks who really aren't as attuned, 90 kilowatts, that's like over a hundred horsepower. So, think about a hundred horsepower worth of energy being used for compute in one of these racks. It's insane. So, we, you can kind of imagine a layperson can kind of imagine the variables that go into this equation of, you know, how do we, how do we bring the power and get the maximum bang for, per kilowatt hour. But, are there any, are there any kind of interesting odd twists in your equations that you find when you're trying to figure out. Do you have a- >> Yeah, and we, a lot of these trends when we look at it, okay, it's not, we think about it more from a power density that we want to try to go and solve. We are mindful about all the, from an energy perspective where the energy prices are moving. So, what we do is we try to be optimizing right at the node level and how we going to do our liquid-cooling and air cooled infrastructure. So, it's trying to, how do you keep a balance with it? That's what we are thinking about. And thinking about it is not just delivering or consuming the power that is maybe not needed for that particular node itself. So, that's what we are thinking about. The other way we optimize when we built this infrastructure out is we are thinking about, okay, how are we go going to deliver it at the rack level and more keeping in mind as to how this liquid-cooling plumbing will happen. Where is it coming into the data center? Is it coming in the bottom of the floor? Are we going to do it on the left hand side of your rack or the right hand side? It's a big thing. It's like it becomes, okay, yeah, it doesn't matter which side you put it on, but there is a piece of it going into our decision as to how we are going to build that, no doubt. So, there are multiple factors coming in and besides the power and cooling, which we all touched upon, But, Shreya and me also look at is where this whole GPU and accelerators are moving into. So, we're not just looking at the current set of GPUs and where they're moving from a power perspective. We are looking at this whole silicon diversity that is happening out there. So, we've been looking at multiple accelerators. There are multiple companies out there and we can tell you there'll be over three 30 to 50 silicon companies out there that we are actively engaged and looking into. So, our decision in building this particular portfolio out was being mindful about what the maturity curve is from a software point of view. From a hardware point of view and what can we deliver, what the customer really needs in it, yeah. >> It's a balancing act, yeah. >> Bhavesh: It is a balancing act. >> Let's, let's stay in that zone a little bit. What other trends, Shreya, let's go to you on this one. What other trends are you seeing in the acceleration landscape? >> Yeah, I think you know, to your point, the balancing act is actually a very interesting paradigm. One of the things that Bhavesh and I constantly think about, and we call it the Goldilocks syndrome, which is, you know, at that 90 and and a hundred, right? Density matters. >> Savannah: A lot. >> But, what we've done is we have really figured out what that optimal point is, 'cause we don't want to be the thinnest most possible. You lose a lot of power redundancy, you lose a lot of I/O capability, you lose a lot of storage capability. And so, from our portfolio perspective, we've really tried to think about the Goldilocks syndrome and where that sweet spot is. >> I love that. I love the thought of you all just standing around server racks, having a little bit of porridge and determining >> the porridge. Exactly the thickness that you want in terms of the density trade off there. Yeah, that's, I love that, though. I mean it's very digestible. Are you seeing anything else? >> No, I think that's pretty much, Shreya summed it up and we think about what we are thinking about, where the technology features are moving and what we are thinking, in terms of our portfolio, so it is, yeah. >> So, just a lesson, you know, Shreya, a lesson for us, a rudimentary lesson. You put power into a CPU or a GPU and you're getting something out and a lot of what we get out is heat. Is there a measure, is there an objective measure of efficiency in these devices that we look at? Because you could think of a 100 watt light bulb, an incandescent light bulb is going to give out a certain amount of light and a certain amount of heat. A 100 watt equivalent led, in terms of the lumens that it's putting out, in terms of light, a lot more light for the power going in, a lot less heat. We have led lights around us, thankfully, instead of incandescent lights. >> Savannah: Otherwise we would be melting. >> But, what is, when you put power into a CPU or a GPU, how do you measure that efficiency? 'Cause it's sort of funny, 'cause it's like, it's not moving, so it's not like measuring, putting power into a vehicle and measuring forward motion and heat. You're measuring this, sort of, esoteric thing, this processing thing that you can't see or touch. But, I mean, how much per watt of power, how do you, how do you measure it I guess? Help us out, from the base up understanding, 'cause people generally, most people have never been in a data center before. Maybe they've put their hand behind the fan in a personal computer or they've had a laptop feel warm on their lap. But, we're talking about massive amounts of heat being generated. Can you, kind of, explain the fundamentals of that? >> So, the way we think about it is, you know, there's a performance per dollar metric. There's a performance per dollar per watt metric and that's where the power kind of comes in. But, on the flip side, we have something called PUE, power utilization efficiency from a data center aspect. And so, we try to marry up those concepts together and really try to find that sweet spot. >> Is there anything in the way of harvesting that heat to do other worthwhile work, I mean? >> Yes. >> You know, it's like, hey, everybody that works in the data center, you all have your own personal shower now, water heated. >> Recirculating, too. >> Courtesy of Intel AMD. >> Or a heated swimming pool. >> Right, a heated swimming pool. >> I like the pool. >> So, that's the circulation of, or recycling of that thermal heat that you're talking about, absolutely. And we see that our customers in the, you know, in the Europe region, actually a lot more advanced in terms of taking that power and doing something that's valuable with it, right? >> Cooking croissant and, and making lattes, probably right? >> (laughing) Or heating your home. >> Makes me want to go on >> vacation, a pool, croissants. >> That would be a good use. But, do you, it's more on the PUE aspect of it. It's more thinking about how are we more energy efficient in our design, even, so we are more thinking about what's the best efficiency we can get, but what's the amount of heat capture we can get? Are we just kind of wasting any heat out there? So, that's always the goal when designing these particular platforms, so that's something that we had kept in mind with a lot of our power and cooling experts within Dell. When thinking about, okay, is it, how much can we get, can we capture? If we are not capturing anything, then what are we, kind of, recirculating it back in order to get much better efficiency when we think about it at a rack level and for the other equipment which is going to be purely air-cooled out there and what can we do about it, so. >> Do you think both of these technologies are going to continue to work in tandem, air cooling and liquid cooling? Yeah, so we're not going to see- >> Yeah, we don't, kind of, when we think about our portfolio and what we see the trends moving in the future, I think so, air-cooling is definitely going to be there. There'll be a huge amount of usage for customers looking into air-cooling. Air-cooling is not going to go away. Liquid-cooling is definitely something that a lot of customers are looking into adopting. PUE become the bigger factor for it. How much can I heat capture with it? That's a bigger equation that is coming into the picture. And that's where we said, okay, we have a transition happening. And that's what you see in our portfolio now. >> Yeah, Intel is, Intel, excuse me, Dell is agnostic when it comes to things like Intel, AMD, Broadcom, Nvidia. So, you can look at this landscape and I think make a, you know, make a fair judgment. When we talk about GPU versus CPU, in terms of efficiency, do you see that as something that will live on into the future for some applications? Meaning look, GPU is the answer or is it simply a question of leveraging what we think of as CPU cores differently? Is this going to be, is this going to ebb and flow back and forth? Shreya, are things going to change? 'Cause right now, a lot of what's announced recently, in the high performance computer area, leverages GPUs. But, we're right in the season of AMD and Intel coming out with NextGen processor architectures. >> Savannah: Great point. >> Shreya: Yeah >> Any thoughts? >> Yeah, so what I'll tell you is that it is all application dependent. If you rewind, you know, a couple of generations you'll see that the journey for GPU just started, right? And so there is an ROI, a minimum threshold ROI that customers have to realize in order to move their workloads from CPU-based to GPU-based. As the technology evolves and matures, you'll have more and more applications that will fit within that bucket. Does that mean that everything will fit in that bucket? I don't believe so, but as, you know, the technology will continue to mature on the CPU side, but also on the GPU side. And so, depending on where the customer is in their journey, it's the same for air versus liquid. Liquid is not an if, but it's a when. And when the environment, the data center environment is ready to support that, and when you have that ROI that goes with it is when it makes sense to transition to one way or the other. >> That's awesome. All right, last question for you both in a succinct phrase, if possible, I won't character count. What do you hope that we get to talk about next year when we have you back on theCUBE? Shreya, we'll start with you. >> Ooh, that's a good one. I'm going to let Bhavesh go first. >> Savannah: Go for it. >> (laughs) >> What do you think, Bhavesh? Next year, I think so, what you'll see more, because I'm in the CTI group, more talking about where cache coherency is moving. So, that's what, I'll just leave it at that and we'll talk about it more. >> Savannah: All right. >> Dave: Tantalizing. >> I was going to say, a little window in there, yeah. And I think, to kind of add to that, I'm excited to see what the future holds with CPUs, GPUs, smart NICs and the integration of these technologies and where that all is headed and how that helps ultimately, you know, our customers being able to solve these really, really large and complex problems. >> The problems our globe faces. Wow, well it was absolutely fantastic to have you both on the show. Time just flew. David, wonderful questions, as always. Thank you all for tuning in to theCUBE. Here live from Dallas where we are broadcasting all about supercomputing, high-performance computing, and everything that a hardware nerd, like I, loves. My name is Savannah Peterson. We'll see you again soon. (upbeat jingle)

>>Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions and they were largely confined to regulatory regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become and the value proposition for data quality and trust. It evolved from primarily a compliance driven issue to becoming a lynchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. >>And it resulted in a lot of frustration with data initiatives for most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today for example, this quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like data mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business Uni users, you hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that, but also how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. >>In other words, while it's enticing to experiment and run fast and loose with data initiatives kinda like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated. And intelligence governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is gonna use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. >>Hello and welcome to the Cube's coverage of Data Citizens made possible by Calibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Ante and I'm one of the hosts of our program, which is running in parallel to data citizens. Now at the Cube we like to say we extract the signal from the noise, and over the, the next couple of days, we're gonna feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives. Felix Von Dala, who is the co-founder and CEO of Collibra, will join us along with one of the other founders of Collibra, Stan Christians, who's gonna join my colleague Lisa Martin. I'm gonna also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the, the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Hasselbeck. >>He's the vice president of Data quality at Collibra. He's an amazingly smart dude who founded Owl dq, a company that he sold to Col to Collibra last year. Now many companies, they didn't make it through the Hado era, you know, they missed the industry waves and they became Driftwood. Collibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio, and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. >>Last year, the Cube Covered Data Citizens Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hado movement, we had data lakes, we'd spark the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of ai, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights for data, trust the data, and begin to use that data in new ways, fueling data, products, monetization and insights data citizens 2022 is back and we're pleased to have Felix Van Dema, who is the founder and CEO of Collibra. He's on the cube or excited to have you, Felix. Good to see you again. >>Likewise Dave. Thanks for having me again. >>You bet. All right, we're gonna get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Collibra has been up to over the past year and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >>Yeah, absolutely. And, and I think you said it well, Dave, and and the intro that that rising complexity and fragmentation in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kinda more, more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well, which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. >>So it's become much more acute. And, and to your earlier point, we do live in a different world and and the the past couple of years we could probably just kind of brute for it, right? We could focus on, on the top line. There was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are, are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, How do we truly get value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale it data, not just from a a technology and infrastructure perspective, but how do you actually scale data from an organizational perspective, right? You said at the the people and process, how do we do that at scale? And that's only, only only becoming much more important. And we do believe that the, the economic environment that we find ourselves in today is gonna be catalyst for organizations to really dig out more seriously if, if, if, if you will, than they maybe have in the have in the best. >>You know, I don't know when you guys founded Collibra, if, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >>Yeah, absolutely. We, we started Colli in 2008. So in some sense and the, the last kind of financial crisis, and that was really the, the start of Colli where we found product market fit, working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis and kind of here we are again in a very different environment, of course 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we are still relatively early in that, in that journey. >>Well, that's interesting because, you know, in my observation it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your, your current momentum? >>Yeah, absolutely. Again, there's, there's a lot of tail organizations that are only maturing the data practices and we've seen it kind of transform or, or, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in, in the, in the markets with some of the cloud partners like Google, Amazon, Snowflake, data bricks and, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners and of course our customers to help them kind of transition to the cloud even faster. >>And so we see a lot of excitement and momentum there within an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging ai, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architecture arch architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical so that they're really excited about about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believe. Then federated focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations. And so that aligns really well with our vision and, and from a product perspective, we've seen a lot of momentum with our customers there as well. >>Yeah, you know, a couple things there. I mean, the acquisition of i l dq, you know, Kirk Hasselbeck and, and their team, it's interesting, you know, the whole data quality used to be this back office function and, and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh. You mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the, the products. We're gonna go deeper in into products later on at, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the, the the under the covers in security, sort of making data more accessible for people just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >>Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission, either customers are still start, are just starting on that, on that journey. We wanna make it as easy as possible for the, for our organization to actually get started because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to, to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving. >>A lot of kind of ease of adoption, ease of use, but also then how do we make sure that lio becomes this kind of mission critical enterprise platform from a security performance architecture scale supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme from an innovation perspective, From a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction, how to make it easy. How do we make, how do we make available to true kind of shopping experience that anybody in your organization can, in a very easy search first way, find the right data product, find the right dataset, that data can then consume usage analytics. How do you, how do we help organizations drive adoption, tell them where they're working really well and where they have opportunities homepages again to, to make things easy for, for people, for anyone in your organization to kind of get started with ppia, you mentioned workflow designer, again, we have a very powerful enterprise platform. >>One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around K Bear Protect, which in partnership with Snowflake, which has been a strategic investor in kib, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as much more effective, effective rate, really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. >>So we launch more data quality cloud product as well as making use of those, those native compute capabilities in platforms like Snowflake, Data, Bricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down. So actually pushing down the computer and data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is gonna make a massive difference. And then more broadly, we, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So there's a lot coming out. The, the team has been work at work really hard and we are really, really excited about what we are coming, what we're bringing to markets. >>Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard. So how do you see sort of the future and, you know, give us the, your closing thoughts please? >>Yeah, absolutely. And I, and I think we we're really at this pivotal moment, and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can. It's kind of, of our, it's our mission. And so I'm really, really excited to see what we, what we are gonna, how the marks gonna evolve over the next, next few quarters and years. I think the trend is clearly there when we talk about data mesh, this kind of federated approach folks on data products is just another signal that we believe that a lot of our organization are now at the time. >>The understanding need to go beyond just the technology. I really, really think about how do we actually scale data as a business function, just like we've done with it, with, with hr, with, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in much more focus on control, much more focused on productivity efficiency and now's the time. We need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >>Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much and good luck in, in San Diego. I know you're gonna crush it out there. >>Thank you Dave. >>Yeah, it's a great spot for an in-person event and, and of course the content post event is gonna be available@collibra.com and you can of course catch the cube coverage@thecube.net and all the news@siliconangle.com. This is Dave Valante for the cube, your leader in enterprise and emerging tech coverage. >>Hi, I'm Jay from Collibra's Data Office. Today I want to talk to you about Collibra's data intelligence cloud. We often say Collibra is a single system of engagement for all of your data. Now, when I say data, I mean data in the broadest sense of the word, including reference and metadata. Think of metrics, reports, APIs, systems, policies, and even business processes that produce or consume data. Now, the beauty of this platform is that it ensures all of your users have an easy way to find, understand, trust, and access data. But how do you get started? Well, here are seven steps to help you get going. One, start with the data. What's data intelligence? Without data leverage the Collibra data catalog to automatically profile and classify your enterprise data wherever that data lives, databases, data lakes or data warehouses, whether on the cloud or on premise. >>Two, you'll then wanna organize the data and you'll do that with data communities. This can be by department, find a business or functional team, however your organization organizes work and accountability. And for that you'll establish community owners, communities, make it easy for people to navigate through the platform, find the data and will help create a sense of belonging for users. An important and related side note here, we find it's typical in many organizations that data is thought of is just an asset and IT and data offices are viewed as the owners of it and who are really the central teams performing analytics as a service provider to the enterprise. We believe data is more than an asset, it's a true product that can be converted to value. And that also means establishing business ownership of data where that strategy and ROI come together with subject matter expertise. >>Okay, three. Next, back to those communities there, the data owners should explain and define their data, not just the tables and columns, but also the related business terms, metrics and KPIs. These objects we call these assets are typically organized into business glossaries and data dictionaries. I definitely recommend starting with the topics that are most important to the business. Four, those steps that enable you and your users to have some fun with it. Linking everything together builds your knowledge graph and also known as a metadata graph by linking or relating these assets together. For example, a data set to a KPI to a report now enables your users to see what we call the lineage diagram that visualizes where the data in your dashboards actually came from and what the data means and who's responsible for it. Speaking of which, here's five. Leverage the calibra trusted business reporting solution on the marketplace, which comes with workflows for those owners to certify their reports, KPIs, and data sets. >>This helps them force their trust in their data. Six, easy to navigate dashboards or landing pages right in your platform for your company's business processes are the most effective way for everyone to better understand and take action on data. Here's a pro tip, use the dashboard design kit on the marketplace to help you build compelling dashboards. Finally, seven, promote the value of this to your users and be sure to schedule enablement office hours and new employee onboarding sessions to get folks excited about what you've built and implemented. Better yet, invite all of those community and data owners to these sessions so that they can show off the value that they've created. Those are my seven tips to get going with Collibra. I hope these have been useful. For more information, be sure to visit collibra.com. >>Welcome to the Cube's coverage of Data Citizens 2022 Collibra's customer event. My name is Dave Valante. With us is Kirk Hasselbeck, who's the vice president of Data Quality of Collibra Kirk, good to see you. Welcome. >>Thanks for having me, Dave. Excited to be here. >>You bet. Okay, we're gonna discuss data quality observability. It's a hot trend right now. You founded a data quality company, OWL dq, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >>Yeah, absolutely. It's, it's definitely exciting times for data quality, which you're right, has been around for a long time. So why now and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And, and while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as, as to why this is becoming so important now. And, and I guess you could kind of break this down simply and think about if Dave, you and I were gonna build, you know, a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, you know, what the ramifications could be, what, what those incidents would look like, or maybe better yet, we try to build a, a new trading algorithm with a crossover strategy where the 50 day crosses the, the 10 day average. >>And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, you know, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. You know, I, I bought a car not too long ago and my dad called and said, How many cylinders does it have? And I realized in that moment, you know, I might have failed him because, cause I didn't know. And, and I used to ask those types of questions about any lock brakes and cylinders and, and you know, if it's manual or, or automatic and, and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips, I, I really don't know that much about it. >>And, and that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the, the individuals loading and consuming all of this data for the company actually may not know that much about the data itself, and that's not even their job anymore. So we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >>You know, the other thing too about data quality, and for years we did the MIT CDO IQ event, we didn't do it last year, Covid messed everything up. But the observation I would make there thoughts is, is it data quality? Used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a, a risk to data as a, as an asset. And now as we say, we're gonna talk about observability. And so it's really become front and center just the whole quality issue because data's so fundamental, hasn't it? >>Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my, my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And, and that's kind of what's going on. There's, there's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before calibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is, is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, you know, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's, it's not ever going to be based on one or two domain experts anymore. >>So, So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they, are they cousins? What's your perspective on that? >>Yeah, it's, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the, the lingo is constantly moving is, you know, as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens, it's wrong and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. You know, everybody's talking about fresh data and stale data and, and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good in the bads. That was kind of your, your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data, but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >>So what's the Collibra angle on all this stuff made the acquisition, you got data quality observability coming together, you guys have a lot of expertise in, in this area, but you hear providence of data, you just talked about, you know, stale data, you know, the, the whole trend toward real time. How is Calibra approaching the problem and what's unique about your approach? >>Well, I think where we're fortunate is with our background, myself and team, we sort of lived this problem for a long time, you know, in, in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the, the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution, it's more advanced than some of the observation techniques that that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights, and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong, just show me the big picture, help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows, you can actually achieve total data governance at this point with the acquisition of what was a Lineage company years ago, and then my company Ldq now Collibra, Data quality Collibra may be the best positioned for total data governance and intelligence in the space. >>Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, you know, they just said, Oh, it's a glitch, you know, so they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you gotta announce new products, right? You're yearly event what's, what's new. Give us a sense as to what products are coming out, but specifically around data quality and observability. >>Absolutely. There's this, you know, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks is Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook in to these databases. And while we've always worked with the the same databases in the past, they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did your, my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? >>And with these native integrations that we're building and about to unveil, here's kind of a sneak peek for, for next week at Data Citizens. We're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration, you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress, cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >>So this is interesting because what you just described, you know, you mentioned Snowflake, you mentioned Google, Oh actually you mentioned yeah, data bricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool, but then Google's got the open data cloud. If you heard, you know, Google next and now data bricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm, I'm hearing to, to really understand the relationships between all those and have confidence across, you know, it's like Jak Dani, you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And, and, and that's what you're bringing to the table, Is that right? Did I get that right? >>Yeah, that's right. And it's, for us, it's, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now, we can send them the, the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network costs, zero egress cost, zero latency of time. And so when you were to log into Big Query tomorrow using our tool or like, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there, just like all of the major brands that you mentioned, but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And, and we think that this positions us to be the leader there. >>I love this example because, you know, Barry talks about, wow, the cloud guys are gonna own the world and, and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. All right, Kirk, give us your, your final thoughts and on on the trends that we've talked about and Data Citizens 22. >>Absolutely. Well, I think, you know, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there, they wanna know where everything is, where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're gonna see more one click solutions, more SAS based solutions and solutions that hopefully prove faster time to value on, on all of these modern cloud platforms. >>Excellent. All right, Kurt Hasselbeck, thanks so much for coming on the Cube and previewing Data Citizens 22. Appreciate it. >>Thanks for having me, Dave. >>You're welcome. Right, and thank you for watching. Keep it right there for more coverage from the Cube. Welcome to the Cube's virtual Coverage of Data Citizens 2022. My name is Dave Valante and I'm here with Laura Sellers, who's the Chief Product Officer at Collibra, the host of Data Citizens. Laura, welcome. Good to see you. >>Thank you. Nice to be here. >>Yeah, your keynote at Data Citizens this year focused on, you know, your mission to drive ease of use and scale. Now when I think about historically fast access to the right data at the right time in a form that's really easily consumable, it's been kind of challenging, especially for business users. Can can you explain to our audience why this matters so much and what's actually different today in the data ecosystem to make this a reality? >>Yeah, definitely. So I think what we really need and what I hear from customers every single day is that we need a new approach to data management and our product teams. What inspired me to come to Calibra a little bit a over a year ago was really the fact that they're very focused on bringing trusted data to more users across more sources for more use cases. And so as we look at what we're announcing with these innovations of ease of use and scale, it's really about making teams more productive in getting started with and the ability to manage data across the entire organization. So we've been very focused on richer experiences, a broader ecosystem of partners, as well as a platform that delivers performance, scale and security that our users and teams need and demand. So as we look at, Oh, go ahead. >>I was gonna say, you know, when I look back at like the last 10 years, it was all about getting the technology to work and it was just so complicated. But, but please carry on. I'd love to hear more about this. >>Yeah, I, I really, you know, Collibra is a system of engagement for data and we really are working on bringing that entire system of engagement to life for everyone to leverage here and now. So what we're announcing from our ease of use side of the world is first our data marketplace. This is the ability for all users to discover and access data quickly and easily shop for it, if you will. The next thing that we're also introducing is the new homepage. It's really about the ability to drive adoption and have users find data more quickly. And then the two more areas of the ease of use side of the world is our world of usage analytics. And one of the big pushes and passions we have at Collibra is to help with this data driven culture that all companies are trying to create. And also helping with data literacy, with something like usage analytics, it's really about driving adoption of the CLE platform, understanding what's working, who's accessing it, what's not. And then finally we're also introducing what's called workflow designer. And we love our workflows at Libra, it's a big differentiator to be able to automate business processes. The designer is really about a way for more people to be able to create those workflows, collaborate on those workflow flows, as well as people to be able to easily interact with them. So a lot of exciting things when it comes to ease of use to make it easier for all users to find data. >>Y yes, there's definitely a lot to unpack there. I I, you know, you mentioned this idea of, of of, of shopping for the data. That's interesting to me. Why this analogy, metaphor or analogy, I always get those confused. I let's go with analogy. Why is it so important to data consumers? >>I think when you look at the world of data, and I talked about this system of engagement, it's really about making it more accessible to the masses. And what users are used to is a shopping experience like your Amazon, if you will. And so having a consumer grade experience where users can quickly go in and find the data, trust that data, understand where the data's coming from, and then be able to quickly access it, is the idea of being able to shop for it, just making it as simple as possible and really speeding the time to value for any of the business analysts, data analysts out there. >>Yeah, I think when you, you, you see a lot of discussion about rethinking data architectures, putting data in the hands of the users and business people, decentralized data and of course that's awesome. I love that. But of course then you have to have self-service infrastructure and you have to have governance. And those are really challenging. And I think so many organizations, they're facing adoption challenges, you know, when it comes to enabling teams generally, especially domain experts to adopt new data technologies, you know, like the, the tech comes fast and furious. You got all these open source projects and get really confusing. Of course it risks security, governance and all that good stuff. You got all this jargon. So where do you see, you know, the friction in adopting new data technologies? What's your point of view and how can organizations overcome these challenges? >>You're, you're dead on. There's so much technology and there's so much to stay on top of, which is part of the friction, right? It's just being able to stay ahead of, of and understand all the technologies that are coming. You also look at as there's so many more sources of data and people are migrating data to the cloud and they're migrating to new sources. Where the friction comes is really that ability to understand where the data came from, where it's moving to, and then also to be able to put the access controls on top of it. So people are only getting access to the data that they should be getting access to. So one of the other things we're announcing with, with all of the innovations that are coming is what we're doing around performance and scale. So with all of the data movement, with all of the data that's out there, the first thing we're launching in the world of performance and scale is our world of data quality. >>It's something that Collibra has been working on for the past year and a half, but we're launching the ability to have data quality in the cloud. So it's currently an on-premise offering, but we'll now be able to carry that over into the cloud for us to manage that way. We're also introducing the ability to push down data quality into Snowflake. So this is, again, one of those challenges is making sure that that data that you have is d is is high quality as you move forward. And so really another, we're just reducing friction. You already have Snowflake stood up. It's not another machine for you to manage, it's just push down capabilities into Snowflake to be able to track that quality. Another thing that we're launching with that is what we call Collibra Protect. And this is that ability for users to be able to ingest metadata, understand where the PII data is, and then set policies up on top of it. So very quickly be able to set policies and have them enforced at the data level. So anybody in the organization is only getting access to the data they should have access to. >>Here's Topica data quality is interesting. It's something that I've followed for a number of years. It used to be a back office function, you know, and really confined only to highly regulated industries like financial services and healthcare and government. You know, you look back over a decade ago, you didn't have this worry about personal information, g gdpr, and, you know, California Consumer Privacy Act all becomes, becomes so much important. The cloud is really changed things in terms of performance and scale and of course partnering for, for, with Snowflake it's all about sharing data and monetization, anything but a back office function. So it was kind of smart that you guys were early on and of course attracting them and as a, as an investor as well was very strong validation. What can you tell us about the nature of the relationship with Snowflake and specifically inter interested in sort of joint engineering or, and product innovation efforts, you know, beyond the standard go to market stuff? >>Definitely. So you mentioned there were a strategic investor in Calibra about a year ago. A little less than that I guess. We've been working with them though for over a year really tightly with their product and engineering teams to make sure that Collibra is adding real value. Our unified platform is touching pieces of our unified platform or touching all pieces of Snowflake. And when I say that, what I mean is we're first, you know, able to ingest data with Snowflake, which, which has always existed. We're able to profile and classify that data we're announcing with Calibra Protect this week that you're now able to create those policies on top of Snowflake and have them enforce. So again, people can get more value out of their snowflake more quickly as far as time to value with, with our policies for all business users to be able to create. >>We're also announcing Snowflake Lineage 2.0. So this is the ability to take stored procedures in Snowflake and understand the lineage of where did the data come from, how was it transformed with within Snowflake as well as the data quality. Pushdown, as I mentioned, data quality, you brought it up. It is a new, it is a, a big industry push and you know, one of the things I think Gartner mentioned is people are losing up to $15 million without having great data quality. So this push down capability for Snowflake really is again, a big ease of use push for us at Collibra of that ability to, to push it into snowflake, take advantage of the data, the data source, and the engine that already lives there and get the right and make sure you have the right quality. >>I mean, the nice thing about Snowflake, if you play in the Snowflake sandbox, you, you, you, you can get sort of a, you know, high degree of confidence that the data sharing can be done in a safe way. Bringing, you know, Collibra into the, into the story allows me to have that data quality and, and that governance that I, that I need. You know, we've said many times on the cube that one of the notable differences in cloud this decade versus last decade, I mean ob there are obvious differences just in terms of scale and scope, but it's shaping up to be about the strength of the ecosystems. That's really a hallmark of these big cloud players. I mean they're, it's a key factor for innovating, accelerating product delivery, filling gaps in, in the hyperscale offerings cuz you got more stack, you know, mature stack capabilities and you know, it creates this flywheel momentum as we often say. But, so my question is, how do you work with the hyperscalers? Like whether it's AWS or Google, whomever, and what do you see as your role and what's the Collibra sweet spot? >>Yeah, definitely. So, you know, one of the things I mentioned early on is the broader ecosystem of partners is what it's all about. And so we have that strong partnership with Snowflake. We also are doing more with Google around, you know, GCP and kbra protect there, but also tighter data plex integration. So similar to what you've seen with our strategic moves around Snowflake and, and really covering the broad ecosystem of what Collibra can do on top of that data source. We're extending that to the world of Google as well and the world of data plex. We also have great partners in SI's Infosys is somebody we spoke with at the conference who's done a lot of great work with Levi's as they're really important to help people with their whole data strategy and driving that data driven culture and, and Collibra being the core of it. >>Hi Laura, we're gonna, we're gonna end it there, but I wonder if you could kind of put a bow on, you know, this year, the event your, your perspectives. So just give us your closing thoughts. >>Yeah, definitely. So I, I wanna say this is one of the biggest releases Collibra's ever had. Definitely the biggest one since I've been with the company a little over a year. We have all these great new product innovations coming to really drive the ease of use to make data more valuable for users everywhere and, and companies everywhere. And so it's all about everybody being able to easily find, understand, and trust and get access to that data going forward. >>Well congratulations on all the pro progress. It was great to have you on the cube first time I believe, and really appreciate you, you taking the time with us. >>Yes, thank you for your time. >>You're very welcome. Okay, you're watching the coverage of Data Citizens 2022 on the cube, your leader in enterprise and emerging tech coverage. >>So data modernization oftentimes means moving some of your storage and computer to the cloud where you get the benefit of scale and security and so on. But ultimately it doesn't take away the silos that you have. We have more locations, more tools and more processes with which we try to get value from this data. To do that at scale in an organization, people involved in this process, they have to understand each other. So you need to unite those people across those tools, processes, and systems with a shared language. When I say customer, do you understand the same thing as you hearing customer? Are we counting them in the same way so that shared language unites us and that gives the opportunity for the organization as a whole to get the maximum value out of their data assets and then they can democratize data so everyone can properly use that shared language to find, understand, and trust the data asset that's available. >>And that's where Collibra comes in. We provide a centralized system of engagement that works across all of those locations and combines all of those different user types across the whole business. At Collibra, we say United by data and that also means that we're united by data with our customers. So here is some data about some of our customers. There was the case of an online do it yourself platform who grew their revenue almost three times from a marketing campaign that provided the right product in the right hands of the right people. In other case that comes to mind is from a financial services organization who saved over 800 K every year because they were able to reuse the same data in different kinds of reports and before there was spread out over different tools and processes and silos, and now the platform brought them together so they realized, oh, we're actually using the same data, let's find a way to make this more efficient. And the last example that comes to mind is that of a large home loan, home mortgage, mortgage loan provider where they have a very complex landscape, a very complex architecture legacy in the cloud, et cetera. And they're using our software, they're using our platform to unite all the people and those processes and tools to get a common view of data to manage their compliance at scale. >>Hey everyone, I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizens. Stan, it's great to have you back on the cube. >>Hey Lisa, nice to be. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation. It also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow gonna to be a data citizen, right? So you need to make sure that these people are aware of it. You need that. People have skills and competencies to do with data what necessary and that's on, all right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in dashboard to actually make that decision and take that action. Right? >>And once you have that why to the organization, that's when you have a good data culture. Now that's continuous effort for most organizations because they're always moving, somehow they're hiring new people and it has to be continuous effort because we've seen that on the hand. Organizations continue challenged their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefit. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example, and we did an IDC study earlier this year, quite interesting. I can recommend anyone to it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, ok, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this re reasons you're trying to bring both of those together and the ones that get data intelligence right, are successful and competitive. That's, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, the organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, laptops, what have you, you're not using those, right? Or you know, you're delivering them throughout organization, but not enabling your colleagues to actually do something with that asset. Same thing as through with data today, right? If you're not properly using the data asset and competitors are, they're gonna to get more advantage. So as to how you get this done, establish this. There's angles to look at, Lisa. So one angle is obviously the leadership whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? So I'm just gonna summarize it as a data leader for a second. >>So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can leadership in the organization and also the business value. And that's important. Cause those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You, I really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like s then the in place to really start upgrading that culture inch by inch if you'll, >>Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Calibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speaks here, are very excited. You know, we have Barb from m MIT speaking about data monetization. We have Dilla at the last minute. So really exciting agen agenda. Can't wait to get back out there essentially. So over the years at, we've doing this since two and eight, so a good years and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, if you, so everybody's wearing all sorts of hat at time. But over the years I've run, you know, presales that sales partnerships, product cetera. And as our company got a little bit biggish, we're now thousand two. Something like people in the company. >>I believe systems and processes become a lot important. So we said you CBRA isn't the size our customers we're getting there in of organization structure, process systems, et cetera. So we said it's really time for us to put our money where is and to our own data office, which is what we were seeing customers', organizations worldwide. And they organizations have HR units, they have a finance unit and over time they'll all have a department if you'll, that is responsible somehow for the data. So we said, ok, let's try to set an examples that other people can take away with it, right? Can take away from it. So we set up a data strategy, we started building data products, took care of the data infrastructure. That's sort of good stuff. And in doing all of that, ISA exactly as you said, we said, okay, we need to also use our product and our own practices and from that use, learn how we can make the product better, learn how we make, can make the practice better and share that learning with all the, and on, on the Monday mornings, we sometimes refer to eating our dog foods on Friday evenings. >>We referred to that drinking our own champagne. I like it. So we, we had a, we had the driver to do this. You know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should, this is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders, if you'll or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products can run, the data can flow and you know, the quality can be checked. >>And then we have a data intelligence or data governance builders where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the CBRA approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a map and started execution use of the use case. And a important ones are very simple. We them with our, our customers as well, people talking about the cata, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and privacy. So they have their process registry and they can see how the data flows. >>So that's a starting place and that turns into a marketplace so that if new analysts and data citizens join kbra, they immediately have a place to go to, to look at, see, ok, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? So they can immediately get access data. And another one that we is around trusted business. We're seeing that since, you know, self-service BI allowed everyone to make beautiful dashboards, you know, pie, pie charts. I always, my pet pee is the pie chart because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted this reporting. So we know if a, the dashboard, a data product essentially is built, we not that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either, Right. And that silver browser, right? Absolutely >>Decay. >>Exactly. Yes, >>Absolutely. Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with to your organization, but there's a few that we use that might be of interest. Use those pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Are the, is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data sciences and products. Are people using them? Are they getting value from it? >>Can we calculate that value in ay perspective, right? Yeah. So that we can to the rest of the business continue to say we're tracking all those numbers and those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or, or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so and so forth. So these are an set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in thousand 10 there may have been like 10 achieve data officers or something. Gartner has exact numbers on them, but then they grew, you know, industries and the number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data. So you'll see over the years that's gonna evolve more digital and more data products. So for next years, my, my prediction is it's all products because it's an immediate link between data and, and the essentially, right? Right. So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. I think there's gonna be a continued challenge for the chief officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? >>So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful and the ones who get that will the ones that do it on the basis of data monetization, right? Connecting value to the data and making that value clear to all the data citizens in the organization, right? And in that sense, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an asset. >>Absolutely. Because there's so much value that can be extracted. Organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful and being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the cube at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage. >>Okay, this concludes our coverage of Data Citizens 2022, brought to you by Collibra. Remember, all these videos are available on demand@thecube.net. And don't forget to check out silicon angle.com for all the news and wiki bod.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on the Cube, your leader in enterprise and emerging tech coverage. We'll see you soon.

