(light upbeat music) >> Hey, everyone. Welcome back to theCUBE's day long coverage of Women in Data Science 2023. Live from Stanford University, I'm Lisa Martin. We've had some amazing conversations today with my wonderful co-host, as you've seen. Tracy Zhang joins me next for a very interesting and inspiring conversation. I know we've been bringing them to you, we're bringing you another one here. Dr. Irene Dankwa-Mullan joins us, the Chief Medical Officer at Marti Health, and a speaker at WIDS. Welcome, Irene, it's great to have you. >> Thank you. I'm delighted to be here. Thank you so much for this opportunity. >> So you have an MD and a Master of Public Health. Covid must have been an interesting time for you, with an MPH? >> Very much so. >> Yeah, talk a little bit about you, your background, and Marti Health? This is interesting. This is a brand new startup. This is a digital health equity startup. >> Yes, yes. So, I'll start with my story a little bit about myself. So I was actually born in Ghana. I finished high school there and came here for college. What would I say? After I finished my undergraduate, I went to medical school at Dartmouth and I always knew I wanted to go into public health as well as medicine. So my medical education was actually five years. I did the MPH and my medical degree, at the same time, I got my MPH from Yale School of Public Health. And after I finished, I trained in internal medicine, Johns Hopkins, and after that I went into public health. I am currently living in Maryland, so I'm in Bethesda, Maryland, and that's where I've been. And really enjoyed public health, community health, combining that aspect of sort of prevention and wellness and also working in making sure that we have community health clinics and safety net clinics. So a great experience there. I also had the privilege, after eight years in public health, I went to the National Institute of Health. >> Oh, wow. >> Where I basically worked in clinical research, basically on minority health and health disparities. So, I was in various leadership roles and helped to advance the science of health equity, working in collaboration with a lot of scientists and researchers at the NIH, really to advance the science. >> Where did your interest in health equity come from? Was there a defining moment when you were younger and you thought "There's a lot of inequities here, we have to do something about this." Where did that interest start? >> That's a great question. I think this influence was basically maybe from my upbringing as well as my family and also what I saw around me in Ghana, a lot of preventable diseases. I always say that my grandfather on my father's side was a great influence, inspired me and influenced my career because he was the only sibling, really, that went to school. And as a result, he was able to earn enough money and built, you know, a hospital. >> Oh wow. >> In their hometown. >> Oh my gosh! >> It started as a 20 bed hospital and now it's a 350 bed hospital. >> Oh, wow, that's amazing! >> In our hometown. And he knew that education was important and vital as well for wellbeing. And so he really inspired, you know, his work inspired me. And I remember in residency I went with a group of residents to this hospital in Ghana just to help over a summer break. So during a summer where we went and helped take care of the sick patients and actually learned, right? What it is like to care for so many patients and- >> Yeah. >> It was really a humbling experience. But that really inspired me. I think also being in this country. And when I came to the U.S. and really saw firsthand how patients are treated differently, based on their background or socioeconomic status. I did see firsthand, you know, that kind of unconscious bias. And, you know, drew me to the field of health disparities research and wanted to learn more and do more and contribute. >> Yeah. >> Yeah. So, I was curious. Just when did the data science aspect tap in? Like when did you decide that, okay, data science is going to be a problem solving tool to like all the problems you just said? >> Yeah, that's a good question. So while I was at the NIH, I spent eight years there, and precision medicine was launched at that time and there was a lot of heightened interest in big data and how big data could help really revolutionize medicine and healthcare. And I got the opportunity to go, you know, there was an opportunity where they were looking for physicians or deputy chief health officer at IBM. And so I went to IBM, Watson Health was being formed as a new business unit, and I was one of the first deputy chief health officers really to lead the data and the science evidence. And that's where I realized, you know, we could really, you know, the technology in healthcare, there's been a lot of data that I think we are not really using or optimizing to make sure that we're taking care of our patients. >> Yeah. >> And so that's how I got into data science and making sure that we are building technologies using the right data to advance health equity. >> Right, so talk a little bit about health equity? We mentioned you're with Marti Health. You've been there for a short time, but Marti Health is also quite new, just a few months old. Digital health equity, talk about what Marti's vision is, what its mission is to really help start dialing down a lot of the disparities that you talked about that you see every day? >> Yeah, so, I've been so privileged. I recently joined Marti Health as their Chief Medical Officer, Chief Health Officer. It's a startup that is actually trying to promote a value-based care, also promote patient-centered care for patients that are experiencing a social disadvantage as a result of their race, ethnicity. And were starting to look at and focused on patients that have sickle cell disease. >> Okay. >> Because we realize that that's a population, you know, we know sickle cell disease is a genetic disorder. It impacts a lot of patients that are from areas that are endemic malaria. >> Yeah. >> Yeah. >> And most of our patients here are African American, and when, you know, they suffer so much stigma and discrimination in the healthcare system and complications from their sickle cell disease. And so what we want to do that we feel like sickle cell is a litmus test for disparities. And we want to make sure that they get in patient-centered care. We want to make sure that we are leveraging data and the research that we've done in sickle cell disease, especially on the continent of Africa. >> Okay. >> And provide, promote better quality care for the patients. >> That's so inspiring. You know, we've heard so many great stories today. Were you able to watch the keynote this morning? >> Yes. >> I loved how it always inspires me. This conference is always, we were talking about this all day, how you walk in the Arrillaga Alumni Center here where this event is held every year, the vibe is powerful, it's positive, it's encouraging. >> Inspiring, yeah. >> Absolutely. >> Inspiring. >> Yeah, yeah. >> It's a movement, WIDS is a movement. They've created this community where you feel, I don't know, kind of superhuman. "Why can't I do this? Why not me?" We heard some great stories this morning about data science in terms of applications. You have a great application in terms of health equity. We heard about it in police violence. >> Yes. >> Which is an epidemic in this country for sure, as we know. This happens too often. How can we use data and data science as a facilitator of learning more about that, so that that can stop? I think that's so important for more people to understand all of the broad applications of data science, whether it's police violence or climate change or drug discovery or health inequities. >> Irene: Yeah. >> The potential, I think we're scratching the surface. But the potential is massive. >> Tracy: It is. >> And this is an event that really helps women and underrepresented minorities think, "Why not me? Why can't I get involved in that?" >> Yeah, and I always say we use data to make an make a lot of decisions. And especially in healthcare, we want to be careful about how we are using data because this is impacting the health and outcomes of our patients. And so science evidence is really critical, you know? We want to make sure that data is inclusive and we have quality data. >> Yes. >> And it's transparent. Our clinical trials, I always say are not always diverse and inclusive. And if that's going to form the evidence base or data points then we're doing more harm than good for our patients. And so data science, it's huge. I mean, we need a robust, responsible, trustworthy data science agenda. >> "Trust" you just brought up "trust." >> Yeah. >> I did. >> When we talk about data, we can't not talk about security and privacy and ethics but trust is table stakes. We have to be able to evaluate the data and trust in it. >> Exactly. >> And what it says and the story that can be told from it. So that trust factor is, I think, foundational to data science. >> We all see what happened with Covid, right? I mean, when the pandemic came out- >> Absolutely. >> Everyone wanted information. We wanted data, we wanted data we could trust. There was a lot of hesitancy even with the vaccine. >> Yeah. >> Right? And so public health, I mean, like you said, we had to do a lot of work making sure that the right information from the right data was being translated or conveyed to the communities. And so you are totally right. I mean, data and good information, relevant data is always key. >> Well- >> Is there any- Oh, sorry. >> Go ahead. >> Is there anything Marti Health is doing in like ensuring that you guys get the right data that you can put trust in it? >> Yes, absolutely. And so this is where we are, you know, part of it would be getting data, real world evidence data for patients who are being seen in the healthcare system with sickle cell disease, so that we can personalize the data to those patients and provide them with the right treatment, the right intervention that they need. And so part of it would be doing predictive modeling on some of the data, risk, stratifying risk, who in the sickle cell patient population is at risk of progressing. Or getting, you know, they all often get crisis, vaso-occlusive crisis because the cells, you know, the blood cell sickles and you want to avoid those chest crisis. And so part of what we'll be doing is, you know, using predictive modeling to target those at risk of the disease progressing, so that we can put in preventive measures. It's all about prevention. It's all about making sure that they're not being, you know, going to the hospital or the emergency room where sometimes they end up, you know, in pain and wanting pain medicine. And so. >> Do you see AI as being a critical piece in the transformation of healthcare, especially where inequities are concerned? >> Absolutely, and and when you say AI, I think it's responsible AI. >> Yes. >> And making sure that it's- >> Tracy: That's such a good point. >> Yeah. >> Very. >> With the right data, with relevant data, it's definitely key. I think there is so much data points that healthcare has, you know, in the healthcare space there's fiscal data, biological data, there's environmental data and we are not using it to the full capacity and full potential. >> Tracy: Yeah. >> And I think AI can do that if we do it carefully, and like I said, responsibly. >> That's a key word. You talked about trust, responsibility. Where data science, AI is concerned- >> Yeah. >> It has to be not an afterthought, it has to be intentional. >> Tracy: Exactly. >> And there needs to be a lot of education around it. Most people think, "Oh, AI is just for the technology," you know? >> Yeah, right. >> Goop. >> Yes. >> But I think we're all part, I mean everyone needs to make sure that we are collecting the right amount of data. I mean, I think we all play a part, right? >> We do. >> We do. >> In making sure that we have responsible AI, we have, you know, good data, quality data. And the data sciences is a multi-disciplinary field, I think. >> It is, which is one of the things that's exciting about it is it is multi-disciplinary. >> Tracy: Exactly. >> And so many of the people that we've talked to in data science have these very non-linear paths to get there, and so I think they bring such diversity of thought and backgrounds and experiences and thoughts and voices. That helps train the AI models with data that's more inclusive. >> Irene: Yes. >> Dropping down the volume on the bias that we know is there. To be successful, it has to. >> Definitely, I totally agree. >> What are some of the things, as we wrap up here, that you're looking forward to accomplishing as part of Marti Health? Like, maybe what's on the roadmap that you can share with us for Marti as it approaches the the second half of its first year? >> Yes, it's all about promoting health equity. It's all about, I mean, there's so much, well, I would start with, you know, part of the healthcare transformation is making sure that we are promoting care that's based on value and not volume, care that's based on good health outcomes, quality health outcomes, and not just on, you know, the quantity. And so Marti Health is trying to promote that value-based care. We are envisioning a world in which everyone can live their full life potential. Have the best health outcomes, and provide that patient-centered precision care. >> And we all want that. We all want that. We expect that precision and that personalized experience in our consumer lives, why not in healthcare? Well, thank you, Irene, for joining us on the program today. >> Thank you. >> Talking about what you're doing to really help drive the volume up on health equity, and raise awareness for the fact that there's a lot of inequities in there we have to fix. We have a long way to go. >> We have, yes. >> Lisa: But people like you are making an impact and we appreciate you joining theCUBE today and sharing what you're doing, thank you. >> Thank you. >> Thank you- >> Thank you for having me here. >> Oh, our pleasure. For our guest and Tracy Zhang, this is Lisa Martin from WIDS 2023, the eighth Annual Women in Data Science Conference brought to you by theCUBE. Stick around, our show wrap will be in just a minute. Thanks for watching. (light upbeat music)

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

(upbeat music) >> Hey, everyone. Welcome to theCUBE's coverage of the International Women's Showcase for 2022. I'm your host, Lisa Martin. I'm pleased to welcome Nancy Wong, the general manager of Data Protection and Governance at AWS to the program. Nancy, it's great to have you. >> Thanks so much for having me Lisa, and you know, I really hope that this is hopefully the last year that we'll be celebrating International Women's Day all virtually. >> I agree. I agree. Well, we're going in that right direction globally. So let's cross our fingers. Talk to me a little bit about your role at AWS and what you do there. >> Sure. So as a GM of AWS Data Protection and Governance, a lot of, we tackle quite a few problems that our biggest customers face, right? When they think about, "How do I manage my data?" Right. Especially in this digital world. And speaking of the pandemic, how much data has been generated by consumers, by devices, by systems, by servers? How do you protect all of that data? Right. Especially we hear about cyber crime, cyber attacks. Right. Data breaches. It's really important to make sure that all of our customers have a coherent strategy around not just management, right, but also protection and really how you govern your data. Right. And there's just so many awesome conversations that my team and I have had lately with CSOs or chief technology officers on this topic, as it evolves. >> Data protection is so critical. It's one of my favorite topics to talk about, cybersecurity as well. Talk to me about what it means though if we keep this at a bit of a different level to be an operator within the the big ecosystem that is AWS. >> Yeah. And that's actually one of the the favorite aspects of my role. Right. Which is, you know, I get to innovate every day on behalf of my customers. For example, I love having one-on-one dialogues. I love having architecture conversations where we brainstorm. Right. And so those type of conversations help inform how we deliver and develop products. And so in an operator role, right, for the the women in the audience today, is it really gives you that perspective into not just how, what type of products do you want to build that delight your customers but also from an engineering. Right. And a bottom line perspective of, well how do you make this happen? Right. How do you fund this? And how do you plan out your development milestones? >> What are, tell me a little bit about your background and then what makes women in technology such an important initiative for you to stand behind? >> Absolutely. So I'm so proud today to see that the number of women or the percentage of women enrolled at engineering curriculums just continue to rise. Right. And especially as someone who went through an engineering degree in her undergraduate studies, that was not always the case. Right. So oftentimes, you know, I would look around the classroom and be the only woman on the lab bench or only woman in a CS classroom. And so when you have roles in tech, specifically, that require an undergraduate degree in computer science or a degree in engineering, that helps to, or that only serves to really reduce the population of eligible candidates. Right. Who then, if you look at that pool of eligible candidates who then you can invest and accelerate through the career ladder to become leaders in tech, well that's where you may end up with a representation issue. Right. And that's why we have, for example, so few women leaders in tech that we can look up to as role models. And that's really the problem or the gap that I'm very passionate about solving. And also, Lisa, I'm really excited to tell you a little bit more about advancing women in tech, which is a 501c3 nonprofit organization that I started to tackle this exact problem. >> Talk to me about that, cause it's one of the things that you bring up is, you know, we always say when we're having conversations like this, we can't be what we can't see. We need to be able to see those female leaders. To your point, there aren't a ton in comparison to the male leaders. So talk to me about advancing women in technology, why you founded this, and what you guys are accomplishing. >> Absolutely. So it's been such a personal journey as well. Just starting this organization called Advancing Women In Tech because I started it in 2017. Right. So when I really was, you know, just starting out as a product manager, I was at another big tech company at the time. And what I really realized, right, is looking around you know, I had so many, for example, bosses, managers, peer leaders, who were really invested in growing me as a product manager and growing my tech and career. And this is right after I'd made the transition from the federal government into big tech. What that said though, looking around, there weren't that many women tech leaders that I could look up to, or get coffee, or just have a mentoring conversation. And quickly I realized, well, it's not so much that women can't do it. Right. It's the fact that we're not advancing enough women into leadership roles. And so really we have to look at why that is. Right. And we, you know, from a personal perspective, one contribution towards that angle is upskilling. Right. So if you think about what skills one needs as one climbs a career ladder, whether that's your first people management role, or your first manager manager's role, or obviously for bigger leaders when they start managing thousands, tens of thousands of individuals, well all of that requires different skills. And so learning those skills about how to manage people, how to motivate your teams effectively, super, super important. And of course on the other side, and one that I'm, you know, near to dear to me is that of mentorship and executive sponsorship because you can have all the skills in the world, right. And especially with digital learning and AWIT is very involved with Coursera and AWS in producing and making those resources readily available and accessible. Well, if you don't have those opportunities, if you don't have mentors and sponsors who are well to push you or give you a step ladder to those roles, well you're still not going to get there. Right. And so, that's why actually, if you look at the AWIT mission, it's really those two pillars working very closely together to help advance women into leadership roles. >> The idea of mentorship and sponsorship is so critical. And I think a lot of people don't understand the difference between a mentor and a sponsor. How do you define that difference and how do you bring them into the organization so that they can be mentors and sponsors? >> Yeah, absolutely. And there's, you know, these two terms are often used today so interchangeably that I do get a lot of questions around, well, what is the difference? Right. And how does, let's say a mentor become a sponsor? So, maybe just taking a few steps back, right. When you have let's say questions around compensation or, "Hey I have some job offers, which ones do I consider?" And you ask someone a question or advice, well that person's likely your mentor. Right? And typically a mentor is someone who you can ask those questions on a repeated basis. Who's very accessible to you. Well, a sponsor takes that a few steps forward in the sense that they are sponsoring you into a role or into a project or initiative that you on your own may not be able to achieve. And by doing so, I think what really differentiates a sponsor from a mentor is that the sponsor will actually put their own reputation on the line. Right. They're using their own political capital in order to make sure that you get into that role, you get into that room. Right. And that's why it's so key, for example, especially if you have that relationship already with a person who's your mentor, you're able to ask questions or advice from, to convert them into a sponsor so that you can accelerate your career. >> Great definition, description, and great recommendations for converting mentors to sponsors. You know, I only learned the difference about a mentor and a sponsor a few years ago at another women in tech event that I was hosting. And I thought, "It's brilliant. It makes perfect sense." We need more people to understand the difference, the synergies, and how to promote mentors to sponsors. Talk to me now about advancing women in tech plus the power of AWS. How are they helping this nonprofit to really accelerate? >> Sure. So from an organization perspective, right, there's many women, for example, across the the tech companies who are part of Advancing Women In Tech, obviously Amazon of course as an employee has a very large community within who's part of AWIT. But we also have members across the tech industry from startups to VC firms to of course, Google, Microsoft, and Netflix. You name it. With that said, you know, what AWS has done with AWIT is actually very special in the sense that if you go to the Coursera platform, coursera.org/awit you can see our two Coursera specializations. Four courses each that go through the real world product management fundamentals. Or the business side, the technical skills, and even interviewing for mid-career product management roles. And the second specialization, which I'm super excited to share today, is actually geared towards getting folks ramped up and prepared to successfully pass the Cloud Practitioner's Exam, which is one of the industry recognized standards about understanding the AWS Cloud and being functional in the AWS Cloud. This summer, of course, and I'm sharing kind of a sneak peek announcement that I'll be making tomorrow with the University of Pennsylvania, is that we're kicking off a program for the masters of CIS program, or the Computer Information Systems Master students, to actually go through this Coursera specialization, which is produced by AWIT, sponsored by AWS, and AWS Training and Certifications has so generously donated exam vouchers for these students so that they can then go on and be certified in the AWS Cloud. So that's one just really cool collaboration that we are doing between AWS and AWIT to get more qualified folks in the door in tech jobs, and hopefully at jobs in AWS. >> That's a great collaboration. What are some of the goals in terms of metrics, the number of women that you want to get into the program and complete the program? What are some of those on your radar? >> Absolutely. So one of the reasons, of course, that the Master's of CIS Program, the University of Pennsylvania caught my eye, not withstanding, I graduated from there, but also that just the statistics of women enrolled. Right. So what's really notable about this program is it's entirely online, which as a university creating a Master's degree fully online, well, it takes a ton of resources from the university, from the faculty. And what's really special about these students is that they're already full-time adult professionals, which means that they're working a full-time job, they might be taking care of family obligations, and they're still finding time to advance themselves, to acquire a Master's degree in CS. And best of all, 42% of these students are women. Right. And so that's a number that is multiples of what we're finding in engineering curriculums today. And so my theory is, well if you go to a student population that is over 40%, 42 to be exact percent women, and enable these women to be certified in AWS Cloud, to have direct interview prep and mentorship from AWS software development leaders, well, that greatly increases their chances of getting a full-time role, right, at AWS. Right. At which then we can help them advance their careers to further and further roles in software development. >> So is this curriculum also open to women who aren't currently in tech to be able to open the door for them to get into tech and STEM fields? >> Absolutely. And so in my bad and remiss in mentioning, which is students of this Master's in CS Program are actually students not from tech already. So they're not in a tech field. And they did not have a degree in CS or even engineering as part of their undergraduate studies. So it's truly folks who are outside of tech, that are 42% women, that we're getting into the tech industry with this collaboration between AWS, AWIT, and the University of Pennsylvania. >> That's outstanding to get them in from completely different fields into tech. >> Absolutely. >> How do you help women have the confidence to say, "I want to try this." Cause if we think about every company today is a tech company. It's a data company. It has to be to be competitive. You know, the pandemic taught us that everything we're able to do online and digitally, for example, but how do you help women get the confidence to say, "Okay, I'm going to go from a completely different field into tech." >> Absolutely. So if we, you know, define tech of course as big tech or, you know, now the main companies, right, I myself made that transition, which is why it is a topic near and dear to me because I can personally speak to my journey because I didn't start my career out in tech. Right. Yes. I studied engineering. But with that said, my first full-time job out of college was with the federal government because I wanted to go and build healthdata.gov, right, which gave folks a lot of access to the healthcare data, roles, right, that existed within the U.S. government and the CMS, NIH, you know, CDC, so on and so forth. But that was quite a big change from then taking a product management job at Google. Right. And so how did I make that change? Well, a lot of it came from, you know, the mentors that I had. Right. What I call my personal board of directors who gave me that confidence. And sure, I mean even today, I still have imposter syndrome where, you know, I think, "Am I good enough." Right. "Should I be leading this organization," right, "of data protection and governance." But I think what it boils down to is, you know, inner confidence. Right. And goes back to those two pillars of having the right skills and also the right mentors and sponsors who are willing to help sponsor you into those opportunities and help sponsor you to success. >> Absolutely. Great advice and recommendations. Thanks for sharing your background, Nancy, it's outstanding to see where you started to where you are now and also to what you're enabling for so many other females to get into tech with the AWIT program combined with AWS and UPenn. Exciting stuff. Can't wait to talk to you next year to see where you guys go from here. >> Absolutely Lisa. And what I'm really looking forward to sharing with you next year is the personal testimonials of other women who have gone through the AWIT, the AWS, the UPenn Program and have gotten their tech jobs and also promotions. >> That sounds like a great thing to look forward to. I'm looking forward to that. Nancy, thanks so much for your time and the insight that you shared. >> Thanks so much for having me, Lisa. >> My pleasure. For Nancy Wong, I'm Lisa Martin. You're watching theCUBE's coverage of the International Women's Showcase 2022. (upbeat music)

