(gentle upbeat music) >> Hello, everyone, welcome to theCUBE's coverage of International Women's Day. I'm John Furrier host here in Palo Alto, California. theCUBE's second year covering International Women's Day. It's been a great celebration of all the smart leaders in the world who are making a difference from all kinds of backgrounds, from technology to business and everything in between. Today we've got a great guest, Dominique Bastos, who's the senior Vice President of Cloud at Persistent Systems, formerly with AWS. That's where we first met at re:Invent. Dominique, great to have you on the program here for International Women's Day. Thanks for coming on. >> Thank you John, for having me back on theCUBE. This is an honor, especially given the theme. >> Well, I'm excited to have you on, I consider you one of those typecast personas where you've kind of done a lot of things. You're powerful, you've got great business acumen you're technical, and we're in a world where, you know the world's coming completely digital and 50% of the world is women, 51%, some say. So you got mostly male dominated industry and you have a dual engineering background and that's super impressive as well. Again, technical world, male dominated you're in there in the mix. What inspires you to get these engineering degrees? >> I think even it was more so shifted towards males. When I had the inspiration to go to engineering school I was accused as a young girl of being a tomboy and fiddling around with all my brother's toys versus focusing on my dolls and other kind of stereotypical toys that you would give a girl. I really had a curiosity for building, a curiosity for just breaking things apart and putting them back together. I was very lucky in that my I guess you call it primary school, maybe middle school, had a program for, it was like electronics, that was the class electronics. So building circuit boards and things like that. And I really enjoyed that aspect of building. I think it was more actually going into engineering school. Picking that as a discipline was a little bit, my mom's reaction to when I announced that I wanted to do engineering which was, "No, that's for boys." >> Really. >> And that really, you know, I think she, it came from a good place in trying to protect me from what she has experienced herself in terms of how women are received in those spaces. So I kind of shrugged it off and thought "Okay, well I'm definitely now going to do this." >> (laughs) If I was told not to, you're going to do it. >> I was told not to, that's all I needed to hear. And also, I think my passion was to design cars and I figured if I enroll in an industrial engineering program I could focus on ergonomic design and ultimately, you know have a career doing something that I'm passionate about. So yeah, so my inspiration was kind of a little bit of don't do this, a lot of curiosity. I'm also a very analytical person. I've been, and I don't know what the science is around left right brain to be honest, but been told that I'm a very much a logical person versus a feeler. So I don't know if that's good or bad. >> Straight shooter. What were your engineering degrees if you don't mind sharing? >> So I did industrial engineering and so I did a dual degree, industrial engineering and robotics. At the time it was like a manufacturing robotics program. It was very, very cool because we got to, I mean now looking back, the evolution of robotics is just insane. But you, you know, programmed a robotic arm to pick things up. I actually crashed the Civil Engineering School's Concrete Canoe Building Competition where you literally have to design a concrete canoe and do all the load testing and the strength testing of the materials and basically then, you know you go against other universities to race the canoe in a body of water. We did that at, in Alabama and in Georgia. So I was lucky to experience that two times. It was a lot of fun. >> But you knew, so you knew, deep down, you were technical you had a nerd vibe you were geeking out on math, tech, robotics. What happened next? I mean, what were some of the challenges you faced? How did you progress forward? Did you have any blockers and roadblocks in front of you and how did you handle those? >> Yeah, I mean I had, I had a very eye-opening experience with, in my freshman year of engineering school. I kind of went in gung-ho with zero hesitation, all the confidence in the world, 'cause I was always a very big nerd academically, I hate admitting this but myself and somebody else got most intellectual, voted by the students in high school. It's like, you don't want to be voted most intellectual when you're in high school. >> Now it's a big deal. (laughs) >> Yeah, you want to be voted like popular or anything like that? No, I was a nerd, but in engineering school, it's a, it was very humbling. That whole confidence that I had. I experienced prof, ooh, I don't want to name the school. Everybody can google it though, but, so anyway so I had experience with some professors that actually looked at me and said, "You're in the wrong program. This is difficult." I, and I think I've shared this before in other forums where, you know, my thermodynamic teacher basically told me "Cheerleading's down the hall," and it it was a very shocking thing to hear because it really made me wonder like, what am I up against here? Is this what it's going to be like going forward? And I decided not to pay attention to that. I think at the moment when you hear something like that you just, you absorb it and you also don't know how to react. And I decided immediately to just walk right past him and sit down front center in the class. In my head I was cursing him, of course, 'cause I mean, let's be real. And I was like, I'm going to show this bleep bleep. And proceeded to basically set the curve class crushed it and was back to be the teacher's assistant. So I think that was one. >> But you became his teacher assistant after, or another one? >> Yeah, I gave him a mini speech. I said, do not do this. You, you could, you could have broken me and if you would've done this to somebody who wasn't as steadfast in her goals or whatever, I was really focused like I'm doing this, I would've backed out potentially and said, you know this isn't something I want to experience on the daily. So I think that was actually a good experience because it gave me an opportunity to understand what I was up against but also double down in how I was going to deal with it. >> Nice to slay the misogynistic teachers who typecast people. Now you had a very technical career but also you had a great career at AWS on the business side you've handled 'em all of the big accounts, I won't say the names, but like we're talking about monster accounts, sales and now basically it's not really selling, you're managing a big account, it's like a big business. It's a business development thing. Technical to business transition, how do you handle that? Was that something you were natural for? Obviously you, you stared down the naysayers out of the gate in college and then in business, did that continue and how did you drive through that? >> So I think even when I was coming out of university I knew that I wanted to have a balance between the engineering program and business. A lot of my colleagues went on to do their PEs so continue to get their masters basically in engineering or their PhDs in engineering. I didn't really have an interest for that. I did international business and finance as my MBA because I wanted to explore the ability of taking what I had learned in engineering school and applying it to building businesses. I mean, at the time I didn't have it in my head that I would want to do startups but I definitely knew that I wanted to get a feel for what are they learning in business school that I missed out in engineering school. So I think that helped me when I transitioned, well when I applied, I was asked to come apply at AWS and I kind of went, no I'm going to, the DNA is going to be rejected. >> You thought, you thought you'd be rejected from AWS. >> I thought I'd be, yeah, because I have very much a startup founder kind of disruptive personality. And to me, when I first saw AWS at the stage early 2016 I saw it as a corporation. Even though from a techie standpoint, I was like, these people are insane. This is amazing what they're building. But I didn't know what the cultural vibe would feel like. I had been with GE at the beginning of my career for almost three years. So I kind of equated AWS Amazon to GE given the size because in between, I had done startups. So when I went to AWS I think initially, and I do have to kind of shout out, you know Todd Weatherby basically was the worldwide leader for ProServe and it was being built, he built it and I went into ProServe to help from that standpoint. >> John: ProServe, Professional services >> Professional services, right. To help these big enterprise customers. And specifically my first customer was an amazing experience in taking, basically the company revolves around strategic selling, right? It's not like you take a salesperson with a conventional schooling that salespeople would have and plug them into AWS in 2016. It was very much a consultative strategic approach. And for me, having a technical background and loving to solve problems for customers, working with the team, I would say, it was a dream team that I joined. And also the ability to come to the table with a technical background, knowing how to interact with senior executives to help them envision where they want to go, and then to bring a team along with you to make that happen. I mean, that was like magical for me. I loved that experience. >> So you like the culture, I mean, Andy Jassy, I've interviewed many times, always talked about builders and been a builder mentality. You mentioned that earlier at the top of this interview you've always building things, curious and you mentioned potentially your confidence might have been shaken. So you, you had the confidence. So being a builder, you know, being curious and having confidence seems to be what your superpower is. A lot of people talk about the confidence angle. How important is that and how important is that for encouraging more women to get into tech? Because I still hear that all the time. Not that they don't have confidence, but there's so many signals that potentially could shake confidence in industry >> Yeah, that's actually a really good point that you're making. A lot of signals that women get could shake their confidence and that needs to be, I mean, it's easy to say that it should be innate. I mean that's kind of like textbook, "Oh it has to come from within." Of course it does. But also, you know, we need to understand that in a population where 50% of the population is women but only 7% of the positions in tech, and I don't know the most current number in tech leadership, is women, and probably a smaller percentage in the C-suite. When you're looking at a woman who's wanting to go up the trajectory in a tech company and then there's a subconscious understanding that there's a limit to how far you'll go, your confidence, you know, in even subconsciously gets shaken a little bit because despite your best efforts, you're already seeing the cap. I would say that we need to coach girls to speak confidently to navigate conflict versus running away from it, to own your own success and be secure in what you bring to the table. And then I think a very important thing is to celebrate each other and the wins that we see for women in tech, in the industry. >> That's awesome. What's, the, in your opinion, the, you look at that, the challenges for this next generation women, and women in general, what are some of the challenges for them and that they need to overcome today? I mean, obviously the world's changed for the better. Still not there. I mean the numbers one in four women, Rachel Thornton came on, former CMO of AWS, she's at MessageBird now. They had a study where only one in four women go to the executive board level. And so there's still, still numbers are bad and then the numbers still got to get up, up big time. That's, and the industry's working on that, but it's changed. But today, what are some of the challenges for this current generation and the next generation of women and how can we and the industry meet, we being us, women in the industry, be strong role models for them? >> Well, I think the challenge is one of how many women are there in the pipeline and what are we doing to retain them and how are we offering up the opportunities to fill. As you know, as Rachel said and I haven't had an opportunity to see her, in how are we giving them this opportunity to take up those seats in the C-suite right, in these leadership roles. And I think this is a little bit exacerbated with the pandemic in that, you know when everything shut down when people were going back to deal with family and work at the same time, for better or for worse the brunt of it fell on probably, you know the maternal type caregiver within the family unit. You know, I've been, I raised my daughter alone and for me, even without the pandemic it was a struggle constantly to balance the risk that I was willing to take to show up for those positions versus investing even more of that time raising a child, right? Nevermind the unconscious bias or cultural kind of expectations that you get from the male counterparts where there's zero understanding of what a mom might go through at home to then show up to a meeting, you know fully fresh and ready to kind of spit out some wisdom. It's like, you know, your kid just freaking lost their whatever and you know, they, so you have to sort a bunch of things out. I think the challenge that women are still facing and will we have to keep working at it is making sure that there's a good pipeline. A good amount of young ladies of people taking interest in tech. And then as they're, you know, going through the funnel at stages in their career, we're providing the mentoring we're, there's representation, right? To what they're aspiring to. We're celebrating their interest in the field, right? And, and I think also we're doing things to retain them, because again, the pandemic affected everybody. I think women specifically and I don't know the statistics but I was reading something about this were the ones to tend to kind of pull it back and say well now I need to be home with, you know you name how many kids and pets and the aging parents, people that got sick to take on that position. In addition to the career aspirations that they might have. We need to make it easier basically. >> I think that's a great call out and I appreciate you bringing that up about family and being a single mom. And by the way, you're savage warrior to doing that. It's amazing. You got to, I know you have a daughter in computer science at Stanford, I want to get to that in a second. But that empathy and I mentioned Rachel Thornton, who's the CMO MessageBird and former CMO of AWS. Her thing right now to your point is mentoring and sponsorship is very key. And her company and the video that's on the site here people should look at that and reference that. They talk a lot about that empathy of people's situation whether it's a single mom, family life, men and women but mainly women because they're the ones who people aren't having a lot of empathy for in that situation, as you called it out. This is huge. And I think remote work has opened up this whole aperture of everyone has to have a view into how people are coming to the table at work. So, you know, props are bringing that up, and I recommend everyone look at check out Rachel Thornton. So how do you balance that, that home life and talk about your daughter's journey because sounds like she's nerding out at Stanford 'cause you know Stanford's called Nerd Nation, that's their motto, so you must be proud. >> I am so proud, I'm so proud. And I will say, I have to admit, because I did encounter so many obstacles and so many hurdles in my journey, it's almost like I forgot that I should set that aside and not worry about my daughter. My hope for her was for her to kind of be artistic and a painter or go into something more lighthearted and fun because I just wanted to think, I guess my mom had the same idea, right? She, always been very driven. She, I want to say that I got very lucky that she picked me to be her mom. Biologically I'm her mom, but I told her she was like a little star that fell from the sky and I, and ended up with me. I think for me, balancing being a single mom and a career where I'm leading and mentoring and making big decisions that affect people's lives as well. You have to take the best of everything you get from each of those roles. And I think that the best way is play to your strengths, right? So having been kind of a nerd and very organized person and all about, you know, systems for effectiveness, I mean, industrial engineering, parenting for me was, I'm going to make it sound super annoying and horrible, but (laughs) >> It's funny, you know, Dave Vellante and I when we started SiliconANGLE and theCUBE years ago, one of the things we were all like sports lovers. So we liked sports and we are like we looked at the people in tech as tech athletes and except there's no men and women teams, it's one team. It's all one thing. So, you know, I consider you a tech athlete you're hard charging strong and professional and smart and beautiful and brilliant, all those good things. >> Thank you. >> Now this game is changing and okay, and you've done startups, and you've done corporate jobs, now you're in a new role. What's the current tech landscape from a, you know I won't say athletic per standpoint but as people who are smart. You have all kinds of different skill sets. You have the startup warriors, you have the folks who like to be in the middle of the corporate world grow up through corporate, climb the corporate ladder. You have investors, you have, you know, creatives. What have you enjoyed most and where do you see all the action? >> I mean, I think what I've enjoyed the most has been being able to bring all of the things that I feel I'm strong at and bring it together to apply that to whatever the problem is at hand, right? So kind of like, you know if you look at a renaissance man who can kind of pop in anywhere and, oh, he's good at, you know sports and he's good at reading and, or she's good at this or, take all of those strengths and somehow bring them together to deal with the issue at hand, versus breaking up your mindset into this is textbook what I learned and this is how business should be done and I'm going to draw these hard lines between personal life and work life, or between how you do selling and how you do engineering. So I think my, the thing that I loved, really loved about AWS was a lot of leaders saw something in me that I potentially didn't see, which was, yeah you might be great at running that big account but we need help over here doing go to market for a new product launch and boom, there you go. Now I'm in a different org helping solve that problem and getting something launched. And I think if you don't box yourself in to I'm only good at this, or, you know put a label on yourself as being the rockstar in that. It leaves room for opportunities to present themselves but also it leaves room within your own mind to see yourself as somebody capable of doing anything. Right, I don't know if I answered the question accurately. >> No, that's good, no, that's awesome. I love the sharing, Yeah, great, great share there. Question is, what do you see, what do you currently during now you're building a business of Persistent for the cloud, obviously AWS and Persistent's a leader global system integrator around the world, thousands and thousands of customers from what we know and been reporting on theCUBE, what's next for you? Where do you see yourself going? Obviously you're going to knock this out of the park. Where do you see yourself as you kind of look at the continuing journey of your mission, personal, professional what's on your mind? Where do you see yourself going next? >> Well, I think, you know, again, going back to not boxing yourself in. This role is an amazing one where I have an opportunity to take all the pieces of my career in tech and apply them to building a business within a business. And that involves all the goodness of coaching and mentoring and strategizing. And I'm loving it. I'm loving the opportunity to work with such great leaders. Persistent itself is very, very good at providing opportunities, very diverse opportunities. We just had a huge Semicolon; Hackathon. Some of the winners were females. The turnout was amazing in the CTO's office. We have very strong women leading the charge for innovation. I think to answer your question about the future and where I may see myself going next, I think now that my job, well they say the job is never done. But now that Chloe's kind of settled into Stanford and kind of doing her own thing, I have always had a passion to continue leading in a way that brings me to, into the fold a lot more. So maybe, you know, maybe in a VC firm partner mode or another, you know CEO role in a startup, or my own startup. I mean, I never, I don't know right now I'm super happy but you never know, you know where your drive might go. And I also want to be able to very deliberately be in a role where I can continue to mentor and support up and coming women in tech. >> Well, you got the smarts but you got really the building mentality, the curiosity and the confidence really sets you up nicely. Dominique great story, great inspiration. You're a role model for many women, young girls out there and women in tech and in celebration. It's a great day and thank you for sharing that story and all the good nuggets there. Appreciate you coming on theCUBE, and it's been my pleasure. Thanks for coming on. >> Thank you, John. Thank you so much for having me. >> Okay, theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE here in Palo Alto getting all the content, check out the other interviews some amazing stories, lessons learned, and some, you know some funny stories and some serious stories. So have some fun and enjoy the rest of the videos here for International Women's Days, thanks for watching. (gentle inspirational 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)

(upbeat music) >> Hello and welcome to theCube's coverage of International Women's Day. I'm John Furrier, your host of "theCUBE." We've got great two remote guests coming into our Palo Alto Studios, some tech athletes, as we say, people that've been in the trenches, years of experience, Lena Smart, CISO at MongoDB, Cube alumni, and Tara Hernandez, VP of Developer Productivity at MongoDB as well. Thanks for coming in to this program and supporting our efforts today. Thanks so much. >> Thanks for having us. >> Yeah, everyone talk about the journey in tech, where it all started. Before we get there, talk about what you guys are doing at MongoDB specifically. MongoDB is kind of gone the next level as a platform. You have your own ecosystem, lot of developers, very technical crowd, but it's changing the business transformation. What do you guys do at Mongo? We'll start with you, Lena. >> So I'm the CISO, so all security goes through me. I like to say, well, I don't like to say, I'm described as the ones throat to choke. So anything to do with security basically starts and ends with me. We do have a fantastic Cloud engineering security team and a product security team, and they don't report directly to me, but obviously we have very close relationships. I like to keep that kind of church and state separate and I know I've spoken about that before. And we just recently set up a physical security team with an amazing gentleman who left the FBI and he came to join us after 26 years for the agency. So, really starting to look at the physical aspects of what we offer as well. >> I interviewed a CISO the other day and she said, "Every day is day zero for me." Kind of goofing on the Amazon Day one thing, but Tara, go ahead. Tara, go ahead. What's your role there, developer productivity? What are you focusing on? >> Sure. Developer productivity is kind of the latest description for things that we've described over the years as, you know, DevOps oriented engineering or platform engineering or build and release engineering development infrastructure. It's all part and parcel, which is how do we actually get our code from developer to customer, you know, and all the mechanics that go into that. It's been something I discovered from my first job way back in the early '90s at Borland. And the art has just evolved enormously ever since, so. >> Yeah, this is a very great conversation both of you guys, right in the middle of all the action and data infrastructures changing, exploding, and involving big time AI and data tsunami and security never stops. Well, let's get into, we'll talk about that later, but let's get into what motivated you guys to pursue a career in tech and what were some of the challenges that you faced along the way? >> I'll go first. The fact of the matter was I intended to be a double major in history and literature when I went off to university, but I was informed that I had to do a math or a science degree or else the university would not be paid for. At the time, UC Santa Cruz had a policy that called Open Access Computing. This is, you know, the late '80s, early '90s. And anybody at the university could get an email account and that was unusual at the time if you were, those of us who remember, you used to have to pay for that CompuServe or AOL or, there's another one, I forget what it was called, but if a student at Santa Cruz could have an email account. And because of that email account, I met people who were computer science majors and I'm like, "Okay, I'll try that." That seems good. And it was a little bit of a struggle for me, a lot I won't lie, but I can't complain with how it ended up. And certainly once I found my niche, which was development infrastructure, I found my true love and I've been doing it for almost 30 years now. >> Awesome. Great story. Can't wait to ask a few questions on that. We'll go back to that late '80s, early '90s. Lena, your journey, how you got into it. >> So slightly different start. I did not go to university. I had to leave school when I was 16, got a job, had to help support my family. Worked a bunch of various jobs till I was about 21 and then computers became more, I think, I wouldn't say they were ubiquitous, but they were certainly out there. And I'd also been saving up every penny I could earn to buy my own computer and bought an Amstrad 1640, 20 meg hard drive. It rocked. And kind of took that apart, put it back together again, and thought that could be money in this. And so basically just teaching myself about computers any job that I got. 'Cause most of my jobs were like clerical work and secretary at that point. But any job that had a computer in front of that, I would make it my business to go find the guy who did computing 'cause it was always a guy. And I would say, you know, I want to learn how these work. Let, you know, show me. And, you know, I would take my lunch hour and after work and anytime I could with these people and they were very kind with their time and I just kept learning, so yep. >> Yeah, those early days remind me of the inflection point we're going through now. This major C change coming. Back then, if you had a computer, you had to kind of be your own internal engineer to fix things. Remember back on the systems revolution, late '80s, Tara, when, you know, your career started, those were major inflection points. Now we're seeing a similar wave right now, security, infrastructure. It feels like it's going to a whole nother level. At Mongo, you guys certainly see this as well, with this AI surge coming in. A lot more action is coming in. And so there's a lot of parallels between these inflection points. How do you guys see this next wave of change? Obviously, the AI stuff's blowing everyone away. Oh, new user interface. It's been called the browser moment, the mobile iPhone moment, kind of for this generation. There's a lot of people out there who are watching that are young in their careers, what's your take on this? How would you talk to those folks around how important this wave is? >> It, you know, it's funny, I've been having this conversation quite a bit recently in part because, you know, to me AI in a lot of ways is very similar to, you know, back in the '90s when we were talking about bringing in the worldwide web to the forefront of the world, right. And we tended to think in terms of all the optimistic benefits that would come of it. You know, free passing of information, availability to anyone, anywhere. You just needed an internet connection, which back then of course meant a modem. >> John: Not everyone had though. >> Exactly. But what we found in the subsequent years is that human beings are what they are and we bring ourselves to whatever platforms that are there, right. And so, you know, as much as it was amazing to have this freely available HTML based internet experience, it also meant that the negatives came to the forefront quite quickly. And there were ramifications of that. And so to me, when I look at AI, we're already seeing the ramifications to that. Yes, are there these amazing, optimistic, wonderful things that can be done? Yes. >> Yeah. >> But we're also human and the bad stuff's going to come out too. And how do we- >> Yeah. >> How do we as an industry, as a community, you know, understand and mitigate those ramifications so that we can benefit more from the positive than the negative. So it is interesting that it comes kind of full circle in really interesting ways. >> Yeah. The underbelly takes place first, gets it in the early adopter mode. Normally industries with, you know, money involved arbitrage, no standards. But we've seen this movie before. Is there hope, Lena, that we can have a more secure environment? >> I would hope so. (Lena laughs) Although depressingly, we've been in this well for 30 years now and we're, at the end of the day, still telling people not to click links on emails. So yeah, that kind of still keeps me awake at night a wee bit. The whole thing about AI, I mean, it's, obviously I am not an expert by any stretch of the imagination in AI. I did read (indistinct) book recently about AI and that was kind of interesting. And I'm just trying to teach myself as much as I can about it to the extent of even buying the "Dummies Guide to AI." Just because, it's actually not a dummies guide. It's actually fairly interesting, but I'm always thinking about it from a security standpoint. So it's kind of my worst nightmare and the best thing that could ever happen in the same dream. You know, you've got this technology where I can ask it a question and you know, it spits out generally a reasonable answer. And my team are working on with Mark Porter our CTO and his team on almost like an incubation of AI link. What would it look like from MongoDB? What's the legal ramifications? 'Cause there will be legal ramifications even though it's the wild, wild west just now, I think. Regulation's going to catch up to us pretty quickly, I would think. >> John: Yeah, yeah. >> And so I think, you know, as long as companies have a seat at the table and governments perhaps don't become too dictatorial over this, then hopefully we'll be in a good place. But we'll see. I think it's a really interest, there's that curse, we're living in interesting times. I think that's where we are. >> It's interesting just to stay on this tech trend for a minute. The standards bodies are different now. Back in the old days there were, you know, IEEE standards, ITF standards. >> Tara: TPC. >> The developers are the new standard. I mean, now you're seeing open source completely different where it was in the '90s to here beginning, that was gen one, some say gen two, but I say gen one, now we're exploding with open source. You have kind of developers setting the standards. If developers like it in droves, it becomes defacto, which then kind of rolls into implementation. >> Yeah, I mean I think if you don't have developer input, and this is why I love working with Tara and her team so much is 'cause they get it. If we don't have input from developers, it's not going to get used. There's going to be ways of of working around it, especially when it comes to security. If they don't, you know, if you're a developer and you're sat at your screen and you don't want to do that particular thing, you're going to find a way around it. You're a smart person. >> Yeah. >> So. >> Developers on the front lines now versus, even back in the '90s, they're like, "Okay, consider the dev's, got a QA team." Everything was Waterfall, now it's Cloud, and developers are on the front lines of everything. Tara, I mean, this is where the standards are being met. What's your reaction to that? >> Well, I think it's outstanding. I mean, you know, like I was at Netscape and part of the crowd that released the browser as open source and we founded mozilla.org, right. And that was, you know, in many ways kind of the birth of the modern open source movement beyond what we used to have, what was basically free software foundation was sort of the only game in town. And I think it is so incredibly valuable. I want to emphasize, you know, and pile onto what Lena was saying, it's not just that the developers are having input on a sort of company by company basis. Open source to me is like a checks and balance, where it allows us as a broader community to be able to agree on and enforce certain standards in order to try and keep the technology platforms as accessible as possible. I think Kubernetes is a great example of that, right. If we didn't have Kubernetes, that would've really changed the nature of how we think about container orchestration. But even before that, Linux, right. Linux allowed us as an industry to end the Unix Wars and as someone who was on the front lines of that as well and having to support 42 different operating systems with our product, you know, that was a huge win. And it allowed us to stop arguing about operating systems and start arguing about software or not arguing, but developing it in positive ways. So with, you know, with Kubernetes, with container orchestration, we all agree, okay, that's just how we're going to orchestrate. Now we can build up this huge ecosystem, everybody gets taken along, right. And now it changes the game for what we're defining as business differentials, right. And so when we talk about crypto, that's a little bit harder, but certainly with AI, right, you know, what are the checks and balances that as an industry and as the developers around this, that we can in, you know, enforce to make sure that no one company or no one body is able to overly control how these things are managed, how it's defined. And I think that is only for the benefit in the industry as a whole, particularly when we think about the only other option is it gets regulated in ways that do not involve the people who actually know the details of what they're talking about. >> Regulated and or thrown away or bankrupt or- >> Driven underground. >> Yeah. >> Which would be even worse actually. >> Yeah, that's a really interesting, the checks and balances. I love that call out. And I was just talking with another interview part of the series around women being represented in the 51% ratio. Software is for everybody. So that we believe that open source movement around the collective intelligence of the participants in the industry and independent of gender, this is going to be the next wave. You're starting to see these videos really have impact because there are a lot more leaders now at the table in companies developing software systems and with AI, the aperture increases for applications. And this is the new dynamic. What's your guys view on this dynamic? How does this go forward in a positive way? Is there a certain trajectory you see? For women in the industry? >> I mean, I think some of the states are trying to, again, from the government angle, some of the states are trying to force women into the boardroom, for example, California, which can be no bad thing, but I don't know, sometimes I feel a bit iffy about all this kind of forced- >> John: Yeah. >> You know, making, I don't even know how to say it properly so you can cut this part of the interview. (John laughs) >> Tara: Well, and I think that they're >> I'll say it's not organic. >> No, and I think they're already pulling it out, right. It's already been challenged so they're in the process- >> Well, this is the open source angle, Tara, you are getting at it. The change agent is open, right? So to me, the history of the proven model is openness drives transparency drives progress. >> No, it's- >> If you believe that to be true, this could have another impact. >> Yeah, it's so interesting, right. Because if you look at McKinsey Consulting or Boston Consulting or some of the other, I'm blocking on all of the names. There has been a decade or more of research that shows that a non homogeneous employee base, be it gender or ethnicity or whatever, generates more revenue, right? There's dollar signs that can be attached to this, but it's not enough for all companies to want to invest in that way. And it's not enough for all, you know, venture firms or investment firms to grant that seed money or do those seed rounds. I think it's getting better very slowly, but socialization is a much harder thing to overcome over time. Particularly, when you're not just talking about one country like the United States in our case, but around the world. You know, tech centers now exist all over the