>>Hi everyone. Welcome to the Cube special presentation here in Palo Alto, California. I'm John Foer, host of the Cube. We've got two great guests, one for calling in from Germany, our videoing in from Germany, one from Maryland. We've got VMware and aws. This is the customer successes with VMware cloud on AWS showcase, accelerating business transformation here in the showcase with Samir Candu Worldwide. VMware strategic alliance solution, architect leader with AWS Samir. Great to have you and Daniel Re Myer, principal architect global AWS synergy at VMware. Guys, you guys are, are working together. You're the key players in the re relationship as it rolls out and continues to grow. So welcome to the cube. >>Thank you. Greatly appreciate it. >>Great to have you guys both on, As you know, we've been covering this since 2016 when Pat Geling, then CEO and then then CEO AWS at Andy Chasy did this. It kind of got people by surprise, but it really kind of cleaned out the positioning in the enterprise for the success. OFM workloads in the cloud. VMware's had great success with it since, and you guys have the great partnerships. So this has been like a really strategic, successful partnership. Where are we right now? You know, years later we got this whole inflection point coming. You're starting to see, you know, this idea of higher level services, more performance are coming in at the infrastructure side. More automation, more serverless, I mean, and a, I mean it's just getting better and better every year in the cloud. Kinda a whole nother level. Where are we, Samir? Let's start with you on, on the relationship. >>Yeah, totally. So I mean, there's several things to keep in mind, right? So in 2016, right, that's when the partnership between AWS and VMware was announced, and then less than a year later, that's when we officially launched VMware cloud on aws. Years later, we've been driving innovation, working with our customers, jointly engineering this between AWS and VMware day in, day out. As far as advancing VMware cloud on aws. You know, even if you look at the innovation that takes place with a solution, things have modernized, things have changed, there's been advancements, you know, whether it's security focus, whether it's platform focus, whether it's networking focus, there's been modifications along the way, even storage, right? More recently, one of the things to keep in mind is we're looking to deliver value to our customers together. These are our joint customers. So there's hundreds of VMware and AWS engineers working together on this solution. >>And then factor in even our sales teams, right? We have VMware and AWS sales teams interacting with each other on a constant daily basis. We're working together with our customers at the end of the day too. Then we're looking to even offer and develop jointly engineered solutions specific to VMware cloud on aws, and even with VMware's, other platforms as well. Then the other thing comes down to is where we have dedicated teams around this at both AWS and VMware. So even from solutions architects, even to our sales specialists, even to our account teams, even to specific engineering teams within the organizations, they all come together to drive this innovation forward with VMware cloud on AWS and the jointly engineered solution partnership as well. And then I think one of the key things to keep in mind comes down to we have nearly 600 channel partners that have achieved VMware cloud on AWS service competency. So think about it from the standpoint there's 300 certified or validated technology solutions, they're now available to our customers. So that's even innovation right off the top as well. >>Great stuff. Daniel, I wanna get to you in a second. Upon this principal architect position you have in your title, you're the global a synergy person. Synergy means bringing things together, making it work. Take us through the architecture, because we heard a lot of folks at VMware explore this year, formerly world, talking about how the, the workloads on it has been completely transforming into cloud and hybrid, right? This is where the action is. Where are you? Is your customers taking advantage of that new shift? You got AI ops, you got it. Ops changing a lot, you got a lot more automation edges right around the corner. This is like a complete transformation from where we were just five years ago. What's your thoughts on the >>Relationship? So at at, at first, I would like to emphasize that our collaboration is not just that we have dedicated teams to help our customers get the most and the best benefits out of VMware cloud on aws. We are also enabling US mutually. So AWS learns from us about the VMware technology, where VMware people learn about the AWS technology. We are also enabling our channel partners and we are working together on customer projects. So we have regular assembled globally and also virtually on Slack and the usual suspect tools working together and listening to customers, that's, that's very important. Asking our customers where are their needs? And we are driving the solution into the direction that our customers get the, the best benefits out of VMware cloud on aws. And over the time we, we really have involved the solution. As Samia mentioned, we just added additional storage solutions to VMware cloud on aws. We now have three different instance types that cover a broad range of, of workload. So for example, we just added the I four I host, which is ideally for workloads that require a lot of CPU power, such as you mentioned it, AI workloads. >>Yeah. So I wanna guess just specifically on the customer journey and their transformation. You know, we've been reporting on Silicon angle in the queue in the past couple weeks in a big way that the OPS teams are now the new devs, right? I mean that sounds OP a little bit weird, but operation IT operations is now part of the, a lot more data ops, security writing code composing, you know, with open source, a lot of great things are changing. Can you share specifically what customers are looking for when you say, as you guys come in and assess their needs, what are they doing? What are some of the things that they're doing with VMware on AWS specifically that's a little bit different? Can you share some of and highlights there? >>That, that's a great point because originally VMware and AWS came from very different directions when it comes to speaking people at customers. So for example, aws very developer focused, whereas VMware has a very great footprint in the IT ops area. And usually these are very different, very different teams, groups, different cultures, but it's, it's getting together. However, we always try to address the customers, right? There are customers that want to build up a new application from the scratch and build resiliency, availability, recoverability, scalability into the application. But there are still a lot of customers that say, well we don't have all of the skills to redevelop everything to refactor an application to make it highly available. So we want to have all of that as a service, recoverability as a service, scalability as a service. We want to have this from the infrastructure. That was one of the unique selling points for VMware on premise and now we are bringing this into the cloud. >>Samir, talk about your perspective. I wanna get your thoughts, and not to take a tangent, but we had covered the AWS remar of, actually it was Amazon res machine learning automation, robotics and space. It was really kinda the confluence of industrial IOT software physical. And so when you look at like the IT operations piece becoming more software, you're seeing things about automation, but the skill gap is huge. So you're seeing low code, no code automation, you know, Hey Alexa, deploy a Kubernetes cluster. Yeah, I mean, I mean that's coming, right? So we're seeing this kind of operating automation meets higher level services meets workloads. Can you unpack that and share your opinion on, on what you see there from an Amazon perspective and how it relates to this? >>Yeah, totally. Right. And you know, look at it from the point of view where we said this is a jointly engineered solution, but it's not migrating to one option or the other option, right? It's more or less together. So even with VMware cloud on aws, yes it is utilizing AWS infrastructure, but your environment is connected to that AWS VPC in your AWS account. So if you wanna leverage any of the native AWS services, so any of the 200 plus AWS services, you have that option to do so. So that's gonna give you that power to do certain things, such as, for example, like how you mentioned with iot, even with utilizing Alexa or if there's any other service that you wanna utilize, that's the joining point between both of the offerings. Right off the top though, with digital transformation, right? You, you have to think about where it's not just about the technology, right? There's also where you want to drive growth in the underlying technology. Even in your business leaders are looking to reinvent their business. They're looking to take different steps as far as pursuing a new strategy. Maybe it's a process, maybe it's with the people, the culture, like how you said before, where people are coming in from a different background, right? They may not be used to the cloud, they may not be used to AWS services, but now you have that capability to mesh them together. Okay. Then also, Oh, >>Go ahead, finish >>Your thought. No, no, I was gonna say, what it also comes down to is you need to think about the operating model too, where it is a shift, right? Especially for that VS four admin that's used to their on-premises at environment. Now with VMware cloud on aws, you have that ability to leverage a cloud, but the investment that you made and certain things as far as automation, even with monitoring, even with logging, yeah. You still have that methodology where you can utilize that in VMware cloud on AWS two. >>Danielle, I wanna get your thoughts on this because at at explore and, and, and after the event, now as we prep for Cuban and reinvent coming up the big AWS show, I had a couple conversations with a lot of the VMware customers and operators and it's like hundreds of thousands of, of, of, of users and millions of people talking about and and peaked on VM we're interested in v VMware. The common thread was one's one, one person said, I'm trying to figure out where I'm gonna put my career in the next 10 to 15 years. And they've been very comfortable with VMware in the past, very loyal, and they're kind of talking about, I'm gonna be the next cloud, but there's no like role yet architects, is it Solution architect sre. So you're starting to see the psychology of the operators who now are gonna try to make these career decisions, like how, what am I gonna work on? And it's, and that was kind of fuzzy, but I wanna get your thoughts. How would you talk to that persona about the future of VMware on, say, cloud for instance? What should they be thinking about? What's the opportunity and what's gonna happen? >>So digital transformation definitely is a huge change for many organizations and leaders are perfectly aware of what that means. And that also means in, in to to some extent, concerns with your existing employees. Concerns about do I have to relearn everything? Do I have to acquire new skills? And, and trainings is everything worthless I learned over the last 15 years of my career? And the, the answer is to make digital transformation a success. We need not just to talk about technology, but also about process people and culture. And this is where VMware really can help because if you are applying VMware cloud on a, on AWS to your infrastructure, to your existing on-premise infrastructure, you do not need to change many things. You can use the same tools and skills, you can manage your virtual machines as you did in your on-premise environment. You can use the same managing and monitoring tools. If you have written, and many customers did this, if you have developed hundreds of, of scripts that automate tasks and if you know how to troubleshoot things, then you can use all of that in VMware cloud on aws. And that gives not just leaders, but but also the architects at customers, the operators at customers, the confidence in, in such a complex project, >>The consistency, very key point, gives them the confidence to go and, and then now that once they're confident they can start committing themselves to new things. Samir, you're reacting to this because you know, on your side you've got higher level services, you got more performance at the hardware level. I mean, lot improvement. So, okay, nothing's changed. I can still run my job now I got goodness on the other side. What's the upside? What's in it for the, for the, for the customer there? >>Yeah, so I think what it comes down to is they've already been so used to or entrenched with that VMware admin mentality, right? But now extending that to the cloud, that's where now you have that bridge between VMware cloud on AWS to bridge that VMware knowledge with that AWS knowledge. So I will look at it from the point of view where now one has that capability and that ability to just learn about the cloud, but if they're comfortable with certain aspects, no one's saying you have to change anything. You can still leverage that, right? But now if you wanna utilize any other AWS service in conjunction with that VM that resides maybe on premises or even in VMware cloud on aws, you have that option to do so. So think about it where you have that ability to be someone who's curious and wants to learn. And then if you wanna expand on the skills, you certainly have that capability to do so. >>Great stuff. I love, love that. Now that we're peeking behind the curtain here, I'd love to have you guys explain, cuz people wanna know what's goes on in behind the scenes. How does innovation get happen? How does it happen with the relationship? Can you take us through a day in the life of kind of what goes on to make innovation happen with the joint partnership? You guys just have a zoom meeting, Do you guys fly out, you write go do you ship thing? I mean I'm making it up, but you get the idea, what's the, what's, how does it work? What's going on behind the scenes? >>So we hope to get more frequently together in person, but of course we had some difficulties over the last two to three years. So we are very used to zoom conferences and and Slack meetings. You always have to have the time difference in mind if we are working globally together. But what we try, for example, we have reg regular assembled now also in person geo based. So for emia, for the Americas, for aj. And we are bringing up interesting customer situations, architectural bits and pieces together. We are discussing it always to share and to contribute to our community. >>What's interesting, you know, as, as events are coming back to here, before you get, you weigh in, I'll comment, as the cube's been going back out to events, we are hearing comments like what, what pandemic we were more productive in the pandemic. I mean, developers know how to work remotely and they've been on all the tools there, but then they get in person, they're happy to see people, but there's no one's, no one's really missed the beat. I mean it seems to be very productive, you know, workflow, not a lot of disruption. More if anything, productivity gains. >>Agreed, right? I think one of the key things to keep in mind is, you know, even if you look at AWS's and even Amazon's leadership principles, right? Customer obsession, that's key. VMware is carrying that forward as well. Where we are working with our customers, like how Daniel said met earlier, right? We might have meetings at different time zones, maybe it's in person, maybe it's virtual, but together we're working to listen to our customers. You know, we're taking and capturing that feedback to drive innovation and VMware cloud on AWS as well. But one of the key things to keep in mind is yes, there have been, there has been the pandemic, we might have been disconnected to a certain extent, but together through technology we've been able to still communicate work with our customers. Even with VMware in between, with AWS and whatnot. We had that flexibility to innovate and continue that innovation. So even if you look at it from the point of view, right? VMware cloud on AWS outposts, that was something that customers have been asking for. We've been been able to leverage the feedback and then continue to drive innovation even around VMware cloud on AWS outposts. So even with the on premises environment, if you're looking to handle maybe data sovereignty or compliance needs, maybe you have low latency requirements, that's where certain advancements come into play, right? So the key thing is always to maintain that communication track. >>And our last segment we did here on the, on this showcase, we listed the accomplishments and they were pretty significant. I mean go, you got the global rollouts of the relationship. It's just really been interesting and, and people can reference that. We won't get into it here, but I will ask you guys to comment on, as you guys continue to evolve the relationship, what's in it for the customer? What can they expect next? Cuz again, I think right now we're in at a, an inflection point more than ever. What can people expect from the relationship and what's coming up with reinvent? Can you share a little bit of kind of what's coming down the pike? >>So one of the most important things we have announced this year, and we will continue to evolve into that direction, is independent scale of storage. That absolutely was one of the most important items customer asked us for over the last years. Whenever, whenever you are requiring additional storage to host your virtual machines, you usually in VMware cloud on aws, you have to add additional notes. Now we have three different note types with different ratios of compute, storage and memory. But if you only require additional storage, you always have to get also additional compute and memory and you have to pay. And now with two solutions which offer choice for the customers, like FS six one, NetApp onap, and VMware cloud Flex Storage, you now have two cost effective opportunities to add storage to your virtual machines. And that offers opportunities for other instance types maybe that don't have local storage. We are also very, very keen looking forward to announcements, exciting announcements at the upcoming events. >>Samir, what's your, what's your reaction take on the, on what's coming down on your side? >>Yeah, I think one of the key things to keep in mind is, you know, we're looking to help our customers be agile and even scale with their needs, right? So with VMware cloud on aws, that's one of the key things that comes to mind, right? There are gonna be announcements, innovations and whatnot with outcoming events. But together we're able to leverage that to advance VMware cloud on AWS to Daniel's point storage, for example, even with host offerings. And then even with decoupling storage from compute and memory, right now you have the flexibility where you can do all of that. So to look at it from the standpoint where now with 21 regions where we have VMware cloud on AWS available as well, where customers can utilize that as needed when needed, right? So it comes down to, you know, transformation will be there. Yes, there's gonna be maybe where workloads have to be adapted where they're utilizing certain AWS services, but you have that flexibility and option to do so. And I think with the continuing events that's gonna give us the options to even advance our own services together. >>Well you guys are in the middle of it, you're in the trenches, you're making things happen, you've got a team of people working together. My final question is really more of a kind of a current situation, kind of future evolutionary thing that you haven't seen this before. I wanna get both of your reaction to it. And we've been bringing this up in, in the open conversations on the cube is in the old days it was going back this generation, you had ecosystems, you had VMware had an ecosystem they did best, had an ecosystem. You know, we have a product, you have a product, biz dev deals happen, people sign relationships and they do business together and they, they sell to each other's products or do some stuff. Now it's more about architecture cuz we're now in a distributed large scale environment where the role of ecosystems are intertwining. >>And this, you guys are in the middle of two big ecosystems. You mentioned channel partners, you both have a lot of partners on both sides. They come together. So you have this now almost a three dimensional or multidimensional ecosystem, you know, interplay. What's your thoughts on this? And, and, and because it's about the architecture, integration is a value, not so much. Innovation is only, you gotta do innovation, but when you do innovation, you gotta integrate it, you gotta connect it. So what is, how do you guys see this as a, as an architectural thing, start to see more technical business deals? >>So we are, we are removing dependencies from individual ecosystems and from individual vendors. So a customer no longer has to decide for one vendor and then it is a very expensive and high effort project to move away from that vendor, which ties customers even, even closer to specific vendors. We are removing these obstacles. So with VMware cloud on aws moving to the cloud, firstly it's, it's not a dead end. If you decide at one point in time because of latency requirements or maybe it's some compliance requirements, you need to move back into on-premise. You can do this if you decide you want to stay with some of your services on premise and just run a couple of dedicated services in the cloud, you can do this and you can mana manage it through a single pane of glass. That's quite important. So cloud is no longer a dead and it's no longer a binary decision, whether it's on premise or the cloud. It it is the cloud. And the second thing is you can choose the best of both works, right? If you are migrating virtual machines that have been running in your on-premise environment to VMware cloud on aws, by the way, in a very, very fast cost effective and safe way, then you can enrich later on enrich these virtual machines with services that are offered by aws. More than 200 different services ranging from object based storage, load balancing and so on. So it's an endless, endless possibility. >>We, we call that super cloud in, in a, in a way that we be generically defining it where everyone's innovating, but yet there's some common services. But the differentiation comes from innovation where the lock in is the value, not some spec, right? Samir, this is gonna where cloud is right now, you guys are, are not commodity. Amazon's completely differentiating, but there's some commodity things. Having got storage, you got compute, but then you got now advances in all areas. But partners innovate with you on their terms. Absolutely. And everybody wins. >>Yeah. And a hundred percent agree with you. I think one of the key things, you know, as Daniel mentioned before, is where it it, it's a cross education where there might be someone who's more proficient on the cloud side with aws, maybe more proficient with the viewers technology, but then for partners, right? They bridge that gap as well where they come in and they might have a specific niche or expertise where their background, where they can help our customers go through that transformation. So then that comes down to, hey, maybe I don't know how to connect to the cloud. Maybe I don't know what the networking constructs are. Maybe I can leverage that partner. That's one aspect to go about it. Now maybe you migrated that workload to VMware cloud on aws. Maybe you wanna leverage any of the native AWS services or even just off the top 200 plus AWS services, right? But it comes down to that skill, right? So again, solutions architecture at the back of, back of the day, end of the day, what it comes down to is being able to utilize the best of both worlds. That's what we're giving our customers at the end of the >>Day. I mean, I just think it's, it's a, it's a refactoring and innovation opportunity at all levels. I think now more than ever, you can take advantage of each other's ecosystems and partners and technologies and change how things get done with keeping the consistency. I mean, Daniel, you nailed that, right? I mean, you don't have to do anything. You still run the fear, the way you working on it and now do new things. This is kind of a cultural shift. >>Yeah, absolutely. And if, if you look, not every, not every customer, not every organization has the resources to refactor and re-platform everything. And we gave, we give them a very simple and easy way to move workloads to the cloud. Simply run them and at the same time they can free up resources to develop new innovations and, and grow their business. >>Awesome. Samir, thank you for coming on. Danielle, thank you for coming to Germany, Octoberfest, I know it's evening over there, your weekend's here. And thank you for spending the time. Samir final give you the final word, AWS reinvents coming up. Preparing. We're gonna have an exclusive with Adam, but Fry, we do a curtain raise, a dual preview. What's coming down on your side with the relationship and what can we expect to hear about what you got going on at reinvent this year? The big show? >>Yeah, so I think, you know, Daniel hit upon some of the key points, but what I will say is we do have, for example, specific sessions, both that VMware's driving and then also that AWS is driving. We do have even where we have what I call a chalk talks. So I would say, and then even with workshops, right? So even with the customers, the attendees who are there, whatnot, if they're looking for to sit and listen to a session, yes that's there. But if they wanna be hands on, that is also there too. So personally for me as an IT background, you know, been in CIS admin world and whatnot, being hands on, that's one of the key things that I personally am looking forward. But I think that's one of the key ways just to learn and get familiar with the technology. Yeah, >>Reinvents an amazing show for the in person. You guys nail it every year. We'll have three sets this year at the cube. It's becoming popular. We more and more content. You guys got live streams going on, a lot of content, a lot of media, so thanks, thanks for sharing that. Samir Daniel, thank you for coming on on this part of the showcase episode of really the customer successes with VMware Cloud Ons, really accelerating business transformation withs and VMware. I'm John Fur with the cube, thanks for watching. Hello everyone. Welcome to this cube showcase, accelerating business transformation with VMware cloud on it's a solution innovation conversation with two great guests, Fred and VP of commercial services at aws and NA Ryan Bard, who's the VP and general manager of cloud solutions at VMware. Gentlemen, thanks for joining me on this showcase. >>Great to be here. >>Hey, thanks for having us on. It's a great topic. You know, we, we've been covering this VMware cloud on abus since, since the launch going back and it's been amazing to watch the evolution from people saying, Oh, it's the worst thing I've ever seen. It's what's this mean? And depress work were, we're kind of not really on board with kind of the vision, but as it played out as you guys had announced together, it did work out great for VMware. It did work out great for a D and it continues two years later and I want just get an update from you guys on where you guys see this has been going. I'll see multiple years. Where is the evolution of the solution as we are right now coming off VMware explorer just recently and going in to reinvent, which is only a couple weeks away, feels like tomorrow. But you know, as we prepare a lot going on, where are we with the evolution of the solution? >>I mean, first thing I wanna say is, you know, PBO 2016 was a someon moment and the history of it, right? When Pat Gelsinger and Andy Jessey came together to announce this and I think John, you were there at the time I was there, it was a great, great moment. We launched the solution in 2017, the year after that at VM Word back when we called it Word, I think we have gone from strength to strength. One of the things that has really mattered to us is we have learned froms also in the processes, this notion of working backwards. So we really, really focused on customer feedback as we build a service offering now five years old, pretty remarkable journey. You know, in the first years we tried to get across all the regions, you know, that was a big focus because there was so much demand for it. >>In the second year we started going really on enterprise grade features. We invented this pretty awesome feature called Stretch clusters, where you could stretch a vSphere cluster using VSA and NSX across two AZs in the same region. Pretty phenomenal four nine s availability that applications start started to get with that particular feature. And we kept moving forward all kinds of integration with AWS direct connect transit gateways with our own advanced networking capabilities. You know, along the way, disaster recovery, we punched out two, two new services just focused on that. And then more recently we launched our outposts partnership. We were up on stage at Reinvent, again with Pat Andy announcing AWS outposts and the VMware flavor of that VMware cloud and AWS outposts. I think it's been significant growth in our federal sector as well with our federal and high certification more recently. So all in all, we are super excited. We're five years old. The customer momentum is really, really strong and we are scaling the service massively across all geos and industries. >>That's great, great update. And I think one of the things that you mentioned was how the advantages you guys got from that relationship. And, and this has kind of been the theme for AWS since I can remember from day one. Fred, you guys do the heavy lifting as as, as you always say for the customers here, VMware comes on board, takes advantage of the AWS and kind of just doesn't miss a beat, continues to move their workloads that everyone's using, you know, vSphere and these are, these are big workloads on aws. What's the AWS perspective on this? How do you see it? >>Yeah, it's pretty fascinating to watch how fast customers can actually transform and move when you take the, the skill set that they're familiar with and the advanced capabilities that they've been using on Preem and then overlay it on top of the AWS infrastructure that's, that's evolving quickly and, and building out new hardware and new instances we'll talk about. But that combined experience between both of us on a jointly engineered solution to bring the best security and the best features that really matter for those workloads drive a lot of efficiency and speed for the, for the customer. So it's been well received and the partnership is stronger than ever from an engineering standpoint, from a business standpoint. And obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and, and responding to what customers want. So pretty, pretty excited about just seeing the transformation and the speed that which customers can move to bmc. Yeah, >>That's what great value publish. We've been talking about that in context too. Anyone building on top of the cloud, they can have their own supercloud as we call it. If you take advantage of all the CapEx and and investment Amazon's made and AWS has made and, and and continues to make in performance IAS and pass all great stuff. I have to ask you guys both as you guys see this going to the next level, what are some of the differentiations you see around the service compared to other options on the market? What makes it different? What's the combination? You mentioned jointly engineered, what are some of the key differentiators of the service compared to others? >>Yeah, I think one of the key things Fred talked about is this jointly engineered notion right from day one. We were the earlier doctors of AWS Nitro platform, right? The reinvention of E two back five years ago. And so we have been, you know, having a very, very strong engineering partnership at that level. I think from a VMware customer standpoint, you get the full software defined data center or compute storage networking on EC two, bare metal across all regions. You can scale that elastically up and down. It's pretty phenomenal just having that consistency globally, right on aws EC two global regions. Now the other thing that's a real differentiator for us that customers tell us about is this whole notion of a managed service, right? And this was somewhat new to VMware, but we took away the pain of this undifferentiated heavy lifting where customers had to provision rack, stack hardware, configure the software on top, and then upgrade the software and the security batches on top. >>So we took, took away all of that pain as customers transitioned to VMware cloud and aws. In fact, my favorite story from last year when we were all going through the lock for j debacle industry was just going through that, right? Favorite proof point from customers was before they put even race this issue to us, we sent them a notification saying we already patched all of your systems, no action from you. The customers were super thrilled. I mean these are large banks, many other customers around the world, super thrilled they had to take no action, but a pretty incredible industry challenge that we were all facing. >>Nora, that's a great, so that's a great point. You know, the whole managed service piece brings up the security, you kind of teasing at it, but you know, there's always vulnerabilities that emerge when you are doing complex logic. And as you grow your solutions, there's more bits. You know, Fred, we were commenting before we came on camera, there's more bits than ever before and, and at at the physics layer too, as well as the software. So you never know when there's gonna be a zero day vulnerability out there. Just, it happens. We saw one with fornet this week, this came outta the woodwork. But moving fast on those patches, it's huge. This brings up the whole support angle. I wanted to ask you about how you guys are doing that as well, because to me we see the value when we, when we talk to customers on the cube about this, you know, it was a real, real easy understanding of how, what the cloud means to them with VMware now with the aws. But the question that comes up that we wanna get more clarity on is how do you guys handle support together? >>Well, what's interesting about this is that it's, it's done mutually. We have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer, including all the way up into the app layer, as you think about some of the other workloads like sap, we'll go end to end and make sure that we support the customer regardless of where the particular issue might be for them. And on top of that, we look at where, where we're improving reliability in, in as a first order of, of principle between both companies. So from an availability and reliability standpoint, it's, it's top of mind and no matter where the particular item might land, we're gonna go help the customer resolve. That works really well >>On the VMware side. What's been the feedback there? What's the, what are some of the updates? >>Yeah, I think, look, I mean, VMware owns and operates the service, but we have a phenomenal backend relationship with aws. Customers call VMware for the service for any issues and, and then we have a awesome relationship with AWS on the backend for support issues or any hardware issues. The BASKE management that we jointly do, right? All of the hard problems that customers don't have to worry about. I think on the front end, we also have a really good group of solution architects across the companies that help to really explain the solution. Do complex things like cloud migration, which is much, much easier with VMware cloud aws, you know, we are presenting that easy button to the public cloud in many ways. And so we have a whole technical audience across the two companies that are working with customers every single day. >>You know, you had mentioned, I've got a list here, some of the innovations the, you mentioned the stretch clustering, you know, getting the GOs working, Advanced network, disaster recovery, you know, fed, Fed ramp, public sector certifications, outposts, all good. You guys are checking the boxes every year. You got a good, good accomplishments list there on the VMware AWS side here in this relationship. The question that I'm interested in is what's next? What recent innovations are you doing? Are you making investments in what's on the lists this year? What items will be next year? How do you see the, the new things, the list of accomplishments, people wanna know what's next. They don't wanna see stagnant growth here, they wanna see more action, you know, as as cloud kind of continues to scale and modern applications cloud native, you're seeing more and more containers, more and more, you know, more CF C I C D pipe pipelining with with modern apps, put more pressure on the system. What's new, what's the new innovations? >>Absolutely. And I think as a five yearold service offering innovation is top of mind for us every single day. So just to call out a few recent innovations that we announced in San Francisco at VMware Explorer. First of all, our new platform i four I dot metal, it's isolate based, it's pretty awesome. It's the latest and greatest, all the speeds and feeds that we would expect from VMware and aws. At this point in our relationship. We announced two different storage options. This notion of working from customer feedback, allowing customers even more price reductions, really take off that storage and park it externally, right? And you know, separate that from compute. So two different storage offerings there. One is with AWS Fsx, with NetApp on tap, which brings in our NetApp partnership as well into the equation and really get that NetApp based, really excited about this offering as well. >>And the second storage offering for VMware cloud Flex Storage, VMware's own managed storage offering. Beyond that, we have done a lot of other innovations as well. I really wanted to talk about VMware cloud Flex Compute, where previously customers could only scale by hosts and a host is 36 to 48 cores, give or take. But with VMware cloud Flex Compute, we are now allowing this notion of a resource defined compute model where customers can just get exactly the V C P memory and storage that maps to the applications, however small they might be. So this notion of granularity is really a big innovation that that we are launching in the market this year. And then last but not least, talk about ransomware. Of course it's a hot topic in industry. We are seeing many, many customers ask for this. We are happy to announce a new ransomware recovery with our VMware cloud DR solution. >>A lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots and backups are actually safe to use. So there's a lot of differentiation on that front as well. A lot of networking innovations with Project Knot star for ability to have layer flow through layer seven, you know, new SaaS services in that area as well. Keep in mind that the service already supports managed Kubernetes for containers. It's built in to the same clusters that have virtual machines. And so this notion of a single service with a great TCO for VMs and containers and sort of at the heart of our office, >>The networking side certainly is a hot area to keep innovating on. Every year it's the same, same conversation, get better, faster networking, more, more options there. The flex computes. Interesting. If you don't mind me getting a quick clarification, could you explain the Drew screen resource defined versus hardware defined? Because this is kind of what we had saw at Explore coming out, that notion of resource defined versus hardware defined. What's the, what does that mean? >>Yeah, I mean I think we have been super successful in this hardware defined notion. We we're scaling by the hardware unit that we present as software defined data centers, right? And so that's been super successful. But we, you know, customers wanted more, especially customers in different parts of the world wanted to start even smaller and grow even more incrementally, right? Lower their costs even more. And so this is the part where resource defined starts to be very, very interesting as a way to think about, you know, here's my bag of resources exactly based on what the customers request for fiber machines, five containers, its size exactly for that. And then as utilization grows, we elastically behind the scenes, we're able to grow it through policies. So that's a whole different dimension. It's a whole different service offering that adds value and customers are comfortable. They can go from one to the other, they can go back to that post based model if they so choose to. And there's a jump off point across these two different economic models. >>It's kind of cloud of flexibility right there. I like the name Fred. Let's get into some of the examples of customers, if you don't mind. Let's get into some of the ex, we have some time. I wanna unpack a little bit of what's going on with the customer deployments. One of the things we've heard again on the cube is from customers is they like the clarity of the relationship, they love the cloud positioning of it. And then what happens is they lift and shift the workloads and it's like, feels great. It's just like we're running VMware on AWS and then they would start consuming higher level services, kind of that adoption next level happens and because it it's in the cloud, so, So can you guys take us through some recent examples of customer wins or deployments where they're using VMware cloud on AWS on getting started, and then how do they progress once they're there? How does it evolve? Can you just walk us through a couple of use cases? >>Sure. There's a, well there's a couple. One, it's pretty interesting that, you know, like you said, as there's more and more bits you need better and better hardware and networking. And we're super excited about the I four and the capabilities there in terms of doubling and or tripling what we're doing around a lower variability on latency and just improving all the speeds. But what customers are doing with it, like the college in New Jersey, they're accelerating their deployment on a, on onboarding over like 7,400 students over a six to eight month period. And they've really realized a ton of savings. But what's interesting is where and how they can actually grow onto additional native services too. So connectivity to any other services is available as they start to move and migrate into this. The, the options there obviously are tied to all the innovation that we have across any services, whether it's containerized and with what they're doing with Tanu or with any other container and or services within aws. >>So there's, there's some pretty interesting scenarios where that data and or the processing, which is moved quickly with full compliance, whether it's in like healthcare or regulatory business is, is allowed to then consume and use things, for example, with tech extract or any other really cool service that has, you know, monthly and quarterly innovations. So there's things that you just can't, could not do before that are coming out and saving customers money and building innovative applications on top of their, their current app base in, in a rapid fashion. So pretty excited about it. There's a lot of examples. I think I probably don't have time to go into too, too many here. Yeah. But that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform. >>Nora, what's your perspective from the VMware sy? So, you know, you guys have now a lot of headroom to offer customers with Amazon's, you know, higher level services and or whatever's homegrown where's being rolled out? Cuz you now have a lot of hybrid too, so, so what's your, what's your take on what, what's happening in with customers? >>I mean, it's been phenomenal, the, the customer adoption of this and you know, banks and many other highly sensitive verticals are running production grade applications, tier one applications on the service over the last five years. And so, you know, I have a couple of really good examples. S