>>Mhm >>Welcome to the cube where we're celebrating the EC 2/15 birthday anniversary. My name is Dave Volonte and we're joined right now by Sandy carter, Vice President of AWS. Welcome Sandy, it's great to see you again, >>David. So great to see you too. Thanks for having me on the show today. >>Very welcome. We were last physically together. I think it was reinvent 2019. Hopefully I'll see you before 2022. But first happy birthday to EC two. I mean, it's hard to imagine back in 2006, the degree to which EC two would impact our industry. Sandy, >>I totally agree. You know, I joined a W S about 4.5 years ago in EC two and it's, it's even amazing to see what's just happened in the last 4.5 years. So I'm with you. Nobody really expected the momentum, but EC two has really shone brightly in value to our customers. >>You know, we've done the public sector summit, you know, many times. It's a great event. Things are a little different in public sector as you well know. So talk about the public sector momentum with EC two and that journey. What have you seen? >>Yeah, so it's a great question day. So I had to go back in the time vault. You know, public sector was founded in 2010 and we were actually founded by the amazon process writing a paper setting up a two pizza team, which happened to be six people. And that journey really started with a lot of our public sector customers thinking that we don't know about the cloud. So we might want to do a pilot or just look at non mission critical workloads now public sector and I know you know this day but public sector is more than just government, it has education, not for profit healthcare and now space. But everybody at that time was very skeptical. So we had to really work hard to migrate some workloads over. And one of our very first non mission critical workloads was the U. S. Navy. Um and what they did was the Navy Media Services actually moved images over to EC two. Now today that seems like oh that's pretty easy. But back then that was a big monumental reference. Um and we had to spend a lot of time on training and education to win the hearts and souls of our customers. So back then we had half of the floor and Herndon Washington, we just had a few people and that room really became a training room. We trained our reps, we trained our customers um research drive. A lot of our early adopters accounts like Nasa and jpl. And um then when cloud first came out and governments that started with the U. S. A. And we announced Govcloud, you know, things really picked up, we had migration of significant workloads. So if you think back to that S. A. P. And just moving media over um with the Navy, the Navy and S. A. P. Migrated their largest S A P E R P solution to the cloud in that time as well. Um, then we started international. Our journey continued with the UK International was UK and us was us. Then we added a P. J. And latin America and Canada. And then of course the partner team which you know, is very close to my heart. Partners today are about 73% of our overall public sector business. And it started out with some interesting small pro program SVS being very crucial to that, accelerating adoption. And then of course now the journey has continued with Covid. That has really accelerated that movement to the cloud. And we're seeing, you know, use of ec two to really help us drive by the cute power needed for A I N. M. L. And taking all that data in from IOT and computing that data. And are they are. Um, and we're really seeing that journey just continue and we see no end in sight. >>So if we can stay in the infancy and sort of the adolescent years of public sector, I mean, remember, I mean as analysts, we were really excited about, you know, the the the introduction of of of of EC two. But but there was a lot of skepticism in whatever industry, financial services, healthcare concerns about security, I presume it was similar in public sector, but I'm interested in how you you dealt with those challenges, how you you listen to folks, you know, how did you drive that leadership to where it is today? >>Yeah, you're right. The the first questions were what is the cloud? Doesn't amazon sell books? What is this clown thing? Um, what is easy to, what is easy to stand for and then what the heck is an instance? You know, way back when there was one instance, it didn't even have a name. And today of course we have over 400 instant types with different names for each one. Um and the big challenges you asked about challenges, the big challenges that we had to face. Dave were first and foremost, how do we educate? Um we had to educate our employees and then we had to educate our customers. So we created these really innovative hands on training programmes, white boarding um, sessions that we needed. They were wildly popular. So we really have to do that and then also prove security as you know. So you asked how we listen to our customers and of course we followed the amazon way we work backwards from where we were. So at that time, customers needed education. And so we started there um, data was really important. We needed to make customer or data for government more available as well. So for instance, we first started hosting the Census Bureau for instance. Um and that was all on EC two. So we had lots of early adopters and I think the early adopters around EC two really helped us to remember. I said that the UK was our international office for a while. So we had NIH we had a genomes project and the UK Ministry of Justice as well. And we had to prove security out. We had to prove how this drove a structured GovCloud and then we had to also prove it out with our partners with things like helping them get fed ramped or other certifications. I'll for that sort of thing as well. And so we really lead in those early days through that education and training. Um we lead with pilots to show the potential of the possible and we lead with that security setting those security standards and those compliance certifications, always listening to the customer, always listening to the partner, knowing how important the partners we're going to be. So for example, recovery dot gov was the first government wide system that moved to the cloud. Um the recovery transparency board was first overseeing that Recovery act spending, which included stimulus tracking website. I don't know if you remember that, but they hosted the recovery dot gov On amazon.com using EC two. And that site quickly made information available to a million visitors per hour and at that time, that was amazing. And the cost savings were significant. We also launched Govcloud. You'd asked about GovCloud earlier and that federal cloud computing strategy when the U. S. Government came out with cloud first and they had to consider what is really going to compel these federal agencies to consider cloud. They had Public-sector customers had 70 requirements for security and safety of the data that we came out with Govcloud to open up all those great opportunities. And I think Dave we continue to leave because we are customer obsessed uh you know, still supporting more security standards and compliance sort than any other provider. Um You know, now we lead with data not just data for census or images for the US Navy, but we've got now data in space and ground station and data at scale with customers like Finra who's now doing 100 billion financial transactions. Not just that one million from the early days. So it has been a heck of a ride for public sector and I love the way that the public sector team really used and leveraged the leadership principles. Re invent and simplify dive deep. Be obsessed with the customers start where they are. Um and make sure that you're always always always listening to what they need. >>You know, it's interesting just observing public sector. It's not uncommon, especially because of the certifications that some of the services, you know come out after they come out for the commercial sector. And I remember years ago when I was at I. D. C. I was kind of the steward of the public sector business. And that was a time when everybody was trying to focus in public sector on commercial off the shelf software. That was the big thing. And they want to understand, they wanted to look at commercial use cases and how they could apply them to government. And when I dug in a little bit and met with generals and like eight different agencies, I was struck by how many really smart people and the things that they were doing. And I said at the time, you know, a lot of my commercial clients could learn a lot from you. And so the reason I bring that up is because I saw the same thing with Govcloud because there was a lot of skepticism in various industries, particularly regulated industries, financial services, healthcare. And then when Govcloud hit and the CIA deal hit, people said, whoa CIA, they're like the most security conscious industry or organization in the world. And so I feel as though in a way public sector led that that breakthrough. So I'm wondering when you think about EC two today and the momentum that it has in the government, Are there similar things that you see? Where's the momentum today in public sector? >>You are right on target day? I mean that CIA was a monumental moment and that momentum with ever increasing adoption to the cloud has continued in public sector. In fact today, public sector is one of our fastest growing areas. So we've got um, you know, thousands of startups or multiple countries that were helping out today to really ignite that innovation. We have over 4000 government agencies, 9000 education agencies. Um 2000 public sector partners from all over the globe. 24,000 not for profit organizations. And what I see is the way that they're using EC two um is is leading the pack now, especially after Covid, you know, many of these folks accelerated their journey because of Covid. They got to the cloud faster and now they are doing some really things that no one else is doing like sending an outpost postbox into space or leveraging, you know robots and health care for sure. So that momentum continues today and I love that you were the champion of that you know way back when even when you were with I. D. C. >>So I want to ask you, you sort of touched on some interesting use cases, what are some of the more unusual ones and maybe breakthrough use cases that you see? >>Oh so yeah we have a couple. So one is um I mentioned it earlier but there is a robot now that is powered by IOT and EC two and the robot helps to take temperature and and readings for folks that are entering the hospital in latin America really helped during Covid, one of my favorites. It actually blew the socks off of verne or two and you know that's hard to do is a space startup called lunar outpost and they are synthesizing oxygen on mars now that's, that's driven by Ec two. That's crazy. Right? Um, we see state governments like new york, they've got this vision zero traffic and they're leveraging that to prevent accidents all through new york city. I used to live in new york city. So this is really needed. Um, and it continues like with education, we see university of Illinois and Splunk one of our partners, they created a boarding pass for students to get back to school. So I have a daughter in college. Um, and you know, it's really hard for her to prove that she's had the vaccine or that she's tested negative on the covid test. They came out with a past of this little boarding pass, just like you used to get on an airplane to get into different classes and labs and then a couple of my favorites and you guys actually filmed the Cherokee nation. So the Cherokee nation, the chief of the Cherokee nation was on our silicon um show and silicon angles show and the cube featured them And as the chief talked about how he preserves the Cherokee language. And if you remember the Cherokee language has been used to help out the US in many different ways and Presidio. One of our partners helped to create a game, a super cool game that links in with unity To help teach that next generation the language while they're playing a game and then last but not least axle three d out of the UK. Um, they're using easy to, to save lives. They've created a three D imaging process for people getting ready to get kidney transplants and they have just enhanced that taken the time frame down for months. Now today's that they can actually articulate whether the kidney transplant will work. And when I talked to roger their Ceo, they're doing R. O. L return on life's not return on investment. So those are just some of the unusual and breakthrough use cases that we see powered by E. C. To >>Sandy. I'll give you the last word. Your final closing comments. >>Well, my final closing comments are happy birthday to ec two celebrating 15 years. What a game changer and value added. It has been the early days of Ec two. Of course we're about education like what is the cloud? Why is a bookseller doing it. But um, easy to really help to create a new hub of value Now. We've got customers moving so fast with modernization using a I. M and M. L. Containers survivalists. Um, and all of these things are really changing the game and leveling it up as we increased that business connection. So I think the future is really bright. We've only just begun. We've only just begun with EC two and we've only just begun with public sector. You know, our next great moments are still left to come. >>Well, Sandy, thanks so much. Always Great to see you. Really appreciate your time. >>Thank you so much. Dave. I really appreciate it. And happy birthday again to E. C. To keep >>It right there were celebrating Ec 2's 15th birthday right back. >>Mhm.

>>Mhm Hello and welcome to the cubes coverage of AWS amazon web services, Global public Sector partner awards program. I'm john for your host of the cube here we're gonna talk about the best covid solution to great guests. Benham or with healthcare and life sciences lead at palantir Ben welcome to the cube SAm Michaels, Director of automation and compound management and Cats. National Center for advancing translational sciences and Cats. Part of the NIH National sort of health Gentlemen, thank you for coming on and and congratulations on the best covid solution. >>Thank you so much john >>so I gotta, I gotta ask you the best solution is when can I get the vaccine? How fast how long it's gonna last but I really appreciate you guys coming on. I >>hope you're vaccinated. I would say john that's outside of our hands. I would say if you've not got vaccinated, go get vaccinated right now, have someone stab you in the arm, you know, do not wait and and go for it. That's not on us. But you got that >>opportunity that we have that done. I got to get on a plane and all kinds of hoops to jump through. We need a better solution anyway. You guys have a great technical so I wanna I wanna dig in all seriousness aside getting inside. Um you guys have put together a killer solution that really requires a lot of data can let's step back and and talk about first. What was the solution that won the award? You guys have a quick second set the table for what we're talking about. Then we'll start with you. >>So the national covered cohort collaborative is a secure data enclave putting together the HR records from more than 60 different academic medical centers across the country and they're making it available to researchers to, you know, ask many and varied questions to try and understand this disease better. >>See and take us through the challenges here. What was going on? What was the hard problem? I'll see everyone had a situation with Covid where people broke through and cloud as he drove it amazon is part of the awards, but you guys are solving something. What was the problem statement that you guys are going after? What happened? >>I I think the problem statement is essentially that, you know, the nation has the electronic health records, but it's very fragmented, right. You know, it's been is highlighted is there's there's multiple systems around the country, you know, thousands of folks that have E H. R. S. But there is no way from a research perspective to actually have access in any unified location. And so really what we were looking for is how can we essentially provide a centralized location to study electronic health records. But in a Federated sense because we recognize that the data exist in other locations and so we had to figure out for a vast quantity of data, how can we get data from those 60 sites, 60 plus that Ben is referencing from their respective locations and then into one central repository, but also in a common format. Because that's another huge aspect of the technical challenge was there's multiple formats for electronic health records, there's different standards, there's different versions. And how do you actually have all of this data harmonised into something which is usable again for research? >>Just so many things that are jumping in my head right now, I want to unpack one at the time Covid hit the scramble and the imperative for getting answers quickly was huge. So it's a data problem at a massive scale public health impact. Again, we were talking before we came on camera, public health records are dirty, they're not clean. A lot of things are weird. I mean, just just massive amount of weird problems. How did you guys pull together take me through how this gets done? What what happened? Take us through the the steps He just got together and said, let's do this. How does it all happen? >>Yeah, it's a great and so john, I would say so. Part of this started actually several years ago. I explain this when people talk about in three C is that and Cats has actually established what we like to call, We support a program which is called the Clinical translation Science Award program is the largest single grant program in all of NIH. And it constitutes the bulk of the Cats budget. So this is extra metal grants which goes all over the country. And we wanted this group to essentially have a common research environment. So we try to create what we call the secure scientific collaborative platforms. Another example of this is when we call the rare disease clinical research network, which again is a consortium of 20 different sites around the nation. And so really we started working this several years ago that if we want to Build an environment that's collaborative for researchers around the country around the world, the natural place to do that is really with a cloud first strategy and we recognize this as and cats were about 600 people now. But if you look at the size of our actual research community with our grantees were in the thousands. And so from the perspective that we took several years ago was we have to really take a step back. And if we want to have a comprehensive and cohesive package or solution to treat this is really a mid sized business, you know, and so that means we have to treat this as a cloud based enterprise. And so in cats several years ago had really gone on this strategy to bring in different commercial partners, of which one of them is Palin tear. It actually started with our intramural research program and obviously very heavy cloud use with AWS. We use your we use google workspace, essentially use different cloud tools to enable our collaborative researchers. The next step is we also had a project. If we want to have an environment, we have to have access. And this is something that we took early steps on years prior that there is no good building environment if people can't get in the front door. So we invested heavily and create an application which we call our Federated authentication system. We call it unified and cats off. So we call it, you know, for short and and this is the open source in house project that we built it and cats. And we wanted to actually use this for all sorts of implementation, acting as the front door to this collaborative environment being one of them. And then also by by really this this this interest in electronic health records that had existed prior to the Covid pandemic. And so we've done some prior work via mixture of internal investments in grants with collaborative partners to really look at what it would take to harmonize this data at scale. And so like you mentioned, Covid hit it. Hit really hard. Everyone was scrambling for answers. And I think we had a bit of these pieces um, in play. And then that's I think when we turned to ban and the team at volunteer and we said we have these components, we have these pieces what we really need. Something independent that we can stand up quickly to really address some of these problems. One of the biggest one being that data ingestion and the harmonization step. And so I can let Ben really speak to that one. >>Yeah. Ben Library because you're solving a lot of collaboration problems, not just the technical problem but ingestion and harmonization ingestion. Most people can understand is that the data warehousing or in the database know that what that means? Take us through harmonization because not to put a little bit of shade on this, but most people think about, you know, these kinds of research or non profits as a slow moving, you know, standing stuff up sandwich saying it takes time you break it down. By the time you you didn't think things are over. This was agile. So take us through what made it an agile because that's not normal. I mean that's not what you see normally. It's like, hey we'll see you next year. We stand that up. Yeah. At the data center. >>Yeah, I mean so as as Sam described this sort of the question of data on interoperability is a really essential problem for working with this kind of data. And I think, you know, we have data coming from more than 60 different sites and one of the reasons were able to move quickly was because rather than saying oh well you have to provide the data in a certain format, a certain standard. Um and three C. was able to say actually just give us the data how you have it in whatever format is easiest for you and we will take care of that process of actually transforming it into a single standard data model, converting all of the medical vocabularies, doing all of the data quality assessment that's needed to ensure that data is actually ready for research and that was very much a collaborative endeavor. It was run out of a team based at johns Hopkins University, but in collaboration with a broad range of researchers who are all adding their expertise and what we were able to do was to provide the sort of the technical infrastructure for taking the transformation pipelines that are being developed, that the actual logic and the code and developing these very robust kind of centralist templates for that. Um, that could be deployed just like software is deployed, have changed management, have upgrades and downgrades and version control and change logs so that we can roll that out across a large number of sites in a very robust way very quickly. So that's sort of that, that that's one aspect of it. And then there was a bunch of really interesting challenges along the way that again, a very broad collaborative team of researchers worked on and an example of that would be unit harmonization and inference. So really simple things like when a lab result arrives, we talked about data quality, um, you were expected to have a unit right? Like if you're reporting somebody's weight, you probably want to know if it's in kilograms or pounds, but we found that a very significant proportion of the time the unit was actually missing in the HR record. And so unless you can actually get that back, that becomes useless. And so an approach was developed because we had data across 60 or more different sites, you have a large number of lab tests that do have the correct units and you can look at the data distributions and decide how likely is it that this missing unit is actually kilograms or pounds and save a huge portion of these labs. So that's just an example of something that has enabled research to happen that would not otherwise have been able >>just not to dig in and rat hole on that one point. But what time saving do you think that saves? I mean, I can imagine it's on the data cleaning side. That's just a massive time savings just in for Okay. Based on the data sampling, this is kilograms or pounds. >>Exactly. So we're talking there's more than 3.5 billion lab records in this data base now. So if you were trying to do this manually, I mean, it would take, it would take to thousands of years, you know, it just wouldn't be a black, it would >>be a black hole in the dataset, essentially because there's no way it would get done. Ok. Ok. Sam take me through like from a research standpoint, this normalization, harmonization the process. What does that enable for the, for the research and who decides what's the standard format? So, because again, I'm just in my mind thinking how hard this is. And then what was the, what was decided? Was it just on the base records what standards were happening? What's the impact of researchers >>now? It's a great quite well, a couple things I'll say. And Ben has touched on this is the other real core piece of N three C is the community, right? You know, And so I think there's a couple of things you mentioned with this, johN is the way we execute this is, it was very nimble, it was very agile and there's something to be said on that piece from a procurement perspective, the government had many covid authorities that were granted to make very fast decisions to get things procured quickly. And we were able to turn this around with our acquisition shop, which we would otherwise, you know, be dead in the water like you said, wait a year ago through a normal acquisition process, which can take time, but that's only one half the other half. And really, you're touching on this and Ben is touching on this is when he mentions the research as we have this entire courts entire, you know, research community numbering in the thousands from a volunteer perspective. I think it's really fascinating. This is a really a great example to me of this public private partnership between the companies we use, but also the academic participants that are actually make up the community. Um again, who the amount of time they have dedicated on this is just incredible. So, so really, what's also been established with this is core governance. And so, you know, you think from assistance perspective is, you know, the Palin tear this environment, the N three C environment belongs to the government, but the N 33 the entire actually, you know, program, I would say, belongs to the community. We have co governance on this. So who decides really is just a mixture between the folks on End Cats, but not just end cast as folks at End Cats, folks that, you know, and I proper, but also folks and other government agencies, but also the, the academic communities and entire these mixed governance teams that actually set the stage for all of this. And again, you know, who's gonna decide the standard, We decide we're gonna do this in Oman 5.3 point one um is the standard we're going to utilize. And then once the data is there, this is what gets exciting is then they have the different domain teams where they can ask different research questions depending upon what has interest scientifically to them. Um and so really, you know, we viewed this from the government's perspective is how do we build again the secure platform where we can enable the research, but we don't really want to dictate the research. I mean, the one criteria we did put your