world, including places that even 10 years ago we might not have expected like Nairobi, right. Which I think is amazing, but you have to factor in the cultural implications of that as well, right. So yes, the openness is important and we have, it's important that we have those voices, but I don't think it's a panacea solution, right. It's just one more piece. I think honestly that one of the most important opportunities has been with Cloud computing and Cloud's been around for a while. So why would I say that? It's because if you think about like everybody holds up the Steve Jobs, Steve Wozniak, back in the '70s, or Sergey and Larry for Google, you know, you had to have access to enough credit card limit to go to Fry's and buy your servers and then access to somebody like Susan Wojcicki to borrow the garage or whatever. But there was still a certain amount of upfrontness that you had to be able to commit to, whereas now, and we've, I think, seen a really good evidence of this being able to lease server resources by the second and have development platforms that you can do on your phone. I mean, for a while I think Africa, that the majority of development happened on mobile devices because there wasn't a sufficient supply chain of laptops yet. And that's no longer true now as far as I know. But like the power that that enables for people who would otherwise be underrepresented in our industry instantly opens it up, right? And so to me that's I think probably the biggest opportunity that we've seen from an industry on how to make more availability in underrepresented representation for entrepreneurship. >> Yeah. >> Something like AI, I think that's actually going to take us backwards if we're not careful. >> Yeah. >> Because of we're reinforcing that socialization. >> Well, also the bias. A lot of people commenting on the biases of the large language inherently built in are also problem. Lena, I want you to weigh on this too, because I think the skills question comes up here and I've been advocating that you don't need the pedigree, college pedigree, to get into a certain jobs, you mentioned Cloud computing. I mean, it's been around for you think a long time, but not really, really think about it. The ability to level up, okay, if you're going to join something new and half the jobs in cybersecurity are created in the past year, right? So, you have this what used to be a barrier, your degree, your pedigree, your certification would take years, would be a blocker. Now that's gone. >> Lena: Yeah, it's the opposite. >> That's, in fact, psychology. >> I think so, but the people who I, by and large, who I interview for jobs, they have, I think security people and also I work with our compliance folks and I can't forget them, but let's talk about security just now. I've always found a particular kind of mindset with security folks. We're very curious, not very good at following rules a lot of the time, and we'd love to teach others. I mean, that's one of the big things stem from the start of my career. People were always interested in teaching and I was interested in learning. So it was perfect. And I think also having, you know, strong women leaders at MongoDB allows other underrepresented groups to actually apply to the company 'cause they see that we're kind of talking the talk. And that's been important. I think it's really important. You know, you've got Tara and I on here today. There's obviously other senior women at MongoDB that you can talk to as well. There's a bunch of us. There's not a whole ton of us, but there's a bunch of us. And it's good. It's definitely growing. I've been there for four years now and I've seen a growth in women in senior leadership positions. And I think having that kind of track record of getting really good quality underrepresented candidates to not just interview, but come and join us, it's seen. And it's seen in the industry and people take notice and they're like, "Oh, okay, well if that person's working, you know, if Tara Hernandez is working there, I'm going to apply for that." And that in itself I think can really, you know, reap the rewards. But it's getting started. It's like how do you get your first strong female into that position or your first strong underrepresented person into that position? It's hard. I get it. If it was easy, we would've sold already. >> It's like anything. I want to see people like me, my friends in there. Am I going to be alone? Am I going to be of a group? It's a group psychology. Why wouldn't? So getting it out there is key. Is there skills that you think that people should pay attention to? One's come up as curiosity, learning. What are some of the best practices for folks trying to get into the tech field or that's in the tech field and advancing through? What advice are you guys- >> I mean, yeah, definitely, what I say to my team is within my budget, we try and give every at least one training course a year. And there's so much free stuff out there as well. But, you know, keep learning. And even if it's not right in your wheelhouse, don't pick about it. Don't, you know, take a look at what else could be out there that could interest you and then go for it. You know, what does it take you few minutes each night to read a book on something that might change your entire career? You know, be enthusiastic about the opportunities out there. And there's so many opportunities in security. Just so many. >> Tara, what's your advice for folks out there? Tons of stuff to taste, taste test, try things. >> Absolutely. I mean, I always say, you know, my primary qualifications for people, I'm looking for them to be smart and motivated, right. Because the industry changes so quickly. What we're doing now versus what we did even last year versus five years ago, you know, is completely different though themes are certainly the same. You know, we still have to code and we still have to compile that code or package the code and ship the code so, you know, how well can we adapt to these new things instead of creating floppy disks, which was my first job. Five and a quarters, even. The big ones. >> That's old school, OG. There it is. Well done. >> And now it's, you know, containers, you know, (indistinct) image containers. And so, you know, I've gotten a lot of really great success hiring boot campers, you know, career transitioners. Because they bring a lot experience in addition to the technical skills. I think the most important thing is to experiment and figuring out what do you like, because, you know, maybe you are really into security or maybe you're really into like deep level coding and you want to go back, you know, try to go to school to get a degree where you would actually want that level of learning. Or maybe you're a front end engineer, you want to be full stacked. Like there's so many different things, data science, right. Maybe you want to go learn R right. You know, I think it's like figure out what you like because once you find that, that in turn is going to energize you 'cause you're going to feel motivated. I think the worst thing you could do is try to force yourself to learn something that you really could not care less about. That's just the worst. You're going in handicapped. >> Yeah and there's choices now versus when we were breaking into the business. It was like, okay, you software engineer. They call it software engineering, that's all it was. You were that or you were in sales. Like, you know, some sort of systems engineer or sales and now it's,- >> I had never heard of my job when I was in school, right. I didn't even know it was a possibility. But there's so many different types of technical roles, you know, absolutely. >> It's so exciting. I wish I was young again. >> One of the- >> Me too. (Lena laughs) >> I don't. I like the age I am. So one of the things that I did to kind of harness that curiosity is we've set up a security champions programs. About 120, I guess, volunteers globally. And these are people from all different backgrounds and all genders, diversity groups, underrepresented groups, we feel are now represented within this champions program. And people basically give up about an hour or two of their time each week, with their supervisors permission, and we basically teach them different things about security. And we've now had seven full-time people move from different areas within MongoDB into my team as a result of that program. So, you know, monetarily and time, yeah, saved us both. But also we're showing people that there is a path, you know, if you start off in Tara's team, for example, doing X, you join the champions program, you're like, "You know, I'd really like to get into red teaming. That would be so cool." If it fits, then we make that happen. And that has been really important for me, especially to give, you know, the women in the underrepresented groups within MongoDB just that window into something they might never have seen otherwise. >> That's a great common fit is fit matters. Also that getting access to what you fit is also access to either mentoring or sponsorship or some sort of, at least some navigation. Like what's out there and not being afraid to like, you know, just ask. >> Yeah, we just actually kicked off our big mentor program last week, so I'm the executive sponsor of that. I know Tara is part of it, which is fantastic. >> We'll put a plug in for it. Go ahead. >> Yeah, no, it's amazing. There's, gosh, I don't even know the numbers anymore, but there's a lot of people involved in this and so much so that we've had to set up mentoring groups rather than one-on-one. And I think it was 45% of the mentors are actually male, which is quite incredible for a program called Mentor Her. And then what we want to do in the future is actually create a program called Mentor Them so that it's not, you know, not just on the female and so that we can live other groups represented and, you know, kind of break down those groups a wee bit more and have some more granularity in the offering. >> Tara, talk about mentoring and sponsorship. Open source has been there for a long time. People help each other. It's community-oriented. What's your view of how to work with mentors and sponsors if someone's moving through ranks? >> You know, one of the things that was really interesting, unfortunately, in some of the earliest open source communities is there was a lot of pervasive misogyny to be perfectly honest. >> Yeah. >> And one of the important adaptations that we made as an open source community was the idea, an introduction of code of conducts. And so when I'm talking to women who are thinking about expanding their skills, I encourage them to join open source communities to have opportunity, even if they're not getting paid for it, you know, to develop their skills to work with people to get those code reviews, right. I'm like, "Whatever you join, make sure they have a code of conduct and a good leadership team. It's very important." And there are plenty, right. And then that idea has come into, you know, conferences now. So now conferences have codes of contact, if there are any good, and maybe not all of them, but most of them, right. And the ideas of expanding that idea of intentional healthy culture. >> John: Yeah. >> As a business goal and business differentiator. I mean, I won't lie, when I was recruited to come to MongoDB, the culture that I was able to discern through talking to people, in addition to seeing that there was actually women in senior leadership roles like Lena, like Kayla Nelson, that was a huge win. And so it just builds on momentum. And so now, you know, those of us who are in that are now representing. And so that kind of reinforces, but it's all ties together, right. As the open source world goes, particularly for a company like MongoDB, which has an open source product, you know, and our community builds. You know, it's a good thing to be mindful of for us, how we interact with the community and you know, because that could also become an opportunity for recruiting. >> John: Yeah. >> Right. So we, in addition to people who might become advocates on Mongo's behalf in their own company as a solution for themselves, so. >> You guys had great successful company and great leadership there. I mean, I can't tell you how many times someone's told me "MongoDB doesn't scale. It's going to be dead next year." I mean, I was going back 10 years. It's like, just keeps getting better and better. You guys do a great job. So it's so fun to see the success of developers. Really appreciate you guys coming on the program. Final question, what are you guys excited about to end the segment? We'll give you guys the last word. Lena will start with you and Tara, you can wrap us up. What are you excited about? >> I'm excited to see what this year brings. I think with ChatGPT and its copycats, I think it'll be a very interesting year when it comes to AI and always in the lookout for the authentic deep fakes that we see coming out. So just trying to make people aware that this is a real thing. It's not just pretend. And then of course, our old friend ransomware, let's see where that's going to go. >> John: Yeah. >> And let's see where we get to and just genuine hygiene and housekeeping when it comes to security. >> Excellent. Tara. >> Ah, well for us, you know, we're always constantly trying to up our game from a security perspective in the software development life cycle. But also, you know, what can we do? You know, one interesting application of AI that maybe Google doesn't like to talk about is it is really cool as an addendum to search and you know, how we might incorporate that as far as our learning environment and developer productivity, and how can we enable our developers to be more efficient, productive in their day-to-day work. So, I don't know, there's all kinds of opportunities that we're looking at for how we might improve that process here at MongoDB and then maybe be able to share it with the world. One of the things I love about working at MongoDB is we get to use our own products, right. And so being able to have this interesting document database in order to put information and then maybe apply some sort of AI to get it out again, is something that we may well be looking at, if not this year, then certainly in the coming year. >> Awesome. Lena Smart, the chief information security officer. Tara Hernandez, vice president developer of productivity from MongoDB. Thank you so much for sharing here on International Women's Day. We're going to do this quarterly every year. We're going to do it and then we're going to do quarterly updates. Thank you so much for being part of this program. >> Thank you. >> Thanks for having us. >> Okay, this is theCube's coverage of International Women's Day. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(soft corporate jingle) >> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat jingle intro) >> Welcome back to Barcelona. We're here live at the Fira. (laughs) Just amazing day two of MWC23. It's packed today. It was packed yesterday. It's even more packed today. All the news is flowing. Check out siliconangle.com. John Furrier is in the studio in Palo Alto breaking all the news. And, we are here live. Really excited to have Udayan Mukherjee who's the Senior Fellow and Chief Architect of wireless product at Network and Edge for Intel. And, Manish Singh is back. He's the CTO of Telecom Systems Business at Dell Jets. Welcome. >> Thank you. >> Thank you >> We're going to talk about greening the network. I wonder, Udayan, if you could just set up why that's so important. I mean, it's obvious that it's an important thing, great for the environment, but why is it extra important in Telco? >> Yeah, thank you. Actually, I'll tell you, this morning I had a discussion with an operator. The first thing he said, that the electricity consumption is more expensive nowadays that total real estate that he's spending money on. So, it's like that is the number one thing that if you can change that, bring that power consumption down. And, if you talk about sustainability, look what is happening in Europe, what's happening in all the electricity areas. That's the critical element that we need to address. Whether we are defining chip, platforms, storage systems, that's the number one mantra right now. You know, reduce the power. Electricity consumption, because it's a sustainable planet that we are living in. >> So, you got CapEx and OpEx. We're talking about the big piece of OpEx is now power consumption? >> Power Consumption >> That's the point. Okay, so in my experience, servers are the big culprit for power consumption, which is powered by core semiconductors and microprocessors. So, what's the strategy to reduce the power consumption? You're probably not going to reduce the bill overall. You maybe just can keep pace, but from a technical standpoint, how do you attack that? >> Yeah, there are multiple defined ways of adding. Obviously the process technology, that micro (indistinct) itself is evolving to make it more low-power systems. But, even within the silicon, the server that we develop, if you look in a CPU, there is a lot of power states. So, if you have a 32 code platform, as an example, every code you can vary the frequency and the C-states, power states. So, if you look into any traffic, whether it's a radio access network, packet code. At any given time the load is not peak. So, your power consumption, actual what we are drawing from the wall, it also needs to vary with that. So, that's how if you look into this there's a huge savings. If you go to Intel booth or Ericson booth or anyone, you will see right now every possible, the packet code, radio access network, everything network. They're talking about our energy consumption, how they're lowering this. These states, as we call it power states, C-state P-state they've built in intel chip for a long time. The cloud providers are taking advantage of it. But Telcos, with even two generation before they used to actually switch it off in the bios. I say no, we need peak. Now, that thing is changing. Now, it's all like, how do I take advantage of the built in technologies? >> I remember the enterprise virtualization, Manish, was a big play. I remember PG&E used to give rebates to customers that would install virtualized software, VMware. >> And SSDs. >> Yeah. And SSDs, you know, yes. Because, the spinning disc was, but, nowhere near with a server consumption. So, how virtualized is the telco network? And then, what I'm saying is there other things, other knobs, you can of course turn. So, what's your perspective on this as a server player? >> Yeah, absolutely. Let me just back up a little bit and start at the big picture to share what Udayan said. Here, day two, every conversation I've had yesterday and today morning with every operator, every CTO, they're coming in and first topic they're talking about is energy. And, the reason is, A, it's the right thing to do, sustainability, but, it's also becoming a P&L issue. And, the reason it's becoming a P&L issue is because we are in this energy inflationary environment where the energy costs are constantly going up. So, it's becoming really important for the service providers to really drive more efficiency onto their networks, onto their infrastructure. Number one. Two, then to your question on what all knobs need to be turned on, and what are the knobs? So, Udayan talked about within the intel, silicon, the C-states, P-states and all these capabilities that are being brought up, absolutely important. But again, if we take a macro view of it. First of all, there are opportunities to do infrastructure audit. What's on, why is it on, does it need to be on right now? Number two, there are opportunities to do infrastructure upgrade. And, what I mean by that is as you go from previous generation servers to next generation servers, better cooling, better performance. And through all of that you start to gain power usage efficiency inside a data center. And, you take that out more into the networks you start to achieve same outcomes on the network site. Think about from a cooling perspective, air cooling but for that matter, even liquid cooling, especially inside the data centers. All opportunities around PUE, because PUE, power usage efficiency and improvement on PUE is an opportunity. But, I'll take it even further. Workloads that are coming onto it, core, RAN, these workloads based on the dynamic traffic. Look, if you look at the traffic inside a network, it's not constant, it's varied. As the traffic patterns change, can you reduce the amount of infrastructure you're using? I.e. reduce the amount of power that you're using and when the traffic loads are going up. So, the workloads themselves need to become more smarter about that. And last, but not the least. From an orchestration layer if you think about it, where you are placing these workloads, and depending on what's available, you can start to again, drive better energy outcomes. And, not to forget acceleration. Where you need acceleration, can you have the right hardware infrastructures delivering the right kind of accelerations to again, improve those energy efficiency outcomes. So, it's a complex problem. But, there are a lot of levers, lot of tools that are in place that the service providers, the technology builders like us, are building the infrastructure, and then the workload providers all come together to really solve this problem. >> Yeah, Udayan, Manish mentioned this idea of moving from one generation to a new generation and gaining benefits. Out there on the street, if you will. Most of the time it's an N plus 2 migration. It's not just moving from last generation to this next generation, but it's really a generation ago. So, those significant changes in the dynamics around power density and cooling are meaningful? You talk about where performance should be? We start talking about the edge. It's hard to have a full-blown raised data center floor edge everywhere. Do these advances fundamentally change the kinds of things that you can do at the base of a tower? >> Yeah, absolutely. Manish talked about that, the dynamic nature of the workload. So, we are using a lot of this AIML to actually predict. Like for example, your multiple force in a systems. So, why is the 32 core as a system, why is all running? So, your traffic profile in the night times. So, you are in the office areas, in the night has gone home and nowadays everybody's working from remote anyway. So, why is this thing a full blown, spending the TDP, the total power and extreme powers. You bring it down, different power states, C-states. We talked about it. Deeper C-states or P-states, you bring the frequency down. So, lot of those automation, even at the base of the tower. Lot of our deployment right now, we are doing a whole bunch of massive MIMO deployment. Virtual RAN in Verizon network. All actually cell-site deployment. Those eight centers are very close to the cell-site. And, they're doing aggressive power management. So, you don't have to go to a huge data centers, even there's a small rack of systems, four to five, 10 systems, you can do aggressive power management. And, you built it up that way. >> Okay. >> If I may just build on what Udayan said. I mean if you look at the radio access network, right? And, let's start at the bottom of the tower itself. The infrastructure that's going in there, especially with Open RAN, if you think about it, there are opportunities now to do a centralized RAN where you could do more BBU pooling. And, with that, not only on a given tower but across a given given coverage area, depending on what the traffics are, you can again get the infrastructure to become more efficient in terms of what traffic, what needs are, and really start to benefit. The pooling gains which is obviously going to give you benefit on the CapEx side, but from an energy standpoint going to give you benefits on the OpEx side of things. So that's important. The second thing I will say is we cannot forget, especially on the radio access side of things, that it's not just the bottom of the tower what's happening there. What's happening on the top of the tower especially with the radio, that's super important. And, that goes into how do you drive better PA efficiency, how do you drive better DPD in there? This is where again, applying AI machine learning there is a significant amount of opportunity there to improve the PA performance itself. But then, not only that, looking at traffic patterns. Can you do sleep modes, micro sleep modes to deep sleep modes. Turning down the cells itself, depending on the traffic patterns. So, these are all areas that are now becoming more and more important. And, clearly with our ecosystem of partners we are continuing to work on these. >> So we hear from the operators, it's an OpEx issue. It's hitting the P&L. They're in search of PUE of one. And, they've historically been wasteful, they go full throttle. And now, you're saying with intelligence you can optimize that consumption. So, where does the intelligence live? Is it in the rig. Where is it all throughout the network? Is it in the silicon? Maybe you could paint a picture as to where those smarts exist. >> I can start. It's across the stack. It starts, we talked about the C-states, P-states. If you want to take advantage of that, that intelligence is in the workload, which has to understand when can I really start to clock things down or turn off the cores. If you really look at it from a traffic pattern perspective you start to really look at a rig level where you can have power. And, we are working with the ecosystem partners who are looking at applying machine learning on that to see what can we really start to turn on, turn off, throttle things down, depending on what the, so yes, it's across the stack. And lastly, again, I'll go back to cannot forget orchestration, where you again have the ability to move some of these workloads and look at where your workload placements are happening depending on what infrastructure is and what the traffic needs are at that point in time. So it's, again, there's no silver bullet. It has to be looked across the stack. >> And, this is where actually if I may, last two years a sea change has happened. People used to say, okay there are C-states and P-states, there's silicon every code. OS operating system has a governor built in. We rely on that. So, that used to be the way. Now that applications are getting smarter, if you look at a radio access network or the packet core on the control plane signaling application, they're more aware of the what is the underlying silicon power state sleep states are available. So, every time they find some of these areas there's no enough traffic there, they immediately goes to a transition. So, the workload has become more intelligent. The rig application we talked about. Every possible rig application right now are apps on xApps. Most of them are on energy efficiency. How are they using it? So, I think lot more even the last two years. >> Can I just say one more thing there right? >> Yeah. >> We cannot forget the infrastructure as well, right? I mean, that's the most important thing. That's where the energy is really getting drawn in. And, constant improvement on the infrastructure. And, I'll give you some data points, right? If you really look at the power at servers, right? From 2013 to 2023, like a decade. 85% energy intensity improvement, right? So, these gains are coming from performance with better cooling, better technology applications. So, that's super critical, that's important. And, also to just give you another data point. Apart from the infrastructure what cache layers we are running and how much CPU and compute requirements are there, that's also important. So, looking at it from a cache perspective are we optimizing the required infrastructure blocks for radio access versus core? And again, really taking that back to energy efficiency outcomes. So, some of the work we've been doing with Wind River and Red Hat and some of our ecosystem partners around that for radio access network versus core. Really again, optimizing for those different use cases and the outcomes of those start to come in from an energy utilization perspective >> So, 85% improvement in power consumption. Of course you're doing, I don't know, 2, 300% more work, right? So, let's say, and I'm just sort of spit balling numbers but, let's say that historically powers on the P&L has been, I don't know, single digits, maybe 10%. Now, it's popping up the much higher. >> Udayan: Huge >> Right? >> I mean, I don't know what the number is. Is it over 20% in some cases or is it, do you have a sense of that? Or let's say it is. The objective I presume is you're probably not going to lower the power bill overall, but you're going to be able to lower the percent of cost on the OpEx as you grow, right? I mean, we're talking about 5G networks. So much more data >> Capacity increasing. >> Yeah, and so is it, am I right about that the carriers, the best they can hope for is to sort of stay even on that percentage or maybe somewhat lower that percentage? Or, do you think they can actually cut the bill? What's the goal? What are they trying to do? >> The goal is to cut the bill. >> It is! >> And the way you get started to cut the bill is, as I said, first of all on the radio side. Start to see where the improvements are and look, there's not a whole lot there to be done. I mean, the PS are as efficient as they can be, but as I said, there are things in DPD and all that still can be improved. But then, sleep modes and all, yes there are efficiencies in there. But, I'll give you one important, another interesting data point. We did a work with ACG Research on our 16G platform. The power edge service that we have recently launched based on Intel's Sapphire Rapids. And, if you look at the study there. 30% TCR reduction, 10% in CapEx gains, 30% in OpEx gains from moving away from these legacy monolithic architectures to cloud native architectures. And, a large part of that OpEx gain really starts to come from energy to the point of 800 metric tonnes of carbon reduction to the point of you could have, and if you really translate that to around 160 homes electric use per year, right? So yes, I mean the opportunity there is to reduce the bill. >> Wow, that's big, big goal guys. We got to run. But, thank you for informing the audience on the importance and how you get there. So, appreciate that. >> One thing that bears mentioning really quickly before we wrap, a lot of these things we're talking about are happening in remote locations. >> Oh, back to that point of distributed nature of telecom. >> Yes, we talked about a BBU being at the base of a tower that could be up on a mountain somewhere. >> No, you made the point. You can't just say, oh, hey we're going to go find ambient air or going to go... >> They don't necessarily... >> Go next to a waterfall. >> We don't necessarily have the greatest hydro tower. >> All right, we got to go. Thanks you guys. Alright, keep it right there. Wall to wall coverage is day two of theCUBE's coverage of MWC 23. Stay right there, we'll be right back. (corporate outro jingle)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Welcome to the Fira in Barcelona, everybody. This is theCUBE's coverage of MWC 23, day one of that coverage. We have four days of wall-to-wall action going on, the place is going crazy. I'm here with Dave Nicholson, Lisa Martin is also in the house. Today's ecosystem day, and we're really excited to have Manish Singh who's the CTO of the Telecom Systems Business unit at Dell Technologies. He's joined by Doug Wolf who's the head of strategy for the Telecom Systems Business unit at Dell. Gents, welcome. What a show. I mean really the first major MWC or used to be Mobile World Congress since you guys have launched your telecom business, you kind of did that sort of in the Covid transition, but really exciting, obviously a huge, huge venue to match the huge market. So Manish, how did you guys get into this? What did you see? What was the overall thinking to get Dell into this business? >> Manish: Yeah, well, I mean just to start with you know, if you look at the telecom ecosystem today, the service providers in particular, they are looking for network transformation, driving more disaggregation into their network so that they can get better utilization of the infrastructure, but then also get more agility, more cloud native characteristics onto their, for their networks in particular. And then further on, it's important for them to really start to accelerate the pace of innovation on the networks itself, to start more supply chain diversity, that's one of the challenges that they've been having. And so there've been all these market forces that have been really getting these service providers to really start to transform the way they have built the infrastructure in the past, which was legacy monolithic architectures to more cloud native disaggregated. And from a Dell perspective, you know, that really gives us the permission to play, to really, given all the expertise on the work we have done in the IT with all the IT transformations to leverage all that expertise and bring that to the service providers and really help them in accelerating their network transformation. So that's where the journey started. We've been obviously ever since then working on expanding the product portfolio on our compute platforms to bring Teleco great compute platforms with more capabilities than we can talk about that. But then working with partners and building the ecosystem to again create this disaggregated and open ecosystem that will be more cloud native and really meet the objective that the service providers are after. >> Dave Vellante: Great, thank you. So, Doug the strategy obviously is to attack this market, as Manish said, from an open standpoint, that's sort of new territory. It's like a little bit like the wild, wild west. So maybe you could double click on what Manish was saying from a, from a strategy standpoint, yes, the Telecos need to be more flexible, they need to be more open, but they also need this reliability piece. So talk about that from a strategy standpoint of what you guys saw. >> Doug: Yeah, absolutely. As Manish mentioned, you know, Dell getting into open systems isn't something new. You know, Dell has been kind of playing in that world for years and years, but the opportunity in Telecom that came was opening of the RAN, the core network, the edge, all of these with 5G really created a wide opening for us. So we started developing products and solutions, you know, built our first Telecom grade servers for open RAN over the last year, we'll talk about those at the show. But you know, as, as Manish mentioned, an open ecosystem is new to Telecom. I've been in the Telecom business along with Manish for, you know, 25 plus years and this is a new thing that they're embarking on. So started with virtualization about five, six years ago, and now moving to cloud native architectures on the core, suddenly there's this need to have multiple parties partner really well, share specifications, and put that together for an operator to consume. And I think that's just the start of really where all the challenges are and the opportunities that we see. >> Where are we in this transition cycle? When the average consumer hears 5G, feels like it's been around for a long time because it was hyped beforehand. >> Doug: Yeah. >> If you're talking about moving to an open infrastructure model from a proprietary closed model, when is the opportunity for Dell to become part of that? Is it, are there specific sites that have already transitioned to 5G, therefore they've either made the decision to be open or not? Or are there places where the 5G transition has taken place, and they might then make a transition to open brand with 5G? Where, where are we in that cycle? What does the opportunity look like? >> I'll kind of take it from the typology of the operator, and I'm sure Manish will build on this, but if I look back on the core, started to get virtualized you know, back around 2015-16 with some of the lead operators like AT&T et cetera. So Dell has been partnering with those operators for some years. So it really, it's happening on the core, but it's moving with 5G to more of a cloud-like architecture, number one. And number two, they're going beyond just virtualizing the network. You know, they previously had used OpenStack and most of them are migrating to more of a cloud native architecture that Manish mentioned. And that is a bit different in terms of there's more software vendors in that ecosystem because the software is disaggregated also. So Dell's been playing in the core for a number of years, but we brought out new solutions we've announced at the show for the core. And the parts that are really starting that transition of maybe where the core was back in 2015 is on the RAN and on the edge in particular. >> Because NFV kind of predated the ascendancy of cloud. >> Exactly, yeah. >> Right, so it really didn't have the impact that people had hoped. And there's some, when you look back, 'cause it's not same wine, new bottle as the open systems movement, there are a lot of similarities but you know, you mentioned cloud, and cloud native, you really didn't have, back in the nineties, true engineered systems. You didn't really have AI that, you know, to speak of at the sort of volume of the data that we have. So Manish, from a CTO's perspective, how are you attacking some of those differences in bringing that to market? >> Manish: Yeah, I mean, I think you touched on some very important points there. So first of all, the duck's point, a lot of this transformation started in the core, right? And as the technology evolution progress, the opportunities opened up. It has now come into the edge and the radio access network as well, in particular with open RAN. And so when we talk about the disaggregation of the infrastructure from the software itself and an open ecosystem, this now starts to create the opportunity to accelerate innovation. And I really want to pick up on the point that you'd said on AI, for example. AI and machine learning bring a whole new set of capabilities and opportunities for these service providers to drive better optimization, better performance, better sustainability and energy efficiency on their infrastructure, on and on and on. But to really tap into these technologies, they really need to open that up to third parties implementation solutions that are coming up. And again, the end objective remains to accelerate that innovation. Now that said, all these things need to be brought together, right? And delivered and deployed in the network without any degradation in the KPIs and actually improving the performance on different vectors, right? So this is what the current state of play is. And with this aggregation I'm definitely a believer that all these new technologies, including AI, machine learning, and there's a whole area, host area of problems that can be solved and attacked and are actually getting attacked by applying AI and machine learning onto these networks. >> Open obviously is good. Nobody's ever going to, you know, argue that open is a bad thing. It's like democracy is a good thing, right? At least amongst us. And so, but, the RAN, the open RAN, has to be as reliable and performant, right, as these, closed networks. Or maybe not, maybe it doesn't have to be identical. Just has to be close enough in order for that tipping point to occur. Is that a fair summarization? What are you guys hearing from carriers in terms of their willingness to sort of put their toe in the water and, and what could we expect in terms of the maturity model of, of open RAN and adoption? >> Right, so I mean I think on, on performance that, that's a tough one. I think the operators will demand performance and you've seen experiments, you've really seen more of the Greenfield operators kind of launch. >> Okay. >> Doug: Open RAN or vRAN type solutions. >> So they're going to disrupt. >> Doug: Yeah, they're going to disrupt. >> Yeah. >> Doug: And there's flexibility in an open RAN architecture also for 5G that they, that they're interested in and I think the Brownfield operators are too, but let's say maybe the Greenfield jump first in terms of doing that from a mass deployment perspective. But I still think that it's going to be critical to meet very similar SLAs and end user performance. And, you know, I think that's where, you know, maturity of that model is what's required. I think Brownfield operators are conservative in terms of, you know, going with something they know, but the opportunities and the benefits of that architecture and building new flexible, potentially cost advantaged over time solutions, that's what the, where the real interest is going forward. >> And new services that you can introduce much more quickly. You know, the interesting thing about Dell to me, you don't compete with the carriers, the public cloud vendors though, the carriers are concerned about them sort of doing an end run on them. So you provide a potential partnership for the carriers that's non-threatening, right? 