and p Global is one of my favorite examples. Large bank, they merge with IHS market, big sort of conglomeration. Now both customers were using VMware cloud and AWS in different ways. And with the, with the use case, one of their use cases was how do I just respond to these global opportunities without having to invest in physical data centers? And then how do I migrate and consolidate all my data centers across the global, which there were many. And so one specific example for this company was how they migrated thousand 1000 workloads to VMware cloud AWS in just six weeks. Pretty phenomenal. If you think about everything that goes into a cloud migration process, people process technology and the beauty of the technology going from VMware point A to VMware point B, the the lowest cost, lowest risk approach to adopting VMware, VMware cloud, and aws. So that's, you know, one of my favorite examples. There are many other examples across other verticals that we continue to see. The good thing is we are seeing rapid expansion across the globe that constantly entering new markets with the limited number of regions and progressing our roadmap there. >>Yeah, it's great to see, I mean the data center migrations go from months, many, many months to weeks. It's interesting to see some of those success stories. So congratulations. One >>Of other, one of the other interesting fascinating benefits is the sustainability improvement in terms of being green. So the efficiency gains that we have both in current generation and new generation processors and everything that we're doing to make sure that when a customer can be elastic, they're also saving power, which is really critical in a lot of regions worldwide at this point in time. They're, they're seeing those benefits. If you're running really inefficiently in your own data center, that is just a, not a great use of power. So the actual calculators and the benefits to these workloads is, are pretty phenomenal just in being more green, which I like. We just all need to do our part there. And, and this is a big part of it here. >>It's a huge, it's a huge point about the sustainability. Fred, I'm glad you called that out. The other one I would say is supply chain issues. Another one you see that constrains, I can't buy hardware. And the third one is really obvious, but no one really talks about it. It's security, right? I mean, I remember interviewing Stephen Schmidt with that AWS and many years ago, this is like 2013, and you know, at that time people were saying the cloud's not secure. And he's like, listen, it's more secure in the cloud on premise. And if you look at the security breaches, it's all about the on-premise data center vulnerabilities, not so much hardware. So there's a lot you gotta to stay current on, on the isolation there is is hard. So I think, I think the security and supply chain, Fred is, is another one. Do you agree? >>I I absolutely agree. It's, it's hard to manage supply chain nowadays. We put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and, and have the resources that are available and run them, run them more efficiently. Yeah, and then like you said on the security point, security is job one. It is, it is the only P one. And if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers, there's nothing more important. >>And naron your point earlier about the managed service patching and being on top of things, it's really gonna get better. All right, final question. I really wanna thank you for your time on this showcase. It's really been a great conversation. Fred, you had made a comment earlier. I wanna kind of end with kind of a curve ball and put you eyes on the spot. We're talking about a modern, a new modern shift. It's another, we're seeing another inflection point, we've been documenting it, it's almost like cloud hitting another inflection point with application and open source growth significantly at the app layer. Continue to put a lot of pressure and, and innovation in the infrastructure side. So the question is for you guys each to answer is what's the same and what's different in today's market? So it's kind of like we want more of the same here, but also things have changed radically and better here. What are the, what's, what's changed for the better and where, what's still the same kind of thing hanging around that people are focused on? Can you share your perspective? >>I'll, I'll, I'll, I'll tackle it. You know, businesses are complex and they're often unique that that's the same. What's changed is how fast you can innovate. The ability to combine manage services and new innovative services and build new applications is so much faster today. Leveraging world class hardware that you don't have to worry about that's elastic. You, you could not do that even five, 10 years ago to the degree you can today, especially with innovation. So innovation is accelerating at a, at a rate that most people can't even comprehend and understand the, the set of services that are available to them. It's really fascinating to see what a one pizza team of of engineers can go actually develop in a week. It is phenomenal. So super excited about this space and it's only gonna continue to accelerate that. That's my take. All right. >>You got a lot of platform to compete on with, got a lot to build on then you're Ryan, your side, What's your, what's your answer to that question? >>I think we are seeing a lot of innovation with new applications that customers are constant. I think what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly, you know, build on the agility that developers desire and build all the security and the pipelines to energize that motor production quickly and efficiently. I think we, we are seeing, you know, we are at the very start of that sort of of journey. Of course we have invested in Kubernetes the means to an end, but there's so much more beyond that's happening in industry. And I think we're at the very, very beginning of this transformations, enterprise transformation that many of our customers are going through and we are inherently part of it. >>Yeah. Well gentlemen, I really appreciate that we're seeing the same thing. It's more the same here on, you know, solving these complexities with distractions. Whether it's, you know, higher level services with large scale infrastructure at, at your fingertips. Infrastructures, code, infrastructure to be provisioned, serverless, all the good stuff happen in Fred with AWS on your side. And we're seeing customers resonate with this idea of being an operator, again, being a cloud operator and developer. So the developer ops is kind of, DevOps is kind of changing too. So all for the better. Thank you for spending the time and we're seeing again, that traction with the VMware customer base and of us getting, getting along great together. So thanks for sharing your perspectives, >>I appreciate it. Thank you so >>Much. Okay, thank you John. Okay, this is the Cube and AWS VMware showcase, accelerating business transformation. VMware cloud on aws, jointly engineered solution, bringing innovation to the VMware customer base, going to the cloud and beyond. I'm John Fur, your host. Thanks for watching. Hello everyone. Welcome to the special cube presentation of accelerating business transformation on vmc on aws. I'm John Furrier, host of the Cube. We have dawan director of global sales and go to market for VMware cloud on adb. This is a great showcase and should be a lot of fun. Ashish, thanks for coming on. >>Hi John. Thank you so much. >>So VMware cloud on AWS has been well documented as this big success for VMware and aws. As customers move their workloads into the cloud, IT operations of VMware customers has signaling a lot of change. This is changing the landscape globally is on cloud migration and beyond. What's your take on this? Can you open this up with the most important story around VMC on aws? >>Yes, John. The most important thing for our customers today is the how they can safely and swiftly move their ID infrastructure and applications through cloud. Now, VMware cloud AWS is a service that allows all vSphere based workloads to move to cloud safely, swiftly and reliably. Banks can move their core, core banking platforms, insurance companies move their core insurance platforms, telcos move their goss, bss, PLA platforms, government organizations are moving their citizen engagement platforms using VMC on aws because this is one platform that allows you to move it, move their VMware based platforms very fast. Migrations can happen in a matter of days instead of months. Extremely securely. It's a VMware manage service. It's very secure and highly reliably. It gets the, the reliability of the underlyings infrastructure along with it. So win-win from our customers perspective. >>You know, we reported on this big news in 2016 with Andy Chas, the, and Pat Geling at the time, a lot of people said it was a bad deal. It turned out to be a great deal because not only could VMware customers actually have a cloud migrate to the cloud, do it safely, which was their number one concern. They didn't want to have disruption to their operations, but also position themselves for what's beyond just shifting to the cloud. So I have to ask you, since you got the finger on the pulse here, what are we seeing in the market when it comes to migrating and modern modernizing in the cloud? Because that's the next step. They go to the cloud, you guys have done that, doing it, then they go, I gotta modernize, which means kind of upgrading or refactoring. What's your take on that? >>Yeah, absolutely. Look, the first step is to help our customers assess their infrastructure and licensing and entire ID operations. Once we've done the assessment, we then create their migration plans. A lot of our customers are at that inflection point. They're, they're looking at their real estate, ex data center, real estate. They're looking at their contracts with colocation vendors. They really want to exit their data centers, right? And VMware cloud and AWS is a perfect solution for customers who wanna exit their data centers, migrate these applications onto the AWS platform using VMC on aws, get rid of additional real estate overheads, power overheads, be socially and environmentally conscious by doing that as well, right? So that's the migration story, but to your point, it doesn't end there, right? Modernization is a critical aspect of the entire customer journey as as well customers, once they've migrated their ID applications and infrastructure on cloud get access to all the modernization services that AWS has. They can correct easily to our data lake services, to our AIML services, to custom databases, right? They can decide which applications they want to keep and which applications they want to refactor. They want to take decisions on containerization, make decisions on service computing once they've come to the cloud. But the most important thing is to take that first step. You know, exit data centers, come to AWS using vmc or aws, and then a whole host of modernization options available to them. >>Yeah, I gotta say, we had this right on this, on this story, because you just pointed out a big thing, which was first order of business is to make sure to leverage the on-prem investments that those customers made and then migrate to the cloud where they can maintain their applications, their data, their infrastructure operations that they're used to, and then be in position to start getting modern. So I have to ask you, how are you guys specifically, or how is VMware cloud on s addressing these needs of the customers? Because what happens next is something that needs to happen faster. And sometimes the skills might not be there because if they're running old school, IT ops now they gotta come in and jump in. They're gonna use a data cloud, they're gonna want to use all kinds of machine learning, and there's a lot of great goodness going on above the stack there. So as you move with the higher level services, you know, it's a no brainer, obviously, but they're not, it's not yesterday's higher level services in the cloud. So how are, how is this being addressed? >>Absolutely. I think you hit up on a very important point, and that is skills, right? When our customers are operating, some of the most critical applications I just mentioned, core banking, core insurance, et cetera, they're most of the core applications that our customers have across industries, like even, even large scale ERP systems, they're actually sitting on VMware's vSphere platform right now. When the customer wants to migrate these to cloud, one of the key bottlenecks they face is skill sets. They have the trained manpower for these core applications, but for these high level services, they may not, right? So the first order of business is to help them ease this migration pain as much as possible by not wanting them to, to upscale immediately. And we VMware cloud and AWS exactly does that. I mean, you don't have to do anything. You don't have to create new skill set for doing this, right? Their existing skill sets suffice, but at the same time, it gives them that, that leeway to build that skills roadmap for their team. DNS is invested in that, right? Yes. We want to help them build those skills in the high level services, be it aml, be it, be it i t be it data lake and analytics. We want to invest in them, and we help our customers through that. So that ultimately the ultimate goal of making them drop data is, is, is a front and center. >>I wanna get into some of the use cases and success stories, but I want to just reiterate, hit back your point on the skill thing. Because if you look at what you guys have done at aws, you've essentially, and Andy Chassey used to talk about this all the time when I would interview him, and now last year Adam was saying the same thing. You guys do all the heavy lifting, but if you're a VMware customer user or operator, you are used to things. You don't have to be relearn to be a cloud architect. Now you're already in the game. So this is like almost like a instant path to cloud skills for the VMware. There's hundreds of thousands of, of VMware architects and operators that now instantly become cloud architects, literally overnight. Can you respond to that? Do you agree with that? And then give an example. >>Yes, absolutely. You know, if you have skills on the VMware platform, you know, know, migrating to AWS using via by cloud and AWS is absolutely possible. You don't have to really change the skills. The operations are exactly the same. The management systems are exactly the same. So you don't really have to change anything but the advantages that you get access to all the other AWS services. So you are instantly able to integrate with other AWS services and you become a cloud architect immediately, right? You are able to solve some of the critical problems that your underlying IT infrastructure has immediately using this. And I think that's a great value proposition for our customers to use this service. >>And just one more point, I want just get into something that's really kind of inside baseball or nuanced VMC or VMware cloud on AWS means something. Could you take a minute to explain what on AWS means? Just because you're like hosting and using Amazon as a, as a work workload? Being on AWS means something specific in your world, being VMC on AWS mean? >>Yes. This is a great question, by the way, You know, on AWS means that, you know, VMware's vse platform is, is a, is an iconic enterprise virtualization software, you know, a disproportionately high market share across industries. So when we wanted to create a cloud product along with them, obviously our aim was for them, for the, for this platform to have the goodness of the AWS underlying infrastructure, right? And, and therefore, when we created this VMware cloud solution, it it literally use the AWS platform under the eighth, right? And that's why it's called a VMs VMware cloud on AWS using, using the, the, the wide portfolio of our regions across the world and the strength of the underlying infrastructure, the reliability and, and, and sustainability that it offers. And therefore this product is called VMC on aws. >>It's a distinction I think is worth noting, and it does reflect engineering and some levels of integration that go well beyond just having a SaaS app and, and basically platform as a service or past services. So I just wanna make sure that now super cloud, we'll talk about that a little bit in another interview, but I gotta get one more question in before we get into the use cases and customer success stories is in, in most of the VM world, VMware world, in that IT world, it used to, when you heard migration, people would go, Oh my God, that's gonna take months. And when I hear about moving stuff around and doing cloud native, the first reaction people might have is complexity. So two questions for you before we move on to the next talk. Track complexity. How are you addressing the complexity issue and how long these migrations take? Is it easy? Is it it hard? I mean, you know, the knee jerk reaction is month, You're very used to that. If they're dealing with Oracle or other old school vendors, like, they're, like the old guard would be like, takes a year to move stuff around. So can you comment on complexity and speed? >>Yeah. So the first, first thing is complexity. And you know, what makes what makes anything complex is if you're, if you're required to acquire new skill sets or you've gotta, if you're required to manage something differently, and as far as VMware cloud and AWS on both these aspects, you don't have to do anything, right? You don't have to acquire new skill sets. Your existing idea operation skill sets on, on VMware's platforms are absolutely fine and you don't have to manage it any differently like, than what you're managing your, your ID infrastructure today. So in both these aspects, it's exactly the same and therefore it is absolutely not complex as far as, as far as, as far as we cloud and AWS is concerned. And the other thing is speed. This is where the huge differentiation is. You have seen that, you know, large banks and large telcos have now moved their workloads, you know, literally in days instead of months. >>Because because of VMware cloud and aws, a lot of time customers come to us with specific deadlines because they want to exit their data centers on a particular date. And what happens, VMware cloud and AWS is called upon to do that migration, right? So speed is absolutely critical. The reason is also exactly the same because you are using the exactly the same platform, the same management systems, people are available to you, you're able to migrate quickly, right? I would just reference recently we got an award from President Zelensky of Ukraine for, you know, migrating their entire ID digital infrastructure and, and that that happened because they were using VMware cloud database and happened very swiftly. >>That's been a great example. I mean, that's one political, but the economic advantage of getting outta the data center could be national security. You mentioned Ukraine, I mean Oscar see bombing and death over there. So clearly that's a critical crown jewel for their running their operations, which is, you know, you know, world mission critical. So great stuff. I love the speed thing. I think that's a huge one. Let's get into some of the use cases. One of them is, the first one I wanted to talk about was we just hit on data, data center migration. It could be financial reasons on a downturn or our, or market growth. People can make money by shifting to the cloud, either saving money or making money. You win on both sides. It's a, it's a, it's almost a recession proof, if you will. Cloud is so use case for number one data center migration. Take us through what that looks like. Give an example of a success. Take us through a day, day in the life of a data center migration in, in a couple minutes. >>Yeah. You know, I can give you an example of a, of a, of a large bank who decided to migrate, you know, their, all their data centers outside their existing infrastructure. And they had, they had a set timeline, right? They had a set timeline to migrate the, the, they were coming up on a renewal and they wanted to make sure that this set timeline is met. We did a, a complete assessment of their infrastructure. We did a complete assessment of their IT applications, more than 80% of their IT applications, underlying v vSphere platform. And we, we thought that the right solution for them in the timeline that they wanted, right, is VMware cloud ands. And obviously it was a large bank, it wanted to do it safely and securely. It wanted to have it completely managed, and therefore VMware cloud and aws, you know, ticked all the boxes as far as that is concerned. >>I'll be happy to report that the large bank has moved to most of their applications on AWS exiting three of their data centers, and they'll be exiting 12 more very soon. So that's a great example of, of, of the large bank exiting data centers. There's another Corolla to that. Not only did they manage to manage to exit their data centers and of course use and be more agile, but they also met their sustainability goals. Their board of directors had given them goals to be carbon neutral by 2025. They found out that 35% of all their carbon foot footprint was in their data centers. And if they moved their, their ID infrastructure to cloud, they would severely reduce the, the carbon footprint, which is 35% down to 17 to 18%. Right? And that meant their, their, their, their sustainability targets and their commitment to the go to being carbon neutral as well. >>And that they, and they shift that to you guys. Would you guys take that burden? A heavy lifting there and you guys have a sustainability story, which is a whole nother showcase in and of itself. We >>Can Exactly. And, and cause of the scale of our, of our operations, we are able to, we are able to work on that really well as >>Well. All right. So love the data migration. I think that's got real proof points. You got, I can save money, I can, I can then move and position my applications into the cloud for that reason and other reasons as a lot of other reasons to do that. But now it gets into what you mentioned earlier was, okay, data migration, clearly a use case and you laid out some successes. I'm sure there's a zillion others. But then the next step comes, now you got cloud architects becoming minted every, and you got managed services and higher level services. What happens next? Can you give us an example of the use case of the modernization around the NextGen workloads, NextGen applications? We're starting to see, you know, things like data clouds, not data warehouses. We're not gonna data clouds, it's gonna be all kinds of clouds. These NextGen apps are pure digital transformation in action. Take us through a use case of how you guys make that happen with a success story. >>Yes, absolutely. And this is, this is an amazing success story and the customer here is s and p global ratings. As you know, s and p global ratings is, is the world leader as far as global ratings, global credit ratings is concerned. And for them, you know, the last couple of years have been tough as far as hardware procurement is concerned, right? The pandemic has really upended the, the supply chain. And it was taking a lot of time to procure hardware, you know, configure it in time, make sure that that's reliable and then, you know, distribute it in the wide variety of, of, of offices and locations that they have. And they came to us. We, we did, again, a, a, a alar, a fairly large comprehensive assessment of their ID infrastructure and their licensing contracts. And we also found out that VMware cloud and AWS is the right solution for them. >>So we worked there, migrated all their applications, and as soon as we migrated all their applications, they got, they got access to, you know, our high level services be our analytics services, our machine learning services, our, our, our, our artificial intelligence services that have been critical for them, for their growth. And, and that really is helping them, you know, get towards their next level of modern applications. Right Now, obviously going forward, they will have, they will have the choice to, you know, really think about which applications they want to, you know, refactor or which applications they want to go ahead with. That is really a choice in front of them. And, but you know, the, we VMware cloud and AWS really gave them the opportunity to first migrate and then, you know, move towards modernization with speed. >>You know, the speed of a startup is always the kind of the Silicon Valley story where you're, you know, people can make massive changes in 18 months, whether that's a pivot or a new product. You see that in startup world. Now, in the enterprise, you can see the same thing. I noticed behind you on your whiteboard, you got a slogan that says, are you thinking big? I know Amazon likes to think big, but also you work back from the customers and, and I think this modern application thing's a big deal because I think the mindset has always been constrained because back before they moved to the cloud, most IT, and, and, and on-premise data center shops, it's slow. You gotta get the hardware, you gotta configure it, you gotta, you gotta stand it up, make sure all the software is validated on it, and loading a database and loading oss, I mean, mean, yeah, it got easier and with scripting and whatnot, but when you move to the cloud, you have more scale, which means more speed, which means it opens up their capability to think differently and build product. What are you seeing there? Can you share your opinion on that epiphany of, wow, things are going fast, I got more time to actually think about maybe doing a cloud native app or transforming this or that. What's your, what's your reaction to that? Can you share your opinion? >>Well, ultimately we, we want our customers to utilize, you know, most of our modern services, you know, applications should be microservices based. When desired, they should use serverless applic. So list technology, they should not have monolithic, you know, relational database contracts. They should use custom databases, they should use containers when needed, right? So ultimately, we want our customers to use these modern technologies to make sure that their IT infrastructure, their licensing, their, their entire IT spend is completely native to cloud technologies. They work with the speed of a startup, but it's important for them to, to, to get to the first step, right? So that's why we create this journey for our customers, where you help them migrate, give them time to build the skills, they'll help them mo modernize, take our partners along with their, along with us to, to make sure that they can address the need for our customers. That's, that's what our customers need today, and that's what we are working backwards from. >>Yeah, and I think that opens up some big ideas. I'll just say that the, you know, we're joking, I was joking the other night with someone here in, in Palo Alto around serverless, and I said, you know, soon you're gonna hear words like architectural list. And that's a criticism on one hand, but you might say, Hey, you know, if you don't really need an architecture, you know, storage lists, I mean, at the end of the day, infrastructure is code means developers can do all the it in the coding cycles and then make the operations cloud based. And I think this is kind of where I see the dots connecting. Final thought here, take us through what you're thinking around how this new world is evolving. I mean, architecturals kind of a joke, but the point is, you know, you have to some sort of architecture, but you don't have to overthink it. >>Totally. No, that's a great thought, by the way. I know it's a joke, but it's a great thought because at the end of the day, you know, what do the customers really want? They want outcomes, right? Why did service technology come? It was because there was an outcome that they needed. They didn't want to get stuck with, you know, the, the, the real estate of, of a, of a server. They wanted to use compute when they needed to, right? Similarly, what you're talking about is, you know, outcome based, you know, desire of our customers and, and, and that's exactly where the word is going to, Right? Cloud really enforces that, right? We are actually, you know, working backwards from a customer's outcome and using, using our area the breadth and depth of our services to, to deliver those outcomes, right? And, and most of our services are in that path, right? When we use VMware cloud and aws, the outcome is a, to migrate then to modernize, but doesn't stop there, use our native services, you know, get the business outcomes using this. So I think that's, that's exactly what we are going through >>Actually, should actually, you're the director of global sales and go to market for VMware cloud on Aus. I wanna thank you for coming on, but I'll give you the final minute. Give a plug, explain what is the VMware cloud on Aus, Why is it great? Why should people engage with you and, and the team, and what ultimately is this path look like for them going forward? >>Yeah. At the end of the day, we want our customers to have the best paths to the cloud, right? The, the best path to the cloud is making sure that they migrate safely, reliably, and securely as well as with speed, right? And then, you know, use that cloud platform to, to utilize AWS's native services to make sure that they modernize their IT infrastructure and applications, right? We want, ultimately that our customers, customers, customer get the best out of, you know, utilizing the, that whole application experience is enhanced tremendously by using our services. And I think that's, that's exactly what we are working towards VMware cloud AWS is, is helping our customers in that journey towards migrating, modernizing, whether they wanna exit a data center or whether they wanna modernize their applications. It's a essential first step that we wanna help our customers with >>One director of global sales and go to market with VMware cloud on neighbors. He's with aws sharing his thoughts on accelerating business transformation on aws. This is a showcase. We're talking about the future path. We're talking about use cases with success stories from customers as she's thank you for spending time today on this showcase. >>Thank you, John. I appreciate it. >>Okay. This is the cube, special coverage, special presentation of the AWS Showcase. I'm John Furrier, thanks for watching.

>>Hello everyone. My name is Savannah Peterson, coming to you from the Cube Studios in Palo Alto, California. We're gonna be talking about super computing an event coming up in Dallas this November. I'm joined by the infamous John Furrier. John, thank you for joining me today. >>Great to see you. You look great. >>Thank you. You know, I don't know if anyone's checked out the conference colors for for supercomputing, but I happen to match the accent pink and you are rocking their blue. I got the so on >>There it is. >>We don't always tie our fashion to the tech ladies and gentlemen, but we're, we're a new crew here at, at the Cube and I think it should be a thing that we, that we do moving forward. So John, you are a veteran and I'm a newbie to Supercomputing. It'll be my first time in Dallas. What can I expect? >>Basically it's a hardware nerd fest, basically of the top >>Minds. So it's like ces, >>It's like CES for like, like hardware. It's like really the coolest show if you're into like high performance computing, I mean game changing kind of, you know, physics, laws of physics and hardware. This is the show. I mean this is like the confluence of it's, it's really old. It started when I graduated college, 1988. And back then it was servers, you know, super computing was a concept. It was usually a box and it was hardware, big machine. And it would crank out calculations, simulations and, and you know, you were limited to the processor and all the, the systems components, just the architecture system software, I mean it was technical, it was, it was, it was hardware, it was fun. Very cool back then. But you know, servers got bigger and you got grid computing, you got clusters and then it be really became high performance computing concept. But that's now multiple disciplines, hence it's been around for a while. It's evergreen in the sense it's always changing, attracting talent, students, mentors, scholarships. It's kind of big funding and big companies are behind it. Wl, look, Packard Enterprise, Dell computing startups and hardware matters more than ever. You look at the cloud, what Amazon and, and the cloud hyper skills, they're building the fastest chips down at the root level hardware's back. And I think this show's gonna show a lot of that. >>There isn't the cloud without hardware to support it. So I think it's important that we're all headed here. You, you touched on the evolution there from super computing in the beginning and complex calculations and processing to what we're now calling high performance computing. Can you go a little bit deeper? What is, what does that mean, What does that cover? >>Well, I mean high high performance computing and now is a range of different things. So the super computing needs to be like a thing now. You got clusters and grids that's distributed, you got a backbone, it's well architected and there's a lot involved. This network and security, there's system software. So now it's multiple disciplines in high performance computing and you can do a lot more. And now with cloud computing you can do simulations, say drug research or drug testing. You have, you can do all kinds of cal genome sequencing. I mean the, the, the ability to actually use compute right now is so awesome. The field's got, you know, is rebooting itself in real time, you know, pun intended. So it's like really, it's really good thing. More compute makes things go faster, especially with more data. So high encapsulates all the, the engineering behind it. A lot of robotics coming in the future. All this is gonna be about the edge. You're seeing a lot more hardware making noise around things that are new use cases. You know, your Apple watch that's, you know, very high functionality to a cell tower. Cars again, high performance computing hits all these new use cases. >>It yeah, it absolutely does. I mean high performance computing touches pretty much every aspect of our lives in some capacity at this point and including how we drive our cars to, to get to the studio here in Palo Alto. Do you think that we're entering an era when all of this is about to scale exponentially versus some of the linear growth that we've seen in the space due to the frustration of some of us in the hardware world the last five to 10 years? >>Well, it's a good question. I think everyone has, has seen Moore's law, right? They've seen, you know, that's been, been well documented. I think the world's changing. You're starting to see the trend of more hardware that's specialized like DPU are now out there. You got GPUs, you're seeing the, you know, Bolton hardware, accelerators, you got chi layer software abstraction. So essentially it's, it's a software industry that's in impacted the hardware. So hardware really is software too and it's a lot more software in there. Again, system software's a lot different. So it's, I think it's, it's boomerang back up. I think there's an inflection point because if you look at cyber security and physical devices, they all kind of play in this world where they need compute at the edge. Edge is gonna be a big use case. You can see Dell Technologies there. I think they have a really big opportunity to sell more hardware. H WL Packard Enterprise, others, these are old school >>Box companies. >>So I think the distributed nature of cloud and hybrid and multi-cloud coming on earth and in space means a lot more high performance computing will be sold and and implemented. So that's my take on it. I just think I'm very bullish on this space. >>Ah, yes. And you know me, I get really personally excited about the edge. So I can't wait to see what's in store. Thinking about the variety of vendors and companies, I know we see some of the biggest players in the space. Who are you most excited to see in Dallas coming up in November? >>You know, HP enter, you look back on enterprise has always been informally, HP huge on hpc, Dell and hpe. This is their bread and butter. They've been making servers from many computers to Intel based servers now to arm-based servers and and building their own stuff. So you're gonna start to see a lot more of those players kind of transforming. We're seeing both Dell and HPE transforming and you're gonna see a lot of chip companies there. I'm sure you're gonna see a lot more younger talent, a lot, a lot of young talent are coming, like I said, robotics and the new physical world we're living in is software and IP connected. So it's not like the old school operational technology systems. You have, you know, IP enabled devices that opens up all kinds of new challenges around security vulnerabilities and also capabilities. So it's, I think it's gonna be a lot younger crowd I think than we usually see this year. And you seeing a lot of students, and again universities participating. >>Yeah, I noticed that they have a student competition that's a, a big part of the event. I'm curious when you say younger, are you expecting to see new startups and some interesting players in the space that maybe we haven't heard of before? >>I think we might see more use cases that are different. When I say younger, I don't mean so much on the Democratic but young, younger i new ideas, right? So I think you're gonna see a lot of smart people coming in that might not have the, you know, the, the lens from when it started in 1988 and remember 1988 to now so much has changed. In fact we just did AEG a segment on the cube called does hardware matter because for many, many years, over the past decades, like hardware doesn't matter, it's all about the cloud and we're not a box company. Boxes are coming back. So you know, that's gonna be music for for into the years of Dell Technologies HPE the world. But like hardware does matter and this, you're starting to see that here. So I think you'll see a lot a younger thinking, a little bit different thinking. You're gonna start to see more conf confluence of like machine learning. You're gonna see security and again, I mentioned space. These are areas where you're starting to see where hardware and high performance is gonna be part of all the new systems. And so it's just gonna be industrial to i o is gonna be a big part too. >>Yeah, absolutely. I, I was thinking about some of these use cases, I don't know if you heard about the new drones they're sending up into hurricanes, but it takes literally what a, what an edge use case, how durable it has to be and the rapid processing that has to happen as a result of the software. So many exciting things we could dive down the rabbit hole with. What can folks expect to see here on the cube during supercomputing? >>Well we're gonna talk to a lot of the leaders on the cube from this community, mostly from the practitioner's side, expert side. We're gonna have, we're gonna hear from Dell Technologies, Hewlett Packer Enterprise and a lot of other executives who are investing wanna find out what they're investing in, how it ties into the cloud. Cuz the cloud has become a great environment for multi-cloud with more grid-like capability and what's the future? Where's the hardware going, what's the evolution of the components? How is it being designed? And then how does it fit into the overall software open source market that's booming right now that cloud technology has been doing. So I wanna, we wanna try to connect the dots on the cube. >>Great. So we have a very easy task ahead of us. Hopefully everyone will enjoy the content and the guests that we leaving to, to our table here from from the show floor. When we think about, do you think there's gonna be any trends that we've seen in the past that might not be there? Has anything phased out of the super computing world? You're someone who's been around this game for a while? >>Yeah, that's a good question. I think the game is still the same but the players might shift a little bit. So for example, a lot more with the supply chain challenges you might see that impact. We're gonna watch that very closely to find out what components are gonna be in what. But I'm thinking more about system architecture because the use case is interesting. You know, I was talking to Dell folks about this, you know they have standard machines but then they have use cases for how do you put the equivalent of a data center next to say a mobile cell tower because now you have the capability for wireless and 5g. You gotta put the data center like CAPA speed functionality and capacity for compute at these edges in a smaller form factor. How do you do that? How do you handle all the IO and that's gonna be all these, all these things are nerd again nerdy conversations but they're gonna be very relevant. So I like the new use cases of power more compute in places that they've never been before. So I think that to me is where the exciting part is. Like okay, who's got the, who's really got the real deal going on here? That's something be the fun part. >>I think it allows for a new era in innovation and I don't say that lightly, but when we can put processing power literally anywhere, it certainly thrills the minds of hardware nerds. Like me, my I'm OG hardware, I know you are too, I won't reveal your roots, but I got my, my start in in hardware product design back in the day. So I can't wait >>To, well you then, you know, you know hardware, when you talk about processing power and memory, you can never have enough compute and memory. It's like, it's like the internet bandwidth. You can't never have enough bandwidth. Bandwidth, right? Network power, compute power, you know, bring it on, you know, >>Even battery life, simple things like that when it comes to hardware, especially when we're talking about being on the edge. It's just like our cell phones. Our cell phones are an edge device >>And we get, well when you combine cloud on premises hybrid and then multi-cloud and edge, you now have the ability to get compute at capabilities that were never fathom in the past. And most of the creativity is limited to the hardware capability and now that's gonna be unleashed. I think a lot of creativity. That's again back to the use cases and yes, again, you're gonna start to see more industrial stuff come out edge and I, I, I love the edge. I think this is a great use case for the edge. >>Me too. A absolutely so bold claim. I don't know if you're ready to, to draw a line in the sand. Are we on the precipice of a hardware renaissance? >>Definitely no doubt about it. When we, when we did the does hardware matter segment, it was really kind of to test, you know, everyone's talking about the cloud, but cloud also runs hardware. You look at what AWS is doing, for instance, all the innovation, it's at robotics, it's at that at the physical level, pro, pro, you know you got physics, I mean they're working on so low level engineering and the speed difference. I think from a workload standpoint, whoever can get the best out of the physics and the materials will have a winning formula. Cause you can have a lot more processing specialized processors. That's a new system architecture. And so to me the hype, definitely the HPC high press computing fits perfectly into that construct because now you got more power so that software can be more capable. And I think at the end of the day, nobody wants to write a app on our workload to run on on bad hardware, not have enough compute. >>Amen to that. On that note, John, how can people get in touch with you and us here on the show in anticipation of supercomputing? >>Of course hit the cube handle at the cube at Furrier, my last name F U R R I E R. And of course my dms are always open for scoops and story ideas. And go to silicon angle.com and the cube.net. >>Fantastic. John, I look forward to joining you in Dallas and thank you for being here with me today. And thank you all for joining us for this super computing preview. My name is Savannah Peterson and we're here on the cube live. Well not live prerecorded from Palo Alto. And look forward to seeing you for some high performance computing excitement soon.

