>>Welcome back to The Cube's coverage of Supercomputing Conference 2022, otherwise known as SC 22 here in Dallas, Texas. This is day three of our coverage, the final day of coverage here on the exhibition floor. I'm Dave Nicholson, and I'm here with my co-host, tech journalist extraordinaire, Paul Gillum. How's it going, >>Paul? Hi, Dave. It's going good. >>And we have a wonderful guest with us this morning, Dr. Panda from the Ohio State University. Welcome Dr. Panda to the Cube. >>Thanks a lot. Thanks a lot to >>Paul. I know you're, you're chopping at >>The bit, you have incredible credentials, over 500 papers published. The, the impact that you've had on HPC is truly remarkable. But I wanted to talk to you specifically about a product project you've been working on for over 20 years now called mva, high Performance Computing platform that's used by more than 32 organ, 3,200 organizations across 90 countries. You've shepherded this from, its, its infancy. What is the vision for what MVA will be and and how is it a proof of concept that others can learn from? >>Yeah, Paul, that's a great question to start with. I mean, I, I started with this conference in 2001. That was the first time I came. It's very coincidental. If you remember the Finman Networking Technology, it was introduced in October of 2000. Okay. So in my group, we were working on NPI for Marinette Quadrics. Those are the old technology, if you can recollect when Finman was there, we were the very first one in the world to really jump in. Nobody knew how to use Infin van in an HPC system. So that's how the Happy Project was born. And in fact, in super computing 2002 on this exhibition floor in Baltimore, we had the first demonstration, the open source happy, actually is running on an eight node infinite van clusters, eight no zeros. And that was a big challenge. But now over the years, I means we have continuously worked with all infinite van vendors, MPI Forum. >>We are a member of the MPI Forum and also all other network interconnect. So we have steadily evolved this project over the last 21 years. I'm very proud of my team members working nonstop, continuously bringing not only performance, but scalability. If you see now INFIN event are being deployed in 8,000, 10,000 node clusters, and many of these clusters actually use our software, stack them rapid. So, so we have done a lot of, like our focuses, like we first do research because we are in academia. We come up with good designs, we publish, and in six to nine months, we actually bring it to the open source version and people can just download and then use it. And that's how currently it's been used by more than 3000 orange in 90 countries. And, but the interesting thing is happening, your second part of the question. Now, as you know, the field is moving into not just hvc, but ai, big data, and we have those support. This is where like we look at the vision for the next 20 years, we want to design this MPI library so that not only HPC but also all other workloads can take advantage of it. >>Oh, we have seen libraries that become a critical develop platform supporting ai, TensorFlow, and, and the pie torch and, and the emergence of, of, of some sort of default languages that are, that are driving the community. How, how important are these frameworks to the, the development of the progress making progress in the HPC world? >>Yeah, no, those are great. I mean, spite our stencil flow, I mean, those are the, the now the bread and butter of deep learning machine learning. Am I right? But the challenge is that people use these frameworks, but continuously models are becoming larger. You need very first turnaround time. So how do you train faster? How do you do influencing faster? So this is where HPC comes in and what exactly what we have done is actually we have linked floor fighters to our happy page because now you see the MPI library is running on a million core system. Now your fighters and tenor four clan also be scaled to to, to those number of, large number of course and gps. So we have actually done that kind of a tight coupling and that helps the research to really take advantage of hpc. >>So if, if a high school student is thinking in terms of interesting computer science, looking for a place, looking for a university, Ohio State University, bruns, world renowned, widely known, but talk about what that looks like from a day on a day to day basis in terms of the opportunity for undergrad and graduate students to participate in, in the kind of work that you do. What is, what does that look like? And is, and is that, and is that a good pitch to for, for people to consider the university? >>Yes. I mean, we continuously, from a university perspective, by the way, the Ohio State University is one of the largest single campus in, in us, one of the top three, top four. We have 65,000 students. Wow. It's one of the very largest campus. And especially within computer science where I am located, high performance computing is a very big focus. And we are one of the, again, the top schools all over the world for high performance computing. And we also have very strength in ai. So we always encourage, like the new students who like to really work on top of the art solutions, get exposed to the concepts, principles, and also practice. Okay. So, so we encourage those people that wish you can really bring you those kind of experience. And many of my past students, staff, they're all in top companies now, have become all big managers. >>How, how long, how long did you say you've been >>At 31 >>Years? 31 years. 31 years. So, so you, you've had people who weren't alive when you were already doing this stuff? That's correct. They then were born. Yes. They then grew up, yes. Went to university graduate school, and now they're on, >>Now they're in many top companies, national labs, all over the universities, all over the world. So they have been trained very well. Well, >>You've, you've touched a lot of lives, sir. >>Yes, thank you. Thank >>You. We've seen really a, a burgeoning of AI specific hardware emerge over the last five years or so. And, and architectures going beyond just CPUs and GPUs, but to Asics and f PGAs and, and accelerators, does this excite you? I mean, are there innovations that you're seeing in this area that you think have, have great promise? >>Yeah, there is a lot of promise. I think every time you see now supercomputing technology, you see there is sometime a big barrier comes barrier jump. Rather I'll say, new technology comes some disruptive technology, then you move to the next level. So that's what we are seeing now. A lot of these AI chips and AI systems are coming up, which takes you to the next level. But the bigger challenge is whether it is cost effective or not, can that be sustained longer? And this is where commodity technology comes in, which commodity technology tries to take you far longer. So we might see like all these likes, Gaudi, a lot of new chips are coming up, can they really bring down the cost? If that cost can be reduced, you will see a much more bigger push for AI solutions, which are cost effective. >>What, what about on the interconnect side of things, obvi, you, you, your, your start sort of coincided with the initial standards for Infin band, you know, Intel was very, very, was really big in that, in that architecture originally. Do you see interconnects like RDMA over converged ethernet playing a part in that sort of democratization or commoditization of things? Yes. Yes. What, what are your thoughts >>There for internet? No, this is a great thing. So, so we saw the infinite man coming. Of course, infinite Man is, commod is available. But then over the years people have been trying to see how those RDMA mechanisms can be used for ethernet. And then Rocky has been born. So Rocky has been also being deployed. But besides these, I mean now you talk about Slingshot, the gray slingshot, it is also an ethernet based systems. And a lot of those RMA principles are actually being used under the hood. Okay. So any modern networks you see, whether it is a Infin and Rocky Links art network, rock board network, you name any of these networks, they are using all the very latest principles. And of course everybody wants to make it commodity. And this is what you see on the, on the slow floor. Everybody's trying to compete against each other to give you the best performance with the lowest cost, and we'll see whoever wins over the years. >>Sort of a macroeconomic question, Japan, the US and China have been leapfrogging each other for a number of years in terms of the fastest supercomputer performance. How important do you think it is for the US to maintain leadership in this area? >>Big, big thing, significantly, right? We are saying that I think for the last five to seven years, I think we lost that lead. But now with the frontier being the number one, starting from the June ranking, I think we are getting that leadership back. And I think it is very critical not only for fundamental research, but for national security trying to really move the US to the leading edge. So I hope us will continue to lead the trend for the next few years until another new system comes out. >>And one of the gating factors, there is a shortage of people with data science skills. Obviously you're doing what you can at the university level. What do you think can change at the secondary school level to prepare students better to, for data science careers? >>Yeah, I mean that is also very important. I mean, we, we always call like a pipeline, you know, that means when PhD levels we are expecting like this even we want to students to get exposed to, to, to many of these concerts from the high school level. And, and things are actually changing. I mean, these days I see a lot of high school students, they, they know Python, how to program in Python, how to program in sea object oriented things. Even they're being exposed to AI at that level. So I think that is a very healthy sign. And in fact we, even from Ohio State side, we are always engaged with all this K to 12 in many different programs and then gradually trying to take them to the next level. And I think we need to accelerate also that in a very significant manner because we need those kind of a workforce. It is not just like a building a system number one, but how do we really utilize it? How do we utilize that science? How do we propagate that to the community? Then we need all these trained personal. So in fact in my group, we are also involved in a lot of cyber training activities for HPC professionals. So in fact, today there is a bar at 1 1 15 I, yeah, I think 1215 to one 15. We'll be talking more about that. >>About education. >>Yeah. Cyber training, how do we do for professionals? So we had a funding together with my co-pi, Dr. Karen Tom Cook from Ohio Super Center. We have a grant from NASA Science Foundation to really educate HPT professionals about cyber infrastructure and ai. Even though they work on some of these things, they don't have the complete knowledge. They don't get the time to, to learn. And the field is moving so fast. So this is how it has been. We got the initial funding, and in fact, the first time we advertised in 24 hours, we got 120 application, 24 hours. We couldn't even take all of them. So, so we are trying to offer that in multiple phases. So, so there is a big need for those kind of training sessions to take place. I also offer a lot of tutorials at all. Different conference. We had a high performance networking tutorial. Here we have a high performance deep learning tutorial, high performance, big data tutorial. So I've been offering tutorials at, even at this conference since 2001. Good. So, >>So in the last 31 years, the Ohio State University, as my friends remind me, it is properly >>Called, >>You've seen the world get a lot smaller. Yes. Because 31 years ago, Ohio, in this, you know, of roughly in the, in the middle of North America and the United States was not as connected as it was to everywhere else in the globe. So that's, that's pro that's, I i it kind of boggles the mind when you think of that progression over 31 years, but globally, and we talk about the world getting smaller, we're sort of in the thick of, of the celebratory seasons where, where many, many groups of people exchange gifts for varieties of reasons. If I were to offer you a holiday gift, that is the result of what AI can deliver the world. Yes. What would that be? What would, what would, what would the first thing be? This is, this is, this is like, it's, it's like the genie, but you only get one wish. >>I know, I know. >>So what would the first one be? >>Yeah, it's very hard to answer one way, but let me bring a little bit different context and I can answer this. I, I talked about the happy project and all, but recently last year actually we got awarded an S f I institute award. It's a 20 million award. I am the overall pi, but there are 14 universities involved. >>And who is that in that institute? >>What does that Oh, the I ici. C e. Okay. I cycle. You can just do I cycle.ai. Okay. And that lies with what exactly what you are trying to do, how to bring lot of AI for masses, democratizing ai. That's what is the overall goal of this, this institute, think of like a, we have three verticals we are working think of like one is digital agriculture. So I'll be, that will be my like the first ways. How do you take HPC and AI to agriculture the world as though we just crossed 8 billion people. Yeah, that's right. We need continuous food and food security. How do we grow food with the lowest cost and with the highest yield? >>Water >>Consumption. Water consumption. Can we minimize or minimize the water consumption or the fertilization? Don't do blindly. Technologies are out there. Like, let's say there is a weak field, A traditional farmer see that, yeah, there is some disease, they will just go and spray pesticides. It is not good for the environment. Now I can fly it drone, get images of the field in the real time, check it against the models, and then it'll tell that, okay, this part of the field has disease. One, this part of the field has disease. Two, I indicate to the, to the tractor or the sprayer saying, okay, spray only pesticide one, you have pesticide two here. That has a big impact. So this is what we are developing in that NSF A I institute I cycle ai. We also have, we have chosen two additional verticals. One is animal ecology, because that is very much related to wildlife conservation, climate change, how do you understand how the animals move? Can we learn from them? And then see how human beings need to act in future. And the third one is the food insecurity and logistics. Smart food distribution. So these are our three broad goals in that institute. How do we develop cyber infrastructure from below? Combining HP c AI security? We have, we have a large team, like as I said, there are 40 PIs there, 60 students. We are a hundred members team. We are working together. So, so that will be my wish. How do we really democratize ai? >>Fantastic. I think that's a great place to wrap the conversation here On day three at Supercomputing conference 2022 on the cube, it was an honor, Dr. Panda working tirelessly at the Ohio State University with his team for 31 years toiling in the field of computer science and the end result, improving the lives of everyone on Earth. That's not a stretch. If you're in high school thinking about a career in computer science, keep that in mind. It isn't just about the bits and the bobs and the speeds and the feeds. It's about serving humanity. Maybe, maybe a little, little, little too profound a statement, I would argue not even close. I'm Dave Nicholson with the Queue, with my cohost Paul Gillin. Thank you again, Dr. Panda. Stay tuned for more coverage from the Cube at Super Compute 2022 coming up shortly. >>Thanks a lot.

(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)

(gentle music) >> Welcome back to theCUBE's virtual program, covering VMware Explorer, 2022. The first time since 2019 that the VMware ecosystem is gathered in person. But in the post isolation economy, hybrid is the new format, cube plus digital, we call it. And so we're really happy to welcome Cal Al-Dhubaib who's the founder and CEO and AI strategist of Pandata. And Jonathan Seckler back in theCUBE, the senior director of product marketing at Dell Technologies. Guys, great to see you, thanks for coming on. >> Yeah, thanks a lot for having us. >> Yeah, thank you >> Cal, Pandata, cool name, what's it all about? >> Thanks for asking. Really excited to share our story. I'm a data scientist by training and I'm based here in Cleveland, Ohio. And Pandata is a company that helps organizations design and develop machine learning and AI technology. And when I started this here in Cleveland six years ago, I had people react to me with, what? So we help demystify AI and make it practical. And we specifically focus on trustworthy AI. So we work a lot in regulated industries like healthcare. And we help organizations navigate the complexities of building machine learning and AI technology when data's hard to work with, when there's risk on the potential outcomes, or high cost in the consequences. And that's what we do every day. >> Yeah, yeah timing is great given all the focus on privacy and what you're seeing with big tech and public policy, so we're going to get into that. Jonathan, I understand you guys got some hard news. What's your story around AI and AutoML? Share that with us. >> Yeah, thanks. So having the opportunity to speak with Cal today is really important because one of the hardest things that we find that our customers have is making that transition of experimenting with AI to making it really useful in real life. >> What is the tech underneath that? Are we talking VxRail here? Are you're talking servers? What do you got? >> Yeah, absolutely. So the Dell validated design for AI is a reference framework that is based on the optimized set of hardware for a given outcome. That includes it could be VxRail, VMware, vSphere and Nvidia GPUs and Nvidia software to make all of that happen. And for today, what we're working with is H2O.ai's solution to develop automatic machine learning. So take just that one more step to make it easier for customers to bring AI into production. >> Cool. >> So it's a full stack of software that includes automated machine learning, it includes NVIDIA's AI enterprise for deployment and development, and it's all built on an engineering validated set of hardware, including servers and storage and whatever else you need >> AI out of the box, I don't have to worry about cobbling it all together. >> Exactly. >> Cal, I want to come back to this trusted AI notion. A lot of people don't trust AI just by the very nature of it. I think about, okay, well how does it know it's a cat? And then you can never explain, it says black box. And so I'm like, what are they do with my data? And you mentioned healthcare, financial services, the government, they know everything about me. I just had to get a real ID and Massachusetts, I had to give all my data away. I don't trust it. So what is trusted AI? >> Well, so let me take a step back and talk about sobering statistics. There's a lot of different sources that report on this, but anywhere you look, you'll hear somewhere between 80 to 90% of AI projects fail to yield a return. That's pretty scary, that's a disappointing industry. And why is that? AI is hard. Versus traditional software, you're programming rules hard and fast. If I click this button, I expect A, B, C to happen. And we're talking about recognizing and reacting to patterns. It's not, will it be wrong? It's, when it's wrong, how wrong will it be? And what are it cost to accept related to that? So zooming back in on this lens of trustworthy AI, much of the last 10 years the development in AI has looked like this. Let's get the data, let's race to build the warehouses, okay we did that, no problem. Next was race to build the algorithms. Can we build more sophisticated models? Can we work with things like documents and images? And it used to be the exclusive domain of deep tech companies. You'd have to have teams of teams building the software, building the infrastructure, working on very specific components in this pipeline. And now we have this explosion of technologies, very much like what Jonathan was talking about with validated designs. So it removes the complexities of the infrastructure, it removes the complexities of being able to access the right data. And we have a ton of modeling capabilities and tools out there, so we can build a lot of things. Now, this is when we start to encounter risk in machine learning and AI. If you think about the models that are being used to replicate or learn from language like GPT-3 to create new content, it's training data set is everything that's on the internet. And if you haven't been on the internet recently, it's not all good. So how do you go about building technology to recognize specific patterns, pick up patterns that are desirable, and avoid unintended consequences? And no one's immune to this. So the discipline of trustworthy AI is building models that are easier to interrogate, that are useful for humans, and that minimize the risk of unintended consequences. >> I would add too, one of the good things about the Pandata solution is how it tries to enforce fairness and transparency in the models. We've done some studies recently with IDC, where we've tried to compare leaders in AI technology versus those who are just getting started. And I have to say, one of the biggest differences between a leader in AI and the rest of us is often that the leaders have a policy in place to deal with the risks and the ethics of using data through some kind of machine oriented model. And it's a really important part of making AI usable for the masses. >> You certainly hear a lot about, AI ultimately, there's algorithms which are built by humans. Although of course, there's algorithms to build algorithms, we know that today. >> Right, exactly. >> But humans are biased, there's inherent bias, and so this is a big problem. Obviously Dell, you have a giant observation space in terms of customers. But I wonder, Cal, if you can share with us how you're working with your customers at Pandata? What kind of customers are you working with? What are they asking? What problems are they asking you to solve? And how does it manifest itself? >> So when I like to talk about AI and where it's useful, it usually has to do with taking a repetitive task that humans are tasked with, but they're starting to act more like machines than humans. There's not much creativity in the process, it's handling something that's fairly routine, and it ends up being a bottleneck to scaling. And just a year ago even, we'd have to start approaching our clients with conversations around trustworthy AI, and now they're starting to approach us. Really example, this actually just happened earlier today, we're partnering with one of our clients that basically scans medical claims from insurance providers. And what they're trying to do is identify members that qualify for certain government subsidies. And this isn't as straightforward as it seems because there's a lot of complexities in how the rules are implemented, how judges look at these cases. Long story short, we help them build machine learning to identify these patients that qualify. And a question that comes up, and that we're starting to hear from the insurance companies they serve is how do you go about making sure that your decisions are fair and you're not selecting certain groups of individuals over others to get this assistance? And so clients are starting to wise up to that and ask questions. Other things that we've done include identifying potential private health information that's contained in medical images so that you can create curated research data sets. We've helped organizations identify anomalies in cybersecurity logs. And go from an exploration space of billions of eventual events to what are the top 100 that I should look at today? And so it's all about, how do you find these routine processes that humans are bottlenecked from getting to, we're starting to act more like machines and insert a little bit of outer recognition intelligence to get them to spend more time on the creative side. >> Can you talk a little bit more about how? A lot of people talk about augmented AI. AI is amazing. My daughter the other day was, I'm sure as an AI expert, you've seen it, where the machine actually creates standup comedy which it's so hilarious because it is and it isn't. Some of the jokes are actually really funny. Some of them are so funny 'cause they're not funny and they're weird. So it really underscored the gap. And so how do you do it? Is it augmented? Is it you're focusing on the mundane things that you want to take humans out of the loop? Explain how. >> So there's this great Wall Street Journal article by Jennifer Strong that she published I think four years ago now. And she says, "For AI to become more useful, it needs to become more boring." And I really truly believe in that. So you hear about these cutting edge use cases. And there's certainly some room for these generative AI applications inspiring new designs, inspiring new approaches. But the reality is, most successful use cases that we encounter in our business have to do with augmenting human decisions. How do you make arriving at a decision easier? How do you prioritize from millions of options, hundreds of thousands of options down to three or four that a human can then take the last stretch and really consider or think about? So a really cool story, I've been playing around with DALL.E 2. And for those of you who haven't heard, it's this algorithm that can create images from props. And they're just painting I really wish I had bought when I was in Paris a few years ago. And I gave it a description, skyline of the Sacre-Coeur Church in Montmartre with pink and white hues. And it came up with a handful of examples that I can now go take to an artist and say paint me this. So at the end of the day, automation, it's not really, yes, there's certain applications where you really are truly getting to that automated AI in action. But in my experience, most of the use cases have to do with using AI to make humans more effective, more creative, more valuable. >> I'd also add, I think Cal, is that the opportunity to make AI real here is to automate these things and simplify the languages so that can get what we call citizen data scientists out there. I say ordinary, ordinary employees or people who are at the front line of making these decisions, working with the data directly. We've done this with customers who have done this on farms, where the growers are able to use AI to monitor and to manage the yield of crops. I think some of the other examples that you had mentioned just recently Cal I think are great. The other examples is where you can make this technology available to anyone. And maybe that's part of the message of making it boring, it's making it so simple that any of us can use it. >> I love that. John Furrier likes to say that traditionally in IT, we solve complexity with more complexity. So anything that simplifies things is goodness. So how do you use automated machine learning at Pandata? Where does that fit in here? >> So really excited that the connection here through H2O that Jonathan had mentioned earlier. So H2O.ai is one of the leading AutoML platforms. And what's really cool is if you think about the traditional way you would approach machine learning, is you need to have data scientists. These patterns might exist in documents or images or boring old spreadsheets. And the way you'd approach this is, okay, get these expensive data scientists, and 80% of what they do is clean up the data. And I'm yet to encounter a situation where there isn't cleaning data. Now, I'll get through the cleaning up the data step, you actually have to consider, all right, am I working with language? Am I working with financial forecasts? What are the statistical modeling approaches I want to use? And there's a lot of creativity involved in that. And you have to set up a whole experiment, and that takes a lot of time and effort. And then you might test one, two or three models because you know to use those or those are the go to for this type of problem. And you see which one performs best and you iterate from there. The AutoML framework basically allows you to cut through all of that. It can reduce the amount of time you're spending on those steps to 1/10 of the time. You're able to very quickly profile data, understand anomalies, understand what data you want to work with, what data you don't want to work with. And then when it comes to the modeling steps, instead of iterating through three or four AutoML is throwing the whole kitchen sink at it. Anything that's appropriate to the task, maybe you're trying to predict a category or label something, maybe you're trying to predict a value like a financial forecast or even generate test. And it tests all of the models that it has at its disposal that are appropriate to the task and says, here are the top 10. You can use features like let me make this more explainable, let me make the model more accurate. I don't necessarily care about interrogating the results because the risk here is low, I want to a model that predicts things with a higher accuracy. So you can use these dials instead of having to approach it from a development perspective. You can approach it from more of an experimental mindset. So you still need that expertise, you still need to understand what you're looking at, but it makes it really quick. And so you're not spending all that expensive data science time cleaning up data. >> Makes sense. Last question, so Cal, obviously you guys go deep into AI, Jonathan Dell works with every customer on the planet, all sizes, all industries. So what are you hearing and doing with customers that are best practices that you can share for people that want to get into it, that are concerned about AI, they want to simplify it? What would you tell them? Go ahead, Cal. >> Okay, you go first, Cal. >> And Jonathan, you're going to bring us home. >> Sure. >> This sounds good. So as far as where people get scared, I see two sides of it. One, our data's not clean enough, not enough quality, I'm going to stay away from this. So one, I combat that with, you've got to experiment, you got to iterate, And that's the only way your data's going to improve. Two, there's organizations that worry too much about managing the risk. We don't have the data science expertise that can help us uncover potential biases we have. We are now entering a new stage of AI development and machine learning development, And I use those terms interchangeably anymore. I know some folks will differentiate between them. But machine learning is the discipline driving most of the advances. The toolkits that we have at our disposal to quickly profile and manage and mitigate against the risk that data can bring to the table is really giving organizations more comfort, should give organizations more comfort to start to build mission critical applications. The thing that I would encourage organizations to look for, is organizations that put trustworthy AI, ethical AI first as a consideration, not as an afterthought or not as a we're going to sweep this on the carpet. When you're intentional with that, when you bring that up front and you make it a part of your design, it sets you up for success. And we saw this when GDPR changed the IT world a few years ago. Organizations that built for privacy first to begin with, adapting to GDPR was relatively straightforward. Organizations that made that an afterthought or had that as an afterthought, it was a huge lift, a huge cost to adapt and adjust to those changes. >> Great example. All right, John, I said bring us home, put a bow on this. >> Last bit. So I think beyond the mechanics of how to make a AI better and more workable, one of the big challenges with the AI is this concern that you're going to isolate and spend too much effort and dollars on the infrastructure itself. And that's one of the benefits that Dell brings to the table here with validated designs. Is that our AI validated design is built on a VMware vSphere architecture. So your backup, your migration, all of the management and the operational tools that IT is most comfortable with can be used to maintain and develop and deploy artificial intelligence projects without having to create unique infrastructure, unique stacks of hardware, and then which potentially isolates the data, potentially makes things unavailable to the rest of the organization. So when you run it all in a VMware environment, that means you can put it in the cloud, you can put it in your data center. Just really makes it easier for IT to build AI into their everyday process >> Silo busting. All right, guys, thanks Cal, John. I really appreciate you guys coming on theCUBE. >> Yeah, it's been a great time, thanks. >> All right. And thank you for watching theCUBE's coverage of VMware Explorer, 2022. Keep it right there for more action from the show floor with myself, Dave Velante, John Furrier, Lisa Martin and David Nicholson, keep it right there. (gentle music)