'Cause you're, you're an arms dealer, you're selling hardware and software, right? But, but how do you see that? Because we heard in the keynote today, one of the Teleco, I think it was the chairman of Telefonica said, you know, cloud guys can't do this alone. You know, they need, you know, this massive, you know, build out. And so, what do you think about that in terms of your relationship with the carriers not being threatening? I mean versus say potentially the cloud guys, who are also your partners, I understand, it's a really interesting dynamic, isn't it? >> Manish: Yeah, I mean I think, you know, I mean, the way I look at it, the carriers actually need someone like Dell who really come in who can bring in the right capabilities, the right infrastructure, but also bring in the ecosystem together and deliver a performance solution that they can deploy and that they can trust, number one. Number two, to your point on cloud, I mean, from a Dell perspective, you know, we announced our Dell Telecom Multicloud Foundation and as part of that last year in September, we announced what we call is the Dell Telecom Infrastructure Blocks. The first one we announced with Wind River, and this is, think of it as the, you know, hardware and the cashier all pre-integrated with lot of automation around it, factory integrated, you know, delivered to customers in an integrated model with all the licenses, everything. And so it starts to solve the day zero, day one, day two integration deployment and then lifecycle management for them. So to broaden the discussion, our view is it's a multicloud world, the future is multicloud where you can have different clouds which can be optimized for different workloads. So for example, while our work with Wind River initially was very focused on virtualization of the radio access network, we just announced our infrastructure block with Red Hat, which is very much targeted and optimized for core network and edge, right? So, you know, there are different workflows which will require different capabilities also. And so, you know, again, we are bringing those things to these service providers to again, bring those cloud characteristics and cloud native architecture for their network. >> And It's going to be hybrid, to your point. >> David N.: And you, just hit on something, you said cloud characteristics. >> Yeah. >> If you look at this through the lens of kind of the general world of IT, sometimes when people hear the word cloud, they immediately leap to the idea that it's a hyperscale cloud provider. In this scenario we're talking about radio towers that have intelligence living on them and physically at the base. And so the cloud characteristics that you're delivering might be living physically in these remote locations all over the place, is that correct? >> Yeah, I mean that, that's true. That will definitely happen over time. But I think, I think we've seen the hyperscalers enter, you know, public cloud providers, enter at the edge and they're dabbling maybe with private, but I think the public RAN is another further challenge. I think that maybe a little bit down the road for them. So I think that is a different characteristic that you're talking about managing the macro RAN environment. >> Manish: If I may just add one more perspective of this cloud, and I mean, again, the hyperscale cloud, right? I mean that world's been great when you can centralize a lot of compute capability and you can then start to, you know, do workload aggregation and use the infrastructure more efficient. When it comes to Telecom, it is inherently it distributed architecture where you have access, you talked about radio access, your port, and it is inherently distributed because it has to provide the coverage and capacity. And so, you know, it does require different kind of capabilities when you're going out and about, and this is where I was talking about things like, you know, we just talked, we just have been working on our bare metal orchestration, right? This is what we are bringing is a capability where you can actually have distributed infrastructure, you can deploy, you can actually manage, do lifecycle management, in a distributed multicloud form. So it does require, you know, different set of capabilities that need to be enabled. >> Some, when talking about cloud, would argue that it's always been information technology, it always will be information technology, and especially as what we might refer to as public cloud or hyperscale cloud providers, are delivering things essentially on premises. It's like, well, is that cloud? Because it feels like some of those players are going to be delivering physical infrastructure outside of their own data centers in order to address this. It seems the nature, the nature of the beast is that some of these things need to be distributed. So it seems perfectly situated for Dell. That's why you guys are both at Dell now and not working for other Telecom places, right? >> Exactly. Exactly, yes. >> It's definitely an exciting space. It's transformed, the networks are under transformation and I do think that Dell's very well positioned to, to really help the customers, the service providers in accelerating their transformation journey with an open ecosystem. >> Dave V.: You've got the brand, and the breadth, and the resources to actually attract an ecosystem. But I wonder if you could sort of take us through your strategy of ecosystem, the challenges that you've seen in developing that ecosystem and what the vision is that ultimately, what's the outcome going to be of that open ecosystem? >> Yeah, I can start. So maybe just to give you the big picture, right? I mean the big picture, is disaggregation with performance, right, TCO models to the service providers, right? And it starts at the infrastructure layer, builds on bringing these cloud capabilities, the cast layer, right? Bringing the right accelerators. All of this requires to pull the ecosystem. So give you an example on the infrastructure in a Teleco grade servers like XR8000 with Sapphire, the new intel processors that we've just announced, and an extended array of servers. These are Teleco grade, short depth, et cetera. You know, the Teleco great characteristic. Working with the partners like Marvel for bringing in the accelerators in there, that's important to again, drive the performance and optimize for the TCO. Working then with partners like Wind River, Red Hat, et cetera, to bring in the cast capabilities so you can start to see how this ecosystem starts to build up. And then very recently we announced our private 5G solution with AirSpan and Expeto on the core site. So bringing those workloads together. Similarly, we have an open RAN solution we announce with Fujitsu. So it's, it's open, it's disaggregated, but bringing all these together. And one of the last things I would say is, you know, to make all this happen and make all of these, we've also been putting together our OTEL, our open Telecom ecosystem lab, which is very much geared, really gives this open ecosystem a playground where they can come in and do all that heavy lifting, which is anyways required, to do the integration, optimization, and board. So put all these capabilities in place, but the end goal, the end vision again, is that cloud native disaggregated infrastructure that starts to innovate at the speed of software and scales at the speed of cloud. >> And this is different than the nineties. You didn't have something like OTEL back then, you know, you didn't have the developer ecosystem that you have today because on top of everything that you just said, Manish, are new workloads and new applications that are going to be developed. Doug, anything you'd add to what Manish said? >> Doug: Yeah, I mean, as Manish said, I think adding to the infrastructure layers, which are, you know, critical for us to, to help integrate, right? Because we kind of took a vertical Teleco stack and we've disaggregated it, and it's gotten a little bit more complex. So our Solutions Dell Technology infrastructure block, and our lab infrastructure with OTEL, helps put those pieces together. But without the software players in this, you know, that's what we really do, I think in OTEL. And that's just starting to grow. So integrating with those software providers with that integration is something that the operators need. So we fill a gap there in terms of either providing engineered solutions so they can readily build on or actually bringing in that software provider. And I think that's what you're going to see more from us going forward is just extending that ecosystem even further. More software players effectively. >> In thinking about O-RAN, are they, is it possible to have the low latency, the high performance, the reliability capabilities that carriers are used to and the flexibility? Or can you sort of prioritize one over the other from a go to market and rollout standpoint and optimize one, maybe get a foothold in the market? How do you see that balance? >> Manish: Oh the answer is absolutely yes you can have both We are on that journey, we are on that journey. This is where all these things I was talking about in terms of the right kind of accelerators, right kind of capabilities on the infrastructure, obviously retargeting the software, there are certain changes, et cetera that need to be done on the software itself to make it more cloud native. And then building all the surrounding capabilities around the CICD pipeline and all where it's not just day zero or day one that you're doing the cloud-like lifecycle management of this infrastructure. But the answer to your point, yes, absolutely. It's possible, the technology is there, and the ecosystem is coming together, and that's the direction. Now, are there challenges? Absolutely there are challenges, but directionally that's the direction the industry is moving to. >> Dave V.: I guess my question, Manish, is do they have to go in lockstep? Because I would argue that the public cloud when it first came out wasn't nearly as functional as what I could get from my own data center in terms of recovery, you know, backup and recovery is a perfect example and it took, you know, a decade plus to get there. But it was the flexibility, and the openness, and the developer affinity, the programmability, that attracted people. Do you see O-RAN following a similar path? Or does it, my question is does it have to have that carrier class reliability today? >> David N.: Everything on day one, does it have to have everything on day one? >> Yeah, I mean, I would say, you know, like again, the Greenfield operators I think we're, we're willing do a little bit more experimentation. I think the operators, Brownfield operators that have existing, you know, deployments, they're going to want to be closer. But I think there's room for innovation here. And clearly, you know, Manish came from, from Meta and we're, we've been very involved with TIP, we're very involved with the O-RAN alliance, and as Manish mentioned, with all those accelerators that we're working with on our infrastructure, that is a space that we're trying to help move the ball forward. So I think you're seeing deployments from mainstream operators, but it's maybe not in, you know, downtown New York deployment, they're more rural deployments. I think that's getting at, you know, kind of your question is there's maybe a little bit more flexibility there, they get to experiment with the technology and the flexibility and then I think it will start to evolve >> Dave V.: And that's where the disruption's going to come from, I think. >> David N.: Well, where was the first place you could get reliable 4K streaming of video content? It wasn't ABC, CBS, NBC. It was YouTube. >> Right. >> So is it possible that when you say Greenfield, are a lot of those going to be what we refer to as private 5G networks where someone may set up a private 5G network that has more functions and capabilities than the public network? >> That's exactly where I was going is that, you know, that that's why you're seeing us getting very active in 5G solutions that Manish mentioned with, you know, Expeto and AirSpan. There's more of those that we haven't publicly announced. So I think you'll be seeing more announcements from us, but that is really, you know, a new opportunity. And there's spectrum there also, right? I mean, there's public and private spectrum. We plan to work directly with the operators and do it in their spectrum when needed. But we also have solutions that will do it, you know, on non-public spectrum. >> So let's close out, oh go ahead. You you have something to add there? >> I'm just going to add one more point to Doug's point, right? Is if you look on the private 5G and the end customer, it's the enterprise, right? And they're, they're not a service provider. They're not a carrier. They're more used to deploying, you know, enterprise infrastructure, maintaining, managing that. So, you know, private 5G, especially with this open ecosystem and with all the open run capabilities, it naturally tends to, you know, blend itself very well to meet those requirements that the enterprise would have. >> And people should not think of private 5G as a sort of a replacement for wifi, right? It's to to deal with those, you know, intense situations that can afford the additional cost, but absolutely require the reliability and the performance and, you know, never go down type of scenario. Is that right? >> Doug: And low latencies usually, the primary characteristics, you know, for things like Industry 4.0 manufacturing requirements, those are tough SLAs. They're just, they're different than the operator SLAs for coverage and, you know, cell performance. They're now, you know, Five9 type characteristics, but on a manufacturing floor. >> That's why we don't use wifi on theCUBE to broadcast, we need a hard line. >> Yeah, but why wouldn't it replace wifi over time? I mean, you know, I still have a home phone number that's hardwired to align, but it goes to a voicemail. We don't even have handset anymore for it, yeah. >> I think, well, unless the cost can come down, but I think that wifi is flexible, it's cheap. It's, it's kind of perfect for that. >> Manish: And it's good technology. >> Dave V.: And it works great. >> David N.: For now, for now. >> Dave V.: But you wouldn't want it in those situations, and you're arguing that maybe. >> I'm saying eventually, what, put a sim in a device, I don't know, you know, but why not? >> Yeah, I mean, you know, and Dell offers, you know, from our laptop, you know, our client side, we do offer wifi, we do offer 4G and 5G solutions. And I think those, you know, it's a volume and scale issue, I think for the cost structure you're talking about. >> Manish: Come to our booth and see the connected laptop. >> Dave V.: Well let's, let's close on that. Why don't you guys talk a little bit about what you're going on at the show, I did go by the booth, you got a whole big lineup of servers. You got some, you know, cool devices going on. So give us the rundown and you know, let's end with the takeaways here. >> The simple rundown, a broad range of new powered servers, broad range addressing core, edge, RAN, optimized for those with all the different kind of acceleration capabilities. You can see that, you can see infrastructure blocks. These are with Wind River, with Red Hat. You can see OTEL, the open telecom ecosystem lab where all that playground, the integration, the real work, the real sausage makings happening. And then you will see some interesting solutions in terms of co-creation that we are doing, right? So you, you will see all of that and not to forget the connected laptops. >> Dave V.: Yeah, yeah, cool. >> Doug: Yeah and, we mentioned it before, but just to add on, I think, you know, for private 5G, you know, we've announced a few offers here at the show with partners. So with Expeto and AirSpan in particular, and I think, you know, I just want to emphasize the partnerships that we're doing. You know, we're doing some, you know, fundamental integration on infrastructure, bare metal and different options for the operators to get engineered systems. But building on that ecosystem is really, the move to cloud native is where Dell is trying to get in front of. And we're offering solutions and a much larger ecosystem to go after it. >> Dave V.: Great. Manish and Doug, thanks for coming on the program. It was great to have you, awesome discussion. >> Thank you for having us. >> Thanks for having us. >> All right, Dave Vellante for Dave Nicholson and Lisa Martin. We're seeing the disaggregation of the Teleco network into open ecosystems with integration from companies like Dell and others. Keep it right there for theCUBE's coverage of MWC 23. We'll be right back. (upbeat tech music)

(upbeat music) >> Hello, this is Dave Valente with theCUBE, and one of the most gratifying aspects of my role as a host of "theCUBE TV" is I get to cover a wide range of topics. And quite often, we're able to bring to our program a level of expertise that allows us to more deeply explore and unpack some of the topics that we cover throughout the year. And one of our favorite topics, of course, is data. Now, in 2021, after being in isolation for the better part of two years, a group of industry analysts met up at AWS re:Invent and started a collaboration to look at the trends in data and predict what some likely outcomes will be for the coming year. And it resulted in a very popular session that we had last year focused on the future of data management. And I'm very excited and pleased to tell you that the 2023 edition of that predictions episode is back, and with me are five outstanding market analyst, Sanjeev Mohan of SanjMo, Tony Baer of dbInsight, Carl Olofson from IDC, Dave Menninger from Ventana Research, and Doug Henschen, VP and Principal Analyst at Constellation Research. Now, what is it that we're calling you, guys? A data pack like the rat pack? No, no, no, no, that's not it. It's the data crowd, the data crowd, and the crowd includes some of the best minds in the data analyst community. They'll discuss how data management is evolving and what listeners should prepare for in 2023. Guys, welcome back. Great to see you. >> Good to be here. >> Thank you. >> Thanks, Dave. (Tony and Dave faintly speaks) >> All right, before we get into 2023 predictions, we thought it'd be good to do a look back at how we did in 2022 and give a transparent assessment of those predictions. So, let's get right into it. We're going to bring these up here, the predictions from 2022, they're color-coded red, yellow, and green to signify the degree of accuracy. And I'm pleased to report there's no red. Well, maybe some of you will want to debate that grading system. But as always, we want to be open, so you can decide for yourselves. So, we're going to ask each analyst to review their 2022 prediction and explain their rating and what evidence they have that led them to their conclusion. So, Sanjeev, please kick it off. Your prediction was data governance becomes key. I know that's going to knock you guys over, but elaborate, because you had more detail when you double click on that. >> Yeah, absolutely. Thank you so much, Dave, for having us on the show today. And we self-graded ourselves. I could have very easily made my prediction from last year green, but I mentioned why I left it as yellow. I totally fully believe that data governance was in a renaissance in 2022. And why do I say that? You have to look no further than AWS launching its own data catalog called DataZone. Before that, mid-year, we saw Unity Catalog from Databricks went GA. So, overall, I saw there was tremendous movement. When you see these big players launching a new data catalog, you know that they want to be in this space. And this space is highly critical to everything that I feel we will talk about in today's call. Also, if you look at established players, I spoke at Collibra's conference, data.world, work closely with Alation, Informatica, a bunch of other companies, they all added tremendous new capabilities. So, it did become key. The reason I left it as yellow is because I had made a prediction that Collibra would go IPO, and it did not. And I don't think anyone is going IPO right now. The market is really, really down, the funding in VC IPO market. But other than that, data governance had a banner year in 2022. >> Yeah. Well, thank you for that. And of course, you saw data clean rooms being announced at AWS re:Invent, so more evidence. And I like how the fact that you included in your predictions some things that were binary, so you dinged yourself there. So, good job. Okay, Tony Baer, you're up next. Data mesh hits reality check. As you see here, you've given yourself a bright green thumbs up. (Tony laughing) Okay. Let's hear why you feel that was the case. What do you mean by reality check? >> Okay. Thanks, Dave, for having us back again. This is something I just wrote and just tried to get away from, and this just a topic just won't go away. I did speak with a number of folks, early adopters and non-adopters during the year. And I did find that basically that it pretty much validated what I was expecting, which was that there was a lot more, this has now become a front burner issue. And if I had any doubt in my mind, the evidence I would point to is what was originally intended to be a throwaway post on LinkedIn, which I just quickly scribbled down the night before leaving for re:Invent. I was packing at the time, and for some reason, I was doing Google search on data mesh. And I happened to have tripped across this ridiculous article, I will not say where, because it doesn't deserve any publicity, about the eight (Dave laughing) best data mesh software companies of 2022. (Tony laughing) One of my predictions was that you'd see data mesh washing. And I just quickly just hopped on that maybe three sentences and wrote it at about a couple minutes saying this is hogwash, essentially. (laughs) And that just reun... And then, I left for re:Invent. And the next night, when I got into my Vegas hotel room, I clicked on my computer. I saw a 15,000 hits on that post, which was the most hits of any single post I put all year. And the responses were wildly pro and con. So, it pretty much validates my expectation in that data mesh really did hit a lot more scrutiny over this past year. >> Yeah, thank you for that. I remember that article. I remember rolling my eyes when I saw it, and then I recently, (Tony laughing) I talked to Walmart and they actually invoked Martin Fowler and they said that they're working through their data mesh. So, it takes a really lot of thought, and it really, as we've talked about, is really as much an organizational construct. You're not buying data mesh >> Bingo. >> to your point. Okay. Thank you, Tony. Carl Olofson, here we go. You've graded yourself a yellow in the prediction of graph databases. Take off. Please elaborate. >> Yeah, sure. So, I realized in looking at the prediction that it seemed to imply that graph databases could be a major factor in the data world in 2022, which obviously didn't become the case. It was an error on my part in that I should have said it in the right context. It's really a three to five-year time period that graph databases will really become significant, because they still need accepted methodologies that can be applied in a business context as well as proper tools in order for people to be able to use them seriously. But I stand by the idea that it is taking off, because for one thing, Neo4j, which is the leading independent graph database provider, had a very good year. And also, we're seeing interesting developments in terms of things like AWS with Neptune and with Oracle providing graph support in Oracle database this past year. Those things are, as I said, growing gradually. There are other companies like TigerGraph and so forth, that deserve watching as well. But as far as becoming mainstream, it's going to be a few years before we get all the elements together to make that happen. Like any new technology, you have to create an environment in which ordinary people without a whole ton of technical training can actually apply the technology to solve business problems. >> Yeah, thank you for that. These specialized databases, graph databases, time series databases, you see them embedded into mainstream data platforms, but there's a place for these specialized databases, I would suspect we're going to see new types of databases emerge with all this cloud sprawl that we have and maybe to the edge. >> Well, part of it is that it's not as specialized as you might think it. You can apply graphs to great many workloads and use cases. It's just that people have yet to fully explore and discover what those are. >> Yeah. >> And so, it's going to be a process. (laughs) >> All right, Dave Menninger, streaming data permeates the landscape. You gave yourself a yellow. Why? >> Well, I couldn't think of a appropriate combination of yellow and green. Maybe I should have used chartreuse, (Dave laughing) but I was probably a little hard on myself making it yellow. This is another type of specialized data processing like Carl was talking about graph databases is a stream processing, and nearly every data platform offers streaming capabilities now. Often, it's based on Kafka. If you look at Confluent, their revenues have grown at more than 50%, continue to grow at more than 50% a year. They're expected to do more than half a billion dollars in revenue this year. But the thing that hasn't happened yet, and to be honest, they didn't necessarily expect it to happen in one year, is that streaming hasn't become the default way in which we deal with data. It's still a sidecar to data at rest. And I do expect that we'll continue to see streaming become more and more mainstream. I do expect perhaps in the five-year timeframe that we will first deal with data as streaming and then at rest, but the worlds are starting to merge. And we even see some vendors bringing products to market, such as K2View, Hazelcast, and RisingWave Labs. So, in addition to all those core data platform vendors adding these capabilities, there are new vendors approaching this market as well. >> I like the tough grading system, and it's not trivial. And when you talk to practitioners doing this stuff, there's still some complications in the data pipeline. And so, but I think, you're right, it probably was a yellow plus. Doug Henschen, data lakehouses will emerge as dominant. When you talk to people about lakehouses, practitioners, they all use that term. They certainly use the term data lake, but now, they're using lakehouse more and more. What's your thoughts on here? Why the green? What's your evidence there? >> Well, I think, I was accurate. I spoke about it specifically as something that vendors would be pursuing. And we saw yet more lakehouse advocacy in 2022. Google introduced its BigLake service alongside BigQuery. Salesforce introduced Genie, which is really a lakehouse architecture. And it was a safe prediction to say vendors are going to be pursuing this in that AWS, Cloudera, Databricks, Microsoft, Oracle, SAP, Salesforce now, IBM, all advocate this idea of a single platform for all of your data. Now, the trend was also supported in 2023, in that we saw a big embrace of Apache Iceberg in 2022. That's a structured table format. It's used with these lakehouse platforms. It's open, so it ensures portability and it also ensures performance. And that's a structured table that helps with the warehouse side performance. But among those announcements, Snowflake, Google, Cloud Era, SAP, Salesforce, IBM, all embraced Iceberg. But keep in mind, again, I'm talking about this as something that vendors are pursuing as their approach. So, they're advocating end users. It's very cutting edge. I'd say the top, leading edge, 5% of of companies have really embraced the lakehouse. I think, we're now seeing the fast followers, the next 20 to 25% of firms embracing this idea and embracing a lakehouse architecture. I recall Christian Kleinerman at the big Snowflake event last summer, making the announcement about Iceberg, and he asked for a show of hands for any of you in the audience at the keynote, have you heard of Iceberg? And just a smattering of hands went up. So, the vendors are ahead of the curve. They're pushing this trend, and we're now seeing a little bit more mainstream uptake. >> Good. Doug, I was there. It was you, me, and I think, two other hands were up. That was just humorous. (Doug laughing) All right, well, so I liked the fact that we had some yellow and some green. When you think about these things, there's the prediction itself. Did it come true or not? There are the sub predictions that you guys make, and of course, the degree of difficulty. So, thank you for that open assessment. All right, let's get into the 2023 predictions. Let's bring up the predictions. Sanjeev, you're going first. You've got a prediction around unified metadata. What's the prediction, please? >> So, my prediction is that metadata space is currently a mess. It needs to get unified. There are too many use cases of metadata, which are being addressed by disparate systems. For example, data quality has become really big in the last couple of years, data observability, the whole catalog space is actually, people don't like to use the word data catalog anymore, because data catalog sounds like it's a catalog, a museum, if you may, of metadata that you go and admire. So, what I'm saying is that in 2023, we will see that metadata will become the driving force behind things like data ops, things like orchestration of tasks using metadata, not rules. Not saying that if this fails, then do this, if this succeeds, go do that. But it's like getting to the metadata level, and then making a decision as to what to orchestrate, what to automate, how to do data quality check, data observability. So, this space is starting to gel, and I see there'll be more maturation in the metadata space. Even security privacy, some of these topics, which are handled separately. And I'm just talking about data security and data privacy. I'm not talking about infrastructure security. These also need to merge into a unified metadata management piece with some knowledge graph, semantic layer on top, so you can do analytics on it. So, it's no longer something that sits on the side, it's limited in its scope. It is actually the very engine, the very glue that is going to connect data producers and consumers. >> Great. Thank you for that. Doug. Doug Henschen, any thoughts on what Sanjeev just said? Do you agree? Do you disagree? >> Well, I agree with many aspects of what he says. I think, there's a huge opportunity for consolidation and streamlining of these as aspects of governance. Last year, Sanjeev, you said something like, we'll see more people using catalogs than BI. And I have to disagree. I don't think this is a category that's headed for mainstream adoption. It's a behind the scenes activity for the wonky few, or better yet, companies want machine learning and automation to take care of these messy details. We've seen these waves of management technologies, some of the latest data observability, customer data platform, but they failed to sweep away all the earlier investments in data quality and master data management. So, yes, I hope the latest tech offers, glimmers that there's going to be a better, cleaner way of addressing these things. But to my mind, the business leaders, including the CIO, only want to spend as much time and effort and money and resources on these sorts of things to avoid getting breached, ending up in headlines, getting fired or going to jail. So, vendors bring on the ML and AI smarts and the automation of these sorts of activities. >> So, if I may say something, the reason why we have this dichotomy between data catalog and the BI vendors is because data catalogs are very soon, not going to be standalone products, in my opinion. They're going to get embedded. So, when you use a BI tool, you'll actually use the catalog to find out what is it that you want to do, whether you are looking for data or you're looking for an existing dashboard. So, the catalog becomes embedded into the BI tool. >> Hey, Dave Menninger, sometimes you have some data in your back pocket. Do you have any stats (chuckles) on this topic? >> No, I'm glad you asked, because I'm going to... Now, data catalogs are something that's interesting. Sanjeev made a statement that data catalogs are falling out of favor. I don't care what you call them. They're valuable to organizations. Our research shows that organizations that have adequate data catalog technologies are three times more likely to express satisfaction with their analytics for just the reasons that Sanjeev was talking about. You can find what you want, you know you're getting the right information, you know whether or not it's trusted. So, those are good things. So, we expect to see the capabilities, whether it's embedded or separate. We expect to see those capabilities continue to permeate the market. >> And a lot of those catalogs are driven now by machine learning and things. So, they're learning from those patterns of usage by people when people use the data. (airy laughs) >> All right. Okay. Thank you, guys. All right. Let's move on to the next one. Tony Bear, let's bring up the predictions. You got something in here about the modern data stack. We need to rethink it. Is the modern data stack getting long at the tooth? Is it not so modern anymore? >> I think, in a way, it's got almost too modern. It's gotten too, I don't know if it's being long in the tooth, but it is getting long. The modern data stack, it's traditionally been defined as basically you have the data platform, which would be the operational database and the data warehouse. And in between, you have all the tools that are necessary to essentially get that data from the operational realm or the streaming realm for that matter into basically the data warehouse, or as we might be seeing more and more, the data lakehouse. And I think, what's important here is that, or I think, we have seen a lot of progress, and this would be in the cloud, is with the SaaS services. And especially you see that in the modern data stack, which is like all these players, not just the MongoDBs or the Oracles or the Amazons have their database platforms. You see they have the Informatica's, and all the other players there in Fivetrans have their own SaaS services. And within those SaaS services, you get a certain degree of simplicity, which is it takes all the housekeeping off the shoulders of the customers. That's a good thing. The problem is that what we're getting to unfortunately is what I would call lots of islands of simplicity, which means that it leads it (Dave laughing) to the customer to have to integrate or put all that stuff together. It's a complex tool chain. And so, what we really need to think about here, we have too many pieces. And going back to the discussion of catalogs, it's like we have so many catalogs out there, which one do we use? 