(gentle music) >> Hey! Welcome back to theCUBE's coverage of WiDS 2023, the eighth Annual Women In Data Science Conference. I'm your host, Lisa Martin. We are at Stanford University, as you know we are every year, having some wonderful conversations with some very inspiring women and men in data science and technical roles. I'm very pleased to introduce Tracy Zhang, my co-host, who is in the Data Journalism program at Stanford. And Tracy and I are pleased to welcome our next guest, Rhonda Crate, Principal Data Scientist at Boeing. Great to have you on the program, Rhonda. >> Tracy: Welcome. >> Hey, thanks for having me. >> Were you always interested in data science or STEM from the time you were young? >> No, actually. I was always interested in archeology and anthropology. >> That's right, we were talking about that, anthropology. Interesting. >> We saw the anthropology background, not even a bachelor's degree, but also a master's degree in anthropology. >> So you were committed for a while. >> I was, I was. I actually started college as a fine arts major, but I always wanted to be an archeologist. So at the last minute, 11 credits in, left to switch to anthropology. And then when I did my master's, I focused a little bit more on quantitative research methods and then I got my Stat Degree. >> Interesting. Talk about some of the data science projects that you're working on. When I think of Boeing, I always think of aircraft. But you are doing a lot of really cool things in IT, data analytics. Talk about some of those intriguing data science projects that you're working on. >> Yeah. So when I first started at Boeing, I worked in information technology and data analytics. And Boeing, at the time, had cored up data science in there. And so we worked as a function across the enterprise working on anything from shared services to user experience in IT products, to airplane programs. So, it has a wide range. I worked on environment health and safety projects for a long time as well. So looking at ergonomics and how people actually put parts onto airplanes, along with things like scheduling and production line, part failures, software testing. Yeah, there's a wide spectrum of things. >> But I think that's so fantastic. We've been talking, Tracy, today about just what we often see at WiDS, which is this breadth of diversity in people's background. You talked about anthropology, archeology, you're doing data science. But also all of the different opportunities that you've had at Boeing. To see so many facets of that organization. I always think that breadth of thought diversity can be hugely impactful. >> Yeah. So I will say my anthropology degree has actually worked to my benefit. I'm a huge proponent of integrating liberal arts and sciences together. And it actually helps me. I'm in the Technical Fellowship program at Boeing, so we have different career paths. So you can go into management, you can be a regular employee, or you can go into the Fellowship program. So right now I'm an Associate Technical Fellow. And part of how I got into the Fellowship program was that diversity in my background, what made me different, what made me stand out on projects. Even applying a human aspect to things like ergonomics, as silly as that sounds, but how does a person actually interact in the space along with, here are the actual measurements coming off of whatever system it is that you're working on. So, I think there's a lot of opportunities, especially in safety as well, which is a big initiative for Boeing right now, as you can imagine. >> Tracy: Yeah, definitely. >> I can't go into too specifics. >> No, 'cause we were like, I think a theme for today that kind of we brought up in in all of our talk is how data is about people, how data is about how people understand the world and how these data can make impact on people's lives. So yeah, I think it's great that you brought this up, and I'm very happy that your anthropology background can tap into that and help in your day-to-day data work too. >> Yeah. And currently, right now, I actually switched over to Strategic Workforce Planning. So it's more how we understand our workforce, how we work towards retaining the talent, how do we get the right talent in our space, and making sure overall that we offer a culture and work environment that is great for our employees to come to. >> That culture is so important. You know, I was looking at some anitab.org stats from 2022 and you know, we always talk about the number of women in technical roles. For a long time it's been hovering around that 25% range. The data from anitab.org showed from '22, it's now 27.6%. So, a little increase. But one of the biggest challenges still, and Tracy and I and our other co-host, Hannah, have been talking about this, is attrition. Attrition more than doubled last year. What are some of the things that Boeing is doing on the retention side, because that is so important especially as, you know, there's this pipeline leakage of women leaving technical roles. Tell us about what Boeing's, how they're invested. >> Yeah, sure. We actually have a publicly available Global Diversity Report that anybody can go and look at and see our statistics for our organization. Right now, off the top of my head, I think we're hovering at about 24% in the US for women in our company. It has been a male majority company for many years. We've invested heavily in increasing the number of women in roles. One interesting thing about this year that came out is that even though with the great resignation and those types of things, the attrition level between men and women were actually pretty close to being equal, which is like the first time in our history. Usually it tends on more women leaving. >> Lisa: That's a good sign. >> Right. >> Yes, that's a good sign. >> And we've actually focused on hiring and bringing in more women and diversity in our company. >> Yeah, some of the stats too from anitab.org talked about the increase, and I have to scroll back and find my notes, the increase in 51% more women being hired in 2022 than 2021 for technical roles. So the data, pun intended, is showing us. I mean, the data is there to show the impact that having females in executive leadership positions make from a revenue perspective. >> Tracy: Definitely. >> Companies are more profitable when there's women at the head, or at least in senior leadership roles. But we're seeing some positive trends, especially in terms of representation of women technologists. One of the things though that I found interesting, and I'm curious to get your thoughts on this, Rhonda, is that the representation of women technologists is growing in all areas, except interns. >> Rhonda: Hmm. >> So I think, we've got to go downstream. You teach, I have to go back to my notes on you, did my due diligence, R programming classes through Boeings Ed Wells program, this is for WSU College of Arts and Sciences, talk about what you teach and how do you think that intern kind of glut could be solved? >> Yeah. So, they're actually two separate programs. So I teach a data analytics course at Washington State University as an Adjunct Professor. And then the Ed Wells program is a SPEEA, which is an Aerospace Union, focused on bringing up more technology and skills to the actual workforce itself. So it's kind of a couple different audiences. One is more seasoned employees, right? The other one is our undergraduates. I teach a Capstone class, so it's a great way to introduce students to what it's actually like to work on an industry project. We partner with Google and Microsoft and Boeing on those. The idea is also that maybe those companies have openings for the students when they're done. Since it's Senior Capstone, there's not a lot of opportunities for internships. But the opportunities to actually get hired increase a little bit. In regards to Boeing, we've actually invested a lot in hiring more women interns. I think the number was 40%, but you'd have to double check. >> Lisa: That's great, that's fantastic. >> Tracy: That's way above average, I think. >> That's a good point. Yeah, it is above average. >> Double check on that. That's all from my memory. >> Is this your first WiDS, or have you been before? >> I did virtually last year. >> Okay. One of the things that I love, I love covering this event every year. theCUBE's been covering it since it's inception in 2015. But it's just the inspiration, the vibe here at Stanford is so positive. WiDS is a movement. It's not an initiative, an organization. There are going to be, I think annually this year, there will be 200 different events. Obviously today we're live on International Women's Day. 60 plus countries, 100,000 plus people involved. So, this is such a positive environment for women and men, because we need everybody, underrepresented minorities, to be able to understand the implication that data has across our lives. If we think about stripping away titles in industries, everybody is a consumer, not everybody, most of mobile devices. And we have this expectation, I was in Barcelona last week at a Mobile World Congress, we have this expectation that we're going to be connected 24/7. I can get whatever I want wherever I am in the world, and that's all data driven. And the average person that isn't involved in data science wouldn't understand that. At the same time, they have expectations that depend on organizations like Boeing being data driven so that they can get that experience that they expect in their consumer lives in any aspect of their lives. And that's one of the things I find so interesting and inspiring about data science. What are some of the things that keep you motivated to continue pursuing this? >> Yeah I will say along those lines, I think it's great to invest in K-12 programs for Data Literacy. I know one of my mentors and directors of the Data Analytics program, Dr. Nairanjana Dasgupta, we're really familiar with each other. So, she runs a WSU program for K-12 Data Literacy. It's also something that we strive for at Boeing, and we have an internal Data Literacy program because, believe it or not, most people are in business. And there's a lot of disconnect between interpreting and understanding data. For me, what kind of drives me to continue data science is that connection between people and data and how we use it to improve our world, which is partly why I work at Boeing too 'cause I feel that they produce products that people need like satellites and airplanes, >> Absolutely. >> and everything. >> Well, it's tangible, it's relatable. We can understand it. Can you do me a quick favor and define data literacy for anyone that might not understand what that means? >> Yeah, so it's just being able to understand elements of data, whether that's a bar chart or even in a sentence, like how to read a statistic and interpret a statistic in a sentence, for example. >> Very cool. >> Yeah. And sounds like Boeing's doing a great job in these programs, and also trying to hire more women. So yeah, I wanted to ask, do you think there's something that Boeing needs to work on? Or where do you see yourself working on say the next five years? >> Yeah, I think as a company, we always think that there's always room for improvement. >> It never, never stops. >> Tracy: Definitely. (laughs) >> I know workforce strategy is an area that they're currently really heavily investing in, along with safety. How do we build safer products for people? How do we help inform the public about things like Covid transmission in airports? For example, we had the Confident Traveler Initiative which was a big push that we had, and we had to be able to inform people about data models around Covid, right? So yeah, I would say our future is more about an investment in our people and in our culture from my perspective >> That's so important. One of the hardest things to change especially for a legacy organization like Boeing, is culture. You know, when I talk with CEO's or CIO's or COO's about what's your company's vision, what's your strategy? Especially those companies that are on that digital journey that have no choice these days. Everybody expects to have a digital experience, whether you're transacting an an Uber ride, you're buying groceries, or you're traveling by air. That culture sounds like Boeing is really focused on that. And that's impressive because that's one of the hardest things to morph and mold, but it's so essential. You know, as we look around the room here at WiDS it's obviously mostly females, but we're talking about women, underrepresented minorities. We're talking about men as well who are mentors and sponsors to us. I'd love to get your advice to your younger self. What would you tell yourself in terms of where you are now to become a leader in the technology field? >> Yeah, I mean, it's kind of an interesting question because I always try to think, live with no regrets to an extent. >> Lisa: I like that. >> But, there's lots of failures along the way. (Tracy laughing) I don't know if I would tell myself anything different because honestly, if I did, I wouldn't be where I am. >> Lisa: Good for you. >> I started out in fine arts, and I didn't end up there. >> That's good. >> Such a good point, yeah. >> We've been talking about that and I find that a lot at events like WiDS, is women have these zigzaggy patterns. I studied biology, I have a master's in molecular biology, I'm in media and marketing. We talked about transportable skills. There's a case I made many years ago when I got into tech about, well in science you learn the art of interpreting esoteric data and creating a story from it. And that's a transportable skill. But I always say, you mentioned failure, I always say failure is not a bad F word. It allows us to kind of zig and zag and learn along the way. And I think that really fosters thought diversity. And in data science, that is one of the things we absolutely need to have is that diversity and thought. You know, we talk about AI models being biased, we need the data and we need the diverse brains to help ensure that the biases are identified, extracted, and removed. Speaking of AI, I've been geeking out with ChatGPT. So, I'm on it yesterday and I ask it, "What's hot in data science?" And I was like, is it going to get that? What's hot? And it did it, it came back with trends. I think if I ask anything, "What's hot?", I should be to Paris Hilton, but I didn't. And so I was geeking out. One of the things I learned recently that I thought was so super cool is the CTO of OpenAI is a woman, Mira Murati, which I didn't know until over the weekend. Because I always think if I had to name top females in tech, who would they be? And I always default to Sheryl Sandberg, Carly Fiorina, Susan Wojcicki running YouTube. Who are some of the people in your history, in your current, that are really inspiring to you? Men, women, indifferent. >> Sure. I think Boeing is one of the companies where you actually do see a lot of women in leadership roles. I think we're one of the top companies with a number of women executives, actually. Susan Doniz, who's our Chief Information Officer, I believe she's actually slotted to speak at a WiDS event come fall. >> Lisa: Cool. >> So that will be exciting. Susan's actually relatively newer to Boeing in some ways. A Boeing time skill is like three years is still kind of new. (laughs) But she's been around for a while and she's done a lot of inspiring things, I think, for women in the organization. She does a lot with Latino communities and things like that as well. For me personally, you know, when I started at Boeing Ahmad Yaghoobi was one of my mentors and my Technical Lead. He came from Iran during a lot of hard times in the 1980s. His brother actually wrote a memoir, (laughs) which is just a fun, interesting fact. >> Tracy: Oh my God! >> Lisa: Wow! >> And so, I kind of gravitate to people that I can learn from that's not in my sphere, that might make me uncomfortable. >> And you probably don't even think about how many people you're influencing along the way. >> No. >> We just keep going and learning from our mentors and probably lose sight of, "I wonder how many people actually admire me?" And I'm sure there are many that admire you, Rhonda, for what you've done, going from anthropology to archeology. You mentioned before we went live you were really interested in photography. Keep going and really gathering all that breadth 'cause it's only making you more inspiring to people like us. >> Exactly. >> We thank you so much for joining us on the program and sharing a little bit about you and what brought you to WiDS. Thank you so much, Rhonda. >> Yeah, thank you. >> Tracy: Thank you so much for being here. >> Lisa: Yeah. >> Alright. >> For our guests, and for Tracy Zhang, this is Lisa Martin live at Stanford University covering the eighth Annual Women In Data Science Conference. Stick around. Next guest will be here in just a second. (gentle music)

(ambient music) >> Good morning, everyone. Lisa Martin with theCUBE, live at the eighth Annual Women in Data Science Conference. This is one of my absolute favorite events of the year. We engage with tons of great inspirational speakers, men and women, and what's happening with WiDS is a global movement. I've got two fabulous co-hosts with me today that you're going to be hearing and meeting. Please welcome Tracy Zhang and Hannah Freitag, who are both from the sata journalism program, master's program, at Stanford. So great to have you guys. >> So excited to be here. >> So data journalism's so interesting. Tracy, tell us a little bit about you, what you're interested in, and then Hannah we'll have you do the same thing. >> Yeah >> Yeah, definitely. I definitely think data journalism is very interesting, and in fact, I think, what is data journalism? Is definitely one of the big questions that we ask during the span of one year, which is the length of our program. And yeah, like you said, I'm in this data journalism master program, and I think coming in I just wanted to pivot from my undergrad studies, which is more like a traditional journalism, into data. We're finding stories through data, so that's why I'm also very excited about meeting these speakers for today because they're all, they have different backgrounds, but they all ended up in data science. So I think they'll be very inspirational and I can't wait to talk to them. >> Data in stories, I love that. Hannah, tell us a little bit about you. >> Yeah, so before coming to Stanford, I was a research assistant at Humboldt University in Berlin, so I was in political science research. And I love to work with data sets and data, but I figured that, for me, I don't want this story to end up in a research paper, which is only very limited in terms of the audience. And I figured, okay, data journalism is the perfect way to tell stories and use data to illustrate anecdotes, but to make it comprehensive and accessible for a broader audience. So then I found this program at Stanford and I was like, okay, that's the perfect transition from political science to journalism, and to use data to tell data-driven stories. So I'm excited to be in this program, I'm excited for the conference today and to hear from these amazing women who work in data science. >> You both brought up great points, and we were chatting earlier that there's a lot of diversity in background. >> Tracy: Definitely. >> Not everyone was in STEM as a young kid or studied computer science. Maybe some are engineering, maybe some are are philosophy or economic, it's so interesting. And what I find year after year at WiDS is it brings in so much thought diversity. And that's what being data-driven really demands. It demands that unbiased approach, that diverse, a spectrum of diverse perspectives, and we definitely get that at WiDS. There's about 350 people in person here, but as I mentioned in the opening, hundreds of thousands will engage throughout the year, tens of thousands probably today at local events going on across the globe. And it just underscores the importance of every organization, whether it's a bank or a grocer, has to be data-driven. We have that expectation as consumers in our consumer lives, and even in our business lives, that I'm going to engage with a business, whatever it is, and they're going to know about me, they're going to deliver me a personalized experience that's relevant to me and my history. And all that is powered by data science, which is I think it's fascinating. >> Yeah, and the great way is if you combine data with people. Because after all, large data sets, they oftentimes consist of stories or data that affects people. And to find these stories or advanced research in whatever fields, maybe in the financial business, or in health, as you mentioned, the variety of fields, it's very powerful, powerful tool to use. >> It's a very power, oh, go ahead Tracy. >> No, definitely. I just wanted to build off of that. It's important to put a face on data. So a dataset without a name is just some numbers, but if there's a story, then I think it means something too. And I think Margot was talking about how data science is about knowing or understanding the past, I think that's very interesting. That's a method for us to know who we are. >> Definitely. There's so many opportunities. I wanted to share some of the statistics from AnitaB.org that I was just looking at from 2022. We always talk at events like WiDS, and some of the other women in tech things, theCUBE is very much pro-women in tech, and has been for a very long, since the beginning of theCUBE. But we've seen the numbers of women technologists historically well below 25%, and we see attrition rates are high. And so we often talk about, well, what can we do? And part of that is raising the awareness. And that's one of the great things about WiDS, especially WiDS happening on International Women's Day, today, March 8th, and around event- >> Tracy: A big holiday. >> Exactly. But one of the nice things I was looking at, the AnitaB.org research, is that representation of tech women is on the rise, still below pre-pandemic levels, but it's actually nearly 27% of women in technical roles. And that's an increase, slow increase, but the needle is moving. We're seeing much more gender diversity across a lot of career levels, which is exciting. But some of the challenges remain. I mean, the representation of women technologists is growing, except at the intern level. And I thought that was really poignant. We need to be opening up that pipeline and going younger. And you'll hear a lot of those conversations today about, what are we doing to reach girls in grade school, 10 year olds, 12 year olds, those in high school? How do we help foster them through their undergrad studies- >> And excite them about science and all these fields, for sure. >> What do you think, Hannah, on that note, and I'll ask you the same question, what do you think can be done? The theme of this year's International Women's Day is Embrace Equity. What do you think can be done on that intern problem to help really dial up the volume on getting those younger kids interested, one, earlier, and two, helping them stay interested? >> Yeah. Yeah, that's a great question. I think it's important to start early, as you said, in school. Back in the day when I went to high school, we had this one day per year where we could explore as girls, explore a STEM job and go into the job for one day and see how it's like to work in a, I dunno, in IT or in data science, so that's a great first step. But as you mentioned, it's important to keep girls and women excited about this field and make them actually pursue this path. So I think conferences or networking is very powerful. Also these days with social media and technology, we have more ability and greater ways to connect. And I think we should even empower ourselves even more to pursue this path if we're interested in data science, and not be like, okay, maybe it's not for me, or maybe as a woman I have less chances. So I think it's very important to connect with other women, and this is what WiDS is great about. >> WiDS is so fantastic for that network effect, as you talked about. It's always such, as I was telling you about before we went live, I've covered five or six WiDS for theCUBE, and it's always such a day of positivity, it's a day of of inclusivity, which is exactly what Embrace Equity is really kind of about. Tracy, talk a little bit about some of the things that you see that will help with that hashtag Embrace Equity kind of pulling it, not just to tech. Because we're talking and we saw Meta was a keynote who's going to come to talk with Hannah and me in a little bit, we see Total Energies on the program today, we see Microsoft, Intuit, Boeing Air Company. What are some of the things you think that can be done to help inspire, say, little Tracy back in the day to become interested in STEM or in technology or in data? What do you think companies can and should be doing to dial up the volume for those youngsters? >> Yeah, 'cause I think somebody was talking about, one of the keynote speakers was talking about how there is a notion that girls just can't be data scientists. girls just can't do science. And I think representation definitely matters. If three year old me see on TV that all the scientists are women, I think I would definitely have the notion that, oh, this might be a career choice for me and I can definitely also be a scientist if I want. So yeah, I think representation definitely matters and that's why conference like this will just show us how these women are great in their fields. They're great data scientists that are bringing great insight to the company and even to the social good as well. So yeah, I think that's very important just to make women feel seen in this data science field and to listen to the great woman who's doing amazing work. >> Absolutely. There's a saying, you can't be what you can't see. >> Exactly. >> And I like to say, I like to flip it on its head, 'cause we can talk about some of the negatives, but there's a lot of positives and I want to share some of those in a minute, is that we need to be, that visibility that you talked about, the awareness that you talked about, it needs to be there but it needs to be sustained and maintained. And an organization like WiDS and some of the other women in tech events that happen around the valley here and globally, are all aimed at raising the profile of these women so that the younger, really, all generations can see what they can be. We all, the funny thing is, we all have this expectation whether we're transacting on Uber ride or we are on Netflix or we're buying something on Amazon, we can get it like that. They're going to know who I am, they're going to know what I want, they're going to want to know what I just bought or what I just watched. Don't serve me up something that I've already done that. >> Hannah: Yeah. >> Tracy: Yeah. >> So that expectation that everyone has is all about data, though we don't necessarily think about it like that. >> Hannah: Exactly. >> Tracy: Exactly. >> But it's all about the data that, the past data, the data science, as well as the realtime data because we want to have these experiences that are fresh, in the moment, and super relevant. So whether women recognize it or not, they're data driven too. Whether or not you're in data science, we're all driven by data and we have these expectations that every business is going to meet it. >> Exactly. >> Yeah. And circling back to young women, I think it's crucial and important to have role models. As you said, if you see someone and you're younger and you're like, oh I want to be like her. I want to follow this path, and have inspiration and a role model, someone you look up to and be like, okay, this is possible if I study the math part or do the physics, and you kind of have a goal and a vision in mind, I think that's really important to drive you. >> Having those mentors and sponsors, something that's interesting is, I always, everyone knows what a mentor is, somebody that you look up to, that can guide you, that you admire. I didn't learn what a sponsor was until a Women in Tech event a few years ago that we did on theCUBE. And I was kind of, my eyes were open but I didn't understand the difference between a mentor and a sponsor. And then it got me thinking, who are my sponsors? And I started going through LinkedIn, oh, he's a sponsor, she's a sponsor, people that help really propel you forward, your recommenders, your champions, and it's so important at every level to build that network. And we have, to your point, Hannah, there's so much potential here for data drivenness across the globe, and there's so much potential for women. One of the things I also learned recently , and I wanted to share this with you 'cause I'm not sure if you know this, ChatGPT, exploding, I was on it yesterday looking at- >> Everyone talking about it. >> What's hot in data science? And it was kind of like, and I actually asked it, what was hot in data science in 2023? And it told me that it didn't know anything prior to 2021. >> Tracy: Yes. >> Hannah: Yeah. >> So I said, Oh, I'm so sorry. But everyone's talking about ChatGPT, it is the most advanced AI chatbot ever released to the masses, it's on fire. They're likening it to the launch of the iPhone, 100 million-plus users. But did you know that the CTO of ChatGPT is a woman? >> Tracy: I did not know, but I learned that. >> I learned that a couple days ago, Mira Murati, and of course- >> I love it. >> She's been, I saw this great profile piece on her on Fast Company, but of course everything that we're hearing about with respect to ChatGPT, a lot on the CEO. But I thought we need to help dial up the profile of the CTO because she's only 35, yet she is at the helm of one of the most groundbreaking things in our lifetime we'll probably ever see. Isn't that cool? >> That is, yeah, I completely had no idea. >> I didn't either. I saw it on LinkedIn over the weekend and I thought, I have to talk about that because it's so important when we talk about some of the trends, other trends from AnitaB.org, I talked about some of those positive trends. Overall hiring has rebounded in '22 compared to pre-pandemic levels. And we see also 51% more women being hired in '22 than '21. So the data, it's all about data, is showing us things are progressing quite slowly. But one of the biggest challenges that's still persistent is attrition. So we were talking about, Hannah, what would your advice be? How would you help a woman stay in tech? We saw that attrition last year in '22 according to AnitaB.org, more than doubled. So we're seeing women getting into the field and dropping out for various reasons. And so that's still an extent concern that we have. What do you think would motivate you to stick around if you were in a technical role? Same question for you in a minute. >> Right, you were talking about how we see an increase especially in the intern level for women. And I think if, I don't know, this is a great for a start point for pushing the momentum to start growth, pushing the needle rightwards. But I think if we can see more increase in the upper level, the women representation in the upper level too, maybe that's definitely a big goal and something we should work towards to. >> Lisa: Absolutely. >> But if there's more representation up in the CTO position, like in the managing level, I think that will definitely be a great factor to keep women in data science. >> I was looking at some trends, sorry, Hannah, forgetting what this source was, so forgive me, that was showing that there was a trend in the last few years, I think it was Fast Company, of more women in executive positions, specifically chief operating officer positions. What that hasn't translated to, what they thought it might translate to, is more women going from COO to CEO and we're not seeing that. We think of, if you ask, name a female executive that you'd recognize, everyone would probably say Sheryl Sandberg. But I was shocked to learn the other day at a Women in Tech event I was doing, that there was a survey done by this organization that showed that 78% of people couldn't identify. So to your point, we need more of them in that visible role, in the executive suite. >> Tracy: Exactly. >> And there's data that show that companies that have women, companies across industries that have women in leadership positions, executive positions I should say, are actually more profitable. So it's kind of like, duh, the data is there, it's telling you this. >> Hannah: Exactly. >> Right? >> And I think also a very important point is work culture and the work environment. And as a woman, maybe if you enter and you work two or three years, and then you have to oftentimes choose, okay, do I want family or do I want my job? And I think that's one of the major tasks that companies face to make it possible for women to combine being a mother and being a great data scientist or an executive or CEO. And I think there's still a lot to be done in this regard to make it possible for women to not have to choose for one thing or the other. And I think that's also a reason why we might see more women at the entry level, but not long-term. Because they are punished if they take a couple years off if they want to have kids. >> I think that's a question we need to ask to men too. >> Absolutely. >> How to balance work and life. 'Cause we never ask that. We just ask the woman. >> No, they just get it done, probably because there's a woman on the other end whose making it happen. >> Exactly. So yeah, another thing to think about, another thing to work towards too. >> Yeah, it's a good point you're raising that we have this conversation together and not exclusively only women, but we all have to come together and talk about how we can design companies in a way that it works for everyone. >> Yeah, and no slight to men at all. A lot of my mentors and sponsors are men. They're just people that I greatly admire who saw raw potential in me 15, 18 years ago, and just added a little water to this little weed and it started to grow. In fact, theCUBE- >> Tracy: And look at you now. >> Look at me now. And theCUBE, the guys Dave Vellante and John Furrier are two of those people that are sponsors of mine. But it needs to be diverse. It needs to be diverse and gender, it needs to include non-binary people, anybody, shouldn't matter. We should be able to collectively work together to solve big problems. Like the propaganda problem that was being discussed in the keynote this morning with respect to China, or climate change. Climate change is a huge challenge. Here, we are in California, we're getting an atmospheric river tomorrow. And Californians and rain, we're not so friendly. But we know that there's massive changes going on in the climate. Data science can help really unlock a lot of the challenges and solve some of the problems and help us understand better. So there's so much real-world implication potential that being data-driven can really lead to. And I love the fact that you guys are studying data journalism. You'll have to help me understand that even more. But we're going to going to have great conversations today, I'm so excited to be co-hosting with both of you. You're going to be inspired, you're going to learn, they're going to learn from us as well. So let's just kind of think of this as a community of men, women, everything in between to really help inspire the current generations, the future generations. And to your point, let's help women feel confident to be able to stay and raise their hand for fast-tracking their careers. >> Exactly. >> What are you guys, last minute, what are you looking forward to most for today? >> Just meeting these great women, I can't wait. >> Yeah, learning from each other. Having this conversation about how we can make data science even more equitable and hear from the great ideas that all these women have. >> Excellent, girls, we're going to have a great day. We're so glad that you're here with us on theCUBE, live at Stanford University, Women in Data Science, the eighth annual conference. I'm Lisa Martin, my two co-hosts for the day, Tracy Zhang, Hannah Freitag, you're going to be seeing a lot of us, we appreciate. Stick around, our first guest joins Hannah and me in just a minute. (ambient music)

>>Set restaurants. And who says TEUs had got a little ass more skin in the game for us, in charge of his destiny? You guys are excited. Robert Worship is Chief Alumni. >>My name is Dave Ante, and I'm a long time industry analyst. So when you're as old as I am, you've seen a lot of transitions. Everybody talks about industry cycles and waves. I've seen many, many waves. Met a lot of industry executives and of a little bit of a, an industry historian. When you interview many thousands of people, probably five or 6,000 people as I have over the last half of a decade, you get to interact with a lot of people's knowledge and you begin to develop patterns. And so that's sort of what I bring is, is an ability to catalyze the conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody's expert at something. Everybody's passionate about something and has real deep knowledge about that's something well, we wanna focus in on that area and extract that knowledge and share it with our communities. This is Dave Ante. Thanks for watching the Cube. >>Hello everyone and welcome back to the Cube where we are streaming live this week from CubeCon. I am Savannah Peterson and I am joined by an absolutely stellar lineup of cube brilliance this afternoon. To my left, a familiar face, Lisa Martin. Lisa, how you feeling? End of day two. >>Excellent. It was so much fun today. The buzz started yesterday, the momentum, the swell, and we only heard even more greatness today. >>Yeah, yeah, abs, absolutely. You know, I, I sometimes think we've hit an energy cliff, but it feels like the energy is just >>Continuous. Well, I think we're gonna, we're gonna slide right into tomorrow. >>Yeah, me too. I love it. And we've got two fantastic analysts with us today, Sarge and Keith. Thank you both for joining us. We feel so lucky today. >>Great being back on. >>Thanks for having us. Yeah, Yeah. It's nice to have you back on the show. We were, had you yesterday, but I miss hosting with you. It's been a while. >>It has been a while. We haven't done anything in since, Since pre >>Pandemic, right? Yeah, I think you're >>Right. Four times there >>Be four times back in the day. >>We, I always enjoy whole thing, Lisa, cuz she's so well prepared. I don't have to do any research when I come >>Home. >>Lisa will bring up some, Oh, sorry. Jeep, I see that in 2008 you won this award for Yeah. Being just excellent and I, I'm like, Oh >>Yeah. All right Keith. So, >>So did you do his analysis? >>Yeah, it's all done. Yeah. Great. He only part, he's not sitting next to me too. We can't see it, so it's gonna be like a magic crystal bell. Right. So a lot of people here. You got some stats in terms of the attendees compared >>To last year? Yeah, Priyanka told us we were double last year up to 8,000. We also got the scoop earlier that 2023 is gonna be in Chicago, which is very exciting. >>Oh, that is, is nice. Yeah, >>We got to break that here. >>Excellent. Keith, talk to us about what some of the things are that you've seen the last couple of days. The momentum. What's the vibe? I saw your tweet about the top three things you were being asked. Kubernetes was not one of them. >>Kubernetes were, was not one of 'em. This conference is starting to, it, it still feels very different than a vendor conference. The keynote is kind of, you know, kind of all over the place talking about projects, but the hallway track has been, you know, I've, this is maybe my fifth or sixth CU con in person. And the hallway track is different. It's less about projects and more about how, how do we adjust to the enterprise? How do we Yes. Actually do enterprise things. And it has been amazing watching this community grow. I'm gonna say grow up and mature. Yes. You know, you know, they're not wearing ties yet, but they are definitely understanding kind of the, the friction of implementing new technology in, in an enterprise. >>Yeah. So ge what's your, what's been your take, We were with you yesterday. What's been the take today to take aways? >>NOMA has changed since yesterday, but a few things I think I, I missed talking about that yesterday were that, first of all, let's just talk about Amazon. Amazon earnings came out, it spooked the market and I think it's relevant in this context as well, because they're number one cloud provider. Yeah. And all, I mean, almost all of these technologies on the back of us here, they are related to cloud, right? So it will have some impact on these. Like we have to analyze that. Like will it make the open source go faster or slower in, in lieu of the fact that the, the cloud growth is slowing. Right? So that's, that's one thing that's put that's put that aside. I've been thinking about the, the future of Kubernetes. What is the future of Kubernetes? And in that context, I was thinking like, you know, I think in, when I put a pointer there, I think in tangents, like, what else is around this thing? So I think CN CNCF has been writing the success of Kubernetes. They are, that was their number one flagship project, if you will. And it was mature enough to stand on its own. It it was Google, it's Google's Borg dub da Kubernetes. It's a genericized version of that. Right? So folks who do tech deep down, they know that, Right. So I think it's easier to stand with a solid, you know, project. But when the newer projects come in, then your medal will get tested at cncf. Right. >>And cncf, I mean they've got over 140 projects Yeah. Right now. So there's definitely much beyond >>Kubernetes. Yeah. So they, I have numbers there. 18 graduated, right, 37 in incubation and then 81 in Sandbox stage. They have three stages, right. So it's, they have a lot to chew on and the more they take on, the less, you know, quality you get goes into it. Who is, who's putting the money behind it? Which vendors are sponsoring like cncf, like how they're getting funded up. I think it >>Something I pay attention to as well. Yeah. Yeah. Lisa, I know you've got >>Some insight. Those are the things I was thinking about today. >>I gotta ask you, what's your take on what Keith said? Are you also seeing the maturation of the enterprise here at at coupon? >>Yes, I am actually, when you say enterprise versus what's the other side? Startups, right? Yeah. So startups start using open source a lot more earlier or lot more than enterprises. The enterprise is what they need. Number one thing is the, for their production workloads, they want a vendor sporting them. I said that yesterday as well, right? So it depend depending on the size of the enterprise. If you're a big shop, definitely if you have one of the 500 or Fortune five hundreds and your tech savvy shop, then you can absorb the open source directly coming from the open source sort of universe right. Coming to you. But if you are the second tier of enterprise, you want to go to a provider which is managed service provider, or it can be cloud service provider in this case. Yep. Most of the cloud service providers have multiple versions of Kubernetes, for example. >>I'm not talking about Kubernetes only, but like, but that is one example, right? So at Amazon you can get five different flavors of Kubernetes, right? Fully manage, have, manage all kind of stuff. So people don't have bandwidth to manage that stuff locally. You have to patch it, you have to roll in the new, you know, updates and all that stuff. Like, it's a lot of work for many. So CNCF actually is formed for that reason. Like the, the charter is to bring the quality to open source. Like in other companies they have the release process and they, the stringent guidelines and QA and all that stuff. So is is something ready for production? That's the question when it comes to any software, right? So they do that kind of work and, and, and they have these buckets defined at high level, but it needs more >>Work. Yeah. So one of the things that, you know, kind of stood out to me, I have good friend in the community, Alex Ellis, who does open Fast. It's a serverless platform, great platform. Two years ago or in 2019, there was a serverless day date. And in serverless day you had K Native, you had Open Pass, you had Ws, which is supported by IBM completely, not CNCF platforms. K native came into the CNCF full when Google donated the project a few months ago or a couple of years ago, now all of a sudden there's a K native day. Yes. Not a serverless day, it's a K native day. And I asked the, the CNCF event folks like, what happened to Serverless Day? I missed having open at serverless day. And you know, they, they came out and said, you know what, K native got big enough. >>They came in and I think Red Hat and Google wanted to sponsor a K native day. So serverless day went away. So I think what what I'm interested in and over the next couple of years is, is they're gonna be pushback from the C against the cncf. Is the CNCF now too big? Is it now the gatekeeper for do I have to be one of those 147 projects, right? In order enough to get my project noticed the open, fast, great project. I don't think Al Alex has any desire to have his project hosted by cncf, but it probably deserves, you know, shoulder left recognition with that. So I'm pushing to happen to say, okay, if this is open community, this is open source. If CNC is the place to have the cloud native conversation, what about the projects that's not cncf? Like how do we have that conversation when we don't have the power of a Google right. Or a, or a Lenox, et cetera, or a Lenox Foundation. So GE what, >>What are your thoughts on that? Is, is CNC too big? >>I don't think it's too big. I think it's too small to handle the, what we are doing in open source, right? So it's a bottle. It can become a bottleneck. Okay. I think too big in a way that yeah, it has, it has, it has power from that point of view. It has that cloud, if you will. The people listen to it. If it's CNCF project or this must be good, it's like in, in incubators. Like if you are y white Combinator, you know, company, it must be good. You know, I mean, may not be >>True, but, >>Oh, I think there's a bold assumption there though. I mean, I think everyone's just trying to do the best they can. And when we're evaluating projects, a very different origin and background, it's incredibly hard. Very c and staff is a staff of 30 people. They've got 180,000 people that are contributing to these projects and a thousand maintainers that they're trying to uphold. I think the challenge is actually really great. And to me, I actually look at events as an illustration of, you know, what's the culture and the health of an organization. If I were to evaluate CNCF based on that, I'd say we're very healthy right now. I would say that we're in a good spot. There's a lot of momentum. >>Yeah. I, I think CNCF is very healthy. I'm, I'm appreciative for it being here. I love coupon. It's becoming the, the facto conference to have this conversation has >>A totally >>Different vibe to other, It's a totally different vibe. Yeah. There needs to be a conduit and truth be told, enterprise buyers, to subject's point, this is something that we do absolutely agree on, on enterprise buyers. We want someone to pick winners and losers. We do, we, we don't want a box of Lego dumped on our, the middle of our table. We want somebody to have sorted that out. So while there may be five or six different service mesh solutions, at least the cncf, I can go there and say, Oh, I'll pick between the three or four that are most popular. And it, it's a place to curate. But I think with that curation comes the other side of it. Of how do we, how, you know, without the big corporate sponsor, how do I get my project pushed up? Right? Elevated. Elevated, Yep. And, and put onto the show floor. You know, another way that projects get noticed is that startups will adopt them, Push them. They may not even be, I don't, my CNCF project may not, my product may not even be based on the CNCF product. But the new stack has a booth, Ford has a booth. Nothing to do with a individual prod up, but promoting open source. What happens when you're not sponsored? >>I gotta ask you guys, what do you disagree on? >>Oh, so what, what do we disagree on? So I'm of the mindset, I can, I can say this, I I believe hybrid infrastructure is the future of it. Bar none. If I built my infrastructure, if I built my application in the cloud 10 years ago and I'm still building net new applications, I have stuff that I built 10 years ago that looks a lot like on-prem, what do I do with it? I can't modernize it cuz I don't have the developers to do it. I need to stick that somewhere. And where I'm going to stick that at is probably a hybrid infrastructure. So colo, I'm not gonna go back to the data center, but I'm, I'm gonna look, pick up something that looks very much like the data center and I'm saying embrace that it's the future. And if you're Boeing and you have, and Boeing is a member, cncf, that's a whole nother topic. If you have as 400 s, hpu X, et cetera, stick that stuff. Colo, build new stuff, but, and, and continue to support OpenStack, et cetera, et cetera. Because that's the future. Hybrid is the future. >>And sub g agree, disagree. >>I okay. Hybrid. Nobody can deny that the hybrid is the reality, not the future. It's a reality right now. It's, it's a necessity right now you can't do without it. Right. And okay, hybrid is very relative term. You can be like 10% here, 90% still hybrid, right? So the data center is shrinking and it will keep shrinking. Right? And >>So if by whole is the data center shrinking? >>This is where >>Quick one quick getting guys for it. How is growing by a clip? Yeah, but there's no data supporting. David Lym just came out for a report I think last year that showed that the data center is holding steady, holding steady, not growing, but not shrinking. >>Who sponsored that study? Wait, hold on. So the, that's a question, right? So more than 1 million data centers have been closed. I have, I can dig that through number through somebody like some organizations we published that maybe they're cloud, you know, people only. So the, when you get these kind of statements like it, it can be very skewed statements, right. But if you have seen the, the scene out there, which you have, I know, but I have also seen a lot of data centers walk the floor of, you know, a hundred thousand servers in a data center. I cannot imagine us consuming the infrastructure the way we were going into the future of co Okay. With, with one caveat actually. I am not big fan of like broad strokes. Like make a blanket statement. Oh no, data center's dead. Or if you are, >>That's how you get those esty headlines now. Yeah, I know. >>I'm all about to >>Put a stake in the ground. >>Actually. The, I think that you get more intelligence from the new end, right? A small little details if you will. If you're golden gold manak or Bank of America, you have so many data centers and you will still have data centers because performance matters to you, right? Your late latency matters for applications. But if you are even a Fortune 500 company on the lower end and or a healthcare vertical, right? That your situation is different. If you are a high, you know, growth startup, your situation is different, right? You will be a hundred percent cloud. So cloud gives you velocity, the, the, the pace of change, the pace of experimentation that actually you are buying innovation through cloud. It's proxy for innovation. And that's how I see it. But if you have, if you're stuck with older applications, I totally understand. >>Yeah. So the >>We need that OnPrem. Yeah, >>Well I think the, the bring your fuel sober, what we agree is that cloud is the place where innovation happens. Okay? At some point innovation becomes legacy debt and you have thus hybrid, you are not going to keep your old applications up to date forever. The, the, the math just doesn't add up. And where I differ in opinion is that not everyone needs innovation to keep moving. They need innovation for a period of time and then they need steady state. So Sergeant, we >>Argue about this. I have a, I >>Love this debate though. I say it's efficiency and stability also plays an important role. I see exactly what you're talking about. No, it's >>Great. I have a counter to that. Let me tell you >>Why. Let's >>Hear it. Because if you look at the storage only, right? Just storage. Just take storage computer network for, for a minute. There three cost reps in, in infrastructure, right? So storage earlier, early on there was one tier of storage. You say pay the same price, then now there are like five storage tiers, right? What I'm trying to say is the market sets the price, the market will tell you where this whole thing will go, but I know their margins are high in cloud, 20 plus percent and margin will shrink as, as we go forward. That means the, the cloud will become cheaper relative to on-prem. It, it, in some cases it's already cheaper. But even if it's a stable workload, even in that case, we will have a lower tier of service. I mean, you, you can't argue with me that the cloud versus your data center, they are on the same tier of services. Like cloud is a better, you know, product than your data center. Hands off. >>I love it. We, we are gonna relish in the debates between the two of you. Mic drops. The energy is great. I love it. Perspective. It's not like any of us can quite see through the crystal ball that we have very informed opinions, which is super exciting. Yeah. Lisa, any last thoughts today? >>Just love, I love the debate as well. That, and that's, that's part of what being in this community is all about. So sharing about, sharing opinions, expressing opinions. That's how it grows. That's how, that's how we innovate. Yeah. Obviously we need the cloud, but that's how we innovate. That's how we grow. Yeah. And we've seen that demonstrated the last couple days and I and your, your takes here on the Cuban on Twitter. Brilliant. >>Thank you. I absolutely love it. I'm gonna close this out with a really important analysis on the swag of the show. Yes. And if you know, yesterday we were looking at what is the weirdest swag or most unique swag We had that bucket hat that took the grand prize. Today we're gonna focus on something that's actually quite cool. A lot of the vendors here have really dedicated their swag to being local to Detroit. Very specific in their sourcing. Sonotype here has COOs. They're beautiful. You can't quite feel this flannel, but it's very legit hand sound here in Michigan. I can't say that I've been to too many conferences, if any, where there was this kind of commitment to localizing and sourcing swag from around the corner. We also see this with the Intel booth. They've got screen printers out here doing custom hoodies on spot. >>Oh fun. They're even like appropriately sized. They had local artists do these designs and if you're like me and you care about what's on your wrist, you're familiar with Shinola. This is one of my favorite swags that's available. There is a contest. Oh going on. Hello here. Yeah, so if you are Atan, make sure that you go and check this out. The we, I talked about this on the show. We've had the founder on the show or the CEO and yeah, I mean Shine is just full of class as since we are in Detroit as well. One of the fun themes is cars. >>Yes. >>And Storm Forge, who are also on the show, is actually giving away an Aston Martin, which is very exciting. Not exactly manufactured in Detroit. However, still very cool on the car front and >>The double oh seven version named the best I >>Know in the sixties. It's love it. It's very cool. Two quick last things. We talk about it a lot on the show. Every company now wants to be a software company. Yep. On that vein, and keeping up with my hat theme, the Home Depot is here because they want everybody to know that they in fact are a technology company, which is very cool. They have over 500,000 employees. You can imagine there's a lot of technology that has to go into keeping Napa. Absolutely. Yep. Wild to think about. And then last, but not at least very quick, rapid fire, best t-shirt contest. If you've ever ran to one of these events, there are a ton of T-shirts out there. I rate them on two things. Wittiest line and softness. If you combine the two, you'll really be our grand champion for the year. I'm just gonna hold these up and set them down for your laughs. Not afraid to commit, which is pretty great. This is another one designed by locals here. Detroit Code City. Oh, love it. This one made me chuckle the most. Kiss my cash. >>Oh, that's >>Good. These are also really nice and soft, which is fantastic. Also high on the softness category is this Op Sarah one. I also like their bird logo. These guys, there's just, you know, just real nice touch. So unfortunately, if you have the fumble, you're not here with us, live in Detroit. At least you're gonna get taste of the swag. I taste of the stories and some smiles hear from those of us on the cube. Thank you both so much for being here with us. Lisa, thanks for another fabulous day. Got it, girl. My name's Savannah Peterson. Thank you for joining us from Detroit. We're the cube and we can't wait to see you tomorrow.