>> Announcer: theCube presents HPE Discover 2022 brought to you by HPE. >> Hello and welcome back to theCube's continuous coverage HPE Discover 2022 and from Las Vegas the formerly Sands Convention Center now Venetian, John Furrier and Dave Vellante here were excited to welcome in Jen Huffstetler. Who's the Chief product Sustainability Officer at Intel Jen, welcome to theCube thanks for coming on. >> Thank you very much for having me. >> You're really welcome. So you dial back I don't know, the last decade and nobody really cared about it but some people gave it lip service but corporations generally weren't as in tune, what's changed? Why has it become so top of mind? >> I think in the last year we've noticed as we all were working from home that we had a greater appreciation for the balance in our lives and the impact that climate change was having on the world. So I think across the globe there's regulations industry and even personally, everyone is really starting to think about this a little more and corporations specifically are trying to figure out how are they going to continue to do business in these new regulated environments. >> And IT leaders generally weren't in tune cause they weren't paying the power bill for years it was the facilities people, but then they started to come together. How should leaders in technology, business tech leaders, IT leaders, CIOs, how should they be thinking about their sustainability goals? >> Yeah, I think for IT leaders specifically they really want to be looking at the footprint of their overall infrastructure. So whether that is their on-prem data center, their cloud instances, what can they do to maximize the resources and lower the footprint that they contribute to their company's overall footprint. So IT really has a critical role to play I think because as you'll find in IT, the carbon footprint of the data center of those products in use is actually it's fairly significant. So having a focus there will be key. >> You know compute has always been one of those things where, you know Intel's been makes chips so that, you know heat is important in compute. What is Intel's current goals? Give us an update on where you guys are at. What's the ideal goal in the long term? Where are you now? You guys always had a focus on this for a long, long time. Where are we now? Cause I won't say the goalpost of changed, they're changing the definitions of what this means. What's the current state of Intel's carbon footprint and overall goals? >> Yeah, no thanks for asking. As you mentioned, we've been invested in lowering our environmental footprint for decades in fact, without action otherwise, you know we've already lowered our carbon footprint by 75%. So we're really in that last mile. And that is why when we recently announced a very ambitious goal Net-Zero 2040 for our scope one and two for manufacturing operations, this is really an industry leading goal. And partly because the technology doesn't even exist, right? For the chemistries and for making the silicon into the sand into, you know, computer chips yet. And so by taking this bold goal, we're going to be able to lead the industry, partner with academia, partner with consortia, and that drive is going to have ripple effects across the industry and all of the components in semiconductors. >> Is there a changing definition of Net-Zero? What that means, cause some people say they're Net-Zero and maybe in one area they might be but maybe holistically across the company as it becomes more of a broader mandate society, employees, partners, Wall Street are all putting pressure on companies. Is the Net-Zero conversation changed a little bit or what's your view on that? >> I think we definitely see it changing with changing regulations like those coming forth from the SEC here in the US and in Europe. Net-Zero can't just be lip service anymore right? It really has to be real reductions on your footprint. And we say then otherwise and even including in our supply chain goals what we've taken new goals to reduce, but our operations are growing. So I think everybody is going through this realization that you know, with the growth, how do we keep it lower than it would've been otherwise, keep focusing on those reductions and have not just renewable credits that could have been bought in one location and applied to a different geographical location but real credible offsets for where the the products manufactured or the computes deployed. >> Jen, when you talk about you've reduced already by 75% you're on that last mile. We listened to Pat Gelsinger very closely up until recently he was the number one most frequently had on theCube guest. He's been busy I guess. But as you apply that discipline to where you've been, your existing business and now Pat's laid out this plan to increase the Foundry business how does that affect your... Are you able to carry through that reduction to, you know, the new foundries? Do you have to rethink that? How does that play in? >> Certainly, well, the Foundry expansion of our business with IBM 2.0 is going to include the existing factories that already have the benefit of those decades of investment and focus. And then, you know we have clear goals for our new factories in Ohio, in Europe to achieve goals as well. That's part of the overall plan for Net-Zero 2040. It's inclusive of our expansion into Foundry which means that many, many many more customers are going to be able to benefit from the leadership that Intel has here. And then as we onboard acquisitions as any company does we need to look at the footprint of the acquisition and see what we can do to align it with our overall goals. >> Yeah so sustainable IT I don't know for some reason was always an area of interest to me. And when we first started, even before I met you, John we worked with PG&E to help companies get rebates for installing technologies that would reduce their carbon footprint. >> Jen: Very forward thinking. >> And it was a hard thing to get, you know, but compute was the big deal. And there were technologies and I remember virtualization at the time was one and we would go in and explain to the PG&E engineers how that all worked. Cause they had metrics and that they wanted to see, but anyway, so virtualization was clearly one factor. What are the technologies today that people should be paying, flash storage was another one. >> John: AI's going to have a big impact. >> Reduce the spinning disk, but what are the ones today that are going to have an impact? >> Yeah, no, that's a great question. We like to think of the built in acceleration that we have including some of the early acceleration for virtualization technologies as foundational. So built in accelerated compute is green compute and it allows you to maximize the utilization of the transistors that you already have deployed in your data center. This compute is sitting there and it is ready to be used. What matters most is what you were talking about, John that real world workload performance. And it's not just you know, a lot of specsmanship around synthetic benchmarks, but AI performance with the built in acceleration that we have in Xeon processors with the Intel DL Boost, we're able to achieve four X, the AI performance per Watts without you know, doing that otherwise. You think about the consolidation you were talking about that happened with virtualization. You're basically effectively doing the same thing with these built in accelerators that we have continued to add over time and have even more coming in our Sapphire Generation. >> And you call that green compute? Or what does that mean, green compute? >> Well, you are greening your compute. >> John: Okay got it. >> By increasing utilization of your resources. If you're able to deploy AI, utilize the telemetry within the CPU that already exists. We have customers KDDI in Japan has a great Proofpoint that they already announced on their 5G data center, lowered their data center power by 20%. That is real bottom line impact as well as carbon footprint impact by utilizing all of those built in capabilities. So, yeah. >> We've heard some stories earlier in the event here at Discover where there was some cooling innovations that was powering moving the heat to power towns and cities. So you start to see, and you guys have been following this data center and been part of the whole, okay and hot climates, you have cold climates, but there's new ways to recycle energy where's that cause that sounds very Sci-Fi to me that oh yeah, the whole town runs on the data center exhaust. So there's now systems thinking around compute. What's your reaction to that? What's the current view on re-engineering a system to take advantage of that energy or recycling? >> I think when we look at our vision of sustainable compute over this horizon it's going to be required, right? We know that compute helps to solve society's challenges and the demand for it is not going away. So how do we take new innovations looking at a systems level as compute gets further deployed at the edge, how do we make it efficient? How do we ensure that that compute can be deployed where there is air pollution, right? So some of these technologies that you have they not only enable reuse but they also enable some you know, closing in of the solution to make it more robust for edge deployments. It'll allow you to place your data center wherever you need it. It no longer needs to reside in one place. And then that's going to allow you to have those energy reuse benefits either into district heating if you're in, you know Northern Europe or there's examples with folks putting greenhouses right next to a data center to start growing food in what we're previously food deserts. So I don't think it's science fiction. It is how we need to rethink as a society. To utilize everything we have, the tools at our hand. >> There's a commercial on the radio, on the East Coast anyway, I don't know if you guys have heard of it, it's like, "What's your one thing?" And the gentleman comes on, he talks about things that you can do to help the environment. And he says, "What's your one thing?" So what's the one thing or maybe it's not just one that IT managers should be doing to affect carbon footprint? >> The one thing to affect their carbon footprint, there are so many things. >> Dave: Two, three, tell me. >> I think if I was going to pick the one most impactful thing that they could do in their infrastructure is it's back to John's comment. It's imagine if the world deployed AI, all the benefits not only in business outcomes, you know the revenue, lowering the TCO, but also lowering the footprint. So I think that's the one thing they could do. If I could throw in a baby second, it would be really consider how you get renewable energy into your computing ecosystem. And then you know, at Intel, when we're 80% renewable power, our processors are inherently low carbon because of all the work that we've done others have less than 10% renewable energy. So you want to look for products that have low carbon by design, any Intel based system and where you can get renewables from your grid to ask for it, run your workload there. And even the next step to get to sustainable computing it's going to take everyone, including every enterprise to think differently and really you know, consider what would it look like to bring renewables onto my site? If I don't have access through my local utility and many customers are really starting to evaluate that. >> Well Jen its great to have you on theCube. Great insight into the current state of the art of sustainability and carbon footprint. My final question for you is more about the talent out there. The younger generation coming in I'll say the pressure, people want to work for a company that's mission driven we know that, the Wall Street impact is going to be financial business model and then save the planet kind of pressure. So there's a lot of talent coming in. Is there awareness at the university level? Is there a course where can, do people get degrees in sustainability? There's a lot of people who want to come into this field what are some of the talent backgrounds of people learning or who might want to be in this field? What would you recommend? How would you describe how to onboard into the career if they want to contribute? What are some of those factors? Cause it's not new, new, but it's going to be globally aware. >> Yeah well there certainly are degrees with focuses on sustainability maybe to look at holistically at the enterprise, but where I think the globe is really going to benefit, we didn't really talk about the software inefficiency. And as we delivered more and more compute over the last few decades, basically the programming languages got more inefficient. So there's at least 35% inefficiency in the software. So being a software engineer, even if you're not an AI engineer. So AI would probably be the highest impact being a software engineer to focus on building new applications that are going to be efficient applications that they're well utilizing the transistor that they're not leaving zombie you know, services running that aren't being utilized. So I actually think-- >> So we got a program in assembly? (all laughing) >> (indistinct), would get really offended. >> Get machine language. I have to throw that in sorry. >> Maybe not that bad. (all laughing) >> That's funny, just a joke. But the question is what's my career path. What's a hot career in this area? Sustainability, AI totally see that. Anything else, any other career opportunities you see or hot jobs or hot areas to work on? >> Yeah, I mean, just really, I think it takes every architect, every engineer to think differently about their design, whether it's the design of a building or the design of a processor or a motherboard we have a whole low carbon architecture, you know, set of actions that are we're underway that will take to the ecosystem. So it could really span from any engineering discipline I think. But it's a mindset with which you approach that customer problem. >> John: That system thinking, yeah. >> Yeah sustainability designed in. Jen thanks so much for coming back in theCube, coming on theCube. It's great to have you. >> Thank you. >> All right. Dave Vellante for John Furrier, we're sustaining theCube. We're winding down day three, HPE Discover 2022. We'll be right back. (upbeat music)

>>Okay, welcome back. Everyone's Cube's coverage here in Las Vegas for Amazon re Mars machine learning, automation, robotics, and space out. John fir host of the queue. Got a great set of guests here talking about AI, Jason Montgomery CTO and co-founder man and Ryans CEO, founder guys. Thanks for coming on. We're just chatting, lost my train of thought. Cuz we were chatting about something else, your history with DataRobot and, and your backgrounds entrepreneurs. Welcome to the queue. Thanks >>Tur. Thanks for having >>Us. So first, before we get into the conversation, tell me about the company. You guys have a history together, multiple startups, multiple exits. What are you guys working on? Obviously AI is hot here as part of the show. M is Mars machine learning, which we all know is the basis for AI. What's the story. >>Yeah, really. We're we're here for two of the letters and Mars. We're here for the machine learning and the automation part. So at the high level, man is a no code AI application development platform. And basically anybody could log in and start making AI applications. It could be anything from just texting it with the Twilio integration to tell you that you're doing great or that you need to exercise more to integrating with zenes to get support tickets classified. >>So Jason, we were talking too about before he came on camera about the cloud and how you can spin up resources. The data world is coming together and I, and I like to see two flash points. The, I call it the 2010 big data era that began and then failed Hadoop crashed and burned. Yeah. Then out of the, out of the woodwork came data robots and the data stacks and the snowflakes >>Data break snowflake. >>And now you have that world coming back at scale. So we're now seeing a huge era of, I need to stand up infrastructure and platform to do all this heavy lifting. I don't have time to do. Right. That sounds like what you guys are doing. Is that kind of the case? >>That's absolutely correct. Yeah. Typically you would have to hire a whole team. It would take you months to sort of get the infrastructure automation in place, the dev ops DevOps pipelines together. And to do the automation to spin up, spin down, scale up scale down requires a lot of special expertise with, you know, Kubernetes. Yeah. And a lot of the other data pipelines and a lot of the AWS technologies. So we automate a lot of that. So >>If, if DevOps did what they did, infrastructure has code. Yeah. Data has code. This is kind of like that. It's not data ops per se. Is there a category? How do you see this? Cuz it's you could say data ops, but that's also it's DevOps dev. It's a lot going on. Oh yeah. It's not just seeing AI ops, right? There's a lot more, what, what would you call this? >>It's a good question. I don't know if we've quite come up with the name. I know >>It's not data ops. It's not >>Like we call it AI process automation >>SSPA instead of RPA, >>What RPA promised to be. Yes, >>Exactly. But what's the challenge. The number one problem is it's I would say not, not so much all on ever on undifferent heavy lifting. It's a lot of heavy lifting that for sure. Yes. What's involved. What's the consequences of not going this way. If I want to do it myself, can you take me through the, the pros and cons of what the scale scope, the scale of without you guys? >>Yeah. Historically you needed to curate all your data, bring it together and have some sort of data lake or something like that. And then you had to do really a lot of feature engineering and a lot of other sort of data science on the back end and automate the whole thing and deploy it and get it out there. It's a, it's a pretty rigorous and, and challenging problem that, you know, we there's a lot of automation platforms for, but they typically focus on data scientists with these large language models we're using they're pre-trained. So you've sort of taken out that whole first step of all that data collection to start out and you can basically start prototyping almost instantly because they've already got like 6 billion parameters, 10 billion parameters in them. They understand the human language really well. And a lot of other problems. I dunno if you have anything you wanna add to that, Ryan, but >>Yeah, I think the other part is we deal with a lot of organizations that don't have big it teams. Yeah. And it would be impossible quite frankly, for them to ever do something like deploy text, track as an example. Yeah. They're just not gonna do it, but now they can come to us. They know the problem they want solved. They know that they have all these invoices as an example and they wanna run it through a text track. And now with us they can just drag and drop and say, yeah, we want tech extract. Then we wanted to go through this. This is what we >>Want. Expertise is a huge problem. And the fact that it's changing too, right? Yeah. Put that out there. You guys say, you know, cybersecurity challenges. We guys do have a background on that. So you know, all the cutting edge. So this just seems to be this it, I hate to say transformation. Cause I not the word I'm looking for, I'd say stuck in the mud kind of scenario where they can't, they have to get bigger, faster. Yeah. And the scale is bigger and they don't have the people to do it. So you're seeing the rise of managed service. You mentioned Kubernetes, right? I know this young 21 year old kid, he's got a great business. He runs a managed service. Yep. Just for Kubernetes. Why? Because no, one's there to stand up the clusters. >>Yeah. >>It's a big gap. >>So this, you have these sets of services coming in now, where, where do you guys fit into that conversation? If I'm the customer? My problem is what, what is my, what is my problem that I need you guys for? What does it look like to describe my problem? >>Typically you actually, you, you kind of know that your employees are spending a lot of time, a lot of hours. So I'll just give you a real example. We have a customer that they were spending 60 hours a week just reviewing these accounts, payable, invoices, 60 hours a week on that. And they knew there had to be a better way. So manual review manual, like when we got their data, they were showing us these invoices and they had to have their people circle the total on the invoice, highlight the customer name, the >>Person who quit the next day. Right? >>No like they, they, Hey, you know, they had four people doing this, I think. And the point is, is they come to us and we say, well, you know, AI can, can just basically using something like text track can just do this. And then we can enrich those outputs from text track with the AI. So that's where the transformers come in. And when we showed them that and got them up and running in about 30 minutes, they were mind blown. Yeah. And now this is a company that doesn't have a big it department. So the >>Kind, and they had the ability to quantify the problem >>They knew. And, and in this case it was actually a business user. It was not a technical >>In is our she consequence technical it's hours. She consequences that's wasted. Manual, labor wasted. >>Exactly. Yeah. And, and to their point, it was look, we have way more high, valuable tasks that our people could be doing yeah. Than doing this AP thing. It takes 60 hours. And I think that's really important to remember about AI. What're I don't think it's gonna automate away people's jobs. Yeah. What it's going to do is it's going to free us up to focus on what really matters and focus on the high value stuff. And that's what people should >>Be doing. I know it's a cliche. I'm gonna say it again. Cause I keep saying, cause I keep saying for people to listen, the bank teller argument always was the big thing. Oh yeah. They're gonna get killed by the ATM machine. No, they're opening up more branches. That's right. That's right. So it's like, come on. People let's get, get over that. So I, I definitely agree with that. Then the question, next question is what's your secret sauce? I'm the customer I'm gonna like that value proposition. You make something go away. It's a pain relief. Then there's the growth side. Okay. You can solve from problems. Now I want this, the, the vitamin you got aspirin. And I want the vitamin. What's the growth angle for you guys with your customers. What's the big learnings. Once they get the beach head with problem solving. >>I think it, it, it it's the big one is let's say that we start with the account payable thing because it's so our platform's so approachable. They go in and then they start tinkering with the initial, we'll call it a template. So they might say, Hey, you know what, actually, in this edge case, I'm gonna play with this. And not only do I want it to go to our accounting system, but if it's this edge case, I want it to email me. So they'll just drag and drop an email block into our canvas. And now they're making it >>Their own. There is the no code, low code's situation. They're essentially building a notification engine under the covers. They have no idea what they're doing. That's >>Right. They get the, they just know that, Hey, you know what? When, when like the amount's over $10,000, I want an email. They know that's what they want. They don't, they don't know that's the notification engine. Of >>Course that's value email. Exactly. I get what I wanted. All right. So tell me about the secret sauce. What's under the covers. What's the big, big, big scale, valuable, valuable, secret sauce. >>I would say part of it. And, and honestly, the reason that we're able to do this now is transformer architecture. When the transformer papers came out and then of course the attention is all you need paper, those kind of unlocked it and made this all possible. Beyond that. I think the other secret sauce we've been doing this a long time. >>So we kind of, we know we're in the paid points. We went to those band points. Cause we weren't data scientists or ML people. >>Yeah. >>Yeah. You, you walked the snow and no shoes on in the winter. That's right. These kids now got boots on. They're all happy. You've installed machines. You've loaded OSS on, on top of rack switches. Yeah. I mean, it's unbelievable how awesome it's right now to be a developer and now a business user's doing the low code. Yep. If you have the system architecture set up, so back to the data engineering side, you guys had the experience got you here. This is a big discussion right now. We're having in, in, on the cube and many conversations like the server market, you had that go away through Amazon and Google was one of the first, obviously the board, but the idea that servers could be everywhere. So the SRE role came out the site reliability engineer, right. Which was one guy or gal and zillions of servers. Now you're seeing the same kind of role with data engineering. And then there's not a lot of people that fit the requirement of being a data engineer. It's like, yeah, it's very unique. Cause you're dealing with a system architecture, not data science. So start to see the role of this, this, this new persona, because they're taking on all the manual challenges of doing