'Cause chances are of most organizations do not rely on a single catalog at this point. What I'm calling on all the data providers or all the SaaS service providers, is to literally get it together and essentially make this modern data stack less of a stack, make it more of a blending of an end-to-end solution. And that can come in a number of different ways. Part of it is that we're data platform providers have been adding services that are adjacent. And there's some very good examples of this. We've seen progress over the past year or so. For instance, MongoDB integrating search. It's a very common, I guess, sort of tool that basically, that the applications that are developed on MongoDB use, so MongoDB then built it into the database rather than requiring an extra elastic search or open search stack. Amazon just... AWS just did the zero-ETL, which is a first step towards simplifying the process from going from Aurora to Redshift. You've seen same thing with Google, BigQuery integrating basically streaming pipelines. And you're seeing also a lot of movement in database machine learning. So, there's some good moves in this direction. I expect to see more than this year. Part of it's from basically the SaaS platform is adding some functionality. But I also see more importantly, because you're never going to get... This is like asking your data team and your developers, herding cats to standardizing the same tool. In most organizations, that is not going to happen. So, take a look at the most popular combinations of tools and start to come up with some pre-built integrations and pre-built orchestrations, and offer some promotional pricing, maybe not quite two for, but in other words, get two products for the price of two services or for the price of one and a half. I see a lot of potential for this. And it's to me, if the class was to simplify things, this is the next logical step and I expect to see more of this here. >> Yeah, and you see in Oracle, MySQL heat wave, yet another example of eliminating that ETL. Carl Olofson, today, if you think about the data stack and the application stack, they're largely separate. Do you have any thoughts on how that's going to play out? Does that play into this prediction? What do you think? >> Well, I think, that the... I really like Tony's phrase, islands of simplification. It really says (Tony chuckles) what's going on here, which is that all these different vendors you ask about, about how these stacks work. All these different vendors have their own stack vision. And you can... One application group is going to use one, and another application group is going to use another. And some people will say, let's go to, like you go to a Informatica conference and they say, we should be the center of your universe, but you can't connect everything in your universe to Informatica, so you need to use other things. So, the challenge is how do we make those things work together? As Tony has said, and I totally agree, we're never going to get to the point where people standardize on one organizing system. So, the alternative is to have metadata that can be shared amongst those systems and protocols that allow those systems to coordinate their operations. This is standard stuff. It's not easy. But the motive for the vendors is that they can become more active critical players in the enterprise. And of course, the motive for the customer is that things will run better and more completely. So, I've been looking at this in terms of two kinds of metadata. One is the meaning metadata, which says what data can be put together. The other is the operational metadata, which says basically where did it come from? Who created it? What's its current state? What's the security level? Et cetera, et cetera, et cetera. The good news is the operational stuff can actually be done automatically, whereas the meaning stuff requires some human intervention. And as we've already heard from, was it Doug, I think, people are disinclined to put a lot of definition into meaning metadata. So, that may be the harder one, but coordination is key. This problem has been with us forever, but with the addition of new data sources, with streaming data with data in different formats, the whole thing has, it's been like what a customer of mine used to say, "I understand your product can make my system run faster, but right now I just feel I'm putting my problems on roller skates. (chuckles) I don't need that to accelerate what's already not working." >> Excellent. Okay, Carl, let's stay with you. I remember in the early days of the big data movement, Hadoop movement, NoSQL was the big thing. And I remember Amr Awadallah said to us in theCUBE that SQL is the killer app for big data. So, your prediction here, if we bring that up is SQL is back. Please elaborate. >> Yeah. So, of course, some people would say, well, it never left. Actually, that's probably closer to true, but in the perception of the marketplace, there's been all this noise about alternative ways of storing, retrieving data, whether it's in key value stores or document databases and so forth. We're getting a lot of messaging that for a while had persuaded people that, oh, we're not going to do analytics in SQL anymore. We're going to use Spark for everything, except that only a handful of people know how to use Spark. Oh, well, that's a problem. Well, how about, and for ordinary conventional business analytics, Spark is like an over-engineered solution to the problem. SQL works just great. What's happened in the past couple years, and what's going to continue to happen is that SQL is insinuating itself into everything we're seeing. We're seeing all the major data lake providers offering SQL support, whether it's Databricks or... And of course, Snowflake is loving this, because that is what they do, and their success is certainly points to the success of SQL, even MongoDB. And we were all, I think, at the MongoDB conference where on one day, we hear SQL is dead. They're not teaching SQL in schools anymore, and this kind of thing. And then, a couple days later at the same conference, they announced we're adding a new analytic capability-based on SQL. But didn't you just say SQL is dead? So, the reality is that SQL is better understood than most other methods of certainly of retrieving and finding data in a data collection, no matter whether it happens to be relational or non-relational. And even in systems that are very non-relational, such as graph and document databases, their query languages are being built or extended to resemble SQL, because SQL is something people understand. >> Now, you remember when we were in high school and you had had to take the... Your debating in the class and you were forced to take one side and defend it. So, I was was at a Vertica conference one time up on stage with Curt Monash, and I had to take the NoSQL, the world is changing paradigm shift. And so just to be controversial, I said to him, Curt Monash, I said, who really needs acid compliance anyway? Tony Baer. And so, (chuckles) of course, his head exploded, but what are your thoughts (guests laughing) on all this? >> Well, my first thought is congratulations, Dave, for surviving being up on stage with Curt Monash. >> Amen. (group laughing) >> I definitely would concur with Carl. We actually are definitely seeing a SQL renaissance and if there's any proof of the pudding here, I see lakehouse is being icing on the cake. As Doug had predicted last year, now, (clears throat) for the record, I think, Doug was about a year ahead of time in his predictions that this year is really the year that I see (clears throat) the lakehouse ecosystems really firming up. You saw the first shots last year. But anyway, on this, data lakes will not go away. I've actually, I'm on the home stretch of doing a market, a landscape on the lakehouse. And lakehouse will not replace data lakes in terms of that. There is the need for those, data scientists who do know Python, who knows Spark, to go in there and basically do their thing without all the restrictions or the constraints of a pre-built, pre-designed table structure. I get that. Same thing for developing models. But on the other hand, there is huge need. Basically, (clears throat) maybe MongoDB was saying that we're not teaching SQL anymore. Well, maybe we have an oversupply of SQL developers. Well, I'm being facetious there, but there is a huge skills based in SQL. Analytics have been built on SQL. They came with lakehouse and why this really helps to fuel a SQL revival is that the core need in the data lake, what brought on the lakehouse was not so much SQL, it was a need for acid. And what was the best way to do it? It was through a relational table structure. So, the whole idea of acid in the lakehouse was not to turn it into a transaction database, but to make the data trusted, secure, and more granularly governed, where you could govern down to column and row level, which you really could not do in a data lake or a file system. So, while lakehouse can be queried in a manner, you can go in there with Python or whatever, it's built on a relational table structure. And so, for that end, for those types of data lakes, it becomes the end state. You cannot bypass that table structure as I learned the hard way during my research. So, the bottom line I'd say here is that lakehouse is proof that we're starting to see the revenge of the SQL nerds. (Dave chuckles) >> Excellent. Okay, let's bring up back up the predictions. Dave Menninger, this one's really thought-provoking and interesting. We're hearing things like data as code, new data applications, machines actually generating plans with no human involvement. And your prediction is the definition of data is expanding. What do you mean by that? >> So, I think, for too long, we've thought about data as the, I would say facts that we collect the readings off of devices and things like that, but data on its own is really insufficient. Organizations need to manipulate that data and examine derivatives of the data to really understand what's happening in their organization, why has it happened, and to project what might happen in the future. And my comment is that these data derivatives need to be supported and managed just like the data needs to be managed. We can't treat this as entirely separate. Think about all the governance discussions we've had. Think about the metadata discussions we've had. If you separate these things, now you've got more moving parts. We're talking about simplicity and simplifying the stack. So, if these things are treated separately, it creates much more complexity. I also think it creates a little bit of a myopic view on the part of the IT organizations that are acquiring these technologies. They need to think more broadly. So, for instance, metrics. Metric stores are becoming much more common part of the tooling that's part of a data platform. Similarly, feature stores are gaining traction. So, those are designed to promote the reuse and consistency across the AI and ML initiatives. The elements that are used in developing an AI or ML model. And let me go back to metrics and just clarify what I mean by that. So, any type of formula involving the data points. I'm distinguishing metrics from features that are used in AI and ML models. And the data platforms themselves are increasingly managing the models as an element of data. So, just like figuring out how to calculate a metric. Well, if you're going to have the features associated with an AI and ML model, you probably need to be managing the model that's associated with those features. The other element where I see expansion is around external data. Organizations for decades have been focused on the data that they generate within their own organization. We see more and more of these platforms acquiring and publishing data to external third-party sources, whether they're within some sort of a partner ecosystem or whether it's a commercial distribution of that information. And our research shows that when organizations use external data, they derive even more benefits from the various analyses that they're conducting. And the last great frontier in my opinion on this expanding world of data is the world of driver-based planning. Very few of the major data platform providers provide these capabilities today. These are the types of things you would do in a spreadsheet. And we all know the issues associated with spreadsheets. They're hard to govern, they're error-prone. And so, if we can take that type of analysis, collecting the occupancy of a rental property, the projected rise in rental rates, the fluctuations perhaps in occupancy, the interest rates associated with financing that property, we can project forward. And that's a very common thing to do. What the income might look like from that property income, the expenses, we can plan and purchase things appropriately. So, I think, we need this broader purview and I'm beginning to see some of those things happen. And the evidence today I would say, is more focused around the metric stores and the feature stores starting to see vendors offer those capabilities. And we're starting to see the ML ops elements of managing the AI and ML models find their way closer to the data platforms as well. >> Very interesting. When I hear metrics, I think of KPIs, I think of data apps, orchestrate people and places and things to optimize around a set of KPIs. It sounds like a metadata challenge more... Somebody once predicted they'll have more metadata than data. Carl, what are your thoughts on this prediction? >> Yeah, I think that what Dave is describing as data derivatives is in a way, another word for what I was calling operational metadata, which not about the data itself, but how it's used, where it came from, what the rules are governing it, and that kind of thing. If you have a rich enough set of those things, then not only can you do a model of how well your vacation property rental may do in terms of income, but also how well your application that's measuring that is doing for you. In other words, how many times have I used it, how much data have I used and what is the relationship between the data that I've used and the benefits that I've derived from using it? Well, we don't have ways of doing that. What's interesting to me is that folks in the content world are way ahead of us here, because they have always tracked their content using these kinds of attributes. Where did it come from? When was it created, when was it modified? Who modified it? And so on and so forth. We need to do more of that with the structure data that we have, so that we can track what it's used. And also, it tells us how well we're doing with it. Is it really benefiting us? Are we being efficient? Are there improvements in processes that we need to consider? Because maybe data gets created and then it isn't used or it gets used, but it gets altered in some way that actually misleads people. (laughs) So, we need the mechanisms to be able to do that. So, I would say that that's... And I'd say that it's true that we need that stuff. I think, that starting to expand is probably the right way to put it. It's going to be expanding for some time. I think, we're still a distance from having all that stuff really working together. >> Maybe we should say it's gestating. (Dave and Carl laughing) >> Sorry, if I may- >> Sanjeev, yeah, I was going to say this... Sanjeev, please comment. This sounds to me like it supports Zhamak Dehghani's principles, but please. >> Absolutely. So, whether we call it data mesh or not, I'm not getting into that conversation, (Dave chuckles) but data (audio breaking) (Tony laughing) everything that I'm hearing what Dave is saying, Carl, this is the year when data products will start to take off. I'm not saying they'll become mainstream. They may take a couple of years to become so, but this is data products, all this thing about vacation rentals and how is it doing, that data is coming from different sources. I'm packaging it into our data product. And to Carl's point, there's a whole operational metadata associated with it. The idea is for organizations to see things like developer productivity, how many releases am I doing of this? What data products are most popular? I'm actually in right now in the process of formulating this concept that just like we had data catalogs, we are very soon going to be requiring data products catalog. So, I can discover these data products. I'm not just creating data products left, right, and center. I need to know, do they already exist? What is the usage? If no one is using a data product, maybe I want to retire and save cost. But this is a data product. Now, there's a associated thing that is also getting debated quite a bit called data contracts. And a data contract to me is literally just formalization of all these aspects of a product. How do you use it? What is the SLA on it, what is the quality that I am prescribing? So, data product, in my opinion, shifts the conversation to the consumers or to the business people. Up to this point when, Dave, you're talking about data and all of data discovery curation is a very data producer-centric. So, I think, we'll see a shift more into the consumer space. >> Yeah. Dave, can I just jump in there just very quickly there, which is that what Sanjeev has been saying there, this is really central to what Zhamak has been talking about. It's basically about making, one, data products are about the lifecycle management of data. Metadata is just elemental to that. And essentially, one of the things that she calls for is making data products discoverable. That's exactly what Sanjeev was talking about. >> By the way, did everyone just no notice how Sanjeev just snuck in another prediction there? So, we've got- >> Yeah. (group laughing) >> But you- >> Can we also say that he snuck in, I think, the term that we'll remember today, which is metadata museums. >> Yeah, but- >> Yeah. >> And also comment to, Tony, to your last year's prediction, you're really talking about it's not something that you're going to buy from a vendor. >> No. >> It's very specific >> Mm-hmm. >> to an organization, their own data product. So, touche on that one. Okay, last prediction. Let's bring them up. Doug Henschen, BI analytics is headed to embedding. What does that mean? >> Well, we all know that conventional BI dashboarding reporting is really commoditized from a vendor perspective. It never enjoyed truly mainstream adoption. Always that 25% of employees are really using these things. I'm seeing rising interest in embedding concise analytics at the point of decision or better still, using analytics as triggers for automation and workflows, and not even necessitating human interaction with visualizations, for example, if we have confidence in the analytics. So, leading companies are pushing for next generation applications, part of this low-code, no-code movement we've seen. And they want to build that decision support right into the app. So, the analytic is right there. Leading enterprise apps vendors, Salesforce, SAP, Microsoft, Oracle, they're all building smart apps with the analytics predictions, even recommendations built into these applications. And I think, the progressive BI analytics vendors are supporting this idea of driving insight to action, not necessarily necessitating humans interacting with it if there's confidence. So, we want prediction, we want embedding, we want automation. This low-code, no-code development movement is very important to bringing the analytics to where people are doing their work. We got to move beyond the, what I call swivel chair integration, between where people do their work and going off to separate reports and dashboards, and having to interpret and analyze before you can go back and do take action. >> And Dave Menninger, today, if you want, analytics or you want to absorb what's happening in the business, you typically got to go ask an expert, and then wait. So, what are your thoughts on Doug's prediction? >> I'm in total agreement with Doug. I'm going to say that collectively... So, how did we get here? I'm going to say collectively as an industry, we made a mistake. We made BI and analytics separate from the operational systems. Now, okay, it wasn't really a mistake. We were limited by the technology available at the time. Decades ago, we had to separate these two systems, so that the analytics didn't impact the operations. You don't want the operations preventing you from being able to do a transaction. But we've gone beyond that now. We can bring these two systems and worlds together and organizations recognize that need to change. As Doug said, the majority of the workforce and the majority of organizations doesn't have access to analytics. That's wrong. (chuckles) We've got to change that. And one of the ways that's going to change is with embedded analytics. 2/3 of organizations recognize that embedded analytics are important and it even ranks higher in importance than AI and ML in those organizations. So, it's interesting. This is a really important topic to the organizations that are consuming these technologies. The good news is it works. Organizations that have embraced embedded analytics are more comfortable with self-service than those that have not, as opposed to turning somebody loose, in the wild with the data. They're given a guided path to the data. And the research shows that 65% of organizations that have adopted embedded analytics are comfortable with self-service compared with just 40% of organizations that are turning people loose in an ad hoc way with the data. So, totally behind Doug's predictions. >> Can I just break in with something here, a comment on what Dave said about what Doug said, which (laughs) is that I totally agree with what you said about embedded analytics. And at IDC, we made a prediction in our future intelligence, future of intelligence service three years ago that this was going to happen. And the thing that we're waiting for is for developers to build... You have to write the applications to work that way. It just doesn't happen automagically. Developers have to write applications that reference analytic data and apply it while they're running. And that could involve simple things like complex queries against the live data, which is through something that I've been calling analytic transaction processing. Or it could be through something more sophisticated that involves AI operations as Doug has been suggesting, where the result is enacted pretty much automatically unless the scores are too low and you need to have a human being look at it. So, I think that that is definitely something we've been watching for. I'm not sure how soon it will come, because it seems to take a long time for people to change their thinking. But I think, as Dave was saying, once they do and they apply these principles in their application development, the rewards are great. >> Yeah, this is very much, I would say, very consistent with what we were talking about, I was talking about before, about basically rethinking the modern data stack and going into more of an end-to-end solution solution. I think, that what we're talking about clearly here is operational analytics. There'll still be a need for your data scientists to go offline just in their data lakes to do all that very exploratory and that deep modeling. But clearly, it just makes sense to bring operational analytics into where people work into their workspace and further flatten that modern data stack. >> But with all this metadata and all this intelligence, we're talking about injecting AI into applications, it does seem like we're entering a new era of not only data, but new era of apps. Today, most applications are about filling forms out or codifying processes and require a human input. And it seems like there's enough data now and enough intelligence in the system that the system can actually pull data from, whether it's the transaction system, e-commerce, the supply chain, ERP, and actually do something with that data without human involvement, present it to humans. Do you guys see this as a new frontier? >> I think, that's certainly- >> Very much so, but it's going to take a while, as Carl said. You have to design it, you have to get the prediction into the system, you have to get the analytics at the point of decision has to be relevant to that decision point. >> And I also recall basically a lot of the ERP vendors back like 10 years ago, we're promising that. And the fact that we're still looking at the promises shows just how difficult, how much of a challenge it is to get to what Doug's saying. >> One element that could be applied in this case is (indistinct) architecture. If applications are developed that are event-driven rather than following the script or sequence that some programmer or designer had preconceived, then you'll have much more flexible applications. You can inject decisions at various points using this technology much more easily. It's a completely different way of writing applications. And it actually involves a lot more data, which is why we should all like it. (laughs) But in the end (Tony laughing) it's more stable, it's easier to manage, easier to maintain, and it's actually more efficient, which is the result of an MIT study from about 10 years ago, and still, we are not seeing this come to fruition in most business applications. >> And do you think it's going to require a new type of data platform database? Today, data's all far-flung. We see that's all over the clouds and at the edge. Today, you cache- >> We need a super cloud. >> You cache that data, you're throwing into memory. I mentioned, MySQL heat wave. There are other examples where it's a brute force approach, but maybe we need new ways of laying data out on disk and new database architectures, and just when we thought we had it all figured out. >> Well, without referring to disk, which to my mind, is almost like talking about cave painting. I think, that (Dave laughing) all the things that have been mentioned by all of us today are elements of what I'm talking about. In other words, the whole improvement of the data mesh, the improvement of metadata across the board and improvement of the ability to track data and judge its freshness the way we judge the freshness of a melon or something like that, to determine whether we can still use it. Is it still good? That kind of thing. Bringing together data from multiple sources dynamically and real-time requires all the things we've been talking about. All the predictions that we've talked about today add up to elements that can make this happen. >> Well, guys, it's always tremendous to get these wonderful minds together and get your insights, and I love how it shapes the outcome here of the predictions, and let's see how we did. We're going to leave it there. I want to thank Sanjeev, Tony, Carl, David, and Doug. Really appreciate the collaboration and thought that you guys put into these sessions. Really, thank you. >> Thank you. >> Thanks, Dave. >> Thank you for having us. >> Thanks. >> Thank you. >> All right, this is Dave Valente for theCUBE, signing off for now. Follow these guys on social media. Look for coverage on siliconangle.com, theCUBE.net. Thank you for watching. (upbeat music)

>> Presenter: theCUBE presents Ignite '22, brought to you by Palo Alto Networks. >> Hey guys and girls. Welcome back to theCube's live coverage at Palo Alto Ignite '22. We're live at the MGM Grand Hotel in beautiful Las Vegas. Lisa Martin here with Dave Vellante. This is day one of our coverage. We've been talking with execs from Palo Alto, Partners, but one of our most exciting things is talking with Founders day. We get to do that next. >> The thing is, it's like I wrote this weekend in my breaking analysis. Understanding the problem in cybersecurity is really easy, but figuring out how to fix it ain't so much. >> It definitely isn't. >> So I'm excited to have Nir here. >> Very excited. Nir Zuk joins us, the founder and CTO of Palo Alto Networks. Welcome, Nir. Great to have you on the program. >> Thank you. >> So Palo Alto Networks, you founded it back in 2005. It's hard to believe that's been 18 years, almost. You did something different, which I want to get into. But tell us, what was it back then? Why did you found this company? >> I thought the world needed another cybersecurity company. I thought it's because there were so many cybersecurity vendors in the world, and just didn't make any sense. This industry has evolved in a very weird way, where every time there was a new challenge, rather than existing vendors dealing with a challenge, you had new vendors dealing with it, and I thought I could put a stop to it, and I think I did. >> You did something differently back in 2005, looking at where you are now, the leader, what was different in your mind back then? >> Yeah. When you found a new company, you have really two good options. There's also a bad option, but we'll skip that. You can either disrupt an existing market, or you can create a new market. So first, I decided to disrupt an existing market, go into an existing market first, network security, then cyber security, and change it. Change the way it works. And like I said, the challenges that every problem had a new vendor, and nobody just stepped back and said, "I think I can solve it with the platform." Meaning, I think I can spend some time not solving a specific problem, but building a platform that then can be used to solve many different problems. And that's what I've done, and that's what Palo Alto Networks has done, and that's where we are today. >> So you look back, you call it now, I think you call it a next gen firewall, but nothing in 2005, can it be next gen? Do you know the Silicon Valley Show? Do you know the show Silicon Valley? >> Oh! Yeah. >> Yeah, of course. >> You got to have a box. But it was a different kind of box- >> Actually. >> Explain that. >> Actually, it's exactly the same thing. You got to have a box. So I actually wanted to call it a necessary evil. Marketing wouldn't go for that. >> No. >> And the reason I wanted to call it a necessary evil, because one of the things that we've done in order to platform our cyber security, again, first network security now, also cloud security, and security operations, is to turn it into a SaaS delivered industry. Today every cyber security professional knows that, when they buy cyber security, they buy usually a SaaS delivered service. Back then, people thought I was crazy to think that customers are going to send their data to their vendor in order to process, and they wanted everything on premise and so on, but I said, "No, customers are going to send information to us for processing, because we have much more processing power than they have." And we needed something in the infrastructure to send us the information. So that's why I wanted to call it the necessary evil. We ended up calling it next generation firewall, which was probably a better term. >> Well, even Veritas. Remember Veritas? They had the no hardware agenda. Even they have a box. So it is like you say, you got to have it. >> It's necessary. >> Okay. You did this, you started this on your own cloud, kind of like Salesforce, ServiceNow. >> Correct. >> Similar now- >> Build your own data centers. >> Build your own data center. Okay, I call it a cloud, but no. >> No, it's the same. There's no cloud, it's just someone else's computer. >> According to Larry Ellison, he was actually probably right about that. But over time, you've had this closer partnership with the public clouds. >> Correct. >> What does that bring you and your customers, and how hard was that to navigate? >> It wasn't that hard for us, because we didn't have that many services. Usually it's harder. Of course, we didn't do a lift and shift, which is their own thing to do with the cloud. We rebuild things for the cloud, and the benefits, of course, are time to market, scale, agility, and in some cases also, cost. >> Yeah, some cases. >> In some cases. >> So you have a sort of a hybrid model today. You still run your own data centers, do you not? >> Very few. >> Really? >> There are very, very few things that we have to do on hardware, like simulating malware and things that cannot be done in a virtual machine, which is pretty much the only option you have in the cloud. They provide bare metal, but doesn't serve our needs. I think that we don't view cloud, and your viewers should not be viewing cloud, as a place where they're going to save money. It's a place where they're going to make money. >> I like that. >> You make much more money, because you're more agile. >> And that's why this conversation is all about, your cost of goods sold they're going to be so high, you're going to have to come back to your own data centers. That's not on your mind right now. What's on your mind is advancing the unit, right? >> Look, my own data center would limit me in scale, would limit my agility. If you want to build something new, you don't have all the PaaS services, the platform as a service, services like database, and AI, and so on. I have to build them myself. It takes time. So yeah, it's going to be cheaper, but I'm not going to be delivering the same thing. So my revenues will be much lower. >> Less top line. What can humans do better than machines? You were talking about your keynote... I'm just going to chat a little bit. You were talking about your keynote. Basically, if you guys didn't see the keynote, that AI is going to run every soc within five years, that was a great prediction that you made. >> Correct. >> And they're going to do things that you can't do today, and then in the future, they're going to do things that you can't... Better than you can do. >> And you just have to be comfortable with that. >> So what do you think humans can do today and in the future better than machines? >> Look, humans can always do better than machines. The human mind can do things that machines cannot do. We are conscious, I don't think machines will be conscious. And you can do things... My point was not that machines can do things that humans cannot do. They can just do it better. The things that humans do today, machines can do better, once machines do that, humans will be free to do things that they don't do today, that machines cannot do. >> Like what? >> Like finding the most difficult, most covert attacks, dealing with the most difficult incidents, things that machines just can't do. Just that today, humans are consumed by finding attacks that machines can find, by dealing with incidents that machines can deal with. It's a waste of time. We leave it to the machines and go and focus on the most difficult problems, and then have the machines learn from you, so that next time or a hundred or a thousand times from now, they can do it themselves, and you focus on the even more difficult. >> Yeah, just like after 9/11, they said that we lack the creativity. That's what humans have, that machines don't, at least today. >> Machines don't. Yeah, look, every airplane has two pilots, even though airplanes have been flying themselves for 30 years now, why do you have two pilots, to do the things that machines cannot do? Like land on the Hudson, right? You always need humans to do the things that machines cannot do. But to leave the things that machines can do to the machines, they'll do it better. >> And autonomous vehicles need breaks. (indistinct) >> In your customer conversations, are customers really grappling with that, are they going, "Yeah, you're right?" >> It depends. It's hard for customers to let go of old habits. First, the habit of buying a hundred different solutions from a hundred different vendors, and you know what? Why would I trust one vendor to do everything, put all my eggs in the same basket? They have all kind of slogans as to why not to do that, even though it's been proven again and again that, doing everything in one system with one brain, versus a hundred systems with a hundred brains, work much better. So that's one thing. The second thing is, we always have the same issue that we've had, I think, since the industrial revolution, of what machines are going to take away my job. No, they're just going to make your job better. So I think that some of our customers are also grappling with that, like, "What do I do if the machines take over?" And of course, like we've said, the machines aren't taking over. They're going to do the benign work, you're going to do the interesting work. You should embrace it. >> When I think about your history as a technology pro, from Check Point, a couple of startups, one of the things that always frustrated you, is when when a larger company bought you out, you ended up getting sucked into the bureaucratic vortex. How do you avoid that at Palo Alto Networks? >> So first, you mean when we acquire company? >> Yes. >> The first thing is that, when we acquire companies, we always acquire for integration. Meaning, we don't just buy something and then leave it on the side, and try to sell it here and there. We integrate it into the core of our products. So that's very important, so that the technology lives, thrives and continues to grow as part of our bigger