>> Announcer: "theCUBE" presents "Kubecon and Cloudnativecon Europe, 2022" brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain and "Kubecon + Cloudnativecon Europe, 2022." I'm Keith Townsend, and we're continuing the conversations with amazing people doing amazing things. I think we've moved beyond a certain phase of the hype cycle when it comes to Kubernetes. And we're going to go a little bit in detail with that today, and on all the sessions, I have today with me, Taylor Dolezal. New head of CNCF Ecosystem. So, first off, what does that mean new head of? You're the head of CNCF Ecosystem? What is the CNCF Ecosystem? >> Yeah. Yeah. It's really the end user ecosystem. So, the CNCF is comprised of really three pillars. And there's the governing board, they oversee the budget and fun things, make sure everything's signed and proper. Then there's the Technical Oversight Committee, TOC. And they really help decide the technical direction of the organization through deliberation and talking about which projects get invited and accepted. Projects get donated, and the TOC votes on who's going to make it in, based on all this criteria. And then, lastly, is the end user ecosystem, that encompasses a whole bunch of different working groups, special interest groups. And that's been really interesting to kind of get a deeper sense into, as of late. So, there are groups like the developer experience group, and the user research group. And those have very specific focuses that kind of go across all industries. But what we've seen lately, is that there are really deep wants to create, whether it be financial services user group, and things like that, because end users are having trouble with going to all of the different meetings. If you're a company, a vendor member company that's selling authentication software, or something in networking, makes sense to have a SIG network, SIG off, and those kinds of things. But when it comes down to like Boeing that just joined, does that make sense for them to jump into all those meetings? Or does it make sense to have some other kind of thing that is representative of them, so that they can attend that one thing, it's specific to their industry? They can get that download and kind of come up to speed, or find the best practices as quickly as possible in a nice synthesized way. >> So, you're 10 weeks into this role. You're coming from a customer environment. So, talk to me a little bit about the customer side of it? When you're looking at something, it's odd to call CNCF massive. But it is, 7.1 million members, and the number of contributing projects, et cetera. Talk to me about the view from the outside versus the view now that you're inside? >> Yeah, so honestly, it's been fun to kind of... For me, it's really mirrored the open-source journey. I've gone to Kubecon before, gotten to enjoy all of the booths, and trying to understand what's going on, and then worked for HashiCorp before coming to the CNCF. And so, get that vendor member kind of experience working the booth itself. So, kind of getting deeper and deeper into the stack of the conference itself. And I keep saying, vendor member and end user members, the difference between those, is end users are not organizations that sell cloud native services. Those are the groups that are kind of more consuming, the Airbnbs, the Boeings, the Mercedes, these people that use these technologies and want to kind of give that feedback back to these projects. But yeah, very incredibly massive and just sprawling when it comes to working in all those contexts. >> So, I have so many questions around, like the differences between having you as an end user and in inter-operating with vendors and the CNCF itself. So, let's start from the end user lens. When you're an end user and you're out discovering open-source and cloud native products, what's that journey like? How do you go from saying, okay, I'm primarily focused on vendor solutions, to let me look at this cloud native stack? >> Yeah, so really with that, there's been, I think that a lot of people have started to work with me and ask for, "Can we have recommended architectures? Can we have blueprints for how to do these things?" When the CNCF doesn't want to take that position, we don't want to kind of be the king maker and be like, this is the only way forward. We want to be inclusive, we want to pull in these projects, and kind of give everyone the same boot strap and jump... I missing the word of it, just ability to kind of like springboard off of that. Create a nice base for everybody to get started with, and then, see what works out, learn from one another. I think that when it comes to Kubernetes, and Prometheus, and some other projects, being able to share best practices between those groups of what works best as well. So, within all of the separations of the CNCF, I think that's something I've found really fun, is kind of like seeing how the projects relate to those verticals and those groups as well. Is how you run a project, might actually have a really good play inside of an organization like, "I like that idea. Let's try that out with our team." >> So, like this idea of springboarding. You know, is when an entrepreneur says, "You know what? I'm going to quit my job and springboard off into doing something new." There's a lot of uncertainty, but for enterprise, that can be really scary. Like we're used to our big vendors, HashiCorp, VMware, Cisco kind of guiding us and telling us like, what's next? What is that experience like, springboarding off into something as massive as cloud native? >> So, I think it's really, it's a great question. So, I think that's why the CNCF works so well, is the fact that it's a safe place for all these companies to come together, even companies of competing products. you know, having that common vision of, we want to make production boring again, we don't want to have so much sprawl and have to take in so much knowledge at once. Can we kind of work together to create all these things to get rid of our adminis trivia or maintenance tasks? I think that when it comes to open-source in general, there's a fantastic book it's called "Working in Public," it's by Stripe Press. I recommend it all over the place. It's orange, so you'll recognize it. Yeah, it's easy to see. But it's really good 'cause it talks about the maintainer journey, and what things make it difficult. And so, I think that that's what the CNCF is really working hard to try to get rid of, is all this monotonous, all these monotonous things, filing issues, best practices. How do you adopt open-source within your organization? We have tips and tricks, and kind of playbooks in ways that you could accomplish that. So, that's what I find really useful for those kinds of situations. Then it becomes easier to adopt that within your organization. >> So, I asked Priyanka, CNCF executive director last night, a pretty tough question. And this is kind of in the meat of what you do. What happens when you? Let's pick on service mesh 'cause everyone likes to pick on service mesh. >> XXXX: Yeah. >> What happens when there's differences at that vendor level on the direction of a CIG or a project, or the ecosystem around service mesh? >> Yeah, so that's the fun part. Honestly, is 'cause people get to hash it out. And so, I think that's been the biggest thing for me finding out, was that there's more than one way to do thing. And so, I think it always comes down to use case. What are you trying to do? And then you get to solve after that. So, it really is, I know it depends, which is the worst answer. But I really do think that's the case, because if you have people that are using something within the automotive space, or in the financial services space, they're going to have completely different needs, wants, you know, some might need to run Coball or Fortran, others might not have to. So, even at that level, just down to what your tech stack looks like, audits, and those kinds of things, that can just really differ. So, I think it does come down to something more like that. >> So, the CNCF loosely has become kind of a standards body. And it's centered around the core project Kubernetes? >> Mm-hmm. >> So, what does it mean, when we're looking at larger segments such as service mesh or observability, et cetera, to be Kubernetes compliant? Where's the point, if any, that the CNCF steps in versus just letting everyone hash it out? Is it Kubernetes just need to be Kubernetes compliant and everything else is free for all? >> Honestly, in many cases, it's up to the communities themselves to decide that. So, the groups that are running OCI, the Open Container Interface, Open Storage Interface, all of those things that we've agreed on as ways to implement those technologies, I think that's where the CNCF, that's the line. That's where the CNCF gets up to. And then, it's like we help foster those communities and those conversations and asking, does this work for you? If not, let's talk about it, let's figure out why it might not. And then, really working closely with community to kind of help bring those things forward and create action items. >> So, it's all about putting the right people in the rooms and not necessarily playing referee, but to get people in the right room to have and facilitate the conversation? >> Absolutely. Absolutely. Like all of the booths behind us could have their own conferences, but we want to bring everybody together to have those conversations. And again, sprawling can be really wild at certain times, but it's good to have those cross understandings, or to hear from somebody that you're like, "Oh, my goodness, I didn't even think about that kind of context or use case." So, really inclusive conversation. >> So, organizations like Boeing, Adobe, Microsoft, from an end user perspective, it's sometimes difficult to get those organizations into these types of communities. How do you encourage them to participate in the conversation 'cause their voice is extremely important? >> Yeah, that I'd also say it really is the community. I really liked the Kubernetes documentary that was put out, working with some of the CNCF folks and core, and beginning Kubernetes contributors and maintainers. And it just kind of blew me away when they had said, you know, what we thought was success, was seeing Kubernetes in an Amazon Data Center. That's when we knew that this was going to take root. And you'd rarely hear that, is like, "When somebody that we typically compete with, its success is seeing it, seeing them use that." And so, I thought was really cool. >> You know, I like to use this technology for my community of skipping rope. You see the girls and boys jumping double Dutch rope. And you think, "I can do that. Like it's just jumping." But there's this hesitation to actually, how do you start? How do you get inside of it? The question is how do you become a member of the community? We've talked a lot about what happens when you're in the community. But how do you join the community? >> So, really, there's a whole bunch of ways that you can. Actually, the shirt that I'm wearing, I got from the 114 Release. So, this is just a fun example of that community. And just kind of how welcoming and inviting that they are. Really, I do think it's kind of like a job breaker. Almost you start at the outside, you start using these technologies, even more generally like, what is DevOps? What is production? How do I get to infrastructure, architecture, or software engineering? Once you start there, you start working your way in, you develop a stack, and then you start to see these tools, technologies, workflows. And then, after you've kind of gotten a good amount of time spent with it, you might really enjoy it like that, and then want to help contribute like, "I like this, but it would be great to have a function that did this. Or I want a feature that does that." At that point in time, you can either take a look at the source code on GitHub, or wherever it's hosted, and then start to kind of come up with that, some ideas to contribute back to that. And then, beyond that, you can actually say, "No, I kind of want to have these conversations with people." Join in those special interest groups, and those meetings to kind of talk about things. And then, after a while, you can kind of find yourself in a contributor role, and then a maintainer role. After that, if you really like the project, and want to kind of work with community on that front. So, I think you had asked before, like Microsoft, Adobe and these others. Really it's about steering the projects. It's these communities want these things, and then, these companies say, "Okay, this is great. Let's join in the conversation with the community." And together again, inclusivity, and bringing everybody to the table to have that discussion and push things forward. >> So, Taylor, closing message. What would you want people watching this show to get when they think about ecosystem and CNCF? >> So, ecosystem it's a big place, come on in. Yeah, (laughs) the water's just fine. I really want people to take away the fact that... I think really when it comes down to, it really is the community, it's you. We are the end user ecosystem. We're the people that build the tools, and we need help. No matter how big or small, when you come in and join the community, you don't have to rewrite the Kubernetes scheduler. You can help make documentation that much more easy to understand, and in doing so, helping thousands of people, If I'm going through the instructions or reading a paragraph, doesn't make sense, that has such a profound impact. And I think a lot of people miss that. It's like, even just changing punctuation can have such a giant difference. >> Yeah, I think people sometimes forget that community, especially community-run projects, they need product managers. They need people that will help with communications, people that will help with messaging, websites updating. Just reachability, anywhere from developing code to developing documentation, there's ways to jump in and help the community. From Valencia, Spain, I'm Keith Townsend, and you're watching "theCUBE," the leader in high tech coverage. (bright upbeat music)

>>Time series data is any data that's stamped in time in some way that could be every second, every minute, every five minutes, every hour, every nanosecond, whatever it might be. And typically that data comes from sources in the physical world like devices or sensors, temperature, gauges, batteries, any device really, or things in the virtual world could be software, maybe it's software in the cloud or data and containers or microservices or virtual machines. So all of these items, whether in the physical or virtual world, they're generating a lot of time series data. Now time series data has been around for a long time, and there are many examples in our everyday lives. All you gotta do is punch up any stock, ticker and look at its price over time and graphical form. And that's a simple use case that anyone can relate to and you can build timestamps into a traditional relational database. >>You just add a column to capture time and as well, there are examples of log data being dumped into a data store that can be searched and captured and ingested and visualized. Now, the problem with the latter example that I just gave you is that you gotta hunt and Peck and search and extract what you're looking for. And the problem with the former is that traditional general purpose databases they're designed as sort of a Swiss army knife for any workload. And there are a lot of functions that get in the way and make them inefficient for time series analysis, especially at scale. Like when you think about O T and edge scale, where things are happening super fast, ingestion is coming from many different sources and analysis often needs to be done in real time or near real time. And that's where time series databases come in. >>They're purpose built and can much more efficiently support ingesting metrics at scale, and then comparing data points over time, time series databases can write and read at significantly higher speeds and deal with far more data than traditional database methods. And they're more cost effective instead of throwing processing power at the problem. For example, the underlying architecture and algorithms of time series databases can optimize queries and they can reclaim wasted storage space and reuse it. At scale time, series databases are simply a better fit for the job. Welcome to moving the world with influx DB made possible by influx data. My name is Dave Valante and I'll be your host today. Influx data is the company behind InfluxDB. The open source time series database InfluxDB is designed specifically to handle time series data. As I just explained, we have an exciting program for you today, and we're gonna showcase some really interesting use cases. >>First, we'll kick it off in our Palo Alto studios where my colleague, John furrier will interview Evan Kaplan. Who's the CEO of influx data after John and Evan set the table. John's gonna sit down with Brian Gilmore. He's the director of IOT and emerging tech at influx data. And they're gonna dig into where influx data is gaining traction and why adoption is occurring and, and why it's so robust. And they're gonna have tons of examples and double click into the technology. And then we bring it back here to our east coast studios, where I get to talk to two practitioners, doing amazing things in space with satellites and modern telescopes. These use cases will blow your mind. You don't want to miss it. So thanks for being here today. And with that, let's get started. Take it away. Palo Alto. >>Okay. Today we welcome Evan Kaplan, CEO of influx data, the company behind influx DB. Welcome Evan. Thanks for coming on. >>Hey John, thanks for having me >>Great segment here on the influx DB story. What is the story? Take us through the history. Why time series? What's the story >><laugh> so the history history is actually actually pretty interesting. Um, Paul dicks, my partner in this and our founder, um, super passionate about developers and developer experience. And, um, he had worked on wall street building a number of time series kind of platform trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave, which means you had to do a ton of work just to start doing work, which means you had to write a bunch of extrinsic routines. You had to write a bunch of application handling on existing relational databases in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view is this is not how developers should work. And so in 2013, he went through why Combinator and he built something for, he made his first commit to open source in flu DB at the end of 2013. And, and he basically, you know, from my point of view, he invented modern time series, which is you start with a purpose-built time series platform to do these kind of workloads. And you get all the benefits of having something right outta the box. So a developer can be totally productive right away. >>And how many people in the company what's the history of employees and stuff? >>Yeah, I think we're, I, you know, I always forget the number, but it's something like 230 or 240 people now. Um, the company, I joined the company in 2016 and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. Cuz if you think about it, what sensors do is they speak time, series, pressure, temperature, volume, humidity, light, they're measuring they're instrumenting something over time. And so I thought that would be super relevant over long term and I've not regretted it. >>Oh no. And it's interesting at that time, go back in the history, you know, the role of databases, well, relational database is the one database to rule the world. And then as clouds started coming in, you starting to see more databases, proliferate types of databases and time series in particular is interesting. Cuz real time has become super valuable from an application standpoint, O T which speaks time series means something it's like time matters >>Time. >>Yeah. And sometimes data's not worth it after the time, sometimes it worth it. And then you get the data lake. So you have this whole new evolution. Is this the momentum? What's the momentum, I guess the question is what's the momentum behind >>You mean what's causing us to grow. So >>Yeah, the time series, why is time series >>And the >>Category momentum? What's the bottom line? >>Well, think about it. You think about it from a broad, broad sort of frame, which is where, what everybody's trying to do is build increasingly intelligent systems, whether it's a self-driving car or a robotic system that does what you want to do or a self-healing software system, everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well, and you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened what's gonna happen? And so you get to these applications like predictive maintenance or smarter systems. And increasingly you want to do that stuff, not just intelligently, but fast in real time. So millisecond response so that when you're driving a self-driving car and the system realizes that you're about to do something, essentially you wanna be able to act in something that looks like real time, all systems want to do that, want to be more intelligent and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a >>Market. It's interesting near real time. Isn't good enough when you need real time. >><laugh> yeah, it's not, it's not. And it's like, and it's like, everybody wants, even when you don't need it, ironically, you want it. It's like having the feature for, you know, you buy a new television, you want that one feature, even though you're not gonna use it, you decide that your buying criteria real time is a buying criteria >>For, so you, I mean, what you're saying then is near real time is getting closer to real time as possible, as fast as possible. Right. Okay. So talk about the aspect of data, cuz we're hearing a lot of conversations on the cube in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get, know how to fix it. So this is a big part of how we're seeing with people saying, Hey, you know, I wanna make my machine learning algorithms better after the fact I wanna learn from the data. Um, how does that, how do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data knowing when it happened? >>Well, for sure. So, so for sure, what you're saying is, is, is none of this is non-linear, it's all incremental. And so if you take something, you know, just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop, which is I instrumented, I watch what happens, oh, that's wrong? Oh, I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car, but every system moves along that evolution. And so you get the dynamic of, you know, of constantly instrumenting watching the system behave and do it. And this and sets up driving car is one thing. But even in the human genome, if you look at some of our customers, you know, people like, you know, people doing solar arrays, people doing power walls, like all of these systems are getting smarter. >>Well, let's get into that. What are the top applications? What are you seeing for your, with in, with influx DB, the time series, what's the sweet spot for the application use case and some customers give some >>Examples. Yeah. So it's, it's pretty easy to understand on one side of the equation that's the physical side is sensors are sensors are getting cheap. Obviously we know that and they're getting the whole physical world is getting instrumented, your home, your car, the factory floor, your wrist, watch your healthcare, you name it. It's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but, but they're all on that side. They're all about IOT. So they're think about consumer IOT projects like Google's nest todo, um, particle sensors, um, even delivery engines like rapid who deliver the Instacart of south America, like anywhere there's a physical location do and that's on the consumer side. And then another exciting space is the industrial side factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational because what, what has to get smarter when you're building, when you're building a factory is systems all have to get smarter. And then, um, lastly, a lot in the renewables sustainability. So a lot, you know, Tesla, lucid, motors, Cola, motors, um, you know, lots to do with electric cars, solar arrays, windmills, arrays, just anything that's gonna get instrumented that where that instrumentation becomes part of what the purpose >>Is. It's interesting. The convergence of physical and digital is happening with the data IOT. You mentioned, you know, you think of IOT, look at the use cases there, it was proprietary OT systems. Now becoming more IP enabled internet protocol and now edge compute, getting smaller, faster, cheaper AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? What was the, what's the IOT where's the IOT dots connecting to because you know, as these two cultures merge yeah. Operations, basically industrial factory car, they gotta get smarter, intelligent edge is a buzzword, but I mean, it has to be more intelligent. Where's the, where's the action in all this. So the >>Action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the actions really happen at the developer. And so what you're seeing is a movement in the world that, that maybe you and I grew up in with it or OT moving increasingly that developer driven capability. And so all of these IOT systems they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business. What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express theself or am I trying to figure out when the next heart rate monitor's gonna show up on my apple watch, right? What am I trying to do? What's the system I need to build. And so starting with the developers where all of the good stuff happens here, which is different than it used to be, right. Used to be you'd buy an application or a service or a SA thing for, but with this dynamic, with this integration of systems, it's all about bespoke. It's all about building >>Something. So let's get to the developer real quick, real highlight point here is the data. I mean, I could see a developer saying, okay, I need to have an application for the edge IOT edge or car. I mean, we're gonna have, I mean, Tesla's got applications of the car it's right there. I mean, yes, there's the modern application life cycle now. So take us through how this impacts the developer. Does it impact their C I C D pipeline? Is it cloud native? I mean, where does this all, where does this go to? >>Well, so first of all, you're talking about, there was an internal journey that we had to go through as a company, which, which I think is fascinating for anybody who's interested is we went from primarily a monolithic software that was open sourced to building a cloud native platform, which means we had to move from an agile development environment to a C I C D environment. So to a degree that you are moving your service, whether it's, you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right. To degree that that service is cloud. Then increasingly remove from an agile development to a C I C D environment, which you're shipping code to production every day. And so it's not just the developers, all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also gonna happen in a big way >>When your customer base that you have now, and as you see, evolving with infl DB, is it that they're gonna be writing more of the application or relying more on others? I mean, obviously there's an open source component here. So when you bring in kind of old way, new way old way was I got a proprietary, a platform running all this O T stuff and I gotta write, here's an application. That's general purpose. Yeah. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does its job >>A good way to think about this is versus a new way >>Is >>What so yeah, good way to think about this is what, what's the role of the developer slash architect CTO that chain within a large, within an enterprise or a company. And so, um, the way to think about it is I started my career in the aerospace industry <laugh> and so when you look at what Boeing does to assemble a plane, they build very, very few of the parts. Instead, what they do is they assemble, they buy the wings, they buy the engines, they assemble, actually, they don't buy the wings. It's the one thing they buy the, the material for the w they build the wings, cuz there's a lot of tech in the wings and they end up being assemblers smart assemblers of what ends up being a flying airplane, which is pretty big deal even now. And so what, what happens with software people is they have the ability to pull from, you know, the best of the open source world. So they would pull a time series capability from us. Then they would assemble that with, with potentially some ETL logic from somebody else, or they'd assemble it with, um, a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers, but they become masters of that bespoke application. And I think that's where it goes, cuz you're not writing native code for everything. >>So they're more flexible. They have faster time to market cuz they're assembling way faster and they get to still maintain their core competency. Okay. Their wings in this case, >>They become increasingly not just coders, but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff by the way, this is not different than the people just up the road Google have been doing for years or the tier one, Amazon building all their own. >>Well, I think one of the things that's interesting is is that this idea of a systems developing a system architecture, I mean systems, uh, uh, systems have consequences when you make changes. So when you have now cloud data center on premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >>That's exactly. But that's where the that's where the, you know, that that Boeing or that airplane building analogy comes in for us. We've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on pre edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that you wanna make sure, at least that base layer, that database layer, that those components talk to each other. >>So I'll have to ask you if I'm the customer. I put my customer hat on. Okay. Hey, I'm dealing with a lot. >>That mean you have a PO for <laugh> >>A big check. I blank check. If you can answer this question only if the tech, if, if you get the question right, I got all this important operation stuff. I got my factory, I got my self-driving cars. This isn't like trivial stuff. This is my business. How should I be thinking about time series? Because now I have to make these architectural decisions, as you mentioned, and it's gonna impact my application development. So huge decision point for your customers. What should I care about the most? So what's in it for me. Why is time series >>Important? Yeah, that's a great question. So chances are, if you've got a business that was, you know, 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that you built something on a Oracle or you built something on IBM's DB two, right. And you made it work within your system. Right? And so that's what you started building. So it's already out there. There are, you know, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time. I hate the word, but digital transformation. Then you start with time series. It's a foundational base layer for any system that you're gonna build. There's no system I can think of where time series, shouldn't be the foundational base layer. If you just wanna store your data and just leave it there and then maybe look it up every five years. That's fine. That's not time. Series time series is when you're building a smarter, more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems, the more obvious it becomes. >>And since I have a PO for you and a big check, yeah. What is, what's the value to me as I, when I implement this, what's the end state, what's it look like when it's up and running? What's the value proposition for me. What's an >>So, so when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, they're transforming it in near real time. So that the other dependencies that a system that gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's, you know, it's not like it's doing every action that's above, but it's foundational to build a really compelling, intelligent system. I think that's what developers and archs are seeing now. >>Bottom line, final word. What's in it for the customer. What's what, what's your, um, what's your statement to the customer? What would you say to someone looking to do something in time series on edge? >>Yeah. So, so it's pretty clear to clear to us that if you're building, if you view yourself as being in the build business of building systems that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time that you start from time series. But I also wanna say what's in it for us influx what's in it for us is people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare it's hard not to be proud or feel like, wow. Yeah. Somehow I've been lucky. I've arrived at the right time, in the right place with the right people to be able to deliver on that. That's that's also exciting on our side of the equation. >>Yeah. It's critical infrastructure, critical, critical operations. >>Yeah. >>Yeah. Great stuff, Evan. Thanks for coming on. Appreciate this segment. All right. In a moment, Brian Gilmore director of IOT and emerging technology that influx day will join me. You're watching the cube leader in tech coverage. Thanks for watching >>Time series data from sensors systems and applications is a key source in driving automation and prediction in technologies around the world. But managing the massive amount of timestamp data generated these days is overwhelming, especially at scale. That's why influx data developed influx DB, a time series data platform that collects stores and analyzes data influx DB empowers developers to extract valuable insights and turn them into action by building transformative IOT analytics and cloud native applications, purpose built and optimized to handle the scale and velocity of timestamped data. InfluxDB puts the power in your hands with developer tools that make it easy to get started quickly with less code InfluxDB is more than a database. It's a robust developer platform with integrated tooling. That's written in the languages you love. So you can innovate faster, run in flex DB anywhere you want by choosing the provider and region that best fits your needs across AWS, Microsoft Azure and Google cloud flex DB is fast and automatically scalable. So you can spend time delivering value to customers, not managing clusters, take control of your time series data. So you can focus on the features and functionalities that give your applications a competitive edge. Get started for free with influx DB, visit influx data.com/cloud to learn more. >>Okay. Now we're joined by Brian Gilmore director of IOT and emerging technologies at influx data. Welcome to the show. >>Thank you, John. Great to be here. >>We just spent some time with Evan going through the company and the value proposition, um, with influx DV, what's the momentum, where do you see this coming from? What's the value coming out of this? >>Well, I think it, we're sort of hitting a point where the technology is, is like the adoption of it is becoming mainstream. We're seeing it in all sorts of organizations, everybody from like the most well funded sort of advanced big technology companies to the smaller academics, the startups and the managing of that sort of data that emits from that technology is time series and us being able to give them a, a platform, a tool that's super easy to use, easy to start. And then of course will grow with them is, is been key to us. Sort of, you know, riding along with them is they're successful. >>Evan was mentioning that time series has been on everyone's radar and that's in the OT business for years. Now, you go back since 20 13, 14, even like five years ago that convergence of physical and digital coming together, IP enabled edge. Yeah. Edge has always been kind of hyped up, but why now? Why, why is the edge so hot right now from an adoption standpoint? Is it because it's just evolution, the tech getting better? >>I think it's, it's, it's twofold. I think that, you know, there was, I would think for some people, everybody was so focused on cloud over the last probably 10 years. Mm-hmm <affirmative> that they forgot about the compute that was available at the edge. And I think, you know, those, especially in the OT and on the factory floor who weren't able to take Avan full advantage of cloud through their applications, you know, still needed to be able to leverage that compute at the edge. I think the big thing that we're seeing now, which is interesting is, is that there's like a hybrid nature to all of these applications where there's definitely some data that's generated on the edge. There's definitely done some data that's generated in the cloud. And it's the ability for a developer to sort of like tie those two systems together and work with that data in a very unified uniform way. Um, that's giving them the opportunity to build solutions that, you know, really deliver value to whatever it is they're trying to do, whether it's, you know, the, the out reaches of outer space or whether it's optimizing the factory floor. >>Yeah. I think, I think one of the things you also mentions genome too, dig big data is coming to the real world. And I think I, OT has been kind of like this thing for OT and, and in some use case, but now with the, with the cloud, all companies have an edge strategy now. So yeah, what's the secret sauce because now this is hot, hot product for the whole world and not just industrial, but all businesses. What's the secret sauce. >>Well, I mean, I think part of it is just that the technology is becoming more capable and that's especially on the hardware side, right? I mean, like technology compute is getting smaller and smaller and smaller. And we find that by supporting all the way down to the edge, even to the micro controller layer with our, um, you know, our client libraries and then working hard to make our applications, especially the database as small as possible so that it can be located as close to sort of the point of origin of that data in the edge as possible is, is, is fantastic. Now you can take that. You can run that locally. You can do your local decision making. You can use influx DB as sort of an input to automation control the autonomy that people are trying to drive at the edge. But when you link it up with everything that's in the cloud, that's when you get all of the sort of cloud scale capabilities of parallelized, AI and machine learning and all of that. >>So what's interesting is the open source success has been something that we've talked about a lot in the cube about how people are leveraging that you guys have users in the enterprise users that IOT market mm-hmm <affirmative>, but you got developers now. Yeah. Kind of together brought that up. How do you see that emerging? How do developers engage? What are some of the things you're seeing that developers are really getting into with InfluxDB >>What's? Yeah. Well, I mean, I think there are the developers who are building companies, right? And these are the startups and the folks that we love to work with who are building new, you know, new services, new products, things like that. And, you know, especially on the consumer side of IOT, there's a lot of that, just those developers. But I think we, you gotta pay attention to those enterprise developers as well, right? There are tons of people with the, the title of engineer in, in your regular enterprise organizations. And they're there for systems integration. They're there for, you know, looking at what they would build versus what they would buy. And a lot of them come from, you know, a strong, open source background and they, they know the communities, they know the top platforms in those spaces and, and, you know, they're excited to be able to adopt and use, you know, to optimize inside the business as compared to just building a brand new one. >>You know, it's interesting too, when Evan and I were talking about open source versus closed