(upbeat music) >> Hi, everyone. Welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. As part of International Women's Day, we're featuring some of the leading women in business technology from developer to all types of titles and to the executive level. And one topic that's really important is called Getting a Seat at the Table, board makeup, having representation at corporate boards, private and public companies. It's been a big push. And former technology operating executive and corporate board member, she's a board machine Sue Barsamian, formerly with HPE, Hewlett Packard. Sue, great to see you. CUBE alumni, distinguished CUBE alumni. Thank you for coming on. >> Yes, I'm very proud of my CUBE alumni title. >> I'm sure it opens a lot of doors for you. (Sue laughing) We're psyched to have you on. This is a really important topic, and I want to get into the whole, as women advance up, and they're sitting on the boards, they can implement policy and there's governance. Obviously public companies have very strict oversight, and not strict, but like formal. Private boards have to operate, be nimble. They don't have to share all their results. But still, boards play an important role in the success of scaled up companies. So super important, that representation there is key. >> Yes. >> I want to get into that, but first, before we get started, how did you get into tech? How did it all start for you? >> Yeah, long time ago, I was an electrical engineering major. Came out in 1981 when, you know, opportunities for engineering, if you were kind, I went to Kansas State as an undergrad, and basically in those days you went to Texas and did semiconductors. You went to Atlanta and did communication satellites. You went to Boston or you went to Silicon Valley. And for me, that wasn't too hard a choice. I ended up going west and really, I guess what, embarked on a 40 year career in Silicon Valley and absolutely loved it. Largely software, but some time on the hardware side. Started out in networking, but largely software. And then, you know, four years ago transitioned to my next chapter, which is the corporate board director. And again, focused on technology software and cybersecurity boards. >> For the folks watching, we'll cut through another segment we can probably do about your operating career, but you rose through the ranks and became a senior operating executive at the biggest companies in the world. Hewlett Packard Enterprise, Hewlett Packard Enterprise and others. Very great career, okay. And so now you're kind of like, put that on pause, and you're moving on to the next chapter, which is being a board director. What inspired you to be a board director for multiple public companies and multiple private companies? Well, how many companies are you on? But what's the inspiration? What's the inspiration? First tell me how many board ships you're on, board seats you're on, and then what inspired you to become a board director? >> Yeah, so I'm on three public, and you are limited in terms of the number of publics that you can do to four. So I'm on three public, and I'm on four private from a tech perspective. And those range from, you know, a $4 billion in revenue public company down to a 35 person private company. So I've got the whole range. >> So you're like freelancing, I mean, what is it like? It's a full-time job, obviously. It's a lot of work involved. >> Yeah, yeah, it's. >> John: Why are you doing it? >> Well, you know, so I retired from being an operating executive after 37 years. And, but I loved, I mean, it's tough, right? It's tough these days, particularly with all the pressures out there in the market, not to mention the pandemic, et cetera. But I loved it. I loved working. I loved having a career, and I was ready to back off on, I would say the stresses of quarterly results and the stresses of international travel. You have so much of it. But I wasn't ready to back off from being involved and engaged and continuing to learn new things. I think this is why you come to tech, and for me, why I went to the valley to begin with was really that energy and that excitement, and it's like it's constantly reinventing itself. And I felt like that wasn't over for me. And I thought because I hadn't done boards before I retired from operating roles, I thought, you know, that would fill the bill. And it's honestly, it has exceeded expectations. >> In a good way. You feel good about where you're at and. >> Yeah. >> What you went in, what was the expectation going in and what surprised you? And were there people along the way that kind of gave you some pointers or don't do this, stay away from this. Take us through your experiences. >> Yeah, honestly, there is an amazing network of technology board directors, you know, in the US and specifically in the Valley. And we are all incredibly supportive. We have groups where we get together as board directors, and we talk about topics, and we share best practices and stories, and so I underestimated that, right? I thought I was going to, I thought I was going to enter this chapter where I would be largely giving back after 37 years. You've learned a little bit, right? What I underestimated was just the power of continuing to learn and being surrounded by so many amazing people. When, you know, when you do, you know, multiple boards, your learnings are just multiplied, right? Because you see not just one model, but you see many models. You see not just one problem, but many problems. Not just one opportunity, but many opportunities. And I underestimated how great that would be for me from a learning perspective and then your ability to share from one board to the other board because all of my boards are companies who are also quite close to each other, the executives collaborate. So that has turned out to be really exciting for me. >> So you had the stressful job. You rose to the top of the ranks, quarterly shot clock earnings, and it's hard charging. It's like, it's like, you know, being an athlete, as we say tech athlete. You're a tech athlete. Now you're taking that to the next level, which is now you're juggling multiple operational kind of things, but not with super pressure. But there's still a lot of responsibility. I know there's one board, you got compensation committee, I mean there's work involved. It's not like you're clipping coupons and having pizza. >> Yeah, no, it's real work. Believe me, it's real work. But I don't know how long it took me to not, to stop waking up and looking at my phone and thinking somebody was going to be dropping their forecast, right? Just that pressure of the number, and as a board member, obviously you are there to support and help guide the company and you feel, you know, you feel the pressure and the responsibility of what that role entails, but it's not the same as the frontline pressure every quarter. It's different. And so I did the first type. I loved it, you know. I'm loving this second type. >> You know, the retirement, it's always a cliche these days, but it's not really like what people think it is. It's not like getting a boat, going fishing or whatever. It's doing whatever you want to do, that's what retirement is. And you've chose to stay active. Your brain's being tested, and you're working it, having fun without all the stress. But it's enough, it's like going the gym. You're not hardcore workout, but you're working out with the brain. >> Yeah, no, for sure. It's just a different, it's just a different model. But the, you know, the level of conversations, the level of decisions, all of that is quite high. Which again, I like, yeah. >> Again, you really can't talk about some of the fun questions I want to ask, like what's the valuations like? How's the market, your headwinds? Is there tailwinds? >> Yes, yes, yes. It's an amazing, it's an amazing market right now with, as you know, counter indicators everywhere, right? Something's up, something's down, you know. Consumer spending's up, therefore interest rates go up and, you know, employment's down. And so or unemployment's down. And so it's hard. Actually, I really empathize with, you know, the, and have a great deal of respect for the CEOs and leadership teams of my board companies because, you know, I kind of retired from operating role, and then everybody else had to deal with running a company during a pandemic and then running a company through the great resignation, and then running a company through a downturn. You know, those are all tough things, and I have a ton of respect for any operating executive who's navigating through this and leading a company right now. >> I'd love to get your take on the board conversations at the end if we have more time, what the mood is, but I want to ask you about one more thing real quick before we go to the next topic is you're a retired operating executive. You have multiple boards, so you've got your hands full. I noticed there's a lot of amazing leaders, other female tech athletes joining boards, but they also have full-time jobs. >> Yeah. >> And so what's your advice? Cause I know there's a lot of networking, a lot of sharing going on. There's kind of a balance between how much you can contribute on the board versus doing the day job, but there's a real need for more women on boards, so yet there's a lot going on boards. What's the current state of the union if you will, state of the market relative to people in their careers and the stresses? >> Yeah. >> Cause you left one and jumped in all in there. >> Yeah. >> Some can't do that. They can't be on five boards, but they're on a few. What's the? >> Well, and you know, and if you're an operating executive, you wouldn't be on five boards, right? You would be on one or two. And so I spend a lot of time now bringing along the next wave of women and helping them both in their career but also to get a seat at the table on a board. And I'm very vocal about telling people not to do it the way I do it. There's no reason for it to be sequential. You can, you know, I thought I was so busy and was traveling all the time, and yes, all of that was true, but, and maybe I should say, you know, you can still fit in a board. And so, and what I see now is that your learnings are so exponential with outside perspective that I believe I would've been an even better operating executive had I done it earlier. I know I would've been an even better operating executive had I done it earlier. And so my advice is don't do it the way I did it. You know, it's worked out fine for me, but hindsight's 2020, I would. >> If you can go back and do a mulligan or a redo, what would you do? >> Yeah, I would get on a board earlier, full stop, yeah. >> Board, singular, plural? >> Well, I really, I don't think as an operating executive you can do, you could do one, maybe two. I wouldn't go beyond that, and I think that's fine. >> Yeah, totally makes sense. Okay, I got to ask you about your career. I know technical, you came in at that time in the market, I remember when I broke into the business, very male dominated, and then now it's much better. When you went through the ranks as a technical person, I know you had some blockers and definitely some, probably some people like, well, you know. We've seen that. How did you handle that? What were some of the key pivot points in your journey? And we've had a lot of women tell their stories here on theCUBE, candidly, like, hey, I was going to tell that professor, I'm going to sit in the front row. I'm going to, I'm getting two degrees, you know, robotics and aerospace. So, but they were challenged, even with the aspiration to do tech. I'm not saying that was something that you had, but like have you had experience like that, that you overcome? What were those key points and how did you handle them and how does that help people today? >> Yeah, you know, I have to say, you know, and not discounting that obviously this has been a journey for women, and there are a lot of things to overcome both in the workforce and also just balancing life honestly. And they're all real. There's also a story of incredible support, and you know, I'm the type of person where if somebody blocked me or didn't like me, I tended to just, you know, think it was me and like work harder and get around them, and I'm sure that some of that was potentially gender related. I didn't interpret it that way at the time. And I was lucky to have amazing mentors, many, many, many of whom were men, you know, because they were in the positions of power, and they made a huge difference on my career, huge. And I also had amazing female mentors, Meg Whitman, Ann Livermore at HPE, who you know well. So I had both, but you know, when I look back on the people who made a difference, there are as many men on the list as there are women. >> Yeah, and that's a learning there. Create those coalitions, not just one or the other. >> Yeah, yeah, yeah, absolutely. >> Well, I got to ask you about the, well, you brought up the pandemic. This has come up on some interviews this year, a little bit last year on the International Women's Day, but this year it's resonating, and I would never ask in an interview. I saw an interview once where a host asked a woman, how do you balance it all? And I was just like, no one asked men that. And so it's like, but with remote work, it's come up now the word empathy around people knowing each other's personal situation. In other words, when remote work happened, everybody went home. So we all got a glimpse of the backdrop. You got, you can see what their personal life was on Facebook. We were just commenting before we came on camera about that. So remote work really kind of opened up this personal side of everybody, men and women. >> Yeah. >> So I think this brings this new empathy kind of vibe or authentic self people call it. Is remote work an opportunity or a threat for advancement of women in tech? >> It's a much debated topic. I look at it as an opportunity for many of the reasons that you just said. First of all, let me say that when I was an operating executive and would try to create an environment on my team that was family supportive, I would do that equally for young or, you know, early to mid-career women as I did for early to mid-career men. And the reason is I needed those men, you know, chances are they had a working spouse at home, right? I needed them to be able to share the load. It's just as important to the women that companies give, you know, the partner, male or female, the partner support and the ability to share the love, right? So to me it's not just a woman thing. It's women and men, and I always tried to create the environment where it was okay to go to your soccer game. I knew you would be online later in the evening when the kids were in bed, and that was fine. And I think the pandemic has democratized that and made that, you know, made that kind of an everyday occurrence. >> Yeah the baby walks in. They're in the zoom call. The dog comes in. The leaf blower going on the outside the window. I've seen it all on theCUBE. >> Yeah, and people don't try to pretend anymore that like, you know, the house is clean, the dog's behaved, you know, I mean it's just, it's just real, and it's authentic, and I think that's healthy. >> Yeah. >> I do, you know, I also love, I also love the office, and you know, I've got a 31 year old and a soon to be 27 year old daughter, two daughters. And you know, they love going into the office, and I think about when I was their age, how just charged up I would get from being in the office. I also see how great it is for them to have a couple of days a week at home because you can get a few things done in between Zoom calls that you don't have to end up piling onto the weekend, and, you know, so I think it's a really healthy, I think it's a really healthy mix now. Most tech companies are not mandating five days in. Most tech companies are at two to three days in. I think that's a, I think that's a really good combination. >> It's interesting how people are changing their culture to get together more as groups and even events. I mean, while I got you, I might as well ask you, what's the board conversations around, you know, the old conferences? You know, before the pandemic, every company had like a user conference. Right, now it's like, well, do we really need to have that? Maybe we do smaller, and we do digital. Have you seen how companies are handling the in-person? Because there's where the relationships are really formed face-to-face, but not everyone's going to be going. But now certain it's clearly back to face-to-face. We're seeing that with theCUBE as you know. >> Yeah, yeah. >> But the numbers aren't coming back, and the numbers aren't that high, but the stakeholders. >> Yeah. >> And the numbers are actually higher if you count digital. >> Yeah, absolutely. But you know, also on digital there's fatigue from 100% digital, right? It's a hybrid. People don't want to be 100% digital anymore, but they also don't want to go back to the days when everybody got on a plane for every meeting, every call, every sales call. You know, I'm seeing a mix on user conferences. I would say two-thirds of my companies are back, but not at the expense level that they were on user conferences. We spend a lot of time getting updates on, cause nobody has put, interestingly enough, nobody has put T&E, travel and expense back to pre-pandemic levels. Nobody, so everybody's pulled back on number of trips. You know, marketing events are being very scrutinized, but I think very effective. We're doing a lot of, and, you know, these were part of the old model as well, like some things, some things just recycle, but you know, there's a lot of CIO and customer round tables in regional cities. You know, those are quite effective right now because people want some face-to-face, but they don't necessarily want to get on a plane and go to Las Vegas in order to do it. I mean, some of them are, you know, there are a lot of things back in Las Vegas. >> And think about the meetings that when you were an operating executive. You got to go to the sales kickoff, you got to go to this, go to that. There were mandatory face-to-faces that you had to go to, but there was a lot of travel that you probably could have done on Zoom. >> Oh, a lot, I mean. >> And then the productivity to the family impact too. Again, think about again, we're talking about the family and people's personal lives, right? So, you know, got to meet a customer. All right. Salesperson wants you to get in front of a customer, got to fly to New York, take a red eye, come on back. Like, I mean, that's gone. >> Yeah, and oh, by the way, the customer doesn't necessarily want to be in the office that day, so, you know, they may or may not be happy about that. So again, it's and not or, right? It's a mix. And I think it's great to see people back to some face-to-face. It's great to see marketing and events back to some face-to-face. It's also great to see that it hasn't gone back to the level it was. I think that's a really healthy dynamic. >> Well, I'll tell you that from our experience while we're on the topic, we'll move back to the International Women's Day is that the productivity of digital, this program we're doing is going to be streamed. We couldn't do this face-to-face because we had to have everyone fly to an event. We're going to do hundreds of stories that we couldn't have done. We're doing it remote. Because it's better to get the content than not have it. I mean it's offline, so, but it's not about getting people to the event and watch the screen for seven hours. It's pick your interview, and then engage. >> Yeah. >> So it's self-service. So we're seeing a lot, the new user experience kind of direct to consumer, and so I think there will be an, I think there's going to be a digital first class citizen with events, so that that matches up with the kind of experience, but the offline version. Face-to-face optimized for relationships, and that's where the recruiting gets done. That's where, you know, people can build these relationships with each other. >> Yeah, and it can be asynchronous. I think that's a real value proposition. It's a great point. >> Okay, I want to get, I want to get into the technology side of the education and re-skilling and those things. I remember in the 80s, computer science was software engineering. You learned like nine languages. You took some double E courses, one or two, and all the other kind of gut classes in school. Engineering, you had the four class disciplines and some offshoots of specialization. Now it's incredible the diversity of tracks in all engineering programs and computer science and outside of those departments. >> Yeah. >> Can you speak to the importance of STEM and the diversity in the technology industry and how this brings opportunity to lower the bar to get in and how people can stay in and grow and keep leveling up? >> Yeah, well look, we're constantly working on how to, how to help the incoming funnel. But then, you know, at a university level, I'm on the foundation board of Kansas State where I got my engineering degree. I was also Chairman of the National Action Council for Minorities in Engineering, which was all about diversity in STEM and how do you keep that pipeline going because honestly the US needs more tech resources than we have. And if you don't tap into the diversity of our entire workforce, we won't be able to fill that need. And so we focused a lot on both the funnel, right, that starts at the middle school level, particularly for girls, getting them in, you know, the situation of hands-on comfort level with coding, with robot building, you know, whatever gives them that confidence. And then keeping that going all the way into, you know, university program, and making sure that they don't attrit out, right? And so there's a number of initiatives, whether it's mentoring and support groups and financial aid to make sure that underrepresented minorities, women and other minorities, you know, get through the funnel and stay, you know, stay in. >> Got it. Now let me ask you, you said, I have two daughters. You have a family of girls too. Is there a vibe difference between the new generation and what's the trends that you're seeing in this next early wave? I mean, not maybe, I don't know how this is in middle school, but like as people start getting into their adult lives, college and beyond what's the current point of view, posture, makeup of the talent coming in? >> Yeah, yeah. >> Certain orientations, do you see any patterns? What's your observation? >> Yeah, it's interesting. So if I look at electrical engineering, my major, it's, and if I look at Kansas State, which spends a lot of time on this, and I think does a great job, but the diversity of that as a major has not changed dramatically since I was there in the early 80s. Where it has changed very significantly is computer science. There are many, many university and college programs around the country where, you know, it's 50/50 in computer science from a gender mix perspective, which is huge progress. Huge progress. And so, and to me that's, you know, I think CS is a fantastic degree for tech, regardless of what function you actually end up doing in these companies. I mean, I was an electrical engineer. I never did core electrical engineering work. I went right into sales and marketing and general management roles. So I think, I think a bunch of, you know, diverse CS graduates is a really, really good sign. And you know, we need to continue to push on that, but progress has been made. I think the, you know, it kind of goes back to the thing we were just talking about, which is the attrition of those, let's just talk about women, right? The attrition of those women once they got past early career and into mid-career then was a concern, right? And that goes back to, you know, just the inability to, you know, get it all done. And that I am hopeful is going to be better served now. >> Well, Sue, it's great to have you on. I know you're super busy. I appreciate you taking the time and contributing to our program on corporate board membership and some of your story and observations and opinions and analysis. Always great to have you and call you a contributor for theCUBE. You can jump on on one more board, be one of our board contributors for our analysts. (Sue laughing) >> I'm at capacity. (both laughing) >> Final, final word. What's the big seat at the table issue that's going well and areas that need to be improved? >> So I'll speak for my boards because they have made great progress in efficiency. You know, obviously with interest rates going up and the mix between growth and profitability changing in terms of what investors are looking for. Many, many companies have had to do a hard pivot from grow at all costs to healthy balance of growth and profit. And I'm very pleased with how my companies have made that pivot. And I think that is going to make much better companies as a result. I think diversity is something that has not been solved at the corporate level, and we need to keep working it. >> Awesome. Thank you for coming on theCUBE. CUBE alumni now contributor, on multiple boards, full-time job. Love the new challenge and chapter you're on, Sue. We'll be following, and we'll check in for more updates. And thank you for being a contributor on this program this year and this episode. We're going to be doing more of these quarterly, so we're going to move beyond once a year. >> That's great. (cross talking) It's always good to see you, John. >> Thank you. >> Thanks very much. >> Okay. >> Sue: Talk to you later. >> This is theCUBE coverage of IWD, International Women's Day 2023. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(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)

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

