(bright music) >> Hello, everyone. Welcome to theCUBE special presentation of International Women's Day. I'm John Furrier, host of theCUBE. This is a global special open program we're doing every year. We're going to continue it every quarter. We're going to do more and more content, getting the voices out there and celebrating the diversity. And I'm excited to have an amazing guest here, LaDavia Drane, who's the head of Global Inclusion Diversity & Equity at AWS. LaDavia, we tried to get you in on AWS re:Invent, and you were super busy. So much going on. The industry has seen the light. They're seeing everything going on, and the numbers are up, but still not there, and getting better. This is your passion, our passion, a shared passion. Tell us about your situation, your career, how you got into it. What's your story? >> Yeah. Well, John, first of all, thank you so much for having me. I'm glad that we finally got this opportunity to speak. How did I get into this work? Wow, you know, I'm doing the work that I love to do, number one. It's always been my passion to be a voice for the voiceless, to create a seat at the table for folks that may not be welcome to certain tables. And so, it's been something that's been kind of the theme of my entire professional career. I started off as a lawyer, went to Capitol Hill, was able to do some work with members of Congress, both women members of Congress, but also, minority members of Congress in the US Congress. And then, that just morphed into what I think has become a career for me in inclusion, diversity, and equity. I decided to join Amazon because I could tell that it's a company that was ready to take it to the next level in this space. And sure enough, that's been my experience here. So now, I'm in it, I'm in it with two feet, doing great work. And yeah, yeah, it's almost a full circle moment for me. >> It's really an interesting background. You have a background in public policy. You mentioned Capitol Hill. That's awesome. DC kind of moves slow, but it's a complicated machinery there. Obviously, as you know, navigating that, Amazon grew significantly. We've been at every re:Invent with theCUBE since 2013, like just one year. I watched Amazon grow, and they've become very fast and also complicated, like, I won't say like Capitol, 'cause that's very slow, but Amazon's complicated. AWS is in the realm of powering a generation of public policy. We had the JEDI contract controversy, all kinds of new emerging challenges. This pivot to tech was great timing because one, (laughs) Amazon needed it because they were growing so fast in a male dominated world, but also, their business is having real impact on the public. >> That's right, that's right. And when you say the public, I'll just call it out. I think that there's a full spectrum of diversity and we work backwards from our customers, and our customers are diverse. And so, I really do believe, I agree that I came to the right place at the right time. And yeah, we move fast and we're also moving fast in this space of making sure that both internally and externally, we're doing the things that we need to do in order to reach a diverse population. >> You know, I've noticed how Amazon's changed from the culture, male dominated culture. Let's face it, it was. And now, I've seen over the past five years, specifically go back five, is kind of in my mental model, just the growth of female leaders, it's been impressive. And there was some controversy. They were criticized publicly for this. And we said a few things as well in those, like around 2014. How is Amazon ensuring and continuing to get the female employees feel represented and empowered? What's going on there? What programs do you have? Because it's not just doing it, it's continuing it, right? And 'cause there is a lot more to do. I mean, the half (laughs) the products are digital now for everybody. It's not just one population. (laughs) Everyone uses digital products. What is Amazon doing now to keep it going? >> Well, I'll tell you, John, it's important for me to note that while we've made great progress, there's still more that can be done. I am very happy to be able to report that we have big women leaders. We have leaders running huge parts of our business, which includes storage, customer experience, industries and business development. And yes, we have all types of programs. And I should say that, instead of calling it programs, I'm going to call it strategic initiatives, right? We are very thoughtful about how we engage our women. And not only how we hire, attract women, but how we retain our women. We do that through engagement, groups like our affinity groups. So Women at Amazon is an affinity group. Women in finance, women in engineering. Just recently, I helped our Black employee network women's group launch, BEN Women. And so you have these communities of women who come together, support and mentor one another. We have what we call Amazon Circles. And so these are safe spaces where women can come together and can have conversations, where we are able to connect mentors and sponsors. And we're seeing that it's making all the difference in the world for our women. And we see that through what we call Connections. We have an inclusion sentiment tracker. So we're able to ask questions every single day and we get a response from our employees and we can see how are our women feeling, how are they feeling included at work? Are they feeling as though they can be who they are authentically at Amazon? And so, again, there's more work that needs to be done. But I will say that as I look at the data, as I'm talking to engaging women, I really do believe that we're on the right path. >> LaDavia, talk about the urgent needs of the women that you're hearing from the Circles. That's a great program. The affinity circles, the groups are great. Now, you have the groups, what are you hearing? What are the needs of the women? >> So, John, I'll just go a little bit into what's becoming a conversation around equity. So, initially I think we talked a lot about equality, right? We wanted everyone to have fair access to the same things. But now, women are looking for equity. We're talking about not just leveling the playing field, which is equality, but don't give me the same as you give everyone else. Instead, recognize that I may have different circumstances, I may have different needs. And give me what I need, right? Give me what I need, not just the same as everyone else. And so, I love seeing women evolve in this way, and being very specific about what they need more than, or what's different than what a man may have in the same situation because their circumstances are not always the same and we should treat them as such. >> Yeah, I think that's a great equity point. I interviewed a woman here, ex-Amazonian, she's now a GSI, Global System Integrator. She's a single mom. And she said remote work brought her equity because people on her team realized that she was a single mom. And it wasn't the, how do you balance life, it was her reality. And what happened was, she had more empathy with the team because of the new work environment. So, I think this is an important point to call out, that equity, because that really makes things smoother in terms of the interactions, not the assumptions, you have to be, you know, always the same as a man. So, how does that go? What's the current... How would you characterize the progress in that area right now? >> I believe that employers are just getting better at this. It's just like you said, with the hybrid being the norm now, you have an employer who is looking at people differently based on what they need. And it's not a problem, it's not an issue that a single mother says, "Well, I need to be able to leave by 5:00 PM." I think that employers now, and Amazon is right there along with other employers, are starting just to evolve that muscle of meeting the needs. People don't have to feel different. You don't have to feel as though there's some kind of of special circumstance for me. Instead, it's something that we, as employers, we're asking for. And we want to meet those needs that are different in some situations. >> I know you guys do a lot of support of women outside of AWS, and I had a story I recorded for the program. This woman, she talked about how she was a nerd from day one. She's a tomboy. They called her a tomboy, but she always loved robotics. And she ended up getting dual engineering degrees. And she talked about how she didn't run away and there was many signals to her not to go. And she powered through, at that time, and during her generation, that was tough. And she was successful. How are you guys taking the education to STEM, to women, at young ages? Because we don't want to turn people away from tech if they have the natural affinity towards it. And not everyone is going to be, as, you know, (laughs) strong, if you will. And she was a bulldog, she was great. She's just like, "I'm going for it. I love it so much." But not everyone's like that. So, this is an educational thing. How do you expose technology, STEM for instance, and making it more accessible, no stigma, all that stuff? I mean, I think we've come a long way, but still. >> What I love about women is we don't just focus on ourselves. We do a very good job of thinking about the generation that's coming after us. And so, I think you will see that very clearly with our women Amazonians. I'll talk about three different examples of ways that Amazonian women in particular, and there are men that are helping out, but I'll talk about the women in particular that are leading in this area. On my team, in the Inclusion, Diversity & Equity team, we have a program that we run in Ghana where we meet basic STEM needs for a afterschool program. So we've taken this small program, and we've turned their summer camp into this immersion, where girls and boys, we do focus on the girls, can come and be completely immersed in STEM. And when we provide the technology that they need, so that they'll be able to have access to this whole new world of STEM. Another program which is run out of our AWS In Communities team, called AWS Girls' Tech Day. All across the world where we have data centers, we're running these Girls' Tech Day. They're basically designed to educate, empower and inspire girls to pursue a career in tech. Really, really exciting. I was at the Girls' Tech Day here recently in Columbus, Ohio, and I got to tell you, it was the highlight of my year. And then I'll talk a little bit about one more, it's called AWS GetIT, and it's been around for a while. So this is a program, again, it's a global program, it's actually across 13 countries. And it allows girls to explore cloud technology, in particular, and to use it to solve real world problems. Those are just three examples. There are many more. There are actually women Amazonians that create these opportunities off the side of their desk in they're local communities. We, in Inclusion, Diversity & Equity, we fund programs so that women can do this work, this STEM work in their own local communities. But those are just three examples of some of the things that our Amazonians are doing to bring girls along, to make sure that the next generation is set up and that the next generation knows that STEM is accessible for girls. >> I'm a huge believer. I think that's amazing. That's great inspiration. We need more of that. It's awesome. And why wouldn't we spread it around? I want to get to the equity piece, that's the theme for this year's IWD. But before that, getting that segment, I want to ask you about your title, and the choice of words and the sequence. Okay, Global Inclusion, Diversity, Equity. Not diversity only. Inclusion is first. We've had this debate on theCUBE many years now, a few years back, it started with, "Inclusion is before diversity," "No, diversity before inclusion, equity." And so there's always been a debate (laughs) around the choice of words and their order. What's your opinion? What's your reaction to that? Is it by design? And does inclusion come before diversity, or am I just reading it to it? >> Inclusion doesn't necessarily come before diversity. (John laughs) It doesn't necessarily come before equity. Equity isn't last, but we do lead with inclusion in AWS. And that is very important to us, right? And thank you for giving me the opportunity to talk a little bit about it. We lead with inclusion because we want to make sure that every single one of our builders know that they have a place in this work. And so it's important that we don't only focus on hiring, right? Diversity, even though there are many, many different levels and spectrums to diversity. Inclusion, if you start there, I believe that it's what it takes to make sure that you have a workplace where everyone knows you're included here, you belong here, we want you to stay here. And so, it helps as we go after diversity. And we want all types of people to be a part of our workforce, but we want you to stay. And inclusion is the thing. It's the thing that I believe makes sure that people stay because they feel included. So we lead with inclusion. Doesn't mean that we put diversity or equity second or third, but we are proud to lead with inclusion. >> Great description. That was fabulous. Totally agree. Double click, thumbs up. Now let's get into the theme. Embracing equity, 'cause this is a term, it's in quotes. What does that mean to you? You mentioned it earlier, I love it. What does embrace equity mean? >> Yeah. You know, I do believe that when people think about equity, especially non-women think about equity, it's kind of scary. It's, "Am I going to give away what I have right now to make space for someone else?" But that's not what equity means. And so I think that it's first important that we just educate ourselves about what equity really is. It doesn't mean that someone's going to take your spot, right? It doesn't mean that the pie, let's use that analogy, gets smaller. The pie gets bigger, right? >> John: Mm-hmm. >> And everyone is able to have their piece of the pie. And so, I do believe that I love that IWD, International Women's Day is leading with embracing equity because we're going to the heart of the matter when we go to equity, we're going to the place where most people feel most challenged, and challenging people to think about equity and what it means and how they can contribute to equity and thus, embrace equity. >> Yeah, I love it. And the advice that you have for tech professionals out there on this, how do you advise other groups? 'Cause you guys are doing a lot of great work. Other organizations are catching up. What would be your advice to folks who are working on this equity challenge to reach gender equity and other equitable strategic initiatives? And everyone's working on this. Sustainability and equity are two big projects we're seeing in every single company right now. >> Yeah, yeah. I will say that I believe that AWS has proven that equity and going after equity does work. Embracing equity does work. One example I would point to is our AWS Impact Accelerator program. I mean, we provide 30 million for early stage startups led by women, Black founders, Latino founders, LGBTQ+ founders, to help them scale their business. That's equity. That's giving them what they need. >> John: Yeah. >> What they need is they need access to capital. And so, what I'd say to companies who are looking at going into the space of equity, I would say embrace it. Embrace it. Look at examples of what companies like AWS is doing around it and embrace it because I do believe that the tech industry will be better when we're comfortable with embracing equity and creating strategic initiatives so that we could expand equity and make it something that's just, it's just normal. It's the normal course of business. It's what we do. It's what we expect of ourselves and our employees. >> LaDavia, you're amazing. Thank you for spending the time. My final couple questions really more around you. Capitol Hill, DC, Amazon Global Head of Inclusion, Diversity & Equity, as you look at making change, being a change agent, being a leader, is really kind of similar, right? You've got DC, it's hard to make change there, but if you do it, it works, right? (laughs) If you don't, you're on the side of the road. So, as you're in your job now, what are you most excited about? What's on your agenda? What's your focus? >> Yeah, so I'm most excited about the potential of what we can get done, not just for builders that are currently in our seats, but for builders in the future. I tend to focus on that little girl. I don't know her, I don't know where she lives. I don't know how old she is now, but she's somewhere in the world, and I want her to grow up and for there to be no question that she has access to AWS, that she can be an employee at AWS. And so, that's where I tend to center, I center on the future. I try to build now, for what's to come, to make sure that this place is accessible for that little girl. >> You know, I've always been saying for a long time, the software is eating the world, now you got digital transformation, business transformation. And that's not a male only, or certain category, it's everybody. And so, software that's being built, and the systems that are being built, have to have first principles. Andy Jassy is very strong on this. He's been publicly saying, when trying to get pinned down about certain books in the bookstore that might offend another group. And he's like, "Look, we have first principles. First principles is a big part of leading." What's your reaction to that? How would you talk to another professional and say, "Hey," you know this, "How do I make the right call? Am I doing the wrong thing here? And I might say the wrong thing here." And is it first principles based? What's the guardrails? How do you keep that in check? How would you advise someone as they go forward and lean in to drive some of the change that we're talking about today? >> Yeah, I think as leaders, we have to trust ourselves. And Andy actually, is a great example. When I came in as head of ID&E for AWS, he was our CEO here at AWS. And I saw how he authentically spoke from his heart about these issues. And it just aligned with who he is personally, his own personal principles. And I do believe that leaders should be free to do just that. Not to be scripted, but to lead with their principles. And so, I think Andy's actually a great example. I believe that I am the professional in this space at this company that I am today because of the example that Andy set. >> Yeah, you guys do a great job, LaDavia. What's next for you? >> What's next. >> World tour, you traveling around? What's on your plate these days? Share a little bit about what you're currently working on. >> Yeah, so you know, at Amazon, we're always diving deep. We're always diving deep, we're looking for root cause, working very hard to look around corners, and trying to build now for what's to come in the future. And so I'll continue to do that. Of course, we're always planning and working towards re:Invent, so hopefully, John, I'll see you at re:Invent this December. But we have some great things happening throughout the year, and we'll continue to... I think it's really important, as opposed to looking to do new things, to just continue to flex the same muscles and to show that we can be very, very focused and intentional about doing the same things over and over each year to just become better and better at this work in this space, and to show our employees that we're committed for the long haul. So of course, there'll be new things on the horizon, but what I can say, especially to Amazonians, is we're going to continue to stay focused, and continue to get at this issue, and doing this issue of inclusion, diversity and equity, and continue to do the things that work and make sure that our culture evolves at the same time. >> LaDavia, thank you so much. I'll give you the final word. Just share some of the big projects you guys are working on so people can know about them, your strategic initiatives. Take a minute to plug some of the major projects and things that are going on that people either know about or should know about, or need to know about. Take a minute to share some of the big things you guys got going on, or most of the things. >> So, one big thing that I would like to focus on, focus my time on, is what we call our Innovation Fund. This is actually how we scale our work and we meet the community's needs by providing micro grants to our employees so our employees can go out into the world and sponsor all types of different activities, create activities in their local communities, or throughout the regions. And so, that's probably one thing that I would like to focus on just because number one, it's our employees, it's how we scale this work, and it's how we meet our community's needs in a very global way. And so, thank you John, for the opportunity to talk a bit about what we're up to here at Amazon Web Services. But it's just important to me, that I end with our employees because for me, that's what's most important. And they're doing some awesome work through our Innovation Fund. >> Inclusion makes the workplace great. Empowerment, with that kind of program, is amazing. LaDavia Drane, thank you so much. Head of Global Inclusion and Diversity & Equity at AWS. This is International Women's Day. I'm John Furrier with theCUBE. Thanks for watching and stay with us for more great interviews and people and what they're working on. Thanks for watching. (bright music)

(upbeat music) >> Hello everyone, welcome back to theCUBE's coverage of Cloud Native SecurityCon North America 2023. Obviously, CUBE's coverage with our CUBE Center Report. We're not there on the ground, but we have folks and our CUBE Alumni there. We have entrepreneurs there. Of course, we want to be there in person, but we're remote. We've got Ben Hirschberg, CTO and Co-Founder of Armo, a cloud native security startup, well positioned in this industry. He's there in Seattle. Ben, thank you for coming on and sharing what's going on with theCUBE. >> Yeah, it's great to be here, John. >> So we had written on you guys up on SiliconANGLE. Congratulations on your momentum and traction. But let's first get into what's going on there on the ground? What are some of the key trends? What's the most important story being told there? What is the vibe? What's the most important story right now? >> So I think, I would like to start here with the I think the most important thing was that I think the event is very successful. Usually, the Cloud Native Security Day usually was part of KubeCon in the previous years and now it became its own conference of its own and really kudos to all the organizers who brought this up in, actually in a short time. And it wasn't really clear how many people will turn up, but at the end, we see a really nice turn up and really great talks and keynotes around here. I think that one of the biggest trends, which haven't started like in this conference, but already we're talking for a while is supply chain. Supply chain is security. I think it's, right now, the biggest trend in the talks, in the keynotes. And I think that we start to see companies, big companies, who are adopting themselves into this direction. There is a clear industry need. There is a clear problem and I think that the cloud native security teams are coming up with tooling around it. I think for right now we see more tools than adoption, but the adoption is always following the tooling. And I think it already proves itself. So we have just a very interesting talk this morning about the OpenSSL vulnerability, which was I think around Halloween, which came out and everyone thought that it's going to be a critical issue for the whole cloud native and internet infrastructure and at the end it turned out to be a lesser problem, but the reason why I think it was understood that to be a lesser problem real soon was that because people started to use (indistinct) store software composition information in the environment so security teams could look into, look up in their systems okay, what, where they're using OpenSSL, which version they are using. It became really soon real clear that this version is not adopted by a wide array of software out there so the tech surface is relatively small and I think it already proved itself that the direction if everyone is talking about. >> Yeah, we agree, we're very bullish on this move from the Cloud Native Foundation CNCF that do the security conference. Amazon Web Services has re:Invent. That's their big show, but they also have re:Inforce, the security show, so clearly they work together. I like the decoupling, very cohesive. But you guys have Kubescape of Kubernetes security. Talk about the conversations that are there and that you're hearing around why there's different event what's different around KubeCon and CloudNativeCon than this Cloud Native SecurityCon. It's not called KubeSucSecCon, it's called Cloud Native SecurityCon. What's the difference? Are people confused? Is it clear? What's the difference between the two shows? What are you hearing? >> So I think that, you know, there is a good question. Okay, where is Cloud Native Computing Foundation came from? Obviously everyone knows that it was somewhat coupled with the adoption of Kubernetes. It was a clear understanding in the industry that there are different efforts where the industry needs to come together without looking be very vendor-specific and try to sort out a lot of issues in order to enable adoption and bring great value and I think that the main difference here between KubeCon and the Cloud Native Security Conference is really the focus, and not just on Kubernetes, but the whole ecosystem behind that. The way we are delivering software, the way we are monitoring software, and all where Kubernetes is only just, you know, maybe the biggest clog in the system, but, you know, just one of the others and it gives great overview of what you have in the whole ecosystem. >> Yeah, I think it's a good call. I would add that what I'm hearing too is that security is so critical to the business model of every company. It's so mainstream. The hackers have a great business model. They make money, their costs are lower than the revenue. So the business of hacking in breaches, ransomware all over the place is so successful that they're playing offense, everyone's playing defense, so it's about time we can get focus to really be faster and more nimble and agile on solving some of these security challenges in open source. So I think that to me is a great focus and so I give total props to the CNC. I call it the event operating system. You got the security group over here decoupled from the main kernel, but they work together. Good call and so this brings back up to some of the things that are going on so I have to ask you, as your startup as a CTO, you guys have the Kubescape platform, how do you guys fit into the landscape and what's different from your tools for Kubernetes environments versus what's out there? >> So I think that our journey is really interesting in the solution space because I think that our mode really tries to understand where security can meet the actual adoption because as you just said, somehow we have to sort out together how security is going to be automated and integrated in its best way. So Kubescape project started as a Kubernetes security posture tool. Just, you know, when people are really early in their adoption of Kubernetes systems, they want to understand whether the installation is is secure, whether the basic configurations are look okay, and giving them instant feedback on that, both in live systems and in the CICD, this is where Kubescape came from. We started as an open source project because we are big believers of open source, of the power of open source security, and I can, you know I think maybe this is my first interview when I can say that Kubescape was accepted to be a CNCF Sandbox project so Armo was actually donating the project to the CNCF, I think, which is a huge milestone and a great way to further the adoption of Kubernetes security and from now on we want to see where the users in Armo and Kubescape project want to see where the users are going, their Kubernetes security journey and help them to automatize, help them to to implement security more fast in the way the developers are using it working. >> Okay, if you don't mind, I want to just get clarification. What's the difference between the Armo platform and Kubescape because you have Kubescape Sandbox project and Armo platform. Could you talk about the differences and interaction? >> Sure, Kubescape is an open source project and Armo platform is actually a managed platform which runs Kubescape in the cloud for you because Kubescape is part, it has several parts. One part is, which is running inside the Kubernetes cluster in the CICD processes of the user, and there is another part which we call the backend where the results are stored and can be analyzed further. So Armo platform gives you managed way to run the backend, but I can tell you that backend is also, will be available within a month or two also for everyone to install on their premises as well, because again, we are an open source company and we are, we want to enable users, so the difference is that Armo platform is a managed platform behind Kubescape. >> How does Kubescape differ from closed proprietary sourced solutions? >> So I can tell you that there are closed proprietary solutions which are very good security solutions, but I think that the main difference, if I had to pick beyond the very specific technicalities is the worldview. The way we see that our user is not the CISO. Our user is not necessarily the security team. From our perspective, the user is the DevOps and the developers who are working on the Kubernetes cluster day to day and we want to enable them to improve their security. So actually our approach is more developer-friendly, if I would need to define it very shortly. >> What does this risk calculation score you guys have in Kubscape? That's come up and we cover that in our story. Can you explain to the folks how that fits in? Is it Kubescape is the platform and what's the benefit, what's the purpose? >> So the risk calculation is actually a score we are giving to clusters in order for the users to understand where they are standing in the general population, how they are faring against a perfect hardened cluster. It is based on the number of different tests we are making. And I don't want to go into, you know, the very specifics of the mathematical functions, but in general it takes into account how many functions are failing, security tests are failing inside your cluster. How many nodes you are having, how many workloads are having, and creating this number which enables you to understand where you are standing in the global, in the world. >> What's the customer value that you guys pitching? What's the pitch for the Armo platform? When you go and talk to a customer, are they like, "We need you." Do they come to you? Is it word of mouth? You guys have a strategy? What's the pitch? What's so appealing to the customers? Why are they enthusiastic about you guys? >> So John, I can tell you, maybe it's not so easy to to say the words, but I nearly 20 years in the industry and though I've been always around cyber and the defense industry and I can tell you that I never had this journey where before where I could say that the the customers are coming to us and not we are pitching to customers. Simply because people want to, this is very easy tool, very very easy to use, very understandable and it very helps the engineers to improve security posture. And they're coming to us and they're saying, "Well, awesome, okay, how we can like use it. Do you have a graphical interface?" And we are pointing them to the Armor platform and they are falling in love and coming to us even more and we can tell you that we have a big number of active users behind the platform itself. >> You know, one of the things that comes up every time at KubeCon and Cloud NativeCon when we're there, and we'll be in Amsterdam, so folks watching, you know, we'll see onsite, developer productivity is like the number one thing everyone talks about and security is so important. It's become by default a blocker or anchor or a drag on productivity. This is big, the things that you're mentioning, easy to use, engineering supporting it, developer adoption, you know we've always said on theCUBE, developers will be the de facto standards bodies by their choices 'cause developers make all the decisions. So if I can go faster and I can have security kind of programmed in, I'm not shifting left, it's just I'm just having security kind of in there. That's the dream state. Is that what you guys are trying to do here? Because that's the nirvana, everyone wants to do that. >> Yeah, I think your definition is like perfect because really we had like this, for a very long time we had this world where we decoupled security teams from developers and even for sometimes from engineering at all and I think for multiple reasons, we are more seeing a big convergence. Security teams are becoming part of the engineering and the engineering becoming part of the security and as you're saying, okay, the day-to-day world of developers are becoming very tangled up in the good way with security, so the think about it that today, one of my developers at Armo is creating a pull request. He's already, code is already scanned by security scanners for to test for different security problems. It's already, you know, before he already gets feedback on his first time where he's sharing his code and if there is an issue, he already can solve it and this is just solving issues much faster, much cheaper, and also you asked me about, you know, the wipe in the conference and we know no one can deny the current economic wipe we have and this also relates to security teams and security teams has to be much more efficient. And one of the things that everyone is talking, okay, we need more automation, we need more, better tooling and I think we are really fitting into this. >> Yeah, and I talked to venture capitalists yesterday and today, an angel investor. Best time for startup is right now and again, open source is driving a lot of value. Ben, it's been great to have you on and sharing with us what's going on on the ground there as well as talking about some of the traction you have. Just final question, how old's the company? How much funding do you have? Where you guys located? Put a plug in for the company. You guys looking to hire? Tell us about the company. Were you guys located? How much capital do you have? >> So, okay, the company's here for three years. We've passed a round last March with Tiger and Hyperwise capitals. We are located, most of the company's located today in Israel in Tel Aviv, but we have like great team also in Ukraine and also great guys are in Europe and right now also Craig Box joined us as an open source VP and he's like right now located in New Zealand, so we are a really global team, which I think it's really helps us to strengthen ourselves. >> Yeah, and I think this is the entrepreneurial equation for the future. It's really great to see that global. We heard that in Priyanka Sharma's keynote. It's a global culture, global community. >> Right. >> And so really, really props you guys. Congratulations on Armo and thanks for coming on theCUBE and sharing insights and expertise and also what's happening on the ground. Appreciate it, Ben, thanks for coming on. >> Thank you, John. >> Okay, cheers. Okay, this is CUB coverage here of the Cloud Native SecurityCon in North America 2023. I'm John Furrier for Lisa Martin, Dave Vellante. We're back with more of wrap up of the event after this short break. (gentle upbeat music)

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