platform. And I think that the second thing that is very important, from past experience what we've learned, is to put the people that we acquire in key positions. Meaning, you don't buy a company and then put the leader of that company five levels below the CEO. You always put them in very senior positions. Almost always, we have the leaders of the companies that we acquire, be two levels below the CEO, so very senior in the company, so they can influence and make changes. >> So two questions related to that. One is, as you grow your team, can you be both integrated? And second part of the question, can you be both integrated and best of breed? Second part of the question is, do you even have to be? >> So I'll answer it in the third way, which is, I don't think you can be best of breed without being integrated in cybersecurity. And the reason is, again, this split brain that I've mentioned twice. When you have different products do a part of cybersecurity and they don't talk to each other, and they don't share a single brain, you always compromise. You start looking for things the wrong way. I can be a little bit technical here, but please. Take the example of, traditionally you would buy an IDS/IPS, separately from your filtering, separately from DNS security. One of the most important things we do in network security is to find combining control connections. Combining control connections where the adversaries controlling something behind your firewall and is now going around your network, is usually the key heel of the attack. That's why attacks like ransomware, that don't have a commanding control connection, are so difficult to deal with, by the way. So commanding control connections are a key seal of the attacks, and there are three different technologies that deal with it. Neural filtering for neural based commanding control, DNS security for DNS based commanding control, and IDS/IPS for general commanding control. If those are three different products, they'll be doing the wrong things. The oral filter will try to find things that it's not really good at, that the IPS really need to find, and the DN... It doesn't work. It works much better when it's one product doing everything. So I think the choice is not between best of breed and integrated. I think the only choice is integrated, because that's the only way to be best of breed. >> And behind that technology is some kind of realtime data store, I'll call it data lake, database. >> Yeah. >> Whatever. >> It's all driven by the same data. All the URLs, all the domain graph. Everything goes to one big data lake. We collect about... I think we collect about, a few petabytes per day. I don't write the exact number of data. It's all going to the same data lake, and all the intelligence is driven by that. >> So you mentioned in a cheeky comment about, why you founded the company, there weren't enough cybersecurity companies. >> Yeah. >> Clearly the term expansion strategy that Palo Alto Networks has done has been very successful. You've been, as you talked about, very focused on integration, not just from the technology perspective, but from the people perspective as well. >> Correct. >> So why are there still so many cybersecurity companies, and what are you thinking Palo Alto Networks can do to change that? >> So first, I think that there are a lot of cybersecurity companies out there, because there's a lot of money going into cybersecurity. If you look at the number of companies that have been really successful, it's a very small percentage of those cybersecurity companies. And also look, we're not going to be responsible for all the innovation in cybersecurity. We need other people to innovate. It's also... Look, always the question is, "Do you buy something or do you build it yourself?" Now we think we're the smartest people in the world. Of course, we can build everything, but it's not always true that we can build everything. Know that we're the smartest people in the world, for sure. You see, when you are a startup, you live and die by the thing that you build. Meaning if it's good, it works. If it's not good, you die. You run out of money, you shut down, and you just lost four years of your life to this, at least. >> At least. >> When you're a large company, yeah, I can go and find a hundred engineers and hire them. And especially nowadays, it becomes easier, as it became easier, and give them money, and have them go and build the same thing that the startup is building, but they're part of a bigger company, and they'll have more coffee breaks, and they'll be less incentive to go and do that, because the company will survive with or without them. So that's why startups can do things much better, sometimes than larger companies. We can do things better than startups, when it comes to being data driven because we have the data, and nobody can compete against the amount of data that we have. So we have a good combination of finding the right startups that have already built something, already proven that it works with some customers, and of course, building a lot of things internally that we cannot do outside. >> I heard you say in one of the, I dunno, dozens of videos I've listened to you talked to. The industry doesn't need or doesn't want another IoT stovepipe. Okay, I agree. So you got on-prem, AWS, Azure, Google, maybe Alibaba, IoT is going to be all over the place. So can you build, I call it the security super cloud, in other words, a consistent experience with the same policies and edicts across all my estates, irrespective of physical location? Is that technically feasible? Is it what you are trying to do? >> Certainly, what we're trying to do with Prisma Cloud, with our cloud security product, it works across all the clouds that you mentioned, and Oracle as well. It's almost entirely possible. >> Almost. >> Almost. Well, the things that... What you do is you normalize the language that the different cloud scale providers use, into one language. This cloud calls it a S3, and so, AWS calls it S3, and (indistinct) calls it GCS, and so on. So you normalize their terminology, and then build policy using a common terminology that your customers have to get used to. Of course, there are things that are different between the different cloud providers that cannot be normalized, and there, it has to be cloud specific. >> In that instance. So is that, in part, your strategy, is to actually build that? >> Of course. >> And does that necessitate running on all the major clouds? >> Of course. It's not just part of our strategy, it's a major part of our strategy. >> Compulsory. >> Look, as a standalone vendor that is not a cloud provider, we have two advantages. The first one is we're security product, security focused. So we can do much better than them when it comes to security. If you are a AWS, GCP, Azure, and so on, you're not going to put your best people on security, you're going to put them on the core business that you have. So we can do much better. Hey, that's interesting. >> Well, that's not how they talk. >> I don't care how they talk. >> Now that's interesting. >> When something is 4% of your business, you're not going to put it... You're not going to put your best people there. It's just, why would you? You put your best people on 96%. >> That's not driving their revenue. >> Look, it's simple. It's not what we- >> With all due respect. With all due respect. >> So I think we do security much better than them, and they become the good enough, and we become the premium. But certainly, the second thing that give us an advantage and the right to be a standalone security provider, is that we're multicloud, private cloud and all the major cloud providers. >> But they also have a different role. I mean, your role is not the security, the Nitro card or the Graviton chip, or is it? >> They are responsible for securing up to the operating system. We secure everything. >> They do a pretty good job of that. >> No, they do, certainly they have to. If they get bridged at that level, it's not just that one customer is going to suffer, the entire customer base. They have to spend a lot of time and money on it, and frankly, that's where they put their best security people. Securing the infrastructure, not building some cloud security feature. >> Absolutely. >> So Palo Alto Networks is, as we wrap here, on track to nearly double its revenues to nearly seven billion in FY '23, just compared to 2020, you were quoted in the press by saying, "We will be the first $100 billion cyber company." What is next for Palo Alto to achieve that? >> Yeah, so it was Nikesh, our CEO and chairman, that was quoted saying that, "We will double to a hundred billion." I don't think he gave it a timeframe, but what it takes is to double the sales, right? We're at 50 billion market cap right now, so we need to double sales. But in reality, you mentioned that we're growing the turn by doing more and more cybersecurity functions, and taking away pieces. Still, we have a relatively small, even though we're the largest cybersecurity vendor in the world, we have a very low market share that shows you how fragmented the market is. I would also like to point out something that is less known. Part of what we do with AI, is really take the part of the cybersecurity industry, which are service oriented, and that's about 50% of the cybersecurity industry services, and turn it into products. I mean, not all of it. But a good portion of what's provided today by people, and tens of billions of dollars are spent on that, can be done with products. And being one of the very, very few vendors that do that, I think we have a huge opportunity at turning those tens of billions of dollars in human services to AI. >> It's always been a good business taking human labor and translating into R and D, vendor R and D. >> Especially- >> It never fails if you do it well. >> Especially in difficult times, difficult economical times like we are probably experiencing right now around the world. We, not we, but we the world. >> Right, right. Well, congratulations. Coming up on the 18th anniversary. Tremendous amount of success. >> Thank you. >> Great vision, clear vision, STEM expansion strategy, really well underway. We are definitely going to continue to keep our eyes. >> Big company, a hundred billion, that's market capital, so that's a big company. You said you didn't want to work for a big company unless you founded it, is that... >> Unless it acts like a small company. >> There's the caveat. We'll keep our eye on that. >> Thank you very much. >> It's such a pleasure having you on. >> Thank you. >> Same here, thank you. >> All right, for our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live emerging and enterprise tech coverage. (upbeat music)

(bright music) >> Well, hey, everybody. John Walls here with theCUBE continuing coverage at AWS re:Invent '22. It has been three really fantastic days here at the Venetian in Las Vegas. And we still have more to come with us to talk about Persistent Systems, the Senior Vice President of Cloud at Persistent Dominique Bastos. Dominique, good to see you. >> Pleasure to see you. >> Thanks for joining us here on the queue. >> Thank you for having me. >> Oh, you bet. You bet. >> Thank you. All right. Tell us about Persistent Systems. So, first off, core focus, what you're up to and then we'll jump in from there. >> Sure, sure. So Persistent Systems is a digital engineering solutions and services provider. They've been around for 32 years doing software engineering, innovating in several areas within different verticals. There's over 22,500 people at Persistent now as of my last count. We're in 18 countries. >> Mm. >> And in October we hit the $1 billion annualized recurring revenue mark. >> Oh, that's a good number right there. >> It's a good number. It's a great company. It's been such an interesting journey. I was with AWS for almost seven years before recently joining Persistent, and it almost felt like a such a logical transition in terms of bringing what I've seen in my entire career of interacting with customers and businesses to what Persistent can provide as people are looking to make their journey to the cloud whatever stage they might be at so. >> Right. And we should point out is that SVP of Cloud, but your focus is AWS. >> My focus AWS. >> Other options, other opportunities. >> Right. >> But you're AWS all the way. >> Right. It's a multicloud company because, you know, we really don't believe in dictating to a customer what they need. I think the benefit, one of the differentiators for Persistent is the amount of legacy history that they have across these industries and customers. I mean, 32 years is a lot, and in terms of like software engineering. So it's like really doing the hard work, the heavy lifting. And then seeing what can actually be commoditized, repeatable building solutions within these verticals to help customers accelerate their transformations. >> Mm hmm. >> So... >> You know, when we talk about cloud, I mean, this has been something that's been on the forefront feel like a long time. Right? But yet there are still many and maybe you can help me out with that percentage, whatever of companies who are either haven't begun yet, are just beginning, they're really in a nascent stage of this transformation. And yeah, I found it curious this week as we've talked with different people about where are you in your journey and so and so forth. A lot of people are way back just starting pass go, and aren't as mature as I would've thought. I mean, do you find that to be the case? >> Absolutely. And there's many reasons for that. I mean, I think what I've started, I mean I've been seeing it over the years, but we all know IT and business back then was very much kept separate. >> Two separate animals. >> Two separate animals. >> Yeah. >> IT made the decisions, not in a vacuum, but almost in a vacuum, right? Now, obviously companies who know it's necessary and have embraced it, bring together the function of looking at the technological solutions that they're adopting to solve a business problem. Right? But that business problem really is dictated by the customer need. >> Mm hmm. >> So I think I have seen, you know, in terms of like the life cycle of a business adopting technology, post cloud, there's a lot of enterprises that are still, they've made such big investments in their legacy infrastructure. >> Mm hmm. >> And in actually, you know, the developers and the people that are maintaining those systems, and the different connections to put it in layman's terms between their systems and their customers systems, right? So, that entire scenario makes it very difficult for them to move. >> Mm hmm. >> It's like moving a mountain. So, I would say there's like three ways of looking at it. You have those that kind of want to revitalize their technology, right? Their backend systems, they want to optimize costs, they want to, and my background in technology is specifically in data, kind of I came up as a DBA and built data models, and I've always loved data before it was a thing to love data. (John chuckles) So... >> You were so far ahead of the curve. >> I was ahead of the curve. I was a trendsetter. >> What a trendsetter? >> I'm a trendsetter. (Dominique chuckles) So I think from that perspective they're looking at, you know, these enormous of amounts of data that they've been capturing in these legacy systems that they're so heavily invested in, but they're not able to derive the insights to better serve their customers or to even innovate new revenue streams from that data. But, they're taking the first step to say, look, you know, we can actually operate more smoothly at a lower cost by moving to the cloud. >> Mm hmm. >> So there's that. Then there are those that are looking to actually innovate and create new revenue streams, monetize their data, look at opportunities to integrate feedback that they've been getting from their customers to provide new services. So they're using the cloud journey, they've probably already moved into the cloud. They're starting to look at analytics, and potentially using AIML to facilitate creating these solutions and services. And then there's those that, you know, want to pioneer, and break into new inventions and ways of solving the big world problems. >> Mm hmm. >> Right? I mean, I think that's one thing I noticed in this re:Invent that I thought was so special is there's like a really big focus on humanity, on humans, on you know, as we were talking earlier everything and I myself have like holding books and I don't like people being on their phone when we're having a conversation. (John chuckles) >> Right. But I think, you know, we are where we are. The reality is the world has evolved in such a way that community is no longer, it takes a small village, all, you know everybody knows each other. You have face to face interactions. You're not doing that with your customers either. There's digitally native businesses that have for a long time cropped up in the FinTech space in you know, you name the space, there's a startup that was born in the cloud that can reach customers immediately, and can provide a service that an enterprise that's kind of like weighed down with their legacy systems. They can't pivot fast enough. So, I think, you know, the pioneers think beyond that. How do we use quantum computing? You know, how do we use 3D simulation to anticipate solving big world problems? Whether it's, you know, people no longer, I don't know what the statistics are, but it's very sad. That elderly people, you know, the amount of human contact that they have is very little. You know, and if you could provide, I don't know, an experience, an immersive experience where their memories are triggered, you know, to help them with dementia, or Alzheimer's. >> Sure. >> I mean, those types of things, those are the things that I think that's what excites me about the launches that I see at re:Invent. And I think the innovation, you know, you have to take that journey. Unless you're born in the cloud, you do have to kind of take that journey. >> You got to get there. >> You have to get there. >> Right. Sure. >> But it's so worth it. >> So how about, let's just say, if I'm a health sciences company, or I'm a pharmaceutical or whatever, and so I've got this desire to create this new opportunity you know, with a human, I say, but yeah, but if you're also Persistent Systems and you're working with you know, somebody in FinTech, or somebody in EEG or whatever, you can't really understand my challenges or my problems. I mean, how do you wear those different hats so you can identify not only what the focus of that client is, but also their technology and how you're going to get them to marry up so they can achieve their goals? >> Well, the beauty of being, you know, in a company with teams of people that you work with, I cut across industries. Right? So we have vertical leaders that have very deep subject matter expertise in any number of those areas. You know, we're working with genomics for example. So, for example, you know, we engage with a customer that we've been helping over the past 32 years use technology to bring services to their customers. And now we are seeing an opportunity to help them innovate to keep up for their business for obvious reasons, but also to supply their customers with the new innovative solutions within that industry, right? 'Cause you need that vehicle to kind of deploy and deliver what customers need. The way we do it is from end to end, right? So, we have in the partnership with AWS, we're a partner of AWS, and as such we are able to collaborate with AWS and their customers or bring our customers to the cloud for all the way from assessment to planning to execution. And even within Persistent, we have ways to main operationalize the maintenance of these solutions. So it's really very easy managed services type framework that we work under. In terms of like migration planning, we have competencies within AWS. For looking at migrations we have AIML, we have DevOps. So we have the various competencies aligned with AWS to be able to execute at whatever stage the customer is. But also in terms of like the accelerators that we provide or the frameworks to look at total cost, that cuts across, right? And then we don't kind of like, here's what you needed and buy, never speak to us again. (John chuckles) I mean, I think the beauty of this company and what I really loved when I was first speaking to them is the depth of the relationships with their customers and the longevity of them. So they've really seen their customers grow. And you can only do that if you're there for the long run. >> You've got to be present. >> You have to be present. >> Sure. So how do you handle if people are making this transformation and they're moving into the cloud, but the people they have on staff might not be familiar with it, right? They have great expertise in what they've been doing on these legacy systems, but now you're moving, you're migrating to a new world, new culture, new environment, and you got to get 'em up to speed. And that's not easy. >> No. >> Right? So what do you do, or what does Persistent suggest or what are you doing and with regard to closing that gap into making that bridge so that they can maintain a little bit on their own. >> Yeah. >> They can execute and implement on their own. >> Yep. >> A little bit. They don't need somebody there to stand over their shoulder the whole time. >> I won't geek out on having joined AWS in professional services way back when to migrate a major company to the cloud, and having lived through painstakingly all those problems and blockers and adoption roadblocks that you speak of. >> Mm hmm. >> You know, I think the way Persistent handles it is what I would've done myself, right? If I were to start a company and say how do we help customers simplify their cloud journey, and remove the complexity? I think that's what Persistent Systems does. We, there's training programs that we are aligned to with AWS. So there's up-skilling of development teams, application developers. We collaborate from the top down with executives to look at the resources that they have available. Obviously mission critical systems that cannot sacrifice having engineers pulled away for a new project. You know, you take that into account. I think, you know, when I spoke earlier about assessments, you're not just assessing what needs to be lifted and shifted or refactored or rearchitected, you're looking at, you know, all these applications that are going to move to the cloud. Who owns them? >> Mm hmm. >> You know, do you have a CI/CD pipeline, or a data pipeline built? Well, we're going to need that, right? So, the continuous integration, continuous development of applications, that type of DevOps, obviously security also DevSecOps, we look at it from end to end as well. We have a very strong security practice. So, all those advisory pieces we have, but we also have the capability to execute on it. Where we're not just coming in and saying well this is what you should do. We're kind of in there saying, this is what you should do, here's how we can get you started. And then, you know, it's a collaborative effort with our customers to see how much they still want us to stay versus how much they want to take over. >> Right. It's nice to have a friend. >> Yeah. (John laughs) Who doesn't need a friend. (Dominique laughs) And Persistent Systems is your friend. Dominique, thanks for the time. >> Oh, my pleasure. >> I appreciate it. >> Thanks again for having me. >> Thanks for being here on theCUBE. You bet. >> Absolutely. >> You are watching theCUBE as you well know the leader in high tech coverage. (soft music)

(upbeat music) >> Welcome back to theCUBE's live coverage of AWS re:Invent. Friends, it's good to see you. Lisa Martin here with Dave Vellante. This is our fourth day of CUBE wall-to-wall coverage, Dave. I can't believe it. And the expo hall is still going incredibly strong. >> Yeah, it is. It feels like the biggest re:Invent ever. I'm told it's almost as big as 2019. I don't know, maybe I was half asleep at 2019. That's very possible. But I'm excited because in 2017 Andy Jassy came on theCUBE and he said if Amazon had to do it all over again, if it knew then what it had now, we would've done the whole thing in containers or using Lambda, using serverless and using containers. Didn't have that opportunity back then. And I'm excited 'cause Rafay Systems is someone we've worked with a lot as an innovator in this space. >> Yep, and we're going to be talking with Rafay again. I think it's your 10th time Haseeb on the show >> Like once or twice. >> And a great customer who's going to talk about their serverless journey. Haseeb Budhani joins us once again, the CEO of Rafay. Great to see you. Rakesh Singh is here as well, the Head of Cloud and DevOps at Regeneron. Guys, it's great to have you on the program. How you feeling on day four of re:Invent? >> Excitement is as high as ever basically. >> Isn't it amazing? >> Rakesh: That's true. >> Haseeb: I just need some sleep. >> I'm with you on that. Caffeine and sleep. >> So many parties. So many meetings, oh my God. >> But the great thing is, Haseeb, that people want to engage with you. They're loving what Rafay is doing. You guys are a great testament to that, which we're going to uncover on the show. What are some of the things that you're hearing in the booth from customers? What's been some of the feedback? >> So firstly, as I said, it feels like the biggest one ever. I've been coming to re:Invent a long time and I mean, I know the numbers say it's not, but oh my God, this is a lot of people. Every time we've spoken over the last year and the point I always make to you, and we've spoken enough time about this is that enterprises are truly adopting this idea of Kubernetes containers, serverless, et cetera. And they're all trying to figure out what is the enterprise strategy for these things? They're thinking beyond technology and thinking operationalization of these technologies. And that's not the same thing. There's a toy and then there's the real thing. And that's not the same thing. And that's the gap that every enterprise customer I talked to and the booth traffic has been just amazing. I mean, but coming here I was thinking, my God, this is really expensive. And I'm thinking, wow, this is a great investment. Because we met such amazing companies who all essentially are saying exactly the same thing, which is as we go and productize and bring our high value applications to the modern infrastructure space, like Kubernetes, Lambda, et cetera, solving for the automation governance is really, really hard because, well, at one point, I guess when the economy was doing crazy well, I could keep hiring people, but I can't do that anymore either. So they're out looking for automation strategies that allow them to do more with the teams they have. And that's exactly what Rafay is here for. >> Yeah. Lisa, Adam Selipsky in his keynote, I love the, he said, "If you want to save money, the cloud is the place to do it." >> Exactly. Yep. Let's talk about Regeneron. Everyone knows it's a household word especially over the last couple of years, but talk about, Rakesh, Regeneron as a technology company that delivers life-saving pharmaceuticals. And where does cloud and Rafay fit into your strategy? >> So cloud has been a backbone of our compute strategy within Regeneron for a very long time now. The evolution from a traditional compute structure to more serverless compute has been growing at a rapid pace. And I would say like we are seeing exponential growth within the adaption of the compute within containers and Kubernetes world. So we've been on this journey for a long time and I think it's not stopping anytime soon. So we have more and more workload, which is running on Kubernetes containers and we are looking forward to our partnership with Rafay to further enhance it, as Haseeb mentioned, the efficiency is the key. We need to do more with less. Resourcing is critical and cloud is evolved from that journey that do more things in a more efficient manner. >> That was the original catalyst as we got to help our development team, be more productive. >> That's correct. >> Eliminate the heavy lifting. And then you started presumably doing some of the less heavy, but still heavy lifting and we talked off camera and then you're increasingly moving toward serverless. >> Rakesh: That's correct. >> Can you describe that journey? What that's like? >> So I think like with the whole adoption that things are taking a much faster pace. Basically we are putting more compute onto containers and the DevOps journey is increasingly getting more, more faster. >> Go ahead. 'Cause I want to understand where Rafay sits in this whole equation. I was talking about, I'm not a developer, but I was talking to developer yesterday trying to really understand the benefits of containers and serverless and I said, take me through what you have to do when you're using containers. He said, I got to build the container image then I got to deploy an EC2 instance where I got to choose and I got to allocate memory of the fence the app in a VM then I got to run the computing instance against the app. And then, oh by the way, I got to pay 'cause all that EC2 that whole time. Depending on how you approach serverless you're going to eliminate a lot of those steps. >> That is correct. So what we do is basically like in a traditional sense, the computer is sitting idle at quite a lot basically. >> But you're paying. >> And you're still paying for that. Serverless technologies allows us to use the compute as needed basis. So whenever you need it, it is available. You run your workload on that and after that it shuts down or goes to minimal state and you don't need to pay as much as your paying. >> And then where do you guys fit in that whole equation? >> Look, serverless has a paradigm. If you step back from the idea of containers versus Lambda or whatever functions. The idea should be that the list you just read out of what developers have to do. Here's what they really should do. They should write their code, they should check it in, and they never have to think about it again. That should be the case. If they want to debug their application, there should be a nice front end where they go and they interact with their application and that's it. What is Kubernetes? I don't care. That's the right answer. And we did not start this journey as an industry there because usually the initial adopters are developers who do the heavy lifting. Developers want to learn, they want to solve these problems. But then eventually the expectation is that the platform organization and an enterprise is going to own this platform for me so I can go back to doing my job, which is writing code. And that's where Rakesh's team comes in. So Rakesh team is building the standard at Regeneron. Whether you're writing a long-lasting app, which is going to run in a container or you're going to write an event-driven application, which is going to be a function, whatever. You write your app, we will give you the necessary tooling and plumbing to take care of all these things. And this is my problem. My being Rakesh. Rakesh is my customer. He has his customers. We as Rafay, A, we have to make Rakesh's system successful because we have to give them right automation to do all these things so that he can service hundred, or in his case, thousands and thousands of different individuals. But then collectively, we have to make sure that the developer experience is optimal so that truly they just write their code and EC2, they don't want to deal with this. In fact, on Monday evening, in the Kubernetes keynote by Barry Cooks, one of the things he said was that in a CIO sort of survey they did, CIO said, 80% of the time of developers is wasted on infrastructure stuff and not on innovation. We need to bring that 80% back so that a hundred percent of the work is on innovation and today it's not. >> And that's what you do. >> That's what we do. >> In your world as a developer, I only have to worry about my writing my code and what functions I'm going to call. >> That is correct. And it is important because the efficiencies of a developer need to be focused on doing the things which business is asking for. The 80% of the work like to make sure the things are secure, they're done the right way, the standards are followed, scanning part of it, that work if we can offload to a platform, for example, Rafay, saves a lot of works, a lot of work cycles from the developers perspective. >> Thank you for that. It was nice little tutorial on the benefits. >> Absolutely. So you transform the developer experience. >> That's correct. >> How does that impact Regeneron overall business? We uplevel that. Give me that view. >> So with that, like what happens, the key thing is the developers productivity increases. We are able to do more with less. And that is the key thing to our strategy that like with the increase in business demand, with the increase in lot of compute things, which we are doing, we need to do and hiring resources is getting more difficult than ever. And we need to make sure that we are leveraging platforms and tools basically to do, enable our developers to focus on key business activity rather than doing redundant things and things which we can leverage some other tooling and platform for that business. >> Is this something in terms of improving the developer experience and their productivity faster time to market? Is this accelerating? >> That's correct. >> Is this even like accelerating drug discovery in some cases? >> So COVID is like a great example for that. Like we were able to fast track our drug discovery and like we were able to turn it into an experience where we were able to discover new drugs and get it to the market in a much faster pace. That whole process was expedited using these tools and processes basically. So we are very proud of that. >> So my understanding is you're running Rafay with EKS. A lot of choices out there. Why? Why did you choose to go in that direction? >> So Regeneron has heavily invested in cloud recently, over the years basically. And then we are focusing on hybrid cloud now that we we are like, again, these multiple cloud providers of platforms which are coming in are strategies to focus on hybrid cloud and Rafay is big leader in that particular space where we felt that we need to engage or partner with Rafay to enable those capabilities, not just on AWS, but across the board. One single tool, one single process, one single knowledge base helps us achieve more efficiencies. >> Less chaos, less complexity. >> That's correct. Let's say when you're in customer conversations, which I know you've had many this week, but you probably do that all the time. Regeneron is a great use case for Rafay. It's so tangible, life sciences. We all get that, especially coming out of the pandemic. What do you say to customers are the top three differentiators of Rafay and why they should go Rafay on top of EKS? >> What's really interesting about these conversations is that, look, we have some pretty cool features in our product. Obviously we must have something interesting otherwise nobody would buy our product. And we have access management and zero trust models and cluster provisioning, all these very nice things. But it always comes down to exactly the same thing, which is every large enterprise that started a journey, independent or Rafay because they didn't know who we were, it's fine. Last year we were a young company, now we are a larger company and they all are basically building towards a roadmap which Rafay truly understands. And in my opinion, and I'm confident when I say this, we understand their life, their journey better than any other company in the market. The reason why we have the flurry of customers we have, the reason why the product has the capacity that it does is because for whatever reason, look, it's scale lock. That's for the history books. But we have complete clarity on what a pharmaceutical company or financial customers company or a high tech company the journey they will take to the cloud and automation for modern infrastructure, we get it. And what I'm selling them is the is the why, not the what. There's a lot of great answers for the what? What do we do? Rakesh doesn't care. I mean, he's trying to solve a bigger problem. He's trying to get his researchers to go faster. So then when they want to run a model, they should be able to do it right now. That's what he cares about. Then he looks for a tool to solve the business problem. And we figured out how to have that conversation and explain why Rafay helps him, essentially multiply the bandwidth that he has in his organization. And of course to that end we have some great technology/ But that's a secondary issue, the first, to me the why is more important than the what. And then we talk about how, which he has to pay us money. That's the how. But yeah, we get there too. But look, this is the important thing. Every enterprise is on exactly the same journey, Lisa. And that if you think about it from just purely economic efficiencies perspective that is not a good investment for our industry. If everybody's solving the same problem that's a waste of resources. Let's find a way to do, what is the point of the cloud? We used to all build data centers. That was not efficient. We all went to the cloud because it's more efficient to have somebody else, AWS, solve this problem for us so we can now focus on the next level problem. And then Rafay solving that problem so that he can focus on his drug discovery, not on Kubernetes. >> That's correct. It's all about efficiencies. Like doing things, learn from each other's experience and build upon it. So the things have been solved. One way you need to leverage that, reuse it. So the principles are the same. >> So then what's next? You had done an amazing job transforming the company. You're facilitating drug discovery faster than ever before. From an infrastructure perspective, what's next on your journey? >> So right now the roadmap what we have is basically talking about making sure that the workload are running more efficient, they're more secure. As we go into these expandable serverless technology, there are more challenging opportunities for us to solve. Those challenges are coming up. We need to make sure that with the new, the world we are living in, we are more securely doing stuff what we were doing previously. More efficiencies is also the key and more distributed. Like if we can leverage the power of cloud in doing more things on demand is on our roadmap. And I think that is where we are all driving. >> And when you said hybrid, you're talking about connecting to your on-prem tools and data? How about cross cloud? >> We are invested in multiple cloud platform itself and we are looking forward to leveraging a technology, which is truly cloud native and we can leverage things together on that. >> And I presume you're helping with that, obviously. >> Last question for both of you. We're making an Instagram reel. Think of this as a sizzle reel, like a 32nd elevator pitch. Question, first one goes to you, Rakesh. If you had a bumper sticker, you put it on, I don't know, say a DeLorean, I hear those are coming back. What would it say about Regeneron as a technology company that's delivering therapeutics? >> It's a tough question, but I would try my best. The bumper sticker would say, discover drug more faster, more efficient. >> Perfect. Haseeb, question about Rafay. What's the bumper sticker? If you had a billboard in on Highway 101 in Redwood City about Rafay and what it's enabling organizations enterprises across the globe to achieve, what would it say? >> I'll tell you what our customers say. So our customers call us the vCenter for Kubernetes and we all know what a vCenter is. We all know why vCenter's so amazingly successful because it takes IT engineers and gives them superpowers. You can run a data center. What is the vCenter for this new world? It us. So vCenter is obviously a trademark with our friends at VMware, so that's why I'm, but our customers truly call us the vCenter for Kubernetes. And I think that's an incredible moniker because that truly codifies our roadmap. It codifies what we are selling today. >> There's nothing more powerful and potent in the voice of the customer. Thank you both for coming on. Thank you for sharing the Regeneron story. Great to have you back on, Haseeb. You need a pin for the number of times you've been on theCUBE. >> At least a gold star. >> We'll work on that. Guys, thank you. We appreciate your time. >> Haseeb: Thank you very much. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