OT systems, mm-hmm <affirmative> so how do you support the backwards compatibility of older systems while maintaining open dozens of data formats out there? Bunch of standards, protocols, new things are emerging. Everyone wants to have a control plane. Everyone wants to leverage the value of data. How do you guys keep track of it all? What do you guys support? >>Yeah, well, I mean, I think either through direct connection, like we have a product called Telegraph, it's unbelievable. It's open source, it's an edge agent. You can run it as close to the edge as you'd like, it speaks dozens of different protocols in its own, right? A couple of which MQTT B, C U a are very, very, um, applicable to these T use cases. But then we also, because we are sort of not only open source, but open in terms of our ability to collect data, we have a lot of partners who have built really great integrations from their own middleware, into influx DB. These are companies like ke wear and high bite who are really experts in those downstream industrial protocols. I mean, that's a business, not everybody wants to be in. It requires some very specialized, very hard work and a lot of support, um, you know, and so by making those connections and building those ecosystems, we get the best of both worlds. The customers can use the platforms they need up to the point where they would be putting into our database. >>What's some of customer testimonies that they, that share with you. Can you share some anecdotal kind of like, wow, that's the best thing I've ever used. This really changed my business, or this is a great tech that's helped me in these other areas. What are some of the, um, soundbites you hear from customers when they're successful? >>Yeah. I mean, I think it ranges. You've got customers who are, you know, just finally being able to do the monitoring of assets, you know, sort of at the edge in the field, we have a customer who's who's has these tunnel boring machines that go deep into the earth to like drill tunnels for, for, you know, cars and, and, you know, trains and things like that. You know, they are just excited to be able to stick a database onto those tunnel, boring machines, send them into the depths of the earth and know that when they come out, all of that telemetry at a very high frequency has been like safely stored. And then it can just very quickly and instantly connect up to their, you know, centralized database. So like just having that visibility is brand new to them. And that's super important. On the other hand, we have customers who are way far beyond the monitoring use case, where they're actually using the historical records in the time series database to, um, like I think Evan mentioned like forecast things. So for predictive maintenance, being able to pull in the telemetry from the machines, but then also all of that external enrichment data, the metadata, the temperatures, the pressure is who is operating the machine, those types of things, and being able to easily integrate with platforms like Jupyter notebooks or, you know, all of those scientific computing and machine learning libraries to be able to build the models, train the models, and then they can send that information back down to InfluxDB to apply it and detect those anomalies, which >>Are, I think that's gonna be an, an area. I personally think that's a hot area because I think if you look at AI right now, yeah. It's all about training the machine learning albums after the fact. So time series becomes hugely important. Yeah. Cause now you're thinking, okay, the data matters post time. Yeah. First time. And then it gets updated the new time. Yeah. So it's like constant data cleansing data iteration, data programming. We're starting to see this new use case emerge in the data field. >>Yep. Yeah. I mean, I think you agree. Yeah, of course. Yeah. The, the ability to sort of handle those pipelines of data smartly, um, intelligently, and then to be able to do all of the things you need to do with that data in stream, um, before it hits your sort of central repository. And, and we make that really easy for customers like Telegraph, not only does it have sort of the inputs to connect up to all of those protocols and the ability to capture and connect up to the, to the partner data. But also it has a whole bunch of capabilities around being able to process that data, enrich it, reform at it, route it, do whatever you need. So at that point you're basically able to, you're playing your data in exactly the way you would wanna do it. You're routing it to different, you know, destinations and, and it's, it's, it's not something that really has been in the realm of possibility until this point. Yeah. Yeah. >>And when Evan was on it's great. He was a CEO. So he sees the big picture with customers. He was, he kinda put the package together that said, Hey, we got a system. We got customers, people are wanting to leverage our product. What's your PO they're sell. He's selling too as well. So you have that whole CEO perspective, but he brought up this notion that there's multiple personas involved in kind of the influx DB system architect. You got developers and users. Can you talk about that? Reality as customers start to commercialize and operationalize this from a commercial standpoint, you got a relationship to the cloud. Yep. The edge is there. Yep. The edge is getting super important, but cloud brings a lot of scale to the table. So what is the relationship to the cloud? Can you share your thoughts on edge and its relationship to the cloud? >>Yeah. I mean, I think edge, you know, edges, you can think of it really as like the local information, right? So it's, it's generally like compartmentalized to a point of like, you know, a single asset or a single factory align, whatever. Um, but what people do who wanna pro they wanna be able to make the decisions there at the edge locally, um, quickly minus the latency of sort of taking that large volume of data, shipping it to the cloud and doing something with it there. So we allow them to do exactly that. Then what they can do is they can actually downsample that data or they can, you know, detect like the really important metrics or the anomalies. And then they can ship that to a central database in the cloud where they can do all sorts of really interesting things with it. Like you can get that centralized view of all of your global assets. You can start to compare asset to asset, and then you can do those things like we talked about, whereas you can do predictive types of analytics or, you know, larger scale anomaly detections. >>So in this model you have a lot of commercial operations, industrial equipment. Yep. The physical plant, physical business with virtual data cloud all coming together. What's the future for InfluxDB from a tech standpoint. Cause you got open. Yep. There's an ecosystem there. Yep. You have customers who want operational reliability for sure. I mean, so you got organic <laugh> >>Yeah. Yeah. I mean, I think, you know, again, we got iPhones when everybody's waiting for flying cars. Right. So I don't know. We can like absolutely perfectly predict what's coming, but I think there are some givens and I think those givens are gonna be that the world is only gonna become more hybrid. Right. And then, you know, so we are going to have much more widely distributed, you know, situations where you have data being generated in the cloud, you have data gen being generated at the edge and then there's gonna be data generated sort sort of at all points in between like physical locations as well as things that are, that are very virtual. And I think, you know, we are, we're building some technology right now. That's going to allow, um, the concept of a database to be much more fluid and flexible, sort of more aligned with what a file would be like. >>And so being able to move data to the compute for analysis or move the compute to the data for analysis, those are the types of, of solutions that we'll be bringing to the customers sort of over the next little bit. Um, but I also think we have to start thinking about like what happens when the edge is actually off the planet. Right. I mean, we've got customers, you're gonna talk to two of them, uh, in the panel who are actually working with data that comes from like outside the earth, like, you know, either in low earth orbit or you know, all the way sort of on the other side of the universe. Yeah. And, and to be able to process data like that and to do so in a way it's it's we gotta, we gotta build the fundamentals for that right now on the factory floor and in the mines and in the tunnels. Um, so that we'll be ready for that one. >>I think you bring up a good point there because one of the things that's common in the industry right now, people are talking about, this is kind of new thinking is hyper scale's always been built up full stack developers, even the old OT world, Evan was pointing out that they built everything right. And the world's going to more assembly with core competency and IP and also property being the core of their apple. So faster assembly and building, but also integration. You got all this new stuff happening. Yeah. And that's to separate out the data complexity from the app. Yes. So space genome. Yep. Driving cars throws off massive data. >>It >>Does. So is Tesla, uh, is the car the same as the data layer? >>I mean the, yeah, it's, it's certainly a point of origin. I think the thing that we wanna do is we wanna let the developers work on the world, changing problems, the things that they're trying to solve, whether it's, you know, energy or, you know, any of the other health or, you know, other challenges that these teams are, are building against. And we'll worry about that time series data and the underlying data platform so that they don't have to. Right. I mean, I think you talked about it, uh, you know, for them just to be able to adopt the platform quickly, integrate it with their data sources and the other pieces of their applications. It's going to allow them to bring much faster time to market on these products. It's gonna allow them to be more iterative. They're gonna be able to do more sort of testing and things like that. And ultimately it will, it'll accelerate the adoption and the creation of >>Technology. You mentioned earlier in, in our talk about unification of data. Yeah. How about APIs? Cuz developers love APIs in the cloud unifying APIs. How do you view view that? >>Yeah, I mean, we are APIs, that's the product itself. Like everything, people like to think of it as sort of having this nice front end, but the front end is B built on our public APIs. Um, you know, and it, it allows the developer to build all of those hooks for not only data creation, but then data processing, data analytics, and then, you know, sort of data extraction to bring it to other platforms or other applications, microservices, whatever it might be. So, I mean, it is a world of APIs right now and you know, we, we bring a very sort of useful set of them for managing the time series data. These guys are all challenged with. It's >>Interesting. You and I were talking before we came on camera about how, um, data is, feels gonna have this kind of SRE role that DevOps had site reliability engineers, which manages a bunch of servers. There's so much data out there now. Yeah. >>Yeah. It's like reigning data for sure. And I think like that ability to be like one of the best jobs on the planet is gonna be to be able to like, sort of be that data Wrangler to be able to understand like what the data sources are, what the data formats are, how to be able to efficiently move that data from point a to point B and you know, to process it correctly so that the end users of that data aren't doing any of that sort of hard upfront preparation collection storage's >>Work. Yeah. That's data as code. I mean, data engineering is it is becoming a new discipline for sure. And, and the democratization is the benefit. Yeah. To everyone, data science get easier. I mean data science, but they wanna make it easy. Right. <laugh> yeah. They wanna do the analysis, >>Right? Yeah. I mean, I think, you know, it, it's a really good point. I think like we try to give our users as many ways as there could be possible to get data in and get data out. We sort of think about it as meeting them where they are. Right. So like we build, we have the sort of client libraries that allow them to just port to us, you know, directly from the applications and the languages that they're writing, but then they can also pull it out. And at that point nobody's gonna know the users, the end consumers of that data, better than those people who are building those applications. And so they're building these user interfaces, which are making all of that data accessible for, you know, their end users inside their organization. >>Well, Brian, great segment, great insight. Thanks for sharing all, all the complexities and, and IOT that you guys helped take away with the APIs and, and assembly and, and all the system architectures that are changing edge is real cloud is real. Yeah, absolutely. Mainstream enterprises. And you got developer attraction too, so congratulations. >>Yeah. It's >>Great. Well, thank any, any last word you wanna share >>Deal with? No, just, I mean, please, you know, if you're, if you're gonna, if you're gonna check out influx TV, download it, try out the open source contribute if you can. That's a, that's a huge thing. It's part of being the open source community. Um, you know, but definitely just, just use it. I think when once people use it, they try it out. They'll understand very, >>Very quickly. So open source with developers, enterprise and edge coming together all together. You're gonna hear more about that in the next segment, too. Right. Thanks for coming on. Okay. Thanks. When we return, Dave LAN will lead a panel on edge and data influx DB. You're watching the cube, the leader in high tech enterprise coverage. >>Why the startup, we move really fast. We find that in flex DB can move as fast as us. It's just a great group, very collaborative, very interested in manufacturing. And we see a bright future in working with influence. My name is Aaron Seley. I'm the CTO at HBI. Highlight's one of the first companies to focus on manufacturing data and apply the concepts of data ops, treat that as an asset to deliver to the it system, to enable applications like overall equipment effectiveness that can help the factory produce better, smarter, faster time series data. And manufacturing's really important. If you take a piece of equipment, you have the temperature pressure at the moment that you can look at to kind of see the state of what's going on. So without that context and understanding you can't do what manufacturers ultimately want to do, which is predict the future. >>Influx DB represents kind of a new way to storm time series data with some more advanced technology and more importantly, more open technologies. The other thing that influx does really well is once the data's influx, it's very easy to get out, right? They have a modern rest API and other ways to access the data. That would be much more difficult to do integrations with classic historians highlight can serve to model data, aggregate data on the shop floor from a multitude of sources, whether that be P C U a servers, manufacturing execution systems, E R P et cetera, and then push that seamlessly into influx to then be able to run calculations. Manufacturing is changing this industrial 4.0, and what we're seeing is influx being part of that equation. Being used to store data off the unified name space, we recommend InfluxDB all the time to customers that are exploring a new way to share data manufacturing called the unified name space who have open questions around how do I share this new data that's coming through my UNS or my QTT broker? How do I store this and be able to query it over time? And we often point to influx as a solution for that is a great brand. It's a great group of people and it's a great technology. >>Okay. We're now going to go into the customer panel and we'd like to welcome Angelo Fasi. Who's a software engineer at the Vera C Ruben observatory in Caleb McLaughlin whose senior spacecraft operations software engineer at loft orbital guys. Thanks for joining us. You don't wanna miss folks this interview, Caleb, let's start with you. You work for an extremely cool company. You're launching satellites into space. I mean, there, of course doing that is, is highly complex and not a cheap endeavor. Tell us about loft Orbi and what you guys do to attack that problem. >>Yeah, absolutely. And, uh, thanks for having me here by the way. Uh, so loft orbital is a, uh, company. That's a series B startup now, uh, who and our mission basically is to provide, uh, rapid access to space for all kinds of customers. Uh, historically if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, you know, have a big software teams, uh, and then eventually worry about, you know, a bunch like just a lot of very specialized engineering. And what we're trying to do is change that from a super specialized problem that has an extremely high barrier of access to a infrastructure problem. So that it's almost as simple as, you know, deploying a VM in, uh, AWS or GCP is getting your, uh, programs, your mission deployed on orbit, uh, with access to, you know, different sensors, uh, cameras, radios, stuff like that. >>So that's, that's kind of our mission. And just to give a really brief example of the kind of customer that we can serve. Uh, there's a really cool company called, uh, totem labs who is working on building, uh, IOT cons, an IOT constellation for in of things, basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor T, which means you have this little modem inside a container container that you, that you track from anywhere in the world as it's going across the ocean. Um, so they're, it's really little and they've been able to stay a small startup that's focused on their product, which is the, uh, that super crazy complicated, cool radio while we handle the whole space segment for them, which just, you know, before loft was really impossible. So that's, our mission is, uh, providing space infrastructure as a service. We are kind of groundbreaking in this area and we're serving, you know, a huge variety of customers with all kinds of different missions, um, and obviously generating a ton of data in space, uh, that we've gotta handle. Yeah. >>So amazing Caleb, what you guys do, I, now I know you were lured to the skies very early in your career, but how did you kinda land on this business? >>Yeah, so, you know, I've, I guess just a little bit about me for some people, you know, they don't necessarily know what they wanna do like early in their life. For me, I was five years old and I knew, you know, I want to be in the space industry. So, you know, I started in the air force, but have, uh, stayed in the space industry, my whole career and been a part of, uh, this is the fifth space startup that I've been a part of actually. So, you know, I've, I've, uh, kind of started out in satellites, did spent some time in working in, uh, the launch industry on rockets. Then, uh, now I'm here back in satellites and you know, honestly, this is the most exciting of the difference based startups. That I've been a part of >>Super interesting. Okay. Angelo, let's, let's talk about the Ruben observatory, ver C Ruben, famous woman scientist, you know, galaxy guru. Now you guys the observatory, you're up way up high. You're gonna get a good look at the Southern sky. Now I know COVID slowed you guys down a bit, but no doubt. You continued to code away on the software. I know you're getting close. You gotta be super excited. Give us the update on, on the observatory and your role. >>All right. So yeah, Rubin is a state of the art observatory that, uh, is in construction on a remote mountain in Chile. And, um, with Rubin, we conduct the, uh, large survey of space and time we are going to observe the sky with, uh, eight meter optical telescope and take, uh, a thousand pictures every night with a 3.2 gig up peaks of camera. And we are going to do that for 10 years, which is the duration of the survey. >>Yeah. Amazing project. Now you, you were a doctor of philosophy, so you probably spent some time thinking about what's out there and then you went out to earn a PhD in astronomy, in astrophysics. So this is something that you've been working on for the better part of your career, isn't it? >>Yeah, that's that's right. Uh, about 15 years, um, I studied physics in college, then I, um, got a PhD in astronomy and, uh, I worked for about five years in another project. Um, the dark energy survey before joining rubing in 2015. >>Yeah. Impressive. So it seems like you both, you know, your organizations are looking at space from two different angles. One thing you guys both have in common of course is, is, is software. And you both use InfluxDB as part of your, your data infrastructure. How did you discover influx DB get into it? How do you use the platform? Maybe Caleb, you could start. >>Uh, yeah, absolutely. So the first company that I extensively used, uh, influx DBN was a launch startup called, uh, Astra. And we were in the process of, uh, designing our, you know, our first generation rocket there and testing the engines, pumps, everything that goes into a rocket. Uh, and when I joined the company, our data story was not, uh, very mature. We were collecting a bunch of data in LabVIEW and engineers were taking that over to MATLAB to process it. Um, and at first there, you know, that's the way that a lot of engineers and scientists are used to working. Um, and at first that was, uh, like people weren't entirely sure that that was a, um, that that needed to change, but it's something the nice thing about InfluxDB is that, you know, it's so easy to deploy. So as the, our software engineering team was able to get it deployed and, you know, up and running very quickly and then quickly also backport all of the data that we collected thus far into influx and what, uh, was amazing to see. >>And as kind of the, the super cool moment with influx is, um, when we hooked that up to Grafana Grafana as the visualization platform we used with influx, cuz it works really well with it. Uh, there was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data where they could just almost instantly easily discover data that they hadn't been able to see before and take the manual processes that they would run after a test and just throw those all in influx and have live data as tests were coming. And, you know, I saw them implementing like crazy rocket equation type stuff in influx, and it just was totally game changing for how we tested. >>So Angelo, I was explaining in my open, you know, you could, you could add a column in a traditional RDBMS and do time series, but with the volume of data that you're talking about, and the example of the Caleb just gave you, I mean, you have to have a purpose built time series database, where did you first learn about influx DB? >>Yeah, correct. So I work with the data management team, uh, and my first project was the record metrics that measured the performance of our software, uh, the software that we used to process the data. So I started implementing that in a relational database. Um, but then I realized that in fact, I was dealing with time series data and I should really use a solution built for that. And then I started looking at time series databases and I found influx B. And that was, uh, back in 2018. The another use for influx DB that I'm also interested is the visits database. Um, if you think about the observations we are moving the telescope all the time in pointing to specific directions, uh, in the Skype and taking pictures every 30 seconds. So that itself is a time series. And every point in that time series, uh, we call a visit. So we want to record the metadata about those visits and flex to, uh, that time here is going to be 10 years long, um, with about, uh, 1000 points every night. It's actually not too much data compared to other, other problems. It's, uh, really just a different, uh, time scale. >>The telescope at the Ruben observatory is like pun intended, I guess the star of the show. And I, I believe I read that it's gonna be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hub's widest camera view, which is amazing, right? That's like 40 moons in, in an image amazingly fast as well. What else can you tell us about the telescope? >>Um, this telescope, it has to move really fast and it also has to carry, uh, the primary mirror, which is an eight meter piece of glass. It's very heavy and it has to carry a camera, which has about the size of a small car. And this whole structure weighs about 300 tons for that to work. Uh, the telescope needs to be, uh, very compact and stiff. Uh, and one thing that's amazing about it's design is that the telescope, um, is 300 tons structure. It sits on a tiny film of oil, which has the diameter of, uh, human hair. And that makes an almost zero friction interface. In fact, a few people can move these enormous structure with only their hands. Uh, as you said, uh, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So each image has, uh, in diameter the size of about seven full moons. And, uh, with that, we can map the entire sky in only, uh, three days. And of course doing operations everything's, uh, controlled by software and it is automatic. Um there's a very complex piece of software, uh, called the scheduler, which is responsible for moving the telescope, um, and the camera, which is, uh, recording 15 terabytes of data every night. >>Hmm. And, and, and Angela, all this data lands in influx DB. Correct. And what are you doing with, with all that data? >>Yeah, actually not. Um, so we are using flex DB to record engineering data and metadata about the observations like telemetry events and commands from the telescope. That's a much smaller data set compared to the images, but it is still challenging because, uh, you, you have some high frequency data, uh, that the system needs to keep up and we need to, to start this data and have it around for the lifetime of the price. Mm, >>Got it. Thank you. Okay, Caleb, let's bring you back in and can tell us more about the, you got these dishwasher size satellites. You're kind of using a multi-tenant model. I think it's genius, but, but tell us about the satellites themselves. >>Yeah, absolutely. So, uh, we have in space, some satellites already that as you said, are like dishwasher, mini fridge kind of size. Um, and we're working on a bunch more that are, you know, a variety of sizes from shoebox to, I guess, a few times larger than what we have today. Uh, and it is, we do shoot to have effectively something like a multi-tenant model where, uh, we will buy a bus off the shelf. The bus is, uh, what you can kind of think of as the core piece of the satellite, almost like a motherboard or something where it's providing the power. It has the solar panels, it has some radios attached to it. Uh, it handles the attitude control, basically steers the spacecraft in orbit. And then we build also in house, what we call our payload hub, which is, has all, any customer payloads attached and our own kind of edge processing sort of capabilities built into it. >>And, uh, so we integrate that. We launch it, uh, and those things, because they're in lower orbit, they're orbiting the earth every 90 minutes. That's, you know, seven kilometers per second, which is several times faster than a speeding bullet. So we've got, we have, uh, one of the unique challenges of operating spacecraft and lower orbit is that generally you can't talk to them all the time. So we're managing these things through very brief windows of time, uh, where we get to talk to them through our ground sites, either in Antarctica or, you know, in the north pole region. >>Talk more about how you use influx DB to make sense of this data through all this tech that you're launching into space. >>We basically previously we started off when I joined the company, storing all of that as Angelo did in a regular relational database. And we found that it was, uh, so slow in the size of our data would balloon over the course of a couple days to the point where we weren't able to even store all of the data that we were getting. Uh, so we migrated to influx DB to store our time series telemetry from the spacecraft. So, you know, that's things like, uh, power level voltage, um, currents counts, whatever, whatever metadata we need to monitor about the spacecraft. We now store that in, uh, in influx DB. Uh, and that has, you know, now we can actually easily store the entire volume of data for the mission life so far without having to worry about, you know, the size bloating to an unmanageable amount. >>And we can also seamlessly query, uh, large chunks of data. Like if I need to see, you know, for example, as an operator, I might wanna see how my, uh, battery state of charge is evolving over the course of the year. I can have a plot and an influx that loads that in a fraction of a second for a year's worth of data, because it does, you know, intelligent, um, I can intelligently group the data by, uh, sliding time interval. Uh, so, you know, it's been extremely powerful for us to access the data and, you know, as time has gone on, we've gradually migrated more and more of our operating data into influx. >>You know, let's, let's talk a little bit, uh, uh, but we throw this term around a lot of, you know, data driven, a lot of companies say, oh, yes, we're data driven, but you guys really are. I mean, you' got data at the core, Caleb, what does that, what does that mean to you? >>Yeah, so, you know, I think the, and the clearest example of when I saw this be like totally game changing is what I mentioned before at Astro where our engineer's feedback loop went from, you know, a lot of kind of slow researching, digging into the data to like an instant instantaneous, almost seeing the data, making decisions based on it immediately, rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. Um, but to give another practical example, uh, as I said, we have a huge amount of data that comes down every orbit, and we need to be able to ingest all of that data almost instantaneously and provide it to the operator. And near real time, you know, about a second worth of latency is all that's acceptable for us to react to, to see what is coming down from the spacecraft and building that pipeline is challenging from a software engineering standpoint. >>Um, our primary language is Python, which isn't necessarily that fast. So what we've done is started, you know, in the, in the goal of being data driven is publish metrics on individual, uh, how individual pieces of our data processing pipeline are performing into influx as well. And we do that in production as well as in dev. Uh, so we have kind of a production monitoring, uh, flow. And what that has done is allow us to make intelligent decisions on our software development roadmap, where it makes the most sense for us to, uh, focus our development efforts in terms of improving our software efficiency. Uh, just because we have that visibility into where the real problems are. Um, it's sometimes we've found ourselves before we started doing this kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. Uh, but now, now that we're being a bit more data driven, there we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scale to, from supporting a couple satellites, to supporting many, many satellites at >>Once. Yeah. Coach. So you reduced those dead ends, maybe Angela, you could talk about what, what sort of data driven means to, to you and your teams? >>I would say that, um, having, uh, real time visibility, uh, to the telemetry data and, and metrics is, is, is crucial for us. We, we need, we need to make sure that the image that we collect with the telescope, uh, have good quality and, um, that they are within the specifications, uh, to meet our science goals. And so if they are not, uh, we want to know that as soon as possible and then, uh, start fixing problems. >>Caleb, what are your sort of event, you know, intervals like? >>So I would say that, you know, as of today on the spacecraft, the event, the, the level of timing that we deal with probably tops out at about, uh, 20 Hertz, 20 measurements per second on, uh, things like our, uh, gyroscopes, but the, you know, I think the, the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications. And I'll give an example, uh, from when I worked at, on the rocket at Astra there, our baseline data rate that we would ingest data during a test is, uh, 500 Hertz. So 500 samples per second. And in some cases we would actually, uh, need to ingest much higher rate data, even up to like 1.5 kilohertz. So, uh, extremely, extremely high precision, uh, data there where timing really matters a lot. And, uh, you know, I can, one of the really powerful things about influx is the fact that it can handle this. >>That's one of the reasons we chose it, uh, because there's times when we're looking at the results of a firing where you're zooming in, you know, I talked earlier about how on my current job, we often zoom out to look, look at a year's worth of data. You're zooming in to where your screen is preoccupied by a tiny fraction of a second. And you need to see same thing as Angela just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers. So that can be something like, Hey, I opened this valve at exactly this time and that goes, we wanna have that at, you know, micro or even nanosecond precision so that we know, okay, we saw a spike in chamber pressure at, you know, at this exact moment, was that before or after this valve open, those kind of, uh, that kind of visibility is critical in these kind of scientific, uh, applications and absolutely game changing to be able to see that in, uh, near real time and, uh, with a really easy way for engineers to be able to visualize this data themselves without having to wait for, uh, software engineers to go build it for them. >>Can the scientists do self-serve or are you, do you have to design and build all the analytics and, and queries for your >>Scientists? Well, I think that's, that's absolutely from, from my perspective, that's absolutely one of the best things about influx and what I've seen be game changing is that, uh, generally I'd say anyone can learn to use influx. Um, and honestly, most of our users might not even know they're using influx, um, because what this, the interface that we expose to them is Grafana, which is, um, a generic graphing, uh, open source graphing library that is very similar to influx own chronograph. Sure. And what it does is, uh, let it provides this, uh, almost it's a very intuitive UI for building your queries. So you choose a measurement and it shows a dropdown of available measurements. And then you choose a particular, the particular field you wanna look at. And again, that's a dropdown, so it's really easy for our users to discover. And there's kind of point and click options for doing math aggregations. You can even do like perfect kind of predictions all within Grafana, the Grafana user interface, which is really just a wrapper around the APIs and functionality of the influx provides putting >>Data in the hands of those, you know, who have the context of domain experts is, is key. Angela, is it the same situation for you? Is it self serve? >>Yeah, correct. Uh, as I mentioned before, um, we have the astronomers making their own dashboards because they know what exactly what they, they need to, to visualize. Yeah. I mean, it's all about using the right tool for the job. I think, uh, for us, when I joined the company, we weren't using influx DB and we, we were dealing with serious issues of the database growing to an incredible size extremely quickly, and being unable to like even querying short periods of data was taking on the order of seconds, which is just not possible for operations >>Guys. This has been really formative it's, it's pretty exciting to see how the edge is mountaintops, lower orbits to be space is the ultimate edge. Isn't it. I wonder if you could answer two questions to, to wrap here, you know, what comes next for you guys? Uh, and is there something that you're really excited about that, that you're working on Caleb, maybe you could go first and an Angela, you can bring us home. >>Uh, basically what's next for loft. Orbital is more, more satellites, a greater push towards infrastructure and really making, you know, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, uh, making that happen, it's extremely exciting and extremely exciting time to be in this company and to be in this industry as a whole, because there are so many interesting applications out there. So many cool ways of leveraging space that, uh, people are taking advantage of. And with, uh, companies like SpaceX and the now rapidly lowering cost, cost of launch, it's just a really exciting place to be. And we're launching more satellites. We are scaling up for some constellations and our ground system has to be improved to match. So there's a lot of, uh, improvements that we're working on to really scale up our control software, to be best in class and, uh, make it capable of handling such a large workload. So >>You guys hiring >><laugh>, we are absolutely hiring. So, uh, I would in we're we need, we have PE positions all over the company. So, uh, we need software engineers. We need people who do more aerospace, specific stuff. So, uh, absolutely. I'd encourage anyone to check out the loft orbital website, if there's, if this is at all interesting. >>All right. Angela, bring us home. >>Yeah. So what's next for us is really, uh, getting this, um, telescope working and collecting data. And when that's happen is going to be just, um, the Lu of data coming out of this camera and handling all, uh, that data is going to be really challenging. Uh, yeah. I wanna wanna be here for that. <laugh> I'm looking forward, uh, like for next year we have like an important milestone, which is our, um, commissioning camera, which is a simplified version of the, of the full camera it's going to be on sky. And so yeah, most of the system has to be working by them. >>Nice. All right, guys, you know, with that, we're gonna end it. Thank you so much, really fascinating, and thanks to influx DB for making this possible, really groundbreaking stuff, enabling value creation at the edge, you know, in the cloud and of course, beyond at the space. So really transformational work that you guys are doing. So congratulations and really appreciate the broader community. I can't wait to see what comes next from having this entire ecosystem. Now, in a moment, I'll be back to wrap up. This is Dave ante, and you're watching the cube, the leader in high tech enterprise coverage. >>Welcome Telegraph is a popular open source data collection. Agent Telegraph collects data from hundreds of systems like IOT sensors, cloud deployments, and enterprise applications. It's used by everyone from individual developers and hobbyists to large corporate teams. The Telegraph project has a very welcoming and active open source community. Learn how to get involved by visiting the Telegraph GitHub page, whether you want to contribute code, improve documentation, participate in testing, or just show what you're doing with Telegraph. We'd love to hear what you're building. >>Thanks for watching. Moving the world with influx DB made possible by influx data. I hope you learn some things and are inspired to look deeper into where time series databases might fit into your environment. If you're dealing with large and or fast data volumes, and you wanna scale cost effectively with the highest performance and you're analyzing metrics and data over time times, series databases just might be a great fit for you. Try InfluxDB out. You can start with a free cloud account by clicking on the link and the resources below. Remember all these recordings are gonna be available on demand of the cube.net and influx data.com. So check those out and poke around influx data. They are the folks behind InfluxDB and one of the leaders in the space, we hope you enjoyed the program. This is Dave Valante for the cube. We'll see you soon.