research has to be covid focused because very clearly in response to covid, so you have to have a Covid focus and then we have data use agreements, data use request. You know, we have entire governance committees that decide is this research in scope, but we don't want to dictate the research types that the domain teams are bringing to the table. >>And I think the National Institutes of Health, you think about just that their mission is to serve the public health. And I think this is a great example of when you enable data to be surfaced and available that you can really allow people to be empowered and not to use the cliche citizen analysts. But in a way this is what the community is doing. You're doing research and allowing people from volunteers to academics to students to just be part of it. That is citizen analysis that you got citizen journalism. You've got citizen and uh, research, you've got a lot of democratization happening here. Is that part of it was a result of >>this? Uh, it's both. It's a great question. I think it's both. And it's it's really by design because again, we want to enable and there's a couple of things that I really, you know, we we clamor with at end cats. I think NIH is going with this direction to is we believe firmly in open science, we believe firmly in open standards and how we can actually enable these standards to promote this open science because it's actually nontrivial. We've had, you know, the citizen scientists actually on the tricky problem from a governance perspective or we have the case where we actually had to have students that wanted access to the environment. Well, we actually had to have someone because, you know, they have to have an institution that they come in with, but we've actually across some of those bridges to actually get students and researchers into this environment very much by design, but also the spirit which was held enabled by the community, which, again, so I think they go they go hand in hand. I planned for >>open science as a huge wave, I'm a big fan, I think that's got a lot of headroom because open source, what that's done to software, the software industry, it's amazing. And I think your Federated idea comes in here and Ben if you guys can just talk through the Federated, because I think that might enable and remove some of the structural blockers that might be out there in terms of, oh, you gotta be affiliate with this or that our friends got to invite you, but then you got privacy access and this Federated ID not an easy thing, it's easy to say. But how do you tie that together? Because you want to enable frictionless ability to come in and contribute same time you want to have some policies around who's in and who's not. >>Yes, totally, I mean so Sam sort of already described the the UNa system which is the authentication system that encounters has developed. And obviously you know from our perspective, you know we integrate with that is using all of the standard kind of authentication protocols and it's very easy to integrate that into the family platform um and make it so that we can authenticate people correctly. But then if you go beyond authentication you also then to actually you need to have the access controls in place to say yes I know who this person is, but now what should they actually be able to see? Um And I think one of the really great things in Free C has done is to be very rigorous about that. They have their governance rules that says you should be using the data for a certain purpose. You must go through a procedure so that the access committee approves that purpose. And then we need to make sure that you're actually doing the work that you said you were going to. And so before you can get your data back out of the system where your results out, you actually have to prove that those results are in line with the original stated purpose and the infrastructure around that and having the access controls and the governance processes, all working together in a seamless way so that it doesn't, as you say, increase the friction on the researcher and they can get access to the data for that appropriate purpose. That was a big component of what we've been building out with them three C. Absolutely. >>And really in line john with what NIH is doing with the research, all service, they call this raz. And I think things that we believe in their standards that were starting to follow and work with them closely. Multifactor authentication because of the point Ben is making and you raised as well, you know, one you need to authenticate, okay. This you are who you say you are. And and we're recognizing that and you're, you know, the author and peace within the authors. E what do you authorized to see? What do you have authorization to? And they go hand in hand and again, non trivial problems. And especially, you know, when we basis typically a lot of what we're using is is we'll do direct integrations with our package. We using commons for Federated access were also even using login dot gov. Um, you know, again because we need to make sure that people had a means, you know, and login dot gov is essentially a runoff right? If they don't have, you know an organization which we have in common or a Federated access to generate a login dot gov account but they still are whole, you know beholden to the multi factor authentication step and then they still have to get the same authorizations because we really do believe access to these environment seamlessly is absolutely critical, you know, who are users are but again not make it restrictive and not make it this this friction filled process. That's very that's very >>different. I mean you think about nontrivial, totally agree with you and if you think about like if you were in a classic enterprise, I thought about an I. T. Problem like bring your own device to work and that's basically what the whole world does these days. So like you're thinking about access, you don't know who's coming in, you don't know where they're coming in from, um when the churn is so high, you don't know, I mean all this is happening, right? So you have to be prepared two Provisions and provide resource to a very lightweight access edge. >>That's right. And that's why it gets back to what we mentioned is we were taking a step back and thinking about this problem, you know, an M three C became the use case was this is an enterprise I. T. Problem. Right. You know, we have users from around the world that want to access this environment and again we try to hit a really difficult mark, which is secure but collaborative, Right? That's that's not easy, you know? But but again, the only place this environment could take place isn't a cloud based environment, right? Let's be real. You know, 10 years ago. Forget it. You know, Again, maybe it would have been difficult, but now it's just incredible how much they advanced that these real virtual research organizations can start to exist and they become the real partnerships. >>Well, I want to Well, that's a great point. I want to highlight and call out because I've done a lot of these interviews with awards programs over the years and certainly in public sector and open source over many, many years. One of the things open source allows us the code re use and also when you start getting in these situations where, okay, you have a crisis covid other things happen, nonprofits go, that's the same thing. They, they lose their funding and all the code disappears. Saying with these covid when it becomes over, you don't want to lose the momentum. So this whole idea of re use this platform is aged deplatforming of and re factoring if you will, these are two concepts with a cloud enables SAM, I'd love to get your thoughts on this because it doesn't go away when Covid's >>over, research still >>continues. So this whole idea of re platform NG and then re factoring is very much a new concept versus the old days of okay, projects over, move on to the next one. >>No, you're absolutely right. And I think what first drove us is we're taking a step back and and cats, you know, how do we ensure that sustainability? Right, Because my background is actually engineering. So I think about, you know, you want to build things to last and what you just described, johN is that, you know, that, that funding, it peaks, it goes up and then it wanes away and it goes and what you're left with essentially is nothing, you know, it's okay you did this investment in a body of work and it goes away. And really, I think what we're really building are these sustainable platforms that we will actually grow and evolve based upon the research needs over time. And I think that was really a huge investment that both, you know, again and and Cats is made. But NIH is going in a very similar direction. There's a substantial investment, um, you know, made in these, these these these really impressive environments. How do we make sure the sustainable for the long term? You know, again, we just went through this with Covid, but what's gonna come next? You know, one of the research questions that we need to answer, but also open source is an incredibly important piece of this. I think Ben can speak this in a second, all the harmonization work, all that effort, you know, essentially this massive, complex GTL process Is in the N three Seagate hub. So we believe, you know, completely and the open source model a little bit of a flavor on it too though, because, you know, again, back to the sustainability, john, I believe, you know, there's a room for this, this marriage between commercial platforms and open source software and we need both. You know, as we're strong proponents of N cats are both, but especially with sustainability, especially I think Enterprise I. T. You know, you have to have professional grade products that was part of, I would say an experiment we ran out and cast our thought was we can fund academic groups and we can have them do open source projects and you'll get some decent results. But I think the nature of it and the nature of these environments become so complex. The experiment we're taking is we're going to provide commercial grade tools For the academic community and the researchers and let them use them and see how they can be enabled and actually focus on research questions. And I think, you know, N3C, which we've been very successful with that model while still really adhering to the open source spirit and >>principles as an amazing story, congratulated, you know what? That's so awesome because that's the future. And I think you're onto something huge. Great point, Ben, you want to chime in on this whole sustainability because the public private partnership idea is the now the new model innovation formula is about open and collaborative. What's your thoughts? >>Absolutely. And I mean, we uh, volunteer have been huge proponents of reproducibility and openness, um in analyses and in science. And so everything done within the family platform is done in open source languages like python and R. And sequel, um and is exposed via open A. P. I. S and through get repository. So that as SaM says, we've we've pushed all of that E. T. L. Code that was developed within the platform out to the cats get hub. Um and the analysis code itself being written in those various different languages can also sort of easily be pulled out um and made available for other researchers in the future. And I think what we've also seen is that within the data enclave there's been an enormous amount of re use across the different research projects. And so actually having that security in place and making it secure so that people can actually start to share with each other securely as well. And and and be very clear that although I'm sharing this, it's still within the range of the government's requirements has meant that the, the research has really been accelerated because people have been able to build and stand on the shoulders of what earlier projects have done. >>Okay. Ben. Great stuff. 1000 researchers. Open source code and get a job. Where do I sign up? I want to get involved. This is amazing. Like it sounds like a great party. >>We'll send you a link if you do a search on on N three C, you know, do do a search on that and you'll actually will come up with a website hosted by the academic side and I'll show you all the information of how you can actually connect and john you're welcome to come in. Billion by all means >>billions of rows of data being solved. Great tech he's working on again. This is a great example of large scale the modern era of solving problems is here. It's out in the open, Open Science. Sam. Congratulations on your great success. Ben Award winners. You guys doing a great job. Great story. Thanks for sharing here with us in the queue. Appreciate it. >>Thank you, john. >>Thanks for having us. >>Okay. It is. Global public sector partner rewards best Covid solution palantir and and cats. Great solution. Great story. I'm john Kerry with the cube. Thanks for watching. Mm mm. >>Mhm

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020, sponsored by Intel and AWS. >>Welcome back to the cubes coverage of AWS reinvent 2020 I'm Lisa Martin. Joining me next is one of our cube alumni. Breton McMillan is back the director of us, federal for AWS. Right. It's great to see you glad that you're safe and well. >>Great. It's great to be back. Uh, I think last year when we did the cube, we were on the convention floor. It feels very different this year here at reinvent, it's gone virtual and yet it's still true to how reinvent always been. It's a learning conference and we're releasing a lot of new products and services for our customers. >>Yes. A lot of content, as you say, the one thing I think I would say about this reinvent, one of the things that's different, it's so quiet around us. Normally we're talking loudly over tens of thousands of people on the showroom floor, but great. That AWS is still able to connect in such an actually an even bigger way with its customers. So during Theresa Carlson's keynote, want to get your opinion on this or some info. She talked about the AWS open data sponsorship program, and that you guys are going to be hosting the national institutes of health, NIH sequence, read archive data, the biologist, and may former gets really excited about that. Talk to us about that because especially during the global health crisis that we're in, that sounds really promising >>Very much is I am so happy that we're working with NIH on this and multiple other initiatives. So the secret greed archive or SRA, essentially what it is, it's a very large data set of sequenced genomic data. And it's a wide variety of judge you gnomic data, and it's got a knowledge human genetic thing, but all life forms or all branches of life, um, is in a SRA to include viruses. And that's really important here during the pandemic. Um, it's one of the largest and oldest, um, gen sequence genomic data sets are out there and yet it's very modern. It has been designed for next generation sequencing. So it's growing, it's modern and it's well used. It's one of the more important ones that it's out there. One of the reasons this is so important is that we know to find cures for what a human ailments and disease and death, but by studying the gem genomic code, we can come up with the answers of these or the scientists can come up with answer for that. And that's what Amazon is doing is we're putting in the hands of the scientists, the tools so that they can help cure heart disease and diabetes and cancer and, um, depression and yes, even, um, uh, viruses that can cause pandemics. >>So making this data, sorry, I'm just going to making this data available to those scientists. Worldwide is incredibly important. Talk to us about that. >>Yeah, it is. And so, um, within NIH, we're working with, um, the, um, NCBI when you're dealing with NIH, there's a lot of acronyms, uh, and uh, at NIH, it's the national center for, um, file type technology information. And so we're working with them to make this available as an open data set. Why, why this is important is it's all about increasing the speed for scientific discovery. I personally think that in the fullness of time, the scientists will come up with cures for just about all of the human ailments that are out there. And it's our job at AWS to put into the hands of the scientists, the tools they need to make things happen quickly or in our lifetime. And I'm really excited to be working with NIH on that. When we start talking about it, there's multiple things. The scientists needs. One is access to these data sets and SRA. >>It's a very large data set. It's 45 petabytes and it's growing. I personally believe that it's going to double every year, year and a half. So it's a very large data set and it's hard to move that data around. It's so much easier if you just go into the cloud, compute against it and do your research there in the cloud. And so it's super important. 45 petabytes, give you an idea if it were all human data, that's equivalent to have a seven and a half million people or put another way 90% of everybody living in New York city. So that's how big this is. But then also what AWS is doing is we're bringing compute. So in the cloud, you can scale up your compute, scale it down, and then kind of the third they're. The third leg of the tool of the stool is giving the scientists easy access to the specialized tool sets they need. >>And we're doing that in a few different ways. One that the people would design these toolsets design a lot of them on AWS, but then we also make them available through something called AWS marketplace. So they can just go into marketplace, get a catalog, go in there and say, I want to launch this resolve work and launches the infrastructure underneath. And it speeds the ability for those scientists to come up with the cures that they need. So SRA is stored in Amazon S3, which is a very popular object store, not just in the scientific community, but virtually every industry uses S3. And by making this available on these public data sets, we're giving the scientists the ability to speed up their research. >>One of the things that Springs jumps out to me too, is it's in addition to enabling them to speed up research, it's also facilitating collaboration globally because now you've got the cloud to drive all of this, which allows researchers and completely different parts of the world to be working together almost in real time. So I can imagine the incredible power that this is going to, to provide to that community. So I have to ask you though, you talked about this being all life forms, including viruses COVID-19, what are some of the things that you think we can see? I expect this to facilitate. Yeah. >>So earlier in the year we took the, um, uh, genetic code or NIH took the genetic code and they, um, put it in an SRA like format and that's now available on AWS and, and here's, what's great about it is that you can now make it so anybody in the world can go to this open data set and start doing their research. One of our goals here is build back to a democratization of research. So it used to be that, um, get, for example, the very first, um, vaccine that came out was a small part. It's a vaccine that was done by our rural country doctor using essentially test tubes in a microscope. It's gotten hard to do that because data sets are so large, you need so much computer by using the power of the cloud. We've really democratized it and now anybody can do it. So for example, um, with the SRE data set that was done by NIH, um, organizations like the university of British Columbia, their, um, cloud innovation center is, um, doing research. And so what they've done is they've scanned, they, um, SRA database think about it. They scanned out 11 million entries for, uh, coronavirus sequencing. And that's really hard to do in a typical on-premise data center. Who's relatively easy to do on AWS. So by making this available, we can have a larger number of scientists working on the problems that we need to have solved. >>Well, and as the, as we all know in the U S operation warp speed, that warp speed alone term really signifies how quickly we all need this to be progressing forward. But this is not the first partnership that AWS has had with the NIH. Talk to me about what you guys, what some of the other things are that you're doing together. >>We've been working with NIH for a very long time. Um, back in 2012, we worked with NIH on, um, which was called the a thousand genome data set. This is another really important, um, data set and it's a large number of, uh, against sequence human genomes. And we moved that into, again, an open dataset on AWS and what's happened in the last eight years is many scientists have been able to compute about on it. And the other, the wonderful power of the cloud is over time. We continue to bring out tools to make it easier for people to work. So what they're not they're computing using our, um, our instance types. We call it elastic cloud computing. whether they're doing that, or they were doing some high performance computing using, um, uh, EMR elastic MapReduce, they can do that. And then we've brought up new things that really take it to the next layer, like level like, uh, Amazon SageMaker. >>And this is a, um, uh, makes it really easy for, um, the scientists to launch machine learning algorithms on AWS. So we've done the thousand genome, uh, dataset. Um, there's a number of other areas within NIH that we've been working on. So for example, um, over at national cancer Institute, we've been providing some expert guidance on best practices to how, how you can architect and work on these COVID related workloads. Um, NIH does things with, um, collaboration with many different universities, um, over 2,500, um, academic institutions. And, um, and they do that through grants. And so we've been working with doc office of director and they run their grant management applications in the RFA on AWS, and that allows it to scale up and to work very efficiently. Um, and then we entered in with, um, uh, NIH into this program called strides strides as a program for knowing NIH, but also all these other institutions that work within NIH to use the power of the cloud use commercial cloud for scientific discovery. And when we started that back in July of 2018, long before COVID happened, it was so great that we had that up and running because now we're able to help them out through the strides program. >>Right. Can you imagine if, uh, let's not even go there? I was going to say, um, but so, okay. So the SRA data is available through the AWS open data sponsorship program. You talked about strides. What are some of the other ways that AWS system? >>Yeah, no. So strides, uh, is, uh, you know, wide ranging through multiple different institutes. So, um, for example, over at, uh, the national heart lung and blood Institute, uh, do di NHL BI. I said, there's a lot of acronyms and I gel BI. Um, they've been working on, um, harmonizing, uh, genomic data. And so working with the university of Michigan, they've been analyzing through a program that they call top of med. Um, we've also been working with a NIH on, um, establishing best practices, making sure everything's secure. So we've been providing, um, AWS professional services that are showing them how to do this. So one portion of strides is getting the right data set and the right compute in the right tools, in the hands of the scientists. The other areas that we've been working on is making sure the scientists know how to use it. And so we've been developing these cloud learning pathways, and we started this quite a while back, and it's been so helpful here during the code. So, um, scientists can now go on and they can do self-paced online courses, which we've been really helping here during the, during the pandemic. And they can learn how to maximize their use of cloud technologies through these pathways that we've developed for them. >>Well, not education is imperative. I mean, there, you think about all of the knowledge that they have with within their scientific discipline and being able to leverage technology in a way that's easy is absolutely imperative to the timing. So, so, um, let's talk about other data sets that are available. So you've got the SRA is available. Uh, what are their data sets are available through this program? >>What about along a wide range of data sets that we're, um, uh, doing open data sets and in general, um, these data sets are, um, improving the human condition or improving the, um, the world in which we live in. And so, um, I've talked about a few things. There's a few more, uh, things. So for example, um, there's the cancer genomic Atlas that we've been working with, um, national cancer Institute, as well as the national human genomic research Institute. And, um, that's a very important data set that being computed against, um, uh, throughout the world, uh, commonly within the scientific community, that data set is called TCGA. Um, then we also have some, uh, uh, datasets are focused on certain groups. So for example, kids first is a data set. That's looking at a lot of the, um, challenges, uh, in diseases that kids get every kind of thing from very rare pediatric cancer as to heart defects, et cetera. >>And so we're working with them, but it's not just in the, um, uh, medical side. We have open data sets, um, with, uh, for example, uh, NOAA national ocean open national oceanic and atmospheric administration, um, to understand what's happening better with climate change and to slow the rate of climate change within the department of interior, they have a Landsat database that is looking at pictures of their birth cell, like pictures of the earth, so we can better understand the MCO world we live in. Uh, similarly, uh, NASA has, um, a lot of data that we put out there and, um, over in the department of energy, uh, there's data sets there, um, that we're researching against, or that the scientists are researching against to make sure that we have better clean, renewable energy sources, but it's not just government agencies that we work with when we find a dataset that's important. >>We also work with, um, nonprofit organizations, nonprofit organizations are also in, they're not flush with cash and they're trying to make every dollar work. And so we've worked with them, um, organizations like the child mind Institute or the Allen Institute for brain science. And these are largely like neuro imaging, um, data. And we made that available, um, via, um, our open data set, um, program. So there's a wide range of things that we're doing. And what's great about it is when we do it, you democratize science and you allowed many, many more science scientists to work on these problems. They're so critical for us. >>The availability is, is incredible, but also the, the breadth and depth of what you just spoke. It's not just government, for example, you've got about 30 seconds left. I'm going to ask you to summarize some of the announcements that you think are really, really critical for federal customers to be paying attention to from reinvent 2020. >>Yeah. So, um, one of the things that these federal government customers have been coming to us on is they've had to have new ways to communicate with their customer, with the public. And so we have a product that we've had for a while called on AWS connect, and it's been used very extensively throughout government customers. And it's used in industry too. We've had a number of, um, of announcements this weekend. Jasmine made multiple announcements on enhancement, say AWS connect or additional services, everything from helping to verify that that's the right person from AWS connect ID to making sure that that customer's gets a good customer experience to connect wisdom or making sure that the managers of these call centers can manage the call centers better. And so I'm really excited that we're putting in the hands of both government and industry, a cloud based solution to make their connections to the public better. >>It's all about connections these days, but I wish we had more time, cause I know we can unpack so much more with you, but thank you for joining me on the queue today, sharing some of the insights, some of the impacts and availability that AWS is enabling the scientific and other federal communities. It's incredibly important. And we appreciate your time. Thank you, Lisa, for Brett McMillan. I'm Lisa Martin. You're watching the cubes coverage of AWS reinvent 2020.