(lively music) >> Good afternoon cloud community and welcome back to beautiful Las Vegas, Nevada. We are here at AWS re:Invent, day four of our wall to wall coverage. It is day four in the afternoon and we are holding strong. I'm Savannah Peterson, joined by my fabulous co-host Paul Gillen. Paul, how you doing? >> I'm doing well, fine Savannah. You? >> You look great. >> We're in the home stretch here. >> Yeah, (laughs) we are. >> You still look fresh as a daisy. I don't know how you do it. >> (laughs) You're too kind. You're too kind, but I'm vain enough to take that compliment. I'm very excited about the conversation that we're going to have up next. We get to get a little DevRel and we got a little swagger on the stage. Welcome, Austin. How you doing? >> Hey, great to be here. Thanks for having me. >> Savannah: Yeah, it's our pleasure. How's the show been for you so far? >> Busy, exciting. Feels a lot like, you know it used to be right? >> Yeah, I know. A little reminiscent of the before times. >> Well, before times. >> Before we dig into the technical stuff, you're the most intriguingly dressed person we've had on the show this week. >> Austin: I feel extremely underdressed. >> Well, and we were talking about developer fancy. Talk to me a little bit about your approach to fashion. Wasn't expecting to lead with this, but I like this but I like this actually. >> No, it's actually good with my PR. You're going to love it. My approach, here's the thing, I give free advice all the time about developer relations, about things that work, have worked, and don't work in community and all that stuff. I love talking about that. Someone came up to me and said, "Where do you get your fashion tips from? What's the secret Discord server that I need to go on?" I'm like, "I will never tell." >> Oh, okay. >> This is an actual trait secret. >> Top secret. Wow! Talk about. >> If someone else starts wearing the hat, then everyone's going to be like, "There's so many white guys." Look, I'm a white guy with a beard that works in technology. >> Savannah: I've never met one of those. >> Exactly, there's none of them at all. So, you have to do something to kind stand out from the crowd a little bit. >> I love it, and it's a talk trigger. We're talking about it now. Production team loved it. It's fantastic. >> It's great. >> So your DevRel for Lightstep, in case the audience isn't familiar tell us about Lightstep. >> So Lightstep is a cloud native observability platform built at planet scale, and it powers observability at some places you've heard of like Spotify, GitHub, right? We're designed to really help developers that are working in the cloud with Kubernetes, with these huge distributed systems, understand application performance and being able to find problems, fix problems. We're also part of the ServiceNow family and as we all know ServiceNow is on a mission to help the world of work work better by powering digital transformation around IT and customer experiences for their many, many, many global 2000 customers. We love them very much. >> You know, it's a big love fest here. A lot of people have talked about the collaboration, so many companies working together. You mentioned unified observability. What is unified observability? >> So if you think about a tradition, or if you've heard about this traditional idea of observability where you have three pillars, right? You have metrics, and you have logs, and you have traces. All those three things are different data sources. They're picked up by different tools. They're analyzed by different people for different purposes. What we believe and what we're working to accomplish right now is to take all that and if you think those pillars, flip 'em on their side and think of them as streams of data. If we can take those streams and integrate them together and let you treat traces and metrics and logs not as these kind of inviolate experiences where you're kind of paging between things and going between tab A to tab B to tab C, and give you a standard way to query this, a standard way to display this, and letting you kind of find the most relevant data, then it really unlocks a lot of power for like developers and SREs to spend less time like managing tools. You know, figuring out where to build their query or what dashboard to check, more just being able to like kind of ask a question, get an answer. When you have an incident or an outage that's the most important thing, right? How quickly can you get those answers that you need so that you can restore system health? >> You don't want to be looking in multiple spots to figure out what's going on. >> Absolutely. I mean, some people hear unified observability and they go to like tool consolidation, right? That's something I hear from a lot of our users and a lot of people in re:Invent. I'll talk to SREs, they're like, "Yeah, we've got like six or seven different metrics products alone, just on services that they cover." It is important to kind of consolidate that but we're really taking it a step lower. We're looking at the data layer and trying to say, "Okay, if the data is all consistent and vendor neutral then that gives you flexibility not only from a tool consolidation perspective but also you know, a consistency, reliability. You could have a single way to deploy your observability out regardless of what cloud you're on, regardless if you're using Kubernetes or Fargate or whatever else. or even just Bare Metal or EC2 Bare Metal, right? There's been so much historically in this space. There's been a lot of silos and we think that unify diversability means that we kind of break down those silos, right? The way that we're doing it primarily is through a project called OpenTelemetry which you might have heard of. You want to talk about that in a minute? . >> Savannah: Yeah, let's talk about it right now. Why don't you tell us about it? Keep going, you're great. You're on a roll. >> I am. >> Savannah: We'll just hang out over here. >> It's day four. I'm going to ask the questions and answer the questions. (Savannah laughs) >> Yes, you're right. >> I do yeah. >> Open Tele- >> OpenTelemetry . >> Explain what OpenTelemetry is first. >> OpenTelemetry is a CNCF project, Cloud Native Computing Foundation. The goal is to make telemetry data, high quality telemetry data, a builtin feature of cloud native software right? So right now if you wanted to get logging data out, depending on your application stack, depending on your application run time, depending on language, depending on your deployment environment. You might have a lot... You have to make a lot of choices, right? About like, what am I going to use? >> Savannah: So many different choices, and the players are changing all the time. >> Exactly, and a lot of times what people will do is they'll go and they'll say like, "We have to use this commercial solution because they have a proprietary agent that can do a lot of this for us." You know? And if you look at all those proprietary agents, what you find very quickly is it's very commodified right? There's no real difference in what they're doing at a code level and what's stopped the industry from really adopting a standard way to create this logs and metrics and traces, is simply just the fact that there was no standard. And so, OpenTelemetry is that standard, right? We've got dozens of companies many of them like very, many of them here right? Competitors all the same, working together to build this open standard and implementation of telemetry data for cloud native software and really any software right? Like we support over 12 languages. We support Kubernetes, Amazon. AWS is a huge contributor actually and we're doing some really exciting stuff with them on their Amazon distribution of OpenTelemetry. So it's been extremely interesting to see it over the past like couple years go from like, "Hey, here's this like new thing that we're doing over here," to really it's a generalized acceptance that this is the way of the future. This is what we should have been doing all along. >> Yeah. >> My opinion is there is a perception out there that observability is kind of a commodity now that all the players have the same set of tools, same set of 15 or 17 or whatever tools, and that there's very little distinction in functionality. Would you agree with that? >> I don't know if I would characterize it that way entirely. I do think that there's a lot of duplicated effort that happens and part of the reason is because of this telemetry data problem, right? Because you have to wind up... You know, there's this idea of table stakes monitoring that we talk about right? Table stakes monitoring is the stuff that you're having to do every single day to kind of make sure your system is healthy to be able to... When there's an alert, gets triggered, to see why it got triggered and to go fix it, right? Because everyone has the kind of work on that table stake stuff and then build all these integrations, there's very little time for innovation on top of that right? Because you're spending all your time just like working on keeping up with technology. >> Savannah: Doing the boring stuff to make sure the wheels don't fall off, basically. >> Austin: Right? What I think the real advantage of OpenTelemetry is that it really, from like a vendor perspective, like it unblocks us from having to kind of do all this repetitive commodified work. It lets us help move that out to the community level so that... Instead of having to kind of build, your Kubernetes integration for example, you can just have like, "Hey, OpenTelemetry is integrated into Kubernetes and you just have this data now." If you are a commercial product, or if you're even someone that's interested in fixing a, scratching a particular itch about observability. It's like, "I have this specific way that I'm doing Kubernetes and I need something to help me really analyze that data. Well, I've got the data now I can just go create a project. I can create an analysis tool." I think that's what you'll see over time as OpenTelemetry promulgates out into the ecosystem is more people building interesting analysis features, people using things like machine learning to analyze this large amount, large and consistent amount of OpenTelemetry data. It's going to be a big shakeup I think, but it has the potential to really unlock a lot of value for our customers. >> Well, so you're, you're a developer relations guy. What are developers asking for right now out of their observability platforms? >> Austin: That's a great question. I think there's two things. The first is that they want it to just work. It's actually the biggest thing, right? There's so many kind of... This goes back to the tool proliferation, right? People have too much data in too many different places, and getting that data out can still be really challenging. And so, the biggest thing they want is just like, "I want something that I can... I want a lot of these questions I have to ask, answered already and OpenTelemetry is going towards it." Keep in mind it's the project's only three years old, so we obviously have room to grow but there are people running it in production and it works really well for them but there's more that we can do. The second thing is, and this isn't what really is interesting to me, is it's less what they're asking for and more what they're not asking for. Because a lot of the stuff that you see people, saying around, "Oh, we need this like very specific sort of lower level telemetry data, or we need this kind of universal thing." People really just want to be able to get questions or get questions answered, right? They want tools that kind of have these workflows where you don't have to be an expert because a lot of times this tooling gets locked behind sort of is gate kept almost in a organization where there are teams that's like, "We're responsible for this and we're going to set it up and manage it for you, and we won't let you do things outside of it because that would mess up- >> Savannah: Here's your sandbox and- >> Right, this is your sandbox you can play in and a lot of times that's really useful and very tuned for the problems that you saw yesterday, but people are looking at like what are the problems I'm going to get tomorrow? We're deploying more rapidly. We have more and more intentional change happening in the system. Like it's not enough to have this reactive sort of approach where our SRE teams are kind of like or this observability team is building a platform for us. Developers want to be able to get in and have these kind of guided workflows really that say like, "Hey, here's where you're starting at. Let's get you to an answer. Let's help you find the needle in the haystack as it were, without you having to become a master of six different or seven different tools." >> Savannah: Right, and it shouldn't be that complicated. >> It shouldn't be. I mean we've certainly... We've been working on this problem for many years now, starting with a lot of our team that started at Google and helped build Google's planet scale monitoring systems. So we have a lot of experience in the field. It's actually one... An interesting story that our founder or now general manager tells BHS, Ben Sigelman, and he told me this story once and it's like... He had built this really cool thing called Dapper that was a tracing system at Google, and people weren't using it. Because they were like, "This is really cool, but I don't know how to... but it's not relevant to me." And he's like, the one thing that we did to get to increase usage 20 times over was we just put a link. So we went to the place that people were already looking for that data and we added a link that says, "Hey, go over here and look at this." It's those simple connections being able to kind of draw people from like point A to point B, take them from familiar workflows into unfamiliar ones. You know, that's how we think about these problems right? How is this becoming a daily part of someone's usage? How is this helping them solve problems faster and really improve their their life? >> Savannah: Yeah, exactly. It comes down to quality of life. >> Warner made the case this morning that computer architecture should be inherently event-driven and that we are moving toward a world where the person matters less than what the software does, right? The software is triggering events. Does this complicate observability or simplify it? >> Austin: I think that at the end of the day, it's about getting the... Observability to me in a lot of ways is about modeling your system, right? It's about you as a developer being able to say this is what I expect the system to do and I don't think the actual application architecture really matters that much, right? Because it's about you. You are building a system, right? It can be event driven, can be support request response, can be whatever it is. You have to be able to say, "This is what I expect to... For these given inputs, this is the expected output." Now maybe there's a lot of stuff that happens in the middle that you don't really care about. And then, I talk to people here and everyone's talking about serverless right? Everyone... You can see there's obviously some amazing statistics about how many people are using Lambda, and it's very exciting. There's a lot of stuff that you shouldn't have to care about as a developer, but you should care about those inputs and outputs. You will need to have that kind of intermediate information and understand like, what was the exact path that I took through this invented system? What was the actual resources that were being used? Because even if you trust that all this magic behind the scenes is just going to work forever, sometimes it's still really useful to have that sort of lower level abstraction, to say like, "Well, this is what actually happened so that I can figure out when I deployed a new change, did I make performance better or worse?" Or being able to kind of segregate your data out and say like... Doing AB testing, right? Doing canary releases, doing all of these things that you hear about as best practices or well architected applications. Observability is at the core of all that. You need observability to kind of do any of, ask any of those higher level interesting questions. >> Savannah: We are here at ReInvent. Tell us a little bit more about the partnership with AWS. >> So I would have to actually probably refer you to someone at Service Now on that. I know that we are a partner. We collaborate with them on various things. But really at Lightstep, we're very focused on kind of the open source part of this. So we work with AWS through the OpenTelemetry project, on things like the AWS distribution for OpenTelemetry which is really... It's OpenTelemetry, again is really designed to be like a neutral standard but we know that there are going to be integrators and implementers that need to package up and bundle it in a certain way to make it easy for their end users to consume it. So that's what Amazon has done with ADOT which is the shortening for it. So it's available in several different ways. You can use it as like an SDK and drop it into your application. There's Lambda layers. If you want to get Lambda observability, you just add this extension in and then suddenly you're getting OpenTelemetry data on the other side. So it's really cool. It's been a really exciting to kind of work with people on the AWS side over the past several years. >> Savannah: It's exciting, >> I've personally seen just a lot of change. I was talking to a PM earlier this week... It's like, "Hey, two years ago I came and talked to you about OpenTelemetry and here we are today. You're still talking about OpenTelemetry." And they're like, "What changes?" Our customers have started coming to us asking for OpenTelemetry and we see the same thing now. >> Savannah: Timing is right. >> Timing is right, but we see the same thing... Even talking to ServiceNow customers who are... These very big enterprises, banks, finance, healthcare, whatever, telcos, it used to be... You'd have to go to them and say like, "Let me tell you about distributed tracing. Let me tell you about OpenTelemetry. Let me tell you about observability." Now they're coming in and saying, "Yeah, so we're standard." If you think about Kubernetes and how Kubernetes, a lot of enterprises have spent the past five-six years standardizing, and Kubernetes is a way to deploy applications or manage containerized applications. They're doing the same journey now with OpenTelemetry where they're saying, "This is what we're betting on and we want partners we want people to help us go along that way." >> I love it, and they work hand in hand in all CNCF projects as well that you're talking about. >> Austin: Right, so we're integrated into Kubernetes. You can find OpenTelemetry and things like kept in which is application standards. And over time, it'll just like promulgate out from there. So it's really exciting times. >> A bunch of CNCF projects in this area right? Prometheus. >> Prometheus, yeah. Yeah, so we inter-operate with Prometheus as well. So if you have Prometheus metrics, then OpenTelemetry can read those. It's a... OpenTelemetry metrics are like a super set of Prometheus. We've been working with the Prometheus community for quite a while to make sure that there's really good compatibility because so many people use Prometheus you know? >> Yeah. All right, so last question. New tradition for us here on theCUBE. We're looking for your 32nd hot take, Instagram reel, biggest theme, biggest buzz for those not here on the show floor. >> Oh gosh. >> Savannah: It could be for you too. It could be whatever for... >> I think the two things that are really striking to me is one serverless. Like I see... I thought people were talking about servers a lot and they were talking about it more than ever. Two, I really think it is observability right? Like we've gone from observability being kind of a niche. >> Savannah: Not that you're biased. >> Huh? >> Savannah: Not that you're biased. >> Not that I'm biased. It used to be a niche. I'd have to go niche thing where I would go and explain what this is to people and nowpeople are coming up. It's like, "Yeah, yeah, we're using OpenTelemetry." It's very cool. I've been involved with OpenTelemetry since the jump, since it was started really. It's been very exciting to see and gratifying to see like how much adoption we've gotten even in a short amount of time. >> Yeah, absolutely. It's a pretty... Yeah, it's been a lot. That was great. Perfect soundbite for us. >> Austin: Thanks, I love soundbites. >> Savannah: Yeah. Awesome. We love your hat and your soundbites equally. Thank you so much for being on the show with us today. >> Thank you for having me. >> Savannah: Hey, anytime, anytime. Will we see you in Amsterdam, speaking of KubeCon? Awesome, we'll be there. >> There's some real exciting OpenTelemetry stuff coming up for KubeCon. >> Well, we'll have to get you back on theCUBE. (talking simultaneously) Love that for us. Thank you all for tuning in two hour wall to wall coverage here, day four at AWS re:Invent in fabulous Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)

(bright upbeat music) >> Well, hi everybody, John Wallace here and welcome to theCUBE, the leader in high-tech coverage. Glad to have you aboard here as we continue our coverage here at re:Invent 2022. We're out at The Venetian in Las Vegas. A lot of energy down on that exhibit floor, I promise you. We're a little bit away from the maddening crowd, but we're here with the Executive Summit sponsored by Accenture. I've got two guests I want to introduce you to. Jason Beyer who is the vice president of Data and Analytics at Bridgestone Americas. Jason, good to see you, sir. >> Hello, John. >> And Josh von Schaumburg, who is the managing director and North America lead for AWS Security at Accenture. Josh, good to see you. >> Thanks for having us. >> Yeah, first off, just quick take on the show. I know you've only been here about a day or so, but just your thoughts about what you're seeing on the floor in terms of energy, enthusiasm and, I think, turnout, right? I'm really impressed by it. We've got a lot of people down there. >> Yeah, I've been certainly impressed, John, with the turnout. But just as you say, the energy of the crowd, the excitement for the new things coming, it seems like it's a really pivotal moment for many organizations, including my own, and really excited to see what's coming over the next couple days. >> Let's jump into Bridgestone then. I kind of kidded you before we started the interview saying, all right, tires and golf balls, that's what I relate to, but you have a full array of consumer products and solution you're offering and your responsibility is managing the data and the analytics and making sure those business lines are as efficient as possible. >> Absolutely, John. So in my role, I have the privilege of being in an enterprise position. So I get to see the vast array of Bridgestone, which it is a large, highly vertically integrated company all the way from raw material sourcing of natural rubber to retail services in the automotive industry. We're at scale across those areas. The exciting thing about the company right now is we're going through this business transformation of becoming, you know, building on that heritage and that great legacy of having high quality high performance, highly focused on safety products to becoming a product and solutions company, and particular a sustainable solutions company. So what that means is we're bringing not only those great products to market, tires, golf balls, hoses, all kinds of rubber, air springs products to market, but thinking about how do we service those after they're in the market, how do we bring solutions to help fleets, vehicle owners, vehicle operators operate those in a sustainable way, in a cost effective way? So those solutions, of course, bring all new sets of data and analytics that come with it, and technology and moving to the cloud to be cloud native. So this new phase for the organization that we refer to as Bridgestone 3.0, and that business strategy is driving our cloud strategy, our technology strategy, and our data strategy and AWS and Accenture are important partners in that. >> Yeah, so we hear a lot about that these days about this transformation, this journey that people are on now. And Josh, when Bridgestone or other clients come to you and they talk about their migrations and what's their footprint going to look like and how do they get there, in the case of Bridgestone when they came to you and said, "All right, this is where we want to go with this. We're going to embark on a significant upgrade of our systems here," how do you lead 'em? How do you get 'em there? >> Yeah, I think there are a couple key cloud transformation value drivers that we've emphasized and that I've seen at Bridgestone in my time there. I mean, number one, just the rapid increase in the pace of innovation that we've seen over the last couple years. And a lot of that is also led by the scalability of all of the cloud native AWS services that we're leveraging, and in particular with the CDP platform. It really started off as a single-use case and really a single-tenant data lake. And then through the strategic vision of Jason and the leadership team, we've been able to expand that to 10 plus tenants and use cases. And a big reason behind that is the scalability of all these AWS services, right? So as we add more and more tenants, all the infrastructure just scales without any manual provisioning any tuning that we need to do. And that allows us to go really from idea, to POC, to production in really a matter of months when traditionally it might take years. >> So- >> If I can build upon that. >> Please do, yeah. >> The CDP, or central data platform, is part of a broader reference architecture that reflects that business strategy. So we looked at it and said, we could have taken a couple of different approaches to recognize the business challenges we're facing. We needed to modernize our core, our ERP, our manufacturing solutions move to smart factory and green factories, our PLM solutions. But at the same time, we're moving quickly. We have a startup mindset in our mobility solutions businesses where we're going to market on our customer and commerce solutions, and we needed to move at a different pace. And so to decouple those, we, in partnership with Accenture and AWS, built out a reference architecture that has a decoupling layer that's built around a data fabric, a data connected layer, integrated data services as well. A key part of that architecture is our central data platform built on AWS. This is a comprehensive data lake architecture using all the modern techniques within AWS to bring data together, to coalesce data, as well as recognize the multiple different modes of consumption, whether that's classic reporting, business intelligence, analytics, machine learning data science, as well as API consumption. And so we're building that out. A year ago it was a concept on a PowerPoint and just show and kind of reflect the innovation and speed. As Josh mentioned, we're up to 10 tenants, we're growing exponentially. There's high demand from the organization to leverage data at scale because of the business transformation that I mentioned and that modernization of the core ecosystem. >> That's crazy fast, right? And all of a sudden, whoa! >> Faster than I expected. >> Almost snap overnight. And you raise an interesting point too. I think when you talk about how there was a segment of your business that you wanted to get in the startup mode, whereas I don't think Bridgestone, I don't think about startup, right? I think in a much more, I wouldn't say traditional, but you've got big systems, right? And so how did you kind of inject your teams with that kind of mindset, right? That, hey, you're going to have to hit the pedal here, right? And I want you to experiment. I want you to innovate. And that might be a little bit against the grain from what they were used to. >> So just over two years ago, we built and started the organization that I have the privilege of leading, our data and analytics organization. And it's a COE. It's a center of expertise in the organization. We partner with specialized teams in product development, marketing, other places to enable data and analytics everywhere. We wanted to be pervasive, it's a team sport. But we really embraced at that moment what we refer to as a dual speed mindset. Speed one, we've got to move at the speed of the business. And that's variable. Based on the different business units and lines of lines of business and functional areas, the core modernization efforts, those are multi-year transformation programs that have multiple phases to them, and we're embedded there building the fundamentals of data governance and data management and reporting operational things. But at the same time, we needed to recognize that speed of those startup businesses where we're taking solutions and service offerings to market, doing quick minimum viable product, put it in a market, try it, learn from it adapt. Sometimes shut it down and take those learnings into the next area as well as joint ventures. We've been much more aggressive in terms of the partnerships in the marketplace, the joint ventures, the minority investments, et cetera, really to give us that edge in how we corner the market on the fleet and mobility solutions of the future. So having that dual speed approach of operating at the speed of the business, we also needed to balance that with speed two, which is building those long term capabilities and fundamentals. And that's where we've been building out those practical examples of having data governance and data management across these areas, building robust governance of how we're thinking about data science and the evolution of data science and that maturity towards machine learning. And so having that dual speed approach, it's a difficult balancing act, but it's served us well, really partnering with our key business stakeholders of where we can engage, what services they need, and where do we need to make smart choices between those two different speeds. >> Yeah, you just hit on something I want to ask Josh about, about how you said sometimes you have to shut things down, right? It's one thing to embark on I guess a new opportunity or explore, right? New avenues. And then to tell your client, "Well, might be some bumps along the way." >> Yeah. >> A lot of times people in Jason's position don't want to hear that. (laughs) It's like, I don't want to hear about bumps. >> Yeah. >> We want this to be, again, working with clients in that respect and understanding that there's going to be a learning curve and that some things might not function the way you want them to, we might have to take a right instead of a left. >> Yeah, and I think the value of AWS is you really can fail fast and try to innovate and try different use cases out. You don't have any enormous upfront capital expenditure to start building all these servers in your data center for all of your use cases. You can spin something up easily based in idea and then fail fast and move on to the next idea. And I also wanted to emphasize I think how critical top-down executive buy-in is for any cloud transformation. And you could hear it, the excitement in Jason's voice. And anytime we've seen a failed cloud transformation, the common theme is typically lack of executive buy-in and leadership and vision. And I think from day one, Bridgestone has had that buy-in from Jason throughout the whole executive team, and I think that's really evident in the success of the CDP platform. >> Absolutely. >> And what's been your experience in that regard then? Because I think that's a great point Josh raised that you might be really excited in your position, but you've got to convince the C-suite. >> Yeah. >> And there are a lot of variables there that have to be considered, that are kind of out of your sandbox, right? So for somebody else to make decisions based on a holistic approach, right? >> I could tell you, John, talking with with peers of mine, I recognize that I've probably had a little bit of privilege in that regard because the leadership at Bridgestone has recognized to move to this product and solutions organization and have sustainable solutions for the future we needed to move to the cloud. We needed to shift that technology forward. We needed to have a more data-driven approach to things. And so the selling of that was not a huge uphill a battle to be honest. It was almost more of a pull from the top, from our global group CEO, from our CEOs in our different regions, including in Bridgestone Americas. They've been pushing that forward, they've been driving it. And as Josh mentioned, that's been a really huge key to our success, is that executive alignment to move at this new pace, at this new frame of innovation, because that's what the market is demanding in the changing landscape of mobility and the movement of vehicles and things on the road. >> So how do you two work together going forward, Ben? Because you're in a great position now. You've had this tremendous acceleration in the past year, right? Talking about this tenfold increase and what the platform's enabled you to do, but as you know, you can't stand still. Right? (laughs) >> Yeah. There's so much excitement, so many use cases in the backlog now, and it's really been a snowball effect. I think one of the use cases I'm most excited about is starting to apply ML, you know, machine learning to the data sets. And I think there's an amazing IoT predictive maintenance use case there for all of the the censored data collected across all of the tires that are sold. There's an immense amount of data and ultimately we can use that data to predict failures and make our roads safer and help save lives >> Right. >> It's hard to not take a long time to explain all the things because there is a lot ahead of us. The demand curve for capabilities and the enabling things that AWS is going to support is just tremendous. As Josh mentioned, the, the AI ML use cases ahead of us, incredibly exciting. The way we're building and co-innovating things around how we make data more accessible in our data marketplace and more advanced data governance and data quality techniques. The use of, you know, creating data hubs and moving our API landscape into this environment as well is going to be incredibly empowering in terms of accessibility of data across our enterprise globally, as well as both for our internal stakeholders and our external stakeholders. So, I'll stop there because there's a lot of things in there. >> We could be here a long time. >> Yes, we could. >> But it is an exciting time and I appreciate that you're both sharing your perspectives on this because you've got a winning formula going and look forward to what's happening. And we'll see you next year right back here on the Executive Summit. >> Absolutely. >> To measure the success in 2023. How about that? >> Sounds good, thank you, Jim. >> Is that a deal? >> Awesome. >> Sounds good. >> Excellent, good deal. You've been watching AWS here at Coverage of Reinvent '22. We are the Executive Summit sponsored by Accenture and you are watching theCUBE, the leader in high tech coverage. 