>>Okay. Today we welcome Evan Kaplan, CEO of Influx Data, the company behind Influx DB Welcome, Evan. Thanks for coming on. >>Hey, John. Thanks for having me. >>Great segment here on the influx. DB Story. What is the story? Take us through the history. Why Time series? What's the story? >>So the history of history is actually actually pretty interesting. Paul Dicks, my partner in this and our founder, um, super passionate about developers and developer experience. And, um, he had worked on Wall Street building a number of times series kind of platform trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave, which means you have to do a tonne of work just to start doing work. Which means you have to write a bunch of extrinsic routines. You had to write a bunch of application handling on existing relational databases in order to come up with something that was optimised for a trading platform or a time series platform. And he sort of he just developed This real clear point of view is this is not how developers should work. And so in 2013, he went through y Combinator and he built something for he made his first commit to open source influx TB at the end of 2013. And basically, you know, from my point of view, you invented modern time series, which is you start with a purpose built time series platform to do these kind of work clothes, and you get all the benefits of having something right out of the box or developer can be totally productive right away. >>And how many people in the company What's the history of employees and stuff? Yeah, >>I think we're you know, I always forget the number, but it's something like 230 or 240 people now. Um, the company I joined the company in 2016 and I love Paul's vision, and I just had a strong conviction about the relationship between Time series and Iot. Because if you think about it, what sensors do is they speak time, series, pressure, temperature, volume, humidity, light. They're measuring their instrumented something over time. And so I thought that would be super relevant over long term, and I've not regretted. Oh, >>no, and it's interesting at that time to go back in history. You know the role of databases are relational database, the one database to rule the world. And then, as clouds started coming in, you're starting to see more databases, proliferate types of databases. And Time series in particular, is interesting because real time has become super valuable. From an application standpoint, Iot, which speaks Time series, means something. It's like time matters >>times, >>and sometimes date is not worth it after the time. Sometimes it's worth it. And then you get the Data lake, so you have this whole new evolution. Is this the momentum? What's the momentum? I guess the question is, what's the momentum behind >>what's causing us to grow? So >>the time series. Why is time series in the category momentum? What's the bottom line? We'll >>think about it. You think about it from abroad, abroad, sort of frame, which is where what everybody's trying to do is build increasingly intelligent systems, whether it's a self driving car or a robotic system that does what you want to do or self healing software system. Everybody wants to build increasing intelligence systems, and so, in order to build these increasingly intelligence systems. You have to instrument the system well, and you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened? What happened? What happened? What's going to happen? And so you get to these applications, like predictive maintenance or smarter systems. And increasingly, you want to do that stuff not just intelligently, but fast in real time, so millisecond response, so that when you're driving a self driving car and the system realises that you're about to do something, essentially, you want to be able to act in something that looks like real time. All systems want to do that. I want to be more intelligent, and they want to be more real time. So we just happened to, you know, we happen to show up at the right time. In the evolution of the market. >>It's interesting. Near real time isn't good enough when you need real time. Yeah, >>it's not, it's not, and it's like it's like everybody wants even when you don't need it. Uh, ironically, you want it. It's like having the feature for, you know, you buy a new television, you want that one feature even though you're not going to use it, you decide that you're buying criteria. Real time is a buying criteria. >>So what you're saying, then is near real time is getting closer to real time as possible as possible. Okay, so talk about the aspect of data cause we're hearing a lot of conversations on the Cubans particular around how people are implementing and actually getting better. So iterating on data. >>But >>you have to know when it happened to get know how to fix it. So this is a big part of what we're seeing with people saying, Hey, you know, I want to make my machine learning albums better after the fact I want to learn from the data. Um, how does that How do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data knowing when it happened? >>Well, for sure, So for sure, what you're saying is is none of this is non linear. It's all incremental. And so if you take something, you know, just as an easy example. If you take a self driving car, what you're doing is your instrument in that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop, which is I instrumented, I watch what happens. Oh, that's wrong. Oh, I have to correct for that. Correct for that in the software, if you do that four billion times, you get a self driving car. But every system moves along that evolution. And so you get the dynamic of you know of constantly instrumented, watching the system behave and do it and this and sets up driving cars. One thing. But even in the human genome, if you look at some of our customers, you know people like, you know, people doing solar arrays. People doing power walls like all of these systems, are getting smarter. >>What are the top application? What are you seeing your with Influx DB The Time series. What's the sweet spot for the application use case and some customers give some examples. >>Yeah, so it's pretty easy to understand. On one side of the equation. That's the physical side is sensors are the sensors are getting cheap. Obviously, we know that, and they're getting. The whole physical world is getting instrumented your home, your car, the factory floor, your wrist watch your healthcare, you name it. It's getting instrumented in the physical world. We're watching the physical world in real time, and so there are three or four sweet spots for us. But they're all on that side. They're all about Iot. So they're talking about consumer Iot projects like Google's Nest Tato Um, particle sensors, Um, even delivery engines like Happy who deliver the interesting part of South America. Like anywhere. There's a physical location doing that's on the consumer side. And then another exciting space is the industrial side. Factories are changing dramatically over time, increasingly moving away from proprietary equipment to develop or driven systems that run operational because what it has to get smarter when you're building, when you're building a factory, systems all have to get smarter. And then lastly, a lot in the renewables sustainability. So a lot, you know, Tesla, lucid motors, Nicola Motors, um you know, lots to do with electric cars, solar arrays, windmills are raised just anything that's going to get instrumented, that where that instrumentation becomes part of what the purpose is. >>It's interesting. The convergence of physical and digital is happening with the data Iot you mentioned. You know, you think of Iot. Look at the use cases there. It was proprietary OT systems now becoming more I p enabled Internet protocol and now edge compute getting smaller, faster, cheaper ai going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing Iot going to a new level? What was that? What's the Iot? Where's the Iot dots connecting to? Because, you know, as these two cultures merge operations basically industrial factory car, they gotta get smarter. Intelligent edge is a buzzword, but it has to be more intelligent. Where's the where's the action in all this? So the >>action really, really at the core? >>It's >>at the developer, right, Because you're looking at these things. It's very hard to get off the shelf system to do the kinds of physical and software interaction. So the actions really happen at the developers. And so what you're seeing is a movement in the world that that maybe you and I grew up in with I t r o T moving increasingly that developer driven capability. And so all of these Iot systems, their bespoke, they don't come out of the box. And so the developer and the architect, the CTO they define what's my business? What am I trying to do trying to sequence the human genome and figure out when these genes express themselves? Or am I trying to figure out when the next heart rate monitor is going to show up in my apple watch, right? What am I trying to do? What's the system I need to build? And so starting with the developers where all of the good stuff happens here, which is different than it used to be, right, used to be used by an application or a service or a sad thing for But with this dynamic with this integration of systems, it's all about bespoke. It's all about building something. >>So let's get to the death of a real quick, real highlight point. Here is the data. I mean, I could see a developer saying, Okay, I need to have an application for the edge Iot, edge or car. I mean, we're gonna test look at applications of the cars right there. I mean, there's the modern application lifecycle now, so take us through how this impacts the developer doesn't impact their CI CD. Pipeline is a cloud native. I mean, where does this all Where does this go to? >>Well, so first of all you talking about, there was an internal journey that we had to go through as a company, which which I think is fascinating for anybody's interested as we went from primarily a monolithic software that was open source to building a cloud native platform, which means we have to move from an agile development environment to a C I C d. Environ. So two degree that you're moving your service whether it's, you know, Tesla, monitoring your car and updating your power walls right? Or whether it's a solar company updating your race right to the degree that services cloud then increasingly removed from an agile development to a CI CD environment which is shipping code to production every day. And so it's not just the developers, all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also going to happen in a big way >>when your customer base that you have now and you see evolving with influx DB is it that they're gonna be writing more of the application or relying more on others? I mean, obviously the open source component here. So when you bring in kind of old way new Way Old Way was, I got a proprietary platform running all this Iot stuff and I got to write, Here's an application. That's general purpose. I have some flexibility, somewhat brittle. Maybe not a lot of robustness to it, but it does its job >>a good way to think about this. >>This is what >>So, yeah, a good way to think about this is what What's the role of the developer slashed architect C T o that chain within a large enterprise or a company. And so, um, the way to think about is I started my career in the aerospace industry, and so when you look at what Boeing does to assemble a plane, they build very, very few of the parts instead. What they do is they assemble, they buy the wings, they buy the engines they assemble. Actually, they don't buy the wings. It's the one thing they buy, the material of the way they build the wings because there's a lot of tech in the wings and they end up being assemblers, smart assemblers of what ends up being a flying aeroplane, which is pretty big deal even now. And so what happens with software people is they have the ability to pull from, you know, the best of the open source world, so they would pull a time series capability from us. Then they would assemble that with potentially some E t l logic from somebody else, or they assemble it with, um, a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers. But they become masters of that bespoke application, and I think that's where it goes because you're not writing native code for everything, >>so they're more flexible. They have faster time to market because they're assembling way faster and they get to still maintain their core competency. OK, the wings. In this case, >>they become increasingly not just coders, but designers and developers. They become broadly builders is what we like to think of it. People who started build stuff. By the way. This is not different than the people have just up the road Google have been doing for years or the tier one Amazon building all their own. >>Well, I think one of the things that's interesting is that this idea of a systems developing a system architecture, I mean systems, uh, systems have consequences when you make changes. So when you have now cloud data centre on premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing. That's exactly >>that's where that's where the, you know that that Boeing or that aeroplane building analogy comes in for us. We've really been thoughtful about that because I o. T. It's critical. So are open Source Edge has the same API as our cloud native stuff that hasn't enterprise on premises or multiple products have the same API, and they have a relationship with each other. They can talk with each other, so the builder builds at once. And so this is where when you start thinking about the components that people have to use to build these services is that you want to make sure at least that base layer that database layer that those components talk to each other. >>We'll have to ask you. I'm the customer. I put my customer hat on. Okay. Hey, I'm dealing with a lot. >>I mean, you have appeal for >>a big check blank check. If you can answer this question only if you get the question right. I got all this important operation stuff. I got my factory. I got my self driving cars. This isn't like trivial stuff. This is my business. How should I be thinking about Time Series? Because now I have to make these architectural decisions as you mentioned and it's going to impact my application development. So huge decision point for your customers. What should I care about the most? What's in it for me? Why is time series important? Yeah, >>that's a great question. So chances are if you've got a business that was 20 years old or 25 years old, you're already thinking about Time series. You probably didn't call it that you built something on a work call or you build something that IBM db two. Right, and you made it work within your system, right? And so that's what you started building. So it's already out there. There are, you know, they're probably hundreds of millions of Time series applications out there today. But as you start to think about this increasing need for real time and you start to think about increasing intelligence, you think about optimising those systems over time. I hate the word but digital transformation, and you start with Time series. It's a foundational base layer for any system that you're going to build. There's no system I can think of where time series shouldn't be the foundational base layer. If you just want to store your data and just leave it there and then maybe look it up every five years, that's fine. That's not time. Serious time series when you're building a smarter, more intelligent, more real time system, and the developers now know that, and so the more they play a role in building these systems, the more obvious it becomes. >>And since I have a P o for you in a big check, what what's the value to me as like when I implement this What's the end state? What's it look like when it's up and running? What's the value proposition for me? What's in it? >>So when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data transforming it in near real time. So the other dependencies that a system that gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome those systems work better. So time series is foundational. It's not like it's, you know, it's not like it's doing every action that's above, but it's foundational to build a really compelling intelligence system. I think that's what developers and architects are seeing now. >>Bottom line. Final word. What's in it for the customer? What's what's your What's your statement of the customer? Would you say to someone looking to do something in time, series and edge? >>Yeah. So it's pretty clear to clear to us that if you're building, if you view yourself as being in the building business of building systems that you want them to be increasingly intelligent, self healing, autonomous, you want them to operate in real time that you start from Time series. I also want to say What's in it for us in flux? What's in it for us is people are doing some amazing stuff. I highlighted some of the energy stuff, some of the human genome, some of the health care. It's hard not to be proud or feel like. Wow. Somehow I've been lucky. I've arrived at the right time in the right place, with the right people to be able to deliver on that. That's That's also exciting on our side of the equation. >>It's critical infrastructure, critical critical operations. >>Yeah, great >>stuff. Evan. Thanks for coming on. Appreciate this segment. All right. In a moment. Brian Gilmore, director of Iot and emerging Technology that influx, they will join me. You're watching the Cube leader in tech coverage. Thanks for watching

>> The Cube presents Dell Technologies World brought to you by Dell. (crowd murmuring) >> Welcome back to Las Vegas. It's The Cube live at Dell Technologies World 2022. This is day two of our coverage Lisa Martin, with Dave Vellante. We've had a lot of great conversations all day today half a day yesterday. We've got another great conversation coming up about ESG environmental, social and governance. Please welcome JJ Davis, the Chief Corporate Affairs Officer at Dell Technologies. Welcome to the program. >> Hi, thanks for having me. >> Hey, hey. >> It's great to be here. >> ESG is a very popular topic. >> Yes. >> It's one thing to talk about another thing to actually have a plan, have a strategy, have those 20, 30 moonshot goals and implement. Talk to us about what ESG means for Dell Technologies and some of these great things, that you have going on. >> Absolutely. So you said it, I mean it can be acronym soup. When you think about, is it social impact? Is it corporate social responsibility? Is it ESG and the beauty of having an environmental social governance strategy is we now are bringing ESG much closer to the corporate strategy and how we meet the needs of all of our stakeholders. So I'd love to just back it up for a minute and think about the purpose of Dell Technologies is to create technologies that advance human potential. Our vision is to be the most essential technology company for the data era. The way we do that is we're growing and modernizing our core businesses like PC servers and storage while we're building the technology ecosystem of the future. Well guess what? ESG is embedded in all of that because the future is more sustainable, built by people that represent our customer base with a workforce that is more diverse and a workplace that is more inclusive. We put human rights and the needs of people at the center of what we do as well as the needs of the planet. And when I get to put together purpose planet and profit and bring that strategy together in partnership with so many leaders of across the company and meeting the demands of our customers. ESG is just a part of the way we do business now >> It's part of the DNA. >> Yeah. >> Talk to us about some of the key priorities from a climate perspective, for example. >> Sure. >> What are some of Dell's key focus areas where that's concerned? >> So when we think about our ESG priorities as a whole there are four climate, circular, economy, diverse workplace and digital inclusion. And so within our sustainability pillar of our strategy or the E, we are committed to being net zero across scopes 1, 2 and 3 emissions by 2050. We are revamping our product energy goal right now to relaunch that. When we think about our customers 95% of our big customer RFPs ask about sustainability and our commitment and what we'll be doing to help them because they're going to be reliant on technology to meet their own sustainability and climate goals, whether it's green IT or IT for green and they're going to really be looking to us to help them. >> You know, I love this purpose planet profit. >> Yeah. >> You and I have talked about this a little bit. It's actually good business. Explain why ESG is good business? >> Well, I mean, used to social impact kind of sat off to the side. We might have been called do gooders or people that are passionate about things that maybe don't align to the corporate strategy. And now when you think about business round table and Michael Dell as a member and they came out with their purpose of a company statement it'll be three years in August to really redefine the purpose of a company to meet the needs of all stakeholders from employees, to customers, to shareholders as well. And so we know that new hires and new buyers demand more of their employer and of the companies they buy from. They want their own personal values to align with that of the company they work for or buy from. And so now we need to the needs of our business commitments, but also if companies don't take a leadership role, we're screwed, we're not going to be able to reverse the negative impacts. So climate change and technology plays a big role. >> Yeah. "The earth gets the last at bat," as they say. >> Yeah. >> From an accountability perspective that you mentioned 95% of RFPs are coming in and customers are looking for- >> Yes. >> Dell Technologies's commitment to ESG. Talk about the accountability to your customers to all customers where ESG is concerned and how is it measured? >> Sure. So we've been spending a lot of time over the last year, year and a half on the G of ESG the governance. And so we have been doing this for a couple decades really moving the needle on social impact. Michael talked about it in his key note, that this is in our DNA like you said. But now we have to be able to really measure. You can't manage what you can't measure. We have put a lot of governance around, what do we disclose and why Michael Dell is an active participant in the world economic forum, common metrics project because, you know, there's too many metrics and frameworks to know what companies need to be measuring and how we hold ourselves accountable and what we ultimately report to our shareholders. And so there's a lot of work to get more clarity there. You're seeing the SEC put out new rules around climate and human rights. And so when you start to get regulated that changes the game in terms of how transparent you need to be. And then what are the third party assurances that you need to have to validate the data that you're reporting on? We do have an annual ESG report that comes out every June where we report across several moonshot goals across sustainability, inclusive culture, transforming lives and ethics and privacy. Then we have sub goals. There's probably about 25 in total. And we're going to tell you our stakeholders every year how we're doing against our 20, 30 commitment. And I think it's that level of transparency and measurement that we have to hold ourselves accountable to and our customers do as well. >> Can you share a little bit about where you are on the 2030 moonshot that was announced about a couple years ago at the beginning of 20, yeah, towards the beginning of 2020. Where is Dell on the that, what's your moonscape look like? >> Yeah, sure. So we are announcing our update from calendar year 21 in June. So I'm not going to get the numbers exactly right. But if you take sustainability so one of our moonshot goals is around 100% of our packaging by 2030 will be made of recycled or renewable content. We're over 90% now. So we're going to probably restate that goal and evolve it or meet it early and set a new one. In terms of product contents. We have a goal that is 50% of our product contents will be from recycled over renewable materials. That's a little harder, plastic is easy, steel is hard. And so we're still working through how across the main components that go into our machines. How does that become more renewed and sustainable? If you think about 50% women in our workforce 25% African American or Hispanic in our US workforce we're making really good progress. And we have scaled programs that are helping us deliver on those commitments. >> Yeah. I think I'm quoting JJ Davis, correct me if I'm wrong but, "ESG marries who we are with what we do." What do you mean by that? >> So when you think about what we do, we build technology that delivers or advances human progress. We help our customers solve their biggest problems but really who we are. We are a founder-led company and Michael Dell was a purpose led driven CEO before that was even a term. And so he always wanted to have an ethical company that just did business above and beyond what the law required. And we'd been recycling PC for more than 20 years. And so we are an inclusive culture where we can bring our full selves to work and we are entrepreneurial. And, you know, if we have an idea and you raise that idea or a problem, you see then oftentimes the management will say, "Okay you go fix that." And so I think just what we do, we build technology. Who we are, is we're problem solvers for our customers. And that is good for business and good for the environment and what it is society really expects of us. And we're empowered to make a difference. Feels good. >> One of, I'm curious to get your perspective on , you know, the events of the last two years. One of the things that's happened is the great resignation. I think we all all know multiple people who have decided they're moving forward, lots of opportunity but where is Dell's ESG strategy as a differentiator for people going, I get it, I support that, that's the kind of company I want to work for? >> Our Chief Human Resources Officer Jen Saavedra calls it, "The great reshuffle." I think that's maybe a more positive way to look at it. And, you know, I've had people actually join my team because they are really positive on our mission and not just our proactive strategy around ESG but how we have handled our response to social issues. >> Yeah. >> I mean, who knew that company CEOs would be expected to speak out on voter access or LGBTQ rights and, you know. So a lot of people are coming to work for us because we are very measured in where we weigh in and what we stand for, how we speak out. But they're also really buying into our ESG strategy. I would also say our flexible work commitment. It's a big part of our DNI strategy as well and helps us attract and retain diverse talent. You can live and work wherever you want to proximity the headquarters is no longer criteria for advancement. And that's going to be a really big differentiator companies that get this right will win the talent war. And that means they'll better serve their customers. >> When you took over this role, I'm guessing you kind of did a scan to see who else was out there, what others were doing, not just in Tech. >> Sure. >> Not just in North America, but globally. What did you find? Where do you get your inspiration? Are there any organizations out there that are really models that you get inspiration from? Or is it so new? You are the model. Can you just talk about that? >> Well I mean, I think we're doing a really good job and we're pretty advanced, but nobody has this figured out and frankly, we need to do it together. This is a space where you don't actually want to compete. >> Right. >> You want to partner. And so we have our own sustainability advisory aboard and companies like Boeing or on that. I serve on a sustain the advisory board from McLaren and Unilever's chief sustainability officers there. That is a company that is really inspirational to us. And so partners like Intel, they're very involved in 50. So the next 50% that needs to get connected to the internet and participate in the digital economy. We're big partner, as you know we're their largest customer. And so there's a lot going on across our competition our customers and our partners. And we're all inspiring each other and figuring it out together. Cause it's evolving so fast. Nobody has all the answers. >> But that's a great point. The evolution is happening so quickly and every day you turn on the news and there's something else that needs to be responded to. >> Yeah. >> I mean, think that from a strategic perspective from that overall vision perspective, it sounds like what and there's been some announcements this week. >> Yeah. >> That respect to issue. What's been some of the feedback from the part of ecosystem, from customers, from investors on this laser focused vision that Dell has with respect to sustainability and ESG? >> So Cassandra Garber, our head of ESG just finished out of cycle road show with investors and had really good conversations. They're asking a lot of questions about our strategy. They're asking questions about executive compensation tied to ESG as an example. Our customers are very positive and responding. They're looking for technology solutions. As I mentioned to meet their own climate commitments. And from our channel partners they really want to partner on our initiatives and really go do good and make an impact together. And we're getting really good feedback. >> So carrot or stick, it's probably not 100% that the channel partners or even suppliers, you know, some just don't have the resource possibly or maybe they don't share your values. >> Right. >> So how do you approach that? Is it through inspiration? Is it through a little tap in the head or a little headlock? How do you deal with that? >> It's both. I mean, our suppliers have to adhere to the contract and the RSA code of conduct that they have to sign on to uphold. And so we very much hold them accountable just like we do our ourselves. And so that is more compliance driven but we do have partners like Western's Green in our supply chain who we're really involved with us in some early work around recycled gold and partners that are involved with us in setting up the ocean plastic supply chain. And so we have great partnership but there are things they have to do from a human rights perspective or commitment to the environment that are required. From a channel partner perspective, you know, we want to incent them. We want to make money together. We are for profit businesses after all. And ESG can be a part of that. And if you don't have the resources to drive your own take back initiative, then we can do that in partnership through our asset recovery services which partners can sell and then use our infrastructure to take back and recycle old equipment. >> I mean, I feel like a lot of my questions are two-way but you feel as though you're in influencing public policy or a public policy is influencing you? >> Both. I mean, early on when the SEC was looking at the climate rules that they just put out, there was, I think we submitted a six page response to their, you know, ask for inquiry and response. And so that's good. We're able to talk to each other and have conversations and shape things, but ultimately we'll be regulated in these areas and that's fine. We just got to make sure that we're ready. >> Great. >> It's always good to have that push and pull it's like with the pandemic all the silver linings that have come out of the acceleration, we talk about that all the time on this show. The acceleration of digital transformation, we were talking about the acceleration of retail in the intelligence store. >> Right. >> And as consumers, we expect that, but that push and pull sometimes those forcing functions are necessary to be able to drive forward. >> For sure. >> Yeah. >> Yeah. >> My last question for you is Dell just came off it's most successful year. >> Yes. >> First time hitting north of 100 billion. >> Yes. >> In the company's history. What are some of the things that we think is the moonshot goals, we're only in 2020. >> I know. >> But as time is going by so quickly, what are some of the things that you are personally looking forward to from a corporate affairs ESG perspective say the next like three to five years? >> Well, I'm really excited about some of the groundwork we've laid in digital inclusion. We just made some new hires there. We're connecting the dots, you know, and we have a lot of initiatives that can really if we can scale them, make a big impact. So we have student tech crew, it's where high school students serve as the technical support in their local high school and get certified. So they are job ready the minute they graduate. If they don't want to go to community college or university they can go right into the workforce. How do we marry that up with other skill building initiatives that we have? And if you add 1 plus 1 it equals 3. And I think this year will be a really big accelerator for us in the area of digital inclusion and how we bring connectivity, community services and support and digital skills together. Because that's what, you know, those that aren't participating in the digital economy we need to partner and really deliver on the promise of what it means to be in technology and at least have the skills to compete >> Right. Start eliminating that digital divide. JJ, thank you for joining David and me today talking about ESG- >> Thank you. >> corporate affairs, such an interesting focused efforts that Dell is really wrapped around. And it sounds like there's that push pull from the customers, from policy, but ultimately going in a great direction that can be measured. Thank you for your insights and your time. >> Thank you. >> For JJ and Dave Vellante I'm Lisa Martin. You've been watching The Cube live from Las Vegas. This is the end of day 2 of our coverage of Dell Technologies World. We thank you for watching. You can find all of our content on replay on theCUBE.net. And of course, we will be here tomorrow with John Farrier and Dave Nicholson as well. Have a great night. We'll see you tomorrow. (upbeat music)

(upbeat music) >> Okay today, we welcome Evan Kaplan, CEO of InfluxData, the company behind InfluxDB. Welcome Evan, thanks for coming on. >> Hey John, thanks for having me. >> Great segment here on the InfluxDB story. What is the story? Take us through the history, why time series? What's the story? >> So the history history is actually pretty interesting. Paul Dix my partner in this and our founder, super passionate about developers and developer experience. And he had worked on wall street building a number of time series kind of platform, trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave. Which means you had to do a ton of work just to start doing work. Which means you had to write a bunch of extrinsic routines, you had to write a bunch of application handling on existing relational databases, in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view. This is not how developers should work. And so in 2013, he went through Y Combinator, and he built something for, he made his first commit to open source InfluxDB in the end of 2013. And he basically, you know from my point of view, he invented modern time series, which is you start with a purpose built time series platform to do these kind of workloads, and you get all the benefits of having something right out of the box. So a developer can be totally productive right away. >> And how many people are in the company? What's the history of employees is there? >> Yeah, I think we're, you know, I always forget the number but something like 230 or 240 people now. I joined the company in 2016, and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. 'Cause if you think about it, what sensors do is they speak time series. Pressure, temperature, volume, humidity, light, they're measuring, they're instrumenting something over time. And so I thought that would be super relevant over the long term, and I've not regretted it. >> Oh no, and it's interesting at that time if you go back in history, you know, the role of database. It's all relational database, the one database to rule the world. And then as cloud started coming in, you started to see more databases proliferate, types of databases. And time series in particular is interesting 'cause real time has become super valuable from an application standpoint. IOT which speaks time series, means something. It's like time matters >> Times yeah. >> And sometimes data's not worth it after the time, sometimes it's worth it. And then you get the data lake, so you have this whole new evolution. Is this the momentum? What's the momentum? I guess the question is what's the momentum behind it? >> You mean what's causing us to grow so fast? >> Yeah the time series, why is time series- >> And the category- >> Momentum, what's the bottom line? >> Well think about it, you think about it from a broad sort of frame which is, what everybody's trying to do is build increasingly intelligent systems. whether it's a self-driving car or a robotic system that does what you want to do, or a self-healing software system. Everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well. And you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened, what's going to happen. And so you get to these applications like predictive maintenance, or smarter systems, and increasingly you want to do that stuff not just intelligently, but fast in real time. So millisecond response, so that when you're driving a self-driving car, and the system realizes that you're about to do something, essentially you want to be able to act in something that looks like real time. All systems want to do that, they want to be more intelligent, and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a market. >> It's interesting near real time isn't good enough when you need real time. >> Yeah, it's not, it's not. And it's like everybody wants real even when you don't need it, ironically you want it. It's like having the feature for, you know you buy a new television, you want that one feature, even though you're not going to use it. You decide that's your buying criteria. Real time is criteria for people. >> So I mean, what you're saying then is near realtime is getting closer to real time as fast as possible? >> Right. >> Okay, so talk about the aspect of data, 'cause we're hearing a lot of conversations on theCUBE in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get know how to fix it. So this is a big part of what we're seeing with people saying, "Hey, you know I want to "make my machine learning algorithms better "after the fact, I want to learn from the data." How do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data, knowing when it happened? >> Well, for sure what you're saying is, is none of this is non-linear, it's all incremental. And so if you take something, you know just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop which is, I instrument it, I watch what happens, oh that's wrong, oh I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car. But every system moves along that evolution. And so you get the dynamic of constantly instrumenting, watching the system behave and do it. And so a self driving car is one thing, but even in the human genome, if you look at some of our customers, you know, people like, people doing solar arrays, people doing power walls like all of these systems are getting smarter and smarter. >> Well, let's get into that. What are the top applications? What are you seeing with InfluxDB, the time series, what's the sweet spot for the application use case and some customers? Give some examples. >> Yeah so it's pretty easy to understand on one side of the equation, that's the physical side is, sensors are getting cheap obviously we know that. The whole physical world is getting instrumented, your home, your car, the factory floor, your wrist watch, your healthcare, you name it, it's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but they're all on that side, they're all about IOT. So they're thinking about consumer IOT kind of projects like Google's Nest, Tudor, particle sensors, even delivery engines like Rappi, who deliver the instant car to South America. Like anywhere there's a physical location and that's on the consumer side. And then another exciting space is the industrial side. Factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational. Because what has to get smarter when you're building a factory is systems all have to get smarter. And then lastly, a lot in the renewables, so sustainability. So a lot, you know, Tesla, Lucid motors, Nicola motors, you know, lots to do with electric cars, solar arrays, windmills arrays, just anything that's going to get instrumented that where that instrumentation becomes part of what the purpose is. >> It's interesting the convergence of physical and digital is happening with the data. IOT you mentioned, you know, you think of IOT, look at the use cases there. It was proprietary OT systems, now becoming more IP enabled, internet protocol. And now edge compute, getting smaller, faster, cheaper. AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? Where's the IOT OT dots connecting to? Because, you know as these two cultures merge, operations basically, industrial, factory, car, they got to get smarter. Intelligent edge is a buzzword but I mean, it has to be more intelligent. Where's the action in all this? >> So the action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the action's really happen at the developer. And so what you're seeing is a movement in the world that maybe you and I grew up in with IT or OT moving increasingly that developer driven capability. And so all of these IOT systems, they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business? What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express themselves? Or am I trying to figure out when the next heart rate monitor is going to show up in my apple watch? Right, what am I trying to do? What's the system I need to build? And so starting with the developer is where all of the good stuff happens here. Which is different than it used to be, right. It used to be you'd buy an application or a service or a SaaS thing for, but with this dynamic, with this integration of systems, it's all about bespoke, it's all about building something. >> So let's get to the developer real quick. Real highlight point here is the data, I mean, I could see a developer saying, "Okay, I need to have an application for the edge," IOT edge or car, I mean we're going to have, I mean Tesla got applications of the car, it's right there. I mean, there's the modern application life cycle now. So take us through how does this impacts the developer. Does it impact their CICD pipeline? Is it cloud native? I mean where does this go to? >> Well, so first of all you're talking about, there was an internal journey that we had to go through as a company which I think is fascinating for anybody that's interested, is we went from primarily a monolithic software that was open sourced to building a Cloud-native platform. Which means we had to move from an agile development environment to a CICD environment. So to degree that you are moving your service, whether it's you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right, to a degree that that service is cloud. Then increasingly we remove from an agile development to a CICD environment, which you're shipping code to production every day. And so it's not just the developers, it's all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also going to happen in a big way. >> When your customer base that you have now, and as you see evolving with in InfluxDB, is it that they're going to be writing more of the application or relying more on others? I mean obviously it's an open source component here. So when you bring in kind of old way, new way, old way was, I got a proprietary platform running all this IOT stuff, and I got to write, here's an application that's general purpose. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does this job. >> A good way to think about this is- >> Versus new way which is what? >> So yeah a good way to think about this is what's the role of the developer/architect, CTO, that chain within a large, with an enterprise or a company. And so the way to think about is I started my career in the aerospace industry. And so when you look at what Boeing does to assemble a plane, they build very very few of the parts. Instead what they do is they assemble. They buy the wings, they buy the engines, they assemble, actually they don't buy the wings. That's the one thing, they buy the material for the wing. They build the wings 'cause there's a lot of tech in the wings, and they end up being assemblers, smart assemblers of what ends up being a flying airplane. Which is a pretty big deals even now. And so what happens with software people is, they have the ability to pull from you know, the best of the open source world. So they would pull a time series capability from us, then they would assemble that with potentially some ETL logic from somebody else. Or they'd assemble it with a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers but they become masters of that bespoke application. And I think that's where it goes 'cause you're not writing native code for everything. >> So they're more flexible, they have faster time to market 'cause they're assembling. >> Way faster. >> And they get to still maintain their core competency, AKA their wings in this case. >> They become increasingly not just coders but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff. By the way, this is not different than the people just up the road. Google have been doing for years or the tier one Amazon building all their own. >> Well, I think one of the things that's interesting is that this idea of a systems developing, a system architecture. I mean systems have consequences when you make changes. So when you have now cloud data center on-premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >> That's exactly, but that's where that Boeing or that airplane building analogy comes in. For us, we've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on prem edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that, you want to make sure at least that base layer, that database layer that those components talk to each other. >> So I'll have to ask you if I'm the customer, I put my customer hat on. Okay, hey, I'm dealing with a lot. >> Does that mean you have a PO for- >> (laughs) A big check, a blank check, if you can answer this question. >> Only if in tech. >> If you get the question right. I got all this important operation stuff, I got my factory, I got my self-driving cars, this isn't like trivial stuff, this is my business. How should I be thinking about time series? Because now I have to make these architectural decisions as you mentioned and it's going to impact my application development. So huge decision point for your customers. What should I care about the most? What's in it for me? Why is time series important? >> Yeah, that's a great question. So chances are, if you've got a business that was 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that, you built something on Oracle, or you built something on IBM's Db2, right, and you made it work within your system. Right, and so that's what you started building. So it's already out there, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time, I hate the word, but digital transformation. Then you start with time series, it's a foundational base layer for any system that you're going to build. There's no system I can think of where time series shouldn't be the foundational base layer. If you just want to store your data and just leave it there and then maybe look it up every five years, that's fine. That's not time series. Time series is when you're building a smarter more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems the more obvious it becomes. >> And since I have a PO for you and a big check. >> Yeah. >> What's the value to me when I implement this? What's the end state? What's it look like when it's up and running? What's the value proposition for me? What's in it for me? >> So when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, the transforming it in near real time. So that the other dependencies that a system it gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's doing every action that's above, but it's foundational to build a really compelling intelligence system. I think that's what developers and architects are seeing now. >> Bottom line, final word, what's in it for the customer? What's your statement to the customer? What would you say to someone looking to do something in time series and edge? >> Yeah so it's pretty clear to us that if you're building, if you view yourself as being in the business of building systems, that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time, that you start from time series. But I also want to say what's in it for us, Influx. What's in it for us is, people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare, it's hard not to be proud or feel like, "Wow." >> Yeah. >> "Somehow I've been lucky, I've arrived at the right time, "in the right place with the right people "to be able to deliver on that." That's also exciting on our side of the equation. >> Yeah, it's critical infrastructure, critical of operations. >> Yeah. >> Great stuff. Evan thanks for coming on, appreciate this segment. All right, in a moment, Brian Gilmore director of IOT and emerging technology at InfluxData will join me. You're watching theCUBE, leader in tech coverage. Thanks for watching. (upbeat music)

>>Welcome back to the cubes coverage of Couchbase connect online, where the theme of the event is, or is modernized now. Yes, let's talk about that. And with me is Ravi, who's the senior vice president of engineering and the CTO at Couchbase Ravi. Welcome. Great to see you. >>Thank you so much. I'm so glad to be here with you. >>I asked you what the new requirements are around modern applications. I've seen some, you know, some of your comments, you gotta be flexible, distributed, multimodal, mobile edge. It, that those are all the very cool sort of buzz words, smart applications. What does that all mean? And how do you put that into a product and make it real? >>Yeah, I think what has basically happened is that, uh, so far, uh, it's been a transition of sorts. And now we are come to a point where, uh, the tipping point and the tipping point has been, uh, uh, more because of COVID and there COVID has pushed us to a world where we are living, uh, in a sort of, uh, occasionally connected manner where our digital, uh, interactions, precede our physical interactions in one sense. So it's a world where we do a lot more stuff that's less than, uh, in a digital manner, as opposed to sort of making a more specific human contact that has really been the, uh, sort of accelerant to this modernized. Now, as a team in this process, what has happened is that so far all the databases and all the data infrastructure that we have built historically, are all very centralized. >>They're all sitting behind. Uh, they used to be in mainframes from where they came to like your own data centers, where we used to run hundreds of servers to where they're going now, which is the computing marvelous change to consumption-based computing, which is all cloud oriented now. And so, uh, but they are all centralized still. Uh, but where our engagement happens with the data is, uh, at the edge, uh, at your point of convenience at your point of consumption, not where the data is actually sitting. So this has led to, uh, you know, all those buzzwords, as you said, which is like, oh, well we need a distributed data infrastructure, where is the edge? Uh, but it just basically comes down to the fact that the data needs to be where you are engaging with it. And that means if you are doing it on your mobile phone, or if you are sitting, uh, doing something in your body or traveling, or whether you are in a subway, whether you're in a plane or a ship, wherever the data needs to come to you, uh, and be available as opposed to every time you going to the data, which is centrally sitting in some place. >>And that is the fundamental shift in terms of how the modern architecture needs to think, uh, when they, when it comes to digital transformation and, uh, transitioning their old applications to, uh, the, the modern infrastructure, because that's, what's going to define your customer experiences and your personalized experiences. Uh, otherwise people are basically waiting for that circle of death that we all know, uh, and blaming the networks and other pieces. The problem is actually, the data is not where you are engaging with. It has got to be fetched, you know, seven seas away. Um, and that is the problem that we are basically solving in this modern modernization of that data, data infrastructure. >>I love this conversation and I love the fact that there's a technical person that can kind of educate us on, on this, because date data by its very nature is distributed. It's always been distributed, but w w but distributed database has always been incredibly challenging, whether it was a global SIS Plex or an eventual consistency of getting recovery for a distributed architecture has been extremely difficult. You know, I hate that this is a terrible term, lots of ways to skin a cat, but, but you've been the visionary behind this notion of optionality, how to solve technical problems in different ways. So how do you solve that, that problem of, of, of, uh, of, uh, of a super rock solid database that can handle, you know, distributed data? Yes. >>So there are two issues that you're a little too over there with Forrest is the optionality piece of it, which is that same data that you have that requires different types of processing on it. It's almost like fractional distillation. It is, uh, like your crude flowing through the system. You start all over from petrol and you can end up with Vaseline and rayon on the other end, but the raw material, that's our data in one sense. So far, we never treated the data that way. That's part of the problem. It has always been very purpose built and cast first problem. And so you just basically have to recast it every time we want to look at the data. The first thing that we have done is make data that fluid. So when you're actually, uh, when you have the data, you can first look at it to perform. >>Let's say a simple operation that we call as a key value store operation. Given my ID, give him a password kind of scenarios, which is like, you know, there are customers of ours who have billions of user IDs in their management. So things get slower. How do you make it fast and easily available? Log-in should not take more than five minutes. Again, this is a, there's a class of problem that we solve that same data. Now, eventually, without you ever having to, uh, sort of do a casting it to a different database, you can now do a solid, uh, acquire. These are classic sequel queries, which is our next magic. We are a no SQL database, but we have a full functional sequel. The sequel has been the language that has talked to data for 40 odd years successfully. Every other database has come and try to implement their own QL query language, but they've all failed only sequel as which stood the test of time of 40 odd years. >>Why? Because there's a solid mathematics behind it. It's called a relational calculus. And what that helps you is, is, uh, basically, uh, look at the data and any common tutorial, uh, any, uh, any which way you look at the data. All it will come, uh, the data in a format that you can consume. That's the guarantee sort of gives you in one sense. And because of that, you can now do some really complex in the database signs, what we call us, predicate logic on top of that. And that gives you the ability to do the classic relational type queries, select star from where Canada stuff, because it's at an English level, it becomes easy to, so the same data, you didn't have to go move it to another database, do your, uh, sort of transformation of the data and all this stuff. Same day that you do this. >>Now, that's where the optionality comes in. Now you can do another piece of logic on top of this, which we call search. This is built on this concept of inverted index and TF IDF, the classic Google in a very simple terms, but Google tokenized search, you can do that in the same data without you ever having to move the data to a different format. And then on top of it, they can do what is known as a eventing or your own custom logic, which we all which we do on a, on programming language called Java script. And finally analytics and analytics is the ability to query the operational data in a different way. I'll talk budding. What was my sales of this widget year over year on December 1st week, that's a very complex question to ask, and it takes a lot of different types of processing. >>So these are different types of that's optionality with different types of processing on the same data without you having to go to five different systems without you having to recast the data in five different ways and find different application logic. So you put them in one place. Now is your second question. Now this has got to be distributed and made available in multiple cloud in your data center, all the way to the edge, which is the operational side of the, uh, the database management system. And that's where the distributed, uh, platform that we have built enables us to get it to where you need the data to be, you know, in a classic way, we call it CDN in the data as in like content delivery networks. So far do static, uh, uh, sort of moving of static content to the edges. Now we can actually dynamically move the data. Now imagine the richness of applications you can develop. >>The first part of the, the answer to my question, are you saying you could do this without skiing with a no schema on, right? And then you can apply those techniques. >>Uh, fantastic question. Yes. That's the brilliance of this database is that so far classically databases have always demanded that you first define a schema before you can write a single byte of data. Couchbase is one of the rare databases. I, for one don't know any other one, but there could be, let's give the benefit of doubt. It's a database which writes data first and then late binds to schema as we call it. It's a schema on read things. So because there is no schema, it is just a on document that is sitting inside. And Jason is the lingua franca of the web, as you very well know by now. So it just Jason that we manage, you can do key lookups of the Jason. You can do full credit capability, like a classic relational database. We even have cost-based optimizers and the other sophisticated pieces of technology behind it. >>You can do searching on it, using the, um, the full textual analysis pipeline. You can do ad hoc wedding on the analytic side, and you can write your own custom logic on it using our eventing capabilities. So that's, that's what it allows because we keep the data in the native form of Jason. It's not a data structure or a data schema imposed by a database. It is how the data is produced. And on top of it, we bring different types of logic, five different types of it's like the philosophy is bringing logic to data as opposed to moving data to logic. This is what we have been doing, uh, in the last 40 years because we developed various, uh, database systems and data processing systems of various points. In time in our history, we had key value stores. We had relational systems, we had search systems, we had analytical systems. >>We had queuing systems, all the systems, if you want to use any one of them, our answer has always been, just move the data to that system. Versus we are saying that do not move the data as we get bigger and bigger and data just moving this data is going to be a humongous problem. If you're going to be moving petabytes of data for this is not one to fly instead, bring the logic to the data. So you can now apply different types of logic to the data. I think that's what, in one sense, the optionality piece of this, >>As you know, there's plenty of schema-less data stores. They're just, they're called data swamps. I mean, that's what they, that's what they became, right? I mean, so this is some, some interesting magic that you're applying here. >>Yes. I mean, the one problem with the data swamps as you call them is that that was a little too open-ended because the data format itself could change. And then you do your, then everything became like a game data casting because it required you to have it in seven schema in one sense at the end of the day, for certain types of processing. So in that where a lot of gaps it's probably flooded, but it not really, uh, how do you say, um, keep to the promise that it actually meant to be? So that's why it was a swamp I need, because it was fundamentally not managing the data. The data was sitting in some file system, and then you are doing something, this is a classic database where the data is managed and you create indexes to manage it, and you create different types of indexes to manage it. You distribute the index, you distribute the data you have, um, like we were discussing, you have acid semantics on top of, and when you, when you put all these things together, uh, it's, it's, it's a tough proposition, but they have solved some really tough problems, which are good computer science stuff, computer science problems that we have to solve to bring this, to bring this, to bear, to bring this to the market. >>So you predicted the trend around multimodal and converged, uh, databases. Um, you kind of led Couchbase through that. I want to, I always ask this question because it's clearly a trend in the industry and it, it definitely makes sense from a simplification standpoint. And, and, and so that I don't have to keep switching databases or the flip side of that though, Ravi. And I wonder if you could give me your opinion on this is kind of the right tool for the right job. So I often say isn't that the Swiss army knife approach, we have a little teeny scissors and a knife. That's not that sharp. How do you respond to that? Uh, >>A great one. Um, my answer is always, I use another analogy to tackle that, but is that, have you ever accused a smartphone of being a Swiss army knife? No. No. Nobody does that because it's actually 40 functions in one is what a smartphone becomes. You never call your iPhone or your Android phone, a Swiss army knife, because here's the reason is that you can use that same device in the full capacity. That's what optionality is. It's not, I'm not, it's not like your good old one where there's a keyboard hiding half the screen, and you can do everything only through the keyboard without touching and stuff like that. That's not the whole devices available to you to do one type of processing when you want it. When you're done with that, it can do another completely different types of processing. Like as in a moment, it could be a Tom, Tom telling you all the directions, the next one, it's your PDA. >>Third one, it's a fantastic phone. Uh, four, it's a beautiful camera, which can do your f-stop management and give you a nice SLR quality picture. Right? So next moment is a video camera. People are shooting movies with this thing in Hollywood, these days for God's sake. So it gives you the full power of what you want to do when you want it. And now, if you just taught that iPhone is a great device or any smartphone is a great device, because you can do five things in one or 50 things in one, and at a certain level, they missed the point because what that device really enabled is not just these five things in one place. It becomes easy to consume and easy to operate. It actually started the app is the economy. That's the brilliance of bringing so many things in one place, because in the morning, you know, I get the alert saying that today you got to leave home at eight 15 for your nine o'clock meeting. >>And the next day it might actually say 8 45 is good enough because it knows where the phone is sitting. The geo position of it. It knows from my calendar where the meeting is actually happening. It can do a traffic calculation because it's got my map and all of the routes. And then it's gone there's notification system, which eventually pops up on my phone to say, Hey, you got to leave at this time. Now five different systems have to come together and they can because the data is in one place without that, you couldn't even do this simple function, uh, in a, in a sort of predictable manner in a, in a, in a manner that's useful to you. So I believe a database which gives you this optionality of doing multiple data processing on the same set of data allows you will allow you to build a class of products, which you are so far been able to struggling to build, because half the time you're running sideline to sideline, just, you know, um, integrating data from one system to the other. >>So I love the analogy with the smartphone. I w I want to, I want to continue it and double click on it. So I use this camera. I used to, you know, my kid had a game. I would bring the, the, the big camera, the 35 millimeter. So I don't use that anymore no way, but my wife does, she still uses the DSLR. So is, is there a similar analogy here? That those, and by the way, the camera, the camera shop in my town went out of business, you know? And so, so, but, but is there, is that a fair, where, in other words, those specialized databases, they say there still is a place for them, but they're getting >>Absolutely, absolutely great analogy and a great extension to the question. That's, that's the contrarian side of it in one sense is that, Hey, if everything can just be done in one, do you have a need for the other things? I mean, you gave a camera example where it is sort of, it's a, it's a slippery slope. Let me give you another one, which is actually less straight to the point better. I've been just because my, I, I listened to half of the music on the iPhone. Doesn't stop me from having my full digital receiver. And, you know, my Harman Kardon speakers at home because they haven't, they produce a kind of sounded immersive experience. This teeny little speaker has never in its lifetime intended to produce, right? It's the convenience. Yes. It's the convenience of convergence that I can put my earphones on and listen to all the great music. >>Yes, it's 90% there or 80% there. It depends on your audio file mess of your, uh, I mean, you don't experience the super specialized ones do not go away. You know, there are, there are places where, uh, the specialized use cases will demand a separate system to exist, but even there that has got to be very closed. Um, how do you say close, binding or late binding? I should be able to stream that song from my phone to that receiver so I can get it from those speakers. You can say that, oh, there's a digital divide between these two things done, and I can only play CDs on that one. That's not how it's going to work going forward. It's going to be, this is the connected world, right? As in, if I'm listening to the song in my car and then step off the car and walk into my living room, that's same songs should continue and play in my living room speakers. Then it's a world because it knows my preference and what I'm doing that all happened only because of this data flowing between all these systems. >>I love, I love that example too. When I was a kid, we used to go to Twitter, et cetera. And we'd to play around with, we take off the big four foot speakers. Those stores are out of business too. Absolutely. Um, now we just plug into Sonos. So that is the debate between relational and non-relational databases over Ravi. >>I believe so. Uh, because I think, uh, what had happened was the relational systems. Uh, I've been where the norm, they rule the roost, if you will, for the last 40 odd years, and then gain this no sequel movement, which was almost as though a rebellion from the relational world, we all inhibited, uh, uh, because we, it was very restrictive. It, it had the schema definition and the schema evolution as we call it, all those things, they were like, they required a committee, they required your DBA and your data architect. And you have to call them just to add one column and stuff like that. And the world had moved on. This was the world of blogs and tweets and, uh, you know, um, mashups and, um, uh, uh, a different generation of digital behavior, digital, native people now, um, who are operating in these and the, the applications, the, the consumer facing applications. >>We are living in this world. And yet the enterprise ones were still living in the, um, in the other, the other side of the divide. So all came this solution to say that we don't need SQL. Actually, the problem was never sequel. No sequel was, you know, best approximation, good marketing name, but from a technologist perspective, the problem was never the query language, no SQL was not the problem, the schema limitations, and the inability for these, the system to scale, the relational systems were built like, uh, airplanes, which is that if, uh, San Francisco Boston, there is a flight route, it's so popular that if you want to add 50 more seats to it, the only way you can do that is to go back to Boeing and ask them to get you a set in from 7 3 7 2 7 7 7, or whatever it is. And they'll stick you with a billion dollar bill on the alarm to somehow pay that by, you know, either flying more people or raising the rates or whatever you have to do. >>These are called vertically scaling systems. So relational systems are vertically scaling. They are expensive. Versus what we have done in this modern world, uh, is make the system how it is only scaling, which is more like the same thing. If it's a train that is going from San Francisco to Boston, you need 50 more people be my guests. I'll add one more coach to it, one more car to it. And the better part of the way we have done this year is that, and we have super specialized on that. This route actually requires three, three dining cars and only 10 sort of sleeper cars or whatever. Then just pick those and attach the next route. You can choose to have ID only one dining car. That's good enough. So the way you scale the plane is also can be customized based on the route along the route, more, more dining capabilities, shorter route, not an abandoned capability. >>You can attach the kind of coaches we call this multi-dimensional scaling. Not only do we scale horizontally, we can scale to different types of workloads by adding different types of coaches to it quite. So that's the beauty of this architecture. Now, why is that important? Is that where we land eventually is the ability to do operational and analytical in the same place. This is another thing which doesn't happen in the past, because you would say that I cannot run this analytical Barre because then my operational workload will suffer. Then my friend, then we'll slow down millions of customers that impacted that problem. We will solve the same data in which you can do analytical buddy, an operational query because they're separated by these cars, right? As in like we, we fence the, the, the resources, so that one doesn't impede the other. So you can, at the same time, have a microsecond 10 million ops per second, happening of a key value or equity. >>And then yet you can run this analytical body, which will take a couple of minutes to run one, not impeding the other. So that's in one sense, sort of the, part of the, um, uh, problems that we have solved here is that relational versus, uh, uh, the no SQL portion of it. These are the kinds of problems we have to solve. We solve those. And then we yet put back the same quality language on top. Y it's like Tesla in one sense, right underneath the surface is where all the stuff that had to be changed had to change, which is like the gasoline, uh, the internal combustion engine, uh, I think gas, uh, you says, these are the issues we really wanted to solve. Um, so solve that, change the engine out, you don't need to change the steering wheel or the gas pedal or the, you know, the battle shifters or whatever else you need, or that are for your shifters. >>Those need to remain in the same place. Otherwise people won't buy it. Otherwise it does not even look like a car to people. So, uh, even when you feed people the most advanced technology, it's got to be accessible to them in the manner that people can consume. Only in software, we forget this first design principle, and we go and say that, well, I got a car here, you got the blue harder to go fast and lean back for, for it to, you know, uh, to apply a break that's, that's how we seem to define, uh, design software. Instead, we should be designing them in a manner that it is easiest for our audience, which is developers to consume. And they've been using SQL for 40 years or 30 years. And so we give them the steering wheel on the, uh, and the gas bottle and the, um, and the gear shifter is by putting cul back on underneath the surface, we have completely solved, uh, the relational, uh, uh, limitations of schema, as well as scalability. >>So in, in, in that way, and by bringing back the classic acid capabilities, which is what relational systems, uh, we accounted on and being able to do that with the sequel programming language, we call it like multi-state SQL transaction. So to say, which is what a classic way all the enterprise software was built by putting that back. Now, I can say that that debate between relational and non-relational is over because this has truly extended the database to solve the problems that the relational systems had to grow up the salt in the modern times, but rather than get, um, sort of pedantic about whether it's, we have no SQL or sequel or new sequel, or, uh, you know, any of that sort of, uh, jargon, oriented debate, uh, this, these are the debates of computer science that they are actually, uh, and they were the solve and they have solved them with, uh, the latest release of $7, which we released a few months ago. >>Right, right. Last July, Ravi, we got to leave it there. I, I love the examples and the analogies. I can't wait to be face to face with you. I want to hang with you at the cocktail party because I've learned so much and really appreciate your time. Thanks for coming to the cube. >>Fantastic. Thanks for the time. And the Aboriginal Dan was, I mean, very insightful questions really appreciate it. Thank you. >>Okay. This is Dave Volante. We're covering Couchbase connect online, keep it right there for more great content on the cube.