>> Narrator: From around the globe it's theCUBE with digital coverage of DockerCon Live 2020. Brought to you by Docker and its ecosystem partners. >> Hi, I'm Stu Miniman and welcome to theCUBE's coverage of DockerCon Live 2020. Really excited to be part of this online event. We've been involved with DockerCon for a long time, of course one of my favorite things is always to be able to talk to the practitioners. Of course we remember for years, Docker exploded onto the marketplace, millions of people downloaded it, using it. So joining me is Hui Xue, who is a Principal Deputy Director of Medical Signal Processing at the National Heart, Lung, and Blood Institute, which is part of the National Institute of Health. Hui, thank you so much for joining us. >> Thank you for inviting me. >> So let's start. Of course, the name of your institute, very specific. I think anyone in the United States knows the NIH. Tell us a little bit about your role there and kind of the scope of what your team covers. >> So I'm basically a researcher and developer of the medical imaging technology. We are the heart, lung and the blood, so we work and focus on imaging the heart. So what we exactly do is to develop the new and novel imaging technology and deploy them to the front of our clinical library, which Docker played an essential role in the process. So, yeah, that's what we do at NHLBI. >> Okay, excellent. So research, you know, of course in the medical field with the global pandemic gets a lot of attention. So you keyed it up there. Let's understand, where does containerization and Docker specifically play into the work that your team is doing? >> So, maybe I'd like to give an example which will suffice. So for example, we're working on the magnetic resonance imaging, MRI. Many of us may may already have been scanned. So we're using MRI to image the heart. What Docker plays, is Docker allow us to deploy our imaging technology to the clinical hospital. So we have a global deployment around 40 hospitals, a bit more, around the world. If we are for example develop a new AI-based image analysis for the heart image, what we do with Docker is we can put our model and software into the Docker so that our collaboration sites, they will pull the software that contains the latest technology, then use them for the patients, of course under the research agreement at NIH. Because Docker is so efficient, available globally, we can actually implement a continuous integration and testing, update the framework based on Docker. Then our collaborators would have the latest technology instead of, you know, in the traditional medical imaging in general, the iteration of technology is pretty slow. But with all this latest technology, and such like container Docker come into the field. It's actually relatively new. In the past two to three years, all these paradigm is, it's changing, certainly very exciting to us. It give us the flexibility we never had before to reach our customers, to reach other people in the world to help them. They also help us so that's a very good experience to have. >> Yeah that's pretty powerful what you're talking about there rather than you know, we install some equipment, who knows how often things get updated, how do you make sure to synchronize between different locations. Obviously the medical field highly regulated and being a government agency, talk a little bit about how you make sure you have the right version control, security is in place, how do all of those things sort out? >> Yes, that's an essential question. So firstly I want to clarify one thing. So it's not NIH who endorse Docker, it's us as researchers. We practiced Docker too and we trust its performance. This container technology is efficient, it's globally available and it's very secure. So all the communication between the container and the imaging equipment is encrypted. We also have all the paperwork it saved to set up to allow us to provide technology to our clinician. When they post the latest software, every version they put up into the Docker went through an automated integration test system. So every time they make a change, the newer version of software runs through a rigorous test, something like 200 gigabytes of data runs through and checked everything is still working. So the basic principle is we don't allow any version of the software to be delivered to customer without testing Docker. Let's say this container technology in general actually is 100% automating all this process, which actually give us a lot of freedom so we have a rather very small team here at NIH. Many people are actually very impressed by how many customer we support within this so small team. So the key reason is because we have a strongly utilized container technology, so its automation is unparalleled, certainly much better than anything I had before using this container technology. So that's actually the key to maintain the quality and the continuous service to our customers. >> Yeah, absolutely. Automation is something we've been talking about in the industry for a long time but if we implement it properly it can have a huge impact. Can you bring us inside a little bit, you know, what tools are you doing? How is that automation set up and managed? And how that fits into the Docker environment. >> So I kind of describe to be more specific. So we are using a continuous testing framework. There are several apps to be using a specific one to build on, which is an open source Python tool, rather small actually. What it can do is, this tool will set up at the service, then this service will watch for example our GitHub repo. Whenever I make a change or someone in the team makes a change for example, fix a bug, add a new feature, or maybe update a new AI model, we push the edge of the GitHub then there's a continuous building system that will notice, it will trigger the integration test run all inside Docker environment. So this is the key. What container technology offers is that we can have 100% reproducible runtime environment for our customers as the software provider, because in our particular use case we don't set up customer with the uniform hardware so they bought their own server around the world, so everyone may have slightly different hardware. We don't want that to get into our software experience. So Docker actually offers us the 100% control of the runtime environment which is very essential if we want to deliver a consistent medical imaging experience because most applications actually it's rather computational intensive, so they don't want something to run for like one minute in one site and maybe three minutes at another site. So what Docker place is that Docker will run all the integration tests. If everything pass then they pack the Docker image then send to the Docker Hub. Then all our collaborators around the world have new image then they will coordinate with them so they will find a proper time to update then they have the newer technology in time. So that's why Docker is such a useful tool for us. >> Yeah, absolutely. Okay, containerization in Docker really transformed the way a lot of those computational solutions happen. I'm wondering if you can explain a little bit more the stack that you're using if people that might not have looked at solutions for a couple of years think oh it's containers, it's dateless architectures, I'm not sure how it fits into my other network environment. Can you tell us what are you doing for the storage in the network? >> So we actually have a rather vertical integration in this medical imaging application, so we build our own service as the software, its backbone is C++ for the higher computational efficiency. There's lots of Python because these days AI model essential. What Docker provides, as I mentioned, uniform always this runtime environment so we have a fixed GCC version then if we want to go into that detail. Specific version of numerical library, certain versions of Python, will be using PyTorch a lot. So that's our AI backbone. Another way of using Docker is actually we deploy the same container into the Microsoft Azure cloud. That's another ability I found out about Docker, so we never need to change anything in our software development process, but the same container I give you must work everywhere on the cloud, on site, for our customers. This actually reduces the development cost, also improve our efficiency a lot. Another important aspect is this actually will improve customers', how do they say it, customer acceptance a lot because they go to one customer, tell them the software you are running is actually running on 30 other sites exactly the same up to the let's say heights there, so it's bit by bit consistent. This actually help us convince many people. Every time when I describe this process I think most people accept the idea. They actually appreciate the way how we deliver software to them because we always can falling back. So yes, here is another aspect. So we have many Docker images that's in the Docker Hub, so if one deployment fails, they can easily falling back. That's actually very important for medical imaging applications that fail because hospitals need to maintain their continuous level of service. So even we want to avoid this completely but yes occasionally, very occasionally, there will be some function not working or some new test case never covered before, then we give them an magnet then, falling back, that's actually also our policy and offered by the container technology. >> Yeah, absolutely. You brought up, many have said that the container is that atomic unit of building block and that portability around any platform environment. What about container orchestration? How are you managing these environments you talked about in the public cloud or in different environments? What are you doing for container orchestration? >> Actually our set-up might be the simplest case. So we basically have a private Docker repo which we paid, actually the Institute has paid. We have something like 50 or 100 private repos, then for every repo we have one specific Docker setup with different software versions of different, for example some image is for PyTorch another for TensorFlow depending on our application. Maybe some customer has the requirement to have rather small Docker image size then they have some trimmed down version of image. In this process, because it's still in a small number like 20, 30 active repo, we are actually managing it semi-automatically so we have the service running to push and pull, and loading back images but we actually configured this process here at the Institute whenever we feel we have something new to offer to the customer. Regarding managing this Docker image, it's actually another aspect for the medical image. So at the customer side, we had a lot of discussion with them for whether we want to set up a continuous automated app, but in the end they decided, they said they'd better have customers involved. Better have some people. So we were finally stopped there by, we noticed customer, there are something new to update then they will decide when to update, how to test. So this is another aspect. Even we have a very high level of confirmation using the container technology, we found it's not 100%. In some site, it's still better have human supervision to help because if the goal is to maintain 100% continuous service then in the end they need some experts on the field to test and verify. So that's how they are in the current stage of deployment of this Docker image. We found it's rather light-weight so even with a few people at NIH in our team, they can manage a rather large network globally, so it's really exciting for us. >> Excellent. Great. I guess final question, give us a little bit of a road map as to, you've already talked about leveraging AI in there, the various pieces, what are you looking for from Docker in the ecosystem, and your solution for the rest of the year? >> I would say the future definitely is on the cloud. One major direction we are trying to push is to go the clinical hospital, linking and use the cloud in building as a routine. So in current status, some of sites, hospital may be very conservative, they are afraid of the security, the connection, all kinds of issues related to cloud. But this scenario is changing rapidly, especially container technology contributes a lot on the cloud. So it makes the whole thing so easy, so reliable. So our next push is to move in lots of the application into the cloud only. So the model will be, for example, we have new AI applications. It may be only available on the cloud. If some customer is waiting to use them they will have to be willing to connect to the cloud and maybe sending data there and receive, for example, the AI apps from our running Docker image in the cloud, but what we need to do is to make the Docker building even more efficiency. Make the computation 100% stable so we can utilize the huge computational power in the cloud. Also the price, so the key here is the price. So if we have one setup in the cloud, a data center for example, we currently maintain two data centers one across Europe, another is in United States. So if we have one data center and 50 hospitals using it every day, then we need the numbers. The average price for one patient comes to a few dollars per patient. So if we consider this medical health care system the costs, the ideal costs of using cloud computing can be truly trivial, but what we can offer to patients and doctor has never happened. The computation you can bring to us is something they never saw before and they never experienced. So I believe that's the future, it's not, the old model is everyone has his own computational server, then maintaining that, it costs a lot of work. Even doctor make the software aspects much easier, but the hardware, someone still need to set-up them. But using cloud will change all of. So I think the next future is definitely to wholly utilize the cloud with the container technology. >> Excellent. Well, we thank you so much. I know everyone appreciates the work your team's doing and absolutely if things can be done to allow scalability and lower cost per patient that would be a huge benefit. Thank you so much for joining us. >> Thank you. >> All right, stay tuned for lots more coverage from theCUBE at DockerCon Live 2020. I'm Stu Miniman and thank you for watching theCUBE. (gentle music)

you live from Miami Beach Florida 2019 brought to you by V we're back this is the cube the leader in live tech coverage we're here in Miami this is a wrap of v-mon 2019 two days of coverage I'm Dave Volante with my co-host Peterborough's our third year covering v-mon we started in New Orleans we've seen you know veeam go from what they called at this show act one to act two and we talked two years ago about you know to the our first V Mon about the ascendancy of Veeam being so tightly tied to the rise of virtualization and now we heard this year act to being cloud multi cloud and we heard a number of announcements that are in support of that we're going to talk about that but Peter there were three key announcements this week one was the the billion dollar you know milestone they actually you know they finally hit a billion dollars I've been talking about it for a while it's now official billion dollars on a trailing 12-month basis they're a profitable company veem and a focused billion dollar yeah I think that's really a very focused I mean they do some M&A but not a lot of M&A and that's because of NIH I mean you know these guys they trust themselves to write code it's also it's also sustained that simple value proposition right and that's a in a fundamental Dogma I think I think it's fair to say we we heard the announcement of the the the with Veeam a API infrastructure which which is key we're going to talk about that we I think there were two companies they announced partnerships with Nutanix with mine and exa grid both taking advantage of that there will be others can ring doll just told us you know maybe 10 to 12 it's not going to be an enormous number at least for secondary storage yeah but and but that'll knock down a large portion of the infrastructure market and then a Veeam availability Orchestrator version 2 which allows you to do if fast backups recover from from backups without having to go to a replicated you know off-site and some other capabilities they call the dynamic documentation and automating testing and some DevOps capabilities so you know the people seem pretty excited about that it wasn't a sea of announcements like you see it some of these things which I think Peter talks to the degree of focus that you were just mentioning you know they're not about your bragging rights and the number of announcements that they can make you know it's really all about extending that platform a lot of incremental announcements ratmir told us not a big roadmap company even though he did show a roadmap today but the roadmap he showed was a lot of near-term functional improvement so very function rich you know the the tagline of it just works but um let's see I think there's the first time you and I have done v-mon together I've been here your impressions look I love wandering the halls and talked into the actual attendees and seeing what they have to say so I spent about an hour hour and a half just doing some work in one of the hallways here and one of the reasons I do that is because it's an opportunity here with the attendees and the customers are talking about and what's important to them you've got a lot of these shows and everybody's buzzing about one or another product announcement you go here and everybody's talking about the problems that they're solving and I think that one of the reasons why we didn't have this frenzy of product announcements like we have in so many other places because the focus is though because a lot of companies want the focus to be on them I think what we heard here or what I heard here somewhat different was again customers trying to solve the problems and Veeam creating an opportunity for them to talk in terms of some of the new directions and some of the new products that being are being introduced but the focus stayed on the customer and the problems of trying to solve and that's that's what to my mind that's what successful companies focus on yeah and I come back to this notion of the with Veeam the whole API integration cloud hybrid cloud the edge V wants to be and they've laid they laid this vision out you know certainly last year and even started the year before of of essentially being that that that backup capability data protection capability across wherever your data lives you know on from in cloud now they really are focused on on backup and data protection they even say backups where it starts a lot of other companies like don't even use the term backup no it's not about backup it's about data management and data protection so it's interesting that veem is really focused on on backup and when you do what you did and talk to the customers what do you use the V for backup backup backup backup and so so they're not over rotating to that vision now they're many of their competitors are going hard after that and doing some great great marketing so the competitive dynamics are very interesting now you got cohesive e you got rubric doing really well with positioning as a modern architecture in veeam definitely not a legacy company their business is growing you've got you've got CommVault you've got Dell EMC Veritas IBM you know trying to hit single-digit growth trying not to decline I mean IBM in particular declined and then and really had to do a deal with CAD illogic to stop veem from eating its market share that's really what that deal was all about you saw Dell EMC kind of take its eye off the ball when it merged with with Dell EMC you know it was the leader in in purpose-built backup appliances it's made some announcements recently to try to get you know it's got some really good start back in the game right so you know you don't ever count those guys out Comicon vaults approached it differently they've got a large install base you know Veritas went through private equity and so they had some some other challenges but again they're investing and so it's a big market you know people are gonna go fight hard for it and then and then with with the outside funding that's come in it's really up the game now a lot of that funding is gonna go to promotion which again comes back to your point about focused R&D really really important to focus R&D on things that customers want that you're gonna solve a business problem so if you go back and just just to take your segmentation and we can kind of look at it in a couple of perhaps simple ways you've got you've got you've got veem and companies like beam who saw the hole virtualization and the need to do a better job of supporting and protecting and and replicating and backing up virtualized resources all hitting the market pretty hard and then you have the Delhi MCS and a lot of the other companies that you mentioned trying to sustain or keep pace with those guys and then you have the new guys the Dhruv is and what not are we talking about just cross cloud multi cloud backup on top of that you have and something we talked about with a couple of guests the security guys are looking at this and saying wait a minute you know data is data and protection and security are going to be increasingly difficult to separate because data is going to move and I have to be able to move security with the data it's going to be an inevitability it's we're talking about a cloud that allows us to more do more distribution of data because we're gonna do more distribution of work and the security is gonna have to move for the data so the security guys are gonna get in this the networking guys are gonna be asked some questions about the opportunity you got the old guard who is more focused on devices and managing and backing up devices trying to get back in you got the new guys you're saying let's let's lead the the the act to before you know the veins get there it's gonna be an extremely complex market but all of its gonna boil down to this simple fact I'm gonna distribute data in response to the work that needs to be performed and how am I going to manage the digital assets that I have to make that easy so that it doesn't explode and all of these companies at some point kind of the next phase of this is going to be on protecting data but can I turn it into a digital asset so here's what I saw I saw them talking about the idea of you know what we're gonna protect locally I'll suggest it over the course the next couple of years it's going to be we're gonna do you know data asset management with protection with where the actual act of protecting it is similar to the act of defining it as an asset so being able to you know use a a snapshot for a lot of different uses already happening now but adding services you know a consistent set of services on top of that through with veem and other resources allow them to do that and then move more of that what's today regarded as replication function into that protection side of things a lot more support for locally because that's where the services are going to become having the services are not having the services it's really going to be an essential question because we're gonna move more of this data out to where the work is going to be profound we often talk about customers having to place bets but but the the the vendors are having to place bets as well they're obviously betting on multi-cloud but but juxtapose for example what themes doing it was interesting to hear ken ring doll he answered your question about whether it was em through M&A and he answered in an M&A context but or maybe organic development around more security functions and he kind of said Never Say Never but really focused the team the engineering team is really focused on backup and data protection and what they call data management juxtapose that now with way say for instance what a daydream is doing X data domain guys built their own file system trying to bring both primary and secondary stores together yeah and which I like and I think it's really powerful themes taking a different approach they're saying and with with VM api's we're gonna partner with pure we're gonna partner with with Cisco we're gonna partner with Nutanix so different approach and they're gonna obviously you know claim the same capability hey we can do that too you know date tree I'm saying well we can do that too with just one mousetrap you know the integration points etc so it's gonna really be interesting to see how that all shakes out that that word seamless you know I said it sometimes triggers me if it really is seamless you know theme has a go to market advantage relative to you know the the Swiss Army knife approach if it's not seamless then you know ad atrium approach will have an event it's from a product standpoint you and I both know there's so much more to success than just having a great product absolutely you know and mentioned it but but here's you know it's interesting one of the thought about what will the roadmap the practical roadmap because FEMA's altered its roadmap in response to customer demand quite frankly very successfully and and and and you know you got to applaud him for doing so but one of the things we heard was it look we don't want we don't want to over promise on the engineering front because you've got a certain number of Engineers and a certain engineering capacity focus them on things that are creating value to the problems you're trying to solve the same things true within a lot of user shops you don't want to throw a whole bunch of new function to new requirements and a bunch of guys who are still themselves trying to evolve from backing up devices to now actually protecting data and and so there's a there's a natural evolution that's going to take place and I and I think veeam that's done a pretty good job of keeping their finger on what that pulse is it's it's what can be invented but also what can be innovated if we think of innovation as the customer adopting and applying it and betting it and changing their activities around it and I think themes done a pretty good job of navigating you know that what can customers really do right now not getting too far ahead so a lot of these guys that the natural tendency that you come from a product perspective and you say put more into the product and you know get the better check marks and you know have the better it's better statute is better factsheet and I think Veeam is taking a simpler approach almost an apple like approach is an enterprise sense and saying look give them what they can a candle give them what they can use give them what's going to generate value and as they master that give them a little bit more it reminds me of is you said Apple it reminds me of early EMC days when EMC brought out you know it's symmetric it was it would connect you know AIX solaris unisys obviously the IBM mainframe it had all the optionality all the connectivity and that's kind of what would be and then the features that it announced were really practical they clearly solved the problem now since then you know MCS evolved into the checkbox so we have more features than anybody that's what happens when you everybody wants right you have the customer base everybody wants and they say check we have that thin provisioning we have that too and you know we're gonna freeze the market that's the you know much more mature company in their defense it's also in response to an increasingly specialized and complex customer base they're trying to cover all the base and you know competitive guys eating that they're absolutely absolutely and the sales guys saying hey we need something and they've done a great job of doing that but but Veeam is very very focused on the optionality in four years they they wouldn't talk about bare metal and a couple of years ago would beam on the big thing was hey we said for years that were only virtualization well guess what now we do bare metal that was sort of the one the big announcement one year so they're they're very judicious about how they allocate their R&D you know capital and in you're seeing