(bright music) (crowd talking indistinctly in the background) >> Hey guys, welcome back to Detroit, Michigan. theCUBE is live at KubeCon + CloudNativeCon 2022. You might notice something really unique here. Lisa Martin with our newest co-host of theCUBE, Savannah Peterson! Savannah, it's great to see you. >> It's so good to be here with you (laughs). >> I know, I know. We have a great segment coming up. I always love talking couple things, cars, one, two, with companies that have been around for a hundred plus years and how they've actually transformed. >> Oh yeah. >> Ford is here. You have a great story about how you, about Ford. >> Ford brought me to Detroit the first time. I was here at the North American International Auto Show. Some of you may be familiar, and the fine folks from Ford brought me out to commentate just like this, as they were announcing the Ford Bronco. >> Satish: Oh wow. >> Which I am still lusting after. >> You don't have one yet? >> For the record. No, I don't. My next car's got to be an EV. Although, ironically, there's a Ford EV right behind us here on set today. >> I know, I know. >> Which we were both just contemplating before we went live. >> It's really shiny. >> We're going to have to go check it out. >> I have to check it out. Yep, we'll do that. Yeah. Well, please welcome our two guests from Ford, Satish Puranam, is here, The Technical Leader at Cloud and Rebecca Risk, Principal Architect, developer relations. We are so excited to have you guys on the program. >> Clearly. >> Thanks for joining us. (all laugh) >> Thank you for having us. >> I love you're Ford enthusiasts! Yeah, that's awesome. >> I drive a Ford. >> Oh, awesome! Thank you. >> I can only say that's one car company here. >> That's great. >> Yes, yes. >> Great! Thank you a lot. >> Thank you for your business! >> Absolutely. (all laugh) >> So, Satish, talk to us a little bit about- I mean I think of Cloud as a car company but it seems like it's a technology company that makes cars. >> Yes. Talk to us about Ford as a Cloud first, technology driven company, and then we're going to talk about what you're doing with Red Hat and Boston University. >> Yeah, I'm like everything that all these cars that you're seeing, beautiful right behind us it's all built on, around, and with technology, right? So there's so much code goes into these cars these days, it's probably, it's mind boggling to think that probably your iPhones might be having less code as opposed to these cars. Everything from control systems, everything is code. We don't do any more clay models. Everything is done digital, 3D, virtual reality and all that stuff. So all that takes code, all of that takes technology. And we have been in that journey for the last- since 2016 when we started our first mobile app and all that stuff. And of late we have been like, heavily invested in Google. Moving a lot of these experiences, data acquisition systems AI/ML modeling for like all the autonomous cars. It's all technology and like from the day it is conceived, to the day it is marketed, to the day when you show up for a servicing, and hopefully soon how you can buy and you know, provide feedback to us, is all technology that drives all of this stuff. So it's amazing for us to see everything that we go and immerse ourselves in the technology. There is a real life thing that we can see what we all do for it, right? So- >> Yes, we're only sorry that our audience can't actually see the car, >> Yep. >> but we'll get some B-roll for you later on. Rebecca, talk a little bit about your role. Here we are at KubeCon, Savannah and I and John were talking when we went live this morning, that this is huge. That the show floor is massive, a lot bigger than last year. The collaboration and the spirit of the community is not only alive and well, as we heard in the keynote this morning, it's thriving. >> Yeah. >> Talk about developer relations at Ford and what you are helping to drive in your role. >> Yeah, so my team is all about helping developers work faster with different platforms that my team curates and produces, so that our developers don't have to deal with all of the details of setting up their environments to actually code. And we have really great people, kind of the top software developers in the company, are part of my team to produce those products that other people can use, and accelerate their development. And we have a great relationship with the developers in the company and outside with the different vendor relationships that we have, to make sure that we're always producing the next platform with the next tech stack that our developers will want to continue to use to produce the really great products that we are all about making at Ford. >> Let's dig in there a little bit because I'm curious and I suspect you both had something to do with it. How did you approach your Cloud Native transformation and how do you evaluate new technologies for the team? >> It's sometimes- many a times I would say it's like dogfooding and like experimentation. >> Yeah. Isn't anything in innovation a lot of- >> Yeah, a lot of experimentation. We started our, as I said, the Cloud Native journey back in 2016 with Cloud Foundry and things, technologies around that. Soon realized, that there was like a lot of buzz around that time. Twelve-Factor was a thing, Stateless was a thing. And then all those Stateful needs to drive the Stateless. So where do we do that thing? And the next logical iteration was Kubernetes was bursting upon the scene at that time. So we started doing a lot of experimentation. >> Like the Kool-Aid man, burst on the Kubernetes scene- >> Exactly right. >> Through the wall. >> So, the question is like, why can't we do? I think we were like crazy enough to say that Kubernetes people are talking about our serverless or Twelve-Factor on Kubernetes. We are crazy enough to do Stateful on Kubernetes and we've been doing it successfully for five years. So it's a lot about experimentation. I think good chunk of experiments that we do do not yield the results that we get, but many a times, some of them are like Gangbusters. Like, other aspects that we've been doing of late is like partnering with Becky and rest of the organization, right? Because they are the people who are like closest to the developers. We are somewhat behind the scenes doing some things but it is Becky and the rest of the architecture teams who are actually front and center with the customers, right? So it is the collaborative effort that we've been working through past few years that has been really really been useful and coming around and helping us to make some of these products really beautiful. >> Yeah, well you make a lot of beautiful products. I think we've all, I think we've all seen them. Something that I think is really interesting and part of why I was so excited for this interview, and kind of nudged John out, was because you've been- Ford has been investing in technology in a committed way for decades and I don't think most people are aware of that. When I originally came out to Dearborn, I learned that you've had a head of VR who happens to be a female. For what it's worth, Elizabeth, who's been running VR for you for two and a half decades, for 25 years. >> Satish: Yep. >> That is an impressive commitment. What is that like from a culture perspective inside of Ford? What is the attitude around innovation and technology? >> So I've been a long time Ford employee. I just celebrated my 29th year. >> Oh, wow! >> Congratulations! >> Wow, congrats! That's a huge deal. >> Yeah, it's a huge deal. I'm so proud of my career and all that Ford has brought to me and it's just a testament. I have many colleagues like me who've been there for their whole career or have done other things and come to Ford and then spent another 20 years with us because we foster the culture that makes you want to stay. We have development programs to allow you to upscale and change your role and learn new things and play with the new technologies that people are interested in doing and really make an impact to our community of developers at Ford or the company itself and the results that we're delivering. So to have that, you know, culture for so many years that people really love to work. They love to work with the people that they're working with. They love to stay engaged and they love the fact that you can have many different careers within the same umbrella, which we call the "blue oval". And that's really why I've been there for so long. I think I probably had 13 very unique and different jobs along the way. It's as if I left, and you know shopped around my skills elsewhere. But I didn't ever have to leave the company. It's been fabulous. >> The cultural change and adoption of- embracing modern technology- Cloud Native automotive software is impressive because a lot of historied companies, you guys have been there a long time, have challenges with that because it's really hard to get an entire moving, you'll call it the blue oval, to change and adapt- >> Savannah: I love that. >> and be willing to experiment. So that that is impressive. Talk about, you go by Becky, so I'll call you Becky, >> Rebecca/Becky: Yeah. >> The developer culture in terms of the developers really being the center of the nucleus of influencing the direction in which the company's going. I imagine that they probably are fairly influential. >> Yeah, so I had a very- one of the unique positions I held was a culture change for our department, Information Technology in 2016. >> Satish: Yeah. >> As the teacher was involved with moving us to the cloud, I was responsible- >> You are the transformation team! This is beautiful. I love this. We've got the right people on the show. >> Yeah, we do. >> I was responsible for changing the culture to orient our employees to pay attention to what do we want to create for tomorrow? What are the kind of skills we need to trust each other to move quickly. And that was completely unique. >> Satish: Yeah. >> Like I had men in the trenches delivering software before that, and then plucked out because they wanted someone, you know who had authentic experience with our development team to be that voice. And it was such a great investment that Ford continues to do is invest in our culture transformation. Because with each step forward that we do, we have to refine what our priorities are. And you do that through culture transformation and culture management. And that's been, I think really, the key to our successful pivots that we've made over the last six years that we've been able to continue to refine and hone where we really want to go through that culture movement. >> Absolutely. I think if I could add another- >> Please. >> spotlight to it is like the biggest thing about Ford has been among various startup-like culture, right? So the idea is that we encourage people to think outside the box, right? >> Savannah: Or outside the oval? >> Right! (laughs) >> Lisa: Outside the oval, yes! >> Absolutely! Right. >> So the question is like, you can experiment with various things, new technologies and you will get all the leadership support to go along with it. I think that is very important too and like we can be in the trenches and talk about all of these nice little things but who the heck would've thought that, you know Kubernetes was announced in 2015, in late 2016, we have early dev Kubernetes clusters already running. 2017, we are live with workloads on Kubernetes! >> Savannah: Early adopters over here. >> Yeah. >> Yeah. >> I'm like all of this thing doesn't happen without lot of foresight and support from the leadership, but it's also the grassroot efforts that is encouraged all along to be on the front end of all of these things and try different things. Some of them may not work >> Savannah: Right. >> But that's okay. But how do we know we are doing something, if you're not failing? We have to fail in order to do something, right? >> Lisa: I always say- >> So I think that's been a great thing that is encouraged very often and otherwise I would not be doing, I've done a whole bunch of stuff at Ford. Without that kind of ability to support and have an appetite for, some of those things would not have been here at all. >> I always say failure is not a bad F-word. >> Satish: Yep. >> Savannah: I love that. >> But what you're talking about there is kind of like driving this hot wheel of experimentation. You have to have the right culture and the mindset- >> Satish: Absolutely. >> to do that. Try fail, move on, learn, iterate, go. >> Satish: Correct. >> You guys have a great partnership with Red Hat and Boston University. You're speaking about that later today. >> Satish: Yes. >> Unpack that for us. What, from a technical perspective, what are you doing and what's it resulting in? >> Yeah, I think the biggest thing is Becky was talking about as during this transformation journey, is lot has changed in very small amount of time. So we traditionally been like, "Hey, here's a spreadsheet of things I need you to deliver for me" to "Here is a catalog of things, you can get it today and be successful with it". That is frightening to several of our developers. The goal, one of the things that we've been working with Q By Example, Red Hat and all the thing, is that how can we lower the bar for the developers, right? Kubernetes is great. It's also a wall of YAML. >> It's extremely complex, number one complaint. >> The question is how can I zero on? I'm like, if we go back think like when we talk about in cars with human-machine interfaces, which parts do I need to know? Here's the steering wheel, here's the gas pedal, or here's the brake. As long as you know these two, three different things you should be fairly be okay to drive those things, right? So the idea of some of the things with enablementing we are trying to do is like reduce that barrier, right? Reduce- lower the bar so that more people can participate in it. >> One of the ways that you did that was Q By Example, right, QBE? >> Satish: Yes, Yes. >> Can you tell us a little bit more about that as you finish this answer? >> Yeah, I think the biggest thing with Q By Example is like Q By Example gives you the small bite-sized things about Kubernetes, right? >> Savannah: Great place to start. >> But what we wanted to do is that we wanted to reinforce that learning by turning into a real world living example app. We took part info, we said, Hey, what does it look like? How do I make sure that it is highly available? How do I make sure that it is secure? Here is an example YAML of it that you can literally verbatim copy and paste into your editor and click run and then you will get an instant gratification feedback loop >> I was going to say, yeah, they feel like you're learning too! >> Yes. Right. So the idea would be is like, and then instead of giving you just a boring prose text to read, we actually drop links to relevant blog posts saying that, hey you can just go there. And that has been inspirational in terms of like and reinforcing the learning. So that has been where we started working with the Boston University, Red Hat and the community around all of that stuff. >> Talk a little bit about, Becky, about some of the business outcomes. You mentioned things like upskilling the workforce which is really nice to hear that there's such a big focus on it. But I imagine too, there's more participation in the community, but also from an end customer perspective. Obviously, everything Ford's doing is to serve the end customers >> Becky: Right. How does this help the end customer have that experience that they really, these days, demand with patience being something that, I think, is gone because of the pandemic? >> Right? Right. So one of the things that my team does is we create the platforms that help Accelerate developers be successful and it helps educate them more quickly on appropriate use of the platforms and helps them by adopting the platforms to be more secure which inherently lead to the better results for our end customers because their data is secure because the products that they have are well created and they're tested thoroughly. So we catch all those things earlier in the cycle by using these platforms that we help curate and produce. And that's really important because, like you had mentioned, this steep learning curve associated with Kubernetes, right? >> Savannah: Yeah. >> So my team is able to kind of help with that abstraction so that we solve kind of the higher complex problems for them so that developers can move faster and then we focus our education on what's important for them. We use things like Q By Example, as a source instead of creating that content ourselves, right? We are able to point them to that. So it's great that there's that community and we're definitely involved with that. But that's so important to help our developers be successful in moving as quickly as they want and not having 20,000 people solve the same problems. >> Satish: (chuckles) Yeah. >> Each individually- >> Savannah: you don't need to! >> and sometimes differently. >> Savannah: We're stronger together, you know? >> Exactly. >> The water level rises together and Ford is definitely a company that illustrates that by example. >> Yeah, I'm like, we can't make a better round wheel right? >> Yeah! So, we have to build upon what we have already been built ahead of us. And I think a lot of it is also about how can we give back and participate in the community, right? So I think that is paramount for us as like, here we are in Detroit so we're trying to recruit and show people that you know, everything that we do is not just old car and sheet metal >> Savannah: Combustion. >> and everything and right? There's a lot of tech goes and sometimes it is really, really cool to do that. And biggest thing for us is like how can we involve our community of developers sooner, earlier, faster without actually encumbering them and saying that, hey here is a book, go master it. We'll talk two months later. So I think that has been another journey. I think that has been a biggest uphill challenge for us is that how can we actually democratize all of these things for everybody. >> Yeah. Well no one better to try than you I would suspect. >> We can only try and hope everything turns out well, right? >> You know, as long as there's room for the bumpers on the lane for if you fail. >> Exactly. >> It sounds like you're driving the program in the right direction. Closing question for you, what's next? Is electric the future? Is Kubernetes the future? What's Ford all in on right now, looking forward? (crowd murmuring in the background) >> Data is the king, right? >> Savannah: Oh, okay, yes! >> Data is a new currency. We use that for several things to improve the cars improve the quality of autonomous driving Is Level 5 driving here? Maybe will be here soon, we'll see. But we are all working towards it, right? So machine learning, AI feedback. How do you actually post sale experience for example? So all of these are all areas that we are working to. We are, may not be getting like Kubernetes in a car but we are putting Kubernetes in plants. Like you order a Marquis or you order a Bronco, you see that here. Here's where in the assembly line your car is. It's taking pictures. It's actually taking pictures on Kubernetes platform. >> That's pretty cool. >> And it is tweeting for you on the Twitter and the social media platform. So there's a lot of that. So it is real and we are doing it. We need more help. A lot of the community efforts that we are seeing and a lot of the innovation that is happening on the floor here, it's phenomenal. The question is how we can incorporate those things into our workflows. >> Yeah, well you have the right audience for that here. You also have the right attitude, >> Exactly. >> the right appetite, and the right foundation. Becky, last question for you. Top three takeaways from your talk today. If you're talking to the developer community you want to inspire: Come work for us! What would you say? >> If you're ready to invest in yourself and upskill and be part of something that is pretty remarkable, come work for us! We have many, many different technical career paths that you can follow. We invest in our employees. When you master something, it's time for you to move on. We have career growth for you. It's been a wonderful gift to me and my family and I encourage everyone to check us out careers.ford.com or stop by our booth if you're happen to be here in person. >> Satish: Absolutely! >> We have our curated job openings that are specific for this community, available. >> Satish: Absolutely. >> Love it. Perfect close. Nailed pitch there. I'm sure you're all going to check out their job page. (all laugh) >> Exactly! And what you talked about, the developer experience, the customer experience are inextricably linked and you guys are really focused on that. Congratulations on all the work that you've done. We got to go get a selfie with that car girl. >> Yes, we do. >> Absolutely. >> We got to show them, we got to show the audience what it looks like on the inside too. We'll do a little IG video. (Lisa laughs) >> Absolutely. >> We will show you that for our guests and my cohost, Savannah Peterson. Lisa Martin here live in Detroit with theCUBE at KubeCon and CloudNativeCon 2022. The one and only John Furrier, who you know gets FOMO, is going to be back with me next. So stick around. (all laugh) (bright music)