>> Hey everyone. Welcome back to theCUBE's coverage day two of CloudNative Security CON 23. Lisa Martin here in studio in Palo Alto with John Furrier. John, we've had some great conversations. I've had a global event. This was a global event. We had Germany on yesterday. We had the Boston Studio. We had folks on the ground in Seattle. Lot of great conversations, a lot of great momentum at this event. What is your number one takeaway with this inaugural event? >> Well, first of all, our coverage with our CUBE alumni experts coming in remotely this remote event for us, I think this event as an inaugural event stood out because one, it was done very carefully and methodically from the CNCF. I think they didn't want to overplay their hand relative to breaking out from CUBE CON So Kubernetes success and CloudNative development has been such a success and that event and ecosystem is booming, right? So that's the big story is they have the breakout event and the question was, was it a good call? Was it successful? Was it going to, would the dog hunt as they say, in this case, I think the big takeaway is that it was successful by all measures. One, people enthusiastic and confident that this has the ability to stand on its own and still contribute without taking away from the benefits and growth of Kubernetes CUBE CON and CloudNative console. So that was the key. Hallway conversations, the sessions all curated and developed properly to be different and focused for that reason. So I think the big takeaway is that the CNCF did a good job on how they rolled this out. Again, it was very intimate event small reminds me of first CUBE CON in Seattle, kind of let's test it out. Let's see how it goes. Again, clearly it was people successful and they understood why they're doing it. And as we commented out in our earlier segments this is not something new. Amazon Web Services has re:Invent and re:Inforce So a lot of parallels there. I see there. So I think good call. CNCF did the right thing. I think this has legs. And then as Dave pointed out, Dave Vellante, on our last keynote analysis was the business model of the hackers is better than the business model of the industry. They're making more money, it costs less so, you know, they're playing offense and the industry playing defense. That has to change. And as Dave pointed out we have to make the cost of hacking and breaches and cybersecurity higher so that the business model crashes. And I think that's the strategic imperative. So I think the combination of the realities of the market globally and open source has to go faster. It's good to kind of decouple and be highly cohesive in the focus. So to me that's the big takeaway. And then the other one is, is that there's a lot more security problems still unresolved. The emphasis on developers productivity is at risk here, if not solved. You saw supply chain software, again, front and center and then down in the weeds outside of Kubernetes, things like BIND and DNS were brought up. You're seeing the Linux kernel. Really important things got to be paid attention to. So I think very good call, very good focus. >> I would love if for us to be able to, as the months go on talk to some of the practitioners that actually got to attend. There were 72 sessions, that's a lot of content for a small event. Obviously to your point, very well curated. We did hear from some folks yesterday who were just excited to get the community back together in person. To your point, having this dedicated focus on CloudNativesecurity is incredibly important. You talked about, you know, the offense defense, the fact that right now the industry needs to be able to pivot from being on defense to being on offense. This is a challenging thing because it is so lucrative for hackers. But this seems to be from what we've heard in the last couple days, the right community with the right focus to be able to make that pivot. >> Yeah, and I think if you look at the success of Kubernetes, 'cause again we were there at theCUBE first one CUBE CON, the end user stories really drove end user participation. Drove the birth of Kubernetes. Left some of these CloudNative early adopters early pioneers that were using cloud hyperscale really set the table for CloudNative CON. I think you're seeing that here with this CloudNative SecurityCON where I think we're see a lot more end user stories because of the security, the hairs on fire as we heard from Madrona Ventures, you know, as they as an investor you have a lot of use cases out there where customers are leaning in with getting the rolling up their sleeves, working with open source. This has to be the driver. So I'm expecting to see the next level of SecurityCON to be end user focused. Much more than vendor focused. Where CUBECON was very end user focused and then attracted all the vendors in that grew the industry. I expect the similar pattern here where end user action will be very high at the beginning and that will essentially be the rising tide for the vendors to be then participating. So I expect almost a similar trajectory to CUBECON. >> That's a good path that it needs to all be about all the end users. One of the things I'm curious if what you heard was what are some of the key factors that are going to move CloudNative Security forward? What did you hear the last two days? >> I heard that there's a lot of security problems and no one wants to kind of brag about this but there's a lot of under the hood stuff that needs to get taken care of. So if automation scales, and we heard that from one of the startups we've just interviewed. If automation and scale continues to happen and with the business model of the hackers still booming, security has to be refactored quickly and there's going to be an opportunity structurally to use the cloud for that. So I think it's a good opportunity now to get dedicated focus on fixing things like the DNS stuff old school under the hood, plumbing, networking protocols. You're going to start to see this super cloud-like environment emerge where data's involved, everything's happening and so security has to be re imagined. And I think there's a do over opportunity for the security industry with CloudNative driving that. And I think this is the big thing that I see as an opportunity to, from a story standpoint from a coverage standpoint is that it's a do-over for security. >> One of the things that we heard yesterday is that there's a lot of it, it's a pretty high percentage of organizations that either don't have a SOCK or have a very primitive SOCK. Which kind of surprised me that at this day and age the risks are there. We talked about that today's focus and the keynote was a lot about the software supply chain and what's going on there. What did you hear in terms of the appetite for organizations through the voice of the practitioner to say, you know what guys, we got to get going because there's going to be the hackers are they're here. >> I didn't hear much about that in the coverage 'cause we weren't in the hallways. But from reading the tea leaves and talking to the folks on the ground, I think there's an implied like there's an unlimited money from customers. So it's a very robust from the data infrastructure stack building we cover with the angel investor Kane you're seeing data infrastructure's going to be part of the solution here 'cause data and security go hand in hand. So everyone's got basically checkbook wide open everyone wants to have the answer. And we commented that the co-founder of Palo Alto you had on our coverage yesterday was saying that you know, there's no real platform, there's a lot of tools out there. People will buy anything. So there's still a huge appetite and spend in security but the answer's not going to more tool sprawling. It's going to more platform auto, something that enables automation, fix some of the underlying mechanisms involved and fix it fast. So to me I think it's going to be a robust monetary opportunity because of the demand on the business side. So I don't see that changing at all and I think it's going to accelerate. >> It's a great point in terms of the demand for the business side because as we know as we said yesterday, the next Log4j is out there. It's not a matter of if this happens again it's when, it's the extent, it's how frequent we know that. So organizations all the way up to the board have to be concerned about brand reputation. Nobody wants to be the next big headline in terms of breaches and customer data being given to hackers and hackers making all this money on that. That has to go all the way up to the board and there needs to be alignment between the board and the executives at the organization in terms of how they're going to deal with security, and now. This is not a conversation that can wait. Yeah, I mean I think the five C's we talked about yesterday the culture of companies, the cloud is an enabler, you've got clusters of servers and capabilities, Kubernetes clusters, you've got code and you've got all kinds of, you know, things going on there. Each one has elements that are at risk for hacking, right? So that to me is something that's super important. I think that's why the focus on security's different and important, but it's not going to fork the main event. So that's why I think the spin out was, spinout, or the new event is a good call by the CNCF. >> One of the things today that struck me they're talking a lot about software supply chain and that's been in the headlines for quite a while now. And a stat that was shared this morning during the keynote just blew my brains that there was a 742% increase in the software supply chain attacks occurring over the last three years. It's during Covid times, that is a massive increase. The threat landscape is just growing so amorphously but organizations need to help dial that down because their success and the health of the individuals and the end users is at risk. Well, Covid is an environment where everyone's kind of working at home. So there was some disruption to infrastructure. Also, when you have change like that, there's opportunities for hackers, they'll arbitrage that big time. But I think general the landscape is changing. There's no perimeter anymore. It's CloudNative, this is where it is and people who are moving from old IT to CloudNative, they're at risk. That's why there's tons of ransomware. That's why there's tons of risk. There's just hygiene, from hygiene to architecture and like Nick said from Palo Alto, the co-founder, there's not a lot of architecture in security. So yeah, people have bulked up their security teams but you're going to start to see much more holistic thinking around redoing security. I think that's the opportunity to propel CloudNative, and I think you'll see a lot more coming out of this. >> Did you hear any specific information on some of the CloudNative projects going on that really excite you in terms of these are the right people going after the right challenges to solve in the right direction? >> Well I saw the sessions and what jumped out to me at the sessions was it's a lot of extensions of what we heard at CUBECON and I think what they want to do is take out the big items and break 'em out in security. Kubescape was one we just covered. They want to get more sandbox type stuff into the security side that's very security focused but also plays well with CUBECON. So we'll hear more about how this plays out when we're in Amsterdam coming up in April for CUBECON to hear how that ecosystem, because I think it'll be kind of a relief to kind of decouple security 'cause that gives more focus to the stakeholders in CUBECON. There's a lot of issues going on there and you know service meshes and whatnot. So it's a lot of good stuff happening. >> A lot of good stuff happening. One of the things that'll be great about CUBECON is that we always get the voice of the customer. We get vendors coming on with the voice of the customer talking about and you know in that case how they're using Kubernetes to drive the business forward. But it'll be great to be able to pull in some of the security conversations that spin out of CloudNative Security CON to understand how those end users are embracing the technology. You brought up I think Nir Zuk from Palo Alto Networks, one of the themes there when Dave and I did their Ignite event in December was, of 22, was really consolidation. There are so many tools out there that organizations have to wrap their heads around and they need to be able to have the right enablement content which this event probably delivered to figure out how do we consolidate security tools effectively, efficiently in a way that helps dial down our risk profile because the risks just seem to keep growing. >> Yeah, and I love the technical nature of all that and I think this is going to be the continued focus. Chris Aniszczyk who's the CTO listed like E and BPF we covered with Liz Rice is one of the most three important points of the conference and it's just, it's very nerdy and that's what's needed. I mean it's technical. And again, there's no real standards bodies anymore. The old days developers I think are super important to be the arbiters here. And again, what I love about the CNCF is that they're developer focused and we heard developer first even in security. So you know, this is a sea change and I think, you know, developers' choice will be the standards bodies. >> Lisa: Yeah, yeah. >> They decide the future. >> Yeah. >> And I think having the sandboxing and bringing this out will hopefully accelerate more developer choice and self-service. >> You've been talking about kind of putting the developers in the driver's seat as really being the key decision makers for a while. Did you hear information over the last couple of days that validates that? >> Yeah, absolutely. It's clearly the fact that they did this was one. The other one is, is that engineering teams and dev teams and script teams, they're blending together. It's not just separate silos and the ones that are changing their team dynamics, again, back to the culture are winning. And I think this has to happen. Security has to be embedded everywhere in making it frictionless and to provide kind of the guardrail so developers don't slow down. And I think where security has become a drag or an anchor or a blocker has been just configuration of how the organization's handling it. So I think when people recognize that the developers are in charge and they're should be driving the application development you got to make sure that's secure. And so that's always going to be friction and I think whoever does it, whoever unlocks that for the developer to go faster will win. >> Right. Oh, that's what I'm sure magic to a developer's ear is the ability to go faster and be able to focus on co-development in a secure fashion. What are some of the things that you're excited about for CUBECON. Here we are in February, 2023 and CUBECON is just around the corner in April. What are some of the things that you're excited about based on the groundswell momentum that this first inaugural CloudNative Security CON is generating from a community, a culture perspective? >> I think this year's going to be very interesting 'cause we have an economic challenge globally. There's all kinds of geopolitical things happening. I think there's going to be very entrepreneurial activity this year more than ever. I think you're going to see a lot more innovative projects ideas hitting the table. I think it's going to be a lot more entrepreneurial just because the cycle we're in. And also I think the acceleration of mainstream deployments of out of the CNCF's main event CUBECON will happen. You'll see a lot more successes, scale, more clarity on where the security holes are or aren't. Where the benefits are. I think containers and microservices are continuing to surge. I think the Cloud scale hyperscale as Amazon, Azure, Google will be more aggressive. I think AI will be a big theme this year. I think you can see how data is going to infect some of the innovation thinking. I'm really excited about the data infrastructure because it powers a lot of things in the Cloud. So I think the Amazon Web Services, Azure next level gen clouds will impact what happens in the CloudNative foundation. >> Did you have any conversations yesterday or today with respect to AI and security? Was that a focus of anybody's? Talk to me about that. >> Well, I didn't hear any sessions on AI but we saw some demos on stage. But they're teasing out that this is an augmentation to their mission, right? So I think a lot of people are looking at AI as, again, like I always said there's the naysayers who think it's kind of a gimmick or nothing to see here, and then some are just going to blown away. I think the people who are alpha geeks and the industry connect the dots and understand that AI is going to be an accelerant to a lot of heavy lifting that was either manual, you know, hard to do things that was boring or muck as they say. I think that's going to be where you'll see the AI stories where it's going to accelerate either ways to make security better or make developers more confident and productive. >> Or both. >> Yeah. So definitely AI will be part of it. Yeah, definitely. One of the things too that I'm wondering if, you know, we talk about CloudNative and the goal of it, the importance of it. Do you think that this event, in terms of what we were able to see, obviously being remote the event going on in Seattle, us being here in Palo Alto and Boston and guests on from Seattle and Germany and all over, did you hear the really the validation for why CloudNative Security why CloudNative is important for organizations whether it's a bank or a hospital or a retailer? Is that validation clear and present? >> Yeah, absolutely. I think it was implied. I don't think there was like anyone's trying to debate that. I think this conference was more of it's assumed and they were really trying to push the ability to make security less defensive, more offensive and more accelerated into the solving the problems with the businesses that are out there. So clearly the CloudNative community understands where the security challenges are and where they're emerging. So having a dedicated event will help address that. And they've got great co-chairs too that put it together. So I think that's very positive. >> Yeah. Do you think, is it possible, I mean, like you said several times today so eloquently the industry's on the defense when it comes to security and the hackers are on the offense. Is it really possible to make that switch or obviously get some balances. As technology advances and industry gets to take advantage of that, so do the hackers, is that balance achievable? >> Absolutely. I mean, I think totally achievable. The question's going to be what's the environment going to be like? And I remember as context to understanding whether it's viable or not, is to look at, just go back 13 years ago, I remember in 2010 Amazon was viewed as an unsecure environment. Everyone's saying, "Oh, the cloud is not secure." And I remember interviewing Steve Schmidt at AWS and we discussed specifically how Amazon Cloud was being leveraged by hackers. They made it more complex for the hackers. And he said, "This is just the beginning." It's kind of like barbed wire on a fence. It's yeah, you're not going to climb it so people can get over it. And so since then what's happened is the Cloud has become more secure than on premises for a lot of either you know, personnel reasons, culture reasons, not updating, you know, from patches to just being insecure to be more insecure. So that to me means that the flip the script can be flipped. >> Yeah. And I think with CloudNative they can build in automation and code to solve some of these problems and make it more complex for the hacker. >> Lisa: Yes. >> And increase the cost. >> Yeah, exactly. Make it more complex. Increase the cost. That'll be in interesting journey to follow. So John, here we are early February, 2023 theCUBE starting out strong as always. What year are we in, 12? Year 12? >> 13th year >> 13! What's next for theCUBE? What's coming up that excites you? >> Well, we're going to do a lot more events. We got the theCUBE in studio that I call theCUBE Center as kind of internal code word, but like, this is more about getting the word out that we can cover events remotely as events are starting to change with hybrid, digital is going to be a big part of that. So I think you're going to see a lot more CUBE on location. We're going to do, still do theCUBE and have theCUBE cover events from the studio to get deeper perspective because we can then bring people in remote through our our studio team. We can bring our CUBE alumni in. We have a corpus of content and experts to bring to table. So I think the coverage will be increased. The expertise and data will be flowing through theCUBE and so Cube Center, CUBE CUBE Studio. >> Lisa: Love it. >> Will be a integral part of our coverage. >> I love that. And we have such great conversations with guests in person, but also virtually, digitally as well. We still get the voices of the practitioners and the customers and the vendors and the partner ecosystem really kind of lauded loud and clear through theCUBE megaphone as I would say. >> And of course getting the clips out there, getting the highlights. >> Yeah. >> Getting more stories. No stories too small for theCUBE. We can make it easy to get the best content. >> The best content. John, it's been fun covering CloudNative security CON with you with you. And Dave and our guests, thank you so much for the opportunity and looking forward to the next event. >> John: All right. We'll see you at Amsterdam. >> Yeah, I'll be there. We want to thank you so much for watching TheCUBES's two day coverage of CloudNative Security CON 23. We're live in Palo Alto. You are live wherever you are and we appreciate your time and your view of this event. For John Furrier, Dave Vellante, I'm Lisa Martin. Thanks for watching guys. We'll see you at the next show.

(upbeat music) >> Hello, everybody. This is Dave Vellante. Welcome back to Supercloud2, where we're exploring the intersection of data analytics and the future of cloud. In this segment, we're going to look at how the Supercloud will support a new class of applications, not just work that runs on multiple clouds, but rather a new breed of apps that can orchestrate things in the real world. Think Uber for many types of businesses. These applications, they're not about codifying forms or business processes. They're about orchestrating people, places, and things in a business ecosystem. And I'm pleased to welcome my colleague and friend, George Gilbert, former Gartner Analyst, Wiki Bond market analyst, former equities analyst as my co-host. And we're thrilled to have Tristan Handy, who's the founder and CEO of DBT Labs and Bob Muglia, who's the former President of Microsoft's Enterprise business and former CEO of Snowflake. Welcome all, gentlemen. Thank you for coming on the program. >> Good to be here. >> Thanks for having us. >> Hey, look, I'm going to start actually with the SuperCloud because both Tristan and Bob, you've read the definition. Thank you for doing that. And Bob, you have some really good input, some thoughts on maybe some of the drawbacks and how we can advance this. So what are your thoughts in reading that definition around SuperCloud? >> Well, I thought first of all that you did a very good job of laying out all of the characteristics of it and helping to define it overall. But I do think it can be tightened a bit, and I think it's helpful to do it in as short a way as possible. And so in the last day I've spent a little time thinking about how to take it and write a crisp definition. And here's my go at it. This is one day old, so gimme a break if it's going to change. And of course we have to follow the industry, and so that, and whatever the industry decides, but let's give this a try. So in the way I think you're defining it, what I would say is a SuperCloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. >> Boom. Nice. Okay, great. I'm going to go back and read the script on that one and tighten that up a bit. Thank you for spending the time thinking about that. Tristan, would you add anything to that or what are your thoughts on the whole SuperCloud concept? >> So as I read through this, I fully realize that we need a word for this thing because I have experienced the inability to talk about it as well. But for many of us who have been living in the Confluence, Snowflake, you know, this world of like new infrastructure, this seems fairly uncontroversial. Like I read through this, and I'm just like, yeah, this is like the world I've been living in for years now. And I noticed that you called out Snowflake for being an example of this, but I think that there are like many folks, myself included, for whom this world like fully exists today. >> Yeah, I think that's a fair, I dunno if it's criticism, but people observe, well, what's the big deal here? It's just kind of what we're living in today. It reminds me of, you know, Tim Burns Lee saying, well, this is what the internet was supposed to be. It was supposed to be Web 2.0, so maybe this is what multi-cloud was supposed to be. Let's turn our attention to apps. Bob first and then go to Tristan. Bob, what are data apps to you? When people talk about data products, is that what they mean? Are we talking about something more, different? What are data apps to you? >> Well, to understand data apps, it's useful to contrast them to something, and I just use the simple term people apps. I know that's a little bit awkward, but it's clear. And almost everything we work with, almost every application that we're familiar with, be it email or Salesforce or any consumer app, those are applications that are targeted at responding to people. You know, in contrast, a data application reacts to changes in data and uses some set of analytic services to autonomously take action. So where applications that we're familiar with respond to people, data apps respond to changes in data. And they both do something, but they do it for different reasons. >> Got it. You know, George, you and I were talking about, you know, it comes back to SuperCloud, broad definition, narrow definition. Tristan, how do you see it? Do you see it the same way? Do you have a different take on data apps? >> Oh, geez. This is like a conversation that I don't know has an end. It's like been, I write a substack, and there's like this little community of people who all write substack. We argue with each other about these kinds of things. Like, you know, as many different takes on this question as you can find, but the way that I think about it is that data products are atomic units of functionality that are fundamentally data driven in nature. So a data product can be as simple as an interactive dashboard that is like actually had design thinking put into it and serves a particular user group and has like actually gone through kind of a product development life cycle. And then a data app or data application is a kind of cohesive end-to-end experience that often encompasses like many different data products. So from my perspective there, this is very, very related to the way that these things are produced, the kinds of experiences that they're provided, that like data innovates every product that we've been building in, you know, software engineering for, you know, as long as there have been computers. >> You know, Jamak Dagani oftentimes uses the, you know, she doesn't name Spotify, but I think it's Spotify as that kind of example she uses. But I wonder if we can maybe try to take some examples. If you take, like George, if you take a CRM system today, you're inputting leads, you got opportunities, it's driven by humans, they're really inputting the data, and then you got this system that kind of orchestrates the business process, like runs a forecast. But in this data driven future, are we talking about the app itself pulling data in and automatically looking at data from the transaction systems, the call center, the supply chain and then actually building a plan? George, is that how you see it? >> I go back to the example of Uber, may not be the most sophisticated data app that we build now, but it was like one of the first where you do have users interacting with their devices as riders trying to call a car or driver. But the app then looks at the location of all the drivers in proximity, and it matches a driver to a rider. It calculates an ETA to the rider. It calculates an ETA then to the destination, and it calculates a price. Those are all activities that are done sort of autonomously that don't require a human to type something into a form. The application is using changes in data to calculate an analytic product and then to operationalize that, to assign the driver to, you know, calculate a price. Those are, that's an example of what I would think of as a data app. And my question then I guess for Tristan is if we don't have all the pieces in place for sort of mainstream companies to build those sorts of apps easily yet, like how would we get started? What's the role of a semantic layer in making that easier for mainstream companies to build? And how do we get started, you know, say with metrics? How does that, how does that take us down that path? >> So what we've seen in the past, I dunno, decade or so, is that one of the most successful business models in infrastructure is taking hard things and rolling 'em up behind APIs. You take messaging, you take payments, and you all of a sudden increase the capability of kind of your median application developer. And you say, you know, previously you were spending all your time being focused on how do you accept credit cards, how do you send SMS payments, and now you can focus on your business logic, and just create the thing. One of, interestingly, one of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse, inside of your data lake. These are core concepts that, you know, you would imagine that the business would be able to create applications around very easily, but in fact that's not the case. It's actually quite challenging to, and involves a lot of data engineering pipeline and all this work to make these available. And so if you really want to make it very easy to create some of these data experiences for users, you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes, and they don't need to. >> So how rich can that API layer grow if you start with metric definitions that you've defined? And DBT has, you know, the metric, the dimensions, the time grain, things like that, that's a well scoped sort of API that people can work within. How much can you extend that to say non-calculated business rules or governance information like data reliability rules, things like that, or even, you know, features for an AIML feature store. In other words, it starts, you started pragmatically, but how far can you grow? >> Bob is waiting with bated breath to answer this question. I'm, just really quickly, I think that we as a company and DBT as a product tend to be very pragmatic. We try to release the simplest possible version of a thing, get it out there, and see if people use it. But the idea that, the concept of a metric is really just a first landing pad. The really, there is a physical manifestation of the data and then there's a logical manifestation of the data. And what we're trying to do here is make it very easy to access the logical manifestation of the data, and metric is a way to look at that. Maybe an entity, a customer, a user is another way to look at that. And I'm sure that there will be more kind of logical structures as well. >> So, Bob, chime in on this. You know, what's your thoughts on the right architecture behind this, and how do we get there? >> Yeah, well first of all, I think one of the ways we get there is by what companies like DBT Labs and Tristan is doing, which is incrementally taking and building on the modern data stack and extending that to add a semantic layer that describes the data. Now the way I tend to think about this is a fairly major shift in the way we think about writing applications, which is today a code first approach to moving to a world that is model driven. And I think that's what the big change will be is that where today we think about data, we think about writing code, and we use that to produce APIs as Tristan said, which encapsulates those things together in some form of services that are useful for organizations. And that idea of that encapsulation is never going to go away. It's very, that concept of an API is incredibly useful and will exist well into the future. But what I think will happen is that in the next 10 years, we're going to move to a world where organizations are defining models first of their data, but then ultimately of their business process, their entire business process. Now the concept of a model driven world is a very old concept. I mean, I first started thinking about this and playing around with some early model driven tools, probably before Tristan was born in the early 1980s. And those tools didn't work because the semantics associated with executing the model were too complex to be written in anything other than a procedural language. We're now reaching a time where that is changing, and you see it everywhere. You see it first of all in the world of machine learning and machine learning models, which are taking over more and more of what applications are doing. And I think that's an incredibly important step. And learned models are an important part of what people will do. But if you look at the world today, I will claim that we've always been modeling. Modeling has existed in computers since there have been integrated circuits and any form of computers. But what we do is what I would call implicit modeling, which means that it's the model is written on a whiteboard. It's in a bunch of Slack messages. It's on a set of napkins in conversations that happen and during Zoom. That's where the model gets defined today. It's implicit. There is one in the system. It is hard coded inside application logic that exists across many applications with humans being the glue that connects those models together. And really there is no central place you can go to understand the full attributes of the business, all of the business rules, all