>> Welcome back to the cubes coverage of Couchbase connect online, where the theme of the event is, is modernize now. Yes, let's talk about that. And with me is Ravi mayor him, who's the senior vice president of engineering and the CTO at Couchbase Ravi. Welcome. Great to see you. >> Thank you so much. I'm so glad to be here with you. >> I want to ask you what the new requirements are around modern applications. I've seen some of your comments, you got to be flexible, distributed, multimodal, mobile, edge. Those are all the very cool sort of buzz words, smart applications. What does that all mean? And how do you put that into a product and make it real? >> Yeah, I think what has basically happened is that so far it's been a transition of sorts. And now we are come to a point where that tipping point and that tipping point has been more because of COVID and there are COVID has pushed us to a world where we are living in a in a sort of occasionally connected manner where our digital interactions precede, our physical interactions in one sense. So it's a world where we do a lot more stuff that's less than in a digital manner, as opposed to sort of making a more specific human contact. That does really been the sort of accelerant to this modernize Now, as a team. In this process, what has happened is that so far all the databases and all the data infrastructure that we have built historically, are all very centralized. They're all sitting behind. They used to be in mainframes from where they came to like your own data centers, where we used to run hundreds of servers to where they're going now, which is the computing marvelous change to consumption-based computing, which is all cloud oriented now. And so, but they are all centralized still, but where our engagement happens with the data is at the edge at your point of convenience, at your point of consumption, not where the data is actually sitting. So this has led to, you know, all those buzzwords, as you said, which is like, oh, well we need a distributed data infrastructure, where is the edge? But it just basically comes down to the fact that the data needs to be there, if you are engaging with it. And that means if you are doing it on your mobile phone, or if you're sitting, but doing something in your while you're traveling, or whether you're in a subway, whether you're in a plane or a ship, wherever the data needs to come to you and be available, as opposed to every time you going to the data, which is centrally sitting in some place. And that is the fundamental shift in terms of how the modern architecture needs to think when they, when it comes to digital transformation and, transitioning their old applications to the, the modern infrastructure, because that's, what's going to define your customer experiences and your personalized experiences. Otherwise, people are basically waiting for that circle of death that we all know, and blaming the networks and other pieces. The problem was actually, the data is not where you are engaging with it. It's got to be fetched, you know, seven sea's away. And that is the problem that we are basically solving in this modern modernization of that data, data infrastructure. >> I love this conversation and I love the fact that there's a technical person that can kind of educate us on, on this because date data by its very nature is distributed. It's always been distributed, but with the distributed database has always been incredibly challenging, whether it was a global SIS Plex or an eventual consistency of getting recovery for a distributed architecture has been extremely difficult. You know, I hate that this is a terrible term, lots of ways to skin a cat, but, but you've been the visionary behind this notion of optionality, how to solve technical problems in different ways. So how do you solve that, that problem of, of, of, of, of a super rock solid database that can handle, you know, distributed data? >> Yes. So there are two issues that you alluded little too over there. The first is the optionality piece of it, which is that same data that you have that requires different types of processing on it. It's almost like fractional distillation. It is like your crude flowing through the system. You start all over from petrol and you can end up with Vaseline and rayon on the other end, but the raw material, that's our data. In one sense. So far, we never treated the data that way. That's part of the problem. It has always been very purpose built and cast first problem. And so you just basically have to recast it every time we want to look at the data. The first thing that we have done is make data that fluid. So when you're actually, when you have the data, you can first look at it to perform. Let's say a simple operation that we call as a key value store operation. Given my ID, give him a password kind of scenarios, which is like, you know, there are customers of ours who have billions of user IDs in their management. So things get slower. How do you make it fast and easily available? Log-in should not take more than five milliseconds, this is, this is a class of problem that we solve that same data. Now, eventually, without you ever having to sort of do a casting it to a different database, you can now do solid queries. Our classic SQL queries, which is our next magic. We are a no SQL database, but we have a full functional SQL. The SQL has been the language that has talked to data for 40 odd years successfully. Every other database has come and tried to implement their own QL query language, but they've all failed only SQL has stood the test of time of 40 odd years. Why? Because there's a solid mathematics behind it. It's called a relational calculus. And what that helps you is, is basically a look at the data and any common editorial, any, any which way you look at the data, all it will come, the data in a format that you can consume. That's the guarantee sort of gives you in one sense. And because of that, you can now do some really complex in the database signs, what we call us, predicate logic on top of that. And that gives you the ability to do the classic relational type queries select star from where, kind of stuff, because it's at an English level becomes easy to so the same day that you didn't have to go move it to another database, do your sort of transformation of the data and all the stuff, same day that you do this. Now that's where the optionality comes in. Now you can do another piece of logic on top of this, which we call search. This is built on this concept of inverted index and TF IDF, the classic Google in a very simple terms, what Google tokenized search, you can do that in the same data without you ever having to move the data to a different format. And then on top of it, they can do what is known as a eventing or your own custom logic, which we all which we do on a, on programming language called Java script. And finally analytics and analytics is the, your ability to query the operational data in a different way. And talk querying, what was my sales of this widget year over year on December 1st week, that's a very complex question to ask, and it takes a lot of different types of processing. So these are different types of that's optionality with different types of processing on the same data without you having to go to five different systems without you having to recast the data in five different ways and apply different application logic. So you put them in one place. Now is your second question. Now this has got to be distributed and made available in multiple cloud in your data center, all the way to the edge, which is the operational side of the, the database management system. And that's where the distributed platform that we have built enables us to get it to where you need the data to be, you know, in the classic way we call it CDN'ing the data as in like content delivery networks. So far do static, sort of moving of static content to the edges. Now we can actually dynamically move the data. Now imagine the richness of applications you can develop. >> And on the first part of, of the, the, the answer to my question, are you saying you could do this without scheme with a no schema on, right? And then you can apply those techniques. >> Fantastic question. Yes. That's the brilliance of this database is that so far classically databases have always demanded that you first define a schema before you can write a single byte of data. Couchbase is one of the rare databases. I, for one don't know any other one, but there could be, let's give the benefit of doubt. It's a database which writes data first and then late binds to schema as we call it. It's a schema on read thing. So, because there is no schema, it is just a Json document that is sitting inside. And Json is the lingua franca of the web, as you very well know by now. So it just Json that we manage, you can do key value look ups of the Json. You can do full credit capability, like a classic relational database. We even have cost-based optimizers and other sophisticated pieces of technology behind it. You can do searching on it, using the, the full textual analysis pipeline. You can do ad hoc webbing on the analytics side, and you can write your own custom logic on it using or inventing capabilities. So that's, that's what it allows because we keep the data in the native form of Json. It's not a data structure or a data schema imposed by a database. It is how the data is produced. And on top of it, bring, we bring different types of logic, five different types of it's like the philosophy is bringing logic to data as opposed to moving data to logic. This is what we have been doing in the last 40 years, because we developed various database systems and data processing systems at various points in time in our history, we had key value stores. We had relational systems, we had search systems, we had analytical systems. We had queuing systems, all these systems, if you want to use any one of them are answered. It always been, just move the data to that system. Versus we are saying that do not move the data as we get bigger and bigger and data just moving this data is going to be a humongous problem. If you're going to be moving petabytes of data for this, it's not going to fly instead, bring the logic to the data, right? So you can now apply different types of logic to the data. I think that's what, in one sense, the optionality piece of this. >> But as you know, there's plenty of schema-less data stores. They're just, they're called data swamps. I mean, that's what they, that's what they became, right? I mean, so this is some, some interesting magic that you're applying here. >> Yes. I mean, the one problem with the data swamps as you call them is that that was a little too open-ended because the data format itself could change. And then you do your, then everything became like a game data recasting because it required you to have it in seven schema in one sense at, at the end of the day, for certain types of processing. So in that where a lot of gaps it's probably related, but it not really, how do you say keep to the promise that it actually meant to be? So that's why it was a swamp I mean, because it was fundamentally not managing the data. The data was sitting in some file system, and then you are doing something, this is a classic database where the data is managed and you create indexes to manage it. And you create different types of indexes to manage it. You distribute the index, you distribute the data you have, like we were discussing, you have ACID semantics on top of, and when you, when you put all these things together, it's, it's, it's a tough proposition, but we have solved some really tough problems, which are good computer science stuff, computer science problems that we have to solve to bring this, to bring this, to bear, to bring this to the market. >> So you predicted the trend around multimodal and converged databases. You kind of led Couchbase through that. I, I want, I always ask this question because it's clearly a trend in the industry and it, and it definitely makes sense from a simplification standpoint. And, and, and so that I don't have to keep switching databases or the flip side of that though, Ravi. And I wonder if you could give me your opinion on this is kind of the right tool for the right job. So I often say isn't that the Swiss army knife approach, where you have have a little teeny scissors and a knife, that's not that sharp. How, how do you respond to that? >> A great one. My answer is always, I use another analogy to tackle that, and is that, have you ever accused a smartphone of being a Swiss army knife? - No. No. >> Nobody does. That because it actually 40 functions in one is what a smartphone becomes. You never call your iPhone or your Android phone, a Swiss army knife, because here's the reason is that you can use that same device in the full capacity. That's what optionality is. It's not, I'm not, it's not like your good old one where there's a keyboard hiding half the screen, and you can do everything only through the keyboard without touching and stuff like that. That's not the whole devices available to you to do one type of processing when you want it. When you're done with that, it can do another completely different types of processing. Right? As in a moment, it could be a TomTom, telling you all the directions, the next one, it's your PDA. Third one. It's a fantastic phone. Four. It's a beautiful camera which can do your f-stop management and give you a nice SLR quality picture. Right? So next moment, it's the video camera. People are shooting movies with this thing in Hollywood, these days for God's sake. So it gives you the full power of what you want to do when you want it. And now, if you just thought that iPhone is a great device or any smartphone is a great device, because you can do five things in one or 50 things in one, and at a certain level, he missed the point because what that device really enabled is not just these five things in one place. It becomes easy to consume and easy to operate. It actually started the app based economy. That's the brilliance of bringing so many things in one place, because in the morning, you know, I get an alert saying that today you got to leave home at >> 8: 15 for your nine o'clock meeting. And the next day it might actually say 8 45 is good enough because it knows where the phone is sitting. The geo position of it. It knows from my calendar where the meeting is actually happening. It can do a traffic calculation because it's got my map and all of the routes. And then it's got this notification system, which eventually pops up on my phone to say, Hey, you got to leave at this time. Now five different systems have to come together and they can because the data is in one place. Without that, you couldn't even do this simple function in a, in a sort of predictable manner in a, in a, in a manner that's useful to you. So I believe a database which gives you this optionality of doing multiple data processing on the same set of data allows you will allow you to build a class of products, which you are so far been able to struggling to build. Because half the time you're running sideline to sideline, just, you know, integrating data from one system to the other. >> So I love the analogy with the smartphone. I want to, I want to continue it and double click on it. So I use this camera. I used to, you know, my kid had a game. I would bring the, the, the big camera, the 35 millimeter. So I don't use that anymore no way, but my wife does, she still uses the DSLR. So is, is there a similar analogy here? That those, and by the way, the camera, the camera shop in my town went out of business, you know? So, so, but, but is there, is that a fair and where, in other words, those specialized databases, they say there still is a place for them, but they're getting. >> Absolutely, absolutely great analogy and a great extension to the question. That's like, that's the contrarian side of it in one sense is that, Hey, if everything can just be done in one, do you have a need for the other things? I mean, you gave a camera example where it is sort of, it's a, it's a slippery slope. Let me give you another one, which is actually less straight to the point better. I've been just because my, I, I listened to half of my music on the iPhone. Doesn't stop me from having my full digital receiver. And, you know, my Harman Kardon speakers at home because they, I mean, they produce a kind of sounded immersive experience. This teeny little speaker has never in its lifetime intended to produce, right? It's the convenience. Yes. It's the convenience of convergence that I can put my earphones on and listen to all the great music. Yes, it's 90% there or 80% there. It depends on your audio file-ness of your, I mean, your experience super specialized ones do not go away. You know, there are, there are places where the specialized use cases will demand a separate system to exist. But even there that has got to be very closed. How do you say close, binding or late binding? I should be able to stream that song from my phone to that receiver so I can get it from those speakers. You can say that all, there's a digital divide between these two things done, and I can only play CDs on that one. That's not how it's going to work going forward. It's going to be, this is the connected world, right? As in, if I'm listening to the song in my car and then step off the car, walk into my living room, that same songs should continue and play in my living room speakers. Then it's a connected world because it knows my preference and what I'm doing that all happened only because of this data flowing between all these systems. >> I love, I love that example too. When I was a kid, we used to go to Tweeter, et cetera. And we used to play around with three, take home, big four foot speakers. Those stores are out of business too. Absolutely. And now we just plug into Sonos. So that is the debate between relational and non-relational databases over Ravi? >> I believe so, because I think what had happened was relational systems. I've mean where the norm, they rule the roost, if you will, for the last 40 odd years and then gain this no SQL movement, which was almost as though a rebellion from the relational world, we all inhabited because we, it was very restrictive. It, it had the schema definition and the schema evolution as we call it, all those things, they were like, they required a committee. They required your DBA and your data architect. And you had to call them just to add one column and stuff like that. And the world had moved on. This was a world of blogs and tweets and, you know, mashups and a different generation of digital behavior, There are digital, native people now who are operating in these and the, the applications, the, the consumer facing applications. We are living in this world. And yet the enterprise ones were still living in the, in the other, the other side of the divide. So out came this solution to say that we don't need SQL. Actually the problem was never SQL. No SQL was, you know, best approximation, good marketing name, but from a technologist perspective, the problem was never the query language, no SQL was not the problem, the schema limitations and the inability for these, the system to scale, the relational systems were built like airplanes, which is that if a San Francisco, Boston, there is a flight route, it's so popular that if you want to add 50 more seats to it, the only way you can do that is to go back to Boeing and ask them to get you a set from 7 3 7 2 7 7 7, or whatever it is. And they'll stick you with a billion dollar bill on the allowance that you'll somehow pay that by, you know, either flying more people or raising the rates or whatever you have to do. These are all vertically scaling systems. So relational systems are vertically scaling. They are expensive. Versus what we have done in this modern world is make the system horizontally scaling, which is more like the same thing. If it's a train that is going from San Francisco to Boston, you need 50 more people be my guest. I'll add one more coach to it, one more car to it. And the better part of the way we have done this here is that, and we are super specialized on that. This route actually requires three, three dining cars and only 10 sort of sleeper cars or whatever. Then just pick those and attach the next route. You can choose to have, I need only one dining car. That's good enough. So the way you scale the plane is also can be customized based on the route along the route, more, more dining capabilities, shorter route, not an abandoned capability. You can attach the kind of coaches we call this multidimensional scaling. Not only do we scale horizontally, we can scale to different types of workloads by adding different types of coaches to it, right? So that's the beauty of this architecture. Now, why is that architecture important? Is that where we land eventually is the ability to do operational and analytical in the same place. This is another thing which doesn't happen in the past, because, you would say that I cannot run this analytical query because then my operational workload will suffer. Then my front end, then we'll slow down millions of customers that impacted that problem. They'll solve the same data once again, do analytical query, an operational query because they're separated by these cars, right? As in like we, we, we fence the, the, the resources so that one doesn't impede the other. So you can, at the same time, have a microsecond 10 million ops per second, happening of a key value or a query. And then yet you can run this analytical query, which will take a couple of minutes to them. One, not impeding the other. So that's in one sense, sort of the part of the problems that we have solved it here is that relational versus the no SQL portion of it. These are the kinds of problems we have to solve. We solve those. And then we yet put back the same query language on top. Why? It's like Tesla in one sense, right underneath the surface is where all the stuff that had to be changed had to change, which is like the gasoline, the internal combustion engine the gas, you says, these were the issues we really wanted to solve. So solve that, change the engine out, you don't need to change the steering wheel or the gas pedal or the, you know, the battle shifters or whatever else you need, over there your gear shifters. Those need to remain in the same place. Otherwise people won't buy it. Otherwise it does not even look like a car to people. So even when you feed people, the most advanced technology, it's got to be accessible to them in the manner that people can consume. Only in software, we forget this first design principle, and we go and say that, well, I got a car here, you got the blow harder to go fast. And they lean back for, for it to, you know, to apply a break that's, that's how we seem to define design software. Instead, we shouldn't be designing them in a manner that it is easiest for our audience, which is developers to consume. And they've been using SQL for 40 years or 30 years. And so we give them the steering wheel on the, and the gas pedal and the, and the gear shifters by putting SQL back on underneath the surface, we have completely solved the relational limitations of schema, as well as scalability. So in, in, in that way, and by bringing back the classic ACID capabilities, which is what relational systems we accounted on, and being able to do that with the SQL programming language, we call it like multi-statement SQL transaction. So to say, which is what a classic way all the enterprise software was built by putting that back. Now, I can say that that debate between relational and non-relational is over because this has truly extended the database to solve the problems that the relational systems had to grow up to solve in the modern times, rather than get sort of pedantic about whether it's we have no SQL or SQL or new SQL, or, you know, any of that sort of jargon oriented debate. This is, these are the debates of computer science that they are actually, and they were the solve, and they have solved them with the latest release of 7.0, which we released a few months ago. >> Right, right. Last July, Ravi, we got got to leave it there. I love the examples and the analogies. I can't wait to be face-to-face with you. I want to hang with you at the cocktail party because I've learned so much and really appreciate your time. Thanks for coming to the cube. >> Fantastic. Thanks for the time. And the opportunity I was, I mean, very insightful questions really appreciate it. - Thank you. >> Okay. This is Dave Volante. We're covering Couchbase connect online, keep it right there for more great content on the cube.

(digital music) >> Welcome to this CUBE Conversation. I'm Lisa Martin. Bren Briggs, joins me next, the Director of DevOps and Cybersecurity at Hypergiant. Bren, welcome to theCUBE. >> Hey there, I'm glad to be here. >> You have a very cool background, which I wish we had time to get into your mandolin playing, but we don't. Tell me a little bit about Hypergiant this is a company that's new to me? >> So we are an AI and Machine Learning Company, and we had the slogan we talked about a lot, it's almost tongue in cheek, "Tomorrowing Today" where we want to build and focus on technology that advances the state-of-the-art and we want to, where this deep history and background in services, where we build custom solutions for companies that have data problems and that have AI and machine learning problems. And they come to us and we help them make sense of their data and we build a custom software solution from top to bottom. And we help them with their data problems and their really difficult problems that they have there in a very specialized way. And yeah, that's what we do. It's really fun. >> "Tomorrowing Today", I like that build T-shirts with that on that. (Bren chuckles) So talk to me about the work that you guys are doing with SUSE Rancher Government Labs. You're doing some very cool work with the air force, help me understand that. >> Sure, so about a year and some change ago, we had a government contract, an air force contract, to develop some new or just to basically write an experiment with some new sensing technology onboard a satellite. So we built this satellite, we were talking about how we're going to employ DevOps' best practices on the satellite and if that's even a thing that can be done. How we get these rights of space and really thinking through the entire process. And as we did this, we were getting more and more deeply involved with a very very new group. Actually, we kind of started at the same time. A new group within the air force called, Platform One. Platform One's mission is to bring DevSecOps to the DoD Enterprise. And so as we're kind of starting off together and getting to know each other, Rob Slaughter who started and ran Platform One for the first bit of his existence, he said, "hey, we're going to incorporate some Platform One stuff into this. Let's talk about just building an actual Platform One satellite and see what that looks like." And so that was kind of the start of this whole idea was what do we do and how do we do DevSecOps in low Earth orbit? Can we put Kubernetes on satellite and will it work? >> And tell me some of the results? So, I used to work for NASA, so I would geek out on anything that has to do with the space program. But talk to me about some of the things that you uncovered bringing Kubernetes, AI, machine learning to this, outer Edge of Earth? >> I think the first thing that we learned that I think, it's an understatement to say that space is hard. (Both laughing) But it really is. And that was the part that we learned about was it was hard in all of the ways that we did not expect. And a lot of it had to do with just government and logistics. We learned that it is difficult a lot of times to just to find a way to get into space and then once you're there, how you operate in the conditions that you're in and how you could even communicate with your satellite is it's just a logistical adventure on top of all of the other engineering problems that you have while you're on low Earth orbit? The other thing that we figured out was awkward things are difficult. While you're on orbit, they can be slow or fragmented and so it pays to get it right the first time but that's not the nature of modern software development is you'd never get it right and you're continually updating. So that was a problem that really nagged us for awhile was after we did the wider experiment, like how would we continuously update this and what would we do? And those ideas and questions fed into the experiment that became Sat One and then the follow one much bigger experiment that became the Edge One and Edge working group. >> Tell me a little bit about the wider experiment, give me some context of how that relates to Platform One, Sat One? >> I can't (laughing) I can't really go into details about what wider did or anything like that. It was not a classified mission, it's just not something that I can disclose. >> Okay, got it. >> Sorry. >> So talk to me about some of the work that you guys are doing together Hypergiant with SUSE in terms of pushing forward the next generation of Kubernetes to low Earth orbit and beyond. >> Sure, so SUSE RGS, specifically, Chris Nuber, like, one of the things that I have to do is I have to be a cheerleader for all of the amazing people that were on this project. And two people in particular, Chris Tacke and Chris Nuber, were instrumental in making this work. I was like almost tangentially involved where I was doing some input and architecture and helping debug but it was really Chris Tacke and Chris Nuber that made this thing, that built this thing and made it work. And Chris Nuber, was our assigned resource from SUSE RGS. And he said, "Obviously SUSE is going to prefer, or SUSE is going to prefer SUSE products." That it makes sense. But there's a reason because the products that he implemented and the patterns that he implemented and the architecture and expertise that he brought were second to none, I don't think that we could have done better with any other distribution of Kubernetes. He recommended a K3s is a very lightweight Kubernetes distribution that had really good opinions. It's a single binary. It was very easy to deploy and manage and update and it just, it really didn't break. That was the best thing that we were looking for (chuckles) it was one solid piece with no moving parts, relatively speaking. And so Chris Nuber was very essential in providing the Kubernetes architecture while Chris Tacky was the one who helped us write some of the demo applications and build the fail over and out of band interaction that we were going to have from the hardware on the satellite to the Kubernetes control plane. >> Very cool. It sounds like you had a great collaborative team there, which is essential in any environment. >> We deed. >> And I liked how you described space as a logistical adventure that reminds me very much of my days at NASA. (Bren laughing) It definitely is a logistical adventure to put it mildly. Talk to me a little bit about the work that you're doing to define the Edge for the Department of Defense? That sounds very intriguing. >> Yeah, so this was almost a direct result of what happened with the sat one experiment where Rob Slaughter and a few of the other folks who saw what we did with sat one, you know, were again, logistical adventure. We built this entire thing and we worked so hard and we're moving through fright flight readiness checks and as things happen, funding kind of went. And so you've got all this experience and this like, prototype that this really confident that it's space ready and everything and they said, "hey, listen, you know, we have the same problem on our flight with terrestrial environments, they're nearly identical the only difference is, you know, you don't have to worry about radiation nearly as much." (laughing) So then, you know, we joked about that and we started this new idea, this Edge One idea as part of the AVMs program, where they're figuring out this new, like battlefield communications pattern of the future. And one of the things that they're really concerned about is secure processing and how do you do applications at like where people are stationed, which could be anywhere in very remote locations. Then that's what turned into Edge One is, you know, we imagined initially Edge One as satellite one without wings and earth bound and that grew into, well, what about submarines? What about carriers? What about command and control squadrons that are stationed in cities? What about special operators that are far forward? What about first responders who are moving into, you know, hazardous environmental conditions? Can you wear a Kubernetes cluster with like super low power arm chips? And so we started thinking of all these different applications of what Edge could be anywhere from a five volt board all the way up to a data center in a box. And that caused us to realize that we're going to break Edge into really three categories based on the amount of material or resources needed to power it and how hard it is to get to. So we have the Near Edge, which is, you know, you have data center like capabilities, and it's easy to get to it, but you, because you have people stationed with it, but you may have reached back once every month or so. So think, you know, a shift that's underway or an air gap system or something like that. And then you have a Tiny Edge, which is exactly like kind of the more traditional idea that you think of when you think of Edge, which is really, really tiny compute, maybe it's on a windmill or something I don't really know, pick your thing to put Kubernetes on that should never have Kubernetes, that's the kind of thing. And then you've got Far Edge, which is, you know, if the control plane crashes, good luck, you'll never getting to it. And so that would be a satellite. And so the far it... so really a lot of these, it depends on the failure mode. Like what happens when it fails and that for the most part defines kind of what category you're going to be in. >> Tiny Edge, Near Edge and Far Edge. I think Sir. Richard Branson and his team went to the Far Edge (chuckles) low Earth orbit >> He did (laughing). >> This last weekend, I guess, yeah. That low Earth orbit does seem like it would be the Far Edge. Talk to me a little bit about, I mean, you talk about these applications then from a defense perspective that very dramatically, what are some of the important lessons that you've learned besides if it breaks in the Far Edge, you're not getting to it. >> Some of the important lessons that we learned. So I actually did this exact job in the air force. I was a combat communicator, which meant that we took, by pure coincidence I'm back in this, like, I did not intend for this to happen its pure coincidence, (Lisa laughing) but, you know, we communicate, we went out to the Edge, right. We went out to the Near Edge and we did all of this stuff. And the biggest lesson, I think learning from doing this or doing that and then going into this is that the world doesn't have to revolve around SharePoint anymore (Lisa laughing) because we can shape our own habitation (Both laughing) >> That is good to know. >> If it can be done on SharePoint, the air force and the army will do it in SharePoint, I promise you. They've done some actually terrifying things with it. All joking aside though, I think that one of the things that we learned was the difference between like something being complex and complicated when it came to systems engineering and management, like this is a very complex system it's actually orders of magnitude more complex than the current deployments that are out there which is effectively VMware and you're migrating virtual machines across multiple physical nodes in these remote data centers. But it's also complicated, it's really difficult to manage these deployments and the hardware. And I remember like when I was in combat comm, we had this 72 hour goal to get all of our systems up. And it was kind of like a 50-50, if we would make it, it felt like most of the time where you had priorities for getting things up and running. And obviously, you know, that certain applications weren't as important as others. So they were the ones that had to fall on the wayside if you're going to make your 72 hour mark. But I'm just thinking about like how difficult it was to deploy and manage all of this stuff and now with Kubernetes, yes, the complexity is far higher, but we can make it so it's not as complicated. We can offload a lot of that brain sweat, the people in the rear echelon, where they can connect in remotely after you come up and you get reached back, they push your config and your mission profile is there. And now you're focused on the mission you're not focused on debugging pods, and you're focused on the mission and not focused on, you know, why my virtual machine didn't migrate or something like that. And we can get applications that are built in-house and updated continuously, and we can verify and validate the sources of where these things are coming from. And all of these are important problems to everybody, not just the military, but the military tends to have the money and the ability to think about these things first, 'cause that's where these problems tend to get solved first. >> So interesting. You've sort of had this circular experience being in the air force, now coming back and working on projects like this, what are some of the things that Hypergiant has learned? And some of the things that are next next for Hypergiant as a company? >> I think that we are getting really good at being a small contractor in the Federal space where we actually were just awarded an IDIQ with a cap of $950 million in a small group of, I think, 23 other companies. And so that shows right there the investment that the Federal Government has in us and the potential that they see for us to build and deliver these highly tailored and specialized solutions. The other thing that we've learned is how to form like coalitions to collaborate with a lot of these other smaller companies. I think that the days of seeing the Defense Industrial Base dominated by the same four people or five people are over. And it's not that these people, I mean, they've been, they've basically been propping up most of the defense industry for a very long time and I think a lot of people would argue that, you know, this is a problem, right, you have this near monopoly of a very few people, but the other thing is that they're not as nimble, they grow by acquisition and we have this ability to be highly tailored and specialized and we don't need to do everything in the world to survive. We can go and form coalitions with other groups to go solve a particular problem. Like we're great at AI and ML, and we're great at DevSecOps, then maybe we're not so great at, you know, hardware or you know, things like that. Like we can go partner up with these people and solve problems together and we don't have to be a Boeing to do it and you don't have to go hire a Boeing to do this. And I think that's really, really great, no slight to Boeing, but I think it's really great that it's a lot easier for smaller companies to do this and we are navigating this new world and we're bringing Agile into the government and that's, yeah, in some cases we have to drag them, kicking and screaming into this decade, but, you know, that's what we're doing and I'm very excited to see that because when I was in Agile and DevOps, those were words you didn't say, you weren't allowed to do that. >> No. >> Now they've done a complete 180, it's really cool. >> That's cool. I have a minimum that brings in thought diversity, having more companies to work with, but to your point, the agility that you bring in as a smaller company helping them to actually embrace Agile, that's huge because to your point, that's kind of historically not what government organizations are used to. So it sounds like a little bit they've learned a tremendous amount from working with small companies like Pepperdine. >> I like the thing so. Platform One is a fantastic example. So it was really started as a what we're calling software factories within the air force and within the DOD and other DOD branches have now started to replicate the pattern. So we have several software factories within the air force and Platform One is like the DevSecOps Software factory, and we have the ski camp and space camping, Kobayashi Maru and you're noticing a theme here (laughing) and so they're very nerdy names, but so we have these software factories and there's all these projects are being worked. But one of the amazing things I noticed when I showed up to work on the first day was that I had no idea who was uniformed and who was civilian. It was a completely badge off rank, off situation. Very few people showed up in uniform and the ones that did typically had their blouse off so you had no idea what their rank was. Everybody went by first name and we behaved like a start-up. And these civilians were coming from other startups like Hypergiant or a Timo or other very small, very specialized groups and SUSE RGS, of course they were there too and they're embedded in several different teams. And so you have this, like this quasi company that got this startup really that got formed and the culture is very, you know, very varies, you know, bay area startup type in some ways, for both better and worse. There's, I mean, we're, definitely full tilt on (laughs) on the Agile train there, but it's just, it's like nothing I've ever seen inside the DOD. And they're not just learning from these small companies and from Agile companies, but they're behaving like them. And it's spreading, they're seeing what work is getting done and what can be accomplished and how you can continuously deliver value instead of working for, you know, six or eight months and then showing the customer something and them hating it and you sending it back and, you know, it's more of a continuous improvement type thing. And I think that they're embracing that and I'm very excited to see it. >> That's important 'cause changing a culture is incredibly hard but seeing and hearing that they're embracing that is exciting. And I'm sure there's going to be many more things you could talk about generally, but I got to ask you if somebody like SUSE gave you $250,000, and you could buy one of the tickets on Branson's next flight, would you do it? >> I mean, yeah, why would I not? Like, how can I pass up a trip, (Lisa laughing) you know, go to the Edge of space. >> The Far Edge. >> Like yeah, the Far Edge, maybe I'll just, you know, hurdle the satellite out the window, as you know, we're up there, you know, peak and probably could throw it quite that fast, but we'll see. (Lisa laughing) But yeah, no, I think I would take the trip, yeah, that'd be fun. >> You're brave. Brave than I'm, I don't know. Well, Bren it's been delightful talking to you. Thank you for sharing what you guys at Hypergiant and SUSE have been doing together, the Department of Defense, the exciting things going on there and for the new definitions and my lexicon of the Edge, it's been great talking to you. >> Thank you, have a great day. >> You too. For Bren Briggs, I'm Lisa Martin. You're watching a CUBE Conversation. (digital music)