>>Yeah. Hello and welcome to the Cubes Presentation of Women in Tech Global Event Celebrating International Women's Day I'm John for a host of the Cube. We had a great guest in Cuba. Alumni Veranda re vice president. Commercial sales for Europe, Middle East and Africa. EMEA at AWS Amazon Web service to great to see you. Thank you for coming in all the way across the pond and the US to Palo Alto from London. >>Thank you, John. Great to see you again. I'm super excited to be part of this particularly special event. >>Well, this is a celebration of International Women's Day. It's gonna continue throughout the rest of the year, and every day is International Women's Day. But you're actually international. Your women in Tech had a great career. We talk that reinvent. Let's step back and walk through your career. Highlights to date. What have been some of the key things in your career history that you can share? >>Uh, thanks, John. It's always nice to reflect on this, you know? Look, I the way I would classify my career. First of all, it's very it's been very international. I was born and raised in India I went to study in the US It was always a dream to go do that. I did my masters in Boston University. I then worked in the U S. For a good 17 years across A number of tech, uh, tech companies in particular, started my career at McKinsey in the very early days and then moved on to work for E M. C. You'll you'll probably remember them, John. Very well, of course, There now, Del um And then I moved over to Europe. So I've spent the last 18 years here in Europe. Um, and that's been across a couple of different things. I I always classify. Half my career has been strategy, transformation, consulting, and the other half of my career is doing the real job of actually running operations. And I've been, you know, 12 15 years in the tech and telecom sector had the excitement of running Schneider Electric's business in the UK Denniston and Private Equity went back to McKinsey Boomerang, and then a W s called me, and how could I possibly refuse that? So it's been really exciting, I think the one big take away when I reflect on my career is. I've always had this Northstar about leading a business someday, and then I've sort of through my career master set of skills to be able to do that. And I think that's probably what you see. Very eclectic, very mobile, very international and cross industry. Uh, in particular. >>I love the strategy and operations comment because they're both fun, but they're different ones. Very execution, tactical operating. The business strategy is kind of figuring out the future of the 20 mile stare. You know, playing that chess match, so to speak, all great skills and impressive. But I have to ask you, what got you in the tech sector? Why technology? >>Well, so you know, in some ways I kind of fell into it, John, right? Because when I was growing up, my father was always in the tech space, so he had a business and fax machines and he was a reseller of cannon. If you remember Cannon, um, and microfilm equipment and I grew up around him, and he was a real entrepreneur. I mean, always super visionary about new things that were coming out. And so as I followed him around, I said, I kind of wanna be him. And it's a little bit about that sort of role model right early in your career. And then when I moved to the U. S. To study again, it wasn't like I thought I was gonna go to attack. I mean, I wasn't an engineer, you know. I grew up in India with economics degree. That's when women went into We didn't necessarily go into science. But when I joined McKinsey in the early days, I ended up working with, you know, the big companies of the days. You know, the IBMs, the E M. C. Is the Microsoft the oracles, etcetera. So I just then began to love, love the innovation, always being on the sort of bleeding edge. Um, and I guess it was a little bit just fascinating for me not being an engineer to learn how technology had all these applications in terms of how businesses advanced. So I guess, Yeah, that's kind of why I still think it around with it. It's interesting >>how you mentioned how you at that time you pipeline into economics, which is math. Of course. Uh, math is needed for economics, but also the big picture and This is one of the conversation we're having, Uh, this year, the breaking down the barriers for women in tech. Now there's more jobs you don't You don't need to have one pathway into into science or, you know, we're talking stem versus steam arts are super important, being creative. So the barriers to get in are being removed. I mean, if you think about the surface area for technology. So I got to ask you, what barriers do you think Stop girls and young women the most in considering a career in Tech? >>I've got to start with role models, John. Right? Because I think a number of us grew up, by the way, being the only not having the allies in the business, right? All of us, all the all the managers and hiring people are males rather than females. And the fact of the matter is, we didn't have this sort of he for she movement. And I think that's the biggest barrier is not having enough role models and positive role models in the business. I can tell you that research shows that actually, when you have female role models, you tend to hire more and actually what employees say is they feel more supportive when they have actually female managers. So I think there are lots of goodness, but we just need to accelerate how many role models we have. I think the other things I will say to you as well is, if you look at just the curriculum and the ability to get women into stem, right, I mean, we need to have colleges, universities, schools also encouraging women into stem. And you've probably heard about our programme. You know, it's something we do to encourage girls into stem. I think it's really important that teachers and others are actually encouraging girls to do math, for example, right? It's not just about science. Math is great. Logic is great, by the way. Philosophy is great. I just love what you said. I think increasingly, the EQ and EQ parts have to come together, and I think that's what women excel at. Um, so I think that's another very, very big carrier, and then the only other thing I will say is we're gonna watch the language we use, like when I think about job descriptions, they tend to be very male oriented languages we look at CVS now, if you haven't been a female in tech for a long time, your CV isn't going to show a lot of tech, is it? So for recruiters out there, look for competencies. Look for capabilities. You mentioned strategy and arts earlier. We have this leadership principles, As you know, John, really well, think big and dive deep, right? That strategy and operations. And so I think we we need to recruit for that. And we need to recruit for culture. And we need to recruit for people with ambition, an aspiration and not always Just look at 20 years of experience because you're not gonna find it. So I think those are some of the big barriers. Um, that I that I at least think, is stopping women from getting into town. But the biggest one is not enough women at the top hiring women. >>I think people want to see themselves, or at least an aspirational version of what they could be. And I think that's only gonna get better. Lots changed. A lot has happened over the years, but now, with technology in everyone's life, covid pulled forward a lot of realities. You know, the current situation in Europe where you're you are now has pulled forward a lot of realities around community, cyber, digital, our lives. And I think this opens up new positions, clearly cybersecurity. And I'm sure the job boards in every company is hiring people that didn't exist years ago, but also this new problems to solve. So the younger generation coming up, um, is gonna work on these problems, and they need to have role models. So what's your reaction to that? You know, new problems are opportunities their new so usually solved by probably the next generation. Uh, they need mentors. All this kind of works together. What's your reaction? >>Yeah, and, you know, let me pick up on something we're doing that I think is really important. I think you have to address age on the pipeline problem, you know, because they're just is a pipeline problem, you know, at the end of the day, And by that, what I mean is, we need to have more and more people with the and I'm not gonna use the word engineering or science. I'm going to use the word digital skills, right? And I think what we've we've committed to doing, John, you know, I'm very proud of this is we said we're gonna train 29 people 29 million people around this world on digital skills for free by 2025. Right, That's gonna help us get that pipeline going. The other thing we do is something called Restart where we actually do 12 weeks of training for the under, employed and under served right and underrepresented communities. And that means in 12 weeks we can get someone. And you know, this case I talk to you about this before I love it. Fast food operator to cloud, right? I mean, that's that's what I call changing the game on pipeline. But But here's the other stand. Even if the pipeline is good and we often see that the pipeline can be as much as 50% at the very early career women, by the time you get into the C suite, you're not a 50 anymore. You're less than 20%. So the other big thing John there, and this comes back to the types of roles you have an opportunities you create. We've got to pull women through the pipeline. We've really got to encourage that there are sponsors and not just mentors. I think women are sorry to say this over mentored and under sponsored. We need more people say I'm gonna open the door for you and create the opportunity I had that advantage. I hit people through my career. By the way, they were all men, right? Who actually stood out there and bang on the door and said, Okay, Tunisia is gonna go do this. And my first break I remember was having done strategy all my life when the CEO come into the room and you said, You're gonna better locks and you're gonna go run the P and L in Benelux and I almost fainted because I thought, Oh, my God, I've never run a PNR before But it's that type of risk taking that's going to be critical. And I think we've got to train our leaders and our managers to have those conversations be the sponsors, get that unconscious bias training. We all have it. Every single one of us has it. I think those are the combinations of things that are going to actually help open the door and make a see that Actually, it's not just about coding. It's actually about sales. It's about marketing. It's about product management. It's about strategy. It's about sales operations. It's about really, really thinking differently about your customers, right? And that's the thing that I think is attractive about technology. And you know what? Maybe that leads you to eventually become a coder. Or maybe not. Maybe you enter from coding, but those are all the range is available to you in technology, which is not good at advertising, >>that there's more applications than ever before. But I love your comment about over mentoring and under sponsored. Can you quickly just define the difference between those two support elements sponsoring versus, uh, mentoring sponsoring >>So mentors And by the way they can range from my son is my mentor, you know, is a great reverse mentor. By the way, I really encourage you to have the reverse mentoring going. So many mentors are people from all walks of your life, right? And you should have, you know, half a dozen of those. At least I think right who are going to be able to help you deal with situations, help coach you give you feedback respond to concerns You're having find ways for you to navigate all the stuff you need, by the way. Right? And feedback the gift we need that sponsors. It's not about the feedback. Necessarily. It's people who literally will create opportunities for you. Mentors don't necessarily do that. Sponsors will say you You know what? We got the phone. Call John and say, John, I've got the perfect person for you. You need to go speak to her. That's the big difference. John and a couple of sponsors. It's not about many, >>and that's where the change happens. I love that comment. Good call. I'm glad I could double down on that. Now that you have the environment, pipeline and working, you have the people themselves in the environment getting better sponsors and mentors, hopefully working more and more together. But once they're in the environment, they still got to be part of it. So as girls and young women and to the working sector for tech, what advice would you give them? Because now they're in the game there in the arena. So what advice would you give them? Because the environments they are now >>yeah, yeah. I mean, Gosh, John, it's you know, you've lived your career in this space. It's an exciting place to be right. Um, it's a growth opportunity. And I think that's a really important point because the more you enter sectors where there's a lot of growth and I would say hyper right growth, that's just gonna open the doors to so many more things. If you're in a place where it's all about cost cutting and restructuring, do you know what? It's super hard to really compete and have fun, right? And as we say, make history. So it's an exciting place. Today's world transformation equals digital transformation, right? So tech is the place to be, because tech is about transformation, Right? So coming in here, the one advice I would give you is Just do it because believe me, there's so much you can do, like take the risk, find someone is going to give you that entree point and get in the door right? And look, you know what's the worst that could happen? The worst that could happen is you don't like it. Fine. There's lots of other things than to go to. So my advice is, you know, don't take the mm. The really bad tips I've received in my career, right? Don't let people tell you you can't do it. You're not good enough. You don't have the experience, right? It's a male's world. You're a woman. It's all about you and not about EQ. Because that's just rubbish, Frankly, right. The top tip I was ever given was actually to take the risk and go for it. And that was my father. And then all these other sponsors I've had around the way. So that's that's the one thing I would say. The other thing I will say to you is the reason I advise it and the reason you should go for it. It's purposeful. Technology is changing our lives, you know, And we will all live to be no longer. 87 I think 100 right? And so you have the opportunity to change the course of the world by coming to technology. The vaccine deployment John was a great example, right? Without cloud, we couldn't have launch these vaccines as fast as we did. Right? Um, so I think there's a tonne of purpose. You've got to get in and then you've got to find. As I said, those sponsors, you've got to find those mentors. You've got to not worry about vertical opportunities and getting promoted. You gotta worry about horizontal opportunities, right? And doing the things that I needed to get the skills that you require, right? I also say one thing. Um, don't Don't let people tell you not to speak up, not to express your opinion. Do all of the above be authentic, Be authentic style. You will see more role models. Many, many more role models are gonna come out in tech that are going to be female role models. And actually, the men are really stepping up to the role models. And so we will be better together. And here's the big thing. We need you. We can do this without women. There's no possible way that we will be able to deliver on the absolute incredible transformation we have ahead of us without you. >>Inclusion, Diversity equity. These are force multipliers for companies. If applied properly, it's competitive advantage. And so breaking the bias. The theme this year is super super important. It sounds like common sense, but the reality is you break the bias It's not just women as men, as all of us. What can we do? Better to bring that force multiplier capabilities and competitive advantage of inclusion, diversity, equity to business. >>So the first thing I would say and my doctor used to always tell me this if it hurts, don't do it right. I would say to you just do it. Get diverse teams in place because if you have diverse teams, you have diversity of thought. You don't have to worry as much about bias because, you know, you've got the people around the table who actually represent the world. We also do something really cool. We have something called biassed busters. And so in meetings we have bias borders. People are going to, like, raise their hand and say, I'm not sure that that was really meant the way it was supposed to be, So I think that's just a nice little mechanism that we have here, Um, in a W s that helps. The other thing I would say to you is being your authentic self. You can't be a man and mentioned be women, and you're not gonna replicate somebody else because you're never gonna succeed if you do that, you know? So I would say be your authentic self all of the time, You know, we know. We know that women are sometimes labelled as aggressive when they're really not. Don't worry about it. It's not personal. I think the main thing you have to do is and I advise women all the time Is calibrate the feedback you're getting okay? Don't catastrophizing it right. Calibrate it. Taken in, you don't have to react to every feedback in the world, right? And make sure that you're also conscious of your own biases, right? So I think those are my Those are my two cents John for what they were for breaking device. I love the thing. >>Be yourself, You know, Don't take it too personal. Have some fun. That's life. That's a life lesson. Um, Final question, while I got you here, you're a great inspiration, and you're a great role model. You're running a very big business for Amazon web services. Europe, Middle East and Africa is a huge territory. It's its own thing. It's It's like you're bigger than some companies out there. Your role in your organisation. What's the hot area out there you were talking before camera. That's emerging areas that you're focused on. People are watching this young women, young ladies around the world. We're gonna look at this and say, What wave should I jump on? What's the hot things happening in in Europe? Middle Eastern Africa? >>I think the three things I would mention and I'm sure there's I'm sure, John, as we've spoken to my peers across the other gos, right, there are some similarities. The very, very hot thing right now is sustainability. Um, and you know, people are really building sustainability into their strategy. It's no longer sort of just an E S G goal in itself. It's actually very much part of changing the way they do business. So I think that's the hard part. And that's why again, I think it's a phenomenal place to be. I think the other big thing that we're absolutely talking about a lot is, and you know, this is getting even more complicated right now is just around security and cyber security and where that's going and how can we be really thinking about how we address some of these concerns that are coming out and I think there's There's something. There's a lot to be said about the way we build our infrastructure in terms of that context. So I think that's the second one. I think the third one is. People are really looking at technology to change the way businesses operate. So how does HR operate? How do you improve your employee value proposition? How do you do marketing in the next generation? How do you do finance in the next generation? So across the business is no longer the place of I t. It really is about changing the way we are as businesses and all of us becoming tech companies at the core. So the big thing there, John, is data data at the heart of everything we do data not because it's there in front of you, but data because you can actually make decisions on the back of it. So those are the things, Um, I seem to come across a lot more than anything else. >>It's always great to talk to you, your senior leader at AWS, um, inspirational to many. And thank you for taking the time to speak with us here on this great event. Women in text. Global Celebration of International Women's Day. Thank you so much for your time. >>Thank you, John. Always great to talk to you. >>We will definitely be keeping in touch More storeys to be had and we're gonna bring it to you. This is the cubes continuing presentation of women in tech. A global event celebrating International Women's Day. I'm John for your host. Thanks for watching. Yeah.