that. You guys are kind of replaced that I think. Well, do you agree with it about the data engineer? First of all? >>I think, yeah. Well and it's different cuz there's the older data engineer and then there's sort of the newer cloud aware one who knows how to use all the cloud technologies. And so when you're trying, we've tried to hire some of those and it's like, okay, you're really familiar with old database technology, but can you orchestrate that in a serverless environment with a lot of AWS technology for instance. And it's, and that's hard though. They don't, they don't, there's not a lot of people who know that space, >>So there's no real curriculum out there. That's gonna teach you how to handle, you know, ETL. And also like I got I'm on stream data from this source. Right. I'm using sequel I'm I got put all together. >>Yeah. So it's yeah, it's a lot of just not >>Data science. It's >>Figure that out. So its a large language models too. We don't have to worry about some of the data there too. It's it's already, you know, codified in the model. And then as we collect data, as people use our platform, they can then curate data. They want to annotate or enrich the model with so that it works better as it goes. So we're kind of curating, collecting the data as it's used. So as it evolves, it just gets better. >>Well, you guys obviously have a lot of experience together and congratulations on the venture. Thank you. What's going on here at re Mars. Why are you here? What's the pitch. What's the story. Where's your, you got two letters. You got the, you got the M for the machine learning and AI and you got the, a for automation. What's the ecosystem here for you? What are you doing? >>Well, I mean, I think you, you kind of said it right. We're here because the machine learning and the automation part, >>But >>More, more widely than that. I mean we work very, very closely with Amazon on a number of front things like text track, transcribe Alexa, basically all these AWS services are just integrations within our system. So you might want to hook up your AI to an Alexa so that you could say, Hey Alexa, tell me updates about my LinkedIn feed. I don't know, whatever, whatever your hearts content >>Is. Well what about this cube transcription? >>Yeah, exactly. A hundred percent. >>Yeah. We could do that. You know, feed all this in there and then we could do summarization of everything >>Here, >>Q and a extraction >>And say, Hey, these guys are >>Technicals. Yeah, >>There you go. No, they mentioned Kubernetes. We didn't say serverless chef puppet. Those are words straight, you know, and no linguistics matters right into that's a service that no one's ever gonna build. >>Well, and actually on that point, really interesting. We work with some healthcare companies and when you're basically, when people call in and they call into the insurance, they have a question about their, what like is this gonna be covered? And what they want to key in on are things like I just went to my doctor and got a cancer diagnosis. So the, the, the relevant thing here is they just got this diagnosis. And why is that important? Well, because if you just got a diagnosis, they want to start a certain triage to make you successful with your treatments. Because obviously there's an >>Incentive to do time. That time series matters and, and data exactly. And machine learning reacts to it. But also it could be fed back old data. It used to be time series to store it. Yeah. But now you could reuse it to see how to make the machine learning better. Are you guys doing anything, anything around that, how to make that machine learning smarter, look doing look backs or maybe not the right word, but because you have data, I might as well look back at it's happened. >>So part of, part of our platform and part of what we do is as people use these applications, to your point, there's lots of data that's getting generated, but we capture all that. And that becomes now a labeled data set within our platform. And you can take that label data set and do something called fine tuning, which just makes the underlying model more and more yours. It's proprietary. The more you do it. And it's more accurate. Usually the more you do it. >>So yeah, we keep all that. I wanna ask your reaction on this is a good point. The competitive advantage in the intellectual property is gonna be the workflows. And so the data is the IP. If this refinement happens, that becomes intellectual property. Yeah. That's kind of not software. It's the data modeling. It's the data itself is worth something. Are you guys seeing that? >>Yeah. And actually how we position the company is man team is a control plane and you retain ownership of the data plane. So it is your intellectual property. Yeah. It's in your system, it's in your AWS environment. >>That's not what everyone else is doing. Everyone wants to be the control plane and the data plan. We >>Don't wanna own your data. We don't, it's a compliance and security nightmare. Yeah. >>Let's be, Real's the question. What do you optimize for? Great. And I think that's a fair, a fair bet. Given the fact that clients want to be more agile with their data anyway, and the more restrictions you put on them, why would that this only gets you in trouble? Yeah. I could see that being a and plus lock. In's gonna be a huge factor. Yeah. I think this is coming fast and no one's talking about it in the press, but everyone's like run to silos, be a silo and that's not how data works. No. So the question is how do you create siloing of data for say domain specific applications while maintaining a horizontally scalable data plan or control plan that seems to be kind of disconnected everyone to lock in their data. What do you guys think about that? This industry transition we're in now because it seems people are reverting back to fourth grade, right. And to, you know, back to silos. >>Yeah. I think, well, I think the companies probably want their silo of data, their IP. And so as they refine their models and, and we give them the ability to deploy it in their own stage maker and their own VPC, they, they retain and own it. They can actually get rid of us and they still have that model. Now they may have to build, you know, a lot of pipelines and other technology to support it. But well, >>Your lock in is usability. Exactly. And value. Yeah. Value proposition is the lock in bingo. That's not counterintuitive. Exactly. Yeah. You say, Hey, more value. How do I wanna get rid of it? Valuable. I'll pay for it. Right. As long as you have multiple value, step up. And that's what cloud does. I mean, think that's the thing about cloud. That's gonna make all this work. In my opinion, the value enablement is much higher. Yeah. So good business model. Anything else here at the show that you observed that you like, that you think people would be interested in? What's the most important story coming out of the, the holistic, if you zoom up and look at re Mars, what's, what's coming out of the vibe. >>You know, one thing that I think about a lot is we're, you know, we have Artis here, humanity hopefully soon gonna be going to Mars. And I think that's really, really exciting. And I also think when we go to Mars, we're probably not gonna send a bunch of software engineers up there. >>Right. So like robots will do break fix now. So, you know, we're good. It's gone. So services are gonna be easy. >>Yeah. But I, oh, >>I left that device back at earth. I just think that's not gonna be good. Just >>Replicated it in one. I think there's like an eight >>Minute, the first monopoly on next day delivery in space. >>They'll just have a spaceship that sends out drones to Barss. Yeah. But I think that when we start going back to the moon and we go to Mars, people are gonna think, Hey, I need this application now to solve this problem that I didn't anticipate having. And in science fiction, we kind of saw this with like how, right? Like you had this AI on this computer or this, on this spaceship that could do all this stuff. We need that. And I haven't seen that here yet. >>No, it's not >>Here yet. And >>It's right now I think getting the hardware right first. Yep. But we did a lot of reporting on this with the D O D and the tactile edge, you know, military applications. It's a fundamental, I won't say it's a tech, religious argument. Like, do you believe in agile realtime data or do you believe in democratizing multi-vendor, you know, capability? I think, I think the interesting needs to sort itself out because sometimes multi vendor multi-cloud might not work for an application that needs this database or this application at the edge. >>Right. >>You know, so if you're in space, the back haul, it matters. >>It really does. Yeah. >>Yeah. Not a good time to go back and get that highly available data. You mean highly, is it highly available or there's two terms highly available, which means real time and available. Yeah. Available means it's on a dis, right? >>Yeah. >>So that's a big challenge. Well guys, thanks for coming on. Plug for the company. What are you guys up to? How much funding do you have? How old are you staff hiring? What's some of the details. >>We're about 45 people right now. We are a globally distributed team. So we hire every like from every country, pretty much we are fully remote. So if you're looking for that, hit us up, definitely always look for engineers, looking for more data scientists. We're very, very well funded as well. And yeah. So >>You guys headquarters out, you guys headquartered. >>So a lot of us live in Columbus, Ohio that's technically HQ, but like I said, we we're in pretty much every continent except in Antarctica. So >>You're for all virtual. >>Yeah. A hundred percent virtual, a hundred percent. >>Got it. Well, congratulations and love to hear that Datadog story at another time >>Or DataBot >>Yeah. I mean data, DataBot sorry. Let's get, get all confused >>Data dog data company. >>Well, thanks for coming on and congratulations for your success and thanks for sharing. Yeah. >>Thanks for having us for having >>Pleasure to be here. It's a cube here at rebars. I'm John furier host. Thanks for watching more coming back after this short break.

(upbeat music) >> Hello, welcome to this CUBE Conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We're here with Tim Everson, CISO at Kalahari Resorts & Conventions. Tim, great to see you. Thanks for coming on theCUBE. >> Thank you for having me. Looking forward to it. >> So, you know, RSA is going on this week. We're talking a lot about security. You've got a lot of conferences. Security is a big scale now across all enterprises, all businesses. You're in the hospitality, you got conventions. You're in the middle of it. You have an interesting environment. You've got a lot of diverse use cases. And you've got a lot of needs. They're always changing. I mean, you talk about change. You've got a network that has to be responsive, robust and support a lot of tough customers who want to have fun or do business. >> Exactly, yeah. We have customers that come in, that we were talking about this before the segment. And we have customers that come in that bring their own Roku Sticks their own Amazon devices. All these different things they bring in. You know, our resort customers need dedicated bandwidth. So they need dedicated network segments stood up at a moment's notice to do the things they're doing and run the shows they're showing. So it's never, never ending. It's constantly changing in our business. And there's just data galore to keep an eye on. So it's really interesting. >> Can you scope the scale of the current cybersecurity challenges these days in the industry? Because they're wide and far, they're deep. You got zero trust on one end, which is essentially don't trust anything. And then you got now on the software supply chain, things like more trust. So you got the conflict between a direction that's more trusted and then zero trust, and everything in between. From, endpoint protection. It's a lot going on. What's the scale of this situation right now in cyber? >> You know, right now everything's very, very up in the air. You talk about zero trust. And zero trust can be defined a lot of ways depending on what security person you talk to today. So, I won't go into my long discussion about zero trust but suffice to say, like I said zero trust can be perceived so many different ways. From a user perspective, from a network perspective, from an end point. I look more broadly at the regulatory side of things and how that affects things too. Because, regulations are changing daily. You've got your GDPRs, your CCPAs, your HIPAA regulations, PCI. All these different things that affect businesses, and affect businesses different ways. I mean, at Kalahari we're vulnerable or we're not vulnerable, but we're subject to a lot of these different regulations, more so than other people. You wouldn't expect a lot of hotels to have HIPAA regulations for instance. We have health people at our resorts. So we actually are subject to HIPAA in a lot of cases. So there's a lot of these broad scenarios that apply and they come into play with all different industries. And again, things you don't expect. So, when you see these threats coming, when you see all the hacks coming. Even today I got an email that the Marriott breach data from a few years ago, or the MGM breach from a few years ago. We've got all these breaches out there in the world, are coming back to the surface and being looked at again. And our users and our guests and our corporate partners, and all these different people see those things and they rely on us to protect them. So it makes that scope just exponentially bigger. >> Yeah, there's so many threads to pull on here. One is, you know we've observed certainly with the pandemic and then now going forward is that if you weren't modern in your infrastructure, in your environment, you are exposed. Even, I'm not talking old and antiquated like in the dark ages IT. We're talking like really state of the art, current. If you're lagging just by a few years, the hackers have an advantage. So, the constant bar raising, leveling up on technology is part of this arms race against the bad guys. >> Absolutely. And you said it, you talked earlier about the supply chain. Supply chain, these attacks that have come through the SolarWinds attacks and some of these other supply chain attacks that are coming out right now. Everybody's doing their best to stay on top of the latest, greatest. And the problem with that is, when you rely on other vendors and other companies to be able to help you do that. And you're relying on all these different tool sets, the supply chain attack is hugely critical. It makes it really, really important that you're watching where you're getting your software from, what they're doing with it, how they secure it. And that when you're dealing with your vendors and your different suppliers, you're making sure that they're securing things as well as you are. And it just, it adds to the complexity, it adds to the footprint and it adds to the headache that a lot of these security teams have. Especially small teams where they don't have the people to manage those kind of contacts. >> It's so interesting, I think zero trust is a knee jerk reaction to the perimeter being gone. It's like, you got to People love the zero trust. Oh it's like, "We're going to protect this that nobody, and then vet them in." But once you're trusted, trust also is coming in to play here. And in your environment, you're a hotel, you're a convention. You have a lot of rotation of guests coming in. Very much high velocity. And spear phishing and phishing, I could be watching and socially engineering someone that could be on your property at any given time. You got to be prepared for that. Or, you got ransomware coming around the corners or heavily. So, you got the ransomware threat and you got potentially spear phishing that could be possible at your place. These are things that are going on, right? That you got to protect for. What's your reaction to that? >> Absolutely. We see all those kind of attacks on a daily basis. I see spear phishing attacks. I see, web links and I chase them down and see what's going on. I see that there's ransomware trying to come in. We see these things every single day. And the problem you have with it is not only, especially in a space where you have a high volume of customers and a high turnover of customers like you're talking about that are in and out of our resorts, in and out of our facilities. Those attacks aren't just coming from our executives and their email. We can have a guest sitting on a guest network, on a wireless network. Or on one of our business center machines, or using our resort network for any one of a number of the conference things that they're doing and the different ports that we have to open and the different bandwidth scenarios that you've got dealing with. All of these things come into play because if any attack comes from any of those channels you have to make sure that segmentation is right, that your tooling is proper and that your team is aware and watching for it. And so it does. It makes it a very challenging environment to be in. >> You know, I don't want to bring up the budget issue but I'll bring up the budget issue. You can have unlimited budget because there's so many tools out there and platforms now. I mean, if you've look at the ecosystem map of the cybersecurity landscape that you have to navigate through as a customer. You've got a lot of people knocking on your door to sell you stuff. So I have to ask you, what is the scale? I mean, you can't have unlimited budget. But the reality is you have to kind of, do the right thing. What's the most helpful kind of tools and platforms for you that you've seen that you've had experience with? Where's this going in terms of the most effective mechanisms and software and platforms that are available out there? >> From the security perspective specifically, the three things that are most important to me are visibility. Whether it's asset visibility or log visibility. You know, being able to see the data, being able to see what's going on. End user. Making sure that the end user has been trained, is aware and that you're watching them. Because the end user, the human is always the weakest link. The human doesn't have digital controls that can be hard set and absolutely followed. The human changes every day. And then our endpoint security solutions. Those are the three biggest things for me. You know, you have your network perimeter, your firewalls. But attackers aren't always looking for those. They're coming from the inside, they're finding a way around those. The biggest three things for me are endpoint, visibility and the end user. >> Yeah, it's awesome. And a lot of companies are really looking at their posture right now. So I would ask you as a CISO, who's in the front end of all this great stuff and protecting your networks and all your environments and the endpoints and assets. What advice would you have for other CISOs who are kind of trying to level up to where you're at, in terms of rethinking their security posture? What advice would you give them? >> The advice I would give you is surround yourself with people that are like-minded on the security side. Make sure that these people are aware but that they're willing to grow. Because security's always changing. If you get a security person that's dead set that they're going to be a network security person and that's all they're going to do. You know, you may have that need and you may fill it. But at the end of the day, you need somebody who's open rounded and ready to change. And then you need to make sure that you can have somebody, and the team that you work with is able to talk to your executives. It never fails, the executives. They understand security from the standpoint of the business, but they don't necessarily understand security from the technical side. So you have to make sure that you can cross those two boundaries. And when you grow your team you have to make sure that that's the biggest focus. >> I have to ask the pandemic question, but I know cybersecurity hasn't changed. In fact, it's gotten more aggressive in the pandemic. How has the post pandemic or kind of like towards the tail end of where we're at now, affect the cybersecurity landscape? Has it increased velocity? Has it changed any kind of threat vectors? Has it changed in any way? Can you share your thoughts on what happened during the pandemic and now has we come out of it into the next, well post pandemic? >> Absolutely. It affected hospitality in a kind of unique way. Because, a lot of the different governments, state, federal. I'm in Ohio. I work out of our Ohio resort. A lot of the governments literally shut us down or limited severely how many guests we could have in. So on the one hand you've got less traffic internal over the network. So you've got a little bit of a slow down there. But on the flip side it also meant a lot of our workers were working from home. So now you've got a lot of remote access coming in. You've got people that are trying to get in from home and work machines. You have to transition call centers and call volume and all of the things that come along with that. And you have to make sure that that human element is accounted for. Because, again, you've got people working from home, you no longer know if the person that's calling you today, if it's not somebody you're familiar with you don't know if that person is Joe Blow from the front desk or if that person's a vendor or who they are. And so when you deal with a company with 5,000 ish employees or 10,000 that some of these bigger companies are. 15,000, whatever the case may be. You know, the pandemic really put a shift in there because now you're protecting not only against the technologies, but you're dealing with all of the scams, all of the phishing attempts that are coming through that are COVID related. All of these various things. And it really did. It threw a crazy mix into cybersecurity. >> I can imagine that the brain trust over there is prior thinking, "Hey, we were a hybrid experience." Now, if people who have come and experienced our resorts and conventions can come in remotely, even in a hybrid experience with folks that are there. You've seen a lot of hybrid events for instance go on, where there's shared experience. I can almost imagine your service area is now extending to the homes of those guests. That you got to start thinking differently. Has that been something that you guys are looking at? >> We're looking at it from the standpoint of trying to broaden some of the events. In the case of a lot of our conventions, things of that nature. The conventions that aren't actually Kalahari's run conventions, we host them, we manage them. But it does... When you talk about workers coming from home to attend these conventions. Or these telecommuters that are attending these conventions. It does affect us in the stance that, like I said we have to provision network for these various events. And we have to make sure that the network and the security around the network are tight. So it does. It makes a big deal as far as how Kalahari does its business. Being able to still operate these different meetings and different conventions, and being able to host remotely as well. You know, making sure that telecommunications are available to them. Making sure that network access and room access are available to them. You know for places where we can't gather heavily in meetings. You know, these people still being able to be near each other, still being able to talk, but making sure that that technology is there between them. >> Well, Tim is great to have you on for this CUBE Conversation. CISO from the middle of all the action. You're seeing a lot. There's a lot of surface area you got to watch. There's a lot of data you got to observe. You got to get that visibility. You can only protect what you can see, and the more you see the better it is. The better the machine learning. You brought up the the common area about like-minded individuals. I want to just ask you on the final point here, on hiring and talent coming into the marketplace. I mean, this younger generation coming out of university and college is, or not even going to school. There's no cyber degree. I mean, there are now. But I mean, the world's changing. It's easy to level up. So, skill sets you can't get a degree in certain things. I mean, you got to have a broad set. What do you look for in talent? Is there a trend you see in terms of what makes a good cybersecurity professional, developer, analyst? Is there roles that you see emerging that you think people should pay attention to? What's your take on this as someone who's looking at the future? And- >> You know, it's very interesting that you bring this up. I actually have two of my team members, one directly working for me and another team member at Kalahari that are currently going through college degree programs for cybersecurity. And I wrote recommendations for them. I've worked with them, I'm helping them study. But as you bring people up, you know the other thing I do is I mentor at a couple of the local technical schools as well. I go in, I talk to people, I help them design their programs. And the biggest thing I try to get across to them is, number one, if you're in the learning side of it. Not even talking about the hiring side of it. If you're in the learning side of it, you need to come into it with a kind of an understanding to begin with to where you want to fit into security. You know, do you want to be an attacker, a defender, a manager? Where do you want to be? And then you also need to look at the market and talk to the businesses in the area. You know, I talk to these kids regularly about what their need is. Because if you're in school and you're taking Cisco classes, and focusing on firewalls and what an organization needs as somebody who can read log and do things like that. Or somebody who can do pen testing. You know, that's a huge thing. So I would say if you're on the hiring side of that equation, you know. Like you said, there's no super degrees that I can speak to. There's a lot of certifications. There's a lot of different things like that. The goal for me is finding somebody who can put hands to the ground and feet to the ground, and show me that they know what they know. You know, I'll pull somebody in, I'll ask them to show me a certain specific or I'll ask them for specific information and try to feel that out. Because at the end of the day, there's no degree that's going to protect my network. There's no degree that's a hundred percent going to understand Kalahari, for instance. So I want to make sure that the people I talk to, I get a broad interview scope, I get a number of people to talk to. And really get a feel for what it is they know, and what tools they want to work with and make sure it's going to align with us. >> Well, Tim, that's great that you do that. I think the industry needs that. And I think that's really paying it forward, by getting in and using your time to help shape the young curriculums and the young guns out there. It's interesting you know, like David Vellante and I talk on theCUBE all the time. Cyber is like sports. If you're playing football, you got to know the game. If you're playing football and you come in as a baseball player, the skills might not translate, right? So it's really more of, categorically cyber has a certain pattern to it. Math, open mindedness, connecting dots, seeing things around corners. Maybe it's more holistic views, if you're at the visibility level or getting the weeds with data. A lot of different skill sets needed. The aperture of the job requirements are changing a lot. >> They are. And you know, you touched on that really well. You know, they talk about hacking and the hacker mindset. You know, all the security stuff revolves around hacker. And people mislabel hacker. Hacking in general is making something do something that it wasn't originally designed to do. And when I hire people in security, I want people that have that mindset. I want people that not only are going to work with the tool set we have, and use that mathematical ability and that logic and that reasoning. But I want them to use a reasoning of, "Hey, we have this tool here today. How can this tool do what I want it do but what else can it do for me?" Because like any other industry we have to stretch our dollar. So if I have a tool set that can meet five different needs for me today, rather than investing in 16 different tool sets and spreading that data out and spreading all the control around. Let's focus on those tool sets and let's focus on using that knowledge and that adaptive ability that the human people have on the security side, and put that to use. Make them use the tools that work for them but make 'em develop things, new tools, new methods, new techniques that help us get things across. >> Grow the capabilities, protect, trust all things coming in. And Tim, you're a tech athlete, as we say and you've got a great thing going on over there. And again, congratulations on the work you're doing on the higher ed and the education side and the Kalahari Resorts & Conventions. Thanks for coming on theCUBE. I really appreciate the insight you're sharing. Thank you. >> Thanks for having me. >> Okay. I'm John Furrier here in Palo Alto for theCUBE. Thanks for watching. (somber music)