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from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante over the past decade cloudflare has built a Global Network that has the potential to become the fourth us-based hyperscale class cloud in our view the company is building a durable Revenue model with hooks into many important markets these include the more mature DDOS protection space to other growth sectors such as zero trust a serverless platform for application development and an increasing number of services such as database and object storage and other network services in essence cloudflare could be thought of as a giant distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine at scale its disruptive DNA is increasingly attracting novel startups and established Global firms alike looking for Reliable secure high performance low latency and more cost-effective alternatives to AWS and Legacy infrastructure Solutions hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we initiate our deeper coverage of cloudflare we'll briefly explain our take on the company and its unique business model we'll then share some peer comparisons with both the financial snapshot and some fresh ETR survey data finally we'll share some examples of how we think cloudflare could be a disruptive force with a super cloud-like offering that in many respects is what multi-cloud should have been cloudflare has been on our peripheral radar Ben Thompson and many others have written about their disruptive business model and recently a breaking analysis follower who will remain anonymous emailed with some excellent insights on cloudflare that prompted us to initiate more detailed coverage let's first take a look at how cloudflare seize the world in terms of its view of a modern stack this is a graphic from cloudflare that shows a simple three-layer Stack comprising Storage and compute the lower level and application layer and the network and their key message is basically that the big four hyperscalers have replaced the on-prem leaders apps have been satisfied and that mess of network that you see and Security in the upper left can now be handled all by cloudflare and the stack can be rented via Opex versus requiring heavy capex investment so okay somewhat of a simplified view is those companies on the the left are you know not standing still and we're going to come back to that but cloudflare has done something quite amazing I mean it's been a while since we've invoked Russ hanneman of Silicon Valley Fame on breaking analysis but remember when he was in a meeting one of his first meetings if not the first with Richard Hendricks it was the whiz kid on the show Silicon Valley and hanneman said something like if you had a blank check and you could build anything in the world what would it be and Richard's answer was basically a new internet and that led to Pied Piper this peer-to-peer Network powered by decentralized devices and and iPhones and this amazing compression algorithm that enabled high-speed data movement and low latency uh up to no low latency access across the network well in a way that's what cloudflare has built its founding premise reimagined how the internet should be built with a consistent set of server infrastructure where each server had lots of cores lots of dram lots of cash fast ssds and plenty of network connectivity and bandwidth and well this picture makes it look like a bunch of dots and points of presence on a map which of course it is there's a software layer that enables cloudflare to efficiently allocate resources across this Global Network the company claims that it's Network utilization is in the 70 percent range and it has used its build out to enter the technology space from the bottoms up offering for example free tiers of services to users with multiple entry points on different services and selling then more services over time to a customer which of course drives up its average contract value and its lifetime value at the same time the company continues to innovate and add new services at a very rapid cloud-like Pace you can think of cloudflare's initial Market entry as like a lightweight Cisco as a service the company's CFO actually he uses that term he calls it that which really must tick off Cisco who of course has a massive portfolio and a dominant Market position now because it owns the network cloudflare is a marginal cost of adding new Services is very small and goes towards zero so it's able to get software like economics at scale despite all this infrastructure that's building out so it doesn't have to constantly face the increasing infrastructure tax snowflake for example doesn't own its own network infrastructure as it grows it relies on AWS or Azure gcp and and while it gives the company obvious advantages it doesn't have to build out its own network it also requires them to constantly pay the tax and negotiate with hyperscalers for better rental rates now as previously mentioned Cloud Fair cloudflare claims that its utilization is very high probably higher than the hyperscalers who can spin up servers that they can charge for underutilized customer capacity cloudflare also has excellent Network traffic data that it can use to its Advantage with its Analytics the company has been rapidly innovating Beyond its original Core Business adding as I said before serverless zero trust offerings it has announced a database it calls its database D1 that's pretty creative and it's announced an object store called R2 that is S3 minus one both from the alphabet and the numeric I.E minus the egress cost saying no egress cost that's their big claim to fame and they've made a lot of marketing noise around about that and of course they've promised in our a D2 database which of course is R2D2 RR they've launched a developer platform cloudflare can be thought of kind of like first of all a modern CDN they've got a simpler security model that's how they compete for example with z-scaler that brings uh they also bring VPN sd-wan and DDOS protection services that are that are part of the network and they're less expensive than AWS that's kind of their sort of go to market and messaging and value proposition and they're positioning themselves as a neutral Network that can connect across multiple clouds now to be clear unlike AWS in particular cloudflare is not well suited to lift and shift your traditional apps like for instance sap Hana you're not going to run that in on cloudflare's platform rather the company started by making websites more secure and faster and it flew under the radar and much in the same way that clay Christensen described the disruption in the steel industry if you've seen that where new entrants picked off the low margin rebar business then moved up the stack we've used that analogy in the semiconductor business with arm and and even China cloudflare is running a similar playbook in the cloud and in the network so in the early part of the last decade as aws's ascendancy was becoming more clear many of us started thinking about how and where firms could compete and add value as AWS is becoming so dominant so for instance take an industry Focus you could do things like data sharing with snowflake eventually you know uh popularized you could build on top of clouds again snowflake is doing that as are others you could build private clouds and of course connect to hybrid clouds but not many had the wherewithal and or the hutzpah to build out a Global Network that could serve as a connecting platform for cloud services cloudflare has traction in the market as it adds new services like zero trust and object store or database its Tam continues to grow here's a quick snapshot of cloudflare's financials relative to Z scalar which is both a competitor and a customer fastly which is a smaller CDN and Akamai a more mature CDN slash Edge platform cloudflare and fastly both reported earnings this past week Cloud Fair Cloud flare surpassed a billion dollar Revenue run rate but they gave tepid guidance and the stock got absolutely crushed today which is Friday but the company's business model is sound it's growing close to 50 annually it has sas-like gross margins in the mid to high 70s and it's it it's got a very strong balance sheet and a 13x revenue run rate multiple in fact it's Financial snapshot is quite close to that of z-scaler which is kind of interesting which zinc sailor of course doesn't own its own network that's a pure play software company fastly is much smaller and growing more slowly than cloudflare hence its lower multiple well Akamai as you can see is a more mature company but it's got a nice business now on its earnings call this week cloudflare announced that its head of sales was stepping down and the company has brought in a new leader to take the firm to five billion dollars in sales I think actually its current sales leader felt like hey you know my work is done here bring on somebody else to take it to the next level the company is promising to be free cash flow positive by the end of the year and is working hard toward its long-term financial model or so working towards sorry it's a long-term financial model with gross margin Targets in the mid 70s it's targeting 20 non-gaap operating margins so so solid you know very solid not like completely off the charts but you know very good and to our knowledge it has not committed to a long-term growth rate but at that sort of operating profit level you would like to see growth be consistently at least in the 20 range so they could at least be a rule of 40 company or perhaps even even five even higher if they're going to continue to command a premium valuation okay let's take a look at the ETR data ETR is very positive on cloudflare and has recently published a report on the company like many companies cloudflare is seeing an across the board slowdown in spending velocity we've reported on this quite extensively using the ETR data to quantify the degree to that Slowdown and on the data set with ETR we see that many customers they're shifting their spend to Flat spend you know plus or minus let's say you know single digits you know two three percent or even zero or in the market we're seeing a shift from paid to free tiers remember cloudflare offers a lot of free services as you're seeing customers maybe turn off the pay for a while and going with the freebie but we're also seeing some larger customers in the data and the fortune 1000 specifically they're actually spending more which was confirmed on cloudflare's earnings call they did say everything across the board was softer but they did also indicate that some of their larger customers are actually growing faster than their smaller customers and their churn is very very low here's a two-dimensional graphic we'd like to share this view a lot it's got Net score or spending momentum on the vertical axis and overlap or pervasiveness in the survey on the horizontal axis and this cut isolates three segments in the etrs taxonomy that cloudflare plays in Cloud security and networking now the table inserted in that upper left there shows the raw data which informs the position of each company in the dots with Net score in the ends listed in that rightmost column the red dotted line indicates a highly elevated Net score and finally we posted the breakdown those colors in the bottom right of cloudflare's Net score the lime green that's new adoptions the forest green is we're spending more six percent or more the gray is flat plus or minus uh five percent and you can see that the majority of customers you can see that's the majority of the customers that gray area the pink is we're spending Less in other words down six percent or worse and the bright red is churn which is minimal one percent very good indicator for for cloudflare what you do to get etr's proprietary Net score and they've done this for many many quarters so we have that time series data you subtract the Reds from the greens and that's Net score cloudflare is at 39 just under that magic red line now note that cloudflare and zscaler are right on top of each other Cisco has a dominant position on the x-axis that cloudflare and others are eyeing AWS is also dominant but note that its Net score is well above the red dotted line it's incredible Palo Alto networks is also very impressive it's got both a strong presence on the horizontal axis and it's got a Net score that's pretty comparable to cloudflare and z-scaler to much smaller companies Akamai is actually well positioned for a reasonably mature company and you can see fastly ATT Juniper and F5 have far less spending momentum on their platforms than does cloudflare but at least they are in positive Net score territory so what's going to be really interesting to see is whether cloudflare can continue to hold this momentum or even accelerate it as we've seen with some other clouds as it scales its Network and keeps adding more and more services cloudflare has a couple of potential strategic vectors that we want to talk about and it'll be going to be interesting to see how that plays out Now One path is to compete more directly as a Cloud Player offering secure access Edge services like firewall as a service and zero Trust Services like data loss prevention email security from its area one acquisition and other zero trust offerings as well as Network Services like routing and network connectivity this is The Sweet Spot of the company load balancing many others and then add in things like Object Store and database Services more Edge services in the future it might be telecom like services such as Network switching for offices so that's one route and cloudflare is clearly on that path more services more cohorts at innovating and and growing the company and bringing in more Revenue increasing acvs and and increasing long-term value and keeping retention high now the other Vector is what we're just going to refer to as super cloud as an enabler of cross-cloud infrastructure this is new value uh relative to the former Vector that we were just talking about now the title of this episode is what multi-cloud should have been meaning cloudflare could be the control plane providing a consistent experience across clouds one that is fast and secure at global scale now to give you Insight on this let's take a look at some of the comments made by Matthew Prince the CEO and co-founder of cloudflare cloudflare put its R2 Object Store into public beta this past May and I believe it's storing around a petabyte of data today I think that's what they said in their call here's what Prince said about that quote we are talking to very large companies about moving more and more of their stored objects to where we can store that with R2 and one of the benefits is not only can we help them save money on the egress fees but it allows them to then use those object stores or objects across any of the different Cloud platforms they're that they're using so by being that neutral third party we can let people adopt a little bit of Amazon a little bit of Microsoft a little bit of Google a little bit of SAS vendors and share that data across all those different places so what's interesting about this in the super cloud context is it suggests that customers could take the best of each Cloud to power their digital businesses I might like AWS for in redshift for my analytic database or I love Google's machine learning Microsoft's collaboration and I'd like a consistent way to connect those resources but of course he's strongly hinting and has made many public statements that aws's egress fees are a blocker to that vision now at a recent investor event Matthew Prince added some color to this concept when he talked about one metric of success being how much R2 capacity was consumed and how much they sold but perhaps a more interesting Benchmark is highlighted by the following statement that he made he said a completely different measure of success for R2 is Andy jassy says I'm sick and tired of these guys meaning cloudflare taking our objects away we're dropping our egress fees to zero I would be so excited because we've then unlocked the ability to be the network that interconnects the cloud together now of course it would be Adam solipski who would be saying that or maybe Andy Jesse you know still watching over AWS and I think it's highly unlikely that that's going to happen anytime soon and that of course but but in theory gets us closer to the super cloud value proposition and to further drive that point home and we're paraphrasing a little bit his comments here he said something the effect of quote customers need one consistent control plane across clouds and we are the neutral Network that can be consistent no matter which Cloud you're using interesting right that Prince sees the world that's similar to if not nearly identical to the concepts that the cube Community has been putting forth around supercloud now this vision is a ways off let's be real Prince even suggested that his initial vision of an application running across multiple clouds you know that's like super cloud Nirvana isn't what customers are doing today that's that's really hard to do and perhaps you know it's never going to happen but there's a little doubt that cloudflare could be and is positioning itself as that cross-cloud control plane it has the network economics and the business model levers to pull it's got an edge up on the competition at the edge pun intended cloudflare is the definition of Edge and it's distributed platform it's decentralized platform is much better suited for Edge workloads than these giant data centers that are you know set up to to try and handle that today the the hyperscalers are building out you know their Edge networks things like outposts you know going out to the edge and other local zones Etc now cloudflare is increasingly competitive to the hyperscalers and those traditional Stacks that it depositioned on an earlier slide that we showed but you know the likes of AWS and Dell and hpe and Cisco and those others they're not sitting in their hands they have a huge huge customer install bases and they are definitely a moving Target they're investing and they're building out their own Super clouds with really robust stacks as well let's face it it's going to take a decade or more for Enterprises to adopt a developer platform or a new database Cloud plus cloudflare's capabilities when compared to incumbent stacks and the hyperscalers is much less robust in these areas and even in storage you know despite all the great conversation that R2 generated and the buzz you take a specialist like Wasabi they're more mature they're more functional and they're way cheaper even than cloudflare so you know it's not a fake a complete that cloudflare is going to win in those markets but we love the disruption and if cloudflare wants to be the fourth us-based hyperscaler or join the the big four as the as the fifth if we put Alibaba in the mix it's got a lot of work to do in the ecosystem by its own admission as much to learn and is part of the value by the way that it sees in its area one acquisition it's email security company that it bought but even in that case much of the emphasis has been on reseller channels compare that to the AWS ecosystem which is not only a channel play but is as much an innovation flywheel filling gaps where companies like snowflake Thrive side by side with aws's data stores as well all the on-prem stacks are building hybrid connections to AWS and other clouds as a means of providing consistent experiences across clouds indeed many of them see what they call cross-cloud services or what we call super cloud hyper cloud or whatever you know Mega Cloud you want to call it we use super cloud they are really eyeing that opportunity so very few companies frankly are not going after that space but we're going to close with this cloudflare is one of those companies that's in a position to wake up each morning and ask who can we disrupt today and very few companies are in a position to disrupt the hyperscalers to the degree that cloudflare is and that my friends is going to be fascinating to watch unfold all right let's call it a wrap I want to thank Alex Meyerson who's on production and manages the podcast as well as Ken schiffman who's our newest addition to the Boston Studio Kristen Martin and Cheryl Knight help us get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at silicon angle thank you to all remember all these episodes are available as podcasts wherever you listen all you're going to do is search breaking analysis podcasts I publish each week on wikibon.com and siliconangle.com you can email me at david.velante at siliconangle.com or DM me at divalante if you comment on my LinkedIn posts and please do check out etr.ai they got the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thank you very much for watching and we'll see you next time on breaking analysis

>>Welcome back to super cloud 22, our inaugural event. It's a pilot event here in the cube studios we're live and streaming virtually until we do it in person. Maybe next year. I'm John fury, host of the cube with Dave Lon two great guests, distinguished engineers managers, CTOs investors. Mariana Tessel is a CTO of Intuit ins Ray founder of vertex ventures. Both have a lot of DNA. Founder allow cloud here with mark Andre and Ben Horowitz, a variety of other great ventures you've done. And now you're an investor. Yep. Maria, you've been a seasoned CTO, VP of engineering, VMware Docker Intuit. Now thanks for joining us. >>Absolutely. >>So super cloud is a, is a thing. And apparently it's got a lot of momentum and you guys got stats over there at, at Intuit in, so you're investing and we were challenged on super cloud. Our initial thesis was you build on the clouds, get all that leverage like snowflake, you get a good differentiation and then you compete and then move to other clouds. Now it's becoming a thing where I can do this. Every enterprise could possibly do it. So I want to get your guys thoughts on what you think of super cloud concept and where are the holes in it, what needs to be defined. And so we'll start with you. You've done a lot of cloud things in your day. What >>Do you think? Yeah, it's the whole cloud journey started with a desire to consolidate and desire to actually provide uniformity and, and standards driven ways of doing things. And I think Amazon was a leader there. They helped kind of teach everybody else. You know, when I was in loud cloud, we were trying to do it with proprietary stacks just wouldn't work. But once everyone standardized upon Unix and you know, the chip sets no longer became as relevant. They did a lot of good things there, but what's happened since then is now you've got competing standards at the API layer at the interface layer no longer at the chip set layer, no longer at the operating system layer. Right? So the evolution of the, the, the battles are still there. When you talk about multicloud and super cloud, though, like one of the big things you have to keep in mind is latency is not free. Latency is very expensive and it's getting even more expensive now with, with multi-cloud. So you have to really understand where the separations of boundaries are between your data, your compute, and, and the network is just there as a facilitator to help binding compute and data. Right? And I think there's a lot of bets being made across different vendors like CloudFlare Akamai, as well as Amazon Google Microsoft in terms of how they think we should take computing either to the edge, from the core or back and forth. >>These, this is structural change. I mean, this is structural, >>It's desired by incumbents, but it's not something that I'm seeing from the consumption. I'd love to hear, hear from our end's per perspective, from a consumption point of view, like how much edge computing really matters. Right. >>Mario. >>So I think there's like, there's kind of a, a story of like two, like it's kind of, you can cut it for both edges. No, no pun intended on one end. It is really simplifying to actually go into like a single cloud and standardize on it and just have everything there. But I think what over time companies find is that they end up in multiple clouds, whether like, you know, through acquisitions or through like needing to use a service in another cloud. So you do find yourself in a situation where you have multi multi-cloud and you have to kind of work through it and understand how to make it all like work and latency is an issue, but also for many, many workloads, you can work around it and you can make it work where you have workloads that actually span multiple vendors and clouds. You know, again, having said that, I would say the world is such, that is still a simplifying assumption. When if you go to a single cloud, it's much easier to just go and, and bet on that >>Easier in terms of everything's integrated, IAS works with SAS, they solve a lot of problems. >>Correct. And you can do like for your developers, you can actually provide an environment that's super homogenous, simple. You can use services easily up and down the stack. And, you know, we, we actually made that deliberate decision. When we started migrating to the cloud at the beginning, it was like, oh, let's do like hybrid we'll, you know, make it, so it work anywhere. It was so complicated. It was not worth it. >>When was the, when did you give up, what was the moment? Was there a flash point where you said, oh, this is terrible. This is >>Dead. Yeah. When, when we started to try to make it interoperable and you just see what it requires to do that and the complexity of the architecture that it just became not worth it for the gains you have. >>So speaking obviously as a SAS provider, right. So it just doesn't, it didn't make business case sense for you guys to do that. So it was super cloud. Then an infrastructure thing we just heard from Ben wa deja VI that they're not, they're going beyond instantiating their, their data cloud. They're actually running, you know, their own little snow grid. They called it. And, and then when I asked him, well, what about latency? He said, well, we copied data over, you know, so, okay. That's you have to do, but that's a singular experience with the same governance or the same security. Just wasn't worth it for you guys is what I'm hearing. >>Correct. But again, like for some workload or for some services that we want to use, we are gonna go there and we are gonna then figure out what is the work around the latency issue, whether it's like copy or, you know, redundancy. >>Well, the question I have Dave on snowflake is maybe the question for you and in the panel is snowflake a tan expansion opportunity, or is there a technical reason to go to other clouds? >>I think they wanted to leverage the hyperscale infrastructure globally. And they said that they're out there, it's a free gift. We're gonna go take it. I, I think it started with we're on AWS. Do you think? And then we're on Azure and then we're on Google. And then they said, why don't we just connect all these and make it a singular experience? And yeah, I guess it's a TA expansion as a differentiator and it's, it adds value. Right. If I can share data across that global network, >>We have customers on Azure now, >>Right? Yeah. Yeah. Of course. >>You guys don't need to go CP. What do you think about that? >>Well, I think Snowflake's in a good position cuz they work mostly with analytical workloads and you have capacity. That's always gonna increase like no one subtracts, their analytical workload like ever, right. So there was just compounded growth is like 50% or 80% for, you know, many enterprises despite their best intentions, not to collect more data, they just can't stop doing it. So it's different than if you're like an Oracle or a transactional database where you don't have those, you know, like kind of infinite growth paths. So Snowflake's gonna continue to expand footprint their customers. They don't mind as long as you, they can figure out the, the lowest cost on denominator for, for that. >>Yeah. So it makes sense to be in all the clouds >>For them, for, for them, for sure. Yeah. >>But, but, but Oracle just announced with Microsoft what I would call super cloud, a, a cross cloud database service running on OCI and Azure with very low latency and a database that looks like a, the singular experience. Yeah. With, with a PAs layers >>That lost me after OCI that's >>Okay. You know, but that's the, that's the, the BS answer for all U VCs. The do nobody develops on Oracle? Well, it's a 240 billion market cap company. Show me who you all want be. >>We're gonna talk about SRDF and em C next, you >>All want Oracle. So there we go. You throw that into, you all want Oracle to buy your companies, your funding, you know, cause, cause we all wanna be like Oracle with that kinda cash flow. But, but anyway, >>Here's, here's one thing that I'm noticing that is gonna be really practical. I think for companies that do run SA is because like, you know, you have all these solutions, whether it's like analytics or like monitoring or logging or whatever. And each one of them is very data hungry and all of them have like SAS solutions that end up copy the data, moving data to their cloud, and then they might charge you by the size of your data. It does become kind of overwhelming for companies to use that many tools and basically maybe have that data kind of charge for it, multiple places because you use it for different purposes or just in general, if you have a lot of data, you know, that that is becoming an issue. So that's something that I've noticed in our, in our own kind of, you know, a world, but it's just something that I think companies need to think about how they solve because eventually a lot of companies will say, I cannot have all these solutions, so there's no way I'm gonna be willing to have so many copies of the data and actually pay for that. >>So many times, just something to think about. >>But one of the criticisms of the super cloud concept is that it's just SAS. If I'm running workload on prem and I, and I've got, you know, a connection to the cloud, which you probably do, that's, that's SAS, what's, what's the big deal and that's not anything new or different. So I'd love to get your thoughts on that. But Goldman Sachs, for instance, just announced the service last reinvent with AWS, connecting their tools, their data, and their software from on-prem to AWS, they're offering it as a service. I'm like, Hmm. Kind of looking like Supercloud, but maybe it's just SAS. >>It could be. And like, what I'm talking about is not so much like, you know, like what you wanna connect your data. But the idea is like a lot of the providers of different services, like in the past and, and like higher layer, they're actually COPI the data. They need the data in their cloud or their solution. And it just becomes complicated and expensive is, is kind of like my point. So yes, connecting it like for you to have the data in one place and then be able to connect to it. I think that is a valid, if, if that's kinda what you think about as a super cloud, that is a valid need, I think that companies will >>Have where developers actually want access to tools that might exist. >>Also the key is developers, right? Yeah. Developers decide all decisions, not database on administrators, not, you know, a hundred percent security engineers, not admins. So what's really interesting is where are the developers going next? If you look at the current winners in the current ecosystem, companies like MongoDB, I mean, they capture the minds of yeah. The JavaScript, you know, no JS developers absolutely very early on. And I started catch base and I could tell you like the difference was that capture motion was so important. So developers are basically used to this game-like experience now where they want to see tools that are free, whether it's open source or not, they actually don't care. They just want, and they want it SAS. They want it SAS delivered on demand. Right. And pay as you go. And so there's a lot of these different frameworks coming out next generation, no code, low code, whether it's Java, JavaScript, rust, you know, whatever, you know, go Lang. And there's a lot of people fighting religious wars about how to develop the next kind of modern pattern design pattern. Okay. And that's where a lot of excitement is how we look at like investment opportunities. Like where are those big bets who are, you know, frustrated developers, who are they frustrated, what's wrong with their current environment? You know, do they really enjoy using Kubernetes or trying to use Kubernetes? Yeah. Right. Like developers have a very different view than operator, >>But you mentioned couch base. I mean, I look at couch base what they're doing with Capellas as a form of Supercloud. I mean, I think that's an excellent, they're bringing that out to the edge. We're gonna hear later on from someone from couch base. That's gonna talk about that now. It's kind of a lightweight, you know, sort of, it's gonna be a, a synchronization, but it's the beginning >>A cool new venture deal that I'm not in, but was like duck DB. I'm like, what's duck DB like, well, it's an Emory database that has like this like remote store thing. I'm like, okay, that sounds interesting. Like let's call Mike Olson cuz that sounds like sleepy cat redone red distributed world. But like it's, it's like there's a lot of people refactoring design patterns that we're all grew up with since the popup days of, you know, typical round. Right? >>Yeah. That's the refactory I think that's the big pattern. So I have to ask you guys, what are you guys investing in? We've got a couple minutes left to chat about that. What are you investing at into it from a, from a, a CTO engineering perspective and what are you investing in that feels super cloud like to you? >>Well, the, the thing that like I'm focused on is to make sure that we have absolutely best in the world development environment for our engineers, where it's modern, it's easy to use and it incorporates as many things as we can into that environment. So the engineers don't have to think about it. Like one big example would be security and how we incorporated that into development environment. So again, the engineers don't have to bother with trying to think through how they secure their workloads and every step of the way their other things that we incorporated, whether it's like rollbacks or monitoring or, you know, like baly enough other things. But I think that's really an investment that has panned off for us. We actually started investing in development environment several years ago. We started measure our development velocity and we, it actually went up by six X justly investing. So >>User experience, developer experience and productivity pretty much right. >>Yeah. AB absolutely. Yeah. That's like a big investment area for us that, you know, cloud cloud >>Sounds like super cloudlike factor and I'm assuming it's you're on AWS. >>We are mostly on AWS. Yes. >>And so what are you investing in that from a VC money doling out standpoint? That feels super cloudlike >>So very similar to what we just touched on a lot of developer tool experiences. We have a company that we've invested in called ops level that the service catalogs it's, it's helping, you know, understand your, where your services live and how they could be accessed and, and you know, enterprise kind of that come with that. And then we have a company called Lugo that helps you do serverless debugging container debugging, cuz it turns out debugging distributed, you know, applications is a real problem right now just you can only do so much by log tracing, right? We have a company haven't announced yet that's in the web assembly space. So we're looking at modernizing the next generation past stack and throwing everything out the window, including Java and all of the, you know, current prebuilt components because turns out 90% of enterprise workloads are actually not used. They're they're just policy code. You compiled with they're sitting there as vulnerabilities that no one's actually accessing, but you still have to compile with all of it. So we have a lot of bloatware happening in the enterprise. So we're thinking about how do you skinny that up with the next generation paths that's enterprise capable with security context and frameworks >>Super pass. >>Well, yeah, super pass. That's a kind of good way to, well, is >>It, is it a consistent developer experience across clouds? >>It is. And, and, and, and web assembly is a very raw standard if you can call it that. I mean it's, but it's supported by every modern browser, every major platform, vendor cloud, and Adobe and others, and are using it for their uses. And it's not just about your edge browser compute. It's really, you can take the same framework and compile it down to server side as well as client site, just like JavaScript was a client side tool before it became node. Right. Right. So we're looking at that as a very interesting opportunity. It's very nascent. Yeah. >>Great patterns. Yeah. Well, thanks so much for spending the time outta your busy day. Ariana. Thanks for your commentary. Appreciate your coming on the cubes first in IGUR super cloud event, pilot. Thanks for, for sharing. Thanks for having, thanks for having us. Okay. More coverage here. Super cloud 2022. I'm Jeff David Alane stay with us. We got our cloud ARA panel coming up next.