>>Everyone, welcome to the cube here in Palo Alto, California for a special presentation on Cloud native at scale, enabling super cloud modern applications with Platform nine. I'm John Furry, your host of The Cube. We've got a great lineup of three interviews we're streaming today. Mattor Makki, who's the co-founder and VP of Product of Platform nine. She's gonna go into detail around Arlon, the open source products, and also the value of what this means for infrastructure as code and for cloud native at scale. Bickley the chief architect of Platform nine Cube alumni. Going back to the OpenStack days. He's gonna go into why Arlon, why this infrastructure as code implication, what it means for customers and the implications in the open source community and where that value is. Really great wide ranging conversation there. And of course, Vascar, Gort, the CEO of Platform nine, is gonna talk with me about his views on Super Cloud and why Platform nine has a scalable solutions to bring cloud native at scale. So enjoy the program, see you soon. Hello and welcome to the cube here in Palo Alto, California for a special program on cloud native at scale, enabling next generation cloud or super cloud for modern application cloud native developers. I'm John Forry, host of the Cube. Pleasure to have here me Makowski, co-founder and VP of product at Platform nine. Thanks for coming in today for this Cloudnative at scale conversation. >>Thank you for having >>Me. So Cloudnative at scale, something that we're talking about because we're seeing the, the next level of mainstream success of containers Kubernetes and cloud native develop, basically DevOps in the C I C D pipeline. It's changing the landscape of infrastructure as code, it's accelerating the value proposition and the super cloud as we call it, has been getting a lot of traction because this next generation cloud is looking a lot different, but kind of the same as the first generation. What's your view on Super cloud as it fits to cloud native as scales up? >>Yeah, you know, I think what's interesting, and I think the reason why Super Cloud is a really good and a really fit term for this, and I think, I know my CEO was chatting with you as well, and he was mentioning this as well, but I think there needs to be a different term than just multi-cloud or cloud. And the reason is because as cloud native and cloud deployments have scaled, I think we've reached a point now where instead of having the traditional data center style model, where you have a few large distributors of infrastructure and workload at a few locations, I think the model is kind of flipped around, right? Where you have a large number of micro sites. These micro sites could be your public cloud deployment, your private on-prem infrastructure deployments, or it could be your edge environment, right? And every single enterprise, every single industry is moving in that direction. And so you gotta rougher that with a terminology that, that, that indicates the scale and complexity of it. And so I think super cloud is a, is an appropriate term for >>That. So you brought a couple things I want to dig into. You mentioned Edge Notes. We're seeing not only edge nodes being the next kind of area of innovation, mainly because it's just popping up everywhere. And that's just the beginning. Wouldn't even know what's around the corner. You got buildings, you got iot, o ot, and it kind of coming together, but you also got this idea of regions, global infrastructures, big part of it. I just saw some news around cloud flare shutting down a site here, there's policies being made at scale. These new challenges there. Can you share because you can have edge. So hybrid cloud is a winning formula. Everybody knows that it's a steady state. Yeah. But across multiple clouds brings in this new un engineered area, yet it hasn't been done yet. Spanning clouds. People say they're doing it, but you start to see the toe in the water, it's happening, it's gonna happen. It's only gonna get accelerated with the edge and beyond globally. So I have to ask you, what is the technical challenges in doing this? Because it's something business consequences as well, but there are technical challenge. Can you share your view on what the technical challenges are for the super cloud across multiple edges and >>Regions? Yeah, absolutely. So I think, you know, in in the context of this, the, this, this term of super cloud, I think it's sometimes easier to visualize things in terms of two access, right? I think on one end you can think of the scale in terms of just pure number of nodes that you have, deploy number of clusters in the Kubernetes space. And then on the other access you would have your distribution factor, right? Which is, do you have these tens of thousands of nodes in one site or do you have them distributed across tens of thousands of sites with one node at each site? Right? And if you have just one flavor of this, there is enough complexity, but potentially manageable. But when you are expanding on both these access, you really get to a point where that skill really needs some well thought out, well-structured solutions to address it, right? A combination of homegrown tooling along with your, you know, favorite distribution of Kubernetes is not a strategy that can help you in this environment. It may help you when you have one of this or when you, when you scale, is not at the level. >>Can you scope the complexity? Because I mean, I hear a lot of moving parts going on there, the technology's also getting better. We we're seeing cloud native become successful. There's a lot to configure, there's a lot to install. Can you scope the scale of the problem? Because we're talking about at scale Yep. Challenges here. >>Yeah, absolutely. And I think, you know, I I like to call it, you know, the, the, the problem that the scale creates, you know, there's various problems, but I think one, one problem, one way to think about it is, is, you know, it works on my cluster problem, right? So, you know, I come from engineering background and there's a, you know, there's a famous saying between engineers and QA and the support folks, right? Which is, it works on my laptop, which is I tested this change, everything was fantastic, it worked flawlessly on my machine, on production, It's not working. The exact same problem now happens and these distributed environments, but at massive scale, right? Which is that, you know, developers test their applications, et cetera within the sanctity of their sandbox environments. But once you expose that change in the wild world of your production deployment, right? >>And the production deployment could be going at the radio cell tower at the edge location where a cluster is running there, or it could be sending, you know, these applications and having them run at my customer's site where they might not have configured that cluster exactly the same way as I configured it, or they configured the cluster, right? But maybe they didn't deploy the security policies or they didn't deploy the other infrastructure plugins that my app relies on all of these various factors at their own layer of complexity. And there really isn't a simple way to solve that today. And that is just, you know, one example of an issue that happens. I think another, you know, whole new ball game of issues come in the context of security, right? Because when you are deploying applications at scale in a distributed manner, you gotta make sure someone's job is on the line to ensure that the right security policies are enforced regardless of that scale factor. So I think that's another example of problems that occur. >>Okay. So I have to ask about scale because there are a lot of multiple steps involved when you see the success cloud native, you know, you see some, you know, some experimentation. They set up a cluster, say it's containers and Kubernetes, and then you say, Okay, we got this, we can configure it. And then they do it again and again, they call it day two. Some people call it day one, day two operation, whatever you call it. Once you get past the first initial thing, then you gotta scale it. Then you're seeing security breaches, you're seeing configuration errors. This seems to be where the hotpot is. And when companies transition from, I got this to, Oh no, it's harder than I thought at scale. Can you share your reaction to that and how you see this playing out? >>Yeah, so, you know, I think it's interesting. There's multiple problems that occur when, you know, the, the two factors of scale is we talked about start expanding. I think one of them is what I like to call the, you know, it, it works fine on my cluster problem, which is back in, when I was a developer, we used to call this, it works on my laptop problem, which is, you know, you have your perfectly written code that is operating just fine on your machine, your sandbox environment. But the moment it runs production, it comes back with p zeros and POS from support teams, et cetera. And those issues can be really difficult to try us, right? And so in the Kubernetes environment, this problem kind of multi folds, it goes, you know, escalates to a higher degree because yeah, you have your sandbox developer environments, they have their clusters and things work perfectly fine in those clusters because these clusters are typically handcrafted or a combination of some scripting and handcrafting. >>And so as you give that change to then run at your production edge location, like say you radio sell tower site, or you hand it over to a customer to run it on their cluster, they might not have not have configured that cluster exactly how you did it, or they might not have configured some of the infrastructure plugins. And so the things don't work. And when things don't work, triaging them becomes like ishly hard, right? It's just one of the examples of the problem. Another whole bucket of issues is security, which is, is you have these distributed clusters at scale, you gotta ensure someone's job is on the line to make sure that these security policies are configured properly. >>So this is a huge problem. I love that comment. That's not not happening on my system. It's the classic, you know, debugging mentality. Yeah. But at scale it's hard to do that with error prone. I can see that being a problem. And you guys have a solution you're launching, Can you share what our lawn is, this new product, What is it all about? Talk about this new introduction. >>Yeah, absolutely. I'm very, very excited. You know, it's one of the projects that we've been working on for some time now because we are very passionate about this problem and just solving problems at scale in on-prem or at in the cloud or at edge environments. And what arwan is, it's an open source project and it is a tool, it's a Kubernetes native tool for complete end to end management of not just your clusters, but your clusters. All of the infrastructure that goes within and along the sites of those clusters, security policies, your middleware plugins, and finally your applications. So what alarm lets you do in a nutshell is in a declarative way, it lets you handle the configuration and management of all of these components in at scale. >>So what's the elevator pitch simply put for what this solves in, in terms of the chaos you guys are reigning in. What's the, what's the bumper sticker? Yeah, >>What would it do? There's a perfect analogy that I love to reference in this context, which is think of your assembly line, you know, in a traditional, let's say, you know, an auto manufacturing factory or et cetera, and the level of efficiency at scale that that assembly line brings, right online. And if you look at the logo we've designed, it's this funny little robot. And it's because when we think of online, we, we think of these enterprise large scale environments, you know, sprawling at scale creating chaos because there isn't necessarily a well thought through, well structured solution that's similar to an assembly line, which is taking each components, you know, addressing them, manufacturing, processing them in a standardized way, then handing to the next stage. But again, it gets, you know, processed in a standardized way. And that's what Arlon really does. That's like the I pitch. If you have problems of scale of managing your infrastructure, you know, that is distributed. Arlon brings the assembly line level of efficiency and consistency >>For those. So keeping it smooth, the assembly on things are flowing. C C I CD pipelining. Exactly. So that's what you're trying to simplify that ops piece for the developer. I mean, it's not really ops, it's their ops, it's coding. >>Yeah. Not just developer, the ops, the operations folks as well, right? Because developers, you know, there is, the developers are responsible for one picture of that layer, which is my apps, and then maybe that middleware of application that they interface with, but then they hand it over to someone else who's then responsible to ensure that these apps are secure properly, that they are logging, logs are being collected properly, monitoring and observability integrated. And so it solves problems for both those >>Teams. Yeah. It's DevOps. So the DevOps is the cloud native developer. The OP teams have to kind of set policies. Is that where the declarative piece comes in? Is that why that's important? >>Absolutely. Yeah. And, and, and, and you know, Kubernetes really in introduced or elevated this declarative management, right? Because, you know, c communities clusters are Yeah. Or your, yeah, you know, specifications of components that go in Kubernetes are defined in a declarative way. And Kubernetes always keeps that state consistent with your defined state. But when you go outside of that world of a single cluster, and when you actually talk about defining the clusters or defining everything that's around it, there really isn't a solution that does that today. And so online addresses that problem at the heart of it, and it does that using existing open source well known solutions. >>Ed, do I wanna get into the benefits? What's in it for me as the customer developer? But I want to finish this out real quick and get your thoughts. You mentioned open source. Why open source? What's the, what's the current state of the product? You run the product group over at platform nine, is it open source? And you guys have a product that's commercial? Can you explain the open source dynamic? And first of all, why open source? Yeah. And what is the consumption? I mean, open source is great, People want open source, they can download it, look up the code, but maybe wanna buy the commercial. So I'm assuming you have that thought through, can you share open source and commercial relationship? >>Yeah, I think, you know, starting with why open source? I think it's, you know, we as a company, we have, you know, one of the things that's absolutely critical to us is that we take mainstream open source technologies components and then we, you know, make them available to our customers at scale through either a SaaS model on from model, right? But, so as we are a company or startup or a company that benefits, you know, in a massive way by this open source economy, it's only right, I think in my mind that we do our part of the duty, right? And contribute back to the community that feeds us. And so, you know, we have always held that strongly as one of our principles. And we have, you know, created and built independent products starting all the way with fi, which was a serverless product, you know, that we had built to various other, you know, examples that I can give. But that's one of the main reasons why opensource and also opensource because we want the community to really firsthand engage with us on this problem, which is very difficult to achieve if your product is behind a wall, you know, behind, behind a block box. >>Well, and that's, that's what the developers want too. I mean, what we're seeing in reporting with Super Cloud is the new model of consumption is I wanna look at the code and see what's in there. That's right. And then also, if I want to use it, I, I'll do it. Great. That's open source, that's the value. But then at the end of the day, if I wanna move fast, that's when people buy in. So it's a new kind of freemium, I guess, business model. I guess that's the way that, Well, but that's, that's the benefit. Open source. This is why standards and open source is growing so fast. You have that confluence of, you know, a way for helpers to try before they buy, but also actually kind of date the application, if you will. We, you know, Adrian Karo uses the dating me metaphor, you know, Hey, you know, I wanna check it out first before I get married. Right? And that's what open source, So this is the new, this is how people are selling. This is not just open source, this is how companies are selling. >>Absolutely. Yeah. Yeah. You know, I think, and you know, two things. I think one is just, you know, this, this, this cloud native space is so vast that if you, if you're building a close flow solution, sometimes there's also a risk that it may not apply to every single enterprises use cases. And so having it open source gives them an opportunity to extend it, expand it, to make it proper to their use case if they choose to do so, right? But at the same time, what's also critical to us is we are able to provide a supported version of it with an SLA that we, you know, that's backed by us, a SAS hosted version of it as well, for those customers who choose to go that route, you know, once they have used the open source version and loved it and want to take it at scale and in production and need, need, need a partner to collaborate with, who can, you know, support them for that production >>Environment. I have to ask you now, let's get into what's in it for the customer. I'm a customer, why should I be enthused about Arlo? What's in it for me? You know? Cause if I'm not enthused about it, I'm not gonna be confident and it's gonna be hard for me to get behind this. Can you share your enthusiastic view of, you know, why I should be enthused about Arlo customer? >>Yeah, absolutely. And so, and there's multiple, you know, enterprises that we talk to, many of them, you know, our customers, where this is a very kind of typical story that you hear, which is we have, you know, a Kubernetes distribution. It could be on premise, it could be public clouds, native es, and then we have our C I CD pipelines that are automating the deployment of applications, et cetera. And then there's this gray zone. And the gray zone is well before you can you, your CS CD pipelines can deploy the apps. Somebody needs to do all of their groundwork of, you know, defining those clusters and yeah. You know, properly configuring them. And as these things, these things start by being done hand grown. And then as the, as you scale, what typically enterprises would do today is they will have their home homegrown DIY solutions for this. >>I mean, the number of folks that I talk to that have built Terra from automation, and then, you know, some of those key developers leave. So it's a typical open source or typical, you know, DIY challenge. And the reason that they're writing it themselves is not because they want to. I mean, of course technology is always interesting to everybody, but it's because they can't find a solution that's out there that perfectly fits the problem. And so that's that pitch. I think Spico would be delighted. The folks that we've talked, you know, spoken with, have been absolutely excited and have, you know, shared that this is a major challenge we have today because we have, you know, few hundreds of clusters on s Amazon and we wanna scale them to few thousands, but we don't think we are ready to do that. And this will give us >>Stability. Yeah, I think people are scared, not sc I won't say scare, that's a bad word. Maybe I should say that they feel nervous because, you know, at scale small mistakes can become large mistakes. This is something that is concerning to enterprises. And, and I think this is gonna come up at co con this year where enterprises are gonna say, Okay, I need to see SLAs. I wanna see track record, I wanna see other companies that have used it. Yeah. How would you answer that question to, or, or challenge, you know, Hey, I love this, but is there any guarantees? Is there any, what's the SLAs? I'm an enterprise, I got tight, you know, I love the open source trying to free fast and loose, but I need hardened code. >>Yeah, absolutely. So, so two parts to that, right? One is Arlan leverages existing open source components, products that are extremely popular. Two specifically. One is Lon uses Argo cd, which is probably one of the highest rated and used CD open source tools that's out there, right? It's created by folks that are as part of Intuit team now, you know, really brilliant team. And it's used at scale across enterprises. That's one. Second is arlon also makes use of cluster api capi, which is a ES sub-component, right? For lifecycle management of clusters. So there is enough of, you know, community users, et cetera, around these two products, right? Or, or, or open source projects that will find Arlan to be right up in their alley because they're already comfortable, familiar with algo cd. Now Arlan just extends the scope of what Algo CD can do. And so that's one. And then the second part is going back to a point of the comfort. And that's where, you know, Platform nine has a role to play, which is when you are ready to deploy Alon at scale, because you've been, you know, playing with it in your DEF test environments, you're happy with what you get with it, then Platform nine will stand behind it and provide that sla. >>And what's been the reaction from customers you've talked to Platform nine customers with, with, that are familiar with, with Argo and then Arlo? What's been some of the feedback? >>Yeah, I, I, I think the feedback's been fantastic. I mean, I can give you examples of customers where, you know, initially, you know, when you are, when you're telling them about your entire portfolio of solutions, it might not strike a card right away. But then we start talking about Arlan and, and we talk about the fact that it uses Argo CD and they start opening up, they say, We have standardized on Argo and we have built these components, homegrown, we would be very interested. Can we co-develop? Does it support these use cases? So we've had that kind of validation. We've had validation all the way at the beginning of our line before we even wrote a single line of code saying this is something we plan on doing. And the customer said, If you had it today, I would've purchased it. So it's been really great validation. >>All right. So next question is, what is the solution to the customer? If I asked you, Look it, I have, I'm so busy, my team's overworked. I got a skills gap. I don't need another project that's, I'm so tied up right now and I'm just chasing my tail. How does Platform nine help me? >>Yeah, absolutely. So I think, you know, one of the core tenets of Platform nine has always been that we try to bring that public cloud like simplicity by hosting, you know, this in a lot of such similar tools in a SaaS hosted manner for our customers, right? So our goal behind doing that is taking away or trying to take away all of that complexity from customer's hands and offloading it to our hands, right? And giving them that full white glove treatment as we call it. And so from a customer's perspective, one, something like arlon will integrate with what they have so they don't have to rip and replace anything. In fact, it will, even in the next versions, it may even discover your clusters that you have today and, you know, give you an inventory and that, >>So customers have clusters that are growing, that's a sign correct call you guys. >>Absolutely. Either they're, they have massive large clusters, right? That they wanna split into smaller clusters, but they're not comfortable doing that today, or they've done that already on say, public cloud or otherwise. And now they have management challenges. So >>Especially operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure Yeah. And or scale out. >>That's right. Exactly. >>And you provide that layer of policy. >>Absolutely. >>Yes. That's the key value >>Here. That's right. >>So policy based configuration for cluster scale up >>Profile and policy based declarative configuration and life cycle management for clusters. >>If I asked you how this enables Super club, what would you say to that? >>I think this is one of the key ingredients to super cloud, right? If you think about a super cloud environment, there's at least few key ingredients that that come to my mind that are really critical. Like they are, you know, life saving ingredients at that scale. One is having a really good strategy for managing that scale, you know, in a, going back to assembly line in a very consistent, predictable way so that our lot solves then you, you need to compliment that with the right kind of observability and monitoring tools at scale, right? Because ultimately issues are gonna happen and you're gonna have to figure out, you know, how to solve them fast. And alon by the way, also helps in that direction, but you also need observability tools. And then especially if you're running it on the public cloud, you need some cost management tools. In my mind, these three things are like the most necessary ingredients to make Super Cloud successful. And, you know, alarm flows >>In one. Okay, so now the next level is, Okay, that makes sense. There's under the covers kind of speak under the hood. Yeah. How does that impact the app developers and the cloud native modern application workflows? Because the impact to me, seems the apps are gonna be impacted. Are they gonna be faster, stronger? I mean, what's the impact if you do all those things, as you mentioned, what's the impact of the apps? >>Yeah, the impact is that your apps are more likely to operate in production the way you expect them to, because the right checks and balances have gone through, and any discrepancies have been identified prior to those apps, prior to your customer running into them, right? Because developers run into this challenge to their, where there's a split responsibility, right? I'm responsible for my code, I'm responsible for some of these other plugins, but I don't own the stack end to end. I have to rely on my ops counterpart to do their part, right? And so this really gives them, you know, the right tooling for >>That. So this is actually a great kind of relevant point, you know, as cloud becomes more scalable, you're starting to see this fragmentation gone of the days of the full stack developer to the more specialized role. But this is a key point, and I have to ask you because if this Arlo solution takes place, as you say, and the apps are gonna be stupid, there's designed to do, the question is, what did, does the current pain look like of the apps breaking? What does the signals to the customer Yeah. That they should be calling you guys up into implementing Arlo, Argo, and, and, and on all the other goodness to automate, What are some of the signals? Is it downtime? Is it, is it failed apps, Is it latency? What are some of the things that Yeah, absolutely would be in indications of things are effed up a little bit. >>Yeah. More frequent down times, down times that are, that take longer to triage. And so you are, you know, the, you know, your mean times on resolution, et cetera, are escalating or growing larger, right? Like we have environments of customers where they, they have a number of folks on in the field that have to take these apps and run them at customer sites. And that's one of our partners. And they're extremely interested in this because the, the rate of failures they're encountering for this, you know, the field when they're running these apps on site, because the field is automating their clusters that are running on sites using their own script. So these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to reduce your, your meantime to resolution, if you're looking to reduce the number of failures that occur on your production site, that's one. And second, if you are looking to manage these at scale environments with a relatively small, focused, nimble ops team, which has an immediate impact on your, So those are, those are the >>Signals. This is the cloud native at scale situation, the innovation going on. Final thought is your reaction to the idea that if the world goes digital, which it is, and the confluence of physical and digital coming together, and cloud continues to do its thing, the company becomes the application, not where it used to be supporting the business, you know, the back office and the IIA terminals and some PCs and handhelds. Now if technology's running, the business is the business. Yeah. The company's the application. Yeah. So it can't be down. So there's a lot of pressure on, on CSOs and CIOs now and see, and boards is saying, how is technology driving the top line revenue? That's the number one conversation. Yeah. Do you see that same thing? >>Yeah. It's interesting. I think there's multiple pressures at the CXO CIO level, right? One is that there needs to be that visibility and clarity and guarantee almost that, you know, that the, the technology that's, you know, that's gonna drive your top line is gonna drive that in a consistent, reliable, predictable manner. And then second, there is the constant pressure to do that while always lowering your costs of doing it, right? Especially when you're talking about, let's say retailers or those kinds of large scale vendors, they many times make money by lowering the amount that they spend on, you know, providing those goods to their end customers. So I think those, both those factors kind of come into play and the solution to all of them is usually in a very structured strategy around automation. >>Final question. What does cloudnative at scale look like to you? If all the things happen the way we want 'em to happen, The magic wand, the magic dust, what does it look like? >>What that looks like to me is a CIO sipping at his desk on coffee production is running absolutely smooth. And his, he's running that at a nimble, nimble team size of at the most, a handful of folks that are just looking after things with things. So just >>Taking care of, and the CIO doesn't exist. There's no CSO there at the beach. >>Yeah. >>Thank you for coming on, sharing the cloud native at scale here on the cube. Thank you for your time. >>Fantastic. Thanks for having >>Me. Okay. I'm John Fur here for special program presentation, special programming cloud native at scale, enabling super cloud modern applications with Platform nine. Thanks for watching. Welcome back everyone to the special presentation of cloud native at scale, the cube and platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here at Bickley, who's the chief architect and co-founder of Platform nine b. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or well later, earlier when opens Stack was going. Great to see you and great to see congratulations on the success of platform nine. >>Thank you very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now was realized, and you've seen what Docker's doing with the new docker, the open source Docker now just a success Exactly. Of containerization, right? And now the Kubernetes layer that we've been working on for years is coming, bearing fruit. This is huge. >>Exactly. Yes. >>And so as infrastructure's code comes in, we talked to Bacar talking about Super Cloud, I met her about, you know, the new Arlon, our R lawn you guys just launched, the infrastructure's code is going to another level. And then it's always been DevOps infrastructure is code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon, connect the dots for us. What is the state of infrastructures code today? >>So I think, I think I'm, I'm glad you mentioned it, everybody or most people know about infrastructures code. But with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure as configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D instead with Kubernetes, you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specify. So I think it's, it's a even better version of infrastructures code. >>Yeah, yeah. And, and that really means it's developer just accessing resources. Okay. Not declaring, Okay, give me some compute, stand me up some, turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean now with open source, so popular, you don't have to have to write a lot of code. It's code being developed. And so it's into integration, it's configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these new, new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space that, >>That's, I wrote a LinkedIn post today was comments about, you know, hey, enterprise is the new breed, the trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your >>View? It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we try to do with this new project. Arlon. >>Yeah. So, so we're gonna get into Arlan in a second. I wanna get into the why Arlon. You guys announced that at our GoCon, which was put on here in Silicon Valley at the, at the by intu. They had their own little day over there at their headquarters. But before we get there, Vascar, your CEO came on and he talked about Super Cloud at our inaugural event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system, so to deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection for the internet at the, the layer too is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, it's gonna continue. >>It's interesting. I just really wrote another post today on LinkedIn called the Silicon Wars AMD Stock is down arm has been on rise, we've remember pointing for many years now, that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a service layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd wanna have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in, in this community of co con, which will be a covering. So that brings up the whole what's next? You guys just announced our lawn at ar GoCon, which came out of Intuit. We've had Maria Teel at our super cloud event, She's a cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why our lawn, why this announcement? Yeah, >>So the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built AR lawn and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, And >>What's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, so let's get into what that means for up above and below the, the, this abstraction or thin layer below the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads at the end of the day, and I talk to CXOs and IT folks that, that are now DevOps engineers. They care about the workloads and they want the infrastructure's code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened. They need observability and they need to, to know that it's working. That's right. And here's my workloads running effectively. So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, right? >>So workloads, so Kubernetes has defined kind of a standard way to describe workloads and you can, you know, tell Kubernetes, I want to run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem, like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases it is like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's coming like an EC two instance, spin up a cluster. We've heard people used words like that. That's >>Right. And before arlon you kind of had to do all of that using a different set of tools as, as I explained. So with AR loan you can kind of express everything together. You can say I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call the profile. And then you can stamp out your app, your applications and your clusters and manage them in a very, So >>It's essentially standard, like creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook, just deploy it. Now what there is between say a script like I'm, I have scripts, I can just automate scripts >>Or yes, this is where that declarative API and infrastructure as configuration comes in, right? Because scripts, yes you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things are controllers which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure as configuration is built kind of on, it's a super set of infrastructures code because it's >>An evolution. >>You need edge's code, but then you can configure the code by just saying do it. You basically declaring saying Go, go do that. That's right. Okay, so, alright, so cloud native at scale, take me through your vision of what that means. Someone says, Hey, what does cloud native at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years. I mean people are now starting to figure out, okay, it's not as easy as it sounds. Kubernetes has value. We're gonna hear this year at CubeCon a lot of this, what does cloud native at scale >>Mean? Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users there, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we try to address with Arran. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state, and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, so I'll put you on the spot rogue, that CubeCon coming up and now this'll be shipping this segment series out before. What do you expect to see at this year? It's the big story this year. What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jockeying for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time and there's ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of coupon and I expect to continue and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, well >>Maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there are just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. >>Yeah. Vic, you've had an storied career VMware over decades with them within 12 years with 14 years or something like that. Big number co-founder here a platform. I you's been around for a while at this game, man. We talked about OpenStack, that project we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a Cloud Aati team at that time. We would joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform Nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? Opens Stack was an example and then Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will a, platform nine will be there and we will, you know, take the innovations from the the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yes. Yeah, I think the, the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart this segment. What is at scale, how many clusters do you see that would be a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you, Yeah, how would you describe that? When people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. >>Yeah. And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing, doing over $2 billion billions of transactions a year and, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud need of its scale? >>The, the hyper squares? >>Yeah, yeah. A's Azure Google, >>You mean from a business perspective, they're, they have their own interests that, you know, that they're, they will keep catering to, they, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep well, >>They got great performance. I mean, from a, from a hardware standpoint, yes. That's gonna be key, >>Right? Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyper skaters really want to be in the game in terms of, you know, the, the new risk and arm ecosystems, the platforms. >>Yeah. Not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, I remember our first year doing the cube. Oh the cloud is one big distributed computer. It's, it's hardware and you got software and you got middleware and he kinda over, well he's kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. Yes, >>Exactly. >>It's, we're back in the same game. Thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super cloud Arlon open source and how to run large scale applications on the cloud, cloud native develop for developers. And John Furrier with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up. Hey, welcome back everyone to Super Cloud 22. I'm John Fur, host of the Cuba here all day talking about the future of cloud. Where's it all going? Making it super multi-cloud is around the corner and public cloud is winning. Got the private cloud on premise and Edge. Got a great guest here, Vascar Gorde, CEO of Platform nine, just on the panel on Kubernetes. An enabler blocker. Welcome back. Great to have you on. >>Good to see you >>Again. So Kubernetes is a blocker enabler by, with a question mark I put on on there. Panel was really to discuss the role of Kubernetes. Now great conversation operations is impacted. What's just thing about what you guys are doing at Platform nine? Is your role there as CEO and the company's position, kind of like the world spun into the direction of Platform nine while you're at the helm, right? >>Absolutely. In fact, things are moving very well and since they came to us, it was an insight to call ourselves the platform company eight years ago, right? So absolutely whether you are doing it in public clouds or private clouds, you know, the application world is moving very fast in trying to become digital and cloud native. There are many options for you to run the infrastructure. The biggest blocking factor now is having a unified platform. And that's what where we come into >>Patrick, we were talking before we came on stage here about your background and we were kind of talking about the glory days in 2000, 2001 when the first ASPs application service providers came out. Kind of a SaaS vibe, but that was kind of all kind of cloud-like >>It wasn't, >>And web services started then too. So you saw that whole growth. Now, fast forward 20 years later, 22 years later, where we are now, when you look back then to here and all the different cycles, >>In fact, you know, as we were talking offline, I was in one of those ASPs in the year 2000 where it was a novel concept of saying we are providing a software and a capability as a service, right? You sign up and start using it. I think a lot has changed since then. The tooling, the tools, the technology has really skyrocketed. The app development environment has really taken off exceptionally well. There are many, many choices of infrastructure now, right? So I think things are in a way the same but also extremely different. But more importantly now for any company, regardless of size, to be a digital native, to become a digital company is extremely mission critical. It's no longer a nice to have everybody's in the journey somewhere. >>Everyone is going digital transformation here. Even on a so-called downturn recession that's upcoming inflations sea year. It's interesting. This is the first downturn, the history of the world where the hyperscale clouds have been pumping on all cylinders as an economic input. And if you look at the tech trends, GDPs down, but not tech. Nope. Cause pandemic showed everyone digital transformation is here and more spend and more growth is coming even in, in tech. So this is a unique factor which proves that that digital transformation's happening and company, every company will need a super cloud. >>Everyone, every company, regardless of size, regardless of location, has to become modernize their infrastructure. And modernizing infrastructure is not just some, you know, new servers and new application tools. It's your approach, how you're serving your customers, how you're bringing agility in your organization. I think that is becoming a necessity for every enterprise to survive. >>I wanna get your thoughts on Super Cloud because one of the things Dave Alon and I want to do with Super Cloud and calling it that was we, I, I personally, and I know Dave as well, he can, I'll speak from, he can speak for himself. We didn't like multi-cloud. I mean not because Amazon said don't call things multi-cloud, it just didn't feel right. I mean everyone has multiple clouds by default. If you're running productivity software, you have Azure and Office 365. But it wasn't truly distributed. It wasn't truly decentralized, it wasn't truly cloud enabled. It didn't, it felt like they're not ready for a market yet. Yet public clouds booming on premise. Private cloud and Edge is much more on, you know, more, More dynamic, more unreal. >>Yeah. I think the reason why we think Super cloud is a better term than multi-cloud. Multi-cloud are more than one cloud, but they're disconnected. Okay, you have a productivity cloud, you have a Salesforce cloud, you may have, everyone has an internal cloud, right? So, but they're not connected. So you can say, okay, it's more than one cloud. So it's, you know, multi-cloud. But super cloud is where you are actually trying to look at this holistically. Whether it is on-prem, whether it is public, whether it's at the edge, it's a store at the branch. You are looking at this as one unit. And that's where we see the term super cloud is more applicable because what are the qualities that you require if you're in a super cloud, right? You need choice of infrastructure, you need, but at the same time you need a single pan or a single platform for you to build your innovations on, regardless of which cloud you're doing it on, right? So I think Super Cloud is actually a more tightly integrated orchestrated management philosophy we think. >>So let's get into some of the super cloud type trends that we've been reporting on. Again, the purpose of this event is as a pilot to get the conversations flowing with, with the influencers like yourselves who are running companies and building products and the builders, Amazon and Azure are doing extremely well. Google's coming up in third Cloudworks in public cloud. We see the use cases on premises use cases. Kubernetes has been an interesting phenomenon because it's become from the developer side a little bit, but a lot of ops people love Kubernetes. It's really more of an ops thing. You mentioned OpenStack earlier. Kubernetes kind of came out of that open stack. We need an orchestration. And then containers had a good shot with, with Docker. They re pivoted the company. Now they're all in an open source. So you got containers booming and Kubernetes as a new layer there. >>What's, >>What's the take on that? What does that really mean? Is that a new defacto enabler? It >>Is here. It's for here for sure. Every enterprise somewhere in the journey is going on. And you know, most companies are, 70 plus percent of them have 1, 2, 3 container based, Kubernetes based applications now being rolled out. So it's very much here. It is in production at scale by many customers. And it, the beauty of it is yes, open source, but the biggest gating factor is the skill set. And that's where we have a phenomenal engineering team, right? So it's, it's one thing to buy a tool and >>Just be clear, you're a managed service for Kubernetes. >>We provide, provide a software platform for cloud acceleration as a service and it can run anywhere. It can run in public private. We have customers who do it in truly multi-cloud environments. It runs on the edge, it runs at this in stores about thousands of stores in a retailer. So we provide that and also for specific segments where data sovereignty and data residency are key regulatory reasons. We also un on-prem as an air gap version. Can >>You give an example on how you guys are deploying your platform to enable a super cloud experience for your customer? Right. >>So I'll give you two different examples. One is a very large networking company, public networking company. They have hundreds of products, hundreds of r and d teams that are building different, different products. And if you look at few years back, each one was doing it on a different platforms, but they really needed to bring the agility. And they worked with us now over three years where we are their build test dev pro platform where all their products are built on, right? And it has dramatically increased their agility to release new products. Number two, it actually is a light out operation. In fact, the customer says like, like the Maytag service person, cuz we provide it as a service and it barely takes one or two people to maintain it for them. >>So it's kinda like an SRE vibe. One person managing a >>Large 4,000 engineers building infrastructure >>On their tools, >>Whatever they want on their tools. They're using whatever app development tools they use, but they use our platform. What >>Benefits are they seeing? Are they seeing speed? >>Speed, definitely. Okay. Definitely they're speeding. Speed uniformity because now they're building able to build, so their customers who are using product A and product B are seeing a similar set of tools that are being used. >>So a big problem that's coming outta this super cloud event that we're, we're seeing and we heard it all here, ops and security teams. Cause they're kind of part of one thing, but option security specifically need to catch up speed wise. Are you delivering that value to ops and security? Right? >>So we, we work with ops and security teams and infrastructure teams and we layer on top of that. We have like a platform team. If you think about it, depending on where you have data centers, where you have infrastructure, you have multiple teams, okay, but you need a unified platform. Who's your buyer? Our buyer is usually, you know, the product divisions of companies that are looking at or the CTO would be a buyer for us functionally cio definitely. So it it's, it's somewhere in the DevOps to infrastructure. But the ideal one we are beginning to see now many large corporations are really looking at it as a platform and saying we have a platform group on which any app can be developed and it is run on any infrastructure. So the platform engineering teams. So >>You working two sides to that coin. You've got the dev side and then >>And then infrastructure >>Side. >>Okay. Another customer that I give an example, which I would say is kind of the edge of the store. So they have thousands of stores. Retail, retail, you know food retailer, right? They have thousands of stores that are on the globe, 50,000, 60,000. And they really want to enhance the customer experience that happens when you either order the product or go into the store and pick up your product or buy or browse or sit there. They have applications that were written in the nineties and then they have very modern AIML applications today. They want something that will not have to send an IT person to install a rack in the store or they can't move everything to the cloud because the store operations has to be local. The menu changes based on it's classic edge. It's classic edge, yeah. Right? They can't send it people to go install rack access servers then they can't sell software people to go install the software and any change you wanna put through that, you know, truck roll. So they've been working with us where all they do is they ship, depending on the size of the store, one or two or three little servers with instructions that >>You, you say little servers like how big one like a box, like a small little box, >>Right? And all the person in the store has to do like what you and I do at home and we get a, you know, a router is connect the power, connect the internet and turn the switch on. And from there we pick it up. >>Yep. >>We provide the operating system, everything and then the applications are put on it. And so that dramatically brings the velocity for them. They manage thousands of >>Them. True plug and play >>Two, plug and play thousands of stores. They manage it centrally. We do it for them, right? So, so that's another example where on the edge then we have some customers who have both a large private presence and one of the public clouds. Okay. But they want to have the same platform layer of orchestration and management that they can use regardless of the locations. >>So you guys got some success. Congratulations. Got some traction there. It's awesome. The question I want to ask you is that's come up is what is truly cloud native? Cuz there's lift and shift of the cloud >>That's not cloud native. >>Then there's cloud native. Cloud native seems to be the driver for the super cloud. How do you talk to customers? How do you explain when someone says what's cloud native, what isn't cloud native? >>Right. Look, I think first of all, the best place to look at what is the definition and what are the attributes and characteristics of what is truly a cloud native, is CNC foundation. And I think it's very well documented, very well. >>Tucan, of course Detroit's >>Coming so, so it's already there, right? So we follow that very closely, right? I think just lifting and shifting your 20 year old application onto a data center somewhere is not cloud native. Okay? You can't put to cloud, not you have to rewrite and redevelop your application in business logic using modern tools. Hopefully more open source and, and I think that's what Cloudnative is and we are seeing a lot of our customers in that journey. Now everybody wants to be cloudnative, but it's not that easy, okay? Because it's, I think it's first of all, skill set is very important. Uniformity of tools that there's so many tools there. Thousands and thousands of tools you could spend your time figuring out which tool to use. Okay? So I think the complexity is there, but the business benefits of agility and uniformity and customer experience are truly being done. >>And I'll give you an example, I don't know how clear native they are, right? And they're not a customer of ours, but you order pizzas, you do, right? If you just watch the pizza industry, how dominoes actually increase their share and mind share and wallet share was not because they were making better pizzas or not, I don't know anything about that, but the whole experience of how you order, how you watch what's happening, how it's delivered. There were a pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow to the application changes what the expectations >>Are >>For the customer. Customer, >>The customer's expectations change, right? Once you get used to a better customer experience, you learn. >>That's to wrap it up. I wanna just get your perspective again. One of the benefits of chatting with you here and having you part of the Super Cloud 22 is you've seen many cycles, you have a lot of insights. I want to ask you, given your career where you've been and what you've done and now let's CEO platform nine, how would you compare what's happening now with other inflection points in the industry? And you've been, again, you've been an entrepreneur, you sold your company to Oracle, you've been seeing the big companies, you've seen the different waves. What's going on right now put into context this moment in time around Super Cloud. >>Sure. I think as you said, a lot of battles. CARSs being been in an asb, being in a real time software company, being in large enterprise software houses and a transformation. I've been on the app side, I did the infrastructure right and then tried to build our own platforms. I've gone through all of this myself with lot of lessons learned in there. I think this is an event which is happening now for companies to go through to become cloud native and digitalize. If I were to look back and look at some parallels of the tsunami that's going on is a couple of paddles come to me. One is, think of it, which was forced to honors like y2k. Everybody around the world had to have a plan, a strategy, and an execution for y2k. I would say the next big thing was e-commerce. I think e-commerce has been pervasive right across all industries. >>And disruptive. >>And disruptive, extremely disruptive. If you did not adapt and adapt and accelerate your e-commerce initiative, you were, it was an existence question. Yeah. I think we are at that pivotal moment now in companies trying to become digital and cloudnative. You know, that is what I see >>Happening there. I think that that e-commerce is interesting and I think just to riff with you on that is that it's disrupting and refactoring the business models. I think that is something that's coming out of this is that it's not just completely changing the gain, it's just changing how you operate, >>How you think and how you operate. See, if you think about the early days of e-commerce, just putting up a shopping cart that made you an e-commerce or e retailer or an e e e customer, right? Or so. I think it's the same thing now is I think this is a fundamental shift on how you're thinking about your business. How are you gonna operate? How are you gonna service your customers? I think it requires that just lift and shift is not gonna work. >>Nascar, thank you for coming on, spending the time to come in and share with our community and being part of Super Cloud 22. We really appreciate, we're gonna keep this open. We're gonna keep this conversation going even after the event, to open up and look at the structural changes happening now and continue to look at it in the open in the community. And we're gonna keep this going for, for a long, long time as we get answers to the problems that customers are looking for with cloud cloud computing. I'm Sean Fur with Super Cloud 22 in the Cube. Thanks for watching. >>Thank you. Thank you. >>Hello and welcome back. This is the end of our program, our special presentation with Platform nine on cloud native at scale, enabling the super cloud. We're continuing the theme here. You heard the interviews Super Cloud and its challenges, new opportunities around solutions around like Platform nine and others with Arlon. This is really about the edge situations on the internet and managing the edge multiple regions, avoiding vendor lock in. This is what this new super cloud is all about. The business consequences we heard and and the wide ranging conversations around what it means for open source and the complexity problem all being solved. I hope you enjoyed this program. There's a lot of moving pieces and things to configure with cloud native install, all making it easier for you here with Super Cloud and of course Platform nine contributing to that. Thank you for watching.