>>mhm Yes. >>Welcome back to the cubes coverage of red hat summit 2021 virtual. I'm john for a host of the cube we're here in Palo alto. Were remote with our great guest here cube alumni. I've been on many times chris wright, Senior vice president and CTO of red hat chris great to see you. Always a pleasure to have you on the screen here too. But we're not in person but thanks for coming in remote. >>Yeah, you bet. Glad to be here. >>Not only were talking about speeds and feeds, digital transformation going under the hood here we're gonna talk about red hats, expanded collaboration with boston University to help fund education and research for open source projects. So you guys have a huge relationship with boston University. Talk about this continued commitment. What's the news, what's the, what's the story? >>Well, we have a couple different things going on uh and and the relationship we have with the EU is many years in. So this itself isn't brand new. Um one of the things that's important to highlight here is we are giving something north of $550 million dollars worth of software to be you really in pursuit of running uh powering and running scaled infrastructure. That's part of the open hybrid class. Um and that's that's an important piece which we can touch on a little bit as we talk to this conversation. The other one is like I said, this isn't a new relationship with the U. And what we're doing now is really expanding the relationship. So we've we've built a great connection directly with the You were substantially expanding that. Um The original relationship we had was a $5 million relationship spread over five years now. We're talking about a $20 million Relationship spread over five years. So really a significant expansion. And of course that expansion is connected to some of the work that we plan to do together in this open hybrid cloud infrastructure and research space. So a lot of things coming together at once to really really advance the red hat ca laboratory at the U. That combined effort in bringing you know, cloud research and open source and all these things together >>and a lot of actually going on. So basically the boston area lot of universities, but I love the shirt you're wearing with his red hat innovation in the open. This is kind of one of those things you also mentioned out of this huge subscription of software grant that's going to be you just a huge number give value for for the boston University. But you also have another project that's been going on the collaborative research and education agreement called red hat collaborative orI Okay, this was in place. You mentioned that. How's that tying in because that was pre existing. Now. You've got the grant, you got your funding more and more research. Talk about how this connects into the open cloud initiative because this is kind of interesting. You're not bringing hybrid cloud kind of research and practical value in A i ops is hot. You can't you can't go anywhere these days without having great observe ability. Cloud native more and more is more complex and you've got these young students and researchers dying and get their hands on it. Take us through the connection between the CA laboratory and open open cloud. >>So the CA laboratory is a clever name that just talks about collaboration and research laboratory type research. And initially the CA laboratory focus was on the infrastructure running the cloud and some of the application workloads that can run on top of an open cloud infrastructure uh that are that's very data centric. And so this is uh an opportunity for multidisciplinary work looking at modeling for um for health care, for example for how you can improve imaging and we've had a great results in this collaboration. Um We've talked at times about the relationship with the boston Children's Hospital and the chris project not related to me, but just similar acronym that spells chris. Um and these things come together in part through connecting relationships to academia, where academia as research is increasingly built in on and around open source software. So if you think of two parallel worlds, open source software development, just the activity of building open source software, it brings so many people together and it moves so quickly that if you're not directly connected to that as an academic researcher, you risk producing academic research results that aren't relevant because it's hard for them to connect back to these large, fast moving projects, which may have invented a solution to the problem you've been focused on as an academic if you're not directly connected. So we see academia and open source coming together to build really a next generation of understanding of the scientific in depth and he's joining the >>train operations you're talking about here though, this is significant because there's dollars behind it, right? There's real money, it's not >>just the right software, >>it's it's a center, it's a joint operation. >>That's right. And so when you think about just the academic research of producing um ideas that manifest themselves as code and software projects, we want to make sure we're first connecting the software projects to open source communities in with our own engineering experience, bringing code into these open, open source projects to just advance the the feeds and speeds and speeds, the kind of functionality the state of the art of the actual project. We're also taking this to a new level with this expanded relationship and that is software today. When you, when you operate software as a cloud, a critical part of the software is the operationalization of that software. So software just sitting there on the shelf doesn't do anybody any good. Even if the shelf is an open source project, it's a tar ball waiting for you to download. If you don't ever grab it and run it, it's not doing anybody any good. And if the challenge of running it is substantial enough that it stops you from using that software, you've created a barrier to the value that's locked inside that project. The focus here is how can we take that the operations experience of running a cloud, which itself is a big complex distributed system, tie some of those experiences back into the projects that are used to build that infrastructure. So you're taking not just the output of the project, but also the understanding of what it takes to run a project and bringing that understanding and even the automation and code associated with that back into the project. So, your operational izing this open source software and you're building deeper understanding of what it means to operate things that scale, including data and data sets that you can use to build models that show how you can create the remediation and closed loop systems with AI and machine learning, you know, sort of synthesizing all the data that you generate out of a big distributed infrastructure and feed that back into the operations of that same infrastructure. So a lot going on there at the same time operationalization as as an open source initiative but also um really the understanding advancement of A I and data centric operations, so ai ops and closed the remediation. >>Yeah, I mean, devops developer and operations to operationalize it and certainly cloud Native put an emphasis on Day two operations, which leads a lot more research, a lot more uh student work on understanding the coding environment. Um so with that I got to ask um I asked you about this uh massachusetts focused or this open cloud initiative because you guys are talking about this open cloud initiative including this massachusetts. Open Cloud, what is that? What is the massachusetts? Open Cloud sounds like you're offering a kind of open person, not just bu but other um Yeah, institutions. >>That's right. So the the M o C massachusetts open cloud is itself a cross um organizational collaboration bringing together five different academic institutions in New England In massachusetts. It's bu it's Harvard mit, its Northeastern and its U. Mass. Coming together to support a common set of infrastructure which is cloud. It's a cloud that runs in a data center and then um it serves a couple of different purposes. One is research on clouds directly. So what does it mean to run a cloud? What does it look like from a research point of view to understand large scale distributed systems? And then the other is more on top. When you have a cloud you can run workloads and those workloads scaled out to do say data processing, looking at the implications of across different fields which could be natural sciences, could be medicine, could be, even political science or social science is really a multidisciplinary view of what it means to leverage a cloud and run data centric workloads on top. So two different areas that are of a focus for the M. O. C. And this becomes this sort of vehicle for collaboration between Red Hat View and the Red Hot Laboratory. >>So I have to ask only because I'm a big fan of the area and I went to one of those schools, is there like a bean pot for technical hackathons where you get all the schools matched up against each other on the mass open cloud and compete for who gets bragging rights and the text city there. >>It's a great question. Not yet. But I'll jot that down here in hell. Up on that. >>Happy to sponsor. We'll we'll do the play by play coverage, you know. Great. >>I love that. Yeah, kind of twitch tv style. The one thing that there is which is very practical is academic research grants themselves are competitive, right? People are vying for research dollars to put together proposals, Bring those proposals to um the agency that's that's that's giving out grants and winning those grants is certainly prestigious. It's important as part of her research institutes continue to fund the work that they're doing. Uh Now we've been associated uh through the work we've done to date with the U. With Yeah almost $15 million 20 papers. So there's there's a lot of work you can't quite call the play by play. It's a >>scoreboard. I mean their numbers you can put numbers on the board. I mean that's what's one of the things you can measure. But let me ask you on those grants. So you're saying this is just the bu you guys actually have data on um the impact of the relationship in terms of grants and papers and stuff like that academic work. >>That's right. That's right. And so those numbers that I'm giving you are examples of how we've worked together with the u to help their faculty generate grant dollars that then fund some of the research that's happening there together with redhead engineers and on and on the infrastructure like the massachusetts Open cloud. >>That's a good way to look at the scoreboard. It's a good point. We have to research that if you don't mind me asking on this data that you have um are all those projects contributing to open source or do they have to be? That's just generic. Is that all of you all papers around bu is part of the research. In other words, I'm trying to think if I'm in open source, has this contributed to me as an >>open source? Yeah, it's a big and complex question because there's so much research that can happen through a research institution. And those research grants tend to be governed with agreements and some of those agreements have intellectual property rights um front and center and might require things like open source software as a result, the stuff that we're working on clearly isn't that focus area of open source software and and research activities that help kind of propel our understanding forward of what does it mean to do large scale distributed systems creation and then operation. So how do you develop software that does it? How do you how do you run the software that builds these big large distributed systems? So we're focused in that area. Um some of the work that we facilitated through that focus includes integrating non open source software that might be part of um same medical imaging. So for example work we've done with the boston Children's Hospital That isn't 100 doesn't require us to be involved 100 of the open source pieces. All the infrastructure there to support it is. And so we're learning how we can build integrated pipelines for data analysis and image analysis and data sharing across different institutions uh at the open source project level. Well maybe we have a specific imaging program that is not generated from this project. And of course that's okay with >>us. You know chris you bring up a good point with all those conversations. I could see this really connecting the dots. Most computer science programs. Most engineering programs haven't really traditionally focused on it at the scale we're talking about because we look at cloud scale but now scaling with hybrid it's real engineering going on to think about the large scale. We know all the big hyper scale ear's right so it's not just I. T. Provisioning you know network connection and doing some I. T. Work. We're talking about large scale. So I have to ask you as you guys look at these relationships with academics uh academia like like bu and others um how are the students responding to this? Are you guys seeing any specific graduate level advancements? Because you're talking about operational roles that are becoming so important whether it's cyber security and as cloud needed because once more data driven you need to have all this new scale engineered up. That's >>what how >>do you look at that? >>There's two different pieces that I would highlight. One is just the data science itself. So schools still need to produce data scientists. And having data is a big part of being a data scientist and knowing what your what your goals are with that data and then experimenting with different techniques, whether it's algorithms or tools. It's a big part of being a data scientist sort of spelunking through the data. So we're helping produce data. We're looking at data science efforts around data that's used to operationalize infrastructure, which is an interesting data science endeavor by itself. The other piece is really what you highlighted, which is there's an emergence of a skill set in the industry, often referred to as SRE site reliability engineering. Um it is a engineering discipline. And if you back up a little bit and you start thinking about what are the underlying principles behind large scale distributed systems, you get to some information theory and computer science. So this isn't just something that you might think of as um some simple training of a few key tools and knowing how to interpret a dashboard. And you're good to go, this is a much more sophisticated view of what does it mean to really operate large scale infrastructure, which to date, there aren't a lot of these large scale infrastructures available to academics to research because their commercial endeavors >>and their new to me. I was talking to some young folks my son's age and daughters age and I was saying, you know, architect in a building, a skyscraper isn't trivial. You can't just do that overnight. There's a lot of engineering that goes on in that science, but you're bringing kind of operating systems theory, systems thinking to distributed computing. I mean that's combination of a interdisciplinary shift and you got, I won't say civil engineering, but like concept is there, you've got structure, you've got networks, they're changing and then you've got software so again completely new area. >>That's right and there's not a lot of even curriculum that explores this space. So one of the opportunity, there's a great program that really focuses on um that that space of site reliability engineering or operational izing software. Um And then the other piece that I'm I'm really excited about is connecting to open source communities so that as we build software, we have a way to run and operationalize that software that doesn't have to be directly tied to a commercial outlet. So products running in the cloud will have a commercial S. L. A. And commercial agreements between the user and the producer of that service. How do you do that in open source context? How do you leverage a community, bring that community software to a community run service, learn through the running of that service. How to best build architect the service itself and then operationalized with the tooling and automation that service? How do you, how do you bring that into the open source community? And that's something that we've been referring to as the operate first initiative. How do you get the operationalization of software? Really thought of as a primary focal point in the software project where you normally think about the internals of software, the features, the capabilities of functionality, less about the operationalization. So important shift at the open source project level, which is something that I think will really be interesting and we'll see a lot of reaping a lot of rewards. Just an open source communities directly. >>Yeah, speed and durability. Certainly having that reliability is great. You know, I love talking with you guys at red hat because, you know, software, you know, open source and you know, operating systems because as it comes together in this modern era, what a great, great fit, great work you're doing with Boston University's and the mass open cloud initiative. Congratulations on that. I got I got to ask you about this Red Hat Graduate Fellows program you have because this kind of speaks to what you guys are doing, you have this kind of this redhead graduate fellows network and the work that's being done. Does that translate into red hat at all? From an engineering standpoint? How does that, how does that work together? >>Basically, what we do is we support um PhD students, we support post docs. So there's a real direct support to the, you know, that is the Red Jack Graduate Fellow program on our focus there is connecting those um uh academics, the faculty members and the students to our engineers to work together on key research initiatives that we think will help drive open source software agendas forward really broad can be in all different areas from security to virtualization too, the operating systems to cloud distributed systems, uh and one of the things that we've discovered is it creates a great relationship with the university and we find students that will be excited to leave university and come into the the industry workforce and work at Red hat. So there is a direct talent relationship between the work that we do at bu and the talent that we can bring into red hat, which is awesome. Uh We know these people we've worked with well with them, but also we're kind of expanding understanding of open source across, you know, more and more of academia, which I think is really valuable and important for red hat. We just go out to the the industry at large, um, and helping bring a set of skills to the industry that whether they're coming, whether these are students that come into red hat or go elsewhere into the industry, these are important skills to have in the industry. So we look at the, how do you work in open source communities? How to operationalize software at scale? These are important things. They didn't >>expand, expand the territory if you will in terms of systems thinking. We just talked about great collaboration. You guys do a great job chris great to have you on a quick final word from you on this year at red hat summer. I know it's virtual again, which we could be in person, but we're starting to come out of the covid kind of post covid right around the corner. Um, what's the update? How would you describe the current state of red hat? Obviously you guys still got that, that vibe. You still pumping strong a lot going on. What's the current? What's the current, uh, bumper sticker? What's the vibe? >>Well, in many ways, because we're so large and distributed. Um, the last year has been, uh, can't say business as usual because it's been an impact on everybody, but it hasn't required us to fundamentally change. And as we work across open source communities, there's been a lot of continuity that's come through a workforce that's gone completely distributed. People are anxious to get to the next phase, whatever back to normal means. Uh, and people at Red Hat are no different. So we're looking forward to what it can mean to spend time with colleagues in offices, were looking forward to what it means to spend time together with our friends and families and travel and all those things. But from a, from a business point of view, Red Hat's focus on the open hybrid cloud and that distributed view of how we work with open source communities. That's something that's, it's only continued to grow and pick up over the course of the last year. So it's clearly an important area for the industry and we've been busier than ever the last year. So, uh, interesting, interesting times for everybody. >>Well, it's great to see and I love how the culture maintains its its relevance, its coolness intersection between software, Open Source and systems. Great, Great working congratulations chris. Thanks for coming on. >>Thank you. >>All right. I'm John for here with the Cube for Red Hat Summit 2021. Thanks for watching. Mhm.

>>mhm Yes. Welcome back to the cubes coverage of red hat summit 2021 virtual john for your host of the cube paul. Comey who's here is the president and Ceo of red hat cube alumni paul always great to have you on the leader of red hat now President and Ceo for a year I think about a year now we're looking at under your belt now part of IBM Great to see you. >>You too nice to see you again john. >>So we've talked many times on the Cuban now. It's kind of playing out in real time. The software world with open source has gone mainstream. The conversation was moved to the cloud. Okay. People move to the cloud. Cloud native emerges devil has been around for a while. But now the conversation is cloud for the enterprise that uh, the enterprises, it's a tough world. You gotta, it's complicated is a lot of legacies, a lot of value and you want the new stuff. This is what the conversation is now. It's shifted to I got cloud, it's hybrid. What's your reaction to that? >>Well, you know, it really is, as you say, it's complicated but it's evolving and really, really fast. I mean, you know, I think you remember we've been here a lot. You first remember first software is eating the world and open source software is eating the world and in every every company is becoming a software company. All true. But that evolution continues today with the proliferation of hybrid cloud environments that it encompasses everything from data centers to public cloud services to And even now we'll talk about two for far flung edge deployments. That's all now part of the cloud. I mean, this is all what makes up hybrid. I like to always say that Hybrid really is the new data centers but now see IOS and I thi leaders, they need to reconsider what their roles, what their role here is and the way we look at it as every C I O now needs to be a cloud operator because because Hybrid is what their environment is now today, that used to be all in their data center. So, so but one of the things that really makes a choice even more important and its leaders, they need to address address specific needs, um not only to the organization, but even as they change and evolve in this because it really is a dynamic environment, I mean think about it and just mentioned edge and how how important that is to see IOS, we weren't even talking about that two years ago, so, so it's not a single answer here, right? Um and and you know, and there as there wasn't a single answer when it was all in one building or in one data center, but now it's even it's even more complex. So, so we need to enable really a new wave of cloud operators here with technologies that can be deployed as cloud services as well as on premises. We'll talk more about this too, but and we'll talk about this at the summit. We talked about the summit. Cloud services become really important, especially managed services, for example, because, um because we're so complex, Hybrid brings so much power, but it is complex. You know, see I need help with this, they need help managing this now. And so that's really where a lot of our focus is today. >>It's interesting you say there's no single answer. I would agree with you because it's now you can actually do a lot more customization with cloud and Hybrid. I think there's a general sentiment and directionally correct answer uh in the industry is that hybrid is operating model right? And I think you guys are have a whole division of SRS google talks about this all the time and their cloud site reliability engineers. And I think you're seeing that in educational institutions which we'll talk about. But I think this idea of cloud scale as the new I. T. And you mentioned hybrids, the new data center. You know, I don't I don't want to offend my I. T. Friends out there but they're kind of all realizing it to that if they don't understand how to operate cloud scale they'll be irrelevant and they're and they understand that their jobs are not just provisioning storage, networking and servers. Those are now involved in a hybrid architecture. And by the way, there is no one recipe, it's dependent. Each enterprise can have its own set of architecture based on their workloads again. So I buy that no single answer, but there is hybrid and I think it's pretty well understood. I mean, do you agree with that? >>I absolutely agree with that. But let's take a look at this, unpack it a little bit and take a look at the building blocks a bit. Right. Um, you know, we talked about open sources, what's driving all of this now and and everything we're talking about here is built in and around Lennox and it was only possible because Lennox was so open, so available and became so powerful, that's now been the platform that all this new innovation is built around. I mean, I oftentimes saying it's true the cloud just wouldn't be here had Lennox not only made its way in the open source development environment, but made its way into the enterprise to enable it to companies like us that make it enterprise ready, secure etcetera. So I think that's really an important thing to understand here. So when you talk about skills that the Ceos need certainly SRE skills, operation skills etcetera, but they also need Lennox skills and even open source skills. So so I think I think that's important, everything that's coming down the road and in in this space in um in his open source based and built in and around Lennox things like ai quantum computing, autonomous vehicles um IOT in and out to the edge all built on a foundation of Lennox and open source. So we see it in the enterprise everywhere now. I mean a survey where you know we did a survey out there and looking at the survey of C I O s out there, open is predominant out there, Lennox is predominant out there in hybrid is predominant and growing in a pretty big clip every year. >>You know, paul, I want to get your reaction to something because this may be kind of a dot connecting moment for me because I want to get your thoughts on this because it's a it's a pattern I'm seeing emerging now multiple times and usually I thought this was kind of a one off, but I'm starting to see it. So I'm going to get your thoughts on this. You guys have been super successful with open source in the enterprise, Super successful over decades, building a community and an ecosystem now with open source with with cloud Native, specifically we're seeing end users participating more in the, in the contribution starts out with the hyper scale ear's but now you're seeing kind of, I would call general purpose mainstream enterprises contributing projects, not necessarily their expertise, but they've been participating in taking the goodness of open source and bringing that into the into the enterprise. And I'll see you relying on you guys as well. But now I'm starting to see the pattern where people are relying on you to bring your community to them and they merge their communities with you guys and being kind of a steward there, is that a pattern? Do you see that evolving? Because we've heard that on multiple interviews on the cube where we've heard end users say we love the red hat ecosystem and and that seems to be more and more about they want to be building their ecosystem. So you did it for yourselves, you did it for the industry. Now, enterprises want this service is this is this is a pattern. And what's your reaction to that? >>It actually is a pattern because it's actually one of the reasons why innovation is moving so quickly right now. As I just said, you know, you know, this whole area here in infrastructure and cloud and development environments, Hybrid included. It's all built in and around, it's all built in and around Lennox. And in the past, what's happening and driven by open source development in the past? What happened? Look at the old fashioned way, right, where a company like us would be in a company, software company, not like us, but any old software company would be, you know, in their stovepipe, talking to their customers, getting their requirements and then bringing those requirements back from the customer base and then trying to work that into their products over time, get that back out to the customer to test it and try it, see it as it works. That's probably a five year, there's probably a five year journey, uh, for big, big requirements for big change requirements you look at now with, with actually end users now participating in upstream development, they're building their requirements into that upstream, which is our development environment. And actually that's what feeds our products. And so we've cut out the middleman, if you will completely in there now when we're building those requirements into our future future, R and D work in the upstream and then we bring that down into a product back into their enterprise for them to use in production. So it cuts out years of time for that innovation to get from concept to building to product, rising to production. And, and I think, you know, john, that's one of the big reasons why that customer base participating is one of the big reason why we're seeing innovation move like we've never seen it before in the enterprise, which in the old days that was a stodgy place where they didn't want to move very quickly. >>Yeah. And the values there, I mean I think it's clear what the pandemic we get to this towards the the last last talking track here. But with the pandemic I think it's pretty clear what the value is and the speed to capture opportunities and growth. I think enterprises are realizing that I think the power of the ecosystem is a modern error kind of phenomenon that is now kind of showing its its value and clearly in the market. And I think people who harness communities and ecosystems not try to fork them but connect them and and intersect them and kind of played well together. So again this is an open source concept kind of re imagined so we'll keep an eye on that. So, um, I want to get to your comment in the kino you mentioned at the top here every C I. O. It has to be a cloud operator. You know, that reminds me of all the start ups and all the positioning statements. Every