>> Narrator: From the CUBE Studios in Palo Alto, in Boston. Connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hi, everybody. Welcome to the special Cube Conversation. With COVID-19 hitting, organizations really had to focus on business resiliency, and we've got two great guests here to talk about that topic. Bob Bender's the chief technology officer at Founders Federal Credit Union. And he's joined by Jim Shook, who is the director of cybersecurity and compliance practice at Dell Technologies. Gentlemen, thanks for coming on the CUBE, great to see you. >> Thanks, Dave, great to see you, thank you. So, Bob, let's start with you, give us a little bit of background on Founders and your role. >> Founders Federal Credit Union is a financial institution that has about 225,000 members, serving them in 30 different locations, located in the Carolinas. I serve as chief technology officer bringing in the latest technology and cyber resilient direction for the company. >> Great. And Jim, talk about your role. Is this a new role that was precipitated by COVID or was this something that Dell has had for a while? Certainly relevant. >> It's actually been around for a while, Dave. The organization invested in this space going back about five years, I founded the cyber security and compliance practice. So really, my role is most of the time in the field with our customers, helping them to understand and solve their issues around the cyber resilience and cyber recovery field that we're talking about. But I also, to do that properly, spend a lot of time with organizations that are interested in that space. So it could be with an advisory partner, could be the FBI, might be a regulator, a particular group like Sheltered Harbor that we've worked with frequently. So it's just really, as you point out, taken off first with ransomware a couple of years ago, and then with the recent challenges from work from home in COVID. So we're really helping out a lot of our customers right now. >> Bob, I've talked privately to a number of CIOs and CSOs and many have said to me that when COVID hit that their business continuance was really much too (voice cuts out) Now, you guys actually started your journey way back in 2017. I wonder if you could take us back a few years and what were the trends that you were seeing that precipitated you to go on this journey? >> Well, I think we actually saw the malware, the horizon there. And I'll take you back a little further 'cause I just love that story is, when we looked at the relationship of Dell EMC, we talked to the 1% of the 1%, who is protecting their environment, their data capital, the new critical asset in our environment. And Dell EMC was the top of the line every time. When we looked at the environment and what it required, to put our assets under protection, again, we turned to Dell EMC and said, where do we need to go here? You look at this Mecklenburg County, you look at the city of Atlanta, you look at Boeing and I hate to use the examples, but some very large companies, some really experienced companies were susceptible to this malware attacks that we just knew ourself it was going to change us. So the horizon was moving fast and we had to as well. >> Well, you were in a highly regulated industry as well. How did that factor into the move? Well, you're exactly right. We had on our budget, our capital budget horizon, to do an air gap solution. We were looking at that. So the regulatory requirements were requiring that, the auditors were in every day talking about that. And we just kept framing that in what we were going to do in that environment. We wanted to make sure as we did this purpose built data bunker, that we looked at everything, talk to the experts, whether that was federal state regulation. You mentioned Sheltered Harbor, there's GDPR. All these things are changing how are we going to be able to sustain a forward look as we stand this environment up. And we also stood up a cyber security operations center. So we felt very confident in our Runbooks, in our incident response, that you would think that we would be ready to execute. I'll share with you that we reached out every which way and a friend called me and was actually in a live ransomware event and asked if I wanted to come on to their site to help them through that incident. We had some expertise on our staff that they did not possess at that time. So going into that environment, spending 30 hours of the last 72 hours of an attack we came back changed. We came back changed and went to our board and our executives and said, "We thought we knew what we were doing." But when you see the need to change from one to 10 servers recovery to 300 in 72 hours, we just realized that we had to change our plan. We turned to the investment we had already made and what we had looked at for some time, and said, "Dell EMC, we're ready to look at that "PowerProtect Cyber Recovery solution. "How can you stand this up very quickly?" >> So, Jim, Bob was saying that he looked at the 1% of the 1%, so these guys are early adopters, but anything you can add to that discussion in terms of what you saw precipitate the activity, let's go pre-COVID, certainly ransomware was part of that. Was that the big catalyst that you saw? >> It really was. So when we started the practice, it was following up on the Sony Pictures attack, which only hit Sony in that. But it was unique in that it was trying to destroy an organization as opposed to just steal their data. So we had financial industry really leading the way, the regulators in the financial industry saying, "Gosh, these attacks could happen here "and they would be devastating." So they led the way. And as our practice continued, 2016 became the year of ransomware and became more prevalent, with the attackers getting more sophisticated and being able to monetize their efforts more completely with things like cryptocurrencies. And so as we come around and start talking to Bob, he still was well ahead of the game. People were talking about these issues, starting to grow concerned, but didn't really understand what to do. And Dave, I know we'll get to this a little bit later, but even today, there's quite a bit of disconnect, many times between the business, understanding the risks of the business and then the technology, which really is the business now, but making those pieces fit together and understanding where you need to improve to secure against these risks is a difficult process. >> Well, I think I'd love to come back to Bob and try to understand how you pitch this to the board, if you will, how you made the business case. To Jim's point, the adversaries are highly capable. It's a lucrative business. I always talk to my kids about ROI numerator and denominator. If you can raise the denominator, that's going to lower the value. And that's the business that you're in is making it less attractive for the bad guys. But how did you present this to the board? Was it a board level discussion? >> It was, exactly. We brought Dell EMC PowerProtect Cyber Recovery solution to them and said, not only you're experiencing and seeing in the news daily, these attacks in our regions, but we have actually gone out into an environment and watch that attack play out. Not only that is when we stepped away, and we ran through some tabletops with them and we stepped away. And we said, "Are you okay? "Do you know how it got in? "Are you prepared to protect now and detect that again?" Within 30 days, they were hit again by the same ransomware attacks and hackers. So I hate to say this, but I probably fast forwarded on the business case and in the environment, the horizon around me, players, they made my case for me. So I really appreciated that top down approach. The board invested, the executive invested, they understood what was at risk. They understood that you don't have weeks to recover in the financial institution. You're dealing with hundreds of thousand transactions per second so it made my case. We had studied, we had talked to the experts. We knew what we wanted. We went to Dell EMC and said, "I have six months and here's my spend." And that's from equipment hitting our CoLOS and our data centers, standing it up, standing up the Runbooks and it's fully executed. And I wanted an environment that was not only holistic. We built it out to cover all of our data and that I could stand up the data center within that environment. I didn't need another backup solution. I needed a cyber recovery environment, a lifestyle change, if you would say. It's got to be different than your BCP/DR. While it inherits some of those relationships, we fund it with employees separately. We treated the incident response separately, and it is really benefited. And I think we've really grown. And we continue to stress that to educate ourselves not only at the board level, but a bottom up approach as well with the employees. 'cause they're a part of that human firewall as well. >> I think you've seen this where a lot of organizations, they do a checkbox on backup or as I was saying before, DR. But then in this world of digital, when a problem hits, it's like, "Oh-oh, we're not ready." So I wonder Jim, if we can get into this solution that Bob has been talking about the Dell EMC PowerProtect Cyber Recovery solution, there's a mouthful there. You got the power branding going on. What is that all about? Talk to us about the tech that's behind this. >> It's something that we've developed over time and really added to in our capability. So at its core, PowerProtect Cyber Recovery is going to protect your most critical data and applications so that if there is a cyber attack, a ransomware or destructive attack, they're safe from that attack. And you can take that data and recover the most important components of the business. And to do that, we do a number of things, Dave. The solution itself takes care of all these things. But number one is we isolate the data so that you can't get there from here. If you're a bad actor, even an insider, you can't get to the data because of how we've architected. And so we'll use that to update the critical applications and data. Then we'll lock that data down. People will use terms like immutability or retention lock. So we'll lock it down in that isolated environment, and then we'll analyze it. So it's one thing to be able to protect the data with the solution, it's another, to be able to say that what I have here in my data vault, in my air gapped isolated environment is clean. It's good data. And if there was an attack, I can use that to recover. And then of course over time, we've built out all the capabilities. We've made it easier to deploy, easier to manage. We have very sophisticated services for organizations that need them. And then we can do a much lighter touch for organizations that have a lot of their built in capabilities. At its core, it's a recover capability so that if there was an attack that was unfortunately successful, you don't lose your business. You're not at the mercy of the criminals to pay the ransom. You have this data and you can recover it. >> So Bob, talk to us about your objectives going into this. It's more than a project. It really is a transformation of your resiliency infrastructure, I'll call it. What were your objectives going in? A lot of companies are reacting, and it's like, you don't have time to really think. So what are the objectives? How long did it take? Paint a picture of the project and what it looked like, some of the high level milestones that you were able to achieve. >> Well, I think several times Dell EMC was able to talk us off the edge, where it really got complicated. The Foundation Services is just one of your more difficult conversations, one of the top three, definitely, patch management, notification, and how you're going to rehydrate that data, keeping that window very small to reduce that risk almost completely as you move. I think other area this apply is that we really wanted to understand our data. And I think we're on a road to achieving that. It was important that if we were going to put it into the vault, it had a purpose. And if we weren't going to put it in a vault, let's see why would we choose to do that? Why would we have this data? Why would we have this laying around? Because that's a story of our members, 225 stories. So their ability to move into financial security, that story is now ours to protect. Not only do we want to serve you in the services and the industry and make sure you achieve what you're trying to, but now we have that story about you that we have to protect just as passionately. And we had that. I think that was two of the biggest things. I think the third is that we wanted to make sure we could be successful moving forward. And I'll share with you that in the history of the credit union, we achieved one of the biggest projects here, in the last two years. That umbrella of the Cyber Recovery solution protection was immediate. We plugged in a significant project of our data capital and it's automatically covered. So I take that out of the vendor of responsibility, which is very difficult to validate, to hold accountable sometimes. And it comes back under our control into this purpose built data security and cyber resilient, business strategy. That's a business strategy for us is to maintain that presence. So everything new, we feel that we're sized, there's not going to be a rip and replace, a huge architectural change because we did have this as an objective at the very beginning. >> Tim, when you go into a project like this, what do you tell customers in terms of things that they really should be focused on to have a successful outcome? >> I'm going to say first that not everybody has a Bob Bender. So we have a lot of these conversations where we have to really start from the beginning and work through it with our customers. If you approach this the right way, it's really about the business. So what are the key processes for your business? It can be different from a bank than from a hospital than from a school point. So what are the key things that you do? And then what's the tech that supports that and underlies those processes? That's what we want to get into the vault. So we'll have those conversations early on. I think we have to help a lot of organizations through the risks too. So understand the risk landscape, why doing one or two little things aren't really going to protect you from the full spectrum of attackers. And then the third piece really is, where do we start? How do we get moving on this process? How do we get victory so that the board can understand and the business can understand, and we can continue to progress along the way? So it's always a bit of a journey, but getting that first step and getting some understanding there on the threat landscape, along with why we're doing this is very important. >> So, Bob, what about any speed bumps that you encountered? What were some of those? No project is ever perfect. What'd you run into? How'd you deal with it? >> Well, I would say the Foundation Services were major part of our time. So it really helped for Dell EMC to come and explain to us and look at that perimeter and how our data is brought into that and size that for us and make sure it's sustainable. So that is definitely, could be a speed bump that we had to overcome. But today, because of those lifts, those efforts invested the Runbooks, the increase in new products, new data as our business organically grows is a non-event. It's very plug and play and that's what we wanted from the start. Again, you go back to that conversation at 1% of the 1%, it's saying, who protects you? We followed that. We stayed with the partner we trusted, the horizon holistically has come back and paid for itself again and again. So speed bumps, we're just enjoying that we were early adapters. I don't want to throw anybody out there, but you look about two weeks ago, there was a major announcement about an attack that was successful. They got them with ransomware and the company paid the ransom. But it wasn't for the ransomware, it was for the data they stole so that they would delete it. That's again, why we wanted this environment is we needed time to react in the case that these malwares are growing much faster than we're capable of understanding how they're attacking. Now it's one, two punch, where's it going to be? Where is it going to end? We're not going to likely be patient zero, but we're also not going to have to be up at night worrying that there's a new strain out there. We have a little time now that we have this secure environment that we know has that air gap solution that was built with the regulatory consideration, with the legal considerations, with the data capital, with the review of malware and such. You can go back in time and say, "Scan to see if I have a problem. So again, the partnership is while we focus on our business, they're focusing on the strategy for the future. And that's what we need. We can't be in both places at once. >> How long did the project take from the point of which you agreed, signed the contract to where you felt like you were getting value out of the solution? >> Six months. >> Really? >> We were adamant. I'd put it off for a year and a half, that's two budget cycles basically is what it felt. And then I had to come back and ask for that money back because we felt so passionate that our data, our critical data didn't need to be at that risk any longer. So it was a very tight timeline. And again, product on prem within six months. And it was a lot of things going on there. So I just wasn't idle during that time. I was having a conversation with Dell EMC about our relationship and our contracts. Let's build that cyber resilience into the contract. Now we've got this, PowerProtect Cyber Recovery environment, let's build it here where you also agree to bring on extra hardware or product if I need that. Let's talk about me being on a technology advisory panel So I can tell you where the pricing of the regulations are going, so you can start to build that in. Let's talk about the executive board reporting of your products and how that can enable us. We're not just talking about cyber and protecting your data. We're talking about back then 60% of your keep the lights on IT person will spend with auditors, talking about how we were failing. This product helped us get ahead of that to now where we're data analytic. We're just analysts that can come back to the business table and say, "We can stand that up very quickly." Not only because of the hardware and the platform solution we have, but it is now covered with a cyber resilience of the the cyber security recovery platform. >> I want to ask you about analytics. Do you feel as though you've been able to go from what is generally viewed as a reactive mode into something that is more anticipatory or proactive using analytics? >> Well, I definitely do. We pull analytics daily and sometimes hourly to make sure we're achieving our KPIs. And looking at the KRIs, we do risk assessments from the industry to make sure if our controls layer of defenses are there, that they will still work what we stood up three years ago. So I definitely think we've gone from an ad hoc rip and replace approach to transformation into a more of a threat hunting type of approach. So our cyber security operation center, for us, is very advanced and is always looking for opportunities not only to improve, to do self-assessments, but we're very active. We're monetizing that with a CUSO arm of the credit union to go out and help others where we're successful, others that may not have that staff. It's very rewarding for us. And I hate to say it sometimes it's at their expense of being in-evolved in the event of a ransomware attack or a malware event. We learned so much the gaps we have, that we could take this back, create Runbooks and make the industry stronger against these types of attacks. >> Well, so Jim, you said earlier, not every company has a Bob Bender. How common is it that you're able to see customers go from that reactive mode into one that is proactive? Is that rare or is it increasingly common? It can't be a 100%, but what are you seeing as trends? >> It's more common now. You think of, again, back to Bob, that's three plus years ago, and he's been a tireless supporter and tireless worker in his industry and in his community, in the cyber area. And efforts like those of Bob's have helped so many other organizations I think, understand the risks and take further action. I think too, Bob talks about some of the challenges with getting started in that three year timeframe, PowerProtect Cyber Recovery has become more productized, our practice is more mature. We have more people, more help. We're still doing things out there that nobody else is touching. And so we've made it easier for organizations that have an interest in this area, to deploy and deploy quickly and to get quick value from their projects. So I think between that some of the ease of use, and then also there's more understanding, I think, of what the bad actors can do and those threats. This isn't about somebody maybe having an outage for a couple of hours. This is about the very existence of a business being threatened. That if you're attacked, you might not come back from it. And there've been some significant example that you might lose hundreds of millions of dollars. So as that awareness has grown, more and more people have come on board and been able to leverage learnings from people like Bob who started much earlier. >> Well, I can see the CFO saying, "Okay, I get it. "I have no choice where we're going to be attacked. "We know that, I got to buy the insurance. You got me." But I can see the CFO saying, "Is there any way we can "get additional value out of this? "Can we use it to improve our processes and cut our costs? "Can we monetize this in some way?" Bob, what's the reality there? Are you able to find other sources of value beyond just an insurance policy? >> Definitely, Dave you're exactly right. We're able to go out there and take these Runbooks and really start to educate what cyber resilience means and what air gap means, what are you required to do, and then what is your responsibility to do it. When you take these exercises that are offered and you go through them, and then you change that perspective and go through a live event with other folks that see that after 60 hours of folks being up straight, it really changes your view to understand that there's no finish line here. We're always going to be trying to improve the product and why not pick somebody that you're comfortable with and you trust. And I think that's the biggest win we have from this is that was a Dell EMC partnership with us. It is very comfortable fit. We moved from backup and recovery into cyber resilience and cybersecurity as a business strategy with that partner, with our partner Dell, and it hasn't failed us. It's a very comforting. We're talking about quality of life for the employee. You hear that, keep the lights on. And they've really turned into professionals to really understand what security means differently today and what that quality of data is. Reports, aren't just reports, they're data capital. The new currency today of the value we bring. So how are we going to use that? How are we going to monetize that? It's changing. And then I hate to jump ahead, but we had our perimeters at 1% of our workforce remote and all of a sudden COVID-19 takes on a different challenge. We thought we were doing really good and next, we had to move 50% of our employees out in five days. And because of that Dell EMC, holistic approach, we were protected every step of the way. We didn't lose any time saying, we bought the wrong control, the wrong hardware, the wrong software. It was a very comfortable approach. The Runbooks held us, our security posture stayed solid. It's been a very rewarding. >> Well, Bob, that was my next question, actually is because you've started the journey. >> Sorry. >> No, no, it's okay. Because you started the journey early, were you able to respond to COVID in a more fast sell manner? it sounds like you just went right in. But there's nuance there, because you've got now 50% or more of the workforce working at home, you got endpoint security to worry about. You got identity access management, and it sounds like you were, "No problem. "We've got this covered." Am I getting that right? >> You're exactly right, Dave. We test our endpoints daily. We make sure that we understand what residue of data is where. And when we saw that employee shift to a safe environment, our most consideration at that time, we felt very comfortable that the controls we had in place, again, Dell and their business partners who we are going to hold true and be solid. And we test those metrics daily. I get reports back telling me, what's missing in patch management, what's missing in a backup. I'll go back to keeping BCP and cyber security separate. In the vault, we take approach of recovery and systems daily. And now that goes from maybe a 2% testing rate almost to 100% annually. So again, to your point, COVID was a real setback. We just executed the same Runbooks we had been maturing all along. So it was very comfortable for employees and it was very comfortable for our IT structure. We did not feel any service delays or outages because of that. In a day, when you have to produce that data, secure that data, every minute of every day of every year, it's very comforting to know it's going to happen. You don't push that button and nothing happens. It's executed as planned. >> Jim, did you see a huge spike in demand for your services as a result of COVID and how did you handle it? You guys got a zillion customers, how did you respond and make sure that you were taking care of everybody? >> We really did see a big spike, Dave. I think there were a couple of things going on. As Bob points out, the security posture changes very quickly when you're sending people to work from home or people remotely, you've expanded or obliterated your parameter, you're not ready for it. And so security becomes even more important and more top of mind. So with PowerProtect Cyber Recovery, we can go in and we can protect those most critical applications. So organizations are really looking at their full security posture. What can we do better to detect and protect against these threats? And that's really important. For us, we're focusing on what happens when those fail? And with that extension and people going home, and then the threat actors getting even more active, the possibilities of those failures become more possible and the risks are just in front of everybody. So I think it was a combination of all of those things. Many, many customers came to us very quickly and said, "Tell us more about what you're doing here. "How does it fit into our infrastructure? "What does it protect us against? "How quickly can we deploy?" And so there has been a huge uptake in interest. And we're fortunate in that, as you pointed out early on, Dave, we invested early here. I'm five years into the practice. We've got a lot of people, very mature, very sophisticated in this area, a lot of passion among our team. And we can go take care of all those customers. >> Bob, if you had a mulligan, thinking about this project, what would you do differently if you had a chance to do it over? >> I think I would start earlier. I think that was probably the biggest thing I regret in that realizing you need to understand that you may not have the time you think you do. And luckily, we came to our senses, we executed and I got to say it was with common sense, comfortable products that we already understood. We didn't have to learn a whole new game plan. I don't worry about that. I don't worry about the sizing of the product 'cause we did it, I feel correctly going in and it fits us as we move forward. And we're growing at an increased rate that we may not expect. It's plug and play. Again, I would just say, stay involved, get involved, know that what we know today about malware and these attacks are only going to get more complicated. And that's where I need to spend my time, my group become experts there. Why I really cherish the Dell EMC relationship is from the very beginning, they've always been very passionate on delivering products that recover and protect and now are cyber resilient. I don't have to challenge that, you pay for what you get for. And I just got to say, I don't think there's much other than I would have started earlier. So start today, don't put it off. >> So you said earlier though, you're never done, you never are, in this industry. So what's your roadmap look like? Where do you want to go from here with this capability? >> I definitely want to keep educating my staff, keep training them, keep working with Dell. Again, I tell you they're such forward thinking as a company. They saved me that investment. So if you're looking at part of the investment, it's got to be, are you with a partner that's forward thinking? So we definitely want to mature this, challenge it, keep challenging, keep working with Dell and their products to deliver more. Again, we go to the federal and state regulatory requirements. You go to the Sheltered Harbor, the ACET testing from the NCUA regulators, just software asset management. You can keep on going down the line. This product, I hate to say it, it's like the iPhone. You think about how many products the iPhone has now made not relevant. I don't even own a flashlight, I don't think. This is what the Dell product line brings to me is that I can trust they're going to keep me relevant so I can stay at the business table and design products that help our members today. >> Jim, how about from Dell's perspective, the roadmap, without giving away any confidential information, where do you want to take this? We talk about air gaps. I remember watching that documentary Zero Days and hearing them say, "We got through an air gap. "No problem." So analytics obviously plays a role in this machine intelligence, machine learning, AI. Where does Dell want to take this capability? Where do you see that going? >> We've got some things in mind and then we're always going to listen to our customers and see where the regulations are going to. And thus far, we've been ahead of those with the help of people like Bob. I think where we have a huge advantage, Dave is with PowerProtect Cyber Recovery. It's a product. So we've got people who are dedicated to this full time. We have a maturity in the organization, in the field to deliver it and to service it. And having something as a product like that really enables us to have roadmaps and support and things that customers need to really make this effective for them. So as we look out on the product, and thanks for your reminder, I don't want to risk saying anything here I'm going to get in trouble for. We look at things in three paths. One is we want to increase the ability for our customers to consume the product. So they want it in different forms. They might want it in appliances, in the Cloud, virtual, all of those things are things that we've developed and continue to develop. They want more capabilities. So they want the product to do more things. They want it to be more secure, and keeping up. As you mentioned, machine learning with the analytics is a big key for us. Even more mundane things like operational information makes it easier to keep the vault secure and understand what's going on there without having to get into it all the time. So those are really valuable. And then our third point, really, we can't do everything. And so we have great partners, whether they're doing delivery, offering cyber recovery as a service or providing secure capabilities, like our relationship with Unisys. They have a stealth product that is a zero knowledge, zero trust product that helps us to secure some of the connections to the vault. We'll keep iterating on all of those things and being innovative in this space, working with the regulators, doing things. Bob's mentioned a couple of times, Sheltered Harbor. We've been working with them for two years to have our product endorsed to their specification. Something that nobody else is even touching. So we'll continue along all those paths, but really following our customer's lead in addition to maybe going some places that they haven't thought about before. >> It's great guys. I have to fear that when you talk to SecOps pros, you ask them what their biggest challenge is, and they'll say lack of talent, lack of skills. And so this is a great example, Jim, you're mentioning it, you've productized this. This is a great example of a technology company translating, IT labor costs into R&D. And removing those so customers can spend time running their business. Bob and Jim, thanks so much for coming on the CUBE. Great story. Really appreciate your time. >> Thank you, Dave. >> Thank you, Dave. >> Thanks, Bob. >> All right. And thank you everybody for watching. This is Dave Vellante for the CUBE. We'll see you next time. (instrumental music)

>>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 live I'm Lisa Martin. Really exciting topic coming up for you next, please. Welcome Blake shoulda, founder and CEO of boom supersonic Blake. It's great to have you on the program. Thank you for having me, Lisa, and your background gives me all the way with what we're going to talk about in the next few minutes or so, but supersonic flight has existed for quite a long time, like 50 or so years. I think those of us in certain generations remember the Concorde for example, but the technology to make it efficient and mainstream is only recently been approved by or accepted by regulators. Tell us a little bit about boom, your mission to make the world more accessible with supersonic commercial flight. Well, a supersonic flight has >> actually been around since 1949 when Chuck Yeager broke the speed barrier or sorry, the sound barrier. >>And as, as many of you know, he actually passed yesterday, uh, 97. So very, very sad to see one of the supersonic pioneers behind us. Uh, but, uh, but as I say goodbye to Jaeger, a new era of supersonic flight is here. And if you look at the history of progress and transportation, since the Dawn of the industrial revolution, uh, we used to make regular progress and speed. As we went from, uh, the horse to the iron horse, to the, the boats, to the, the early propeller airplanes that have the jet age. And what happened was every time we made transportation faster, instead of spending less time traveling, we actually spent more time traveling because there were more places to go, more people to meet. Uh, we haven't had a world war since the Dawn of the jet age. Uh, places like Hawaii have become, uh, a major tourist destination. >>Uh, but today, uh, today it's been 60 years since we've had a mainstream re uh, step forward and speed. So what we're doing here at boom is picking up where Concord left off building an aircraft that flies faster by factor to the, anything you can get a ticket on today. And yet is 75% more affordable than Concorde was. So we want to make Australia as accessible as a why yesterday. We want to enable you to cross the Atlantic, do business, be home in time, detect your kids into bed, or take a three-day business trip to Asia and let you do it in just 24 >> hours. I like the sound of all of that. Even getting on a plane right now in general. I think we all do so, so interesting that you, you want to make this more accessible. And I did see the news about Chuck Yeager last night. >>Um, designing though the first supersonic airliner overture, it's called in decades, as you said, this dates back 60 years, rolling it out goal is to roll it out in 2025 and flying more than 500 trans oceanic routes. Talk to me about how you're leveraging technology and AWS to help facilitate that. Right. Well, so one of the really fascinating things is the new generation of airplanes, uh, are getting born in the cloud and then they're going to go fly through actual clouds. And so there are, there are a bunch of revolutions in technology that have happened since Concord's time that are enabling what we're doing now, their breakthroughs and materials. We've gone from aluminum to carbon fiber they're breakthroughs and engines. We've gone from after burning turbo jets that are loud and inefficient to quiet, clean, efficient turbo fans. But one of the most interesting breakthroughs has been in a available to do design digitally and iteration digitally versus, uh, versus physically. >>So when conquer was designed as an example, they were only able to do about a dozen wind tunnel tests because they were so expensive. And so time consuming and on, uh, on our XP one aircraft, which is our prototype that rolled out in October. Um, uh, we did hundreds of iterations of the design in virtual wind tunnels, where we could spin up a, uh, a simulation and HPC cluster in AWS, often more than 500 cores. And then we'd have our airplanes flying through virtual wind tunnels, thousands of flights scenarios you can figure out which were the losers, which were the winners keep iterating on the winners. And you arrive at an aerodynamic design that is more efficient at high speed. We're going very safely, very quickly in a straight line, but also a very smooth controllable for safe takeoff and landing. And the part of the artist supersonic airplane design is to accomplish both of those things. One, one airplane, and, uh, being able to design in the cloud, the cloud allows us to start up to do what previously only governments and militaries could do. I mentioned we rolled out our XP one prototype in October. That's the first time anyone has rolled out a supersonic civil aircraft since the Soviet union did it in 1968. And we're able to do as a startup because of computing. >>That's incredible born in the cloud to fly in the cloud. So talk to me about a lot of, of opportunity that technology has really accelerated. And we've seen a lot of acceleration this year in particular digital transformation businesses that if they haven't pivoted are probably in some challenging waters. So talk to us about how you're going all in with AWS to facilitate all these things that you just mentioned, which has dramatic change over 12, uh, when tone test for the Concord and how many times did it, >>Uh, I mean for 27 years, but not that many flights, never, it never changed the way mainstream, uh, never, never district some of you and I fly. Right. Um, so, so how, how are we going all in? So we've, you know, we've been using AWS for, uh, you know, basically since the founding of the company. Uh, but what we, what we're doing now is taking things that we were doing outside of the cloud and cloud. Uh, as an example, uh, we have 525 terabytes of XP one design and test data that what used to be backed up offsite. Um, and, and what we're doing is migrating into the cloud. And then your data is next. Your compute, you can start to do these really interesting things as an example, uh, you can run machine learning models to calibrate your simulations to your wind tunnel results, which accelerates convergence allows you to run more iterations even faster, and ultimately come up with a more efficient airplane, which means it's going to be more affordable for all of us to go to go break the sound barrier. >>And that sounds like kind of one of the biggest differences that you just said is that it wasn't built for mainstream before. Now, it's going to be accessibility affordability as well. So how are you going to be leveraging the cloud, you know, design manufacturing, but also other areas like the beyond onboard experience, which I'm already really excited to be participating in in the next few years. >>Yeah. So there's so many, so many examples. We've talked about design a little bit already. Uh, it's going to manifest in the manufacturing process, uh, where the, the, the, the, the supply chain, uh, will be totally digital. The factory operations will be run out of the cloud. You know, so what that means concretely is, uh, you know, literally there'll be like a million parts of this airplane. And for any given unit goes through their production line, you'll instantly know where they all are. Um, you'll know which serial numbers went on, which airplanes, uh, you'll understand, uh, if there was a problem with one of it, how you fixed it. And as you continue to iterate and refine the airplane, this, this is one of things that's actually a big deal, uh, with, with digital in the cloud is, you know, exactly what design iteration went into, exactly which airplane and, uh, and that allows you to actually iterate faster and any given airline with any given airplane will actually know exactly what, what airplane they have, but the next one that rolls off the line might be even a little bit better. >>And so it allows you to keep track of all of that. It allows you to iterate faster, uh, it allows you to spot bottlenecks in your supply chain before they impact production. Um, and then it allows you to, uh, to do preventive maintenance later. So there's to be digital interpretation all over the airplane, it's going to update the cloud on, you know, uh, are the engines running expected temperature. So I'm gonna run a little bit hot, is something vibrating more than it should vibrate. And so you catch these things way before there's any kind of real maintenance issue. You flag it in the cloud. The next time the airplane lands, there's a tech waiting for the airplane with whatever the part is and able to install it. And you don't have any downtime, and you're never anywhere close to a safety issue. You're able to do a lot more preventively versus what you can do today. >>Wow. So you have to say that you're going to be able to, to have a hundred percent visibility into manufacturing design, everything is kind of an understatement, but you launched XQ on your prototype in October. So during the pandemic, as I mentioned, we've been talking for months now on the virtual cube about the acceleration of digital transformation. Andy, Jassy talked about it in his keynote at AWS reinventing, reinventing this year, virtual, what were some of the, the, the advantages that you got, being able to stay on track and imagine if you were on track to launch in October during a time that has been so chaotic, uh, everywhere else, including air travel. >>Well, some of it's very analog, uh, and some of it's very digital. So to start with the analog, uh, we took COVID really seriously at Bo. Uh, we went into that, the pandemic first hit, we shut the company down for a couple of weeks, so we'd kind of get our feet underneath of us. And then we sort of testing, uh, everyone who had to work on the airplane every 14 days, we were religious about wearing masks. And as a result, we haven't had anyone catch COVID within the office. Um, and I'm super proud that we're able to stay productive and stay safe during the pandemic. Um, and you do that, but kind of taking it seriously, doing common sense things. And then there's the digital effort. And, uh, and so, you know, part of the company runs digitally. What we're able to do is when there's kind of a higher alert level, we go a little bit more digital when there's a lower alert level. >>Uh, we have more people in the office cause we, we still really do value that in-person collaboration and which brings it back through to a bigger point. It's been predicted for a long time, that the advent of digital communication is going to cause us not to need to travel. And, uh, what we've seen, you know, since the Dawn of the telephone is that it's actually been the opposite. The more you can know, somebody even a little bit, uh, at distance, the hungry you are to go see them in person, whether it's a business contact or someone you're in love with, um, no matter what it is, there's still that appetite to be there in person. And so I think what we're seeing with the digitization of communication is ultimately going to be very, um, uh, it's very complimentary with supersonic because you can get to know somebody a little bit over a long distance. You can have some kinds of exchanges and then you're, and then the friction for be able to see them in person is going to drop. And that is, uh, that's a wonderful combination. >>I think everybody on the planet welcomes that for sure, given what we've all experienced in the last year, you can have a lot of conversations by zoom. Obviously this was one of them, but there is to your point, something about that in-person collaboration that really takes things can anyway, to the next level. I am curious. So you launched XB one in October, as I mentioned a minute ago, and I think I read from one of your press releases planning to launch in 2025, the overture with over 500 trans oceanic routes. What can we expect from boom and the next year or two, are you on track for that 2025? >>Yeah. Things are going, things are going great. Uh, so to give a sense of what the next few years hold. So we rolled out the assembled XB one aircraft this year, uh, next year that's going to fly. And so that will be the first civil supersonic, uh, flying aircraft ever built by an independent company. Uh, and along the way, we are building the foundation of overture. So that design efforts happening now as XB one is breaking the sound barrier. We'll be finalizing the overture design in 22, we'll break ground in the factory in 23, we'll start building the first airplane and 25, we'll roll it out. And 26 we'll start flight tests. And, uh, and then we'll go through the flight test methodically, uh, systematically as carefully as we can, uh, and then be ready to carry passengers as soon as we are convinced that safe, which will be right around the end of the decade, most likely. >>Okay. Exciting. And so it sounds like you talked about the safety protocols that you guys put in place in the office, which is great. It's great to hear that, but also that this, this time hasn't derailed because you have the massive capabilities of, to be able to do all of the work that's necessary, way more than was done with before with the Concorde. And that you can do that remotely with cloud is a big facilitator of that communication. >>Yeah. You're able to do the cloud enables a lot of computational efficiencies. And I think about the, um, many times projects are not measured in how many months or years exactly does it take you to get done, but it's actually much easier to think about in terms of number of iterations. And so every time we do an airplane iteration, we look at the aerodynamics high speed. We look at the low speed. We look at the engine, uh, we look at the, the weights. Uh, we look at stability and control. We look at pilots, light aside, et cetera, et cetera. And every time you do an iteration, you're kind of looking around all of those and saying, what can I make better? But each one of those, uh, lines up a little bit differently with the rest now, for example, uh, uh, to get the best airplane aerodynamically, doesn't have a good view for the pilot. >>And that's why Concord had that droop nose famously get the nose out of the way so we can see the runway. And so we're able to do digital systems for virtual vision to let the pilot kind of look through the nose of the runway. But even then they're, trade-offs like, how, how good of an actual window do you need? And so your ability to make progress in all of this is proportional to how quickly you can make it around that, that iteration loop, that design cycle loop. And that's, that's part of where the cloud helps us. And we've, we've got some, uh, uh, some stuff we've built in house that runs on the cloud that lets you basically press a button with a whole set of airplane parameters. And bam, it gives you a, it gives you an instant report. I'm like, Oh, was it that this is a good change or bad change, uh, based on running some pretty high fidelity simulations with a very high degree of automation. And you can actually do many of those in parallel. And so it's about, you know, at this stage of the program, it's about accelerating, accelerating your design iterations, uh, giving everyone of the team visibility into those. And then, uh, I think you get together in person as it makes sense to now we're actually hitting a major design milestone with over-treat this week and we're, COVID testing everybody and get them all in the same room. Cause sometimes that in-person collaboration, uh, is really significant, even though you can still do so much digitally. >>I totally agree. There's there's certain things that you just can't replicate. Last question since my brother is a pilot for Southwest and retired Lieutenant Colonel from the air force, any special training that pilots will have to have, or are there certain pilots that are going to be maybe lower hanging fruit, if they have military experience versus commercial flight? Just curious. >>Yeah. So our XB one aircraft is being flown by test pilots. There's one ex Navy one ex air force on our crew, but, uh, overture, uh, will be accessible to any commercial pilot. So, uh, think about it as if you're, if you're used to flying Boeing, it'd be like switching to Airbus, uh, or vice versa. So the, uh, Concord is a complicated aircraft to fly because they didn't have computers. And all the complexity, the soup of supersonic flight was right there and the pilots and an overture, all that gets extracted by software. And, uh, you know, the, the, the ways the flight controls change over speed regimes. You don't have to worry about it, but the airplane is handled beautifully, no matter what you're doing. And so, uh, and so there are many, many places to innovate, but actually pilot experience, not one of them, >>Because the more conventional you can make it for people like your brother, the easier it's going to be for them to learn the aircraft. And therefore the safer it's going to be to fly. I'll let them know, like this has been fantastic, really exciting to see what boom supersonic is doing and the opportunities to make supersonic travel accessible. And I think at a time when everybody wants the world to open up, so by 20, 26, I'm going to be looking for my ticket. Awesome. Can't wait to have you on board. Likewise for Blake shul, I'm Lisa Martin. You're watching the QS live coverage of AWS reinvent 2020.