of the business logic, the business data. That's going to change in the next 10 years. And we'll start to have a world where we can define models about what we're doing. Now in the short run, the most important models to build are data models and to describe all of the attributes of the data and their relationships. And that's work that DBT Labs is doing. A number of other companies are doing that. We're taking steps along that way with catalogs. People are trying to build more complete ontologies associated with that. The underlying infrastructure is still super, super nascent. But what I think we'll see is this infrastructure that exists today that's building learned models in the form of machine learning programs. You know, some of these incredible machine learning programs in foundation models like GPT and DALL-E and all of the things that are happening in these global scale models, but also all of that needs to get applied to the domains that are appropriate for a business. And I think we'll see the infrastructure developing for that, that can take this concept of learned models and put it together with more explicitly defined models. And this is where the concept of knowledge graphs come in and then the technology that underlies that to actually implement and execute that, which I believe are relational knowledge graphs. >> Oh, oh wow. There's a lot to unpack there. So let me ask the Colombo question, Tristan, we've been making fun of your youth. We're just, we're just jealous. Colombo, I'll explain it offline maybe. >> I watch Colombo. >> Okay. All right, good. So but today if you think about the application stack and the data stack, which is largely an analytics pipeline. They're separate. Do they, those worlds, do they have to come together in order to achieve Bob's vision? When I talk to practitioners about that, they're like, well, I don't want to complexify the application stack cause the data stack today is so, you know, hard to manage. But but do those worlds have to come together? And you know, through that model, I guess abstraction or translation that Bob was just describing, how do you guys think about that? Who wants to take that? >> I think it's inevitable that data and AI are going to become closer together? I think that the infrastructure there has been moving in that direction for a long time. Whether you want to use the Lakehouse portmanteau or not. There's also, there's a next generation of data tech that is still in the like early stage of being developed. There's a company that I love that is essentially Cross Cloud Lambda, and it's just a wonderful abstraction for computing. So I think that, you know, people have been predicting that these worlds are going to come together for awhile. A16Z wrote a great post on this back in I think 2020, predicting this, and I've been predicting this since since 2020. But what's not clear is the timeline, but I think that this is still just as inevitable as it's been. >> Who's that that does Cross Cloud? >> Let me follow up on. >> Who's that, Tristan, that does Cross Cloud Lambda? Can you name names? >> Oh, they're called Modal Labs. >> Modal Labs, yeah, of course. All right, go ahead, George. >> Let me ask about this vision of trying to put the semantics or the code that represents the business with the data. It gets us to a world that's sort of more data centric, where data's not locked inside or behind the APIs of different applications so that we don't have silos. But at the same time, Bob, I've heard you talk about building the semantics gradually on top of, into a knowledge graph that maybe grows out of a data catalog. And the vision of getting to that point, essentially the enterprise's metadata and then the semantics you're going to add onto it are really stored in something that's separate from the underlying operational and analytic data. So at the same time then why couldn't we gradually build semantics beyond the metric definitions that DBT has today? In other words, you build more and more of the semantics in some layer that DBT defines and that sits above the data management layer, but any requests for data have to go through the DBT layer. Is that a workable alternative? Or where, what type of limitations would you face? >> Well, I think that it is the way the world will evolve is to start with the modern data stack and, you know, which is operational applications going through a data pipeline into some form of data lake, data warehouse, the Lakehouse, whatever you want to call it. And then, you know, this wide variety of analytics services that are built together. To the point that Tristan made about machine learning and data coming together, you see that in every major data cloud provider. Snowflake certainly now supports Python and Java. Databricks is of course building their data warehouse. Certainly Google, Microsoft and Amazon are doing very, very similar things in terms of building complete solutions that bring together an analytics stack that typically supports languages like Python together with the data stack and the data warehouse. I mean, all of those things are going to evolve, and they're not going to go away because that infrastructure is relatively new. It's just being deployed by companies, and it solves the problem of working with petabytes of data if you need to work with petabytes of data, and nothing will do that for a long time. What's missing is a layer that understands and can model the semantics of all of this. And if you need to, if you want to model all, if you want to talk about all the semantics of even data, you need to think about all of the relationships. You need to think about how these things connect together. And unfortunately, there really is no platform today. None of our existing platforms are ultimately sufficient for this. It was interesting, I was just talking to a customer yesterday, you know, a large financial organization that is building out these semantic layers. They're further along than many companies are. And you know, I asked what they're building it on, and you know, it's not surprising they're using a, they're using combinations of some form of search together with, you know, textual based search together with a document oriented database. In this case it was Cosmos. And that really is kind of the state of the art right now. And yet those products were not built for this. They don't really, they can't manage the complicated relationships that are required. They can't issue the queries that are required. And so a new generation of database needs to be developed. And fortunately, you know, that is happening. The world is developing a new set of relational algorithms that will be able to work with hundreds of different relations. If you look at a SQL database like Snowflake or a big query, you know, you get tens of different joins coming together, and that query is going to take a really long time. Well, fortunately, technology is evolving, and it's possible with new join algorithms, worst case, optimal join algorithms they're called, where you can join hundreds of different relations together and run semantic queries that you simply couldn't run. Now that technology is nascent, but it's really important, and I think that will be a requirement to have this semantically reach its full potential. In the meantime, Tristan can do a lot of great things by building up on what he's got today and solve some problems that are very real. But in the long run I think we'll see a new set of databases to support these models. >> So Tristan, you got to respond to that, right? You got to, so take the example of Snowflake. We know it doesn't deal well with complex joins, but they're, they've got big aspirations. They're building an ecosystem to really solve some of these problems. Tristan, you guys are part of that ecosystem, and others, but please, your thoughts on what Bob just shared. >> Bob, I'm curious if, I would have no idea what you were talking about except that you introduced me to somebody who gave me a demo of a thing and do you not want to go there right now? >> No, I can talk about it. I mean, we can talk about it. Look, the company I've been working with is Relational AI, and they're doing this work to actually first of all work across the industry with academics and research, you know, across many, many different, over 20 different research institutions across the world to develop this new set of algorithms. They're all fully published, just like SQL, the underlying algorithms that are used by SQL databases are. If you look today, every single SQL database uses a similar set of relational algorithms underneath that. And those algorithms actually go back to system R and what IBM developed in the 1970s. We're just, there's an opportunity for us to build something new that allows you to take, for example, instead of taking data and grouping it together in tables, treat all data as individual relations, you know, a key and a set of values and then be able to perform purely relational operations on it. If you go back to what, to Codd, and what he wrote, he defined two things. He defined a relational calculus and relational algebra. And essentially SQL is a query language that is translated by the query processor into relational algebra. But however, the calculus of SQL is not even close to the full semantics of the relational mathematics. And it's possible to have systems that can do everything and that can store all of the attributes of the data model or ultimately the business model in a form that is much more natural to work with. >> So here's like my short answer to this. I think that we're dealing in different time scales. I think that there is actually a tremendous amount of work to do in the semantic layer using the kind of technology that we have on the ground today. And I think that there's, I don't know, let's say five years of like really solid work that there is to do for the entire industry, if not more. But the wonderful thing about DBT is that it's independent of what the compute substrate is beneath it. And so if we develop new platforms, new capabilities to describe semantic models in more fine grain detail, more procedural, then we're going to support that too. And so I'm excited about all of it. >> Yeah, so interpreting that short answer, you're basically saying, cause Bob was just kind of pointing to you as incremental, but you're saying, yeah, okay, we're applying it for incremental use cases today, but we can accommodate a much broader set of examples in the future. Is that correct, Tristan? >> I think you're using the word incremental as if it's not good, but I think that incremental is great. We have always been about applying incremental improvement on top of what exists today, but allowing practitioners to like use different workflows to actually make use of that technology. So yeah, yeah, we are a very incremental company. We're going to continue being that way. >> Well, I think Bob was using incremental as a pejorative. I mean, I, but to your point, a lot. >> No, I don't think so. I want to stop that. No, I don't think it's pejorative at all. I think incremental, incremental is usually the most successful path. >> Yes, of course. >> In my experience. >> We agree, we agree on that. >> Having tried many, many moonshot things in my Microsoft days, I can tell you that being incremental is a good thing. And I'm a very big believer that that's the way the world's going to go. I just think that there is a need for us to build something new and that ultimately that will be the solution. Now you can argue whether it's two years, three years, five years, or 10 years, but I'd be shocked if it didn't happen in 10 years. >> Yeah, so we all agree that incremental is less disruptive. Boom, but Tristan, you're, I think I'm inferring that you believe you have the architecture to accommodate Bob's vision, and then Bob, and I'm inferring from Bob's comments that maybe you don't think that's the case, but please. >> No, no, no. I think that, so Bob, let me put words into your mouth and you tell me if you disagree, DBT is completely useless in a world where a large scale cloud data warehouse doesn't exist. We were not able to bring the power of Python to our users until these platforms started supporting Python. Like DBT is a layer on top of large scale computing platforms. And to the extent that those platforms extend their functionality to bring more capabilities, we will also service those capabilities. >> Let me try and bridge the two. >> Yeah, yeah, so Bob, Bob, Bob, do you concur with what Tristan just said? >> Absolutely, I mean there's nothing to argue with in what Tristan just said. >> I wanted. >> And it's what he's doing. It'll continue to, I believe he'll continue to do it, and I think it's a very good thing for the industry. You know, I'm just simply saying that on top of that, I would like to provide Tristan and all of those who are following similar paths to him with a new type of database that can actually solve these problems in a much more architected way. And when I talk about Cosmos with something like Mongo or Cosmos together with Elastic, you're using Elastic as the join engine, okay. That's the purpose of it. It becomes a poor man's join engine. And I kind of go, I know there's a better answer than that. I know there is, but that's kind of where we are state of the art right now. >> George, we got to wrap it. So give us the last word here. Go ahead, George. >> Okay, I just, I think there's a way to tie together what Tristan and Bob are both talking about, and I want them to validate it, which is for five years we're going to be adding or some number of years more and more semantics to the operational and analytic data that we have, starting with metric definitions. My question is for Bob, as DBT accumulates more and more of those semantics for different enterprises, can that layer not run on top of a relational knowledge graph? And what would we lose by not having, by having the knowledge graph store sort of the joins, all the complex relationships among the data, but having the semantics in the DBT layer? >> Well, I think this, okay, I think first of all that DBT will be an environment where many of these semantics are defined. The question we're asking is how are they stored and how are they processed? And what I predict will happen is that over time, as companies like DBT begin to build more and more richness into their semantic layer, they will begin to experience challenges that customers want to run queries, they want to ask questions, they want to use this for things where the underlying infrastructure becomes an obstacle. I mean, this has happened in always in the history, right? I mean, you see major advances in computer science when the data model changes. And I think we're on the verge of a very significant change in the way data is stored and structured, or at least metadata is stored and structured. Again, I'm not saying that anytime in the next 10 years, SQL is going to go away. In fact, more SQL will be written in the future than has been written in the past. And those platforms will mature to become the engines, the slicer dicers of data. I mean that's what they are today. They're incredibly powerful at working with large amounts of data, and that infrastructure is maturing very rapidly. What is not maturing is the infrastructure to handle all of the metadata and the semantics that that requires. And that's where I say knowledge graphs are what I believe will be the solution to that. >> But Tristan, bring us home here. It sounds like, let me put pause at this, is that whatever happens in the future, we're going to leverage the vast system that has become cloud that we're talking about a supercloud, sort of where data lives irrespective of physical location. We're going to have to tap that data. It's not necessarily going to be in one place, but give us your final thoughts, please. >> 100% agree. I think that the data is going to live everywhere. It is the responsibility for both the metadata systems and the data processing engines themselves to make sure that we can join data across cloud providers, that we can join data across different physical regions and that we as practitioners are going to kind of start forgetting about details like that. And we're going to start thinking more about how we want to arrange our teams, how does the tooling that we use support our team structures? And that's when data mesh I think really starts to get very, very critical as a concept. >> Guys, great conversation. It was really awesome to have you. I can't thank you enough for spending time with us. Really appreciate it. >> Thanks a lot. >> All right. This is Dave Vellante for George Gilbert, John Furrier, and the entire Cube community. Keep it right there for more content. You're watching SuperCloud2. (upbeat music)

>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>>Hey everyone, welcome to this event, HPE Compute Security. I'm your host, Lisa Martin. Kevin Dee joins me next Senior director, future Surfer Architecture at hpe. Kevin, it's great to have you back on the program. >>Thanks, Lisa. I'm glad to be here. >>One of the topics that we're gonna unpack in this segment is, is all about cybersecurity. And if we think of how dramatically the landscape has changed in the last couple of years, I was looking at some numbers that H P V E had provided. Cybercrime will reach 10.5 trillion by 2025. It's a couple years away. The average total cost of a data breach is now over 4 million, 15% year over year crime growth predicted over the next five years. It's no longer if we get hit, it's when it's how often. What's the severity? Talk to me about the current situation with the cybersecurity landscape that you're seeing. >>Yeah, I mean the, the numbers you're talking about are just staggering and then that's exactly what we're seeing and that's exactly what we're hearing from our customers is just absolutely key. Customers have too much to lose. The, the dollar cost is just, like I said, staggering. And, and here at HP we know we have a huge part to play, but we also know that we need partnerships across the industry to solve these problems. So we have partnered with, with our, our various partners to deliver these Gen 11 products. Whether we're talking about partners like a M D or partners like our Nick vendors, storage card vendors. We know we can't solve the problem alone. And we know this, the issue is huge. And like you said, the numbers are staggering. So we're really, we're really partnering with, with all the right players to ensure we have a secure solution so we can stay ahead of the bad guys to try to limit the, the attacks on our customers. >>Right. Limit the damage. What are some of the things that you've seen particularly change in the last 18 months or so? Anything that you can share with us that's eye-opening, more eye-opening than some of the stats we already shared? >>Well, there, there's been a massive number of attacks just in the last 12 months, but I wouldn't really say it's so much changed because the amount of attacks has been increasing dramatically over the years for many, many, many years. It's just a very lucrative area for the bad guys, whether it's ransomware or stealing personal data, whatever it is, it's there. There's unfortunately a lot of money to be made into it, made from it, and a lot of money to be lost by the good guys, the good guys being our customers. So it's not so much that it's changed, it's just that it's even accelerating faster. So the real change is, it's accelerating even faster because it's becoming even more lucrative. So we have to stay ahead of these bad guys. One of the statistics of Microsoft operating environments, the number of tax in the last year, up 50% year over year, that's a huge acceleration and we've gotta stay ahead of that. We have to make sure our customers don't get impacted to the level that these, these staggering number of attacks are. The, the bad guys are out there. We've gotta protect, protect our customers from the bad guys. >>Absolutely. The acceleration that you talked about is, it's, it's kind of frightening. It's very eye-opening. We do know that security, you know, we've talked about it for so long as a, as a a C-suite priority, a board level priority. We know that as some of the data that HPE e also sent over organizations are risking are, are listing cyber risks as a top five concern in their organization. IT budgets spend is going up where security is concerned. And so security security's on everyone's mind. In fact, the cube did, I guess in the middle part of last, I did a series on this really focusing on cybersecurity as a board issue and they went into how companies are structuring security teams changing their assumptions about the right security model, offense versus defense. But security's gone beyond the board, it's top of mind and it's on, it's in an integral part of every conversation. So my question for you is, when you're talking to customers, what are some of the key challenges that they're saying, Kevin, these are some of the things the landscape is accelerating, we know it's a matter of time. What are some of those challenges and that they're key pain points that they're coming to you to help solve? >>Yeah, at the highest level it's simply that security is incredibly important to them. We talked about the numbers. There's so much money to be lost that what they come to us and say, is security's important for us? What can you do to protect us? What can you do to prevent us from being one of those statistics? So at a high level, that's kind of what we're seeing at a, with a little more detail. We know that there's customers doing digital transformations. We know that there's customers going hybrid cloud, they've got a lot of initiatives on their own. They've gotta spend a lot of time and a lot of bandwidth tackling things that are important to their business. They just don't have the bandwidth to worry about yet. Another thing which is security. So we are doing everything we can and partnering with everyone we can to help solve those problems for customers. >>Cuz we're hearing, hey, this is huge, this is too big of a risk. How do you protect us? And by the way, we only have limited bandwidth, so what can we do? What we can do is make them assured that that platform is secure, that we're, we are creating a foundation for a very secure platform and that we've worked with our partners to secure all the pieces. So yes, they still have to worry about security, but there's pieces that we've taken care of that they don't have to worry about and there's capabilities that we've provided that they can use and we've made that easy so they can build su secure solutions on top of it. >>What are some of the things when you're in customer conversations, Kevin, that you talk about with customers in terms of what makes HPE E'S approach to security really unique? >>Well, I think a big thing is security is part of our, our dna. It's part of everything we do. Whether we're designing our own asics for our bmc, the ilo ASIC ILO six used on Gen 11, or whether it's our firmware stack, the ILO firmware, our our system, UFI firmware, all those pieces in everything we do. We're thinking about security. When we're building products in our factory, we're thinking about security. When we're think designing our supply chain, we're thinking about security. When we make requirements on our suppliers, we're driving security to be a key part of those components. So security is in our D N a security's top of mind. Security is something we think about in everything we do. We have to think like the bad guys, what could the bad guy take advantage of? What could the bad guy exploit? So we try to think like them so that we can protect our customers. >>And so security is something that that really is pervasive across all of our development organizations, our supply chain organizations, our factories, and our partners. So that's what we think is unique about HPE is because security is so important and there's a whole lot of pieces of our reliance servers that we do ourselves that many others don't do themselves. And since we do it ourselves, we can make sure that security's in the design from the start, that those pieces work together in a secure manner. So we think that gives us a, an advantage from a security standpoint. >>Security is very much intention based at HPE e I was reading in some notes, and you just did a great job of talking about this, that fundamental security approach, security is fundamental to defend against threats that are increasingly complex through what you also call an uncompromising focus to state-of-the-art security and in in innovations built into your D N A. And then organizations can protect their infrastructure, their workloads, their data from the bad guys. Talk to us briefly in our final few minutes here, Kevin, about fundamental uncompromising protected the value in it for me as an HPE customer. >>Yeah, when we talk about fundamental, we're talking about the those fundamental technologies that are part of our platform. Things like we've integrated TPMS and sorted them down in our platforms. We now have platform certificates as a standard part of the platform. We have I dev id and probably most importantly, our platforms continue to support what we really believe was a groundbreaking technology, Silicon Root of trust and what that's able to do. We have millions of lines of firmware code in our platforms and with Silicon Root of trust, we can authenticate all of those lines of firmware. Whether we're talking about the the ILO six firmware, our U E I firmware, our C P L D in the system, there's other pieces of firmware. We authenticate all those to make sure that not a single line of code, not a single bit has been changed by a bad guy, even if the bad guy has physical access to the platform. >>So that silicon route of trust technology is making sure that when that system boots off and that hands off to the operating system and then eventually the customer's application stack that it's starting with a solid foundation, that it's starting with a system that hasn't been compromised. And then we build other things into that silicon root of trust, such as the ability to do the scans and the authentications at runtime, the ability to automatically recover if we detect something has been compromised, we can automatically update that compromised piece of firmware to a good piece before we've run it because we never want to run firmware that's been compromised. So that's all part of that Silicon Root of Trust solution and that's a fundamental piece of the platform. And then when we talk about uncompromising, what we're really talking about there is how we don't compromise security. >>And one of the ways we do that is through an extension of our Silicon Root of trust with a capability called S Spdm. And this is a technology that we saw the need for, we saw the need to authenticate our option cards and the firmware in those option cards. Silicon Root Prota, Silicon Root Trust protects against many attacks, but one piece it didn't do is verify the actual option card firmware and the option cards. So we knew to solve that problem we would have to partner with others in the industry, our nick vendors, our storage controller vendors, our G vendors. So we worked with industry standards bodies and those other partners to design a capability that allows us to authenticate all of those devices. And we worked with those vendors to get the support both in their side and in our platform side so that now Silicon Rivers and trust has been extended to where we protect and we trust those option cards as well. >>So that's when, when what we're talking about with Uncompromising and with with Protect, what we're talking about there is our capabilities around protecting against, for example, supply chain attacks. We have our, our trusted supply chain solution, which allows us to guarantee that our server, when it leaves our factory, what the server is, when it leaves our factory, will be what it is when it arrives at the customer. And if a bad guy does anything in that transition, the transit from our factory to the customer, they'll be able to detect that. So we enable certain capabilities by default capability called server configuration lock, which can ensure that nothing in the server exchange, whether it's firmware, hardware, configurations, swapping out processors, whatever it is, we'll detect if a bad guy did any of that and the customer will know it before they deploy the system. That gets enabled by default. >>We have an intrusion detection technology option when you use by the, the trusted supply chain that is included by default. That lets you know, did anybody open that system up, even if the system's not plugged in, did somebody take the hood off and potentially do something malicious to it? We also enable a capability called U EFI secure Boot, which can go authenticate some of the drivers that are located on the option card itself. Those kind of capabilities. Also ilo high security mode gets enabled by default. So all these things are enabled in the platform to ensure that if it's attacked going from our factory to the customer, it will be detected and the customer won't deploy a system that's been maliciously attacked. So that's got >>It, >>How we protect the customer through those capabilities. >>Outstanding. You mentioned partners, my last question for you, we've got about a minute left, Kevin is bring AMD into the conversation, where do they fit in this >>AMD's an absolutely crucial partner. No one company even HP can do it all themselves. There's a lot of partnerships, there's a lot of synergies working with amd. We've been working with AMD for almost 20 years since we delivered our first AM MD base ProLiant back in 2004 H HP ProLiant, DL 5 85. So we've been working with them a long time. We work with them years ahead of when a processor is announced, we benefit each other. We look at their designs and help them make their designs better. They let us know about their technology so we can take advantage of it in