that you know translate into function that actually gets used actually give yeah I think it's a key point I think your analogy with EMC is actually really good Dave because if you go back thirty years when the EMC first started getting going what was the problem controllers on mainframes and mini-computers were getting incredibly complex it's you know the Daddy controllers and the amount of processing that was being put into that in the microcode was just overwhelming most people's ability to deal with it and so MC came along and said well if that's the problem can we fix it we put cash in that'll just make this whole system simpler and then they stayed true to that for a number of years and they turn into a beer mark and it's interesting I think it is a good analogy because what is the problem the problem is data's going to be more distributed it's going to be more central to a company's mission it's gonna be used by more functions and repurposed into more applications that have a greater diversity of RTO and RPO and as a consequence they're saying they seem to be saying we're going to do our best to pose much function to that protect side of things local as we possibly can so that people who aren't PhDs in computer science to perform a real business service by making all that stuff work and then will at the same time work very closely with third parties who can bring specialization of that secondary storage to bear as the specialization increases because it's going to increase and the other the other you know China MB a case study example that I would point to is the early days of Veritas when Jim when Jeremy Burton was running Merrick marketing it Veritas II sort of coined the language Jeremy calling the no hardware agenda a pure software a lot of function and they you know rose to a couple of billion dollar you know in revenue you know very very successful now have the big install base that everybody wants to eat it's just again reminiscent the pure software company they're not shipping boxes they're not shipping appliances they're they're not selling direct their pure channel play there's a big tamp to just continue to do virtualization like the big question is are they going to will their focus on what they're currently doing translate into focus on multi cloud and here at this conference they're claiming yes we've heard nothing that suggests that they won't be able to but there's a lot of new players out there who are looking at that space and saying you know what I can do that too and there's gonna be a lot of invention a lot of investment and you know there's good reasons to suspect it beans gonna be able to evolve successfully but there are a few areas where I think they're gonna have to focus more time in the big part of a CEOs job is Tam expansion and you know right now there are you know a billion out of fifteen let's call it so there's a long way to go but as you point out that multi-cloud appears like it's gonna be lucrative and there's a lot of different companies coming at it from from different angles you guys tell me we look at it is this big blob yeah this is gonna be incredibly specialized very fragmented I mean you got Cisco coming at it from a networking perspective RedHat coming from a past perspective Google you know partnering everybody Amazon right now ignoring it but you guarantee they're gonna be awesome and Microsoft has to be in it because of the huge estate of on-prem you know software and there's a dozen security guys are gonna be looking at this and saying oh look data in motion that's my service now is going to get its pieces so very interesting how that's all gonna shake out it's okay so wrap it up Peter you know kind of summarize your thoughts on the space v-mon so first beam on for me a lot of customers that we're talking about solving complex problems during their digital business transformation that's always good to hear got to a billion dollars that's a great milestone for any software company good reasons is the fact that beam is going to evolve into a company like Veritas like one of the big guys this is a company that's got legs and I think that the final one that I'd say not got legs but that they've got what it takes to be able to affect this transition they probably got the execution chops look we had a user on here who effectively said if you're not using if you're CIO and you're not using veem you're not competent and you know he said that that's not that's not a bad testimonial when you come down to it yeah and then the one thing that we have not talked about which is it shines through is culture yeah you know this company has a culture that is a winning culture it's a fun culture there's an accountability associated with it and and very customer orientation solutely up so that's the winning formulas have been fun sort of watching these guys grow and interacting with a number of their customers and you saw you saw a couple years ago Veeam saying okay we're going Enterprise so I ain't so easy there's just say we're going enterprise but in interestingly even though they've somewhat retrenched from that messaging they're having success in the enterprise clearly with their partnerships with guys like HPE at Cisco and NetApp and and others and so they're just gonna let it bake a little bit and go from there position of strength which is that you know kind of s in an MB do more simply with your protection environment is not a bad story a company of any size right right and okay Peter hey you spent great working with you thank you and thank you for watching guys great job awesome go to Silicon angle comm you'll see all the news the cube net is where we host all these videos and you'll see wiki bond comm has all the research Peter recently wrote a great piece on on data protection and how that markets involving check out our Twitter at the cube and at the cube 365 Twitter handles you'll see all kinds of clips coming out of this show and other shows let's see where we got a lot coming up good for you and what do you think so I think you're seeing as I said before a very practical approach to gaining foothold and in maintaining and growing in a market I like the business model this this company has been somewhat opaque you know european-based you know the Russian founders but and and most of us businesses outside of the US and and I think they're really coming into the mainstream now and Cube helps make it more transparent yeah absolutely and right because you can ask the questions of people and you know you get you get all kinds of different answers so and we're able to have you know independence on you know guys like Justin the firm's like the four five one guys that you know Gartner coming on and and it's fun to have those guys so so it's been great thank you for watching the cube go to the cube dotnet check out the events that are coming up we got a huge huge season May and June or our busiest months take a slight break in July although you know we'll be cranking this summer as well so thank you for watching everybody we're out Dave a lot day for Peterborough's we'll see you next time

>> Live from Miami Beach Florida, it's theCUBE. Covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to Miami everybody, we're here at the Fontainebleau hotel. You're watching theCUBE, the leader of live tech coverage. This is day one of our coverage of VeeamON, the third year that we've covered Veeam, they've selected this great location here in Miami. I'm Dave Vellante, with my co-host Peter Burris. Ratmir Timashev is here, he is the co-founder and executive vice president, world-wide sales of Veeam, business guru, sales and marketing maven, a very successful entrepreneur, welcome to the theCUBE and thanks so much for having us. >> Thank you Dave, thank you Peter, thanks for having us. Thanks for doing this at our event. >> You're very welcome, so first of all congratulations, you hit that billion dollar milestone. You predicted it back in 2013, you missed it by about six months Ratmir, you know, (laughs) but really, great. Trailing 12 months, a billion dollars in revenue that includes of course your Ratable revenue, the subscription revenue, which who could have predicted that back in 2013, so amazing milestone, congratulations. And great venue here, you must be really pleased with the turnout, couple thousand people, your thoughts? >> Yeah absolutely, I personally love Miami, this is the best city. Always sunny, always ocean, always blue sky, awesome. And always sand, like that's the best place. So I've always had the dream to have VeeamON in Miami, so the dream comes true, we have over 2,000 people here and many more are watching livestream online. Very excited, very excited. >> Well, Veeam's always been a hip company, always a lot of fun, this is obviously a hip place, good fun part of the country. Let's talk about act one and act two. Act one was, you guys really rode the virtualization wave and you talked today about act two really being cloud and hybrid cloud data management. What are the similarities and the differences between act one and act two? >> So like we discussed during the keynote session, every 10 years or so there is a major industry transformation shift from one platform to another platform, so Veeamware 10 years ago created this technology visualization that dramatically fundamentally changed the way modern data centers are built and managed. And Veeam was very lucky to be at the earlier stage of that virtualization revolution that changed the whole data center. that changed the whole data center. So we were at the right time at the right place. We created the new market, Veeamware backup, and then we extended it to hyperV and HV. So we dominated that mode of data LAE share. But in the last few years we expanded our platform. So beyond just the virtualization, we added the physical support, the Unix support, the cloud support. So now Veeam represents broad, what we call Veeam Availability Platform that supports LAE clouds, virtual, physical clouds. That was act one, we dominated it. We grew from zero to 1 billion within 10, 12 years. We added 350,000 customers over that timeframe. And now it's act two, what is act two? Act two is the, again, the new major industry transformation to a hybrid cloud. What are the similarities? Again, Veeam is in a great position because we're at the right time at the right place with a brilliant product. We have the broad LAE system of our channel partners. We have a broad customer base, 350,000. And we have great technology partnerships with HP, Cisco, NetUP, Nutanix, Pure, and others, so as well as AWS, and Microsoft, and Google, and IBM cloud. So we are in extremely great position to dominate this second wave, what we call second act, which will be the next decade of hybrid cloud. >> Yeah, so optionality was a key, being able to support multiple use cases and supporting different environments. You're well positioned, you're saying, in act two. Act one you really didn't have a lot of competition, you kind of schooled the competition, I think Dell took out some of your early competition then you ran circles around everybody else. A lot more money pouring into this space now, you showed the slide, 15 billion, you've got a 15th of it. Tell us again why you feel like you can, you just used the word, dominate, with all this competition. You got the big guys now sort of learning from you and trying to copy some of your moves and maybe pre announcing some stuff to try and freeze the market. What gives you great confidence that you will dominate act two. >> Again, we have a history of innovation, so we know that there are new requirements for the hybrid cloud. People not only want to protect the data, they want to make sure that when they move to a hybrid cloud, when they put the workloads in a public cloud, that that data is protected, is secured and protected. So that's one capability that customers are looking for. Another capability, they want to be able to move the data back on-prem, or between the clouds, what we call cloud mobility, so they want to have this flexibility and freedom, be cloud agnostic or avoid that cloud lock-in. So they want to also make sure that from compliance standpoint, they are able to move the data if needed. In other use cases they want to leverage the cloud for different data protection capabilities. They want to leverage the cloud for backup, for disaster recovery as well as for long term retention, what we call cloud tier, so they want to, instead of tape, they want to replace tape with the public cloud low storage. So they want to use the cost and the skill ability of the public cloud for long term retentions. So all these use cases, extension of our platform. So we already have the, we own the one component of the hybrid cloud which is on-prem, modern data center, what some people call private cloud. We already own one component and we have 350,000 customers. Most of these customers are going to deploy hybrid cloud. In fact, according to our survey, 73% of our customers are deploying or planning to deploy a hybrid cloud. So most of them I think, in how to leverage the performance, the skill ability, and the elasticity, of the public cloud. So we own this component, we have the capabilities and we're developing product capabilities for the public cloud and with our orchestration on top of it and monitoring and analytics capabilities. So it's a complete solution. >> So Ratmir, I want to build upon this notion of act one and act two because good for you guys over ten years but the industry also is going through an act one to act two when you come right down to it. Where data, for the first four years of this industry, was about recording events that have happened. And now data going forward is becoming a strategic asset that's actually shaping the events that are happening or will happen. And it requires a new approach. It requires that data be regarded as a strategic asset and capabilities have to be established to support that data. I'm especially itched in with the introduction that you made because it suggests that you guys are going to look to an ecosystem to bring that degree of specialization and uniqueness and invention, on top of your platform, to serve a rapidly expanding range of strategic capability requirements when we think about data protection, data assurance. Do you see it the same way? >> Absolutely yeah, I 100% agree. I talked about that briefly during my keynote. We see that there are this four technology superpowers what Pat Galson from Veeamware calls technology superpowers. And those are the cloud, the mobile, artificial intelligence and age in internal things. So all this four technology superpowers. The biggest producers and consumers of the data. So it has to be both in the cloud and on the age so the new product and services are built on that data. Either we are talking about self driving cars, or we are talking about breakthrough in DNA research or cancer research. It's all built both in the cloud and on the age. And Veeam has this technology called data lapse. So when we've actually provide the access to the data, to a field party, either security or compliance or analytical tenders. So they can build more solutions on top of our data lapse. >> So talk a little bit about how you planned to deploy capital going forward, particularly as you try to leverage the opportunities in cloud two. You're seeing all kinds of new emerging technologies. We talk about coup berneties and containers all the time. You've made some acquisitions in the cloud area. Should we think about your emanate strategies as just sort of advancing your ability to either form ecosystems or actually bring in more cloud like capabilities, beyond act one into act two? >> Yeah I mean, first of all, we have a very powerful product and RNZ group. Partially we have this mentality not invented here so in other words we want to invent more in house. However, there are some cases where we need to extend our platform and we might not have the bandwidths or time through market so we're looking at some adjacent in the cloud management space, in the cloud optimization, course optimization, analytics. Those areas are very interesting for us to expand our platform to. >> I'm guessing that NIH mentality, acquisitions you make have to fit into that platform, that architecture. How do you evaluate? You say okay, can we do this ourselves? You say do we have the bandwidth? Is that technology here now? >> Does with Veeam help? >> Yeah with Veeam that's a great problem that we announced today as well. Yeah so the way we evaluate is that, is this adjacent market to what we're doing? For example, AWS or Asur, how close the buyer is. Or Office 365 backup we evolved in house. Or Office 365 backup we evolved in house. Azureware developed in house. Some technologies we are looking to acquire. The question is, is that the same buyer? If the buyer is the same, we prefer to develop in house. If the buyer, for now, is different, we would like to acquire the company and let it grow, and then merge into Veeam later. >> So your co founder runs RND correct? >> Correct >> And you run sales and marketing? So you guys fight over how you're going to allocate the dollars. But as a specialist in data protection, you're allocating all of your RND funding toward data protection. Presumably that helps you compete against the guys who are doing primary storage, secondary storage, all kinds of other software. So when you think about that road map, you told the story about how you got inspiration. You went to Silicon Valley and you were flying back and your partner said, well you know the best product just doesn't always win but you said, whoa so what, do we not invent the best products? You want to have the best products. Talk a little about that sort of organic development. How you guys think about that approach. Where the ideas come from. Is it obviously the customer input? Your knowledge of the space? Where do you see that going? >> So Veeam we believe is very different from other companies. First, we don't build long term road map because the technology is changing so fast that we want to keep that flexibility and agility to change our roadmap. We only disclose our release that we're imminent. Within the next six, nine months we already know. Beyond that, we don't provide the roadmap. We have the vision but we don't have the roadmap with the exact specific dates. >> But it's not a waterfall thinking. It's more agile applied to our-- >> Exactly, agile and flexibility that's what's, agility and flexibility that's what's most important. For example, a year ago or even two years ago when we announced version 10. We didn't know that object storage will become such a needed hot thing that all our customers are asking for. Including the on-prem object storage and the cloud object storage. So we changed our plans and we put lots of resources into object storage. And we finally released the best capability to use the object storage. We believe that object storage is the next cool thing in cloud data management because it will provide 10 times more capacity at the 10th of the course and 10 times faster performance. So it's like it's the next cool technology. That's just one example. Another thing is that, what differentiates Veeam in terms of RNZ and product strategy is that, if we release the feature, we don't do it as a marketing check box, we do cloud storage or we do object storage or we do this or we support Azure. When we design the feature, we think about is it going to be really really valuable? So that our customers, when they get it, they say wow, that's exactly what I needed. So we don't do as a marketing check box, we do provide and our customers really value that. They expect from Veeam that when Veeam releases something, it's going to be useful. >> And easy to use. >> Easy to use and very useful. >> That's important because when you're on offence, you don't have to do check box marketing. We know that a lot of times companies will do check box marketing 'cause they'll hear it in the field. The innovater has it, oh we have it too. And when you really peel the onion you see the differences and start to move forward. Okay so let's talk a little about customers. You had United Health on today. What are you hearing from customers? What are the customers saying that are inspiring you and your team? >> Today's conversations with the customers they start with the modernizing the, continue modernizing their data. A lot of customers still use the legacy backup solutions. They want to modernize. But the conversation quickly shifts to the hybrid cloud. How Veeam is going to help me not only modernize the backup data management on-prem, but how Veeam is going to help me to move to the cloud, manage the data, orchestrate the data movement in the cloud and maybe if needed, bring the data back for compliance reasons. So that conversation always occurs with any size companies. In fact, according to our survey, 73% of our customers say that they have a hybrid cloud strategy. Only 10% say no, we will always stay 100% on-prem. And about 15% say I will move everything to a public cloud. The huge majority is in the middle. 73% have the hybrid strategy. >> Yeah that sort of answers my next question but I'm going to ask it anyway. So an observer might well aren't the cloud guys just going to do their own backup and recovery. Why wouldn't that supplant Veeam? You sort of addressed it with the hybrid approach but I want to hear your answer. All the cloud guys have some form of replication or snapshotting, granted it's not as robust, you and I know that. But for the audience, explain to them why the cloud doesn't put you out of business. >> In fact cloud represents the biggest opportunity for the next 5-7-10 years. It's just historically, the platform vendors they don't provide the good tools, security tools or backup tools. We've been in this business over 25 years. Our first company was specialized in Windows Enterprise Management so we developed lots of tools around Microsoft platforms for managing active directory exchange server, share points, equal server. We always were afraid maybe Microsoft will come up with the similar solutions but they never did. The same is for today's world. Customers want to have the independence from the platform and the vendor, like AWS or Microsoft, they will never provide the capability to move the data outside of AWS. But for the true compliance security, a vendor like Veeam you need the capability not just backup AWS to AWS but you want to be able to backup AWS to on-prem and on-prem to AWS. Or AWS to Azure. So only Veeam can platform vendors, they are not looking to do that. So they want to move the data to the cloud. They're not necessarily providing more capabilities. Move the data outside of their cloud and that's where Veeam comes in, with the cloud mobility capabilities. >> One of the things that our researchers strongly pointed out, is that there are few places within a technology set of capabilities that they must control. And data protection is one of them. So they have to have an approach for managing data protection within their business that's their approach. And there are a few companies in a position to actually provide that. >> Yeah, I absolutely agree. Some customers they think that if I put the data into AWS or Azure or Office 365, Microsoft is going to protect it or AWS. No, it's your data, microsoft protects the infrastructure. So it's a off time service. That's where Microsoft or AWS are responsible. The data is yours. You are responsible for protecting the data recovery. If you delete an email, it's not Microsoft's fault. If you need to do an e-discovery on your email system, that's not Microsoft's problem. >> If you're out of compliance, Microsoft executives aren't going to jail. >> Exactly. That's your responsibility. Your data, Your responsibility. In fact we have a white paper that talks about the shared responsibility model. So there is a shared responsibility. AWS, public cloud providers, they're responsible to keep the service up and running. So therefore resilient infrastructure. Not the data, the data is yours. That sits on top of that resilient infrastructure. >> Yeah you've gone after Office 365 as the starting point for SaaS. Maybe there's other opportunities down the road. Right now it's probably a small market but I think it could emerge over time. But the overall time, you showed $15 billion. Today you have 1/15th of it. Lot more competition today. You see some of your competitors risk $250 million you have to one up them with a $500 million risk. You told me years ago Ratmir, we're probably not going to do an IPO. Give us an update there, same stance on that? >> No we've actually very open to the idea about IPO and we're exploring different opportunities. But we believe that we can continue growing organically because the company is very profitable. So we're reinvesting money into RNZ and we have good foundation for the next act two. But speaking about Office 365 by the way, it's the fastest growing product in the history of Veeam. >> Really? >> Of backup for Office 365 is the fastest growing because we have 350,000 customers, most of them are using Office 365 and they need to protect that data. So and they love Veeam, they are buying. But also we'll actually need new customers just buying Office 365. 23% of our customers for Office 365 are new customers. Also a little bit surprising for us. >> So O365 OneDrive is another opportunity that you guys have gone after. >> It's all part of the same product, yes. >> Salesforce maybe not quite there yet but you could potentially see that emerging as an opportunity? Do you see that? >> Yes we are looking at Salesforce. We are looking at G's width. We are looking at other SaaS applications that are popular among the business customers. >> One point really quickly Dave, is that 1/15th of that $15 billion TAM is just Veeam. Your ecosystem is increasingly going to use the Veeam services to expand the Veeam share of that, the virtual Veeam share of that, even as you grow. I think that's what's particularly interesting is how will that ecosystem add additional services on top of that, to grab more of that overall share. >> And I think, and please comment on that, that's unique to Veeam and the data protection space. You have your own events. You have premier partners that come in. Some of your competitors don't, they're not quite there yet. Some of the other larger competitors it's a small little piece of their whole business so the focus really is accentuated. >> Veeam has always had a channel part in ariant stretch. From day one we were 100% channel, 100%. We don't take the deal directly. Also, we build the broad service provider system network. So we have over 20,000 what we call Veeam cloud and service providers that provide the services to our customers based on Veeam platform backup in the cloud, disaster recovery, manage backup. Finally today we announce with Veeam that's another new initiative that we are expanding our ecosystem with Veeam APS where we want our partners, together with us, build this secondary storage systems that provide a single solution because some customers they want to buy in the form of the hardware appliance, our solution. So it's going to be pre installed, similar experience, out of the box functionality, easy to deploy, easy to manage with a single interphase. All provided and with a single support wise. So those systems will be created together with our partners. Like we announced one with Nutanix as well as with ExaGrid. We are working, Nutanix is one of the most innovative companies in our industry and we were very happy to partner with them because we believe that we will develop the right solution and we will be able to take this APS and offer our other partners to Build a secondary storage system, together with us. >> Well we've seen this little company, years ago, called Veeam, what a great name, superglue itself to the virtualization trend and really ride that wave now going onto act two, which is a cloud rapid timid shift. Thanks so much for coming to theCUBE. Great to see you again. >> Thank you Dave. >> Keep right there everybody. This is theCUBE, we're here at VeeamOn2019 in Miami. We'll be right back after this short break.