>>covering the space and cybersecurity symposium 2020 hosted by Cal poly. Hold on. Welcome to this special presentation with Cal poly hosting the space and cybersecurity symposium, 2020 virtual, um, John for your host with the cube and Silicon angle here in our Palo Alto studios with our remote guests, we couldn't be there in person, but we're going to be here remotely. Got a great session and a panel for one hour topic preparing students for the jobs of today and tomorrow, but a great lineup. Bill Britain, Lieutenant Colonel from the us air force, retired vice president for information technology and CIO and the director of the California cyber security Institute for Cal poly bill. Thanks for joining us, dr. Amy Fisher, who's the Dean of the college of engineering at Cal poly and trunk fam professor and researcher at the U S air force Academy. Folks, thanks for joining me today. >>Our pleasure got a great, great panel. This is one of my favorite topics preparing students for the next generation, the jobs for today and tomorrow. We've got an hour. I'd love you guys to start with an opening statement, to kick things off a bill. We'll start with you. Well, I'm really pleased to be, to start on this. Um, as the director for the cybersecurity Institute and the CIO at Cal poly, it's really a fun, exciting job because as a Polytechnic technology, as such a forefront in what we're doing, and we've had a, a wonderful opportunity being 40 miles from Vandenberg air force base to really look at the nexus of space and cyber security. And if you add into that, uh, both commercial government and civil space and cybersecurity, this is an expanding wide open time for cyber and space. In that role that we have with the cyber security Institute, we partner with elements of the state and the university. >>And we try to really add value above our academic level, which is some of the highest in the nation and to really merge down and go a little lower and start younger. So we actually are running the week prior to this showing a cybersecurity competition for high schools or middle schools in the state of California, that competition this year is based on a scenario around hacking of a commercial satellite and the forensics of the payload that was hacked and the networks associated with it. This is going to be done using products like Wireshark autopsy and other tools that will give those high school students. What we hope is a huge desire to follow up and go into cyber and cyber space and space and follow that career path. And either come to Cal poly or some other institution that's going to let them really expand their horizons in cybersecurity and space for the future >>Of our nation. >>Bill, thanks for that intro, by the way, it's gonna give you props for an amazing team and job you guys are doing at Cal poly, that Dex hub and the efforts you guys are having with your challenge. Congratulations on that great work. Thank you >>Star team. It's absolutely amazing. You find that much talent in one location. And I think Amy is going to tell you she's got the same amount of talent in her staff. So it's, it's a great place to be. >>Amy flasher. You guys have a great organization down there, amazing curriculum, grazing people, great community, your opening statement. >>Hello everybody. It's really great to be a part of this panel on behalf of the Cal poly college of engineering here at Cal poly, we really take preparing students for the jobs of today and tomorrow completely seriously. And we claim that our students really graduate. So they're ready day one for their first real job, but that means that in getting them to that point, we have to help them get valuable and meaningful job experience before they graduate, but through our curriculum and through multiple internship or summer research opportunities. So we focus our curriculum on what we call a learn by doing philosophy. And this means that we have a combination of practical experience and learn by doing both in and out of the classroom. And we find that to be really critical for preparing students for the workforce here at Cal poly, we have more than 6,000 engineering students. >>We're one of the largest undergraduate engineering schools in the country. Um, and us news ranks us the eighth best undergraduate engineering program in the, in the country and the top ranked state school. We're really, really proud that we offer this impactful hands on engineering education that really exceeds that of virtually all private universities while reaching a wider audience of students. We offer 14 degree programs and really we're talking today about cyber and space. And I think most of those degree programs can really make an impact in the space and cybersecurity economy. And this includes not only things like Aero and cyber directly, but also electrical engineering, mechanical engineering, computer engineering, materials, engineering, even manufacturing, civil and biomedical engineering. As there's a lot of infrastructure needs that go into supporting launch capabilities. Our aerospace program graduates hundreds of aerospace engineers, and most of them are working right here in California. >>I'm with many of our corporate partners, including Northrop Grumman, Lockheed, Boeing, Raytheon space, X, Virgin, galactic JPL, and so many other places where we have Cal poly engineer's impacting the space economy. Our cybersecurity focus is found mainly in our computer science and software engineering programs. And it's really a rapidly growing interest among our students. Computer science is our most popular major and industry interest and partnerships are integrated into our curriculum. And we do that oftentimes through support from industry. So we have partnerships with Northrop Grumman for professorship and a cyber lab and from PG and E for critical infrastructure, cybersecurity lab, and professorship. And we think that industry partnerships like these are really critical to preparing students for the future as the field's evolving so quickly and making sure we adapt our facilities and our curriculum to stay in line with what we're seeing in industry is incredibly important. >>In our aerospace program, we have an educational partnership with the air force research labs. That's allowing us to install new high performance computing capabilities and a space environments lab. That's going to enhance our satellite design capabilities. And if we talk about satellite design, Cal poly is the founding home of the cube sat program, which pioneered small satellite capabilities. And we remain the worldwide leader in maintaining the cube set standard. And our student program has launched more cube sets than any other program. So here again, we have this learn by doing experience every year for dozens of aerospace, electrical, computer science, mechanical engineering students, and other student activities that we think are just as important include ethical hacking through our white hat club, Cal poly space systems, which does really, really big rocket launches and our support program for women in both of these fields like wish, which is women in software and hardware. >>Now, you know, really trying to bring in a wide variety of people into these fields is incredibly important and outreach and support to those demographics. Traditionally underrepresented in these fields is going to be really critical to future success. So by drawing on the lived experiences by people with different types of backgrounds, while we develop the type of culture and environment where all of us can get to the best solution. So in terms of bringing people into the field, we see that research shows, we need to reach kids when they're in late elementary and middle schools to really overcome that cultural bias that works against diversity in our fields. And you heard bill talking about the cyber cybersec, the California cybersecurity institutes a year late cyber challenge. There's a lot of other people who are working to bring in a wider variety of, uh, of people into the field, like girl Scouts, which has introduced dozens of new badges over the past few years, including a whole cybersecurity series of badges and a concert with Palo Alto networks. So we have our work cut out for us, but we know what we need to do. And if we're really committed to prep properly preparing the workforce for today and tomorrow, I think our future is going to be bright. I'm looking forward to our discussion today. >>Yeah, you got a flashy for great, great comment, opening statement and congratulations. You got the right formula down there, the right mindset, and you got a lot of talent and community as well. Thank thank you for that opening statement. Next step from Colorado Springs, trunk fam, who's a professor and researcher. The us air force Academy is doing a lot of research around the areas that are most important for the intersection of space and technology trunk. >>Good afternoon, first electric and Cal poli for the opportunity. And today I want to go briefly about cyber security in S application. Whenever we talk about cyber security, the impression is got yes, a new phew that is really highly complex involving a lot of technical area. But in reality, in my personal opinion, it is in be complex because involve many disciplines. The first thing we think about is computer engineering and computer networking, but it's also involving communication sociology, law practice. And this practice of cyber security goes in on the info computer expert, but it's also info everybody else who has a computing device that is connected to the internet. And this participation is obviously every body in today's environment. When we think about the internet, we know that is a good source of information, but come with the convenience of information that we can access. >>We are constantly faced in being from the internet. Some of them, we might be aware of some of them we might not be aware of. For example, when we search on the internet, a lot of time, our browser will be saved and gotten this site is not trusted. So we will be more careful. What about the sites that we trusted? We know getting those salad chicken sites, but they're not a hundred percent good at proof. What happened? It was all side, uh, attack by hacker. And then they will be a silent source that we might not be aware of. So in the reality, we need to be more practicing the, um, cyber security from our SIBO point of view and not from a technical point of view. When we talk about space application, we should know that all the hardware, a computer based tool by computer system and therefore the hardware and the software must go through some certification process so that they can be record that air with the flight. >>What the, when we know that in the certification process is focusing on the functionality of the hardware and software, but one aspect that is explicitly and implicitly required is the security of those components. And we know that those components have to be connected with the ground control station and be communication is through the air, through the layby or signal. So anybody who has access to those communication regular signal will be able to control the space system that we put up there. And we certainly do not want our system to be hijacked by a third party. >>I'm not going to aspect of cybersecurity is we try to design the space system in a very strong manner. So it's almost impossible to hack in, but what about some August week system that might be connected to so strong system? For example, the spare system will be connected to the ground control station and on the ground control station, we have the human controller in those people have cell phone. They are allowed to use cell phones for communication, but at the same time, they are connected to the internet, to the cell phone and their cell phone might be connected to the computer that control the flight software and hardware. So what I want to say is that we try to build strong system and we protected them, but there will be some weaker system that we could not intended, but exists to be connected to our strong system. And those are the points that hacker will be trying to attack. If we know how to control the access to those points, we will be having a much better system for the space system. And when we see the cybersecurity that is requiring the participation everywhere, it's important to Merck that there is a source of opportunity for students to engage the workforce. To concede the obviously student in engineering can focus their knowledge and expertise to provide technological solution, to protect the system that we view. But we also >>Have students in business who can focus to write a business plan to reach the market. We also have student in law who can focus policy governing the cyber security. And we also have student in education who can focus the expert. She should be saying how to teach cyber security practice and students can focus the effort to implement security measures and it implies job opportunity. >>Thank you trunk for those great comments, great technology opportunities, but interesting as well as the theme that we're seeing across the entire symposium and in the virtual hallways that we're hearing conversations and you pointed out some of them, dr. Fleischer did as well. And bill, you mentioned it. It's not one thing. It's not just technology, it's different skills. And, um, Amy, you mentioned that computer science is the hottest degree, but you have the hottest aerospace program in the world. I mean, so all of this is kind of balancing it's interdisciplinary. It's a structural change before we get into some of the, um, how they prepare the students. Can you guys talk about some of the structural changes that are modern now in preparing, um, in these opportunities because societal impact is a law potentially impact it's, it's how we educate there's no cross-discipline skillsets. It's not just get the degree, see out in the field bill, you want to start. >>Well, what's really fun about this job is, is that in the air force, uh, I worked in the space and missile business and what we saw was a heavy reliance on checklist format, security procedures, analog systems, and what we're seeing now in our world, both in the government and the commercial side, uh, is a move to a digital environment. And the digital environment is a very quick and adaptive environment. And it's going to require a digital understanding. Matter of fact, um, the, uh, under secretary of the air force for acquisition, uh, rev recently referenced the need to understand the digital environment and how that's affecting acquisition. So as, as both Amy, um, and trunk said, even business students are now in the >>Cybersecurity business. And, and so, again, what we're seeing is, is the change. Now, another phenomenon that we're seeing in the space world is there's just so much data. Uh, one of the ways that we addressed that in the past was to look at high performance computing. It was a lot stricter control over how that worked, but now what we're seeing these adaptation of cloud cloud technologies in space support, space, data, command, and control. Uh, and so what we see is a modern space engineer who asked to understand digital, has to understand cloud and has to understand the context of all those with a cyber environment. That's really changing the forefront of what is a space engineer, what is a digital engineer and what does a future engineer, both commercial or government? So I think the opportunity for all of these things is really good, particularly for a Polytechnic air force Academy and others that are focusing on a more, uh, widened experiential level of cloud and engineering and other capabilities. >>And I'll tell you the part that as the CIO, I have to remind everybody, all this stuff works for the it stuff. So you've got to understand how your it infrastructures are tied and working together. Um, as we noted earlier, one of the things is, is that these are all relays from point the point, and that architecture is part of your cybersecurity architecture. So again, every component has now become a cyber aware cyber knowledgeable, and in what we'd like to call as a cyber cognizant citizen, where they have to understand the context, patients chip software, that the Fleischer talk about your perspective, because you mentioned some of the things that computer science. Remember when I'm in the eighties, when I got my computer science degree, they call the software engineers, and then you became software developers. And then, so again, engineering is the theme. If you're engineering a system, there's now software involved, um, and there's also business engineering business models. So talk about some of your comments was, you mentioned, computer science is hot. You got the aerospace, you've got these multidisciplines you got definitely diversity as well. It brings more perspectives in as well. Your thoughts on these structural interdisciplinary things. >>I think this is, this is really key to making sure that students are prepared to work in the workforce is looking at the, the blurring between fields no longer are you just a computer scientist, no longer are you just an aerospace engineer? You really have to have an expertise where you can work with people across disciplines. All of these, all of these fields are just working with each other in ways we haven't seen before. And bill brought up data, you know, data science is something that's cross cutting across all of our fields. So we want engineers that have the disciplinary expertise so that they can go deep into these fields, but we want them to be able to communicate with each and to be able to communicate across disciplines and to be able to work in teams that are across disciplines. You can no longer just work with other computer scientists or just work with other aerospace engineers. >>There's no part of engineering that is siloed anymore. So that's how we're changing. You have to be able to work across those, those disciplines. And as you, as Tron pointed out, you know, ethics has to come into this. So you can no longer try to fully separate what we would traditionally have called the, the liberal arts and say, well, that's over there in general education. No ethics is an important part of what we're doing and how we integrate that into our curriculum. So it was communication. So is working on public policy and seeing where all of these different aspects tied together to make the impact that we want to have in the world. So it, you no longer can work solo in these fields. >>Great point. And bill also mentioned the cloud. One thing about the cloud that showed us as horizontal scalability has created a lot of value and certainly data is now horizontal Trung. You mentioned some of the things about cryptography for the kids out there. I mean, you can look at the pathway for career. You can do a lot of tech and, but you don't have to go deep. Sometimes you can go, you can go as deep as you want, but there's so much more there. Um, what technology do you see, how it's going to help students in your opinion? >>Well, I'm a professor in computer science, so I'd like to talk out a little bit about computer programming. Now we, uh, working in complex project. So most of the time we design a system from scratch. We view it from different components and the components that we have either we get it from or some time we get it from the internet in the open source environment, it's fun to get the source code and then work to our own application. So now when we are looking at a Logie, when we talk about encryption, for example, we can easily get the source code from the internet. And the question is, is safe to use those source code. And my, my, my question is maybe not. So I always encourage my students to learn how to write source score distribution, where that I learned a long time ago before I allow them to use the open source environment. And one of the things that they have to be careful, especially with encryption is be quote that might be hidden in the, in the source, get the download here, some of the source. >>So open source, it's a wonderful place to be, but it's also that we have to be aware of >>Great point before we get into some of the common one quick thing for each of you like to get your comments on, you know, the there's been a big movement on growth mindset, which has been a great, I'm a big believer in having a growth mindset and learning and all that good stuff. But now that when you talk about some of these things that we're mentioning about systems, there's, there's an, there's a new trend around a systems mindset, because if everything's now a system distributed systems, now you have space in cyber security, you have to understand the consequences of changes. And you mentioned some of that Trung in changes in the source code. Could you guys share your quick opinions on the, the idea of systems thinking, is that a mindset that people should be looking at? Because it used to be just one thing, Oh, you're a systems guy or galley. There you go. You're done. Now. It seems to be in social media and data. Everything seems to be systems. What's your take dr. Fleischer, we'll start with you. >>Uh, I'd say it's a, it's another way of looking at, um, not being just so deep in your discipline. You have to understand what the impact of the decisions that you're making have on a much broader, uh, system. And so I think it's important for all of our students to get some exposure to that systems level thinking and looking at the greater impact of the decision that they're making. Now, the issue is where do you set the systems boundary, right? And you can set the systems boundary very close in and concentrate on an aspect of a design, or you can continually move that system boundary out and see, where do you hit the intersections of engineering and science along with ethics and public policy and the greater society. And I think that's where some of the interesting work is going to be. And I think at least exposing students and letting them know that they're going to have to make some of these considerations as they move throughout their career is going to be vital as we move into the future. Bill. What's your thoughts? >>Um, I absolutely agree with Amy and I think there's a context here that reverse engineering, um, and forensics analysis and forensics engineering are becoming more critical than ever, uh, the ability to look at what you have designed in a system and then tear it apart and look at it for gaps and holes and problem sets, or when you're given some software that's already been pre developed, checking it to make sure it is, is really going to do what it says it's going to do. That forensics ability becomes more and more a skillset that also you need the verbal skills to explain what it is you're doing and what you found. So the communication side, the systems analysis, >>The forensics analysis side, >>These are all things that are part of that system >>Approach that I think you could spend hours on. And we still haven't really done great job on it. So it's a, it's. One of my fortes is the really the whole analysis side of forensics and it reverse engineering >>Try and real quick systems thinking. >>Well, I'd like to share with you my experience. When I worked in the space patient program at NASA, we had two different approaches. One is a down approach where we design it from the system general point of view, where we put components to complex system. But at the same time, we have the bottom up approach where we have Ken Chile who spent time and effort the individual component. And they have to be expert in those Chinese component. That might be general component the gallery. And in the space station program, we bring together the welcome up engineer, who designed everything in detail in the system manager who manage the system design from the top down. And we meet in the middle and took the idea with compromise a lot of differences. Then we can leave a display station that we are operating to be okay, >>Great insight. And that's the whole teamwork collaboration that, that was mentioning. Thanks so much for that insight. I wanted to get that out there because I know myself as a, as a parent, I'm always trying to think about what's best for my kids in their friends, as they grow up into the workforce. I know educators and leaders in industry would love to know some of the best practices around some of the structural changes. So thanks for that insight, but this topics about students and helping them prepare. Uh, so we heard, you know, be, be multiple discipline, broaden your horizons, think like systems top down, bottom up, work together as a team and follow the data. So I got to ask you guys, there's a huge amount of job openings in cybersecurity. It's well documented and certainly at the intersection of space and cyber, it's only gonna get bigger, right? You're going to see more and more demand for new types of jobs. How do we get high school and college students interested in security as a career at the flagship? We'll start with you in this one. >>I would say really one of the best ways to get students interested in the career is to show them the impact that it's going to have. There's definitely always going to be students who are going to want to do the technology for the technology sake, but that will limit you to a narrow set of students. And by showing that the greater impact that these types of careers are going to have on the types of problems that you're going to be able to solve and the impact you're going to be able to have on the world, around you, that's the word that we really need to get out. And a wide variety of students really respond to these messages. So I think it's really kind of reaching out at the, uh, the elementary, the middle school level, and really kind of getting this idea that you can make a big difference, a big positive difference in the field with some of these careers is going to be really critical. >>Real question, follow up. What do you think is the best entry point? You mentioned middle squad in here, elementary school. This comes, there's a lot of discussions around pipelining and we're going to get into women in tech and under-represented matters later, but you know, is it too early or what's the, what's your feeling on this? >>My feeling is the earlier we can normalize it the better the, uh, if you can normalize an interest in, in computers and technology and building an elementary school, that's absolutely critical. But the dropoff point that we're seeing is between what I would call like late elementary and early middle school. Um, and just kind of as an anecdote, I, for years ran an outreach program for girl Scouts in grades four and five and grade six, seven, and eight. And we had a hundred slots in each program. And every year the program would sell out for girls in grades four and five, and every year we'd have spots remaining in grades six, seven, and eight. And that's literally where the drop-off is occurring between that late elementary and that middle school range. So that's the area that we need to target to make sure we keep those young women involved and interested as we move forward. >>Bill, how are we going to get these kids interested in security? You mentioned a few programs you got. Yeah. I mean, who wants to, who wouldn't want to be a white hat hacker? I mean, yeah, that sounds exciting. Yeah. Great questions. Let's start with some basic principles though. Is let me ask you a question, John, a name for me, one white hat, good person hacker. The name who works in the space industry and is an exemplar for students to look up to, um, you, um, Oh man. I'm hearing really. I can't, I can't, I can't, I can't imagine because the answer we normally get is the cricket sound. So we don't have individuals we've identified in those areas for them to look up to. I was going to be snarky and say, most white hackers won't even use their real name, but, um, there's a, there's an aura around their anonymity here. >>So, so again, the real question is, is how do we get them engaged and keep them engaged? And that's what Amy was pointing out too. Exactly the engagement and sticking with it. So one of the things that we're trying to do through our competition on the state level and other elements is providing connections. We call them ambassadors. These are people in the business who can contact the students that are in the game or in that, uh, challenge environment and let them interact and let them talk about what they do and what they're doing in life would give them a challenging game format. Um, a lot of computer based training, um, capture the flag stuff is great, but if you can make it hands on, if you can make it a learn by doing experiment, if you can make it am personally involved and see the benefit as a result of doing that challenge and then talk to the people who do that on a daily basis, that's how you get them involved. >>The second part is as part of what we're doing is, is we're involving partnership companies in the development of the teams. So this year's competition that we're running has 82 teams from across the state of California, uh, of those 82 teams at six students team, middle school, high school, and many of those have company partners. And these are practitioners in cybersecurity who are working with those students to participate. It's it's that adult connectivity, it's that visualization. Um, so at the competition this year, um, we have the founder of Def con red flag is a participant to talk to the students. We have Vince surf as who is of course, very well known for something called the internet to participate. It's really getting the students to understand who's in this. Who can I look up to and how do I stay engaged with them? >>There's definitely a celebrity aspect of it. I will agree. I mean, the influencer aspect here with knowledge is key. Can you talk about, um, these ambassadors and, and, and how far along are you on that program? First of all, the challenge stuff is anything gamification wise. We've seen that with hackathons is just really works well. Grades, bonding, people who create together kinda get sticky and get very high community aspect to it. Talking about this ambassador thing. What does that industry is that academic >>Absolutely partners that we've identified? Um, some of which, and I won't hit all of them. So I'm sure I'll short changes, but, uh, Palo Alto, Cisco, um, Splunk, um, many of the companies in California and what we've done is identified, uh, schools, uh, to participate in the challenge that may not have a strong STEM program or have any cyber program. And the idea of the company is they look for their employees who are in those school districts to partner with the schools to help provide outreach. It could be as simple as a couple hours a week, or it's a team support captain or it's providing computers and other devices to use. Uh, and so again, it's really about a constant connectivity and, uh, trying to help where some schools may not have the staff or support units in an area to really provide them what they need for connectivity. What that does gives us an opportunity to not just focus on it once a year, but throughout the year. So for the competition, all the teams that are participating have been receiving, um, training and educational opportunities in the game of education side, since they signed up to participate. So there's a website, there's learning materials, there's materials provided by certain vendor companies like Wireshark and others. So it's a continuum of opportunity for the, >>You know, I've seen just the re randomly, just going to random thought, you know, robotics clubs are moving den closer into that middle school area, in fact Fleischer. And certainly in high schools, it's almost like a varsity sport. E-sports is another one. My son just combined made the JV at the college Dean, you know, it's big and it's up and serious. Right. And, um, it's fun. This is the aspect of fun. It's hands on. This is part of the culture down there you learn by doing, is there like a group? Is it like, um, is it like a club? I mean, how do you guys organize these bottoms up organically interest topics? >>So, so here in the college of engineering, uh, when we talk about learning by doing, we have learned by doing both in the classroom and out of the classroom. And if we look at the, these types of, out of the classroom activities, we have over 80 clubs working on all different aspects of many of these are bottom up. The students have decided what they want to work on and have organized themselves around that. And then they get the leadership opportunities. The more experienced students train in the less experienced students. And it continues to build from year after year after year with them even doing aspects of strategic planning from year to year for some of these competitions. So, yeah, it's an absolutely great experience. And we don't define for them how their learned by doing experiences should be, we want them to define it. And I think the really cool thing about that is they have the ownership and they have the interest and they can come up with new clubs year after year to see which direction they want to take it. And, you know, we will help support those clubs as old clubs fade out and new clubs come in >>Trunk real quick. Before we go on the next, uh, talk track, what, what do you recommend for, um, middle school, high school or even elementary? Um, a little bit of coding Minecraft. I mean, what, how do you get them hooked on the fun and the dopamine of, uh, technology and cybersecurity? What's your, what's your take on that? >>On, on this aspect, I like to share with you my experience as a junior high and high school student in Texas, the university of Texas in Austin organized a competition for every high school in Texas. If we phew from poetry to mathematics, to science, computer engineering, but it's not about with university of Texas. The university of Texas is on the serving SSN for the final competition that we divide the competition to be strict and then regional, and then spit at each level, we have local university and colleges volunteering to host it competition and make it fun. >>Also students with private enterprises to raise funding for scholarship. So students who see the competition they get exposed to so they can see different option. They also get a scholarship when they attend university in college. So I've seen the combination in competition aspect would be a good thing to be >>Got the engagement, the aspiration scholarship, you know, and you mentioned a volunteer. I think one of the things I'll observe is you guys are kind of hitting this as community. I mean, the story of Steve jobs and was, was building the Mac, they call it bill Hewlett up in Palo Alto. It was in the phone book and they scoured some parts from them. That's community. This is kind of what you're getting at. So this is kind of the formula we're seeing. So the next question I really want to get into is the women in technology, STEM, underrepresented minorities, how do we get them on cybersecurity career path? Is there a best practices there, bill, we'll start with you? >>Well, I think it's really interesting. First thing I want to add is if I could have just a clarification, what's really cool that the competition that we have and we're running, it's run by student from Cal poly. Uh, so, you know, Amy referenced the clubs and other activities. So many of the, uh, organizers and developers of the competition that we're running are the students, but not just from engineering. So we actually have theater and liberal arts majors and technology for liberal arts majors who are part of the competition. And we use their areas of expertise, set design, and other things, uh, visualization of virtualization. Those are all part of how we then teach and educate cyber in our game effication and other areas. So they're all involved in their learning as well. So we have our students teaching other students. So we're really excited about that. And I think that's part of what leads to a mentoring aspect of what we're providing, where our students are mentoring the other students. And I think it's also something that's really important in the game. Um, the first year we held the game, we had several all girl teams and it was really interesting because a, they, they didn't really know if they could compete. I mean, this is their, their reference point. We don't know if they did better than anybody. I mean, they, they knocked the ball out >>Of the park. The second part then is building that confidence level that they can going back and telling their cohorts that, Hey, it's not this thing you can't do. It's something real that you can compete and win. And so again, it's building that comradery, that spirit, that knowledge that they can succeed. And I think that goes a long way and an Amy's programs and the reach out and the reach out that Cal poly does to schools to develop. Uh, I think that's what it really is going to take. It. It is going to take that village approach to really increase diversity and inclusivity for the community. >>That's the flusher. I'd love to get your thoughts. You mentioned, um, your, your outreach program and the dropoff, some of those data, uh, you're deeply involved in this. You're passionate about it. What's your thoughts on this career path opportunity for STEM? >>Yeah, I think STEM is an incredible career path opportunity for so many people. There's so many interesting problems that we can solve, particularly in cyber and in space systems. And I think we have to meet the kids where they are and kind of show them, you know, what the exciting part is about it, right. But, you know, bill was, was alluding to this. And when he was talking about, you know, trying to name somebody that you can can point to. And I think having those visible people where you can see yourself in that is, is absolutely critical and those mentors and that mentorship program. So we use a lot of our students going out into California, middle schools and elementary schools. And you want to see somebody that's like you, somebody that came from your background and was able to do this. So a lot of times we have students from our national society of black engineers or a society of Hispanic professional engineers or our society of women engineers. >>We have over a thousand members, a thousand student members in our society of women engineers who were doing these outreach programs. But like I also said, it's hitting them at the lower levels too. And girl Scouts is actually distinguishing themselves as one of the leading STEM advocates in the country. And like I said, they developed all these cybersecurity badges, starting in kindergarten. There's a cybersecurity badge for kindergarten and first graders. And it goes all the way up through late high school, the same thing with space systems. And they did the space systems in partnership with NASA. They did the cybersecurity and partnership with Palo Alto networks. And what you do is you want to build these, these skills that the girls are developing. And like bill said, work in and girl led teams where they can do it. And if they're doing it from kindergarten on, it just becomes normal. And they never think, well, this is not for me. And they see the older girls who are doing it and they see a very clear path leading them into these careers. >>Yeah. It's interesting. You used the word normalization earlier. That's exactly what it is. It's life, you get life skills and a new kind of badge. Why wouldn't learn how to be a white, white hat hacker, or have fun or learn new skills just in, in the, in the grind of your fun day. Super exciting. Okay. Trung your thoughts on this. I mean, you have a diverse diversity. It brings perspective to the table in cybersecurity because you have to think like the other, the adversary, you got to be the white headed hippie, a white hat, unless you know how black hat thinks. So there's a lot of needs here for more, more, more points of view. How are we going to get people trained on this from under represented minorities and women? What's your thoughts? >>Well, as a member of, I took a professional society of directed pool in the electronic engineer. You have the, uh, we participate in the engineering week. We'll be ploy our members to local junior high school and high school to talk about our project, to promote the discovery of engineering. But at the same time, we also participate in the science fair that we scaled up flex. As the squad organizing our engineer will be mentoring students, number one, to help them with the part check, but number two, to help us identify talents so that we can recruit them further into the field of STEM. One of the participation that week was the competition of the, what they call future CV. We're still going, we'll be doing a CT on a computer simulation. And in recent year we promote ops smart CV where CT will be connected the individual houses to be added in through the internet. >>And we want to bring awareness of cybersecurity into competition. So we deploy engineer to supervise the people, the students who participate in the competition, we bring awareness, not in the technical be challenged level, but in what we've called the compound level. So speargun will be able to know what is, why to provide cyber security for the smart city that they are building. And at the same time, we were able to identify talent, especially talent in the minority and in the room. And so that we can recruit them more actively. And we also raise money for scholarship. We believe that scholarship is the best way to get students to continue education in Epic college level. So with scholarship, it's very easy to recruit them, to give you and then push them to go further into the cyber security Eylea. >>Yeah. I mean, you know, I see a lot of the parents like, Oh, my kid's going to go join the soccer team, >>Private lessons, and maybe look at a scholarship >>Someday. Well, they only do have scholarships anyway. I mean, this is if they spent that time doing other things, it's just, again, this is a new lifestyle, like the girl Scouts. And this is where I want to get into this whole silo breaking down because Amy, you brought this up and bill, you were talking about as well, you've got multiple stakeholders here with this event. You got, you know, public, you got private and you've got educators. It's the intersection of all of them. It's again, that those, if those silos break down the confluence of those three stakeholders have to work together. So let's, let's talk about that. Educators. You guys are educating young minds, you're interfacing with private institutions and now the public. What about educators? What can they do to make cyber better? Cause there's no real manual. I mean, it's not like this court is a body of work of how to educate cybersecurity is maybe it's more recent, it's cutting edge, best practices, but still it's an, it's an evolving playbook. What's your thoughts for educators, bill? We'll start with you. >>Well, I don't really, I'm going to turn it off. >>I would say, I would say as, as educators, it's really important for us to stay on top of how the field is evolving, right? So what we want to do is we want to promote these tight connections between educators and our faculty and, um, applied research in industry and with industry partnerships. And I think that's how we're going to make sure that we're educating students in the best way. And you're talking about that inner, that confluence of the three different areas. And I think you have to keep those communication lines open to make sure that the information on where the field is going and what we need to concentrate on is flowing down into our educational process. And that, that works in both ways that, you know, we can talk as educators and we can be telling industry what we're working on and what are types of skills our students have and working with them to get the opportunities for our students to work in industry and develop those skills along the way as well. >>And I think it's just all part of this is really looking at, at what's going to be happening and how do we get people talking to each other and the same thing with looking at public policy and bringing that into our education and into these real hands on experiences. And that's how you really cement this type of knowledge with students, not by not by talking to them and not by showing them, but letting them do it. It's this learn by doing and building the resiliency that it takes when you learn by doing. And sometimes you learn by failing, but you just up and you keep going. >>And these are important skills that you develop along the way >>You mentioned, um, um, sharing too. That's the key collaborating and sharing knowledge. It's an open, open world and everyone's collaborating feel private public partnerships. I mean, there's a real private companies. You mentioned Palo Alto networks and others. There's a real intersection there there's, they're motivated. They could, the scholarship opportunities, trunk points to that. What is the public private educator view there? How do companies get involved? What's the benefit for them? >>Well, that's what a lot of the universities are doing is to bring in as part of either their cyber centers or institutes, people who are really focused on developing and furthering those public private partnerships. That's really what my role is in all these things is to take us to a different level in those areas, uh, not to take away from the academic side, but to add additional opportunities for both sides. Remember in a public private partnership, all entities have to have some gain in the process. Now, what I think is really interesting is the timing on particularly this subject space and cyber security. This has been an absolute banner year for space. The Stanhope of space force, the launch of commercial partnership, leaving commercial platforms, delivering astronauts to the space station, recovering them and bringing back the ability of a commercial satellite platform to be launched a commercial platforms that not only launch, but return back to where they're launched from. >>These are things that are stirring the hearts of the American citizens, the kids, again, they're getting interested, they're seeing this and getting enthused. So we have to seize upon that and we have to find a way to connect that public private partnerships is the answer for that. It's not one segment that can handle it all. It's all of them combined together. If you look at space, space is going to be about commercial. It's going to be about civil moving from one side of the earth, to the other via space. And it's about government. And what's really cool for us. All those things are in our backyard. Yeah. That's where that public private comes together. The government's involved, the private sector is involved. The educators are involved and we're all looking at the same things and trying to figure out like this forum, what works best to go to the future. >>You know, if people are bored and they want to look for an exciting challenge, he couldn't have laid it out any clearer. It's the most exciting discipline. It hits everything. I mean, we just talk about space. GPS is everything we do is well tested. Do with satellites. >>I have to tell you a story on that, right? We have a very unique GPS story right in our backyard. So our sheriff is the son of the father of GPS for the air force. So you can't get better than that when it comes to being connected to all those platforms. So we, we really want to say, you know, this is so exciting for all of us because >>It gives everybody a job for a long time. >>You know, the kids that don't think tick toxic, exciting, wait til they see what's going on here with you guys, this program, trunk final word on this from the public side, you're at the air force. You're doing research. Are you guys opening it up? Are you integrating into the private and educational sectors? How do you see that formula playing out? And what's the best practice for students and preparing them? >>I think it's the same in athlete university CP in the engineering program will require our students to be final project before graduation. And in this kind of project, we send them out to work in the private industry. The private company got sponsor. Then they get the benefit of having an intern working for them and they get the benefit of reviewing the students as the prospective employee in the future. So it's good for the student to gain practical experience working in this program. Some, some kind of, we call that a core program, some kind, we call that a capstone program and the company will accept the students on a trial PRCS, giving them some assignment and then pay them a little bit of money. So it's good for the student to earn some extra money, to have some experience that they can put on their resume when they apply for the final of the job. >>So the collaboration between university and private sector is really important. We, when I joined a faculty, normally they already exist that connection. It came from. Normally it came from the Dean of engineering who would whine and dine with companies. We work relationship and sign up women, but it's approach to do a good performance so that we can be credibility to continue the relationship with those company and the students that we selected to send to those company. We have to make sure that they will represent the university. Well, they will go a good job and they will make a good impression. >>Thank you very much for great insight, trunk, bill, Amy, amazing topic. I'd like to end this session with each of you to make a statement on the importance of cybersecurity to space. We'll go Trung bill and Amy Truong, the importance of cybersecurity space statement. >>We know that it's affecting components that we are using and we are connecting to. And normally we use them for personal purpose. But when we connect to the important system that the government public company put into space, so it's really important to practice cyber security and a lot of time, it's very easy to know concept. We have to be careful, but in reality, we tend to forget to partnership the way we forget how to ride safely. And with driving a car, we have a program called defensive driving that requires every two or three years to get. We can get discount. >>We are providing the cyber security practice, not to tell people about the technology, but to remind them not practicing cybersecurity. And it's a requirement for every one of us, bill, the importance of cyber security to space. It's not just about young people. It's about all of us as we grow and we change as I referenced it, you know, we're changing from an analog world to a digital world. Those of us who have been in the business and have hair that looks like mine. We need to be just as cognizant about cybersecurity practice as the young people, we need to understand how it affects our lives and particularly in space, because we're going to be talking about people, moving people to space, moving payloads, data, transfer all of those things. And so there's a whole workforce that needs to be retrained or upskilled in cyber that's out there. So the opportunity is ever expensive for all of us, Amy, the importance of cybersecurity space, >>Uh, and the, the emphasis of cybersecurity is space. Just simply, can't be over emphasized. There are so many aspects that are going to have to be considered as systems get ever more complex. And as we pointed out, we're putting people's lives at stake here. This is incredibly, incredibly complicated and incredibly impactful, and actually really exciting the opportunities that are here for students and the workforce of the future to really make an enormous impact on the world around us. And I hope we're able to get that message out to students, to children >>Today. But these are my really interesting fields that you need to consider. >>Thank you very much. I'm John foray with the cube and the importance of cybersecurity and space is the future of the world's all going to happen in and around space with technology, people and society. Thank you to Cal poly. And thank you for watching the Cypress of computer security and space symposium 2020.