our designs. So they have a lot of security capabilities, like their memory encryption technologies, their a MD secure processor, their secure encrypted virtualization, which is an absolutely unique and breakthrough technology to protect virtual machines and hypervisor environments and protect them from malicious hypervisors. So they have some really great capabilities that they've built into their processor, and we also take advantage of the capabilities they have and ensure those are used in our solutions and in securing the platform. So a really such >>A great, great partnership. Great synergies there. Kevin, thank you so much for joining me on the program, talking about compute security, what HPE is doing to ensure that security is fundamental, that it is unpromised and that your customers are protected end to end. We appreciate your insights, we appreciate your time. >>Thank you very much, Lisa. >>We've just had a great conversation with Kevin Depu. Now I get to talk with David Chang, data center solutions marketing lead at a md. David, welcome to the program. >>Thank, thank you. And thank you for having me. >>So one of the hot topics of conversation that we can't avoid is security. Talk to me about some of the things that AMD is seeing from the customer's perspective, why security is so important for businesses across industries. >>Yeah, sure. Yeah. Security is, is top of mind for, for almost every, every customer I'm talking to right now. You know, there's several key market drivers and, and trends, you know, in, out there today that's really needing a better and innovative solution for, for security, right? So, you know, the high cost of data breaches, for example, will cost enterprises in downtime of, of the data center. And that time is time that you're not making money, right? And potentially even leading to your, to the loss of customer confidence in your, in your cust in your company's offerings. So there's real costs that you, you know, our customers are facing every day not being prepared and not having proper security measures set up in the data center. In fact, according to to one report, over 400 high-tech threats are being introduced every minute. So every day, numerous new threats are popping up and they're just, you know, the, you know, the bad guys are just getting more and more sophisticated. So you have to take, you know, measures today and you have to protect yourself, you know, end to end with solutions like what a AM MD and HPE has to offer. >>Yeah, you talked about some of the costs there. They're exorbitant. I've seen recent figures about the average, you know, cost of data breacher ransomware is, is close to, is over $4 million, the cost of, of brand reputation you brought up. That's a great point because nobody wants to be the next headline and security, I'm sure in your experiences. It's a board level conversation. It's, it's absolutely table stakes for every organization. Let's talk a little bit about some of the specific things now that A M D and HPE E are doing. I know that you have a really solid focus on building security features into the EPIC processors. Talk to me a little bit about that focus and some of the great things that you're doing there. >>Yeah, so, you know, we partner with H P E for a long time now. I think it's almost 20 years that we've been in business together. And, and you know, we, we help, you know, we, we work together design in security features even before the silicons even, you know, even born. So, you know, we have a great relationship with, with, with all our partners, including hpe and you know, HPE has, you know, an end really great end to end security story and AMD fits really well into that. You know, if you kind of think about how security all started, you know, in, in the data center, you, you've had strategies around encryption of the, you know, the data in, in flight, the network security, you know, you know, VPNs and, and, and security on the NS. And, and even on the, on the hard drives, you know, data that's at rest. >>You know, encryption has, you know, security has been sort of part of that strategy for a a long time and really for, you know, for ages, nobody really thought about the, the actual data in use, which is, you know, the, the information that's being passed from the C P U to the, the, the memory and, and even in virtualized environments to the, the, the virtual machines that, that everybody uses now. So, you know, for a long time nobody really thought about that app, you know, that third leg of, of encryption. And so a d comes in and says, Hey, you know, this is things that as, as the bad guys are getting more sophisticated, you, you have to start worrying about that, right? And, you know, for example, you know, you know, think, think people think about memory, you know, being sort of, you know, non-persistent and you know, when after, you know, after a certain time, the, the, you know, the, the data in the memory kind of goes away, right? >>But that's not true anymore because even in in memory data now, you know, there's a lot of memory modules that still can retain data up to 90 minutes even after p power loss. And with something as simple as compressed, compressed air or, or liquid nitrogen, you can actually freeze memory dams now long enough to extract the data from that memory module for up, you know, up, up to two or three hours, right? So lo more than enough time to read valuable data and, and, and even encryption keys off of that memory module. So our, our world's getting more complex and you know, more, the more data out there, the more insatiable need for compute and storage. You know, data management is becoming all, all the more important, you know, to keep all of that going and secure, you know, and, and creating security for those threats. It becomes more and more important. And, and again, especially in virtualized environments where, you know, like hyperconverged infrastructure or vir virtual desktop memories, it's really hard to keep up with all those different attacks, all those different attack surfaces. >>It sounds like what you were just talking about is what AMD has been able to do is identify yet another vulnerability Yes. Another attack surface in memory to be able to, to plug that hole for organizations that didn't, weren't able to do that before. >>Yeah. And, you know, and, and we kind of started out with that belief that security needed to be scalable and, and able to adapt to, to changing environments. So, you know, we, we came up with, you know, the, you know, the, the philosophy or the design philosophy that we're gonna continue to build on those security features generational generations and stay ahead of those evolving attacks. You know, great example is in, in the third gen, you know, epic C P U, that family that we had, we actually created this feature called S E V S N P, which stands for SECURENESS Paging. And it's really all around this, this new attack where, you know, your, the, the, you know, it's basically hypervisor based attacks where people are, you know, the bad actors are writing in to the memory and writing in basically bad data to corrupt the mem, you know, to corrupt the data in the memory. So s e V S and P is, was put in place to help, you know, secure that, you know, before that became a problem. And, you know, you heard in the news just recently that that becoming a more and more, more of a bigger issue. And the great news is that we had that feature built in, you know, before that became a big problem. >>And now you're on the fourth gen, those epic crosses talk of those epic processes. Talk to me a little bit about some of the innovations that are now in fourth gen. >>Yeah, so in fourth gen we actually added, you know, on top of that. So we've, we've got, you know, the sec the, the base of our, our, what we call infinity guard is, is all around the secure boot. The, you know, the, the, the, the secure root of trust that, you know, that we, we work with HPE on the, the strong memory encryption and the S E V, which is the secure encrypted virtualization. And so remember those s s and p, you know, incap capabilities that I talked about earlier. We've actually, in the fourth gen added two x the number of sev v s and P guests for even higher number of confidential VMs to support even more customers than before. Right? We've also added more guest protection from simultaneous multi threading or S M T side channel attacks. And, you know, while it's not officially part of Infinity Guard, we've actually added more APEC acceleration, which greatly benefits the security of those confidential VMs with the larger number of VCPUs, which basically means that you can build larger VMs and still be secured. And then lastly, we actually added even stronger a e s encryption. So we went from 128 bit to 256 bit, which is now military grade encryption on top of that. And, you know, and, and that's really, you know, the de facto crypto cryptography that is used for most of the applications for, you know, customers like the US federal government and, and all, you know, the, is really an essential element for memory security and the H B C applications. And I always say if it's good enough for the US government, it's good enough for you. >>Exactly. Well, it's got to be, talk a little bit about how AMD is doing this together with HPE a little bit about the partnership as we round out our conversation. >>Sure, absolutely. So security is only as strong as the layer below it, right? So, you know, that's why modern security must be built in rather than, than, you know, bolted on or, or, or, you know, added after the fact, right? So HPE and a MD actually developed this layered approach for protecting critical data together, right? Through our leadership and, and security features and innovations, we really deliver a set of hardware based features that, that help decrease potential attack surfaces. With, with that holistic approach that, you know, that safeguards the critical information across system, you know, the, the entire system lifecycle. And we provide the confidence of built-in silicon authentication on the world's most secure industry standard servers. And with a 360 degree approach that brings high availability to critical workloads while helping to defend, you know, against internal and external threats. So things like h hp, root of silicon root of trust with the trusted supply chain, which, you know, obviously AMD's part of that supply chain combined with AMD's Infinity guard technology really helps provide that end-to-end data protection in today's business. >>And that is so critical for businesses in every industry. As you mentioned, the attackers are getting more and more sophisticated, the vulnerabilities are increasing. The ability to have a pa, a partnership like H P E and a MD to deliver that end-to-end data protection is table stakes for businesses. David, thank you so much for joining me on the program, really walking us through what am MD is doing, the the fourth gen epic processors and how you're working together with HPE to really enable security to be successfully accomplished by businesses across industries. We appreciate your insights. >>Well, thank you again for having me, and we appreciate the partnership with hpe. >>Well, you wanna thank you for watching our special program HPE Compute Security. I do have a call to action for you. Go ahead and visit hpe com slash security slash compute. Thanks for watching.

>>Welcome to the Cube's Continuing coverage of AMD's fourth generation Epic launch. I'm Dave Nicholson and I'm joining you here in our Palo Alto Studios. We have two very interesting guests to dive into some of the announcements that have been made and maybe take a look at this from an AI and ML perspective. Our first guest is Milland Doley. He's a senior director for software and solutions at amd, and we're also joined by Shamus Jones, who's a director of server engineering at Dell Technologies. Welcome gentlemen. How are you? >>Very good, thank >>You. Welcome to the Cube. So let's start out really quickly, Shamus, what, give us a thumbnail sketch of what you do at Dell. >>Yeah, so I'm the director of technical marketing engineering here at Dell, and our team really takes a look at the technical server portfolio and solutions and ensures that we can look at, you know, the performance metrics, benchmarks, and performance characteristics, so that way we can give customers a good idea of what they can expect from the server portfolio when they're looking to buy Power Edge from Dell. >>Milland, how about you? What's, what's new at a M D? What do you do there? >>Great to be here. Thank you for having me at amd, I'm the senior director of performance engineering and ISV ecosystem enablement, which is a long winter way of saying we do a lot of benchmarks, improved performance and demonstrate with wonderful partners such as Shamus and Dell, the combined leverage that AMD four generation processes and Dell systems can bring to bear on a multitude of applications across the industry spectrum. >>Shamus, talk about that relationship a little bit more. The relationship between a M D and Dell. How far back does it go? What does it look like in practical terms? >>Absolutely. So, you know, ever since AM MD reentered the server space, we've had a very close relationship. You know, it's one of those things where we are offering solutions that are out there to our customers no matter what generation A portfolio, if they're, if they're demanding either from their competitor or a m d, we offer a portfolio solutions that are out there. What we're finding is that within their generational improvements, they're just getting better and better and better. Really exciting things happening from a m D at the moment, and we're seeing that as we engineer those CPU stacks into our, our server portfolio, you know, we're really seeing unprecedented performance across the board. So excited about the, the history, you know, my team and Lin's team work very closely together, so much so that we were communicating almost on a daily basis around portfolio platforms and updates around the, the, the benchmarks testing and, and validation efforts. >>So Melind, are you happy with these PowerEdge boxes that Seamus is building to, to house, to house your baby? >>We are delighted, you know, it's hard to find stronger partners than Shamus and Dell with AMD's, second generation epic service CPUs. We already had undisputable industry performance leadership, and then with the third and now the fourth generation CPUs, we've just increased our lead with competition. We've got so many outstanding features at the platform, at the CPU level, everybody focuses on the high core counts, but there's also the DDR five, the memory, the io, and the storage subsystem. So we believe we have a fantastic performance and performance per dollar performance per what edge over competition, and we look to partners such as Dell to help us showcase that leadership. >>Well. So Shay Yeah, through Yeah, go ahead >>Dave. What, what I'd add, Dave, is that through the, the partnership that we've had, you know, we've been able to develop subsystems and platform features that historically we couldn't have really things around thermals power efficiency and, and efficiency within the platform. That means that customers can get the most out of their compute infrastructure. >>So this is gonna be a big question moving forward as next generation platforms are rolled out, there's the potential for people to have sticker shock. You talk about something that has eight or 12 cores in a, in a physical enclosure versus 96 cores, and, and I guess the, the question is, do the ROI and TCO numbers look good for someone to make that upgrade? Shamus, you wanna, you wanna hit that first or you guys are integrated? >>Absolutely, yeah, sorry. Absolutely. So we, I'll tell you what, at the moment, customers really can't afford not to upgrade at the moment, right? We've taken a look at the cost basis of keeping older infrastructure in place, let's say five or seven year old infrastructure servers that are, that are drawing more power maybe are, are poorly utilized within the infrastructure and take more and more effort and time to manage, maintain and, and really keep in production. So as customers look to upgrade or refresh their platforms, what we're finding right is that they can take a dynamic consolidation sometimes 5, 7, 8 to one consolidation depending on which platform they have as a historical and which one they're looking to upgrade to. Within AI specifically and machine learning frameworks, we're seeing really unprecedented performance. Lin's team partnered with us to deliver multiple benchmarks for the launch, some of which we're still continuing to see the goodness from things like TP C X AI as a framework, and I'm talking about here specifically the CPU U based performance. >>Even though in a lot of those AI frameworks, you would also expect to have GPUs, which all of the four platforms that we're offering on the AM MD portfolio today offer multiple G P U offerings. So we're seeing a balance between a huge amount of C P U gain and performance, as well as more and more GPU offerings within the platform. That was real, that was a real challenge for us because of the thermal challenges. I mean, you think GPUs are going up 300, 400 watt, these CPUs at 96 core are, are quite demanding thermally, but what we're able to do is through some, some unique smart cooling engineering within the, the PowerEdge portfolio, we can take a look at those platforms and make the most efficient use case by having things like telemetry within the platform so that way we can dynamically change fan speeds to get customers the best performance without throttling based on their need. >>Melin the cube was at the Supercomputing conference in Dallas this year, supercomputing conference 2022, and a lot of the discussion was around not only advances in microprocessor technology, but also advances in interconnect technology. How do you manage that sort of research partnership with Dell when you aren't strictly just focusing on the piece that you are bringing to the party? It's kind of a potluck, you know, we, we, we, we mentioned P C I E Gen five or 5.0, whatever you want to call it, new DDR storage cards, Nicks, accelerators, all of those, all of those things. How do you keep that straight when those aren't things that you actually build? >>Well, excellent question, Dave. And you know, as we are developing the next platform, obviously the, the ongoing relationship is there with Dell, but we start way before launch, right? Sometimes it's multiple years before launch. So we are not just focusing on the super high core counts at the CPU level and the platform configurations, whether it's single socket or dual socket, we are looking at it from the memory subsystem from the IO subsystem, P c i lanes for storage is a big deal, for example, in this generation. So it's really a holistic approach. And look, core counts are, you know, more important at the higher end for some customers h HPC space, some of the AI applications. But on the lower end you have database applications or some other is s v applications that care a lot about those. So it's, I guess different things matter to different folks across verticals. >>So we partnered with Dell very early in the cycle, and it's really a joint co-engineering. Shamus talked about the focus on AI with TP C X xci, I, so we set five world records in that space just on that one benchmark with AD and Dell. So fantastic kick kick off to that across a multitude of scale factors. But PPP c Xci is not just the only thing we are focusing on. We are also collaborating with Dell and des e i on some of the transformer based natural language processing models that we worked on, for example. So it's not just a steep CPU story, it's CPU platform, es subsystem software and the whole thing delivering goodness across the board to solve end user problems in AI and and other verticals. >>Yeah, the two of you are at the tip of the spear from a performance perspective. So I know it's easy to get excited about world records and, and they're, they're fantastic. I know Shamus, you know, that, you know, end user customers might, might immediately have the reaction, well, I don't need a Ferrari in my data center, or, you know, what I need is to be able to do more with less. Well, aren't we delivering that also? And you know, you imagine you milland you mentioned natural, natural language processing. Shamus, are you thinking in 2023 that a lot more enterprises are gonna be able to afford to do things like that? I mean, what are you hearing from customers on this front? >>I mean, while the adoption of the top bin CPU stack is, is definitely the exception, not the rule today we are seeing marked performance, even when we look at the mid bin CPU offerings from from a m d, those are, you know, the most common sold SKUs. And when we look at customers implementations, really what we're seeing is the fact that they're trying to make the most, not just of dollar spend, but also the whole subsystem that Melin was talking about. You know, the fact that balanced memory configs can give you marked performance improvements, not just at the CPU level, but as actually all the way through to the, to the application performance. So it's, it's trying to find the correct balance between the application needs, your budget, power draw and infrastructure within the, the data center, right? Because not only could you, you could be purchasing and, and look to deploy the most powerful systems, but if you don't have an infrastructure that's, that's got the right power, right, that's a large challenge that's happening right now and the right cooling to deal with the thermal differences of the systems, might you wanna ensure that, that you can accommodate those for not just today but in the future, right? >>So it's, it's planning that balance. >>If I may just add onto that, right? So when we launched, not just the fourth generation, but any generation in the past, there's a natural tendency to zero in on the top bin and say, wow, we've got so many cores. But as Shamus correctly said, it's not just that one core count opn, it's, it's the whole stack. And we believe with our four gen CPU processor stack, we've simplified things so much. We don't have, you know, dozens and dozens of offerings. We have a fairly simple skew stack, but we also have a very efficient skew stack. So even, even though at the top end we've got 96 scores, the thermal budget that we require is fairly reasonable. And look, with all the energy crisis going around, especially in Europe, this is a big deal. Not only do customers want performance, but they're also super focused on performance per want. And so we believe with this generation, we really delivered not just on raw performance, but also on performance per dollar and performance per one. >>Yeah. And it's not just Europe, I'm, we're, we are here in Palo Alto right now, which is in California where we all know the cost of an individual kilowatt hour of electricity because it's quite, because it's quite high. So, so thermals, power cooling, all of that, all of that goes together and that, and that drives cost. So it's a question of how much can you get done per dollar shame as you made the point that you, you're not, you don't just have a one size fits all solution that it's, that it's fit for function. I, I'm, I'm curious to hear from you from the two of you what your thoughts are from a, from a general AI and ML perspective. We're starting to see right now, if you hang out on any kind of social media, the rise of these experimental AI programs that are being presented to the public, some will write stories for you based on prom, some will create images for you. One of the more popular ones will create sort of a, your superhero alter ego for, I, I can't wait to do it, I just got the app on my phone. So those are all fun and they're trivial, but they sort of get us used to this idea that, wow, these systems can do things. They can think on their own in a certain way. W what do, what do you see the future of that looking like over the next year in terms of enterprises, what they're going to do for it with it >>Melan? Yeah, I can go first. Yeah, yeah, yeah, yeah, >>Sure. Yeah. Good. >>So the couple of examples, Dave, that you mentioned are, I, I guess it's a blend of novelty and curiosity. You know, people using AI to write stories or poems or, you know, even carve out little jokes, check grammar and spelling very useful, but still, you know, kind of in the realm of novelty in the mainstream, in the enterprise. Look, in my opinion, AI is not just gonna be a vertical, it's gonna be a horizontal capability. We are seeing AI deployed across the board once the models have been suitably trained for disparate functions ranging from fraud detection or anomaly detection, both in the financial markets in manufacturing to things like image classification or object detection that you talked about in, in the sort of a core AI space itself, right? So we don't think of AI necessarily as a vertical, although we are showcasing it with a specific benchmark for launch, but we really look at AI emerging as a horizontal capability and frankly, companies that don't adopt AI on a massive scale run the risk of being left behind. >>Yeah, absolutely. There's an, an AI as an outcome is really something that companies, I, I think of it in the fact that they're adopting that and the frameworks that you're now seeing as the novelty pieces that Melin was talking about is, is really indicative of the under the covers activity that's been happening within infrastructures and within enterprises for the past, let's say 5, 6, 7 years, right? The fact that you have object detection within manufacturing to be able to, to be able to do defect detection within manufacturing lines. Now that can be done on edge platforms all the way at the device. So you're no longer only having to have things be done, you know, in the data center, you can bring it right out to the edge and have that high performance, you know, inferencing training models. Now, not necessarily training at the edge, but the inferencing models especially, so that way you can, you know, have more and, and better use cases for some of these, these instances things like, you know, smart cities with, with video detection. >>So that way they can see, especially during covid, we saw a lot of hospitals and a lot of customers that were using using image and, and spatial detection within their, their video feeds to be able to determine who and what employees were at risk during covid. So there's a lot of different use cases that have been coming around. I think the novelty aspect of it is really interesting and I, I know my kids, my daughters love that, that portion of it, but really what's been happening has been exciting for quite a, quite a period of time in the enterprise space. We're just now starting to actually see those come to light in more of a, a consumer relevant kind of use case. So the technology that's been developed in the data center around all of these different use cases is now starting to feed in because we do have more powerful compute at our fingertips. We do have the ability to talk more about the framework and infrastructure that's that's right out at the edge. You know, I know Dave in the past you've said things like the data center of, you know, 20 years ago is now in my hand as, as my cell phone. That's right. And, and that's, that's a fact and I'm, it's exciting to think where it's gonna be in the next 10 or 20 years. >>One terabyte baby. Yeah. One terabyte. Yeah. It's mind bo. Exactly. It's mind boggling. Yeah. And it makes me feel old. >>Yeah, >>Me too. And, and that and, and Shamus, that all sounded great. A all I want is a picture of me as a superhero though, so you guys are already way ahead of the curve, you know, with, with, with that on that note, Seamus wrap us up with, with a, with kind of a summary of the, the highlights of what we just went through in terms of the performance you're seeing out of this latest gen architecture from a md. >>Absolutely. So within the TPC xai frameworks that Melin and my team have worked together to do, you know, we're seeing unprecedented price performance. So the fact that you can get 220% uplift gen on gen for some of these benchmarks and, you know, you can have a five to one consolidation means that if you're looking to refresh platforms that are historically legacy, you can get a, a huge amount of benefit, both in reduction in the number of units that you need to deploy and the, the amount of performance that you can get per unit. You know, Melinda had mentioned earlier around CPU performance and performance per wat, specifically on the Tu socket two U platform using the fourth generation a m d Epic, you know, we're seeing a 55% higher C P U performance per wat that is that, you know, when for people who aren't necessarily looking at these statistics, every generation of servers, that that's, that is a huge jump leap forward. >>That combined with 121% higher spec scores, you know, as a benchmark, those are huge. Normally we see, let's say a 40 to 60% performance improvement on the spec benchmarks, we're seeing 121%. So while that's really impressive at the top bin, we're actually seeing, you know, large percentile improvements across the mid bins as well, you know, things in the range of like 70 to 90% performance improvements in those standard bins. So it, it's a, it's a huge performance improvement, a power efficiency, which means customers are able to save energy, space and time based on, on their deployment size. >>Thanks for that Shamus, sadly, gentlemen, our time has expired. With that, I want to thank both of you. It's a very interesting conversation. Thanks for, thanks for being with us, both of you. Thanks for joining us here on the Cube for our coverage of AMD's fourth generation Epic launch. Additional information, including white papers and benchmarks plus editorial coverage can be found on does hardware matter.com.