company needs to be a software company. Every company needs to be a media company. Every company needs to be a cloud operator. So I love that. What does it mean? Because I could say, hey paul, I have a cloud, I'm working on amazon Or is that it? Or wait a minute as yours got, I got 365 over here and I'm using big query over here. I might use oracle over here. I mean all these multi cloud conversations. So it's confusing. >>Yeah. Tell me what, you know, if you look at, if you look at it, we were really one of the first ones to really build around this hybrid, this hybrid concept. And the reason why we were one of the first ones is because what amazon hit the world 12 or 13 years ago or something like that, They were the first major cloud and at the time that the narrative was that, you know, every application was going to move to the cloud tomorrow. Right well, because as I said earlier, everything is built in and in and around open source. And legs were very involved with our customers as they tried to move those first applications to the cloud. So certainly is a lot of value and moving to the cloud. But our customers quickly realized with us helping them, quickly realized that you know what, this is great. But not every application suited for the cloud, um for any cloud, but also I may want to run multiple clouds because another cloud provider over here might have a better service than this particular service over here, vice versa. And so we were in the middle of that. So one of the decisions we made seven or eight years ago, everything we did in that last seven or eight years around the portfolio, whether it was building products, m and A, requiring new companies etcetera, was built around that hybrid portfolio. What that means is a common platform that sits both on premise and bare metal machines. Virtual machines, private clouds on premise multiple clouds across out in the enterprise, that common platform so that developers, operators and the security people have that common platform to build with because just like in Lenox, even though they are all derived from open source upstream, they're all different, they all make different choices and how they're going to configure themselves. So, so that's important. So now we're out there with these multiple clouds. One of our surveys we see our Ceo is telling us now that You're using on the average I think six Clouds today and they expect that to go 8-10 over the next 3-5 years. So how are they going to manage that? How are they going to secure that? How are their operations people going to operate with that? That's all the things that we've been working on over the last number of years. So from that common platform, which is sort of the basis which is open shift to underneath it, which is the Linux operating system, which is well that spans all those footprints that I talked about. And then also you look at one of the latest trends is as well as manage services because what customers are now telling us is okay I got this environment that this hybrid is now my data center. It means I have to worry about these apps all in different footprints. Um I want to the platform to act like a cloud in some cases I don't want to I don't want to even manage it. I want you to manage it for me because for many reasons I want great up time. I might not have the right skill sets in my organization and so I want you to manage it. And so that's where we develop managed services and that's where we have set a large group today large SRE group that's providing those managed services no matter where our platform runs for our customers. Also, what I talked about in my keynote today is that to support that thought process is that we're doing a lot of research in this and so, you know, in a typical computer science research world, you know, of the past, you might really be into the into the real computer science of Research. We with the consortium around mass Open cloud with Boston University, MIT, Harvard Northeastern with this consortium. We're running mass Open cloud on all Red Hat with the collaboration of these universities and we're really focusing on the sorry aspect of it. What do we need to manage it? What do we need around automation to manage it? What do we need around ai to manage it? What do we need for tools to manage it? And and that's really goes down to what I fully briefly said in the beginning, is that every C I O N I T uh executive now has to be their own cloud operator because they are effectively stitching all these disparate clouds together. So that's where a big part of our focus takes us all the way from, You know, upstream development to product to the research we're doing for the next 3-5 plus years. >>You know, I gotta say the hybrid cloud is a new data center which is implying I T in the cloud operators with C X O S and C IOS is interesting because it's validated by Mckinsey's recent report that came out that said there's a trillion dollars of untapped value in one retrofitting existing infrastructure and operations and to net new operate use cases that the cloud enables. So there's clearly not two categories of value proposition that businesses are facing. One is, you know, kind of take care of the existing and then also bring in the new that cloud enables. So, you know, I think that's really key and that will drive the business leaders to foresight, if you will to be agile and adaptive to that. So so totally agree on that. I love this open cloud initiative, you mentioned the mass open cloud which I know is kind of like this beanpot for techies, um people who know what that means, uh it's in the boston area these institutions um this is gonna be a training and an opportunity to train the next generation and if you take it to the next level cybersecurity is also in this kind of net new novelty, interdisciplinary components. So you got engineering which is like devops engineering and then Systems Engineering and Computer Science intersecting together with kind of this data discipline. So it hits cybersecurity which is a board level conversation, it hits the new business model opportunities which is a driver, this is new, this is there's no pre existing curriculum. What how do you explain that to heads of the departments and the deans of these institutions saying, you know, it's an engineering thing. No, it's computer science thing. No, it's a it's a business school thing with data science. What's your what's your conversation with folks in the industry when you say this is a different thing? >>Uh you know, the university, you know, the university is getting, it was actually one of the one of the first things this is you know what you'll see. You know, I talked to uh dr bob Brown from President bu earlier in an interview and and this is what we imagined with them early on and even they brought those disciplines together now in in in what they call a harry institute, where to bring data, computer science engineering as you say. And now even operations, it's almost like, you know, systems engineering on steroids, it's a really big spanning system. And so so the universities are starting understand that's why these universities in the consortium, that's why we're working here. But also, you know, the industry's kind of learning it the hard way because now that they get some of their developers starting to move some of their application developments out into one, maybe two clouds and having the now they have to figure out how they're going to do all those things that we talked about, develop, secure operated. So they're they're learning the hard way that this is the new discipline because that's reality. I also think that, you know, as I said, like anything in tech, we always say this is going to happen tomorrow. I also think, like I said, when when cloud first came came out, everybody saying, I'm moving every app to the cloud tomorrow. We even had customers that bought into that said we're moving going full board but they realized once they get into it it wasn't practical. Don't take me wrong. Cloud brings a ton of value here but from a practical perspective it's going to be some apps and across many clouds and and so now they're having to deal with the I. T. Execs and the C. I. Was having to deal with it. So they're learning really fast because of the reality that they have to deal with. Now having said all that to it also brings up why managed services you're seeing so popular right now because as that's moving so fast they just don't have the skills necessary in many cases to really operate and run in this in this type of environment. It brings so much power but the skills aren't necessarily there in the industry. So that now you see the connection between the industry where we sit and even the university now looking at this whole big problem as as you put said, john, actually a new discipline, >>I think, I think, and I think one final leg of a three legged stool is at the business schools because when you think about systems programming, you mentioned that and you know, I love to go back in history and look at the history of operating systems. And you know, paul, we've talked us in the past and you guys know a lot about operating systems from a technology standpoint, it's not just about a productivity suite for a user or a department with the system, it's a company that needs to be programmed. So when people want to globally operate their business, that software defined this isn't now and this is now happening, right? So this the new leaders in these companies that want to run these global companies that scale operate them, just like operating the business not necessary. Operating a tech or shiny new toy, have to build the operating system for the business. To me, I think that's where I see IBM looking at cloud differently and saying, hey, this is an operating system under the covers for the business. The applications are multi fold from, you know, an application for productivity to an edge device, industrial or consumer user work at home. I mean it's a plethora of applications. What's your reaction to that? And you you see the same thing? >>I mean frankly, I think this is an area that a lot of the infrastructure players missed in the past. And I think I think this is what IBM saw with with bringing us in as well. It's all about the application. You know, I said earlier that, you know, we said every every company was a software company is true. And so that means the companies are running their businesses on these applications. So it's all about the app and I think a lot of infrastructure companies miss that. And and so with Hybrid now you have that ability to run the app wherever makes the most sense for for a whole host of reasons. And so now, but now comes the complexity of all of that. I think, I think IBM with bringing us in saw that that Hybrid was maybe as big, if not a bigger opportunity than cloud itself because of of the complexity it's going to bring, the power is going to bring. But also the complexity is gonna bring. I see that's why, you see Arvind, I sort of doubling down the entire IBM company on on hybrid services that are that are going to be really important here, that they provide these applications on top that are going to be really important, but that have to be architected in such a way that they can run in a hybrid environment. And finally there's all the infrastructure and tools and development pieces that we bring to the table. So, So yeah, I think I think are really, really understood that as they made the decision to bring redheaded, >>I talked to a center all the time and they also have this kind of concept of re factoring and reprogramming your business. Uh, it's not, it's a holistic view. This is kind of what's happening. So my final question for you is as as that becomes software enabled and programmed if you will with applications the business with many different subsystems in there. Um a lot of companies now looking at the light at the end of the tunnel with the pandemic and they're seeing vaccines coming out. Some say vaccines will be pretty much everywhere, everyone over 12 by the fall. So we're back to real life. There's gonna be a pullback of some projects on doubling down on others. As you as you mentioned, what are we doing? We're starting to see hybrid as companies come out of the pandemic, they're all jockeying to make sure that they have either done their work to re factor or reposition, reprogrammed their business and be set up for net new opportunities. >>What >>do you see as a growth model or growth opportunities for companies? You want to come out with a growth strategy out of the gate of the pandemic. What's your thoughts? >>Well, I mean, I think you have to plan for companies have to plan for your workforce to be anywhere, but in order to be anywhere in and to be productive, you need you need services like we're on right now for example, but you need the infrastructure to be able to do that. You need you need a way for your customers if you buy the fact that every company is a software company, you're running a business through their applications either way for your customers to be able to interact with you anywhere from where they are anywhere in a real time way. And so I think that's why from our perspective, things like that we're pushing a lot on the edge. Now, that's why you're seeing the hybrid cloud moved all the way out into the edge and you can see it in every vertical, you know, in the telco space. The edge means you gotta do, you have data and compute that needs to be done on the set on the cell tower in the manufacturing world. You have the state and compute that needs to be done on the factory floor, in the retail vertical. We see the edge really being significant in all these verticals, but but that edge is now extends that hybrid data center that we've been talking so much about. So even though you have all these edge devices way out there on the edge, it's a critical part of the business. So you have to have, your developers need need to be able to develop for it, you need to secure it, you need to and you need to operate it and manage it. So now, you know, in a very short period of time, hybrids taken on another dimension, bringing you out to all these points on the edge which is the same but slightly different in every vertical. Now comes complexity and that's why automation is so important because with that power comes complexity but it's going to take automation to keep it all running, >>paul. Great insight. Thanks for coming on the cube. Open innovation out in the open with with you guys again continue. And the focus of the evolution of software and the cloud with enterprise I. T. Clearly a lot of innovation and your contribution to academia and the mass open cloud and all the open cloud initiatives, phenomenal. The world's going. Open source and continues and continues. Doesn't stop. The operating system of businesses is coming and you guys are well positioned. Thanks for coming on. >>Thanks again john. Always a pleasure. >>Okay paul, Cormier, President Ceo of Red Hat here on the Cuban, john for your host. Thanks for watching. Yeah. Yeah. Mhm mm.

>>from around the globe. It's the Cube with digital coverage of biz ops Manifesto unveiled. Brought to you by biz ops Coalition. Hey, welcome back your body, Jeffrey here with the Cube. Welcome back to our ongoing coverage of the busy ops manifesto unveiling its been in the works for a while. But today is the day that it actually kind of come out to the to the public. And we're excited to have a real industry luminary here to talk about what's going on, Why this is important and share his perspective. And we're happy to have from Cape Cod, I believe, is Tom Davenport. He is a distinguished author on professor at Babson College. We could go on. He's got a lot of great titles and and really illuminate airy in the area of big data and analytics. Thomas, great to see you. >>Thanks, Jeff. Happy to be here with you. Great. >>So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn post. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address long term issues, Uh, in how technology works within businesses. Biz ops. What did you see in biz ops? That that kind of addresses one of these really big long term problems? >>Well, yeah. The long term problem is that we've had a poor connection between business people and I t people between business objectives and the i t. Solutions that address them. This has been going on, I think, since the beginning of information technology, and sadly, it hasn't gone away. And so busy ops is new attempt to deal with that issue with a, you know, a new framework. Eventually a broad set of solutions that increase the likelihood that will actually solve a business problem with a nightie capability. >>Right. You know, it's interesting to compare it with, like, Dev ops, which I think a lot of people are probably familiar with, which was, you know, built around a agile software development and the theory that we want to embrace change that that changes okay on. We wanna be able to iterate quickly and incorporate that, and that's been happening in the software world for for 20 plus years. What's taking so long to get that to the business side because the pace of change is change on the software side. You know, that's a strategic issue in terms of execution on the business side that they need now to change priorities. And, you know, there's no P R D S and M R. D s and big giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. Took a long time to get here. >>Yeah, it did. And, you know, there have been previous attempts to make a better connection between business and i t. There was the so called strategic alignment framework that a couple of friends of mine from Boston University developed, I think more than 20 years ago. But, you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's, um you know, time for another serious attempt at it, >>right? And do you think doing it this way right with the bizarre coalition, you know, getting a collection of of kind of like minded individuals and companies together and actually even having a manifesto which were making this declarative statement of principles and values. You think that's what it takes to kind of drive this, you know, kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in in production in the field. >>I think certainly no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think a coalition is a good idea, and a manifesto is just a good way to kind of lay out. What you see is the key principles of the idea, and that makes it much easier for everybody. Toe I understand and act on. >>Yeah, I I think it's just it's really interesting having, you know, having them written down on paper and having it just be so clearly articulated both in terms of the of the values as well as as the the principles and and the values, you know. Business outcomes, matter, trust and collaboration, data driven decisions, which is the number three or four and then learn, responded pivot. It doesn't seem like those should have to be spelled out so clearly. But obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are. But you're the data guy. You're the analytics guy. Yeah, And a big piece of this is data analytics and moving to data driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process. And informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the many stages of analytics. Onda. How has that's evolved over over time? You know, it is You think of analytics and machine learning driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that? What's that think for you? What does that make you? You know, start to think Wow, this is This is gonna be pretty significant. >>Yeah, well, you know, this has been a long term interest of mine. Um, the last generation of a I I was very interested in expert systems. And then e think more than 10 years ago, I wrote an article about automated decision making using, um, what was available then, which is rule based approaches. But, you know, this address is an issue that we've always had with analytics and ai. Um, you know, we tended Thio refer to those things as providing decision support. The problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions with now contemporary ai tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think, at least for, you know, repetitive tactical decisions, um, involving a lot of data. We want most of those I think, to be at least, um, recommended, if not totally made by analgesic rhythm or an AI based system, and that, I believe would add to the quality and the precision and the accuracy of decisions. And in most organizations, >>you know, I think I think you just answered my next question before I Before I asked it. You know, we had Dr Robert Gates on the former secretary of Defense on a few years back, and we were talking about machines and machines making decisions, and he said at that time, you know, the only weapon systems that actually had an automated trigger on it, We're on the North Korean South Korea border. Um, everything else that you said had to go through some person before the final decision was made. And my question is, you know what are kind of the attributes of the decision that enable us that more easily automated? And then how do you see that kind of morphing over time both as the the data to support that as well as our comfort level, Um, enables us to turn mawr mawr actual decisions over to the machine? >>Well, yeah, I suggested we need data, and the data that we have to kind of train our models has to be high quality and current, and we need to know the outcomes of the that data. You know, most machine learning models, at least in business, are supervised, and that means we need tohave labeled outcomes in the in the training data. But you know, the pandemic that we're living through is a good illustration of the fact that the data also have to be reflective of current reality. And, you know, one of the things that were finding out quite frequently these days is that the data that we have a do not reflect you know what it's like to do business in a pandemic. I wrote a little piece about this recently with Jeff Cam at Wake Forest University. We call it Data Science Quarantined and it we interviewed somebody who said, You know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Our models may be have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have toe make sure that the data from the past and you know that's all we have, of course, is a good guide toe. You know what's happening in the present and in the future, as far as we understand it. >>Yeah, I used to joke when we started this calendar year 2020 was finally the year that we know everything with the benefit of hindsight. But it turned out 2020 the year we found out we actually know nothing and everything >>we thought we d >>o. But I wanna I wanna follow up on that because, you know, it did suddenly change everything, right? We got this light switch moment. Everybody's working from home now. We're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold, fold or double down, and And I can't think of, um or, you know, kind of appropriate metaphor for driving the value of the biz ops. When now your whole portfolio strategy, um, needs to really be questioned. And, you know, you have to be really well executing on what you are holding. What you're folding and what you're doubling down with this completely new environment? >>Well, yeah, And I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine was a senior executive at gen. Packed, and I used it mostly to talk about AI and AI applications, but I think you could You could use it much more broadly to talk about your entire sort of portfolio. Digital projects you need to think about. Well, um, given some constraints on resource is and a difficulty economy for a while. Which of our projects do we wanna keep going on Pretty much the way we were for and which ones, um, are not that necessary anymore. You see a lot of that in a I because we had so many pilots. Somebody told me, You know, we've got more pilots around here than O'Hare Airport in a I, um and then the the ones that involve double down there, even mawr Important to you, they are. You know, a lot of organizations have found this out in the pandemic on digital projects. It's more and more important for customers to be ableto interact with you digitally. And so you certainly wouldn't want toe cancel those projects or put them on hold. So you double down on them, get them done faster and better. >>Another. Another thing I came up in my research that that you quoted um, was was from Jeff. Bezos is talking about the great bulk of what we do is quietly but meaning fleeing, improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which which gets way too much buzz but really applied, applied to a specific problem. And that's where you start to see the value. And, you know, the biz ops manifesto is calling it out in this particular process. But I just love to get your perspective. As you know, you speak generally about this topic all the time, but how people should really be thinking about where the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, the kind of once in a lifetime decisions, uh, the ones that a G laugh. Li, the former CEO of Proctor and Gamble, used to call the big swing decisions. You only get a few of those, he said. In your tenure as CEO, those air probably not going to be the ones that you're automating in part because you don't have much data about them. Your you know, only making them a few times and in part because they really require that big picture thinking and the ability to kind of anticipate the future that the best human decision makers have. Um, but in general, I think where they I The projects that are working well are you know what I call the low hanging fruit ones? The some people even report to refer to it as boring A. I so you know, sucking data out of a contract in order to compare it Thio bill of lading for what arrived at your supply chain. Companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but a I, as you suggest, is really good at those narrow kinds of tasks. Um, it's not so good at the at the really big Moonshots like curing cancer or, you know, figuring out well, what's the best stock or bond under all circumstances or even autonomous vehicles. We made some great progress in that area, but everybody seems to agree that they're not gonna be perfect for quite a while. And we really don't wanna be driving around on, um in that very much, unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic. And you know that sort of thing, right? >>That's funny. Bring up contract management. I had a buddy years ago. They had a startup around contract management, and I'm like and this was way before we had the compute power today and cloud proliferation. I said, You know how How could you possibly built off around contract management? It's language. It's legalese. It's very specific. He's like Jeff. We just need to know where's the contract and when does it expire? And who's the signatory? And he built a business on those you know, very simple little facts that weren't being covered because their contracts from people's drawers and files and homes and Lord only knows so it's really interesting as you said. These kind of low hanging fruit opportunities where you could extract a lot of business value without trying to, you know, boil the ocean. >>Yeah, I mean, if you're Amazon, Jeff Bezos thinks it's important toe have some kind of billion dollar projects, and he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to what a I has been doing for a long time, which is, you know, making smarter decisions based on based on data. >>Right? So, Tom, I want to shift gears one more time before before you let Ugo on on kind of a new topic for you, not really new, but you know, not not the vast majority of your publications. And that's the new way toe work, you know, as as the pandemic hit in mid March, right? And we had this light switch moment. Everybody had to work from home, and it was, you know, kind of crisis and get everybody set up. Well, you know, now we're five months, six months, seven months. A number of companies have said that people are not gonna be going back to work for a while, and so we're going to continue on this for a while, and then even when it's not what it is now, it's not gonna be what it was before. So, you know, I wonder and I know you, you tease. You're working on a a new book, you know, some of your thoughts on, you know, kind of this new way, uh, toe work and and and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess, >>Yeah, this was an interest of mine. I think. Back in the nineties, I wrote an article called a co authored an article called Two Cheers for the Virtual Office. And, you know, it was just starting to emerge than some people were very excited about it. Some people were skeptical, and we said to cheers rather than three cheers because clearly there's some shortcomings and, you know, I keep seeing these pop up. It's it's great that we can work from our homes. It's great that we can accomplish most of what we need to do with a digital interface, but you know, things like innovation and creativity and certainly, um a A good, um, happy social life kind of requires some face to face contact every now and then. And so you know, I think we'll go back to an environment where there is some of that. Um, will have, um, time when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and toe jump on airplanes. Thio, Thio, give every little sales call or give every little presentation we just have to really narrow down. What are the circumstances, where face to face contact really matters and when can we get by with digital? You know, I think one of the things in my current work on finding is that even when you have AI based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, we need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next and make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence of an AI system, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. Yeah, >>I think such such a huge opportunity as you just said, because I forget the stats on how often were interrupted with notifications between email text, slack asana, salesforce The list goes on and on. So, you know, t put an AI layer between the person and all these systems that are begging for attention. And you've written a you know, a book on the attention economy, which is a whole nother topic will say for another day. You know, it really begs. It really begs for some assistance because, you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not it's just not realistic. And you know what? I don't think that's the future that we're looking for. >>Great. Totally. Alright, >>Tom. Well, thank you so much for your time. Really enjoyed the conversation. I got to dig into the library. It's very long song. I might started the attention economy. I haven't read that one in to me. I think that's the fascinating thing in which we're living. So thank you for your time. And, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right, take care. Alright. East, Tom. I'm Jeff. You are watching the continuing coverage of the biz ops manifesto. Unveil. Thanks for watching the Cube. We'll see you next time.