>>Hello, welcome to the Cube here in Palo Alto, California for a special presentation on Cloud native at scale, enabling super cloud modern applications with Platform nine. I'm John Furr, your host of The Cube. We had a great lineup of three interviews we're streaming today. Meor Ma Makowski, who's the co-founder and VP of Product of Platform nine. She's gonna go into detail around Arlon, the open source products, and also the value of what this means for infrastructure as code and for cloud native at scale. Bickley the chief architect of Platform nine Cube alumni. Going back to the OpenStack days. He's gonna go into why Arlon, why this infrastructure as code implication, what it means for customers and the implications in the open source community and where that value is. Really great wide ranging conversation there. And of course, Vascar, Gort, the CEO of Platform nine, is gonna talk with me about his views on Super Cloud and why Platform nine has a scalable solutions to bring cloudnative at scale. So enjoy the program. See you soon. Hello everyone. Welcome to the cube here in Palo Alto, California for special program on cloud native at scale, enabling next generation cloud or super cloud for modern application cloud native developers. I'm John Furry, host of the Cube. A pleasure to have here, me Makoski, co-founder and VP of product at Platform nine. Thanks for coming in today for this Cloudnative at scale conversation. Thank >>You for having me. >>So Cloudnative at scale, something that we're talking about because we're seeing the, the next level of mainstream success of containers Kubernetes and cloud native develop, basically DevOps in the C I C D pipeline. It's changing the landscape of infrastructure as code, it's accelerating the value proposition and the super cloud as we call it, has been getting a lot of traction because this next generation cloud is looking a lot different, but kind of the same as the first generation. What's your view on super cloud as it fits to cloud native as scales up? >>Yeah, you know, I think what's interesting, and I think the reason why Super Cloud is a really good, in a really fit term for this, and I think, I know my CEO was chatting with you as well, and he was mentioning this as well, but I think there needs to be a different term than just multi-cloud or cloud. And the reason is because as cloud native and cloud deployments have scaled, I think we've reached a point now where instead of having the traditional data center style model where you have a few large distributions of infrastructure and workload at a few locations, I think the model is kind of flipped around, right? Where you have a large number of microsites, these microsites could be your public cloud deployment, your private on-prem infrastructure deployments, or it could be your edge environment, right? And every single enterprise, every single industry is moving in that direction. And so you gotta rougher that with a terminology that, that, that indicates the scale and complexity of it. And so I think supercloud is a, is an appropriate term for that. >>So you brought a couple of things I want to dig into. You mentioned edge nodes. We're seeing not only edge nodes being the next kind of area of innovation, mainly because it's just popping up everywhere. And that's just the beginning. Wouldn't even know what's around the corner. You got buildings, you got iot, ot, and IT kind of coming together, but you also got this idea of regions, global infras infrastructures, big part of it. I just saw some news around CloudFlare shutting down a site here. There's policies being made at scale, These new challenges there. Can you share because you can have edge. So hybrid cloud is a winning formula. Everybody knows that it's a steady state. Yeah. But across multiple clouds brings in this new un engineered area, yet it hasn't been done yet. Spanning clouds. People say they're doing it, but you start to see the toe in the water, it's happening, it's gonna happen. It's only gonna get accelerated with the edge and beyond globally. So I have to ask you, what is the technical challenges in doing this? Because there's something business consequences as well, but there are technical challenges. Can you share your view on what the technical challenges are for the super cloud or across multiple edges and regions? >>Yeah, absolutely. So I think, you know, in in the context of this, the, this, this term of super cloud, I think it's sometimes easier to visualize things in terms of two access, right? I think on one end you can think of the scale in terms of just pure number of nodes that you have deploy a number of clusters in the Kubernetes space. And then on the other axis you would have your distribution factor, right? Which is, do you have these tens of thousands of nodes in one site or do you have them distributed across tens of thousands of sites with one node at each site? Right? And if you have just one flavor of this, there is enough complexity, but potentially manageable. But when you are expanding on both these access, you really get to a point where that scale really needs some well thought out, well structured solutions to address it, right? A combination of homegrown tooling along with your, you know, favorite distribution of Kubernetes is not a strategy that can help you in this environment. It may help you when you have one of this or when you, when you scale, is not at the level. >>Can you scope the complexity? Because I mean, I hear a lot of moving parts going on there, the technology's also getting better. We we're seeing cloud native become successful. There's a lot to configure, there's a lot to install. Can you scope the scale of the problem? Because we're talking about at scale Yep. Challenges here. Yeah, >>Absolutely. And I think, you know, I I like to call it, you know, the, the, the problem that the scale creates, you know, there's various problems, but I think one, one problem, one way to think about it is, is, you know, it works on my cluster problem, right? So I, you know, I come from engineering background and there's a, you know, there's a famous saying between engineers and QA and the support folks, right? Which is, it works on my laptop, which is I tested this chain, everything was fantastic, it worked flawlessly on my machine, on production, It's not working. The exact same problem now happens and these distributed environments, but at massive scale, right? Which is that, you know, developers test their applications, et cetera within the sanctity of their sandbox environments. But once you expose that change in the wild world of your production deployment, right? >>And the production deployment could be going at the radio cell tower at the edge location where a cluster is running there, or it could be sending, you know, these applications and having them run at my customer site where they might not have configured that cluster exactly the same way as I configured it, or they configured the cluster, right? But maybe they didn't deploy the security policies, or they didn't deploy the other infrastructure plugins that my app relies on. All of these various factors are their own layer of complexity. And there really isn't a simple way to solve that today. And that is just, you know, one example of an issue that happens. I think another, you know, whole new ball game of issues come in the context of security, right? Because when you are deploying applications at scale in a distributed manner, you gotta make sure someone's job is on the line to ensure that the right security policies are enforced regardless of that scale factor. So I think that's another example of problems that occur. >>Okay. So I have to ask about scale, because there are a lot of multiple steps involved when you see the success of cloud native. You know, you see some, you know, some experimentation. They set up a cluster, say it's containers and Kubernetes, and then you say, Okay, we got this, we can figure it. And then they do it again and again, they call it day two. Some people call it day one, day two operation, whatever you call it. Once you get past the first initial thing, then you gotta scale it. Then you're seeing security breaches, you're seeing configuration errors. This seems to be where the hotspot is in when companies transition from, I got this to, Oh no, it's harder than I thought at scale. Can you share your reaction to that and how you see this playing out? >>Yeah, so, you know, I think it's interesting. There's multiple problems that occur when, you know, the two factors of scale, as we talked about, start expanding. I think one of them is what I like to call the, you know, it, it works fine on my cluster problem, which is back in, when I was a developer, we used to call this, it works on my laptop problem, which is, you know, you have your perfectly written code that is operating just fine on your machine, your sandbox environment. But the moment it runs production, it comes back with p zeros and pos from support teams, et cetera. And those issues can be really difficult to triage us, right? And so in the Kubernetes environment, this problem kind of multi folds, it goes, you know, escalates to a higher degree because you have your sandbox developer environments, they have their clusters and things work perfectly fine in those clusters because these clusters are typically handcrafted or a combination of some scripting and handcrafting. >>And so as you give that change to then run at your production edge location, like say your radio cell tower site, or you hand it over to a customer to run it on their cluster, they might not have not have configured that cluster exactly how you did, or they might not have configured some of the infrastructure plugins. And so the things don't work. And when things don't work, triaging them becomes nightmarishly hard, right? It's just one of the examples of the problem, another whole bucket of issues is security, which is, is you have these distributed clusters at scale, you gotta ensure someone's job is on the line to make sure that these security policies are configured properly. >>So this is a huge problem. I love that comment. That's not not happening on my system. It's the classic, you know, debugging mentality. Yeah. But at scale it's hard to do that with error prone. I can see that being a problem. And you guys have a solution you're launching. Can you share what Arlon is this new product? What is it all about? Talk about this new introduction. >>Yeah, absolutely. Very, very excited. You know, it's one of the projects that we've been working on for some time now because we are very passionate about this problem and just solving problems at scale in on-prem or at in the cloud or at edge environments. And what arlon is, it's an open source project, and it is a tool, it's a Kubernetes native tool for complete end to end management of not just your clusters, but your clusters. All of the infrastructure that goes within and along the site of those clusters, security policies, your middleware, plug-ins, and finally your applications. So what our LA you do in a nutshell is in a declarative way, it lets you handle the configuration and management of all of these components in at scale. >>So what's the elevator pitch simply put for what dissolves in, in terms of the chaos you guys are reigning in, what's the, what's the bumper sticker? Yeah, what >>Would it do? There's a perfect analogy that I love to reference in this context, which is think of your assembly line, you know, in a traditional, let's say, you know, an auto manufacturing factory or et cetera, and the level of efficiency at scale that that assembly line brings, right? Our line, and if you look at the logo we've designed, it's this funny little robot. And it's because when we think of online, we think of these enterprise large scale environments, you know, sprawling at scale, creating chaos because there isn't necessarily a well thought through, well structured solution that's similar to an assembly line, which is taking each component, you know, addressing them, manufacturing, processing them in a standardized way, then handing to the next stage. But again, it gets, you know, processed in a standardized way. And that's what arlon really does. That's like the deliver pitch. If you have problems of scale of managing your infrastructure, you know, that is distributed. Arlon brings the assembly line level of efficiency and consistency for >>Those. So keeping it smooth, the assembly on things are flowing. See c i CD pipe pipelining. Exactly. So that's what you're trying to simplify that ops piece for the developer. I mean, it's not really ops, it's their ops, it's coding. >>Yeah. Not just developer, the ops, the operations folks as well, right? Because developers, you know, there is, developers are responsible for one picture of that layer, which is my apps, and then maybe that middleware of applications that they interface with, but then they hand it over to someone else who's then responsible to ensure that these apps are secure properly, that they are logging, logs are being collected properly, monitoring and observability integrated. And so it solves problems for both >>Those teams. Yeah. It's DevOps. So the DevOps is the cloud needed developer's. That's right. The option teams have to kind of set policies. Is that where the declarative piece comes in? Is that why that's important? >>Absolutely. Yeah. And, and, and, and you know, ES really in introduced or elevated this declarative management, right? Because, you know, s clusters are Yeah. Or your, yeah, you know, specifications of components that go in Kubernetes are defined a declarative way, and Kubernetes always keeps that state consistent with your defined state. But when you go outside of that world of a single cluster, and when you actually talk about defining the clusters or defining everything that's around it, there really isn't a solution that does that today. And so Arlon addresses that problem at the heart of it, and it does that using existing open source well known solutions. >>And do I want to get into the benefits? What's in it for me as the customer developer? But I want to finish this out real quick and get your thoughts. You mentioned open source. Why open source? What's the, what's the current state of the product? You run the product group over at Platform nine, is it open source? And you guys have a product that's commercial? Can you explain the open source dynamic? And first of all, why open source? Yeah. And what is the consumption? I mean, open source is great, People want open source, they can download it, look up the code, but maybe wanna buy the commercial. So I'm assuming you have that thought through, can you share open source and commercial relationship? >>Yeah, I think, you know, starting with why open source? I think it's, you know, we as a company, we have, you know, one of the things that's absolutely critical to us is that we take mainstream open source technologies components and then we, you know, make them available to our customers at scale through either a SaaS model or on-prem model, right? But, so as we are a company or startup or a company that benefits, you know, in a massive way by this open source economy, it's only right, I think in my mind that we do our part of the duty, right? And contribute back to the community that feeds us. And so, you know, we have always held that strongly as one of our principles. And we have, you know, created and built independent products starting all the way with fision, which was a serverless product, you know, that we had built to various other, you know, examples that I can give. But that's one of the main reasons why opensource and also open source, because we want the community to really firsthand engage with us on this problem, which is very difficult to achieve if your product is behind a wall, you know, behind, behind a block box. >>Well, and that's, that's what the developers want too. And what we're seeing in reporting with Super Cloud is the new model of consumption is I wanna look at the code and see what's in there. That's right. And then also, if I want to use it, I'll do it. Great. That's open source, that's the value. But then at the end of the day, if I wanna move fast, that's when people buy in. So it's a new kind of freemium, I guess, business model. I guess that's the way that long. But that's, that's the benefit. Open source. This is why standards and open source is growing so fast. You have that confluence of, you know, a way for developers to try before they buy, but also actually kind of date the application, if you will. We, you know, Adrian Karo uses the dating met metaphor, you know, Hey, you know, I wanna check it out first before I get married. Right? And that's what open source, So this is the new, this is how people are selling. This is not just open source, this is how companies are selling. >>Absolutely. Yeah. Yeah. You know, I think, and you know, two things. I think one is just, you know, this, this, this cloud native space is so vast that if you, if you're building a close flow solution, sometimes there's also a risk that it may not apply to every single enterprises use cases. And so having it open source gives them an opportunity to extend it, expand it, to make it proper to their use case if they choose to do so, right? But at the same time, what's also critical to us is we are able to provide a supported version of it with an SLA that we, you know, that's backed by us, a SAS hosted version of it as well, for those customers who choose to go that route, you know, once they have used the open source version and loved it and want to take it at scale and in production and need, need, need a partner to collaborate with, who can, you know, support them for that production >>Environment. I have to ask you now, let's get into what's in it for the customer. I'm a customer. Yep. Why should I be enthused about Arla? What's in it for me? You know? Cause if I'm not enthused about it, I'm not gonna be confident and it's gonna be hard for me to get behind this. Can you share your enthusiastic view of, you know, why I should be enthused about Arlo? I'm a >>Customer. Yeah, absolutely. And so, and there's multiple, you know, enterprises that we talk to, many of them, you know, our customers, where this is a very kind of typical story that you hear, which is we have, you know, a Kubernetes distribution. It could be on premise, it could be public clouds, native Kubernetes, and then we have our C I C D pipelines that are automating the deployment of applications, et cetera. And then there's this gray zone. And the gray zone is well before you can you, your CS c D pipelines can deploy the apps. Somebody needs to do all of that groundwork of, you know, defining those clusters and yeah. You know, properly configuring them. And as these things, these things start by being done hand grown. And then as the, as you scale, what typically enterprises would do today is they will have their home homegrown DIY solutions for this. >>I mean, the number of folks that I talk to that have built Terra from automation, and then, you know, some of those key developers leave. So it's a typical open source or typical, you know, DIY challenge. And the reason that they're writing it themselves is not because they want to. I mean, of course technology is always interesting to everybody, but it's because they can't find a solution that's out there that perfectly fits the problem. And so that's that pitch. I think Ops FICO would be delighted. The folks that we've talk, you know, spoken with, have been absolutely excited and have, you know, shared that this is a major challenge we have today because we have, you know, few hundreds of clusters on ecos Amazon, and we wanna scale them to few thousands, but we don't think we are ready to do that. And this will give us the >>Ability to, Yeah, I think people are scared. Not sc I won't say scare, that's a bad word. Maybe I should say that they feel nervous because, you know, at scale small mistakes can become large mistakes. This is something that is concerning to enterprises. And, and I think this is gonna come up at co con this year where enterprises are gonna say, Okay, I need to see SLAs. I wanna see track record, I wanna see other companies that have used it. Yeah. How would you answer that question to, or, or challenge, you know, Hey, I love this, but is there any guarantees? Is there any, what's the SLAs? I'm an enterprise, I got tight, you know, I love the open source trying to free fast and loose, but I need hardened code. >>Yeah, absolutely. So, so two parts to that, right? One is Arlan leverages existing open source components, products that are extremely popular. Two specifically. One is Arlan uses Argo cd, which is probably one of the highest and used CD open source tools that's out there. Right's created by folks that are as part of into team now, you know, really brilliant team. And it's used at scale across enterprises. That's one. Second is Alon also makes use of Cluster api cappi, which is a Kubernetes sub-component, right? For lifecycle management of clusters. So there is enough of, you know, community users, et cetera, around these two products, right? Or, or, or open source projects that will find Arlan to be right up in their alley because they're already comfortable, familiar with Argo cd. Now Arlan just extends the scope of what City can do. And so that's one. And then the second part is going back to a point of the comfort. And that's where, you know, platform line has a role to play, which is when you are ready to deploy online at scale, because you've been, you know, playing with it in your DEF test environments, you're happy with what you get with it, then Platform nine will stand behind it and provide that >>Sla. And what's been the reaction from customers you've talked to Platform nine customers with, with that are familiar with, with Argo and then rlo? What's been some of the feedback? >>Yeah, I, I think the feedback's been fantastic. I mean, I can give you examples of customers where, you know, initially, you know, when you are, when you're telling them about your entire portfolio of solutions, it might not strike a card right away. But then we start talking about Arlan and, and we talk about the fact that it uses Argo adn, they start opening up, they say, We have standardized on Argo and we have built these components, homegrown, we would be very interested. Can we co-develop? Does it support these use cases? So we've had that kind of validation. We've had validation all the way at the beginning of our land before we even wrote a single line of code saying this is something we plan on doing. And the customer said, If you had it today, I would've purchased it. So it's been really great validation. >>All right. So next question is, what is the solution to the customer? If I asked you, Look it, I have, I'm so busy, my team's overworked. I got a skills gap. I don't need another project that's, I'm so tied up right now and I'm just chasing my tail. How does Platform nine help me? >>Yeah, absolutely. So I think, you know, one of the core tenets of Platform nine has always been been that we try to bring that public cloud like simplicity by hosting, you know, this in a lot of such similar tools in a SaaS hosted manner for our customers, right? So our goal behind doing that is taking away or trying to take away all of that complexity from customers' hands and offloading it to our hands, right? And giving them that full white glove treatment, as we call it. And so from a customer's perspective, one, something like arlon will integrate with what they have so they don't have to rip and replace anything. In fact, it will, even in the next versions, it may even discover your clusters that you have today and you know, give you an inventory. And that will, >>So if customers have clusters that are growing, that's a sign correct call you guys. >>Absolutely. Either they're, they have massive large clusters, right? That they wanna split into smaller clusters, but they're not comfortable doing that today, or they've done that already on say, public cloud or otherwise. And now they have management challenges. So >>Especially operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure Yep. And or scale out. >>That's right. Exactly. And >>You provide that layer of policy. >>Absolutely. >>Yes. That's the key value here. >>That's right. >>So policy based configuration for cluster scale up, >>Well profile and policy based declarative configuration and lifecycle management for clusters. >>If I asked you how this enables supercloud, what would you say to that? >>I think this is one of the key ingredients to super cloud, right? If you think about a super cloud environment, there's at least few key ingredients that that come to my mind that are really critical. Like they are, you know, life saving ingredients at that scale. One is having a really good strategy for managing that scale, you know, in a, going back to assembly line in a very consistent, predictable way so that our lot solves then you, you need to compliment that with the right kind of observability and monitoring tools at scale, right? Because ultimately issues are gonna happen and you're gonna have to figure out, you know, how to solve them fast. And arlon by the way, also helps in that direction, but you also need observability tools. And then especially if you're running it on the public cloud, you need some cost management tools. In my mind, these three things are like the most necessary ingredients to make Super Cloud successful. And you know, our alarm fills in >>One. Okay. So now the next level is, Okay, that makes sense. Is under the covers kind of speak under the hood. Yeah. How does that impact the app developers and the cloud native modern application workflows? Because the impact to me, seems the apps are gonna be impacted. Are they gonna be faster, stronger? I mean, what's the impact if you do all those things, as you mentioned, what's the impact of the apps? >>Yeah, the impact is that your apps are more likely to operate in production the way you expect them to, because the right checks and balances have gone through, and any discrepancies have been identified prior to those apps, prior to your customer running into them, right? Because developers run into this challenge to their, where there's a split responsibility, right? I'm responsible for my code, I'm responsible for some of these other plugins, but I don't own the stack end to end. I have to rely on my ops counterpart to do their part, right? And so this really gives them, you know, the right tooling for that. >>So this is actually a great kind of relevant point, you know, as cloud becomes more scalable, you're starting to see this fragmentation gone of the days of the full stack developer to the more specialized role. But this is a key point, and I have to ask you because if this RLO solution takes place, as you say, and the apps are gonna be stupid, they're designed to do, the question is, what did does the current pain look like of the apps breaking? What does the signals to the customer Yeah. That they should be calling you guys up into implementing Arlo, Argo and, and all the other goodness to automate? What are some of the signals? Is it downtime? Is it, is it failed apps, Is it latency? What are some of the things that Yeah, absolutely would be indications of things are effed up a little bit. Yeah. >>More frequent down times, down times that are, that take longer to triage. And so you are, you know, the, you know, your mean times on resolution, et cetera, are escalating or growing larger, right? Like we have environments of customers where they're, they have a number of folks on in the field that have to take these apps and run them at customer sites. And that's one of our partners. And they're extremely interested in this because they're the, the rate of failures they're encountering for this, you know, the field when they're running these apps on site, because the field is automating their clusters that are running on sites using their own script. So these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to reduce your meantime to resolution, if you're looking to reduce the number of failures that occur on your production site, that's one. And second, if you are looking to manage these at scale environments with a relatively small, focused, nimble ops team, which has an immediate impact on your budget. So those are, those are the signals. >>This is the cloud native at scale situation, the innovation going on. Final thought is your reaction to the idea that if the world goes digital, which it is, and the confluence of physical and digital coming together, and cloud continues to do its thing, the company becomes the application, not where it used to be supporting the business, you know, the back office and the maybe terminals and some PCs and handhelds. Now if technology's running, the business is the business. Yeah. Company's the application. Yeah. So it can't be down. So there's a lot of pressure on, on CSOs and CIOs now and boards is saying, How is technology driving the top line revenue? That's the number one conversation. Yep. Do you see that same thing? >>Yeah. It's interesting. I think there's multiple pressures at the CXO CIO level, right? One is that there needs to be that visibility and clarity and guarantee almost that, you know, that the, the technology that's, you know, that's gonna drive your top line is gonna drive that in a consistent, reliable, predictable manner. And then second, there is the constant pressure to do that while always lowering your costs of doing it, right? Especially when you're talking about, let's say retailers or those kinds of large scale vendors, they many times make money by lowering the amount that they spend on, you know, providing those goods to their end customers. So I think those, both those factors kind of come into play and the solution to all of them is usually in a very structured strategy around automation. >>Final question. What does cloudnative at scale look like to you? If all the things happen the way we want 'em to happen, The magic wand, the magic dust, what does it look like? >>What that looks like to me is a CIO sipping at his desk on coffee production is running absolutely smooth. And his, he's running that at a nimble, nimble team size of at the most, a handful of folks that are just looking after things, but things are >>Just taking care of the CIO doesn't exist. There's no ciso, they're at the beach. >>Yep. >>Thank you for coming on, sharing the cloud native at scale here on the cube. Thank you for your time. >>Fantastic. Thanks for >>Having me. Okay. I'm John Fur here for special program presentation, special programming cloud native at scale, enabling super cloud modern applications with Platform nine. Thanks for watching. Welcome back everyone to the special presentation of cloud native at scale, the cube and platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here with Bickley, who's the chief architect and co-founder of Platform nine Pick. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or later, earlier when OpenStack was going. Great to see you and great to see congratulations on the success of platform nine. >>Thank you very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now has realized, and you've seen what Docker's doing with the new docker, the open source Docker now just the success Exactly. Of containerization, right? And now the Kubernetes layer that we've been working on for years is coming, bearing fruit. This is huge. >>Exactly. Yes. >>And so as infrastructures code comes in, we talked to Bacar talking about Super Cloud, I met her about, you know, the new Arlon, our, our lawn, and you guys just launched the infrastructures code is going to another level, and then it's always been DevOps infrastructures code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon, connect the dots for us. What is the state of infrastructure as code today? >>So I think, I think I'm, I'm glad you mentioned it, everybody or most people know about infrastructures code. But with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure is configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D instead with Kubernetes, you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specified. So I think it's, it's a even better version of infrastructures code. >>Yeah. And that really means it's developer just accessing resources. Okay. That declare, Okay, give me some compute, stand me up some, turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean now with open source so popular, you don't have to have to write a lot of code, this code being developed. And so it's into integration, it's configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space. >>That's, I wrote a LinkedIn post today was comments about, you know, hey, enterprise is a new breed. The trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your view? >>It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we try to do with this new project. Arlon. >>Yeah. So, so we're gonna get into Arlan in a second. I wanna get into the why Arlon. You guys announced that at AR GoCon, which was put on here in Silicon Valley at the, at the community meeting by in two, they had their own little day over there at their headquarters. But before we get there, vascar, your CEO came on and he talked about Super Cloud at our in AAL event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or applications specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system, so of deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection for the internet at the, the layer two is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think that the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, it's gonna >>Continue. It's interesting. I just, when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on a rise. We remember pointing for many years now that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a service layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd wanna have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in in this community of, of co con, which will be a covering. So that brings up the whole what's next? You guys just announced our lawn at Argo Con, which came out of Intuit. We've had Mariana Tessel at our super cloud event. She's the cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why our lawn, why this announcement? >>Yeah, so the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and, you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself. You can, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built our lawn and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, And >>What's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, so let's get into what that means for up above and below the the, this abstraction or thin layer below as the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads. At the end of the day, you know, I talk to CXOs and IT folks that are now DevOps engineers. They care about the workloads and they want the infrastructures code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened. They need observability and they need to, to know that it's working. That's right. And is my workloads running effectively? So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, >>Right? So workloads, so Kubernetes has defined kind of a standard way to describe workloads and you can, you know, tell Kubernetes, I want to run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases it is like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's kinda like an EC two instance, spin up a cluster. We very, people used words like that. That's >>Right. And before arlon you kind of had to do all of that using a different set of tools as, as I explained. So with Armon you can kind of express everything together. You can say I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call a profile. And then you can stamp out your app, your applications and your clusters and manage them in a very, so >>Essentially standard creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook. You deploy it. Now what's there is between say a script like I'm, I have scripts, I could just automate scripts >>Or yes, this is where that declarative API and infrastructures configuration comes in, right? Because scripts, yes you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things about controllers which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure has configuration is built kind of on, it's as super set of infrastructures code because it's >>An evolution. >>You need edge's code, but then you can configure the code by just saying do it. You basically declaring and saying Go, go do that. That's right. Okay, so, alright, so cloud native at scale, take me through your vision of what that means. Someone says, Hey, what does cloud native at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years? I mean people are now starting to figure out, okay, it's not as easy as it sounds. Could be nice, it has value. We're gonna hear this year coan a lot of this. What does cloud native at scale >>Mean? Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users there, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we try to address with Arran. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, so I'll put you on the spot road that CubeCon coming up and obviously this will be shipping this segment series out before. What do you expect to see at Coan this year? What's the big story this year? What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jogging for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time and there's ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of cons and I expect to continue and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, well >>Maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there are just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. >>Yeah. Vic, you've had an storied career, VMware over decades with them obviously in 12 years with 14 years or something like that. Big number co-founder here at Platform. Now you guys have been around for a while at this game. We, man, we talked about OpenStack, that project you, we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. And I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a cloud ERO team at that time. We would to joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys tr pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? OpenStack was an example when the Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will a, platform nine will be there and we will, you know, take the innovations from the the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yes. Yeah, I think the, the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart this segment. What is at scale, how many clusters do you see that would be a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you, Yeah, how would you describe that? When people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. >>Yeah. And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing over $2 billion billions of transactions a year and, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud native of its scale? >>The, the hyperscalers, >>Yeahs Azure, Google. >>You mean from a business perspective? Yeah, they're, they have their own interests that, you know, that they're, they will keep catering to, they, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep, >>Well they got great I performance, I mean from a, from a hardware standpoint, yes, that's gonna be key, right? >>Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyperscalers really want to be in the game in terms of, you know, the the new risk and arm ecosystems and the platforms. >>Yeah, not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, I remember our first year doing the cube. Oh the cloud is one big distributed computer, it's, it's hardware and he got software and you got middleware and he kind over, well he's kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. >>Yes, >>Exactly. It's, we're back on the same game. Vic, thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super cloud Arlon open source and how to run large scale applications on the cloud Cloud Native Phil for developers and John Furrier with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up. Hey, welcome back everyone to Super Cloud 22. I'm John Fur, host of the Cuba here all day talking about the future of cloud. Where's it all going? Making it super multi-cloud clouds around the corner and public cloud is winning. Got the private cloud on premise and edge. Got a great guest here, Vascar Gorde, CEO of Platform nine, just on the panel on Kubernetes. An enabler blocker. Welcome back. Great to have you on. >>Good to see you >>Again. So Kubernetes is a blocker enabler by, with a question mark. I put on on that panel was really to discuss the role of Kubernetes. Now great conversation operations is impacted. What's interest thing about what you guys are doing at Platform nine? Is your role there as CEO and the company's position, kind of like the world spun into the direction of Platform nine while you're at the helm? Yeah, right. >>Absolutely. In fact, things are moving very well and since they came to us, it was an insight to call ourselves the platform company eight years ago, right? So absolutely whether you are doing it in public clouds or private clouds, you know, the application world is moving very fast in trying to become digital and cloud native. There are many options for you do on the infrastructure. The biggest blocking factor now is having a unified platform. And that's what we, we come into, >>Patrick, we were talking before we came on stage here about your background and we were gonna talk about the glory days in 2000, 2001, when the first as piece application service providers came out, kind of a SaaS vibe, but that was kind of all kind of cloudlike. >>It wasn't, >>And and web services started then too. So you saw that whole growth. Now, fast forward 20 years later, 22 years later, where we are now, when you look back then to here and all the different cycles, >>I, in fact you, you know, as we were talking offline, I was in one of those ASPs in the year 2000 where it was a novel concept of saying we are providing a software and a capability as a service, right? You sign up and start using it. I think a lot has changed since then. The tooling, the tools, the technology has really skyrocketed. The app development environment has really taken off exceptionally well. There are many, many choices of infrastructure now, right? So I think things are in a way the same but also extremely different. But more importantly now for any company, regardless of size, to be a digital native, to become a digital company is extremely mission critical. It's no longer a nice to have everybody's in the journey somewhere. >>Everyone is going digital transformation here. Even on a so-called downturn recession that's upcoming inflation's here. It's interesting. This is the first downturn in the history of the world where the hyperscale clouds have been pumping on all cylinders as an economic input. And if you look at the tech trends, GDPs down, but not tech. >>Nope. >>Cuz the pandemic showed everyone digital transformation is here and more spend and more growth is coming even in, in tech. So this is a unique factor which proves that that digital transformation's happening and company, every company will need a super cloud. >>Everyone, every company, regardless of size, regardless of location, has to become modernize their infrastructure. And modernizing Infras infrastructure is not just some new servers and new application tools, It's your approach, how you're serving your customers, how you're bringing agility in your organization. I think that is becoming a necessity for every enterprise to survive. >>I wanna get your thoughts on Super Cloud because one of the things Dave Ante and I want to do with Super Cloud and calling it that was we, I, I personally, and I know Dave as well, he can, I'll speak from, he can speak for himself. We didn't like multi-cloud. I mean not because Amazon said don't call things multi-cloud, it just didn't feel right. I mean everyone has multiple clouds by default. If you're running productivity software, you have Azure and Office 365. But it wasn't truly distributed. It wasn't truly decentralized, it wasn't truly cloud enabled. It didn't, it felt like they're not ready for a market yet. Yet public clouds booming on premise. Private cloud and Edge is much more on, you know, more, more dynamic, more real. >>Yeah. I think the reason why we think super cloud is a better term than multi-cloud. Multi-cloud are more than one cloud, but they're disconnected. Okay, you have a productivity cloud, you have a Salesforce cloud, you may have, everyone has an internal cloud, right? So, but they're not connected. So you can say okay, it's more than one cloud. So it's you know, multi-cloud. But super cloud is where you are actually trying to look at this holistically. Whether it is on-prem, whether it is public, whether it's at the edge, it's a store at the branch. You are looking at this as one unit. And that's where we see the term super cloud is more applicable because what are the qualities that you require if you're in a super cloud, right? You need choice of infrastructure, you need, but at the same time you need a single pain, a single platform for you to build your innovations on regardless of which cloud you're doing it on, right? So I think Super Cloud is actually a more tightly integrated orchestrated management philosophy we think. >>So let's get into some of the super cloud type trends that we've been reporting on. Again, the purpose of this event is to, as a pilots, to get the conversations flowing with with the influencers like yourselves who are running companies and building products and the builders, Amazon and Azure are doing extremely well. Google's coming up in third cloudworks in public cloud. We see the use cases on premises use cases. Kubernetes has been an interesting phenomenon because it's become from the developer side a little bit, but a lot of ops people love Kubernetes. It's really more of an ops thing. You mentioned OpenStack earlier. Kubernetes kind of came out of that open stack. We need an orchestration and then containers had a good shot with, with Docker. They re pivoted the company. Now they're all in an open source. So you got containers booming and Kubernetes as a new layer there. What's the, what's the take on that? What does that really mean? Is that a new defacto enabler? It >>Is here. It's for here for sure. Every enterprise somewhere else in the journey is going on. And you know, most companies are, 70 plus percent of them have won two, three container based, Kubernetes based applications now being rolled out. So it's very much here, it is in production at scale by many customers. And the beauty of it is, yes, open source, but the biggest gating factor is the skill set. And that's where we have a phenomenal engineering team, right? So it's, it's one thing to buy a tool >>And just be clear, you're a managed service for Kubernetes. >>We provide, provide a software platform for cloud acceleration as a service and it can run anywhere. It can run in public private. We have customers who do it in truly multi-cloud environments. It runs on the edge, it runs at this in stores are thousands of stores in a retailer. So we provide that and also for specific segments where data sovereignty and data residency are key regulatory reasons. We also un OnPrem as an air gap version. >>Can you give an example on how you guys are deploying your platform to enable a super cloud experience for your >>Customer? Right. So I'll give you two different examples. One is a very large networking company, public networking company. They have, I dunno, hundreds of products, hundreds of r and d teams that are building different, different products. And if you look at few years back, each one was doing it on a different platforms but they really needed to bring the agility and they worked with us now over three years where we are their build test dev pro platform where all their products are built on, right? And it has dramatically increased their agility to release new products. Number two, it actually is a light out operation. In fact the customer says like, like the Maytag service person cuz we provide it as a service and it barely takes one or two people to maintain it for them. >>So it's kinda like an SRE vibe. One person managing a >>Large 4,000 engineers building infrastructure >>On their tools, >>Whatever they want on their tools. They're using whatever app development tools they use, but they use our platform. >>What benefits are they seeing? Are they seeing speed? >>Speed, definitely. Okay. Definitely they're speeding. Speed uniformity because now they're building able to build, so their customers who are using product A and product B are seeing a similar set of tools that are being used. >>So a big problem that's coming outta this super cloud event that we're, we're seeing and we've heard it all here, ops and security teams cuz they're kind of too part of one theme, but ops and security specifically need to catch up speed wise. Are you delivering that value to ops and security? Right. >>So we, we work with ops and security teams and infrastructure teams and we layer on top of that. We have like a platform team. If you think about it, depending on where you have data centers, where you have infrastructure, you have multiple teams, okay, but you need a unified platform. Who's your buyer? Our buyer is usually, you know, the product divisions of companies that are looking at or the CTO would be a buyer for us functionally cio definitely. So it it's, it's somewhere in the DevOps to infrastructure. But the ideal one we are beginning to see now many large corporations are really looking at it as a platform and saying we have a platform group on which any app can be developed and it is run on any infrastructure. So the platform engineering teams, >>You working two sides of that coin. You've got the dev side and then >>And then infrastructure >>Side side, okay. >>Another customer like give you an example, which I would say is kind of the edge of the store. So they have thousands of stores. Retail, retail, you know food retailer, right? They have thousands of stores that are on the globe, 50,000, 60,000. And they really want to enhance the customer experience that happens when you either order the product or go into the store and pick up your product or buy or browse or sit there. They have applications that were written in the nineties and then they have very modern AIML applications today. They want something that will not have to send an IT person to install a rack in the store or they can't move everything to the cloud because the store operations has to be local. The menu changes based on, It's a classic edge. It's classic edge. Yeah. Right. They can't send it people to go install rack access servers then they can't sell software people to go install the software and any change you wanna put through that, you know, truck roll. So they've been working with us where all they do is they ship, depending on the size of the store, one or two or three little servers with instructions that >>You, you say little servers like how big one like a net box box, like a small little >>Box and all the person in the store has to do like what you and I do at home and we get a, you know, a router is connect the power, connect the internet and turn the switch on. And from there we pick it up. >>Yep. >>We provide the operating system, everything and then the applications are put on it. And so that dramatically brings the velocity for them. They manage >>Thousands of them. True plug and play >>Two, plug and play thousands of stores. They manage it centrally. We do it for them, right? So, so that's another example where on the edge then we have some customers who have both a large private presence and one of the public clouds. Okay. But they want to have the same platform layer of orchestration and management that they can use regardless of the location. So >>You guys got some success. Congratulations. Got some traction there. It's awesome. The question I want to ask you is that's come up is what is truly cloud native? Cuz there's lift and shift of the cloud >>That's not cloud native. >>Then there's cloud native. Cloud native seems to be the driver for the super cloud. How do you talk to customers? How do you explain when someone says what's cloud native, what isn't cloud native? >>Right. Look, I think first of all, the best place to look at what is the definition and what are the attributes and characteristics of what is truly a cloud native, is CNC foundation. And I think it's very well documented where you, well >>Con of course Detroit's >>Coming here, so, so it's already there, right? So, so we follow that very closely, right? I think just lifting and shifting your 20 year old application onto a data center somewhere is not cloud native. Okay? You can't put to cloud native, you have to rewrite and redevelop your application and business logic using modern tools. Hopefully more open source and, and I think that's what Cloudnative is and we are seeing a lot of our customers in that journey. Now everybody wants to be cloudnative, but it's not that easy, okay? Because it's, I think it's first of all, skill set is very important. Uniformity of tools that there's so many tools there. Thousands and thousands of tools you could spend your time figuring out which tool to use. Okay? So I think the complexities there, but the business benefits of agility and uniformity and customer experience are truly them. >>And I'll give you an example. I don't know how clear native they are, right? And they're not a customer of ours, but you order pizzas, you do, right? If you just watch the pizza industry, how dominoes actually increase their share and mind share and wallet share was not because they were making better pizzas or not, I don't know anything about that, but the whole experience of how you order, how you watch what's happening, how it's delivered. There were a pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow to the application changes what the expectations of the, for the customer. >>Customer, the customer's expectations change, right? Once you get used to a better customer experience, you learn >>Best car. To wrap it up, I wanna just get your perspective again. One of the benefits of chatting with you here and having you part of the Super Cloud 22 is you've seen many cycles, you have a lot of insights. I want to ask you, given your career where you've been and what you've done and now the CEO platform nine, how would you compare what's happening now with other inflection points in the industry? And you've been, again, you've been an entrepreneur, you sold your company to Oracle, you've been seeing the big companies, you've seen the different waves. What's going on right now put into context this moment in time around Super >>Cloud. Sure. I think as you said, a lot of battles. Cars being been, been in an asp, been in a realtime software company, being in large enterprise software houses and a transformation. I've been on the app side, I did the infrastructure right and then tried to build our own platforms. I've gone through all of this myself with a lot of lessons learned in there. I think this is an event which is happening now for companies to go through to become cloud native and digitalize. If I were to look back and look at some parallels of the tsunami that's going on is a couple of paddles come to me. One is, think of it, which was forced to honors like y2k. Everybody around the world had to have a plan, a strategy, and an execution for y2k. I would say the next big thing was e-commerce. I think e-commerce has been pervasive right across all industries. >>And disruptive. >>And disruptive, extremely disruptive. If you did not adapt and adapt and accelerate your e-commerce initiative, you were, it was an existence question. Yeah. I think we are at that pivotal moment now in companies trying to become digital and cloudnative that know that is what I see >>Happening there. I think that that e-commerce was interesting and I think just to riff with you on that is that it's disrupting and refactoring the business models. I think that is something that's coming out of this is that it's not just completely changing the game, it's just changing how you operate, >>How you think, and how you operate. See, if you think about the early days of eCommerce, just putting up a shopping cart didn't made you an eCommerce or an E retailer or an e e customer, right? Or so. I think it's the same thing now is I think this is a fundamental shift on how you're thinking about your business. How are you gonna operate? How are you gonna service your customers? I think it requires that just lift and shift is not gonna work. >>Mascar, thank you for coming on, spending the time to come in and share with our community and being part of Super Cloud 22. We really appreciate, we're gonna keep this open. We're gonna keep this conversation going even after the event, to open up and look at the structural changes happening now and continue to look at it in the open in the community. And we're gonna keep this going for, for a long, long time as we get answers to the problems that customers are looking for with cloud cloud computing. I'm Sean Feer with Super Cloud 22 in the Cube. Thanks for watching. >>Thank you. Thank you, John. >>Hello. Welcome back. This is the end of our program, our special presentation with Platform nine on cloud native at scale, enabling the super cloud. We're continuing the theme here. You heard the interviews Super Cloud and its challenges, new opportunities around the solutions around like Platform nine and others with Arlon. This is really about the edge situations on the internet and managing the edge multiple regions, avoiding vendor lock in. This is what this new super cloud is all about. The business consequences we heard and and the wide ranging conversations around what it means for open source and the complexity problem all being solved. I hope you enjoyed this program. There's a lot of moving pieces and things to configure with cloud native install, all making it easier for you here with Super Cloud and of course Platform nine contributing to that. Thank you for watching.

>>Hi, welcome to this cube conversation here in Palo Alto, California. I'm John fur, host of the cube here at our headquarters on the west coast in Palo Alto, California. Got a great news guest here. Matt McGill, Wayne managing director of Madrona venture group is here with me on the big news and drone raising their record 690 million fund and partnering with their innovative founders. Matt, thanks for coming on and, and talking about the news and congratulations on the dry powder. >>Well, Hey, thanks so much, John. Appreciate you having me on the show. >>Well, great news here. Oley validation. We're in a new market. Everyone's talking about the new normal, we're talking about a recession inflation, but yet we've been reporting that this is kind of the first generation that cloud hyperscale economic scale and technical benefits have kind of hit any kind of economic downturn. If you go back to to 2008, our last downturn, the cloud really hasn't hit that tipping point. Now the innovation, as we've been reporting with our startup showcases and looking at the results from the hyperscalers, this funding news is kind of validation that the tech society intersection is working. You guys just get to the news 430 million in the Madrona fund nine and 200. And I think 60 million acceleration fund three, which means you're gonna go stay with your roots with seed early stage and then have some rocket fuel for kind of the accelerated expansion growth side of it. Not like late stage growth, but like scaling growth. This is kind of the news. Is that right? >>That's right. You know, we, we've had a long time strategy over 25 years here in Seattle of being early, early stage. You know, it's like our friends at Amazon like to say is, well, we're there at day one and we wanna help build companies for the long run for over 25 years. We've been doing that in Seattle. And I think one of the things we've realized, I mean, this is, these funds are the largest funds ever raised by a Seattle based venture capital firm and that's notable in and of itself. But we think that's the reason is because Seattle has continued to innovate in areas like consumer internet software cloud, of course, where the cloud capital of the world and increasingly the applications of machine learning. And so with all that combination, we believe there's a ton more companies to be built here in the Pacific Northwest and in Seattle in particular. And then through our acceleration fund where we're investing in companies anywhere in the country, in fact, anywhere in the world, those are the kinds of companies that want to have the Seattle point of view. They don't understand how to work with Amazon and AWS. They don't understand how to work with Microsoft and we have some unique relationships in those places and we think we can help them succeed in doing that. >>You know, it's notable that you guys in particular have been very close with Jeff Bayo Andy Jesse, and the success of ABUS as well as Microsoft. So, you know, Seattle has become cloud city. Everyone kind of knows that from a cloud perspective, obviously Microsoft's roots have been there for a long, long time. You go back, I mean, August capital, early days, funding Microsoft. You remember those days not to date myself, but you know, Microsoft kind of went up there and kind of established it a Amazon there as well. Now you got Google here, you got Facebook in the valley. You guys are now also coming down. This funding comes on the heels of you appointing a new managing director here in Palo Alto. This is now the migration of Madrona coming into the valley. Is that right? Is that what we're seeing? >>Well, I think what we're trying to do is bring the things that we know uniquely from Seattle and the companies here down to Silicon valley. We've got a terrific partner in Karama Hend, Andrew he's somebody that we have worked together with over the years, co-investing in companies. So we knew him really well. It was a bit opportunistic for us, but what we're hearing over and over again is a lot of these companies based in the valley, based in other parts of the country, they don't know really how to best work with the Microsoft and Amazons are understand the services that they offer. And, you know, we have that capability. We have those relationships. We wanna bring that to bear and helping build great companies. >>What is your expectation on the Silicon valley presence here? You can kind of give a hint here kind of a gateway to Seattle, but you got a lot of developers here. We just reported this morning that MEA just open source pie, torch to the Linux foundation again, and Mary material kind of trend we are seeing open source now has become there's no debate anymore has become the software industry. There's no more issue around that. This is real. I >>Think that's right. I mean, you know, once, you know, Satya became CEO, Microsoft, and they started embracing open source, you know, that was gonna be the last big tech holdout. We think open source is very interesting in terms of what it can produce and create in terms of next generation, innovative innovation. It's great to see companies like Facebook like Uber and others that have had a long track record of open source capabilities. But what we're also seeing is you need to build businesses around that, that a lot of enterprises don't wanna buy just the open source and stitch it together themselves. They want somebody to do it with them. And whether that's the way that, you know, companies like MongoDB have built that out over time or that's, you know, or elastic or, you know, companies like opt ML and our portfolio, or even the big cloud, you know, hyperscalers, you know, they are increasingly embracing open source and building finished services, managed services on top of it. So that's a big wave that we've been investing in for a number of years now and are highly confident gonna >>Continue. You know, I've been a big fan of Pacific Northwest for a while. You know, love going up there and talking to the folks at Microsoft and Amazon and AWS, but there's been a big trend in venture capital where a lot of the, the later stage folks, including private equity have come in, you seen tiger global even tiger global alumni, that the Cubs they call them, you know, they're coming down and playing in the early state and the results haven't been that good. You guys have had a track record in your success. Again, a hundred percent of your institutional investors have honed up with you on this two fund strategy of close to 700 million. What's this formula says, why aren't they winning what's is it, they don't have the ecosystem? Is it they're spraying and praying without a lot of discipline? What's the dynamic between the folks like Madrona, the Neas of the world who kind of come in and Sequoia who kind of do it right, right. Come in. And they get it done in the right way. The early stage. I just say the private equity folks, >>You know, I think that early stage venture is a local business. It is a geographically proximate business when you're helping incredible founders, try to really dial in that early founder market fit. This is before you even get to product market fit. And, and so the, the team building that goes on the talking to potential customers, the ITER iterating on business strategy, this is a roll up your sleeves kind of thing. It's not a financial transaction. And so what you're trying to do is have a presence and an understanding, a prepared mind of one of the big themes and the kinds of founders that with, you know, our encouragement and our help can go build lasting companies. Now, when you get to a, a, a later stage, you know, you get to that growth stage. It is generally more of a financial, you know, kind of engineering sort of proposition. And there's some folks that are great at that. What we do is we support these companies all the way through. We reserve enough capital to be with them at the seed stage, the series B stage the, you know, the crossover round before you go public, all of those sorts of things. And we love partnering with some of these other people, but there's a lot of heavy lifting at the early, early stages of a business. And it's, it's not, I think a model that everybody's architected to do >>Well, you know, trust becomes a big factor in all this. You kind of, when you talk about like that, I hear you speaking. It makes me think of like trusted advisor meets money, not so much telling people what to do. You guys have had a good track record and, and being added value, not values from track. And sometimes that values from track is getting in the way of the entrepreneur by, you know, running the certain meetings, driving board meetings and driving the agenda that you see to see that trend where people try too hard and that a force function, the entrepreneur we're living in a world now where everyone's talking to each other, you got, you know, there's no more glass door it's everyone's on Twitter, right? So you can see some move, someone trying to control the supply chain of talent by term sheet, overvaluing them. >>You guys are, have a different strategy. You guys have a network I've noticed that Madrona has attracted them high end talent coming outta Microsoft outta AWS season, season, senior talent. I won't say, you know, senior citizens, but you know, people have done things scaled up businesses, as well as attract young talent. Can you share with our audience that dynamic of the, the seasoned veterans, the systems thinkers, the ones who have been there done that built software, built teams to the new young entrepreneurs coming in, what's the dynamic, like, how do you guys look at at those networks? How do you nurture them? Could you share your, your strategy on how you're gonna pull all this together, going forward? >>You know, we, we think a lot about building the innovation ecosystem, like a phrase around here that you hear a lot is the bigger pie theory. How do we build the bigger pie? If we're focusing on building the bigger pie, there'll be plenty of that pie for Madrona Madrona companies. And in that mindset says, okay, how are we gonna invest in the innovation ecosystem? And then actually to use a term, you know, one of our founders who unfortunately passed away this year, Tom Aber, he had just written a book called flywheel. And I think it embodies this mindset that we have of how do you create that flywheel within a community? And of course, interestingly enough, I think Tom both learned and contributed to that. He was on the board of Amazon for almost 20 years in helping build some of the flywheels at Amazon. >>So that's what we carry forward. And we know that there's a lot of value in experiential learning. And so we've been fortunate to have some folks, you know, that have worked at some of those, you know, kind iconic companies, join us and find that they really love this company building journey. We've also got some terrific younger folks that have, you know, some very fresh perspectives and a lot of, a lot of creativity. And they're bringing that together with our team overall. And you know, what we really are trying to do at the end of the day is find incredible founders who wanna build something lasting, insignificant, and provide our kind of our time, our best ideas, our, our perspective. And of course our capital to help them be >>Successful. I love the ecosystem play. I think that's a human capital game too. I like the way you guys are thinking about that. I do wanna get your reaction, cause I know you're close to Amazon and Microsoft, but mainly Jeff Bezos as well. You mentioned your, your partner who passed away was on the board. A lot of great props on and tributes online. I saw that, I know I didn't know him at all. So I really can't comment, but I did notice that Bezos and, and jazz in particular were complimentary. And recently I just saw Bezos comment on Twitter about the, you know, the Lord of the rings movie. They're putting out the series and he says, you gotta have a team. That's kinda like rebels. I'm paraphrasing, cuz these folks never done a movie like this before. So they're, they're getting good props and reviews in this new world order where entrepreneurs gotta do things different. >>What's the one thing that you think entrepreneurs need to do different to make this next startup journey different and successful because the world is different. There's not a lot of press to relate to Andy Jassey even on stage last week in, in, in LA was kind of, he's not really revealing. He's on his talking points, message, the press aren't out there and big numbers anymore. And you got a lot of different go-to market strategies, omnichannel, social different ways to communicate to customers. Yeah. So product market fit is becomes big. So how do you see this new flywheel emerging for those entrepreneurs have to go out there, roll up their sleeves and make it happen. And what kind of resources do you think they need to be successful? What are you guys advocating? >>Well, you know, what's really interesting about that question is I've heard Jeff say many times that when people ask him, what's gotta be different. He, he reminds them to think about what's not gonna change. And he usually starts to then talk about things like price, convenience, and selection. Customer's never gonna want a higher price, less convenience, smaller selection. And so when you build on some of those principles of, what's not gonna change, it's easier for you to understand what could be changing as it relates to the differences. One of the biggest differences, I don't think any of us have fully figured out yet is what does it mean to be productive in a hybrid work mode? We happen to believe that it's still gonna have a kernel of people that are geographically close, that are part of the founding and building in the early stages of a company. >>And, and it's an and equation that they're going to also have people that are distributed around the country, perhaps around the world that are some of the best talent that they attract to their team. The other thing that I think coming back to what remains the same is being hyper focused on a certain customer and a certain problem that you're passionate about solving. And that's really what we look for when we look for this founder market fit. And it can be a lot of different things from the next generation water bottle to a better way to handle deep learning models and get 'em deployed in the cloud. If you've got that passion and you've got some inkling of the skill of how to build a better solution, that's never gonna go away. That's gonna be enduring, but exactly how you do that as a team in a hybrid world, I think that's gonna be different. >>Yeah. One thing that's not changing is that your investor, makeup's not changing a hundred percent of your existing institutional investors have signed back on with you guys and your oversubscribed, lot of demand. What is your flywheel success formula? Why is Tron is so successful? Can you share some feedback from your investors? What are they saying? Why are they re-upping share some inside baseball or anecdotal praise? >>Well, I think it's very kind to you to frame it that way. I mean, you know, it does for investors come back to performance. You know, these are university endowments and foundations that have a responsibility to, to generate great returns. And we understand that and we're very aligned with that. I think to be specific in the last couple years, they appreciated that we were also not holding onto our, our stocks forever, that we actually made some thoughtful decisions to sell some shares of companies like Smartsheet and snowflake and accolade in others, and actually distribute capital back to them when things were looking really, really good. But I think the thing, other thing that's very important here is that we've created a flywheel with our core strategy being Seattle based and then going out from there to try to find the best founders, build great companies with them, roll up our sleeves in a productive way and help them for the long term, which now leads to multiple generations of people, you know, at those companies. And beyond that we wanna be, you know, partner with and back again. And so you create this flywheel by having success with people in doing it in a respectful. And as you said earlier, a trusted way, >>What's the message for the Silicon valley crowd, obviously bay area, Silicon valley, Palo Alto office, and the center of it. Obviously you got them hybrid workforce hybrid venture model developing what's the goals. What's the message for Silicon valley? >>Well, our message for folks in Silicon valley is the same. It's always been, we we're excited to partner with them largely up here again, cause this is still our home base, but there'll be a, you know, select number of opportunities where we'll get a chance to partner together down in Silicon valley. And we think we bring something different with that deep understanding of cloud computing, that deep understanding of applied machine learning. And of course, some of our unique relationships up here that can be additive to what the they've already done. And some of them are just great partners and have built, you know, help build some really incredible companies over >>The years. Matt, I really appreciate you taking the time for this interview, given them big news. I guess the question on everyone's mind, certainly the entrepreneur's mind is how do I get some of that cash you have and put it into work for my opportunity. One what's the investment thesis can take a minute to put the plug in for the firm. What are you looking to invest in? What's the thesis? What kind of entrepreneurs you're looking for? I know fund one is seed fund nine is seed to, to a and B and the second one is beyond B and beyond for growth. What's the pitch. What's the pitch. >>Yeah. Well you can, you can think of us as you know, any stage from pre-seed to series seed. You know, we'll make a new investment in companies in all of those stages. You know, I think that, you know, the, the core pitch, you know, to us is, you know, your passion for the, for the problem that you're trying to, trying to get solved. And we're of course, very excited about that. And you know, at, at, at the end of the day, you know, if you want somebody that has a distinct point of view on the market that is based up here and can roll up their sleeves and work alongside you. We're, we're, we're the ones that are more than happy to do that. Proven track record of doing that for 25 plus years. And there's so much innovation ahead. There's so many opportunities to disrupt to pioneer, and we're excited to be a part of working with great founders to do that. >>Well, great stuff. We'll see you ATS reinvent coming up shortly and your annual get together. You always have your crew down there and, and team engaging with some of the cloud players as well. And looking forward to seeing how the Palo Alto team expands out. And Matt, thanks for coming on the cube. Appreciate your time. >>Thanks very much, John. Appreciate you having me look forward to seeing you at reinvent. >>Okay. Matt, Matt here with Madrona venture group, he's the partner managing partner Madrona group raises 690 million to fund nine and, and, and again, and big funds for accelerated growth fund. Three lot of dry powder. Again, entrepreneurship in technology is scaling. It's not going down. It's continuing to accelerate into this next generation super cloud multi-cloud hybrid cloud world steady state. This is the cubes coverage. I'm John for Silicon angle and host of the cube. Thanks for watching.