foreign welcome back to re invent 2022 we're wrapping up four days well one evening and three solid days wall-to-wall of cube coverage I'm Dave vellante John furrier's birthday is today he's on a plane to London to go see his nephew get married his his great Sister Janet awesome family the furriers uh spanning the globe and uh and John I know you wanted to be here you're watching in Newark or you were waiting to uh to get in the plane so all the best to you happy birthday one year the Amazon PR people brought a cake out to celebrate John's birthday because he's always here at AWS re invented his birthday so I'm really pleased to have two really special guests uh former Cube host Cube Alum great wikibon contributor Stu miniman now with red hat still good to see you again great to be here Dave yeah I was here for that cake uh the twitterverse uh was uh really helping to celebrate John's birthday today and uh you know always great to be here with you and then with this you know Awesome event this week and friend of the cube of many time Cube often Cube contributor as here's a cube analyst this week as his own consultancy sarbj johal great to see you thanks for coming on good to see you Dave uh great to see you stu I'm always happy to participate in these discussions and um I enjoy the discussion every time so this is kind of cool because you know usually the last day is a getaway day and this is a getaway day but this place is still packed I mean it's I mean yeah it's definitely lighter you can at least walk and not get slammed but I subjit I'm going to start with you I I wanted to have you as the the tail end here because cause you participated in the analyst sessions you've been watching this event from from the first moment and now you've got four days of the Kool-Aid injection but you're also talking to customers developers Partners the ecosystem where do you want to go what's your big takeaways I think big takeaways that Amazon sort of innovation machine is chugging along they are I was listening to some of the accessions and when I was back to my room at nine so they're filling the holes in some areas but in some areas they're moving forward there's a lot to fix still it doesn't seem like that it seems like we are done with the cloud or The Innovation is done now we are building at the millisecond level so where do you go next there's a lot of room to grow on the storage side on the network side uh the improvements we need and and also making sure that the software which is you know which fits the hardware like there's a specialized software um sorry specialized hardware for certain software you know so there was a lot of talk around that and I attended some of those sessions where I asked the questions around like we have a specialized database for each kind of workload specialized processes processors for each kind of workload yeah the graviton section and actually the the one interesting before I forget that the arbitration was I asked that like why there are so many so many databases and IRS for the egress costs and all that stuff can you are you guys thinking about reducing that you know um the answer was no egress cost is not a big big sort of uh um show stopper for many of the customers but but the from all that sort of little discussion with with the folks sitting who build these products over there was that the plethora of choice is given to the customers to to make them feel that there's no vendor lock-in so if you are using some open source you know um soft software it can be on the you know platform side or can be database side you have database site you have that option at AWS so this is a lot there because I always thought that that AWS is the mother of all lock-ins but it's got an ecosystem and we're going to talk about exactly we'll talk about Stu what's working within AWS when you talk to customers and where are the challenges yeah I I got a comment on open source Dave of course there because I mean look we criticized to Amazon for years about their lack of contribution they've gotten better they're doing more in open source but is Amazon the mother of all lock-ins many times absolutely there's certain people inside Amazon I'm saying you know many of us talk Cloud native they're like well let's do Amazon native which means you're like full stack is things from Amazon and do things the way that we want to do things and you know I talk to a lot of customers they use more than one Cloud Dave and therefore certain things absolutely I want to Leverage The Innovation that Amazon has brought I do think we're past building all the main building blocks in many ways we are like in day two yes Amazon is fanatically customer focused and will always stay that way but you know there wasn't anything that jumped out at me last year or this year that was like Wow new category whole new way of thinking about something we're in a vocals last year Dave said you know we have over 200 services and if we listen to you the customer we'd have over two thousand his session this week actually got some great buzz from my friends in the serverless ecosystem they love some of the things tying together we're using data the next flywheel that we're going to see for the next 10 years Amazon's at the center of the cloud ecosystem in the IT world so you know there's a lot of good things here and to your point Dave the ecosystem one of the things I always look at is you know was there a booth that they're all going to be crying in their beer after Amazon made an announcement there was not a tech vendor that I saw this week that was like oh gosh there was an announcement and all of a sudden our business is gone where I did hear some rumbling is Amazon might be the next GSI to really move forward and we've seen all the gsis pushing really deep into supporting Cloud bringing workloads to the cloud and there's a little bit of rumbling as to that balance between what Amazon will do and their uh their go to market so a couple things so I think I think we all agree that a lot of the the announcements here today were taping seams right I call it and as it relates to the mother of all lock-in the reason why I say that it's it's obviously very much a pejorative compare Oracle company you know really well with Amazon's lock-in for Amazon's lock-in is about bringing this ecosystem together so that you actually have Choice Within the the house so you don't have to leave you know there's a there's a lot to eat at the table yeah you look at oracle's ecosystem it's like yeah you know oracle is oracle's ecosystem so so that is how I think they do lock in customers by incenting them not to leave because there's so much Choice Dave I agree with you a thousand I mean I'm here I'm a I'm a good partner of AWS and all of the partners here want to be successful with Amazon and Amazon is open to that it's not our way or get out which Oracle tries how much do you extract from the overall I.T budget you know are you a YouTube where you give the people that help you create a large sum of the money YouTube hasn't been all that profitable Amazon I think is doing a good balance of the ecosystem makes money you know we used to talk Dave about you know how much dollars does VMware make versus there um I think you know Amazon is a much bigger you know VMware 2.0 we used to think talk about all the time that VMware for every dollar spent on VMware licenses 15 or or 12 or 20 were spent in the ecosystem I would think the ratio is even higher here sarbji and an Oracle I would say it's I don't know yeah actually 1 to 0.5 maybe I don't know but I want to pick on your discussion about the the ecosystem the the partner ecosystem is so it's it's robust strong because it's wider I was I was not saying that there's no lock-in with with Amazon right AWS there's lock-in there's lock-in with everything there's lock-in with open source as well but but the point is that they're they're the the circle is so big you don't feel like locked in but they're playing smart as well they're bringing in the software the the platforms from the open source they're picking up those packages and saying we'll bring it in and cater that to you through AWS make it better perform better and also throw in their custom chips on top of that hey this MySQL runs better here so like what do you do I said oh Oracle because it's oracle's product if you will right so they are I think think they're filing or not slenders from their go to market strategy from their engineering and they listen to they're listening to customers like very closely and that has sort of side effects as well listening to customers creates a sprawl of services they have so many services and I criticized them last year for calling everything a new service I said don't call it a new service it's a feature of a existing service sure a lot of features a lot of features this is egress our egress costs a real problem or is it just the the on-prem guys picking at the the scab I mean what do you hear from customers so I mean Dave you know I I look at what Corey Quinn talks about all the time and Amazon charges on that are more expensive than any other Cloud the cloud providers and partly because Amazon is you know probably not a word they'd use they are dominant when it comes to the infrastructure space and therefore they do want to make it a little bit harder to do that they can get away with it um because um yeah you know we've seen some of the cloud providers have special Partnerships where you can actually you know leave and you're not going to be charged and Amazon they've been a little bit more flexible but absolutely I've heard customers say that they wish some good tunning and tongue-in-cheek stuff what else you got we lay it on us so do our players okay this year I think the focus was on the upside it's shifting gradually this was more focused on offside there were less talk of of developers from the main stage from from all sort of quadrants if you will from all Keynotes right so even Werner this morning he had a little bit for he was talking about he he was talking he he's job is to Rally up the builders right yeah so he talks about the go build right AWS pipes I thought was kind of cool then I said like I'm making glue easier I thought that was good you know I know some folks don't use that I I couldn't attend the whole session but but I heard in between right so it is really adopt or die you know I am Cloud Pro for last you know 10 years and I think it's the best model for a technology consumption right um because of economies of scale but more importantly because of division of labor because of specialization because you can't afford to hire the best security people the best you know the arm chip designers uh you can't you know there's one actually I came up with a bumper sticker you guys talked about bumper sticker I came up with that like last couple of weeks The Innovation favorite scale they have scale they have Innovation so that's where the Innovation is and it's it's not there again they actually say the market sets the price Market you as a customer don't set the price the vendor doesn't set the price Market sets the price so if somebody's complaining about their margins or egress and all that I think that's BS um yeah I I have a few more notes on the the partner if you you concur yeah Dave you know with just coming back to some of this commentary about like can Amazon actually enable something we used to call like Community clouds uh your companies like you know Goldman and NASDAQ and the like where Industries will actually be able to share data uh and you know expand the usage and you know Amazon's going to help drive that API economy forward some so it's good to see those things because you know we all know you know all of us are smarter than just any uh single company together so again some of that's open source but some of that is you know I think Amazon is is you know allowing Innovation to thrive I think the word you're looking for is super cloud there well yeah I mean it it's uh Dave if you want to go there with the super cloud because you know there's a metaphor for exactly what you described NASDAQ Goldman Sachs we you know and and you know a number of other companies that are few weeks at the Berkeley Sky Computing paper yeah you know that's a former supercloud Dave Linthicum calls it metacloud I'm not really careful I mean you know I go back to the the challenge we've been you know working at for a decade is the distributed architecture you know if you talk about AI architectures you know what lives in the cloud what lives at the edge where do we train things where do we do inferences um locations should matter a lot less Amazon you know I I didn't hear a lot about it this show but when they came out with like local zones and oh my gosh out you know all the things that Amazon is building to push out to the edge and also enabling that technology and software and the partner ecosystem helps expand that and Pull It in it's no longer you know Dave it was Hotel California all of the data eventually is going to end up in the public cloud and lock it in it's like I don't think that's going to be the case we know that there will be so much data out at the edge Amazon absolutely is super important um there some of those examples we're giving it's not necessarily multi-cloud but there's collaboration happening like in the healthcare world you know universities and hospitals can all share what they're doing uh regardless of you know where they live well Stephen Armstrong in the analyst session did say that you know we're going to talk about multi-cloud we're not going to lead with it necessarily but we are going to actually talk about it and that's different to your points too than in the fullness of time all the data will be in the cloud that's a new narrative but go ahead yeah actually Amazon is a leader in the cloud so if they push the cloud even if they don't say AWS or Amazon with it they benefit from it right and and the narrative is that way there's the proof is there right so again Innovation favorite scale there are chips which are being made for high scale their software being tweaked for high scale you as a Bank of America or for the Chrysler as a typical Enterprise you cannot afford to do those things in-house what cloud providers can I'm not saying just AWS Google cloud is there Azure guys are there and few others who are behind them and and you guys are there as well so IBM has IBM by the way congratulations to your red hat I know but IBM won the award um right you know very good partner and yeah but yeah people are dragging their feet people usually do on the change and they are in denial denial they they drag their feet and they came in IBM director feed the cave Den Dell drag their feed the cave in yeah you mean by Dragon vs cloud deniers cloud deniers right so server Huggers I call them but they they actually are sitting in Amazon Cloud Marketplace everybody is buying stuff from there the marketplace is the new model OKAY Amazon created the marketplace for b2c they are leading the marketplace of B2B as well on the technology side and other people are copying it so there are multiple marketplaces now so now actually it's like if you're in in a mobile app development there are two main platforms Android and Apple you first write the application for Apple right then for Android hex same here as a technology provider as and I I and and I actually you put your stuff to AWS first then you go anywhere else yeah they are later yeah the Enterprise app store is what we've wanted for a long time the question is is Amazon alone the Enterprise app store or are they partner of a of a larger portfolio because there's a lot of SAS companies out there uh that that play into yeah what we need well and this is what you're talking about the future but I just want to make a point about the past you talking about dragging their feet because the Cube's been following this and Stu you remember this in 2013 IBM actually you know got in a big fight with with Amazon over the CIA deal you know and it all became public judge wheeler eviscerated you know IBM and it ended up IBM ended up buying you know soft layer and then we know what happened there and it Joe Tucci thought the cloud was Mosey right so it's just amazing to see we have booksellers you know VMware called them books I wasn't not all of them are like talking about how great Partnerships they are it's amazing like you said sub GC and IBM uh with the the GSI you know Partnership of the year but what you guys were just talking about was the future and that's what I wanted to get to is because you know Amazon's been leading the way I I was listening to Werner this morning and that just reminded me of back in the days when we used to listen to IBM educate us give us a master class on system design and decoupled systems and and IO and everything else now Amazon is you know the master educator and it got me thinking how long will that last you know will they go the way of you know the other you know incumbents will they be disrupted or will they you know keep innovating maybe it's going to take 10 or 20 years I don't know yeah I mean Dave you actually you did some research I believe it was a year or so ago yeah but what will stop Amazon and the one thing that worries me a little bit um is the two Pizza teams when you have over 202 Pizza teams the amount of things that each one of those groups needs to take care of was more than any human could take care of people burn out they run out of people how many amazonians only last two or three years and then leave because it is tough I bumped into plenty of friends of mine that have been you know six ten years at Amazon and love it but it is a tough culture and they are driving werner's keynote I thought did look to from a product standpoint you could say tape over some of the seams some of those solutions to bring Beyond just a single product and bring them together and leverage data so there are some signs that they might be able to get past some of those limitations but I still worry structurally culturally there could be some challenges for Amazon to keep the momentum going especially with the global economic impact that we are likely to see in the next year bring us home I think the future side like we could talk about the vendors all day right to serve the community out there I think we should talk about how what's the future of technology consumption from the consumer side so from the supplier side just a quick note I think the only danger AWS has has that that you know Fred's going after them you know too big you know like we will break you up and that can cause some disruption there other than that I think they they have some more steam to go for a few more years at least before we start thinking about like oh this thing is falling apart or anything like that so they have a lot more they have momentum and it's continuing so okay from the I think game is on retail by the way is going to get disrupted before AWS yeah go ahead from the buyer's side I think um the the future of the sort of Technology consumption is based on the paper uh use and they actually are turning all their services to uh they are sort of becoming serverless behind the scenes right all analytics service they had one service left they they did that this year so every service is serverless so that means you pay exactly for the amount you use the compute the iops the the storage so all these three layers of course Network we talked about the egress stuff and that's a problem there because of the network design mainly because Google has a flatter design and they have lower cost so so they are actually squeezing the their their designing this their services in a way that you don't waste any resources as a buyer so for example very simple example when early earlier In This Cloud you will get a VM right in Cloud that's how we started so and you can get 20 use 20 percent of the VM 80 is getting wasted that's not happening now that that has been reduced to the most extent so now your VM grows as you grow the usage and if you go higher than the tier you picked they will charge you otherwise they will not charge you extra so that's why there's still a lot of instances like many different types you have to pick one I think the future is that those instances will go away the the instance will be formed for you on the fly so that is the future serverless all right give us bumper sticker Stu and then Serb G I'll give you my quick one and then we'll wrap yeah so just Dave to play off of sharp G and to wrap it up you actually wrote about it on your preview post for here uh serverless we're talking about how developers think about things um and you know Amazon in many ways you know is the new default server uh you know for the cloud um and containerization fits into the whole serverless Paradigm uh it's the space that I live in uh you know every day here and you know I was happy to see the last few years serverless and containers there's a blurring a line and you know subject we're still going to see VMS for a long time yeah yeah we will see that so give us give us your book Instagram my number six is innovation favorite scale that's my bumper sticker and and Amazon has that but also I I want everybody else to like the viewers to take a look at the the Google Cloud as well as well as IBM with others like maybe you have a better price to Performance there for certain workloads and by the way one vendor cannot do it alone we know that for sure the market is so big there's a lot of room for uh Red Hats of the world and and and Microsoft's the world to innovate so keep an eye on them they we need the competition actually and that's why competition Will Keep Us to a place where Market sets the price one vendor doesn't so the only only danger is if if AWS is a monopoly then I will be worried I think ecosystems are the Hallmark of a great Cloud company and Amazon's got the the biggest and baddest ecosystem and I think the other thing to watch for is Industries building on top of the cloud you mentioned the Goldman Sachs NASDAQ Capital One and Warner media these all these industries are building their own clouds and that's where the real money is going to be made in the latter half of the 2020s all right we're a wrap this is Dave Valente I want to first of all thank thanks to our great sponsors AWS for for having us here this is our 10th year at the cube AMD you know sponsoring as well the the the cube here Accenture sponsor to third set upstairs upstairs on the fifth floor all the ecosystem partners that came on the cube this week and supported our mission for free content our content is always free we try to give more to the community and we we take back so go to thecube.net and you'll see all these videos go to siliconangle com for all the news wikibon.com I publish weekly a breaking analysis series I want to thank our amazing crew here you guys we have probably 30 35 people unbelievable our awesome last session John Walls uh Paul Gillen Lisa Martin Savannah Peterson John Furrier who's on a plane we appreciate Andrew and Leonard in our ear and all of our our crew Palo Alto Boston and across the country thank you so much really appreciate it all right we are a wrap AWS re invent 2022 we'll see you in two weeks we'll see you two weeks at Palo Alto ignite back here in Vegas thanks for watching thecube the leader in Enterprise and emerging Tech coverage [Music]

>>Oh, welcome back to the Cube here at aws Reinvent 22. As we continue our coverage here, the AWS Global Showcase, the Startup Showcase, John Wall is here hosting for the Cube as we've been here all week. Hope you're enjoying our coverage here. This is day three, by the way. We're wrapping it up shortly with us to talk about what's going on in the, kind of the hotel world in it and what's going on in the cloud, especially at I hg is Eric Norman, head of infrastructure, architecture, and innovation at I H G Hotels and Resorts. Eric, good to see you, >>Sir. Oh, thank you. And thank you for inviting me. Yeah, >>You bet. Glad to have you board here on the queue. First time, I think too, by the way, right? >>It is. And can I just tell you who IHG is >>Real quick? Yeah, wait a second. First I want another rest. I got Introduc to Rod Stuller, who is the Vice president and of Solutions marketing at Aviatrix and Rod. Good to see you, sir. Thanks a lot. Now let's talk about I ih. >>Great. Well, IHGs a a hospitality company, it's been around for 200 years, that has 17 brands globally in over a hundred countries. We sleek, you know, up could up to 888,000 people a night. So it's a pretty large company that we compete with, you know, all the hotel companies globally. >>So let's talk about your, your footprint right now in, in terms of what your needs are, because you've mentioned obviously a lot of, you have a lot of customers needs, you have a lot of internal stakeholder needs. Yeah. So just from that perspective, how are you balancing out, you know, the products you wanna launch as opposed to the, on the development side and the maintenance side? >>Yeah, I mean we, we have focused our, our attention to our, our guests and our hotels globally and, and taking technology and from a foundation, getting it at, at the edge so that way the consumer and the hotel owner can deliver a quality product to a guest experience. You know, we've have moved larger, a large deployment of our mission critical applications over the last five years really, of moving into more SaaS and infrastructure like AWS and GCP and, and leveraging their global scale to be able to deliver at the edge or get closer to the edge. And so we've, you know, I'm pretty sure you've seen, you know, kind of people building, you know, mission critical apps. You know, probably in the last three years it's probably escalating and more of like a hockey stick of moving stuff. I'd love to hear what AVIA is seeing. Oh >>Yeah. Now we're, we're seeing that quite a bit, right? As people move into the cloud, it's now business critical applications that are going there. So good enough isn't good enough anymore, right? It has to be, you know, a powerful capability that's business critical, can support that, give people the ability to troubleshoot it when something goes wrong. And then multi-cloud, you mentioned a couple different cloud companies, a lot of enterprises are moving to multiple clouds and you don't want to have to do it differently in every cloud. You want a infrastructure management layer that allows you to do that across >>Clouds. So how do you go about that, you know, deciding what goes where. I mean, it sounds like a simple question, but, but if you are dealing in a lot of different kinds of environments, different needs and different requirements, whatever, you know, how are you sorting out, delegating, you know, you know, you're, you're you're gonna be working here, you're gonna be >>Working there. Yeah. So we built some standards base that says, you know, certain types of apps, you know, transactional base, you know, go to this cloud provider and data analytics that's gonna go to another, another cloud provider based on our decision of key capability, native capability, and, and also coverage. You know, cuz we are in China, right? You know, you know, I, I've gotta be able to get into China and, and build not only a network that can support that, but also business apps locally to meet, compete with compliance, regulatory type activities. I mean, even in, in the US market, I got, you know, California privacy laws, you know, you have globally, you've gotta deal with getting data applications into compliance for those globally, right? >>Yeah. So, so you got that compliance slash governance Yeah. Issue. Huge issue. Yeah. I would think for you, you gotta decide who's gonna get to what when, and also we have to meet certain regulatory standards as you pointed out. And not just there, but you got European footprint, right? I mean, you're global. Yeah. So, so you know, handling that kind of scope or scale, what kind of nightmares or challenges does that provide you and how's Aviatrix helping you solve >>That? Yeah, in the early days, you know, we were using cloud native, you know, constructs for networking and a little bit of a security type angle to it. What we found was, you know, you can't get the automation you need. You can't get the, the scalability, you know, cuz we're, we're trying to shift left our, you know, our DevOps and our ability to deploy infrastructure. Aviatrix had come in and, and provided a, a solution that gets us there quicker than anybody else. It's allow us to, you know, build a mesh network across all our regions globally. I'm able to deploy, you know, new landing zones or, you know, public cloud fairly quickly with my, you know, networking construct. We also, we found that because we