>>from around the globe. It's the Cube with digital coverage of biz ops Manifesto unveiled. Brought to you by biz ops Coalition. Hey, welcome back your body, Jeffrey here with the Cube. Welcome back to our ongoing coverage of the busy ops manifesto unveiling its been in the works for a while. But today is the day that it actually kind of come out to the to the public. And we're excited to have a real industry luminary here to talk about what's going on, Why this is important and share his perspective. And we're happy to have from Cape Cod, I believe, is Tom Davenport. He is a distinguished author on professor at Babson College. We could go on. He's got a lot of great titles and and really illuminate airy in the area of big data and analytics. Thomas, great to see you. >>Thanks, Jeff. Happy to be here with you. Great. >>So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn post. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address long term issues, Uh, in how technology works within businesses. Biz ops. What did you see in biz ops? That that kind of addresses one of these really big long term problems? >>Well, yeah. The long term problem is that we've had a poor connection between business people and I t people between business objectives and the i t. Solutions that address them. This has been going on, I think, since the beginning of information technology, and sadly, it hasn't gone away. And so busy ops is new attempt to deal with that issue with a, you know, a new framework. Eventually a broad set of solutions that increase the likelihood that will actually solve a business problem with a nightie capability. >>Right. You know, it's interesting to compare it with, like, Dev ops, which I think a lot of people are probably familiar with, which was, you know, built around a agile software development and the theory that we want to embrace change that that changes okay on. We wanna be able to iterate quickly and incorporate that, and that's been happening in the software world for for 20 plus years. What's taking so long to get that to the business side because the pace of change is change on the software side. You know, that's a strategic issue in terms of execution on the business side that they need now to change priorities. And, you know, there's no P R D S and M R. D s and big giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. Took a long time to get here. >>Yeah, it did. And, you know, there have been previous attempts to make a better connection between business and i t. There was the so called strategic alignment framework that a couple of friends of mine from Boston University developed, I think more than 20 years ago. But, you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's, um you know, time for another serious attempt at it, right? >>And do you think doing it this way right with the bizarre coalition, you know, getting a collection of of kind of like minded individuals and companies together and actually even having a manifesto which were making this declarative statement of principles and values. You think that's what it takes to kind of drive this, you know, kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in in production in the field. >>Well, you know, the manifesto approach worked for Karl Marx and communism. So maybe it'll work. Here is Well, now, I think certainly no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think a coalition is a good idea, and a manifesto is just a good way to kind of lay out. What you see is the key principles of the idea, and that makes it much easier for everybody. Toe I understand and act on. >>Yeah, I I think it's just it's really interesting having you know, having them written down on paper and having it just be so clearly articulated both in terms of the of the values as well as as the the principles and and the values, you know, business outcomes, matter, trust and collaboration, data driven decisions, which is the number three or four and then learn responded Pivot, It doesn't seem like those should have to be spelled out so clearly, but obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are. But you're the data guy. You're the analytics guy. Uh, and a big piece of this is data analytics and moving to data driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process. And informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the many stages of analytics Onda how that's evolved over over time. You know, it is you think of analytics and machine learning driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that? What's that think for you? What does that make you? You know, start to think Wow, this is this is gonna be pretty significant. >>Yeah, well, you know, this has been a long term interest of mine. Um, the last generation of a I I was very interested in expert systems. And then e think more than 10 years ago I wrote an article about automated decision making using, um, what was available then, which is rule based approaches. But, you know, this address is an issue that we've always had with analytics and ai. Um, you know, we tended Thio refer to those things as providing decision support. The problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions with now contemporary ai tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think, at least for, you know, repetitive tactical decisions, um, involving a lot of data. We want most of those I think, to be at least, um, recommended, if not totally made by analgesic rhythm or an AI based system, and that I believe would add to the quality and the precision and the accuracy of decisions in in most organizations. >>You know, I think I think you just answered my next question before I before I asked it. You know, we had Dr Robert Gates on the former secretary of Defense on a few years back, and we were talking about machines and machines making decisions, and he said at that time, you know, the only weapon systems that actually had an automated trigger on it, We're on the North Korea and South Korea border. Everything else, as you said, had to go through some person before the final decision was made. And my question is, you know what are kind of the attributes of the decision that enable us to more easily automated? And then how do you see that kind of morphing over time both as the data to support that as well as our comfort level, Um, enables us to turn Maura Maura actual decisions over to the machine? >>Well, yeah, I suggested we need data and the data that we have to kind of train our models has to be high quality and current, and we need to know the outcomes of that data. You know, most machine learning models, at least in business, are supervised, and that means we need tohave labeled outcomes in the in the training data. But, you know, the pandemic that we're living through is a good illustration of the fact that the the data also have to be reflective of current reality. And, you know, one of the things that we're finding out quite frequently these days is that the data that we have do not reflect. You know what it's like to do business in it. Pandemic it. I wrote a little piece about this recently with Jeff Cam at Wake Forest University. We call it Data Science quarantined, and we interviewed somebody who said, You know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Our models may be have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have toe, make sure that the data from the past and you know, that's all we have, of course, is a good guide toe. You know what's happening in the present and and the future as far as we understand it. >>Yeah, I used to joke when we started this calendar year 2020 is finally the year that we know everything with the benefit of hindsight. But it turned out 2020 the year we found out we actually know nothing and everything way. But I wanna I wanna follow up on that because, you know, it did suddenly change everything, right? We got this light switch moment. Everybody's working from home now. We're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold, fold or double down and and I can't think of, um or, you know, kind of appropriate metaphor for driving the value of the biz ops. When now your whole portfolio strategy, um, needs to really be questioned. And, you know, You have to be really well, executing on what you are holding, what you're folding and what you're doubling down with this completely new environment. >>Well, yeah, And I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine who's a senior executive at gen. Packed. And I used it mostly to talk about AI and AI applications, but I think you could You could use it much more broadly to talk about your entire sort of portfolio of digital projects you need to think about. Well, um, given some constraints on resource is and a difficulty economy for a while. Which of our projects do we wanna keep going on Pretty much the way we were And which ones, um, are not that necessary anymore. You see a lot of that in a I because we had so many pilots, somebody for me, you know, we've got more pilots around here, then O'Hare airport in a I, um and then the the ones that involve double down there, even mawr Important to you, they are, you know, a lot of organizations have found this out in the pandemic on digital projects, it's more and more important for customers to be ableto interact with you, um, digitally. And so you certainly wouldn't want toe cancel those projects or put them on hold. So you double down on them, get them done faster and better. >>Another. Another thing that came up in my research that that you quoted, um, was was from Jeff. Bezos is talking about the great bulk of what we do is quietly but meaning fleeing, improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which which gets way too much buzz but really applied, applied to a specific problem. And that's where you start to see the value and, you know, the biz ops. Uh, manifesto is calling it out in this particular process, but I just love to get your perspective. As you know, you speak generally about this topic all the time, but how people should really be thinking about where the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions? Uh, the kind of once in a lifetime decisions, uh, the ones that a g laugh Li, the former CEO of Proctor and Gamble, used to call the big swing decisions. You only get a few of those, he said. In your tenure as CEO, those air probably not going to be the ones that you're automating in part because you don't have much data about them. You're only making them a few times, and in part because they really require that big picture thinking and the ability to kind of anticipate the future that the best human decision makers have. Um, but in general, I think where they I the projects that are working well are you know what I call the low hanging fruit ones? The some people even report to refer to it as boring A I so you know, sucking data out of a contract in order to compare it Thio bill of lading for what arrived at your supply chain. Companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but a I, as you suggest, is really good at those narrow kinds of tasks. Um, it's not so good at the at the really big Moonshots like curing cancer or, you know, figuring out well, what's the best stock or bond under all circumstances or even autonomous vehicles. We made some great progress in that area, but everybody seems to agree that they're not going to be perfect for quite a while. And we really don't wanna be driving around on, um in that very much, unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic. And you know that sort of thing, right? >>That's funny. Bring up contract management. I had a buddy years ago. They had a startup around contract management, and I'm like, and this was way before we had the compute power today and and cloud proliferation. I said, You know how How could you possibly built off around contract management? It's language. It's legalese. It's very specific. He's like Jeff. We just need to know where's the contract and when does it expire? And who's a signatory? And he built a business on those you know, very simple little facts that weren't being covered because their contracts from People's drawers and files and homes, and Lord only knows So it's really interesting, as you said, these kind of low hanging fruit opportunities where you could extract a lot of business value without trying to, you know, boil the ocean. >>Yeah, I mean, if you're Amazon, Jeff Bezos thinks it's important toe have some kind of billion dollar projects, and he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to what a I has been doing for a long time, which is, you know, making smarter decisions based on based on data. >>Right? So, Tom, I want to shift gears one more time before before you let Ugo on on kind of a new topic for you, not really new, but you know, not not the vast majority of your publications. And that's the new way toe work, you know, as as the pandemic hit in mid March, right? And we had this light switch moment. Everybody had to work from home, and it was, you know, kind of crisis and get everybody set up well you know, Now we're five months, six months, seven months. A number of companies have said that people are not gonna be going back to work for a while. And so we're going to continue on this for a while, and then even when it's not what it is now, it's not gonna be what it was before. So, you know, I wonder and I know you, you tease. You're working on a a new book, you know, some of your thoughts on, you know, kind of this new way. Uh, toe work and and and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess. >>Yeah, This was an interest of mine. I think back in the nineties, I wrote an article called Ah Co authored an article called Two Cheers for the Virtual Office. And, you know, it was just starting to emerge. Then some people were very excited about it. Some people were skeptical and we said to cheers rather than three cheers because clearly there's some shortcomings and, you know, I keep seeing these pop up. It's great that we can work from our homes. It's great that we can accomplish most of what we need to do with a digital interface. But you know, things like innovation and creativity and certainly a a good, um, happy social life kind of requires some face to face contact every now and then. And so you know, I think we'll go back to an environment where there is some of that. We'll have, um, time when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and toe jump on airplanes. Thio, Thio give every little mhm, uh, sales call or give every little presentation. We just have to really narrow down. What are the circumstances, where face to face contact really matters and when can we get by with digital? You know, I think one of the things in my current work I'm finding is that even when you have a I based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, We need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next and make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence oven, a isis some, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. Yeah, >>I think such such a huge opportunity as you just said, because I forget the stats on how often were interrupted with notifications between email text, slack asana, salesforce The list goes on on and on. So, you know, t put an AI layer between the person and all these systems that are begging for attention. And you've written a you know, a book on the attention economy, which is a whole nother topic will say for another day. You know, it really begs. It really begs for some assistance because, you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not it's just not realistic. And you know what? I don't think that's the future that we're looking for. >>Great totally alright, >>Tom. Well, thank you so much for your time. Really enjoyed the conversation. I gotta dig into the library. It's very long song. I might started the attention economy. I haven't read that one in to me. I think that's the fascinating thing in which we're living. So thank you for your time. And, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right, take care. Alright. He's Tom. I'm Jeff. You are watching the continuing coverage of the biz ops manifesto. Unveil. Thanks for watching. The Cube will see you next time.