>>Good morning friends. Live from Las Vegas. It's the Cube Day four of our coverage of AWS. Reinvent continues. Lisa Martin here with Dave Valante. You >>Can tell it's day four. Yeah. >>You can tell, you >>Get punchy. >>Did you? Yes. Did you know that the Vegas rodeo is coming into town? I'm kind of bummed down, leaving tonight. >>Really? You rodeo >>Fan this weekend? No, but to see a bunch of cowboys in Vegas, >>I'd like to see the Raiders. I'd like to see the Raiders get tickets. >>Yeah. And the hockey team. Yeah. We have had an amazing event, Dave. The cubes. 10th year covering reinvent 11th. Reinvent >>Our 10th year here. Yeah. Yes. Yeah. I mean we covered remotely in during Covid, but >>Yes, yes, yes. Awesome content. Anything jump out at you that we really, we, we love talking to aws, the ecosystem. We got a customer next. Anything jump out at you that's really a kind of a key takeaway? >>Big story. The majority of aws, you know, I mean people ask me what's different under a Adam than under Andy. And I'm like, really? It's the maturity of AWS is what's different, you know, ecosystem, connecting the dots, moving towards solutions, you know, that's, that's the big thing. And it's, you know, in a way it's kind of boring relative to other reinvents, which are like, oh wow, oh my god, they announced outposts. So you don't see anything like that. It's more taking the platform to the next level, which is a good >>Thing. The next level it is a good thing. Speaking of next level, we have a couple of next level guests from T-Mobile joining us. We're gonna be talking through their customers story, their business transformation with aws. Glenn Curing joins us, the director product and technology. And Nick Chris, senior manager, product and technology guys. Welcome. Great to have you on brand. You're on T-Mobile brand. I love it. >>Yeah, >>I mean we are always T-Mobile. >>I love it. So, so everyone knows T-Mobile Blend, you guys are in the digital commerce domain. Talk to us about what that is, what functions that delivers for T-Mobile. Yeah, >>So the digital commerce domain operates and runs a platform called the Digital commerce platform. What this essentially does, it's a set of APIs that are headless that power the shopping experiences. When you talk about shopping experiences at T-Mobile, a customer comes to either a T-Mobile website or goes to a store. And what they do is they start with the discovery process of a phone. They take it through the process, they decide to purchase the phone day at, at the phone to cart, and then eventually they decide to, you know, basically pull the trigger and, and buy the phone at, at which point they submit the order. So that whole experience, essentially from start to finish is powered by the digital commerce platform. Just this year we have processed well over three and a half million orders amounting to a billion and a half dollars worth of business for T-Mobile. >>Wow. Big outcomes. Nick, talk about the before stage, obviously the, the customer experience is absolutely critical because if, if it goes awry, people churn. We know that and nobody wants, you know, brand reputation is is at stake. Yep. Talk about some of the challenges before that you guys faced and how did you work with AWS and part its partner ecosystem to address those challenges? >>Sure. Yeah. So actually before I started working with Glen on the commerce domain, I was part of T-Mobile's cloud team. So we were the team that kind of brought in AWS and commerce platform was really the first tier one system to go a hundred percent cloud native. And so for us it was very much a learning experience and a journey to learn how to operate on the cloud and which was fundamentally different from how we were doing things in the old on-prem days. When >>You talk about headless APIs, you talk, I dunno if you saw Warren a Vogel's keynote this morning, but you're talking about loosely coupled, a loosely coupled system that you can evolve without ripping out the whole system or without bringing the whole system down. Can you explain that in a little bit more >>Detail? Absolutely. So the concept of headless API exactly opens up that possibility. What it allows us to do is to build and operator platform that runs sort of loosely coupled from the user experiences. So when you think about this from a simplistic standpoint, you have a set of APIs that are headless and you've got the website that connects to it, the retail store applications that connect to it, as well as the customer care applications that connect to it. And essentially what that does is it allows us to basically operate all these platforms without being sort of tightly coupled to >>Each other. Yeah, he was talking about this morning when, when AWS announced s3, you know, there was just a handful of services maybe at just two or three. I think now there's 200 and you know, it's never gone down, it's never been, you know, replaced essentially. And so, you know, the whole thing was it's an asynchronous system that's loosely coupled and then you create that illusion of synchronicity for the customer. >>Exactly. >>Which was, I thought, you know, really well described, but maybe you guys could talk about what the genesis was for this system. Take us kind of to the, from the before or after, you know, the classic as as was and the, and as is. Did you talk about that? >>Yeah, I can start and then hand it off to Nick for some more details. So we started this journey back in 2016 and at that point T-Mobile had seven or eight different commerce platforms. Obviously you can think about the complexity involved in running and operating platforms. We've all talked about T-Mobile being the uncarrier. It's a brand that we have basically popularized in the telco industry. We would come out with these massive uncarrier moves and every time that announcement was made, teams have to scramble because you've got seven systems, seven teams, every single system needs to be updated, right? So that's where we started when we kicked off this transformational journey over time, essentially we have brought it down to one platform that supports all these experiences and what that allows us to do is not only time to market gets reduced immensely, but it also allows us to basically reduce our operational cost. Cuz we don't have to have teams running seven, eight systems. It's just one system with one team that can focus on making it a world class, you know, platform. >>Yeah, I think one of the strategies that definitely paid off for us, cuz going all the way back to the beginning, our little platform was powering just a tiny little corner of the, of the webspace, right? But even in those days we approached it from we're gonna build functions in a way that is sort of agnostic to what the experience is gonna be. So over time as we would build a capability that one particular channel needed primary, we were still thinking about all the other channels that needed it. So now over a few years that investment pays off and you have basically the same capabilities working in the same way across all the channels. >>When did the journey start? >>2016. >>2016, yeah. It's been, it's been six years. >>What are some of the game changers in, in this business transformation that you would say these are some of the things that really ignited our transformation? >>Yeah, there's particularly one thing that we feel pretty proud about, which is the fact that we now operate what we call active active stacks. And what that means is you've got a single stack of the eCommerce platform start to finish that can run in an independent manner, but we can also start adding additional stacks that are basically loosely coupled from each other but can, but can run to support the business. What that basically enables is it allows us to run in active active mode, which itself is a big deal from a system uptime perspective. It really changes the game. It allows us to push releases without worrying about any kind of downtime. We've done canary releases, we are in the middle of retail season and we can introduce changes without worrying about it. And more importantly, I think what it has also allowed us to do is essentially practice disaster recovery while doing a release. Cuz that's exactly what we do is every time we do a release we are switching between these separate stacks and essentially are practicing our DR strategy. >>So you do this, it's, it's you separate across regions I presume? Yes. Is that right? Yes. This was really interesting conversation because as you well know in the on-prem world, you never tested that disaster recovery was too risky because you're afraid you're gonna take your whole business down and you're essentially saying that the testing is fundamental to the implementation. >>Absolutely. >>It, it is the thing that you do for every release. So you know, at least every week or so you are doing this and you know, in the old world, the active passive world on paper you had a bunch of capabilities and in in incidents that are even less than say a full disaster recovery scenario, you would end up making the choice not to use that capability because there was too much complexity or risk or problem. When we put this in place. Now if I, I tell people everything we do got easier after that. >>Is it a challenge for you or how do you deal with the challenge? Correct me if it's not a, a challenge that sometimes Amazon services are not available in both regions. I think for instance, the observability thing that they just announced this week is it's not cross region or maybe I'm getting that wrong, but there are services where, you know, you might not be able to do data sharing across region. How do you manage that? Or maybe there's different, you know, levels of certifications. How do you manage that discontinuity or is that not an issue for you? >>Yeah, I mean it, it is certainly a concern and so the stacks, like Glen said, they are largely decoupled and that what that means is practically every component and there's a lot of lot of components in there. I have redundancy from an availability zone point of view. But then where the real magic happens is when you come in as a user to the stack, we're gonna initially kind of lock you on one stack. And then the key thing that we do is we, we understand the difference between what, what we would call the critical data. So think of like your shopping carts and then contextual data that we can relatively easily reload if we need to. And so that critical data is constantly in an async fashion. So it's not interrupting your performance, being broadcast out to a place where we can recover it if we need to, if we need to send you to another stack and then we call that dehydration. And if you end up getting bumped to a new stack, we rehydrate you on that stack and reload that, that contextual data. So to make that whole thing happen, we rely on something we call the global cart store and that's basically powered by Dynamo. So Dynamo is highly, highly reliable and multi >>Reason. So, and, and presume you're doing some form of server list for the stateless stuff and, and maybe taking control of the run time for the stateful things you, are you leaning into to servers and lambda or Not yet cuz you want control over the, the, the EC two and the memory configs. What, what's, I mean, I know we're going inside the plumbing a little bit, but it's kind of fun. >>That's always fun. You >>Went Yeah, and, and it has been a journey. Back in 2016 when we started, we were all on EC twos and across, you know, over the last three or four years we have kind of gone through that journey where we went from easy two to, to containers and we are at some point we'll get to where we will be serverless, we've got a few functions running. But you know, in that journey, I think when you look at the full end of the spectrum, we are somewhere towards the, the process of sort of going from, you know, containers to, to serverless. >>Yeah. So today your team is setting up the containers, they're fencing 'em off, fencing off the app and doing all that sort of sort of semi heavy lifting. Yeah. How do you deal with the, you know, this is one of the things Lisa, you and I were talking about is the skill sets. We always talk about this. What's that? What's your team look like and what are the skill sets that you've got that you're deploying? >>Yeah, I mean, as you can imagine, it's a challenge and it's a, a highly specialized skill set that you need. And you talk about cloud, you know, I, I tell developers when we bring new folks in, in the old days, you could just be like really good at Java and study that for and be good at that for decades. But in the cloud world, you have to be wide in, in your breadth. And so you have to understand those 200 services, right? And so one of the things that really has helped us is we've had a partner. So UST Global is a digital services company and they've really kind of been on the journey up the same timeline that we were. And I had worked with them on the cloud team, you know, before I came to commerce. And when I came to, to the commerce team, we were really struggling, especially from that operational perspective. >>The, the team was just not adapting to that new cloud reality. They were used to the on-prem world, but we brought these folks in because not only were they really able to understand the stuff, but they had built a lot of the platforms that we were gonna be leveraging for commerce with us on the cloud team. So for example, we have built, T-Mobile operates our own customized Kubernetes platform. We've done some stuff for serverless development, C I C D, cloud security. And so not only did these folks have the right skill sets, but they knew how we were approaching it from a T-mobile cloud perspective. And so it's kind of kind of fun to see, you know, when they came on board with this journey with us, we were both, both companies were relatively new and, and learning. Now I look and, you know, I I think that they're like a, a platinum sponsor these days here of aws and so it's kind of cool to see how we've all grown together, >>A lot of evolution, a lot of maturation. Glen, I wanna know from you when we're almost out of time here, but tell me the what the digital commerce domain, you kind of talked about this in the beginning, but I wanna know what's the value in it for me as a customer? All of this under the hood plumbing? Yeah, the maturation, the transformation. How does it benefit mean? >>Great question. So as a customer, all they care about is coming into, going to the website, walking into a store, and without spending too much time completed that transaction and walkout, they don't care about what's under the hood, right? So this transformational journey from, you know, like I talked about, we started with easy twos back in the day. It was what we call the wild west in the, on a cloud native platform to where we have reached today. You know, the journey we have collectively traversed with the USD has allowed us to basically build a system that allows a customer to walk into a store and not spend a whole hour dealing with a sales rep that's trying to sell them things. They can walk in and out quickly, they go to the website, literally within a couple minutes they can complete the transaction and leave. That's what customers want. It is. And that has really sort of helped us when you think about T-Mobile and the fact that we are now poised to be a leader in the US in telco at this whole concept of systems that really empower the customers to quickly complete their transaction has been one of the key components of allowing us to kind of make that growth. Right. So >>Right. And a big driver of revenue. >>Exactly. >>I have one final question for each of you. We're making a Instagram reel, so think about if you had 30 seconds to describe T-Mobile as a technology company that sells phones or a technology company that delights people, what, what would you say if you had a billboard, what would it say about that? Glen, what do you think? >>So T-Mobile, from a technology company perspective, the, the whole purpose of setting up T-mobile's, you know, shopping experience is about bringing customers in, surprising and delighting them with the frictionless shopping experiences that basically allow them to come in and complete the transaction and move on with their lives. It's not about keeping them in the store for too long when they don't want to do it. And essentially the idea is to just basically surprise and delight our customers. >>Perfect. Nick, what would you say, what's your billboard about T-Mobile as a technology company that's delivering great services to its customers? >>Yeah, I think, you know, Glen really covered it well. What I would just add to that is I think the way that we are approaching it these days, really starting from that 2016 period is we like to say we don't think of ourselves as a telco company anymore. We think of ourselves as a technology company that happens to do telco among other things, right? And so we've approached this from a point of view of we're here to provide the best possible experience we can to our customers and we take it personally when, when we don't reach that high bar. And so what we've done in the last few years as a transformation is really given us the toolbox that we need to be able to meet that promise. >>Awesome. Guys, it's been a pleasure having you on the program, talking about the transformation of T-Mobile. Great to hear what you're doing with aws, the maturation, and we look forward to having you back on to see what's next. Thank you. >>Awesome. Thank you so much. >>All right, for our guests and Dave Ante, I'm Lisa Martin, you watching The Cube, the leader in live enterprise and emerging tech coverage.

(bright upbeat music) >> Welcome back everyone to theCUBE's live coverage here in Las Vegas for wall-to-wall coverage. It is re:Invent 2022, our 10th year with theCUBE. Dave and I started this journey 10 years ago here at re:Invent. There are two sets, here, a set upstairs. Great content, I'm here with Paul Gillin, my cohost. Paul's out reporting on the floor, doing some interviews. Paul, what do you think so far? It's pretty crazy activity going on here. >> Well, the activity hasn't declined at all. I mean here we are in day three of the show and it's just as busy out there as it was in day one. And there's just an energy here that you can feel, it's palpable. There is a lot of activity around developers, a lot around data. Which actually brings us a good segue into our next guest because one of the leaders in data management in the cloud is MariaDB. And John Bakke is the CRO at MariaDB, and here to talk to us about your cloud version and how open source is going for you. >> Yeah, thanks for having me. >> Paul: Thanks for joining us. >> To get the update on the product, what do you guys do on the relation to AWS? How's that going? Give us a quick update. >> In the relational database? >> No, no. The relationship with AWS >> Oh, with AWS? >> And SkySQL, what's the update? >> There's no relationship that we have that's more important than the AWS relationship. We're building our cloud, our premier cloud service called SkySQL on AWS. And they offer the best in class infrastructure for a SaaS company to build what they're building. And for us, it's a database service, right? And then beyond that, they help you from the business side, right? They try to get you lined up in the marketplace and make it possible for you to work best with customers. And then from a customer perspective, they're super helpful in not only finding prospective customers, but making that customer successful. 'Cause everybody's got a vested interest in the outcome. Right? >> Yeah, a little tongue twister there. Relational data-based relationship. We've got relational databases, we've got unstructured, data is at the center of the value proposition. Swami's keynote today and the Adam CEO's keynote, data and security dominated the keynotes >> John: Yes. >> and the conversations. So, this is real. The customers are really wanting to accelerate the developer experience, >> John: Yep. >> Developer pipe lining, more code faster, more horsepower under the hood. But this data conversation, it just never goes away. The world's keeping on coming around. >> John: It never goes away. I've been in this business for almost 30 years and we're still talking about the same key factors, right? Reliability, availability, performance, security. These things are pervasive in the data management because it's such a critical aspect to success. >> Yeah, in this case of SkySQL, you have both a transactional and an analytical engine in one. >> John: That's correct. >> Right? >> John: Yep. >> And that was a, what has the customer adoption been like of that hybrid, or I guess not a hybrid, but a dual function? >> Yeah. So the thing that makes that important is that instead of having siloed services, you have integrated data services. And a lot of times when you ask a question that's analytical it might depend on a transaction. And so, that makes the entire experience best for the developer, right? So, to take that further, we also, in SkySQL, offer a geospatial offering that integrates with all of that. And then we even take it further than that with distributed database with Xpand or ready to be Xpand. >> A lot of discussion. Geospatial announcement today on stage, just the diversity of data, and your experience in the industry. There's not the one database that rule them all anymore. There's a lot of databases out there. How are customers dealing with, I won't say database for all, 'Cause you need databases. And then you've got real time transactional, you got batch going on, you got streaming data, all kinds of data use cases now, all kind of having to be rolled together. What's your reaction? What's your take on the state of data and databases? >> Yeah, yeah, yeah. So when I started in this business, there were four databases, and now there's 400 databases. And the best databases really facilitate great application development. So having as many of those services in real time or in analytics as possible means that you are a database for everyone or for all users, right? And customers don't want to use multiple databases. Sometimes they feel like they're forced to do that, but if you're like MariaDB, then you offer all of those capabilities in an integrated way that makes the developer move faster. >> Amazon made a number of announcements this morning in the data management area, including geospatial support on RDS, I believe. How do you, I guess, coordinate yourself, your sales message with their sales message, given that you are partners, but they are competing with you in some ways? >> Yeah, there's always some cooperatition, I guess, that happens with AWS in the various product silos that they're offering their customers. For us, we're one of thousands of obviously partners that they have. And we're out there trying to do what our customers want, which is to have those services integrated, not glued together with a variety of different integration software. We want it integrated in the service so that it's one data provision, data capability for the application developer. It makes for a better experience for the developer in the end. >> On the customer side, what's the big activity? I mean, you got the on-premises database, you've got the cloud. When should a customer decide, or what's the signals to them that they should either move to the cloud, or change, be distributed? What are some of the forcing functions? What does the mark look like? >> Yeah, I've come a long way on this, but my opinion is that every customer should be in the cloud. And the reason simply is the economies that are involved, the pace of execution, the resilience and dependability of the cloud, Amazon being the leader in that space. So if you were to ask me, right now is the time to be in SkySQL because it's the premier data service in the cloud. So I would take my customer out of their on-prem and put them all in AWS, on SkySQL, if I could. Not everybody's ready for that, but my opinion is that the security is there, the reliability, the privacy, all of the things that maybe are legacy concerns, it's all been proven to be adequate and probably even better because of all of the economies of scale that you get out of being in the cloud just generally. >> Now, MariaDB, you started on-premise though. You still have a significant customer base on-premise. What, if anything are you doing to encourage them to migrate to the cloud? >> Well, so we have hundreds and hundreds of customers as MariaDB, and we weren't the first database company to put their database in the cloud, but watching it unfold helped us realize that we're going to put MariaDB in its best form factor in SkySQL. It's the only place you could get the enterprise version of MariaDB in a cloud service, right? So when we look at our customers on-prem, we're constantly telling them, obviously, that we have a cloud service. When they subscribe, we show them the efficiencies and the economies, and we do get customers that are moving. We had a customer go to Telefonica over in the UK that moved from an on-premise to manage their wifi services across Europe. And they're very happy. They were one of our very first SkySQL customers. And that has routinely proven itself to be a path towards not only a better operation for the customer, they're up more, they have fewer outages because they're not inflicting their own self wounds that they have in their own data center. They're running on world class infrastructure on world class databases. >> What are some of those self wounds? Is it personnel, kind of manual mistakes, just outages, reliability? What's the real cause, and then what's the benefit alternative in the cloud that is outside? >> Yeah. I mean, I think, when you repeat the same database implementation over and over on the infrastructure, it gets tested thousands and thousands of times. Whereas if I'm a database team and I install it once, I've tested it one time, and I can't account for all of the things that might happen in the future. So the benefit of the cloud is that you just get that repeat ability that happens and all of the sort of the kinks and bugs and issues are worked out of the system. And that's why it's just fundamentally better. We get 99.9999% uptime because all of those mistakes have been made, solved, and fixed. >> Fully managed, obviously. >> Yes. Right. >> Huge benefit. >> John: Right. >> And people are moving, it's just a great benefit. >> John: Yeah. >> So I'm a fan obviously. I think it's a great way to go. I got to ask about the security though, because big conversation here is security. What's the security posture? What's the security story to customers with SkySQL and MariaDB? >> Right, right, right. So we've taken the server, which was the initial product that MariaDB was founded upon, right? And we've come a long way over the several years that we've been in business. In SkySQL, we have SOC 2 compliance, for example. So we've gone through commercial certifications to make sure that customers can depend that we are following processes, we have technology in place in order to secure and protect their data. And in that environment, it is repeatable. So every time a customer uses our DBaaS infrastructure, databases a service infrastructure called SkySQL, they're benefiting from all of the testing that's been done. They go there and do that themselves, they would've to go through months and months of processes in order to reach the same level of protection. >> Now MariaDB is distributed by design. Is that right? >> Yes. So we have a distributed database, it's called Xpand, MariaDB Xpand. And it's an option inside of SkySQL. It's the same cost as MariaDB server, but Xpand is distributed. And the easiest way to understand what distributed database is is to understand what it is not first. What it is not is like every other cloud database. So most of the databases strangely in the cloud are not distributed databases. They have one single database node in a cluster that is where all of the changes and rights happen. And that creates a bottleneck in the database. And that's why there's difficulties in scale. AWS actually talked about this in the keynote which is the difficulty around multi writer in the cloud. And that's what Xpand does. And it spreads out the reads and the rights to make it scalable, more performant, and more resilient. One node goes down, still stays up, but you get the benefit of the consistency and the parallelization that happens in Xpand. >> So when would a customer choose Xpand versus SkySQL Vanilla? >> So we have, I would say a lot of times, but the profile of our customers are typically like financial services, trade stores. We have Samsung Cloud, 500,000 transactions per second in an expand cluster where they run sort of their Samsung cloud for their mobile device unit. We have many customers like that where it's a commercial facing website often or a service where the brand depends on uptime. Okay. So if you're in exchange or if you are a mobile device company or an IOT company, you need those databases to be working all the time and scale broadly and have high performance. >> So you have resiliency built in essentially? >> Yes, yeah. And that's the major benefit of it. It hasn't been solved by anybody other than us in the cloud to be quite honest with you. >> That's a differentiator for sure. >> It is a huge differentiator, and there are a lot of interested parties. We're going to see that be the next discussion probably next year when we come back is, what's the state of distributed database? Because it's really become really the tip of the spear with the database industry right now. >> And what's the benefits of that? Just quickly describe why that's important? >> Obviously the performance and the resilience are the two we just talked about, but also the efficiency. So if you have a multi-node cluster of a single master database, that gets replicated four times, five times over, five times the cost. And so we're taking cost out, adding performance in. And so, you're really seeing a revolution there because you're getting a lot more for a lot less. And whenever you do that, you win the game. Right? >> Awesome. Yeah, that's true. And it seems like, okay, that might be more costly but you're not replicating. >> That's right. >> That's the key. >> Replicating just enough to be resilient but not excessively to be overly redundant. Right. >> Yeah. I find that the conversation this year is starting to unpack some of these cloud native embedded capabilities inside AWS. So are you guys doing more around, on the customer side, around marketplace? Are you guys, how do people consume products? >> Yeah. It's really both. So sometimes they come to us from AWS. AWS might say, "Hey, you know what," "we don't really have an answer." And that's specifically true on the expand side. They don't really have that in their list of databases yet. Right. Hopefully, we'll get out in front of them. But they oftentimes come through our front door where they're a MariaDB customer already, right? There's over a hundred thousand production systems with MariaDB in the world, and hundreds of thousands of users of the database. So they know our brand, not quite as well as AWS, but they know our brand... >> You've got a customer base. >> We do. Right. I mean people love MariaDB. They just think it's the database that they use for application development all the time. And when they see us release an offering like Xpand just a few years ago, they're interested, they want to use that. They want to see how that works. And then when they take it into production and it works as advertised, of course, success happens. Right? >> Well great stuff, John. Great to have you on theCUBE. Paul, I guess time we do the Insta challenge here. New format on theCUBE, we usually say at the end, summarize what's most important story for you or show, what's the bumper sticker? We kind of put it around more of an Instagram reel. What's your sizzle reel? What's your thought leadership statement? 30 seconds >> John: Thought leadership. >> John? >> So the thought leadership is really in scaling the cloud to the next generation. We believe MariaDB's Xpand product will be the the technology that fronts the next wave of database solutions in the cloud. And AWS has become instrumental in helping us do that with their infrastructure and all the help that they give us, I think at the end of the day, when the story on Xpand is written, it's going to be a very fun ride over the next few years. >> John, thank you. CRO, chief revenue officer of MariaDB, great to have you on. >> Thank you. >> 34-year veteran or so in databases. (laughs) >> You're putting a lot of age on me. I'm 29. I'm 29 again. (all laugh) >> I just graduated high school and I've been doing this for 10 years. Great to have you on theCUBE. Thanks for coming on. >> Thanks guys. Yeah. >> Thanks for sharing. >> Appreciate it. >> I'm John Furrier with Paul Gillin here live on the floor, wall-to-wall coverage. We're already into like 70 videos already. Got a whole another day, finish out day three. Keep watching theCUBE, thanks for watching. We'll be right back. (calm music)