are a multi hybrid cloud, we, we introduced on the edge a a new network. We had to introduce a performance hub architecture that's using Equinix that sits in every region in every public cloud and partner. Cuz all our partners, you know, we, we've moved a lot of stuff to sas. You know, Amadeus is our centralized reservation system. That's our key, you know? Sure. You know, reservation tool, it's so sourced out. I need to bring them in and I need to get data that's closer to where, in a region to where it needs the land so I can process it. Right. >>And it's a big world out there too. I mean, you're, you're not in your head Rod. So talk about if you would share some of the, the aviatrix experience in that regard. When you have a client like this that has these, you know, multinational locations and, and yet you're looking for some consistency and some uniformity. You don't, you know, you can't be reinventing the wheel every time something pops up, right? >>Right. No. And then, and it's about agility and speed and, you know, being able to do it with less people than you used to have to do things, right? You, you want to be able to give the developers what they need when they need it. There was a time when people were going around it, swiping their credit card and, and saying, it doesn't give me what I need. And so cloud is supposed to change that. So we're trying to deliver the ability to do that for the developers a lot faster than had been done in the past. But at the same time, giving the enterprise the controls, the security, the compliance that they need. And sometimes those things got in the way, but now we're building systems that allow that to happen at, at the piece that developers needed to happen. >>But what Rod said about, you know, one of the big things you sparked my thinking is it also, you know, building a overlay of the cloud native construct allows for visibility that, you know, you didn't have, you know, from a developer or even a operations day two operations, now you get that visibility into the network space and controls and management of that space a lot easier now, you know? >>Yeah. I mean, business critical applications, right? People, the people, the business does not care about networking, right? They see it as electricity and if it's down somebody else's problem to fix it. But the people who do need to keep it up, they need the telemetry. They need the ability to understand, are we trending in the wrong direction? Should we be doing something so that we don't get to the point where it goes down? And that's the kind of information that we're providing in this multi-cloud environment. You mentioned Equinix, we, we just have a partnership with Equinix where we're extending the cloud operational model that Aviatrix delivers all the way out to Equinix and that global fabric that you're talking about. So this is allowing the, the comp companies to have that visibility, that operational ability all the way globally. >>Yeah. Because you know, when you start building all these clouds now and multi regions, multiple AZs or different cloud providers or SaaS providers, you're moving data all over the place. And if you, if you don't have a single pane of glass to see that entire network and be able to route stuff accordingly, it's gonna be a zoo. It's not gonna >>Work. We were, I was talking earlier with, with another guest and we were just talking about companies in your case, I, I IHG kind of knowing what you have and it's not like such a basic thing he said, but yeah, you'd be surprised how many people don't know what they have. Oh, yeah. And so they're trying to provide that visibility and, and, and awareness. So, so I'm kind of curious because you were just the next interview up, so sorry Ken, but, but do you know what you have, I mean, are you learning what you have or is how do you identify, prioritize? How valuable is this asset as opposed to this can wait? I mean, is that still an ongoing process for >>You? It, it's definitely an ongoing process. I mean, we've done over the last three years of constantly assessing all our inventory of what we have, making sure we have the right mo roadmaps for each of the apps and products that we have. Cause we've turned to more of a product driven organization and a DevOps and we're, we're moving more and more product teams onto that DevOps process. Yep. So we can shift left a lot of the activities that developer in the past had to go over a fence to ask for help and, and, you know, kind of the automation of the network and the security built in allows us to be able to shift that left. >>Did that, I, you were saying too three years, right? You've been on, on this path Yep. Going back then to 2019 right. Pandemic hits, right. The world changes. How has that affected this three year period for you? And where are you in terms of where you expected to be and, and Yep. And then what's your, what are your headlights seeing down the road as to what your, your eventual journey, how you want that to end? >>I probably, the biggest story that we have a success story is when the pandemic did happen, you know, all our call centers, all agents had to go home. We were able within 30 days be able to bring up remote desktops, you know, workspaces an a uws and give access to globally in China and in Singapore and in the Americas. There's >>No small task there, >>That's for sure. So we built a desktop, certified it, and, and agents were able to answer calls for guests, you know, you know, so it was a huge success to us. Sure. It did slow down. I mean, during the pandemic it did slow us down from what gets migrated. You know, our focus is, you know, again, back to what I was saying earlier is around our guests and our loyalty and, you know, how do we give value back to our hotel owners and our guests? >>And how do you measure that? I mean, how do you know that what you're doing is working with, with that key audience? >>We'd measured by, you know, one occupa >>There so many, how many people do we have in the rooms? Right? But in terms of the interface, in terms of the effectiveness, the applications, in terms of what you're offering. Yeah. >>It gets back to uptime of our systems and you know, being able to deploy an application in multiple regions elevates the availability of the product to our guest. You know, the longer I'm up, the more revenue I can produce. Right. So, you know, so we, we try to, you know, we measure also guest satisfaction at the properties, you know, them using our tech and that kind of stuff to >>Be so you surveying just to find out what, how they feel about, so some, >>Cause we have a lot of tech inside of our hotels that allow for, we have ISG connect, which allows for people to go from one hotel another and not ask for passwords and, you know, that kind of stuff. >>That would not be made by the way. I'd be begging for help. Let's talk about skills, because I hear that a lot. Talk a lot about that this week. Hearing that, that, you know, the advancement of knowledge is obviously a very powerful thing, but it's also a bit of a shortcoming right now in terms of, of having a need for skills and not having that kind of firepower horsepower on your bench. What, what do you see in that regard? And, and first off, what did you see about it? And then I'll follow >>Up with Yeah, I mean, over our journey, it started off where you didn't have the skills, you know, you didn't have the skill from an operations engineering architecture. So we went on a, you know, you know, how do we build training programs? How do we get, you know, tools to, to either virtual training, bringing teachers, we built, you know, daily, our weekly calls where we bring our experts from our vendors in there to be able to ask questions to help engineering people or architecture people or operations to ask questions and get answers. You know, we, we've been on a role of, you know, upscaling over the last three years and we continue to drive that, you know, we have lunch and learns that we bring people to. Yep. You know, and, and we, and we, we ta tailor the, the content for that training based on what we are consuming and what we're using as opposed to just a, you know, a broad stroke of, of public cloud or, it's >>Almost like you don't have to be holistic about it. You just need to, what do you need to know to >>Make >>Them successful, to be better at what you're doing here? Right. Sure. >>And that's been huge. And, >>And yeah, we, and we have a program called ace, which is AVIATRIX certified engineer. And there's a bunch of different types of classes. So if you're a networking person in the past it's like A C C I E, but we have about 18,000 people over the last three years who have gone through that training. One of them. One of them, right? Is that right? Yeah. Yeah. And, and this is not necessarily about aviatrix. What we're doing is trying to give multi-cloud, you know, networking expertise because a lot of the people that we're talking about are coming from the data center world. And networking is so different in the cloud. We're helping them understand it's not as scary as they might think. Right. If your whole career has been networking in the data center and all of a sudden there's this cloud thing that you don't really understand, you need somebody to help you sort of get there. And we're doing that in a multi-cloud way. And we have all kinds of different levels to teach people how to do, do infrastructure as code. That's another thing, you know, data center guys, they never did infrastructure as code. It was, you had to bolt it in and plug stuff in. Right. But now things are being done much faster with infrastructure as code. And we're teaching people how >>To do that. Yeah. I mean, yesterday, one of the keynotes is about the partner in the, the marketplace. And they use the image imagery of, of marathon runner, you know, a marathon runner. Yeah. You could do a marathon by yourself, but if you want to improve and become a, a great marathon runner, you need a coach, you need nutritionist, you need people running with you to, to make that engine go faster a little bit. Yeah, exactly. And you know, having a partner like Aviatrix helps you know the team to be successful. >>Well, it is, it is a marathon, not a sprint. That's for sure. And you've been on this kind of three year jog. You might feel like you've been running a marathon a little bit, but it sounds like you're really off to a great start and, and have a pretty good partnership here. So thank you. Congratulations on that, Eric. Thank you for being with us. And Rod, same to you. Thank you. Appreciate the time here on the AWS Global Showcase. I'm John Wal, you're watching The Cube. We're out in Las Vegas and of course the cube, as you well know, is the leader in high tech coverage.

>>Hello, brilliant humans and welcome back to Las Vegas, Nevada, where we are live from the AWS Reinvent Show floor here with the cube. My name is Savannah Peterson, joined with Dave Valante, and we have a very exciting conversation with you. Two, two companies you may have heard of. We've got AWS and Red Hat in the house. Manu and Joel, thank you so much for being here. Love this little fist bump. Started off, that's right. Before we even got rolling, Manu, you said that you wanted this to be the best segment of, of the cubes airing. We we're doing over a hundred segments, so you're gonna have to bring the heat. >>We're ready. We're did go. Are we ready? Yeah, go. We're ready. Let's bring it on. >>We're ready. All right. I'm, I'm ready. Dave's ready. Let's do it. How's the show going for you guys real quick before we dig in? >>Yeah, I think after Covid, it's really nice to see that we're back into the 2019 level and, you know, people just want to get out, meet people, have that human touch with each other, and I think a lot of trust gets built as a functional that, so it's super amazing to see our partners and customers here at Reedman. Yeah, >>And you've got a few in the house. That's true. Just a few maybe, maybe a couple >>Very few shows can say that, by the way. Yeah, it's maybe a handful. >>I think one of the things we were saying, it's almost like the entire Silicon Valley descended in the expo hall area, so >>Yeah, it's >>For a few different reasons. There's a few different silicon defined. Yeah, yeah, yeah. Don't have strong on for you. So far >>It's, it's, it is amazing. It's the 10th year, right? It's decade, I think I've been to five and it's, it grows every single year. It's the, you have to be here. It's as simple as that. And customers from every single industry are here too. You don't get, a lot of shows have every single industry and almost every single location around the globe. So it's, it's a must, must be >>Here. Well, and the personas evolved, right? I was at reinvent number two. That was my first, and it was all developers, not all, but a lot of developers. And today it's a business mix, really is >>Totally, is a business mix. And I just, I've talked about it a little bit down the show, but the diversity on the show floor, it's the first time I've had to wait in line for the ladies' room at a tech conference. Almost a two decade career. It is, yeah. And it was really refreshing. I'm so impressed. So clearly there's a commitment to community, but also a commitment to diversity. Yeah. And, and it's brilliant to see on the show floor. This is a partnership that is robust and has been around for a little while. Money. Why don't you tell us a little bit about the partnership here? >>Yes. So Red Hand and AWS are best friends, you know, forever together. >>Aw, no wonder we got the fist bumps and all the good vibes coming out. I know, it's great. I love that >>We have a decade of working together. I think the relationship in the first phase was around running rail bundled with E two. Sure. We have about 70,000 customers that are running rail, which are running mission critical workloads such as sap, Oracle databases, bespoke applications across the state of verticals. Now, as more and more enterprise customers are finally, you know, endorsing and adopting public cloud, I think that business is just gonna continue to grow. So a, a lot of progress there. The second titration has been around, you know, developers tearing Red Hat and aws, Hey, listen, we wanna, it's getting competitive. We wanna deliver new features faster, quicker, we want scale and we want resilience. So just entire push towards devs containers. So that's the second chapter with, you know, red Hat OpenShift on aws, which launched as a, a joint manage service in 2021 last year. And I think the third phase, which you're super excited about, is just bringing the ease of consumption, one click deployment, and then having our customers, you know, benefit from the joint committed spend programs together. So, you know, making sure that re and Ansible and JBoss, the entire portfolio of Red Hat products are available on AWS marketplace. So that's the 1, 2, 3, it of our relationship. It's a decade of working together and, you know, best friends are super committed to making sure our customers and partners continue successful. >>Yeah, that he said it, he said it perfectly. 2008, I know you don't like that, but we started with Rel on demand just in 2008 before E two even had a console. So the partnership has been there, like Manu says, for a long time, we got the partnership, we got the products up there now, and we just gotta finalize that, go to market and get that gas on the fire. >>Yeah. So Graviton Outpost, local zones, you lead it into all the new stuff. So that portends, I mean, 2008, we're talking two years after the launch of s3. >>That's right. >>Right. So, and now look, so is this a harbinger of things to come with these new innovations? >>Yeah, I, I would say, you know, the innovation is a key tenant of our partnership, our relationship. So if you look at from a product standpoint, red Hat or Rel was one of the first platforms that made a support for graviton, which is basically 40% better price performance than any other distribution. Then that translated into making sure that Rel is available on all of our regions globally. So this year we launched Switzerland, Spain, India, and Red Hat was available on launch there, support for Nitro support for Outpost Rosa support on Outpost as well. So I think that relationship, that innovation on the product side, that's pretty visible. I think that innovation again then translates into what we are doing on marketplace with one click deployments we spoke about. I think the third aspect of the know innovation is around making sure that we are making our partners and our customers successful. So one of the things that we've done so far is Joe leads a, you know, a black belt team that really goes into each customer opportunity, making sure how can we help you be successful. We launched and you know, we should be able to share that on a link. After this, we launched like a big playlist, which talks about every single use case on how do you get successful and running OpenShift on aws. So that innovation on behalf of our customers partners to make them successful, that's been a key tenant for us together as >>Well. That's right. And that team that Manu is talking about, we're gonna, gonna 10 x that team this year going into January. Our fiscal yield starts in January. Love that. So yeah, we're gonna have a lot of no hiring freeze over here. Nope. No ma'am. No. Yeah, that's right. Yeah. And you know what I love about working with aws and, and, and Manu just said it very, all of that's customer driven. Every single event that we, that he just talked about in that timeline, it's customer driven, right? Customers wanted rail on demand, customers want JBoss up in the cloud, Ansible this week, you know, everything's up there now. So it's just getting that go to market tight and we're gonna, we're gonna get that done. >>So what's the algorithm for customer driven in terms of taking the input? Because if every customers saying, Hey, I this a >>Really similar >>Question right up, right? I, that's what I want. And if you know, 95% of the customers say it, Jay, maybe that's a good idea. >>Yeah, that's right. Trends. But >>Yeah. You know, 30% you might be like, mm, you know, 20%, you know, how do you guys decide when to put gas on the fire? >>No, that, I think, as I mentioned, there are about 70,000 large customers that are running rail on Easy Two, many of these customers are informing our product strategy. So we have, you know, close to about couple of thousand power users. We have customer advisory booths, and these are the, you know, customers are informing us, Hey, let's get all of the Red Hat portfolio and marketplace support for graviton, support for Outpost. Why don't we, why are we not able to dip into the consumption committed spend programs for both Red Hat and aws? That's right. So it's these power users both at the developer level as well as the guys who are actually doing large commercial consumption. They are the ones who are informing the roadmap for both Red Hat and aws. >>But do, do you codify the the feedback? >>Yeah, I'm like, I wanna see the database, >>The, I think it was, I don't know, it was maybe Chasy, maybe it was Besos, that that data beats intuition. So do you take that information and somehow, I mean, it's global, 70,000 customers, right? And they have different weights, different spending patterns, different levels of maturity. Yeah. Do you, how do you codify that and then ultimately make the decision? Yeah, I >>If, I mean, well you, you've got the strategic advisory boards, which are made up of customers and partners and you know, you get, you get a good, you gotta get a good slice of your customer base to get, and you gotta take their feedback and you gotta do something with it, right? That's the, that's the way we do it and codify it at the product level, I'm sure open source. That's, that's basically how we work at the product level, right? The most elegant solution in open source wins. And that's, that's pretty much how we do that at the, >>I would just add, I think it's also just the implicit trust that the two companies had built with each other, working in the trenches, making our customers and partners successful over the last decade. And Alex, give an example. So that manifests itself in context of like, you know, Amazon and Red Hat just published the entire roadmap for OpenShift. What are the new features that are becoming over the next six to nine to 12 months? It's open source available on GitHub. Customers can see, and then they can basically come back and give feedback like, Hey, you know, we want hip compliance. We just launched. That was a big request that was coming from our >>Customers. That is not any process >>Also for Graviton or Nvidia instances. So I I I think it's a, >>Here's the thing, the reason I'm pounding on this is because you guys have a pretty high hit rate, and I think as a >>Customer, mildly successful company >>As, as a customer advocate, the better, you know, if, if you guys make bets that pay off, it's gonna pay off for customers. Right. And because there's a lot of failures in it. Yeah. I mean, let's face it. That's >>Right. And I think, I think you said the key word bets. You place a lot of small bets. Do you have the, the innovation engine to do that? AWS is the perfect place to place those small bets. And then you, you know, pour gas on the fire when, when they take off. >>Yeah, it's a good point. I mean, it's not expensive to experiment. Yeah. >>Especially in the managed service world. Right? >>And I know you love taking things to market and you're a go to market guy. Let's talk gtm, what's got your snow pumped about GTM for 2023? >>We, we are gonna, you know, 10 x the teams that's gonna be focused on these products, right? So we're gonna also come out with a hybrid committed spend program for our customers that meet them where they want to go. So they're coming outta the data center going into a cloud. We're gonna have a nice financial model for them to do that. And that's gonna take a lot of the friction out. >>Yeah. I mean, you've nailed it. I, I think the, the fact that now entire Red Hat portfolio is available on marketplace, you can do it on one click deployment. It's deeply integrated with Amazon services and the most important part that Joel was making now customers can double dip. They can drive benefit from the consumption committed spend programs, both from Red Hat and from aws, which is amazing. Which is a game changer That's right. For many of our large >>Customers. That's right. And that, so we're gonna, we're gonna really go to town on that next year. That's, and all the, all the resources that I have, which are the technology sellers and the sas, you know, the engineers we're growing this team the most out that team. So it's, >>When you say 10 x, how many are you at now? I'm >>Curious to see where you're headed. Tell you, okay. There's not right? Oh no, there's not one. It's triple digit. Yeah, yeah. >>Today. Oh, sweet. Awesome. >>So, and it's a very sizable team. They're actually making sure that each of our customers are successful and then really making sure that, you know, no customer left behind policy. >>And it's a great point that customers love when Amazonians and Red Hats show up, they love it and it's, they want to get more of it, and we're gonna, we're gonna give it to 'em. >>Must feel great to be loved like that. >>Yeah, that's right. Yeah. Yeah. I would say yes. >>Seems like it's safe to say that there's another decade of partnership between your two companies. >>Hope so. That's right. That's the plan. >>Yeah. And I would say also, you know, just the IBM coming into the mix here. Yeah. I, you know, red Hat has informed the way we have turned around our partnership with ibm, essentially we, we signed the strategic collaboration agreement with the company. All of IBM software now runs on Rosa. So that is now also providing a lot of tailwinds both to our rail customers and as well as Rosa customers. And I think it's a very net creative, very positive for our partnership. >>That's right. It's been very positive. Yep. Yeah. >>You see the >>Billboards positive. Yeah, right. Also that, that's great. Great point, Dave. Yep. We have a, we have a new challenge, a new tradition on the cube here at Reinvent where we're, well, it's actually kind of a glamor moment for you, depending on how you leverage it. We're looking for your 32nd hot take your Instagram reel, your sizzle thought leadership, biggest takeaway, most important theme from this year's show. I know you want, right, Joel? I mean, you TM boy, I feel like you can spit the time. >>Yeah. It is all about Rosa for us. It is all in on that, that's the native OpenShift offering on aws and that's, that's the soundbite we're going go to town with. Now, I don't wanna forget all the other products that are in there, but Rosa is a, is a very key push for us this year. >>Fantastic. All right. Manu. >>I think our customers, it's getting super competitive. Our customers want to innovate just a >>Little bit. >>The enterprise customers see the cloud native companies. I wanna do what these guys are doing. I wanna develop features at a fast clip. I wanna scale, I wanna be resilient. And I think that's really the spirit that's coming out. So to Joel's point, you know, move to worlds containers, serverless, DevOps, which was like, you know, aha, something that's happening on the side of an enterprise is not becoming mainstream. The business is demanding it. The, it is becoming the centerpiece in the business strategy. So that's been really like the aha. Big thing that's happening here. >>Yeah. And those architectures are coming together, aren't they? That's correct. Right. You know, VMs and containers, it used to be one architecture and then at the other end of the spectrum is serverless. People thought of those as different things and now it's a single architecture and, and it's kind of right approach for the right job. >>And, and a compliments say to Red Hat, they do an incredible job of hiding that complexity. Yeah. Yes. And making sure that, you know, for example, just like, make it easier for the developers to create value and then, and you know, >>Yeah, that's right. Those, they were previously siloed architectures and >>That's right. OpenShift wanna be place where you wanna run containers or virtual machines. We want that to be this Yeah. Single place. Not, not go bolt on another piece of architecture to just do one or the other. Yeah. >>And hey, the hybrid cloud vision is working for ibm. No question. You know, and it's achievable. Yeah. I mean, I just, I've said unlike, you know, some of the previous, you know, visions on fixing the world with ai, hybrid cloud is actually a real problem that you're attacking and it's showing the results. Agreed. Oh yeah. >>Great. Alright. Last question for you guys. Cause it might be kind of fun, 10 years from now, oh, we're at another, we're sitting here, we all look the same. Time has passed, but we are not aging, which is a part of the new technology that's come out in skincare. That's my, I'm just throwing that out there. Why not? What do you guys hope that you can say about the partnership and, and your continued commitment to community? >>Oh, that's a good question. You go first this time. Yeah. >>I think, you know, the, you know, for looking into the future, you need to look into the past. And Amazon has always been driven by working back from our customers. That's like our key tenant, principle number 1 0 1. >>Couple people have said that on this stage this week. Yeah. >>Yeah. And I think our partnership, I hope over the next decade continues to keep that tenant as a centerpiece. And then whatever comes out of that, I think we, we are gonna be, you know, working through that. >>Yeah. I, I would say this, I think you said that, well, the customer innovation is gonna lead us to wherever that is. And it's, it's, it's gonna be in the cloud for sure. I think we can say that in 10 years. But yeah, anything from, from AI to the quant quantum computing that IBM's really pushing behind that, you know, those are, those are gonna be things that hopefully we show up on a, on a partnership with Manu in 10 years, maybe sooner. >>Well, whatever happens next, we'll certainly be covering it here on the cube. That's right. Thank you both for being here. Joel Manu, fantastic interview. Thanks to see you guys. Yeah, good to see you brought the energy. I think you're definitely ranking high on the top interviews. We >>Love that for >>The day. >>Thank >>My pleasure >>Job, guys. Now that you're competitive at all, and thank you all for tuning in to our live coverage here from AWS Reinvent in Las Vegas, Nevada, with Dave Valante. I'm Savannah Peterson. You're watching The Cube, the leading source for high tech coverage.