>>Hi, everyone. This is L. A from Visa Research today. I would like to tell you about my work with Salim. Earlier. Took from Boston University about how to construct group with invisible inversion from heart problems on ice Arjuna graphs over I say model E eso Let me start this talk by tell you, uh, what is a group with invisible inversion? A group was invisible Inversion is defined by Hulkenberg and Mona In 2003 It says a representation off a group should satisfy two properties. The first is literally that inversion. It's heart. Namely that giving an including off group element X computing Uh, the including off its inverse his heart. The second is that the composition is still easy, namely given the including off X and Y computing the including off X plus y is easy here we're seeing. Plus, is the group operation. So let me explain this definition by going through our favorite example where discreet log it's hard, namely in the Multiplicity group of finance field. We include a group element A as G today, namely, put it into the exponents and more, uh, cute. So given G energy today finding a it's hard. So this group representation at least satisfy one way, as you mean this great look. It's hard. So let's look at at whether this a group satisfied group was invisible inversion. So it turns out it is not because given due to the A finding G to the minus A, it's still easy. So if we say this is the representation off the universe, then computing this reputation is simple. So this is a no example. Off group was invisible invasion. So the work off Falkenburg and Mona started by looking. How can we find group was invisible inversion? And what are the applications off such a group? Representation, >>It turns out, in their sisters. They did not find any group reputation representation that satisfy this property. But instead they find out that if you can find such a group and then they they have >>a cryptographic applications, namely building direct directed transitive signatures a year later in the work off Iraq at or they also find that if you can have this kind of group with invisible inversion there, you can also construct broadcast encryption with a small overhead, and this is before we know how to construct the broadcast encryption with small overhead over Terry's elliptic curve. Paris. So let's look at another attempt off constructing group with invisible inversion. So instead off defining. Still, let's look at a group where we put >>the including in the exponents and instead of defining due to the minus A as the inversion Let's define due to the one over a as the the inverse off do today. So it turns out you can also define that. And it happens that in many groups, minimally, if you more, uh, some special value a que then given G energy to the A, then competing due to the one over A is also conjectured to be hard. But if you define the group element in the experiment in that way, then multiplication in >>the group exponents is also hard, and so we cannot compose. So this is another no example where group inversion is actually difficult to compute. But composition is difficult to compute, uh, either. So for this kind of group, they cannot use this to build directly transitive signatures or broadcast encryption. So now let's make this attempt, uh, visible by allowing thio. So so thio have ability to compute composition. Namely, we represent the including off A as the follows. So first we help you today >>and then we also give an office Kate the circuit which contains a and n such that I take a group element X, and it can output due to the to a model end. So it turns out giving this circuit you have a feasibility off doing composition and in the work off yamakawa at all to show that if and that the underlying off station is io and assuming and it's an R s a moderately then Thistle >>is actually a good construction off group with invisible university. So technically, assuming I oh, we have already know candidates for group was in physical inversion. Uh, but that work still leaves the open problem off constructing group with invisible inversion without using general purpose sophistication. And in this talk, I would like to talk to tell you about a group was inversion candidate from some new certainly problems And the brief logic off this talk is the following. So elliptical insurgencies can be represented by graph, uh, and the graphs has a ship off volcanoes. For example, this one if you look imagine you're looking for a volcano from top to down and this is the Creator, and this is like the direction off going down the volcano. And arguably this is the reason which attracts me to looking to. I certainly problems, and also I certainly graphs can be an I certainly can be used to represent a group called Idea Class Group >>and then eventually we will find some group >>problems on this graph, which we conjecture to be hard. And they use map thes harness to the harness off inverting group elements in the ideal classroom. So this will be the high level overview off this talk. >>So what are a little bit curve? Assertiveness? So to talk about elliptic curve, I certainly okay spend the whole day talking about its mathematical definition and the many backgrounds off elliptic curve. But today we only have 15 minutes. So instead, let me just to give you a highlight help have overview off what I certain this and I certainly is a mapping from when a little bit of curve to another, and I certainly is an interesting equivalence relation between elliptic curves. It's interesting in its mathematical theory, over a finite field and elliptic curve can be identified by its J environment. And later, >>when we talk about elliptic, curve will think about their represented by their environment, which is a number in the finance field >>and given to elliptic curves and namely, given their environments, we can efficiently decide whether these two groups assertiveness, namely in polynomial time. And given these backgrounds, let me now jump to the exciting volcanoes. So it turns out >>the relation among I certainly occurred. Assertiveness curbs can be represented by the I certainly graphs, which looks like volcanoes. So let's first look at the graph on the left and let's fix a degree for that. I certainly so I certainly has different degrees. So let's for simplicity. Think about their crimes. So let's fix a degree Air say equals 23 >>and we will let each of the note in the graph to represent a different elliptic curve, namely a different Jane environment, and each is represent an air degree by certainly so if you fix the degree ill and I certainly is their religions, uh, they just look like what I said, like what kind of going from top to bottom and if, let's say, fix all the >>elliptic curve on the creator or, in general, all the elliptic curves on the same layer off the volcano, Then you allowed to have different degrees. So this is degree L and this is degree M, etcetera, etcetera. And then the graph actually looks like it's almost fully connected. Eso imagine all of them are connected by different degrees. And the graph structure is actually described not too long ago in the pH. Diseases off Davico Hell in 1996 and later it gets popularized in a paper in 2002 because they say, Hey, this looks like a volcano. So now the I certainly will. Kind of is they used in many reference by according the graph. >>So let me tell you a little bit more about the relation off. I certainly and the idea class group. So the short story is, if you fix a layer on the uncertainty graph, say the creator. So actually, all the notes has a 1 to 1 mapping to the group element in an ideal >>class group. The foremost Siri is the ideal class group acts on the, uh, set off a surgeon is which have the same in the more it is a Marine. But we will not go into their, uh in the talk today. So let me give you a simple example. So this is, ah, concrete representation off an ideal class group off seven group elements. And if we fix a J zero j environment off one off the grade curve, let's say this guy represents the identity in the idea class group. And then we let J one to represent one off the class group elements. Then it's inverse is just going one step back from the origin in the opposite direction S O. This is a very important picture we will use exactly the J environments to represent and the idea class group elements eso This is exactly the reputation we're gonna take, except we're gonna work with over the icy modeling. So after giving some mathematical background off elliptical by certainly in a certain graph now, let's talk about competition of problems >>and before jumping into I say model E, let me start from the, uh, more traditionally studied. I certainly problems over the finite field. The first problem is if I fix a degree, air and I give you a J environment off elliptic curve. Ast one off the note. That's first. Take an easy question. Is it easy to find all off? >>It's certainly neighbors off degree will say there is a polynomial. >>The answer is yes. And the technically there are two different ways. Uh, I will not go to the details off what they are, but what we need to know is they require serving, uh, polynomial off degree or air squares. Let's look at another problem that so imagine I select to random >>curves from an I certainly graph. So think about this. Uncertainty graph is defined over a large field, and they are super polynomial limited graphs off them. I'm choosing to random curves. >>The question is, can you find out an explicit I Certainly between them naming and Emily passed from one to the other. It turns out this >>problem is conjecture to be hard even for quantum computers, and this is exactly what was used in the post to quantum key exchange proposals in those works. So they have different structures could aside the seaside. They're just a different types off in the book is a Marine off the question is off the same nature finding and passed from one curve to the other. So these are not relevant to our work. But I would like to introduce them for for some background, off the history off. I certainly problems, >>So you have a work we need to >>study. I certainly problems over in, I say endogenous. And so the first question is even how to define. And I certainly, uh oh, and I certainly graph over the ring like, uh, over and I say modular. Same. So >>there is a general way off defining it in the special case. So in this talk, I will just talk about the special case because this is easier to understand. So think about I have the have the ability off peaking too. I certainly volcan als over multi and multi cube. That has exactly the same structure. And then I just use a C a c r T composition to stick them together. So namely a J >>zero. The value is the CRT off the J zero over. They're over the small fields P and the Cube and the N S equals to P times Q. And by the way, thes gene variants will be exactly the way to represent an ideal class group off such a size in this example is the ideal class group off, uh, with discriminate minus 250 bucks. Okay, so now let's look at what this magical over this representation. So let's look at back to the problem we start from namely, finding all the insurgents neighbors at this time over. And I see model E eso. I give you the J environment off easier and ask you to find a one off the its neighbors finding the J environment off one off its neighbors. So it turns out, even this problem is hard. And actually, we can prove this problem is as hard as factory and naive. Way off. Explaining off What's going on is that the two methods that work over the finite field that doesn't work anymore, since they both required to solve high degree polynomial model end, and that this is hard where when end is in, I certainly I say modelers. So to be useful for constructing a group off invisible inversion, we actually need to look at this called a joint neighbors. Such problems, namely, if I give you a curve zero, which represents the identity, then another crib, which represents a the group element. Your task is to find its inverse namely one off the E two candidate beneath zero. Yeah, eso it turns out this problem. We also conjectured to it to be hard and we don't know how to base it on how this a factoring, uh, again, the not even reason is the way to solve it over the finite field doesn't work because they both required to solve polynomial off degree higher than one over in i. C model is. And this is exactly the reason that we believe the group inversion is hard over deserve visitation Now. Finally, we also would like to remind the readers that for death according to the definition off group with invisible inversion, we would also like the group elements to be easy to compose. No, that's not. Make another observation that over. If you're finding the joint neighbor off, I certainly off different degree. Say, if I give you a J invent off Iwan and Jane Barrett off you to ask you to find the J environment off the three and they happened to off co prime degree I. Certainly then there is a way to find their joint neighbor because they're cold prime. And there's only one solution to solving the modular polynomial that I haven't defined out. But this is the way we make sure that composition is easy. Normally we output, including that are a cold prime so that they can be composed to summarize that we propose a group candidate group with invisible inversion from any particular I. Certainly it requires a chapter because you need to know the prime factors off. I seem odd early to set up the whole system and generated the including in our me assumption is that certain joint neighbors such problem on the I certainly graphs defined over S a moderately it's hard again group within physical inversion has the application of constructing broadcasting, corruption directed transitive signatures, and it's a very interesting problem to explore

>> live from Boston, Massachusetts. It's the you covering your red hat. Some twenty nineteen rots. You buy bread hat. >> Well, good afternoon. Welcome back here on the Cube as we continue our coverage of the Red Hat Summit and you know, every once in a while you come across one of these fascinating topics. It's what's doing I get so excited about when we do the Cube interviews is that you never know where >> you're >> going to go, the direction you're going to take. And I think this next interview has been a fit into one of those wow interviews for you at home. Along was to minimum. I am John Walls, and we're joined by Dr Ellen Grant, who was the director of the fetal neo NATO Neuroimaging and Developmental Science Center of Boston Children's Hospital. So far, so good, right? And the professor, Radiology and pediatrics at the Harvard Medical School's Dr Grant. Thank you for joining us here on the Cube and Dr Rudolph Pienaar, who is the technical director at the F n N D. S. C. And an instructor of radiology at the Harvard Medical School. So Dr Rudolph Pienaar, thank you for joining us as well. Thank you very much. All right. Good. So we're talking about what? The Chris Project, which was technically based. Project Boston Children's Hospital. I'm going to let you take from their doctor Grant. If you would just talk about the genesis of this program, the project, what its goal, wass And now how it's been carried out. And then we'LL bring in Dr PNR after that. So if you would place >> sure, it's so The goal of the Chris Project was to bring innovated imaging, announces to the bedside to the front end where clinicians are not like high are working all the time but aren't sophisticated enough or don't have enough memory to remember how to do, you know, line code in Lenox. So this is where initially started when I was reading clinical studies and I wanted to run a complex analysis, but there was no way to do it easily. I'd have tio call up someone to log into a different computer, bring the images over again lots of conflict steps to run that analysis, and even to do any of these analysis, you have to download the program set up your environment again. Many many steps, said someone. As a physician, I would rather deal with the interpretation and understanding the meaning of those images. Then all that infrastructure steps to bring it together. So that was the genesis of Chris's trying to have a simple Windows point and click way for a physician such as myself, to be able to rapidly do something interesting and then able to show it to a clinician in a conference or in the at the bedside >> and who's working on it, then, I mean, who was supplying what kind of manpower, If you will root off of the project >> kind of in the beginning, I would say maybe one way to characterize it is that we wanted to bring this research software, which lives mostly online, ex onto a Windows world, right? So the people developing that software researchers or computational researchers who do a lot of amazing stuff with image processing. But those tools just never make it really from the research lab outside of that. And one of the reasons is because someone like Ellen might not ever want to fire paternal and typing these commands. So people working on it are all this huge population of researchers making these tools on what we try to do. What I try to help with, How do we get those tools really easily usable in excess of one and, you know, to make a difference? Obviously. So that was a genesis. I was kind of need that we had in the beginning, so it started out, really, as a bunch of scrips, shell scripts, you slight a type of couple stuff, but not so many things on gradually, with time, we try to move to the Web, and then it began to grow and then kind of from the Web stretching to the cloud. And that's kind of the trajectory in the natural. As each step moved along, more and more people kind of came in to play. >> Dr Grant, I think back, you know, I work for a very large storage company and member object storage was going to transform because we have the giant files. We need to be able to store them and manage them and hold them up. But let's talk about the patient side of things. What does this really mean? You know, we had a talk about order of magnitude that cloud can make things faster and easier. But what? What does this mean to patient care? Quality service? >> Well, I think what it means or the goal for patient care is really getting to specialized medicine or individualized medicine on to be able to not just rely on my memory as to what a normal or abnormal images or the patients I may have seen just in my institution. But can we pull together all the knowledge across multiple institutions throughout the country and use more rigorous data announces to support my memory? So I want to have these big bridal in front lobes that air there, the cloud that helped me remember things into tidies connections and not have to remind just rely on my visual gestalt memory, which is obviously going to have some flaws in it. So and if I've never seen a specific disorder, say, for example, at my institution, if they've seen it at other institutions who run these comparisons all of sudden, I made be aware of a new treatment that otherwise I may not have known about >> All right, so one of my understanding is this is tied into the mass open cloud which I've had the pleasure of talking on the program at another show back here in Boston. Talk about a little bit about you know how this is enable I mean massive amounts of data you need to make sure you get that. You know the right data and it's valuable information and to the right people, and it gets updated all the time, so give us a little bit of the inner workings. >> Exactly. So thie inner workings, That's it can be a pretty big story, but kind of the short >> story time Theo Short >> story is that if we can get data in one place, and not just from one institution, from many places, that we can start to do things that are not really possible otherwise so, that's kind of the grand vision. So we're moving along those steps on the mass Open cloud for us makes perfect sense because it's there's a academic linked to Boston University. And then there's thie, Red Hat, being one of the academic sponsors as well in that for this kind of synergy that came together really almost perfectly at the right time, as the cloud was developing as where that was moving in it as we were trying to move to the cloud. It just began to link all together. And that's very much how we got there at the moment on what we're trying to do, which is get data so that we can cause medicine. Really, it's amazing to me. In some ways there's all these amazing devices, but computational e medicine lag so far behind the rest of the industry. There's so little integration. There's so little advanced processing going on. There's so much you can do with so little effort, you could do so much. So that's part of the >> vision as well. So help me out here a little bit, Yeah, I mean, maybe it before and after. Let's look at the situation may be clinically speaking here, where a finding or a revelation that you developed is now possible where it wasn't before and kind of what those consequences might have been. And then maybe, how the result has changed now. So maybe that would help paint up a practical picture of what we're talking about. >> I could use one example we're working on, but we haven't got fully to the clouds. All of these things are in their infancy because we still have to deal with the encryption part, which is a work in progress. But for example, we have mind our clinical databases to get examples of normal images and using that I can run comparisons of a case. It comes up to say whether this looks normal or abnormal sweat flags. The condition is to whether it's normal or abnormal, and that helps when there's trainees are people, not is experienced in reading those kinds of images. So again we're at the very beginnings of this. It's one set of pictures. There's many sets of pictures that we get, so there's a long road to get to fully female type are characterized anyone brain. But we're starting at the beginning those steps to very to digitally characterize each brain so we can then start to run. Comparisons against large libraries of other normals are large libraries of genetic disorders and start to match them up. And >> this is insecure. You working in fetal neural imaging as well. So you're saying you could take a an image of ah baby in a mother's womb and many hundreds thousands, whatever it is and you developed this basically a catalogue of what a healthy brain might look like. And now you're offering an opportunity to take a image here on early May of twenty nineteen. And compared to that catalogue, look and determine whether might be anabel normality that otherwise could have been spotted before. >> Correct and put a number to that in terms of a similarity value our probability values so that it's not just Mia's a collision, say Well, I think it's a little abnormal because it is hard to interpret that in terms of how severe is the spectrum of normal. How how? Sure you. So we put all these dated together. We can start to get more predictive value because we couldn't follow more kids and understand if it's that a a sima that too similar what's most likely disorder? What's the best treatment? So it gives you better FINA typing of the disorders that appear early and fetal life, some of which are linked to we think he treated, say, for example, with upcoming gene therapies and other nutritional intervention so we could do this characterization early on. We hope we can identify early therapies that our target to targeted to the abnormalities we detect. >> So intervene well ahead of time. Absolutely. >> I don't know. The other thing is, I mean Ellen has often times said how many images she looks at in the day on other radiologist, and it's it's amazing. It's she said, the number hundred thousand one point so you can imagine the human fatigue, right? So it Matt, imagine if you could do a quick pre processing on just flag ones that really are abnormal by you know they could be grossly abnormal. But at least let's get those on the top of the queue when you can look at it when you are much more able to, you know, think, think, think these things through. So there's one good reason of having these things sitting on an automated system. Stay out of the cloud over it might be >> Where are we with the roll out of this? This and kind of expansion toe, maybe other partners. >> So a lot of stuff has been happening over the last year. I mean, the the entire platform is still, I would say, somewhat prototypical, but we have a ll the pipelines kind of connected, so data can flow from a place like the hospital flowed to the cloud. Of course, this is all you know, protected and encrypted on the cloud weaken Do kind of weaken. Do any analysis we want to do Provided the analysis already exists, we can get the results back. Two definition we have the interface is the weapon to faces built their growing. So you can at this point, almost run the entire system without ever touching a command line. A year ago, it was partially there. A year ago, you had to use a command line. Now you don't have to. Next year will be even more streamlined. So this is the way it's moving right now and was great for me personally. About the cloud as well is that it's not just here in Boston where you, Khun benefit from using these technologies, you know, for the price of a cellphone on DH cell signal. You can use this kind of technology anywhere. You could be in the bush in Africa for argument's sake, and you can have access to these libraries of databases imaging that might exist. You, khun compare Images are collected wherever it might be just for the price of connecting to the Internet. >> You just need a broadband connection >> just right. Just exactly. >> Sometimes when you think about again about you know, we've talked about mobile technology five g coming on as it is here in the U. S. Rural health care leveling that and Third World, I was thinking more along the lines of here in the States and with some memories that just don't have access to the kind of, like, obviously platinum carry you get here in the Boston area. But all those possibilities would exist or could exist based on the findings that you're getting right now with Chris Project. So >> where does the Chris project go from here? >> Well, what we'd like to do is get more hospitals on board, uh, thinking pediatrics, we have a lot of challenge because there are so many different rare disorders that it's hard to study any one of them from one hospital. So we have to work together. There's been some effort to bring together some genetic databases, but we really need to being also the imaging bait databases together. So hopefully we can start to get a consortium of some of the pediatric hospitals working together. We need that also because normal for normal, you need to know the gender, the age, the thie ethnicity. You know, so many demographics that are nice to characterize what normal is. So if we all work together, we can also get a better idea of what is normal. What is normal variants. And there's a lot of other projects that are funded by N. H. Building up some of those databases as well, too. But we could put him into all into one place where we can actually now query on that. Then we could start to really do precision medicine. >> And the other thing, which we definitely are working on and I want to do, is build a community of developers around this platform because, you know, there's no way our team can write all of these tools. No, no, no, we want to. But we want everyone else who wants to make these tools very easily hop onto this platform. And that's very important to us because it's so much easier to develop to christen it just about the Amazon. There's almost no comparison. How much easier >> we'Ll Definitely theme, we hear echoing throughout Red Hat summit here is that Does that tie into, like, the open shift community? Or, you know, what is the intersection with red hat? >> It definitely does, because this is kind of the age of continue ization, which makes so many things so much easier on DH. This platform that we've developed is all about container ization. So we want to have medical by medical or any kind of scientific developers get onto that container ization idea because when they do that and it's not that hard to do. But when you do that, then suddenly you can have your your analysis run almost anywhere. >> And that's an important part in medicine, because I run the same analysis on different computers, get different results. So the container ization concept, I think, is something that we've been after, which is a reproduce ability that anybody can run it along there, use the same container we know we're going. Same result. And that is >> critical. Yes, especially with what you're doing right, you have to have that one hundred percent certainty. Yep. Standardisation goes along, Ray. Sort of fascinating stuff. Thank you both for joining us. And good luck. You're an exciting phase, that's for sure. And we wish you all the best going forward here. Thank you so much. Thank you both. Back with more from Boston. You're watching Red Hat Summit coverage live here on the Q t.