>> Well, welcome back here to the Venetian. We're in Las Vegas. It is Wednesday, Day 2 of our coverage here of AWS re:Invent, 22. I'm your host, John Walls on theCUBE and it's a pleasure to welcome in two more guests as part of our AWS startup showcase, which is again part of the startup program globally at AWS. I've got Anant Verma, who is the Vice President of Engineering at Elation. Anant, good to see you, sir. >> Good to see you too. >> Good to be with us. And Haseeb Budhani, who is the CEO and co-founder of Rafay Systems. Good to see you, sir. >> Good to see you again. >> Thanks for having, yeah. A cuber, right? You've been on theCUBE? >> Once or twice. >> Many occasions. But a first timer here, as a matter of fact, glad to have you aboard. All right, tell us about Elation. First for those whom who might not be familiar with what you're up to these days, just give it a little 30,000 foot level. >> Sure, sure. So, yeah, Elation is a startup and a leader in the enterprise data intelligence space. That really includes a lot of different things including data search, data discovery, metadata management, data cataloging, data governance, data policy management, a lot of different things that companies want to do with the hoards of data that they have and Elation, our product is the answer to solve some of those problems. We've been doing pretty good. Elation is in running for about 10 years now. We are a series A startup now, we just raised around a few, a couple of months ago. We are already a hundred million plus in revenue. So. >> John: Not shabby. >> Yeah, it's a big benchmark for companies to, startup companies, to cross that milestone. So, yeah. >> And what's the relationship? I know Rafay and you have worked together, in fact, the two of you have, which I find interesting, you have a chance, you've been meeting on Zoom for a number of months, as many of us have it meeting here for the first time. But talk about that relationship with Rafay. >> Yeah, so I actually joined Elation in January and this is part of the move of Elation to a more cloud native solution. So, we have been running on AWS since last year and as part of making our solution more cloud native, we have been looking to containerize our services and run them on Kubernetes. So, that's the reason why I joined Elation in the first place to kind of make sure that this migration or move to a cloud native actually works out really well for us. This is a big move for the companies. A lot of companies that have done in the past, including, you know, Confluent or MongoDB, when they did that, they actually really reap great benefits out of that. So to do that, of course, you know, as we were looking at Kubernetes as a solution, I was personally more looking for a way to speed up things and get things out in production as fast as possible. And that's where I think, Janeb introduced us... >> That's right. >> Two of us. I think we share the same investor actually, so that's how we found each other. And yeah, it was a pretty simple decision in terms of, you know, getting the solution, figuring it out if it's useful for us and then of course, putting it out there. >> So you've hit the keyword, Kubernetes, right? And, so if you would to honestly jump in here, there are challenges, right? That you're trying to help them solve and you're working on the Kubernetes platform. So, you know, just talk about that and how that's influenced the work that the two of you are doing together. >> Absolutely. So, the business we're in is to help companies who adopt Kubernetes as an orchestration platform do it easier, faster. It's a simple story, right? Everybody is using Kubernetes, but it turns out that Kubernetes is actually not that easy to to operationalize, playing in a sandbox is one thing. Operationalizing this at a certain level of scale is not easy. Now, we have a lot of enterprise customers who are deploying their own applications on Kubernetes, and we've had many, many of them. But when it comes to a company like Elation, it's a more complicated problem set because they're taking a very complex application, their application, but then they're providing that as a service to their customers. So then we have a chain of customers we have to make happy. Anant's team, the platform organization, his internal customers who are the developers who are deploying applications, and then, the company has customers, we have to make sure that they get a good experience as they consume this application that happens to be running on Kubernetes. So that presented a really interesting challenge, right? How do we make this partnership successful? So I will say that, we've learned a lot from each other, right? And, end of the day, the goal is, my customer, Anant's specifically, right? He has to feel that, this investment, 'cause he has to pay us money, we would like to get paid. >> John: Sure. (John laughs) >> It reduces his internal expenditure because otherwise he'd have to do it himself. And most importantly, it's not the money part, it's that he can get to a certain goalpost significantly faster because the invention time for Kubernetes management, the platform that you have to build to run Kubernetes is a very complex exercise. It took us four and a half years to get here. You want to do that again, as a company, right? Why? Why do you want to do that? We, as Rafay, the way I think about what we deliver, yes, we sell a product, but to what end? The product is the what, the why, is that every enterprise, every ISV is building a Kubernetes platform in house. They shouldn't, they shouldn't need to. They should be able to consume that as a service. They consume the Kubernetes engine the EKS is Amazon's Kubernetes, they consume that as an engine. But the management layer was a gap in the market. How do I operationalize Kubernetes? And what we are doing is we're going to, you know, the Anant said. So the warden saying, "Hey you, your team is technical, you understand the problem set. Would you like to build it or would you rather consume this as a service so you can go faster?" And, resoundingly the answer is, I don't want to do this anymore. I wouldn't allow to buy. >> Well, you know, as Haseeb is saying, speed is again, when we started talking, it only took us like a couple of months to figure out if Rafay is the right solution for us. And so we ended up purchasing Rafay in April. We launched our product based on Rafay in Kubernetes, in EKS in August. >> August. >> So that's about four months. I've done some things like this before. It takes a couple of years just to sort of figure out, how do you really work with Kubernetes, right? In a production at a large scale. Right now, we are running about a 600 node cluster on Rafay and that's serving our customers. Like, one of the biggest thing that's actually happening on December 8th is we are running what we call a virtual hands on lab. >> A virtual? >> Hands on lab. >> Okay. >> For Elation. And they're probably going to be about 500 people is going to be attending it. It's like a webinar style. But what we do in that hands on lab is we will spin up an Elation instance for each attendee, right on the spot. Okay? Now, think about this enterprise software running and people just sign up for it and it's there for you, right on the spot. And that's the beauty of the software that we have been building. There's the beauty of the work that Rafay has helped us to do over the last few months. >> Okay. >> I think we need to charge them more money, I'm getting from this congregation. I'm going to go work on that. >> I'm going to let the two of you work that out later. All right. I don't want to get in the way of a big deal. But you mentioned that, we heard about it earlier that, it's you that would offer to your cert, to your clients, these services. I assume they have their different levels of tolerance and their different challenges, right? They've got their own complexities and their own organizational barriers. So how are you juggling that end of it? Because you're kind of learning as, well, not learning, but you're experiencing some of the thing. >> Right. Same things. And yet you've got this other client base that has a multitude of experiences that they're going through. >> Right. So I think, you know a lot of our customers, they are large enterprise companies. They got a whole bunch of data that they want work with us. So one of the thing that we have learned over the past few years is that we used to actually ship our software to the customers and then they would manage it for their privacy security reasons. But now, since we're running in the cloud, they're really happy about that because they don't need to juggle with the infrastructure and the software management and upgrades and things like that, we do it for them, right? And, that's the speed for them because now they are only interested in solving the problems with the data that they're working with. They don't need to deal with all these software management issues, right? So that frees our customers up to do the thing that they want to do. Of course it makes our job harder and I'm sure in turn it makes his job harder. >> We get a short end of the stick, for sure. >> That's why he is going to get more money. >> Exactly. >> Yeah, this is a great conversation. >> No, no, no. We'll talk about that. >> So, let's talk about the cloud then. How, in terms of being the platform where all this is happening and AWS, about your relationship with them as part of the startup program and what kind of value that brings to you, what does that do for you when you go out and are looking for work and what kind of cache that brings to you >> Talk about the AWS? >> Yes, sir. >> Okay. Well, so, the thing is really like of course AWS, a lot of programs in terms of making sure that as we move our customers into AWS, they can give us some, I wouldn't call it discount, but there's some credits that you can get as you move your workloads onto AWS. So that's a really great program. Our customers love it. They want us to do more things with AWS. It's a pretty seamless way for us to, as we were talking about or thinking about moving into the cloud, AWS was our number one choice and that's the only cloud that we are in, today. We're not going to go to any other place. >> That's it. >> Yeah. >> How would you characterize? I mean, we've already heard, from one side of the fence here, but. >> Absolutely. So for us, AWS is a make or break partner, frankly. As the EKS team knows very well, we support Azure's Kubernetes and Google's Kubernetes and the community Kubernetes as well. But the number of customers on our platform who are AWS native, either a hundred percent or a large percentage is, you know, that's the majority of our customer base. >> John: Yeah. >> And AWS has made it very easy for us in a variety of ways to make us successful and our customers successful. So Anant mentioned the credit program they have which is very useful 'cause we can, you know, readily kind of bring a customer to try things out and they can do that at no cost, right? So they can spin up infrastructure, play with things and AWS will cover the cost, as one example. So that's a really good thing. Beyond that, there are multiple programs at AWS, ISV accelerate, et cetera. That, you know, you got to over time, you kind of keep getting taller and taller. And you keep getting on bigger and bigger. And as you make progress, what I'm finding is that there's a great ecosystem of support that they provide us. They introduce us to customers, they help us, you know, think through architecture issues. We get access to their roadmap. We work very, very closely with the guest team, for example. Like the, the GM for Kubernetes at AWS is a gentleman named Barry Cooks who was my sponsor, right? So, we spend a lot of time together. In fact, right after this, I'm going to be spending time with him because look, they take us seriously as a partner. They spend time with us because end of the day, they understand that if they make their partners, in this case, Rafay successful, at the end of the day helps the customer, right? Anant's customer, my customer, their AWS customers, also. So they benefit because we are collectively helping them solve a problem faster. The goal of the cloud is to help people modernize, right? Reduce operational costs because data centers are expensive, right? But then if these complex solutions this is an enterprise product, Kubernetes, at the enterprise level is a complex problem. If we don't collectively work together to save the customer effort, essentially, right? Reduce their TCO for whatever it is they're doing, right? Then the cost of the cloud is too high. And AWS clearly understands and appreciates that and that's why they are going out of their air, frankly, to make us successful and make other companies successful in the startup program. >> Well. >> I would just add a couple of things there. Yeah, so, you know, cloud is not new. It's been there for a while. You know, people used to build things on their own. And so what AWS has really done is they have advanced technology enough where everything is really simple as just turning on a switch and using it, right? So, just a recent example, and I, by the way, I love managed services, right? So the reason is really because I don't need to put my own people to build and manage those things, right? So, if you want to use a search, they got the open search, if you want to use caching, they got elastic caching and stuff like that. So it's really simple and easy to just pick and choose which services you want to use and they're ready to be consumed right away. And that's the beautiful, and that that's how we can move really fast and get things done. >> Ease of use, right? Efficiency, saving money. It's a winning combination. Thanks for sharing this story, appreciate. Anant, Haseeb thanks for being with us. >> Yeah, thank you so much having us. >> We appreciate it. >> Thank you so much. >> You have been a part of the global startup program at AWS and startup showcase. Proud to feature this great collaboration. I'm John Walls. You're watching theCUBE, which is of course the leader in high tech coverage.

(upbeat music playing) >> Hey, all you cool cats and kittens, and welcome back to AWS re:Invent. We are live from the show floor, here in fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by my co-host Paul Gillian. Paul, how you doing? We're now full blown into your first day of AWS re:Invent ever. >> Overwhelmed. >> Overwhelmed! >> Drinking from the fire hose. There's so much going on here. >> Yeah. There really is, isn't there? Anything stood out to you in that fire hose? >> I think the importance of data, hearing about a lot of tools here, a lot of talk about how organizations need to take advantage of the cloud to leverage their data more effectively, that's clearly a theme in the show. Hearing a lot about vertical industries and the move of the cloud into more verticalization which we're going to be talking about here with our next guest, among other things. Monty Bhatia, who's the Vice President of Global Systems Integrators at VMware, a company that really pioneered partnerships with AWS, as well as other cloud providers. And also Ranjit Bawa, the principal, US cloud leader for Deloitte, a company that has been a leader in vertical clouds as well as in cloudefying its customers, if you will. Welcome, thank you both for joining us. >> Thank you very much. >> Thank you for having us. >> We're happy to be here. >> Monty, I just have to say, I know I said it before, I think you might be the best dressed. >> You know, you may have to say it again. I've got to record this and show it to my wife, because she always says that I should wear age appropriate colors, and she thinks yellow and hot pinks are not age appropriate. So I've made a deal with her that when I'm traveling, and everybody else has heard the story, when I'm traveling and she's not around I can wear any colors I want. It is an attention grabber, it is a conversation starter, and I love it. >> I'm all for the talk trigger and you told me you have 32 different sets. >> That's right. >> And you're branded, right? Give us a little lapel peak. >> I am branded. (Monty and Ranjit chuckling) >> Brilliant. We don't always do a fashion segment to open each clip but I just, I couldn't let this pass, Monty- >> Thank you, I appreciate that. >> You're just absolutely, absolutely smashing it. Deloitte and VMware, you've got a unique strategic partnership. Ranjit can you tell me a little bit about that? >> Yeah, absolutely. We've been working together for close to a decade now with VMware. >> Nice. In Techland that might as well be a century. >> That's right. >> It is. (Savannah chuckling) >> And we've had a number of very successful large scale transformations across industries together, particularly as our clients are moving to cloud, which really in our world is a metaphor for modern engineering, modern technology, how tech shows up differently to support the business. So we're really excited about what we've done and where we are going together. >> I want to ask you about the transition that we see going on at AWS really going from being an infrastructure to provider to more of a platform provider for vertical applications for HPC, for AI, for specific uses. Is this a transition that you see your customers- are they applauding this transition? >> Yeah, most certainly, and we saw this coming a while ago, and as does AWS and VMware and others, that for more horizontal clouds we're going to start to move into vertical clouds that support industries and sectors and sub-sectors. So increasingly as we move from IIS to more PaaS and even into SaaS land, that is going to continue. The good news is that AWS has formed a really good foundation and a set of common frameworks that people can use to build upon. And then with VMware as well, we've started to build these vertical clouds and insurance and life sciences and healthcare and all kinds of other sectors, including manufacturing and you know, in our booth here, we have a demo of our manufacturing vertical clouds as well. So we certainly see that the direction of travel and our clients are really egging us on as well. >> So what is VMware's role in building these vertical clouds? Because you're not a vertical, I don't think of you as being a vertical services provider. >> Yeah, so from a VMware standpoint, we're going through a transition ourselves, right? It's a transformation happening at VMware. And while we are traditionally an infrastructure we're a plumbing company, right? We are, we provide all the horizontal space, that's where we need the partnership. So we do have some capability built around industries but that's where our partnership with Deloitte is very important to us because they have all these industry clouds. We have the tech platform that provides that. And then when partnering three way partnerships with you know, hyperscalers like AWS you know we can bring the scale and everything together to serve our customers. So it's very important for us to make use of our technology stack. We have customers in all industries, right? We have huge customer base, and we have customers in all industries, right? And so we want to really create that industry angle, working with our partners like Deloitte to serve those customers and working with, you know, our ecosystem partners ISV partners, hyperscaler partners. Obviously AWS is a big partner of ours and want to bring it all together to serve our customers you know, their journeys, basically. >> Let's hang out there for a second because you you see, you both see extraordinarily large customers across different verticals and industries. Talk about some of the trends that you might be seeing that transcend across all of them. Ranjit, we'll start with you. >> Yeah, it's a great question. You know, certainly more, you know, sort of fundamentally, we see this as a huge opportunity this decade. Many folks that I work with call this the roaring twenties all over again. You know, hopefully it won't end the same way as the last one. But in many ways, every client of ours, across every industry, is going through a huge disruption as they're thinking about the businesses they're in, the products they serve, the segments they support, the client demographics that are changing. So that's one big mega sort of trend. The other one is the rate of change. I think most everybody's dealing with the rate of change of technology, right? You come here last year and this year there are a thousand new services. Every day they release five or seven more and every other, you know, technology provider out there as well. So our clients in general are struggling with how do they embrace and adopt this change quickly. >> Right. >> And today they're not set up for that, right? >> Decision overload too, so much. >> Absolutely. >> That one, and then their ability to be able to absorb this change, right? A typical client of ours, enterprise client, has a three to four year journey to embrace new technology. That's the refresh cycle. But now we see that half life going down to three months and six months. So large part of this transformation is how do you build that muscle to be able to deal with this change that's only going to continue to accelerate. So not only are we helping them think about new products and new businesses, but also how to build this muscle and fundamentally change the way they deliver technology. And that's, I think also a place where our partnership is really valuable. >> It's like your sprint muscles versus your marathon muscles, you know? >> Right. >> You're totally fast, which is an entirely different set. >> Exactly right. >> What about you Monty? >> Yeah, and so from a technology standpoint, also one of the biggest trends that we are seeing, you know, two years ago when you looked at it, you know it was all about hyperscaler, public cloud, cloud first. Now we're seeing more of a multicloud approach, right? We're seeing that pull back in towards hybrid cloud. I know John talks about the- >> The Super cloud. >> The Super cloud, right? >> Yes, one of our favorite- >> I know Deloitte talks about Meta cloud, we talk about cross cloud services. So that's a trend that's coming up. And, and you know, we're, from a VM VMware standpoint we're very well positioned in the multicloud space, you know, our partnership with other hyperscalers, actually all cloud providers and then our partnerships with, you know, system integrators like Deloitte, it is really helping us propel, you know that solution to our customers. And so that's a big trend we're seeing around the multicloud and the modern application space. >> How, I mean the multicloud issue seem to be very hot a couple of years ago to die down, at least with, you know, the amount of coverage that's afforded to it. Is that because customers are less interested in multiple clouds or is it because that's become simply part of the landscape? >> Yeah, well, you know, I think it's there was a recent study done that over 70% of the enterprise customers are inherently multicloud, right? And multicloud just doesn't meet the hyperscalers, right? We take multicloud as the hyperscalers the private cloud, the edge cloud, the industry cloud. They've got data all over the place, right? So inherently, most enterprises are multicloud. They're realizing it now that the, when they're lock-in is an issue with them. And so, you know, over 70% of the hundred customers are actually looking at building that orchestration layer on top of the clouds which can provide them a, you know, a more meaningful and simplified decision making for their cloud workloads. >> And maybe to add to that, John, I think your point about the fascination with multicloud four or five years ago and how that tapered off I think the use case people were solving for back then was to have three different cloud options for the same workload. That they could swap between those three, maybe they could arbitrage on cost, et cetera. That in our view is a fool's errand because it's just the you know, the juice isn't worth the squeeze. But what we are seeing now is for different workloads you want to give people optionality. So you an edge computing workload you're serving a restaurant, you need that to run on a different cloud provider because they have better analytics the better geospatial data, that's fine. But your main core application, we run on a different cloud. So you're still supporting multicloud but you're not confusing the same workload to be trying to run them on multiple clouds at the same time or things of that nature. So I think that's where it's kind of moving towards. >> So I, we've talked a lot about big partnerships. One of the exciting trends at the show is all the new collaboration that's happening. I love that you've been partners for a decade. It shows a long term commitment to the community. If I'm an AWS customer who has not yet taken advantage of your fabulous partnership, what is it about it that makes it so magic? Give me a little bit of the pitch. >> So.. >> Go for it, Monty. You're rolling, I like it. (Monty chuckling) Let's go with it. >> Right. So I think for an AWS customer, so we have, VMware has an offering that we built with AWS VMC on AWS right? I think there is a real value in it. There are specific use cases that create a financial benefit an operational benefit for the customers, right? We've traditionally not done a great job of elevating that message. And that's our goal, right? That's our goal is to make sure that the VMC on AWS offering, it's not a competitive offering to AWS, it's actually a complimentary offering. It helps everybody, it helps the customer, it helps VMware it helps AWS in bringing all these pieces together to solve the customer problems. There are certain use cases that are really good for moving to a native cloud like AWS. There are definitely use cases, there are financial advantages, operational advantages that the customers will get out of doing the VMC on AWS offering. And again, our partnerships with our, you know, most strategic partners, who are bringing the industry expertise on top of it will even accelerate that even faster. >> I know you're not at liberty to talking at length about the Broadcom acquisition but can you offer our listeners any insight into what will be continued, what Broadcom's approach or attitude toward the partnerships that you've already built and how strong those are, how committed they are to continuing them. >> You know, there's things we can share, there's things we cannot share and I'll let Ranjit talk about it, but from our standpoint, I think, you know, know what Broadcom has openly stated, we'll say that again, right? They are looking at this as a very strategic acquisition. From their standpoint, they've made it clear that multicloud and modern applications are two of the big strategic initiatives they want to continue. They've also stated openly that, you know, in order for us to scale, we still need these partnerships. And so the partnerships and the ecosystem that VMware has built, you know, it's going to be looked upon as, you know, something they'll continue to do for at least for the near future. You know, what's going to happen in future, we don't know. But in the near future, they don't want to disrupt the partnership, the channel programs that we've already built, you know? And that's very important to us because that's one of our biggest go-to market routes through the partners. >> And most importantly, that logo isn't changing. So you get to wear all of your- >> Well, yes, I was worried if they change the logo then I have to reorder my T-shirts again. But now, you know, we're good for now. (Monty chuckling) >> We're good for now. You both are such wonderfully seasoned veterans so you don't look it like we talked about earlier, but both of you with 20 plus years of experience in the industry. We're doing a new thing on theCUBE this show, where we're looking for your 30 second hot take. Think of it as your thought leadership sizzle reel. What is the most important story or theme coming out of this year's show? I'll see who looks most ready. Monty looks ready. All right, let's go. >> Well, you know, I, you know, one of the things that I've seen, and I've been coming to re:Invents for quite some time you know, this is my sixth re:Ivent, but I really like the ecosystem story that is now building, right? It used to be from an Amazon standpoint, it used to be always customer obsession, which is still there, but they've added partner obsession now, right? And that's a new thing. That means now they are focusing on the ecosystem, just like we are focusing, just like Deloitte is focusing on ecosystem and that to me is a trend worth talking about. >> I love that. And very holistic and very astute. All right, Ranjit, what about you? >> Well, first I love the energy. It almost feels like there was no pandemic, right? So that's a good reminder- >> We're all ready for that feeling- >> and hopefully we're world beyond what we've been through. I also think, you know to that point, there's a lot more focus on ecosystem plays that move beyond just the less lift and shift with the cloud. But let's be thoughtful about changing the way you serve your clients, the capabilities you want to deliver. And a lot of that is through the ecosystem around client problems and working backwards from clients I think is also amazing. >> Yeah. >> And finally, I'm also always energized by the the team that's here or the folks that are here. I think it's become more pervasive, you know, earlier on it was more CIOs and, you know, senior execs. I think we're seeing a lot more across the organization, which is a great way to drive adoption and things. >> Really beautiful point. I love that. The diversity here is definitely noticeable. This is a cheeky thing to say live, but I noticed this is probably the first tech conference I've ever been to as a woman where I, there was actually a line for the restroom. Normally we're straight in at these and it's a silly thing. Yeah, now at breaks I have to allow a little extra time, but it was one of those moments where I very much noticed it earlier today and had to text to know I was going to be a little later back to the set, but I think it- I'm glad you brought that up cuz this community is special, it's inclusive, it's collaborative, it's massive companies as well as tiny startups from all over the world. It's very exciting. I really enjoyed talking with both of you. I hope we get to have you back on the show. It was fun. It was fashionable. Ranjit, Monty, thank you both so much for bringing your energy and your thoughts >> We'd love to come back. Yes, we'd love to come back in hot pink next time and talk about. >> I mean, the Deloitte consultants usually know how to thread up but (Savannah chuckling) >> I know. I'm seriously overshadowed >> And I'm wearing my neons next time. I wear a very brave pink. So generally speaking, although the sequence were- We'll definitely do it. Thank you so much for being here, and thank all of you for tuning in for our continuous live coverage here from AWS re:Invent in Las Vegas in Nevada. My name is Savannah Peterson with Paul Gillian. We are theCUBE and we are the source for leading and spicy, zesty, fashionable tech coverage. (upbeat music playing)

(upbeat music) >> It's theCUBE live in Las Vegas, covering AWS re:Invent 2022. This is the first full day of coverage. We will be here tomorrow and Thursday but we started last night. So hopefully you've caught some of those interviews. Lisa Martin here in Vegas with Paul Gillin. Paul, it's great to be back. We just saw a tweet from a very reliable source saying that there are upwards of 70,000 people here at rei:Invent '22 >> I think there's 70,000 people just in that aisle right there. >> I think so. It's been great so far we've gotten, what are some of the things that you have been excited about today? >> Data, I just see data everywhere, which very much relates to our next guest. Companies realizing the value of data and the strategic value of data, beginning to treat it as an asset rather than just exhaust. I see a lot of focus on app development here and building scalable applications now. Developers have to get over that, have to sort of reorient themselves toward building around the set of cloud native primitives which I think we'll see some amazing applications come out of that. >> Absolutely, we will. We're pleased to welcome back one of our alumni to the program. Shinji Kim joins us, the CEO and founder of Select Star. Welcome back Shinji. It's great to have you. >> Thanks Lisa, great to be back. >> So for the audience who may not know much about Select Star before we start digging into all of the good stuff give us a little overview about what the company does and what differentiates you. >> Sure, so Select Star is an automated data discovery platform. We act like it's Google for data scientists, data analysts and data engineers to help find and understand their data better. Lot of companies today, like what you mentioned, Paul, have 100s and 1000s of database tables now swimming through large volumes of data and variety of data today and it's getting harder and harder for people that wants to utilize data make decisions around data and analyze data to truly have the full context of where this data came from, who do you think that's inside the company or what other analysis might have been done? So Select Star's role in this case is we connect different data warehouses BI tools, wherever the data is actually being used inside the company, bringing out all the usage analytics and the pipeline and the models in one place so anyone can search through what's available and how the data has been created, used and being analyzed within the company. So that's why we call it it's kind of like your Google for data. >> What are some of the biggest challenges to doing that? I mean you've got data squirreled away in lots of corners of the organization, Excel spreadsheets, thumb drives, cloud storage accounts. How granular do you get and what's the difficulty of finding all this data? >> So today we focus primarily on lot of cloud data warehouses and data lakes. So this includes data warehouses like Redshift, Snowflake (indistinct), Databricks, S3 buckets, where a lot of the data from different sources are arriving. Because this is a one area where a lot of analysis are now being done. This is a place where you can join other data sets within the same infrastructural umbrella. And so that is one portion that we always integrate with. The other part that we also integrate a lot with are the BI tools. So whether that's (indistinct) where you are running analysis, building reports, and dashboards. We will pull out how those are, which analysis has been done and which business stakeholders are consuming that data through those tools. So you also mentioned about the differentiation. I would say one of the biggest differentiation that we have in the market today is that we are more in the cloud. So it's very cloud native, fully managed SaaS service and it's really focused on user experience of how easily anyone can really search and understand data through Select Star. In the past, data catalogs as a sector has been primarily focused on inventorizing all your enterprise data which are in many disciplinary forces. So it was more focused on technical aspect of the metadata. At the same time now this enterprise data catalog is important and is needed for even smaller companies because they are dealing with ton of data. Another part that we also see is more of democratization of data. Many different types of users are utilizing data whether they are fully technical or not. So we had basically emphasis around how to make our user interface as intuitive as possible for business users or non-technical users but also bring out as much context as possible from the metadata and the laws that we have access to, to bring out these insights for our customers. >> Got it. What was the impetus or the catalyst to launch the business just a couple of years ago? >> Yeah, so prior to this I had another data startup called Concord Systems. We focused on distributed stream processing framework. I sold the company to Akamai which is now called ... and the product is now called IoT Edge Connect. Through Akamai I started working with a lot of enterprises in automotive and consumer electronics and this is where I saw lot of the issues starting to happen when enterprises are starting to try to use the data. Collection of data, storage of data, processing of data with the help of lot of cloud providers, scaling that is not going to be a challenge as much anymore. At the same time now lot of enterprises, what I realized is a lot of enterprises were sitting on top of ton of data that they may not know how to utilize it or know even how to give the access to because they are not 100% sure what's really inside. And more and more companies, as they are building up their cloud data warehouse infrastructure they're starting to run into the same issue. So this is a part that I felt like was missing gap in the market that I wanted to fulfill and that's why I started the company. >> I'm fascinated with some of the mechanics of doing that. In March of 2020 when lockdowns were happening worldwide you're starting new a company, you have to get funding, you have to hire people, you don't have a team in place presumably. So you have to build that as free to core. How did you do all that? (Shinji laughs) >> Yeah, that was definitely a lot of work just starting from scratch. But I've been brewing this idea, I would say three four months prior. I had a few other ideas. Basically after Akamai I took some time off and then when I decided I wanted to start another company there were a number of ideas that I was toying around with. And so late 2019 I was talking to a lot of different potential customers and users to learn a little bit more about whether my hypothesis around data discovery was true or not. And that kind of led into starting to build prototypes and designs and showing them around to see if there is an interest. So it's only after all those validations and conversations in place that I truly decided that I was going to start another company and it just happened to be at the timing of end of February, early March. So that's kind of how it happened. At the same time, I'm very lucky that I was able to have had number of investors that I kept in touch with and I kept them posted on how this process was going and that's why I think during the pandemic it was definitely not an easy thing to raise our initial seed round but we were able to close it and then move on to really start building the product in 2020. >> Now you were also entering a market that's there's quite a few competitors already in that market. What has been your strategy for getting a foot in the door, getting some name recognition for your company other than being on the queue? >> Yes, this is certainly part of it. So I think there are a few things. One is when I was doing my market research and even today there are a lot of customers out there looking for an easier, faster, time to value solution. >> Yes. >> In the market. Today, existing players and legacy players have a whole suite of platform. However, the implementation time for those platforms take six months or longer and they don't necessarily are built for lot