(soft bright music) (logo swooshing) (crowd murmuring) >> Hey everyone, welcome to Las Vegas! Lisa Martin here on the ground with theCUBE about Coupa Inspire 2022. And can you hear the buzz behind me? It is so great to be in person. Nick Banich joins me, the Chief Revenue Officer and Global Partnership Manager for the Coupa Alliance at Miebach Consulting. Nick, it's great to have you on the program. >> Thanks for having me, Lisa. First time here at Inspire and it's exciting. >> Is it exciting? It's great to see this room packed. >> It is! It feels, like, the pandemic is finally- >> It does. >> Maybe behind us. >> Right, fingers crossed. (Nick chuckles) So talk to us a little bit about Miebach Consulting and a little bit about the Coupa Partnership, so the audience gets that understanding of what you guys do. >> Yeah, guess, we're kind of new to the Coupa ecosystem. You could say, we came as part of the acquisition of LLamasoft. So Miebach is a supply chain focus, advisory, consultancy, engineering firm. So we have three different business lines. Supply chain strategy, where we do things like supply chain design and the Coupa platform, planning, inventory, engineering, automation studies, and distribution centers, with the labor crunch that we're facing right now. As well as we have a digital transformation group that works on getting the decision-making as a supply chain industry into the digital realm and away from Microsoft Excel. >> Let's talk about the digitization of the supply chain. You know, one of the things that we've seen in the last couple of years is this massive acceleration to digital because businesses in every industry had no choice. But where are, what are the current trends from a digital supply chain perspective? >> You know, I think the, kind of the integration of the compression of the decision-making cycle has really gotten companies to not look at strategic decisions then operational decisions and tactical decisions in execution. That all has to be compressed now with the volatility we've all been exposed to. I mean, basically, for the past 20 years, we took the supply chain and turned it into a Swiss watch. It was very long, very well orchestrated. But with the volatility, with labor issues, with the land war in Europe, this volatility and change is requiring companies to be much more adaptive. And they've had to compress that decision cycle down and the Coupa platform, certainly, from a supply chain standpoint, absolutely helps infuse that process to shorten time from question to answer and allow you to address strategic and tactical topics in parallel to one another and not kind of waterfall down over the decision making product. >> That's important, 'cause these days, there is no time for waterfalls. So let's unpack the Coupa supply chain design platform. Talk to me about it, what it does and how it is helping that acceleration? >> Yeah, so it's incredibly powerful. And what it allows you to do is create that digital representation. We can take a three dimensional world and put it into a two dimensional linear program. And within the same platform we can optimize strategically and take a look at end to end type of supply chain decisions, nearshoring, onshoring, supplier diversification, and risk aspects. We can look at it more operationally. We're actually looking at which manufacturing plans should make what? What distribution centers should serve what customers? How do I segment my products? How do I segment my customers? Then within the same modules, you can use and go to your inventory optimization, not only optimize inventory, but also simulate it, which gives you phenomenal power in a world where there is so much uncertainty. You can apply risk in those questions of what if, so you're ready. So that way, when the thing happens, you're not that scrambling to have analysts crunch Excel files to see what do you do to normalize inventory levels or normalize your supplier base. You're able to be more proactive with the predictive and prescriptive analytics that the full suite provides for you. >> That is essential. If that's one of the lessons we've learned in the last couple of years, not if, but when. >> Nick: Yes. >> Talk to me about customers that are using the platform. What are some of the, using it well. What are some of the things that they have in common? >> You know, I think the organizations that are implementing it well, look for it. They view it as a real platform. You know, historically, supply chain design, network optimization, was seen as a tool, and companies implement it as a tool. You purchase licenses, you assign a couple of people to work on it from your analytical department and you just went with it. This is a very powerful platform to completely revolutionize how you make decisions within your supply chain. And you need to approach it the same way you approach a new warehouse management system, a new planning platform, a new labor management system, the change management aspects, the organizational aspects, the education of stakeholders on what is this, demystifying it. So it's not a black box and everybody knows what it can and should do and how best to utilize it. So those organizations that view it as more than a distribution network tool, "Hey, where do I put my new warehouse? Hey, this lease is coming up in Central Europe. It's coming up in Ohio. Do I extend the lease? Do I need to move?" That's, like, a level zero maturity on our maturity graph. The very mature companies are using it and infusing it both strategically, operational, technically, and are using it for distribution decisions, transportation decisions around mode selection, production footprint decisions. You have the capability to have a digital twin. And by having, the other thing companies struggle with is, they just build one model. >> Uh-hmm. >> I start out, I buy the product. You know, I get it built in, I move everything to the cloud and then I do a distribution solve for the U.S. And then the European group says, "Hey, that was great. That was insightful. Can we do the same thing in Europe?" And you take that model and then you add Europe into it. And then the production group says, "Hey, you know, we're thinking about changing some of our make-buy decisions. Can you model what the effect would be on total cost if we did do some nearshoring?" And all of a sudden, you turn your one model that you had built for a specific purpose into this Christmas tree where everybody's hanging their ornaments. And what you really need to do is having a modeling strategy. What type, you should have a volume, a portfolio of models you can pull from and say, "Hey, here's our strategic end to end model. Hey, here's our tactical Asian production models. Hey, here's our total landed cost for top 15% of our customers." And having that set of models, so you have right models, the right questions. >> Uh-hmm. >> That's what the companies that are really scaling this and really excelling. And you'll notice a pattern. The companies that are excelling that have the Coupa platform, typically, you'll find them on list, like, Gartner's Top 25 and things along those lines. Because it is a very powerful platform when you unlock the art of the possible with it. >> Sounds, like, those are companies that are very innovative. But where does the company, that maybe isn't there yet? How do they start? 'Cause it sounds, like, there's a tremendous wealth of potential and opportunities that the technology can deliver. Do they have to start with executive buy-in? What do you see as kind of, like, some of those early steps? >> This is a change management exercise from the very beginning. So creating that sense of urgency, creating your powerful coalition. You have to start with that. If you view this as, "Hey, we're going to have a tool, we're going to use this once, and then our supply chain's fixed for the next 10 years." I mean, I think most leaders are realizing that those days are long gone. That supply chain design has to be a continual topic at the top levels. You know, supply chain is on the lips of every politician and every (chuckles) board member right now. So this is a wonderful moment for those supply chain leaders that have wanted to infuse a greater level of digital decision-making. This is the perfect opportunity. You can get buy-in, like, you never had before. Your CFO is probably analyzing labor inflation, fuel inflation rates, disruptions on supply base, and you're probably having to deal with more pressure out of the CFO and its department than you ever had to in the past. We see it with our clients. The pressure is on with those leaders. And this allows you to very quickly be much more holistic in that decision-making. You're not relying on how good was the analyst, that made this Excel file that told you to open up this plan, move this distribution center, serve this customer base in this way. It's not based on how that data looks and how good that analyst was, you're infusing an entire practice into your organization. >> That's critical, because every company these days is a data company. If they're not, they're not going to be around. It's about the ability to have visibility extract the value from the data to make those data-driven decisions, because we don't have time. We heard a lot about that from a real-time perspective and the keynote this morning that's table stakes run any organization. >> Yeah, and with the move of the platform to the cloud, as part of the Coupa ecosystem, with the DDM, with the rapid model builder, and all those things that come along with it, it will significantly squash the amount out of time you have from question to answer. Because the first time you do this, it probably takes four months. And of that four months to ask that question, and get an answer, build your model, you know, replicate the 3D world in that 2D environment. Over half of that time is spent on cleaning data, building the baseline model, aligning with finance, they peanut butter spread certain aspects of cost onto the onto SKUs and really getting correct cost allocations for A, B, and C SKUs. You spend half your time just playing around with your data to get the model to work right now. Once you add that model, next time, question and answer infinitely quicker. But you have to have a good data strategy. You have to have the right data architecture. If you don't have that specific to supply chain, leaders really need to get on that. Because what we see a lot of times is organizations will have an enterprise data strategy. >> Uh-hmm. >> And they're going to build a data warehouse or a data lake, you know, whatever, I'm a consultant, so I'm also guilty of the buzz words. But, we kind of call it the supply chain data plan. You don't need to wait for the whole enterprise to get ready to have all of your data sorted out in a single instance, homogenize. Start collecting that supply chain data, have a data strategy around it. So that way, you can start replicating these things then you can feed it back into the enterprise data strategy. But you have to get your data right. It's the old adage garbage in garbage out. >> Right. >> It's still true to this day. No matter how powerful the analytical tools are, we're infusing machine learning, artificial intelligence into some of the solves in the platform. But if you don't have that good data, you're going to struggle. So that's a key piece to it, getting that executive buy-in and having that right data strategy will set you on a much smoother path to success than if you don't do those things. >> Right, the data strategy is critical. If not, one of the biggest competitive differentiators these days. Where is the chief data officer, the chief digital officer, the chief information officer, in these conversations that Miebach is having with customers? >> Too often, not at the forefront enough. >> Lisa: Really? >> Those clients that have that group, have that organization, and they have influencing power, those programs go much quicker, much simpler. The rate of adoption, the scalability of the program. All of a sudden, you're not thinking about, "What am I going to do with one or two analysts interacting with the product?" You're now developing apps. You have your planners interfacing with it. You have capacity managers interacting with the digital model. Those that don't have that, do have much more impetus, because it's always the adage of, "Oh, IT, what do we do? And our data's a mess. We have this data program and our IT resources are super constrained." So you have to bring those people to the table. You have to have them part of the conversation, 'cause they can be an incredible enabler if you bring them and get them bought in. >> That's a great point of those enablers. And especially, given the fact that nobody has extra time to waste here. This is a, everything is so fast moving. You mentioned supply chain being on the lips of every politician. Everybody's lips, everybody's expecting some delivery that is delayed for whatever reason. >> I mean, 12 years ago when I started with the firm, and people, "Oh, what does the firm do?" I'm like, "Oh we're a global supply chain consultancy." And they're like, "What?" >> Yeah. (laughs) >> You know, now everybody knows. And they're like, "Oh, yeah!" It's amazing that the revolution, I mean, the pandemic has been incredibly unfortunate with all the hardships and deaths and everything and still dealing with hotspots and things. I think it did bring supply chain, supply chain was struggling for a while to get a seat at the table. Organizations started having chief supply chain officers. You know, that was a new thing not that long ago. This has brought table stakes to the supply chain organization. My challenge back to us is what do we do with this now? >> Right. >> For years, as an industry, we've asked to be at the table, we're here now, spotlight's on us. It's time for us to deliver. Things like the Coupa platform are an incredible enabler of that. But you got to get it right when you roll it out. >> The spotlight's on you, but there's also a skill shortage. Talk to me about that. I just saw you do a big sigh. How can Miebach and Coupa with this platform help to mitigate some of the supply chain skills gap that organizations in every industry are facing? >> You know, it really comes down to the human element and when people talk a lot about sustainability, they talk about environmental conditions. There's a human sustainability topic we have to cover. Nobody likes being assigned to be a data analyst on a transformational project. And you're crunching Excel spreadsheets and running it sequel coding. No, no, that's not an enjoyable fulfilling task for many people. >> Lisa: No. >> There are special people that it is, and God bless (chuckles) them. So with things, like, the apps, with things, like, building out, so that way, we can take the people that you do have and have them making decisions, driving discussions around the insights the platform's giving versus just crunching numbers and building models. This is where you're going to have a much higher retainment. People are going to be excited about the job. They're going to have fun at the job because you do see a turnover of organizations that don't get the data strategy right, that people don't like being in a supply chain center of excellence in perpetuity. Again, there are certain people that are, but a lot of times, once the people get this analytical insight to how strategically the design of the company is set up, business units will grab them and give them a significant role. And then you're continually churning and replacing your COE talent. So having a talent strategy for your COE and having a strategy of how you're going to leverage, you know, we're in a world where my first grader's are learning coding, right? Like, you need to have a data strategy. So that way, that becomes your people strategy as well. And too many times, people think, "Hey, I buy the platform. I need a project strategy. What are the projects we're going to do?" And not often enough, do they talk about the people element of it to really make this work. And it absolutely has to be part of the discussion as you're setting up your center of excellence, it's people, it's processes and it's technology. >> Absolutely! >> You got to bring those three together or you real struggle a bit. >> You do. And then change management is not an easy thing to do for anybody. But one of the things you talked about, this is the pandemic as an accelerator of getting the supply chain folks to the table, being able to accelerate, getting data into the hands of people that can actually take in clean insights and make decisions based on that. So if you look into a crystal ball, what's the future of supply chain design? Where is it going? >> I believe we're going to see a lot more of movement towards applications and infusing of artificial intelligence and machine learning. It's there. It's ready to go. What a lot of companies are lacking and it goes back to what we already talked about is the data piece of it. I mean, we have been developing algorithms in a machine learning environment for three, four years now. It goes back to garbage in, and garbage out. So I think it's going to be a big element of supply chain talent, securing that, figuring out with robotic product process automation and things like that. How do you take non-value added work so you can take the talent you do have and give them more fulfilling work? I think companies are going to need to have data strategies and all that unlocks applications and things. So you can democratize, right? You have this digital twin in the cloud. How many people within the organization cross-functionally have questions about the supply chain? >> Right. >> What if this happens? What if that happens? Hey, if we do this, what does it effect upstream downstream? >> Right. >> So once you build that cloud, develop the applications that allow the entire enterprise to interface with this digital representation to play around and see what the effect is to then make better, more informed, more holistic decisions, drive more conversational, cross functionally amongst leaders, and even below the top leadership level. I think this is really where we're going to go and the companies that don't just survive, but thrive in this new normal, whatever that's going to be, is going to be the companies that get that right. >> They have to embrace that. There's no doubt. >> Nick: Have to embrace it. >> Nick, it's been great having you on the program, talking about supply chain, what's going on there, the accelerators, but also the opportunities. Thank you so much for sharing your insights. >> I appreciate the opportunity. So it's been a great conversation. I look forward to the rest of the event! >> I agree. For Nick Banich, I'm Lisa Martin on the ground in Las Vegas at Coupa Inspire 2022. Stick around, I'll be back with my next guest shortly. (bright music)

(upbeat music) >> Welcome everyone, this is Stephanie Chan with theCUBE. Recently analyst Dave Ross RADIO entitled, Pat Gelsinger has a vision. It just needs the time, the cash and a miracle where he highlights why he thinks Intel is years away from reversing position in the semiconductor industry. Welcome Dave. >> Hey thanks, Stephanie. Good to see you. >> So, Dave you been following the company closely over the years. If you look at Wall Street Journal most analysts are saying to hold onto Intel. can you tell us why you're so negative on it? >> Well, you know, I'm not a stock picker Stephanie, but I've seen the data there are a lot of... some buys some sells, but most of the analysts are on a hold. I think they're, who knows maybe they're just hedging their bets they don't want to a strong controversial call that kind of sitting in the fence. But look, Intel still an amazing company they got tremendous resources. They're an ICON and they pay a dividend. So, there's definitely an investment case to be made to hold onto the stock. But I would generally say that investors they better be ready to hold on to Intel for a long, long time. I mean, Intel's they're just not the dominant player that it used to be. And the challenges have been mounting for a decade and look competitively Intel's fighting a five front war. They got AMD in both PCs and the data center the entire Arm Ecosystem` and video coming after with the whole move toward AI and GPU they're dominating there. Taiwan Semiconductor is by far the leading fab in the world with terms of output. And I would say even China is kind of the fifth leg of that stool, long term. So, lot of hurdles to jump competitively. >> So what are other sources of Intel's trouble sincere besides what you just mentioned? >> Well, I think they started when PC volumes peaked which was, or David Floyer, Wikibon wrote back in 2011, 2012 that he tells if it doesn't make some moves, it's going to face some trouble. So, even though PC volumes have bumped up with the pandemic recently, they pair in comparison to the wafer volume that are coming out of the Arm Ecosystem, and TSM and Samsung factories. The volumes of the Arm Ecosystem, Stephanie they dwarf the output of Intel by probably 10 X in semiconductors. I mean, the volume in semiconductors is everything. And because that's what costs down and Intel they just knocked a little cost manufacture any anymore. And in my view, they may never be again, not without a major change in the volume strategy, which of course Gelsinger is doing everything he can to affect that change, but they're years away and they're going to have to spend, north of a 100 billion dollars trying to get there, but it's all about volume in the semiconductor game. And Intel just doesn't have it right now. >> So you mentioned Pat Gelsinger he was a new CEO last January. He's a highly respected CEO and in truth employed more than four decades, I think he has knowledge and experience. including 30 years at Intel where he began his career. What's your opinion on his performance thus far besides the volume and semiconductor industry position of Intel? >> Well, I think Gelsinger is an amazing executive. He's a technical visionary, he's an execution machine, he's doing all the right things. I mean, he's working, he was at the state of the union address and looking good in a suit, he's saying all the right things. He's spending time with EU leaders. And he's just a very clear thinker and a super strong strategist, but you can't change Physics. The thing about Pat is he's known all along what's going on with Intel. I'm sure he's watched it from not so far because I think it's always been his dream to run the company. So, the fact that he's made a lot of moves. He's bringing in new management, he's repairing some of the dead wood at Intel. He's launched, kind of relaunched if you will, the Foundry Business. But I think they're serious about that. You know, this time around, they're spinning out mobile eye to throw off some cash mobile eye was an acquisition they made years ago to throw off some more cash to pay for the fabs. They have announced things like; a fabs in Ohio, in the Heartland, Ze in Heartland which is strikes all the right chords with the various politicians. And so again, he's doing all the right things. He's trying to inject. He's calling out his best Andrew Grove. I like to say who's of course, The Iconic CEO of Intel for many, many years, but again you can't change Physics. He can't compress the cycle any faster than the cycle wants to go. And so he's doing all the right things. It's just going to take a long, long time. >> And you said that competition is better positioned. Could you elaborate on why you think that, and who are the main competitors at this moment? >> Well, it's this Five Front War that I talked about. I mean, you see what's happened in Arm changed everything, Intel remember they passed on the iPhone didn't think it could make enough money on smartphones. And that opened the door for Arm. It was eager to take Apple's business. And because of the consumer volumes the semiconductor industry changed permanently just like the PC volume changed the whole mini computer business. Well, the smartphone changed the economics of semiconductors as well. Very few companies can afford the capital expense of building semiconductor fabrication facilities. And even fewer can make cutting edge chips like; five nanometer, three nanometer and beyond. So companies like AMD and Invidia, they don't make chips they design them and then they ship them to foundries like TSM and Samsung to manufacture them. And because TSM has such huge volumes, thanks to large part to Apple it's further down or up I guess the experience curve and experience means everything in terms of cost. And they're leaving Intel behind. I mean, the best example I can give you is Apple would look at the, a series chip, and now the M one and the M one ultra, I think about the traditional Moore's law curve that we all talk about two X to transistor density every two years doubling. Intel's lucky today if can keep that pace up, let's assume it can. But meanwhile, look at Apple's Arm based M one to M one Ultra transition. It occurred in less than two years. It was more like, 15 or 18 months. And it went from 16 billion transistors on a package to over a 100 billion. And so we're talking about the competition Apple in this case using Arm standards improving it six to seven X inside of a two year period while Intel's running it two X. And that says it all. So Intel is on a curve that's more expensive and slower than the competition. >> Well recently, until what Lujan Harrison did with 5.4 billion So it can make more check order companies last February I think the middle of February what do you think of that strategic move? >> Well, it was designed to help with Foundry. And again, I said left that out of my things that in Intel's doing, as Pat's doing there's a long list actually and many more. Again I think, it's an Israeli based company they're a global company, which is important. One of the things that Pat stresses is having a a presence in Western countries, I think that's super important, he'd like to get the percentage of semiconductors coming out of Western countries back up to at least maybe not to where it was previously but by the end of the decade, much more competitive. And so that's what that acquisition was designed to do. And it's a good move, but it's, again it doesn't change Physics. >> So Dave, you've been putting a lot of content out there and been following Intel for years. What can Intel do to go back on track? >> Well, I think first it needs great leadership and Pat Gelsinger is providing that. Since we talked about it, he's doing all the right things. He's manifesting his best. Andrew Grove, as I said earlier, splitting out the Foundry business is critical because we all know Moore's law. This is Right Law talks about volume in any business not just semiconductors, but it's crucial in semiconductors. So, splitting out a separate Foundry business to make chips is important. He's going to do that. Of course, he's going to ask Intel's competitors to allow Intel to manufacture their chips which they very well may well want to do because there's such a shortage right now of supply and they need those types of manufacturers. So, the hope is that that's going to drive the volume necessary for Intel to compete cost effectively. And there's the chips act. And it's EU cousin where governments are going to possibly put in some money into the semiconductor manufacturing to make the west more competitive. It's a key initiative that Pat has put forth and a challenge. And it's a good one. And he's making a lot of moves on the design side and committing tons of CapEx in these new fabs as we talked about but maybe his best chance is again the fact that, well first of all, the market's enormous. It's a trillion dollar market, but secondly there's a very long term shortage in play here in semiconductors. I don't think it's going to be cleared up in 2022 or 2023. It's just going to be keep being an explotion whether it's automobiles and factory devices and cameras. I mean, virtually every consumer device and edge device is going to use huge numbers of semiconductor chip. So, I think that's in Pat's favor, but honestly Intel is so far behind in my opinion, that I hope by the end of this decade, it's going to be in a position maybe a stronger number two position, and volume behind TSM maybe number three behind Samsung maybe Apple is going to throw Intel some Foundry business over time, maybe under pressure from the us government. And they can maybe win that account back but that's still years away from a design cycle standpoint. And so again, maybe in the 2030's, Intel can compete for top dog status, but that in my view is the best we can hope for this national treasure called Intel. >> Got it. So we got to leave it right there. Thank you so much for your time, Dave. >> You're welcome Stephanie. Good to talk to you >> So you can check out Dave's breaking analysis on theCUBE.net each Friday. This is Stephanie Chan for theCUBE. We'll see you next time. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> If it weren't for Pat Gelsinger, Intel's future would be a disaster. Even with his clear vision, fantastic leadership, deep technical and business acumen, and amazing positivity, the company's future is in serious jeopardy. It's the same story we've been telling for years. Volume is king in the semiconductor industry, and Intel no longer is the volume leader. Despite Intel's efforts to change that dynamic With several recent moves, including making another go at its Foundry business, the company is years away from reversing its lagging position relative to today's leading foundries and design shops. Intel's best chance to survive as a leader in our view, will come from a combination of a massive market, continued supply constraints, government money, and luck, perhaps in the form of a deal with apple in the midterm. Hello, and welcome to this week's "Wikibon CUBE Insights, Powered by ETR." In this "Breaking Analysis," we'll update you on our latest assessment of Intel's competitive position and unpack nuggets from the company's February investor conference. Let's go back in history a bit and review what we said in the early 2010s. If you've followed this program, you know that our David Floyer sounded the alarm for Intel as far back as 2012, the year after PC volumes peaked. Yes, they've ticked up a bit in the past couple of years but they pale in comparison to the volumes that the ARM ecosystem is producing. The world has changed from people entering data into machines, and now it's machines that are driving all the data. Data volumes in Web 1.0 were largely driven by keystrokes and clicks. Web 3.0 is going to be driven by machines entering data into sensors, cameras. Other edge devices are going to drive enormous data volumes and processing power to boot. Every windmill, every factory device, every consumer device, every car, will require processing at the edge to run AI, facial recognition, inference, and data intensive workloads. And the volume of this space compared to PCs and even the iPhone itself is about to be dwarfed with an explosion of devices. Intel is not well positioned for this new world in our view. Intel has to catch up on the process, Intel has to catch up on architecture, Intel has to play catch up on security, Intel has to play catch up on volume. The ARM ecosystem has cumulatively shipped 200 billion chips to date, and is shipping 10x Intel's wafer volume. Intel has to have an architecture that accommodates much more diversity. And while it's working on that, it's years behind. All that said, Pat Gelsinger is doing everything he can and more to close the gap. Here's a partial list of the moves that Pat is making. A year ago, he announced IDM 2.0, a new integrated device manufacturing strategy that opened up its world to partners for manufacturing and other innovation. Intel has restructured, reorganized, and many executives have boomeranged back in, many previous Intel execs. They understand the business and have a deep passion to help the company regain its prominence. As part of the IDM 2.0 announcement, Intel created, recreated if you will, a Foundry division and recently acquired Tower Semiconductor an Israeli firm, that is going to help it in that mission. It's opening up partnerships with alternative processor manufacturers and designers. And the company has announced major investments in CAPEX to build out Foundry capacity. Intel is going to spin out Mobileye, a company it had acquired for 15 billion in 2017. Or does it try and get a $50 billion valuation? Mobileye is about $1.4 billion in revenue, and is likely going to be worth more around 25 to 30 billion, we'll see. But Intel is going to maybe get $10 billion in cash from that, that spin out that IPO and it can use that to fund more FABS and more equipment. Intel is leveraging its 19,000 software engineers to move up the stack and sell more subscriptions and high margin software. He got to sell what he got. And finally Pat is playing politics beautifully. Announcing for example, FAB investments in Ohio, which he dubbed Silicon Heartland. Brilliant! Again, there's no doubt that Pat is moving fast and doing the right things. Here's Pat at his investor event in a T-shirt that says, "torrid, bringing back the torrid pace and discipline that Intel is used to." And on the right is Pat at the State of the Union address, looking sharp in shirt and tie and suit. And he has said, "a bet on Intel is a hedge against geopolitical instability in the world." That's just so good. To that statement, he showed this chart at his investor meeting. Basically it shows that whereas semiconductor manufacturing capacity has gone from 80% of the world's volume to 20%, he wants to get it back to 50% by 2030, and reset supply chains in a market that has become important as oil. Again, just brilliant positioning and pushing all the right hot buttons. And here's a slide underscoring that commitment, showing manufacturing facilities around the world with new capacity coming online in the next few years in Ohio and the EU. Mentioning the CHIPS Act in his presentation in The US and Europe as part of a public private partnership, no doubt, he's going to need all the help he can get. Now, we couldn't resist the chart on the left here shows wafer starts and transistor capacity growth. For Intel, overtime speaks to its volume aspirations. But we couldn't help notice that the shape of the curve is somewhat misleading because it shows a two-year (mumbles) and then widens the aperture to three years to make the curve look steeper. Fun with numbers. Okay, maybe a little nitpick, but these are some of the telling nuggets we pulled from the investor day, and they're important. Another nitpick is in our view, wafers would be a better measure of volume than transistors. It's like a company saying we shipped 20% more exabytes or MIPS this year than last year. Of course you did, and your revenue shrank. Anyway, Pat went through a detailed analysis of the various Intel businesses and promised mid to high double digit growth by 2026, half of which will come from Intel's traditional PC they center in network edge businesses and the rest from advanced graphics HPC, Mobileye and Foundry. Okay, that sounds pretty good. But it has to be taken into context that the balance of the semiconductor industry, yeah, this would be a pretty competitive growth rate, in our view, especially for a 70 plus billion dollar company. So kudos to Pat for sticking his neck out on this one. But again, the promise is several years away, at least four years away. Now we want to focus on Foundry because that's the only way Intel is going to get back into the volume game and the volume necessary for the company to compete. Pat built this slide showing the baby blue for today's Foundry business just under a billion dollars and adding in another $1.5 billion for Tower Semiconductor, the Israeli firm that it just acquired. So a few billion dollars in the near term future for the Foundry business. And then by 2026, this really fuzzy blue bar. Now remember, TSM is the new volume leader, and is a $50 billion company growing. So there's definitely a market there that it can go after. And adding in ARM processors to the mix, and, you know, opening up and partnering with the ecosystems out there can only help volume if Intel can win that business, which you know, it should be able to, given the likelihood of long term supply constraints. But we remain skeptical. This is another chart Pat showed, which makes the case that Foundry and IDM 2.0 will allow expensive assets to have a longer useful life. Okay, that's cool. It will also solve the cumulative output problem highlighted in the bottom right. We've talked at length about Wright's Law. That is, for every cumulative doubling of units manufactured, cost will fall by a constant percentage. You know, let's say around 15% in semiconductor world, which is vitally important to accommodate next generation chips, which are always more expensive at the start of the cycle. So you need that 15% cost buffer to jump curves and make any money. So let's unpack this a bit. You know, does this chart at the bottom right address our Wright's Law concerns, i.e. that Intel can't take advantage of Wright's Law because it can't double cumulative output fast enough? Now note the decline in wafer starts and then the slight uptick, and then the flattening. It's hard to tell what years we're talking about here. Intel is not going to share the sausage making because it's probably not pretty, But you can see on the bottom left, the flattening of the cumulative output curve in IDM 1.0 otherwise known as the death spiral. Okay, back to the power of Wright's Law. Now, assume for a second that wafer density doesn't grow. It does, but just work with us for a second. Let's say you produce 50 million units per year, just making a number up. That gets you cumulative output to $100 million in, sorry, 100 million units in the second year to take you two years to get to that 100 million. So in other words, it takes two years to lower your manufacturing cost by, let's say, roughly 15%. Now, assuming you can get wafer volumes to be flat, which that chart showed, with good yields, you're at 150 now in year three, 200 in year four, 250 in year five, 300 in year six, now, that's four years before you can take advantage of Wright's Law. You keep going at that flat wafer start, and that simplifying assumption we made at the start and 50 million units a year, and well, you get to the point. You get the point, it's now eight years before you can get the Wright's Law to kick in, and you know, by then you're cooked. But now you can grow the density of transistors on a chip, right? Yes, of course. So let's come back to Moore's Law. The graphic on the left says that all the growth is in the new stuff. Totally agree with that. Huge term that Pat presented. Now he also said that until we exhaust the periodic table of elements, Moore's Law is alive and well, and Intel is the steward of Moore's Law. Okay, that's cool. The chart on the right shows Intel going from 100 billion transistors today to a trillion by 2030. Hold that thought. So Intel is assuming that we'll keep up with Moore's Law, meaning a doubling of transistors every let's say two years, and I believe it. So bring that back to Wright's Law, in the previous chart, it means with IDM 2.0, Intel can get back to enjoying the benefits of Wright's Law every two years, let's say, versus IDM 1.0 where they were failing to keep up. Okay, so Intel is saved, yeah? Well, let's bring into this discussion one of our favorite examples, Apple's M1 ARM-based chip. The M1 Ultra is a new architecture. And you can see the stats here, 114 billion transistors on a five nanometer process and all the other stats. The M1 Ultra has two chips. They're bonded together. And Apple put an interposer between the two chips. An interposer is a pathway that allows electrical signals to pass through it onto another chip. It's a super fast connection. You can see 2.5 terabytes per second. But the brilliance is the two chips act as a single chip. So you don't have to change the software at all. The way Intel's architecture works is it takes two different chips on a substrate, and then each has its own memory. The memory is not shared. Apple shares the memory for the CPU, the NPU, the GPU. All of it is shared, meaning it needs no change in software unlike Intel. Now Intel is working on a new architecture, but Apple and others are way ahead. Now let's make this really straightforward. The original Apple M1 had 16 billion transistors per chip. And you could see in that diagram, the recently launched M1 Ultra has $114 billion per chip. Now if you take into account the size of the chips, which are increasing, and the increase in the number of transistors per chip, that transistor density, that's a factor of around 6x growth in transistor density per chip in 18 months. Remember Intel, assuming the results in the two previous charts that we showed, assuming they were achievable, is running at 2x every two years, versus 6x for the competition. And AMD and Nvidia are close to that as well because they can take advantage of TSM's learning curve. So in the previous chart with Moore's Law, alive and well, Intel gets to a trillion transistors by 2030. The Apple ARM and Nvidia ecosystems will arrive at that point years ahead of Intel. That means lower costs and significantly better competitive advantage. Okay, so where does that leave Intel? The story is really not resonating with investors and hasn't for a while. On February 18th, the day after its investor meeting, the stock was off. It's rebound a little bit but investors are, you know, they're probably prudent to wait unless they have really a long term view. And you can see Intel's performance relative to some of the major competitors. You know, Pat talked about five nodes in for years. He made a big deal out of that, and he shared proof points with Alder Lake and Meteor Lake and other nodes, but Intel just delayed granite rapids last month that pushed it out from 2023 to 2024. And it told investors that we're going to have to boost spending to turn this ship around, which is absolutely the case. And that delay in chips I feel like the first disappointment won't be the last. But as we've said many times, it's very difficult, actually, it's impossible to quickly catch up in semiconductors, and Intel will never catch up without volume. So we'll leave you by iterating our scenario that could save Intel, and that's if its Foundry business can eventually win back Apple to supercharge its volume story. It's going to be tough to wrestle that business away from TSM especially as TSM is setting up shop in Arizona, with US manufacturing that's going to placate The US government. But look, maybe the government cuts a deal with Apple, says, hey, maybe we'll back off with the DOJ and FTC and as part of the CHIPS Act, you'll have to throw some business at Intel. Would that be enough when combined with other Foundry opportunities Intel could theoretically produce? Maybe. But from this vantage point, it's very unlikely Intel will gain back its true number one leadership position. If it were really paranoid back when David Floyer sounded the alarm 10 years ago, yeah, that might have made a pretty big difference. But honestly, the best we can hope for is Intel's strategy and execution allows it to get competitive volumes by the end of the decade, and this national treasure survives to fight for its leadership position in the 2030s. Because it would take a miracle for that to happen in the 2020s. Okay, that's it for today. Thanks to David Floyer for his contributions to this research. Always a pleasure working with David. Stephanie Chan helps me do much of the background research for "Breaking Analysis," and works with our CUBE editorial team. Kristen Martin and Cheryl Knight to get the word out. And thanks to SiliconANGLE's editor in chief Rob Hof, who comes up with a lot of the great titles that we have for "Breaking Analysis" and gets the word out to the SiliconANGLE audience. Thanks, guys. Great teamwork. Remember, these episodes are all available as podcast wherever you listen. Just search "Breaking Analysis Podcast." You'll want to check out ETR's website @etr.ai. We also publish a full report every week on wikibon.com and siliconangle.com. You could always get in touch with me on email, david.vellante@siliconangle.com or DM me @dvellante, and comment on my LinkedIn posts. This is Dave Vellante for "theCUBE Insights, Powered by ETR." Have a great week. Stay safe, be well, and we'll see you next time. (upbeat music)

>>mm We're entering the fourth grade era of VM ware Executive management From its beginnings in the late 90s is a Silicon Valley startup. It's five founders quickly built the company and it ended up as one of the greatest acquisitions in the history of enterprise tech when EMC bought VM ware for $625 million as a public company. But still under EMC's governance, paul Maritz was appointed Ceo in 2000 and eight and set the company on a journey to build what he called at the time. The software mainframe meaning the company's platform would run any application at high performance with low overhead and world class recovery. Pat Gelsinger took over the Ceo reins in 2012 and through organic investments and clever m and a set of course for the software defined data center and after some early miscalculations in cloud, realigned the company strategy to successfully partner with hyper scale hours and position the company for the multi cloud future. The hallmarks of VM where over the course of its history have been great engineering that led to great products, loyal customers and a powerful ecosystem. The other telling attribute of VM where is it? CEOs have always had a deep understanding of technology and its latest Ceo is no different. It's our pleasure to welcome raghu Raghuram back to the cube the fourth Ceo of VM ware and yet another Silicon Valley Ceo graduated from the IIttie rgu, great to see you again and congratulations on your new role. >>Thanks. It's great to be here. >>Okay, five months in 1st 100 days what we have focused on that journey to become the Switzerland of multi cloud, tell us about your early experience as ceo >>it's been fantastic. Uh our customers, all our employees, all our partners have been very welcoming and of course I've given me great input. What we've been able to do in the last 100 days is to really crystallize the strategy and focus it around what I'm sure we're gonna be spending a lot of time talking about. And that's about the multi cloud era of computing that most enterprises are going to go through over the next decade. And so that's really what I've been up to and you'll see the results of that in next week's uh we involved and uh where we would be talking about the strategy and some product announcements that go along with the strategy and so it's a very exciting time to be at Vandenberg. >>Yeah, I mean, I referenced it in my intro, it's almost like the light bulb went off when VM ware realized, wow, this cloud build out is just an opportunity for us and that's really what you're doing with the multi cloud as you're building on top of all the infrastructure that the hyper cloud vendors are putting out there. Maybe you can talk about that, that opportunity and what customers are telling you. >>Yeah, it's uh here is how I describe what has happened in the industry. Right, and what will happen in the industry. So, if you look at the the past decade, as cloud became a mainstream thing, most customers pick the cloud, they built their first digital applications into it, the ones that serve their mobile users or end users with digital products and that worked great for them. Then they step back and say, okay, how many modernize everything that we're doing has become a digital company. And when you go from 10, of your portfolio, 100% of your application portfolio being modernized. What has to happen is you got to go from figuring out, okay, how am I gonna put everything in one cloud to what does the application need and how do I put it on the right place? I look at the same time, the industry has also evolved from being uh predominantly supplied by one cloud provider to multiple cloud providers. At the same time, the thanks to companies like IBM where the data center has been transformed into a private cloud. The edges growing up to be its own location for a cloud sovereign clouds are going. So truly what has happened is it's become a multi cloud world. And customers are saying in addition to just being cloud first, I want to be cloud smart. And so this distributed era of computing that we are entering is what we are seeing in the industry. And what the empire is trying to do is to say, look, let's provide customers with the fastest way of getting to this multi cloud era of computing so that they can go fast, they can spend less and most importantly, they can be free, in other words, choose the right application, right cloud for right applications and have control over how they deploy and use their applications and data. That really is a strategy that we are putting in place. This is something that we've been working towards in the last couple of years now. I'm accelerating that and making that the main piece of what we end, where is doing in order to do that, we have a great opportunity to take partner even better with all of our cloud provider partners and that's where the Switzerland of the industry comes in without impending spin, especially, we have great partnership with the cloud players, great partnerships with infrastructure players. We truly can be a neutral partner to the customers as they look at all these choices and make the right choices for their applications. >>So, I want to ask you about this multi cloud when when the early multi cloud narrative came out where I go, I was saying, look, multi cloud is really multi vendor, you you've got workloads and apps running on different, different clouds. And then increasingly, the promise and your promises, we're going to abstract the underlying complexity of those clouds and we're going to give you an experience whether it's on premise, hybrid into a cloud. Across clouds. Eventually out to the edge, it's gonna be a singular, substantially identical, if not identical experience and we're going to manage the whole kit and caboodle. And how where are we in that first of all? Is that the right way to think about it? Where are we in that sort of transition from plugging into any, you know, a cloud? I'm compatible with the cloud to it's a singular sort of VM ware cloud if you will. >>Yeah. So, um, so I wanna clarify something that he said because this tends to be very commonly confused by customers use the word abstraction. And usually when people think of abstraction, they think it hides capabilities of the uh, cloud providers. That's not what we are trying to. In fact, that's the last thing we're trying to do. What we're trying to do is to provide a consistent developer experience regardless of where you want to build your application so that you can use the cloud provider services if that's what you want to use. But the deficit cops toolchain, the runtime environment, which turns out to be Cuban aires and how you control the kubernetes environment. How do you manage and secure and connect all of these things. Those are the places where we are adding the value. Right. And so really the VM ware value proposition is you can build on the cloud of your choice but providing these consistent elements. Number one, you can make better use of us, your scarce developer or operator resources and expertise. Right. And number two, you can move faster and number three can spend less as a result of this. So that's really what we're trying to do, but not. So I just wanted to clarify the word abstraction in terms of their way, we're still, I would say in the early stages, so if you look at what customers are trying to do, they're trying to build these Greenfield applications and there is an entire ecosystem emerging around Campaneris. There is still kubernetes is not a developer platform. The developer experience on top of kubernetes is highly inconsistent. And so those are some of the areas where we are introducing new innovations with our towns, our application platform. And then if you take enterprise applications, what does it take to have enterprise applications running all the time, be entirely secure, etcetera, etcetera. That's where the we ever cloud assets that are traditionally this fear based come into play and we've got this now in all of the clouds but it's still in the early days from uh on Azure and google et cetera. How do you manage and secure those things again? We're in the early days. So that's where we are. I would say, >>yeah, thank you for that clarification, I want to sort of come back to that and just make sure we understand it. So for example, if I'm a developer and I want to take advantage of, let's say graviton uh and build an app on that, that so maybe it's some kind of data intensive app or whatever it is. I can do that. You won't restrict me from doing that at the same time. If I want to use the VM where management experience across all my clouds, I can do that as well. Is that the right way to think about it? >>Yeah, exactly. So the management experience by the way, and this is the other thing that gets missed in the remember dialogue because we've been so phenomenally successful with this fear. There's a misperception that everything we are doing atmosphere today works only on top. So everything we're doing at BM wear works only on top of the sphere. That's not the case. Take management, for example, our management portfolio is modular and independent of these, which means it can manage the Graviton application that you're building, right. It can manage a traditional, these fear based application, it can manage rage application, it can manage VM based applications, can manage computer based applications. Uh so it's truly uh, overall management layer. So that is really what we're trying to do. Same thing with our kubernetes example. Right, So our communities control plane allows you to control these kubernetes clusters. Whether the clusters are utilizing gravity and whether clusters are utilizing these fear based crew binaries environments. >>Okay, that's great. So it's kind of a set up question because my next question relates to project Monterey, Because, you know, I've always said when I write about about these things, when I saw Nitro, I saw Graviton, I saw project monitor, I said uh everybody needs a Nitro Nitro or a graviton because new workloads are coming. It's not just the X 86 can handle everything anymore asap whether it's sequel server, whatever we've got new workloads that are coming ai ml data intensive edge workloads, et cetera. Is that how we should think of? Project Monterrey. Where are you in Project Monterey? Why is it so important? Help people understand that? >>Yeah. Project mantra is super exciting for a couple of different reasons. One is uh in its first iteration and uh we announced project monitoring and last being well, we continue to build and we're making great progress along with the hardware partners that we are working with um in its first hydration it allows um um some of the functions that you would expect in the software defined data center to be offloaded into these montri processors. The smart nick processes. Right. So what that does, is it clears up the core CPU for other application functions. Right, so you get better scalability, more resource utilization, etcetera, etcetera. The second thing it does is because some of the software defined data center functions are done in the smart make um it gets accelerated as well. Because it takes advantage of the special accelerators that are there security functions, manageability functions, networking functions etcetera, etcetera. So that's that what you're alluding to is overall it's the v sphere, the sX Hyper Visor complimentary itself. That's moving into the specialized processors which allows the hyper Visor will be built into these smart mix, which means the main CPU can be an intel. CPU can be an M D C P. You can be an arm. CPU can be whatever it is you want in the future. So truly enables Monte CPU heterogeneous computing. So that's that's why this is exciting. And of course because it is the sphere, it can happen in the data centers, it can happen in Carlos. It can happen in Sovereign clouds. It can happen in the public clouds all over a period of time. And >>and potentially the Edge I would presume in the future. >>Sorry. Yeah, that's a great point. Thanks for pointing that out. In fact, the Edge is one of the most important places that will happen because we need these low latency applications such as in the telco case for example, right. Or we need these applications that have specialized processing the required. If you're setting up a cashier less store and you need to process and you need a lot of influence engines. So, Monterey helps with all of those things. >>I want to make sure our audience understands. It's because the software defined data center was awesome but but it also created waste in the sense that you have all these offload functions in storage and networking and security running on on x 86 processors which may not be the most efficient way. So emerging architectures around arm might be less expensive, maybe more cost effective, lower power. Uh maybe they do memory management differently. So there are these offload use cases. But as well you we talked about the edge there could be a lot of edge use cases that or whatever whether it's arm or in video etcetera. So now you're driving that optionality for customers so you can support more workloads of the future. >>Yeah, so this is exactly if you think about in europe when you talked about the embers evolution, the inverse core DNA has always been to master hydrogen. Itty right. And what we're seeing is this world of heterogeneous hardware coming alive. Right. You talked about Professor hydrogen Itty including GPU chips and so on. There is a memory architecture heterogeneous, their storage architecture heterogeneous. And so the idea is that regardless of what you use, how do you provide the best workload platform and a consistent way of managing all of these things and reducing the complexity while gaining the efficiency benefits and the other benefits that you talked about. >>So speaking of geniality that brings me to Tansu, you know early on people thought, oh wow containers, that's gonna kill VM where this is the opposite happened. You guys leaned in as