from Boston Massachusetts it's the cube covering wtg transform 2018 brought to you by Winslow technology group welcome back I'm Stu minimun and this is the cube coverage of wdg transform 2018 I'm happy to welcome back to the program probably an interesting who's come all the way from Boston University he said three blocks away about three blocks why yes all right Brian's the director of College of Arts and Sciences information technology great to see you again thank you all right back so good news is we spoke it was just about a year ago it was August last year it's June this year I'm sure nothing's changed in your environment you know students never change technology never changes there's a little bit of change on your end a little bit a little bit last year we'd spoke of quite a bit about hyperconvergence and what's that's gonna mean in terms of Education and how we deliver that and what the experience could be like for these students and I think at this point we're satisfied with everything that Nutanix has brought to us we've deployed VDI and a couple of large deployments for whole bunch of classes so we decided to reassess and reevaluate work what we're doing this year and now we move on to application development that's great so we get many ways they say you need to modernize your platform and then once you do that we can look at what the long haul 210 which is really at the application side right exactly once we knew what we had what we could possibly do with it we decided to move forward and figure out what else can we change and we had a lot of legacy applications for the business and so this past year we hired a developer who's focusing solely on docker izing our applications so we're deploying docker and a whole bunch of applications within the college and then we're going to be doing kubernetes deployment later this year ok and let's be clear where does this live you know is this on the Nutanix platform is it in you know service riders public clouds where does this span because kubernetes can live in all of those environments in the containerized stuff at Casa and currently it's all contained within a handful of VMs within our Nutanix server environment ok we're planning on looking at calm and use using natural blueprints to deploy kubernetes and docker down the road ok so I've got the Nutanix platform what hypervisor am i using HP ok so using the HP using which of courses Newt annexes comes on on the platform and then you know in the VMS you're using containers we are um have you looked at bare metal um you know because that's one of the discussions is like well if I'm doing containers you know do I just do that on Linux on bare metal or do I do it virtual is a virtualized and there's there's pluses and minuses for each of those we did a few of the pluses that my sis had means really enjoy is when our developer is going to go crazy and do new things we can make snapshot so if he happens to do something to the environment we can restore it in ten minutes and I think as far as my developer is concerned he doesn't want to have to rebuild the environment every time he makes a mistake he's had a few close calls so far and having HP and the ability to snapshot restore it's been awesome for him okay what insight can you give us about what you know what sort of applications are they building and you said Dockers in two minute Kruger burn Eddie's you know are they building their own stack are they leveraging you know how are they getting to that state well we're taking some business apps that were focusing on both student and faculty applications dealing with various components of each and he's pulling them apart to figure out what components go into the docker containers what do we have to still reside in VMs for security and long-term use and try to figure out how to reimagine the application stack to move forward we're starting to look at reusing components that he's developing and I'm hoping that we have a lot of pieces that we can do that with so we have a lot of applications to rewrite okay and just to drill in a little bit because I've got we've got a team of the cube that's gonna be at docker con next week I've been go to the kubernetes show for a while so when you say docker are you using just the free containers which is now called mobi or using the dr. CEO as part of that I actually can't tell you that because that's miss all my developers work I did so they're using docker as you said it's like the Kleenex and do you know from kubernetes standpoint have they just built their own do you have a distribution or a platform that you just do Tanic we just downloaded the distro from kubernetes instead of a small cluster himself we're going to be looking at using calm to do a deployment on their channels natively okay really interesting stuff what what is you know you talked a bit about you know you can give a little bit of stability and recovery and things like that for your developers to be able to play in that sandbox is what gives us a little bit of the roadmap as to you know how long do they play with this and then you know how does this roll out for the university so we're looking at probably a three to six month development cycle on a lot of new applications right now part of my developers job is to try to figure out how this environments going to work my sis admins are deeply engaged with him but since most of doctrine kubernetes is developed with faced he has to do most of the legwork and figure out how it's all gonna work and so we're hoping to leverage Nutanix to have multiple environments all with the same back-end so we have dev tests and production all in the same hardware but different pieces of actually physical clusters that'll be separated so he doesn't mess around the production all too much but set up a baseline that we can use to short that development cycle even further yeah one of the things we always look at is right you've got your developers doing their thing how does that fit with the operation side is it DevOps even I interviewed Solomon hikes last year that was the founder of docker and he said actually it was an operation mindset that I had when I created this container format how are you seeing it's actually great you're all working together you're you're in discussion there do you have a DevOps rollout and what you're doing or you do you keep it separate I still keep them somewhat separate but my administrators are writing a little bit more code and scripting than they used to and I think in general that's going to be the in the entire industry where you can't just look at and have your developer do everything in docker and not understand how it works Brian talk to us about your partners for doing this how involved are the likes of Nutanix and Winslet technology and you know in Dell in this discussion of the containers agent and your developers Nutanix we've been utilizing a lot of documentation and we're gonna be leveraging them a lot when we start to look at com Winslow's we haven't really talked to them about it to be honest we probably should because they might have some ideas and other partners we can talk to Dell in it there's really just a hardware to run everything on that's stable we don't have to worry about it I'm so happy with that yeah that's not in any you know oh I don't need to worry about them there's certain pieces we always look at and I'd love your feedback on this if you know when we virtualized first and now even when we containerize how much don't I need to worry about the infrastructure I mean remember back you know 15 years ago it's like oh I'll virtualized that well have you checked the BIOS because the BIOS might not work and the server could break things the OS could cause problem you know virtualization relatively stable these days how are you finding the container stuff it's really interesting and very very unique to virtualize a virtualized environment even further it's it's kind of mind-blowing just I've been doing this for twenty years and this is much further than I've ever expected the industry to go oh yeah just wait and it's you go even further than kubernetes it's like wait is it on top of underneath or side by side with the technologies you're doing from a Cooper nettie standpoint you said today it's all in the note annex what's the value of kubernetes for you is it just kind of the cluster orchestration of containers or you know are you is its portability a piece even part of the concern that you look at there oh it's it's mostly from portability part of the applications that we're looking at down the road are going to be vertical applications especially some student facing ones and certain times of the year we're gonna have to go from maybe a hundred people logged in to several thousand at the same time so we're hoping to stand up something that we can easily move to a cloud provider and still work the same way that we're expecting it to and so I think kubernetes along with the orchestration internally on-prem it's gonna be a huge benefit for us to know the environment it's gonna be exactly the same when we move it to Amazon or Google or adder all right so so Brian you're still kind of in the thick of it here but from what you've learned so far any any learnings or things that you'd recommend to your peers that oh wait if I could turn back the clock three months I might have adjusted or pointed things in a different direction yes yeah well when our developer started he focused more on getting an application up and running before starting to learn docker I would encourage anybody that's just starting down the road get your developer learning doctor and kubernetes first because they might want to rewrite what they're doing in the application okay well Brian this has been fascinating want to give you the final word is that you look out through the rest of the year so it's a lot you know so far since last time we talked but by the time we come around next year you'll be all serverless and you know deploying things off side the globe I'm assuming but I have no idea if you told me your ago that we're gonna be doing what we're doing now I wouldn't believe you it's it's a fantastic journey it's it's amazing what we learn every day all right well Brian appreciate you sharing some of the learnings as we go it's one of the reasons we come to events like this I know yourself to talk to your peers here what's going out thank you for moving forward with thank you all right plus more coverage here at wtg transform 2018 I'm Stu minimun and thanks for watching the Q

(inspirational music) - So GDPR, the General Data Protection Regulation was passed by the EU in 2016, in May of 2016. It is, as Ronald was saying it's four base things. The right to privacy, the right to be forgotten, privacy built into systems by default, and the right to data transfer. - [Panelist] Takes effect next year. - It is already in effect. GDPR took effect in May of 2016. The enforcement penalties take place the 25th of May 2018. Now here's where there's two things on the penalty side that are important for everyone to know. Number one. GDPR is extra territorial. Which means that any EU citizen anywhere on the planet has GDPR goes with them. So say you are a pizza shop in Nebraska. An EU citizen walks in, orders a pizza, gives the credit card, stuff like that. If you for some reason destroy that data, GDPR now applies to you Mr. Pizza Shop, whether or not you do business in the EU, because an EU citizens data is with you. It's true, the penalties are much different than they ever have been. In the old days companies could simply write off penalties as saying that's cost of doing business. With GDPR the penalties are up to 4% of your annual revenue or 20 million euros, which ever is greater, and there may be criminal sanctions against, charges against key company executives. So there's a lot of questions about how this is going to be implemented. But one of the first impacts you will see from a marketing perspective is, all the advertising we do, targeting people by their age, by their personal identifiable information, by their demographics, between now and May 25th 2018 a good chunk of that may have to go away because we may not, there's no way for you to say well this person's an EU citizen this person's not. People give false information all the time online. So how do you differentiate every company regardless whether they are in the EU or not will have to adapt to it. Or deal with the penalties. - When you think about the principles that GDPR gives you, I look at that and think that's just, to me that's just good data management practices and principles. It happens to be around personal data for GDPR right now, but those principles are just valley for probably kind of any kind of data. So if you're on the digital transformation journey, with all the change and all the opportunity that brings, these practices and principles for GDPR, they should be helping drive things like your digital transformation. For a lot of our customers, change is the only constant they've got, especially managing all this whilst everything is changing around you. It's tough for a lot of them. - How are people thinking about the data layer, where it lives, on prem, in the cloud, think about GDPR compliance, you know all that sort of good stuff. How are you and Red Hat, how are you asking people to think about that? - So, you know, data management is a big question. We build storage tooling. We understand how to put the bytes on disk, and persist and maintain the storage. It's a different question what are the data services and what is the data governance or policy around placement. And, I think it's a really interesting part of the ecosystem today. We've been working with some research partners in the Massachusets open cloud at Boston University on a project called Cloud Dataverse. And it has a whole policy question around data. It's there, scientists want to share data sets, to control and understand who you're sharing your data sets with. So its definitely a space that we are interested in. Understand that there's a lot of work to be done there, and GDPR just kind of shines the light right on it. Says, policy and governance around where data is placed is actually fundamental and important. And I think it's an important part because you have seen some of the data issues recently in the news. And, we got to get a handle on where data goes, and ultimately I'd love to see a place where I'm in control of how my data is shared with the rest of the world. - GDPR provides for two types of things that a business must do. It must provide insight into the data that it's captured, about business or an individual, legal entity. And it must also then provide the processes for mediating or taking action against that data according to whatever the customers virtues are. Tell us a little bit about that. - So these are two important features because of GDPR. First thing GDPR has 99 articles and 173 articles and 99 like term technological ways. There are other ways, legal ways to do it, but technologically what they want. Like if Peter decides, that I need to know from this bank or from this social media company how much information you have about me, and what are you doing with it. They have to provide that information in 30 days. That is called right to access. And the second thing is you can come and say, well I'm not using these five things which you sold me earlier I don't want you to use that information, or even have information on that for me or my son or my kid. So you can tell them delete that information or mask that. - And that's call the right to? - Right to erasure, right to remove the data. And these two things are very important. This gives customer, they make customer the king. They make the individual the king. He can say tell me what you have on me, and delete what you have on me. - Now the laws have been in the books in, at least in the EU for GDPR for a while. But the fines start getting leveled in May. - May 5th. - Now we've heard that... - So GDPR is a big thing for us and our customers and prospects as well. So we are actively working on getting GDPR compliant. Today our platform is FIPS compliance, so that's already a big stepping stone to getting there. So we look at GDPR in one of, in two ways again, right? One is the solution that we provide to our customers, the data platform and the data protect as we call it. Being GDPR complaint. Meaning the data that lands on that system. The ability to delete the data, the ability to say who has access to the data, rules based taxes, things like that. The second aspect is, our support and the fact that we have access to a lot of customer information ourselves, right? The fact that we can look at their systems and make sure that, everything we do internally is also GDPR compliant, so that the customers and our support systems and our sales force database is all GDPR as well. So both those elements come into play and we are actively working on all of them. (inspirational music)

>> Narrator: Live from San Francisco. It's theCUBE! Covering RedHat Summit 2018. Brought to you by Red Hat. >> Alright welcome back, this is theCUBE's exclusive coverage of Red Hat 2018. I'm John Furrier, the co host of theCUBE with John Troyer, co-founder of TechReckoning Advisory Firm. Next guest is Chris Wright, Vice President and CTO Chief of Technology of his Red Hat. Great to see you again, thanks for joining us today. >> Yeah, great to be here. >> Day one of three days of CUBE coverage, you got, yesterday had sessions over there in Moscone South, yet in classic Red Hat fashion, good vibes, things are rocking. Red Hat's got a spring to their step, making some good calls technically. >> Chris: That's right. >> Kubernetes' one notable, Core OS Acquisition, really interesting range, this gives, I mean I think people are now connecting the dots from the tech side, but also now on the business side, saying "Okay we can see now some, a wider market opportunity for Red Hat". Not just doing it's business with Linux, software, you're talking about a changing modern software architecture, for application developers. I mean, this is a beautiful thing, I mean. >> Chris: It's not just apps but it's the operator, you know, operation side as well, so we've been at it for a long time. We've been doing something that's really similar for quite some time, which is building a platform for applications, independent from the underlying infrastructure, in the Linux days I was X86 hardware, you know, you get this HeteroGenius hardware underneath, and you get a consistent standardized application run time environment on top of Linux. Kubernetes is helping us do that at a distributive level. And it's taken some time for the industry to kind of understand what's going on, and we've been talking about hybrid cloud for years and, you really see it real and happening and it's in action and for us that distributed layer round Kubernetes which just lights up how do you manage distributed applications across complex infrastructure, makes it really real. >> Yeah it's also timing's everything too right? I mean, good timing, that helps, the evolution of the business, you always have these moments and these big waves where you can kind of see clunking going on, people banging against each other and you know, the glue layers developing, and then all of a sudden snaps into place, and then it just scales, right? So you're starting to see that, we've seen this in other ways, TCPIP, Linux itself, and you guys are certainly making that comparison, being Red Hat, but what happens next is usually an amazing growth phase. Again, small little, and move the ball down the field, and then boom, it opens up. As a CTO, you have to look at that 20 mile stair now, what's next? What's that wave coming that you're looking at in the team that you have on Red Hat's side and across your partners? What's the wave next? >> Well there's a lot of activity going on that's beyond what we're building today. And so much of it, first of all, is happening in Open Source. So that itself is awesome. Like we're totally tuned into these environments, it's core to who we are, it's our DNA to be involved in these Open Source communities, and you look across all of the different projects and things like machine learning and blockchain, which are really kind of native Open Source developments, become really relevant in ways that we can change how we build functionality and build business, and build business value in the future. So, those are the things that we look at, what's emerging out of the Open Source communities, what's going to help continue to accelerate developers' ability to quickly build applications? Operations team's ability to really give that broad scale, policy level view of what's going on inside your infrastructure to support those applications, and all the data that we're gathering and needing to sift through and build value from inside the applications, that's very much where we're going. >> Well I think we had a really good example of machine learning used in an everyday enterprise application this morning, they kicked off the keynote, talking about optimizing the schedule and what sessions were in what rooms, you know, using an AI tool right? >> Chris: That's right. >> And so, that's reality as you look at, is that going to be the new reality as you're looking into the future of building in these kind of machine learning opportunities into everyday business applications that, you know, in the yesteryear would've been just some, I don't know, visual basic, or whatever, depending on how far back you look, right? You know, is that really going to be a reality in the enterprise? It seems so. >> It is, absolutely. And so what we're trying to do is build the right platforms, and build the right tools, and then interfaces to those platforms and tools to make it easier and easier for developers to build, you know, what we've been calling "Intelligent Apps", or applications that take advantage of the data, and the insights associated with that data, right in the application. So, the scheduling optimization that you saw this morning in the keynote is a great example of that. Starting with basic rules engine, and augmenting that with machine learning intelligence is one example, and we'll see more and more of that as the sophisticated tools that are coming out of Open Source communities building machine learning platforms, start to specialize and make it easier and easier to do specific machine learning tasks within an application. So you don't have to be a data scientist and an app developer all in one, you know, that's, there's different roles and different responsibilities, and how do we build, develop, life cycle managed models is one question, and how do we take advantage of those models and applications is another question, and we're really looking at that from a Red Hat perspective. >> John F: And the enterprises are always challenged, they always (mumbles), Cloud Native speaks to both now, right? So you got hybrid cloud and now multi-cloud on the horizon, set perfectly up with Open Shift's kind of position in that, kind of the linchpin, but you got, they're still two different worlds. You got the cloud-native born in the cloud, and that's pretty much a restart-up these days, and then you've got legacy apps with container, so the question is, that people are asking is, okay, I get the cloud-native, I see the benefits, I know what the investment is, let's do it upfront, benefits are horizontally scalable, asynchronous, et cetera et cetera, but I got legacy. I want to do micro-servicing, I want to do server-less, do I re-engineer that or just containers, what's the technical view and recommendation from Red Hat when you say, when the CIO says or enterprise says, "Hey I want to go cloud native for over here and new staff, but I got all this old staff, what do I do?". Do I invest more region, or just containerize it, what's the play? >> I think you got to ask kind of always why? Why you're doing something. So, we hear a lot, "Can I containerize it?", often the answer is yes. A different question might be, "What's the value?", and so, a containerized application, whether it's an older application that's stateful or whether it's a newer cloud-native application (mumbles), horizontally scalable, and all the great things, there's value potentially in just the automation around the API's that allow you to lifecycle manage the application. So if the application itself is still continuing to change, we have some great examples with some of our customers, like Keybank, doing what we call the "Fast moving monolith". So it's still a traditional application, but it's containerized and then you build a CICD model around it, and you have automation on how you deliver and deploy production. There's value there, there's also value in your existing system, and maybe building some different services around the legacy system to give you access, API access, to data in that system. So different ways to approach that problem, I don't think there's a one size fits all. >> So Chris, some of this is also a cultural and a process shift. I was impressed this morning, we've already talked with two Red Hat customers, Macquarie and Amadeus, and you know Macquarie was talking about, "Oh yeah we moved 40 applications in a year, you know, onto Open Shift", and it turns out they were already started to be containerized and dockerized and, oh yeah yeah you know, that is