>>Hello, and welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four, the ongoing series covering exciting startups from the AWS ecosystem to talk about cyber security. I'm your host, John feer. And today we're excited to join by a Mediatel Walker, CEO of Quin security and sub IER, vice president of product management of sequence security gentlemen, thanks for joining us today on this showcase. >>Thank you, John PRAs. >>So the title of this session is continuous API protection life cycle to discover, detect, and defend security. APIs are part of it. They're hardened, everyone's using them, but they're they're target for malicious behavior. This is the focus of this segment. You guys are in the leading edge of this. What are the biggest challenges for organizations right now in assessing their security risks? Because you're seeing APIs all over the place in the news, just even this week, Twitter had a whistleblower come out from the security group, talking about their security plans, misleading the FTC on the bots and some of the malicious behavior inside the API interface of Twitter. This is really a mainstream Washington post is reporting on it. New York times, all the global outlets are talking about this story. This is the risk. I mean, yeah, this is what you guys do protect against this. >>Yeah, this is absolutely top of mind for a lot of security folks today. So obviously in the media and the type of attack that that is being discussed with this whistleblower coming out is called reputation bombing. This is not new. This has been going on since I would say at least eight to 10 years where the, the bad actors are using bots or automation and ultimately using APIs on these large social media platforms, whether it's Facebook, whether it's Twitter or some other social media platform and messing with the reputation system of those large platforms. And what I mean by that is they will do fake likes, fake commenting, fake retweeting in the case of Twitter. And what that means is that things that are, should not be very popular, all of a sudden become popular. That that way they're able to influence things like elections, shopping habits, personnel. >>We, we work with similar profile companies and we see this all the time. We, we mostly work on some of the secondary platforms like dating and other sort of social media platforms around music sharing and things like video sharing. And we see this all the time. These, these bots are bad. Actors are using bots, but ultimately it's an API problem. It's not just a bot problem. And that's what we've been trying to sort of preach to the world, which is your bot problem is subset of your API security challenges that you deal as an organization. >>You know, IMIA, we talked about this in the past on a previous conversation, but this really is front and center mainstream for the whole world to see around the challenges. All companies face, every CSO, every CIO, every board member organizations out there looking at this security posture that spans not just information technology, but physical and now social engineering. You have all kinds of new payloads of malicious behavior that are being compromised through, through things like APIs. This is not just about CSO, chief information security officer. This is chief security officer issues. What's your reaction >>Very much so I think the, this is a security problem, but it's also a reputation problem. In some cases, it's a data governance problem. We work with several companies which have very restrictive data governance and data regulations or data residency regulations there to conform to those regulations. And they have to look at that. It's not just a CSO problem anymore. In case of the, the news of the day to day, this is a platform problem. This goes all the way to the, that time CTO of Twitter. And now the CEO of Twitter, who was in charge of dealing with these problems. We see as just to give you an example, we, we work, we work with a similar sort of social media platform that allows Oop based login to their platform that is using tokens. You can sort of sign in with Facebook, sign in with Twitter, sign in with Google. These are API keys that are generated and trusted by these social media platforms. When we saw that Facebook leaked about 50 million of these login credentials or API keys, this was about three, four years ago. I wrote a blog about it. We saw a huge spike in those API keys being used to log to other social media platforms. So although one social platform might be taking care of its, you know, API or what problem, if something else gets reached somewhere else, it has a cascading impact on a variety of platforms. >>You know, that's a really interesting dynamic. And if you think about just the token piece that you mentioned, that's kind of under the coverage, that's a technology challenge, but also you get in the business logic. So let's go back and, and unpack that, okay, they discontinue the tokens. Now they're being reused here. In the case of Twitter, I was talking to an executive here in Silicon valley and they said, yeah, it's a cautionary tale, for sure. Although Twitter's a unique situation, but they abstract out the business value and say, Hey, they had an M and a deal on the table. And so if someone wants to unwind that deal, all I gotta say is, Hey, there's a bot problem. And now you have essentially new kinds of risk in the business have nothing to do with some sign the technology, okay. They got a security breach, but here with Twitter, you have an, an, an M and a deal, an acquisition that's being contested because of the, the APIs. So, so if you're in business, you gotta think to yourself, what am I risking with my API? So every organization should be assessing their security risks, tied to their APIs. This is a huge awakening for them. Where should they start? And that's the, that's the core question. Okay. You got my attention risks with the API. What do I do? >>So when I talked to you in my previous interview, the start is basically knowing what to, in most cases, you see these that are hitting the wire much. Every now there is a major in cases you'll find these APIs are targeted, that are not poorly protected. They're absolutely just not protected at all, which means the security team or any sort of team that is responsible for protecting these APIs are just completely unaware of these APIs being there in the first place. And this is where we talk about the shadow it or shadow API problem. Large enterprises have teams that are geo distributed, and this problem is escalated after the pandemic even more because now you have teams that are completely distributed. They do M and a. So they acquire new companies and have no visibility into their API or security practices. And so there are a lot of driving factors why these APIs are just not protected and, and just unknown even more to the security team. So the first step has to be discover your API attack surface, and then prioritize which APIs you wanna target in terms of runtime protection. >>Yeah. I wanna dig into that API kind of attack surface area management, runtime monitoring capability in a second, but so I wanna get you in here too, because we're talking about APIs, we're talking about attacks. What does an API attack look like? >>Yeah, that's a very good question, John, there are really two different forms of attacks of APIs, one type of attack, exploits, APIs that have known vulnerabilities or some form of vulnerabilities. For instance, APIs that may use a weak form of authentication or are really built with no authentication at all, or have some sort of vulnerability that makes them very good targets for an attacker to target. And the second form of attack is a more subtle one. It's called business logic abuse. It's, it's utilizing APIs in completely legitimate manner manners, but exploiting those APIs to exfiltrate information or key sensitive information that was probably not thought through by the developer or the designers or those APIs. And really when we do API protection, we really need to be able to handle both of those scenarios, protect against abuse of APIs, such as broken authentication, or broken object level authorization APIs with that problem, as well as protecting APIs from business logic abuse. And that's really how we, you know, differentiate against other vendors in this >>Market. So just what are the, those key differentiated ways to identify the, in the malicious intents with APIs? Can you, can you just summarize that real quick, the three ways? >>Sure. Yeah, absolutely. There are three key ways that we differentiate against our competition. One is in the, we have built out a, in the ability to actually detect such traffic. We have built out a very sophisticated threat intelligence network built over the entire lifetime of the company where we have very well curated information about malicious infrastructures, malicious operators around the world, including not just it address ranges, but also which infrastructures do they operate on and stuff like that, which actually helps a lot in, in many environments in especially B2C environments, that alone accounts for a lot of efficacy for us in detecting our weed out bad traffic. The second aspect is in analyzing the request that are coming in the API traffic that is coming in and from the request itself, being able to tell if there is credential abuse going on or credential stuffing going on or known patterns that the traffic is exhibiting, that looks like it is clearly trying to attack the attack, the APM. >>And the third one is, is really more sophisticated as they go farther and farther. It gets more sophisticated where sequence actually has a lot of machine learning models built in which actually profile the traffic that is coming in and separate. So the legitimate or learns the legitimate traffic from the anomalous or suspicious traffic. So as the traffic, as the API requests are coming in, it automatically can tell that this traffic does not look like legitimate traffic does not look like the traffic that this API typically gets and automatically uses that to figure out, okay, where is this traffic coming from? And automatically takes action to prevent that attack? >>You know, it's interesting APIs have been part of the goodness of cloud and cloud scale. And it reminds me of the old Andy Grove quote, founder of, in one of the founders of Intel, you know, let chaos, let, let the chaos happen, then reign it in it's APIs. You know, a lot of people have been creating them and you've got a lot of different stakeholders involved in creating them. And so now securing them and now manage them. So a lot of creation now you're starting to secure them and now you gotta manage 'em. This all is now big focus. As you pointed out, what are some of the dynamics that customers who have to deal with on the product side and, and organization, let, let chaos rain, and then rain in the chaos, as, as the saying goes, what, what do companies do? >>Yeah. Typically companies start off with like, like a mayor talked about earlier. Discovery is really the key thing to start with, like figuring out what your API attack surfaces and really getting your arms around that problem. And typically we are finding customers start that off from the security organization, the CSO organization to really go after that problem. And in some cases, in some customers, we even find like dedicated centers of excellence that are created for API security, which go after that problem to be able to get their arms around the whole API attack surface and the API protection problem statement. So that's where usually that problem starts to get addressed. >>I mean, organizations and your customers have to stop the attacks. A lot of different techniques, you know, run time. You mentioned that earlier, the surface area monitoring, what's the choice. What's the, where are, where are, where is everybody? Is everyone in the, in the boiling water, like the frog and boiling water or they do, they know it's happening? Like what did they do? What's their opportunity to get in >>Position? Yeah. So I, I think let's take a step back a little bit, right? What has happened is if you draw the cloud security market, if you will, right. Which is the journey to the cloud, the security of these applications or APIs at a container level, in terms of vulnerabilities and, and other things that market grew with the journey to the cloud, pretty much locked in lockstep. What has happened in the API side is the API space has kind of lacked behind the growth and explosion in the API space. So what that means is APIs are getting published way faster than the security teams are able to sort of control and secure them. APIs are getting published in environments that the security completely unaware of. We talked about in the past about the parameter, the parameter, as we know, it doesn't exist anymore. It used to be the case that you hit a CDN, you terminate your SSL, you stop your layer three and four DDoS. >>And then you go into the application and do the business logic. That parameter is just gone because it's now could be living in multi-cloud environment. It could be living in the on-prem environment, which is PubNet is friendly. And so security teams that are used to protecting apps, using a perimeter defense plus changes, it's gone. You need to figure out where your perimeter is. And therefore we sort of recommend an approach, which is have a uniform view across all your APIs, wherever they could be distributed and have a single point of control across those with a solution like sequence. And there are others also in this space, which is giving you that uniform view, which is first giving you that, you know, outside and looking view of what APIs to protect. And then let's, you sort of take the journey of securing the API life cycle. >>So I would say that every company now hear me out on this indulges me for a second. Every company in the world will be non perimeter based, except for maybe 5% because of maybe unique reason, proprietary lockdown, information, whatever. But for most, most companies, everyone will be in the cloud or some cloud native, non perimeter based security posture. So the question is, how does your platform fit into that trajectory? And specifically, why are you guys in the position in your mind to help customers solve this API problem? Because again, APIs have been the greatest thing about the cloud, right? Yeah. So the goodness is there because of APS. Now you gotta reign it in reign in the chaos. Yeah. What, what about your platform share? What is it, why is it win? Why should customers care about this? >>Absolutely. So if you think about it, you're right, the parameter doesn't exist. People have APIs deployed in multiple environments, multicloud hybrid, you name it sequence is uniquely positioned in a way that we can work with your environment. No matter what that environment is. We're the only player in this space that can protect your APIs purely as a SA solution or purely as an on-prem deployment. And that could be a SaaS platform. It doesn't need to be RackN, but we also support that and we could be a hybrid deployment. We have some deployments which are on your prem and the rest of this solution is in our SA. If you think about it, customers have secured their APIs with sequence with 15 minutes, you know, going live from zero to life and getting that protection instantaneously. We have customers that are processing a billion API calls per day, across variety of different cloud environments in sort of six different brands. And so that scale, that flexibility of where we can plug into your infrastructure or be completely off of your infrastructure is something unique to sequence that we offer that nobody else is offering >>Today. Okay. So I'll be, I'll be a naysayer. Yeah, look, it, we are perfectly coded APIs. We are the best in the business. We're locked down. Our APIs are as tight as a drum. Why do I need you? >>So that goes back to who's answer. Of course, >>Everyone's say that that's, that's great, but that's my argument. >>There are two types of API attacks. One is a tactic problem, which is exploiting a vulnerability in an API, right? So what you're saying is my APIs are secure. It does not have any vulnerability I've taken care of all vulnerabilities. The second type of attack that targets APIs is the business logic. Use this stuff in the news this week, which is the whistleblower problem, which is, if you think APIs that Twitter is publishing for users are perfectly secure. They are taking care of all the vulnerabilities and patching them when they find new ones. But it's the business logic of, you know, REWE liking or commenting that the bots are targeting, which they have no against. Right. And then none of the other social networks too. Yeah. So there are many examples. Uber wrote a program to impersonate users in different geo locations to find lifts, pricing, and driver information and passenger information, completely legitimate use of APIs for illegitimate, illegitimate purpose using bots. So you don't need bots by the way, don't, don't make this about bot versus not. Yeah. You can use APIs sort of for the, the purpose that they're not designed for sort of exploiting their business logic, either using a human interacting, a human farm, interacting with those APIs or a bot form targeting those APIs, I think. But that's the problem when you have, even when you've secured all your problem, all your APIs, you still have to worry about these of challenges. >>I think that's the big one. I think the business logic one, certainly the Twitter highlights that the Uber example is a good one. That is basically almost the, the backlash of having a simplistic API, which people design to. Right. Yeah. You know, as you point out, Twitter is very simple API, hardened, very strong security, but they're using it to maliciously manipulate what's inside. So in a way that perimeter's dead too. Right. So how do you stop that business logic? What's the, what's the solution what's the customer do about that? Because their goal is to create simple, scalable APIs. >>Yeah. I'll, I'll give you a little bit, and then I think Subaru should maybe go into a little bit of the depth of the problem, but what I think that the answer lies in what Subaru spoke earlier, which is our ML. AI is, is good at profiling plus split between the API users, are these legitimate users, humans versus bots. That's the first split we do. The split second split we do is even when these, these are classified users as bots, we will say there are some good bots that are necessary for the business and bad bots. So we are able to split this across three types of users, legitimate humans, good bots and bad bots. And just to give you an example of good bots is there are in the financial work, there are aggregators that are scraping your data and aggregating for end users to consume, right? Your, your, and other type of financial aggregators FinTech companies like MX. These are good bots and you wanna allow them to, you know, use your APIs, whereas you wanna stop the bad bots from using your APIs super, if you wanna add so, >>So good bots versus bad bots, that's the focus. Go ahead. Weigh in, weigh in on your thought on this >>Really breaks down into three key areas that we talk about here, sequence, right? One is you start by discovering all your APIs. How many APIs do I have in my environment that ly immediately highlight and say, Hey, you have, you know, 10,000 APIs. And that usually is an eye opener to many customers where they go, wow. I thought we had a 10th of that number. That usually is an eyeopener for them to, to at least know where they're at. The second thing is to tell them detection information. So discover, detect, and defend detect will tell them, Hey, your APIs are getting traffic from. So and so it addresses so and so infrastructure. So and so countries and so on that usually is another eye opener for them. They then get to see where their API traffic is coming from. Let's say, if you are a, if you're running a pizza delivery service out of California and your traffic is coming from Eastern Europe to go, wait a minute, nobody's trying, I'm not, I'm not, I don't deliver pizzas in Eastern Europe. Why am I getting traffic from that part of the world? So that sort of traffic immediately comes up and it will tell you that it is hitting your unauthenticated API. It is hitting your API. That has, that is vulnerable to a broken object level, that authorization, vulnerable be and so on. >>Yeah, I think, and >>Then comes the different aspect. Yeah. The different aspect is where you can take action and say, I wanna block certain types of traffic, or I wanna rate limit certain types of traffic. If, if you're seeing spikes there or you could maybe insert header so that it passes on to the end application and the application team can use that bit to essentially take a, a conscious response. And so, so the platform is very flexible in allowing them to take an action that suits their needs. >>Yeah. And I think this is the big trend. This is why I like what you guys are doing. One APIs we're built for the goodness of cloud. They're now the plumbing, you know, anytime you see plumbing involved, connection points, you know, that's pretty important. People are building it out and it has made the cloud what it is. Now, you got a security challenge. You gotta add more intelligence, more smarts to it. This is where I think platform versus tools matter. Can you guys just quickly share your thoughts on that? Cuz a lot of your customers and, and future customers have dealt with the sprawls of all these different tools. Right? I got a tool for this. I got a tool for that, but people are gravitating towards platforms, but how many platforms can a customer have? So again, this brings up the point point around how you guys are engaging with customers. Can you share your thoughts on tooling platforms? Your customers are constantly inundated with the same tsunami. Isn't new thing. Why, what, how should they look at this? >>Yeah, I mean, we don't wanna be, we don't wanna add to that alert fatigue problem that affects much of the cybersecurity industry by generating a whole bunch of alerts and so on. So what we do is we actually integrate very well with S IEM systems or so systems and allow customers to integrate the information that we are detecting or mitigating and feed them onto enterprise systems like a Splunk or a Datadog where they may have sophisticated processes built in to monitor, you know, spikes in anomalous traffic or actions that are taken by sequence. And that can be their dashboard where a whole bunch of alerting and reporting actually happens. So we play in the security ecosystem very well by integrating with other products and integrate very tightly with them, right outta the box. >>Okay. Mia, this is a wrap up now for the showcase. Really appreciate you guys sharing your awesome technology and very relevant product for your customers and where we are right now in this we call Supercloud or now multi-cloud or hybrid world of cloud. Share a, a little bit about the company, how people can get involved in your solution, how they can consume it and things they should know about, about sequence security. >>Yeah, we've been on this journey, an exciting journey it's been for, for about eight years. We have very large fortune 100 global 500 customers that use our platform on a daily basis. We have some amazing logos, both in Europe and, and, and in us customers are, this is basically not the shelf product customers not only use it, but depend on sequence. Several retailers. We are sitting in front of them handling, you know, black Friday, cyber, Monday, Christmas shopping, or any sort of holiday seasonality shopping. And we have handled that the journey starts by, by just simply looking at your API attack surface, just to a discover call with sequence, figure out where your APIs are posted work with you to prioritize how to protect them in a sort of a particular order and take the whole life cycle with sequence. This is, this is an exciting phase exciting sort of stage in the company's life. We just raised a very sort of large CDC round of funding in December from Menlo ventures. And we are excited to see, you know, what's next in, in, in the next, you know, 12 to 18 months. It certainly is the, you know, one of the top two or three items on the CSOs, you know, budget list for next year. So we are extremely busy, but we are looking for, for what the next 12 to 18 months are, are in store for us. >>Well, congratulations to all the success. So will you run the roadmap? You know, APIs are the plumbing. If you will, you know, they connection points, you know, you want to kind of keep 'em simple, as they say, keep the pipes dumb and make the intelligence around it. You seem to see more and more intelligence coming around, not just securing it, but does, where does this go in your mind? Where, where do we go beyond once we secure everything and manage it properly, APRs, aren't going away, they're only gonna get better and smarter. Where's the intelligence coming share a little bit. >>Absolutely. Yeah. I mean, there's not a dull moment in the space. As digital transformation happens to most enterprise systems, many applications are getting transformed. We are seeing an absolute explosion in the volume of APIs and the types of APIs as well. So the applications that were predominantly limited to data centers sort of deployments are now splintered across multiple different cloud environments are completely microservices based APIs, deep inside a Kubernetes cluster, for instance, and so on. So very exciting stuff in terms of proliferation of volume of APIs, as well as types of APIs, there's nature of APIs. And we are building very sophisticated machine learning models that can analyze traffic patterns of such APIs and automatically tell legitimate behavior from anomalous or suspicious behavior and so on. So very exciting sort of breadth of capabilities that we are looking at. >>Okay. I mean, yeah. I'll give you the final words since you're the CEO for the CSOs out there, the chief information security officers and the chief security officers, what do you want to tell them? If you could give them a quick shout out? What would you say to them? >>My shout out is just do an assessment with sequence. I think this is a repeating thing here, but really get to know your APIs first, before you decide what and where to protect them. That's the one simple thing I can mention for thes >>Am. Thank you so much for, for joining me today. Really appreciate it. >>Thank you. >>Thank you. Okay. That is the end of this segment of the eight of his startup showcase. Season two, episode four, I'm John for your host and we're here with sequin security. Thanks for watching.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's day one coverage of HPE discover 22 live from the Venetian in Las Vegas. I got a power panel here, Lisa Martin, with Dave Valante, John furrier, Holger Mueller also joins us. We are gonna wrap this, like you've never seen a rap before guys. Lot of momentum today, lot, lot of excitement, about 8,000 or so customers, partners, HPE leaders here. Holger. Let's go ahead and start with you. What are some of the things that you heard felt saw observed today on day one? >>Yeah, it's great to be back in person. Right? 8,000 people events are rare. Uh, I'm not sure. Have you been to more than 8,000? <laugh> yeah, yeah. Okay. This year, this year. I mean, historically, yes, but, um, >>Snowflake was 10. Yeah. >>So, oh, wow. Okay. So 8,000 was my, >>Cisco was, they said 15, >>But is my, my 8,000, my record, I let us down with 7,000 kind of like, but it's in the Florida swarm. It's not nicely. Like, and there's >>Usually what SFI, there's usually >>20, 20, 30, 40, 50. I remember 50 in the nineties. Right. That was a different time. But yeah. Interesting. Yeah. Interesting what people do and it depends how much time there is to come. Right. And know that it happens. Right. But yeah, no, I think it's interesting. We, we had a good two analyst track today. Um, interesting. Like HPE is kind of like back not being your grandfather's HPE to a certain point. One of the key stats. I know Dave always for the stats, right. Is what I found really interesting that over two third of GreenLake revenue is software and services. Now a love to know how much of that services, how much of that software. But I mean, I, I, I, provocate some, one to ones, the HP executives saying, Hey, you're a hardware company. Right. And they didn't even come back. Right. But Antonio said, no, two thirds is, uh, software and services. Right. That's interesting. They passed the one exabyte, uh, being managed, uh, as a, as a hallmark. Right. I was surprised only 120,000 users if I had to remember the number. Right, right. So that doesn't seem a terrible high amount of number of users. Right. So, but that's, that's, that's promising. >>So what software is in there, cuz it's gotta be mostly services. >>Right? Well it's the 70 plus cloud services, right. That everybody's talking about where the added eight of them shockingly back up and recovery, I thought that was done at launch. Right. >>Still who >>Keep recycling storage and you back. But now it's real. Yeah. >>But the company who knows the enterprise, right. HPE, what I've been doing before with no backup and recovery GreenLake. So that was kind of like, okay, we really want to do this now and nearly, and then say like, oh, by the way, we've been doing this all the time. Yeah. >>Oh, what's your take on the installed base of HP. We had that conversation, the, uh, kickoff or on who's their target, what's the target audience environment look like. It certainly is changing. Right? If it's software and services, GreenLake is resonating. Yeah. Um, ecosystems responding. What's their customers cuz managed services are up too Kubernetes, all the managed services what's what's it like what's their it transformation base look like >>Much of it is of course install base, right? The trusted 20, 30 plus year old HP customer. Who's keeping doing stuff of HP. Right. And call it GreenLake. They've been for so many name changes. It doesn't really matter. And it's kind of like nice that you get the consume pain only what you consume. Right. I get the cloud broad to me then the general markets, of course, people who still need to run stuff on premises. Right. And there's three reasons of doing this performance, right. Because we know the speed of light is relative. If you're in the Southern hemisphere and even your email servers in Northern hemisphere, it takes a moment for your email to arrive. It's a very different user experience. Um, local legislation for data, residency privacy. And then, I mean Charles Phillips who we all know, right. Former president of uh, info nicely always said, Hey, if the CIOs over 50, I don't have to sell qu. Right. So there is not invented. I'm not gonna do cloud here. And now I've kind of like clouded with something like HP GreenLake. That's the customers. And then of course procurement is a big friend, right? Yeah. Because when you do hardware refresh, right. You have to have two or three competitors who are the two or three competitors left. Right. There's Dell. Yeah. And then maybe Lenovo. Right? So, so like a >>Little bit channels, the strength, the procurement physicians of strength, of course install base question. Do you think they have a Microsoft opportunity where, what 365 was Microsoft had office before 365, but they brought in the cloud and then everything changed. Does HP have that same opportunity with kind of the GreenLake, you know, model with their existing stuff. >>It has a GreenLake opportunity, but there's not much software left. It's a very different situation like Microsoft. Right? So, uh, which green, which HP could bring along to say, now run it with us better in the cloud because they've been selling much of it. Most of it, of their software portfolio, which they bought as an HP in the past. Right. So I don't see that happening so much, but GreenLake as a platform itself course interesting because enterprise need a modern container based platform. >>I want, I want to double click on this a little bit because the way I see it is HP is going to its installed base. I think you guys are right on say, this is how we're doing business now. Yeah. You know, come on along. But my sense is, some customers don't want to do the consumption model. There are actually some customers that say, Hey, of course I got, I don't have a cash port problem. I wanna pay for it up front and leave me alone. >>I've been doing this since 50 years. Nice. As I changed it, now <laugh> two know >>Money's wants to do it. And I don't wanna rent because rental's more expensive and blah, blah, blah. So do you see that in the customer base that, that some are pushing back? >>Of course, look, I have a German accent, right? So I go there regularly and uh, the Germans are like worried about doing anything in the cloud. And if you go to a board in Germany and say, Hey, we can pay our usual hardware, refresh, CapEx as usual, or should we bug consumption? And they might know what we are running. <laugh> so not whole, no offense against the Germans out. The German parts are there, but many of them will say, Hey, so this is change with COVID. Right. Which is super interesting. Right? So the, the traditional boards non-technical have been hearing about this cloud variable cost OPEX to CapEx and all of a sudden there's so much CapEx, right. Office buildings, which are not being used truck fleets. So there's a whole new sensitivity by traditional non-technical boards towards CapEx, which now the light bulb went on and say, oh, that's the cloud thing about also. So we have to find a way to get our cost structure, to ramp up and ramp down as our business might be ramping up through COVID through now inflation fears, recession, fears, and so on. >>So, okay. HP's, HP's made the statement that anything you can do in the cloud you can do in GreenLake. Yes. And I've said you can't run on snowflake. You can't run Mongo Atlas, you can't run data bricks, but that's okay. That's fine. Let's be, I think they're talking about, there's >>A short list of things. I think they're talking about the, their >>Stuff, their, >>The operating experience. So we've got single sign on through a URL, right. Uh, you've got, you know, some level of consistency in terms of policy. It's unclear exactly what that is. You've got storage backup. Dr. What, some other services, seven other services. If you had to sort of take your best guess as to where HP is now and peg it toward where Amazon was in which year? >>20 14, 20 14. >>Yeah. Where they had their first conference or the second we invent here with 3000 people and they were thinking, Hey, we're big. Yeah. >>Yeah. And I think GreenLake is the building blocks. So they quite that's the >>Building. Right? I mean similar. >>Okay. Well, I mean they had E C, Q and S3 and SQS, right. That was the core. And then the rest of those services were, I mean, base stock was one of that first came in behind and >>In fairness, the industry has advanced since then, Kubernetes is further along. And so HPE can take advantage of that. But in terms of just the basic platform, I, I would agree. I think it's >>Well, I mean, I think, I mean the software, question's a big one. I wanna bring up because the question is, is that software is getting the world. Hardware is really software scales, everything, data, the edge story. I love their story. I think HP story is wonderful Aruba, you know, hybrid cloud, good story, edge edge. But if you look under the covers, it's weak, right? It's like, it's not software. They don't have enough software juice, but the ecosystem opportunity to me is where you plug and play. So HP knows that game. But if you look historically over the past 25 years, HP now HPE, they understand plug and play interoperability. So the question is, can they thread the needle >>Right. >>Between filling the gaps on the software? Yeah. With partners, >>Can they get the partners? Right. And which have been long, long time. Right. For a long time, HP has been the number one platform under ICP, right? Same thing. You get certified for running this. Right. I know from my own history, uh, I joined Oracle last century and the big thing was, let's get your eBusiness suite certified on HP. Right? Like as if somebody would buy H Oracle work for them, right. This 20 years ago, server >>The original exit data was HP. Oracle. >>Exactly. Exactly. So there's this thinking that's there. But I think the key thing is we know that all modern forget about the hardware form in the platforms, right? All modern software has to move to containers and snowflake runs in containers. You mentioned that, right? Yeah. If customers force snowflake and HPE to the table, right, there will be a way to make it work. Right. And which will help HPE to be the partner open part will bring the software. >>I, I think it's, I think that's an opportunity because that changes the game and agility and speed. If HP plays their differentiation, right. Which we asked on their opening segment, what's their differentiation. They got size scale channel, >>What to the enterprise. And then the big benefit is this workload portability thing. Right? You understand what is run in the public cloud? I need to run it local. For whatever reason, performance, local residency of data. I can move that. There that's the big benefit to the ISVs, the sales vendors as well. >>But they have to have a stronger data platform story in my that's right. Opinion. I mean, you can run Oracle and HPE, but there's no reason they shouldn't be able to do a deal with, with snowflake. I mean, we saw it with Dell. Yep. We saw it with, with, with pure and I, if our HPE I'd be saying, Hey, because the way the snowflake deal worked, you probably know this is your reading data into the cloud. The compute actually occurs in the cloud viral HB going snowflake saying we can separate compute and storage. Right. And we have GreenLake. We have on demand. Why don't we run the compute on-prem and make it a full class, first class citizen, right. For all of our customers data. And that would be really innovative. And I think Mongo would be another, they've got OnPrem. >>And the question is, how many, how many snowflake customers are telling snowflake? Can I run you on premise? And how much defo open years will they hear from that? Right? This is >>Why would they deal Dell? That >>Deal though, with that, they did a deal. >>I think they did that deal because the customer came to them and said, you don't exactly that deal. We're gonna spend the >>Snowflake >>Customers think crazy things happen, right? Even, even put an Oracle database in a Microsoft Azure data center, right. Would off who, what as >>Possible snowflake, >>Oracle. So on, Aw, the >>Snow, the snowflakes in the world have to make a decision. Dave on, is it all snowflake all the time? Because what the reality is, and I think, again, this comes back down to the, the track that HP could go up or down is gonna be about software. Open source is now the software industry. There's no such thing as proprietary software, in my opinion, relatively speaking, cloud scale and integrated, integrated integration software is proprietary. The workflows are proprietary. So if they can get that right with the partners, I would focus on that. I think they can tap open source, look at Amazon with open source. They sucked it up and they integrated it in. No, no. So integration is the deal, not >>Software first, but Snowflake's made the call. You were there, Lisa. They basically saying it's we have, you have to be in snowflake in order to get the governance and the scalability, all that other wonderful stuff. Oh, but we we'll do Apache iceberg. We'll we'll open it up. We'll do Python. Yeah. >>But you can't do it data clean room unless you are in snowflake. Exactly. Snowflake on snowflake. >>Exactly. >>But got it. Isn't that? What you heard from AWS all the time till they came out outposts, right? I mean, snowflake is a market leader for what they're doing. Right. So that they want to change their platform. I mean, kudos to them. They don't need to change the platform. They will be the last to change their platform to a ne to anything on premises. Right. But I think the trend already shows that it's going that way. >>Well, if you look at outpost is an signal, Dave, the success of outpost launched what four years ago, they announced it. >>What >>EKS is beating, what outpost is doing. Outpost is there. There's not a lot of buzz and talk to the insiders and the open source community, uh, EKS and containers. To your point mm-hmm <affirmative> is moving faster on, I won't say commodity hardware, but like could be white box or HP, Dell, whatever it's gonna be that scale differentiation and the edge story is, is a good one. And I think with what we're seeing in the market now it's the industrial edge. The back office was gen one cloud back office data center. Now it's hybrid. The focus will be industrial edge machine learning and AI, and they have it here. And there's some, some early conversations with, uh, I heard it from, uh, this morning, you guys interviewed, uh, uh, John Schultz, right? With the world economic 4k birth Butterfield. She was amazing. And then you had Justin bring up a Hoar, bring up quantum. Yes. That is a differentiator. >>HP. >>Yes. Yeah. You, they have the computing shops. They had the R and D can they bring it to the table >>As, as HPC, right. To what they Schultz for of uh, the frontier system. Right. So very impressed. >>So the ecosystem is the key for them is because that's how they're gonna fill the gaps. They can't, they can't only, >>They could, they could high HPC edge piece. I wouldn't count 'em out of that game yet. If you co-locate a box, I'll use the word box, particularly at a telco tower. That's a data center. Yep. Right. If done properly. Yep. So, you know, what outpost was supposed to do actually is a hybrid opportunity. Aruba >>Gives them a unique, >>But the key thing is right. It's a yin and yang, right? It's the ecosystem it's partners to bring those software workload. Absolutely. Right. But HPE has to keep the platform attractive enough. Right. And the key thing there is that you have this workload capability thing that you can bring things, which you've built yourself. I mean, look at the telcos right. Network function, visualization, thousands of man, years into these projects. Right. So if I can't bring it to your edge box, no, I'm not trying to get to your Xbox. Right. >>Hold I gotta ask you since in the Dave too, since you guys both here and Lisa, you know, I said on the opening, they have serious customers and those customers have serious problems, cyber security, ransomware. So yeah. I teach transformation now. Industrial transformation machine learning, check, check, check. Oh, sounds good. But at the end of the day, their customers have some serious problems. Right? Cyber, this is, this is high stakes poker. Yeah. What do you think HP's position for in the security? You mentioned containers, you got all this stuff, you got open source, supply chain, you have to left supply chain issues. What is their position with security? Cuz that's the big one. >>I, I think they have to have a mature attitude that customers expect from HPE. Right? I don't have to educate HP on security. So they have to have the partner offerings again. We're back at the ecosystem to have what probably you have. So bring your own security apart from what they have to have out of the box to do business with them. This is why the shocker this morning was back up in recovery coming. <laugh> it's kind like important for that. Right? Well >>That's, that's, that's more ransomware and the >>More skeleton skeletons in the closet there, which customers should check of course. But I think the expectations HP understands that and brings it along either from partner or natively. >>I, I think it's, I think it's services. I think point next is the point of integration for their security. That's why two thirds is software and services. A lot of that is services, right? You know, you need security, we'll help you get there. We people trust HP >>Here, but we have nothing against point next or any professional service. They're all hardworking. But if I will have to rely on humans for my cyber security strategy on a daily level, I'm getting gray hair and I little gray hair >>Red. Okay. I that's, >>But >>I think, but I do think that's the camera strategy. I mean, I'm sure there's a lot of that stuff that's beginning to be designed in, but I, my guess is a lot of it is services. >>Well, you got the Aruba. Part of the booth was packed. Aruba's there. You mentioned that earlier. Is that good enough? Because the word zero trust is kicked around a lot. On one hand, on the other hand, other conversations, it's all about trust. So supply chain and software is trusting trust, trust and verified. So you got this whole mentality of perimeter gone mentality. It's zero trust. And if you've got software trust, interesting thoughts there, how do you reconcile zero trust? And then I need trust. What's what's you? What are you seeing older on that? Because I ask people all the time, they're like, uh, I'm zero trust or is it trust? >>Yeah. The middle ground. Right? Trusted. The meantime people are man manipulating what's happening in your runtime containers. Right? So, uh, drift control is a new password there that you check what's in your runtime containers, which supposedly impenetrable, but people finding ways to hack them. So we'll see this cat and mouse game going on all the time. Yeah. Yeah. There's always gonna be the need for being in a secure, good environment from that perspective. Absolutely. But the key is edge has to be more than Aruba, right? If yeah. HV goes away and says, oh yeah, we can manage your edge with our Aruba devices. That's not enough. It's the virtual probability. And you said the important thing before it's about the data, right? Because the dirty secret of containers is yeah, I move the code, but what enterprise code works without data, right? You can't say as enterprise, okay, we're done for the day check tomorrow. We didn't persist your data, auditor customer. We don't have your data anymore. So filling a way to transport the data. And there just one last thought, right? They have a super interesting asset. They want break lands for the venerable map R right. Which wrote their own storage drivers and gives you the chance to potentially do something in that area, which I'm personally excited about. But we'll see what happens. >>I mean, I think the holy grail is can I, can I put my data into a cloud who's ever, you know, call it a super cloud and can I, is it secure? Is it governed? Can I share it and be confident that it's discoverable and that the, the person I give it to has the right to use it. Yeah. And, and it's the correct data. There's not like a zillion copies running. That's the holy grail. And I, I think the answer today is no, you can, you can do that maybe inside of AWS or maybe inside of Azure, look maybe certainly inside of snowflake, can you do that inside a GreenLake? Well, you probably can inside a GreenLake, but then when you put it into the cloud, is it cross cloud? Is it really out to the edge? And that's where it starts to break down, but that's where the work is to be done. That's >>The one Exide is in there already. Right. So men being men. Yeah. >>But okay. But it it's in there. Yeah. Okay. What do you do with it? Can you share that data? What can you actually automate governance? Right? Uh, is that data discoverable? Are there multiple copies of that data? What's the, you know, master copy. Here's >>A question. You guys, here's a question for you guys analyst, what do you think the psychology is of the CIO or CSO when HP comes into town with GreenLake, uh, and they say, what's your relationship with the hyperscalers? Cause I'm a CIO. I got my environment. I might be CapEx centric or Hey, I'm open model. Open-minded to an operating model. Every one of these enterprises has a cloud relationship. Yeah. Yeah. What's the dynamic. What do you think the psychology is of the CIO when they're rationalizing their, their trajectory, their architecture, cloud, native scale integration with HPE GreenLake or >>HP service. I think she or he hears defensiveness from HPE. I think she hears HPE or he hears HPE coming in and saying, you don't need to go to the cloud. You know, you could keep it right here. I, I don't think that's the right posture. I think it should be. We are your cloud. And we can manage whether it's OnPrem hybrid in AWS, Azure, Google, across those clouds. And we have an edge story that should be the vision that they put forth. That's the super cloud vision, but I don't hear it >>From these guys. What do you think psycho, do you agree with that? >>I'm totally to make, sorry to be boring, but I totally agree with, uh, Dave on that. Right? So the, the, the multi-cloud capability from a trusted large company has worked for anybody up and down the stack. Right? You can look historically for, uh, past layers with cloud Foundry, right? It's history vulnerable. You can look for DevOps of Hashi coop. You can look for database with MongoDB right now. So if HPE provides that data access, right, with all the problems of data gravity and egres cost and the workability, they will be doing really, really well, but we need to hear it more, right. We didn't hear much software today in the keynote. Right. >>Do they have a competitive offering vis-a-vis or Azure? >>The question is, will it be an HPE offering or will, or the software platform, one of the offerings and you as customer can plug and play, right. Will software be a differentiator for HP, right. And will be close, proprietary to the point to again, be open enough for it, or will they get that R and D format that, or will they just say, okay, ES MES here on the side, your choice, and you can use OpenShift or whatever, we don't matter. That's >>The, that's the key question. That's the key question. Is it because it is a competitive strategy? Is it highly differentiated? Oracle is a highly differentiated strategy, right? Is Dell highly differentiated? Eh, Dell differentiates based on its breadth. What? >>Right. Well, let's try for the control plane too. Dell wants to be an, >>Their, their vision is differentiated. Okay. But their execution today is not >>High. All right. Let me throw, let me throw this out at you then. I'm I'm, I'm sorry. I'm I'm HPE. I wanna be the glue layer. Is that, does that fly? >>What >>Do you mean? The group glue layer? I'll I wanna be, you can do Amazon, but I wanna be the glue layer between the clouds and our GreenLake will. >>What's the, what's the incremental value that, that glue provides, >>Provides comfort and reliability and control for the single pane of glass for AWS >>And comes back to the data. In my opinion. Yeah. >>There, there there's glue levels on the data level. Yeah. And there's glue levels on API level. Right. And there's different vendors in the different spaces. Right. Um, I think HPE will want to play on the data side. We heard lots of data stuff. We >>Hear that, >>But we have to see it. Exactly. >>Yeah. But it's, it's lacking today. And so, Hey, you know, you guys know better than I APIs can be fragile and they can be, there's a lot of diversity in terms of the quality of APIs and the documentation, how they work, how mature they are, what, how, what kind of performance they can provide and recoverability. And so just saying, oh wow. We are living the API economy. You know, the it's gonna take time to brew, chime in here. Hi. >><laugh> oh, so guys, you've all been covering HPE for a long time. You know, when Antonio stood up on stage three years ago and said by 2022, and here we are, we're gonna be delivering everything as a service. He's saying we've, we've done it, but, and we're a new company. Do you guys agree with that? >>Definitely. >>I, yes. Yes. With the caveat, I think, yes. The COVID pandemic slowed them down a lot because, um, that gave a tailwind to the hyperscalers, um, because of the, the force of massive O under forecasting working at home. I mean, everyone I talked to was like, no one forecasted a hundred percent work at home, the, um, the CapEx investments. So I think that was an opportunity that they'd be much farther along if there's no COVID people >>Thought it wasn't impossible. Yeah. But so we had the old work from home thing right. Where people trying to get people fired at IBM and Yahoo. Right. So I would've this question covering the HR side and my other hat on. Right. And I would ask CHS let's assume, because I didn't know about COVID shame on me. Right. I said, big California, earthquake breaks. Right. Nobody gets hurt, but all the buildings have to be retrofitted and checked for seism logic down. So everybody's working from home, ask CHS, what kind of productivity gap hit would you get by forcing everybody working from home with the office unsafe? So one, one gentleman, I won't know him, his name, he said 20% and the other one's going ha you're smoking. It's 40 50%. We need to be in the office. We need to meet it first night. And now we went for this exercise. Luckily not with the California. Right. Well, through the price of COVID and we've seen what it can do to, to productivity well, >>The productivity, but also the impact. So like with all the, um, stories we've done over two years, the people that want came out ahead were the ones that had good cloud action. They were already in the cloud. So I, I think they're definitely in different company in the sense of they, I give 'em a pass. I think they're definitely a new company and I'm not gonna judge 'em on. I think they're doing great. But I think pandemic definitely slowed 'em down that about >>It. So I have a different take on this. I think. So we've go back a little history. I mean, you' said this, I steal your line. Meg Whitman took one for the Silicon valley team. Right. She came in. I don't think she ever was excited that I, that you said, you said that, and I think you wrote >>Up, get tape on that one. She >>Had to figure out how do I deal with this mess? I have EDS. I got PC. >>She never should have spun off the PC, but >>Okay. But >>Me, >>Yeah, you can, you certainly could listen. Maybe, maybe Gerstner never should have gone all in on services and IBM would dominate something other than mainframes. They had think pads even for a while, but, but, but so she had that mess to deal with. She dealt with it and however, they dealt with it, Antonio came in, he, he, and he said, all right, we're gonna focus the company. And we're gonna focus the mission on not the machine. Remember those yeah. Presentations, but you just make your eyes glaze over. We're going all in on Azure service >>And edge. He was all on. >>We're gonna build our own cloud. We acquired Aruba. He made some acquisitions in HPC to help differentiate. Yep. And they are definitely a much more focused company now. And unfortunately I wish Antonio would CEO in 2015, cuz that's really when this should have started. >>Yeah. And then, and if you remember back then, Dave, we were interviewing Docker with DevOps teams. They had composability, they were on hybrid really early. I think they might have even coined the term hybrid before VMware tri-state credit for it. But they were first on hybrid. They had DevOps, they had infrastructure risk code. >>HPE had an HP had an awesome cloud team. Yeah. But, and then, and then they tried to go public cloud. Yeah. You know, and then, you know, just made them, I mean, it was just a mess. The focus >>Is there. I give them huge props. And I think, I think the GreenLake to me is exciting here because it's much better than it was two years ago. When, when we talked to, when we started, it's >>Starting to get real. >>It's, it's a real thing. And I think the, the tell will be partners. If they make that right, can pull their different >>Ecosystem, >>Their scale and their customers and fill the software gas with partners mm-hmm <affirmative> and then create that integration opportunity. It's gonna be a home run if they don't do that, they're gonna miss the operating, >>But they have to have their own to your point. They have to have their own software innovation. >>They have to good infrastructure ways to build applications. I don't wanna build with somebody else. I don't wanna take a Microsoft stack on open source stack. I'm not sure if it's gonna work with HP. So they have to have an app dev answer. I absolutely agree with that. And the, the big thing for the partners is, which is a good thing, right? Yep. HPE will not move into applications. Right? You don't have to have the fear of where Microsoft is with their vocal large. Right. If AWS kind of like comes up with APIs and manufacturing, right. Google the same thing with their vertical push. Right. So HPE will not have the CapEx, but >>Application, >>As I SV making them, the partner, the bonus of being able to on premise is an attractive >>Part. That's a great point. >>Hold. So that's an inflection point for next 12 months to watch what we see absolutely running on GreenLake. >>Yeah. And I think one of the things that came out of the, the last couple events this past year, and I'll bring this up, we'll table it and we'll watch it. And it's early in this, I think this is like even, not even the first inning, the machine learning AI impact to the industrial piece. I think we're gonna see a, a brand new era of accelerated digital transformation on the industrial physical world, back office, cloud data center, accounting, all the stuff. That's applications, the app, the real world from space to like robotics. I think that HP edge opportunity is gonna be visible and different. >>So guys, Antonio Neri is on tomorrow. This is only day one. If you can imagine this power panel on day one, can you imagine tomorrow? What is your last question for each of you? What is your, what, what question would you want to ask him tomorrow? Hold start with you. >>How is HPE winning in the long run? Because we know their on premise market will shrink, right? And they can out execute Dell. They can out execute Lenovo. They can out Cisco and get a bigger share of the shrinking market. But that's the long term strategy, right? So why should I buy HPE stock now and have a good return put in the, in the safe and forget about it and have a great return 20 years from now? What's the really long term strategy might be unfair because they, they ran in survival mode to a certain point out of the mass post equipment situation. But what is really the long term strategy? Is it more on the hardware side? Is it gonna go on the HPE, the frontier side? It's gonna be a DNA question, which I would ask Antonio. >>John, >>I would ask him what relative to the macro conditions relative to their customer base, I'd say, cuz the customers are the scoreboard. Can they create a value proposition with their, I use the Microsoft 365 example how they kind of went to the cloud. So my question would be Antonio, what is your core value proposition to CIOs out there who want to transform and take a step function, increase for value with HPE? Tell me that story. I wanna hear. And I don't want to hear, oh, we got a portfolio and no, what value are you enabling your customers to do? >>What and what should that value be? >>I think it's gonna be what we were kind of riffing on, which is you have to provide either what their product market fit needs are, which is, are you solving a problem? Is it a pain point is a growth driver. Uh, and what's the, what's that tailwind. And it's obviously we know at cloud we know edge. The story is great, but what's the value proposition. But by going with HPE, you get X, Y, and Z. If they can explain that clearly with real, so qualitative and quantitative data it's home >>Run. He had a great line of the analyst summit today where somebody asking questions, I'm just listening to the customer. So be ready for this Steve jobs photo, listening to the customer. You can't build something great listening to the customer. You'll be good for the next quarter. The next exponential >>Say, what are the customers saying? <laugh> >>So I would make an observation. And my question would, so my observation would be cloud is growing collectively at 35%. It's, you know, it's approaching 200 billion with a big, big four. If you include Alibaba, IBM has actually said, Hey, we're gonna gr they've promised 6% growth. Uh, Cisco I think is at eight or 9% growth. Dow's growing in double digits. Antonio and HPE have promised three to 4% growth. So what do you have to do to actually accelerate growth? Because three to 4%, my view, not enough to answer Holger's question is why should I buy HPE stock? Well, >>If they have product, if they have customer and there's demand and traction to me, that's going to drive the growth numbers. And I think the weak side of the forecast means that they don't have that fit yet. >>Yeah. So what has to happen for them to get above five, 6% growth? >>That's what we're gonna analyze. I mean, I, I mean, I don't have an answer for that. I wish I had a better answer. I'd tell them <laugh> but I feel, it feels, it feels like, you know, HP has an opportunity to say here's the new HPE. Yeah. Okay. And this is what we stand for. And here's the one thing that we're going to do that consistently drives value for you, the customer. And that's gonna have to come into some, either architectural cloud shift or a data thing, or we are your store for blank. >>All of the above. >>I guess the other question is, would, would you know, he won't answer a rude question, would suspending things like dividends and stock buybacks and putting it into R and D. I would definitely, if you have confidence in the market and you know what to do, why wouldn't you just accelerate R and D and put the money there? IBM, since 2007, IBM spent is the last stat. And I'm looking go in 2007, IBM way, outspent, Google, and Amazon and R and D and, and CapEx two, by the way. Yep. Subsequent to that, they've spent, I believe it's the numbers close to 200 billion on stock buyback and dividends. They could have owned cloud. And so look at this business, the technology business by and large is driven by innovation. Yeah. And so how do you innovate if >>You have I'm buying, I'm buying HP because they're reliable high quality and they have the outcomes that I want. Oh, >>Buy their products and services. I'm not sure I'd buy the stock. Yeah. >>Yeah. But she has to answer ultimately, because a public company. Right. So >>Right. It's this job. Yeah. >>Never a dull moment with the three of you around <laugh> guys. Thank you so much for sharing your insights, your, an analysis from day one. I can't imagine what day two is gonna bring tomorrow. Debut and I are gonna be anchoring here. We've got a jam packed day, lots going on, hearing from the ecosystem from leadership. As we mentioned, Antonio is gonna be Tony >>Alma Russo. I'm dying. Dr. >>EDMA as well as on the CTO gonna be another action pack day. I'm excited for it, guys. Thanks so much for sharing your insights and for letting me join this power panel. >>Great. Great to be here. >>Power panel plus me. All right. For Holger, John and Dave, I'm Lisa, you're watching the cube our day one coverage of HPE discover wraps right now. Don't go anywhere, cuz we'll see you tomorrow for day two, live from Vegas, have a good night.