as you have as a sign of great leadership these days. You don't get defensive, you just, you know, get the trend is your friend, as they say, give us the update on on Tan xue. Why is that so important to the future? >>Yeah. So if you look at any enterprises portfolio right, they are looking at it and saying look, there's a whole set of applications that I need to modernize. Now. The question becomes how do you modernize these applications in a way that it is essentially done with these microservices architectures and so on and so forth. In that context, how do I maximize the developer productivity and provide a great developer experience because there is not enough developers in the world to modernize every application that that's in every enterprise. Right. So, Tan xue is our answer to help enterprises modernize their applications and deliver in a way that the developed makes the developers very productive on the cloud of their choice. So that is really the strategic intent of Tancill and the core building block for Tan xue is of course kubernetes as you well know, Kubernetes has become the common infrastructure abstraction across clouds. So if you want portability for traditional VM based applications, he used this fear, if you want portability for traditional for containerized microservices applications, you assume kubernetes, that's how companies companies are thinking about it. And so that's the first thing that we did now. The second is you've got developers building applications all over the place. So now, just like you used to have physical server sprawl and now and then VM sprawl these days you have cluster sprawl, kubernetes, cluster sprawl and tons of mission control affects as a multi cloud, multi cluster kubernetes control plan works on the chaos and everything else that some of the Sun. The third point of Tanzania is the developer experience and we have introduced Andrew application platform, which is really focused on delivering a great developer experience on top of any Cuban Aires. So that's really how we're building out the towns of portfolio. And then of course we got Spring and uh as you well know a majority of enterprise applications today are java and if you want to modernize java, you use spring boot and so we had tremendous success with our uh spring boot technology and our startup, Springdale Ohio capabilities and so on and so forth. So that's the entirety of the towns of portfolio. It's multi cloud, it's kubernetes agnostic. Of course it runs great on this fear but it's really the approach making developers productive in the enterprise >>awesome. Thank you for that. I know we're tight on time but it's like speed dating with you raghu. So I'm gonna go on to another topic. Really important topic of security, you've made obviously some big acquisitions, there are things like carbon black, you've got a lot of stuff going on with, with, with endpoint, with end user computing, I'm first interested in sort of how you organize it looks like you're putting security and the networking piece together and then what's your swim lane? It seems like you're, you're focused obviously on your infrastructure. You're not trying to be all things to all people. Help us understand your strategy in that regard. >>Yeah, I mean security is a massive space, Right? And you covered very well. Hundreds and thousands of security problems that customers want to be solving. What we are focused on is how do we simplify the security problem for the customers? And we're doing it through three wells. The first one is we are baking security into the platforms that customers used ones. Right. But there are more obvious fear our workspace one, our container platform etcetera, etcetera. Right? Cloud platforms. So that's the first thing that we're doing. The second is we are putting um, bringing together, we're taking an end to end view of security, which is everything from an end user connecting from home to the corporate network or the sassy, sassy applications to the Windows devices they are using to the data center applications they're using to the club. Right? So we're taking a holistic view of security. So which means we want to combine our network security assets with our endpoint security assets with our workload security assets. That is why we bought all of those things together under one roof. And the third is we are instrumental in all of these and collecting signals from all of these and pulling it into the cloud and turning security into a machine learning and the data problem, right? And that is where the problem. Black cloud comes in and by doing that, we are able to provide a holistic view of where uh customer security posture, right? And these sensors can be on BMR platforms, on non BMR platforms etcetera. And so so that's really how we are approaching it. I mean there's the emerging industry term for a policy XDR. You might follow that. So that's really what we're trying to do. >>Outstanding. Last question and I know, I know we got to go. You mentioned the spin that's happening in november. That's an exciting time for a lot of reasons. I think the ecosystem, you know, emphasizing your independence but also gives you control of your balance sheet, regaining control of your balance sheet, tongue in cheek there. But it's important because all this, this cloud build out this multi cloud, exposing the primitives, leveraging the primitives and the A. P. I. S. Of these clouds making them identical across all these estates. That's not trivial and you're obviously gonna need resources to do that. So maybe you can talk about that and how you see the future playing out organic inorganic, maybe a little lemon A in there. What's your approach? How are you thinking about that? >>Yeah. So we are very excited with the impending spain, which like you said is on track to happen early november. Um and if you think about the spin, there are three aspects that we are excited about. The first aspect is uh we have a great relationship with Dell Tech, the company right. What we have done is we have codified that into a framework agreement that covers the gold market and technology collaboration and we are super excited by that and that baselines against what we do today and then as incentives on both sides to continue to grow that tremendously. So we're gonna continue being, doing that and that's going to continue being a great partner at the same time. From a partnership point of view, is truly going to be a Switzerland of the industry. So previously companies that were otherwise a little bit more competitive with dull now no longer have that reservation in partnering very deeply with us. I'm totally, like you said from a capital structure point of view, it gives us the flexibility to use to do em in a should we decide to do so in the future right? And use both equity and cash for them in a so so that's the capital structure, flexibility, the Switzerland positioning and the continuing great relationship with dull Those are the benefits of the spin >>love and the partner ecosystem has always been a source of, of innovation and it's a big part of the flywheel, the power of many versus the resources of one Ragu, Thanks so much for coming back in the queue. Best of luck. We're really excited for you and for the future of VM ware. >>Thank you and thanks for all the great work that you do and look forward to continuing to read your great research, >>appreciate that. And thank you for >>watching the cubes, continuous >>Coverage of VM World 2021. Keep it right there. >>Thank you. Mhm. Yeah.

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by >>Welcome to the cubes coverage of UI path forward for live from Las Vegas. We're here at the Bellagio. Lisa Martin, with Dave a long time, very excited to have in-person events back ish. I'll say we're going to be talking about automation as a boardroom imperative. We have two guests joining us here, James Matras here consulting principal. America's intelligent automation leader at UI and Irv. Dennis retired EA partner, and former CFO of HUD gentlemen. Welcome to the program. Exciting topic automation as a boardroom imperative, James says COO and start with you. How do you discuss the value of automation as being a key component and driver of transformation? >>That's a great question. I think what we've seen in the last couple of years is the evolution of what automation used to be. Two is going nine. And we've seen the shift from what we call generation one, which is very RPA centric type automation to more generation two, which is the combined integration of multiple technologies. It can target an intern process and it's quite important that you understand the pivotal shift because it's not enabling us to move from a task micro top agenda to a macro agenda actually impacts an organization at a strategic level. The ability to be able to look at processes more deeply to automate them in an end to end process collectively and use these different technologies in a synergistic manner truly becomes powerful because it shifts the narrative from a micro process agenda into more systemic area. >>So gen zero is an Emmanuel gen one is RPA point tools that individual maybe getting their personal productivity out. And then now you're saying gen three is across the enterprise. Where are we in terms of, you know, take your experience from your practical experience? Where do you think the world is? It's like probably between zero and one still. Right. But the advanced folks of thinking about gen three, w what's your, >>Yeah, it's a great question. And, um, when you and I, I can do the comparison being private and public sector on this because I was 37 years with E Y then went into retirement and CFL at HUD CFO. Ed was, was a HUD was nowhere. They had to just do all the intelligence digitalization, um, throughout, uh, from scratch. The private sector is probably five or six years ahead of them. But when you think about James talks about the gen one, two and three, the private sector is probably somewhere between two and three. And I know we're talking about the board in this conversation. Um, boards probably have one and two on their radar. Some boards may have three, some may not, but that's where the real strategic focus for boards needs to be is looking forward and, and getting ahead. But I think from a public sector standpoint, lot to go private sector, more to go as well. But, uh, there's a, there's a bit of a gap, but the public sector is probably only about three or four years behind the private sector >>To be okay. Let's look at the numbers, look at, look at the progress for the quarter. And now it's like discussion on cyber discussion on digital discussion on automated issue. It really changed the narrative over the last decade. >>Yeah, I think when you think of boards today, the lots of conversation on cyber that that conversation has been around for a while. A lot of conversation on ESG today, that conversation is getting, getting very popular. But I think when you think of next three, a Jen talks that bear James talks about, um, that's got to start elevating itself if it's not within the boardroom right now, because that will be the future of the company. And the way I think of it from a board's conversation is if a company doesn't think of themselves as a technology company in all aspects, no matter what you do, you are a technology company or you need to be. And if you're not thinking along that way, you're gonna, you're gonna lose market share and you're going to start falling behind your competitors. >>Well, and how much acceleration did the pandemic bring to just that organizations that weren't digital forward last year are probably gone? >>I think it certainly has shifted quite a lot. There's been a drive, the relevance of technology and hard plays for us in the modern workforce in the modern workplace has fundamentally changed the pandemic. We reimagine how we do things. Technology has progressed in itself significantly, and that made a big difference for, for all the environments as a result of that. So certainly is one of the byproducts of the pandemic has been certainly a good thing for everybody. >>Where does automation fit in the board? Virginia? You've got compensation committee. You've probably, I mean, there's somebody in charge of cyber. You got ESG now there's automation part of a broader digital agenda. Where's what's the right word. >>You know, I, I would personally put it in a enterprise risk management from a standpoint that if you're not focused on it, it's going to be a risk to the enterprise. And, um, when you think of automation and intelligent automation and RPA, uh, I think boards have a pretty good sense of how you interface with your customers and your vendors. I think a big push ought to be looking internally at your own infrastructure. You know, what are you, what are you doing in the HR space? What are you doing in a financial statement, close process? What are you doing your procurement process? I suspect there's still a lot of very routine transactions and processing within those, that infrastructure that if you just apply some RPA artificial intelligence, that data extraction techniques, you can probably eliminate a lot of man hours from the routine stuff. And, and the many man hours is probably not the right way to think of it. You could elevate people's work from being pushing numbers around to being data analyzers. And that's where the excitement is for people to see. >>It's not how it's viewed at organizations. We're not eliminating hours. Well focusing folks on much more strategic down at a test. >>Yes. I would say that that's exactly right now in the private sector, you're always going to have the efficiency play and profitability. So there will be an element of that. I know when at HUD we're, we're focused, we were not focused on eliminating hours because we needed people and we focused on creating efficiencies within the space and having people convert from, again, being Trent routine transactions, to being data analyzers and made the jobs, I'm sure. Fund for them as well. I mean, this is a lot of fun stuff. And, and if, uh, uh, companies need to be pushing this down through their entire infrastructure, not just dealing with our customers and the third parties that they deal with >>Catalyst or have been public sector. So you mentioned they may be five or six years behind, but I've seen certain public sector organizations really lean in, they learn from, from the private sector. And then even when you think about some of the military, how advanced they are absolutely. You know, the private could learn from them and if they could open it up. But >>So, yeah, I think that's, that's well said I was in this, you know, the that's the civilian part with, with the housing and urban development. I think the catalyst is, uh, bringing the expertise in, uh, I know when I, when I came, I went to HUD to elevate their financial infrastructure. It was, it was probably the worst of the cabinet agency. The financials were a mess. There was no, there was a, uh, there was not a clean audit opinion for eight years. And I was there to fix that and we fixed it through digitalization and digital transformation, as well as a financial transformation. The catalyst is just creating the education, letting people know what is, what, what technology can do. You don't have to be a programmer, but it's like driving a car. Anybody can drive a car, but we can't mechanic, you know, work as a mechanic on it. >>So I think it's creating education, letting people know what it can do. And at HUD, for example, we did a very simple, I was telling James earlier, we did a very simple RPA project on an, an, a financial statement, close process. It was 2,600 hours, six months. Once we implemented the RPA, brought that down to 70 hours, two weeks, people's eyes exploded with it. And then all of a sudden, I said, I want everyone to go back and come back with, with any manual process, any routine process that can convert to an RPA. And I got a list of a hundred, then it came then became trying to slow everything down. We're not going to do it overnight. Yeah, exactly. >>So, but it was self-funding. It was >>Self-funded. Yes. >>And, and how do you take that message to customers that it could be self-funding how how's that resonating >>Very well. And I think it was important. I always like to say, it's a point of differentiation because you look at, uh, mentioned earlier that organizations are basically technology companies. That's what they are. But now if you look across that we no longer compete at the ERP level without got SAP, Oracle, it's not a point of differentiation. We don't compete the application layer where they've got service. Now, black line, how we use them is helpful. We competed the digital layer and with automation is a major component of that. That's where your differentiation takes place. Now, if you have a point of differentiation, that is self-funding, it fundamentally changes the game. And that's why it's so important for boards to understand this, because that risk management, if you've not doing it, somebody is getting ahead of the game much faster than you are. >>Yeah. Yeah. You mentioned ERP and it, and it triggered something in my mind. Cause I, I said this 10 years ago about data. If in the nineties, you, you couldn't have picked SAP necessarily as the winner of ERP. But if you could have picked the companies that were using ERP could have made a lot of money in the stock market because they outperform their peers. And the same thing was true with data. And I think the same thing is going to be true with automation in the coming decade. >>Couldn't agree more. And I think that's exactly the point that differential acceleration happening this. And it's harder because of the Europeans. Once you knew what it was, you can put the boundaries on it. Digital, the options are infinite. It's just continuous progress as are from there. >>I've got a question for you. You talked about some great stats about how dramatically faster things were took far less time. How does that help from an adoption perspective? I know how much cultural change is very difficult for folks in any organization, but that sort of self-serving how does that help fuel adoption? >>Well, it's interesting. Um, it's, it is a, we're actually going to talk about this tomorrow. It is a framework and it's got to start at the leadership has got to start with governance. It's got to start with a detailed plan. That's executable. And it's got to start with getting buy-in from not only your, the, the organization, but the people you're dealing with outside the organization. Um, it's, it's, uh, I think that's absolutely critical. And when you bring this back to the boardroom, they are the leaders of the companies. And, and I, James, I talked about this as we're getting ready for tomorrow's session. I think the number one thing a board can do today is an own personal self assessment. Do they understand automation? Do they understand what next generation three is? Do they understand what the different components can do? And do they understand how the companies are implementing it? And if I was a board member, uh, on our boards, I say, we need to understand that or else this is nothing's going to happen. We're going to be here at the reliance of the CEO and the CFO strategy, which may or may not include or be thinking about this next three. So leadership at the top is going to drive this. And it's so critical. >>We were talking about catalyst before. And you mentioned education and expertise. I'm always curious as to what drew you to public sector because it's, yeah, I mean, very successful, you know, you're, you're with one of the global SIS directly, you can make a lot more money and that side. So what was it did, was it a desire to it's a great country? Was it >>Take one for the team and I'm going to do a selfish plug here. I just actually wrote a book in this whole thing called transforming a federal agency. What's the name of the book transforming and federal agency. And it's, uh, I spent my time at E Y for 37 years, fully retired. I wanted to give back and do meaningful work. And we lived in Columbus, Ohio, as I was talking about earlier, I was going to go teach and I got a call from the president's personnel office to see if I wanted to come. And these, the CFO at HUD with secretary Carson and change turn the agency around, uh, that took me a little while to say yes, because I wasn't sure I wanted something full time. It was a, it was in DC. So I'd be in a commuting role back and forth. My family's in Columbus. >>Um, but it was, uh, I did it and I loved it. It was, uh, I would pray, I would ask anyone that's has the ability to go into public service at any point in their career to do it. It's it was very rewarding. It was one of my favorite three years of life. And to your point, I didn't have to do it, but, uh, if I wanted to do something and give back and that met the criteria and we were very successful in turning it around with the digital transformation and a lot of stuff that we're talking about today gave me the ability to talk about it because I helped lead it >>For sharing that and did it. So did it start with the CFO's office? Because the first time I ever even heard about our RPO RPA was at a CFO conference and I started talking to him like, oh, this is going to be game changing. Is that where it started? Is that where it lands today? >>From an infrastructure standpoint, the CFO has the wonderful ability to see most processes within a company and its entire lifestyle from beginning to end. So CFO has that visibility to understand where efficiencies can happen in the process. And so the CFO plays a dramatically important role in this. And you think about a CFO's role today versus 20 years ago, it's no longer this, the bean counter rolling up numbers that become a business advisors to the board, to the CEO and to the executive suite. Um, so the CFO, I think has probably the best visibility of all the processes on a global basis. And they can see where the, the efficiencies and the implementation of automation can happen. >>So they can be catalysts and really fueling the actual >>Redesign of work. Yes, they, they, they probably need to be the catalyst. And as a board member, you want to be asking what is the CFO's strategic imperative for the next year? And if it doesn't include this, it's just got to get on the agenda. >>Well, curve ball here is his CFO question and you know, three years or two years ago, you wouldn't have even thought, I mean, let me set it up better. One of the industries that is highly automated is crypto. Yeah. You wouldn't even thought about crypto in your balance sheet a couple of years ago, but I'm not sure it's a widespread board level discussion, but as a CFO, what do you make of the trend to put Bitcoin on balance sheets? >>Yeah, I'm probably not the right person to ask because I'm a conservative guy. >>If somebody supported me and he said, Hey, why don't we put crypto on the balance sheet? >>I would get much more educated. I wouldn't shut it down. I would put it into, let's get more educated. Let's get the experts in here. Let's understand what's really happening with it. Let's understand what the risks are, what the rewards are. And can we absorb any sort of risk or reward with it? And when you say put it on the balance sheet, you can put it on in a small way to test it out. I wouldn't put the whole, I wouldn't make the whole balance sheet for Dell on day one. So that's why I would think about it. Just tell, tell me more, get me educated. How did you think about it? How can it help our business? How can I help our shareholders? How does it grow the bottom line? And then, then you start making decisions. >>Cause CFOs, let me find nature often conservative and most CFOs that I talked to just say no way, not a chance, but you're, maybe you're not as conservative as you think. Well, >>No, but I will never say go away on anything. I mean, cause I want to learn. I want to know. I mean, um, if you like all this stuff, that's new, it's easy to say go away, right? Yeah. But all of a sudden, three years later, the go away, all your competitors are doing it at a competitive advantage. So never say go away, get yourself educated before you jump into it. >>That's good advice. Yeah. In any walk of life question for you, or have you talked about the education aspect there? I'm curious from a risk mitigation perspective, especially given the last 18, 19 months, so tumultuous, so scary for all those organizations that were very digital, they're either gone or they accelerated very quickly. How much of an education do you have to provide certain industries? And are you seeing certain industries? I think healthcare manufacturing, financial services as being leaders in the uptake? >>Well, I think the financial service industries, for sure, they, they, they get this and then they need to, uh, cause they, you know, they're, they're a transaction and based, uh, industry. Uh, so they get it completely. Um, you know, I think maybe some manufacturing distribution, some of the old line businesses are, you know, they may not be thinking of this as progressively as they should. Um, but they'll get there. They're going to have to get there eventually. Um, you know, when you think about the education, my, I thought you were gonna ask a question about the education of the workforce. And I think as a board member, I would be really focused on, uh, how am I educating my workforce of the future? And do I have the workforce of the future today? Do I have to educate them to have to bring in hiring for it? Do I have to bring third-party service providers to get us there? So as a board member really focus on, do I have the right workforce to get us to this next stage? And if not, what do I need to do to get there? Because >>We'll allocate a percentage of their budgets to training and education. And the question is where do they put it >>In? Is it the right training and education, right? >>Where do they focus though? Right now we hear you iPad talking about they're a horizontal play, but James, when you and Lisa, we were asking about industry, when you go to market, are you, are you more focused on verticals? Are you thinking, >>No, it's on two things. So which often find is regardless of the sector with some nuanced variation, the back office functions are regionally the procure to pay process as the same fundamentals, regardless of the sector where the differentiation comes in at a sector of service is when you start going to the middle of the front office, I mean a mining has only one customer. They sold their product to image the retailer has an endless number of them. So when you get to the middle and front office and really start engaging with a customer and external vendors, then a differentiation is very unique and you'd have a lot of sort of customers having sector specific nuances and variations in how you use the platform. And that's where the shift now is happening as well is the back office functions that are largely driven by the CFO. If now getting good, robust value out of it, there's pivot to make it a differentiator in the market, comes in the front and middle office. And that's where we starting to say, sector specific genres solutions, nuances really come to the fall >>Deep industry expertise. Do you think digital at all changes that the reason I ask it because I see Amazon as a retail and then they're in cloud and they're in grocery other in content Apple's in, in financial services and you're seeing these internet giants with a dual agenda, they're disrupting horizontal technology and then there's disruptive industries. And my premise is it's because of data and digital. Do you ever see that industry specialization changing that value chain >>Without a doubt? And I think it's happens initially. It starts off. When people have started looking at the process, they realize there's such key dependencies on the upstream and downstream components of the value chain that they want to control it. So they actually start bridging out of what the core practices or the core business to own a broader agenda. And with digital, you can do it. You can actively interact more systemically that installs triggering, well, maybe I have a different product offering. Maybe I can own this. Could I monetize the information I had at my disposal today in a completely new line. And that really what gets truly innovative and starts creating a revenue increase as opposed as the cost saving. And that's what they're really going after. It's how do I, >>The vertical integration is not new. The plenty of ended up Koch industries, Tyson foods, but now it's digital. So presumably you can do it faster with greater greater scale >>Without a doubt. And you don't have to move your big ERP and things like that. Cause that's the only way it takes five years to move my technology backbone with digital. I can do the interaction tomorrow and we can build up enough to be able to sustain that in the short term. >>Right. And speaking of speed, unfortunately, guys, we are out of time, but thank you. Fantastic conversation automation as a board imperative guys, that's been great James or >>Thank you for your time. Thank you so much >>For Dave a long day. I'm Lisa Martin. You're watching the queue. We are live in Las Vegas at the Bellagio at UI path forward for stick around Dave and I will be right back. Okay.