>>Good morning, everyone. Welcome to the cubes day two coverage of VMware Explorer, 2022 live from San Francisco. Lisa Martin here with Dave Nicholson. We're excited to kick off day two of great conversations with VMware partners, customers it's ecosystem. We've got a V an alumni back with us Kumer on Siva corporate VP of business development from AMD joins us. Great to have you on the program in person. Great >>To be here. Yes. In person. Indeed. Welcome. >>So the great thing yesterday, a lot of announcements and B had an announcement with VMware, which we will unpack that, but there's about 7,000 to 10,000 people here. People are excited, ready to be back, ready to be hearing from this community, which is so nice. Yesterday am B announced. It is optimizing AMD PON distributed services card to run on VMware. Bsphere eight B for eight was announced yesterday. Tell us a little bit about that. Yeah, >>No, absolutely. The Ben Sando smart neck DPU. What it allows you to do is it, it provides a whole bunch of capabilities, including offloads, including encryption DEC description. We can even do functions like compression, but with, with the combination of VMware project Monterey and, and Ben Sando, we we're able to do is even do some of the vSphere, actual offloads integration of the hypervisor into the DPU card. It's, it's pretty interesting and pretty powerful technology. We're we're pretty excited about it. I think this, this, this could, you know, potentially, you know, bring some of the cloud value into, in terms of manageability, in terms of being able to take care of bare metal servers and also, you know, better secure infrastructure, you know, cloudlike techniques into the, into the mainstream on-premises enterprise. >>Okay. Talk a little bit about the DPU data processing unit. They talked about it on stage yesterday, but help me understand that versus the CPU GPU. >>Yeah. So it's, it's, it's a different, it's a different point, right? So normally you'd, you'd have the CPU you'd have we call it dumb networking card. Right. And I say dumb, but it's, it's, you know, it's just designed to go process packets, you know, put and put them onto PCI and have the, the CPU do all of the, kind of the, the packet processing, the, the virtual switching, all of those functions inside the CPU. What the DPU allows you to do is, is actually offload a bunch of those functions directly onto the, onto the deep view card. So it has a combination of these special purpose processors that are programmable with the language called P four, which is one, one of the key things that pan Sando brings. Here's a, it's a, it's a real easy to program, easy to use, you know, kind of set so that not some of, some of our larger enterprise customers can actually go in and, you know, do some custom coding depending on what their network infrastructure looks like. But you can do things like the V switch in, in the, in the DPU, not having to all have that done on the CPU. So you freeze up some of the CPU course, make sure, make sure infrastructure run more efficiently, but probably even more importantly, it provides you with more, with greater security, greater separation between the, between the networking side and the, the CPU side. >>So, so that's, that's a key point because a lot of us remember the era of the tonic TCP, I P offload engine, Nick, this isn't simply offloading CPU cycles. This is actually providing a sort of isolation. So that the network that's right, is the network has intelligence that is separate from the server. Is that, is that absolutely key? Is that absolutely >>Key? Yeah. That's, that's a good way of looking at it. Yeah. And that's, that's, I mean, if you look at some of the, the, the techniques used in the cloud, the, you know, this, this, this in fact brings some of those technologies into, into the enterprise, right. So where you are wanting to have that level of separation and management, you're able to now utilize the DPU card. So that's, that's a really big, big, big part of the value proposition, the manageability manageability, not just offload, but you know, kind of a better network for enterprise. Right. >>Right. >>Can you expand on that value proposition? If I'm a customer what's in this for me, how does this help power my multi-cloud organization? >>Yeah. >>So I think we have some, we actually have a number of these in real customer use cases today. And so, you know, folks will use, for example, the compression and the, sorry, the compression and decompression, that's, that's definitely an application in the storage side, but also on the, just on the, just, just as a, as a DPU card in the mainstream general purpose, general purpose server server infrastructure fleet, they're able to use the encryption and decryption to make sure that their, their, their infrastructure is, is kind of safe, you know, from point to point within the network. So every, every connected, every connection there is actually encrypted and that, that, you know, managing those policies and orchestrating all of that, that's done to the DPU card. >>So, so what you're saying is if you have DPU involved, then the server itself and the CPUs become completely irrelevant. And basically it's just a box of sheet metal at that point. That's, that's a good way of looking at that. That's my segue talking about the value proposition of the actual AMD. >>No, absolutely. No, no. I think, I think, I think the, the, the CPUs are always going to be central in this and look. And so, so I think, I think having, having the, the DPU is extremely powerful and, and it does allow you to have better infrastructure, but the key to having better infrastructure is to have the best CPU. Well, tell >>Us, tell >>Us that's what, tell us us about that. So, so I, you know, this is, this is where a lot of the, the great value proposition between VMware and AMD come together. So VMware really allows enterprises to take advantage of these high core count, really modern, you know, CPU, our, our, our, our epic, especially our Milan, our 7,003 product line. So to be able to take advantage of 64 course, you know, VMware is critical for that. And, and so what they, what they've been able to do is, you know, know, for example, if you have workloads running on legacy, you know, like five year old servers, you're able to take a whole bunch of those servers and consolidate down, down into a single node, right. And the power that VMware gives you is the manageability, the reliability brings all of that factors and allows you to take advantage of, of the, the, the latest, latest generation CPUs. >>You know, we've actually done some TCO modeling where we can show, even if you have fully depreciated hardware, like, so it's like five years old plus, right. And so, you know, the actual cost, you know, it's already been written off, but the cost just the cost of running it in terms of the power and the administration, you know, the OPEX costs that, that are associated with it are greater than the cost of acquiring a new set of, you know, a smaller set of AMD servers. Yeah. And, and being able to consolidate those workloads, run VMware, to provide you with that great, great user experience, especially with vSphere 8.0 and the, and the hooks that VMware have built in for AMD AMD processors, you actually see really, really good. It's just a great user experience. It's also a more efficient, you know, it's just better for the planet. And it's also better on the pocketbook, which is, which is, which is a really cool thing these days, cuz our value in TCO translates directly into a value in terms of sustainability. Right. And so, you know, from, from energy consumption, from, you know, just, just the cost of having that there, it's just a whole lot better >>Talk about on the sustainability front, how AMD is helping its customers achieve their sustainability goals. And are you seeing more and more customers coming to you saying, we wanna understand what AMD is doing for sustainability because it's important for us to work with vendors who have a core focus on it. >>Yeah, absolutely. You know, I think, look, I'll be perfectly honest when we first designed our CPU, we're just trying to build the biggest baddest thing that, you know, that, that comes out in terms of having the, the, the best, the, the number, the, the largest number of cores and the best TCO for our customers, but what it's actually turned out that TCO involves energy consumption. Right. And, and it involves, you know, the whole process of bringing down a whole bunch of nodes, whole bunch of servers. For example, we have one calculation where we showed 27, you know, like I think like five year old servers can be consolidated down into five AMD servers that, that ratio you can see already, you know, huge gains in terms of sustainability. Now you asked about the sustainability conversation. This I'd say not a week goes by where I'm not having a conversation with, with a, a, a CTO or CIO who is, you know, who's got that as part of their corporate, you know, is part of their corporate brand. And they want to find out how to make their, their infrastructure, their data center, more green. Right. And so that's, that's where we come in. Yeah. And it's interesting because at least in the us money is also green. So when you talk about the cost of power, especially in places like California, that's right. There's, there's a, there's a natural incentive to >>Drive in that direction. >>Let's talk about security. You know, the, the, the threat landscape has changed so dramatically in the last couple of years, ransomware is a household word. Yes. Ransomware attacks happened like one every 11 seconds, older technology, a little bit more vulnerable to internal threats, external threats. How is AMD helping customers address the security fund, which is the board level conversation >>That that's, that's, that's a, that's a great, great question. Look, I look at security as being, you know, it's a layered thing, right? I mean, if you talk to any security experts, security, doesn't, you know, there's not one component and we are an ingredient within the, the greater, you know, the greater scheme of things. A few things. One is we have partnered very closely with the VMware. They have enabled our SUV technology, secure encrypted virtualization technology into, into the vSphere. So such that all of the memory transactions. So you have, you have security, you know, at, you know, security, when you store store on disks, you have security over the network and you also have security in the compute. And when you go out to memory, that's what this SUV technology gives you. It gives you that, that security going, going in your, in your actual virtual machine as it's running. And so the, the, we take security extremely seriously. I mean, one of the things, every generation that you see from, from AMD and, and, you know, you have seen us hit our cadence. We do upgrade all of the security features and we address all of the sort of known threats that are out there. And obviously this threats, you know, kind of coming at us all the time, but our CPUs just get better and better from, from a, a security stance. >>So shifting gears for a minute, obviously we know the pending impossible acquisition, the announced acquisition of VMware by Broadcom, AMD's got a relationship with Broadcom independently, right? No, of course. What is, how's that relationship? >>Oh, it's a great relationship. I mean, we, we, you know, they, they have certified their, their, their niche products, their HPA products, which are utilized in, you know, for, for storage systems, sand systems, those, those type of architectures, the hardcore storage architectures. We, we work with them very closely. So they, they, they've been a great partner with us for years. >>And you've got, I know, you know, we are, we're talking about current generation available on the shelf, Milan based architecture, is that right? That's right. Yeah. But if I understand correctly, maybe sometime this year, you're, you're gonna be that's right. Rolling out the, rolling out the new stuff. >>Yeah, absolutely. So later this year, we've already, you know, we already talked about this publicly. We have a 96 core gen platform up to 96 cores gen platform. So we're just, we're just taking that TCO value just to the next level, increasing performance DDR, five CXL with, with memory expansion capability. Very, very neat leading edge technology. So that that's gonna be available. >>Is that NextGen P C I E, or has that shift already been made? It's >>Been it's NextGen. P C I E P C E gen five. Okay. So we'll have, we'll have that capability. That'll be, that'll be out by the end of this year. >>Okay. So those components you talk about. Yeah. You know, you talk about the, the Broadcom VMware universe, those components that are going into those new slots are also factors in performance and >>Yeah, absolutely. You need the balance, right? You, you need to have networking storage and the CPU. We're very cognizant of how to make sure that these cores are fed appropriately. Okay. Cuz if you've just put out a lot of cores, you don't have enough memory, you don't have enough iOS. That's, that's the key to, to, to, you know, our approach to, to enabling performance in the enterprise, make sure that the systems are balanced. So you get the experience that you've had with, let's say your, you know, your 12 core, your 16 core, you can have that same experience in the 96 core in a node or 96 core socket. So maybe a 192 cores total, right? So you can have that same experience in, in a tune node in a much denser, you know, package server today or, or using Melan technology, you know, 128 cores, super, super good performance. You know, its super good experience it's, it's designed to scale. Right. And especially with VMware as, as our infrastructure, it works >>Great. I'm gonna, Lisa, Lisa's got a question to ask. I know, but bear with me one bear >>With me. Yes, sir. >>We've actually initiated coverage of this question of, you know, just hardware matter right anymore. Does it matter anymore? Yeah. So I put to you the question, do you think hardware still matters? >>Oh, I think, I think it's gonna matter even more and more going forward. I mean just, but it's all cloud who cares just in this conversation today. Right? >>Who cares? It's all cloud. Yeah. >>So, so, so definitely their workloads moving to the cloud and we love our cloud partners don't get me wrong. Right. But there are, you know, just, I've had so many conversations at this show this week about customers who cannot move to the cloud because of regulatory reasons. Yeah. You know, the other thing that you don't realize too, that's new to me is that people have depreciated their data centers. So the cost for them to just go put in new AMD servers is actually very low compared to the cost of having to go buy, buy public cloud service. They still want to go buy public cloud services and that, by the way, we have great, great, great AMD instances on, on AWS, on Google, on Azure, Oracle, like all of our major, all of the major cloud providers, support AMD and have, have great, you know, TCO instances that they've, they've put out there with good performance. Yeah. >>What >>Are some of the key use cases that customers are coming to AMD for? And, and what have you seen change in the last couple of years with respect to every customer needing to become a data company needing to really be data driven? >>No, that's, that's also great question. So, you know, I used to get this question a lot. >>She only asks great questions. Yeah. Yeah. I go down and like all around in the weeds and get excited about the bits and the bites she asks. >>But no, I think, look, I think the, you know, a few years ago and I, I think I, I used to get this question all the time. What workloads run best on AMD? My answer today is unequivocally all the workloads. Okay. Cuz we have processors that run, you know, run at the highest performance per thread per per core that you can get. And then we have processors that have the highest throughput and, and sometimes they're one in the same, right. And Ilan 64 configured the right way using using VMware vSphere, you can actually get extremely good per core performance and extremely good throughput performance. It works well across, just as you said, like a database to data management, all of those kinds of capabilities, DevOps, you know, E R P like there's just been a whole slew slew of applications use cases. We have design wins in, in major customers, in every single industry in every, and these, these are big, you know, the big guys, right? >>And they're, they're, they're using AMD they're successfully moving over their workloads without, without issue. For the most part. In some cases, customers tell us they just, they just move the workload on, turn it on. It runs great. Right. And, and they're, they're fully happy with it. You know, there are other cases where, where we've actually gotten involved and we figured out, you know, there's this configuration of that configuration, but it's typically not a, not a huge lift to move to AMD. And that's that I think is a, is a key, it's a key point. And we're working together with almost all of the major ISV partners. Right. And so just to make sure that, that, that they have run tested certified, I think we have over 250 world record benchmarks, you know, running in all sorts of, you know, like Oracle database, SAP business suite, all of those, those types of applications run, run extremely well on AMD. >>Is there a particular customer story that you think really articulates the value of running on AMD in terms of enabling bus, big business outcome, safer a financial services organization or healthcare organization? Yeah. >>I mean we, yeah, there's certainly been, I mean, across the board. So in, in healthcare we've seen customers actually do the, the server consolidation very effectively and then, you know, take advantage of the, the lower cost of operation because in some cases they're, they're trying to run servers on each floor of a hospital. For example, we've had use cases where customers have been able to do that because of the density that we provide and to be able to, to actually, you know, take, take their compute more even to the edge than, than actually have it in the, in those use cases in, in a centralized matter. The another, another interesting case FSI in financial services, we have customers that use us for general purpose. It, we have customers that use this for kind of the, the high performance we call it grid computing. So, you know, you have guys that, you know, do all this trading during the day, they collect tons and tons of data, and then they use our computers to, or our CPUs to just crunch to that data overnight. >>And it's just like this big, super computer that just crunches it's, it's pretty incredible. They're the, the, the density of the CPUs, the value that we bring really shines, but in, in their general purpose fleet as well. Right? So they're able to use VMware, a lot of VMware customers in that space. We love our, we love our VMware customers and they're able to, to, to utilize this, they use use us with HCI. So hyperconverge infrastructure with V VSAN and that's that that's, that's worked works extremely well. And, and, and our, our enterprise customers are extremely happy with that. >>Talk about, as we wrap things up here, what's next for AMD, especially AMD with VMwares VMware undergoes its potential change. >>Yeah. So there there's a lot that we have going on. I mean, I gotta say VMware is one of the, let's say premier companies in terms of, you know, being innovative and being, being able to drive new, new, interesting pieces of technology and, and they're very experimentive right. So they, we have, we have a ton of things going with them, but certainly, you know, driving pin Sando is, is very, it is very, very important to us. Yeah. I think that the whole, we're just in the, the cusp, I believe of, you know, server consolidation becoming a big thing for us. So driving that together with VMware and, you know, into some of these enterprises where we can show, you know, save the earth while we, you know, in terms of reducing power, reducing and, and saving money in terms of TCO, but also being able to enable new capabilities. >>You know, the other part of it too, is this new infrastructure enables new workloads. So things like machine learning, you know, more data analytics, more sophisticated processing, you know, that, that is all enabled by this new infrastructure. So we, we were excited. We think that we're on the precipice of, you know, going a lot of industries moving forward to, to having, you know, the next level of it. It's no longer about just payroll or, or, or enterprise business management. It's about, you know, how do you make your, you know, your, your knowledge workers more productive, right. And how do you give them more capabilities? And that, that is really, what's exciting for us. >>Awesome Cooper. And thank you so much for joining Dave and me on the program today, talking about what AMD, what you're doing to supercharge customers, your partnership with VMware and what is exciting. What's on the, the forefront, the frontier, we appreciate your time and your insights. >>Great. Thank you very much for having me. >>Thank you for our guest and Dave Nicholson. I'm Lisa Martin. You're watching the cube live from VMware Explorer, 22 from San Francisco, but don't go anywhere, Dave and I will be right back with our next guest.