>> Narrator: From Berlin, Germany, it's theCUBE, covering Dataworks Summit Europe 2018. Brought to you by Hortonworks. >> Well hello, welcome to the Cube. I'm James Kobielus, I'm the lead analyst for the Wikibon team within SiliconANGLE Media. I'm your host today here at Dataworks Summit 2018 in Berlin, Germany. We have one of Hortonworks' customers in South America with us. This is Fernando Lopez of Quanam. He's based in Montevideo, Uruguay. And he has won, here at the conference, he and his company have won an award, a data science award so what I'd like to do is ask Fernando, Fernando Lopez to introduce himself, to give us his job description, to describe the project for which you won the award and take it from there, Fernando. >> Hello and thanks for the chance >> Great to have you. >> I work for Quanam, as you already explained. We are about 400 people in the whole company. And we are spread across Latin America. I come from the kind of headquarters, which is located in Montevideo, Uruguay. And there we have a business analytics business unit. Within that, we are about 70 people and we have a big data and artificial intelligence and cognitive computing group, which I lead. And yes, we also implement Hortonworks. We are actually partnering with Hortonworks. >> When you say you lead the group, are you a data scientist yourself, or do you manage a group of data scientists or a bit of both? >> Well a bit of both. You know, you have to do different stuff in this life. So yes, I lead implementation groups. Sometimes the project is more big data. Sometimes it's more data science, different flavors. But within this group, we try to cover different aspects that are related in some sense with big data. It could be artificial intelligence. It could be cognitive computing, you know. >> Yes, so describe how you're using Hortonworks and describe the project for which you won, I assume it's a one project, for which you won the award, here at this conference. >> All right, yes. We are running several projects, but this one, the one about the prize, is one that I like so much because I'm actually a bioinformatics student so I have a special interest in this one. >> James: Okay. >> It's good to clarify that this was a joint effort between Quanam and GeneLifes. >> James: Genelabs. >> GeneLifes. >> James: GeneLifes. >> Yes, it's genetics and bioinformatics company. >> Right. >> That they specialize-- >> James: Is that a Montevideo based company? >> Yes. In a line, they are a startup that was born from the Institut Pasteur, but in Montevideo and they have a lot of people, who are specialists in bioinformatics, genetics, with a long career in the subject. And we come from the other side, from big data. I was kind of in the middle because of my interest with bioinformatics. So something like one year and a half ago, we met both companies. Actually there is a research, an innovation center, ICT4V. You can visit ICT4V.org, which is a non-profit organization after an agreement between Uruguay and France, >> Oh okay. >> Both governments. >> That makes possible different private or public organizations to collaborate. We have brainstorming sessions and so on. And from one of that brainstorming sessions, this project was born. So, after that we started to discuss ideas of how to bring tools to the medical genetiticists in order to streamline his work, in order to put on the top of his desktop different tools that could make his work easier and more productive. >> Looking for genetic diseases, or what are they looking for in the data specifically? >> Correct, correct. >> I'm not a geneticist but I try to explain myself as good as I can. >> James: Okay, that's good. You have a great job. >> If I am-- >> If I am the doctor, then I will spend a lot of hours researching literature. Bear in mind that we have nearly 300 papers each day, coming up in PubMed, that could be related with genetics. That's a lot. >> These are papers in Spanish that are published in South America? >> No, just talking about, >> Or Portuguese? >> PubMed from the NIH, it's papers published in English. >> Okay. >> PubMed or MEDLINE or-- >> Different languages different countries different sources. >> Yeah but most of it or everything in PubMed is in English. There is another PubMed in Europe and we have SciELO in Latin America also. But just to give you an idea, there's only from that source, 300 papers each day that could be related to genetics. So only speaking about literature, there's a huge amount of information. If I am the doctor, it's difficult to process that. Okay, so that's part of the issue. But on the core of the solution, what we want to give is, starting from the sequence genome of one patient, what can we assert, what can we say about the different variations. It is believed that we have around, each one of us, has about four million mutations. Mutation doesn't mean disease. Mutation actually leads to variation. And variation is not necessarily something negative. We can have different color of the eyes. We can have more or less hair. Or this could represent some disease, something that we need to pay attention as doctors, okay? So this part of the solution tries to implement heuristics on what's coming from the sequencing process. And this heuristics, in short, they tell you, which is the score of each variant, variation, of being more or less pathogenic. So if I am the doctor, part of the work is done there. Then I have to decide, okay, my diagnosis is there is this disease or not. This can be used in two senses. It can be used as prevention, in order to predict, this could happen, you have this genetic risk or this could be used in order to explain some disease and find a treatment. So that's the more bioinformatics part. On the other hand we have the literature. What we do with the literature is, we ingest this 300 daily papers, well abstracts not papers. Actually we have about three million abstracts. >> You ingest text and graphics, all of it? >> No, only the abstract, which is about a few hundred words. >> James: So just text? >> Yes >> Okay. >> But from there we try to identify relevant identities, proteins, diseases, phenotypes, things like that. And then we try to infer valid relationships. This phenotype or this disease can be caused because of this protein or because of the expression of that gene which is another entity. So this builds up kind of ontology, we call it the mini-ontology because it's specific to this domain. So we have kind of mini-semantic network with millions of nodes and edges, which is quite easy to interrogate. But the point is, there you have more than just text. You have something that is already enriched. You have a series of nodes and arrows, and you can query that in terms of reasoning. What leads to what, you know? >> So the analytical tools you're using, they come from, well Hortonworks doesn't make those tools. Are they coming from another partner in South America? Or another partner of Hortonworks' like an IBM or where does that come from? >> That's a nice question. Actually, we have an architecture. The core of the architecture is Hortonworks because we have scalability topics >> James: Yeah, HDP? >> Yes, HDFS, High-von-tessa, Spark. We have a number of items that need to be easily, ultra-escalated because when we talk about genome, it's easy to think about one terrabyte per patient of work. So that's one thing regarding storage and computing. On the other hand, we use a graph database. We use Neo4j for that. >> James: Okay the Neo4j for graph. The Neo4j, you have Hortonworks. >> Yes and we also use, in order to process natural language processing, we use Nine, which is based here in Berlin, actually. So we do part of the machine learning with Nine. Then we have Neo4j for the graph, for building this semantic network. And for the whole processing we have Hortonworks, for running this analysis and heuristics, and scoring the variance. We also use Solr for enterprise search, on top of the documents, or the conclusions of the documents that come from the ontology. >> Wow, that's a very complex and intricate deployment. So, great, in terms of the takeaways from this event, we only just have a little bit more time, what of all the discussions, the breakouts and the keynotes did you find most interesting so far about this show? Data stewardship was a theme of Scott Knowles, with that new solution, you know, in terms of what you're describing as operational application, have you built out something that can be deployed, is being deployed by your customers on an ongoing basis? It wasn't a one-time project, right? This is an ongoing application they can use internally. Is there a need in Uruguay or among your customers to provide privacy protections on this data? >> Sure. >> Will you be using these solutions like the data studio to enable a degree of privacy, protection of data equivalent to what, say, GDPR requires in Europe? Is that something? >> Yes actually we are running other projects in Uruguay. We are helping the, with other companies, we are helping the National Telecommunications Company. So there are security and privacy topics over there. And we are also starting these days a new project, again with ICT4V, another French company. We are in charge of their big data part, for an education program, which is based on the one laptop per child initiative, from the times of Nicholas Negroponte. Well, that initiative has already 10 years >> James: Oh from MIT, yes. >> Yes, from MIT, right. That initiative has already 10 years old in Uruguay, and now it has evolved also to retired people. So it's a kind of going towards the digital society. >> Excellent, I have to wrap it up Fernando, that's great you have a lot of follow on work. This is great, so clearly a lot of very advanced research is being done all over the world. I had the previous guest from South Africa. You from Uruguay so really south of the Equator. There's far more activity in big data than, we, here in the northern hemisphere, Europe and North America realize so I'm very impressed. And I look forward to hearing more from Quanam and through your provider, Hortonworks. Well, thank you very much. >> Thank you and thanks for the chance. >> It was great to have you here on theCUBE. I'm James Kobielus, we're here at DataWorks Summit, in Berlin and we'll be talking to another guest fairly soon. (mood music)

>> Announcer: Live, from Orlando, Florida, it's the Cube covering Grace Hopper's celebration of women in computing brought to you by Silicon Angle Media >> Welcome back to the Cube's coverage of the Grace Hopper conference here in Orlando, Florida I'm your host Rebecca Knight, along with my co host Jeff Frick. We're joined by Megan Smith. We're very excited to have you on the show. >> It's good to be here >> She is the third US CTO and also the CEO of a new company, Shift7.co, so thanks so much for joining us. >> Thanks for having me, it's great to be here. It's so fun to be at Hopper, >> Rebecca: It is, it is! >> It's cool, it's the Grace Hopper celebration, because we're trying to celebrate women in computing, and we're what, at 18 thousand people now, >> The biggest ever, >> Plus I think, 6 thousand people joining on the livestream, which is great. >> Before the cameras were rolling, we were talking about your role as the 3rd US CTO, and just talking about getting more technology into government to help leaders work together, and move faster. Tell us a little about this initiative. >> What's so great, is it's not partisan, fixing the government and making it work better, so all the work that we were doing continues. What we were able to put in place, during the Obama administration, and continues to Trump, were things like, the CT office. Having technical people, so I worked at Google, people work at Amazon, Facebook, Twitter, these companies who have that background, to join in on policy conversations, one, to join in on capacity building the government, so data sciences and tech and, let's have our services be as great as Amazon, or as Twitter, or Oracle, and not be sort of retro, really serve the American people. And then also, helping the American people in general, with capacity building, things like computer science for all. So that was an initiative that continues to get all of our children to have coding at school. That all children, you couldn't graduate from high school without having had some experience on learning of coding Coding is a 21st century fluency, it's a skill we all need, Like freshman biology. You want to know some biology, you want to know some coding, you want to know how to write, so making sure they have is tech-up, which was a program we started to help train Americans, there's six hundred thousand jobs open, in the United States, and they pay 50% more than the average American salary. The companies are starving. How do we rapidly get more Americans into these jobs? It turns out that people have, of course, created these fabulous code boot camps, you can train in three months for these jobs, some of them are paid, some times they pay you, all different kinds, some are online, some are offline, they're all over the country. So we're able to get more people to consider, a job like that, culturally they think, Well I don't, why would I, I don't know how to do that. Well you can, this is a fun and interesting and exciting career, you can do digital marketing, you can do user interface design. You can get involved in front end or back end coding, product management, all those things, sales. And so, how do you pull lots more Americans in, get our companies fueled so we have really the economic opportunity, and they're all over the country. Location wise, and topic wise. So we did tech hour now, and a tech jobs tour, which is not what we did in government, but we continue some of that work. >> This weird dichotomy, because on one end, people are worried about tech taking jobs, on the other hand, there's a ton of open tech jobs. And there's this transition period, that's difficult, obviously for people that didn't grow up, but one of the keynote speakers today, told a really heartening story, that she didn't get into it until the day she had to leave her abusive husband, and now she is a coder >> That's Doctor Sue Black, who was just given the Order of the British Empire, I mean, she is an incredible computer scientist. Yes, she escaped an abusive marriage with three small children, in her early 20s, I think. Ended up moving into public housing, and dealing with three children only being the school from 9 until 3, and eventually getting her PhD in computer science, and really, she started Techmoms now, she continues to do research in other things, but she's really trying to use her story, and her organizing capacity, to have more people realize this isn't hard like figuring out gravity waves that won the Nobel prize. This is hard like writing a hard essay, so we all can learn to write an essay. It takes some mastery work, you don't learn it in kindergarten but by the time you're in 7th, 8th, 9th, 10th, 12th grade, you can do it. >> It's not rocket science. >> Right, so coding is like that. >> The other piece you said that's very interesting, is the consumerization of IT. We've seen it at enterprise, a huge trend. But, now I expect everything that's on my phone, when I interact with Facebook or Amazon, or whatever, to be in all the applications, so, as you said, that's influencing government, and the way they have to deliver services, and I would imagine, too, with kind of the next wave of kids coming in, graduating, going into public service, they certainly have that expectation, right? They've been working on their phone forever of course it should be on the phone. >> And so we want everybody in our country fluent in computer science and coding at a basic level, like again, like freshman biology or takin' chemistry in high school, or taking writing. So that everyone could realize this is not rocket science we could have these kinds of capabilities as part of our services, from Housing and Urban Development, from the Department of Education. You know, a lot of us use our phones to get places, you know, on our maps, and so that's actually data coming from the US Geological survey, if you're looking at the weather, you're looking at NOAA's satellites, this is open government data. We were able to open over two hundred thousand data sets, from all over government, not private data, but public data, that you could make an entire app store, or Google play set of products on top of that. Government wouldn't have to pay for that, it just packages up the API as well. A really good example of that, is the US census team. There's nothing more big data than census, they have all of our information from a data perspective, and so they did opportunity.census.gov, and they said to various agencies, let us help you bridge these data sets into something that someone could build on top of, like we're seeing from the courses sector, we saw wonderful things like, Housing and Urban Development said, okay, our challenges are housing affordability, mobility, these are the challenges instead of having HUD make an app for Americans to come to, they just can explain what their problem is, what data sets, and then engage extraordinary companies, like airbnb, Redfins, Zillow, these fabulous tech companies, who can make instead a product for 100% of the Americans, rather than only wealthy or middle class Americans, and so they did things like, opportunity score, and airbnb helping you figuring out, if I rent a room in my house I can make my rent more affordable, very creative apps, that we can see, same thing for the Department of Ed or Department of Labor, and as the data gets out there, and as apps come, also the opportunity for data science and machine learning. What if, as much as we serve ads to ourselves, in these algorithms, what if we use the algorithms to help Americans find a job that they would love? You know, job matching, and these kinds of opportunities. of the problems in the world, and helping government get more fluent at that. And the way to do that is not so much, jam the government You have to do this, but find terrific talent like we see at Hopper, and have them cycle into the government, to be co-leaders just like a surgeon general would come. >> Are you facing recruitment challenges in that same way though? In the sense that technology is having a hard enough time recruiting and retaining women, but the government, too, is that seen as enough of an employer of choice for young talented, bright ambitious, young women? >> I'm not in government now, but when we were in there, we found a very interesting thing. Alex Mcgovern, who had been the general counsel of Twitter who was Stephanie's CTO with me and led a lot of our tech quals we called TQ like tech IQ in policy, together with economists and lawyers and others have if we're going to decide net neutrality, let's include everyone, including computer scientists, and we're going to sue bridge and open source, So we talked about that, and on the way going in Mcgovern, he said, wouldn't it be cool if, just like when you look at a lawyer's resume, you might see that they clerk and they served their county through clerking and through the judicial system, as well as being a private lawyer, they were a public defender, that's a pretty normal thing to see on a legal resume. If you looked at medical, you might see them going into NIH or doing some research, if you looked at a scientist, they might have gone to, done some NSF work or others. But for the tech crew, there is of course amazing technical people in NASA, NAH and the Department of Energy, and there's great IT teams, but there's not this thing that the Silicon Valley crew resume would say, oh, yeah, I served my country. So that's why, under President Obama, we were able to create these incredible programs. The Presidential Innovation Fellows, which was a one year term of service, The United States Digital Service, which is a three months to a two year term of service in the VA. What's more amazing if you build Amazon, than to go as a second act and help our veterans? It's an incredible honor, to the point of, will they come? Yes, that's what we were hoping, could we have that be a normal thing, and yes it's become a normal thing. And the Trump administration continues it. The 18F team is in the general services administration, they're on 18th and F so they have a code name. But that particular team is located around the country, not only in DC but in San Francisco, in Chicago, and others. So you see this tech sector flowing now into the government on a regular basis, and we welcome more peoples. The government is who shows up to help, so we need the tech sector to show up cause we've got a lot of money as a country, but if we're not effectively using it we're not serving the American people and foster children, veterans, elders, others need the services that they deserve and we have the money, so let's make it happen the way the tech sector is delivering Amazon packages or searches. >> What is your feeling, this is not your first Grace Hopper obviously, but what is your feeling about this conference, and advice that you would give to young women who are here, maybe for their first or second time, in terms of getting the most their time here? >> You know, I think the main thing is, it's a celebration, that's fun and you can walk up to anyone, so just talk to everyone. I've been talking to a million people on the floor, fabulous. Students are here, more senior technical leaders are here. We've been running speed mentoring, we're running a program called the Tech Jobs Tour, it's at Techjobstour.com, it's a #Americanshiring, and we've been going to 50 different cities and so we're running a version of that, and we do speed mentoring, so come to the speed mentoring sessions, it's a five minute pop, talk to someone about what you're tryin' to do. Lot's of programs like that, get into the sessions, come to the keynotes which are so inspiring, and Melinda Gates was amazing today, Dr. Fefe Lee was incredible, just across aboard, Dr Sue Black was here, I thought it was great today, actually, just to reflect on Melinda's keynote, I think this might have been the first time, I was talking to her, that she's really talked about her own technical experience >> That struck me, too! As a coder, starting in computer science. I didn't really understand that she had really started very early, with Apple 3 and the story of her dad >> And her love of her Apple 3, right! and really high school coding, which is so important for young people in high school and middle school, even younger. The Muscogee Creek Tribe, in Oklahoma, is teaching robotics in head start, so we can start in preschool. Just make it fun, and interesting. They're funny, they don't do battle bots, because you don't really want to teach 3 and 4 year olds to fight, so instead they have collaborative robots. >> Robots who work together Age appropriate. >> Well Megan Smith, this has been so fun talking to you, thanks so much for coming on our show. >> Thanks for having me. >> We will have more from the Grace Hopper Conference just after this, I'm Rebecca Knight for Jeff Frick (music)