standard operating procedure, for that set of companies. There's a long tail of folks who are still dealing with the rest of the stuff we've had to deal, the stack we've had to deal with for years. How is Red Hat, how are you looking at this kind of cultural shift? It's nice that it's real, right? It's not like we're talking about microservices, or some sort of future, you know, Jettison sort of thing, that's going to save us all, it's here today and they're doing it. You know, how are you helping companies get there? >> So we have a practice that we put in place that we call the "Open Innovation Lab". And it's very much an immersive practice to help our customers first get experience building one of these cloud native applications. So we start with a business problem, what are you trying to solve? We take that through a workshop, which is a multi-week workshop, really to build on top of a platform like Open Shift, real code that's really useful for that business, and those engineers that go through that process can then go back to their company and be kind of the change agent for how do we build the internal cultural shift and the appreciation for Agile development methodologies across our organization, starting with some of this practical, tangible and realist. That's one great example of how we can help, and I think part of it is just helping customers understand it isn't just technology, I'm a technologist so there's part of me that feels pain to say that but the practical reality is there's whole organizational shifts, there's mindset and cultural changes that need to happen inside the organization to take advantage of the technology that we put in place to build that optimize. >> John F: And roles are changing too, I'll see the system admin kind of administrative things getting automated way through more operating role. I heard some things last week at CubeCon in Copenhagen, Denmark, and I want to share some quotes and I want to get your reaction. >> Alright. >> This is the hallway, I won't attribute the names but, these were quotes, I need, quote, "I need to get away from VP Engine firewalls. I need user and application layer security with unfishable access, otherwise I'm never safe". Second quote, "Don't confuse lift and shift with running cloud-native global platform. Lot of actors in this system already running seamlessly. Versus say a VM Ware running environment wherein V Center running in a data center is an example of a lift and shift". So the comments are one for (mumbles) cloud, you need to have some sort of security model, and then two, you know we did digital transformation before with VM's, that was a different world, but the new world's not a lift and shift, it's re-architect of a cloud-native global platform. Your reaction to those two things, and what that means to customers as they think about what they're going to look like, as they build that bridge to the future. >> Security peace is critical, so every CIO that we're talking to, it's top of mind, nobody wants to be on the front page of The Wall Street Journal for the wrong reasons. And so understanding, as you build a micro-services software architected application, the components themselves are exposed to services, those services are API's that become potentially part of the attack surface. Thinking of it in terms of VPN's and firewalls, is the kind of traditional way that we manage security at the edge. Hardened at the edge, soft in the middle isn't an acceptable way to build a security policy around applications that are internally exposing parts of their API's to other parts of the application. So, looking at it for me, application use case perspective, which portions of the application need to be able to talk to one another, and it's part of why somebody like Histio are so exciting, because it builds right in to the platform, the notion of mutual authentication between services. So that you know you're talking to a service that you're allowed to talk to. Encryption associated with that, so that you get another level of security for data and motion, and all of that is not looking at what is the VPN or what is the VLAN tag, or what is the encapsulation ID, and thinking layer two, layer three security, it's really application layer, and thinking in terms of that policy, which pieces of the application have to talk to each other, and nobody else can talk to that service unless it's, you know, understood that that's an important part for how the application works. So I think, really agree, and you could even say DevSecOps to me is something that I've come around to. Initially I thought it was a bogus term and I see the value in considering security at every step of build, test and deliver an application. Lift and shift, totally different topic. What does it mean to lift and shift? And I think there's still, some people want to say there's no value in lift and shift, and I don't fully agree, I think there's still value in moving, and modernizing the platform without changing the application, but ultimately the real value does come in re-architecting, and so there's that balance. What can you optimize by moving? And where does that free up resources to invest in that real next generation application re-architecting? >> So Chris, you've talked about machine learning, right? Huge amounts of data, you've just talked about security, we've talked about multi-cloud, to me that says we might have an issue in the future with the data layer. How are people thinking about the data layer, where it lives, on prem, in the cloud, think about GDPR compliance, you know, all that sort of good stuff. You know, how are you and Red Hat, how are you asking people to think about that? >> So, data management is a big question. We build storage tooling, we understand how to put the bytes on disc, and persist, and maintain the storage, it's a different question what are the data services, and what is the data governance, or policy around placement, and I think it's a really interesting part of the ecosystem today. We've been working with some research partners in the Massachusetts Open Cloud and Boston University on a project called "Cloud Dataverse", and it has a whole policy question around data. 'Cause there, scientists want to share data sets, but you have to control and understand who you're sharing your data sets with. So, it's definitely a space that we are interested in, understand, that there's a lot of work to be done there, and GDPR just kind of shines a light right on it and says policy and governance around where data is placed is actually fundamental and important, and I think it's an important part, because you've seen some of the data issues recently in the news, and you know, we got to get a handle on where data goes, and ultimately, I'd love to see a place where I'm in control of how my data is shared with the rest of the world. >> John F: Yeah, certainly the trend. So a final question for you, Open Source absolutely greatness going on, more and more good things are happening in projects, and bigger than ever before, I mean machine learning's a great example, seeing not just code snippets, code bases being you know, TensorFlow jumps out at me (mumbles), what are you doing here this year that's new and different from an Open Source standpoint, but also from a Red Hat standpoint that's notable that people should pay attention to? >> Well, one of the things that we're focused on is that platform layer, how do we enable a machine learning workload to run well on our platform? So it starts actually at the very bottom of the stack, hardware enablement. You got to get GPUs functional, you got to get them accessible to virtual machine based applications, and container based applications, so that's kind of table stakes. Accelerate a machine learning workload to make it usable, and valuable, to an enterprise by reducing the training and interference times for a machine learning model. Some of the next questions are how do we embed that technology in our own products? So you saw Access Insights this morning, talking about how we take machine learning, look at all of the data that we're gathering from the systems that our customers are deploying, and then derive insights from those and then feed those back to our customers so they can optimize the infrastructure that they're building and running and maintaining, and then, you know, the next step is that intelligent application. How do we get that machine learning capability into the hands of the developer, and pair the data scientist with the developers so you build these intelligent applications, taking advantage of all the data that you're gathering as an enterprise, and turning that into value as part of your application development cycle. So those are the areas that we're focused on for machine learning, and you know, some of that is partnering, you know, talking through how do we connect some of these services from Open Shift to the cloud service providers that are building some of these great machine learning tools, so. >> Any new updates on (mumbles) the success of Red Hat just in the past two years? You see the growth, that correlates, that was your (mumbles) Open Shift, and a good calls there, positioned perfectly, analysts, financial analysts are really giving you guys a lot of props on Wall Street, about the potential revenue growth opportunities on the business side, what's it like now at Red Hat? I mean, do you look back and say, "Hey, it was only like three years ago we did this", and I mean, the vibes are good, I mean share some inside commentary on what's happening inside Red Hat. >> It's really exciting. I mean, we've been working on these things for a long time. And, the simplest example I have is the combination of tools like the JBoss Middleware Suite and Linux, well they could run well together and we have a lot of customers that combine those, but when you take it to the next step, and you build containerized services and you distribute those broadly, you got a container platform, you got middleware components, you know, even providing functionality as services, you see how it all comes together and that's just so exciting internally. And at the same time we're growing. And a big part of-- >> John F: Customers are using it. >> Customers are using it, so putting things into production is critical. It's not just exciting technology but it's in production. The other piece is we're growing, and as we grow, we have to maintain the core of who we are. There's some humility that's involved, there's some really core Open Source principles that are involved, and making sure that as we continue to grow, we don't lose sight of who we are, really important thing for our internal culture, so. >> John F: Great community driven, and great job. Chris, thanks for coming on theCUBE, appreciate it. Chris Wright, CTO of Red Hat, sharing his insights here on theCUBE. Of course, bringing you all a live action as always here in San Francisco in Moscone West, for Red Hat Summit 2018, we'll be right back. (electronic music) (intense music)

>> Announcer: Live, from Boston, Massachusetts. It's theCUBE. Covering OpenStack Summit 2017. Brought to you by the OpenStack Foundation, Red Hat, and additional ecosystem support. >> Welcome back. I'm Stu Miniman joined by my cohost this week, John Troyer. Hi and welcome to the program, a first time guest, Professor at Boston University, and lead of the Massachusetts Open Cloud, Orran Krieger. Thanks so much for joining us. >> Ah, my pleasure, thank you. >> Alright, so, we're here in Boston, the center of culture, the revolution, a lot of universities. Tell us a little about you, just click on yourself, your role at BU, and then we'll get into the MOC stuff in a little bit too. >> Sure, I mean, I sort of came back from industry after 15 years in industry, to this incredible opportunity we had, to create this entity. I mean, there's no other place like this, if you take the universities in this city, it's equivalent to all the universities on the Pacific West Coast. Right, the concentration of high-tech is unbelievable here. >> I want to remind you, my wife was actually involved when Partners Healthcare first got launched here in Boston, was an early technology and collaboration here in Boston. Sounds similar, what you are, what you're doing with some of the universities in Cloud. Maybe you talk, you came from the vendor side. Just real quick, your background, you worked at a company that John and I know quite well. Maybe just give a quick background? >> Sure. I left academia, I don't know how many years ago. Ended up going to IBM research, and was there for about 10 years. And then I joined this little start-up called VMWare. And started up and then worked as sort of one of the lead architects for vCloud Director and the whole vCloud Initiative. >> Alright, great. Let's speak today, you also have, you're the lead in Massachusetts Open Cloud. We actually had a couple of guests on from Red Hat that talked a little bit about it. But tell us about the project, the scope of it, how many people involved, how many users you reach with this. >> Sure. The future is in the Cloud. I mean, you look at sort of the fact that users can use what they need, when they need it. Producers can get massive economies of scale. You know, the future of computing is in the cloud. And when I was on the industry side, what really concerned me, what was going on, is that these clouds were really closed. You couldn't see what was going on inside them. Innovation was sort of gated by this single provider, that operated and controlled each of these clouds. So, the question that I was struggling with back then, is how can we create a cloud that's open? That multiple technology companies can participate. And certainly when I came back to academia, a cloud where I could do innovation in. Where not just me, but many many different researchers. You look at how much research has fundamentally impacted our field. It's dramatic. Even in just sort of the very area we're talking about. From what Mendall and team did with VMWare, and then Zen coming out of Cambridge. I mean, Ceph coming out of, just like technology after technologies come out of academia. But now clouds are these closed boxes you can't get into. So we had this incredible opportunity. There'd be this data center, the Massachusetts Green High Performance Computing Data Center, MGHPCC. 15 megawatts. That's more than half the size of one of Google's 16 data centers. That had been built, right next to Hydro Dam, one third the power costs of what it is in Boston. By five big institutions: MIT, Harvard, BU, Northeastern, UMass. And we thought, wow, couldn't we create a cloud there? Couldn't we create a cloud with some 157,000 potential students as well as the broader ecosystem? So we started discussing that idea. All the universities kind of signed up behind it. The model of the cloud is not to create another single provider cloud. It's not going to be my cloud. The idea is to have many vendors participate. Stand up different services, and create an open cloud, where there's not just multiple tenants but there's also multiple landlords with the cloud. >> Great. Could you talk to us a little about how do some of those pieces get chosen? How does OpenStack fit into it? And if you can talk about some of the underlining pieces it'd be good to understand how you sort that out too. >> Sure. So in doing that we, it's actually been sort of this cool, you know you have to kind of build different levels simultaneously. When we started the project, you know our first thing was, oh you know we'll be able to just stand up a cloud. It wasn't that easy. OpenStack is actually a complicated learning curve to get up. Now it's matured tremendously. We've been in production for about ten months, with no significant failures. I'm almost thinking that we need to kind of bring it down for a couple hours. Just so the people start realizing this is not intended to be a place where you run it like you would a production data center facility. That we don't guarantee it as so, 'cause people are starting to assume we do. (laughing) But, we started off and we sort of solved OpenStack, got it up and running. Took us a while to get it to the production layer. Started hosting courses, and users, and stuff like that. And some tastes that with sort of two other tracks. One is I'm developing some of the base technologies to enable a cloud to be multi-vendor. So mix-and-match fetterations serve our core of that. Which is this new capability that we've, after like five iterations on the right way to do this to allow multiple different clouds with their own keystone, mix different administrators say from MIT or Harvard, or from companies that might want to participate and set up a service. So, to have a capability of fettering between those things. Allowing you, for example, to use storage from one and compute from another. We started off with OpenStack because OpenStack already had the right architecture. It was designed as a series of different services. Each one which could be scaled independently. Each one that had it's own well defined API. And it seemed natural, jeez, we should be able to compose them together. Have, you know, one stand up, Nova compute. Another one stand up, Swift storage. Another one stand up, Cinder Storage. Turned out not to be that easy. There was assumptions that all these services were stood up by the same administrative entity. After three iterations of trying to figure out with the community how to make it, we finally have a capability of doing that now. That we're putting into production in the MOC itself. >> You talked about the different projects inside OpenStack, that's been one of the discussions here this week at the Summit. Different projects, the core, which are important and also the whole ecosystem of other cloud native and open source projects that have grown-up around OpenStack over the last six or seven years. Any commentary on how, which kind of projects you're finding are the most useful and the UC as kind of the core of OpenStack going on? And also, which projects from other ecosystems do you think are natural fits into working on an OpenStack base platform? >> Sure. So in our environment, we serve all the core services you think of, obviously Nova and Cinder and Swift. We're using Ceph in most of our environments. Sahara, Heat. We've actually expanded beyond in a couple of different dimensions. I guess that, one thing is we've been using extensively Ceph, that's been very valuable for us. And we've also been modifying it actually, substantially. It's actually kind of exciting cause we have graduate students that are making changes that are now going upstream in the Ceph community as a result of their experiences in doing things within our environment. But, there's other projects that sort of tied in sort of two different levels. One is we're working very closely with Red Hat, today around OpenShift. And we're making the first deployment of that available in the very near future. And the other thing is very important for our environment, we have I think three different talks related to this to have data sets in the cloud. To have data sets shared between communities of people. Data sets that are discoverable. Data sets where you can actually, that are citable. So we've been working very closely with Harvard and the OpenSource dataverse community and we've together created the cloud dataverse. Which is now actually in the MOC. So researchers from all these institutions can actually publish their data sets. As well as researchers from around the world. So there's over 15,000 data sets today in the Harvard dataverse for example. >> Curious if you can give us any commentary on how open source fits into education these days? Talk about the pipeline and the next generation of workers. Do your students get, you talked about upstream contributions, how do they get involved? How early are they getting involved? >> Well, actually, that's sort of a bit of a passion of mine. So multiple different levels, I guess. One of them I think is this is a great way for a student to sort of get exposed to a broad community of people to interact with. I think it's, rather than going in to serve one company, and getting locked down doing one thing, I think it's just enormously valuable. There's sort of two different dimensions I guess, educationally and from a research prospective. And both of them were very tied to open source. So from an education perspective, we have a course, for example, one of my frustrations of having come back from industry was students had done a lot of great, learned how to program, often as individuals they really didn't learn how to do agile, they didn't learn how to work with teams of people, so we have a large course that's served by multiple institutions today that's sort of tied to the MOC where we actually have industry mentors, we teach them agile methods, we teach them a lot of the sort of fundamentals of cloud, but we also have industry mentors come in and mentor teams of five students to create a product. There's actually three different lightning talks by different students that have taken this course, that are here in the OpenStack forum today. So it's kind of exciting to see. We've had several hundred students that have learned that and at least, in my experience, learning how to deal with open source communities, mentorship is a great way of doing that. First year we started teaching this course we had sort of struggled finding mentors, now we're about twice as many mentors applying to mentor teams as we can accommodate in it. So that's been kind of exciting. >> That's great. That's super important and learning right and not just learning how to program but how to operate as a engineer and a team. >> So in the MOC itself, a lot of it's stood up by students. We have like 20 to 30 students. We have a very small core development in our operations team and most of it is actually students doing all the real work. It's been amazing how much they can accomplish in that environment. >> You mentioned OpenShift. So another conversation that's been somewhat confusing in the broader industry is the talking about containers versus VMs and virtualization and OpenStack. Here this week, I thought it's been a fairly clear message that there's some you can be containerizing the stack itself and then there's also a role for containers on top. Obviously been involved in virtualization for a long time, how are you seeing the evolution of both containerization as a technology, but also container based platforms versus kind of the infrastructure and provisioning of the cloud part? >> I mean, there's three levels that all have its role. There's actually people that want to control all the way down to the operating system and want to do, customize things who want to use SRLV and want to use accelerators that haven't. So there's people that actually want hardware as a service and we provide a capability for doing that that's got its limitations today. There's people that want to use virtual machines and there's people that actually want to use containers. And the ability to orchestrate setting up a complex multitiered environment on that and doing fine-grain sharing in a containerized environment is huge. I think that actually all three are going to have a continued role going forward. And certainly containerized approach is an awesome way to deploy a cloud environment and scale the cloud environment even the IAS environment. So we're certainly doing that. >> Love the idea of the collaboration you have both intermittently with all the universities. Are you getting reached out by outside of Massachusetts? How do you interact with the broader community and share ideas back and forth? >> So of course there is multiple streams of that one of them is our industry partners are very broad. Second, we've participated in sort of the OpenStack Summits and all those kind of things. The other thing is that the model that we are doing, I think has a lot of excitement and interest from very many different segments. I don't think people want to see the public cloud be dominated, or could see always be dominated by a very small number of vendors. So the idea of actually creating an open mall of cloud. Lots of other academic institutions have talked with us both about setting up sister organizations, fettering between clouds and replicating the model. We're still at an early stage. This model still has to be proven out. We're excited that we have users that are using us now to get their work done. Rather than just courses and things like that. But it's still at a very early stage So I think as we scale up we'll start looking at replicating that model more broadly. >> Is there any public information about what you're doing? And I'm curious, will this tie into like mooc delivery, things like that? >> Oh, absolutely yeah. It's all on our webpage info.massopencloud.org. So everything is done in the open, I guess. So all the projects, they're all, everything is on the websites and you can discover all about it. And we welcome participation from a broad community. And are excited about that. >> Orran Krieger. Really appreciate you sharing with our community everything there. Congratulations. Local, we'd love to stop by some time to check out even more. John and I will be back with lots more coverage here from openStack Summit 2017, Boston, Massachusetts. You're watching theCUBE. (upbeat music)