>>Hello. Welcome back to our super cloud 22 event. I'm John F host the cue with my co-host Dave ante. Extracting the signal from noise. We're proud to have two amazing cube alumnis here. We got Sanja Putin. Who's now the CEO of cohesive the emo Aaron who's the CTO. Co-founder also former CEO Cub alumni. The father of hyper-converged welcome back to the cube I endorsed the >>Cloud. Absolutely. Is the father. Great >>To see you guys. Thank thanks for coming on and perfect timing. The new job taking over that. The helm Mo it at cohesive big news, but part of super cloud, we wanna dig into it. Thanks for coming on. >>Thank you for having >>Us here. So first of all, we'll get into super before we get into the Supercloud. I want to just get the thoughts on the move Sanjay. We've been following your career since 2010. You've been a cube alumni from that point, we followed that your career. Why cohesive? Why now? >>Yeah, John David, thank you first and all for having us here, and it's great to be at your event. You know, when I left VMware last year, I took some time off just really primarily. I hadn't had a sabbatical in probably 18 years. I joined two boards, Phillips and sneak, and then, you know, started just invest and help entrepreneurs. Most of them were, you know, Indian Americans like me who were had great tech, were looking for the kind of go to market connections. And it was just a wonderful year to just de to unwind a bit. And along the, the way came CEO calls. And I'd asked myself, the question is the tech the best in the industry? Could you see value creation that was signi significant and you know, three, four months ago, Mohit and Carl Eschenbach and a few of the board members of cohesive called me and walk me through Mo's decision, which he'll talk about in a second. And we spent the last few months getting to know him, and he's everything you describe. He's not just the father of hyperconverge. And he wrote the Google file system, wicked smart, built a tech platform better than that second time. But we had to really kind of walk through the chemistry between us, which we did in long walks in, in, you know, discrete places so that people wouldn't find us in a Starbucks and start gossiping. So >>Why Sanjay? There you go. >>Actually, I should say it's a combination of two different decisions. The first one was to, for me to take a different role and I run the company as a CEO for, for nine years. And, you know, as a, as a technologist, I always like, you know, going deep into technology at the same time, the CEO duties require a lot of breadth, right? You're talking to customers, you're talking to partners, you're doing so much. And with the way we've been growing the with, you know, we've been fortunate, it was becoming hard to balance both. It's really also not fair to the company. Yeah. So I opted to do the depth job, you know, be the visionary, be the technologist. And that was the first decision to bring a CEO, a great CEO from outside. >>And I saw your video on the site. You said it was your decision. Yes. Go ahead. I have to ask you, cuz this is a real big transition for founders and you know, I have founder artists cuz everyone, you know, calls me that. But being the founder of a company, it's always hard to let go. I mean nine years as CEO, it's not like you had a, you had a great run. So this was it timing for you? Was it, was it a structural shift, like at super cloud, we're talking about a major shift that's happening right now in the industry. Was it a balance issue? Was it more if you wanted to get back in and in the tech >>Look, I, I also wanna answer, you know, why Sanja, but, but I'll address your question first. I always put the company first what's right for the company. Is it for me to start get stuck the co seat and try to juggle this depth and Brad simultaneously. I mean, I can stroke my ego a little bit there, but it's not good for the company. What's best for the company. You know, I'm a technologist. How about I oversee the technology part in partnership with so many great people I have in the company and I bring someone kick ass to be the CEO. And so then that was the second decision. Why Sanja when Sanjay, you know, is a very well known figure. He's managed billions of dollars of business in VMware. You know, been there, done that has, you know, some of the biggest, you know, people in the industry on his speed dial, you know, we were really fortunate to have someone like that, come in and accept the role of the CEO of cohesive. I think we can take the company to new Heights and I'm looking forward to my partnership with, with Sanja on this. >>It it's we, we called it the splash brothers and >>The, >>In the vernacular. It doesn't matter who gets the ball, whether it's step clay, we shoot. And I think if you look at some of the great partnerships, whether it was gates bomber, there, plenty of history of this, where a founder and a someone who was, it has to be complimentary skills. If I was a technologist myself and wanted to code we'd clash. Yeah. But I think this was really a match me in heaven because he, he can, I want him to keep innovating and building the best platform for today in the future. And our customers tell one customer told me, this is the best tech they've seen since VMware, 20 years ago, AWS, 10 years ago. And most recently this was a global 100 big customers. So I feel like this combination, now we have to show that it works. It's, you know, it's been three, four months. My getting to know him, you know, I'm day eight on the job, but I'm loving it. >>Well, it's a sluman model too. It's more modern example. You saw, he did it with Fred Ludy at service now. Yes. And, and of course at, at snowflake, yeah. And his book, you read his book. I dunno if you've read his book, amp it up, but app it up. And he says, I always you'll love this. Give great deference to the founder. Always show great respect. Right. And for good reason. So >>In fact, I mean you could talk to him, you actually met to >>Frank. I actually, you know, a month or so back, I actually had dinner with him in his ranch in Moana. And I posed the question. There was a number of CEOs that went there and I posed him the question. So Frank, you know, many of us, we grow being deaf guys, you know? And eventually when we take on the home of our CEO, we have to do breadth. How do you do it? And he's like, well, let me tell you, I was never a death guy. I'm a breath guy. >>I'm like, >>That's my answer. Yeah. >>So, so I >>Want the short story. So the day I got the job, I, I got a text from Frank and I said, what's your advice the first time CEO, three words, amp it up, >>Amp it up. Right? Yeah. >>And so you're always on brand, man. >>So you're an amazing operator. You've proven that time and time again at SAP, VMware, et cetera, you feel like now you, you, you wanna do both of those skills. You got the board and you got the operations cuz you look, you know, look at sloop when he's got Scarelli wherever he goes, he brings Scarelli with him as sort of the operator. How, how do you, how are you thinking >>About that? I mean it's early days, but yeah. Yeah. Small. I mean I've, you know, when I was, you know, it was 35,000 people at VMware, 80, 90,000 people at SAP, a really good run. The SAP run was 10 to 20 billion innovative products, especially in analytics and VMware six to 12 end user computing cloud. So I learned a lot. I think the company, you know, being about 2000 employees plus not to mayor tomorrow, but over the course next year I can meet everybody. Right? So first off the executive team, 10 of us, we're, we're building more and more cohesiveness if I could use that word between us, which is great, the next, you know, layers of VPs and every manager, I think that's possible. So I I'm a people person and a customer person. So I think when you take that sort of extroverted mindset, we'll bring energy to the workforce to, to retain the best and then recruit the best. >>And you know, even just the week we, we were announced that this announcement happened. Our website traffic went through the roof, the highest it's ever been, lots of resumes coming in. So, and then lots of customer engagement. So I think we'll take this, but I, I feel very good about the possibilities, because see, for me, I didn't wanna walk into the company to a company where the technology risk was high. Okay. I feel like that I can go to bed at night and the technology risk is low. This guy's gonna run a machine at the current and the future. And I'm hearing that from customers. Now, what I gotta do is get the, the amp it up part on the go to market. I know a little thing or too about >>That. You've got that down. I think the partnership is really key here. And again, nine use the CEO and then Sanja points to our super cloud trend that we've been looking at, which is there's another wave happening. There's a structural change in real time happening now, cloud one was done. We saw that transition, AWS cloud native now cloud native with an kind of operating system kind of vibe going on with on-premise hybrid edge. People say multi-cloud, but we're looking at this as an opportunity for companies like cohesive to go to the next level. So I gotta ask you guys, what do you see as structural change right now in the industry? That's disruptive. People are using cloud and scale and data to refactor their business models, change modern cases with cloud native. How are you guys looking at this next structural change that's happening right now? Yeah, >>I'll take that. So, so I'll start by saying that. Number one, data is the new oil and number two data is exploding, right? Every year data just grows like crazy managing data is becoming harder and harder. You mentioned some of those, right? There's so many cloud options available. Cloud one different vendors have different clouds. There is still on-prem there's edge infrastructure. And the number one problem that happens is our data is getting fragmented all over the place and managing so many fragments of data is getting harder and harder even within a cloud or within on-prem or within edge data is fragmented. Right? Number two, I think the hackers out there have realized that, you know, to make money, it's no longer necessary to Rob banks. They can actually see steal the data. So ransomware attacks on the rise it's become a boardroom level discussion. They say there's a ransomware attack happening every 11 seconds or so. Right? So protecting your data has become very important security data. Security has become very important. Compliance is important, right? So people are looking for data management solutions, the next gen data management platform that can really provide all this stuff. And that's what cohesive is about. >>What's the difference between data management and backup. Explain that >>Backup is just an entry point. That's one use case. I wanna draw an analogy. Let's draw an analogy to my former company, Google right? Google started by doing Google search, but is Google really just a search engine. They've built a platform that can do multiple things. You know, they might have started with search, but then they went down to roll out Google maps and Gmail and YouTube and so many other things on that platform. So similarly backups might be just the first use case, but it's really about that platform on which you can do more with the data that's next gen data management. >>But, but you am, I correct. You don't consider yourself a security company. One of your competitors is actually pivoting and in positioning themselves as a security company, I've always felt like data management, backup and recovery data protection is an adjacency to security, but those two worlds are coming together. How do you see >>It? Yeah. The way I see it is that security is part of data management. You start maybe by backing with data, but then you secure it and then you do more with that data. If you're only doing security, then you're just securing the data. You, you gotta do more with the data. So data management is much bigger. So >>It's a security is a subset of data. I mean, there you go. Big TA Sanjay. >>Well, I mean I've, and I, I, I I'd agree. And I actually, we don't get into that debate. You know, I've told the company, listen, we'll figure that out. Cuz who cares about the positioning at the bottom? My email, I say we are data management and data security company. Okay. Now what's the best word that describes three nouns, which I think we're gonna do management security and analytics. Okay. He showed me a beautiful diagram, went to his home in the course of one of these, you know, discrete conversations. And this was, I mean, he's done this before. Many, if you watch on YouTube, he showed me a picture of an ice big iceberg. And he said, listen, you know, if you look at companies like snowflake and data bricks, they're doing the management security and mostly analytics of data. That's the top of the iceberg, the stuff you see. >>But a lot of the stuff that's get backed archive is the bottom of the iceberg that you don't see. And you try to, if you try to ask a question on age data, the it guy will say, get a ticket. I'll come back with three days. I'll UNIV the data rehydrate and then you'll put it into a database. And you can think now imagine that you could do live searches analytics on, on age data that's analytics. So I think the management, the security, the analytics of, you know, if you wanna call it secondary data or backed up data or data, that's not hot and live warm, colder is a huge opportunity. Now, what do you wanna call one phrase that describes all of it. Do you call that superpower management security? Okay, whatever you wanna call it. I view it as saying, listen, let's build a platform. >>Some people call Google, a search company. People, some people call Google and information company and we just have to go and pursue every CIO and every CSO that has a management and a security and do course analytics problem. And that's what we're doing. And when I talk to the, you know, I didn't talk to all the 3000 customers, but the biggest customers and I was doing diligence. They're like this thing has got enormous potential. Okay. And we just have to now go focus, get every fortune 1000 company to pick us because this problem, even the first use case you talk back up is a little bit like, you know, razor blades and soap you've needed. You needed it 30 years ago and you'll need it for 30 years. It's just that the tools that were built in the last generation that were companies formed in 1990s, one of them I worked for years ago are aids are not built for the cloud. So I think this is a tremendous opportunity where many of those, those, those nos management security analytics will become part of what we do. And we'll come up with the right phrase for what the companies and do course >>Sanjay. So ma and Sanja. So given that given that's this Google transition, I like that example search was a data problem. They got sequenced to a broader market opportunity. What super cloud we trying to tease out is what does that change over from a data standpoint, cuz now the operating environments change has become more complex and the enterprises are savvy. Developers are savvy. Now they want, they want SAS solutions. They want freemium and expanding. They're gonna drive the operations agenda with DevOps. So what is the complexity that needs to be abstracted away? How do you see that moment? Because this is what people are talking about. They're saying security's built in, driven by developers. Developers are driving operations behavior. So what is the shift? Where do you guys see this new? Yeah. Expansive for cohesive. How do you fit into super cloud? >>So let me build up from that entry point. Maybe back up to what you're saying is the super cloud, right? Let me draw that journey. So let's say the legacy players are just doing backups. How, how sad is it that you have one silo sitting there just for peace of mind as an insurance policy and you do nothing with the data. If you have to do something with the data, you have to build another silo, you have to build another copy. You have to manage it separately. Right. So clearly that's a little bit brain damaged. Right. So, okay. So now you take a little bit of, you know, newer vendors who may take that backup platform and do a little bit more with that. Maybe they provide security, but your problem still remains. How do you do more with the data? How do you do some analytics? >>Like he's saying, right. How do you test development on that? How do you migrate the data to the cloud? How do you manage it? The data at scale? How do you do you provide a unified experience across, across multiple cloud, which you're calling the super cloud. That's where cohesive goes. So what we do, we provide a platform, right? We have tentacles in on-prem in each of the clouds. And on top of that, it looks like one platform that you manage. We have a single control plane, a UI. If you may, a single pin of glass, if, if you may, that our customers can use to manage all of it. And now it looks, starts looking like one platform. You mentioned Google, do you, when you go to, you know, kind Google search or a URL, do you really care? What happens behind the scenes mean behind the scenes? Google's built a platform that spans the whole world. No, >>But it's interesting. What's behind the scenes. It's a beautiful now. And I would say, listen, one other thing to pull on Dave, on the security part, I saw a lot of vendors this day in this space, white washing a security message on top of backup. Okay. And CSO, see through that, they'll offer warranties and guarantees or whatever, have you of X million dollars with a lot of caveats, which will never paid because it's like escape clause here. We won't pay it. Yeah. And, and what people really want is a scalable solution that works. And you know, we can match every warranty that's easy. And what I heard was this was the most scalable solution at scale. And that's why you have to approach this with a Google type mindset. I love the fact that every time you listen to sun pitch, I would, what, what I like about him, the most common word to use is scale. >>We do things at scale. So I found that him and AUR and some of the early Google people who come into the company had thought about scale. And, and even me it's like day eight. I found even the non-tech pieces of it. The processes that, you know, these guys are built for simple things in some cases were better than some of the things I saw are bigger companies I'd been used to. So we just have to continue, you know, building a scale platform with the enterprise. And then our cloud product is gonna be the simple solution for the masses. And my view of the world is there's 5,000 big companies and 5 million small companies we'll push the 5 million small companies as the cloud. Okay. Amazon's an investor in the company. AWS is a big partner. We'll talk about I'm sure knowing John's interest in that area, but that's a cloud play and that's gonna go to the cloud really fast. You not build you're in the marketplace, you're in the marketplace. I mean, maybe talk about the history of the Amazon relationship investing and all that. >>Yeah, absolutely. So in two years back late 2020, we, you know, in collaboration with AWS who also by the way is an investor now. And in cohesive, we rolled out what we call data management as a service. It's our SaaS service where we run our software in the cloud. And literally all customers have to do is just go there and sign on, right? They don't have to manage any infrastructure and stuff. What's nice is they can then combine that with, you know, software that they might have bought from cohesive. And it still looks like one platform. So what I'm trying to say is that they get a choice of the, of the way they wanna consume our software. They can consume it as a SAS service in the cloud. They can buy our software, manage it themselves, offload it to a partner on premises or what have you. But it still looks like that one platform, what you're calling a Supercloud >>Yeah. And developers are saying, they want the bag of Legos to compose their solutions. That's the Nirvana they want to get there. So that's, it has to look the same. >>Well, what is it? What we're calling a Superlo can we, can we test that for a second? So data management and service could span AWS and on-prem with the identical experience. So I guess I would call that a Supercloud I presume it's not gonna through AWS span multiple clouds, but, but >>Why not? >>Well, well interesting cuz we had this, I mean, so, okay. So we could in the future, it doesn't today. Well, >>David enough kind of pause for a second. Everything that we do there, if we do it will be customer driven. So there might be some customers I'll give you one Walmart that may want to store the data in a non AWS cloud risk cuz they're competitors. Right. So, but the control plane could still be in, in, in the way we built it, but the data might be stored somewhere else. >>What about, what about a on-prem customer? Who says, Hey, I, I like cohesive. I've now got multiple clouds. I want the identical experience across clouds. Yeah. Okay. So, so can you do that today? How do you do that today? Can we talk >>About that? Yeah. So basically think roughly about the split between the data plane and the control plane, the data plane is, you know, our cohesive clusters that could be sitting on premises that could be sitting in multiple data centers or you can run an instance of that cluster in the cloud, whichever cloud you choose. Right. That's what he was referring to as the data plane. So collectively all these clusters from the data plane, right? They stored the data, but it can all be managed using the control plane. So you still get that single image, the single experience across all clouds. And by the way, the, the, the, the cloud vendor does actually benefit because here's a customer. He mentioned a customer that may not wanna go to AWS, but when they get the data plane on a different cloud, whether it's Azure, whether it's the Google cloud, they then get data management services. Maybe they're able to replicate the data over to AWS. So AWS also gains. >>And your deployment model is you instantiate the cohesive stack on each of the regions and clouds, is that correct? And you building essentially, >>It all happens behind the scenes. That's right. You know, just like Google probably has their tentacles all over the world. We will instantiate and then make it all look like one platform. >>I mean, you should really think it's like a human body, right? The control planes, the head. Okay. And that controls everything. The data plane is large because it's a lot of the data, right? It's the rest of the body, that data plane could be wherever you want it to be. Traditionally, the part the old days was tape. Then you got disk. Now you got multiple clouds. So that's the way we think about it. And there on that piece of it will be neutral, right? We should be multi-cloud to the data plane being every single place. Cause it's customer demand. Where do you want your store data? Air gapped. On-prem no problem. We'll work with Dell. Okay. You wanna be in a particular cloud, AWS we'll work then optimized with S3 and glacier. So this is where I think the, the path to a multi-cloud or Supercloud is to be customer driven, but the control plane sits in Amazon. So >>We're blessed to have a number of, you know, technical geniuses in here. So earlier we were speaking to Ben wa deja VI, and what they do is different. They don't instantiate an individual, you know, regions. What they do is of a single global. Is there a, is there an advantage of doing it the way the cohesive does it in terms of simplicity or how do you see that? Is that a future direction for you from a technology standpoint? What are the trade offs there? >>So you want to be where the data is when you said single global, I take it that they run somewhere and the data has to go there. And in this day age, correct >>Said that. He said, you gotta move that in this >>Day and >>Age query that's, you know, across regions, look >>In this day and age with the way the data is growing, the way it is, it's hard to move around the data. It's much easier to move around the competition. And in these instances, what have you, so let the data be where it is and you manage it right there. >>So that's the advantage of instantiating in multiple regions. As you don't have to move the >>Data cost, we have the philosophy we call it. Let's bring the, the computation to the data rather than the data to >>The competition and the same security model, same governance model, same. How do you, how do you federate that? >>So it's all based on policies. You know, this overarching platform controlled by, by the control plane, you just, our customers just put in the policies and then the underlying nuts and bolts just take care >>Of, you know, it's when I first heard and start, I started watching some of his old videos, ACE really like hyperconverged brought to secondary storage. In fact, he said, oh yeah, that's great. You got it. Because I first called this idea, hyperconverged secondary storage, because the idea of him inventing hyperconverge was bringing compute to storage. It had never been done. I mean, you had the kind of big VC stuff, but these guys were the first to bring that hyperconverge at, at Nutanix. So I think this is that same idea of bringing computer storage, but now applied not to the warm data, but to the rest of the data, including a >>Lot of, what about developers? What's, what's your relationship with developers? >>Maybe you talk about the marketplace and everything >>He's yeah. And I'm, I'm curious as to do you have a PAs layer, what we call super PAs layer to create an identical developer experience across your Supercloud. I'm gonna my >>Term. So we want our customers not just to benefit from the software that we write. We also want them to benefit from, you know, software that's written by developers by third party people and so on and so forth. So we also support a marketplace on the platform where you can download apps from third party developers and run them on this platform. There's a, a number of successful apps. There's one, you know, look like I said, our entry point might be backups, but even when backups, we don't do everything. Look, for instance, we don't backup mainframes. There is a, a company we partner with, you know, and their software can run in our marketplace. And it's actually used by many, many of our financial customers. So our customers don't get, just get the benefit of what we build, but they also get the benefit of what third parties build. Another analogy I like to draw. You can tell. And front of analogy is I drew an analogy to hyperscale is like Google. Yeah. The second analogy I like to draw is that to a simple smartphone, right? A smartphone starts off by being a great phone. But beyond that, it's also a GPS player. It's a, it's a, it's a music player. It's a camera, it's a flashlight. And it also has a marketplace from where you can download apps and extend the power of that platform. >>Is that a, can we think of that as a PAs layer or no? Is it really not? You can, okay. You can say, is it purpose built for what you're the problem that you're trying to solve? >>So we, we just built APIs. Yeah. Right. We have an SDK that developers can use. And through those APIs, they get to leverage the underlying services that exist on the platform. And now developers can use that to take advantage of all that stuff. >>And it was, that was a key factor for me too. Cause I, what I, you know, I've studied all the six, seven players that sort of so-called leaders. Nobody had a developer ecosystem, nobody. Right? The old folks were built for the hardware era, but anyones were built for the cloud to it didn't have any partners were building on their platform. So I felt for me listen, and that the example of, you know, model nine rights, the name of the company that does back up. So there's, there's companies that are built on and there's a number of others. So our goal is to have a big tent, David, to everybody in the ecosystem to partner with us, to build on this platform. And, and that may take over time, but that's the way we're build >>It. And you have a metadata layer too, that has the intelligence >>To correct. It's all abstract. That that's right. So it's a combination of data and metadata. We have lots of metadata that keeps track of where the data is. You know, it allows you to index the data you can do quick searches. You can actually, you, we talking about the control plan from that >>Tracing, >>You can inject a search that'll through search throughout your multi-cloud environment, right? The super cloud that you call it. We have all that, all that goodness sounds >>Like a Supercloud John. >>Yeah. I mean, data tracing involved can trace the data lineage. >>You, you can trace the data lineage. So we, you know, provide, you know, compliance and stuff. So you can, >>All right. So my final question to wrap up, we guys, first of all, thanks for coming on. I know you're super busy, San Jose. We, we know what you're gonna do. You're gonna amp it up and, you know, knock all your numbers out. Think you always do. But what I'm interested in, what you're gonna jump into, cuz now you're gonna have the creative license to jump in to the product, the platform there has to be the next level in your mind. Can you share your thoughts on where this goes next? Love the control plane, separate out from the data plane. I think that plays well for super. How >>Much time do you have John? This guy's got, he's got a wealth. Ditis keep >>Going. Mark. Give us the most important thing you're gonna focus on. That kind of brings the super cloud and vision together. >>Yeah. Right away. I'm gonna, perhaps I, I can ion into two things. The first one is I like to call it building the, the machine, the system, right. Just to draw an analogy. Look, I draw an analogy to the us traffic system. People from all walks of life, rich, poor Democrats, Republicans, you know, different states. They all work in the, the traffic system and we drive well, right. It's a system that just works. Whereas in some other countries, you know, the system doesn't work. >>We know, >>We know a few of those. >>It's not about works. It's not about the people. It's the same people who would go from here to those countries and, and not dry. Well, so it's all about the system. So the first thing I, I have my sights on is to really strengthen the system that we have in our research development to make it a machine. I mean, it functions quite well even today, but wanna take it to the next level. Right. So that I wanna get to a point where innovation just happens in the grassroots. And it just, just like >>We automations scale optic brings all, >>Just happens without anyone overseeing it. Anyone there's no single point of bottleneck. I don't have to go take any diving catches or have you, there are people just working, you know, in a decentralized fashion and innovation just happens. Yeah. The second thing I work on of course is, you know, my heart and soul is in, you know, driving the vision, you know, the next level. And that of course is part of it. So those are the two things >>We heard from all day in our super cloud event that there's a need for an, an operating system. Yeah. Whether that's defacto standard or open. Correct. Do you see a consortium around the corner potentially to bring people together so that things could work together? Cuz there really isn't no stand there. Isn't a standards bodies. Now we have great hyperscale growth. We have on-prem we got the super cloud thing happening >>And it's a, it's kind of like what is an operating system? Operating system exposes some APIs that the applications can then use. And if you think about what we've been trying to do with the marketplace, right, we've built a huge platform and that platform is exposed through APIs. That third party developers can use. Right? And even we, when we, you know, built more and more services on top, you know, we rolled our D as we rolled out, backup as a service and a ready for thing security as a service governance, as a service, they're using those APIs. So we are building a distributor, putting systems of sorts. >>Well, congratulations on a great journey. Sanja. Congratulations on taking the hem. Thank you've got ball control. Now you're gonna be calling the ball cohesive as they say, it's, >>It's a team. It's, you know, I think I like that African phrase. If you want to go fast, you go alone. If you wanna go far, you go together. So I've always operated with the best deal. I'm so fortunate. This is to me like a dream come true because I always thought I wanted to work with a technologist that frees me up to do what I like. I mean, I started as an engineer, but that's not what I am today. Right? Yeah. So I do understand the product and this category I think is right for disruption. So I feel excited, you know, it's changing growing. Yeah. No. And it's a, it requires innovation with a cloud scale mindset and you guys have been great friends through the years. >>We'll be, we'll be watching you. >>I think it's not only disruption. It's creation. Yeah. There's a lot of white space that just hasn't been created yet. >>You're gonna have to, and you know, the proof, isn't the pudding. Yeah. You already have five of the biggest 10 financial institutions in the us and our customers. 25% of the fortune 500 users, us two of the biggest five pharmaceutical companies in the world use us. Probably, you know, some of the biggest companies, you know, the cars you have, you know, out there probably are customers. So it's already happening. >>I know you got an IPO filed confidentially. I know you can't talk numbers, but I can tell by your confidence, you're feeling good right now we are >>Feeling >>Good. Yeah. One day, one week, one month at a time. I mean, you just, you know, I like the, you know, Jeff Bezos, Andy jazzy expression, which is, it's always day one, you know, just because you've had success, even, you know, if, if a and when an IPO O makes sense, you just have to stay humble and hungry because you realize, okay, we've had a lot of success in the fortune 1000, but there's a lot of white space that hasn't picked USS yet. So let's go, yeah, there's lots of midmarket account >>Product opportunities are still, >>You know, I just stay humble and hungry and if you've got the team and then, you know, I'm really gonna be working also in the ecosystem. I think there's a lot of very good partners. So lots of ideas brew through >>The head. Okay. Well, thank you so much for coming on our super cloud event and, and, and also doubling up on the news of the new appointment and congratulations on the success guys. Coverage super cloud 22, I'm sure. Dave ante, thanks for watching. Stay tuned for more segments after this break.