>>from around the globe. It's the Cube covering >>space and cybersecurity. Symposium 2020 hosted by Cal Poly >>Over On Welcome to this Special virtual conference. The Space and Cybersecurity Symposium 2020 put on by Cal Poly with support from the Cube. I'm John for your host and master of ceremonies. Got a great topic today in this session. Really? The intersection of space and cybersecurity. This topic and this conversation is the cybersecurity workforce development through public and private partnerships. And we've got a great lineup. We have Jeff Armstrong's the president of California Polytechnic State University, also known as Cal Poly Jeffrey. Thanks for jumping on and Bang. Go ahead. The second director of C four s R Division. And he's joining us from the office of the Under Secretary of Defense for the acquisition Sustainment Department of Defense, D O D. And, of course, Steve Jake's executive director, founder, National Security Space Association and managing partner at Bello's. Gentlemen, thank you for joining me for this session. We got an hour conversation. Thanks for coming on. >>Thank you. >>So we got a virtual event here. We've got an hour, have a great conversation and love for you guys do? In opening statement on how you see the development through public and private partnerships around cybersecurity in space, Jeff will start with you. >>Well, thanks very much, John. It's great to be on with all of you. Uh, on behalf Cal Poly Welcome, everyone. Educating the workforce of tomorrow is our mission to Cal Poly. Whether that means traditional undergraduates, master students are increasingly mid career professionals looking toe up, skill or re skill. Our signature pedagogy is learn by doing, which means that our graduates arrive at employers ready Day one with practical skills and experience. We have long thought of ourselves is lucky to be on California's beautiful central Coast. But in recent years, as we have developed closer relationships with Vandenberg Air Force Base, hopefully the future permanent headquarters of the United States Space Command with Vandenberg and other regional partners, we have discovered that our location is even more advantages than we thought. We're just 50 miles away from Vandenberg, a little closer than u C. Santa Barbara, and the base represents the southern border of what we have come to think of as the central coast region. Cal Poly and Vandenberg Air force base have partner to support regional economic development to encourage the development of a commercial spaceport toe advocate for the space Command headquarters coming to Vandenberg and other ventures. These partnerships have been possible because because both parties stand to benefit Vandenberg by securing new streams of revenue, workforce and local supply chain and Cal Poly by helping to grow local jobs for graduates, internship opportunities for students, and research and entrepreneurship opportunities for faculty and staff. Crucially, what's good for Vandenberg Air Force Base and for Cal Poly is also good for the Central Coast and the US, creating new head of household jobs, infrastructure and opportunity. Our goal is that these new jobs bring more diversity and sustainability for the region. This regional economic development has taken on a life of its own, spawning a new nonprofit called Reach, which coordinates development efforts from Vandenberg Air Force Base in the South to camp to Camp Roberts in the North. Another factor that is facilitated our relationship with Vandenberg Air Force Base is that we have some of the same friends. For example, Northrop Grumman has has long been an important defense contractor, an important partner to Cal poly funding scholarships and facilities that have allowed us to stay current with technology in it to attract highly qualified students for whom Cal Poly's costs would otherwise be prohibitive. For almost 20 years north of grimness funded scholarships for Cal Poly students this year, their funding 64 scholarships, some directly in our College of Engineering and most through our Cal Poly Scholars program, Cal Poly Scholars, a support both incoming freshman is transfer students. These air especially important because it allows us to provide additional support and opportunities to a group of students who are mostly first generation, low income and underrepresented and who otherwise might not choose to attend Cal Poly. They also allow us to recruit from partner high schools with large populations of underrepresented minority students, including the Fortune High School in Elk Grove, which we developed a deep and lasting connection. We know that the best work is done by balanced teams that include multiple and diverse perspectives. These scholarships help us achieve that goal, and I'm sure you know Northrop Grumman was recently awarded a very large contract to modernized the U. S. I. C B M Armory with some of the work being done at Vandenberg Air Force Base, thus supporting the local economy and protecting protecting our efforts in space requires partnerships in the digital realm. How Polly is partnered with many private companies, such as AWS. Our partnerships with Amazon Web services has enabled us to train our students with next generation cloud engineering skills, in part through our jointly created digital transformation hub. Another partnership example is among Cal Poly's California Cybersecurity Institute, College of Engineering and the California National Guard. This partnership is focused on preparing a cyber ready workforce by providing faculty and students with a hands on research and learning environment, side by side with military, law enforcement professionals and cyber experts. We also have a long standing partnership with PG and E, most recently focused on workforce development and redevelopment. Many of our graduates do indeed go on to careers in aerospace and defense industry as a rough approximation. More than 4500 Cal Poly graduates list aerospace and defense as their employment sector on linked in, and it's not just our engineers and computer sciences. When I was speaking to our fellow Panelists not too long ago, >>are >>speaking to bang, we learned that Rachel sins, one of our liberal arts arts majors, is working in his office. So shout out to you, Rachel. And then finally, of course, some of our graduates sword extraordinary heights such as Commander Victor Glover, who will be heading to the International space station later this year as I close. All of which is to say that we're deeply committed the workforce, development and redevelopment that we understand the value of public private partnerships and that were eager to find new ways in which to benefit everyone from this further cooperation. So we're committed to the region, the state in the nation and our past efforts in space, cybersecurity and links to our partners at as I indicated, aerospace industry and governmental partners provides a unique position for us to move forward in the interface of space and cybersecurity. Thank you so much, John. >>President, I'm sure thank you very much for the comments and congratulations to Cal Poly for being on the forefront of innovation and really taking a unique progressive. You and wanna tip your hat to you guys over there. Thank you very much for those comments. Appreciate it. Bahng. Department of Defense. Exciting you gotta defend the nation spaces Global. Your opening statement. >>Yes, sir. Thanks, John. Appreciate that day. Thank you, everybody. I'm honored to be this panel along with President Armstrong, Cal Poly in my long longtime friend and colleague Steve Jakes of the National Security Space Association, to discuss a very important topic of cybersecurity workforce development, as President Armstrong alluded to, I'll tell you both of these organizations, Cal Poly and the N S. A have done and continue to do an exceptional job at finding talent, recruiting them in training current and future leaders and technical professionals that we vitally need for our nation's growing space programs. A swell Asare collective National security Earlier today, during Session three high, along with my colleague Chris Hansen discussed space, cyber Security and how the space domain is changing the landscape of future conflicts. I discussed the rapid emergence of commercial space with the proliferations of hundreds, if not thousands, of satellites providing a variety of services, including communications allowing for global Internet connectivity. S one example within the O. D. We continue to look at how we can leverage this opportunity. I'll tell you one of the enabling technologies eyes the use of small satellites, which are inherently cheaper and perhaps more flexible than the traditional bigger systems that we have historically used unemployed for the U. D. Certainly not lost on Me is the fact that Cal Poly Pioneer Cube SATs 2020 some years ago, and they set the standard for the use of these systems today. So they saw the valiant benefit gained way ahead of everybody else, it seems, and Cal Poly's focus on training and education is commendable. I especially impressed by the efforts of another of Steve's I colleague, current CEO Mr Bill Britain, with his high energy push to attract the next generation of innovators. Uh, earlier this year, I had planned on participating in this year's Cyber Innovation Challenge. In June works Cal Poly host California Mill and high school students and challenge them with situations to test their cyber knowledge. I tell you, I wish I had that kind of opportunity when I was a kid. Unfortunately, the pandemic change the plan. Why I truly look forward. Thio feature events such as these Thio participating. Now I want to recognize my good friend Steve Jakes, whom I've known for perhaps too long of a time here over two decades or so, who was in acknowledge space expert and personally, I truly applaud him for having the foresight of years back to form the National Security Space Association to help the entire space enterprise navigate through not only technology but Polly policy issues and challenges and paved the way for operational izing space. Space is our newest horrifying domain. That's not a secret anymore. Uh, and while it is a unique area, it shares a lot of common traits with the other domains such as land, air and sea, obviously all of strategically important to the defense of the United States. In conflict they will need to be. They will all be contested and therefore they all need to be defended. One domain alone will not win future conflicts in a joint operation. We must succeed. All to defending space is critical as critical is defending our other operational domains. Funny space is no longer the sanctuary available only to the government. Increasingly, as I discussed in the previous session, commercial space is taking the lead a lot of different areas, including R and D, A so called new space, so cyber security threat is even more demanding and even more challenging. Three US considers and federal access to and freedom to operate in space vital to advancing security, economic prosperity, prosperity and scientific knowledge of the country. That's making cyberspace an inseparable component. America's financial, social government and political life. We stood up US Space force ah, year ago or so as the newest military service is like the other services. Its mission is to organize, train and equip space forces in order to protect us and allied interest in space and to provide space capabilities to the joint force. Imagine combining that US space force with the U. S. Cyber Command to unify the direction of space and cyberspace operation strengthened U D capabilities and integrate and bolster d o d cyber experience. Now, of course, to enable all of this requires had trained and professional cadre of cyber security experts, combining a good mix of policy as well as high technical skill set much like we're seeing in stem, we need to attract more people to this growing field. Now the D. O. D. Is recognized the importance of the cybersecurity workforce, and we have implemented policies to encourage his growth Back in 2013 the deputy secretary of defense signed the D. O d cyberspace workforce strategy to create a comprehensive, well equipped cyber security team to respond to national security concerns. Now this strategy also created a program that encourages collaboration between the D. O. D and private sector employees. We call this the Cyber Information Technology Exchange program or site up. It's an exchange programs, which is very interesting, in which a private sector employees can naturally work for the D. O. D. In a cyber security position that spans across multiple mission critical areas are important to the d. O. D. A key responsibility of cybersecurity community is military leaders on the related threats and cyber security actions we need to have to defeat these threats. We talk about rapid that position, agile business processes and practices to speed up innovation. Likewise, cybersecurity must keep up with this challenge to cyber security. Needs to be right there with the challenges and changes, and this requires exceptional personnel. We need to attract talent investing the people now to grow a robust cybersecurity, workforce, streets, future. I look forward to the panel discussion, John. Thank you. >>Thank you so much bomb for those comments and you know, new challenges and new opportunities and new possibilities and free freedom Operating space. Critical. Thank you for those comments. Looking forward. Toa chatting further. Steve Jakes, executive director of N. S. S. A Europe opening statement. >>Thank you, John. And echoing bangs thanks to Cal Poly for pulling these this important event together and frankly, for allowing the National Security Space Association be a part of it. Likewise, we on behalf the association delighted and honored Thio be on this panel with President Armstrong along with my friend and colleague Bonneau Glue Mahad Something for you all to know about Bomb. He spent the 1st 20 years of his career in the Air Force doing space programs. He then went into industry for several years and then came back into government to serve. Very few people do that. So bang on behalf of the space community, we thank you for your long life long devotion to service to our nation. We really appreciate that and I also echo a bang shot out to that guy Bill Britain, who has been a long time co conspirator of ours for a long time and you're doing great work there in the cyber program at Cal Poly Bill, keep it up. But professor arms trying to keep a close eye on him. Uh, I would like to offer a little extra context to the great comments made by by President Armstrong and bahng. Uh, in our view, the timing of this conference really could not be any better. Um, we all recently reflected again on that tragic 9 11 surprise attack on our homeland. And it's an appropriate time, we think, to take pause while the percentage of you in the audience here weren't even born or babies then For the most of us, it still feels like yesterday. And moreover, a tragedy like 9 11 has taught us a lot to include to be more vigilant, always keep our collective eyes and ears open to include those quote eyes and ears from space, making sure nothing like this ever happens again. So this conference is a key aspect. Protecting our nation requires we work in a cybersecurity environment at all times. But, you know, the fascinating thing about space systems is we can't see him. No, sir, We see Space launches man there's nothing more invigorating than that. But after launch, they become invisible. So what are they really doing up there? What are they doing to enable our quality of life in the United States and in the world? Well, to illustrate, I'd like to paraphrase elements of an article in Forbes magazine by Bonds and my good friend Chuck Beans. Chuck. It's a space guy, actually had Bonds job a fuse in the Pentagon. He is now chairman and chief strategy officer at York Space Systems, and in his spare time he's chairman of the small satellites. Chuck speaks in words that everyone can understand. So I'd like to give you some of his words out of his article. Uh, they're afraid somewhat. So these are Chuck's words. Let's talk about average Joe and playing Jane. Before heading to the airport for a business trip to New York City, Joe checks the weather forecast informed by Noah's weather satellites to see what pack for the trip. He then calls an uber that space app. Everybody uses it matches riders with drivers via GPS to take into the airport, So Joe has lunch of the airport. Unbeknownst to him, his organic lunch is made with the help of precision farming made possible through optimized irrigation and fertilization, with remote spectral sensing coming from space and GPS on the plane, the pilot navigates around weather, aided by GPS and nose weather satellites. And Joe makes his meeting on time to join his New York colleagues in a video call with a key customer in Singapore made possible by telecommunication satellites. Around to his next meeting, Joe receives notice changing the location of the meeting to another to the other side of town. So he calmly tells Syria to adjust the destination, and his satellite guided Google maps redirects him to the new location. That evening, Joe watches the news broadcast via satellite. The report details a meeting among world leaders discussing the developing crisis in Syria. As it turns out, various forms of quote remotely sensed. Information collected from satellites indicate that yet another band, chemical weapon, may have been used on its own people. Before going to bed, Joe decides to call his parents and congratulate them for their wedding anniversary as they cruise across the Atlantic, made possible again by communications satellites and Joe's parents can enjoy the call without even wondering how it happened the next morning. Back home, Joe's wife, Jane, is involved in a car accident. Her vehicle skids off the road. She's knocked unconscious, but because of her satellite equipped on star system, the crash is detected immediately and first responders show up on the scene. In time, Joe receives the news books. An early trip home sends flowers to his wife as he orders another uber to the airport. Over that 24 hours, Joe and Jane used space system applications for nearly every part of their day. Imagine the consequences if at any point they were somehow denied these services, whether they be by natural causes or a foreign hostility. And each of these satellite applications used in this case were initially developed for military purposes and continue to be, but also have remarkable application on our way of life. Just many people just don't know that. So, ladies and gentlemen, now you know, thanks to chuck beans, well, the United States has a proud heritage being the world's leading space faring nation, dating back to the Eisenhower and Kennedy years. Today we have mature and robust systems operating from space, providing overhead reconnaissance to quote, wash and listen, provide missile warning, communications, positioning, navigation and timing from our GPS system. Much of what you heard in Lieutenant General J. T. Thompson earlier speech. These systems are not only integral to our national security, but also our also to our quality of life is Chuck told us. We simply no longer could live without these systems as a nation and for that matter, as a world. But over the years, adversary like adversaries like China, Russia and other countries have come to realize the value of space systems and are aggressively playing ketchup while also pursuing capabilities that will challenge our systems. As many of you know, in 2000 and seven, China demonstrated it's a set system by actually shooting down is one of its own satellites and has been aggressively developing counter space systems to disrupt hours. So in a heavily congested space environment, our systems are now being contested like never before and will continue to bay well as Bond mentioned, the United States has responded to these changing threats. In addition to adding ways to protect our system, the administration and in Congress recently created the United States Space Force and the operational you United States Space Command, the latter of which you heard President Armstrong and other Californians hope is going to be located. Vandenberg Air Force Base Combined with our intelligence community today, we have focused military and civilian leadership now in space. And that's a very, very good thing. Commence, really. On the industry side, we did create the National Security Space Association devoted solely to supporting the national security Space Enterprise. We're based here in the D C area, but we have arms and legs across the country, and we are loaded with extraordinary talent. In scores of Forman, former government executives, So S s a is joined at the hip with our government customers to serve and to support. We're busy with a multitude of activities underway ranging from a number of thought provoking policy. Papers are recurring space time Webcast supporting Congress's Space Power Caucus and other main serious efforts. Check us out at NSS. A space dot org's One of our strategic priorities in central to today's events is to actively promote and nurture the workforce development. Just like cow calling. We will work with our U. S. Government customers, industry leaders and academia to attract and recruit students to join the space world, whether in government or industry and two assistant mentoring and training as their careers. Progress on that point, we're delighted. Be delighted to be working with Cal Poly as we hopefully will undertake a new pilot program with him very soon. So students stay tuned something I can tell you Space is really cool. While our nation's satellite systems are technical and complex, our nation's government and industry work force is highly diverse, with a combination of engineers, physicists, method and mathematicians, but also with a large non technical expertise as well. Think about how government gets things thes systems designed, manufactured, launching into orbit and operating. They do this via contracts with our aerospace industry, requiring talents across the board from cost estimating cost analysis, budgeting, procurement, legal and many other support. Tasker Integral to the mission. Many thousands of people work in the space workforce tens of billions of dollars every year. This is really cool stuff, no matter what your education background, a great career to be part of. When summary as bang had mentioned Aziz, well, there is a great deal of exciting challenges ahead we will see a new renaissance in space in the years ahead, and in some cases it's already begun. Billionaires like Jeff Bezos, Elon Musk, Sir Richard Richard Branson are in the game, stimulating new ideas in business models, other private investors and start up companies. Space companies are now coming in from all angles. The exponential advancement of technology and microelectronics now allows the potential for a plethora of small SAT systems to possibly replace older satellites the size of a Greyhound bus. It's getting better by the day and central to this conference, cybersecurity is paramount to our nation's critical infrastructure in space. So once again, thanks very much, and I look forward to the further conversation. >>Steve, thank you very much. Space is cool. It's relevant. But it's important, as you pointed out, and you're awesome story about how it impacts our life every day. So I really appreciate that great story. I'm glad you took the time Thio share that you forgot the part about the drone coming over in the crime scene and, you know, mapping it out for you. But that would add that to the story later. Great stuff. My first question is let's get into the conversations because I think this is super important. President Armstrong like you to talk about some of the points that was teased out by Bang and Steve. One in particular is the comment around how military research was important in developing all these capabilities, which is impacting all of our lives. Through that story. It was the military research that has enabled a generation and generation of value for consumers. This is kind of this workforce conversation. There are opportunities now with with research and grants, and this is, ah, funding of innovation that it's highly accelerate. It's happening very quickly. Can you comment on how research and the partnerships to get that funding into the universities is critical? >>Yeah, I really appreciate that And appreciate the comments of my colleagues on it really boils down to me to partnerships, public private partnerships. You mentioned Northrop Grumman, but we have partnerships with Lockie Martin, Boeing, Raytheon Space six JPL, also member of organization called Business Higher Education Forum, which brings together university presidents and CEOs of companies. There's been focused on cybersecurity and data science, and I hope that we can spill into cybersecurity in space but those partnerships in the past have really brought a lot forward at Cal Poly Aziz mentioned we've been involved with Cube set. Uh, we've have some secure work and we want to plan to do more of that in the future. Uh, those partnerships are essential not only for getting the r and d done, but also the students, the faculty, whether masters or undergraduate, can be involved with that work. Uh, they get that real life experience, whether it's on campus or virtually now during Covic or at the location with the partner, whether it may be governmental or our industry. Uh, and then they're even better equipped, uh, to hit the ground running. And of course, we'd love to see even more of our students graduate with clearance so that they could do some of that a secure work as well. So these partnerships are absolutely critical, and it's also in the context of trying to bring the best and the brightest and all demographics of California and the US into this field, uh, to really be successful. So these partnerships are essential, and our goal is to grow them just like I know other colleagues and C. S u and the U C are planning to dio, >>you know, just as my age I've seen I grew up in the eighties, in college and during that systems generation and that the generation before me, they really kind of pioneered the space that spawned the computer revolution. I mean, you look at these key inflection points in our lives. They were really funded through these kinds of real deep research. Bond talk about that because, you know, we're living in an age of cloud. And Bezos was mentioned. Elon Musk. Sir Richard Branson. You got new ideas coming in from the outside. You have an accelerated clock now on terms of the innovation cycles, and so you got to react differently. You guys have programs to go outside >>of >>the Defense Department. How important is this? Because the workforce that air in schools and our folks re skilling are out there and you've been on both sides of the table. So share your thoughts. >>No, thanks, John. Thanks for the opportunity responded. And that's what you hit on the notes back in the eighties, R and D in space especially, was dominated by my government funding. Uh, contracts and so on. But things have changed. As Steve pointed out, A lot of these commercial entities funded by billionaires are coming out of the woodwork funding R and D. So they're taking the lead. So what we can do within the deal, the in government is truly take advantage of the work they've done on. Uh, since they're they're, you know, paving the way to new new approaches and new way of doing things. And I think we can We could certainly learn from that. And leverage off of that saves us money from an R and D standpoint while benefiting from from the product that they deliver, you know, within the O D Talking about workforce development Way have prioritized we have policies now to attract and retain talent. We need I I had the folks do some research and and looks like from a cybersecurity workforce standpoint. A recent study done, I think, last year in 2019 found that the cybersecurity workforce gap in the U. S. Is nearing half a million people, even though it is a growing industry. So the pipeline needs to be strengthened off getting people through, you know, starting young and through college, like assess a professor Armstrong indicated, because we're gonna need them to be in place. Uh, you know, in a period of about maybe a decade or so, Uh, on top of that, of course, is the continuing issue we have with the gap with with stamps students, we can't afford not to have expertise in place to support all the things we're doing within the with the not only deal with the but the commercial side as well. Thank you. >>How's the gap? Get? Get filled. I mean, this is the this is again. You got cybersecurity. I mean, with space. It's a whole another kind of surface area, if you will, in early surface area. But it is. It is an I o t. Device if you think about it. But it does have the same challenges. That's kind of current and and progressive with cybersecurity. Where's the gap Get filled, Steve Or President Armstrong? I mean, how do you solve the problem and address this gap in the workforce? What is some solutions and what approaches do we need to put in place? >>Steve, go ahead. I'll follow up. >>Okay. Thanks. I'll let you correct. May, uh, it's a really good question, and it's the way I would. The way I would approach it is to focus on it holistically and to acknowledge it up front. And it comes with our teaching, etcetera across the board and from from an industry perspective, I mean, we see it. We've gotta have secure systems with everything we do and promoting this and getting students at early ages and mentoring them and throwing internships at them. Eyes is so paramount to the whole the whole cycle, and and that's kind of and it really takes focused attention. And we continue to use the word focus from an NSS, a perspective. We know the challenges that are out there. There are such talented people in the workforce on the government side, but not nearly enough of them. And likewise on industry side. We could use Maura's well, but when you get down to it, you know we can connect dots. You know that the the aspect That's a Professor Armstrong talked about earlier toe where you continue to work partnerships as much as you possibly can. We hope to be a part of that. That network at that ecosystem the will of taking common objectives and working together to kind of make these things happen and to bring the power not just of one or two companies, but our our entire membership to help out >>President >>Trump. Yeah, I would. I would also add it again. It's back to partnerships that I talked about earlier. One of our partners is high schools and schools fortune Margaret Fortune, who worked in a couple of, uh, administrations in California across party lines and education. Their fifth graders all visit Cal Poly and visit our learned by doing lab and you, you've got to get students interested in stem at a early age. We also need the partnerships, the scholarships, the financial aid so the students can graduate with minimal to no debt to really hit the ground running. And that's exacerbated and really stress. Now, with this covert induced recession, California supports higher education at a higher rate than most states in the nation. But that is that has dropped this year or reasons. We all understand, uh, due to Kobe, and so our partnerships, our creativity on making sure that we help those that need the most help financially uh, that's really key, because the gaps air huge eyes. My colleagues indicated, you know, half of half a million jobs and you need to look at the the students that are in the pipeline. We've got to enhance that. Uh, it's the in the placement rates are amazing. Once the students get to a place like Cal Poly or some of our other amazing CSU and UC campuses, uh, placement rates are like 94%. >>Many of our >>engineers, they have jobs lined up a year before they graduate. So it's just gonna take key partnerships working together. Uh, and that continued partnership with government, local, of course, our state of CSU on partners like we have here today, both Stephen Bang So partnerships the thing >>e could add, you know, the collaboration with universities one that we, uh, put a lot of emphasis, and it may not be well known fact, but as an example of national security agencies, uh, National Centers of Academic Excellence in Cyber, the Fast works with over 270 colleges and universities across the United States to educate its 45 future cyber first responders as an example, so that Zatz vibrant and healthy and something that we ought Teoh Teik, banjo >>off. Well, I got the brain trust here on this topic. I want to get your thoughts on this one point. I'd like to define what is a public private partnership because the theme that's coming out of the symposium is the script has been flipped. It's a modern error. Things air accelerated get you got security. So you get all these things kind of happen is a modern approach and you're seeing a digital transformation play out all over the world in business. Andi in the public sector. So >>what is what >>is a modern public private partnership? What does it look like today? Because people are learning differently, Covert has pointed out, which was that we're seeing right now. How people the progressions of knowledge and learning truth. It's all changing. How do you guys view the modern version of public private partnership and some some examples and improve points? Can you can you guys share that? We'll start with the Professor Armstrong. >>Yeah. A zai indicated earlier. We've had on guy could give other examples, but Northup Grumman, uh, they helped us with cyber lab. Many years ago. That is maintained, uh, directly the software, the connection outside its its own unit so that students can learn the hack, they can learn to penetrate defenses, and I know that that has already had some considerations of space. But that's a benefit to both parties. So a good public private partnership has benefits to both entities. Uh, in the common factor for universities with a lot of these partnerships is the is the talent, the talent that is, that is needed, what we've been working on for years of the, you know, that undergraduate or master's or PhD programs. But now it's also spilling into Skilling and re Skilling. As you know, Jobs. Uh, you know, folks were in jobs today that didn't exist two years, three years, five years ago. But it also spills into other aspects that can expand even mawr. We're very fortunate. We have land, there's opportunities. We have one tech part project. We're expanding our tech park. I think we'll see opportunities for that, and it'll it'll be adjusted thio, due to the virtual world that we're all learning more and more about it, which we were in before Cove it. But I also think that that person to person is going to be important. Um, I wanna make sure that I'm driving across the bridge. Or or that that satellites being launched by the engineer that's had at least some in person training, uh, to do that and that experience, especially as a first time freshman coming on a campus, getting that experience expanding and as adult. And we're gonna need those public private partnerships in order to continue to fund those at a level that is at the excellence we need for these stem and engineering fields. >>It's interesting People in technology can work together in these partnerships in a new way. Bank Steve Reaction Thio the modern version of what a public, successful private partnership looks like. >>If I could jump in John, I think, you know, historically, Dodi's has have had, ah, high bar thio, uh, to overcome, if you will, in terms of getting rapid pulling in your company. This is the fault, if you will and not rely heavily in are the usual suspects of vendors and like and I think the deal is done a good job over the last couple of years off trying to reduce the burden on working with us. You know, the Air Force. I think they're pioneering this idea around pitch days where companies come in, do a two hour pitch and immediately notified of a wooden award without having to wait a long time. Thio get feedback on on the quality of the product and so on. So I think we're trying to do our best. Thio strengthen that partnership with companies outside the main group of people that we typically use. >>Steve, any reaction? Comment to add? >>Yeah, I would add a couple of these air. Very excellent thoughts. Uh, it zits about taking a little gamble by coming out of your comfort zone. You know, the world that Bond and Bond lives in and I used to live in in the past has been quite structured. It's really about we know what the threat is. We need to go fix it, will design it says we go make it happen, we'll fly it. Um, life is so much more complicated than that. And so it's it's really to me. I mean, you take you take an example of the pitch days of bond talks about I think I think taking a gamble by attempting to just do a lot of pilot programs, uh, work the trust factor between government folks and the industry folks in academia. Because we are all in this together in a lot of ways, for example. I mean, we just sent the paper to the White House of their requests about, you know, what would we do from a workforce development perspective? And we hope Thio embellish on this over time once the the initiative matures. But we have a piece of it, for example, is the thing we call clear for success getting back Thio Uh, President Armstrong's comments at the collegiate level. You know, high, high, high quality folks are in high demand. So why don't we put together a program they grabbed kids in their their underclass years identifies folks that are interested in doing something like this. Get them scholarships. Um, um, I have a job waiting for them that their contract ID for before they graduate, and when they graduate, they walk with S C I clearance. We believe that could be done so, and that's an example of ways in which the public private partnerships can happen to where you now have a talented kid ready to go on Day one. We think those kind of things can happen. It just gets back down to being focused on specific initiatives, give them giving them a chance and run as many pilot programs as you can like these days. >>That's a great point, E. President. >>I just want to jump in and echo both the bank and Steve's comments. But Steve, that you know your point of, you know, our graduates. We consider them ready Day one. Well, they need to be ready Day one and ready to go secure. We totally support that and and love to follow up offline with you on that. That's that's exciting, uh, and needed very much needed mawr of it. Some of it's happening, but way certainly have been thinking a lot about that and making some plans, >>and that's a great example of good Segway. My next question. This kind of reimagining sees work flows, eyes kind of breaking down the old the old way and bringing in kind of a new way accelerated all kind of new things. There are creative ways to address this workforce issue, and this is the next topic. How can we employ new creative solutions? Because, let's face it, you know, it's not the days of get your engineering degree and and go interview for a job and then get slotted in and get the intern. You know the programs you get you particularly through the system. This is this is multiple disciplines. Cybersecurity points at that. You could be smart and math and have, ah, degree in anthropology and even the best cyber talents on the planet. So this is a new new world. What are some creative approaches that >>you know, we're >>in the workforce >>is quite good, John. One of the things I think that za challenge to us is you know, we got somehow we got me working for with the government, sexy, right? The part of the challenge we have is attracting the right right level of skill sets and personnel. But, you know, we're competing oftentimes with the commercial side, the gaming industry as examples of a big deal. And those are the same talents. We need to support a lot of programs we have in the U. D. So somehow we have to do a better job to Steve's point off, making the work within the U. D within the government something that they would be interested early on. So I tracked him early. I kind of talked about Cal Poly's, uh, challenge program that they were gonna have in June inviting high school kid. We're excited about the whole idea of space and cyber security, and so on those air something. So I think we have to do it. Continue to do what were the course the next several years. >>Awesome. Any other creative approaches that you guys see working or might be on idea, or just a kind of stoked the ideation out their internship. So obviously internships are known, but like there's gotta be new ways. >>I think you can take what Steve was talking about earlier getting students in high school, uh, and aligning them sometimes. Uh, that intern first internship, not just between the freshman sophomore year, but before they inter cal poly per se. And they're they're involved s So I think that's, uh, absolutely key. Getting them involved many other ways. Um, we have an example of of up Skilling a redeveloped work redevelopment here in the Central Coast. PG and e Diablo nuclear plant as going to decommission in around 2020 24. And so we have a ongoing partnership toe work on reposition those employees for for the future. So that's, you know, engineering and beyond. Uh, but think about that just in the manner that you were talking about. So the up skilling and re Skilling uh, on I think that's where you know, we were talking about that Purdue University. Other California universities have been dealing with online programs before cove it and now with co vid uh, so many more faculty or were pushed into that area. There's going to be much more going and talk about workforce development and up Skilling and Re Skilling The amount of training and education of our faculty across the country, uh, in in virtual, uh, and delivery has been huge. So there's always a silver linings in the cloud. >>I want to get your guys thoughts on one final question as we in the in the segment. And we've seen on the commercial side with cloud computing on these highly accelerated environments where you know, SAS business model subscription. That's on the business side. But >>one of The >>things that's clear in this trend is technology, and people work together and technology augments the people components. So I'd love to get your thoughts as we look at the world now we're living in co vid um, Cal Poly. You guys have remote learning Right now. It's a infancy. It's a whole new disruption, if you will, but also an opportunity to enable new ways to collaborate, Right? So if you look at people and technology, can you guys share your view and vision on how communities can be developed? How these digital technologies and people can work together faster to get to the truth or make a discovery higher to build the workforce? These air opportunities? How do you guys view this new digital transformation? >>Well, I think there's there's a huge opportunities and just what we're doing with this symposium. We're filming this on one day, and it's going to stream live, and then the three of us, the four of us, can participate and chat with participants while it's going on. That's amazing. And I appreciate you, John, you bringing that to this this symposium, I think there's more and more that we can do from a Cal poly perspective with our pedagogy. So you know, linked to learn by doing in person will always be important to us. But we see virtual. We see partnerships like this can expand and enhance our ability and minimize the in person time, decrease the time to degree enhanced graduation rate, eliminate opportunity gaps or students that don't have the same advantages. S so I think the technological aspect of this is tremendous. Then on the up Skilling and Re Skilling, where employees air all over, they can be reached virtually then maybe they come to a location or really advanced technology allows them to get hands on virtually, or they come to that location and get it in a hybrid format. Eso I'm I'm very excited about the future and what we can do, and it's gonna be different with every university with every partnership. It's one. Size does not fit all. >>It's so many possibilities. Bond. I could almost imagine a social network that has a verified, you know, secure clearance. I can jump in, have a little cloak of secrecy and collaborate with the d o. D. Possibly in the future. But >>these are the >>kind of kind of crazy ideas that are needed. Are your thoughts on this whole digital transformation cross policy? >>I think technology is gonna be revolutionary here, John. You know, we're focusing lately on what we call digital engineering to quicken the pace off, delivering capability to warfighter. As an example, I think a I machine language all that's gonna have a major play and how we operate in the future. We're embracing five G technologies writing ability Thio zero latency or I o t More automation off the supply chain. That sort of thing, I think, uh, the future ahead of us is is very encouraging. Thing is gonna do a lot for for national defense on certainly the security of the country. >>Steve, your final thoughts. Space systems are systems, and they're connected to other systems that are connected to people. Your thoughts on this digital transformation opportunity >>Such a great question in such a fun, great challenge ahead of us. Um echoing are my colleague's sentiments. I would add to it. You know, a lot of this has I think we should do some focusing on campaigning so that people can feel comfortable to include the Congress to do things a little bit differently. Um, you know, we're not attuned to doing things fast. Uh, but the dramatic You know, the way technology is just going like crazy right now. I think it ties back Thio hoping Thio, convince some of our senior leaders on what I call both sides of the Potomac River that it's worth taking these gamble. We do need to take some of these things very way. And I'm very confident, confident and excited and comfortable. They're just gonna be a great time ahead and all for the better. >>You know, e talk about D. C. Because I'm not a lawyer, and I'm not a political person, but I always say less lawyers, more techies in Congress and Senate. So I was getting job when I say that. Sorry. Presidential. Go ahead. >>Yeah, I know. Just one other point. Uh, and and Steve's alluded to this in bonded as well. I mean, we've got to be less risk averse in these partnerships. That doesn't mean reckless, but we have to be less risk averse. And I would also I have a zoo. You talk about technology. I have to reflect on something that happened in, uh, you both talked a bit about Bill Britton and his impact on Cal Poly and what we're doing. But we were faced a few years ago of replacing a traditional data a data warehouse, data storage data center, and we partner with a W S. And thank goodness we had that in progress on it enhanced our bandwidth on our campus before Cove. It hit on with this partnership with the digital transformation hub. So there is a great example where, uh, we we had that going. That's not something we could have started. Oh, covitz hit. Let's flip that switch. And so we have to be proactive on. We also have thio not be risk averse and do some things differently. Eyes that that is really salvage the experience for for students. Right now, as things are flowing, well, we only have about 12% of our courses in person. Uh, those essential courses, uh, and just grateful for those partnerships that have talked about today. >>Yeah, and it's a shining example of how being agile, continuous operations, these air themes that expand into space and the next workforce needs to be built. Gentlemen, thank you. very much for sharing your insights. I know. Bang, You're gonna go into the defense side of space and your other sessions. Thank you, gentlemen, for your time for great session. Appreciate it. >>Thank you. Thank you. >>Thank you. >>Thank you. Thank you. Thank you all. >>I'm John Furry with the Cube here in Palo Alto, California Covering and hosting with Cal Poly The Space and Cybersecurity Symposium 2020. Thanks for watching.