>>Hey, welcome back everyone. Day three of eight of us Reinvent 2022. I'm John Farmer with Dave Volante, co-host the q Dave. 10 years for us, the leader in high tech coverage is our slogan. Now 10 years of reinvent day. We've been to every single one except with the original, which we would've come to if Amazon actually marketed the event, but they didn't. It's more of a customer event. This is day three. Is the machine learning ai keynote sws up there. A lot of announcements. We're gonna break this down. We got, we got Andy Thra here, vice President, prince Constellation Research. Andy, great to see you've been on the cube before one of our analysts bringing the, bringing the, the analysis, commentary to the keynote. This is your wheelhouse. Ai. What do you think about Swami up there? I mean, he's awesome. We love him. Big fan Oh yeah. Of of the Cuban we're fans of him, but he got 13 announcements. >>A lot. A lot, >>A lot. >>So, well some of them are, first of all, thanks for having me here and I'm glad to have both of you on the same show attacking me. I'm just kidding. But some of the announcement really sort of like a game changer announcements and some of them are like, meh, you know, just to plug in the holes what they have and a lot of golf claps. Yeah. Meeting today. And you could have also noticed that by, when he was making the announcements, you know, the, the, the clapping volume difference, you could say, which is better, right? But some of the announcements are, are really, really good. You know, particularly we talked about, one of that was Microsoft took that out of, you know, having the open AI in there, doing the large language models. And then they were going after that, you know, having the transformer available to them. And Amazon was a little bit weak in the area, so they couldn't, they don't have a large language model. So, you know, they, they are taking a different route saying that, you know what, I'll help you train the large language model by yourself, customized models. So I can provide the necessary instance. I can provide the instant volume, memory, the whole thing. Yeah. So you can train the model by yourself without depending on them kind >>Of thing. So Dave and Andy, I wanna get your thoughts cuz first of all, we've been following Amazon's deep bench on the, on the infrastructure pass. They've been doing a lot of machine learning and ai, a lot of data. It just seems that the sentiment is that there's other competitors doing a good job too. Like Google, Dave. And I've heard folks in the hallway, even here, ex Amazonians saying, Hey, they're train their models on Google than they bring up the SageMaker cuz it's better interface. So you got, Google's making a play for being that data cloud. Microsoft's obviously putting in a, a great kind of package to kind of make it turnkey. How do they really stand versus the competition guys? >>Good question. So they, you know, each have their own uniqueness and the we variation that take it to the field, right? So for example, if you were to look at it, Microsoft is known for as industry or later things that they are been going after, you know, industry verticals and whatnot. So that's one of the things I looked here, you know, they, they had this omic announcement, particularly towards that healthcare genomics space. That's a huge space for hpz related AIML applications. And they have put a lot of things in together in here in the SageMaker and in the, in their models saying that, you know, how do you, how do you use this transmit to do things like that? Like for example, drug discovery, for genomics analysis, for cancer treatment, the whole, right? That's a few volumes of data do. So they're going in that healthcare area. Google has taken a different route. I mean they want to make everything simple. All I have to do is I gotta call an api, give what I need and then get it done. But Amazon wants to go at a much deeper level saying that, you know what? I wanna provide everything you need. You can customize the whole thing for what you need. >>So to me, the big picture here is, and and Swami references, Hey, we are a data company. We started, he talked about books and how that informed them as to, you know, what books to place front and center. Here's the, here's the big picture. In my view, companies need to put data at the core of their business and they haven't, they've generally put humans at the core of their business and data. And now machine learning are at the, at the outside and the periphery. Amazon, Google, Microsoft, Facebook have put data at their core. So the question is how do incumbent companies, and you mentioned some Toyota Capital One, Bristol Myers Squibb, I don't know, are those data companies, you know, we'll see, but the challenge is most companies don't have the resources as you well know, Andy, to actually implement what Google and Facebook and others have. >>So how are they gonna do that? Well, they're gonna buy it, right? So are they gonna build it with tools that's kind of like you said the Amazon approach or are they gonna buy it from Microsoft and Google, I pulled some ETR data to say, okay, who are the top companies that are showing up in terms of spending? Who's spending with whom? AWS number one, Microsoft number two, Google number three, data bricks. Number four, just in terms of, you know, presence. And then it falls down DataRobot, Anaconda data icu, Oracle popped up actually cuz they're embedding a lot of AI into their products and, and of course IBM and then a lot of smaller companies. But do companies generally customers have the resources to do what it takes to implement AI into applications and into workflows? >>So a couple of things on that. One is when it comes to, I mean it's, it's no surprise that the, the top three or the hyperscalers, because they all want to bring their business to them to run the specific workloads on the next biggest workload. As you was saying, his keynote are two things. One is the A AIML workloads and the other one is the, the heavy unstructured workloads that he was talking about. 80%, 90% of the data that's coming off is unstructured. So how do you analyze that? Such as the geospatial data. He was talking about the volumes of data you need to analyze the, the neural deep neural net drug you ought to use, only hyperscale can do it, right? So that's no wonder all of them on top for the data, one of the things they announced, which not many people paid attention, there was a zero eight L that that they talked about. >>What that does is a little bit of a game changing moment in a sense that you don't have to, for example, if you were to train the data, data, if the data is distributed everywhere, if you have to bring them all together to integrate it, to do that, it's a lot of work to doing the dl. So by taking Amazon, Aurora, and then Rich combine them as zero or no ETL and then have Apaches Apaches Spark applications run on top of analytical applications, ML workloads. That's huge. So you don't have to move around the data, use the data where it is, >>I, I think you said it, they're basically filling holes, right? Yeah. They created this, you know, suite of tools, let's call it. You might say it's a mess. It's not a mess because it's, they're really powerful but they're not well integrated and now they're starting to take the seams as I say. >>Well yeah, it's a great point. And I would double down and say, look it, I think that boring is good. You know, we had that phase in Kubernetes hype cycle where it got boring and that was kind of like, boring is good. Boring means we're getting better, we're invisible. That's infrastructure that's in the weeds, that's in between the toes details. It's the stuff that, you know, people we have to get done. So, you know, you look at their 40 new data sources with data Wrangler 50, new app flow connectors, Redshift Auto Cog, this is boring. Good important shit Dave. The governance, you gotta get it and the governance is gonna be key. So, so to me, this may not jump off the page. Adam's keynote also felt a little bit of, we gotta get these gaps done in a good way. So I think that's a very positive sign. >>Now going back to the bigger picture, I think the real question is can there be another independent cloud data cloud? And that's the, to me, what I try to get at my story and you're breaking analysis kind of hit a home run on this, is there's interesting opportunity for an independent data cloud. Meaning something that isn't aws, that isn't, Google isn't one of the big three that could sit in. And so let me give you an example. I had a conversation last night with a bunch of ex Amazonian engineering teams that left the conversation was interesting, Dave. They were like talking, well data bricks and Snowflake are basically batch, okay, not transactional. And you look at Aerospike, I can see their booth here. Transactional data bases are hot right now. Streaming data is different. Confluence different than data bricks. Is data bricks good at hosting? >>No, Amazon's better. So you start to see these kinds of questions come up where, you know, data bricks is great, but maybe not good for this, that and the other thing. So you start to see the formation of swim lanes or visibility into where people might sit in the ecosystem, but what came out was transactional. Yep. And batch the relationship there and streaming real time and versus you know, the transactional data. So you're starting to see these new things emerge. Andy, what do you, what's your take on this? You're following this closely. This seems to be the alpha nerd conversation and it all points to who's gonna have the best data cloud, say data, super clouds, I call it. What's your take? >>Yes, data cloud is important as well. But also the computational that goes on top of it too, right? Because when, when the data is like unstructured data, it's that much of a huge data, it's going to be hard to do that with a low model, you know, compute power. But going back to your data point, the training of the AIML models required the batch data, right? That's when you need all the, the historical data to train your models. And then after that, when you do inference of it, that's where you need the streaming real time data that's available to you too. You can make an inference. One of the things, what, what they also announced, which is somewhat interesting, is you saw that they have like 700 different instances geared towards every single workload. And there are some of them very specifically run on the Amazon's new chip. The, the inference in two and theran tr one chips that basically not only has a specific instances but also is run on a high powered chip. And then if you have that data to support that, both the training as well as towards the inference, the efficiency, again, those numbers have to be proven. They claim that it could be anywhere between 40 to 60% faster. >>Well, so a couple things. You're definitely right. I mean Snowflake started out as a data warehouse that was simpler and it's not architected, you know, in and it's first wave to do real time inference, which is not now how, how could they, the other second point is snowflake's two or three years ahead when it comes to governance, data sharing. I mean, Amazon's doing what always does. It's copying, you know, it's customer driven. Cuz they probably walk into an account and they say, Hey look, what's Snowflake's doing for us? This stuff's kicking ass. And they go, oh, that's a good idea, let's do that too. You saw that with separating compute from storage, which is their tiering. You saw it today with extending data, sharing Redshift, data sharing. So how does Snowflake and data bricks approach this? They deal with ecosystem. They bring in ecosystem partners, they bring in open source tooling and that's how they compete. I think there's unquestionably an opportunity for a data cloud. >>Yeah, I think, I think the super cloud conversation and then, you know, sky Cloud with Berkeley Paper and other folks talking about this kind of pre, multi-cloud era. I mean that's what I would call us right now. We are, we're kind of in the pre era of multi-cloud, which by the way is not even yet defined. I think people use that term, Dave, to say, you know, some sort of magical thing that's happening. Yeah. People have multiple clouds. They got, they, they end up by default, not by design as Dell likes to say. Right? And they gotta deal with it. So it's more of they're inheriting multiple cloud environments. It's not necessarily what they want in the situation. So to me that is a big, big issue. >>Yeah, I mean, again, going back to your snowflake and data breaks announcements, they're a data company. So they, that's how they made their mark in the market saying that, you know, I do all those things, therefore you have, I had to have your data because it's a seamless data. And, and Amazon is catching up with that with a lot of that announcements they made, how far it's gonna get traction, you know, to change when I to say, >>Yeah, I mean to me, to me there's no doubt about Dave. I think, I think what Swamee is doing, if Amazon can get corner the market on out of the box ML and AI capabilities so that people can make it easier, that's gonna be the end of the day tell sign can they fill in the gaps. Again, boring is good competition. I don't know mean, mean I'm not following the competition. Andy, this is a real question mark for me. I don't know where they stand. Are they more comprehensive? Are they more deeper? Are they have deeper services? I mean, obviously shows to all the, the different, you know, capabilities. Where, where, where does Amazon stand? What's the process? >>So what, particularly when it comes to the models. So they're going at, at a different angle that, you know, I will help you create the models we talked about the zero and the whole data. We'll get the data sources in, we'll create the model. We'll move the, the whole model. We are talking about the ML ops teams here, right? And they have the whole functionality that, that they built ind over the year. So essentially they want to become the platform that I, when you come in, I'm the only platform you would use from the model training to deployment to inference, to model versioning to management, the old s and that's angle they're trying to take. So it's, it's a one source platform. >>What about this idea of technical debt? Adrian Carro was on yesterday. John, I know you talked to him as well. He said, look, Amazon's Legos, you wanna buy a toy for Christmas, you can go out and buy a toy or do you wanna build a, to, if you buy a toy in a couple years, you could break and what are you gonna do? You're gonna throw it out. But if you, if you, if part of your Lego needs to be extended, you extend it. So, you know, George Gilbert was saying, well, there's a lot of technical debt. Adrian was countering that. Does Amazon have technical debt or is that Lego blocks analogy the right one? >>Well, I talked to him about the debt and one of the things we talked about was what do you optimize for E two APIs or Kubernetes APIs? It depends on what team you're on. If you're on the runtime gene, you're gonna optimize for Kubernetes, but E two is the resources you want to use. So I think the idea of the 15 years of technical debt, I, I don't believe that. I think the APIs are still hardened. The issue that he brings up that I think is relevant is it's an end situation, not an or. You can have the bag of Legos, which is the primitives and build a durable application platform, monitor it, customize it, work with it, build it. It's harder, but the outcome is durability and sustainability. Building a toy, having a toy with those Legos glued together for you, you can get the play with, but it'll break over time. Then you gotta replace it. So there's gonna be a toy business and there's gonna be a Legos business. Make your own. >>So who, who are the toys in ai? >>Well, out of >>The box and who's outta Legos? >>The, so you asking about what what toys Amazon building >>Or, yeah, I mean Amazon clearly is Lego blocks. >>If people gonna have out the box, >>What about Google? What about Microsoft? Are they basically more, more building toys, more solutions? >>So Google is more of, you know, building solutions angle like, you know, I give you an API kind of thing. But, but if it comes to vertical industry solutions, Microsoft is, is is ahead, right? Because they have, they have had years of indu industry experience. I mean there are other smaller cloud are trying to do that too. IBM being an example, but you know, the, now they are starting to go after the specific industry use cases. They think that through, for example, you know the medical one we talked about, right? So they want to build the, the health lake, security health lake that they're trying to build, which will HIPPA and it'll provide all the, the European regulations, the whole line yard, and it'll help you, you know, personalize things as you need as well. For example, you know, if you go for a certain treatment, it could analyze you based on your genome profile saying that, you know, the treatment for this particular person has to be individualized this way, but doing that requires a anomalous power, right? So if you do applications like that, you could bring in a lot of the, whether healthcare, finance or what have you, and then easy for them to use. >>What's the biggest mistake customers make when it comes to machine intelligence, ai, machine learning, >>So many things, right? I could start out with even the, the model. Basically when you build a model, you, you should be able to figure out how long that model is effective. Because as good as creating a model and, and going to the business and doing things the right way, there are people that they leave the model much longer than it's needed. It's hurting your business more than it is, you know, it could be things like that. Or you are, you are not building a responsibly or later things. You are, you are having a bias and you model and are so many issues. I, I don't know if I can pinpoint one, but there are many, many issues. Responsible ai, ethical ai. All >>Right, well, we'll leave it there. You're watching the cube, the leader in high tech coverage here at J three at reinvent. I'm Jeff, Dave Ante. Andy joining us here for the critical analysis and breaking down the commentary. We'll be right back with more coverage after this short break.

>>Hello everyone and welcome back to Las Vegas. I've got my jazz hands because I am very jazzed to be here at AWS Reinvent Live from the show floor all week. My name is Savannah Peterson, joined with the infamous John Farer. John, how you feeling >>After feeling great? Love? What's going on here? The vibe is a cloud, cloud native. Lot of security conversation, data, stuff we love Cloud Native, >>M I >>A L, I mean big news. Security, security, data lake. I mean, who would've thought Amazon have a security data lake? You know, e k s, I mean >>You might have with that tweet you had out >>Inside outside the containers. Reminds me, it feels like coan here. >>It honestly, and there's a lot of overlap and it's interesting that you mention CubeCon because we talked to the next company when we were in Detroit just a couple weeks ago. Teleport E is the CEO and founder F Welcome to the show. How you doing? >>I'm doing well. Thank you for having me today. >>We feel very lucky to have you. We hosted Drew who works on the product marketing side of Teleport. Yeah, we got to talk caddies and golf last time on the show. We'll talk about some of your hobbies a little bit later, but just in case someone's tuning in, unfamiliar with Teleport, you're all about identity. Give us a little bit of a pitch, >>Little bit of our pitch. Teleport is the first identity native infrastructure access platform. It's used by engineers and it's used by machines. So notice that I used very specific choice of words first identity native, what does it mean? Identity native? It consists of three things and we're writing a book about those, but I'll let you know. Stay >>Tuned on that front. >>Exactly, yes, but I can talk about 'em today. So the first component of identity, native access is moving away from secrets towards true identity. The secrets, I mean things like passwords, private keys, browser cookies, session tokens, API keys, all of these things is secrets and they make you vulnerable. The point is, as you scale, it's absolutely impossible to protect all of the seekers because they keep growing and multiplying. So the probability of you getting hacked over time is high. So you need to get rid of secrets altogether that that's the first thing that we do. We use something called True Identity. It's a combination of your biometrics as well as identity of your machines. That's tpms, HSMs, Ubikes and so on, so forth. >>Go >>Ahead. The second component is Zero Trust. Like Teleport is built to not trust the network. So every resource inside of your data center automatically gets configured as if there is no perimeter it, it's as safe as it was on the public network. So that's the second thing. Don't trust the network. And the third one is that we keep access policy in one place. So Kubernetes clusters, databases on stage, rdp, all of these protocols, the access policy will be in one place. That's identity. Okay, >>So I'm, I'm a hacker. Pretend I'm a hacker. >>Easy. That sounds, >>That sounds really good to me. Yeah, I'm supposed to tell 'em you're hacker. Okay. I can go to one place and hack that. >>I get this question a lot. The thing is, you want centralization when it comes to security, think about your house being your AWS account. Okay? Everything inside your furniture, your valuable, like you'll watch collection, like that's your data, that's your servers, paper clusters, so and so forth. Right Now I have a choice and your house is in a really bad neighborhood. Okay, that's the bad internet. Do you wanna have 20 different doors or do you want to have one? But like amazing one, extremely secure, very modern. So it's very easy for you to actually maintain it and enforce policy. So the answer is, oh, you probably need to have >>One. And so you're designing security identity from a perspective of what's best for the security posture. Exactly. Sounds like, okay, so now that's not against the conventional wisdom of the perimeter's dead, the cloud's everywhere. So in a way kind of brings perimeter concepts into the posture because you know, the old model of the firewall, the moat >>It Yeah. Just doesn't scale. >>It doesn't scale. You guys bring the different solution. How do you fit into the new perimeters dead cloud paradigm? >>So the, the way it works that if you are, if you are using Teleport to access your infrastructure, let's just use for example, like a server access perspective. Like that machine that you're accessing doesn't listen on a network if it runs in Teleport. So instead Teleport creates this trusted outbound tunnels to the proxy. So essentially you are managing devices using out going connection. It's kind of like how your phone runs. Yeah. Like your phone is actually ultimate, it's like a teleport like, like I It's >>Like teleporting into your environment. >>Yeah, well play >>Journal. But >>Think about actually like one example of an amazing company that's true Zero trust that we're all familiar with would be Apple. Because every time you get a new iOS on your phone, the how is it different from Apple running massive software deployment into enormous cloud with billions of servers sprinkle all over the world without perimeter. How is it possible That's exactly the kind of technology that Teleports >>Gives you. I'm glad you clarified. I really wanted to get that out on the table. Cuz Savannah, this is, this is the paradigm shift around what an environment is Exactly. Did the Apple example, so, okay, tell 'em about customer traction. Are people like getting it right away? Are their teams ready? Are they go, oh my god this is >>Great. Pretty much you see we kinda lucky like in a, in a, like in this business and I'm walking around looking at all these successful startups, like every single one of them has a story about launching the right thing at just the right like moment. Like in technology, like the window to launch something is extremely short. Like months. I'm literally talking months. So we built Teleport started to work on it in like 2015. It was internal project, I believe it or not, also a famous example. It's really popular like internal project, put it on GitHub and it sat there relatively unnoticed for a while and then it just like took off around 2000 >>Because people start to feel the pain. They needed it. Exactly, >>Exactly. >>Yeah. The timing. Well and And what a great way to figure out when the timing is right? When you do something like that, put it on GitHub. Yeah. >>People >>Tell you what's up >>Yeah's Like a basketball player who can just like be suspended in the air over the hoop for like half the game and then finally his score and wins >>The game. Or video gamer who's lagged, everyone else is lagging and they got the latency thing. Exactly. Thing air. Okay. Talk about the engineering side. Cause I, I like this at co con, you mentioned it at the opening of this segment that you guys are for engineers, not it >>Business people. That's right. >>Explain that. Interesting. This is super important. Explain why and why that's resonating. >>So there is this ongoing shift on more and more responsibilities going to engineers. Like remember back in the day before we even had clouds, we had people actually racking servers, sticking cables into them, cutting their fingers, like trying to get 'em in. So those were not engineers, they were different teams. Yeah. But then you had system administrators who would maintain these machines for you. Now all of these things are done with code. And when these things are done with code and with APIs, that shifts to engineers. That is what Teleport does with policy. So if you want to have a set of rules that govern who or what and when under what circumstances can access what data like on Kubernetes, on databases, on, on servers wouldn't be nice to use code for it. So then you could use like a version control and you can keep track of changes. That's what teleport enables. Traditionally it preferred more kind of clicky graphical things like clicking buttons. And so it's just a different world, different way of doing it. So essentially if you want security as code, that's what Teleport provides and naturally this language resonates with this persona. >>Love that. Security is coding. It's >>A great term. Yeah. Love it. I wanna, I wanna, >>Okay. We coined it, someone else uses it on the show. >>We borrow it >>To use credit. When did you, when did you coin that? Just now? >>No, >>I think I coined it before >>You wanted it to be a scoop. I love that. >>I wish I had this story when I, I was like a, like a poor little 14 year old kid was dreaming about security code but >>Well Dave Ante will testify that I coined data as code before anyone else but it got 10 years ago. You >>Didn't hear it this morning. Jimmy actually brought it back up. Aws, you're about startups and he's >>Whoever came up with lisp programming language that had this concept that data and code are exact same thing, >>Right? We could debate nerd lexicon all day on the cube. In fact, that could even be a segment first >>Of we do. First of all, the fact that Lisp came up on the cube is actually a milestone because Lisp is a very popular language for object-oriented >>Grandfather of everything. >>Yes, yes, grandfather. Good, good. Good catch there. Yeah, well done. >>All right. I'm gonna bring us back. I wanna ask you a question >>Talking about nerd this LIS is really >>No, I think it's great. You know how nerdy we can get here though. I mean we can just hang out in the weeds the whole time. All right. I wanna ask you a question that I asked Drew when we were in Detroit just because I think for some folks and especially the audience, they may not have as distinctive a definition as y'all do. How do you define identity? >>Oh, that's a great question. So identity as a term was, it was always used for security purposes. But most people probably use identity in the context of single signon sso. Meaning that if your company uses identity for access, which instead of having each application have an account for you, like a data entry with your first name, last name emails and your role. Yeah. You instead have a central database, let's say Okta or something like that. Yep. And then you, you use that to access everything