>>We're back in Boston, the Cube's coverage of AWS reinforced 2022. My name is Dave ante. Steve Malanney is here as the CEO of Aviatrix longtime cube alum sort of collaborator on super cloud. Yeah. Uh, which we have an event, uh, August 9th, which you guys are participating in. So, um, thank you for that. And, yep. Welcome to the cube. >>Yeah. Thank you so great to be here as >>Always back in Boston. Yeah. I'd say good show. Not, not like blow me away. We were AWS, um, summit in New York city three weeks ago. I >>Took, heard it took three hours to get in >>Out control. I heard, well, there were some people two I, maybe three <laugh>, but there was, they expected like maybe nine, 10,000, 19,000 showed up. Now it's a free event. Yeah. 19,000 people. >>Oh, I didn't know it >>Was that many. It was unbelievable. I mean, it was packed. Yeah. You know, so it's a little light here and I think it's cuz you know, everybody's down the Cape, >>There are down the Cape, Rhode Island that's after the fourth. The thing is that we were talking about this. The quality of people are pretty good though. Yeah. Right. This is there's no looky lose it's everybody. That's doing stuff in cloud. They're moving in. This is no longer, Hey, what's this thing called cloud. Right. I remember three, four years ago at AWS. You'd get a lot of that, that kind of stuff. Some the summit meetings and things like that. Now it's, we're a full on deployment mode even >>Here in 2019, the conversation was like, so there's this shared responsibility model and we may have to make sure you understand. I mean, nobody's questioning that today. Yeah. It's more really hardcore best practices and you know how to apply tools. Yeah. You know, dos and don't and so it's a much more sophisticated narrative, I think. Yeah. >>Well, I mean, that's one of the things that Aviatrix does is our whole thing is architecturally. I would say, where does network security belong in the network? It shouldn't be a bolt on it. Shouldn't be something that you add on. It should be something that actually gets integrated into the fabric of the network. So you shouldn't be able to point to network security. It's like, can you point to the network? It's everywhere. Point to air it's everywhere. Network security should be integrated in the fabric and that wasn't done. On-prem that way you steered traffic to this thing called a firewall. But in the cloud, that's not the right architectural way. It it's a choke point. Uh, operationally adds tremendous amount of complexity, which is the whole reason we're going to cloud in the first place is for that agility and the ability to operationally swipe the card and get our developers running to put in these choke points is completely the wrong architecture. So conversations we're having with customers is integrate that security into the fabric of the network. And you get rid of all those, all those operational >>Issues. So explain that how you're not a, a checkpoint, but if you funnel everything into one sort of place >>In the, so we are a networking company, uh, it is uh, cloud networking company. So we, we were born in the cloud cloud native. We, we are not some on-prem networking solution that was jammed in the cloud, uh, wrapped >>In stack wrapped >>In, you know, or like that. No, no, no. And looking for wires, right? That's VM series from Palo. It doesn't even know it's in the cloud. Right. It's looking for wires. Um, and of course multicloud, cuz you know, Larry E said now, could you believe that on stage with sat, Nadela talking about multi-cloud now you really know we've crossed over to this is a, this is a thing, whoever would've thought you'd see that. But anyway, so we're networking. We're cloud networking, of course it's multi-cloud networking and we're gonna integrate these intelligent services into the fabric. And one of those is, is networking. So what happens is you should do security everywhere. So the place to do it is at every single point in the network that you can make a decision and you embed it and actually embed it into the network. So it's that when you're making a decision of does that traffic need to go somewhere or not, you're doing a little bit of security everywhere. And so what, it looks like a giant firewall effectively, but it's actually distributed in software through every single point in a network. >>Can I call it a mesh? >>It's kind of a mesh you can think of. Yeah, it's a fabric. >>Okay. It's >>A, it's a fabric that these advanced services, including security are integrated into that fabric. >>So you've been in networking much of >>Your career career, >>37 years. All your career. Right? So yay. Cisco Palo Alto. Nicera probably missing one or two, but so what do you do with all blue coat? Blue coat? What do you do with all that stuff? That's out there that >>Symantics. >>Yes. <laugh> keep going. >>Yeah, I think that's it. That's >>All I got. Okay. So what do you do with all that stuff? That's that's out there, you rip and replace it. You, >>So in the cloud you mean yeah. >>All this infrastructure that's out there. What is that? Well, you >>Don't have it in the right. And so right now what's happening is people, look, you can't change too many things. If you're a human, you know, they always tell you don't change a job, get married and have a kid or something all in the same year. Like they just, just do one of 'em cuz you it's too much. When people move to the cloud, what they do is they tend to take what they do on Preem and they say, look, I'm gonna change one thing. We're gonna go to the cloud, everything else. I'm gonna keep the same. Cuz I don't wanna change three things. So they kind of lift and shift their same mentality. They take their firewalls, their next gen fire. I want them, they take all the things that they currently do. And they say, I'm gonna try to do that in the cloud. >>It's not really the right way to do it. But sometimes for people that are on-prem people, that's the way to get started and I'll screw it up and not screw it up and, and not change too many things. And look, I'm just used to that. And, and then I'll, then I'll go to change things, to be more cloud native, then I'll realize I can get rid of this and get rid of that and do that. But, but that's where people are. The first thing is bring these things over. We help them do that, right? From a networking perspective, I'll make it easier to bring your old security stuff in. But in parallel to that, we start adding things into the fabric and what's gonna happen is eventually we start adding all these things and things that you can't do separately. We start doing anomaly detection. We start doing behavioral analysis. Why? Because the entire network, we are the data plan. We see everything. And so we can start doing things that a standalone device can't do because not all the traffic steered to them. It can only control what's steered to you. And then eventually what's happening is people look at that device. And then they look at us and then they look at the device and they look at us and they go, why do I have both of this? And we go, I don't know. >>You don't need it. >>Well, can I get rid of that other thing? That's a tool. >>Sure. And there's not a trade off. There's not a trade off. You >>Don't have to. No. Now people rid belts and suspenders. Yeah. Cause it's just, who has, who has enough? Who has too much security buddy? They're gonna, they're gonna do belt suspenders. You know anything they can do. But eventually what will happened is they'll look at what we do and they'll go, that's good enough. That happened to me. When I was at Palo Alto networks, we inserted as a firewall. They kept their existing firewall. They had all these other devices and eventually all those went away and you just had a NextGen >>Firewall just through attrition, >>Through Atian. You're like, you're looking, you go, well, that platform is doing all these functions. Same. Thing's gonna happen to us. The platform of networking's gonna do all your network security devices. So any tool or agent or external, you know, device that you have to steer traffic to ISS gonna go away. You're not gonna need it. >>And, and you talking multi-cloud obviously, >>And then don't wanna do the same thing. Whether man Azure, you know the same. >>Yeah. >>Same, same experie architecture, same experience, same set of services. True. Multi-cloud native. Like you, that's what you want. And oh, by the way, skill, gap, skill shortage is a real thing. And it's getting worse. Cause now with the recession, you think you're gonna be able to add more people. Nope. You're gonna have less people. How do I do this? Any multicloud world with security and all this kind of stuff. You have to put the intelligence in the software, not on your people. Right? >>So speaking of recession. Yep. As a CEO of a well funded company, that's got some momentum. How are you approaching it? Do you have like, did you bring in the war time? Conig I mean, you've been through, you know, downturns before. This is you are you >>I'm on war time already. >>Okay. So yeah. Tell me more about how you you're kind of approaching this >>So recession down. So didn't change what we were doing one bit, because I run it that way from the very beginning. So I've been around 30 years, that's >>Told me he he's like me. You know what he said? >>Yeah. Or maybe >>I'm like, I want be D cuz he said, you know, people talk about, you know, only do things that are absolutely necessary during times like this. I always do things that are only, >>That's all I >>Do necessary. Why would you ever do things that aren't necessary? >><laugh> you'd be surprised. Most companies don't. Yeah. Uh, recession's very good for people like snowflake and for us because we run that way anyway. Mm-hmm <affirmative> um, I, I constantly make decisions that we have to go and dip there's people that aren't right for the business. I move 'em out. Like I don't wait for some like Sequoia stupid rest in peace. The world's ending fire all your people that has no impact on me because I already operated that way. So we, we kind of operate that way and we are, we are like sat Nadel even came out and kind of said, I don't wanna say cloud is recession proof, but it kind of is, is we are so look, our top customer spends 5 million a year. Nothing. We haven't even started yet. David that's minuscule. We're not macro. We're micro 5 million a year for these big enterprises is nothing right. SA Nadel is now starting to count people who do billion dollar agreements with him billion over a period of number of years. Like that's the, the scale we have not even >>Gun billion dollar >>Agreements. We haven't even under begun to understand the scope of what's happening in the cloud. Right. And so yeah, the recession's happening. I don't know. I guess it's impacting somebody. It's not impacting me. It's actually accelerating things because it's a flight to quality and customers go and say, I can't get gear on on-prem anyway, cuz of the, uh, shortage, you know, the, uh, uh, get chips. Um, and that's not the right thing. So guess what the recession says, I'm gonna stop spending more money there and I'm gonna put it into the cloud. >>All right. So you opened up Pandora's box, man. I wanna ask you about your sort of management philosophy. When you come into a company to take, to go lead a company like that. Yeah. How, what, what's your approach to assess the team? Who do you, who do you decide? How do you decide who to keep on the bus? Who to throw off the bus put in the right seats. So how long does that take you? >>Doesn't take long. When I join, we were 30, 30, 8 people. We're now 525. Um, and my view on everything and I I've never met Frank Lubin, but I guarantee you, he has the same philosophy. You have a one year contract me included next year, the board might come to me and say, you were the right CEO for this year. You're not next year. Ben Horowitz taught me that it's a one year contract. There's no multi-year contract. So everybody in the company, including the CEO has a one year >>Contract. So you would say that to the board. Hey, if you can find somebody better, >>If, and, and you know what, I'll be the first one to pull myself, fire myself and say, we're, we're replacing me with somebody better right now. There isn't anybody better. So it's me. So, okay, next year maybe there's somebody better. Or we hit a certain point where I'm not the right guy. I'll I'll, I'll pull myself out as the CEO, but also internally the same thing just because you're the right guy this year. And we hire people for the, what you need to do this year. We're not gonna, we don't hire, oh, like this is the mistake. A lot of companies make, well, we wanna be a billion dollars in sales. So we're gonna go hire some loser from HPE. Who's worked at a company for a billion dollars. And by the way has no idea how they became a billion dollars, right. In revenue or billions of dollars. >>But we're gonna go hire 'em because they must know more than we do. And what every single time you bring them in what you realize, they're idiots. They have no idea how we got to that. And so you, you don't pre-hire for where you want to be. You hire for where you are that year. And then if it's not right, and then if it's not right, you'd be really nice to them. Have great severance packages, be, be respectful for people and be honest with them. I guarantee you Frank, Salman's not, if you're not just have this conversation with a sales guy before I came into here, very straight conversation, Northeast hockey player mentality. We're straight. If you're not working out or I don't think you're doing things right. You're gonna know. And so it's a one year, it's a one year contract. That's what you do. So you don't have time. You don't the luxury of >>Time. So, so that's probably the hardest part of, of any leadership job is, and people don't like confrontation. They like to put it off, but you don't run away from it. It's >>All in a confrontation, right? That's what relationships have built. Why do war buddies hang out with each other? Cuz they've gone through hell, right? It's in the confrontation. And it's, it's actually with customers too, right? If there's an issue, you don't run from it. You actually bring it up in a very straightforward manner and say, Hey, we got a problem, right? They respect you. You respect them, blah, blah, blah. And then you come out of it and go, you know, you have to fight like, look with your wife. You have to fight. If you don't fight, it's not a relationship you've gotta see in that, in that tension is where the relationship's >>Built. See, I should go home and have a fight tonight. You gotta have a fight with your wife. <laugh> you know, you mentioned Satia and Nadella and Larry Ellison. Interesting point. I wanna come back to that. What Oracle did is actually pretty interesting, do we? For their use case? Yeah. You know, it's not your thing. It's like low latency database across clouds. Yeah. Who would ever thought that? But >>We love it. We love it because it drives multi-cloud it drives. Um, and, and, and I actually think we're gonna have multi-cloud applications that are gonna start happening. Um, right now you don't, you have developers that, that, that kind of will use one cloud. But as we start developing and you call it the super cloud, right. When that starts really happening, the infrastructure's gonna allow that networking and network security is that bottom layer that Aviatrix helps once that gets all handled. The app, people are gonna say, so there's no friction. So maybe I can use autonomous database here. I can use this service from GCP. I can use that service and, and put it all into one app. So where's the app run. It's a multicloud app. Doesn't exist today. >>No, that doesn't happen today. >>It's it's happen. It's gonna happen. >>But that's kind of what the vision was. No, seven, eight years ago of what >>It's >>Gonna, that would be, you know, the original premise of hybrid. Right? Right. Um, I think Chuck Hollis, the guy was at EMC at the time he wrote this piece on, he called it private cloud, but he was really describing hybrid cloud application and running in both places that never happened. But it's starting to, I mean, the infrastructure is getting put in place to enable that, I guess is what you're saying. >>Yep. >>Yeah. >>Cool. And multicloud is, is becoming not just four plus one is a lot of enterprises it's becoming plus one, meaning you're gonna have more and more. And then there won't be infrastructure clouds like AWS and so forth, but it's gonna be industry clouds. Right? You've you've talked about that again, back to super clouds. You're gonna have Goldman Sachs creating clouds and you're gonna have AI companies creating clouds. You're gonna have clouds at the edge, you know, for edge computing and all these things all need to be networked with network security integrated. And you mentioned fact >>Aviatrix you mentioned Ben Horowitz, that's mark Andreesen. All, all companies are software companies. All companies are becoming cloud companies. Yeah. Or, or they're missing missing opportunities or they might get disrupted. >>Yeah. Every single company I talk to now, you know, whether you're Heineken, they don't think of themselves as a beer company anymore. We are the most technologically, you know, advanced brewer in the world. Like they all think they're a technology company. Now, whether you're making trucks, whether you're making sneakers, whether you're making beer, you're now a technology company, every single company in >>The world, we are too, we're we're building a media cloud. You're you know, John's, it's a technology company laying that out and yeah. That's we got developers doing that. That's our, that's our future. Yep. You know? Cool. Hey, thanks for coming on, man. Thank you. Great to see you. Thank you for watching. Keep it right there. We'll be back right after this short break. It keeps coverage. AWS reinforced 20, 22 from Boston. Keep it right there. >>You tired? How many interviewed.

(pulsing music) (digital music) >> Welcome back to the Seaport in Boston. You're watching theCUBE's coverage of Red Hat Summit 2022. A lot of bummed out Bruins fans, but a lot of happy Celtics fans. We're optimistic for tonight, Boston's crazy sports town, but we're talking tech, we're talking open source. Dr. Amanda Purnell is here. She's the director of data and analytics innovation at the US Department of Veteran Affairs, and Ben Cushing is the chief architect for federal health and life sciences at Red Hat. Folks, welcome to theCUBE, thank for coming on. >> Thank you for having us. >> So glad to be here. >> So we heard your keynote this morning, project Arches. Now you were telling us just briefly about your previous life as a clinician. >> That's right. >> That's really interesting, because you know what the outcome has to be. So talk about that project in your perspective. What the goals were and how you actually got it done. >> I could tell the long view. I'm a psychologist by training. I spent the first 10 years of my VA career providing care to veterans. So engaging in healthcare behavior change, providing training to providers and really trying to understand what is the care pathway for veterans, what's the experience of veterans along each of those touchpoints, and it became clear to me over time that there were opportunities for us to improve the transitions of care and provide better information at the right time to improve those decisions that are being made at the point of care. Ben and I were just talking before we began today, part of the core of the development of Arches was beginning with human-centered design. We wanted to interview and better understand what was the experience across the VA of many different stakeholders and trying to access meaningful information, understand in that moment what do I need to make a decision with a veteran or what do I need to make a decision with my care team and how can I improve the quality of care for veterans? And so, hundreds of interviews later, it became clear to us that we wanted to help those individuals already working for the VA to continue to improve excellence of care and one of those ways that we're trying to do that is using technology to make life easier for our veterans and for our clinicians. >> I always like to say, they say, "Follow the money." I like to follow the data. And you said something in your keynote about nurses have to have access to information and it just gets to an architectural question, because as a caregiver, you have to get insights and data and you need it fast, 'cause you're saving lives, but a lot of times, architectures are very centralized. They're monolithic and you have to beg, borrow, steal, break through blockers to get to the data that you need. How do you square that circle in today's world? Maybe you could talk about that, and then specific to Arches, how you dealt with that. >> I can dive into that a little bit. I have to say, Amanda had touched on this during the keynote, VA was one of the first, if not the first, healthcare organizations in the world to actually adopt electronic health records and because of that, they just have this incredibly rich amount of historical data and the challenge, as you pointed out, is gaining access to it. So there are a number of programs within VA designed specifically for that. And they are bringing data not just from the data warehouses, but also data from the electronic health records that are running inside of VA right now, and then also third party community data sets, as well as applications that run inside the VA. Now the value here really happens when you produce insights. Data by itself is useless. >> Lot of data out there. They're plentiful. >> You need to create knowledge and then you need that knowledge to inform your process that comes next. Those actions are really what matters. All of healthcare is process and activity and data is really just a historical record. I mean, all data that we look at is happening in the past and then as we're reading it, we're producing knowledge, again, to inform our process. Arches, the program itself, is right in that space at the knowledge layer of actually taking that data and turning it into actual insight and something that is usable and insightful for clinicians to affect the ability to deliver better care and also to actually improve their own working experience. A lot of the models that are getting built out are specifically designed to help their workflow, help them reach better outcomes for the veterans, but also for themselves, because if we can care for the providers, it'll certainly help them care for the patients even more so. >> So how does it work? I mean, from the provider's perspective, how was their life improved by Arches? >> That's a great question. We want to make it easier to access the information. So as Ben noted, the average person providing care in the field doesn't know how to code, doesn't know how to pull a unique request for an individual data point, and what we're trying to do with Arches is provide a user interface that allows for both a non-technical person and a very technical person to access information, and then what gets provisioned in front of a provider is something that is farther abstracted from the underlying data layer and more like here's a specific insight. So I use the example in my keynote of chronic kidney disease. So what's provisioned to the provider in that moment is this person is at higher risk for chronic kidney disease based on this basic information. So it's surfacing just the right amount of information to allow for that care pathway to be improved, but the physician doesn't need to see all of the layers of code underneath. They need to trust that it's worthwhile, but they don't need to know all the background abstractions. >> So it's a self-service, essentially, infrastructure in that sense. You're hiding the underlying complexities. You gave an example in your keynote of an individual who realized that they were under counting the probability of a potential disease for African Americans. >> Yes. >> I believe she just rewrote the algorithm. >> She did. >> Describe that process, because in a lot of organizations, injecting that new algorithm may have required new data sources, would take an act of the Pope to do. How did it work in Arches? >> This is what I get excited about with Arches is that we have the opportunity to empower enthusiastic people like Dr. Joshi to discover an insight and she's a talented informaticist, so she could do the technical work and provision a container for her to work in, for her to do the data analysis, the underground stuff that we're not letting the average provider have to cope with. We were able to provision the tools that she need, the environment that she needed to be able to test and develop the new insight, confirm that they're there and then begin to validate that and test it in other facilities. So our thinking is, how do we bring the resources to the users rather than saying to the users, "This is what's available. Good luck." (chuckles) >> So we've been talking a lot about, I'm sorry, go ahead. >> I want to add on to that. What we're actually experiencing inside of healthcare right now is the emergence of of learning health systems. >> Yes. >> And this is a great example of that. The terrifying number is, it takes 17 years for new knowledge that gets created with healthcare research, whether it's NIH or VA or elsewhere, it takes 17 years for those practices to make their way into practice. Generally the way that happens is through the education of new staff. And so the dissemination of that knowledge is just so freaking slow that we cannot move nimbly enough to take on that new knowledge and actually implement it in clinical space. What Amanda's describing is something that now happens in months. New knowledge getting produced and then actually getting disseminated out, both the insights, whether they are those probabilities, predictions and recommendations and the actual processes, which are getting automated, as well. So if you think about healthcare as just a process, you can automate a whole lot of that and we can move that needle really fast and actually take that 70-year number down to a couple months. >> In the early days when we were all talking about AI and getting excited about digital, I would often ask the question, will machines be able to make better diagnoses than doctors and to your point, Ben, that's not the right question. >> Exactly. >> It isn't the right question. >> The question is, how can machines compress the time to better patient outcomes- >> Yes. >> in concert with humans and that's what we're seeing now. >> That's right, it's surfacing those insights to start a conversation. >> We've been talking a lot about artificial intelligence for the last two days. As clinician or someone with a clinical background, how do you see the clinical experience changing as machines grow more intelligent? >> I think that there's a learning curve for people to feel confident in an artificial intelligence. It makes sense. So someone spent decades, perhaps, of their life obtaining medical training, doing fellowships, doing additional training that they have trust in that deep training. There are times, however, where a technology is able to surface something that we didn't know that we didn't know and it's important, as we make use of artificial intelligence, that we clearly validate it with independent means and that we clearly also bring in additional analysis to understand what are the elements and then test that new technology in an environment before we scale it widely, so that clinicians can see, yes, this was useful. If it wasn't useful, how can we make it even better? So it goes back to what we were talking about earlier that we have to bring in human-centered design to figuring out how do we make use of AI or machine learning models and make sure that there's trust in those models and that we can clearly articulate value for the clinicians and care teams on the ground. >> Is that a natural evolution of Arches? >> This is all built around it. Arches is the technology platform, but there's no magical technology that's going to change how humans interact. And so the way we think about each project is we think about what are the technological components and what are the human factors components? And we have to think about the entire care pathway. I'll go back to that example, the chronic kidney disease. She identified that we were under identifying African Americans for chronic kidney disease. So she changed the algorithm. Not only did she change the algorithm, we also had to think about who would be informed of those changes, how would that change, who would be connected to the veteran in that point of care and build out the care pathway in the care team and that's really how you actually influence an outcome. Surfacing an insight is important, but it's one part of a much larger picture. >> So what is Arches? You said it's a technology platform built on open source. At least, there's a lot of open source in there. And it's got API connectors to all the legacy technologies that you need it to. Can you describe, paint a picture of what it actually is? >> Arches is evolving as it should. So it's designed to meet the unique needs that aren't being met by other infrastructure in the VA. So we started first by identifying the need for cloud compute, so it's in the cloud, it has open source technology so that we're not stuck with any one provider and also has the ability to use containers to be able to move insights out of Arches to an enterprise solution. We're also bringing in multi-cloud strategy, which also something had been discussed quite a bit at this conference, to make sure that we're not saying only one cloud provider can be the solution for veterans' needs. Our mission is serving veterans and so we want to have access to all the technology and not just one and so we're looking at how do we expand the scope to make sure that we have the most variety possible so we can meet the needs of veterans. >> I can add a little bit to it, as well. Think of Arches as a program. It's an incubation space under the office of innovation. So it's a place where the governance allows for trying new ideas and really pushing the envelope for VA in general. There's not a lot of organizations, if any at VA, that allow for that type of incubation and so Arches is in a unique position to create new technologies and new novel approaches to solving big problems. And then the next step to that is moving the work from Arches out into the enterprise, as you called it out. So for instance, the system of engagement where the actual clinicians interact with patients, the model needs to find its way there and we can't do that in a way that disturbs the current workflow that the clinicians have. We need to be able to bring the model to where the clinician is, have those recommendations, probabilities and predictions surfaced to the clinician in a way that is precise to their existing workflow. They need it at the time they need it. Arches itself is not delivering that part of it. It's more like the place where the innovation happens and the incubation really occurs and then it's about taking this container, really, and moving out to other systems that are already deployed out to the hospitals, the edge, and in the cloud. >> And the federated governance occurs in Arches or elsewhere? >> It happens across the continuum. It's starting in Arches. the clinical validation that happens there is wickedly important, because the clinicians need to know that what they're working with is actually legit. And so when they know that the researchers and the clinicians who are involved in that incubation period have done their work, they can feel confident with the recommendations they're getting from the machine learning models that are getting deployed to one of them. >> So many questions, so little time. What's the business impact? How would you describe that? >> For me, it's an emotional impact. People have a sense of, "I have a place to develop a solution and I can get in there quick, and I can test out an idea. I could potentially partner with an external partner or if I have the talents and skills to do it myself." It's empowering all of those innovators who have great ideas to work together to test and develop and validate solutions, and they're not waiting years to get the idea off the ground. >> Amazing. >> Go ahead, bring it. >> Is Arches open source? >> Arches is a platform and it has open source component. So that the underlying infrastructure of technology is open source. >> Why was it important to you that this be built on an open source platform? >> It's important for us that we not marry ourself to any one technology and that we allow for, as much as possible, transparency and many different tools and the right tools for the right solution. So we didn't want to find ourselves connected to only one way of doing things. We want to have versatility to have the right tool for the right problem at the right time. >> I'm so sorry, we're out of time. This is so interesting and I really appreciate you here guys, coming on and sharing your insights for theCUBE audience. All right, keep it right there. This is Dave Vellante for Paul Gillin. We're in day two of Red Hat Summit 2022. You're watching theCUBE. (digital pulsing music) >> Due to the pandemic, the federal government declared a public health emergency, which created an urgency for healthcare coverage. >> One of the biggest-