(upbeat music) >> Welcome, everyone, to this CUBE Conversation here in Palo Alto, California. I'm John Furrier, host of the CUBE. We're here to talk about the state of MarTech and AI. We're here with the co-founder and head of AI for Blueshift, Manyam Mallela. Welcome to the CUBE, thanks for coming on. >> Thank you, John. Thank you for having me, excited to chat with you. >> Blueshift is a company you've co-founded with a couple other co-founders and you guys have a stellar pedigree going in data AI back before it was fashionable, in the old days, Web 1.0, if you want to call it that. So, you know, we know what you guys have been doing in your careers. Now you got a company on the cutting edge, solving problems for customers as they transition from this new, new way of doing things where users have data and power and control, customers are trying to be more authentic, got walled gardens emerging everywhere but that we're supposed to be away from walled gardens. So there's a whole set of new patterns, new expectations and new behaviors. So all this is challenging, but yet it's an opportunity. So I want to get into it. What is your vision? And what's your view on the MarTech today and AI, and how do you guys fit into that, that story? >> Yeah. Great question, John. We are still in the very early innings of where every digital experience is informed, both creatively from the marketing side of our organization, as well as the AI doing the heavy lifting under the herd to be able to create those experience at scale. And I think today every digital customer and every user out there are leaving a trail of very rich, very frequent interaction data with their brands and organizations that they interact with. You know, if you look at each of us, many, many moments and hours of our digital lives are with these interactions that we do on screens and devices, and that leaves a rich trail of data. And brands that are winning, brands that we want to interact with more, have user privacy and user safety at the center of it. And then they build that authentic connection from there on. And, you know, just like when we log into our favorite streaming shows or streaming applications, we want to see things that are relevant to us. They, in some sense, knowing kind of intimately our preferences or changing taste. And how does a brand or organization react to that but still make room for that authentic connection? >> It's an awesome opportunity. And it's a lot of challenges, and it's just starting, I totally agree. Let me ask you a question, Manyam, if you don't mind. How did you guys come up with Blueshift? I know you guys have been in this game before it was fashionable, so to speak, but you know, solving Web 1.0, 2.0 problems. And then, you know, Walmart Labs, everyone knows the history of Walmart and how fast they were with inventory and how they used data. You have that kind of trajectory. When you saw this opportunity, was it like the team was saying, wow, look at this, it's right in our wheelhouse, or, how did you guys get here, and then how did it all come together? >> Yeah, thanks for offering me an opportunity to share our personal journey. You know, I think prior to starting Blueshift with my co-founders, who I worked with for almost the past 20 years of my life, we were at a company called Kosmix, which was a Silicon Valley, early AI pioneer. We were doing semantics search, and in 2011, Walmart started their Silicon Valley innovation hub, Walmart Labs, with the acquisition of Kosmix. And, you know, we went into Walmart Labs, and until then they were already an e-commerce leader. They had been practicing e-commerce for better part of 12 years prior to that, but they're certainly you know, behind, compared to their peers, right? And the peers to be named! (laughs) But, they saw this lack of what it is that they were doing so well in brick and mortar that they're not able to fully get there on the digital side. And, you know, this was almost a decade ago. And when they brought in our team with a lot of AI and data systems at scale, building things at the cutting edge, you know, we went into it a little bit naively, thinking, you know, hey, we are going to solve this problem for Walmart scale in three months. (laughs) But it took us three years to build those systems of engagement. Despite Walmart having an enormous amount of resources being the number one retailer in the world and the data and the resource at their disposal, we had to rethink a lot of assumptions and the trends that were converging were, you know, uses for interacting with them across multiple formats and channels. And both offline and online, the velocity and complexity of the data was increasing. All the marketing and merchandising teams said even a millisecond delay for me is unconscionable. And how do you get fresh data and activated at the moment of experience, without delay, this significant challenge at scale? And that's what we solve for our organizations. >> It really is the data problem. It's a scale problem. It's all that. And then having the software to have that AI predictive and, you know, it's omnichannel when you think about it, in that retail and that brick and mortar term used for physical space and digital converging. And we saw the pandemic pull forward this same dynamic where events and group behaviors and just interactions were all converging. So this line between physical and digital is now blurred, completely blended, the line between customer experience and marketing has been erased, and you guys are the center of this. What does it mean for the customer? Because the customers out there, your customers, or potential customers. They got problems to solved. They're going all digital cloud-native applications, the digital transformation. This is the new normal, and some are on it, are starting it, some are way behind. What are they- What's the situation with the customers? >> Yeah, that's certainly the maturity of, you know, the, each brand and organization along that, you know, both transformation and from transformation to actually thriving in that ecosystem. And how do we actually win, you know, share of mind and then share of, like, that market that they're looking to does take a while. And, and many are, you know, kind of midway through their journey. I think, there was, initially there is a lot of, you know, push towards let's collect all the data that we can but then, you know, how does the actually data becomes something useful that changes experience for Manyam versus John is really that critical moment. And that moment is when, you know, a lot of things come into place. And if I look at, like, the broader landscape, there are certainly lines of powers like Discovery, like Udacity and LendingTree, and Zumper car pods across all these industries. Who would've thought like, you know, all these industries who you would not think of actually as solving a digital engagement problem are now saying that's the key to our success and our growth. >> Yeah. It's absolutely the number one problem. This is the number one opportunity for all businesses, not just verticals here and there, all verticals. So walk me through your typical customer scenario. You know, what are the challenges that they face? You're in the middle of it, you're solving these problems, what are their challenges that they face and how do you guys solve them? >> Absolutely. So I'll talk through two examples, one from a finance industry, one from online learning, you know, o One of our great customers that we partner with is LendingTree. They offer tens of millions of customers' finance products that span from home loans, students loans, auto loans, credits, all of that. And, and let these people come into their website and collect information that is relevant to the loan that they're considering, but engage them in a way for the next period of time. So if you typically think about engagement, it's not just a one interaction, usually that follows a series of steps an organization has to take to be able to explain all their offerings in a way that is digestible and relevant and personalized to each of those millions of customers and actually have them through the funnel and measure it and report on it and make sure that that is the most relevant to them. So in a finance setting that is about consuming credit products, consuming loan products, consuming reporting products in an online context. I'll give you an example of one of our customers, Udacity. Imagine you are a marketing team of two people, and you are in challenged with, how do you engage 20 million students. You're not going to write 20 million communications that are different for each of those students, certainly. I think you need a system to say what did actually all these students come for? How do I learn what they want at this moment in time? What do they want next? If they actually finished something that they started two months ago, would they be eligible for the right course? Maybe today we are talking about self-driving cars. That's the course that I should bring in front of them. And that's only a small segment of the students but someone else maybe on the media and the production side. How do I personalize the experience so that every single step of the way for that student is, you know, created and delivered at scale? And that's kind of the problem that we solve for our brands, which is they have these millions of touchpoint that are, that they have, how do they bring all their data, very fresh and activated at the moment of action? >> So you guys are creating the 10x marketer. I mean, kind of- >> That's right. That's a very (indistinct)- >> 10X engineer, the famous, you're 10X engineer. >> Right. >> You guys are bringing a lot of heavy lifting to short staffs or folks that don't have a data science team or data engineering team. You're kind of bringing that 10x marketing capability. >> Absolutely. I think that's a great way to put it. I call it the mission impossible, which is, you know, you're signing up for the mission impossible, for every marketing team, it's like, now they're like, they are the product managers they're the data scientists, they're the analysts. They are the creator, you know, author, all of that combined into a role. And now you're entrusted with this really massive challenge. And how do you actually get there? And it's that 10x marketer who are embracing these technologies to get there. >> Well, I'm looking forward to challenging though because I can imagine you get a lot of skeptics out there. I don't believe you. It sounds too good to be true. And I want to get to that in the next segment, but I want to ask you about the state of MarTech and AI specifically. MarTech traditionally has been on Web 2.0 standards, DNS, URLs. It's the naming system of the internet. It's the internet infrastructure. So- >> Right. what needs to change to make that scale higher? Does, is there any new abstraction or any kind of opportunities for doing things in just managing you know, tokens that need to be translated? It's hard to do cross to- I mean, there's a lot of problems with Web 2.0 legacy that kind of holds back the promise of high availability of data, privacy, AI, more machine learning, more exposure of data. Can you share your vision on this next layer? >> Absolutely. Yeah, I think, you know, there's a lot of excitement about what Web3 would bring us there in the very early innings of that possibility. But the challenge of, you know, data that leads to authentic experience still remains the same whichever metaverse we might actually interact with a brand name, like, you know, even if I go to a Nike store in the Metaverse, I still need to understand what that customer really prefers and keep up with that customer as they change their preferences. And AI is the key to be able to help a marketer. I call it the, you know, our own group call it like IPA you know, which is ingest all possible data, even from Metaverse, you know, the protocols might change, the formats might change, but then you have to not only have a sense of what happened in the past. I think there are more than enough tools to know what happened. There are only emerging tools to tell you what might happen. How do I predict? So ingest, predict, and then next step is activate. Actually you had to do something with it. How do I activate it, that the experience for you, whether it's Web3 or Web2 changes, and that IPA is kind of our own brew of, you know, AI marketing that we are taking to market. >> And that's the enablement piece, so how does this relate to the customer's data? You guys are storing all the data? Are they coming in? Is there a huge data lake involved? Can I bring in third party data? Does it have to be all be first party? How is that platform-level enabling this new form of customer engagement? >> Absolutely. There's a lot of heavy lifting that the data systems that one has to you know, bring to bear upon the problem, data systems ranging from, you know, distributed search, distributed indexing, low latency systems, data lakes that are built for high velocity, AI machine learning, training model inference, that validation pipeline. And, you know, we certainly leverage a lot of of data lake systems out there, including many of the components that are, you know, provided by our preferred partner, AWS and open source tools. And these data systems are certainly very complex to manage. And for an organization that, with a, you know, 5 to 10 people team of marketers, they're usually short staffed on the, the amount of attention that they get from rest of the organization. And what we have made is that you can ingest a lot more raw data. We do the heavy lifting, but both data management, identity resolution, segmentation, audience building, predictions, recommendations, and then give you also the delivery piece, which is, can I actually send you something? Can I put something in front of the user and measure it and report on it and tell you that, this is the ROI? How do, if all this would be for nothing, if actually you go through all this and there's no real ROI. And we have kind of, you know, our own forester did a total economic impact study with us. And they have found, they have found 781% ROI for implementing Blueshift. And it's a tremendous amount of ROI you get once you are able to reorient your organizations towards that. >> You know, Manyam, one of the problems of being a visionary and a pioneer like you guys are, you're early a lot. And so you must be scratching your head going, oh, the hot buzzword these days is the semantic layer, in Khan, you see snowflake and a bunch of other people kind of pushing this semantic layer. It's basically a data plane essentially for data, right? >> Right. >> And you guys have done that. Been there, done that, but now that's in play, you guys have this. >> That's right. >> You've got all this semantic search built in into the system, all this in data ingestion, it's a full platform. And so I need to ask you how you see this vectoring into the future state of customer engagement. Where, where do you see this intersecting with the organizations you're trying to bring this to? Are they putting more investment in, are they pulling back? Are they, where are, where are they and where are you guys relative to this, this technology? And, and, and, and first of all let's get your reaction to this semantic layer first. >> Right, right. It's a fantastic, you know, as a technologist, I love, you know, kind of the ontology and semantic differences, you know, how, how, you know, data planes, data meshes, data fabrics are put together. And, you know, I saw this, you know, kind of a dichotomy between CIO org and CMO org, right? The CO says like, you know, I have the best data plane, the data mesh, the data fabric. And the CMO says like, but I'm actually trying to accomplish something for this campaign. And they're like, oh, that, does it actually connect the both of pieces? >> So I think, the- >> Yeah? >> The CMO org certainly will need purpose-built applications, on top of the data fabric, on top of the data lakes, on top of the data measures, to be able to help marketing teams both technical and semi-technical to be able to accomplish that. >> Yeah. And then, and the new personas they want turnkey, they want to have it self-service. Again, the 10x marketer is someone with a small staff that can do the staff of hundred people, right? >> That's absolutely- >> So that's where it's going. And this is, this i6s the new normal. >> So, we call them AI marketers. And I think it's a, it's like you're calling a 10x marketer. I think, you know, over time we didn't have, you know this word, business intelligence analyst, but then once the tool are there, then they become business intelligence analysts. I think likewise, once these tools are available then we'll have AI marketers out in the market. >> Well, Manyam, I'd love to do a full, like, one-hour podcast with you. You can go for a long time with these topics given what you guys are working on, how relevant it is, how cool it is right now, and with what you guys have as a team and solution. I really appreciate you coming on the CUBE to chat. For the last minute we have here, give a quick plug for the company, what you guys are up to, size, funding, revenues, what you're looking for. What should people pay attention to? Give the plug. >> Yeah. Yeah, we are a global team, spanning, you know, multiple time zones. You know, we have raised $65 million to date to build out our vision and, you know, over the last eight years of our funding, we have served hundreds of customers and continuing to, you know, take on more. I think, you know, our hope is that over time, the next 10,000 organizations see this as a very much an approachable, you know, problem to solve for themselves, which I think is where we are. AI marketing is real doable, proven ROI. Can we get the next 10,000 customers to embrace that? >> You know, as we always used to say in the kind of web business and search, it's the contextual and the behavioral, you got to bring 'em together here. You got all that technology for the, for the sites and applications for the behavior and converting that contextually into value. Really compelling solution. Thanks for sharing your insight. >> Yeah. Thank you John, really appreciate this. >> Okay, this is CUBE Conversation. I'm John Furrier here in Palo Alto. Thanks for watching. (upbeat music)

>> (bright music) >> Narrator: The Cube, presents Kubecon and Cloudnativecon, year of 2022, brought to you by Red Hat, the cloud native computing foundation and its ecosystem partners. >> Now what we're opening. Welcome to Valencia, Spain in Kubecon Cloudnativecon, Europe, 2022. I'm Keith Townsend, along with my host, Paul Gillin, who is the senior editor for architecture at Silicon angle, Paul. >> Keith you've been asking me questions all these last two days. Let me ask you one. You're a traveling man. You go to a lot of conferences. What's different about this one. >> You know what, we're just talking about that pre-conference, open source conferences are usually pretty intimate. This is big. 7,500 people talking about complex topics, all in one big area. And then it's, I got to say it's overwhelming. It's way more. It's not focused on a single company's product or messaging. It is about a whole ecosystem, very different show. >> And certainly some of the best t-shirts I've ever seen. And our first guest, Jim has one of the better ones. >> I mean a bit cockroach come on, right. >> Jim Walker, principal product evangelist at CockroachDB and Christian Huning, tech director of cloud technologies at Finleap Connect, a financial services company that's based out of Germany, now offering services in four countries now. >> Basically all over Europe. >> Okay. >> But we are in three countries with offices. >> So you're CockroachDB customer and I got to ask the obvious question. Databases are hard and started the company in 2015 CockroachDB, been a customer since 2019, I understand. Why take the risk on a four year old database. I mean that just sounds like a world of risk and trouble. >> So it was in 2018 when we joined the company back then and we did this cloud native transformation, that was our task basically. We had very limited amount of time and we were faced with a legacy infrastructure and we needed something that would run in a cloud native way and just blend in with everything else we had. And the idea was to go all in with Kubernetes. Though early days, a lot of things were alpha beta, and we were running on mySQL back then. >> Yeah. >> On a VM, kind of small setup. And then we were looking for something that we could just deploy in Kubernetes, alongside with everything else. And we had to stack and we had to duplicate it many times. So also to maintain that we wanted to do it all the same like with GitOps and everything and Cockroach delivered that proposition. So that was why we evaluate the risk of relatively early adopting that solution with the proposition of having something that's truly cloud native and really blends in with everything else we do in the same way was something we considered, and then we jumped the leap of faith and >> The fin leap of faith >> The fin leap of faith. Exactly. And we were not dissatisfied. >> So talk to me a little bit about the challenges because when we think of MySQL, MySQL scales to amazing sizes, it is the de facto database for many cloud based architectures. What problems were you running into with MySQL? >> We were running into the problem that we essentially, as a finTech company, we are regulated and we have companies, customers that really value running things like on-prem, private cloud, on-prem is a bit of a bad word, maybe. So it's private cloud, hybrid cloud, private cloud in our own data centers in Frankfurt. And we needed to run it in there. So we wanted to somehow manage that and with, so all of the managed solution were off the table, so we couldn't use them. So we needed something that ran in Kubernetes because we only wanted to maintain Kubernetes. We're a small team, didn't want to use also like full blown VM solution, of sorts. So that was that. And the other thing was, we needed something that was HA distributable somehow. So we also looked into other solutions back at the time, like Vitis, which is also prominent for having a MySQL compliant interface and great solution. We also got into work, but we figured, this is from the scale, and from the sheer amount of maintenance it would need, we couldn't deliver that, we were too small for that. So that's where then Cockroach just fitted in nicely by being able to distribute BHA, be resilient against failure, but also be able to scale out because we had this problem with a single MySQL deployment to not really, as it grew, as the data amounts grew, we had trouble to operatively keep that under control. >> So Jim, every time someone comes to me and says, I have a new database, I think we don't need it, yet another database. >> Right. >> What problem, or how does CockroachDB go about solving the types of problems that Christian had? >> Yeah. I mean, Christian laid out why it exists. I mean, look guys, building a database isn't easy. If it was easy, we'd have a database for every application, but you know, Michael Stonebraker, kind of godfather of all database says it himself, it takes seven, eight years for a database to fully gestate to be something that's like enterprise ready and kind of, be relied upon. We've been billing for about seven, eight years. I mean, I'm thankful for people like Christian to join us early on to help us kind of like troubleshoot and go through some things. We're building a database, it's not easy. You're right. But building a distributor system is also not easy. And so for us, if you look at what's going on in just infrastructure in general, what's happening in Kubernetes, like this whole space is Kubernetes. It's all about automation. How do I automate scale? How do I automate resilience out of the entire equation of what we're actually doing? I don't want to have to think about active passive systems. I don't want to think about sharding a database. Sure you can scale MySQL. You know, how many people it takes to run three or four shards of MySQL database. That's not automation. And I tell you what, this world right now with the advances in data how hard it is to find people who actually understand infrastructure to hire them. This is why this automation is happening, because our systems are more complex. So we started from the very beginning to be something that was very different. This is a cloud native database. This is built with the same exact principles that are in Kubernetes. In fact, like Kubernetes it's kind of a spawn of borg, the back end of Google. We are inspired by Spanner. I mean, this started by three engineers that worked at Google, are frustrated, they didn't have the tools, they had at Google. So they built something that was, outside of Google. And how do we give that kind of Google like infrastructure for everybody. And that's, the advent of Cockroach and kind of why we're doing, what we're doing. >> As your database has matured, you're now beginning a transition or you're in a transition to a serverless version. How are you doing that without disrupting the experience for existing customers? And why go serverless at all? >> Yeah, it's interesting. So, you know, serverless was, it was kind of a an R&D project for us. And when we first started on a path, because I think you know, ultimately what we would love to do for the database is let's not even think about database, Keith. Like, I don't want to think about the database. What we're building too is, we want a SQL API in the cloud. That's it. I don't want to think about scale. I don't want to think about upgrades. I literally like. that stuff should just go away. That's what we need, right. As developers, I don't want to think about isolation levels or like, you know, give me DML and I want to be able to communicate. And for us the realization of that vision is like, if we're going to put a database on the planet for everybody to actually use it, we have to be really, really efficient. And serverless, which I believe really should be infrastructure less because I don't think we should be thinking of just about service. We got to think about, how do I take the context of regions out of this thing? How do I take the context of cloud providers out of what we're talking about? Let's just not think about that. Let's just code against something. Serverless was the answer. Now we've been building for about a year and a half. We launched a serverless version of Cockroach last October and we did it so that everybody in the public could have a free version of a database. And that's what serverless allows us to do. It's all consumption based up to certain limits and then you pay. But I think ultimately, and we spoke a little bit about this at the very beginning. I think as ISVs, people who are building software today the serverless vision gets really interesting because I think what's on the mind of the CTO is, how do I drive down my cost to the cloud provider? And if we can basically, drive down costs through either making things multi-tenant and super efficient, and then optimizing how much compute we use, spinning things down to zero and back up and auto scaling these sort of things in our software. We can start to make changes in the way that people are thinking about spend with the cloud provider. And ultimately we did that, so we could do things for free. >> So, Jim, I think I disagree Christian, I'm sorry, Jim. I think I disagree with you just a little bit. Christian, I think the biggest challenge facing CTOs are people. >> True. >> Getting the people to worry about cost and spend and implementation. So as you hear the concepts of CoachDB moving to a serverless model, and you're a large customer how does that make you think or react to your people side of your resources? >> Well, I can say that from the people side of resources luckily Cockroach is our least problem. So it just kind of, we always said, it's an operator stream because that was the part that just worked for us, so. >> And it's worked as you have scaled it? without you having ... >> Yeah. I mean, we use it in a bit of a, we do not really scale out like the Cockroach, like really large. It's like, more that we use it with the enterprise features of encryption in the stack and our customers then demand. If they do so, we have the Zas offering and we also do like dedicated stacks. So by having a fully cloud native solution on top of Kubernetes, as the foundational layer we can just use that and stamp it out and deploy it. >> How does that translate into services you can provide your customers? Are there services you can provide customers that you couldn't have, if you were running, say, MySQL? >> No, what we do is, we run this, so the SAS offering runs in our hybrid private cloud. And the other thing that we offer is that we run the entire stack at a cloud provider of their choosing. So if they are an AWS, they give us an AWS account, we put it in there. Theoretically, we could then also talk about using the serverless variant, if they like so, but it's not strictly required for us. >> So Christian, talk to me about that provisioning process because if I had a MySQL deployment before I can imagine how putting that into a cloud native type of repeatable CICD pipeline or Ansible script that could be difficult. Talk to me about that. How CockroachDB enables you to create new onboarding experiences for your customers? >> So what we do is, we use helm charts all over the place as probably everybody else. And then each application team has their parts of services, they've packaged them to helm charts, they've wrapped us in a super chart that gets wrapped into the super, super chart for the entire stack. And then at the right place, somewhere in between Cockroach is added, where it's a dependency. And as they just offer a helm chart that's as easy as it gets. And then what the teams do is they have an inner job, that once you deploy all that, it would spin up. And as soon as Cockroach is ready it's just the same reconcile loop as everything. It will then provision users, set up database schema, do all that. And initialize, initial data sets that might be required for a new setup. So with that setup, we can spin up a new cluster and then deploy that stack chart in there. And it takes some time. And then it's done. >> So talk to me about life cycle management. Because when I have one database, I have one schema. When I have a lot of databases I have a lot of different schemas. How do you keep your stack consistent across customers? >> That is basically part of the same story. We have get offs all over the place. So we have this repository, we see the super helm chart versions and we maintain like minus three versions and ensure that we update the customers and keep them up to date. It's part of the contract sometimes, down to the schedule of the customer at times. And Cockroach nicely supports also, these updates with these migrations in the background, the schema migrations in the background. So we use in our case, in that integration SQL alchemy, which is also nicely supported. So there was also part of the story from MySQL to Postgres, was supported by the ORM, these kind of things. So the skill approach together with the ease of helm charts and the background migrations of the schema is a very seamless upgrade operations. Before that we had to have downtime. >> That's right, you could have online schema changes. Upgrading the database uses the same concept of rolling upgrades that you have in Kubernetes. It's just cloud native. It just fits that same context, I think. >> Christian: It became a no-brainer. >> Yeah. >> Yeah. >> Jim, you mentioned the idea of a SQL API in the cloud, that's really interesting. Why does such a thing not exist? >> Because it's really difficult to build. You know, SQL API, what does that mean? Like, okay. What I'm going to, where does that endpoint live? Is there one in California one on the east coast, one in Europe, one in Asia? Okay. And I'm asking that endpoint for data. Where does that data live? Can you control where data lives on the planet? Because ultimately what we're fighting in software today in a lot of these situations is the speed of light. And so how do you intelligently place data on this planet? So that, you know, when you're asking for data, when you're maybe home, it's a different latency than when you're here in Valencia. Does that data follow and move you? These are really, really difficult problems to solve. And I think that we're at that layer of, we're at this moment in time in software engineering, we're solving some really interesting, interesting things cause we are budding against this speed of light problem. And ultimately that's one of the biggest challenges. But underneath, it has to have all this automation like the ease at which we can scale this database like the always on resilient, the way that we can upgrade the entire thing with just rolling upgrades. The cloud native concepts is really what's enabling us to do things at global scale it's automation. >> Let's alk about that speed of light in global scale. There's no better conference for speed of light, for scale, than Kubecon. Any predictions coming out of the show? >> It's less a prediction for me and more of an observation, you guys. Like look at two years ago, when we were here in Barcelona at QCon EU, it was a lot of hype. It's a lot of hype, a lot of people walking around, curious, fascinated, this is reality. The conversations that I'm having with people today, there's a reality. There's people really doing, they're becoming cloud native. And to me, I think what we're going to see over the next two to three years is people start to adopt this kind of distributed mindset. And it permeates not just within infrastructure but it goes up into the stack. We'll start to see much more developers using, Go and these kind of the threaded languages, because I think that distributed mindset, if it starts at the chip all the way to the fingertip of the person clicking and you're distributed everywhere in between. It is extremely powerful. And I think that's what Finleap, I mean, that's exactly what the team is doing. And I think there's a lot of value and a lot of power in that. >> Jim, Christian, thank you so much for coming on the Cube and sharing your story. You know what we're past the hype cycle of Kubernetes, I agree. I was a nonbeliever in Kubernetes two, three years ago. It was mostly hype. We're looking at customers from Microsoft, Finleap and competitors doing amazing things with this platform and cloud native in general. Stay tuned for more coverage of Kubecon from Valencia, Spain. I'm Keith Townsend, along with Paul Gillin and you're watching the Cube, the leader in high tech coverage. (bright music)