>>from the cube studios in Palo alto >>in boston >>connecting with thought leaders all around the >>world. This >>is a cute conversation. Hello and welcome to today's session of the AWS Global Public sector Partner Awards. I'm your host Natalie ehrlich. Today we're going to focus on the following award for best partner transformation. I'm pleased to introduce our guests, josh door smith, vice president of public sector at Effectual and jeremy Yates, deputy technology architect at jenny May. Welcome gentlemen so glad to have you on our show. >>Hi there. Very nice to be here. Thank you so much for having me >>terrific. Well josh, I'd like to start with you. How can companies leverage cloud native solutions to deliver higher quality services? >>So Natalie, that's a great question. And in the public sector and our our government customers, we run into this all the time. It's kind of our bread and butter. What what they can do is the first thing they need to be aware of is you don't have to be afraid of the cloud as some very obscure technology that is just emerging. It's been out for 10, 11 years now, customers across government space are using it lock stock and barrel to do everything from just managing simple applications, simple websites all the way through hosting their entire infrastructure, both in production and for disaster recovery purposes as well. So the first thing to note is just don't be afraid of the cloud. Um secondly, it's, it's imperative that they select the right partner who is able to kind of be there Sherpa to go into however far they want to dip their toe into the, into the proverbial cloud waters. Um to select somebody who knows whatever it is that they need to go do. So if they want to go Aws as we are talking about today, pick a partner who has the right experience, past performance designations and competencies with the cloud that they're interested in. >>Terrific. Well, you know, Jeremy, I'd love to move to you. What does modern modernization mean to jenny May? >>Sure, Thanks Natalie, great to be here. Thanks josh as well, you know. So for jenny May, modernization is really, it's not just technology is holistic across the organization. So that includes things like the business, um not just you know, the the I. T. Division. So we're looking at the various things to modernize like our culture and structural changes within the organization. Um moving to implement some, some proven practices like def sec ops and continuous integration and continuous delivery or deployment. Uh and then, you know, our overall overarching goal is to give the best and most secure technology to the business that we can to meet the Jeannie Mai mission and the needs of our customers >>terrific. Well josh, how is Effectual planning to support jenny Maes modernization plans? >>So we have been supporting jenny May for about 14 months now. Uh and back in september of last year, we rewarded a co prime 10 year contract for Jeannie Mai to do exactly that. It's to provide all things cloud to Jeannie Mai for 10 years on AWS and that's including reselling AWS. That's including providing all sorts of professional services to them. And it's, it's providing some third party software applications to help them support their applications themselves. So what Effectual is doing is kind of a threefold. We are supporting the modernization of their process, which jeremy mentioned a moment ago and that includes in stan shih ating a cloud center of Excellence for jenny May, which enables them to modernize the way they do cloud governance while they're modernizing their technology stack. We're also providing a very expert team of cloud architects and Dempsey cops engineers to be able to, to design the Jeannie Mai environment, collaborating with our co prime uh to ensure that it meets the security requirements, the compliance requirements that jerry mentions. Uh, Jeannie Mai is a federal entity, but it also has to adhere to all the finance industry uh compliance requirements as well. So very strenuous from that perspective. And then the third thing that we're doing to help them kind of along their modernization journey is in stan shih aging infrastructure as code. So in the cloud, rather than building everything in the AWS management console, we script everything to build it automatically, so it improves consistency, it improves the customer experience regardless of which resource is working on it. And it improves disaster recovery capability as well. And also, just quite frankly, the speed by which they can actually deploy things. >>And jeremy, how is this transition helping your security really enhancing it now? >>Uh From a security perspective we're implementing a number of various tools um both, you know, a W. S based as well as other software that josh mentioned. Um So we're able to utilize those in a more scalable manner than we could previously in the traditional data center. Um we've got a number of things such as we're looking at multiple vulnerability management products like 10 of Ohio and Wallace. Um we're using uh tools such as Centra fi for our our pam or privileged access management capabilities. Um Splunk a pretty industry standard. Um software for log and data correlation and analysis um will also be using that for some system and application monitoring. Um as well as uh the Mcafee envision product for endpoint and other cloud service security. So being able to pull all those in in a more scalable and more cost efficient way as well from cloud based services. Uh, it's really helped us be able to get those services and integrate them together in a way that, you know, we may not previously been able to. >>Yeah, terrific. Well, josh, let's move back to you and talk further about compliance. You know, any insight here, how Effectual is building a modern cloud infrastructure to integrate AWS services with third party tools to really achieve compliance with the government requirements. Just any further insight on that >>front? That's a great question. Natalie and I'm gonna tag team with Jeremy on this one if you don't mind, but I'll start off so jenny may obviously I mentioned earlier has federal requirements and financial requirements so focused right now on on those federal aspects. Um, so the tools that Jeremy mentioned a moment ago, we are integrating all of them with a W. S native meaning all of the way we do log aggregation in the various tools within AWS cloudwatch cloud trail. All of those things were implementing an AWS native, integrating them with Splunk to aggregate all of that information. But then one of the key requirements that's coming up with the federal government in the very near future is tick three dot or trusted internet connection. Basically in the first iteration a decade or so ago, the government wanted to limit the amount of points of presence that they have with the public facing internet fast forward several versions to today and they're pushing that that onus back on the various entities like jenny May and like hud, which Jeannie Mai is a part of but they still want to have that kind of central log repository to where all of the, all of the security logs and vulnerability logs and things like that. Get shipped to a central repository and that will be part of DHS. So what effectual has done in partnership with jenny May is create a, a W. S native solution leveraging some of those third party tools that we mentioned earlier to get all of those logs aggregated in a central repository for Ginny MaE to inspect ingest and take action from. But then also provide the mechanism to send that to DHS to do that and correlate that information with everything coming in from feeds across the government. Now that's not required just yet. But we're future proofing jenny Maes infrastructure in order to be able to facilitate adherence to those requirements when it becomes uh required. Um, and so jeremy, I'll pass it over to you to talk a little bit further about that because I know that's one of the things that's near and dear to your sister's heart as well as jenny may overall. >>Yeah, absolutely. Thanks josh. Um, so yeah, we, as you mentioned, we have implemented um, uh, sort of a hybrid tech model right now, um, to to handle compliance on that front. Um, so we're still using a, you know, some services from the legacy or our existing T two dot x models. That that josh was mentioning things such as m tips, um, uh, the Einstein sensors, etcetera. But we're also implementing that take 30 architecture on our own. As josh mentioned that that will allow us to sort of future proof and and seamlessly really transitioned to once we make that decision or guidance comes out or, you know, mandates or such. Um, so that effort is good to future proof house from a compliance perspective. Um, also, you know, the tools that I mentioned, uh, josh reiterated, those are extremely important to our our security and compliance right. Being able to ensure, you know, the integrity and the confidentiality of of our systems and our data is extremely important. Not both, not just both on the r not only on the government side, but as josh mentioned, the finance side as well. >>Terrific. Well, I'd love to get your insight to on AWS workspaces. Um, if either one of you would like to jump in on this question, how did they empower the jenny May team to work remotely through this pandemic? >>That's a great question. I guess I'll start and then we'll throw it to jeremy. Um, so obviously uh effectual started working with jenny May about three weeks after the pandemic formally started. So perfect timing for any new technology initiative. But anyway, we, we started talking with Jeremy and with his leadership team about what is required to actually facilitate and enable our team as well as the government resources and the other contractors working for jenny May to be able to leverage the new cloud environment that we were building and the very obvious solution was to implement a virtual desktop infrastructure uh type solution. And obviously Jeannie Mai had gone all in on amazon web services, so it became the national natural fit to look first at AWS workspaces. Um, so we have implemented that solution. There are now hundreds of jenny May and jenny make contractor resources that have a WS workspaces functioning in the GovCloud regions today and that's a very novel approach to how to facilitate and enable not only our team who is actually configuring the infrastructure, but all the application developers, the security folks and the leadership on the jenny may side to be able to access, review, inspect, check log etcetera, through this remote capability. It's interesting to note that Jeannie Mai has been entirely remote since the pandemic initiated. Jeremy's coming to us from, from west Virginia today, I'm coming to us from national harbor Maryland And we are operating totally remotely with a team of 60 folks about supporting this specific initiative for the cloud, not to mention the hundreds that are supporting the applications that Jamie runs to do its day to day business. So jeremy, if you wouldn't mind talking about that day to day business that jenny may has and, and kind of what the, the mission statement of Jeannie Mai is and how us enabling these workspaces uh facilitates that mission >>or you know, so the part of the overall mission of jenny Maes to, to ensure affordable housing is, is made available to uh, the american public. Um that's hud and, and jenny may as part of that and we provide um mortgage backed securities to help enable that. Um, so we back a lot of V A. Loans, um, F H A, those sort of loans, um, workspaces has been great in that manner from a technology perspective, I think because as you mentioned, josh, it's really eliminated the need for on premise infrastructure, right? We can be geographically dispersed, We can be mobile, um, whether we're from the east coast or west coast, we can access our environment securely. Uh, and then we can, you know, administer and operate and maintain the technology that the business needs to, to fulfill the mission. Um, and because we're able to do that quickly and securely and effectively, that's really helpful for the business >>Terrific. And um, you know, I'd like to shift gears a bit and uh you know, discuss what you're looking ahead toward. What is your vision for 2021? How do you see this partnership evolving? >>Yeah, you >>Take that 1/1. >>Sure. Yeah. Um you know, definitely some of the things we look forward to in 2021 as we evolve here is we're going to continue our cloud journey um you know, through practices like Deb said cops, you realize that uh that journey has never done. It's always a continual improvement process. It's a loop to continually work towards um a few specific things or at least one specific thing that we're looking forward to in the future, as josh mentioned earlier was our arctic three Oh Initiative. Um, so with that we think will be future proofed. Um as there's been a lot of um a lot of recent cyber security activity and things like that, that's going to create um opportunities I think for the government and Jeannie Mai is really looking forward to to leading in that area. >>Mhm and josh, can you weigh in quickly on that? >>Absolutely. Uh First and foremost we're very much looking forward to receiving authority to operate with our production environment. We have been preparing for that for this last year plus. Uh but later on this summer we will achieve that 80 oh status. And we look forward to starting to migrate the applications into production for jenny May. And then for future proof, it's as jerry jerry mentioned, it's a journey and we're looking forward to cloud optimizing all of their applications to ensure that they're spending the right money in the right places uh and and ensuring that they're not spending over on any of the one given area. So we're very excited to optimize and then see what the technology that we're being able to provide to them will bring to them from an idea and a conceptual future for jenny may. >>Well thank you both so very much for your insights. It's been a really fantastic interview. Our guests josh duggar smith as well as jeremy Gates. Really appreciate it. >>Thank you very much. >>Thank you so much. >>Terrific. Well, I'm your host for the cube Natalie or like to stay tuned for more coverage. Thanks so much for watching.

>>from around the globe it's the >>cube >>presenting >>Future Cloud one event. A >>world of >>opportunities >>brought to you by Cisco. We're here with Dejoy Pandey a VP of emerging tech and incubation at Cisco. V. Joy. Good to see you welcome. >>Good to see you as well. Thank you Dave and pleasure to be here. >>So in 2020 we kind of had to redefine the notion of agility when it came to digital business or you know organizations, they had to rethink their concept of agility and business resilience. What are you seeing in terms of how companies are thinking about their operations in this sort of new abnormal context? >>Yeah I think that's a great question I think what what we're seeing is that pretty much the application is the center of the universe and if you think about it the application is actually driving brand recognition and the brand experience and the brand value. So the example I like to give is think about a banking app uh recovered that did everything that you would expect it to do. But if you wanted to withdraw cash from your bank you would actually have to go to the ATM and punch in some numbers and then look at your screen and go through a process and then finally withdraw cash. Think about what that would have, what that would do in a post pandemic era where people are trying to go contact less. And so in a situation like this the digitization efforts that all of these companies are going through and the modernization of the automation is what is driving brand recognition, brand trust and brand experience. >>Yeah. So I was gonna ask you when I heard you say that, I was gonna say well but hasn't it always been about the application? But it's different now, isn't it? So I wonder if you talk more about how the application is experience is changing? Yes. As a result of this new digital mandate. But how should organizations think about optimizing those experiences in this new world? >>Absolutely. And I think, yes, it's always been about the application, but it's becoming the center of the universe right now because all interactions with customers and consumers and even businesses are happening through that application. So if the application is unreliable or if the application is not available is untrusted insecure, uh, there's a problem. There's a problem with the brand with the company and the trust that consumers and customers have with our company. So if you think about an application developer, the weight he or she is carrying on their shoulders is tremendous because you're thinking about rolling features quickly to be competitive. That's the only way to be competitive in this world. You need to think about availability and resiliency, like you pointed out and experience, you need to think about security and trust. Am I as a customer or consumer willing to put my data in that application? So velocity availability, security and trust and all of that depends on the developer. So the experience, the security, the trust, the feature velocity is what is driving the brand experience now. >>So are those two tensions that say agility and trust, you know, zero trust used to be a buzzword now, it's a mandate. But are those two vectors counter posed? Can they be merged into one and not affect each other? Does the question makes sense? Right? Security usually handcuffs my speed. But how do you address that? >>Yeah, that's a great question. And I think if you think about it today, that's the way things are. And if you think about this developer, all they want to do is run fast because they want to build those features out and they're going to pick and choose a purpose and services that matter to them and build up their app and they want the complexities of the infrastructure and security and trust to be handled by somebody else is not that they don't care about it, but they want that abstraction so that is handled by somebody else. And typically within an organization we've seen in the past where there's friction between Netapp, Succop cited hopes and the cloud platform teams and the developer on one side and these these frictions and these meetings and toil actually take a toll on the developer and that's why companies and apps and developers are not as agile as they would like to be. So I think, but it doesn't have to be that way. So I think if there was something that would allow a developer to pick and choose, discover the apis that they would like to use, connect those api is in a very simple manner and then be able to scale them out and be able to secure them and in fact not just secure them during the run time when it's deployed, we're right off the back when the fire up that I'd and start developing the application, wouldn't that be nice? And as you do that, there is a smooth transition between that discovery connectivity and ease of consumption and security with the idea cops, netapp psych ops teams and see source to ensure that they are not doing something that the organization won't allow them to do in a very seamless manner. >>I want to go back and talk about security but I want to add another complexity before we do that. So for a lot of organizations in the public cloud became a staple of keeping the lights on during the pandemic. But it brings new complexities and differences in terms of latency security, which I want to come back to deployment models etcetera. So what are some of the specific networking challenges that you've seen with the cloud? Native architecture is how are you addressing those? >>Yeah. In fact, if you think about cloud, to me that is a that is a different way of seeing a distributed system. And if you think about a distributed system, what is at the center of the distributed system is the network. So my my favorite comment here is that the network is the wrong time for all distribute systems and modern applications. And that is true because if you think about where things are today, like you said, there's there's cloud assets that a developer might use in the banking example that I gave earlier. I mean if you want to build a contact less app so that you get verified, a customer gets verified on the app. They walk over to the ATM and they were broadcast without touching that ATM. In that kind of an example, you're touching the mobile Rus, let's say, Ohio escapees, you're touching Cloud API is where the back end might sit, you're touching on primary purpose, maybe it's an oracle database or a mainframe even where transactional data exists, you're touching branch pipes were the team actually exists and the need for consistency when you withdraw cash and you're carrying all of this and in fact there might be customer data sitting in Salesforce somewhere. So it's cloud API is a song premise branch, it's ass is mobile and you need to bring all of these things together and over time you will see more and more of these API is coming from various as providers. So it's not just cloud providers but saAS providers that the developer has to use. And so this complexity is very very real and this complexity is across the wide open internet. So the application is built across this wide open internet. So the problems of discovery ability, the problems of being able to simply connect these apis and manage the data flow across these apis. The problems of consistency of policy and consumption because all of these areas have their own nuances and what they mean, what the arguments mean and what the A. P. I. Actually means. How do you make it consistent and easy for the developer? That is the networking problem. And that is a problem of building out this network, making traffic engineering easy making policy easy, making scale out, scale down easy, all of that our networking problems. And so we are solving those problems. Uh Francisco >>Yeah the internet is the new private network but it's not so private. So I want to go back to security. I often say that the security model of building a moat, you dig the moat, you get the hardened castle that's just outdated now that the queen is left her castle. I always say it's dangerous out there. And the point is you touched on this? It's it's a huge decentralized system and with distributed apps and data, that notion of perimeter security, it's just no longer valid. So I wonder if you could talk more about how you're thinking about this problem and you definitely address some of that in your earlier comments. But what are you specifically doing to address this? And how do you see it evolving? >>Yeah, I mean that that's that's a very important point. I mean I think if you think about again the wide open internet being the wrong time for all modern applications, what is perimeter security in this uh in this new world? I mean it's to me it boils down to securing an API because again, going with that running example of this contact lists cash withdrawal feature for a bank. The FBI wherever it sits on tram branch sas cloud, IOS android doesn't matter that FBI is your new security perimeter and the data object that is trying to access is also the new security perimeter. So if you can secure ap to ap communication and P two data object communication, you should be good. So that is the new frontier. But guess what? Software is buggy? Everybody's software not saying Cisco software, everybody's Softwares buggy. Uh software is buggy, humans are not reliable and so things mature, Things change, Things evolve over time. So there needs to be defense in depth. So you need to secure at the API layer had the data object layer, but you also need to secure at every layer below it so that you have good defense and depth if any layer in between is not working out properly. So for us that means ensuring ap to ap communication, not just during long time when the app has been deployed and is running, but during deployment and also during the development life cycle. So as soon as the developer launches an ID, they should be able to figure out that this API is security uses reputable. It has compliant, it is compliant to my my organization's needs because it is hosted, let's say from Germany and my organization wants a P is to be used only if they are being hosted out of Germany. So compliance needs and and security needs and reputation. Is it available all the time? Is it secure and being able to provide that feedback all the time between the security teams and the developer teams in a very seamless real time manner? Yes, again, that's something that we're trying to solve through some of the services that we're trying to produce in SAN Francisco. >>Yeah, I mean those that layered approach that you're talking about is critical because every layer has, you know, some vulnerability and so you you've got to protect that with some depth in terms of thinking about security, how should we think about where where Cisco's primary value add is, I mean it's parts of the interview has a great security business. Is growing business. Is it your intention to to to to add value across the entire value chain? I mean obviously you can't do everything so you've got a partner but so has the we think about Cisco's role over the next I'm thinking longer term over the over the next decade. >>Yeah, I mean I think so. We do come in with good strength from the runtime side of the house. So if you think about the security aspects that we haven't played today, uh there's a significant set of assets that we have around user security around around uh with with do and password less. We have significant assets in random security. I mean the entire portfolio that Cisco brings to the table is I don't run time security. The security checks aspects around posture and policy that will bring to the table. And as you see, Cisco evolve over time, you will see us shifting left. I mean I know it's an overused term, but that is where security is moving towards. And so that is where api security and data security are moving towards. So learning what we have during runtime. Because again, runtime is where you learn what's available and that's where you can apply all of the M. L. And I models to figure out what works what doesn't taking those learnings, Taking those catalogs, taking that reputation database and moving it into the deployment and development life cycle and making sure that that's part of that entire they have to deploy to runtime chain is what you will see Cisco do overtime. >>That's fantastic phenomenal perspective video. Thanks for coming on the cube. Great to have you and look forward to having you again. >>Absolutely. Thank you. Pleasure to be here. >>This is Dave Volonte for the cube. Thank you for watching. Mhm. >>Mhm mm.