>> theCube presents Dell Technologies World, brought to you by Dell. >> Hi everyone, welcome back to Dell Technologies World 2022. You're watching theCube's coverage of this, three-day coverage wall to wall. My name is David Vellante John Furrier's here, Lisa Martin, David Nicholson. Talk of the town here is data. And one of the big announcements at the show is Snowflake and Dell partnering up, building ecosystems. Snowflake reaching into on-prem, allowing customers to actually access the Snowflake Data Cloud without moving the data or if they want to move the data they can. This is really one of the hotter announcements of the show. Martin Glynn is here, he's the Senior Director of Storage Product Management at Dell Technologies. And Clark Patterson, he's the Head of Product Marketing for Snowflake. Guys, welcome. >> Thanks for having us. >> So a lot of buzz around this and, you know, Clark, you and I have talked about the need to really extend your data vision. And this really is the first step ever you've taken on-prem. Explain the motivation for this from your customer's perspective. >> Yeah. I mean, if you step back and think about Snowflake's vision and our mission of mobilizing the world's data, it's all around trying to break down silos for however customers define what a silo is, right? So we've had a lot of success breaking down silos from a workload perspective where we've expanded the platform to be data warehousing, and data engineering, and machine learning, and data science, and all the kind of compute intensive ways that people work with us. We've also had a lot of success in our sharing capabilities and how we're breaking down silos of organizations, right? So I can share data more seamlessly within my team, I can do it across totally disparate organizations, and break down silos that way. So this partnership is really like the next leg of the stool, so to speak, where we're breaking down the silos of the the data and where the data lives ultimately, right? So up until this point, Cloud, all focus there, and now we have this opportunity with Dell to expand that and into on-premises world and people can bring all those data sets together. >> And the data target for this Martin, is Dell ECS, right? Your object store, and it's got S3 compatibility. Explain that. >> Yeah, we've actually got sort of two flavors. We'll start with ECS, which is our turnkey object storage solution. Object storage offers sort of the ultimate in flexibility, you know, potential performance, ease of use, right? Which is why it fits so well with Snowflake's mission for sort of unlocking, you know, the data within the data center. So we'll offer it to begin with ECS, and then we also recently announced our software defined object scale solution. So add even more flexibility there. >> Okay. And the clock, the way it works is I can now access non-native Snowflake data using what? Materialized views, external tables, how does that work? >> Some combination of all the above. So we've had in Snowflake a capability called external tables which we refer to, it goes hand in hand with this notion of external stages. Basically through the combination of those two capabilities, it's a metadata layer on data wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud up until this point. So it's effectively an extension of that functionality into the Dell on-premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake so that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> Okay. So for a while you've allowed non-native Snowflake data but it had to be in the Cloud. >> Correct. >> It was the first time it's on-prem, >> that's correct >> that's the innovation here. Okay. And if I want to bring it into the Cloud, can I? >> Yeah, the connection here will help in a migration sense as well, right? So that's the good thing is, it's really giving the user the choice. So we are integrating together as partners to make connection as seamless as possible. And then the end user will say like, look I've got data that needs to live on-premises, for whatever reasons, data sovereignty whatever they decide. And they can keep it there and still do the analytics in another place. But if there's a need and a desire to use this as an opportunity to migrate some of that data to Cloud, that connection between our two platforms will make that easier. >> Well, Michael always says, "Hey, it's customer choice, we're flexible." So you're cool with that? That's been the mission since we kind of came together, right? Is if our customers needed to stay in their data center, if that makes more sense from a cost perspective or, you know, a data gravity perspective, then they can do that. But we also want to help them unlock the value of that data. So if they need to copy it up to the public Cloud and take advantage of it, we're going to integrate directly with Snowflake to make that really easy to do. >> So there are engineering integrations here, obviously that's required. Can you describe what that looks like? Give us the details on when it's available. >> Sure. So it's going to be sort of second half this year that you'll see, we're demoing it this week, but the availability we second half this year. And fundamentally, it's the way Clark described it, that Snowflake will reach into our S3 interface using the standard S3 interface. We're qualifying between the way they expect that S3 interface to present the data and the way our platform works, just to ensure that there's smooth interaction between the two. So that's sort of the first simplest use case. And then the second example we gave where the customer can copy some of that data up to the public Cloud. We're basically copying between two S3 buckets and making sure that Snowflake's Snowpipe is aware that data's being made available and can easily ingest it. >> And then that just goes into a virtual warehouse- >> Exactly. >> and customer does to know or care. >> Yep Exactly. >> Yeah. >> The compute happens in Snowflake the way it does in any other manner. >> And I know you got to crawl, walk, run second half of this year, but I would imagine, okay, you're going to start with AWS, correct? And then eventually you go to other Clouds. I mean, that's going to take other technical integrations, I mean, obviously. So should we assume there's a roadmap here or is this a one and done? >> I would assume that, I mean, based on our multi-Cloud approach, that's kind of our approach at least, yeah. >> Kind of makes sense, right? I mean, that would seem to be a natural progression. My other thought was, okay, I've got operational systems. They might be transaction systems running on a on a PowerMax. >> Yeah. >> Is there a way to get the data into an object store and make that available, now that opens up even more workloads. I know you're not committing to doing that, but it just, conceptually, it seems like something a customer might want to do. >> Yeah. I, a hundred percent, agree. I mean, I think when we brought our team together we started with a blank slate. It was what's the best solution we can build. We landed on this sort of first step, but we got lots of feedback from a lot of our big joint customers about you know, this system over there, this potential integration over here, and whether it's, you know, PowerMax type systems or other file workloads with native Snowflake data types. You know, I think this is just the beginning, right? We have lots of potential here. >> And I don't think you've announced pricing, right? It's premature for that. But have you thought about, and how are you thinking about the pricing model? I mean, you're a consumption based pricing, is that kind of how this is going to work? Or is it a sort of a new pricing model or haven't you figured that out yet? >> I don't know if you've got any details on that, but from a Snowflake perspective, I would assume it's consistent with how our customers engage with us today. >> Yeah. >> And we'll offer both possibilities, right? So you can either continue with the standard, you know, sort of CapEx motion, maybe that's the most optimal for you from a cost perspective, or you can take advantage through our OpEx option, right? So you can do consumption on-prem also. >> Okay. So it could be a dual model, right? Depending on what the customer wants. If they're a Snowflake customer, obviously it's going to be consumption based, however, you guys price. What's happening, Clark, in in the market? Explain why Snowflake has so much momentum and, you know, traction in the marketplace. >> So like I spent a lot of time doing analysis on why we win and lose, core part of my role. And, you know, there's a couple of, there's really three things that come up consistently as to why people people are really excited about Snowflake platform. One is the most simplest thing of all. It feels like is just ease of use and it just works, right? And I think the way that this platform was built for the Cloud from the ground up all the way back 10 years ago, really a lot allows us to deliver that seamless experience of just like instant compute when you want it, it goes away, you know, only pay for what you use. Very few knobs to turn and things like that. And so people absolutely love that factor. The other is multi-Cloud. So, you know, there's definitely a lot of organizations out there that have a multi-Cloud strategy, and, you know, what that means to them can be highly variable, but regardless, they want to be able to interact across Clouds in some capacity. And of course we are a single platform, like literally one single interface, consistent across all the three Cloud providers that we work upon. And it gives them that flexibility to mix and match Cloud infrastructure under any Snowflake however they see fit. The last piece of it is sharing. And, you know, I think it's that ability as I kind of alluded to around like breaking down organizational silos, and allow people to be able to actually connect with each other in ways that you couldn't do before. Like, if you think about how you and I would've shared data before, I'd be like, "Hey, Dave, I'm going to unload this table into a spreadsheet and I'm going to send it over in email." And there's the whole host of issues that get introduced in that and world, now it's like instantly available. I have a lot of control over it, it's governed it's all these other things. And I can create kind of walled gardens, so to speak, of how far out I want that to go. It could be in a controlled environment of organizations that I want to collaborate with, or I can put it on our marketplace and expose it to the whole world, because I think there's a value in that. And if I choose I can monetize it, right? So those, you know, the ease of use aspect of it, absolutely, it's just a fantastic platform. The multi-Cloud aspect of it and our unique differentiation around sharing in our marketplace and monetization. >> Yeah, on the sharing front. I mean, it's now discoverable. Like if you send me an email, like what'd you call that? When did you send that email? And then the same time I can forward that to somebody else's not governed. >> Yeah. >> All right. So that just be creates a nightmare for the compliance. >> Right. Yeah. You think about how you revoke access in that situation. You just don't, right? Now I can just turn it off and you go in to run your query. >> Don't get access on that data anymore. Yeah. Okay. And then the other thing I wanted to ask you, Clark is Snowflake started really as analytics platform, simplifying data warehousing, you're moving into that world of data science, you know, the whole data lake movement, bringing those two worlds together. You know, I was talking to Ben Ward about this, maybe there's a semantic layer that helps us kind of talk between those two worlds, but you don't care, right? If it's in an object store, it can play in both of those worlds, right? >> That's right. >> Yeah, it's up to you to figure it out and the customer- >> Yeah. >> from a storage standpoint. Here it is, serve it up. >> And that's the thrust of this announcement, right? Is bringing together two great companies, the Dell platform, the Snowflake platform, and allowing organizations to bring that together. And they decide like it, as we all know, customers decide how they're going to build their architecture. And so this is just another way that we're helping them leverage the capabilities of our two great platforms. >> Does this push or pull or little bit of both? I mean, where'd this come from? Or customers saying, "Hey, it would be kind of cool if we could have this." Or is it more, "Hey, what do you guys think?" You know, where are you at with that? >> It was definitely both, right? I mean, so we certainly started with, you know, a high level idea that, you know, the technologies are complimentary, right? I mean, as Clark just described, and at the same time we had customers coming to us saying, "Hey, wait a minute, I'm doing this over here, and this over here, how can I make this easier?" So that was like I said, we started with a blank sheet and lots of long customer conversations and this is what resulted. So >> So what are the sequence of events to kind of roll this out? You said it's second half, you know, when do you start getting customers involved? Do you have your already, you know, to poke at this and what's that look like? >> Yeah, sure. I can weigh in there. So, absolutely. We've had a few of our big customers that have been involved sort of in the design already who understand how they want to use it. So I think our expectation is that now that the sort of demonstrations have been in place, we have some pre functionality, we're going to see some initial testing and usage, some beta type situations with our customers. And then second half, we'll ramp from there. >> It's got to be a huge overlap between Dell customers and Snowflake customers. I mean, it's hundred billion. You can't not bump into Dell somewhere. >> Exactly. Yeah, you know. >> So where do you guys want to see this relationship go, kind of how should we measure success? Maybe you could each give your perspectives of that. >> I mean, for us, I think it's really showing the value of the Snowflake platform in this new world where there's a whole new ecosystem of data that is accessible to us, right? So seeing those organizations that are saying like, "Look, I'm doing new things with on-premises data that I didn't think that I could do before", or, "I'm driving efficiency in how I do analytics, and data engineering, and data science, in ways that I couldn't do before," 'cause they were locked out of using a Snowflake-like technology, right? So I think for me, that's going to be that real excitement. I'm really curious to see how the collaboration and the sharing component comes into this, you know, where you can think of having an on-premises data strategy and a need, right? But you can really connect to Cloud native customers and partners and suppliers that live in the Snowflake ecosystem, and that wasn't possible before. And so that is very conceivable and very possible through this relationship. So seeing how those edges get created in in our world and how people start to collaborate across data, both in the Cloud and on-prem is going to be really exciting. >> I remember I asked Frank, it was kind of early in the pandemic. I asked him, come on, tell me about how you're managing things. And he was awesome. And I asked him to at the time, you know, "You're ever going to do, you know, bring this platform on-prem?" He's like unequivocal, "No way, that's never going to happen. We're not going to do it halfway house ware Cloud only." And I kept thinking, but there's got to be a way to expand that team. There's so much data out there, and so boom, now we see the answer . Martin, from your standpoint, what does success look like? >> I think it starts with our partnership, right? So I've been doing this a long time. Probably the first time I've worked so closely with a partner like Snowflake. Joint customer conversations, joint solutioning, making sure what we're building is going to be really, truly as useful as possible to them. And I think we're going to let them guide us as we go forward here, right? You mentioned, you know, systems or record or other potential platforms. We're going to let them tell us where exactly the most value will come from the integration between the two companies. >> Yeah. Follow data. I mean, remember in the old days a hardware company like Dell would go to an ISP like Snowflake and say, "Hey, we ran some benchmarks. Your software runs really fast on our hardware, can we work together?" And you go, "Yeah, of course. Yeah, no problem." But wow! What a different dynamic it is today. >> Yeah. Yeah, absolutely. >> All right guys. Hey, thanks so much for coming to theCube. It's great to see you. We'll see you at the Snowflake Summit in June. >> Snowflake Summit in a month and a half. >> Looking forward to that. All right. Thank you again. >> Thank you Dave. >> All right. Keep it right there everybody. This is Dave Vellante, wall to wall coverage of Dell Tech World 2022. We'll be right back. (gentle music)

>> theCube presents Dell Technologies World, brought to you by Dell. >> Hi everyone, welcome back to Dell Technologies World 2022. You're watching theCube's coverage of this, three-day coverage wall to wall. My name is David Vellante John Furrier's here, Lisa Martin, David Nicholson. Talk of the town here is data. And one of the big announcements at the show is Snowflake and Dell partnering up, building ecosystems. Snowflake reaching into on-prem, allowing customers to actually access the Snowflake Data Cloud without moving the data or if they want to move the data they can. This is really one of the hotter announcements of the show. Martin Glynn is here, he's the Senior Director of Storage Product Management at Dell Technologies. And Clark Patterson, he's the Head of Product Marketing for Snowflake. Guys, welcome. >> Thanks for having us. >> So a lot of buzz around this and, you know, Clark, you and I have talked about the need to really extend your data vision. And this really is the first step ever you've taken on-prem. Explain the motivation for this from your customer's perspective. >> Yeah. I mean, if you step back and think about Snowflake's vision and our mission of mobilizing the world's data, it's all around trying to break down silos for however customers define what a silo is, right? So we've had a lot of success breaking down silos from a workload perspective where we've expanded the platform to be data warehousing, and data engineering, and machine learning, and data science, and all the kind of compute intensive ways that people work with us. We've also had a lot of success in our sharing capabilities and how we're breaking down silos of organizations, right? So I can share data more seamlessly within my team, I can do it across totally disparate organizations, and break down silos that way. So this partnership is really like the next leg of the stool, so to speak, where we're breaking down the silos of the the data and where the data lives ultimately, right? So up until this point, Cloud, all focus there, and now we have this opportunity with Dell to expand that and into on-premises world and people can bring all those data sets together. >> And the data target for this Martin, is Dell ECS, right? Your object store, and it's got S3 compatibility. Explain that. >> Yeah, we've actually got sort of two flavors. We'll start with ECS, which is our turnkey object storage solution. Object storage offers sort of the ultimate in flexibility, you know, potential performance, ease of use, right? Which is why it fits so well with Snowflake's mission for sort of unlocking, you know, the data within the data center. So we'll offer it to begin with ECS, and then we also recently announced our software defined object scale solution. So add even more flexibility there. >> Okay. And the clock, the way it works is I can now access non-native Snowflake data using what? Materialized views, external tables, how does that work? >> Some combination of all the above. So we've had in Snowflake a capability called external tables which we refer to, it goes hand in hand with this notion of external stages. Basically through the combination of those two capabilities, it's a metadata layer on data wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud up until this point. So it's effectively an extension of that functionality into the Dell on-premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake so that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> Okay. So for a while you've allowed non-native Snowflake data but it had to be in the Cloud. >> Correct. >> It was the first time it's on-prem, >> that's correct >> that's the innovation here. Okay. And if I want to bring it into the Cloud, can I? >> Yeah, the connection here will help in a migration sense as well, right? So that's the good thing is, it's really giving the user the choice. So we are integrating together as partners to make connection as seamless as possible. And then the end user will say like, look I've got data that needs to live on-premises, for whatever reasons, data sovereignty whatever they decide. And they can keep it there and still do the analytics in another place. But if there's a need and a desire to use this as an opportunity to migrate some of that data to Cloud, that connection between our two platforms will make that easier. >> Well, Michael always says, "Hey, it's customer choice, we're flexible." So you're cool with that? That's been the mission since we kind of came together, right? Is if our customers needed to stay in their data center, if that makes more sense from a cost perspective or, you know, a data gravity perspective, then they can do that. But we also want to help them unlock the value of that data. So if they need to copy it up to the public Cloud and take advantage of it, we're going to integrate directly with Snowflake to make that really easy to do. >> So there are engineering integrations here, obviously that's required. Can you describe what that looks like? Give us the details on when it's available. >> Sure. So it's going to be sort of second half this year that you'll see, we're demoing it this week, but the availability we second half this year. And fundamentally, it's the way Clark described it, that Snowflake will reach into our S3 interface using the standard S3 interface. We're qualifying between the way they expect that S3 interface to present the data and the way our platform works, just to ensure that there's smooth interaction between the two. So that's sort of the first simplest use case. And then the second example we gave where the customer can copy some of that data up to the public Cloud. We're basically copying between two S3 buckets and making sure that Snowflake's Snowpipe is aware that data's being made available and can easily ingest it. >> And then that just goes into a virtual warehouse- >> Exactly. >> and customer does to know or care. >> Yep Exactly. >> Yeah. >> The compute happens in Snowflake the way it does in any other manner. >> And I know you got to crawl, walk, run second half of this year, but I would imagine, okay, you're going to start with AWS, correct? And then eventually you go to other Clouds. I mean, that's going to take other technical integrations, I mean, obviously. So should we assume there's a roadmap here or is this a one and done? >> I would assume that, I mean, based on our multi-Cloud approach, that's kind of our approach at least, yeah. >> Kind of makes sense, right? I mean, that would seem to be a natural progression. My other thought was, okay, I've got operational systems. They might be transaction systems running on a on a PowerMax. >> Yeah. >> Is there a way to get the data into an object store and make that available, now that opens up even more workloads. I know you're not committing to doing that, but it just, conceptually, it seems like something a customer might want to do. >> Yeah. I, a hundred percent, agree. I mean, I think when we brought our team together we started with a blank slate. It was what's the best solution we can build. We landed on this sort of first step, but we got lots of feedback from a lot of our big joint customers about you know, this system over there, this potential integration over here, and whether it's, you know, PowerMax type systems or other file workloads with native Snowflake data types. You know, I think this is just the beginning, right? We have lots of potential here. >> And I don't think you've announced pricing, right? It's premature for that. But have you thought about, and how are you thinking about the pricing model? I mean, you're a consumption based pricing, is that kind of how this is going to work? Or is it a sort of a new pricing model or haven't you figured that out yet? >> I don't know if you've got any details on that, but from a Snowflake perspective, I would assume it's consistent with how our customers engage with us today. >> Yeah. >> And we'll offer both possibilities, right? So you can either continue with the standard, you know, sort of CapEx motion, maybe that's the most optimal for you from a cost perspective, or you can take advantage through our OpEx option, right? So you can do consumption on-prem also. >> Okay. So it could be a dual model, right? Depending on what the customer wants. If they're a Snowflake customer, obviously it's going to be consumption based, however, you guys price. What's happening, Clark, in in the market? Explain why Snowflake has so much momentum and, you know, traction in the marketplace. >> So like I spent a lot of time doing analysis on why we win and lose, core part of my role. And, you know, there's a couple of, there's really three things that come up consistently as to why people people are really excited about Snowflake platform. One is the most simplest thing of all. It feels like is just ease of use and it just works, right? And I think the way that this platform was built for the Cloud from the ground up all the way back 10 years ago, really a lot allows us to deliver that seamless experience of just like instant compute when you want it, it goes away, you know, only pay for what you use. Very few knobs to turn and things like that. And so people absolutely love that factor. The other is multi-Cloud. So, you know, there's definitely a lot of organizations out there that have a multi-Cloud strategy, and, you know, what that means to them can be highly variable, but regardless, they want to be able to interact across Clouds in some capacity. And of course we are a single platform, like literally one single interface, consistent across all the three Cloud providers that we work upon. And it gives them that flexibility to mix and match Cloud infrastructure under any Snowflake however they see fit. The last piece of it is sharing. And, you know, I think it's that ability as I kind of alluded to around like breaking down organizational silos, and allow people to be able to actually connect with each other in ways that you couldn't do before. Like, if you think about how you and I would've shared data before, I'd be like, "Hey, Dave, I'm going to unload this table into a spreadsheet and I'm going to send it over in email." And there's the whole host of issues that get introduced in that and world, now it's like instantly available. I have a lot of control over it, it's governed it's all these other things. And I can create kind of walled gardens, so to speak, of how far out I want that to go. It could be in a controlled environment of organizations that I want to collaborate with, or I can put it on our marketplace and expose it to the whole world, because I think there's a value in that. And if I choose I can monetize it, right? So those, you know, the ease of use aspect of it, absolutely, it's just a fantastic platform. The multi-Cloud aspect of it and our unique differentiation around sharing in our marketplace and monetization. >> Yeah, on the sharing front. I mean, it's now discoverable. Like if you send me an email, like what'd you call that? When did you send that email? And then the same time I can forward that to somebody else's not governed. >> Yeah. >> All right. So that just be creates a nightmare for the compliance. >> Right. Yeah. You think about how you revoke access in that situation. You just don't, right? Now I can just turn it off and you go in to run your query. >> Don't get access on that data anymore. Yeah. Okay. And then the other