>> Announcer: Live from Orlando, Florida. It's theCUBE, covering Grace Hopper's Celebration of Women in Computing, brought to you by Silicon Angle Media. (bright music) >> Welcome back to the Cube's coverage of the Grace Hopper Conference here in Orlando, Florida. I'm your host Rebecca Knight. I'm joined by Ayanna Howard. She is a professor at the Georgia Institute of Technology and also Chief Technology Officer at Zyrobotics. >> Thank you. >> Thanks so much for joining us. >> Thank you very much for having me. >> So start to tell our viewers a little bit about Zyrobotics. I know it was a spin-off of your research that you were doing at Georgia Tech. >> Yeah, so interesting enough Zyrobotics, so at Georgia Tech I focus on working in technologies, robotics for children with special needs. Primarily children with motor disabilities, cerebral palsy for example, children with autism. And so one of the things as we had developed was the ability to access computing technology because I was running robot programming camp. So I was running camps for all children, so an inclusive camp and I had typical children and children with special needs, and what happened was people kept asking me, "Oh, can we take this home?" It was like, "Yeah, no, (laughing) "that's got to stay in the lab, sorry. "But you can bring your kid back." And so the company really came out of trying to commercialize that special technology that allows inclusiveness for kids in this kind of STEM education. So that's how Zyrobotics came about. >> So talk a little bit about the technology. What does it do? How does it help kids with these different learning needs? >> So imagine you have a child who has motor limitation, and if you look now, so much is on tablets. Tablets, smartphones, even education. And if I have a motor disability, have you ever tried swiping with your fist? Right, or even if you're an older adult, and taking your finger, and if you have a tremor, like moving things around, so this is very difficult. And yet that is the way the technology is made, which isn't a service. It's just not made for everyone. And so what we've done is we've created these devices, very fun, think of it as a stuffed animal, that allows you to, if you want to stomp, if you want to do your finger, if your access point is in your foot, and you just tap your foot, it allows you to interact with the different educational apps. But what we found is that typical kids also like (laughing) playing with the toys. >> Rebecca: Right, right, right. >> So it's like, oh what is this? This is interesting. And so that's why it provided this nice blend of kids of any ability the ability to access these educational apps. So but you also are a full-time professor at Georgia Tech, and you run a traineeship in healthcare robotics. Tell our viewers a little bit more about that. >> Yeah, so I run a program called ARMS, so it's funded by the National Science Foundation. And what I've found is, a long time ago, the way that we were training our computer science students, our engineering students in robotics was typically I would say ad hoc. So I'd have a student, and they were like, "I'm interested in healthcare robotics." And I would call up my clinician friend and say, "hey, can we do an observation?" And my student would go there and basically shadow a therapist or a doctor for the day. And then they go back. And so this is what I was doing. And I found out that most professors who had students in healthcare-related activities were doing the same thing. And I was like, wait, hold it. This sounds like it's more than just me. Maybe we can formalize this a little bit more. And so the trainee-ship program actually takes roboticist students and immerses them in the medical side. And so for example this past summer, they spent the entire summer over in the clinic and the hospital watching surgeries, I mean actually scrubbing up, following patients, understanding what is Parkinson's and how do you do assessments. And so they were fully immersed as if they were medical resident students, or resident person in the clinic. And what happens is, then, and this is all in their first year, they come back into their studies, and now they understand, "okay, if I'm designing "this technology, what does it mean "if I'm designing for someone who's recovering from stroke? "What does that really mean?" And they have a vision of the patients, not just their own, I mean, they have a real vision of Mister Joe, that they've worked with and how he might have struggled with some concept and what they're doing can actually enable. And so it gives engineers, scientists, roboticists that power. >> And the empathy to really understand how it will be used. >> Yes, and understand that and not build or design in a box, which is really unfortunate that sometimes we do that. We design based on our own beliefs, not taking into account that there are other users and you are not the user, necessarily, of your own technology. >> So I want talk a little bit about this conference. This is your third Grace Hopper Conference. What does it mean to you to be here, and what do you get out of it? Are you here for Zyrobotics? Are you here for Georgia Tech? >> I am here for women in computing. And so it's actually not linked to a specific company or an organization. It's the fact that I feel a responsibility, they call me a role model, but- >> Rebecca: We're going to go with it, we're going to go with it. >> We're going to go with it. (laughing) I mean, I had a lot of mentors growing up. Not many were women. It's only at my later age that I've actually met some great, great women mentors. And so I feel a responsibility to come to Grace Hopper and just talk, share my experiences, sometimes be vulnerable and open to the trials and tribulations, but then the pure joy you get from staying in the field and the pure joy you get from actually impacting the world with your mind, with your technology, with your stuff. And I think it's amazing how, to be here and see all these young ladies, both students and older, well-established women leaders, and say, "yeah, we got this. "We can change the world with our power." >> So we're really at this inflection point in technology where problems, the biases, the barriers that have kept women from progressing, from first of all getting into the field and also progressing, are really front-page news. And sort of the problems that women have faced in the industry, the sexism, is really being talked about. But is that a good thing in the sense, I mean, yes, it's one thing to get these problems out there, but are we also discouraging women because it's showing women how tough it is to be in this industry and this bro-grammer culture? >> I think it's a two-edged sword. So in one instance, these things were happening anyway. And if you actually look at retention, which is surprising, retention of women who've been in the computing field for a longer period of time, a lot of them were dropping out. It's like, wait, hold it. You got through the pipeline, what happened? And so we all knew a lot of this stuff was going on. We have first-hand experience with it. And so the conversation now is letting everyone know about it. And I think that's how anything happens. It's that others are like, "I didn't realize." others start empathizing. "I didn't realize that this is what you were "going through. "What can I do to help?" Even if they are not necessarily a woman or a minority. And so I think what happens is by having that conversation, it makes everyone aware of it so that things can start changing. It's a negative, the fact that maybe young women are like, "oh, I don't want to go through that." I think by having role models that are like, "hey, yeah, that's what it's like, "but guess what, I'm running the company. "I'm the CEO, and so imagine what it'd be like "if you come in now that the conversation is open "versus what I was going through "when nobody was talking about it." We didn't have anyone to say, "hey, can you help me? "I just need some assistance, just to talk about something." Now you can, you can be open about it. >> So what is your advice? I mean, we know that the numbers are bleak. Tech is comprised of 25% women, 15% in leadership positions. For black and Latina, it's abysmal. What do you tell your students about this industry? >> So I tell my students, one is, if you want to change the world, and usually students that take my course and work with me are ones that want to have an impact with their minds and their technology, and so my thing is if you want to change the world, computer science, engineering is the only way that you can because the world is based on you and your technology. And in fact, if you don't, I put in the guilt, if you don't get involved in this, then the world is not going to change. And your kids' kids will have to live in this world that you have. So it's really your responsibility (laughing) to get into this space. >> The guilt is good, that's good, yeah. >> It is, for women, guilt is really good. >> I know, it's powerful, so powerful. >> Yeah, yeah. >> I want to talk a little bit about funding because I know that your trainee program, it's partly funded by the National Science Foundation. So funding is such a hot topic here, and whether you're a female entrepreneur who's trying to get money for your idea or you're a scientist trying to fund your research, tell us a little bit about the landscape, what you're seeing, what you're feeling. >> I would say that government funding, so the National Science Foundation, I would say NIH, there is more equality in the representation. >> Rebecca: There is more equality. >> It's not 50-50. But you have a fighting chance, right? I would argue, though, that in the startup world, you need to go for government funding and non-profits that may be angels because honey, VCs are not going to look at you. I truly believe that, and being a startup company, I talked to a lot of women entrepreneurs who have broke in the VC field, and they tell me basically how many frogs they had to kiss, you know? And so I think that landscape has not changed as much. But I think funding as a scientist for government grants, I think it's more, it's not fair, but it's more equal because in government, it's okay for you to say, as a program manager, "hey, something's wrong here." Because the government represents the population. So it's okay as a program manager to say that. I don't know that it's as safe to say that as a VC, like, "hey, our company portfolio doesn't look "like the rest of America." >> Right, right. So your advice there for female entrepreneurs or female researchers trying to get money is to go first to either angels or the government. >> I say that will help you keep your company alive. But you still have to kiss a lot of frogs. You still do. And eventually you will find a frog that turns into a princess and will fund you. But if you think about, how do you survive through this company and how do you keep it to the next levels, you go through any type of funding resource that you can. And so if the angel funding world in terms of government, it's not a guarantee, but it's easier, grab that, non-diluted, by the way, typically, until you go the VC direction. >> Now, in terms of the funding environment, though, NIH and NSF, do you feel they're giving as much money right now? We have an administration that is... >> Yeah, no, so overall the budgets themselves are, so NSF and NIH, this last cycle they kind of weathered a cut. But if you look overall over the last umpteen years, you see that the rate of acceptance has dropped because there's a lot more researchers going for funding, the budget doesn't keep up, necessarily, with the cost of living expenses kind of thing, cost for tuition, cost for grad students. And so overall the funding has declined. But that is not a gender issue. That is a issue just about the value of basic research in general. And the US, a lot of us understand but a lot of us do not. And so we feel that in terms of the funding process. >> So as a professor but then also as someone who's working in industry, how do you make sure that women can see themselves and see potentially rich and rewarding careers? >> So I do a couple of activities. For example, I'm going to talk about one, which CRWA grad cohort. And so what that focuses on is graduate students, women, either PhD, Master's wanting to be a PhD, and what we do is we provide those mechanisms for them to interact with community members. So we bring in these- >> Rebecca: So this is not just at Georgia Tech. This is nationwide. >> This is nationwide. Young women, they come in, like, "oh, what is this?" First off, they get to see other of their peers at other schools. Second is we bring in senior women that are doing exceptionally well, and they do things like one on one mentorship. They share. So we select these women who are open to sharing their experiences, both the good and the bad, and so it provides that network of, "okay, look, it might be hard in grad school, "but we have a peer network, take advantage. "And there are senior women you can take advantage, "to talk to and kind of ping them on different issues "that you have." So I think programs like that, and we're not the only one, but programs like CRWA grad cohort, CRAW URM, undergraduate cohort, are ways to ensure that you don't get discouraged at a younger age. >> So Zyrobotics, it's founded in 2013. What is the future of it? I mean, it's such an exciting technology and one that I think really has a lot of uses because as you said, it's not only for children but it could be for stroke victims, for aging people who are sort of losing some of their mobility. >> So my goal, I always say five years, right? So when I started it was like, five year goal cause that's like the holy grail, you make it for five years. So we're at year four, we just crossed. So we're in that five years. But what I see more as the vision, what I would say the secret magic of Zyrobotics is to make sure that accessibility is an integral part of the conversation. It's not an afterthought, it's not a someone designed technology, oh, let's think about accessibility and inclusiveness after the fact. And so I'm hoping that one, the product of course takes off, but also that it starts changing the conversation a little bit. So for example, I go out, I talk about how do you design technology that is really, really cool, is cutting edge, that's accessible at its core. It's accessible to the different learning ways, different access ways that people have of interacting with technology. How do you get that message across that, "hey, you can so this and you can still make money." So it's not like oh, accessibility, we can't make any money. Like, no, you can actually still make money even if it's a core value. So that's my vision is to have basically, have Zyrobotics lead that but then have other companies adopt it as, "oh, yeah, why haven't we done this? "Yeah, this makes total, total sense." >> Great, Ayanna Howard, thank you so much for joining us. It's been a pleasure having you on theCUBE. >> Thank you, this was fun. Thank you for the invite. >> I'm Rebecca Knight, here in Orlando, Florida at Grace Hopper. We will have more just after this. (bright music)

>> Announcer: Live from Washington, D.C., it's theCUBE covering AWS Public Sector Summit 2017. Brought to you by Amazon Web Services and it's partner ecosystem. >> Welcome back, live here on theCUBE along with John Furrier, I'm John Walls. Welcome to AWS Public Sector Summit 2017. Again, live from Washington, D.C., your nation's capital, our nation's capital. With us now is our host for the week, puts on one heck of a show, I'm want to tell you, 10,000 strong here, jammed into the Washington Convention Center, Theresa Carlson from World Wide Public Sector. Nice to have you here, Theresa. >> Hi, good afternoon. >> Thanks for joining us. >> Love theCUBE and thank you for being here with us today. >> Absolutely. >> All week in fact. >> It's been great, it really has. Let's just talk about the show first off. Way back, six years ago, we could probably get everybody there jammed into our little area here, just about I think. >> Pretty much. >> Hard to do today. >> That's right. >> How do you feel about when you've seen this kind of growth not only of the show, but in your sector in general? >> I think at AWS we're humbled and excited and, on a personal level because I was sort of given the charge of go create this Public Sector business world-wide, I'm blown away, I pinch myself every time because you did hear my story. The first event, we had about 50 people in the basement of some hotel. And then, we're like, okay. And today, 10,000 people. Last year we had it at the Marriott Wardman Park and we shut down Connecticut Avenue so we knew we needed to make a change. (laughing) But it's great, this is really about our customers and partners. This is really for them. It's for them to make connections, share, and the whole theme of this is superheroes and they are our superheroes. >> One of the heroes you had on the stage today, John Edwards from the CIA, one of your poster-children if you will for great success and that kind of collaboration, said something to the effect of quote, "The best decision we ever made at the CIA "was engaging with AWS in that partnership." When you hear something like that from such a treasured partner, you got to feel pretty good. >> You just have to drop the microphone, boom, and you're sort of done. They are doing amazing work and their innovation levels are really leading, I would say, in the US Public Sector for sure and also, not just in US Public Sector but around the world. Their efforts of what they're doing and the scale and reach at which they're doing it so that's pretty cool. >> John, you've talked about the CIA moment, I'd like to hear the story, share with Theresa. >> Oh, you're going to steal my thunder here? >> No, I'm setting you up. That's what a good partner does. It's all yours. >> Well, John, we've talked multiple times already so I'll say it for the third time. The shot heard around the cloud was my definition of seminal moment, in big mega-trends there's always a moment. It was when Obama tweeted, Twitter grew, plane landing on the Hudson, there's always a seminal moment in major trends that make or break companies. For you guys, it was the CIA. Since then, it's just been a massive growth for you guys. That deal was interesting because it validated Shadow IT, validated the cloud, and it also unseated IBM, the behemoth sales organization that owned the account. In a way, a lot of things lined up. Take us through what's happened then, and since then to now. >> Well, you saw between yesterday at Werner Vogels' keynote and my keynote this morning, just the breadth and depth of the type of customers we have. Everything from the UK government, GCHQ, the Department of Justice with the IT in the UK, to the centers for Medicare for HHS, to amazing educational companies, Cal. Polytech., Australian Tax Office. That's just the breadth and depth of the type of customers we have and all of their stories were impactful, every story is impactful in their own way and across whatever sector they have. That really just tells you that the type of workloads that people are running has evolved because I remember in the early days, when you and I first talked, we talked about what are the kind of workloads and we were talking a little bit about website hosting. That's, of course, really evolved into things like machine learning, artificial intelligence, a massive scale of applications. >> Five or six years ago when we first chatted at re:Invent, it's interesting 'cause now this is the size of re:Invent what it was then so you're on a same trajectory from a show size. Again, validation to the growth in Public Sector. But I was complimenting you on our opening today, saying that you're tenacious because we've talked early days, it was a slog in the early days to get going in the cloud, you were knocking on a lot of doors, convincing people, hey, the future's going to look his way and I don't want to say they slammed the proverbial door in your face but it was more of, woah, they don't believe the cloud is ever going to happen for the government. Share some of those stories because now, looking back, obviously the world has changed. >> It has and, in fact, it's changed in many aspects of it, from policy makers, which I think would be great for you all to have on here sometime to get their perspective on cloud, but policy makers who are now thinking about, we just had a new modernization of IT mandate come out in the US Federal Government where they're going to give millions and millions of dollars toward the modernization of IT for US Government agencies which is going to be huge. That's the first time that's ever happened. To an executive order around cyber-security which is pretty much mandated to look at cloud and how you use it. You're seeing thing like that to even how grants are given where it used to be an old-school model of hardware only to now use cloud. Those ideas and aspects of how individuals are using IT but also just the procurements that are coming out. The buying vehicles that you're seeing come out of government, almost all of them have cloud now. >> John and I were talking about D.C. and the political climate. Obviously, we always talk about it on my show, comment on that. But, interesting, theCUBE, we could do damage here in D.C.. So much target-rich environment for content but more than ever, to me, is the tech scene here is really intrinsically different. For example, this is not a shiny new toy kind of trend, it is a fundamental transformation of the business model. What's interesting to me is, again, since the CIA shot heard around the cloud moment, you've seen a real shift in operating model. So the question I have for you, Theresa, if you can comment on this is: how has that changed? How has the procuring of technology changed? How has he human side of it changed? Because people want to do a good job, they're just on minicomputers and mainframes from the old days with small incremental improvement over the years in IT but now to a fundamental, agile, there's going to be more apps, more action. >> You said something really important just a moment ago, this is a different kind of group than you'll get in Silicon Valley and it is but it's very enterprise. Everybody you see here, every project they work on, we're talking DoD, the enterprise of enterprises. They have really challenging and tough problems to solve every day. How that's changed, in the old days here in government, they know how to write acquisitions for a missile or a tank or something really big in IT. What's changing is their ability to write acquisitions for agile IT, things like cloud utility based models, moving fast, flywheel approach to IT acquisitions. That's what's changing, that kind of acquisition model. Also, you're seeing the system integrator community here change. Where they were, what I call, body shops to do a lot of these projects, they're having to evolve their IT skills, they're getting much more certified in areas of AWS, at the system admin to certified solution architects at the highest level, to really roll these projects out. So training, education, the type of acquisition, and how they're doing it. >> What happened in terms of paradigm shift, mindset? Something had to happen 'cause you brought a vision to the table but somebody had to buy it. Usually, when we talk about legacy systems, it was a legacy mindset too, resistant, reluctant, cautious, all those things. >> Theresa: Well, everything gets thrown out. >> What happened? Where did it tip the other way? Where did it go? >> I think, over time, it's different parts of the government but culture is the hardest thing to, always, change. Other elements of any changes, you get there, but culture is fundamentally the hardest thing. You're seeing that. You've always heard us say, you can't fight gravity, and cloud is the new normal. That's for the whole culture. People are like, I cannot do my project anymore without the use of cloud computing. >> We also have a saying, you can't fight fashion either, and sometimes being in fashion is what the trends are going on. So I got to ask you, what is the fashion statement in cloud these days with your customers? Is it, you mentioned there, moving much down in the workload, is it multi-cloud? Is it analytics? Where's the fashionable, cool action right now? >> I think, here, right now, the cool thing that people really are talking about are artificial intelligence and machine learning, how they take advantage of that. You heard a lot about recognition yesterday, Poly and Lex, these new tools how they are so differentiating anything that they can possibly develop quickly. It's those kind of tools that really we're hearing and of course, IOT for state and local is a big deal. >> I got to ask you the hard question, I always ask Andy a hard question too, if he's watching, you're going to get this one probably at re:Invent. Amazon is a devops culture, you ship code fast and you make all these updates and it's moving very, very fast. One of the things that you guys have done well, but I still think you need some work to do in terms of critical analysis, is getting the releases out that are on public cloud into the GovCloud. You guys have shortened that down to less than a year on most things. You got the east region now rolled out so full disaster recovery but government has always been lagging behind most commercial. How are you guys shrinking that window? When do you see the day when push button commercial, GovCloud are all lockstep and pushing code to both clouds? >> We could do that today but there's a couple of big differentiators that are important for the GovCloud. That is it requires US citizenship, which as you know, we've talked about the challenges of technology and skills. That's just out there, right? At Amazon Web Services, we're a very diverse company, a group of individuals that do our coding and development, and not all of them are US citizens. So for these two clouds, you have to be a US citizen so that is an inhibitor. >> In terms of developers? In terms of building the product? >> Not building but the management aspect. Because of their design, we have multiple individuals managing multiple clouds, right? Now, with us, it's about getting that scale going, that flywheel for us. >> So now it's going to be managed in the USA versus made in the USA with everything as a service. >> Yeah, it is. For us, it's about making sure, number one, we can roll them out, but secondly, we do not want to roll services into those clouds unless they are critical. We are moving a lot faster, we rolled in a lot more services, and the other cool thing is we're starting to do some unique things for our GovCloud regions which, maybe the next time, we can talk a little bit more about those things. >> Final question for me, and let John jump in, the CIA has got this devops factory thing, I want you to talk about it because I think it points to the trend that's encouraging to me at least 'cause I'm skeptical on