of users to use. They are built for database administrators or more technical people to use so that they end up finding their data governance project not necessarily succeeding or getting as much value out of it as they were hoping for. So this is an area that we really try to fill the gaps in because for us from day one you will be able to see all the usage analysis, how your data models look like, and the analysis right up front. And this is one part that a lot of our customers really like and also some of those customers have moved from the legacy players to Select Star's floor. >> Interesting, so you're actually taking business from some of the legacy guys and girls that may not be able to move as fast and quickly as you can. But I'd love to hear, every company these days has to be a data company, whether it's a grocery store or obviously a bank or a car dealership, there's no choice anymore. As consumers, we have this expectation that we're going to be able to get what we want, self-service. So these companies have to figure out where all the data is, what's the insides, what does it say, how can they act on that quickly? And that's a big challenge to enable organizations to be able to see what it is that they have, where's the value, where's the liability as well. Give me a favorite customer story example that you think really highlights the value of what Select Star is delivering. >> Sure, so one customer that we helped and have been working with closely is Pitney Bowes. It's one of the oldest companies, 100 year old company in logistics and manufacturing. They have ton of IoT data they collect from parcels and all the tracking and all the manufacturing that they run. They have recently, I would say a couple years ago moved to a cloud data warehouse. And this is where their challenge around managing data have really started because they have many different teams accessing the data warehouses but maybe different teams creating different things that might have been created before and it's not clear to the other teams and there is no single source of truth that they could manage. So for them, as they were starting to look into implementing data mesh architecture they adopted Select Star. And they have a, as being a very large and also mature company they have considered a lot of other legacy solutions in the market as well. But they decided to give it a try with select Star mainly because all of the automated version of data modeling and the documentation that we were able to provide upfront. And with all that, with the implementation of Select Star now they claim that they save more than 30 hours a month of every person that they have in the data management team. And we have a case study about that. So this is like one place where we see it save a lot of time for the data team as well as all the consumers that data teams serve. >> I have to ask you this as a successful woman in technology, a field that has not been very inviting to women over the years, what do you think this industry has to do better in terms of bringing along girls and young women, particularly in secondary school to encourage them to pursue careers in science and technology? >> Like what could they do better? >> What could this industry do? What is this industry, these 70,000 people here need to do better? Of which maybe 15% are female. >> Yeah, so actually I do see a lot more women and minority in data analytics field which is always great to see, also like bridging the gap between technology and the business point of view. If anything as a takeaway I feel like just making more opportunities for everyone to participate is always great. I feel like there has been, or you know just like being in the industry, a lot of people tends to congregate with people that they know or more closed groups but having more inclusive open groups that is inviting regardless of the level or gender I think is definitely something that needs to be encouraged more just overall in the industry. >> I agree. I think the inclusivity is so important but it also needs to be intentional. We've done a lot of chatting with women in tech lately and we've been talking about this very topic and that they all talk about the inclusivity, diversity, equity but it needs to be intentional by companies to be able to do that. >> Right, and I think in a way if you were to put it as like women in tech then I feel like that's also making it more explosive. I think it's better when it's focused on the industry problem or like the subject matter, but then intentionally inviting more women and minority to participate so that there's more exchange with more diverse attendees in the AWS. >> That's a great point and I hope to your 0.1 day that we're able to get there, but we don't have to call out women in tech but it is just so much more even playing field. And I hope like you that we're on our way to doing that but it's amazing that Paul brought up that you started the company during the pandemic. Also as a female founder getting funding is incredibly difficult. So kudos to you. >> Thank you. >> For all the successes that you've had. Tell us what's next for Select Star before we get to that last question. >> Yeah, we have a lot of exciting features that have been recently released and also coming up. First and foremost we have an auto documentation feature that we recently released. We have a fairly sophisticated data lineage function that parses through activity log and sequel queries to give you what the data pipeline models look like. This allows you to tell what is the dependency of different tables and dashboards so you can plan what your migration or any changes that might happen in the data warehouse so that nothing breaks whenever these changes happen. We went one step further to that to understand how the data replication actually happens and based on that we are now able to detect which are the duplicated data sets and how each different field might have changed their data values. And if the data actually stays the same then we can also propagate the same documentation as well as tagging. So this is particularly useful if you are doing like a PII tagging, you just mark one thing once and based on the data model we will also have the rest of the PII that it's associated with. So that's one part. The second part is more on the security and data governance front. So we are really seeing policy based access control where you can define who can see what data in the catalog based on their team tags and how you want to define the model. So this allows more enterprises to be able to have different teams to work together. And last one at least we have more integrations that we are releasing. We have an upgraded integration now with Redshift so that there's an easy cloud formation template to get it set up, but we now have not added Databricks, and power BI as well. So there are lots of stuff coming up. >> Man, you have accomplished a lot in two and a half years Shinji, my goodness! Last question for you, describing Select Star in a bumper sticker, what would that bumper sticker say? >> So this is on our website, but yes, automated data catalog in 15 minutes would be what I would call. >> 15 minutes. That's awesome. Thank you so much for joining us back on the program reintroducing our audience to Select Star. And again, congratulations on the successes that you've had. You have to come back because what you're creating is a flywheel and I can't wait to see where it goes. >> Awesome, thanks so much for having me here. >> Oh, our pleasure. Shinji Kim and Paul Gillin, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

>>Hey everyone, and welcome back to The Cube's live coverage of AWS Reinvented 2022 Live from the Venetian Expo in Las Vegas. We're happy to be back. This is first full day of coverage over here last night. We've got three full days of coverage in addition to last night, and there's about 50,000 people here. This event is ready, people are ready to be back, which is so exciting. Lisa Martin here with Paul Gill and Paul, it's great to be back in person. Great to be hosting with you >>And likewise with you, Lisa. I think the first time we hosted again, >>It is our first time exactly. >>And we come here to the biggest event that the cube ever does during the year. >>It's the Super Bowl of the >>Cube. It's it's elbow to elbow out there. It's, it's, it's full tackle football, totally on the, on the floor of reinvent. And very exciting. This, you know, I've been to a lot of conferences going back 40 years, long as I can remember. Been going to tech conferences. This one, the, the intensity, the excitement around this is really unusual. People are jazzed, they're excited to be here, and that's great to see, particularly coming back from two years of isolation. >>Absolutely. The energy is so palpable. Even yesterday, evening, afternoon when I was walking in, you just feel it with all the people here. You know, we talk to so many different companies on the Q Paul. Every company these days has to be a data company. The most important thing about data is making sure that it's backed up and it's protected, that it's secure, that it can be recovered if anything happens. So we're gonna be having a great conversation next about data resiliency with one of our alumni. >>And that would be Rick Scott, Rick, excuse me, Rick Scott, >>Rick Clark. Rick Clark, say Rick Scott, cloud sales Veritas. Rick, welcome back >>To the program. Thank you. Thank you so much. It's a pleasure being here, you know, thank you so much. You're definitely very excited to myself and 40,000 of my closest cousins and friends all in one place. Yep. Or I could possibly go wrong, right? So >>Yeah, absolutely nothing. So, Rick, so Veritas has made some exciting announcements. Talk to us about some of the new things that you've >>Unveiled. Yeah, we've been, we've been incredibly busy and, you know, the journey that we've been on, one of the big announcement that we made about three or four weeks ago is the introduction, really, of a brand new cloud native data management platform that we call Veritas Alta. And this is a journey that we've been on for the better part of seven years. We actually started it with our, our flex appliances. We continued, that was a containerization of our traditional net backup business in, into a highly secured appliance that was loved by our customers. And we continued that theme and that investment into what we call a scale out and scale up form factor appliance as well, what we called flex scale. And then we continued on that investment theme, basically spending over a billion dollars over that seven year journey in our cloud native. And we call that basically the Veritas altar platform with our cloud native platform. And I think if you really look at what that is, it truly is a data management platform. And I emphasize the term cloud native. And so our traditional technologies around data protection, obviously application resiliency and digital compliance or data compliance and governance. We are the only, the first and only company in the world to provide really a cloud optimized, cloud native platform, really, that addresses that. So it's been fun, it's been a fun journey. >>Talk a little bit about the customer experience. I see over 85% of the Fortune 100 trust Veritas with their data management. That's >>A big number. Yeah. Yeah. It's, it is incredible actually. And it really comes back to the Veritas older platform. We sort of built that with, with four tenants in mind, all driving back to this very similar to AWS's customer obsession. Everything we do each and every day of our waiting moments is a Veritas employee is really surrounds the customer. So it starts with the customer experience on how do they find us to, how do they procure our solutions through things like AWS marketplace and how do they deploy it? And the second thing is around really cost optimization, as we know, you know, to, to say that companies are going through a digital transformation and moving workloads to the cloud. I mean, I've got customers that literally were 20% in cloud a year ago and 80% a year later, we've never seen that kind of velocity. >>And so we've doubled down on this notion of cost optimization. You can only do that with these huge investments that I talked about. And so we're a very profitable company. We've been around, got a great heritage of over 30 years, and we've really taken those investments in r and d to provide that sort of cloud native technology to ultimately make it elastic. And so everything from will spin up and spin down services to optimize the cloud bill for our customers, but we'll also provide the greatest workload support. You know, obviously on-prem workloads are very different from cloud workloads and it's almost like turning the clock back 20 years to see all of those new systems. There's no standard API like s and MP on the network. And so we have to talk to every single PAs service, every single DB PAs, and we capture that information and protect it. So it's really has been a phenomenal journey. It's been great. >>You said this, that that al represents a shift from clouds from flex scale to cloud native. What is the difference there? >>The, the main difference really is we took, you know, obviously our traditional product that you've known for many media years, net backup. It's got, you know, tens of millions of lines of code in that. And we knew if we lifted and shifted it up into the cloud, into an I AEs infrastructure, it's just not, it obviously would perform extremely well, but it wasn't cost optimized for our customer. It was too expensive to to run. And so what we did is we rewrote with microservices and containerization, Kubernetes huge parts of that particular product to really optimize it for the cloud. And not only have we done it for that technology, what we now call alter data protection, but we've done it across our entire port portfolio. That was really the main change that we made as part of this particular transition. And >>What have you done to prepare customers for that shift? Is this gonna be a, a drop in simple upgrade for them? >>Absolutely. Yeah. In fact, one of the things that we introduced is we, we invest still very heavily with regards to our OnPrem solutions. We're certainly not abandoning, we're still innovating. There's a lot of data still OnPrem that needs to move to the cloud. And so we have a unique advantage of all of the different workload supports that we provide OnPrem. We continue that expansion into the cloud. So we, we create it as part of the Veritas AL Vision, a technology, we call it AL view. So it's a single painter glass across both OnPrem and cloud for our customers. And so now they can actually see all of their data protection, all our application availability, single collect, all through that single unified interface, which is really game changing in the industry for us. >>It's game changing for customers too, because customers have what generally six to seven different backup technologies in their environment that they're having to individually manage and provision. So the, the workforce productivity improvements I can imagine are, are huge with Veritas. >>Yeah. You you nailed it, right? You must have seen my script, but Absolutely. I mean, I look at the analogy of, you think about the airlines, what's one of the first things airlines do with efficiency? South Southwest Airlines was the best example, a standardized on the 7 37, right? And so all of their pilots, all of their mechanics, all know how to operate the 7 37. So we are doing the same thing with enterprise data protection. So whether you're OnPrem at the edge or in the cloud or even multi-cloud, we can provide that single painter glass. We've done it for our customers for 30 plus years. We'll continue to do it for another 30 something years. And so it's really the first time with Veritas altar that, that we're, we're coming out with something that we've invested for so long and put, put such a huge investment on that can create those changes and that compelling solution for our customers. So as you can see, we're pretty pumped and excited about it. >>Yes, I can >>Use the term data management to describe Alta, and I want to ask about that term because I hear it a lot these days. Data management used to be database, now data management is being applied to all kinds of different functions across the spectrum. How do you define data management in Veritas >>Perspective? Yeah, there's a, we, we see it as really three main pillars across the environment. So one is protection, and we'll talk a little bit about this notion of ransomware is probably the number one use case. So the ability to take the most complex and the biggest, most vast applications. SAP is an example with hundreds of different moving parts to it and being able to protect that. The second is application resiliency. If, if you look at the cloud, there's this notion of, of responsibility, shared responsibility in the cloud. You've heard it, right? Yep. Every single one of the cloud service providers, certainly AWS has up on their website, this is what we protect, here's the demarcation line, the line in the sand, and you, the customer are responsible for that other level. And so we've had a technology, you previously knew it as InfoScale, we now call it alter application resiliency. >>And it can provide availability zone to availability zone, real time replication, high availability of your mission critical applications, right? So not only do we do the traditional backups, but we can also provide application resiliency for mission critical. And then the third thing really from a data management standpoint is all around governance and compliance. You know, ac a lot of our customers need to keep data for five, 10 years or forever. They're audited. There's regulations and different geographies around the world. And, and those regulations require them to be able to really take control of their cloud, take control of their data. And so we have a whole portfolio of solutions under that data compliance, data government. So back to your, your question Paul, it's really the integration and the intersection of those three main pillars. We're not a one trick pony. We've been at this for a long time, and they're not just new products that we invented a couple of months ago and brought to market. They're tried and tested with eight 80,000 customers and the most complex early solutions on the planet that we've been supporting. >>I gotta ask you, you know, we talked about those three pillars and you talked about the shared responsibility model. And think of that where you mentioned aws, Salesforce, Microsoft 365, Google workspace, whatnot. Are you finding that most customers aren't aware of that and haven't been protecting those workloads and then come to you and saying, Hey guys, guess what, this is what this is what they're responsible for. The data is >>You Yeah, I, it's, it's our probably biggest challenge is, is one of awareness, you know, with the cloud, I mean, how many times have you spoken to someone? You just put it in the cloud. Your applications, like the cloud providers like aws, they'll protect everything. Nothing will ever go down. And it's kind like if you, unless your house was ever broken into, you're probably not gonna install that burglar alarm or that fire alarm, right? Hopefully that won't be an event that you guys have to suffer through. So yeah, it's definitely, it wasn't till the last year or so the cloud service providers really published jointly as to where is their responsibility, right? So a great example is an attack vector for a lot of corporations is their SAS applications. So, you know, whether it it's your traditional SA applications that is available that's available on the web to their customers as a sas. >>And so it's certainly available to the bad actors. They're gonna, where there's, there's gonna be a point they're gonna try to get in. And so no matter what your resiliency plan is, at the end of the day, you really need to protect it. And protection isn't just, for example, with M 365 having a snapshot or a recycle bin, that's just not good enough. And so we actually have some pretty compelling technology, what we call ALTA SAS protection, which covers the, pretty much the, the gamut of the major SAS technologies to protect those and make it available for our customers. So yeah, certainly it's a big part of it is awareness. Yeah. >>Well, I understand that the shared responsibility model, I, I realize there's a lot of confusion about that still, but in the SaaS world that's somewhat different. The responsibility of the SaaS provider for protecting data is somewhat different. How, how should, what should customers know about that? >>I think, you know, the, the related to that, if, if you look at OnPrem, you know, approximately 35 to 40% of OnPrem enterprise data is protected. It's kind of in a long traditional problem. Everyone's aware of it. You know, I remember going to a presentation from IBM 20 something years ago, and someone held their push hand up in the room about the dis drives and says, you need to back it up. And the IBM sales guy said, no, IBM dis drives never crash. Right? And so fast forward to here we are today, things have changed. So we're going through almost a similar sort of changes and culture in the cloud. 8% of the data in the cloud is protected today, 8%. That's incredible. Meaning >>That there is independent backup devoted >>To that data in some cases, not at all. And something many cases, the customer just assumes that it's in the cloud, therefore it's always available. I never have to worry about protecting it, right? And so that's a big problem that we're obviously trying to, trying to solve. And we do that all under the umbrella of ransomware. That's a huge theme, huge investment that, that Veritas does with regards to providing that resiliency for our >>Customers. Ransomware is scary. It is becoming so prolific. The bad actors have access to technologies. Obviously companies are fighting them, but now ransomware has evolved into, no longer are we gonna get hit, it's when, yeah, it's how often it's what's the damage going to be. So the ability to help customers recover from ransomware, that resiliency is table stakes for businesses in any industry these days. Does that, that one of the primary pain points that your customers are coming to you with? >>It's the number one pain point. Yeah, it's, it's incredible. I mean, there's not a single briefing that our teams are doing customer meetings where that term ransomware doesn't come up as, as their number one use case. Just to give you something, a couple of statistics. There's a ransomware attack attack that happens 11 times a second right around the globe. And this isn't just, you know, minor stuff, right? I've got friends that are, you know, executives of large company that have been hit that have that some, you know, multimillion dollar ransom attack. So our, our play on this is, when you think about it, is data protection is the last line of defense. Yes. And so if they break through, it's not a case, Lisa, as you mentioned, if it's a case of when Yeah. And so it's gonna happen. So one of the most important things is knowing how do you know you have a gold copy, a clean copy, and you can recover at speed in some cases. >>We're talking about tens of thousands of systems to do that at speed. That's in our dna. We've been doing it for many, many years. And we spoke through a lot of the cyber insurance companies on this particular topic as well. And what really came back from that is that they're actually now demanding things like immutable storage, malware detection, air gaping, right? Anomaly detection is sort of core technologies tick the box that they literally won't ensure you unless you have those core components. And so what we've done is we've doubled down on that investment. We use AI in ML technologies, particularly around the anomaly detection. One of the, the, the unique and ne differentiators that Verto provides is a ransomware resiliency scorecard. Imagine the ability to save uran a corporation. We can come in and run our analytics on your environment and kind of give you a grade, right? Wouldn't you prefer that than waiting for the event to take place to see where your vulnerability really is? And so these are some of the advantages that we can actually provide for our customers, really, really >>To help. Just a final quick question. There is a, a common perception, I believe that ransomware is an on premise problem. In fact, it is also a cloud problem. Is that not right? >>Oh, absolutely. I I think that probably the biggest attack vector is in the cloud. If it's, if it's OnPrem, you've certainly got a certain line of defense that's trying to break through. But, you know, you're in the open world there. Obviously with SAS applications in the cloud, it's not a case of if, but when, and it's, and it's gonna continue to get, you know, more and more prevalent within corporations. There's always gonna be those attack factors that they find the, the flash wounds that they can attack to break through. What we are concentrating on is that resiliency, that ability for customers to recover at speed. We've done that with our traditional appliances from our heritage OnPrem. We continue to do that with regard to resiliency at speed with our customers in the cloud, with partners like aws >>For sure. Almost done. Give me your 30 seconds on AWS and Veritas. >>We've had a partnership for the better part of 10 years. It's incredible when you think about aws, where they released the elastic compute back in 2006, right? We've been delivering data protection, a data management solutions for, for the better part of 30 years, right? So, so we're, we're Junos in our space. We're the leader in, in data protection and enterprise data protection. We were on-prem. We, we continue to be in the cloud as AWS was with the cloud service provided. So the synergies are incredible. About 80 to 85% of our, our joint customers are the same. We take core unique superpowers of aws, like AWS outposts and AWS Glacier Instant retrieval, for example, those core technologies and incorporate them into our products as we go to Mark. And so we released a core technology a few months ago, we call it ultra recovery vault. And it's an air gap, a mutable storage, worm storage, right Once, right? You can't change it even when the bad actors try to get in. They're independent from the customer's tenant and aws. So we manage it as a managed backup service for our customers. Got it. And so our customers are using that to really help them with their ransomware. So it's been a tremendous partnership with AWS >>Standing 10 years of accounting. Last question for you, Rick. You got a billboard on the 1 0 1 in Santa Clara, right? By the fancy Verto >>1 0 1? >>Yeah. Right. Well, there's no traffic. What does that billboard say? What's that bumper sticker about? Vertus, >>I think, I think the billboard would say, welcome to the new Veritas. This is not your grandfather's old mobile. We've done a phenomenal job in, in the last, particularly the last three or four years, to really reinvent ourselves in the cloud and the investments that we made are really paying off for our customers today. So I'm excited to be part of this journey and excited to talk to you guys today. >>Love it. Not your grandfather's Veritas. Rick, thank you so much for joining Paula, me on the forgot talking about what you guys are doing, how you're helping customers, really established that cyber of resiliency, which is absolutely critical these days. We appreciate your >>Time. My pleasure. Thank you so much. >>All right, for our guest and Paul Gilland, I'm Lisa Martin, you're watching the Queue, which as you know is the leader in live enterprise and emerging check coverage.

>>We're back at Supercomputing 22 in Dallas, winding down day four of this conference. I'm Paul Gillan, my co-host Dave Nicholson. We are talking, we've been talking super computing all week and you hear a lot about what's going on in the United States, what's going on in China, Japan. What we haven't talked a lot about is what's going on in Europe and did you know that two of the top five supercomputers in the world are actually from European countries? Well, our guest has a lot to do with that. Florian, bearish, I hope I pronounce that correctly. My German is, German is not. My strength is the operations director for price, ais, S B L. And let's start with that. What is price? >>So, hello and thank you for the invitation. I'm Flon and Price is a partnership for Advanced Computing in Europe. It's a non-profit association with the seat in Brussels in Belgium. And we have 24 members. These are representatives from different European countries dealing with high performance computing in at their place. And we, so far, we provided the resources for our European research communities. But this changed in the last year, this oral HPC joint undertaking who put a lot of funding in high performance computing and co-funded five PET scale and three preis scale systems. And two of the preis scale systems. You mentioned already, this is Lumi and Finland and Leonardo in Bologna in Italy were in the place for and three and four at the top 500 at least. >>So why is it important that Europe be in the top list of supercomputer makers? >>I think Europe needs to keep pace with the rest of the world. And simulation science is a key technology for the society. And we saw this very recently with a pandemic, with a covid. We were able to help the research communities to find very quickly vaccines and to understand how the virus spread around the world. And all this knowledge is important to serve the society. Or another example is climate change. Yeah. With these new systems, we will be able to predict more precise the changes in the future. So the more compute power you have, the better the smaller the grid and there is resolution you can choose and the lower the error will be for the future. So these are, I think with these systems, the big or challenges we face can be addressed. This is the climate change, energy, food supply, security. >>Who are your members? Do they come from businesses? Do they come from research, from government? All of the >>Above. Yeah. Our, our members are public organization, universities, research centers, compute sites as a data centers, but But public institutions. Yeah. And we provide this services for free via peer review process with excellence as the most important criteria to the research community for free. >>So 40 years ago when, when the idea of an eu, and maybe I'm getting the dates a little bit wrong, when it was just an idea and the idea of a common currency. Yes. Reducing friction between, between borders to create a trading zone. Yes. There was a lot of focus there. Fast forward to today, would you say that these efforts in supercomputing, would they be possible if there were not an EU super structure? >>No, I would say this would not be possible in this extent. I think when though, but though European initiatives are, are needed and the European Commission is supporting these initiatives very well. And before praise, for instance 2008, there were research centers and data centers operating high performance computing systems, but they were not talking to each other. So it was isolated praise created community of operation sites and it facilitated the exchange between them and also enabled to align investments and to, to get the most out of the available funding. And also at this time, and still today for one single country in Europe, it's very hard to provide all the different architectures needed for all the different kind of research communities and applications. If you want to, to offer always the latest technologies, though this is really hardly possible. So with this joint action and opening the resources for other research groups from other countries, you, we, we were able to, yeah, get access to the latest technology for different communities at any given time though. And >>So, so the fact that the two systems that you mentioned are physically located in Finland and in Italy, if you were to walk into one of those facilities and meet the people that are there, they're not just fins in Finland and Italians in Italy. Yeah. This is, this is very much a European effort. So this, this is true. So, so in this, in that sense, the geography is sort of abstracted. Yeah. And the issues of sovereignty that make might take place in in the private sector don't exist or are there, are there issues with, can any, what are the requirements for a researcher to have access to a system in Finland versus a system in Italy? If you've got a EU passport, Hmm. Are you good to go? >>I think you are good to go though. But EU passport, it's now it becomes complicated and political. It's, it's very much, if we talk about the recent systems, well first, let me start a praise. Praise was inclusive and there was no any constraints as even we had users from US, Australia, we wanted just to support excellence in science. And we did not look at the nationality of the organization, of the PI and and so on. There were quotas, but these quotas were very generously interpreted. So, and if so, now with our HPC joint undertaking, it's a question from what European funds, these systems were procured and if a country or being country are associated to this funding, the researchers also have access to these systems. And this addresses basically UK and and Switzerland, which are not in the European Union, but they were as created to the Horizon 2020 research framework. And though they could can access the systems now available, Lumi and Leono and the Petascale system as well. How this will develop in the future, I don't know. It depends to which research framework they will be associated or not. >>What are the outputs of your work at price? Are they reference designs? Is it actual semiconductor hardware? Is it the research? What do you produce? >>So the, the application we run or the simulation we run cover all different scientific domains. So it's, it's science, it's, but also we have industrial let projects with more application oriented targets. Aerodynamics for instance, for cars or planes or something like this. But also fundamental science like the physical elementary physics particles for instance or climate change, biology, drug design, protein costa, all these >>Things. Can businesses be involved in what you do? Can they purchase your, your research? Do they contribute to their, I'm sure, I'm sure there are many technology firms in Europe that would like to be involved. >>So this involving industry though our calls are open and is, if they want to do open r and d, they are invited to submit also proposals. They will be evaluated and if this is qualifying, they will get the access and they can do their jobs and simulations. It's a little bit more tricky if it's in production, if they use these resources for their business and do not publish the results. They are some, well, probably more sites who, who are able to deal with these requests. Some are more dominant than others, but this is on a smaller scale, definitely. Yeah. >>What does the future hold? Are you planning to, are there other countries who will be joining the effort, other institutions? Do you plan to expand your, your scope >>Well, or I think or HPC joint undertaking with 36 member states is quite, covers already even more than Europe. And yeah, clearly if, if there are other states interest interested to join that there is no limitation. Although the focus lies on European area and on union. >>When, when you interact with colleagues from North America, do you, do you feel that there is a sort of European flavor to supercomputing that is different or are we so globally entwined? No. >>So research is not national, it's not European, it's international. This is also clearly very clear and I can, so we have a longstanding collaboration with our US colleagues and also with Chap and South Africa and Canada. And when Covid hit the world, we were able within two weeks to establish regular seminars inviting US and European colleagues to talk to to other, to each other and exchange the results and find new collaboration and to boost the research activities. So, and I have other examples as well. So when we, we already did the joint calls US exceed and in Europe praise and it was a very interesting experience. So we received applications from different communities and we decided that we will review this on our side, on European, with European experts and US did it in US with their experts. And you can guess what the result was at the meeting when we compared our results, it was matching one by one. It was exactly the same. Recite >>That it, it's, it's refreshing to hear a story of global collaboration. Yeah. Where people are getting along and making meaningful progress. >>I have to mention you, I have to to point out, you did not mention China as a country you were collaborating with. Is that by, is that intentional? >>Well, with China, definitely we have less links and collaborations also. It's also existing. There, there was initiative to look at the development of the technologies and the group meet on a regular basis. And there, there also Chinese colleagues involved. It's on a lower level, >>Yes, but is is the con conversations are occurring. We're out of time. Florian be operations director of price, European Super Computing collaborative. Thank you so much for being with us. I'm always impressed when people come on the cube and submit to an interview in a language that is not their first language. Yeah, >>Absolutely. >>Brave to do that. Yeah. Thank you. You're welcome. Thank you. We'll be right back after this break from Supercomputing 22 in Dallas.