thing I wanted to ask you, Clark is Snowflake started really as analytics platform, simplifying data warehousing, you're moving into that world of data science, you know, the whole data lake movement, bringing those two worlds together. You know, I was talking to Ben Ward about this, maybe there's a semantic layer that helps us kind of talk between those two worlds, but you don't care, right? If it's in an object store, it can play in both of those worlds, right? >> That's right. >> Yeah, it's up to you to figure it out and the customer- >> Yeah. >> from a storage standpoint. Here it is, serve it up. >> And that's the thrust of this announcement, right? Is bringing together two great companies, the Dell platform, the Snowflake platform, and allowing organizations to bring that together. And they decide like it, as we all know, customers decide how they're going to build their architecture. And so this is just another way that we're helping them leverage the capabilities of our two great platforms. >> Does this push or pull or little bit of both? I mean, where'd this come from? Or customers saying, "Hey, it would be kind of cool if we could have this." Or is it more, "Hey, what do you guys think?" You know, where are you at with that? >> It was definitely both, right? I mean, so we certainly started with, you know, a high level idea that, you know, the technologies are complimentary, right? I mean, as Clark just described, and at the same time we had customers coming to us saying, "Hey, wait a minute, I'm doing this over here, and this over here, how can I make this easier?" So that was like I said, we started with a blank sheet and lots of long customer conversations and this is what resulted. So >> So what are the sequence of events to kind of roll this out? You said it's second half, you know, when do you start getting customers involved? Do you have your already, you know, to poke at this and what's that look like? >> Yeah, sure. I can weigh in there. So, absolutely. We've had a few of our big customers that have been involved sort of in the design already who understand how they want to use it. So I think our expectation is that now that the sort of demonstrations have been in place, we have some pre functionality, we're going to see some initial testing and usage, some beta type situations with our customers. And then second half, we'll ramp from there. >> It's got to be a huge overlap between Dell customers and Snowflake customers. I mean, it's hundred billion. You can't not bump into Dell somewhere. >> Exactly. Yeah, you know. >> So where do you guys want to see this relationship go, kind of how should we measure success? Maybe you could each give your perspectives of that. >> I mean, for us, I think it's really showing the value of the Snowflake platform in this new world where there's a whole new ecosystem of data that is accessible to us, right? So seeing those organizations that are saying like, "Look, I'm doing new things with on-premises data that I didn't think that I could do before", or, "I'm driving efficiency in how I do analytics, and data engineering, and data science, in ways that I couldn't do before," 'cause they were locked out of using a Snowflake-like technology, right? So I think for me, that's going to be that real excitement. I'm really curious to see how the collaboration and the sharing component comes into this, you know, where you can think of having an on-premises data strategy and a need, right? But you can really connect to Cloud native customers and partners and suppliers that live in the Snowflake ecosystem, and that wasn't possible before. And so that is very conceivable and very possible through this relationship. So seeing how those edges get created in in our world and how people start to collaborate across data, both in the Cloud and on-prem is going to be really exciting. >> I remember I asked Frank, it was kind of early in the pandemic. I asked him, come on, tell me about how you're managing things. And he was awesome. And I asked him to at the time, you know, "You're ever going to do, you know, bring this platform on-prem?" He's like unequivocal, "No way, that's never going to happen. We're not going to do it halfway house ware Cloud only." And I kept thinking, but there's got to be a way to expand that team. There's so much data out there, and so boom, now we see the answer . Martin, from your standpoint, what does success look like? >> I think it starts with our partnership, right? So I've been doing this a long time. Probably the first time I've worked so closely with a partner like Snowflake. Joint customer conversations, joint solutioning, making sure what we're building is going to be really, truly as useful as possible to them. And I think we're going to let them guide us as we go forward here, right? You mentioned, you know, systems or record or other potential platforms. We're going to let them tell us where exactly the most value will come from the integration between the two companies. >> Yeah. Follow data. I mean, remember in the old days a hardware company like Dell would go to an ISP like Snowflake and say, "Hey, we ran some benchmarks. Your software runs really fast on our hardware, can we work together?" And you go, "Yeah, of course. Yeah, no problem." But wow! What a different dynamic it is today. >> Yeah. Yeah, absolutely. >> All right guys. Hey, thanks so much for coming to theCube. It's great to see you. We'll see you at the Snowflake Summit in June. >> Snowflake Summit in a month and a half. >> Looking forward to that. All right. Thank you again. >> Thank you Dave. >> All right. Keep it right there everybody. This is Dave Vellante, wall to wall coverage of Dell Tech World 2022. We'll be right back. (gentle music)

>>Hi everybody. This is Dave Volante. Welcome to this cube conversation where we're going to go back in time a little bit and explore the early days of Kubernetes. Talk about how it formed the improbable events, perhaps that led to it. And maybe how customers are taking advantage of containers and container orchestration today, and maybe where the industry is going. Matt Provo is here. He's the founder and CEO of storm forge and Chandler Huntington hoes. Hoisington is the general manager of EKS edge and hybrid AWS guys. Thanks for coming on. Good to see you. Thanks for having me. Thanks. So, Jenny, you were the vice president of engineering at miso sphere. Is that, is that correct? >>Well, uh, vice-president engineering basis, fear and then I ran product and engineering for DTQ masons. >>Yeah. Okay. Okay. So you were there in the early days of, of container orchestration and Matt, you, you were working at a S a S a Docker swarm shop, right? Yep. Okay. So I mean, a lot of people were, you know, using your platform was pretty novel at the time. Uh, it was, it was more sophisticated than what was happening with, with Kubernetes. Take us back. What was it like then? Did you guys, I mean, everybody was coming out. I remember there was, I think there was one Docker con and everybody was coming, the Kubernetes was announced, and then you guys were there, doc Docker swarm was, was announced and there were probably three or four other startups doing kind of container orchestration. And what, what were those days like? Yeah. >>Yeah. I wasn't actually atmosphere for those days, but I know them well, I know the story as well. Um, uh, I came right as we started to pivot towards Kubernetes there, but, um, it's a really interesting story. I mean, obviously they did a documentary on it and, uh, you know, people can watch that. It's pretty good. But, um, I think that, from my perspective, it was, it was really interesting how this happened. You had basically, uh, con you had this advent of containers coming out, right? So, so there's new novel technology and Solomon, and these folks started saying, Hey, you know, wait a second, wait if I put a UX around these couple of Linux features that got launched a couple of years ago, what does that look like? Oh, this is pretty cool. Um, so you have containers starting to crop up. And at the same time you had folks like ThoughtWorks and other kind of thought leaders in the space, uh, starting to talk about microservices and saying, Hey, monoliths are bad and you should break up these monoliths into smaller pieces. >>And any Greenfield application should be broken up into individuals, scalable units that a team can can own by themselves, and they can scale independent of each other. And you can write tests against them independently of other components. And you should break up these big, big mandalas. And now we are kind of going back to model this, but that's for another day. Um, so, so you had microservices coming out and then you also had containers coming out, same time. So there was like, oh, we need to put these microservices in something perfect. We'll put them in containers. And so at that point, you don't really, before that moment, you didn't really need container orchestration. You could just run a workload in a container and be done with it, right? You didn't need, you don't need Kubernetes to run Docker. Um, but all of a sudden you had tons and tons of containers and you had to manage these in some way. >>And so that's where container orchestration came, came from. And, and Ben Heineman, the founder of Mesa was actually helping schedule spark at the time at Berkeley. Um, and that was one of the first workloads with spark for Macy's. And then his friends at Twitter said, Hey, come over, can you help us do this with containers at Twitter? He said, okay. So when it helped them do it with containers at Twitter, and that's kinda how that branch of the container wars was started. And, um, you know, it was really, really great technology and it actually is still in production in a lot of shops today. Um, uh, more and more people are moving towards Kubernetes and Mesa sphere saw that trend. And at the end of the day, Mesa sphere was less concerned about, even though they named the company Mesa sphere, they were less concerned about helping customers with Mesa specifically. They really want to help customers with these distributed problems. And so it didn't make sense to, to just do Mesa. So they would took on Kubernetes as well. And I hope >>I don't do that. I remember, uh, my, my co-founder John furrier introduced me to Jerry Chen way back when Jerry is his first, uh, uh, VC investment with Greylock was Docker. And we were talking in these very, obviously very excited about it. And, and his Chandler was just saying, it said Solomon and the team simplified, you know, containers, you know, simple and brilliant. All right. So you guys saw the opportunity where you were Docker swarm shop. Why? Because you needed, you know, more sophisticated capabilities. Yeah. But then you, you switched why the switch, what was happening? What was the mindset back then? We ran >>And into some scale challenges in kind of operationalize or, or productizing our kind of our core machine learning. And, you know, we, we, we saw kind of the, the challenges, luckily a bit ahead of our time. And, um, we happen to have someone on the team that was also kind of moonlighting, uh, as one of the, the original core contributors to Kubernetes. And so as this sort of shift was taking place, um, we, we S we saw the flexibility, uh, of what was becoming Kubernetes. Um, and, uh, I'll never forget. I left on a Friday and came back on a Monday and we had lifted and shifted, uh, to Kubernetes. Uh, the challenge was, um, you know, you, at that time, you, you didn't have what you have today through EKS. And, uh, those kinds of services were, um, just getting that first cluster up and running was, was super, super difficult, even in a small environment. >>And so I remember we, you know, we, we finally got it up and running and it was like, nobody touch it, don't do anything. Uh, but obviously that doesn't, that doesn't scale either. And so that's really, you know, being kind of a data science focused shop at storm forge from the very beginning. And that's where our core IP is. Uh, our, our team looked at that problem. And then we looked at, okay, there are a bunch of parameters and ways that I can tune this application. And, uh, why are the configurations set the way that they are? And, you know, uh, is there room to explore? And that's really where, unfortunately, >>Because Mesa said much greater enterprise capabilities as the Docker swarm, at least they were heading in that direction, but you still saw that Kubernetes was, was attractive because even though it didn't have all the security features and enterprise features, because it was just so simple. I remember Jen Goldberg who was at Google at the time saying, no, we were focused on keeping it simple and we're going from mass adoption, but does that kind of what you said? >>Yeah. And we made a bet, honestly. Uh, we saw that the, uh, you know, the growing community was really starting to, you know, we had a little bit of an inside view because we had, we had someone that was very much in the, in the original part, but you also saw the, the tool chain itself start to, uh, start to come into place right. A little bit. And it's still hardening now, but, um, yeah, we, as any, uh, as any startup does, we, we made a pivot and we made a bet and, uh, this, this one paid off >>Well, it's interesting because, you know, we said at the time, I mean, you had, obviously Amazon invented the modern cloud. You know, Microsoft has the advantage of has got this huge software stays, Hey, just now run it into the cloud. Okay, great. So they had their entry point. Google didn't have an entry point. This is kind of a hail Mary against Amazon. And, and I, I wrote a piece, you know, the improbable, Verizon, who Kubernetes to become the O S you know, the cloud, but, but I asked, did it make sense for Google to do that? And it never made any money off of it, but I would argue they, they were kind of, they'd be irrelevant if they didn't have, they hadn't done that yet, but it didn't really hurt. It certainly didn't hurt Amazon EKS. And you do containers and your customers you've embraced it. Right. I mean, I, I don't know what it was like early days. I remember I've have talked to Amazon people about this. It's like, okay, we saw it and then talk to customers, what are they doing? Right. That's kind of what the mindset is, right? Yeah. >>That's, I, I, you know, I've, I've been at Amazon a couple of years now, and you hear the stories of all we're customer obsessed. We listened to our customers like, okay, okay. We have our company values, too. You get told them. And when you're, uh, when you get first hired in the first day, and you never really think about them again, but Amazon, that really is preached every day. It really is. Um, uh, and that we really do listen to our customers. So when customers start asking for communities, we said, okay, when we built it for them. So, I mean, it's, it's really that simple. Um, and, and we also, it's not as simple as just building them a Kubernetes service. Amazon has a big commitment now to start, you know, getting involved more in the community and working with folks like storm forage and, and really listening to customers and what they want. And they want us working with folks like storm florigen and that, and that's why we're doing things like this. So, well, >>It's interesting, because of course, everybody looks at the ecosystem, says, oh, Amazon's going to kill the ecosystem. And then we saw an article the other day in, um, I think it was CRN, did an article, great job by Amazon PR, but talk about snowflake and Amazon's relationship. And I've said many times snowflake probably drives more than any other ISV out there. And so, yeah, maybe the Redshift guys might not love snowflake, but Amazon in general, you know, they're doing great three things. And I remember Andy Jassy said to me, one time, look, we love the ecosystem. We need the ecosystem. They have to innovate too. If they don't, you know, keep pace, you know, they're going to be in trouble. So that's actually a healthy kind of a dynamic, I mean, as an ecosystem partner, how do you, >>Well, I'll go back to one thing without the work that Google did to open source Kubernetes, a storm forge wouldn't exist, but without the effort that AWS and, and EKS in particular, um, provides and opens up for, for developers to, to innovate and to continue, continue kind of operationalizing the shift to Kubernetes, um, you know, we wouldn't have nearly the opportunity that we do to actually listen to them as well, listen to the users and be able to say, w w w what do you want, right. Our entire reason for existence comes from asking users, like, how painful is this process? Uh, like how much confidence do you have in the, you know, out of the box, defaults that ship with your, you know, with your database or whatever it is. And, uh, and, and how much do you love, uh, manually tuning your application? >>And, and, uh, obviously nobody's said, I love that. And so I think as that ecosystem comes together and continues expanding, um, it's just, it opens up a huge opportunity, uh, not only for existing, you know, EKS and, uh, AWS users to continue innovating, but for companies like storm forge, to be able to provide that opportunity for them as well. And, and that's pretty powerful. So I think without a lot of the moves they've made, um, you know, th the door wouldn't be nearly as open for companies like, who are, you know, growing quickly, but are smaller to be able to, you know, to exist. >>Well, and I was saying earlier that, that you've, you're in, I wrote about this, you're going to get better capabilities. You're clearly seeing that cluster management we've talked about better, better automation, security, the whole shift left movement. Um, so obviously there's a lot of momentum right now for Kubernetes. When you think about bare metal servers and storage, and then you had VM virtualization, VMware really, and then containers, and then Kubernetes as another abstraction, I would expect we're not at the end of the road here. Uh, what's next? Is there another abstraction layer that you would think is coming? Yeah, >>I mean, w for awhile, it looked like, and I remember even with our like board members and some of our investors said, well, you know, well, what about serverless? And, you know, what's the next Kubernetes and nothing, we, as much as I love Kubernetes, um, which I do, and we do, um, nothing about what we particularly do. We are purpose built for Kubernetes, but from a core kind of machine learning and problem solving standpoint, um, we could apply this elsewhere, uh, if we went that direction and so time will tell what will be next, then there will be something, uh, you know, that will end up, you know, expanding beyond Kubernetes at some point. Um, but, you know, I think, um, without knowing what that is, you know, our job is to, to, to serve our, you know, to serve our customers and serve our users in the way that they are asking for that. >>Well, serverless obviously is exploding when you look again, and we tucked the ETR survey data, when you look at, at the services within Amazon and other cloud providers, you know, the functions off, off the charts. Uh, so that's kind of an interesting and notable now, of course, you've got Chandler, you've got edge in your title. You've got hybrid in, in your title. So, you know, this notion of the cloud expanding, it's not just a set of remote services, just only in the public cloud. Now it's, it's coming to on premises. You actually got Andy, Jesse, my head space. He said, one time we just look at it. The data centers is another edge location. Right. Okay. That's a way to look at it and then you've got edge. Um, so that cloud is expanding, isn't it? The definition of cloud is, is, is evolving. >>Yeah, that's right. I mean, customers one-on-one run workloads in lots of places. Um, and that's why we have things like, you know, local zones and wavelengths and outposts and EKS anywhere, um, EKS, distro, and obviously probably lots more things to come. And there's, I always think of like, Amazon's Kubernetes strategy on a manageability scale. We're on one far end of the spectrum, you have EKS distro, which is just a collection of the core Kubernetes packages. And you could, you could take those and stand them up yourself in a broom closet, in a, in a retail shop. And then on the other far in the spectrum, you have EKS far gate where you can just give us your container and we'll handle everything for you. Um, and then we kind of tried to solve everything in between for your data center and for the cloud. And so you can, you can really ask Amazon, I want you to manage my control plane. I want you to manage this much of my worker nodes, et cetera. And oh, I actually want help on prem. And so we're just trying to listen to customers and solve their problems where they're asking us to solve them. Cut, >>Go ahead. No, I would just add that in a more vertically focused, uh, kind of orientation for us. Like we, we believe that op you know, optimization capabilities should transcend the location itself. And, and, and so whether that's part public part, private cloud, you know, that's what I love part of what I love about EKS anywhere. Uh, it, you know, you shouldn't, you should still be able to achieve optimal results that connect to your business objectives, uh, wherever those workloads, uh, are, are living >>Well, don't wince. So John and I coined this term called Supercloud and people laugh about it, but it's different. It's, it's, you know, people talk about multi-cloud, but that was just really kind of vendor diversity. Right? I got to running here, I'm running their money anywhere. Uh, but, but individually, and so Supercloud is this concept of this abstraction layer that floats wherever you are, whether it's on prem, across clouds, and you're taking advantage of those native primitives, um, and then hiding that underlying complexity. And that's what, w re-invent the ecosystem was so excited and they didn't call it super cloud. We, we, we called it that, but they're clearly thinking differently about the value that they can add on top of Goldman Sachs. Right. That to me is an example of a Supercloud they're taking their on-prem data and their, their, their software tooling connecting it to AWS. They're running it on AWS, but they're, they're abstracting that complexity. And I think you're going to see a lot, a lot more of that. >>Yeah. So Kubernetes itself, in many cases is being abstracted away. Yeah. There's a disability of a disappearing act for Kubernetes. And I don't mean that in a, you know, in an, a, from an adoption standpoint, but, uh, you know, Kubernetes itself is increasingly being abstracted away, which I think is, is actually super interesting. Yeah. >>Um, communities doesn't really do anything for a company. Like we run Kubernetes, like, how does that help your bottom line? That at the end of the day, like companies don't care that they're running Kubernetes, they're trying to solve a problem, which is the, I need to be able to deploy my applications. I need to be able to scale them easily. I need to be able to update them easily. And those are the things they're trying to solve. So if you can give them some other way to do that, I'm sure you know, that that's what they want. It's not like, uh, you know, uh, a big bank is making more money because they're running Kubernetes. That's not, that's not the current, >>It gets subsumed. It's just become invisible. Right. Exactly. You guys back to the office yet. What's, uh, what's the situation, >>You know, I, I work for my house and I, you know, we go into the office a couple of times a week, so it's, it's, uh, yeah, it's, it's, it's a crazy time. It's a crazy time to be managing and hiring. And, um, you know, it's, it's, it's, it's definitely a challenge, but there's a lot of benefits of working home. I got two young kids, so I get to see them, uh, grow up a little bit more working, working out of my house. So it's >>Nice also. >>So we're in, even as a smaller startup, we're in 26, 27 states, uh, Canada, Germany, we've got a little bit of presence in Japan, so we're very much distributed. Um, we, uh, have not gone back and I'm not sure we will >>Permanently remote potentially. >>Yeah. I mean, w we made a, uh, pretty like for us, the timing of our series B funding, which was where we started hiring a lot, uh, was just before COVID started really picking up. So we, you know, thankfully made a, a pretty good strategic decision to say, we're going to go where the talent is. And yeah, it was harder to find for sure, especially in w we're competing, it's incredibly competitive. Uh, but yeah, we've, it was a good decision for us. Um, we are very about, you know, getting the teams together in person, you know, as often as possible and in the safest way possible, obviously. Um, but you know, it's been a, it's been a pretty interesting, uh, journey for us and something that I'm, I'm not sure I would, I would change to be honest with you. Yeah. >>Well, Frank Slootman, snowflakes HQ to Montana, and then can folks like Michael Dell saying, Hey, same thing as you, wherever they want to work, bring yourself and wherever you are as cool. And do you think that the hybrid mode for your team is kind of the, the, the operating mode for the, for the foreseeable future is a couple of, >>No, I think, I think there's a lot of benefits in both working from the office. I don't think you can deny like the face-to-face interactions. It feels good just doing this interview face to face. Right. And I can see your mouth move. So it's like, there's a lot of benefits to that, um, over a chime call or a zoom call or whatever, you know, that, that also has advantages, right. I mean, you can be more focused at home. And I think some version of hybrid is probably in the industry's future. I don't know what Amazon's exact plans are. That's above my pay grade, but, um, I know that like in general, the industry is definitely moving to some kind of hybrid model. And like Matt said, getting people I'm a big fan at Mesa sphere, we ran a very diverse, like remote workforce. We had a big office in Germany, but we'd get everybody together a couple of times a year for engineering week or, or something like this. And you'd get a hundred people, you know, just dedicated to spending time together at a hotel and, you know, Vegas or Hamburg or wherever. And it's a really good time. And I think that's a good model. >>Yeah. And I think just more ETR data, the current thinking now is that, uh, the hybrid is the number one sort of model, uh, 36% that the CIO is believe 36% of the workforce are going to be hybrid permanently is kind of their, their call a couple of days in a couple of days out. Um, and the, the percentage that is remote is significantly higher. It probably, you know, high twenties, whereas historically it's probably 15%. Yeah. So permanent changes. And that, that changes the infrastructure. You need to support it, the security models and everything, you know, how you communicate. So >>When COVID, you know, really started hitting and in 2020, um, the big banks for example, had to, I mean, you would want to talk about innovation and ability to, to shift quickly. Two of the bigger banks that have in, uh, in fact, adopted Kubernetes, uh, were able to shift pretty quickly, you know, systems and things that were, you know, historically, you know, it was in the office all the time. And some of that's obviously shifted back to a certain degree, but that ability, it was pretty remarkable actually to see that, uh, take place for some of the larger banks and others that are operating in super regulated environments. I mean, we saw that in government agencies and stuff as well. >>Well, without the cloud, no, this never would've happened. Yeah. >>And I think it's funny. I remember some of the more old school manager thing people are, aren't gonna work less when they're working from home, they're gonna be distracted. I think you're seeing the opposite where people are too much, they get burned out because you're just running your computer all day. And so I think that we're learning, I think everyone, the whole industry is learning. Like, what does it mean to work from home really? And, uh, it's, it's a fascinating thing is as a case study, we're all a part of right now. >>I was talking to my wife last night about this, and she's very thoughtful. And she w when she was in the workforce, she was at a PR firm and a guy came in a guest speaker and it might even be in the CEO of the company asking, you know, what, on average, what time who stays at the office until, you know, who leaves by five o'clock, you know, a few hands up, or who stays until like eight o'clock, you know, and enhancement. And then, so he, and he asked those people, like, why, why can't you get your work done in a, in an eight hour Workday? I go home. Why don't you go in? And I sit there. Well, that's interesting, you know, cause he's always looking at me like, why can't you do, you know, get it done? And I'm saying the world has changed. Yeah. It really has where people are just on all the time. I'm not sure it's sustainable, quite frankly. I mean, I think that we have to, you know, as organizations think about, and I see companies doing it, you guys probably do as well, you know, take a four day, you know, a week weekend, um, just for your head. Um, but it's, there's no playbook. >>Yeah. Like I said, we're a part of a case study. It's also hard because people are distributed now. So you have your meetings on the east coast, you can wake up at seven four, and then you have meetings on the west coast. You stay until seven o'clock therefore, so your day just stretches out. So you've got to manage this. And I think we're, I think we'll figure it out. I mean, we're good at figuring this stuff. >>There's a rise in asynchronous communication. So with things like slack and other tools, as, as helpful as they are in many cases, it's a, it, isn't always on mentality. And like, people look for that little green dot and you know, if you're on the you're online. So my kids, uh, you know, we have a term now for me, cause my office at home is upstairs and I'll come down. And if it's, if it's during the day, they'll say, oh dad, you're going for a walk and talk, you know, which is like, it was my way of getting away from the desk, getting away from zoom. And like, you know, even in Boston, uh, you know, getting outside, trying to at least, you know, get a little exercise or walk and get, you know, get my head away from the computer screen. Um, but even then it's often like, oh, I'll get a slack notification on my phone or someone will call me even if it's not a scheduled walk and talk. Um, uh, and so it is an interesting, >>A lot of ways to get in touch or productivity is presumably going to go through the roof. But now, all right, guys, I'll let you go. Thanks so much for coming to the cube. Really appreciate it. And thank you for watching this cube conversation. This is Dave Alante and we'll see you next time.