government, as you know. But this is a full transformation shift on how they do development. Talk about these 4000 developers that got rid of their development workstations, are now doing cloud, and the question is, who else is doing it? Is this a trend that you see happening across other agencies? >> The reason that's really important, I know you know, in the old-school model, you waited forever to provision anything, even just to do development, and you heard John talk about that. That's what he meant on this sort of workstation, this long period of time it took for them to do any kind of development. Now, what they do is they just use any move they have and they go and they provision the cloud like that. Then, they can also not just do that, they can create armies of cores or Amazon machine images so they have super-repeatable tools. Think about that. When you have these super-repeatable tools sitting in the cloud, that you can just pull down these machine images and begin to create both code and development and build off those building blocks, you move so much faster than you did in the past. So that's sort of a big trend, I would say they're definitely leading it. But other key groups are NASA, HHS, Department of Justice. Those are some of the key, big groups that we're seeing really do a lot changes in their dev. >> I got to ask you about the-- >> Oh, I have to say DHS, also DHS on customs and border patrols, they're doing the same, really innovators. >> One of the things that's happening which I'm intrigued by is the whole digital transformation in our culture, right, society. Certainly, the Federal Government wants to take care of the civil liberties of the citizens. So it's not a privacy question, it's more about where smart cities is going. We're starting to see, I call, the digital parks, if you will, where you're starting to see a digital park go into Yosemite and camping out and using pristine resources and enjoying them. There's a demand for citizens to democratize resources available to them, supercomputing or datasets, what's your philosophy on that? What is Amazon doing to facilitate and accelerate the citizen's value of technology so it can be in the hands of anyone? >> I love that question because I'll tell you, at the heart of our business is what we call citizen service, paving the way for disruptive innovation, making the world a better place. That's through citizen's services and they're access. For us, we have multiple things. Everything from our dataset program, where we fund multiple datasets that we put up on the cloud and let everybody take advantage of them, from the individual student to the researcher, for no fee. >> John F.: You pick up the cost on that? >> We do, we fund, we put those datasets in completely, we allow them to go and explore and use. The only time they would ever pay is if they go off and start creating their own systems. The most highly curated datasets up there right now are pretty much on AWS. You heard me talk about the earth, through AWS Earth that we have that shows the earth. We have weather datasets, cancer datasets, we're working with so many groups, genomic, phenotypes, genomes of rice, the rice genome that we've done. >> So this is something that you see that you're behind, >> Oh, completely. >> you're passionate about and will continue to do? >> Because you never know when that individual student or small community school is out there and they can access tools that they never could've accessed before. The training and education, that creativity of the mind, we need to open that up to everybody and we fundamentally believe that cloud is a huge opportunity for that. You heard me tell the 1000 genomes story in the past of where took that cancer dataset or that genome dataset from NIH, put it into AWS for the first time, the first week we put it up we had 3200 new researchers crowdsource on that dataset. That was the first time, that I know of, that anyone had put up a major dataset for researchers. >> And the scale, certainly, is a great resource. And smart cities is an interesting area. I want to get your thoughts on your relationship with Intel. They have 5G coming out, they have a full network transformation, you're going to have autonomous vehicles out there, you're going to have all kinds of digital. How are you guys planning on powering the cloud and what's the role that Intel will play with you guys in the relationship? >> Of course, serverless computing comes into play significantly in areas like that because you want to create efficiencies, even in the cloud, we're all about that. People have always said, oh, AWS won't do that 'cause that's disrupting themselves. We're okay with disrupting ourselves if it's the right thing. We also don't want to hog resourcing of these tools that aren't necessary. So when it comes to devices like that and IOT, you need very efficient computing and you need tools that allow that efficient computing to both scale but not over-resource things. You'll see us continue to have models like that around IOT, or lambda, or serverless computing and how we access and make sure that those resources are used appropriately. >> We're almost out of time so I'd like to shift over if we can. Really impressed with the NGO work, the non-profit work as well and your work in the education space. Just talk about the nuance, differences between working with those particular constituents in the customer base, what you've learned and the kind of work you're providing in those silos right now. >> They are amazing, they are so frugal with their resources and it makes you hungry to really want to go out and help their mission because what you will find when you go meet with a lot of these not-for-profits, they are doing some of the most amazing work that even many people have really not heard of and they're being so frugal with how they resource and drive IT. There's a program called Feed the World and I met the developer of this and it's like two people. They've fed millions of people around the world with like three developers and creating an app and doing great work. To everything from like the American Heart Association that has a mission, literally, of stopping heart disease which is our number one killer around the world. When you meet them and you see the things they're doing and how they are using cloud computing to change and forward their mission. You heard us talk about human trafficking, it's a horrible, misunderstood environment out there that more of us need to be informed on and help with but computing can be a complete differentiator for them, cloud computing. We give millions of dollars of grants away, not just give away, we help them. We help them with the technical resourcing, how they're efficient, and we work really hard to try to help forward their mission and get the word out. It's humbling and it's really nice to feel that you're not only doing things for big governments but you also can help that individual not-for-profit that has a mission that's really important to not only them but groups in the world. >> It's a different level of citizen service, right? I mean, ocean conservancy this morning, talking about that and tidal change. >> What's the biggest thing that, in your mind, personal question, obviously you've been through from the beginning to now, a lot more growth ahead of you. I'm speculating that AWS Public Sector, although you won't disclose the numbers, I'll find a number out there. It's big, you guys could run the table and take a big share, similar to what you've done with startup and now enterprise market. Do you have a pinch-me moment where you go, where are we? Where are you on that spectrum of self-awareness of what's actually happening to you and this world and your team? In Public Sector, we operate just like all of AWS and all of Amazon. We really have treated this business like a startup and I create new teams just like everybody else does. I make them frugal and small and I say go do this. I will tell you, I don't even think about it because we are just scratching the surface, we are just getting going, and today we have customers in 155 countries and I have employees in about 25 countries now. Seven years ago, that was not the case. When you're moving that fast, you know that you're just getting going and that you have so much more that you can do to help your customers and create a partner ecosystem. It's a mission for us, it really is a mission and my team and myself are really excited, out there every day working to support our customers, to really grow and get them moving faster. We sort of keep pushing them to go faster. We have a long way to go and maybe ask me five years from now, we'll see. >> How about next year? We'll come back, we'll ask you again next year. >> Yeah, maybe I'll know more next year. >> John W.: Theresa, thank you for the time, very generous with your time. I know you have a big schedule over the course of this week so thank you for being here with us once again on theCUBE. >> Thank you. >> Many time CUBE alum, Theresa Carlson from AWS. Back with more here from the AWS Public Sector Summit 2017, Washington, D.C. right after this. (electronic music)

>> Voiceover: Live from Boston, Massachusetts, it's the Cube, covering OpenStack Summit 2017. Brought to you by the OpenStack Foundation, Red Hat, and additional Ecosystem as support. >> Welcome back, I'm Stu Miniman joined by John Troyer. This is Silken Angle Media's production of the Cube at OpenStack Summit. We're the world wide leader in tech coverage, live tech coverage. Happy to welcome back to the program someone we've had on so many times we can't keep track. He is the creator of the term Pets versus Cattle, he is one of the OG of The Cloud Group, Randy, you know, wrote about everything before most of it was done. So good to see you, thank you for joining us. >> Thanks for having me. >> Alright, so Randy, coming into this show we felt that it was a bit of resetting expectations, people not understanding, you know, where infrastructure's going, a whole hybrid multi-cloud world, so, I mean you've told us all how it's going to go, so where are we today, what have people been getting wrong, what's your take coming into this week and what you've seen? >> Well, I've said it before, which is that the public clouds have done more than just deliver compute storage and networking on demand. What they've really done is they've built these massive development organizations. They're very sophisticated, that are, you know, that really come from that Webscale background and move at a velocity that's really different than anything we've seen before, and I think the hope in the early days of OpenStack was that we would achieve a similar kind of velocity and momentum, but I think the reality is is that it just hasn't really materialized; that while there are a lot of projects and there are a lot of contributors the coordination between them is very poor, and you know it's just not the, like architectural oversight that we really needed isn't there. I, a couple years ago at the Openstack Silicon Valley gave a presentation called The Lie of the Benevolent Dictator, and I chartered a course for how we could actually have more of a technical architecture oversight, and just that really fell on deaf ears. And so we continue to do the same thing and expect different results and I just, that's a little disappointing for me. >> Yeah. So what is your view of hybrid cloud? You know, no disagreement, you look at what the public cloud companies, especially the big three, the development that they can do, Amazon, a thousand new features a year, Google, what they can do with data, Microsoft has a whole lot of applications and communities around them. We're mostly talking about private cloud here, it was a term that you fought against for many years, we've had great debates on it, so how does that hybrid play out? Cause customers, they're keeping on premises. Edge fits into a lot of this too, so it's, there's not one winner, it's not a zero sum game, but how does that hybrid cloud work? >> Yeah so, I didn't fight against private cloud, I qualified it. I said if it's going to be a private cloud it's got to be built and look and smell the way that the public cloud was. Alright? If it's just VM ware with VM's on demand, that's not a private cloud. That was my position. And then in terms of hybrid cloud, you know, I don't think we're there yet. I've presented on this at many different OpenStacks, you can see it in the past, and I sort of laid out what needs to happen and that didn't happen. But I think there's hope, and I think the hope comes in the form of Kubernetes, and to a certain degree, Helm. And the reason that Kubernetes with Helm is very powerful is that Kubernetes gives us a computive traction, so that you don't care if you're on the public cloud, or you know OpenStack or Vmware or whatever, and then what Helm gives us is our charts, so ways to deploy services, not just software, and so what we could think about doing in the future is building hybrid cloud based off of Kubernetes and Helm. >> Yeah, so Randy since last time we talked you've got a new role, you're now with Juniper. Juniper had done a Contrail acquisition. You know, quite a few years back you wrote a good blueprint on one of the Juniper forums about the OpenContrail communities. So tell us a little bit about your role, your goals, in that community. >> So OpenContrail has been a primarily Juniper initiative, and we're going to press the reset button on the OpenContrail community. I'm going to do it tonight and call for people to sort of get involved in doing that reset, and when I say reset I mean, wipe the operating system, reload it from scratch, and do it really as a community, not just as a Juniper run initiative, and so people inside Juniper are very excited about this, and what we're trying to do is that we believe that the path forward for OpenContrail is ubiquitous adoption. So rather then playing for just the pieces that we have, which we've done a great job of, we want to take the world's best SDN controller and we want to make sure everybody uses it, because we think aggregate that's good for not only the entire community but also Juniper. >> So, love the idea of kind of rebooting the community in the open, right, because you have to be transparent about these sort of things. >> Randy: Yeah, that's right. >> What are the community segments that you would like to see join you here in the OpenContrail? What kind of users, what kind of companies would you like to see come in to the tent? >> Well anybody's welcome, but we want to start with all of our key stakeholders that exist today, so first one, and arguably one of the most important is our competitors, right so we're hoping to have Mirantis at the table, maybe Ericcson, Huawei, anybody. Cisco, hey come join the party. Second is that we have done really well in Sass and in gaming, and we'd like to see all of those companies come to the table as well, Workday, Symantech, and so on. The third segment is enterprises, we've done well in financial services, we think that that's a really important segment because they're leading edge of enterprises typically, and the fourth is the carrier's obviously incredibly important for Juniper, folks like AT&T, Direction Telecom, all those companies we'd love to see come to the table. And then that's really the primary focus, and then anybody else who wants to show up, anybody who wants to develop in Contrail in the future we'd love to have there. >> Well with open source communities, right, there's always a balance of the contributors and developers versus operators, and we can use the word contributors in a lot of roles. Some open source communities, much more developer focused, >> Randy: That's right. >> Others more operator focused, where do you see this OpenContrail community starting out? >> So where it's been historically is more of our end users and operators. >> I think that's interesting and an interesting twist because I think sometimes open source communities get stuck with just the people who can contribute code, and I'm from an operator community myself, >> Randy: Right. >> So I think that's really interesting. >> We still want all those people but I think what has happened is that when people have come in and they wanted to be more sort of on the developer side, the community hasn't been friendly to them. >> John: Okay. >> Randy: And so we want, that's a key thing that we want to change. You know when we were talking, to certain carriers they came and they said look, it's great you're going to do this, we want to be a part of it, and one of the things we'd like to contribute is more advanced testing around VMFs. And I just look at that and I'm just like that's what we need, right? Juniper is not, can't carry all the water on having, you know, sophisticated test suites for VMFs and more advanced networking use cases, but the carriers are deep into this and we'd love to have them come and bring that. So not just developers, but also QA, people who want to increase the code quality, the architectural quality, and the aggregate value of OpenContrail. >> Okay, Randy can you help place OpenContrail where it fits in this kind of networking spectrum, especially, there's open source things, we've talked about about VPP a couple times on theCube here. The joke for many years was SDN still does nothing, NFV solutions have grown, have been huge use case, is really where the early money for big deployments have been for OpenStack. Where does OpenContrail fit, where does it kind of compare and contrast against some of the other options out there. >> I'm going to answer that slightly differently. I've been skeptical about SDN overlays for a long time, and now I am helping with one of the world's best SDN overlays, and what's changed for me is that in the last year I've seen key customers of Contrail's, of Juniper's actually do something very interesting, right. You've got an SDN overlay, it's complex, it's hard to void, you got to wonder, why should I do this? Well I thought the same thing about virtualization, right, until I figured out, sort of what was the killer app. And what we've seen is a company, one of our customers, and several others, but one in particular I can talk about publicly, Riot Games, take containers and OpenContrail and marry them so that you have an abstraction around compute, and an abstraction around networking, so that their developers can write to that, and they don't care whether that's running on top of public cloud, private cloud, or in some partner's data center globally. And in fact they're going to talk about that today at OpenContrail days at 3:30, and are going to present a lot more details, and that's amazing to me because by abstracting a way and disintermediating the public clouds, you actually have more power, right. You can build your own framework. And if you're using Kubernetes as a baseline you can do a lot more on top of that computing network abstraction. >> You talked about OpenContrail days, again my first summit, I've actually been impressed by the foundation, acknowledging there's a huge landscape of open source and other technologies around there, OpenStack itself doesn't invent everything. Can you talk a little bit about that kind of attitude of bringing, I mean we talk about Kubernetes and that sort of thing, but all the other CNCF projects, monitoring, even components like SCD, right, we're talking about here at this conference. So, can you talk a little bit about how OpenStack can interact with the rest of the open source and cloud native at-large community? >> That's sort of a tough question John. >> John: Okay. >> I mean the reason I say that is like the origins of OpenStack are very much NIH and there has been a very disturbing tendency to sort of re-invent the wheel. A great example is Keystone, still to this day I don't know why Keystone exists and why we created a whole new authentic standard when there were dozens and dozens of battle-tested, battle-hardened protocols and bits of code that existed prior. It's great that we're getting a little bit better at that but I still sense that the origins of the community and some of the technical leadership have resistance to organizing and working with outside components and playing nice. So, it's better but it's not great, it's not where it should be. Really OpenStack needs to be broken down into a lot of different projects that can compete with each other and all run in parallel without having to be so tightly wound together. It's still disappointing to me that we aren't doing that today. >> Randy, wonder if you could give us a little bit of a personal reflection, you've been involved in cloud many years, we've talked about some of the state of it, where do you think enterprises are when they think about their IT, how IT relates to business, some of the big challenges they're facing, and kind of this rapid pace of change that's happening in our industry right now >> Yeah well the pressures just increase. The need to pick up speed and to move faster and to have a greater velocity, that's not going away, that seems to be like an incredible macro-trend that's just going to keep driving people towards the next event. But what I see is that the tension between the infra-structure IT teams and the line of business hasn't really started to get resolved. You see a lot of enterprises back into using DevOps as a way to try to fix the culture change problems but it's just not happening fast enough. I have a lot of concerns that basically private cloud or private infra-structure for enterprises will just not materialize in the way it needs to for the next generation. And that the line of business will continue to just keep moving to public cloud. All the while all the money that's being reinvested in the public cloud is increasing their capabilities in terms feature sets and security capabilities and so on. I just, I don't see the materialization of private cloud happening very well at this point in time and I don't see any trendlines that tell me it's going to change. >> Yeah, what recommendations do you give today to the OpenStack foundation? I know that you haven't been shy in the past about giving guidance as to the direction, what do you think needs to happen to be able to help customers along that journey that they need? >> I don't give any guidance to the OpenStack Foundation anymore, I'm not on the Board of Directors, and frankly I gave a lot of advice in the past that fell on deaf ears and people were unwilling to make the changes that were necessary I think to create success. And even though I was eventually proven right, there doesn't seem to be an appetite for change. I would say that the hard partition between the Board of Directors and the technical committee that was created at the outset with the founding of the Foundation has let to a big problem which is that there's simply business concerns that are technical concerns and there are technical concerns which are business concerns and the actual structure of the Foundation does not allow that to occur because that hard partition between them. So if people on Board of Directors can't actually tell the TC that they'd like to see certain technical changes because they're business concerns and Technical Committee can't tell the Board of Directors they'd like to see business changes made because they're technical concerns around them. And I think that's, it's fundamentally broken until the bylaws are fixed. >> So Randy beyond what we've talked about already what's exciting you these days, you look at like the serverless trend, is that something that you find intriguing or maybe contrary view on it, what's exciting you these days? >> Serverless is really interesting. In fact I'd like to see serverless at the edge. I think it would be fascinating if Amazon webservices could sell a serverless capability that was actually running in the mobile carriers edge. So like on the mobile towers or in essential offices. But you could do distributive computation for IOT literally at the very edge of the network, that would be incredibly powerful. So I am very interested in serverless in that regard. With Kubernetes, I think that this is the future, I think I've seen most of the other initiatives start to fail at this point. Docker Incorporated just hasn't made the progress they need to, hopefully a change in leadership will fix that. But it does mean that more and more people are gravitating towards Kubernetes and that's a thing because whereas OpenStack is historically got no opinion, Kubernetes is a much more prescriptive model and I think that actually leads to faster innovation, a greater pace of change and combined with Helm charts, I think that we're going to see an ecosystem develop around Kubernetes that actually could be a counterweight to the public clouds and really be sort of cloud agnostic. Private, public, at the edge, who cares? >> Randy Bias, always appreciated your very opinionated viewpoints on everything that are happening here. Pleasure to catch up with you as always. John and I will be back will lots more coverage here from OpenStack Summit in Boston, thanks for watching the Cube.