that's kind of identity based access because there is a single source of identity. What we say is that we, that needs to be extended because it it no longer enough because that identity can be stolen. So if someone gets access to your Okta account using your credentials, then they can become you. So in order for identity to be attached to you and become your true identity, you have to rely on physical world objects. That's biometrics your facial fingerprint, like your facial print, your fingerprints as well as biometric of your machine. Like your laptops have PPM modules on it. They're absolutely unique. They cannot be cloned stolen. So that is your identity as well. So if you combine whatever is in Octa with the biker chip in this laptop and with your finger that collectively is your true identity, which cannot be stolen. So it's can't be hacked. >>And someone can take my finger like they did in the movies. >>So they would have to do that. And they would also have to They'd >>Steal your match. Exactly, exactly. Yeah. And they'd have to have your eyes >>And they have to, and you have >>Whatever the figure that far, they meant what >>They want. So that is what Drew identity is from telecom and >>Biometric. I mean it's, we're so there right now it's, it's really not an issue. It's only getting faster and better to >>Market. There is one important thing I said earlier that I want to go back to that I said that teleport is not just for engineers, it's also for machines. Cuz machines they also need the identity. So when we talk about access silos and that there are many different doors into your apartment, there are many different ways to access your data. So on the infrastructure side, machines are doing more and more. So we are offloading more and more tasks to them. That's a really good, what do machines use to access each other? Biome? They use API keys, they use private keys, they use basically passwords. Yeah. Like they're secrets and we already know that that's bad, right? Yeah. So how do you extend biometrics to machines? So this is why AWS offers cloud HSM service. HSM is secure hardware security module. That's a unique private key for the machine that is not accessible by anyone. And Teleport uses that to give identities to machines. Does do >>Customers have to enable that themselves or they have that part of a Amazon, the that >>Special. So it's available on aws. It's available actually in good old, like old bare metal machines that have HSMs on them on the motherboard. And it's optional by the way Teleport can work even if you don't have that capability. But the point is that we tried, you >>Have a biometric equivalent for the machines with >>Take advantage of it. Yeah. It's a hardware thing that you have to have and we all have it. Amazon sells it. AWS sells it to us. Yeah. And Teleport allows you to leverage that to enhance security of the infrastructure. >>So that classic hardware software play on that we're always talking about here on the cube. It's all, it's all important. I think this is really fascinating though. So I had an on the way to the show, I just enrolled in Clear and I had used a different email. I enrolled for the second time and my eyes wouldn't let me have two accounts. And this was the first time I had tried to sort of hack my own digital identity. And the girl, I think she was humoring me that was, was kindly helping me, the clear employee. But I think she could tell I was trying to mess with it and I wanted to see what would happen. I wanted to see if I could have two different accounts linked to my biometric data and I couldn't it, it picked it up right away. >>That's your true >>Identity. Yeah, my true identity. So, and forgive me cuz this is kind of just a personal question. It might be a little bit finger finger to the wind, but how, just how much more secure if you could, if you could give us a, a rating or a percentage or a a number. How much more secure is leveraging biometric data for identity than the secrets we've been using historically? >>Look, I could, I played this game with you and I can answer like infinitely more secure, right? Like but you know how security works that it all depends on implementation. So let's say you, you can deploy teleport, you can put us on your infrastructure, but if you're running, let's say like a compromised old copy of WordPress that has vulnerability, you're gonna get a hack through that angle. But >>Happens happens to my personal website all the time. You just touched Yeah, >>But the fact is that we, I I don't see how your credentials will be stolen in this system simply because your TPM on your laptop and your fingerprint, they cannot be downloaded. They like a lot of people actually ask us a slightly different question. It's almost the opposite of it. Like how can I trust you with my biometrics? When I use my fingerprint? That's my information. I don't want the company I work at to get my fingerprint people. I think it's a legit question to ask. >>Yeah. And it's >>What you, the answer to that question is your fingerprint doesn't really leave your laptop teleport doesn't see your fingerprint. What happens is when your fingerprint gets validated, it's it's your laptop is matching what's on the tpm. Basically Apple does it and then Apple simply tells teleport, yep that's F or whoever. And that's what we are really using. So when you are using this form authentication, you're not sharing your biometric with the company you work at. >>It's a machine to human confirmation first and >>Then it's it. It's basically you and the laptop agreeing that my fingerprint matches your TPM and if your laptop agrees, it's basically hardware does validation. So, and teleport simply gets that signal. >>So Ed, my final question for you is here at the show coupon, great conversations there for your company. What's your conversations here like at reinvent? Are you meeting with Amazon people, customers? What are some of the conversations? Because this is a much broader, I mean it's still technical. Yep. But you know, a lot of business kind of discussions, architectural refactoring of organizations. What are some of the things that you're talking about here with Telepo? What are, >>So I will mention maybe two trends I observed. The first one is not even security related. It's basically how like as a cloud becomes more mature, people now actually at different organizations develop their own internal ways of doing cloud properly. And they're not the same. Because when cloud was earlier, like there were this like best practices that everyone was trying to follow and there was like, there was just a maybe lack of expertise in the world and and now finding that different organizations just do things completely different. Like one, like for example, yeah, like some companies love having handful, ideally just one enormous Kubernetes cluster with a bunch of applications on it. And the other companies, they create Kubernetes clusters for different workloads and it's just like all over the map and both of them are believed that they're doing it properly. >>Great example of bringing in, that's Kubernetes with the complexity. And >>That's kind of one trend I'm noticing. And the second one is security related. Is that everyone is struggling with the access silos is that ideally every organization is dreaming about a day, but they have like one place which is which with great user experience that simply spells out this is what policy is to access this particular data. And it gets a automatically enforced by every single cloud provider, but every single application, but every single protocol, but every single resource. But we don't have that unfortunately Teleport is slowly becoming that, of course. Excuse me for plugging >>TelePro. No, no worries. >>But it is this ongoing theme that everyone is can't wait to have that single source of truth for accessing their data. >>The second person to say single source of truth on this stage in the last 24 >>Hours or nerds will love that. I >>Know I feel well, but it's all, it all comes back to that. I keep using this tab analogy, but we all want everything in one place. We don't wanna, we don't wanna have to be going all over the place and to look for >>Both. Because if it's and everything else places, it means that different teams are responsible for it. Yeah. So it becomes this kind of internal information silo as well. So you not even, >>And the risks and liabilities there, depending on who's overseeing everything. That's awesome. Right? So we have a new challenge on the cube specific to this show thing of this as your 30 minute or 30 minute that would be bold. 32nd sizzle reel, Instagram highlight. What is your hot take? Most important thing, biggest theme of the show this year. >>This year. Okay, so here's my thing. Like I want cloud to become something I want it to be. And every time I come here and I'm like, are we closer? Are we closer? So here's what I want. I want all cloud providers collectively to kind of merge. So then when we use them, it feels like we are programming one giant machine. Kind of like in the matrix, right? The movie. So like I want cloud to feel like a computer, like to have this almost intimate experience you have with your laptop. Like you can like, like do this and the laptop like performs the instructions. So, and it feels to me that we are getting closer. So like walking around here and seeing how everything works now, like on the single signon on from a security perspective, there is so that consolidation is finally happening. So it's >>The software mainframe we used to call it back in 2010. >>Yeah, yeah. Just kind of planetary scale thing. Yes. It's not the Zuckerberg that who's building metaverse, it's people here at reinvent. >>Unlimited resource for developers. Just call in. Yeah, yeah. Give me some resource, spin me up some, some compute. >>I would like alter that slightly. I would just basically go and do this and you shouldn't even worry about how it gets done. Just put instructions into this planetary mainframe and mainframe will go and figure this out. Okay. >>We gotta take blue or blue or red pill. I >>Know. I was just gonna say y'all, we are this, this, this, this segment is lit. >>We got made tricks. We got brilliant. We didn't get super cloud in here but we, we can weave that in. We got >>List. We just said it. So >>We got lisp. Oh great con, great conversation. Cloud native. >>Outstanding conversation. And thank you so much for being here. We love having teleport on the show. Obviously we hope to see you back again soon and and Drew as well. And thank all of you for tuning in this afternoon. Live from Las Vegas, Nevada, where we are hanging out at AWS Reinvent with John Furrier. I'm Savannah Peterson. This is the Cube. We are the source for high tech coverage.

>>We are back in the final stretch at Supercomputing 22 here in Dallas. I'm your host Paul Gillum with my co-host Dave Nicholson, and we've been talking to so many smart people this week. It just, it makes, boggles my mind are next guest. J Poso is the HPC and AI technology strategist at Dell. Jay also has a PhD in astronomy from the University of Texas. And I'm guessing you were up watching the Artemis launch the other night? >>I, I wasn't. I really should have been, but, but I wasn't, I was in full super computing conference mode. So that means discussions at, you know, various venues with people into the wee hours. >>How did you make the transition from a PhD in astronomy to an HPC expert? >>It was actually really straightforward. I did theoretical astrophysics and I was modeling what white dwarfs look like when they create matter and then explode as type one A super Novi, which is a class of stars that blow up. And it's a very important class because they blow up almost exactly the same way. So if you know how bright they are physically, not just how bright they appear in the sky, but if you can determine from first principles how bright they're, then you have a standard ruler for the universe when they go off in a galaxy, you know how far the galaxy is about how faint it is. So to model these though, you had to understand equations of physics, including electron degeneracy pressure, as well as normal fluid dynamics kinds of of things. And so you were solving for an explosive burning front, ripping through something. And that required a supercomputer to have anywhere close to the fat fidelity to get a reasonable answer and, and hopefully some understanding. >>So I've always said electrons are degenerate. I've always said it and I, and I mentioned to Paul earlier, I said, finally we're gonna get a guest to consort through this whole dark energy dark matter thing for us. We'll do that after, after, after the segment. >>That's a whole different, >>So, well I guess super computing being a natural tool that you would use. What is, what do you do in your role as a strategist? >>So I'm in the product management team. I spend a lot of time talking to customers about what they want to do next. HPC customers are always trying to be maximally productive of what they've got, but always wanting to know what's coming next. Because if you think about it, we can't simulate the entire human body cell for cell on any supercomputer day. We can simulate parts of it, cell for cell or the whole body with macroscopic physics, but not at the, you know, atomic level, the entire organism. So we're always trying to build more powerful computers to solve larger problems with more fidelity and less approximations in it. And so I help people try to understand which technologies for their next system might give them the best advance in capabilities for their simulation work, their data analytics work, their AI work, et cetera. Another part of it is talking to our great technology partner ecosystem and learning about which technologies they have. Cause it feeds the first thing, right? So understanding what's coming, and Dell has a, we're very proud of our large partner ecosystem. We embrace many different partners in that with different capabilities. So understanding those helps understand what your future systems might be. That those are two of the major roles in it. Strategic customers and strategic technologies. >>So you've had four days to wander the, this massive floor here and lots of startups, lots of established companies doing interesting things. What have you seen this week that really excites you? >>So I'm gonna tell you a dirty little secret here. If you are working for someone who makes super computers, you don't get as much time to wander the floor as you would think because you get lots of meetings with people who really want to understand in an NDA way, not just in the public way that's on the floor, but what's, what are you not telling us on the floor? What's coming next? And so I've been in a large number of customer meetings as well as being on the floor. And while I can't obviously share the everything, that's a non-disclosure topic in those, some things that we're hearing a lot about, people are really concerned with power because they see the TDP on the roadmaps for all the silicon providers going way up. And so people with power comes heat as waste. And so that means cooling. >>So power and cooling has been a big topic here. Obviously accelerators are, are increasing in importance in hpc not just for AI calculations, but now also for simulation calculations. And we are very proud of the three new accelerator platforms we launched here at the show that are coming out in a quarter or so. Those are two of the big topics we've seen. You know, there's, as you walk the floor here, you see lots of interesting storage vendors. HPC community's been do doing storage the same way for roughly 20 years. But now we see a lot of interesting players in that space. We have some great things in storage now and some great things that, you know, are coming in a year or two as well. So it's, it's interesting to see that diversity of that space. And then there's always the fun, exciting topics like quantum computing. We unveiled our first hybrid classical quantum computing system here with I on Q and I can't say what the future holds in this, in this format, but I can say we believe strongly in the future of quantum computing and that this, that future will be integrated with the kind of classical computing infrastructure that we make and that will help make quantum computing more powerful downstream. >>Well, let's go down that rabbit hole because, oh boy, boy, quantum computing has been talked about for a long time. There was a lot of excitement about it four or five years ago, some of the major vendors were announcing quantum computers in the cloud. Excitement has kind of died down. We don't see a lot of activity around, no, not a lot of talk around commercial quantum computers, yet you're deep into this. How close are we to have having a true quantum computer or is it a, is it a hybrid? More >>Likely? So there are probably more than 20 and I think close to 40 companies trying different approaches to make quantum computers. So, you know, Microsoft's pursuing a topol topological approach, do a photonics based approach. I, on Q and i on trap approach. These are all different ways of trying to leverage the quantum properties of nature. We know the properties exist, we use 'em in other technologies. We know the physics, but trying the engineering is very difficult. It's very difficult. I mean, just like it was difficult at one point to split the atom. It's very difficult to build technologies that leverage quantum properties of nature in a consistent and reliable and durable way, right? So I, you know, I wouldn't wanna make a prediction, but I will tell you I'm an optimist. I believe that when a tremendous capability with, with tremendous monetary gain potential lines up with another incentive, national security engineering seems to evolve faster when those things line up, when there's plenty of investment and plenty of incentive things happen. >>So I think a lot of my, my friends in the office of the CTO at Dell Technologies, when they're really leading this effort for us, you know, they would say a few to several years probably I'm an optimist, so I believe that, you know, I, I believe that we will sell some of the solution we announced here in the next year for people that are trying to get their feet wet with quantum. And I believe we'll be selling multiple quantum hybrid classical Dell quantum computing systems multiple a year in a year or two. And then of course you hope it goes to tens and hundreds of, you know, by the end of the decade >>When people talk about, I'm talking about people writ large, super leaders in supercomputing, I would say Dell's name doesn't come up in conversations I have. What would you like them to know that they don't know? >>You know, I, I hope that's not true, but I, I, I guess I understand it. We are so good at making the products from which people make clusters that we're number one in servers, we're number one in enterprise storage. We're number one in so many areas of enterprise technology that I, I think in some ways being number one in those things detracts a little bit from a subset of the market that is a solution subset as opposed to a product subset. But, you know, depending on which analyst you talk to and how they count, we're number one or number two in the world in supercomputing revenue. We don't always do the biggest splashy systems. We do the, the frontier system at t, the HPC five system at ENI in Europe. That's the largest academic supercomputer in the world and the largest industrial super >>That's based the world on Dell. Dell >>On Dell hardware. Yep. But we, I think our vision is really that we want to help more people use HPC to solve more problems than any vendor in the world. And those problems are various scales. So we are really concerned about the more we're democratizing HPC to make it easier for more people to get in at any scale that their budget and workloads require, we're optimizing it to make sure that it's not just some parts they're getting, that they are validated to work together with maximum scalability and performance. And we have a great HPC and AI innovation lab that does this engineering work. Cuz you know, one of the myths is, oh, I can just go buy a bunch of servers from company X and a network from company Y and a storage system from company Z and then it'll all work as an equivalent cluster. Right? Not true. It'll probably work, but it won't be the highest performance, highest scalability, highest reliability. So we spend a lot of time optimizing and then we are doing things to try to advance the state of HPC as well. What our future systems look like in the second half of this decade might be very different than what they look like right. Now. >>You mentioned a great example of a limitation that we're running up against right now. You mentioned an entire human body as a, as a, as an organism >>Or any large system that you try to model at the atomic level, but it's a huge macro system, >>Right? So will we be able to reach milestones where we can get our arms entirely around something like an entire human organism with simply quantitative advances as opposed to qualitative advances? Right now, as an example, let's just, let's go down to the basics from a Dell perspective. You're in a season where microprocessor vendors are coming out with next gen stuff and those next NextGen microprocessors, GPUs and CPUs are gonna be plugged into NextGen motherboards, PCI e gen five, gen six coming faster memory, bigger memory, faster networking, whether it's NS or InfiniBand storage controllers, all bigger, better, faster, stronger. And I suspect that systems like Frontera, I don't know, but I suspect that a lot of the systems that are out there are not on necessarily what we would think of as current generation technology, but maybe they're n minus one as a practical matter. So, >>But yeah, I mean they have a lifetime, so Exactly. >>The >>Lifetime is longer than the evolution. >>That's the normal technologies. Yeah. So, so what some people miss is this is, this is the reality that when, when we move forward with the latest things that are being talked about here, it's often a two generation move for an individual, for an individual organization. Yep. >>So now some organizations will have multiple systems and they, the system's leapfrog and technology generations, even if one is their real large system, their next one might be newer technology, but smaller, the next one might be a larger one with newer technology and such. Yeah. So the, the biggest super computing sites are, are often running more than one HPC system that have been specifically designed with the latest technologies and, and designed and configured for maybe a different subset of their >>Workloads. Yeah. So, so the, the, to go back to kinda the, the core question, in your opinion, do we need that qualitative leap to something like quantum computing in order to get to the point, or is it simply a question of scale and power at the, at the, at the individual node level to get us to the point where we can in fact gain insight from a digital model of an entire human body, not just looking at a, not, not just looking at an at, at an organ. And to your point, it's not just about human body, any system that we would characterize as being chaotic today, so a weather system, whatever. Do you, are there any milestones that you're thinking of where you're like, wow, you know, I have, I, I understand everything that's going on, and I think we're, we're a year away. We're a, we're, we're a, we're a compute generation away from being able to gain insight out of systems that right now we can't simply because of scale. It's a very, very long question that I just asked you, but I think I, but hopefully, hopefully you're tracking it. What, what are your, what are your thoughts? What are these, what are these inflection points that we, that you've, in your mind? >>So I, I'll I'll start simple. Remember when we used to buy laptops and we worried about what gigahertz the clock speed was Exactly. Everybody knew the gigahertz of it, right? There's some tasks at which we're so good at making the hardware that now the primary issues are how great is the screen? How light is it, what's the battery life like, et cetera. Because for the set of applications on there, we we have enough compute power. We don't, you don't really need your laptop. Most people don't need their laptop to have twice as powerful a processor that actually rather up twice the battery life on it or whatnot, right? We make great laptops. We, we design for all of those, configure those parameters now. And what, you know, we, we see some customers want more of x, somewhat more of y but the, the general point is that the amazing progress in, in microprocessors, it's sufficient for most of the workloads at that level. Now let's go to HPC level or scientific and technical level. And when it needs hpc, if you're trying to model the orbit of the moon around the earth, you don't really need a super computer for that. You can get a highly accurate model on a, on a workstation, on a server, no problem. It won't even really make it break a sweat. >>I had to do it with a slide rule >>That, >>That >>Might make you break a sweat. Yeah. But to do it with a, you know, a single body orbiting with another body, I say orbiting around, but we both know it's really, they're, they're both ordering the center of mass. It's just that if one is much larger, it seems like one's going entirely around the other. So that's, that's not a super computing problem. What about the stars in a galaxy trying to understand how galaxies form spiral arms and how they spur star formation. Right now you're talking a hundred billion stars plus a massive amount of inter stellar medium in there. So can you solve that on that server? Absolutely not. Not even close. Can you solve it on the largest super computer in the world today? Yes and no. You can solve it with approximations on the largest super computer in the world today. But there's a lot of approximations that go into even that. >>The good news is the simulations produce things that we see through our great telescopes. So we know the approximations are sufficient to get good fidelity, but until you really are doing direct numerical simulation of every particle, right? Right. Which is impossible to do. You need a computer as big as the universe to do that. But the approximations and the science in the science as well as the known parts of the science are good enough to give fidelity. So, and answer your question, there's tremendous number of problem scales. There are problems in every field of science and study that exceed the der direct numerical simulation capabilities of systems today. And so we always want more computing power. It's not macho flops, it's real, we need it, we need exo flops and we will need zeta flops beyond that and yada flops beyond that. But an increasing number of problems will be solved as we keep working to solve problems that are farther out there. So in terms of qualitative steps, I do think technologies like quantum computing, to be clear as part of a hybrid classical quantum system, because they're really just accelerators for certain kinds of algorithms, not for general purpose algorithms. I do think advances like that are gonna be necessary to solve some of the very hardest problem. It's easy to actually formulate an optimization problem that is absolutely intractable by the larger systems in the world today, but quantum systems happen to be in theory when they're big and stable enough, great at that kind of problem. >>I, that should be understood. Quantum is not a cure all for absolutely. For the, for the shortage of computing power. It's very good for certain, certain >>Problems. And as you said at this super computing, we see some quantum, but it's a little bit quieter than I probably expected. I think we're in a period now of everybody saying, okay, there's been a lot of buzz. We know it's gonna be real, but let's calm down a little bit and figure out what the right solutions are. And I'm very proud that we offered one of those >>At the show. We, we have barely scratched the surface of what we could talk about as we get into intergalactic space, but unfortunately we only have so many minutes and, and we're out of them. Oh, >>I'm >>J Poso, HPC and AI technology strategist at Dell. Thanks for a fascinating conversation. >>Thanks for having me. Happy to do it anytime. >>We'll be back with our last interview of Supercomputing 22 in Dallas. This is Paul Gillen with Dave Nicholson. Stay with us.