>>Hey, everyone. I want to welcome you back. This is our intermission. And let me tell you what a morning we've had for those of you that don't know. I'm, Hayma Ganapati, I'm in product marketing at Docker. And I would just want to quote, actually someone who was in one of the chat rooms and this, I think encapsulates exactly how I feel today, because this is my first Docker con and the quote was from. And he said, I feel like a kid in an ice cream store where I don't know which flavor to choose. I want to go to all of the sessions and I got to tell you that's how I felt. And, you know, um, I want to just do some specific call-ups. Um, first of all, Dana way to keep it real in your interview. I love the cube interview. If you miss that, um, it was really great. >>She talks a lot about, uh, CI CD pipeline and you know, what to do with GoodHub. It was great. Um, I also want to say that I was, uh, slipping back and forth between the community rooms and way to go Brazil obrigado until all of the people who participate in the Brazil room, we had about 250 plus people in that room. And the, the chat window was just going crazy and in the French community room, Vive left hall. So if you've a uncle funny, uh, we had about 150 plus people in that room. So I just want to say that, you know, we've been seeing a lot of participation and I just want to thank everyone for attending and for participating on people have been so kind in the chat rooms, we just want to remind you to stay kind, you know, presenters put a lot of effort into their presentations, so just, you know, offer some positive and supportive critique to them. >>And the other thing I want to mention is all of the countries that we're seeing, all of the participation. So I'm just going to call out a few. We have people from the Netherlands, from Canada, from South Africa, Akron, Ohio, Belgium, Austria, yeah, Ecuador, New Zealand. And he cut up Westchester. Like, I mean, it just goes list goes on and on and on. And I think this really speaks to the power of Docker community. And it's a real testimony to how people from all over the world are in love with Docker technology and are excited to be here. And so I just wanted to thank everyone again and want to remind you that we want to leverage the power of community. And we have a fundraising campaign going on to help, uh, people who are affected by COVID. And you know, some of our big communities, especially in India and Brazil are, have been really affected by COVID. >>So we're asking you to contribute and we'd really like you to participate. Um, we have, uh, the, the link you can see here, Docker donates, you can tweet about it and would love to see the numbers go up for those donations, because, you know, I've personally been affected, had some family members pass away from COVID in India, and I'm sure other people may have stories that firsthand or secondhand. So please do that and let's show what the power of Docker community can do. And before I hand over to, to Peter, I'm just going to read out some of the tweets we've been getting, okay, this Brett and Peter, these are great. Uh, one of the, one of the tweets said dev environments is one of the most exciting features in the past few years. Super excited to try this out. Great, great, great tweet. Yeah. >>I agree to, um, another loving the content that was not your tweets. You can, you can slip me the 20 bucks later. Um, there's another tweet that says loving the content from hashtag Docker con so far fascinating use cases and interesting progress and future directions love that. And then there's another one I'm trying to find it here. Uh, I've been waiting for this so long Docker builds now work on Intel and M one. So keep those tweets coming. We love getting this kind of feedback and we love reading the chat room. So, um, Peter, you know, I attended your, your panel and I love that we were talking about a security and that moving, moving it left. So how did that go for you? >>Uh, it was, it was, uh, it was extremely fun. And for those that are, uh, I think my parents might be watching, so they probably watched it and were like, w this is the most boring thing I've ever seen, but, um, you know, you get a bunch of geeks and, uh, Brett has told me I should use geek instead of nerd, but I, I liked, uh, geek. So you get a bunch of geeks talking about security and coding and, um, what, what, what containers actually are, what vulnerabilities are. Yeah, it was, it was extremely fun. The panel was fantastic. They were very engaging the chat. I mean, I couldn't keep up with the chat. Right. It would just kept flying by, uh, luckily I had a helper to pull off questions, but, um, yeah, it's super exciting. You can, I know we're all remote, but you can just feel that energy, right. It was, it was great. It was great. Yeah. Yeah, for sure. It's super >>Connected. I felt that with your panel to Brett as well, sorry to talk over you there, but yeah. How did, how did it go for you? I, there was a lot of engagement in your session. >>Uh, ditto, like it was just, uh, there was so many questions. We only got to get a fraction of them. I tried to pick themes because, uh, when you talk about continuous testing and integration and all the things that take a part of that, um, you, you end up with lots of, well, what I like is the discussion around opinions, because so much of these pipelines from code on your machine, into production and everything in between, it's really, uh, it's a culture. It turns out to be the description of your culture and how you all perceive testing, how you, what you value in testing. And so that really started to come out as a theme, um, throughout that show. And we, we ran at a time. I was also watching Peters and it was fantastic, but like you think an hour is enough time to cover a topic, but it's just tipping tip of the iceberg kind of stuff. So I think it was super helpful. I learned some things, um, I really enjoyed watching Peters and, uh, yeah, can't wait for the next one. There's >>More than that. And likewise, great. I mean, I know, I know we're w maybe we pat chose it, but it, it was, it was super exciting to watch your panel. They were very Nikos, one of my favorite people in the world, uh, a fellow Austinite, but, um, yeah, I love that too. How you, uh, you were talking about opinions right. And playing off each other. It's, it's always interesting to hear smart people, uh, how they think, right. Yeah. I learned from how they think, right. Yeah. A hundred percent. >>So, all right. So we're, we're, um, what's next? Like, we, we gotta keep this thing going, so I've got to remember that. >>I want to, so I want to talk a bit about some of the panels that are, or the sessions that are coming up and just want to remind people that happened this afternoon. I'm all about use cases. You know, I was a developer for many decades, and it's great to hear how other developers are using the tools. But, uh, as a developer, I always wanted to know how are, what are the end user applications? And so we have two exciting sessions at 1:00 PM. We have sneak and red ventures, and they're going to be talking about how they used Docker containers. The title of the, uh, uh, session is great. An ounce of prevention, curing, insecure, container images. So check that out. And we also have another one at one 30 with Massimo, from AWS and Dexter Legaspi from Sirius XM. And they're going to be talking about a real world application using Docker containers. So I really want you to, to encourage you to attend those. >>Yeah. Um, can I say one really quick? Cause I'm Sue and a shout out to Eric Smalling. He's giving the red ventures talk with our partners. He's awesome. Go check out his, uh, but I'm really excited about Matt. Jarvis's sneak talk around. Uh, I think we might've talked about it earlier. My container image has 500 vulnerabilities vulnerabilities now what, right. I mean, I think as developers, as we're coming into this and dev ops and everybody right. You scan and then you see all these vulnerabilities just shoot by. And you're like, well, what do I do? So Matt, Matt will be addressing that. And he is fantastic. I can go on. There's a bunch of them. >>Yeah. There's a whole bunch of coming up and right up after this, I'm on a live stream with a bunch of panels on get ops. And then after that, Peter will be back. And so stay tuned and thanks for watching during the intermission. And we'll see you soon. >>I'm also leading the women in tech panel attend that. Don't forget to do that. >>Absolutely. Yep. All right. Ciao. Ciao >>For me like my first, oh, I get it about Docker was when I used a SQL server container on my neck book for the first time >>Being able to install Docker desktop, which was the first thing that I did and be able to build this without worrying about any of my software versions that I currently had on my machine. It was >>Awesome. One of the things, because I love the most about Docker is because I write books and I do video training courses to help a lot of people take their first steps with Docker and containers and to get a connection with those people and for them to come back to me and say, do you know what this is so cool, so easy, and it's going to change both my job. And, but also my organization, my team, all of that kind of stuff, change the experience that our customers have with our applications and what our business really puts a smile on my face. If >>You want to use containers, then Docker is the first toys, especially with tools like the mark Docker, compose, you can, uh, easily do your day-to-day job as a developer, or even if you're an ops person, then there are the books of the cloud and other things. So yeah, the idea is that we can go the simplicity one simple task, uh, to, uh, Daugherty mate and make that reuse as many times. Uh, that is one of the cool things I like about my >>Favorite part about Docker is using it as a developer tool. I using Docker desktop, really easy to install, really easy to run. >>Every time I come back to DACA, I love the simplicity of the way that it works, especially on things like security, which I find frustrating and hard. It's just done so seamlessly. And so my favorite thing about DACA is not just that it changed the world in the way that we develop in and ship and build applications and put that. It's just so easy that even the guy, like, I think >>It really is all about finding that aha moment, that hook where Docker really makes sense to you because once you have that moment, then all of a sudden, you, you know, you are on your way to being a Docker power user. >>We need for people to understand this technology better before they can, uh, actually dive deep into that. And Docker makes it easier to explain things, to explain the concept of containers, to explain how containers will work, how you can split your environments, how you can, uh, standardize all your pipelines and so on. It's important that we also take the time to help other people. And I think it's very important that we also give back and that's part of the motto of open sources. How do we give back to other people and how we help other people learn? And I think that's what I'm really passionate about. This whole thing is continuing, uh, giving back to the community. I just >>Hope and has fun at Docker con. And I know that there's a lot of great speakers coming and I will be watching the talks, even though they're happening at 3:00 AM and in my local time zone, um, I'm pretty excited to watch and, uh, hopefully watch more than later on streaming or YouTube or wherever they're going to be. So I hope everyone has fun and learn something and yeah, I don't see how you couldn't have fun.

>>Mhm Yes. Welcome to this cube conversation. I'm john Kerry host of the cube here in Palo alto California. We've got two great guests all the way from Ohio and here in the bay area with sequence securities is our focus on cloud growth companies. Sri and met a co founder and CTO of sequence security and Jason Kent hacker in residence at sequence security. We're gonna find out what that actually means in the second but this is a really important company in the sense of A P. I. S. As they are starting to be the connective tissue between systems and and data. Um you're starting to see more vulnerabilities, more risk but also more upside. So risk, reward is high. And anyone who's doing things in the cloud obviously deals with the A. P. I. So Trey and Jason. Thanks for let's keep conversation. >>Happy to be here >>guys. Let's let's talk about A P. I. Security. And but first before we get there trans what does sequence security do? What do you guys specifically build? And what do you sell >>sequences in the business protecting your web and um A P. I. S from various kinds of attacks? Uh We protect from business logic attacks, A P. I. Uh do your api inventory, uh also the detect and defend against things like a town taker. Where's fake account creation, scraping pretty much anything and everything. An application on a PDA is exposed to from from the Attackers. >>Jason. What do you what do you do there as hacker and residents? I also want to get your perspective on api security from the point of view of, you know, uh attack standpoint from a vector. How are people doing it? So first explain what you do and uh love the title hacker and residents. But also what does that actually mean from a security standpoint? >>Yeah. So we can't be in the business that we're in without having an adversarial approach to where our customers are deployed and how we look at them. So a lot of times I spend my time trying to be on the client's backdoors and and try to hit their A. P. I. S. With as many kinds of attacks that I can. It helps us understand how an attacker is going to approach a specific client as well as helps us tune for our machine learning models to make sure that we can defend against those kinds of things. Um as a hacker and residents, my mostly my position is client facing. But I do spend an awful lot of time being research and looking for the next api threat that's out there. >>You gotta stay ahead of the bad guys. But let's bring up some kind of cutting edge relevant topics. One is all over the news cycle. You heard peloton, very highly visible company, It represents that new breed of digital companies that have a new approach and it's absolutely doing very, very well. The new consumers like this product and you're seeing a lot more peloton, like companies out there that are leveraging technology, so they're fully integrated, they had an A. P. I. Issue recently. Um what does it mean? Is that, is that something we're gonna see more of these kind of leaks in these kind of vulnerabilities? What do you guys think about this political thing, >>You know, from an attacker's perspective as a really boring attack? Um, but it led to a huge amount of data leaking out. Same with, you know, the news has been been right with this lately, right, john Deere got hit. Um We've seen yet another credit bureau got hit right. Um and these attacks are coming off as fairly simple attacks that are dumping huge amounts of data, just proving that the FBI attack surface is really a great place to get a rich amount of data, but you have to have a good understanding of how the application works so you can spend a little bit of time on it. But once you've taken a look at how the data flows, you end up with, you know, pretty rich data set as an attacker. I go after them just by simply utilizing their products, utilizing the programs and understanding how they work. And then I drag out all the pieces that I think are going to be interesting and start plucking away at it. If I see a like a profile, for instance, that I can edit, I wonder can I edit someone else's profile. And this is how the peloton attack work. I'm logged in, I'm allowed to see my things, what other things can I see? And it turns out they can see everything. >>So we also saw a hack with clubhouse, which is the hot app now I think just opened up to android users, but they were simply calling it back and Agora, which is, you know, I've seen china, but once you've understood that the tokens work, once you understood what they were doing, you could essentially go in and figure things out. There seems to be like pretty like trivial stuff, but it gets exposed. No one kind of thinks it through. How does someone protect themselves against these things? Because that's the real issue, like just make it less secure. Our Api is gonna be more secure in the future. What can customers do about what do you guys to think about this? >>Yeah, but the reality is, I mean that's just uh too many babies out there. I mean if you see the transition that is happening and that is the transformation where it used to be like a one app or two apps before and now there are like hundreds and thousands of applications driven by the devops world, a child development and and what matters is, I mean the starting point really is you cannot protect what, you cannot see what used to be. Uh an up hosted in your data center is now being hosted in the cloud environments, in the virtual environments, in several less environments and coordinators, you name it, they're out there. So the key is really to understand your attack surface, that's your starting point. So you're you're tooling your applications need to uh I need to be able to provide that visibility that that that is needed to protect these applications and you can't rely just on your developers to do this for you. So you need a right tool that can secure these applications, >>Jason what's the steps that an attacker takes to uncover vulnerabilities? What goes through the mind of the attacker? Um I mean the old days you used to just do port scans and try to penetrate you get through the perimeter. Now with this no perimeter mindset, the surface area Schramm was talking about is huge. What what's going on the mind of the attacker here and the A P I S and vulnerabilities. >>So the very first thing that we do is we sign up for an account, we use the thing, right? We look at all the different endpoints. Um I've got scripts running in my attack tools that do things like show me comments uh in case the developer left some comments in there to tell me where things are. Um I basically I'm just going to poke around using it like a regular user, but in that I'm going to look for places. That makes sense to try to do an attack. So the login screen is a really easy thing. Everybody understands that you put in a user name, you put in a password, you can't go. What I'm gonna do is put in a bad username and a bad password. I'm gonna put in a good user name and a bad password and I'm gonna see what changes, what are the different things that your application is telling me. And so when we look at an application for flaws and ways to get to the data on the back end, all we're doing is seeing what data do you present me on standard use. And then I'm going to look at, well, how can I change these parameters or what are the things that I can change in my requests to get a different response? So in the early phases of an attack, Attackers are very difficult to a seat. Right. They just look like a regular user just doing regular things. It's when we decide. All right. I've found something that starts to get actually interesting and we start to try to pull data out. >>What are some of the common vulnerabilities and risks that you guys see in the A. P. I is when you look when you poke at them that people are are doing is that they're not really doing their homework. Doing good. Security designers are just more of tech risk. What's the most common vulnerabilities and risks? >>Well, so for me, I I've noticed a lot of the OAS KPI top 10, the first couple of things you see them on almost all applications, so broken object level authorization is the first one. It's mouthful. Um but basically all it is is I log onto the platform, I'm authorized to be there, but I can see someone else's stuff and that's exactly what happened in peloton. Um that and what we call insecure direct object reference where I don't have to be logged in, I can just make the request without any authentication and get information back. So those are pretty common areas um that you know people need to focus on, but there's a few others that are outside the top 10 that really make a lot more sense as a defender strains probably has a little better answer to me. >>Yeah. So um I'm like like we said um creating that inventories is key, but where are they being hostess? Another another aspect of things. So so when when Jason spoke about um like hackers are actually probing, trying to figure out what are the different entry points? It could be your production environment, it could be your QA environment staging environment and you're not even aware of, but once you've actually figured out those entry points, the next step of attack was like at peloton and and other places is really eggs filtering. Exfiltrate ng that that information. Right. Is it, is it the O P II information, ph I information um and and you don't want to exfiltrate as a hacker, just one person's information. You you're automating that business logic that is behind it ability to protect and defend against those kinds of attacks, giving that visibility, even though you might not have instrumented that application for for that kind of visibility is key. Once you are bubbling up those behaviors, then you can go ahead and and and protect from these kinds of attacks. And it could be about just simply enumerating through I. D. S. Uh that paladin might have or uh experience might have and just enumerate through that and exfiltrate the information behind it. So the tools need to be able to protect from those kinds of attacks out there. >>Yeah, I think I was actually on clubhouse when um that went down that hole enumerating through the I. D. S. Room I. D. S. And then the people just querying once they got an I. D. They essentially just sucked all the content out because they were just calling the back end. It was just like the most dumbest thing I've ever seen, but they didn't think about, I mean, you know, they were just rushing really fast. So So the question I have for transit and on a defense basis, people are going first party um with a P. I. S. A. P. I. First strategies because it's just some benefits there as we were talking about what do I need to do to protect myself? So I don't have that clubhouse problem or the pelton problem. Is there a Is there a playbook or is their software tools that I could use? How do I build? My apologies from day one and my principles around it to be good hygiene or good design? What's the what's the >>yeah. So aPI security is sort of a looking uh less known given that it's constantly evolving and changing. And the adoption of A P. S. Have gone up significantly. So what you need to start with effectively is the runtime security aspect of things. When a an aPI is live, how do I actually protected? And it ranges from simple syntactic protection things around people. Can can go ahead and break these ap is by providing sort of uh going after endpoints that you don't think exist anymore or going after certain functions by giving large values that they're not sort of coded to accept and so on so forth. Once you've done that runtime protection from a syntactic aspect, you also need to protect from a business logic aspect. I mean, mps will will expose uh information, interact with the customers and partners, what what business logic are they actually exposing and how can it be abused? Understanding that is another big aspects and then you can go ahead and protect from a runtime uh from a long time security perspective, once you've done that and understood that, well then you can start shifting lap things, invest in your uh sort of uh Dass tools or static analysis tools which can catch these things early so that they don't bubble up all the way, but none of them are actually silver bullets, right? So that you have a good uh time security tools, so I don't need to invest in dust or assessed whatever I have invested in my shift left aspect of things and uh and nothing will flow through. So you you need to start shifting left uh but covered all your bases properly, >>you can't shift left, there's nothing to shift from. I mean if you don't have that baseline foundation, what does that even mean to shift left and get that built into the Ci cd pipeline? So that's a great point. How does how does someone and some companies and teams set that foundation with the run time? Do you think it's a critical problem right now or most people are do a good job or they just get get lazy or just lose track of it or you know what, what's what's the common um, use case? Do you see behavior behaviorally inside these enterprises? >>Yeah. So what, what we're seeing is adoption of new technologies and environments um, and they're not um, well suited for the traditional way of doing that time. Security. Like if if you have an app running in your kubernetes environment, if you have an app running in in in a serval less environment, how do you actually protected with the traditional appliance based approach? So I think being able to get that visibility into these environments, understanding the the user behavior, how these applications are interacted with being able to differentiate from that uh, normal human behavior or even sometimes legitimate automation uh from from the malicious intents or or the the probing and the business logic attacks is key to understanding and defending these applications. >>Before we wrap up, I want to just get your expert opinion since you guys are both here around, you know, the next level of of innovation. Also you got cloud public cloud showed us a P. I. S are great. Now you're starting to see cloud operations, they call day two operations or whatever you call it A IOP. There's all kinds of buzz words are for it, but hybrid cloud and multi cloud, Edge five G. These are all basically pointing to distributed computing systems, basically distributed cloud. So that means more A P. I. Is gonna be out there. Um So in a way the surface area of a piece is increasing. What's your what's your view on this as a market? I mean, early days developing fast and what's, what's the, what's the landscape look like? What do you guys see from a attack and defense standpoint? >>Well, just from the attacker's perspective, you know, I see a lot more traffic going, what we call east west traffic, where it's traveling inside the application, it's a P is feeding a ps more data. Um, but what is really happening is we're trying to figure out how to hook third parties into our api is more and more. The john Deere attack was just simply their development api platform that they open up for other organizations to integrate with them. Um, you know, it's, it's very beneficial for John Deere to be able to say I planted this seed at an inch and a half of depth and later, uh, I harvested 280 bushels of corn off that acres. So I know that's perfect. I can feed that back to my seed guy. Well that kind of data flow that's going around from AP to AP means that there's far more attack surface and we're going to see it more and more. I I don't think that we're going to have less Ap is communicating in the near future. I think this is the foundation that we're building for what it's gonna look like for almost every business in the near term. >>I mean this is the plumbing of integration. I mean as people work with each other data transfer, data knowledge format, you mentioned syntax and all these basic things in computer science are coming to A PS which was supposed to be just a dumb pipe or just, you know, rest api those glory days now it's not there. They're basically, it's basically connections. >>Yeah. You're absolutely right. John, I mean like what Jason mentioned earlier, uh, in terms of the way the A. P. I. S are going to grow and the bad guys are going to go after it. You need to think like a bad guy, what are they going to go after? Uh, these assets that are going to be in the cloud, in your hybrid environment, in in your own prem environment. And, and it's, it's a flip of a switch where an internal API can be externally exposed or, or just a new api getting rolled out. So all those things you need to be able to protect, um, and get that visibility first and then being then protect these environments. >>That's awesome. You guys represent the new kind of company that's going to take advantage of the cloud scale and as people shift to the new structural change and people are re factoring security, This is an area that's going to be explosive in development. Obviously the upside is huge. Um Quickly before to end, you guys take a minute to give a plug for the company. Um This is pretty cool. I love love what you guys do. I think it's very relevant and cool at the same time. So sequence security. What are you guys doing funding hiring? What's the plug? Tell folks about it. >>Yeah. So uh we we we started about six years ago but we like starting in the the body defense space by focusing on obscenity ice. And from then we we've grown and we've grown significantly in terms of our customer base, the verticals that we're going after in financial retail social media, you name it, we are there because pretty much all these these uh articles depends on A. P. I. S. To interact with their customers. Uh We've we've raised our cities we last year we've we've grown our customer base. Uh Just in the last year when there was a lockdown people were all these retailers were transforming from brick and mortar to online. Social media also also grew and we grew with them. So >>Jason your thoughts. >>I think that sequence is his ability to scale out to any size environment. We've got a customer that does a billion and a half transactions a month. Um That are ap is from 1000 other clients of theirs. Being able to protect environments that are confusing and cloudy like that. Um Is really it makes what we do shine. We use a lot of machine learning models and ai in order to surface real problems. And we have a lot of great humans behind all of that, making sure that the bad guy maybe they're right now, but they're going away and we're going to keep them away. >>It's super, super awesome. I think it's a combination of more connections, distributed computing at large scale with a data problem. That's, that's playing out. You guys are solving great stuff and hey, you know when the cube studio ap I gets built, we're gonna need to call you guys up to to help us secure the cube data. >>Absolutely right. Absolutely. >>Hey, thanks for coming on the q Great uh, great insight and thanks for sharing about sequence. Appreciate you coming on, >>appreciate the time. >>Okay. It's a cube conversation here in Palo alto with remote guests. I'm john for your host. Thanks for watching. Yeah.